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Biology subjects

Nandi, A. K.

Publications and source records attributed to Nandi, A. K..

2 recordsLinked to original sources

Efflux-linked Accelerated Evolution of Antibiotic Resistance at a Population Edge

Efflux is a common mechanism of resistance to antibiotics. We show that efflux itself promotes accumulation of antibiotic-resistance mutations (ARM). This phenomenon was initially discovered in a bacterial swarm where the linked phenotypes of high efflux and high mutation frequencies spatially segregated to the swarm edge, driven there by motility. We uncovered and validated a global regulatory network that connects high efflux to downregulation of specific DNA repair pathways even in non-swarming states. The efflux-DNA repair link was corroborated in a clinical resistome database: genomes with mutations that increase efflux exhibit a significant increase in ARMs. Accordingly, efflux inhibitors decreased evolvability to antibiotic resistance. Swarms also revealed how bacterial populations serve as reservoir of ARMs even in absence of antibiotic selection pressure. High efflux at the edge births mutants that, despite compromised fitness, survive there because of reduced competition. This finding is relevant to biofilms where efflux activity is high.

microbiology↗

Musical skills can be decoded from magnetic resonance images

Learning induces structural changes in the brain. Especially repeated, long-term behaviors, such as extensive training of playing a musical instrument, are likely to produce characteristic features to brain structure. However, it is not clear to what extent such structural features can be extracted from magnetic resonance images of the brain. Here we show that it is possible to predict whether a person is a musician or a non-musician based on the thickness of the cerebral cortex measured at 148 brain regions en-compassing the whole cortex. Using a supervised machine-learning technique, we achieved a significant ({kappa} = 0.321, p < 0.001) agreement between the actual and predicted participant groups of 30 musicians and 85 non-musicians. The areas contributing to the prediction were mostly in the frontal, parietal, and occipital lobes of the left hemisphere. Our results suggest that decoding musicianship from magnetic resonance images of brain structure is feasible. Further, the distribution of the areas that were informative in the classification, which mostly, but not entirely, overlapped with earlier findings on areas relevant for musical skills, implies that decoding-based analyses of structural properties of the brain can reveal novel aspects of musical aptitude. In particular, our results highlight differences in visual areas in addition to the already more established differences located in motor networks and networks of higher-order cognitive function.

neuroscience↗