Probability-based protein identification by searching sequence databases using mass spectrometry data

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Cryo-EM analysis of Pseudomonas phage Pa193 structural components

The World Health Organization has designated Pseudomonas aeruginosa as a critical pathogen for the development of new antimicrobials. Bacterial viruses, or bacteriophages, have been used in various clinical settings, commonly called phage therapy, to address this growing public health crisis. Here, we describe a high-resolution structural atlas of a therapeutic, contractile-tailed Pseudomonas phage, Pa193. We used bioinformatics, proteomics, and cryogenic electron microscopy single particle analysis to identify, annotate, and build atomic models for 21 distinct structural polypeptide chains forming the icosahedral capsid, neck, contractile tail, and baseplate. We identified a putative scaffolding protein stabilizing the interior of the capsid 5-fold vertex. We also visualized a large portion of Pa193 ~ 500 Å long tail fibers and resolved the interface between the baseplate and tail fibers. The work presented here provides a framework to support a better understanding of phages as biomedicines for phage therapy and inform engineering opportunities.

A Concise Guide to Essential R Packages for Analyses of DNA, RNA, and Proteins

R is widely regarded as unrivalled by other high-level programming languages for its statistical functions. The popularity of R as a statistical language has led many to overlook its applications outside the statistical realm. In this brief review, we present a list of R packages for supporting projects that entail analyses of DNA, RNA, and proteins. These R packages span the gamut of important molecular techniques, from routine quantitative PCR and Western blotting to high-throughput sequencing and proteomics generating very large datasets. The text-mining power of R can also be harnessed to facilitate literature reviews and predict future research trends and avenues. We encourage researchers to make full use of R in their work, given the versatility of the language, as well as its straightforward syntax which eases the initial learning curve.

Influence of Software Settings on the Identification Rate, Quantification Results, and Reproducibility in Profiling Post-Translational Modifications by Microflow Liquid Chromatography-Ion Mobility-Quadrupole Time-Of-Flight Analysis Using PEAKS Software

The influence of data evaluation parameters on qualitative and quantitative results of untargeted shotgun profiling of enzymatic and nonenzymatic post-translational modifications (PTMs) was investigated in a model of bovine whey protein α-lactalbumin heated with lactose. Based on the same raw data, individual adjustments to the protein database and enzyme settings of PEAKS studio software increased the identification rate from 27 unmodified peptides to 48 and from 322 peptides in total to 535. The qualitative and quantitative reproducibility was also assessed based on 18 measurements of one sample across three batches. A total of 570 peptides were detected. While 89 peptides were identified in all measurements, the majority of peptides (161) were detected only once and mostly based on nonindicative spectra. The reproducibility of label-free quantification (LFQ) in six measurements of the same sample was similar after processing the data by either the PTM algorithm or the LFQ algorithm. In both cases, about one-third of the peptides showed a coefficient of variation of above 20%. However, the LFQ algorithm increased the number of quantified peptides from 75 to 179. Data are available at the PRIDE Archive with the data set identifier PXD050363.

The TRIM4 E3 ubiquitin ligase degrades TPL2 and is modulated by oncogenic KRAS

Loss-of-function mutations in the C terminus of TPL2 kinase promote oncogenesis by impeding its proteasomal degradation, leading to sustained protein expression. However, the degradation mechanism for TPL2 has remained elusive. Through proximity-dependent biotin identification (BioID), we uncovered tripartite motif-containing 4 (TRIM4) as the E3 ligase that binds and degrades TPL2 by polyubiquitination of lysines 415 and 439. The naturally occurring TPL2 mutants R442H and E188K exhibit impaired TRIM4 binding, enhancing their stability. We further discovered that TRIM4 itself is stabilized by another E3 ligase, TRIM21, which in turn is regulated by KRAS. Mutant KRAS recruits RNF185 to degrade TRIM21 and subsequently TRIM4, thereby stabilizing TPL2. In the presence of mutant KRAS, TPL2 phosphorylates and degrades GSK3β, resulting in β-catenin stabilization and activation of the Wnt pathway. These findings elucidate the physiological mechanisms regulating TPL2 and its exploitation by mutant KRAS, underscoring the need to develop TPL2 inhibitors for KRAS-mutant cancers.

An integrated multi-omics analysis of the effects of the food processing-induced contaminant 2-monochloropropane-1,3-diol (2-MCPD) in rat heart

Many foods including edible oils contain 2-monochloropropane-1,3-diol (2-MCPD), a processing-induced chemical contaminant. Cardiotoxic effects have been shown to result from oral 2-MCPD exposure in rodents, but the underlying mechanisms of action remain poorly understood. We undertook a comprehensive multi-omics approach to assess changes at the transcriptomic, proteomic, and oxylipin levels in heart tissues from male F344 rats that were exposed to 0 or 40 mg/kg BW/day of 2-MCPD in the diet for 90 days, in a regulatory compliant rodent bioassay. Heart tissues were collected for RNA sequencing, quantitative PCR analysis, proteomic analysis via two-dimensional gel electrophoresis and mass spectrometry, and targeted lipidomic profiling by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Transcriptomic and proteomic data analyses revealed upregulation of immune/inflammatory response processes and downregulation of energy metabolism and cardiac structure and functions. Among differentially expressed gene-protein pairs, coronin-1A, a key leukocyte-regulating protein, emerged as markedly up-regulated. Oxylipin profiling highlighted a selective suppression of docosahexaenoic acid-derived metabolites, suggesting a disruption in cardioprotective lipid pathways. These findings suggest that 2-MCPD disrupts homeostasis through inflammatory activation and suppression of metabolic and cardiac function. This research provides insights into 2-MCPD's cardiotoxicity, emphasizing the need for further studies to support hazard characterization.

Tissue-specific accumulation of PIP aquaporins of a particular heteromeric composition is part of the maize response to mycorrhiza and drought

The systemic coordination of accumulation of plasma membrane aquaporins (PIP) was investigated in this study in relation to mycorrhized maize response to a rapid development of severe drought followed by rewatering. In non-mycorrhizal roots, drought led to a drop in PIP abundance, followed by a transient increase under rewatering, whereas leaves showed an opposite pattern. In contrast, mycorrhiza contributed to maintenance of high and stable levels of PIPs in both plant organs after an initial increase, prolonged over the irrigation period. Isoelectric focusing electrophoresis resolved up to 13 aquaporin complexes with highly reproducible pl positions across leaf and root samples, symbiotic and non-symbiotic, stressed or not. Mass spectrometry recognized in leaves and roots a different ratio of PIP1 and PIP2 subunits within 2D spots that accumulated the most. Regardless of symbiotic status, drought regulation of aquaporins in roots was manifested as the prevalence of complexes that comprise almost exclusively PIP2 monomers. In contrast, the leaf response involved enrichment in PIP1s. PIP1s are thought to enhance water transport, facilitate CO2 diffusion but also affect stomatal movements. These features, together with elevated aquaporin levels, might explain a stress tolerance mechanism observed in mycorrhizal plants, resulting in faster recovery of stomatal water conductance and CO2 assimilation rate after drought.

Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia

BACKGROUND

Acute myeloid leukaemia (AML) is a bone marrow malignancy with poor prognosis. One of several treatments for AML is midostaurin combined with intensive chemotherapy (MIC), currently approved for FLT3 mutation-positive (FLT3-MP) AML. However, many patients carrying FLT3 mutations are refractory or experience an early relapse following MIC treatment, and might benefit more from receiving a different treatment. Development of a stratification method that outperforms FLT3 mutational status in predicting MIC response would thus benefit a large number of patients.

