A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.

Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics.

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

Quantitative proteomics analysis reveals the protective role of S14G-humanin in septic acute kidney injury using 4D-label-free and PRM Approaches.

Mitochondrial dysfunction contributes to septic acute kidney injury (S-AKI), making mitochondrial protection a potential therapeutic strategy. This study investigates the effects of S14G-humanin (HNG) in S-AKI, utilizing 4D-label-free and parallel reaction monitoring (PRM) techniques for proteomic analysis. An S-AKI model was created in male C57BL/6 mice using lipopolysaccharide (LPS) injection, followed by HNG administration. After 24 h, kidney tissues were analyzed for histology, biochemistry, mitochondrial function, and proteomics. HNG treatment improved renal function, reduced tubular injury, and decreased pro-inflammatory cytokines and oxidative stress markers. Proteomic analysis identified 5900 proteins, with 5111 quantifiable. HNG altered the expression of 132 proteins, with 18 selected for PRM validation. Ten of these proteins were linked to key pathways, including fatty acid degradation and PPAR signaling. This study is the first to show HNG's protective effects in S-AKI, providing insights into its mechanisms through advanced proteomic techniques.

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA.

BACKGROUND: Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring. METHODS: Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides. RESULTS: We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making. CONCLUSIONS: Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.

Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS.

Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.

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.

Exoproteome analysis of Pseudomonas aeruginosa response to high alkane stress.

Microbial biodegradation serves as an effective approach to treat oil pollution. However, the application of such methods for the degrading long-chain alkanes still encounters significant challenges. Comparative proteomics has extensively studied the intracellular proteins of bacteria that degrade short- and medium-chain alkanes, but the role and mechanism of extracellular proteins in many microorganism remain unclear. To enhance our understanding of the roles of extracellular proteins in the adaptation to long-chain alkanes, a label-free LC-MS/MS strategy was applied for the relative quantification of extracellular proteins of Pseudomonas aeruginosa SJTD-1-M (ProteomeXchange identifier PXD014638). 444 alkane-sentitive proteins were acquired and their cell localization analysis was performed using the Pseudomonas Genome Database. Among them, 111 proteins were found to be located in extracellular or Outer Membrane Vesicles (OMVs). The alkane-induced abundance of 11 extracellular or OMV target proteins was confirmed by parallel reaction monitoring (PRM). Furthermore, we observed that the expression levels of three proteins (Pra, PA2815, and FliC) were associated with the carbon chain length of the added alkane in the culture medium. The roles of these proteins in cell mobility, alkane emulsification, assimilation, and degradation were further discussed. OMVs were found to contain a number of enzymes involved in alkane metabolism, fatty acid beta-oxidation, and the TCA cycle, suggesting their potential as sites for facilitated alkane degradation. In this sense, this exoproteome analysis contributes to a better understanding of the role of extracellular proteins in the hydrocarbon treatment process.

Proteomics revealed an association between ribosome-associated proteins and amyloid beta deposition in Alzheimer's disease.

Most scholars believe that amyloid-beta (Aß) has the potential to induce apoptosis, stimulate an inflammatory cascade, promote oxidative stress and exacerbate the pathological progression of Alzheimer's disease (AD). Therefore, it is crucial to investigate the deposition of Aß in AD. At approximately 6 months of age, APP/PS1 double transgenic mice gradually exhibit the development of plaques, as well as spatial and learning impairment. Notably, the hippocampus is specifically affected in the course of AD. Herein, 6-month-old APP/PS1 double transgenic mice were utilized, and the differentially expressed (DE) proteins in the hippocampus were identified and analyzed using 4D label-free quantitative proteomics technology and parallel reaction monitoring (PRM). Compared to wild-type mice, 29 proteins were upregulated and 25 proteins were downregulated in the AD group. Gene Ontology (GO) enrichment analysis of biological processes (BP) indicated that the DE proteins were mainly involved in 'ribosomal large subunit biogenesis'. Molecular function (MF) analysis results were primarily associated with '5.8S rRNA binding' and 'structural constituent of ribosome'. In terms of cellular components (CC), the DE proteins were mainly found in 'polysomal ribosome', 'cytosolic large ribosomal subunit', 'cytosolic ribosome', and 'large ribosomal subunit', among others. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the results were mainly enriched in the 'Ribosome signaling pathway'. The key target proteins identified were ribosomal protein (Rp)l18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6. The PRM verification results were consistent with the findings of the 4D label-free quantitative proteomics analysis. Overall, these findings suggest that Rpl18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6 may have potential therapeutic value for the treatment of AD by targeting Aß.

Targeted Mass Spectrometry Analyses of Somatic Mutations in Colorectal Cancer Specimens Using Differential Ion Mobility.

