The Proteomics Identifications database: 2010 update

Unveiling the power of proteomics in advancing tropical animal health and production

Proteomics, the large-scale study of proteins in biological systems has emerged as a pivotal tool in the field of animal and veterinary sciences, mainly for investigating local and rustic breeds. Proteomics provides valuable insights into biological processes underlying animal growth, reproduction, health, and disease. In this review, we highlight the key proteomics technologies, methodologies, and their applications in domestic animals, particularly in the tropical context. We also discuss advances in proteomics research, including integration of multi-omics data, single-cell proteomics, and proteogenomics, all of which are promising for improving animal health, adaptation, welfare, and productivity. However, proteomics research in domestic animals faces challenges, such as sample preparation variation, data quality control, privacy and ethical considerations relating to animal welfare. We also provide recommendations for overcoming these challenges, emphasizing the importance of following best practices in sample preparation, data quality control, and ethical compliance. We therefore aim for this review to harness the full potential of proteomics in advancing our understanding of animal biology and ultimately improve animal health and productivity in local breeds of diverse animal species in a tropical context.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Perturbations of the Proteome and of Secreted Metabolites in Primary Astrocytes from the hSOD1(G93A) ALS Mouse Model

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease whose pathophysiology is largely unknown. Despite the fact that motor neuron (MN) death is recognized as the key event in ALS, astrocytes dysfunctionalities and neuroinflammation were demonstrated to accompany and probably even drive MN loss. Nevertheless, the mechanisms priming astrocyte failure and hyperactivation are still obscure. In this work, altered pathways and molecules in ALS astrocytes were unveiled by investigating the proteomic profile and the secreted metabolome of primary spinal cord astrocytes derived from transgenic ALS mouse model overexpressing the human (h)SOD1(G93A) protein in comparison with the transgenic counterpart expressing hSOD1(WT) protein. Here we show that ALS primary astrocytes are depleted of proteins-and of secreted metabolites-involved in glutathione metabolism and signaling. The observed increased activation of Nf-kB, Ebf1, and Plag1 transcription factors may account for the augmented expression of proteins involved in the proteolytic routes mediated by proteasome or endosome-lysosome systems. Moreover, hSOD1(G93A) primary astrocytes also display altered lipid metabolism. Our results provide novel insights into the altered molecular pathways that may underlie astrocyte dysfunctionalities and altered astrocyte-MN crosstalk in ALS, representing potential therapeutic targets to abrogate or slow down MN demise in disease pathogenesis.

Nucleolin Rescues TDP-43 Toxicity in Yeast and Human Cell Models

TDP-43 is a nuclear protein involved in pivotal processes, extensively studied for its implication in neurodegenerative disorders. TDP-43 cytosolic inclusions are a common neuropathologic hallmark in amyotrophic lateral sclerosis (ALS) and related diseases, and it is now established that TDP-43 misfolding and aggregation play a key role in their etiopathology. TDP-43 neurotoxic mechanisms are not yet clarified, but the identification of proteins able to modulate TDP-43-mediated damage may be promising therapeutic targets for TDP-43 proteinopathies. Here we show by the use of refined yeast models that the nucleolar protein nucleolin (NCL) acts as a potent suppressor of TDP-43 toxicity, restoring cell viability. We provide evidence that NCL co-expression is able to alleviate TDP-43-induced damage also in human cells, further supporting its beneficial effects in a more consistent pathophysiological context. Presented data suggest that NCL could promote TDP-43 nuclear retention, reducing the formation of toxic cytosolic TDP-43 inclusions.

maTE: discovering expressed interactions between microRNAs and their targets

MOTIVATION

Disease is often manifested via changes in transcript and protein abundance. MicroRNAs (miRNAs) are instrumental in regulating protein abundance and may measurably influence transcript levels. miRNAs often target more than one mRNA (for humans, the average is three), and mRNAs are often targeted by more than one miRNA (for the genes considered in this study, the average is also three). Therefore, it is difficult to determine the miRNAs that may cause the observed differential gene expression. We present a novel approach, maTE, which is based on machine learning, that integrates information about miRNA target genes with gene expression data. maTE depends on the availability of a sufficient amount of patient and control samples. The samples are used to train classifiers to accurately classify the samples on a per miRNA basis. Multiple high scoring miRNAs are used to build a final classifier to improve separation.

RESULTS

The aim of the study is to find a set of miRNAs causing the regulation of their target genes that best explains the difference between groups (e.g. cancer versus control). maTE provides a list of significant groups of genes where each group is targeted by a specific miRNA. For the datasets used in this study, maTE generally achieves an accuracy well above 80%. Also, the results show that when the accuracy is much lower (e.g. ∼50%), the set of miRNAs provided is likely not causative of the difference in expression. This new approach of integrating miRNA regulation with expression data yields powerful results and is independent of external labels and training data. Thereby, this approach allows new avenues for exploring miRNA regulation and may enable the development of miRNA-based biomarkers and drugs.

AVAILABILITY AND IMPLEMENTATION

The KNIME workflow, implementing maTE, is available at Bioinformatics online.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Secretome Analysis of Hypoxia-Induced 3T3-L1 Adipocytes Uncovers Novel Proteins Potentially Involved in Obesity

In the obese state, as adipose tissue expands, adipocytes become hypoxic and dysfunctional, leading to changes in the pattern of adipocyte-secreted proteins. To better understand the role of hypoxia in the mechanisms linked to obesity, we comparatively analyzed the secretome of murine differentiated 3T3-L1 adipocytes exposed to normoxia or hypoxia for 24 h. Proteins secreted into the culture media were precipitated by trichloroacetic acid and then digested with trypsin. The peptides were labeled with dimethyl labeling and analyzed by reversed phase nanoscale liquid chromatography coupled to a quadrupole Orbitrap mass spectrometer. From a total of 1508 identified proteins, 109 were differentially regulated, of which 108 were genuinely secreted. Factors significantly downregulated in hypoxic conditions included adiponectin, a known adipokine implicated in metabolic processes, as well as thrombospondin-1 and -2, and matrix metalloproteinase-11, all multifunctional proteins involved in extracellular matrix (ECM) homeostasis. Findings were validated by Western blot analysis. Expression studies of the relative genes were performed in parallel experiments in vitro, in differentiated 3T3-L1 adipocytes, and in vivo, in fat tissues from obese versus lean mice. Our observations are compatible with the concept that hypoxia may be an early trigger for both adipose cell dysfunction and ECM remodeling.

