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.

While 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 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: i) compliance to medicinal chemistry rules; ii) distinctive structural features; and iii) enrichment in “rod-like” over other shapes. 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.

While amyriad non-coding RNAs are knowntobe essential in cellular processes and misregulated in diseases,the development of RNA-targeted small molecule probes has met with limited success.T oe lucidate the guiding principles for selective small molecule/RNArecognition, 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.S everal striking trends emerged for bioactive RNAligands,including:1)Compliance to medicinal chemistry rules,2 )distinctive structural features, and 3) enrichment in rod-like shapes over others.T his 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.Supportinginformation and the ORCID identification number(s) for the author(s) of this article can be found under: https://doi.

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.

The spatiotemporal structure of the human microbiome1,2, proteome3 and metabolome4,5 reflects and determines regional intestinal physiology and may have implications for disease6. Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals7. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

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.

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18Commensal bacteria from the human intestinal microbiota play important roles in health 19 and disease. Research into the mechanisms by which these bacteria exert their effects is 20 hampered by the complexity of the microbiota and by the strict growth requirements of 21 the individual species. The assembly of ordered transposon insertion libraries, in which 22 38 39 Keywords: anaerobic bacteria, human gut microbiota, ordered mutant library, transposon 40 insertion, barcode, Bar-seq, Tn-seq, RB-TnSeq, high-throughput genetics, systems 41 biology 42 43 126 127Given a diverse transposon insertion pool, both the sorting portion of the protocol and the 128 strain identification portion can be accomplished in two weeks. As transformation 129 methods are developed for more bacterial residents of the human microbiota, we expect 130 that this protocol will enable the rapid and cost-effective investigation of microbe-host 131 interactions, metabolite production, and other genotype-phenotype relationships in an 132 ever-expanding set of bacteria. 133 134