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Microorganism Utilization for Synthetic Milk Production

A desired architecture for long duration spaceflight, such as aboard the International Space Station (ISS) or for future missions to Mars, is to provide a supply of fresh food crops for the astronauts. However, some crops can create a high proportion of inedible plant waste. The main goal of this project was to produce the components of milk (sugar, lipid, protein) from inedible plant waste by utilizing microorganisms (fungi, yeast, bacteria). Of particular interest was utilizing the valuable polysaccharide, cellulose, found in plant waste, to naturally fuel- through microorganism cellular metabolism- the creation of sugar (glucose), lipid (milk fat), and protein (casein) to produce a synthetic edible food product. Environmental conditions such as pH, temperature, carbon source, aeration, and choice microorganisms were optimized in the laboratory and the desired end-products, sugars and lipids, were analyzed. Trichoderma reesei, a known cellulolytic fungus, was utilized to drive the production of glucose, with the intent that the produced glucose would serve as the carbon source for milk fat production and be a substitute for the milk sugar lactose. Lipid production would be carried out by Rhodosporidium toruloides, yeast known to accumulate those lipids that are typically found in milk fat. Results showed that glucose and total lipid content were below what was expected during this phase of experimentation. In addition, individual analysis of six fatty acids revealed that the percentage of each fatty acid was lower than naturally produced bovine milk. Overall, this research indicates that microorganisms could be utilized to breakdown inedible solid waste to produce useable products.

Utilization↗

Microorganism Utilization for Synthetic Milk

A desired architecture for long duration spaceflight, like aboard the International Space Station or for future missions to Mars, is to provide a supply of fresh food crops for the astronauts. However, some crops can create a high proportion of inedible plant waste. The main goal of the Synthetic Biology project, Cow in a Column, was to produce the components of milk (sugar, lipid, protein) from inedible plant waste by utilizing microorganisms (fungi, yeast, bacteria). Of particular interest was utilizing the valuable polysaccharide, cellulose, found in plant waste, to naturally fuel-through microorganism cellular metabolism- the creation of sugar (glucose), lipid (milk fat), and protein (casein) in order to produce a synthetic edible food product. Environmental conditions such as pH, temperature, carbon source, aeration, and choice microorganisms were optimized in the laboratory and the desired end-products, sugars and lipids, were analyzed. Trichoderma reesei, a known cellulolytic fungus, was utilized to drive the production of glucose, with the intent that the produced glucose would serve as the carbon source for milk fat production and be a substitute for the milk sugar lactose. Lipid production would be carried out by Rhodosporidium toruloides, yeast known to accumulate those lipids that are typically found in milk fat. Results showed that glucose and total lipid content were below what was expected during this phase of experimentation. In addition, individual analysis of six fatty acids revealed that the percentage of each fatty acid was lower than naturally produced bovine milk. Overall, this research indicates that microorganisms could be utilized to breakdown inedible solid waste to produce useable products. For future work, the production of the casein protein for milk would require the development of a genetically modified organism, which was beyond the scope of the original project. Additional trials would be needed to further refine the required environment/organisms for the production of desired sugar and lipid end-products.

Microorganisms↗

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These important enzymes are often bimodular, including a catalytic domain and carbohydrate binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relationships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able discriminate GH7 CBHs and EGs with up to 99% accuracy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our ML results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