The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition

Local burn wound environment versus systemic response: Comparison of proteins and metabolites

In this study, paired blood plasma (BP) and blister fluid (BF) samples from five paediatric burn patients were analysed using mass spectrometry to compare their protein and metabolite composition. The relative quantification of proteins was achieved through a label-free data independent acquisition mode. The relative quantification of metabolites was achieved using a Shimadzu Smart Metabolite Database gas chromatography mass spectrometry (GCMS) targeted assay. In total, 562 proteins and 141 individual metabolites were identified in the samples. There was 81% similarity in the proteins present in the BP and BF, with 50 and 54 unique proteins found in each sample type respectively. BF contained keratinocyte proliferation-related proteins and blood plasma contained abundant blood clotting proteins and apolipoproteins. BF contained more carbohydrates and less alpha-hydroxy acid metabolites than the BP. In this study, there were unique proteins and metabolites in BF and BP which were reflective of the local wound environment and systemic environments respectively. The results from this study demonstrate that the biomolecule content of BF is mostly the same as blood, but it also contains information specific to the local wound environment.

MetaProClust-MS1: an MS1 Profiling Approach for Large-Scale Microbiome Screening

Metaproteomics is used to explore the functional dynamics of microbial communities. However, acquiring metaproteomic data by tandem mass spectrometry (MS/MS) is time-consuming and resource-intensive, and there is a demand for computational methods that can be used to reduce these resource requirements. We present MetaProClust-MS1, a computational framework for microbiome feature screening developed to prioritize samples for follow-up MS/MS. In this proof-of-concept study, we tested and compared MetaProClust-MS1 results on gut microbiome data, from fecal samples, acquired using short 15-min MS1-only chromatographic gradients and MS1 spectra from longer 60-min gradients to MS/MS-acquired data. We found that MetaProClust-MS1 identified robust gut microbiome responses caused by xenobiotics with significantly correlated cluster topologies of comparable data sets. We also used MetaProClust-MS1 to reanalyze data from both a clinical MS/MS diagnostic study of pediatric patients with inflammatory bowel disease and an experiment evaluating the therapeutic effects of a small molecule on the brain tissue of Alzheimer's disease mouse models. MetaProClust-MS1 clusters could distinguish between inflammatory bowel disease diagnoses (ulcerative colitis and Crohn's disease) using samples from mucosal luminal interface samples and identified hippocampal proteome shifts of Alzheimer's disease mouse models after small-molecule treatment. Therefore, we demonstrate that MetaProClust-MS1 can screen both microbiomes and single-species proteomes using only MS1 profiles, and our results suggest that this approach may be generalizable to any proteomics experiment. MetaProClust-MS1 may be especially useful for large-scale metaproteomic screening for the prioritization of samples for further metaproteomic characterization, using MS/MS, for instance, in addition to being a promising novel approach for clinical diagnostic screening. IMPORTANCE Growing evidence suggests that human gut microbiome composition and function are highly associated with health and disease. As such, high-throughput metaproteomic studies are becoming more common in gut microbiome research. However, using a conventional long liquid chromatography (LC)-MS/MS gradient metaproteomics approach as an initial screen in large-scale microbiome experiments can be slow and expensive. To combat this challenge, we introduce MetaProClust-MS1, a computational framework for microbiome screening using MS1-only profiles. In this proof-of-concept study, we show that MetaProClust-MS1 identifies clusters of gut microbiome treatments using MS1-only profiles similar to those identified using MS/MS. Our approach allows researchers to prioritize samples and treatments of interest for further metaproteomic analyses and may be generally applicable to any proteomic analysis. In particular, this approach may be especially useful for large-scale metaproteomic screening or in clinical settings where rapid diagnostic evidence is required.

Serum Proteomic and Oxidative Modification Profiling in Mice Exposed to Total Body X-Irradiation

The details of the dose-dependent response of serum proteins exposed to ionizing radiation, especially the oxidative modification response in amino acid sequences of albumin, the most abundant protein, are unknown. Thus, a proteomic analysis of the serum components from mice exposed to total body X-irradiation (TBI) ranging from 0.5 Gy to 3.0 Gy was conducted using LC-MS/MS. The analysis of oxidative modification sequences of albumin (mOMSA) in TBI mouse serum revealed significant moderate or strong correlations between the X-irradiation exposure dose and modification of 11 mOMSAs (especially the 97th, 267th and 499th lysine residues, 159th methionine residue and 287th tyrosine residues). In the case of X-irradiation of serum alone, significant correlations were also found in the 14 mOMSAs. In addition, a dose-dependent variation in six proteins (Angiotensinogen, Odorant-binding protein 1a, Serine protease inhibitor A3K, Serum paraoxonase/arylesterase 1, Prothrombin and Epidermal growth factor receptor) was detected in the serum of mice exposed to TBI. These findings suggest the possibility that the protein variation and serum albumin oxidative modification responses found in exposed individuals are important indicators for considering the effects of radiation on living organisms, along with DNA damage, and suggests their possible application as biomarkers of radiation dose estimation.

An Optimized Comparative Proteomic Approach as a Tool in Neurodegenerative Disease Research

Recent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteome coverage but rather by insufficient analyses. Proteomic experimentation requires a careful methodological selection to account for variables from sample collection, through to database searches for peptide identification to standardised post-mass spectrometry options directed analysis workflow, which should be adjusted for each study, from determining when and how to filter proteomic data to choosing holistic versus trend-wise analyses for biologically relevant patterns. Finally, we highlight and discuss the difficulties inherent in the modelling and study of the majority of progressive neurodegenerative conditions. We provide evidence (in the context of neurodegenerative research) for the benefit of undertaking a comparative approach through the application of the above considerations in the alignment of publicly available pre-existing data sets to identify potential novel regulators of neuronal stability.

Quantitative bile and serum proteomics for the screening and differential diagnosis of primary sclerosing cholangitis

Background

Primary sclerosing cholangitis (PSC) is a chronic liver disease characterized by biliary strictures, cholestasis, and a markedly increased risk of cholangiocarcinoma. New markers for the screening and differential diagnosis of PSC are needed. In this pilot study, we have analyzed both the bile and serum proteomic profiles of 80 PSC patients and non-PSC controls (n = 6 for bile and n = 18 for serum).

Aim

The aim of this study was to discover candidates for new biomarkers for the differential diagnosis of PSC.

Methods

Bile and serum samples were processed and subsequently analyzed using ultra performance liquid chromatography-ultra definition mass spectrometry (UPLC-UDMSE). Further analysis included statistical analyses such as receiver operating characteristic curve analysis as well as pathway analysis using Ingenuity Pathway Analysis.

Results and conclusions

In bile, we discovered 64 proteins with significantly different levels between the groups, with fold changes of up to 129. In serum, we discovered 112 proteins with significantly different levels. Receiver operating characteristic curve analysis found multiple proteins with high area under the curve values, up to 0.942, indicating that these serum proteins are of value as new non-invasive classifiers of PSC. Pathway analysis revealed multiple canonical pathways that were enriched in the dataset, which have roles in bile homeostasis and metabolism. We present several serum proteins that could serve as new blood-based markers for the diagnosis of PSC after further validation. The measurement of serum levels of these proteins could be of use in the screening of patients with suspected PSC.

