A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability.

Mutations truncating a single copy of the tumor suppressor, BRCA2, cause cancer susceptibility. In cells bearing such heterozygous mutations, we find that a cellular metabolite and ubiquitous environmental toxin, formaldehyde, stalls and destabilizes DNA replication forks, engendering structural chromosomal aberrations. Formaldehyde selectively depletes BRCA2 via proteasomal degradation, a mechanism of toxicity that affects very few additional cellular proteins. Heterozygous BRCA2 truncations, by lowering pre-existing BRCA2 expression, sensitize to BRCA2 haploinsufficiency induced by transient exposure to natural concentrations of formaldehyde. Acetaldehyde, an alcohol catabolite detoxified by ALDH2, precipitates similar effects. Ribonuclease H1 ameliorates replication fork instability and chromosomal aberrations provoked by aldehyde-induced BRCA2 haploinsufficiency, suggesting that BRCA2 inactivation triggers spontaneous mutagenesis during DNA replication via aberrant RNA-DNA hybrids (R-loops). These findings suggest a model wherein carcinogenesis in BRCA2 mutation carriers can be incited by compounds found pervasively in the environment and generated endogenously in certain tissues with implications for public health.

Identification of a Proteomic Signature for Predicting Immunotherapy Response in Patients With Metastatic Non-Small Cell Lung Cancer.

Immunotherapy has improved survival rates in patients with cancer, but identifying those who will respond to treatment remains a challenge. Advances in proteomic technologies have enabled the identification and quantification of nearly all expressed proteins in a single experiment. Integrating mass spectrometry with high-throughput technologies has facilitated comprehensive analysis of the plasma proteome in cancer, facilitating early diagnosis and personalized treatment. In this context, our study aimed to investigate the predictive and prognostic value of plasma proteome analysis using the SWATH-MS (Sequential Window Acquisition of All Theoretical Mass Spectra) strategy in newly diagnosed patients with non-small cell lung cancer (NSCLC) receiving pembrolizumab therapy. We enrolled 64 newly diagnosed patients with advanced NSCLC treated with pembrolizumab. Blood samples were collected from all patients before and during therapy. A total of 171 blood samples were analyzed using the SWATH-MS strategy. Plasma protein expression in metastatic NSCLC patients prior to receiving pembrolizumab was analyzed. A first cohort (discovery cohort) was employed to identify a proteomic signature predicting immunotherapy response. Thus, 324 differentially expressed proteins between responder and non-responder patients were identified. In addition, we developed a predictive model and found a combination of seven proteins, including ATG9A, DCDC2, HPS5, FIL1L, LZTL1, PGTA, and SPTN2, with stronger predictive value than PD-L1 expression alone. Additionally, survival analyses showed an association between the levels of ATG9A, DCDC2, SPTN2 and HPS5 with progression-free survival (PFS) and/or overall survival (OS). Our findings highlight the potential of proteomic technologies to detect predictive biomarkers in blood samples from NSCLC patients, emphasizing the correlation between immunotherapy response and the idenfied protein set.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein.

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis.

In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.

Global proteomic analyses of human cytotrophoblast differentiation/invasion.

During human pregnancy, cytotrophoblasts (CTBs) from the placenta differentiate into specialized subpopulations that play crucial roles in proper fetal growth and development. A subset of these CTBs differentiate along an invasive pathway, penetrating the decidua and anchoring the placenta to the uterus. A crucial hurdle in pregnancy is the ability of these cells to migrate, invade and remodel spiral arteries, ensuring adequate blood flow to nourish the developing fetus. Although advances continue in describing the molecular features regulating the differentiation of these cells, assessment of their global proteomic changes at mid-gestation remain undefined. Here, using sequential window acquisition of all theoretical fragment-ion spectra (SWATH), which is a data-independent acquisition strategy, we characterized the protein repertoire of second trimester human CTBs during their differentiation towards an invasive phenotype. This mass spectrometry-based approach allowed identification of 3026 proteins across four culture time points corresponding to sequential stages of differentiation, confirming the expression dynamics of established molecules and offering new information into other pathways involved. The availability of a SWATH CTB global spectral library serves as a beneficial resource for hypothesis generation and as a foundation for further understanding CTB differentiation dynamics.

Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort.

BACKGROUND: The early identification of patients at high-risk for end-stage renal disease (ESRD) is essential for providing optimal care and implementing targeted prevention strategies. While the Kidney Failure Risk Equation (KFRE) offers a more accurate prediction of ESRD risk compared to static eGFR-based thresholds, it does not provide insights into the patient-specific biological mechanisms that drive ESRD. This study focused on evaluating the effectiveness of KFRE in a UK-based advanced chronic kidney disease (CKD) cohort and investigating whether the integration of a proteomic signature could enhance 5-year ESRD prediction. METHODS: Using the Salford Kidney Study biobank, a UK-based prospective cohort of over 3000 non-dialysis CKD patients, 433 patients met our inclusion criteria: a minimum of four eGFR measurements over a two-year period and a linear eGFR trajectory. Plasma samples were obtained and analysed for novel proteomic signals using SWATH-Mass-Spectrometry. The 4-variable UK-calibrated KFRE was calculated for each patient based on their baseline clinical characteristics. Boruta machine learning algorithm was used for the selection of proteins most contributing to differentiation between patient groups. Logistic regression was employed for estimation of ESRD prediction by (1) proteomic features; (2) KFRE; and (3) proteomic features alongside KFRE. RESULTS: SWATH maps with 943 quantified proteins were generated and investigated in tandem with available clinical data to identify potential progression biomarkers. We identified a set of proteins (SPTA1, MYL6 and C6) that, when used alongside the 4-variable UK-KFRE, improved the prediction of 5-year risk of ESRD (AUC = 0.75 vs AUC = 0.70). Functional enrichment analysis revealed Rho GTPases and regulation of the actin cytoskeleton pathways to be statistically significant, inferring their role in kidney function and the pathogenesis of renal disease. CONCLUSIONS: Proteins SPTA1, MYL6 and C6, when used alongside the 4-variable UK-KFRE achieve an improved performance when predicting a 5-year risk of ESRD. Specific pathways implicated in the pathogenesis of podocyte dysfunction were also identified, which could serve as potential therapeutic targets. The findings of our study carry implications for comprehending the involvement of the Rho family GTPases in the pathophysiology of kidney disease, advancing our understanding of the proteomic factors influencing susceptibility to renal damage.

Using SWATH-MS to identify new molecular biomarkers in gingival crevicular fluid for detecting periodontitis and its response to treatment.

AIM: To identify new biomarkers to detect untreated and treated periodontitis in gingival crevicular fluid (GCF) using sequential window acquisition of all theoretical mass spectra (SWATH-MS). MATERIALS AND METHODS: GCF samples were collected from 44 periodontally healthy subjects and 40 with periodontitis (Stages III-IV). In the latter, 25 improved clinically 2 months after treatment. Samples were analysed using SWATH-MS, and proteins were identified by the UniProt human-specific database. The diagnostic capability of the proteins was determined with generalized additive models to distinguish the three clinical conditions. RESULTS: In the untreated periodontitis vs. periodontal health modelling, five proteins showed excellent or good bias-corrected (bc)-sensitivity/bc-specificity values of >80%. These were GAPDH, ZG16B, carbonic anhydrase 1, plasma protease inhibitor C1 and haemoglobin subunit beta. GAPDH with MMP-9, MMP-8, zinc-α-2-glycoprotein and neutrophil gelatinase-associated lipocalin and ZG16B with cornulin provided increased bc-sensitivity/bc-specificity of >95%. For distinguishing treated periodontitis vs. periodontal health, most of these proteins and their combinations revealed a predictive ability similar to previous modelling. No model obtained relevant results to differentiate between periodontitis conditions. CONCLUSIONS: New single and dual GCF protein biomarkers showed outstanding results in discriminating untreated and treated periodontitis from periodontal health. Periodontitis conditions were indistinguishable. Future research must validate these findings.

Proteomic Profiling Identifies Candidate Diagnostic Biomarkers of Hydrosalpinx in Endometrial Fluid: A Pilot Study.

