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Epilepsy is characterized by hypersynchronous neuronal discharges, which are associated with an increased cerebral metabolic rate of oxygen and ATP demand. Uncontrolled seizure activity (status epilepticus) results in mitochondrial exhaustion and ATP depletion, which potentially generate energy mismatch and neuronal loss. Many cells can adapt to increased energy demand by increasing metabolic capacities. However, acute metabolic adaptation during epileptic activity and its relationship to chronic epilepsy remains poorly understood. We elicited seizure-like events (SLEs) in an in vitro model of status epilepticus for eight hours. Electrophysiological recording and tissue oxygen partial pressure recordings were performed. After eight hours of ongoing SLEs, we used proteomics-based kinetic modeling to evaluate changes in metabolic capacities. We compared our findings regarding acute metabolic adaptation to published proteomic and transcriptomic data from chronic epilepsy patients. Epileptic tissue acutely responded to uninterrupted SLEs by upregulating ATP production capacity. This was achieved by a coordinated increase in the abundance of proteins from the respiratory chain and oxidative phosphorylation system. In contrast, chronic epileptic tissue shows a 25-40% decrease in ATP production capacity. In summary, our study reveals that epilepsy leads to dynamic metabolic changes. Acute epileptic activity boosts ATP production, while chronic epilepsy reduces it significantly.

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Metabolic pathways are affected by the impacts of environmental contaminants underlying a large variability of toxic effects across different species. However, the systematic reconstruction of metabolic pathways remains limited in environmental sentinel species due to the lack of available genomic data in many taxa of animal diversity. In this study we used a multi-omics approach to reconstruct the most comprehensive map of metabolic pathways for a crustacean model in biomonitoring, the amphipod Gammarus fossarum in order to improve the knowledge of the metabolism of this sentinel species. We revisited the assembly of RNA-seq data by de novo approaches to reduce RNA contaminants and transcript redundancy. We also acquired extensive mass spectrometry shotgun proteomic data on several organs from a reference population of G. fossarum males and females to identify organ-specific metabolic profiles. The G. fossarum metabolic pathway reconstruction (available through the metabolic database GamfoCyc) was performed by adapting the genomic tool CycADS and we identified 377 pathways representing 7630 annotated enzymes, 2610 enzymatic reactions and the expression of 858 enzymes was experimentally validated by proteomics. To our knowledge, our analysis provides for the first time a systematic metabolic pathway reconstruction and the proteome profiles of these pathways at the organ level in this sentinel species. As an example, we show an elevated abundance in enzymes involved in ATP biosynthesis and fatty acid beta-oxidation indicative of the high-energy requirement of the gills, or the key anabolic and detoxification role of the hepatopancreatic caeca, as exemplified by the specific expression of the retinoid biosynthetic pathways and glutathione synthesis. In conclusion, the multi-omics data integration performed in this study provides new resources to investigate metabolic processes in crustacean amphipods and their role in mediating the effects of environmental contaminant exposures in sentinel species. SYNOPSIS: This study provide the first evidence that it is possible to combine multiple omics data to exhaustively describe the metabolic network of a model species in ecotoxicology, Gammarus fossarum, for which a reference genome is not yet available.

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BACKGROUND: Research biopsies have great potential to advance scientific knowledge by helping to establish predictors of favourable or unfavourable outcomes in kidney transplantation. We evaluated punch and core biopsies of different sizes to determine the optimal size for clinical use. METHODS: A total of 54 punch biopsies and 18 core needle biopsies were retrieved by three transplant surgeons. Each surgeon obtained three separate 2 mm, 3 mm and 4 mm punch biopsy samples and three 23 mm (length) core needle biopsies from two pig kidneys. RESULTS: 4 mm punch biopsies yielded the greatest amount of protein (2.11 ± 0.41 mg) with good reproducibility between surgeons and biopsy types (Coefficient of Variation ∼ 22.13%). All surgeons found 2 mm biopsies technically challenging to obtain and sample processing was difficult due to the sample size. Shotgun proteomics identified 3853 gene products with no significant difference in the quantitative proteome of 2 mm and 3 mm punch biopsies. However, the expression of 158 Kidney enriched genes, was higher in bigger and deeper 4 mm punch and core needle biopsies compared to 2 mm biopsy. Only 80% of 2 mm biopsies demonstrated the presence of glomeruli, whereas glomeruli were present in 100% of all other biopsy sizes. CONCLUSIONS: The 2 mm punch biopsy has been shown to be challenging to use and frequently provides inadequate tissue for histology and proteomics while 3 mm research biopsies were the smallest size that were technically obtainable with adequate tissue for molecular studies.

