Improved mouse models of the small intestine microbiota using region-specific sampling from humans.

Our understanding of region-specific microbial function within the gut is limited due to reliance on stool. Using a recently developed capsule device, we exploit regional sampling from the human intestines to develop models for interrogating small intestine (SI) microbiota composition and function. In vitro culturing of human intestinal contents produced stable, representative communities that robustly colonize the SI of germ-free mice. During mouse colonization, the combination of SI and stool microbes altered gut microbiota composition, functional capacity, and response to diet, resulting in increased diversity and reproducibility of SI colonization relative to stool microbes alone. Using a diverse strain library representative of the human SI microbiota, we constructed defined communities with taxa that largely exhibited the expected regional preferences. Response to a fiber-deficient diet was region-specific and reflected strain-specific fiber-processing and host mucus-degrading capabilities, suggesting that dietary fiber is critical for maintaining SI microbiota homeostasis. These tools should advance mechanistic modeling of the human SI microbiota and its role in disease and dietary responses.

Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron.

BACKGROUND: Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development. RESULTS: Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data. CONCLUSION: We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.

Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type-specific RNA splicing was discovered and analyzed across tissues within an individual.

Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale.

BACKGROUND: Populations of closely related microbial strains can be simultaneously present in bacterial communities such as the human gut microbiome. We recently developed a de novo genome assembly approach that uses read cloud sequencing to provide more complete microbial genome drafts, enabling precise differentiation and tracking of strain-level dynamics across metagenomic samples. In this case study, we present a proof-of-concept using read cloud sequencing to describe bacterial strain diversity in the gut microbiome of one hematopoietic cell transplantation patient over a 2-month time course and highlight temporal strain variation of gut microbes during therapy. The treatment was accompanied by diet changes and administration of multiple immunosuppressants and antimicrobials. METHODS: We conducted short-read and read cloud metagenomic sequencing of DNA extracted from four longitudinal stool samples collected during the course of treatment of one hematopoietic cell transplantation (HCT) patient. After applying read cloud metagenomic assembly to discover strain-level sequence variants in these complex microbiome samples, we performed metatranscriptomic analysis to investigate differential expression of antibiotic resistance genes. Finally, we validated predictions from the genomic and metatranscriptomic findings through in vitro antibiotic susceptibility testing and whole genome sequencing of isolates derived from the patient stool samples. RESULTS: During the 56-day longitudinal time course that was studied, the patient's microbiome was profoundly disrupted and eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allowed us to identify differences in substrain populations over time. Based on this, we predicted that particular mobile element integrations likely resulted in increased antibiotic resistance, which we further supported using in vitro antibiotic susceptibility testing. CONCLUSIONS: We find read cloud assembly to be useful in identifying key structural genomic strain variants within a metagenomic sample. These strains have fluctuating relative abundance over relatively short time periods in human microbiomes. We also find specific structural genomic variations that are associated with increased antibiotic resistance over the course of clinical treatment.

Ribosome biogenesis factor Ltv1 chaperones the assembly of the small subunit head.

The correct assembly of ribosomes from ribosomal RNAs (rRNAs) and ribosomal proteins (RPs) is critical, as indicated by the diseases caused by RP haploinsufficiency and loss of RP stoichiometry in cancer cells. Nevertheless, how assembly of each RP is ensured remains poorly understood. We use yeast genetics, biochemistry, and structure probing to show that the assembly factor Ltv1 facilitates the incorporation of Rps3, Rps10, and Asc1/RACK1 into the small ribosomal subunit head. Ribosomes from Ltv1-deficient yeast have substoichiometric amounts of Rps10 and Asc1 and show defects in translational fidelity and ribosome-mediated RNA quality control. These defects provide a growth advantage under some conditions but sensitize the cells to oxidative stress. Intriguingly, relative to glioma cell lines, breast cancer cells have reduced levels of LTV1 and produce ribosomes lacking RPS3, RPS10, and RACK1. These data describe a mechanism to ensure RP assembly and demonstrate how cancer cells circumvent this mechanism to generate diverse ribosome populations that can promote survival under stress.

Discovery of Key Physicochemical, Structural, and Spatial Properties of RNA-Targeted Bioactive Ligands.

While a myriad non-coding RNAs are known to be essential in cellular processes and misregulated in diseases, the development of RNA-targeted small molecule probes has met with limited success. To elucidate the guiding principles for selective small molecule/RNA recognition, we analyzed cheminformatic and shape-based descriptors for 104 RNA-targeted ligands with demonstrated biological activity (RNA-targeted BIoactive ligaNd Database, R-BIND). We then compared R-BIND to both FDA-approved small molecule drugs and RNA ligands without reported bioactivity. Several striking trends emerged for bioactive RNA ligands, including: 1) Compliance to medicinal chemistry rules, 2) distinctive structural features, and 3) enrichment in rod-like shapes over others. This work provides unique insights that directly facilitate the selection and synthesis of RNA-targeted libraries with the goal of efficiently identifying selective small molecule ligands for therapeutically relevant RNAs.