Search

Pectobacterium and Dickeya species belonging to the Soft Rot Pectobacteriaceae (SRP) are one of the most devastating phytopathogens. They degrade plant tissues by producing an arsenal of plant cell wall degrading enzymes. However, SRP-plant interactions are not restricted to the production of these "brute force" weapons. Additionally, these bacteria apply stealth behavior related to (1) manipulation of the host plant via induction of susceptible responses and (2) formation of heterogeneous populations with functionally specialized cells. Our review aims to summarize current knowledge on SRP-induced plant susceptible responses and on the heterogeneity of SRP populations. The review shows that SRP are capable of adjusting the host's hormonal balance, inducing host-mediated plant cell wall modification, promoting iron assimilation by the host, stimulating the accumulation of reactive oxygen species and host cell death, and activating the synthesis of secondary metabolites that are ineffective in limiting disease progression. By this means, SRP facilitate host plant susceptibility. During host colonization, SRP populations produce various functionally specialized cells adapted for enhanced virulence, increased resistance, motility, vegetative growth, or colonization of the vascular system. This enables SRP to perform self-contradictory tasks, which benefits a population's overall fitness in various environments, including host plants. Such stealthy tactical actions facilitate plant-SRP interactions and disease progression.

Context Glucose-dependent insulinotropic polypeptide (GIP) has been proposed to exert insulin-independent effects on lipid and bone metabolism. Objective We investigated the effects of a 6-day subcutaneous GIP infusion on circulating lipids, white adipose tissue (WAT), brown adipose tissue (BAT), hepatic fat content, inflammatory markers, respiratory exchange ratio (RER), and bone homeostasis in patients with type 1 diabetes. Methods In a randomized, placebo-controlled, double-blind, crossover study, 20 men with type 1 diabetes underwent a 6-day continuous subcutaneous infusion with GIP (6 pmol/kg/min) and placebo (saline), with an interposed 7-day washout period. Results During GIP infusion, participants (26 ± 8 years [mean ± SD]; BMI 23.8 ± 1.8 kg/m2; glycated hemoglobin A1c 51 ± 10 mmol/mol [6.8 ± 3.1%]) experienced transiently increased circulating concentrations of nonesterified fatty acid (NEFA) (P = 0.0005), decreased RER (P = 0.009), indication of increased fatty acid β-oxidation, and decreased levels of the bone resorption marker C-terminal telopeptide (P = 0.000072) compared with placebo. After 6 days of GIP infusion, hepatic fat content was increased by 12.6% (P = 0.007) and supraclavicular skin temperature, a surrogate indicator of BAT activity, was increased by 0.29 °C (P < 0.000001) compared with placebo infusion. WAT transcriptomic profile as well as circulating lipid species, proteome, markers of inflammation, and bone homeostasis were unaffected. Conclusion Six days of subcutaneous GIP infusion in men with type 1 diabetes transiently decreased bone resorption and increased NEFA and β-oxidation. Further, hepatic fat content, and supraclavicular skin temperature were increased without affecting WAT transcriptomics, the circulating proteome, lipids, or inflammatory markers.

Current proteomics approaches rely almost exclusively on using positive ionization mode, which results in inefficient ionization of many acidic peptides. With an equal quantity of acidic and basic proteins and, correspondingly, the similar number for their derived peptides in case of the human proteome, this inefficient ionization poses both a substantial challenge and a potential. In this work, we study the efficiency of protein identification in the bottom-up proteomic analysis performed in negative ionization mode, using the recently introduced MS1-only ultra-fast data acquisition method DirectMS1. This method is based on accurate peptide mass measurements and predicted retention times. Our method achieves the highest rate of protein identifications in negative ion mode to date, with over 1,000 proteins identified in a human cell line at a 1% false discovery rate using a single-shot 10-min separation gradient, which is comparable with hours-long MS/MS-based analyses. Evaluating the proteins as a function of pI indicated preferable identification of the acidic part of the proteome. Optimization of separation and mass spectrometric experimental conditions facilitated the performance of the method with the best results in terms of spray stability and signal abundance obtained using mobile buffers at 2.5 mM imidazole and 3% isopropanol. The work also highlighted the complementarity of data acquired in positive and negative modes: Combining the results for all replicates for both polarities, the number of identified proteins increased up to 1,774. Finally, we performed analysis of the method’s efficiency when different proteases are used for protein digestion. Among the four studied proteases (LysC, GluC, AspN, and trypsin), we found that trypsin and LysC performed best in terms of protein identification yield. Thus, digestion procedures used for positive mode proteomics can be efficiently utilized for analysis in negative ion mode.

Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at 1% false discovery rate (FDR) when using 5-min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000 to 5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue we performed one-by-one comparison of quantitation results obtained using DirectMS1 with three popular MS/MS-based quantitation methods: label-free quantification (LFQ), tandem mass tag (TMT), both based on data dependent acquisition (DDA), and data independent acquisition (DIA). For the comparison we performed a series of proteome-wide analysis of well-characterized (ground truth) and biological relevant samples, including a mix of UPS1 proteins spiked at different concentrations into E. coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods utilizing 10 to 20-fold longer instrumentation time.

Bacterial adaptation is regulated at the population level with the involvement of intercellular communication (quorum sensing). When the population density is insufficient for adaptation under starvation, bacteria can adjust it to a quorum level through cell divisions at the expense of endogenous resources. This phenomenon has been described for the phytopathogenic bacterium Pectobacterium atrosepticum (Pba), and it is called, in our study, adaptive proliferation. An important attribute of adaptive proliferation is its timely termination, which is necessary to prevent the waste of endogenous resources when the required level of population density is achieved. However, metabolites that provide the termination of adaptive proliferation remained unidentified. We tested the hypothesis of whether quorum sensing-related autoinducers prime the termination of adaptive proliferation and assessed whether adaptive proliferation is a common phenomenon in the bacterial world. We showed that both known Pba quorum sensing-related autoinducers act synergistically and mutually compensatory to provide the timely termination of adaptive proliferation and formation of cross-protection. We also demonstrated that adaptive proliferation is implemented by bacteria of many genera and that bacteria with similar quorum sensing-related autoinducers have similar signaling backgrounds that prime the termination of adaptive proliferation, enabling the collaborative regulation of this adaptive program in multispecies communities.

The Svx proteins are virulence factors of phytopathogenic bacteria of the Pectobacterium genus. The specific functions of these proteins are unknown. Here we show that most of the phytopathogenic species of Pectobacterium, Dickeya, and Xanthomonas genera have genes encoding Svx proteins, as well as some plant-non-associated species of different bacterial genera. As such, the Svx-like proteins of phytopathogenic species form a distinct clade, pointing to the directed evolution of these proteins to provide effective interactions with plants. To get a better insight into the structure and functions of the Svx proteins, we analyzed the Svx of Pectobacterium atrosepticum (Pba)—an extracellular virulence factor secreted into the host plant cell wall (PCW). Using in silico analyses and by obtaining and analyzing the recombinant Pba Svx and its mutant forms, we showed that this protein was a gluzincin metallopeptidase. The 3D structure model of the Pba Svx was built and benchmarked against the experimental overall secondary structure content. Structure-based substrate specificity analysis using molecular docking revealed that the Pba Svx substrate-binding pocket might accept α-glycosylated proteins represented in the PCW by extensins—proteins that strengthen the PCW. Thus, these results elucidate the way in which the Pba Svx may contribute to the Pba virulence.

Cryptic peptides (cryptides) are biologically active peptides formed after proteolysis of native precursors present in animal venoms, for example. Proteolysis is an overlooked post-translational modification that increases venom complexity. The tripeptide KPP (Lys-Pro-Pro) is a peptide encrypted in the C-terminus of Ts14-a 25-mer peptide from the venom of the Tityus serrulatus scorpion that has a positive impact on the cardiovascular system, inducing vasodilation and reducing arterial blood pressure of hypertensive rats among other beneficial effects. A previous study reported that KPP and its native peptide Ts14 act via activation of the bradykinin receptor B2 (B2R). However, the cellular events underlying the activation of B2R by KPP are unknown. To study the cell signaling triggered by the Ts14 cryptide KPP, we incubated cardiac myocytes isolated from C57BL/6 mice with KPP (10 -7 mol·L -1) for 0, 5, or 30 min and explored the proteome and phosphoproteome. Our results showed that KPP regulated cardiomyocyte proteins associated with, but not limited to, apoptosis, muscle contraction, protein turnover, and the respiratory chain. We also reported that KPP led to AKT phosphorylation, activating AKT and its downstream target nitric oxide synthase. We also observed that KPP led to dephosphorylation of phospholamban (PLN) at its activation sites (S16 and T17), leading to reduced contractility of treated cardiomyocytes. Some cellular targets reported here for KPP (e.g., AKT, PLN, and ERK) have already been reported to protect the cardiac tissue from hypoxia-induced injury. Hence, this study suggests potential beneficial effects of this scorpion cryptide that needs to be further investigated, for example, as a drug lead for cardiac infarction.