Prognostic Value of Molecular Intratumor Heterogeneity in Primary Oral Cancer and Its Lymph Node Metastases Assessed by Mass Spectrometry Imaging

Different aspects of intra-tumor heterogeneity (ITH), which are associated with the development of cancer and its response to treatment, have postulated prognostic value. Here we searched for potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients which enabled their separation into two groups: with no evidence of disease (NED, n = 41) and with progressive disease (PD, n = 36). After on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Furthermore, a positive correlation between ITH and histopathological lymphocytic host response was observed. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment.

Ezrin deficiency triggers glial fibrillary acidic protein upregulation and a distinct reactive astrocyte phenotype

Astrocytes are increasingly being recognized as contributors to physiological brain function and behavior. Astrocytes engage in glia-synaptic interactions through peripheral astrocyte processes, thus modulating synaptic signaling, for example, by handling glutamate removal from the synaptic cleft and (re)provision to axonal terminals. Peripheral astrocyte processes are ultrafine membrane protrusions rich in the membrane-to-actin cytoskeleton linker Ezrin, an essential component of in vitro filopodia formation and in vivo peripheral astrocyte process motility. Consequently, it has been postulated that Ezrin significantly contributes to neurodevelopment as well as astrocyte functions within the adult brain. However, while Ezrin has been studied in vitro within cultured primary astrocytes, in vivo studies on the role of Ezrin in astrocytes remain to be conducted and consequences of its depletion to be studied. Here, we investigated consequences of Ezrin deletion in the mouse brain starting from early neuronal specification. While Ezrin knockout did not impact prenatal cerebral cortex development, behavioral phenotyping depicted reduced exploratory behavior. Starting with postnatal appearance of glia cells, Ezrin was verified to remain predominantly expressed in astrocytes. Proteome analysis of Ezrin deficient astrocytes revealed alterations in glutamate and ion homeostasis, metabolism and cell morphology - important processes for synaptic signal transmission. Notably, Ezrin deletion in astrocytes provoked (GFAP) glial fibrillary acidic protein upregulation - a marker of astrocyte activation and reactive astrogliosis. However, this spontaneous, reactive astrogliosis exhibited proteome changes distinct from ischemic-induced reactive astrogliosis. Moreover, in experimental ischemic stroke, Ezrin knockout mice displayed reduced infarct volume, indicating a protective effect of the Ezrin deletion-induced changes and astrogliosis.

Pulse labeling reveals the tail end of protein folding by proteome profiling

Accurate and efficient folding of nascent protein sequences into their native states requires support from the protein homeostasis network. Herein we probe which newly translated proteins are thermo-sensitive, making them susceptible to misfolding and aggregation under heat stress using pulse-SILAC mass spectrometry. We find a distinct group of proteins that is highly sensitive to this perturbation when newly synthesized but not once matured. These proteins are abundant and highly structured. Notably, they display a tendency to form β sheet secondary structures, have more complex folding topology, and are enriched for chaperone-binding motifs, suggesting a higher demand for chaperone-assisted folding. These polypeptides are also more often components of stable protein complexes in comparison with other proteins. Combining these findings suggests the existence of a specific subset of proteins in the cell that is particularly vulnerable to misfolding and aggregation following synthesis before reaching the native state.

Uncoupling of Mitosis and Cytokinesis Upon a Prolonged Arrest in Metaphase Is Influenced by Protein Phosphatases and Mitotic Transcription in Fission Yeast

Depletion of the Anaphase-Promoting Complex/Cyclosome (APC/C) activator Cdc20 arrests cells in metaphase with high levels of the mitotic cyclin (Cyclin B) and the Separase inhibitor Securin. In mammalian cells this arrest has been exploited for the treatment of cancer with drugs that engage the spindle assembly checkpoint and, recently, with chemical inhibitors of the APC/C. While most cells arrested in mitosis for prolonged periods undergo apoptosis, others skip cytokinesis and enter G1 with unsegregated chromosomes. This process, known as mitotic slippage, generates aneuploidy and increases genomic instability in the cancer cell. Here, we analyze the behavior of fission yeast cells arrested in mitosis through the transcriptional silencing of the Cdc20 homolog slp1. While depletion of slp1 readily halts cells in metaphase, this arrest is only transient and a majority of cells eventually undergo cytokinesis and show steady mitotic dephosphorylation. Notably, this occurs in the absence of Cyclin B (Cdc13) degradation. We investigate the involvement of phosphatase activity in these events and demonstrate that PP2A-B55^Pab1 is required to prevent septation and, during the arrest, its CDK-mediated inhibition facilitates the induction of cytokinesis. In contrast, deletion of PP2A-B56^Par1 completely abrogates septation. We show that this effect is partly due to this mutant entering mitosis with reduced CDK activity. Interestingly, both PP2A-B55^Pab1 and PP2A-B56^Par1, as well as Clp1 (the homolog of the budding yeast mitotic phosphatase Cdc14) are required for the dephosphorylation of mitotic substrates during the escape. Finally, we show that the mitotic transcriptional wave controlled by the RFX transcription factor Sak1 facilitates the induction of cytokinesis and also requires the activity of PP2A-B56^Par1 in a mechanism independent of CDK.

Proteomic analysis of low- and high-grade human colon adenocarcinoma tissues and tissue-derived primary cell lines reveals unique biological functions of tumours and new protein biomarker candidates

Background

Colon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.

Methods

Four low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.

Results

A total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.

Conclusions

The differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09364-y.

Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine

Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.

Multiple Myeloma-Derived Extracellular Vesicles Modulate the Bone Marrow Immune Microenvironment

Multiple myeloma (MM), the third most frequent hematological cancer worldwide, is characterized by the proliferation of neoplastic plasma cells in the bone marrow (BM). One of the hallmarks of MM is a permissive BM microenvironment. Increasing evidence suggests that cell-to-cell communication between myeloma and immune cells via tumor cell-derived extracellular vesicles (EV) plays a key role in the pathogenesis of MM. Hence, we aimed to explore BM immune alterations induced by MM-derived EV. For this, we inoculated immunocompetent BALB/cByJ mice with a myeloma cell line, MOPC315.BM, inducing a MM phenotype. Upon tumor establishment, characterization of the BM microenvironment revealed the expression of both activation and suppressive markers by lymphocytes, such as granzyme B and PD-1, respectively. In addition, conditioning of the animals with MOPC315.BM-derived EV, before transplantation of the MOPC315.BM tumor cells, did not anticipate the disease phenotype. However, it induced features of suppression in the BM milieu, such as an increase in PD-1 expression by CD4+ T cells. Overall, our findings reveal the involvement of MOPC315.BM-derived EV protein content as promoters of immune niche remodeling, strengthening the importance of assessing the mechanisms by which MM may impact the immune microenvironment.

Proteomic repository data submission, dissemination, and reuse: key messages

INTRODUCTION

The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public.

AREAS COVERED

Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed.

EXPERT OPINION

The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.

