Large-scale Proteomic Analysis Research Articles

Towards Phytopathogen Diagnostics? Coconut Bud Rot Pathogen Phytophthora palmivora Mycelial Proteome Analysis Informs Genome Annotation.

Planetary agriculture stands to benefit immensely from phytopathogen diagnostics, which would enable early detection of pathogens with harmful effects on crops. For example, Phytophthora palmivora is one of the most destructive phytopathogens affecting many economically important tropical crops such as coconut. P. palmivora causes diseases in over 200 host plants, and notably, the bud rot disease in coconut and oil palm, which is often lethal because it is usually detected at advanced stages of infection. Limited availability of large-scale omics datasets for P. palmivora is an important barrier for progress toward phytopathogen diagnostics. We report here the mycelial proteome of P. palmivora using high-resolution mass spectrometry analysis. We identified 8073 proteins in the mycelium. Gene Ontology-based functional classification of detected proteins revealed 4884, 4981, and 3044 proteins, respectively, with roles in biological processes, molecular functions, and cellular components. Proteins such as P-loop, NTPase, and WD40 domains with key roles in signal transduction pathways were identified. KEGG pathway analysis annotated 2467 proteins to various signaling pathways, such as phosphatidylinositol, Ca2+, and mitogen-activated protein kinase, and autophagy and cell cycle. These molecular substrates might possess vital roles in filamentous growth, sporangia formation, degradation of damaged cellular content, and recycling of nutrients in P. palmivora. This large-scale proteomics data and analyses pave the way for new insights on biology, genome annotation, and vegetative growth of the important plant pathogen P. palmivora. They also can help accelerate research on future phytopathogen diagnostics and preventive interventions.

The Lack of Dopamine Transporter Is Associated With Conditional Associative Learning Impairments and Striatal Proteomic Changes.

Dopamine (DA) is critically involved in different functions of the central nervous system (CNS) including control of voluntary movement, affect, reward, sleep, and cognition. One of the key components of DA neurotransmission is DA reuptake by the DA transporter (DAT), ensuring rapid clearance of DA from the synaptic cleft. Thus, lack of DAT leads to persistent high extracellular DA levels. While there is strong evidence for a role of striatal dopaminergic activity in learning and memory processes, little is known about the contribution of DAT deficiency to conditional learning impairments and underlying molecular processes. DAT-knockout (DAT-KO) rats were tested in a set of behavioral experiments evaluating conditional associative learning, which requires unaltered striatal function. In parallel, a large-scale proteomic analysis of the striatum was performed to identify molecular factors probably underlying behavioral patterns. DAT-KO rats were incapable to acquire a new operant skill in Pavlovian/instrumental autoshaping, although the conditional stimulus–unconditional stimulus (CS-US) association seems to be unaffected. These findings suggest that DAT directly or indirectly contributes to the reduction of transference of incentive salience from the reward to the CS. We propose that specific impairment of conditional learning might be caused by molecular adaptations to the hyperdopaminergic state, presumably by dopamine receptor 1 (DRD1) hypofunction, as proposed by proteomic analysis. Whether DRD1 downregulation can cause cognitive deficits in the hyperdopaminergic state is the subject of discussion, and further studies are needed to answer this question. This study may be useful for the interpretation of previous and the design of future studies in the dopamine field.

Tryptophan depletion results in tryptophan-to-phenylalanine substitutants

Activated T cells secrete interferon-γ, which triggers intracellular tryptophan shortage by upregulating the indoleamine 2,3-dioxygenase 1 (IDO1) enzyme1–4. Here we show that despite tryptophan depletion, in-frame protein synthesis continues across tryptophan codons. We identified tryptophan-to-phenylalanine codon reassignment (W>F) as the major event facilitating this process, and pinpointed tryptophanyl-tRNA synthetase (WARS1) as its source. We call these W>F peptides ‘substitutants’ to distinguish them from genetically encoded mutants. Using large-scale proteomics analyses, we demonstrate W>F substitutants to be highly abundant in multiple cancer types. W>F substitutants were enriched in tumours relative to matching adjacent normal tissues, and were associated with increased IDO1 expression, oncogenic signalling and the tumour-immune microenvironment. Functionally, W>F substitutants can impair protein activity, but also expand the landscape of antigens presented at the cell surface to activate T cell responses. Thus, substitutants are generated by an alternative decoding mechanism with potential effects on gene function and tumour immunoreactivity.