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Chronic liver disease is becoming a leading cause of illness and mortality in patients living with human immunodeficiency virus (HIV; PLWH) undergoing suppressive anti-retroviral therapy. Its primary etiology is coinfection with hepatitis B and C virus (HBV and HCV, respectively). Chronic liver inflammation and fibrosis can potentially lead to the development of hepatocellular carcinoma (HCC). Therefore, monitoring of the disease progression in PLWH is required. The present study aimed to explore plasma protein profiles of PLWH and those coinfected with HBV and HCV using shotgun proteomics. HIV-monoinfected, HIV/HBV-coinfected, HIV/HCV-coinfected and uninfected control individuals were recruited. Patients in the three virus-infected groups had significantly higher levels of liver fibrosis indices (fibrosis-4 score and aspartate aminotransferase to platelet ratio index) compared with the control group. Liquid chromatography-tandem mass spectrometry analysis of plasma samples identified 1,074 proteins that were differentially expressed, where subsequent partial least squares-discriminant analysis model demonstrated clear clustering of proteomes from the four sample groups; 18 proteins that were significantly differentially expressed. Heatmap analysis identified two main groups of proteins, six proteins being upregulated only in the HIV/HBV-coinfection group and 10 proteins downregulated in all three virally infected groups. STITCH 5.0 analysis predicted an interaction network containing two identified proteins in the latter group, specifically ubiquitin interaction motif-containing 1 (UIMC1) and haptoglobin (HP), which are part of the profibrogenic TGF-1ß/SMAD, inflammatory TNF and tumor suppressor BRCA1 pathways. Expression levels of UIMC1 and HP were significantly lower in HIV-infected groups compared with those in uninfected controls. Altogether, these proteomics data provide protein expression profiles potentially associated with HIV infection and coinfection with HBV/HCV, which may be applied to predict progression to advanced liver disease or HCC in PLWH.

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Mucosal-associated invariant T (MAIT) cells represent a unique unconventional T cell population important in eliciting immunomodulatory responses in a range of diseases, including infectious diseases, autoimmunity and cancer. This innate-like T cell subset predominantly express CD8 in humans. Unlike conventional CD8+ T cells, which recognize peptide antigen presented by polymorphic major histocompatibility complex (MHC) molecules, MAIT cells are restricted by MR1, a non-polymorphic antigen-presenting molecule widely expressed in multiple tissues. Thus, identification of proteomic signature of MAIT cells in relation to conventional T cells is pivotal in understanding it's specific functional characteristics. The high-resolution dataset presents here comprehensively describes and compare the whole cell proteomes of MAIT (TCRVα7.2+CD161+) and conventional/non-MAIT T cells (TCR Vα7.2-CD161-) in humans. The dataset was generated using the proteomic samples prepared from matched T cell subsets sorted from peripheral blood mononuclear cells (PBMC) of three healthy volunteers. Peptides obtained from trypsin-digested cell lysates were analysed using Data-Dependent Mass Spectrometry (DDA-MS). Label-free quantitation of DDA-MS data using MaxQuant and MaxLFQ software identified 4,442 proteins at a 1 % false discovery rate. Of them, 3680 proteins that were detected with single UniProt accession and a minimum of 2 unique or razor peptides were assessed to identify differentially abundant proteins between MAIT cells and conventional T cells, including total T cells and CD8+ T cells. The dataset comprises high-quality label-free quantitative proteomic data that can be used to compare the expression pattern of whole cell proteomes between the above-mentioned T cell populations. Further, this can be used as a reference proteome of human MAIT cells for the in-depth understanding of the MAIT cell behaviour among T cells and to discover potential therapeutic targets to modulate MAIT cell function.

