Biology subjects

Shrestha, M.

Publications and source records attributed to Shrestha, M..

9 recordsLinked to original sources

bioRxiv2026

Lytic bacteriophages against Salmonella Typhi as a potential alternative to antibiotics

IntroductionEnteric fever, being endemic with seasonal peaks in low- and middle-income countries, is a major health concern. Moreover, the rise in antibiotic resistance has exacerbated the situation. This study was undertaken to investigate the lytic bacteriophages against Salmonella Typhi with a potential for phage therapy. Materials and MethodsA hospital-based cross-sectional study was conducted from October 2023 to March 2024. Blood cultures were processed by the BACTEC automated culture system following standard microbiological techniques to isolate typhoidal Salmonella. Antibiotic susceptibility was tested by the modified Kirby-Bauer disc diffusion method. Lytic bacteriophages isolated by the double-layer agar method were assessed for their host range and lytic ability with spot and turbidimetric assays. ResultsOf the total 1054 blood specimens, 35 (3.2%) were positive for S. Typhi. All the isolates were susceptible to first-line antibiotics--ampicillin, chloramphenicol, and cotrimoxazole. The isolates were also sensitive to nalidixic acid (80%) as well as fluoroquinolones; ciprofloxacin (62.86%), levofloxacin (77.14%), and ofloxacin (80%). Fifteen lytic phages were isolated against S. Typhi Ty2 and CT18 strains. Four phages--vB_SaTy_ST2, vB_SaTy_ST7, vB_SaTy_ST17, and vB_SaTy_ST18--lysed all 35 clinical S. Typhi isolates. While vB_SaTy_ST17 and vB_SaTy_ST18 also lysed 7 out of 20 S. Paratyphi A isolates. Three phages (vB_SaTy_ST2, vB_SaTy_ST7, vB_SaTy_ST17) were tested against S. Typhi isolate S30. Individually, vB_SaTy_ST17 suppressed the growth for 13 hours, vB_SaTy_ST2 and vB_SaTy_ST7 for 10 hours. The phage cocktail vB_SaTy_ST2 + vB_SaTy_ST17 was the most effective, which extended the inhibition time to 15 hours. ConclusionThis study highlights the ongoing burden of enteric fever in Nepal and the increase in susceptibility of S. Typhi to nalidixic acid and fluoroquinolones. It also demonstrates the promising lytic potential of bacteriophages, particularly vB_SaTy_ST17 and the phage cocktail vB_SaTy_ST2 + vB_SaTy_ST17, against clinical S. Typhi, highlighting their potential as alternatives to antibiotics.

microbiology↗

bioRxiv2024

Prevalence of Class 1 integron in disease-causing carbapenem-resistant Escherichia coli in a tertiary hospital in Kathmandu, Nepal

BackgroundHigh prevalence of carbapenem resistance genes have been abundantly reported within clinical E. coli in Nepal but their co-prevalence with class-1 integron is poorly documented. These Class I Integrons play pivotal role in evolution and spread of antimicrobial resistance (AMR). Therefore, it is necessary to highlight their epidemiological significance, so this study determined the prevalence of Class 1 integrons within Carbapenem resistance Escherichia coli (CREc) population. MethodsFifty-two clinical E. coli with confirmed resistance to Meropenem were collected between January 2020-April 2022 in Kathmandu Model Hospital, and undergone antimicrobial susceptibility testing for 11 antimicrobial classes. Carbapenemase production was confirmed by eCIM and mCIM methods. Presence of Class I integron and carbapenemase genes, blaNDM-1, blaKPC, blaIMP, blaVIM, blaOXA-23, blaOXA-48, was confirmed by PCR method. ResultsThe result revealed 92.3% (n=48/52) of the isolates harbored intI1 gene. Among integron-positive population, 97.9% (n=47/48) were carbapenemase producers which were further identified as metallo {beta}-lactamase (MBL) producers (82.9%, n=39/47) and serine {beta}-lactamase (SBL) producer (17%, n=8/47). Carbapenemase gene blaNDM-1 (79.2%, n=38/48) was highly prevalent within integron-positive isolates, followed by blaOXA-23 (62.5%, n=30/48) and blaOXA-48 (54.2%, n=26/48). All integron-positive CREc isolates were resistant to minimum 16 antibiotics tested, but were susceptible to Colistin, Polymixin B, and Tigecycline. ConclusionIn conclusion, Class 1 integrons were highly prevalent within clinical CREc in Nepal, and their co-prevalence with other CRE gene is concerning due to possibility of wider spread. Therefore, an in-depth genomic analysis of Class 1 integrons is needed to understand the integron mediated AMR in high risk clones like CREc and inform intervention measures to stop spread of such pathogens.

