Proteome-pI 2.0: proteome isoelectric point database update

Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.

The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms

The Human Proteoform Atlas (HPfA) is a web-based repository of experimentally verified human proteoforms on-line at http://human-proteoform-atlas.org and is a direct descendant of the Consortium of Top-Down Proteomics' (CTDP) Proteoform Atlas. Proteoforms are the specific forms of protein molecules expressed by our cells and include the unique combination of post-translational modifications (PTMs), alternative splicing and other sources of variation deriving from a specific gene. The HPfA uses a FAIR system to assign persistent identifiers to proteoforms which allows for redundancy calling and tracking from prior and future studies in the growing community of proteoform biology and measurement. The HPfA is organized around open ontologies and enables flexible classification of proteoforms. To achieve this, a public registry of experimentally verified proteoforms was also created. Submission of new proteoforms can be processed through email vianrtdphelp@northwestern.edu, and future iterations of these proteoform atlases will help to organize and assign function to proteoforms, their PTMs and their complexes in the years ahead.

Multiplexed single-cell proteomics using SCoPE2

Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying >1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Here we describe the Single Cell ProtEomics (SCoPE2) protocol, which uses an isobaric carrier to enhance peptide sequence identification. Single cells are isolated by FACS or CellenONE into multiwell plates and lysed by Minimal ProteOmic sample Preparation (mPOP), and their peptides labeled by isobaric mass tags (TMT or TMTpro) for multiplexed analysis. SCoPE2 affords a cost-effective single-cell protein quantification that can be fully automated using widely available equipment and scaled to thousands of single cells. SCoPE2 uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. The SCoPE2 workflow allows analyzing ~200 single cells per 24 h using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis.

Dependence of Graphene Oxide (GO) Toxicity on Oxidation Level, Elemental Composition, and Size

The mass production of graphene oxide (GO) unavoidably elevates the chance of human exposure, as well as the possibility of release into the environment with high stability, raising public concern as to its potential toxicological risks and the implications for humans and ecosystems. Therefore, a thorough assessment of GO toxicity, including its potential reliance on key physicochemical factors, which is lacking in the literature, is of high significance and importance. In this study, GO toxicity, and its dependence on oxidation level, elemental composition, and size, were comprehensively assessed. A newly established quantitative toxicogenomic-based toxicity testing approach, combined with conventional phenotypic bioassays, were employed. The toxicogenomic assay utilized a GFP-fused yeast reporter library covering key cellular toxicity pathways. The results reveal that, indeed, the elemental composition and size do exert impacts on GO toxicity, while the oxidation level exhibits no significant effects. The UV-treated GO, with significantly higher carbon-carbon groups and carboxyl groups, showed a higher toxicity level, especially in the protein and chemical stress categories. With the decrease in size, the toxicity level of the sonicated GOs tended to increase. It is proposed that the covering and subsequent internalization of GO sheets might be the main mode of action in yeast cells.

Proteome Analysis and In Vitro Antiviral, Anticancer and Antioxidant Capacities of the Aqueous Extracts of Lentinula edodes and Pleurotus ostreatus Edible Mushrooms

In this study, we examined aqueous extracts of the edible mushrooms Pleurotus ostreatus (oyster mushroom) and Lentinula edodes (shiitake mushroom). Proteome analysis was conducted using LC-Triple TOF-MS and showed the expression of 753 proteins by Pleurotus ostreatus, and 432 proteins by Lentinula edodes. Bioactive peptides: Rab GDP dissociation inhibitor, superoxide dismutase, thioredoxin reductase, serine proteinase and lectin, were identified in both mushrooms. The extracts also included promising bioactive compounds including phenolics, flavonoids, vitamins and amino acids. The extracts showed promising antiviral activities, with a selectivity index (SI) of 4.5 for Pleurotus ostreatus against adenovirus (Ad7), and a slight activity for Lentinula edodes against herpes simplex-II (HSV-2). The extracts were not cytotoxic to normal human peripheral blood mononuclear cells (PBMCs). On the contrary, they showed moderate cytotoxicity against various cancer cell lines. Additionally, antioxidant activity was assessed using DPPH radical scavenging, ABTS radical cation scavenging and ORAC assays. The two extracts showed potential antioxidant activities, with the maximum activity seen for Pleurotus ostreatus (IC50 µg/mL) = 39.46 ± 1.27 for DPPH; 11.22 ± 1.81 for ABTS; and 21.40 ± 2.20 for ORAC assays. This study encourages the use of these mushrooms in medicine in the light of their low cytotoxicity on normal PBMCs vis à vis their antiviral, antitumor and antioxidant capabilities.

Age-dependent shift in the de novo proteome accompanies pathogenesis in an Alzheimer's disease mouse model

Alzheimer's disease (AD) is an age-related neurodegenerative disorder associated with memory loss, but the AD-associated neuropathological changes begin years before memory impairments. Investigation of the early molecular abnormalities in AD might offer innovative opportunities to target memory impairment prior to onset. Decreased protein synthesis plays a fundamental role in AD, yet the consequences of this dysregulation for cellular function remain unknown. We hypothesize that alterations in the de novo proteome drive early metabolic alterations in the hippocampus that persist throughout AD progression. Using a combinatorial amino acid tagging approach to selectively label and enrich newly synthesized proteins, we found that the de novo proteome is disturbed in young APP/PS1 mice prior to symptom onset, affecting the synthesis of multiple components of the synaptic, lysosomal, and mitochondrial pathways. Furthermore, the synthesis of large clusters of ribosomal subunits were affected throughout development. Our data suggest that large-scale changes in protein synthesis could underlie cellular dysfunction in AD.

Characterization of Extracellular Vesicle Cargo in Sjögren's Syndrome through a SWATH-MS Proteomics Approach

Primary Sjögren’s syndrome (pSS) is a complex heterogeneous disease characterized by a wide spectrum of glandular and extra-glandular manifestations. In this pilot study, a SWATH-MS approach was used to monitor extracellular vesicles-enriched saliva (EVs) sub-proteome in pSS patients, to compare it with whole saliva (WS) proteome, and assess differential expressed proteins between pSS and healthy control EVs samples. Comparison between EVs and WS led to the characterization of compartment-specific proteins with a moderate degree of overlap. A total of 290 proteins were identified and quantified in EVs from healthy and pSS patients. Among those, 121 proteins were found to be differentially expressed in pSS, 82% were found to be upregulated, and 18% downregulated in pSS samples. The most representative functional pathways associated to the protein networks were related to immune-innate response, including several members of S100 protein family, annexin A2, resistin, serpin peptidase inhibitors, azurocidin, and CD14 monocyte differentiation antigen. Our results highlight the usefulness of EVs for the discovery of novel salivary-omic biomarkers and open novel perspectives in pSS for the identification of proteins of clinical relevance that could be used not only for the disease diagnosis but also to improve patients’ stratification and treatment-monitoring. Data are available via ProteomeXchange with identifier PXD025649.

IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell

Intrinsic disorder can be found in all proteomes of all kingdoms of life and in viruses, being particularly prevalent in the eukaryotes. We conduct a comprehensive analysis of the intrinsic disorder in the human proteins while mapping them into 24 compartments of the human cell. In agreement with previous studies, we show that human proteins are significantly enriched in disorder relative to a generic protein set that represents the protein universe. In fact, the fraction of proteins with long disordered regions and the average protein-level disorder content in the human proteome are about 3 times higher than in the protein universe. Furthermore, levels of intrinsic disorder in the majority of human subcellular compartments significantly exceed the average disorder content in the protein universe. Relative to the overall amount of disorder in the human proteome, proteins localized in the nucleus and cytoskeleton have significantly increased amounts of disorder, measured by both high disorder content and presence of multiple long intrinsically disordered regions. We empirically demonstrate that, on average, human proteins are assigned to 2.3 subcellular compartments, with proteins localized to few subcellular compartments being more disordered than the proteins that are localized to many compartments. Functionally, the disordered proteins localized in the most disorder-enriched subcellular compartments are primarily responsible for interactions with nucleic acids and protein partners. This is the first-time disorder is comprehensively mapped into the human cell. Our observations add a missing piece to the puzzle of functional disorder and its organization inside the cell.

Pfam: The protein families database in 2021

The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to existing entries. To facilitate research on COVID-19, we have revised the Pfam entries that cover the SARS-CoV-2 proteome, and built new entries for regions that were not covered by Pfam. We have reintroduced Pfam-B which provides an automatically generated supplement to Pfam and contains 136 730 novel clusters of sequences that are not yet matched by a Pfam family. The new Pfam-B is based on a clustering by the MMseqs2 software. We have compared all of the regions in the RepeatsDB to those in Pfam and have started to use the results to build and refine Pfam repeat families. Pfam is freely available for browsing and download at http://pfam.xfam.org/.

LectomeXplore, an update of UniLectin for the discovery of carbohydrate-binding proteins based on a new lectin classification

Lectins are non-covalent glycan-binding proteins mediating cellular interactions but their annotation in newly sequenced organisms is lacking. The limited size of functional domains and the low level of sequence similarity challenge usual bioinformatics tools. The identification of lectin domains in proteomes requires the manual curation of sequence alignments based on structural folds. A new lectin classification is proposed. It is built on three levels: (i) 35 lectin domain folds, (ii) 109 classes of lectins sharing at least 20% sequence similarity and (iii) 350 families of lectins sharing at least 70% sequence similarity. This information is compiled in the UniLectin platform that includes the previously described UniLectin3D database of curated lectin 3D structures. Since its first release, UniLectin3D has been updated with 485 additional 3D structures. The database is now complemented by two additional modules: PropLec containing predicted β-propeller lectins and LectomeXplore including predicted lectins from sequences of the NBCI-nr and UniProt for every curated lectin class. UniLectin is accessible at https://www.unilectin.eu/.

METATRYP v 2.0: Metaproteomic Least Common Ancestor Analysis for Taxonomic Inference Using Specialized Sequence Assemblies-Standalone Software and Web Servers for Marine Microorganisms and Coronaviruses

We present METATRYP version 2 software that identifies shared peptides across the predicted proteomes of organisms within environmental metaproteomics studies to enable accurate taxonomic attribution of peptides during protein inference. Improvements include ingestion of complex sequence assembly data categories (metagenomic and metatranscriptomic assemblies, single cell amplified genomes, and metagenome assembled genomes), prediction of the least common ancestor (LCA) for a peptide shared across multiple organisms, increased performance through updates to the backend architecture, and development of a web portal (https://metatryp.whoi.edu). Major expansion of the marine METATRYP database with predicted proteomes from environmental sequencing confirms a low occurrence of shared tryptic peptides among disparate marine microorganisms, implying tractability for targeted metaproteomics. METATRYP was designed to facilitate ocean metaproteomics and has been integrated into the Ocean Protein Portal (https://oceanproteinportal.org); however, it can be readily applied to other domains. We describe the rapid deployment of a coronavirus-specific web portal (https://metatryp-coronavirus.whoi.edu/) to aid in use of proteomics on coronavirus research during the ongoing pandemic. A coronavirus-focused METATRYP database identified potential SARS-CoV-2 peptide biomarkers and indicated very few shared tryptic peptides between SARS-CoV-2 and other disparate taxa analyzed, sharing <1% peptides with taxa outside of the betacoronavirus group, establishing that taxonomic specificity is achievable using tryptic peptide-based proteomic diagnostic approaches.

Effects of Yersinia ruckeri invasion on the proteome of the Chinook salmon cell line CHSE-214

Yersinia ruckeri is an important bacterial pathogen of fish, in particular salmonids, it has been associated with systemic infections worldwide and, like many enteric bacteria, it is a facultative intracellular pathogen. However, the effect of Y. ruckeri's interactions with the host at the cellular level have received little investigation. In the present study, a culture of Chinook Salmon Embryo (CHSE) cell line was exposed to Y. ruckeri. Afterwards, the proteins were investigated and identified by mass spectrometry and compared to the content of unexposed cultures. The results of this comparison showed that 4.7% of the identified proteins were found at significantly altered concentrations following infection. Interestingly, infection with Y. ruckeri was associated with significant changes in the concentration of surface adhesion proteins, including a significantly decreased presence of β-integrins. These surface adhesion molecules are known to be the target for several adhesion molecules of Yersiniaceae. The concentration of several anti-apoptotic regulators (HSP90 and two DNAj molecules) appeared similarly downregulated. Taken together, these findings suggest that Y. ruckeri affects the proteome of infected cells in a notable manner and our results shed some light on the interaction between this important bacterial pathogen and its host.

Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms

Despite tremendous efforts in genomics, transcriptomics, and proteomics communities, there is still no comprehensive data about the exact number of protein-coding genes, translated proteoforms, and their function. In addition, by now, we lack functional annotation for 1193 genes, where expression was confirmed at the proteomic level (uPE1 proteins). We re-analyzed results of AP-MS experiments from the BioPlex 2.0 database to predict functions of uPE1 proteins and their splice forms. By building a protein-protein interaction network for 12 ths. identified proteins encoded by 11 ths. genes, we were able to predict Gene Ontology categories for a total of 387 uPE1 genes. We predicted different functions for canonical and alternatively spliced forms for four uPE1 genes. In total, functional differences were revealed for 62 proteoforms encoded by 31 genes. Based on these results, it can be carefully concluded that the dynamics and versatility of the interactome is ensured by changing the dominant splice form. Overall, we propose that analysis of large-scale AP-MS experiments performed for various cell lines and under various conditions is a key to understanding the full potential of genes role in cellular processes.

