Single-cell transcriptomics: background, technologies, applications, and challenges.

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Exploring structural antigens of yellow fever virus to design multi-epitope subunit vaccine candidate by utilizing an immuno-informatics approach.

BACKGROUND: Yellow fever is a mosquito-borne viral hemorrhagic disease transmitted by several species of virus-infected mosquitoes endemic to tropical regions of Central and South America and Africa. Earlier in the twentieth century, mass vaccination integrated with mosquito control was implemented to eradicate the yellow fever virus. However, regular outbreaks occur in these regions which pose a threat to travelers and residents of Africa and South America. There is no specific antiviral therapy, but there can be an effective peptide-based vaccine candidate to combat infection caused by the virus. Therefore, the study aims to design a multi-epitope-based subunit vaccine (MESV) construct against the yellow fever virus to reduce the time and cost using reverse vaccinology (RV) approach. METHODS: Yellow fever virus contains 10,233 nucleotides that encode for 10 proteins (C, prM, E, NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) including 3 structural and 7 non-structural proteins. Structural proteins-precursor membrane protein (prM) and envelope protein (E)-were taken as a target for B cell and T cell epitope screening. Further, various immunoinformatics approaches were employed to FASTA sequences of structural proteins to retrieve B cell and T cell epitopes. MESV was constructed from these epitopes based on allergenicity, antigenicity and immunogenicity, toxicity, conservancy, and population coverage followed by structure prediction. The efficacy of the MESV construct to bind with human TLR-3, TLR-4, and TLR-8 were evaluated using molecular docking and simulation studies. Finally, in-silico cloning of vaccine construct was performed withpBR322 Escherichia coli expression system using codon optimization. RESULTS: Predicted epitopes evaluated and selected for MESV construction were found stable, non-allergenic, highly antigenic, and global population coverage of 68.03% according to in-silico analysis. However, this can be further tested in in-vitro and in-vivo investigations. Epitopes were sequentially merged to construct a MESV consisting of 393 amino acids using adjuvant and linkers. Molecular docking and simulation studies revealed stable and high-affinity interactions. Furthermore, in-silico immune response graphs showed effective immune response generation. Finally, higher CAI value ensured high gene expression of vaccine in the host cell. CONCLUSION: The designed MESV construct in the present in-silico study can be effective in generating an immune response against the yellow fever virus. Therefore, to prevent yellow fever, it can be an effective vaccine candidate. However, further downstream, in-vitro study is required.

In silico and in vitro evaluation of designed fluconazole analogues as lanosterol 14α-demethylase inhibitors.

The drugs fighting against aggressive fungal infections are in limited number, therefore, extensive research is obligatory to develop new therapeutic strategies. Fluconazole (FLZ) is a clinically approved drug, but resistant drug against most fungal pathogens, thus it is vital to identify more compounds that can better check the fungal growth. Analogue-based drug designing is a quick and economical way since it has inherent drug-like properties of marketed drugs. This study aims to generate and evaluate analogues of FLZ with better potency against fungal-borne infections. A total of 3307 analogues of FLZ were developed from six scaffold structures. Only 390 compounds passed Lipinski's rule, of which 247 analogues exhibited lower docking scores than FLZ with 5FSA. These inhibitors were further subjected to pharmacokinetics property evaluation and cytotoxicity test and it was found that only 46 analogues were suitable for further evaluation. Based on the molecular docking score of the best two analogues, 6f (-12.7 kcal/mol) and 8f (-12.8 kcal/mol) were selected for molecular dynamics and in-vitro studies. Antifungal activities of both compounds against 4 strains of Candida albicans were evaluated by disc diffusion assay and micro broth dilution assay and Minimum inhibitory concentrations (MICs) for 6f and 8f were observed as 256 µg/ml against 4719, 4918 and 5480 strains but the MIC was extended to 512 µg/ml for strain 3719. Both analogues exhibited low antifungal activities as compared to FLZ (8-16 µg/ml). The interaction of 6f with Mycostatin was also performed using a chequerboard assay that was found additive.Communicated by Ramaswamy H. Sarma.

Development of pharmacophore model to identify potential DNA gyrase inhibitors.

