TY - JOUR AB - Through metabolic engineering cyanobacteria can be employed in biotechnology. Combining the capacity for oxygenic photosynthesis and carbon fixation with an engineered metabolic pathway allows carbon-based product formation from CO2, light, and water directly. Such cyanobacterial 'cell factories' are constructed to produce biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers and synthetic biologists allow the modification of the intermediary metabolism at various branching points, expanding the product range. The new biosynthesis routes 'tap' the metabolism ever more efficiently, particularly through the engineering of driving forces and utilization of cofactors generated during the light reactions of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling ultimately allow an almost-complete allocation of fixed carbon to product above biomass. AU - Angermayr, Andreas AU - Gorchs, Aleix AU - Hellingwerf, Klaas ID - 1586 IS - 6 JF - Trends in Biotechnology TI - Metabolic engineering of cyanobacteria for the synthesis of commodity products VL - 33 ER - TY - JOUR AB - Background Photosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible. Results We present a method for high-throughput, single-cell analysis and sorting of genetically engineered l-lactate-producing strains of Synechocystis sp. PCC6803. A microfluidic device is used to encapsulate single cells in picoliter droplets, assay the droplets for l-lactate production, and sort strains with high productivity. We demonstrate the separation of low- and high-producing reference strains, as well as enrichment of a more productive l-lactate-synthesizing population after UV-induced mutagenesis. The droplet platform also revealed population heterogeneity in photosynthetic growth and lactate production, as well as the presence of metabolically stalled cells. Conclusions The workflow will facilitate metabolic engineering and directed evolution studies and will be useful in studies of cyanobacteria biochemistry and physiology. AU - Hammar, Petter AU - Angermayr, Andreas AU - Sjostrom, Staffan AU - Van Der Meer, Josefin AU - Hellingwerf, Klaas AU - Hudson, Elton AU - Joensson, Hakaan ID - 1623 IS - 1 JF - Biotechnology for Biofuels TI - Single-cell screening of photosynthetic growth and lactate production by cyanobacteria VL - 8 ER - TY - JOUR AB - Combining antibiotics is a promising strategy for increasing treatment efficacy and for controlling resistance evolution. When drugs are combined, their effects on cells may be amplified or weakened, that is the drugs may show synergistic or antagonistic interactions. Recent work revealed the underlying mechanisms of such drug interactions by elucidating the drugs'; joint effects on cell physiology. Moreover, new treatment strategies that use drug combinations to exploit evolutionary tradeoffs were shown to affect the rate of resistance evolution in predictable ways. High throughput studies have further identified drug candidates based on their interactions with established antibiotics and general principles that enable the prediction of drug interactions were suggested. Overall, the conceptual and technical foundation for the rational design of potent drug combinations is rapidly developing. AU - Bollenbach, Mark Tobias ID - 1810 JF - Current Opinion in Microbiology TI - Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution VL - 27 ER - TY - JOUR AB - Abstract Drug combinations are increasingly important in disease treatments, for combating drug resistance, and for elucidating fundamental relationships in cell physiology. When drugs are combined, their individual effects on cells may be amplified or weakened. Such drug interactions are crucial for treatment efficacy, but their underlying mechanisms remain largely unknown. To uncover the causes of drug interactions, we developed a systematic approach based on precise quantification of the individual and joint effects of antibiotics on growth of genome-wide Escherichia coli gene deletion strains. We found that drug interactions between antibiotics representing the main modes of action are highly robust to genetic perturbation. This robustness is encapsulated in a general principle of bacterial growth, which enables the quantitative prediction of mutant growth rates under drug combinations. Rare violations of this principle exposed recurring cellular functions controlling drug interactions. In particular, we found that polysaccharide and ATP synthesis control multiple drug interactions with previously unexplained mechanisms, and small molecule adjuvants targeting these functions synthetically reshape drug interactions in predictable ways. These results provide a new conceptual framework for the design of multidrug combinations and suggest that there are universal mechanisms at the heart of most drug interactions. Synopsis A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways. Drug interactions between antibiotics are highly robust to genetic perturbations. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions. Diverse drug interactions are controlled by recurring cellular functions, including LPS synthesis and ATP synthesis. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways. AU - Chevereau, Guillaume AU - Bollenbach, Mark Tobias ID - 1823 IS - 4 JF - Molecular Systems Biology TI - Systematic discovery of drug interaction mechanisms VL - 11 ER - TY - GEN AU - Chevereau, Guillaume AU - Lukacisinova, Marta AU - Batur, Tugce AU - Guvenek, Aysegul AU - Ayhan, Dilay Hazal AU - Toprak, Erdal AU - Bollenbach, Mark Tobias ID - 9711 TI - Excel file containing the raw data for all figures ER -