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Recent advances in "omics" technologies have enabled the identification of new beef quality biomarkers and have also allowed for the early detection of quality defects such as dark-cutting beef, also known as DFD (dark, firm, and dry) beef. However, most of the studies conducted were carried out on a small number of animals and mostly applied gel-based proteomics. The present study proposes for the first time a Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) proteomics approach to characterize and comprehensively quantify the post-mortem muscle proteome of DFD (pH24 ≥ 6.2) and CONTROL (5.4 ≤ pH24 ≤ 5.6) beef samples within the largest database of DFD/CONTROL beef samples to date (26 pairs of the Longissimus thoracis muscle samples of young bulls from Asturiana de los Valles breed, n = 52). The pairwise comparison yielded 35 proteins that significantly differed in their abundances between the DFD and CONTROL samples. Chemometrics methods using both PLS-DA and OPLS-DA revealed 31 and 36 proteins with VIP > 2.0, respectively. The combination of different statistical methods these being Volcano plot, PLS-DA and OPLS-DA allowed us to propose 16 proteins as good candidate biomarkers of DFD beef. These proteins are associated with interconnected biochemical pathways related to energy metabolism (DHRS7B and CYB5R3), binding and signaling (RABGGTA, MIA3, BPIFA2B, CAP2, APOBEC2, UBE2V1, KIR2DL1), muscle contraction, structure and associated proteins (DMD, PFN2), proteolysis, hydrolases, and activity regulation (AGT, C4A, GLB1, CAND2), and calcium homeostasis (ANXA6). These results evidenced the potential of SWATH-MS and chemometrics to accurately identify novel biomarkers for meat quality defects, providing a deeper understanding of the molecular mechanisms underlying dark-cutting beef condition.

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Many factors, such as the farming systems and preslaughter rearing practices, can influence the physiological and metabolic functions of poultry with consequent effects on poultry meat quality. In this trial, label-free shotgun proteomics was used to analyze the early post-mortem Pectoralis major muscle proteomes of Ross 308 and Ranger Classic chicken strains raised under two divergent farming systems these being organic and antibiotic-free. The combination of chemometrics using partial-least-square discriminant analysis (PLS-DA) and shotgun proteomics allowed clear discrimination between the different groups. Chicken strains were discriminated by differences in the abundance of 73 and 62 proteins within the antibiotic-free and organic farming systems, respectively. The abundances of 71 and 52 proteins were impacted by the farming system within the Ross 308 and Ranger Classic chicken strains, respectively. The analyses allowed for the proposal of several putative biomarkers of meat authenticity, which were found to be related to muscle structure and energy metabolism pathways. This study is a significant step forward in elucidating the potential of proteomics profiling and chemometrics in chicken meat, which may provide opportunities for the efficient assessment of chicken authenticity.

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The effects of ionizing radiation (IR) on the protein dynamics of cold-stressed cells of a radioresistant actinobacterium, Kocuria rhizophila PT10, isolated from the rhizosphere of the desert plant Panicum turgidum were investigated using a shotgun methodology based on nanoflow liquid chromatography coupled to tandem mass spectrometry. Overall, 1487 proteins were certified, and their abundances were compared between the irradiated condition and control. IR of cold-acclimated PT10 triggered the over-abundance of proteins involved in (1) a strong transcriptional regulation, (2) amidation of peptidoglycan and preservation of cell envelope integrity, (3) detoxification of reactive electrophiles and regulation of the redox status of proteins, (4) base excision repair and prevention of mutagenesis and (5) the tricarboxylic acid (TCA) cycle and production of fatty acids. Also, one of the more significant findings to emerge from this study is the SOS response of stressed PT10. Moreover, a comparison of top hits radio-modulated proteins of cold-acclimated PT10 with proteomics data from gamma-irradiated Deinococcus deserti showed that stressed PT10 has a specific response characterised by a high over-abundance of NemA, GatD, and UdgB.