METHODS

We employed mass spectrometry phosphoproteomics to analyse 71 diagnosis samples of 47 patients with FLT3-MP AML who subsequently received MIC. We then used machine learning to identify biomarkers of response to MIC, and validated the resulting predictive model in two independent validation cohorts (n = 20).

FINDINGS

We identified three distinct phosphoproteomic AML subtypes amongst long-term survivors. The subtypes showed similar duration of MIC response, but different modulation of AML-implicated pathways, and exhibited distinct, highly-predictive biomarkers of MIC response. Using these biomarkers, we built a phosphoproteomics-based predictive model of MIC response, which we called MPhos. When applied to two retrospective real-world patient test cohorts (n = 20), MPhos predicted MIC response with 83% sensitivity and 100% specificity (log-rank p < 7∗10-5, HR = 0.005 [95% CI: 0-0.31]).

INTERPRETATION

In validation, MPhos outperformed the currently-used FLT3-based stratification method. Our findings have the potential to transform clinical decision-making, and highlight the important role that phosphoproteomics is destined to play in precision oncology.

FUNDING

This work was funded by Innovate UK grants (application numbers: 22217 and 10054602) and by Kinomica Ltd.

Comparison of cat stone matrix and cat urine proteomes to human calcium oxalate stone matrix and urine proteomes

Cat calcium oxalate monohydrate kidney stone matrix proteome showed great similarity to human calcium oxalate monohydrate stone matrix proteome, but inference of mechanistic similarity was limited by the absence of cat urine proteomic data. In this study, urine proteome distributions were measured by the same methods in 7 healthy cats for comparison to both the published human urine and cat calcium oxalate stone matrix proteomes to assess for similar enrichment patterns in both species. Furthermore, proteomic distributions were determined in cat struvite stone matrix to test for similarity to calcium oxalate monohydrate stone matrix and urine proteomes. Cat urine proteins demonstrated a similar distribution of abundance as a function of isoelectric points or net charge to human urine samples, and consequently the similarly altered patterns of protein distributions seen in calcium oxalate monohydrate stone matrix seen from both cat and human stones likely derives from the same preferential adsorption mechanism. Furthermore, the fact that protein abundance patterns seen in cat struvite stone matrix samples differ from both urine and calcium oxalate monohydrate stone matrix proteomes in systematic ways suggests that a combination of protein-protein and protein crystal interactions underly the formation of the crystal aggregates that comprise stones.

Exploring Protein Post-Translational Modifications of Breast Cancer Cells Using a Novel Combinatorial Search Algorithm

Post-translational modification of proteins plays an important role in cancer cell biology. Proteins encoded by oncogenes may be activated by phosphorylation, products of tumour suppressors might be inactivated by phosphorylation or ubiquitinylation, which marks them for degradation; chromatin-binding proteins are often methylated and/or acetylated. These are just a few of the many hundreds of post-translational modifications discovered by years of painstaking experimentation and the chemical analysis of purified proteins. In recent years, mass spectrometry-based proteomics emerged as the principal technique for identifying such modifications in samples from cultured cells and tumour tissue. Here, we used a recently developed combinatorial search algorithm implemented in the MGVB toolset to identify novel modifications in samples from breast cancer cell lines. Our results provide a rich resource of coupled protein abundance and post-translational modification data seen in the context of an important biological function-the response of cells to interferon gamma treatment-which can serve as a starting point for future investigations to validate promising modifications and explore the utility of the underlying molecular mechanisms as potential diagnostic or therapeutic targets.

Deciphering Host-Parasite Interplay in Leishmania Infection through a One Health View of Proteomics Studies on Drug Resistance

Recent efforts in the study of vector-borne parasitic diseases (VBPDs) have emphasized an increased consideration for preventing drug resistance and promoting the environmental safety of drugs, from the beginning of the drug discovery pipeline. The intensive use of the few available antileishmanial drugs has led to the spreading of hyper-resistant Leishmania infantum strains, resulting in a chronic burden of the disease. In the present work, we have investigated the biochemical mechanisms of resistance to antimonials, paromomycin, and miltefosine in three drug-resistant parasitic strains from human clinical isolates, using a whole-cell mass spectrometry proteomics approach. We identified 14 differentially expressed proteins that were validated with their transcripts. Next, we employed functional association networks to identify parasite-specific proteins as potential targets for novel drug discovery studies. We used SeqAPASS analysis to predict susceptibility based on the evolutionary conservation of protein drug targets across species. MATH-domain-containing protein, adenosine triphosphate (ATP)-binding cassette B2, histone H4, calpain-like cysteine peptidase, and trypanothione reductase emerged as top candidates. Overall, this work identifies new biological targets for designing drugs to prevent the development of Leishmania drug resistance, while aligning with One Health principles that emphasize the interconnected health of people, animals, and ecosystems.

In-Depth Host Cell Protein Analysis and Viral Protein Impurity Monitoring in Adeno-Associated Virus-Based Gene Therapy Products Using Optimized Wide Window Data-Dependent Acquisition Method

Compared to other protein therapeutics, there is currently limited knowledge about the residual host cell proteins (HCPs) in adeno-associated virus (AAV)-based gene therapy products. This is primarily due to the lack of a robust and sensitive mass spectrometry-based method for HCP analysis in AAV samples. Existing liquid chromatography-mass spectrometry methods used for analyzing HCPs in therapeutic monoclonal antibodies (mAbs) often cannot be directly applied to AAVs, due to some unique characteristics of AAV samples encountered during their development such as limited sample availability/protein concentration and the presence of surfactants. In this study, we have developed a novel workflow for robust and in-depth HCP analysis of AAV samples by combining wide-window data-dependent acquisition for improved low-abundance HCP detection with single-pot, solid-phase-enhanced sample preparation (SP3) for low-input sample preparation. Using this newly developed method, we were able to detect more than 650 HCPs in a commercial AAV1 sample with a high quantitative reproducibility. This represents a greater than 5-fold increase in HCP protein identification compared to an in-solution digestion method followed by traditional data-dependent acquisition. Similar benefits can also be achieved for other AAV serotypes that were produced internally and purified through different processes. The detection limit of this method is as low as 0.06 ng/mL, enabling more comprehensive HCP coverage in AAV samples. Moreover, for the first time, we have identified several process-related viral proteins, such as Rep 78 and E4. These proteins need to be closely monitored during AAV process development as they may present a greater risk for immunogenicity compared to HCPs that are derived from human HEK293 cells.

Detection of gluten peptides in human duodenal fluids with immuno-liquid chromatography-mass spectrometry

Gluten proteins are storage proteins in wheat that exhibit a certain resistance to gastrointestinal digestion. To explore solutions to cope with accidental ingestion of gluten in individuals suffering from gluten-related disorders, it is essential to monitor the fate of gluten peptides in biological samples, i.e., gastrointestinal juices, blood plasma or urine. In this work, we aimed at developing a mass spectrometry (MS)-based method for measuring gluten peptides in human duodenal fluids. Seven gluten peptides, including the well-documented 33-mer gluten peptide (LQLQPFPQPQLPYPQPQLPYPQPQLPYPQPQPF), were selected after a literature review and characterization of a gluten-containing product. Isotopically labelled peptides were used as references and a targeted liquid chromatography (LC) MS assay based on high resolution parallel reaction monitoring (PRM) was designed. Despite iterative and fine tuning of the LC-PRM-MS method, the low level of endogenous gluten peptides in human duodenal fluid samples precluded their direct detection. Thus, an initial immunoprecipitation (IP) step was included. Several antibodies were tested, and one proved reliable for the enrichment of the 33-mer gluten peptide as well as a few additional gluten peptides. Figures-of-merits of the immuno-LC-PRM-MS assay were assessed with a focus on quantification trueness and precision. We have developed an MS-based method for measuring the 33-mer gluten peptide in human duodenal fluids. Based on isotopic dilution, the method relies on the combination of IP and LC-PRM-MS analysis. Measurements were shown to be sensitive, quantitative, and reproducible.

