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Results for “molecular biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2020

Unexpected variability of allelic imbalance estimates from RNA sequencing

RNA sequencing and other experimental methods that produce large amounts of data are increasingly dominant in molecular biology. However, the noise properties of these techniques have not been fully understood. We assessed the reproducibility of allele-specific expression measurements by conducting replicate sequencing experiments from the same RNA sample. Surprisingly, variation in the estimates of allelic imbalance (AI) between technical replicates was up to 7-fold higher than expected from commonly applied noise models. We show that AI overdispersion varies substantially between replicates and between experimental series, appears to arise during the construction of sequencing libraries, and can be measured by comparing technical replicates. We demonstrate that compensation for AI overdispersion greatly reduces technical variation and enables reliable differential analysis of allele-specific expression across samples and across experiments. Conversely, not taking AI overdispersion into account can lead to a substantial number of false positives in analysis of allele-specific gene expression

bioinformatics↗

bioRxiv2020

Bacteriophages targeting Acinetobacter baumannii capsule induce antimicrobial resensitization

Carbapenem-resistant Acinetobacter baumannii is responsible for frequent, hard-to-treat and often fatal healthcare-associated infections. Phage therapy, the use of viruses that infect and kill bacteria, is an approach gaining significant clinical interest to combat antibiotic-resistant infections. However, a major limitation is that bacteria can develop resistance against phages. Here, we isolated phages with activity against a panel of A. baumannii strains and focused on clinical isolates AB900 and A9844 and their phages for detailed characterization. As expected, coincubation of the phages with their hosts in vitro resulted in the emergence of phage-resistant bacterial mutants. Genome sequence analysis revealed that phage-resistant mutants harbored loss-of-function mutations in genes from the K locus, responsible for the biosynthesis of the bacterial capsule. Using molecular biology techniques, phage adsorption assays, and quantitative evaluation of capsule production, we established that the bacterial capsule serves as the primary receptor for these phages. As a collateral phenotype of impaired capsule production, the phage-resistant strains could not form biofilms, became fully sensitized to the human complement system, showed increased susceptibility to beta-lactam antibiotics, and became vulnerable to additional phages. Finally, in a murine model of bacteremia, the phage-resistant A. baumannii demonstrated a diminished capacity to colonize blood and solid tissues. This study demonstrates that phages can be used not only for their lytic activity but, if combined with a posteriori knowledge of their receptors and the mechanism of bacterial resistance, for their potential synergy with other antimicrobial agents, thus providing even broader clinical options for phage therapy.

microbiology↗

bioRxiv2020

Short and Long-read Sequencing Survey of the Dynamic Transcriptomes of African Swine Fever Virus and its Host

African swine fever virus (ASFV) is an important animal pathogen causing substantial economic losses in the swine industry globally. At present, little is known about the molecular biology of ASFV, including its transcriptome organization. In this study, we applied cutting-edge sequencing approaches, namely the Illumina short-read sequencing (SRS) and the Oxford Nanopore Technologies long-read sequencing (LRS) techniques, together with several library preparation chemistries to analyze the ASFV dynamic transcriptome. SRS can generate a large amount of high-precision sequencing reads, but it is inefficient for identifying long RNA molecules, transcript isoforms and overlapping transcripts. LRS can overcome these limitations, but this approach also has shortcomings, such as its high error rate and the low coverage. Amplification-based LRS techniques produce relatively high read counts but also high levels of spurious transcripts, whereas the non-amplified cDNA and direct RNA sequencing techniques are more precise but achieve lower throughput. The drawbacks of the various technologies can be circumvented by the combined use of these approaches.

genomics↗

bioRxiv2020

Optimization of data-independent acquisition using predicted libraries for deep and accurate proteome profiling