Quantitative MS-Based Proteomics: Comparing the MCF-7 Cellular Response to Hypoxia and a 2-Oxoglutarate Analogue

The hypoxia-inducible factors (HIFs) are key transcription factors in determining cellular responses involving alterations in protein levels in response to limited oxygen availability in animal cells. 2-Oxoglutarate-dependent oxygenases play key roles in regulating levels of HIF and its transcriptional activity. We describe MS-based proteomics studies in which we compared the results of subjecting human breast cancer MCF-7 cells to hypoxia or treating them with a cell-penetrating derivative (dimethyl N-oxalylglycine; DMOG) of the stable 2OG analogue N-oxalylglycine. The proteomic results are consistent with reported transcriptomic analyses and support the proposed key roles of 2OG-dependent HIF prolyl- and asparaginyl-hydroxylases in the hypoxic response. Differences between the data sets for hypoxia and DMOG might reflect context-dependent effects or HIF-independent effects of DMOG.

Comparative differential cuproproteomes of Rhodobacter capsulatus reveal novel copper homeostasis related proteins

Copper (Cu) is an essential, but toxic, micronutrient for living organisms and cells have developed sophisticated response mechanisms towards both the lack and the excess of Cu in their environments. In this study, we achieved a global view of Cu-responsive changes in the prokaryotic model organism Rhodobacter capsulatus using label-free quantitative differential proteomics. Semi-aerobically grown cells under heterotrophic conditions in minimal medium (∼0.3 μM Cu) were compared with cells supplemented with either 5 μM Cu or with 5 mM of the Cu-chelator bathocuproine sulfonate. Mass spectrometry based bottom-up proteomics of unfractionated cell lysates identified 2430 of the 3632 putative proteins encoded by the genome, producing a robust proteome dataset for R. capsulatus. Use of biological and technical replicates for each growth condition yielded high reproducibility and reliable quantification for 1926 of the identified proteins. Comparison of cells grown under Cu-excess or Cu-depleted conditions to those grown under minimal Cu-sufficient conditions revealed that 75 proteins exhibited statistically significant (p < 0.05) abundance changes, ranging from 2- to 300-fold. A subset of the highly Cu-responsive proteins was orthogonally probed using molecular genetics, validating that several of them were indeed involved in cellular Cu homeostasis.

VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques

Subcellular localization prediction of the proteome is one of major goals of large-scale genome or proteome sequencing projects to define the gene functions that could be possible with the help of computational modeling techniques. Previously, different methods have been developed for this purpose using multi-label classification system and achieved a high level of accuracy. However, during the validation of our blind dataset of plant vacuole proteins, we observed that they have poor performance with accuracy value range from ~1.3% to 48.5%. The results showed that the previously developed methods are not very accurate for the plant vacuole protein prediction and thus emphasize the need to develop a more accurate and reliable algorithm. In this study, we have developed various compositions as well as PSSM-based models and achieved a high accuracy than previously developed methods. We have shown that our best model achieved ~63% accuracy on blind dataset, which is far better than currently available tools. Furthermore, we have implemented our best models in the form of GUI-based free software called 'VacPred' which is compatible with both Linux and Window platform. This software is freely available for download at www.deepaklab.com/vacpred.

Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility

OBJECTIVE

Label-free quantitative proteomics has emerged as a powerful strategy to obtain high quality quantitative measures of the proteome with only a very small quantity of total protein extract. Because our research projects were requiring the application of bottom-up shotgun mass spectrometry proteomics in the pathogenic yeasts Candida glabrata and Candida albicans, we performed preliminary experiments to (i) obtain a precise list of all the proteins for which measures of abundance could be obtained and (ii) assess the reproducibility of the results arising respectively from biological and technical replicates.

DATA DESCRIPTION

Three time-courses were performed in each Candida species, and an alkaline pH stress was induced for two of them. Cells were collected 10 and 60 min after stress induction and proteins were extracted. Samples were analysed two times by mass spectrometry. Our final dataset thus comprises label-free quantitative proteomics results for 24 samples (two species, three time-courses, two time points and two runs of mass spectrometry). Statistical procedures were applied to identify proteins with differential abundances between stressed and unstressed situations. Considering that C. glabrata and C. albicans are human pathogens, which face important pH fluctuations during a human host infection, this dataset has a potential value to other researchers in the field.

Profiling of Seed Proteome in Pea (Pisum sativum L.) Lines Characterized with High and Low Responsivity to Combined Inoculation with Nodule Bacteria and Arbuscular Mycorrhizal Fungi

Legume crops represent the major source of food protein and contribute to human nutrition and animal feeding. An essential improvement of their productivity can be achieved by symbiosis with beneficial soil microorganisms-rhizobia (Rh) and arbuscular mycorrhizal (AM) fungi. The efficiency of these interactions depends on plant genotype. Recently, we have shown that, after simultaneous inoculation with Rh and AM, the productivity gain of pea (Pisum sativum L) line K-8274, characterized by high efficiency of interaction with soil microorganisms (EIBSM), was higher in comparison to a low-EIBSM line K-3358. However, the molecular mechanisms behind this effect are still uncharacterized. Therefore, here, we address the alterations in pea seed proteome, underlying the symbiosis-related productivity gain, and identify 111 differentially expressed proteins in the two lines. The high-EIBSM line K-8274 responded to inoculation by prolongation of seed maturation, manifested by up-regulation of proteins involved in cellular respiration, protein biosynthesis, and down-regulation of late-embryogenesis abundant (LEA) proteins. In contrast, the low-EIBSM line K-3358 demonstrated lower levels of the proteins, related to cell metabolism. Thus, we propose that the EIBSM trait is linked to prolongation of seed filling that needs to be taken into account in pulse crop breeding programs. The raw data have been deposited to the ProteomeXchange with identifier PXD013479.

Treatment of Common Sunflower (Helianthus annus L.) Seeds with Radio-frequency Electromagnetic Field and Cold Plasma Induces Changes in Seed Phytohormone Balance, Seedling Development and Leaf Protein Expression

Treatment of plant seeds with electromagnetic fields or non-thermal plasmas aims to take advantage of plant functional plasticity towards stimulation of plant agricultural performance. In this study, the effects of pre-sowing seed treatment using 200 Pa vacuum (7 min), 5.28 MHz radio-frequency cold plasma (CP -2, 5, and 7 min) and electromagnetic field (EMF -5, 10, 15 min) on seed germination kinetics, content of phytohormones, morphometric parameters of seedlings and leaf proteome were assessed. CP 7 min and EMF 15 min treatments caused 19-24% faster germination in vitro; germination in the substrate was accelerated by vacuum (9%) and EMF 15 min (17%). The stressors did not change the seed germination percentage, with exception of EMF 5 min treatment that caused a decrease by 7.5%. Meanwhile both CP 7 min and EMF 15 min treatments stimulated germination, but the EMF treatment resulted in higher weight of leaves. Stressor-specific changes in phytohormone balance were detected in seeds: vacuum treatment decreased zeatin amount by 39%; CP treatments substantially increased gibberellin content, but other effects strongly varied with the treatment duration; the abscisic acid content was reduced by 55-60% after the EMF treatment. Analysis of the proteome showed that short exposure of seeds to the EMF or CP induced a similar long-term effect on gene expression in leaves, mostly stimulating expression of proteins involved in photosynthetic processes and their regulation.