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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.

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Alzheimer's disease (AD) is a neurodegenerative disease that causes physical damage to neuronal connections, leading to brain atrophy. This disruption of synaptic connections results in mild to severe cognitive impairments. Unfortunately, no effective treatment is currently known to prevent or reverse the symptoms of AD. The aim of this study was to investigate the effects of three synthetic peptides, i.e., KLVFF, RGKLVFFGR and RIIGL, on an AD in vitro model represented by differentiated SH-SY5Y neuroblastoma cells exposed to retinoic acid (RA) and brain-derived neurotrophic factor (BDNF). The results demonstrated that RIIGL peptide had the least significant cytotoxic activity to normal SH-SY5Y while exerting high cytotoxicity against the differentiated cells. The mechanism of RIIGL peptide in the differentiated SH-SY5Y was investigated based on changes in secretory proteins compared to another two peptides. A total of 380 proteins were identified, and five of them were significantly detected after treatment with RIIGL peptide. These secretory proteins were found to be related to microtubule-associated protein tau (MAPT) and amyloid-beta precursor protein (APP). RIIGL peptide acts on differentiated SH-SY5Y by regulating amyloid-beta formation, neuron apoptotic process, ceramide catabolic process, and oxidative phosphorylation and thus has the potentials to treat AD.

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Arouquesa cattle breed is an autochthonous Portuguese breed produced under a traditional mountain system that need improvement without affecting beef quality. The aim of this work is to compare the proteomics profiles of the Longissimus thoracis muscle from Arouquesa animals produced under different production systems. Sixty weaners were produced under the following systems: traditional (TF) and traditional with starter feed supplementation (TF + S1) with weaning and slaughtering at 9 months, the S1 + S2 (weaning at 5 months and grower supplement until slaughter) and two rearing periods with finishing supplementation (TF + S3 and S3). Upon slaughter, samples of L. thoracis were taken and analyzed using a shotgun proteomics workflow. Several putative markers of beef quality for the Arouquesa breed were identified: VIM, FSCN1, SERPINH1, ALDH1A1, NDUFB5, ANXA1, PDK4, CEMIP2, NDUFB9, PDLIM1, OXCT1, MYH4. These proteins are involved in actin binding, skeletal muscle development and in the mitochondrial respiratory chain and they can influence mostly meat tenderness and color. We identified specific proteins for each group related to different metabolisms involved in several aspects that affect meat quality parameters. Our results demonstrate the link between production practices and putative meat characteristics, which have the potential to improve the traceability of certified products. SIGNIFICANCE: Arouquesa breed is produced in a sustainable system using natural resources and contributing to the economy of low-populated rural regions in Northern Portugal. Besides their economic relevance, producing autochthonous breeds can counter rural depopulation and maintain local heritage. Additionally, consumer awareness about product quality is increasing and PDO products contribute to satisfying this demand. However, it is necessary to increase production so that it is possible to sell these products outside the production region. To ensure robust traceability and that PDO label characteristics are maintained despite increasing production yield, product analysis is of paramount importance. For this reason, proteomic approaches can provide insight into how production changes will affect beef quality and generate putative biomarkers of certified production systems.

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Buffalo is a dominant dairy animal in many agriculture-based economies. However, the poor reproductive efficiency (low conception rate) of the buffalo bulls constrains the realization of its full production potential. This in turn leads to economic and welfare issues, especially for the marginal farmers in such economies. The mammalian sperm surface proteins have been implicated in the regulation of survival and function of the spermatozoa in the female reproductive tract (FRT). Nonetheless, the lack of specific studies on buffalo sperm surface makes it difficult for researchers to explore and investigate the role of these proteins in the regulation of mechanisms associated with sperm protection, survival, and function. This study aimed to generate a buffalo sperm surface-specific proteomic fingerprint (LC-MS/MS) and to predict the functional roles of the identified proteins. The three treatments used to remove sperm surface protein viz. Elevated salt, phosphoinositide phospholipase C (PI-PLC) and in vitro capacitation led to the identification of N = 1,695 proteins (≥1 high-quality peptide-spectrum matches (PSMs), p < 0.05, and FDR<0.01). Almost half of these proteins (N = 873) were found to be involved in crucial processes relevant in the context of male fertility, e.g., spermatogenesis, sperm maturation and protection in the FRT, and gamete interaction or fertilization, amongst others. The extensive sperm-surface proteomic repertoire discovered in this study is unparalleled vis-à-vis the depth of identification of reproduction-specific cell-surface proteins and can provide a potential framework for further studies on the functional aspects of buffalo spermatozoa.