Distilled spirits production using Saccharomyces cerevisiae requires understanding of the mechanisms of yeast cell response to alcohol stress. Reportedly, specific mutations in genes of the ubiquitin-proteasome system, e.g., RPN4, may result in strains exhibiting hyper-resistance to different alcohols. To study the Rpn4-dependent yeast response to short-term ethanol exposure, we performed a comparative analysis of the wild-type (WT) strain, strain with RPN4 gene deletion (rpn4-Δ), and a mutant strain with decreased proteasome activity and consequent Rpn4 accumulation due to PRE1 deregulation (YPL). The stress resistance tests demonstrated an increased sensitivity of mutant strains to ethanol compared with WT. Comparative proteomics analysis revealed significant differences in molecular responses to ethanol between these strains. GO analysis of proteins upregulated in WT showed enrichments represented by oxidative and heat responses, protein folding/unfolding, and protein degradation. Enrichment of at least one of these responses was not observed in the mutant strains. Moreover, activity of autophagy was not increased in the RPN4 deletion strain upon ethanol stress which agrees with changes in mRNA levels of ATG7 and PRB1 genes of the autophagy system. Activity of the autophagic system was clearly induced and accompanied with PRB1 overexpression in the YPL strain upon ethanol stress. We demonstrated that Rpn4 stabilization contributes to the PRB1 upregulation. CRISPR-Cas9-mediated repression of PACE-core Rpn4 binding sites in the PRB1 promoter inhibits PRB1 induction in the YPL strain upon ethanol treatment and results in YPL hypersensitivity to ethanol. Our data suggest that Rpn4 affects the autophagic system activity upon ethanol stress through the PRB1 regulation. These findings can be a basis for creating genetically modified yeast strains resistant to high levels of alcohol, being further used for fermentation in ethanol production.

New derivatives of benzofuroxan containing triazidoisobutyl fragments, opening the way for the creation of highly effective compositions with an increased value of energy characteristics, were synthesized for the first time. Such compounds are also an excellent platform for further modification and for the preparation of new biologically-active compounds containing tetrazole and triazole fragments. Calculations of heats of formation performed with the DFT (density functional theory) method showed that the studied compounds are high-energetic density ones, the enthalpies of formation of which are comparable to the enthalpies of formation of similar benzofuroxan derivatives and exceeds experimental enthalpy of formation of CL-14 (5,7-diamino-4,6-dinitrobenzofuroxan). The analysis of DSC indicates a sufficiently high thermal stability of the synthesized azidobenzofuroxans, which are acceptable for their use as components in the creation of highly efficient compositions with an increased value of energy characteristics.

The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.

Simple Summary This study aims to uncover the contribution of interferon-dependent antiviral mechanisms preserved in tumor cells to the resistance of glioblastoma multiforme cells to oncolytic viruses. To characterize the functionality of interferon signaling, we used omics profiling and titration-based measurements of cell sensitivity to a panel of viruses of diverse oncolytic potential. This study shows why patient-derived glioblastoma cultures can acquire increased resistance to oncolytic viruses in the presence of interferons and suggests an approach to ranking glioblastoma cells by the acquired resistance. Our findings are important for monitoring the oncolytic potential of viruses to overcome IFN-induced resistance of tumor cells and contribute to successful therapy. Abstract Oncolytic viruses have gained momentum in the last decades as a promising tool for cancer treatment. Despite the progress, only a fraction of patients show a positive response to viral therapy. One of the key variable factors contributing to therapy outcomes is interferon-dependent antiviral mechanisms in tumor cells. Here, we evaluated this factor using patient-derived glioblastoma multiforme (GBM) cultures. Cell response to the type I interferons’ (IFNs) stimulation was characterized at mRNA and protein levels. Omics analysis revealed that GBM cells overexpress interferon-stimulated genes (ISGs) and upregulate their proteins, similar to the normal cells. A conserved molecular pattern unambiguously differentiates between the preserved and defective responses. Comparing ISGs’ portraits with titration-based measurements of cell sensitivity to a panel of viruses, the “strength” of IFN-induced resistance acquired by GBM cells was ranked. The study demonstrates that suppressing a single ISG and encoding an essential antiviral protein, does not necessarily increase sensitivity to viruses. Conversely, silencing IFIT3 and PLSCR1 genes in tumor cells can negatively affect the internalization of vesicular stomatitis and Newcastle disease viruses. We present evidence of a complex relationship between the interferon response genes and other factors affecting the sensitivity of tumor cells to viruses.