Detection, isolation and characterization of phage-host complexes using BONCAT and click chemistry

Introduction

Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation and accurate prediction of the host specificity of phages as well as in the identification of newly replicated virions in response to environmental challenges.

Methods

A new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allowed the combined analysis of phages and their hosts, the identification of newly replicated virions, and the specific tagging of phages with biotin for affinity chromatography.

Results

Replication of phage λ in Escherichia coli was selected as a model for workflow development. Specific labeling of phage λ proteins with the non-canonical amino acid 4-azido-L-homoalanine (AHA) during phage development in E. coli was confirmed by LC-MS/MS. Subsequent tagging of AHA with fluorescent dyes via CC allowed the visualization of phages adsorbed to the cell surface by fluorescence microscopy. Flow cytometry enabled the automated detection of these fluorescent phage-host complexes. Alternatively, AHA-labeled phages were tagged with biotin for purification by affinity chromatography. Despite biotinylation the tagged phages could be purified and were infectious after purification.

Discussion

Applying this approach to environmental samples would enable host screening without cultivation. A flexible and powerful workflow for the detection and enrichment of phages and their hosts in pure cultures has been established. The developed method lays the groundwork for future workflows that could enable the isolation of phage-host complexes from diverse complex microbial communities using fluorescence-activated cell sorting or biotin purification. The ability to expand and customize the workflow through the growing range of compounds for CC offers the potential to develop a versatile toolbox in phage research. This work provides a starting point for these further studies by providing a comprehensive standard operating procedure.

Analysis of serum proteomic profiles of endangered Siamese and Burmese Eld's deer infected with subclinical Babesia bovis in Thailand

The endangered Eld's deer is a conserved species in Thailand, where tropical parasitic infections are endemic. Although Eld's deer with babesiosis are generally asymptomatic, they can still harbor the parasite and serve as reservoirs for ticks, spreading the infection to healthy animals within the herd. The present study aimed to investigate potential serum proteome biomarkers of Eld's deer with subclinical Babesia bovis infection. A total of 67 blood samples were collected from captive Siamese and Burmese Eld's deer showing no signs of parasitic infection. The nested polymerase chain reaction (nPCR) of a conserved spherical body protein 2 (sbp-2) gene of B. bovis was utilized to classify Eld's deer groups, with 25.37 % (17/67) testing positive for B. bovis. Additionally, the application of proteomic studies showed that six B. bovis proteins, such as Obg-like ATPase 1 (OLA1) and heat shock protein 90 (HSP90), were significantly upregulated by more than a two-fold change compared with the PCR-negative samples. Of the 55 overexpressed serum proteins in the PCR-positives, alpha 2-HS glycoprotein (AHSG) and immunoglobulin lambda variable 2-8 (IGLV2-8) were notably among the top 10 proteins with the highest area under curve (AUC) values. Hence, they were proposed as potential biomarkers for subclinical B. bovis infection in Eld's deer. Analysis of the protein interaction network revealed interactions between Eld's deer AHSG and B. bovis OLA1 and HSP90, alongside associations with other proteins such as erb-b2 receptor tyrosine kinase 2 (ERBB2) and epidermal growth factor receptor (EGFR). These interactions were involved in the immune system pathway and inflammatory responses. Our findings shed light on subclinical infection of B. bovis in Eld's deer and identify potential biomarkers, contributing to the further effective detection and monitoring of B. bovis infection in this endangered species.

Quantitative proteome analysis of LAP1-deficient human fibroblasts: A pilot approach for predicting the signaling pathways deregulated in LAP1-associated diseases

Lamina-associated polypeptide 1 (LAP1), a ubiquitously expressed nuclear envelope protein, appears to be essential for the maintenance of cell homeostasis. Although rare, mutations in the human LAP1-encoding TOR1AIP1 gene cause severe diseases and can culminate in the premature death of affected individuals. Despite there is increasing evidence of the pathogenicity of TOR1AIP1 mutations, the current knowledge on LAP1's physiological roles in humans is limited; hence, investigation is required to elucidate the critical functions of this protein, which can be achieved by uncovering the molecular consequences of LAP1 depletion, a topic that remains largely unexplored. In this work, the proteome of patient-derived LAP1-deficient fibroblasts carrying a pathological TOR1AIP1 mutation (LAP1 E482A) was quantitatively analyzed to identify global changes in protein abundance levels relatively to control fibroblasts. An in silico functional enrichment analysis of the mass spectrometry-identified differentially expressed proteins was also performed, along with additional in vitro functional assays, to unveil the biological processes that are potentially dysfunctional in LAP1 E482A fibroblasts. Collectively, our findings suggest that LAP1 deficiency may induce significant alterations in various cellular activities, including DNA repair, messenger RNA degradation/translation, proteostasis and glutathione metabolism/antioxidant response. This study sheds light on possible new functions of human LAP1 and could set the basis for subsequent in-depth mechanistic investigations. Moreover, by identifying deregulated signaling pathways in LAP1-deficient cells, our work may offer valuable molecular targets for future disease-modifying therapies for TOR1AIP1-associated nuclear envelopathies.

Innovations Toward Immunopeptidomics

Over the past 30 years, immunopeptidomics has grown alongside improvements in mass spectrometry technology, genomics, transcriptomics, T cell receptor sequencing, and immunological assays to identify and characterize the targets of activated T cells. Together, multiple research groups with expertise in immunology, biochemistry, chemistry, and peptide mass spectrometry have come together to enable the isolation and sequence identification of endogenous major histocompatibility complex (MHC)-bound peptides. The idea to apply highly sensitive mass spectrometry techniques to study the landscape of peptide antigens presented by cell surface MHCs was innovative and continues to be successfully used and improved upon to deepen our understanding of how peptide antigens are processed and presented to T cells. Multiple research groups were involved in this bringing immunopeptidomics to the forefront of translational research, and we will highlight the contributions of one of the earliest developers, Professor Donald F. Hunt, and his research group at the University of Virginia. The Hunt laboratory applied cutting edge mass spectroscopy-based immunopeptidomics to study cancer, autoimmunity, transplant rejection, and infectious diseases. Across these diverse research areas, the Hunt laboratory and collaborators would characterize previously unknown MHC peptide-binding motifs and identify immunologically active antigens using ultra sensitive mass spectrometry techniques. Amazingly, many of the MHC-bound peptide antigens discovered in collaborations with the Hunt laboratory were sequenced by mass spectrometry before the completion of the human genome using manual de novo sequencing. In this perspective article, we will chronicle the work of the Hunt laboratory and their many collaborators that would be a major part of the foundation for mass spectrometry-based immunopeptidomics and its application to immunology research.

