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Quake, S.

Publications and source records attributed to Quake, S..

21 records · Page 2Linked to original sources

Virus-inclusive single cell RNA sequencing reveals molecular signature predictive of progression to severe dengue infection

Dengue virus (DENV) infection can result in severe complications. Yet, the understanding of the molecular correlates of severity is limited, partly due to difficulties in defining the peripheral blood mononuclear cells (PBMCs) that are associated with DENV in vivo. Additionally, there are currently no biomarkers predictive of progression to severe dengue (SD). Bulk transcriptomics data are difficult to interpret because blood consists of multiple cell types that may react differently to infection. Here we applied virus-inclusive single cell RNA-seq approach (viscRNA-Seq) to profile transcriptomes of thousands of single PBMCs derived early in the course of disease from six dengue patients and four healthy controls, and to characterize distinct DENV-associated leukocytes. Multiple genes, particularly interferon response genes, were upregulated in a cell-specific manner prior to progression to SD. Expression of MX2 in naive B cells and CD163 in CD14+ CD16+ monocytes was predictive of SD. The majority of DENV-associated cells in the blood of two patients who progressed to SD were naive IgM B cells expressing the CD69 and CXCR4 receptors and antiviral genes, followed by monocytes. Bystander uninfected B cells also demonstrated immune activation, and plasmablasts from two patients exhibited antibody lineages with convergently hypermutated heavy chain sequences. Lastly, assembly of the DENV genome revealed diversity at unexpected genomic sites. This study presents a multi-faceted molecular elucidation of natural dengue infection in humans and proposes biomarkers for prediction of SD, with implications for profiling any tissue and viral infection, and for the development of a dengue prognostic assay.\n\nSignificanceA fraction of the 400 million people infected with dengue annually progresses to severe dengue (SD). Yet, there are currently no biomarkers to effectively predict disease progression. We profiled the landscape of host transcripts and viral RNA in thousands of single blood cells from dengue patients prior to progressing to SD. We discovered cell-type specific immune activation and candidate predictive biomarkers. We also revealed preferential virus association with specific cell populations, particularly naive B cells and monocytes. We then explored immune activation of bystander cells, clonality and somatic evolution of adaptive immune repertoires, and viral genomics. This multi-faceted approach could advance understanding of pathogenesis of any viral infection, map an atlas of infected cells and promote the development of prognostics.

immunology↗

Aged blood inhibits hippocampal neurogenesis and activates microglia through VCAM1 at the blood-brain barrier

An aged circulatory environment can promote brain dysfunction and we hypothesized that the blood-brain barrier (BBB) mediates at least some of these effects. We observe brain endothelial cells (BECs) in the aged mouse hippocampus express an inflammatory transcriptional profile with focal upregulation of Vascular Cell Adhesion Molecule 1 (VCAM1), a protein that facilitates vascular-immune cell interactions. Concomitantly, the shed, soluble form of VCAM1 is prominently increased in the aged circulation of humans and mice, and aged plasma is sufficient to increase VCAM1 expression in cultured BECs and young mouse hippocampi. Systemic anti-VCAM1 antibody or genetic ablation of VCAM1 in BECs counteracts the detrimental effects of aged plasma on young brains and reverses aging aspects in old mouse brains. Thus, VCAM1 is a negative regulator of adult neurogenesis and inducer of microglial reactivity, establishing VCAM1 and the luminal side of the BBB as possible targets to treat age-related neurodegeneration.

neuroscience↗

PhaMers identifies novel bacteriophage sequences from thermophilic hot springs

Metagenomic sequencing approaches have become popular for the purpose of dissecting environmental microbial diversity, leading to the characterization of novel microbial lineages. In addition of bacterial and fungal genomes, metagenomic analysis can also reveal genomes of viruses that infect microbial cells. Because of their small genome size and limited knowledge of phage diversity, discovering novel phage sequences from metagenomic data is often challenging. Here we describe PhaMers (Phage k-Mers). a phage identification tool that uses supervised learning to classify metagenomic contigs as phage or non-phage on the basis of tetranucleotide frequencies. a technique that does not depend on existing gene annotations. PhaMers compares the tetranucleotide frequencies of metagenomic contigs to phage and bacteria references from online databases. resulting in assignments of lower level phage taxonomy based on sequence similarity. Using PhaMers. we identified 103 novel phage sequences from hot spring samples of Yellowstone National Park based on data generated from a microfluidic-based minimetagenomic approach. We analyzed assembled contigs over 5 kbp in length using PhaMers and compared the results with those generated by VirSorter, a publicly available phage identification and annotation package. We analyzed the performance of phage genome prediction and taxonomic classification using PhaMers. and presented putative hosts and taxa for some of the novel phage sequences. Finally. mini-metagenomic occurrence profiles of phage and prokaryotic genomes were used to verify putative hosts.

bioinformatics↗