Proteomic Analysis of Human Macrophages Overexpressing Angiotensin-Converting Enzyme.

Angiotensin converting enzyme (ACE) exerts strong modulation of myeloid cell function independently of its cardiovascular arm. The success of the ACE-overexpressing murine macrophage model, ACE 10/10, in treating microbial infections and cancer opens a new avenue into whether ACE overexpression in human macrophages shares these benefits. Additionally, as ACE inhibitors are a widely used antihypertensive medication, their impact on ACE expressing immune cells is of interest and currently understudied. In the present study, we utilized mass spectrometry to characterize and assess global proteomic changes in an ACE-overexpressing human THP-1 cell line. Additionally, proteomic changes and cellular uptake following treatment with an ACE C-domain selective inhibitor, lisinopril-tryptophan, were also assessed. ACE activity was significantly reduced following inhibitor treatment, despite limited uptake within the cell, and both RNA processing and immune pathways were significantly dysregulated with treatment. Also present were upregulated energy and TCA cycle proteins and dysregulated cytokine and interleukin signaling proteins with ACE overexpression. A novel, functionally enriched immune pathway that appeared both with ACE overexpression and inhibitor treatment was neutrophil degranulation. ACE overexpression within human macrophages showed similarities with ACE 10/10 murine macrophages, paving the way for mechanistic studies aimed at understanding the altered immune function.

Shotgun proteomic analyses of Pseudomonas species isolated from fish products.

Numerous Pseudomonas species can infect aquatic animals, such as farmed rainbow trout, sea trout, sea bass, and sea bream, by causing disease or stress reactions. In aquaculture facilities, a number of Pseudomonas species have been isolated and identified as the main pathogens. The present study describes the characterization of 18 Pseudomonas strains, isolated from fish products using shotgun proteomics. The bacterial proteomes obtained were further analyzed to identify the main functional pathway proteins involved. In addition, this study revealed the presence of 1015 non-redundant peptides related to virulence factors. An additional 25 species-specific peptides were identified as putative Pseudomonas spp. biomarkers. The results constitute the largest dataset, described thus far for the rapid identification and characterization of Pseudomonas species present in edible fish; furthermore, these data can provide the basis for further research into the development of new therapies against these harmful pathogens.

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus.

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in manufacturing biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study, the aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. The protein AexA belongs to the Major Facilitator Superfamily (MFS). Deletion of aexA almost abolished aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step in its production. In vitro, proteoliposome transport assay further validated AexA's function and substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate metabolic engineering to improve secretion capability and lower the cost of bioproduction.

Validation of MS/MS Identifications and Label-Free Quantification Using Proline.

In the proteomics field, the production and publication of reliable mass spectrometry (MS)-based label-free quantitative results is a major concern. Due to the intrinsic complexity of bottom-up proteomics experiments (requiring aggregation of data relating to both precursor and fragment peptide ions into protein information, and matching this data across samples), inaccuracies and errors can occur throughout the data-processing pipeline. In a classical label-free quantification workflow, the validation of identification results is critical since errors made at this first stage of the workflow may have an impact on the following steps and therefore on the final result. Although false discovery rate (FDR) of the identification is usually controlled by using the popular target-decoy method, it has been demonstrated that this method can sometimes lead to inaccurate FDR estimates. This protocol shows how Proline can be used to validate identification results by using the method based on the Benjamini-Hochberg procedure and then quantify the identified ions and proteins in a single software environment providing data curation capabilities and computational efficiency.

Dynamin-like Protein 1 (DNML1) as a Molecular Target for Antibody-Based Immunotherapy to Treat Glaucoma.

Slow and progressive loss of retinal ganglion cells (RGCs) is the main characteristic of glaucoma, the second leading cause of blindness worldwide. Previous studies have shown that impaired mitochondrial dynamics could facilitate retinal neurodegeneration. Mitochondrial dynamics are regulated directly (fission) or more indirectly (fusion) by dynamin-like protein 1 (DNML1). Therefore, DNM1L might be a promising target for an antibody-based approach to treat glaucoma. The consequences of targeting endogenous DNM1L by antibodies in a glaucoma animal model have not been investigated yet. Here, we show that the intravitreal application of an anti-DNM1L antibody showed protective effects regarding the survival of RGCs and their axons in the retinal nerve fiber layer (RNFL). Antibody treatment also improved retinal functionality, as observed by electroretinography (Ganzfeld ERG). Western blot analysis revealed altered DNM1L phosphorylation and altered expression of proteins related to apoptosis suggesting a decreased apoptosis rate. Mass spectrometry analysis revealed 28 up-regulated and 21 down-regulated proteins (p < 0.05) in both experimental groups. Protein pathway analysis showed that many proteins interacted directly with the target protein DNM1L and could be classified into three main protein clusters: Vesicle traffic-associated (NSF, SNCA, ARF1), mitochondrion-associated (HSP9A, SLC25A5/ANT2, GLUD1) and cytoskeleton-associated (MAP1A) signaling pathway. Our results demonstrate that DNM1L is a promising target for an antibody-based approach to glaucoma therapy.

