Biology subjects

Palmisano, G.

Publications and source records attributed to Palmisano, G..

At least 19 recordsLinked to original sources

bioRxiv2026

STEP-PTMs: Sequential TMT-based Enrichment and Profiling of Post-Translational Modifications

Comprehensive characterization of protein abundance and multiple post-translational modifications (PTMs) from the same biological samples is essential for understanding cellular regulation and PTM crosstalk but remains analytically challenging. Here, we present STEP-PTM (Sequential Tag-based Enrichment of Post-Translational Modifications), a modular TMT-multiplexed workflow that enables integrated quantitative analysis of the proteome, metabolome and multiple PTM classes from a single peptide preparation. Proteins are digested, isobarically labeled using tandem mass tags (TMT), and combined into a single multiplexed peptide pool prior to sequential PTM enrichment, thereby minimizing technical variability, reducing sample requirements and facilitating direct quantitative integration across datasets. STEP-PTM supports flexible sequential enrichment of phosphopeptides, peptides containing free and reversibly modified cysteines, sialylated N-linked glycopeptides, lysine-acetylated peptides and S-palmitoylated peptides, while preserving non-modified peptides for global proteome analysis. PTM-specific database searches further improve identification confidence and quantitative accuracy, and the modular workflow can readily be adapted by incorporating or omitting enrichment modules according to the biological question. Application of STEP-PTM to TMT16-plex cerebral brain organoids enabled the quantification of 10,413 proteins, 2,969 metabolites, 19,655 phosphopeptides, 28,876 peptides containing reversibly modified cysteines, 9,723 peptides containing free cysteines, 1,716 intact sialylated N-linked glycopeptides and 771 lysine-acetylated peptides from the same biological samples. We further demonstrate the applicability of the workflow to multiple mouse tissues, highlighting its broad utility for integrated systems-level characterization of protein expression and PTM regulation across diverse biological models.

biochemistry↗

bioRxiv2026

GPMAW Glyco-Search: An Integrated Workflow for Identification and Validation of Intact Sialylated N-Glycopeptides

Comprehensive analysis of intact sialylated N-glycopeptides remains challenging because of their low abundance, extensive structural heterogeneity, and limited peptide backbone fragmentation during tandem mass spectrometry. Here, we present an integrated workflow for high-confidence identification of intact sialylated N-glycopeptides that combines selective TiO2 enrichment, dual LC-MS/MS analysis of intact and deglycosylated glycopeptides, and the GPMAW glyco-search platform based on high-accuracy mass mapping. Unlike most conventional glycoproteomics search engines, GPMAW uses experimentally identified deglycopeptides to constrain glycan assignment before matching intact glycopeptide precursor masses to candidate glycan compositions. Identifications were validated using diagnostic oxonium ions, glycopeptide-associated Y-ion fragments, and an experimentally derived glycopeptide score. In addition, GPMAW integrates an interactive spectrum annotation interface that enables rapid manual validation of candidate identifications through visualization of annotated Y-ion series, oxonium ions, and peptide fragments, allowing individual assignments to be readily accepted or rejected. The workflow was optimized using bovine fetuin, validated on standard glycoproteins, and applied to depleted human plasma, where more than 2800 unique intact sialylated N-glycopeptides were identified across hundreds of glycosites and glycoproteins. Moreover, more than 1000 unique N-glycopeptides were identified from only 1 L of plasma. Comparative analysis demonstrated that GPMAW glyco-search identified more confidently assigned intact sialylated N-glycopeptides than three widely used N-glycoproteomics search engines while maintaining high reproducibility and low false-positive rates following manual validation. Together, this workflow provides a robust, flexible, and accessible platform for large-scale, high-confidence characterization of intact N-glycopeptides and establishes experimentally constrained glycan composition assignment combined with interactive spectrum validation as an effective strategy for reducing ambiguity in N-glycoproteomics. HighlightsO_LIThe program "GPMAW glyco-search" enables high-accuracy mass mapping for confident identification of intact N-glycopeptides. C_LIO_LIIntegrated workflow combining TiO2 enrichment, dual LC-MS/MS of intact and deglycosylated glycopeptides and GPMAW glyco-search for intact sialylated N-glycopeptides. C_LIO_LIOptimized TiO2 enrichment provides >95% selective enrichment of sialylated N-glycopeptides from complex biological samples. C_LIO_LIInteractive spectrum annotation and Y-ion-based scoring enable rapid manual validation and high-confidence glycopeptide identification. C_LIO_LIGPMAW glyco-search confidently identified more intact sialylated N-linked glycopeptides compared to three established glycoproteomics search engines. C_LI

biochemistry↗

bioRxiv2025

Fractal and Machine Learning analyses of MALDI-TOF Mass Spectrometry data in glioblastoma

