1
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Conacher CG, Watson BW, Bauer FF. Gradient boosted regression as a tool to reveal key drivers of temporal dynamics in a synthetic yeast community. FEMS Microbiol Ecol 2024; 100:fiae080. [PMID: 38777744 PMCID: PMC11212668 DOI: 10.1093/femsec/fiae080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 05/14/2024] [Accepted: 05/21/2024] [Indexed: 05/25/2024] Open
Abstract
Microbial communities are vital to our lives, yet their ecological functioning and dynamics remain poorly understood. This understanding is crucial for assessing threats to these systems and leveraging their biotechnological applications. Given that temporal dynamics are linked to community functioning, this study investigated the drivers of community succession in the wine yeast community. We experimentally generated population dynamics data and used it to create an interpretable model with a gradient boosted regression tree approach. The model was trained on temporal data of viable species populations in various combinations, including pairs, triplets, and quadruplets, and was evaluated for predictive accuracy and input feature importance. Key findings revealed that the inoculation dosage of non-Saccharomyces species significantly influences their performance in mixed cultures, while Saccharomyces cerevisiae consistently dominates regardless of initial abundance. Additionally, we observed multispecies interactions where the dynamics of Wickerhamomyces anomalus were influenced by Torulaspora delbrueckii in pairwise cultures, but this interaction was altered by the inclusion of S. cerevisiae. This study provides insights into yeast community succession and offers valuable machine learning-based analysis techniques applicable to other microbial communities, opening new avenues for harnessing microbial communities.
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Affiliation(s)
- Cleo Gertrud Conacher
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Private Bag X1, Stellenbosch University, Stellenbosch 7600, South Africa
- Centre for Artificial Intelligence Research (CAIR), School for Data-Science & Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Bruce William Watson
- Centre for Artificial Intelligence Research (CAIR), School for Data-Science & Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Florian Franz Bauer
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Private Bag X1, Stellenbosch University, Stellenbosch 7600, South Africa
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2
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Tang X, Wu Q, Shang L, Liu K, Ge Y, Liang P, Li B. Raman cell sorting for single-cell research. Front Bioeng Biotechnol 2024; 12:1389143. [PMID: 38832129 PMCID: PMC11145634 DOI: 10.3389/fbioe.2024.1389143] [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: 02/21/2024] [Accepted: 04/08/2024] [Indexed: 06/05/2024] Open
Abstract
Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research. Raman cell sorting technology has garnered attention owing to its non-labeling, non-destructive detection features and the capability to analyze samples containing water. In addition, this technology can provide live cells for subsequent genomics analysis and gene sequencing. This paper emphasizes the importance of single-cell research, describes the single-cell research methods that currently exist, including single-cell manipulation and single-cell identification techniques, and highlights the advantages of Raman spectroscopy in the field of single-cell analysis by comparing it with the fluorescence-activated cell sorting (FACS) technique. It describes various existing Raman cell sorting techniques and introduces their respective advantages and disadvantages. The above techniques were compared and analyzed, considering a variety of factors. The current bottlenecks include weak single-cell spontaneous Raman signals and the requirement for a prolonged total cell exposure time, significantly constraining Raman cell sorting technology's detection speed, efficiency, and throughput. This paper provides an overview of current methods for enhancing weak spontaneous Raman signals and their associated advantages and disadvantages. Finally, the paper outlines the detailed information related to the Raman cell sorting technology mentioned in this paper and discusses the development trends and direction of Raman cell sorting.
