Biology subjects

Glaichenhaus, N.

Publications and source records attributed to Glaichenhaus, N..

2 recordsLinked to original sources

bioRxiv2020

Gut microbial metabolite p-Cresol promotes autistic-like behaviors in mice through remodeling of the microbiota

BackgroundAutism Spectrum Disorders (ASD) are associated with dysregulation of the microbiota-gut-brain axis resulting in changes in microbiota composition as well as fecal, serum and urine levels of microbial metabolites. Yet, a causal relationship between dysregulation of the microbiota-gut-brain axis and ASD remains to be demonstrated. Here, we hypothesized that the microbial metabolite p-Cresol, which is more abundant in ASD patients compared to neurotypical individuals, could induce ASD-like behavior in mice. ResultsMice exposed to p-Cresol for 4 weeks in drinking water presented social behavior deficits, stereotypies, and perseverative behaviors, but no changes in anxiety, locomotion, or cognition. Abnormal social behavior induced by p-Cresol was associated with decreased activity of central dopamine neurons involved in the social reward circuit. Further, p-Cresol induced changes in microbiota composition and social behavior deficits could be transferred from p-Cresol-treated mice to control mice by fecal microbiota transplantation (FMT). We also showed that mice transplanted with the microbiota of p-Cresol-treated mice exhibited increased fecal p-Cresol levels compared to mice transplanted with the microbiota of control mice and identified possible p-Cresol bacterial producers. Lastly, the microbiota of control mice rescued social interactions, dopamine neurons excitability and fecal p-Cresol levels when transplanted to p-Cresol-treated mice. ConclusionsThe microbial metabolite p-Cresol induces ASD core behavioral symptoms in mice via a gut microbiota-dependent mechanism. Our study paves the way for therapeutic interventions targeting the microbiota to treat patients with ASD.

neuroscience↗

bioRxiv2020

Integration of behavioral and biological variables using penalized regression: an application to the maternal immune activation model of autism

Maternal immune activation (MIA) during pregnancy increases the odds of developing neuropsychiatric disorders such as autism spectrum disorder (ASD) later in life. In pregnant mice, MIA can be induced by injecting the viral mimic polyinosinic:polycytidylic acid (poly(I:C) to pregnant dams resulting in altered fetal neurodevelopmental and behavioral changes in their progeny. Although the murine MIA model has been extensively studied worldwide, the underlying mechanisms have only been partially elucidated. Furthermore, the murine MIA model suffers from lack of reproducibility, at least in part because it is highly influenced by subtle changes in environmental conditions. In human studies, multivariable (MV) statistical analysis is widely used to control for covariates including sex, age, exposure to environmental factors and many others. We reasoned that animal studies in general, and studies on the MIA model in particular, could therefore benefit from MV analyzes to account for complex phenotype interactions and high inter-individual variability. Here, we used a dataset consisting of 26 variables collected on 67 male pups during the course of several independent experiments on the MIA model. We then analyzed this dataset using penalized regression to identify variables associated with in utero exposure to MIA. In addition to confirming the association between some previously described biological variables and MIA, we identified new variables that could play a role in neurodevelopment alterations. Aside from providing new insights into variable interactions in the MIA model, this study highlights the importance of extending the use of MV statistics to animal studies.

neuroscience↗