Data pre-processing is a critical step in the analysis of MALDI-TOF MS spectra for machine learning applications, typically involving steps such as spectra trimming, baseline correction, smoothing, transformation, and peak picking or spectral binning. While traditional approaches focus on protein/peptide peaks as features, this study explores a novel method of feature extraction by treating MALDI-TOF spectra as time-series data. This study investigates the use of computational fractal-based analysis to assess the complexity of MALDI-TOF spectra. Fractal analysis, previously successful in glioblastoma diagnosis using MRI, was applied here to proteomics data for the first time. By treating each MALDI spectrum as a time series and calculating its fractal dimension using various algorithms, machine learning models were trained to differentiate between glioblastoma patients and healthy controls. We demonstrate that fractals are sufficient to obtain accurate models for glioblastoma diagnosis, despite still underperforming when compared to the traditional feature extraction method. We also show that fractals can be used as support features to increase model performance. This work highlights the potential and limitations of fractal analysis in proteomics, offering a new perspective for disease diagnosis and broadening the applicability of time-series data analysis in mass spectrometry.

bioinformatics↗

bioRxiv2025

Identification of astrocytomas through serum protein fingerprint using MALDI-TOF MS and machine learning

Gliomas account for most brain malignancies, with astrocytomas being the most common subtype. Among these, glioblastoma (GBM) stands out as the most aggressive form, exhibiting a median survival time of just 15 months despite intensive therapy. Current diagnostic practices rely on magnetic resonance imaging (MRI) and histopathological analysis, which often necessitate invasive surgical sampling. This underscores the need for minimally invasive diagnostic tools capable of characterizing glioma progression and guiding treatment strategies. Advances in glioma classification have integrated histological and molecular markers, notably IDH1 mutations, which are prognostically significant, particularly in low-grade gliomas and in the previously defined "secondary GBM" (IDH-mutant astrocytoma grade 4). This study aimed to explore the potential of serum proteomics as a non-invasive diagnostic tool using MALDI-TOF mass spectrometry (MS) combined with machine learning techniques. We analyzed serum samples from 269 patients, employing machine learning models to differentiate between healthy individuals and astrocytoma patients. The MALDI-TOF MS approach achieved a balanced accuracy of 94.5% in distinguishing GBM patients from healthy controls. However, it showed limited efficacy in classifying tumor grades or determining IDH1 mutational status. Further investigation using bottom-up proteomics by GeLC-MS/MS identified potential biomarkers, such as transthyretin, previously associated with high-grade gliomas. These findings highlight the promise of MALDI-TOF MS in identifying serum-based biomarkers for astrocytoma diagnosis. While the results are promising, further validation in independent cohorts is essential to assess the clinical utility of these biomarkers for non-invasive glioma diagnostics and patient monitoring.

systems biology↗

bioRxiv2023

The protein map of the protozoan parasite Leishmania (Leishmania) amazonensis, Leishmania (Viannia) braziliensis and Leishmania (Leishmania) infantum during growth phase transition and temperature stress

Leishmania parasites cause a spectrum of diseases termed leishmaniasis, which manifests in two main clinical forms, cutaneous and visceral leishmaniasis. Leishmania promastigotes transit from proliferative exponential to quiescent stationary phases inside the insect vector, a relevant step that recapitulates early molecular events of metacyclogenesis. During the insect blood meal of the mammalian hosts, the released parasites interact initially with the skin, an event marked by temperature changes. Deep knowledge on the molecular events activated during Leishmania-host interactions in each step is crucial to develop better therapies and to understand the pathogenesis. In this study, the proteomes of Leishmania (Leishmania) amazonensis (La), Leishmania (Viannia) braziliensis (Lb), and Leishmania (Leishmania) infantum (syn L. L. chagasi) (Lc) were analyzed using quantitative proteomics to uncover the proteome modulation in three different conditions related to growth phases and temperature shifts: 1) exponential phase (Exp); 2) stationary phase (Sta25) and; 3) stationary phase subjected to heat stress (Sta34). Functional validations were performed using orthogonal techniques, focusing on -tubulin, gp63 and heat shock proteins (HSPs). Species-specific and condition-specific modulation highlights the plasticity of the Leishmania proteome, showing that pathways related to metabolism and cytoskeleton are significantly modulated from exponential to stationary growth phases, while protein folding, unfolded protein binding, signaling and microtubule-based movement were differentially altered during temperature shifts. This study provides an in-depth proteome analysis of three Leishmania spp., and contributes compelling evidence of the molecular alterations of these parasites in conditions mimicking the interaction of the parasites with the insect vector and vertebrate hosts.

