Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions

External validation of serum biomarkers predicting short-term and mid/long-term relapse in patients with Crohn's disease stopping infliximab

OBJECTIVE

In patients with Crohn's disease (CD) on combination therapy (infliximab and immunosuppressant) and stopping infliximab (cohort from the study of infliximab diSconTinuation in CrOhn's disease patients in stable Remission on combined therapy with Immunosuppressors (STORI)), the risk of short-term (≤6 months) and mid/long-term relapse (>6 months) was associated with distinct blood protein profiles. Our aim was to test the external validity of this finding in the SPARE cohort (A proSpective Randomized Controlled Trial comParing infliximAb-antimetabolites Combination Therapy to Anti-metabolites monotheRapy and Infliximab monothErapy in Crohn's Disease Patients in Sustained Steroid-free Remission on Combination Therapy).

DESIGN

In SPARE, patients with CD in sustained steroid-free clinical remission and on combination therapy were randomly allocated to three arms: continuing combination therapy, stopping infliximab or stopping immunosuppressant. In the baseline serum of the STORI and SPARE (arm stopping infliximab) cohorts, we studied 202 immune-related proteins. The proteins associated with time to relapse (univariable Cox model) were compared between STORI and SPARE. The discriminative ability of biomarkers (individually and combined in pairs) was evaluated by the c-statistic (concordance analysis) which was compared with C-reactive protein (CRP), faecal calprotectin and a previously validated model (CEASE).

RESULTS

In STORI and SPARE, distinct blood protein profiles were associated with the risk of short-term (eg, high level: CRP, haptoglobin, interleukin-6, C-type lectin domain family 4 member C) and mid/long-term relapse (eg, low level: Fms-related tyrosine kinase 3 ligand, kallistatin, fibroblast growth factor 2). At external validation, the top 10 biomarker pairs showed a higher c-statistic than the CEASE model, CRP and faecal calprotectin in predicting short-term (0.76-0.80 vs 0.74 vs 0.71 vs 0.69, respectively) and mid/long-term relapse (0.66-0.68 vs 0.61 vs 0.52 vs 0.59, respectively).

CONCLUSION

In patients with CD stopping infliximab, we confirm that the risk of short-term and mid/long-term relapse is associated with distinct blood protein profiles showing the potential to guide infliximab withdrawal.

TRIAL REGISTRATION NUMBER

NCT00571337 and NCT02177071.

Small molecule modulation of protein corona for deep plasma proteome profiling

The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

Evaluation of Serum Proteome Sample Preparation Methods to Support Clinical Proteomics Applications

Serum contains several proteins that are associated with disease-related processes. Mass spectrometry (MS)-based proteomics approaches greatly facilitate serum protein biomarker development. However, the serum proteome complexity presents a technical challenge for the accurate, sensitive, and reproducible quantification of proteins by MS. Thus, efficient sample preparation methods are of critical importance for serum proteome analyses. In this study, we evaluated the technical performance of two serum proteome sample preparation methods using sera from patients with high-grade serous ovarian cancer and patients with benign nongynecological conditions with a goal of providing insight into their compatibility with clinical proteomics workflows. One method entailed the use of immobilized trypsin (SMART Digest Trypsin) with RapiGest SF, an acid-labile surfactant designed to enhance the in-solution enzymatic digestion of proteins. The other method incorporated a commercially available sample preparation kit, iST-BCT, which contains standardized reagents. Significantly higher protein sequence coverage, albeit with lower digestion efficiency, was obtained with the immobilized trypsin + RapiGest SF workflow, whereas the iST-BCT workflow was quicker and had marginally better reproducibility. Protein relative abundance analysis revealed that the serum proteomes clustered primarily by the sample processing workflow and secondarily by disease state. We conducted a time course study to determine whether differences in the relative abundance of diagnostic high-grade serous ovarian cancer serum protein biomarker candidates were biased according to the duration of enzymatic digestion. Our results highlight the importance of optimizing enzymatic digestion kinetics according to the peptide targets of interest while considering the sensitivity of the downstream analytical method utilized in clinical proteomics workflows designed to measure biomarkers.

Mass spectrometry-based proteomics for source-level attribution after DNA extraction

Biological traces recovered from crime scenes serve as vital evidence in forensic investigations. While DNA evidence is frequently used to address the sub-source level of the hierarchy of propositions, the biological source of the DNA can be highly probative at the source level. Current body fluid detection methods pose certain limitations, such as reports of false positive results from some of the presumptive and/or confirmatory tests in current use. These tests are also individual tests for the detection of one body fluid, meaning that if the sample is suspected to be a mixture of multiple body fluids, then different tests would need to be conducted to confirm the body fluid(s) present, which may exhaust small amounts of available biological trace. Proteomics applications for the identification of body fluids have been previously explored, and potential biomarkers indicative of body fluids discovered from liquid-chromatography tandem mass spectrometry (LC-MS/MS) methods have been reported. This work focuses on developing a mass spectrometry-based proteomics approach for the identification of body fluids by targeting discriminating peptide biomarkers from the non-DNA component left over after DNA extraction of samples. The non-DNA component is typically a waste product but with unappreciated evidential value. Our methodology for the purification of proteins from the post-DNA extraction waste includes an acetone precipitation and single-pot solid-phase-enhanced sample preparation (SP3) technique, microwave-assisted trypsin digestion, and LC-MS/MS analysis of the resultant peptides. Preliminary results from this proof-of-concept study include a list of potentially discriminating proteins and peptides for blood, saliva, and semen developed from the analysis of post-DNA extraction waste. Our method allows for multiple analytes to be targeted simultaneously from a DNA profiling waste stream and we anticipate that it could eventually be incorporated into standard forensic laboratory workflows.

