Cancer driver genes are either oncogenes or tumour suppressor genes that are classically activated or inactivated, respectively, by driver mutations. Alternative splicing-which produces various mature mRNAs and, eventually, protein variants from a single gene-may also result in driving neoplastic transformation because of the different and often opposed functions of the variants of driver genes. The present review analyses the different alternative splicing events that result in driving neoplastic transformation, with an emphasis on their molecular mechanisms. To do this, we collected a list of 568 gene drivers of cancer and revised the literature to select those involved in the alternative splicing of other genes as well as those in which its pre-mRNA is subject to alternative splicing, with the result, in both cases, of producing an oncogenic isoform. Thirty-one genes fall into the first category, which includes splicing factors and components of the spliceosome and splicing regulators. In the second category, namely that comprising driver genes in which alternative splicing produces the oncogenic isoform, 168 genes were found. Then, we grouped them according to the molecular mechanisms responsible for alternative splicing yielding oncogenic isoforms, namely, mutations in cis splicing-determining elements, other causes involving non-mutated cis elements, changes in splicing factors, and epigenetic and chromatin-related changes. The data given in the present review substantiate the idea that aberrant splicing may regulate the activation of proto-oncogenes or inactivation of tumour suppressor genes and details on the mechanisms involved are given for more than 40 driver genes.

The diagnosis of alpha-1-antitrypsin (A1AT) deficiency is established by quantitation of protein concentration in serum (immunoassay) followed by determination of specific allelic variants by phenotyping (isoelectric focusing (IEF) gel electrophoresis) and/or allele-specific genotyping. Various phenotyping and genotyping methodologies are available, and each has their own advantages and disadvantages. As an alternative, mass spectrometry is emerging as a powerful tool in the identification and quantitation of proteins and peptides. The method described here, referred to as proteotyping, is a proteomic method using trypsin digestion and tandem mass spectrometry that detects the most common deficiency alleles, S and Z, associated with A1AT deficiency.This qualitative mass spectrometry method is based on the principle that the S and Z mutations lead to amino acid changes which result in a change in the mass of the A1AT protein. When the A1AT protein is proteolytically digested, multiple peptides are generated, two of which include the sites of the S and Z mutations, respectively. Peptides generated from wild-type A1AT (M alleles) differ in sequence and mass from peptides generated from the S and Z alleles at these two specific locations. The mass difference allows for differentiation of S and Z peptides, representing the deficiency alleles, from non-S and non-Z peptides, representing the wild-type alleles (M). Interpretation of the peptide patterns in conjunction with A1AT quantitation by immunoassay allows for an accurate assessment for the presence of deficiency alleles in the majority of patients.

Itraconazole is a triazole anti-infective drug that has been proven to prevent and treat a variety of fungal and viral infections and has been considered to be a potential therapeutic remedy for COVID-19 treatment. In this study, we aimed to completely evaluate the impacts of Cytochrome P450 3A4 (CYP3A4) variant proteins and drug interactions on the metabolism of itraconazole in recombinant insect microsomes, and to characterize the potential mechanism of substrate selectivity. Incubations with itraconazole (0.2-15 μM) in the presence/absence of lopinavir or darunavir were assessed by CYP3A4 variants, and the metabolite hydroxyitraconazole concentrations were measured by UPLC-MS/MS. Our data showed that when compared with CYP3A4.1, 4 variants (CYP3A4.9, .10, .28 and .34) displayed no significant differences, and 3 variants (CYP3A4.14, .15 and .19) exhibited increased intrinsic clearance (CLint), whereas the remaining 17 variant proteins showed decreased enzyme activities for the catalysis of itraconazole. Moreover, the inhibitory effects of lopinavir and darunavir on itraconazole metabolism varied in different degrees. Furthermore, different changed trend of the kinetic parameters in ten variants (CYP3A4.5, .9, .10, .16, .19, .24, .28, .29, .31, and .33) were observed, especially CYP3A4.5 and CYP3A4.16, and this may be related to the metabolic site-heme iron atom distance. In the present study, we functionally analyzed the effects of 25 CYP3A4 protein variants on itraconazole metabolism for the first time, and provided comprehensive data on itraconazole metabolism in vitro. This may help to better assess the metabolism and elimination of itraconazole in clinic to improve the safety and efficacy of its clinical treatment and also provide new possibilities for the treatment of COVID-19.