microbiology↗

bioRxiv2023

ST8Sia2 polysialyltransferase protects against infection by Trypanosoma cruzi

Glycosylation is one of the most structurally and functionally diverse co- and post-translational modifications in a cell. Addition and removal of glycans, especially to proteins and lipids, characterize this process which have important implications in several biological processes. In mammals, the repeated enzymatic addition of a sialic acid unit to underlying sialic acids (Sia) by polysialyltransferases, including ST8Sia2, leads to the formation of a sugar polymer called polysialic acid (polySia). The functional relevance of polySia has been extensively demonstrated in the nervous system. However, the role of polysialylation in infection is still poorly explored. Previous reports have shown that Trypanosoma cruzi (T. cruzi), a flagellated parasite that causes Chagas disease (CD), changes host sialylation of glycoproteins. To understand the role of host polySia during T. cruzi infection, we used a combination of in silico and experimental tools. We observed that T. cruzi reduces both the expression of the ST8Sia2 and the polysialylation of target substrates. We also found that chemical and genetic inhibition of host ST8Sia2 increased the parasite load in mammalian cells. These findings suggest a novel approach to interfere with parasite infections through modulation of host polysialylation. AUTHOR SUMMARYGlycosylation is a co- and/or post-translational modification regulated by the addition and removal of glycans. This process shapes the cellular glycome, which in turn, holds significant implications in various biological processes. Trypanosoma cruzi (T. cruzi), the etiological agent of Chagas disease, a globally concerning neglected tropical disease affecting 6 to 8 million individuals worldwide, exerts a profound influence on host glycoprotein sialylation. Remarkably, T. cruzi is incapable of synthesizing sialic acid (Sia) and relies on acquiring it from host glycoconjugates. In mammals, the formation of polysialic acid (polySia) is mediated by polysialyltransferases, such as ST8Sia2. The functional relevance of polySia has been extensively documented in the nervous system. Nevertheless, its role within the context of infectious processes remains largely unexplored. Herein, we demonstrate that in T. cruzi-infected host cells, the expression of the ST8Sia2 enzyme is downregulated, resulting in diminished levels of polysialylation. Furthermore, a reduction in the levels of NCAM1 and SCN5A was observed, which can be attributed to the decreased host polysialylation. Moreover, enzymatic removal of polySia, along with chemical inhibition and genetic silencing of ST8Sia2, led to a marked increase in the number of intracellular parasites. We posit that ST8Sia2 inhibition favors T. cruzi infection, thereby elucidating novel avenues for understanding the mechanisms associated with Chagas disease pathogenesis, prominently featuring the pivotal role of host polysialylation.

microbiology↗

bioRxiv2023

ATE1 activates ER-stress and UPR pathways in glioblastoma

Post-translational modifications (PTM) have been recognized as a relevant regulation of key processes in cancer pathophysiology, such as cell migration, adhesion, and proliferation. N-terminal protein arginylation is an emerging PTM involved in tumor progression; however, the mechanisms by which this modification influences these events are poorly understood and vary according to cancer type. Glioblastoma (GBM) is an aggressive intra-axial brain tumor associated with poor prognosis, low survival, and high recurrence rate. We performed a study combining in silico, in vitro, and patients samples analysis to understand the impact of N-terminal protein arginylation in GBM, including overexpression and silencing of ATE1 in GBM-U87MG cell line with RNASeq analysis, immunofluorescence, and validation of the identified targets at the protein level by immunoblotting. The arginylation pattern differed in GBM compared with non-neoplastic brain tissues, and upregulation of ATE1 was associated with increased tumor cell proliferation. We identified a strong activation of the unfolded protein response (UPR) pathway associated with increased ATE1 level, inducing autophagy and not apoptosis. Protein arginylation in GBM proved to be an important mechanism for tumor growth, with the recycling of cell substrates by autophagy, providing fitness for tumor cells. The expressions of the main markers of UPR and autophagy pathways were validated in human GBM samples, reinforcing the role of ATE1 in the most aggressive brain tumor.

