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Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities culturedin vitrofrom human feces to uncover simple assembly rules and develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Community membership was largely determined by the donor feces, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient, due to the ability of fast-growing organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that community assembly follows simple rules of nutrient utilization dynamics and provides a predictive framework for manipulating gut commensal communities through nutritional perturbations.

Summary Due to limitations on high-resolution strain tracking, selection dynamics during gut microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutations in genes involved in motility and metabolite utilization are reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates revealed linked alleles that demonstrate between-host transmission. A population-genetics model predicts substantial fitness advantages for certain mutants and that migration accounted for ∼10% of the resident microbiota each day. Treatment with ciprofloxacin suggests interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Significance Cas9 proteins have revolutionized biotechnology by enabling flexible and facile targeted cleavage of nucleic acids. Nearly all of these proteins are active only at moderate, near-physiological temperatures. Through mini-metagenomic sequencing of hot spring samples from Yellowstone National Park, we discovered and characterized a novel hyperthermophilic Cas9 protein from an unculturable Ignavibacterium. This Cas9 protein, IgnaviCas9, expands the temperature range at which targeted nucleic acid cleavage is possible, thus speeding the development of new biotechnological techniques. We demonstrated one such application by using IgnaviCas9 to deplete undesired amplicons during the amplification step of library preparation in sequencing workflows. This Cas9 protein underscores the exciting applications that can be made possible by exploring nature’s diversity., Clustered regularly interspaced short palindromic repeats (CRISPR)-associated 9 (Cas9) systems have been effectively harnessed to engineer the genomes of organisms from across the tree of life. Nearly all currently characterized Cas9 proteins are derived from mesophilic bacteria, and canonical Cas9 systems are challenged by applications requiring enhanced stability or elevated temperatures. We discovered IgnaviCas9, a Cas9 protein from a hyperthermophilic Ignavibacterium identified through mini-metagenomic sequencing of samples from a hot spring. IgnaviCas9 is active at temperatures up to 100 °C in vitro, which enables DNA cleavage beyond the 44 °C limit of Streptococcus pyogenes Cas9 (SpyCas9) and the 70 °C limit of both Geobacillus stearothermophilus Cas9 (GeoCas9) and Geobacillus thermodenitrificans T12 Cas9 (ThermoCas9). As a potential application of this enzyme, we demonstrate that IgnaviCas9 can be used in bacterial RNA-seq library preparation to remove unwanted cDNA from 16s ribosomal rRNA without increasing the number of steps, thus underscoring the benefits provided by its exceptional thermostability in improving molecular biology and genomic workflows. IgnaviCas9 is an exciting addition to the CRISPR-Cas9 toolbox and expands its temperature range.

Hydrothermal vents have been key to our understanding of the limits of life, and the metabolic and phylogenetic diversity of thermophilic organisms. Here we used environmental metagenomics combined with analysis of physico-chemical data and 16S rRNA amplicons to characterize the diversity, temperature optima, and biogeographic distribution of sediment-hosted microorganisms at the recently discovered Auka vents in the Gulf of California, the deepest known hydrothermal vent field in the Pacific Ocean. We recovered 325 metagenome assembled genomes (MAGs) representing 54 phyla, over 1/3 of the currently known phylum diversity, showing the microbial community in Auka hydrothermal sediments is highly diverse. Large scale 16S rRNA amplicon screening of 227 sediment samples across the vent field indicates that the MAGs are largely representative of the microbial community. Metabolic reconstruction of a vent-specific, deeply branching clade within the Desulfobacterota (Tharpobacteria) suggests these organisms metabolize sulfur using novel octaheme cytochrome-c proteins related to hydroxylamine oxidoreductase. Community-wide comparison of the average nucleotide identity of the Auka MAGs with MAGs from the Guaymas Basin vent field, found 400 km to the Northwest, revealed a remarkable 20% species-level overlap between vent sites, suggestive of long-distance species transfer and sediment colonization. An adapted version of a recently developed model for predicting optimal growth temperature to the Auka and Guaymas MAGs indicates several of these uncultured microorganisms could grow at temperatures exceeding the currently known upper limit of life. Extending this analysis to reference data shows that thermophily is a trait that has evolved frequently among Bacteria and Archaea. Combined, our results show that Auka vent field offers new perspectives on our understanding of hydrothermal vent microbiology.