Hydrosalpinx is a fluid occlusion and distension of the fallopian tubes, often resulting from pelvic inflammatory disease, which reduces the success of artificial reproductive technologies (ARTs) by 50%. Tubal factors account for approximately 25% of infertility cases, but their underlying molecular mechanisms and functional impact on other reproductive tissues remain poorly understood. This proteomic profiling study applied sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) to study hydrosalpinx cyst fluid and pre- and post-salpingectomy endometrial fluid. Among the 967 proteins identified, we found 19 and 17 candidate biomarkers for hydrosalpinx in pre- and post-salpingectomy endometrial fluid, respectively. Salpingectomy significantly affected 76 endometrial proteins, providing insights into the enhanced immune response and inflammation present prior to intervention, and enhanced coagulation cascades and wound healing processes occurring one month after intervention. These findings confirmed that salpingectomy reverses the hydrosalpinx-related functional impairments in the endometrium and set a foundation for further biomarker validation and the development of less-invasive diagnostic strategies for hydrosalpinx.

Peeking into the Stingers: A Comprehensive SWATH-MS Study of the European Hornet Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae) Venom Sac Extracts.

This study aimed to investigate the venom sac extracts (VSEs) of the European hornet (EH) Vespa crabro (Linnaeus, 1758) (Hymenoptera: Vespidae), focusing on the differences between stinging females, gynes (G), and workers (W), at the protein level. Using a quantitative "Sequential Window Acquisition of all Theoretical Fragment Ion Mass Spectra" (SWATH-MS) analysis, we identified and quantified a total of 240 proteins. Notably, within the group, 45.8% (n = 110) showed significant differential expression between VSE-G and VSE-W. In this set, 57.3% (n = 63) were upregulated and 42.7% (n = 47) downregulated in the G. Additionally, the two-hundred quantified proteins from the class Insecta belong to sixteen different species, six of them to the Hymenoptera/Apidae lineage, comprising seven proteins with known potential allergenicity. Thus, phospholipase A1 (Vesp v 1), phospholipase A1 verutoxin 2b (VT-2b), hyaluronidase A (Vesp v 2A), hyaluronidase B (Vesp v 2B), and venom allergen 5 (Vesp v 5) were significantly downregulated in the G, and vitellogenin (Vesp v 6) was upregulated. Overall, 46% of the VSE proteins showed differential expression, with a majority being upregulated in G. Data are available via ProteomeXchange with identifier PXD047955. These findings shed light on the proteomic differences in VSE between EH castes, potentially contributing to our understanding of their behavior and offering insights for allergy research.

Patterns of gene expression in pollen of cotton (Gossypium hirsutum) indicate downregulation as a feature of thermotolerance.

Reproductive performance in plants is impaired as maximum temperatures consistently approach 40°C. However, the timing of heatwaves critically affects their impact. We studied the molecular responses during pollen maturation in cotton to investigate the vulnerability to high temperature. Tetrads (TEs), uninucleate and binucleate microspores, and mature pollen were subjected to SWATH-MS and RNA-seq analyses after exposure to 38/28°C (day/night) for 5 days. The results indicated that molecular signatures were downregulated progressively in response to heat during pollen development. This was even more evident in leaves, where three-quarters of differentially changed proteins decreased in abundance during heat. Functional analysis showed that translation of genes increased in TEs after exposure to heat; however, the reverse pattern was observed in mature pollen and leaves. For example, proteins involved in transport were highly abundant in TEs whereas in later stages of pollen formation and leaves, heat suppressed synthesis of proteins involved in cell-to-cell communication. Moreover, a large number of heat shock proteins were identified in heat-affected TEs, but these proteins were less abundant in mature pollen and leaves. We speculate that the sensitivity of TE cells to heat is related to high rates of translation targeted to pathways that might not be essential for thermotolerance. Molecular signatures during stages of pollen development after heatwaves could provide markers for future genetic improvement.

Proteomic analysis identifies dysregulated proteins and associated molecular pathways in a cohort of gallbladder cancer patients of African ancestry.