cancer biology↗

bioRxiv2023

Leishmaniinae: evolutionary inferences based on protein expression profiles (PhyloQuant) congruent with phylogenetic relationships among Leishmania, Endotrypanum, Porcisia, Zelonia, Crithidia, and Leptomonas

Evolutionary relationships among parasites of the subfamily Leishmaniinae, which comprises pathogen agents of leishmaniasis, were inferred based on differential protein expression profiles from mass spectrometry-based quantitative data using the PhyloQuant method. Evolutionary distances following identification and quantification of protein and peptide abundances using Proteome Discoverer (PD) and MaxQuant (MQ) softwares were estimated for 11 species from 6 Leishmaniinae genera. Results clustered all dixenous species of the genus Leishmania, subgenera L. (Leishmania), L. (Viannia) and L. (Mundinia), sister to the dixenous species of genera Endotrypanum and Porcisia. Positioned basal to the assemblage formed by all these parasites were the species of genera Zelonia, Crithidia and Leptomonas, so far described as monoxenous of insects although eventually reported from humans. Inferences based on protein expression profiles were congruent with currently established phylogeny using DNA sequences. Our results reinforce PhyloQuant as a valuable approach to infer evolutionary relationships consistent with genera, subgenera, and species-specific biological characteristics, able to resolve within Leishmaniinae, which is comprised of very tightly related trypanosomatids that are just beginning to be phylogenetically unravelled. In additional to evolutionary history, mapping of species-specific protein expression is paramount to understand differences in infection processes, disease presentations, tissue tropisms, potential to jump from insects to vertebrates including humans, and potential targets for species-specific diagnostic and drug development.

evolutionary biology↗

bioRxiv2023

Plasmodium falciparum MORC protein modulates gene expression through interaction with heterochromatin

Dynamic control of gene expression is critical for blood stage development of malaria parasites. Here, we used multi-omic analyses to investigate transcriptional regulation by the chromatin-associated microrchidia protein, MORC, during asexual blood stage development of the human malaria parasite Plasmodium falciparum. We show that PfMORC (PF3D7_1468100) interacts with a suite of nuclear proteins, including APETALA2 (AP2) transcription factors (PfAP2-G5, PfAP2-O5, PfAP2-I, PF3D7_0420300, PF3D7_0613800, PF3D7_1107800, and PF3D7_1239200), a DNA helicase DS60 (PF3D7_1227100), and other chromatin remodelers (PfCHD1 and PfEELM2). Transcriptomic analysis of PfMORCHA-glmS knockdown parasites revealed 163 differentially expressed genes belonging to hypervariable multigene families, along with upregulation of genes mostly involved in host cell invasion. In vivo genome-wide chromatin occupancy analysis during both trophozoite and schizont stages of development demonstrates that PfMORC is recruited to repressed, multigene families, including the var genes in subtelomeric chromosomal regions. Collectively, we find that PfMORC is found in chromatin complexes that play a role in the epigenetic control of asexual blood stage transcriptional regulation and chromatin organization.

microbiology↗

bioRxiv2023

A phylogenetic approach to explore the Aspergillus fumigatus conidial surface-associated proteome and its role in pathogenesis

Aspergillus fumigatus, an important pulmonary fungal pathogen causing several diseases collectively called aspergillosis, relies on asexual spores or conidia for initiating host infection. Here, we used a phylogenomic approach to compare proteins in the conidial surface of A. fumigatus, two closely related non-pathogenic species, Aspergillus fischeri and Aspergillus oerlinghausenensis, and the cryptic pathogen Aspergillus lentulus. After identifying 62 proteins uniquely expressed on the A. fumigatus conidial surface, we deleted 42 genes encoding conidial proteins. We found deletion of 33 of these genes altered susceptibility to macrophage killing, penetration and damage to epithelial cells, and cytokine production. Notably, a gene that encodes glycosylasparaginase, which modulates levels of the host pro-inflammatory cytokine IL-1{beta}, is important for infection in an immunocompetent murine model of fungal disease. These results suggest that A. fumigatus conidial surface proteins and effectors are important for evasion and modulation of the immune response at the onset of fungal infection.

