A tunable metabolic valve for precise growth control and increased product formation in Pseudomonas putida.

Metabolic engineering of microorganisms aims to design strains capable of producing valuable compounds under relevant industrial conditions and in an economically competitive manner. From this perspective, and beyond the need for a catalyst, biomass is essentially a cost-intensive, abundant by-product of a microbial conversion. Yet, few broadly applicable strategies focus on the optimal balance between product and biomass formation.

Live Cell Imaging of Male Meiosis in by a Landmark-based System.

Live cell imaging has tremendously promoted our understanding of cellular and subcellular processes such as cell division. Here, we present a step-by-step protocol for a robust and easy-to-use live cell imaging approach to study male meiosis in the plant as recently established. Our method relies on the concomitant analysis of two reporter genes that highlight chromosome configurations and microtubule dynamics.

Live cell imaging of meiosis in .

To follow the dynamics of meiosis in the model plant Arabidopsis, we have established a live cell imaging setup to observe male meiocytes. Our method is based on the concomitant visualization of microtubules (MTs) and a meiotic cohesin subunit that allows following five cellular parameters: cell shape, MT array, nucleus position, nucleolus position, and chromatin condensation. We find that the states of these parameters are not randomly associated and identify 11 cellular states, referred to as landmarks, which occur much more frequently than closely related ones, indicating that they are convergence points during meiotic progression.

DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

Background: Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology.