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      Cross‐species comparison illuminates the importance of iron homeostasis for splenic anti‐immunosenescence

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          Abstract

          Although immunosenescence may result in increased morbidity and mortality, many mammals have evolved effective immune coping strategies to extend their lifespans. Thus, the immune systems of long‐lived mammals present unique models to study healthy longevity. To identify the molecular clues of anti‐immunosenescence, we first built high‐quality reference genome for a long‐lived myotis bat, and then compared three long‐lived mammals (i.e., bat, naked mole rat, and human) versus the short‐lived mammal, mouse, in splenic immune cells at single‐cell resolution. A close relationship between B:T cell ratio and immunosenescence was detected, as B:T cell ratio was much higher in mouse than long‐lived mammals and significantly increased during aging. Importantly, we identified several iron‐related genes that could resist immunosenescence changes, especially the iron chaperon, PCBP1, which was upregulated in long‐lived mammals but dramatically downregulated during aging in all splenic immune cell types. Supportively, immune cells of mouse spleens contained more free iron than those of bat spleens, suggesting higher level of ROS‐induced damage in mouse. PCBP1 downregulation during aging was also detected in hepatic but not pulmonary immune cells, which is consistent with the crucial roles of spleen and liver in organismal iron recycling. Furthermore, PCBP1 perturbation in immune cell lines would result in cellular iron dyshomeostasis and senescence. Finally, we identified two transcription factors that could regulate PCBP1 during aging. Together, our findings highlight the importance of iron homeostasis in splenic anti‐immunosenescence, and provide unique insight for improving human healthspan.

          Abstract

          To identify molecular clues of anti‐immunosenescence, we compare three long‐lived mammals versus the short‐lived mammal, mouse, in splenic immune cells at single‐cell resolution. We detect higher splenic B:T cell ratio and higher free iron level in mice, while higher expression levels of iron homeostasis‐related genes in long‐lived species. Our findings highlight the importance of iron homeostasis in splenic anti‐immunosenescence, and provide unique insight for improving human healthspan.

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          Most cited references58

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          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. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

              A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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                Author and article information

                Contributors
                liu_meiling2@gzlab.ac.cn
                dong_ji@gzlab.ac.cn
                Journal
                Aging Cell
                Aging Cell
                10.1111/(ISSN)1474-9726
                ACEL
                Aging Cell
                John Wiley and Sons Inc. (Hoboken )
                1474-9718
                1474-9726
                08 September 2023
                November 2023
                : 22
                : 11 ( doiID: 10.1111/acel.v22.11 )
                : e13982
                Affiliations
                [ 1 ] GMU‐GIBH Joint School of Life Sciences, The Guangdong‐Hong Kong‐Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory Guangzhou Medical University Guangzhou China
                [ 2 ] Faculty of Health Sciences University of Macau Macau China
                [ 3 ] Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) Guangzhou China
                [ 4 ] Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization Institute of Zoology, Guangdong Academy of Sciences Guangzhou China
                Author notes
                [*] [* ] Correspondence

                Meiling Liu and Ji Dong, GMU‐GIBH Joint School of Life Sciences, The Guangdong‐Hong Kong‐Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou 510799, China.

                Email: liu_meiling2@ 123456gzlab.ac.cn and dong_ji@ 123456gzlab.ac.cn

                Author information
                https://orcid.org/0000-0002-8953-5284
                Article
                ACEL13982 ACE-23-0117.R2
                10.1111/acel.13982
                10652311
                37681451
                0c6bd792-81eb-494a-b7af-da1a3a77d573
                © 2023 The Authors. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 August 2023
                : 20 February 2023
                : 23 August 2023
                Page count
                Figures: 7, Tables: 0, Pages: 18, Words: 12010
                Funding
                Funded by: Bioland Laboratory
                Award ID: 1102101216
                Funded by: China Postdoctoral Science Foundation , doi 10.13039/501100002858;
                Award ID: 2021M692241
                Funded by: Guangzhou National Laboratory
                Award ID: YW‐JCYJ0604
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                November 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.4 mode:remove_FC converted:16.11.2023

                Cell biology
                cross‐species comparison,immunosenescence,iron homeostasis,pcbp1,single‐cell transcriptomics,splenic immune cells

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