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.

A non-lethal method for studying scorpion venom gland transcriptomes, with a review of potentially suitable taxa to which it can be applied

Scorpion venoms are mixtures of proteins, peptides and small molecular compounds with high specificity for ion channels and are therefore considered to be promising candidates in the venoms-to-drugs pipeline. Transcriptomes are important tools for studying the composition and expression of scorpion venom. Unfortunately, studying the venom gland transcriptome traditionally requires sacrificing the animal and therefore is always a single snapshot in time. This paper describes a new way of generating a scorpion venom gland transcriptome without sacrificing the animal, thereby allowing the study of the transcriptome at various time points within a single individual. By comparing these venom-derived transcriptomes to the traditional whole-telson transcriptomes we show that the relative expression levels of the major toxin classes are similar. We further performed a multi-day extraction using our proposed method to show the possibility of doing a multiple time point transcriptome analysis. This allows for the study of patterns of toxin gene activation over time a single individual, and allows assessment of the effects of diet, season and other factors that are known or likely to influence intraindividual venom composition. We discuss the gland characteristics that may allow this method to be successful in scorpions and provide a review of other venomous taxa to which this method may potentially be successfully applied.

PopCover-2.0. Improved Selection of Peptide Sets With Optimal HLA and Pathogen Diversity Coverage

The use of minimal peptide sets offers an appealing alternative for design of vaccines and T cell diagnostics compared to conventional whole protein approaches. T cell immunogenicity towards peptides is contingent on binding to human leukocyte antigen (HLA) molecules of the given individual. HLA is highly polymorphic, and each variant typically presents a different repertoire of peptides. This polymorphism combined with pathogen diversity challenges the rational selection of peptide sets with broad immunogenic potential and population coverage. Here we propose PopCover-2.0, a simple yet highly effective method, for resolving this challenge. The method takes as input a set of (predicted) CD8 and/or CD4 T cell epitopes with associated HLA restriction and pathogen strain annotation together with information on HLA allele frequencies, and identifies peptide sets with optimal pathogen and HLA (class I and II) coverage. PopCover-2.0 was benchmarked on historic data in the context of HIV and SARS-CoV-2. Further, the immunogenicity of the selected SARS-CoV-2 peptides was confirmed by experimentally validating the peptide pools for T cell responses in a panel of SARS-CoV-2 infected individuals. In summary, PopCover-2.0 is an effective method for rational selection of peptide subsets with broad HLA and pathogen coverage. The tool is available at https://services.healthtech.dtu.dk/service.php?PopCover-2.0.

ChimST: An Efficient Spectral Library Search Tool for Peptide Identification from Chimeric Spectra in Data-Dependent Acquisition

Accurate and sensitive identification of peptides from MS/MS spectra is a very challenging problem in computational shotgun proteomics. To tackle this problem, spectral library search has been one of the competitive solutions. However, most existing library search tools were developed on the basis of one peptide per spectrum, which prevents them from working properly on chimeric spectra where two or more peptides are co-fragmented. In this work, we present a new library search tool called ChimST, which is particularly capable of reliably identifying multiple peptides from a chimeric spectrum. It starts with associating each query MS/MS spectrum with MS precursor features. For each precursor feature, there is a list of peptide candidates extracted from an input spectral library. Then, it takes one peptide candidate from each associated feature and scores how well they could collectively interpret the query spectrum. The highest-scoring set of peptide candidates are finally reported as the identification of the query spectrum. Our experimental tests show that ChimST could significantly outperform the three state-of-the-art library search tools, SpectraST, reSpect, and MSPLIT, in terms of the numbers of both peptide-spectrum matches and unique peptides, especially when the acquisition isolation window is broad.

New developments in RiPP discovery, enzymology and engineering

Covering: up to June 2020Ribosomally-synthesized and post-translationally modified peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 described the emerging commonalities in the biosynthesis of RiPPs and the opportunities they offered for bioengineering and genome mining. Since then, the field has seen tremendous advances in understanding of the mechanisms by which nature assembles these compounds, in engineering their biosynthetic machinery for a wide range of applications, and in the discovery of entirely new RiPP families using bioinformatic tools developed specifically for this compound class. The First International Conference on RiPPs was held in 2019, and the meeting participants assembled the current review describing new developments since 2013. The review discusses the new classes of RiPPs that have been discovered, the advances in our understanding of the installation of both primary and secondary post-translational modifications, and the mechanisms by which the enzymes recognize the leader peptides in their substrates. In addition, genome mining tools used for RiPP discovery are discussed as well as various strategies for RiPP engineering. An outlook section presents directions for future research.

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.

Visualizing the agreement of peptide assignments between different search engines

There is a trend in the analysis of shotgun proteomics data that aims to combine information from multiple search engines to increase the number of peptide annotations in an experiment. Typically, the degree of search engine complementarity and search engine agreement is visually illustrated by means of Venn diagrams that present the findings of a database search on the level of the nonredundant peptide annotations. We argue this practice to be not fit-for-purpose since the diagrams do not take into account and often conceal the information on complementarity and agreement at the level of the spectrum identification. We promote a new type of visualization that provides insight on the peptide sequence agreement at the level of the peptide-spectrum match (PSM) as a measure of consensus between two search engines with nominal outcomes. We applied the visualizations and percentage sequence agreement to an in-house data set of our benchmark organism, Caenorhabditis elegans, and illustrated that when assessing the agreement between search engine, one should disentangle the notion of PSM confidence and PSM identity. The visualizations presented in this manuscript provide a more informative assessment of pairs of search engines and are made available as an R function in the Supporting Information.

Genome-wide analysis and transcript profiling of PSKR gene family members in Oryza sativa

Peptide signalling is an integral part of cell-to-cell communication which helps to relay the information responsible for coordinating cell proliferation and differentiation. Phytosulfokine Receptor (PSKR) is a transmembrane LRR-RLK family protein with a binding site for small signalling peptide, phytosulfokine (PSK). PSK signalling through PSKR promotes normal growth and development and also plays a role in defense responses. Like other RLKs, these PSKRs might have a role in signal transduction pathways related to abiotic stress responses. Genome-wide analysis of phytosulfokine receptor gene family has led to the identification of fifteen putative members in the Oryza sativa genome. The expression analysis of OsPSKR genes done using RNA-seq data, showed that these genes were differentially expressed in different tissues and responded specifically to heat, salt, drought and cold stress. Furthermore, the real-time quantitative PCR for fifteen OsPSKR genes revealed temporally and spatially regulated gene expression corresponding to salinity and drought stress. Our results provide useful information for a better understanding of OsPSKR genes and provide the foundation for additional functional exploration of the rice PSKR gene family in development and stress response.

