Unique Peptide Sequences Research Articles

Isolation, Virtual Screening, and Evaluation of Hazelnut-Derived Immunoactive Peptides for the Inhibition of SARS-CoV-2 Main Protease.

The aim of this study is to validate the activity of hazelnut (Corylus avellana L.)-derived immunoactive peptides inhibiting the main protease (Mpro) of SARS-CoV-2 and further unveil their interaction mechanism using in vitro assays, molecular dynamics (MD) simulations, and binding free energy calculations. In general, the enzymatic hydrolysis components, especially molecular weight < 3 kDa, possess good immune activity as measured by the proliferation ability of mouse splenic lymphocytes and phagocytic activity of mouse peritoneal macrophages. Over 866 unique peptide sequences were isolated, purified, and then identified by nanohigh-performance liquid chromatography/tandem mass spectrometry (NANO-HPLC-MS/MS) from hazelnut protein hydrolysates, but Trp-Trp-Asn-Leu-Asn (WWNLN) and Trp-Ala-Val-Leu-Lys (WAVLK) in particular are found to increase the cell viability and phagocytic capacity of RAW264.7 macrophages as well as promote the secretion of the cytokines nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β). Fluorescence resonance energy transfer assay elucidated that WWNLN and WAVLK exhibit excellent inhibitory potency against Mpro, with IC50 values of 6.695 and 16.750 μM, respectively. Classical all-atom MD simulations show that hydrogen bonds play a pivotal role in stabilizing the complex conformation and protein-peptide interaction. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation indicates that WWNLN has a lower binding free energy with Mpro than WAVLK. Furthermore, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions illustrate favorable drug-likeness and pharmacokinetic properties of WWNLN compared to WAVLK. This study provides a new understanding of the immunomodulatory activity of hazelnut hydrolysates and sheds light on peptide inhibitors targeting Mpro.

Discovery of leaderless bacteriocins through genome mining

The emergence of antimicrobial resistance has prompted the search for antibiotic alternatives, and bacteriocins have emerged as promising alternatives to traditional antibiotics. Bacteriocins refer to a large family of antimicrobial peptides that are ribosomally synthesized by bacteria. The class of bacteriocins called leaderless bacteriocins is a unique group distinguished by the absence of a leader peptide and post-translational modifications, and hence their linear structures. Members of this class have been discovered by a traditional approach of screening bacterial isolates for antimicrobial activity and subsequently identifying the active molecule. This study presents the first extensive genome mining approach for leaderless bacteriocin discovery. In detail, we performed a precursor peptide-based genome mining to search for novel leaderless bacteriocins. Over 400 producer organisms with putative leaderless bacteriocins encoded in their genomes were identified, revealing the widespread occurrence of leaderless bacteriocins. Among the identified putative bacteriocins, 122 are unique peptide sequences. To validate our genome mining results, a novel bacteriocin we termed miticin, encoded in the genome of Streptococcus mitis, was obtained through chemical synthesis. Miticin was indeed found to be active, specifically against a wide range of Gram-positive bacteria. With this study, we provide the foundation for exploring a repertoire of potential novel antimicrobials identified through an innovative bioinformatics-guided approach, representing a significant leap compared to traditional screening and isolation methods for the discovery of bioactive molecules, specifically leaderless bacteriocins.