LC-SRM Combined With Machine Learning Enables Fast Identification and Quantification of Bacterial Pathogens in Urinary Tract Infections

Urinary tract infections (UTIs) are a worldwide health problem. Fast and accurate detection of bacterial infection is essential to provide appropriate antibiotherapy to patients and to avoid the emergence of drug-resistant pathogens. While the gold standard requires 24 h to 48 h of bacteria culture prior to MALDI-TOF species identification, we propose a culture-free workflow, enabling bacterial identification and quantification in less than 4 h using 1 ml of urine. After rapid and automatable sample preparation, a signature of 82 bacterial peptides, defined by machine learning, was monitored in LC-MS, to distinguish the 15 species causing 84% of the UTIs. The combination of the sensitivity of the SRM mode on a triple quadrupole TSQ Altis instrument and the robustness of capillary flow enabled us to analyze up to 75 samples per day, with 99.2% accuracy on bacterial inoculations of healthy urines. We have also shown our method can be used to quantify the spread of the infection, from 8 × 104 to 3 × 107 CFU/ml. Finally, the workflow was validated on 45 inoculated urines and on 84 UTI-positive urine from patients, with respectively 93.3% and 87.1% of agreement with the culture-MALDI procedure at a level above 1 × 105 CFU/ml corresponding to an infection requiring antibiotherapy.

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Absolute quantification of viral proteins from pseudotyped VSV-GP using UPLC-MRM

The rapidly developing field of oncolytic virus (OV) therapy necessitates the development of new and improved analytical approaches for the characterization of the virus during production and development. Accurate monitoring and absolute quantification of viral proteins are crucial for OV product characterization and can facilitate the understanding of infection, immunogenicity, and development stages of viral replication. Targeted mass spectrometry methods like multiple reaction monitoring (MRM) offer a robust way to directly detect and quantify specific targeted proteins represented by surrogate peptides. We have leveraged the power of MRM by combining ultra-high performance liquid chromatography (UPLC) with a Sciex 6500 triple-stage quadrupole mass spectrometer to develop an assay that accurately and absolutely quantifies the structural proteins of a pseudotyped vesicular stomatitis virus (VSV) intended for use as a new biotherapeutic (designated hereafter as VSV-GP to differentiate it from native VSV). The new UPLC-MRM method provides absolute quantification with the use of heavy-labeled reference standard surrogate peptides. When added in known exact amounts to standards and samples, the reference standards normalize and account for any small perturbations during sample preparation and/or instrument performance, resulting in accurate and precise quantification. Because of the multiplexed nature of MRM, all targeted proteins are quantified at the same time. The optimized assay has been enhanced to quantify the ratios of the processed GP1 and GP2 proteins while simultaneously measuring any remaining or unprocessed form of the envelope protein GP complex (GPC; full-length GPC).

IMPORTANCE

The development of oncolytic viral therapy has gained considerable momentum in recent years. Vesicular stomatitis virus glycoprotein (VSV-GP) is a new biotherapeutic emerging in the oncolytic viral therapy platform. Novel analytical assays that can accurately and precisely quantify the viral proteins are a necessity for the successful development of viral vector as a biotherapeutic. We developed an ultra-high performance liquid chromatography multiple reaction monitoring-based assay to quantify the absolute concentrations of the different structural proteins of VSV-GP. The complete processing of GP complex (GPC) is a prerequisite for the infectivity of the virus. The assay extends the potential for quantifying full-length GPC, which provides an understanding of the processing of GPC (along with the quantification of GP1 and GP2 separately). We used this assay in tracking GPC processing in HEK-293-F production cell lines infected with VSV-GP.

Molecular beacon-peptide probe based double recycling amplification for multiplexed detection of serum exosomal microRNAs

Exosomal microRNAs (exomiRs) have been shown to play crucial roles as biomarkers for early detection and prognosis of cancer. However, simultaneous quantification of multiplex exomiRs is hindered by methods that require additional steps, such as labeling with fluorophores or gel visualization, which are susceptible to various factors. Herein, we developed a mass spectrometry-detectable and target-triggered method for multiplexed exomiR detection using three enzyme-based double recycling amplification in combination with well-designed molecular beacon-peptide (MBP) probes, called molecular beacon-peptide probe-based double recycling amplification (MBPDRA). MBP probes mediated the double recycling amplification reaction and were released as mass-detectable reporter peptides. In particular, the hybridization of the target microRNAs (miRNAs) with the stem-loop of the probe triggers two consecutive processes. The first cycle involved polymerase strand displacement amplification, leading to the production of complementary DNA (cycle I), and the second cycle encompassed the recycling exonuclease cleavage of the MBP probe (cycle II). Subsequently, excess probes were removed by interaction with streptavidin beads via biotin-streptavidin binding. The reporter peptides were released using trypsin and subsequently detected by mass spectrometry. Our method enables quantitative detection of multiple exomiRs with a dynamic range from 0.1 fM to 10 pM and a limit of quantification of 0.1 fM. Moreover, the proposed assay was successfully employed for quantification of three exomiRs, exmiR-21, exmiR-191, and exmiR-451a, in the sera of patients with pancreatic cancer. Based on these findings, we believe that the MBPDRA assay holds significant promise as a reliable method for quantifying multiple miRNAs in biomedical research and clinical diagnostics.

Identification of Acyl-Protein Thioesterase-1 as a Polysorbate-Degrading Host Cell Protein in a Monoclonal Antibody Formulation Using Activity-Based Protein Profiling

Polysorbate (PS) degradation in monoclonal antibody (mAb) formulations poses a significant challenge in the biopharmaceutical industry. PS maintains protein stability during drug product's shelf life but is vulnerable to breakdown by low-abundance residual host cell proteins (HCPs), particularly hydrolytic enzymes such as lipases and esterases. In this study, we used activity-based protein profiling (ABPP) coupled with mass spectrometry to identify acyl-protein thioesterase-1 (APT-1) as a polysorbate-degrading HCP in one case of mAb formulation with stability problems. We validated the role of APT1 by matching the polysorbate degradation fingerprint in the mAb formulation with that of a recombinant APT1 protein. Furthermore, we found an agreement between APT1 levels and PS degradation rates in the mAb formulation, and we successfully halted PS degradation using APT1-specific inhibitors ML348 and ML211. APT1 was found to co-purify with a specific mAb via hitchhiking mechanism. Our work provides a streamlined approach to identifying critical HCPs in PS degradation, supporting quality-by-design principles in pharmaceutical development.