Speeding Up Percolator

The processing of peptide tandem mass spectrometry data involves matching observed spectra against a sequence database. The ranking and calibration of these peptide-spectrum matches can be improved substantially using a machine learning postprocessor. Here, we describe our efforts to speed up one widely used postprocessor, Percolator. The improved software is dramatically faster than the previous version of Percolator, even when using relatively few processors. We tested the new version of Percolator on a data set containing over 215 million spectra and recorded an overall reduction to 23% of the running time as compared to the unoptimized code. We also show that the memory footprint required by these speedups is modest relative to that of the original version of Percolator.

In-Search Assignment of Monoisotopic Peaks Improves the Identification of Cross-Linked Peptides

Cross-linking/mass spectrometry has undergone a maturation process akin to standard proteomics by adapting key methods such as false discovery rate control and quantification. A poorly evaluated search setting in proteomics is the consideration of multiple (lighter) alternative values for the monoisotopic precursor mass to compensate for possible misassignments of the monoisotopic peak. Here, we show that monoisotopic peak assignment is a major weakness of current data handling approaches in cross-linking. Cross-linked peptides often have high precursor masses, which reduces the presence of the monoisotopic peak in the isotope envelope. Paired with generally low peak intensity, this generates a challenge that may not be completely solvable by precursor mass assignment routines. We therefore took an alternative route by '"in-search assignment of the monoisotopic peak" in the cross-link database search tool Xi (Xi-MPA), which considers multiple precursor masses during database search. We compare and evaluate the performance of established preprocessing workflows that partly correct the monoisotopic peak and Xi-MPA on three publicly available data sets. Xi-MPA always delivered the highest number of identifications with ∼2 to 4-fold increase of PSMs without compromising identification accuracy as determined by FDR estimation and comparison to crystallographic models.

Screening, large-scale production and structure-based classification of cystine-dense peptides

Peptides folded through interwoven disulfides display extreme biochemical properties and unique medicinal potential. However, their exploitation has been hampered by the limited amounts isolatable from natural sources and the expense of chemical synthesis. We developed reliable biological methods for high-throughput expression, screening and large-scale production of these peptides: 46 were successfully produced in multimilligram quantities, and >600 more were deemed expressible through stringent screening criteria. Many showed extreme resistance to temperature, proteolysis and/or reduction, and all displayed inhibitory activity against at least 1 of 20 ion channels tested, thus confirming their biological functionality. Crystal structures of 12 confirmed proper cystine topology and the utility of crystallography to study these molecules but also highlighted the need for rational classification. Previous categorization attempts have focused on limited subsets featuring distinct motifs. Here we present a global definition, classification and analysis of >700 structures of cystine-dense peptides, providing a unifying framework for these molecules.

Immuno-informatics driven proteome-wide investigation revealed novel peptide-based vaccine targets against emerging multiple drug resistant Providencia stuartii

The bacterium Providencia stuartii, is associated with urinary tract infections and is the most common cause of purple urine bag syndrome. The increasing multi-drug resistance pattern shown by the pathogen and lack of licensed vaccines make treatment of infections caused by P. stuartii challenging. As vaccinology data against the pathogen is scarce, an in silico proteome based Reverse Vaccinology (RV) protocol, in combination with subtractive proteomics is introduced in this work to screen potential vaccine candidates against P. stuartii. The analysis identified three potential vaccine candidates for designing broad-spectrum and strain-specific peptide vaccines: FimD4, FimD6, and FimD8. These proteins are essential for pathogen survival, localized in the outer membrane, virulent, and antigenic in nature. Immunoproteomic tools mapped surface exposed and non-allergenic 9mer B-cell derived T-cell antigenic epitopes for the proteins. The epitopes also show stable and rich interactions with the most predominant HLA allele (DRB1*0101) in the human population. Metabolic pathway annotation of the proteins indicated that fimbrial biogenesis outer membrane usher protein (FimD6) is the most suitable candidate for vaccine design, due to its involvement in several significant pathways. These pathways include: the bacterial secretion system, two-component system, β-lactam resistance, and cationic antimicrobial peptide pathways. The predicted epitopes may provide a basis for designing a peptide-based vaccine against P. stuartii.

Follow-up on the characterization of peptidic markers in hair and fur for the identification of common North American species

RATIONALE

Species identification of hair is routinely done by microscopic analysis. Following previous studies that used protein analysis to characterize species markers in hair and wool, the present work aims at covering a larger number of species and to ultimately offer a method for rapid hair identification in forensics and archaeology.

METHODS

Hair is mostly made of alpha-keratins; these proteins have only been sequenced in a handful of species and most animal families are under-represented. Using a methodology developed for the characterization of peptidic markers in tissues such as bone (peptide mass fingerprinting or PMF) and commonly applied on collagen, hair from common North American fur-bearing species was analyzed by MALDI-TOF-MS to obtain peptidic profiles.

RESULTS

Alpha-keratin peptides that are typically dominant on peptide mass profiles of hair were chosen as markers. Matching peaks were identified for each species tested and compared to known sequences from related organisms whenever possible. The markers were used to create a flowchart to narrow down identification to the family level.

CONCLUSIONS

The methodology was developed on a limited numbers of markers chosen for their variability and reliability on the peptide mass fingerprint. In the absence of genetic sequences, this strategy is a quick way to compare species from a common geographic origin. The work presented here was focused on North American species but could be applied to other animal families.

Spider Neurotoxins, Short Linear Cationic Peptides and Venom Protein Classification Improved by an Automated Competition between Exhaustive Profile HMM Classifiers

Spider venoms are rich cocktails of bioactive peptides, proteins, and enzymes that are being intensively investigated over the years. In order to provide a better comprehension of that richness, we propose a three-level family classification system for spider venom components. This classification is supported by an exhaustive set of 219 new profile hidden Markov models (HMMs) able to attribute a given peptide to its precise peptide type, family, and group. The proposed classification has the advantages of being totally independent from variable spider taxonomic names and can easily evolve. In addition to the new classifiers, we introduce and demonstrate the efficiency of hmmcompete, a new standalone tool that monitors HMM-based family classification and, after post-processing the result, reports the best classifier when multiple models produce significant scores towards given peptide queries. The combined used of hmmcompete and the new spider venom component-specific classifiers demonstrated 96% sensitivity to properly classify all known spider toxins from the UniProtKB database. These tools are timely regarding the important classification needs caused by the increasing number of peptides and proteins generated by transcriptomic projects.