Unveiling the role of protein kinase A (PKA) activity in bovine oviductal epithelial cells: implications on apoptotic signaling pathways during the estrous cycle

The complex interactome crucial for successful pregnancy is constituted by the intricate network of endocrine and paracrine signaling pathways, involving gametes, embryos, and the female reproductive tract. Specifically, the oviduct exhibits distinct responses to gametes and early embryos during particular phases of the estrus cycle, a process tightly regulated by reproductive hormones. Moreover, these hormones play a pivotal role in orchestrating cyclical changes within oviductal epithelial cells. To unravel the molecular mechanisms underlying these dynamic changes, our study aimed to investigate the involvement of protein kinase A (PKA) in oviductal epithelial cells throughout the estrus cycle and in advanced pregnancy, extending our studies to oviductal epithelial cell in primary culture. By a combination of 2D-gel electrophoresis, Western blotting, and mass spectrometry, we identified 17 proteins exhibiting differential phosphorylation status mediated by PKA. Among these proteins, we successfully validated the phosphorylation status of heat shock 70 kDa protein (HSP70), aconitase 2 (ACO2), and lamin B1 (LMNB1). Our findings unequivocally demonstrate the dynamic regulation of PKA throughout the estrus cycle in oviductal epithelial cells. Also, analysis by bioinformatics tools suggest its pivotal role in mediating cyclical changes possibly through modulation of apoptotic pathways. This research sheds light on the intricate molecular mechanisms underlying reproductive processes, with implications for understanding fertility and reproductive health.

Death-associated protein kinase 3 modulates migration and invasion of triple-negative breast cancer cells

Sixteen patient-derived xenografts (PDXs) were analyzed using a mass spectrometry (MS)-based kinase inhibitor pull-down assay (KIPA), leading to the observation that death-associated protein kinase 3 (DAPK3) is significantly and specifically overexpressed in the triple-negative breast cancer (TNBC) models. Validation studies confirmed enrichment of DAPK3 protein, in both TNBC cell lines and tumors, independent of mRNA levels. Genomic knockout of DAPK3 in TNBC cell lines inhibited in vitro migration and invasion, along with down-regulation of an epithelial-mesenchymal transition (EMT) signature, which was confirmed in vivo. The kinase and leucine-zipper domains within DAPK3 were shown by a mutational analysis to be essential for functionality. Notably, DAPK3 was found to inhibit the levels of desmoplakin (DSP), a crucial component of the desmosome complex, thereby explaining the observed migration and invasion effects. Further exploration with immunoprecipitation-mass spectrometry (IP-MS) identified that leucine-zipper protein 1 (LUZP1) is a preferential binding partner of DAPK3. LUZP1 engages in a leucine-zipper domain-mediated interaction that protects DAPK3 from proteasomal degradation. Thus, the DAPK3/LUZP1 heterodimer emerges as a newly discovered regulator of EMT/desmosome components that promote TNBC cell migration.

GRA47 is important for the morphology and permeability of the parasitophorous vacuole in Toxoplasma gondii

Establishing an intact intracellular parasitophorous vacuole (PV) that enables efficient nutrient uptake and protein trafficking is essential for the survival and proliferation of Toxoplasma gondii. Although the PV membrane (PVM)-localized dense granule protein 17 (GRA17) and GRA23 mediate the permeability of the PVM to small molecules, including nutrient uptake and excretion of metabolic by-products, the molecular mechanism by which T. gondii acquires nutrients remains unclear. In this study, we showed that the secreted protein GRA47 contributed to normal PV morphology, PVM permeability to small molecules, growth, and virulence in T. gondii. Co-immunoprecipitation analysis demonstrated potential interaction of GRA47 with GRA72, and the loss of GRA72 affected PV morphology, parasite growth and infectivity. To investigate the biological relationship among GRA47, GRA72, GRA17 and GRA23, attempts were made to construct strains with double gene deletion and overexpressing strains. Only Δgra23Δgra72 was successfully constructed. This strain exhibited a significant increase in the proportion of aberrant PVs compared with the Δgra23 strain. Overexpressing one of the three related GRAs partially rescued PVs with aberrant morphology in Δgra47, Δgra72 and Δgra17, while the expression of the Plasmodium falciparum PVM protein PfExp2, an ortholog of GRA17 and GRA23, fully rescued the PV morphological defect in all three Δgra strains. These results suggest that these GRA proteins may not be functionally redundant but rather work in different ways to regulate nutrient acquisition. These findings highlight the versatility of the nutrient uptake mechanisms in T. gondii, which may contribute to the parasite's remarkable ability to grow in different cellular niches in a very broad range of hosts.

FAM72A degrades UNG2 through the GID/CTLH complex to promote mutagenic repair during antibody maturation

A diverse antibody repertoire is essential for humoral immunity. Antibody diversification requires the introduction of deoxyuridine (dU) mutations within immunoglobulin genes to initiate somatic hypermutation (SHM) and class switch recombination (CSR). dUs are normally recognized and excised by the base excision repair (BER) protein uracil-DNA glycosylase 2 (UNG2). However, FAM72A downregulates UNG2 permitting dUs to persist and trigger SHM and CSR. How FAM72A promotes UNG2 degradation is unknown. Here, we show that FAM72A recruits a C-terminal to LisH (CTLH) E3 ligase complex to target UNG2 for proteasomal degradation. Deficiency in CTLH complex components result in elevated UNG2 and reduced SHM and CSR. Cryo-EM structural analysis reveals FAM72A directly binds to MKLN1 within the CTLH complex to recruit and ubiquitinate UNG2. Our study further suggests that FAM72A hijacks the CTLH complex to promote mutagenesis in cancer. These findings show that FAM72A is an E3 ligase substrate adaptor critical for humoral immunity and cancer development.

Functional genomic analysis of genes important for Candida albicans fitness in diverse environmental conditions

Fungal pathogens such as Candida albicans pose a significant threat to human health with limited treatment options available. One strategy to expand the therapeutic target space is to identify genes important for pathogen growth in host-relevant environments. Here, we leverage a pooled functional genomic screening strategy to identify genes important for fitness of C. albicans in diverse conditions. We identify an essential gene with no known Saccharomyces cerevisiae homolog, C1_09670C, and demonstrate that it encodes subunit 3 of replication factor A (Rfa3). Furthermore, we apply computational analyses to identify functionally coherent gene clusters and predict gene function. Through this approach, we predict the cell-cycle-associated function of C3_06880W, a previously uncharacterized gene required for fitness specifically at elevated temperatures, and follow-up assays confirm that C3_06880W encodes Iml3, a component of the C. albicans kinetochore with roles in virulence in vivo. Overall, this work reveals insights into the vulnerabilities of C. albicans.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

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.

Proteomic characterization of peanut flour fermented by Rhizopus oryzae

Fermentation alters the protein content and composition of foods. To characterize fungal catabolism of peanut proteins, defatted peanut flour was fermented by Rhizopus oryzae (R. oryzae) for up to 48 h and evaluated by SDS-PAGE, mass spectrometry, and antibody binding. A clear change in peanut protein migration was observed by SDS-PAGE after 16 h of fermentation. Mass spectrometric analysis indicated changes in allergen peptides and R. oryzae proteins. Several low molecular weight allergen fragments produced during fermentation were identified by mass spectrometry. Immunoassays using anti-peanut allergen antibodies demonstrated reduced allergen content as early as 16 h of fermentation. However, ELISA with peanut allergic IgE indicated only slightly reduced allergen binding even after 48 h. These results indicate that while R. oryzae fermentation efficiently metabolizes peanut allergens, significant IgE binding remains in lower molecular mass peptides, and therefore R. oryzae fermented peanut products would not be safe for peanut allergic individuals.

