Dynamic Colonization of Microbes and Their Functions after Fecal Microbiota Transplantation for Inflammatory Bowel Disease.

For fecal microbiota transplantation (FMT) to be successful in immune diseases like inflammatory bowel disease, it is assumed that therapeutic microbes and their beneficial functions and immune interactions must colonize a recipient patient and persist in sufficient quantity and for a sufficient period of time to produce a clinical benefit. Few studies, however, have comprehensively profiled the colonization and persistence of transferred microbes along with the transfer of their microbial functions and interactions with the host immune system. Using 16S, metagenomic, and immunoglobulin A (IgA) sequencing, we analyzed hundreds of longitudinal microbiome samples from a randomized controlled trial of 12 patients with ulcerative colitis who received fecal transplant or placebo for 12 weeks. We uncovered diverse competitive dynamics among donor and patient strains, showing that persistence of transferred microbes is far from static. Indeed, one patient experienced a dramatic loss of donor bacteria 10 weeks into the trial, coinciding with a bloom of pathogenic bacteria and worsening symptoms. We evaluated the transfer of microbial functions, including desired ones, such as butyrate production, and unintended ones, such as antibiotic resistance. By profiling bacteria coated with IgA, we identified bacteria associated with inflammation and found that microbial interactions with the host immune system can be transferred across people, which could play a role in gut microbiome therapeutics for immune-related diseases. Our findings shed light on the colonization dynamics of gut microbes and their functions in the context of FMT to treat a complex disease-information that may provide a foundation for developing more-targeted therapeutics. IMPORTANCE Fecal microbiota transplantation (FMT)-transferring fecal microbes from a healthy donor to a sick patient-has shown promise for gut diseases such as inflammatory bowel disease. Unlike pharmaceuticals, however, fecal transplants are complex mixtures of living organisms, which must then interact with the microbes and immune system of the recipient. We sought to understand these interactions by tracking the microbes of 12 inflammatory bowel disease patients who received fecal transplants for 12 weeks. We uncovered a range of dynamics. For example, one patient experienced successful transfer of donor bacteria, only to lose them after 10 weeks. We similarly evaluated transfer of microbial functions, including how they interacted with the recipient's immune system. Our findings shed light on the colonization dynamics of gut microbes, as well as their functions in the context of FMT-information that may provide a critical foundation for the development of more-targeted therapeutics.

Beyond Fecal Microbiota Transplantation: Developing Drugs from the Microbiome.

The transfer of live gut microbes may transform patient care across a range of autoimmune, metabolic, hepatic, and infectious diseases. One early approach, fecal microbiota transplantation, has shown promise in Clostridiodes difficile infection and the potential for improving clinical and public health outcomes for other antibiotic-resistant bacteria. These clinical successes have motivated the development of microbiome drugs, which will need to address challenges in safety, uniformity, and delivery while seeking to preserve the benefits of using whole microbiome communities as novel therapeutics and an innovative platform for drug discovery.

Genome and sequence determinants governing the expression of horizontally acquired DNA in bacteria.

While horizontal gene transfer is prevalent across the biosphere, the regulatory features that enable expression and functionalization of foreign DNA remain poorly understood. Here, we combine high-throughput promoter activity measurements and large-scale genomic analysis of regulatory regions to investigate the cross-compatibility of regulatory elements (REs) in bacteria. Functional characterization of thousands of natural REs in three distinct bacterial species revealed distinct expression patterns according to RE and recipient phylogeny. Host capacity to activate foreign promoters was proportional to their genomic GC content, while many low GC regulatory elements were both broadly active and had more transcription start sites across hosts. The difference in expression capabilities could be explained by the influence of the host GC content on the stringency of the AT-rich canonical σ70 motif necessary for transcription initiation. We further confirm the generalizability of this model and find widespread GC content adaptation of the σ70 motif in a set of 1,545 genomes from all major bacterial phyla. Our analysis identifies a key mechanism by which the strength of the AT-rich σ70 motif relative to a host's genomic GC content governs the capacity for expression of acquired DNA. These findings shed light on regulatory adaptation in the context of evolving genomic composition.

