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      Single-nuclear transcriptomics reveals diversity of proximal tubule cell states in a dynamic response to acute kidney injury

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          Significance

          A single acute kidney injury event increases the risk of progression to chronic kidney disease (CKD). Combining single-nucleus RNA sequencing with genetic tracing of injured proximal tubule cells identified a spatially dynamic, evolving injury response following ischemia–reperfusion injury. Failed proximal tubule repair leads to the persistence of a profibrotic, proinflammatory Vcam1 +/ Ccl2 + cell type exhibiting a senescence-associated secretory phenotype and a marked transcriptional activation of NF-κB and AP-1 pathway signatures, but no signs of G 2/M cell cycle arrest. Insights from this study can inform strategies to improve renal repair and prevent CKD progression.

          Abstract

          Acute kidney injury (AKI), commonly caused by ischemia, sepsis, or nephrotoxic insult, is associated with increased mortality and a heightened risk of chronic kidney disease (CKD). AKI results in the dysfunction or death of proximal tubule cells (PTCs), triggering a poorly understood autologous cellular repair program. Defective repair associates with a long-term transition to CKD. We performed a mild-to-moderate ischemia–reperfusion injury (IRI) to model injury responses reflective of kidney injury in a variety of clinical settings, including kidney transplant surgery. Single-nucleus RNA sequencing of genetically labeled injured PTCs at 7-d (“early”) and 28-d (“late”) time points post-IRI identified specific gene and pathway activity in the injury–repair transition. In particular, we identified Vcam1 +/ Ccl2 + PTCs at a late injury stage distinguished by marked activation of NF-κB–, TNF-, and AP-1–signaling pathways. This population of PTCs showed features of a senescence-associated secretory phenotype but did not exhibit G 2/M cell cycle arrest, distinct from other reports of maladaptive PTCs following kidney injury. Fate-mapping experiments identified spatially and temporally distinct origins for these cells. At the cortico-medullary boundary (CMB), where injury initiates, the majority of Vcam1 +/ Ccl2 + PTCs arose from early replicating PTCs. In contrast, in cortical regions, only a subset of Vcam1 +/ Ccl2 + PTCs could be traced to early repairing cells, suggesting late-arising sites of secondary PTC injury. Together, these data indicate even moderate IRI is associated with a lasting injury, which spreads from the CMB to cortical regions. Remaining failed-repair PTCs are likely triggers for chronic disease progression.

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          Most cited references77

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          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            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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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                06 July 2021
                28 June 2021
                28 June 2021
                : 118
                : 27
                : e2026684118
                Affiliations
                [1] aDepartment of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, Keck School of Medicine of the University of Southern California , Los Angeles, CA 90033
                Author notes
                3To whom correspondence may be addressed. Email: amcmahon@ 123456med.usc.edu .

                This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2020.

                Contributed by Andrew P. McMahon, April 23, 2021 (sent for review December 28, 2020; reviewed by Lloyd G. Cantley and Mark P. de Caestecker)

                Author contributions: L.M.S.G., J.L., K.K., P.E.C., and A.P.M. designed research; L.M.S.G., J.L., K.K., and P.E.C. performed research; L.M.S.G., J.L., P.E.C., and A.P.M. analyzed data; and L.M.S.G. and A.P.M. wrote the paper.

                Reviewers: L.G.C., Yale University School of Medicine; and M.P.d.C., Vanderbilt University Medical Center.

                1L.M.S.G. and J.L. contributed equally to this work.

                2Present address: Division of Nephrology, Ente Ospedaliero Cantonale, 6500 Lugano, Switzerland.

                Author information
                https://orcid.org/0000-0003-3052-1563
                https://orcid.org/0000-0002-9507-0057
                Article
                202026684
                10.1073/pnas.2026684118
                8271768
                34183416
                0b26c5da-de4a-452a-9cf4-f45ce4748751
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 11
                Funding
                Funded by: HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 100000062
                Award ID: U01DK107350
                Award Recipient : Andrew P. McMahon
                Funded by: HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 100000062
                Award ID: UC2DK126024
                Award Recipient : Andrew P. McMahon
                Funded by: Deutsche Forschungsgemeinschaft (DFG) 501100001659
                Award ID: GE 3179/1-1
                Award Recipient : Louisa Maria Sophie Gerhardt
                Funded by: Swiss National Science Foundation
                Award ID: 167773
                Award Recipient : PIetro Cippà
                Categories
                1
                422
                Biological Sciences
                Medical Sciences
                From the Cover
                Inaugural Article

                acute kidney injury,proximal tubule,repair,transcriptomics,single-nucleus rna sequencing

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