Biology subjects

Kelada, S. N. P.

Publications and source records attributed to Kelada, S. N. P..

8 recordsLinked to original sources

bioRxiv2024

Alveolar macrophages play a key role in tolerance to ozone

Acute exposure to ozone (O3) causes pulmonary inflammation and injury in humans and animal models. In rodents, acute O3-induced inflammation and injury can be mitigated by pre-exposure to relatively low concentration O3, a phenomenon referred to as tolerance. While tolerance was described long ago, the underlying mechanisms are not known, though upregulation of antioxidants has been proposed. To identify new mechanisms for O3 tolerance, we generated a mouse model in which female C57BL6/NJ mice were pre-exposed to filtered air (FA) or 0.8 ppm O3 for four days (4 hours/day), then challenged with 2 ppm O3 (3 hours) 2 days later, and phenotyped for airway inflammation and injury 6 or 24 hours thereafter. As expected, pre-exposure to O3 resulted in significantly reduced airway inflammation and injury at 24 hours, as well as reduced induction of antioxidant genes. Like previous studies in rats, tolerance was associated with changes in the frequency and proliferation of alveolar epithelial cells, but was not associated with upregulation of antioxidants, CCSP (SCGB1A1), or mucus. We found that alveolar macrophages (AMs) play a critical role in tolerance, as depletion of AMs using clodronate in mice pre-exposed to O3 restored many responses to acute O3 challenge. Further, AMs of O3 tolerized mice exhibited decreased expression of genes involved in cellular signaling via Toll-like receptors, MYD88, and NF-kB, and proinflammatory cytokine production. We conclude that O3 tolerance is highly, but not exclusively, dependent on AMs, and that further studies investigating how repeated O3 exposure induces hypo-responsiveness in AMs are warranted.

pharmacology and toxicology↗

bioRxiv2021

A novel gene-by-environment quantitative trait locus on mouse chromosome 15 underlies susceptibility to acute ozone-induced lung injury

Respiratory toxicity caused by the common urban air pollutant ozone (O3) varies considerably within the human population and across inbred mouse strains, suggestive of gene-environment interactions (GxE). Though previous studies genetic mapping studies using classical inbred strains have identified several and quantitative trait locus (QTL) and candidate genes underlying responses to O3 exposure, precise mechanisms of susceptibility remain incompletely described. We sought to expand our understanding of the genetic architecture of O3 responsiveness using the Collaborative Cross (CC) recombinant inbred mouse panel, which contains more genetic diversity than previous inbred strain panels. We evaluated hallmark O3-induced respiratory phenotypes in 56 CC strains after exposure to filtered air or 2 ppm O3, and performed focused genetic analysis of variation in lung injury as measured by the total bronchoalveolar lavage protein concentration. Because animals were exposed in sex- and batch-matched pairs, we defined a protein response phenotype as the difference in lavage protein between the O3- and FA-exposed animal within a pair. The protein response phenotype was heritable, and QTL mapping revealed two novel loci on Chromosomes 10 (peak: 26.2 Mb; 80% CI: 24.6-43.6 Mb) and 15 (peak: 47.1 Mb; 80% CI: 40.2-54.9 Mb), the latter surpassing the 95% significance threshold. At the Chr. 15 locus, C57BL/6J and CAST/EiJ founder haplotypes were associated with higher protein responses compared to all other CC founder strain haplotypes. Using additional statistical analysis and high-density SNP data, we delimited the Chr. 15 QTL to a [~]2 Mb region containing 21 genes (10 protein coding). Using a weight of evidence approach that incorporated candidate variant analysis, functional annotations, and publicly available lung gene expression data, we nominated three candidate genes (Oxr1, Rspo2, and Angpt1). In summary, we have shown that O3-induced lung injury is modulated by genetic variation and demonstrated the value of the CC for uncovering and dissecting gene-environment interactions.

genetics↗

bioRxiv2021

Integrative phenotypic and genomic analyses reveal strain-dependent responses to acute ozone exposure and their associations with airway macrophage transcriptional activity

Acute ozone (O3) exposure is associated with multiple adverse cardiorespiratory outcomes, the severity of which varies across human populations and rodent models from diverse genetic backgrounds. However, molecular determinants of response, including biomarkers that distinguish which individuals will develop more severe injury and inflammation (i.e., high responders), are poorly characterized. Here, we exposed adult, female and male mice from 6 strains, including 5 Collaborative Cross (CC) strains, to filtered air (FA) or 2 ppm O3 for 3 hours, and measured several inflammatory and injury parameters 21 hours later. Additionally, we collected airway macrophages and performed RNA-seq analysis to investigate influences of strain, treatment, and strain-by-treatment interactions on gene expression as well as transcriptional correlates of lung phenotypes. Animals exposed to O3 developed airway neutrophilia and lung injury, with varying degrees of severity. We identified many genes that were altered by O3 exposure across all strains, and examination of genes whose expression was influenced by strain-by-treatment interactions revealed prominent differences in response between the CC017/Unc and CC003/Unc strains, which were low- and high-responders, respectively (as measured by cellular inflammation and injury). Further investigation of this contrast indicated that baseline gene expression differences likely contribute to their divergent post-O3 exposure transcriptional responses. We also observed alterations in chromatin accessibility that differed by strain and with strain-by-treatment interactions, lending further plausibility that baseline differences can modulate post-exposure responses. Together, these results suggest that aspects of the respiratory response to O3 exposure may be mediated through altered airway macrophage transcriptional signatures, and further confirms the importance of gene-by-environment interactions in mediating differential responsiveness to environmental agents.

pharmacology and toxicology↗

bioRxiv2020

BPIFB1 loss alters airway mucus properties and diminishes mucociliary clearance.

