Protein identification using MS/MS data

Beyond the surface: the plant secretome as a bridge between the cell and its environment

MAIN CONCLUSIONS

We describe the biological importance of proteins secreted in plants under different conditions and biological processes, the secretion mechanisms, methodologies for obtaining and identifying these proteins, and future perspectives. Molecule secretion inside and outside the cell is relevant to all areas of plant biology. Protein secretion, in particular, has intriguing possibilities due to the different secretion pathways that the cell uses to send biochemical messages. The secretion of proteins-secretomes-into extracellular space in response to different stimuli or stress situations, in vitro or in planta conditions, has been studied in plants and plant tissues. Proteomics has allowed the quantitative and qualitative analysis of this process and the measurement of proteins associated with the cellular development of different tissues. This has provided the means of evaluating a more precise biochemical state of the cells and the changes that occur during their growth. With the development of new techniques in proteomics, such as mass spectrometry, sequencing, and bioinformatics, it is now possible to elucidate the main proteins secreted, with all their posttranslational modifications, in different plant species and under different specific conditions. This review presents the different pathways of protein secretion in plants, highlighting the well-known importance of signal peptides. The advances and disadvantages of in planta and in vitro systems used for proteomic purposes are discussed. The principal proteomic techniques to better understand the biological function of the secretome are summarized.

High fat diet-induced obesity and gestational DMBA exposure alter folliculogenesis and the proteome of the maternal ovary†

Obesity and ovotoxicant exposures impair female reproductive health with greater ovotoxicity reported in obese relative to lean females. The mother and developing fetus are vulnerable to both during gestation. 7,12-dimethylbenz[a]anthracene (DMBA) is released during carbon combustion including from cigarettes, coal, fossil fuels, and forest fires. This study investigated the hypothesis that diet-induced obesity would increase sensitivity of the ovaries to DMBA-induced ovotoxicity and determined impacts of both obesity and DMBA exposure during gestation on the maternal ovary. Female C57BL/6 J mice were fed a control or a High Sugar High Fat (45% kcal from fat; 20% kcal from sucrose) diet until ~30% weight gain was attained before mating with unexposed males. From gestation Day 7, mice were exposed intraperitoneally to either vehicle control (corn oil) or DMBA (1 mg/kg diluted in corn oil) for 7 d. Thus, there were four groups: lean control (LC); lean DMBA exposed; obese control; obese DMBA exposed. Gestational obesity and DMBA exposure decreased (P < 0.05) ovarian and increased liver weights relative to LC dams, but there was no treatment impact (P > 0.05) on spleen weight or progesterone. Also, obesity exacerbated the DMBA reduction (P < 0.05) in the number of primordial, secondary follicles, and corpora lutea. In lean mice, DMBA exposure altered abundance of 21 proteins; in obese dams, DMBA exposure affected 134 proteins while obesity alone altered 81 proteins in the maternal ovary. Thus, the maternal ovary is impacted by DMBA exposure and metabolic status influences the outcome.

Coexistence of nonfluorescent chromoproteins and fluorescent proteins in massive Porites spp. corals manifesting a pink pigmentation response

Introduction

Several fluorescent proteins (FPs) and chromoproteins (CPs) are present in anthozoans and play possible roles in photoprotection. Coral tissues in massive corals often display discoloration accompanied by inflammation. Incidences of the pink pigmentation response (PPR) in massive Porites, described as inflammatory pink lesions of different shapes and sizes, has recently increased worldwide. FPs are reported to be present in PPR lesions, wherein a red fluorescent protein (RFP) appears to play a role in reducing reactive oxygen species. However, to date, the biochemical characterization and possible roles of the pigments involved are poorly understood. The present study aimed to identify and characterize the proteins responsible for pink discoloration in massive Porites colonies displaying PPRs, as well as to assess the differential distribution of pigments and the antioxidant properties of pigmented areas.

Method

CPs were extracted from PPR lesions using gel-filtration chromatography and identified via genetic analysis using liquid chromatography-tandem mass spectrometry. The coexistence of CPs and RFP in coral tissues was assessed using microscopic observation. Photosynthetic antivity and hydrogen peroxide-scavenging activitiy were measured to assess coral stress conditions.

Results

The present study revealed that the same CP (plut2.m8.16902.m1) isolated from massive Porites was present in both the pink spot and patch morphologies of the PPR. CPs were also found to coexist with RFP in coral tissues that manifested a PPR, with a differential distribution (coenosarc or tip of polyps' tentacles). High hydrogen peroxide-scavenging rates were found in tissues affected by PPR.

Discussion and Conclusion

The coexistence of CPs and RFP suggests their possible differential role in coral immunity. CPs, which are specifically expressed in PPR lesions, may serve as an antioxidant in the affected coral tissue. Overall, this study provides new knowledge to our understanding of the role of CPs in coral immunity.

Isolation and characterization of a lectin-like chitinase from the hepatopancreas of freshwater prawn, Macrobrachium rosenbergii

A lectin was isolated from the hepatopancreas of freshwater prawn, Macrobrachium rosenbergii by affinity chromatography using mucin-sepharose matrix. The purity of the isolated lectin was confirmed in native gradient PAGE that showed a single protein band of ∼37.9 kDa. In SDS-PAGE also one band of ∼43.3 kDa molecular weight was observed that indicated the protein to be a monomer. The band from the SDS-PAGE gel was identified through mass spectrometry as chitinase 1. The purified chitinase (50 μg/ml) hemagglutinated rabbit RBCs and, mucin and glucose inhibited hemagglutination with minimum concentrations of 0.1 mg/ml and 100 mM, respectively. Bacterial agglutination with Gram -ve Vibrio harveyi, Aeromonas sobria and Escherichia coli was also observed by this protein. Thus, chitinase 1 showed lectin-like properties besides its chitin hydrolytic activity. In western blot with hepatopancreas sample, rabbit antiserum against chitinase 1 cross-reacted to two additional proteins namely, chitinase 1C and obstructor E (a chitin-binding protein, CBP), besides its specific reactivity. An indirect ELISA was developed with the antiserum to quantify chitinases/CBP in hepatopancreas and serum samples of M. rosenbergii. The assay was used in samples from juvenile prawns following V. harveyi challenge. At 72 h post-challenge, significantly higher levels of chitinases/CBP were quantified in the hepatopancreas of the challenged group (1.8 ± 0.2 mg/g tissue) compared to the control (1.2 ± 0.1 mg/g tissue). This study suggests that the chitinase 1 protein with lectin-like properties is possibly induced at the protein level and can be putatively involved in the innate immune response of M. rosenbergii.