Trypanosoma cruzi invades non-professional phagocytic cells by subverting their membrane repair process, which is dependent on membrane injury and cell signaling, intracellular calcium increase, and lysosome recruitment. Cells lacking lysosome-associated membrane proteins 1 and 2 (LAMP1 and LAMP2) are less permissive to parasite invasion but more prone to parasite intracellular multiplication. Several passages through a different intracellular environment can significantly change T. cruzi’s gene expression profile. Here, we evaluated whether one single passage through LAMP-deficient (KO) or wild-type (WT) fibroblasts, thus different intracellular environments, could influence T. cruzi Y strain trypomastigotes’ ability to invade L6 myoblasts and WT fibroblasts host cells. Parasites released from LAMP2 KO cells (TcY-L2−/−) showed higher invasion, calcium signaling, and membrane injury rates, for the assays in L6 myoblasts, when compared to those released from WT (TcY-WT) or LAMP1/2 KO cells (TcY-L1/2−/−). On the other hand, TcY-L1/2−/− showed higher invasion, calcium signaling, and cell membrane injury rates, for the assays in WT fibroblasts, compared to TcY-WT and TcY-L1/2−/−. Albeit TcY-WT presented an intermediary invasion and calcium signaling rates, compared to the others, in WT fibroblasts, they induced lower levels of injury, which reinforces that signals mediated by surface membrane protein interactions also have a significant contribution to trigger host cell calcium signals. These results clearly show that parasites released from WT or LAMP KO cells are distinct from each other. Additionally, these parasites’ ability to invade the cell may be distinct depending on which cell type they interact with. Since these alterations most likely would reflect differences among parasite surface molecules, we also evaluated their proteome. We identified few protein complexes, membrane, and secreted proteins regulated in our dataset. Among those are some members of MASP, mucins, trans-sialidases, and gp63 proteins family, which are known to play an important role during parasite infection and could correlate to TcY-WT, TcY-L1/2−/−, and TcY-L2−/− biological behavior.

Summary Acetylation of lysine 16 on histone H4 (H4K16ac) is catalyzed by histone acetyltransferase KAT8 and can prevent chromatin compaction in vitro. Although extensively studied in Drosophila, the functions of H4K16ac and two KAT8-containing protein complexes (NSL and MSL) are not well understood in mammals. Here, we demonstrate a surprising complex-dependent activity of KAT8: it catalyzes H4K5ac and H4K8ac as part of the NSL complex, whereas it catalyzes the bulk of H4K16ac as part of the MSL complex. Furthermore, we show that MSL complex proteins and H4K16ac are not required for cell proliferation and chromatin accessibility, whereas the NSL complex is essential for cell survival, as it stimulates transcription initiation at the promoters of housekeeping genes. In summary, we show that KAT8 switches catalytic activity and function depending on its associated proteins and that, when in the NSL complex, it catalyzes H4K5ac and H4K8ac required for the expression of essential genes.

Rationale One of the important steps in initial data processing of peptide mass spectra is the detection of peptide features in full-range mass spectra. Ion mobility offers advantages over previous methods performing this detection by providing an additional structure-specific separation dimension. However, there is a lack of open-source software that utilizes these advantages and detects peptide features in mass spectra acquired along with ion mobility data using new instruments such as timsTOF and/or FAIMS-Orbitrap. Methods Recently, a utility called Dinosaur was presented, which provides an efficient way for feature detection in peptide ion mass spectra. In this work we extended its functionality by developing Biosaur software to fully employ the additional information provided by ion mobility data. Biosaur was developed using the Python 3.8 programming language. Results Biosaur supports the processing of data acquired using mass spectrometers with ion mobility capabilities, specifically timsTOF and FAIMS. In addition, it processes mass spectra obtained in negative ion mode and reports cosine correlation table for peptide features which is useful for differentiation between in-source fragments and semi-tryptic peptides. Conclusions Biosaur is a utility for detecting peptide features in liquid chromatography-mass spectra with ion mobility and negative ion supports. The software is distributed with an open-source APACHE 2.0 license and is freely available on Github: https://github.com/abdrakhimov1/Biosaur.

Breast cancer is the most prevalent cancer in women worldwide. Its molecular subtypes are based on the presence/absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). MACL-1 and MGSO-3 are cell lines derived from primary tumor sites of patients diagnosed with luminal A subtype carcinoma (ER+/PR+/HER2-) and ductal carcinoma in situ (ER-/PR-/HER2+), respectively. However, these cell lines lost the expression of these markers over cell culturing, and both have triple-negative phenotypes (ER-/PR-/HER2-), which has the poorest prognosis. Here, we sought to study the proteome signature of MGSO-3 and MACL-1, comparing them with the epithelial cell line MCF-10A and the well-established metastatic-derived breast cancer cell line MDA-MB-231. Our results showed that proteins associated with the tricarboxylic acid cycle (TCA) and oxidative phosphorylation (OXPHOS) were upregulated in MGSO-3 and MACL-1 cells. These cell lines also showed upregulation of pro-apoptotic proteins when compared with MDA-MB-231. The molecular differences highlighted in this study may clarify the molecular basis behind cancer cells functioning and may reveal novel signatures across the breast cancer cell models.