PhDHS Is Involved in Chloroplast Development in Petunia

Deoxyhypusine synthase (DHS) is encoded by a nuclear gene and is the key enzyme involved in the post-translational activation of the eukaryotic translation initiation factor eIF5A. DHS plays important roles in plant growth and development. To gain a better understanding of DHS, the petunia (Petunia hybrida) PhDHS gene was isolated, and the role of PhDHS in plant growth was analyzed. PhDHS protein was localized to the nucleus and cytoplasm. Virus-mediated PhDHS silencing caused a sectored chlorotic leaf phenotype. Chlorophyll levels and photosystem II activity were reduced, and chloroplast development was abnormal in PhDHS-silenced leaves. In addition, PhDHS silencing resulted in extended leaf longevity and thick leaves. A proteome assay revealed that 308 proteins are upregulated and 266 proteins are downregulated in PhDHS-silenced plants compared with control, among the latter, 21 proteins of photosystem I and photosystem II and 12 thylakoid (thylakoid lumen and thylakoid membrane) proteins. In addition, the mRNA level of PheIF5A-1 significantly decreased in PhDHS-silenced plants, while that of another three PheIF5As were not significantly affected in PhDHS-silenced plants. Thus, silencing of PhDHS affects photosynthesis presumably as an indirect effect due to reduced expression of PheIF5A-1 in petunia. Significance: PhDHS-silenced plants develop yellow leaves and exhibit a reduced level of photosynthetic pigment in mesophyll cells. In addition, arrested development of chloroplasts is observed in the yellow leaves.

The identification of carbon dioxide mediated protein post-translational modifications

Carbon dioxide is vital to the chemistry of life processes including metabolism, cellular homoeostasis, and pathogenesis. CO₂ is generally unreactive but can combine with neutral amines to form carbamates on proteins under physiological conditions. The most widely known examples of this are CO₂ regulation of ribulose 1,5-bisphosphate carboxylase/oxygenase and haemoglobin. However, the systematic identification of CO₂-binding sites on proteins formed through carbamylation has not been possible due to the ready reversibility of carbamate formation. Here we demonstrate a methodology to identify protein carbamates using triethyloxonium tetrafluoroborate to covalently trap CO₂, allowing for downstream proteomic analysis. This report describes the systematic identification of carbamates in a physiologically relevant environment. We demonstrate the identification of carbamylated proteins and the general principle that CO₂ can impact protein biochemistry through carbamate formation. The ability to identify protein carbamates will significantly advance our understanding of cellular CO₂ interactions.

Carbon dioxide can interact with proteins to form carbamate post-translational modifications. Here, the authors developed a strategy to identify carbamate post-translational modifications by trapping carbon dioxide and subsequently identifying the carbamylated proteins.

The Sharpin interactome reveals a role for Sharpin in lamellipodium formation via the Arp2/3 complex

Sharpin, a multifunctional adaptor protein, regulates several signalling pathways. For example, Sharpin enhances signal-induced NF-κB signalling as part of the linear ubiquitin assembly complex (LUBAC) and inhibits integrins, the T cell receptor, caspase 1 and PTEN. However, despite recent insights into Sharpin and LUBAC function, a systematic approach to identify the signalling pathways regulated by Sharpin has not been reported. Here, we present the first 'Sharpin interactome', which identifies a large number of novel potential Sharpin interactors in addition to several known ones. These data suggest that Sharpin and LUBAC might regulate a larger number of biological processes than previously identified, such as endosomal trafficking, RNA processing, metabolism and cytoskeleton regulation. Importantly, using the Sharpin interactome, we have identified a novel role for Sharpin in lamellipodium formation. We demonstrate that Sharpin interacts with Arp2/3, a protein complex that catalyses actin filament branching. We have identified the Arp2/3-binding site in Sharpin and demonstrate using a specific Arp2/3-binding deficient mutant that the Sharpin-Arp2/3 interaction promotes lamellipodium formation in a LUBAC-independent fashion.This article has an associated First Person interview with the first author of the paper.

Temperature-dependent regulation of the Ochrobactrum anthropi proteome

Ochrobactrum anthropi is a Gram-negative rod belonging to the Brucellaceae family, able to colonize a variety of environments, and actually reported as a human opportunistic pathogen. Despite its low virulence, the bacterium causes a growing number of hospital-acquired infections mainly, but not exclusively, in immunocompromised patients. The aim of this study was to obtain an overview of the global proteome changes occurring in O. anthropi in response to different growth temperatures, in order to achieve a major understanding of the mechanisms by which the bacterium adapts to different habitats and to identify some potential virulence factors. Combined quantitative mass spectrometry-based proteomics and bioinformatics approaches were carried out on two O. anthropi strains grown at temperatures miming soil/plants habitat (25°C) and human host environment (37°C), respectively. Proteomic analysis led to the identification of over 150 differentially expressed proteins in both strains, out of over 1200 total protein identifications. Among them, proteins responsible for heat shock response (DnaK, GrpE), motility (FliC, FlgG, FlgE), and putative virulence factors (TolB) were identified. The study represents the first quantitative proteomic analysis of O. anthropi performed by high-resolution quantitative mass spectrometry.