In silico spectral library prediction of all possible peptides from whole organisms has a great potential for improving proteome profiling by data-independent acquisition (DIA) and extending its scope of application. In combination with other recent improvements in the field of mass spectrometry (MS)-based proteomics, including sample preparation, peptide separation and data analysis, we aimed to uncover the full potential of such an advanced DIA strategy by optimization of the data acquisition. The results demonstrate that the combination of high-quality in silico libraries, reproducible and high-resolution peptide separation using micro-pillar array columns as well as neural network supported data analysis enables the use of long MS scan cycles without impairing the quantification performance. The study demonstrates that mean coefficient of variations of 4 % were obtained even at only 1.5 data points per peak (full width at half maximum) across different gradient lengths, which in turn improved proteome coverage up to more than 8000 proteins from HeLa cells using empirically-corrected libraries and more than 7000 proteins using a whole human in silico predicted library. These data were obtained using a Q Exactive orbitrap mass spectrometer with moderate scanning speed (12 Hz) and perform very well in comparison to recent studies using more advanced MS instruments, which underline the high potential of this optimization strategy for various applications in clinical proteomics, microbiology and molecular biology.

systems biology↗

bioRxiv2020

RNA editing in inflorescences of wild grapevine unveils association to sex and development

RNA editing challenges the central dogma of molecular biology, by modifying the genetic information at the transcription level. Recent reports, suggesting increased levels of RNA editing in plants, raised questions on the nature and dynamics of such events during development. We here report the occurrence of distinct RNA editing patterns in wild Vitis flowers during development, with twelve possible RNA editing modifications observed for the first time in plants. RNA editing events are gender and developmental stage specific, identical in subsequent years of this perennial species and with distinct nucleotide frequencies neighboring editing sites on the 5 and 3 flanks. The transcriptome dynamics unveils a new regulatory layer responsible for gender plasticity enhancement or underling dioecy evolution in Vitis.

plant biology↗

bioRxiv2020

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miR-Base miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

bioinformatics↗

bioRxiv2020

OmicsDB::Pathogens - A database for exploring functional networks of plant pathogens

Plant pathogens are a great threat to food security. To combat them we need an understanding of how they work. Integrating large-scale omics datasets such as genomes and transcriptomes has been shown to provide deeper insights into many aspects of molecular biology. For a better understanding of plant pathogens, we aim to construct a platform for accessing genomic and gene co-expression networks for a range of pathogens and reference species. Currently we have integrated genomic and transcriptomics data from 10 species (Fusarium graminearum, Ustilago maydis, Blumeria graminis, Neurospora crassa, Schizosaccharomyces pombe, Saccharomyces cerevisiae, Escherichia coli, Arabidopsis thaliana, Mus musculus and Homo sapiens). Here we introduce OmicsDB::Pathogens (http://pathogens.omicsdb.org), a publicly available web portal with an underlying database containing genomic, and transcriptomic data and analysis tools. It allows non-bioinformaticians to browse genomic data and inspect and compare biological networks across species. The information is modelled in a graph-based database, enabling flexibility for querying and future extensions. Tools such as BLAST and Cytoscape.js are available together with the option of performing GO enrichment analysis. The database also enables the user to browse information such as Orthologs, Protein domains and publications citing a given gene. Herein we describe how to use this platform for generating hypotheses for the function of a gene. Availability and ImplementationCurrently, Omicsdb supports networks for 10 organisms and is freely available for public use at http://pathogens.omicsdb.org

microbiology↗

bioRxiv2020

Fine-mapping and QTL tissue-sharing information improve causal gene identification and transcriptome prediction performance

The integration of transcriptomic studies and GWAS (genome-wide association studies) via imputed expression has seen extensive application in recent years, enabling the functional characterization and causal gene prioritization of GWAS loci. However, the techniques for imputing transcriptomic traits from DNA variation remain underdeveloped. Furthermore, associations found when linking eQTL studies to complex traits through methods like PrediXcan can lead to false positives due to linkage disequilibrium between distinct causal variants. Therefore, the best prediction performance models may not necessarily lead to more reliable causal gene discovery. With the goal of improving discoveries without increasing false positives, we develop and compare multiple transcriptomic imputation approaches using the most recent GTEx release of expression and splicing data on 17,382 RNA-sequencing samples from 948 post-mortem donors in 54 tissues. We find that informing prediction models with posterior causal probability from fine-mapping (dap-g) and borrowing information across tissues (mashr) lead to better performance in terms of number and proportion of significant associations that are colocalized and the proportion of silver standard genes identified as indicated by precision-recall and ROC (Receiver Operating Characteristic) curves. All prediction models are made publicly available at predictdb.org. Author summaryIntegrating molecular biology information with genome-wide association studies (GWAS) sheds light on the mechanisms tying genetic variation to complex traits. However, associations found when linking eQTL studies to complex traits through methods like PrediXcan can lead to false positives due to linkage disequilibrium of distinct causal variants. By integrating fine-mapping information into the models, and leveraging the widespread tissue-sharing of eQTLs, we improve the proportion of likely causal genes among significant gene-trait associations, as well as the prediction of "ground truth" genes.

