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Banks M, Taylor M, Guo M. High throughput parameter estimation and uncertainty analysis applied to the production of mycoprotein from synthetic lignocellulosic hydrolysates. Curr Res Food Sci 2024; 9:100908. [PMID: 39555020 PMCID: PMC11565039 DOI: 10.1016/j.crfs.2024.100908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 10/22/2024] [Accepted: 10/27/2024] [Indexed: 11/19/2024] Open
Abstract
The current global food system produces substantial waste and carbon emissions while exacerbating the effects of global hunger and protein deficiency. This study aims to address these challenges by exploring the use of lignocellulosic agricultural residues as feedstocks for microbial protein fermentation, focusing on Fusarium venenatum A3/5, a mycelial strain known for its high protein yield and nutritional quality. We propose a high throughput microlitre batch fermentation system paired with analytical chemistry to generate time series data of microbial growth and substrate utilisation. An unstructured biokinetic model was developed using a bootstrap sampling approach to quantify uncertainty in the parameter estimates. The model was validated against an independent data set of a different glucose-xylose composition to assess the predictive performance. Our results indicate a robust model fit with high coefficients of determination and low root mean squared errors for biomass, glucose, and xylose concentrations. Estimated parameter values provided insights into the resource utilisation strategies of Fusarium venenatum A3/5 in mixed substrate cultures, aligning well with previous research findings. Significant correlations between estimated parameters were observed, highlighting challenges in parameter identifiability. The high throughput workflow presents a novel, rapid methodology for biokinetic model development, enabling efficient exploration of microbial growth dynamics and substrate utilisation. This innovative method directly supports the development of a foundational model for optimising microbial protein production from lignocellulosic hydrolysates, contributing to a more sustainable global food system.
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Affiliation(s)
- Mason Banks
- Department of Engineering, Faculty of Natural Mathematical & Engineering Sciences, King's College London, Strand, London, WC2R 2LS, United Kingdom
| | - Mark Taylor
- Fermentation Lead, Marlow Ingredients, Nelson Ave, Billingham, North Yorkshire, TS23 4HA, United Kingdom
| | - Miao Guo
- Department of Engineering, Faculty of Natural Mathematical & Engineering Sciences, King's College London, Strand, London, WC2R 2LS, United Kingdom
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Javad Jafari M, Golabi M, Ederth T. Antimicrobial susceptibility testing using infrared attenuated total reflection (IR-ATR) spectroscopy to monitor metabolic activity. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 304:123384. [PMID: 37714109 DOI: 10.1016/j.saa.2023.123384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/17/2023]
Abstract
Fast and accurate detection of antimicrobial resistance in pathogens remains a challenge, and with the increase in antimicrobial resistance due to mis- and overuse of antibiotics, it has become an urgent public health problem. We demonstrate how infrared attenuated total reflection (IR-ATR) can be used as a simple method for assessment of bacterial susceptibility to antibiotics. This is achieved by monitoring the metabolic activities of bacterial cells via nutrient consumption and using this as an indicator of bacterial viability. Principal component analysis of the obtained spectra provides a tool for fast and simple discrimination of antimicrobial resistance in the acquired data. We demonstrate this concept using four bacterial strains and four different antibiotics, showing that the change in glucose concentration in the growth medium after 2 h, as monitored by IR-ATR, can be used as a spectroscopic diagnostic technique, to reduce detection time and to improve quality in the assessment of antimicrobial resistance in pathogens.
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Affiliation(s)
- Mohammad Javad Jafari
- Division of Biophysics and Bioengineering, Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-581 83 Linköping, Sweden
| | - Mohsen Golabi
- Department of Biotechnology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan 81746-73441, Iran; Division of Biosensors and Bioelectronics, Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-581 83 Linköping, Sweden.
| | - Thomas Ederth
- Division of Biophysics and Bioengineering, Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-581 83 Linköping, Sweden.
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Kassem A, Abbas L, Coutinho O, Opara S, Najaf H, Kasperek D, Pokhrel K, Li X, Tiquia-Arashiro S. Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives. Front Microbiol 2023; 14:1304081. [PMID: 38075889 PMCID: PMC10703385 DOI: 10.3389/fmicb.2023.1304081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 11/03/2023] [Indexed: 01/02/2024] Open
Abstract
Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.
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Affiliation(s)
- Amin Kassem
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Lana Abbas
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Oliver Coutinho
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Somie Opara
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Hawraa Najaf
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Diana Kasperek
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Keshav Pokhrel
- Department of Mathematics and Statistics, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Xiaohua Li
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
| | - Sonia Tiquia-Arashiro
- Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, United States
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