Arabidopsis AGO1 N-terminal extension acts as an essential hub for PRMT5 interaction and post-translational modifications

Plant ARGONAUTE (AGO) proteins play pivotal roles regulating gene expression through small RNA (sRNA) -guided mechanisms. Among the 10 AGO proteins in Arabidopsis thaliana, AGO1 stands out as the main effector of post-transcriptional gene silencing. Intriguingly, a specific region of AGO1, its N-terminal extension (NTE), has garnered attention in recent studies due to its involvement in diverse regulatory functions, including subcellular localization, sRNA loading and interactions with regulatory factors. In the field of post-translational modifications (PTMs), little is known about arginine methylation in Arabidopsis AGOs. In this study, we show that NTE of AGO1 (NTEAGO1) undergoes symmetric arginine dimethylation at specific residues. Moreover, NTEAGO1 interacts with the methyltransferase PRMT5, which catalyzes its methylation. Notably, we observed that the lack of symmetric dimethylarginine has no discernible impact on AGO1's subcellular localization or miRNA loading capabilities. However, the absence of PRMT5 significantly alters the loading of a subgroup of sRNAs into AGO1 and reshapes the NTEAGO1 interactome. Importantly, our research shows that symmetric arginine dimethylation of NTEs is a common process among Arabidopsis AGOs, with AGO1, AGO2, AGO3 and AGO5 undergoing this PTM. Overall, this work deepens our understanding of PTMs in the intricate landscape of RNA-associated gene regulation.

Proteomics and Bioinformatics Identify Drug-Resistant-Related Genes with Prognostic Potential in Cholangiocarcinoma

Drug resistance is a major challenge in the treatment of advanced cholangiocarcinoma (CCA). Understanding the mechanisms of drug resistance can aid in identifying novel prognostic biomarkers and therapeutic targets to improve treatment efficacy. This study established 5-fluorouracil- (5-FU) and gemcitabine-resistant CCA cell lines, KKU-213FR and KKU-213GR, and utilized comparative proteomics to identify differentially expressed proteins in drug-resistant cells compared to parental cells. Additionally, bioinformatics analyses were conducted to explore the biological and clinical significance of key proteins. The drug-resistant phenotypes of KKU-213FR and KKU-213GR cell lines were confirmed. In addition, these cells demonstrated increased migration and invasion abilities. Proteomics analysis identified 81 differentially expressed proteins in drug-resistant cells, primarily related to binding functions, biological regulation, and metabolic processes. Protein-protein interaction analysis revealed a highly interconnected network involving MET, LAMB1, ITGA3, NOTCH2, CDH2, and NDRG1. siRNA-mediated knockdown of these genes in drug-resistant cell lines attenuated cell migration and cell invasion abilities and increased sensitivity to 5-FU and gemcitabine. The mRNA expression of these genes is upregulated in CCA patient samples and is associated with poor prognosis in gastrointestinal cancers. Furthermore, the functions of these proteins are closely related to the epithelial-mesenchymal transition (EMT) pathway. These findings elucidate the potential molecular mechanisms underlying drug resistance and tumor progression in CCA, providing insights into potential therapeutic targets.

A triple cysteine motif as major determinant of the modulation of neuronal KV7 channels by the paracetamol metabolite N-acetyl-p-benzo quinone imine

BACKGROUND AND PURPOSE

The analgesic action of paracetamol involves KV7 channels, and its metabolite N-acetyl-p-benzo quinone imine (NAPQI), a cysteine modifying reagent, was shown to increase currents through such channels in nociceptors. Modification of cysteine residues by N-ethylmaleimide, H2O2, or nitric oxide has been found to modulate currents through KV7 channels. The study aims to identify whether, and if so which, cysteine residues in neuronal KV7 channels might be responsible for the effects of NAPQI.

EXPERIMENTAL APPROACH

To address this question, we used a combination of perforated patch-clamp recordings, site-directed mutagenesis, and mass spectrometry applied to recombinant KV7.1 to KV7.5 channels.

KEY RESULTS

Currents through the cardiac subtype KV7.1 were reduced by NAPQI. Currents through all other subtypes were increased, either by an isolated shift of the channel voltage dependence to more negative values (KV7.3) or by such a shift combined with increased maximal current levels (KV7.2, KV7.4, KV7.5). A stretch of three cysteine residues in the S2-S3 linker region of KV7.2 was necessary and sufficient to mediate these effects.

CONCLUSION AND IMPLICATION

The paracetamol metabolite N-acetyl-p-benzo quinone imine (NAPQI) modifies cysteine residues of KV7 subunits and reinforces channel gating in homomeric and heteromeric KV7.2 to KV7.5, but not in KV7.1 channels. In KV7.2, a triple cysteine motif located within the S2-S3 linker region mediates this reinforcement that can be expected to reduce the excitability of nociceptors and to mediate antinociceptive actions of paracetamol.

Plasmodium RNA triphosphatase validation as antimalarial target

Target-based approaches have traditionally been used in the search for new anti-infective molecules. Target selection process, a critical step in Drug Discovery, identifies targets that are essential to establish or maintain the infection, tractable to be susceptible for inhibition, selective towards their human ortholog and amenable for large scale purification and high throughput screening. The work presented herein validates the Plasmodium falciparum mRNA 5' triphosphatase (PfPRT1), the first enzymatic step to cap parasite nuclear mRNAs, as a candidate target for the development of new antimalarial compounds. mRNA capping is essential to maintain the integrity and stability of the messengers, allowing their translation. PfPRT1 has been identified as a member of the tunnel, metal dependent mRNA 5' triphosphatase family which differs structurally and mechanistically from human metal independent mRNA 5' triphosphatase. In the present study the essentiality of PfPRT1 was confirmed and molecular biology tools and methods for target purification, enzymatic assessment and target engagement were developed, with the goal of running a future high throughput screening to discover PfPRT1 inhibitors.

Cabozantinib inhibits the growth of lenvatinib-resistant hepatoma cells restoring FTCD expression

Cabozantinib is a newly developed tyrosine kinase inhibitor, which is applied on patients with hepatocellular carcinoma (HCC) unresponsive to conventional tyrosine kinase inhibitors, including lenvatinib. However, the mechanism of cabozantinib efficacy for lenvatinib-resistant tumor cells has not been well established in basic studies. The purpose of this study is to elucidate the mechanisms by which cabozantinib inhibits tumor growth of lenvatinib-resistant hepatocellular carcinoma cell lines in vitro and in vivo. We established a lenvatinib-resistant Hep3B cell line (Hep3B-LR) and evaluated the inhibitory effect of cabozantinib on the growth of Hep3B-LR cells. Hep3B-LR exhibited approximately 20 times greater IC50 for lenvatinib than the wild type. Compared with wild-type Hep3B, Hep3B-LR was characterized by enhanced expression of EGFR, MET and ErbB2. Cabozantinib suppressed tumor growth of Hep3B-LR in vitro and in vivo. Microarray analysis and real-time qPCR using the xenografts revealed cabozantinib downregulated miR-126-3p, a tumor suppressor miRNA, suggesting that miR-126-3p did not contribute to tumor inhibitory effect of cabozantinib. Proteome analysis using xenograft tissues demonstrated an upregulation of FTCD, a tumor suppressor gene, by cabozantinib administration. The enhanced expression of FTCD by cabozantinib was confirmed by western blot and immunohistochemistry analysis. Furthermore, FTCD expression in Hep3B-LR before cabozantinib administration was weaker than that in wild-type Hep3B. FTCD expression was weakened along with acquisition of lenvatinib-resistance, and was restored by cabozantinib administration. FTCD may be a novel therapeutic target of cabozantinib in case of lenvatinib treatment failure.