Short macrocyclic peptides in sponge genomes

Sponges (Porifera) contain many peptide-specialized metabolites with potent biological activities and significant roles in shaping marine ecology. It is well established that symbiotic bacteria produce bioactive "sponge" peptides, both on the ribosome (RiPPs) and nonribosomally. Here, we demonstrate that sponges themselves also produce many bioactive macrocyclic peptides, such as phakellistatins and related proline-rich macrocyclic peptides (PRMPs). Using the Stylissa carteri sponge transcriptome, methods were developed to find sequences encoding 46 distinct RiPP-type core peptides, of which ten encoded previously identified PRMP sequences. With this basis set, the genome and transcriptome of the sponge Axinella corrugata was interrogated to find 35 PRMP precursor peptides encoding 31 unique core peptide sequences. At least 11 of these produced cyclic peptides that were present in the sponge and could be characterized by mass spectrometry, including stylissamides A-D and seven previously undescribed compounds. Precursor peptides were encoded in the A. corrugata genome, confirming their animal origin. The peptides contained signal peptide sequences and highly repetitive recognition sequence-core peptide elements with up to 25 PRMP copies in a single precursor. In comparison to sponges without PRMPs, PRMP sponges are incredibly enriched in potentially secreted polypeptides, with >23,000 individual signal peptide encoding genes found in a single transcriptome. The similarities between PRMP biosynthetic genes and neuropeptides in terms of their biosynthetic logic suggest a fundamental biology linked to circular peptides, possibly indicating a widespread and underappreciated diversity of signaling peptide post-translational modifications across the animal kingdom.

Structural, Biochemical, and Bioinformatic Basis for Identifying Radical SAM Cyclopropyl Synthases.

The importance of radical S-adenosyl-l-methionine (RS) enzymes in the maturation of ribosomally synthesized and post-translationally modified peptides (RiPPs) continues to expand, specifically for the RS-SPASM subfamily. We recently discovered an RS-SPASM enzyme that installs a carbon-carbon bond between the geminal methyls of valine residues, resulting in the formation of cyclopropylglycine (CPG). Here, we sought to define the family of cyclopropyl (CP) synthases because of the importance of cyclopropane scaffolds in pharmaceutical development. Using RadicalSAM.org, we bioinformatically expanded the family of CP synthases and assigned unique peptide sequences to each subclade. We identified a unique RiPP biosynthetic pathway that encodes a precursor peptide, TigB, with a repeating TIGSVS motif. Using LCMS and NMR techniques, we show that the RS enzyme associated with the pathway, TigE, catalyzes the formation of a methyl-CPG from the conserved isoleucine residing in the repeating motif of TigB. Furthermore, we obtained a crystal structure of TigE, which reveals an unusual tyrosyl ligation to the auxiliary I [4Fe-4S] cluster, provided by a glycine-tyrosine-tryptophan motif unique to all CP synthases. Further, we show that this unique tyrosyl ligation is absolutely required for TigE activity. Together, our results provide insight into how CP synthases perform this unique reaction.

Proteomic assessment of SKBR3/HER2+ breast cancer cellular response to Lapatinib and investigational Ipatasertib kinase inhibitors.

Modern cancer treatment strategies aim at achieving cancer remission by using targeted and personalized therapies, as well as harnessing the power of the immune system to recognize and eradicate the cancer cells. To overcome a relatively short-lived response due to resistance to the administered drugs, combination therapies have been pursued. The objective of this study was to use high-throughput data generation technologies such as mass spectrometry and proteomics to investigate the broader implications, and to expand the outlook, of such therapeutic approaches. Specifically, we investigated the systems-level response of a breast cancer cell line model to a mixture of kinase inhibitors that has not been adopted yet as a standard therapeutic regime. Two critical pathways that sustain the growth and survival of cancer cells, EGFR and PI3K/AKT, were inhibited in SKBR3/HER2+ breast cancer cells with Lapatinib (Tyr kinase inhibitor) and Ipatasertib (Ser/Thr kinase inhibitor), and the landscape of the affected biological processes was investigated with proteomic technologies. Over 800 proteins matched by three unique peptide sequences were affected by exposing the cells to the drugs. The work corroborated the anti-proliferative activity of Lapatinib and Ipatasertib and uncovered a range of impacted cancer-supportive hallmark processes, among which immune response, adhesion, and migration emerged as particularly relevant to the ability of drugs to effectively suppress the proliferation and dissemination of cancer cells. Changes in the expression of key cancer drivers such as oncogenes, tumor suppressors, EMT and angiogenesis regulators underscored the inhibitory effectiveness of drugs on cancer proliferation. The supplementation of Lapatinib with Ipatasertib further affected additional transcription factors and proteins involved in gene expression, trafficking, DNA repair, and development of multidrug resistance. Furthermore, over fifty of the impacted proteins represent approved or investigational targets in the DrugBank database, which through their protein-protein interaction networks can inform the selection of effective therapeutic partners. Altogether, the exposure of SKBR3/HER2+ cells to Lapatinib and Ipatasertib kinase inhibitors uncovered a broad plethora of yet untapped opportunities that can be further explored for enhancing the anti-cancer effects of each drug as well as of many other multi-drug therapies that target the EGFR/ERBB2 and PI3K/AKT pathways.

