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van Rij, T.

Publications and source records attributed to van Rij, T..

2 recordsLinked to original sources

Monitoring single cell bioenergetic status and cell lysis in dense and differentiating Bacillus subtilis cultures

BackgroundThe Gram-positive bacterium Bacillus subtilis is a rapidly growing and easily manipulated microbe with a long history of exploitation for the commercial production of industrial enzymes, high-value biochemicals, antibiotics and other secondary metabolites. More recently, it has been developed as a food additive and plant probiotic . It grows on cheap substrates and remains productive during extended batch-fed growth conditions. Extensive knowledge of its genetics, biochemistry and gene regulation has facilitated the use of metabolic engineering strategies to optimise substrate utilisation and product yield. As a free-living environmental organism, B. subtilis differentiates into subpopulations with distinct biological functions (e.g. sporulation, biofilm formation, antimicrobials production, etc). However, during fermentation, cellular differentiation processes can pose a challenge for its optimal biotechnological utilization, particularly when emerging subpopulations do not contribute to product biosynthesis. Here, we present robust assays that facilitate the analysis of two previously difficult-to-study population properties of B. subtilis: (i) the energization levels of individual cells within post-exponential but actively growing cultures and (ii) the extent of cell lysis that can occur under such conditions. ResultsOur findings reveal an unappreciated level of heterogeneity in cell energization within post-exponential cultures, and a surprisingly high degree of cell lysis in seemingly healthy, actively growing populations. These data provide insights and add to our understanding of the biological complexities and single-cell heterogeneities present in superficially simple bacterial clonal cultures. They establish robust and well-validated analytical tools with which to study the associated processes and provide a foundation for further optimizing B. subtilis as an industrial production host. ConclusionsConsiderable research efforts have been aimed at increasing the productivity of B. subtilis for industrial, medical and agricultural products. However, its ability to undergo physiological and morphological differentiation processes at high cell densities ultimately limits its productivity. Our research reveals how the resulting heterogeneity impacts the population-level energy status of individual cells in the culture and the surprisingly high extent of population-level cell lysis. The ability to monitor these processes provides tools for evaluating the impact of genetic and metabolic engineering strategies to improve productivity.

microbiology↗

Signal peptide efficiency: from high-throughput data to prediction and explanation

The passage of proteins across biological membranes via the general secretory (Sec) pathway is a universally conserved process with critical functions in cell physiology and important industrial applications. Proteins are directed into the Sec pathway by a signal peptide at their N-terminus. Estimating the impact of physicochemical signal peptide features on protein secretion levels has not been achieved so far, partially due to the extreme sequence variability of signal peptides. To elucidate relevant features of the signal peptide sequence that influence secretion efficiency, an evaluation of ~12,000 different designed signal peptides was performed using a novel miniaturized high-throughput assay. The results were used to train a machine learning model, and a post-hoc explanation of the model is provided. By describing each signal peptide with a selection of 156 physicochemical features, it is now possible to both quantify feature importance and predict the protein secretion levels directed by each signal peptide. Our analyses allow the detection and explanation of the relevant signal peptide features influencing the efficiency of protein secretion, generating a versatile tool for the in silico evaluation of signal peptides.

synthetic biology↗