HOW MICROBIOME
MULTI-OMICS CAN
BOLSTER HUMAN HEALTH
Sequencing technologies are enabling a deeper analysis of the gut’s
microbiome. Researchers can now explore what our microbial inhabitants
are doing and how they contribute to, or protect from, disease.

Forby

CUSTOM MEDIAA DV E RT I S E M E N T FE AT U R E

A DV E RT I S E M E N T FE AT U R E

HOW MICROBIOME
MULTI-OMICS CAN BOLSTERHUMAN HEALTH
Sequencing technologies are enabling A DEEPER ANALYSIS OF THE GUT’S MICROBIOME.
Researchers can now explore what our microbial inhabitants are doing and how they contribute to,or protect from, disease.

Microbiome research ischanging how we see
ourselves as humans.
The body harbours at least as
many microbial cells as humancells, and our microbial genecatalogue has more than amillion genes. Yet, we still know
very little about the function ofmuch of the ‘second genome’and how it influences health.
“The gut microbiome is likea wild-card organ in the human
body,” says Gary Schroth,Distinguished Scientist andVP at sequencing technology
developer, Illumina, based in San
Diego. “Everybody has a different
gut microbiome that has a huge
effect on how we digest food andmetabolize drugs.”
Large collaborative
projects, such as the HumanMicrobiome Project in the US
and MetaHIT (Metagenomics ofthe Human Intestinal Tract) inEurope, have produced a wealthof data on the gut’s microbialcommunities in people withspecific diseases, as well as
in healthy populations. These
projects revealed the microbial
diversity among individuals, andhighlighted the need for deeper
analysis of the microbiome tounderstand its contribution.
Perturbation of the gut
microbiome is associatedwith numerous diseases— and not just those that
affect the digestive system,
such as inflammatory bowel
disease (IBD). Heritable
immune-mediated diseases
such as asthma, neurologicalconditions including autism,and genetically driven diseases
such as cancer, have all been
linked to dysregulation of thegut microbiota. Translating
microbiome research into
treatments that modulate themicrobiome could transformthe management of commondiseases.
This is an opportunity thatAmi S. Bhatt, a physicianscientist at Stanford University
in California, finds very
attractive. “We have known
for decades that specifichuman gene mutations areassociated with disease, but
fixing those are really difficult,”
she says. ”However, there arealso microbiome compositions

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associated with disease, and wealready have interesting tools toalter them.”
Bhatt’s research focuses on
the communication, not justbetween microbes and thehuman cells, but also within
microbial communities. “Weare trying to understand what
microbes are there, what they
encode, what they produce ascommunication signals and“COMING UP
WITH WAYS
TO GENERATENOVEL GENOMESIS AN EXCITINGCHALLENGE.”
how these change over time,”
she explains. Her team isinvestigating how manipulatingthese signals could improvehealth and patient outcomes.
Technologies to mine themicrobiome
For decades, sequencebased bacterial analysis
relied on genes encoding the16S ribosomal RNA (rRNA).
16S rRNA genes consist ofhighly conserved nucleotide
sequences separated byvariable regions that aregenus- or species-specific.
Researchers find the conserved
regions, then amplify andanalyse the interspersed
variable regions — comparing
them with reference sequences
to identify the bacterial
species present.
However, because only
one gene out of eachgenome is examined, 16S
sequencing provides very
limited information about
the functional potential ofa microbial community. It
also underestimates thetotal diversity of microbes
in a sample, as it can’t easily
distinguish bacteria that areclosely related and it doesn’t
detect other microbes,
such as fungi and viruses,
which also contribute tomicrobiome function.
The falling cost ofsequencing and thedevelopment of improved
computational methods has led
to the widespread adoption of‘shotgun metagenomics’. Using

