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Biology subjects

Thomason, M.

Publications and source records attributed to Thomason, M..

2 recordsLinked to original sources

Staphylococcus aureus small-colony variants exhibit genotype specific hyperinflammation

Antibiotics remain one of the most effective methods for controlling bacterial infection. However, the diverse impacts of antimicrobials on bacterial physiology and host immunity remain unclear. A comprehensive antibiotic screen revealed that disruption of thymidine synthesis in Firmicutes with anti-folate antibiotics promoted elevated levels of the bacterial second messenger cyclic di-AMP, and consequently induced host STING activation during infection. Extensive exposure to antibiotics targeting folate synthesis drives the emergence of thymidine-dependent Staphylococcus aureus SCVs (TD-SCVs). Respiratory infections with TD-SCVs are common among children with cystic fibrosis and are associated with worse clinical outcomes, although the underlying pathophysiological mechanisms remain to be defined. Our study reveals that TD-SCV isolates exhibited excessive c-di-AMP production and STING activation in a thymidine-dependent manner. Murine lung infection with TD-SCVs revealed STING-dependent elevation of proinflammatory cytokines, leading to higher airway neutrophil infiltration and activation comparing to normal colony S. aureus and hemin-dependent SCV. Our results suggest the elevated inflammatory capacity of TD-SCVs contribute to their pathogenesis and revealed a new aspect of STING signaling in the airway by characterizing its role in neutrophil recruitment.

molecular biology↗

Observing the origins of human brain development: Automated processing of fetal fMRI

AO_SCPLOWBSTRACTC_SCPLOWFetal resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a critical new approach for characterizing brain development before birth. Despite rapid and widespread growth of this approach, at present we lack neuroimaging processing pipelines suited to address the unique challenges inherent in this data type. Here, we solve the most challenging processing step, rapid and accurate isolation of the fetal brain from surrounding tissue across thousands of non-stationary 3D brain volumes. Leveraging our library of 1,241 manually traced fetal fMRI images from 207 fetuses (gestational age 24-39 weeks, M=30.9, SD=4.2), we trained a Convolutional Neural Network (CNN) that achieved excellent performance across two held-out test sets from separate scanners and populations. Furthermore, we unite the auto-masking model with additional fMRI preprocessing steps from existing software and provide insight into our adaptation of each step. This work represents an initial advancement towards a fully comprehensive, open source workflow for fetal functional MRI data preprocessing.

neuroscience↗