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Myers KS, Ingle AT, Walters KA, Fortney NW, Scarborough MJ, Donohue TJ, Noguera DR. Comparison of metagenomes from fermentation of various agroindustrial residues suggests a common model of community organization. Front Bioeng Biotechnol 2023; 11:1197175. [PMID: 37260833 PMCID: PMC10228549 DOI: 10.3389/fbioe.2023.1197175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 04/27/2023] [Indexed: 06/02/2023] Open
Abstract
The liquid residue resulting from various agroindustrial processes is both rich in organic material and an attractive source to produce a variety of chemicals. Using microbial communities to produce chemicals from these liquid residues is an active area of research, but it is unclear how to deploy microbial communities to produce specific products from the different agroindustrial residues. To address this, we fed anaerobic bioreactors one of several agroindustrial residues (carbohydrate-rich lignocellulosic fermentation conversion residue, xylose, dairy manure hydrolysate, ultra-filtered milk permeate, and thin stillage from a starch bioethanol plant) and inoculated them with a microbial community from an acid-phase digester operated at the wastewater treatment plant in Madison, WI, United States. The bioreactors were monitored over a period of months and sampled to assess microbial community composition and extracellular fermentation products. We obtained metagenome assembled genomes (MAGs) from the microbial communities in each bioreactor and performed comparative genomic analyses to identify common microorganisms, as well as any community members that were unique to each reactor. Collectively, we obtained a dataset of 217 non-redundant MAGs from these bioreactors. This metagenome assembled genome dataset was used to evaluate whether a specific microbial ecology model in which medium chain fatty acids (MCFAs) are simultaneously produced from intermediate products (e.g., lactic acid) and carbohydrates could be applicable to all fermentation systems, regardless of the feedstock. MAGs were classified using a multiclass classification machine learning algorithm into three groups, organisms fermenting the carbohydrates to intermediate products, organisms utilizing the intermediate products to produce MCFAs, and organisms producing MCFAs directly from carbohydrates. This analysis revealed common biological functions among the microbial communities in different bioreactors, and although different microorganisms were enriched depending on the agroindustrial residue tested, the results supported the conclusion that the microbial ecology model tested was appropriate to explain the MCFA production potential from all agricultural residues.
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Affiliation(s)
- Kevin S. Myers
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
| | - Abel T. Ingle
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
- Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, United States
| | - Kevin A. Walters
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, United States
| | - Nathaniel W. Fortney
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
| | - Matthew J. Scarborough
- Department of Civil and Environmental Engineering, University of Vermont, Burlington, VT, United States
| | - Timothy J. Donohue
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, United States
| | - Daniel R. Noguera
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI, United States
- Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, United States
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Abstract
Bifidobacteria naturally inhabit diverse environments, including the gastrointestinal tracts of humans and animals. Members of the genus are of considerable scientific interest due to their beneficial effects on health and, hence, their potential to be used as probiotics. By definition, probiotic cells need to be viable despite being exposed to several stressors in the course of their production, storage, and administration. Examples of common stressors encountered by probiotic bifidobacteria include oxygen, acid, and bile salts. As bifidobacteria are highly heterogenous in terms of their tolerance to these stressors, poor stability and/or robustness can hamper the industrial-scale production and commercialization of many strains. Therefore, interest in the stress physiology of bifidobacteria has intensified in recent decades, and many studies have been established to obtain insights into the molecular mechanisms underlying their stability and robustness. By complementing traditional methodologies, omics technologies have opened new avenues for enhancing the understanding of the defense mechanisms of bifidobacteria against stress. In this review, we summarize and evaluate the current knowledge on the multilayered responses of bifidobacteria to stressors, including the most recent insights and hypotheses. We address the prevailing stressors that may affect the cell viability during production and use as probiotics. Besides phenotypic effects, molecular mechanisms that have been found to underlie the stress response are described. We further discuss strategies that can be applied to improve the stability of probiotic bifidobacteria and highlight knowledge gaps that should be addressed in future studies.
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Affiliation(s)
- Marie Schöpping
- Systems Biology, Discovery, Chr. Hansen A/S, Hørsholm, Denmark
- Division of Industrial Biotechnology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Ahmad A. Zeidan
- Systems Biology, Discovery, Chr. Hansen A/S, Hørsholm, Denmark
| | - Carl Johan Franzén
- Division of Industrial Biotechnology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
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Patel S, Tan J, Börner R, Zhang S, Priour S, Lima A, Ngom-Bru C, Cotter P, Duboux S. A temporal view of the water kefir microbiota and flavour attributes. INNOV FOOD SCI EMERG 2022. [DOI: 10.1016/j.ifset.2022.103084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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Abstract
Over the last decade, the genomes of several Bifidobacterium strains have been sequenced, delivering valuable insights into their genetic makeup. However, bifidobacterial genomes have not yet been systematically mined for genes associated with stress response functions and their regulation. In this work, a list of 76 genes related to stress response in bifidobacteria was compiled from previous studies. The prevalence of the genes was evaluated among the genome sequences of 171 Bifidobacterium strains. Although genes of the protein quality control and DNA repair systems appeared to be highly conserved, genome-wide in silico screening for consensus sequences of putative regulators suggested that the regulation of these systems differs among phylogenetic groups. Homologs of multiple oxidative stress-associated genes are shared across species, albeit at low sequence similarity. Bee isolates were confirmed to harbor unique genetic features linked to oxygen tolerance. Moreover, most studied Bifidobacterium adolescentis and all Bifidobacterium angulatum strains lacked a set of reactive oxygen species-detoxifying enzymes, which might explain their high sensitivity to oxygen. Furthermore, the presence of some putative transcriptional regulators of stress responses was found to vary across species and strains, indicating that different regulation strategies of stress-associated gene transcription contribute to the diverse stress tolerance. The presented stress response gene profiles of Bifidobacterium strains provide a valuable knowledge base for guiding future studies by enabling hypothesis generation and the identification of key genes for further analyses. IMPORTANCE Bifidobacteria are Gram-positive bacteria that naturally inhabit diverse ecological niches, including the gastrointestinal tract of humans and animals. Strains of the genus Bifidobacterium are widely used as probiotics, since they have been associated with health benefits. In the course of their production and administration, probiotic bifidobacteria are exposed to several stressors that can challenge their survival. The stress tolerance of probiotic bifidobacteria is, therefore, an important selection criterion for their commercial application, since strains must maintain their viability to exert their beneficial health effects. As the ability to cope with stressors varies among Bifidobacterium strains, comprehensive understanding of the underlying stress physiology is required for enabling knowledge-driven strain selection and optimization of industrial-scale production processes.
