Enabling Biological Nitrogen Fixation for Cereal Crops in Fertilized Fields.

Agricultural productivity relies on synthetic nitrogen fertilizers, yet half of that reactive nitrogen is lost to the environment. There is an urgent need for alternative nitrogen solutions to reduce the water pollution, ozone depletion, atmospheric particulate formation, and global greenhouse gas emissions associated with synthetic nitrogen fertilizer use. One such solution is biological nitrogen fixation (BNF), a component of the complex natural nitrogen cycle. BNF application to commercial agriculture is currently limited by fertilizer use and plant type. This paper describes the identification, development, and deployment of the first microbial product optimized using synthetic biology tools to enable BNF for corn (Zea mays) in fertilized fields, demonstrating the successful, safe commercialization of root-associated diazotrophs and realizing the potential of BNF to replace and reduce synthetic nitrogen fertilizer use in production agriculture. Derived from a wild nitrogen-fixing microbe isolated from agricultural soils, Klebsiella variicola 137-1036 ("Kv137-1036") retains the capacity of the parent strain to colonize corn roots while increasing nitrogen fixation activity 122-fold in nitrogen-rich environments. This technical milestone was then commercialized in less than half of the time of a traditional biological product, with robust biosafety evaluations and product formulations contributing to consumer confidence and ease of use. Tested in multi-year, multi-site field trial experiments throughout the U.S. Corn Belt, fields grown with Kv137-1036 exhibited both higher yields (0.35 ± 0.092 t/ha ± SE or 5.2 ± 1.4 bushels/acre ± SE) and reduced within-field yield variance by 25% in 2018 and 8% in 2019 compared to fields fertilized with synthetic nitrogen fertilizers alone. These results demonstrate the capacity of a broad-acre BNF product to fix nitrogen for corn in field conditions with reliable agronomic benefits.

Effects of imperfect dynamic clamp: computational and experimental results.

In the dynamic clamp technique, a typically nonlinear feedback system delivers electrical current to an excitable cell that represents the actions of "virtual" ion channels (e.g., channels that are gated by local membrane potential or by electrical activity in neighboring biological or virtual neurons). Since the conception of this technique, there have been a number of different implementations of dynamic clamp systems, each with differing levels of flexibility and performance. Embedded hardware-based systems typically offer feedback that is very fast and precisely timed, but these systems are often expensive and sometimes inflexible. PC-based systems, on the other hand, allow the user to write software that defines an arbitrarily complex feedback system, but real-time performance in PC-based systems can be deteriorated by imperfect real-time performance. Here, we systematically evaluate the performance requirements for artificial dynamic clamp knock-in of transient sodium and delayed rectifier potassium conductances. Specifically, we examine the effects of controller time step duration, differential equation integration method, jitter (variability in time step), and latency (the time lag from reading inputs to updating outputs). Each of these control system flaws is artificially introduced in both simulated and real dynamic clamp experiments. We demonstrate that each of these errors affect dynamic clamp accuracy in a way that depends on the time constants and stiffness of the differential equations being solved. In simulations, time steps above 0.2ms lead to catastrophic alteration of spike shape, but the frequency-current relationship is much more robust. Latency (the part of the time step that occurs between measuring membrane potential and injecting re-calculated membrane current) is a crucial factor as well. Experimental data are substantially more sensitive to inaccuracies than simulated data.