Cilia loss on distinct neuron populations differentially alters cocaine-induced locomotion and reward.

BACKGROUND: Neuronal primary cilia are being recognized for their role in mediating signaling associated with a variety of neurobehaviors, including responses to drugs of abuse. They function as signaling hubs, enriched with a diverse array of G-protein coupled receptors (GPCRs), including several associated with motivation and drug-related behaviors. However, our understanding of how cilia regulate neuronal function and behavior is still limited. AIMS: The objective of the current study was to investigate the contributions of primary cilia on specific neuronal populations to behavioral responses to cocaine. METHODS: To test the consequences of cilia loss on cocaine-induced locomotion and reward-related behavior, we selectively ablated cilia from dopaminergic or GAD2-GABAergic neurons in mice. RESULTS: Cilia ablation on either population of neurons failed to significantly alter acute locomotor responses to cocaine at a range of doses. With repeated administration, mice lacking cilia on GAD2-GABAergic neurons showed no difference in locomotor sensitization to cocaine compared to wild-type (WT) littermates, whereas mice lacking cilia on dopaminergic neurons exhibited reduced locomotor sensitization to cocaine at 10 and 30 mg/kg. Mice lacking cilia on GAD2-GABAergic neurons showed no difference in cocaine conditioned place preference (CPP), whereas mice lacking cilia on dopaminergic neurons exhibited reduced CPP compared to WT littermates. CONCLUSIONS: Combined with previous findings using amphetamine, our results show that behavioral effects of cilia ablation are cell- and drug type-specific, and that neuronal cilia contribute to modulation of both the locomotor-inducing and rewarding properties of cocaine.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters.

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.