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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The advent of soft ionization mass spectrometry‐based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global‐integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label‐free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non‐model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review‐essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof‐of‐concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism. [ABSTRACT FROM AUTHOR]

Background Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilises open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

Mass spectrometry‐based proteomics, born from the invention of soft ionization, has revolutionized protein analysis. In‐depth characterization of complex and variable mixtures of proteins, such as that found at crime‐scenes, is now possible. This capability continues to expand with advancements in mass spectral instrumentation and computational power, allowing for the development of dynamic data acquisition approaches and sophisticated bioinformatics tools for data interpretation. Proteins are the major component of all biological material, as a result they have been of interest to forensic practitioners for centuries. While DNA is the gold standard for identification, proteins are able to provide contextual information about biological material not available through genomic approaches alone. Mass spectrometry‐based proteomics has expanded the breadth and ease of forensic protein analysis with several emerging applications that promise to become common place as investigative tools, particularly in forensic serology and toxicology. This includes the targeted analysis of protein biomarkers for the classification of biological tissue and fluids, the detection of protein toxins such as ricin and identification of peptide hormones such as insulin. The ability of protein analysis to leverage information from the genome has been demonstrated to achieve individual identification from biological material, an emerging technology that can be used in the absence of extractable DNA. In recent years, there has been considerable scrutiny of forensic techniques that lack objectivity and a statistical basis, an alternative molecular approach for forensic analysis that utilizes the high specificity of mass spectrometry, is a welcome addition with many potential future applications. This article is categorized under:Forensic Chemistry and Trace Evidence > Trace Evidence [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Background Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilises open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

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.

Abstract Cerebral amyloid angiopathy (CAA) is a form of small vessel disease characterised by the progressive deposition of amyloid β protein in the cerebral vasculature, inducing symptoms including cognitive impairment and cerebral haemorrhages. Due to their accessibility and homogeneous disease phenotypes, animal models are advantageous platforms to study diseases like CAA. Untargeted proteomics studies of CAA rat models (e.g. rTg-DI) and CAA patients provide opportunities for the identification of novel biomarkers of CAA. We performed untargeted, data-independent acquisition proteomic shotgun analyses on the cerebrospinal fluid of rTg-DI rats and wild-type (WT) littermates. Rodents were analysed at 3 months (n = 6/10), 6 months (n = 8/8), and 12 months (n = 10/10) for rTg-DI and WT respectively. For humans, proteomic analyses were performed on CSF of sporadic CAA patients (sCAA) and control participants (n = 39/28). We show recurring patterns of differentially expressed (mostly increased) proteins in the rTg-DI rats compared to wild type rats, especially of proteases of the cathepsin protein family (CTSB, CTSD, CTSS), and their main inhibitor (CST3). In sCAA patients, decreased levels of synaptic proteins (e.g. including VGF, NPTX1, NRXN2) and several members of the granin family (SCG1, SCG2, SCG3, SCG5) compared to controls were discovered. Additionally, several serine protease inhibitors of the SERPIN protein family (including SERPINA3, SERPINC1 and SERPING1) were differentially expressed compared to controls. Fifteen proteins were significantly altered in both rTg-DI rats and sCAA patients, including (amongst others) SCG5 and SERPING1. These results identify specific groups of proteins likely involved in, or affected by, pathophysiological processes involved in CAA pathology such as protease and synapse function of rTg-DI rat models and sCAA patients, and may serve as candidate biomarkers for sCAA.

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.

Cerebral amyloid angiopathy (CAA) is a form of small vessel disease characterised by the progressive deposition of amyloid β protein in the cerebral vasculature, inducing symptoms including cognitive impairment and cerebral haemorrhages. Due to their accessibility and homogeneous disease phenotypes, animal models are advantageous platforms to study diseases like CAA. Untargeted proteomics studies of CAA rat models (e.g. rTg-DI) and CAA patients provide opportunities for the identification of novel biomarkers of CAA. We performed untargeted, data-independent acquisition proteomic shotgun analyses on the cerebrospinal fluid of rTg-DI rats and wild-type (WT) littermates. Rodents were analysed at 3 months (n = 6/10), 6 months (n = 8/8), and 12 months (n = 10/10) for rTg-DI and WT respectively. For humans, proteomic analyses were performed on CSF of sporadic CAA patients (sCAA) and control participants (n = 39/28). We show recurring patterns of differentially expressed (mostly increased) proteins in the rTg-DI rats compared to wild type rats, especially of proteases of the cathepsin protein family (CTSB, CTSD, CTSS), and their main inhibitor (CST3). In sCAA patients, decreased levels of synaptic proteins (e.g. including VGF, NPTX1, NRXN2) and several members of the granin family (SCG1, SCG2, SCG3, SCG5) compared to controls were discovered. Additionally, several serine protease inhibitors of the SERPIN protein family (including SERPINA3, SERPINC1 and SERPING1) were differentially expressed compared to controls. Fifteen proteins were significantly altered in both rTg-DI rats and sCAA patients, including (amongst others) SCG5 and SERPING1. These results identify specific groups of proteins likely involved in, or affected by, pathophysiological processes involved in CAA pathology such as protease and synapse function of rTg-DI rat models and sCAA patients, and may serve as candidate biomarkers for sCAA. [ABSTRACT FROM AUTHOR]