Machine learning and 4D-LFQ quantitative proteomic analysis explore the molecular mechanism of kidney stone formation

Background

Nephrolithiasis, a common and chronic urological condition, exerts significant pressure on both the general public and society as a whole. The precise mechanisms of nephrolith formation remain inadequately comprehended. Nevertheless, the utilization of proteomics methods has not been employed to examine the development of renal calculi in order to efficiently hinder and manage the creation and reappearance of nephrolith. Nowadays, with the rapid development of proteomics techniques, more efficient and more accurate proteomics technique is utilized to uncover the mechanisms underlying diseases. The objective of this study was to investigate the possible alterations of HK-2 cells when exposed to varying amounts of calcium oxalate (CaOx). The aim was to understand the precise development of stone formation and recurrence, in order to find effective preventive and treatment methods.

Methods

To provide a complete view of the proteins involved in the development of nephrolithiasis, we utilized an innovative proteomics method called 4D-LFQ proteomic quantitative techniques. HK-2 cells were selected as our experimental subjects. Three groups (n = 3) of HK-2 cells were treated with intervention solutions containing 0 (negative control, NC), 1 mM, and 2 mM CaOx, respectively. For the proteins that showed differential expression, various analyses were conducted including examination of Gene Ontology (GO), Clusters of Orthologous Groups of proteins (KOG), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, enrichment analysis of protein domains, and hierarchical clustering analysis. The STRING database was used to identify the interaction network of the chosen proteins. Candidate proteins were validated using parallel reaction monitoring (PRM) in the end.

Results

All three groups verified the repeatability of samples. According to the results of 4D-LFQ proteomic quantitative analysis, there were 120, 262, and 81 differentially expressed proteins (DEPs) in the 1 mM-VS-NC, 2 mM-VS-NC, and 2 mM-VS-1mM conditions, respectively. According to GO annotation, the functional enrichment analysis indicates that the differentially expressed proteins (DEPs) were notably enriched in promoting cell migration and the extracellular matrix, among other functions. Analysis of enrichment, based on the KEGG pathway, revealed significant enrichment of DEPs in complement and coagulation cascades, as well as in ECM-receptor (extracellular matrix-receptor) interaction and other related pathways. 14 DEPs of great interest were selected as candidate proteins, including FN1, TFRC, ITGA3, FBN1, HYOU1, SPP1, HSPA5, COL6A1, MANF, HIP1R, JUP, AXL, CTNNB1 and DSG2.The data from PRM demonstrated the variation trend of 14 DEPs was identical as 4D-LFQ proteomic quantitative analysis.

Conclusion

Proteomics studies of CaOx-induced HK-2 cells using 4D-LFQ proteomic quantitative analysis and PRM may help to provide crucial potential target proteins and signaling pathways for elucidating the mechanism of nephrolithiasis and better treating nephrolithiasis.

Quantitative Measurement of Rate of Targeted Protein Degradation

Targeted protein degradation (TPD) is a therapeutic approach that leverages the cell's natural machinery to degrade targets instead of inhibiting them. This is accomplished by using mono- or bifunctional small molecules designed to induce the proximity of target proteins and E3 ubiquitin ligases, leading to ubiquitination and subsequent proteasome-dependent degradation of the target. One of the most significant attributes of the TPD approach is its proposed catalytic mechanism of action, which permits substoichiometric exposure to achieve the desired pharmacological effects. However, apart from one in vitro study, studies supporting the catalytic mechanism of degraders are largely inferred based on potency. A more comprehensive understanding of the degrader catalytic mechanism of action can help aspects of compound development. To address this knowledge gap, we developed a workflow for the quantitative measurement of the catalytic rate of degraders in cells. Comparing a selective and promiscuous BTK degrader, we demonstrate that both compounds function as efficient catalysts of BTK degradation, with the promiscuous degrader exhibiting faster rates due to its ability to induce more favorable ternary complexes. By leveraging computational modeling, we show that the catalytic rate is highly dynamic as the target is depleted from cells. Further investigation of the promiscuous kinase degrader revealed that the catalytic rate is a better predictor of optimal degrader activity toward a specific target compared to degradation magnitude alone. In summary, we present a versatile method for mapping the catalytic activity of any degrader for TPD in cells.

Quantitative Analysis of Complement Membrane Attack Complex Proteins Associated with Extracellular Vesicles

Extracellular vesicles (EVs) represent a universal mechanism of intercellular communication in normal and pathological conditions. There are reports showing the presence of complement proteins in EV preparations, specifically those that can form a membrane attack complex (MAC). In the present work, we have used a quantitative mass spectrometry method that allows for the measurement of multiple targeted proteins in one experimental run. The quantification of MAC-forming proteins, namely C5b, C6, C7, C8, and C9, in highly purified EVs from normal human plasma revealed the presence of MAC proteins at approximately equal stoichiometry that does not fit the expected stoichiometry of preformed MAC. We concluded that while MAC proteins can be associated with EVs from normal plasma and presumably can be delivered to the recipient cells, there is no evidence that the EVs carry preformed MAC.

Standards-Free Absolute Quantitation of Oxidizable Glycopeptides by Coulometric Mass Spectrometry

Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(β-GlcNAc)TGNL-OH and NYSVPSS(β-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

Serum proteome signatures associated with ileal and colonic ulcers in Crohn's disease

At a clinical level, ileal and colonic Crohn's disease (CD) are considered as separate entities. These subphenotypes need to be better supported by biological data to develop personalised medicine in CD. To this end, we combined different technologies (proximity extension assay, selected reaction monitoring, and high-sensitivity turbidimetric immunoassay (hsCRP)) to measure 207 immune-related serum proteins in CD patients presenting no endoscopic lesions (endoscopic remission) (n = 23), isolated ileal ulcers (n = 17), or isolated colonic ulcers (n = 16). We showed that isolated ileal ulcers and isolated colonic ulcers were specifically associated with 6 and 18 serum proteins, respectively: (high level: JUN, CNTNAP2; low level: FCRL6, LTA, CLEC4A, NTF4); (high level: hsCRP, IL6, APCS, CFB, MBL2, IL7, IL17A, CCL19, CXCL10, CSF3, IL10, CLEC4G, MMP12, VEGFA; low level: CLEC3B, GSN, TNFSF12, TPSAB1). Isolated ileal ulcers and isolated colonic ulcers were detected by hsCRP with an area under the receiver operating characteristics curve of 0.64 (p-value = 0.07) and 0.77 (p-value = 0.001), respectively. We highlighted distinct serum proteome profiles associated with ileal and colonic ulcers in CD, this finding might support the development of therapeutics and biomarkers tailored to disease location. SIGNIFICANCE: Although ileal and colonic Crohn's disease present important clinical differences (eg, progression, response to treatment and reliability of biomarkers), these two entities are managed with the same therapeutic strategy. The biological specificities of ileal and colonic Crohn's disease need to be better characterised to develop more personalised approaches. The present study used robust technologies (selected reaction monitoring, proximity extension assays and turbidimetric immunoassay) to quantify precisely 207 serum immune-related proteins in three groups of Crohn's disease patients presenting: 1) no endoscopic lesions (endoscopic remission) (n = 23); 2) isolated ileal ulcers (n = 17); 3) isolated colonic ulcers (n = 16). We found distinct serum proteome signatures associated with ileal and colonic ulcers. Our findings could foster the development of biomarkers and treatments tailored to Crohn's disease location.

