Microbial composition and function

Knowing which microorganisms are present in the intestine is important.

It is not the same as knowing what the microbial community is doing.

This distinction has become increasingly important as microbiome science has moved from descriptive surveys of community composition towards metagenomics, metatranscriptomics, proteomics and metabolomics. These approaches reveal different layers of microbial biology: which organisms are detected, which genes they carry, which genes are expressed, which proteins are produced and which metabolites accumulate within a particular biological environment.^¹–⁴

Each layer adds information.

None can simply stand in for another.

A taxonomic difference may have functional consequences, but those consequences cannot always be predicted from the name or relative abundance of the organism alone. Conversely, different microbial communities may perform overlapping functions because unrelated organisms can carry similar metabolic pathways.^²,⁵,⁶

The distinction between composition and function therefore changes how microbiome findings should be interpreted.

The central question is no longer only:

Who is there?

It is also:

What biological capacity is present, what is active, and what reaches the host?

Taxonomy is an important beginning

Taxonomic profiling transformed microbiome research.

16S ribosomal RNA gene sequencing made it possible to characterise bacterial communities across large numbers of samples without culturing each organism individually. This revealed enormous interpersonal variation and established associations between microbial-community structure and a wide range of physiological and clinical phenotypes.^⁷–⁹

The method remains useful.

But 16S sequencing primarily tells us about bacterial and archaeal community composition at a taxonomic resolution determined by the amplified region, reference database and analytical pipeline. It provides limited information about strain-level variation and does not directly measure microbial genes, gene expression or metabolic activity.^¹,¹⁰

This creates an important inferential boundary.

If a taxon is more abundant in one group than another, we have evidence of a compositional difference.

We do not yet know what that difference means functionally.

Species names can conceal strain-level biology

Microbial species are not functionally uniform.

Strains within the same species can differ substantially in gene content, metabolic capacity, virulence factors, antimicrobial resistance and interactions with the host.^¹¹,¹²

This means that species-level classification can sometimes group together organisms with biologically important differences.

Escherichia coli provides an obvious example: strains belonging to the same species can range from commensal organisms to pathogens with specialised virulence programmes.

The principle extends well beyond classical pathogens.

Strain-specific gene repertoires can influence carbohydrate utilisation, metabolite production, ecological fitness and interaction with other members of the microbial community.^¹¹,¹²

A statement that a particular bacterial species is “beneficial” or “harmful” can therefore be biologically crude.

The relevant unit may be the strain.

In other cases, the relevant unit may not be a taxon at all, but a microbial function distributed across several organisms.

Metagenomics asks what the community could do

Shotgun metagenomic sequencing moves beyond targeted taxonomic profiling by sequencing microbial DNA across the sample.

This can improve taxonomic resolution and, importantly, provide information about the genes and metabolic pathways encoded by the microbial community.^¹,²,¹³

Metagenomics therefore allows us to ask about functional potential.

Does the community contain genes required for degradation of a particular substrate?

Does it encode pathways associated with synthesis or transformation of metabolites?

Are antimicrobial-resistance genes present?

Which organisms may carry those functions?

These are substantially richer questions than taxonomic abundance alone can answer.

But metagenomic potential remains potential.

A gene present in microbial DNA is not necessarily being expressed.

A metabolic pathway encoded in the community is not necessarily active under the conditions in which the sample was collected.

And a predicted microbial function is not equivalent to a measured microbial product.

The distinction between capacity and activity remains essential.

Metatranscriptomics asks what is being expressed

Metatranscriptomics examines microbial RNA and therefore provides information about genes being transcribed within the sampled community.

Comparisons between metagenomic and metatranscriptomic data have demonstrated that transcriptional activity cannot be reliably inferred from DNA abundance alone.^³

An organism present at relatively low abundance may contribute disproportionately to transcription of a particular pathway.

A highly abundant organism may carry genes that are minimally expressed under the conditions studied.

The same community may also change its transcriptional programme in response to diet, inflammation, medication or other environmental changes without undergoing a dramatic taxonomic shift.

Function can therefore change while composition appears relatively stable.

This is one reason why absence of a large compositional difference does not necessarily imply absence of biologically meaningful microbial change.

Proteins and metabolites move closer to biological activity

Microbial proteins and metabolites provide further layers of functional information.

Metaproteomics can identify proteins produced within complex microbial communities, while metabolomics can quantify chemical compounds present in biological samples.^⁴,¹⁴

These approaches move closer to biological activity.