Comparative Analysis of the Adhesive Proteins of the Adult Stalked Goose Barnacle Pollicipes pollicipes (Cirripedia: Pedunculata)

Adhesion in barnacles is still poorly understood. The cement gland secretes an insoluble multi-protein complex, which adheres very strongly to a variety of substrates in the presence of water. This adhesion mechanism is bioinspiring for the engineering of new adhesive materials, but to replicate this adhesive system, the genes coding for the cement constitutive proteins must be identified and elucidated, and their products characterised. Here, the complete sequences of three cement protein (CP) genes (CP-100K, CP-52K, and CP-19K) isolated from the cement gland of the stalked barnacle Pollicipes pollicipes (order Scalpelliformes) were obtained using RACE PCR. The three genes were compared to the 23 other acorn barnacle CP genes so far sequenced (order Sessilia) to determine common and differential patterns and molecular properties, since the adhesives of both orders have visibly different characteristics. A shotgun proteomic analysis was performed on the cement, excreted at the membranous base of specimens, where the products of the three genes sequenced in the gland were identified, validating their function as CPs. A principal component analysis (PCA) was performed, to cluster CPs into groups with similar amino acid composition. This analysis uncovered three CP groups, each characterised by similar residue composition, features in secondary structure, and some biochemical properties, including isoelectric point and residue accessibility to solvents. The similarity among proteins in each defined group was low despite comparable amino acid composition. PCA can identify putative adhesive proteins from NGS transcriptomic data regardless of their low homology. This analysis did not highlight significant differences in residue composition between homologous acorn and stalked barnacle CPs. The characteristics responsible for the structural differences between the cement of stalked and acorn barnacles are described, and the presence of nanostructures, such as repetitive homologous domains and low complexity regions, and repetitive β-sheets are discussed relatively to self-assembly and adhesion.

Phosphodiesterase beta is the master regulator of cAMP signalling during malaria parasite invasion

Cyclic nucleotide signalling is a major regulator of malaria parasite differentiation. Phosphodiesterase (PDE) enzymes are known to control cyclic GMP (cGMP) levels in the parasite, but the mechanisms by which cyclic AMP (cAMP) is regulated remain enigmatic. Here, we demonstrate that Plasmodium falciparum phosphodiesterase β (PDEβ) hydrolyses both cAMP and cGMP and is essential for blood stage viability. Conditional gene disruption causes a profound reduction in invasion of erythrocytes and rapid death of those merozoites that invade. We show that this dual phenotype results from elevated cAMP levels and hyperactivation of the cAMP-dependent protein kinase (PKA). Phosphoproteomic analysis of PDEβ-null parasites reveals a >2-fold increase in phosphorylation at over 200 phosphosites, more than half of which conform to a PKA substrate consensus sequence. We conclude that PDEβ plays a critical role in governing correct temporal activation of PKA required for erythrocyte invasion, whilst suppressing untimely PKA activation during early intra-erythrocytic development.

Production of Lipids and Proteome Variation in a Chilean Thraustochytrium striatum Strain Cultured under Different Growth Conditions

Total lipids and docosahexaenoic acid (DHA) production by a Chilean isolated thraustochytrid were evaluated under different growth conditions in shake flasks. The analyzed strain was identified as Thraustochytrium striatum according to an 18S rRNA gene sequence analysis. The strain (T. striatum AL16) showed negligible growth in media prepared with artificial seawater at concentrations lower than 50% v/v and pH lower than 5. Maltose and starch were better carbon sources for growth than glucose. DHA content of the biomass grown with maltose (60 g L^-1) was doubled by increasing the agitation rate from 150 to 250 rpm. The DHA (0.8-6%) and eicosapentaenoic acid (0.2-21%) content in the total lipids varied depending on culture conditions and culture age. Lipid and DHA concentration increased (up to 5 g L^-1 and 66 mg L^-1, respectively) by regularly feeding the culture with a concentrated starch solution. Carotenoid accumulation was detected in cells grown with maltose or starch. Contrasting conditions of starch and glucose cultures were selected for comparative proteomics. Total protein extracts were separated by two-dimensional gel electrophoresis; 25 spots were identified using ESI-MS/MS. A protein database (143,006 entries) for proteomic interrogation was generated using de novo assembling of Thraustochytrium sp. LLF1b - MMETSP0199_2 transcriptome; 18 proteins differentially expressed were identified. Three ATP synthases were differentially accumulated in cultures with glucose, whereas malate dehydrogenase was more abundant in cells cultured with starch.

Protein Barcodes Enable High-Dimensional Single-Cell CRISPR Screens

CRISPR pools are being widely employed to identify gene functions. However, current technology, which utilizes DNA as barcodes, permits limited phenotyping and bulk-cell resolution. To enable novel screening capabilities, we developed a barcoding system operating at the protein level. We synthesized modules encoding triplet combinations of linear epitopes to generate >100 unique protein barcodes (Pro-Codes). Pro-Code-expressing vectors were introduced into cells and analyzed by CyTOF mass cytometry. Using just 14 antibodies, we detected 364 Pro-Code populations; establishing the largest set of protein-based reporters. By pairing each Pro-Code with a different CRISPR, we simultaneously analyzed multiple phenotypic markers, including phospho-signaling, on dozens of knockouts. Pro-Code/CRISPR screens found two interferon-stimulated genes, the immunoproteasome component Psmb8 and a chaperone Rtp4, are important for antigen-dependent immune editing of cancer cells and identified Socs1 as a negative regulator of Pd-l1. The Pro-Code technology enables simultaneous high-dimensional protein-level phenotyping of 100s of genes with single-cell resolution.

Highly Efficient Phosphoproteome Capture and Analysis from Urinary Extracellular Vesicles

Analysis of protein phosphorylation in extracellular vesicles (EVs) offers an unprecedented potential for understanding cancer signaling and early stage disease diagnosis. However, prior to the phosphoproteome analysis step, the isolation of EVs from biofluids remains a challenging issue to overcome due to the low yield and impurity from current isolation methods. Here, we carry out an extensive assessment of several EV isolation methods including a novel rapid isolation method EVTRAP for highly efficient capture of extracellular vesicles from human urine sample. We demonstrate that over 95% recovery yield can be consistently achieved by EVTRAP, a significant improvement over current standard techniques. We then applied EVTRAP to identify over 16 000 unique peptides representing 2000 unique EV proteins from 200 μL urine sample, including all known EV markers with substantially increased recovery levels over ultracentrifugation. Most importantly, close to 2000 unique phosphopeptides were identified from more than 860 unique phosphoproteins using 10 mL of urine. The data demonstrated that EVTRAP is a highly effective and potentially widely implementable clinical isolation method for analysis of EV protein phosphorylation.