There is great concern in the medical community due to rapid increase in antibiotic resistance, causing 700,000 deaths annually worldwide. Therefore, there is paramount need to develop novel and innovative antibacterial agents active against resistant bacterial strains. DNA gyrase is a crucial enzyme in bacterial replication that is absent in eukaryotes, making it effective curative target for antibacterials. To identify potential DNA gyrase inhibitors by virtual screening of NCI database using a 3-step approach. A total of 271 compounds with known IC50 values against Escherichia coli DNA GyrA were selected to develop a pharmacophore model for dual screening approach to identify new potential hits from the NCI database. In the second step, the NCI database was also screened using in-house built NN-QSAR model. Molecular docking of common 5298 compounds screened from both methods were performed against E. coli DNA GyrA (PDB id- 6RKU), and 3004 compounds are reported to exhibit lower binding energies than ciprofloxacin (-6.77 Kcal/mol). The top three compounds (NCI371878, NCI371876 and NCI142159) reported with binding energy of -13.5, -13.19 and -13.03 Kcal/mol were further subjected to MD simulation studies for 100 ns supporting the stability of the docked complexes.

A computational approach to discover antioxidant and anti-inflammatory attributes of silymarin derived from Silybum marianum by comparison with hydroxytyrosol.

Medicinal plants possess therapeutic potential for reducing reactive oxygen species (ROS)-mediated cellular damage. Hydroxytyrosol is one of the most potent antioxidants that served as control in the current study, including other synthetic antioxidants to computationally identify the antioxidant properties of Silymarin. The sequences of the receptors IκB kinase (IKK), Kelch-like ECH-associated protein 1 (Keap-1) and mitochondrial transcription factor A (Tfam) were retrieved from UniProtKB and homology modeling was performed using Swiss-Model server. Thereof the molecular docking and dynamic simulation studies were performed using Schrödinger's software version 11.5. From the current study, it was reported that on comparison of the binding energy of silymarin, hydroxytyrosol, α-tocopherol, ascorbic acid, butylated hydroxy anisole (BHA) and butylated hydroxytoluene (BHT), Silymarin exhibited better affinities with IKK receptor followed by Hydroxytyrosol suggesting it as the best or comparable of all other known antioxidants that could potentially suppress inflammation and other diseases. Also, Silymarin exhibited poorest binding affinity with Tfam promoting mitochondrial biogenesis, thereby scavenging ROS. However, with Keap-1, Silymarin is ranked 4th in the list, whereas hydroxytyrosol exhibited highest binding affinity to release oxidative stress. The stability of docked complexes made us conclude that Silymarin has comparable antioxidant properties to hydroxytyrosol, better anti-inflammatory potential and mitochondrial biogenesis enhancing properties to ultimately reduce oxidative stress. Now it can be tested further for in vitro or in vivo studies as potential drug against oxidative insult.Communicated by Ramaswamy H. Sarma.

Comparative genome analysis of Streptococcus strains to identify virulent genes causing neonatal meningitis.

AIM: To determine Streptococcus agalactiae genes responsible for causing neonatal meningitis. BACKGROUND: Streptococcus agalactiae strain 2603 V/R is causative agent of neonatal meningitis, maternal infection and sepsis in young children. World health organisation reported high burden of new born death caused by this bacterium. Streptococcus agalactiae colonizing epithelial cells of vagina and endothelial cells have high resistance to available antibiotic drugs which makes it essential to determine new drug targets. OBJECTIVES: To compare the genome of selected strain with the non-pathogenic strains of streptococcus and identify the virulent and antibiotic resistant genes for adaptation in host environment. METHOD: The whole genome of human pathogen Streptococcus agalactiae strain 2603 V/R was analysed and compared with Streptococcus dysgalactiae strains using visualization and annotation tools. Genomic islands, mobile genetic elements, virulent and resistant genes were studied. RESULTS: Genetically pathogenic strain is most similar to Streptococcus dysgalactiae subsp. equisimilis strain NCTC 7136. Comparative analysis revealed the importance of capsular polysaccharides and surface proteins responsible for avoiding immune system attachment to host epithelial cells and virulent behaviour. High number of genes coding for antibiotics resistance may provide a competitive advantage for survival of pathogenic Streptococcus agalactiae strain 2603 V/R in its niche. CONCLUSIONS: The comparative analysis of pathogenic strain Streptococcus agalactiae with non-pathogenic strains of Streptococcus dysgalactiae provided new insights in pathogenicity that could aid in recognization for new regions and genes for development of new drug development strategies considering presence of high number of resistance genes.

