Technologies for Characterizing Molecular and Cellular 

Systems Relevant to Bioenergy and Environment Workshop

September 21–23, 2016

Convened by

U.S. Department of Energy

Office of Science

Office of Biological and Environmental Research

Co-Chairs

Organizers

Paul Adams, Ph.D.

Lawrence Berkeley National Laboratory 

Elizabeth Wright, Ph.D. 

Emory University

Biological Systems Science Division

Todd Anderson, Ph.D.

Amy Swain, Ph.D.

Amy.Swain@science.doe.gov

301.903.1828

This report is available at science.energy.gov/ber/community-resources/ and genomicscience.energy.gov.

Mission

The Office of Biological and Environmental Research (BER) advances world-class fundamental research programs and scientific user 

facilities to support the Department of Energy’s energy, environment, and basic research missions. Addressing diverse and critical global 

challenges, the BER program seeks to understand how genomic information is translated to functional capabilities, enabling more confident 

redesign of microbes and plants for sustainable biofuel production, improved carbon storage, or contaminant bioremediation. BER research 

advances understanding of the roles of Earth’s biogeochemical systems (the atmosphere, land, oceans, sea ice, and subsurface) in 

determining climate so that it can be predicted decades or centuries into the future, information needed to plan for future energy and resource 

needs. Solutions to these challenges are driven by a foundation of scientific knowledge and inquiry in atmospheric chemistry and physics, 

ecology, biology, and biogeochemisty.

Suggested citation for this report: U.S. DOE. 2017. Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy 

and Environment, DOE/SC-0189, U.S. Department of Energy Office of Science. science.energy.gov/ber/community-resources/.
Technologies for Characterizing 

Molecular and Cellular Systems Relevant 

to Bioenergy and Environment

Workshop Report

September 2017

Office of Biological and Environmental Research

DOE/SC-0189
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

ii U.S. Department of Energy • Office of Biological and Environmental Research September 2017
Chapter 1 – Introduction

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research iii

Contents

Executive Summary ..................................................................................................................................v

Research Themes....................................................................................................................................................v

Overarching Challenges and Opportunities ........................................................................................................... vii

1. Introduction............................................................................................................................................1

1.1 Historical Perspective of BSSD Genomics Characterization .............................................................................1

1.2 BSSD Structural Biology and Bioimaging Science: Atoms to Mesoscale ..........................................................2

2. Cell Wall Composition and Degradation .............................................................................................5

2.1 Current Science and Technologies ....................................................................................................................5

2.2 Major Challenges in Monitoring Plant Cell Walls ...............................................................................................6

2.3 Advancing Biofuel and Bioproduct Design and Production..............................................................................14

3. Rhizosphere Community Interactions...............................................................................................15

3.1 Current Science and Technologies ..................................................................................................................16

3.2 Major Challenges in Detecting Rhizosphere Interactions ................................................................................17

3.3 Major Needs in State-of-the-Art Technologies for Understanding Rhizospheres.............................................19

3.4 Optimizing Plant Health, Soil Fertility, and Carbon Storage.............................................................................27

4. BiogeochemicalCycling......................................................................................................................29

4.1 Current Science and Technologies ..................................................................................................................29

4.2 Major Challenges in Learning How Microbes Control Biogeochemistry Cycling and Mobility .........................30

4.3 Improving Model Predictions of Biological and Environmental Systems..........................................................35

5. Metabolic Pathways in Plants, Microbes, and Fungi .......................................................................37

5.1 Current Science and Technologies ..................................................................................................................38

5.2 Major Challenges in Detecting Metabolic Pathways ........................................................................................40

5.3 Predictively Understanding the Metabolome Across Scales, from Organisms to Ecosystems........................43

6. Biosystems Design .............................................................................................................................45

6.1 Current Science and Technologies ..................................................................................................................46

6.2 Major Challenges in Design of Engineered Biosystems ..................................................................................51

6.3 Leveraging Synthetic Biology for Future Energy and Resource Needs...........................................................56

7. Cellular Ultrastructureand Physiology..............................................................................................59

7.1 Science and Technologies ...............................................................................................................................59

7.2 Understanding Genotype-Phenotype Interactions to Improve Biofuel Feedstocks..........................................69
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

iv U.S. Department of Energy • Office of Biological and Environmental Research September 2017

8. Integration and Analysis....................................................................................................................71

8.1 Current Science and Technologies ..................................................................................................................71

8.2 Major Challenges in Data and Computation ....................................................................................................74

8.3 Advancing Computational Platforms for Large-Scale Data Processing and Analysis......................................78

9. Summary and Conclusions ................................................................................................................81

Appendices ..............................................................................................................................................87

Appendix A: Workshop Participants .....................................................................................................................87

Appendix B: Workshop Agenda............................................................................................................................88

Appendix C: Figure Credits ..................................................................................................................................91

Appendix D: Acronyms and Abbreviations ...........................................................................................................93

Appendix E: References.......................................................................................................................................95
Executive Summary

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research v

The Biological Systems Science Division 

(BSSD) within the U.S. Department of 

Energy’s (DOE) Office of Biological and 

Environmental Research (BER) funds basic research 

on plants and microbes relevant to several DOE 

bioenergy and environmental mission areas. BSSD’s 

long history of developing and supporting genomic 

characterization of biological systems has led, in 

part, to the high-throughput DNA sequencing technology available to researchers worldwide. In recent 

years, genome sequencing has vastly outpaced the 

ability to interpret genome function. Fully maximizing this wealth of data will require new technology 

advancements, along with improvements and an 

increase in the throughput of existing methods for 

characterizing molecular- to cellular-level processes 

important for inferring biological function.

BSSD research seeks to understand the fundamental 

genome-encoded properties of plants and microbes 

that can be harnessed or redesigned for beneficial 

purposes. Current emphases are leading to the discovery, development, and understanding of numerous plant and microbial species with traits suitable 

for the production of fuels and chemical products 

from renewable biomass that could be grown synergistically with food or animal feed crops while not 

competing with other societal needs. Additionally, 

BSSD further supports research leading to an understanding of the complex and essential interactions 

among plants, microbial communities, and the environment to find new ways to sustainably produce 

biomass for a range of bioenergy and bioproduct 

applications. This research also is relevant for incorporation into larger-scale environmental models 

such as those developed through the research supported by BER’s Earth and Environmental Systems 

Sciences programs.

To engage the relevant scientific communities in 

discussions of these research areas, BER convened 

the Technologies for Characterizing Molecular 

Executive Summary

and Cellular Systems Relevant to Bioenergy and 

Environment workshop on September 21–23, 2016 

(see Appendix A, p. 87, and Appendix B, p. 88). 

Seeking to enable more comprehensive systems 

biology–based approaches, which typically require 

measurements of many samples, workshop participants highlighted the need for the development 

of highly sensitive methods to provide accurate 

measurements from small sample volumes and that 

are operable in high-throughput or highly parallel 

modes. Achieving these goals is critical to enabling 

predictive engineering of biological systems, as is 

further development of manipulation technologies. 

Biosystems design has the potential to revolutionize 

the way biology is exploited to produce economically valuable molecules; however, this will be 

possible only if high-throughput measurement 

technologies are combined with tools for precise 

genetic manipulation, and computational algorithms 

are devised for accurate prediction of phenotype 

resulting from genome manipulation. Participants at 

the workshop, organized by BSSD, concluded that 

multimodal methods will be required for many of 

the research needs discussed. As structural biology 

and imaging methods are converging, multiscale, 

multidisciplinary approaches to plant and microbial 

cell biology are increasingly emerging.

Research Themes

These fundamental research efforts require new and 

innovative methods and technologies to elucidate 

the foundational principles that drive biological 

systems of interest to DOE’s energy and environmental missions. Characterizing biological systems 

involves analytical approaches that illuminate cellular 

components and their form, structure, size, function, 

spatial location, dynamics, and interactions with 

the environment. Workshop discussions identified 

new technologies and combinations of existing 

capabilities to address the challenges associated with 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

vi U.S. Department of Energy • Office of Biological and Environmental Research September 2017

characterizing molecular and cellular systems relevant 

to bioenergy and environmental research. Participants included technology developers and biology 

researchers with expertise in cellular ultrastructure 

and physiology, bioenergy and bioproducts, and 

environmental microbiology. Attendees developed 

a series of research and technology development 

needs across six thematic areas spanning the range of 

BSSD-supported research. The challenges of studying 

these systems are many and broad in scope, covering 

time scales from femtoseconds to weeks and length 

scales from Angstroms to centimeters. This report 

addresses this very broad measurement range—from 

cells and their metabolism and mineralogy (Angstroms to micrometers), to rhizosphere ecosystem 

processes and community biochemical activity (millimeters to a meter). In this context, the range from 

micrometers to a meter is referred to as “mesoscale.” 

Despite the breadth of the challenges, participants 

identified key needed technologies and improvements 

in current techniques that could advance BER science. 

These six major research themes are discussed below.

Cell Wall Composition and Degradation. The 

benefits from gaining a molecular-level understanding of plant cell wall composition and degradation 

were discussed in the context of using plants in 

the production of biofuels and bioproducts. As a 

renewable resource for biofuels and biomaterials, 

lignocellulosic biomass can partially replace the use 

of diminishing petroleum-based fuels and products and help meet increasing consumer demand 

for green chemicals. However, the varying structure and chemical composition of the cell walls 

of different plants and tissue types may hinder 

industrial-scale processes for converting biomass to 

bioproducts. Needed to address this challenge are 

better atomic- and molecular-level understandings 

of the structure and dynamics of naturally occurring cell wall processes, as well as the processes 

involved in the production of biofuels and other 

chemicals. Also needed are new characterization 

techniques with nanometer-scale resolution that 

require minimal sample preparation and keep the 

sample in close-to-natural conditions.

Several technologies and techniques identified will 

aid the understanding of plant cell wall properties 

at the anatomical, cellular, molecular, and genetic 

levels. Other new approaches suggested will provide as-yet-undiscovered molecular details about 

structural and temporal rearrangement of cell wall 

components during biomass deconstruction prior to 

conversion to biofuels and bioproducts.

Rhizosphere Community Interactions. A better 

understanding of ecosystems is yielding deeper 

insights into plant-microbe-mineral interactions 

important for bioenergy production. Knowing the 

complex interdependencies of these three systems is 

critical to understanding and developing sustainable 

biofuel production practices. Root system architecture has a dramatic bearing on plant viability and 

crop productivity in given soil conditions. Namely, 

the rhizosphere, the area immediately surrounding 

plant roots, is a nexus of biological activity and the 

foundational ecosystem for any plant-microbe system. Thus, studies are needed of all essential communal elements necessary for plant growth and yield 

across a range of geographic regions. Understanding 

these ecosystems can enable the design of optimally 

mutualistic plant-microbe interactions to improve 

biofuel crop sustainability.

For these studies, the development of penetrating 

imaging tools is needed to study entire, complex soil 

environments and root system architectures.

Biogeochemical Cycling. Environmental system 

function is intimately tied to the biogeochemical 

cycling of the major elements, particularly their 

reduction-oxidation (redox) transformations. 

Spatial and temporal imaging and measurements 

of biogeochemical systems are necessary for a 

mechanistic understanding of how different biogeochemical systems function. There also is a need for 

development of, and improvements to, technologies 

and approaches that will enable researchers (1) to 

understand and predict the dynamic interplay 
Executive Summary

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research vii

between environmental biotic and abiotic factors 

that often are opaque to imaging tools, from the 

molecular to the mesoscale, and (2) to use this new 

understanding to predict larger-scale phenomena.

A combined and holistic use of a variety of dynamic 

imaging and characterization probes, coupled with 

multiomic and modeling approaches, is necessary to 

span spatial and temporal scales in biogeochemical 

systems to better understand their role in key environmental processes.

Metabolic Pathways in Plants, Microbes, and 

Fungi. Plants and microbes exchange metabolites in 

a community economy that ultimately determines 

the rates at which nutrients and water are extracted 

from soil and soil carbon is cycled (i.e., the biogeochemistry). A deeper understanding of the mechanisms by which organisms interact with each other 

in the environment, and the metabolic pathways and 

specific molecules involved in these interactions, will 

enable the modification of these pathways to improve 

nutrient-use efficiency and soil-carbon performance.

New tools are required for predicting and measuring 

metabolites from organisms key to BER bioenergy 

and environmental missions. Combined with new 

higher-resolution approaches, these technologies 

will need capabilities for determining spatiotemporal localization and mechanisms responsible for 

metabolite synthesis, transport, degradation, and 

perception. The ultimate goal is a “balanced record” 

of metabolite economy among plant-microbe-fungi 

interactions and the environment that fully accounts 

for all carbon and nutrient cycling in the system.

Biosystems Design. Synthetic biology provides 

a valuable approach to probe, study, and engineer 

new functions into biological systems through the 

introduction or modification of metabolic pathways, 

specifically generating biologically derived chemicals, fuels, and materials to ensure environmental 

sustainability. Challenges include (1) applying 

synthetic biology to intractable eukaryotic and 

multicellular organisms, (2) engineering communities of microorganisms and microbe-plant interfaces, 

(3) exploring genotype-phenotype landscapes 

resulting from genome engineering, (4) isolating 

engineered organisms with desired functions, and 

(5) safeguarding engineered biosystems.

Efficient tools for the precise manipulation of 

genomes in diverse target organisms will need to 

be combined with improved computational modeling methods to support predictive biology. These 

coupled approaches will require assistance from new 

methods for rapidly assaying function and fitness. 

They also must be applicable to technologies for 

controlling the containment of engineered systems 

and the products of engineered pathways.

Cellular Ultrastructure and Physiology. BER 

research examines a range of plant and microbial 

cell structures and organization, from the atomic 

level to complex molecular machines, cellular 

compartments, scaffolds, and whole cells. Workshop 

participants identified several measurement challenges, including how to detect and visualize cellular 

dynamic processes such as metabolic cycles, signaling and trafficking in plants, and interactions among 

microbial and fungal communities. They described 

needs for improved (1) structural imaging at the 

atomic and molecular level, (2) methods for illuminating whole organisms to understand the internal 

organization of cells, and (3) imaging chemical 

events that underlie biology. These needs include 

methods to determine the locations and dynamic 

parameters of enzyme reactions within cells, as well 

as the flow of chemicals and macromolecules within 

and between cells. The structural and dynamical 

insights from such studies will inform and enable 

more accurate modeling of biogeochemical cycling 

and metabolic pathways important in rhizospheric 

communities and biofuel or bioproduct processes.

Overarching Challenges 

and Opportunities

Several challenges common to all the research 

themes emerged throughout workshop discussions. Translating information from genomic 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

viii U.S. Department of Energy • Office of Biological and Environmental Research September 2017

studies to the molecular and cellular realm for 

characterization will require increased throughput 

for existing technologies and the development 

of new high-throughput approaches. Achieving 

these goals will necessarily involve more automation and computational algorithms to manage 

the high data volumes that will be produced. 

Improved machine-learning approaches and large 

data-handling capacity will be essential. Integration 

of disparate data types from multiple and heterogeneous sources remains a challenge, so continued 

development of integrative and interpretive computational approaches is needed. Similar needs also 

were discussed at a workshop hosted by DOE’s 

Office of Advanced Scientific Computing Research 

(ASCR), the DOE Exascale Requirements Review, 

held March 28–31, 2016, in Rockville, Md., which 

generated the meeting report, ASCR Exascale 

Requirements Review (science.energy.gov/ascr/

community-resources/program-documents/).

The tools and methods described in this BER report 

are critical for advancing the deep understanding of 

complex, multicomponent systems that are central to bioenergy and the environment. While new 

technologies are needed for advancing leading-edge 

biological insights, they are of limited value if they 

are not readily accessible by the scientists who need 

them to conduct their research. As new instruments, platforms, and approaches are created, it 

is important that they be developed in ways that 

ultimately enable biology researchers to use them, 

either by adopting them in their own laboratories or 

by having access to the tools, appropriate expertise, 

and support at national user facilities. Elements will 

include robust hardware, physiologically relevant 

sample preparation and measurement conditions, 

automation, sophisticated analytical algorithms, and 

user-friendly interfaces. For facility-based technologies, long-term and productive community access 

requires recognition of the need for ongoing operational support.

Described herein are some of the workshop’s identified challenges to studying the biological systems 

of interest to BSSD, which has a history of developing and supporting highly sophisticated research 

tools and techniques and ensuring that researchers 

can access them to advance science in support of 

the division’s goals. Workshop discussions reflected 

in this document will help guide the next generation of imaging and analytical instrumentation 

needed to gain a predictive understanding of 

biological systems supporting DOE’s energy and 

environmental missions.

BER appreciates the tireless efforts of the workshop co-chairs and the contributions of all the workshop 

participants. BER also extends special thanks to Kris Christen, Holly Haun, Brett Hopwood, Sheryl 

Martin, Stacey McCray, Marissa Mills, Judy Wyrick, and Betty Mansfield of Oak Ridge National 

Laboratory’s Biological and Environmental Research Information System for editing and preparing this 

report for publication.
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 1

Chapter 1 – Introduction

The Biological Systems Science Division (BSSD) of the U.S. Department 

of Energy’s (DOE) Office of Biological 

and Environmental Research (BER) supports 

systems biology research that targets the 

foundational principles driving biological 

systems of microbes, plants, and multispecies 

communities relevant to BSSD’s bioenergy 

and environmental missions (see Fig. 1.1, 

this page). Managed within DOE’s Office 

of Science, this research includes pursuit of 

a systems-level understanding of the spatiotemporal expression of biomolecules and 

structures within microbial and plant cells.

1.1 Historical Perspective of BSSD 

Genomics Characterization

BSSD’s long history of developing and supporting the 

use of genomic characterization of biological systems has 

led, in part, to the high-throughput DNA sequencing technology available to researchers worldwide. In recent years, 

genome sequencing has vastly outpaced the ability to interpret genome function. There is a great opportunity for the 

further development of methods for characterizing biological 

processes at the molecular and cellular level to enable the 

inference of function. BSSD research seeks to understand 

the fundamental genome-encoded properties of plants and 

microbes that can be harnessed or redesigned for beneficial 

purposes. Current emphases are leading to the discovery, 

development, and understanding of numerous plant and 

microbial species with traits suitable for the production of 

fuels and chemical products from renewable biomass that 

could be grown synergistically with food or animal feed crops 

while not competing with other societal needs. Additionally, 

Chapter 1

Fig. 1.1. Research Targets Supported by 

the Office of Biological and Environmental 

Research (BER) Biological Systems Science 

Division (BSSD). BER is managed within the 

U.S. Department of Energy’s Office of Science. 

Clockwise from top: (1) Biogeochemical 

cycling; (2) cell wall composition and degradation; (3) cellular ultrastructure and physiology; 

(4) biosystems design; (5) metabolic pathways 

in plants, microbes, and fungi; (6) rhizosphere 

community; (center) mesoscale molecular 

model. BSSD research is linked via data integration and analysis. [See Appendix C, p. 91, to 

view image attributions and permissions.]

Introduction
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

2 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

BSSD supports research leading to an understanding 

of the complex and essential interactions among 

plants, microbial communities, and the environment. Also aiming to create a more mechanistic 

understanding of the dynamic nature of cellular 

metabolism, much of the BSSD research portfolio 

spans the following three broad areas.

Bioenergy and Bioproduct Production. Central to DOE’s mission is support of fundamental 

research to provide the knowledge underpinning 

development of renewable energy sources. Plant 

biomass is a long-recognized source of renewable 

sugars and other compounds for the biological 

production of fuels and other useful chemicals. Successful development of these biological approaches 

ultimately will require a detailed understanding of 

how to optimize plants and microbes for biomass 

production and sustainable growth, how biomass 

is constructed and how to deconstruct it, how to 

optimize enzymatic pathways that produce desired 

molecules and biopolymers (bioproducts), and how 

these pathways are regulated in the context of cell 

metabolism.

Environmental Microbiology. Microbes and their 

communities significantly affect biogeochemical 

transformations in a wide range of diverse ecosystems. BSSD-funded research efforts focus on how 

microbial consortia communicate; evolve; share 

resources; interact with other organisms in the rhizosphere and aquatic environments; are affected by 

changes in the environment; and, ultimately, play a 

role in defining the Earth’s landscape. The improvement and use of novel instrumentation and methodologies will further inform BER-sponsored research 

directions associated with microbial ecology and 

environmental and climatic changes.

Cellular Ultrastructure and Physiology. BSSD 

supports research that focuses on examining the 

structure and function of whole microbial organisms 

and plant cells to assess how cellular and subcellular 

structures of individual organisms correlate with 

specific biochemical, molecular, genetic, and behavioral pathways. Successful investigations may lead 

to the development of synthetic systems that can 

replicate functions of natural systems or carry out 

novel functions not observed in nature.

1.2 BSSD Structural Biology 

and Bioimaging Science: 

Atoms to Mesoscale

Analysis of biological systems generally extends 

across many orders of magnitude in length and time 

(see Fig. 1.2, p. 3). Environmental phenomena at 

the meter-length scale are intrinsically linked with 

the activities of biological systems at the cellular 

level, which in turn are the result of the activities of 

individual enzymes at the atomic level. This report 

addresses the very broad measurement ranges 

required—from cells and their metabolism and mineralogy (Angstroms to micrometers), to rhizosphere 

ecosystem processes and community biochemical 

activity (millimeters to a meter). In this context, the 

range from micrometers to a meter is referred to as 

“mesoscale.” Combined experiments that traverse 

all these length scales are currently rare, highlighting 

the important need for capabilities to measure these 

systems at very different length scales and resolutions and then rigorously correlate the results. The 

time domain in biology is equally as important as 

length. Emergent environmental phenomena may 

evolve over months or years but, ultimately, they are 

influenced by cellular activities on the millisecond 

time scale. In turn, cellular activities are a result of 

enzymatic activities whose key steps may be atomic 

rearrangements at the subpicosecond time scale. 

The ability to predict the time evolution of complex 

biological systems demonstrates a profound level of 

understanding and opens up the possibility of their 

control and manipulation for defined outcomes. 

Over the last century, multiple techniques have been 

developed to measure biological systems across these 

length and time scales.

Participants in BER’s Technologies for Characterizing Molecular and Cellular Systems Relevant 

to Bioenergy and Environment workshop in September 2016 considered gaps in technologies for 
Chapter 1 – Introduction

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 3

Fig.1.2. Overview of Needed Length and Time Scales. Biological and Environmental Research program biological interests 

include complex processes that span a size range from Angstroms to a meter and a dynamic range from femtoseconds to 

a week. Representative processes and their elements are illustrated. [See Appendix C, p. 91, to view image attributions and 

permissions.]

Key: Å, Angstrom; cm, centimeter; fs, femtosecond; m, meter; mm, millimeter; min, minute; μm, micrometer; μs, microsecond; ms, millisecond; nm, nanometer; ns, nanosecond; ps, picosecond; s, second; sub-ps, subpicosecond.

characterizing biological systems. They cited the 

importance of knowing what technologies exist, 

but also, on a more practical level, what is currently 

available to BSSD researchers. Furthermore, participants recognized that BER supports a number 

of resources that should be kept at the leading edge 

of science. Development or implementation of new 

technologies, where appropriate and needed, may 

strategically leverage or add to existing resources. 

Following are examples of the BER-supported 

advanced technology resources available to and used 

by the BSSD research community.

• The DOE Joint Genome Institute ( JGI; jgi.doe.

gov) provides advanced sequencing and synthesis of plant and microbial genomes.

• The DOE Systems Biology Knowledgebase 

(KBase; kbase.us) is an openly available informatics resource for collaborative, computational modeling of plant, microbial, and community systems.

• BER-supported structural biology beamline 

resources (berstructuralbioportal.org) are 

available at synchrotron and neutron facilities 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

4 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

supported by the DOE Office of Basic Energy 

Sciences (BES). These beamlines elucidate structures ranging from the atomic to the tissue scale 

and provide dynamic information from femtosecond to seconds.

• The BER Environmental Molecular Sciences 

Laboratory (EMSL; emsl.pnl.gov/emslweb/)

offers a suite of over 50 advanced and varied 

capabilities, many of which are immensely useful 

for BSSD researchers, including computing 

resources.

• BER researchers also have access to advanced 

computing resources (science.energy.gov/ascr/

facilities/); in particular, the National Energy 

Research Scientific Computing Center (NERSC; 

nersc.gov).

BSSD’s Bioimaging Technology program (science.

energy.gov/ber/bioimaging-technology/) targets creation of novel multifunctional technologies to image, 

measure, and model key metabolic processes within 

and among microbial cells and multicellular plant 

tissues. This ongoing program supports the development of stand-alone, in situ, nondestructive imaging 

platforms. As they are made robust, these instrument 

platforms are made available to BSSD researchers.

The following six chapters summarize the driving 

research needs in areas key to BSSD, the current 

technologies available, and the needed new and 

improved technologies and their potential impact. 

The penultimate chapter discusses the need for new 

computational and modeling approaches to enable 

these areas of BSSD-supported biological research.
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 5

Chapter 2 – Cell Wall Composition and Degradation

Plant cell walls consist primarily of cellulose, hemicelluloses, and lignin that, in addition to starch, are 

the major carbon-containing products of photosynthesis. This lignocellulosic fraction of plant biomass 

has great potential as a renewable feedstock for 

biofuels and biomaterials. Achieving this potential 

can offset the diminishing availability of fossil 

fuels and meet increasing consumer demand for 

green chemicals. Emerging biorefinery methods use thermochemical pretreatment and 

enzymatic hydrolysis to deconstruct plant cell 

walls to monomeric sugars that microbes then 

ferment into biofuels. Advancing the viability 

of biorefineries requires deeper understanding 

of the biosynthesis of plant cell walls and their 

physiochemical properties as well as the rate and 

yield of chemical and enzyme processes used for 

biomass deconstruction.

Understanding the complex organization of plant tissues and 

the cell wall polymers that comprise them requires the use of 

many techniques to characterize differences in cellular ultrastructure and chemical composition across spatial scales of 

millimeters to nanometers. Scientists need improved spatial 

resolution correlated with chemical bonding information to 

advance knowledge of how chemical treatments and biological catalysts work synergistically to convert plant feedstocks 

into useful sugars that are the basis for biofuels.

2.1 Current Science and Technologies

Cellulose. Of the three major structural polymers constituting the plant cell wall, the most abundant is cellulose, 

Cell Wall Composition 

and Degradation

Chapter 2
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

6 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

composed of linear β-(1,4)-glucan chains. Together, 

these chains form a cellulose elementary fibril 

(CEF), which contains glucan chains packed in 

parallel and associated through extensive hydrogen 

bond networks. The exact number of CEF glucan 

chains and their geometric arrangement are still 

subjects of debate (Ding and Himmel 2006; Evert 

2006; Ding et al. 2012.) Studies also show that CEFs 

aggregate into large bundles called macrofibrils 

and that the number of CEFs in a macrofibril varies 

among cell types and cell wall layers (Ding et al. 

2012). Tightly packed and highly hydrogen bonded, 

cellulose polymers are not easily accessible to hydrolytic enzymes, presenting a significant challenge for 

biomass deconstruction.

Hemicelluloses. This class of branched or 

unbranched polysaccharides comprises a β-(1,4)- 

linked sugar backbone with short side chains consisting of a wide variety of sugar residues linked with 

different glycosidic bonds. Hemicelluloses sometimes also include sugar acids and noncarbohydrate 

subunits and contain both C5 (e.g., xylose) and C6 

(e.g., glucose) sugars. For example, the hemicellulose 

xyloglucan has the same β-(1,4)-glucan backbone as 

cellulose along with side chains composed of xylose 

and other sugars. The β-(1,4)-glucan backbone may 

facilitate interactions with cellulose and serve as a 

bridge between CEFs. Hemicellulose branching and 

side groups also form covalent bonds with other cell 

wall polymers, such as pectin and lignins in lignified 

walls. These covalent bonds, and the interactions 

with cellulose, make hemicelluloses barriers to 

enzymatic access to cellulose, although they are much 

more amenable to enzymatic breakdown because of 

their noncrystalline state.

Lignin. The second most abundant polymer in plant 

biomass, lignin is a covalently linked heterogeneous 

composition of aromatic phenols. Despite its abundance, the structure of native lignin in a plant cell 

wall is poorly understood. In addition to providing 

mechanical support to plants, lignin is believed to be 

the major factor in biomass recalcitrance—the resistance of plant cell walls to microbial and enzymatic 

deconstruction—because it impedes enzymatic 

accessibility to the polysaccharide substrates (Zeng 

et al. 2014).

2.2 Major Challenges in 

Monitoring Plant Cell Walls

The changes that occur in lignocellulosic biomass 

structure and associations during and after pretreatments are not well understood, but this knowledge is 

essential for efficient deconstruction. Pretreatments 

that use different chemical and thermal conditions 

appear to change specific cell wall components in 

different ways—all increasing enzymatic digestibility, but the mechanisms are poorly understood. 

Identified changes include transitions in cellulose 

crystallinity and the rearrangement or removal of 

matrix copolymers with subsequent improvements 

in hydrolysis. Most current information pertaining 

to cellulose involves unpretreated samples, so characterizations of the transitions that occur following 

removal of disruptive agents, washing, drying, 

and rehydration are incomplete. Improved understanding requires technologies for atomic- and 

molecular-level investigations of the structure and 

dynamics of both naturally occurring and pretreated 

fibrous cellulose. Also poorly defined are structural 

transformations in lignin and interactions among 

lignin, hemicellulose, and cellulose during and after 

different pretreatments.

Understanding the Genetic 

and Molecular Basis of Plant 

Cell Wall Properties

Over the past 2 decades, field studies of plant cell wall 

biosynthesis have yielded valuable insights into the 

molecular mechanisms of synthesis and deposition 

of cellulose, lignin, hemicellulose, and pectin (Kalluri 

et al. 2014). However, critical questions in cell wall 

biosynthesis and biomass formation remain:

• What does the transition zone between primary 

and secondary walls look like?

• Which cellular processes lead to unique cell wall 

properties of a given type of biomass?
Chapter 2 – Cell Wall Composition and Degradation

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 7

• What determines cellulose variations (commonly 

found in all plant cell wall types) and the accompanying cellulose composition?

• What controls the arrangement and turnover of 

protein complexes that synthesize wall polymers 

(i.e., cellulose synthase complexes) and the directionality of cellulose deposition?

• Do the spatial distribution patterns of hemicellulose and lignin polymers in the cell wall 

relate to patterns of transport and delivery of 

precursor-containing secretory vesicles?

Further elaborating the identity of intra- and interpolymer cross-linkages and the role of wall proteins 

and metals will be important, as will clarifying the 

extent of uniformity in cell wall architecture and wall 

polymer distribution along the cell boundary. Also 

of great interest is resolving the system dynamics 

that underlie and control achievement of defined cell 

wall phenotypes. These dynamics include changes in 

(1) membrane lipid dynamics, (2) metabolites and 

the local environment (e.g., shifts in H+

, Ca2+, and 

reactive oxygen species in the apoplast, membrane, 

and cytosolic space), and (3) cellular signaling and 

regulatory events.

