Highly multiplexed spatial mapping of microbial communities.

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density1 and rich diversity2 of species in environmental microbiomes and the limitations of optical imaging technology3-6. Here we introduce high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging and decoding based on machine learning to create micrometre-scale maps of the locations and identities of hundreds of microbial species in complex communities. We show that 10-bit HiPR-FISH can distinguish between 1,023 isolates of Escherichia coli, each fluorescently labelled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and analysis of single-cell images, reveals the disruption of spatial networks in the mouse gut microbiome in response to treatment with antibiotics, and the longitudinal stability of spatial architectures in the human oral plaque microbiome. Combined with super-resolution imaging, HiPR-FISH shows the diverse strategies of ribosome organization that are exhibited by taxa in the human oral microbiome. HiPR-FISH provides a framework for analysing the spatial ecology of environmental microbial communities at single-cell resolution.

Segatella copri strains adopt distinct roles within a single individual's gut.

Segatella copri is a dominant member of individuals' gut microbiomes worldwide, especially in non-Western populations. Although metagenomic assembly and genome isolation have shed light on the genetic diversity of S. copri, the lack of available isolates from this clade has resulted in a limited understanding of how members' genetic diversity translates into phenotypic diversity. Within the confines of a single gut microbiome, we have isolated 63 strains from diverse lineages of S. copri. We performed comparative analyses that exposed differences in cellular morphologies, preferences in polysaccharide utilization, yield of short-chain fatty acids, and antibiotic resistance across isolates. We further show that exposure to S. copri lineages either evokes strong or muted transcriptional responses in human intestinal epithelial cells. Our study exposes large phenotypic differences within related S. copri isolates, extending this to host-microbe interactions.

Host-microbiome protein-protein interactions capture disease-relevant pathways.

BACKGROUND: Host-microbe interactions are crucial for normal physiological and immune system development and are implicated in a variety of diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), obesity, and type 2 diabetes (T2D). Despite large-scale case-control studies aimed at identifying microbial taxa or genes involved in pathogeneses, the mechanisms linking them to disease have thus far remained elusive. RESULTS: To identify potential pathways through which human-associated bacteria impact host health, we leverage publicly-available interspecies protein-protein interaction (PPI) data to find clusters of microbiome-derived proteins with high sequence identity to known human-protein interactors. We observe differential targeting of putative human-interacting bacterial genes in nine independent metagenomic studies, finding evidence that the microbiome broadly targets human proteins involved in immune, oncogenic, apoptotic, and endocrine signaling pathways in relation to IBD, CRC, obesity, and T2D diagnoses. CONCLUSIONS: This host-centric analysis provides a mechanistic hypothesis-generating platform and extensively adds human functional annotation to commensal bacterial proteins.

Inflammatory Bowel Disease-Associated Gut Commensals Degrade Components of the Extracellular Matrix.

Extracellular matrix (ECM) remodeling has emerged as a key feature of inflammatory bowel disease (IBD), and ECM fragments have been proposed as markers of clinical disease severity. Recent studies report increased protease activity in the gut microbiota of IBD patients. Nonetheless, the relationship between gut microbiota and ECM remodeling has remained unexplored. We hypothesized that members of the human gut microbiome could degrade the host ECM and that bacteria-driven remodeling, in turn, could enhance colonic inflammation. Through a variety of in vitro assays, we first confirmed that multiple bacterial species found in the human gut are capable of degrading specific ECM components. Clinical stool samples obtained from ulcerative colitis patients also exhibited higher levels of proteolytic activity in vitro, compared to those of their healthy counterparts. Furthermore, culture supernatants from bacteria species that are capable of degrading human ECM accelerated inflammation in dextran sodium sulfate (DSS)-induced colitis. Finally, we identified several of the bacterial proteases and carbohydrate degrading enzymes (CAZymes) that are potentially responsible for ECM degradation in vitro. Some of these protease families and CAZymes were also found in increased abundance in a metagenomic cohort of IBD. These results demonstrate that some commensal bacteria in the gut are indeed capable of degrading components of human ECM in vitro and suggest that this proteolytic activity may be involved in the progression of IBD. A better understanding of the relationship between nonpathogenic gut microbes, host ECM, and inflammation could be crucial to elucidating some of the mechanisms underlying host-bacteria interactions in IBD and beyond. IMPORTANCE Healthy gut epithelial cells form a barrier that keeps bacteria and other substances from entering the blood or tissues of the body. Those cells sit on scaffolding that maintains the structure of the gut and informs our immune system about the integrity of this barrier. In patients with inflammatory bowel disease (IBD), breaks are formed in this cellular barrier, and bacteria gain access to the underlying tissue and scaffolding. In our study, we discovered that bacteria that normally reside in the gut can modify and disassemble the underlying scaffolding. Additionally, we discovered that changes to this scaffolding affect the onset of IBD in mouse models of colitis as well as the abilities of these mice to recover. We propose that this new information will reveal how breaks in the gut wall lead to IBD and will open up new avenues by which to treat patients with IBD.