Domesticated LTR-Retrotransposon gag-Related Gene (Gagr) as a Member of the Stress Response Network in Drosophila.

The most important sources of new components of genomes are transposable elements, which can occupy more than half of the nucleotide sequence of the genome in higher eukaryotes. Among the mobile components of a genome, a special place is occupied by retroelements, which are similar to retroviruses in terms of their mechanisms of integration into a host genome. The process of positive selection of certain sequences of transposable elements and retroviruses in a host genome is commonly called molecular domestication. There are many examples of evolutionary adaptations of gag (retroviral capsid) sequences as new regulatory sequences of different genes in mammals, where domesticated gag genes take part in placenta functioning and embryogenesis, regulation of apoptosis, hematopoiesis, and metabolism. The only gag-related gene has been found in the Drosophila genome—Gagr. According to the large-scale transcriptomic and proteomic analysis data, the Gagr gene in D. melanogaster is a component of the protein complex involved in the stress response. In this work, we consider the evolutionary processes that led to the formation of a new function of the domesticated gag gene and its adaptation to participation in the stress response. We discuss the possible functional role of the Gagr as part of the complex with its partners in Drosophila, and the pathway of evolution of proteins of the complex in eukaryotes to determine the benefit of the domesticated retroelement gag gene.

Abstract 014: Protein Biomarkers Of Healthy Dietary Patterns In The Atherosclerosis Risk In Communities Study

Introduction: Molecular mechanisms underlying the benefits of healthy dietary patterns on chronic diseases are poorly understood. Identifying protein biomarkers of healthy diets can help us characterize biological pathways influenced by diet quality and confirm the validity of established healthy dietary patterns. Objectives: To identify protein biomarkers that are associated with diet quality using four metrics of adherence to dietary guidelines and healthy dietary patterns: the Alternative Healthy Eating Index-2010 (AHEI-2010); the Alternate Mediterranean Diet (aMED); the Dietary Approaches to Stop Hypertension (DASH) diet; and the Healthy Eating Index-2015 (HEI-2015). Methods: We examined 4,877 plasma proteins among 10,593 participants with available proteomics and dietary data from the Atherosclerosis Risk in Communities (ARIC) Study at visit 3 (1993-1995). Dietary intake data were collected through a food frequency questionnaire, and proteins were measured in plasma using an aptamer-based proteomics assay from SomaLogic. We used multivariable linear regression models to examine the association between proteins and each dietary pattern. Results: In the multivariable adjusted model, 276 out of 4,877 proteins (5.7%) were associated with at least one dietary pattern (AHEI: 74; aMED: 37; DASH: 250; HEI: 135; p-value < 0.05/4,877=1.0х10 -5 ) ( Figure ). There were 140 proteins that were associated with only one dietary pattern (AHEI: 6; aMED: 0; DASH: 116; HEI: 18). Conclusion: Large-scale proteomic analysis identified proteins that are representative of a range of healthy dietary patterns and proteins that are specific to single healthy dietary pattern. Future studies are warranted to link diet-related proteins with clinical outcomes.

Annotated Protein Database Using Known Cleavage Sites for Rapid Detection of Secreted Proteins.

Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of secreted proteins has contributed to our understanding of human disease and physiology but is limited by its need for accurate protein database annotation. Common assumptions used in proteomics of perfect protease specificity are inaccurate for secreted proteins, which are cleaved by numerous endogenous proteases. Here, we describe the generation of an optimized protein database that divides proteins into their individual biological chains and peptides to allow fast identification of semi-tryptic peptides from secreted proteins using fully tryptic searches. We applied this biologically annotated database to previously published human plasma proteome data sets containing either DIA or DDA data, using Spectronaut, DIA-NN, MaxDIA, and MaxQuant. Using our annotated database, we greatly reduced search times while achieving similar protein and peptide identifications compared to that obtained from standard approaches using semi-tryptic searches. Furthermore, our database enables the identification of biologically relevant semi-tryptic peptides using data analysis packages that are not capable of semi-tryptic searches. Together, these findings demonstrate that our annotated database is more capable than currently available databases for secreted protein analysis and is particularly useful for large-scale plasma proteome analysis.

Shotgun Proteomics as a Powerful Tool for the Study of the Proteomes of Plants, Their Pathogens, and Plant-Pathogen Interactions.

The interaction between plants and pathogenic microorganisms is a multifaceted process mediated by both plant- and pathogen-derived molecules, including proteins, metabolites, and lipids. Large-scale proteome analysis can quantify the dynamics of proteins, biological pathways, and posttranslational modifications (PTMs) involved in the plant–pathogen interaction. Mass spectrometry (MS)-based proteomics has become the preferred method for characterizing proteins at the proteome and sub-proteome (e.g., the phosphoproteome) levels. MS-based proteomics can reveal changes in the quantitative state of a proteome and provide a foundation for understanding the mechanisms involved in plant–pathogen interactions. This review is intended as a primer for biologists that may be unfamiliar with the diverse range of methodology for MS-based shotgun proteomics, with a focus on techniques that have been used to investigate plant–pathogen interactions. We provide a summary of the essential steps required for shotgun proteomic studies of plants, pathogens and plant–pathogen interactions, including methods for protein digestion, identification, separation, and quantification. Finally, we discuss how protein PTMs may directly participate in the interaction between a pathogen and its host plant.

Proteomic Analysis of Human Neural Stem Cell Differentiation by SWATH-MS.

The unique properties of stem cells to self-renew and differentiate hold great promise in disease modelling and regenerative medicine. However, more information about basic stem cell biology and thorough characterization of available stem cell lines is needed. This is especially essential to ensure safety before any possible clinical use of stem cells or partially committed cell lines. As proteins are the key effector molecules in the cell, the proteomic characterization of cell lines, cell compartments or cell secretome and microenvironment is highly beneficial to answer above mentioned questions. Nowadays, method of choice for large-scale discovery-based proteomic analysis is mass spectrometry (MS) with data-independent acquisition (DIA). DIA is a robust, highly reproducible, high-throughput quantitative MS approach that enables relative quantification of thousands of proteins in one sample. In the current protocol, we describe a specific variant of DIA known as SWATH-MS for characterization of neural stem cell differentiation. The protocol covers the whole process from cell culture, sample preparation for MS analysis, the SWATH-MS data acquisition on TTOF 5600, the complete SWATH-MS data processing and quality control using Skyline software and the basic statistical analysis in R and MSstats package. The protocol for SWATH-MS data acquisition and analysis can be easily adapted to other samples amenable to MS-based proteomics.

Proteomics of isolated sieve tubes from Nicotiana tabacum: sieve element–specific proteins reveal differentiation of the endomembrane system

