Distinct baseline immune characteristics associated with responses to conjugated and unconjugated pneumococcal polysaccharide vaccines in older adults.

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.

Baseline immune states (BIS) associated with vaccine responsiveness and factors that shape the BIS.

Vaccines are among the greatest inventions in medicine, leading to the elimination or control of numerous diseases, including smallpox, polio, measles, rubella, and, most recently, COVID-19. Yet, the effectiveness of vaccines varies among individuals. In fact, while some recipients mount a robust response to vaccination that protects them from the disease, others fail to respond. Multiple clinical and epidemiological factors contribute to this heterogeneity in responsiveness. Systems immunology studies fueled by advances in single-cell biology have been instrumental in uncovering pre-vaccination immune cell types and genomic features (i.e., the baseline immune state, BIS) that have been associated with vaccine responsiveness. Here, we review clinical factors that shape the BIS, and the characteristics of the BIS associated with responsiveness to frequently studied vaccines (i.e., influenza, COVID-19, bacterial pneumonia, malaria). Finally, we discuss potential strategies to enhance vaccine responsiveness in high-risk groups, focusing specifically on older adults.

Distinct baseline immune characteristics associated with responses to conjugated and unconjugated pneumococcal polysaccharide vaccines in older adults.

Pneumococcal infections cause serious illness and death among older adults. A capsular polysaccharide vaccine PPSV23 (Pneumovax®) and a conjugated polysaccharide vaccine PCV13 (Prevnar®) are used to prevent these infections, yet underlying responses, and baseline predictors remain unknown. We recruited and vaccinated 39 older adults (>60 years) with PPSV23 or PCV13. Both vaccines induced strong antibody responses at day 28 and similar plasmablast transcriptional signatures at day 10, however, their baseline predictors were distinct. Analyses of baseline flow cytometry and RNA-seq data (bulk and single cell) revealed a novel baseline phenotype that is specifically associated with weaker PCV13 responses, characterized by i) increased expression of cytotoxicity-associated genes and increased CD16+ NK frequency; ii) increased Th17 and decreased Th1 cell frequency. Men were more likely to display this cytotoxic phenotype and mounted weaker responses to PCV13 than women. Baseline expression levels of a distinct gene set was predictive of PPSV23 responses. This first precision vaccinology study for pneumococcal vaccine responses of older adults uncovered novel and distinct baseline predictors that might transform vaccination strategies and initiate novel interventions.

A new blood-based RNA signature (R9), for monitoring effectiveness of tuberculosis treatment in a South Indian longitudinal cohort.

Tuberculosis (TB) treatment involves a multidrug regimen for six months, and until two months, it is unclear if treatment is effective. This delay can lead to the evolution of drug resistance, lung damage, disease spread, and transmission. We identify a blood-based 9-gene signature using a computational pipeline that constructs and interrogates a genome-wide transcriptome-integrated protein-interaction network. The identified signature is able to determine treatment response at week 1-2 in three independent public datasets. Signature-based R9-score correctly detected treatment response at individual timepoints (204 samples) from a newly developed South Indian longitudinal cohort involving 32 patients with pulmonary TB. These results are consistent with conventional clinical metrics and can discriminate good from poor treatment responders at week 2 (AUC 0.93(0.81-1.00)). In this work, we provide proof of concept that the R9-score can determine treatment effectiveness, making a case for designing a larger clinical study.

VB10, a new blood biomarker for differential diagnosis and recovery monitoring of acute viral and bacterial infections.