HSP90 and Aha1 modulate microRNA maturation through promoting the folding of Dicer1

Aha1 is a co-chaperone of heat shock protein 90 (HSP90), and it stimulates the ATPase activity of HSP90 to promote the folding of its client proteins. By employing ascorbate peroxidase (APEX)-based proximity labeling and proteomic analysis, we identified over 30 proteins exhibiting diminished abundances in the proximity proteome of HSP90 in HEK293T cells upon genetic depletion of Aha1. Dicer1 is a top-ranked protein, and we confirmed its interactions with HSP90 and Aha1 by immunoprecipitation followed by western blot analysis. Genetic depletion of Aha1 and pharmacological inhibition of HSP90 both led to reduced levels of Dicer1 protein. Additionally, HSP90 and Aha1 bind preferentially to newly translated Dicer1. Reconstitution of Aha1-depleted cells with wild-type Aha1 substantially rescued Dicer1 protein level, and a lower level of restoration was observed for complementation with the HSP90-binding-defective Aha1-E67K, whereas an Aha1 mutant lacking the first 20 amino acids-which abolishes its chaperone activity-failed to rescue Dicer1 protein level. Moreover, knockdown of Aha1 and inhibition of HSP90 led to diminished levels of mature microRNAs (miRNAs), but not their corresponding primary miRNAs. Together, we uncovered a novel mechanism of HSP90 and Aha1 in regulating the miRNA pathway through promoting the folding of Dicer1 protein, and we also demonstrated that Aha1 modulates this process by acting as an autonomous chaperone and a co-chaperone for HSP90.

Patient-Derived Extracellular Vesicles Proteins as New Biomarkers in Multiple Myeloma - A Real-World Study

Multiple myeloma (MM) is a hematological malignancy of clonal antibody–secreting plasma cells (PCs). MM diagnosis and risk stratification rely on bone marrow (BM) biopsy, an invasive procedure prone to sample bias. Liquid biopsies, such as extracellular vesicles (EV) in peripheral blood (PB), hold promise as new minimally invasive tools. Real-world studies analyzing patient-derived EV proteome are rare. Here, we characterized a small EV protein content from PB and BM samples in a cohort of 102 monoclonal gammopathies patients routinely followed in the clinic and 223 PB and 111 BM samples were included. We investigated whether EV protein and particle concentration could predict an MM patient prognosis. We found that a high EV protein/particle ratio, or EV cargo >0.6 µg/108 particles, is related to poorer survival and immune dysfunction. These results were supported at the protein level by mass spectrometry. We report a set of PB EV-proteins (PDIA3, C4BPA, BTN1A1, and TNFSF13) with a new biomarker potential for myeloma patient outcomes. The high proteomic similarity between PB and BM matched pairs supports the use of circulating EV as a counterpart of the BM EV proteome. Overall, we found that the EV protein content is related to patient outcomes, such as survival, immune dysfunction, and possibly treatment response.

Proteomics and phosphoproteomics datasets of a muscle-specific STIM1 loss-of-function mouse model

STIM1 is an ER/SR transmembrane protein that interacts with ORAI1 to activate store operated Ca2+ entry (SOCE) upon ER/SR depletion of calcium. Normally highly expressed in skeletal muscle, STIM1 deficiency causes significant changes to mitochondrial ultrastructure that do not occur with loss of ORAI1 or other components of SOCE. The datasets in this article are from large-scale proteomics and phosphoproteomics experiments in an inducible mouse model of skeletal muscle-specific STIM1 knock out (KO). These data reveal statistically significant changes in the relative abundance of specific proteins and sites of protein phosphorylation in STIM1 KO gastrocnemius. Protein samples from five biological replicates of each condition (+/- STIM1) were enzymatically digested, the resulting peptides labeled with tandem mass tag (TMT) reagents, mixed, and fractionated. Phosphopeptides were enriched and a small amount of each input retained for protein abundance analysis. All phosphopeptide and input fractions were analyzed by nano LC-MS/MS on a Q Exactive Plus Orbitrap mass spectrometer, searched with Proteome Discoverer software, and processed with in-house R-scripts for data normalization and statistical analysis. Article published in Molecular Metabolism [1].

Regulatory Modules of Metabolites and Protein Phosphorylation in Arabidopsis Genotypes With Altered Sucrose Allocation

Multi-omics data sets are increasingly being used for the interpretation of cellular processes in response to environmental cues. Especially, the posttranslational modification of proteins by phosphorylation is an important regulatory process affecting protein activity and/or localization, which, in turn, can have effects on metabolic processes and metabolite levels. Despite this importance, relationships between protein phosphorylation status and metabolite abundance remain largely underexplored. Here, we used a phosphoproteomics-metabolomics data set collected at the end of day and night in shoots and roots of Arabidopsis to propose regulatory relationships between protein phosphorylation and accumulation or allocation of metabolites. For this purpose, we introduced a novel, robust co-expression measure suited to the structure of our data sets, and we used this measure to construct metabolite-phosphopeptide networks. These networks were compared between wild type and plants with perturbations in key processes of sugar metabolism, namely, sucrose export (sweet11/12 mutant) and starch synthesis (pgm mutant). The phosphopeptide-metabolite network turned out to be highly sensitive to perturbations in sugar metabolism. Specifically, KING1, the regulatory subunit of SnRK1, was identified as a primary candidate connecting protein phosphorylation status with metabolism. We additionally identified strong changes in the fatty acid network of the sweet11/12 mutant, potentially resulting from a combination of fatty acid signaling and metabolic overflow reactions in response to high internal sucrose concentrations. Our results further suggest novel protein-metabolite relationships as candidates for future targeted research.

Predicting fragment intensities and retention time of iTRAQ- and TMTPro-labeled peptides with Prosit-TMT

Isobaric labeling increases the throughput of proteomics by enabling the parallel identification and quantification of peptides and proteins. Over the past decades, a variety of isobaric tags have been developed allowing the multiplexed analysis of up to 18 samples. However, experiments utilizing such tags often exhibit reduced identification rates and thus show decreased analytical depth. Re-scoring has been shown to rescue otherwise missed identifications but was not yet systematically applied on isobarically labeled data. Because iTRAQ 4/8-plex and the recently released TMTpro 16/18-plex share similar characteristics with TMT 6/10/11-plex, we hypothesized that Prosit-TMT, trained exclusively on 6/10/11-plex labeled peptides, may be applicable to these isobaric labeling strategies as well. To investigate this, we re-analyzed nine publicly available datasets covering iTRAQ and TMTpro labeling for samples with human and mouse origin. We highlight that Prosit-TMT shows remarkably good performance when comparing experimentally acquired and predicted fragmentation spectra (R of 0.84 - 0.9) and retention times (ΔRT95% of 3 - 10% gradient time) of peptides. Furthermore, re-scoring substantially increases the number of confidently identified spectra, peptides, and proteins. This article is protected by copyright. All rights reserved.

Activated SUMOylation restricts MHC class I antigen presentation to confer immune evasion in cancer

Activated SUMOylation is a hallmark of cancer. Starting from a targeted screening for SUMO-regulated immune evasion mechanisms, we identified an evolutionarily conserved function of activated SUMOylation, which attenuated the immunogenicity of tumor cells. Activated SUMOylation allowed cancer cells to evade CD8⁺ T cell–mediated immunosurveillance by suppressing the MHC class I (MHC-I) antigen-processing and presentation machinery (APM). Loss of the MHC-I APM is a frequent cause of resistance to cancer immunotherapies, and the pharmacological inhibition of SUMOylation (SUMOi) resulted in reduced activity of the transcriptional repressor scaffold attachment factor B (SAFB) and induction of the MHC-I APM. Consequently, SUMOi enhanced the presentation of antigens and the susceptibility of tumor cells to CD8⁺ T cell–mediated killing. Importantly, SUMOi also triggered the activation of CD8⁺ T cells and thereby drove a feed-forward loop amplifying the specific antitumor immune response. In summary, we showed that activated SUMOylation allowed tumor cells to evade antitumor immunosurveillance, and we have expanded the understanding of SUMOi as a rational therapeutic strategy for enhancing the efficacy of cancer immunotherapies.

