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Staphylococcal food poisoning is considered to be one of the most common foodborne illnesses worldwide. Because milk is rich in nutrients and its neutral pH, it leads to the growth of various bacteria. To date, the correlation between enterotoxigenic potential in Staphylococcus species and antimicrobial resistance (AMR), using bioinformatics analysis in buffalo and cow raw milk and the possible health risks from these bacteria, has not been examined in Egypt. A total of 42 Staphylococcus isolates representing 12 coagulase-positive staphylococci (Staphylococcus aureus and Staphylococcus intermedius) and 30 coagulase-negative staphylococci (Staphylococcus capitis, Staphylococcus xylosus, Staphylococcus carnosus, Staphylococcus saccharolyticus, and Staphylococcus auricularis) were isolated. An assay of the antimicrobial resistance phenotypes indicated low resistance against vancomycin (9.5%). The blaZ gene was associated with penicillin G and methicillin resistance and not with sulbactam + ampicillin. The presence of the gene ermB presented the correlation with erythromycin resistance and tetK with tetracycline resistance (correlation index: 0.57 and 0.49, respectively), despite the absence of the same behavior for ermC and tetM, respectively. Interestingly, the gene mecA was not correlated with resistance to methicillin or any other β-lactam. Correlation showed that slime-producing isolates had more resistance to antibiotics than those of nonslime producers. The multiple correlations between antibiotic resistance phenotypes and resistance genes indicate a complex nature of resistance in Staphylococcus species. The antimicrobial resistance could potentially spread to the community and thus, the resistance of Staphylococcus species to various antibiotics does not depend only on the use of a single antimicrobial, but also extends to other unrelated classes of antimicrobials.

Defensins comprise a polyphyletic group of multifunctional defense peptides. Cis-defensins, also known as cysteine stabilized αβ (CSαβ) defensins, are one of the most ancient defense peptide families. In plants, these peptides have been divided into two classes, according to their precursor organization. Class I defensins are composed of the signal peptide and the mature sequence, while class II defensins have an additional C-terminal prodomain, which is proteolytically cleaved. Class II defensins have been described in Solanaceae and Poaceae species, indicating this class could be spread among all flowering plants. Here, a search by regular expression (RegEx) was applied to theArabidopsis thalianaproteome, a model plant with more than 300 predicted defensin genes. Two sequences were identified, A7REG2 and A7REG4, which have a typical plant defensin structure and an additional C-terminal prodomain. TraVA database indicated they are expressed in flower, ovules and seeds, and being duplicated genes, this indicates they could be a result of a subfunctionalization process. The presence of class II defensin sequences in Brassicaceae and Solanaceae and evolutionary distance between them suggest class II defensins may be present in other eudicots. Discovery of class II defensins in other plants could shed some light on flower, ovules and seed physiology, as this class is expressed in these locations.

The antimicrobial activity prediction tools aim to help the novel antimicrobial peptides (AMP) sequences discovery, utilizing machine learning methods. Such approaches have gained increasing importance in the generation of novel synthetic peptides by means of rational design techniques. This study focused on predictive ability of such approaches to determine the antimicrobial sequence activities, which were previously characterized at the protein level by in vitro studies. Using four web servers and one standalone software, we evaluated 78 sequences generated by the so-called linguistic model, being 40 designed and 38 shuffled sequences, with ∼60 and ∼25% of identity to AMPs, respectively. The ab initio molecular modelling of such sequences indicated that the structure does not affect the predictions, as both sets present similar structures. Overall, the systems failed on predicting shuffled versions of designed peptides, as they are identical in AMPs composition, which implies in accuracies below 30%. The prediction accuracy is negatively affected by the low specificity of all systems here evaluated, as they, on the other hand, reached 100% of sensitivity. Our results suggest that complementary approaches with high specificity, not necessarily high accuracy, should be developed to be used together with the current systems, overcoming their limitations.

Mutations in the growth hormone receptor (GHR) gene can cause disruption of the growth hormone signaling pathway, resulting in growth deficiency due to growth hormone (GH) resistance. Both recessive and apparently dominant mutations have been described in the literature. In order to shed some light on the molecular mechanism of partial growth hormone resistance caused by heterozygous mutations, we performed an in-depth in silico analysis of a mutation found in a girl with a previous diagnosis of idiopathic short stature. An array of algorithms was used to predict pathogenicity and potential impact on the protein, and molecular modeling, docking and dynamics were used to determine structural consequences. The results suggest that both of the possible single mutation-containing heteromeric GH-GHR complexes, as well as the double GHR mutant complex result in perturbation of complex structures, with altered ability of the GHR dimers to interact with the GH peptide. J. Cell. Biochem. 118: 4762-4771, 2017. © 2017 Wiley Periodicals, Inc.

