COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets

May 11, 2021·
T. m. delorey
,
C. g. k. ziegler
,
G. heimberg
,
R. normand
Yiming Yang
Yiming Yang
,
A. segerstolpe
,
D. abbondanza
,
S. j. fleming
,
A. subramanian
,
D. t. montoro
,
K. a. jagadeesh
,
K. k. dey
,
P. sen
,
M. slyper
,
Y. h. pita juarez
,
D. phillips
,
J. biermann
,
Z. bloom ackermann
,
N. barkas
,
A. ganna
,
J. gomez
,
J. c. melms
,
I. katsyv
,
E. normandin
,
P. naderi
,
Y. v. popov
,
S. s. raju
,
S. niezen
,
L. t. y. tsai
,
K. j. siddle
,
M. sud
,
V. m. tran
,
S. k. vellarikkal
,
Y. wang
,
L. amir zilberstein
,
D. s. atri
,
J. beechem
,
O. r. brook
,
J. chen
,
P. divakar
,
P. dorceus
,
J. m. engreitz
,
A. essene
,
D. m. fitzgerald
,
R. fropf
,
S. gazal
Joshua Gould
Joshua Gould
,
J. grzyb
,
T. harvey
,
J. hecht
,
T. hether
,
J. jane valbuena
,
M. leney greene
,
H. ma
,
C. mccabe
,
D. e. mcloughlin
,
E. m. miller
,
C. muus
,
M. niemi
,
R. padera
,
L. pan
,
D. pant
,
C. peer
,
J. pfiffner borges
,
C. j. pinto
,
J. plaisted
,
J. reeves
,
M. ross
,
M. rudy
,
E. h. rueckert
,
M. siciliano
,
A. sturm
,
E. todres
,
A. waghray
,
S. warren
,
S. zhang
,
D. r. zollinger
,
L. cosimi
,
R. m. gupta
,
N. hacohen
,
H. hibshoosh
,
W. hide
,
A. l. price
,
J. rajagopal
,
P. r. tata
,
S. riedel
,
G. szabo
,
T. l. tickle
,
P. t. ellinor
,
D. hung
,
P. c. sabeti
,
R. novak
,
R. rogers
,
D. e. ingber
,
Z. g. jiang
,
D. juric
,
M. babadi
,
S. l. farhi
,
B. izar
,
J. r. stone
,
I. s. vlachos
,
I. h. solomon
,
O. ashenberg
,
C. b. m. porter
Dr. Bo Li
Dr. Bo Li
,
A. k. shalek
,
A. c. villani
,
O. rozenblatt rosen
,
A. regev
· 0 min read
Abstract
COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.
Type
Publication
Nature
Authors
Yiming Yang
Authors
Bioinformatics Software Engineer
Yiming Yang is a bioinformatics software engineer in Li Lab.
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Joshua Gould
Authors
Senior Research Software Engineer
Joshua Gould is a senior research software engineer in Li Lab.
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Authors
Dr. Bo Li
Authors
Principal Scientist II
Dr. Bo Li is a Principal Scientist II at AI for Biology and Translation (AIBT), Genentech, Inc. His research focuses on three major topics: Science, Technology and Computational Methods. For Science, his team works on lung cancer and especially small cell lung cancer. For Technology, his team evaluates and adopts cutting-edge high-throughput data generation technologies, such as Cellanome and SBX sequencing. For Computational Methods, his team develops novel computational and deep learning tools for enabling insight discovery from high-throughput multi-modal data. Before joining in Genentech, he was an Assistant Professor of Medicine at Harvard Medical School and the director of Bioinformatics and Computational Biology at Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital. He received his Ph.D. in computer science from UW-Madison and completed two postdoctoral trainings with Dr. Lior Pachter at UC Berkeley and Dr. Aviv Regev at Broad Institute. He is best known for developing RSEM, an impactful RNA-seq transcript quantification software. RSEM is cited 22,602 times (Google Scholar) and adopted by several big consortia such as TCGA, ENCODE, GTEx and TOPMed.
Authors