The Golgi apparatus and vesicle trafficking system are integral players in cell wall biosynthesis, 

which in turn determines biomass properties 

(see Fig. 2.1, p. 8). Golgi-derived vesicles carry 

both precursors of wall polymers (i.e., lignin 

and hemicellulose) and cellulose synthase complexes (CSCs) for cellulose synthesis in plasma 

membranes (Bashline et al. 2014). Research also 

shows that clathrin-mediated endocytosis (CME) 

underlies cellulose synthase (CesA) recycling and 

that CSC turnover affects the degree of cellulose 

Effectively Modeling 

and Predicting Plant 

Cell Wall Systems

Technological improvements 

and innovative developments for 

monitoring molecular-scale structural changes in the cell wall (e.g., 

chemical-physical changes accompanying biopolymer deposition).

• In situ and in vivo

approaches at atomic- and 

molecular-scale resolution 

to use with minimal sample 

preparation and in conditions closely resembling 

the natural environment.

• Effective modeling and 

prediction of spatiotemporally emergent plant system properties to improve 

the precision and pace of 

biomass research.

Cell Wall Composition and Degradation Needs

Characterizing Cell Wall Structure and Chemistry

Further development of imaging techniques and correlative 

approaches for conducting real-time visualization of plant cell wall 

biosynthesis (including secondary cell wall deposition, where most 

lignification occurs) and biomass deconstruction processes in vivo

and in planta.

• Real-time, nanometer-scale imaging techniques to visualize the trafficking of cell wall synthases and modification 

enzymes and the dynamics of cytoskeletal networks.

• Techniques to characterize in situ the bioassembly of plant 

cell wall polymers, such as cellulose microfibril networks 

and interactions among cellulose, pectin, hemicellulose, and 

lignification.

• Improved methods to label proteins and increase throughput, combined with new omics technologies to improve the 

pace and precision of structure-function prediction.

• Synthetic biology approaches to incorporate deuterium into 

cell wall polymers in a controlled manner.

• Systems biology approaches to study plant cell wall biosynthesis, specifically relevant genes and their regulatory networks.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

8 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

polymerization and patterning (McFarlane et al. 

2014). Despite these findings, there is a critical lack 

in the understanding of cell 

wall formation occurring in 

these organelles and vesicles. Molecular and cellular 

(mesoscale) technologies 

are needed to fill these 

knowledge gaps. On the 

molecular front, the ability 

to monitor trafficking of 

vesicles and identify their 

contents in situ and in real 

time, while simultaneously 

detecting changes in cell 

wall properties, will open 

up the next frontier of cell 

wall research. Extending 

the resolution of live-cell 

imaging at single-molecule 

resolution—such as the 

recently demonstrated twocolor nanoscale imaging of 

intracellular targets (Bottanelli et al. 2016)—will 

help researchers examine 

the range of bioenergy-relevant biomolecules in 

plant cells.

Multimodal Biomass Imaging Methods

Traditionally, biomass composition is analyzed by 

wet chemistry (Sluiter et al. 2013). The research 

community has used many other analytical methods to characterize plant cell wall structure, such as 

(1) electron microscopy (Ohad et al. 1962; Ohad 

and Danon 1964; Ha et al. 1998), (2) 13C solid-state 

nuclear magnetic resonance (NMR; Ha et al. 

1998; Sturcova et al. 2004), (3) X-ray diffraction, (4) small-angle neutron scattering (SANS; 

Sugiyama et al. 1998), and (5) Fourier transform 

infrared (FTIR) spectroscopy (Sene et al. 1994). 

Advances in some technologies particularly applicable to plant cell walls include:

• Atomic force microscopy (AFM). A scanning 

probe microscopy imaging technique offering subnanometer resolution of surface topography under 

aqueous conditions (see Fig. 2.2, p. 9).

• Advanced transmission electron microscopy 

(TEM) techniques. Scanning TEM for generating nanometer-resolution tomographic 

reconstructions of plant cell wall sections 

(~1 micrometer thick), both before and after 

pretreatment are under development.

• Soft X-ray microscopy and Fourier transform 

infrared (FTIR) microscopy. Two techniques for 

Fig. 2.1. Overview of the Localization and Proposed Trafficking Pathways, Compartments, and Mechanisms of Cellulose Synthase Complexes (CSCs). Although 

pectin and hemicellulose are synthesized in the Golgi apparatus and secreted to the 

cell wall, cellulose is exclusively synthesized by CSCs located at the plasma membrane. 

CSCs are thought to be assembled in the Golgi apparatus, which is responsible for the 

actin-dependent, cell-wide distribution of these complexes. Researchers believe CSCs 

are secreted through the trans-Golgi network/early endosome (TGN/EE) and may be 

partitioned into a specific domain within it. [Image reprinted from Bashline L., S. Li, and 

Y. Gu. 2014. “The Trafficking of the Cellulose Synthase Complex in Higher Plants,” Annals 

of Botany 114(6), 1059–67, by permission of Oxford University Press.]

Key: AP, adaptor protein; CME, clathrin-mediated endocytosis; CSI, compound structure identification; MASC, macrotubule-associated cellulose synthase compartments. 
Chapter 2 – Cell Wall Composition and Degradation

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 9

providing needed spatial information about the 

distribution of lignocellulosic polymers.

• Nano-Secondary Ion Mass Spectrometry (NanoSIMS). Imaging technique enabling elemental 

compositional analysis of samples with a resolution of ~50 nanometers.

• Coherent Raman scattering (CRS) and synchrotron infrared nanospectroscopy (SINS). Two 

techniques providing chemical information at the 

level of functional groups with ~20 to 30 nm resolution (Bechtel et al. 2014; Amenbar et al. 2017).

The ability to overlay results of these emerging 

techniques is promising, yielding high spatial, 

Fig. 2.2. Infrared Light Scattered off a Metallic Atomic 

Force Microscope Tip. The combination of synchrotron 

infrared radiation with scattering, scanning near-field optical microscopy (s-SNOM) enables infrared spectroscopic 

investigations with ~20 nanometer spatial resolution. This 

synchrotron infrared nanospectroscopy (SINS) technique 

can be applied to hard and soft matter, including biominerals, proteins, bacteria, fungi, and other biomaterials to 

identify and measure local surface properties (instead of 

chemistry). The illustration shows the setup for an experiment at Lawrence Berkeley National Laboratory’s Advanced 

Light Source, in which SINS measurements identified 

site-dependent reactivity of chemically active molecules 

that were anchored to the surface of metallic nanoparticles. [Reproduced with permission from Elad Gross, 

The Hebrew University of Jerusalem, Israel; from Faraday 

Discussions 188, 345–53, with permission from The Royal 

Society of Chemistry.]

temporal, and chemical information on plant cell 

walls at the molecular (nano-) through cellular 

(micro-) scales. Further development of these 

correlative imaging techniques will allow realtime visualization of plant cell wall biosynthesis 

and biomass deconstruction processes in vivo

and in planta. Techniques that can co-register and 

overlay chemical, structural, and biomechanical 

characteristics will be essential in closing existing 

knowledge gaps in biomass structure and composition and in supporting the development of more 

effective cell wall utilization methods (see Fig. 2.3, 

p. 10, and Fig. 2.4, p. 11). Recently demonstrated 

multimodal chemical imaging technologies include 

the Hybrid Photonic Mode-Synthesizing Atomic 

Force Microscopy (HPFM), which combines the 

disciplines of nanospectroscopy, nanomechanical 

microscopy (10 to 50 nm), and AFM with Raman, 

fluorescence, and infrared imaging. Another example is multimodal imaging with mass spectrometry 

(MS) that provides spatially resolved molecular and 

elemental mass–based chemical imaging. Newly 

available technologies include matrix-assisted laser 

desorption ionization (MALDI) time-of-flight 

mass spectrometry (TOF-MS), secondary ion mass 

spectrometry (SIMS), helium ion microscopy with 

SIMS (HIM-SIMS), and SINS. A number of the 

methods proposed for measuring metabolites at the 

cellular level also will be important for multimodal 

biomass imaging (see Chapter 5. Metabolic Pathways in Plants, Microbes, and Fungi, p. 37).

Multiscale Computational 

and Modeling Approaches

As a complement to imaging and spectroscopic 

analyses of plant cell wall polymers, multiscale 

computational approaches, such as those below, 

can play a critical role in linking cell wall structure 

and dynamics to natural and engineered changes 

in composition.

• At the atomic level, quantum chemical calculations yield assessments of the strength of 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

10 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

association between biomass components such 

as cellulose and lignin.

• At the molecular level, molecular dynamics simulations, both atomistic and coarse grained, can 

provide information on plant polymer structure at 

nanometer to micrometer resolution and dynamics at nanosecond- to microsecond-length scales.

Scientists also can use such simulations to predict 

the effects of thermochemical pretreatment. Molecular simulation is highly complementary with 

neutron and X-ray scattering experiments that probe 

similar time and length scales. High-performance 

computing extends the time and length scales 

accessible to high-resolution physical simulations. 

Furthermore, lower-resolution, finite-element methods can help characterize the elastic and viscoelastic responses of plant cell walls, important for cell 

expansion during plant growth.

Generating a basic model of a plant cell is the 

unifying goal in developing and applying technologies to probe molecular and phenotypic responses 

in the same or similar plant cells. Achieving this 

goal will entail defined monitoring, visualizations, 

models of plant cell wall biosynthesis and deposition, and remodeling within a given plant cell type 

in optimal growth conditions and in a time-resolved 

manner. Developing this basic model, where none 

exists today, will open doors for independent model 

iterations. The design of these models will need to 

accommodate cell-type heterogeneity within a given 

plant, species-level distinctions, and dynamics in 

response to both internal cues (e.g., developmental 

and physiological) and external ones (e.g., biotic and 

abiotic stressors).

Capabilities are needed to monitor (i.e., image) 

molecular changes (e.g., in nucleic acids, proteins, protein complexes, and metabolites) in the 

context of fine-scale phenotypic changes such as 

chemical-physical shifts accompanying biopolymer 

deposition. These developments will be powerful in accurately co-registering information for 

effective use in modeling efforts. Also needed are 

advancements enabling these technologies to probe 

cells in situ and in vivo. Finally, addressing discovery science–driven goals will require expanding 

Fig. 2.3. Exploring Plant Cell Wall Architecture and 

Chemistry. Plant cell walls are structurally and chemically 

complex at the mesoscale and nanoscale. This complexity 

can be measured by spatial and chemical imaging techniques. At the tissue level, these approaches include optical 

microscopy, which can provide diffraction-limited spatial 

resolution, and micro-spectroscopy for in situ chemical resolution. Other analytical techniques such as mass spectrometry, nuclear magnetic resonance, and X-ray scattering can 

reveal specific physical-chemical information of bulk biomass. At the subnanometer scale, atomic force microscopy 

and electron microscopy can image the cell wall. Beyond 

these technologies, correlative and nondestructive imaging 

techniques are needed to improve the understanding of 

the structure and chemistry of plant cell walls, as well as 

their biosynthesis and bioconversion processes. [(a) Image 

courtesy Shi-You Ding, Department of Plant Biology, Michigan State University from Ding, S., et al. 2014. “Size, Shape, 

and Arrangement of Native Cellulose Fibrils in Maize Cell 

Walls,” Cellulose 21(2), 863–71, with permission of Springer. 

(b) Reprinted from Zeng, Y., et al. 2014. “Lignin Plays a Negative Role in the Biochemical Process for Producing Lignocellulosic Biofuels,” Current Opinion in Biotechnology 27, 38–45, 

with permission from Elsevier. (c) From Ding, S., et al. 2012. 

“How Does Plant Cell Wall Nanoscale Architecture Correlate 

with Enzymatic Digestibility?” Science 338(6110), 1055–60. 

Reprinted with permission from AAAS.]

a

b

c

Different types of cell walls

In situ chemical imaging

Imaging nanoscale architecture
Chapter 2 – Cell Wall Composition and Degradation

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 11

Fig. 2.4 Three-Dimensional (3D) Tomographic Reconstructions of Populus Wood Using Synchrotron Fourier 

Transform Infrared Spectro-Microtomography. Elucidating the 3D molecular architecture of plant cell walls is 

one of the most challenging problems in plant biology, and 

the deconstruction of lignified cell walls is a critical step in 

converting biomass to liquid biofuels and other value-added 

products. (a) Bright-field image of plant biomass. (b, d–f)

The brown in these tomograms represents reconstructed 

intensities of hydrocarbon stretching absorption modes. 

(c, g–i) The red in these images is spectrally associated with 

lignin superimposed on the blue-green colors associated 

with holocellulose. Panels d–i are virtual slices 10 micrometers (μm) thick across the three longitudinal vessels of this 

specimen at locations indicated by the dashed lines. Holocellulose is more prominent in the middle of the wall, whereas 

lignin dominates around the exterior of the wall and middle 

lamellae between vessels. (Scale bars, 20 μm). [Reprinted by 

permission from Macmillan Publishers Ltd: Martin, M. C., et al. 

2013. “3D Spectral Imaging with Synchrotron Fourier Transform Infrared Spectro-Microtomography,” Nature Methods 10, 

861–64.]

phenotypic databases with genotype-to-phenotype 

correlative analyses to enable early identification of 

the molecular and phenotypic properties that can 

effectively predict emergent properties.

Characterizing Cell Wall Structure 

and Chemistry

Development of Correlative Nondestructive 

Methods. The ability to track single-molecule 

behavior has changed the fundamental approach 

to studying biological processes in cell walls. 

Further development of correlative imaging 

techniques will allow real-time visualization of 

biosynthesis and biomass deconstruction processes in vivo and in planta. Early approaches to 

single-molecule imaging in biology primarily have 

focused on fluorescence-based microscopy, in which 

a fluorophore—such as a dye, quantum dot, or 

fluorescent protein—is chemically or genetically 

tagged to a molecule of interest and deterministic 

or stochastic super-resolution techniques track 

the molecule in two or three dimensions (2D or 

3D). However, labeling potentially can interrupt 

the biomolecule’s functions, especially in complex 

systems such as biomass conversion reactions. 

The desire to analyze at nanometer-scale resolution, with minimal sample preparation, and under 

natural conditions excludes most high-resolution 

electron microscopy techniques. These techniques, 

however, are completely amenable to AFM and the 

recently developed stimulated Raman scattering 

(SRS) microscopy for real-time visualization of the 

reaction interface and in situ mapping of cell wall 

chemistry, respectively.

AFM Investigations of the Cell Wall Surface.

Although limited in application to images of a 

substrate’s surface, AFM is especially advantageous 

for studying cell wall accessibility and digestibility 

and thus is a powerful tool for mapping surface 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

12 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

properties. In addition, the cantilever tip (<5 nm) 

is smaller than most enzymes. As demonstrated in 

the literature (Ding et al. 2012), surface properties 

measured by AFM possibly are correlated to enzyme 

accessibility. Notably, researchers can apply AFM 

imaging under nearly the same physiological conditions as enzymatic digestion, meaning that cell wall 

surface interactions are essentially the same with 

both the AFM tip and the enzymes.

NMR and Polymer Structure and Bonds. NMR 

can provide detailed molecular information about 

lignin and polysaccharide structures and detect 

covalent linkages between these two biopolymers 

(del Río et al. 2016). Both solution- and solid-state 

NMR frequently are used to monitor changes 

resulting from biomass pretreatment (Trajano et al. 

2013; Petersen et al. 2014). Carbon-13 labeling 

of whole plants allows sensitive acquisition of 2D 

solid-state carbon-carbon correlation spectra of cell 

walls, enabling detailed study of cell wall architecture 

(Wang and Hong 2016). These studies have shown 

that cellulose microfibrils are cross-linked more 

through pectin than through xyloglucan (Dick-Perez 

et al. 2011) and have helped determine the number of cellulose chains that make up a microfibril 

(Wang and Hong 2016). Comprehensive multiphase 

NMR—a combination of liquid, gel, and solid-phase 

NMR—can investigate intact plants, avoiding the 

need for any type of extraction (Wheeler et al. 2015). 

This approach uses filtering techniques to observe 

components present separately in the three phases.

MS Techniques for Cell Wall Characterization.

Several MS-based approaches provide chemical 

and structural information on cell wall polymers. 

Techniques such as negative and positive ion 

electrospray (ESI) tandem mass spectrometry 

(MS/MS) can analyze the sequencing and linkages of underivatized oligosaccharides obtained 

from partial depolymerization of several α- and 

β-glucans (Palma et al. 2015). ESI-MS/MS also 

can structurally characterize branched hemicellulose oligosaccharides (Quemener et al. 2015). 

Ion mobility–MS, in combination with ESI-MS, 

is able to separate and distinguish closely related 

hemicellulose oligosaccharide isomers (Plancot 

et al. 2014). Researchers can use MALDI-MS imaging to identify and localize cell wall polysaccharides 

on biomass samples by performing partial enzymatic digestions directly on the biomass, without 

translocation of the released oligosaccharides. They 

then can detect and characterize these polymers 

by MALDI-MS and localize them at micrometer 

resolution (Veličković et al. 2014; Veličković et al. 

2016). Finally, scientists can determine lignin structure and its changes, including ratios of constituent 

monolignols and of C5 and C6 sugars, in a topdown approach and in high-throughput fashion by 

several means. They include pyrolysis–molecular 

beam MS, ESI-MS, atmospheric pressure photoionization (APPI), MALDI-MS, and MS/MS 

(Kelley et al. 2002; Banoub et al. 2015).

Nondestructive Imaging Using Neutrons. Many 

of the techniques described above can be used 

to provide information about structural changes 

in lignocellulose components before and after a 

pretreatment regime. However, to best understand 

the morphological changes that occur during pretreatment, structural analysis must be performed 

in situ. Neutron scattering techniques are ideally 

suited to this task because they can probe the length 

and time scales relevant to lignocellulose characterization (see Fig. 2.5, p. 13). Moreover, because 

neutrons do not destroy delicate biological samples, 

scientists can study structural changes to biomass 

in situ and in real time using a specialized reaction 

cell. A unique property of neutron scattering is that 

it enables contrast variation techniques that allow 

separation of scattering contributions from different components within intact lignocellulose. This 

process occurs through the controlled replacement 

of hydrogen with its isotope deuterium. Developing 

synthetic biology approaches to incorporate deuterium into cell wall polymers in a controlled manner 

would provide new details about the structural and 

temporal rearrangement of lignocellulose during 

pretreatment. For example, feeding deuterated 

variants of specific metabolic intermediates such

as GDP-fucose or GDP-rhamannose may produce 
Chapter 2 – Cell Wall Composition and Degradation

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 13

specific labeling of Fuc and Rha polymers, which 

then can be probed with neutrons.

Techniques for Characterizing Holoproteins 

and Their Interactions. Cellulytic enzymes 

are typically multidomain proteins with wellfolded domains separated by flexible linkers. 

Although X-ray diffraction and NMR have provided atomic-resolution structural information 

about the ordered domains of these proteins, 

only low-resolution information, obtained using 

small-angle X-ray and neutron scattering, is available for holoproteins. Recent advancements in 

cryo-electron microscopy (or cryoEM) techniques 

(see Chapter 6. Biosystems Design, p. 45) with new 

direct electron detector technology, have enabled 

(1) the determination of increasingly complex 

systems at near-atomic resolution and (2) the 

characterization of different conformational states 

of biomolecules resulting from conformational 

heterogeneity in samples. This technique has the 

potential to overcome limitations of other techniques and provide new insights into the structure 

of complex cellulolytic complexes such as the bacterial cellulosome.

New approaches to Investigate How Cellulases 

Interact with Insoluble Substrates. Typically, 

studies are limited to using soluble oligosaccharides or indirect approaches such as binding assays. 

Methods to prepare more realistic polysaccharide 

substrates with minimal structural heterogeneity 

will enhance structural and functional studies. 

SANS with contrast variation and biomolecule 

deuterium labeling has the potential to provide 

structural insight into cellulase-cellulose interactions. Researchers also could use this approach to 

understand the mechanism of cellulase inhibition 

by nonproductive interactions with lignin and other 

compounds. Such studies could yield more-specific 

Fig. 2.5. Real-Time Small-Angle 

Neutron Scattering (SANS) Supported by Molecular Dynamics 

Simulation for Identifying Processes Occurring During Biomass 

Thermochemical Pretreatment.

(Left panels) Illustration of changes 

to lignocellulose. Changes in cellulose morphology (brown hexagons), 

lignin (red chains) aggregates, and 

hemicellulose (green chains) occur 

during the pretreatment process. 

(Middle) Two-dimensional SANS 

images. (Right) In situ SANS reaction 

cell. [(Left) Pingali, S. V., et al. 2014. 

“Morphological Changes in the 

Cellulose and Lignin Components 

of Biomass Occur at Different Stages 

During Steam Pretreatment,” Cellulose 21(2), 873–78, with permission 

of Springer. (Left) Reproduced from 

Langan, P., et al. 2014. “Common 

processes drive the thermochemical 

pretreatment of lignocellulosic biomass,” Green Chemistry 16(1), 63–68, 

with permission from The Royal 

Society of Chemistry.]
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

14 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

structural information on enzyme-lignin-cellulose 

interactions needed to elucidate these mechanisms.

Improved Methods for Elucidating Interaction 

Mechanisms. Molecular interactions, such as 

enzyme with substrate or enzyme with donor can be 

probed by saturation transfer difference NMR spectroscopy (STD) or transferred nuclear Overhauser 

effect spectroscopy (tr-NOESY) NMR (Marchetti 

et al. 2016). In STD, selected protons throughout 

the protein are magnetically saturated. This saturation then is transferred to the carbohydrate ligand, 

leading to reduced signal intensity of protons that 

interact with the protein and thus enabling elucidation of the interaction mechanism between binding 

partners. The use of tr-NOESY allows detection of 

NOE contacts present only in the bound state, thus 

characterizing the conformation of the interacting 

oligosaccharide. Methods to prepare the necessary 

labeled proteins are known but could be improved 

along with greater spectral sensitivity to increase the 

throughput of these approaches.

Sequence-to-Function Continuum. To accelerate the pace of biomass improvement efforts, new 

genomic technologies are needed to manipulate 

plant systems at the molecular, cellular, tissue, and 

organismal levels. Genome and transcriptome 

sequencing technologies are yielding a wealth of 

information, yet it is only partially annotated or 

interpreted for function. Greater pace and precision would enable prediction of (1) the functional 

consequence of gene sequence variation on cell 

wall and biomass properties and (2) sustainability traits based on a comprehensive protein 

sequence-structure-function knowledgebase. Key to 

maximizing the functional interpretation of genome 

sequences and sequence variation is to develop and 

make available molecular and mesoscale technologies that can assist in understanding protein structure, activity, and function. Progress in this area 

could advance significantly from the iteration of 

computational prediction and simulation methods 

with experimental characterization and verification. 

New technologies would transform the current 

research landscape, enabling characterization of 

plant cell wall biosynthesis and remodeling pathways based on structural biology and multiplexed 

protein assay platforms that include multiplexed 

protein-ligand binding, enzyme-substrate conversion, and single-molecule protein pull-down 

(SiMPULL; Jain et al. 2012).

2.3 Advancing Biofuel and 

Bioproduct Design and Production

A deeper understanding of plant cell wall architecture at the molecular to mesoscale levels will provide knowledge of the structure and dynamics of 

native biomass and the response of its components 

to pretreatment regimes and subsequent enzymatic 

processing. To achieve this understanding, scientists must develop approaches that combine disparate datasets from analytical chemistry, direct and 

indirect imaging techniques, and spectroscopies. 

Incorporating experimental datasets in computational cell wall models will overcome the knowledge gap that exists in understanding the structure 

of the plant cell wall and the critical structural rearrangements that increase biomass digestibility for 

biofuel and bioproduct production. These advances 

will transform the current pace and depth of understanding of plant biomass improvement efforts.

Genomic studies have identified many genes 

involved in plant cell wall biosynthesis and modification. However, the regulation of these genes and 

how they communicate (i.e., interact) with environmental factors are still poorly understood. Research 

in understanding biosynthesis and trafficking of cell 

wall components is critical to enable the rational 

design and production of improved biomass. Achieving this understanding requires new tool development for visualizing in vivo and real-time biosynthesis 

events, such as deposition of cellulose microfibrils, 

secretion of hemicelluloses, and transformation of 

lignin monomers and lignification. Also needed is 

cell imaging with single-molecule resolution, which 

will enable visualization of a range of cellular biomolecules. These capabilities will open up the next 

frontier of cell wall research and lead to technological 

improvements in bioenergy feedstock plants.
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 15

Chapter 3 – Rhizosphere Community Interactions

Microbes play critically important roles in 

the environment, shaping plant health 

and productivity, the terrestrial carbon 

cycle, and environmental remediation. Although 

the ability to identify the organisms involved in 

these processes has significantly improved with 

modern sequencing technologies, characterizing microbial activities and their interactions 

with plants, viruses, soil fauna, and the abiotic 

environment remains a significant challenge. 

These interactions are particularly impactful 

in the rhizosphere, the biologically active area 

immediately surrounding plant roots. Rhizosphere 

microbiomes (consisting of bacteria, fungi, archaea, 

protists, and phages) include diverse taxa such as 

nitrogen fixers and crop pathogens, mycorrhizal fungi, 

and beneficial bacteria that enhance plant nutrient acquisition and drought tolerance. Stimulated by root exudates and 

root decay, rhizosphere organisms interact to move carbon 

from root tissues to the surrounding soil, a process that 

ultimately regulates both soil carbon stabilization and ecosystem processes such as trace gas production. Plant-microbe 

interactions occurring within plant tissues and on leaf surfaces 

also play important roles in plant health. However, knowledge 

of plant-microbe interactions is constrained to only a few 

model systems. Little is known about interactions among 

root-associated microbes and even less about their interactions with other members of the soil food web (e.g., fungi, 

fauna, and phages; see Fig. 3.1, p. 16).

Chapter 3

Rhizosphere 

Community 

Interactions
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

16 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

3.1 Current Science and 

Technologies

Rhizospheric microbial communities drive fundamental processes in the global carbon cycle 

and regulate levels of atmospheric carbon dioxide (CO2) and soil carbon storage. Microbiome 

research seeks to define community membership, 

ecological relationships among organisms, and the 

roles specific taxa play in systems-level chemical 

and biological processes. Regardless of their habitat, microbiomes comprise many different taxa, 

exploiting an energy source, yet these microbial 

assemblages often are inherently interdependent and 

dynamic in both space and time. The comprehensive 

understanding of in situ microbiome ecology has 

become tantalizingly possible with the advent of 

high-throughput sequencing, advanced microscopy, 

and stable-isotope tracing techniques. However, current microbiome studies often are highly descriptive, 

focused on correlation patterns or simple one-onone interactions between culturable organisms.

This chapter describes current and needed technologies that address (1) microbe-microbe and 

plant-microbe interactions and their influence on 

rhizosphere processes and ecosystem services that 

benefit humankind, (2) plant genetic and physiological controls on root exudate composition and 

beneficial interactions with microbial symbionts, 

(3) soil chemical and biological processes, and 

(4) interkingdom interactions (e.g., algae-bacteria, 

Fig. 3.1. Significant Effects of Plants, Microbes, and Their Communities on Biogeochemical Transformations at Multiple Scales. New methodologies and technologies are needed to inform a wide range of mission-relevant questions for the 

U.S. Department of Energy Office of Biological and Environmental Research. [Image adapted from David McNear, University of 

Kentucky Rhizosphere Science Laboratory.]
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 17

fungi-bacteria, and bacteria-phage). Many of these 

approaches seek to link the identity of uncultivated 

microbes with their potential to metabolize compounds in the environment—a topic that remains 

a “grand challenge” area for the field of microbial 

ecology (Neufeld et al. 2007).

3.2 Major Challenges in Detecting 

Rhizosphere Interactions

Capturing Molecular Exchanges 

Underpinning Plant-Microbe Interactions

Critical research in environmental microbiology and 

phytobiome studies hinges on questions such as, 

Rhizosphere Community Interactions Needs

Revealing and Monitoring 

Plant and Microbe Interactions

Improved biofuel and bioproduct production with 

sustainable agriculture practices and better comprehension of both beneficial and harmful plant-microbe 

interactions for making quantitative, in situ, and 

three-dimensional measurements of dynamic 

molecular phenomena with nanometer to centimeter resolution.

• New ways to collect plant exudates and 

metabolites under realistic conditions.

• Reference databases to help identify 

the detected transcripts, proteins, and 

metabolites.

• Methods to noninvasively monitor root 

growth in a field setting over a growing 

season and root impacts on soil carbon or 

water stocks.

• Efforts to determine minimal necessary 

biological information (e.g., key microbial 

processes and critical environmental drivers) 

to parameterize soil models.

• Biotechnologies to enable persistence of 

relationships between plants and growthpromoting microbes in field settings.

Improving Image or Sensor-Based Systems 

to Monitor Root-Microbe Interactions

Improved image- or sensor-based systems for monitoring root exudates and rhizospheric microorganisms in situ at biologically relevant length and time 

scales for revealing deeper insights into interdependencies within the rhizosphere.

• Methods to monitor root-microbe interactions in real time in the soil.

• Novel frameworks to perform 13C metabolic 

flux analysis for consortia systems having 

more than three members and harnessed for 

nonmodel rhizospheric systems.

• Reference metabolism databases to use for 

nonmodel microbes in the rhizosphere.

• Improvements in detector technologies and 

optics to increase spatial resolution to less 

than 10 micrometers for cellular-level imaging.

• Novel contrast agents to enable new experiments for following dynamic processes in 

plants and their associated rhizosphere.

• Genetic tools to study systems with no 

available draft genome and with polyploid 

conditions that limit genetic-modification 

effectiveness.

“Which organisms live where, and what do they do?” 

However, obtaining simultaneous spatial, temporal, chemical, and phylogenetic information for 

native microbial communities is extremely difficult, 

particularly in opaque systems such as the soil or 

faunal guts. To better comprehend both beneficial 

and harmful plant-microbe interactions, researchers 

need capabilities to make quantitative, in situ, and 

three-dimensional (3D) measurements of dynamic 

molecular phenomena with nanometer to centimeter resolution. These technologies are needed to 

discover the ephemeral molecular signals serving 

as communication pathways between plants and 

their microbial partners. While measurement of 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

18 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

intra- and intercellular fluxes is currently possible 

in simple mixtures, such as between microalgae and 

bacteria (Hom et al. 2015), novel approaches are 

needed to extend this capability into the rhizosphere 

and capture the molecular exchanges that underpin 

multitrophic interactions (e.g., soil food webs).

Particularly in the rhizosphere, these interactions 

often are mediated by competition, cooperation, or 

interconnected metabolisms involving mixed populations of microbes, fungi, protists, microfauna, and 

phages. The use of metagenomic sequencing provides the genomic profile of all members of such a 

communal system. Recent advances in metagenomics have enabled researchers to identify and “count” 

members within these communities and suggest 

a system’s genetic potential, but without quantitative and temporal resolution. Approaches such as 

metatranscriptomic sequencing and metaproteomic 

or metabolite profiling may reflect current community activity, but they continue to be limited by the 

quality of reference databases, which are needed 

to help identify the detected transcripts, proteins, 

and metabolites through comparison with known 

samples. Another key challenge in this area is the 

identification of a community’s eukaryotic components (e.g., protists, fungi, and microfauna), whose 

genomes often are large, difficult to assemble, and 

highly underrepresented in reference databases.