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Affiliation(s)
- Xusheng Tang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qingyi Wu
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lindong Shang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Kunxiang Liu
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yan Ge
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Peng Liang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
- Hooke Instruments Ltd., Changchun, China
| | - Bei Li
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
- Hooke Instruments Ltd., Changchun, China
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3
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Egli T, Campostrini L, Leifels M, Füchslin HP, Kolm C, Dan C, Zimmermann S, Hauss V, Guiller A, Grasso L, Shajkofci A, Farnleitner AH, Kirschner AKT. Domestic hot-water boilers harbour active thermophilic bacterial communities distinctly different from those in the cold-water supply. WATER RESEARCH 2024; 253:121109. [PMID: 38377920 DOI: 10.1016/j.watres.2024.121109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 12/29/2023] [Accepted: 01/04/2024] [Indexed: 02/22/2024]
Abstract
Running cold and hot water in buildings is a widely established commodity. However, interests regarding hygiene and microbiological aspects had so far been focussed on cold water. Little attention has been given to the microbiology of domestic hot-water installations (DHWIs), except for aspects of pathogenic Legionella. World-wide, regulations consider hot (or warm) water as 'heated drinking water' that must comply (cold) drinking water (DW) standards. However, the few reports that exist indicate presence and growth of microbial flora in DHWIs, even when supplied with water with disinfectant residual. Using flow cytometric (FCM) total cell counting (TCC), FCM-fingerprinting, and 16S rRNA-gene-based metagenomic analysis, the characteristics and composition of bacterial communities in cold drinking water (DW) and hot water from associated boilers (operating at 50 - 60 °C) was studied in 14 selected inhouse DW installations located in Switzerland and Austria. A sampling strategy was applied that ensured access to the bulk water phase of both, supplied cold DW and produced hot boiler water. Generally, 1.3- to 8-fold enhanced TCCs were recorded in hot water compared to those in the supplied cold DW. FCM-fingerprints of cold and corresponding hot water from individual buildings indicated different composition of cold- and hot-water microbial floras. Also, hot waters from each of the boilers sampled had its own individual FCM-fingerprint. 16S rRNA-gene-based metagenomic analysis confirmed the marked differences in composition of microbiomes. E.g., in three neighbouring houses supplied from the same public network pipe each hot-water boiler contained its own thermophilic bacterial flora. Generally, bacterial diversity in cold DW was broad, that in hot water was restricted, with mostly thermophilic strains from the families Hydrogenophilaceae, Nitrosomonadaceae and Thermaceae dominating. Batch growth assays, consisting of cold DW heated up to 50 - 60 °C and inoculated with hot water, resulted in immediate cell growth with doubling times between 5 and 10 h. When cold DW was used as an inoculum no significant growth was observed. Even boilers supplied with UVC-treated cold DW contained an actively growing microbial flora, suggesting such hot-water systems as autonomously operating, thermophilic bioreactors. The generation of assimilable organic carbon from dissolved organic carbon due to heating appears to be the driver for growth of thermophilic microbial communities. Our report suggests that a man-made microbial ecosystem, very close to us all and of potential hygienic importance, may have been overlooked so far. Despite consumers having been exposed to microbial hot-water flora for a long time, with no major pathogens so far been associated specifically with hot-water usage (except for Legionella), the role of harmless thermophiles and their interaction with potential human pathogens able to grow at elevated temperatures in DHWIs remains to be investigated.
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Affiliation(s)
- Thomas Egli
- Microbes-in-Water GmbH, Feldmeilen CH-8706, Switzerland.
| | - Lena Campostrini
- Institute for Hygiene and Applied Immunology, Water Microbiology, Medical University of Vienna, Vienna A-1090, Austria; Interuniversity Cooperation Centre Water & Health, Austria
| | - Mats Leifels
- Division of Water Quality and Health, Dept. Pharmacology, Physiology and Microbiology, Karl Landsteiner University, Krems A-3500, Austria; Interuniversity Cooperation Centre Water & Health, Austria
| | | | - Claudia Kolm
- Division of Water Quality and Health, Dept. Pharmacology, Physiology and Microbiology, Karl Landsteiner University, Krems A-3500, Austria; Centre for Water Resource Systems, Vienna University of Technology, Vienna A-1040, Austria; Interuniversity Cooperation Centre Water & Health, Austria
| | - Cheng Dan
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | | | - Vivian Hauss
- bNovate Technologies SA, Zurich CH-8045, Switzerland
| | | | | | | | - Andreas H Farnleitner
- Division of Water Quality and Health, Dept. Pharmacology, Physiology and Microbiology, Karl Landsteiner University, Krems A-3500, Austria; Centre for Water Resource Systems, Vienna University of Technology, Vienna A-1040, Austria; Interuniversity Cooperation Centre Water & Health, Austria
| | - Alexander K T Kirschner
- Institute for Hygiene and Applied Immunology, Water Microbiology, Medical University of Vienna, Vienna A-1090, Austria; Division of Water Quality and Health, Dept. Pharmacology, Physiology and Microbiology, Karl Landsteiner University, Krems A-3500, Austria; Interuniversity Cooperation Centre Water & Health, Austria.
