Study Of Complex Microbial Communities Research Articles

Bridging the Gaps in Meta-Omic Analysis: Workflows and Reproducibility.

The past few years have seen significant advances in the study of complex microbial communities associated with the evolution of sequencing technologies and increasing adoption of whole genome shotgun sequencing methods over the once more traditional Amplicon-based methods. Although these advances have broadened the horizon of meta-omic analyses in planetary health, human health, and ecology from simple sample composition studies to comprehensive taxonomic and metabolic profiles, there are still significant challenges in processing these data. First, there is a widespread lack of standardization in data processing, including software choices and the ease of installing and running attendant software. This can lead to several inconsistencies, making comparing results across studies and reproducing original results difficult. We argue that these drawbacks are especially evident in metatranscriptomic analysis, with most analyses relying on ad hoc scripts instead of pipelines implemented in workflow managers. Additional challenges rely on integrating meta-omic data, since methods have to consider the biases in the library preparation and sequencing methods and the technical noise that can arise from it. Here, we critically discuss the current limitations in metagenomics and metatranscriptomics methods with a view to catalyze future innovations in the field of Planetary Health, ecology, and allied fields of life sciences. We highlight possible solutions for these constraints to bring about more standardization, with ease of installation, high performance, and reproducibility as guiding principles.

Influence of Extraction Solvent on Nontargeted Metabolomics Analysis of Enrichment Reactor Cultures Performing Enhanced Biological Phosphorus Removal (EBPR).

Metabolome profiling is becoming more commonly used in the study of complex microbial communities and microbiomes; however, to date, little information is available concerning appropriate extraction procedures. We studied the influence of different extraction solvent mixtures on untargeted metabolomics analysis of two continuous culture enrichment communities performing enhanced biological phosphate removal (EBPR), with each enrichment targeting distinct populations of polyphosphate-accumulating organisms (PAOs). We employed one non-polar solvent and up to four polar solvents for extracting metabolites from biomass. In one of the reactor microbial communities, we surveyed both intracellular and extracellular metabolites using the same set of solvents. All samples were analysed using ultra-performance liquid chromatography mass spectrometry (UPLC-MS). UPLC-MS data obtained from polar and non-polar solvents were analysed separately and evaluated using extent of repeatability, overall extraction capacity and the extent of differential abundance between physiological states. Despite both reactors demonstrating the same bioprocess phenotype, the most appropriate extraction method was biomass specific, with methanol: water (50:50 v/v) and methanol: chloroform: water (40:40:20 v/v/v) being chosen as the most appropriate for each of the two different bioreactors, respectively. Our approach provides new data on the influence of solvent choice on the untargeted surveys of the metabolome of PAO enriched EBPR communities and suggests that metabolome extraction methods need to be carefully tailored to the specific complex microbial community under study.

Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data

The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learning algorithm of standard cell type recognition (CellCognize). As a proof-of-concept, we trained neural networks with 32 microbial cell and bead standards. The resulting classifiers were extensively validated in silico on known microbiota, showing on average 80% prediction accuracy. Furthermore, the classifiers could detect shifts in microbial communities of unknown composition upon chemical amendment, comparable to results from 16S-rRNA-amplicon analysis. CellCognize was also able to quantify population growth and estimate total community biomass productivity, providing estimates similar to those from 14C-substrate incorporation. CellCognize complements current sequencing-based methods by enabling rapid routine cell diversity analysis. The pipeline is suitable to optimize cell recognition for recurring microbiota types, such as in human health or engineered systems.

Diet-induced microbial autofluorescence confounds flow cytometry of ex vivo isolated fecal microbes.

Microbial flow cytometry is a powerful emerging technology with a broad range of applications including the study of complex microbial communities. Immunologists are increasingly using this technology to study antibody responses against pathogenic and commensal microbes. We employed microbial flow cytometry to quantify the proportion of fecal microbes bound by six different Ig isotypes: IgA, IgM, IgG1, IgG2b, IgG2c, and IgG3. In healthy mammals, secretory IgA (sIgA) binds to a subset of commensal microbes in the gut whereas IgG is not typically found in the intestinal tract of healthy mammals. Unexpectedly, fecal microbes isolated from SPF C57BL/6 mice housed in the Hill facility and imported from the vendors The Jackson Laboratory and Taconic Biosciences showed a strong signal in the Brilliant Violet 711 (BV711) channel. Unstained fecal samples from these mice demonstrated that the BV711 signal was due to bacterial autofluorescence. We found that murine diets containing alfalfa induce ex vivo microbial autofluorescence in the far red spectrum, likely due to chlorophyll. Analysis of unstained intestinal microbes is an important step in microbial flow cytometry to identify diet-induced autofluorescence. We recommend fluorophores with emission spectra below 650 nm (e.g. BV421, PE).

Using bioreactors to study the effects of drugs on the human microbiota.

