Literature DB >> 29291760

Bringing Renal Biopsy Interpretation Into the Molecular Age With Single-Cell RNA Sequencing.

Andrew F Malone1, Haojia Wu1, Benjamin D Humphreys2.   

Abstract

The renal biopsy provides critical diagnostic and prognostic information to clinicians including cases of acute kidney injury, chronic kidney disease, and allograft dysfunction. Today, biopsy specimens are read using a combination of light microscopy, electron microscopy, and indirect immunofluorescence, with a limited number of antibodies. These techniques all were perfected decades ago with only incremental changes since then. By contrast, recent advances in single-cell genomics are transforming scientists' ability to characterize cells. Rather than measure the expression of several genes at a time by immunofluorescence, it now is possible to measure the expression of thousands of genes in thousands of single cells simultaneously. Here, we argue that the development of single-cell RNA sequencing offers an opportunity to describe human kidney disease comprehensively at a cellular level. It is particularly well suited for the analysis of immune cells, which are characterized by multiple subtypes and changing functions depending on their environment. In this review, we summarize the development of single-cell RNA sequencing methodologies. We discuss how these approaches are being applied in other organs, and the potential for this powerful technology to transform our understanding of kidney disease once applied to the renal biopsy.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  RNA sequencing; biopsy; informatics; microfluidics

Mesh:

Year:  2018        PMID: 29291760      PMCID: PMC5753432          DOI: 10.1016/j.semnephrol.2017.09.005

Source DB:  PubMed          Journal:  Semin Nephrol        ISSN: 0270-9295            Impact factor:   5.299


  52 in total

1.  Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development.

Authors:  Sean C Bendall; Kara L Davis; El-Ad David Amir; Michelle D Tadmor; Erin F Simonds; Tiffany J Chen; Daniel K Shenfeld; Garry P Nolan; Dana Pe'er
Journal:  Cell       Date:  2014-04-24       Impact factor: 41.582

2.  CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification.

Authors:  Tamar Hashimshony; Florian Wagner; Noa Sher; Itai Yanai
Journal:  Cell Rep       Date:  2012-08-30       Impact factor: 9.423

3.  Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons.

Authors:  Naomi Habib; Yinqing Li; Matthias Heidenreich; Lukasz Swiech; Inbal Avraham-Davidi; John J Trombetta; Cynthia Hession; Feng Zhang; Aviv Regev
Journal:  Science       Date:  2016-07-28       Impact factor: 47.728

4.  Single-cell RNA-sequence analysis of mouse glomerular mesangial cells uncovers mesangial cell essential genes.

Authors:  Yuqiu Lu; Yuting Ye; Qianqian Yang; Shaolin Shi
Journal:  Kidney Int       Date:  2017-03-18       Impact factor: 10.612

5.  Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis.

Authors:  Evan Der; Saritha Ranabothu; Hemant Suryawanshi; Kemal M Akat; Robert Clancy; Pavel Morozov; Manjunath Kustagi; Mareike Czuppa; Peter Izmirly; H Michael Belmont; Tao Wang; Nicole Jordan; Nicole Bornkamp; Janet Nwaukoni; July Martinez; Beatrice Goilav; Jill P Buyon; Thomas Tuschl; Chaim Putterman
Journal:  JCI Insight       Date:  2017-05-04

6.  Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis.

Authors:  Fuchou Tang; Catalin Barbacioru; Siqin Bao; Caroline Lee; Ellen Nordman; Xiaohui Wang; Kaiqin Lao; M Azim Surani
Journal:  Cell Stem Cell       Date:  2010-05-07       Impact factor: 24.633

7.  Mouse embryonic stem cells can differentiate via multiple paths to the same state.

Authors:  James Alexander Briggs; Victor C Li; Seungkyu Lee; Clifford J Woolf; Allon Klein; Marc W Kirschner
Journal:  Elife       Date:  2017-10-09       Impact factor: 8.140

8.  Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types.