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4
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Peña FJ, Martín-Cano FE, Becerro-Rey L, Ortega-Ferrusola C, Gaitskell-Phillips G, da Silva-Álvarez E, Gil MC. The future of equine semen analysis. Reprod Fertil Dev 2024; 36:RD23212. [PMID: 38467450 DOI: 10.1071/rd23212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 02/15/2024] [Indexed: 03/13/2024] Open
Abstract
We are currently experiencing a period of rapid advancement in various areas of science and technology. The integration of high throughput 'omics' techniques with advanced biostatistics, and the help of artificial intelligence, is significantly impacting our understanding of sperm biology. These advances will have an appreciable impact on the practice of reproductive medicine in horses. This article provides a brief overview of recent advances in the field of spermatology and how they are changing assessment of sperm quality. This article is written from the authors' perspective, using the stallion as a model. We aim to portray a brief overview of the changes occurring in the assessment of sperm motility and kinematics, advances in flow cytometry, implementation of 'omics' technologies, and the use of artificial intelligence/self-learning in data analysis. We also briefly discuss how some of the advances can be readily available to the practitioner, through the implementation of 'on-farm' devices and telemedicine.
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Affiliation(s)
- Fernando J Peña
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - Francisco Eduardo Martín-Cano
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - Laura Becerro-Rey
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - Cristina Ortega-Ferrusola
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - Gemma Gaitskell-Phillips
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - Eva da Silva-Álvarez
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
| | - María Cruz Gil
- Laboratory of Equine Reproduction and Equine Spermatology, Veterinary Teaching Hospital, University of Extremadura, Cáceres, Spain
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5
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Jyoti TP, Chandel S, Singh R. Flow cytometry: Aspects and application in plant and biological science. JOURNAL OF BIOPHOTONICS 2024; 17:e202300423. [PMID: 38010848 DOI: 10.1002/jbio.202300423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 10/28/2023] [Indexed: 11/29/2023]
Abstract
Flow cytometry is a potent method that enables the quick and concurrent investigation of several characteristics of single cells in solution. Photodiodes or photomultiplier tubes are employed to detect the dispersed and fluorescent light signals that are produced by the laser beam as it passes through the cells. Photodetectors transform the light signals produced by the laser into electrical impulses. A computer then analyses these electrical impulses to identify and measure the various cell populations depending on their fluorescence or light scattering characteristics. Based on their fluorescence or light scattering properties, cell populations can be examined and/or isolated. This review covers the basic principle, components, working and specific biological applications of flow cytometry, including studies on plant, cell and molecular biology and methods employed for data processing and interpretation as well as the potential future relevance of this methodology in light of retrospective analysis and recent advancements in flow cytometry.
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Affiliation(s)
- Thakur Prava Jyoti
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
| | - Shivani Chandel
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
| | - Rajveer Singh
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
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6
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Mermans F, Mattelin V, Van den Eeckhoudt R, García-Timermans C, Van Landuyt J, Guo Y, Taurino I, Tavernier F, Kraft M, Khan H, Boon N. Opportunities in optical and electrical single-cell technologies to study microbial ecosystems. Front Microbiol 2023; 14:1233705. [PMID: 37692384 PMCID: PMC10486927 DOI: 10.3389/fmicb.2023.1233705] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/03/2023] [Indexed: 09/12/2023] Open
Abstract
New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.
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Affiliation(s)
- Fabian Mermans
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
- Department of Oral Health Sciences, KU Leuven, Leuven, Belgium
| | - Valérie Mattelin
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Ruben Van den Eeckhoudt
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Cristina García-Timermans
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Josefien Van Landuyt
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Yuting Guo
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Irene Taurino
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
- Semiconductor Physics, Department of Physics and Astronomy, KU Leuven, Leuven, Belgium
| | - Filip Tavernier
- MICAS, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Michael Kraft
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
- Leuven Institute of Micro- and Nanoscale Integration (LIMNI), KU Leuven, Leuven, Belgium
| | - Hira Khan
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Nico Boon
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
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7
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Hasanin G, Mosquera AM, Emwas AH, Altmann T, Das R, Buijs PJ, Vrouwenvelder JS, Gonzalez-Gil G. The microbial growth potential of antiscalants used in seawater desalination. WATER RESEARCH 2023; 233:119802. [PMID: 36871379 DOI: 10.1016/j.watres.2023.119802] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 02/10/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
20 years since the first report on the biofouling potential of chemicals used for scale control, still, antiscalants with high bacterial growth potential are used in practice. Evaluating the bacterial growth potential of commercially available antiscalants is therefore essential for a rational selection of these chemicals. Previous antiscalant growth potential tests were conducted in drinking water or seawater inoculated with model bacterial species which do not represent natural bacterial communities. To reflect better on the conditions of desalination systems, we investigated the bacterial growth potential of eight different antiscalants in natural seawater and an autochthonous bacterial population as inoculum. The antiscalants differed strongly in their bacterial growth potential varying from ≤ 1 to 6 μg easily biodegradable C equivalents/mg antiscalant. The six phosphonate-based antiscalants investigated showed a broad range of growth potential, which depended on their chemical composition, whilst the biopolymer and the synthetic carboxylated polymers-based antiscalants showed limited or no significant bacterial growth. Moreover, nuclear magnetic resonance (NMR) scans enabled antiscalant fingerprinting, identifying components and contaminants, providing a rapid and sensitive characterization, and opening opportunities for rational selection of antiscalants for biofouling control.