Discovery of Novel Inhibitors of Bacterial DNA Gyrase Using a QSAR-Based Approach.

Type II topoisomerases like DNA gyrase initiate ATP-dependent negative supercoils in bacterial DNA. It is critical in all of the bacteria but is missing from eukaryotes, making it a striking target for antibacterials. Ciprofloxacin is a clinically approved drug, but its clinical effectiveness is affected by the emergence of resistance in both Gram-positive and Gram-negative bacteria. Thus, it is vital to identify novel compounds that can efficiently inhibit DNA gyrase, and quantitative structure-activity relationship (QSAR) modeling is a quick and economical means to do so. A QSAR-based virtual screening approach was applied to identify new gyrase inhibitors using an in-house-generated combinatorial library of 29828 compounds from seven ciprofloxacin scaffold structures. QSAR was built using a data set of 271 compounds, which were identified as positive and negative inhibitors from existing data reported in in vitro studies. The best QSAR model was developed using the 5-fold cross-validation Neural Network in Orange, and it was based on five PaDEL descriptors with an accuracy and sensitivity of 83%. As a result of screening of an in-house-built combinatorial library with the best-developed QSAR model, 675 compounds were identified as potential inhibitors of DNA gyrase. These inhibitors were further docked with DNA gyrase using AutoDock to compare the binding mode and score of the selected/screened compounds, and 615 compounds exhibited a docking score comparable to or lower than that of ciprofloxacin. Out of these, the top five analogues 902b, 9699f, 4419f, 5538f, and 898b reported in our study have binding scores of -13.81, -12.95, -12.52, -12.43, and -12.41 kcal/mol, respectively. The MD simulations of these five analogues for 100 ns supported the interaction stability of analogues with Escherichia coli DNA gyrase. Ninety-one per cent of the analogues screened by the QSAR model displayed better binding energy than ciprofloxacin, demonstrating the efficacy of the generated model. The NN-QSAR model proposed in this manuscript can be downloaded from https://github.com/ritu225/NN-QSAR_model.git.

Chemotherapeutic Strategies for Combating Staphylococcus aureus Infections.

Staphylococcus aureus is a prominent human pathogen that causes nosocomial and community acquired infections. The accelerating emergence and prevalence of staphylococcal infections have grotesque health consequences which are mostly due to its anomalous capability to acquire drug resistance and scarcity of novel classes of antibacterials. Many combating therapies are centered on primary targets of S. aureus which are cell envelope, ribosomes and nucleic acids. This review describes various chemotherapeutic strategies for combating S. aureus infections including monotherapy, combination drug therapy, phage endolysin therapy, lysostaphins and antibacterial drones. Monotherapy has dwindled in due course of time, but combination therapy, endolysin therapy, lysostaphin and antibacterial drones are emerging alternatives which efficiently conquer the shortcomings of monotherapy. Combinations of more than one antibiotic agents or combination of adjuvant with antibiotics provide a synergistic approach to combat infections causing pathogenic strains. Phage endolysin therapy and lysostaphin are also presented as possible alternatives to conventional antibiotic therapies. Antibacterial Drones go a step further by specifically targeting the virulence genes in bacteria, giving them a certain advantage over existing antibacterial strategies. But the challenge remains on the better understanding of these strategies for executing and implementing them in the health sector. In this day and age, most of the S. aureus strains are resistant to an ample number of antibiotics, so there is an urgent need to overcome such multidrug-resistant strains for the welfare of our community.

Growing Preferences towards Analog-based Drug Discovery.

BACKGROUND: The major concern of today's time is the developing resistance in most of the clinically derived pathogenic micro-organisms for available drugs through several mechanisms. Therefore, there is a dire need to develop novel molecules with drug-like properties that can be effective against the otherwise resistant micro-organisms. METHODS: New drugs can be developed using several methods like structure-based drug design, ligandbased drug design, or by developing analogs of the available drugs to further improve their effects. However, the smartness is to opt for the techniques that have comparatively less expenditure, lower failure rates, and faster discovery rates. RESULTS: Analog-Based Drug Design (ABDD) is one such technique that researchers worldwide are opting to develop new drug-like molecules with comparatively lower market values. They start by first designing the analogs sharing structural and pharmacological similarities to the existing drugs. This method embarks on scaffold structures of available drugs already approved by the clinical trials, but are left ineffective because of resistance developed by the pathogens. CONCLUSION: In this review, we have discussed some recent examples of anti-fungal and anti-bacterial (antimicrobial) drugs that were designed based on the ABDD technique. Also, we have tried to focus on the in silico tools and techniques that can contribute to the designing and computational screening of the analogs, so that these can be further considered for in vitro screening to validate their better biological activities against the pathogens with comparatively reduced rates of failure.

