Cell-Penetrating Milk-Derived Peptides with a Non-Inflammatory Profile.

Milk-derived peptides are known to confer anti-inflammatory effects. We hypothesised that milk-derived cell-penetrating peptides might modulate inflammation in useful ways. Using computational techniques, we identified and synthesised peptides from the milk protein Alpha-S1-casein that were predicted to be cell-penetrating using a machine learning predictor. We modified the interpretation of the prediction results to consider the effects of histidine. Peptides were then selected for testing to determine their cell penetrability and anti-inflammatory effects using HeLa cells and J774.2 mouse macrophage cell lines. The selected peptides all showed cell penetrating behaviour, as judged using confocal microscopy of fluorescently labelled peptides. None of the peptides had an effect on either the NF-κB transcription factor or TNFα and IL-1ß secretion. Thus, the identified milk-derived sequences have the ability to be internalised into the cell without affecting cell homeostatic mechanisms such as NF-κB activation. These peptides are worthy of further investigation for other potential bioactivities or as a naturally derived carrier to promote the cellular internalisation of other active peptides.

Relationship between Protein Digestibility and the Proteolysis of Legume Proteins during Seed Germination.

Legume seed protein is an important source of nutrition, but generally it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defenses against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defense or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species- and strain-dependent. Further research is needed to highlight which changes contribute most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry-identified peptide breakdown products.

Modelling the Transitioning of SARS-CoV-2 nsp3 and nsp4 Lumenal Regions towards a More Stable State on Complex Formation.

During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3-nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection.

Computational modelling of chromosomally clustering protein domains in bacteria.

BACKGROUND: In bacteria, genes with related functions-such as those involved in the metabolism of the same compound or in infection processes-are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a "gene", since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. RESULTS: We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. CONCLUSIONS: Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

Enriching antimicrobial peptides from milk hydrolysates using pectin/alginate food-gels.

Cationic antimicrobial peptides have raised interest as attractive alternatives to classical antibiotics, and also have utility in preventing food spoilage. We set out to enrich cationic antimicrobial peptides from milk hydrolysates using gels containing various ratios of anionic pectin/alginate. All processes were carried out with food-grade materials in order to suggest food-safe methods suited for producing food ingredients or supplements. Hydrolysed caseinate peptides retained in the gel fraction, identified by mass spectrometry, were enriched for potential antimicrobial peptides, as judged by a computational predictor of antimicrobial activity. Peptides retained in a 60:40 pectin:alginate gel fraction had a strong antimicrobial effect against 8 tested bacterial strains with a minimal inhibitory concentration of 1.5-5 mg/mL, while the unfractionated hydrolysate only had a detectable effect in one of the eight strains. Among 110 predicted antimicrobial peptides in the gel fraction, four are known antimicrobial peptides, HKEMPFPK, TTMPLW, YYQQKPVA and AVPYPQR. These results highlight the potential of pectin/alginate food-gels based processes as safe, fast, cost-effective methods to separate and enrich for antimicrobial peptides from complex food protein hydrolysates.

Short linear motif candidates in the cell entry system used by SARS-CoV-2 and their potential therapeutic implications.

The first reported receptor for SARS-CoV-2 on host cells was the angiotensin-converting enzyme 2 (ACE2). However, the viral spike protein also has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif (ELM) resource and identified candidate short linear motifs (SLiMs) in their short, unstructured, cytosolic tails with potential roles in endocytosis, membrane dynamics, autophagy, cytoskeleton, and cell signaling. These SLiM candidates are highly conserved in vertebrates and may interact with the µ2 subunit of the endocytosis-associated AP2 adaptor complex, as well as with various protein domains (namely, I-BAR, LC3, PDZ, PTB, and SH2) found in human signaling and regulatory proteins. Several motifs overlap in the tail sequences, suggesting that they may act as molecular switches, such as in response to tyrosine phosphorylation status. Candidate LC3-interacting region (LIR) motifs are present in the tails of integrin ß3 and ACE2, suggesting that these proteins could directly recruit autophagy components. Our findings identify several molecular links and testable hypotheses that could uncover mechanisms of SARS-CoV-2 attachment, entry, and replication against which it may be possible to develop host-directed therapies that dampen viral infection and disease progression. Several of these SLiMs have now been validated to mediate the predicted peptide interactions.

Resolving the Interactome of the Human Macrophage Immunometabolism Regulator (MACIR) with Enhanced Membrane Protein Preparation and Affinity Proteomics.

Expression of the macrophage immunometabolism regulator gene (MACIR) is associated with severity of autoimmune disease pathology and with the regulation of macrophage biology through unknown mechanisms. The encoded 206 amino acid protein lacks homology to any characterized protein sequence and is a disordered protein according to structure prediction algorithms. To identify interactions of MACIR with proteins from all subcellular compartments, a membrane solubilization buffer is employed, that together with a high affinity EF hand based pull down method, increases the resolution of quantitative mass spectrometry analysis with significant enrichment of interactions from membrane bound nuclear and mitochondrial compartments compared to samples prepared with radioimmunoprecipitation assay buffer. A total of 63 significant interacting proteins are identified and interaction with the nuclear transport receptor TNPO1 and the trafficking proteins UNC119 homolog A and B are validated by immunoprecipitation. Mutational analysis in two candidate nuclear localization signal motifs in the MACIR amino acid sequence shows the interaction with TNPO1 is likely via a non-classical proline/tyrosine-nuclear localization signal motif (aa98-117). It is shown that employing a highly specific and high affinity pull down method that performs efficiently in this glycerol and detergent rich buffer is a powerful approach for the analysis of uncharacterized protein interactomes.

Prediction of polyproline II secondary structure propensity in proteins.

Background: The polyproline II helix (PPIIH) is an extended protein left-handed secondary structure that usually but not necessarily involves prolines. Short PPIIHs are frequently, but not exclusively, found in disordered protein regions, where they may interact with peptide-binding domains. However, no readily usable software is available to predict this state. Results: We developed PPIIPRED to predict polyproline II helix secondary structure from protein sequences, using bidirectional recurrent neural networks trained on known three-dimensional structures with dihedral angle filtering. The performance of the method was evaluated in an external validation set. In addition to proline, PPIIPRED favours amino acids whose side chains extend from the backbone (Leu, Met, Lys, Arg, Glu, Gln), as well as Ala and Val. Utility for individual residue predictions is restricted by the rarity of the PPIIH feature compared to structurally common features. Conclusion: The software, available at http://bioware.ucd.ie/PPIIPRED, is useful in large-scale studies, such as evolutionary analyses of PPIIH, or computationally reducing large datasets of candidate binding peptides for further experimental validation.

The future of genomics in Ireland - focus on genomics for health.

Genomics is revolutionizing biomedical research, medicine and healthcare globally in academic, public and industry sectors alike. Concrete examples around the world show that huge benefits for patients, society and economy can be accrued through effective and responsible genomic research and clinical applications. Unfortunately, Ireland has fallen behind and needs to act now in order to catch up. Here, we identify key issues that have resulted in Ireland lagging behind, describe how genomics can benefit Ireland and its people and outline the measures needed to make genomics work for Ireland and Irish patients. There is now an urgent need for a national genomics strategy that enables an effective, collaborative, responsible, well-regulated, and patient centred environment where genome research and clinical genomics can thrive.  We present eight recommendations that could be the pillars of a national genomics health strategy.

An intrinsically disordered proteins community for ELIXIR.

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled "An intrinsically disordered protein user community proposal for ELIXIR" held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

Implications of kappa-casein evolutionary diversity for the self-assembly and aggregation of casein micelles.

Milk alpha-, beta- and kappa-casein proteins assemble into casein micelles in breast epithelial cells. The glycomacropeptide (GMP) tails of kappa-casein that extend from the surface of the micelle are key to assembly and aggregation. Aggregation is triggered by stomach pepsin cleavage of GMP from para-kappa-casein (PKC). While one casein micelle model emphasizes the importance of hydrophobic interactions, another focuses on polar residues. We performed an evolutionary analysis of kappa-casein primary sequence and predicted features that potentially impact on protein interactions. We noted more rapid change in the earlier period (166 to 60 Ma). Pepsin and plasmin cleavage sites were avoided in the GMP, which may partly explain its amino acid composition. Short tandem repeats have led to modest expansions of PKC, and to large GMP expansions, suggesting the GMP is less length constrained. Amino acid compositional constraints were assessed across species. Polarity and hydrophobicity properties were insufficient to explain differences between PKC and GMP. Among polar residues, threonine dominates the GMP, compared to serine, probably reflecting its preference for O-glycosylation over phosphorylation. Glutamine, enriched in the bovine PQ-rich region, is not positionally conserved in other species. Among hydrophobic residues, isoleucine is clearly preferred over leucine in the GMP, and patches of hydrophobicity are not markedly positionally conserved. PKC tyrosine and charged residues showed stronger conservation of position, suggesting a role for pi-interactions, seen in other structurally dynamic protein membraneless assemblies. Independent acquisitions of cysteines are consistent with a trend of increasing stabilization of multimers by covalent disulphide bonds, over evolutionary time. In conclusion, kappa-casein compositional and positional constraints appear to be influenced by modification preferences, protease evasion and protein-protein interactions.

Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions.

Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.

Computational and experimental analysis of bioactive peptide linear motifs in the integrin adhesome.

Therapeutic modulation of protein interactions is challenging, but short linear motifs (SLiMs) represent potential targets. Focal adhesions play a central role in adhesion by linking cells to the extracellular matrix. Integrins are central to this process, and many other intracellular proteins are components of the integrin adhesome. We applied a peptide network targeting approach to explore the intracellular modulation of integrin function in platelets. Firstly, we computed a platelet-relevant integrin adhesome, inferred via homology of known platelet proteins to adhesome components. We then computationally selected peptides from the set of platelet integrin adhesome cytoplasmic and membrane adjacent protein-protein interfaces. Motifs of interest in the intracellular component of the platelet integrin adhesome were identified using a predictor of SLiMs based on analysis of protein primary amino acid sequences (SLiMPred), a predictor of strongly conserved motifs within disordered protein regions (SLiMPrints), and information from the literature regarding protein interactions in the complex. We then synthesized peptides incorporating these motifs combined with cell penetrating factors (tat peptide and palmitylation for cytoplasmic and membrane proteins respectively). We tested for the platelet activating effects of the peptides, as well as their abilities to inhibit activation. Bioactivity testing revealed a number of peptides that modulated platelet function, including those derived from α-actinin (ACTN1) and syndecan (SDC4), binding to vinculin and syntenin respectively. Both chimeric peptide experiments and peptide combination experiments failed to identify strong effects, perhaps characterizing the adhesome as relatively robust against within-adhesome synergistic perturbation. We investigated in more detail peptides targeting vinculin. Combined experimental and computational evidence suggested a model in which the positively charged tat-derived cell penetrating part of the peptide contributes to bioactivity via stabilizing charge interactions with a region of the ACTN1 negatively charged surface. We conclude that some interactions in the integrin adhesome appear to be capable of modulation by short peptides, and may aid in the identification and characterization of target sites within the complex that may be useful for therapeutic modulation.

Peptides derived from cadherin juxtamembrane region inhibit platelet function.

The juxtamembrane domains (JMD) of transmembrane proteins are rich in critical peptide sequences that participate in dynamic cell signalling events. Synthetic JMD peptides derived from cadherin cell adhesion proteins have previously been shown to modulate platelet function. In this study, we aimed to develop functional bioactive agents from bioinformatically identified critical peptide sequences. We synthesized overlapping 12-15 amino acid peptides from E- and N-cadherin JMD and assessed their effect on platelet aggregation and platelet ATP secretion. Peptides derived from close to the membrane proximal region inhibit platelet function. Sequential deletion of amino acids from the N- and C-termini of the inhibitory E-cadherin peptides identified the short K756EPLLP763 motif as a critical bioactive sequence. Alanine scanning studies further identified that the di-leucine (LL) motif and positively charged lysine (K) are crucial for peptide activity. Moreover, scrambled peptides failed to show any effect on platelet activity. We conclude that peptides derived from JMD of E-cadherin provide potential lead peptides for the development of anti-thrombotic agents and to enable further understanding of the role of cadherins in platelet function.

Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer.

Classifying indolent prostate cancer represents a significant clinical challenge. We investigated whether integrating data from different omic platforms could identify a biomarker panel with improved performance compared to individual platforms alone. DNA methylation, transcripts, protein and glycosylation biomarkers were assessed in a single cohort of patients treated by radical prostatectomy. Novel multiblock statistical data integration approaches were used to deal with missing data and modelled via stepwise multinomial logistic regression, or LASSO. After applying leave-one-out cross-validation to each model, the probabilistic predictions of disease type for each individual panel were aggregated to improve prediction accuracy using all available information for a given patient. Through assessment of three performance parameters of area under the curve (AUC) values, calibration and decision curve analysis, the study identified an integrated biomarker panel which predicts disease type with a high level of accuracy, with Multi AUC value of 0.91 (0.89, 0.94) and Ordinal C-Index (ORC) value of 0.94 (0.91, 0.96), which was significantly improved compared to the values for the clinical panel alone of 0.67 (0.62, 0.72) Multi AUC and 0.72 (0.67, 0.78) ORC. Biomarker integration across different omic platforms significantly improves prediction accuracy. We provide a novel multiplatform approach for the analysis, determination and performance assessment of novel panels which can be applied to other diseases. With further refinement and validation, this panel could form a tool to help inform appropriate treatment strategies impacting on patient outcome in early stage prostate cancer.