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Affiliation(s)
- Ghadeer Hasanin
- Biological and Environmental Science and Engineering Division (BESE), Water Desalination and Reuse Center (WDRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Ana Maria Mosquera
- Biological and Environmental Science and Engineering Division (BESE), Water Desalination and Reuse Center (WDRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Abdul-Hamid Emwas
- Advanced Nanofabrication Imaging and Characterization, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Thomas Altmann
- Innovation and New Technology, ACWA Power, 41st Floor, The One Tower, Barsha Heights, Sheikh Zayed Road, Dubai, United Arab Emirates
| | - Ratul Das
- Innovation and New Technology, ACWA Power, 41st Floor, The One Tower, Barsha Heights, Sheikh Zayed Road, Dubai, United Arab Emirates.
| | - Paulus J Buijs
- Biological and Environmental Science and Engineering Division (BESE), Water Desalination and Reuse Center (WDRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Johannes S Vrouwenvelder
- Biological and Environmental Science and Engineering Division (BESE), Water Desalination and Reuse Center (WDRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Graciela Gonzalez-Gil
- Biological and Environmental Science and Engineering Division (BESE), Water Desalination and Reuse Center (WDRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
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8
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Shan Y, Guo Y, Jiao W, Zeng P. Single-Cell Techniques in Environmental Microbiology. Processes (Basel) 2023. [DOI: 10.3390/pr11041109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023] Open
Abstract
Environmental microbiology has been an essential part of environmental research because it provides effective solutions to most pollutants. Hence, there is an interest in investigating microorganism behavior, such as observation, identification, isolation of pollutant degraders, and interactions between microbial species. To comprehensively understand cell heterogeneity, diverse approaches at the single-cell level are demanded. Thus far, the traditional bulk biological tools such as petri dishes are technically challenging for single cells, which could mask the heterogeneity. Single-cell technologies can reveal complex and rare cell populations by detecting heterogeneity among individual cells, which offers advantages of higher resolution, higher throughput, more accurate analysis, etc. Here, we overviewed several single-cell techniques on observation, isolation, and identification from aspects of methods and applications. Microscopic observation, sequencing identification, flow cytometric identification and isolation, Raman spectroscopy-based identification and isolation, and their applications are mainly discussed. Further development on multi-technique integrations at the single-cell level may highly advance the research progress of environmental microbiology, thereby giving more indication in the environmental microbial ecology.
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Affiliation(s)
- Yongping Shan
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuting Guo
- Flow Cytometry Center, National Institute of Biological Sciences, Beijing 102206, China
| | - Wentao Jiao
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Ping Zeng
- Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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9
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Zhang Z, Wei Y, Peng Z, Du P, Du X, Zuo G, Wang C, Li P, Wang J, Wang R. Exploration of microbiome diversity of stacked fermented grains by flow cytometry and cell sorting. Front Microbiol 2023; 14:1160552. [PMID: 37051523 PMCID: PMC10083240 DOI: 10.3389/fmicb.2023.1160552] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/06/2023] [Indexed: 03/28/2023] Open
Abstract
Sauce-flavor baijiu is one of the twelve flavor types of Chinese distilled fermented product. Microbial composition plays a key role in the stacked fermentation of Baijiu, which uses grains as raw materials and produces flavor compounds, however, the active microbial community and its relationship remain unclear. Here, we investigated the total and active microbial communities of stacked fermented grains of sauce-flavored Baijiu using flow cytometry and high-throughput sequencing technology, respectively. By using traditional high-throughput sequencing technology, a total of 24 bacterial and 14 fungal genera were identified as the core microbiota, the core bacteria were Lactobacillus (0.08–39.05%), Acetobacter (0.25–81.92%), Weissella (0.03–29.61%), etc. The core fungi were Issatchenkia (23.11–98.21%), Monascus (0.02–26.36%), Pichia (0.33–37.56%), etc. In contrast, using flow cytometry combined with high-throughput sequencing, the active dominant bacterial genera after cell sorting were found to be Herbaspirillum, Chitinophaga, Ralstonia, Phenylobacterium, Mucilaginibacter, and Bradyrhizobium, etc., whereas the active dominant fungal genera detected were Aspergillus, Pichia, Exophiala, Candelabrochaete, Italiomyces, and Papiliotrema, etc. These results indicate that although the abundance of Acetobacter, Monascus, and Issatchenkia was high after stacked fermentation, they may have little biological activity. Flow cytometry and cell sorting techniques have been used in the study of beer and wine, but exploring the microbiome in such a complex environment as Chinese baijiu has not been reported. The results also reveal that flow cytometry and cell sorting are convenient methods for rapidly monitoring complex microbial flora and can assist in exploring complex environmental samples.