Genomic, transcriptomic, metabolomic, and proteomic methods have advanced considerably, but 

they still are most often applied to single-microbe, 

cultured systems. Results from these data streams 

need to be more effectively integrated and their predictions verified through manipulative experiments, 

metabolic modeling, and quantitative observations 

of metabolic fluxes within and between organisms 

(via imaging or biochemical characterization). 

Natural microbiomes are teeming with a mixture of 

organisms that interact not only with each other, but 

at surface interfaces, in environmentally sensitive 

zones, and at points of biocatalysis (i.e., enzymatic 

transformation of organic compounds). Although 

conducting “bulk” measurements is sometimes 

desirable for mixed microbial systems, determining 

interaction mechanisms among the system members 

often requires measuring reactions at key biological 

interfaces in real time, with high spatial resolution 

[1 micrometer (μm) to 10 mm]. For example, an 

ideal scenario would involve discovering the repertoire of enzymes and the composition of chemical 

breakout products generated by saprotrophic fungi 

and bacteria during lignocellulosic breakdown of a 

decaying root. Similarly, scientists can derive knowledge of plant metabolites primarily from highly simplified hydroponic systems, but plants grow naturally 

in a soil matrix where metabolites of interest likely 

are intercepted by the surrounding microbiome 

before they can be collected. Thus, new ways are 

needed to collect plant exudates and metabolites 

under realistic conditions.

Understanding the Soil Carbon Cycle 

to Aid Sustainable Biomass Agriculture 

for Bioenergy Production

Microbial communities drive fundamental processes 

in the global carbon cycle and regulate levels of 

atmospheric CO2 and soil carbon storage. Underlying these activities is the ability of microbiota 

to aggregate newly formed minerals and oxidized 

residues of microbial biomass to create a structured, 

porous matrix that serves as a reactor for cycling 

matter and as a reservoir of nutrients and water. 

However, a mechanistic, genomically informed 

molecular understanding of the fate and turnover 

of soil organic matter (SOM) is lacking. Myriad 

decomposition processes shape SOM—originating 

from root exudates, root turnover, and microbial and 

invertebrate necromass. These processes determine 

nutrient availability and the tilth of a soil, a critical 

yet difficult-to-measure trait reflecting soil structure, 

aggregation, and overall suitability for agriculture. 

Efforts to make agricultural practices more sustainable for biofeedstock production, and thus bioenergy endeavors, require in situ measurements of soil 

tilth attributes and new technologies that can track 

SOM from its source to its fate with high molecular, 

spatial, and temporal resolution.
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 19

Optimizing System Effects 

of Plant Genotypes

Optimizing plant feedstocks for bioenergy and 

sustainable agriculture also requires a better comprehension of the genetic underpinnings of plant 

gene–environment interactions, particularly for root 

architecture and function. Although the architecture 

of the root system is widely known to have a strong 

genetic component, its topology, cell morphology, 

and function can be very responsive to environmental drivers and the surrounding microbial holobiome. Currently, there are no means of noninvasively 

monitoring root growth over a growing season in a 

field setting or monitoring root impacts on soil carbon or water stocks. Other needs are biotechnologies that enable persistence of relationships between 

plants and growth-promoting microbes in field settings (see Chapter 6. Biosystems Biodesign, p. 45). 

Well-designed mutualistic plant-microbe interactions could improve plant nutrient and water acquisition and stress tolerance while simultaneously 

promoting carbon stabilization, soil fertility, and a 

diverse soil biota.

Scaling Data from Genomics 

to Ecosystem Processes

Researchers currently cannot model microbial 

activities at a scale useful for predicting responses to 

environmental changes such as temperature variation, 

drought, and land-use shifts. Some have proposed 

using trait-based modeling approaches to represent 

microbial genetic capacities in ecosystem-scale carbon cycle models, and early results suggest significant 

positive effects on the predicted responses of soil 

carbon (Wieder et al. 2013; Hagerty et al. 2014). 

Additional efforts are needed to determine the minimal biological information (e.g., key microbial processes and critical environmental drivers) necessary 

to parameterize soil models. An example of current 

capabilities in modeling a community’s metabolic 

networks and improving the understanding of them 

is what the DOE Systems Biology Knowledgebase 

(KBase; see box, this page) calls a Narrative (narrative.

kbase.us/narrative/ws.13807.obj.1). Presented at the 

meeting was an example of a KBase computational 

workflow associated with a publication (Henry et al. 

2016) that tests the use of community-level data for 

network reconstruction for interspecies interactions 

when members are not well characterized and cannot 

be experimentally isolated.

3.3 Major Needs in State-of-the-Art 

Technologies for Understanding 

Rhizospheres

Acquiring New Genetic Tools 

for Recalcitrant Organisms

Unfortunately, the vast majority of microbes within 

environmental consortia cannot be cultured, leading 

to a lack of understanding of how microbial communities are structured and evolve (Solomon et al. 

2014) and limiting the research community’s ability 

to harness these microbes for bioenergy applications 

through genetic manipulation (see Fig. 3.2, p. 20). 

With the advent of approaches enabled by clustered 

regularly interspaced short palindromic repeats 

KBase Narratives

Within the DOE Systems 

Biology Knowledgebase 

(KBase), computational 

experiments are captured 

in dynamic, interactive 

documents called Narratives that promote collaboration and reproducibility 

of scientific results. In addition to all the data, 

parameters, analysis steps, and output reports 

associated with an experiment, Narratives can 

include user images, notes, and commentary. The 

KBase system also maintains Narrative provenance 

and versioning, tracking a user’s edits and app 

re-executions, along with resulting updates in the 

underlying data. Narratives can be kept private, 

shared with colleagues and collaborators, or made 

public for the benefit of the research community. 

Because the Narrative Interface is built on the 

Jupyter Notebook, users can write custom scripts 

in their Narratives. A selection of KBase Narratives 

is showcased in the Narrative library (kbase.us/

narrative-library/).

kbase.us
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

20 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

(CRISPRs; Cong et al. 2013; Qi et al. 2013) targeted 

to both prokaryotic and eukaryotic systems, researchers can now genetically modify an expanded set of 

organisms. However, additional barriers mitigate the 

effectiveness even of CRISPR systems, including but 

not limited to cell wall thickness, recombination, and 

transformation efficiency. Strategies need to be developed for systems with no available draft genome and 

with polyploid conditions that limit the effectiveness 

of genetic modification.

Characterizing Metagenomes for 

Proteomic and Metabolomic Analyses

Whole-community proteomics and metabolomics 

are promising approaches for integrated systems 

biology research addressing questions about 

microbial activities and interactions of uncultured, 

in situ taxa. However, many components of environmental and root microbiomes have no associated 

genomic sequence information, necessitating full 

metagenomic characterization prior to proteomic 

and metabolomic analyses. Quantitative mass 

spectrometry and shotgun proteomic approaches, 

the current standards for investigating these systems, 

are expensive, extremely limited in throughput, 

and inaccessible to many laboratories. Numerous 

research groups could benefit from increased 

access to shared informatics tools and data storage. 

Another key challenge requires technologies with 

sensitivity for low-abundance proteins and metabolites in natural samples such as soils and sediments, 

especially when considering metaproteomic characterization of an interacting system.

Quantitative proteomic approaches are excellent 

for assessing overall changes in the “physiology” 

of microbial communities and for helping identify 

biomarkers of the co-culture community that may 

indicate its stability (or instability), the presence or 

absence of particular organisms, and other important features of interest. Monitoring of such biomarkers is best performed using selected reaction 

monitoring (SRM) assays on a mass spectrometer 

that also can be multiplexed in multiple reaction 

monitoring (MRM). MRMs are fast, sensitive, 

and quantitative approaches to simultaneously 

monitor multiple proteins or peptides of interest. 

These technologies are rapidly replacing immunology-based tests (e.g., enzyme-linked immunosorbent assay, or ELISA) developed mostly for human 

health applications (Choi et al. 2013) but also 

applicable to environmental biological systems.

Monitoring Microbial Activity 

with Isotope Tracing

Currently, a large emphasis in microbial ecology is 

on sequencing DNA and RNA of natural microbial populations. Ideally, sequencing should be 

paired with direct monitoring of microbial activity 

to determine the relationship between genetic 

potential and actual process rates. Isotope-tracing 

Fig. 3.2. Anaerobic Fungi Isolated from the Digestive 

Tract of Large Herbivores. These fungi thrive on the 

hydrolyzed sugars from crude biomass, potentially an aid 

in bioenergy production. As yet, there are no genetic tools 

that can modify the function of anaerobic fungi because 

of a lack of genomic information coupled with the formidable barrier of the fungal cell wall. In the image, helium 

ion microscopy illustrates growth of the novel isolate, 

Anaeromyces robustus, a depolymerizing crude reed canary 

grass. [Image courtesy Chuck Smallwood, Pacific Northwest 

National Laboratory.]
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 21

experiments are useful for monitoring microbial 

activity and have been used to study specific 

interactions in plant systems as well (Hernández 

et al. 2015; Moyes et al. 2016), including mycorrhizal fungi (Nuccio et al. 2013; Kaiser et al. 

2015) and rhizosphere communities (Hernández 

et al. 2015; Shi et al. 2015; Pett-Ridge and Firestone 2017). To analyze more complex communities, researchers have applied combinations 

of (1) stable-isotope probing (SIP; Radajewski 

et al. 2000; Mayali et al. 2012; Hungate et al. 

2015); (2) nanoscale secondary ion mass spectrometry (NanoSIMS) imaging (Pett-Ridge and 

Weber 2012); see Fig. 3.3, this page); and, for 

microbe identification, (3) fluorescence in situ

hybridization (FISH; Behrens et al. 2008; Dekas 

and Orphan 2011; Musat et al. 2016) or Raman 

single-cell sorting (Eichorst et al. 2015). All these 

techniques have provided valuable links between 

identity and function in mixed microbial communities but need further adaptation for applications 

in soil and on root surfaces. New approaches also 

are needed for molecular-scale imaging of root 

exudates and microbial metabolites to capture the 

extremely rapid specific exchanges between plants 

and microbes. In these cases, the targeting of 

metabolically active microorganisms in detail may 

be best suited to molecular imaging techniques 

such as nanostructure-initiator mass spectrometry (NIMS; Northen et al. 2008) and SIP-based 

approaches including SIP-metagenomics, mRNASIP (Haichar et al. 2012), protein-SIP ( Jehmlich 

et al. 2010), and metabolomics-SIP (Freund and 

Hegeman 2017).

Measuring Taxa-Specific Secondary 

Metabolites, Metabolic Fluxes, 

and Modeling

Natural ecosystems consist of thousands of 

different microbial species that share the same 

habitat. Although some organisms may compete 

for the same substrate, the waste product of one 

microbe could inhibit a neighbor, or two different microbes might simbiotically feed off each 

Fig. 3.3. Multimode Imaging of Organismal Interactions 

Relevant to the Rhizosphere. (From top) Fluorescence 

in situ hybridization (FISH)–tagged bacteria on an Avena 

fatua root. Scanning electron microscopy (SEM) and 

nanoscale secondary ion mass spectrometry (nanoSIMS) 

images of kaolinite-coated fungal hypha from a 13C-plant 

incubation; a sectioned protist cell containing 13C-cellulose–

degrading bacteria; viral particles with 15N-thymidine–

enriched DNA. [Bacteria in Protist images from Carpenter, 

K. J., et al. 2013. “Correlated SEM, TEM, and NanoSIMS 

Imaging of Microbes from the Hindgut of a Lower Termite: 

Methods for In Situ Functional and Ecological Studies of 

Uncultivable Microbes,” Microscopy and Microanalysis 19(6), 

1490–501, reproduced with permission. All other images 

courtesy Jennifer Pett-Ridge, Rhona Stuart, Rachel Neurath, 

Kevin Carpenter, Peter Weber, Alex Malkin, and Sean Gates. ]
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

22 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

other’s byproducts (Morris et al. 2013). All these 

processes happen simultaneously across countless 

microbes, controlling community structure and 

function as well as interactions with associated 

root networks. Of key interest are the secondary 

metabolites within microbial communities, which 

often are produced by cryptic environmental 

triggers that are difficult to reproduce in a laboratory (Cane et al. 1998). Current technologies 

are limited to genome-mining methods (e.g., 

antiSMASH) to posit putative (Blin et al. 2013) 

structures of these metabolites. New technologies 

are needed to advance genomic, transcriptomic, 

and metabolomic capabilities to (1) provide accurate predictions of novel metabolite structures, 

(2) quantify their production spatially in native 

environments, and (3) link metabolite generation to specific constituents within microbial 

communities.

Specific chemical signaling (both nonvolatile and 

volatile) between plants and microorganisms is 

understudied, with the exception of a few examples 

such as rhizobia and arbuscular-mycorrhizal fungi 

(AMF). Less is known about signaling between 

plants and nonendophytes or directly between 

microorganisms in soil. Fungi-bacteria interactions 

are of special interest, particularly in cases where 

nutrient foraging partnerships are expected (e.g., 

with AMF). Determining available metabolic 

networks within a suite of interacting organisms is 

critical to monitoring the community’s key integration points. The development of radioactive tracer 

experiments has enabled verification of metabolic 

pathways predicted from genomic information 

(Stewart et al. 2010), but additional work using 

high-sensitivity approaches [e.g., accelerator mass 

spectrometry (AMS)] is needed to quantitatively 

parameterize multitaxa metabolic models. Novel 

frameworks for performing 13C metabolic flux 

analysis (13C-MFA) are now a reality for co-culture 

systems (Antoniewicz 2014; Gebreselassie and 

Antoniewicz 2014) but have yet to prove accurate 

for consortia systems with more than three members. Although promising, these frameworks are 

limited to model systems such as Escherichia coli

and have not yet been harnessed for the nonmodel 

systems of interacting microbes more typically 

found in the rhizosphere. In addition, approaches 

using optimal isotopic tracers for 13C-flux analysis 

often provide unclear results but still are needed to 

amplify differences for detection in cellular metabolism for the different community members. Typical 

outputs of these experiments are measured using 

gas chromatography mass spectrometry, or GC-MS 

and then are computationally deconvoluted using 

in-house software tools to produce species-specific 

metabolic fluxes. These computational tools also 

lack metabolic models for nonmodel microbes 

within the rhizosphere.

Imaging Plant-Microbe Interfaces

The rhizosphere is highly dynamic in time and 

space, and its spatial relationships difficult to 

study in a high-throughput manner because of 

the soil’s opacity and large surface area. A suite of 

well-validated imaging methods could play a greater 

role in imaging plant-microbe interactions in both 

the rhizosphere and within plant tissues (Oburger 

and Schmidt 2016; see Fig. 3.4, p. 23). These methods include neutron radiography (in combination 

with deuterated water tracing; see Fig. 3.5, p. 24), 

14C phosphor-imaging, optode−diffusive gradient 

in thin films (DGT) sensor imaging, zymography, 

confocal scanning laser microscopy along with 

FISH combined with catalyzed reporter deposition (CARD-FISH), and labeling of target microorganisms with green fluorescent protein (GFP).

Information on the temporal behavior of localized chemical events is fundamental to understanding the highly dynamic interactions at the 

plant-microbe interface. As such, the ability to 

image chemical gradients and processes at the 

nano- to micrometer scale in real time will provide 

the highly informative data needed to unravel the 

complex networks of interface processes. Existing synchrotron FTIR (sFTIR) imaging methods 

have enabled insights into (1) micrometer-scale 

microbial community activities (Hazen et al. 2010; 
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 23

Fig. 3.4. Imaging of Processes at Root-Microbe-Soil Interfaces on Various Scales. (a) Nanoscale secondary ion mass spectrometry (nanoSIMS) of arbuscular-mycorrhizal fungal hyphae in a wheat root; (b) neutron radiographs showing flow of deuterated water into roots; (c) optode–diffusive gradients in thin film (DGT) sensor images of oxygen, iron, arsenic, and nickel 

in the rhizosphere of rice; (d) zymograph showing nitrogen-acetyl-glucosaminidase (chitinase) activity around lupin roots; 

(e, f) confocal scanning laser microscope images of microbes labeled with green fluorescent protein (GFP) and fluorescence 

in situ hybridization (FISH) in the rhizoplane, (g) synchrotron tomography illustrating rhizoplane root hairs (green), soil particles (brown) and water (blue), (h) X-ray microtomography reconstruction of bean root system architecture. [Reprinted from 

Oburger, E., and H. Schmidt. 2016. “New Methods to Unravel Rhizosphere Processes,” Trends in Plant Science 21(3), 243–55. 

© 2016, with permission from Elsevier.]

a

b

d

g h

e f

12 c C14N 31P:12C 13C:12C

Low

t=0 t=8 min t=15 min

High 0.0108 0.0130

0.0 1.68 3.36 6.24 9.60 11.5

N-acetyl-β-glucosaminidase activity

(pmol mm-2h-1)

2 mm

Low High

Ni

As

Fe

O2

150 μm 

300 μm 

Soil water potential (hPa) Root age (d)

–2e+003 –500 6 34

20
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

24 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Baelum et al. 2012; Mason et al. 2012; Probst et al. 

2013; Bouskill et al. 2016) and (2) plant root processes at micrometer spatial resolution (Cohen et al. 

2015). Researchers need access to methods to characterize various plant-microbe interfaces, as well as 

additional sFTIR developments to image interface 

processes at nanometer length scales in situ and in 

real time.

Using X-ray and Neutron Imaging

Using X-rays to penetrate soil would seem like an 

obvious solution to the problem of soil opacity. 

However, such analysis has three primary impediments: (1) roots have the same attenuation level 

as water and organic matter, (2) the resolution of 

X-ray systems has precluded the detection of fine 

roots, and (3) X-ray system use has been restricted 

to the laboratory and with relatively small containers. Despite these challenges, the research 

community has made recent improvements on all 

fronts. For example, a group in the United Kingdom 

has developed robust software to identify roots 

in imaging data from complex soil environments 

(Mairhofer et al. 2013; Pound et al. 2013; Mairhofer 

et al. 2015). They also have built a high-powered 

X-ray system that can image plants grown in larger 

containers (Daly et al. 2015). Others have demonstrated the use of X-ray computed tomography for 

detecting rice roots, which are relatively thin, and 

have used this technology to investigate differences 

in root system architecture for the same genotypes 

in different soil substrates (Rogers et al. 2016).

Neutrons are uniquely sensitive to light elements 

such as hydrogen and its isotope deuterium; they 

are highly penetrating and, unlike X-rays, do not 

cause radiation damage to sensitive biological 

samples. Neutron radiography and tomography 

have made possible the study of (1) root system 

architecture and (2) water dynamics in the roots 

and the surrounding rhizosphere in situ using 

deuterium oxide as a contrast agent (Warren et al. 

2013; Kroener et al. 2014; Totzke et al. 2017). The 

spatial resolution of neutron radiography is currently ~50 μm, and temporal resolution is 1 second. 

Improvements in detector technologies and optics 

to increase spatial resolution to less than 10 μm 

would enable imaging at the cellular level. In addition, the development of new contrast agents would 

allow new types of experiments to follow dynamic 

processes in plants and the associated rhizosphere.

Modeling Internal Root Anatomy 

to Optimize Function

Researchers have used mathematical models to simulate root growth under various environmental conditions (Walk et al. 2004; Dathe et al. 2016). These 

models make assumptions about the rates and direction of growth for different types of roots in response 

to nutrients, toxins, and water. One assumption is 

that growth rates for any particular root type in a 

homogeneous medium should be relatively constant. 

Challenging this assumption are recent observations 

of root growth rates over time that have detected 

Fig. 3.5. Neutron Imaging Reveals Root Architecture and 

Internal Plant Water Dynamics In Situ. (a) Maize seedlings 

grown in sand imaged using radiography and tomography. 

(b) Pulses of water or deuterium oxide tracked through the 

root systems. Water flux within individual roots responded 

differentially to foliar illumination based on supply and 

demand of water in the roots. (c) Tomographic reconstruction of root architecture. [Reprinted from Warren, J. M., 

et al. 2013. “Neutron Imaging Reveals Internal Plant Water 

Dynamics,” Plant and Soil 366(1–2), 683–93, with permission 

of Springer.]

a b c
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 25

high levels of stochasticity in growth rates for roots 

from the same plant (Symonova et al. 2015). Modeling and experimentation indicate that internal root 

anatomy can play a role in optimizing root function. 

In particular, the formation of air spaces called 

“aerenchyma” appears to reduce carbon allocation 

to the root (Postma and Lynch 2011), while large 

cortical cell size may affect drought tolerance (Chimungu et al. 2014). Efforts have begun to integrate 

available phenotypic and molecular information 

into a platform called, “Plants In Silico” (Zhu et al. 

2015). However, improved and validated modeling 

resources are needed to analyze this compiled information to determine which physiological and genetic 

traits determine differences in function.

Creating Nondestructive Methods 

to Detect Root Biomass, Architecture, 

and Function

In addition to interacting with soil microbes, roots 

anchor plants and are a plant’s primary sites of 

nutrient and water acquisition. An improved understanding of root biology could help reduce fertilizer and irrigation use and improve carbon cycling 

models. As noted previously, soil opacity is the 

primary impediment to understanding root biology. 

Ideally, researchers want to be able to noninvasively 

determine the location of roots in soil and how they 

grow over time. Needed are new approaches for 

characterizing root system architecture in the field 

to target both shallow and deep roots. For shallow 

roots, “shovelomics” is the most common approach, 

involving cutting the root system close to the stem 

and characterizing the type and angle of visible 

roots (York and Lynch 2015). In addition, a recently 

developed image analysis platform can digitally 

characterize images of washed roots (Bucksch et al. 

2014; Das et al. 2015), but this approach also has a 

major drawback—its destructive nature that precludes measurement of the same root system over 

time. Moreover, analysis of deeper roots relies primarily on various types of excavation, including total 

roots, soil cores, trenches, access shafts, caves, and 

mines (Maeght et al. 2013). Though an alternative 

approach employs cameras buried in tubes called 

mini-rhizotrons, their burial also disturbs the soil, 

creating preferred paths for root growth, among 

other problems (Maeght et al. 2013). Clearly, 

improved capabilities are needed for nondestructive 

characterization of shallow and deep roots in situ.

Development of noninvasive technologies such as 

ground-penetrating radar (GPR) also could enable 

in situ root detection. Primarily, GPR is useful for 

tree root detection (Barton and Montagu 2004; 

Jayawickreme et al. 2014), with a resolution limit 

around 5 cm. Lowering this resolution limit to 

detect crop roots and increasing the penetration 

depth to enable deeper root detection would make 

this technology more broadly useful. However, 

challenges would remain, including the need to 

move the GPR equipment within the narrow 

confines of normal breeding plots and the potential 

cost of its frequent use during the growing season.

The use of X-rays offers another possible means of 

measuring root biomass in situ. An example is the 

combination of X-ray, MS, and isotopic techniques 

that has enabled the tracking of organic molecules 

in rhizosphere environments in the laboratory (see 

Fig. 3.6, p. 26). Although potentially feasible for use 

in the field, the use of X-rays is limited there because 

of requirements for a very powerful generator and 

placement of a detector on the opposite side of the 

roots. One solution could be the creation of simplified, 

controlled environmental systems, called Ecotrons 

(Lawton et al. 1993), for developing new imaging 

approaches and conducting in situ experiments.

A final approach being investigated for in situ root 

detection involves the use of sensors that report 

contact with or close proximity to roots. New, miniaturized sensors attached to a cage-like device buried 

in the soil could provide a low-cost and noninvasive 

alternative to the direct imaging of plants.

Another useful capability, in addition to determining root system architecture, would be the ability 

to discover the internal root anatomy. For example, 

research indicates that aerenchyma formation is 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

26 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Fig. 3.6. Characterization of Organic Molecules from Soil Using Multimodal Imaging Techniques. Combined imaging using high-resolution technologies with both isotopic and molecular sensitivity enables researchers to track several 

activities of organic molecules: (1) transfer among system components, (2) biological modification, (3) assimilation into 

cells, or (4) association with inorganic particles (Keiluweit et al. 2012). In these figures, sequential imaging with scanning 

transmission X-ray microscopy (STXM), scanning electron microscopy (SEM), and nanoscale secondary ion mass spectrometry (NanoSIMS) illustrate how isotopically enriched (13C) fungal cell material is transformed during soil decomposition and 

subsequently becomes preferentially sorbed to iron oxide mineral surfaces. (a, e) STXM and near-edge X-ray absorption fine 

structure carbon image and spectra. (c) SEM of iron oxide mineral. (b, d) NanoSIMS images showing nitrogen enrichment 

and iron distribution. [Images courtesy Jennifer Pett-Ridge. Reprinted from Kuweit, M., et al. 2012. “Nano-Scale Investigation 

of the Association of Microbial Nitrogen Residues with Iron (Hydr)oxides in a Forest Soil O-horizon,” Geochimica et Cosmochimica Acta 95, 213–26. © 2016, with permission from Elsevier.]

important under certain environmental conditions. 

To date, this type of analysis has been limited to 

destructive methods, but techniques enabling 

in situ anatomical analysis would be very valuable. 

Monitoring root functional attributes, such as 

nutrient and water dynamics, is another area of 

interest. Although researchers have examined these 

attributes in the laboratory with positron emission 

tomography imaging (PET) and NMR, in-field 

approaches capturing these physiological functions 

apparently do not yet exist. Finally, other needed 

capabilities involve nondestructive tracking of 

microbe-root interactions in soil. To date, researchers document these interactions through excavation 

and root washing. A transforming development 

in rhizosphere research would be a sensor-based 

system to detect microbes associated with roots in 

soil and perhaps even metabolites associated with 

specific microbial taxa.

Developing Transparent 

Model Soil System

Development of a transparent medium having the 

properties of soil potentially could make laboratory analysis of root growth more relevant to the 

field. Treating soil with the polymer Nafion renders it transparent with a refractive index close to 

that of water, and this treated soil has some of the 

1: Fungal hyphae

2 and 3: Soil minerals

4 and 5: Microbial tissue

a b

d

c

e

Carbon

SEM

fungal cell wall materials

mineral-associated 

organic matter

polysaccharide standard

amino sugar standard

protein standard

bacteria standard
Chapter 3 – Rhizosphere Community Interactions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 27

physical properties of native soils. Its primary use 

to date has been to observe root-microbe interactions (Downie et al. 2012).

Modeling Interactions Among Fauna and 

Microorganisms in the Rhizosphere

Carbon dynamics within soil ecosystems is dominated by a web of biotic transformations mediated 

by photosynthetic and heterotrophic microbes 

and metazoans. Recognition of these dynamics has 

enabled development of consumer-resource models 

of food webs to (1) predict the quantitative effects of 

species removal on the remaining taxa within intertidal food webs (Berlow et al. 2009) and (2) forecast 

seasonal changes in microbial and metazoan carbon 

dynamics in a complex aquatic ecosystem (Boit et al. 

2012). The cryptic nature of soil ecosystems has 

prevented the understanding of soil food webs from 

developing as rapidly as that of more easily observed 

aquatic systems (Brose and Scheu 2014). The 

discovery of more powerful “omics” and isotopic 

techniques is rapidly increasing the ability to more 

accurately model soil ecosystem carbon dynamics 

( Jakobsen and Rosendahl 1990; Digel et al. 2014). 

For example, research has recently identified unique 

structural aspects of complex soil food webs (Riede 

et al. 2010) and explored the effects of temperature 

and moisture on the dynamics of simple soil food 

chains—theoretically (Binzer et al. 2012) and experimentally (Lang et al. 2012; Lang, B., et al. 2014). 

The next challenges are to (1) integrate simple 

components of soil food webs into more realistic and 

predictive networks by resolving resource flow and 

incorporating key additional processes and (2) add 

the ecological and biogeochemical roles of understudied groups such as viruses and microfauna.

3.4 Optimizing Plant Health, 

Soil Fertility, and Carbon Storage

The condition of the root system of a plant directly 

relates to its aboveground health and productivity, 

and thus the amount of biofeedstock produced. 

Microbial communities drive fundamental processes in the global carbon cycle, regulating both 

atmospheric CO2 levels and soil carbon storage. 

These communities are particularly impactful in the 

rhizosphere, where they may assist the plant host 

with nutrient or water acquisition, provide pathogen defense, or mediate the transformation of root 

tissues into stabilized SOM. To better understand 

plant-microbe interactions, researchers need the 

ability to make quantitative, in situ, 3D measurements of dynamic molecular phenomena and to capture the interactions and exchanges between plants 

and their microbial partners at scales ranging from 

single cells to field plots. A related need is the ability 

to monitor root growth noninvasively over a growing 

season in a field setting, capturing root impacts on 

soil carbon and water stocks. Well-designed mutualistic plant-microbe interactions could improve plant 

nutrient and water acquisition and stress tolerance 

while simultaneously promoting carbon stabilization, soil fertility, and a diverse soil biota.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

28 U.S. Department of Energy • Office of Biological and Environmental Research September 2017
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 29

Chapter 4 – Biogeochemical Cycling

Environmental system function is intimately tied 

to biogeochemical cycling of the major elements, 

particularly their reduction-oxidation (redox) 

transformations. The inherent complexity of natural 

systems creates a network of pathways for electron 

transfer that closely couples biogeochemical cycles. 

Microorganisms inhabiting these environments, 

such as rhizospheres or leaf surfaces, are known 

to play important roles in global biogeochemical 

processes by catalyzing the chemical transformations and movement of carbon, nutrients, and 

contaminants (Anderson et al. 2003; Karl et al. 

2012). The populations within a community 

respond differently to environmental parameters 

that include biotic and abiotic variables within the 

system’s boundaries. The cumulative effect caused 

by these multiple populations, directly or indirectly 

connected, facilitates the net movement of energy and 

nutrients through the system. However, the understanding of 

all these interactions from molecular to microscale to macroscale, even for simplified communities, is limited. To understand, model, and predict microbial behavior and function, 

conditions for microbial communities must be delineated for 

spatial and temporal relationships among phylogenetic diversity, functional potential (e.g., carbon fixation, phosphorous 

and nitrogen cycling, and metal binding), and habitat.

4.1 Current Science and Technologies

Some research efforts funded by the U.S. Department of 

Energy’s Office of Biological and Environmental Research 

(BER) focus on microbial populations—how they communicate; evolve; share resources; interact with abiotic 

Chapter 4

Biogeochemical 

Cycling
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

30 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

constituents and other organisms in subsurface, rhizosphere, and aquatic environments; are affected by 

environmental changes; and, ultimately, define the 

Earth’s landscape. Research techniques are needed 

to enable and transform mechanistic understanding 

of structure-function relationships, from biological 

cells at the nanoscale to complex microbial communities at the macroscale, in three dimensions and 

across time, to improve capabilities for modeling 

and predicting microbial behavior and function.

BER-relevant ecosystems and environments include 

the subsurface and rhizosphere, surface waters, 

groundwater, rivers, wetlands, peatland and bogs, 

permafrosts, grasslands, forests, agricultural soils, and 

engineered systems (e.g., bioreactors). Within the 

ecosystems of these terrestrial and aquatic environments, microorganisms, plants, and soil and sediment 

constituents biogeochemically interact with and 

affect each other, exerting great control on the partitioning of elements and chemical compounds among 

the air, water, and land. In turn, such biogeochemical 

interactions have a major impact on critical environmental phenomena such as nutrient availability to 

living organisms, contaminant fate and transport, 

and water quality. Interactions from the molecular 

scale (Angstrom to nanometers) to the mesoscale 

(millimeters to a meter) also can drive emergent 

biogeochemical processes at larger scales. Moreover, 

with unknown metabolic interactions distributed 

across heterogeneous matrices that have complex 

diffusion characteristics, there is difficulty determining the impact of biotic and abiotic structures across 

temporal and spatial scales. For example, metabolic 

crosstalk in specific and nonspecific consortia, redox 

zonation resulting from combined biotic and abiotic 

interactions, hydrology and water quality linked to 

microbial activity, and carbon reduction and oxidation across oxic and anoxic boundaries are all affected 

by these complex biogeochemical interactions.

