Search

Additional file of Automatic reconstruction of metabolic pathways from identified biosynthetic gene clusters

Additional file 2. Detailed comparison of 8 BGCs for evaluation the accuracy of the BiGMeC pipeline.

Additional file 1. Details on tailoring reactions and synthesis of the rare extender unit methoxymalonyl-ACP, as well as a description of the analysis used to develop the heuristics that indicate the presence of these reactions from smCOG annotations.

Concrete is the second most consumed product by humans, after water. However, the production of cement, which is used as a binding material in concrete, causes more than 5% of anthropogenic CO2emissions and has therefore a significant contribution to climate change and global warming. Due to increasing environmental awareness and international climate goals, there is a need for emission-reduced materials, that can replace conventional concrete in certain applications. One path to produce a solid, concrete-like construction material is microbial-induced calcium carbonate precipitation (MICP). As a calcium source in MICP, crushed limestone, which mainly consists out of CaCO3, can be dissolved with acids, for example lactic acid. The pH evolution during crystallization and dissolution processes provides important information about kinetics of the reactions. However, previous research on MICP has mainly been focused on macro-scale pH evolution and on characterization of the finished material. To get a better understanding of MICP it is important to be able to follow also local pH changes in a sample. In this work we present a new method to study processes of MICP at micro-scalein situand in real time. We present two different methods to monitor the pH changes during the precipitation process of CaCO3. In the first method, the average pHs of small sample volumes are measured in real time, and pH changes are subsequently correlated with processes in the sample by comparing to optical microscope results. The second method is introduced to follow local pH changes at a grain scale insituand in real time. Furthermore, local pH changes during the dissolution of CaCO3crystals are monitored. We demonstrate that these two methods are powerful tools to investigate pH changes for both MICP precipitation and CaCO3dissolution for knowledge-based improvement of MICP-based material properties.Graphical TOC Entry

Many biosynthetic gene clusters (BGCs) in the genomes of environmental microorganisms require heterologous expression in order to realize their genetic potential, including cryptic and metagenomic BGCs. Streptomyces coelicolor M1152 is a widely used host strain for the heterologous expression of BGCs, as it has been genetically engineered for this purpose via the deletion of four of its native biosynthetic gene clusters (BGCs) and the introduction of a point mutation in the rpoB gene that encodes the beta subunit of RNA polymerase. This latter mutation was shown to have a strong positive impact on antibiotic biosynthesis via processes that remain poorly understood. Therefore, a systemic understanding of the consequences on cellular metabolism of the genomic changes of M1152 could greatly contribute to this understanding. Here we carried out a comparative analysis of M1152 and its ancestor strain M145, connecting observed phenotypic differences to changes in transcript and protein abundance. Measured protein abundance was used to constrain an amended genome-scale model (GEM) and to predict metabolic fluxes. This approach connects observed differences in growth rate and glucose consumption to changes in central carbon metabolism, accompanied by differential expression of important regulons. Our results suggest that precursor availability is not limiting the biosynthesis of secondary metabolites. This implies that alternative strategies could be beneficial for further development of S. coelicolor for heterologous production of novel compounds. Importance This study provides the first systems description of S. coelicolor M1152, an engineered host widely used for the heterologous expression of BGCs directing the synthesis of natural products. By combining time-series proteomics and transcriptomics, batch fermentation data and genome-scale modelling, we can connect observed phenotypes to known genetic modifications and find extensive metabolic rewiring in the M1152 strain compared to the wild-type stain M145. Our study indicates that the deletion of secondary metabolite biosynthetic pathways thought to enhance precursor availability, only has a minor impact on the ability of the modified strain to produced heterologous molecules. In contrast, the rpoB mutation is likely responsible for the most dramatic changes in regulatory features and precursor availability. The amended genome-scale model, reconstructed in an open-science framework, allowed us to contextualize the transcriptional changes. This framework facilitates further development by the research community in an organized manner, including version control, continuous integration and quality control and tracking of individual contributions.

We applied response surface methodology to understand the effect and extend of carbon catabolite repression (CCR) on growth of Clostridium beijerinckii NCIMB 8052 using xylose and glucose as representative lignocellulosic sugars. We performed batch growth experiments based on the central composite design with different concentrations of glucose and xylose, and estimated the respective growth rates as the response. Fitting the quadratic model with interaction coefficient to experimental data gave a good quality of fit (R-squared=0.939). We found that glucose is the most significant factor affecting the growth rate. Interaction between glucose and xylose is another highly significant factor. Response surface illustrated that increasing or decreasing both sugar concentrations at the same time results in a decreasing growth rate, and increasing either sugar concentration while decreasing the other sugar increases the growth rate. It is an important finding as it suggests that CCR can be not only from glucose on xylose but also from xylose on glucose. A transcriptional study will be necessary to understand the repression mechanism and to improve the utilization of sugars in mixed form, thus lignocellulosic fermentation processes.

To our knowledge, this is the first growth model of Clostridium beijerinckii NCIMB 8052 on glucose and xylose as representative lignocellulosic sugars, which considers the synergistic effects of sugars on the growth rate. We fitted models with different types of interactions between the substrates to the growth rate data obtained with varying sugar concentrations. Noncompetitive binary substrate growth model gave the best fit with the smallest mean standard errors (MSE), and sum of squares error (SSE), 0.0778 and 0.0071, respectively. Confidence intervals for the parameter estimates showed that the substrate affinity constant for xylose, KsX (g/l) had the largest uncertainty, while the maximum specific growth rate on xylose, μmaxX (h-1) had the smallest. The correlation matrix showed that the model parameters were highly correlated. Carbon catabolite repression (CCR) effect on the growth rate was of the noncompetitive type. Validation with other sugar concentration values is necessary to evaluate the prediction capability of the proposed model. A transcriptional study will be beneficial to understand global gene regulation mechanisms as guidance for improving the efficiency of lignocellulosic fermentation processes.