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Affiliation(s)
- Ziyang Zhang
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
| | - Yanwei Wei
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
| | - Zehao Peng
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
| | - Peng Du
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
| | - Xinyong Du
- Gubeichun Group Co., Ltd., Jinan, Shandong, China
| | - Guoying Zuo
- Gubeichun Group Co., Ltd., Jinan, Shandong, China
| | | | - Piwu Li
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
| | - Junqing Wang
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
- *Correspondence: Junqing Wang,
| | - Ruiming Wang
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Jinan, Shandong, China
- Department of Biological Engineering, Qilu University of Technology, Jinan, Shandong, China
- Ruiming Wang,
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10
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Tracey H, Coates N, Hulme E, John D, Michael DR, Plummer SF. Insights into the enumeration of mixtures of probiotic bacteria by flow cytometry. BMC Microbiol 2023; 23:48. [PMID: 36849905 PMCID: PMC9969615 DOI: 10.1186/s12866-023-02792-2] [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: 10/07/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023] Open
Abstract
The use of flow cytometry to enumerate microorganisms is gaining traction over the traditional plate count technique on the basis of superior accuracy, precision and time-to-result. Here, we assessed the suitability of live/dead flow cytometry for the enumeration of mixed populations of probiotic bacteria (L. acidophilus, L. paracasei, L. plantarum, L. salivarius, B. lactis and B. bifidum) whilst comparing outcomes with plate counting. Using a novel gating strategy designed specifically for the enumeration of mixed populations, the application of flow cytometry resulted in the detection of higher numbers of viable bacteria with a greater level of repeatability than plate counting (RSD of 6.82 and 13.14% respectively). Across all multi-species blends tested, viable cell input was more accurately recovered by flow cytometry (101.8 ± 6.95%) than plate counts (81.37 ± 16.03%). However, when certain probiotic mixtures contained preparations with high numbers of non-viable cells in their total population, flow cytometry had the potential for overestimation of the viable population. Nevertheless, the comparative plate counts of these mixtures were low and variable, thus supporting the use of flow cytometry for the enumeration of viable bacteria in mixed populations.
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Affiliation(s)
- Harry Tracey
- Cultech Limited, Unit 2 Christchurch Road, Baglan Industrial Park, Port Talbot, UK
| | - Niall Coates
- Cultech Limited, Unit 2 Christchurch Road, Baglan Industrial Park, Port Talbot, UK.
