Averina, O. | Search bioRxiv

bioRxiv2026

Study the dynamics of behavioral and biochemical parameters in the PARK2-knock-out mice model of Parkinson's disease

BackgroundParkinsons disease (PD) is a progressive chronic neurodegenerative disease. The PARK2 gene encoding the Parkin protein accounts for approximately half of early-onset autosomal recessive PD cases in humans. ObjectiveThe aim of this work was to study the effect of the PARK2 gene knockout in mice on the dynamics of behavioral and biochemical parameters of PD. MethodsThe study was performed on C57BL/6-line mice aged from 4 months to 1.5 years: wild type (park2 +/+), heterozygotes (park2 +/-) and homozygotes (park2 -/-) knocked out by the PARK2 using CRISPR-Cas9. The open field test, the Porsolt forced swimming test, the grid-walk test, the beam-walking test, the elevated plus maze test, the accelerating rotarod test were used to assess the behavioral phenotype. Measurement of the concentration of bioamines and their metabolites by HPLC and evaluation of the amount of tyrosine hydroxylase, BDNF and GDNF by Western Blot were used to study the biochemical signs of PD. ResultsPark2 -/- mice begin to show signs of decreased motor activity no earlier than at 4 months of life. At 12 months of life, it was shown only a decrease in the level of the mature isoform of GDNF and an increase in the number of immature isoforms in the frontal cortex and striatum were revealed. ConclusionThe data obtained indicates a different age dynamic of the condition of mice associated with the PARK2 knockout. However, no pronounced specific manifestations of PD in human were found in park2 -/- mice.

neuroscience↗

bioRxiv2022

Multi-omic analysis along the gut-brain axis points to a functional architecture of autism

Autism is a highly heritable neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in autism, with dozens of cross-sectional microbiome and other omic studies revealing autism-specific profiles along the GBA albeit with little agreement in composition or magnitude. To explore the functional architecture of autism, we developed an age and sex-matched Bayesian differential ranking algorithm that identified autism-specific profiles across 10 cross-sectional microbiome datasets and 15 other omic datasets, including dietary patterns, metabolomics, cytokine profiles, and human brain expression profiles. The analysis uncovered a highly significant, functional architecture along the GBA that encapsulated the overall heterogeneity of autism phenotypes. This architecture was determined by autism-specific amino acid, carbohydrate and lipid metabolism profiles predominantly encoded by microbial species in the genera Prevotella, Enterococcus, Bifidobacterium, and Desulfovibrio, and was mirrored in brain-associated gene expression profiles and restrictive dietary patterns in individuals with autism. Pro-inflammatory cytokine profiling and virome association analysis further supported the existence of an autism-specific architecture associated with particular microbial genera. Re-analysis of a longitudinal intervention study in autism recapitulated the cross-sectional profiles, and showed a strong association between temporal changes in microbiome composition and autism symptoms. Further elucidation of the functional architecture of autism, including of the role the microbiome plays in it, will require deep, multi-omic longitudinal intervention studies on well-defined stratified cohorts to support causal and mechanistic inference.

microbiology↗