A Liquid Chromatography with Tandem Mass Spectrometry-Based Proteomic Analysis of Cells Cultured in DMEM 10% FBS and Chemically Defined Medium Using Human Adipose-Derived Mesenchymal Stem Cells

Human adipose-derived mesenchymal stem cells (hADSCs) are representative cell sources for cell therapy. Classically, Dulbecco's Modified Eagle's medium (DMEM) containing 10% fetal bovine serum (FBS) has been used as culture medium for hADSCs. A chemically defined medium (CDM) containing no heterologous animal components has recently been used to produce therapeutic hADSCs. However, how the culture environment using a medium without FBS affects the protein expression of hADSC is unclear. We subjected hADSCs cultured in CDM and DMEM (10% FBS) to a protein expression analysis by tandem mass spectrometry liquid chromatography and noted 98.2% agreement in the proteins expressed by the CDM and DMEM groups. We classified 761 proteins expressed in both groups by their function in a gene ontology analysis. Thirty-one groups of proteins were classified as growth-related proteins in the CDM and DMEM groups, 16 were classified as antioxidant activity-related, 147 were classified as immune system process-related, 557 were involved in biological regulation, 493 were classified as metabolic process-related, and 407 were classified as related to stimulus responses. These results show that the trend in the expression of major proteins related to the therapeutic effect of hADSCs correlated strongly in both groups.

Family-specific scaling laws in bacterial genomes

Among several quantitative invariants found in evolutionary genomics, one of the most striking is the scaling of the overall abundance of proteins, or protein domains, sharing a specific functional annotation across genomes of given size. The size of these functional categories change, on average, as power-laws in the total number of protein-coding genes. Here, we show that such regularities are not restricted to the overall behavior of high-level functional categories, but also exist systematically at the level of single evolutionary families of protein domains. Specifically, the number of proteins within each family follows family-specific scaling laws with genome size. Functionally similar sets of families tend to follow similar scaling laws, but this is not always the case. To understand this systematically, we provide a comprehensive classification of families based on their scaling properties. Additionally, we develop a quantitative score for the heterogeneity of the scaling of families belonging to a given category or predefined group. Under the common reasonable assumption that selection is driven solely or mainly by biological function, these findings point to fine-tuned and interdependent functional roles of specific protein domains, beyond our current functional annotations. This analysis provides a deeper view on the links between evolutionary expansion of protein families and the functional constraints shaping the gene repertoire of bacterial genomes.

Protein lipograms

Linguistic analysis of protein sequences is an underexploited technique. Here, we capitalize on the concept of the lipogram to characterize sequences at the proteome levels. A lipogram is a literary composition which omits one or more letters. A protein lipogram likewise omits one or more types of amino acid. In this article, we establish a usable terminology for the decomposition of a sequence collection in terms of the lipogram. Next, we characterize Uniref50 using a lipogram decomposition. At the global level, protein lipograms exhibit power-law properties. A clear correlation with metabolic cost is seen. Finally, we use the lipogram construction to assign proteomes to the four branches of the tree-of-life: archaea, bacteria, eukaryotes and viruses. We conclude from this pilot study that the lipogram demonstrates considerable potential as an additional tool for sequence analysis and proteome classification.

High-throughput metaproteomics data analysis with Unipept: A tutorial

In recent years, shotgun metaproteomics has established itself as an important tool to study the composition of complex ecosystems and microbial communities. Two key steps in metaproteomics data analysis are the inference of proteins from the identified peptides, and the determination of the taxonomic origin and function of these proteins. This tutorial therefore introduces the Unipept command line interface (http://unipept.ugent.be/clidocs) as a platform-independent tool for such metaproteomics data analyses. First, a detailed overview is given of the available Unipept commands and their functions. Next, the power of the Unipept command line interface is illustrated using two case studies that analyze a single tryptic peptide, and a set of peptides retrieved from a shotgun metaproteomics experiment, respectively. Finally, the analysis results obtained using these command line tools are compared with the interactive taxonomic analysis that is available on the Unipept website.

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

Time- and radiation-dose dependent changes in the plasma proteome after total body irradiation of non-human primates: Implications for biomarker selection

Acute radiation syndrome (ARS) is a complex multi-organ disease resulting from total body exposure to high doses of radiation. Individuals can be exposed to total body irradiation (TBI) in a number of ways, including terrorist radiological weapons or nuclear accidents. In order to determine whether an individual has been exposed to high doses of radiation and needs countermeasure treatment, robust biomarkers are needed to estimate radiation exposure from biospecimens such as blood or urine. In order to identity such candidate biomarkers of radiation exposure, high-resolution proteomics was used to analyze plasma from non-human primates following whole body irradiation (Co-60 at 6.7 Gy and 7.4 Gy) with a twelve day observation period. A total of 663 proteins were evaluated from the plasma proteome analysis. A panel of plasma proteins with characteristic time- and dose-dependent changes was identified. In addition to the plasma proteomics study reported here, we recently identified candidate biomarkers using urine from these same non-human primates. From the proteomic analysis of both plasma and urine, we identified ten overlapping proteins that significantly differentiate both time and dose variables. These shared plasma and urine proteins represent optimal candidate biomarkers of radiation exposure.

Understanding the cochlear implant environment by mapping perilymph proteomes from different species

Cochlear implants operate within a bony channel of the cochlea, bathed in a fluid known as the perilymph. The perilymph is a complex fluid containing ions and proteins, which are known to actively interact with metallic electrodes. To improve our understanding of how cochlear implant performance varies in preclinical in vivo studies in comparison to human trials and patient outcomes, the protein composition (or perilymph proteome) is needed. Samples of perilymph were gathered from feline and guinea pig subjects and analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS) to produce proteomes and compare against the recently published human proteome. Over 64% of the proteins in the guinea pig proteome were found to be common to the human proteome. The proportions of apolipoproteins, enzymes and immunoglobulins showed little variation between the two proteomes, with other classes showing similarity. This establishes a good basis for comparison of results. The results for the feline profile showed less similarity with the human proteome and would not provide a quality comparison. This work highlights the suitability of the guinea pig to model the biological environment of the human cochlear and the need to carefully select models of the biological environment of a cochlear implant to more adequately translate in vitro and in vivo studies to the clinic.