microbiology↗

bioRxiv2023

The Respiratory Syncytial Virus M2-2 protein is targeted for proteasome degradation and inhibits translation and stress granules assembly

The M2-2 protein from the respiratory syncytial virus (RSV) is a 10 kDa protein expressed by the second ORF of the viral gene M2. During infection, M2-2 has been described as the polymerase cofactor responsible for promoting genome replication. This function was first inferred by infection with a mutant virus lacking the M2-2 ORF, in which viral genome presented delayed accumulation in comparison to wild-type virus. In accordance with this phenotype, it has been recently shown that M2-2 promotes changes in interactions between the polymerase and other viral proteins at early stages of infection. Despite its well-explored role in the regulation of the polymerase activity, little has been made to investigate the relationship of M2-2 with cellular proteins. In fact, a previous report showed poor recruitment of M2-2 to viral structures, with the protein being mainly localized to the nucleus and cytoplasmic granules. To unravel which other functions M2-2 exerts during infection, we expressed the protein in HEK293T cells and performed proteomic analysis of co-immunoprecipitated partners, identifying enrichment of proteins involved with regulation of translation, protein folding and mRNA splicing. In approaches based on these data, we found that M2-2 expression downregulates eiF2 phosphorylation and inhibits stress granules assembly under arsenite induction. In addition, we also verified that M2-2 inhibits translation initiation, and is targeted for proteasome degradation, being localized to granules composed by defective ribosomal products at the cytoplasm. These results suggest that besides its functions in the regulation of genome replication, M2-2 may exert additional functions to contribute to successful RSV infection. Author summaryExploring how viruses take control of the cellular machinery is a common strategy to understand the infection process and to identify targets for inhibition of virus replication. In this work we investigated the cellular functions of the protein M2-2 from the respiratory syncytial virus. Although this virus is an important pathogen responsible for respiratory infections in immunocompromised individuals, currently there are no vaccines or effective treatments to inhibit its infection. Our findings showed that the protein M2-2 interferes with protein synthesis, being able to downregulate the assembly of stress granules during stress stimuli. Besides, we verified the relationship between M2-2 and the proteasome machinery, which is responsible for protein degradation and is also involved with protein synthesis. These results present new functions for the protein M2-2, indicating additional mechanisms utilized by the virus to facilitate infection, providing new perspectives for the search of antiviral targets.

microbiology↗

bioRxiv2022

P2RX7 signaling drives the differentiation of Th1 cells through metabolic reprogramming for aerobic glycolysis

This study provides evidence on the molecular mechanisms by which P2RX7 signaling promotes the differentiation of Th1 cells. In vivo analysis was performed in the Plasmodium chabaudi model of malaria in view of the great relevance of this infectious disease for human health, as well as the great availability of data concerning Th1/Tfh differentiation. We show that P2RX7 induces T-bet expression and aerobic glycolysis in splenic CD4+ T cells that respond to malaria, at a time prior to Th1/Tfh polarization. Cell-intrinsic P2RX7 signaling sustains the glycolytic pathway and causes bioenergetic mitochondrial stress in activated CD4+ T cells. We also show in vitro the phenotypic similarities of Th1-conditioned CD4+ T cells that do not express P2RX7 and those in which the glycolytic pathway is pharmacologically inhibited. In addition, in vitro ATP synthase blockade and the consequent inhibition of oxidative phosphorylation, which drives cellular metabolism for aerobic glycolysis, is sufficient to promote rapid CD4+ T cell proliferation and polarization to the Th1 profile in the absence of P2RX7. These data demonstrate that P2RX7-mediated metabolic reprograming for aerobic glycolysis is a key event for Th1 differentiation and suggest that ATP synthase inhibition is a downstream effect of P2RX7 signaling that potentiates the Th1 response.

immunology↗

bioRxiv2021

Urine proteomics as a non-invasive approach to monitor exertional rhabdomyolysis during military training