Examining horizontal gene transfer in microbial communities.

Bacteria acquire novel DNA through horizontal gene transfer (HGT), a process that enables an organism to rapidly adapt to changing environmental conditions, provides a competitive edge and potentially alters its relationship with its host. Although the HGT process is routinely exploited in laboratories, there is a surprising disconnect between what we know from laboratory experiments and what we know from natural environments, such as the human gut microbiome. Owing to a suite of newly available computational algorithms and experimental approaches, we have a broader understanding of the genes that are being transferred and are starting to understand the ecology of HGT in natural microbial communities. This Review focuses on these new technologies, the questions they can address and their limitations. As these methods are applied more broadly, we are beginning to recognize the full extent of HGT possible within a microbiome and the punctuated dynamics of HGT, specifically in response to external stimuli. Furthermore, we are better characterizing the complex selective pressures on mobile genetic elements and the mechanisms by which they interact with the bacterial host genome.

Functions predict horizontal gene transfer and the emergence of antibiotic resistance.

Phylogenetic distance, shared ecology, and genomic constraints are often cited as key drivers governing horizontal gene transfer (HGT), although their relative contributions are unclear. Here, we apply machine learning algorithms to a curated set of diverse bacterial genomes to tease apart the importance of specific functional traits on recent HGT events. We find that functional content accurately predicts the HGT network [area under the receiver operating characteristic curve (AUROC) = 0.983], and performance improves further (AUROC = 0.990) for transfers involving antibiotic resistance genes (ARGs), highlighting the importance of HGT machinery, niche-specific, and metabolic functions. We find that high-probability not-yet detected ARG transfer events are almost exclusive to human-associated bacteria. Our approach is robust at predicting the HGT networks of pathogens, including Acinetobacter baumannii and Escherichia coli, as well as within localized environments, such as an individual's gut microbiome.

Mobile Gene Sequence Evolution within Individual Human Gut Microbiomes Is Better Explained by Gene-Specific Than Host-Specific Selective Pressures.

Pangenomes-the cumulative set of genes encoded by a population or species-arise from the interplay of horizontal gene transfer, drift, and selection. The balance of these forces in shaping pangenomes has been debated, and studies to date focused on ancient evolutionary time scales have suggested that pangenomes generally confer niche adaptation to their bacterial hosts. To shed light on pangenome evolution on shorter evolutionary time scales, we inferred the selective pressures acting on mobile genes within individual human microbiomes from 176 Fiji islanders. We mapped metagenomic sequence reads to a set of known mobile genes to identify single nucleotide variants (SNVs) and calculated population genetic metrics to infer deviations from a neutral evolutionary model. We found that mobile gene sequence evolution varied more by gene family than by human social attributes, such as household or village. Patterns of mobile gene sequence evolution could be qualitatively recapitulated with a simple evolutionary simulation without the need to invoke the adaptive value of mobile genes to either bacterial or human hosts. These results stand in contrast with the apparent adaptive value of pangenomes over longer evolutionary time scales. In general, the most highly mobile genes (i.e., those present in more distinct bacterial host genomes) tend to have higher metagenomic read coverage and an excess of low-frequency SNVs, consistent with their rapid spread across multiple bacterial species in the gut. However, a subset of mobile genes-including those involved in defense mechanisms and secondary metabolism-showed a contrasting signature of intermediate-frequency SNVs, indicating species-specific selective pressures or negative frequency-dependent selection on these genes. Together, our evolutionary models and population genetic data show that gene-specific selective pressures predominate over human or bacterial host-specific pressures during the relatively short time scales of a human lifetime.