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.

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 %.

Class I and Class II Lanthipeptides Produced by Bacillus spp

The increasing number of multidrug-resistant pathogens, along with the small number of new antimicrobials under development, leads to an increased need for novel alternatives. Class I and class II lanthipeptides (also known as lantibiotics) have been considered promising alternatives to classical antibiotics. In addition to their relevant medical applications, they are used as probiotics, prophylactics, preservatives, and additives in cosmetics and personal-care products. The genus Bacillus is a prolific source of bioactive compounds including ribosomally and nonribosomally synthesized antibacterial peptides. Accordingly, there is significant interest in the biotechnological potential of members of the genus Bacillus as producers of antimicrobial lanthipeptides. The present review focuses on aspects of the biosynthesis, gene cluster organization, structure, antibacterial spectrum, and bioengineering approaches of lanthipeptides produced by Bacillus strains. Their efficacy and potency against some clinically relevant strains, including MRSA and VRE, are also discussed. Although no lanthipeptides are currently in clinical use, the information herein highlights the potential of these compounds.

Genome-wide analyses and functional classification of proline repeat-rich proteins: potential role of eIF5A in eukaryotic evolution

The eukaryotic translation factor, eIF5A has been recently reported as a sequence-specific elongation factor that facilitates peptide bond formation at consecutive prolines in Saccharomyces cerevisiae, as its ortholog elongation factor P (EF-P) does in bacteria. We have searched the genome databases of 35 representative organisms from six kingdoms of life for PPP (Pro-Pro-Pro) and/or PPG (Pro-Pro-Gly)-encoding genes whose expression is expected to depend on eIF5A. We have made detailed analyses of proteome data of 5 selected species, Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster, Mus musculus and Homo sapiens. The PPP and PPG motifs are low in the prokaryotic proteomes. However, their frequencies markedly increase with the biological complexity of eukaryotic organisms, and are higher in newly derived proteins than in those orthologous proteins commonly shared in all species. Ontology classifications of S. cerevisiae and human genes encoding the highest level of polyprolines reveal their strong association with several specific biological processes, including actin/cytoskeletal associated functions, RNA splicing/turnover, DNA binding/transcription and cell signaling. Previously reported phenotypic defects in actin polarity and mRNA decay of eIF5A mutant strains are consistent with the proposed role for eIF5A in the translation of the polyproline-containing proteins. Of all the amino acid tandem repeats (≥3 amino acids), only the proline repeat frequency correlates with functional complexity of the five organisms examined. Taken together, these findings suggest the importance of proline repeat-rich proteins and a potential role for eIF5A and its hypusine modification pathway in the course of eukaryotic evolution.

Origin of chordate peptides by horizontal protozoan gene transfer in early metazoans and protists: evolution of the teneurin C-terminal associated peptides (TCAP)

The teneurin C-terminal associated peptides (TCAP) are found at the extracellular face in C-terminal region of the teneurin transmembrane proteins. One of these peptides, TCAP-1 is independently transcribed as a smaller bioactive peptide that possesses a number of stress response-attenuating activities. The teneurin-TCAP system appears to be the result of a horizontal gene transfer from a prokaryotic proteinaceous polymorphic toxin to a choanoflagellate. In a basal metazoan, the TCAP region has been modified from a toxin to a soluble intercellular signaling system. New studies indicate that the teneurin-TCAP system form a complex signaling system associated with adhesion, cytoskeletal regulation and intracellular signaling. TCAP-1 is highly conserved in all vertebrates and in mammals, inhibits corticotropin-releasing factor (CRF)-associated stress. Using the TCAP-teneurin system as a model, it is likely that numerous peptide systems in the Chordata began as a result of horizontal gene transfer from prokaryotes early in metazoan ancestry.

Transcriptional profiles of mating-responsive genes from testes and male accessory glands of the Mediterranean fruit fly, Ceratitis capitata

BACKGROUND

Insect seminal fluid is a complex mixture of proteins, carbohydrates and lipids, produced in the male reproductive tract. This seminal fluid is transferred together with the spermatozoa during mating and induces post-mating changes in the female. Molecular characterization of seminal fluid proteins in the Mediterranean fruit fly, Ceratitis capitata, is limited, although studies suggest that some of these proteins are biologically active.

METHODOLOGY/PRINCIPAL FINDINGS

We report on the functional annotation of 5914 high quality expressed sequence tags (ESTs) from the testes and male accessory glands, to identify transcripts encoding putative secreted peptides that might elicit post-mating responses in females. The ESTs were assembled into 3344 contigs, of which over 33% produced no hits against the nr database, and thus may represent novel or rapidly evolving sequences. Extraction of the coding sequences resulted in a total of 3371 putative peptides. The annotated dataset is available as a hyperlinked spreadsheet. Four hundred peptides were identified with putative secretory activity, including odorant binding proteins, protease inhibitor domain-containing peptides, antigen 5 proteins, mucins, and immunity-related sequences. Quantitative RT-PCR-based analyses of a subset of putative secretory protein-encoding transcripts from accessory glands indicated changes in their abundance after one or more copulations when compared to virgin males of the same age. These changes in abundance, particularly evident after the third mating, may be related to the requirement to replenish proteins to be transferred to the female.

CONCLUSIONS/SIGNIFICANCE

We have developed the first large-scale dataset for novel studies on functions and processes associated with the reproductive biology of Ceratitis capitata. The identified genes may help study genome evolution, in light of the high adaptive potential of the medfly. In addition, studies of male recovery dynamics in terms of accessory gland gene expression profiles and correlated remating inhibition mechanisms may permit the improvement of pest management approaches.

ClassAMP: a prediction tool for classification of antimicrobial peptides

Antimicrobial peptides (AMPs) are gaining popularity as anti-infective agents. Information on sequence features that contribute to target specificity of AMPs will aid in accelerating drug discovery programs involving them. In this study, an algorithm called ClassAMP using Random Forests (RFs) and Support Vector Machines (SVMs) has been developed to predict the propensity of a protein sequence to have antibacterial, antifungal, or antiviral activity. ClassAMP is available at http://www.bicnirrh.res.in/classamp/.