Symplasmicly connected cells called sieve elements form a network of tubes in the phloem of vascular plants. Sieve elements have essential functions as they provide routes for photoassimilate distribution, the exchange of developmental signals, and the coordination of defense responses. Nonetheless, they are the least understood main type of plant cells. They are extremely sensitive, possess a reduced endomembrane system without Golgi apparatus, and lack nuclei and translation machineries, so that transcriptomics and similar techniques cannot be applied. Moreover, the analysis of phloem exudates as a proxy for sieve element composition is marred by methodological problems. We developed a simple protocol for the isolation of sieve elements from leaves and stems of Nicotiana tabacum at sufficient amounts for large-scale proteome analysis. By quantifying the enrichment of individual proteins in purified sieve element relative to bulk phloem preparations, proteins of increased likelyhood to function specifically in sieve elements were identified. To evaluate the validity of this approach, yellow fluorescent protein constructs of genes encoding three of the candidate proteins were expressed in plants. Tagged proteins occurred exclusively in sieve elements. Two of them, a putative cytochrome b561/ferric reductase and a reticulon-like protein, appeared restricted to segments of the endoplasmic reticulum (ER) that were inaccessible to green fluorescent protein dissolved in the ER lumen, suggesting a previously unknown differentiation of the endomembrane system in sieve elements. Evidently, our list of promising candidate proteins ( SI Appendix, Table S1) provides a valuable exploratory tool for sieve element biology.

Transcription-wide mapping of dihydrouridine reveals that mRNA dihydrouridylation is required for meiotic chromosome segregation

The epitranscriptome has emerged as a new fundamental layer of control of gene expression. Nevertheless, the determination of the transcriptome-wide occupancy and function of RNA modifications remains challenging. Here we have developed Rho-seq, an integrated pipeline detecting a range of modifications through differential modification-dependent rhodamine labeling. Using Rho-seq, we confirm that the reduction of uridine to dihydrouridine (D) by the Dus reductase enzymes targets tRNAs in E.coli and fission yeast. We find that the D modification is also present on fission yeast mRNAs, particularly those encoding cytoskeleton-related proteins, which is supported by large-scale proteome analyses and ribosome profiling. We show that the α-tubulin encoding mRNA nda2 undergoes Dus3-dependent dihydrouridylation, which affects its translation. The absence of the modification on nda2 mRNA strongly impacts meiotic chromosome segregation, resulting in low gamete viability. Applying Rho-seq to human cells revealed that tubulin mRNA dihydrouridylation is evolutionarily conserved.

Biomarkers of subclinical atherosclerosis in patients with psoriasis

Psoriasis is linked with increased risk of cardiovascular disease (CVD) that is underestimated by traditional risk stratification. We conducted a large-scale plasma proteomic analysis by use of a proximity extension assay in 85 patients with a history of moderate-to-severe psoriasis with or without established atherosclerotic CVD. Differentially expressed proteins associated with CVD were correlated with subclinical atherosclerotic markers including vascular inflammation determined by 18F-fluorodeoxyglucose positron emission tomography/computed tomography, carotid intima-media thickness (CIMT), carotid artery plaques, and coronary artery calcium score (CCS) in the patients without CVD and statin treatment. We also examined the association between the neutrophil-to-lymphocyte ratio (NLR) and subclinical atherosclerosis. In unadjusted analyses, growth differentiation factor-15 (GDF-15) levels and NLR were increased, while tumor necrosis factor (TNF)-related activation-inducing ligand (TRANCE) and TNF-related apoptosis-induced ligand (TRAIL) levels were decreased in patients with established CVD compared to those without CVD. Among patients with psoriasis without CVD and statin treatment, GDF-15 levels were negatively associated with vascular inflammation in the ascending aorta and entire aorta, and positively associated with CIMT and CCS. NLR was positively associated with vascular inflammation in the carotid arteries. Our data suggest that circulating GDF-15 levels and NLR might serve as biomarkers of subclinical atherosclerosis in patients with psoriasis.

Integrating Molecular Biomarker Inputs Into Development and Use of Clinical Cancer Therapeutics.

Biomarkers can contribute to clinical cancer therapeutics at multiple points along the patient’s diagnostic and treatment course. Diagnostic biomarkers can screen or classify patients, while prognostic biomarkers predict their survival. Biomarkers can also predict treatment efficacy or toxicity and are increasingly important in development of novel cancer therapeutics. Strategies for biomarker identification have involved large-scale genomic and proteomic analyses. Pathway-specific biomarkers are already in use to assess the potential efficacy of immunotherapy and targeted cancer therapies. Judicious application of machine learning techniques can identify disease-relevant features from large data sets and improve predictive models. The future of biomarkers likely involves increasing utilization of liquid biopsy and multiple samplings to better understand tumor heterogeneity and identify drug resistance.

