Tryptic Peptides Research Articles

New plasma LC-MS/MS assays for the quantitation of beta-amyloid peptides and identification of apolipoprotein E proteoforms for Alzheimer's disease risk assessment.

Early detection of Alzheimer's disease (AD) represents an unmet clinical need. Beta-amyloid (Aβ) plays an important role in AD pathology, and the Aβ42/40 peptide ratio is a good indicator for amyloid deposition. In addition, variants of the apolipoprotein E (APOE) gene are associated with variable AD risk. Here, we describe the development and validation of high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays for plasma Aβ40 and Aβ42 quantitation, as well as apolipoprotein E (ApoE) proteotype determination as a surrogate for APOE genotype. Aβ40 and Aβ42 were simultaneously immunoprecipitated from plasma, proteolytically digested, and quantitated by LC-MS/MS. ApoE proteotype status was qualitatively assessed by targeting tryptic peptides from the ApoE2, ApoE3, and ApoE4 proteoforms. Both assays were validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Within-run precision was 1.8%-4.2% (Aβ40), 1.9%-7.2% (Aβ42), and 2.6%-8.3% (Aβ42/40 ratio). Between-run precision was 3.5%-5.9% (Aβ40), 3.8%-8.0% (Aβ42), and 3.3%-8.7% (Aβ42/40 ratio). Both Aβ40 and Aβ42 were linear from 10 to 2500 pg/mL. Identified ApoE proteotypes had 100% concordance with APOE genotypes. We have developed a precise, accurate, and sensitive high-throughput LC-MS/MS assay for plasma Aβ40, Aβ42, and proteoforms of ApoE.

Polyaminated, acetylated and stop codon readthrough of recombinant Francisella tularensis universal stress protein in Escherichia coli.

Recombinant Francisella tularensis universal stress protein with a C-terminal histidine-tag (rUsp/His6) was expressed in Escherichia coli. Endogenous F. tularensis Usp has a predicted molecular mass of 30 kDa, but rUsp/His6 had an apparent molecular weight of 33 kDa based on Western blot analyses. To determine the source of the higher molecular weight for rUsp/His6, post translational modifications were examined. Tryptic peptides of purified rUsp/His6 were subjected to liquid chromatography tandem mass spectrometry (LC-MS/MS) and fragmentation spectra were searched for acetylated lysines and polyaminated glutamines. Of the 24 lysines in rUsp/His6, 10 were acetylated (K63, K68, K72, K129, K175, K201, K208, K212, K233, and K238) and three of the four glutamines had putrescine, spermidine and spermine adducts (Q55, Q60 and Q267). The level of post-translational modification was substoichiometric, eliminating the possibility that these modifications were the sole contributor to the 3 kDa extra mass of rUsp/His6. LC-MS/MS revealed that stop codon readthrough had occurred resulting in the unexpected addition of 20 extra amino acids at the C-terminus of rUsp/His6, after the histidine tag. Further, the finding of polyaminated glutamines in rUsp/His6 indicated that E. coli is capable of transglutaminase activity.

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide.

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics.

Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.

Removal of isobaric interference using pseudo-multiple reaction monitoring and energy-resolved mass spectrometry for the isotope dilution quantification of a tryptic peptide.

Energy-resolved mass spectrometry (ERMS) and an isotopically labelled internal standard were successfully combined to accurately quantify a tryptic peptide despite the presence of an isobaric interference. For this purpose, electrospray ionisation tandem mass spectrometry (ESI-MS/MS) experiments were conducted into an ion trap instrument using an unconventional 8m/z broadband isolation window, which encompassed both the tryptic peptide and its internal standard. Interference removal was assessed by determining an excitation voltage that was high enough to maintain a constant value for the analyte/internal standard peaks intensity ratio, thus ensuring accurate quantification even in the presence of isobaric contamination. Pseudo-multiple reaction monitoring (MRM) was employed above this excitation voltage to quantify the trypic peptide. The internal standard calibration model showed no lack of fit and exhibited a linear dynamic range from 0.5μM up to 2.5μM. The detection limit was 0.08 μM. The accuracy of the method was evaluated by quantifying the tryptic peptide of three reference samples intentionally contaminated with the isobaric interference. All the reference samples were accurately quantified with ∼1% deviation despite the isobaric contamination. Furthermore, we have demonstrated that this methodology can also be applied to quantify the isobaric peptide by standard additions down to 0.2μM. Finally, liquid chromatography ERMS (LC ERMS) experiments yielded similar results, suggesting the potential of the proposed methodology for analysing complex samples.

