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Highlights d Link between SARS-COV-2 mutation biases, HLA alleles, and immune escape d Dominant C/U SARS-CoV-2 mutations diversify the CD8 + T cell epitope repertoire d Mutation biases modulate epitope presentation in an HLAsupertype-dependent manner d Preferential loss of epitopes in B7 HLA supertype due to prevalent loss of proline Authors

Optimizing the quality of proteomics data collected from a mass spectrometer (MS) requires careful selection of acquisition parameters and proper assessment of instrument performance. Software tools capable of extracting a broad set of information from raw files, including meta, scan, quantification, and identification data, are needed to provide guidance for MS system management. In this work, direct extraction and utilization of these data is demonstrated using RawTools, a standalone tool for extracting meta and scan data directly from raw MS files generated on Thermo Orbitrap instruments. RawTools generates summarized and detailed plain text outputs after parsing individual raw files, including scan rates and durations, duty cycle characteristics, precursor and reporter ion quantification, and chromatography performance. RawTools also contains a diagnostic module that includes an optional “preview” database search for facilitating informed decision-making related to optimization of MS performance based on a variety of metrics. RawTools has been developed in C# and utilizes the Thermo RawFileReader library and thus can process raw MS files with high speed and high efficiency on all major operating systems (Windows, MacOS, Linux). To demonstrate the utility of RawTools, the extraction of meta and scan data from both individual and large collections of raw MS files was carried out to identify problematic characteristics of instrument performance. Taken together, the combined rich feature-set of RawTools with the capability for interrogation of MS and experiment performance makes this software a valuable tool for proteomics researchers.

A free solution method was developed for evaluating the specific binding affinity and stoichiometry of small molecules with oligo DNA subsequent to cation-induced G-quadruplex formation. A nonlinear curve fitting equation capable of extracting specific binding constants in the presence of nonspecific binding without the need for reference compounds was proposed and tested. Electrospray ionization mass spectrometry was first used to rapidly screen the small molecule candidates; then, the stoichiometry and affinity constants of the native state binding pair in solution were obtained with capillary electrophoresis frontal analysis (CE-FA). The B cell lymphoma 2 (Bcl-2) oncogene is directly responsible for the expression of Bcl-2 protein, which plays a significant role in cell apoptosis. The binding of a G-quadruplex formed in the promoter region of the Bcl-2 oncogene with a small molecule could stabilize the quadruplex structure and potentially regulate the transcription of Bcl-2. Four natural product drug candidates were tested for their ability to bind the Bcl-2 promoter G-quadruplex. Using this reference-free method based on CE-FA data, jatrorrhizine and palmatine were found to bind specifically to the Bcl-2 promoter G-quadruplex with stoichiometries of 4:1 and 3:1, respectively.

Capillary electrophoresis frontal analysis (CE‐FA) can be used to determine binding affinity of molecular interactions. However, its current data processing method mandate specific requirement on the mobilities of the binding pair in order to obtain accurate binding constants. This work shows that significant errors are resulted when the mobilities of the interacting species do not meet these requirements. Therefore, the applicability of CE‐FA in many real word applications becomes questionable. An electrophoretic mobility‐based correction method is developed in this work based on the flux of each species. A simulation program and a pair of model compounds are used to verify the new equations and evaluate the effectiveness of this method. Ibuprofen and hydroxypropyl‐β‐cyclodextrinare used to demonstrate the differences in the obtained binding constant by CE‐FA when different calculation methods are used, and the results are compared with those obtained by affinity capillary electrophoresis (ACE). The results suggest that CE‐FA, with the mobility‐based correction method, can be a generally applicable method for a much wider range of applications.

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Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS, MS, and MS metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags.

MS-based immunopeptidomics is maturing into an automatized and high-throughput technology, producing small- to large-scale datasets of clinically relevant major histocompatibility complex (MHC) class I-associated and class II-associated peptides. Consequently, the development of quality control (QC) and quality assurance systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semiautomated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts. In essence, MVP provides a rapid and consolidated view of sample quality, composition, and MHC specificity to greatly accelerate the “pass–fail” QC decision-making process toward data interpretation. MVP parallelizes the use of well-established immunopeptidomic algorithms (NetMHCpan, NetMHCIIpan, and GibbsCluster) and rapidly generates organized and easy-to-understand reports in HTML format. The reports are fully portable and can be viewed on any computer with a modern web browser. MVP is intuitive to use and will find utility in any specialized immunopeptidomic laboratory and proteomics core facility that provides immunopeptidomic services to the community.