genomics↗

bioRxiv2020

Identification of genes required for enzalutamide resistance in castration-resistant prostate cancer cells in vitro

Castration-resistant prostate cancer can be treated with the anti-androgen enzalutamide, but responses and duration of response are variable. To identify genes that support enzalutamide resistance, we performed a short hairpin RNA (shRNA) screen in the bone-homing, castration-resistant prostate cancer cell line, C4-2B. We identified eleven genes (TFAP2C, CAD, SPDEF, EIF6, GABRG2, CDC37, PSMD12, COL5A2, AR, MAP3K11, and ACAT1), whose loss resulted in decreased cell survival in response to enzalutamide. To validate our screen, we performed transient knockdowns in C4-2B and 22Rv1 cells and evaluated cell survival in response to enzalutamide. Through these studies, we validated three genes (ACAT1, MAP3K11, and PSMD12) as supporters of enzalutamide resistance in vitro. Although ACAT1 expression is lower in metastatic castration-resistant prostate cancer samples versus primary prostate cancer samples, knockdown of ACAT1 was sufficient to reduce cell survival in C4-2B and 22Rv1 cells. MAP3K11 expression increases with Gleason grade, and the highest expression is observed in metastatic castration-resistant disease. Knockdown of MAP3K11 reduced cell survival and pharmacologic inhibition of MAP3K11 with CEP-1347 in combination with enzalutamide resulted in a dramatic increase in cell death. This was associated with decreased phosphorylation of AR-Serine650, which is required for maximal AR activation. Finally, while PSMD12 expression did not change during disease progression, knockdown of PSMD12 resulted in decreased AR and AR splice variant expression, likely contributing to the C4-2B and 22Rv1 decrease in cell survival. Our study has therefore identified at least three new supporters of enzalutamide resistance in castration-resistant prostate cancer cells in vitro. Financial supportThe authors would like to acknowledge funding from the Joe C. Davis Foundation (to RJM), the Vanderbilt Institute for Clinical and Translational Research (VICTR, to YY, PEC, and RJM). The Vanderbilt Institute for Clinical and Translational Research (VICTR) is funded by the National Center for Advancing Translational Sciences (NCATS) Clinical Translational Science Award (CTSA) Program, Award Number 5UL1TR002243. The content of this manuscript solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We would also like to acknowledge the Case Research Institute, a joint venture between University Hospitals and Case Western Reserve University, start-up funds (to MMG), and the Cell and Molecular Biology Training Program (T32 GM 008056 to SEK).

cancer biology↗

bioRxiv2020

Chidamide decreases c-MET mRNA methylation and in turn increases the sensitivity of non-small cell lung cancer to crizotinib