The study of complex microbial communities has become a major research focus as mounting evidence suggests the pivotal role microbial communities play in host health and disease. Microbial communities of the gastrointestinal tract, known as the gut microbiota, have been implicated in aiding the host with vitamin biosynthesis, regulation of host energy metabolism, immune system development, and resistance to pathogen invasion. Conversely, disruptions of the gut microbiota have been linked to host morbidity, including the development of inflammatory diseases, metabolic disorders, increased cardiovascular risk, and increased risk of infectious diseases. However, studying the gut microbiota in humans and animals is challenging, as many microorganisms are fastidious with unique nutritional or environmental requirements that are often not met using conventional culture techniques. Bioreactors provide a unique solution to overcome some of the limitations of conventional culture techniques. Bioreactors have been used to propagate and establish complex microbial communities in vitro by recapitulating the physiological conditions found in the GI tract. These systems further our understanding of microbial physiology and facilitate our understanding of the impact of medications and xenobiotics on microbial communities. Here, we review the versatility and breadth of bioreactor systems that are currently available and how they are being used to study faecal and defined microbial communities. Bioreactors provide a unique opportunity to study complex microbial interactions and perturbations in vitro in a controlled environment without confounding biotic and abiotic variables.

The Madness of Microbiome: Attempting To Find Consensus "Best Practice" for 16S Microbiome Studies.

ABSTRACTThe development and continuous improvement of high-throughput sequencing platforms have stimulated interest in the study of complex microbial communities. Currently, the most popular sequencing approach to study microbial community composition and dynamics is targeted 16S rRNA gene metabarcoding. To prepare samples for sequencing, there are a variety of processing steps, each with the potential to introduce bias at the data analysis stage. In this short review, key information from the literature pertaining to each processing step is described, and consequently, general recommendations for future 16S rRNA gene metabarcoding experiments are made.

Evaluating the core microbiota in complex communities: A systematic investigation.

The study of complex microbial communities poses unique conceptual and analytical challenges, with microbial species potentially numbering in the thousands. With transient or allochthonous microorganisms often adding to this complexity, a 'core' microbiota approach, focusing only on the stable and permanent members of the community, is becoming increasingly popular. Given the various ways of defining a core microbiota, it is prudent to examine whether the definition of the core impacts upon the results obtained. Here we used complex marine sponge microbiotas and undertook a systematic evaluation of the degree to which different factors used to define the core influenced the conclusions. Significant differences in alpha- and beta-diversity were detected using some but not all core definitions. However, findings related to host specificity and environmental quality were largely insensitive to major changes in the core microbiota definition. Furthermore, none of the applied definitions altered our perception of the ecological networks summarising interactions among bacteria within the sponges. These results suggest that, while care should still be taken in interpretation, the core microbiota approach is surprisingly robust, at least for comparing microbiotas of closely related samples.

In this issue of Gut Microbes

It is an amazing time to be a microbiologist. We have progressed from the study of microbes in monoculture to the study of microbes in mixed culture to the study of complex microbial communities in...

Computational challenges of sequence classification in microbiomic data

Next-generation sequencing technologies have opened up an unprecedented opportunity for microbiology by enabling the culture-independent genetic study of complex microbial communities, which were so far largely unknown. The analysis of metagenomic data is challenging: potentially, one is faced with a sample containing a mixture of many different bacterial species, whose genome has not necessarily been sequenced beforehand. In the simpler case of the analysis of 16S ribosomal RNA metagenomic data, for which databases of reference sequences are known, we survey the computational challenges to be solved in order to be able to characterize and quantify a sample. In particular, we examine two aspects: how the necessary adoption of new tools geared towards high-throughput analysis impacts the quality of the results, and how good is the performance of various established methods to assign sequence reads to microbial species, with and without taking taxonomic information into account.

Abstract ED06-02: Understanding the structure and function of the gut microbiota

Abstract Until recently, the study of complex microbial communities was limited by the culture-based methodologies that only captured a subset of the diversity present. The advent of molecular methods for the study of microbial consortia has allowed us to greatly increase our understanding of the structure, function and dynamics of the indigenous human microbiota. In this opening lecture of the session I will introduce the techniques and strategies for studying the structure and function of complex consortia of microbes, with a focus on the community that inhabits the gastrointestinal tract. Using the example of Clostridium difficile infection following antibiotic administration as an example, I will demonstrate how changes in the community structure of the gut microbiota can be monitored over time. The associated functional changes associated with changes in microbial community structure will be discussed. We have recently applied culture-independent molecular methods, largely based on retrieval of 16S rRNA-encoding gene sequences, to investigate the role of the indigenous microbiota in C. difficile infection (CDI). Through studies of human patients with CDI we have demonstrated that recurrent disease is associated with an overall decrease in the diversity of the fecal microbiota. We have leveraged a recently described murine model of CDI to conduct more detailed studies of the role of the microbiota in C. difficile infection. Data from this model system indicates that a subset of the indigenous microbiota is important in mediating colonization resistance against C. difficile and possibly in modulating the effects of C. difficile toxin. This example will allow the audience to understand and appreciate the growing number of studies that are examining associations between the community structure of the gut microbiota and a variety of disease states including colorectal cancer. Citation Information: Cancer Prev Res 2010;3(12 Suppl):ED06-02.