Multi-omics reveals mitochondrial metabolism proteins susceptible for drug discovery in AML

Acute myeloid leukemia (AML) is a devastating cancer affecting the hematopoietic system. Previous research has relied on RNA sequencing and microarray techniques to study the downstream effects of genomic alterations. While these studies have proven efficacious, they fail to capture the changes that occur at the proteomic level. To interrogate the effect of protein expression alterations in AML, we performed a quantitative mass spectrometry in parallel with RNAseq analysis using AML mouse models. These combined results identified 34 proteins whose expression was upregulated in AML tumors, but strikingly, were unaltered at the transcriptional level. Here we focus on mitochondrial electron transfer proteins ETFA and ETFB. Silencing of ETFA and ETFB led to increased mitochondrial activity, mitochondrial stress, and apoptosis in AML cells, but had little to no effect on normal human CD34+ cells. These studies identify a set of proteins that have not previously been associated with leukemia and may ultimately serve as potential targets for therapeutic manipulation to hinder AML progression and help contribute to our understanding of the disease.

Detection of biological responses to low-dose radiation in humans

It has been considered difficult to detect the biological effects of low-dose radiation exposure below approximately 100 mSv in humans. Serum proteomic analysis and oxidative modification profiling were conducted with blood samples collected from residents of a newly discovered high-level natural background radiation area (annual effective dose approximately 50 mSv y^-1) and normal-level area (1.22 mSv y^-1) in Mamuju, Indonesia, where many people have been living for generations. Dose-dependent oxidative modifications in amino acid sequences of human serum albumin, especially the 162^nd and 356^th tyrosine residues and 111^th and 470^th methionine residues, were found. None of these findings have been reported in humans exposed to chronic low-dose radiation. It can be used as a biomarker not only for the assessment of the presence or absence of radiation exposure but also for dose prediction in living organisms for chronic radiation. These results suggest that traces of radiation exposure are recorded in serum albumin and that there is a possibility of a new methodology that can evaluate biological responses below 100 mSv.

Suboptimal folic acid exposure rewires oncogenic metabolism and proteomics signatures to mediate human breast cancer malignancy

Whether treatment with folic acid (FA) affects human breast cancer positively or negatively remains unclear. We subjected human MCF-7 cells, a human breast cancer cell line, to suboptimal FA at low levels (10 nM; LF) and high levels (50 μM; HF) and investigated the molecular mechanisms underlying their effects through metabolic flux and systematic proteomics analyses. The data indicated that LF induced and HF aggravated 2-fold higher mitochondrial toxicity in terms of suppressed oxidative respiration, increased fermented glycolysis, and enhanced anchorage-independent oncospheroid formation. Quantitative proteomics and Gene Ontology enrichment analysis were used to profile LF- and HF-altered proteins involved in metabolism, apoptosis, and malignancy pathways. Through STRING analysis, we identified a connection network between LF- and HF-altered proteins with mTOR. Rapamycin-induced blockage of mTOR complex 1 (mTORC1) signaling, which regulates metabolism, differentially inhibited LF- and HF-modulated protein signatures of mitochondrial NADH dehydrogenase ubiquinone flavoprotein 2, mitochondrial glutathione peroxidase 4, kynureninase, and alpha-crystallin B chain as well as programmed cell death 5 in transcript levels; it subsequently diminished apoptosis and oncospheroid formation in LF/HF-exposed cells. Taken together, our data indicate that suboptimal FA treatment rewired oncogenic metabolism and mTORC1-mediated proteomics signatures to promote breast cancer development.

Specific inflammatory osteoclast precursors induced during chronic inflammation give rise to highly active osteoclasts associated with inflammatory bone loss

Elevated osteoclast (OC) activity is a major contributor to inflammatory bone loss (IBL) during chronic inflammatory diseases. However, the specific OC precursors (OCPs) responding to inflammatory cues and the underlying mechanisms leading to IBL are poorly understood. We identified two distinct OCP subsets: Ly6C^hiCD11b^hi inflammatory OCPs (iOCPs) induced during chronic inflammation, and homeostatic Ly6C^hiCD11b^lo OCPs (hOCPs) which remained unchanged. Functional and proteomic characterization revealed that while iOCPs were rare and displayed low osteoclastogenic potential under normal conditions, they expanded during chronic inflammation and generated OCs with enhanced activity. In contrast, hOCPs were abundant and manifested high osteoclastogenic potential under normal conditions but generated OCs with low activity and were unresponsive to the inflammatory environment. Osteoclasts derived from iOCPs expressed higher levels of resorptive and metabolic proteins than those generated from hOCPs, highlighting that different osteoclast populations are formed by distinct precursors. We further identified the TNF-α and S100A8/A9 proteins as key regulators that control the iOCP response during chronic inflammation. Furthermore, we demonstrated that the response of iOCPs but not that of hOCPs was abrogated in tnf-α^-/- mice, in correlation with attenuated IBL. Our findings suggest a central role for iOCPs in IBL induction. iOCPs can serve as potential biomarkers for IBL detection and possibly as new therapeutic targets to combat IBL in a wide range of inflammatory conditions.

SP3-Enabled Rapid and High Coverage Chemoproteomic Identification of Cell-State-Dependent Redox-Sensitive Cysteines

Proteinaceous cysteine residues act as privileged sensors of oxidative stress. As reactive oxygen and nitrogen species have been implicated in numerous pathophysiological processes, deciphering which cysteines are sensitive to oxidative modification and the specific nature of these modifications is essential to understanding protein and cellular function in health and disease. While established mass spectrometry-based proteomic platforms have improved our understanding of the redox proteome, the widespread adoption of these methods is often hindered by complex sample preparation workflows, prohibitive cost of isotopic labeling reagents, and requirements for custom data analysis workflows. Here, we present the SP3-Rox redox proteomics method that combines tailored low cost isotopically labeled capture reagents with SP3 sample cleanup to achieve high throughput and high coverage proteome-wide identification of redox-sensitive cysteines. By implementing a customized workflow in the free FragPipe computational pipeline, we achieve accurate MS1-based quantitation, including for peptides containing multiple cysteine residues. Application of the SP3-Rox method to cellular proteomes identified cysteines sensitive to the oxidative stressor GSNO and cysteine oxidation state changes that occur during T cell activation.

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High-coverage Cys oxidation state quantification using custom isotopic probes.

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FragPipe-IonQuant accurately quantifies Cys labeling comparably to Skyline.

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PTMProphet enables site-of-labeling localization for multi-Cys–containing peptides.

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SP3-Rox identifies changes in Cys oxidation during T cell activation.