microbiology↗

bioRxiv2024

Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex Diseases

Genome-wide association studies (GWAS) provide valuable insights into the genetic architecture of complex traits, yet interpreting their results remains challenging due to the polygenic nature of most traits. Gene set analysis offers a solution by aggregating genetic variants into biologically relevant pathways, enhancing the detection of coordinated effects across multiple genes. In this study, we present and evaluate a gene set prioritization approach utilizing Bayesian Linear Regression (BLR) models to uncover shared genetic components among different phenotypes and facilitate biological interpretation. Through extensive simulations and analyses of real traits, we demonstrate the efficacy of the BLR model in prioritizing pathways for complex traits. Simulation studies reveal insights into the models performance under various scenarios, highlighting the impact of factors such as the number of causal genes, proportions of causal variants, heritability, and disease prevalence. Application of both single-trait and multi-trait BLR models to real data, specifically GWAS summary data for type 2 diabetes (T2D) and related phenotypes, identifies significant associations with T2D-related pathways. Furthermore, comparison between single- and multi-trait BLR analyses highlights the superior performance of the multi-trait approach in identifying associated pathways, showcasing increased statistical power when analyzing multiple traits jointly. Additionally, enrichment analysis with integrated data from various public resources supports our results, confirming significant enrichment of diabetes-related genes within the top T2D pathways resulting from the multi-trait analysis. The BLR models ability to handle diverse genomic features, perform regularization, conduct variable selection, and integrate information from multiple traits, genders, and ancestries demonstrates its utility in understanding the genetic architecture of complex traits. Our study provides insights into the potential of the BLR model to prioritize gene sets, offering a flexible framework applicable to various datasets. This model presents opportunities for advancing personalized medicine by exploring the genetic underpinnings of multifactorial traits, potentially leading to tailored therapeutic interventions.

genomics↗

bioRxiv2024

Evaluation of Bayesian Linear Regression Derived Gene Set Test Methods

Gene set tests can pinpoint genes and biological pathways that exert small to moderate effects on complex diseases like Type 2 Diabetes (T2D). By aggregating genetic markers based on biological information, these tests can enhance the statistical power needed to detect genetic associations. Our goal was to develop a gene set test utilizing Bayesian Linear Regression (BLR) models, which account for both linkage disequilibrium (LD) and the complex genetic architectures intrinsic to diseases, thereby increasing the detection power of genetic associations. Through a series of simulation studies, we demonstrated how the efficacy of BLR derived gene set tests is influenced by several factors, including the proportion of causal markers, the size of gene sets, the percentage of genetic variance explained by the gene set, and the genetic architecture of the traits. Comparing our method with other approaches, such as the gold standard MAGMA (Multi-marker Analysis of Genomic Annotation) approach, our BLR gene set test showed superior performance. This suggests that our BLR-based approach could more accurately identify genes and biological pathways underlying complex diseases.

genomics↗

bioRxiv2023

Comparative reservoir competence of Peromyscus leucopus and mouse models for Borrelia burgdorferi B31