Chemical and linguistic considerations for encoding Chinese characters: an embodiment using chain-end degradable sequence-defined oligourethanes created by consecutive solid phase click chemistry

Sequence-defined polymers (SDPs) are currently being investigated for use as information storage media. As the number of monomers in the SDPs increases, with a corresponding increase in mathematical base, the use of tandem-MS for de novo sequencing becomes more challenging. In contrast, chain-end degradation routines are truly de novo, potentially allowing very large mathematical bases for encoding. While alphabetic scripts have a few dozen symbols, logographic scripts, such as Chinese, can have several thousand symbols. Using a new in situ consecutive click reaction approach on an oligourethane backbone for writing, and a previously reported chain-end degradation routine for reading, we encoded/decoded a confucius proverb written in Chinese characters using two encoding schemes: Unicode and Zhèng Mă. Unicode is an internationally standardized arbitrary string of hexadecimal (base-16) symbols which efficiently encodes uniquely identifiable symbols but requires complete fidelity of transmission, or context-based inferential strategies to be interpreted. The Zhèng Mă approach encodes with a base-26 system using the visual characteristics and internal composition of Chinese characters themselves, which leads to greater ambiguity of encoded strings, but more robust retrievability of information from partial or corrupted encodings. The application of information-encoded oligourethanes to two different encoding systems allowed us to establish their flexibility and versatility for data storage. We found the oligourethanes immensely adaptable to both encoding schemes for Chinese characters, and we highlight the expected tradeoff between the efficiency and uniqueness of Unicode encoding on the one hand, and the fidelity to a scripts' particular visual characteristics on the other.

GV1001 reduces neurodegeneration and prolongs lifespan in 3xTg-AD mouse model through anti-aging effects

GV1001, which mimics the activity of human telomerase reverse transcriptase, protects neural cells from amyloid beta (Aβ) toxicity and other stressors through extra-telomeric function, as noted in our prior in vitro studies. As per a recent phase II clinical trial, it improves cognitive function in patients with moderate to severe dementia. However, the underlying protective mechanisms remain unclear. This study aimed to investigate the effects of GV1001 on neurodegeneration, senescence, and survival in triple transgenic Alzheimer's disease (3xTg-AD) mice. GV1001 (1 mg/kg) was subcutaneously injected into old 3xTg-AD mice thrice a week until the endpoint for sacrifice, and survival was analysed. Magnetic resonance imaging (MRI) and Prussian blue staining (PBS) were performed to evaluate entry of GV1001 entrance into the brain. Diverse molecular studies were performed to investigate the effect of GV1001 on neurodegeneration and cellular senescence in AD model mice, with a particular focus on BACE, amyloid beta1-42 (Aβ1-42), phosphorylated tau, volume of dentate gyrus, β-galactosidase positive cells, telomere length, telomerase activity, and ageing-associated proteins. GV1001 crossed the blood-brain barrier, as confirmed by assessing the status of ferrocenecarboxylic acid-conjugated GV1001 using magnetic resonance imaging and PBS. GV1001 increased the survival of 3xTg-AD mice. It decreased BACE and Aβ1-42 levels, neurodegeneration (i.e., reduced CA1, CA3 and dentate gyrus volume, decreased levels of senescence-associated β-galactosidase positive cells, and increased telomere length and telomerase activity), and levels of ageing-associated proteins. We suggest that GV1001 exerts anti-ageing effects in 3xTg-AD mice by reducing neurodegeneration and senescence, which contributes to improved survival.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

Peptide-Based Mass Spectrometry for the Investigation of Protein Complexes

In the last two decades, biological mass spectrometry has become the gold standard for the identification of proteins in biological samples. The technological advancement of mass spectrometers and the development of methods for ionization, gas phase transfer, peptide fragmentation as well as for acquisition of high-resolution mass spectrometric data marked the success of the technique. This chapter introduces peptide-based mass spectrometry as a tool for the investigation of protein complexes. It provides an overview of the main steps for sample preparation starting from protein fractionation, reduction, alkylation and focus on the final step of protein digestion. The basic concepts of biological mass spectrometry as well as details about instrumental analysis and data acquisition are described. Finally, the most common methods for data analysis and sequence determination are summarized with an emphasis on its application to protein-protein complexes.

Proteomic methods for the study of porcine acute phase proteins - anything new to detect?

Acute phase proteins (APPs) reflect the health status of individuals and are important tools in diagnostics, as their altered levels are a sign of disturbed homeostasis. While, in most cases, quantitation of known serum APPs is routinely performed by immunoassays, proteomics is helpful in discovery of new biomarker candidates, especially in samples other than body fluids. Besides putting APP regulation into an overall context of differentially abundant proteins, this approach can detect further details or outright new features in protein structure or specific modifications, and help understand better their function. Thus, it can show up ways to make present diagnostic assays more sensitive and/or specific, or correlate regulations of disease-specific proteins. The APP repertoire is dependent on the species. The pig is both, an important farm animal and a model animal for human diseases, due to similarities in physiology. Besides reviewing existing literature, yet unpublished examples for two-dimensional electrophoresis in connection with pig APPs highlight some of the benefits of proteomics. Of further help would be the emerging targeted proteomics, offering the possibility to determine particular isoforms or proteoforms, without the need of specific antibodies, but this method is presently scarcely used in veterinary medicine.

Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review

Peptide sequencing is of great significance to fundamental and applied research in the fields such as chemical, biological, medicinal and pharmaceutical sciences. With the rapid development of mass spectrometry and sequencing algorithms, de-novo peptide sequencing using tandem mass spectrometry (MS/MS) has become the main method for determining amino acid sequences of novel and unknown peptides. Advanced algorithms allow the amino acid sequence information to be accurately obtained from MS/MS spectra in short time. In this review, algorithms from exhaustive search to the state-of-art machine learning and neural network for high-throughput and automated de-novo sequencing are introduced and compared. Impacts of datasets on algorithm performance are highlighted. The current limitations and promising direction of de-novo peptide sequencing are also discussed in this review.

ProtView: A Versatile Tool for In Silico Protease Evaluation and Selection in a Proteomic and Proteogenomic Context

Many tools have been created to generate in silico proteome digests with different protease enzymes and provide useful information for selecting optimal digest schemes for specific needs. This can save on time and resources and generate insights on the observable proteome. However, there remains a need for a tool that evaluates digest schemes beyond protein and amino acid coverages in the proteomic domain. Here, we present ProtView, a versatile in silico protease combination digest evaluation workflow that maps in silico-digested peptides to both protein and genome references, so that the potential observable portions of the proteome, transcriptome, and genome can be identified. The proteomic identification and quantification of evidence for transcriptional, co-transcriptional, post-transcriptional, translational, and post-translational regulation can all be examined in silico with ProtView prior to an experiment. Benchmarking against biological data comparing multiple proteases shows that ProtView can correctly estimate performances among the digest schemes. ProtView provides this information in a way that is easy to interpret, allowing for digest schemes to be evaluated before carrying out an experiment, in context that can optimize both proteomic and proteogenomic experiments. ProtView is available at https://github.com/SSPuliasis/ProtView.

Sex-Biased Expression of Genes Allocated in the Autosomal Chromosomes: Blood LC-MS/MS Protein Profiling in Healthy Subjects

BACKGROUND

Sex and gender have a large impact in human health and disease prediction. According to genomic/genetics, men differ from women by a limited number of genes in Y chromosome, while the phenotypes of the 2 sexes differ markedly.