Problems with the male reproductive system are of both medical and social significance. As a rule, spermatozoa and seminal plasma proteomes are investigated separately to assess sperm quality. The current study aimed to compare ejaculate proteomes with spermatozoa and seminal plasma protein profiles regarding the identification of proteins related to fertility scores. A total of 1779, 715, and 2163 proteins were identified in the ejaculate, seminal plasma, and spermatozoa, respectively. Among these datasets, 472 proteins were shared. GO enrichment analysis of the common proteins enabled us to distinguish biological processes such as single fertilization (GO:0007338), spermatid development (GO:0007286), and cell motility (GO:0048870). Among the abundant terms for GO cellular components, zona pellucida receptor complex, sperm fibrous sheath, and outer dense fiber were revealed. Overall, we identified 139 testis-specific proteins. For these proteins, PPI networks that are common in ejaculate, spermatozoa, and seminal plasma were related to the following GO biological processes: cilium movement (GO:0003341), microtubule-based movement (GO:0007018), and sperm motility (GO:0097722). For ejaculate and spermatozoa, they shared 15 common testis-specific proteins with spermatogenesis (GO:0007283) and male gamete generation (GO:0048232). Therefore, we speculated that ejaculate-based proteomics could yield new insights into the peculiar reproductive physiology and spermatozoa function of men and potentially serve as an explanation for male infertility screening. [ABSTRACT FROM AUTHOR]

Strain Q11T of an irregular coccoid Gram-positive bacterium, aerobic and non-motile, was isolated from Meconopsis integrifolia seeds. Strain Q11T grew optimally in 1% (w/v) NaCl, pH 7, at 30 °C. Strain Q11T is most closely related to Flexivirga, as evidenced by 16S rRNA gene analysis, and shares the highest similarity with Flexivirga aerilata ID2601ST (99.24%). Based on genome sequence analysis, the average nucleotide identity and digital DNA–DNA hybridization values of strains Q11T and D2601ST were 88.82% and 36.20%, respectively. Additionally, strain Q11T showed the abilities of nitrogen fixation and indole acetic acid production and was shown to promote maize growth under laboratory conditions. Its genome contains antibiotic resistance genes (the vanY gene in the vanB cluster and the vanW gene in the vanI cluster) and extreme environment tolerance genes (ectoine biosynthetic gene cluster). Shotgun proteomics also detected antibiotic resistance proteins (class A beta-lactamases, D-alanine ligase family proteins) and proteins that improve plant cold tolerance (multispecies cold shock proteins). Strain Q11T was determined to be a novel species of the genus Flexivirga, for which the name Flexivirga meconopsidis sp. nov. is proposed. The strain type is Q11T (GDMCC 1.3002T = JCM 36020 T). [ABSTRACT FROM AUTHOR]

Snakebite envenoming is one of the most significantly neglected tropical diseases in the world. The lack of diagnosis/prognosis methods for snakebite is one of our motivations to develop innovative technological solutions for Brazilian health. The objective of this work was to evaluate the protein and metallic ion composition of Crotalus durissus terrificus, Bothrops jararaca, B. alternatus, B. jararacussu, B. moojeni, B. pauloensis, and Lachesis muta muta snake venoms. Brazilian snake venoms were subjected to the shotgun proteomic approach using mass spectrometry, and metal ion analysis was performed by atomic spectrometry. Shotgun proteomics has shown three abundant toxin classes (PLA2, serine proteases, and metalloproteinases) in all snake venoms, and metallic ions analysis has evidenced that the Cu2+ ion is present exclusively in the L. m. muta venom; Ca2+ and Mg2+ ions have shown a statistical difference between the species of Bothrops and Crotalus genus, whereas the Zn2+ ion presented a statistical difference among all species studied in this work. In addition, Mg2+ ions have shown 42 times more in the C. d. terrificus venom when compared to the average concentration in the other genera. Though metal ions are a minor fraction of snake venoms, several venom toxins depend on them. We believe that these non-protein fractions are capable of assisting in the development of unprecedented diagnostic devices for Brazilian snakebites. [ABSTRACT FROM AUTHOR]

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution. [ABSTRACT FROM AUTHOR]

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.

ABSTRACTIron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS−). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS2). Recently, paradigm-shifting studies indicate that Fe and S in FeS2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS2, as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS2, Fe(II)/HS−, or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS−, either as a component of the growth medium [Fe(II)/HS−] or generated through reduction of FeS2, were likely a major factor underpinning these phenotypic differences.IMPORTANCEThe methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

