Biology subjects

Criswell, A.

Publications and source records attributed to Criswell, A..

3 recordsLinked to original sources

bioRxiv2026

Cell-type targeted CRISPR/Cas9 Clock knockdown in mouse VTA dopamine neurons alter sleep, behavior, and cellular excitability

Bipolar disorder (BD) is a severe psychiatric disease characterized by recurrent mania, depression, and circadian rhythm disruption. Among circadian regulators implicated in mood-related dysfunction, Clock has emerged as a particularly strong mechanistic candidate. However, cell type-specific functions of Clock within mood-relevant circuits remain incompletely defined. Here, we developed and applied a Cre-dependent AAV-SaCas9 gene-editing strategy to disrupt Clock selectively in ventral tegmental area dopamine neurons. We first established a rapid in vitro screening pipeline for guide RNA selection that accurately predicted in vivo editing efficiency. We then targeted Clock in vivo using a single AAV-based editing strategy and observed robust titer-dependent reduction of Clock expression, by targeted sequencing, in situ hybridization, and immunohistochemistry. We assessed the functional consequences of Clock disruption across analysis levels, including a behavioral battery, circadian and sleep-wake measurements using EEG and EMG, and electrophysiological recordings. These results establish a practical framework for rapid, cell-type-specific disruption of candidate psychiatric risk genes and provide a mechanistically grounded model for investigating how loss of Clock function in mesolimbic dopaminergic circuits contributes to BD-relevant phenotypes.

neuroscience↗

bioRxiv2025

Novel Machine Learning-based Approach to Identify Viral Biomarkers of Human Respiratory Emissions from Oral and Nasal Metagenomes

Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental sampling of respiratory viral pathogens is often challenging because of frequent non-detect measurements. Non-detect measurements do not differentiate between samples containing low or no pathogens from samples that simply lack respiratory expulsions altogether. This ambiguity can be resolved by scanning samples for a biomarker of human respiratory emissions. To do so, reliable biomarkers for environmental monitoring need to be identified. Ideal biomarkers are prevalent across individuals, abundant, and unique to the human respiratory tract. Here, we present a new machine learning-based approach to query for suitable biomarker candidates from publicly available metagenomes and apply it to identify viral biomarkers of healthy oral and nasal microbiomes. Twelve viral biomarker candidates were selected from 1,232 curated viral operational taxonomic units. The viral biomarker candidates had as much as 63% prevalence across respiratory metagenomes and prevalence was further increased to 77-81% by combining two or three biomarkers. Quantitative PCR confirmed that these viral biomarkers were prevalent and abundant in nasal swabs and saliva samples. Notably, top candidate biomarkers remained stable and detectable through multiple lab purification steps, increasing confidence in their viral origins and demonstrating their suitability for environmental monitoring. These findings demonstrate that existing metagenomes can be used to identify effective biomarker candidates for environmental sampling. IMPORTANCEDeveloping non-pharmaceutical interventions to reduce virus transmission indoors relies on robust environmental monitoring methods. Monitoring viral pathogens is challenging because of frequent non-detect measurements that introduce uncertainty. For instance, a non-detect measurement could indicate either the absence of the pathogen or simply the lack of human respiratory activity and thus exposure. To aid in distinguishing these scenarios, this study identifies viruses from the human respiratory tract using publicly available sequencing data that can be incorporated into environmental monitoring as biomarkers of human respiratory activity. These viral biomarkers will improve indoor monitoring to help enact interventions to mitigate virus transmission. Furthermore, our approach to identify biomarkers from existing metagenomes can be adapted for future biomarker identification in any system.

microbiology↗

bioRxiv2024

Stronger evidence for relaxed selection than adaptive evolution in high-elevation animal mtDNA

Mitochondrial (mt) genes are the subject of many adaptive hypotheses due to the key role of mitochondria in energy production and metabolism. One widespread adaptive hypothesis is that selection imposed by life at high elevation leads to the rapid fixation of beneficial alleles in mtDNA, reflected in the increased rates of mtDNA evolution documented in many high-elevation species. However, the assumption that fast mtDNA evolution is caused by positive, rather than relaxed purifying selection has rarely been tested. Here, we calculated the dN/dS ratio, a metric of nonsynonymous substitution bias, and explicitly tested for relaxed selection in the mtDNA of over 700 species of terrestrial vertebrates, freshwater fishes, and arthropods, with information on elevation and latitudinal range limits, range sizes, and body sizes. We confirmed that mitochondrial genomes of high-elevation taxa have slightly higher dN/dS ratios compared to low-elevation relatives. High-elevation species tend to have smaller ranges, which predict higher dN/dS ratios and more relaxed selection across species and clades, while absolute elevation and latitude do not predict higher dN/dS. We also find a positive relationship between body mass and dN/dS, supporting a role for small effective population size leading to relaxed selection. We conclude that higher mt dN/dS among high-elevation species is more likely to reflect relaxed selection due to smaller ranges and reduced effective population size than adaptation to the environment. Our results highlight the importance of rigorously testing adaptive stories against non-adaptive alternative hypotheses, especially in mt genomes.

evolutionary biology↗