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Gökırmaklı Ç, Guzel-Seydim ZB. Water Kefir Grains vs. Milk Kefir Grains: Physical, Microbial and Chemical Comparison. J Appl Microbiol 2022; 132:4349-4358. [PMID: 35301787 DOI: 10.1111/jam.15532] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/10/2022] [Accepted: 03/14/2022] [Indexed: 11/30/2022]
Abstract
AIMS Even though kefir has been known for centuries, there is confusion between the two types of kefir grains, e.g., milk kefir grain and water kefir grain. This study aimed to unravel the differences and similarities between water kefir grain and milk kefir grain. METHODS AND RESULTS Microbiological analyses, identification of grains microbiota and enumeration of microbiological content of the grains as well as Scanning Electron Microscope (SEM) imaging, dry matter, protein, ash, and mineral content, and color analyses were carried out for the two types of grains. As a result, significant differences were found in microbiological content, chemical properties, and colors (p<0.05). Additionally, SEM images revealed the different intrinsic structures for the microbiota and the structure of the two types of grains. CONCLUSIONS MK grain has more nutritional content compared to WK grain. Despite not as widely known and used as MK grain, WK grain is a good source for minerals and health-friendly microorganisms like lactic acid bacteria (LAB) and yeasts. WK grain is possibly suitable for vegans and allergic individuals to fulfill nutritional requirements. Moreover, in this study, the variety of WK grain microbial consortia was wider than that of MK grains, and this significantly affected the resultant WK products. SIGNIFICANCE AND IMPACT OF THE STUDY This is the first study that comprehensively compares two different kefir grains in microbial, chemical, and physical properties.
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Affiliation(s)
- Çağlar Gökırmaklı
- Department of Ffood Engineering, Süleyman Demirel University, Isparta 32260, Turkey
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Laureys D, Leroy F, Hauffman T, Raes M, Aerts M, Vandamme P, De Vuyst L. The Type and Concentration of Inoculum and Substrate as Well as the Presence of Oxygen Impact the Water Kefir Fermentation Process. Front Microbiol 2021; 12:628599. [PMID: 33643256 PMCID: PMC7904701 DOI: 10.3389/fmicb.2021.628599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 01/18/2021] [Indexed: 11/13/2022] Open
Abstract
Eleven series of water kefir fermentation processes differing in the presence of oxygen and the type and concentration of inoculum and substrate, were followed as a function of time to quantify the impact of these parameters on the kinetics of this process via a modeling approach. Increasing concentrations of the water kefir grain inoculum increased the water kefir fermentation rate, so that the metabolic activity during water kefir fermentation was mainly associated with the grains. Water kefir liquor could also be used as an alternative means of inoculation, but the resulting fermentation process progressed slower than the one inoculated with water kefir grains, and the production of water kefir grain mass was absent. Substitution of sucrose with glucose and/or fructose reduced the water kefir grain growth, whereby glucose was fermented faster than fructose. Lacticaseibacillus paracasei (formerly known as Lactobacillus paracasei), Lentilactobacillus hilgardii (formerly known as Lactobacillus hilgardii), Liquorilactobacillus nagelii (formerly known as Lactobacillus nagelii), Saccharomyces cerevisiae, and Dekkera bruxellensis were the main microorganisms present. Acetic acid bacteria were present in low abundances under anaerobic conditions and only proliferated under aerobic conditions. Visualization of the water kefir grains through scanning electron microscopy revealed that the majority of the microorganisms was attached onto their surface. Lactic acid bacteria and yeasts were predominantly associated with the grains, whereas acetic acid bacteria were predominantly associated with the liquor.
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Affiliation(s)
- David Laureys
- Research Group of Industrial Microbiology and Food Biotechnology, Faculty of Sciences and Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Frédéric Leroy
- Research Group of Industrial Microbiology and Food Biotechnology, Faculty of Sciences and Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Tom Hauffman
- Research Group of Electrochemical and Surface Engineering, Faculty of Engineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Marc Raes
- Research Group of Electrochemical and Surface Engineering, Faculty of Engineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Maarten Aerts
- Laboratory of Microbiology, Department of Biochemistry and Microbiology, Faculty of Sciences, Ghent University, Ghent, Belgium
| | - Peter Vandamme
- Laboratory of Microbiology, Department of Biochemistry and Microbiology, Faculty of Sciences, Ghent University, Ghent, Belgium
| | - Luc De Vuyst
- Research Group of Industrial Microbiology and Food Biotechnology, Faculty of Sciences and Bioengineering Sciences, Vrije Universiteit Brussel, Brussels, Belgium
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