Nonspecific cleavages arising from reconstitution of trypsin under mildly acidic conditions

Qualification of a LC-HRMS platform method for biosimilar development using NISTmab as a model

Biosimilars are a cost-effective alternative to biopharmaceuticals, necessitating rigorous analytical methods for consistency and compliance. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is a versatile tool for assessing key attributes, encompassing molecular mass, primary structure, and post-translational modifications (PTMs). Adhering to ICH Q2R1, we validated an LC-HRMS based peptide mapping method using NISTmab as a reference. The method validation parameters, covering system suitability, specificity, accuracy, precision, robustness, and carryover, were comprehensively assessed. The method effectively differentiated the NISTmab from similar counterparts as well as from artificially introduced spiked conditions. Notably, the accuracy of mass error for NISTmab specific complementarity determining region peptides was within a maximum of 2.42 parts per million (ppm) from theoretical and the highest percent relative standard deviation (%RSD) observed for precision was 0.000219 %. It demonstrates precision in sequence coverage and PTM detection, with a visual inspection of total ion chromatogram approach for variability assessment. The method maintains robustness when subjected to diverse storage conditions, encompassing variations in column temperature and mobile phase composition. Negligible carryover was noted during the carryover analysis. In summary, this method serves as a versatile platform for multiple biosimilar development by effectively characterizing and identifying monoclonal antibodies, ultimately ensuring product quality.

Optimal conditions for carrying out trypsin digestions on complex proteomes: From bulk samples to single cells

To identify proteins by the bottom-up mass spectrometry workflow, enzymatic digestion is essential to break down proteins into smaller peptides amenable to both chromatographic separation and mass spectrometric analysis. Trypsin is the most extensively used protease due to its high cleavage specificity and generation of peptides with desirable positively charged N- and C-terminal amino acid residues that are amenable to reverse phase HPLC separation and MS/MS analyses. However, trypsin can yield variable digestion profiles and its protein cleavage activity is interdependent on trypsin source and quality, digestion time and temperature, pH, denaturant, trypsin and substrate concentrations, composition/complexity of the sample matrix, and other factors. There is therefore a need for a more standardized, general-purpose trypsin digestion protocol. Based on a review of the literature we delineate optimal conditions for carrying out trypsin digestions of complex proteomes from bulk samples to limiting amounts of protein extracts. Furthermore, we highlight recent developments and technological advances used in digestion protocols to quantify complex proteomes from single cells. SIGNIFICANCE: Currently, bottom-up MS-based proteomics is the method of choice for global proteome analysis. Since trypsin is the most utilized protease in bottom-up MS proteomics, delineating optimal conditions for carrying out trypsin digestions of complex proteomes in samples ranging from tissues to single cells should positively impact a broad range of biomedical research.

Mass Spectrometry Analysis on the Breakage of Allergens in High-Molecular-Mass Polymer of Roasted Peanuts

Peanut allergy is a prevalent and concerning food allergy. Roasting can introduce structural changes to peanut allergens, affecting their allergenicity, but the structure on the primary structure is unclear. Here, the breakage sites were identified by mass spectrometry and software tools, and structural changes were simulated by molecular dynamics and displayed by PyMOL software. Results revealed that the appearance frequencies of L, Q, F, and E were high at the N-terminal of the breakage site, while S and E were dominant at the C-terminal. In the conformational structure, breakage sites were found close to disulfide bonds and the Cupin domains of Ara h 1 and Ara h 3. The breakage of allergens destroyed linear epitopes and might change the conformation of epitopes, which could influence peanuts' potential allergenicity.