Human aqueous humor proteome in cataract, glaucoma, and pseudoexfoliation syndrome

Twenty-nine human aqueous humor samples from patients with eye diseases such as cataract and glaucoma with and without pseudoexfoliation syndrome were characterized by LC-high resolution MS analysis. In total, 269 protein groups were identified with 1% false discovery rate including 32 groups that were not reported previously for this biological fluid. Since the samples were analyzed individually, but not pooled, 36 proteins were identified in all samples, comprising the constitutive proteome of the fluid. The most dominant molecular function of aqueous humor proteins as determined by GO analysis is endopeptidase inhibitor activity. Label-free protein quantification showed no significant difference between glaucoma and cataract aqueous humor proteomes. At the same time, we found decrease in the level of apolipoprotein D as a marker of the pseudoexfoliation syndrome. The data are available from ProteomeXchange repository (PXD002623).

Antibiotic-dependent perturbations of extended spectrum beta-lactamase producing Klebsiella pneumoniae proteome

Extended spectrum beta-lactamase producing Klebsiella pneumoniae (ESBL-KP) causes life-threatening infections in susceptible and immuno-compromised individuals. Because of the emergence of multidrug resistance and tolerance, it is crucial to better understand the mechanisms by which ESBL-KP can adapt to antibiotic stress. The aim of this study was to provide an overview of the global proteome changes occurring in ESBL-KP in response to sub-lethal concentrations of the antibiotics doxycycline (DC, bacteriostatic) and streptomycin (SM, bactericidal), which both impair ribosomal synthesis of bacterial proteins. These results represent the greatest experimental coverage of the ESBL-KP proteome yet described. The 1538 proteins, representing 30% of the 5126 predicted KP gene products were identified from the combined experimental groups. Antibiotic stress resulted in significantly elevated levels of 42 proteins for DC and 55 for SM treatments, whereas 53 proteins were reduced for DC- and six for SM-treated bacteria. Specifically, the ESBL-KP response to DC was accompanied by the reduced levels of the porins LamB, CirA, FepA, and OmpC. In contrast to DC, the stress response to SM demonstrated a dramatic increase in the peroxidase detoxification pathway proteins PutA, KatG, KatE, and Dps, which prevent harmful hydroxyl radical formation. The results from this proteomic study are important for understanding adaptive responses to antibiotics, and may provide novel targets for the development of new therapeutic strategies.

Proteomes and Ubiquitylomes Analysis Reveals the Involvement of Ubiquitination in Protein Degradation in Petunias

Petal senescence is a complex programmed process. It has been demonstrated previously that treatment with ethylene, a plant hormone involved in senescence, can extensively alter transcriptome and proteome profiles in plants. However, little is known regarding the impact of ethylene on posttranslational modification (PTM) or the association between PTM and the proteome. Protein degradation is one of the hallmarks of senescence, and ubiquitination, a major PTM in eukaryotes, plays important roles in protein degradation. In this study, we first obtained reference petunia (Petunia hybrida) transcriptome data via RNA sequencing. Next, we quantitatively investigated the petunia proteome and ubiquitylome and the association between them in petunia corollas following ethylene treatment. In total, 51,799 unigenes, 3,606 proteins, and 2,270 ubiquitination sites were quantified 16 h after ethylene treatment. Treatment with ethylene resulted in 14,448 down-regulated and 6,303 up-regulated unigenes (absolute log₂ fold change > 1 and false discovery rate < 0.001), 284 down-regulated and 233 up-regulated proteins, and 320 up-regulated and 127 down-regulated ubiquitination sites using a 1.5-fold threshold (P < 0.05), indicating that global ubiquitination levels increase during ethylene-mediated corolla senescence in petunia. Several putative ubiquitin ligases were up-regulated at the protein and transcription levels. Our results showed that the global proteome and ubiquitylome were negatively correlated and that ubiquitination could be involved in the degradation of proteins during ethylene-mediated corolla senescence in petunia. Ethylene regulates hormone signaling transduction pathways at both the protein and ubiquitination levels in petunia corollas. In addition, our results revealed that ethylene increases the ubiquitination levels of proteins involved in endoplasmic reticulum-associated degradation.

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/.

Integrating transcriptome and proteome profiling: Strategies and applications

Discovering the gene expression signature associated with a cellular state is one of the basic quests in majority of biological studies. For most of the clinical and cellular manifestations, these molecular differences may be exhibited across multiple layers of gene regulation like genomic variations, gene expression, protein translation and post-translational modifications. These system wide variations are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. This necessitates the integrative analysis of such multiple layers of information to understand the interplay of the individual components of the biological system. Recent developments in high throughput RNA sequencing and mass spectrometric (MS) technologies to probe transcripts and proteins made these as preferred methods for understanding global gene regulation. Subsequently, improvements in "big-data" analysis techniques enable novel conclusions to be drawn from integrative transcriptomic-proteomic analysis. The unified analyses of both these data types have been rewarding for several biological objectives like improving genome annotation, predicting RNA-protein quantities, deciphering gene regulations, discovering disease markers and drug targets. There are different ways in which transcriptomics and proteomics data can be integrated; each aiming for different research objectives. Here, we review various studies, approaches and computational tools targeted for integrative analysis of these two high-throughput omics methods.

Further development of biomarkers in amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is an idiopathic neurodegenerative disease usually fatal in less than three years. Even if standard guidelines are available to diagnose ALS, the mean diagnosis delay is more than one year. In this context, biomarker discovery is a priority. Research has to focus on new diagnostic tools, based on combined explorations.

AREAS COVERED

In this review, we specifically focus on biology and imaging markers. We detail the innovative field of 'omics' approach and imaging and explain their limits to be useful in routine practice. We describe the most relevant biomarkers and suggest some perspectives for biomarker research. Expert commentary: The successive failures of clinical trials in ALS underline the need for new strategy based on innovative tools to stratify patients and to evaluate their responses to treatment. Biomarker data may be useful to improve the designs of clinical trials. Biomarkers are also needed to better investigate disease pathophysiology, to identify new therapeutic targets, and to improve the performance of clinical assessments for diagnosis and prognosis in the clinical setting. A consensus on the best management of neuroimaging and 'omics' methods is necessary and a systematic independent validation of findings may add robustness to future studies.

