Sathyabaarathi Ravichandran

Macrophages are driven to form distinct functional phenotypes in response to different immunological stimuli, in a process widely referred to as macrophage polarization. Transcriptional regulators that guide macrophage polarization in response to a given trigger remain largely unknown. In this study, we interrogate the programmable landscape in macrophages to find regulatory panels that determine the precise polarization state that a macrophage is driven to. Toward this, we configure an integrative network analysis pipeline that utilizes macrophage transcriptomes in response to 28 distinct stimuli, reconstructs contextualized human gene regulatory networks, and identifies epicenters of perturbations in each case. We find that these contextualized regulatory networks form a spectrum of 13 distinct clusters, with M1 and M2 at the two ends. Using our computational pipeline, we identify combinatorial panels of epicentric regulatory factors (RFs) for each polarization state. We demonstrate that a set of three RFs, that is, CEBPB , NFE2L2 , and BCL3 , is sufficient to change the polarization destination from M1 to M2. siRNA knockdown of the 3-RF-set in THP1-derived M0 cells, despite exposure to an M1 stimulant, significantly attenuated the shift to M1 phenotype and instead increased the expression of M2 markers. Single knockdown of each RF also showed a similar trend. The siRNA-mediated knockdown of the 3-RF-set rendered the macrophages hyper-susceptible to Staphylococcus aureus infection, demonstrating the importance of these factors in modulating immune responses. Overall, our results provide insights into the transcriptional mechanisms underlying macrophage polarization and identify key RFs that may be targeted to modulate immune responses.

Macrophages are driven to form distinct functional phenotypes in response to different immunological stimuli, in a process widely referred to as macrophage polarization. Transcriptional regulators that guide macrophage polarization in response to a given trigger remain largely unknown. In this study, we interrogate the programmable landscape in macrophages to find regulatory panels that determine the precise polarization state that a macrophage is driven to. Towards this, we configure an integrative network analysis pipeline that utilizes macrophage transcriptomes in response to 28 distinct stimuli and reconstructs contextualized human gene regulatory networks, and identifies epicentres of perturbations in each case. We find that these contextualized regulatory networks form a spectrum of thirteen distinct clusters with M1 and M2 at the two ends. Using our computational pipeline, we identify combinatorial panels of epicentric regulatory factors (RFs) for each polarization state. We demonstrate that a set of three RFs i.e., CEBPB, NFE2L2 and BCL3, is sufficient to change the polarization destination from M1 to M2. siRNA knockdown of the 3-RF set in THP1 derived M0 cells, despite exposure to an M1 stimulant, significantly attenuated the shift to M1 phenotype, and instead increased the expression of M2 markers. Single knockdown of each RF also showed a similar trend. The siRNA-mediated knockdown of the 3-RF set rendered the macrophages hyper-susceptible to Staphylococcus aureus infection, demonstrating the importance of these factors in modulating immune responses. Overall, our results provide insights into the transcriptional mechanisms underlying macrophage polarization and identify key regulatory factors that may be targeted to modulate immune responses.

Pneumococcal infections cause serious illness and death among older adults. The capsular polysaccharide vaccine PPSV23 and conjugated alternative PCV13 can prevent these infections; yet, underlying immunological responses and baseline predictors remain unknown. We vaccinated 39 older adults (>60 years) with PPSV23 or PCV13 and observed comparable antibody responses (day 28) and plasmablast transcriptional responses (day 10); however, the baseline predictors were distinct. Analyses of baseline flow cytometry and bulk and single-cell RNA-sequencing data revealed a baseline phenotype specifically associated with weaker PCV13 responses, which was characterized by increased expression of cytotoxicity-associated genes, increased frequencies of CD16⁺ natural killer cells and interleukin-17-producing helper T cells and a decreased frequency of type 1 helper T cells. Men displayed this phenotype more robustly and mounted weaker PCV13 responses than women. Baseline expression levels of a distinct gene set predicted PPSV23 responses. This pneumococcal precision vaccinology study in older adults uncovered distinct baseline predictors that might transform vaccination strategies and initiate novel interventions.

Macrophages are driven to form distinct functional phenotypes in response to different immunological stimuli, in a process widely referred to as macrophage polarization. Transcriptional regulators that guide macrophage polarization in response to a given trigger remain largely unknown. In this study, we interrogate the programmable landscape in macrophages to find regulatory panels that determine the precise polarization state that a macrophage is driven to. Towards this, we configure an integrative network analysis pipeline that utilizes macrophage transcriptomes in response to 28 distinct stimuli and reconstructs contextualized human gene regulatory networks, and identifies epicentres of perturbations in each case. We find that these contextualized regulatory networks form a spectrum of thirteen distinct clusters with M1 and M2 at the two ends. Using our computational pipeline, we identify combinatorial panels of epicentric regulatory factors (RFs) for each polarization state. We demonstrate that a set of three RFs i.e., CEBPB , NFE2L2 and BCL3 , is sufficient to change the polarization destination from M1 to M2. siRNA knockdown of the 3-RF set in THP1 derived M0 cells, despite exposure to an M1 stimulant, significantly attenuated the shift to M1 phenotype, and instead increased the expression of M2 markers. Single knockdown of each RF also showed a similar trend. The siRNA-mediated knockdown of the 3-RF set rendered the macrophages hyper-susceptible to Staphylococcus aureus infection, demonstrating the importance of these factors in modulating immune responses. Overall, our results provide insights into the transcriptional mechanisms underlying macrophage polarization and identify key regulatory factors that may be targeted to modulate immune responses.