METHODS

In this study, serum samples from six healthy Bahraini men and women were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Bioinformatics databases and tools were used for protein/peptide (PPs) identification and gene localization. The PPs that differed significantly (p < 0.05, ANOVA) in abundance with a fold change (FC) of ≥1.5 were identified.

RESULTS

Revealed 20 PPs, 11 were upregulated in women with very high FC (up to 8 folds), and 9 were upregulated in men but with much lower FC. The PPs are encoded by genes located in autosomal chromosomes, indicative of sex-biased gene expression. The only PP related to sex, the sex hormone-binding globulin, was upregulated in women. The remaining PPs were involved in immunity, lipid metabolism, gene expression, connective tissue, and others, with some overlap in function.

CONCLUSIONS

The upregulated PPs in men or women are mostly reflecting the functon or risk/protection provided by the PPs to the specific sex, e.g., Apo-B100 of LDLC. Finally, the basis of sex-biased gene expression and sex phenotypic differences needs further investigation.

Free Radical-Based Sequencing for Native Top-Down Mass Spectrometry

Native top-down proteomics allows for both proteoform identification and high-order structure characterization for cellular protein complexes. Unfortunately, tandem MS-based fragmentation efficiencies for such targets are low due to an increase in analyte ion mass and the low ion charge states that characterize native MS data. Multiple fragmentation methods can be integrated in order to increase protein complex sequence coverage, but this typically requires use of specialized hardware and software. Free-radical-initiated peptide sequencing (FRIPS) enables access to charge-remote and electron-based fragmentation channels within the context of conventional CID experiments. Here, we optimize FRIPS labeling for native top-down sequencing experiments. Our labeling approach is able to access intact complexes with TEMPO-based FRIPS reagents without significant protein denaturation or assembly disruption. By combining CID and FRIPS datasets, we observed sequence coverage improvements as large as 50% for protein complexes ranging from 36 to 106 kDa. Fragment ion production in these experiments was increased by as much as 102%. In general, our results indicate that TEMPO-based FRIPS reagents have the potential to dramatically increase sequence coverage obtained in native top-down experiments.

Bioactive Peptides: An Understanding from Current Screening Methodology

Bioactive peptides with high potency against numerous human disorders have been regarded as a promising therapy in disease control. These peptides could be released from various dietary protein sources through hydrolysis processing using physical conditions, chemical agents, microbial fermentation, or enzymatic digestions. Considering the diversity of the original proteins and the complexity of the multiple structural peptides that existed in the hydrolysis mixture, the screening of bioactive peptides will be a challenge task. Well-organized and well-designed methods are necessarily required to enhance the efficiency of studying the potential peptides. This article, hence, provides an overview of bioactive peptides with an emphasis on the current strategy used for screening and characterization methods. Moreover, the understanding of the biological activities of peptides, mechanism inhibitions, and the interaction of the complex of peptide–enzyme is commonly evaluated using specific in vitro assays and molecular docking analysis.

Targeted proteomics and specific immunoassays reveal the presence of shared allergens between the zoonotic nematodes Anisakis simplex and Pseudoterranova decipiens

The family Anisakidae, mainly represented by Anisakis simplex s.l. and Pseudoterranova decipiens, encompasses zoonotic nematodes infecting many marine fish. Both are responsible for gastrointestinal disease in humans after ingestion of a live larva by consumption of undercooked fish, and, in the case of A. simplex, an allergic reaction may occur after consuming or even handling infected fish. Due to its phylogenetic relatedness with A. simplex, few studies investigated the allergenic potential of P. decipiens, yet none of them focused on its excretory/secretory (E/S) proteins that easily get missed when working solely on extracts from crushed nematodes. Moreover, these E/S allergens remain behind even when the larva has been removed during fish quality processing. Therefore, the aim was to investigate if Anisakis-like allergens could also be detected in both crushed and E/S P. decipiens protein extract using targeted mass spectrometry analysis and immunological methods. The results confirmed that at least five A. simplex allergens have homologous proteins in P. decipiens; a result that emphasizes the importance of also including E/S protein extracts in proteomic studies. Not only A. simplex, but also P. decipiens should therefore be considered a potential source of allergens that could lead to hypersensitivity reactions in humans.

The impact of noise and missing fragmentation cleavages on de novo peptide identification algorithms

•

Most correct de novo peptides have ⩽1 missing fragmentation cleavages.

•

DeepNovo outperforms Novor for peptide accuracy for both data types.

•

Novor excels at amino acid recall when many fragmentation cleavages are missing.

•

Deep learning allows DeepNovo to predict amino acids without adjacent peaks.

Proteomics aims to characterise system-wide protein expression and typically relies on mass-spectrometry and peptide fragmentation, followed by a database search for protein identification. It has wide ranging applications from clinical to environmental settings and virtually impacts on every area of biology. In that context, de novo peptide sequencing is becoming increasingly popular. Historically its performance lagged behind database search methods but with the integration of machine learning, this field of research is gaining momentum. To enable de novo peptide sequencing to realise its full potential, it is critical to explore the mass spectrometry data underpinning peptide identification. In this research we investigate the characteristics of tandem mass spectra using 8 published datasets. We then evaluate two state of the art de novo peptide sequencing algorithms, Novor and DeepNovo, with a particular focus on their performance with regard to missing fragmentation cleavage sites and noise. DeepNovo was found to perform better than Novor overall. However, Novor recalled more correct amino acids when 6 or more cleavage sites were missing. Furthermore, less than 11% of each algorithms’ correct peptide predictions emanate from data with more than one missing cleavage site, highlighting the issues missing cleavages pose. We further investigate how the algorithms manage to correctly identify peptides with many of these missing fragmentation cleavages. We show how noise negatively impacts the performance of both algorithms, when high intensity peaks are considered. Finally, we provide recommendations regarding further algorithms’ improvements and offer potential avenues to overcome current inherent data limitations.

Campylobacter jejuni Virulence Factors Identified by Modulating Their Synthesis on Ribosomes With Altered rRNA Methylation

Campylobacter jejuni is a major cause of food poisoning worldwide, and remains the main infective agent in gastroenteritis and related intestinal disorders in Europe and the USA. As with all bacterial infections, the stages of adhesion to host tissue, survival in the host and eliciting disease all require the synthesis of proteinaceous virulence factors on the ribosomes of the pathogen. Here, we describe how C. jejuni virulence is attenuated by altering the methylation of its ribosomes to disrupt the composition of its proteome, and how this in turn provides a means of identifying factors that are essential for infection and pathogenesis. Specifically, inactivation of the C. jejuni Cj0588/TlyA methyltransferase prevents methylation of nucleotide C1920 in the 23S rRNA of its ribosomes and reduces the pathogen’s ability to form biofilms, to attach, invade and survive in host cells, and to provoke the innate immune response. Mass spectrometric analyses of C. jejuni TlyA-minus strains revealed an array of subtle changes in the proteome composition. These included reduced amounts of the cytolethal distending toxin (CdtC) and the MlaEFD proteins connected with outer membrane vesicle (OMV) production. Inactivation of the cdtC and mlaEFD genes confirmed the importance of their encoded proteins in establishing infection. Collectively, the data identify a subset of genes required for the onset of human campylobacteriosis, and serve as a proof of principle for use of this approach in detecting proteins involved in bacterial pathogenesis.