In situ cell-type-specific cell-surface proteomic profiling in mice.

Cell-surface proteins (CSPs) mediate intercellular communication throughout the lives of multicellular organisms. However, there are no generalizable methods for quantitative CSP profiling in specific cell types in vertebrate tissues. Here, we present in situ cell-surface proteome extraction by extracellular labeling (iPEEL), a proximity labeling method in mice that enables spatiotemporally precise labeling of cell-surface proteomes in a cell-type-specific environment in native tissues for discovery proteomics. Applying iPEEL to developing and mature cerebellar Purkinje cells revealed differential enrichment in CSPs with post-translational protein processing and synaptic functions in the developing and mature cell-surface proteomes, respectively. A proteome-instructed in vivo loss-of-function screen identified a critical, multifaceted role for Armh4 in Purkinje cell dendrite morphogenesis. Armh4 overexpression also disrupts dendrite morphogenesis; this effect requires its conserved cytoplasmic domain and is augmented by disrupting its endocytosis. Our results highlight the utility of CSP profiling in native mammalian tissues for identifying regulators of cell-surface signaling.

Functional Diversity and Evolution of the Drosophila Sperm Proteome.

Spermatozoa are central to fertilization and the evolutionary fitness of sexually reproducing organisms. As such, a deeper understanding of sperm proteomes (and associated reproductive tissues) has proven critical to the advancement of the fields of sexual selection and reproductive biology. Due to their extraordinary complexity, proteome depth-of-coverage is dependent on advancements in technology and related bioinformatics, both of which have made significant advancements in the decade since the last Drosophila sperm proteome was published. Here, we provide an updated version of the Drosophila melanogaster sperm proteome (DmSP3) using improved separation and detection methods and an updated genome annotation. Combined with previous versions of the sperm proteome, the DmSP3 contains a total of 3176 proteins, and we provide the first label-free quantitation of the sperm proteome for 2125 proteins. The top 20 most abundant proteins included the structural elements α- and ß-tubulins and sperm leucyl-aminopeptidases. Both gene content and protein abundance were significantly reduced on the X chromosome, consistent with prior genomic studies of X chromosome evolution. We identified 9 of the 16 Y-linked proteins, including known testis-specific male fertility factors. We also identified almost one-half of known Drosophila ribosomal proteins in the DmSP3. The role of this subset of ribosomal proteins in sperm is unknown. Surprisingly, our expanded sperm proteome also identified 122 seminal fluid proteins (Sfps), proteins originally identified in the accessory glands. We show that a significant fraction of 'sperm-associated Sfps' are recalcitrant to concentrated salt and detergent treatments, suggesting this subclass of Sfps are expressed in testes and may have additional functions in sperm, per se. Overall, our results add to a growing landscape of both sperm and seminal fluid protein biology and in particular provides quantitative evidence at the protein level for prior findings supporting the meiotic sex-chromosome inactivation model for male-specific gene and X chromosome evolution.

A Monoclonal Anti-HMGB1 Antibody Attenuates Neurodegeneration in an Experimental Animal Model of Glaucoma.

Neuroinflammation is a crucial process for the loss of retinal ganglion cells (RGC), a major characteristic of glaucoma. High expression of high-mobility group box protein 1 (HMGB1) plays a detrimental role in inflammatory processes and is elevated in the retinas of glaucoma patients. Therefore, this study aimed to investigate the effects of the intravitreal injection of an anti-HMGB1 monoclonal antibody (anti-HMGB1 Ab) in an experimental animal model of glaucoma. Two groups of Spraque Dawley rats received episcleral vein occlusion to chronically elevate intraocular pressure (IOP): (1) the IgG group, intravitreal injection of an unspecific IgG as a control, n = 5, and (2) the HMGB1 group, intravitreal injection of an anti-HMGB1 Ab, n = 6. IOP, retinal nerve fiber layer thickness (RNFLT), and the retinal flash response were monitored longitudinally. Post-mortem examinations included immunohistochemistry, microarray, and mass spectrometric analysis. RNFLT was significantly increased in the HMGB1 group compared with the IgG group (p < 0.001). RGC density showed improved neuronal cell survival in the retina in HMGB1 compared with the IgG group (p < 0.01). Mass spectrometric proteomic analysis of retinal tissue showed an increased abundance of RNA metabolism-associated heterogeneous nuclear ribonucleoproteins (hnRNPs), such as hnRNP U, D, and H2, in animals injected with the anti-HMGB1 Ab, indicating that the application of the antibody may cause increased gene expression. Microarray analysis showed a significantly decreased expression of C-X-C motif chemokine ligand 8 (CXCL8, p < 0.05) and connective tissue growth factor (CTGF, p < 0.01) in the HMGB1 group. Thus, these data suggest that intravitreal injection of anti-HMGB1 Ab reduced HMGB1-dependent inflammatory signaling and mediated RGC neuroprotection.