Metaproteomics, Heterotrophic Growth, and Distribution of Nitrosomonas europaea and Nitrobacter winogradskyi after Long-Term Operation of an Autotrophic Nitrifying Biofilm Reactor

Bioregenerative life support systems (BLSS) are currently in development to tackle low recovery efficiencies, high energy demands, as well as food, water, and oxygen production challenges through the regeneration of nutrients from waste streams. The MELiSSA pilot plant has been developed as a testbed for regenerative life support system bioreactor operation and characterization. As nitrogen is a vital resource in such systems, we studied the functional composition of a new packed-bed nitrifying bioreactor inoculated with a co-culture of Nitrosomonas europaea (ATCC 25978) and Nitrobacter winogradskyi (ATCC 25391). After 840 days of autotrophic continuous cultivation, the packed-bed was sampled at five vertical positions, each with three horizontal positions, and the biomass at each position was characterized via qPCR, 16S amplicon sequencing, and liquid chromatography tandem mass spectrometry. The total number of cells within the different sections fluctuated around 8.95 ± 5.10 × 107 cells/mL of beads. Based on 16S amplicons and protein content, N. europaea and N. winogradskyi constituted overall 44.07 ± 11.75% and 57.53 ± 12.04% of the nitrifying bioreactor, respectively, indicating the presence of a heterotrophic population that, even after such a long operation time, did not affect the nitrification function of the bioreactor. In addition, DNA-based abundance estimates showed that N. europaea was slightly more abundant than N. winogradskyi, whereas protein-based abundance estimates indicated a much higher abundance of N. europaea. This highlights that single-method approaches need to be carefully interpreted in terms of overall cell abundance and metabolic activity.

Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces

Bottom-up proteomics is a powerful method for the functional characterization of mouse gut microbiota. To date, most of the bottom-up proteomics studies of the mouse gut rely on limited amounts of fecal samples. With mass-limited samples, the performance of such analyses is highly dependent on the protein extraction protocols and contaminant removal strategies. Here, protein extraction protocols (using different lysis buffers) and contaminant removal strategies (using different types of filters and beads) were systematically evaluated to maximize quantitative reproducibility and the number of identified proteins. Overall, our results recommend a protein extraction method using a combination of sodium dodecyl sulfate (SDS) and urea in Tris-HCl to yield the greatest number of protein identifications. These conditions led to an increase in the number of proteins identified from gram-positive bacteria, such as Firmicutes and Actinobacteria, which is a challenging task. Our analysis further confirmed these conditions led to the extraction of non-abundant bacterial phyla such as Proteobacteria. In addition, we found that, when coupled to our optimized extraction method, suspension trap (S-Trap) outperforms other contaminant removal methods by providing the most reproducible method while producing the greatest number of protein identifications. Overall, our optimized sample preparation workflow is straightforward and fast, and requires minimal sample handling. Furthermore, our approach does not require high amounts of fecal samples, a vital consideration in proteomics studies where mice produce smaller amounts of feces due to a particular physiological condition. Our final method provides efficient digestion of mouse fecal material, is reproducible, and leads to high proteomic coverage for both host and microbiome proteins.

Comment on: The m6A Reader IGF2BP2 Regulates Macrophage Phenotypic Activation and Inflammatory Diseases by Stabilizing TSC1 and PPARγ

Recently, first insights into the regulation and the role of the RNA-binding protein IMP2 in macrophage activation have been published by Wang et al. This study addresses differences in the regulation of IMP2 between the human and murine system. While the expression of IMP2 in anti-inflammatory macrophages is synchronous in mice and men, IMP2 expression is regulated differently in inflammatory macrophages.

Protein Expression of AEBP1, MCM4, and FABP4 Differentiate Osteogenic, Adipogenic, and Mesenchymal Stromal Stem Cells

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

Novel feature selection method via kernel tensor decomposition for improved multi-omics data analysis

BACKGROUND

Feature selection of multi-omics data analysis remains challenging owing to the size of omics datasets, comprising approximately [Formula: see text]-[Formula: see text] features. In particular, appropriate methods to weight individual omics datasets are unclear, and the approach adopted has substantial consequences for feature selection. In this study, we extended a recently proposed kernel tensor decomposition (KTD)-based unsupervised feature extraction (FE) method to integrate multi-omics datasets obtained from common samples in a weight-free manner.

METHOD

KTD-based unsupervised FE was reformatted as the collection of kernelized tensors sharing common samples, which was applied to synthetic and real datasets.

RESULTS

The proposed advanced KTD-based unsupervised FE method showed comparative performance to that of the previously proposed KTD method, as well as tensor decomposition-based unsupervised FE, but required reduced memory and central processing unit time. Moreover, this advanced KTD method, specifically designed for multi-omics analysis, attributes P values to features, which is rare for existing multi-omics-oriented methods.

CONCLUSIONS

The sample R code is available at https://github.com/tagtag/MultiR/ .

Characterization of Glycoproteoforms of Integrins α2 and β1 in Megakaryocytes in the Occurrence of JAK2V617F Mutation-Induced Primary Myelofibrosis

Primary myelofibrosis (PMF) is a neoplasm prone to leukemic transformation, for which limited treatment is available. Among individuals diagnosed with PMF, the most prevalent mutation is the JAK2V617F somatic point mutation that activates the Janus kinase 2 (JAK2) enzyme. Our earlier reports on hyperactivity of β1 integrin and enhanced adhesion activity of the α2β1 complex in JAK2V617F megakaryocytes (MKs) led us to examine the new hypothesis that this mutation leads to posttranslational modification via changes in glycosylation. Samples were derived from immunoprecipitation of MKs obtained from Vav1-hJAK2^V617F and WT mice. Immunoprecipitated fractions were separated by SDS-PAGE and analyzed using LC-MS/MS techniques in a bottom-up glycoproteomics workflow. In the immunoprecipitate, glycopeptiforms corresponding to 11 out of the 12 potential N-glycosylation sites of integrin β1 and to all nine potential glycosylation sites of integrin α2 were observed. Glycopeptiforms were compared across WT and JAK2V617F phenotypes for both integrins. The overall trend observed is that JAK2V617F mutation in PMF MKs leads to changes in β1 glycosylation; in most cases, it results in an increase in the integrated area of glycopeptiforms. We also observed that in mutated MKs, changes in integrin α2 glycosylation were more substantial than those observed for integrin β1 glycosylation, a finding that suggests that altered integrin α2 glycosylation may also affect activation. Additionally, the identification of proteins associated to the cytoskeleton that were co-immunoprecipitated with integrins α2 and β1 demonstrated the potential of the methodology employed in this study to provide some insight, at the peptide level, into the consequences of integrin activation in MKs. The extensive and detailed glycosylation patterns we uncovered provide a basis for future functional studies of each site in control cells as compared to JAK2V617F-mutated cells. Data are available via ProteomeXchange with identifier PXD030550.