The guanylate cyclase activator 2B, also known as uroguanylin, is part of the guanylin peptide family, which includes peptides such as guanylin and lymphoguanylin. The guanylin peptides could be related to sodium absorption inhibition and water secretion induction and their dysfunction may be related to various pathologies such as chronic renal failure, congestive heart failure and nephrotic syndrome. Besides, uroguanylin point mutations have been associated with essential hypertension. However, currently there are no studies on the impact of missense SNPs on uroguanylin structure. This study applied in silico SNP impact prediction tools to evaluate the impact of uroguanylin missense SNPs and to filter those considered as convergent deleterious, which were then further analyzed through long-term molecular dynamics simulations of 1 μs of duration. The simulations suggested that all missense SNPs considered as convergent deleterious caused some kind of structural change to the uroguanylin peptide. Additionally, four of these SNPs were also shown to cause modifications in peptide flexibility, possibly resulting in functional changes.

Pseudomonas aeruginosa (P. aeruginosa) produces a suite of virulence factors that are coordinated by Quorum Sensing (QS) contributing to its disease-causing ability in aquaculture. The present study is first of its kind to obtain information regarding the presence and distribution of five QS genes, three virulence genes viz: lasI, lasR, rhlI, rhlR, rhlAB, toxA, aprA and plcH and seven of the Extended-spectrum βlactamases (blaVEB, blaPER, blaTEM,, blaSHV, blaCTX-M1, blaCTX-M2 and blaCTX-M3) of Pseudomonas species isolated from fish meat by direct PCR. Bacterial identification was based mainly on conventional biochemical techniques using the Vitek 2, automated system. Phenotypic sensitivity of antibiotics was established by the agar disc diffusion technique through 16 various antimicrobial drugs. Quantification of their in vitro production of numerous virulence genes outside the cell that are QS dependent namely, pyocyanin, elastase, alkaline protease, biofilm and cytotoxicity of Vero cell was as well executed. Fifteen genes demonstrated an enormous variety in their association. The total number of Pseudomonas species isolates were 30/100 to be identified by the API 20NE system as P. aeruginosa 12/30 (40%), P. fluorescens 8/30 (27%), P. putida 6/30 (20%) and P. alkylphenolia 4/30 (13%). The outcomes of this study have great significance for the strategic designation of QS quenching.

Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or high dose requirement for a therapeutic effect . Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics., Antimicrobial peptides are considered promising alternatives to antibiotics. Here the authors developed a computational algorithm that starts with peptides naturally occurring in plants and optimizes this starting material to yield new variants which are highly distinct from the parent peptide.

Pseudomonas aeruginosa produces a suite of virulence factors that are coordinated by Quorum Sensing (QS) contributing to its disease-causing ability in aquaculture. However, the bacterial infections in aquaculture hatcheries and farms cause a huge loss in productivity and remain a major challenge for the growth of this vital industry and to the ill effects to the environment and public health. It has been well documented that the exhibition of virulence factors and formation of biofilms are the major factors for the establishment of disease in aquaculture animals by the bacterial pathogens. The present study is first of its kind to obtain information regarding the presence and distribution of QS, virulence and Extended-spectrum β-lactamases genes of Pseudomonas species isolated from fish meat by direct PCR. In addition, quantification of their in vitro production of QS-regulated phenotypes, including biofilm formation, virulence factor production and antibiotic susceptibility were executed. The influence of resistance genes in the prevalence of antibiotic resistance was evaluated by using correlation analyses. Only four correlations showed a significant level higher than 0.05. Besides, all correlations were related to extended spectrum β-lactamase (SHV, TEM and PER). In order to verify which characteristics, represent the sample, we carried out a principal component analysis (PCA) using all phenotypic (antibiotic resistance profile) and genotypic (resistance, virulence and QS genes) data from the strains. Based on the results, the P. alkylphenolia seems to be the most different of the species identified, being well clustered. Moreover, only six (resistance to Chloramphenicol, Aztreonam, Cefepime and Ceftriaxone, VEB and CTX-M1 resistance genes) of the 23 characteristics represent almost 70% of the variation. The outcomes of this study have great significance for the strategic designation of QS quenching. By the use of Quorum quenching (QQ) may provide a novel approach for treating bacterial infections of aquacultures. QQ may act as a non-specific (or broad-spectrum) inhibitor of biofilm formation that will help control infectious diseases that adversely affect the aquaculture industry. Effective inhibitors of biofilm formation may prove to be important for protecting industrial aquaculture from the devastating effects of bacterial infections.