Anti-tubulin beta 4A (TBB4A) antibody immobilized sperm in a complement-dependent manner in humans

Sperm-immobilizing antibodies (SI-Abs) are detected in the sera of 3 % of infertile women. SI-Abs are occasionally produced as allogeneic antibodies against sperm, causing immune infertility. SI-Abs inhibit the passage of sperm through the female reproductive tract. Research on anti-sperm antibodies (ASA) remains of great importance for population control. We aimed to identify the antigens recognized by SI-Abs and elucidate the pathogenesis of immune infertility. Twelve sperm-immobilization test (SIT)-positive and fourteen SIT-negative sera were analyzed by two-dimensional electrophoresis and western blotting. Antigenic materials were extracted from well-motile sperm prepared using 0.1 % sodium dodecyl sulfate. In total, 22 different spots were detected in the 12 positive sera. Among these, three positive serum samples showed two positive signals with similar migration patterns. The significant positive spots were Mr: 49 K, pI: 5.1 and Mr: 51 K, pI: 5.6. All these positive spots were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS); tubulin beta-4A (TBB4A) was identified from the spot Mr: 49 K, pI: 5.1. TBB4A is a major component of tubulin and constitutes the axoneme in the sperm tail and the centrosome in the sperm neck; it is generally located inside the cell. An authentic antibody against TBB4A showed a positive reaction in the sperm neck and tail regions in an immunofluorescence study. This antibody also inhibited sperm motility in a complement-dependent manner. Sperm membrane permeability reportedly changes during swimming and capacitation. We identified TBB4A as an antigenic molecule recognized by SI-Abs, which may be relevant to immunological contraception in the future.

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

Identification of the proteolytic signature in CVB3-infected cells

Coxsackievirus B3 (CVB3) encodes proteinases that are essential for processing of the translated viral polyprotein. Viral proteinases also target host proteins to manipulate cellular processes and evade innate antiviral responses to promote replication and infection. While some host protein substrates of the CVB3 3C and 2A cysteine proteinases have been identified, the full repertoire of targets is not known. Here, we utilize an unbiased quantitative proteomics-based approach termed terminal amine isotopic labeling of substrates (TAILS) to conduct a global analysis of CVB3 protease-generated N-terminal peptides in both human HeLa and mouse cardiomyocyte (HL-1) cell lines infected with CVB3. We identified >800 proteins that are cleaved in CVB3-infected HeLa and HL-1 cells including the viral polyprotein, known substrates of viral 3C proteinase such as PABP, DDX58, and HNRNPs M, K, and D and novel cellular proteins. Network and GO-term analysis showed an enrichment in biological processes including immune response and activation, RNA processing, and lipid metabolism. We validated a subset of candidate substrates that are cleaved under CVB3 infection and some are direct targets of 3C proteinase in vitro. Moreover, depletion of a subset of TAILS-identified target proteins decreased viral yield. Characterization of two target proteins showed that expression of 3Cpro-targeted cleaved fragments of emerin and aminoacyl-tRNA synthetase complex-interacting multifunctional protein 2 modulated autophagy and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway, respectively. The comprehensive identification of host proteins targeted during virus infection provides insights into the cellular pathways manipulated to facilitate infection.

IMPORTANCE

RNA viruses encode proteases that are responsible for processing viral proteins into their mature form. Viral proteases also target and cleave host cellular proteins; however, the full catalog of these target proteins is incomplete. We use a technique called terminal amine isotopic labeling of substrates (TAILS), an N-terminomics to identify host proteins that are cleaved under virus infection. We identify hundreds of cellular proteins that are cleaved under infection, some of which are targeted directly by viral protease. Revealing these target proteins provides insights into the host cellular pathways and antiviral signaling factors that are modulated to promote virus infection and potentially leading to virus-induced pathogenesis.

LC-MS/MS profiling and analysis of Bacillus licheniformis extracellular proteins for antifungal potential against Candida albicans

Candida albicans, a significant human pathogenic fungus, employs hydrolytic proteases for host invasion. Conventional antifungal agents are reported with resistance issues from around the world. This study investigates the role of Bacillus licheniformis extracellular proteins (ECP) as effective antifungal peptides (AFPs). The aim was to identify and characterize the ECP of B. licheniformis through LC-MS/MS and bioinformatics analysis. LC-MS/MS analysis identified 326 proteins with 69 putative ECP, further analyzed in silico. Of these, 21 peptides exhibited antifungal properties revealed by classAMP tool and are predominantly anionic. Peptide-protein docking revealed interactions between AFPs like Peptide chain release factor 1 (Q65DV1_Seq1: SASEQLSDAK) and Putative carboxy peptidase (Q65IF0_Seq7: SDSSLEDQDFILESK) with C. albicans virulent SAP5 proteins (PDB ID 2QZX), forming hydrogen bonds and significant Pi-Pi interactions. The identification of B. licheniformis ECP is the novelty of the study that sheds light on their antifungal potential. The identified AFPs, particularly those interacting with bonafide pharmaceutical targets SAP5 of C. albicans represent promising avenues for the development of antifungal treatments with AFPs that could be the pursuit of a novel therapeutic strategy against C. albicans. SIGNIFICANCE OF STUDY: The purpose of this work was to carry out proteomic profiling of the secretome of B. licheniformis. Previously, the efficacy of Bacillus licheniformis extracellular proteins against Candida albicans was investigated and documented in a recently communicated manuscript, showcasing the antifungal activity of these proteins. In order to achieve high-throughput identification of ES (Excretory-secretory) proteins, the utilization of liquid chromatography tandem mass spectrometry (LC-MS) was utilized. There was a lack of comprehensive research on AFPs in B. licheniformis, nevertheless. The proteins secreted by B. licheniformis in liquid medium were initially discovered using liquid chromatography-tandem mass spectrometry (LC-MS) analysis and identification in order to immediately characterize the unidentified active metabolites in fermentation broth.

Investigation of coagulation and proteomics profiles in symptomatic feline hypertrophic cardiomyopathy and healthy control cats

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is a crucial heart disease in cats. The clinical manifestations of HCM comprise pulmonary edema, dyspnea, syncope, arterial thromboembolism (ATE), and sudden cardiac death. D-dimer and prothrombin time (PT) are powerful biomarkers used to assess coagulation function. Dysregulation in these two biomarkers may be associated with HCM in cats. This study aims to assess D-dimer levels, PT, and proteomic profiling in healthy cats in comparison to cats with symptomatic HCM.

RESULTS

Twenty-nine client-owned cats with HCM were enrolled, including 15 healthy control and 14 symptomatic HCM cats. The D-dimer concentration and PT were examined. Proteomic analysis was conducted by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry and liquid chromatography-tandem mass spectrometry (LC-MS/MS). In symptomatic cats, D-dimer levels were statistically significantly higher (mean ± SEM: 372.19 ng/ml ± 58.28) than in healthy cats (mean ± SEM: 208.54 ng/ml ± 10.92) with P-value of less than 0.01, while PT was statistically significantly lower in symptomatic cats (mean ± SEM: 9.8 s ± 0.15) compared to healthy cats (mean ± SEM: 11.08 s ± 0.23) with P-value of less than 0.0001. The proteomics analysis revealed upregulation of integrin subunit alpha M (ITGAM), elongin B (ELOB), and fibrillin 2 (FBN2) and downregulation of zinc finger protein 316 (ZNF316) and ectonucleoside triphosphate diphosphohydrolase 8 (ENTPD8) in symptomatic HCM cats. In addition, protein-drug interaction analysis identified the Ras signaling pathway and PI3K-Akt signaling pathway.

