1887

A Simulator-Assisted Workshop for Teaching Chemostat Cultivation in Academic Classes on Microbial Physiology

    Authors: Xavier D. V. Hakkaart1, Jack T. Pronk1, Antonius J. A. van Maris1,2,*
    VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Department of Biotechnology, Delft University of Technology, Van der Maasweg 9, 2629HZ Delft, The Netherlands; 2: Present address: Division of Industrial Biotechnology, School of Biotechnology, KTH Royal Institute of Technology, AlbaNova University Center, SE 106 91, Stockholm, Sweden
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Received 23 December 2016 Accepted 05 August 2017 Published 04 October 2017
    • ©2017 Author(s). Published by the American Society for Microbiology
    • [open-access] This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-NoDerivatives 4.0 International license (https://creativecommons.org/licenses/by-nc-nd/4.0/ and https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode), which grants the public the nonexclusive right to copy, distribute, or display the published work.

    • Supplemental materials available at http://asmscience.org/jmbe
    • *Corresponding author. Mailing address: Division of Industrial Biotechnology, School of Biotechnology, KTH Royal Institute of Technology, AlbaNova University Center, SE 106 91, Stockholm, Sweden. E-mail: [email protected].
    Source: J. Microbiol. Biol. Educ. October 2017 vol. 18 no. 3 doi:10.1128/jmbe.v18i3.1292
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    Abstract:

    Understanding microbial growth and metabolism is a key learning objective of microbiology and biotechnology courses, essential for understanding microbial ecology, microbial biotechnology and medical microbiology. Chemostat cultivation, a key research tool in microbial physiology that enables quantitative analysis of growth and metabolism under tightly defined conditions, provides a powerful platform to teach key features of microbial growth and metabolism.

    Substrate-limited chemostat cultivation can be mathematically described by four equations. These encompass mass balances for biomass and substrate, an empirical relation that describes distribution of consumed substrate over growth and maintenance energy requirements (Pirt equation), and a Monod-type equation that describes the relation between substrate concentration and substrate-consumption rate. The authors felt that the abstract nature of these mathematical equations and a lack of visualization contributed to a suboptimal operative understanding of quantitative microbial physiology among students who followed their Microbial Physiology B.Sc. courses.

    The studio-classroom workshop presented here was developed to improve student understanding of quantitative physiology by a set of question-guided simulations. Simulations are run on Chemostatus, a specially developed MATLAB-based program, which visualizes key parameters of simulated chemostat cultures as they proceed from dynamic growth conditions to steady state.

    In practice, the workshop stimulated active discussion between students and with their teachers. Moreover, its introduction coincided with increased average exam scores for questions on quantitative microbial physiology. The workshop can be easily implemented in formal microbial physiology courses or used by individuals seeking to test and improve their understanding of quantitative microbial physiology and/or chemostat cultivation.

Key Concept Ranking

Microbial Growth Kinetics
0.43121523
0.43121523

References & Citations

1. Bull AT 2010 The renaissance of continuous culture in the post-genomics age J Ind Microbiol Biotechnol 37 993 1021 10.1007/s10295-010-0816-4 20835748 http://dx.doi.org/10.1007/s10295-010-0816-4
2. Monod J 1949 The growth of bacterial cultures Annu Rev Microbiol 3 371 394 10.1146/annurev.mi.03.100149.002103 http://dx.doi.org/10.1146/annurev.mi.03.100149.002103
3. Novick A, Szilard L 1950 Description of the chemostat Science 112 2920 715 716 10.1126/science.112.2920.715 14787503 http://dx.doi.org/10.1126/science.112.2920.715
4. Herbert D, Elsworth R, Telling RC 1956 The continuous culture of bacteria; a theoretical and experimental study J Gen Microbiol 14 601 622 10.1099/00221287-14-3-601 13346021 http://dx.doi.org/10.1099/00221287-14-3-601
5. Daran-Lapujade P, Daran JM, van Maris AJA, de Winde JH, Pronk JT 2009 Chemostat-based micro-array analysis in baker’s yeast Adv Microb Physiol 54 257 311 10.1016/S0065-2911(08)00004-0 http://dx.doi.org/10.1016/S0065-2911(08)00004-0
6. Monod J 1950 La technique de culture continue théorie et applications Ann Inst Pasteur (Paris) 79 390 412
7. Sevella B, Bertalan G 2000 Development of a MATLAB-based bioprocess simulation tool 23 621 626
8. Enfors SO 2015 Simuplot 4 Available on www.enfors.eu
9. Pirt SJ 1982 Maintenance energy: a general model for energy-limited and energy-sufficient growth Arch Microbiol 133 300 302 10.1007/BF00521294 7171288 http://dx.doi.org/10.1007/BF00521294
10. Pirt SJ 1965 The maintenance energy of bacteria in growing cultures Proc R Soc London 163 224 231 10.1098/rspb.1965.0069 http://dx.doi.org/10.1098/rspb.1965.0069
11. Snoep JL, Mrwebi M, Schuurmans JM, Rohwer JM, Teixeira de Mattos MJ 2009 Control of specific growth rate in Saccharomyces cerevisiae Microbiology 155 1699 1707 10.1099/mic.0.023119-0 19359324 http://dx.doi.org/10.1099/mic.0.023119-0
12. Diderich JA, Schepper M, van Hoek P, Luttik MAH, van Dijken JP, Pronk JT, Klaassen P, Boelens HFM, Teixeira de Mattos MJ, van Dam K, Kruckeberg AL 1999 Glucose uptake kinetics and transcription of HXT Genes in chemostat cultures of Saccharomyces cerevisiae J Biol Chem 274 15350 15359 10.1074/jbc.274.22.15350 10336421 http://dx.doi.org/10.1074/jbc.274.22.15350
13. van Uden N 1967 Transport-limited growth in the chemostat and its competitive inhibition; a theoretical treatment Arch Mikrobiol 58 2 145 154 10.1007/BF00406675 4878543 http://dx.doi.org/10.1007/BF00406675
14. de Jong-Gubbels P, Bauer J, Niederberger P, Stückrath I, van Dijken JP, Pronk JT 1998 Physiological characterisation of a pyruvate-carboxylase-negative Saccharomyces cerevisiae mutant in batch and chemostat cultures Antonie van Leeuwenhoek 74 4 253 263 10.1023/A:1001772613615 http://dx.doi.org/10.1023/A:1001772613615
15. Tagoe D, Ansah FK 2010 Computer keyboard and mice: potential sources of disease transmission and infections Int J Pub Health 1 1 6
16. Harder W, Kuenen JG, Matin A 1977 Microbial selection in continuous culture J Appl Bacteriol 43 1 24 10.1111/j.1365-2672.1977.tb00717.x 332677 http://dx.doi.org/10.1111/j.1365-2672.1977.tb00717.x
17. Dijkhuizen DE, Hartl DL 1983 Selection in chemostats Microbiol Rev 47 150 168
18. Novick A, Szilard L 1950 Experiments with the chemostat on spontaneous mutations in bacteria Proc Natl Acad Sci USA 36 12 708 719 10.1073/pnas.36.12.708 14808160 1063276 http://dx.doi.org/10.1073/pnas.36.12.708