PLCG1 is required for AML1-ETO leukemia stem cell self-renewal

In an effort to identify novel drugs targeting fusion-oncogene-induced acute myeloid leukemia (AML), we performed high-resolution proteomic analysis. In AML1-ETO (AE)-driven AML, we uncovered a deregulation of phospholipase C (PLC) signaling. We identified PLCgamma 1 (PLCG1) as a specific target of the AE fusion protein that is induced after AE binding to intergenic regulatory DNA elements. Genetic inactivation of PLCG1 in murine and human AML inhibited AML1-ETO dependent self-renewal programs, leukemic proliferation, and leukemia maintenance in vivo. In contrast, PLCG1 was dispensable for normal hematopoietic stem and progenitor cell function. These findings are extended to and confirmed by pharmacologic perturbation of Ca++-signaling in AML1-ETO AML cells, indicating that the PLCG1 pathway poses an important therapeutic target for AML1-ETO+ leukemic stem cells.

Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

Rapid and precise diagnostic methods are required to control emerging infectious diseases effectively. Human body fluids are attractive clinical samples for discovering diagnostic targets because they reflect the clinical statuses of patients and most of them can be obtained with minimally invasive sampling processes. Body fluids are good reservoirs for infectious parasites, bacteria, and viruses. Therefore, recent clinical proteomics methods have focused on body fluids when aiming to discover human- or pathogen-originated diagnostic markers. Cutting-edge liquid chromatography-mass spectrometry (LC-MS)-based proteomics has been applied in this regard; it is considered one of the most sensitive and specific proteomics approaches. Here, the clinical characteristics of each body fluid, recent tandem mass spectroscopy (MS/MS) data-acquisition methods, and applications of body fluids for proteomics regarding infectious diseases (including the coronavirus disease of 2019 [COVID-19]), are summarized and discussed.

Comparative Metabolomics and Proteomics Reveal Vibrio parahaemolyticus Targets Hypoxia-Related Signaling Pathways of Takifugu obscurus

Coronavirus disease 2019 (COVID-19) raises the issue of how hypoxia destroys normal physiological function and host immunity against pathogens. However, there are few or no comprehensive omics studies on this effect. From an evolutionary perspective, animals living in complex and changeable marine environments might develop signaling pathways to address bacterial threats under hypoxia. In this study, the ancient genomic model animal Takifugu obscurus and widespread Vibrio parahaemolyticus were utilized to study the effect. T. obscurus was challenged by V. parahaemolyticus or (and) exposed to hypoxia. The effects of hypoxia and infection were identified, and a theoretical model of the host critical signaling pathway in response to hypoxia and infection was defined by methods of comparative metabolomics and proteomics on the entire liver. The changing trends of some differential metabolites and proteins under hypoxia, infection or double stressors were consistent. The model includes transforming growth factor-β1 (TGF-β1), hypoxia-inducible factor-1α (HIF-1α), and epidermal growth factor (EGF) signaling pathways, and the consistent changing trends indicated that the host liver tended toward cell proliferation. Hypoxia and infection caused tissue damage and fibrosis in the portal area of the liver, which may be related to TGF-β1 signal transduction. We propose that LRG (leucine-rich alpha-2-glycoprotein) is widely involved in the transition of the TGF-β1/Smad signaling pathway in response to hypoxia and pathogenic infection in vertebrates as a conserved molecule.

Absence of COVID-19-associated changes in plasma coagulation proteins and pulmonary thrombosis in the ferret model

BACKGROUND

Many patients who are diagnosed with coronavirus disease 2019 (COVID-19) suffer from venous thromboembolic complications despite the use of stringent anticoagulant prophylaxis. Studies on the exact mechanism(s) underlying thrombosis in COVID-19 are limited as animal models commonly used to study venous thrombosis pathophysiology (i.e. rats and mice) are naturally not susceptible to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Ferrets are susceptible to SARS-CoV-2 infection, successfully used to study virus transmission, and have been previously used to study activation of coagulation and thrombosis during influenza virus infection.

OBJECTIVES

This study aimed to explore the use of (heat-inactivated) plasma and lung material from SARS-CoV-2-inoculated ferrets studying COVID-19-associated changes in coagulation and thrombosis.

MATERIAL AND METHODS

Histology and longitudinal plasma profiling using mass spectrometry-based proteomics approach was performed.

RESULTS

Lungs of ferrets inoculated intranasally with SARS-CoV-2 demonstrated alveolar septa that were mildly expanded by macrophages, and diffuse interstitial histiocytic pneumonia. However, no macroscopical or microscopical evidence of vascular thrombosis in the lungs of SARS-CoV-2-inoculated ferrets was found. Longitudinal plasma profiling revealed minor differences in plasma protein profiles in SARS-CoV-2-inoculated ferrets up to 2 weeks post-infection. The majority of plasma coagulation factors were stable and demonstrated a low coefficient of variation.

CONCLUSIONS

We conclude that while ferrets are an essential and well-suited animal model to study SARS-CoV-2 transmission, their use to study SARS-CoV-2-related changes relevant to thrombotic disease is limited.

Vps501, a novel vacuolar SNX-BAR protein cooperates with the SEA complex to regulate TORC1 signaling

The sorting nexins (SNX), constitute a diverse family of molecules that play varied roles in membrane trafficking, cell signaling, membrane remodeling, organelle motility and autophagy. In particular, the SNX-BAR proteins, a SNX subfamily characterized by a C-terminal dimeric Bin/Amphiphysin/Rvs (BAR) lipid curvature domain and a conserved Phox-homology domain, are of great interest. In budding yeast, many SNX-BARs proteins have well-characterized endo-vacuolar trafficking roles. Phylogenetic analyses allowed us to identify an additional SNX-BAR protein, Vps501, with a novel endo-vacuolar role. We report that Vps501 uniquely localizes to the vacuolar membrane and has physical and genetic interactions with the SEA complex to regulate TORC1 inactivation. We found cells displayed a severe deficiency in starvation-induced/nonselective autophagy only when SEA complex subunits are ablated in combination with Vps501, indicating a cooperative role with the SEA complex during TORC1 signaling during autophagy induction. Additionally, we found the SEACIT complex becomes destabilized in vps501Δsea1Δ cells, which resulted in aberrant endosomal TORC1 activity and subsequent Atg13 hyperphosphorylation. We have also discovered that the vacuolar localization of Vps501 is dependent upon a direct interaction with Sea1 and a unique lipid binding specificity that is also required for its function. This article is protected by copyright. All rights reserved.

Multi-attribute Glycan Identification and FDR Control for Glycoproteomics

Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a fast and sensitive glycoproteomics search method in our MSFragger search engine, which reports glycopeptides as a combination of a peptide sequence and the mass of the attached glycan. In samples with complex glycosylation patterns, converting this mass to a specific glycan composition is not straightforward; however, as many glycans have similar or identical masses. Here, we have developed a new method for determining the glycan composition of N-linked glycopeptides fragmented by collisional or hybrid activation that uses multiple sources of information from the spectrum, including observed glycan B-type (oxonium) and Y-type ions and mass and precursor monoisotopic selection errors to discriminate between possible glycan candidates. Combined with false discovery rate estimation for the glycan assignment, we show that this method is capable of specifically and sensitively identifying glycans in complex glycopeptide analyses and effectively controls the rate of false glycan assignments. The new method has been incorporated into the PTM-Shepherd modification analysis tool to work directly with the MSFragger glyco search in the FragPipe graphical user interface, providing a complete computational pipeline for annotation of N-glycopeptide spectra with false discovery rate control of both peptide and glycan components that is both sensitive and robust against false identifications.

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Identifying the glycan on intact glycopeptides remains difficult in glycoproteomics.