Improved Detection of Tryptic Peptides from Tissue Sections Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

DESI-MSI is an ambient ionization technique used frequently for the detection of lipids, small molecules, and drug targets. Until recently, DESI had only limited use for the detection of proteins and peptides due to the setup and needs around deconvolution of data resulting in a small number of species being detected at lower spatial resolution. There are known differences in the ion species detected using DESI and MALDI for nonpeptide molecules, and here, we identify that this extends to proteomic species. DESI MS images were obtained for tissue sections of mouse and rat brain using a precommercial heated inlet (approximately 450 °C) to the mass spectrometer. Ion mobility separation resolved spectral overlap of peptide ions and significantly improved the detection of multiply charged species. The images acquired were of pixel size 100 μm (rat brain) and 50 μm (mouse brain), respectively. Observed tryptic peptides were filtered against proteomic target lists, generated by LC-MS, enabling tentative protein assignment for each peptide ion image. Precise localizations of peptide ions identified by DESI and MALDI were found to be comparable. Some spatially localized peptides ions were observed in DESI that were not found in the MALDI replicates, typically, multiply charged species with a low mass to charge ratio. This method demonstrates the potential of DESI-MSI to detect large numbers of tryptic peptides from tissue sections with enhanced spatial resolution when compared to previous DESI-MSI studies.

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.

Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Toward an Ultimate Solution for Peptide Retention Time Prediction: The Effect of Column Temperature on Separation Selectivity.

We studied the effect of the column temperature on the selectivity of reversed-phase peptide separation in bottom-up proteomics. The number of peptide identifications from 2 h liquid chromatography with tandem mass spectrometry (LC-MS/MS) acquisitions reaches a plateau at 45-55 °C, driven simultaneously by improved separation efficiency, a gradual decrease in peptide retention, and possible on-column degradation of peptides at elevated temperatures. Performing 2D LC-MS/MS acquisitions at 25, 35, 45, and 55 °C resulted in the identification of ∼100,000 and ∼120,000 unique peptides for nonmodified and tandem mass tags (TMT)-labeled samples, respectively. These peptide collections were used to investigate the temperature-driven retention features. The latter is governed by the specific temperature response of individual residues, peptide hydrophobicity and length, and amphipathic helicity. On average, peptide retention decreased by 0.56 and 0.5% acetonitrile for each 10 °C increase for label-free and TMT-labeled peptides, respectively. This generally linear response of retention shifts allowed the extrapolation of predictive models beyond the studied temperature range. Thus, (trap) column cooling from room temperature to 0 °C will allow the retention of an additional 3% of detectable tryptic peptides. Meanwhile, the application of 90 °C would result in the loss of ∼20% of tryptic peptides that were amenable to MS/MS-based identification.

Mass spectrometry imaging protocol for spatial mapping of lipids, N-glycans and peptides in murine lung tissue.

The application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to murine lungs is challenging due to the spongy nature of the tissue. Lungs consist of interconnected air sacs (alveoli) lined by a single layer of flattened epithelial cells, which requires inflation to maintain its natural structure. Therefore, a protocol that is compatible with both lung instillation and high spatial resolution is essential to enable multi-omic studies on murine lung disease models using MALDI-MSI. To maintain the structural integrity of the tissue, murine lungs were inflated with 8% (w/v) gelatin for lipid MSI of fresh frozen tissues or 4% (v/v) paraformaldehyde neutral buffer for N-glycan and peptide MSI of FFPE tissues. Tissues were sectioned and prepared for enzymatic digestion and/or matrix deposition. Glycerol-free PNGase F was applied for N-glycan MSI, while Trypsin Gold was applied for peptide MSI using the iMatrixSpray and ImagePrep Station, respectively. For lipid, N-glycan and peptide MSI, α-cyano-4-hydroxycinnamic acid matrix was deposited using the iMatrixSpray. MS data were acquired with 20 μm spatial resolution using a timsTOF fleX MS instrument followed by MS fragmentation of lipids, N-glycans and peptides. For lipid MSI, trapped ion mobility spectrometry was used to separate isomeric/isobaric lipid species. SCiLS™ Lab was used to visualize all MSI data. For analyte identification, MetaboScape®, GlycoMod and Mascot were used to annotate MS fragmentation spectra of lipids, N-glycans and tryptic peptides, respectively. Our protocol provides instructions on sample preparation for high spatial resolution MALDI-MSI, MS/MS data acquisition and lipid, N-glycan and peptide annotation and identification from murine lungs. This protocol will allow non-biased analyses of diseased lungs from preclinical murine models and provide further insight into disease models.

