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Biology subjects

Mohr, K.

Publications and source records attributed to Mohr, K..

3 recordsLinked to original sources

Structure Elucidation, Biosynthesis and Biological Evaluation of Neosorangicin A, a Member of the Sorangicin Family

Antimicrobial resistance represents an escalating global health crisis, with drug-resistant infections predicted to cause up to 10 million deaths annually by 2050, underscoring the urgent need for novel antibiotics. Natural products play a crucial role in the discovery and development of antibiotics, with myxobacteria emerging as a particularly promising source due to their ability to produce structurally diverse and bioactive compounds. One prominent example of antibiotics from myxobacteria are the sorangicins, potent inhibitors of the bacterial RNA polymerase (RNAP). Here, we report the isolation of two unprecedented compounds, neosorangicin A (1) and neosorangioside A (2), from Sorangium cellulosum strain Soce439, elucidated their molecular structures, thereby revealing significant structural variation in comparison to sorangicin, and describe their biosynthetic pathway. Neosorangicin A (1) exhibited strong activity against various Gram-positive bacteria, with enhanced potency on intracellular Staphylococcus aureus. In a murine wound infection model, a head-to-head comparison of neosorangicin A (1) and sorangicin A (3) provided useful insights into how the altered physicochemical properties, arising from the shortened side chain and the lack of the free carboxylic acid of neosorangicin A, influence the in vivo efficacy of sorangicin derivatives.

microbiology↗

Bursts in biosynthetic gene cluster transcription are accompanied by surges of natural compound production in the myxobacterium Sorangium sp.

We have investigated the time course of genome-wide transcription in the myxobacterium Sorangium sp. So ce836 in relation to its production of natural compounds. Time-resolved RNA sequencing revealed that core biosynthesis genes from 48 biosynthetic gene clusters (BGCs; 92% of all BGCs encoded in the genome) were actively transcribed at specific time points in a batch culture. The majority (80%) of polyketide synthase and non-ribosomal peptide synthetase genes displayed distinct peaks of transcription during exponential bacterial growth. Strikingly, these bursts in BGC transcriptional activity were associated with surges in the production of known natural compounds, indicating that their biosynthesis was critially regulated at the transcriptional level. In contrast, BGC read counts from single time points had limited predictive value about biosynthetic activity, since transcription levels varied >100-fold among BGCs with detected natural products. Taken together, our time-course data provide unique insights into the dynamics of natural compound biosynthesis and its regulation in a wild-type myxobacterium, challenging the commonly cited notion of preferential BGC expression under nutrient-limited conditions. The close association observed between BGC transcription and compound production warrants additional efforts to develop genetic engineering tools for myxobacterial producer strains, to boost compound yields by manipulating transcriptional activity.

genomics↗

EyeBallGUI: A Tool For Visual Inspection And Binary Marking of Multi-Channel Bio-Signals

A wide range of studies in human neuroscience rely on the analysis of electrophysiological bio-signals such as electroencephalogram (EEG) where customized data analysis may require supervised artefact rejection, binary marking through visual inspection, selection of noise and artefact samples for pre-processing algorithms, and selection of clinically-relevant signal segments in neurological conditions. Nevertheless, the existing preprocessing tools do not provide the needed flexibility to handle such tasks efficiently. We therefore developed a free open-source Graphical User Interface (GUI), EyeBallGUI, that allows visualization and flexible, manual marking (binary classification) of multi-channel bio-signal data. EyeBallGUI, developed for MATLAB(R), allows the user to interactively and accurately inspect and mark multi-channel digitized data with no restriction on marking periods of data in subsets of channels (a restriction in place in existing tools). The new tool facilitates precise, manual marking of bio-signals by allowing any desired segment of data to be marked in any subset of channels. It is therefore of utility in circumstances where such flexibility is essential. The developed GUI is an auxiliary analysis tool that shall facilitate neural signal (pre-)processing applications where it is desirable to perform accurate supervised artefact rejection, flexible data marking for increased data retention yield, extraction of specific signal segments by expert users from sample data, or labeling of data for clinical and scientific research purposes.

neuroscience↗