Proteomic Database Search Engine for Two-Dimensional Partial Covariance Mass Spectrometry

We present a protein database search engine for the automatic identification of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Because the 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural specificity afforded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides, the 2D-PC-MS correlation-matching procedure is based on complementary and internal ion correlations, the identification of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.

The potential for using shell proteins in gastropod systematics, assessed in patellogastropod limpets

This investigation of the application of shell protein information to gastropod systematics initially utilized available Lottia gigantea sequences and a transcriptome of Patelloida mimula developed here. Levels of differentiation between predicted sequences of reciprocal best-hit potential homologues in P. mimula and L. gigantea suggested that they could be useful within families, and possibly in higher taxa using some shell-associated proteins, particularly the peroxidases. Subsequently, proteomic analyses of the acid-soluble fraction of extractions from 17 shells and five tissue samples were conducted by combined liquid chromatography/mass spectrometry with nano-electrospray ionization. All proteins with abundance more than 1.2% in the L. gigantea shell proteome were identified with 100% confidence in most extractions by SearchGui/PeptideShaker analyses. In total, 259 of 379 peptides predicted from in silico digestion of L. gigantea shell proteins were represented by validated peptide spectrum matches in one or more specimens. Systematics applications were investigated by analysing metrics such as protein coverage by peptides and phylogenetic analyses of peptide presence/absence. The investigation suggested that diagnostic profiles based on fixed presence/absence differences can be used to separate species pairs. However, further development of analytical techniques and accumulation of reference databases is required for realising fully the systematics potential of the shell proteome.

Characteristics of Food Protein-Derived Antidiabetic Bioactive Peptides: A Literature Update

Diabetes, a glucose metabolic disorder, is considered one of the biggest challenges associated with a complex complication of health crises in the modern lifestyle. Inhibition or reduction of the dipeptidyl peptidase IV (DPP-IV), alpha-glucosidase, and protein-tyrosine phosphatase 1B (PTP-1B) enzyme activities or expressions are notably considered as the promising therapeutic strategies for the management of type 2 diabetes (T2D). Various food protein-derived antidiabetic bioactive peptides have been isolated and verified. This review provides an overview of the DPP-IV, PTP-1B, and α-glucosidase inhibitors, and updates on the methods for the discovery of DPP-IV inhibitory peptides released from food-protein hydrolysate. The finding of novel bioactive peptides involves studies about the strategy of separation fractionation, the identification of peptide sequences, and the evaluation of peptide characteristics in vitro, in silico, in situ, and in vivo. The potential of bioactive peptides suggests useful applications in the prevention and management of diabetes. Furthermore, evidence of clinical studies is necessary for the validation of these peptides’ efficiencies before commercial applications.

Effects of chronic exposure to low levels of IR on Medaka (Oryzias latipes): a proteomic and bioinformatic approach

PURPOSE

Chronic exposure to ionizing radiation (IR) at low doses (<100 mGy) has been insufficiently studied to understand fully the risk to health. Relatively little knowledge exists regarding how species and healthy tissues respond at the protein level to chronic exposure to low doses of IR, and mass spectrometric-based profiling of protein expression is a powerful tool for studying changes in protein abundance.

MATERIALS AND METHODS

SDS gel electrophoresis, LC-MS/MS mass spectrometry-based approaches and bioinformatic data analytics were used to detect proteomic changes following chronic exposure to moderate/low doses of radiation in adults and normally developed Medaka fish (Oryzias latipes).

RESULTS

Significant variations in the abundance of proteins involved in thyroid hormone signaling and lipid metabolism were detected, which could be related to the gonadal regression phenotype observed after 21.04 mGy and 204.3 mGy/day exposure. The global proteomic change was towards overexpression of proteins in muscle and skin, while the opposite effect was observed in internal organs.

CONCLUSION

The present study provides information on the impacts of biologically relevant low doses of IR, which will be useful in future research for the identification of potential biomarkers of IR exposure and allow for a better assessment of radiation biosafety regulations.

Influence of Post-Translational Modifications on Protein Identification in Database Searches

Comprehensive analysis of post-translation modifications (PTMs) is an important mission of proteomics. However, the consideration of PTMs increases the search space and may therefore impair the efficiency of protein identification. Using thousands of proteomic searches, we investigated the practical aspects of considering multiple PTMs in Byonic searches for the maximization of protein and peptide hits. The inclusion of all PTMs, which occur with at least 2% frequency in the sample, has an advantageous effect on protein and peptide identification. A linear relationship was established between the number of considered PTMs and the number of reliably identified peptides and proteins. Even though they handle multiple modifications less efficiently, the results of MASCOT (using the Percolator function) and Andromeda (the search engine included in MaxQuant) became comparable to those of Byonic, in the case of a few PTMs.

Investigation of fennel protein extracts by shot-gun Fourier transform ion cyclotron resonance mass spectrometry

A rapid shot-gun method by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is proposed for the characterization of fennel proteins. After enzymatic digestion with trypsin, few microliters of extract were analyzed by direct infusion in positive ion mode. A custom-made non-redundant fennel-specific proteome database was derived from the well-known NCBI database; additional proteins belonging to recognized allergenic sources (celery, carrot, parsley, birch, and mugwort) were also included in our database, since patients hypersensitive to these plants could also suffer from fennel allergy. The peptide sequence of each protein from that derived list was theoretically sequenced to produce calculated m/z lists of possible m/z ions after tryptic digestions. Then, by using a home-made Matlab algorithm, those lists were matched with the experimental FT-ICR mass spectrum of the fennel peptide mixture. Finally, Peptide Mass Fingerprint searches confirmed the presence of the matched proteins inside the fennel extract with a total of 70 proteins (61 fennel specific and 9 allergenic proteins).

FPTMS: Frequency-based approach to identify the peptide from the low-energy collision-induced dissociation tandem mass spectra

The database search method is a widely accepted method to assign a peptide to the tandem mass spectra. In this study, a new flexible method- FPTMS is introduced to interpret the tandem mass spectra with the known peptide sequences in a protein database. Here the frequency of occurrence of fragment ion peaks extracted from the extensive spectral library is used to predict the theoretical tandem mass spectra of the peptides. The dot product scoring and windowed-xcorr scoring methods were implemented to score the experimental spectrum against the theoretical peptide spectra. Windowed-xcorr is introduced to tackle the mass errors and the cleavage position of the fragmentation process. The new method with windowed-xcorr shows an improved identification rate compared to the existing search engines Crux-Tide and X!Tandem at 1% False Discovery Rate (FDR) for the dataset considered in this study. SIGNIFICANCE: Identifying or sequencing of the peptide from tandem mass spectra is an important application in mass spectrometry-based proteomics. Collision-induced dissociation (CID) fragmentation spectra have been widely used to develop a peptide identification algorithm using database search strategy. CID fragmentation behavior is a complex process and found to have dependency on the sequences of peptide, charge state, and residue content. The inclusion of more features of peptide fragmentation behavior and adaptable scoring algorithm improves the efficiency of the peptide identification algorithm.