Summary Diet modulates the gut microbiome, which in turn can impact the immune system. Here, we determined how two microbiota-targeted dietary interventions, plant-based fiber and fermented foods, influence the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study (n = 18/arm) combined with -omics measurements of microbiome and host, including extensive immune profiling, we found diet-specific effects. The high-fiber diet increased microbiome-encoded glycan-degrading carbohydrate active enzymes (CAZymes) despite stable microbial community diversity. Although cytokine response score (primary outcome) was unchanged, three distinct immunological trajectories in high-fiber consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented-food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in industrialized society.

Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

Background Candida parapsilosis is a common cause of invasive candidiasis, especially in newborn infants, and infections have been increasing over the past two decades. C. parapsilosis has been primarily studied in pure culture, leaving gaps in understanding of its function in a microbiome context. Results Here, we compare five unique C. parapsilosis genomes assembled from premature infant fecal samples, three of which are newly reconstructed, and analyze their genome structure, population diversity, and in situ activity relative to reference strains in pure culture. All five genomes contain hotspots of single nucleotide variants, some of which are shared by strains from multiple hospitals. A subset of environmental and hospital-derived genomes share variants within these hotspots suggesting derivation of that region from a common ancestor. Four of the newly reconstructed C. parapsilosis genomes have 4 to 16 copies of the gene RTA3, which encodes a lipid translocase and is implicated in antifungal resistance, potentially indicating adaptation to hospital antifungal use. Time course metatranscriptomics and metaproteomics on fecal samples from a premature infant with a C. parapsilosis blood infection revealed highly variable in situ expression patterns that are distinct from those of similar strains in pure cultures. For example, biofilm formation genes were relatively less expressed in situ, whereas genes linked to oxygen utilization were more highly expressed, indicative of growth in a relatively aerobic environment. In gut microbiome samples, C. parapsilosis co-existed with Enterococcus faecalis that shifted in relative abundance over time, accompanied by changes in bacterial and fungal gene expression and proteome composition. Conclusions The results reveal potentially medically relevant differences in Candida function in gut vs. laboratory environments, and constrain evolutionary processes that could contribute to hospital strain persistence and transfer into premature infant microbiomes.

SummaryMetabolism of dietary compounds by the gut microbiota generates a vast array of microbiome-dependent metabolites (MDMs), which are highly variable between individuals. The uremic MDMs (uMDMs) phenylacetylglutamine (PAG), p-cresol sulfate (PCS) and indoxyl sulfate (IS) accumulate during renal failure and are associated with poor outcomes. Targeted dietary interventions may reduce toxic MDMs generation; however, it is unclear if interindividual differences in diet or gut microbiome dominantly contribute to MDM variance. Here we use a 7-day homogeneous average American diet to standardize dietary precursor availability in 21 healthy individuals. Notably, the coefficient of variation in three uMDMs of interest, PAG, PCS, and IS (primary outcome), did not significantly decrease. The majority of circulating MDMs maintained variation despite identical diets. These results highlight the highly personalized profile of MDMs and limited contribution of short-term dietary heterogeneity, suggesting that dietary modification may need to be paired with microbial therapies to control MDM profiles.

SummaryDue to limitations on high-resolution strain tracking, selection dynamics during gut-microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutants involved in motility and utilization of abundant metabolites were reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates quantified evolutionary dynamics and revealed linked alleles. A population-genetics model predicted substantial fitness advantages for certain mutants and that migration accounted for ~10% of the resident microbiota each day. Treatment with ciprofloxacin demonstrated the interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Diet modulates the gut microbiome, and gut microbes, in turn, can impact the immune system. Here, we used two gut microbiota-targeted dietary interventions, plant-based fiber or fermented foods, to determine how each influences the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study design combined with -omics measurements of microbiome and host, including extensive immune profiling, we found distinct effects of each diet. High-fiber consumers showed increased gut microbiome-encoded glycan-degrading CAZymes despite stable community diversity. Three distinct immunological trajectories in high fiber-consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Our results indicate that fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in the industrialized society.

