The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.
Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single–cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.
The international spread of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on both healthcare and society. A multitude of research efforts worldwide aim at characterizing the cellular factors involved in viral transmission in order to reveal therapeutic targets. For a full understanding of the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is Angiotensin I converting enzyme 2 (ACE2), and its expression has been reported in various human organs, in some cases with inconsistent or contradictory results. Here, we aim to verify a reliable expression profile of ACE2 in all major human tissues and cell types. Based on stringently validated immunohistochemical analysis and highthroughput mRNA sequencing from several datasets, we found that ACE2 expression is mainly localized to microvilli of the intestinal tract and renal proximal tubules, gallbladder epithelium, testicular Sertoli cells and Leydig cells, glandular cells of seminal vesicle and cardiomyocytes. The expression in several other previously reported locations, including alveolar type II (AT2) cells, could not be confirmed. Furthermore, ACE2 expression was absent in the AT2 lung carcinoma cell line A549, often used as a model for viral replication studies. Our analysis suggests that the expression of ACE2 in the human respiratory system appears to be limited, and the expression of the receptor in lung or respiratory epithelia on the protein level is yet to be confirmed. This raises questions regarding the role of ACE2 for infection of human lungs and highlights the need to further explore the route of transmission during SARS-CoV-2 infection.
The Chromosome-Centric Human Proteome Project aims to identify proteins classed as « missing » in the neXtProt knowledgebase. In this article, we present an in-depth proteomics analysis of the human sperm proteome to identify testis-enriched missing proteins. Using a range of protein extraction procedures and LC-MS/MS analysis, we detected a total of 235 proteins (PE2-PE4) for which no previous evidence of protein expression was annotated. Through a combination of LC-MS/MS and LC-PRM analysis, data mining and immunohistochemistry, we were able to confirm the expression of 206 missing proteins (PE2-4) in line with current HPP guidelines (version 2.0). Parallel Reaction Monitoring (PRM) acquisition combined with synthetic heavy labeled peptides was used to target 36 « one-hit wonder » candidates selected on the basis of prior PSM assessment. Of this subset of candidates, 24 were validated with additional predicted and specifically targeted peptides. Evidence was found for a further 16 missing proteins using immunohistochemistry on human testis sections. The expression pattern for some of these proteins was specific to the testis, and they could potentially be valuable markers with applications in fertility assessment. Strong evidence was also found for the existence of 4 proteins labeled as "uncertain" (PE5); the status of these proteins should therefore be re-examined.Our results show how the use of a range of sample preparation techniques combined with MS-based analysis, expert knowledge and complementary antibody-based techniques can produce data of interest to the community.
BACKGROUND Endometriosis is an estrogen-dependent gynecological disorder that affects at least 10% of women of reproductive age. It may lead to infertility and non-specific symptoms such as chronic pelvic pain. Endometriosis screening and diagnosis are difficult and time-consuming. Late diagnosis (with a delay ranging from 3.3 to 10.7 years) is a major problem and may contribute to disease progression and a worse response to treatment once initiated. Efficient screening tests might reduce this diagnostic delay. As endometriosis is presumed to be a complex disease with several genetic and non-genetic pathogenic factors, many researchers have sought to identify polymorphisms that predispose to this condition. OBJECTIVE AND RATIONALE We performed a systematic review and meta-analysis of the most regularly reported polymorphisms in order to identify those that might predispose to endometriosis and might thus be of value in screening. SEARCH METHODS The MEDLINE database was searched for English-language publications on DNA polymorphisms in endometriosis, with no date restriction. The PubTator text mining tool was used to extract gene names from the selected publications’ abstracts. We only selected polymorphisms reported by at least three studies, having applied strict inclusion and exclusion criteria to their control populations. No stratification based on ethnicity was performed. All steps were carried out according to PRISMA guidelines. OUTCOMES The initial selection of 395 publications cited 242 different genes. Sixty-two genes (corresponding to 265 different polymorphisms) were cited at least in three publications. After the application of our other selection criteria (an original case-control study of endometriosis, a reported association between endometriosis and at least one polymorphism, data on women of reproductive age and a diagnosis of endometriosis in the cases established by surgery and/or MRI and confirmed by histology), 28 polymorphisms were eligible for meta-analysis. Only five of the 28 polymorphisms were found to be significantly associated with endometriosis: interferon gamma (IFNG) (CA) repeat, glutathione S-transferase mu 1 (GSTM1) null genotype, glutathione S-transferase pi 1 (GSTP1) rs1695 and wingless-type MMTV integration site family member 4 (WNT4) rs16826658 and rs2235529. Six others showed a significant trend towards an association: progesterone receptor (PGR) PROGINS, interCellular adhesion molecule 1 (ICAM1) rs1799969, aryl-hydrocarbon receptor repressor (AHRR) rs2292596, cytochrome family 17 subfamily A polypeptide 1 (CYP17A1) rs743572, CYP2C19 rs4244285 and peroxisome proliferator-activated receptor gamma (PPARG) rs1801282), and 12 showed a significant