Identification of K-Ras and B-Raf mutations in colorectal cancer (CRC) is essential to predict patients' response to anti-EGFR therapy and formulate appropriate therapeutic strategies to improve prognosis and survival. Here, we combined parallel reaction monitoring (PRM) with high-field asymmetric waveform ion mobility (FAIMS) to enhance mass spectrometry sensitivity and improve the identification of low-abundance K-Ras and B-Raf mutations in biological samples without immunoaffinity enrichment. In targeted LC-MS/MS analyses, FAIMS reduced the occurrence of interfering ions and enhanced precursor ion purity, resulting in a 3-fold improvement in the detection limit for K-Ras and B-Raf mutated peptides. In addition, the ion mobility separation of isomeric peptides using FAIMS facilitated the unambiguous identification of K-Ras G12D and G13D peptides. The application of targeted LC-MS/MS analyses using FAIMS is demonstrated for the detection and quantitation of B-Raf V600E, K-Ras G12D, G13D, and G12V in CRC cell lines and primary specimens.

A micro-flow, high-pH, reversed-phase peptide fractionation and collection system for targeted and in-depth proteomics of low-abundance proteins in limiting samples.

We present a method and a simple system for high-pH RP-LC peptide fractionation of small sample amounts (30-60 µg), at micro-flow rates with micro-liter fraction collection using ammonium bicarbonate as an optimized buffer for system stability and robustness. The method is applicable to targeted mass spectrometry approaches and to in-depth proteomic studies where the amount of sample is limited. Using targeted proteomics with peptide standards, we present the method's analytical parameters, and potential in increasing the detection of low-abundance proteins that are difficult to quantify with direct targeted or global LC-MS analyses. This fractionation system increased peptide signals by up to 18-fold, while maintaining high quantitative precision, with high fractionation reproducibility across varied sample sets. In real applications, it increased the detection of targeted endogenous peptides by two-fold in a 25 cell-cycle-control protein panel, and in-depth MS analyses of nuclear extracts, it allowed the detection of up to 8,896 proteins with 138,417 peptides in 24-concatenated fractions compared to 3,344 proteins with 23,093 peptides without fractionation. In a relevant biological problem of CDK4/6-inhibitors and breast cancer, the method reproduced known information and revealed novel insights, highlighting that it can be successfully applied in studies involving low-abundance proteins and limited samples. •Tested nine high-pH buffer/solvent systems to obtain a robust, effective, and reproducible micro-flow fractionation method which was devoid of commonly encountered LC clogging/pressure issues after months of use.•Peptide enrichment method to improve detection and quantitation of low-abundance proteins in targeted and in-depth proteomic studies.•Can be applied to diverse protein samples where the available amount is limited.

Quantitative Proteomic Analysis of MCM3 in ThinPrep Samples of Patients with Cervical Preinvasive Cancer.

Triage methods for cervical cancer detection show moderate accuracy and present considerable false-negative and false-positive result rates. A complementary diagnostic parameter could help improve the accuracy of identifying patients who need treatment. A pilot study was performed using a targeted proteomics approach with opportunistic ThinPrep samples obtained from women collected at the hospital's outpatient clinic to determine the concentration levels of minichromosome maintenance-3 (MCM3) and envoplakin (EVPL) proteins. Forty samples with 'negative for intraepithelial lesion or malignancy' (NILM), 21 samples with 'atypical squamous cells of undetermined significance' (ASC-US), and 33 samples with 'low-grade squamous intraepithelial lesion and worse' (≥LSIL) were analyzed, using cytology and the patients' histology reports. Highly accurate concordance was obtained for gold-standard-confirmed samples, demonstrating that the MCM3/EVPL ratio can discriminate between non-dysplastic and dysplastic samples. On that account, we propose that MCM3 and EVPL are promising candidate protein biomarkers for population-based cervical cancer screening.

Tandem mass tag (TMT) quantitative protein analysis-based proteomics and parallel reaction monitoring (PRM) validation revealed that MST4 accelerates osteosarcoma proliferation by increasing MRC2 activity.

Osteosarcoma is one of the most common orthopedic malignancies and is characterized by rapid disease progression and a poor prognosis. Currently, research on methods to inhibit osteosarcoma proliferation is still limited. In this study, we found that MST4 levels were significantly increased in osteosarcoma cell lines and tumor tissues compared to normal controls and demonstrated that MST4 is an influential factor in promoting osteosarcoma proliferation both in vivo and in vitro. Proteomic analysis was performed on osteosarcoma cells in the MST4 overexpression and vector expression groups, and 545 significantly differentially expressed proteins were identified and quantified. The candidate differentially expressed protein MRC2 was then identified using parallel reaction monitoring validation. Subsequently, MRC2 expression was silenced with small interfering RNA (siRNA), and we were surprised to find that this alteration affected the cell cycle of MST4-overexpressing osteosarcoma cells, promoted apoptosis and impaired the positive regulation of osteosarcoma growth by MST4. In conclusion, this study identified a novel approach for suppressing osteosarcoma proliferation. Reduction of MRC2 activity inhibits osteosarcoma proliferation in patients with high MST4 expression by altering the cell cycle, which may be valuable for treating osteosarcoma and improving patient prognosis.