Peptide retention time prediction for peptides with post-translational modifications: N-terminal (α-amine) and lysine (ε-amine) acetylation

Development of a peptide retention prediction model in reversed-phase chromatography is reported for acetylated peptides – both N-terminal (α-) and side chain of Lys (ε-amine) residues. Large-scale proteomic 2D LC-MS analyses of acetylated/non-acetylated tryptic digest of whole human cell lysate have been used to assemble representative retention data sets of 25,000+ modified/non-modified pairs. This allowed elucidating chromatographic behaviour of modified peptides in three different separation modes: high pH reversed-phase, HILIC separation on amide phase (first dimension of 2D) and reversed-phase separation with formic acid as ion-pairing modifier in the second dimension. On average, N-terminal acetylation increases peptide RP retention at acidic pH by 5 Hydrophobicity Index units (% acetonitrile). Acetylation of first lysine adds another 4.1%. The magnitude of the retention shift varies greatly depending on the number of modified amines, peptide length, and N-terminal peptide sequence. Large retention shifts have been observed for peptides with hydrophobic N-termini and specifically peptides carrying sequences characteristic for amphipathic helical structures – all in complete agreement with major sequence-specific features of RP retention mechanism. The utility of the modified Sequence Specific Retention Calculator model has been verified for the in-vivo N-terminally acetylated peptides detected by 2D LC-MS/MS analysis of a yeast tryptic digest. The effect of N-terminal acetylation was also evaluated for six different HILIC columns, strong cation- and strong anion exchange separations using previously acquired 2D LC-MS/MS data.

Proteomic characterization of primary and metastatic prostate cancer reveals reduced proteinase activity in aggressive tumors

Prostate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

Transcriptomic and Proteomic Analysis of Drought Stress Response in Opium Poppy Plants during the First Week of Germination.

Water deficiency is one of the most significant abiotic stresses that negatively affects growth and reduces crop yields worldwide. Most research is focused on model plants and/or crops which are most agriculturally important. In this research, drought stress was applied to two drought stress contrasting varieties of Papaver somniferum (the opium poppy), a non-model plant species, during the first week of its germination, which differ in responses to drought stress. After sowing, the poppy seedlings were immediately subjected to drought stress for 7 days. We conducted a large-scale transcriptomic and proteomic analysis for drought stress response. At first, we found that the transcriptomic and proteomic profiles significantly differ. However, the most significant findings are the identification of key genes and proteins with significantly different expressions relating to drought stress, e.g., the heat-shock protein family, dehydration responsive element-binding transcription factors, ubiquitin E3 ligase, and others. In addition, metabolic pathway analysis showed that these genes and proteins were part of several biosynthetic pathways most significantly related to photosynthetic processes, and oxidative stress responses. A future study will focus on a detailed analysis of key genes and the development of selection markers for the determination of drought-resistant varieties and the breeding of new resistant lineages.

Inhibition of Unc-51 like Autophagy Activating Kinase 1 (ULK1) Is Highly Synergistic with Chemotherapy and Bcl2 Inhibition in Acute Myeloid Leukemia (AML)