Automated Spatially Targeted Optical Microproteomics Investigates Inflammatory Lesions In Situ.

Tissue microenvironment properties like blood flow, extracellular matrix, or proximity to immune-infiltrate are important regulators of cell biology. However, methods to study regional protein expression in the native tissue environment are limited. To address this need, we developed a novel approach to visualize, purify, and measure proteins in situ using automated spatially targeted optical microproteomics (AutoSTOMP). Here, we report custom codes to specify regions of heterogeneity in a tissue section and UV-biotinylate proteins within those regions. We have developed liquid chromatography-mass spectrometry (LC-MS)/MS-compatible biochemistry to purify those proteins and label-free quantification methodology to determine protein enrichment in target cell types or structures relative to nontarget regions in the same sample. These tools were applied to (a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and (b) characterize inflammatory proteins enriched in IgG4+ lesions in human esophageal tissues. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools and sample availability are limited.

Bioenergetic and Proteomic Profiling of Immune Cells in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Patients: An Exploratory Study.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a heterogeneous, debilitating, and complex disease. Along with disabling fatigue, ME/CFS presents an array of other core symptoms, including autonomic nervous system (ANS) dysfunction, sustained inflammation, altered energy metabolism, and mitochondrial dysfunction. Here, we evaluated patients' symptomatology and the mitochondrial metabolic parameters in peripheral blood mononuclear cells (PBMCs) and plasma from a clinically well-characterised cohort of six ME/CFS patients compared to age- and gender-matched controls. We performed a comprehensive cellular assessment using bioenergetics (extracellular flux analysis) and protein profiles (quantitative mass spectrometry-based proteomics) together with self-reported symptom measures of fatigue, ANS dysfunction, and overall physical and mental well-being. This ME/CFS cohort presented with severe fatigue, which correlated with the severity of ANS dysfunction and overall physical well-being. PBMCs from ME/CFS patients showed significantly lower mitochondrial coupling efficiency. They exhibited proteome alterations, including altered mitochondrial metabolism, centred on pyruvate dehydrogenase and coenzyme A metabolism, leading to a decreased capacity to provide adequate intracellular ATP levels. Overall, these results indicate that PBMCs from ME/CFS patients have a decreased ability to fulfill their cellular energy demands.

Proteomics-Based Methodologies for the Detection and Quantification of Seafood Allergens.

Seafood is considered one of the main food allergen sources by the European Food Safety Authority (EFSA). It comprises several distinct groups of edible aquatic animals, including fish and shellfish, such as crustacean and mollusks. Recently, the EFSA recognized the high risk of food allergy over the world and established the necessity of developing new methodologies for its control. Consequently, accurate, sensitive, and fast detection methods for seafood allergy control and detection in food products are highly recommended. In this work, we present a comprehensive review of the applications of the proteomics methodologies for the detection and quantification of seafood allergens. For this purpose, two consecutive proteomics strategies (discovery and targeted proteomics) that are applied to the study and control of seafood allergies are reviewed in detail. In addition, future directions and new perspectives are also provided.

Soybean recovery from stress imposed by multigenerational growth in contaminated Chernobyl environment.