SUMMARY Mechanistic insights into the role of the human microbiome in the predisposition to and treatment of disease are limited by the lack of methods to precisely add or remove microbial strains or genes from complex communities. Here, we demonstrate that engineered bacteriophage M13 can be used to deliver DNA to Escherichia coli within the mouse gastrointestinal (GI) tract. Delivery of a programmable exogenous CRISPR-Cas9 system enables the strain-specific depletion of fluorescently marked isogenic strains during competitive colonization and genomic deletions that encompass the target gene in mice colonized with a single strain. Multiple mechanisms allow E. coli to escape targeting, including loss of the CRISPR array or even the entire CRISPR-Cas9 system. These results provide a robust and experimentally tractable platform for microbiome editing, a foundation for the refinement of this approach to increase targeting efficiency, and a proof of concept for the extension to other phage-bacterial pairs of interest., Graphical Abstract, In brief Lam et al. show that filamentous bacteriophage can be harnessed as agents of gene delivery to bacteria colonizing the gastrointestinal tract. Using M13 to deliver CRISPR-Cas9, they demonstrate sequence-specific targeting of GFP-marked E. coli in the gut and show that CRISPR-Cas9 can induce genomic deletions at the target site.

SummaryMechanistic understanding of the impacts of the gut microbiota on human health has been hampered by limited throughput in animal models. To enable systematic interrogation of gut-relevant microbial communities, here we generated hundreds of in vitro communities cultured from diverse stool samples in various media. Species composition revealed stool-derived communities that are phylogenetically complex, diverse, stable, and highly reproducible. Community membership depended on both medium and initial inoculum, with certain media preserving inoculum compositions. Different inocula yielded different community compositions, indicating their potential for personalized therapeutics. Communities were robust to freezing and large-volume culturing, enabling future translational applications. Defined communities were generated from isolates and reconstituted growth and composition similar to those of communities derived from stool inocula. Finally, in vitro experiments probing the response to ciprofloxacin successfully predicted many changes observed in vivo, including the resilience and sensitivity of each Bacteroides species. Thus, stool-derived in vitro communities constitute a powerful resource for microbiota research.

Despite the remarkable microbial diversity found within humans, our ability to link genes to phenotypes is based upon a handful of model microorganisms. We report a comparative genomics platform for Eggerthella lenta and other Coriobacteriia, a neglected taxon broadly relevant to human health and disease. We uncover extensive genetic and metabolic diversity and validate a tool for mapping phenotypes to genes and sequence variants. We also present a tool for the quantification of strains from metagenomic sequencing data, enabling the identification of genes that predict bacterial fitness. Competitive growth is reproducible under laboratory conditions and attributable to intrinsic growth rates and resource utilization. Unique signatures of invivo competition ingnotobiotic mice include an adhesin enriched in poor colonizers. Together, these computational and experimental resources represent a strong foundation for the continued mechanistic dissection of the Coriobacteriia and a template that can be applied to study other genetically intractable taxa.

Candida parapsilosisis a common cause of invasive candidiasis, especially in newborn infants, and infections have been increasing over the past two decades.C. parapsilosishas been primarily studied in pure culture, leaving gaps in understanding of its function in microbiome context. Here, we reconstructed five uniqueC. parapsilosisgenomes from premature infant fecal samples and analyzed their genome structure, population diversity andin situactivity relative to reference strains in pure culture. All five genomes contain hotspots of single nucleotide variants, some of which are shared by strains from multiple hospitals. A subset of environmental and hospital-derived genomes share variants within these hotspots suggesting derivation of that region from a common ancestor. Four of the newly reconstructedC. parapsilosisgenomes have four to sixteen copies of the gene RTA3, which encodes a lipid translocase and is implicated in antifungal resistance, potentially indicating adaptation to hospital antifungal use. Time course metatranscriptomics and metaproteomics on fecal samples from a premature infant with aC. parapsilosisblood infection revealed highly variablein situexpression patterns that are distinct from those of similar strains in pure cultures. For example, biofilm formation genes were relatively less expressedin situ, whereas genes linked to oxygen utilization were more highly expressed, indicative of growth in a relatively aerobic environment. In gut microbiome samples,C. parapsilosiscoexisted withEnterococcus faecalisthat shifted in relative abundance over time, accompanied by changes in bacterial and fungal gene expression and proteome composition. The results reveal potentially medically relevant differences in Candida function in gut vs. laboratory environments, and constrain evolutionary processes that could contribute to hospital strain persistence and transfer into premature infant microbiomes.