Characterization of a SILAC method for proteomic analysis of primary rat microglia

Microglia play important and dynamic roles in mediating a variety of physiological and pathological processes during the development, normal function and degeneration of the central nervous system. Application of SILAC-based proteomic analysis would greatly facilitate the identification of cellular pathways regulating the multifaceted phenotypes of microglia. We and others have successfully SILAC-labeled immortalized murine microglial cell lines in previous studies. In this study, we report the development and evaluation of a SILAC-labeled primary rat microglia model. Although the isotope labeling scheme for primary microglia is drastically different from that of immortalized cell lines, our de novo and uninterrupted primary culture labeling protocol (DUP-SILAC) resulted in sufficient incorporation of SILAC labels for mass spectrometry-based proteomic profiling. In addition, label incorporation did not alter their morphology and response to endotoxin stimulation. Proteomic analysis of the endotoxin-stimulated SILAC-labeled primary microglia identified expected as well as potentially novel activation markers and pro-inflammatory pathways that could be quantified in a more physiologically relevant cellular model system compared to immortalized cell lines. The establishment of primary microglia SILAC model will further expand our capacity for global scale proteomic profiling of pathways under various physiological and pathological conditions. Proteomic MS data are available via ProteomeXchange with identifier PXD002759.

Comparing isogenic strains of Beijing genotype Mycobacterium tuberculosis after acquisition of Isoniazid resistance: A proteomics approach

We determined differences in the protein abundance among two isogenic strains of Mycobacterium tuberculosis (Mtb) with different Isoniazid (INH) susceptibility profiles. The strains were isolated from a pulmonary tuberculosis patient before and after drug treatment. LC‐MS/MS analysis identified 46 Mtb proteins with altered abundance after INH resistance acquisition. Protein abundance comparisons were done evaluating the different bacterial cellular fractions (membrane, cytosol, cell wall and secreted proteins). MS data have been deposited to the ProteomeXchange with identifier PXD002986.

Proteome and carbon flux analysis of Pseudomonas aeruginosa clinical isolates from different infection sites

Pseudomonas aeruginosa is known as opportunistic pathogen frequently isolated from different infection sites. To investigate the expression rates of P. aeruginosa proteins commonly expressed by different clinical isolates, absolute protein quantities were determined employing a gel-free and data-independent LC-IMS(E) approach. Moreover, the metabolic diversity of these isolates was investigated by (13) C-metabolic flux analyses. 812 proteins were reproducibly identified and absolutely quantified for the reference strain P. aeruginosa PAO1, 363 of which were also identified and relatively quantified in all isolates. Whilst the majority of these proteins were expressed in constant amounts, expression rates of 42 proteins were highly variable between the isolates. Notably, the outer membrane protein OprH and the response regulator PhoP were strongly expressed in burned wounds isolates compared to lung/urinary tract isolates. Moreover, proteins involved in iron/amino acids uptake were found to be highly abundant in urinary tract isolates. The fluxome data revealed a conserved glycolysis, and a niche-specific divergence in fluxes through the glyoxylate shunt and the TCA cycle among the isolates. The integrated proteome/fluxome analysis did not indicate straightforward correlation between the protein amount and flux, but rather points to additional layers of regulation that mediate metabolic adaption of P. aeruginosa to different host environments. All MS data have been deposited in the ProteomeXchange with identifier PXD002373 (http://proteomecentral.proteomexchange.org/dataset/PXD002373).

Quantitative proteomics suggests metabolic reprogramming during ETHE1 deficiency

Deficiency of mitochondrial sulfur dioxygenase (ETHE1) causes the severe metabolic disorder ethylmalonic encephalopathy, which is characterized by early-onset encephalopathy and defective cytochrome C oxidase because of hydrogen sulfide accumulation. Although the severe systemic consequences of the disorder are becoming clear, the molecular effects are not well defined. Therefore, for further elucidating the effects of ETHE1-deficiency, we performed a large scale quantitative proteomics study on liver tissue from ETHE1-deficient mice. Our results demonstrated a clear link between ETHE1-deficiency and redox active proteins, as reflected by downregulation of several proteins related to oxidation-reduction, such as different dehydrogenases and cytochrome P450 (CYP450) members. Furthermore, the protein data indicated impact of the ETHE1-deficiency on metabolic reprogramming through upregulation of glycolytic enzymes and by altering several heterogeneous ribonucleoproteins, indicating novel link between ETHE1 and gene expression regulation. We also found increase in total protein acetylation level, pointing out the link between ETHE1 and acetylation, which is likely controlled by both redox state and cellular metabolites. These findings are relevant for understanding the complexity of the disease and may shed light on important functions influenced by ETHE1 deficiency and by the concomitant increase in the gaseous mediator hydrogen sulfide. All MS data have been deposited in the ProteomeXchange with the dataset identifiers PXD002741 (http://proteomecentral.proteomexchange.org/dataset/PXD002741) and PXD002742 (http://proteomecentral.proteomexchange.org/dataset/PXD002741).

2016 update of the PRIDE database and its related tools

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development 'PRIDE Cluster' and 'PRIDE Proteomes', which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive.

Bioinformatics Analysis of Proteome Changes in Calu-3 Cell Infected by Influenza A Virus (H5N1)

<b><i>Aim:</i></b> This paper aimed to identify the differentially expressed proteins (DEPs) in Calu-3 cells infected by influenza A virus (IAV) subtype H5N1. <b><i>Methods:</i></b> We downloaded proteome data (BTO: 0000762) from the Proteomics Identifications database and identified the DEPs in the IAV-infected Calu-3 cells. Then we constructed a protein-protein interaction network and a transcriptional regulatory network of the proteins. Finally, we performed gene ontology (GO) analysis to study the IAV infection at a functional level. <b><i>Results:</i></b> A total of 4 protein groups between the normal cells and the Calu-3 cells infected by IAV, severe acute respiratory syndrome or swine influenza were identified. In the networks, we found 5 significant proteins including FAN, CPSF2, AGO1, AGO2 and PAX5. In addition, we demonstrated those proteins were associated with GO terms such as phosphate metabolic process, calcium ion transport, cell division and regulation of cell motion. STAT1, NS2, CD5, NCKX6 and PDGFB were significant DEPs in these GO terms. <b><i>Conclusions:</i></b> By referring to the previous studies, we suggest that proteins including FAN, CPSF2, AGO1, AGO2, PAX5, STAT1 and PDGFB can be used as therapeutic targets of IAV infection.