Abstract 3802: Integrating multiplex-staining and multiplex-DIA: Profiling the tumor microenvironment spatial proteome for precision cancer research

Abstract Our innovative dual-dimensional multiplexing approach ushers in a new era of spatial proteomic exploration. Multiplex-staining deepens understanding of tumor-stroma interactions. Our robust dimethyl labeling-based multiplex-DIA workflow enhances throughput and proteome depth in the Deep Visual Proteomics (DVP) technology. Now, our audacious integration of multiplex-staining with multiplex-DIA holds the promise of pushing the boundaries of spatial proteome profiling. This innovation combines the power of mass spectrometry (MS) with clinical viability in 1) requiring just one FFPE section for spatial proteome analysis at the resolution of individual cell types; 2) ingeniously transmuting MS revelations into a clinically feasible staining strategy. A force in personalized oncology, our innovation unravels the intricate dynamics of the cancer ecosystem while ensuring direct clinical relevance. We conducted multiplex immunofluorescent staining on human cancers using the MACSima platform, followed by cellular phenotyping and automated single-cell laser microdissection. Subsequently, we loaded dimethyl-labelled 3-plex tryptic peptides onto Evotips and performed LC-MS analysis using the Evosep One coupled to timsTOF SCP. Pre- and post-22-plex staining proteome analysis confirmed no significant protein loss, validating microdissection compatibility and excellent recovery. The key findings include: 1) profiling of 21 distinct cell types/subtypes in human tonsil cancer tissues, resulting in the identification of 4941 protein groups from a cellular volume of 110,859 µm3, equivalent to approximately 55 cells; 2) observation of a loss of CD45RA/RO expression in tumor-infiltrating cytotoxic T cells, contributing to a reduction in MET and PDGF signaling activity within tumor cells; 3) the presence of abundant cytotoxic T cells, B cells, and plasma cells, coupled with a reduction in tumor cell proliferation, indicative of a hot tumor microenvironment. Proteome analysis revealed enhanced immune cell mobility and interactions with tumor cells. Moreover, our workflow facilitated the identification of potential diagnostic markers for mycosis fungoides, a marker-lacking skin lymphoma, where we achieved the identification of 2964 significant proteins out of a total of 6009. In addition, a rare lymphoma case study not only guided ABVD chemotherapy and suggested IL4 inhibition to address chemoresistance but also identified CDK, MCM, and PSMA/B/C/D/E inhibitors as promising candidates for targeted therapy. The integration of multiplex-staining and multiplex-DIA represents a significant stride in advancing personalized diagnostics and therapeutic strategies. Citation Format: Xiang Zheng, Andreas Mund, Matthias Mann. Integrating multiplex-staining and multiplex-DIA: Profiling the tumor microenvironment spatial proteome for precision cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3802.

Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5’-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model

Human leukocyte antigen (HLA) class I peptide ligands (HLAIps) are key targets for developing vaccines and immunotherapies against infectious pathogens or cancer cells. Identifying HLAIps is challenging due to their high diversity, low abundance, and patient individuality. Here, we develop a highly sensitive method for identifying HLAIps using liquid chromatography-ion mobility-tandem mass spectrometry (LC-IMS-MS/MS). In addition, we train a timsTOF-specific peak intensity MS2PIP model for tryptic and non-tryptic peptides and implement it in MS2Rescore (v3) together with the CCS predictor from ionmob. The optimized method, Thunder-DDA-PASEF, semi-selectively fragments singly and multiply charged HLAIps based on their IMS and m/z. Moreover, the method employs the high sensitivity mode and extended IMS resolution with fewer MS/MS frames (300 ms TIMS ramp, 3 MS/MS frames), doubling the coverage of immunopeptidomics analyses, compared to the proteomics-tailored DDA-PASEF (100 ms TIMS ramp, 10 MS/MS frames). Additionally, rescoring boosts the HLAIps identification by 41.7% to 33%, resulting in 5738 HLAIps from as little as one million JY cell equivalents, and 14,516 HLAIps from 20 million. This enables in-depth profiling of HLAIps from diverse human cell lines and human plasma. Finally, profiling JY and Raji cells transfected to express the SARS-CoV-2 spike protein results in 16 spike HLAIps, thirteen of which have been reported to elicit immune responses in human patients.