CONCLUSIONS

Cats with symptomatic HCM have higher D-dimer and lower PT than healthy cats. Proteomic profiles may be used as potential biomarkers for the detection and management of HCM in cats. The use of D-dimer as a biomarker for HCM detection and the use of proteomic profiling for a better understanding of disease mechanisms remain to be further studied in cats.

APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control

Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.

Direct Identification of Intact Proteins Using a Low-Resolution Mass Spectrometer with CIDn/ETnoD

Over the past decades, proteomics has become increasingly important and a heavily discussed topic. The identification of intact proteins remains a major focus in this field. While most intact proteins are analyzed using high-resolution mass spectrometry, identifying them through low-resolution mass spectrometry continues to pose challenges. In our study, we investigated the capability of identifying various intact proteins using collision-induced dissociation (CID) and electron transfer without dissociation (ETnoD). Using myoglobin as our test protein, stable product ions were generated with CID, and the identities of the product ions were identified with ETnoD. ETnoD uses a short activation time (AcT, 5 ms) to create sequential charge-reduced precursor ion (CRI). The charges of the fragments and their sequences were determined with corresponding CRI. The product ions can be selected for subsequent CID (termed CIDn) combined with ETnoD for further sequence identification and validation. We refer to this method as CIDn/ETnoD. The use of a multistage CID activation (CIDn) and ETnoD protocol has been applied to several intact proteins to obtain multiple sequence identifications.

Soil Metaproteomics for Microbial Community Profiling: Methodologies and Challenges

Soil represents a complex and dynamic ecosystem, hosting a myriad of microorganisms that coexist and play vital roles in nutrient cycling and organic matter transformation. Among these microorganisms, bacteria and fungi are key members of the microbial community, profoundly influencing the fate of nitrogen, sulfur, and carbon in terrestrial environments. Understanding the intricacies of soil ecosystems and the biological processes orchestrated by microbial communities necessitates a deep dive into their composition and metabolic activities. The advent of next-generation sequencing and 'omics' techniques, such as metagenomics and metaproteomics, has revolutionized our understanding of microbial ecology and the functional dynamics of soil microbial communities. Metagenomics enables the identification of microbial community composition in soil, while metaproteomics sheds light on the current biological functions performed by these communities. However, metaproteomics presents several challenges, both technical and computational. Factors such as the presence of humic acids and variations in extraction methods can influence protein yield, while the absence of high-resolution mass spectrometry and comprehensive protein databases limits the depth of protein identification. Notwithstanding these limitations, metaproteomics remains a potent tool for unraveling the intricate biological processes and functions of soil microbial communities. In this review, we delve into the methodologies and challenges of metaproteomics in soil research, covering aspects such as protein extraction, identification, and bioinformatics analysis. Furthermore, we explore the applications of metaproteomics in soil bioremediation, highlighting its potential in addressing environmental challenges.

Interplay between photosynthetic electron flux and organic carbon sinks in sucrose-excreting Synechocystis sp. PCC 6803 revealed by omics approaches

BACKGROUND

Advancing the engineering of photosynthesis-based prokaryotic cell factories is important for sustainable chemical production and requires a deep understanding of the interplay between bioenergetic and metabolic pathways. Rearrangements in photosynthetic electron flow to increase the efficient use of the light energy for carbon fixation must be balanced with a strong carbon sink to avoid photoinhibition. In the cyanobacterium Synechocystis sp. PCC 6803, the flavodiiron protein Flv3 functions as an alternative electron acceptor of photosystem I and represents an interesting engineering target for reorganizing electron flow in attempts to enhance photosynthetic CO2 fixation and increase production yield.

RESULTS

We have shown that inactivation of Flv3 in engineered sucrose-excreting Synechocystis (S02:Δflv3) induces a transition from photoautotrophic sucrose production to mixotrophic growth sustained by sucrose re-uptake and the formation of intracellular carbon sinks such as glycogen and polyhydroxybutyrate. The growth of S02:Δflv3 exceeds that of the sucrose-producing strain (S02) and demonstrates unforeseen proteomic and metabolomic changes over the course of the nine-day cultivation. In the absence of Flv3, a down-regulation of proteins related to photosynthetic light reactions and CO2 assimilation occurred concomitantly with up-regulation of those related to glycolytic pathways, before any differences in sucrose production between S02 and S02:Δflv3 strains were observed. Over time, increased sucrose degradation in S02:Δflv3 led to the upregulation of respiratory pathway components, such as the plastoquinone reductase complexes NDH-11 and NDH-2 and the terminal respiratory oxidases Cyd and Cox, which transfer electrons to O2. While glycolytic metabolism is significantly up-regulated in S02:Δflv3 to provide energy for the cell, the accumulation of intracellular storage compounds and the increase in respiration serve as indirect sinks for photosynthetic electrons.

CONCLUSIONS

Our results show that the presence of strong carbon sink in the engineered sucrose-producing Synechocystis S02 strain, operating under high light, high CO2 and salt stress, cannot compensate for the lack of Flv3 by directly balancing the light transducing source and carbon fixing sink reactions. Instead, the cells immediately sense the imbalance, leading to extensive reprogramming of cellular bioenergetic, metabolic and ion transport pathways that favor mixotrophic growth rather than enhancing photoautotrophic sucrose production.

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities

INTRODUCTION

The human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease.

OBJECTIVES

Here, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics.

METHODS

Comparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data.

RESULTS

Glycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors.

CONCLUSION

Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.

Inferring kinase activity from phosphoproteomic data: Tool comparison and recent applications

Aberrant cellular signaling pathways are a hallmark of cancer and other diseases. One of the most important signaling mechanisms involves protein phosphorylation/dephosphorylation. Protein phosphorylation is catalyzed by protein kinases, and over 530 protein kinases have been identified in the human genome. Aberrant kinase activity is one of the drivers of tumorigenesis and cancer progression and results in altered phosphorylation abundance of downstream substrates. Upstream kinase activity can be inferred from the global collection of phosphorylated substrates. Mass spectrometry-based phosphoproteomic experiments nowadays routinely allow identification and quantitation of >10k phosphosites per biological sample. This substrate phosphorylation footprint can be used to infer upstream kinase activities using tools like Kinase Substrate Enrichment Analysis (KSEA), Posttranslational Modification Substrate Enrichment Analysis (PTM-SEA), and Integrative Inferred Kinase Activity Analysis (INKA). Since the topic of kinase activity inference is very active with many new approaches reported in the past 3 years, we would like to give an overview of the field. In this review, an inventory of kinase activity inference tools, their underlying algorithms, statistical frameworks, kinase-substrate databases, and user-friendliness is presented. The most widely-used tools are compared in-depth. Subsequently, recent applications of the tools are described focusing on clinical tissues and hematological samples. Two main application areas for kinase activity inference tools can be discerned. (1) Maximal biological insights can be obtained from large data sets with group comparisons using multiple complementary tools (e.g., PTM-SEA and KSEA or INKA). (2) In the oncology context where personalized treatment requires analysis of single samples, INKA for example, has emerged as tool that can prioritize actionable kinases for targeted inhibition.