Defensins confer host defense against microorganisms and are important for human health. Single nucleotide polymorphisms (SNPs) in defensin gene-coding regions could lead to less active variants. Using SNP data available at the dbSNP database and frequency information from the 1000 Genomes Project, two DEFA5 (L26I and R13H) and eight DEFB1 (C35S, K31T, K33R, R29G, V06I, C12Y, Y28* and C05*) missense and nonsense SNPs that are located within mature regions of the coded defensins were retrieved. Such SNPs are rare and population restricted. In order to assess their antibacterial activity against Escherichia coli, two linear regression models were used from a previous work, which models the antibacterial activity as a function of solvation potential energy, using molecular dynamics data. Regarding only the antibacterial predictions, for HD5, no biological differences between wild-type and its variants were observed; while for HBD1, the results suggest that the R29G, K31T, Y28* and C05* variants could be less active than the wild-type one. The data here reported could lead to a substantial improvement in knowledge about the impact of missense SNPs in human defensins and their world distribution. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 633-644, 2016.

The structure-activity relationship of defensins is not clear. It is known that point mutations in HD5 and HBD1 could modify their activities; however, these mutations do not seem to alter their three-dimensional structures. Here, applying molecular dynamics simulations, this relationship was studied in depth. There are modifications in flexibility, solvent accessible surface area and radius of gyration, but these properties are not reflected in the activity. Only alterations in the solvation potential energy were correlated to antibacterial activity against Escherichia coli. Data here reported could lead to a better understanding of structural and functional aspects of α- and β-defensins.

Defensins comprise a polyphyletic group of multifunctional defense peptides. Cis-defensins, also known as cysteine stabilized αβ (CSαβ) defensins, are one of the most ancient defense peptide families. In plants, these peptides have been divided into two classes, according to their precursor organization. Class I defensins are composed of the signal peptide and the mature sequence, while class II defensins have an additional C-terminal prodomain, which is proteolytically cleaved. Class II defensins have been described in Solanaceae and Poaceae species, indicating this class could be spread among all flowering plants. Here, a search by regular expression (RegEx) was applied to the Arabidopsis thaliana proteome, a model plant with more than 300 predicted defensin genes. Two sequences were identified, A7REG2 and A7REG4, which have a typical plant defensin structure and an additional C-terminal prodomain. TraVA database indicated they are expressed in flower, ovules and seeds, and being duplicated genes, this indicates they could be a result of a subfunctionalization process. The presence of class II defensin sequences in Brassicaceae and Solanaceae and evolutionary distance between them suggest class II defensins may be present in other eudicots. Discovery of class II defensins in other plants could shed some light on flower, ovules and seed physiology, as this class is expressed in these locations.

Antimicrobial peptides (AMPs) are small molecules present in all living beings. Despite their huge sequence variability, AMPs present great structural conservation, mainly in cysteine-stabilized families. Moreover, in non-model plants, it is possible to detect cysteine-stabilized AMPs (cs-AMPs) with different sequences not covered by conventional searches. Here, we described a threading application for cs-AMP identification in the non-model arum lily (Zantedeschia aethiopica) plant, exploring the spathe transcriptome. By using the predicted proteins from the Z. aethiopica transcriptome as our primary source of sequences, we have filtered by using structural alignments of 12 putative cs-AMP sequences. The two unreported sequences were submitted to PCR validation, and ZaLTP7 gene was confirmed. By using the structure alignments, we classified ZaLTP7 as an LTP type 2-like. The successful threading application for cs-AMP identification is an important advance in transcriptomic and proteomic data mining. Besides, the same approach could be applied to the use of NGS public data to discover molecules to combat multidrug-resistant bacteria.

A Paenibacillus elgii strain isolated from soil samples from Cerrado, Brazil, showed antimicrobial activity. Its genome sequence was acquired (GS20 FLX Titanium 454 platform) and comprises 108 contigs (N50, 198,427 bp) and 6,810 predicted sequences., A Paenibacillus elgii strain isolated from soil samples from Cerrado, Brazil, showed antimicrobial activity. Its genome sequence was acquired (GS20 FLX Titanium 454 platform) and comprises 108 contigs (N50, 198,427 bp) and 6,810 predicted sequences. Here, we shed some light on the antimicrobial genes of the strain, including a nonribosomal peptide synthetase (NRPS) module identified as part of a pelgipeptin gene cluster.

ApoE3 is the major chylomicron apolipoprotein, binding in a specific liver peripheral cell receptor, allowing transport and normal catabolism of triglyceride-rich lipoprotein constituents. Point mutations in ApoE3 have been associated with Alzheimer’s disease, type III hyperlipoproteinemia, atherosclerosis, telomere shortening and impaired cognitive function. Here, we evaluate the impact of missense SNPs in APOE retrieved from dbSNP through 16 computational prediction tools, and further evaluate the structural impact of convergent deleterious changes using 100 ns molecular dynamics simulations. We have found structural changes in four analyzed variants (Pro102Arg, Arg132Ser, Arg176Cys and Trp294Cys), two of them (Pro102Arg and Arg176Cys) being previously associated with human diseases. In all cases, except for Trp294Cys, there was a loss in the number of hydrogen bonds between CT and NT domains that could result in their detachment. In conclusion, data presented here could increase the knowledge of ApoE3 activity and be a starting point for the study of the impact of variations on APOE gene.