Biological Applications for LC-MS-Based Proteomics

Since its inception, liquid chromatography-mass spectrometry (LC-MS) has been continuously improved upon in many aspects, including instrument capabilities, sensitivity, and resolution. Moreover, the costs to purchase and operate mass spectrometers and liquid chromatography systems have decreased, thus increasing affordability and availability in sectors outside of academic and industrial research. Processing power has also grown immensely, cutting the time required to analyze samples, allowing more data to be feasibly processed, and allowing for standardized processing pipelines. As a result, proteomics via LC-MS has become popular in many areas of biological sciences, forging an important seat for itself in targeted and untargeted assays, pure and applied science, the laboratory, and the clinic. In this chapter, many of these applications of LC-MS-based proteomics and an outline of how they can be executed will be covered. Since the field of personalized medicine has matured alongside proteomics, it has also come to rely on various mass spectrometry methods and will be elaborated upon as well. As time goes on and mass spectrometry evolves, there is no doubt that its presence in these areas, and others, will only continue to grow.

Snake venom proteome of Protobothrops mucrosquamatus in Taiwan: Delaying venom-induced lethality in a rodent model by inhibition of phospholipase A2 activity with varespladib

Protobothrops mucrosquamatus, also known as the brown spotted pit viper or Taiwanese habu, is a medically significant venomous snake in Taiwan, especially in the northern area. To more fully understand the proteome profile of P. mucrosquamatus, we characterized its venom composition using a bottom-up proteomic approach. Whole venom components were fractionated by RP-HPLC and then analyzed by SDS-PAGE. Each protein band in gels was excised and subjected to protein identification by LC-MS/MS. A subsequent proteomic analysis revealed the presence of 61 distinct proteins belonging to 19 families in P. mucrosquamatus venom. Snake venom metalloproteinase (SVMP; 29.4%), C-type lectin (CLEC; 21.1%), snake venom serine protease (SVSP; 17.6%) and phospholipase A₂ (PLA₂; 15.9%) were the most abundant protein families, whereas several low-abundance proteins, categorized into eight protein families, were demonstrated in P. mucrosquamatus venom for the first time. Because PLA₂ is known to make a major contribution to venom lethality, we evaluated whether the known PLA₂ inhibitor, varespladib, was capable of preventing the toxic effects of P. mucrosquamatus venom. This small-molecule drug demonstrated the ability to inhibit PLA₂ activity in vitro (IC₅₀ = 101.3 nM). It also blunted lethality in vivo, prolonging survival following venom injection in a mouse model, but it showed limited potency against venom-induced local hemorrhage in this model. Our findings provide essential biological and pathophysiological insights into the composition of P. mucrosquamatus venom and suggest PLA₂ inhibition as an adjunctive or alternative therapeutic strategy in the clinical management of P. mucrosquamatus envenoming in emergency medicine. SIGNIFICANCE: P. mucrosquamatus envenomation is a significant medical concern in Taiwan, especially in the northern region. Although antivenom is commonly used for rescuing P. mucrosquamatus envenoming, severe clinical events still occur, with more than 20% of cases requiring surgical intervention. Small-molecule therapy offers several advantages as a potential adjunctive, or even alternative, to antivenom treatment, such as heat stability, low antigenicity and ease of administration, among others. A deeper understanding of the venom proteome of P. mucrosquamatus would aid in the discovery of small-molecule drugs that could be repurposed to target specific venom proteins. Here, we applied a bottom-up proteomic approach to characterize the protein profile of P. mucrosquamatus venom. Varespladib, a small-molecule drug used to treat inflammatory disease, was repurposed to inhibit the toxicity of P. mucrosquamatus venom, and was shown to reduce the lethal effects of P. mucrosquamatus envenomation in a rodent model. Varespladib might be used as a first-aid therapeutic against P. mucrosquamatus envenoming in the pre-referral period and/or as an adjunctive agent administered together with anti-P. mucrosquamatus antivenom.

Differentiating Two Closely Related Alexandrium Species Using Comparative Quantitative Proteomics

Alexandrium minutum and Alexandrium tamutum are two closely related harmful algal bloom (HAB)-causing species with different toxicity. Using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics and two-dimensional differential gel electrophoresis (2D-DIGE), a comprehensive characterization of the proteomes of A. minutum and A. tamutum was performed to identify the cellular and molecular underpinnings for the dissimilarity between these two species. A total of 1436 proteins and 420 protein spots were identified using iTRAQ-based proteomics and 2D-DIGE, respectively. Both methods revealed little difference (10-12%) between the proteomes of A. minutum and A. tamutum, highlighting that these organisms follow similar cellular and biological processes at the exponential stage. Toxin biosynthetic enzymes were present in both organisms. However, the gonyautoxin-producing A. minutum showed higher levels of osmotic growth proteins, Zn-dependent alcohol dehydrogenase and type-I polyketide synthase compared to the non-toxic A. tamutum. Further, A. tamutum had increased S-adenosylmethionine transferase that may potentially have a negative feedback mechanism to toxin biosynthesis. The complementary proteomics approach provided insights into the biochemistry of these two closely related HAB-causing organisms. The identified proteins are potential biomarkers for organismal toxicity and could be explored for environmental monitoring.

A combined microphysiological-computational omics approach in dietary protein evaluation

Food security is under increased pressure due to the ever-growing world population. To tackle this, alternative protein sources need to be evaluated for nutritional value, which requires information on digesta peptide composition in comparison to established protein sources and coupling to biological parameters. Here, a combined experimental and computational approach is presented, which compared seventeen protein sources with cow’s whey protein concentrate (WPC) as the benchmark. In vitro digestion of proteins was followed by proteomics analysis and statistical model-based clustering. Information on digesta peptide composition resulted in 3 cluster groups, primarily driven by the peptide overlap with the benchmark protein WPC. Functional protein data was then incorporated in the computational model after evaluating the effects of eighteen protein digests on intestinal barrier integrity, viability, brush border enzyme activity, and immune parameters using a bioengineered intestine as microphysiological gut system. This resulted in 6 cluster groups. Biological clustering was driven by viability, brush border enzyme activity, and significant differences in immune parameters. Finally, a combination of proteomic and biological efficacy data resulted in 5 clusters groups, driven by a combination of digesta peptide composition and biological effects. The key finding of our holistic approach is that protein source (animal, plant or alternative derived) is not a driving force behind the delivery of bioactive peptides and their biological efficacy.