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Background: Data-dependent, bottom-up proteomics is widely used for identifying proteins and peptides. However, one key challenge is that 70% of fragment ion spectra consistently fail to be assigned by conventional database searching. This 'dark matter' of bottom-up proteomics seems to affect fields where non-model organisms, low-abundance proteins, non-tryptic peptides, and complex modifications may be present. While palaeoproteomics may appear as a niche field, understanding and reporting unidentified ancient spectra require collaborative innovation in bioinformatics strategies. This may advance the analysis of complex datasets. Methods: 14.97 million high-impact ancient spectra published in Nature and Science portfolios were mined from public repositories. Identification rates, defined as the proportion of assigned fragment ion spectra, were collected as part of deposited database search outputs or parsed using open-source python packages. Results and Conclusions: We report that typically 94% of the published ancient spectra remain unidentified. This phenomenon may be caused by multiple factors, notably the limitations of database searching and the selection of user-defined reference data with advanced modification patterns. These 'spectra without stories' highlight the need for widespread data sharing to facilitate methodological development and minimise the loss of often irreplaceable ancient materials. Testing and validating alternative search strategies, such as open searching and de novo sequencing, may also improve overall identification rates. Hence, lessons learnt in palaeoproteomics may benefit other fields grappling with challenging data.

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Fecal metaproteomics is a useful approach to measure changes in microbial and host protein abundance and to infer which members of the gut microbiota are involved in specific functions and pathways. This chapter describes a protocol enabling analysis and characterization of fecal metaproteomes, successfully applied to human, mouse, and rat stool samples. The protocol combines mechanical and thermal treatments for protein extraction, a centrifugal filter-based procedure for cleanup and digestion, long-gradient liquid chromatography for peptide separation, and high-resolution mass spectrometry for peptide detection.

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Single-cell proteomic analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems' heterogeneous populations. Mass spectrometry (MS)-based proteomics is a promising alternative for quantitative single-cell proteomics. Various techniques are continually evolving to address the challenges of limited sample material, detection sensitivity, and throughput constraints. In this chapter, we describe a nanoliter-scale glass-oil-air-droplet (gOAD) chip engineered for heat tolerance, which combines droplet-based microfluidics and shotgun proteomic analysis techniques to enable multistep sample pretreatment.

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The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.

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Breast cancer (BC) remains one of the leading causes of mortality among women, with triple-negative breast cancer (TNBC) standing out for its aggressive nature and limited treatment options. Metabolic reprogramming, one of cancer's hallmarks, underscores the importance of targeting metabolic vulnerabilities for therapeutic intervention. This study aimed to investigate the impact of de novo serine biosynthetic pathway (SSP) inhibition, specifically targeting phosphoglycerate dehydrogenase (PHGDH) with NCT-503, on three TNBC cell lines: MDA-MB-231, MDA-MB-468 and Hs 578T. First, MS-based proteomics was used to confirm the distinct expression of PHGDH and other SSP enzymes using the intracellular proteome profiles of untreated cells. Furthermore, to characterize the response of the TNBC cell lines to the inhibitor, both in vitro assays and label-free, bottom-up proteomics were employed. NCT-503 exhibited significant cytotoxic effects on all three cell lines, with MDA-MB-468 being the most susceptible (IC50 20.2 ± 2.8 µM), while MDA-MB-231 and Hs 578T showed higher, comparable IC50s. Notably, differentially expressed proteins (DEPs) induced by NCT-503 treatment were mostly cell line-specific, both in terms of the intracellular and secreted proteins. Through overrepresentation and Reactome GSEA analysis, modifications of the intracellular proteins associated with cell cycle pathways were observed in the MDA-MBs following treatment. Distinctive dysregulation of signaling pathways were seen in all TNBC cell lines, while modifications of proteins associated with the extracellular matrix organization characterizing both MDA-MB-231 and Hs 578T cell lines were highlighted through the treatment-induced modifications of the secreted proteins. Lastly, an analysis was conducted on the DEPs that exhibited greater abundance in the NCT-503 treatment groups to evaluate the potential chemo-sensitizing properties of NCT-503 and the druggability of these promising targets.