Data in support of peptidomic analysis of spermatozoa during epididymal maturation

The final differentiation of the male germ cell occurs in the epididymal duct where the spermatozoa develop the ability to be motile and fertilize an ovum. Understanding of these biological processes is the key to understanding and controlling male fertility. Comparative studies between several epididymal maturation states could be an informative approach to finding sperm modifications related to maturation and fertility. Here we show the data from differential peptidomic/proteomic analyses on spermatozoa isolated from 4 epididymal regions (immature to mature stage) using a profiling approach based on MALDI-TOF mass spectrometry and, combined to top-down MS in order to identify peptidoforms and proteoforms. By this way, 172m/z peaks ranging between 2 and 20 kDa were found to be modified during maturation of sperm. A total of 62m/z were identified corresponding to 32 different molecular species. The interpretation of these data can be found in the research article published by Labas and colleagues in the Journal of Proteomics in 2014 [1].

Honey Bee Infecting Lake Sinai Viruses

Honey bees are critical pollinators of important agricultural crops. Recently, high annual losses of honey bee colonies have prompted further investigation of honey bee infecting viruses. To better characterize the recently discovered and very prevalent Lake Sinai virus (LSV) group, we sequenced currently circulating LSVs, performed phylogenetic analysis, and obtained images of LSV2. Sequence analysis resulted in extension of the LSV1 and LSV2 genomes, the first detection of LSV4 in the US, and the discovery of LSV6 and LSV7. We detected LSV1 and LSV2 in the Varroa destructor mite, and determined that a large proportion of LSV2 is found in the honey bee gut, suggesting that vector-mediated, food-associated, and/or fecal-oral routes may be important for LSV dissemination. Pathogen-specific quantitative PCR data, obtained from samples collected during a small-scale monitoring project, revealed that LSV2, LSV1, Black queen cell virus (BQCV), and Nosema ceranae were more abundant in weak colonies than strong colonies within this sample cohort. Together, these results enhance our current understanding of LSVs and illustrate the importance of future studies aimed at investigating the role of LSVs and other pathogens on honey bee health at both the individual and colony levels.

Identification of new phosphorylation sites of AMPA receptors in the rat hippocampus--A resource for neuroscience research

PURPOSE

AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors (AMPARs) are glutamate-gated ion channels that mediate the majority of fast excitatory synaptic transmissions in the mammalian brain. A series of phosphorylation sites have been predicted or identified and knowledge on phosphorylations is mandatory for understanding receptor biology and functions.

EXPERIMENTAL DESIGN

Immunoprecipitation from extracted hippocampal rat proteins was carried out using an antibody against the AMPAR GluA1 subunit, followed by identification of GluA1 and binding partners by MS. Bands from SDS-PAGE were picked, peptides were generated by trypsin and chymotrypsin digestion and identified by MS/MS (LTQ Orbitrap Velos).

RESULTS

Using Mascot as a search engine, phosphorylation sites S506, S645, S720, S849, S863, S895, T858, Y228, Y419, and T734 were found on GluA1; S357, S513, S656, S727, T243, T420, T741, Y 143, Y301,Y426 on GluA2; S301, S516, S657, S732, T222, and T746 were observed on GluA3; and S514, S653 was phosphorylated on GluA4.

CONCLUSIONS AND CLINICAL RELEVANCE

A series of additional protein modifications were observed and in particular, tyrosine and tryptophan nitrations on GluA1 were detected that may raise questions on additional regulation mechanisms for AMPARs in addition to phosphorylations. The findings are relevant for interpretation of previous work and design of future studies using AMPAR serving as a resource for neuroscience research and indeed, phosphorylations and PTMs per se would have to be respected when neuropathological and neurological disorders are being studied.

Role of the Tau N-terminal region in microtubule stabilization revealed by new endogenous truncated forms

Tau is a central player in Alzheimer's disease (AD) and related Tauopathies, where it is found as aggregates in degenerating neurons. Abnormal post-translational modifications, such as truncation, are likely involved in the pathological process. A major step forward in understanding the role of Tau truncation would be to identify the precise cleavage sites of the several truncated Tau fragments that are observed until now in AD brains, especially those truncated at the N-terminus, which are less characterized than those truncated at the C-terminus. Here, we optimized a proteomics approach and succeeded in identifying a number of new N-terminally truncated Tau species from the human brain. We initiated cell-based functional studies by analyzing the biochemical characteristics of two N-terminally truncated Tau species starting at residues Met11 and Gln124 respectively. Our results show, interestingly, that the Gln124-Tau fragment displays a stronger ability to bind and stabilize microtubules, suggesting that the Tau N-terminal domain could play a direct role in the regulation of microtubule stabilization. Future studies based on our new N-terminally truncated-Tau species should improve our knowledge of the role of truncation in Tau biology as well as in the AD pathological process.

