Rhinovirus prevalence as indicator for efficacy of measures against SARS-CoV-2

BACKGROUND

Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses.

METHODS

We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany. With a probabilistic model for Bayes inference we quantified prevalence changes of the different viruses between months in the pre-pandemic period 2010-2019 and the corresponding months in 2020, the year of the pandemic with noninvasive measures of various degrees of stringency.

RESULTS

We discovered remarkable reductions δ in rhinovirus (RV) prevalence by about 25% (95% highest density interval (HDI) [-0.35,-0.15]) in the months after the measures against SARS-CoV-2 were introduced in Germany. In the months after the measures began to ease, RV prevalence increased to low pre-pandemic levels, e.g. in August 2020 δ=-0.14 (95% HDI [-0.28,0.12]).

CONCLUSIONS

RV prevalence is negatively correlated with the stringency of anti-SARS-CoV-2 measures with only a short time delay. This result suggests that RV prevalence could possibly be an indicator for the efficiency for these measures. As RV is ubiquitous at higher prevalence than SARS-CoV-2 or other emerging respiratory viruses, it could reflect the efficacy of noninvasive measures better than such emerging viruses themselves with their unevenly spreading clusters.

Comprehensive Comparison of RNA-Seq Data of SARS-CoV-2, SARS-CoV and MERS-CoV Infections: Alternative Entry Routes and Innate Immune Responses

Background

The pathogenesis of COVID-19 emerges as complex, with multiple factors leading to injury of different organs. Some of the studies on aspects of SARS-CoV-2 cell entry and innate immunity have produced seemingly contradictory claims. In this situation, a comprehensive comparative analysis of a large number of related datasets from several studies could bring more clarity, which is imperative for therapy development.

Methods

We therefore performed a comprehensive comparative study, analyzing RNA-Seq data of infections with SARS-CoV-2, SARS-CoV and MERS-CoV, including data from different types of cells as well as COVID-19 patients. Using these data, we investigated viral entry routes and innate immune responses.

Results and Conclusion

First, our analyses support the existence of cell entry mechanisms for SARS and SARS-CoV-2 other than the ACE2 route with evidence of inefficient infection of cells without expression of ACE2; expression of TMPRSS2/TPMRSS4 is unnecessary for efficient SARS-CoV-2 infection with evidence of efficient infection of A549 cells transduced with a vector expressing human ACE2. Second, we find that innate immune responses in terms of interferons and interferon simulated genes are strong in relevant cells, for example Calu3 cells, but vary markedly with cell type, virus dose, and virus type.

Epigenetic Mechanisms Mediating Cell State Transitions in Chondrocytes

Epigenetic modifications play critical roles in regulating cell lineage differentiation, but the epigenetic mechanisms guiding specific differentiation steps within a cell lineage have rarely been investigated. To decipher such mechanisms, we used the defined transition from proliferating (PC) into hypertrophic chondrocytes (HC) during endochondral ossification as a model. We established a map of activating and repressive histone modifications for each cell type. ChromHMM state transition analysis and Pareto-based integration of differential levels of mRNA and epigenetic marks revealed that differentiation-associated gene repression is initiated by the addition of H3K27me3 to promoters still carrying substantial levels of activating marks. Moreover, the integrative analysis identified genes specifically expressed in cells undergoing the transition into hypertrophy. Investigation of enhancer profiles detected surprising differences in enhancer number, location, and transcription factor binding sites between the two closely related cell types. Furthermore, cell type-specific upregulation of gene expression was associated with increased numbers of H3K27ac peaks. Pathway analysis identified PC-specific enhancers associated with chondrogenic genes, whereas HC-specific enhancers mainly control metabolic pathways linking epigenetic signature to biological functions. Since HC-specific enhancers show a higher conservation in postnatal tissues, the switch to metabolic pathways seems to be a hallmark of differentiated tissues. Surprisingly, the analysis of H3K27ac levels at super-enhancers revealed a rapid adaption of H3K27ac occupancy to changes in gene expression, supporting the importance of enhancer modulation for acute alterations in gene expression. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Integrin Alpha E (CD103) Limits Virus-Induced IFN-I Production in Conventional Dendritic Cells

Early and strong production of IFN-I by dendritic cells is important to control vesicular stomatitis virus (VSV), however mechanisms which explain this cell-type specific innate immune activation remain to be defined. Here, using a genome wide association study (GWAS), we identified Integrin alpha-E (Itgae, CD103) as a new regulator of antiviral IFN-I production in a mouse model of vesicular stomatitis virus (VSV) infection. CD103 was specifically expressed by splenic conventional dendritic cells (cDCs) and limited IFN-I production in these cells during VSV infection. Mechanistically, CD103 suppressed AKT phosphorylation and mTOR activation in DCs. Deficiency in CD103 accelerated early IFN-I in cDCs and prevented death in VSV infected animals. In conclusion, CD103 participates in regulation of cDC specific IFN-I induction and thereby influences immune activation after VSV infection.

intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data

BACKGROUND

RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy.

RESULTS

Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization.

CONCLUSION

intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.

IgGeneUsage: differential gene usage in immune repertoires

SUMMARY

Decoding the properties of immune repertoires is key to understanding the adaptive immune response to challenges such as viral infection. One important quantitative property is differential usage of Ig genes between biological conditions. Yet, most analyses for differential Ig gene usage are performed qualitatively or with inadequate statistical methods. Here we introduce IgGeneUsage, a computational tool for the analysis of differential Ig gene usage. IgGeneUsage employs Bayesian inference with hierarchical models to analyze complex gene usage data from high-throughput sequencing experiments of immune repertoires. It quantifies differential Ig gene usage probabilistically and avoids some common problems related to the current practice of null-hypothesis significance testing.

AVAILABILITY AND IMPLEMENTATION

IgGeneUsage is an R-package freely available as part of Bioconductor at: https://bioconductor.org/packages/IgGeneUsage/.

CONTACT

simo.kitanovski@uni-due.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.