Airway mucociliary clearance (MCC) is required for host defense and often diminished in chronic lung diseases. Effective clearance depends upon coordinated actions of the airway epithelium and a mobile mucus layer. Dysregulation of the primary secreted airway mucin proteins, MUC5B and MUC5AC, is associated with a reduction in the rate of MCC; however, how other secreted proteins impact the integrity of the mucus layer and MCC remains unclear. We previously identified the gene Bpifb1/Lplunc1 as a regulator of airway MUC5B levels using genetic approaches. Here, we show that BPIFB1 is required for normal mucociliary clearance in vivo using Bpifb1 knockout (KO) mice. Reduced MCC in Bpifb1 KO mice occurred in the absence of defects in sodium or chloride ion transport or reduced ciliary beat frequency. BPIFB1 loss resulted in airway mucus flakes with significantly increased complex viscosity, a key biophysical property of mucus known to impact MCC. Finally, we detected colocalization of BPIFB1 and MUC5B in secretory granules in mice and in the protein mesh of secreted mucus in human airway cultures. Collectively, our findings demonstrate that BPIFB1 is an important component of the mucociliary apparatus in mice and a key component of the mucus protein network.

physiology↗

bioRxiv2020

Inferring the Allelic Series in a Multiparental Population

Multiparental populations (MPPs) are experimental populations in which the genome of every individual is a mosaic of known founder haplotypes. These populations are useful for detecting quantitative trait loci (QTL) because tests of association can leverage inferred founder haplotype descent. It is difficult, however, to determine how haplotypes at a locus group into distinct functional alleles, termed the allelic series. The allelic series is important because it provides information about the number of causal variants at a QTL and their combined effects. In this study, we introduce a fully-Bayesian model selection framework for inferring the allelic series. This framework accounts for sources of uncertainty found in typical MPPs, including the number and composition of functional alleles. Our prior distribution for the allelic series is based on the Chinese restaurant process, a relative of the Dirichlet process, and we leverage its connection to the coalescent to introduce additional prior information about haplotype relatedness via a phylogenetic tree. We evaluate our approach via simulation and apply it to QTL from two MPPs: the Collaborative Cross (CC) and the Drosophila Synthetic Population Resource (DSPR). We find that, although posterior inference of the exact allelic series is often uncertain, we are able to distinguish biallelic QTL from more complex multiallelic cases. Additionally, our allele-based approach improves haplotype effect estimation when the true number of functional alleles is small. Our method, Tree-Based Inference of Multiallelism via Bayesian Regression (TIMBR), provides new insight into the genetic architecture of QTL in MPPs.

genetics↗

bioRxiv2020

Content and performance of the MiniMUGA genotyping array, a new tool to improve rigor and reproducibility in mouse research

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well annotated genome, wealth of genetic resources and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost effective, informative and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole genome sequencing. Here we describe the content and performance of a new Mouse Universal Genotyping Array (MUGA). MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: 1) chromosomal sex determination, 2) discrimination between substrains from multiple commercial vendors, 3) diagnostic SNPs for popular laboratory strains, 4) detection of constructs used in genetically engineered mice, and 5) an easy to interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA we genotyped 6,899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived and recombinant inbred lines. Here we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, the extension of the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. There is preliminary but striking evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the main stock for a significant action of the genotyped inbred samples. We conclude that MiniMUGA is a valuable platform for genetic QC and important new tool to the increase rigor and reproducibility of mouse research.

genetics↗

bioRxiv2019

Transcriptional profiling of the murine airway response to acute ozone exposure

Exposure to ambient ozone (O3) pollution causes airway inflammation, epithelial injury, and decreased lung function. Long-term exposure is associated with increased mortality and exacerbations of respiratory conditions. While the adverse health effects of O3 exposure have been thoroughly described, less is known about the molecular processes that drive these outcomes. The aim of this study was to describe the cellular and molecular alterations observed in murine airways after exposure to either 1 or 2 ppm O3. After exposing adult, female C57BL/6J mice to filtered air, 1 or 2 ppm O3 for 3 hours, we assessed hallmark responses including airway inflammatory cell counts, epithelial permeability, cytokine secretion, and morphological alterations of the large airways. Further, we performed RNA-seq to profile gene expression in two critical tissues involved in O3 responses: conducting airways (CA) and airway macrophages (AM). We observed a concentration-dependent increase in airway inflammation and injury, and a large number of genes were differentially expressed in both target tissues at both concentrations of O3. Genes that were differentially expressed in CA were generally associated with barrier function, detoxification processes, and cellular proliferation. The differentially expressed genes in AM were associated with innate immune signaling, cytokine production, and extracellular matrix remodeling. Overall, our study has described transcriptional responses to acute O3 exposure, revealing both shared and unique gene expression patterns across multiple concentrations of O3 and in two important O3-responsive tissues. These profiles provide broad mechanistic insight into pulmonary O3 toxicity, and reveal a variety of targets for refined follow-up studies.

pharmacology and toxicology↗

bioRxiv2018

Determinants of QTL mapping power in the realized Collaborative Cross

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses based on extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

genetics↗