Wideband PRM: Highly Accurate and Sensitive Method for High-Throughput Targeted Proteomics

Targeted mass spectrometry (MS) approaches, which are powerful methods for uniquely and confidently quantifying a specific panel of proteins in complex biological samples, play a crucial role in validating and clinically translating protein biomarkers discovered through global proteomic profiling. Common targeted MS methods, such as multiple reaction monitoring (MRM) and parallel-reaction monitoring (PRM), employ specific mass spectrometric technologies to quantify protein levels by comparing the transitions of surrogate endogenous (ENDO) peptides with those of stable isotope-labeled (SIL) peptide counterparts. These methods utilizing amino acid analyzed (AAA) SIL peptides warrant sensitive and precise measurements required for targeted MS assays. Compared with MRM, PRM provides higher experimental throughput by simultaneously acquiring all transitions of the target peptides and thereby compensates for different ion suppressions among transitions of a target peptide. However, PRM still suffers different ion suppressions between ENDO and SIL peptides due to spray instability, as the ENDO and SIL peptides were monitored at different liquid chromatography (LC) retention times. Here we introduce a new targeted MS method, termed wideband PRM (WBPRM), that is designed for high-throughput targeted MS analysis. WBPRM employs a wide isolation window for simultaneous fragmentation of both ENDO and SIL peptides along with multiplexed single ion monitoring (SIM) scans for enhanced MS sensitivity of the target peptides. Compared with PRM, WBPRM was demonstrated to provide increased sensitivity, precision, and reproducibility of quantitative measurements of target peptides with increased throughput, allowing more target peptide measurements in a shortened experiment time. WBPRM is a straightforward adaptation to a manufacturer-provided MS method, making it an easily implementable technique, particularly in complex biological samples where the demand for higher precision, sensitivity, and efficiency is paramount.

Characterization of an expanded set of assays for immunomodulatory proteins using targeted mass spectrometry

Immunotherapies are revolutionizing cancer care, but many patients do not achieve durable responses and immune-related adverse events are difficult to predict. Quantifying the hundreds of proteins involved in cancer immunity has the potential to provide biomarkers to monitor and predict tumor response. We previously developed robust, multiplexed quantitative assays for immunomodulatory proteins using targeted mass spectrometry, providing measurements that can be performed reproducibly and harmonized across laboratories. Here, we expand upon those efforts in presenting data from a multiplexed immuno-oncology (IO)-3 assay panel targeting 43 peptides representing 39 immune- and inflammation-related proteins. A suite of novel monoclonal antibodies was generated as assay reagents, and the fully characterized antibodies are made available as a resource to the community. The publicly available dataset contains complete characterization of the assay performance, as well as the mass spectrometer parameters and reagent information necessary for implementation of the assay. Quantification of the proteins will provide benefit to correlative studies in clinical trials, identification of new biomarkers, and improve understanding of the immune response in cancer.

High-throughput Proteomics-Guided Biomarker Discovery of Hepatocellular Carcinoma

Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes.

Integrated Platform for Large-Scale Quantitative Profiling of Phosphotyrosine Signaling Complexes Based on Cofractionation/Mass Spectrometry and Complex-Centric Algorithm

The scarcity and dynamic nature of phosphotyrosine (pTyr)-modified proteins pose a challenge for researching protein complexes with pTyr modification, which are assembled through multiple protein-protein interactions. We developed an integrated complex-centric platform for large-scale quantitative profiling of pTyr signaling complexes based on cofractionation/mass spectrometry (CoFrac-MS) and a complex-centric algorithm. We initially constructed a trifunctional probe based on pTyr superbinder (SH2-S) for specifically binding and isolation of intact pTyr protein complexes. Then, the CoFrac-MS strategy was employed for the identification of pTyr protein complexes by integrating ion exchange chromatography in conjunction with data independent acquisition mass spectrometry. Furthermore, we developed a novel complex-centric algorithm for quantifying protein complexes based on the protein complex elution curve. Utilizing this algorithm, we effectively quantified 216 putative protein complexes. We further screened 21 regulated pTyr protein complexes related to the epidermal growth factor signal. Our study engenders a comprehensive framework for the intricate examination of pTyr protein complexes and presents, for the foremost occasion, a quantitative landscape delineating the composition of pTyr protein complexes in HeLa cells.

Rapid Screening of New Psychoactive Substances Using pDART-QqQ-MS

Drug abuse is a severe social problem worldwide. Particularly, the issue of new psychoactive substances (NPSs) have increasingly emerged. NPSs are structural or functional analogs of traditional illicit drugs, such as cocaine, cannabis, and amphetamine; these molecules provide the same or more severe neurological effects. Usually, immunoassays are utilized in the preliminary screening method. However, NPSs have poor detectability in commercially available immunoassay kits. Meanwhile, various chromatography combined with the mass spectrometry platform have been developed to quantify NPSs. Still, a significant amount of time and resources are required during these procedures. Therefore, we established a rapid analytical platform for NPSs employing paper-loaded direct analysis in real time triple quadrupole mass spectrometry (pDART-QqQ-MS). We implemented this platform for the semiquantitative analysis of forensic drug tests in urine. This platform significantly shrinks the analytical time of a single sample within 30 s and requires a low volume of the specimen. The platform can detect 21 NPSs in urine mixtures at a lower limit of qualification of concentration ranging from 20 to 75 nanograms per milliliter (ng mL-1) and is lower than the cutoff value of currently available immune-based devices for detecting multiple drugs (1000 ng mL-1). Urine samples from drug addicts have been collected to verify the platform's effectiveness. By combining efficiency and accuracy, our platform offers a promising solution for addressing the challenges posed by NPSs in drug abuse detection.