| | - Eleri Hulme
- Cultech Limited, Unit 2 Christchurch Road, Baglan Industrial Park, Port Talbot, UK
| | - Daniel John
- Cultech Limited, Unit 2 Christchurch Road, Baglan Industrial Park, Port Talbot, UK
| | - Daryn Robert Michael
- Cultech Limited, Unit 2 Christchurch Road, Baglan Industrial Park, Port Talbot, UK
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11
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Pernice MC, Gasol JM. Automated flow cytometry as a tool to obtain a fine-grain picture of marine prokaryote community structure along an entire oceanographic cruise. Front Microbiol 2023; 13:1064112. [PMID: 36687618 PMCID: PMC9853387 DOI: 10.3389/fmicb.2022.1064112] [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: 10/07/2022] [Accepted: 12/12/2022] [Indexed: 01/08/2023] Open
Abstract
On a standard oceanographic cruise, flow cytometry data are usually collected sparsely through a bottle-based sampling and with stations separated by kilometers leading to a fragmented view of the ecosystem; to improve the resolution of the datasets produced by this technique here it is proposed the application of an automatic method of sampling and staining. The system used consists of a flow-cytometer (Accuri-C6) connected to an automated continuous sampler (OC-300) that collects samples of marine surface waters every 15 min. We tested this system for five days during a brief Mediterranean cruise with the aim of estimating the abundance, relative size and phenotypic diversity of prokaryotes. Seawater was taken by a faucet linked to an inlet pump (ca. 5 m depth). Once the sample was taken, the Oncyt-300 stained it and sent it to the flow cytometer. A total of 366 samples were collected, effectively achieving a fine-grained scale view of microbial community composition both through space and time. A significative positive relationship was found comparing data obtained with the automatic method and 10 samples collected from the faucet but processed with the standard protocol. Abundance values retrieved varied from 3.56·105 cell mL-1 in the coastal area till 6.87 105 cell mL-1 in open waters, exceptional values were reached in the harbor area where abundances peaked to 1.28 106 cell mL-1. The measured features (abundance and size) were associated with metadata (temperature, salinity, conductivity) also taken in continuous, of which conductivity was the one that better explained the variability of abundance. A full 24 h measurement cycle was performed resulting in slightly higher median bacterial abundances values during daylight hours compared to night. Alpha diversity, calculated using computational cytometry techniques, showed a higher value in the coastal area above 41° of latitude and had a strong inverse relationship with both salinity and conductivity. This is the first time to our knowledge that the OC-300 is directly applied to the marine environment during an oceanographic cruise; due to its high-resolution, this set-up shows great potential both to cover large sampling areas, and to monitor day-night cycles in situ.
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12
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Midani FS, David LA. Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity. Front Microbiol 2023; 13:910390. [PMID: 36687598 PMCID: PMC9849913 DOI: 10.3389/fmicb.2022.910390] [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: 04/01/2022] [Accepted: 11/29/2022] [Indexed: 01/07/2023] Open
Abstract
Cross feeding between microbes is ubiquitous, but its impact on the diversity and productivity of microbial communities is incompletely understood. A reductionist approach using simple microbial communities has the potential to detect cross feeding interactions and their impact on ecosystem properties. However, quantifying abundance of more than two microbes in a community in a high throughput fashion requires rapid, inexpensive assays. Here, we show that multicolor flow cytometry combined with a machine learning-based classifier can rapidly quantify species abundances in simple, synthetic microbial communities. Our approach measures community structure over time and detects the exchange of metabolites in a four-member community of fluorescent Bacteroides species. Notably, we quantified species abundances in co-cultures and detected evidence of cooperation in polysaccharide processing and competition for monosaccharide utilization. We also observed that co-culturing on simple sugars, but not complex sugars, reduced microbial productivity, although less productive communities maintained higher community diversity. In summary, our multicolor flow cytometric approach presents an economical, tractable model system for microbial ecology using well-studied human bacteria. It can be extended to include additional species, evaluate more complex environments, and assay response of communities to a variety of disturbances.
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Affiliation(s)
- Firas S. Midani
- Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
| | - Lawrence A. David
- Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, United States
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13
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Free T. Investigating myeloid cells? Go with the flow. Biotechniques 2022; 73:163-165. [PMID: 36205120 DOI: 10.2144/btn-2022-0099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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14
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Schmiester M, Maier R, Riedel R, Durek P, Frentsch M, Kolling S, Mashreghi MF, Jenq R, Zhang L, Peterson CB, Bullinger L, Chang HD, Na IK. Flow cytometry can reliably capture gut microbial composition in healthy adults as well as dysbiosis dynamics in patients with aggressive B-cell non-Hodgkin lymphoma. Gut Microbes 2022; 14:2081475. [PMID: 35634713 PMCID: PMC9154785 DOI: 10.1080/19490976.2022.2081475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Modulation of commensal gut microbiota is increasingly recognized as a promising strategy to reduce mortality in patients with malignant diseases, but monitoring for dysbiosis is generally not routine clinical practice due to equipment, expertise and funding required for sequencing analysis. A low-threshold alternative is microbial diversity profiling by single-cell flow cytometry (FCM), which we compared to 16S rRNA sequencing in human fecal samples and employed to characterize longitudinal changes in the microbiome composition of patients with aggressive B-cell non-Hodgkin lymphoma undergoing chemoimmunotherapy. Diversity measures obtained from both methods were correlated and captured identical trends in microbial community structures, finding no difference in patients' pretreatment alpha or beta diversity compared to healthy controls and a significant and progressive loss of alpha diversity during chemoimmunotherapy. Our results highlight the potential of FCM-based microbiome profiling as a reliable and accessible diagnostic tool that can provide novel insights into cancer therapy-associated dysbiosis dynamics.