Microbiome predictors of dysbiosis and VRE decolonization in patients with recurrent C. difficile infections in a multi-center retrospective study.

The gastrointestinal microbiome is intrinsically linked to the spread of antibiotic resistance. Antibiotic treatment puts patients at risk for colonization by opportunistic pathogens like vancomycin resistant Enterococcus and Clostridioides difficile by destroying the colonization resistance provided by the commensal microbiota. Once colonized, the host is at a much higher risk for infection by that pathogen. Furthermore, we know that microbiome community differences are associated with disease states, but we do not have a good understanding of how we can use these changes to classify different patient populations. To that end, we have performed a multicenter retrospective analysis on patients who received fecal microbiota transplants to treat recurrent Clostridioides difficile infection. We performed 16S rRNA gene sequencing on fecal samples collected as part of this study and used these data to develop a microbiome disruption index. Our microbiome disruption index is a simple index that is predictive across cohorts, indications, and batch effects. We are able to classify pre-fecal transplant vs post-fecal transplant samples in patients with recurrent C. difficile infection, and we are able to predict, using previously-published data from a cohort of patients receiving hematopoietic stem cell transplants, which patients would go on to develop bloodstream infections. Finally, we also identified patients in this cohort that were initially colonized with vancomycin resistant Enterococcus and that 92% (11/12) were decolonized after the transplant, but the microbiome disruption index was unable to predict such decolonization. We, however, were able to compare the relative abundance of different taxa between the two groups, and we found that increased abundance of Enterobacteriaceae predicts whether patients were colonized with vancomycin resistant Enterococcus. This work is an early step towards a better understanding of how microbiome predictors can be used to help improve patient care and patient outcomes.

Metagenomic mining of regulatory elements enables programmable species-selective gene expression.

Robust and predictably performing synthetic circuits rely on the use of well-characterized regulatory parts across different genetic backgrounds and environmental contexts. Here we report the large-scale metagenomic mining of thousands of natural 5' regulatory sequences from diverse bacteria, and their multiplexed gene expression characterization in industrially relevant microbes. We identified sequences with broad and host-specific expression properties that are robust in various growth conditions. We also observed substantial differences between species in terms of their capacity to utilize exogenous regulatory sequences. Finally, we demonstrate programmable species-selective gene expression that produces distinct and diverse output patterns in different microbes. Together, these findings provide a rich resource of characterized natural regulatory sequences and a framework that can be used to engineer synthetic gene circuits with unique and tunable cross-species functionality and properties, and also suggest the prospect of ultimately engineering complex behaviors at the community level.

Strain Tracking Reveals the Determinants of Bacterial Engraftment in the Human Gut Following Fecal Microbiota Transplantation.

Fecal microbiota transplantation (FMT) from healthy donor to patient is a treatment for microbiome-associated diseases. Although the success of FMT requires donor bacteria to engraft in the patient's gut, the forces governing engraftment in humans are unknown. Here we use an ongoing clinical experiment, the treatment of recurrent Clostridium difficile infection, to uncover the rules of engraftment in humans. We built a statistical model that predicts which bacterial species will engraft in a given host, and developed Strain Finder, a method to infer strain genotypes and track them over time. We find that engraftment can be predicted largely from the abundance and phylogeny of bacteria in the donor and the pre-FMT patient. Furthermore, donor strains within a species engraft in an all-or-nothing manner and previously undetected strains frequently colonize patients receiving FMT. We validated these findings for metabolic syndrome, suggesting that the same principles of engraftment extend to other indications.

Profiling Living Bacteria Informs Preparation of Fecal Microbiota Transplantations.