Purification and identification of novel antioxidant peptides derived from Bombyx mori pupae hydrolysates

The biological importance of antioxidant peptides was the focus of new natural sources of food preservatives. Bombyx mori pupae are considered a valuable by-product of the silk-reeling industry due to their high-quality protein content. This study aimed to purify and identify the antioxidant peptides obtained from enzymatically hydrolyzed B. mori pupae, which could be used as new sources of natural food preservatives. Among the prepared hydrolysates, pepsin hydrolysate with the highest antioxidant activities was purified sequentially using ultrafiltration and reversed-phase high-performance liquid chromatography (RP-HPLC). The DPPH radical scavenging and ferrous ion chelating activity were used to evaluate antioxidant activity. Fractions with high activity were further analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Three peptides were identified as Glu-Asn-Ile-Ile-Leu-Phe-Arg (ENIILFR), Leu-Asn-Lys-Asp-Leu-Met-Arg (LNKDLMR), and Met-Leu-Ile-Ile-Ile-Met-Arg (MLIIIMR), respectively. All three novel identified peptides exhibited significantly stronger antioxidant capacity than synthetic antioxidants used in the food industry, including butylated hydroxyanisole (BHA), and butylated hydroxytoluene (BHT). ENIILFR showed the best antioxidant activity. These findings indicate that the three peptides have potential applications as natural antioxidants in the food industry.

Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification

Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.

Molecular expression, purification and structural characterization of recombinant L-Glutaminase from Streptomyces roseolus

The present research reports the anti-cancer potential of recombinant L-Glutaminase from Streptomyces roseolus. L-Glutaminase gene was synthesized by codon-optimization, cloned and successfully expressed in E. coli BL21 (DE3). Affinity purified recombinant L-Glutaminase revealed a molecular mass of 32 kDa. Purified recombinant L-Glutaminase revealed stability at pH 7.0-8.0 with optimum activity at 70 °C further indicating its thermostable nature based on thermodynamic characterization. Recombinant L-Glutaminase exhibited profound stability in the presence of several biochemical parameters and demonstrated its metalloenzyme nature and was also found to be highly specific towards favorable substrate (l-Glutamine) based on kinetics. It demonstrated antioxidant property and pronounced cytotoxic effect against breast cancer (MCF-7 cell lines) in a dose dependent behavior with IC50 of 40.68 μg/mL. Matrix-assisted laser desorption ionization-time of flight-mass spectroscopy (MALDI-TOF-MS) analysis of desired mass peaks ascertained the recombinant L-Glutaminase identity. N-terminal amino acid sequence characterization through Edman degradation revealed highest resemblance for L-glutaminase within the Streptomyces sp. family. The purified protein was characterized structurally and functionally by employing spectroscopic methods like Raman, circular dichroism and nuclear magnetic resonance. The thermostability was assessed by thermogravimetric analysis. The outcomes of the study, suggests the promising application of recombinant L-Glutaminase as targeted therapeutic candidate for breast cancer.

Engineering Mycoplasma pneumoniae to bypass the association with Guillain-Barré syndrome

A non-pathogenic Mycoplasma pneumoniae-based chassis is leading the development of live biotherapeutic products (LBPs) for respiratory diseases. However, reports connecting Guillain-Barré syndrome (GBS) cases to prior M. pneumoniae infections represent a concern for exploiting such a chassis. Galactolipids, especially galactocerebroside (GalCer), are considered the most likely M. pneumoniae antigens triggering autoimmune responses associated with GBS development. In this work, we generated different strains lacking genes involved in galactolipids biosynthesis. Glycolipid profiling of the strains demonstrated that some mutants show a complete lack of galactolipids. Cross-reactivity assays with sera from GBS patients with prior M. pneumoniae infection showed that certain engineered strains exhibit reduced antibody recognition. However, correlation analyses of these results with the glycolipid profile of the engineered strains suggest that other factors different from GalCer contribute to sera recognition, including total ceramide levels, dihexosylceramide (DHCer), and diglycosyldiacylglycerol (DGDAG). Finally, we discuss the best candidate strains as potential GBS-free Mycoplasma chassis.

PeposX-Exhaust: A lightweight and efficient tool for identification of short peptides

Short peptides have become the focus of recent research due to their variable bioactivities, good digestibility and wide existences in food-derived protein hydrolysates. However, due to the high complexity of the samples, identifying short peptides still remains a challenge. In this work, a tool, named PeposX-Exhaust, was developed for short peptide identification. Through validation with known peptides, PeposX-Exhaust identified all the submitted spectra and the accuracy rate reached 75.36%, and the adjusted accuracy rate further reached 98.55% when with top 5 candidates considered. Compared with other tools, the accuracy rate by PeposX-Exhaust was at least 70% higher than two database-search tools and 15% higher than the other two de novo-sequencing tools, respectively. For further application, the numbers of short peptides identified from soybean, walnut, collagen and bonito protein hydrolysates reached 1145, 628, 746 and 681, respectively. This fully demonstrated the superiority of the tool in short peptide identification.

An algorithm for decoy-free false discovery rate estimation in XL-MS/MS proteomics

MOTIVATION

Cross-linking tandem mass spectrometry (XL-MS/MS) is an established analytical platform used to determine distance constraints between residues within a protein or from physically interacting proteins, thus improving our understanding of protein structure and function. To aid biological discovery with XL-MS/MS, it is essential that pairs of chemically linked peptides be accurately identified, a process that requires: (i) database search, that creates a ranked list of candidate peptide pairs for each experimental spectrum and (ii) false discovery rate (FDR) estimation, that determines the probability of a false match in a group of top-ranked peptide pairs with scores above a given threshold. Currently, the only available FDR estimation mechanism in XL-MS/MS is the target-decoy approach (TDA). However, despite its simplicity, TDA has both theoretical and practical limitations that impact the estimation accuracy and increase run time over potential decoy-free approaches (DFAs).

RESULTS

We introduce a novel decoy-free framework for FDR estimation in XL-MS/MS. Our approach relies on multi-sample mixtures of skew normal distributions, where the latent components correspond to the scores of correct peptide pairs (both peptides identified correctly), partially incorrect peptide pairs (one peptide identified correctly, the other incorrectly), and incorrect peptide pairs (both peptides identified incorrectly). To learn these components, we exploit the score distributions of first- and second-ranked peptide-spectrum matches for each experimental spectrum and subsequently estimate FDR using a novel expectation-maximization algorithm with constraints. We evaluate the method on ten datasets and provide evidence that the proposed DFA is theoretically sound and a viable alternative to TDA owing to its good performance in terms of accuracy, variance of estimation, and run time.

AVAILABILITY AND IMPLEMENTATION

https://github.com/shawn-peng/xlms.

Mef2d potentiates type-2 immune responses and allergic lung inflammation

Innate lymphoid cells (ILCs) and adaptive T lymphocytes promote tissue homeostasis and protective immune responses. Their production depends on the transcription factor GATA3, which is further elevated specifically in ILC2s and T helper 2 cells to drive type-2 immunity during tissue repair, allergic disorders, and anti-helminth immunity. The control of this crucial up-regulation is poorly understood. Using CRISPR screens in ILCs we identified previously unappreciated myocyte-specific enhancer factor 2d (Mef2d)-mediated regulation of GATA3-dependent type-2 lymphocyte differentiation. Mef2d-deletion from ILC2s and/or T cells specifically protected against an allergen lung challenge. Mef2d repressed Regnase-1 endonuclease expression to enhance IL-33 receptor production and IL-33 signaling and acted downstream of calcium-mediated signaling to translocate NFAT1 to the nucleus to promote type-2 cytokine-mediated immunity.