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We developed a method to assign glycan compositions in N-glycoproteomics searches.

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We demonstrate well-controlled glycan FDR in multiple sample types.

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The method annotates more glycopeptide spectra than competing tools.

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The method is included PTM-Shepherd for a full glycoproteomics workflow in FragPipe.

Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria

Sulfoquinovose, a sulfosugar derivative of glucose, is produced by most photosynthetic organisms and contains up to half of all sulfur in the biosphere. Several pathways for its breakdown are known, though they provide access to only half of the carbon in sulfoquinovose and none of its sulfur. Here, we describe a fundamentally different pathway within the plant pathogen Agrobacterium tumefaciens that features oxidative desulfurization of sulfoquinovose to access all carbon and sulfur within the molecule. Biochemical and structural analyses of the pathway’s key proteins provided insights how the sulfosugar is recognized and degraded. Genes encoding this sulfoquinovose monooxygenase pathway are present in many plant pathogens and symbionts, alluding to a possible role for sulfoquinovose in plant host–bacteria interactions.

Catabolism of sulfoquinovose (SQ; 6-deoxy-6-sulfoglucose), the ubiquitous sulfosugar produced by photosynthetic organisms, is an important component of the biogeochemical carbon and sulfur cycles. Here, we describe a pathway for SQ degradation that involves oxidative desulfurization to release sulfite and enable utilization of the entire carbon skeleton of the sugar to support the growth of the plant pathogen Agrobacterium tumefaciens. SQ or its glycoside sulfoquinovosyl glycerol are imported into the cell by an ATP-binding cassette transporter system with an associated SQ binding protein. A sulfoquinovosidase hydrolyzes the SQ glycoside and the liberated SQ is acted on by a flavin mononucleotide-dependent sulfoquinovose monooxygenase, in concert with an NADH-dependent flavin reductase, to release sulfite and 6-oxo-glucose. An NAD(P)H-dependent oxidoreductase reduces the 6-oxo-glucose to glucose, enabling entry into primary metabolic pathways. Structural and biochemical studies provide detailed insights into the recognition of key metabolites by proteins in this pathway. Bioinformatic analyses reveal that the sulfoquinovose monooxygenase pathway is distributed across Alpha- and Betaproteobacteria and is especially prevalent within the Rhizobiales order. This strategy for SQ catabolism is distinct from previously described pathways because it enables the complete utilization of all carbons within SQ by a single organism with concomitant production of inorganic sulfite.

Nicotinamide riboside supplementation confers marginal metabolic benefits in obese mice without remodeling the muscle acetyl-proteome

Nicotinamide riboside supplements (NRS) have been touted as a nutraceutical that promotes cardiometabolic and musculoskeletal health by enhancing nicotinamide adenine dinucleotide (NAD+) biosynthesis, mitochondrial function, and/or the activities of NAD-dependent sirtuin deacetylase enzymes. This investigation examined the impact of NRS on whole body energy homeostasis, skeletal muscle mitochondrial function, and corresponding shifts in the acetyl-lysine proteome, in the context of diet-induced obesity using C57BL/6NJ mice. The study also included a genetically modified mouse model that imposes greater demand on sirtuin flux and associated NAD+ consumption, specifically within muscle tissues. In general, whole body glucose control was marginally improved by NRS when administered at the midpoint of a chronic high-fat diet, but not when given as a preventative therapy upon initiation of the diet. Contrary to anticipated outcomes, the study produced little evidence that NRS increases tissue NAD+ levels, augments mitochondrial function, and/or mitigates diet-induced hyperacetylation of the skeletal muscle proteome.

A tale of solving two computational challenges in protein science: neoantigen prediction and protein structure prediction

In this article, we review two challenging computational questions in protein science: neoantigen prediction and protein structure prediction. Both topics have seen significant leaps forward by deep learning within the past five years, which immediately unlocked new developments of drugs and immunotherapies. We show that deep learning models offer unique advantages, such as representation learning and multi-layer architecture, which make them an ideal choice to leverage a huge amount of protein sequence and structure data to address those two problems. We also discuss the impact and future possibilities enabled by those two applications, especially how the data-driven approach by deep learning shall accelerate the progress towards personalized biomedicine.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

Altered succinylation of mitochondrial proteins, APP and tau in Alzheimer's disease

Abnormalities in brain glucose metabolism and accumulation of abnormal protein deposits called plaques and tangles are neuropathological hallmarks of Alzheimer's disease (AD), but their relationship to disease pathogenesis and to each other remains unclear. Here we show that succinylation, a metabolism-associated post-translational protein modification (PTM), provides a potential link between abnormal metabolism and AD pathology. We quantified the lysine succinylomes and proteomes from brains of individuals with AD, and healthy controls. In AD, succinylation of multiple mitochondrial proteins declined, and succinylation of small number of cytosolic proteins increased. The largest increases occurred at critical sites of amyloid precursor protein (APP) and microtubule-associated tau. We show that in vitro, succinylation of APP disrupted its normal proteolytic processing thereby promoting Aβ accumulation and plaque formation and that succinylation of tau promoted its aggregation to tangles and impaired microtubule assembly. In transgenic mouse models of AD, elevated succinylation associated with soluble and insoluble APP derivatives and tau. These findings indicate that a metabolism-linked PTM may be associated with AD.

Three Microbial Musketeers of the Seas: Shewanella baltica, Aliivibrio fischeri and Vibrio harveyi, and Their Adaptation to Different Salinity Probed by a Proteomic Approach

Osmotic changes are common challenges for marine microorganisms. Bacteria have developed numerous ways of dealing with this stress, including reprogramming of global cellular processes. However, specific molecular adaptation mechanisms to osmotic stress have mainly been investigated in terrestrial model bacteria. In this work, we aimed to elucidate the basis of adjustment to prolonged salinity challenges at the proteome level in marine bacteria. The objects of our studies were three representatives of bacteria inhabiting various marine environments, Shewanella baltica, Vibrio harveyi and Aliivibrio fischeri. The proteomic studies were performed with bacteria cultivated in increased and decreased salinity, followed by proteolytic digestion of samples which were then subjected to liquid chromatography with tandem mass spectrometry analysis. We show that bacteria adjust at all levels of their biological processes, from DNA topology through gene expression regulation and proteasome assembly, to transport and cellular metabolism. The finding that many similar adaptation strategies were observed for both low- and high-salinity conditions is particularly striking. The results show that adaptation to salinity challenge involves the accumulation of DNA-binding proteins and increased polyamine uptake. We hypothesize that their function is to coat and protect the nucleoid to counteract adverse changes in DNA topology due to ionic shifts.

Interventional- and amputation-stage muscle proteomes in the chronically threatened ischemic limb

BACKGROUND

Despite improved surgical approaches for chronic limb-threatening ischemia (CLTI), amputation rates remain high and contributing tissue-level factors remain unknown. The purpose of this study was twofold: (1) to identify differences between the healthy adult and CLTI limb muscle proteome, and (2) to identify differences in the limb muscle proteome of CLTI patients prior to surgical intervention or at the time of amputation.