Fecal microbiota transplantation is a compelling treatment for recurrent Clostridium difficile infections, with potential applications against other diseases associated with changes in gut microbiota. But variability in fecal bacterial communities-believed to be the therapeutic agent-can complicate or undermine treatment efficacy. To understand the effects of transplant preparation methods on living fecal microbial communities, we applied a DNA-sequencing method (PMA-seq) that uses propidium monoazide (PMA) to differentiate between living and dead fecal microbes, and we created an analysis pipeline to identify individual bacteria that change in abundance between samples. We found that oxygen exposure degraded fecal bacterial communities, whereas freeze-thaw cycles and lag time between donor defecation and transplant preparation had much smaller effects. Notably, the abundance of Faecalibacterium prausnitzii-an anti-inflammatory commensal bacterium whose absence is linked to inflammatory bowel disease-decreased with oxygen exposure. Our results indicate that some current practices for preparing microbiota transplant material adversely affect living fecal microbial content and highlight PMA-seq as a valuable tool to inform best practices and evaluate the suitability of clinical fecal material.

Natural bacterial communities serve as quantitative geochemical biosensors.

UNLABELLED: Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive. IMPORTANCE: Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Transfer of noncoding DNA drives regulatory rewiring in bacteria.

Understanding the mechanisms that generate variation is a common pursuit unifying the life sciences. Bacteria represent an especially striking puzzle, because closely related strains possess radically different metabolic and ecological capabilities. Differences in protein repertoire arising from gene transfer are currently considered the primary mechanism underlying phenotypic plasticity in bacteria. Although bacterial coding plasticity has been extensively studied in previous decades, little is known about the role that regulatory plasticity plays in bacterial evolution. Here, we show that bacterial genes can rapidly shift between multiple regulatory modes by acquiring functionally divergent nonhomologous promoter regions. Through analysis of 270,000 regulatory regions across 247 genomes, we demonstrate that regulatory "switching" to nonhomologous alternatives is ubiquitous, occurring across the bacterial domain. Using comparative transcriptomics, we show that at least 16% of the expression divergence between Escherichia coli strains can be explained by this regulatory switching. Further, using an oligonucleotide regulatory library, we establish that switching affects bacterial promoter architecture. We provide evidence that regulatory switching can occur through horizontal regulatory transfer, which allows regulatory regions to move across strains, and even genera, independently from the genes they regulate. Finally, by experimentally characterizing the fitness effect of a regulatory transfer on a pathogenic E. coli strain, we demonstrate that regulatory switching elicits important phenotypic consequences. Taken together, our findings expose previously unappreciated regulatory plasticity in bacteria and provide a gateway for understanding bacterial phenotypic variation and adaptation.

Fecal microbiota transplant for relapsing Clostridium difficile infection using a frozen inoculum from unrelated donors: a randomized, open-label, controlled pilot study.

BACKGROUND: Recurrent Clostridium difficile infection (CDI) with poor response to standard antimicrobial therapy is a growing medical concern. We aimed to investigate the outcomes of fecal microbiota transplant (FMT) for relapsing CDI using a frozen suspension from unrelated donors, comparing colonoscopic and nasogastric tube (NGT) administration. METHODS: Healthy volunteer donors were screened and a frozen fecal suspension was generated. Patients with relapsing/refractory CDI were randomized to receive an infusion of donor stools by colonoscopy or NGT. The primary endpoint was clinical resolution of diarrhea without relapse after 8 weeks. The secondary endpoint was self-reported health score using standardized questionnaires. RESULTS: A total of 20 patients were enrolled, 10 in each treatment arm. Patients had a median of 4 (range, 2-16) relapses prior to study enrollment, with 5 (range, 3-15) antibiotic treatment failures. Resolution of diarrhea was achieved in 14 patients (70%) after a single FMT (8 of 10 in the colonoscopy group and 6 of 10 in the NGT group). Five patients were retreated, with 4 obtaining cure, resulting in an overall cure rate of 90%. Daily number of bowel movements changed from a median of 7 (interquartile range [IQR], 5-10) the day prior to FMT to 2 (IQR, 1-2) after the infusion. Self-ranked health score improved significantly, from a median of 4 (IQR, 2-6) before transplant to 8 (IQR, 5-9) after transplant. No serious or unexpected adverse events occurred. CONCLUSIONS: In our initial feasibility study, FMT using a frozen inoculum from unrelated donors is effective in treating relapsing CDI. NGT administration appears to be as effective as colonoscopic administration. CLINICAL TRIALS REGISTRATION: NCT01704937.