Advances in venomics: Modern separation techniques and mass spectrometry

Snake venoms are complex chemical mixtures of biologically active proteins and non-protein components. Toxins have a wide range of targets and effects to include ion channels and membrane receptors, and platelet aggregation and platelet plug formation. Toxins target these effectors and effects at high affinity and selectivity. From a pharmacological perspective, snake venom compounds are a valuable resource for drug discovery and development. However, a major challenge to drug discovery using snake venoms is isolating and analyzing the bioactive proteins and peptides in these complex mixtures. Getting molecular information from complex mixtures such as snake venoms requires proteomic analyses, generally combined with transcriptomic analyses of venom glands. The present review summarizes current knowledge and highlights important recent advances in venomics with special emphasis on contemporary separation techniques and bioinformatics that have begun to elaborate the complexity of snake venoms. Several analytical techniques such as two-dimensional gel electrophoresis, RP-HPLC, size exclusion chromatography, ion exchange chromatography, MALDI-TOF-MS, and LC-ESI-QTOF-MS have been employed in this regard. The improvement of separation approaches such as multidimensional-HPLC, 2D-electrophoresis coupled to soft-ionization (MALDI and ESI) mass spectrometry has been critical to obtain an accurate picture of the startling complexity of venoms. In the case of bioinformatics, a variety of software tools such as PEAKS also has been used successfully. Such information gleaned from venomics is important to both predicting and resolving the biological activity of the active components of venoms, which in turn is key for the development of new drugs based on these venom components.

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists.

Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer

Endometrial cancer is the most common malignancy of the female genital tract and its incidence is rising in parallel with the mounting prevalence of obesity. Early diagnosis has great potential to improve outcomes as treatment can be curative, especially for early stage disease. Current tests and procedures for diagnosis are limited by insufficient accuracy in some and unacceptable levels of invasiveness and discomfort in others. There has, therefore, been a growing interest in the search for sensitive and specific biomarkers for endometrial cancer detection based on non-invasive sampling methodologies. Urine, the prototype non-invasive sample, is attractive for biomarker discovery as it is easily accessible and can be collected repeatedly and in quantity. Identification of urinary biomarkers for endometrial cancer detection relies on the excretion of systemic biomarkers by the kidneys or urinary contamination by biomarkers shed from the uterus. In this review, we present the current standing of the search for endometrial cancer urinary biomarkers based on cytology, genomic, transcriptomic, proteomic, and metabolomic platforms. We summarize the biomarker candidates and highlight the challenges inherent in urinary biomarker discovery. We review the various technologies with promise for biomarker detection and assess these novel approaches for endometrial cancer biomarker research.

De novo sequencing of proteins by mass spectrometry

INTRODUCTION

Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed.

AREAS COVERED

De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data.

EXPERT OPINION

As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

Shotgun EM of mycobacterial protein complexes during stationary phase stress

There is little structural information about the protein complexes conferring resistance in Mycobacterium tuberculosis (Mtb) to anti-microbial oxygen and nitrogen radicals in the phagolysosome. Here, we expose the model Mycobacterium, Mycobacterium smegmatis, to simulated oxidative-stress conditions and apply a shotgun EM method for the structural detection of the resulting protein assemblies. We identified: glutamine synthetase I, essential for Mtb virulence; bacterioferritin A, critical for Mtb iron regulation; aspartyl aminopeptidase M18, a protease; and encapsulin, which produces a cage-like structure to enclose cargo proteins. After further investigation, we found that encapsulin carries dye-decolourising peroxidase, a protein antioxidant, as its primary cargo under the conditions tested.

Wild and Cultivated Species of Rice Have Distinctive Proteomic Responses to Drought

Drought often compromises yield in non-irrigated crops such as rainfed rice, imperiling the communities that depend upon it as a primary food source. In this study, two cultivated species (Oryza sativa cv. Nipponbare and Oryza glaberrima cv. CG14) and an endemic, perennial Australian wild species (Oryza australiensis) were grown in soil at 40% field capacity for 7 d (drought). The hypothesis was that the natural tolerance of O. australiensis to erratic water supply would be reflected in a unique proteomic profile. Leaves from droughted plants and well-watered controls were harvested for label-free quantitative shotgun proteomics. Physiological and gene ontology analysis confirmed that O. australiensis responded uniquely to drought, with superior leaf water status and enhanced levels of photosynthetic proteins. Distinctive patterns of protein accumulation in drought were observed across the O. australiensis proteome. Photosynthetic and stress-response proteins were more abundant in drought-affected O. glaberrima than O. sativa, and were further enriched in O. australiensis. In contrast, the level of accumulation of photosynthetic proteins decreased when O. sativa underwent drought, while a narrower range of stress-responsive proteins showed increased levels of accumulation. Distinctive proteomic profiles and the accumulated levels of individual proteins with specific functions in response to drought in O. australiensis indicate the importance of this species as a source of stress tolerance genes.

A comparison of proteomic, genomic, and osteological methods of archaeological sex estimation

Sex estimation of skeletons is fundamental to many archaeological studies. Currently, three approaches are available to estimate sex-osteology, genomics, or proteomics, but little is known about the relative reliability of these methods in applied settings. We present matching osteological, shotgun-genomic, and proteomic data to estimate the sex of 55 individuals, each with an independent radiocarbon date between 2,440 and 100 cal BP, from two ancestral Ohlone sites in Central California. Sex estimation was possible in 100% of this burial sample using proteomics, in 91% using genomics, and in 51% using osteology. Agreement between the methods was high, however conflicts did occur. Genomic sex estimates were 100% consistent with proteomic and osteological estimates when DNA reads were above 100,000 total sequences. However, more than half the samples had DNA read numbers below this threshold, producing high rates of conflict with osteological and proteomic data where nine out of twenty conditional DNA sex estimates conflicted with proteomics. While the DNA signal decreased by an order of magnitude in the older burial samples, there was no decrease in proteomic signal. We conclude that proteomics provides an important complement to osteological and shotgun-genomic sex estimation.

Visualisation tools for dependent peptide searches to support the exploration of in vitro protein modifications

Dependent peptide searching is a method for discovering covalently-modified peptides-and therefore proteins-in mass-spectrometry-based proteomics experiments. Being more permissive than standard search methods, it has the potential to discover novel modifications (e.g., post-translational modifications occurring in vivo, or modifications introduced in vitro). However, few studies have explored dependent peptide search results in an untargeted way. In the present study, we sought to evaluate dependent peptide searching as a means of characterising proteins that have been modified in vitro. We generated a model data set by analysing N-ethylmaleimide-treated bovine serum albumin, and performed dependent peptide searches using the popular MaxQuant software. To facilitate interpretation of the search results (hundreds of dependent peptides), we developed a series of visualisation tools (R scripts). We used the tools to assess the diversity of putative modifications in the albumin, and to pinpoint hypothesised modifications. We went on to explore the tools' generality via analyses of public data from studies of rat and human proteomes. Of 19 expected sites of modification (one in rat cofilin-1 and 18 across six different human plasma proteins), eight were found and correctly localised. Apparently, some sites went undetected because chemical enrichment had depleted necessary analytes (potential 'base' peptides). Our results demonstrate (i) the ability of the tools to provide accurate and informative visualisations, and (ii) the usefulness of dependent peptide searching for characterising in vitro protein modifications. Our model data are available via PRIDE/ProteomeXchange (accession number PXD013040).

Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry

Background

Reliable high-throughput microbial pathogen identification in human urine samples is crucial for patients with cystitis symptoms. Currently employed methods are time-consuming and could lead to unnecessary or inadequate antibiotic treatment. Purpose of this study was to assess the potential of mass spectrometry for uropathogen identification from a native urine sample.