Evolutionary instability of CUG-Leu in the genetic code of budding yeasts.

The genetic code used in nuclear genes is almost universal, but here we report that it changed three times in parallel during the evolution of budding yeasts. All three changes were reassignments of the codon CUG, which is translated as serine (in 2 yeast clades), alanine (1 clade), or the 'universal' leucine (2 clades). The newly discovered Ser2 clade is in the final stages of a genetic code transition. Most species in this clade have genes for both a novel tRNASer(CAG) and an ancestral tRNALeu(CAG) to read CUG, but only tRNASer(CAG) is used in standard growth conditions. The coexistence of these alloacceptor tRNA genes indicates that the genetic code transition occurred via an ambiguous translation phase. We propose that the three parallel reassignments of CUG were not driven by natural selection in favor of their effects on the proteome, but by selection to eliminate the ancestral tRNALeu(CAG).

Casein Hydrolysate with Glycemic Control Properties: Evidence from Cells, Animal Models, and Humans.

Evidence exists to support the role of dairy derived proteins whey and casein in glycemic management. The objective of the present study was to use a cell screening method to identify a suitable casein hydrolysate and to examine its ability to impact glycemia related parameters in an animal model and in humans. Following screening for the ability to stimulate insulin secretion in pancreatic beta cells, a casein hydrolysate was selected and further studied in the ob/ob mouse model. An acute postprandial study was performed in 62 overweight and obese adults. Acute and long-term supplementation with the casein hydrolysate in in vivo studies in mice revealed a glucose lowering effect and a lipid reducing effect of the hydrolysate (43% reduction in overall liver fat). The postprandial human study revealed a significant increase in insulin secretion ( p = 0.04) concomitant with a reduction in glucose ( p = 0.03). The area under the curve for the change in glucose decreased from 181.84 ± 14.6 to 153.87 ± 13.02 ( p = 0.009). Overall, the data supports further work on the hydrolysate to develop into a functional food product.

Genetic variants in PPARGC1B and CNTN4 are associated with thromboxane A2 formation and with cardiovascular event free survival in the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT).

BACKGROUND AND AIMS: Elevated urinary 11-dehydro thromboxane B2 (TxB2), a measure of thromboxane A2 formation in vivo, predicts future atherothrombotic events. To further understand this relationship, the genetic determinants of 11-dehydro TxB2 and their associations with cardiovascular morbidity were investigated in this study. METHODS: Genome-wide and targeted genetic association studies of urinary 11-dehydro TxB2 were conducted in 806 Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT) participants. RESULTS: The strongest associations were in PPARGC1B (rs4235745, rs32582, rs10515638) and CNTN4 (rs10510230, rs4684343), these 5 single nucleotide polymorphisms (SNPs) were independently associated with 11-dehydro TxB2 formation. Haplotypes of 11-dehydro TxB2 increasing alleles for both PPARGC1B and CNTN4 were significantly associated with 11-dehydro TxB2, explaining 5.2% and 4.5% of the variation in the whole cohort, and 8.8% and 7.9% in participants not taking aspirin, respectively. In a second ASCOT population (n = 6199), addition of these 5 SNPs significantly improved the covariate-only Cox proportional hazards model for cardiovascular events (chisq = 14.7, p=0.01). Two of the risk alleles associated with increased urinary 11-dehydro TxB2 were individually associated with greater incidences of cardiovascular events - rs10515638 (HR = 1.31, p=0.01) and rs10510230 (HR = 1.25, p=0.007); effect sizes were larger in those not taking aspirin. CONCLUSIONS: PPARGC1B and CNTN4 genotypes are associated with elevated thromboxane A2 formation and with an excess of cardiovascular events. Aspirin appears to blunt these associations. If specific protection of PPARGC1B and CNTN4 variant carriers by aspirin is confirmed by additional studies, PPARGC1B and CNTN4 genotyping could potentially assist in clinical decision making regarding the use of aspirin in primary prevention.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.