this approach, researchers
can analyse the entire
genomic content of a sample
by sequencing extracted
DNA fragments and either
comparing them to reference
databases or assemblingthem based on overlapping
sequence similarity. With
shotgun metagenomics,
researchers can identify genes
or gene fragments and predict
the function of their encoded
proteins. It is a powerful
technique that provides
information on the functional
potential of a microbialcommunity, but since sequencereads are not confined toa single locus, such as the16S rRNA gene, it requires a
greater depth of sequencing toachieve comparable detection
rates. This can make shotgun
metagenomics prohibitively
expensive for large-scalestudies.
Nevertheless, researchers
are increasingly switching
to shotgun metagenomics.
“Compared to 16S sequencing,shotgun metagenomics
provides much richer
information,” says Schroth.
And, he adds, costs canbe contained withoutcompromising results byadjusting the depth ofsequencing.
Shallow-depth sequencing
relies on microbial reference
genomes to reassemble thefragments, which limits its
utility. For the vast majorityof microorganisms, these
do not yet exist. “We worklargely in a reference-freespace. We can’t map a lot of
the reads that we generate
to reference genomes,” says
Bhatt. “Coming up with ways
to generate novel genomes
is an exciting challenge”, andone that can benefit fromdeep whole-metagenome
shotgun sequencing1.

GUT MICROBIOME MULTI-OMICS
The gut microbiome influences health, notably by interacting with the immune
system. Understanding microbial signals could lead to new ways to tackle disease.
Immunesystem

HealthDrugs

Samplecollection andstorage

16s rRNAgene profiling

Host cell
removalMicrobialcommunity

DNARNA

Proteins

Metabolites

Shotgunmetagenomics

Metatranscriptomics

Metaproteomics

Metametabolomics

Compositionand diversity

Data
integration

Functional
pathways

Microbial
function

Functional
screening

Microbial
activity

Validationin cells/miceTargeted
modulators

Computational
prioritisation

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A DV E RT I S E M E N T FE AT U R E

constituent communities.
“More researchers areusing shotgun metagenomics
alone or in combination with
one other approach such ascommunity metabolomics,”
says Curtis Huttenhower, acomputational microbiologist at
the Harvard T.H. Chan Schoolof Public Health in Boston.
“Linking sequencing withhigh-throughput molecular
tools allows us to ‘see’
microbial communities in newways.” Meta-metabolomic
analyses can help to validate
metagenomic findings byidentifying mechanisms linking
gut microbial metabolism andCHRISCHRISW / ISTOCK / GETTY IMAGES

Functional bioprospecting
Ultimately, to understandthe function of microbialcommunities in the gut
microbiome, it is necessary
to determine which genes
are expressed and beingtranslated into proteins.
Thus metagenomic data
is increasingly being
complemented by RNA
sequencing data that allows
metatranscriptomic analyses,
and molecular separation
methods, coupled with mass
spectrometry or nuclear
magnetic resonance to build
metaproteomic and metametabolomic profiles of theThe microbiota in the human
gut is the source of our ‘second
genome’, and sequencing isrevealing its secrets.

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A DV E RT I S E M E N T FE AT U R E

cardiovascular disease2 risk or
insulin sensitivity3, for example.
Huttenhower is also a
principal investigator of the
Human Microbiome Bioactives
Resource (HMBR), which
provides platforms and methods
to integrate 16S sequencing,shotgun metagenomics,“LINKING
SEQUENCINGWITH HIGHTHROUGHPUT
MOLECULAR TOOLSALLOWS US TO‘SEE’ MICROBIALCOMMUNITIES IN
NEW WAYS.”

metatranscriptomics and metametabolomics for microbiome
discovery. The HMBR’s goal isto identify microbial productsthat are important for humandisease and to determine theirfunctions. “We are working ourway through a shockingly large
number of uncharacterized
genes, gene products andmetabolites that are involved
in disease phenotypes andmodulated by immune activity
or diet,” he says. Indeed, morethan 50% of the genes in thehuman gut microbiome have notbeen characterized4.
“It will take us a while to getthere,” he concedes.

