Pharmacomicrobiomics

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Venn diagram showing pharmacomicrobiomics as a sub-field of genomics, microbiology, and pharmacology. Pharmacomicrobiomics Venn Diagram.png
Venn diagram showing pharmacomicrobiomics as a sub-field of genomics, microbiology, and pharmacology.

Pharmacomicrobiomics, proposed by Prof. Marco Candela for the ERC-2009-StG project call (proposal n. 242860, titled "PharmacoMICROBIOMICS, study of the microbiome determinants of the different drug responses between individuals"), and publicly coined for the first time in 2010 by Rizkallah et al. (from Ramy K. Aziz research group), is defined as the effect of microbiome variations on drug disposition, action, and toxicity. [1] 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. [2] [3] Within the gut, microbes help modulate developmental, immunological and nutrition host functions. [4] The aggregate genome of microbes extends the metabolic capabilities of humans, allowing them to capture nutrients from diverse sources. [5] 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. [6]

Contents

Efforts to understand the interaction between specific xenobiotics and the microbiome have traditionally involved the use of in vivo as well as in vitro models. [7] Recently, next generation sequencing of genomic DNA obtained from a community of microbes has been used to identify organisms within microbial communities, allowing for accurate profiles of the composition of microbes within an environment. Initiatives such as the Human Microbiome Project (HMP) have aimed to characterize the microbial composition of the oral, gut, vaginal, skin and nasal environments. [8] This and other microbiome characterization projects have accelerated the study of pharmacomicrobiomics. An extensive understanding of the microbiome in the human body can lead to the development of novel therapeutics and personalized drug treatments that are not potentiated or activated by processes carried out by the microbiome.

History

In a 1973 paper, Ronald Scheline stated that the gastrointestinal microbiome has the ability to act as an organ with metabolic potential at least equal to the liver. [9] Since then, the importance of the human microbiome in mediating health and disease has been acknowledged, and specific interactions between xenobiotics and microbes have been characterized using in vitro or in vivo methods. However, few studies have taken into account the complete metabolic profile, leading some to say that the microbiome's cumulative role in xenobiotic metabolism and toxicology has largely remained unexplored. [10] It is reported that 84% of the top-selling pharmaceuticals in the US and Europe are administered orally, making it the most common mode of drug administration. [11] The implication of this is that a large proportion of drugs, especially those that are lowly soluble and permeable ones, encounter the microbiome and are subject to reductive and hydrolytic reactions. [7] The view of the human microbiome as an organ is quite common in scientific literature; [12] however, it is more biologically correct to view it as a cloud, [13] since a 'microbiome cloud model' [13] better reflects the uncertainty associated with the dynamic composition of the microbiome. Understanding the microbiome variability is key to understanding and modulating pharmacomicrobiomic interactions. The same patient can respond properly to a drug on a given day, then—as the patient's microbiome dramatically varies after an infection, antimicrobial therapy, or radiation therapy (for example), the drug response can surprisingly be much different. Sequencing technologies such as 16S rRNA shotgun metagenomic sequencing have facilitated the rapid expansion of the pharmacomicrobiomics field by capturing organismal diversity in microbial communities. The Human Microbiome Project and METAgenomics of the Human Intestinal Tract (MetaHIT), established in 2007 and 2008, respectively, aimed to characterize the variation in human microbiomes. [14] These large scale projects are foundational to pharmacomicrobiomic studies, as they allow for the generation of statistic models that can take into account variation in microbial composition across individuals.

History of the term

The term 'pharmacomicrobiomics' was first proposed in literature in 2010 [1] and subsequently, in 2011, the domains 'pharmacomicrobiomics.org' and 'pharmacomicrobiomics.com' were released. A team of freshly graduated pharmacy students (Mariam Rizkallah and Rama Saad) built and published the first public database with that name "PharmacoMicrobiomics" [15] (with a capital M for branding). Since then, the term started appearing in PubMed year after year, and crossed the 50 publications landmark 11 years later (PubMed search).

Methods to elucidate microbiome composition

In a typical pharmacomicrobiomics pipeline, DNA from a microbial sample is isolated, sequenced and then aligned to microbial sequence databases. Based on the composition of the sample, appropriate xenobiotics prescriptions can be identified based on known interactions. Process diagram final edited.png
In a typical pharmacomicrobiomics pipeline, DNA from a microbial sample is isolated, sequenced and then aligned to microbial sequence databases. Based on the composition of the sample, appropriate xenobiotics prescriptions can be identified based on known interactions.

Animal models

Interactions between xenobiotics and the host microbiome have primarily been assessed through the use of in vivo animal models, as it is difficult to model the natural human gut. In general, the pattern of bacterial colonization is the same in different animals, with both pH and the number of microorganisms gradually increasing from the small intestine towards the ileo-caecal junction of the large intestine. [7] Germ-free rats colonized with human faecal matter are generally regarded as the gold standard in animal modeling of gut microbial environment. [7] However, enzyme activity can vary greatly between organisms.