Efforts to probe the role of the gut microbiota in disease would benefit from a system in which patient-derived bacterial communities can be studied at scale. We addressed this by validating a strategy to propagate phylogenetically complex, diverse, stable, and highly reproducible stool-derived communities in vitro. We generated hundreds of in vitro communities cultured from diverse stool samples in various media; certain media generally preserved inoculum composition, and inocula from different subjects yielded source-specific community compositions. Upon colonization of germ-free mice, community composition was maintained, and the host proteome resembled the host from which the community was derived. Treatment with ciprofloxacin in vivo increased susceptibility to Salmonella invasion in vitro, and the in vitro response to ciprofloxacin was predictive of compositional changes observed in vivo, including the resilience and sensitivity of each Bacteroides species. These findings demonstrate that stool-derived in vitro communities can serve as a powerful system for microbiota research.

Single-cell RNA-sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation without prior knowledge has remained challenging. Here we describe a simple yet robust determinant of developmental potential—the number of detectably expressed genes per cell— and leverage this measure of transcriptional diversity to develop a new framework for predicting ordered differentiation states from scRNA-seq data. When evaluated on ~150,000 single-cell transcriptomes spanning 53 lineages and five species, our approach, called CytoTRACE, outperformed previous methods and ~19,000 molecular signatures for resolving experimentally-confirmed developmental trajectories. In addition, it enabled unbiased identification of tissue-resident stem cells, including cells with long-term regenerative potential. When used to analyze human breast tumors, we discovered candidate genes associated with less-differentiated luminal progenitor cells and validated GULP1 as a novel gene involved in tumorigenesis. Our study establishes a key RNA-based correlate of developmental potential and provides a new platform for robust delineation of cellular hierarchies (https://cytotrace.stanford.edu).

SummaryThat antibiotics alter microbiota composition and increase infection susceptibility is well known, but their generalizable effects on the gut commensal community and dependence on environmental variables remain open questions. Here, we systematically compared antibiotic responses in gnotobiotic and conventional mice across antibiotics, microbiotas, diets, and housing status. We identify remarkable resilience, whereby a humanized microbiota recovers before drug administration ends, with transient dominance of resistant Bacteroides and taxa-asymmetric reduction in diversity. In other cases, in vitro sensitivities were not predictive of in vivo responses, underscoring the significance of host and community contexts. A fiber-deficient diet exacerbated collapse of the microbiota and delayed recovery, despite the presence of a similar core community across diets at the point of maximal disturbance. Resilience to a second ciprofloxacin treatment was observed via response reprogramming, in which species replacement after ciprofloxacin treatment established resilience to a second treatment, and also through cross housing transmission. Single-housing drastically disrupted recovery, highlighting the importance of environmental microbial reservoirs and suggesting sanitation may exacerbate the duration of antibiotic-mediated disruption. Our findings highlight the ability of the commensal microbiota to deterministically adapt to large perturbations, and the translational potential for modulating diet, sanitation, and microbiota composition during antibiotics.

