MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets.

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.

The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.

The science that investigates the ensembles of all peptides associated to human leukocyte antigen (HLA) molecules is termed "immunopeptidomics" and is typically driven by mass spectrometry (MS) technologies. Recent advances in MS technologies, neoantigen discovery and cancer immunotherapy have catalyzed the launch of the Human Immunopeptidome Project (HIPP) with the goal of providing a complete map of the human immunopeptidome and making the technology so robust that it will be available in every clinic. Here, we provide a long-term perspective of the field and we use this framework to explore how we think the completion of the HIPP will truly impact the society in the future. In this context, we introduce the concept of immunopeptidome-wide association studies (IWAS). We highlight the importance of large cohort studies for the future and how applying quantitative immunopeptidomics at population scale may provide a new look at individual predisposition to common immune diseases as well as responsiveness to vaccines and immunotherapies. Through this vision, we aim to provide a fresh view of the field to stimulate new discussions within the community, and present what we see as the key challenges for the future for unlocking the full potential of immunopeptidomics in this era of precision medicine.

RawTools: Rapid and Dynamic Interrogation of Orbitrap Data Files for Mass Spectrometer System Management.

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.

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant.

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 MS1, MS2, and MS3 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.

Specific Binding Constant and Stoichiometry Determination in Free Solution by Mass Spectrometry and Capillary Electrophoresis Frontal Analysis.

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.

Mobility-based correction for accurate determination of binding constants by capillary electrophoresis-frontal analysis.

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-ß-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.

Characterization of dicarboxylic naphthenic acid fraction compounds utilizing amide derivatization: Proof of concept.

RATIONALE: The characterization of naphthenic acid fraction compounds (NAFCs) in oil sands process affected water (OSPW) is of interest for both toxicology studies and regulatory reasons. Previous studies utilizing authentic standards have identified dicarboxylic naphthenic acids using two-dimensional gas chromatography hyphenated to time-of-flight mass spectrometry (GC × GC/TOFMS). The selective derivatization of hydroxyl groups has also recently aided in the characterization of oxy-NAFCs, and indirectly the characterization of dicarboxylic NAFCs. However, there has been no previous report of derivatization being used to directly aid in the standard-free characterization of NAFCs with multiple carboxylic acid functional groups. Herein we present proof-of-concept for the characterization of dicarboxylic NAFCs utilizing amide derivatization. METHODS: Carboxylic acid groups in OSPW extract and in a dicarboxylic acidstandard were derivatized to amides using a previously described method. The derivatized extract and derivatized standard were analyzed by direct-injection positive-mode electrospray ionization ((+)ESI) high-resolution mass spectrometry (HRMS), and the underivatized extract was analyzed by (-)ESI MS. Tandem mass spectrometry (MS/MS) was carried out on selected ions of the derivatized standard and derivatized OSPW. Data analysis was carried out using the Python programming language. RESULTS: The distribution of monocarboxylic NAFCs observed in the amide-derivatized OSPW sample by (+)ESI-MS was generally similar to that seen in underivatized OSPW by (-)ESI-MS. The dicarboxylic acid standard shows evidence of being doubly derivatized, although the second derivatization appears to be inefficient. Furthermore, a spectrum of potential diacid NAFCs is presented, identified by both charge state and derivatization mass. Interference due to the presence of multiple derivatization products is noted, but can be eliminated using on-line separation or an isotopically labelled derivatization reagent. CONCLUSIONS: Proof of concept for the characterization of dicarboxylic NAFCs utilizing amide derivatization is demonstrated. Furthermore, (+)ESI-HRMS of the derivatized monocarboxylic NAFCS yields similar information to (-)ESI-MS analysis of underivatized NAFCs, with the benefit of added selectivity for carboxylic acid species and the characterization of diacids.

Understanding the constitutive presentation of MHC class I immunopeptidomes in primary tissues.

Understanding the molecular principles that govern the composition of the MHC-I immunopeptidome across different primary tissues is fundamentally important to predict how T cells respond in different contexts in vivo. Here, we performed a global analysis of the MHC-I immunopeptidome from 29 to 19 primary human and mouse tissues, respectively. First, we observed that different HLA-A, HLA-B, and HLA-C allotypes do not contribute evenly to the global composition of the MHC-I immunopeptidome across multiple human tissues. Second, we found that tissue-specific and housekeeping MHC-I peptides share very distinct properties. Third, we discovered that proteins that are evolutionarily hyperconserved represent the primary source of the MHC-I immunopeptidome at the organism-wide scale. Fourth, we uncovered new components of the antigen processing and presentation network, including the carboxypeptidases CPE, CNDP1/2, and CPVL. Together, this study opens up new avenues toward a system-wide understanding of antigen presentation in vivo across mammalian species.

The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA-supertype-dependent manner.

The rapid, global dispersion of SARS-CoV-2 has led to the emergence of a diverse range of variants. Here, we describe how the mutational landscape of SARS-CoV-2 has shaped HLA-restricted T cell immunity at the population level during the first year of the pandemic. We analyzed a total of 330,246 high-quality SARS-CoV-2 genome assemblies, sampled across 143 countries and all major continents from December 2019 to December 2020 before mass vaccination or the rise of the Delta variant. We observed that proline residues are preferentially removed from the proteome of prevalent mutants, leading to a predicted global loss of SARS-CoV-2 T cell epitopes in individuals expressing HLA-B alleles of the B7 supertype family; this is largely driven by a dominant C-to-U mutation type at the RNA level. These results indicate that B7-supertype-associated epitopes, including the most immunodominant ones, were more likely to escape CD8+ T cell immunosurveillance during the first year of the pandemic.

RHybridFinder: An R package to process immunopeptidomic data for putative hybrid peptide discovery.

Identification of proteasomal spliced peptides (PSPs) by mass spectrometry (MS) is not possible with traditional search engines. Here, we provide a protocol for running RHybridFinder (RHF), an R package for the computational inference of putative PSPs detected by MS. RHF extracts high confidence scored de novo sequenced peptides identified by PEAKS software. Those peptides are then matched to protein databases to infer cis- or trans-spliced major histocompatibility complex (MHC)-associated peptides. RHF is relatively fast and straightforward. PSPs have to be validated experimentally. For complete details on the use and execution of the original protocol, please refer to Faridi et al. (2018).