In vitro models

Microbes found in human fecal samples are fairly representative of the gut microbiome, and are used frequently in in vitro cultures. A variety of in vitro microbial modelling techniques have also been developed. Static batch culturing consists of plating bacteria without replenishing the media at regular intervals. [17] Semi-continuous culture systems allow for the addition of medium without disrupting bacterial growth, and include pH control capabilities. [18] The continuous culture system more closely resembles that of the gut, as it continuously replenishes and removes culture medium. [19] The simulator of the human intestinal microbial system (SHIME) models the small and large intestine through the use of a five-stage reactor, and includes numerous ports for continuous monitoring of pH and volume. [20] Most recently, researchers improved on SHIME by including a computer controlled peristaltic wave to circulate chyme throughout the apparatus. [21] These technologies have given researchers close control over the culturing environment, facilitating the discovery of interactions between xenobiotics and microbes.

High-throughput sequencing

16S rRNA Sequencing

16S ribosomal RNA is the most common housekeeping genetic marker for classifying and identifying bacterial species, as it is present in all bacterial species, has an identical function in most organisms, and is large enough (~1,500 bp) to capture sufficient variation to distinguish bacteria. [22] The sequence of 16S rRNA consists of highly conserved sequences which alternate with nine windows of "hypervariable regions". [23] This allows universal primers to be used to sequence many species at a time, and provides the possibility of distinguishing bacteria given the variable regions alone. Many papers suggest that 16S rRNA gene sequencing provides genus identification in >90% of cases, but species level identification in approximately ~65 to 83% of cases. [24] The Ribosomal Database Project (RDP) [25] and SILVA databases contain sequence information for rRNA in bacteria, eukarya and archaea. [26]

Shotgun sequencing

Advances in high-throughput sequencing has facilitated shotgun metagenome sequencing (SMS), a technology that provides a broader characterization of microbial samples by sequencing a larger number of genes in each organism. SMS involves collecting microbial samples from the environment, isolating DNA, shearing the DNA into small fragments, and then performing whole genome sequencing (WGS). Reads can be assembled de novo or using reference genomes. [27] However, SMS is not without limitations. Reads may overlap and prevent accurate alignment to reference genomes. In addition, reads may be contaminated by human DNA sequence, confounding results. In reference-based assembly, reads may also be biased towards species which have publicly available reference genomes.

Composition of the microbiome

Individual Microbiomes

Gut

Within the intestines, the majority of microbes can be found in the large intestine, where the pH is higher and more conducive to survival. These bacteria are often more efficient than our own digestive enzymes, and function to digest protein and carbohydrates. [9] The results of over 690 human microbiomes have shown that the majority of bacteria of the gut microbiome belongs to four phyla: Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota. [8]

Vagina

The vagina possesses over 200 phylotypes, the most predominant belonging to the phyla Bacillota, Bacteroidota, Actinomycetota, and Fusobacteriota. [28] The secretion of lactic acid and hydrogen peroxide by Lactobacillus sp. can lower the pH, increasing the concentration of bacteria that cause bacterial vaginosis.

Placenta

The first profile of microbes in healthy term pregnancies identified non-pathogenic commensal microbiota from the Firmicutes, Tenericutes, Proteobacteria, Bacteroidetes, and Fusobacteria phyla. [29]

Oral cavity

Through the HMP, nine intraoral sites were in investigated, and found to be enriched in over 300 genera belonging to more than 20 bacterial phyla. [30]

Human Microbiome Project

The Human Microbiome Project (HMP) was established in 2008 by the US National Institutes of Health (NIH). The overarching goal is to establish a comprehensive characterization of the human microbiota and its role in human health and disease, as well as to develop datasets and tools that scientists can use to study microbial populations. [8] The specific initiatives are as follows:

  1. Develop a reference set of microbial genome sequences for an initial characterization of the human microbiome.
  2. Elucidate the relationship between disease and changes in the human microbiome.
  3. Develop technologies for computational analysis, namely methods for sequencing individual microbes or all members of complex populations simultaneously.
  4. Establish a Data Analysis and Coordinating Center to provide publicly available information about the project, outcomes, and raw data.
  5. Establish research repositories to store materials and reagents used in the HMP. This includes cultured organisms and metagenomic DNA samples.
  6. Examine ethical, legal, and social implications of HMP research.

