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1.
Sci Transl Med ; 14(660): eabi8633, 2022 08 31.
Article in English | MEDLINE | ID: mdl-36044598

ABSTRACT

Environmental enteropathy (EE) is a subclinical condition of the small intestine that is highly prevalent in low- and middle-income countries. It is thought to be a key contributing factor to childhood malnutrition, growth stunting, and diminished oral vaccine responses. Although EE has been shown to be the by-product of a recurrent enteric infection, its full pathophysiology remains unclear. Here, we mapped the cellular and molecular correlates of EE by performing high-throughput, single-cell RNA-sequencing on 33 small intestinal biopsies from 11 adults with EE in Lusaka, Zambia (eight HIV-negative and three HIV-positive), six adults without EE in Boston, United States, and two adults in Durban, South Africa, which we complemented with published data from three additional individuals from the same clinical site. We analyzed previously defined bulk-transcriptomic signatures of reduced villus height and decreased microbial translocation in EE and showed that these signatures may be driven by an increased abundance of surface mucosal cells-a gastric-like subset previously implicated in epithelial repair in the gastrointestinal tract. In addition, we determined cell subsets whose fractional abundances associate with EE severity, small intestinal region, and HIV infection. Furthermore, by comparing duodenal EE samples with those from three control cohorts, we identified dysregulated WNT and MAPK signaling in the EE epithelium and increased proinflammatory cytokine gene expression in a T cell subset highly expressing a transcriptional signature of tissue-resident memory cells in the EE cohort. Together, our work elucidates epithelial and immune correlates of EE and nominates cellular and molecular targets for intervention.


Subject(s)
HIV Infections , Intestinal Diseases , Adult , Child , HIV Infections/pathology , Humans , Intestinal Diseases/metabolism , Intestinal Diseases/pathology , Intestinal Mucosa/metabolism , South Africa , Zambia
2.
Nat Med ; 26(4): 511-518, 2020 04.
Article in English | MEDLINE | ID: mdl-32251406

ABSTRACT

Cellular immunity is critical for controlling intracellular pathogens, but individual cellular dynamics and cell-cell cooperativity in evolving human immune responses remain poorly understood. Single-cell RNA-sequencing (scRNA-seq) represents a powerful tool for dissecting complex multicellular behaviors in health and disease1,2 and nominating testable therapeutic targets3. Its application to longitudinal samples could afford an opportunity to uncover cellular factors associated with the evolution of disease progression without potentially confounding inter-individual variability4. Here, we present an experimental and computational methodology that uses scRNA-seq to characterize dynamic cellular programs and their molecular drivers, and apply it to HIV infection. By performing scRNA-seq on peripheral blood mononuclear cells from four untreated individuals before and longitudinally during acute infection5, we were powered within each to discover gene response modules that vary by time and cell subset. Beyond previously unappreciated individual- and cell-type-specific interferon-stimulated gene upregulation, we describe temporally aligned gene expression responses obscured in bulk analyses, including those involved in proinflammatory T cell differentiation, prolonged monocyte major histocompatibility complex II upregulation and persistent natural killer (NK) cell cytolytic killing. We further identify response features arising in the first weeks of infection, for example proliferating natural killer cells, which potentially may associate with future viral control. Overall, our approach provides a unified framework for characterizing multiple dynamic cellular responses and their coordination.


Subject(s)
Cell Communication , HIV Infections/genetics , HIV Infections/immunology , Immunity, Cellular/physiology , Single-Cell Analysis/methods , Acute Disease , Acute-Phase Reaction/genetics , Acute-Phase Reaction/immunology , Acute-Phase Reaction/pathology , Adolescent , Adult , Cell Communication/genetics , Cell Communication/immunology , Female , Gene Expression Profiling , Gene Regulatory Networks/immunology , HIV Infections/pathology , HIV-1/genetics , HIV-1/pathogenicity , Humans , Killer Cells, Natural/immunology , Killer Cells, Natural/metabolism , Leukocytes, Mononuclear/metabolism , Leukocytes, Mononuclear/pathology , Longitudinal Studies , Sequence Analysis, RNA/methods , Systems Integration , T-Lymphocytes, Cytotoxic/immunology , T-Lymphocytes, Cytotoxic/metabolism , Viral Load/genetics , Viral Load/immunology , Young Adult
3.
Methods Mol Biol ; 1979: 111-132, 2019.
Article in English | MEDLINE | ID: mdl-31028635

ABSTRACT

Seq-Well is a low-cost picowell platform that can be used to simultaneously profile the transcriptomes of thousands of cells from diverse, low input clinical samples. In Seq-Well, uniquely barcoded mRNA capture beads and cells are co-confined in picowells that are sealed using a semipermeable membrane, enabling efficient cell lysis and mRNA capture. The beads are subsequently removed and processed in parallel for sequencing, with each transcript's cell of origin determined via the unique barcodes. Due to its simplicity and portability, Seq-Well can be performed almost anywhere.


Subject(s)
High-Throughput Nucleotide Sequencing/methods , RNA, Messenger/genetics , Single-Cell Analysis/methods , Animals , Equipment Design , Gene Expression Profiling/economics , Gene Expression Profiling/instrumentation , Gene Expression Profiling/methods , Gene Library , High-Throughput Nucleotide Sequencing/economics , High-Throughput Nucleotide Sequencing/instrumentation , Humans , Membranes, Artificial , Polymerase Chain Reaction/economics , Polymerase Chain Reaction/instrumentation , Polymerase Chain Reaction/methods , Reverse Transcription , Sequence Analysis, RNA/economics , Sequence Analysis, RNA/instrumentation , Sequence Analysis, RNA/methods , Single-Cell Analysis/economics , Single-Cell Analysis/instrumentation
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