Advances in tuberculous meningitis diagnosis.

Introduction: Tuberculous meningitis (TBM) is the most devastating form of central nervous system tuberculosis (TB) and causes high mortality worldwide. Nonspecific clinical manifestations and limited sensitivity of existing laboratory methods make the diagnosis elusive due to the paucibacillary nature of the infection. Areas Covered: We reviewed current literature on the adequacy and limitations of globally existing laboratory methods for diagnosing TBM. Expert opinion: TBM is deadliest among all TB forms, as the outcome may lead to death in 50% of cases, and survivors undergo irreversible neurological disorders. Therefore, early diagnosis and prompt treatment are cornerstones of effective disease management. Conventional microscopy and culture are widely used modalities but remain inadequate in most TBM cases. Although expanded use of rapid molecular tests such as real-time PCR and Xpert Ultra, even in resource-limited settings, hold promising results for TB diagnosis but need optimization for early detection of TBM. Moreover, CSF IGRA is also used but unable to differentiate between active and latent TB. Overall no single test for diagnosing TBM has adequate accuracy so, there is an urgent need to devise a point-of-care test.

In Silico Protein Interaction Network Analysis of Virulence Proteins Associated with Invasive Aspergillosis for Drug Discovery.

BACKGROUND: Protein-Protein interaction (PPI) network analysis of virulence proteins of Aspergillus fumigatus is a prevailing strategy to understand the mechanism behind the virulence of A. fumigatus. The identification of major hub proteins and targeting the hub protein as a new antifungal drug target will help in treating the invasive aspergillosis. MATERIALS & METHOD: In the present study, the PPI network of 96 virulence (drug target) proteins of A. fumigatus were investigated which resulted in 103 nodes and 430 edges. Topological enrichment analysis of the PPI network was also carried out by using STRING database and Network analyzer a cytoscape plugin app. The key enriched KEGG pathway and protein domains were analyzed by STRING. CONCLUSION: Manual curation of PPI data identified three proteins (PyrABCN-43, AroM-34, and Glt1- 34) of A. fumigatus possessing the highest interacting partners. Top 10% hub proteins were also identified from the network using cytohubba on the basis of seven algorithms, i.e. betweenness, radiality, closeness, degree, bottleneck, MCC and EPC. Homology model and the active pocket of top three hub proteins were also predicted.

The Sesamum indicum Rhizosphere Associated Bacterium: A Source of Antifungal Compound.

BACKGROUND: The impact of fungal infections on human health has increased considerably within a past few decades. Although drugs with antifungal properties are available, but they are less effective and are associated with side effects. OBJECTIVE AND METHOD: To screen the bacterial isolates from Sesamum indicum and to investigate the antifungal activity of the screened bacterial isolates against Aspergillus sp. Co-culture assay and agar overlay were used to scrutinize the anti-Aspergillus activity. Furthermore, optimization of media and growth conditions to enhance the production of anti-Aspergillus compound. RESULTS: Several bacterial cultures were isolated from Sesamum indicum rhizosphere collected from Mandi (H.P.) India. These bacterial cultures were assayed for antifungal activity against Aspergillus species i.e. A. fumigatus and A. niger. Two most potent strains were chosen for more detailed analyses. The biochemical characterization and 16S ribosomal RNA sequencing revealed that Burkholderia sp. strain RC1 and Acinetobacter pittii strain RC2 exhibit strong similarity (100%) with Burkholderia sp. SR2-07 and Acinetobacter sp. strain 3-59. Additionally, it was also validated that RC1 and RC2 showed significant difference in the production of anti-Aspergillusactivity under altered growth conditions. CONCLUSION: Results from this study recommend that plant rhizosphere remains a rich hotspot for delivering a novel antifungal compounds.