'Hygienic' lymphocytes convey increased cancer risk.

Risk of developing inflammation-associated cancers has increased in industrialized countries during the past 30 years. One possible explanation is societal hygiene practices with use of antibiotics and Caesarian births that provide too few early life exposures of beneficial microbes. Building upon a 'hygiene hypothesis' model whereby prior microbial exposures lead to beneficial changes in CD4+ lymphocytes, here we use an adoptive cell transfer model and find that too few prior microbe exposures alternatively result in increased inflammation-associated cancer growth in susceptible recipient mice. Specifically, purified CD4+ lymphocytes collected from 'restricted flora' donors increases multiplicity and features of malignancy in intestinal polyps of recipient ApcMin/+ mice, coincident with increased inflammatory cell infiltrates and instability of the intestinal microbiota. We conclude that while a competent immune system serves to maintain intestinal homeostasis and good health, under hygienic rearing conditions CD4+ lymphocytes instead exacerbate inflammation-associated tumorigenesis, subsequently contributing to more frequent cancers in industrialized societies.

Computational methods for high-throughput comparative analyses of natural microbial communities.

One of the most widely employed methods in metagenomics is the amplification and sequencing of the highly conserved ribosomal RNA (rRNA) genes from organisms in complex microbial communities. rRNA surveys, typically using the 16S rRNA gene for prokaryotic identification, provide information about the total diversity and taxonomic affiliation of organisms present in a sample. Greatly enhanced by high-throughput sequencing, these surveys have uncovered the remarkable diversity of uncultured organisms and revealed unappreciated ecological roles ranging from nutrient cycling to human health. This chapter outlines the best practices for comparative analyses of microbial community surveys. We explain how to transform raw data into meaningful units for further analysis and discuss how to calculate sample diversity and community distance metrics. Finally, we outline how to find associations of species with specific metadata and true correlations between species from compositional data. We focus on data generated by next-generation sequencing platforms, using the Illumina platform as a test case, because of its widespread use especially among researchers just entering the field.

Ecology drives a global network of gene exchange connecting the human microbiome.

Horizontal gene transfer (HGT), the acquisition of genetic material from non-parental lineages, is known to be important in bacterial evolution. In particular, HGT provides rapid access to genetic innovations, allowing traits such as virulence, antibiotic resistance and xenobiotic metabolism to spread through the human microbiome. Recent anecdotal studies providing snapshots of active gene flow on the human body have highlighted the need to determine the frequency of such recent transfers and the forces that govern these events. Here we report the discovery and characterization of a vast, human-associated network of gene exchange, large enough to directly compare the principal forces shaping HGT. We show that this network of 10,770 unique, recently transferred (more than 99% nucleotide identity) genes found in 2,235 full bacterial genomes, is shaped principally by ecology rather than geography or phylogeny, with most gene exchange occurring between isolates from ecologically similar, but geographically separated, environments. For example, we observe 25-fold more HGT between human-associated bacteria than among ecologically diverse non-human isolates (P = 3.0 × 10(-270)). We show that within the human microbiome this ecological architecture continues across multiple spatial scales, functional classes and ecological niches with transfer further enriched among bacteria that inhabit the same body site, have the same oxygen tolerance or have the same ability to cause disease. This structure offers a window into the molecular traits that define ecological niches, insight that we use to uncover sources of antibiotic resistance and identify genes associated with the pathology of meningitis and other diseases.