Bats carry many zoonotic pathogens without showing pronounced pathology, with a few exceptions. The underlying immune tolerance mechanisms in bats remain poorly understood, although information-rich omics tools hold promise for identifying a wide range of immune markers and their relationship with infection. To evaluate the generality of immune responses to infection, we assessed the differences and similarities in serum proteomes of wild vampire bats (Desmodus rotundus) across infection status with five taxonomically distinct pathogens: bacteria (Bartonella spp., hemoplasmas), protozoa (Trypanosoma cruzi), and DNA (herpesviruses) and RNA (alphacoronaviruses) viruses. From 19 bats sampled in 2019 in Belize, we evaluated the up- and downregulated immune responses of infected versus uninfected individuals for each pathogen. Using a high-quality genome annotation for vampire bats, we identified 586 serum proteins but found no evidence for differential abundance nor differences in composition between infected and uninfected bats. However, using receiver operating characteristic curves, we identified four to 48 candidate biomarkers of infection depending on the pathogen, including seven overlapping biomarkers (DSG2, PCBP1, MGAM, APOA4, DPEP1, GOT1, and IGFALS). Enrichment analysis of these proteins revealed that our viral pathogens, but not the bacteria or protozoa studied, were associated with upregulation of extracellular and cytoplasmatic secretory vesicles (indicative of viral replication) and downregulation of complement activation and coagulation cascades. Additionally, herpesvirus infection elicited a downregulation of leukocyte-mediated immunity and defense response but an upregulation of an inflammatory and humoral immune response. In contrast to our two viral infections, we found downregulation of lipid and cholesterol homeostasis and metabolism with Bartonella spp. infection, of platelet-dense and secretory granules with hemoplasma infection, and of blood coagulation pathways with T. cruzi infection. Despite the small sample size, our results suggest that vampire bats have a similar suite of immune mechanisms for viruses distinct from responses to the other pathogen taxa, and we identify potential biomarkers that can expand our understanding of pathogenesis of these infections in bats. By applying a proteomic approach to a multi-pathogen system in wild animals, our study provides a distinct framework that could be expanded across bat species to increase our understanding of how bats tolerate pathogens.

Bacillus toyonensis SFC 500-1E is a member of the consortium SFC 500-1 able to remove Cr(VI) and simultaneously tolerate high phenol concentrations. In order to elucidate mechanisms utilized by this strain during the bioremediation process, the differential expression pattern of proteins was analyzed when it grew with or without Cr(VI) (10 mg/L) and Cr(VI) + phenol (10 and 300 mg/L), through two complementary proteomic approaches: gel-based (Gel-LC) and gel-free (shotgun) nanoUHPLC-ESI–MS/MS. A total of 400 differentially expressed proteins were identified, out of which 152 proteins were down-regulated under Cr(VI) and 205 up-regulated in the presence of Cr(VI) + phenol, suggesting the extra effort made by the strain to adapt itself and keep growing when phenol was also added. The major metabolic pathways affected include carbohydrate and energetic metabolism, followed by lipid and amino acid metabolism. Particularly interesting were also ABC transporters and the iron-siderophore transporter as well as transcriptional regulators that can bind metals. Stress-associated global response involving the expression of thioredoxins, SOS response, and chaperones appears to be crucial for the survival of this strain under treatment with both contaminants. This research not only provided a deeper understanding of B. toyonensis SFC 500-1E metabolic role in Cr(VI) and phenol bioremediation process but also allowed us to complete an overview of the consortium SFC 500-1 behavior. This may contribute to an improvement in its use as a bioremediation strategy and also provides a baseline for further research. [ABSTRACT FROM AUTHOR]

Cigarette smoking is the major cause of chronic inflammatory diseases such as chronic obstructive pulmonary disease (COPD). It is paramount to develop pharmacological interventions and delivery strategies against the cigarette smoke (CS) associated oxidative stress in COPD. This study in Wistar rats examined cysteamine in nanoemulsions to counteract the CS distressed microenvironment. In vivo, 28 days of CS and 15 days of cysteamine nanoemulsions treatment starting on 29th day consisting of oral and inhalation routes were established in Wistar rats. In addition, we conducted inflammatory and epithelial-to-mesenchymal transition (EMT) studies in vitro in human bronchial epithelial cell lines (BEAS2B) using 5% CS extract. Inflammatory and anti-inflammatory markers, such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, IL-1β, IL-8, IL-10, and IL-13, have been quantified in bronchoalveolar lavage fluid (BALF) to evaluate the effects of the cysteamine nanoemulsions in normalizing the diseased condition. Histopathological analysis of the alveoli and the trachea showed the distorted, lung parenchyma and ciliated epithelial barrier, respectively. To obtain mechanistic insights into the CS COPD rat model, "shotgun" proteomics of the lung tissues have been carried out using high-resolution mass spectrometry wherein genes such as ABI1, PPP3CA, PSMA2, FBLN5, ACTG1, CSNK2A1, and ECM1 exhibited significant differences across all the groups. Pathway analysis showed autophagy, signaling by receptor tyrosine kinase, cytokine signaling in immune system, extracellular matrix organization, and hemostasis, as the major contributing pathways across all the studied groups. This work offers new preclinical findings on how cysteamine taken orally or inhaled can combat CS-induced oxidative stress. [ABSTRACT FROM AUTHOR]

A non-motile, Gram-staining-negative, orange-pigmented bacterium called herbae pc1-10T was discovered in Tibet in the soil around Pyrola calliantha H. Andres' roots. The isolate thrived in the temperature range of 10–30 °C (optimal, 25 °C), pH range of 5.0–9.0 (optimum, pH = 6.0), and the NaCl concentration range of 0–1.8% (optimal, 0%). The DNA G+C content of the novel strain was 37.94 mol%. It showed the function of dissolving organophosphorus, acquiring iron from the environment by siderophore and producing indole acetic acid. Moreover, the genome of strain herbae pc1-10T harbors two antibiotic resistance genes (IND-4 and AdeF) encoding a β-lactamase, and the membrane fusion protein of the multidrug efflux complex AdeFGH; antibiotic-resistance-related proteins were detected using the Shotgun proteomics technology. The OrthoANIu values between strains Chryseobacterium herbae pc1-10T; Chryseobacterium oleae CT348T; Chryseobacterium kwangjuense KJ1R5T; and Chryseobacterium vrystaatense R-23566T were 90.94%, 82.96%, and 85.19%, respectively. The in silico DDH values between strains herbae pc1-10T; C. oleae CT348T; C. kwangjuense KJ1R5T; and C. vrystaatense R-23566T were 41.7%, 26.6%, and 29.7%, respectively. Chryseobacterium oleae, Chryseobacterium vrystaatense, and Chryseobacterium kwangjuense, which had 16S rRNA gene sequence similarity scores of 97.80%, 97.52%, and 96.75%, respectively, were its closest phylogenetic relatives. Chryseobacterium herbae sp. nov. is proposed as the designation for the strain herbae pc1-10T (=GDMCC 1.3255 = JCM 35711), which represented a type species based on genotypic and morphological characteristics. This study provides deep knowledge of a Chryseobacterium herbae characteristic description and urges the need for further genomic studies on microorganisms living in alpine ecosystems, especially around medicinal plants. [ABSTRACT FROM AUTHOR]

