Chapter 7 — Microbiome

What is the Microbiome?

The microbiome is the community of organisms (e.g., bacteria, fungi, and others) that exist in a particular environment¹, while the human microbiome is the community of microorganisms—specifically, their genes—present in and on the human body^2,3. The study of the microbiome has been advanced significantly through next-generation sequencing and other omics techniques that are growing in popularity in microbiome studies.

The field has rapidly expanded over the past few decades, revealing not only the vast diversity of microbial life but also its profound impacts on ecosystem dynamics, human health, and disease processes. In humans, the microbiome is essential for digestion⁴, vitamin synthesis⁵, and immune regulation6, and microbiome imbalances (i.e., dysbiosis) have been linked to numerous diseases^8-10. In the environment, microbiomes play a crucial role in nutrient cycling¹¹, plant health¹², and pollution degradation¹³, aiding in ecosystem management and conservation^14,15.

We’ve learned to leverage these microbial communities to make better plant fertilizer¹⁶, eco-friendly biofuels and bioplastics^17,18, microbiome-based therapeutics^19-21, and other innovations, demonstrating their integral role in both natural processes and human-driven technologies.

How is the Microbiome Studied?

Microbiome analyses make use of several sophisticated technologies that allow scientists to examine the microbial community composition, function, and dynamics by providing insight into the genetic material (DNA and RNA), proteins, and metabolites characterizing a given microbiome.

Next-generation sequencing

Studying communities of microorganisms at large was made possible through next generation sequencing, which could capture DNA from an organism regardless of whether it was alive or dead. This was powerful given that when microbiome research began in earnest over a decade ago, many species couldn’t be cultured in the laboratory. There are two main approaches used to sequence microbiomes; both typically performed using the Illumina sequencing platform (though there are examples of microbiome studies using other platforms such as the Ion Torrent).

Marker gene sequencing

Marker gene sequencing^22-24 was a common approach in the early days of microbiome research that PCR amplified and sequenced conserved genomic regions to taxonomically classify the bacteria (16S rRNA gene), eukaryotes (18S rRNA gene), or fungi (ITS) present in samples (as well as their relative abundance to one another). This approach is becoming less common with the decrease in sequencing costs that enable more researchers to use whole genome shotgun sequencing of metagenomes (see below), extracting more information for, in many cases, the same price.

Whole genome shotgun metagenomic sequencing

Whole genome shotgun metagenomic sequencing²⁵, by capturing entire genomes rather than just portions of a highly conserved region of the genome, provides a more comprehensive view of the microbial community. This method can capture information about the bacteria, viruses, and eukaryotes in a sample and, when sequenced deep enough, can even reveal information about antibiotic resistance genes, specific strains, and other information of interest.

• Metatranscriptomics: Although the functional potential of microbiomes can be inferred from metagenomics data, metatranscriptomics²⁶ goes one step further by sequencing RNA. This approach captures which genes are actively transcribed into RNA and therefore functional at the time of sampling. This approach, when combined with longitudinal sampling, provides a dynamic view of microbial community functional responses to environmental conditions.
• Metaproteomics: Although transcriptomics analyses provide important information about gene expression, it cannot detect which proteins are produced and active. Metaproteomics²⁷, by capturing the proteins present in a sample, reveals which transcripts are successfully translated into active proteins that interact with the environment or host.
• Metabolomics: Metabolomics²⁸ is the study of small molecule metabolites produces by the microbiome. A growing number of studies have linked identified various microbial metabolites as the “enforcers” of the beneficial and harmful effects of microbial communities on their environment—including humans. Metabolomics provides the ultimate connection between genomic potential and phentoypic reality.

Modern Uses of Microbiome Research in Multiomics: Case Studies

Metabolon has worked with several customers and collaborators to perform a variety of microbiome research studies across a wide range of topics. Below we discuss some key case studies showcasing the application of multiomics techniques to study the microbiome and eludicate the complex interactions and pathways that influence health, disease mechanisms, and ecological balances.

Multi-omics of gut microbiome-host interactions in short- and long-term myalgic encephalomyelitis/chronic fatigue syndrome patients

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, debilitating disorder, the etiology of which remains largely unknown. In a study published in Cell Host Microbe, Xiong et al. Utilized a multiomics approach to explore gut microbiome-host metabolism interactions in ME/CFS patients²⁹. Their work uncovered potential microbiome-based functional mechanisms behind both disease onset and duration.