Peptide reranking with protein-peptide correspondence and precursor peak intensity information

Searching tandem mass spectra against a protein database has been a mainstream method for peptide identification. Improving peptide identification results by ranking true Peptide-Spectrum Matches (PSMs) over their false counterparts leads to the development of various reranking algorithms. In peptide reranking, discriminative information is essential to distinguish true PSMs from false PSMs. Generally, most peptide reranking methods obtain discriminative information directly from database search scores or by training machine learning models. Information in the protein database and MS1 spectra (i.e., single stage MS spectra) is ignored. In this paper, we propose to use information in the protein database and MS1 spectra to rerank peptide identification results. To quantitatively analyze their effects to peptide reranking results, three peptide reranking methods are proposed: PPMRanker, PPIRanker, and MIRanker. PPMRanker only uses Protein-Peptide Map (PPM) information from the protein database, PPIRanker only uses Precursor Peak Intensity (PPI) information, and MIRanker employs both PPM information and PPI information. According to our experiments on a standard protein mixture data set, a human data set and a mouse data set, PPMRanker and MIRanker achieve better peptide reranking results than PetideProphet, PeptideProphet+NSP (number of sibling peptides) and a score regularization method SRPI. The source codes of PPMRanker, PPIRanker, and MIRanker, and all supplementary documents are available at our website: http://bioinformatics.ust.hk/pepreranking/. Alternatively, these documents can also be downloaded from: http://sourceforge.net/projects/pepreranking/.

New insights into the neuroanatomical distribution and phylogeny of opioids and POMC-derived peptides in fish

This review re-evaluates the use of immunological probes to map enkephalinergic, dynorphinergic, and endorphinergic circuits in the CNS of lobe-finned fishes, ray-finned fishes, and cartilaginous fishes in light of the characterization of proenkephalin, prodynorphin, and POMC sequences from representatives of these groups of fish over the past 20 years. The use of α-MSH specific antisera is a reliable method for detecting POMC immunopositive cell bodies and fibers. Since α-MSH and β-endorphin are co-localized in the same neurons, these studies also reveal the distribution of endorphinergic networks. Met-enkephalin specific antisera can be used to detect enkephalinergic circuits in the CNS of gnathostomes because of the ubiquitous presence of this pentapeptide in the proenkephalin sequences of gnathostomes. However, the use of leu-enkephalin specific antisera to detect enkephalinergic networks is more problematic. While this immunological probe is appropriate for analyzing enkephalinergic networks in mammals and perhaps teleosts, for the lungfishes and cartilaginous fishes this probe is more likely able to detect dynorphinergic circuits. In this regard, there is a need to re-examine dynorphinergic networks in non-mammalian gnathostomes by using species specific antisera directed against dynorphin end-products.

[Dynamic hierarchy of regulatory peptides. Structure of the induction relations of regulators as the target for therapeutic agents]

Based on the database information (literature period 1970-2010 gg.) on the effects of regulatory peptides (RP) and non-peptide neurotransmitters (dopamine, serotonin, norepi-nephrine, acetylcholine) it was analyzed of possible cascade processes of endogenous regulators. It was found that the entire continuum of RP and mediators is a chaotic soup of the ordered three-level compartments. Such a dynamic functional hierarchy of endogenous regulators allows to create start-up and corrective tasks for a variety of physiological functions. Some examples of static and dynamic patterns of induction processes of RP and mediators (that regulate the states of anxiety, depression, learning and memory, feeding behavior, reproductive processes, etc.) are considered.

A new multigene superfamily of Kunitz-type protease inhibitors from sea anemone Heteractis crispa

Despite a considerable number of publications devoted to isolation and physicochemical properties of protease inhibitors from sea anemones, virtually nothing is known about the structure of the genes, and the nature of their isoforms diversity. Using the PCR-based cloning approach we discovered the Kunitz-type multigene superfamily composed of distinct gene families (GS-, RG-, GG-, and GN-gene families). It has been identified only three full-length GS-transcripts indicating a much greater variety of Kunitz homologs in Heteractis crispa. We have examined an exon-intron structure of GS-genes; an open reading frame is interrupted by a single intron located at the middle of the signal peptide. 33 deduced mature GS-polypeptides have been categorized into three groups according to the nature of a P1 residue. Some of them corresponded to native Kunitz-type protease inhibitors earlier isolated from H. crispa. The deduced GS-polypeptide sequences demonstrated diverse charge distribution ranging from the local point charges forms to the overall positive ones. We have suggested that the GS-gene family has evolved through gene tandem duplication followed by adaptive divergence of the P1 residue in the reactive site selected for divergent functions in paralogs. The expansion of this Kunitz-type multigene superfamily during evolution is lineage-specific, providing the tropical sea anemone H. crispa with the ability to interact an increasing diversity of the preys and predators. Our results show that the Kunitz-type polypeptides are encoded by a multigene superfamily and realized via a combinatory Kunitz-type library in the H. crispa tentacles venom.

[Antimicrobial factors of hemolymph and excretion of larvae Lucilia sericata (meigen) (diptera, calliphoridae)]

The present study deals with molecular nature and peculiarities of functioning of two main protective systems of larvae Lucilia sericata--the antimicrobial compounds of hemolymph and of the excretion released by feeding larvae into environmental. There are identified a number of inducible antibacterial peptides including defensins (3844, 4062, and 4117 Da), P-peptide (3043 Da), and four new polypeptides (3235, 3702, 3746, and 3768 Da) In hemolymph of the larvae submitted to bacterial infestation, by the chromatomasspectrometry methods. The excretion of larvae Lucilia sericata contains peptides analogous or identical to hemolymph antibacterial peptides (diptericins: 8882 Da and 9025 Da), high molecular compounds of peptide nature (6466 Da, 6633 Da, 5772 Da, 8631 Da, etc.) differing from the known hemolymph components and low molecular compounds (130-700 Da). Spectrum of excretion bactericidal activity includes various groups of bacterial including the most actual pathogen from medical point of view--the meticillin-resistant Staphylococcus aureus, unlike the hemolymph that does not have antistaphylococcal activity. The excretion components suppressing growth and development of this staphylococcus are represented by substances of the low molecular nature (from 160 to 1020 Da). The performed studies characterize the strategies used by "surgical maggots" for protection from pathogens and for suppression of microbial competitors and allow better understanding of molecular mechanisms of larval therapy of purulent infectious diseases. These studies in perspective can serve the basis for creation of the principally new drugs for struggle with usual and antibiotics-resistant bacterial infections.