The geocycling of elements and other more complex molecules plays an important role in shaping 

the environment. Of the elements, iron and sulfur 

play particularly important roles because of their 

abundance and chemistry. Iron is highly abundant 

and often a dominant redox-active, biogeochemically cycled element in Earth’s outermost shell, the 

lithosphere. Iron-bearing clay minerals and iron 

oxides are common constituents of soils and sediments. Iron’s biogeochemistry in most aquatic and 

terrestrial environments is driven largely by microbial activity, particularly in iron-rich soils and sediments, where iron redox cycling between Fe(II) and 

Fe(III) by microorganisms is a significant component of carbon and nutrient cycling and energy flux 

(Canfield et al. 1993; Nealson and Saffarini 1994; 

Roden and Wetzel 1996; Lovley 2000; Thamdrup 

2000). Although sulfur at times is less abundant 

than iron in typical aquatic and terrestrial environments, it too is one of the main biogeochemically 

cycled elements within the lithosphere that is redox 

active. Sulfur’s biogeochemical transformations 

are more complex because of the variety of sulfur 

oxidation states (VI, V, IV, III, II, I, 0, –I, and –II). 

Sulfur species with intermediate valence states are 

key intermediates in sulfur redox cycling, which, for 

iron as well, is driven largely by microbial activity 

in most aquatic and terrestrial environments. The 

presence of sulfide (as either dissolved sulfide or 

ferrous sulfide minerals) can profoundly affect the 

fate, transport, and bioavailability of a variety of 

nutrients, as well as control the evolving nature of 

microbial community structure and function within 

soils and sediments.

4.2 Major Challenges in Learning How 

Microbes Control Biogeochemistry 

Cycling and Mobility

Understanding Coupled Biogeochemical 

Cycles in Redox-Dynamic Environments

The sulfide generated by microbial sulfate reduction 

and its subsequent reaction with reduced iron, produced by iron-reducing organisms, can lead to the 

formation of insoluble iron sulfides. Such pathways 

are important links coupling iron and sulfur biogeochemistry. Similarly, the redox processes coupling the biogeochemical cycles of iron and sulfur 
Chapter 4 – Biogeochemical Cycling

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 31

with carbon, nitrogen, oxygen, and manganese in 

redox-dynamic environments play a critical role in 

major ecosystem processes, which include carbon 

assimilation, mineralization of organic matter and 

its accompanying release of carbon dioxide (CO2), 

methane (CH4) formation and oxidation, uptake 

and release of nutrients (e.g., nitrogen and phosphorus), and contaminant availability and transformation. Thus, improved understanding of the coupled 

iron and sulfur redox dynamics and their subsequent 

effects on nutrient cycling is key to advancing understanding of how biogeochemical processes help 

to control the cycling and mobility of materials in 

aquatic and terrestrial systems.

A variety of competing biogeochemical processes 

determine the flux of terrestrial greenhouse gases 

(e.g., CO2 , CH4, and nitrogen) to the atmosphere. 

These processes are mediated by both microbes 

and plants. For example, the interaction between 

methanogens (methane producers), methanotrophs 

(methane consumers), and other anaerobic microorganisms (e.g., iron reducers, sulfate reducers, 

and denitrifiers) can create a complex, dynamic 

network of interacting redox processes that directly 

affects global biogeochemical cycling and CO2 and 

CH4 flux. Key genes in the microbial biochemical 

pathways that mediate CH4 flux (e.g., mcr, pmoA, 

and mmo; see box, this page) display substantial 

diversity that varies significantly among sites, even 

within a given region, suggesting a much greater 

degree of metabolic diversity than is known from 

studies of isolated strains. The illustration in Fig. 4.1, 

p. 32, illustrates some of the potentially coupled 

biogeochemical cycles that can affect emissions 

of greenhouse gases such as CO2 and CH4 from a 

redox-active environment such as wetland sediments. 

The coupling of these dynamic biogeochemical 

processes is highly dependent on the spatial arrangement of microbial metabolisms along linear redox 

gradients. The gradients run perpendicular to the 

sediment-water interfaces and radial redox gradients 

emanating from wetland plant arenchyma. For use 

in simulation and prediction of such processes, these 

biogeochemical interactions need to be illuminated 

and quantified across multiple spatial scales—from 

nanometer- to micrometer-scale cellular metabolism 

Key Methane Biochemical Pathway Genes

mcr – methyl coenzyme m reductase gene

pmoA – particulate methane monooxygenase gene

mmo – methane monooxygenase gene

Predicting Regional- and Global-Scale Processes

New insights for understanding and, ultimately, predicting the dynamic interplay among biotic and abiotic environmental components, from molecular to mesoscale and at multiscale spatial and temporal resolutions.

• Probes with a variety of spatial and temporal 

resolutions to study the relevant biogeochemical system.

• New and improved technologies to image 

components at resolutions of nanometers to 

millimeters and subseconds.

• Contrast agents and tags to probe molecular 

to mesoscale processes in biogeochemical 

systems.

• Advancement and standardization in 

imaging technologies to routinely image the 

soil pore network together with the life that 

inhabits it.

• Advanced approaches in the coupled development of X-ray contrast agents and X-ray 

microtomographic imaging to distinguish 

cells from pores, organic matter, and minerals within opaque environmental media.

Biogeochemical Cycling Needs
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

32 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

and mineralogy, to millimeter- and meter-scale community biogeochemical activities, to ecosystem-scale 

processes. This research requires experimentally 

quantified molecular to mesoscale (nanometer- to 

meter-length) measurements of soil carbon and 

nutrient flow, related biogeochemical processes, and 

multiomic characterization of microbial dynamics, 

along with integration of these data into predictive 

microbial metabolic and systems-ecology models.

A research grand challenge would be to image the 

distribution and measure the dynamics of elements, 

microbes, metabolisms, and metabolites within a 

small (e.g. 1 mm3) volume of soil and develop a 

mechanistic understanding and model of its biogeochemical function and control of environmental 

phenomena within that soil aggregate such as redox 

gradients and carbon mineralization. Projected 100- 

to 1,000-fold increases in X-ray brilliance over the 

next 5 years at diffraction-limited X-ray sources, such 

as the Advanced Photon Source, will make achieving these objectives possible for a 1 mm3 volume. 

However, imaging a volume beyond that, 1 cm3

 with 

10 nm3

 voxel resolution, for example, would remain 

an enormous challenge.

Imaging a Biogeochemical System 

with Multiple Technologies

Besides being opaque, environmental media such 

as sediments and soils are dynamic and spatially 

complex. Technology is needed to provide dynamic 

imaging of the biogeochemical processes and 

elemental transformations occurring within these 

complex environmental media. Moreover, because 

these processes often are catalyzed by living organisms to obtain energy or nutrients, technology also 

is needed to enable imaging of inter- and intracellular biological processes. A combined and holistic 

use of various dynamic imaging and characterization probes, coupled with omics and modeling 

Fig. 4.1. Coupled Biogeochemical Cycles. (a) Routes of 

carbon turnover in anoxic and 

oxic interface zones. Arrows 

with gas flux to the atmosphere 

represent potential emission 

routes. (b) Optical microscopy 

cross-section image of wetland 

plant aerenchyma. (c) Corresponding X-ray fluorescence 

image of nutrient elemental 

distributions within aerenchyma 

cross section in b. (d) Spatially 

resolved (25-micrometer resolution) iron X-ray absorption 

spectroscopy measurements of 

iron valence state in rhizoplane 

of wetland plant aerenchyma 

[red Fe(III)] and surrounding sediment [blue Fe(II)]. (e) Confocal 

microscopy image of cytoplasmic fluorescence-labeled 

rhizobacteria (Pseudomonas 

fluorescens SBW25) colonizing 

plant root cells. [Image courtesy 

Ken Kemner, Argonne National 

Laboratory.]

a b c

d

e
Chapter 4 – Biogeochemical Cycling

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 33

approaches, is necessary 

to bridge across spatial 

and temporal scales in 

biogeochemical systems 

to better understand their 

role in key environmental 

processes. The probes 

used comprise photons 

with wavelengths across 

the electromagnetic spectrum, including visible, 

infrared, ultraviolet, and 

soft and hard X-rays; 

charged particles such as 

electrons and ions; and 

neutrons. Examples of 

how some of these characterization probes can be 

used to image a biogeochemical system such as 

wetland sediments and 

plant roots are discussed 

in Chapter 5 (see Fig. 5.1, 

p. 38). In addition to 

approaches for imaging 

in the laboratory, where 

many microscopies may 

be more routinely available, also needed is the 

ability for continuous 

imaging of unmodified, 

untreated natural soils 

and sediments. Described 

below in this section 

are some of the improvements and developments 

needed to advance spatial and temporal imaging 

approaches to gain a better mechanistic understanding of biogeochemical processes from the 

molecular to mesoscale.

Development of Contrast Agents and Tags.

Whole-cell labels, protein tags, and gene expression 

or biosensor reporters have led to numerous insights 

in protein function, cell architecture, and cellular 

processes. Tags and contrast agents for optical, X-ray, 

charged-particle, and neutron imaging are needed to 

advance the use of these probes for optimal understanding of molecular to mesoscale processes in 

biogeochemical systems (see Fig. 4.2, this page).

Visible Light Microscopy. Intracellular transport of nutrients and metabolites in and across 

the cytoplasm—as well as intercellular transport 

across cell walls, microbial membranes, and among 

Fig. 4.2. New Contrast Agents for Biogeochemical Analyses. The development of new 

contrast agents for use in imaging probes should enable the study of biogeochemical 

systems at spatial scales appropriate to the systems interrogated and questions asked. 

Cadmium-selenium (CdSe) and zinc-sulfur (ZnS; core/shell) quantum dots can be useful contrast agents for electron–, X-ray–, and optics–based imaging approaches. (a) As 

demonstrated with transmission electron microscopy imaging, CdSe and ZnS quantum 

dots (identified by red arrows) conjugated to an amino acid enable uptake of quantum 

dots by Pseudomonas protogens. (b) The X-ray fluorescence from selenium atoms within the 

quantum dots can be used to image a similar bacterium with a submicrometer-sized hard 

X-ray microbeam. (c) The visible light resulting from the quantum confinement effects emitted by quantum dots enable bacterial imaging with optical wavelength microscopy. (d) A 

combination of X-ray transmission microtomography (left) and X-ray fluorescence microtomography (right) can be used to create tomographic reconstructions of pore structure (left) 

and the spatial distribution of quantum dot–containing bacteria within the pores (right) 

of a visibly opaque, millimeter-sized soil aggregate. [Image courtesy Ken Kemner, Argonne 

National Laboratory.]
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

34 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

cells—occurs in all three dimensions and can be 

characterized as a complicated multiscale combination of stochastic processes along with active 

transport. Accurate measurements of intracellular 

and intercellular transport and structure that are free 

from temporal and spatial artifacts require data with 

high three-dimensional (3D) spatial resolution and 

simultaneous volumetric acquisition. Estimating 

an object’s 3D structure is one of the most fundamental, yet challenging, tasks in optical microscopy, 

and making this task difficult is the lack of imaging 

sensors that can directly detect 3D information 

[e.g., instead, 2D charge-coupled device (CCD) 

array detectors are used].

Infrared Spectral Microscopy. Key to understanding biogeochemical cycling are in situ and real-time 

measurements of how microorganisms interact with 

terrestrial and aquatic environments through their 

wide range of metabolic capabilities. These measurements are important because the coupling of 

abiotic geochemical cycling of elements (e.g., iron, 

sulfur, carbon, nitrogen, oxygen, and manganese) 

with biotic microbial activities occurs primarily at 

the microbe-substrate interface, and their interfacial 

properties are quite variable spatiotemporally. At 

a spatial scale of several to hundreds of micrometers, the coupling could be dominated by clusters 

of microorganisms that differ in their metabolic 

activity and by spatial variations in reactive molecules of metal oxides and organic molecules. Several 

synchrotron Fourier transform infrared (sFTIR) 

spectromicroscopy tools are available for labelfree, real-time molecular measurements. sFTIR 

can provide detailed molecular information for the 

functional groups of biomolecules, metabolites, and 

geological organic and inorganic materials, as well 

as continuous measurements of in situ biogeochemical processes. Scientists also apply sFTIR to make 

real-time sequential measurements of microbial or 

biogeochemical processes at resolutions of micrometers (i.e., spatial) and minutes to hours (i.e., temporal) (Holman et al. 1999; Holman et al. 2002b; 

Holman et al. 2009a; Holman et al. 2009b). Further 

development of sFTIR would improve chemical 

sensitivity and spatial and temporal resolution, 

providing new insights into biogeochemistry at the 

microbe-environment interface.

Charged-Particle Microscopy. Imaging technologies using electrons and charged particles can provide an opportunity for increased spatial resolution 

and, hence, visualization of subcellular components 

within microorganisms and plant cells. In addition 

to 2D scanning and transmission electron microscopies, electron-based imaging has been revolutionized by electron tomography. Although these 

approaches often require chemical fixation or quick 

freezing of biogeochemical samples, thus hindering 

direct study of biogeochemical process kinetics, they 

do enable 3D imaging of intercellular and intracellular structures with nanometer-scale resolution. In 

addition, judicious sample preparation approaches, 

ensuring that a sample and its reactions are suspended at the appropriate time, can enable reconstruction of dynamic biogeochemical processes after 

microscopy data collection. For holistic imaging and 

better understanding of complex biological systems, 

advancement and standardization are needed in 

electron-based imaging technologies, including their 

coupling with other imaging approaches, and those 

based on optics, X-rays, and charged particles.

X-Ray Microscopy. Further advancements are 

needed for imaging techniques that enable 3D 

imaging of cells as well as metabolic and biogeochemical processes within opaque environmental 

media. Soil pore structure affects water and oxygen diffusion, introduction of microbes and their 

reactants, and root structure (Kemner et al. 1998; 

Bailey et al. 2013). While laboratory-based X-ray 

tomography can image the pore structure of soil 

aggregates, highly coherent X-ray sources provided by synchrotrons enable imaging of root cell 

structure with opaque soils (see Fig. 4.3, p. 35). 

In addition, microbial metabolic activities are the 

primary drivers of biogeochemical processes controlling the terrestrial carbon cycle, plant nutrient 

availability, contaminant remediation, and other 

ecosystem services. However, understanding how 

microbes and microbial metabolism are distributed 
Chapter 4 – Biogeochemical Cycling

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 35

throughout biogeochemical systems such as soil 

aggregates is limited because no standard techniques 

are available to routinely image the soil pore network 

together with the life that inhabits it. Light- or mass 

spectrometry–based imaging approaches [e.g., fluorescence in situ hybridization (FISH) and nanoscale 

secondary ion mass spectrometry (nanoSIMS)] can 

detect the location of organisms in relation to their 

biogeochemical environment, while electron-based 

imaging approaches can determine with high spatial 

resolution the location of heavy metal–tagged 

cells. However, these techniques are unable to go 

beyond the surface of an opaque sample without 

sample sectioning. X-ray tomographic approaches 

(Flannery et al. 1987) are unmatched for producing nondestructive 3D images of rocks without 

any prior preparation. X-ray microtomography can 

provide highly detailed 3D renderings of soil mineral and pore structure (Kemner et al. 1998; Young 

and Crawford 2004; Nunan et al. 2006; Bailey et al 

2013), but these approaches cannot distinguish biological cells from other electron-light materials such 

as air or water. Advances in the coupled development 

Fig. 4.3. Soil Pore Structure and 

Root Cell Structure Within a Soil 

Aggregate. Reconstructed transverse and vertical planes from a 

transmission X-ray microtomography 

measurement of a soil aggregate 

~1 millimeter in size. Highly coherent 

X-rays provided by the Advanced 

Photon Source at Argonne National 

Laboratory enable imaging of pores, 

sand grains, iron-manganese nodules, and cell walls from a root within 

the soil aggregate. [Image courtesy 

Ken Kemner, Argonne National 

Laboratory.]

of X-ray contrast agents and X-ray microtomographic 

imaging approaches are needed to distinguish cells 

from pores, organic matter, and minerals within 

opaque environmental media. Planned upgrades to 

synchrotron and free-electron laser X-ray sources 

will provide many orders of magnitude increases in 

X-ray brilliance. These facilities are expected to offer 

new modes of X-ray–based imaging and increased 

measurement throughput with existing techniques.

4.3 Improving Model Predictions 

of Biological and Environmental 

Systems

Spatial and temporal imaging of biogeochemical system dynamics from the molecular to mesoscale will 

enable the development of more sophisticated and 

precise models to predict (1) ecosystem, regional, 

and global greenhouse gas production; (2) nutrient and contaminant movement and availability; 

(3) sustainable biomass production; and (4) downgradient water quality. These improved models 

also will offer better predictions of how microbial 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

36 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

and environmental drivers will respond to future 

environmental change (i.e., changing atmospheric 

CO2 concentrations and aquatic pH, changing 

temperature, water inundation and dry spells related 

to episodic climatic events, and different types of 

minerals and carbon in soils and sediments).
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 37

Chapter 5 – Metabolic Pathways in Plants, Microbes, and Fungi

Plant and microbial metabolic pathways have 

long been harnessed for making bioproducts. 

Scientists have traditionally relied on breeding 

methods in plants or random mutation methods 

in microbes to select for the genes that improve 

these processes. This has led to the concept of 

biological production of fuels and other compounds, which is central to the mission of the 

Biological Systems Science Division of the Office 

of Biological and Environmental Research. It is 

well established that plant and microbial communities exchange metabolites in an “economy” 

that ultimately determines the rate of nutrient and 

water extraction from soil and cycling of soil carbon 

(Anderson et al. 2003; Johnson and Nielsen 2012; 

Weston et al. 2012; Song et al. 2015). 

A deeper understanding of the mechanisms that these communal organisms use to interact in the environment, as well 

as the metabolic pathways and specific molecules involved in 

this exchange, will enable the modification of such pathways 

to improve nutrient-use efficiency and soil-carbon performance (see Fig. 5.1, p. 38). Ultimately, this knowledge is 

essential for arriving at optimal plants, microbes and pathways 

for the biological production of useful molecules that would 

otherwise be derived from fossil fuels.

Metabolic Pathways 

in Plants, Microbes, 

and Fungi

Chapter 5
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

38 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

5.1 Current Science and 

Technologies

Predicting Metabolic Networks from 

Genomes and Proteomes

Metabolic pathways comprise enzymes encoded by 

genes, substrates endogenously produced or exog-

enously supplied, and products generated through 

a catalyzed reaction. The metabolome is the full 

complement of metabolites present in an organism 

along with a complement of proteins (the proteome) 

that are available to perform chemical reactions. 

Understanding how the proteome influences the 

metabolome requires knowledge of (1) the genes 

present in the genome, where the proteins are 

encoded, and (2) how the sequences of proteins 

relate to their enzymatic function. Model organism 

studies have determined the enzymatic function of a 

large number of proteins (Bassel et al. 2012). Using 

sequence homology, researchers can predict which 

genes in other species might encode enzymes with 

similar substrate specificities and products, but the 

extent to which sequence-based methods result in 

false-positive or -negative predictions is not clear. 

Large numbers of microbial and eukaryotic genomes 

are being sequenced, but little experimental data 

exist for the protein families they express. Thus, 

there is a pressing need for functional characteriza-

tion of specific DOE mission–related enzymes.

All the enzymes that perform known metabolic 

reactions in an organism can be predicted through 

sequence homology to characterized enzymes 

(Mueller et al. 2003; Chae et al. 2014). Many of the 

enzymes involved in central metabolism have been 

well characterized and provide a useful resource 

for comparing these core processes across species. 

Specialized metabolism, on the other hand, is 

necessary for an organism to generate the chemicals 

Fig. 5.1. Defining Metabolic Interactions at the Plant-Soil-MicrobeInterface. Growth and Luminescence Observatory for Roots (GLO-Roots) 

image of soil-grown root system. [Image courtesy Rubén Rellán-Álvarez 

and José R. Dinneny, Carnegie Institute for Science.]
Chapter 5 – Metabolic Pathways in Plants, Microbes, and Fungi

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 39

that perform often species-specific functions, conferring many of the unique adaptive traits needed 

for the survival within its specific environmental 

niche (O’Connor 2015). The plethora of chemicals 

naturally produced by plants and fungi affect biotic 

interactions and, for example, form the basis of pharmacological activities used in traditional and modern medicine (Anarat-Cappillino and Sattely 2014). 

Recent work has shown that the number of genes 

predicted to encode specialized metabolic enzymes 

appears to have expanded to a greater extent during 

plant evolution, compared to genes involved in other 

metabolic pathways. This difference suggests that 

the specialized genes were important for the success 

of plants in land colonization (Chae et al. 2014). 

The co-localization of genes involved in the same 

metabolic pathway along chromosomes appears to 

be a unique property of genes linked to specialized 

metabolism. This finding suggests that co-regulation 

may be important for ensuring that any specialized 

metabolic compounds that are potentially reactive 

or toxic remain relegated to specific tissues or environments during synthesis.

Detecting Metabolites and 

Measuring Metabolic Flux

Detecting the activity of an enzyme or flux through 

a metabolic pathway requires the ability to quantitatively detect the substrate, product, or both. Metabolite detection can be “direct” or “indirect.” Direct 

detection methods usually rely on knowledge of the 

compound’s exact mass, which can be determined 

precisely by mass spectrometry (MS). Modern 

instruments can discriminate thousands of different 

chemicals based on separation through chromatography, ionization, and mass determination (Kusano 

et al. 2015). Indirect detection of known metabolites can be facilitated by using chemicals that 

react specifically with the compound of interest. 

Protein-based sensors, for example, may involve 

an antibody specific to the metabolite of interest, 

and immunohistochemistry can be used for visualization. More recently, a promising development 

concerns proteins whose fluorescent properties 

change when binding to specific chemicals, potentially expanding the spatial and temporal scales at 

which metabolic pathways can be interrogated (see 

Developing Resources and Higher-Resolution 

Tools for Localization and Measurement

Capabilities that detect changes in the dynamic systems of 

plants, microbes, and fungi for finding important functional 

differences that affect physiology and growth, such as a 

metabolite flux highly tuned to suit particular environmental 

conditions.

• Tools to measure the dynamic nature of metabolite 

fluxes within and among organisms, combined with 

new higher-resolution approaches to determine 

spatiotemporal localization and the mechanisms 

responsible for metabolite synthesis, transport, and 

degradation.

• Tools to detect internal and external temporal 

changes in cellular environments, along with cell 

type–specific differences in metabolites.

Metabolic Pathways in Plants, Microbes, and Fungi Needs

Using Advanced Engineering to 

Study Metabolomes and Design 

Organisms

Detection methods and analysis for 

identifying metabolites that vary in 

biologically interesting and DOE mission–

relevant ways.

• Methods to determine reference 

spectra for known chemicals, and 

algorithms that more accurately 

deconvolve the spectra.

• Methods compatible with 

in-field measurements to detect 

metabolites.

• Efforts to establish fabricated 

ecosystems.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

40 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

next section, “Quantifying Metabolites with Direct 

and Indirect In Situ Methods,” this page; Jones 

et al. 2013). Importantly, each of these direct and 

indirect methods requires precise knowledge of the 

chemical composition of the particular compound 

under study. Untargeted detection of the metabolome also can lead to a chemical fingerprint–based 

analysis in which quantitative differences in the 

abundance of chemicals with specific masses are 

used to compare an organism’s overall metabolic 

state (da Silva et al. 2015). Such analyses can 

help to identify metabolites that vary in biologically interesting ways, thus justifying time- and 

resource-consuming approaches that enable exact 

determination of the chemical structure.

Quantifying Metabolites with 

Direct and Indirect In Situ Methods

Tissue-specific methods for characterizing plant 

transcriptomes and proteomes have revealed that 

most biological pathways are highly regulated at the 

spatiotemporal level (Mueller et al. 2003; Fukushima 

et al. 2009). The relative flux through a metabolic 

pathway can be estimated by integrating these omics 

datasets with knowledge of metabolic networks.

Direct Detection. However, direct detection of 

metabolites using cell-specific methods also is necessary because substrate availability and regulation of 

enzymes at the post-translational level influence flux 

through a pathway. Current methods to determine 

a metabolite’s in situ abundance use both direct and 

indirect detection methods. Direct detection includes 

techniques such as fluorescence-activated cell sorting 

(FACS), which isolates a marked population of cells, 

or laser capture microdissection (LCM), which 

isolates material from sectioned tissue (Rogers et al. 

2012; Moussaieff et al. 2013; Dong et al. 2016). More 

recently, direct ionization and detection of metabolites from thin sections of tissue have enabled spatial 

maps of dozens of metabolites from various plant tissues (Dong et al. 2016). Coupling such methods with 

metabolic labeling using radioisotopes has enabled 

direct detection of flux through particular metabolic 

pathways in individual cells (Kopf et al. 2016).

Indirect Detection. These methods include genetically encoded fluorescent protein–based sensors that 

enable the use of light-based microscopy to study 

in situ spatiotemporal dynamics of metabolite flux 

(Okumoto et al. 2012). Sensors based on Förster 

resonance energy transfer (FRET), another indirect 

detection method, encode proteins that change their 

conformation when bound to the metabolite of 

interest, inducing a change in the efficiency of energy 

transfer between fluorophores. Other indirect 

detectors are nonratiometric sensors, which simplify 

imaging requirements, as well as fluorescent sensors 

that can detect the actual activity of transporters 

moving small metabolites and flux across the plasma 

membrane (De Michele et al. 2013). The major limitation in using fluorescent sensors is the extensive 

investment required to design and test such proteins.

Re-Engineering Metabolic Pathways

Engineering metabolic pathways in microbes and 

plants has seen some success in reconstructing pathways necessary for drug synthesis (Lau et al. 2014; 

Lau and Sattely 2015). Introducing the morphine 

pathway into yeast, for example, required not only 

the expression of plant enzymes involved in the 

biosynthesis of this compound, but also ensured 

the correct localization of proteins and transport 

of intermediate substrates among cellular compartments (Thodey et al. 2014; Galanie et al. 2015). 

Thus, understanding how cells subcompartmentalize 

biosynthetic reactions between cells and their subcompartments is needed to reconstruct or redesign 

such synthetic pathways. The ability to localize 

specific enzymatic steps into these discrete organism 

domains may prove useful in avoiding side reactions 

that reduce biosynthetic efficiency or lead to toxic 

byproducts. The methods developed for transferring 

a plant metabolic pathway into yeast can be translated to plant-based bioproduct production.

5.2 Major Challenges in 

Detecting Metabolic Pathways

Metabolic networks often are illustrated as static 

wiring diagrams, but dynamic traffic maps may be a 
Chapter 5 – Metabolic Pathways in Plants, Microbes, and Fungi

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 41

more accurate representation. Current knowledge 

is limited to a small number of reactions revealed by 

assays lacking sufficient spatial or temporal resolution to understand the regulatory mechanisms that 

determine flux through these pathways. The undiscovered metabolome and associated enzymes and 

transporters that regulate the metabolites prevent 

an accurate understanding of how most high-value 

industrial and pharmacological bioproducts are 

made (Lau et al. 2014).

Uncharacterized metabolites can be considered 

biology’s “dark matter.” MS has enabled the direct 

detection of hundreds of compounds for which only 

the mass is known. Determining the exact chemical 

structure of these compounds remains an arduous 

task. Estimates are that an untargeted metabolomics 

experiment can be annotated for only about 1.8% of 

spectra (da Silva et al. 2015). Interactions between 

organisms occur in large part through the exchange 

of metabolites that determine whether such 

exchanges are symbiotic, parasitic, or pathogenic 

(Baran et al. 2015). The interface between organisms offers a rich domain on which to focus efforts 

aimed at understanding the significant role that metabolic pathways play in controlling ecosystem-level 

processes that affect agricultural productivity and 

sustainability. Engineering metabolic pathways 

likely will involve a combination of manipulating 

the activity and expressing endogenously encoded 

genes, as well as introducing genes from other species. Important for facilitating pathway engineering 

will be advancing the understanding of how metabolites themselves affect enzymatic activity and how 

the flux through a metabolic pathway is regulated in 

space and time (Hackett et al. 2016).

Developing Technologies 

for Studying Metabolite Fluxes

Plants, microbes, and fungi are dynamic systems in 

which the flux of a metabolite may be highly tuned to 

suit particular environmental conditions. Detected 

changes will lead to finding important functional 

differences that affect physiology and growth.

Discovery of Key Metabolomes for Organisms 

Relevant to Bioenergy. Research resources and 

consortia are needed for a coordinated effort to 

catalogue the metabolites of organisms important 

for bioenergy development. Included are biosynthetic pathways associated with biomass production, 

nutrient cycling, and carbon fixation, but equally 

important are key metabolites in plant-microbe 

interactions that are poorly understood. Characterizing plant-microbe properties requires technology 

development in several areas, including computational methods, and measurement methods at both 

the cellular and in situ field levels. Computational 

methods being developed will enable the determination of a chemical fingerprint for uncharacterized 

spectra using tandem MS, in which metabolites are 

fragmented to determine the mass of the fragments. 

Using available databases of compounds and their 

known or predicted fragmentation patterns, novel 

small molecules can be categorized based on their 

chemical constituents (Duhrkop et al. 2015). Determining the exact chemical structure can involve 

years of focused effort, but such computational 

methods may identify simpler mass features that can 

be elucidated, especially those seemingly contained 

in a large number of unknown metabolites.

Metabolite Measurement at the Cellular Level 

(Sensors and Direct Detection). Characterizing 

a system’s metabolite flux is limited by constraints 

in the spatial and temporal resolution of detection. 

Several methods enable direct detection of metabolites, but access to the needed equipment is limiting. 

Nuclear magnetic resonance (NMR) spectroscopy 

has been used on plant tissue to characterize the flux 

of simple metabolites such as sugar and amino acids 

across plant stems (Kockenberger et al. 2004; Dong 

et al. 2016). Greater use of this or similar methods 

is needed to characterize a broader range of complex molecules in plants and microbes. Limiting the 

use of such methods are the spatial resolution and 

significant constraints on the size of objects that can 

be imaged. Raman and infrared spectroscopy hold 

promise for enabling in situ determination of the 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

42 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

chemical spectra of cells (Heredia-Guerrero et al. 

2014; Dong et al. 2016). While Raman imaging 

methods use shifts in the wavelength of light scattered from objects, infrared imaging methods measure energy exchange between the infrared photons 

and vibrational motions of atoms in the functional 

groups of molecules. Nevertheless, both methods 

measure the nature of the chemical bonds present. 

Deconvoluting emission spectra often is challenging 

because most biological samples comprise hundreds 

to thousands of molecules. Determining the spectra of known chemicals and developing algorithms 

that more accurately deconvolve such data will be 

needed to make these imaging modalities accessible for in situ metabolite measurements. Acquiring 

additional downstream, spatially resolved MS 

measurements can further elucidate the chemical 

constituents.

