03606nas a2200769   4500000000100000000000100001008004100002260001200043653003300055653002700088100001700115700001900132700001700151700001300168700002600181700001600207700002000223700001800243700002200261700001400283700002600297700001800323700001600341700002100357700002000378700001400398700001300412700001100425700001800436700002200454700001300476700002400489700001900513700001600532700002200548700001400570700001900584700001900603700001300622700002200635700002000657700002200677700002100699700002200720700001800742700001900760700002100779700001600800700001700816700001500833700002000848700002400868700001900892700002200911700002100933700002100954700002300975700001400998700002201012700001601034245007901050856005501129300001201184490000801196520161801204022001402822       2023                            d  c2023-0710aCellular signalling networks10atranslational research1 aBlue B. Lake1 aRajasree Menon1 aSeth Winfree1 aQiwen Hu1 aRicardo Melo Ferreira1 aKian Kalhor1 aDaria Barwinska1 aEdgar A. Otto1 aMichael Ferkowicz1 aDinh Diep1 aNongluk Plongthongkum1 aAmanda Knoten1 aSarah Urata1 aLaura H. Mariani1 aAbhijit S. Naik1 aSean Eddy1 aBo Zhang1 aYan Wu1 aDiane Salamon1 aJames C. Williams1 aXin Wang1 aKarol S. Balderrama1 aPaul J. Hoover1 aEvan Murray1 aJamie L. Marshall1 aTeia Noel1 aAnitha Vijayan1 aAustin Hartman1 aFei Chen1 aSushrut S. Waikar1 aSylvia E. Rosas1 aFrancis P. Wilson1 aPaul M. Palevsky1 aKrzysztof Kiryluk1 aJohn R. Sedor1 aRobert D. Toto1 aChirag R. Parikh1 aEric H. Kim1 aRahul Satija1 aAnna Greka1 aEvan Z. Macosko1 aPeter V. Kharchenko1 aJoseph P. Gaut1 aJeffrey B. Hodgin1 aMichael T. Eadon1 aPierre C. Dagher1 aTarek M. El-Achkar1 aKun Zhang1 aMatthias Kretzler1 aSanjay Jain00aAn atlas of healthy and injured cell states and niches in the human kidney  uhttps://www.nature.com/articles/s41586-023-05769-3  a585-5940 v6193 aUnderstanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.  a1476-4687