Biology subjects

Bachmann, C.

Publications and source records attributed to Bachmann, C..

3 recordsLinked to original sources

bioRxiv2023

The double-edged role of FASII regulator FabT in Streptococcus pyogenes infection

In Streptococcus pyogenes, the type II fatty acid (FA) synthesis pathway FASII is feedback- controlled by the FabT repressor bound to an acyl-Acyl carrier protein. Despite FabT defects being linked to reduced virulence in animal models, spontaneous fabT mutants arise in vivo. To resolve this paradox, we characterized the conditions and mechanisms that require FabT activity, and those that promote fabT mutant emergence. The primary fabT mutant defect is energy dissipation: specific nutrients are consumed, but the mutant fails to grow on human tissue, cells, or cell filtrates where nutrients are limited. These features explain the FabT requirement during infection. Conversely, fabT mutants exhibited a marked growth advantage over the wild-type in biotopes rich in saturated FAs. fabT mutants emerge in this context, where continued FASII activity prevented environmental FA incorporation. An ex vivo muscle model demonstrated that wild-type S. pyogenes was inhibited, while fabT mutant growth was stimulated, but conditional to FASII activity. Our findings elucidate the rationale for emerging fabT mutants that improve survival in lipid-rich biotopes, but lead to a genetic impasse for infection.

microbiology↗

bioRxiv2019

Dose-controlled tDCS reduces electric field intensity variability at a cortical target site

BackgroundVariable effects limit the efficacy of transcranial direct current stimulation (tDCS) as a research and therapeutic tool. Conventional application of a fixed-dose of tDCS does not account for inter-individual differences in anatomy (e.g. skull thickness), which varies the amount of current reaching the brain. Individualised dose-control may reduce the variable effects of tDCS by reducing variability in electric field intensities at a cortical target site.\n\nObjectiveTo characterise the variability in electric field intensity at a cortical site (left primary motor cortex; M1) and throughout the brain for conventional fixed-dose tDCS, and individualised dose-controlled tDCS.\n\nMethodsThe intensity and distribution of the electric field during tDCS was estimated using Realistic Volumetric Approach to Simulate Transcranial Electric Stimulation (ROAST) in 50 individual brain scans taken from the Human Connectome Project, for fixed-dose tDCS (1mA & 2mA) and individualised dose-controlled tDCS targeting left M1.\n\nResultsWith a fixed-dose (1mA & 2mA), E-field intensity in left M1 varied by more than 100% across individuals, with substantial variation observed throughout the brain as well. Individualised dose-controlled ensured the same E-field intensity was delivered to left M1 in all individuals. Its variance in other regions of interest (right M1 and area underneath the electrodes) was comparable with fixed- and individualised-dose.\n\nConclusionsIndividualized dose-control can eliminate the variance in electric field intensities at a cortical target site. Assuming that the current delivered to the brain directly determines its physiological and behavioural consequences, this approach may allow for reducing the known variability of tDCS effects.

neuroscience↗

bioRxiv2018

Inferring health conditions from fMRI-graph data

Automated classification methods for disease diagnosis are currently in the limelight, especially for imaging data. Classification does not fully meet a clinicians needs, however: in order to combine the results of multiple tests and decide on a course of treatment, a clinician needs the likelihood of a given health condition rather than binary classification yielded by such methods. We illustrate how likelihoods can be derived step by step from first principles and approximations, and how they can be assessed and selected, using fMRI data from a publicly available data set containing schizophrenic and healthy control subjects, as a working example. We start from the basic assumption of partial exchangeability, and then the notion of sufficient statistics and the \"method of translation\" (Edgeworth, 1898) combined with conjugate priors. This method can be used to construct a likelihood that can be used to compare different data-reduction algorithms. Despite the simplifications and possibly unrealistic assumptions used to illustrate the method, we obtain classification results comparable to previous, more realistic studies about schizophrenia, whilst yielding likelihoods that can naturally be combined with the results of other diagnostic tests.

neuroscience↗