FRET sensors (see Fig. 5.2, this page) can be 

created using a tool kit of DNA parts that enable 

assembly of dozens of different sensors. These 

designs can be rapidly evaluated using expression 

systems such as yeast or Escherichia coli. FACS 

and high-throughput sequencing enable rapid 

identification of constructs with sufficient expression levels and exhibit a strong change in FRET 

efficiency when binding to the chemical of interest 

( Jones et al. 2014). Currently, most FRET sensors 

are designed to detect a specific chemical. Also 

possible, however, are libraries of potential FRET 

sensors that use enzyme sequences or receptor 

domains. These sensor libraries could be screened 

for their responsiveness to a chemical library, 

enabling further optimization of experimentally 

useful sensors with appropriate binding affinities 

for in vivo measurements.

Metabolite Mechanisms of Synthesis and Transport. The identification of novel chemicals and 

enhanced ability to detect their spatiotemporal 

localization will be important for determining the 

mechanisms responsible for their synthesis, transport, degradation, and perception. Methods to rapidly screen mutant library collections of microbes 

and, more recently, algae and plants will facilitate 

the identification of genetic components for these 

pathways (Zhang et al. 2014). Use of chemical 

genetic screens has been successful in identifying 

signal transduction components (Park et al. 2009). 

Discovery of these molecular mechanisms will 

enable the transfer or reconstitution of biosynthetic 

pathways and greater control over metabolic pathways of interest to BER.

Field Deployment of Sensor Technologies. The 

physiological status of plants and microorganisms 

is highly context dependent. The influence of 

climate and the chemical environment on biological 

systems can be underestimated, especially when 

experiments are conducted under highly controlled 

conditions. Experimental systems must be designed 

based on actual environmental conditions that an 

organism might experience and that can vary across 

similar parameters (Rellán-Álvarez et al. 2016). 

Furthermore, organisms rarely grow in isolation 

from other organisms; thus, interactions among 

Fig. 5.2. Growth of Plant Seedlings in a Perfusion 

Chamber (RootChip) Environment, Allowing Highly 

Controlled Changes in the Root’s Chemical Environment. 

The graphic illustration shows a fluorescence biosensor for 

glucose that is encoded by the plant and imaged. Changes 

in the biosensor’s fluorescent property indicate when glucose enters the root cells. [Reprinted from Jones, A. M., et al. 

2013. “In Vivo Biochemistry: Applications for Small Molecule 

Biosensors in Plant Biology,” Current Opinion in Plant Biology

16(3), 389–95. © 2013, with permission from Elsevier.]
Chapter 5 – Metabolic Pathways in Plants, Microbes, and Fungi

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 43

plants, microbes, fungi, and animals also will exist 

in the context of a changing environment, and all 

these influences will affect the metabolites present 

in cells. Two complementary approaches are needed 

to ensure that observations of biological systems 

are physiologically relevant: (1) development of 

metabolite-detection methods that are compatible 

with in-field measurements and (2) establishment 

of fabricated ecosystems that enable controlled 

manipulation of complex synthetic communities 

and environments that simulate aspects of natural 

environments.

5.3 Predictively Understanding 

the Metabolome Across Scales, 

from Organisms to Ecosystems

Predictive Metabolome Understanding to Enable 

Synthetic Pathway Construction and Optimization. Understanding metabolomes and applying 

improved metabolome discovery tools to a diverse 

collection of organisms will aid in the development 

of a model for predicting how an organism’s total 

chemical constituency is determined. Also making 

this model development possible will be a mechanistic understanding of the proteins that control 

metabolite biosynthesis, localization, degradation, and activity. The determination of genome 

sequence, along with transcriptomic and proteomic 

datasets, will enable predictions of how a cell’s 

chemical environment may change with its environment or vary between genotypes. Ultimately, there 

is the possibility of predicting organisms within a 

system capable of synthesizing chemicals that are 

never actually detected. Cataloguing the genome 

sequences of diverse organisms within a system may 

then enable a predictive catalogue of the chemical 

diversity of life that preserves knowledge of biosynthetic pathways present in extinct or rare organisms.

Metabolite Economy: Whole-Ecosystem 

Accounting of Carbon and Nutrient Cycling.

Matter cannot be created or destroyed, and the 

same is true for metabolites in an ecosystem. A full 

accounting of the carbon and nutrients entering an 

ecosystem is necessary to understand how terrestrial 

life influences the global carbon cycle and climate. 

Development of detection systems for in situ measurements and the establishment of realistic experimental systems will enable relevant measurements 

of metabolic exchanges at the interface between 

organisms. The identification of dependencies essential for maintaining diversity in ecosystems will also 

be enabled. Such metabolic exchange models may 

explain how pathogens or environmental contaminants cause changes in ecosystem diversity and may 

highlight ways to engineer these systems through 

targeted manipulation via chemicals or the introduction of alternative community members.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

44 U.S. Department of Energy • Office of Biological and Environmental Research September 2017
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 45

Chapter 6 – Biosystems Design

Biosystems

Design

Chapter 6

Advances in high-throughput biology and biotechnology have led to an array of biological insights 

in diverse organisms, the environment, medicine, 

agriculture, and energy supply. The enormous breadth of 

genomic diversity that enables organisms to adapt to 

diverse environments also endows them with rich 

biosynthetic potential (Venter et al. 2004; Tringe 

et al. 2005). Harnessing this potential (e.g., 

by generating biologically derived chemicals, 

fuels, and materials to ensure environmental 

sustainability) could enable solutions to global 

challenges (Way et al. 2014). Achieving such 

goals, however, requires a thorough understanding of biological systems, as well as their safe and 

programmable control. In this regard, the ability 

to (1) modify genetic and biochemical molecules in 

cells, (2) apply advanced computation to design and 

analyze engineered biosystems, and (3) isolate engineered cells and communities with desired function remain 

defining challenges.

Fueled by concurrent advances in systems biology and 

the emerging field of synthetic biology, biosystems design 

provides a valuable approach for probing, studying, and 

introducing new functions into biological systems. Synthetic biology combines principles from biology, chemistry, 

physics, mathematics, and engineering to assemble the 

biological tools necessary to redesign biological systems. 

More specifically, synthetic biology employs engineering 

principles to reduce genetic information into DNA “parts,” 

so that those parts can be understood in isolation and 

reassembled into new biological parts, devices, and whole 

systems to build desired or expanded functions in living 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

46 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

cells. In many respects, synthetic organic chemistry 

serves as a model for the nascent field of synthetic 

biology. As a discipline, synthetic organic chemistry shows that organic synthesis could be made 

into a rational science. This is a new paradigm for 

biology, in which a desired biological function is 

conceived, designed, and constructed to work as 

predicted, reliably and robustly using well-defined 

parts (see Fig. 6.1, this page). The field has rapidly advanced over the past 15 years with the use 

of (1) modular and well-characterized biological 

parts; (2) computer-aided design (CAD) software 

customized for biological systems; (3) metabolism 

re-engineering for production of high-value compounds (e.g., butanol and artemisinin); (4) largescale gene synthesis; and (5) designer genomes 

containing refactored pathways and minimal or 

recoded genomes. Given the profusion of these 

advances, synthetic biology is poised to make fundamental breakthroughs in predictive understanding of complex biological systems and actualize an 

array of impactful applications that address global 

challenges in food and energy supply, environmental health, and medicine.

Fig. 6.1. Synthetic Biological 

Devices Based on Gene Regulatory Networks. (Top) The “toggle 

switch” is a co-repressive gene 

network in which two repressors 

turn each other off, permitting 

bistability of gene expression and 

memory. (Bottom) The “repressilator” comprises a network of three 

repressors that sequentially turn 

each other off, leading to oscillations in gene expression over 

time. [Reprinted from Way, J. C., 

et al. 2014. “Integrating Biological 

Redesign: Where Synthetic Biology 

Came from and Where It Needs to 

Go,” Cell 157(1), 151–61. © 2014, 

with permission from Elsevier.]

6.1 Current Science 

and Technologies

Applying Genome Technologies: 

DNA Sequencing, Gene Synthesis, 

and Genome Engineering

Next-generation DNA sequencing has revealed 

the complete genome sequences of numerous 

organisms, establishing a fundamental and growing 

understanding of genetic variation and phenotypic 

diversity. DNA sequencing technologies (that 

“read” genomes) have undergone revolutionary 

advances during the past decade, resulting in a 

precipitous drop in sequencing costs and coinciding with dramatic increases in throughput. Among 

many active genomics research areas, sequencing 

has advanced, leading to unprecedented insights 

into genetic variants associated with an observed 

phenotype, metagenomics, genome structure, and 

genome evolution. DNA sequencing and genome 

engineering are synergistic technologies that establish a platform for pursuing many goals in biological 

design. To date, reading capacity in the biological 

sciences has far outpaced the capability for “writing 

genomes,” but recent developments underscore 
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 47

dramatic progress in this area (see Fig. 6.2, p. 48; 

Boeke et al. 2016).

Technologies for genome engineering (i.e., writing 

genomes) have lagged behind reading genomes, 

so the quest to introduce precise genome modifications at multiple genetic loci remains a defining 

challenge. The development of recombinant DNA 

(rDNA) technologies in the 1970s laid the foundation for current genome engineering technologies. 

Recombinant DNA insertions typically involve 

the transformation of plasmids—the insertion of 

circular rDNA molecules capable of replicating 

alongside the host’s genome or direct insertion 

into the host’s genome using homologous recombination—and typically are limited to single or few 

gene modifications.

The confluence of three complementary technologies has fueled advances in genome engineering 

(see Fig. 6.3, p. 49). First, de novo DNA synthesis technologies enable tailored construction of 

user-defined, double–stranded DNA segments. 

Similar to advances in DNA sequencing, DNA synthesis has undergone logarithmic improvements in 

scale, cost, and throughput. For example, large-scale 

DNA microchip–based synthesis methods permit 

high-density synthesis of about 105

 customized 

single-stranded DNA (oligonucleotides). Gene synthesis (using overlapping oligonucleotides), combined with improvements in DNA error-correction 

methods, has enabled high-quality and cheap 

construction of designer synthetic genes. Second, 

and complementary to DNA synthesis, large-scale 

DNA assembly in vivo and in vitro methods permit 

Designing New Tools for Biosystems 

Study and Safety Measures

Capabilities for modifying genetic and biochemical 

molecules in cells, applying advanced computation 

to the design and analysis of engineered biosystems 

and isolating the cells and communities having 

desired functions; and for addressing the primary 

safety concerns involving up to billions of genotypic 

variants of engineered biosystems.

• New tools to apply biosystems design 

methods to a broader range of organisms, 

including unusual microbes, environmental 

isolates, algae, and plants, as well as microbial communities and plant-microbe 

interfaces.

• Improved methods to explore extensive 

phenotype landscapes and link genotype 

to phenotype.

• Tools to study intractable, eukaryotic, and 

multicellular organisms.

• Methodologies to focus on biocontainment 

and genetic isolation.

Using Genomics Technologies, 

Computational Models, and 

Omics Studies

Technologies and more efficient tools for genome 

and epigenetic engineering adaptable to diverse 

organisms for conducting precise, error-free, and 

high-throughput genome manipulation, enabling 

comprehensive, pertinent biosystems design. 

• Tools to combine with improvements in 

steady-state and time-variant computational 

modeling and omics studies, including fluxomics and metabolomics.

• Methods to rapidly assay function and fitness, together with technologies to manage 

the containment of engineered biosystems and isolate products of engineered 

pathways.

• Further development of organisms that have 

more orthogonal and alternative genetic 

codes to facilitate their implementation 

in model systems, diverse species, or even 

communities.

Biosystems Design Needs
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

48 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

the precise assembly of individual synthetic genes 

into higher-order combinations at the network and 

whole-genome scales. Advanced recombination 

and transplantation techniques are being developed 

to improve the efficiency of introducing synthesized genes, pathways, and genomes into target 

organisms. Finally, genome editing permits targeted 

changes directly in the chromosomes of living cells. 

Many genome-editing technologies generate DNA 

double-strand breaks at targeted loci to introduce 

genomic modifications.

There are four main classes of sequence-specific 

nucleases (SSNs) used to introduce genome 

modifications (reviewed in Voytas and Gao 2014): 

(1) meganucleases, (2) zinc finger nucleases 

(ZFNs), (3) transcription activator-like effector 

nucleases (TALENs), and (4) a nuclease system 

consisting of clustered regularly interspaced palindromic repeats (CRISPRs) and an RNA-guided 

protein called Cas9 (CRISPR-associated protein-9). 

Meganucleases were discovered first, followed by 

ZFNs and TALENs. ZFNs and TALENs recognize 

specific DNA sequences through protein-DNA 

interactions and use the FokI nuclease domain to 

introduce double-strand breaks at genomic loci. 

Construction of functional ZFNs and TALENs 

with desired DNA specificity, however, remains 

laborious, costly, and primarily limited to modifications at a single genetic locus. CRISPR-Cas9 has 

been broadly adopted for multiplexed targeting 

of genomic modifications because the CRISPR 

nuclease Cas9 uses a short-guide RNA to recognize 

the target DNA via Watson-Crick base pairing and 

has been shown to function in many organisms 

( Jinek et al. 2012; Cong et al. 2013; Jinek et al. 

2013; Mali et al. 2013). The CRISPR-Cas9 nuclease 

system is an innate bacterial defense mechanism 

against viruses and plasmids that uses RNA-guided 

nucleases to cut foreign DNA sequences, thereby 

disabling them. Scientists have re-engineered the 

CRISPR-Cas9 system so that a single RNA (the 

guide RNA) can create the Cas9-mediated cut of 

a target sequence in a genome. This system's ease 

of design, specificity, and simplicity have made it a 

popular technique for generating future biotechnological products, but certain features (e.g., the creation of double-strand DNA breaks) are cytotoxic 

and limiting. Other genome-editing approaches are 

still emerging. For example, multiplex automated 

genome engineering (MAGE) permits multisite 

and combinatorial genome modifications through 

hybridization of synthetic oligonucleotides during 

the process of DNA replication (Wang et al. 2009). 

Genome-engineering technologies have enabled 

organism engineering at the gene, network, and 

genome levels, resulting in the de novo synthesis 

of refactored biosynthetic pathways (Smanski 

et al. 2014), whole-genome synthesis of bacterial 

genomes (Gibson et al. 2010; Hutchison et al. 

2016), and whole-genome recoding (see Fig. 6.4, 

p. 50; Isaacs et al. 2011; Lajoie et al. 2013; Ostrov 

et al. 2016).

Biological Applications

Scientists have documented several recent success 

stories of synthetic biology applications to biotechnological products and processes. A prominent 

Fig. 6.2. Temporal Advances in DNA Sequencing and 

Synthesis Technologies. Costs ($/base pair) of DNA 

sequencing (green), single-stranded DNA (ssDNA) synthesis (red), and double-stranded DNA (dsDNA) synthesis 

(blue) are plotted for the past 35 years. [From Boeke, J. D., 

et al. 2016. “The Genome Project-Write,” Science 353(6295), 

126–27. Reprinted with permission from AAAS.]
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 49

(c) Multiplexed Automated Genome Engineering

ssDNA pool 

of mutagenic 

oligonucleotides

Whole genome

Recoding genome: TAG TAA

 321 target loci

 1 oligonucleotide per target

Gene network Gene

Target 1 Target 2

Coding sequence

Nascent polypeptide

Folded protein

Ligand

Mutant 1 ATG STOP

Output

Mutant 2

Mutant n

• • • • • •

NN--C

-C

A B C

MAGE cycle

Fig. 6.3. Genome Engineering Enabling New Possibilities in Biosystems Design. The rapid emergence of genome engineering is driving unprecedented advances in biosystems design. Genome engineering establishes the ability to generate 

precise chromosome modifications, elucidate causal links between genotype and phenotype, and enable the design and 

reprogramming of organisms. (a) De novo DNA synthesis permits customized construction of synthetic DNA fragments. 

Large-scale DNA assembly methods assemble synthetic genes into pathway- and genome-scale constructs. Genome-editing 

technologies introduce modifications at targeted genetic loci of diverse organisms. (b) Nuclease-mediated genome-editing 

technologies generate DNA double-strand breaks at targeted loci to introduce genomic modifications. In particular, the 

CRISPR-Cas9 system has been broadly adopted for multiplexed targeting across genomic loci in many organisms. (c) Multiplex automated genome engineering (MAGE) introduces multisite and combinatorial genome modifications through hybridization of synthetic oligonucleotides during replication. MAGE technologies permit modifications at the gene, pathway, and 

genome levels, leading to refactored biosynthetic pathways, whole-genome synthesis of bacterial genomes, and recoding of 

whole genomes. [Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Genetics. Haimovich, A. D., P. Muir, 

and F. J. Isaacs. 2015. “Genomes by Design,” Nature Reviews Genetics 16, 501–16. © 2015.]

Key: CRISPR, clustered regularly interspaced short palindromic repeats; TALENS, transcription activator-like effector nucleases, ZFN, zinc finger nucleases. 

(a) Genome Synthesis Technologies

Synthesis towards a minimal genome

Synthesized 

oligonucleotides

Overlap 

Assembly

Homologous recombination in S. cerevisiae Transfer to 

M. capricolum

Minimal parts 

for viability

1. Gene a

2. Gene b

3. Gene c

4. Gene d

• • •

X

Nucleotides 

fragment: 103 104 105 106

Fragments: 1,078 109 11 1

...

...

... ...

(b) Nuclease Mediated Genome Editing

Target 

DNA

ZFNs TALENs

Non-homologous end-joining 

(induces indels and inversions)

Homology-directed repair 

(template ) DNA
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

50 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Fig. 6.4. Genomically Recoded Organisms (GROs): “A Living Foundry for Making New Materials.” (a) The GRO was constructed using multiplex automated genome engineering (MAGE) to convert nucleotide triplet TAG stop codons to TAAs in a 

panel of strains. Conjugative assembly genome engineering (CAGE) then was used for the hierarchical assembly of these partially recoded genomes into a fully recoded genome in which all 321 TAG stop codons are reassigned. Release factor 1 (RF1) 

then was deleted to establish TAG as an open (instead of terminating) codon for incorporating nonstandard amino acids 

(nsAAs). (b) Adding an orthogonal translation system capable of changing an nsAA to a TAG-recognizing transfer RNA (tRNA) 

enables the genetic encoding of nsAA-incorporating proteins. (c) The reassignment of TAG from a stop to an open codon can 

render TAG-containing or TAG-terminating genes nonfunctional in a different organism, reducing the probability of horizontal gene transfer (HGT) between recoded and natural organisms. (d) Incorporating TAG codons in essential genes provides a 

method for the biocontainment of recoded organisms by linking their viability to the presence of an exogenous nsAA. aaRS, 

aminoacyl-tRNA synthetase. [Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Genetics. Haimovich, 

A. D., P. Muir, and F. J. Isaacs. 2015. “Genomes by Design,” Nature Reviews Genetics 16, 501–16. © 2015.]

(a) Construction of recoded E. coli

Wild-type E. coli

(321 TAG codons)

nsAA

tRNA

Translation

AUC AUC

321 UAG UAA

AUG UAA

 MAGE conversion 

 of TAG to TAA

 across a panel 

 of strains

Orthogonal translation system (OTS)

ssDNA

CAGE hierarchical assembly

Viability

+ nsAA

Functional 

essential 

protein

Truncated 

essential 

protein

RF1 deletion

• • • • • •

• • •

• • •

(b) Expansion of the genetic code

H

CAC

N 

AAT

T

ACG

A 

GCA

V 

GTA

I 

TAG ATC

X

(c) Genetic isolation (d) Biocontainment

- nsAA

Lethality

HGT out

HGT in Recoded E. coli
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 51

example is the microbial synthesis of artemisinic 

acid, a precursor to the antimalarial therapeutic 

artemisinin (see Fig. 6.5, p. 52). Artemisinin is 

naturally produced by the plant Artemisia annua in 

relatively miniscule quantities, and both synthetic 

biology and organic synthesis were explored as ways 

to amplify production. Much effort on the synthetic 

biology front resulted in artemisinic acid titers as 

high as 25 g per liter in yeast (Paddon et al. 2013). 

This effort required overcoming multiple technical 

barriers, such as optimizing enzyme expression to 

fine-tune metabolic flux toward artemisinic acid as 

well as selecting and using the directed evolution 

of enzymes that oxidized precursor molecules to 

artemisinic acid (Paddon and Keasling 2014). In 

another example, high-throughput genome engineering was used to rapidly identify genetic variants 

that overproduced the phytochemical lycopene. 

Specifically, MAGE resulted in the daily generation of billions of variants, and those variants that 

overproduced lycopene fivefold were identified 

within days (Wang et al. 2009). Another example 

of genome engineering employed combinatorial 

design to reorganize the gene cluster responsible for 

nitrogen fixation in the bacterium Klebsiella oxytoca

(Smanski et al. 2014), a process whose enhancement may have significant promise for agriculture 

(see Fig. 6.6, p. 53). This process resulted in more 

than 100 synthetic variants of a complex gene 

cluster, from which an enzyme assay and RNA 

sequencing were used to identify variants with 

significant activity (Smanski et al. 2014). Other 

notable examples are too numerous to list here. At 

the same time, several computational developments 

are making valuable contributions to biosystems 

design: in silico modeling (e.g., Fiore et al. 2016), 

model-guided design of biosystems (e.g., Schreiber 

et al. 2016), and software tools for biosystems 

design (e.g., Oberortner and Densmore 2015).

Overall, industrial biotechnological research and 

development of genetically modified (GM) organisms have been major contributors to the U.S. economy. Biotechnology revenues in 2012 totaled more 

than $300 billion and were apportioned roughly 

equally among drugs synthesized by GM organisms; 

GM crops; and industrial molecules including fuels, 

chemicals, and biotechnological food products and 

feedstocks (Carlson 2016). A remarkable trend 

is that bioproducts, and not biofuels, are now the 

largest group of industrial biotechnological products. Biochemicals are estimated to contribute about 

0.4% of U.S. gross domestic product, compared 

with roughly 3% for petroleum-derived chemicals 

(Carlson 2016).

6.2 Major Challenges in Design 

of Engineered Biosystems

Synthetic Biology Applied to Intractable, 

Eukaryotic, and Multicellular Organisms. Most 

synthetic biology applications to date have focused 

on model prokaryotic bacteria or simple eukaryotes 

such as yeast. Biosystems design relevant to mission 

areas of the U.S. Department of Energy’s (DOE) 

Office of Biological and Environmental Research 

(BER) warrants the development of tools for 

intractable, eukaryotic, and multicellular organisms. 

These organisms include, but are not restricted to, 

phototrophs (e.g., cyanobacteria), archaea, extremophiles, microbes isolated from biofilm mats, algae 

to herbaceous plants, and woody plants (e.g., trees). 

Such systems present new challenges for synthetic 

biology applications compared to those for model 

prokaryotes. Another challenge is epigenetic regulation of gene expression, a phenomenon infeasible 

in prokaryotic biosystems but often observed in 

eukaryotes (Rodriguez-Escamilla et al. 2016).

Engineered Communities of Microorganisms 

and Microbe-Plant Interfaces. Biosystems consisting of multiple, interacting organisms can use the 

metabolic conversion capabilities of the constituent 

organisms to yield a more efficient process than is 

feasible in a single engineered organism. Already, 

synthetic biology approaches reportedly have been 

used on fungi-bacteria (e.g., Minty et al. 2013) and 

bacteria-yeast (e.g., Hu et al. 2016) consortia. New 

tools that target microbial consortia are needed to 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

52 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

advance research in this area. Similarly, engineering 

metabolite exchange between soil microbes (e.g.,

rhizobia) and plant roots, such as in symbiotic nitrogen fixation, requires genetic tools optimized for 

plant-microbe interfaces.

Exploration of Phenotype Landscapes Resulting 

from Genome Engineering. Genome engineering, 

through de novo DNA synthesis and in vivo genome 

Fig. 6.5. Artemisinic Acid Production Pathway in Saccharomyces cerevisiae. (a) Overview of the artemisinic acid production pathway. Galactose (GAL)-induced genes for overexpression (green). Copper- or methionine-repressed squalene 

synthase (ERG9) (red). (DMAPP, dimethylallyl diphosphate; FPP, farnesyl diphosphate; IPP, isopentenyl diphosphate) 

tHMG1 encodes the truncated HMG-CoA reductase. (b) The full three-step oxidation of amorphadiene to artemisinic acid 

from Artemisia annua expressed in Saccharamyces cerevisiae. CYP71AV1, CPR1, and CYB5 oxidize amorphadiene to artemisinic 

alcohol; ADH1 oxidizes artemisinic alcohol to artemisinic aldehyde; ALDH1 oxidizes artemisinic aldehyde to artemisinic acid. 

[Reprinted by permission from Macmillan Publishers Ltd: Nature. Paddon, C. J., et al. 2013. “High-Level Semi-Synthetic Production of the Potent Antimalarial Artemisinin,” Nature 496(7446), 528–32. © 2013.]

editing, can produce hundreds to billions of genetic 

variants of a natural biosystem. Because phenotypes 

are fundamentally unpredictable, exploring the 

combinatorial space of genotypes is essential, rather 

than focusing on a single, static design. The scale of 

phenotype exploration is a factor of two variables—

ease of genotypic diversification and power of 

selection. Combining design, de novo synthesis, and 

in vivo evolution will lead to the creation of large and 
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 53

diverse populations, though both computation and 

phenotype selections will be key limitations.

Isolation of Engineered Organisms with Desired 

Functions. Biosystems design goals often seek to 

engineer a prescribed function (e.g., maximized production of a chemical or biofuel). Front-end design 

technologies (e.g., CAD software), genome engineering, and omics-level datasets have enabled the generation of many engineered variants of biosystems 

and also established the next phase of challenges. 

Prominent among these challenges is the development of biomolecular technologies capable of isolating engineered organisms with desired functions. 

Genome-engineering technologies are now establishing unprecedented and powerful capabilities to 

enact precise genome modifications across a growing 

suite of organisms, though the task of characterizing 

and isolating optimal variant(s) with a sought-after 

function is daunting. Typical efforts involve costly, 

laborious, and time-consuming omics screening of 

≥102

 clones, generating large genomic, metabolomic, 

and proteomic datasets that require analysis.

Safeguarding Engineered Biosystems. Over 

the past decade, synthetic biology has fueled the 

emergence of GM organisms with increased sophistication as common and valued solutions in clinical, 

Fig. 6.6. Synthesis and Refactoring of Biosynthetic Pathways. Numerous approaches have been pursued to isolate, transfer, and characterize gene clusters. Biosynthetic clusters can be cloned from their native organism and transferred to another 

organism for heterologous expression. For organisms that are recalcitrant to laboratory culture techniques, gene sequences 

of interest can be identified from genomic or metagenomic databases and subsequently synthesized and introduced into a 

production organism. The native regulatory elements of a heterologous pathway may not be optimal for expression in the 

host organism. Refactoring approaches seek to rebuild the pathways using well-characterized modular regulatory elements 

and removing all native regulation. [Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Genetics. 

Haimovich, A. D., P. Muir, and F. J. Isaacs. 2015. “Genomes by Design,” Nature Reviews Genetics 16, 501–16. © 2015.]

Key: BAC, bacterial artificial chromosome; PCR, polymerase chain reaction. 

Direct amplification 

and cloning from isolate

Synthesis and refactoring for network engineering Cloned from 

native organism

PCR

Cloning BAC

Functional

assays

Synthesized network

components

Complex natural pathway De novo synthesis 

based on genomic

or metagenomic 

data

Amplification

Assembly

Functional

assays

 De novo synthesis and 

 refactoring for modular 

 control

Library of standard 

biological parts Synthetic operon library

Transformation 

and library 

screening

Promoter

RBS

Terminator
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

54 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

industrial, and environmental settings (Pieper and 

Reineke 2000; Steidler 2003; Way et al. 2014). 

This advancement necessitated safety and security 

measures, which were first outlined in the 1975 Asilomar conference on recombinant DNA (Berg et al. 

1975). These include the development of robust 

solutions to intrinsic biocontainment and genetic 

isolation. While guidelines for physical containment 

and safe use of organisms have been widely adopted, 

intrinsic biocontainment—biological barriers limiting the spread and survival of microorganisms in 

natural environments—remains a defining challenge. Safeguards have been designed (1) to control 

cell growth by essential gene regulation (Kong et al. 

2008), (2) as inducible toxin switches (Szafranski 

et al. 1997), and (3) as engineered auxotrophies 

(Steidler et al. 2013). Yet these approaches are 

compromised by cross-feeding of essential metabolites, leaked expression of essential genes, or genetic 

mutations ( Jensen et al. 1993; Ronchel and Ramos 

2001). Similarly, genetic isolation of microorganisms by preventing the functional exchange of DNA 

through horizontal gene-transfer events will help 

stabilize engineered biosystems from environmental threats. Recent advances over the past 2 years 

have presented numerous safeguard solutions, but 

they remain limited to model microorganisms (e.g., 

Escherichia coli and Saccharomyces cerevisiae). Key 

challenges remain for their implementation in both 

closed- and open-system applications (e.g., remediation), as well as their development in nonmodel 

organisms, multicellular species (e.g., plants), and 

across communities.

Identifying Technological Needs 

to Support Predictive Biology

Genome-Engineering Technologies Adapted 

to Diverse Organisms and Addressing Epigenetic Engineering. As the efficiencies of 

genome-engineering technologies continue to 

improve, their function increases. They expand 

to adapt to diverse species, requiring new tools to 

complement these technological advances. Specifically, new biomolecular tools (e.g., greater numbers 

of engineered Cas9 protein variants) are needed to 

(1) improve genomic targeting capable of enacting 

precise, base pair–level precision; (2) reduce or 

eliminate unintended off-target genome modifications; and (3) increase multiplex genome-editing 

capabilities that generate combinatorial variation. 

Additionally, these capabilities must expand beyond 

genome modifications to other important forms of 

regulation (e.g., epigenetics, transcription, and translation) to fully enable comprehensive biosystems 

engineering of cells with sophisticated functions.

Computational Modeling Interfaced with Omics 

and Imaging Measurements to Develop Integrated Prediction Tools. Synthetic biosystems ideally are developed via a design-build-test-learn cycle 

(see Fig. 6.7, p. 55) (Paddon and Keasling 2014; 

Petzold et al. 2015). Analytical tools involved in this 

process include computational toolboxes for initial 

biosystem design, omics and imaging measurements 

for testing the biosystem, and further computational 

analysis to interpret the large-scale measurements 

that link genotype to phenotype. Design tools 

include flux balance analysis (FBA), which can be 

used to predict carbon rerouting through large metabolic networks at steady state (Orth et al. 2010) and 

is available for community-developed systems (e.g., 

OptForce; Ranganathan et al. 2010). Successful 

applications of such tools to genetically engineered 

systems have been reported (e.g., Ranganathan 

et al. 2010). Design tools also include those that 

predict the dynamics of time-variant biosystems 

(Lomnitz and Savageau 2016). Omics tools ranging 

from transcriptomics (e.g., RNA-seq), proteomics, 

phosphoproteomics, metabolomics (e.g., discussed 

in Chapter 5. Metabolic Pathways in Plants, 

Microbes, and Fungi, p. 37), and isotope-based metabolic flux analysis (MFA) are enormously beneficial 

for assessing the impact of gene or genome engineering. Of these, transcriptomics and metabolomics 

are high throughput and mature, whereas proteomics and phosphoproteomics are still undergoing 

development. Isotope-based MFA (reviewed in 

Antoniewicz 2015) is a powerful method to measure 
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 55

carbon flow and partitioning in metabolically engineered biosystems. It has been applied to complex 

systems including plants (e.g., Nargund et al. 2014) 

and simple organismal consortia (Ghosh et al. 2014; 

Mandy et al. 2014). The extension of such tools to 

complex consortia prevalent in nature is important 

for testing the performance of these biosystems. 

Meaningful interpretation of the raw data generated 

by omics tools requires extensive modeling and 

computation. Interfacing the ensuing results with 

further computation ultimately will enable successful prediction of regulation and genotype-phenotype 

relationships. Although predictive tools along these 

lines already have been reported, substantially more 

development and integration are essential before 

routine, accurate predictions are achieved for complex, multiorganismal biosystems.

Selection Assays. With the rapid advent of 

powerful biosystems design, diversification, and 

manipulation (e.g., genome engineering) and 

screening technologies, “selection” is the missing 

and necessary component for achieving maximum 

phenotypic benefit and functionality. Thus, the next 

key technological challenge to overcome is isolating 

the cell(s) among a large (~109

) population that 

yields a desired phenotype. The development of biomolecular sensors and selectors capable of reporting 

and selecting cells expressing desired biomolecules 

from engineered microorganisms could address 

this challenge. Drawing inspiration from biology, 

such solutions could establish artificial Darwinian 

selection systems that integrate investigator-defined 

genetic diversification, selection, and isolation of 

optimal strains.

Biocontainment and Genetic Isolation: Auxotrophies, Alternative Genetic Codes, and Microcompartments. Recent studies in biocontainment 

(Cai et al. 2015; Gallagher et al. 2015; Mandell 

et al. 2015; Rovner et al. 2015; Chan et al. 2016) 

and genetic isolation (Lajoie et al. 2013; Ma and 

Isaacs 2016) have developed significantly improved 

solutions for safeguarding engineered biosystems. 

Fig. 6.7. The Design-Build-TestLearn (DBTL) Cycle. DBTL is a basic 

approach for efficient problem 

solving that has been adapted for 

engineering biological systems. 

The design component defines the 

problem, establishes an approach to 

solve the problem, and identifies the 

biological components needed to 

build or modify. The build component synthesizes, assembles, or 

edits (or all three) the components 

of the engineered biological system. 

The test component characterizes 

the different biological systems 

and identifies the variants with the 

prescribed behavior. The learn component analyzes the test data and 

informs subsequent iterations of the 

cycle. [Reprinted under a Creative 

Commons Attribution License from 

Petzold, Chan, Nhan, and Adams.]
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

56 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Even so, many challenges and technological needs 

remain unmet. They include (1) testing of existing 

safeguards in real-world applications (e.g., bioremediation), (2) translating safeguards to nonmodel 

organisms and communities, and (3) scale-up of 

testing and implementation in industrial settings 

to determine optimal utility and identify failure 

points. The development of new safeguard solutions 

remains a high priority. For example, promising avenues are restricting growth to synthetic molecules or 

engineering microcompartments, even in prokaryotes (Sargent et al. 2013), to sequester proteins or 

bring enzymes and substrates into close proximity 

(Choudhary et al. 2012). Potentially, these structures can become biocontainment solutions by 

sequestering toxic products that otherwise would 

endanger the host or its environment. Additionally, 

a set of notable papers that describe the development of genomically recoded organisms (GROs) 

has established promising and robust solutions for 

biocontainment and genetic isolation through the 

design and construction of organisms possessing 

alternative genetic codes (Lajoie et al. 2013; Mandell et al. 2015; Rovner et al. 2015; Ma and Isaacs 

2016). Further development of organisms with 

more orthogonal and alternative genetic codes in 

model systems, as well as their implementation in 

diverse species or even communities, remains an 

unmet technological area whose realization could 

have a big impact on DOE goals and applications in 

energy supply and the environment.

6.3 Leveraging Synthetic 

Biology for Future Energy 

and Resource Needs

Achieving the advances in biosystems design outlined in this chapter is expected to widely benefit 

DOE’s mission of planning for future energy and 

resource needs. Harnessing the novel biological and 

biochemical functions of biology-based sources 

that use fermentative and photosynthetic organisms 

entails the engineering of plants, microbes, and 

organismal communities. Plants must be engineered 

to (1) improve photosynthetic rate and yield by 

incorporating carbon-concentrating mechanisms 

and alleviating photorespiratory carbon losses, 

(2) enhance water- and nutrient-use efficiency 

(especially nitrogen and phosphorus), (3) combat 

abiotic environmental stresses, and, most importantly, (4) facilitate readily degradable cell walls. 

Microbial biosystems design must leverage fermentative and photosynthetic species to target their 

high-efficiency deconstruction of cellulose and 

other cell wall components and synthesis of biofuels or bioproducts, coupled with engineering for 

high-yield and end-product productivity as well as 

improved tolerance to end-product toxicity. Finally, 

engineered microbial biosystems must be able to 

synthesize compounds not attainable via conventional organic chemical synthesis, as well as a wide 

variety of similar compounds (e.g., higher carbon 

content alcohols or hydrocarbons) with product 

variety that can be controlled according to need and 

produced on demand.

Highly desirable applications of complex engineered 

biosystems such as microbial and microbe-plant 

communities include solutions to ecological challenges such as bioremediation, carbon dioxide 

(CO2) capture and storage, and nitrogen fixation, all 

of which are energy-intensive processes. In this context, researchers envision using prokaryotes for carbon capture (Hicks et al. 2017) and plant-invading 

bacteria for symbiotic nitrogen fixation (Hicks 

et al. 2017). Engineering for CO2 sequestration and 

reduction may benefit from the decoupling of electron carrier (e.g., nicotinamide adenine dinucleotide 

phosphate or NADPH) regeneration from carbon 

assimilation. Microbes that perform electrosynthesis 

[i.e., directly use electrons from an electrode toward 

metabolism (Rabaey and Rozendal 2010; Nevin 

et al. 2011)] may be incorporated into biosystems 

that harness electrical energy. Engineering to facilitate nitrogen fixation may benefit from a detailed 

understanding of carbon-nitrogen interactions in 

metabolic networks of individual or symbiotic nitrogen-fixing biosystems.
Chapter 6 – Biosystems Design

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 57

Accomplishing these goals may enable synthetic 

biology to move from the engineering of individual microbes that produce specific molecules 

to engineering of microbial communities and 

microbe-plant symbioses (as in the rhizosphere). 

This trajectory will require the simultaneous development of imaging, metabolomic, fluxomic, and 

other omics tools that can measure metabolism and 

molecular exchange among communities of organisms. Progress is being made toward developing a 

broader set of foundational technologies to engineer 

model and undomesticated microbes, plants, and 

microbial communities. Thus, the new tools discussed in this report—particularly, imaging, measurement, and characterization techniques—will 

be needed to test designer biosystems in organisms. 

These new technologies are expected to (1) enable 

the precise probing and manipulation of genetic and 

biomolecular processes, (2) aid the optimization of 

biosystems design by providing an understanding 

of the spatiotemporal dependencies of engineered 

pathways, (3) enable identification of bottlenecks 

in metabolic networks, and (4) aid in gaining an 

understanding of how incorporating new functions 

produces unintended impacts on the metabolism of 

individual organisms or an organismal consortium. 

Ultimately, the iteration between the design and 

large-scale phenotypic characterization of biosystems will lead to an understanding of how genomes 

translate into function, another goal of BER’s Biological Systems Science Division.
58 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 59

Chapter 7 – Cellular Ultrastructure and Physiology

Biological systems can be metabolically manipulated 

for a variety of beneficial purposes, including the 

sustainable production of fuels and chemicals from 

renewable plant biomass. Maximizing yields from native 

or engineered biological systems while preventing 

unintended consequences to other systems or 

the environment takes significant effort and is a 

major focus for researchers supported by the 

Biological Systems Science Division within the 

U.S. Department of Energy’s (DOE) Office of 

Biological and Environmental Research (BER). 

Achieving the depth of understanding needed 

to control biosystem output and productivity is 

a daunting challenge that will require characterization of processes occurring among vastly diverse 

molecular species and across a range of spatial and 

temporal scales—from the atomic to the cellular and 

multicellular levels.

7.1 Science and Technologies

This chapter reviews current technologies for characterizing 

biological systems on the atomic to cellular scales and identifies technological shortfalls responsible for knowledge gaps in 

key research areas. Given the breadth of science covered and 

the brevity of this report, needed capabilities are discussed in 

terms of the primary data types generated and their optimal 

spatial, temporal, and chemical capabilities.

Cellular Ultrastructure 

and Physiology

Chapter 7
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

60 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Using Structural Imaging to Characterize 

a Biosystem’s Organization

Many different biophysical measurements can provide spatial and temporal information, but structural 

imaging is the most direct means of characterizing a 

biosystem’s organization. The bioimaging community has a multitude of different techniques at their 

disposal, each of which operates optimally over a 

well-defined range of specimen sizes and spatiotemporal resolutions.

Atomic and Molecular-Level 

Structure and Dynamics

The ability to probe biological phenomena at 

the nanoscale and relevant temporal scales has 

been transformed by new developments in 

technologies: cryo-electron microscopy (cryoEM) 

and cryo-electron tomography (cryoET), nuclear 

magnetic resonance (NMR), neutron macromolecular crystallography (NX), small-angle neutron 

scattering (SANS), small-angle X-ray scattering 

(SAXS), and macromolecular X-ray crystallography 

(MX). DOE investments in user facilities have accelerated the application of many of these foundational 

tools while fostering a broad user base. Despite such 

advances, development in these areas is still needed 

to improve resolution, sampling, and throughput; 

bridge the remaining technology gaps; and push the 

frontiers of structural imaging.

Transmission Electron Microscopy (TEM).

Technologies employing TEM (see box, Electron Microscopy Terms, this page) produce 

three-dimensional (3D) images of biological 

specimens in the macromolecular to cellular scale 

range. The recent revolution in single-particle 

cryoEM technologies and approaches has dramatically increased the spatial resolution potential for 

macromolecule and macromolecular complex samples. This can be attributed to the development of 

(1) direct electron detectors (Li et al. 2013; Wang 

et al. 2014), (2) computationally assisted data 

collection in modern electron microscopes (Lyumkis et al. 2013), and (3) image-processing software 

developed in academic laboratories (DiMaio and 

Chiu 2016; Ludtke 2016; Scheres 2016). Continuing development of better recording devices and 

electron optics, such as phase plate technology, 

promises to deliver better resolving power and will 

generate even larger datasets. Advances already 

achieved in those areas have led to the structural 

determination of increasingly complex molecules 

(see Fig. 7.1, p. 62), including (1) multicomponent molecular machines, at near-atomic to atomic 

resolution (Li et al. 2013; Wang et al. 2014; Glaeser 

2016) and (2) the ability to view such molecular 

machines on and inside cells (Guerrero-Ferreira 

et al. 2011; Hu et al. 2013; Mattei et al. 2016). 

Despite the dynamics in vitrified specimens being 

limited to time scales longer than the process of 

freezing (~0.1 milliseconds), the samples’ natural 

heterogeneity reflects the conformational landscape of several macromolecular complexes and has 

enabled some exciting discoveries (Amunts et al. 

2015; Bai et al. 2015; Nguyen et al. 2016). Continued improvements, such as streamlining the methodology for steps ranging from sample preparation 

to data acquisition and computational reconstruction, are needed to empower wider adoption and 

increase throughput of atomic-resolution structure 

determination. In addition, emerging new TEM 

capabilities on the millisecond to nanosecond time 

Electron Microscopy Terms

SEM – Scanning electron microscopy

TEM – Transmission electron microscopy

Cryo – Vitrification of aqueous samples at liquid 

nitrogen or lower temperatures

Single-particle cryoEM – Many individual projections are combined to form a 3D image of a 

biomolecule

Tomography – Many images taken from the 

same cell or cell section as it is being tilted 

are computationally recombined to create a 

3D volume

FIB – Focused ion beam milling, used to prepare thin samples for tomography or combined 

with SEM

Phase plate – Technology for increasing image 

contrast
Chapter 7 – Cellular Ultrastructure and Physiology

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 61

scales with atomic to near-atomic resolution (Evans 

and Browning 2013) would extend this approach 

to spatiotemporal regimes relevant to motions of 

protein secondary structure elements—domains 

and subunits central to regulating protein activity. 

The ability to visualize all conformational states of 

a given enzyme during the continuum of a reaction 

would help advance isozyme engineering for more 

efficient biofuel production.

Light Sources. The commissioning of fourthgeneration X-ray free-electron laser (XFEL) 

light sources such as the Linear Coherent Light 

Source at DOE’s SLAC National Accelerator 

Laboratory has created the new paradigm of 

“diffract-before-destroy” imaging (Spence and 

Hawkes 2008). These femtosecond X-ray sources 

empower new research using MX and absorption 

and emission spectroscopy (Kern et al. 2013). 

Probing Biosystem Dynamics 

with Experimental and 

Computational Methods

Understanding of contributors to biosystem dynamics, such as enzyme function 

incurred by structure, membrane composition, and localization of components 

within a cell, to provide the foundation 

for functional models that bridge chemistry and biology.

• Advanced experimental methods, combined with computation, to probe atomic and 

molecular structure.

• Streamlined transmission 

electron microcrospy methodologies, from sample preparation to data acquisition, and 

computational reconstruction 

improvements in light-source 

peak brightness.

• Methodologies to permit 

atomic-resolution, pump-probe 

imaging of two-dimensional crystals and, ultimately, single-particle macromolecular complexes.

• Advances and rejuvenations to 

“mature techniques” that can 

benefit from insights gained 

from new technologies such as 

X-ray free-electron lasers.

Cellular Ultrastructure and Physiology Needs

Imaging Whole Organisms

Advancements to understand cells, the functional units of 

most biosystems, and their intracellular organization; and how 

cellular phenotypes respond to variations in environmental 

conditions and genetic and chemical modifications.

• New specimen-preserving methods for in situ, dynamic, 

or cryogenic imaging of whole organisms to determine 

the highly heterogeneous organization of cells with 

nanoscale resolution for theory and model refinement.

• Methods to enable in situ analysis of hydrated and 

living specimens.

• Advancements in visual proteomics to pinpoint the 

location of all proteins and complexes of known structure within three-dimensional reconstructions from 

whole-cell electron tomography.

Imaging Chemical Events: Gradients, 

Transformation, and Fate

New imaging methods to understand the series of highly 

orchestrated chemical events occurring at defined locations 

within cells for revealing the network of molecular interactions.

• New methods to image the localization of enzyme 

reactions and the flow of chemicals and macromolecules within and between cells to unravel the complex 

network of molecular interactions defining cell phenotypes and functions.

• Improved approaches to conduct correlative imaging 

of intact or living plants.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

62 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

XFEL light sources enable analysis of certain 

samples—for example, 3D nanocrystals (Aquila 

et al. 2012), 2D crystals (Frank et al. 2014), and 

large single-particle molecular complexes (Saldin 

et al. 2011)—not amenable to investigation at 

synchrotron light sources. Both XFELs and synchrotrons can perform pump-probe dynamic 

experiments on 3D crystals on ultrafast time scales: 

up to tens of femtoseconds for XFELs and up to 

hundreds of picoseconds for synchrotrons (Levantino et al. 2015; Young et al. 2016). Beyond these 

advances are further needs, including light source 

improvements in peak brightness coupled with 

new methodologies to permit atomic-resolution, 

pump-probe imaging of 2D crystals and, ultimately, single-particle macromolecular complexes. 

Improvements in current synchrotron sources will 

also make new measurement methods more widely 

available, such as fluctuation X-ray scattering to 

more accurately probe the structures of molecules 

in solution (Chen et al. 2013; Donatelli et al. 2015), 

diffractive imaging of single molecules (Donatelli 

et al. 2017), and ptychographic imaging (Chapman 

2010) of microbes and microbial communities 

(Zhu et al. 2016). These new light source capabilities will greatly benefit efforts to understand the 

structural dynamics of a wide range of BER-relevant 

targets in near-native geometries and environments.

Fig. 7.1. Atomic Model for the P22 Virus Capsid Obtained from Single-Particle Cryo-Electron Microscopy. Key regions 

in the capsid protein are shown with the corresponding electron microscopy density. [Reprinted from Hryc, C. F., et al. 2017. 

“Accurate Model Annotation of a Near-Atomic Resolution Cryo-EM Map,” Proceedings of the National Academy of Sciences of the 

USA 114(12), 3103–08.]
Chapter 7 – Cellular Ultrastructure and Physiology

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 63

Fig. 7.2. Insight into Oxygen Activation in Lytic Polysaccharide Mono-Oxygenase (LPMO). A structural description of molecular oxygen activation at the Cu active site by 

a fungal LPMO was obtained using X-ray and neutron crystallography and density functional theory calculations. X-ray 

crystallography reveals the positions of heavier elements, 

while neutron crystallography is uniquely capable of visualizing positions of the critical hydrogen atoms. [Reprinted 

from O’Dell, B., P. K. Agarwal, and F. Meilleur. 2017. “Oxygen 

Activation at the Active Site of a Fungal Lytic Polysaccharide 

Monooxygenase,” Angewandte Chemie International Edition 

56(3), 767–70. © The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.]

Mature Technologies. As these newly developed 

light source technologies are providing novel 

insights into more complex systems and at smaller 

time scales, mature technologies such as MX, NX, 

SAXS, SANS, and NMR spectroscopy continue to 

evolve and fulfill new roles in biosystem imaging and 

analysis. Synchrotron-based MX remains unparalleled in providing high-throughput, high-resolution 

macromolecular structures, with recent advances 

extending these results to more challenging and 

flexible systems (Berman et al. 2000; Moult et al. 

2014). The MX workflow is particularly well 

adapted to conduct expansive surveys and rapidly 

test predictions. Recently, the methods for sample 

introduction, data collection, and data processing 

developed for XFELs (and in some cases cryoEM) 

are being implemented at the synchrotrons, 

enabling new science applications. SAXS provides 

high-throughput, moderate-resolution structural 

information (Brunette et al. 2015; Bale et al. 2016; 

Boyken et al. 2016). NMR, SANS, and NX enable 

altered contrast in heterogeneous materials and provide direct insights into the role of hydrogen atoms 

(see Fig. 7.2, this page) that can only be inferred 

by other techniques (Blakeley et al. 2008; Le et al. 

2014; Frederick et al. 2015). In all cases, support 

for these critical capabilities and their continued 

innovation is needed to enhance the understanding 

of biosystem complexity and unravel mechanisms 

central to biological and environmental processes.

Subcellular Localization and 

Organization with Minimal 

Specimen Perturbation

Understanding biological system architecture 

requires the ability to locate specific molecules 

and complexes in the milieu of a cell, community, 

biofilm, or tissue with only minimal perturbation to 

the system. Electron, ion, neutron, optical, and X-ray 

microscopy approaches can image various scales and 

sample states. In many cases, a combination of these 

approaches can provide synergistic imaging modes 

that enable visualizing a sample across scales.

Most biological systems are damaged when exposed 

to ionizing radiation and exhibit photobleaching effects under high-light exposure. In addition 

to physical damage, such exposure can alter the 

chemical nature of the sample if the generated free 

electrons or radicals created during beam and sample interactions diffuse freely through the medium 

and react with the sample. Researchers are developing new approaches to limit such damage during 

in situ analysis, but most experiments currently 

mitigate beam-induced damage using preanalysis 

cryopreservation or chemical fixation. Rapid 

cryopreservation is considered the “gold standard” 

for retaining the specimen in its native state. This 

technique immobilizes water in the specimen as 

amorphous (vitreous) ice rather than in crystalline 

form that can damage ultrastructure. In comparison, 

chemical fixation usually alters the true native state 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

64 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

of a specimen’s function or ultrastructure, but it 

does provide a means to identify structures or locate 

specific molecules in optical, electron, and X-ray 

images via the use of stains or antibody-conjugated 

probes. Unfortunately, the process of chemically 

fixing or cryogenically freezing samples removes the 

experimenter’s ability to track fast dynamic changes 

that occur on the submillisecond and faster time 

scales. Probing the dynamics in this temporal range, 

therefore, requires new methods that enable in situ

analysis of hydrated and living specimens, even if 

only under a single-shot, pump-probe regime to 

avoid damage effects.

Optical Microscopies. These approaches can 

provide static imaging at high spatial resolution for 

both fixed and cryogenic samples as well as images 

depicting dynamics in living cells. Conventional 

widefield epifluorescence, total internal reflection 

fluorescence (TIRF), and confocal microscopies 

have contributed significantly to the understanding of subcellular organization. Researchers have 

used these techniques to (1) localize fluorescently 

labeled components inside living cells; (2) identify 

and quantify the size and shape of organelles and 

their relative positions in 3D; and (3) discern the 

relative positions of various cells and cell types 

within multicellular organisms, plants, or microbial 

communities. Data can be acquired as a continuous 

movie at imaging rates of 1 to 1,000 frames per 

second or via time-lapsed acquisition with a series 

of time-resolved images collected over many 

hours. For these conventional optical microscopy 

approaches, the spatial resolution typically is limited by diffraction to ~200 nanometers (nm) at best. 

However, the development of “super-resolution” 

methods has led to a technology-driven resurgence 

of fluorescence microscopy (see Fig. 7.3, this page). 

These methods—including photoactivated localization microscopy (PALM; Betzig et al. 2006), 

stochastic optical reconstruction microscopy 

(STORM; Rust et al. 2006), and stimulated emission depletion (STED; Klar et al. 1999)—have 

been bolstered by other techniques, such as light 

Fig. 7.3. Super-Resolution Microscopy Enabling 

Nanometer-Scale Imaging, Real-Time Subcellular 

Particle Tracking, and Three-Dimensional (3D) Microscopy in Cells. (a) A mitochondrial network is visualized by 

ultrahigh-resolution 3D imaging of whole cells. (b) 3D diffusion and dwelling behavior of DNA polymerase is resolved 

in live Bacillus subtilis cells. Scale bar: 1 micrometer (μm). 

(c) Subcellular positions (top) and trajectories (bottom) of 

outer-membrane enzymes reveal the interactions of proteins 

with starch during catabolism by living microbial gut symbionts. [(a) Reprinted under a Creative Commons Attribution 

License and modified from Huang, F., et al. 2016. “Ultra-High 

Resolution 3D Imaging of Whole Cells,” Cell 166(4), 1028–40. 

(b) Reprinted from Liao, Y., et al. 2016. “Single-Molecule DNA 

Polymerase Dynamics at a Bacterial Replisome in Live Cells,” 

Biophysical Journal 111(12), 2562–69 with permission from 

Elsevier. (c) Reproduced from Karunatilaka, K. S., et al. 2014. 

“Superresolution Imaging Captures Carbohydrate Utilization 

Dynamics in Human Gut Symbionts,” mBio 5(6), 1–10 with 

permission from the American Society for Microbiology 

under a Creative Commons Attribution NonCommercial 

ShareAlike license.]

sheet microscopy. These techniques enable optical 

sectioning through thicker specimens (Zanacchi 

et al. 2011). Although these instruments and methods have pushed the achievable spatial resolution 

of fluorescence imaging far beyond what once was 

a b

c

x-position (μm)

y-position (μm)
Chapter 7 – Cellular Ultrastructure and Physiology

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 65

thought possible (i.e., precision down to 20 nm 

in some instances), super-resolution fluorescence 

microscopy is limited to imaging fluorescently 

labeled molecules and not the surrounding unlabeled cell environment. As is the case with most 

cutting-edge instrumentation, trade-offs exist, and 

the increase in spatial resolution beyond the diffraction limit for super-resolution optical microscopy 

tends to result in lower temporal resolution.

Alternate, Combined Approaches. In contrast, 

combining optical microscopy with vibrational 

spectroscopy methods such as infrared microspectroscopy and, more recently, nanospectroscopy 

enables the imaging of subcellular components and 

chemical distributions in a label-free manner (Centrone 2015; Muller et al. 2015). Coherent anti-Stokes 

Raman scattering (CARS; Evans and Xie 2008) 

and stimulated Raman scattering (Freudiger et al. 

2008) microspectroscopies are nonlinear optical 

approaches that can achieve the same objective. 

These alternate approaches can image subcellular 

organization with chemical information at a molecular level. Because the resulting infrared or coherent 

Raman signals depend on interactions between light 

and the resonant modes of the functional groups of 

target molecules, detection could be limited to certain classes of molecular components. For a complete 

picture of cellular structure and dynamics, fluorescence and CARS imaging data often are complemented with structural data from electron or X-ray 

microscopy using correlative microscopy workflows.

Tomography and Scanning TEM for 3D Reconstructions. Transmission electron microscopy 

(TEM) combined with tomography produces 

2D images of specimens at very high spatial resolution (nanometers to Angstroms) that can be 

back-projected to reconstruct 3D ultrastructure and 

cellular organization (see Fig. 7.4, p. 66). However, 

the high spatial resolution provided by TEM comes 

with a trade-off related to tolerable specimen thickness. In general, the thicker the specimen, the lower 

the achievable resolution. For conventional microscopes, biological specimens ideally should be less 

than 200 nm thick. Current knowledge of organelle 

structures is almost entirely a result of decades’ 

worth of ultramicrotome sample sectioning in 

combination with room-temperature or cryoEM. 

Though such reconstructions have been immensely 

informative, they are fraught with unavoidable 

image artifacts. 

New advances in phase plate technology (see box, 

Electron Microscopy Terms, p. 60; Danev and 

Nagayama 2001; Danev et al. 2014) and scanning 

TEM (Wolf et al. 2014) have allowed tomographic 

reconstructions of intact bacterial and algal cells 

more than 1 μm thick (Henderson et al. 2007; Dai 

et al. 2013; Guerrero-Ferreira and Wright 2014) 

with a spatial resolution of 2 to 10 nm without 

cell sectioning or staining. Yet visualizing organisms larger than 1 μm in 3D using EM involves a 

technically difficult, time-consuming workflow—

(1) cutting consecutive physical sections of a cell 

thin enough for electron transparency, (2) imaging 

and reconstructing the sections separately, and 

(3) stitching them together computationally. Such 

slice-by-slice imaging methods include serial section 

TEM, slice-and-view scanning EM (Heymann et al. 

2006), bi-directional ion milling to thin a specimen 

already sitting on a TEM grid (Marko et al. 2007; 

Chaikeeratisak et al. 2017), or using a focused 

ion beam (FIB) to selectively lift out a specific 

region from a specimen and attach it to a TEM 

grid (Mahamid et al. 2015). The medical research 

community is using these methods to image large, 

montaged volumes of brain tissue for connectomics (the creation of maps showing the connections 

between neurons), an approach which holds great 

promise for analyzing small ecosystem communities such as biofilms or samples isolated from the 

rhizosphere. Similarly, new advancements in visual 

proteomics (Dai et al. 2013; Mahamid et al. 2016) 

are needed to pinpoint the location of all proteins 

and complexes of known structure within 3D reconstructions from whole-cell electron tomography. 

These highly detailed maps would refine insights 

into how cellular and subcellular organization varies 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

66 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

between phenotypes or in response to environmental changes (see Fig. 7.4, this page).

Transmission X-Ray Microscopes (TXMs). A 

complementary or alternative technology to electron microscopy, TXMs can also image the internal structure of cells (Leis et al. 2009; Larabell 

and Nugent 2010). TXMs use soft X-rays to image 

samples at inherently lower spatial resolution 

than electron microscopy (10 to 50 nm compared 

to 1 to 5 nm, respectively). However, soft X-rays 

can image cryopreserved specimens up to 15 μm 

thick, providing higher sampling rates and sample numbers that can be statistically analyzed for 

most unicellular and some multicellular organisms 

without requiring physical sectioning (Le Gros 

et al. 2012; McDermott et al. 2012). Similar to 

neutron imaging, hard X-ray TXMs can probe 

even thicker samples (greater than centimeters 

thick) to gain insights into plant biology, microbesoil interactions, or microbial communities 

and biofilms. In addition to imaging the spatial 

arrangement in whole cells, TXMs, in combination with linear absorption coefficients, enable 

direct identification of subcellular structures (see 

Fig. 7.5, p. 67; Smith et al. 2014). This capability 

is possible because image contrast in TXMs comes 

from the attenuation of the incident light by biomolecules in the specimen, obviating the need for 

contrast agents or stains (Do et al. 2015). Water is 

relatively transparent (compared to the absorption 

Fig. 7.4. Zernike Phase Contrast Cryo-Electron Tomography of Syn5-Infected Marine Cyanobacteria at Various Stages 

of Infection. Views (a–d: left, tomogram slice view; right, annotated tomographic slice view) of 54 Angstrom sections of 

Cyanobacteria, Synechococcus sp. Strain WH8109, cells during the process of infection by cyanophage Syn5. Sections are 

computationally derived from the middle of tomograms of the whole cells. (a) Uninfected cell, (b–d) early, intermediate, and 

late stages of infection. Cellular components and phages are colored and labeled in the annotated view in c. Phage progeny 

can be separated into three types based on size, shape, and internal density: procapsid, yellow; expanded capsid, pink; and 

DNA-containing capsid, magenta. [Reprinted by permission from Macmillan Publishers Ltd: Nature. Dai, W. et al. 2013. “Visualizing Virus Assembly Intermediates Inside Marine Cyanobacteria,” Nature 502(7473), 707–10. © 2013.]

c

a b

d
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September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 67

Fig. 7.5. Cryogenic Soft X-Ray Nanotomography of 

Cellular Systems. (Top) Cryo-soft X-ray tomography of a 

reconstructed Chromochloris zofingiensis cell with segmented nucleus (purple), chloroplast (green), mitochondria (red), lipids (yellow), and starch granules within the 

chloroplast (blue). (Bottom) Frozen-hydrated whole yeast 

cells imaged at the Advanced Light Source. Organelles 

within the cell can be directly modeled and assigned based 

on their linear absorption coefficients. The central slice of 

the three-dimensional tomogram is shown on the left and 

final model on the right. Vacuoles, nucleus, mitochondria, 

and lipid droplets are colored green, blue, red, and yellow, respectively. [Top image courtesy National Center for 

X-ray Tomography. Reprinted from Roth, M. S. et al. 2017. 

"Chromosome-Level Genome Assembly and Transcriptome 

of the Green Alga Chromochloris zofingiensis Illuminates 

Astaxanthin Production," Proceedings of the National Academy of Sciences of the USA 114(21), E4296–4305. Bottom 

image courtesy James Evans, Chuck Smallwood, and Erin 

Bredeweg, Pacific Northwest National Laboratory.]

by carbon-containing molecules) within the 

so-called soft X-ray “water-window” (Parkinson 

et al. 2013). Consequently, soft X-ray microscopes 

provide an accurate measurement of the cell’s 

carbon content, an important factor in calculating 

a biosystem’s energy balance at the cellular level.

Imaging Chemical Events: 

Spatial and Multiscale Mapping

Biological systems rely on chemistry taking place at 

the correct time and in the right place (Le Gros et al. 

