生物过程
淀粉
发酵
淀粉酶
生物燃料
食品科学
生物反应器
生物量(生态学)
原材料
水解
生物技术
化学
生物
生物化学
酶
植物
农学
古生物学
有机化学
作者
David Ubi,Maurice Ekpenyong,Eloghosa Ikharia,Ernest Akwagiobe,Atim Asitok,S. P. Antai
标识
DOI:10.1080/10826068.2023.2259452
摘要
AbstractThe biological conversion of agro-waste biomass into value-added metabolites is one of the trendy biotechnological research areas in recent times. One of the major drawbacks of the bioprocess is the saccharification potential of the amylolytic enzyme that releases reducing sugar from complex biomass to serve as substrate for fermentation. The present study reports the production of a novel tripartite raw starch-digesting amylase (RSDA) by an indigenous Priestia flexa strain with α-, β-, and gluco-amylolytic activities and its potential for bioethanol production. Response surface statistics was employed to develop a suitable medium for improved production of the tripartite enzyme by submerged fermentation. The bioprocess selected raw starch (4.36%) Ca2+(2.71 g/L) and Zn2+ (0.0177 g/L) as significant variables which demonstrated a total RSDA activity of 7208.23 U/mL in a 5-L batch bioreactor. SDS/Native-PAGE determined the molecular weights of the 27-fold purified product as 25.2 kDa, 57.3 kDa, and 90.1 kDa for α-, β-, and gluco-amylases, respectively. Optimum temperature and pH for enzyme activity were respectively broad at 30–70 °C and 4–11. The enzyme mixture demonstrated digestibility above 90% against a variety of raw starches and simultaneous fermentation of digestate with Saccharomyces cerevisiae generated 71.69 g/L of bioethanol within 24 h suggesting great potential for bioethanologenesis.Keywords: Bio-ethanologenesiscatalytic dynamicsPriestia flexasequential statisticstripartite raw starch-digesting amylase AcknowledgmentsThe technical contributions of technologists at the central laboratory of the University of Ibadan, Nigeria are highly appreciated; likewise, those of Pharmacognosy Department, Faculty of Pharmacy, University of Uyo, Nigeria. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.Authors' contributions[Maurice Ekpenyong] and [David Ubi] conceived the idea and designed the study. Material preparation, data collection and analysis were performed by [Maurice Ekpenyong], [Atim Asitok], [Ernest Akwagiobe] and [Eloghosa Ikharia]. The first draft of the manuscript was written by [David Ubi], [Maurice Ekpenyong] and [Sylvester Antai], and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.Disclosure statementThe authors have no relevant financial or non-financial interests to disclose.Data availability [database]The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.Additional informationFundingThe author(s) reported there is no funding associated with the work featured in this article.
科研通智能强力驱动
Strongly Powered by AbleSci AI