Potential bioactive peptides obtained after in vitro gastrointestinal digestion of wine lees from sequential fermentations

The biotechnological reuse of winery by-products has great potential to increase the value and sustainability of the wine industry. Recent studies revealed that yeast biomass can be an exciting source of bioactive peptides with possible benefits for human health, and its incorporation in plant-based foods is considered innovative and sustainable. In this study, we aimed to identify, through in silico analyses, potential bioactive peptides from yeast extracts after in vitro digestion. Wine lees from a non-Saccharomyces oenological yeast, Starmerella bacillaris FRI751, Saccharomyces cerevisiae EC1118, and sequential fermentation performed with both strains (SEQ) were recovered in a synthetic must. Cellular pellets were enzymatically treated with zymolyase, and the yeast extracts were submitted to in vitro gastrointestinal digestions. LC-MS/MS sequenced the hydrolyzed peptides, and their potential bioactivity was inferred. S. bacillaris FRI751 fermentation showed 132 peptide sequences, S. cerevisiae EC1118 60, SEQ 89. A total of 243 unique peptide sequences were identified across the groups. Furthermore, based on the peptide sequence, the FRI751 extract showed the highest potential antihypertensive with 275 bioactive fragments. Other bioactivities, such as antimicrobial and immunomodulatory, were also identified in all yeast extracts. A potential antiobesity bioactive peptide VVP was identified only in the yeast extract from S. bacillaris single strain. The wine lees from S. bacillaris single strain and SEQ fermentation are a richer source of potential bioactive peptides than those from S. cerevisiae fermentation. This study opens new possibilities in the valorization of winemaking by-products.

Mass spectrometry on cerebrospinal fluid uncovers association of novel glycolysis biomarkers with Alzheimer’s disease in a complex clinical cohort

AbstractBackgroundDiagnosis of Alzheimer’s disease (AD) primarily relies on cognitive assessments supported by imaging and cerebrospinal fluid (CSF) biomarkers of amyloid and tau proteins. These limited biomarkers correlate poorly with disease progression or treatment response. Broader, more comprehensive biomarker sets together with traditional ATN biomarkers could improve the diagnosis and prognosis of AD, identify contributing pathophysiologies and comorbidities, and prove useful in measuring treatment efficacy. In this study we leverage mass‐spectrometry to simultaneously quantify hundreds of proteins in CSF from a large‐scale neurology clinic cohort, all of whom had clinical indication for diagnostic lumbar puncture. We aim to define markers that can stratify and diagnose AD in this “real‐life” clinically complex cohort.MethodCSF samples from 408 patients were collected from the Massachusetts General Hospital Neurology Service following written informed consent for research biobanking and analysis of excess CSF. The patient cohort consisted of ATN‐verified cognitively‐unimpaired (n = 81), mild‐cognitive impairment from AD (n = 116), mild‐cognitive impairment from other non‐AD causes (n = 78), dementia from AD (n = 65) and dementia from other non‐AD causes (n = 31). Samples were analyzed on an Orbitrap Fusion using a Data Independent Acquisition method and raw files were searched using Scaffold‐DIA.Result1761 unique peptide sequences belonging to 516 proteins were robustly quantified by DIA in CSF. Linear regression analyses found 572 peptides to be significantly differentially abundant across all diagnoses compared to AD (padj &lt; 0.05). Ontological analysis of these peptides indicated enrichment of glycolysis in AD, potentially indicating a shift in brain metabolism in AD. 4 peptides belonging to 2 glycolysis proteins (PKM, ALDOA) were elevated in AD compared to all non‐AD diagnoses, suggesting specificity for AD. Differential abundance of these proteins was verified through immunoassay.ConclusionHere, unbiased mass‐spectrometry on CSF highlighted novel AD specific biomarkers ALDOA and PKM, potentially indicating a metabolic shift in the brain. Further mechanistic studies should investigate dysregulation of these markers in AD and correlation with FDG‐PET.