Ionizing radiation is a genotoxic anthropogenic stressor. It can cause heritable changes in the plant genome, which can be either adaptive or detrimental. There is still considerable uncertainty about the effects of chronic low-intensity doses since earlier studies reported somewhat contradictory conclusions. Our project focused on the recovery from the multiyear chronic ionizing radiation stress. Soybean (Glycine max) was grown in field plots located at the Chernobyl exclusion zone and transferred to the clean ground in the subsequent generation. We profiled proteome of mature seeds by two-dimensional gel electrophoresis. Overall, 15 differentially abundant protein spots were identified in the field comparison and 11 in the recovery generation, primarily belonging to storage proteins, disease/defense, and metabolism categories. Data suggested that during multigenerational growth in a contaminated environment, detrimental heritable changes were accumulated. Chlorophyll fluorescence parameters were measured on the late vegetative state, pointing to partial recovery of photosynthesis from stress imposed by contaminating radionuclides. A plausible explanation for the observed phenomena is insufficient provisioning of seeds by lower quality resources, causing a persistent effect in the offspring generation. Additionally, we hypothesized that immunity against phytopathogens was compromised in the contaminated field, but perhaps even primed in the clean ground, yet this idea requires direct functional validation in future experiments. Despite showing clear signs of physiological recovery, one season was not enough to normalize biochemical processes. Overall, our data contribute to the more informed agricultural radioprotection.

Comprehensive Comparison of Clinically Relevant Grain Proteins in Modern and Traditional Bread Wheat Cultivars.

Bread wheat (Triticum aestivum L.) is one of the most valuable cereal crops for human consumption. Its grain storage proteins define bread quality, though they may cause food intolerances or allergies in susceptible individuals. Herein, we discovered a diversity of grain proteins in three Ukrainian wheat cultivars: Sotnytsia, Panna (both modern selection), and Ukrainka (landrace). Firstly, proteins were isolated with a detergent-containing buffer that allowed extraction of various groups of storage proteins (glutenins, gliadins, globulins, and albumins); secondly, the proteome was profiled by the two-dimensional gel electrophoresis. Using multi-enzymatic digestion, we identified 49 differentially accumulated proteins. Parallel ultrahigh-performance liquid chromatography separation followed by direct mass spectrometry quantification complemented the results. Principal component analysis confirmed that differences among genotypes were a major source of variation. Non-gluten fraction better discriminated bread wheat cultivars. Various accumulation of clinically relevant plant proteins highlighted one of the modern genotypes as a promising donor for the breeding of hypoallergenic cereals.

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides.

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge and are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.

Gentle Introduction to the Statistical Foundations of False Discovery Rate in Quantitative Proteomics.

The vocabulary of theoretical statistics can be difficult to embrace from the viewpoint of computational proteomics research, even though the notions it conveys are essential to publication guidelines. For example, "adjusted p-values", "q-values", and "false discovery rates" are essentially similar concepts, whereas "false discovery rate" and "false discovery proportion" must not be confused, even though "rate" and "proportion" are related in everyday language. In the interdisciplinary context of proteomics, such subtleties may cause misunderstandings. This article aims to provide an easy-to-understand explanation of these four notions (and a few other related ones). Their statistical foundations are dealt with from a perspective that largely relies on intuition, addressing mainly protein quantification but also, to some extent, peptide identification. In addition, a clear distinction is made between concepts that define an individual property (i.e., related to a peptide or a protein) and those that define a set property (i.e., related to a list of peptides or proteins).

HIF prolyl hydroxylase PHD3 regulates translational machinery and glucose metabolism in clear cell renal cell carcinoma.

BACKGROUND: A key feature of clear cell renal cell carcinoma (ccRCC) is the inactivation of the von Hippel-Lindau tumour suppressor protein (pVHL) that leads to the activation of hypoxia-inducible factor (HIF) pathway also in well-oxygenated conditions. Important regulator of HIF-α, prolyl hydroxylase PHD3, is expressed in high amounts in ccRCC. Although several functions and downstream targets for PHD3 in cancer have been suggested, the role of elevated PHD3 expression in ccRCC is not clear. METHODS: To gain insight into the functions of high PHD3 expression in ccRCC, we used PHD3 knockdown by siRNA in 786-O cells under normoxic and hypoxic conditions and performed discovery mass spectrometry (LC-MS/MS) of the purified peptide samples. The LC-MS/MS results were analysed by label-free quantification of proteome data using a peptide-level expression-change averaging procedure and subsequent gene ontology enrichment analysis. RESULTS: Our data reveals an intriguingly widespread effect of PHD3 knockdown with 91 significantly regulated proteins. Under hypoxia, the response to PHD3 silencing was wider than under normoxia illustrated by both the number of regulated proteins and by the range of protein expression levels. The main cellular functions regulated by PHD3 expression were glucose metabolism, protein translation and messenger RNA (mRNA) processing. PHD3 silencing led to downregulation of most glycolytic enzymes from glucose transport to lactate production supported by the reduction in extracellular acidification and lactate production and increase in cellular oxygen consumption rate. Moreover, upregulation of mRNA processing-related proteins and alteration in a number of ribosomal proteins was seen as a response to PHD3 silencing. Further studies on upstream effectors of the translational machinery revealed a possible role for PHD3 in regulation of mTOR pathway signalling. CONCLUSIONS: Our findings suggest crucial involvement of PHD3 in the maintenance of key cellular functions including glycolysis and protein synthesis in ccRCC.