Validation of a novel shotgun proteomic workflow for the discovery of protein-protein interactions: focus on ZNF521

The study of protein-protein interactions is increasingly relying on mass spectrometry (MS). The classical approach of separating immunoprecipitated proteins by SDS-PAGE followed by in-gel digestion is long and labor-intensive. Besides, it is difficult to integrate it with most quantitative MS-based workflows, except for stable isotopic labeling of amino acids in cell culture (SILAC). This work describes a fast, flexible and quantitative workflow for the discovery of novel protein-protein interactions. A cleavable cross-linker, dithiobis[succinimidyl propionate] (DSP), is utilized to stabilize protein complexes before immunoprecipitation. Protein complex detachment from the antibody is achieved by limited proteolysis. Finally, protein quantitation is performed via (18)O labeling. The workflow has been optimized concerning (i) DSP concentration and (ii) incubation times for limited proteolysis, using the stem cell-associated transcription cofactor ZNF521 as a model target. The interaction of ZNF521 with the core components of the nuclear remodelling and histone deacetylase (NuRD) complex, already reported in the literature, was confirmed. Additionally, interactions with newly discovered molecular partners of potentially relevant functional role, such as ZNF423, Spt16, Spt5, were discovered and validated by Western blotting.

Recent advances in proteomics: towards the human proteome

After the successful completion of the Human Genome project in 2003, the next major challenge was to understand when and where the encoded proteins were expressed, and to generate a map of the complex, interconnected pathways, networks and molecular systems (the human proteome) that, taken together, control the workings of all cells, tissues, organs and organisms. Proteomics will be fundamental for such studies. This review summarizes the key discoveries that laid down the foundations for proteomics as we now know it, and describes key recent technological advances that will undoubtedly contribute to achieving the initial goal of the Human Proteome Organization of identifying and characterizing at least one protein product and representative post-translational modifications, single amino acid polymorphisms and splice variant isoforms from the 20,300 human protein-coding genes within the next 10 years. Successful unraveling of the human proteome will undoubtedly improve our understanding of human biology at the cellular level and lay the foundations for improved diagnostic, prognostic, therapeutic and preventive medical outcomes as we enter the era of personalized medicine.

A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry

Background

Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field. However, recent most advanced types of LC-MS generate huge amounts of analytical data with high scan speed, high accuracy and resolution, which is often impossible to interpret manually. Moreover, there are still issues to be improved for recent label-free methods, such as how to reduce false positive/negatives of the candidate peaks, how to expand scalability and how to enhance and automate data processing. AB3D (A simple label-free quantitation algorithm for Biomarker Discovery in Diagnostics and Drug discovery using LC-MS) has addressed these issues and has the capability to perform label-free quantitation using MS1 for proteomics study.

Results

We developed an algorithm called AB3D, a label free peak detection and quantitative algorithm using MS1 spectral data. To test our algorithm, practical applications of AB3D for LC-MS data sets were evaluated using 3 datasets. Comparisons were then carried out between widely used software tools such as MZmine 2, MSight, SuperHirn, OpenMS and our algorithm AB3D, using the same LC-MS datasets. All quantitative results were confirmed manually, and we found that AB3D could properly identify and quantify known peptides with fewer false positives and false negatives compared to four other existing software tools using either the standard peptide mixture or the real complex biological samples of Bartonella quintana (strain JK31). Moreover, AB3D showed the best reliability by comparing the variability between two technical replicates using a complex peptide mixture of HeLa and BSA samples. For performance, the AB3D algorithm is about 1.2 - 15 times faster than the four other existing software tools.

Conclusions

AB3D is a simple and fast algorithm for label-free quantitation using MS1 mass spectrometry data for large scale LC-MS data analysis with higher true positive and reasonable false positive rates. Furthermore, AB3D demonstrated the best reproducibility and is about 1.2- 15 times faster than those of existing 4 software tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0376-0) contains supplementary material, which is available to authorized users.

A standardized framing for reporting protein identifications in mzIdentML 1.2

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software.

Data for chicken semen proteome and label free quantitative analyses displaying sperm quality biomarkers

Understanding of biology of the avian male gamete is essential to improve the conservation of genetic resources and performances in farming. In this study, the semen proteome of the main domestic avian species (Gallus gallus) and evaluation of the molecular phenotype related to sperm quality were investigated using GeLC–MS/MS approach and label-free quantitative proteomic based on Spectral Counting (SC) and extracted ion chromatograms (XIC) methods. Here we describe in details the peptide/protein inventory of chicken ejaculated spermatozoa (SPZ) and seminal plasma (SP). We also show differential analyses of chicken semen (SPZ and corresponding SP) from 11 males demonstrating different levels of fertilizing capacity and sperm motility. The interpretation and description of these data can be found in a research article published by Labas and colleagues in the Journal of Proteomics in 2014 [1]. This is a new resource for exploring the molecular mechanisms involved in fertilizing capacity and to reveal new sets of fertility biomarkers.

An integrative omics strategy to assess the germ cell secretome and to decipher sertoli-germ cell crosstalk in the Mammalian testis

Mammalian spermatogenesis, which takes place in complex testicular structures called seminiferous tubules, is a highly specialized process controlled by the integration of juxtacrine, paracrine and endocrine information. Within the seminiferous tubules, the germ cells and Sertoli cells are surrounded by testicular fluid (TF), which probably contains most of the secreted proteins involved in crosstalk between these cells. It has already been established that germ cells can modulate somatic Sertoli cell function through the secretion of diffusible factors. We studied the germ cell secretome, which was previously considered inaccessible, by analyzing the TF collected by microsurgery in an “integrative omics” strategy combining proteomics, transcriptomics, genomics and interactomics data. This approach identified a set of proteins preferentially secreted by Sertoli cells or germ cells. An interaction network analysis revealed complex, interlaced cell-cell dialog between the secretome and membranome of seminiferous cells, mediated via the TF. We then focused on germ cell-secreted candidate proteins, and we identified several potential interacting partners located on the surface of Sertoli cells. Two interactions, APOH/CDC42 and APP/NGFR, were validated in situ, in a proximity ligation assay (PLA). Our results provide new insight into the crosstalk between germ cells and Sertoli cells occurring during spermatogenesis. Our findings also demonstrate that this “integrative omics” strategy is powerful enough for data mining and highlighting meaningful cell-cell communication events between different types of cells in a complex tissue, via a biological fluid. This integrative strategy could be applied more widely, to gain access to secretomes that have proved difficult to study whilst avoiding the limitations of in vitro culture.