Prospection of Peptide Inhibitors of Thrombin from Diverse Origins Using a Machine Learning Pipeline.

Thrombin is a key enzyme involved in the development and progression of many cardiovascular diseases. Direct thrombin inhibitors (DTIs), with their minimum off-target effects and immediacy of action, have greatly improved the treatment of these diseases. However, the risk of bleeding, pharmacokinetic issues, and thrombotic complications remain major concerns. In an effort to increase the effectiveness of the DTI discovery pipeline, we developed a two-stage machine learning pipeline to identify and rank peptide sequences based on their effective thrombin inhibitory potential. The positive dataset for our model consisted of thrombin inhibitor peptides and their binding affinities (KI) curated from published literature, and the negative dataset consisted of peptides with no known thrombin inhibitory or related activity. The first stage of the model identified thrombin inhibitory sequences with Matthew's Correlation Coefficient (MCC) of 83.6%. The second stage of the model, which covers an eight-order of magnitude range in KI values, predicted the binding affinity of new sequences with a log room mean square error (RMSE) of 1.114. These models also revealed physicochemical and structural characteristics that are hidden but unique to thrombin inhibitor peptides. Using the model, we classified more than 10 million peptides from diverse sources and identified unique short peptide sequences (<15 aa) of interest, based on their predicted KI. Based on the binding energies of the interaction of the peptide with thrombin, we identified a promising set of putative DTI candidates. The prediction pipeline is available on a web server.

Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities

IntroductionThe human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease. ObjectivesHere, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics. MethodsComparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data. ResultsGlycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors. ConclusionOur work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.

Exploring the Landscape of the PP7 Virus-like Particle for Peptide Display.

Self-assembling virus-like particles (VLPs) can tolerate a wide degree of genetic and chemical manipulation to their capsid protein to display a foreign molecule polyvalently. We previously reported the successful incorporation of foreign peptide sequences in the junction loop and onto the C-terminus of PP7 dimer VLPs, as these regions are accessible for surface display on assembled capsids. Here, we report the implementation of a library-based approach to test the assembly tolerance of PP7 dimer capsid proteins to insertions or terminal extensions of randomized 15-mer peptide sequences. By performing two iterative rounds of assembly-based selection, we evaluated the degree of favorability of all 20 amino acids at each of the 15 randomized positions. Deep sequencing analysis revealed a distinct preference for the inclusion of hydrophilic peptides and negatively charged amino acids (Asp and Glu) and the exclusion of positively charged peptides and bulky and hydrophobic amino acid residues (Trp, Phe, Tyr, and Cys). Within the libraries tested here, we identified 4000 to 22,000 unique 15-mer peptide sequences that can successfully be displayed on the surface of the PP7 dimer capsid. Overall, the use of small initial libraries consisting of no more than a few million members yielded a significantly larger number of unique and assembly-competent VLP sequences than have been previously characterized for this class of nucleoprotein particle.

The genotype list string code syntax for exchanging nomenclature-level genotyping results in clinical and research data management and analysis systems.