Isolation and Identification of Plasma Extracellular Vesicles Protein Biomarkers.

Extracellular vesicles (EVs) have emerged as a valuable source for disease biomarkers and an alternative drug delivery system due to their ability to carry cargo and target specific cells. Proper isolation, identification, and analytical strategy are required for evaluating their potential in diagnostics and therapeutics. Here, a method is detailed to isolate plasma EVs and analyze their proteomic profiling, combining EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and mass spectrometry qualitative and quantitative strategies for EV proteome characterization. The pipeline provides a highly effective EV-based proteome analysis technique that can be applied for EV characterization and evaluation of EV-based diagnosis and therapy.

Phosphoproteomics Profiling Defines a Target Landscape of the Basophilic Protein Kinases AKT, S6K, and RSK in Skeletal Myotubes.

Phosphorylation-dependent signal transduction plays an important role in regulating the functions and fate of skeletal muscle cells. Central players in the phospho-signaling network are the protein kinases AKT, S6K, and RSK as part of the PI3K-AKT-mTOR-S6K and RAF-MEK-ERK-RSK pathways. However, despite their functional importance, knowledge about their specific targets is incomplete because these kinases share the same basophilic substrate motif RxRxxp[ST]. To address this, we performed a multifaceted quantitative phosphoproteomics study of skeletal myotubes following kinase inhibition. Our data corroborate a cross talk between AKT and RAF, a negative feedback loop of RSK on ERK, and a putative connection between RSK and PI3K signaling. Altogether, we report a kinase target landscape containing 49 so far unknown target sites. AKT, S6K, and RSK phosphorylate numerous proteins involved in muscle development, integrity, and functions, and signaling converges on factors that are central for the skeletal muscle cytoskeleton. Whereas AKT controls insulin signaling and impinges on GTPase signaling, nuclear signaling is characteristic for RSK. Our data further support a role of RSK in glucose metabolism. Shared targets have functions in RNA maturation, stability, and translation, which suggests that these basophilic kinases establish an intricate signaling network to orchestrate and regulate processes involved in translation.

The Controversy of Pepsinogen A/Pepsin A in Detecting Extra-Gastroesophageal Reflux.

BACKGROUND: Pepsinogen A (PGA)/pepsin A is often used as a diagnostic marker of extra-gastroesophageal reflux. We aimed to explore whether its positivity in upper aerodigestive tract (UADT) was specific enough to diagnose reflux. METHODS: PGA/pepsin A protein levels were examined in 10 types of tissues and 10 types of body fluid by immunological staining, western blot or Elisa, using three different commercially available brands simultaneously. Liquid chromatography-tandem mass spectrometry parallel reaction monitoring (LC-MS/MS PRM) served as a gold reference for the detection of PGA/pepsin A proteins. PGA gene expression was analyzed by reverse transcriptase sequencing methods for tissue samples. Specifically, 24 hour pH monitoring technique was conducted for patients who donated saliva samples. RESULTS: Eight out of ten types of human tissue samples (stomach, esophagus, lung, kidney, colon, parotid gland, nasal turbinate and nasal polyps) were confirmed positive for PGA/pepsin A gene and protein by genetic and PRM technique, respectively. Two out of ten types of body fluid samples (gastric fluid, urine) were confirmed positive for PGA/pepsin A protein by PRM technique. The consistence rates of PGA/pepsin A positivity among three commercial antibody brands and Elisa kit were poor, and Elisa results of salivary did not match with 24-hour pH monitoring. CONCLUSIONS: Multiple tissues and body fluid could be detected baseline expression levels of PGA/pepsin A gene and protein. However, those commercially available PGA/pepsin A antibodies achieved poor sensitivity and specificity, therefore, relying on the detection of PGA/pepsin A in UADT by single antibodies to diagnose extra-gastroesophageal reflux without a specific positive cut-off value is unreliable.

Development of Parallel Reaction Monitoring Mass Spectrometry Assay for the Detection of Human Norovirus Major Capsid Protein.