Fatty Acid Synthase as Interacting Anticancer Target of the Terpenoid Myrianthic Acid Disclosed by MS-Based Proteomics Approaches

This research focuses on the target deconvolution of the natural compound myrianthic acid, a triterpenoid characterized by an ursane skeleton isolated from the roots of Myrianthus arboreus and from Oenothera maritima Nutt. (Onagraceae), using MS-based chemical proteomic techniques. Application of drug affinity responsive target stability (DARTS) and targeted-limited proteolysis coupled to mass spectrometry (t-LiP-MS) led to the identification of the enzyme fatty acid synthase (FAS) as an interesting macromolecular counterpart of myrianthic acid. This result, confirmed by comparison with the natural ursolic acid, was thoroughly investigated and validated in silico by molecular docking, which gave a precise picture of the interactions in the MA/FAS complex. Moreover, biological assays showcased the inhibitory activity of myrianthic acid against the FAS enzyme, most likely related to its antiproliferative activity towards tumor cells. Given the significance of FAS in specific pathologies, especially cancer, the myrianthic acid structural moieties could serve as a promising reference point to start the potential development of innovative approaches in therapy.

PPARα Agonism Enhances Immune Response to Radiotherapy While Dietary Oleic Acid Results in Counteraction

PURPOSE

Head and neck cancer (HNC) improvements are stagnant, even with advances in immunotherapy. Our previous clinical trial data show that altered fatty acid (FA) metabolism correlates with outcome. We hypothesized that pharmacologic and dietary modulation of FA catabolism will affect therapeutic efficacy.

EXPERIMENTAL DESIGN

We performed in vivo and in vitro experiments using PPARα agonism with fenofibrate (FF) or high oleic acid diets (OAD) with radiotherapy, generating metabolomic, proteomic, stable isotope tracing, extracellular flux analysis, and flow-cytometric data to investigate these alterations.

RESULTS

FF improved antitumor efficacy of high dose per fraction radiotherapy in HNC murine models, whereas the OAD reversed this effect. FF-treated mice on the control diet had evidence of increased FA catabolism. Stable isotope tracing showed less glycolytic utilization by ex vivo CD8+ T cells. Improved efficacy correlated with intratumoral alterations in eicosanoid metabolism and downregulated mTOR and CD36.

CONCLUSIONS

Metabolic intervention with increased FA catabolism improves the efficacy of HNC therapy and enhances antitumoral immune response.

Applicability of selected reaction monitoring for precise screening tests

INTRODUCTION

The proactive identification of diseases through screening tests has long been endorsed as a means to preempt symptomatic onset. However, such screening endeavors are fraught with complications, such as diagnostic inaccuracies, procedural risks, and patient unease during examinations. These challenges are amplified when screenings for multiple diseases are administered concurrently. Selected Reaction Monitoring (SRM) offers a unique advantage, allowing for the high-throughput quantification of hundreds of analytes with minimal interferences.

AREAS COVERED

Our research posits that SRM-based assays, traditionally tailored for single-disease biomarker profiling, can be repurposed for multi-disease screening. This innovative approach has the potential to substantially alleviate time, labor, and cost demands on healthcare systems and patients alike. Nonetheless, there are formidable methodological hurdles to overcome. These include difficulties in detecting low-abundance proteins and the risk of model overfitting due to the multiple functionalities of single proteins across different disease spectrums - issues especially pertinent in blood-based assays where detection sensitivity is constrained. As we move forward, technological strides in sample preparation, online extraction, throughput, and automation are expected to ameliorate these limitations.

EXPERT OPINION

The maturation of mass spectrometry's integration into clinical laboratories appears imminent, positioning it as an invaluable asset for delivering highly sensitive, reproducible, and precise diagnostic results.

Novel insights into small open reading frame-encoded micropeptides in hepatocellular carcinoma: A potential breakthrough

Traditionally, non-coding RNAs (ncRNAs) are regarded as a class of RNA transcripts that lack encoding capability; however, advancements in technology have revealed that some ncRNAs contain small open reading frames (sORFs) that are capable of encoding micropeptides of approximately 150 amino acids in length. sORF-encoded micropeptides (SEPs) have emerged as intriguing entities in hepatocellular carcinoma (HCC) research, shedding light on this previously unexplored realm. Recent studies have highlighted the regulatory functions of SEPs in the occurrence and progression of HCC. Some SEPs exhibit inhibitory effects on HCC, but others facilitate its development. This discovery has revolutionized the landscape of HCC research and clinical management. Here, we introduce the concept and characteristics of SEPs, summarize their associations with HCC, and elucidate their carcinogenic mechanisms in HCC metabolism, signaling pathways, cell proliferation, and metastasis. In addition, we propose a step-by-step workflow for the investigation of HCC-associated SEPs. Lastly, we discuss the challenges and prospects of applying SEPs in the diagnosis and treatment of HCC. This review aims to facilitate the discovery, optimization, and clinical application of HCC-related SEPs, inspiring the development of early diagnostic, individualized, and precision therapeutic strategies for HCC.