The nomenclatures used to describe HLA and killer-cell immunoglobulin-like receptor (KIR) alleles distinguish unique nucleotide and peptide sequences, and patterns of expression, but are insufficient for describing genotyping results, as description of ambiguities and relations across loci require terminology beyond allele names. The genotype list (GL) String grammar describes genotyping results for genetic systems with defined nomenclatures, like HLA and KIR, documenting what is known and unknown about a given genotyping result. However, the accuracy of a GL String is dependent on the reference database version under which it was generated. Here, we describe the GL string code (GLSC) system, which associates each GL String with meta-data describing the specific reference context in which the GL String was created, and in which it should be interpreted. GLSC is a defined syntax for exchanging GL Strings in the context of a specific gene-family namespace, allele-name code-system, and pertinent reference database version. GLSC allows HLA and KIR genotyping data to be transmitted, parsed and interpreted in the appropriate context, in an unambiguous manner, on modern data-systems, including Health Level 7 Fast Healthcare Interoperability Resource systems. Technical specification for GLSC can be found at https://glstring.org.

Physicochemical properties of infant formula model emulsions stabilised by different whey protein hydrolysates and characteristics of interfacial peptides

Whey protein hydrolysate (WPH) can be an important ingredient of infant formula for improved nutritional benefits. Whey protein isolate was hydrolysed using trypsin, pepsin, bromelain, papain, and flavourzyme to obtain WPH (degree of hydrolysis ∼10%, except for pepsin). The hydrolysates were formulated into infant formula model emulsions. After homogenisation, the droplet sizes of the WPH-stabilised emulsions were smaller than that of the intact whey protein-stabilised emulsion, except for the papain-stabilised emulsion. The peptidomics of WPHs and the interfacial proteins/peptides of WPH-stabilised emulsions were investigated. A large number of unique peptide sequences from different WPHs were found to have high expression on the interfacial proteins/peptides, which significantly depended on their chain length (10–20), molecular weight, high net charge and pI, and amphipathy (positive hydrophobicity). These peptide sequences played an important role in the stabilisation of the emulsions. Different enzymatically hydrolysed whey proteins offered more possibilities for stabilising the infant formula emulsions.

Identification of Macrocyclic Peptide Families from Combinatorial Libraries Containing Noncanonical Amino Acids Using Cheminformatics and Bioinformatics Inspired Clustering.

In the past decade, macrocyclic peptides gained increasing interest as a new therapeutic modality to tackle intracellular and extracellular therapeutic targets that had been previously classified as "undruggable". Several technological advances have made discovering macrocyclic peptides against these targets possible: 1) the inclusion of noncanonical amino acids (NCAAs) into mRNA display, 2) increased availability of next generation sequencing (NGS), and 3) improvements in rapid peptide synthesis platforms. This type of directed-evolution based screening can produce large numbers of potential hit sequences given that DNA sequencing is the functional output of this platform. The current standard for selecting hit peptides from these selections for downstream follow-up relies on the frequency counting and sorting of unique peptide sequences which can result in the generation of false negatives due to technical reasons including low translation efficiency or other experimental factors. To overcome our inability to detect weakly enriched peptide sequences among our large data sets, we wanted to develop a clustering method that would enable the identification of peptide families. Unfortunately, utilizing traditional clustering algorithms, such as ClustalW, is not possible for this technology due to the incorporation of NCAAs in these libraries. Therefore, we developed a new atomistic clustering method with a Pairwise Aligned Peptide (PAP) chemical similarity metric to perform sequence alignments and identify macrocyclic peptide families. With this method, low enriched peptides, including isolated sequences (singletons), can now be clustered into families providing a comprehensive analysis of NGS data resulting from macrocycle discovery selections. Additionally, upon identification of a hit peptide with the desired activity, this clustering algorithm can be used to identify derivatives from the initial data set for structure-activity relationship (SAR) analysis without requiring additional selection experiments.