IntroductionCrizotinib is a kinase inhibitor targeting c-MET/ALK/ROS1 used as the first-line chemical for the treatment of non-small cell lung cancer (NSCLC) with ALK mutations. Although c-MET is frequently overexpressed in 35-72% of NSCLC, most NSCLCs are primarily resistant to crizotinib treatment. MethodA set of NSCLC cell lines were used to test the effect of chidamide on the crizotinib sensitivity in vitro and in vivo. Relationships between the synergistic effect of chidamide and c-MET expression and RNA methylation were systemically studied with a battery of molecular biological assays. ResultsWe found for the first time that chidamide could increase the crizotinib sensitivity of a set of ALK mutation-free NSCLC cell lines, especially those with high levels of c-MET expression. Notably, chidamide could not increase the crizotinib sensitivity of NSCLC cells cultured in serum-free medium without hepatocyte growth factor (HGF; a c-MET ligand). In contrast, the addition of HGF into the serum-/HGF-free medium could restore the synergistic effect of chidamide. Moreover, the synergistic effect of chidamide could also be abolished either by treatment with c-MET antibody or siRNA-knockdown of c-MET expression. While cells with low or no c-MET expression were primarily resistant to chidamide-crizotinib cotreatment, enforced c-MET overexpression could increase the sensitivity of these cells to chidamide-crizotinib cotreatment. Furthermore, chidamide could decrease c-MET expression by inhibiting mRNA N6-methyladenosine (m6A) modification through the downregulation of METTL3 and WTAP expression. Chidamide-crizotinib cotreatment significantly suppressed the activity of c-MET downstream molecules. Conclusionchidamide downregulated c-MET expression by decreasing its mRNA m6A methylation, subsequently increasing the crizotinib sensitivity of NSCLC cells in a c-MET-/HGF-dependent manner. GRAPHIC SUMMARY O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/012971v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@5a81d4org.highwire.dtl.DTLVardef@19f1forg.highwire.dtl.DTLVardef@75d74forg.highwire.dtl.DTLVardef@8a9f77_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2020

Immunity to infections in arboviral vectors by integrated viral sequences: an evolutionary perspective

In the model organism Drosophila melanogaster, the PIWI-interacing RNA pathway contributes in silencing transposable elements (TEs) through smallRNAs (piRNAs), which arise from genomic loci (piRNA clusters) that contain sequences of previously-acquired TEs. As such, they are a functionally-immune archive of previous TE invasions that is passed to the offspring. In the arboviral vector Aedes aegypti, piRNA clusters contain TEs and endogenous viral elements from nonretroviral RNA viruses (nrEVEs) which produce piRNAs, supporting the hypothesis that nrEVEs are heritable immunity effectors. However, direct evidence that nrEVEs mediate adaptive immunity is lacking. Here, by using an analytic approach intersecting population genomics with molecular biology we demonstrate that the composition of piRNA clusters is modular through acquisition and absence of nrEVEs. We show that the genomes of wild-caught mosquitoes have a different set of nrEVEs than those annotated in the reference genome, including population-specific integrations. nrEVEs are not distributed in mosquito genomes only by genetic drift, but some show signs of positive selection. Moreover, by comparing natural mosquito populations expressing or lacking two newly characterised nrEVEs with high sequence complementarity to cell fusing agent virus, we show that nrEVEs confer antiviral immunity in ovaries against the cognate virus. Our results confirm that some nrEVEs have been co-opted for adaptive immunity to viral infections.

evolutionary biology↗

bioRxiv2020

Pacific Biosciences long reads-based genome sequencing data from a widespread bee fungal parasite, Nosema ceranae

Nosema ceranae is a widespread fungal parasite that infects both adult honeybee and honeybee larvae, leading to microsporidiosis, which seriously affects bee health and apicultural industry. In this article, genome sequencing of clean spores of N. ceranae was conducted using third-generation Pacific Biosciences (PacBio) single molecule real time (SMRT) sequencing technology. In total, 152671 subreads were obtained after quality control of raw reads from PacBio SMRT sequencing, with a N50 and average length of 14422 bp and 11310 bp, respectively. Additionally, the length distribution of subreads was from 10000 bp to more than 50000 bp. Nineteen scaffords with a total length of 7354221 bp were assembled, and the N50, N90 and maximum scafford length were 728543 bp, 198795 bp and 1917792 bp, respectively. The GC content was 25.97%. Furthermore, by integration of genes predicted from de novo and homology-based methods, 3112 N. ceranae genes were finally assembled, with a total length of 2730179 bp and mean length of 877.31 bp. In addition, the total length and mean length of exons were 2657637 bp and 854 bp, respectively; and the total length and mean length of introns were 72542 bp and 23.31 bp, respectively. The genome sequencing data documented here will give deep insights into the molecular biology of N. ceranae, facilitate exploration of genes and pathways associated with toxin factors and infection-related factors, and benefit research on comparative genomics and phylogenetic diversity of Nosema species.

bioinformatics↗

bioRxiv2020

Protein structure analysis of the interactions between SARS-CoV-2 spike protein and the human ACE2 receptor: from conformational changes to novel neutralizing antibodies.