Alamandine is a heptapeptide from the renin-angiotensin system (RAS) with similar structure/function to angiotensin-(1-7) [ang-(1-7)], but they act via different receptors. It remains elusive whether alamandine is an antiproliferative agent like ang-(1-7). The goal of this study was to evaluate the potential antiproliferative activity of alamandine and the underlying cellular signaling. We evaluated alamandine effect in the tumoral cell lines Mia PaCa-2 and A549, and in the nontumoral cell lines HaCaT, CHO and CHO transfected with the alamandine receptor MrgD (CHO-MrgD). Alamandine was able to reduce the proliferation of the tumoral cell lines in a MrgD-dependent fashion. We did not observe any effect in the nontumoral cell lines tested. We also performed proteomics and phosphoproteomics to study the alamandine signaling in Mia PaCa-2 and CHO-MrgD. Data suggest that alamandine induces a shift from anaerobic to aerobic metabolism in the tumoral cells, induces a negative regulation of PI3K/AKT/mTOR pathway and activates the transcriptional factor FoxO1; events that could explain, at least partially, the observed antiproliferative effect of alamandine. This study provides for the first time a comprehensive investigation of the alamandine signaling in tumoral (Mia PaCa-2) and nontumoral (CHO-MrgD) cells, highlighting the antiproliferative activity of alamandine/MrgD and its possible antitumoral effect.

Proteome-wide analyses most often rely on tandem mass spectrometry imposing considerable instrumental time consumption that is one of the main obstacles in a broader acceptance of proteomics in biomedical and clinical research. Recently, we presented a fast proteomic method termed DirectMS1 based on MS1-only mass spectra acquisition and data processing. The method allowed significant squeezing of the proteome-wide analysis to a few minute time frame at the depth of quantitative proteome coverage of 1000 proteins at 1% FDR. In this work, to further increase the capabilities of the DirectMS1 method, we explored the opportunities presented by the recent progress in the machine learning area and applied the LightGBM tree-based learning algorithm into the scoring of peptide-feature matches when processing MS1 spectra. Further, we integrated the peptide feature identification algorithm of DirectMS1 with the recently introduced peptide retention time prediction utility, DeepLC. Additional approaches to improve performance of the DirectMS1 method are discussed and demonstrated, such as FAIMS coupled to the Orbitrap mass analyzer. As a result of all improvements to DirectMS1, we succeeded in identifying more than 2000 proteins at 1% FDR from the HeLa cell line in a 5 minute LC-MS1 analysis.

With a steady growth in use of engineered nanoparticles (NPs) in consumer products the unintended exposure to humans has increased. The risks associated with introduction of NPs in the environment have been widely investigated, but mostly for single type of NPs. Herein, a single NP and NP co-exposure study is reported: the cellular effects of silver and platinum NPs on the main components of the blood–brain barrier, human cerebral microvascular endothelial cells, and human primary astrocytes. The synergy is quantitatively evaluated as per the Chou–Talalay method. NP co-exposure synergistically inhibits proliferation of both cell types, to a greater extent for endothelial cells. In addition, astrocytes are more tolerant to NPs. The mechanism of synergy with short-duration incubation time points (up to 30 min) is further explored. Although intracellular trafficking studies and quantitative assessments of NP uptake does not explain the mechanisms of synergistic cytotoxicity, a proteomics analysis suggests that it arises from activation of an immune modulating response and deregulation of the extracellular matrix organization. The substantial synergetic effects in the co-exposure studies highlight the importance of this work in relation to assessment of the health risks associated with nanomaterials.

Biological functions of many proteins are governed by post-translational modifications (PTMs). In particular, the rich PTM complement in histones controls the gene expression and chromatin structure with major health implications via a combinatoric language. Deciphering that "histone code" is the great challenge for proteomics given an astounding number of possible proteoforms, including isomers with different PTM positions. These must be disentangled on the top- or middle-down level to preserve the key PTM connectivity, which condensed-phase separations failed to achieve. We reported the capability of ion mobility spectrometry (IMS) methods to resolve such isomers for model histone tails. Here, we advance to biological samples, showing middle-down analyses of histones from mouse embryonic stem cells via online chromatography to fractionate proteoforms with distinct PTM sets, differential or field asymmetric waveform IMS (FAIMS) to resolve the isomers, and Orbitrap mass spectrometry with electron transfer dissociation to identify the resolved species.

The 2020 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers’ meeting was held from January 13th to January 17th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://doi.org/10.5281/zenodo.3890181.

