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Buan, N. R.

Publications and source records attributed to Buan, N. R..

2 recordsLinked to original sources

Coenzyme M: An Archaeal Antioxidant as an Agricultural Biostimulant

Rising global food demand necessitates improved crop yields. Biostimulants offer a potential solution to meet these demands. Among them, antioxidants have shown potential to improve yield, nutritional quality and resilience to climate change. However, large-scale production of many antioxidants is challenging. Here, we investigate Coenzyme M (CoM), a small, achiral antioxidant from archaea, as a potential biostimulant, investigating its effects on growth and physiology. CoM significantly increased biomass of the model plant Arabidopsis thaliana in a concentration-dependent manner consistent with it being metabolized. In tobacco, CoM increased photosynthetic light capture capacity, consistent with observed growth improvements. Interestingly, this effect was independent of carbon capture rates. Furthermore, CoM promoted early-stage shoot growth in various crops species, including tobacco, basil, cannabis, and soybean. Our results suggest CoM is a promising, scalable biostimulant with potential to modify photosynthesis and enhance crop productivity. Key PointsO_LIAntioxidant application improves plant growth but is typically too expensive to use widely. C_LIO_LICoenzyme M is a small, easily made antioxidant of Archaeal origin. C_LIO_LIApplied exogenously, Coenzyme M conditionally increases plant biomass. C_LIO_LICoenzyme M represents an antioxidant with potential to be a widely used biostimulant. C_LI

plant biology↗

A Molecular Communication model for cellular metabolism

Understanding cellular engagement with its environment is essential to control and monitor metabolism. Molecular Communication theory (MC) offers a computational means to identify environmental perturbations that direct or signify cellular behaviors by quantifying the information about a molecular environment that is transmitted through a metabolic system. We developed an model that integrates conventional flux balance analysis metabolic modeling (FBA) and MC to mechanistically expand the scope of MC, and thereby uniquely blends mechanistic biology and information theory to understand how substrate consumption is captured reaction activity, metabolite excretion, and biomass growth. This is enabled by defining several channels through which environmental information transmits in a metabolic network. The information flow in bits that is calculated through this workflow further determines the maximal metabolic effect of environmental perturbations on cellular metabolism and behaviors, since FBA simulates maximal efficiency of the metabolic system. We exemplify this method on two intestinal symbionts - Bacteroides thetaiotaomicron and Methanobrevibacter smithii - and visually consolidated the results into constellation diagrams that facilitate interpretation of information flow from given environments and thereby cultivate the design of controllable biological systems. The unique confluence of metabolic modeling and information theory in this model advances basic understanding of cellular metabolism and has applied value for the Internet of Bio-Nano Things, synthetic biology, microbial ecology, and autonomous laboratories.

bioinformatics↗