The recent severe acute respiratory syndrome, known as Corona Virus Disease 2019 (COVID-19) has spread so much rapidly and severely to induce World Health Organization (WHO) to declare state of emergency over the new coronavirus SARS-CoV-2 pandemic. While several countries have chosen the almost complete lock-down for slowing down SARS-CoV-2 spread, scientific community is called to respond to the devastating outbreak by identifying new tools for diagnosis and treatment of the dangerous COVID-19. With this aim we performed an in silico comparative modeling analysis, which allows to gain new insights about the main conformational changes occurring in the SARS-CoV-2 spike protein, at the level of the receptor binding domain (RBD), along interactions with human cells angiotensin converting enzyme 2 (ACE2) receptor, that favour human cell invasion. Furthermore, our analysis provides i) an ideal pipeline to identify already characterized antibodies that might target SARS-CoV-2 spike RBD, for preventing interactions with the human ACE2, and ii) instructions for building new possible neutralizing antibodies, according to chemical/physical space restraints and complementary determining regions (CDR) mutagenesis of the identified existing antibodies. The proposed antibodies show in silico a high affinity for SARS-CoV-2 spike RBD and can be used as reference antibodies also for building new high affinity antibodies against present and future coronavirus able to invade human cells through interactions of their spike proteins with the human ACE2. More in general, our analysis provides indications for the set-up of the right biological molecular context for investigating spike RBD-ACE2 interactions for the development of new vaccines, diagnosis kits and other treatments based on the usage or the targeting of SARS-CoV-2 spike protein.

biochemistry↗

bioRxiv2020

A scientometric overview of CORD-19

As the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has been made available along-side calls to help mine the information it contains and to create tools to search it more effectively. We analyse the delineation of the publications included in CORD-19 from a scientometric perspective. Based on a comparison to the Web of Science database, we find that CORD-19 provides an almost complete coverage of research on COVID-19 and coronaviruses. CORD-19 contains not only research that deals directly with COVID-19 and coronaviruses, but also research on viruses in general. Publications from CORD-19 focus mostly on a few well-defined research areas, in particular: coronaviruses (primarily SARS-CoV, MERS-CoV and SARS-CoV-2); public health and viral epidemics; molecular biology of viruses; influenza and other families of viruses; immunology and antivirals; clinical medicine. CORD-19 publications that appeared in 2020, especially editorials and letters, are disproportionately popular on social media. While we fully endorse the CORD-19 initiative, it is important to be aware that CORD-19 extends beyond research on COVID-19 and coronaviruses.

scientific communication and education↗

bioRxiv2020

Analyzing Genomic Data Using Tensor-Based Orthogonal Polynomials

An important goal in molecular biology is to quantify both the patterns across a genomic sequence and the relationship between phenotype and underlying sequence. We propose a multivariate tensor-based orthogonal polynomial approach to characterize nucleotides or amino acids in a given sequence and map corresponding phenotypes onto the sequence space. We have applied this method to a previously published case of small transcription activating RNAs (STARs). Covariance patterns along the sequence showcased strong correlations between nucleotides at the ends of the sequence. However, when the phenotype is projected onto the sequence space, this pattern doesnt emerge. When doing second order analysis and quantifying the functional relationship between the phenotype and pairs of sites along the sequence, we identified sites with high regressions spread across the sequence, indicating potential intramolecular binding. In addition to quantifying interactions between different parts of a sequence, the method quantifies sequence-phenotype interactions at first and higher order levels. We discuss the strengths and constraints of the method and compare it to computational methods such as machine learning approaches. An accompanying command line tool to compute these polynomials is provided. We show proof of concept of this approach and demonstrate its potential application to other biological systems.