The primary means of characterization is through 16S rRNA sequencing and shotgun metagenomic sequencing. Body sites that are sampled include skin, oral cavity, gut, vagina and nasal cavity. [8] The HMP website includes sequence, metabolic reconstruction, and community profile data. These datasets have been used to associate certain clinical variables with microbiome composition [31] [32]

Known Drug Interactions

Microbiota-mediated interference in xenobiotic activity

The microbiome can significantly affect the potency of a pharmaceutical drug. Even though most drugs are absorbed in the upper part of the large intestine, long-acting drugs that are exposed to the microbe-rich area of the lower intestine can be affected by microbial metabolism. For instance, chloramphenicol may cause bone marrow aplasia following oral administration, due to the presence of coliforms that convert chloramphenicol to its toxic form, known as p-aminophenyl-2-amin-1,2-propanediol. [33] In addition, altered abundances of Eggerthella lenta between populations have been found to affect the metabolism of digoxin, potentiating both its activity and toxicity. [34] A non-exhaustive list of drugs and the microbiota's role in potentiating/increasing their effect is provided below.

DrugPharmacological effectEffect of microbiota on clinical outcomeReference
Acetaminophen Analgesic and antipyretic Increased clinical effect and toxicity [35]
Chloramphenicol AntibioticIncrease toxicity [33]
Digoxin Cardiotonic Decrease toxicity and activity [34]
Flucytosine Antifungal Decrease effect [36]
Metronidazole AntibioticProvide resistance to the antimicrobial/antifungal effect. Also lowers the effect by stimulating metabolism. [37]
Sulfinpyrazone AntibioticActivate the drug [38]
Sulindac Nonsteroidal anti-inflammatory drug Activate the drug [38]

Xenobiotic mediated interference in microbiome composition

Even though pharmacomicrobiomics is often interpreted as the impact the microbiome has on xenobiotic metabolism, the term can also encompass the effects of xenobiotics on the microbiome and microbial genes. The impact of antibiotics on the human microbiome has been well studied. It has been shown that antibiotic therapies not only target a specific pathogen, but also the commensal inhabitants of a host. [39] Evidence suggests that commensal bacteria levels in some cases are not normalized after antibiotic treatment, and in fact may be negatively affected for extended periods of time. [39] A study which assessed the oral and gut microbes before, immediately after, and up to 12 months after exposure to antibiotics, found that the microbiome can be altered for over 12 months. [40] Since the microbiome composition can be altered by antibiotics, this implies positive selection for resistant opportunistic pathogens, which can cause acute disease. [41]

The PharmacoMicrobiomics Web Portal

The PharmacoMicrobiomics Web Portal [15] is a student-led initiative to explore how microbes modulate drugs [42] that is intended for bioinformaticians, microbial geneticists, and drug developers. The goal of the project is to mine literature data and extract microbe-drug interactions, including information about drug classes, microbial families, and body systems. Furthermore, the portal includes a relational database with information on microbial composition at different body sites and their specific effects on drug pharmacokinetics and pharmacodynamic properties.

Personalized Medicine

Personalized medicine in the context of pharmacomicrobiomics refers to the ability to predict an individual's response to a xenobiotic based on the composition of their gut microbiome. However, current omics approaches investigating microbiome composition using metagenomic sequencing after xenobiotic treatment are sparse. Instead, research efforts have focused predominantly on modeling changes in microbial composition in different disease states. [43] Future research efforts should combine knowledge relating to what microbes preferentially metabolize certain compounds (garnered from in vitro studies) with the identification of species abundance to predict drug tolerance in patients. However, modeling a microbe's interaction with a particular xenobiotic may not stably predict interactions, as the genomes of microbes are continually reshuffled through horizontal gene transfer. Considering this, approaches that target individual gene/transcript/protein signatures rather than individual microbes will likely lead to more widely applicable personalized approaches. [44]

Limitations

The limitations of pharmacomicrobiomics primarily arise from the uncertainty associated with metagenomic profiling. Namely, short reads obtained by shotgun sequencing can be difficult to align to reference genomes since many organism have homologous sequences. In addition, 16S rRNA sequencing cannot consistently resolve species identity, a finding that casts doubt on species identities in metagenomic samples. Limitations also arise from differing study designs, as unique approaches to identifying the nature of the xenobiotic-microbiome interactions are often taken. For instance, because pharmacomicrobiomics very broadly denotes the association between xenobiotics and the microbiome, the extent to which studies profile the genetics of the microbiome can vary significantly. Studies aiming to characterize organism identity, but not gene identity or copy number may elect to use 16S shotgun sequencing as opposed to SMS. Conversely, studies aiming to identify genes and their products rather than organism identity may elect WMGS coupled with transcriptomic analysis. Initially, these differences may mean that researchers wanting to investigate publicly available data may have to target their research questions to fit the data at hand.

Related Research Articles

<span class="mw-page-title-main">Human microbiome</span> Microorganisms in or on human skin and biofluids

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 skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, conjunctiva, biliary tract, and gastrointestinal 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.

<span class="mw-page-title-main">Metagenomics</span> Study of genes found in the environment

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.