Learning to manipulate thegut microbiome
In the last decade, clinicians
have been able to modify
their patients’ microbial
ecologies, by replacing a ‘bad’microbiome with a ‘good’ onethrough a faecal transplant.
These seem to work forsome diseases, particularly
recurrent Clostridium
difficile infection, but there
are still concerns about
its efficacy for othergastrointestinal conditions5.
Away from gastrointestinal
conditions, the situation
is even murkier about therole of the microbiome andhow it might be influenced.
Certain gut bacteria areassociated with posttransplant infection in cancer
patients who have received
a hematopoietic stem celltransplant6,7. “In around 40%
of patients receiving stem celltransplantation that develop
blood stream infections,
we can trace the pathogen
causing infection to the gut
microbiome,” says Bhatt.
Furthermore, the incidence
and severity of graft-versushost disease, when immune
cells from a donor transplant
attack the recipient’s tissues,
have been linked to gut
microbiome changes, including
low microbial diversity8. Having
a diverse ecosystem of gut
microbe types can help tomodulate host inflammationand immune tolerance. Bhatt’s
team are currently examining
how faecal transplants andprebiotics can change themicrobiome composition ofpeople undergoing stem celltransplants and improvetheir outcomes.
There may be othertreatment options that don’t
involve replacing the whole
microbiome. Last year, Bhattand colleagues reported theexistence of tens of thousandsof previously overlooked small
proteins (shorter than 50
amino acids in length) that arelikely to have important roles
in microbial communication,
both with other microbes
and with host cells9. Further
understanding of the roles ofthese proteins could lead tomore targeted and potentiallymore effective therapeutic
approaches.
Huttenhower’s team isalso interested in targeting
specific components within thegut ecology, either in humancells or in microbes, which
requires detailed functional

understanding. “The hopeis that we can design small
molecules that target just theright host immune receptor
or that inhibit or activate justthe right microbial metabolic
pathway to fix a particular
problem,” he says.
As part of their work with theHMBR on IBD, which includes
Crohn’s disease and ulcerative
colitis, they have been able tocomputationally predict a rolefor previously uncharacterizedbile acids and microbial
proteins in gut inflammation. By
using microbial and mammaliancell screens to test mechanismsof action, and gnotobiotic mice,“THE HOPE IS
THAT WE CANDESIGN SMALL
MOLECULESTHAT TARGETJUST THE RIGHTHOST IMMUNERECEPTOR.”
in which all the microorganisms
are either known or excluded,
they can confirm predictedbioactivities in controlled
experimental settings andassess the contribution of thesebioactive compounds to IBD
pathogenesis10.
Outlook and challenges
To improve the functional
analysis of the gut microbiomeand develop targeted
approaches to modulate it,
Bhatt emphasizes the need tocollect and sequence samples
at different timepoints.
“Microbes are not stable orstationary, they are livingorganisms that can have aselective advantage in different
clinical settings,” she says. She
also looks forward to further
technological developments to
help examine more accurately
how microbial genomes within
a community change over time.

Current methods are alsopoor when it comes to detecting
the exchange of genes between
microorganisms, known as
horizontal gene transfers,
which are a critical part of theway that microbes adapt todifferent circumstances, suchas the presence of antibiotic
for example. Bhatt’s team areexploring ways to overcome thisdetection issue by sequencing
longer DNA fragments that canbe aligned more easily, leading
to more accurate bacterial
genome assembly.
There is little doubt that NGS
technologies have transformed
the field of metagenomics.
Further advances in analyticalmethods, including machinelearning, to integrate multiomic microbiome data will
have a profound impact onhuman disease. “As the numberof tools for detecting andassaying microbes has grown,”says Huttenhower, “so has
the diversity of questions thatcan be asked, and the numberof potential translationalapplications.”
REFERENCES
1.	
Hillmann, B., et al. mSystems
3:e00069-18 (2018).
2.	Feng, Q., et al. Sci Rep 6:22525(2016).
3. 	Pedersen, H.K., et al. Nature
535(7612):376–381 (2016).
4. 	Joice, R. et al. Cell Metab 20(5):731–741 (2014).
5. 	Holleran, G. et al. Drugs Today
54(2):123-136 (2018).
6. 	Ballen, K. et al. Biol Blood Marrow
Transplant 22(9):1636-1645(2016).
7. 	Tamburini, F.B., et al. Nat Med 24,1809–1814 (2018).
8. 	Taur, Y., et al. Blood 14; 124(7):1174–1182 (2014).
9. 	Sberro, H., et al. Cell 178(5):1245–1259.e14 (2019).
10. 	Lloyd-Price, J., et al. Nature 569,655–662 (2019).

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