Resource: Mapping the Triticum aestivum proteome

Yield and quality improvement of bread wheat (Triticum aestivum) is a focus in efforts to meet new demands from population growth and changing human diets. As the complexity of the wheat genome is unravelled, determining how it is used to build the protein machinery of wheat plants is a key next step in explaining detailed aspects of wheat growth and development. The specific functions of wheat organs during vegetative development and the role of metabolism, protein degradation and remobilisation in driving grain production are the foundations of crop performance and have recently become accessible through studies of the wheat proteome. We present a large scale, publicly accessible proteome mapping of wheat consisting of 24 organ and developmental samples. Tissue specific sub-proteomes and ubiquitously expressed markers of the wheat proteome are identified, alongside hierarchical assessment of protein functional classes, their presence in different tissues and correlations between the abundance of functional classes of proteins. Gene-specific identifications and protein family relationships are accounted for in the organisation of the data and 202 new protein-coding transcripts identified by proteogenomic mapping. The interactive database will serve as a vehicle to build, refine and deposit confirmed targeted proteomic assays for wheat proteins and protein families to assess function (www.wheatproteome.org).

Improving Phylogeny Reconstruction at the Strain Level Using Peptidome Datasets

Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.

Towards a Proteomic Catalogue and Differential Annotation of Salivary Gland Proteins in Blood Fed Malaria Vector Anopheles culicifacies by Mass Spectrometry

In order to understand the importance of functional proteins in mosquito behavior, following blood meal, a baseline proteomic dataset is essential for providing insights into the physiology of blood feeding. Therefore, in this study as first step, in solution and 1-D electrophoresis digestion approach combined with tandem mass spectrometry (nano LC-MS/MS) and computational bioinformatics for data mining was used to prepare a baseline proteomic catalogue of salivary gland proteins of sugar fed An. culicifacies mosquitoes. A total of 106 proteins were identified and analyzed by SEQUEST algorithm against mosquito protein database from Uniprot/NCBI. Importantly, D7r1, D7r2, D7r4, salivary apyrase, anti-platelet protein, calreticulin, antigen 5 family proteins were identified and grouped on the basis of biological and functional roles. Secondly, differential protein expression and annotations between salivary glands of sugar fed vs blood fed mosquitoes was analyzed using 2-Delectrophoresis combined with MALDI-TOF mass spectrometry. The alterations in the differential expression of total 38 proteins was observed out of which 29 proteins like beclin-1, phosphorylating proteins, heme oxygenase 1, ferritin, apoptotic proteins, coagulation and immunity like, serine proteases, serpins, c-type lectin and protein in regulation of blood feeding behavior were found to be up regulated while 9 proteins related to blood feeding, juvenile hormone epoxide hydrolase ii, odorant binding proteins and energy metabolic enzymes were found to be down regulated. To our knowledge, this study provides a first time baseline proteomic dataset and functional annotations of An. culicifacies salivary gland proteins that may be involved during the blood feeding. Identification of differential salivary proteins between sugar fed and blood fed mosquitoes and their plausible role may provide insights into the physiological processes associated with feeding behavior and sporozoite transmission during the process of blood feeding.

Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments

The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.

An overarching endeavor in systems biology is to characterize and understand the allocation of an organism’s proteome. Common approaches to characterize proteome allocation are based on annotations of protein functions or transcriptional regulatory targets. Here, we develop a novel approach based on model-predicted proteome utilization. This approach reveals that in many environments, a large fraction of the proteome is unused. Unused protein expression is known to incur costs on organismal fitness. We show that changes in the allocation of the proteome to used versus unused fractions can account for the variability in growth rates observed across environments and is a common mechanism to increase growth rates in laboratory evolution experiments. We compare our approach to classify the proteome based on model-predicted utilization to more traditional approaches to reveal biological functions and transcriptional regulators underlying the expression of unused protein. Expression of these functions may reflect ecological trade-offs between growth, nutrient-readiness, and stress resistance.

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis.

Sub-cellular localisation of proteins is critical to their function in all cellular processes; proteins localising to their intended micro-environment, e.g organelles, vesicles or macro-molecular complexes, will meet the interaction partners and biochemical conditions suitable to pursue their molecular function. Therefore, sound data and methods to reliably and systematically study protein localisation, and hence their mis-localisation and the disruption of protein trafficking, that are relied upon by the cell biology community, are essential. Here we present a method to infer protein localisation relying on the optimal integration of experimental mass spectrometry-based data and auxiliary sources, such as GO annotation, outputs from third-party software, protein-protein interactions or immunocytochemistry data. We found that the application of transfer learning algorithms across these diverse data sources considerably improves on the quantity and reliability of sub-cellular protein assignment, compared to single data classifiers previously applied to infer sub-cellular localisation using experimental data only. We show how our method does not compromise biologically relevant experimental-specific signal after integration with heterogeneous freely available third-party resources. The integration of different data sources is an important challenge in the data intensive world of biology and we anticipate the transfer learning methods presented here will prove useful to many areas of biology, to unify data obtained from different but complimentary sources.

Label-Free Quantitative Proteomic Analysis of Puccinia psidii Uredospores Reveals Differences of Fungal Populations Infecting Eucalyptus and Guava

Puccinia psidii sensu lato (s.l.) is the causal agent of eucalyptus and guava rust, but it also attacks a wide range of plant species from the myrtle family, resulting in a significant genetic and physiological variability among populations accessed from different hosts. The uredospores are crucial to P. psidii dissemination in the field. Although they are important for the fungal pathogenesis, their molecular characterization has been poorly studied. In this work, we report the first in-depth proteomic analysis of P. psidii s.l. uredospores from two contrasting populations: guava fruits (PpGuava) and eucalyptus leaves (PpEucalyptus). NanoUPLC-MSE was used to generate peptide spectra that were matched to the UniProt Puccinia genera sequences (UniProt database) resulting in the first proteomic analysis of the phytopathogenic fungus P. psidii. Three hundred and fourty proteins were detected and quantified using Label free proteomics. A significant number of unique proteins were found for each sample, others were significantly more or less abundant, according to the fungal populations. In PpGuava population, many proteins correlated with fungal virulence, such as malate dehydrogenase, proteossomes subunits, enolases and others were increased. On the other hand, PpEucalyptus proteins involved in biogenesis, protein folding and translocation were increased, supporting the physiological variability of the fungal populations according to their protein reservoirs and specific host interaction strategies.

Isobaric Tag for Relative and Absolute Quantitation (iTRAQ)-Based Protein Profiling in Plants

Isobaric tags for relative and absolute quantitation (iTRAQ) is a technology that utilizes isobaric reagents to label the primary amines of peptides and proteins and is used in proteomics to study quantitative changes in the proteome by tandem mass spectrometry . Here, we present an adaptation of the iTRAQ experimental protocol for plants that allows the identification and quantitation of more than 12,000 plant proteins in Arabidopsis with a false discovery rate of less than 5 %.

Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis

Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

Definition of a consensus integrin adhesome and its dynamics during adhesion complex assembly and disassembly

Integrin receptor activation initiates the formation of integrin adhesion complexes (IACs) at the cell membrane that transduce adhesion-dependent signals to control a multitude of cellular functions. Proteomic analyses of isolated IACs have revealed an unanticipated molecular complexity; however, a global view of the consensus composition and dynamics of IACs is lacking. Here, we have integrated several IAC proteomes and generated a 2,412-protein integrin adhesome. Analysis of this data set reveals the functional diversity of proteins in IACs and establishes a consensus adhesome of 60 proteins. The consensus adhesome is likely to represent a core cell adhesion machinery, centred around four axes comprising ILK-PINCH-kindlin, FAK-paxillin, talin-vinculin and α-actinin-zyxin-VASP, and includes underappreciated IAC components such as Rsu-1 and caldesmon. Proteomic quantification of IAC assembly and disassembly detailed the compositional dynamics of the core cell adhesion machinery. The definition of this consensus view of integrin adhesome components provides a resource for the research community.

A Comprehensive Analysis of Chromoplast Differentiation Reveals Complex Protein Changes Associated with Plastoglobule Biogenesis and Remodeling of Protein Systems in Sweet Orange Flesh

Globular and crystalloid chromoplasts were observed to be region specifically formed in sweet orange (Citrus sinensis) flesh and converted from amyloplasts during fruit maturation, which was associated with the composition of specific carotenoids and the expression of carotenogenic genes. Subsequent isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analyses of purified plastids from the flesh during chromoplast differentiation and senescence identified 1,386 putative plastid-localized proteins, 1,016 of which were quantified by spectral counting. The iTRAQ values reflecting the expression abundance of three identified proteins were validated by immunoblotting. Based on iTRAQ data, chromoplastogenesis appeared to be associated with three major protein expression patterns: (1) marked decrease in abundance of the proteins participating in the translation machinery through ribosome assembly; (2) increase in abundance of the proteins involved in terpenoid biosynthesis (including carotenoids), stress responses (redox, ascorbate, and glutathione), and development; and (3) maintenance of the proteins for signaling and DNA and RNA. Interestingly, a strong increase in abundance of several plastoglobule-localized proteins coincided with the formation of plastoglobules in the chromoplast. The proteomic data also showed that stable functioning of protein import, suppression of ribosome assembly, and accumulation of chromoplast proteases are correlated with the amyloplast-to-chromoplast transition; thus, these processes may play a collective role in chromoplast biogenesis and differentiation. By contrast, the chromoplast senescence process was inferred to be associated with significant increases in stress response and energy supply. In conclusion, this comprehensive proteomic study identified many potentially new plastid-localized proteins and provides insights into the potential developmental and molecular mechanisms underlying chromoplast biogenesis, differentiation, and senescence in sweet orange flesh.

The Kinetic Response of the Proteome in A549 Cells Exposed to ZnSO4 Stress

Zinc, an essential trace element, is involved in many important physiological processes. Cell responses to zinc stress show time-dependent effects besides concentration-dependence and tissue-specificity. Herein, we investigated the time-dependent differential expression of the proteome in A549 cells after administered with ZnSO4 for both 9 and 24 h using 2DE. 123 differentially expressed protein spots were detected, most of which were up-regulated by Zn2+ treatment. Interestingly, 49 proteins exhibited significant differential expression repeatedly during these two treatment periods, and moreover showed a conserved change with different ratios and four time-dependent expression patterns. Pattern 1 (up-regulated with rapid initial induction and subsequent repression) and pattern 4 (down-regulated with steady repression) were the predominant expression patterns. The abundances of the proteins in patterns 1 and 4 after 24 h of zinc treatment are always lower than that after 9 h, indicating that exogenous zinc reduced the expression of proteins in cells after 24 h or longer. Importantly, these findings could also reflect the central challenge in detecting zinc homeostasis proteins by 2DE or other high throughput analytical methods resulting from slight variation in protein expression after certain durations of exogenous zinc treatment and/or low inherent protein content in cells. These time-dependent proteome expression patterns were further validated by measuring dynamic changes in protein content in cells and in expression of two proteins using the Bradford method and western blotting, respectively. The time-dependent changes in total zinc and free Zn2+ ion contents in cells were measured using ICP-MS and confocal microscopy, respectively. The kinetic process of zinc homeostasis regulated by muffling was further revealed. In addition, we identified 50 differentially expressed proteins which are predominantly involved in metabolic process, cellular process or developmental process, and function as binding, catalytic activity or structural molecule activity. This study further elucidates our understanding of dynamic nature of the cellular response to zinc stress and the mechanism of zinc homeostasis.

The membrane proteome of stroma thylakoids from Arabidopsis thaliana studied by successive in-solution and in-gel digestion

From individual localization and large-scale proteomic studies, we know that stroma-exposed thylakoid membranes harbor part of the machinery performing the light-dependent photosynthetic reactions. The minor components of the stroma thylakoid proteome, regulating and maintaining the photosynthetic machinery, are in the process of being unraveled. In this study, we developed in-solution and in-gel proteolytic digestion methods, and used them to identify minor membrane proteins, e.g. transporters, in stroma thylakoids prepared from Arabidopsis thaliana (L.) Heynh Columbia-0 leaves. In-solution digestion with chymotrypsin yielded the largest number of peptides, but in combination with methanol extraction resulted in identification of the largest number of membrane proteins. Although less efficient in extracting peptides, in-gel digestion with trypsin and chymotrypsin led to identification of additional proteins. We identified a total of 58 proteins including 44 membrane proteins. Almost half are known thylakoid proteins with roles in photosynthetic light reactions, proteolysis and import. The other half, including many transporters, are not known as chloroplast proteins, because they have been either curated (manually assigned) to other cellular compartments or not curated at all at the plastid protein databases. Transporters include ATP-binding cassette (ABC) proteins, transporters for K(+) and other cations. Other proteins either have a role in processes probably linked to photosynthesis, namely translation, metabolism, stress and signaling or are contaminants. Our results indicate that all these proteins are present in stroma thylakoids; however, individual studies are required to validate their location and putative roles. This study also provides strategies complementary to traditional methods for identification of membrane proteins from other cellular compartments.

Vitamin D Binding Protein Isoforms and Apolipoprotein E in Cerebrospinal Fluid as Prognostic Biomarkers of Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a multifactorial autoimmune disease of the central nervous system with a heterogeneous and unpredictable course. To date there are no prognostic biomarkers even if they would be extremely useful for early patient intervention with personalized therapies. In this context, the analysis of inter-individual differences in cerebrospinal fluid (CSF) proteome may lead to the discovery of biological markers that are able to distinguish the various clinical forms at diagnosis.