Qualitative and quantitative peptidomic and proteomic approaches to phenotyping chicken semen

Understanding of the avian male gamete biology is essential to improve the conservation of genetic resources and performance in farming. In this study, the chicken semen peptidome/proteome and the molecular phenotype related to sperm quality were investigated. Spermatozoa (SPZ) and corresponding seminal plasma (SP) from 11 males with different fertilizing capacity were analyzed using three quantitative strategies (fluid and intact cells MALDI-MS, SDS-PAGE combined to LC-MS/MS with spectral counting and XIC methods). Individual MALDI profiling in combination with top-down MS allowed to characterize specific profiles per male and to identify 16 biomolecules (e.g.VMO1, AvBD10 and AvBD9 including polymorphism). Qualitative analysis identified 1165 proteins mainly involved in oxidoreduction mechanisms, energy processes, proteolysis and protein localization. Comparative analyses between the most and the least fertile males were performed. The enzymes involved in energy metabolism, respiratory chain or oxido-reduction activity were over-represented in SPZ of the most fertile males. The SP of the most and the least fertile males differed also on many proteins (e.g. ACE, AvBD10 and AvBD9, NEL precursor, acrosin). Thus proteomic is a "phenomic molecular tool" that may help to discriminate avian males on their reproductive capacity. The data have been deposited with ProteomeXchange (identifiers PXD000287 and PXD001254).

BIOLOGICAL SIGNIFICANCE

This peptidomic and proteomic study i) characterized for the first time the semen protein composition of the main domestic avian species (Gallus gallus) by analysis of ejaculated spermatozoa and corresponding seminal plasma; ii) established a characteristic molecular phenotype distinguishing semen and males at an individual level; and iii) proposedthe first evidence of biomarkers related to fertility.

Phosphoproteomic Analyses Reveal Early Signaling Events in the Osmotic Stress Response

Elucidating how plants sense and respond to water loss is important for identifying genetic and chemical interventions that may help sustain crop yields in water-limiting environments. Currently, the molecular mechanisms involved in the initial perception and response to dehydration are not well understood. Modern mass spectrometric methods for quantifying changes in the phosphoproteome provide an opportunity to identify key phosphorylation events involved in this process. Here, we have used both untargeted and targeted isotope-assisted mass spectrometric methods of phosphopeptide quantitation to characterize proteins in Arabidopsis (Arabidopsis thaliana) whose degree of phosphorylation is rapidly altered by hyperosmotic treatment. Thus, protein phosphorylation events responsive to 5 min of 0.3 m mannitol treatment were first identified using ¹⁵N metabolic labeling and untargeted mass spectrometry with a high-resolution ion-trap instrument. The results from these discovery experiments were then validated using targeted Selected Reaction Monitoring mass spectrometry with a triple quadrupole. Targeted Selected Reaction Monitoring experiments were conducted with plants treated under nine different environmental perturbations to determine whether the phosphorylation changes were specific for osmosignaling or involved cross talk with other signaling pathways. The results indicate that regulatory proteins such as members of the mitogen-activated protein kinase family are specifically phosphorylated in response to osmotic stress. Proteins involved in 5' messenger RNA decapping and phosphatidylinositol 3,5-bisphosphate synthesis were also identified as targets of dehydration-induced phosphoregulation. The results of these experiments demonstrate the utility of targeted phosphoproteomic analysis in understanding protein regulation networks and provide new insight into cellular processes involved in the osmotic stress response.

Confident and sensitive phosphoproteomics using combinations of collision induced dissociation and electron transfer dissociation

We present a workflow using an ETD-optimised version of Mascot Percolator and a modified version of SLoMo (turbo-SLoMo) for analysis of phosphoproteomic data. We have benchmarked this against several database searching algorithms and phosphorylation site localisation tools and show that it offers highly sensitive and confident phosphopeptide identification and site assignment with PSM-level statistics, enabling rigorous comparison of data acquisition methods. We analysed the Plasmodium falciparum schizont phosphoproteome using for the first time, a data-dependent neutral loss-triggered-ETD (DDNL) strategy and a conventional decision-tree method. At a posterior error probability threshold of 0.01, similar numbers of PSMs were identified using both methods with a 73% overlap in phosphopeptide identifications. The false discovery rate associated with spectral pairs where DDNL CID/ETD identified the same phosphopeptide was < 1%. 72% of phosphorylation site assignments using turbo-SLoMo without any score filtering, were identical and 99.8% of these cases are associated with a false localisation rate of < 5%. We show that DDNL acquisition is a useful approach for phosphoproteomics and results in an increased confidence in phosphopeptide identification without compromising sensitivity or duty cycle. Furthermore, the combination of Mascot Percolator and turbo-SLoMo represents a robust workflow for phosphoproteomic data analysis using CID and ETD fragmentation.

Biological significance

Protein phosphorylation is a ubiquitous post-translational modification that regulates protein function. Mass spectrometry-based approaches have revolutionised its analysis on a large-scale but phosphorylation sites are often identified by single phosphopeptides and therefore require more rigorous data analysis to unsure that sites are identified with high confidence for follow-up experiments to investigate their biological significance. The coverage and confidence of phosphoproteomic experiments can be enhanced by the use of multiple complementary fragmentation methods. Here we have benchmarked a data analysis pipeline for analysis of phosphoproteomic data generated using CID and ETD fragmentation and used it to demonstrate the utility of a data-dependent neutral loss triggered ETD fragmentation strategy for high confidence phosphopeptide identification and phosphorylation site localisation.

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We report and benchmark a data analysis pipeline for phosphoproteomic data analysis.

