A microbiome-wide association study (MWAS), otherwise known as a metagenome-wide association study (MGWAS), is a statistical methodology used to examine the full metagenome of a defined microbiome in various organisms to determine if some feature (as example, gene or species) of the microbiome is associated with a host trait. MWAS has been adopted by the field of metagenomics from the widely used genome-wide association study (GWAS).
While MWAS is phonetically and conceptually tied to GWAS there are several key differentiations:
There are several ways to classify which feature of the microbiome will be used in a MWAS. MWAS can be assessed using a specific taxonomic level (species, genus, [8] phyla, etc.), operational taxonomic unit (OTU) [1] or amplicon sequence variant (ASV), transcriptome, [9] proteome, [10] and more. The approach used depends upon the research hypothesis as each method will often give differing results.
Often, a taxonomic level or OTU/ASV based approach is used to determine the correlations between the specific microbiome feature and the desired phenotype. Several methods can be employed, such as machine learning approaches like random forests, [11] and deep learning. [12] Feature association can also be established with programs like DESeq2 and ANCOM. However, correlations established by the wide array of tools available may not always translate into causality. Researchers determine causality through sequential testing. [13] Newer methods have explored inference of digital twins of microbial ecosystem to address some modeling challenges arising from the diversity of microbes in such environments, inter-host variability, and compositionality of measurements. [14]
The human microbiome is the aggregate of all microbiota that reside on or within human tissues and biofluids along with the corresponding anatomical sites in which they reside, including the gastrointestinal tract, skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, conjunctiva, and the biliary tract. Types of human microbiota include bacteria, archaea, fungi, protists, and viruses. Though micro-animals can also live on the human body, they are typically excluded from this definition. In the context of genomics, the term human microbiome is sometimes used to refer to the collective genomes of resident microorganisms; however, the term human metagenome has the same meaning.
Metagenomics is the study of genetic material recovered directly from environmental or clinical samples by a method called sequencing. The broad field may also be referred to as environmental genomics, ecogenomics, community genomics or microbiomics.
Gut microbiota, gut microbiome, or gut flora are the microorganisms, including bacteria, archaea, fungi, and viruses, that live in the digestive tracts of animals. The gastrointestinal metagenome is the aggregate of all the genomes of the gut microbiota. The gut is the main location of the human microbiome. The gut microbiota has broad impacts, including effects on colonization, resistance to pathogens, maintaining the intestinal epithelium, metabolizing dietary and pharmaceutical compounds, controlling immune function, and even behavior through the gut–brain axis.
The Integrated Microbial Genomes system is a genome browsing and annotation platform developed by the U.S. Department of Energy (DOE)-Joint Genome Institute. IMG contains all the draft and complete microbial genomes sequenced by the DOE-JGI integrated with other publicly available genomes. IMG provides users a set of tools for comparative analysis of microbial genomes along three dimensions: genes, genomes and functions. Users can select and transfer them in the comparative analysis carts based upon a variety of criteria. IMG also includes a genome annotation pipeline that integrates information from several tools, including KEGG, Pfam, InterPro, and the Gene Ontology, among others. Users can also type or upload their own gene annotations and the IMG system will allow them to generate Genbank or EMBL format files containing these annotations.
Jeffrey Ivan Gordon is a biologist and the Dr. Robert J. Glaser Distinguished University Professor and Director of the Center for Genome Sciences and Systems Biology at Washington University in St. Louis. He is internationally known for his research on gastrointestinal development and how gut microbial communities affect normal intestinal function, shape various aspects of human physiology including our nutritional status, and affect predisposition to diseases. He is a member of the National Academy of Sciences, the American Academy of Arts and Sciences, the Institute of Medicine of the National Academies, and the American Philosophical Society.
The Human Microbiome Project (HMP) was a United States National Institutes of Health (NIH) research initiative to improve understanding of the microbiota involved in human health and disease. Launched in 2007, the first phase (HMP1) focused on identifying and characterizing human microbiota. The second phase, known as the Integrative Human Microbiome Project (iHMP) launched in 2014 with the aim of generating resources to characterize the microbiome and elucidating the roles of microbes in health and disease states. The program received $170 million in funding by the NIH Common Fund from 2007 to 2016.
Microbiota are the range of microorganisms that may be commensal, mutualistic, or pathogenic found in and on all multicellular organisms, including plants. Microbiota include bacteria, archaea, protists, fungi, and viruses, and have been found to be crucial for immunologic, hormonal, and metabolic homeostasis of their host.