METHODS

To this aim, a two dimensional electrophoresis (2-DE) study was carried out on individual CSF samples from 24 untreated women who underwent lumbar puncture (LP) for suspected MS. The patients were clinically monitored for 5 years and then classified according to the degree of disease aggressiveness and the disease-modifying therapies prescribed during follow up.

RESULTS

The hierarchical cluster analysis of 2-DE dataset revealed three protein spots which were identified by means of mass spectrometry as Apolipoprotein E (ApoE) and two isoforms of vitamin D binding protein (DBP). These three protein spots enabled us to subdivide the patients into subgroups correlated with clinical classification (MS aggressive forms identification: 80%). In particular, we observed an opposite trend of values for the two protein spots corresponding to different DBP isoforms suggesting a role of a post-translational modification rather than the total protein content in patient categorization.

CONCLUSIONS

These findings proved to be very interesting and innovative and may be developed as new candidate prognostic biomarkers of MS aggressiveness, if confirmed.

Differential regulation of proteins in rice (Oryza sativa L.) under iron deficiency

Sixty-three proteins were identified to be differentially accumulated due to iron deficiency in shoot and root. The importance of these proteins alterations on shoot physiology is discussed. Iron (Fe) is an essential micronutrient for plant growth and its accumulation affects the quality of edible plant organs. To investigate the adaptive mechanism of a Chinese rice variety grown under iron deficiency, proteins differentially accumulated in leaves and roots of Yangdao 6, an indica cultivar, under Fe deficiency growth condition, were profiled using a two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/MS). The accumulations of seventy-three proteins were detected to be increased or decreased upon iron deficiency, and sixty-three of them were successfully identified. Among the sixty-three proteins, a total of forty proteins were identified in rice leaves, and twenty-three proteins were in roots. Most of these proteins are involved in photosynthesis, C metabolism, oxidative stress, Adenosine triphosphate synthesis, cell growth or signal transduction. The results provide a comprehensive way to understand, at the level of proteins, the adaptive mechanism used by rice shoots and roots under iron deficiency.

Proteomic changes during tuber dormancy release process revealed by iTRAQ quantitative proteomics in potato

Given that limited information is available with regard to tuber dormancy release related proteome, we conducted proteome analysis of tuber dormancy release process at dormant tuber (DT), dormancy release tuber (DRT) and sprouting tuber (ST) using the iTRAQ technology. A total of 1,752 proteins were identified. Among them, a subset of 316 proteins was screened as significant up- (137) and down regulated (179) between DT vs DRT. A subset of 120 proteins experienced significant up- (40) or down-regulation (80) between DRT vs ST. The differentially expressed proteins were grouped into 11 functional categories. Proteins enriched in functional categories of major carbohydrate (CHO) metabolism, glycolysis, fermentation, amino acid metabolism, protein and transport were highly up-regulated, while functional categories of photosynthesis and RNA were down-regulated between DT vs DRT. Proteins enriched in functional groups of protein, cell wall, lipid metabolism, miscellaneous, and signaling were strongly up-regulated, while functional categories of photosynthesis, hormone metabolism and protein were down-regulated between DRT vs ST. Consistent with previous documented differentially expressed genes, most of differentially expressed proteins were also identified between DT and DRT, indicating the metabolism shift from growth suspension to growth activation as tubers dormancy breaking. The changes in protein profiles showed lower concordance with corresponding alterations in transcript levels, indicating possible transcriptional and posttranscriptional regulation. Furthermore, the possible mechanism of tuber dormancy release was discussed in relation to what was known in transcripts change and other plant models from carbohydrate metabolism, protein metabolism, stress response, redox regulation, transcription regulation, DNA metabolism, amino acid metabolism, development, signaling as well as hormone metabolism.

A proteomic strategy for global analysis of plant protein complexes

Global analyses of protein complex assembly, composition, and location are needed to fully understand how cells coordinate diverse metabolic, mechanical, and developmental activities. The most common methods for proteome-wide analysis of protein complexes rely on affinity purification-mass spectrometry or yeast two-hybrid approaches. These methods are time consuming and are not suitable for many plant species that are refractory to transformation or genome-wide cloning of open reading frames. Here, we describe the proof of concept for a method allowing simultaneous global analysis of endogenous protein complexes that begins with intact leaves and combines chromatographic separation of extracts from subcellular fractions with quantitative label-free protein abundance profiling by liquid chromatography-coupled mass spectrometry. Applying this approach to the crude cytosolic fraction of Arabidopsis thaliana leaves using size exclusion chromatography, we identified hundreds of cytosolic proteins that appeared to exist as components of stable protein complexes. The reliability of the method was validated by protein immunoblot analysis and comparisons with published size exclusion chromatography data and the masses of known complexes. The method can be implemented with appropriate instrumentation, is applicable to any biological system, and has the potential to be further developed to characterize the composition of protein complexes and measure the dynamics of protein complex localization and assembly under different conditions.

Extracellular matrix-associated proteome changes during non-host resistance in citrus-Xanthomonas interactions

Non-host resistance (NHR) is a most durable broad-spectrum resistance employed by the plants to restrict majority of pathogens. Plant extracellular matrix (ECM) is a critical defense barrier. Understanding ECM responses during interaction with non-host pathogen will provide insights into molecular events of NHR. In this study, the ECM-associated proteome was compared during interaction of citrus with pathogen Xanthomonas axonopodis pv. citri (Xac) and non-host pathogen Xanthomonas oryzae pv. oryzae (Xoo) at 8, 16, 24 and 48 h post inoculation. Comprehensive analysis of ECM-associated proteins was performed by extracting wall-bound and soluble ECM components using both destructive and non-destructive procedures. A total of 53 proteins was differentially expressed in citrus-Xanthomonas host and non-host interaction, out of which 44 were identified by mass spectrometry. The differentially expressed proteins were related to (1) defense-response (5 pathogenesis-related proteins, 3 miraculin-like proteins (MIR, MIR1 and MIR2) and 2 proteases); (2) enzymes of reactive oxygen species (ROS) metabolism [Cu/Zn superoxide dismutase (SOD), Fe-SOD, ascorbate peroxidase and 2-cysteine-peroxiredoxin]; (3) signaling (lectin, curculin-like lectin and concanavalin A-like lectin kinase); and (4) cell-wall modification (α-xylosidase, glucan 1, 3 β-glucosidase, xyloglucan endotransglucosylase/hydrolase). The decrease in ascorbate peroxidase and cysteine-peroxiredoxin could be involved in maintenance of ROS levels. Increase in defense, cell-wall remodeling and signaling proteins in citrus-Xoo interaction suggests an active involvement of ECM in execution of NHR. Partially compromised NHR in citrus against Xoo, upon Brefeldin A pre-treatment supported the role of non-classical secretory proteins in this phenomenon.