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The expansion of agriculture and the need for sustainable practices drives breeders to develop plant varieties better adapted to abiotic stress such as nutrient deficiency, which negatively impacts yields. Phosphorus (P) is crucial for photosynthesis and plant growth, but its availability in the soil is often limited, hampering crop development. In this study, we examined the response of two popcorn inbred lines, L80 and P7, which have been characterized previously as P-use inefficient and P-use efficient, respectively, under low (stress) and high P (control) availability. Physiological measurements, proteomic analysis, and metabolite assays were performed to unravel the physiological and molecular responses associated with the efficient use of P in popcorn. We observed significant differences in protein abundances in response to the P supply between the two inbred lines. A total of 421 differentially expressed proteins (DEPs) were observed in L80 and 436 DEPs in P7. These proteins were involved in photosynthesis, protein biosynthesis, biosynthesis of secondary metabolites, and energy metabolism. In addition, flavonoids accumulated in higher abundance in P7. Our results help us understand the major components of P utilization in popcorn, providing new insights for popcorn molecular breeding programs.

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This article summarizes the characterization, by shotgun proteomics, of 11 bacterial strains identified as responsible for seafood spoilage. A total of 4455 peptide spectrum matches, corresponding to 4299 peptides and 3817 proteins were identified. Analyses of data determined the functional pathways they are involved in. The proteins identified were integrated into a protein-protein network that involves 371 nodes and 3016 edges. Those proteins are implicated in energy pathways, peptidoglycan biosynthesis, spermidine/putrescine metabolism. An additional 773 peptides were characterized as virulence factors, that participates in bacterial pathogenesis; while 14 peptides were defined as biomarkers, as they can be used to differentiate the bacterial species present. This report represents the most extensive proteomic repository available in the field of seafood spoilage bacteria; the data substantially advances the understanding of seafood decay, as well as provides fundamental bases for the recognition of the bacteria existent in seafood that cause spoilage during food processing/storage.

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Under conditions of soil water limitation and adequate irrigation, we conducted an investigation into the growth dynamics, gas exchange performance, and proteomic profiles of two inbred popcorn lines-L71, characterized as drought-tolerant, and L61, identified as drought-sensitive. Our goal was to uncover the mechanisms associated with tolerance to soil water limitation during the flowering. The plants were cultivated until grain filling in a substrate composed of perlite and peat within 150cm long lysimeter, subjected to two water conditions (WC): i) irrigated (WW) at lysimeter capacity (LC - 100%), and ii) water-stressed (WS). Under WS conditions, the plants gradually reached 45% of LC and were maintained at this level for 10 days. Irrespective of the WC, L71 exhibited the highest values of dry biomass in both shoot and root systems, signifying its status as the most robust genotype. The imposed water limitation led to early senescence, chlorophyll degradation, and increased anthocyanin levels, with a more pronounced impact observed in L61. Traits related to gas exchange manifested differences between the lines only under WS conditions. A total of 1838 proteins were identified, with 169 differentially accumulated proteins (DAPs) in the tolerant line and 386 DAPs in the sensitive line. Notably, differences in energy metabolism, photosynthesis, oxidative stress response, and protein synthesis pathways were identified as the key distinctions between L71 and L61. Consequently, our findings offer valuable insights into the alterations in proteomic profiles associated with the adaptation to soil water limitation in popcorn.

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