trend towards the lack of an association: tumor necrosis factor (TNF) rs1799964, interleukin 6 (IL6) rs1800796, transforming growth factor beta 1 (TGFB1) rs1800469, estrogen receptor 1 (ESR1) rs2234693, PGR rs10895068, FSH receptor (FSHR) rs6166, ICAM1 rs5498, CYP1A1 rs4646903, CYP19A1 rs10046, tumor protein 53 (TP53) rs1042522, X-ray repair complementing defective repair in Chinese hamster cells 1 (XRCC1) rs25487 and serpin peptidase inhibitor clade E member 1 (SERPINE1) rs1799889; however, for the 18 polymorphisms identified in the latter two groups, further studies of the potential association with the endometriosis risk are needed. The remaining five of the 28 polymorphisms were not associated with endometriosis: glutathione S-transferase theta 1 (GSTT1) null genotype, vascular endothelial growth factor alpha (VEGFA) rs699947, rs833061, rs2010963 and rs3025039. WIDER IMPLICATIONS By carefully taking account of how the control populations were defined, we identified polymorphisms that might be candidates for use in endometriosis screening and polymorphisms not associated with endometriosis. This might constitute the first step towards identifying polymorphism combinations that predispose to endometriosis (IFNG (CA) repeat, GSTM1 null genotype, GSTP1 rs1695, WNT4 rs16826658 and WNT4 rs2235529) in a large cohort of patients with well-defined inclusion criteria. In turn, these results might improve the diagnosis of endometriosis in primary care. Lastly, our present findings may enable a better understanding of endometriosis and improve the management of patients with this disease.
In the quest for "missing proteins" (MPs), the proteins encoded by the human genome still lacking evidence of existence at the protein level, novel approaches are needed to detect this challenging group of proteins. The current count stands at 1,343 MPs, and it is likely that many of these proteins are expressed at low levels, in rare cell or tissue types, or the cells in which they are expressed may only represent a small minority of the tissue. Here, we used an integrated omics approach to identify and explore MPs in human ovaries. By taking advantage of publicly available transcriptomics and antibody-based proteomics data in the Human Protein Atlas (HPA), we selected 18 candidates for further immunohistochemical analysis using an exclusive collection of ovarian tissues from women and patients of reproductive age. The results were compared with data from single-cell mRNA sequencing, and seven proteins (CTXN1, MRO, RERGL, TTLL3, TRIM61, TRIM73, and ZNF793) could be validated at the single-cell type level with both methods. We present for the first time the cell type-specific spatial localization of 18 MPs in human ovarian follicles, thereby showcasing the utility of the HPA database as an important resource for identification of MPs suitable for exploration in specialized tissue samples. The results constitute a starting point for further quantitative and qualitative analysis of the human ovaries, and the novel data for the seven proteins that were validated with both methods should be considered as evidence of existence of these proteins in human ovary.
SARS-coronavirus 2 (SARS-CoV-2) that caused the coronavirus disease 2019 (COVID-19) pandemic has posed to be a global challenge. An increasing number of neurological symptoms have been linked to the COVID-19 disease, but the underlying mechanisms of such symptoms and which patients could be at risk are not yet established. The suggested key receptor for host cell entry is angiotensin I converting enzyme 2 (ACE2). Previous studies on limited tissue material have shown no or low protein expression of ACE2 in the normal brain. Here, we used stringently validated antibodies and immunohistochemistry to examine the protein expression of ACE2 in all major regions of the normal brain. The expression pattern was compared with the COVID-19-affected brain of patients with a varying degree of neurological symptoms. In the normal brain, the expression was restricted to the choroid plexus and ependymal cells with no expression in any other brain cell types. Interestingly, in the COVID-19-affected brain, an upregulation of ACE2 was observed in endothelial cells of certain patients, most prominently in the white matter and with the highest expression observed in the patient with the most severe neurological symptoms. The data shows differential expression of ACE2 in the diseased brain and highlights the need to further study the role of endothelial cells in COVID-19 disease in relation to neurological symptoms.
An important quest for the life science community is to deliver a complete annotation of the human building-blocks of life, the genes and the proteins. Here, we report on a genome-wide effort to annotate all protein-coding genes based on single cell transcriptomics data representing all major tissues and organs in the human body, integrated with data from bulk transcriptomics and antibody-based tissue profiling. Altogether, 25 tissues have been analyzed with single cell transcriptomics resulting in genome-wide expression in 444 single cell types using a strategy involving pooling data from individual cells to obtain genome-wide expression profiles of individual cell type. We introduce a new genome-wide classification tool based on clustering of similar expression profiles across single cell types, which can be visualized using dimensional reduction maps (UMAP). The clustering classification is integrated with a new “tau” score classification for all protein-coding genes, resulting in a measure of single cell specificity across all cell types for all individual genes. The analysis has allowed us to annotate all human protein-coding genes with regards to function and spatial distribution across individual cell types across all major tissues and organs in the human body. A new version of the open access Human Protein Atlas (www.proteinatlas.org) has been launched to enable researchers to explore the new genome-wide annotation on an individual gene level.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.