Methods

In total, 16 urine samples having more than 10⁵ CFU/mL were collected from clinical outpatients. These samples were analysed using standard urine culture methods, followed by 16S rRNA gene sequencing serving as control and here described culture-independent MALDI-TOF/TOF MS method being tested.

Results

Here we present advantages and disadvantages of bottom-up proteomics, using MALDI-TOF/TOF tandem mass spectrometry, for culture-independent identification of uropathogens (e.g. directly from urine samples). The direct approach provided reliable identification of bacteria at the genus level in monobacterial samples. Taxonomic identifications obtained by proteomics were compared both to standard urine culture test used in clinics and genomic test based on 16S rRNA sequencing.

Conclusions

Our findings indicate that mass spectrometry has great potential as a reliable high-throughput tool for microbial pathogen identification in human urine samples. In this case, the MALDI-TOF/TOF, was used as an analytical tool for the determination of bacteria in urine samples, and the results obtained emphasize high importance of storage conditions and sample preparation method impacting reliability of MS2 data analysis. The proposed method is simple enough to be utilized in existing clinical settings and is highly suitable for suspected single organism infectious etiologies. Further research is required in order to identify pathogens in polymicrobial urine samples.

Variability in protein cargo detection in technical and biological replicates of exosome-enriched extracellular vesicles

Exosomes are extracellular vesicles (EVs) of ~20-200 nm diameter that shuttle DNAs, RNAs, proteins and other biomolecules between cells. The large number of biomolecules present in exosomes demands the frequent use of high-throughput analysis. This, in turn, requires technical replicates (TRs), and biological replicates (BRs) to produce accurate results. As the number and abundance of identified biomolecules varies between replicates (Rs), establishing the replicate variability predicted for the event under study is essential in determining the number of Rs required. Although there have been few reports of replicate variability in high throughput biological data, none of them focused on exosomes. Herein, we determined the replicate variability in protein profiles found in exosomes released from 3 lung adenocarcinoma cell lines, H1993, A549 and H1975. Since exosome isolates are invariably contaminated by a small percentage of ~200-300 nm microvesicles, we refer to our samples as exosome-enriched EVs (EE-EVs). We generated BRs of EE-EVs from each cell line, and divided each group into 3 TRs. All Rs were analyzed by liquid chromatography/mass spectrometry (LC/MS/MS) and customized bioinformatics and biostatistical workflows (raw data available via ProteomeXchange: PXD012798). We found that the variability among TRs as well as BRs, was largely qualitative (protein present or absent) and higher among BRs. By contrast, the quantitative (protein abundance) variability was low, save for the H1975 cell line where the quantitative variability was significant. Importantly, our replicate strategy identified 90% of the most abundant proteins, thereby establishing the utility of our approach.

Lys-Sequencer: An algorithm for de novo sequencing of peptides by paired single residue transposed Lys-C and Lys-N digestion coupled with high-resolution mass spectrometry

RATIONALE

Database-dependent identification of proteins by mass spectrometry is well established, but has limitations when there are novel proteins, mutations, splice variants, and post-translational modifications (PTMs) not available in the established reference database. De novo sequencing as a database-independent approach could address these limitations by deducing peptide sequences directly from experimental tandem mass spectrometry spectra, while concomitantly yielding residue-by-residue confidence metrics.

METHODS

Equal amounts of bovine serum albumin (BSA) sample aliquots were digested separately with Lys-C and Lys-N complementary peptidases, separated by reversed-phase ultra-high-performance liquid chromatography (UPLC), and analyzed by collision-induced dissociation (CID)-based mass spectrometry on an Orbitrap mass spectrometer. In the Lys-Sequencer algorithm, matched tandem mass spectra with equal precursor ion mass from complementary digestions were paired, and fragment ion types were identified based on the unique mass relationship between fragment ions extracted from a spectrum pair followed by de novo sequencing of peptides with identification confidence assigned at the residue level.

RESULTS

In all the matched spectrum pairs, 34 top-ranked BSA peptides were identified, from which 391 amino acid residues were identified correctly, covering ~67% of the full sequence of BSA (583 residues) with only ~6% (35 residues) exhibiting ambiguity in the sequence order (although amino acid compositions were still correctly assigned). Of note, this approach identified peptide sequences up to 17 amino acids in length without ambiguity, with the exception of the N-terminal or C-terminal peptides containing lysine (18-mer).

CONCLUSIONS

The algorithm ("Lys-Sequencer") developed in this work achieves high precision for de novo sequencing of peptides. This method facilitates the identification of point mutation and new PTMs in the protein characterization and discovery of new peptides and proteins with varying levels of confidence.

EPIFANY: A Method for Efficient High-Confidence Protein Inference

Accurate protein inference in the presence of shared peptides is still one of the key problems in bottom-up proteomics. Most protein inference tools employing simple heuristic inference strategies are efficient but exhibit reduced accuracy. More advanced probabilistic methods often exhibit better inference quality but tend to be too slow for large data sets. Here, we present a novel protein inference method, EPIFANY, combining a loopy belief propagation algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate that EPIFANY combines the reliable protein inference of Bayesian methods with significantly shorter runtimes. On the 2016 iPRG protein inference benchmark data, EPIFANY is the only tested method that finds all true-positive proteins at a 5% protein false discovery rate (FDR) without strict prefiltering on the peptide-spectrum match (PSM) level, yielding an increase in identification performance (+10% in the number of true positives and +14% in partial AUC) compared to previous approaches. Even very large data sets with hundreds of thousands of spectra (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with EPIFANY within minutes. The increased inference quality including shared peptides results in better protein inference results and thus increased robustness of the biological hypotheses generated. EPIFANY is available as open-source software for all major platforms at https://OpenMS.de/epifany.

Mass spectral analysis of acetylated peptides: Implications in proteomics

Sequence determination of peptides using mass spectrometry plays a crucial role in the bottom-up approaches for the identification of proteins. It is crucially important to minimise false detection and validate sequence of the peptides in order to correctly identify a protein. Chemical modification of peptides followed by mass spectrometry is an option for improving the spectral quality. In silico-derived tryptic peptides with different N-terminal amino acids were designed from human proteins and synthesized. The effect of acetylation on the fragmentation of peptides was studied. N-terminal acetylation of the tryptic peptides was shown to form b₁-ions, improve the abundance and occurrence of b-ions. In some cases, the intensity and occurrence of some y-ions also varied. Thus, it is demonstrated that acetylation plays an important role in improving the de novo sequencing efficiency of the peptides. The acetylation method was extended to tryptic peptides generated from the proteome of an Antarctic bacterium Pseudomonas syringae Lz4W using the proteomics work flow and mass spectra of the peptides were analysed. Comparison of the MS/MS spectra of the acetylated and unacetylated peptides revealed that acetylation helped in improving the spectral quality and validated the peptide sequences. Using this method, 673 proteins of the 1070 proteins identified were validated.