Prevotella is a genus of Gram-negative bacteria.
Metaproteomics is an umbrella term for experimental approaches to study all proteins in microbial communities and microbiomes from environmental sources. Metaproteomics is used to classify experiments that deal with all proteins identified and quantified from complex microbial communities. Metaproteomics approaches are comparable to gene-centric environmental genomics, or metagenomics.
Biological dark matter is an informal term for unclassified or poorly understood genetic material. This genetic material may refer to genetic material produced by unclassified microorganisms. By extension, biological dark matter may also refer to the un-isolated microorganism whose existence can only be inferred from the genetic material that they produce. Some of the genetic material may not fall under the three existing domains of life: Bacteria, Archaea and Eukaryota; thus, it has been suggested that a possible fourth domain of life may yet be discovered, although other explanations are also probable. Alternatively, the genetic material may refer to non-coding DNA and non-coding RNA produced by known organisms.
Microbial phylogenetics is the study of the manner in which various groups of microorganisms are genetically related. This helps to trace their evolution. To study these relationships biologists rely on comparative genomics, as physiology and comparative anatomy are not possible methods.
The human virome is the total collection of viruses in and on the human body. Viruses in the human body may infect both human cells and other microbes such as bacteria. Some viruses cause disease, while others may be asymptomatic. Certain viruses are also integrated into the human genome as proviruses or endogenous viral elements.
CrAss-like phage are a bacteriophage family that was discovered in 2014 by cross assembling reads in human fecal metagenomes. In silico comparative genomics and taxonomic analysis have found that crAss-like phages represent a highly abundant and diverse family of viruses. CrAss-like phage were predicted to infect bacteria of the Bacteroidota phylum and the prediction was later confirmed when the first crAss-like phage (crAss001) was isolated on a Bacteroidota host in 2018. The presence of crAss-like phage in the human gut microbiota is not yet associated with any health condition.
A microbiome is the community of microorganisms that can usually be found living together in any given habitat. It was defined more precisely in 1988 by Whipps et al. as "a characteristic microbial community occupying a reasonably well-defined habitat which has distinct physio-chemical properties. The term thus not only refers to the microorganisms involved but also encompasses their theatre of activity". In 2020, an international panel of experts published the outcome of their discussions on the definition of the microbiome. They proposed a definition of the microbiome based on a revival of the "compact, clear, and comprehensive description of the term" as originally provided by Whipps et al., but supplemented with two explanatory paragraphs. The first explanatory paragraph pronounces the dynamic character of the microbiome, and the second explanatory paragraph clearly separates the term microbiota from the term microbiome.
Metatranscriptomics is the set of techniques used to study gene expression of microbes within natural environments, i.e., the metatranscriptome.
Wang Jun is a Chinese scientist, founder and CEO of iCarbonX, and former CEO of the Beijing Genomics Institute.
Hadesarchaea, formerly called the South-African Gold Mine Miscellaneous Euryarchaeal Group, are a class of thermophile microorganisms that have been found in deep mines, hot springs, marine sediments, and other subterranean environments.
Pharmacomicrobiomics, proposed by Prof. Marco Candela for the ERC-2009-StG project call, and publicly coined for the first time in 2010 by Rizkallah et al., is defined as the effect of microbiome variations on drug disposition, action, and toxicity. Pharmacomicrobiomics is concerned with the interaction between xenobiotics, or foreign compounds, and the gut microbiome. It is estimated that over 100 trillion prokaryotes representing more than 1000 species reside in the gut. Within the gut, microbes help modulate developmental, immunological and nutrition host functions. The aggregate genome of microbes extends the metabolic capabilities of humans, allowing them to capture nutrients from diverse sources. Namely, through the secretion of enzymes that assist in the metabolism of chemicals foreign to the body, modification of liver and intestinal enzymes, and modulation of the expression of human metabolic genes, microbes can significantly impact the ingestion of xenobiotics.
Katherine Snowden Pollard is the Director of the Gladstone Institute of Data Science and Biotechnology and a professor at the University of California, San Francisco (UCSF). She is a Chan Zuckerberg Biohub Investigator. She was awarded Fellowship of the International Society for Computational Biology in 2020 and the American Institute for Medical and Biological Engineering in 2021 for outstanding contributions to computational biology and bioinformatics.
Trevor Lawley FMedSci is a Faculty member and Group Leader in the Host-Microbiota Interactions Lab at the Wellcome Sanger Institute (WSI). He is also co-founder and Chief Scientific Officer of the biotech company Microbiotica.
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