Abstract Host response to invasive microbes in the bovine udder has an important role on the animal health and is essential to the dairy industry to ensure production of high-quality milk and reduce the mastitis incidence. To better understand the biology behind these host-microbiome interactions, we investigated the somatic cell proteomes at quarter level for four cows (collected before and after milking) using a shotgun proteomics approach. Simultaneously, we identified the quarter microbiota by amplicon sequencing to detect presence of mastitis pathogens or other commensal taxa. In total, 32 quarter milk samples were analyzed divided in two groups depending on the somatic cell count (SCC). The high SCC group (>100,000 cell/mL) included 10 samples and significant different proteome profiles were detected. Differential abundance analysis uncovers a specific expression pattern in high SCC samples revealing pathways involved in immune responses such as inflammation, activation of the complement system, migration of immune cells, and tight junctions. Interestingly, different proteome profiles were also identified in quarter samples containing one of the two mastitis pathogens, Staphylococcus aureus and Streptococcus uberis, indicating a different response of the host depending on the pathogen. Weighted correlation network analysis identified three modules of co-expressed proteins which were correlated with the SCC in the quarters. These modules contained proteins assigned to different aspects of the immune response, but also amino sugar and nucleotide sugar metabolism, and biosynthesis of amino acids. The results of this study provide deeper insights on how the proteome expression changes at quarter level in naturally infected cows and pinpoint potential interactions and important biological functions during host-microbe interaction.

Background: Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods: Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilizes open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results: The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions: A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

Background: Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods: Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilizes open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results: The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions: A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

Dichloromethane (DCM, methylene chloride) is a toxic, high-volume industrial pollutant of long-standing. Anaerobic biodegradation is crucial for its removal from contaminated environments, yet prevailing mechanisms remain unresolved, especially concerning dehalogenation. In this study, we obtained an assembled genome of a novel DCM-degrading strain, Dehalobacterium formicoaceticum strain EZ94, from a stable DCM-degrading consortium, and we analyzed its proteome during degradation of DCM. A gene cluster recently predicted to play a major role in anaerobic DCM catabolism (the mec cassette) was found. Methyltransferases and other proteins encoded by the mec cassette were among the most abundant proteins produced, suggesting their involvement in DCM catabolism. Reductive dehalogenases were not detected. Genes and corresponding proteins for a complete Wood-Ljungdahl pathway, which could enable further metabolism of DCM carbon, were also found. Unlike for the anaerobic DCM degrader "Ca. F. warabiya," no genes for metabolism of the quaternary amines choline and glycine betaine were identified. This work provides independent and supporting evidence that mec-associated methyltransferases are key to anaerobic DCM metabolism. [ABSTRACT FROM AUTHOR]

Biogenic amine-producing bacteria are responsible for the production of basic nitrogenous compounds (histamine, cadaverine, tyramine, and putrescine) following the spoilage of food due to microorganisms. In this study, we adopted a shotgun proteomics strategy to characterize 15 foodborne strains of biogenic-amine-producing bacteria. A total of 10,673 peptide spectrum matches belonging to 4081 peptides and corresponding to 1811 proteins were identified. Relevant functional pathways were determined, and strains were differentiated into hierarchical clusters. An expected protein-protein interaction network was created (260 nodes/1973 interactions). Most of the determined proteins were associated with networks/pathways of energy, putrescine metabolism, and host-virus interaction. Additionally, 556 peptides were identified as virulence factors. Moreover, 77 species-specific peptide biomarkers corresponding to 64 different proteins were proposed to identify 10 bacterial species. This represents a major proteomic dataset of biogenic-amine-producing strains. These results may also be suitable for new treatments for food intoxication and for tracking microbial sources in foodstuffs. [ABSTRACT FROM AUTHOR]

Shotgun proteomics has proven to be an attractive alternative for identifying a pathogen and characterizing the antimicrobial resistance genes it produces. Because of its performance, proteotyping of microorganisms by tandem mass spectrometry is expected to become an essential tool in modern healthcare. Proteotyping microorganisms that have been isolated from the environment by culturomics is also a cornerstone for the development of new biotechnological applications. Phylopeptidomics is a new strategy that estimates the phylogenetic distances between the organisms present in the sample and calculates the ratio of their shared peptides, thus improving the quantification of their contributions to the biomass. Here, we established the limit of detection of tandem mass spectrometry proteotyping based on MS/MS data recorded for several bacteria. The limit of detection for Salmonella bongori with our experimental set-up is 4 × 104 colony-forming units from a sample volume of 1 mL. This limit of detection is directly related to the amount of protein per cell and therefore depends on the shape and size of the microorganism. We have demonstrated that identification of bacteria by phylopeptidomics is independent of their growth stage and that the limit of detection of the method is not degraded in presence of additional bacteria in the same proportion. [ABSTRACT FROM AUTHOR]