BACKGROUND: Gallbladder cancer (GBC) is a lethal cancer with a poor prognosis. The lack of specific and sensitive biomarkers results in delayed diagnosis with most patients presenting at late stages of the disease. Furthermore, there is little known about the molecular mechanisms associated with GBC, especially in patients of African ancestry. This study aimed to determine dysregulated proteins in South African GBC patients to identify potential mechanisms of the disease progression and plausible biomarkers. METHODS: Tissues (27 GBC, 13 Gallstone disease, and 5 normal tissues) and blood plasma (54 GBC and 73 Benign biliary pathology) were obtained from consenting patients. Protein extraction was performed on all tissues and liquid chromatography-mass spectrometry was used for proteomic profiling. A project-specific spectral library was built using the Pulsar search algorithm. Principal component and Spearman's rank correlation analyses were performed using PAST (V4.07b). Pathway and Network analyses were conducted using REACTOME (v3.7) and stringAPP (v1.7.0), respectively. RESULTS: In the tissue sample group, there were 62 and 194 dysregulated proteins in GBC compared to normal and gallstone groups, respectively. In the plasma group, there were 33 altered proteins in GBC compared to the benign biliary pathology group. We found 9 proteins (APOA1, APOA2, RET4, TTR, HEMO, HBB, HBA, PIGR, and APOE) to be commonly dysregulated in both tissue and plasma. Furthermore, a subset analysis demonstrated that 2 proteins, S100A8 and S100A9, were downregulated in GBC patients with GD history compared to those without. Pathway analysis showed that the dysregulated proteins in GBC patients were enriched in pathways involved in smooth muscle contraction, metabolism, ECM organization, and integrin cell surface interactions. CONCLUSION: The identified dysregulated proteins help in understanding GBC molecular mechanisms in our patient group. Furthermore, the alteration of specific proteins in both tissue and plasma samples suggests their potential utility as biomarkers of GBC in this sample cohort.

Proteomic analysis of sialoliths from calcified, lipid and mixed groups as a source of potential biomarkers of deposit formation in the salivary glands.

Salivary stones, also known as sialoliths, are formed in a pathological situation in the salivary glands. So far, neither the mechanism of their formation nor the factors predisposing to their formation are known despite several hypotheses. While they do not directly threaten human life, they significantly deteriorate the patient's quality of life. Although this is not a typical research material, attempts are made to apply various analytical tools to characterise sialoliths and search for the biomarkers in their proteomes. In this work, we used mass spectrometry and SWATH-MS qualitative and quantitative analysis to investigate the composition and select proteins that may contribute to solid deposits in the salivary glands. Twenty sialoliths, previously characterized spectroscopically and divided into the following groups: calcified (CAL), lipid (LIP) and mixed (MIX), were used for the study. Proteins unique for each of the groups were found, including: for the CAL group among them, e.g. proteins from the S100 group (S100 A8/A12 and P), mucin 7 (MUC7), keratins (KRT1/2/4/5/13), elastase (ELANE) or stomatin (STOM); proteins for the LIP group-transthyretin (TTR), lactotransferrin (LTF), matrix Gla protein (MPG), submandibular gland androgen-regulated protein 3 (SMR3A); mixed stones had the fewest unique proteins. Bacterial proteins present in sialoliths have also been identified. The analysis of the results indicates the possible role of bacterial infections, disturbances in calcium metabolism and neutrophil extracellular traps (NETs) in the formation of sialoliths.

Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

BACKGROUND: Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking. METHODS: Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses. RESULTS: The resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched. CONCLUSIONS: The in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

Liquid chromatography and differential mobility spectrometry-data-independent mass spectrometry for comprehensive multidimensional separations in metabolomics.