On-tissue digestion has become the preferred method to identify proteins in mass spectrometry (MS) imaging. In this study, we report advances in data acquisition and protein identification for MS imaging after on-tissue digestion. Tryptic peptides in a coronal mouse brain section were measured at 50 μm pixel size and revealed detailed histological structures, e.g., the ependyma (consisting of one to two cell layers), which was confirmed by H&E staining. This demonstrates that MS imaging of tryptic peptides at or close to cellular resolution is within reach. We also describe a detailed identification workflow which resulted in the identification of 99 proteins (with 435 corresponding peptides), based on comparison with LC-MS/MS data and in silico digest. These results were obtained with stringent parameters, including high mass accuracy in imaging mode (RSME

Although multiple studies have reported the toxicological effects and underlying mechanisms of toxicity of silver nanoparticles (AgNP) in a variety of organisms, the interactions of AgNP with environmental contaminants such as cadmium are poorly understood. We used biochemical assays and mass spectrometry-based proteomics to assess the cellular and molecular effects induced by a co-exposure of HepG2 cells to AgNP and cadmium. Cell viability and energy homeostasis were slightly affected after a 4-h exposure to AgNP, cadmium, or a combination of the two; these endpoints were substantially altered after a 24-h co-exposure to AgNP and cadmium, while exposure to one of the two contaminants led only to minor changes. Proteomics analysis followed the same trend: while a 4-h exposure induced minor protein deregulation, a 24-h exposure to a combination of AgNP and cadmium deregulated 43% of the proteome. The toxicity induced by a combined exposure to AgNP and cadmium involved (1) inactivation of Nrf2, resulting in downregulation of antioxidant defense and proteasome-related proteins, (2) metabolic adaptation and ADP/ATP imbalance, and (3) increased protein synthesis possibly to reestablish homeostasis. The adaptation strategy was not sufficient to restore ADP/ATP homeostasis and to avoid cell death.

Glioblastoma (GBM) is a highly aggressive brain cancer with poor prognosis and low survival rate. Invasive cancer stem-like cells (CSCs) are responsible for tumor recurrence because they escape current treatments. Our main goal was to study the proteome of three GBM subpopulations to identify key molecules behind GBM cell phenotypes and potential cell markers for migrating cells. We used SuperQuant-an enhanced quantitative proteome approach-to increase proteome coverage. We found 148 proteins differentially regulated in migrating CSCs and 199 proteins differentially regulated in differentiated cells. We used Ingenuity Pathway Analysis (IPA) to predict upstream regulators, downstream effects and canonical pathways associated with regulated proteins. IPA analysis predicted activation of integrin-linked kinase (ILK) signaling, actin cytoskeleton signaling, and lysine demethylase 5B (KDM5B) in CSC migration. Moreover, our data suggested that microRNA-122 (miR-122) is a potential upstream regulator of GBM phenotypes as miR-122 activation was predicted for differentiated cells while its inhibition was predicted for migrating CSCs. Finally, we validated transferrin (TF) and procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 (PLOD2) as potential markers for migrating cells.

Protein arginine methyltransferase 5 (PRMT5) has emerged as a promising cancer drug target, and three PRMT5 inhibitors are currently in clinical trials for multiple malignancies. In this study, we investigated the role of PRMT5 in human acute myeloid leukemia (AML). Using an enzymatic dead version of PRMT5 and a PRMT5-specific inhibitor, we demonstrated the requirement of the catalytic activity of PRMT5 for the survival of AML cells. We then identified PRMT5 substrates using multiplexed quantitative proteomics and investigated their role in the survival of AML cells. We found that the function of the splicing regulator SRSF1 relies on its methylation by PRMT5 and that loss of PRMT5 leads to changes in alternative splicing of multiple essential genes. This explains the requirement of PRMT5 for leukemia cell survival. We show that PRMT5 regulates binding of SRSF1 to mRNAs and proteins and provide potential biomarkers for the treatment response to PRMT5 inhibitors.

Proteome characterization relies heavily on tandem mass spectrometry (MS/MS) and is thus associated with instrumentation complexity, lengthy analysis time, and limited duty-cycle. It was always tempting to implement approaches which do not require MS/MS, yet, they were constantly failing in achieving meaningful depth of quantitative proteome coverage within short experimental times, which is particularly important for clinical or biomarker discovery applications. Here, we report on the first successful attempt to develop a truly MS/MS-free method, DirectMS1, for bottom-up proteomics. The method was compared with the standard MS/MS-based data-dependent acquisition approach for proteome-wide analysis using 5-minute LC gradients. Specifically, we demonstrate identification of 1000 protein groups for a standard HeLa cell line digest. The amount of loaded sample was varied in a range from 1 ng to 500 ng, and the method demonstrated 10-fold higher sensitivity. Combined with the recently introduced Diffacto approach for relative protein quantification, DirectMS1 outperforms most popular MS/MS-based label-free quantitation approaches due to significantly higher protein sequence coverage.