Human Norwalk viruses (HuNoVs), the most common etiological agents of acute gastroenteritis, are genetically diverse RNA viruses that frequently cause mass food poisoning internationally. Although nucleic acid detection methods, such as reverse transcription-quantitative polymerase chain reaction (RT-qPCR), are the gold standard for the diagnosis of norovirus infection, alternative methods are needed for the specific and sensitive viral protein detection for rapid diagnosis and surveillance. In this study, we developed a robust and high-throughput targeted proteomic assay workflow to directly detect the VP1 major capsid protein of HuNoVs. A parallel reaction monitoring (PRM) assay using a high-resolution mass spectrometer was used to detect representative peptides derived from VP1 in six different HuNoV genotypes. An optimized protocol using synthesized heavy isotope-labeled peptides as internal standards was also used to simultaneously genotype and quantify the VP1 protein in human stool specimens. This method is expected to become a new tool for studying the molecular epidemiology of HuNoV and to shed new light on targeted proteomics in clinical practice.

The succinylome of Pinctada fucata martensii implicates lysine succinylation in the allograft-induced stress response.

Lysine succinylation is a novel protein post-translational modification associated with the regulation of a variety of cellular processes. Post-translational modifications may regulate the immune response of Pinctada fucata martensii, a marine bivalve used to produce cultured pearls, in response to the surgical implantation of the seed pearl. This allograft-induced stress response may lead to transplant rejection or host death. However, the regulatory effects of post-translational modifications following nucleus insertion surgery in P.f. martensii remain largely unknown. Here, we used 4D label-free quantitative proteomics (4D-LFQ) with LC-MS/MS to explore the effects of nucleus implantation on lysine succinylation in P.f. martensii. We identified 4430 succinylated sites on 964 succinylated proteins in P.f. martensii after nucleus insertion surgery, and seven conserved motifs were identified upstream and downstream of these sites. In total, 269 succinylation sites were differentially expressed in response to implantation (|fold-change| > 1.5 and FDR <1%; 211 upregulation and 58 downregulation), corresponding to 163 differentially expressed succinylated proteins (DESPs; 124 upregulated and 39 downregulated). The terms over-enriched in the DESPs included "cellular processes", "metabolic pathways", and "binding activity", while the significantly enriched pathways included "ECM-receptor interaction", "PI3K-Akt signaling", and "focal adhesion". "EGF-like structural domains", "platelet-responsive protein type 1 structural domains", and "laminin EGF-like (domains III and V) domains" were overrepresented in the DESPs. Parallel reaction-monitoring (PRM) analysis validated 13 DESPs from the proteomics data. The succinylome of P.f. martensii (generated here for the first time) helps to clarify the biological role of large-scale succinylation in this bivalve after nucleus insertion surgery, providing a theoretical basis for further investigations of stress-induced post-translational modifications in other mollusks and extending our knowledge of the molluscan succinylated proteome.

Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays.

Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.

Proteomic analysis of differential anther development from sterile/fertile lines in Capsicum annuum L.

Background: Pepper (Capsicum annuum L.) is a major cash crop throughout the world. Male sterility is an important characteristic in crop species that leads to a failure to produce functional pollen, and it has crucial roles in agricultural breeding and the utilization of heterosis. Objectives: In this study, we identified many crucial factors and important components in metabolic pathways in anther and pollen development, and elucidated the molecular mechanism related to pollen abortion in pepper. Methods: Pepper pollen was observed at different stages to detect the characteristics associated with male sterility and fertility. The phytohormone and oxidoreductase activities were detected in spectrophotometric and redox reaction assays, respectively. Proteins were extracted from male sterile and fertile pepper lines, and identified by TMT/iTRAQ (tandem mass tags/isobaric tags for relative and absolute quantitation) and LC-MS/MS (liquid chromatograph-mass spectrometer) analysis. Differentially abundant proteins (DAPs) were analyzed based on Gene Ontology annotations and the Kyoto Encyclopedia of Genes and Genomes database according to |fold change)| > 1.3 and P value < 0.05. DAPs were quantified in the meiosis, tetrad, and binucleate stages by parallel reaction monitoring (PRM). Results: In this study, we screened and identified one male sterile pepper line with abnormal cytological characteristics in terms of pollen development. The peroxidase and catalase enzyme activities were significantly reduced and increased, respectively, in the male sterile line compared with the male fertile line. Phytohormone analysis demonstrated that the gibberellin, jasmonic acid, and auxin contents changed by different extents in the male sterile pepper line. Proteome analysis screened 1,645 DAPs in six clusters, which were mainly associated with the chloroplast and cytoplasm based on their similar expression levels. According to proteome analysis, 45 DAPs were quantitatively identified in the meiosis, tetrad, and binucleate stages by PRM, which were related to monoterpenoid biosynthesis, and starch and sucrose metabolism pathways. Conclusions: We screened 1,645 DAPs by proteomic analysis and 45 DAPs were related to anther and pollen development in a male sterile pepper line. In addition, the activities of peroxidase and catalase as well as the abundances of phytohormones such as gibberellin, jasmonic acid, and auxin were related to male sterility. The results obtained in this study provide insights into the molecular mechanism responsible for male sterility and fertility in pepper.