PAComplex: a web server to infer peptide antigen families and binding models from TCR-pMHC complexes

One of the most adaptive immune responses is triggered by specific T-cell receptors (TCR) binding to peptide-major histocompatibility complexes (pMHC). Despite the availability of many prediction servers to identify peptides binding to MHC, these servers are often lacking in peptide-TCR interactions and detailed atomic interacting models. PAComplex is the first web server investigating both pMHC and peptide-TCR interfaces to infer peptide antigens and homologous peptide antigens of a query. This server first identifies significantly similar TCR-pMHC templates (joint Z-value ≥ 4.0) of the query by using antibody-antigen and protein-protein interacting scoring matrices for peptide-TCR and pMHC interfaces, respectively. PAComplex then identifies the homologous peptide antigens of these hit templates from complete pathogen genome databases (≥10(8) peptide candidates from 864,628 protein sequences of 389 pathogens) and experimental peptide databases (80,057 peptides in 2287 species). Finally, the server outputs peptide antigens and homologous peptide antigens of the query and displays detailed interacting models (e.g. hydrogen bonds and steric interactions in two interfaces) of hitTCR-pMHC templates. Experimental results demonstrate that the proposed server can achieve high prediction accuracy and offer potential peptide antigens across pathogens. We believe that the server is able to provide valuable insights for the peptide vaccine and MHC restriction. The PAComplex sever is available at http://PAcomplex.life.nctu.edu.tw.

[Towards the estimation of survival curves parameters and geroprotectors classification]

The following parameters are proposed to estimate in survival curves analysis: Median Life Span, Hill slope, Expected Maximal Life Span. Those estimates enable to classify geroprotectors as weak, moderate and strong.

Divergent M- and O-superfamily peptides from venom of fish-hunting Conus parius

Six novel peptides from the piscivorous cone snail, Conus parius were purified by reverse-phase HPLC fractionation of crude venom. With the use of matrix-assisted laser desorption ionization mass spectrometry and standard Edman sequencing methods, the peptides were characterized. Two peptides were identified as members of the m-2 and m-4 branches of the M-superfamily and were designated as pr3a and pr3b, while four peptides were identified as members of the O-superfamily and were designated as pr6a, pr6b, pr6c and pr6d. Peptide pr3a differs from the majority of the M-superfamily peptides in the presence of two prolines, which are not modified to 4-trans-hydroxyproline. In peptide pr3b, five amino acids out of the 16 non-cysteine residues are identical with those of mu-GIIIA and mu-PIIIA, suggesting that pr3b may be a divergent mu-conotoxin. Peptide pr6a is notable because of its extreme hydrophobicity. Peptide pr6c has three prolines that are unhydroxylated. Peptides pr6b and pr6d differ from the previously characterized O-superfamily peptides in the presence of an extended N-terminus consisting of six amino acids. Peptides pr3a, pr3b, pr6a and pr6b were demonstrated to be biologically active when injected intraperitoneally in fish. The identification and characterization of these peptides in venom of a fish-hunting species establish the divergence of gene products and their patterns of post-translational modification within superfamilies in a single Conus species.

Competition between Phytophthora infestans effectors leads to increased aggressiveness on plants containing broad-spectrum late blight resistance

BACKGROUND

The destructive plant disease potato late blight is caused by the oomycete pathogen Phytophthora infestans (Mont.) de Bary. This disease has remained particularly problematic despite intensive breeding efforts to integrate resistance into cultivated potato, largely because of the pathogen's ability to quickly evolve to overcome major resistance genes. The RB gene, identified in the wild potato species S. bulbocastanum, encodes a protein that confers broad-spectrum resistance to most P. infestans isolates through its recognition of highly conserved members of the corresponding pathogen effector family IPI-O. IpiO is a multigene family of effectors and while the majority of IPI-O proteins are recognized by RB to elicit host resistance, some variants exist that are able to elude detection (e.g. IPI-O4).

METHODS AND FINDINGS

In the present study, analysis of ipiO variants among 40 different P. infestans isolates collected from Guatemala, Thailand, and the United States revealed a high degree of complexity within this gene family. Isolate aggressiveness was correlated with increased ipiO diversity and especially the presence of the ipiO4 variant. Furthermore, isolates expressing IPI-O4 overcame RB-mediated resistance in transgenic potato plants even when the resistance-eliciting IPI-O1 variant was present. In support of this finding, we observed that expression of IPI-O4 via Agrobacterium blocked recognition of IPI-O1, leading to inactivation of RB-mediated programmed cell death in Nicotiana benthamiana.

CONCLUSIONS

In this study we definitively demonstrate and provide the first evidence that P. infestans can defeat an R protein through inhibition of recognition of the corresponding effector protein.

Peri- and postnatal rodent development of Hematide, an erythropoiesis-stimulating agent

BACKGROUND

Aperi- and postnatal reproduction toxicity study was conducted in rats treated with Hematide, a synthetic PEGylated peptidic erythropoiesis stimulating agent (ESA).

METHODS

Hematide, at IV doses of 0, 0.5, 3, and 15 mg/kg, was administered from implantation through lactation on gestation days (GDs) 5 and 18 and lactation day (LD) 13.

RESULTS

Hematide induced pronounced polycythemia in all Hematide-treated dams. On LDs 2 and 21, hemoglobin (Hgb) increases above control levels were 3.1, 5.2, and 5.0 g/dL and 4.1, 5.1, and 5.5 g/dL at the 0.5, 3, and 15 mg/kg/dose, respectively. There were no effects on parturition, lactation, or maternal behavior in the F0 generation female rats. A slight decrease in pup viability on postpartum days 2-4 and lower body weights and/or body weight gain for the F1 generation were associated with pronounced polycythemia and decreases in maternal body weight gain and/or food consumption at > or =3 mg/kg/dose. Hematide fetal exposure was negligible. No Hematide effect, other than on growth and survival, was noted on developmental, functional, mating, and fertility end points in the F1 generation rats, and no effect on litter or fetal parameters was observed in the F2 generation. The maternal no-observed-adverse-effect level (NOAEL) for Hematide was 0.5 mg/kg, and the NOAEL for parturition and maternal behavior was 15 mg/kg. The NOAEL for F1 pup viability and growth was 0.5 mg/kg/dose.