SWATH-MS as a strategy for CHO host cell protein identification and quantification supporting the characterization of mAb purification platforms

Host cell proteins (HCPs) are process-related impurities expressed by the host cells during biotherapeutics' manufacturing, such as monoclonal antibodies (mAbs). Some challenging HCPs evade clearance during the downstream processing and can be co-purified with the molecule of interest, which may impact product stability, efficacy, and safety. Therefore, HCP content is a critical quality attribute to monitor and quantify across the bioprocess. Here we explored a mass spectrometry (MS)-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, as an orthogonal method to traditional ELISA. The SWATH workflow was applied for high-throughput individual HCP identification and quantification, supporting characterization of a mAb purification platform. The design space of HCP clearance of two polishing resins was evaluated through a design of experiment study. Absolute quantification of high-risk HCPs was achieved (reaching 1.8 and 4.2 ppm limits of quantification, for HCP A and B respectively) using HCP-specific synthetic heavy labeled peptide calibration curves. Profiling of other HCPs was also possible using an average calibration curve (using labeled peptides from different HCPs). The SWATH approach is a powerful tool for HCP assessment during bioprocess development enabling simultaneous monitoring and quantification of different individual HCPs and improving process understanding of their clearance.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Absolute quantitation of human wild-type DNAI1 protein in lung tissue using a nanoLC-PRM-MS-based targeted proteomics approach coupled with immunoprecipitation

BACKGROUND

Dynein axonemal intermediate chain 1 protein (DNAI1) plays an essential role in cilia structure and function, while its mutations lead to primary ciliary dyskinesia (PCD). Accurate quantitation of DNAI1 in lung tissue is crucial for comprehensive understanding of its involvement in PCD, as well as for developing the potential PCD therapies. However, the current protein quantitation method is not sensitive enough to detect the endogenous level of DNAI1 in complex biological matrix such as lung tissue.

METHODS

In this study, a quantitative method combining immunoprecipitation with nanoLC-MS/MS was developed to measure the expression level of human wild-type (WT) DNAI1 protein in lung tissue. To our understanding, it is the first immunoprecipitation (IP)-MS based method for absolute quantitation of DNAI1 protein in lung tissue. The DNAI1 quantitation was achieved through constructing a standard curve with recombinant human WT DNAI1 protein spiked into lung tissue matrix.

RESULTS

This method was qualified with high sensitivity and accuracy. The lower limit of quantitation of human DNAI1 was 4 pg/mg tissue. This assay was successfully applied to determine the endogenous level of WT DNAI1 in human lung tissue.

CONCLUSIONS

The results clearly demonstrate that the developed assay can accurately quantitate low-abundance WT DNAI1 protein in human lung tissue with high sensitivity, indicating its high potential use in the drug development for DNAI1 mutation-caused PCD therapy.

Identification of Mortalin as the Main Interactor of Mycalin A, a Poly-Brominated C-15 Acetogenin Sponge Metabolite, by MS-Based Proteomics

Mycalin A (MA) is a polybrominated C-15 acetogenin isolated from the marine sponge Mycale rotalis. Since this substance displays a strong antiproliferative bioactivity towards some tumour cells, we have now directed our studies towards the elucidation of the MA interactome through functional proteomic approaches, (DARTS and t-LIP-MS). DARTS experiments were performed on Hela cell lysates with the purpose of identifying MA main target protein(s); t-LiP-MS was then applied for an in-depth investigation of the MA-target protein interaction. Both these techniques exploit limited proteolysis coupled with MS analysis. To corroborate LiP data, molecular docking studies were performed on the complexes. Finally, biological and SPR analysis were conducted to explore the effect of the binding. Mortalin (GRP75) was identified as the MA's main interactor. This protein belongs to the Hsp70 family and has garnered significant attention due to its involvement in certain forms of cancer. Specifically, its overexpression in cancer cells appears to hinder the pro-apoptotic function of p53, one of its client proteins, because it becomes sequestered in the cytoplasm. Our research, therefore, has been focused on the possibility that MA might prevent this sequestration, promoting the re-localization of p53 to the nucleus and facilitating the apoptosis of tumor cells.

Targeted Proteomics Reveals Quantitative Differences in Low-Abundance Glycosyltransferases of Patients with Congenital Disorders of Glycosylation

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware.

A label free chemoproteomic-based platform to disclose cannabidiol molecular mechanism of action on chronic myelogenous leukemia cancer cells

The discovery of the interactome of cannabidiol (CBD), a non-psychoactive cannabinoid from Cannabis sativa L., has been here performed on chronic myelogenous leukemia cancer cells, using an optimized chemo-proteomic stage, which links Drug Affinity Responsive Target Stability with Limited Proteolysis Multiple Reaction Monitoring approaches. The obtained results showed the ability of CBD to target simultaneously some potential protein partners, corroborating its well-known poly-pharmacology activity. In human chronic myelogenous leukemia K562 cancer cells, the most fascinating protein partner was identified as the 116 kDa U5 small nuclear ribonucleoprotein element called EFTUD2, which fits with the spliceosome complex. The binding mode of this oncogenic protein with CBD was clarified using mass spectrometry-based and in silico analysis.

Chemoproteomics Reveals USP5 (Ubiquitin Carboxyl-Terminal Hydrolase 5) as Promising Target of the Marine Polyketide Gracilioether A

Mass spectrometry-based chemical proteomic approaches using limited proteolysis have become a powerful tool for the identification and analysis of the interactions between a small molecule (SM) and its protein target(s). Gracilioether A (GeA) is a polyketide isolated from a marine sponge, for which we aimed to trace the interactome using this strategy. DARTS (Drug Affinity Responsive Target Stability) and t-LiP-MS (targeted-Limited Proteolysis-Mass Spectrometry) represented the main techniques used in this study. DARTS was applied on HeLa cell lysate for the identification of the GeA target proteins, and t-LiP-MS was employed to investigate the protein's regions involved in the binding with GeA. The results were complemented through the use of binding studies using Surface Plasmon Resonance (SPR) and in silico molecular docking experiments. Ubiquitin carboxyl-terminal hydrolase 5 (USP5) was identified as a promising target of GeA, and the interaction profile of the USP5-GeA complex was explained. USP5 is an enzyme involved in the pathway of protein metabolism through the disassembly of the polyubiquitin chains on degraded proteins into ubiquitin monomers. This activity is connected to different cellular functions concerning the maintenance of chromatin structure and receptors and the degradation of abnormal proteins and cancerogenic progression. On this basis, this structural information opens the way to following studies focused on the definition of the biological potential of Gracilioether A and the rational development of novel USP5 inhibitors based on a new structural skeleton.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera.

METHODS

To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates.

RESULTS

We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions.