The Shelf Life of Milk-A Novel Concept for the Identification of Marker Peptides Using Multivariate Analysis.

The quality of food is influenced by several factors during production and storage. When using marker compounds, different steps in the production chain, as well as during storage, can be monitored. This might enable an optimum prediction of food's shelf life and avoid food waste. Especially, proteoforms and peptides thereof can serve as indicators for exogenous influences. The development of a proteomics-based workflow for detecting and identifying differences in the proteome is complex and time-consuming. The aim of the study was to develop a fast and universal workflow with ultra-high temperature (UHT) milk as a proteinaceous model food with expectable changes in protein/peptide composition. To find an optimum shelf life without sticking to a theoretically fixed best-before date, new evaluation and analytical methods are needed. Consequently, a modeling approach was used to monitor the shelf life of the milk after it was treated thermally and stored. The different peptide profiles determined with high-resolution mass spectrometry (HRMS) showed a significant difference depending on the preparation method of the samples. Potential marker peptides were determined using orthogonal projections to latent structures discriminant analysis (OPLSDA) and principal component analysis (PCA) following a typical proteomics protocol with tryptic hydrolysis. An additional Python-based algorithm enabled the identification of eight potential tryptic marker peptides (with mass spectrometric structural indications m/z 885.4843, m/z 639.3500, m/z 635.8622, m/z 634.3570, m/z 412.7191, m/z 623.2967, m/z 880.4767, and m/z 692.4041), indicating the effect of the heat treatment. The developed workflow is flexible and can be easily adapted to different research questions in the field of peptide analysis. In particular, the process of feature identification can be carried out with significantly less effort than with conventional methods.

The effect of glycation on the identification of characteristic tryptic peptides from porcine gelatin

High-performance liquid chromatography and linear-ion trap/Orbitrap high-resolution mass spectrometry (HPLC-LTQ/Orbitrap MS/MS) was used to trace the origin of porcine gelatin under different glycation reaction times. With the extension of the glycation reaction time, the characteristic peptides of porcine gelatin gradually decreased, indicating that the glycation reaction would have an impact on the identification of porcine gelatin. In addition, compared with the porcine gelatin theoretical characteristic peptide database, it was found that the number of characteristic peptides of porcine gelatin in the glycation reaction of 0, 24, 48, 72 and 96 h were 39, 84, 82, 73 and 70, respectively. Among them, 33 characteristic peptides did not change with the extension of glycation time. Compared with our previous research, 9 characteristic peptides were found to be common to porcine gelatins under the different food processing conditions. These stable common characteristic peptides could be used as an important basis for porcine gelatin traceability with high accuracy.

Evaluation of different isotope dilution mass spectrometry strategies for the characterization of naturally abundant and isotopically labelled peptide standards

Natural abundance and isotopically labelled tryptic peptides are routinely employed as standards in quantitative proteomics. The certification of the peptide content is usually carried out by amino acid analysis using isotope dilution mass spectrometry (IDMS) after the acid hydrolysis of the peptide. For the validation and traceability of the amino acid analysis procedure, expensive certified peptides must be employed. In this work we evaluate different IDMS alternatives which will reduce the amount of certified peptide required for validation of the amino acid analysis procedure. In this context, the characterization of both natural and isotopically labelled synthetic angiotensin I peptides was carried out. First, we applied a fast procedure for peptide hydrolysis based on microwave-assisted digestion and employed two certified peptide reference materials SRM 998 angiotensin I and CRM 6901-b C-peptide for validation of the hydrolysis procedure. The amino acids proline, leucine, isoleucine, valine, tyrosine, arginine and phenylalanine were evaluated for their suitability for peptide certification by IDMS by both liquid chromatography with tandem mass spectrometry (LC–MS/MS) and gas chromatography with mass spectrometry (GC)–MS/MS. Then, natural angiotensin I and 13C1-labelled angiotensin I were synthesized in-house and purified by preparative liquid chromatography. The concentration of the 13C1-labelled angiotensin I peptide was established by reverse IDMS in its native form using SRM 998 angiotensin I as reference. The concentration of the natural synthesized peptide was determined by IDMS both using the 13C1-labelled peptide in its native form and by amino acid analysis showing comparable results. Finally, the synthetic naturally abundant angiotensin I peptide was employed as “in-house” standard for the validation of subsequent peptide characterization procedures. Therefore, the novelty of this work relies on, first, the development of a faster hydrolysis procedure assisted by focused microwaves, providing complete hydrolysis in 150 min, and secondly, a validation strategy combining GC–MS and LC–MS/MS that allowed us to certify the purity of an in-house-synthesized peptide standard that can be employed as quality control in further experiments.Graphical abstract

UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow.

We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high-quality tandem mass spectra (MS2) from 0.8 million unique peptide ions, UniSpec learned with a peptide fragmentation dictionary encompassing 7919 fragment peaks. Among these, 5712 are neutral loss peaks, with 2310 corresponding to modification-specific neutral losses. Remarkably, UniSpec can predict 73%-77% of fragment intensities based on our NIST reference library spectra, a significant leap from the 35%-45% coverage of only b and y ions. Comparative studies with Prosit elucidate that while both models are strong at predicting their respective fragment ion series, UniSpec particularly shines in generating more complex MS2 spectra with diverse ion annotations. The integration of UniSpec's predictions into shotgun proteomics data analysis boosts the identification rate of tryptic peptides by 48% at a 1% false discovery rate (FDR) and 60% at a more confident 0.1% FDR. Using UniSpec's predicted in-silico spectral library, the search results closely matched those from search engines and experimental spectral libraries used in peptide identification, highlighting its potential as a stand-alone identification tool. The source code and Python scripts are available on GitHub (https://github.com/usnistgov/UniSpec) and Zenodo (https://zenodo.org/records/10452792), and all data sets and analysis results generated in this work were deposited in Zenodo (https://zenodo.org/records/10052268).

Mass Spectrometry of Putrescine, Spermidine, and Spermine Covalently Attached to Francisella tularensis Universal Stress Protein and Bovine Albumin.

Bacterial and mammalian cells are rich in putrescine, spermidine, and spermine. Polyamines are required for optimum fitness, but the biological function of these small aliphatic compounds has only been partially revealed. Known functions of polyamines include interaction with nucleic acids that alters gene expression and with proteins that modulate activity. Although polyamines can be incorporated into proteins, very few naturally occurring polyaminated proteins have been identified, which is due in part to the difficulty in detecting these adducts. In the current study, bovine albumin and the recombinant universal stress protein from Francisella tularensis were used as models for mass spectrometry analysis of polyaminated proteins. The proteins were covalently bound to putrescine, spermidine, or spermine by the action of carbodiimide or microbial transglutaminase. Tryptic peptides, subjected to liquid chromatography tandem mass spectrometry (LC-MS/MS), were identified using Protein Prospector software. We describe the search parameters for identifying polyaminated peptides and show MS/MS spectra for adducts with putrescine, spermidine, and spermine. Manual evaluation led us to recognize signature ions for polyamine adducts on aspartate, glutamate, and glutamine, as well as neutral loss from putrescine, spermidine, and spermine during the fragmentation process. Mechanisms for the formation of signature ions and neutral loss are presented. Manual evaluation identified a false-positive adduct that had formed during trypsinolysis and resulted in peptide sequence rearrangement. Another false positive initially appeared to be a 71 kDa putrescine adduct on a cysteine residue. However, it was an acrylamide adduct on cysteine for a sample extracted from a polyacrylamide gel. The information presented in this report provides guidance and serves as a model for identifying naturally occurring polyaminated proteins.

Infliximab Therapeutic monitoring by tryptic peptide LC-MS/MS method improvements lead to improved accuracy with decreased imprecision and turnaround time