CONCLUSIONS

In conclusion, the Hematide-associated adverse findings were attributed to exaggerated erythropoiesis (pronounced and prolonged polycythemia) resulting from administration of an ESA to pregnant animals.

Purification and molecular cloning of antimicrobial peptides from Scots pine seedlings

A novel protocol for rapid and efficient purification of antimicrobial peptides from plant seedlings has been developed. Two peptides with antimicrobial activity, designated p1 and p2, were purified nearly to homogeneity from Scots pine seedlings by a combination of sulfuric acid extraction, ammonium sulfate precipitation, heat-inactivation and ion-exchange chromatography on phosphocellulose. Purified proteins had molecular masses of 11 kDa (p1) and 5.8 kDa (p2) and were identified by mass spectrometry as defensin and lipid-transfer protein, respectively. We demonstrated their growth inhibitory effects against a group of phytopathogenic fungi. Furthermore, we report for the first time molecular cloning and characterization of defensin 1 cDNA from Scots pine. A cDNA expression library from 7 days Scots pine seedlings was generated and used to isolate a cDNA clone corresponding to Scots pine defensin, termed PsDef1. The full-length coding sequence of PsDef1 is 252 bp in length and has an open reading frame capable to encode a protein of 83 amino residues. The deduced sequence has the typical features of plant defensins, including an endoplasmic reticulum signal sequence of 33aa, followed by a characteristic defensin domain of 50 amino acids representing its active form. The calculated molecular weight of the mature form of PsDef1 is 5601.6 Da, which correlates well with the results of SDS-PAGE analysis. Finally, the antimicrobial properties of PsDef1 against a panel of fungi and bacteria define it as a member of the morphogenic group of plant defensins.

Identification of novel I-superfamily conopeptides from several clades of Conus species found in the South China Sea

The I-superfamily of Conus peptides represents a new class of peptides with four disulfide bridges (-C-C-CC-CC-C-C-) that falls into three (I1, I2 and I3) categories according to the different signal peptide sequences. The I-superfamily has received increasing attention because it targets K+ ion channels, a function that is relatively rare in conotoxins. Herein we report 11 novel I-superfamily conotoxins from the venom ducts of five Cone snails (Conus eburneus, Conus imperialis, Conus vitulinus, Conus emaciatus and Conus litteratus) native to the South China Sea using a primer designed according to the N-terminus of the signal sequence of I2-superfamily conotoxins. The alignment of sequences revealed that signal regions exhibited moderate conservation with the exception of Eb11.3 from C. eburneus with homologies of 21.1%, 38.5% and 30.0% to the signal peptides of I1, I2 and I3 superfamily conotoxins, respectively. The mature peptides ranged from almost identical to highly divergent between species. Analyses of the evolutionary trees of these peptides with those of reported I-superfamily conotoxins showed that nine of them fall in I2 superfamily clades, but two of them were neither I1- and I2- nor I3-superfamily clades. Notably, some peptides exhibited significantly different amino acid residues in the intercysteine loops compared with group A, B and C of I-superfamily conopeptides, suggesting that they may have different bioactivities and functions.

In silico structure-based design of a novel class of potent and selective small peptide inhibitor of Mycobacterium tuberculosis Dihydrofolate reductase, a potential target for anti-TB drug discovery

The worldwide TB structural genomics initiative has identified several new drug targets for Mycobacterium tuberculosis (M. tb). Dihydrofolate reductase (DHFR) catalyzes the NADPH-dependent reduction of dihydrofolate to tetrahydrofolate that is essential for DNA synthesis. Inhibition of its activity leads to arrest of DNA synthesis and hence cell death. Thus, M. tb DHFR (mtDHFR) is an attractive novel drug target for developing anti-TB drugs. Structural comparison of mtDHFR and human DHFR (hDHFR) reveals key differences in the active sites. These differences can be exploited for the design of selective inhibitors for mtDHFR. Based on the recently determined high resolution crystal structure of mtDHFR complexed with known inhibitor methotrexate (MTX) and cofactor NADPH, a tri-peptide inhibitor has been identified using a structure-based drug design approach. Docking studies indicate that the designed tripeptide inhibitor has a high potency (K (d) = 1.78 nM) and is a selective (approximately 120 fold over hDHFR) inhibitor for mtDHFR. Hence, the tripeptide is a suitable lead compound for the development of novel anti-TB drugs.

Plant peptides in signalling: looking for new partners

A novel candidate ligand-receptor system, INFLORESCENCE DEFICIENT IN ABSCISSION (IDA) and the related receptor-like kinases (RLKs) HAESA (HAE) and HAESA-LIKE (HSL)2, has been shown to control floral abscission in Arabidopsis thaliana. Furthermore, several IDA-LIKE (IDL) proteins, which contain a conserved C-terminal domain resembling that of the CLAVATA (CLV)3-ENDOSPERM SURROUNDING REGION (ESR)-RELATED (CLE) protein family, have been shown to be partially redundant with IDA. Here, we use the genetic similarities between the IDA and CLV3 signalling systems to hypothesize that closely related peptide ligands are likely to interact with families of closely related RLKs. Guided by this hypothesis and with the aid of genetics and novel methods, ligand-receptor systems can be identified to improve our understanding of developmental processes in plants.

Support vector machines for improved peptide identification from tandem mass spectrometry database search

Accurate identification of peptides is a current challenge in mass spectrometry (MS)-based proteomics. The standard approach uses a search routine to compare tandem mass spectra to a database of peptides associated with the target organism. These database search routines yield multiple metrics associated with the quality of the mapping of the experimental spectrum to the theoretical spectrum of a peptide. The structure of these results make separating correct from false identifications difficult and has created a false identification problem. Statistical confidence scores are an approach to battle this false positive problem that has led to significant improvements in peptide identification. We have shown that machine learning, specifically support vector machine (SVM), is an effective approach to separating true peptide identifications from false ones. The SVM-based peptide statistical scoring method transforms a peptide into a vector representation based on database search metrics to train and validate the SVM. In practice, following the database search routine, a peptide is denoted in its vector representation and the SVM generates a single statistical score that is then used to classify presence or absence in the sample.

