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Journal ArticleDOI: 10.1016/J.CELL.2021.02.021

In vivo CRISPR screening reveals nutrient signaling processes underpinning CD8+ T cell fate decisions.

04 Mar 2021-Cell (Elsevier)-Vol. 184, Iss: 5
Abstract: How early events in effector T cell (TEFF) subsets tune memory T cell (TMEM) responses remains incompletely understood. Here, we systematically investigated metabolic factors in fate determination of TEFF and TMEM cells using in vivo pooled CRISPR screening, focusing on negative regulators of TMEM responses. We found that amino acid transporters Slc7a1 and Slc38a2 dampened the magnitude of TMEM differentiation, in part through modulating mTORC1 signaling. By integrating genetic and systems approaches, we identified cellular and metabolic heterogeneity among TEFF cells, with terminal effector differentiation associated with establishment of metabolic quiescence and exit from the cell cycle. Importantly, Pofut1 (protein-O-fucosyltransferase-1) linked GDP-fucose availability to downstream Notch-Rbpj signaling, and perturbation of this nutrient signaling axis blocked terminal effector differentiation but drove context-dependent TEFF proliferation and TMEM development. Our study establishes that nutrient uptake and signaling are key determinants of T cell fate and shape the quantity and quality of TMEM responses.

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9 results found


Journal ArticleDOI: 10.1038/S41586-021-03692-Z
Guotong Fu1, Clifford S. Guy1, Nicole M. Chapman1, Gustavo Palacios1  +20 moreInstitutions (3)
01 Jul 2021-Nature
Abstract: T follicular helper (TFH) cells are crucial for B cell-mediated humoral immunity1. Although transcription factors such as BCL6 drive the differentiation of TFH cells2,3, it is unclear whether and how post-transcriptional and metabolic programs enforce TFH cell programming. Here we show that the cytidine diphosphate (CDP)–ethanolamine pathway co-ordinates the expression and localization of CXCR5 with the responses of TFH cells and humoral immunity. Using in vivo CRISPR–Cas9 screening and functional validation in mice, we identify ETNK1, PCYT2, and SELENOI—enzymes in the CDP–ethanolamine pathway for de novo synthesis of phosphatidylethanolamine (PE)—as selective post-transcriptional regulators of TFH cell differentiation that act by promoting the surface expression and functional effects of CXCR5. TFH cells exhibit unique lipid metabolic programs and PE is distributed to the outer layer of the plasma membrane, where it colocalizes with CXCR5. De novo synthesis of PE through the CDP–ethanolamine pathway co-ordinates these events to prevent the internalization and degradation of CXCR5. Genetic deletion of Pcyt2, but not of Pcyt1a (which mediates the CDP–choline pathway), in activated T cells impairs the differentiation of TFH cells, and this is associated with reduced humoral immune responses. Surface levels of PE and CXCR5 expression on B cells also depend on Pcyt2. Our results reveal that phospholipid metabolism orchestrates post-transcriptional mechanisms for TFH cell differentiation and humoral immunity, highlighting the metabolic control of context-dependent immune signalling and effector programs. Enzymes in the cytidine diphosphate–ethanolamine metabolic pathway, which promotes de novo synthesis of phosphatidylethanolamine, are shown to act as post-transcriptional mediators of the differentiation of T follicular helper (TFH) cells, by regulating the chemokine receptor CXCR5.

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Topics: Cellular differentiation (54%), Immune system (53%), Lymphocyte differentiation (53%) ... read more

3 Citations


Open accessJournal ArticleDOI: 10.1016/J.JPHS.2021.09.006
Abstract: Ingestion of amino acids is fundamental for cellular activity. Amino acids are important components for protein synthesis but are also crucial for intracellular metabolic reactions and signal transduction. Following activation, immune cells induce metabolic reprogramming to generate adequate energy and constitutive substances. Hence, the delivery of amino acids by transporters is necessary for the progression of metabolic rewiring. In this review, we discuss how amino acids and their transporters regulate immune cell functions, with emphasis on LAT1, a transporter of large neutral amino acids. Furthermore, we explore the possibility of targeting amino acid transporters to improve immune disorders and cancer immune therapies.

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Topics: Amino acid (61%), Immune system (52%), Protein biosynthesis (51%)

3 Citations


Journal ArticleDOI: 10.1016/J.CELL.2021.07.012
Hao Shi1, Hongbo Chi1Institutions (1)
05 Aug 2021-Cell
Abstract: Interplay between metabolic and epigenetic remodeling may be key to cell fate control. In this issue of Cell, Puleston et al. and Wagner et al. use metabolomic, computational, and genetic approaches to uncover that polyamine metabolism directs T helper cell lineage choices, epigenetic state, and pathogenic potential in inflammation.

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Topics: Cell Fate Control (61%), T helper cell (52%)

1 Citations


Open accessJournal ArticleDOI: 10.1093/PCMEDI/PBAB015
Tao Yin1Institutions (1)
Abstract: A commentary on “In vivo CD8+ T cell CRISPR screening reveals control by Fli1 in infection and cancer”.

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Topics: CRISPR (60%)

Open accessJournal ArticleDOI: 10.1101/CSHPERSPECT.A037770
Abstract: The formation of long-lived memory T cells is a critical feature of the adaptive immune response. T cells undergo metabolic reprogramming to establish a functional memory population. While initial studies characterized key metabolic pathways necessary for memory T-cell development, recent findings highlight that metabolic regulation of memory T-cell subsets is diverse. Here we describe the different requirements for metabolic programs and metabolism-related signaling pathways in memory T-cell development. We further discuss the contribution of cellular metabolism to memory T-cell functional reprogramming and stemness within acute and chronic inflammatory environments. Last, we highlight knowledge gaps and propose approaches to determine the roles of metabolites and metabolic enzymes in memory T-cell fate. Understanding how cellular metabolism regulates a functionally diverse memory population will undoubtedly provide new therapeutic insights to modulate protective T-cell immunity in human disease.

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Topics: Memory T cell (56%), Acquired immune system (53%), Population (53%)

References
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84 results found


Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTP352
Heng Li1, Bob Handsaker2, Alec Wysoker2, T. J. Fennell2  +5 moreInstitutions (4)
01 Aug 2009-Bioinformatics
Abstract: Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: [email protected]

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Topics: Variant Call Format (62%), Stockholm format (61%), FASTQ format (56%) ... read more

35,747 Citations


Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTP324
Heng Li1, Richard Durbin1Institutions (1)
01 Jul 2009-Bioinformatics
Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: [email protected]

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Topics: Hybrid genome assembly (54%), Sequence assembly (53%), 2 base encoding (52%) ... read more

35,234 Citations


Open accessJournal ArticleDOI: 10.1186/S13059-014-0550-8
05 Dec 2014-Genome Biology
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html .

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Topics: MRNA Sequencing (54%), Integrator complex (51%), Count data (50%) ... read more

29,675 Citations


Open accessJournal ArticleDOI: 10.1073/PNAS.0506580102
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

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26,320 Citations


Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTQ033
Aaron R. Quinlan1, Ira M. Hall1Institutions (1)
15 Mar 2010-Bioinformatics
Abstract: Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing webbased methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools

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Topics: Software suite (52%), Source code (50%)

14,088 Citations


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