Differentially expressed heterogeneous overdispersion genes testing for count data.

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size, where overdispersion refers to the empirical phenomenon that the variance of read counts is larger than the mean of read counts. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes when the number of replicates is limited as long as the number of conditions is large. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq2 and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments.

Differentially Expressed Heterogeneous Overdispersion Genes Testing for Count Data.

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments.

How Individual Variation in Host Tolerance Affects Competence to Transmit Parasites.

Tolerance, or the maintenance of host health or fitness at a given parasite burden, has often been studied in evolutionary and medical contexts, particularly with respect to effects on the evolution of parasite virulence and individual patient outcomes. These bodies of work have provided insight about tolerance for evolutionary phenomena (e.g., virulence) and individual health (e.g., recovering from an infection). However, due to the specific motivations of that work, few studies have considered the ecological ramifications of variation in tolerance, namely, how variation in forms of tolerance could mediate parasite movement through populations and even community-level disease dynamics. Tolerance is most commonly regarded as the relationship between host fitness and parasite burden. However, few if any studies have actually quantified host fitness, instead utilizing proxies of fitness as the response variables to be regressed against parasite burden. Here, we address how attention to the effects of parasite burden on traits that are relevant to host competence (i.e., the ability to amplify parasites to levels transmissible to other hosts/vectors) will enhance our understanding of disease dynamics in nature. We also provide several forms of guidance for how to overcome the challenges of quantifying tolerance in wild organisms.

Parasite Tolerance and Host Competence in Avian Host Defense to West Nile Virus.

Competence, or the propensity of a host to transmit parasites, is partly underlain by host strategies to cope with infection (e.g., resistance and tolerance). Resistance represents the ability of hosts to prevent or clear infections, whereas tolerance captures the ability of individuals to cope with a given parasite burden. Here, we investigated (1) whether one easy-to-measure form of tolerance described well the dynamic relationships between host health and parasite burden, and (2) whether individual resistance and tolerance to West Nile virus (WNV) were predictable from single cytokine measures. We exposed house sparrows (HOSP) to WNV and measured subsequent changes in host performance, viral burden, and cytokine expression. We then used two novel approaches (one complex, one simpler) to estimate tolerance within-individual HOSP using four separate host performance traits. We lastly investigated changes in the expression of pro-inflammatory cytokine interferon-γ (IFN-γ) and anti-inflammatory cytokine interleukin-10 (IL-10). Both approaches to estimating tolerance were equivalent among WNV-infected HOSP; thus, an easy-to-measure tolerance estimation may be successfully applied in field studies. Constitutive expression of IFN-γ and IL-10 were predictive of resistance and tolerance to WNV, implicating these cytokines as viable biomarkers of host competence to WNV.

Stress hormones predict a host superspreader phenotype in the West Nile virus system.

Glucocorticoid stress hormones, such as corticosterone (CORT), have profound effects on the behaviour and physiology of organisms, and thus have the potential to alter host competence and the contributions of individuals to population- and community-level pathogen dynamics. For example, CORT could alter the rate of contacts among hosts, pathogens and vectors through its widespread effects on host metabolism and activity levels. CORT could also affect the intensity and duration of pathogen shedding and risk of host mortality during infection. We experimentally manipulated songbird CORT, asking how CORT affected behavioural and physiological responses to a standardized West Nile virus (WNV) challenge. Although all birds became infected after exposure to the virus, only birds with elevated CORT had viral loads at or above the infectious threshold. Moreover, though the rate of mortality was faster in birds with elevated CORT compared with controls, most hosts with elevated CORT survived past the day of peak infectiousness. CORT concentrations just prior to inoculation with WNV and anti-inflammatory cytokine concentrations following viral exposure were predictive of individual duration of infectiousness and the ability to maintain physical performance during infection (i.e. tolerance), revealing putative biomarkers of competence. Collectively, our results suggest that glucocorticoid stress hormones could directly and indirectly mediate the spread of pathogens.

Host stress hormones alter vector feeding preferences, success, and productivity.

Stress hormones might represent a key link between individual-level infection outcome, population-level parasite transmission, and zoonotic disease risk. Although the effects of stress on immunity are well known, stress hormones could also affect host-vector interactions via modification of host behaviours or vector-feeding patterns and subsequent reproductive success. Here, we experimentally manipulated songbird stress hormones and examined subsequent feeding preferences, feeding success, and productivity of mosquito vectors in addition to defensive behaviours of hosts. Despite being more defensive, birds with elevated stress hormone concentrations were approximately twice as likely to be fed on by mosquitoes compared to control birds. Moreover, stress hormones altered the relationship between the timing of laying and clutch size in blood-fed mosquitoes. Our results suggest that host stress could affect the transmission dynamics of vector-borne parasites via multiple pathways.