CONCLUSIONS

A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Targeted Mass Spectrometry for Quantification of Receptor Tyrosine Kinase Signaling

Targeted proteomics enables sensitive and specific quantification of proteins and post-translational modifications. By coupling peptide immunoaffinity enrichment with targeted mass spectrometry, we have developed the methodology for multiplexed quantification of proteins and phosphosites involved in the RAS/MAPK signaling network. The method uses anti-peptide antibodies to enrich analytes and heavy stable isotope-labeled internal standards, spiked in at known concentrations. The enriched peptides are directly measured by multiple-reaction monitoring (MRM), a well-characterized quantitative mass spectrometry-based method. The analyte (light) peptide response is measured relative to the heavy standard. The method described provides quantitative measurements of phospho-signaling and is generally applicable to other phosphopeptides and sample types.

Probing Protein Complexes Composition, Stoichiometry, and Interactions by Peptide-Based Mass Spectrometry

The characterization of a protein complex by mass spectrometry can be conducted at different levels. Initial steps regard the qualitative composition of the complex and subunit identification. After that, quantitative information such as stoichiometric ratios and copy numbers for each subunit in a complex or super-complex is acquired. Peptide-based LC-MS/MS offers a wide number of methods and protocols for the characterization of protein complexes. This chapter concentrates on the applications of peptide-based LC-MS/MS for the qualitative, quantitative, and structural characterization of protein complexes focusing on subunit identification, determination of stoichiometric ratio and number of subunits per complex as well as on cross-linking mass spectrometry and hydrogen/deuterium exchange as methods for the structural investigation of the biological assemblies.

Integrative Proteogenomics for Differential Expression and Splicing Variation in a DM1 Mouse Model

Dysregulated mRNA splicing is involved in the pathogenesis of many diseases including cancer, neurodegenerative diseases, and muscular dystrophies such as myotonic dystrophy type 1 (DM1). Comprehensive assessment of dysregulated splicing on the transcriptome and proteome level has been methodologically challenging, and thus investigations have often been targeting only few genes. Here, we performed a large-scale coordinated transcriptomic and proteomic analysis to characterize a DM1 mouse model (HSALR) in comparison to wild type. Our integrative proteogenomics approach comprised gene- and splicing-level assessments for mRNAs and proteins. It recapitulated many known instances of aberrant mRNA splicing in DM1 and identified new ones. It enabled the design and targeting of splicing-specific peptides and confirmed the translation of known instances of aberrantly spliced disease-related genes (e.g., Atp2a1, Bin1, Ryr1), complemented by novel findings (Flnc and Ywhae). Comparative analysis of large-scale mRNA and protein expression data showed quantitative agreement of differentially expressed genes and splicing patterns between disease and wild type. We hence propose this work as a suitable blueprint for a robust and scalable integrative proteogenomic strategy geared toward advancing our understanding of splicing-based disorders. With such a strategy, splicing-based biomarker candidates emerge as an attractive and accessible option, as they can be efficiently asserted on the mRNA and protein level in coordinated fashion.

Food allergen detection by mass spectrometry: From common to novel protein ingredients

Food allergens are molecules, mainly proteins, that trigger immune responses in susceptible individuals upon consumption even when they would otherwise be harmless. Symptoms of a food allergy can range from mild to acute; this last effect is a severe and potentially life-threatening reaction. The European Union (EU) has identified 14 common food allergens, but new allergens are likely to emerge with constantly changing food habits. Mass spectrometry (MS) is a promising alternative to traditional antibody-based assays for quantifying multiple allergenic proteins in complex matrices with high sensitivity and selectivity. Here, the main allergenic proteins and the advantages and drawbacks of some MS acquisition protocols, such as multiple reaction monitoring (MRM) and data-dependent analysis (DDA) for identifying and quantifying common allergenic proteins in processed foodstuffs are summarized. Sections dedicated to novel foods like microalgae and insects as new sources of allergenic proteins are included, emphasizing the significance of establishing stable marker peptides and validated methods using database searches. The discussion involves the in-silico digestion of allergenic proteins, providing insights into their potential impact on immunogenicity. Finally, case studies focussing on microalgae highlight the value of MS as an effective analytical tool for ensuring regulatory compliance throughout the food control chain.

Covalent fragment libraries in drug discovery-Design, synthesis, and screening methods

As the development of drugs with a covalent mode of action is becoming increasingly popular, well-validated covalent fragment-based drug discovery (FBDD) methods have been comparatively slow to keep up with the demand. In this chapter the principles of covalent fragment reactivity, library design, synthesis, and screening methods are explored in depth, focussing on literature examples with direct applications to practical covalent fragment library design and screening. Further, questions about the future of the field are explored and potential useful advances are proposed.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Secreted folate receptor γ drives fibrogenesis in metabolic dysfunction-associated steatohepatitis by amplifying TGFβ signaling in hepatic stellate cells

Hepatic fibrosis is the primary determinant of mortality in patients with metabolic dysfunction-associated steatohepatitis (MASH). Transforming growth factor-β (TGFβ), a master profibrogenic cytokine, is a promising therapeutic target that has not yet been translated into an effective therapy in part because of liabilities associated with systemic TGFβ antagonism. We have identified that soluble folate receptor γ (FOLR3), which is expressed in humans but not in rodents, is a secreted protein that is elevated in the livers of patients with MASH but not in those with metabolic dysfunction-associated steatotic liver disease, those with type II diabetes, or healthy individuals. Global proteomics showed that FOLR3 was the most highly significant MASH-specific protein and was positively correlated with increasing fibrosis stage, consistent with stimulation of activated hepatic stellate cells (HSCs), which are the key fibrogenic cells in the liver. Exposure of HSCs to exogenous FOLR3 led to elevated extracellular matrix (ECM) protein production, an effect synergistically potentiated by TGFβ1. We found that FOLR3 interacts with the serine protease HTRA1, a known regulator of TGFBR, and activates TGFβ signaling. Administration of human FOLR3 to mice induced severe bridging fibrosis and an ECM pattern resembling human MASH. Our study thus uncovers a role of FOLR3 in enhancing fibrosis.

Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) remains a highly unpredictable disease. Many hope that fluid biomarkers may contribute to better stratification of disease, aiding the personalisation of treatment decisions, ultimately improving patient outcomes.

OBJECTIVE

The objective of this study was to evaluate the predictive value of CSF brain-specific proteins from early in the disease course of MS on long term clinical outcomes.