Expression of rdar (red, dry, and rough) colony morphology-based biofilm formation in Escherichia coli is highly variable. To investigate the molecular mechanisms of semi-constitutive rdar morphotype formation, we compared their cyclic di-GMP turnover protein content and variability to the highly regulated, temperature-dependent morphotype of the historical and modern ST10 isolates E. coli MG1655 and Fec10, respectively. Subsequently, we assessed the effects of cyclic di-GMP turnover protein variants of the EAL phosphodiesterases YcgG and YjcC and the horizontally transferred diguanylate cyclase DgcX on biofilm formation and motility. The two YcgG variants with truncations of the N-terminal CSS signaling domain were oppositely effective in targeting downregulation of rdar biofilm formation compared to the full-length reference protein. Expression of the C-terminal truncated variants YjcCFec67 and YjcCTob1 showed highly diminished apparent phosphodiesterase activity compared to the reference YjcCMG1655. For YjcCFec101, substitution of the C-terminus led to an apparently inactive enzyme. Overexpression of the diguanylate cyclase DgcX contributed to upregulation of cellulose biosynthesis but not to elevated expression of the major biofilm regulator csgD in the \"classical\" rdar-expressing commensal strain E. coli Fec10. Thus, the c-di-GMP regulating network is highly complex with protein variants displaying substantially different apparent enzymatic activities.

Although the reversed-phase liquid chromatography (RPLC) is the most used separation front for mass spectrometry, many other separation modes are critical for enabling characterization of the protein therapeutics. Specifically, chromatographic separations under native conditions, such as those based on size exclusion chromatography (SEC) and ion-exchange chromatography (IEX), are used for characterizing important biophysical properties of protein variants in drug substance and drug product. Because most native state separation modes use non-volatile buffers with high salt concentration, optical detection has been traditionally used. However, there is an increasing need to understand and identify the optical underlying peaks by mass spectrometry for structure elucidation. For size variant separation by SEC, the native MS helps to understand the nature of the high molecular weight species, as well as clipping sites for low molecular weight fragments. For charge variant separation by IEX, native MS can reveal the post-translational modifications or other important factors contributing to charge heterogeneity at the intact level. Here, we demonstrate the power of native MS by direct coupling of SEC and IEX eluent to a time-of-flight mass spectrometer to characterize bevacizumab and NISTmAb. Our studies exemplify the effectiveness of native SEC-MS for characterizing bevacizumab\'s high molecular weight species at less than 0.3% (based on SEC/UV peak area%) and analyzing the fragment pathway with single amino acid difference for its low molecular weight species at less than 0.05%. Good IEX charge variant separation was obtained with consistent UV and MS profiles. The identity of separated acidic and basic variants were elucidated by native MS at intact level. We successfully differentiated several charge variants including glycoform variants that have not been reported before. In addition, native MS allowed identification of higher molecular weight species as late eluted variants. Overall, the SEC and IEX separation combined with high resolution and high sensitivity native MS, which is significantly different from the traditional RPLC-MS workflows, can be an effective tool that offers valuable insights for us to understand protein therapeutics at native state.

Current proteomic technologies focus on the quantification of protein levels, while little effort is dedicated to the development of system approaches to simultaneously monitor proteome variability and abundance. Protein variants may display different immunogenic epitopes detectable by monoclonal antibodies. Epitope variability results from alternative splicing, posttranslational modifications, processing, degradation, and complex formation and possesses dynamically changing availability of interacting surface structures that frequently serve as reachable epitopes and often carry different functions. Thus, it is highly likely that the presence of some of the accessible epitopes correlates with function under physiological and pathological conditions. To enable the exploration of the impact of protein variation on the immunogenic epitome first, here, we present a robust and analytically validated PEP technology for characterizing immunogenic epitopes of the plasma. To this end, we prepared mAb libraries directed against the normalized human plasma proteome as a complex natural immunogen. Antibody producing hybridomas were selected and cloned. Monoclonal antibodies react with single epitopes, thus profiling with the libraries is expected to profile many epitopes which we define by the mimotopes, as we present here. Screening blood plasma samples from control subjects (n = 558) and cancer patients (n = 598) for merely 69 native epitopes displayed by 20 abundant plasma proteins resulted in distinct cancer-specific epitope panels that showed high accuracy (AUC 0.826-0.966) and specificity for lung, breast, and colon cancer. Deeper profiling (≈290 epitopes of approximately 100 proteins) showed unexpected granularity of the epitope-level expression data and detected neutral and lung cancer-associated epitopes of individual proteins. Biomarker epitope panels selected from a pool of 21 epitopes of 12 proteins were validated in independent clinical cohorts. The results demonstrate the value of PEP as a rich and thus far unexplored source of protein biomarkers with diagnostic potential.