The researchers performed deep metagenomic sequencing on stool samples and plasma metabolomics on long term (>10 years) and short term (<4 years) ME/CFS patients as well as healthy controls. Their analysis revealed significant microbiome dysbiosis—including a reduction in butyrate producers—in short term patients that appeared to resolve in long term patients. However, metabolic abnormalities were much more pronounced in long-term patients, suggesting a dynamic host-microbiome interplay where early microbial changes may contribute to persistent metabolic disruptions.

Further analyses identified microbial and metabolic biomarkers specific to short- and long-term patients, including reduced butyrate synthesis by gut microbes and reduced butyrate, bile acids, and benzoate, revealing potential functional mechanisms underlying disease onset and duration.

This multiomics approach allowed for high-resolution characterization of microbial and metabolic dysbiosis associated with ME/CFS, revealing specific biomarkers linked to disease onset and progression that otherwise might have been missed. The insight gained provides clues about the underlying mechanisms of this complex disease and may inform future therapeutic strategies.

Multiomics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes

Irritable bowel syndrome is a common gastrointestinal disorder. Although a role for the gut microbiome in this disorder is suspected, the host-microbe connection in IBS remains underexplored. To address this knowledge gap, Jacobs et al. Integrated 16S rRNA sequencing, transcriptomics, and metabolomics analysis of samples collected from IBS patients and healthy controls³⁰. Their work, published in Microbiome, uncovered novel host-microbe functional relationships that may contribute to disease etiology.

The multiomics analysis revealed significant shifts in bacterial taxa, such as increased Bacteroides dorei and Actinomyces spp., and identified metabolites like tyramine, gentisate, and hydrocinnamate that were differentially abundant in IBS patients. This comprehensive approach also allowed for the identification of transcriptional upregulation in pathways related to fructose and glucan metabolism and the succinate pathway of carbohydrate fermentation.

The researchers also developed a multiomics-based classifier (see Figure 2 below), which was more accurate for distinguishing IBS from healthy controls compared to classifiers using individual datasets. Additionally, the study found that diarrhea-predominant IBS (IBS-D) and constipation-predominant IBS (IBS-C) exhibited distinct metatranscriptomic and metabolomic profiles, suggesting that specific microbial and metabolic markers could be used to differentiate between IBS subtypes.

Altogether, this multiomics analysis revealed key microbial, transcript, and metabolite biomarkers associated not only with IBS but with different IBS subtypes. These biomarkers may prove useful in the future as diagnostic and/or therapeutic biomarkers.

Faecal microbiota transplantation affects liver DNA methylation in non-alcoholic fatty liver disease: a multiomics approach

Non-alocholic fatty liver disease is a spectrum of liver diseases that affect over 50% of individuals with type 2 diabetes (T2D). Because NAFLD is regarded as the liver/hepatic component of metabolic syndrome, and due to the recognized connection between the gut microbiome and metabolic disease, researchers recently evaluated fecal material transplant (FMT) in NAFLD patients³¹. Using a combination of microbiome sequencing, metabolomics, and liver DNA methylome analysis before and after FMT, the researchers identified specific microbiome, metabolite, and methylation changes associated with FMT.

Analyzing 21 patients, the researchers observed that T allogenic FMT (from a vegan donor) led to distinct changes in gut microbiota composition, including an increase in beneficial bacteria like Eubacterium siraeum and Blautia wexlerae compared to autologous FMT These changes were associated with altered plasma metabolite levels, such as increased phenylacetylcarnitine and phenylacetylglutamine, which are derived from gut microbial metabolism.

Liver methylome analysis identified specific DNA methylation changes in the liver, particularly in genes like Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). A correlation analysis (see Figure 3 below) highlighted significant relationships between specific gut bacteria, plasma metabolites, and liver DNA methylation sites, suggesting that gut microbiota can influence liver epigenetics through metabolic pathways.

This multiomics analysis demonstrates the advantage of integrating diverse biological data to elucidate the complex interplay between the gut microbiome and host metabolism. It underscores the potential of FMT and microbiome modulation as therapeutic strategies for metabolic diseases like NAFLD. The findings provide new insights into the gut-liver axis and highlight key microbial and metabolic markers that could be targeted to improve liver health and treat NAFLD.

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