Fischer, Christian, Haeussler, Simon, Marr, Carsten, Duchen, Michael, Conradt, Barbara, Rolland, Stephane, Singh, Kritarth, Besora-Casals, Laura
[
International Worm Meeting,
2021]
While the analysis of mitochondrial morphology has emerged as an important tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a difficult task and bottleneck for statistically robust conclusions. Here, we present the Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology (Fischer, Besora-Casals et al. 2020). The MitoSegNet was generated by training a modified fully convolutional neural network with fluorescent microscopy, maximum-intensity projection images, depicting mitochondria in body wall muscle cells of adult C. elegans worms. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet for all operating systems as an easy-to-use graphical user interface tool that combines segmentation with morphological analysis. Reference Fischer, C. A., L. Besora-Casals, S. G. Rolland, S. Haeussler, K. Singh, M. Duchen, B. Conradt and C. Marr (2020). "MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology." iScience 23(10).
[
Antimicrob Agents Chemother,
2016]
Energy-dependent efflux overexpression and altered outer membrane permeability (influx) can promote multidrug resistance (MDR). The present study clarifies the regulatory pathways that control membrane permeability in the pandemic clone E. coli ST131 and evaluates the impact of efflux and influx modulations on biofilm formation, motility and virulence in the Caenorhabditis elegans model. Mutants of two uropathogenic (UPEC) strains, MECB5 (ST131, H30-Rx) and CFT073 (ST73) as well as a fecal strain, S250 (ST131, H22), were in vitro selected using continuous subculture in sub-inhibitory concentration of ertapenem (ETP), chloramphenicol (CMP) and cefoxitin (FOX). Mutations in genes known to control permeability were shown for the two UPEC strains: MECB5-FOX (deletion of 127 base pairs (bp) in marR, deletion of 1 bp and insertion of IS1 element in acrR) and CFT073-CMP (1 bp deletion causing a premature stop in marR). We also demonstrated that efflux phenotypes in the mutants selected by CMP and FOX, were related to the AcrAB-TolC pump but also to other efflux systems. Alteration of membrane permeability, caused by underexpression of the two major porins, OmpF and OmpC, was shown in MECB5-ETP and mutants selected by FOX. Lastly, our findings suggest that efflux pump-overproducing isolates (CMP-mutants) pose a serious threat in terms of virulence (significant reduction in worms median survival) and host colonization. Lack of porins (ETP and FOX-mutants) led to a high level of antibiotic resistance in H30-Rx subclone. Nevertheless, this adaptation created a physiological disadvantage (decreased motility and ability to form biofilm) associated with a low potential of virulence.