Narrow host range is a major limitation for phage applications, but phages can evolve expanded host range through adaptations in the receptor-binding proteins.
Here, we report that Pseudomonas phage K8 can evolve broader host range and higher killing efficiency at the cost of virion stability. Phage K8 host range mutant K8-T239A carries a mutant version of the putative baseplate wedge protein GP075, termed GP075m. While phage K8 adsorbs to hosts via the O-specific antigen of bacterial LPS, phage K8-T239A uses GP075m to also bind the bacterial core oligosaccharide, enabling infection of bacterial strains resistant to K8 infection due to modified O-specific antigens. This mutation in GP075 also alters inter-protein interactions among phage proteins, and reduces the stability of phage particles to environmental stressors like heat, acidity, and alkalinity. We find that a variety of mutations in gp075 are widespread in K8 populations, and that the gp075-like genes are widely distributed among the domains of life.
Our data show that a typical life history tradeoff occurs between the stability and the host range in the evolution of phage K8. Reservoirs of viral gene variants may be widely present in phage communities, allowing phages to rapidly adapt to any emerging environmental stressors. Video Abstract.

Blood-based biomarkers are needed for the early diagnosis of Alzheimer\'s disease (AD). We analyzed longitudinal human plasma samples from AD and control cases to identify biomarkers for the early diagnosis of AD. Plasma samples were grouped based on clinical diagnosis at the time of collection: AD, mild cognitive impairment (MCI), and pre-symptomatic (preMCI). Samples were analyzed by ELISA using a panel of reagents against nine different AD-related amyloid-β (Aβ), tau, or TDP-43 variants. Receiver operating characteristic (ROC) curves of different biomarker panels for different diagnostic sample groups were determined. Analysis of all of the samples gave a sensitivity of 92% and specificity of 76% for the diagnosis of AD. Early-stage diagnosis of AD, utilizing only the preMCI and MCI samples, identified 88% of AD cases. Using sex-biased biomarker panels, early diagnosis of AD cases improved to 96%. Using the sex-biased panels, we also identified 6 of the 25 control group cases as being at high risk of AD, which is consistent with what is expected given the advanced age of the control cases. Specific AD-associated protein variants are effective blood-based biomarkers for the early diagnosis of AD. Notably, significant differences were observed in biomarker profiles for the early detection of male and female AD cases.

Multi-omics approaches including proteomics analyses are becoming an integral component of precision medicine. As clinical proteomics studies gain momentum and their sensitivity increases, research on identifying individuals based on their proteomics data is here examined for risks and ethics-related issues. A great deal of work has already been done on this topic for DNA/RNA sequencing data, but it has yet to be widely studied in other omics fields. The current state-of-the-art for the identification of individuals based solely on proteomics data is explained. Protein sequence variation analysis approaches are covered in more detail, including the available analysis workflows and their limitations. We also outline some previous forensic and omics proteomics studies that are relevant for the identification of individuals. Following that, we discuss the risks of patient reidentification using other proteomics data types such as protein expression abundance and post-translational modification (PTM) profiles. In light of the potential identification of individuals through proteomics data, possible legal and ethical implications are becoming increasingly important in the field.

The SARS-CoV-2 variant Omicron is characterized, among others, by more than 30 amino acid changes occurring on the spike glycoprotein with respect to the original SARS-CoV-2 spike protein. We report a comprehensive analysis of the effects of the Omicron spike amino acid changes in the interaction with human antibodies, obtained by modeling them into selected publicly available resolved 3D structures of spike-antibody complexes and investigating the effects of these mutations at structural level. We predict that the interactions of Omicron spike with human antibodies can be either negatively or positively affected by amino acid changes, with a predicted total loss of interactions only in a few complexes. Moreover, our analysis applied also to the spike-ACE2 interaction predicts that these amino acid changes may increase Omicron transmissibility. Our approach can be used to better understand SARS-CoV-2 transmissibility, detectability, and epidemiology and represents a model to be adopted also in the case of other variants.