Nanoparticles (NPs) in contact with protein-containing media such as biological fluids rapidly acquire a surface layer of proteins, known as the protein corona. The protein composition and structural properties of the protein corona are crucial for NP interactions with living cells. Although much has been learned about the protein corona phenomenon, further elucidation could benefit from extensive quantitative proteomics analysis. Herein we report a comprehensive quantitative characterization (>350 proteins) of the corona that formed on 60 nm silver NPs via interaction with human blood plasma, as a function of pH and temperature. By varying the pH and temperature one can access different conformational spaces and charge localizations of the plasma proteins, which in turn provide knowledge pertinent to how the proteome corresponds to binding affinity. Thirty-eight percent of the quantified proteins bind at all temperatures, 47% at all pH values, and of these most persistent proteins, approximately 60% do not significantly change in abundance within the protein corona. Evaluation of 544 protein properties (present in the Kyoto databank) suggests that binding of these proteins to NPs is determined by the extent of hydrophobicity, β-sheet propensity, α-helical structure (and turns), and amino acid composition. Protein binding is promoted by a larger amount of β-sheets, higher hydrophobicity, and a smaller amount of α-helices. Our work enhances researchers' knowledge of a long-standing, vexing aspect of the nano–bio interface.

Silver nanoparticles (AgNPs) have been reported to penetrate the central nervous system (CNS) and induce neurotoxicity. However, there is a paucity of understanding of the toxicity of AgNPs and their effect on the blood-brain barrier (BBB) including the underlying molecular mechanism(s) of action. Such information is important for the formulation of new strategies for delivery of biological therapeutics to central nervous system (CNS) targets. Using an in vitro BBB model and mass spectrometry-based proteomics, we investigated alterations in the proteomes of brain endothelial cells and astrocytes at different time points after AgNPs exposure (24 and 48 h). Our data showed that several proteins involved in neurodisorders and neurodegeneration were significantly upregulated in endothelial cells (e.g. 7-dehydrocholesterol reductase, zinc transporters 1 and 6), while proteins responsible for maintaining brain homeostasis were significantly downregulated (e.g anti-oxidative proteins glutathione peroxidase 1 and glutathione peroxidase 4). Many inflammatory pathways were significantly upregulated at 24 h post-AgNPs exposure (C9 pathway), while at 48 h proteins involved in BBB damage and anti-inflammatory responses were upregulated (quinoneoxidoreductase1 and glutamate cysteine ligase catalytic subunit) suggesting that by the later time point, cellular protection pathways had been activated to rescue the cells from AgNPs-induced toxicity. Our study suggests that in the initial stage of exposure, AgNPs exerted direct cellular stress on the endothelial cells by triggering a pro-inflammatory cascade. This study provides detailed insight into the toxic potency of AgNPs on in vitro BBB model and adds to the understanding of the adaptive role of BBB with regards to AgNPs-mediated toxicity.

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20–35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications.

Intact protein sequencing by tandem mass spectrometry (MS/MS), known as top-down protein sequencing, relies on efficient gas-phase fragmentation at multiple experimental conditions to achieve extensive amino acid sequence coverage. We developed the "topdownr" R-package for automated construction of multi-modal (i.e. involving CID, HCD, ETD, ETciD, EThcD and UVPD) MS/MS fragmentation methods on an orbitrap instrument platform and systematic analysis of the resultant spectra. We used topdownr to generate and analyze thousands of MS/MS spectra for five intact proteins of 10 - 30kDa. We achieved 90-100% coverage for the proteins tested and derived guiding principles for efficient sequencing of intact proteins. The data analysis workflow and statistical models of topdownr software and multi-modal MS/MS experiments provide a framework for optimizing MS/MS sequencing for any intact protein. Refined topdownr software will be suited for comprehensive characterization of protein pharmaceuticals and eventually also for de novo sequencing and detailed characterization of intact proteins.

Streptomycetes are multicellular bacteria with complex developmental cycles. They are of biotechnological importance as they produce most bioactive compounds used in biomedicine, e.g. antibiotic, antitumoral and immunosupressor compounds. Streptomyces genomes encode many Ser/Thr/Tyr kinases, making this genus an outstanding model for the study of bacterial protein phosphorylation events. We used mass spectrometry based quantitative proteomics and phosphoproteomics to characterize bacterial differentiation and activation of secondary metabolism of Streptomyces coelicolor. We identified and quantified 3461 proteins corresponding to 44.3% of the S. coelicolor proteome across three developmental stages: vegetative hypha (first mycelium); secondary metabolite producing hyphae (second mycelium); and sporulating hyphae. A total of 1350 proteins exhibited more than 2-fold expression changes during the bacterial differentiation process. These proteins include 136 regulators (transcriptional regulators, transducers, Ser/Thr/Tyr kinases, signaling proteins), as well as 542 putative proteins with no clear homology to known proteins which are likely to play a role in differentiation and secondary metabolism. Phosphoproteomics revealed 85 unique protein phosphorylation sites, 58 of them differentially phosphorylated during differentiation. Computational analysis suggested that these regulated protein phosphorylation events are implicated in important cellular processes, including cell division, differentiation, regulation of secondary metabolism, transcription, protein synthesis, protein folding and stress responses. We discovered a novel regulated phosphorylation site in the key bacterial cell division protein FtsZ (pSer319) that modulates sporulation and regulates actinorhodin antibiotic production. We conclude that manipulation of distinct protein phosphorylation events may improve secondary metabolite production in industrial streptomycetes, including the activation of cryptic pathways during the screening for new secondary metabolites from streptomycetes.

