There is a pressing need for new therapeutics to combat multi-drug and carbapenem-resistant bacterial pathogens. This challenge prompted us to use a long short-term memory (LSTM) language model to understand the underlying grammar, i.e. the arrangement and frequencies of amino acid residues, in known antimicrobial peptide sequences. According to the output of our LSTM network, we synthesized 10 peptides and tested them against known bacterial pathogens. All of these peptides displayed broad-spectrum antimicrobial activity, validating our LSTM-based peptide design approach. Our two most effective antimicrobial peptides displayed activity against multidrugresistant (MDR) clinical isolates of Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and coagulase-negative staphylococci (CoNS) strains. High activity against extended-spectrum beta-lactamase (ESBL), meticillin-resistant S. aureus (MRSA), and carbapenem-resistant strains was also observed. Our peptides selectively interacted with and disrupted bacterial cell membranes and caused secondary gene-regulatory effects. Initial structural characterization revealed that our most effective peptide appeared to be well folded. We conclude that our LSTM-based peptide design approach appears to have correctly deciphered the underlying grammar of antimicrobial peptide sequences, as demonstrated by the experimentally observed efficacy of our designed peptides.Antibiotic resistance is an ever-increasing threat which is gradually rendering our current repertoire of antibiotics obsolete. If no new drugs are developed, deaths due to antimicrobial resistance are expected to exceed 10 million annually by 2050 (1). Antimicrobial peptides (AMPs) are one potential solution to this problem. Naturally occurring AMPs continue to remain an important component of the innate immune system despite their ancient evolutionary origin and widespread prevalence across many forms of life (2). Some derivatives of these such as pexiganan (3), omiganan (4), and OP-145 (5) are currently undergoing late-stage clinical trials (for diabetic foot ulcers, rosacea, and ear infections respectively (6)). Other peptides such as Novexatin (7) and Lytixar (8) are currently undergoing early-stage clinical trials (for the treatment of toenail fungal infections and MRSA respectively (6)). Currently, over 2000 natural and designed antimicrobial peptides are curated in various databases (9-11), and have displayed broad-spectrum activity against Gram positive, Gram negative, fungal, mycobacterial, and protozoal pathogens (9). Designed AMPs vs. MDR isolates.positive charge are attracted and incorporated into negatively charged bacterial membranes. Once inside the membrane, they are believed to cause disruption through three possible mechanisms: toroidal pore formation (12), carpet formation (13), and barrel stave formation (14). Although the specifics of each mechanism differ, all propose peptide-induced membrane rupture, allowing cytoplasmic leak...

Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host’s whole blood transcriptomic profiles that were integrated into a genome-scale protein–protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data.

Lipocalins constitute a superfamily of extracellular proteins that are found in all three kingdoms of life. Although very divergent in their sequences and functions, they show remarkable similarity in 3-D structures. Lipocalins bind and transport small hydrophobic molecules. Earlier sequence-based phylogenetic studies of lipocalins highlighted that they have a long evolutionary history. However the molecular and structural basis of their functional diversity is not completely understood. The main objective of the present study is to understand functional diversity of the lipocalins using a structure-based phylogenetic approach. The present study with 39 protein domains from the lipocalin superfamily suggests that the clusters of lipocalins obtained by structure-based phylogeny correspond well with the functional diversity. The detailed analysis on each of the clusters and sub-clusters reveals that the 39 lipocalin domains cluster based on their mode of ligand binding though the clustering was performed on the basis of gross domain structure. The outliers in the phylogenetic tree are often from single member families. Also structure-based phylogenetic approach has provided pointers to assign putative function for the domains of unknown function in lipocalin family. The approach employed in the present study can be used in the future for the functional identification of new lipocalin proteins and may be extended to other protein families where members show poor sequence similarity but high structural similarity.

BackgroundIn biological systems, diseases are caused by small perturbations in a complex network of interactions between proteins. Perturbations typically affect only a small number of proteins, which go on to disturb a larger part of the network. To counteract this, a stress-response is launched, resulting in a complex pattern of variations in the cell. Identifying the key players involved in either spreading the perturbation or responding to it can give us important insights.ResultsWe develop an algorithm, EpiTracer, which identifies the key proteins, or epicenters, from which a large number of changes in the protein-protein interaction (PPI) network ripple out. We propose a new centrality measure, ripple centrality, which measures how effectively a change at a particular node can ripple across the network by identifying highest activity paths specific to the condition of interest, obtained by mapping gene expression profiles to the PPI network.We demonstrate the algorithm using an overexpression study and a knockdown study. In the overexpression study, the gene that was overexpressed (PARK2) was highlighted as the most important epicenter specific to the perturbation. The other top-ranked epicenters were involved in either supporting the activity of PARK2, or counteracting it. Also, 5 of the identified epicenters showed no significant differential expression, showing that our method can find information which simple differential expression analysis cannot. In the second dataset (SP1 knockdown), alternative regulators of SP1 targets were highlighted as epicenters. Also, the gene that was knocked down (SP1) was picked up as an epicenter specific to the control condition. Sensitivity analysis showed that the genes identified as epicenters remain largely unaffected by small changes.ConclusionsWe develop an algorithm, EpiTracer, to find epicenters in condition-specific biological networks, given the PPI network and gene expression levels. EpiTracer includes programs which can extract the immediate influence zone of epicenters and provide a summary of dysregulated genes, facilitating quick biological analysis. We demonstrate its efficacy on two datasets with differing characteristics, highlighting its general applicability. We also show that EpiTracer is not sensitive to minor changes in the network. The source code for EpiTracer is provided at Github (https://github.com/narmada26/EpiTracer).

Background: The objective is to identify the risk factors of Meconium stained deliveries and evaluate the perinatal outcomes in Meconium Stained deliveries.Methods: This prospective observational study included those pregnant women who had completed 37 weeks of gestation, with singleton pregnancies with cephalic presentations and with no known fetal congenital anomalies. Among these, we selected 110 cases with Meconium stained amniotic fluid and they were compared with 110 randomly selected controls.Results: Regular antenatal visits were seen in 22.73 % of the cases while 77.27% cases had no previous visit. Majority of cases were primigravida and gestational ages of >40 weeks was seen in 55.45 % cases. 19.09% cases had meconium staining among pregnancies complicated with pregnancy induced hypertension, as compared to those among controls (5.45%). Fetal heart rate abnormalities were seen in 29.09% cases, and statistically significant fetal bradycardia was seen in cases. Caesarean section rates were nearly double in cases (54.55%). Poor perinatal outcome was found in cases as seen in results by low Apgar score (<7) at 1 minute and 5-minute, higher incidence of birth asphyxia, Meconium Aspiration Syndrome and increased NICU admission as compared to that among controls.Conclusions: Meconium stained amniotic fluid is more commonly associated with higher gestational age >40 weeks, pregnancy induced hypertension and fetal bradycardia, increased cesarean section rates, low APGAR score and higher incidence of birth asphyxia and NICU admissions. Meconium aspiration syndrome was associated with early neonatal death.