Significance Methane-producing microorganisms are thought to be among the earliest cellular life forms colonizing our planet, and are major contributors to the past and present global carbon cycle. Currently, all methanogens belong to the archaeal domain of life, and there is compounding evidence for a variety of methanogenic metabolisms among a wide distribution of archaeal phyla. However, the predominantly hydrogenotrophic (CO2-fixing) Euryarchaeota are distinct from the recently discovered methylotrophic (biomass-degrading) noneuryarchaea, making the shared ancestry and origins of all methanogens unclear. We discovered hydrogenotrophic methanogenesis in a thermophilic order of the Verstraetearchaeota, a noneuryarchaeote. The Verstraetearchaeota, hitherto known as methylotrophs, unify the origins of methanogenesis and shed light on how organisms can evolve to adapt from hydrogenotrophic to methylotrophic methane metabolism., Methanogenic archaea are major contributors to the global carbon cycle and were long thought to belong exclusively to the euryarchaeal phylum. Discovery of the methanogenesis gene cluster methyl-coenzyme M reductase (Mcr) in the Bathyarchaeota, and thereafter the Verstraetearchaeota, led to a paradigm shift, pushing back the evolutionary origin of methanogenesis to predate that of the Euryarchaeota. The methylotrophic methanogenesis found in the non-Euryarchaota distinguished itself from the predominantly hydrogenotrophic methanogens found in euryarchaeal orders as the former do not couple methanogenesis to carbon fixation through the reductive acetyl-CoA [Wood–Ljungdahl pathway (WLP)], which was interpreted as evidence for independent evolution of the two methanogenesis pathways. Here, we report the discovery of a complete and divergent hydrogenotrophic methanogenesis pathway in a thermophilic order of the Verstraetearchaeota, which we have named Candidatus Methanohydrogenales, as well as the presence of the WLP in the crenarchaeal order Desulfurococcales. Our findings support the ancient origin of hydrogenotrophic methanogenesis, suggest that methylotrophic methanogenesis might be a later adaptation of specific orders, and provide insight into how the transition from hydrogenotrophic to methylotrophic methanogenesis might have occurred.

CRISPR-Cas9 systems have been effectively harnessed to engineer the genomes of organisms from across the tree of life. Nearly all currently characterized Cas9 proteins are derived from mesophilic bacteria, and canonical Cas9 systems are challenged by applications requiring enhanced stability or elevated temperatures. We discovered IgnaviCas9, a Cas9 protein from a hyperthermophilic Ignavibacterium identified through mini-metagenomic sequencing of samples from a hot spring. IgnaviCas9 is active at temperatures up to 100 °C in vitro, which enables DNA cleavage beyond the 44 °C limit of Streptococcus pyogenes Cas9 (SpyCas9) and the 70 °C limit of both Geobacillus stearothermophilus Cas9 (GeoCas9) and Geobacillus thermodenitrificans T12 Cas9 (ThermoCas9). As a potential application of this enzyme, we demonstrated that IgnaviCas9 can be used in bacterial RNA-seq library preparation to remove unwanted cDNA from 16s ribosomal rRNA (rRNA) without increasing the number of steps, thus underscoring the benefits provided by its exceptional thermostability in improving molecular biology and genomic workflows. Taken together, IgnaviCas9 is an exciting addition to the CRISPR-Cas9 toolbox and expands its temperature range.

Known giant virus diversity is currently skewed towards viruses isolated from aquatic environments and cultivated in the laboratory. Here, we employ cultivation-independent metagenomics and mini-metagenomics on soils from the Harvard Forest, leading to the discovery of 16 novel giant viruses, chiefly recovered by mini-metagenomics. The candidate viruses greatly expand phylogenetic diversity of known giant viruses and either represented novel lineages or are affiliated with klosneuviruses, Cafeteria roenbergensis virus or tupanviruses. One assembled genome with a size of 2.4 Mb represents the largest currently known viral genome in the Mimiviridae, and others encode up to 80% orphan genes. In addition, we find more than 240 major capsid proteins encoded on unbinned metagenome fragments, further indicating that giant viruses are underexplored in soil ecosystems. The fact that most of these novel viruses evaded detection in bulk metagenomes suggests that mini-metagenomics could be a valuable approach to unearth viral giants., Current knowledge of giant virus diversity is largely based on samples from aquatic environments. Here the authors employ cultivation-independent metagenomics and mini-metagenomics on forest soil and identify 16 novel giant virus genomes, some of which representing novel lineages, including the so far largest genome in Mimiviridae.