A rationally engineered small antimicrobial peptide with potent antibacterial activity

Antimicrobial resistance (AMR) is a silent pandemic declared by the WHO that requires urgent attention in the post-COVID world. AMR is a critical public health concern worldwide, potentially affecting people at different stages of life, including the veterinary and agriculture industries. Notably, very few new-age antimicrobial agents are in the current developmental pipeline. Thus, the design, discovery, and development of new antimicrobial agents are required to address the menace of AMR. Antimicrobial peptides (AMPs) are an important class of antimicrobial agents for combating AMR due to their broad-spectrum activity and ability to evade AMR through a multimodal mechanism of action. However, molecular size, aggregability, proteolytic degradation, cytotoxicity, and hemolysis activity significantly limit the clinical application of natural AMPs. The de novo design and engineering of a short synthetic amphipathic AMP (≤16 aa, Mol. Wt. ≤ 2 kDa) with an unusual architecture comprised of coded and noncoded amino acids (NCAAs) is presented here, which demonstrates potent antibacterial activity against a few selected bacterial strains mentioned in the WHO priority list. The designer AMP is conformationally ordered in solution and effectively permeabilizes the outer and inner membranes, leading to bacterial growth inhibition and death. Additionally, the peptide is resistant to proteolysis and has negligible cytotoxicity and hemolysis activity up to 150 μM toward cultured human cell lines and erythrocytes. The designer AMP is unique and appears to be a potent therapeutic candidate, which can be subsequently subjected to preclinical studies to explicitly understand and address the menace of AMR.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

Assessing the Role of Trypsin in Quantitative Plasma and Single-Cell Proteomics toward Clinical Application

Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large-scale biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa cell lysate, human plasma, and single HEK293 cells, which were analyzed over a range of selected reaction monitoring (SRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) instrument methods on three LC-MS instruments. The quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive data set, we report variations between commercial trypsins, their source, and their concentration. Furthermore, we provide suggestions on the handling of trypsin in large-scale studies.

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

Embedding Dynamics in Intrinsic Physicochemical Profiles of Market-Stage Antibody-Based Biotherapeutics

Adequate stability, manufacturability, and safety are crucial to bringing an antibody-based biotherapeutic to the market. Following the concept of holistic in silico developability, we introduce a physicochemical description of 91 market-stage antibody-based biotherapeutics based on orthogonal molecular properties of variable regions (Fvs) embedded in different simulation environments, mimicking conditions experienced by antibodies during manufacturing, formulation, and in vivo. In this work, the evaluation of molecular properties includes conformational flexibility of the Fvs using molecular dynamics (MD) simulations. The comparison between static homology models and simulations shows that MD significantly affects certain molecular descriptors like surface molecular patches. Moreover, the structural stability of a subset of Fv regions is linked to changes in their specific molecular interactions with ions in different experimental conditions. This is supported by the observation of differences in protein melting temperatures upon addition of NaCl. A DEvelopability Navigator In Silico (DENIS) is proposed to compare mAb candidates for their similarity with market-stage biotherapeutics in terms of physicochemical properties and conformational stability. Expanding on our previous developability guidelines (Ahmed et al. Proc. Natl. Acad. Sci. 2021, 118 (37), e2020577118), the hydrodynamic radius and the protein strand ratio are introduced as two additional descriptors that enable a more comprehensive in silico characterization of biotherapeutic drug candidates. Test cases show how this approach can facilitate identification and optimization of intrinsically developable lead candidates. DENIS represents an advanced computational tool to progress biotherapeutic drug candidates from discovery into early development by predicting drug properties in different aqueous environments.

Investigation of Tryptic Protein Digestion in Microdroplets and in Bulk Solution

Recent studies have shown that ultrafast enzymatic digestion of proteins can be achieved in microdroplet within 250 μs. Further investigation of peptides resulting from microdroplet digestion (MD) would be necessary to evaluate it as an alternative to the conventional bulk digestion for bottom-up and biotherapeutic protein characterization. Herein we examined and compared protein tryptic digestion in both MD and bulk solution. In the case of MD of β-lactoglobulin B, the preservation of long peptides was observed due to the short digestion time. In addition, MD is applicable to digest both high- and low-abundance proteins in mixture. In the case of digesting NIST 8671 mAb antibody containing a low level of commonly encountered host cell protein (HCP) PLBL2 (mAb:PLBL2 = 100:1 by weight), MD produced lower levels of digestion-induced chemical modifications of asparagine/glutamine deamidation, compared with overnight digestion. No significant difference between MD and bulk digestion was observed in terms of trypsin digestion specificity based on examination of semi- and unspecific-cleaved peptides. Our study suggests that MD, a fast digestion approach, could be adopted for bottom-up proteomics research and for peptide mapping of mAbs to characterize site-specific deamidation and glycosylation, for the purpose of development of biopharmaceuticals.

