Proteomic landscape of SARS-CoV-2– and MERS-CoV–infected primary human renal epithelial cells

Renal implications of coronavirus disease 2019: insights into viral tropism and clinical outcomes

In recent years, multiple coronaviruses have emerged, with the latest one, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing a global pandemic. Besides respiratory symptoms, some patients experienced extrapulmonary effects, such as cardiac damage or renal injury, indicating the broad tropism of SARS-CoV-2. The ability of the virus to effectively invade the renal cellular environment can eventually cause tissue-specific damage and disease. Indeed, patients with severe coronavirus disease 2019 exhibited a variety of symptoms such as acute proximal tubular injury, ischemic collapse, and severe acute tubular necrosis resulting in irreversible kidney failure. This review summarizes the current knowledge on how it is believed that SARS-CoV-2 influences the renal environment and induces kidney disease, as well as current therapy approaches.

The Initial COVID-19 Reliable Interactive DNA Methylation Markers and Biological Implications

Earlier research has established the existence of reliable interactive genomic biomarkers. However, reliable DNA methylation biomarkers, not to mention interactivity, have yet to be identified at the epigenetic level. This study, drawing from 865,859 methylation sites, discovered two miniature sets of Infinium MethylationEPIC sites, each having eight CpG sites (genes) to interact with each other and disease subtypes. They led to the nearly perfect (96.87-100% accuracy) prediction of COVID-19 patients from patients with other diseases or healthy controls. These CpG sites can jointly explain some post-COVID-19-related conditions. These CpG sites and the optimally performing genomic biomarkers reported in the literature become potential druggable targets. Among these CpG sites, cg16785077 (gene MX1), cg25932713 (gene PARP9), and cg22930808 (gene PARP9) at DNA methylation levels indicate that the initial SARS-CoV-2 virus may be better treated as a transcribed viral DNA into RNA virus, i.e., not as an RNA virus that has concerned scientists in the field. Such a discovery can significantly change the scientific thinking and knowledge of viruses.

Transcriptomics of Marburg virus-infected primary proximal tubular cells reveals negative correlation of immune response and energy metabolism

Marburg virus, a member of the Filoviridae, is the causative agent of Marburg virus disease (MVD), a hemorrhagic fever with a case fatality rate of up to 90 %. Acute kidney injury is common in MVD and is associated with increased mortality, but its pathogenesis in MVD remains poorly understood. Interestingly, autopsies show the presence of viral proteins in different parts of the nephron, particularly in proximal tubular cells (PTC). These findings suggest a potential role for the virus in the development of MVD-related kidney injury. To shed light on this effect, we infected primary human PTC with Lake Victoria Marburg virus and conducted transcriptomic analysis at multiple time points. Unexpectedly, infection did not induce marked cytopathic effects in primary tubular cells at 20 and 40 h post infection. However, gene expression analysis revealed robust renal viral replication and dysregulation of genes essential for different cellular functions. The gene sets mainly downregulated in PTC were associated with the targets of the transcription factors MYC and E2F, DNA repair, the G2M checkpoint, as well as oxidative phosphorylation. Importantly, the downregulated factors comprise PGC-1α, a well-known factor in acute and chronic kidney injury. By contrast, the most highly upregulated gene sets were those related to the inflammatory response and cholesterol homeostasis. In conclusion, Marburg virus infects and replicates in human primary PTC and induces downregulation of processes known to be relevant for acute kidney injury as well as a strong inflammatory response.

SARS-CoV-2 variants show different host cell proteome profiles with delayed immune response activation in Omicron-infected cells

The ancestral SARS-CoV-2 strain that initiated the Covid-19 pandemic at the end of 2019 has rapidly mutated into multiple variants of concern with variable pathogenicity and increasing immune escape strategies. However, differences in host cellular antiviral responses upon infection with SARS-CoV-2 variants remains elusive. Leveraging whole cell proteomics, we determined host signalling pathways that are differentially modulated upon infection with the clinical isolates of the ancestral SARS-CoV-2 B.1 and the variants of concern Delta and Omicron BA.1. Our findings illustrate alterations in the global host proteome landscape upon infection with SARS-CoV-2 variants and the resulting host immune responses. Additionally, viral proteome kinetics reveal declining levels of viral protein expression during Omicron BA.1 infection when compared to ancestral B.1 and Delta variants, consistent with its reduced replication rates. Moreover, molecular assays reveal deferral activation of specific host antiviral signalling upon Omicron BA.1 and BA.2 infections. Our study provides an overview of host proteome profile of multiple SARS-CoV-2 variants and brings forth a better understanding of the instigation of key immune signalling pathways causative for the differential pathogenicity of SARS-CoV-2 variants.

Choosing a cellular model to study SARS-CoV-2

As new pathogens emerge, new challenges must be faced. This is no different in infectious disease research, where identifying the best tools available in laboratories to conduct an investigation can, at least initially, be particularly complicated. However, in the context of an emerging virus, such as SARS-CoV-2, which was recently detected in China and has become a global threat to healthcare systems, developing models of infection and pathogenesis is urgently required. Cell-based approaches are crucial to understanding coronavirus infection biology, growth kinetics, and tropism. Usually, laboratory cell lines are the first line in experimental models to study viral pathogenicity and perform assays aimed at screening antiviral compounds which are efficient at blocking the replication of emerging viruses, saving time and resources, reducing the use of experimental animals. However, determining the ideal cell type can be challenging, especially when several researchers have to adapt their studies to specific requirements. This review strives to guide scientists who are venturing into studying SARS-CoV-2 and help them choose the right cellular models. It revisits basic concepts of virology and presents the currently available in vitro models, their advantages and disadvantages, and the known consequences of each choice.

Gene Networks of Hyperglycemia, Diabetic Complications, and Human Proteins Targeted by SARS-CoV-2: What Is the Molecular Basis for Comorbidity?

People with diabetes are more likely to have severe COVID-19 compared to the general population. Moreover, diabetes and COVID-19 demonstrate a certain parallelism in the mechanisms and organ damage. In this work, we applied bioinformatics analysis of associative molecular networks to identify key molecules and pathophysiological processes that determine SARS-CoV-2-induced disorders in patients with diabetes. Using text-mining-based approaches and ANDSystem as a bioinformatics tool, we reconstructed and matched networks related to hyperglycemia, diabetic complications, insulin resistance, and beta cell dysfunction with networks of SARS-CoV-2-targeted proteins. The latter included SARS-CoV-2 entry receptors (ACE2 and DPP4), SARS-CoV-2 entry associated proteases (TMPRSS2, CTSB, and CTSL), and 332 human intracellular proteins interacting with SARS-CoV-2. A number of genes/proteins targeted by SARS-CoV-2 (ACE2, BRD2, COMT, CTSB, CTSL, DNMT1, DPP4, ERP44, F2RL1, GDF15, GPX1, HDAC2, HMOX1, HYOU1, IDE, LOX, NUTF2, PCNT, PLAT, RAB10, RHOA, SCARB1, and SELENOS) were found in the networks of vascular diabetic complications and insulin resistance. According to the Gene Ontology enrichment analysis, the defined molecules are involved in the response to hypoxia, reactive oxygen species metabolism, immune and inflammatory response, regulation of angiogenesis, platelet degranulation, and other processes. The results expand the understanding of the molecular basis of diabetes and COVID-19 comorbidity.