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Johnson-Camacho, K.

Publications and source records attributed to Johnson-Camacho, K..

2 recordsLinked to original sources

Polycyclic aromatic hydrocarbons, gut microbiome composition, impulsivity, and attention covary in a human cohort

Polycyclic aromatic hydrocarbons (PAHs) are pervasive environmental pollutants linked to adverse neurobehavioral outcomes, yet the biological pathways coupling exposure to behavior are poorly defined. The gut microbiome is both sensitive to PAH exposure and a modulator of central nervous system function, suggesting it may mediate how PAH exposure influences neurobehavior. We tested whether PAH exposure, gut microbiome composition, and neurobehavioral function covary in a statewide sample of 34 adults stratified into high-impulsivity/poor-attention (HH) and low-impulsivity/fast-attention (LL) groups. Participants provided fecal samples for 16S rRNA profiling and wore silicone wristbands for 30 days to passively sample PAH exposure. Higher PAH exposure associated with HH group membership in a sex-dependent manner, with the largest elevations among HH males. At the community level, PAH exposure profiles correlated with microbiome dissimilarity, and HH membership associated with increased alpha-diversity and altered community composition relative to LL members. At the taxon level, 21 genera were significantly associated with 14 PAH compounds (FDR < 0.1). No individual genera were significantly associated with neurobehavioral group after multiple testing correction. Nevertheless, cross-referencing PAH-responsive genera (FDR < 0.1) against those with nominal neurobehavioral associations (p < 0.05) identified two candidate genera, Hydrogenoanaerobacterium and Methanobrevibacter, whose abundance covaries with both PAH exposure and neurobehavioral phenotype. Both have been independently linked to cognitive or neurological outcomes in prior work. These findings support a three-way relationship among environmental chemical exposure, gut microbiome composition, and neurobehavioral function, establishing an empirical foundation for testing microbiome-mediated links between PAH exposure and neurobehavioral outcomes. IMPORTANCEPAH exposure is widespread and associates with impulsivity and attention problems, but how exposure translates into neurobehavioral risk is unclear. The gut microbiome is a plausible intermediary: gut microbes biotransform environmental chemicals and produce metabolites that influence brain function. In a statewide adult cohort, we show that higher PAH exposure tracks with greater impulsivity and poorer attention in a sex-dependent manner, and that both PAH exposure and neurobehavioral phenotype associate with distinct gut microbiome features at the community and taxon levels. We identify candidate genera at the intersection of PAH exposure and neurobehavioral group whose biology independently implicates them in cognitive and neurological function. By demonstrating that all three domains covary within a single human cohort, this work moves beyond pairwise associations to identify candidate microbial intermediaries for mechanistic investigation. Defining the microbiome constituents that respond to PAH exposure and co-associate with neurobehavioral phenotypes creates opportunities to test microbiome-targeted or exposure-reduction strategies for mitigating PAH-related neurobehavioral impacts.

microbiology↗

Large-scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines

Perturbation biology is a powerful approach to developing quantitative models of cellular behaviors and gaining mechanistic insights into disease development. In recent years, large-scale resources for phenotypic and mRNA responses of cancer cell lines to perturbations have been generated. However, similar large-scale protein response resources are not available, resulting in a critical knowledge gap for elucidating oncogenic mechanisms and developing effective cancer therapies. Here we generated and compiled perturbed expression profiles of ~210 clinically relevant proteins in >12,000 cancer cell-line samples in response to >150 drug compounds using reverse-phase protein arrays. We show that integrating protein response signals substantially increases the predictive power for drug sensitivity and aids in gaining insights into mechanisms of drug resistance. We build a systematic map of protein-drug connectivity and develop an open-access, user-friendly data portal for community use. Our study provides a valuable information resource for a broad range of quantitative modeling and biomedical applications. HighlightsO_LIA large collection of cancer cell line protein responses to drug perturbations C_LIO_LIPerturbed protein responses greatly increase predictive power for drug sensitivity C_LIO_LIBuild a systematic map of protein-drug connectivity based on response profiles C_LIO_LIDevelop a user-friendly, interactive data portal for community use C_LI

systems biology↗