Relative protein quantification and accessible biology in lung tumor proteomes from four LC-MS/MS discovery platforms.

Discovery proteomics experiments include many options for sample preparation and MS data acquisition, which are capable of creating datasets for quantifying thousands of proteins. To define a strategy that would produce a dataset with sufficient content while optimizing required resources, we compared (1) single-sample LC-MS/MS with data-dependent acquisition to single-sample LC-MS/MS with data-independent acquisition and (2) peptide fractionation with label-free (LF) quantification to peptide fractionation with relative quantification of chemically labeled peptides (sixplex tandem mass tags (TMT)). These strategies were applied to the same set of four frozen lung squamous cell carcinomas and four adjacent tissues, and the overall outcomes of each experiment were assessed. We identified 6656 unique protein groups with LF, 5535 using TMT, 3409 proteins from single-sample analysis with data-independent acquisition, and 2219 proteins from single-sample analysis with data-dependent acquisition. Pathway analysis indicated the number of proteins per pathway was proportional to the total protein identifications from each method, suggesting limited biological bias between experiments. The results suggest the use of single-sample experiments as a rapid tissue assessment tool and digestion quality control or as a technique to maximize output from limited samples and use of TMT or LF quantification as methods for larger amounts of tumor tissue with the selection being driven mainly by instrument time limitations. Data are available via ProteomeXchange with identifiers PXD004682, PXD004683, PXD004684, and PXD005733.

Uses and misuses of the fudge factor in quantitative discovery proteomics.

Selecting proteins with significant differential abundance is the cornerstone of many relative quantitative proteomics experiments. To do so, a trade-off between p-value thresholding and fold-change thresholding can be performed because of a specific parameter, named fudge factor, and classically noted s0 . We have observed that this fudge factor is routinely turned away from its original (and statistically valid) use, leading to important distortion in the distribution of p-values, jeopardizing the protein differential analysis, as well as the subsequent biological conclusion. In this article, we provide a comprehensive viewpoint on this issue, as well as some guidelines to circumvent it.

Elucidation of Xylem-Specific Transcription Factors and Absolute Quantification of Enzymes Regulating Cellulose Biosynthesis in Populus trichocarpa.

Cellulose, the main chemical polymer of wood, is the most abundant polysaccharide in nature.1 The ability to perturb the abundance and structure of cellulose microfibrils is of critical importance to the pulp and paper industry as well as for the textile, wood products, and liquid biofuels industries. Although much has been learned at the transcript level about the biosynthesis of cellulose, a quantitative understanding at the proteome level has yet to be established. The study described herein sought to identify the proteins directly involved in cellulose biosynthesis during wood formation in Populus trichocarpa along with known xylem-specific transcription factors involved in regulating these key proteins. Development of an effective discovery proteomic strategy through a combination of subcellular fractionation of stem differentiating xylem tissue (SDX) with recently optimized FASP digestion protocols, StageTip fractionation, as well as optimized instrument parameters for global proteomic analysis using the quadrupole-orbitrap mass spectrometer resulted in the deepest proteomic coverage of SDX protein from P. trichocarpa with 9,146 protein groups being identified (1% FDR). Of these, 20 cellulosic/hemicellulosic enzymes and 43 xylem-specific transcription factor groups were identified. Finally, selection of surrogate peptides led to an assay for absolute quantification of 14 cellulosic proteins in SDX of P. trichocarpa.

Proteomics Is Analytical Chemistry: Fitness-for-Purpose in the Application of Top-Down and Bottom-Up Analyses.

Molecular mechanisms underlying health and disease function at least in part based on the flexibility and fine-tuning afforded by protein isoforms and post-translational modifications. The ability to effectively and consistently resolve these protein species or proteoforms, as well as assess quantitative changes is therefore central to proteomic analyses. Here we discuss the pros and cons of currently available and developing analytical techniques from the perspective of the full spectrum of available tools and their current applications, emphasizing the concept of fitness-for-purpose in experimental design based on consideration of sample size and complexity; this necessarily also addresses analytical reproducibility and its variance. Data quality is considered the primary criterion, and we thus emphasize that the standards of Analytical Chemistry must apply throughout any proteomic analysis.