Microbiome analyses of blood and tissues suggest cancer diagnostic approach.

Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1-10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress.

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.

Single-Cell-Genomics-Facilitated Read Binning of Candidate Phylum EM19 Genomes from Geothermal Spring Metagenomes.

The vast majority of microbial life remains uncatalogued due to the inability to cultivate these organisms in the laboratory. This "microbial dark matter" represents a substantial portion of the tree of life and of the populations that contribute to chemical cycling in many ecosystems. In this work, we leveraged an existing single-cell genomic data set representing the candidate bacterial phylum "Calescamantes" (EM19) to calibrate machine learning algorithms and define metagenomic bins directly from pyrosequencing reads derived from Great Boiling Spring in the U.S. Great Basin. Compared to other assembly-based methods, taxonomic binning with a read-based machine learning approach yielded final assemblies with the highest predicted genome completeness of any method tested. Read-first binning subsequently was used to extract Calescamantes bins from all metagenomes with abundant Calescamantes populations, including metagenomes from Octopus Spring and Bison Pool in Yellowstone National Park and Gongxiaoshe Spring in Yunnan Province, China. Metabolic reconstruction suggests that Calescamantes are heterotrophic, facultative anaerobes, which can utilize oxidized nitrogen sources as terminal electron acceptors for respiration in the absence of oxygen and use proteins as their primary carbon source. Despite their phylogenetic divergence, the geographically separate Calescamantes populations were highly similar in their predicted metabolic capabilities and core gene content, respiring O2, or oxidized nitrogen species for energy conservation in distant but chemically similar hot springs.

Robustness of cancer microbiome signals over a broad range of methodological variation.

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

The long noncoding RNA Malat1 regulates CD8+ T cell differentiation by mediating epigenetic repression.

During an immune response to microbial infection, CD8+ T cells give rise to short-lived effector cells and memory cells that provide sustained protection. Although the transcriptional programs regulating CD8+ T cell differentiation have been extensively characterized, the role of long noncoding RNAs (lncRNAs) in this process remains poorly understood. Using a functional genetic knockdown screen, we identified the lncRNA Malat1 as a regulator of terminal effector cells and the terminal effector memory (t-TEM) circulating memory subset. Evaluation of chromatin-enriched lncRNAs revealed that Malat1 grouped with trans lncRNAs that exhibit increased RNA interactions at gene promoters and gene bodies. Moreover, we observed that Malat1 was associated with increased H3K27me3 deposition at a number of memory cell-associated genes through a direct interaction with Ezh2, thereby promoting terminal effector and t-TEM cell differentiation. Our findings suggest an important functional role of Malat1 in regulating CD8+ T cell differentiation and broaden the knowledge base of lncRNAs in CD8+ T cell biology.

Early precursors and molecular determinants of tissue-resident memory CD8+ T lymphocytes revealed by single-cell RNA sequencing.

During an immune response to microbial infection, CD8+ T cells give rise to distinct classes of cellular progeny that coordinately mediate clearance of the pathogen and provide long-lasting protection against reinfection, including a subset of noncirculating tissue-resident memory (TRM) cells that mediate potent protection within nonlymphoid tissues. Here, we used single-cell RNA sequencing to examine the gene expression patterns of individual CD8+ T cells in the spleen and small intestine intraepithelial lymphocyte (siIEL) compartment throughout the course of their differentiation in response to viral infection. These analyses revealed previously unknown transcriptional heterogeneity within the siIEL CD8+ T cell population at several stages of differentiation, representing functionally distinct TRM cell subsets and a subset of TRM cell precursors within the tissue early in infection. Together, these findings may inform strategies to optimize CD8+ T cell responses to protect against microbial infection and cancer.

Heterogeneity and clonal relationships of adaptive immune cells in ulcerative colitis revealed by single-cell analyses.

Inflammatory bowel disease (IBD) encompasses a spectrum of gastrointestinal disorders driven by dysregulated immune responses against gut microbiota. We integrated single-cell RNA and antigen receptor sequencing to elucidate key components, cellular states, and clonal relationships of the peripheral and gastrointestinal mucosal immune systems in health and ulcerative colitis (UC). UC was associated with an increase in IgG1+ plasma cells in colonic tissue, increased colonic regulatory T cells characterized by elevated expression of the transcription factor ZEB2, and an enrichment of a γδ T cell subset in the peripheral blood. Moreover, we observed heterogeneity in CD8+ tissue-resident memory T (TRM) cells in colonic tissue, with four transcriptionally distinct states of differentiation observed across health and disease. In the setting of UC, there was a marked shift of clonally related CD8+ TRM cells toward an inflammatory state, mediated, in part, by increased expression of the T-box transcription factor Eomesodermin. Together, these results provide a detailed atlas of transcriptional changes occurring in adaptive immune cells in the context of UC and suggest a role for CD8+ TRM cells in IBD.

Novel exons and splice variants in the human antibody heavy chain identified by single cell and single molecule sequencing.

Antibody heavy chains contain a variable and a constant region. The constant region of the antibody heavy chain is encoded by multiple groups of exons which define the isotype and therefore many functional characteristics of the antibody. We performed both single B cell RNAseq and long read single molecule sequencing of antibody heavy chain transcripts and were able to identify novel exons for IGHA1 and IGHA2 as well as novel isoforms for IGHM antibody heavy chain.

The phylogenetic and geographic structure of Y-chromosome haplogroup R1a.

R1a-M420 is one of the most widely spread Y-chromosome haplogroups; however, its substructure within Europe and Asia has remained poorly characterized. Using a panel of 16 244 male subjects from 126 populations sampled across Eurasia, we identified 2923 R1a-M420 Y-chromosomes and analyzed them to a highly granular phylogeographic resolution. Whole Y-chromosome sequence analysis of eight R1a and five R1b individuals suggests a divergence time of ∼25,000 (95% CI: 21,300-29,000) years ago and a coalescence time within R1a-M417 of ∼5800 (95% CI: 4800-6800) years. The spatial frequency distributions of R1a sub-haplogroups conclusively indicate two major groups, one found primarily in Europe and the other confined to Central and South Asia. Beyond the major European versus Asian dichotomy, we describe several younger sub-haplogroups. Based on spatial distributions and diversity patterns within the R1a-M420 clade, particularly rare basal branches detected primarily within Iran and eastern Turkey, we conclude that the initial episodes of haplogroup R1a diversification likely occurred in the vicinity of present-day Iran.

A quantitative comparison of single-cell whole genome amplification methods.

Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA) is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of E. coli DNA: Multiple Displacement Amplification (MDA), Multiple Annealing and Looping Based Amplification Cycles (MALBAC), and the PicoPLEX single-cell WGA kit (NEB-WGA). We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for de-novo genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.