The inaugural European Bioinformatics Community (EuBIC) developer's meeting was held from January 9th to January 12th 2018 in Ghent, Belgium. While the meeting kicked off with an interactive keynote session featuring four internationally renowned experts in the field of computational proteomics, its primary focus were the hands-on hackathon sessions which featured six community-proposed projects revolving around three major topics: (i) quality control; (ii) workflows, protocols, and guidelines; and (iii) quantification. Here, we present an overview of the scientific program of the EuBIC developer's meeting and provide a starting point for follow-up on the covered projects.

An acquisition of increased sensitivity of cancer cells to viruses is a common outcome of malignant progression that justifies the development of oncolytic viruses as anticancer therapeutics. Studying molecular changes that underlie the sensitivity to viruses would help to identify cases where oncolytic virus therapy would be most effective. We quantified changes in protein abundances in two glioblastoma multiforme (GBM) cell lines that differ in the ability to induce resistance to vesicular stomatitis virus (VSV) infection in response to type I interferon (IFN) treatment. In IFN-treated samples we observed an up-regulation of protein products of some IFNregulated genes (IRGs). In total, the proteome analysis revealed up to 20% more proteins encoded by IRGs in the glioblastoma cell line, which develops resistance to VSV infection after pre-treatment with IFN. In both cell lines protein-protein interaction and signaling pathway analyses have revealed a significant stimulation of processes related to type I IFN signaling and defense responses to viruses. However, we observed a deficiency in STAT2 protein in the VSV-sensitive cell line that suggests a de-regulation of the JAK/STAT/IRF9 signaling. The study has shown that the up-regulation of IRG proteins induced by the IFNa treatment of GBM cells can be detected at the proteome level. Similar analyses could be applied for revealing functional alterations within the antiviral mechanisms in glioblastoma samples, accompanying by acquisition of sensitivity to oncolytic viruses. The approach can be useful for discovering the biomarkers that predict a potential sensitivity of individual glioblastoma tumors to oncolytic virus therapy.

Lignosulfonates are abundantly available byproducts of the paper and pulping industry, and they therefore represent a promising feedstock for new sustainable processes. For industrial applications of lignosulfonates, their molecular weight distribution is a critical factor. In order to decrease the average molecular weight of lignosulfonates, Seventeen basidiomycetes were screened for their capability to depolymerize lignosulfonates from spent sulfite liquor (SSL) in surface and liquid cultures. Five basidiomycetes polymerized the lignosulfonates under the selected conditions. Only Irpex consors was found to efficiently degrade calcium lignosulfonates when SSL (0.5%, w/w) was used as the sole carbon and nitrogen source. The average molecular weight of the lignosulfonates was reduced from ∼26 to ∼4 kDa as determined by size exclusion chromatography (SEC) within two weeks. Various extracellular enzyme activities of I. consors were determined over the culture period. High peroxidase activities were correlating with a high degradation rate and the culture was harvested at the day of highest peroxidase activity. A putative versatile peroxidase was isolated by fast protein liquid chromatography (FPLC) and its encoding cDNA was cloned.

SuperQuant is a quantitative proteomics data processing approach that uses complementary fragment ions to identify multiple co-isolated peptides in tandem mass spectra allowing for their quantification. This approach can be applied to any shotgun proteomics data set acquired with high mass accuracy for quantification at the MS1 level. The SuperQuant approach was developed and implemented as a processing node within the Thermo Proteome Discoverer 2.x. The performance of the developed approach was tested using dimethyl-labeled HeLa lysate samples having a ratio between channels of 10(heavy):4(medium):1(light). Peptides were fragmented with collision-induced dissociation using isolation windows of 1, 2, and 4 Th while recording data both with high-resolution and low-resolution. The results obtained using SuperQuant were compared to those using the conventional ion trap-based approach (low mass accuracy MS2 spectra), which is known to achieve high identification performance. Compared to the common high-resolution approach, the SuperQuant approach identifies up to 70% more peptide-spectrum matches (PSMs), 40% more peptides, and 20% more proteins at the 0.01 FDR level. It identifies more PSMs and peptides than the ion trap-based method. Improvements in identifications resulted in up to 10% more PSMs, 15% more peptides, and 10% more proteins quantified on the same raw data. The developed approach does not affect the accuracy of the quantification and observed coefficients of variation between replicates of the same proteins were close to the values typical for other precursor ion-based quantification methods. The raw data is deposited to ProteomeXchange (PXD001907). The developed node is available for testing at https://github.com/caetera/SuperQuantNode.