Biology subjects

Chambers, C.

Publications and source records attributed to Chambers, C..

6 recordsLinked to original sources

bioRxiv2026

Antibiotic Exposure Through Human Milk Influences the Infant Gut Microbiome

Infant antibiotic treatment is associated with increased risk of developing non-communicable diseases, potentially through disruption of the gut microbiome. However, the impact of indirect antibiotic exposure via human milk remains largely unexplored. Here, we investigate a cohort (n=80) of antibiotic-treated breastfeeding mother-infant dyads and untreated matching controls using integrative multi-omics analyses of fecal, milk, and skin samples (n=1,455). Maternal antibiotic treatment was associated with different infant fecal microbiome and metabolome profiles, including lower abundance of Bacteroides, Lactobacillus, and Bifidobacterium, and higher levels of antimicrobial resistance gene reads. Further, fecal metabolic alterations associated with indirect antibiotic exposure were exacerbated by formula milk supplementation. In a subset of infants (n=61), indirect exposure was associated with higher body mass index (BMI). These findings suggest that maternal antibiotic treatment during lactation may influence the early-life infant gut microbiome with potential long-term implications.

microbiology↗

bioRxiv2024

Expansion of mammary intraepithelial lymphocytes and intestinal inputs shape T cell dynamics in lactogenesis

Pregnancy brings about profound changes in the mammary gland to prepare for lactation, yet immunocyte changes that accompany this rapid remodeling are incompletely understood. We comprehensively analyzed mammary T cells, revealing a marked increase in CD4+ and CD8+ T effector cells, including an expansion of TCR{beta}+CD8+ cells, in pregnancy and lactation. T cells were localized in the mammary epithelium, resembling intraepithelial lymphocytes (IELs) typically found in mucosal tissues. Similarity to mucosal tissues was substantiated by demonstrating partial dependence on microbial cues, T cell migration from the intestine to the mammary gland in late pregnancy, and shared TCR clonotypes between intestinal and mammary tissues, including intriguing public TCR families. Putative counterparts of mammary IELs were found in human breast and milk. Mammary T cells are thus poised to manage the transition from a non-mucosal tissue to a mucosal barrier during lactogenesis.

immunology↗

bioRxiv2021

SMARCA4 regulates spatially restricted metabolic plasticity in 3D multicellular tissue

SWI/SNF and related chromatin remodeling complexes act as tissue-specific tumor suppressors and are frequently inactivated in different cancers. Although many regulatory activities of SWI/SNF have been identified using 2D cell culture, the effects of SWI/SNF alterations in more complex 3D tissues have remained poorly understood. Here we employed 3D cell culture conditions that yield transcriptomic states mirroring primary lung adenocarcinoma (LUAD) specimens better than 2D culture. By analyzing spatial patterns of gene expression and DNA accessibility in 3D spheroids using single-cell RNA-seq and ATAC-seq, we find that the SWI/SNF ATPase SMARCA4 (BRG1) induces state-specific changes to DNA accessibility that influence spatially heterogeneous expression patterns and metabolism. In 3D conditions, SMARCA4 promotes accessibility for AP-1 transcription factors, including ATF3, a regulator of metabolism and repressor of NRF2 antioxidant signaling. These changes reduce expression of SLC7A11 in a distinct portion of cells, which sensitizes A549 spheroids to cell death via ferroptosis under oxidizing conditions. Consistent with these results, we find that SMARCA4 alterations are associated with derepression of NRF2 targets in human tumors independently of NRF2/KEAP1 status. Our work reveals new 3D-specific features and unanticipated spatial complexity associated with chromatin remodeling in multicellular tissues.

systems biology↗

bioRxiv2019

Computer vision to automatically assess infant neuromotor risk

An infants risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as video cameras. Here, we automatically extract body poses and movement kinematics from the videos of at-risk infants (N=19). For each infant, we calculate how much they deviate from a group of healthy infants (N=85 online videos) using Naive Gaussian Bayesian Surprise. After pre-registering our Bayesian Surprise calculations, we find that infants that are at higher risk for impairments deviate considerably from the healthy group. Our simple method, provided as an open source toolkit, thus shows promise as the basis for an automated and low-cost assessment of risk based on video recordings.

animal behavior and cognition↗

bioRxiv2017

The Development Of Bayesian Integration In Sensorimotor Estimation

If the brain is inherently Bayesian, then behavior should show the signatures of Bayesian computation from an early stage in life without the need for learning. Children should integrate probabilistic information from prior and likelihood distributions to reach decisions and should be as statistically efficient as adults. To test this idea, we examined the integration of prior and likelihood information in a simple position estimation task comparing children aged 6-11 years and adults. During development, estimation performance became closer to the statistical optimum. Children use likelihood information as well as adults but are limited in their use of priors. This finding suggests that Bayesian behavior is not inherent but learnt over the course of development.

neuroscience↗

bioRxiv2017

Policies or Knowledge: Priors differ between perceptual and sensorimotor tasks

If the brain abstractly represents probability distributions as knowledge, then the modality of a decision, e.g. movement vs perception, should not matter. If on the other hand, learned representations are policies, they may be specific to the task where learning takes place. Here, we test this by asking if a learned spatial prior generalizes from a sensorimotor estimation task to a two-alternative-forced choice (2-Afc) perceptual comparison task. A model and simulation-based analysis revealed that while participants learn the experimentally-imposed prior distribution in the sensorimotor estimation task, measured priors are consistently broader than expected in the 2-Afc task. That the prior does not fully generalize suggests that sensorimotor priors strongly resemble policies. In disagreement with standard Bayesian thought, the modality of the decision has a strong influence on the implied prior distribution.\n\nNEW AND NOTEWORTHYWe do not know if the brain represents abstract and generalizable knowledge or task-specific policies that map internal states to actions. We find that learning in a sensorimotor task does not generalize strongly to a perceptual task, suggesting that humans learned policies and did not truly acquire knowledge. Priors differ across tasks, thus casting doubt on the central tenet of may Bayesian models, that the brains representation of the world is built on generalizable knowledge.

neuroscience↗