IntroductionAcquired resistance to chemotherapy and targeted therapies in AML may be mediated through autophagy. Bcl2 inhibition has also been reported to induce autophagy1. Therapeutic autophagy inhibition has been challenging because of limited druggable targets and pathway redundancy. Our preclinical work confirmed that Atg7 inhibition potentiates chemotherapy effects in AML2. While Atg7 is an E1-like activating enzyme,ULK1 is an apical kinase in the autophagy cascade and the only S/T kinase in the core autophagy pathway that phosphorylates multiple targets (Atg13, Beclin1 and VPS34). ULK1 initiates autophagosome formation and maturation. With the recent development of ULK1 inhibitors we were enabled to investigate the effects of ULK1 inhibition in AML.MethodsFirst we confirmed that chemotherapy (cytarabine, Ara-C) and Bcl2 inhibitor ABT199 induce autophagy in AML cells by LC3 quantification. Next, we studied potential synergy of these agents with ULK1 inhibitor, SBI-0206965 (SBI) in inhibiting cell proliferation and inducing apoptosis. For further insights into the mechanisms of synergy, we conducted large-scale proteomics analyses by reverse phase protein array (RPPA) and mass cytometry (CyTOF).ResultsAs a single agent SBI showed activity against a wide range of AML cell lines (IC50: 250 nM to 3.5 uM) and stem and progenitor cell populations (CD34+/CD38-) in primary AML samples with FLT3-ITD or p53 mutations, while sparing normal CD34+/CD38- cells. Immunoblotting confirmed target inhibition (Fig 1a) and apoptosis induction (Fig 1b).Treatment with Ara-C and ABT199 induced autophagy, which was reversed by SBI (Fig 2). Confirming our hypothesis, SBI showed significant synergy with both Ara-C (CI: 0.52) and ABT199 (CI: 0.16). Additional synergy was seen with FLT3-ITD inhibitor Sorafenib and MEK inhibitor Trametinib.Consistent with previous reports that autophagy deficiency induces DNA damage due to loss of ROS scavenging capacity, downregulation of DNA repair proteins and impaired protein complex formation at the sites of DNA damage3, we found that ULK1 inhibition results in elevated ROS generation which could be reversed by the ROS inhibitor N-acetylcysteine (NAC) (Fig 3a). We also found induction of DNA damage (Fig 3b). Autophagy deficiency has been recently shown to regulate DNA repair via Chk1 downregulation4. Our RPPA data showed significant decrease in cell cycle regulators phosphoS807/811 Rb, CDK1 and Chk1 (Fig 3b). Cell cycle analysis by EdU incorporation assay showed G1 arrest upon treatment with SBI (Fig 3c). In contrast, Bcl2A1 (pro-survival Bcl2 family member) was the most upregulated protein after treatment with SBI; rationalizing our combination studies with ABT199, which exhibits profound synergy (CI: 0.16) associated with increased cleaved Caspase7 and DNA damage (g-H2AX) (Fig 3b).Combinatorial studies with Ara-C also showed increased DNA damage (Fig 4a). Finally, CyTOF confirmed decreased phosphorylation of important signaling molecules like Akt, Erk1/2, MEK1/2, JNK, p38) upon SBI treatment (Fig 4b).We are conducting confirmatory mechanistic studies (changes in DNA damage response, ROS generation, etc.) by genetic silencing of ULK1 as well as studying the effect of drug combinations in the presence or absence of ULK1 inhibition in in vivo models of AML.ConclusionULK1 inhibitor SBI-0206965 effectively reverses therapy induced autophagy and synergizes with chemotherapy and Bcl2 inhibition imparting anti-leukemic effects, thus establishing a therapeutic rationale for ULK1 inhibition in AML. We are pursuing studies to validate the role of ULK1 inhibition in leukemia establishment, engraftment and survival in mice.

Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS.

A current trend in proteomics is to acquire data in a "single-shot" by LC-MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC-MS/MS system operating a 1 mm i.d. × 150 mm column, at a flow-rate of 50 μL/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of ∼9 000 proteins from 50 μg of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by μLC-MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.̀.

