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Noeh, K.

Publications and source records attributed to Noeh, K..

4 recordsLinked to original sources

Does specific membrane surface area constrain Escherichia coli energy spillage and therefore aerobic and anaerobic growth rates?

The physical dimensions of bacterial cells are finite, tightly regulated, and constrain phenotype based on cell surface area to volume ratios. Additionally, bacterial membranes have limited capacity to host proteins, constraining enzymatic potential per area. We combine these biophysical properties into an aggregate parameter termed specific membrane surface area (sMSA, nm2 gcdw-1) which is readily integrated into systems biology analyses including constraint-based stoichiometric models. sMSA-based analyses have remarkable agency to predict and interpret bacterial phenotypes including maximum growth rate, respiration efficiency, and potential for maintenance energy generation. The presented Escherichia coli research 1) quantitatively recreates the membrane proteome from central metabolism as a function of growth rate, 2) demonstrates that the maximum growth rate of both aerobic and anaerobic E. coli cultures abides by similar cell biology constraints including a Pareto tradeoff between simultaneous synthesis of biomass macromolecules and generation of maintenance energy, 3) quantifies the areal capacity of E. coli membranes to dissipate Gibbs energy during enthalpic and entropic dominated metabolisms, and 4) presents evidence that sMSA theory could permit isogenic populations to host multiple concurrent phenotypes with equivalent fitness metrics.The results support our sMSA theory, based on cell geometry and membrane enzyme capacity, as a substantial driver of metabolism in both oxic and anoxic environments.

systems biology↗

ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud

SummaryReliable deep learning segmentation for microfluidic live-cell imaging requires comprehensive ground truth data. ObiWan-Microbi is a microservice platform combining the strength of state-of-the-art technologies into a unique integrated workflow for data management and efficient ground truth generation for instance segmentation, empowering collaborative semi-automated image annotation in the cloud. Availability and ImplementationObiWan-Microbi is open-source and available under the MIT license at https://github.com/hip-satomi/ObiWan-Microbi, along documentation and usage examples. Contactk.noeh@fz-juelich.de Supplementary informationSupplementary data are available online.

bioinformatics↗

CellSium - Versatile Cell Simulator for Microcolony Ground Truth Generation

SummaryTo train deep learning based segmentation models, large ground truth data sets are needed. To address this need in microfluidic live-cell imaging, we present CellSium, a flexibly configurable cell simulator built to synthesize realistic image sequences of bacterial microcolonies growing in monolayers. We illustrate that the simulated images are suitable for training neural networks. Synthetic time-lapse videos with and without fluorescence, using programmable cell growth models, and simulation-ready 3D colony geometries for computational fluid dynamics (CFD) are also supported. Availability and ImplementationCellSium is free and open source software under the BSD license, implemented in Python, available at https://github.com/modsim/cellsium (DOI: 10.5281/zenodo.6193033), along with documentation, usage examples and Docker images. Contactk.noeh@fz-juelich.de Supplementary informationSupplementary data are available online.

bioinformatics↗

Growth-rate dependency of ribosome abundance and translation elongation rate in Corynebacterium glutamicum differs from Escherichia coli

The growth rate {micro} of bacteria depends on the protein synthesis capacity of the cell and thus on the number of active ribosomes and their translation elongation rate. The relationship between these fundamental growth parameters have only been described for a few bacterial species, in particular Escherichia coli, but are missing for most bacterial phyla. In this study, we systematically analysed the growth-rate dependency of ribosome abundance and translation elongation rate for Corynebacterium glutamicum, a gram-positive model species differing from E. coli by a lower growth temperature optimum and a lower {micro}max. Ribosomes were quantified via single-molecule localization microscopy (SMLM) using fluorescently tagged ribosomal proteins and via RNA/protein ratio. Both methods revealed a non-linear relationship with little change in ribosome abundance below {micro} = 0.4 h-1 and a steep increase at higher {micro}. Unlike E. coli, C. glutamicum keeps a large pool of active ribosomes at low {micro}, but the translation elongation rate declines from [~]9 amino acids s-1 at {micro}max to <2 aa s-1 at {micro} < 0.1 h-1. A model-based approach shows that depletion of translation precursors at low growth rates can explain the observed decrease in translation elongation rate. Nutrient up-shift experiments support the hypothesis that maintenance of excess ribosomes during poor nutrient conditions enables C. glutamicum to quickly restart growth when conditions improve.

microbiology↗