Geographic differences in gut microbiota composition impact susceptibility to enteric infection.

Large-scale studies of human gut microbiomes have revealed broad differences in composition across geographically distinct populations. Yet, studies examining impacts of microbiome composition on various health outcomes typically focus on single populations, posing the question of whether compositional differences between populations translate into differences in susceptibility. Using germ-free mice humanized with microbiome samples from 30 donors representing three countries, we observe robust differences in susceptibility to Citrobacter rodentium, a model for enteropathogenic Escherichia coli infections, according to geographic origin. We do not see similar responses to Listeria monocytogenes infections. We further find that cohousing the most susceptible and most resistant mice confers protection from C. rodentium infection. This work underscores the importance of increasing global participation in microbiome studies related to health outcomes. Diverse cohorts are needed to identify both population-specific responses to specific microbiome interventions and to achieve broader-reaching biological conclusions that generalize across populations.

Widespread transfer of mobile antibiotic resistance genes within individual gut microbiomes revealed through bacterial Hi-C.

The gut microbiome harbors a 'silent reservoir' of antibiotic resistance (AR) genes that is thought to contribute to the emergence of multidrug-resistant pathogens through horizontal gene transfer (HGT). To counteract the spread of AR, it is paramount to know which organisms harbor mobile AR genes and which organisms engage in HGT. Despite methods that characterize the overall abundance of AR genes in the gut, technological limitations of short-read sequencing have precluded linking bacterial taxa to specific mobile genetic elements (MGEs) encoding AR genes. Here, we apply Hi-C, a high-throughput, culture-independent method, to surveil the bacterial carriage of MGEs. We compare two healthy individuals with seven neutropenic patients undergoing hematopoietic stem cell transplantation, who receive multiple courses of antibiotics, and are acutely vulnerable to the threat of multidrug-resistant infections. We find distinct networks of HGT across individuals, though AR and mobile genes are associated with more diverse taxa within the neutropenic patients than the healthy subjects. Our data further suggest that HGT occurs frequently over a several-week period in both cohorts. Whereas most efforts to understand the spread of AR genes have focused on pathogenic species, our findings shed light on the role of the human gut microbiome in this process.

The internationalization of human microbiome research.

The human microbiome has now been linked with myriad diseases, yet most of this research has been conducted on American and European populations that make up only 1/6th of the world's population. With growing recognition that human microbiomes differ tremendously across global populations, it is especially important to understand how these compositional differences impact health outcomes. Recent advances in infectious disease and malnutrition research have demonstrated the potential for microbiome-based strategies to address the biggest challenges in global health. This review highlights major advances toward understanding microbiome diversity across the world and its contributions to disease, and outlines key questions, challenges, and opportunities to broaden the scope of and promote inclusivity within microbiome research.

Detection of low-abundance bacterial strains in metagenomic datasets by eigengenome partitioning.

Analyses of metagenomic datasets that are sequenced to a depth of billions or trillions of bases can uncover hundreds of microbial genomes, but naive assembly of these data is computationally intensive, requiring hundreds of gigabytes to terabytes of RAM. We present latent strain analysis (LSA), a scalable, de novo pre-assembly method that separates reads into biologically informed partitions and thereby enables assembly of individual genomes. LSA is implemented with a streaming calculation of unobserved variables that we call eigengenomes. Eigengenomes reflect covariance in the abundance of short, fixed-length sequences, or k-mers. As the abundance of each genome in a sample is reflected in the abundance of each k-mer in that genome, eigengenome analysis can be used to partition reads from different genomes. This partitioning can be done in fixed memory using tens of gigabytes of RAM, which makes assembly and downstream analyses of terabytes of data feasible on commodity hardware. Using LSA, we assemble partial and near-complete genomes of bacterial taxa present at relative abundances as low as 0.00001%. We also show that LSA is sensitive enough to separate reads from several strains of the same species.