Elucidating chemical and disulfide heterogeneities in rituximab using reduced and non-reduced peptide mapping

Peptide mapping by liquid chromatography-mass spectrometry is the gold standard to characterize post-translational modifications and disulfide bonds. The structural integrity, heterogeneity, and quality of biotherapeutic proteins are evaluated via reduced and non-reduced peptide mapping methods. However, non-enzymatic artifacts are often induced during sample preparation when alkaline pH conditions are used. To minimize these artifacts, methods using various acidic pH conditions have been developed by multiple researchers. However, these may lead to missed and non-specific cleavages during the analysis. In this study, improved reduced and non-reduced peptide mapping method has been proposed to characterize endogenous chemical modifications and native disulfide bonds of monoclonal antibody -based products. Solubilization has been carried out at acidic pH conditions under high temperature, followed by the addition of tris (2-carboxyethyl) phosphine as a reducing agent and a low alkylating agent. It was observed that the non-enzymatic post-translational modifications and non-native disulfide scrambled peptides significantly reduced under trypsin plus Lys-C digestion conditions at acidic pH as compared to the traditional methods. The results demonstrate that the proposed peptide mapping method using trypsin plus Lys-C could identify and quantify various chemical and disulfide heterogeneities with minimal artifacts. This article is protected by copyright. All rights reserved.

SPACEPro: A Software Tool for Analysis of Protein Sample Cleavage for Tandem Mass Spectrometry

The efficiency of shotgun proteomic analysis is dependent on the reproducibility of the peptide cleavage process during sample preparation. To generate rapid and useful metrics for peptide cleavage efficiency, as in enzymatic or chemical cleavage, SPACEPro was developed to evaluate efficiency and reproducibility of protein cleavage in peptide samples following data-dependent analysis by mass spectrometry. SPACEPro analyzes samples at the peptide-spectrum match (PSM), peptide, and protein levels to provide a comprehensive representation of the overall sample processing to peptides. All output is provided in human-readable text and JSON files that can be further processed to assess the cleavage efficiency on proteins within the sample. SPACEPro provides a snapshot of the protein cleavage efficiency through very minimal effort so that the user is informed of the quality of the sample processing efficiency and can accordingly develop protocols to improve the initial sample preparation for subsequent analyses.

Fully automated peptide mapping multi-attribute method by liquid chromatography-mass spectrometry with robotic liquid handling system

The multi-attribute method (MAM) based on liquid chromatography (LC)-tandem mass spectrometry is emerging as a powerful tool to directly monitor multiple product quality attributes simultaneously. To better implement MAM, either for product characterization or for quality control (QC), there is a need for a robust, universal, and high-throughput workflow that can be broadly adopted in different laboratories with minimal barriers to implementation. Manual preparation of samples for MAM, however, is labor intensive and produces nontrivial variations across analysts and laboratories. We describe the development of a fully automated peptide mapping procedure with a high-throughput robotic liquid handling system to improve sample handling capacity and outcome reproducibility while saving analyst hands-on time. Our procedure features the automation of a "microdialysis" step, an efficient desalting approach prior to proteolytic digestion that optimizes digestion completeness and consistency each time. The workflow is completely hands-free and requires the analyst only to pre-normalize the sample concentrations and to load buffers and reagents at their designated positions on the robotic deck. The robotic liquid handler performs all the subsequent preparation steps and stores the digested samples on a chiller unit to await retrieval for further analysis. We also demonstrate that the manual and automated procedures are comparable with regard to protein sequence coverage, digestion completeness and consistency, and quantification of posttranslational modifications. Notably, in contrast to a previously reported automated sample preparation protocol that relied on customized accessories, all components in our automation procedure are commercial products that are readily available. In addition, we also present the high-throughput data analysis workflow by using Protein Metrics. The automation procedure can be applied cross-functionally in the biopharmaceutical industry and, given its practicality and reproducibility, can pave the way for MAM implementation in QC laboratories.