Hepatotoxic evaluation of toosendanin via biomarker quantification and pathway mapping of large-scale chemical proteomics

Drug-induced liver injury (DILI) is a major side effect, sometimes can't be exactly evaluated by current approaches partly as the covalent modification of drug or its reactive metabolites (RMs) with proteins is a possible reason. In this study, we developed a rapid, sensitive, and specific analytical method to assess the hepatotoxicity induced by drug covalently modified proteins based on the quantification of the modified amino acids using toosendanin (TSN), a hepatotoxic chemical, as an example. TSN RM-protein adducts both in rat liver and blood showed good correlation with the severity of hepatotoxicity. Thus, TSN RM-protein adducts in serum can potentially serve as minimally invasive biomarkers of hepatotoxicity. Meanwhile, large-scale chemical proteomics analysis showed that at least 84 proteins were modified by TSN RMs in rat liver, and the bioinformatics analysis revealed that TSN might induce hepatotoxicity through multi-target protein-protein interaction especially involved in energy metabolism. These findings suggest that our approach may serve as a valuable tool to evaluate DILI and investigate the possible mechanism, especially for complex compounds.

Biostimulant impacts of Glutacetine® and derived formulations (VNT1 and VNT4) on the bread wheat grain proteome

Nitrogen (N) fertilizer is essential to ensure grain yield and quality in bread wheat. Improving N use efficiency is therefore crucial for wheat grain protein quality. In the present work, we analysed the effects on the winter wheat grain proteome of biostimulants containing Glutacetine® or two derived formulations (VNT1 and 4) when mixed with urea-ammonium-nitrate fertilizer. A large-scale quantitative proteomics analysis of two wheat flour fractions produced a dataset of 4369 identified proteins. Quantitative analysis revealed 9, 39 and 96 proteins with a significant change in abundance after Glutacetine®, VNT1 and VNT4 treatments, respectively, with a common set of 11 proteins that were affected by two different biostimulants. The major effects impacted proteins involved in (i) protein synthesis regulation (mainly ribosomal and binding proteins), (ii) defence and responses to stresses (including chitin-binding protein, heat shock 70 kDa protein 1 and glutathione S-transferase proteins), (iii) storage functions related to gluten protein alpha-gliadins and starch synthase and (iv) seed development with proteins implicated in protease activity, energy machinery, and the C and N metabolism pathways. Altogether, our study showed that Glutacetine®, VNT1 and VNT4 biostimulants positively affected protein composition related to grain quality.Data are available via ProteomeXchange with identifier PXD021513. SignificanceWe performed a large-scale quantitative proteomics study of the total protein extracts from flour samples to determine the effect of Glutacetine®-based biostimulants treatment on the protein composition of bread wheat grain. To our knowledge, only a few studies in the literature have applied proteomic approaches to study bread wheat grains and in particular to investigate the effect of biostimulants on the grain proteome of this cereal crop. In addition, most approaches used fractional extraction of proteins to target reserve proteins followed electrophoresis which leads to low identification rate of proteins. We identified and quantified a large protein dataset of 4369 proteins and determined ontological class of proteins affected by biostimulants treatments. Our proteomics investigation revealed the important role of these new biostimulants in achieving significant changes in protein synthesis regulation, storage functions, protease activity, energy machinery, C and N metabolism pathways and responses to biotic and abiotic stresses in grain.

Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk.

The plasma proteomic changes that precede the onset of dementia could yield insights into disease biology and highlight new biomarkers and avenues for intervention. We quantified 4,877 plasma proteins in nondemented older adults in the Atherosclerosis Risk in Communities cohort and performed a proteome-wide association study of dementia risk over five years (n = 4,110; 428 incident cases). Thirty-eight proteins were associated with incident dementia after Bonferroni correction. Of these, 16 were also associated with late-life dementia risk when measured in plasma collected nearly 20 years earlier, during mid-life. Two-sample Mendelian randomization causally implicated two dementia-associated proteins (SVEP1 and angiostatin) in Alzheimer's disease. SVEP1, an immunologically relevant cellular adhesion protein, was found to be part of larger dementia-associated protein networks, and circulating levels were associated with atrophy in brain regions vulnerable to Alzheimer's pathology. Pathway analyses for the broader set of dementia-associated proteins implicated immune, lipid, metabolic signaling and hemostasis pathways in dementia pathogenesis.