Sequencing of Sequence-Defined Oligourethanes via Controlled Self-Immolation

Sequence-defined polymers show promise for biomimetics, self-assembly, catalysis, and information storage, wherein the primary structure begets complex chemical processes. Here we report the solution-phase and the high-yielding solid-phase syntheses of discrete oligourethanes and methods for their self-immolative sequencing, resulting in rapid and robust characterization of this class of oligomers and polymers, without the use of MS/MS. Crucial to the sequencing is the inherent reactivity of the terminal alcohol to "unzip" the oligomers, in a controlled and iterative fashion, releasing each monomer as a 2-oxazolidinone. By monitoring the self-immolation reaction via LC/MS, an applied algorithm rapidly produces the sequence of the oligourethane. Not only does this process provide characterization of structurally complex molecules, it works as a reader of molecular information.

Proteomics approach and techniques in identification of reliable biomarkers for diseases

Biomarkers, also called biological markers, are indicators to identify a biological case or situation as well as detecting any presence of biological activities and processes. Proteins are considered as a type of biomarkers based on their characteristics. Therefore, proteomics approach is one of the most promising approaches in this field. The purpose of this review is to summarize the use of proteomics approach and techniques to identify proteins as biomarkers for different diseases. This review was obtained by searching in a computerized database. So, different researches and studies that used proteomics approach to identify different biomarkers for different diseases were reviewed. Also, techniques of proteomics that are used to identify proteins as biomarkers were collected. Techniques and methods of proteomics approach are used for the identification of proteins' activities and presence as biomarkers for different types of diseases from different types of samples. There are three essential steps of this approach including: extraction and separation of proteins, identification of proteins, and verification of proteins. Finally, clinical trials for new discovered biomarker or undefined biomarker would be on.

Serum extracellular vesicles contain SPARC and LRG1 as biomarkers of colon cancer and differ by tumour primary location

BACKGROUND

Recently, the distinction between left- and right-sided colon cancer (LCC and RCC) has been brought into focus. RCC is associated with an inferior overall survival and progression-free survival. We aimed to perform a detailed analysis of the diversity of extracellular vesicles (EV) between LCC and RCC using quantitative proteomics and to identify for new diagnostic and prognostic biomarkers.

METHODS

We isolated EVs from patients with LCC, RCC and healthy volunteers, and treated colorectal cancer cell line with serum-derived EVs. We then performed a quantitative proteomics analysis of the serum-derived EVs and cell line treated with EVs. Proteomic data are available via ProteomeXchange with the identifiers PXD012283 and PXD012304. In addition, we assessed the performance of EV SPARC and LRG1 as diagnosis and prognosis biomarkers in colon cancer.

FINDINGS

The expression profile of the serum EV proteome in patients with RCC was different from that of patients with LCC. Serum-derived EVs in RCC promoted cellular mobility more significantly than EVs derived from LCC. EV SPARC and LRG1 expression levels demonstrated area under the receiver-operating characteristic curve values of 0.95 and 0.93 for discriminating patients with colon cancer from healthy controls. Moreover, the expression levels of SPARC and LRG1 correlated with tumour sidedness and were predictive of tumour recurrence.

INTERPRETATION

We identified differences in EV protein profiles between LCC and RCC. Serum-derived EVs of RCC may promote metastasis via upregulation of extracellular matrix (ECM)-related proteins, especially SPARC and LRG1, which may serve as diagnosis and prognosis biomarkers in colon cancer.

A Multiple Protease Strategy to Optimise the Shotgun Proteomics of Mature Medicinal Cannabis Buds

Earlier this year we published a method article aimed at optimising protein extraction from mature buds of medicinal cannabis for trypsin-based shotgun proteomics (Vincent, D., et al. Molecules2019, 24, 659). We then developed a top-down proteomics (TDP) method (Vincent, D., et al. Proteomes2019, 7, 33). This follow-up study aims at optimising the digestion of medicinal cannabis proteins for identification purposes by bottom-up and middle-down proteomics (BUP and MDP). Four proteases, namely a mixture of trypsin/LysC, GluC, and chymotrypsin, which target different amino acids (AAs) and therefore are orthogonal and cleave proteins more or less frequently, were tested both on their own as well as sequentially or pooled, followed by nLC-MS/MS analyses of the peptide digests. Bovine serum albumin (BSA, 66 kDa) was used as a control of digestion efficiency. With this multiple protease strategy, BSA was reproducibly 97% sequenced, with peptides ranging from 0.7 to 6.4 kD containing 5 to 54 AA residues with 0 to 6 miscleavages. The proteome of mature apical buds from medicinal cannabis was explored more in depth with the identification of 27,123 peptides matching 494 unique accessions corresponding to 229 unique proteins from Cannabis sativa and close relatives, including 130 (57%) additional annotations when the list is compared to that of our previous BUP study (Vincent, D., et al. Molecules2019, 24, 659). Almost half of the medicinal cannabis proteins were identified with 100% sequence coverage, with peptides composed of 7 to 91 AA residues with up to 9 miscleavages and ranging from 0.6 to 10 kDa, thus falling into the MDP domain. Many post-translational modifications (PTMs) were identified, such as oxidation, phosphorylations, and N-terminus acetylations. This method will pave the way for deeper proteome exploration of the reproductive organs of medicinal cannabis, and therefore for molecular phenotyping within breeding programs.

Purification and characterization of proteins in multifloral honey from kelulut bee (stingless bee)

The kelulut bee (Meliponini) is a subfamily of stingless bees that produce honey. A total of 89 species out of a total of 500 species of kelulut bees are known to originate from the Indo-Australian region. Kelulut bees do not have quality standards so they still refer to the Codex and EU Directive which basically only applied for Apis honey. The Codex and EU Directive are formed by several psychochemical parameters, one of it is diastase activity. Diastase activity in kelulut honey is known not to meet existing standards or even undetectable. Therefore, this study aimed to explore proteins inside kelulut honey and investigate the possibility of using a specific protein as a biomarker to differentiate honey produced by kelulut bee from other honey. This research can also be considered as an initial step to optimize the exploration of protein in kelulut honey. This research is divided into two sections which are the preliminary research and the research expansion. From preliminary section, glucose dehydrogenase enzyme (GDH) was found to be present inside Tetragonula spp honey. A further examination of GDH enzyme was made in four kelulut bee honeys namely Tetragonula leaviceps, T. biroi, Heterotrigona itama, and Geniotrigona thoracica. The preliminary research has five stages that are exactly the as expansion research section except it didn't include GDH activity measurement. The research includes seven main stages. First honeys were dialyzed to remove the sugar content followed by centrifugation. The samples were then purified using liquid chromatography with anion exchanger column. The molecular weight of proteins was analysed by SDS-PAGE method. The GDH activity was measured using spectrophotometer followed by qualitative analysis using LC-MS/MS. The peptide sequences resulted from LC-MS/MS were then matched with Uniprot to identify the unknow protein. The results showed that only T. biroi and T. laeviceps had GDH enzyme activity of 0,1891 U/mL and 0,1652-1,579 U/mL, respectively. Bands from both species were also qualitatively identified as GDH. With these results, it can be concluded that the GDH enzyme cannot be used as a biomarker to distinguish the kelulut honey.