Guanylin peptides (GPs) are small cysteine-rich peptide hormones involved in salt absorption, regulation of fluids and electrolyte homeostasis. This family presents four members: guanylin (GN), uroguanylin (UGN), lymphoguanylin (LGN) and renoguanylin (RGN). GPs have been used as templates for the development of drugs for the treatment of gastrointestinal disorders. Currently, LGN is the only GP with only one disulfide bridge, making it a remarkable member of this family and a potential drug template; however, there is no structural information about this peptide. In fact, LGN is predicted to be highly disordered and flexible, making it difficult to obtain structural information using in vitro methods. Therefore, this study applied a series of 1 μs molecular dynamics simulations in order to understand the structural behavior of LGN, comparing it to the C115Y variant of GN, which shows the same Cys to Tyr modification. LGN showed to be more flexible than GN C115Y. While the negatively charged N-terminal, despite its repellent behavior, seems to be involved mainly in pH-dependent activity, the hydrophobic core showed to be the determinant factor in LGN's flexibility, which could be essential in its activity. These findings may be determinant in the development of new medicines to help in the treatment of gastrointestinal disorders. Moreover, our investigation of LGN structure clarified some issues in the structure-activity relationship of this peptide, providing new knowledge of guanylin peptides and clarifying the differences between GN C115Y and LGN.

Data mining has been recognized by many researchers as a hot topic in different areas. In the post-genomic era, the growing number of sequences deposited in databases has been the reason why these databases have become a resource for novel biological information. In recent years, the identification of antimicrobial peptides (AMPs) in databases has gained attention. The identification of unannotated AMPs has shed some light on the distribution and evolution of AMPs and, in some cases, indicated suitable candidates for developing novel antimicrobial agents. The data mining process has been performed mainly by local alignments and/or regular expressions. Nevertheless, for the identification of distant homologous sequences, other techniques such as antimicrobial activity prediction and molecular modelling are required. In this context, this review addresses the tools and techniques, and also their limitations, for mining AMPs from databases. These methods could be helpful not only for the development of novel AMPs, but also for other kinds of proteins, at a higher level of structural genomics. Moreover, solving the problem of unannotated proteins could bring immeasurable benefits to society, especially in the case of AMPs, which could be helpful for developing novel antimicrobial agents and combating resistant bacteria.

Defensins confer host defense against microorganisms and are important for human health. Single nucleotide polymorphisms (SNPs) in defensin gene-coding regions could lead to less active variants. Using SNP data available at the dbSNP database and frequency information from the 1000 Genomes Project, two DEFA5 (L26I and R13H) and eight DEFB1 (C35S, K31T, K33R, R29G, V06I, C12Y, Y28* and C05*) missense and nonsense SNPs that are located within mature regions of the coded defensins were retrieved. Such SNPs are rare and population restricted. In order to assess their antibacterial activity against Escherichia coli, two linear regression models were used from a previous work, which models the antibacterial activity as a function of solvation potential energy, using molecular dynamics data. Regarding only the antibacterial predictions, for HD5, no biological differences between wild-type and its variants were observed; while for HBD1, the results suggest that the R29G, K31T, Y28* and C05* variants could be less active than the wild-type one. The data here reported could lead to a substantial improvement in knowledge about the impact of missense SNPs in human defensins and their world distribution. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 633-644, 2016.

The antimicrobial peptides (AMP) have been proposed as an alternative to control resistant pathogens. However, due to multifunctional properties of several AMP classes, until now there has been no way to perform efficient AMP identification, except through in vitro and in vivo tests. Nevertheless, an indication of activity can be provided by prediction methods. In order to contribute to the AMP prediction field, the CS-AMPPred (Cysteine-Stabilized Antimicrobial Peptides Predictor) is presented here, consisting of an updated version of the Support Vector Machine (SVM) model for antimicrobial activity prediction in cysteine-stabilized peptides. The CS-AMPPred is based on five sequence descriptors: indexes of (i) α-helix and (ii) loop formation; and averages of (iii) net charge, (iv) hydrophobicity and (v) flexibility. CS-AMPPred was based on 310 cysteine-stabilized AMPs and 310 sequences extracted from PDB. The polynomial kernel achieves the best accuracy on 5-fold cross validation (85.81%), while the radial and linear kernels achieve 84.19%. Testing in a blind data set, the polynomial and radial kernels achieve an accuracy of 90.00%, while the linear model achieves 89.33%. The three models reach higher accuracies than previously described methods. A standalone version of CS-AMPPred is available for download at and runs on any Linux machine.