Cathelicidin (hCAP-18/LL-37) and beta-defensin 1 (HBD-1) are human antimicrobial peptides (AMPs) with high basal expression levels, which form the first line of host defence against infections over the epithelial surfaces. The antimicrobial functions owe to their direct microbicidal effects as well as the immunomodulatory role. Pathogenic microorganisms have developed multiple modalities including transcriptional repression to combat this arm of the host immune response. The precise mechanisms and the pathogen-derived molecules responsible for transcriptional downregulation remain unknown. Here, we have shown that enteric pathogens suppress LL-37 and HBD-1 expression in the intestinal epithelial cells (IECs) with Vibrio cholerae and enterotoxigenic Escherichia coli (ETEC) exerting the most dramatic effects. Cholera toxin (CT) and labile toxin (LT), the major virulence proteins of V. cholerae and ETEC, respectively, are predominantly responsible for these effects, both in vitro and in vivo. CT transcriptionally downregulates the AMPs by activating several intracellular signalling pathways involving protein kinase A (PKA), ERK MAPKinase and Cox-2 downstream of cAMP accumulation and inducible cAMP early repressor (ICER) may mediate this role of CT, at least in part. This is the first report to show transcriptional repression of the AMPs through the activation of cellular signal transduction pathways by well-known virulence proteins of pathogenic microorganisms.

Gut microbiota of higher vertebrates is host-specific. The number and diversity of the organisms residing within the gut ecosystem are defined by physiological and environmental factors, such as host genotype, habitat, and diet. Recently, culture-independent sequencing techniques have added a new dimension to the study of gut microbiota and the challenge to analyze the large volume of sequencing data is increasingly addressed by the development of novel computational tools and methods. Interestingly, gut microbiota maintains a constant relative abundance at operational taxonomic unit (OTU) levels and altered bacterial abundance has been associated with complex diseases such as symptomatic atherosclerosis, type 2 diabetes, obesity, and colorectal cancer. Therefore, the study of gut microbial population has emerged as an important field of research in order to ultimately achieve better health. In addition, there is a spontaneous, non-linear, and dynamic interaction among different bacterial species residing in the gut. Thus, predicting the influence of perturbed microbe–microbe interaction network on health can aid in developing novel therapeutics. Here, we summarize the population abundance of gut microbiota and its variation in different clinical states, computational tools available to analyze the pyrosequencing data, and gut microbe–microbe interaction networks.

Antimicrobial peptides (AMPs) are integral components of the host innate immune system and functional throughout the plant and animal kingdoms. AMPs are short cationic molecules and lethal against a wide range of bacteria, viruses, fungi, yeast and protozoa due to their membranolytic effects on the negatively-charged microbial membranes. In addition, they exert multiple immunomodulatory roles like chemotaxis, modulation of cytokine and chemokine expression, leukocyte activation etc. Since AMPs suffer loss of microbicidal properties under serum and tissue environments, their capacity to modulate the immune system may predominates under the physiological conditions. Discovery of new antibiotics is lagging far behind the rapidly spreading drug resistance among the microorganisms. Both natural and synthetic AMPs have shown promise as ‘next generation antibiotics’ due to their unique mode of action, which minimises the chance of development of microbial resistance. In addition, they have therapeutic potential against non-infectious diseases like chronic inflammation and cancer. Many of the synthetic AMPs are currently undergoing clinical trials for the treatment of debilitating diseases, such as catheter-related infections, diabetic foot ulcers, chemotherapy-associated infections etc. Some of them have already entered the market as topical preparations. In this review, we synopsise the current literature of natural and synthetic AMPs in different infectious and inflammatory diseases of human microfloral habitats, especially the gastrointestinal, respiratory and genitourinary tracts and the skin. We also discuss the classification of AMPs, their mode action and antimicrobial spectrum, including the pathogen evasion mechanisms. In short, we tried to present the locus standi of AMPs in relation to human diseases and highlight the most promising synthetic peptides emerging from the clinical trials. Finally, we focused on the limitations and hurdles in terms of cost of production, bioavailability, pharmacokinetic stability and toxicity faced by commercial development and clinical use of the AMPs and strategies to overcome these hurdles.

Viral-host protein-protein interaction plays a vital role in pathogenesis, since it defines viral infection of the host and regulation of the host proteins. Identification of key viral-host protein-protein interactions (PPIs) has great implication for therapeutics. In this study, a systematic attempt has been made to predict viral-host PPIs by integrating different features, including domain-domain association, network topology and sequence information using viral-host PPIs from VirusMINT. The three well-known supervised machine learning methods, such as SVM, Naïve Bayes and Random Forest, which are commonly used in the prediction of PPIs, were employed to evaluate the performance measure based on five-fold cross validation techniques. Out of 44 descriptors, best features were found to be domain-domain association and methionine, serine and valine amino acid composition of viral proteins. In this study, SVM-based method achieved better sensitivity of 67% over Naïve Bayes (37.49%) and Random Forest (55.66%). However the specificity of Naïve Bayes was the highest (99.52%) as compared with SVM (74%) and Random Forest (89.08%). Overall, the SVM and Random Forest achieved accuracy of 71% and 72.41%, respectively. The proposed SVM-based method was evaluated on blind dataset and attained a sensitivity of 64%, specificity of 83%, and accuracy of 74%. In addition, unknown potential targets of hepatitis B virus-human and hepatitis E virus-human PPIs have been predicted through proposed SVM model and validated by gene ontology enrichment analysis. Our proposed model shows that, hepatitis B virus “C protein” binds to membrane docking protein, while “X protein” and “P protein” interacts with cell-killing and metabolic process proteins, respectively. The proposed method can predict large scale interspecies viral-human PPIs. The nature and function of unknown viral proteins (HBV and HEV), interacting partners of host protein were identified using optimised SVM model.

Although nanoparticle-tagged antimicrobal peptides have gained considerable importance in recent years, their structure–function correlation has not yet been explored. Here, we have studied the mechanism of action of a designed antimicrobial peptide, VG16KRKP (VARGWKRKCPLFGKGG), delivered via gold nanoparticle tagging against Salmonella infection by combining biological experiments with high- and low-resolution spectroscopic techniques. In comparison with the free VG16KRKP peptide or gold nanoparticle alone, the conjugated variant, Au-VG16KRKP, is non-cytotoxic to eukaryotic cells, but exhibits strong bacteriolytic activity in culture. Au-VG16KRKP can penetrate host epithelial and macrophage cells as well as interact with intracellular S. Typhi LPS under both in vitro and in vivo conditions. Treatment of mice with Au-VG16KRKP post-infection with S. Typhi resulted in reduced intracellular bacterial recovery and highly enhanced protection against S. Typhi challenge. The three-dimensional high resolution structure of nanoparticle conjugated VG16KRKP depicted the generation of a well-separated amphipathic structure with slight aggregation, responsible for the increase of the local concentration of the peptide, thus leading to potent activity. This is the first report on the structural and functional characterization of a nanoparticle conjugated synthetic antimicrobial peptide that can kill intracellular pathogens and eventually protect against S. Typhi challenge in vivo.