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells., Author summary Genetically identical cells growing in the same environment can vary in their cellular state and behavior. Such heterogeneity may explain why some cells in an isogenic population can survive sudden severe environmental stress whereas other cells succumb. Cell-to-cell variation in gene expression has been linked to variable stress survival, but how and why transcript levels vary across the transcriptome in single cells is only beginning to emerge. Here, we used single-cell RNA sequencing (scRNA-seq) to measure cell-to-cell heterogeneity in the transcriptome of budding yeast (Saccharomyces cerevisiae). We find surprising patterns of variation across known sets of transcription factor targets, indicating that cells vary in their transcriptome profile both before and after stress exposure. scRNA-seq analysis combined with live-cell imaging of transcription factor activation dynamics revealed some cells in which the stress response was coordinately activated and other cells in which the traditional response was decoupled, suggesting unrecognized regulatory nuances that expand our understanding of stress response and survival.

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in singleS. cerevisiaecells treated with and without salt stress, to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells decouple expression of ribosomal protein genes from the environmental stress response, in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results reveal that cells maintain a cellular filter against decoupled bursts of transcription-factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

Metagenomics and single-cell genomics have enabled the discovery of many new genomes from previously unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and in many respects represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes from complex samples. In addition, by generating 96 sub-samples from each environmental sample, this method maintains high throughput, reduces sample complexity, and preserves single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes larger than 0.5 Mbps. These genomes represent novel lineages at different taxonomic levels, including three deeply branching lineages. Functional analysis revealed that these organisms utilize diverse pathways for energy metabolism. The resolution of this mini-metagenomic method enabled accurate quantification of genome abundance, even for genomes less than 1% in relative abundance. Our analyses also revealed a wide range of genome level single nucleotide polymorphism (SNP) distributions with nonsynonymous to synonymous ratio indicative of low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomic make it a powerful tool to dissect the genomic structure microbial communities while effectively preserving the fundamental unit of biology, the single cell.

Summary Antibiotics alter microbiota composition and increase infection susceptibility. However, the generalizable effects of antibiotics on and the contribution of environmental variables to gut commensals remain unclear. To address this, we tracked microbiota dynamics with high temporal and taxonomic resolution during antibiotic treatment in a controlled murine system by isolating variables such as diet, treatment history, and housing co-inhabitants. Human microbiotas were remarkably resilient and recovered during antibiotic treatment, with transient dominance of resistant Bacteroides and taxa-asymmetric diversity reduction. In certain cases, in vitro sensitivities were not predictive of in vivo responses, underscoring the significance of host and community context. A fiber-deficient diet exacerbated microbiota collapse and delayed recovery. Species replacement through cross housing after ciprofloxacin treatment established resilience to a second treatment. Single housing drastically disrupted recovery, highlighting the importance of environmental reservoirs. Our findings highlight deterministic microbiota adaptations to perturbations and the translational potential for modulating diet, sanitation, and microbiota composition during antibiotics.

A broad spectrum of metagenomic and single cell sequencing techniques have become popular for dissecting environmental microbial diversity, leading to the characterization of thousands of novel microbial lineages. In addition to recovering bacterial and archaeal genomes, metagenomic assembly can also produce genomes of viruses that infect microbial cells. Because of their diversity, lack of marker genes, and small genome size, identifying novel bacteriophage sequences from metagenomic data is often challenging, especially when the objective is to establish phage-host relationships. The present work describes a computational approach that uses supervised learning to classify metagenomic contigs as phage or non-phage as well as assigning phage taxonomy based on tetranucleotide frequencies. Furthermore, the method assigns phage-host relationships using co-occurrence statistics derived from a recently developed mini-metagenomic experimental technique. This work evaluates method performance at identifying viral contigs and predicting taxonomic classification using publicly available references. Then, using two mini-metagenomic datasets, over 100 novel phage contigs from hot spring samples of Yellowstone National Park are identified and assigned to putative microbial hosts. Results of this work demonstrate the value of combining viral sequence identification with mini-metagenomic experimental methods to understand the microbial ecosystem.