Exertional rhabdomyolysis (ERM), a condition often associated with strenuous exercise, a common practice in the military activities, can be defined as the process of injury and rupture of muscle cell membranes, with leakage of its components into the blood stream. Creatine kinase (CK) has been extensively used for ERM diagnosis, albeit several studies reported the discrepancy between CK levels and clinical signs or symptoms. In this study, we analyzed the biochemical profile of the blood, and the urinary proteome of ten marine soldiers in a special training course. The samples were collected in two periods, M1 and M2, which correspond to the lowest and highest CK levels during training, respectively. Quantitative urinary proteome profile of M1 and M2 was determined showing changes with highest significance in immune system and cell adhesion-related pathways after strenuous physical exercise. Changes in the abundance of several proteins was observed in individuals carrying genetic polymorphisms related to greater risk for muscle damage. Remarkably, we identified a panel of proteins (CTSH, PIK3IP1, DEFB1, ITGB1, BCAN, and TNFRSF10C) that present high correlation with three classical blood biochemical markers of ERM and AGT MET235Thr and ACE I/D polymorphisms. These proteins represent potential urine markers of muscle damage due to intense physical conditions such as military training activities.

biochemistry↗

bioRxiv2021

Protein arginylation is regulated during SARS-CoV-2 infection

In 2019, the world witnessed the onset of an unprecedented pandemic. In September 2021, the infection by SARS-CoV-2 had already been responsible for the death of more than 4 million people worldwide. Recently, we and other groups discovered that SARS-CoV-2 infection induces ER-stress and activation of unfolded protein response (UPR) pathway. The degradation of misfolded/unfolded proteins is an essential element of proteostasis and occurs mainly in lysosomes or proteasomes. The N-terminal arginylation of proteins is characterized as an inducer of ubiquitination and proteasomal degradation by the N-end rule pathway. Here we present, for the first time, data on the role of arginylation during SARS-CoV-2 infection. We studied the modulation of protein arginylation in Vero CCL-81 and Calu-3 cells infected after 2h, 6h, 12h, 24h, and 48h. A reanalysis of in vivo and in vitro public omics data combined with immunoblotting was performed to measure the levels of ATE1 and arginylated proteins. This regulation is seen specifically during infections by coronaviruses. We demonstrate that during SARS-CoV-2 infection there is an increase in the expression of the ATE1 enzyme associated with regulated levels of specific arginylated proteins. On the other hand, infected macrophages showed no ATE1 regulation. An important finding revealed that modulation of the N-end rule pathway differs between different types of infected cells. We also confirmed the potential of tannic acid to reduce viral load, and furthermore, to modulate ATE1 levels during infection. In addition, the arginylation inhibitor merbromin (MER) is also capable of both reducing viral load and reducing ATE1 levels. Taken together, these data show the importance of arginylation during the progression of SARS-CoV-2 infection and open the door for future studies that may unravel the role of ATE1 and its inhibitors in pathogen infection.

cell biology↗

bioRxiv2021

SARS-CoV-2 activates ER stress and Unfolded protein response

Coronavirus disease-2019 (COVID-19) pandemic caused by the SARS-CoV-2 coronavirus infection is a major global public health concern affecting millions of people worldwide. The scientific community has joint efforts to provide effective and rapid solutions to this disease. Knowing the molecular, transmission and clinical features of this disease is of paramount importance to develop effective therapeutic and diagnostic tools. Here, we provide evidence that SARS-CoV-2 hijacks the glycosylation biosynthetic, ER-stress and UPR machineries for viral replication using a time-resolved (0-48 hours post infection, hpi) total, membrane as well as glycoproteome mapping and orthogonal validation. We found that SARS-CoV-2 induces ER stress and UPR is observed in Vero and Calu-3 cell lines with activation of the PERK-eIF2-ATF4-CHOP signaling pathway. ER-associated protein upregulation was detected in lung biopsies of COVID-19 patients and associated with survival. At later time points, cell death mechanisms are triggered. The data show that ER stress and UPR pathways are required for SARS-CoV-2 infection, therefore representing a potential target to develop/implement anti-CoVID-19 drugs.

biochemistry↗

bioRxiv2021

Systems-wide analysis of glycoprotein conformational changes by limited deglycosylation assay

