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Neurological dysfunction following viral infection varies among individuals, largely due to differences in their genetic backgrounds. Gait patterns, which can be evaluated using measures of coordination, balance, posture, muscle function, step-to-step variability, and other factors, are also influenced by genetic background. Accordingly, to some extent gait can be characteristic of an individual, even prior to changes in neurological function. Because neuromuscular aspects of gait are under a certain degree of genetic control, the hypothesis tested was that gait parameters could be predictive of neuromuscular dysfunction following viral infection. The Collaborative Cross (CC) mouse resource was utilized to model genetically diverse populations and the DigiGait treadmill system used to provide quantitative and objective measurements of 131 gait parameters in 142 mice from 23 CC and SJL/J strains. DigiGait measurements were taken prior to infection with the neurotropic virus Theiler's Murine Encephalomyelitis Virus (TMEV). Neurological phenotypes were recorded over 90 days post-infection (d.p.i.), and the cumulative frequency of the observation of these phenotypes was statistically associated with discrete baseline DigiGait measurements. These associations represented spatial and postural aspects of gait influenced by the 90 d.p.i. phenotype score. Furthermore, associations were found between these gait parameters with sex and outcomes considered to show resistance, resilience, or susceptibility to severe neurological symptoms after long-term infection. For example, higher pre-infection measurement values for the Paw Drag parameter corresponded with greater disease severity at 90 d.p.i. Quantitative trait loci significantly associated with these DigiGait parameters revealed potential relationships between 28 differentially expressed genes (DEGs) and different aspects of gait influenced by viral infection. Thus, these potential candidate genes and genetic variations may be predictive of long-term neurological dysfunction. Overall, these findings demonstrate the predictive/prognostic value of quantitative and objective pre-infection DigiGait measurements for viral-induced neuromuscular dysfunction. [ABSTRACT FROM AUTHOR]

Viral infections contribute to neurological and immunological dysfunction driven by complex genetic networks. Theiler's murine encephalomyelitis virus (TMEV) causes neurological dysfunction in mice and can model human outcomes to viral infections. Here, we used genetically distinct mice from five Collaborative Cross mouse strains and C57BL/6J to demonstrate how TMEV-induced immune responses in serum may predict neurological outcomes in acute infection. To test the hypothesis that serum cytokine levels can provide biomarkers for phenotypic outcomes of acute disease, we compared cytokine levels at pre-injection, 4 days post-injection (d.p.i.), and 14 d.p.i. Each strain produced unique baseline cytokine levels and had distinct immune responses to the injection procedure itself. Thus, we eliminated the baseline responses to the injection procedure itself and identified cytokines and chemokines induced specifically by TMEV infection. Then, we identified strain-specific longitudinal cytokine profiles in serum during acute disease. Using stepwise regression analysis, we identified serum immune markers predictive for TMEV-induced neurological phenotypes of the acute phase, e.g., IL-9 for limb paralysis; and TNF-α, IL-1β, and MIP-1β for limb weakness. These findings indicate how temporal differences in immune responses are influenced by host genetic background and demonstrate the potential of serum biomarkers to track the neurological effects of viral infection. [ABSTRACT FROM AUTHOR]

Virus-induced neurological sequelae resulting from infection by Theiler's murine encephalomyelitis virus (TMEV) are used for studying human conditions ranging from epileptic seizures to demyelinating disease. Mouse strains are typically considered susceptible or resistant to TMEV infection based on viral persistence and extreme phenotypes, such as demyelination. We have identified a broader spectrum of phenotypic outcomes by infecting strains of the genetically diverse Collaborative Cross (CC) mouse resource. We evaluated the chronic-infection gene expression profiles of hippocampi and thoracic spinal cords for 19 CC strains in relation to phenotypic severity and TMEV persistence. Strains were clustered based on similar phenotypic profiles and TMEV levels at 90 days post-infection, and we categorized distinct TMEV response profiles. The three most common profiles included "resistant" and "susceptible," as before, as well as a "resilient" TMEV response group which experienced both TMEV persistence and mild neurological phenotypes even at 90 days post-infection. Each profile had a distinct gene expression signature, allowing the identification of pathways and networks specific to each TMEV response group. CC founder haplotypes for genes involved in these pathways/networks revealed candidate response-specific alleles. These alleles demonstrated pleiotropy and epigenetic (miRNA) regulation in long-term TMEV infection, with particular relevance for resilient mouse strains. [ABSTRACT FROM AUTHOR]

A wide range of viruses cause neurological manifestations in their hosts. Infection by neurotropic viruses as well as the resulting immune response can irreversibly disrupt the complex structural and functional architecture of the brain, depending in part on host genetic background. The interaction between host genetic background, neurological response to viral infection, and subsequent clinical manifestations remains poorly understood. In the present study, we used the genetically diverse Collaborative Cross (CC) mouse resource to better understand how differences in genetic background drive clinical signs and neuropathological manifestations of acute Theiler's murine encephalomyelitis virus (TMEV) infection. For the first time, we characterized variations of TMEV viral tropism and load based on host genetic background, and correlated viral load with microglial/macrophage activation. For five CC strains (CC002, CC023, CC027, CC057, and CC078) infected with TMEV, we compared clinical signs, lesion distribution, microglial/macrophage response, expression, and distribution of TMEV mRNA, and identified genetic loci relevant to the early acute (4 days post-infection [dpi]) and late acute (14 dpi) timepoints. We examined brain pathology to determine possible causes of strain-specific differences in clinical signs, and found that fields CA1 and CA2 of the hippocampal formation were especially targeted by TMEV across all strains. Using Iba-1 immunolabeling, we identified and characterized strain- and timepoint-specific variation in microglial/macrophage reactivity in the hippocampal formation. Because viral clearance can influence disease outcome, we used RNA in situ hybridization to quantify viral load and TMEV mRNA distribution at both timepoints. TMEV mRNA expression was broadly distributed in the hippocampal formation at 4 dpi in all strains but varied between radiating and clustered distribution depending on the CC strain. We found a positive correlation between microglial/macrophage reactivity and TMEV mRNA expression at 4 dpi. At 14 dpi, we observed a dramatic reduction in TMEV mRNA expression, and localization to the medial portion of field CA1 and field CA2. To better understand how host genetic background can influence pathological outcomes, we identified quantitative trait loci associated with frequency of lesions in a particular brain region and with microglial/macrophage reactivity. These QTL were located near several loci of interest: lysosomal trafficking regulator ( Lyst ) and nidogen 1 ( Nid1 ), and transmembrane protein 106 B ( Tmem106b). Together, these results provide a novel understanding about the influences of genetic variation on the acute neuropathological and immunopathological environment and viral load, which collectively lead to variable disease outcomes. Our findings reveal possible avenues for future investigation which may lead to more effective intervention strategies and treatment regimens.