Pai, R. | bioRxiv Science

bioRxiv2020

scRNA-seq reveals ACE2 and TMPRSS2 expression in TROP2+ Liver Progenitor Cells: Implications in COVID-19 associated Liver Dysfunction

The recent pandemic of coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 was first reported in China (December 2019) and now prevalent in [~]170 countries across the globe. Entry of SARS-CoV-2 into mammalian cells require the binding of viral Spike (S) proteins to the ACE2 (angiotensin converting enzyme 2) receptor. Once entered the S protein is primed by a specialised serine protease, TMPRSS2 (Transmembrane Serine Protease 2) in the host cell. Importantly, beside respiratory symptoms, consistent with other common respiratory virus infection when patients become viraemic, a significant number of COVID-19 patients also develop liver comorbidities. We explored if specific target cell-type in the mammalian liver, could be implicated in disease pathophysiology other than the general deleterious response to cytokine storms. Here we employed single-cell RNA-seq (scRNA-seq) to survey the human liver and identified potentially implicated liver cell-type for viral ingress. We report the co-expression of ACE2 and TMPRSS2 in a TROP2+ liver progenitor population. Importantly, we fail to detect the expression of ACE2 in hepatocyte or any other liver (immune and stromal) cell types. These results indicated that in COVID-19 associated liver dysfunction and cell death, viral infection of TROP2+ progenitors in liver may significantly impaired liver regeneration and could lead to pathology. Highlights- EPCAM+ Liver progenitors co-express ACE2 and TMPRSS2 - ACE2 and TMPRSS2 expression is highest in TROP2high progenitors - ACE2 and TMPRSS2 cells express cholangiocyte biased fate markers - ACE2 and TMPRSS2 positive cells are absent in human fetal liver

genomics↗

bioRxiv2019

Super-resolution imaging reveals the evolution of higher-order chromatin folding in early carcinogenesis

Aberrant chromatin structure is a hallmark in cancer cells and has long been used for clinical diagnosis of cancer. However, underlying higher-order chromatin folding during malignant transformation remains elusive, due to the lack of molecular scale resolution. Using optimized stochastic optical reconstruction microscopy (STORM) for pathological tissue (PathSTORM), we uncovered a gradual decompaction and fragmented higher-order chromatin folding throughout all stages of carcinogenesis in multiple tumor types, even prior to the tumor formation. Our integrated imaging, genomic, and transcriptomic analyses reveal the functional consequences in enhanced formation of transcription factories, spatial juxtaposition with relaxed nanosized chromatin domains and impaired genomic stability. We also demonstrate the potential of imaging higher-order chromatin decompaction to detect high-risk precursors that cannot be distinguished by conventional pathology. Taken together, our findings reveal the gradual decompaction and fragmentation of higher-order chromatin structure as an enabling characteristic in early carcinogenesis to facilitate malignant transformation, which may improve cancer diagnosis, risk stratification, and prevention.\n\nSIGNIFICANCEGenomic DNA is folded into a higher-order structure that regulates transcription and maintains genomic stability. Although much progress has been made on understanding biochemical characteristics of epigenetic modifications in cancer, the higher-order folding of chromatin structure remains largely unknown. Using optimized super-resolution microscopy, we uncover de-compacted and fragmented chromatin folding in tumor initiation and stepwise progression in multiple tumor types, even prior to the presence of tumor cells. This study underlines the significance of unfolding higher-order chromatin structure as an enabling characteristic to promote tumorigenesis, which may facilitate the development and evaluation of new preventive strategies. The potential of imaging higher-order chromatin folding to improve cancer detection and risk stratification is demonstrated by detecting high-risk precursors that cannot be distinguished by conventional pathology.

cancer biology↗