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Abstract Understanding how photosynthetic organisms including plants and microbes respond to their environment is crucial for optimizing agricultural practices and ensuring food and energy security, particularly in the context of climactic change and sustainability. This perspective embeds back-of-the-envelope calculations across a photosynthetic organism design and scale up workflow. Starting from the whole system level, we provide a recipe to pinpoint key genetic targets, examine the logistics of detailed computational modeling, explore environmentally driven phenotypes, and feasibility as an industrial biofuel production chassis. While complex computer models or high throughput in vivo studies often dominate scientific inquiry, this perspective highlights the power of simple calculations as a valuable tool for initial exploration and evaluating study feasibility. Fermi calculations are defined as quick, approximate estimations made using back-of-the-envelope calculations and straightforward reasoning to achieve order-of-magnitude accuracy, named after the physicist Enrico Fermi. We show how Fermi calculations, based on fundamental principles and readily available data, can offer a first pass understanding of metabolic shifts in plants and microbes in response to environmental and genetic changes. We also discuss how Fermi checks can be embedded in data-driven advanced computing workflows to enable bio-aware machine learning. Lastly, an understanding of state-of-the-art is necessary to guide study feasibility and identifying key levers to maximize cost to return ratios. Combining biology- and resource- aware Fermi calculations, this proposed approach enables researchers to prioritize resource allocation, identify gaps in predictions and experiments, and develop intuition about how observed responses of plants differ between controlled laboratory environments and industrial conditions. 

Abstract Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T‐cell activation by antigen‐presenting beads and their subsequent expansion is formulated in silico. The simulation is used as an environment to train RL‐agents to dynamically control the number of beads in culture to maximize the population of robust effector cells at the end of the culture. We make periodic decisions of incremental bead addition or complete removal. The simulation is designed to operate in OpenAI Gym, enabling testing of different environments, cell types, RL‐agent algorithms, and state inputs to the RL‐agent. RL‐agent training is demonstrated with three different algorithms (PPO, A2C, and DQN), each sampling three different state input types (tabular, image, mixed); PPO‐tabular performs best for this simulation environment. Using this approach, training of the RL‐agent on different cell types is demonstrated, resulting in unique control strategies for each type. Sensitivity to input‐noise (sensor performance), number of control step interventions, and advantages of pre‐trained RL‐agents are also evaluated. Therefore, we present an RL framework to maximize the population of robust effector cells in CAR T‐cell therapy production. 

ABSTRACT Proper disinfection of harvested food and water is critical to minimize infectious disease. Grape seed extract (GSE), a commonly used health supplement, is a mixture of plant-derived polyphenols. Polyphenols possess antimicrobial and antifungal properties, but antiviral effects are not well-known. Here we show that GSE outperformed chemical disinfectants (e.g., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. GSE induced virus aggregation, a process that correlated with a decrease in virus titers. This aggregation and disinfection were not reversible. Molecular docking simulations indicate that polyphenols potentially formed hydrogen bonds and strong hydrophobic interactions with specific residues in viral capsid proteins. Together, these data suggest that polyphenols physically associate with viral capsid proteins to aggregate viruses as a means to inhibit virus entry into the host cell. Plant-based polyphenols like GSE are an attractive alternative to chemical disinfectants to remove infectious viruses from water or food. IMPORTANCE Human noroviruses are major food- and waterborne pathogens, causing approximately 20% of all cases of acute gastroenteritis cases in developing and developed countries. Proper sanitation or disinfection are critical strategies to minimize human norovirus-caused disease until a reliable vaccine is created. Grape seed extract (GSE) is a mixture of plant-derived polyphenols used as a health supplement. Polyphenols are known for antimicrobial, antifungal, and antibiofilm activities, but antiviral effects are not well-known. In studies presented here, plant-derived polyphenols outperformed chemical disinfectants (i.e., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. Based on data from molecular assays and molecular docking simulations, the current model is that the polyphenols in GSE bind to the Tulane virus capsid, an event that triggers virion aggregation. It is thought that this aggregation prevents Tulane virus from entering host cells. 

Abstract Pathogen contamination of water has a massive impact on global human health. In particular, viruses pose unique challenges to water treatment techniques due to their small size and presence in water as both individual virions and when absorbed onto larger particles. Low-energy water treatment processes such as media filtration are not capable of completely removing viruses owing to their small size. Hence, less sustainable processes with high chemical or energy consumption such as chemical disinfection, ultraviolet irradiation, and membrane filtration are usually required. To overcome high energy and/or chemical requirements for virus treatment, designs for sustainable fiber filters fabricated from minimally processed natural materials for efficient virus (MS2) and bacteria (E. coli) removal are presented in this work. These filters were created by functionalizing readily accessible natural fibers including cotton, silk, and flax with a simple aqueous extract containing cationic proteins fromMoringa oleiferaseeds. The proposed filters offer a comprehensive low cost, low energy, and low environmental impact solution for pathogen removal from water with removals of >7log₁₀(99.99999%) for viruses and bacteria. 

Abstract Nature relies on a wide range of enzymes with specific biocatalytic roles to carry out much of the chemistry needed to sustain life. Enzymes catalyze the interconversion of a vast array of molecules with high specificity—from molecular nitrogen fixation to the synthesis of highly specialized hormones and quorum‐sensing molecules. Ever increasing emphasis on renewable sources for energy and waste minimization has turned enzymes into key industrial workhorses for targeted chemical conversions. Modern enzymology is central to not only food and beverage manufacturing processes but also finds relevance in countless consumer product formulations such as proteolytic enzymes in detergents, amylases for excess bleach removal from textiles, proteases in meat tenderization, and lactoperoxidases in dairy products. Herein, we present an overview of enzyme science and engineering milestones and the emergence of directed evolution of enzymes for which the 2018 Nobel Prize in Chemistry was awarded to Dr. Frances Arnold.