Borrelia burgdorferi, a Lyme disease spirochete, causes a range of acute and chronic maladies in humans. However, a primary vertebrate reservoir in the United States, the white-footed deermouse Peromyscus leucopus, is reported not to have reduced fitness following infection. While laboratory strains of Mus musculus mice have successfully been leveraged to model acute human Lyme disease, the ability for these rodents to model B. burgdorferi-P. leucopus interactions remains understudied. Here we compared infection of P. leucopus with B. burgdorferi B31 with infection of the traditional B. burgdorferi murine models--C57BL/6J and C3H/HeN Mus musculus, which develop signs of inflammation akin to human disease. We find that B. burgdorferi were able to reach much higher burdens (10- to 30-times higher) in multiple M. musculus skin sites, and that the overall dynamics of infection differed between the two rodent species. We also found that P. leucopus remained transmissive to larval Ixodes scapularis for a far shorter period than either M. musculus strain. In line with these observations, we found that P. leucopus does launch a modest but sustained inflammatory response against B. burgdorferi in the skin, which we hypothesize leads to reduced bacterial viability and rodent-to-tick transmission in these hosts. Similarly, we also observe evidence of inflammation in infected P. leucopus hearts. These observations provide new insight into reservoir species and the B. burgdorferi enzootic cycle. ImportanceA Lyme disease-causing bacteria, Borrelia burgdorferi, must alternate between infecting a vertebrate host--usually rodents or birds--and ticks. In order to be successful in that endeavor the bacteria must avoid being killed by the vertebrate host before it can infect a new larval tick. In this work we examine how B. burgdorferi and one of its primary vertebrate reservoirs, Peromyscus leucopus, interact during an experimental infection. We find that B. burgdorferi appear to colonize its natural host less successfully than conventional laboratory mouse models which aligns with a sustained seemingly anti-bacterial response by P. leucopus against the microbe. These data enhance our understanding of P. leucopus host-pathogen interactions and could potentially serve as a foundation to uncover ways to disrupt the spread of B. burgdorferi in nature.

microbiology↗

bioRxiv2023

Evaluation of Bayesian Linear Regression Models as a Fine Mapping tool

Our aim was to evaluate Bayesian Linear Regression (BLR) models with BayesC and BayesR priors as a fine mapping tool and compare them to the state-of-the-art external models: FINEMAP, SuSIE-RSS, SuSIE-Inf and FINEMAP-Inf. Based on extensive simulations, we evaluated the different models based on F1 classification score. The different models were applied on quantitative and binary UK Biobank (UKB) phenotypes and evaluated based upon predictive accuracy and features of credible sets (CSs). We used over 533K genotyped and 6.6 million imputed single nucleotide polymorphisms (SNPs) for simulations and UKB phenotypes respectively, from over 335K UKB White British Unrelated samples. We simulated phenotypes from low (GA1) to moderate (GA2) polygenicity, heritability (h2) of 10% and 30%, causal SNPs ({pi}) of 0.1% and 1% sampled genome-wide, and disease prevalence (PV) of 5% and 15%. Single marker summary statistics and in-sample linkage disequilibrium were used to fit models in regions defined by lead SNPs. BayesR improved the F1 score, averaged across all simulations, between 27.26% and 13.32% relative to the external models. Predictive accuracy quantified as variance explained (R2), averaged across all the UKB quantitative phenotypes, with BayesR was decreased by 5.32% (SuSIE-Inf) and 3.71% (FINEMAP-Inf), and was increased by 7.93% (SuSIE-RSS) and 8.3% (BayesC). Area under the receiver operating characteristic curve averaged across all the UKB binary phenotypes, with BayesR was increased between 0.40% and 0.05% relative to the external models. SuSIE-RSS and BayesR, demonstrated the highest number of CSs, with BayesC and BayesR exhibiting the smallest average median size CSs in the UKB phenotypes. The BLR models performed similar to the external models. Specifically, BayesRs performance closely aligned with SuSIE-Inf and FINEMAP-Inf models. Collectively, our findings from both simulations and application of the models in the UKB phenotypes support that the BLR models are efficient fine mapping tools.