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Affiliation(s)
- Maren Schmiester
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany,Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany,CONTACT Maren Schmiester Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin', Berlin, Germany
| | - René Maier
- Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), an Institute of the Leibniz Association, Berlin, Germany
| | - René Riedel
- Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), an Institute of the Leibniz Association, Berlin, Germany
| | - Pawel Durek
- Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), an Institute of the Leibniz Association, Berlin, Germany
| | - Marco Frentsch
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Kolling
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany,Berlin School of Integrative Oncology, Berlin, Germany
| | - Mir-Farzin Mashreghi
- BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany,(DRFZ), an Institute of the Leibniz AssociationTherapeutic Gene Regulation, Deutsches Rheuma-Forschungszentrum, Berlin, Germany
| | - Robert Jenq
- Department of Genomic Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Liangliang Zhang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Christine B. Peterson
- Department of Biostatistics, the University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lars Bullinger
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany,German Cancer Research Center (DKFZ), Heidelberg, Germany,German Cancer Consortium (DKTK), Berlin, Germany
| | - Hyun-Dong Chang
- Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), an Institute of the Leibniz Association, Berlin, Germany,Institute of Biotechnology, Technische Universität Berlin, Germany
| | - Il-Kang Na
- Department of Hematology, Oncology and Tumor Immunology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany,BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany,German Cancer Consortium (DKTK), Berlin, Germany,ECRC Experimental and Clinical Research Center, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
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15
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El Mujtar VA, Chirdo F, Lagares A, Wall L, Tittonell P. Soil bacterial biodiversity characterization by flow cytometry: The bottleneck of cell extraction from soil. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Verónica A. El Mujtar
- Agroecology, Environment and Systems Group, Instituto de Investigaciones Forestales y Agropecuarias de Bariloche (IFAB) INTA‐CONICET, San Carlos de Bariloche Río Negro Argentina
| | - Fernando Chirdo
- Instituto de Estudios Inmunológicos y Fisiopatológicos (IIFP)(UNLP‐CONICET), Facultad de Ciencias Exactas Universidad Nacional de La Plata La Plata Argentina
| | - Antonio Lagares
- IBBM—Instituto de Biotecnología y Biología Molecular, Facultad de Ciencias Exactas Universidad Nacional de La Plata, CCT‐La Plata CONICET La Plata Argentina
| | - Luis Wall
- Laboratorio de Bioquímica y Microbiología de Suelo, Centro de Bioquímica y Microbiología de Suelos Universidad Nacional de Quilmes Bernal Argentina
| | - Pablo Tittonell
- Agroecology, Environment and Systems Group, Instituto de Investigaciones Forestales y Agropecuarias de Bariloche (IFAB) INTA‐CONICET, San Carlos de Bariloche Río Negro Argentina
- Groningen Institute of Evolutionary Life Sciences Groningen University Groningen The Netherlands
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Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data. Curr Opin Biotechnol 2022; 75:102688. [PMID: 35123235 DOI: 10.1016/j.copbio.2022.102688] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/09/2021] [Accepted: 01/05/2022] [Indexed: 01/06/2023]
Abstract
Dynamic analysis of microbial composition is crucial for understanding community functioning and detecting dysbiosis. Compositional information is mostly obtained through sequencing of taxonomic markers or whole meta-genomes, which may be productively complemented by real-time quantitative community multiparametric flow cytometry data (FCM). Patterns and clusters in FCM community data can be distinguished and compared by unsupervised machine learning. Alternatively, FCM data from preselected individual strain phenotypes can be used for supervised machine-training in order to differentiate similar cell types within communities. Both types of machine learning can quantitatively deconvolute community FCM data sets and rapidly analyse global changes in response to treatment. Procedures may further be optimized for recurrent microbiome samples to simultaneously quantify physiological and compositional states.
