The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.

Lentivirus-based vectors derived from human immunodeficiency viruses type 1 and 2 (HIV-1 and 2) are widely used tools in research and may also be utilized in clinical settings. Like their parental virions, they are known to depend on the cellular machinery for successful gene delivery and integration. While most of the studies on cellular proteomic and transcriptomic changes have focused on the late phase of the transduction, studies of those changes in early time-points, especially in the case of HIV-2 based vectors, are widely lacking. Using second generation HIV-1 and 2 vesicular stomatitis virus G protein (VSV-G) pseudotyped lentiviral vectors, we transduced HEK-293T human embryonic kidney cells and carried out transcriptomic profiling at 0 and 2 h time points, with accompanying proteomic analysis at 2 h following transduction. Significant variations were observed in gene expression profile between HIV-1 and HIV-2 transduced samples. Thrombospondin 1 (THBS1), collagens (COL1A2, COL3A1), and eukaryotic translation factors (EIF3CL) in addition to various genes coding for long non-coding RNA (lncRNA) were significantly upregulated 2 h after HIV-2 transduction compared to HIV-1. Label-free quantification mass spectrometry (MS) indicated that seven proteins involved in RNA binding, mRNA transport, and chaperoning were significantly downregulated. The identification of cellular protein targets of lentiviral vectors and their effect on the cellular transcriptome will undoubtedly shed more light on their complex life cycle and may be utilized against infection by their parental lentiviruses. Furthermore, characterizing the early phase of HIV-2 infection may aid in the understanding of its pathomechanism and long incubation period.

Metabolomics strategies are widely used to examine obesity and type 2 diabetes (T2D). Patients with obesity (n = 31) or T2D (n = 26) and sex- and age-matched controls (n = 28) were recruited, and serum and tear samples were collected. The concentration of 23 amino acids and 10 biogenic amines in serum and tear samples was analyzed. Statistical analysis and Pearson correlation analysis along with network analysis were carried out. Compared to controls, changes in the level of 6 analytes in the obese group and of 10 analytes in the T2D group were statistically significant. For obesity, the energy generation, while for T2D, the involvement of NO synthesis and its relation to insulin signaling and inflammation, were characteristic. We found that BCAA and glutamine metabolism, urea cycle, and beta-oxidation make up crucial parts of the metabolic changes in T2D. According to our data, the retromer-mediated retrograde transport, the ethanolamine metabolism, and, consequently, the endocannabinoid signaling and phospholipid metabolism were characteristic of both conditions and can be relevant pathways to understanding and treating insulin resistance. By providing potential therapeutic targets and new starting points for mechanistic studies, our results emphasize the importance of complex data analysis procedures to better understand the pathomechanism of obesity and diabetes.

(1) Background: Wine contains a variety of molecules with potential beneficial effects on human health. Our aim was to examine the wine components with high-resolution mass spectrometry including high-resolution tandem mass spectrometry in two wine types made from grapes with or without the fungus Botrytis cinerea, or “noble rot”. (2) For LC-MS/MS analysis, 12 wine samples (7 without and 5 with noble rotting) from 4 different wineries were used and wine components were identified and quantified. (3) Results: 288 molecules were identified in the wines and the amount of 169 molecules was statistically significantly different between the two wine types. A database search was carried out to find the molecules, which were examined in functional studies so far, with high emphasis on molecules with antiviral, anti-inflammatory and anticancer activities. (4) Conclusions: A comprehensive functional dataset related to identified wine components is also provided highlighting the importance of components with potential health benefits.

The reanalysis of genomics and proteomics datasets by bioinformatics approaches is an appealing way to examine large amounts of reliable data. This can be especially true in cases such as Alzheimer’s disease, where the access to biological samples, along with well-defined patient information can be challenging. Considering the inflammatory part of Alzheimer’s disease, our aim was to examine the presence of antimicrobial and immunomodulatory peptides in human proteomic datasets deposited in the publicly available proteomics database ProteomeXchange (http://www.proteomexchange.org/). First, a unified, comprehensive human antimicrobial and immunomodulatory peptide database, containing all known human antimicrobial and immunomodulatory peptides was constructed and used along with the datasets containing high-quality proteomics data originating from the examination of Alzheimer’s disease and control groups. A throughout network analysis was carried out, and the enriched GO functions were examined. Less than 1% of all identified proteins in the brain were antimicrobial and immunomodulatory peptides, but the alterations characteristic of Alzheimer’s disease could be recapitulated with their analysis. Our data emphasize the key role of the innate immune system and blood clotting in the development of Alzheimer’s disease. The central role of antimicrobial and immunomodulatory peptides suggests their utilization as potential targets for mechanistic studies and future therapies.