genomics↗

bioRxiv2022

Patterns and determinants of the global herbivorous mycobiome

In spite of their indispensable role in host nutrition, the anaerobic gut fungal (AGF) component of the herbivorous gut microbiome remains poorly characterized. To examine global patterns and determinants of AGF diversity, we generated and analyzed an amplicon dataset from 661 fecal samples from 34 animal species, 9 families, and 6 continents. We identified 56 novel genera, greatly expanding AGF diversity beyond current estimates. Both stochastic (homogenizing dispersal and drift) and deterministic (homogenizing selection) processes played an integral role in shaping AGF communities, with a higher level of stochasticity observed in foregut fermenters. Community structure analysis revealed a distinct pattern of phylosymbiosis, where host-associated (animal species, family, and gut type), rather than ecological (domestication status and biogeography) factors predominantly shaped the community. Hindgut fermenters exhibited stronger and more specific fungal-host associations, compared to broader mostly non-host specific associations in foregut fermenters. Transcriptomics-enabled phylogenomic and molecular clock analyses of 52 strains from 14 genera indicated that most genera with preferences for hindgut hosts evolved earlier (44-58 Mya), while those with preferences for foregut hosts evolved more recently (22-32 Mya). This pattern is in agreement with the sole dependence of herbivores on hindgut fermentation past the Cretaceous-Paleogene (K-Pg) extinction event through the Paleocene and Eocene, and the later rapid evolution of animals employing foregut fermentation strategy during the early Miocene. Only a few AGF genera deviated from this pattern of co-evolutionary phylosymbiosis, by exhibiting preferences suggestive of post-evolutionary environmental filtering. Our results greatly expand the documented scope of AGF diversity and provide an ecologically and evolutionary-grounded model to explain the observed patterns of AGF diversity in extant animal hosts.

microbiology↗

bioRxiv2019

Australian native flower colours: does nectar reward drive bee pollinator flower preferences?

Colour is an important signal that flowering plants use to attract insect pollinators like bees. Previous research in Germany has shown that nectar volume is higher for flower colours that are innately preferred by European bees, suggesting an important link between colour signals, bee preferences and floral rewards. In Australia, flower colour signals have evolved in parallel to the Northern hemisphere to enable easy discrimination and detection by the phylogenetically ancient trichromatic visual system of bees, and native Australian bees also possess similar innate colour preferences to European bees. We measured 59 spectral signatures from flowers present at two preserved native habitats in South Eastern Australia and tested whether there were any significant differences in the frequency of flowers presenting higher nectar rewards depending upon the colour category of the flower signals, as perceived by bees. We also tested if there was a significant correlation between chromatic contrast and the frequency of flowers presenting higher nectar rewards. For the entire sample, and for subsets excluding species in the Asteraceae and Orchidaceae, we found no significant difference among colour categories in the frequency of high nectar reward. This suggests that whilst such relationships between flower colour signals and nectar volume rewards have been observed at a field site in Germany, the effect is likely to be specific at a community level rather than a broad general principle that has resulted in the common signalling of bee flower colours around the world.

ecology↗

bioRxiv2019

Organizational properties of a functional mammalian cis-regulome

Mammalian genomic states are distinguished by their chromatin and transcription profiles. Most genomic analyses rely on chromatin profiling to infer cis-regulomes controlling distinctive cellular states. By coupling FAIRE-seq with STARR-seq and integrating Hi-C we assemble a functional cis-regulome for activated murine B-cells. Within 55,130 accessible chromatin regions we delineate 9,989 active enhancers communicating with 7,530 promoters. The cis-regulome is dominated by long range enhancer-promoter interactions (>100kb) and complex combinatorics, implying rapid evolvability. Genes with multiple enhancers display higher rates of transcription and multi-genic enhancers manifest graded levels of H3K4me1 and H3K27ac in poised and activated states, respectively. Motif analysis of pathway-specific enhancers reveals diverse transcription factor (TF) codes controlling discrete processes. The cis-regulome strikingly enriches for combinatorial DNA binding regions of lineage determining TFs. Their genomic binding patterns reveal that onset of chromatin accessibility is associated with binding of simpler combinations whereas enhancer function requires greater complexity.

systems biology↗