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2019-08-25

Abstract:

Understanding microbial growth and metabolism is a key learning objective of microbiology and biotechnology courses, essential for understanding microbial ecology, microbial biotechnology and medical microbiology. Chemostat cultivation, a key research tool in microbial physiology that enables quantitative analysis of growth and metabolism under tightly defined conditions, provides a powerful platform to teach key features of microbial growth and metabolism.

Substrate-limited chemostat cultivation can be mathematically described by four equations. These encompass mass balances for biomass and substrate, an empirical relation that describes distribution of consumed substrate over growth and maintenance energy requirements (Pirt equation), and a Monod-type equation that describes the relation between substrate concentration and substrate-consumption rate. The authors felt that the abstract nature of these mathematical equations and a lack of visualization contributed to a suboptimal operative understanding of quantitative microbial physiology among students who followed their Microbial Physiology B.Sc. courses.

The studio-classroom workshop presented here was developed to improve student understanding of quantitative physiology by a set of question-guided simulations. Simulations are run on Chemostatus, a specially developed MATLAB-based program, which visualizes key parameters of simulated chemostat cultures as they proceed from dynamic growth conditions to steady state.

In practice, the workshop stimulated active discussion between students and with their teachers. Moreover, its introduction coincided with increased average exam scores for questions on quantitative microbial physiology. The workshop can be easily implemented in formal microbial physiology courses or used by individuals seeking to test and improve their understanding of quantitative microbial physiology and/or chemostat cultivation.

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Figures

Image of FIGURE 1

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FIGURE 1

Schematic representation of a chemostat set-up. F and F are volumetric flows, V represents the liquid volume and C represents a concentration. Subscripts in and out denote transport respectively into or from the reactor. Subscript s denotes the carbon and energy-source (substrate) and subscript x denotes biomass.

Source: J. Microbiol. Biol. Educ. October 2017 vol. 18 no. 3 doi:10.1128/jmbe.v18i3.1292
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Image of FIGURE 2

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FIGURE 2

Student performance on exam questions concerning continuous cultivations before (2014 and 2015) and after (2016) the introduction of the simulator workshop. A boxplot of the distribution of average grades of individual students on these questions for the regular exam (Panel A) and resit exams (Panel B) shows the minimum and maximum grades, the 25% and 75% quartiles (upper and lower limit of the box) and the median (black bar in the box). The asterisk indicates that the average grade was significantly higher in 2016 than in the two other years ( < 0.05 in a Student’s -test). Panel A: Student’s -test 2014 to 2016 < 0.001; 2015 to 2016 < 0.001. Panel B: Student’s -test 2014 to 2016 < 0.05; 2015 to 2016 < 0.001. The questions and the corresponding learning outcomes are provided in Appendix 5 . In the Dutch education system, students pass with a grade of 5.5 or higher. The percentage of students passing the exam questions that specifically dealt with steady-state chemostat conditions is shown for the regular exams (Panel C) and resit exams (Panel D).

Source: J. Microbiol. Biol. Educ. October 2017 vol. 18 no. 3 doi:10.1128/jmbe.v18i3.1292
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