Paspalum fasciculatum Willd. ex Flüggé grows in mining soils which are Cd- and Pb-contaminated where it exhibits tolerance to Pb and the ability to extract Pb from these soils. To elucidate tolerance mechanisms to Pb-stress, liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to quantify changes in the accumulation of proteins in leaves. We identified 323 proteins involved in primary metabolism and response to biotic or abiotic stresses. Although proteins involved in the processes of photosynthesis and saccharide and energy metabolism presented the greatest amount of down-regulated proteins, the plant was able to maintain photosynthetic functions and obtain energy to sustain the vital balance. P. fasciculatum based their tolerance on increased antioxidant defenses, improving the protection and repair of proteins and transduction signals to coordinate physiological response to Pb-stress. Our results provide important information to understand the tolerance mechanisms in P. fasciculatum and could be important in future molecular studies on the resistance and accumulation of Pb in plants.

Host response to invasive microbes in the bovine udder has an important role on the animal health and is essential to the dairy industry to ensure production of high-quality milk and reduce the mastitis incidence. To better understand the biology behind these host-microbiome interactions, we investigated the somatic cell proteomes at quarter level for four cows (collected before and after milking) using a shotgun proteomics approach. Simultaneously, we identified the quarter microbiota by amplicon sequencing to detect presence of mastitis pathogens or other commensal taxa. In total, 32 quarter milk samples were analyzed divided in two groups depending on the somatic cell count (SCC). The high SCC group (>100,000 cell/mL) included 10 samples and significant different proteome profiles were detected. Differential abundance analysis uncovers a specific expression pattern in high SCC samples revealing pathways involved in immune responses such as inflammation, activation of the complement system, migration of immune cells, and tight junctions. Interestingly, different proteome profiles were also identified in quarter samples containing one of the two mastitis pathogens, Staphylococcus aureus and Streptococcus uberis, indicating a different response of the host depending on the pathogen. Weighted correlation network analysis identified three modules of co-expressed proteins which were correlated with the SCC in the quarters. These modules contained proteins assigned to different aspects of the immune response, but also amino sugar and nucleotide sugar metabolism, and biosynthesis of amino acids. The results of this study provide deeper insights on how the proteome expression changes at quarter level in naturally infected cows and pinpoint potential interactions and important biological functions during host-microbe interaction. [ABSTRACT FROM AUTHOR]

The common octopus (Octopus vulgaris) is nowadays the most demanded cephalopod species for human consumption. This species was also postulated for aquaculture diversification to supply its increasing demand in the market worldwide, which only relies on continuously declining field captures. In addition, they serve as model species for biomedical and behavioral studies. Body parts of marine species are usually removed before reaching the final consumer as by-products in order to improve preservation, reduce shipping weight, and increase product quality. These by-products have recently attracted increasing attention due to the discovery of several relevant bioactive compounds. Particularly, the common octopus ink has been described as having antimicrobial and antioxidant properties, among others. In this study, the advanced proteomics discipline was applied to generate a common octopus reference proteome to screen potential bioactive peptides from fishing discards and by-products such as ink. A shotgun proteomics approach by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using an Orbitrap Elite instrument was used to create a reference dataset from octopus ink. A total of 1432 different peptides belonging to 361 non-redundant annotated proteins were identified. The final proteome compilation was investigated by integrated in silico studies, including gene ontology (GO) term enrichment, pathways, and network studies. Different immune functioning proteins involved in the innate immune system, such as ferritin, catalase, proteasome, Cu/Zn superoxide dismutase, calreticulin, disulfide isomerase, heat shock protein, etc., were found in ink protein networks. Additionally, the potential of bioactive peptides from octopus ink was addressed. These bioactive peptides can exert beneficial health properties such as antimicrobial, antioxidant, antihypertensive, and antitumoral properties and are therefore considered lead compounds for developing pharmacological, functional foods or nutraceuticals. [ABSTRACT FROM AUTHOR]

Various external and internal factors damaging DNA constantly disrupt the stability of the genome. Cells use numerous dedicated DNA repair systems to detect damage and restore genomic integrity in a timely manner. Ribonucleotide reductase (RNR) is a key enzyme providing dNTPs for DNA repair. Molecular mechanisms of indirect regulation of yeast RNR activity are well understood, whereas little is known about its direct regulation. The study was aimed at elucidation of the proteasome-dependent mechanism of direct regulation of RNR subunits in Saccharomyces cerevisiae. Proteome analysis followed byWestern blot, RT-PCR, and yeast plating analysis showed that upregulation of RNR by proteasome deregulation is associated with yeast hyper resistance to 4-nitroquinoline-1-oxide (4-NQO), a UV-mimetic DNA-damaging drug used in animal models to study oncogenesis. Inhibition of RNR or deletion of RNR regulatory proteins reverses the phenotype of yeast hyper resistance to 4-NQO. We have shown for the first time that the yeast Rnr1 subunit is a substrate of the proteasome, which suggests a common mechanism of RNR regulation in yeast and mammals. [ABSTRACT FROM AUTHOR]