IntroductionTherapeutic drug monitoring of infliximab has become the standard of care for inflammatory bowel disease in the setting of loss of response to therapy, and occasionally in proactive therapy personalization. Measurement of infliximab by tryptic peptide HPLC-MS/MS has been available since 2015, mostly in reference laboratories. ObjectivesHere, we present method improvements to our original published method leading to a more efficient, robust, and high throughput tryptic peptide HPLC-MS/MS assay for infliximab quantitation. MethodsDeidentified residual serum samples submitted for clinical testing were used for method comparison and infliximab was spiked into normal human serum for performance studies. Improvements included the addition of a stable isotope labeled full length infliximab internal standard (IS) replacing a surrogate IS, and immunoenrichment using Melon Gel for immunoglobulins replacing the saturated ammonium sulfate precipitation. Digestion and chromatography were optimized, and automation was added. The method improvements were validated to include precision, accuracy, reportable range, linearity, and analytical sensitivity. ResultsThe digestion time was reduced from overnight to 1 h. The assay analytical measuring range (AMR) remained the same throughout improvements, 1–100 µg/mL, with linearity of 0.98x + 0.50, R2 = 1.00. Intra- and inter-assay imprecision were less than 5 % CV at four different concentrations. Accuracy was assessed with 106 patients within the AMR; Passing-Bablok Regression yielded a slope of 1.00 and a y-intercept of 0.25. Turnaround time was reduced by 1 day, and imprecision of three levels of quality control trended down after new method implementation. ConclusionsMethod improvements including automation have allowed for assay completion in half a day, improving robustness and turnaround time.

Stabilizing the Proteomes of Acute Myeloid Leukemia Cells: Implications for Cancer Proteomics

Previous work has shown that inhibition of abundant myeloid azurophil granule-associated serine proteases (ELANE [neutrophil elastase], PRTN3 [protease 3], and CTSG [Cathepsin G]) is required to stabilize some proteins in myeloid cells. We therefore hypothesized that effective inhibition of these proteases may be necessary for quantitative proteomic analysis of samples containing myeloid cells. To test this hypothesis, we thawed viably preserved acute myeloid leukemia cells from cryovials in the presence or the absence of diisopropyl fluorophosphate (DFP), a cell-permeable and irreversible serine protease inhibitor. Global proteomic analysis was performed, using label-free and isobaric peptide-labeling quantitation. The presence of DFP resulted in an increase of tryptic peptides (14–57%) and proteins (9–31%). In the absence of DFP, 11 to 31% of peptide intensity came from nontryptic peptides; 52 to 75% had cleavage specificity consistent with activities of ELANE–PRTN3. Treatment with DFP reduced the intensity of nontryptic peptides to 4-8% of the total. ELANE inhibition was 95%, based on diisopropyl phosphate modification of active site serine residue. Overall, the relative abundance of 20% of proteins was significantly altered by DFP treatment. These results suggest that active myeloid serine proteases, released during sample processing, can skew quantitative proteomic measurements. Finally, significant ELANE activity was also detected in Clinical Proteomics Tumor Analysis Consortium datasets of solid tumors (many of which have known myeloid infiltration). In the pancreatic cancer dataset, the median percentage of nontryptic intensity detected across patient samples was 34%, with many patient samples having more than half of their detected peptide intensity from nontryptic cleavage events consistent with ELANE-PRTN3 cleavage specificity. Our study suggests that in vitro cleavage of proteins by myeloid serine proteases may be relevant for proteomic studies of any tumor that contains infiltrating myeloid cells.

Deep Learning-Assisted Analysis of Immunopeptidomics Data.

Liquid chromatography-coupled mass spectrometry (LC-MS/MS) is the primary method to obtain direct evidence for the presentation of disease- or patient-specific human leukocyte antigen (HLA). However, compared to the analysis of tryptic peptides in proteomics, the analysis of HLA peptides still poses computational and statistical challenges. Recently, fragment ion intensity-based matching scores assessing the similarity between predicted and observed spectra were shown to substantially increase the number of confidently identified peptides, particularly in use cases where non-tryptic peptides are analyzed. In this chapter, we describe in detail three procedures on how to benefit from state-of-the-art deep learning models to analyze and validate single spectra, single measurements, and multiple measurements in mass spectrometry-based immunopeptidomics. For this, we explain how to use the Universal Spectrum Explorer (USE), online Oktoberfest, and offline Oktoberfest. For intensity-based scoring, Oktoberfest uses fragment ion intensity and retention time predictions from the deep learning framework Prosit, a deep neural network trained on a very large number of synthetic peptides and tandem mass spectra generated within the ProteomeTools project. The examples shown highlight how deep learning-assisted analysis can increase the number of identified HLA peptides, facilitate the discovery of confidently identified neo-epitopes, or provide assistance in the assessment of the presence of cryptic peptides, such as spliced peptides.