Background Cyanobacteria are important agents in global carbon and nitrogen cycling and hold great promise for biotechnological applications. Model organisms such as Synechocystis sp. and Synechococcus sp. have advanced our understanding of photosynthetic capacity and circadian behavior, mostly using population-level measurements in which the behavior of individuals cannot be monitored. Synechocystis sp. cells are small and divide slowly, requiring long-term experiments to track single cells. Thus, the cumulative effects of drift over long periods can cause difficulties in monitoring and quantifying cell growth and division dynamics. Results To overcome this challenge, we enhanced a microfluidic cell-culture device and developed an image analysis pipeline for robust lineage reconstruction. This allowed simultaneous tracking of many cells over multiple generations, and revealed that cells expand exponentially throughout their cell cycle. Generation times were highly correlated for sister cells, but not between mother and daughter cells. Relationships between birth size, division size, and generation time indicated that cell-size control was inconsistent with the “sizer” rule, where division timing is based on cell size, or the “timer” rule, where division occurs after a fixed time interval. Instead, single cell growth statistics were most consistent with the “adder” rule, in which division occurs after a constant increment in cell volume. Cells exposed to light-dark cycles exhibited growth and division only during the light period; dark phases pause but do not disrupt cell-cycle control. Conclusions Our analyses revealed that the “adder” model can explain both the growth-related statistics of single Synechocystis cells and the correlation between sister cell generation times. We also observed rapid phenotypic response to light-dark transitions at the single cell level, highlighting the critical role of light in cyanobacterial cell-cycle control. Our findings suggest that by monitoring the growth kinetics of individual cells we can build testable models of circadian control of the cell cycle in cyanobacteria. Electronic supplementary material The online version of this article (doi:10.1186/s12915-016-0344-4) contains supplementary material, which is available to authorized users.

Macrophages compose a major part of the tumor microenvironment (TME) in several types of cancer, including ovarian cancer [1]. Studies have shown that a high percentage of tumor associated macrophages (TAMs) correlates with a poor prognosis in ovarian cancer [2], due to the crucial role of TAMs in promoting tumor growth and angiogenesis [3,4]. Yet not much investigation has been executed to reveal the function of macrophages in ovarian cancer ascites, a hallmark of ovarian cancer. Previous gene expression analysis in TAMs often used bulk samples [5,6]. However, due to the complexity of the peritoneal environment, this approach had the effect of “dampening” rare and potentially informative signals from a heterogeneous population such as ascites macrophages. Therefore, we resorted to single-cell expression analysis to dissect the heterogeneity of ascites macrophages. Recent breakthroughs in single cell RNA-seq techniques have made it more cost effective to process a large number of samples at single cell resolutions. Here we used Fluidigm's Single-Cell Auto Prep System, a state-of-art technology for automate single cell cDNA synthesis [7]. We sequenced single ascites macrophages from ID8 murine ovarian cancer model and single alternatively activated bone marrow derived macrophages (BMDM-M2). When comparing the single cell expression profiles of ascites macrophages to BMDM using principle component analysis (PCA), we observed that the ascites macrophages scattered broadly and could be further divided into two groups, whereas BMDM were tightly clustered into one group. Furthermore, gene oncology (GO) analysis of highly expressed genes in each group revealed that ascites macrophages had a distinct gene expression profile from BMDM, highlighting the metabolic pathways, especially catabolic process. We are currently working on validating these findings in human patients with ovarian carcinoma. In summary, this work sheds light on the understanding of the role of ascites macrophages in ovarian cancer. 1. Qian BZ, Pollard JW. Cell. 2010;141:39-51. 2. He YF, Zhang MY, Wu X, et al. PLoS One. 2013;8:e79769. 3. Mantovani A, Germano G, Marchesi F, et al. Eur J Immunol 2011;41:2522-25. 4. Murray PJ, Wynn TA. Nat Rev Immunol, 2011;11:723-37. 5. The Cancer Genome Atlas Research Network. Nature. 2014;511:543-50. 6. The Cancer Genome Atlas Research Network. Nature. 2014;513:202-9. 7. Wu AR, Neff NF, Kalisky T, et al. Nat Methods. 2014;11:41-6. Citation Format: Huanhuan Mahsa He, Feiqiao Brian Yu, Stephen R. Quake, Oliver Dorigo. Single cell analysis of ascites macrophages in ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3202. doi:10.1158/1538-7445.AM2015-3202