METHODS AND RESULTS

Gastrocnemius muscle was collected from non-ischemic controls (n = 19) and either pre-interventional surgery (n = 10) or at amputation outcome (n = 29) CLTI patients. All samples were subjected to isobaric tandem-mass-tag-assisted proteomics. The mitochondrion was the primary classification of downregulated proteins (> 70%) in CLTI limb muscles and paralleled robust functional mitochondrial impairment. Upregulated proteins (> 38%) were largely from the extracellular matrix. Across the two independent sites, 39 proteins were downregulated and 12 upregulated uniformly. Pre-interventional CLTI muscles revealed a robust upregulation of mitochondrial proteins but modest functional impairments in fatty acid oxidation as compared with controls. Comparison of pre-intervention and amputation CLTI limb muscles revealed mitochondrial proteome and functional deficits similar to that between amputation and non-ischemic controls. Interestingly, these observed changes occurred despite 62% of the amputation CLTI patients having undergone a prior surgical intervention.

CONCLUSIONS

The CLTI proteome supports failing mitochondria as a phenotype that is unique to amputation outcomes. The signature of pre-intervention CLTI muscle reveals stable mitochondrial protein abundance that is insufficient to uniformly prevent functional impairments. Taken together, these findings support the need for future longitudinal investigations aimed to determine whether mitochondrial failure is causally involved in amputation outcomes from CLTI.

Antagonism of the mu-delta opioid receptor heterodimer enhances opioid antinociception by activating Src and calcium/calmodulin-dependent protein kinase II signaling

ABSTRACT

The opioid receptors are important regulators of pain, reward, and addiction. Limited evidence suggests the mu and delta opioid receptors form a heterodimer (MDOR), which may act as a negative feedback brake on opioid-induced analgesia. However, evidence for the MDOR in vivo is indirect and limited, and there are few selective tools available. We recently published the first MDOR-selective antagonist, D24M, allowing us to test the role of the MDOR in mice. We thus cotreated CD-1 mice with D24M and opioids in tail flick, paw incision, and chemotherapy-induced peripheral neuropathy pain models. D24M treatment enhanced oxymorphone antinociception in all models by 54.7% to 628%. This enhancement could not be replicated with the mu and delta selective antagonists CTAP, naltrindole, and naloxonazine, and D24M had a mild transient effect in the rotarod test, suggesting this increase is selective to the MDOR. However, D24M had no effect on morphine or buprenorphine, suggesting that only specific opioids interact with the MDOR. To find a mechanism, we performed phosphoproteomic analysis on brainstems of mice. We found that the kinases Src and CaMKII were repressed by oxymorphone, which was restored by D24M. We were able to confirm the role of Src and CaMKII in D24M-enhanced antinociception using small molecule inhibitors (KN93 and Src-I1). Together, these results provide direct in vivo evidence that the MDOR acts as an opioid negative feedback brake, which occurs through the repression of Src and CaMKII signal transduction. These results further suggest that MDOR antagonism could be a means to improve clinical opioid therapy.

A chemical probe targeting the PWWP domain alters NSD2 nucleolar localization

Nuclear receptor-binding SET domain-containing 2 (NSD2) is the primary enzyme responsible for the dimethylation of lysine 36 of histone 3 (H3K36), a mark associated with active gene transcription and intergenic DNA methylation. In addition to a methyltransferase domain, NSD2 harbors two proline-tryptophan-tryptophan-proline (PWWP) domains and five plant homeodomains (PHDs) believed to serve as chromatin reading modules. Here, we report a chemical probe targeting the N-terminal PWWP (PWWP1) domain of NSD2. UNC6934 occupies the canonical H3K36me2-binding pocket of PWWP1, antagonizes PWWP1 interaction with nucleosomal H3K36me2 and selectively engages endogenous NSD2 in cells. UNC6934 induces accumulation of endogenous NSD2 in the nucleolus, phenocopying the localization defects of NSD2 protein isoforms lacking PWWP1 that result from translocations prevalent in multiple myeloma (MM). Mutations of other NSD2 chromatin reader domains also increase NSD2 nucleolar localization and enhance the effect of UNC6934. This chemical probe and the accompanying negative control UNC7145 will be useful tools in defining NSD2 biology.

Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies

Constant improvements in mass spectrometry technologies and laboratory workflows have enabled the proteomics investigation of biological samples of growing complexity. Microbiomes represent such complex samples for which metaproteomics analyses are becoming increasingly popular. Metaproteomics experimental procedures create large amounts of data from which biologically relevant signal must be efficiently extracted to draw meaningful conclusions. Such a data processing requires appropriate bioinformatics tools specifically developed for, or capable of handling metaproteomics data. In this chapter, we outline current and novel tools that can perform the most commonly used steps in the analysis of cutting-edge metaproteomics data, such as peptide and protein identification and quantification, as well as data normalization, imputation, mining, and visualization. We also provide details about the experimental setups in which these tools should be used.

Identification of α1,2-fucosylated signaling and adhesion molecules in head and neck squamous cell carcinoma

Head and neck cancer is the seventh most common cancer in the world, and most cases manifest as head and neck squamous cell carcinoma. Despite the prominent role of fucosylated carbohydrate antigens in tumor cell adhesion and metastasis, little is known about the functional role of fucose-modified glycoproteins in head and neck cancer pathobiology. Inactivating polymorphisms of the fut2 gene, encoding for the α1,2-fucosyltransferase FUT2, are associated with an increased incidence of head and neck cancer among tobacco users. Moreover, the presence of the α1,2-fucosylated Lewis Y epitope, with both α1,2- and α1,3-linked fucose, has been observed in head and neck cancer tumors while invasive regions lose expression, suggesting a potential role for α1,2-fucosylation in the regulation of aggressive tumor cell characteristics. Here, we report an association between fut2 expression and head and neck cancer survival, document differential surface expression of α1,2-fucosylated epitopes in a panel of normal, dysplastic, and head and neck cancer cell lines, identify a set of potentially α1,2-fucosylated signaling and adhesion molecules including the epidermal growth factor receptor (EGFR), CD44 and integrins via tandem mass spectrometry, and finally, present evidence that EGFR is among the α1,2-fucosylated and LeY-displaying proteins in head and neck cancer. This knowledge will serve as the foundation for future studies to interrogate the role of LeY-modified and α1,2-fucosylated glycoproteins in head and neck cancer pathogenesis. Data are available via ProteomeXchange with identifier PXD029420.

Skyline Batch: An Intuitive User Interface for Batch Processing with Skyline

Skyline Batch is a newly developed Windows forms application that enables the easy and consistent reprocessing of data with Skyline. Skyline has made previous advances in this direction; however, none enable seamless automated reprocessing of local and remote files. Skyline keeps a log of all of the steps that were taken in the document; however, reproducing these steps takes time and allows room for human error. Skyline also has a command-line interface, enabling it to be run from a batch script, but using the program in this way requires expertise in editing these scripts. By formalizing the workflow of a highly used set of batch scripts into an intuitive and powerful user interface, Skyline Batch can reprocess data stored in remote repositories just by opening and running a Skyline Batch configuration file. When run, a Skyline Batch configuration downloads all necessary remote files and then runs a four-step Skyline workflow. By condensing the steps needed to reprocess the data into one file, Skyline Batch gives researchers the opportunity to publish their processing along with their data and other analysis files. These easily run configuration files will greatly increase the transparency and reproducibility of published work. Skyline Batch is freely available at https://skyline.ms/batch.url.