GROWTH AND DEVELOPMENT SYMPOSIUM: Promoting healthier humans through healthier livestock: Animal agriculture enters the metagenomics era12

The priorities of public health and agricultural sciences intersect through a shared objective to foster better human health. Enhancements in food quality and reductions in the environmental effects of modern agriculture represent 2 distinct paths through which animal sciences can contribute to the cause of public health. Recent developments in the study of human-associated microbial communities (microbiotas), notably in association with disease, indicate that better understanding of the microbial ecology of livestock can contribute to achieving the goals of better foods and a cleaner environment. Culture-independent microbiological technologies now permit comprehensive study of complex microbial communities in their natural environments. Microbiotas associated with both humans and animals provide myriad beneficial services to their hosts that, if lost or diminished, could compromise host health. Dysfunctional microbial communities have been noted in several human conditions, including inflammatory bowel disease, obesity, and antibiotic-associated diarrhea. Examination of the mechanisms by which the human microbiota influences health and disease susceptibility can inform similar studies of host-microbe function in the animal sciences. Insights gained from human studies indicate strategies to raise not only healthier livestock, through selective manipulation of microbial communities, but also healthier humans.

The Human Microbiome and Infectious Diseases: Beyond Koch

A century after Robert Koch linked individual cultured microbes to specific diseases (Koch's postulates), it has become increasingly apparent that the complex community of microorganisms associated with the human body plays a key role in health and disease. The National Institutes of Health recently announced the Human Microbiome Project as part of the NIH Roadmap for medical research, with a primary goal of advancing our understanding of the relationships among host-associated microbial communities, health, and disease. Many physicians and researchers, however, have only passing familiarity with the concepts involved in the study and therapeutic manipulation of complex microbial communities. This special issue was conceived to accomplish several goals. We wanted to provide readily accessible overviews of the concepts and methods used in the study of complex microbial communities, and demonstrate how changes in indigenous microbial communities can play a role in diseases such as antibiotic-associated diarrhea and bacterial vaginosis. We also set out to find examples of how probiotics can be used for the therapeutic manipulation of the indigenous microbiota. We were fortunate to receive a strong collection of review articles and primary research manuscripts to meet the goals of this special issue. In the first article “Conceptualizing the human microbiota: from multicelled organ to ecological community,” B. Foxman et al. present a novel conceptualization of the human microbiome that blends perspectives of epidemiologists, classical ecologists and infectious diseases physicians. The second article “Application of ecological network theory to the human microbiome,” by J. Foster et al., outlines how ecological network theory can be applied to studies of the human microbiome, while the third article “Interactions of the intestinal epithelium with the pathogen and the indigenous microbiota: a three way crosstalk,” by C. V. Srikanth and B. McCormick, review the interactions between epithelial pathogens and the indigenous microbiota in the mammalian gut. In the fourth article “Application of sequence-dependent electrophoresis fingerprinting in exploring biodiversity and population dynamics of human intestinal microbiota: what can be revealed?” G. Huys et al. review the use of sequence-dependent fingerprinting methods for studying the structure and dynamics of complex microbial systems using the human intestinal microbiota as an example. The fifth article “Ecological characterization of the colonic microbiota of normal and diarrheic dogs,” by J. Bell, employs such a fingerprinting method to study the canine colonic microbiota. The sixth article “Emerging insights into antibiotic-associated diarrhea and Clostridium difficile infection through the lens of microbial ecology,” by S. Walk and V. Young, discusses the role of the gut microbiota in antibiotic-associated diarrhea and Clostridium difficile infection while Y. Sanz et al., in the seventh article “Insights into the roles of gut microbes in obesity,” review the evidence for the role of gut microbes in obesity. In the eighth article “The human vaginal bacterial biota and bacterial vaginosis,” by S. Srinivasan and D. Fredericks review the human vaginal bacterial microbiota and the ninth article “Temporal shifts in microbial communities in non-pregnant african-american women with and without bacterial vaginosis,” by J. Wertz et al., examines this microbial community in the setting of bacterial vaginosis. The tenth article “Vaginal microbiota and the use of probiotics,” by S. Cribby et al. discusses the use of probiotics to alter the vaginal microbiota. Finally, the eleventh article “Probiotics and gastrointestinal infections,” by R. Britton and J. Versalovic, and the twelveth article “Probiotic bacteria influence the composition and function of the intestinal microbiota,” by P. O’Toole and J. Cooney, summarize the potential role of probiotics to influence gastrointestinal health.