bioinformatics↗

bioRxiv2020

A Multi-perspective Analysis of Retractions in Life Sciences

The aim of this study is to explore trends in retracted publications in life sciences and biomedical sciences over axes like time, countries, journals and impact factors, and topics. Nearly seven thousand publications, which comprise the entirety of retractions visible through PubMed as of August 2019, were used. This work involved sophisticated data collection and analysis techniques to use data from PubMed, Wikipedia, and WikiData, and study it with respect to the above mentioned axes. Importantly, I employ state-of-the-art analysis and visualization techniques from natural language processing (NLP) to understand the topics in retracted literature. To highlight a few results, the analyses demonstrate an increasing rate of retraction over time and noticeable differences in the publication quality (as measured by journal impact factor) among top countries. Moreover, while molecular biology and cancer dominate retractions, we also see a number of retractions not related to biology. The methods and results of this study can be applied to continuously understand the nature and evolution of retractions in life sciences, thus contributing to the health of this research ecosystem.

scientific communication and education↗

bioRxiv2020

Structural Analysis of 70S Ribosomes by Cross-Linking/Mass Spectrometry Reveals Conformational Plasticity

The ribosome is not only a highly complex molecular machine that executes translation according to the central dogma of molecular biology, but also an exceptional specimen for testing and optimizing cross-linking/mass spectrometry (XL-MS) workflows. Due to its high abundance, ribosomal proteins are frequently identified in proteome-wide XL-MS studies of cells or cell extracts. Here, we performed in-depth cross-linking of the E. coli ribosome using the amine-reactive cross-linker diacetyl dibutyric urea (DSAU). We analyzed 143 E. coli ribosomal structures, mapping a total of 10,771 intramolecular distances for 126 cross-link-pairs and 3,405 intermolecular distances for 97 protein pairs. Remarkably, 44% of intermolecular cross-links covered regions that have not been resolved in any high-resolution E. coli ribosome structure and point to a plasticity of cross-linked regions. We systematically characterized all cross-links and discovered flexible regions, conformational changes, and stoichiometric variations in bound ribosomal proteins, and ultimately remodeled 2,057 residues (15,794 atoms) in total. Our working model explains more than 95% of all cross-links, resulting in an optimized E. coli ribosome structure based on the cross-linking data obtained. Our study might serve as benchmark for conducting biochemical experiments on newly modeled protein regions, guided by XL-MS. Data are available via ProteomeXchange with identifier PXD018935.

biochemistry↗

bioRxiv2020

Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

The coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing global health threat with more than two million infected people since its emergence in late 2019. Detailed knowledge of the molecular biology of the infection is indispensable for understanding of the viral replication, host responses, and disease progression. We provide gene expression profiles of SARS-CoV and SARS-CoV-2 infections in three human cell lines (H1299, Caco-2 and Calu-3 cells), using bulk and single-cell transcriptomics. Small RNA profiling showed strong expression of the immunity and inflammation-associated microRNA miRNA-155 upon infection with both viruses. SARS-CoV-2 elicited approximately two-fold higher stimulation of the interferon response compared to SARS-CoV in the permissive human epithelial cell line Calu-3, and induction of cytokines such as CXCL10 or IL6. Single cell RNA sequencing data showed that canonical interferon stimulated genes such as IFIT2 or OAS2 were broadly induced, whereas interferon beta (IFNB1) and lambda (IFNL1-4) were expressed only in a subset of infected cells. In addition, temporal resolution of transcriptional responses suggested interferon regulatory factors (IRFs) activities precede that of nuclear factor-{kappa}B (NF-{kappa}B). Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 charperone activity by Tanespimycin/17-N-allylamino-17-demethoxygeldanamycin (17-AAG) resulted in a reduction of viral replication, and of TNF and IL1B mRNA levels. In summary, our study established in vitro cell culture models to study SARS-CoV-2 infection and identified HSP90 protein as potential drug target for therapeutic intervention of SARS-CoV-2 infection.

systems biology↗