2012). Tracking the location and concentration of 

molecules over time is thus a key characterization 

step for biological investigations. Determining 

location and concentration is relatively easy if the 

molecule of interest is produced at high levels or 

distributed over large areas, but accurately characterizing small numbers of molecules produced by 

native or engineered biosystems remains challenging, particularly for single-cell measurements. NMR, 

Fourier transform infrared (FTIR) spectroscopy, 

and mass spectrometry (MS) are approaches well 

suited to identifying chemical composition. MS 

imaging, such as with Nano-Secondary Ion Mass 

Spectrometry (NanoSIMS), allows part-per-million 

detection of ions and isotopes with up to ~50 nm 

spatial resolution, but it is a static and destructive 

method best suited to imaging chemical gradients 

and cellular assimilation. In comparison, NMR 

approaches have a lower spatial resolution but can 

image living cells, providing information on native 

states of their lipids, nucleic acids, polysaccharides, 

and proteins. Researchers have recently applied 

neutron scattering techniques in combination with 

isotopic labeling to investigate lipid domains in 

membranes and protein dynamics in vivo, opening 

up new and exciting avenues for live-cell imaging 

(Anunciado et al. 2017). Recently, nano-FTIR 

spectromicroscopy has provided chemical information on organic samples with a spatial resolution of 

30 nm (Amenabar et al. 2017), although the spectral 

range is significantly limited by the use of laser light 

sources. Further development of each technique 

(i.e., imaging MS, NMR, and FTIR) is needed to 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

68 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

simultaneously improve chemical sensitivity and 

spatial resolution. These advances would help reveal 

new insights into biological compartmentalization 

and its role in regulating molecular interactions.

Synchrotron-based X-ray spectroscopy or microspectroscopy can generate elemental maps of 

specimens, but the inherent damage from beams 

can limit these approaches to static observations 

from nearly equivalent samples. In contrast, 

synchrotron-based broadband FTIR (sFTIR) 

spectroscopy or spectromicroscopy does not 

introduce detectable effects on biological materials (Holman et al. 2002a), thereby permitting 

analysis of live cells and observation of chemical 

events in the same cell or sample. sFTIR spectromicroscopy (Holman et al. 2010; Probst et al. 2013) 

and time-resolved microfluidic sFTIR spectromicroscopy (Holman et al. 2009b; Holman et al. 

2010; Loutherback et al. 2016) are now matured 

techniques for measuring chemical changes in live 

microbial specimens with diffraction-limited spatial 

resolution of 2 to 10 μm and temporal resolution of 

several to tens of seconds.

Use of midinfrared wavelengths for sFTIR inherently precludes their use in obtaining nanoscale 

chemical information. Synchrotron infrared nanospectroscopy (SINS; Bechtel et al. 2014) overcomes 

this spatial limitation by combining high spatial 

resolution atomic force microscopy with broadband 

(4,000 to 650 per centimeter) synchrotron infrared 

radiation, enabling the measurement of chemical 

changes down to 20 nm or finer spatial resolution. 

SINS, however, is limited to measuring chemical 

events in water-free environments because water 

induces viscous damping that severely decreases 

the interpretability of the data. Thus, the next key 

technological challenge to overcome is the ability 

to probe live chemical events in living cells at the 

nanoscale. Worth noting is that all FTIR approaches 

are limited to detecting infrared-active molecules. 

Therefore, integration of sFTIR imaging with 

spatially resolved ambient MS (O’Brien et al. 2015) 

is a promising approach to improving the chemical 

specificity for unique compound identification.

Correlative Imaging. Because localizing chemical 

information is fundamental to understanding biological systems, the ability to overlay spectroscopy 

and structural data from the same specimen onto 

information from other imaging approaches creates 

a highly informative composite view of the specimen. The field of correlative imaging has expanded 

rapidly in recent years, leading to many novel 

insights not possible with a single technique (see 

Fig. 7.6, p. 69). Of particular note is the considerable 

correlative power gained by combining fluorescence 

and electron microscopy to visualize the localization 

of labeled protein complexes within a whole-cell 

context using cryoET (Briegel et al. 2008; Hampton 

et al. 2017) or cryo-soft TXM. Challenges remain 

regarding common sample geometries, amenable 

sample thickness, image indexing and registration, 

and computational visualization of data at different 

spatial resolutions. Continued advancements in 

these areas will help make such holistic structural 

and chemical imaging approaches more widely 

adopted and useful for BER applications, including 

understanding (1) the impact of biofuel production on microbes, (2) how microbes communicate 

to form biofilms, and (3) the cellular components 

responsible for biogeochemical cycling. Correlative 

imaging of plants and plant-microbe interactions is 

another area ripe for development, but its large spatial range—covering macromolecules (~10 nm), single microbes (~2 μm), single plant cells (~10 μm), 

and a whole plant (millimeters to meters)—complicates workflows for both data acquisition and downstream analysis and visualization. Although efforts 

to image root systems have advanced significantly in 

recent years, correlative imaging of intact or living 

plants remains challenging because of the inherent 

opaqueness of soils.

Root system architecture has a dramatic bearing on 

plant viability and crop productivity in given soil 

conditions. New developments in dynamic, static, 

or cryogenic multiscale imaging using electron, 
Chapter 7 – Cellular Ultrastructure and Physiology

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 69

neutron, optical, infrared, or X-ray approaches are 

needed to reveal the unperturbed, overall 3D architecture and chemistry of a root system and specific 

cell surface–mediated interactions between root 

cells and microbes. Given the potentially significant 

increase in crop yields that could result from efforts 

to match plant species to optimal soil type and 

texture, increase their drought tolerance, or leverage 

interactions with beneficial microbes, developing 

new technologies for imaging plants from roots to 

leaves could have dramatic environmental, economic, and humanitarian effects.

7.2 Understanding GenotypePhenotype Interactions to 

Improve Biofuel Feedstocks

Comprehensive biosystem characterization 

requires understanding how the system senses 

environmental perturbations and the mechanisms 

that cells use to make changes in response to these 

cues. Developing new bioimaging and spectroscopy capabilities spanning electron, ion, optical, 

neutron, and X-ray modalities and fusing them with 

new advances in systems biology, computation, 

and automation can provide a deeper understanding of the link between genome and phenotype. 

Exploiting and controlling those linkages would 

radically enhance the ability to design and harness 

biosystems for cheaper, more efficient biofuels and 

bioproducts, increased crop yields, and biological 

routes to soil remediation.

Fig 7.6. Correlative Imaging for Structure-Function 

Studies. Cryo-correlative light and electron microscopy 

(cryoCLEM) combines spatiotemporal information from 

fluorescence light microscopy (fLM) with high-resolution 

structural data from cryo-electron tomography (cryoET). 

CryoCLEM enabled the identification of fluorescently 

labeled piliated Caulobacter crescentus swarmer cells 

dispersed on an electron microscopy grid. The combined 

approach facilitated structure-function investigations of the 

pilus filament and pilus assembly complex during secretion and retraction stages. (a) CryofLM of frozen-hydrated 

Caulobacter cells in which the pilus filament was fluorescently labeled (red). (b) Cryo-electron microscopy (cryoEM) 

montage magnified 100x. (c) Tomographic slice through 

the Caulobacter cell with the labeled pili. (d) Segmented 

Caulobacter cell volume. Pili (blue), s-layer (gold), outer 

membrane (yellow), and inner membrane (red). White box 

in (a) corresponds to white box in (b) and tomogram of 

Caulobacter cell (c). Scale bars: (b) 10 mm, and (c) 100 nm. 

[Image courtesy Rebecca S. Dillard, Emory University; Cheri 

M. Hampton, Emory University; Courtney K. Ellison, Indiana 

University; Yves V. Brun, Indiana University; and Elizabeth R. 

Wright, Emory University.]

S-layer

Pili

Outer 

membrane

Inner 

membrane

a

c d

b
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

70 U.S. Department of Energy • Office of Biological and Environmental Research September 2017
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 71

Chapter 8 – Data Integration and Analysis

The streams of data produced by the techniques 

described in the previous chapters can be difficult to interpret unless the data are combined 

and synthesized into visual libraries or, ideally, computational models. Better methods are needed for assembling realistic models of complex biological systems. 

These methods must include the ability to connect 

to and seamlessly integrate multiple sources of 

experimental data, from genomics and proteomics 

to structural data at different scales (atomic to 

cellular, and beyond).

8.1 Current Science and 

Technologies

Integrating Analyses Across Scales

Although integrative analysis across scales can be very 

powerful (see Fig. 8.1, p. 72), it is often performed manually. Showing great promise is the recent development 

of methods that integrate information from multiple 

experimental sources to create models or ensembles of 

models, consistent with the data (Russel et al. 2012). 

Still, these methods fall short of generating models that 

cross multiple length scales, and they do not yet address 

the time domain. Fortunately, researchers are discussing data formats and relationships that would support 

integrative models emerging from multiple experimental approaches (Sali et al. 2015) that also include 

dynamics. These new classes of models potentially can 

provide rich information across the spatial and temporal scales that were the subject of the workshop.

Data Integration 

and Analysis

Chapter 8
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72 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

The creation of integrative models can reach such a 

scale and scope that the data they generate rapidly 

become a peta- to exascale computing challenge, 

especially when coupled with data from the simulation of dynamics. Data handling, visualization, 

and computation, including integrative modeling, 

will benefit from access to state-of-the-art supercomputing facilities typically housed in national 

laboratories. Investigators supported by the Biological Systems Science Division within the U.S. 

Department of Energy’s (DOE) Office of Biological 

and Environmental Research (BER) are studying a 

Fig. 8.1. Examining the 

Impacts of DNA Compaction in 

Escherichia coli Using Multiple 

Techniques: An Example Use 

Case. Applying multiple experimental techniques enables 

elucidation of the molecular 

mechanisms underlying the 

role of DNA compaction in gene 

expression in E. coli. The histone 

(HU) proteins were imaged at 

different resolutions and stages 

using X-ray crystallography and 

small-angle X-ray scattering 

(SAXS) capabilities. The crystallography provides atomic-level 

details of how the HU proteins 

interact with the bacterial DNA, 

while SAXS shows how the HU 

proteins assemble and affect 

the longer DNA strands in a 

solution. X-ray tomography 

reveals the natural contrast in 

organic material in as close to 

a living state as possible and 

provides quantitative comparisons of how compacted the 

chromosomes are in pathogenic 

and normal E. coli strains. [Image 

courtesy Michal Hammel, 

Lawrence Berkeley National 

Laboratory.] 

large landscape of temporal dynamics ranging from 

picoseconds to microseconds (for probing enzyme 

activity) to days or even weeks (for understanding 

subcellular reorganization). Advances in both hardware and software will be required to empower the 

modeling of whole biosystems with fine-grained resolution. For example, these models would simulate 

the motion of individual molecules and macromolecules over milliseconds to hours. Such simulations 

could be used to better understand the flow of 

metabolites between cells, the active transport of 

small molecules across cell membranes, dynamics 

of the molecular machines responsible for cycling 

Wild Type E. coli Invasive E. coli

X-Ray Crystallography

Small-Angle X-Ray Scattering

Soft X-Ray Tomography
Chapter 8 – Data Integration and Analysis

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 73

of elements, and other fundamental processes that 

cannot be measured directly by experiment.

Big Data and High-Performance 

Computing

Many of the imaging techniques described in this 

report are entering the era of big data, where the 

sheer volume of acquired data and variables requiring 

analysis have become intractable for rapid processing 

with personal computers. Consequently, the research 

community’s continued access to high-performance 

computing (HPC) is essential, as is the development 

of new informatics resources that can support automated integration of the hundreds of disparate data 

types generated by new technologies. These technologies include graph database representations of scientific concepts guided by researcher expertise and 

community models, along with real-time machine 

learning and inference. Also needed to support 

scientific discovery are new advances in automated 

processing, registering, overlaying, visualizing, and 

interpreting multimodal or multivariable data.

Currently, access to instrumentation, experts, or 

computational resources is rapidly becoming the 

limiting factor for many bioimaging experiments. As 

these capabilities become widely available or more 

efficient for fast data acquisition, the net result will 

be a continuation of near-exponential growth in 

data flow. Concomitant needs arising are improved 

data handling, archiving, and compressing. Ultimately, the real strength of improved HPC for data 

analysis and modeling will come from developing 

an iterative workflow in which experiment refines 

theory and theory drives next-level experimentation 

to enhance the efficiency of biosystem optimization. The following sections summarize the computational challenges currently faced in multiscale 

simulations of large biological systems and in data 

Conducting Multiple, Systematic Tests 

with Control over Variables

Systematic testing to gather statistics, multiple 

angles of attack to confirm direct linkages, and 

the ability to control variables for assembling data 

needed for realistic biological models.

• Biological experiments to test hypotheses of 

biosystem function.

• Integration and automation methods for 

sampling, acquisition, processing, and modeling bioimaging data to efficiently optimize 

phenotypes.

• Data and management methods to realistically model complex biological systems.

• Improved tools to automate visualization 

tools.

New Data Analysis Approaches

Mathematical and computational approaches for 

analyzing large datasets to provide models of complex systems with fundamental details at atomic and 

molecular scales.

• New mathematical approaches to employ 

the publicly accessible resources of large, 

raw datasets.

• Integration of molecular with genomic 

data to elucidate sequence-structurefunction relationships.

• Technologies to make use of emerging 

insights, such as the productive use of 

complete X-ray diffraction and diffuse scattering data.

• New algorithms and standards to automate 

extraction, classification, and visualization 

of features available in large tomographic 

datasets.

Data Integration and Analysis Needs
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

74 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

analysis via atomic-resolution crystallography and 

microscopy methods.

8.2 Major Challenges 

in Data and Computation

Clearly, atomic-scale modeling is approaching the 

mesoscale, and within 5 years the first atomic-scale 

cell simulation likely will become reality. New 

tools in this arena, such as cellPACK (see Fig. 8.2, 

this page; Johnson et al. 2015) and LipidWrapper 

(Durrant and Amaro 2014) automate and enable 

the construction of molecular models of subcellular 

environments. However, with the petascale computing available on DOE machines during preparation 

of this report, simulations of such models [e.g., 

roughly 180 million atoms, using classical, Newtonian, and molecular dynamics (MD) simulations] 

are able to achieve only dynamic time scales on 

the order of hundreds of nanoseconds (Zhao et al. 

2013; Yu et al. 2016).

Anticipating Exascale Simulation 

of Cellular Systems

A major need is the development of exascale computing architectures that allow for massively parallelizable MD codes. Typically, these codes spatially 

decompose the biosystems in the parallelization 

scheme and therefore scale well with processor 

count, but only if the computing platforms have 

fast interprocessor communication. With exascale 

computational architectures, the sampling of longer 

and more relevant biological time scales (milliseconds) for these large-scale systems will shed light 

on myriad biological processes in realistic in silico

environments. HPC systems on the order of billions 

of atoms (micrometers in dimension; e.g., a fullsized cell) will be able to scale to millions of cores. 

Fig. 8.2. Data-Centric, Data-Driven Modeling Environment. CellPACK enables assembly of models that are consistent with 

many different types of datasets, such as proteomics and genomics, fluorescence microscopy, electron microscopy (EM), and 

X-ray crystallography. The total system volume can be divided into different subvolumes using surface definitions from, for 

example, EM data. Formulas for different system subcompartments can be parameterized and used to generate model ensembles consistent with observed data. [Reprinted from Macmillan Publishers Ltd: Nature Methods. Johnson, G. T., et al. 2015. 

“cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology,” Nature Methods 12(1), 85–95. © 2015.]

Molecular 

ingredients

Surface 

containers

cellPACK

Mesoscale 

molecular model
Chapter 8 – Data Integration and Analysis

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 75

Exascale machines should be equipped with large 

memory nodes to facilitate data processing and 

analysis directly at the computing site, obviating the 

need for moving petabyte-scale datasets between 

sites. Also needed are powerful visualization capabilities that allow researchers to interact with their 

data remotely, both during and after a simulation, 

all without having to transfer the data to their own 

institutions.

Using Enhanced Sampling 

and Multiscale Approaches

Along with exascale simulations of image systems, 

researchers can extract great value from long time 

scale simulation of smaller molecular and macromolecular components with classical MD and 

with so-called enhanced sampling approaches 

(Bernardi et al. 2015). Further development of new 

theoretical or statistical frameworks for simulation 

analysis presents a different set of challenges and 

requirements. For example, the use of Markov state 

models (Malmstrom et al. 2015; Plattner and Noe 

2015; Meng et al. 2016) or milestoning (Faradjian and Elber 2004) now enable the extraction of 

long time scale dynamics (milliseconds to seconds) from many short time scale simulations for 

single-molecule biosystems. Such methods benefit 

from execution on independent graphical processing 

units (GPUs) where interprocessor communication is less of a bottleneck compared to the previously described large spatial systems. Multiscale 

methods embody another set of approaches that 

can seamlessly combine different levels of theory 

or resolution, for example, quantum mechanics 

and molecular mechanics (Chudyk et al. 2014) or 

MD and Brownian dynamics (Votapka and Amaro 

2015), to increase accuracy or access longer time 

scales and larger length scales. Another multiscale 

method class is represented by the hierarchical integration of sets of approaches carried out at different 

scales, where the development of one cohesive 

model is obtained through the interchange of key 

parameters across model scales (Boras et al. 2015; 

Mih et al. 2016; Yu and Bagheri 2016). Capabilities 

on exascale platforms will bring seconds-long 

simulations of macromolecules into routine 

practice, enabling connections to experiments at 

orders-of-magnitude longer time scales than is possible today (i.e., milliseconds, routinely).

Atomic-Scale Spatial and Temporal Data

Crystallography, nuclear magnetic resonance 

(NMR), and, more recently, single-particle cryoEM 

provide some of the highest-resolution information 

at atomic and molecular scales. This information 

usually is interpreted with individual structural 

models but is increasingly useful for supplying the 

fundamental atomic detail for multiscale, integrative 

models. While the isolated structures are highly 

useful, such as in enzyme engineering (Campbell 

et al. 2016), high-resolution structural approaches 

potentially could be used to help “divide and conquer” larger, more complicated systems (Chiu et al. 

2006; Ward et al. 2013). Additionally, new light 

sources, such as the X-ray free-electron laser (XFEL) 

at DOE’s Linac Coherent Light Source (LCLS) 

at the SLAC National Accelerator Laboratory, are 

enabling resolution of atomic details as a function of 

time (Levantino et al. 2015). The internal motions 

of macromolecules are key to their function, so 

researchers could use these new capabilities to visualize how natural and engineered enzyme variants 

differ, potentially improving the further rational 

design or interpretation of mutations (Bhabha et al. 

2015). In addition, the acquisition of time-resolved 

data at near-atomic resolution is valuable for 

improving simulation force fields, which, in turn, 

will enable the development of more predictive and 

dynamic models of biosystems (van den Bedem and 

Fraser 2015; Kupitz et al. 2017). As atomic-scale 

information becomes richer through pushing the 

boundaries of spatial and temporal resolution, several computational challenges must be addressed.

The LCLS pulse of 120 hertz frequency enables 

image collection at that rate (White et al. 2015). 

Larger detectors will be needed to capture 

higher-resolution details, with a large dynamic 

range to properly measure low-resolution data. 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

76 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Typical data collection runs currently generate 

many terabytes (TB) of data. Future pulse rates 

can increase this data rate by more than 2 orders of 

magnitude. At this scale, data storing, transferring, 

and processing represent a significant challenge. 

With the use of imperfect sample introduction 

tools resulting in some collected images that are 

seemingly devoid of data, current emphasis is 

on sorting blank images from those that contain 

“meaningful information.” This has driven development of new algorithms and software (Ginn et al. 

2016), which will need further refinement. Additionally, sample introduction tools are improving, 

so hit rates for serial crystallography experiments 

(see box, Serial Crystallography, this page) are 

increasing (Fromme et al. 2015; Oghbaey et al. 

2016; Fuller et al. 2017). If all images with any nonbackground intensity should be saved, then new 

raw data repositories likely will be needed. 

The current best practices require deposition 

only of data that are used to calculate structures. 

Repositor examples include the SBGrid’s Structural 

Biology Data Grid (Meyer et al. 2016), Coherent 

X-ray Imaging Data Bank (Maia and Hajdu 2016), 

and others (Kroon-Batenburg et al. 2017). However, this practice may limit downstream research 

to mine data not included in the original analysis. 

Looking to the future, the ability to store and 

provide global access to original datasets could 

enable DOE researchers to return to these datasets 

and extract additional value, unseen at the time 

of acquisition.

The most exciting experiments will rely on realtime data processing to optimize serial crystallography experiments on the fly (Lyubimov et al. 

2016), requiring new capabilities and algorithms. 

Moreover, several of the most exciting directions 

in X-ray data processing involve interpreting the 

weakest signals, that is, diffuse (Wall et al. 2014) or 

continuous (Ayyer et al. 2016) intensities, which 

are much harder to distinguish than sharply peaked 

Bragg intensities (Van Benschoten et al. 2016); see 

Fig. 8.3, p. 77). The ability to perform this interpretation efficiently as data are collected has great 

ramifications, as the volume of data needing transfer 

and maintenance potentially can be reduced massively on site.

Major challenges in data representation involve 

accurate representation of multiple conformations (Woldeyes et al. 2014), data uncertainty 

(Terwilliger et al. 2007; Lang, P. T., et al. 2014), 

and time-dependent evolution of the conformational ensemble (Aranda et al. 2006). Particularly 

appealing is the potential for additional data (1) in 

time-resolved experiments (Schmidt et al. 2013), 

(2) in multiple temperatures (Keedy et al. 2015b), 

or (3) from diffuse scattering (Van Benschoten et al. 

2016) to constrain the modeling of multiple conformations (Burnley et al. 2012; Keedy et al. 2015a).

Determining Biological Processes 

with Microscopy and Tomography

Single-particle cryo-electron microscopy 

(cryoEM) has advanced to the point where full 

atomic models can be obtained for protein components in viruses, membrane proteins, filaments, 

and molecular machines (Liao et al. 2013; Zhang 

et al. 2013; Amunts et al. 2014; Bartesaghi et al. 

2014; Galkin et al. 2014; Lu et al. 2014; Wang et al. 

2014). Additionally, cryo-electron tomography 

(cryoET) of frozen, hydrated cells and organelles (Li and Jensen 2009; Davies et al. 2012) has 

enabled subnanometer-resolution structural snapshots of molecular machines in different functional 

states inside the cell under true in situ conditions 

(Mahamid et al. 2016). These recent advances in 

Serial Crystallography

This important new crystallography approach 

was developed at X-ray free-electron lasers 

(XFELs), which exploit the diffract-beforedestroy phenomenon made possible by very 

powerful, short (femtosecond) X-ray pulses. 

More recently, the method has been translated 

to high-brightness synchrotron X-ray sources.
Chapter 8 – Data Integration and Analysis

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 77

both cryoEM and cryoET can provide answers 

to mechanistic questions related to the structural 

dynamics of macromolecules key to many biological processes in gene duplication, translation, 

protein trafficking, protein homeostasis, metabolite 

transport, signal transduction, and responses to 

environmental stresses.

Improved Image Processing and CryoEM. To 

obtain a complete description of these biological 

processes, determining multiple structures at different steps of the processes at different times will 

be necessary. The resulting high-quality data explosion resulting from cryoEM experiments (as well 

as serial crystallography experiments at XFELs and 

synchrotrons) represents an immediate challenge 

for data management, processing, and visualization. 

For example, with the current generation of detectors and reasonable measures for compression, a 

typical cryoEM exposure for a single-particle grid 

area occupies 2 to 4 gigabytes of disk space. At 1,000 

exposures per day, that total amounts to roughly 4 to 

5 TB of collected raw data per day. Inevitably, with 

single-particle data having multiple conformations, 

use of sophisticated algorithms to sort out heterogeneous data will become the norm rather than the 

exception. Such data processing is CPU intensive 

and requires more efficient computational algorithms to reduce data processing time and to include 

structure validation and error measurements. Such 

sophisticated and improved image processing has 

not yet been developed. Final structures, which 

generally are represented by atomic models, must 

be validated and annotated, with their positional 

accuracy quantified. A consensus of metrics to 

report cryoEM structure has not yet emerged from 

the cryoEM community.

* Hinge point

* * *

Fig. 8.3. Diffuse Scattering and Bragg Scattering. (Left) A protein molecule is shown in ribbon format, and contains two 

domains connected by a hinge (marked with an asterisk). The intensities of crystallographic Bragg scattering provide information about the mean squared displacements of atoms, which can be interpreted as the motion of these domains (arrows 

indicate the extent of the motion for each domain). However, the correlations between these motions are lost in the Bragg 

scattering. (Middle) Fortunately, the diffuse scattering between the Bragg peaks contains information about the correlations. 

The rainbow colors indicate the sequence of conformations traced as the domains move. In the left model, when one domain 

moves down so does the other; whereas in the right model, the domains move toward and then away from each other in a 

closing and opening motion. The functional implications of these two modes of motion may be profound. (Right) The diffuse 

scattering between and around the sharp Bragg peaks (deep orange) is shown in a representative diffraction image. [Image 

courtesy James Fraser, University of California San Francisco.]

OR
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

78 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

CryoET and Improved Visualization. For cell 

tomograms obtained by cryoET, the data interpretation challenge is to annotate and segment the 

three-dimensional (3D) tomograms of crowded 

subcellular features (see Fig. 8.4, this page). The 

incomplete data resulting from limited specimen 

tilt angles present challenges in confidently recognizing subcellular components. Automated algorithms must be developed to (1) identify features 

of interest to avoid subjectivity and increase 

throughput; (2) extract subvolumes for classification, alignment, image correction, and averaging; 

and (3) assess the reliability and resolution of the 

resulting structures. In addition to zooming in on 

specific subcellular features, cryoET provides an 

opportunity to generate new hypotheses regarding 

structure and function relationships of subcellular 

organization, as suggested by direct visualization. 

Similar challenges are confronting the study of 

plant tissues or biofilm imaging by Fourier transform infrared microtomography (FTIR μTomography; Martin et al. 2013). Therefore, developing 

user-friendly visualization tools will be key to 

enabling scrutinization of the complex and crowded 

density maps enriched with various features. Feature discovery and conformational dynamics in 

the cellular context will require both statistical and 

visualization tools to reveal them. Furthermore, 

disseminating such multidimensional data to other 

scientists is currently challenging; therefore, new 

standards for data representation and protocols for 

data transfer are needed.

Other Structural Bioinformatics. In addition to 

the structure data generated by cryoEM and cryoET, 

or chemical data generated by FTIR μTomography, 

a timely consideration is the correlation of the spatial and temporal information with other structural 

bioinformatics such as crystal structures and fluorescence imaging, simulation dynamics, and proteomic 

and genomic data. Integrated structural information 

coupled with genomics certainly will be a driving 

force for biology in the coming decades.

8.3 Advancing Computational 

Platforms for Large-Scale Data 

Processing and Analysis

Continued development of imaging and microscopy tools that enable general, highly detailed 3D 

images of cells via serial block face (i.e., volume) 

imaging (Denk and Horstmann 2004) currently 

are and will continue to present data and computing challenges at scale. In addition, developments 

in biophotonics and image capture will enable, in 

time, the extension of these volume images as the 

fourth dimension. Large-scale image processing 

capabilities (e.g., to visualize microbial communities 

Fig. 8.4. Annotation (currently performed manually) of Cryo-Electron 

Tomography of a Cyanobacterium 

Infected with a Syn5 Cyanophage. 

(a) Slice of a tomogram. (b) Annotated subcellular components in 

the three-dimensional tomogram. 

[Reprinted by permission from 

Macmillan Publishers Ltd: Nature 

Protocols. Dai, W., et al. 2017. “Zernike 

Phase-Contrast Electron Cryotomography Applied to Marine Cyanobacteria Infected with Cyanophages,” 

Nature Protocols 9(11), 2630–42. 

© 2014.]
Chapter 8 – Data Integration and Analysis

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 79

and their interactions and growth over time) will 

be needed to handle volumes of single-image data 

on the order of 10 TB and greater. These capabilities will be necessary to train machine-learning 

algorithms to select key biological features from 

the images in an automated fashion, thus accurately 

and rapidly identifying and segmenting the molecular, macromolecular, and subcellular components 

and, ultimately, allowing realistic 3D or 4D cell 

imaging. The potential application of deep-learning 

algorithms for automated, unsupervised learning 

and subsequent data processing is likely to be a key 

area of relevance for BER researchers. These efforts 

will require (1) access to multicore, large-memory 

machines with ultrafast input/output capabilities; 

(2) low-latency and high-bandwidth communication, GPUs, or many integrated cores (MICs) 

for fast, large-matrix mathematics; and (3) faster, 

larger-memory hierarchies for data and model 

parameter staging to drive developments.

A related set of challenges involves the intelligent 

processing of data from experimental sources 

(i.e., mainly microscopy), where advances in applied 

mathematics are needed to address gaps. Current 

algorithms for biological cryoEM of macromolecular components scale to that of Extreme Science 

and Engineering Discovery Environment (XSEDE) 

resources but with inefficient algorithms that are 

incapable of handling sparse datasets. New mathematical methods and advances are needed for 

microscopy related to the cell’s macromolecular 

components, as well as for larger-scale (i.e., volume) 

imaging and other imaging techniques that currently 

could scale to exascale computing but do so inefficiently. Investments in these foundational components can maximize output from exascale platforms.
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

80 U.S. Department of Energy • Office of Biological and Environmental Research September 2017
September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 81

Chapter 9 – Summary and Conclusions

Within the U.S. Department of Energy (DOE), 

the Office of Biological and Environmental 

Research (BER) supports fundamental research 

on complex biological processes to address some of the most 

challenging, long-term energy and environmental issues relevant to DOE BER's mission. The approach to this research, 

managed by BER’s Biological Systems Science Division 

(BSSD), seeks to understand the processes controlling the 

translation of information encoded in the genomes of plants 

and microbes into expressed phenotypes. Gaining an understanding of these mechanisms will lead to improved understanding, manipulation, and design of biological processes 

for a range of beneficial purposes. The study of plants and 

their microbial communities exemplifies the complexity of 

this type of research (see Fig. 9.1, p. 82). Reaching a comprehensive understanding of plants requires research from the 

molecular to the organismal scale, over time periods spanning 

picoseconds to years. Structural and characterization studies 

are needed at vastly different length scales, and they must 

be coupled with an understanding of genomic, proteomic, 

metabolomic, and phenotypic variations.

The presentations and discussions at the Technologies for 

Characterizing Molecular and Cellular Systems Relevant to 

Bioenergy and Environment workshop encompassed very 

diverse areas of research relevant to BER missions. However, these participant interactions brought to light several 

common themes. Perhaps not surprisingly, there is a general 

enthusiasm for increasing the spatial resolution of analysis 

methods, consistent with expressed research needs. Similarly, 

there is increased awareness of the need for methods to probe 

the time dimension in biology. Measuring and following the 

dynamics of biological systems are challenging but key to 

Summary and 

Conclusions

Chapter 9
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

82 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

understanding how microbes and plants function 

and react to their environment and each other. 