Proteomics is an indispensable analytical technique to study the dynamic functioning of biological systems via different proteins and their proteoforms. In recent years, bottom-up shotgun has become more popular than gel-based top-down proteomics. The current study examined the qualitative and quantitative performance of these two fundamentally different methodologies by the parallel measurement of six technical and three biological replicates of the human prostate carcinoma cell line DU145 using its two most common standard techniques, label-free shotgun and two-dimensional differential gel electrophoresis (2D-DIGE). The analytical strengths and limitations were explored, finally focusing on the unbiased detection of proteoforms, exemplified by discovering a prostate cancer-related cleavage product of pyruvate kinase M2. Label-free shotgun proteomics quickly yields an annotated proteome but with reduced robustness, as determined by three times higher technical variation compared to 2D-DIGE. At a glance, only 2D-DIGE top-down analysis provided valuable, direct stoichiometric qualitative and quantitative information from proteins to their proteoforms, even with unexpected post-translational modifications, such as proteolytic cleavage and phosphorylation. However, the 2D-DIGE technology required almost 20 times as much time per protein/proteoform characterization with more manual work. Ultimately, this work should expose both techniques' orthogonality with their different contents of data output to elucidate biological questions. [ABSTRACT FROM AUTHOR]

Ginseng, an important crop in East Asia, exhibits multiple medicinal and nutritional benefits because of the presence of ginsenosides. On the other hand, the ginseng yield is severely affected by abiotic stressors, particularly salinity, which reduces yield and quality. Therefore, efforts are needed to improve the ginseng yield during salinity stress, but salinity stress-induced changes in ginseng are poorly understood, particularly at the proteome-wide level. In this study, we report the comparative proteome profiles of ginseng leaves at four different time points (mock, 24, 72, and 96 h) using a label-free quantitative proteome approach. Of the 2484 proteins identified, 468 were salt-responsive. In particular, glycosyl hydrolase 17 (PgGH17), catalase-peroxidase 2, voltage-gated potassium channel subunit beta-2, fructose-1,6-bisphosphatase class 1, and chlorophyll a-b binding protein accumulated in ginseng leaves in response to salt stress. The heterologous expression of PgGH17 in Arabidopsis thaliana improved the salt tolerance of transgenic lines without compromising plant growth. Overall, this study uncovers the salt-induced changes in ginseng leaves at the proteome level and highlights the critical role of PgGH17 in salt stress tolerance in ginseng. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2DM), also known as adult-onset diabetes or noninsulin-dependent diabetes mellitus, is characterized by hyperglycemia and insulin resistance. Protein biomarker screening plays an essential role in different diseases. Proteomic methods such as MALDI-TOF based peptide mass fingerprinting, LC-MS/MS based peptide sequencing, and multidimensional liquid phase chromatography (MDLC) coupled with tandem mass spectrometry (MS) shotgun proteomics are used to identify biomarkers. Methods: In this study, we used a MDLC coupled with tandem MS shotgun proteomic method to demonstrate protein quantitation results by comparing human serum samples from T2DM patients with those of healthy subjects. We utilized quantitative techniques, dimethyl labeling, MDLC by hydrophilic interaction liquid chromatography separated column, and reverse-phase high-performance liquid chromatography coupled with tandem MS to identify proteins with high potential to be T2DM biomarker candidates. Results: Identified candidates included vitamin D–binding protein, apolipoprotein B-100, apolipoprotein A2, apolipoprotein A1, transthyretin, Ig heavy-chain V–III region BRO, antithrombin-3, fibrinogen gamma chains, fibrinogen alpha chains, and alpha-1-antitrypsin. In addition, we also generated relative protein networks using STRING bioinformatic software. Conclusion: These potential biomarker candidates might be verified by further experiments such as an ELISA assay or multiple reaction monitoring MS screening. [ABSTRACT FROM AUTHOR]

Problems with the male reproductive system are of both medical and social significance. As a rule, spermatozoa and seminal plasma proteomes are investigated separately to assess sperm quality. The current study aimed to compare ejaculate proteomes with spermatozoa and seminal plasma protein profiles regarding the identification of proteins related to fertility scores. A total of 1779, 715, and 2163 proteins were identified in the ejaculate, seminal plasma, and spermatozoa, respectively. Among these datasets, 472 proteins were shared. GO enrichment analysis of the common proteins enabled us to distinguish biological processes such as single fertilization (GO:0007338), spermatid development (GO:0007286), and cell motility (GO:0048870). Among the abundant terms for GO cellular components, zona pellucida receptor complex, sperm fibrous sheath, and outer dense fiber were revealed. Overall, we identified 139 testis-specific proteins. For these proteins, PPI networks that are common in ejaculate, spermatozoa, and seminal plasma were related to the following GO biological processes: cilium movement (GO:0003341), microtubule-based movement (GO:0007018), and sperm motility (GO:0097722). For ejaculate and spermatozoa, they shared 15 common testis-specific proteins with spermatogenesis (GO:0007283) and male gamete generation (GO:0048232). Therefore, we speculated that ejaculate-based proteomics could yield new insights into the peculiar reproductive physiology and spermatozoa function of men and potentially serve as an explanation for male infertility screening.