A new method to probe the conformational changes of glycoproteins on a systems-wide scale, termed limited deglycosylation assay (LDA), is described. The method measures the differential rate of deglycosylation of N-glycans on natively folded proteins by the common peptide:N-glycosidase F (PNGase F) enzyme which in turn informs on their spatial presentation and solvent exposure on the protein surface hence ultimately the glycoprotein conformation. LDA involves 1) protein-level N-deglycosylation under native conditions, 2) trypsin digestion under denaturing conditions, 3) glycopeptide enrichment, 4) peptide-level N-deglycosylation and 5) quantitative MS-based analysis of the formerly N-glycosylated peptides. LDA was initially developed and the experimental conditions optimized using bovine RNase B and fetuin. The method was then applied to glycoprotein extracts from LLC-MK2 epithelial cells upon treatment with dithiothreitol to induce endoplasmic reticulum stress and promote protein misfolding. Data from the LDA and 3D structure analysis showed that glycoproteins predominantly undergo structural changes in loops/turns upon ER stress as exemplified with detailed analysis of ephrin-A5, GALNT10, PVR and BCAM. These results show that LDA accurately reports on systems-wide conformational changes of glycoproteins induced under controlled treatment regimes. Thus, LDA opens avenues to study glycoprotein structural changes in a range of other physiological and pathophysiological conditions relevant to acute and chronic diseases.

biochemistry↗

bioRxiv2021

Resource sharing by outer membrane vesicles from a citrus pathogen

The causative agent of citrus canker disease, Xanthomonas citri pv. citri, was found to produce copious amounts of outer membrane vesicles (OMVs), frequently forming long membranous tubes under different culture conditions. Lipidomic analysis revealed significant differences in lipid composition between purified vesicles in relation to whole cells. The results suggest an enrichment in saturated cardiolipins and a decrease in unsaturated lipids in the OMV samples, possibly granting them a more rigid structure while allowing their high degree of curvature caused by their small diameters. The vesicles proteome was found to be significantly enriched in TonB-dependent receptors related to the acquisition of different nutrients. These proteins are known to transport siderophores, which were evidenced to be present in purified X. citri OMVs, along with essential metals including iron, zinc, and manganese quantified by elemental analysis. The availability of vesicle-associated nutrients to be incorporated by cells was demonstrated by the use of OMVs as the sole carbon source for bacterial growth. At last, the vesicles also presented esterase and protease activities, which have been associated with virulence in phytopathogens. These evidences point that X. citri cells can use OMVs to share resources within microbial communities, which has potential implications for microbial interactions and plant colonization, affecting their survival and persistence on the host and in the environment. ImportanceThe shedding of outer membrane vesicles appears to be universal in Gram-negative bacteria and effectively constitutes a unique secretion pathway for diverse molecules and proteins. To study their possible functions in the citrus pathogen Xanthomonas citri, purified vesicles from this bacterium were studied by omics and functional approaches. Nutrient transporters were found associated to these structures, which were evidenced to contain siderophores and essential metals. The availability of these nutrients to be incorporated by cells was then demonstrated by showing that purified vesicles can be used as sole carbon sources for microbial growth. Additionally, the samples also presented esterase and protease activities which can contribute to the release of substrates from plant host tissues. These observations help to establish the developing idea of vesicles as shared bacterial resources which can participate in shaping host-associated microbial communities in contrast to other interactions such as bacterial competition.

microbiology↗

bioRxiv2021

Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies of Glycopeptide Data

Glycoproteome profiling (glycoproteomics) is a powerful yet analytically challenging research tool. The complex tandem mass spectra generated from glycopeptide mixtures require sophisticated analysis pipelines for structural determination. Diverse software aiding the process have appeared, but their relative performance remains untested. Conducted through the HUPO Human Proteome Project - Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates the performance of informatics solutions for system-wide glycopeptide analysis. Mass spectrometry-based glycoproteomics datasets from human serum were shared with all teams. The relative team performance for N- and O-glycopeptide data analysis was comprehensively established and validated through orthogonal performance tests. Excitingly, several high-performance glycoproteomics informatics solutions were identified. While the study illustrated that significant informatics challenges remain, as indicated by a high discordance between annotated glycopeptides, lists of high-confidence (consensus) glycopeptides were compiled from the standardised team reports. Deep analysis of the performance data revealed key performance-associated search variables and led to recommendations for improved "high coverage" and "high accuracy" glycoproteomics search strategies. This study concludes that diverse software for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies, and specifies key variables that may guide future software developments and assist informatics decision-making in glycoproteomics.

biochemistry↗