But interpretation remains complex.

A metabolite detected in stool may have been produced by microorganisms, modified by other microorganisms, derived from diet, secreted by the host or transformed through interactions among these sources. Its concentration in faeces reflects the balance between production, utilisation, absorption and excretion.

A low faecal concentration does not necessarily mean low production.

The compound may have been efficiently absorbed or consumed.

A high concentration does not necessarily imply greater exposure of host tissues.

The biological meaning depends on location, flux and context.

Measurement becomes closer to function without becoming synonymous with mechanism.

Function can be shared across different communities

One of the striking findings of human microbiome research is that taxonomic variation between individuals can be greater than variation in some broad functional pathways.^⁵,⁶

This phenomenon is sometimes described as functional redundancy.

The term does not mean that microorganisms are interchangeable.

It means that different taxa may contribute overlapping functional capabilities to an ecosystem.

Several organisms may be capable of degrading related substrates.

Different microbial pathways may converge on production of similar metabolites.

If one organism declines, another may partially occupy the functional space it leaves behind.

This can contribute to ecological resilience.

But redundancy is rarely complete.

Different organisms can perform related functions at different rates, under different environmental conditions, in different anatomical niches and while producing different secondary products.

The presence of overlapping functional capacity therefore does not make taxonomic composition irrelevant.

It changes the relationship between composition and outcome.

Microbial functions emerge from communities

Microbial metabolism is frequently discussed as though individual organisms act independently.

In reality, many microbial functions emerge through interactions among community members.

One organism can degrade a complex dietary substrate into smaller molecules that become available to another. A metabolite produced by one species may serve as substrate for a second. Hydrogen transfer, cross-feeding and sequential metabolism can make a pathway possible at the community level even when no single organism performs every step.^{¹⁵–¹⁷}

Short-chain fatty-acid production provides a familiar example.

Dietary fibres and resistant carbohydrates can be degraded through networks of organisms, with intermediate products exchanged among community members before acetate, propionate, butyrate and other metabolites emerge from the system.^¹⁶,¹⁷

The amount and pattern of metabolites produced therefore depend on more than the abundance of a single presumed producer.

Substrate availability matters.

Community structure matters.

Competition and cross-feeding matter.

Transit time and luminal conditions matter.

Host absorption matters.

Microbial function is an ecosystem property.

Diet supplies substrates, not predetermined outcomes

Diet is a major determinant of microbial function because it alters the substrates reaching the colon.

Human intervention studies have shown that dietary changes can rapidly alter microbial-community structure and metabolic activity.^{¹⁸–²⁰} Yet responses vary substantially between individuals.

This variability is biologically informative.

If two individuals consume the same fermentable substrate but harbour different microbial communities, the substrate may enter different metabolic networks. The resulting metabolites can therefore differ in quantity and proportion.^²⁰,²¹

The host also contributes to this variability through digestion, intestinal transit, bile acids, mucus secretion and absorption.

This makes the common idea of “feeding a beneficial bacterium” an incomplete description of what happens after food enters a microbial ecosystem.

Diet provides ecological resources.

The community determines how those resources are transformed.

Microbial metabolism can transform host and dietary compounds

Microbial function is not limited to fermentation of carbohydrates.

Intestinal microorganisms participate in transformations involving amino acids, bile acids, vitamins, xenobiotics and host-derived compounds.^²²–²⁴

Primary bile acids synthesised by the host, for example, can be deconjugated and further transformed by intestinal microorganisms into secondary bile acids with distinct biological activities.^²³

Tryptophan can enter several microbial and host metabolic pathways, generating compounds capable of interacting with epithelial, immune and neural signalling systems.^²⁴

Microorganisms can also modify pharmaceuticals and other xenobiotics, potentially altering drug availability or toxicity.^²²

The microbiome is therefore not simply responding to host physiology.

It participates in chemical transformation within the intestinal environment.

These transformations provide one of the principal routes through which microbial function can influence host biology.

The metabolites themselves will be considered in greater depth separately.

Function depends on place

A microbial function cannot be fully understood without considering where it occurs.

A metabolite produced in the colonic lumen may be absorbed, consumed by another organism or remain largely within the faecal stream.

A microbial product generated close to the mucosal surface may have different access to epithelial or immune receptors from the same product generated in the centre of the lumen.