Applying Data‐Independent Acquisition Mass Spectrometry on Cerebrospinal Fluid Samples from a Neurology Clinic for Biomarker Discovery in Alzheimer’s Disease

AbstractBackgroundDiagnosis of Alzheimer’s disease (AD) primarily relies on cognitive assessments combined with imaging and limited fluid biomarkers. These biomarkers do not correlate with cognitive prognosis. Analysis of larger sets of biomarkers could improve diagnosis and prognosis of AD and differentiate between comorbid pathophysiologies, and measure treatment efficacy. Here, we report analysis of a Data‐independent Acquisition (DIA) mass‐spectrometry method used to simultaneously quantify hundreds of proteins in a large‐scale patient cohort. We aim to define markers that are able to stratify and diagnose AD in this clinically complex cohort.MethodSamples from 408 patients spanning various dementia diagnoses were collected from the Massachusetts General Hospital Lumbar Puncture clinic. The patient cohort consisted of ATN‐verified cognitively‐unimpaired (n = 81), mild‐cognitive impairment from AD (n = 116), mild‐cognitive impairment from other causes (n = 78), dementia from AD (n = 65) and dementia from other causes (n = 31). Samples were analyzed on an Orbitrap Fusion using a DIA method and raw files were searched using Scaffold‐DIA.ResultAnalyses of the method’s technical performance showed a median intrabatch CV of 24.7% which decreased to 17.5% after filtering for peptides expressed in 95% of all samples. The mean interbatch CV was 73.7% which reduced to 28.8% after ComBat batch‐correction. After filtering for missing values and selecting only the peptides with a mean intrabatch CV below 25%, our dataset consists of 1761 unique peptide sequences belonging to 516 proteins.To determine the differential abundance of peptides we fit a linear regression model to the data. 572 peptides were found to be differentially abundant across all diagnoses compared to AD (padj &lt; 0.05). 11 of these peptides belonging to 5 proteins (PKM, ALDOA, GUAD, BASP1 and CH3L1) were differentially abundant between AD and all non‐AD diagnoses, suggesting specificity for AD. PKM and ALDOA, are involved in regulation of balance between glycolysis and oxidative phosphorylation, potentially indicating a shift in brain metabolism in AD.ConclusionTechnically robust unbiased mass‐spectrometry can highlight novel AD specific biomarkers which may reflect pathophysiological processes key to AD progression.

Alpha-aminoisobutyric acid incorporated peptides for the construction of electrochemical biosensors with high stability and low fouling in serum

An effective strategy to construct low fouling electrochemical biosensors for assaying serum biomarkers was proposed based on specially designed α-aminoisobutyric acid (Aib) incorporated peptides. The Aib-peptides were designed to be of antifouling properties, and at the same to incorporate Aib residues in their interior to enhance the hydrolytic stability. In order to construct the electrochemical biosensor, two kinds of Aib-peptides labelled with biotin were modified on the electrode surface: One with cysteine terminal for easy attachment to the electrode modified with gold nanoparticles, the other with unique terminal peptide sequence for specific binding of immunoglobulin G (IgG), and they were connected through the streptavidin-biotin affinity system. Owing to the interposition of Aib residues, the peptides as well as the constructed biosensors showed excellent antifouling performances and enhanced stability against enzymatic degradation in serum. Furthermore, the IgG biosensor constructed with the Aib-peptides displayed a very low detection limit (29.5 pg mL−1) and a broad linear range (100 pg mL−1 - 10 μg mL−1), and it was able to assay IgG in clinical human sera with decent accuracy and reliability. This strategy provides a new path for the construction of stable antifouling biosensors based on functional peptides for practical biomarker assaying in real clinical samples.

