SURVEYING THE PROTEIN DIVERSITY OF COMMUNITIES AND ECOSYSTEMS

Pioneering studies in environmental proteomics have revealed links between protein diversity and ecological function in simple ecological communities such as microbial biofilms. In the near future, high throughput proteomic methods will be applied to more complex ecological systems in which microbes and macrobes interact. Data structures in biodiversity and protein surveys have many similarities, so the statistical methods that ecologists use for analyzing biodiversity data should be adapted for use with quantitative surveys of protein diversity. However, increasing quantities of protein and bioinformatics data will not, by themselves, reveal the functional significance of proteins. Instead, ecologists should be measuring changes in the abundance of protein cohorts in response to replicated field manipulations, including nutrient enrichment and removal of top predators. SURVEYING THE PROTEIN DIVERSITY OF COMMUNITIES AND ECOSYSTEMS High throughput methods for studying and characterizing large numbers of proteins of uncultured biological samples (metaproteomics) now allow for cataloguing the proteins of component species of assemblages (community proteomics) or of parts of ecosystems, without precise knowledge of the organism that produced the protein (environmental proteomics) [1,2]. Pioneering studies have surveyed relatively simple, microbial-dominated assemblages (reviewed in [3,4]), sampled from habitats such as acid-mine drainages [5], microfilm surfaces of leaves [6], seawater [7] and soil [8] (Box 1). These methods and results should be of great interest to all community and ecosystem ecologists, because patterns of differential protein production and expression reflect physiological responses to changing or stressful environmental conditions [9], including climatic change [10] and the presence of predators [11]. In addition, shifts in protein abundance and composition — best characterized through analyses of microbial processes [12] — can indicate changes in magnitude or rates of material and energetic fluxes within and between ecosystems [13]. © 2012 Elsevier Ltd. All rights reserved. *Correspondence Author (ngotelli@uvm.edu). Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author Manuscript Trends Ecol Evol. Author manuscript; available in PMC 2013 August 01. Published in final edited form as: Trends Ecol Evol. 2012 August ; 27(8): 436–442. doi:10.1016/j.tree. 2012.03. 001. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript Although pioneering studies of microbes suggest directions for future work in environmental proteomics, it is unclear how easily results from microbial assemblages can be scaled to more complex ecological systems. The structural complexity of microbial systems appears to be simplified relative to that of most terrestrial and aquatic ecosystems. Biofilm and microbial systems generally lack the photosynthetic primary producers, detritivores, and higher trophic levels that characterize typical “green” and “brown” food webs [14] of interacting multicellular (“macrobial”) eukaryotes and prokaryotes [15]. Technical challenges—including the identification of proteins from species without sequenced genomes, variation in the physical and biological conformation of proteins, in situ activity of isolated proteins and the difficulty of reliably extracting proteins from complex media such as seawater and soil [16] — also hinder the application of proteomic (and genomic) approaches to macrobial assemblages and food webs [3]. Nevertheless, as these challenges are overcome with new technologies and bioinformatics tools, proteomic surveys of a range of ecological communities and ecosystems will become an important complement to parallel metagenomic, metatranscriptomic and metametabolomic surveys [2]. All of these methods generate complementary data, although from our perspective, proteins are the most desirable unit of study because they are most closely related to the functioning of ecosystems and because they are a more direct measure of the “molecular phenotype” [17]. Perhaps the most important practical result of ongoing technological advances is that ecologists will be able to survey proteomes efficiently and repeatedly and describe their variability in natural ecosystems, rather than ignoring variation and classifying species, communities and their proteomes using fixed typologies. For example, Figure 1 shows three proteomic “fingerprints” of samples from three replicate food webs inhabiting water-filled leaves of the pitcher plant Sarracenia purpurea. Each pitcher supports an independent, intact food web consisting of a resource base of captured insect prey (mostly ants and flies), a subweb of bacteria, protozoa, algae, and fungi and a suite of aquatic invertebrate larvae (flies, midges and mosquitoes) that interact as filter feeders, detritivores, omnivores, and top predators [18]. The obvious variability in protein profiles among replicate food webs in the microbial component of each web (Figure 1) likely reflects differences in species composition and abundance of invertebrates and microbes within each leaf, along with differences in the quantity and composition of captured insect prey. At the same time, consistent protein bands suggest repeatable patterns and protein structure among replicate food webs. In an associated community proteomics survey [19], species-specific proteins and peptide signatures of the three most abundant macroinvertebrates were revealed, a first step towards proteomic profiling of an entire microbe-macrobe ecosystem. UNDERSTANDING THE FUNCTIONAL SIGNIFICANCE OF PROTEIN DIVERSITY In just two decades, cost-effective methods have been developed to increase throughput and comprehensive identification of proteins [20,21]; accurately quantify protein relative abundance [22,23]; enrich rare protein types and protein modifications [24, 25]; and expand the capacity and precision of bioinformatic tools that enhance the functional interpretation of proteomic datasets [26,27]. Although some of these methods are still in their infancy, rapid technological and statistical advances daily are increasing the quantity and quality of information about proteins that can be sampled from functioning ecosystems. However, by itself, this flood of bioinformatics data is unlikely to reveal which particular proteins are important causes and consequences of community structure and ecosystem function. An analogous disconnection between data density and functional inference plagued community ecology in the initial stages of documenting the diversity of species, their assembly, and their interactions within food webs. Pioneering naturalists and taxonomists — Gotelli et al. Page 2 Trends Ecol Evol. Author manuscript; available in PMC 2013 August 01. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript Rumphius, Linneaus, Darwin, Wallace, and von Humboldt, among many others —collected, catalogued and named species from around the world. Beginning in the late 1800s, ecologists assembled detailed records of food web structure —extensive lists of “who eats whom” — in plant and animal assemblages. Now, species diversity and food web structure both are encapsulated, respectively, in summary statistics and indices [28] and as network diagrams with nodes representing species and links representing trophic interactions including predation and parasitism [29]. But pattern identification and summary statistics are not the same as identifying causal processes, which requires experimental manipulations and statistical modeling of the results. In studies of biodiversity [30,31] and ecological food webs [32,33], there are long dialectical traditions of thesis, antithesis, and synthesis. The same dialectic could be applied profitably to proteomics research in ecology: characterizing and summarizing the diversity of proteins and their potential interactions, analyzing proteomic assemblages of experimentally manipulated food webs in the field and synthesizing the resulting data with statistical modeling. CHARACTERIZING AND SUMMARIZING PROTEOMIC DIVERSITY Just as the first step to working with an ecosystem is identifying its constituent organisms, a first step towards understanding the functional significance of protein diversity of an ecosystem will be identifying and enumerating their distinct proteins and estimating their relative abundances. However, just as it is impossible to detect all of the species in a microbial or macrobial assemblage [34,35], so too it is unlikely that we will be able to detail an entire ecological proteome in the foreseeable future. Estimates of proteomic diversity in microbial ecosystems range from 104 to 109 expressed proteins [16]. There are approximately 6,000–60,000 protein-encoding genes in a single prokaryote or eukaryote species‘ genome [36], and even a single tissue sampled from a single multicellular species contains hundreds or even thousands of distinct proteins [37]. In ecological assemblages that contain both microbes and macrobes, proteomic diversity likely will exceed 1010 expressed proteins because— unlike the — genome the proteome of a multicellular organism is not constant during its lifetime, but changes ontogenetically [38] and in response to changing biotic and abiotic conditions [9]. For proteins, as for species, ecologists must remain satisfied with sampling only a small fraction of the potential diversity. The resulting data from surveys of both ecosystems a