METHODS

In this study, 34 MS patients had their CSF collected and stored within 5 years of disease onset and were then followed clinically for at least 15 years. CSF concentrations of 64 brain-specific proteins were analyzed in the 34 patient CSF, as well as 19 age and sex-matched controls, using a targeted liquid-chromatography tandem mass spectrometry approach.

RESULTS

We identified six CSF brain-specific proteins that significantly differentiated MS from controls (p < 0.05) and nine proteins that could predict disease course over the next decade. CAMK2A emerged as a biomarker candidate that could discriminate between MS and controls and could predict long-term disease progression.

CONCLUSION

Targeted approaches to identify and quantify biomarkers associated with MS in the CSF may inform on long term MS outcomes. CAMK2A may be one of several candidates, warranting further exploration.

A Critical Overview of HPLC-MS-Based Lipidomics in Determining Triacylglycerol and Phospholipid in Foods

With the current advancement in mass spectrometry (MS)-based lipidomics, the knowledge of lipidomes and their diverse roles has greatly increased, enabling a deeper understanding of the action of bioactive lipid molecules in plant- and animal-based foods. This review provides in-depth information on the practical use of MS techniques in lipidomics, including lipid extraction, adduct formation, MS analysis, data processing, statistical analysis, and bioinformatics. Moreover, this contribution demonstrates the effectiveness of MS-based lipidomics for identifying and quantifying diverse lipid species, especially triacylglycerols and phospholipids, in foods. Further, it summarizes the wide applications of MS-based lipidomics in food science, such as for assessing food processing methods, detecting food adulteration, and measuring lipid oxidation in foods. Thus, MS-based lipidomics may be a useful method for identifying the action of individual lipid species in foods.

Targeted proteomics data interpretation with DeepMRM

Targeted proteomics is widely utilized in clinical proteomics; however, researchers often devote substantial time to manual data interpretation, which hinders the transferability, reproducibility, and scalability of this approach. We introduce DeepMRM, a software package based on deep learning algorithms for object detection developed to minimize manual intervention in targeted proteomics data analysis. DeepMRM was evaluated on internal and public datasets, demonstrating superior accuracy compared with the community standard tool Skyline. To promote widespread adoption, we have incorporated a stand-alone graphical user interface for DeepMRM and integrated its algorithm into the Skyline software package as an external tool.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Recent advances in proteomic-based diagnostics of cystic fibrosis

INTRODUCTION

Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF.

AREAS COVERED

We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers.

EXPERT OPINION

Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.

Omics and systems view of innate immune pathways

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

A single protein to multiple peptides: Investigation of protein-peptide correlations using targeted alpha-2-macroglobulin analysis

Recent advances in proteomics technologies have enabled the analysis of thousands of proteins in a high-throughput manner. Mass spectrometry (MS) based proteomics uses a peptide-centric approach where biological samples undergo specific proteolytic digestion and then only unique peptides are used for protein identification and quantification. Considering the fact that a single protein may have multiple unique peptides and a number of different forms, it becomes essential to understand dynamic protein-peptide relationships to ensure robust and reliable peptide-centric protein analysis. In this study, we investigated the correlation between protein concentration and corresponding unique peptide responses under a conventional proteolytic digestion condition. Protein-peptide correlation, digestion efficiency, matrix-effect, and concentration-effect were evaluated. Twelve unique peptides of alpha-2-macroglobulin (A2MG) were monitored using a targeted MS approach to acquire insights into protein-peptide dynamics. Although the peptide responses were reproducible between replicates, protein-peptide correlation was moderate in protein standards and low in complex matrices. The results suggest that reproducible peptide signal could be misleading in clinical studies and a peptide selection could dramatically change the outcome at protein level. This is the first study investigating quantitative protein-peptide correlations in biological samples using all unique peptides representing the same protein and opens a discussion on peptide-based proteomics.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Aptamer-based sample purification for mass spectrometric quantification of trastuzumab in human serum

In this study, we developed a simple liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay to quantify trastuzumab in human serum using aptamers for sample purification. Trastuzumab was extracted from serum samples using the capture probe based on its aptamer CH1S-3, followed by reduction, alkylation, trypsin digestion, and quantification using LC-MS/MS. Additionally, a unique peptide, FTISADTSK, was employed as a surrogate peptide and quantified, and *FTISADTSK (¹³C₉¹⁵N-labeled phenylalanine) was used as an internal standard to minimize variability in detection among the samples. The detection range for this method was 0.5-250 μg/mL, with a high correlation coefficient (r² > 0.99). The intra- and inter-day precision (%CV, the coefficient of variation) of the quality control samples was less than 12.7%, and the accuracy (%bias) was below 8.64%. After optimization and verification, this assay was used to determine trastuzumab levels in clinical human serum samples. The results indicated that the trastuzumab concentrations had an approximate 4-fold difference among ten patients (range: 11.80-41.90 μg/mL). This study provides a novel approach for the accurate and quantitative monitoring of the mAb-trastuzumab.

Quantitative Mass Spectrometry Analysis of Cerebrospinal Fluid Protein Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT-) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT-), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT- individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

The Edge Effect in High-Throughput Proteomics: A Cautionary Tale

In order for mass spectrometry to continue to grow as a platform for high-throughput clinical and translational research, careful consideration must be given to quality control by ensuring that the assay performs reproducibly and accurately and precisely. In particular, the throughput required for large cohort clinical validation in biomarker discovery and diagnostic screening has driven the growth of multiplexed targeted liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) assays paired with sample preparation and analysis in multiwell plates. However, large scale MS-based proteomics studies are often plagued by batch effects: sources of technical variation in the data, which can arise from a diverse array of sources such as sample preparation batches, different reagent lots, or indeed MS signal drift. These batch effects can confound the detection of true signal differences, resulting in incorrect conclusions being drawn about significant biological effects or lack thereof. Here, we present an intraplate batch effect termed the edge effect arising from temperature gradients in multiwell plates, commonly reported in preclinical cell culture studies but not yet reported in a clinical proteomics setting. We present methods herein to ameliorate the phenomenon including proper assessment of heating techniques for multiwell plates and incorporation of surrogate standards, which can normalize for intraplate variation.