Empirical predictive modelling of poly-ɛ-lysine biosynthesis in resting cells of Streptomyces noursei

Challenges in developing cell culture media using machine learning

Microbial and mammalian cells are widely used in the food, pharmaceutical, and medical industries. Developing or optimizing culture media is essential to improve cell culture performance as a critical technology in cell culture engineering. Methodologies for media optimization have been developed to a great extent, such as the approaches of one-factor-at-a-time (OFAT) and response surface methodology (RSM). The present review introduces the emerging machine learning (ML) technology in cell culture engineering by combining high-throughput experimental technologies to develop highly efficient and effective culture media. The commonly used ML algorithms and the successful applications of employing ML in medium optimization are summarized. This review highlights the benefits of ML-assisted medium development and guides the selection of the media optimization method appropriate for various cell culture purposes.

Recent advances in microbial ε-poly-L-lysine fermentation and its diverse applications

The naturally occurring homo-polyamide biopolymer, ε-poly-L-lysine (ε-PL) consists of 25-35 L-lysine residues with amide linkages between α-carboxyl groups and ε-amino groups. ɛ-PL exhibits several useful properties because of its unusual structure, such as biodegradability, water solubility, no human toxicity, and broad-spectrum antibacterial activities; it is widely applied in the fields of food, medicine, clinical chemistry and electronics. However, current industrial production of ε-PL is only performed in a few countries. Based on an analysis of the physiological characteristics of ε-PL fermentation, current advances that enhance ε-PL fermentation, from strain improvement to product isolation are systematically reviewed, focusing on: (1) elucidating the metabolic pathway and regulatory mechanism of ε-PL synthesis; (2) enhancing biosynthetic performance through mutagenesis, fermentation optimization and metabolic engineering; and (3) understanding and improving the biological activity and functional properties of ε-PL. Finally, perspectives on engineering and exploiting ε-PL as a source material for the production of various advanced materials are also discussed, providing scientific guidelines for researchers to further improve the ε-PL fermentation process.

New Insight into Sugarcane Industry Waste Utilization (Press Mud) for Cleaner Biobutanol Production by Using C. acetobutylicum NRRL B-527

In the present study, press mud, a sugar industry waste, was explored for biobutanol production to strengthen agricultural economy. The fermentative production of biobutanol was investigated via series of steps, viz. characterization, drying, acid hydrolysis, detoxification, and fermentation. Press mud contains an adequate amount of cellulose (22.3%) and hemicellulose (21.67%) on dry basis, and hence, it can be utilized for further acetone-butanol-ethanol (ABE) production. Drying experiments were conducted in the temperature range of 60-120 °C to circumvent microbial spoilage and enhance storability of press mud. Furthermore, acidic pretreatment variables, viz. sulfuric acid concentration, solid to liquid ratio, and time, were optimized using response surface methodology. The corresponding values were found to be 1.5% (v/v), 1:5 g/mL, and 15 min, respectively. In addition, detoxification studies were also conducted using activated charcoal, which removed almost 93-97% phenolics and around 98% furans, which are toxic to microorganisms during fermentation. Finally, the batch fermentation of detoxified press mud slurry (the sample dried at 100 °C and pretreated) using Clostridium acetobutylicum NRRL B-527 resulted in a higher butanol production of 4.43 g/L with a total ABE of 6.69 g/L.