Microbial genes detected in stool therefore describe functional potential within a sampled community, but not necessarily the activity occurring at the epithelial interface.^²⁵,²⁶

This spatial distinction is especially important when microbial findings are linked to barrier biology.

A faecal metagenomic signature and a mucosa-associated microbial process are not interchangeable observations.

The biology of the interface depends on proximity as well as presence.

Host physiology shapes microbial function

The host is not merely the recipient of microbial products.

Host physiology actively shapes microbial metabolism.

Intestinal transit determines how long microorganisms and substrates remain together.

Bile acids create selective pressures while also providing substrates for microbial transformation.

Mucus provides host-derived glycans.

Inflammation can alter nutrient and oxygen availability.

Epithelial metabolism helps maintain the low-oxygen environment required by many colonic anaerobes.^²⁷,²⁸

Changes in host physiology can therefore produce functional microbial changes even without an external dietary intervention.

This is particularly relevant in disease.

A microbial metabolic signature observed in a clinical population may reflect altered host physiology rather than an independent microbial defect.

Again, cause and consequence can become entangled.

Relative abundance can mislead functional interpretation

Most sequencing-based microbiome data are compositional.

The abundances of taxa or genes are often expressed relative to the total number of sequences recovered from the sample.

This creates a mathematical dependency among features.^²⁹

If one organism expands dramatically, the relative abundance of another can appear to decrease even if its absolute abundance remains unchanged.

The same problem applies to functional genes.

An apparent enrichment or depletion in relative abundance does not necessarily represent an equivalent change in absolute microbial load or metabolic activity.

Absolute quantification, microbial-load measurements and appropriately designed statistical approaches can therefore change interpretation.^²⁹,³⁰

This is another reason why microbiome function should not be inferred casually from relative-abundance plots.

The measurement framework matters.

Prediction is not measurement

When shotgun metagenomic data are unavailable, functional profiles are sometimes predicted from marker-gene data using reference genomes and computational inference.

Such approaches can be useful for hypothesis generation.

They do not directly measure microbial genes or pathway activity.

Likewise, pathway reconstruction from metagenomic data does not directly measure transcription or metabolite production.

A useful hierarchy is therefore:

taxonomic composition → predicted functional potential → measured genetic potential → transcriptional activity → protein activity → metabolite production → host exposure → host response.

These levels are connected.

They are not equivalent.

The further a conclusion travels along that chain without direct measurement, the more assumptions it contains.

Function does not automatically establish causality

Functional microbiome measurements can bring us closer to mechanism, but they do not eliminate causal uncertainty.

Suppose a metabolomic study identifies a microbial-associated compound that differs between people with and without disease.

Several explanations remain possible.

The microbial community may be producing more of the compound.

The host may be absorbing less.

Dietary intake may differ.

Medication may influence the pathway.

Disease physiology may alter the intestinal environment and thereby change microbial metabolism.

Or the metabolite may participate causally in the phenotype.

Functional measurement narrows the biological question.

It does not answer every causal question.

Intervention, temporality and mechanistic experimentation remain necessary.

My own work: composition within an experimental context

This distinction has been important in my own experimental work.

In our study of bovine colostrum in wild-type and zonulin-transgenic mice, we examined changes in intestinal microbiota alongside behavioural outcomes within an experimental model of altered barrier regulation.^³¹

The microbial data provided evidence about community composition in response to genotype and intervention.

They did not, by themselves, establish which microbial functions changed or whether a particular microorganism mediated the behavioural findings.

That distinction shaped the next level of interpretation.

Our subsequent transcriptomic work examined host intestinal responses rather than treating microbial composition as a complete mechanistic explanation.^³²

Together, these studies illustrate a broader principle:

different datasets can describe different parts of the same biological system without any one dataset becoming the whole mechanism.

From composition to biological meaning

The shift from composition to function represents one of the most important developments in microbiome science.

Taxonomy tells us something essential about community structure.

Metagenomics expands the question to functional capacity.

Metatranscriptomics asks what is being expressed.

Proteomics and metabolomics move closer to biological activity.

Spatial sampling asks where those processes occur.

Host measurements ask what reaches and affects the organism.

Each step reduces some uncertainty and introduces new questions.

The objective is not to replace taxonomy with function.

It is to understand the relationship between them.

A microbial community is composed of organisms, but its biological effects emerge from what those organisms can do, what they actually do, how they interact, where those interactions occur and how the host responds.

Composition describes the community. Function begins to explain its biology.