Strain Q11T of an irregular coccoid Gram-positive bacterium, aerobic and non-motile, was isolated from Meconopsis integrifolia seeds. Strain Q11T grew optimally in 1% (w/v) NaCl, pH 7, at 30 °C. Strain Q11T is most closely related to Flexivirga, as evidenced by 16S rRNA gene analysis, and shares the highest similarity with Flexivirga aerilata ID2601ST (99.24%). Based on genome sequence analysis, the average nucleotide identity and digital DNA–DNA hybridization values of strains Q11T and D2601ST were 88.82% and 36.20%, respectively. Additionally, strain Q11T showed the abilities of nitrogen fixation and indole acetic acid production and was shown to promote maize growth under laboratory conditions. Its genome contains antibiotic resistance genes (the vanY gene in the vanB cluster and the vanW gene in the vanI cluster) and extreme environment tolerance genes (ectoine biosynthetic gene cluster). Shotgun proteomics also detected antibiotic resistance proteins (class A beta-lactamases, D-alanine ligase family proteins) and proteins that improve plant cold tolerance (multispecies cold shock proteins). Strain Q11T was determined to be a novel species of the genus Flexivirga, for which the name Flexivirga meconopsidis sp. nov. is proposed. The strain type is Q11T (GDMCC 1.3002T = JCM 36020 T).

Snakebite envenoming is one of the most significantly neglected tropical diseases in the world. The lack of diagnosis/prognosis methods for snakebite is one of our motivations to develop innovative technological solutions for Brazilian health. The objective of this work was to evaluate the protein and metallic ion composition of Crotalus durissus terrificus, Bothrops jararaca, B. alternatus, B. jararacussu, B. moojeni, B. pauloensis, and Lachesis muta muta snake venoms. Brazilian snake venoms were subjected to the shotgun proteomic approach using mass spectrometry, and metal ion analysis was performed by atomic spectrometry. Shotgun proteomics has shown three abundant toxin classes (PLA2, serine proteases, and metalloproteinases) in all snake venoms, and metallic ions analysis has evidenced that the Cu2+ ion is present exclusively in the L. m. muta venom; Ca2+ and Mg2+ ions have shown a statistical difference between the species of Bothrops and Crotalus genus, whereas the Zn2+ ion presented a statistical difference among all species studied in this work. In addition, Mg2+ ions have shown 42 times more in the C. d. terrificus venom when compared to the average concentration in the other genera. Though metal ions are a minor fraction of snake venoms, several venom toxins depend on them. We believe that these non-protein fractions are capable of assisting in the development of unprecedented diagnostic devices for Brazilian snakebites.

Abstract Extracellular matrix (ECM) proteins play a pivotal role in cell growth and differentiation. To characterize aged ECM proteins, we compared the proteomes by shotgun method of young (passage #15) and late senescent (passage #40) human dermal fibroblasts (HDFs) using SDS-PAGE coupled with LC–MS/MS. The relative abundance of identified proteins was determined using mol% of individual proteins as a semi-quantitative index. Fifteen ECM proteins including apolipoprotein B (APOB) and high-temperature requirement factor 1 (HTRA1) were up-regulated, whereas 50 proteins including fibronectin 1 (FN1) and vitronectin (VTN) were down-regulated in late senescent HDFs. The identified ECM proteins combined with plasma membrane were queried to construct the protein–protein interaction network using Ingenuity Pathways Analysis, resulting in a distinct FN1-centered network. Of differentially abundant ECM proteins in shotgun proteomics, the protein levels of FN1, VTN, APOB, and HTRA1 were verified by immunoblot analysis. The results suggest that the aging process in HDFs might be finally involved in the impaired FN1 regulatory ECM network combined with altered interaction of neighboring proteins. Shotgun proteomics of highly aged HDFs provides insight for further studies of late senescence-related alterations in ECM proteins.

Paspalum fasciculatum Willd. ex Flüggé grows in mining soils which are Cd- and Pb-contaminated where it exhibits tolerance to Pb and the ability to extract Pb from these soils. To elucidate tolerance mechanisms to Pb-stress, liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to quantify changes in the accumulation of proteins in leaves. We identified 323 proteins involved in primary metabolism and response to biotic or abiotic stresses. Although proteins involved in the processes of photosynthesis and saccharide and energy metabolism presented the greatest amount of down-regulated proteins, the plant was able to maintain photosynthetic functions and obtain energy to sustain the vital balance. P. fasciculatum based their tolerance on increased antioxidant defenses, improving the protection and repair of proteins and transduction signals to coordinate physiological response to Pb-stress. Our results provide important information to understand the tolerance mechanisms in P. fasciculatum and could be important in future molecular studies on the resistance and accumulation of Pb in plants. [ABSTRACT FROM AUTHOR]

Post-translational modifications (PTMs) are covalent changes occurring on amino acid side chains of proteins and yet are neglected structural and functional aspects of protein architecture. The objective was to detect differences in PTM profiles that take place after roasting using open PTM search. We conducted a bottom-up proteomic study to investigate the impact of peanut roasting on readily soluble allergens and their PTM profiles. Proteomic PTM profiling of certain modifications was confirmed by Western blotting with a series of PTM-specific antibodies. In addition to inducing protein aggregation and denaturation, roasting may facilitate change in their PTM pattern and relative profiling. We have shown that Ara h 1 is the most modified major allergen in both samples in terms of modification versatility and extent. The most frequent PTM was methionine oxidation, especially in roasted samples. PTMs uniquely found in roasted samples were hydroxylation (Trp), formylation (Arg/Lys), and oxidation or hydroxylation (Asn). Raw and roasted peanut extracts did not differ in the binding of IgE from the serum of peanut-sensitised individuals done by ELISA. This study provides a better understanding of how roasting impacts the PTM profile of major peanut allergens and provides a good foundation for further exploration of PTMs. [ABSTRACT FROM AUTHOR]