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Combined use of Mascot Percolator and turbo-SLoMo to compare fragmentation methods

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CID and ETD fragmentation for phosphorylation site identification

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Demonstrate the utility of data-dependent neutral loss triggered ETD fragmentation

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High confidence of phosphoproteomic analysis using ETD/CID spectral pairs

Proteomic profiling of the mitochondrial inner membrane of rat renal proximal convoluted tubules

The proximal convoluted tubule is the primary site of renal fluid, electrolyte, and nutrient reabsorption, processes that consume large amounts of adenosine-5'-triphosphate. Previous proteomic studies have profiled the adaptions that occur in this segment of the nephron in response to the onset of metabolic acidosis. To extend this analysis, a proteomic workflow was developed to characterize the proteome of the mitochondrial inner membrane of the rat renal proximal convoluted tubule. Separation by LC coupled with analysis by MS/MS (LC-MS/MS) confidently identified 206 proteins in the combined samples. Further proteomic analysis identified 14 peptides that contain an N-ɛ-acetyl-lysine, seven of which are novel sites. This study provides the first proteomic profile of the mitochondrial inner membrane proteome of this segment of the rat renal nephron. The MS data have been deposited in the ProteomeXchange with the identifier PXD000121.

Controlled vocabularies and ontologies in proteomics: overview, principles and practice

This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the "mapping files" used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

IQGAP1 is a key node within the small GTPase network

Coordination of the activity of multiple small GTPases is required for the regulation of many physiological processes, including cell migration. There are now several examples of functional interplay between small GTPase pairs, but the mechanisms that control GTPase activity in time and space are only partially understood. Here, we build on the hypothesis that small GTPases are part of a large, integrated network and propose that key proteins within this network integrate multiple signaling events and coordinate multiple small GTPase activities. Specifically, we identify the scaffolding protein IQGAP1 as a master regulator of multiple small GTPases, including Cdc42, Rac1, Rap1, and RhoA. In addition, we demonstrate that IQGAP1 promotes Arf6 activation downstream of β1 integrin engagement. Furthermore, following literature-curated searches and recent mass spectrometric analysis of IQGAP1-binding partners, we report that IQGAP1 recruits other small GTPases, including RhoC, Rac2, M-Ras, RhoQ, Rab10, and Rab5, small GTPase regulators, including Tiam1, RacGAP1, srGAP2 and HERC1, and small GTPase effectors, including PAK6, N-WASP, several sub-units of the Arp2/3 complex and the formin mDia1. Therefore, we propose that IQGAP1 acts as a small GTPase scaffolding platform within the small GTPase network, and recruits and/or regulates small GTPases, small GTPase regulators and effectors to orchestrate cell behavior. Finally, to identify other putative key regulators of small GTPase crosstalk, we have assembled a small GTPase network using protein-protein interaction databases.

Proteogenomic analysis of Bradyrhizobium japonicum USDA110 using GenoSuite, an automated multi-algorithmic pipeline

We present GenoSuite, an integrated proteogenomic pipeline to validate, refine and discover protein coding genes using high-throughput mass spectrometry (MS) data from prokaryotes. To demonstrate the effectiveness of GenoSuite, we analyzed proteomics data of Bradyrhizobium japonicum (USDA110), a model organism to study agriculturally important rhizobium-legume symbiosis. Our analysis confirmed 31% of known genes, refined 49 gene models for their translation initiation site (TIS) and discovered 59 novel protein coding genes. Notably, a novel protein which redefined the boundary of a crucial cytochrome P450 system related operon was discovered, known to be highly expressed in the anaerobic symbiotic bacteroids. A focused analysis on N-terminally acetylated peptides indicated downstream TIS for gene blr0594. Finally, ortho-proteogenomic analysis revealed three novel genes in recently sequenced B. japonicum USDA6(T) genome. The discovery of large number of missing genes and correction of gene models have expanded the proteomic landscape of B. japonicum and presents an unparalleled utility of proteogenomic analyses and versatility of GenoSuite for annotating prokaryotic genomes including pathogens.

Functional transcriptomics in the post-ENCODE era

The last decade has seen tremendous effort committed to the annotation of the human genome sequence, most notably perhaps in the form of the ENCODE project. One of the major findings of ENCODE, and other genome analysis projects, is that the human transcriptome is far larger and more complex than previously thought. This complexity manifests, for example, as alternative splicing within protein-coding genes, as well as in the discovery of thousands of long noncoding RNAs. It is also possible that significant numbers of human transcripts have not yet been described by annotation projects, while existing transcript models are frequently incomplete. The question as to what proportion of this complexity is truly functional remains open, however, and this ambiguity presents a serious challenge to genome scientists. In this article, we will discuss the current state of human transcriptome annotation, drawing on our experience gained in generating the GENCODE gene annotation set. We highlight the gaps in our knowledge of transcript functionality that remain, and consider the potential computational and experimental strategies that can be used to help close them. We propose that an understanding of the true overlap between transcriptional complexity and functionality will not be gained in the short term. However, significant steps toward obtaining this knowledge can now be taken by using an integrated strategy, combining all of the experimental resources at our disposal.

Integrated omics study delineates the dynamics of lipid droplets in Rhodococcus opacus PD630

Rhodococcus opacus strain PD630 (R. opacus PD630), is an oleaginous bacterium, and also is one of few prokaryotic organisms that contain lipid droplets (LDs). LD is an important organelle for lipid storage but also intercellular communication regarding energy metabolism, and yet is a poorly understood cellular organelle. To understand the dynamics of LD using a simple model organism, we conducted a series of comprehensive omics studies of R. opacus PD630 including complete genome, transcriptome and proteome analysis. The genome of R. opacus PD630 encodes 8947 genes that are significantly enriched in the lipid transport, synthesis and metabolic, indicating a super ability of carbon source biosynthesis and catabolism. The comparative transcriptome analysis from three culture conditions revealed the landscape of gene-altered expressions responsible for lipid accumulation. The LD proteomes further identified the proteins that mediate lipid synthesis, storage and other biological functions. Integrating these three omics uncovered 177 proteins that may be involved in lipid metabolism and LD dynamics. A LD structure-like protein LPD06283 was further verified to affect the LD morphology. Our omics studies provide not only a first integrated omics study of prokaryotic LD organelle, but also a systematic platform for facilitating further prokaryotic LD research and biofuel development.