The genome of the SARS-CoV-2 virus, the causal agent of the COVID-19 pandemic, has diverged due to multiple mutations since its emergence as a human pathogen in December 2019. Some mutations have defined several SARS-CoV-2 clades that seem to behave differently in terms of regional distribution and other biological features. Next-generation sequencing (NGS) approaches are used to classify the sequence variants in viruses from individual human patients. However, the cost and relative scarcity of NGS equipment and expertise in developing countries prevent studies aimed to associate specific clades and variants to clinical features and outcomes in such territories. As of March 2021, the GR clade and its derivatives, including the B.1.1.7 and B.1.1.28 variants, predominate worldwide. We implemented the post-PCR small-amplicon high-resolution melting analysis to genotype SARS-CoV-2 viruses isolated from the saliva of individual patients. This procedure was able to clearly distinguish two groups of samples of SARS-CoV-2-positive samples predicted, according to their melting profiles, to contain GR and non-GR viruses. This grouping of the samples was validated by means of amplification-refractory mutation system (ARMS) assay as well as Sanger sequencing.
Background: Pituitary adenomas (PA) are the second most common tumor in the central nervous system and have low counts of mutated genes. Splicing occurs in 95% of the coding RNA. There is scarce information about the spliceosome and mRNA-isoforms in PA, and therefore we carried out proteomic and transcriptomic analysis to identify spliceosome components and mRNA isoforms in PA. Methods: Proteomic profile analysis was carried out by nano-HPLC and mass spectrometry with a quadrupole time-of-flight mass spectrometer. The mRNA isoforms and transcriptomic profiles were carried out by microarray technology. With proteins and mRNA information we carried out Gene Ontology and exon level analysis to identify splicing-related events. Results: Approximately 2000 proteins were identified in pituitary tumors. Spliceosome proteins such as SRSF1, U2AF1 and RBM42 among others were found in PA. These results were validated at mRNA level, which showed up-regulation of spliceosome genes in PA. Spliceosome-related genes segregate and categorize PA tumor subtypes. The PA showed alterations in CDK18 and THY1 mRNA isoforms which could be tumor specific. Conclusions: Spliceosome components are significant constituents of the PA molecular machinery and could be used as molecular markers and therapeutic targets. Splicing-related genes and mRNA-isoforms profiles characterize tumor subtypes.
Cellular interactions within the bone marrow microenvironment modulate the properties of subsets of leukemic cells leading to the development of drug-resistant phenotypes. The intercellular transfer of proteins and organelles contributes to this process but the set of transferred proteins and their effects in the receiving cells remain unclear. This study aimed to detect the intercellular protein transfer from mouse bone marrow stromal cells (OP9 cell line) to human T-lymphoblasts (CCRF-CEM cell line) using nanoLC-MS/MS-based shotgun proteomics in a 3D co-culture system. After 24 h of co-culture, 1513 and 67 proteins from human and mouse origin, respectively, were identified in CCRF-CEM cells. The presence of mouse proteins in the human cell line, detected by analyzing the differences in amino acid sequences of orthologous peptides, was interpreted as the result of intercellular transfer. The transferred proteins might have contributed to the observed resistance to vincristine, methotrexate, and hydrogen peroxide in the co-cultured leukemic cells. Our results suggest that shotgun proteomic analyses of co-cultured cells from different species could be a simple option to get a preliminary survey of the proteins exchanged among interacting cells.