Authors:  Diego Adhemar Jaitin; Ephraim Kenigsberg; Hadas Keren-Shaul; Naama Elefant; Franziska Paul; Irina Zaretsky; Alexander Mildner; Nadav Cohen; Steffen Jung; Amos Tanay; Ido Amit
Journal:  Science       Date:  2014-02-14       Impact factor: 47.728

9.  Molecular Markers of Tubulointerstitial Fibrosis and Tubular Cell Damage in Patients with Chronic Kidney Disease.

Authors:  Shunsaku Nakagawa; Kumiko Nishihara; Hitomi Miyata; Haruka Shinke; Eri Tomita; Moto Kajiwara; Takeshi Matsubara; Noriyuki Iehara; Yoshinobu Igarashi; Hiroshi Yamada; Atsushi Fukatsu; Motoko Yanagita; Kazuo Matsubara; Satohiro Masuda
Journal:  PLoS One       Date:  2015-08-28       Impact factor: 3.240

10.  Wishbone identifies bifurcating developmental trajectories from single-cell data.

Authors:  Manu Setty; Michelle D Tadmor; Shlomit Reich-Zeliger; Omer Angel; Tomer Meir Salame; Pooja Kathail; Kristy Choi; Sean Bendall; Nir Friedman; Dana Pe'er
Journal:  Nat Biotechnol       Date:  2016-05-02       Impact factor: 54.908

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  19 in total

1.  Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis.

Authors:  Haojia Wu; Yuhei Kirita; Erinn L Donnelly; Benjamin D Humphreys
Journal:  J Am Soc Nephrol       Date:  2018-12-03       Impact factor: 10.121

Review 2.  Recent advances in acute kidney injury and its consequences and impact on chronic kidney disease.

Authors:  Anna Zuk; Joseph V Bonventre
Journal:  Curr Opin Nephrol Hypertens       Date:  2019-07       Impact factor: 2.894

Review 3.  Single cell immune profiling in transplantation research.

Authors:  Lauren E Higdon; Steven Schaffert; Purvesh Khatri; Jonathan S Maltzman
Journal:  Am J Transplant       Date:  2019-03-20       Impact factor: 8.086

Review 4.  Single-cell Transcriptomics and Solid Organ Transplantation.

Authors:  Andrew F Malone; Benjamin D Humphreys
Journal:  Transplantation       Date:  2019-09       Impact factor: 4.939

Review 5.  The tissue proteome in the multi-omic landscape of kidney disease.

Authors:  Markus M Rinschen; Julio Saez-Rodriguez
Journal:  Nat Rev Nephrol       Date:  2020-10-07       Impact factor: 28.314

6.  Single-Cell RNA Profiling of Glomerular Cells Shows Dynamic Changes in Experimental Diabetic Kidney Disease.

Authors:  Jia Fu; Kemal M Akat; Zeguo Sun; Weijia Zhang; Detlef Schlondorff; Zhihong Liu; Thomas Tuschl; Kyung Lee; John Cijiang He
Journal:  J Am Soc Nephrol       Date:  2019-03-07       Impact factor: 10.121

Review 7.  Single-Cell Transcriptomics of a Human Kidney Allograft Biopsy Specimen Defines a Diverse Inflammatory Response.

Authors:  Haojia Wu; Andrew F Malone; Erinn L Donnelly; Yuhei Kirita; Kohei Uchimura; Sai M Ramakrishnan; Joseph P Gaut; Benjamin D Humphreys
Journal:  J Am Soc Nephrol       Date:  2018-07-06       Impact factor: 10.121

8.  High Dimensional Renal Profiling: Towards a Better Understanding or Renal Transplant Immune Suppression.

Authors:  Cyd M Castro-Rojas; Rita R Alloway; E Steve Woodle; David A Hildeman
Journal:  Curr Transplant Rep       Date:  2019-01-14

Review 9.  Kidney and organoid single-cell transcriptomics: the end of the beginning.

Authors:  Parker C Wilson; Benjamin D Humphreys
Journal:  Pediatr Nephrol       Date:  2019-01-04       Impact factor: 3.714

Review 10.  Using single-cell technologies to map the human immune system - implications for nephrology.

Authors:  Benjamin J Stewart; John R Ferdinand; Menna R Clatworthy
Journal:  Nat Rev Nephrol       Date:  2019-12-12       Impact factor: 28.314

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