The benefits of combining drift time ion mobility (DTIMS) with liquid chromatography-high-resolution mass spectrometry (HRMS) have been reported for metabolomics but the use of differential time mobility spectrometry (DMS) is less obvious due to the need for rapid scanning of the DMS cell. Drift DTIMS provides additional precursor ion selectivity and collisional cross-section information but the separation resolution between analytes remains cell- and component-dependent. With DMS, the addition of 2-propanol modifier can improve the selectivity but on cost of analyte MS response. In the present work, we investigate the liquid chromatography-mass spectrometry (LC-MS) analysis of a mix of 50 analytes, representative for urine and plasma metabolites, using scanning DMS with the single modifiers cyclohexane (Ch), toluene (Tol), acetonitrile (ACN), ethanol (EtOH), and 2-propanol (IPA), and a binary modifier mixture (cyclohexane/2-propanol) with emphasis on selectivity and signal sensitivity. 1.5% IPA in the N2 stream was found to suppress the signal of 50% of the analytes which could be partially recovered with the use of IPA to 0.05% as a Ch/IPA mixture. The potential to use the separation voltage/compensation voltage/modifier (SV/CoV/Mod) feature as an additional analyte identifier for qualitative analysis is also presented and applied to a data-independent LCxDMS-SWATH-MS workflow for the analysis of endogenous metabolites and drugs of abuse in human urine samples from traffic control.

Proteomic characterization and comparison of milk fat globule membrane proteins of Saanen goat milk from 3 habitats in China using SWATH-MS technique.

Saanen goats are among the major dairy goats in China. In present study, variation of milk fat globule membrane proteins profile of Saanen goat milk caused by geographic location was investigated using sequential window acquisition of all theoretical fragment ions data-independent acquisition mass spectrometry based proteomic approach. A total of 1,001 proteins were quantified in goat milk collected from 3 habitats of China [Guangdong (GD); Inner Mongolia (IM); Shannxi (SX)]. Most of the proteins were found to act cellular process of biological process, cell of cellular component, binding of molecular function after Gene Ontology annotation and metabolic of pathway indicated by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Differentially expressed proteins (DEP) for GD versus IM, GD versus SX, IM versus SX were identified to be 81, 91, and 44, respectively. Gene Ontology enrichment analysis showed that the greatest DEP for 3 groups (GD vs. IM, GD vs. SX, IM vs. SX) were cellular process, cellular process and organonitrogen compound biosynthetic process/immune system process for biological process. For cellular component, the largest number of DEP for 3 comparison groups were organelle, organelle and organelle/intracellular. For molecular function, DEP of the 3 comparison groups were expressed most in structural molecule activity, binding and anion binding, respectively. Pathways with the majority of DEP were ribosome, systemic lupus erythematosus and primary immunodeficiency/systemic lupus erythematosus/amoebiasis/PI3K-Akt signaling pathway for GD versus IM, GD versus SX and IM versus SX, severally. Protein-protein interaction network analysis showed that DEP interacted most were 40S ribosomal protein S5, fibronectin and Cytochrome b-c1 complex subunit 2, mitochondrial for GD versus IM, GD versus SX and IM versus SX, separately. Data may give useful information for goat milk selection and milk authenticity in China.

SWATH-MS-Based Proteomics Reveals the Regulatory Metabolism of Amaryllidaceae Alkaloids in Three Lycoris Species.

Alkaloids are a class of nitrogen-containing alkaline organic compounds found in nature, with significant biological activity, and are also important active ingredients in Chinese herbal medicine. Amaryllidaceae plants are rich in alkaloids, among which galanthamine, lycorine, and lycoramine are representative. Since the difficulty and high cost of synthesizing alkaloids have been the major obstacles in industrial production, particularly the molecular mechanism underlying alkaloid biosynthesis is largely unknown. Here, we determined the alkaloid content in Lycoris longituba, Lycoris incarnata, and Lycoris sprengeri, and performed a SWATH-MS (sequential window acquisition of all theoretical mass spectra)-based quantitative approach to detect proteome changes in the three Lycoris. A total of 2193 proteins were quantified, of which 720 proteins showed a difference in abundance between Ll and Ls, and 463 proteins showed a difference in abundance between Li and Ls. KEGG enrichment analysis revealed that differentially expressed proteins are distributed in specific biological processes including amino acid metabolism, starch, and sucrose metabolism, implicating a supportive role for Amaryllidaceae alkaloids metabolism in Lycoris. Furthermore, several key genes collectively known as OMT and NMT were identified, which are probably responsible for galanthamine biosynthesis. Interestingly, RNA processing-related proteins were also abundantly detected in alkaloid-rich Ll, suggesting that posttranscriptional regulation such as alternative splicing may contribute to the biosynthesis of Amaryllidaceae alkaloids. Taken together, our SWATH-MS-based proteomic investigation may reveal the differences in alkaloid contents at the protein levels, providing a comprehensive proteome reference for the regulatory metabolism of Amaryllidaceae alkaloids.

Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma.

Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85-0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.

Quantitative proteomic analysis of hepatic tissue in allotetraploid hybridized from red crucian carp and common carp identified crucial proteins and pathways associated with metabolism and growth rate.

Allotetraploid is a new species produced by distant hybridization between red crucian carp (Carassius auratus red var., abbreviated as RCC) and common carp (Cyprinus carpio L., abbreviated as CC). There is a significant difference in growth rate between allotetraploid and its parents. However, the underlying molecular mechanism is largely unknown. In this study, to find direct evidence associated with metabolism and growth rate in protein level, we performed quantitative proteomics analysis on liver tissues between allotetraploid and its parents. A total of 2502 unique proteins were identified and quantified by SWATH-MS in our proteomics profiling. Subsequently, comprehensive bioinformatics analyses including gene ontology enrichment analysis, pathway and network analysis, and protein-protein interaction analysis (PPI) were conducted based on differentially expressed proteins (DEPs) between allotetraploid and its parents. The results revealed several significant DEPs involved in metabolism pathways in liver. More specifically, the integrative analysis highlighted that the DEPs ACSBG1, OAT, and LDHBA play vital roles in metabolism pathways including "pentose phosphate pathway," "TCA cycle," and "glycolysis and gluconeogenesis." These could directly affect the growth rate in fresh water fishes by regulating the metabolism, utilization, and exchange of substance and energy. Since the liver is the central place for metabolism activity in animals, we firstly established the comprehensive and quantitative proteomics knowledge base for liver tissue from freshwater fishes, our study may serve as an irreplaceable reference for further studies regarding fishes' culture and growth.

A prostate cancer tissue specific spectral library for targeted proteomic analysis.

Prostate cancer is the most common cancer in males worldwide. Mass spectrometry-based targeted proteomics has demonstrated great potential in quantifying proteins from formalin-fixed paraffin-embedded (FFPE) and (fresh) frozen biopsy tissues. Here we provide a comprehensive tissue-specific spectral library for targeted proteomic analysis of prostate tissue samples. Benign and malignant FFPE prostate tissue samples were processed into peptide samples by pressure cycling technology (PCT)-assisted sample preparation, and fractionated with high-pH reversed phase liquid chromatography (RPLC). Based on data-dependent acquisition (DDA) MS analysis using a TripleTOF 6600, we built a library containing 108,533 precursors, 84,198 peptides and 9384 unique proteins (1% FDR). The applicability of the library was demonstrated in prostate specimens.

Comprehensive kinomic study via a chemical proteomic approach reveals kinome reprogramming in hepatocellular carcinoma tissues.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Kinases are attractive therapeutic targets since they are commonly altered in cancers. Here, to identify kinases of potential therapeutic interest in HCC, a quantitative kinomic study of tumour and adjacent non-tumour liver tissues was performed using a chemical proteomics approach. In total, 124 kinases were found differentially expressed and they were distributed over all nine kinase groups. Exploration of The Cancer Genome Atlas (TCGA) data showed that the dysregulation of 45 kinases was correlated with poor prognosis in HCC patients. We then tested 11 inhibitors targeting 12 crucial protein kinases alone or in combination for their ability to inhibit cell growth in Hep3B and PLC/PRF/5 cell lines. Six inhibitors significantly reduced viability in both cell lines. Combination inhibition of polo-like kinase 1 (PLK1) and casein kinase 1 epsilon (CSNK1E) significantly induced growth arrest in both cell lines synergistically. In summary, our analysis presents the most complete view of kinome reprogramming in HCC and provides novel insight into crucial kinases in HCC and potential therapeutic targets for HCC treatment. Moreover, the identification of hundreds of differentially expressed kinases forms a rich resource for novel drug targets or diagnostic biomarker discovery. Data are available via ProteomeXchange (identifier PXD023806).