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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.

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.

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.

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.

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.

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