Fracture healing is a complex process in which the periosteum and endosteum become the main sources of osteoblast progenitor cells. However, cellular mechanisms and signaling cascades underlying the early stages of osteoblast progenitors differentiation in adult bone are still not well understood. Therefore, we performed shotgun proteomics analysis of primary culture of isolated human osteoblasts from femur of adult donors in undifferentiated conditions and on the fifth day of osteogenic differentiation in vitro. This is an early timepoint in which we have observed no extracellular matrix mineralization yet. 1612 proteins identified with at least two unique peptides were included in proteomics analysis. Data are available via ProteomeXchange with identifier PXD033697. Despite the fact, that matrix mineralization starts only after induction of osteogenic differentiation, we revealed unexpectedly weak physiological shift associated with a decrease of cells proliferative activity and changes in proteins involved in extracellular matrix secretion and organization. We demonstrated that osteoblasts were positive for markers of later osteogenic differentiation stages during standard cultivation: osteopontin, osteocalcin, BMP-2/4 and RUNX2. Therefore, further differentiation required for matrix mineralization needs minimal physiological changes. [ABSTRACT FROM AUTHOR]

Due to its outstanding throughput and analytical resolution, gel-free LC-based shotgun proteomics represents the gold standard of proteome analysis. Thereby, the efficiency of sample preparation dramatically affects the correctness and reliability of protein quantification. Thus, the steps of protein isolation, solubilization, and proteolysis represent the principal bottleneck of shotgun proteomics. The desired performance of the sample preparation protocols can be achieved by the application of detergents. However, these compounds ultimately compromise reverse-phase chromatographic separation and disrupt electrospray ionization. Filter-aided sample preparation (FASP) represents an elegant approach to overcome these limitations. Although this method is comprehensively validated for cell proteomics, its applicability to plants and compatibility with plant-specific protein isolation protocols remain to be confirmed. Thereby, the most important gap is the absence of the data on the linearity of underlying protein quantification methods for plant matrices. To fill this gap, we address here the potential of FASP in combination with two protein isolation protocols for quantitative analysis of pea (Pisum sativum) seed and Arabidopsis thaliana leaf proteomes by the shotgun approach. For this aim, in comprehensive spiking experiments with bovine serum albumin (BSA), we evaluated the linear dynamic range (LDR) of protein quantification in the presence of plant matrices. Furthermore, we addressed the interference of two different plant matrices in quantitative experiments, accomplished with two alternative sample preparation workflows in comparison to conventional FASP-based digestion of cell lysates, considered here as a reference. The spiking experiments revealed high sensitivities (LODs of up to 4 fmol) for spiked BSA and LDRs of at least 0.6 × 10². Thereby, phenol extraction yielded slightly better recoveries, whereas the detergent-based method showed better linearity. Thus, our results indicate the very good applicability of FASP to quantitative plant proteomics with only limited impact of the protein isolation technique on the method's overall performance. [ABSTRACT FROM AUTHOR]

Gel-free bottom-up shotgun proteomics is the principal methodological platform for the state-of-the-art proteome research. This methodology assumes quantitative isolation of the total protein fraction from a complex biological sample, its limited proteolysis with site-specific proteases, analysis of the resulted peptides with nanoscaled reversed-phase high-performance liquid chromatography-(tandem) mass spectrometry (nanoRP-HPLC-MS and MS/MS), protein identification by sequence database search and peptide-based quantitative analysis. The most critical steps of this workflow are protein reconstitution and digestion; therefore, detergents and chaotropic agents are strongly mandatory to ensure complete solubilization of complex protein isolates and to achieve accessibility of all protease cleavage sites. However, detergents are incompatible with both RP separation and electrospray ionization (ESI). Therefore, to make LC-MS analysis possible, several strategies were implemented in the shotgun proteomics workflow. These techniques rely either on enzymatic digestion in centrifugal filters with subsequent evacuation of the detergent, or employment of MS-compatible surfactants, which can be degraded upon the digestion. In this review we comprehensively address all currently available strategies for the detergent-assisted proteolysis in respect of their relative efficiency when applied to different biological matrices. We critically discuss the current progress and the further perspectives of these technologies in the context of its advances and gaps. [ABSTRACT FROM AUTHOR]

RNA editing by adenosine deaminases of the ADAR family can lead to protein recoding, since inosine formed from adenosine in mRNA is complementary to cytosine; the resulting codon editing might introduce amino acid substitutions into translated proteins. Proteome recoding can have functional consequences which have been described in many animals including humans. Using protein recoding database derived from publicly available transcriptome data, we identified for the first time the recoding sites in the zebrafish shotgun proteomes. Out of more than a hundred predicted recoding events, ten substitutions were found in six used datasets. Seven of them were in the AMPA glutamate receptor subunits, whose recoding has been well described, and are conserved among vertebrates. Three sites were specific for zebrafish proteins and were found in the transmembrane receptors astrotactin 1 and neuregulin 3b (proteins involved in the neuronal adhesion and signaling) and in the rims2b gene product (presynaptic membrane protein participating in the neurotransmitter release), respectively. Further studies are needed to elucidate the role of recoding of the said three proteins in the zebrafish. [ABSTRACT FROM AUTHOR]