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Predicting the Presence and Abundance of Bacterial Taxa in Environmental Communities through Flow Cytometric Fingerprinting. mSystems 2021; 6:e0055121. [PMID: 34546074 PMCID: PMC8547484 DOI: 10.1128/msystems.00551-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Microbiome management research and applications rely on temporally resolved measurements of community composition. Current technologies to assess community composition make use of either cultivation or sequencing of genomic material, which can become time-consuming and/or laborious in case high-throughput measurements are required. Here, using data from a shrimp hatchery as an economically relevant case study, we combined 16S rRNA gene amplicon sequencing and flow cytometry data to develop a computational workflow that allows the prediction of taxon abundances based on flow cytometry measurements. The first stage of our pipeline consists of a classifier to predict the presence or absence of the taxon of interest, with yielded an average accuracy of 88.13% ± 4.78% across the top 50 operational taxonomic units (OTUs) of our data set. In the second stage, this classifier was combined with a regression model to predict the relative abundances of the taxon of interest, which yielded an average R2 of 0.35 ± 0.24 across the top 50 OTUs of our data set. Application of the models to flow cytometry time series data showed that the generated models can predict the temporal dynamics of a large fraction of the investigated taxa. Using cell sorting, we validated that the model correctly associates taxa to regions in the cytometric fingerprint, where they are detected using 16S rRNA gene amplicon sequencing. Finally, we applied the approach of our pipeline to two other data sets of microbial ecosystems. This pipeline represents an addition to the expanding toolbox for flow cytometry-based monitoring of bacterial communities and complements the current plating- and marker gene-based methods. IMPORTANCE Monitoring of microbial community composition is crucial for both microbiome management research and applications. Existing technologies, such as plating and amplicon sequencing, can become laborious and expensive when high-throughput measurements are required. In recent years, flow cytometry-based measurements of community diversity have been shown to correlate well with those derived from 16S rRNA gene amplicon sequencing in several aquatic ecosystems, suggesting that there is a link between the taxonomic community composition and phenotypic properties as derived through flow cytometry. Here, we further integrated 16S rRNA gene amplicon sequencing and flow cytometry survey data in order to construct models that enable the prediction of both the presence and the abundances of individual bacterial taxa in mixed communities using flow cytometric fingerprinting. The developed pipeline holds great potential to be integrated into routine monitoring schemes and early warning systems for biotechnological applications.
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Conacher CG, Luyt NA, Naidoo-Blassoples RK, Rossouw D, Setati ME, Bauer FF. The ecology of wine fermentation: a model for the study of complex microbial ecosystems. Appl Microbiol Biotechnol 2021; 105:3027-3043. [PMID: 33834254 DOI: 10.1007/s00253-021-11270-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 03/30/2021] [Accepted: 04/04/2021] [Indexed: 12/11/2022]
Abstract
The general interest in microbial ecology has skyrocketed over the past decade, driven by technical advances and by the rapidly increasing appreciation of the fundamental services that these ecosystems provide. In biotechnology, ecosystems have many more functionalities than single species, and, if properly understood and harnessed, will be able to deliver better outcomes for almost all imaginable applications. However, the complexity of microbial ecosystems and of the interactions between species has limited their applicability. In research, next generation sequencing allows accurate mapping of the microbiomes that characterise ecosystems of biotechnological and/or medical relevance. But the gap between mapping and understanding, to be filled by "functional microbiomics", requires the collection and integration of many different layers of complex data sets, from molecular multi-omics to spatial imaging technologies to online ecosystem monitoring tools. Holistically, studying the complexity of most microbial ecosystems, consisting of hundreds of species in specific spatial arrangements, is beyond our current technical capabilities, and simpler model systems with fewer species and reduced spatial complexity are required to establish the fundamental rules of ecosystem functioning. One such ecosystem, the ecosystem responsible for natural alcoholic fermentation, can provide an excellent tool to study evolutionarily relevant interactions between multiple species within a relatively easily controlled environment. This review will critically evaluate the approaches that are currently implemented to dissect the cellular and molecular networks that govern this ecosystem. KEY POINTS: • Evolutionarily isolated fermentation ecosystem can be used as an ecological model. • Experimental toolbox is gearing towards mechanistic understanding of this ecosystem. • Integration of multidisciplinary datasets is key to predictive understanding.
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Affiliation(s)
- C G Conacher
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa
| | - N A Luyt
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa
| | - R K Naidoo-Blassoples
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa
| | - D Rossouw
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa
| | - M E Setati
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa
| | - F F Bauer
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Stellenbosch, 7600, South Africa.
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