Drug resistance is a public health concern that threatens to undermine decades of medical progress. ESKAPE pathogens cause most nosocomial infections, and are frequently resistant to carbapenem antibiotics, usually leaving tigecycline and colistin as the last treatment options. However, increasing tigecycline resistance and colistin’s nephrotoxicity severely restrict use of these antibiotics. We have designed antimicrobial peptides using a maximum common subgraph approach. Our best peptide (Ω76) displayed high efficacy against carbapenem and tigecycline-resistant Acinetobacter baumannii in mice. Mice treated with repeated sublethal doses of Ω76 displayed no signs of chronic toxicity. Sublethal Ω76 doses co-administered alongside sublethal colistin doses displayed no additive toxicity. These results indicate that Ω76 can potentially supplement or replace colistin, especially where nephrotoxicity is a concern. To our knowledge, no other existing antibiotics occupy this clinical niche. Mechanistically, Ω76 adopts an α-helical structure in membranes, causing rapid membrane disruption, leakage, and bacterial death.

Background: Brain-derived neurotrophic factor (BDNF) is a potent neurotrophic factor that is implicated in the regulation of food intake and body weight. Polyunsaturated fatty acids (PUFAs) localised in cell membranes have been shown to alter the levels of BDNF in the brain, suggesting that PUFAs and BDNF could have physical interaction with each other. To decipher the molecular mechanism through which PUFAs modulates BDNF’s activity, molecular docking was performed for BDNF with PUFAs and its metabolites, with 4-Methyl Catechol as a control.Results: Inferring from molecular docking studies, lipoxin A4 (LXA4), and a known anti-inflammatory bioactive metabolite derived from PUFAs, with a binding energy of −3.98 Kcal/mol and dissociation constant of 1.2mM showed highest binding affinity for BDNF in comparison to other PUFAs and metabolites considered in the study. Further, the residues Lys 18, Thr 20, Ala 21, Val 22, Phe 46, Glu 48, Lys 50, Lys 58, Thr 75, Gln 77, Arg 97 and Ile 98 form hot point motif, which on interaction enhances BDNF’s function.Conclusion: These results suggest that PUFAs and their metabolites especially, LXA4, modulate insulin resistance by establishing a physical interaction with BDNF. Similar interaction(s) was noted between BDNF and resolvins and protectins but were of lesser intensity compared to LXA4.

Background: HSV-1 genome is a mosaic of recombinants. Clinical Herpes simplex virus -1 (HSV1) isolates were already genotyped as A, B and C types based on nucleotide variations at Unique Short (US) 4 (gG) and US 7 (gI) regions through phylogeny. Analysis of Glycoprotein C (gC) exon present on the Unique Long (UL) region had also revealed the existence of different genotypes. Glycoprotein C is mainly involved in initial viral attachment to heparan sulphate on host cell surface facilitating the virus's binding and penetration into cell. As the amount of heparan sulphate on the host cell surface varies according to the cell type, it is plausible that different genotypes bind differentially to cell types. Hence, this study was framed to determine the existence of novel genotypes/sub genotypes in the US or UL regions which could associate with clinical entities. Results: All the twenty five isolates analyzed in this study were of genotype A as per their gG gene sequences. In case of gI gene, 16 out of 25 were found to be type A and the remaining nine were type B putative intergenic recombinants. Intragenic recombinations were also encountered in both the US genes, with gG possessing novel subgenotypes, arbitrarily designated A1 and A2. The 9 type B isolates of gI genes also branched out into 2 clades due to genetic variations. Glycoprotein C of UL region had two distinct genotypic clades α and β, whose topological distribution was significantly different from that of the US region. Neither the US nor UL regions, however, showed any preference among the genotypes to a specific anatomic site of infection. Even the non synonymous variations identified in the functional domain of gC, were not confined to a particular genotype/clinical entity. Conclusion: The analyses of the US and UL regions of the HSV-1 genome showed the existence of variegated genotypes in these two regions. In contrary to the documented literature, in which Asian strains were concluded as more conserved than European ones, our study showed the existence of a higher degree of variability among Indian strains. However, the identified novel genotypes and subgenotypes were not found associated with clinical entities.