How close are we to storing data in DNA?

DNA is an intelligent data storage medium due to its stability and high density. It has been used by nature for over 3.5 billion years. Compared with traditional methods, DNA offers better compression and physical density. DNA can retain information for thousands of years. However, challenges exist in scalability, standardization, metadata gathering, biocybersecurity, and specialized tools. Addressing these challenges is crucial for widespread implementation. Collaboration among experts, as well as keeping the future in mind, is needed to unlock the full potential of DNA data storage, which promises low energy costs, high-density storage, and long-term stability.

Quantifying NAD(P)H production in the upper Entner-Doudoroff pathway from Pseudomonas putida KT2440.

Despite the lack of biochemical information, all available in silico metabolic models of Pseudomonas putida KT2440 consider NADP as the only cofactor accepted by the glucose-6-phosphate dehydrogenases. Because the Entner-Doudoroff pathway is the main glycolytic route in this bacterium, determining how much NADH and NADPH are produced in the reaction catalyzed by these enzymes is very important for the correct interpretation of metabolic flux distributions. To determine the actual cofactor preference of the glucose-6-phosphate dehydrogenase encoded by the zwf-1 gene (PputG6PDH-1), the major isoform during growth on glucose, we purified this protein and studied its kinetic properties. Based on simple kinetic principles, we estimated the in vivo relative production of NADH and NADPH during the oxidation of glucose-6-phosphate (G6P). Contrary to the general assumption, our calculations showed that the reaction catalyzed by PputG6PDH-1 yields around 1/3 mol of NADPH and 2/3 mol of NADH per mol of oxidized G6P. Additionally, we obtained data suggesting that the reaction catalyzed by the 6-phosphogluconate dehydrogenase is active during growth on glucose, and it also produces NADH. These results indicate that the stoichiometric matrix of in silico models of P. putida KT2440 must be corrected and highlight the importance of considering the physiological concentrations of the involved metabolites to estimate the actual proportion of NADH and NADPH produced by a dehydrogenase.