Salinity-induced ionoregulatory changes in the gill proteome of the mayfly, Neocloeon triangulifer

Ecologists have observed declines in the biodiversity of sensitive freshwater organisms in response to increasing concentrations of major ions (salinization). Yet, how changing salinities physiologically challenge aquatic organisms, such as mayflies, remains remarkably understudied. Moreover, it is not well understood the degree to which species respond and acclimate to salinity changes. Our lab is developing the Baetid mayfly, N. triangulifer, as a model organism for physiological research. We have previously described acclimatory changes in both ion flux rates and altered mRNA transcript levels in response to chronic exposures to elevated major ion concentrations at the whole animal level. In the present study, we use shotgun proteomics to identify the specific proteins associated with apical ion transport and how their abundance changes in response to chronic salinity exposures in gills. Gills were isolated from the penultimate nymphal stage of N. triangulifer reared under control culture conditions, elevated NaCl (157 mg L−1 Na), elevated CaCl2 (121 mg L−1 Ca), elevated Ca/MgSO4 (735 mg L−1 SO4). These conditions mirrored those from previously published physiological work. We also acutely exposed nymphs to dilute (50% dilution of culture water with deionized water) to explore proteomic changes in the gills in response to dilute conditions. We report 710 unique peptide sequences among treatment groups, including important apical ion transporters such as Ca-ATPase, Na/K ATPase, and V-ATPase. Treatment with elevated NaCl and Ca/MgSO4 appeared to cause more significant differential protein expression (452 and 345, respectively) compared to CaCl2 and dilute groups (134 and 17, respectively). Finally, we demonstrated the breadth of physiological functions in gills by exploring non-transport related pathways found in our dataset, including ATP synthesis, calcium signaling, and oxidative stress response. We discuss our results in the context of freshwater salinization and the challenges of working with non-model species without fully sequenced and annotated genomes.

Identification of Somatic Proteins in Haemonchus Contortus Infective Larvae (L3) and Adults.

SummaryHaemonchus contortus is considered the most pathogenic nematode in sheep production systems based on grazing. Comparing infective larvae (L3) with adult parasites can lead to the identification of proteins that play an important role in parasite-host interactions. In this study, we report a list of H. contortus somatic proteins and made a comparative analysis of somatic proteins of L3 and adult worms. L3 and adult parasites were subjected to protein extraction and subsequently to peptide fractionation. Peptides were analysed by mass spectrometry and LC-MS/MS data analysis. Data analysis and search on SEQUEST and MASCOT against H. contortus from the WormBase ParaSite database resulted in the identification of 775 unique peptide sequences corresponding to 227 proteins at 1 % FDR. From these, 18 proteins were specific to L3 and 63 to adult parasites. The gene ontology (GO) enrichment analysis of the proteins specific to L3 and adult worms to gain insight into cellular components, molecular functions and biological processes that affect the parasite-host interaction showed some differences between the two parasite stages. The list of proteins found provides a database to identify target proteins that could be useful as biomarkers of the infection or in the generation of anthelmintic drugs that inhibit proteins essential for the establishment of the infection and the survival of adult parasites. They can also serve as new candidates for vaccine research.

Picturins and Pictuseptins, two novel antimicrobial peptide families from the skin secretions of the Chachi treefrog, Boana picturata

The Imbabura treefrog (Boana picturata) is an underexplored source of bioactive peptides. The combination of molecular cloning and mass spectrometry allowed us to identify three new peptide families, named “Picturins” (PTR), “Pictuseptins” (PTS), and “Boanins” (BNS). PTR is composed of three 25-mer peptides, characterized by the N-terminal sequence: GVFKDALKQ and the C-terminal sequence: AANALKPK. The sequences of PTR-1, −2 and − 3 are highly conserved only showing two divergent sites: (L/F) in position 10 and (K/Q) in position 17. PTS gathers six peptides. PTS -1, −2 and − 4 have 22 amino acid residues in length, while PTS -3, −5 and − 6 are composed of 26 residues. Whereas BNS are four 28–37 mer peptides, showing two conserved regions: the N-terminal sequence FLGAL and the C-terminal sequence KALNP. PTR-1 to 3 and PTS -1 to −3 were chemically synthetized and their antimicrobial and haemolytic activity was assessed. PTR displayed moderate activity against Escherichia coli (MIC 24.80 to 48.95 μM), while PTS showed a broad antimicrobial and antifungal effect. PTS-1 was the most active peptide against E. coli (6.8 μM) followed by PTS-3 (11.7 μM) and PTS-2 (14.24 μM). These peptides also showed low haemolytic activity, pointing to a favorable selectivity. Overall, new unique non-hemolytic and cationic peptide sequences were characterized that could be valuable for the next-generation of anti-infective drugs. Future functional studies should explore the pharmacological potential of Boanins to include them as antimicrobial scaffolds. Biological significanceNature-inspired solutions have shown their importance mainly for the development of the pharmaceutical industry. Frog skin peptides are excellent examples of the biomedical potential of naturally evolved molecules for specific targets, including multi-resistant bacteria. The characterization of new chemical entities from poorly studied skin secretions of Ecuadorian biodiversity, such as B. picturata, represents an unprecedented opportunity to identify candidates to tackle global concerns, for instance, antibiotic resistance.

Brain Penetrant Humanized scFv Antibody Block of P2 × 4 Receptor for Treatment of Chronic Pain

Our collaborative efforts are focused on validation of promising humanized single chain Fragment variable (hscFv) antibodies targeting a unique amino acid peptide sequence of P2 × 4 receptor (P2 × 4R). Data indicate single dose post-treatment with our newly engineered hP2 × 4 scFv antibody restores mechanical and cold pain-related behaviors to baseline in our trigeminal nerve compression model (FRICT-ION). The reversal to naïve baseline persists until experiment end at 10 weeks. Anxiety-like behaviors that develop in mice with chronic pain do not develop in hscFv antibody treated mice. We are characterizing the efficacy of lead P2 × 4R hscFv antibodies on neuronal cell-type specific activation patterns in medullary spinal V nucleus slices from Fos-TRAP(targeted recombination in active populations) mice and cultured trigeminal ganglia (TG) neurons from FRICT-ION mice. Engineered scFv antibodies feature binding affinity and activity similar to or better than monoclonal antibodies because they are much smaller in size. Thus, they are brain/nervous tissue penetrant due to their small size and have promising biotherapeutic applications for both the nervous and immune systems, now recognized as interactive in chronic pain. The ribosome display method utilized to generate the scFvs is a powerful cell-free technology widely used to select single-chain antibody fragments against the target of choice. This method is inexpensive, rapid, and was used to quickly develop repertoires of high-affinity antibodies targeting P2 × 4. In our hands the scFvs developed have high affinity in the picomolar range, superior stability and solubility. The patent was filed and published. Moving forward we currently continue evaluating these humanized P2 × 4R scFv antibodies that have strong nanomolar binding affinity, reduced self-immunogenicity, and relatively inexpensive large-scale production toward new drug application status based on the successful reversal of pain related measures and reduction of neuronal activation. This project opens new avenues for development of highly effective non-opioid biologic therapeutic interventions for chronic pain. Grant support from DoD grant W81XWH2010930 (KNW, SRAA); VA Merit grant BX002695 (KNW); NIH NIDCR R21 DE028096; NIH UG3 NS123958.

Production and characterization of bioactive peptides from rice beans using Bacillus subtilis

A bioprocess was developed for production of bioactive peptides on microbial fermentation of rice beans using proteolytic Bacillus subtilis strains. The peptides produced were identified by LC-MS/MS analysis, revealing the presence of many unique peptide sequences to individual hydrolysates. On functional properties prediction, antihypertensive peptides (3.90%) were found to be higher in comparison to other bioactive peptides. Among different strains, B. subtilis KN2B fermented hydrolysate exhibited highest angiotensin converting enzyme (ACE)-inhibitory activity (45.73%). Furthermore, 19 selected peptides, including the common and unique peptides were examined for their affinity towards the binding cavity of ACE using molecular docking. The results showed a common peptide PFPIPFPIPIPLP, and another IPFPPIPFLPPI unique to B. subtilis KN2B fermented hydrolysate exhibited promising binding at the ACE binding site with substantial free binding energy. The process developed can be used for the production of bioactive peptides from rice bean for application in nutraceutical industries.