<span class="mw-page-title-main">Gut microbiota</span> Community of microorganisms in the gut

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.

Dysbiosis is characterized by a disruption to the microbiome resulting in an imbalance in the microbiota, changes in their functional composition and metabolic activities, or a shift in their local distribution. For example, a part of the human microbiota such as the skin flora, gut flora, or vaginal flora, can become deranged, with normally dominating species underrepresented and normally outcompeted or contained species increasing to fill the void. Dysbiosis is most commonly reported as a condition in the gastrointestinal tract.

<span class="mw-page-title-main">16S ribosomal RNA</span> RNA component

16S ribosomal RNA is the RNA component of the 30S subunit of a prokaryotic ribosome. It binds to the Shine-Dalgarno sequence and provides most of the SSU structure.

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.

<span class="mw-page-title-main">Human Microbiome Project</span> Former research initiative

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.

<span class="mw-page-title-main">Microbial symbiosis and immunity</span>

Long-term close-knit interactions between symbiotic microbes and their host can alter host immune system responses to other microorganisms, including pathogens, and are required to maintain proper homeostasis. The immune system is a host defense system consisting of anatomical physical barriers as well as physiological and cellular responses, which protect the host against harmful microorganisms while limiting host responses to harmless symbionts. Humans are home to 1013 to 1014 bacteria, roughly equivalent to the number of human cells, and while these bacteria can be pathogenic to their host most of them are mutually beneficial to both the host and bacteria.

<span class="mw-page-title-main">Microbiota</span> Community of microorganisms

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.

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.

<span class="mw-page-title-main">Earth Microbiome Project</span>

The Earth Microbiome Project (EMP) is an initiative founded by Janet Jansson, Jack Gilbert and Rob Knight in 2010 to collect natural samples and to analyze the microbial community around the globe.

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.

The host–pathogen interaction is defined as how microbes or viruses sustain themselves within host organisms on a molecular, cellular, organismal or population level. This term is most commonly used to refer to disease-causing microorganisms although they may not cause illness in all hosts. Because of this, the definition has been expanded to how known pathogens survive within their host, whether they cause disease or not.

Parasutterella is a genus of Gram-negative, circular/rod-shaped, obligate anaerobic, non-spore forming bacteria from the Pseudomonadota phylum, Betaproteobacteria class and the family Sutterellaceae. Previously, this genus was considered "unculturable," meaning that it could not be characterized through conventional laboratory techniques, such as grow in culture due its unique requirements of anaerobic environment. The genus was initially discovered through 16S rRNA sequencing and bioinformatics analysis. By analyzing the sequence similarity, Parasutterella was determined to be related most closely to the genus Sutterella and previously classified in the family Alcaligenaceae.

<span class="mw-page-title-main">Microbiome</span> Microbial community assemblage and activity

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.

Bacteroides dorei is a species of bacteria within the genus Bacteroides, first isolated in 2006. It is found in the intestinal systems of humans and animals. Research is being conducted to better understand the relationship Bacteroides dorei has on the human intestinal system and the autoimmune disease, Type 1 Diabetes (T1D).

Hologenomics is the omics study of hologenomes. A hologenome is the whole set of genomes of a holobiont, an organism together with all co-habitating microbes, other life forms, and viruses. While the term hologenome originated from the hologenome theory of evolution, which postulates that natural selection occurs on the holobiont level, hologenomics uses an integrative framework to investigate interactions between the host and its associated species. Examples include gut microbe or viral genomes linked to human or animal genomes for host-microbe interaction research. Hologenomics approaches have also been used to explain genetic diversity in the microbial communities of marine sponges.

Clinical metagenomic next-generation sequencing (mNGS) is the comprehensive analysis of microbial and host genetic material in clinical samples from patients by next-generation sequencing. It uses the techniques of metagenomics to identify and characterize the genome of bacteria, fungi, parasites, and viruses without the need for a prior knowledge of a specific pathogen directly from clinical specimens. The capacity to detect all the potential pathogens in a sample makes metagenomic next generation sequencing a potent tool in the diagnosis of infectious disease especially when other more directed assays, such as PCR, fail. Its limitations include clinical utility, laboratory validity, sense and sensitivity, cost and regulatory considerations.

Culturomics is the high-throughput cell culture of bacteria that aims to comprehensively identify strains or species in samples obtained from tissues such as the human gut or from the environment. This approach was conceived as an alternative, complementary method to metagenomics, which relies on the presence of homologous sequences to identify new bacteria. Due to the limited phylogenetic information available on bacteria, metagenomic data generally contains large amounts of "microbial dark matter", sequences of unknown origin. Culturomics provides some of the missing gaps with the added advantage of enabling the functional study of the generated cultures. Its main drawback is that many bacterial species remain effectively uncultivable until their growth conditions are better understood. Therefore, optimization of the culturomics approach has been done by improving culture conditions.

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