BACKGROUND: Precise differential diagnosis between acute viral and bacterial infections is important to enable appropriate therapy, avoid unnecessary antibiotic prescriptions and optimize the use of hospital resources. A systems view of host response to infections provides opportunities for discovering sensitive and robust molecular diagnostics. METHODS: We combine blood transcriptomes from six independent datasets (n = 756) with a knowledge-based human protein-protein interaction network, identifies subnetworks capturing host response to each infection class, and derives common response cores separately for viral and bacterial infections. We subject the subnetworks to a series of computational filters to identify a parsimonious gene panel and a standalone diagnostic score that can be applied to individual samples. We rigorously validate the panel and the diagnostic score in a wide range of publicly available datasets and in a newly developed Bangalore-Viral Bacterial (BL-VB) cohort. FINDING: We discover a 10-gene blood-based biomarker panel (Panel-VB) that demonstrates high predictive performance to distinguish viral from bacterial infections, with a weighted mean AUROC of 0.97 (95% CI: 0.96-0.99) in eleven independent datasets (n = 898). We devise a new stand-alone patient-wise score (VB10) based on the panel, which shows high diagnostic accuracy with a weighted mean AUROC of 0.94 (95% CI 0.91-0.98) in 2996 patient samples from 56 public datasets from 19 different countries. Further, we evaluate VB10 in a newly generated South Indian (BL-VB, n = 56) cohort and find 97% accuracy in the confirmed cases of viral and bacterial infections. We find that VB10 is (a) capable of accurately identifying the infection class in culture-negative indeterminate cases, (b) reflects recovery status, and (c) is applicable across different age groups, covering a wide spectrum of acute bacterial and viral infections, including uncharacterized pathogens. We tested our VB10 score on publicly available COVID-19 data and find that our score detected viral infection in patient samples. INTERPRETATION: Our results point to the promise of VB10 as a diagnostic test for precise diagnosis of acute infections and monitoring recovery status. We expect that it will provide clinical decision support for antibiotic prescriptions and thereby aid in antibiotic stewardship efforts. FUNDING: Grand Challenges India, Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology, Govt. of India.

Ω76: A designed antimicrobial peptide to combat carbapenem- and tigecycline-resistant Acinetobacter baumannii.

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.

Computational antimicrobial peptide design and evaluation against multidrug-resistant clinical isolates of bacteria.

There is a pressing need for new therapeutics to combat multidrug- 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 multidrug-resistant clinical isolates of Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and coagulase-negative staphylococci strains. High activity against extended-spectrum ß-lactamase, methicillin-resistant S. aureus, 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.

Modulation of multidrug resistance 1 expression and function in retinoblastoma cells by curcumin.

OBJECTIVE: To determine the possible interaction of curcumin with P-glycoprotein (P-gp) expression and function by in vitro and in silico studies. MATERIALS AND METHODS: In this study, curcumin was compared for its potential to modulate the expression and function of P-gp in Y79 RB cells by western blot, RT-PCR (reverse transcription polymerase chain reaction) and functional assay. Further, in silico molecular modeling and docking simulations were performed to deduce the inhibitory binding mode of curcumin. RESULTS: Western blot and RT-PCR analysis decreased the expression of P-gp in a dose-dependent manner. The effect of curcumin on P-gp function was demonstrated by Rhodamine 123 (Rh123) accumulation and efflux study. Curcumin increased the accumulation of Rh123 and decreased its efflux in retinoblastoma (RB) cells. In addition, curcumin inhibited verapamil stimulated ATPase activity and photoaffinity labeling study showed no effect on the binding of 8-azido-ATP-biotin, indicating its interaction at the substrate binding site. Moreover, molecular docking studies concurrently infer the binding of curcumin into the substrate binding site of P-gp with a binding energy of -7.66 kcal/mol. CONCLUSION: These findings indicate that curcumin suppresses the MDR1 expression and function, and therefore may be useful as modulators of multidrug resistance in RB tumor.

Phylogenetic comparison of exonic US4, US7 and UL44 regions of clinical herpes simplex virus type 1 isolates showed lack of association between their anatomic sites of infection and genotypic/sub genotypic classification.

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 ß, 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.

In vitro and In silico studies on inhibitory effects of curcumin on multi drug resistance associated protein (MRP1) in retinoblastoma cells.

Multi Drug Resistance (MDR) is one of the major causes of chemotherapy failure in human malignancies. Curcumin, the active constituent of Curcuma longa is a proven anticancer agent potentially modulating the expression and function of these MDR proteins. In this study, we attempted to test curcumin for its potential to inhibit the expression and function of multidrug resistance associated protein 1 (MRP1) in retinoblastoma (RB) cell lines through western blot, RT-PCR and functional assays. In silico analysis were also performed to understand the molecular interactions conferred by curucmin on MRP1 in RB cells. Western blot and RTPCR analysis did not show any correlation of MRP1 expression with increase in concentration of curcumin. However, inhibitory effect of curcumin on MRP1 function was observed as a decrease in the efflux of fluorescent substrate. Moreover, Curcumin did not affect 8-azido-ATP-biotin binding to MRP1 and it also showed inhibition of ATP-hydrolysis stimulated by quercetin, which is indicative of curcumin's interaction with the substrate binding site of MRP1. Furthermore, homology modelling and docking simulation studies of MRP1 also provided deeper insights into the molecular interactions, thereby inferring the potential binding mode of curcumin into the substrate binding site of MRP1.