Biology subjects

Weigert, M.

Publications and source records attributed to Weigert, M..

4 recordsLinked to original sources

bioRxiv2017

Content-Aware Image Restoration: Pushing the Limits of Fluorescence Microscopy

Fluorescence microscopy is a key driver of discoveries in the life-sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how image restoration based on deep learning extends the range of biological phenomena observable by microscopy. On seven concrete examples we demonstrate how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to 10-fold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times higher frame-rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FO_SCPLOWIJIC_SCPLOW, and KO_SCPLOWNIMEC_SCPLOW.

bioinformatics↗

bioRxiv2017

Probing the evolutionary robustness of anti-virulence treatments targeting iron uptake in Pseudomonas aeruginosa

Background and objectivesTreatments that inhibit the expression or functioning of bacterial virulence factors hold great promise to be both effective and exert weaker selection for resistance than conventional antibiotics. However, the evolutionary robustness argument, based on the idea that anti-virulence treatments disarm rather than kill pathogens, is controversial. Here we probe the evolutionary robustness of two repurposed drugs, gallium and flucytosine, targeting the iron-scavenging pyoverdine of the opportunistic human pathogen Pseudomonas aeruginosa.\n\nMethodologyWe subjected replicated cultures of bacteria to two concentrations of each drug for 20 consecutive days in human serum as an ex-vivo infection model. We screened evolved populations and clones for resistance phenotypes, including the restoration of growth and pyoverdine production, and the evolution of iron uptake by-passing mechanisms. We whole-genome sequenced evolved clones to identify the genetic basis of resistance.\n\nResultsWe found that mutants resistant against anti-virulence treatments readily arose, but their selective spreading varied between treatments. Flucytosine resistance quickly spread in all populations due to disruptive mutations in upp, a gene encoding an enzyme required for flucytosine activation. Conversely, resistance against gallium arose only sporadically, and was based on mutations in transcriptional regulators, upregulating pyocyanin production, a redox-active molecule promoting siderophore-independent iron acquisition. The spread of gallium resistance could be hampered because pyocyanin-mediated iron delivery benefits resistant and susceptible cells alike.\n\nConclusions and implicationsOur work highlights that anti-virulence treatments are not evolutionarily robust per se. Instead, evolutionary robustness is a relative measure, with specific treatments occupying different positions on a continuous scale.

microbiology↗

bioRxiv2017

The physical boundaries of public goods cooperation between surface-attached bacterial cells

Bacteria secrete a variety of compounds important for nutrient scavenging, competition mediation and infection establishment. While there is a general consensus that secreted compounds can be shared and therefore have social consequences for the bacterial collective, we know little about the physical limits of such bacterial social interactions. Here, we address this issue by studying the sharing of iron-scavenging siderophores between surface-attached microcolonies of the bacterium Pseudomonas aeruginosa. Using single-cell fluorescent microscopy, we show that siderophores, secreted by producers, quickly reach non-producers within a range of 100 m, and significantly boost their fitness. Producers in turn respond to variation in sharing efficiency by adjusting their pyoverdine investment levels. These social effects wane with larger cell-to-cell distances and on hard surfaces. Thus, our findings reveal the boundaries of compound sharing, and show that sharing is particularly relevant between nearby yet physically separated bacteria on soft surfaces, matching realistic natural conditions such as those encountered in soft tissue infections.

evolutionary biology↗

bioRxiv2016

Individual- versus group-optimality in the production of secreted bacterial compounds

How unicellular organisms optimize the production of compounds is a fundamental biological question. While it is typically thought that production is optimized at the individual-cell level, secreted compounds could also allow for optimization at the group level, leading to a division of labor where a subset of cells produces and shares the compound with everyone. Using mathematical modelling, we show that the evolution of such division of labor depends on the cost function of compound production. Specifically, for any trait with saturating benefits, linear costs promote the evolution of uniform production levels across cells. Conversely, production costs that diminish with higher output levels favor the evolution of specialization - especially when compound shareability is high. When experimentally testing these predictions with pyoverdine, a secreted iron-scavenging compound produced by Pseudomonas aeruginosa, we found linear costs and, consistent with our model, detected uniform pyoverdine production levels across cells. We conclude that for shared compounds with saturating benefits, the evolution of division of labor is facilitated by a diminishing cost function. More generally, we note that shifts in the level of selection from individuals to groups do not solely require cooperation, but critically depend on mechanistic factors, including the distribution of compound synthesis costs.

evolutionary biology↗