Biology subjects

Popp, D.

Publications and source records attributed to Popp, D..

5 recordsLinked to original sources

bioRxiv2024

Bacterial genome encoded ParMs

ParMs generally exist on low copy number plasmids where they contribute to plasmid segregation and stable inheritance. We carried out bioinformatics analysis, which indicated that ParM genes are not only confined to plasmids but are also occasionally found on genomes. Here we report the discovery and characterization of two chromosome encoded ParMs (cParMs) from the genomes of Desulfitobacterium hafniense (Dh-cParM1) and Clostridium botulinum (Cb-cParM). Both cParMs form filaments, exhibit nucleotide hydrolysis, and possess characteristic ParM subunit structures. Dh-cParM1 forms single and tightly coupled double filaments and is highly conserved on the chromosomes of five of six Desulfitobacterium species. Interestingly, these bacteria have not been reported to harbour plasmids. Cb-cParM possesses unique properties. Its filaments were stable after nucleotide hydrolysis and Pi release, and its ParR, (Cb-cParR) did not affect the initial stage of Cb-cParM polymerization but displayed properties of a depolymerization factor for mature filaments. These results indicate functional, polymerizing ParMs can be encoded on genomes, suggesting that ParM roles may extend to other functions beyond plasmid segregation.

microbiology↗

bioRxiv2022

Recently evolved combination of unique sulfatase and amidase genes enables bacterial degradation of the wastewater micropollutant acesulfame worldwide

Xenobiotics often challenge the principle of microbial infallibility. One example is acesulfame introduced in the 1980s as zero-calorie sweetener, which was recalcitrant in wastewater treatment plants until the early 2010s. Then, efficient removal has been reported with increasing frequency. By studying acesulfame metabolism in alphaproteobacterial degraders of the genera Bosea and Chelatococcus, we experimentally confirmed the previously postulated route of two subsequent hydrolysis steps via acetoacetamide-N-sulfonate (ANSA) to acetoacetate and sulfamate. Genome comparison of wildtype Bosea sp. 100-5 and a spontaneous acesulfame degradation-defective mutant revealed the involvement of two plasmid-borne gene clusters. The acesulfame-hydrolyzing sulfatase is strictly manganese-dependent and belongs to the metallo beta-lactamase family. In all degraders analyzed, it is encoded on a highly conserved gene cluster embedded in a composite transposon. The ANSA hydrolase, on the other hand, is an amidase signature domain enzyme encoded in another gene cluster showing variable length among degrading strains. Transposition of the sulfatase gene cluster between chromosome and plasmid explains how the two catabolic gene clusters recently combined for the degradation of acesulfame. Searching available genomes and metagenomes for the two hydrolases and associated genes indicates that the acesulfame plasmid evolved and spread worldwide in short time. While the sulfatase is unprecedented and unique for acesulfame degraders, the amidase occurs in different genetic environments and might have evolved for the degradation of other substrates. Evolution of the acesulfame degradation pathway might have been supported by the presence of structurally related natural and anthropogenic compounds, such as aminoacyl sulfamate ribonucleotide or sulfonamide antibiotics.

microbiology↗

bioRxiv2022

An actin-like filament from Clostridium botulinum exhibits a novel mechanism of filament dynamics

Here, we report the discovery of a ParM protein from Clostridium botulinum (CBgs-ParM), which forms a double-stranded polar filament. CBgs-ParM shares many similarities in its basic filament architecture with actin, however, Pi release after nucleotide hydrolysis induces a large lateral strand shift of ~2.5 nm. We identified the ParR (CBgs-ParR) that acts as a nucleation factor in the initial stage of polymerization, similar to ParR from Escherichia coli plasmid R1. CBgs-ParR also functions as a depolymerization factor, probably by recognizing the structural change in the CBgs-ParM filament after Pi release. Comparison with CBH-ParM, another ParM from Clostridum botulinum, showed that subunit-subunit interacting regions largely differ, preventing co-polymerization, implying a selection pressure in evolution to prevent interference between different ParMRC systems.

biophysics↗

bioRxiv2020

Microbial resource management for ex situ biomethanation of hydrogen at alkaline pH

Biomethanation is a promising solution to convert H2 produced from surplus electricity and CO2 to CH4 by using hydrogenotrophic methanogens. In ex situ biomethanation with mixed cultures, homoacetogens and methanogens compete for H2/CO2. We enriched a hydrogenotrophic microbiota on CO2 and H2 as sole carbon and energy sources, respectively, to investigate these competing reactions. Microbial community structure and dynamics of bacteria and methanogenic archaea were evaluated through 16S rRNA and mcrA gene amplicon sequencing, respectively. Hydrogenotrophic methanogens and homoacetogens were enriched as acetate was concomitantly produced along with CH4. By controlling the media composition, especially changing the reducing agent, the formation of acetate was lowered and grid quality CH4 ([≥] 97%) was obtained. Formate was identified as an intermediate that was produced and consumed during the bioprocess. Stirring intensities [≥]1000 rpm were detrimental, probably due to shear force stress. The predominating methanogens belonged to the genera Methanobacterium and Methanoculleus. The bacterial community was dominated by Lutispora. The methanogenic community was stable, whereas the bacterial community was more dynamic. Our results suggest that hydrogenotrophic communities can be steered towards selective production of CH4 from H2/CO2 by adapting the media composition, the reducing agent and the stirring intensity.

bioengineering↗

bioRxiv2019

{micro}bialSim: constraint-based dynamic simulation of complex microbiomes

Microbial communities are pervasive in the natural environment, associated with many animal hosts, and of increasing importance in biotechnological applications. The complexity of these microbial systems makes the underlying mechanisms driving their dynamics difficult to identify. While experimental meta-OMICS techniques are routinely applied to record the inventory and activity of microbiomes over time, it remains difficult to obtain quantitative predictions based on such data. Mechanistic, quantitative mathematical modeling approaches hold the promise to both provide predictive power and shed light on cause-effect relationships driving these dynamic systems. We introduce {micro}bialSim (pronounced \"microbialsim\"), a dynamic Flux-Balance-Analysis-based (dFBA) numerical simulator which is able to predict the time course in terms of composition and activity of microbiomes containing 100s of species in batch or chemostat mode. Activity of individual species is simulated by using separate FBA models which have access to a common pool of compounds, allowing for metabolite exchange. A novel augmented forward Euler method ensures numerically accuracy by temporarily reducing the time step size when compound concentrations decrease rapidly due to high compound affinities and/or the presence of many consuming species. We present three exemplary applications of {micro}bialSim: a batch culture of a hydrogenotrophic archaeon, a syntrophic methanogenic biculture, and a 773-species human gut microbiome which exhibits a complex and dynamic pattern of metabolite exchange.\n\nFocussing on metabolite exchange as the main interaction type, {micro}bialSim allows for the mechanistic simulation of microbiomes at their natural complexity. Simulated trajectories can be used to contextualize experimental meta-OMICS data, and hypotheses on cause-effect relationships driving community dynamics can be derived based on scenario simulations.\n\n{micro}bialSim is implemented in Matlab and relies on the COBRA Toolbox or CellNetAnalyzer for FBA calculations. The source code is available under the GNU General Public License v3.0 at https://git.ufz.de/UMBSysBio/microbialsim.

systems biology↗