Mass-based classification (MBC) of peptides: highly accurate precursor ion mass values can be used to directly recognize peptide phosphorylation

Accurate mass values as obtainable by Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) were employed in a theoretical study to differentiate between nonmodified and phosphorylated peptides. It was found that for peptide masses up to 1,000 u more than 98% of all theoretical monophosphorylated peptides (all possible combinations of proteinogenic amino acids having one phosphorylation on S, T, or Y) can be distinguished from nonphosphorylated peptides directly by their mass, if mass values are determined with an accuracy of better than +/-0.1 ppm. At a peptide mass of 1,500 u still 70% of all possible monophosphorylated peptides are distinguishable from nonmodified peptides by their accurate mass alone. In contrast to established techniques of data-dependent multidimensional mass spectrometry, only the mass of the precursor ion is necessary to decide upon subsequent fragment ion analysis of a peptide for sequence analysis in an LC-MS/MS investigation of a complex sample, when using a precalculated mass distribution table of theoretical peptides. A mass distribution table of nonphosphorylated and monophosphorylated peptides with a bin width of 0.1 mu was made available via the open web site www.peptidecomposer.com.

A consistent nomenclature of antimicrobial peptides isolated from frogs of the subfamily Phyllomedusinae

A growing number of cationic antimicrobial peptides have been isolated from the skin of hylid frogs belonging to the Phyllomedusinae subfamily. The amino acid sequences of these peptides are currently located in several databases under identifiers with no consistent system of nomenclature to describe them. In order to provide a workable terminology for antimicrobial peptides from Phyllomedusid frogs, we have made a systematic effort to collect, analyze, and classify all the Phyllomedusid peptide sequences available in databases. We propose that frogs belonging to the Phyllomedusinae subfamily should be described by the species names set out in Amphibian Species of the World: http://research.amnh.org/herpetology/amphibia/index.php, American Museum of Natural History, New York, USA. Multiple alignments analysis of at least 80 antimicrobial peptides isolated from 12 Phyllomedusinae species were distributed in seven distinct peptide families including dermaseptin, phylloseptin, plasticin, dermatoxin, phylloxin, hyposin and orphan peptides, and will be considered as the name of the headgroup of each family. The parent peptide's name should be followed by the first upper letter of the species for orthologous peptides and publication date determines priority. For example, the abbreviation B for bicolor and H for hypochondrialis. When two species begin with the same letter, two letters in upper case should be used (the first letter followed by the second or the third letter and so on). For example, the abbreviation DI for distincta, DU for duellmani, VA for vaillanti and VN for vanzolinii. Paralogous peptides should bear letter(s) in upper case followed by numbers.

Identification and characterization of novel reptile cathelicidins from elapid snakes

Three cDNA sequences coding for elapid cathelicidins were cloned from constructed venom gland cDNA libraries of Naja atra, Bungarus fasciatus and Ophiophagus hannah. The open reading frames of the cloned elapid cathelicidins were all composed of 576bp and coded for 191 amino acid residue protein precursors. Each of the deduced elapid cathelicidin has a 22 amino acid residue signal peptide, a conserved cathelin domain of 135 amino acid residues and a mature antimicrobial peptide of 34 amino acid residues. Unlike the highly divergent cathelicidins in mammals, the nucleotide and deduced protein sequences of the three cloned elapid cathelicidins were remarkably conserved. All the elapid mature cathelicidins were predicted to be cleaved at Valine157 by elastase. OH-CATH, the deduced mature cathelicidin from king cobra, was chemically synthesized and it showed strong antibacterial activity against various bacteria with minimal inhibitory concentration of 1-20microg/ml in the presence of 1% NaCl. Meanwhile, the synthetic peptide showed no haemolytic activity toward human red blood cells even at a high dose of 200microg/ml. Phylogenetic analysis of cathelicidins from vertebrate suggested that elapid and viperid cathelicidins were grouped together in the tree. Snake cathelicidins were evolutionary closely related to the neutrophilic granule proteins (NGPs) from mouse, rat and rabbit. Snake cathelicidins also showed a close relationship with avian fowlicidins (1-3) and chicken myeloid antimicrobial peptide 27. Elapid cathelicidins might be used as models for the development of novel therapeutic drugs.

Detection of co-eluted peptides using database search methods

BACKGROUND

Current experimental techniques, especially those applying liquid chromatography mass spectrometry, have made high-throughput proteomic studies possible. The increase in throughput however also raises concerns on the accuracy of identification or quantification. Most experimental procedures select in a given MS scan only a few relatively most intense parent ions, each to be fragmented (MS2) separately, and most other minor co-eluted peptides that have similar chromatographic retention times are ignored and their information lost.

RESULTS

We have computationally investigated the possibility of enhancing the information retrieval during a given LC/MS experiment by selecting the two or three most intense parent ions for simultaneous fragmentation. A set of spectra is created via superimposing a number of MS2 spectra, each can be identified by all search methods tested with high confidence, to mimick the spectra of co-eluted peptides. The generated convoluted spectra were used to evaluate the capability of several database search methods - SEQUEST, Mascot, X!Tandem, OMSSA, and RAId_DbS - in identifying true peptides from superimposed spectra of co-eluted peptides. We show that using these simulated spectra, all the database search methods will gain eventually in the number of true peptides identified by using the compound spectra of co-eluted peptides.

OPEN PEER REVIEW

Reviewed by Vlad Petyuk (nominated by Arcady Mushegian), King Jordan and Shamil Sunyaev. For the full reviews, please go to the Reviewers' comments section.

Correlation of circulating CD133+ progenitor subclasses with a mild phenotype in Duchenne muscular dystrophy patients

Background

Various prognostic serum and cellular markers have been identified for many diseases, such as cardiovascular diseases and tumor pathologies. Here we assessed whether the levels of certain stem cells may predict the progression of Duchenne muscular dystrophy (DMD).

Methods and Findings

The levels of several subpopulations of circulating stem cells expressing the CD133 antigen were determined by flow cytometry in 70 DMD patients. The correlation between the levels and clinical status was assessed by statistical analysis. The median (±SD) age of the population was 10.66±3.81 (range 3 to 20 years). The levels of CD133+CXCR4+CD34- stem cells were significantly higher in DMD patients compared to healthy controls (mean±standard deviation: 17.38±1.38 vs. 11.0±1.70; P = 0.03) with a tendency towards decreased levels in older patients. Moreover, the levels of this subpopulation of cells correlated with the clinical condition. In a subgroup of 19 DMD patients after 24 months of follow-up, increased levels of CD133+CXCR4+CD34- cells was shown to be associated with a phenotype characterised by slower disease progression. The circulating CD133+CXCR4+CD34- cells in patients from different ages did not exhibit significant differences in their myogenic and endothelial in vitro differentiation capacity.