Another theme spanning the research topics was 

the ability to measure not only structure (i.e., where

things are), but also chemistry (i.e., what things are 

and how they function). A particular challenge is 

being able to simultaneously measure chemistry 

and structure at high resolution. Finally, for many 

BER-relevant science issues, an important challenge 

is the ability to conduct measurements in situ as 

well as in the laboratory. Figure 9.2, p. 83, charts the 

broad range of imaging methods, as well as their 

length and time scales, that are (1) mature but being 

developed further, (2) under development now, or 

(3) need to be developed in the near future. These 

technologies either are now available to DOE BER 

researchers or could be in the future after they have 

been developed further.

Fig. 9.1. Multiscale Studies of Plant and Microbial Systems and Their Interactions. This illustration highlights the significance of understanding plant and microbial systems and their interactions across hierarchically complex levels of organization 

from the whole plant and tissue levels to the cellular, subcellular, and microbial community levels. Aboveground system: 

(1) Lignocellulosic biomass consists of heterogeneously composed stem biomass. (2) Cell growth and cell wall biosynthesis 

and remodeling are tightly regulated and coordinated across various subcellular compartments in response to internal and 

external cues. (3) The trans-Golgi network plays a central role in cell wall biosynthesis via transport of proteins (i.e., cellulose 

synthase complex and wall glycoproteins) and precursors (i.e., hemicellulose, pectin, and lignin) involved in wall polymer synthesis. (4) Understanding the effect of nucleotide sequence variation on protein structure and activity (i.e., sequence-function 

continuum) is critical for understanding and predicting functional outcomes of feedstock improvement programs based on 

advanced breeding or biosystems design strategies. Belowground system: (5) Plant roots and their associated microbial communities (in the rhizosphere) interact for mutual benefit. Microbial communities acquire sugars and other materials from plant 

roots and assist plant hosts with nutrient and water acquisition, provide pathogen defense, and mediate transformation of root 

tissues into soil organic matter. (6) From this plant-microbial association, soils are further developed into groups of soil particles 

(i.e., aggregates) that consist of plant and fungal debris; microbially derived organo-mineral associations; mycorrhizal fungal 

hyphae; organic matter colonized by saprophytic fungi, clay, and polysaccharides; and other pore-space chemicals. [Image 

courtesy Udaya Kalluri, Oak Ridge National Laboratory. Soil aggregate illustration (6) modified from Jastrow and Miller 1998.]
Chapter 9 – Summary and Conclusions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 83

Fig. 9.2. Spatial and Temporal Resolutions of Imaging Technologies. Summary of imaging and other selected measurement 

technologies discussed at the workshop. Mature technologies that will benefit from further development include X-ray and 

neutron crystallography and scattering, scanning probe microscopies, X-ray tomography, synchrotron spectroscopy, and confocal microscopy. Techniques undergoing rapid development and with potential application to the mission of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) include X-ray free-electron laser ultrafast diffraction, 

time-resolved X-ray scattering, cryo-electron microscopy (cryoEM) and cryo-electron tomography (cryoET), infrared imaging 

methods, super-resolution fluorescence imaging. New technologies not yet fully developed and applied to research supported 

by BER’s Biological Systems Science Division include dynamic EM, fluctuation scattering, ptychography, and in soil sensors.

Key: Å, Angstrom; EXAFS, extended X-ray absorption fine structure; fs, femtosecond; ks, kilosecond; μm, micrometer; μs, 

microsecond; mm, millimeter; ms, millisecond; nm, nanometer; ns, nanosecond; ps, picosecond; s, second; SAXS, small-angle 

X-ray scattering; SEM, scanning electron microscopy; TEM, transmission electron microscopy; TIRF, total internal reflection 

fluorescence; USANS, ultrasmall-angle neutron scattering; WAXS, wide-angle X-ray scattering; XANES, X-ray absorption near 

edge structure.

Workshop participants agreed that multimodal 

methods will be required for many of the research 

needs discussed. Increasingly, as structural biology 

and imaging methods are converging, multiscale, 

multidisciplinary approaches to plant and microbial 

cell biology are emerging. This evolution will be 

important, particularly for approaches that couple 

structural and chemical imaging to provide comprehensive characterization. Ideally, the combination 

of structural imaging and labeling methods that 

pinpoint the location of specific molecules has the 

potential, over time, to dramatically change the 

understanding of microbes, microbial communities, 

and plants. The ability to accurately track molecules 

in unfixed biological systems with single-molecule 

precision will greatly enhance the modeling of 

molecular function in the cell, especially when 

coupling that process with higher-resolution studies 

of enzymes.

BSSD has a long history of developing and supporting the use of genomic characterization of biological 

systems. This, in part, has led to the high-throughput 

DNA sequencing technology available to researchers 

worldwide. In more recent years, genome sequencing 

has vastly outpaced genome writing and the ability to 

Temporal Resolution

X-ray Free-Electron Laser Ultrafast X-ray Diffraction

Synchrotron X-ray 

 Macromolecular 

 Crystallography

• Synchrotron Time-Resolved SAXS/WAXS

• Fluctuation Scattering

Neutron Macromolecular

Crystallography

10 ks

1 ks

100 s

10 s

1 s

100 ms

10 ms

1 ms

100 μs

10 μs

1 μs

100 ns

10 ns

1 ns

100 ps

10 ps

1 ps

100 fs

10 fs

Spatial Resolution

• Single Particle CryoTEM

• Electron Crystallography

• Micro-Electron

 Diffraction

• CryoTEM

 Tomography

Scanning Probe

Microscopy

Dynamic TEM

Super-Resolution Fluorescence

• Single Molecule

 Tracking

• TIRF

• Confocal Microscopy

• Coherent Raman

Focused Ion Beam/SEM

Small Angle

 Neutron Scattering/

 USANS Ptychography

Synchrotron Transmitted X-ray

 Microscopy and Tomography

• Synchrotron XANES 

• Synchrotron EXAFS

Synchrotron FTIR Nanoscopy and Tomography

Nano-SIMS In Soil Sensors

Neutron

Radiography

and 

Tomography

0.1 Å 5 Å 1 nm 5 nm 10 nm 50 nm 100 nm 500 nm 1 μm 10 μm to 1 mm
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

84 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

interpret genome function. Methods for characterizing biological processes at the molecular and cellular 

level, important for inferring function, certainly are 

less mature, and there is a great opportunity for their 

further development to address issues of genomecoded function. Therefore, to enable more comprehensive systems biology–based approaches, which 

typically require measurements be made on many 

samples, workshop participants highlighted the 

need for development of highly sensitive methods to 

provide accurate measurements from small sample 

volumes. In addition, methods need to be operable 

in high-throughput or highly parallel modes to 

enable rapid query of biological systems for data that 

then can be fed iteratively back into the experiment. 

Achieving these two goals is critical to enabling predictive engineering of biological systems. Although 

much of the discussion at the workshop centered on 

measurement, participants also noted that further 

development of manipulation technologies is critical. 

Biosystems design has the potential to revolutionize 

the way biology is exploited to produce economically 

valuable molecules; however, this will be possible 

only if high-throughput measurement technologies 

are combined with tools for precise genetic manipulation and computational algorithms are devised 

for accurate prediction of phenotype resulting from 

genome manipulation.

Recent technology developments are expected to 

address some of the needs raised at the workshop. 

For photon sources, the successful implementation 

of the X-ray free-electron laser (XFEL) technology, first implemented at the Linac Coherent Light 

Source at SLAC National Accelerator Laboratory, 

has made available unprecedented time scale 

measurements. The unique properties of XFEL 

sources have generated several new approaches for 

studying biological systems—for example, serial 

femtosecond X-ray crystallography (SFX), fluctuation X-ray scattering, and diffractive imaging. In 

the future, upgrades to these XFEL facilities will 

enable the exploitation of lower photon energies, 

higher repetition rates, and even shorter pulse 

lengths. Some methods developed at XFELs can 

be implemented at the DOE synchrotron photon 

sources, particularly the National Synchrotron Light 

Source II at Brookhaven National Laboratory with 

its double-bend achromat lattice, where bright and 

almost coherent life science beamlines were recently 

commissioned. Planned upgrades at the Advanced 

Photon Source at Argonne National Laboratory 

and Advanced Light Source at Lawrence Berkeley 

National Laboratory will incorporate multibend 

achromatic technologies to provide researchers with 

diffraction-limited photon sources that produce 

extremely bright and coherent hard and soft X-rays, 

respectively. This will enable (1) high-brightness 

experiments that currently are only possible at 

FEL sources, such as SFX and fluctuation scattering, and (2) completely new methods, such as 

long-wavelength ptychography that can use X-ray 

scattering to image both structure and chemistry.

Nuclear magnetic resonance (NMR) approaches 

have a lower spatial resolution but can be performed 

on living cells to provide information on native 

states of cellular lipids, nucleic acids, polysaccharides, and proteins. The development of higher-field 

magnets will enable the accurate measurement 

of increasingly dilute samples. Instruments with 

increased sensitivity and resolution will enhance 

the ability of NMR to quantify metabolic changes 

and identify intracellular processes. Ultrahigh fields 

will provide access to multinuclear NMR, with sufficient sensitivity and resolution to analyze multicomponent systems with isotopic labeling. These 

fields also will enable the analysis of intrinsically 

disordered macromolecules and low-population 

transition states. The ability of NMR to probe the 

dynamics of molecules in solution is of particular 

importance for the modeling and simulation of 

biological complexes.

Mass spectrometry (MS) technologies continue to 

evolve rapidly, with a strong focus on improved spatial and temporal resolution. Desorption ionization 

techniques such as nanoscale secondary ion mass 

spectrometry (nanoSIMS) and matrix-assisted laser 
Chapter 9 – Summary and Conclusions

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 85

desorption ionization (MALDI) are now routinely 

used for imaging complex samples such as tissue sections. These technologies are moving into the subcellular regime, enabling quantitative interrogation 

of single cells and organelles in situ (Steinhauser and 

Lechene 2013; Caprioli 2016). Software tools such 

as Skyline have made targeted MS a viable alternative for rapid, highly reproducible quantitative analysis of the temporal dynamics of complex systems 

(i.e., proteomics and metabolomics; MacLean et al. 

2010; Glukhova et al. 2013). Top down approaches 

to analysis of intact proteins provide an integrative 

view of sequence variations, post-translational modifications, and three-dimensional (3D) structure, 

enabling a tighter coupling between quantitative 

functional studies and structural biology (Durbin 

et al. 2016). The development of new ion-separation 

technologies, such as structures for lossless ion 

manipulations (SLIM; Deng et al. 2017) will 

increase resolution and sensitivity while substantially simplifying the design of high-performance 

MS systems.

The development of new technologies first must 

be tightly coupled with driving research questions 

and, second, must be disseminated to the broad 

research community in easy-to-access forms. The 

former suggests continued efforts to build multidisciplinary research programs that bring together 

biological researchers and technology developers; 

while the latter requires consideration of a variety of 

different mechanisms for technology dissemination 

and the practical, hands-on training of biologists. 

The facility model has been remarkably successful 

for many technologies—DOE-supported synchrotrons, XFEL, and neutron sources have led the way 

in efficiently providing expert technical resources to 

a diverse research community. This same model is 

expected to be very successful for emerging techniques such as single-particle cryo-electron microscopy (cryoEM) and cryo-electron tomography 

(cryoET). The dissemination of imaging technologies often has been more ad hoc than facility-based 

structural biology methods, with researchers 

initially needing to build their own instruments on 

the basis of prototypes developed by others. Only 

after significant long-term efforts do these new 

technologies mature to the point of being commercially available. DOE BER–supported user facilities, 

the Environmental Molecular Sciences Laboratory 

and Joint Genome Institute, have provided researchers with access to newly commercialized as well as 

further customized technologies through their user 

programs. The Howard Hughes Medical Institute 

has taken this concept one step further through the 

creation of the Advanced Imaging Center at Janelia 

Farms, which makes imaging technologies it developed available to the scientific community before 

the instruments are available commercially. Finally, 

there is the challenge of introducing technologies 

to the broader BER research community. The BER 

Facilities Integrating Collaborations for User Science (FICUS) program provides an excellent example of how providing access to multiple technologies 

through an organized program can stimulate new 

science (Solomon et al. 2016). Extension of this 

program to include other user facilities, such as the 

synchrotron light and neutron sources, potentially 

can introduce many researchers to technologies that 

will enable their research.

Throughout the workshop, the important role of 

computation was discussed many times. The need for 

new measurement and manipulation technologies to 

enable future research was clear, but this is accompanied by the need for improved computational 

methods. Without new developments in computational methods and automation, researchers will not 

be able to fully exploit the wealth of information that 

current and new technologies will provide. Beyond 

the need for sufficient compute and data resources, 

new algorithms are needed to analyze experimental data to extract weak-signal or new information 

previously undetected. One particularly challenging 

problem is that of automated interpretation of 4D 

single-molecule imaging datasets, which can be terabytes in size and show the movements of molecules 

inside the cell over time. These datasets rise to the 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

86 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

level of big data and will require new computational 

approaches for automated feature extraction, dimensionality reduction, and interpretation. In general, 

automated annotation of complex structural and 

chemical imaging data remains an unsolved problem. This gap is compounded by the need for new 

algorithms that can integrate multiple data sources to 

provide an integrated picture of a biological system. 

This becomes a very challenging limitation when 

studying heterogeneous systems, such as microbes 

and plants, in which no two cells are exactly the 

same. New computational methods are needed to 

extract features and map them onto mathematical 

models for further analysis and simulation.

In conclusion, the workshop highlighted several 

BER research needs that would be greatly enhanced 

by further improvement of existing technologies and 

the development of new technologies for measuring 

and manipulating biological processes. Such innovative development is needed both for instruments 

at large-scale user facilities as well as for smaller 

laboratory-scale imaging instruments, techniques, 

and methods. Fully realizing the potential of these 

improved or new developments also will require 

new computational algorithms and the necessary 

computing resources.
Appendix A – Workshop Participants

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 87

Paul Adams (Chair)

Lawrence Berkeley 

National Laboratory 

Elizabeth Wright (Chair)

Emory University 

Rommie Amaro

University of California, 

San Diego 

Parastoo Azadi

Complex Carbohydrate 

Research Center

University of Georgia

Philip Benfey

Duke University

Joerg Bewersdorf

Yale University

Julie Biteen

University of Michigan

Wah Chiu

Baylor College of Medicine 

(Stanford University at time 

of publication)

Bob Cottingham

Oak Ridge 

National Laboratory

Shi‐you Ding

Michigan State University

Jose Dinneny

Carnegie Institution 

for Science

James Evans

Pacific Northwest 

National Laboratory

Matthew Fields

Montana State University

Brian Fox

University of Wisconsin

Madison

James Fraser

University of California 

San Francisco

Britt Hedman

Stanford University

Hoi‐Ying Holman

Lawrence Berkeley 

National Laboratory

Greg Hura

Lawrence Berkeley 

National Laboratory

Farren Isaacs

Yale University

Andrzej Joachimiak

Argonne National Laboratory

Udaya Kalluri

Oak Ridge 

National Laboratory

Ken Kemner

Argonne National Laboratory

Carolyn Larabell

University of California 

San Francisco

Sean McSweeney

Brookhaven 

National Laboratory

Michelle O’Malley

University of California 

Santa Barbara

Hugh O’Neill

Oak Ridge 

National Laboratory

Jennifer Pett‐Ridge

Lawrence Livermore 

National Laboratory

Ganesh Sriram

University of Maryland

Elizabeth Villa

University of California 

San Diego

Tuan Vo‐Dinh

Duke University

Workshop Participants

Appendix A
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

88 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Workshop Agenda

Day 1. Wednesday, September 21

8:30 a.m. Welcome Amy Swain

8:40 a.m. BER/BSSD Background Todd Anderson

9:05 a.m. Welcome from Co-Chairs Paul Adams and Liz Wright

Session 1. BER Enabling Activities – Moderator: Amy Swain

9:25 a.m. Facilities Integrating Collaborations for User Science (FICUS) Report Britt Hedman

9:45 a.m. TCMCS Bioimaging Principal Investigator (PI) Meeting Report James Evans

10:05 a.m. Light/Neutron Source Workshop Report Sean McSweeney

10:30 a.m. Break

Keynote Biology Presentation – Moderator: Liz Wright

10:50 a.m. The Bioenergy Research Centers: 

 Towards Renewable Lignocellulosic biofuels Paul Adams

Short Presentations

11:20 a.m. Tools for Structural Characterization of Polysaccharides and Glycoproteins Parastoo Azadi

11:35 a.m. Functional Annotation of Bioenergy Phylogenetic Space Brian Fox

11:50 a.m. Lignin Degradation by Soil Bacteria Andrzej Joachimiak

12:20 p.m. Lunch

Keynote Technology Presentations – Moderator: Paul Adams

1:30 p.m. Cryo-Electron Microscopy (EM): Investigations 

 from the Molecular to the Mesoscale Elizabeth Wright

1:50 p.m. Birth of the Cool: Multitemperature, Multiconformer 

 X-Ray Crystallography and Allosteric Control Jaime Fraser

Session 2. Cellular Ultrastructure and Physiology – Moderators: Jose Dinneny and Carolyn Larabell

2:10 p.m. Signaling Dynamics in Plant Root Cells Philip Benfey

2:30 p.m. Imaging subcellular behavior at the molecular scale Julie Biteen

3:00 p.m. Break

Short Presentations

3:30 p.m. Opening Windows into the Cell: Bringing Structure and 

 Molecular Context to Cell Biology using Cryo-EM Elizabeth Villa

3:45 p.m. Fourier Transform Infrared (FTIR) Spectroscopy Imaging: 

 Investigations of Cellular Chemistry from Microns to Nanoscale Hoi-Ying Holman

Technologies for Characterizing Molecular and Cellular Systems (TCMCS) 

Relevant to Bioenergy and Environment

September 21–23, 2016

Hilton Washington, D.C./Rockville Hotel

Appendix B
Appendix B – Workshop Agenda

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 89

4:00 p.m. Fluorescence Microscopy with Three-Dimensional, 

 Sub-20 nanometer Resolution Joerg Bewersdorf

Breakout Discussions ( Jackson and Monroe Rooms)

4:30 p.m. Metabolic Pathways in Plants, Microbes, and Fungi Jose Dinneny

 Cellular Structure, Organization, Signaling, Networks Carolyn Larabell

6:00 p.m. Breakout Session Reports Paul Adams and Liz Wright

6:30 p.m. Adjourn

Day 2. Thursday, September 22

Technology Keynote Presentations – Moderator: Liz Wright

8:30 a.m. Multiscale Dynamics: Molecules to Cells Rommie Amaro

8:50 a.m. Plasmonic Nanoprobe Technology for Monitoring 

 Genomic Biomarkers and Molecular Pathways Tuan Vo-Dinh

Session 3. Bioenergy and Bioproducts Production – Moderators: Shi-You Ding and Farren Isaacs

9:10 a.m. Exploiting Anaerobes for Biomass Breakdown and Sustainable Chemistry Michelle O’Malley

9:30 a.m. Fundamental Studies of Biomass Formation to Enable 

 Sustainable Biofuel Production Udaya Kalluri

10:00 a.m. Break

Breakout Discussions ( Jackson and Monroe Rooms)

10:20 a.m. Plant Cell Wall Composition and Degradation Shi-you Ding

 Synthetic Biology (Biosystems Design) Farren Isaacs

11:50 p.m. Breakout Session Reports – Moderators: Paul Adams and Liz Wright

12:20 p.m. Lunch 

Short Presentations

1:30 p.m. Neutron Technologies for Characterizing Molecular 

 to Mesoscale Biological Processes Hugh O’Neill

1:45 p.m. Combining Small-Angle X-Ray Scattering (SAXS) and 

 High-Resolution Structure for Synthetic Biology Greg Hura

2:00 p.m. Instationary Isotope Labeling Dissects Metabolic Cycles 

 in a Photoautotrophic Organism Ganesh Sriram 

Session 4. Environmental Microbiology – Moderator: Ken Kemner

2:30 p.m. Microbial Interactions at Different Scales Matthew Fields

2:50 p.m. Using Isotopes and Imaging to Track Microbe-Mineral Interactions Jennifer Pett-Ridge

3:30 p.m. Break

Breakout Discussions ( Jackson and Monroe Rooms)

4:00 p.m. Community interactions including rhizosphere Jennifer Pett-Ridge

 Biogeochemical cycling of elements Ken Kemner

5:30 p.m. Breakout Session Reports – Moderators: Paul Adams and Liz Wright
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

90 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

6:00 p.m. Day 1 and 2 Summary

6:30 p.m. Adjourn

Day 3. Friday, September 23

Session 5. Community Access to Technology – Moderators: Paul Adams and Liz Wright

8:30 a.m. Cryo-EM Research Resource and Training to a Broad Community Wah Chiu

8:50 a.m. DOE Knowledgebase (KBase) Capabilities and Extension to Address 

 Computation and Data Challenges for Systems Biology Research Bob Cottingham

9:15 a.m. Round Table Discussion of the Charge Questions Paul Adams and Liz Wright

10:00 a.m. Break

10:30 a.m. Develop Plan for Workshop Report Writing and Action Items Paul Adams and Liz Wright

12:00 p.m. Adjourn
Appendix C – Figure Credits

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 91

Figure Credits

Appendix C

Cover, Figure 1.1., and 

chapter front images 

(clockwise from top) 

Biogeochemical cycling. (Chapter 4) Courtesy 

Ken Kemner, Argonne National Laboratory.

Cell wall composition and degradation. (Chapter 2) Courtesy Udaya Kalluri, Oak Ridge National 

Laboratory.

Cellular ultrastructure and physiology. (Chapter 7) Overview of the mitochondria network 

visualized by immunolabeling TOM20 with Alexa 

Flour 647. Courtesy Huang, F., et al. 2016. “UltraHigh Resolution 3D Imaging of Whole Cells,” Cell

166(4), 1028–40.

Biosystems design. (Chapter 6) GLAMM 

metabolic map. Image courtesy Lawrence Berkeley National Laboratory. Bates, J. T., et al. 2011. 

“GLAMM: Genome-Linked Application for Metabolic Maps,” Nucleic Acids Research 39, W400–05.

Metabolic pathways in plants, microbes, and 

fungi. (Chapter 5) GLO-Roots image of soil-grown 

root system. Courtesy Rubén Rellán-Álvarez and 

José R. Dinneny, Carnegie Institute for Science. 

Rhizosphere community interactions. (Chapter 3) Confocal microscope images of bacteria on 

the surface of poplar roots. Courtesy J. L. Morrell-Falvey, Oak Ridge National Laboratory.

Data integration and analysis. (Chapter 8) Mesoscale molecular model. [Reprinted from Macmillan 

Publishers Ltd: Nature Methods. Johnson, G. T., 

et al. 2015. “cellPACK: A Virtual Mesoscope to 

Model and Visualize Structural Systems Biology,” 

Nature Methods 12(1), 85–95. © 2015.]

Figure 1.2.

Row 1, Image 1. Nitrogenase. Courtesy David S. 

Goodsell and the RCSB Protein Data Bank.

Row 1, Image 2. PF1205. Reprinted by permission from Macmillan Publishers Ltd.: Hura, G. L., 

et al. 2009. “Robust, High-Throughput Solution 

Structural Analyses by Small Angle X-ray Scattering 

(SAXS),” Nature Methods 6, 606–12. © 2009.

Row 1, Image 3. Comprehensive imaging of 

densely packed transmembrane proteins using 

photoactivated localization microscopy (PALM). 

Courtesy Greenfield, D., et al. 2009. “Self-Organization of the Escherichia coli Chemotaxis Network 

Imaged with Super-Resolution Light Microscopy,” 

PLoS Biology 7(6): e1000137. 

Row 1, Image 4. Confocal microscope image of 

bacteria on the surface of poplar roots. Courtesy 

J. L. Morrell-Falvey, Oak Ridge National Laboratory.

Row 1, Image 5. Scanning electron microscopy 

(SEM) image of a sulfate-reducing biofilm 

obtained from a borehole used for long-term 

(100+ days) acetate injection during biostimulation activities at DOE’s Integrated Field Research 

Challenge site near Rifle, Colorado. Courtesy A. 

Dohnalkova, Pacific Northwest National Laboratory. 

Biofilm material courtesy K. H. Williams, Lawrence 

Berkeley National Laboratory.

Row 1, Image 6. Positron emission tomography 

(PET) image showing uptake of radioactive 

nitrate in a poplar sapling. Courtesy Richard Ferrieri, University of Missouri.

Row 1, Image 7. X-ray computed tomography 

cross section of an active layer/permafrost soil 

core from the DOE BER NGEE–Arctic project. 
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

92 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

Courtesy Tim Neafsey, Lawrence Berkeley National 

Laboratory.

Row 2, Image 1. Haem-copper active site in 

respiratory enzymes. Reprinted by permission 

from Macmillan Publishers Ltd.: Hura, G.L., et al. 

2009. “The Octahaem MccA is a Haem c–Copper 

Sulfite Reductase,” Nature 520, 706–09. © 2015.

Row 2, Image 2. Density difference map for the 

ensemble structure (mFobs − DFmodel)exp[iφmodel]. 

Reprinted under a Creative Commons Attribution 

License (CC BY 4.0) from Burnley, B.T., et al. 2012. 

“Modelling Dynamics in Protein Crystal Structures 

by Ensemble Refinement,” eLIFE 1, e00311.

Row 2, Image 3. Acetate consumption over time 

of Psychrobacter aestuarii and Geobacter sulfurreducens in axenic cultures and co-cultures. 

Courtesy Alice C. Dohnalkova, Pacific Northwest 

National Laboratory.

Row 2, Image 4. Transmission electron microscope(TEM) image of Escherichia coli O157:H7. 

Courtesy Centers for Disease Control and 

Prevention.

Row 2, Image 5. Plant root nutrient uptake.

Courtesy Jennifer Pett-Ridge and Erin Nuccio, Lawrence Livermore National Laboratory.

Row 2, Image 6. Deconstructed biomass. Courtesy National Renewable Energy Laboratory Biomass Structural Characterization Laboratory.

Row 2, Image 7. Engineered bacteria produce 

biodiesel. Courtesy Joint BioEnergy Institute, Lawrence Berkeley National Laboratory.
Appendix D – Acronyms and Abbreviations

September 2017 U.S. Department of Energy • Office of Biological and Environmental Research 93

Acronyms and Abbreviations

Appendix D

2D, 3D, 4D two-, three-, and four-dimensional

Å Angstrom

AFM atomic force microscopy

AMF arbuscular-mycorrhizal fungi

AMS accelerator mass spectrometry

antiSMASH antibiotics and Secondary 

Metabolite Analysis Shell

ASCR Office of Advanced Scientific 

Computing Research, DOE Office 

of Science

BAC bacterial artificial chromosome

BER Office of Biological and 

Environmental Research, DOE 

Office of Science

BES Office of Basic Energy Sciences, 

DOE Office of Science

BSSD BER Biological Systems Science 

Division

C5, C6 carbon cellulosic sugar molecules, 

such as xylose and glucose, 

respectively

CAGE conjugative assembly genome 

engineering

CARD catalyzed reporter deposition

CARS coherent anti-Stokes Raman 

scattering

Cas9 CRISPR-associated protein-9

CEF cellulose elementary fibril

CesA cellulose synthase

CH4 methane

CLEM correlative light and electron 

microscopy

cm centimeter

CME clathrin-mediated endocytosis

CO2 carbon dioxide

CRISPR clustered regularly interspaced 

short palindromic repeats

CRS coherent Raman scattering

cryo cryogenic

cryoEM cryo-electron microscopy

cryoET cryo-electron tomography

CSC cellulose synthase complexes 

(proteins)

DNA deoxyribonucleic acid 

DGT diffusive gradients in thin films

DMAPP dimethylallyl diphosphate

DOE U.S. Department of Energy

dsDNA double-stranded DNA

EM electron microscopy

EMSL BER Environmental Molecular 

Sciences Laboratory

EXAFS extended X-ray absorption fine 

structure

FEL free-electron laser

FIB focused ion beam SEM

FICUS Facilities Integrating Collaborations 

for User Science

FISH fluorescence in situ hybridization

fLM fluorescence light microscopy

FPP farnesyl diphosphate

FRET Förster resonance energy 

transfer

fs femtosecond

FTIR Fourier transform infrared 

microscopy

GC gas chromatography

GFP green fluorescent protein

GM genetically modified

GPR ground-penetrating radar

GPU graphical processing units

HGT horizontal gene transfer

HIM helium ion microscopy

HIM-SIMS HIM with SIMS

HPC high-performance computing

HPFM hybrid photonic force microscopy 

or Hybrid Photonic ModeSynthesizing Atomic Force 

Microscope

IPP isopentenyl diphosphate

JGI DOE Joint Genome Institute

KBase DOE Systems Biology 

Knowledgebase

LCLS DOE Linac Coherent Light 

Source at SLAC

LPMO lytic polysaccharide 

mono-oxygenase
Technologies for Characterizing Molecular and Cellular Systems Relevant to Bioenergy and Environment

94 U.S. Department of Energy • Office of Biological and Environmental Research September 2017

m meter

MALDI matrix-assisted laser desorption 

ionization

MASC microtubule-associated 

cellulose synthase compartments

MD molecular dynamics

MFA metabolic flux analysis

min minute

mm millimeter

MRM multiple reaction monitoring

ms millisecond

MS mass spectrometry

MS/MS tandem mass spectrometry

μm micrometer

μs microsecond

μTomography microtomography

MX macromolecular X-ray 

crystallography

NADPH nicotinamide adenine dinucleotide 

phosphate

nanoSIMS nanoscale secondary ion mass 

spectrometry

NERSC National Energy Research 

Scientific Computing Center

NIMS nanostructure-initiator mass 

spectrometry

nm nanometer

NMR nuclear magnetic resonance

NOESY nuclear Overhauser effect 

spectroscopy

ns nanosecond

NSLS II National Synchrotron Light 

Source II, at Brookhaven 

National Laboratory

NX neutron macromolecular 

crystallography

OTS orthogonal translation system

PALM photoactivated localization 

microscopy

PCR polymerase chain reaction

PET positron emission tomography

ps picosecond

RNA ribonucleic acid

s second

SANS small-angle neutron scattering

SAXS small-angle X-ray scattering

SEM scanning EM

sFTIR synchrotron FTIR

SIMS secondary ion mass spectrometry

SINS synchrotron infrared 

nanospectroscopy

SIP stable-isotope probing

SLAC DOE SLAC National Accelerator 

Laboratory

SLIM structures for lossless ion 

manipulations

SOM soil organic matter

SRM selected reaction monitoring

ssDNA single-stranded DNA

SSN sequence-specific nuclease

s-SNOM scanning near-field optical 

microscopy with scattering

STD saturation transfer difference 

(NMR spectroscopy)

STED stimulated emission depletion

STORM stochastic optical reconstruction 

microscopy

STXM scanning transmission X-ray 

microscopy

TAA, TAG nucleotide triplets stop (or 

terminating) codon

TALENS transcription activator-like effector 

nucleases

TEM transmission electron microscopy

TIRF total internal reflection 

fluorescence

TOF-MS time-of-flight MS

tr-NOESY transfer-NOESY

tRNA transfer RNA

TXM transmission X-ray microscopy

USANS ultrasmall-angle neutron scattering

WAXS wide-angle X-ray scattering

XANES X-ray absorption near edge 

structure (spectroscopy)

XFEL X-ray free-electron laser

XSEDE Extreme Science and Engineering 

Discovery Environment

ZFN zinc finger nucleases
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