Conclusions

Our results suggest that levels of CD133+CXCR4+CD34- could function as a new prognostic clinical marker for the progression of DMD.

Peptide fingerprinting of snake venoms by direct infusion nano-electrospray ionization mass spectrometry: potential use in venom identification and taxonomy

Fingerprinting by mass spectrometry has been increasingly used to study venom variations and for taxonomic analyses based on venom components. Most of these studies have concentrated on components heavier than 3 kDa, but Bothrops snake venoms contain many biologically active peptides, principally C-type natriuretic peptides and bradykinin-potentiating peptides (BPPs). In this work, we have examined the peptide profile of Bothrops venoms (B. alternatus, B. erythromelas, B. insularis, B. jararaca, B. jararacussu, B. leucurus and B. moojeni) using direct infusion nano-electrospray ionization mass spectrometry (nano-ESI-MS) subjecting the data further to principal components analysis (PCA) to assess whether the peptide distributions are reliable in distinguishing the venoms. ESI-MS of a low molar mass fraction obtained by ultrafiltration of each venom (5 kDa nominal cutoff filters) revealed that the venoms have a variety of peptides in common but that each venom also contains taxonomic marker peptides not shared with other venoms. One BPP peptide, QGGWPRPGPEIPP, was found to be common to the seven Bothrops species examined. This peptide may represent a specific marker for this genus since it was not found in the venom of the South American rattlesnake, Crotalus durissus terrificus. PCA on the ESI-MS data reveals a close relationship between B. jararaca, B. jararacussu and B. moojeni venoms, with B. leucurus and B. erythromelas being more distant from these three; B. alternatus and B. insularis were also located distant from these five species, as was C. d. terrificus. These results agree partially with established phylogenetic relationships among these species and suggest that ESI-MS peptide fingerprinting of snake venoms coupled with PCA is a useful tool for identifying venoms and for taxonomic analyses.

1-(1-Arylethylidene)thiosemicarbazide derivatives: a new class of tyrosinase inhibitors

A series of 1-(1-arylethylidene)thiosemicarbazide compounds and their analogues were synthesized and characterized by 1H NMR, MS. Their tyrosinase inhibitory activities were investigated by an assay based on the catalyzing ability of tyrosinase for the oxidation of L-DOPA, comparing with 4-methoxycinnamic acid and arbutin. The results showed that (1) all the synthesized compounds could perform a significant inhibitory activity for tyrosinase; (2) for these compounds, the main active moiety interacting with the center of tyrosinase would be thiosemicarbazo group; (3) the inhibitory activity was close related with thiosemicarbazide moieties and the groups attached on the aromatic ring.

The middle-molecule hypothesis 30 years after: lost and rediscovered in the universe of uremic toxicity?

The present review gives an overview of the known and newly detected middle molecules and their biological potential. Since many middle molecules were shown to affect leukocyte, endothelial cell, smooth muscle cell and/or thrombocyte function, the likelihood of their role in cardiovascular damage related to renal failure is described. In addition, the middle-molecule behaviour during dialysis is commented. The impact of dialytic removal by diffusion or convection in clinical studies is extensively discussed reflecting the benefit on patient survival and/or clinical outcome. The continuing search for new culprits will result in therapeutic options including improved removal of uremic solutes and/or the search for pharmacological strategies blocking responsible pathophysiological pathways.

Peptide bioinformatics: peptide classification using peptide machines

Peptides scanned from whole protein sequences are the core information for many peptide bioinformatics research such as functional site prediction, protein structure identification, and protein function recognition. In these applications, we normally need to assign a peptide to one of the given categories using a computer model. They are therefore referred to as peptide classification applications. Among various machine learning approaches, including neural networks, peptide machines have demonstrated excellent performance in many applications. This chapter discusses the basic concepts of peptide classification, commonly used feature extraction methods, three peptide machines, and some important issues in peptide classification.

Statistical identification of differentially labeled peptides from liquid chromatography tandem mass spectrometry

LC-MS/MS with certain labeling techniques such as isotope-coded affinity tag (ICAT) enables quantitative analysis of paired protein samples. However, current identification and quantification of differentially expressed peptides (and proteins) are not reliable for large proteomics screening of complex biological samples. The number of replicates is often limited because of the high cost of experiments and the limited supply of samples. Traditionally, a simple fold change cutoff is used, which results in a high rate of false positives. Standard statistical methods such as the two-sample t-test are unreliable and severely underpowered due to high variability in LC-MS/MS data, especially when only a small number of replicates are available. Using an advanced error pooling technique, we propose a novel statistical method that can reliably identify differentially expressed proteins while maintaining a high sensitivity, particularly with a small number of replicates. The proposed method was applied both to an extensive simulation study and a proteomics comparison between microparticles (MPs) generated from platelet (platelet MPs) and MPs isolated from plasma (plasma MPs). In these studies, we show a significant improvement of our statistical analysis in the identification of proteins that are differentially expressed but not detected by other statistical methods. In particular, several important proteins - two peptides for beta-globin and three peptides for von Willebrand Factor (vWF) - were identified with very small false discovery rates (FDRs) by our method, while none was significant when other conventional methods were used. These proteins have been reported with their important roles in microparticles in human blood cells: vWF is a platelet and endothelial cell product that binds to P-selectin, GP1b, and GP IIb/IIIa, and beta-globin is one of the peptides of hemoglobin involved in the transportation of oxygen by red blood cells.

Autologous transplantation of muscle-derived CD133+ stem cells in Duchenne muscle patients

Duchenne muscular dystrophy (DMD) is a lethal X-linked recessive muscle disease due to defect on the gene encoding dystrophin. The lack of a functional dystrophin in muscles results in the fragility of the muscle fiber membrane with progressive muscle weakness and premature death. There is no cure for DMD and current treatment options focus primarily on respiratory assistance, comfort care, and delaying the loss of ambulation. Recent works support the idea that stem cells can contribute to muscle repair as well as to replenishment of the satellite cell pool. Here we tested the safety of autologous transplantation of muscle-derived CD133+ cells in eight boys with Duchenne muscular dystrophy in a 7-month, double-blind phase I clinical trial. Stem cell safety was tested by measuring muscle strength and evaluating muscle structures with MRI and histological analysis. Timed cardiac and pulmonary function tests were secondary outcome measures. No local or systemic side effects were observed in all treated DMD patients. Treated patients had an increased ratio of capillary per muscle fibers with a switch from slow to fast myosin-positive myofibers.