Chemostat Explained

Chemostat
Industry:Biological engineering
Application:Research and Industry

A chemostat (from chemical environment is static) is a bioreactor to which fresh medium is continuously added, while culture liquid containing left over nutrients, metabolic end products and microorganisms is continuously removed at the same rate to keep the culture volume constant.[1] [2] By changing the rate with which medium is added to the bioreactor the specific growth rate of the microorganism can be easily controlled within limits.

Operation

Steady state

One of the most important features of chemostats is that microorganisms can be grown in a physiological steady state under constant environmental conditions. In this steady state, growth occurs at a constant specific growth rate and all culture parameters remain constant (culture volume, dissolved oxygen concentration, nutrient and product concentrations, pH, cell density, etc.). In addition, environmental conditions can be controlled by the experimenter.[3] Microorganisms growing in chemostats usually reach a steady state because of a negative feedback between growth rate and nutrient consumption: if a low number of cells are present in the bioreactor, the cells can grow at growth rates higher than the dilution rate as they consume little nutrient so growth is less limited by the addition of limiting nutrient with the inflowing fresh medium. The limiting nutrient is a nutrient essential for growth, present in the medium at a limiting concentration (all other nutrients are usually supplied in surplus). However, the higher the number of cells becomes, the more nutrient is consumed, lowering the concentration of the limiting nutrient. In turn, this will reduce the specific growth rate of the cells, which will lead to a decline in the number of cells as they keep being removed from the system with the outflow. This results in a steady state. Due to self-regulation, the steady state is stable. This enables the experimenter to control the specific growth rate of the microorganisms by changing the speed of the pump feeding fresh medium into the vessel.

Well-mixed

Another important feature of chemostats and other continuous culture systems is that they are well-mixed so that environmental conditions are homogenous or uniform and microorganisms are randomly dispersed and encounter each other randomly. Therefore, competition and other interactions in the chemostat are global, in contrast to biofilms.

Dilution rate

The rate of nutrient exchange is expressed as the dilution rate D. At steady state, the specific growth rate μ of the micro-organism is equal to the dilution rate D. The dilution rate is defined as the flow of medium per unit of time, F, over the volume V of culture in the bioreactor

D=

mediumflowrate
culturevolume

=

F
V

Maximal growth rate and critical dilution rate

Specific growth rate μ is inversely related to the time it takes the biomass to double, called doubling time td, by:

\mu=

ln2
td

Therefore, the doubling time td becomes a function of dilution rate D in steady state:

td=

ln2
D

Each microorganism growing on a particular substrate has a maximal specific growth rate μmax (the rate of growth observed if growth is limited by internal constraints rather than external nutrients). If a dilution rate is chosen that is higher than μmax, the cells cannot grow at a rate as fast as the rate with which they are being removed so the culture will not be able to sustain itself in the bioreactor, and will wash out.

However, since the concentration of the limiting nutrient in the chemostat cannot exceed the concentration in the feed, the specific growth rate that the cells can reach in the chemostat is usually slightly lower than the maximal specific growth rate because specific growth rate usually increases with nutrient concentration as described by the kinetics of the Monod equation. The highest specific growth' rates (μmax) cells can attain is equal to the critical dilution rate (D'c):

D=\mumax{S\overKS+S},

where S is the substrate or nutrient concentration in the chemostat and KS is the half-saturation constant (this equation assumes Monod kinetics).

Applications

Research

Chemostats in research are used for investigations in cell biology, as a source for large volumes of uniform cells or protein. The chemostat is often used to gather steady state data about an organism in order to generate a mathematical model relating to its metabolic processes. Chemostats are also used as microcosms in ecology[4] [5] and evolutionary biology.[6] [7] [8] [9] In the one case, mutation/selection is a nuisance, in the other case, it is the desired process under study. Chemostats can also be used to enrich for specific types of bacterial mutants in culture such as auxotrophs or those that are resistant to antibiotics or bacteriophages for further scientific study.[10] Variations in the dilution rate permit the study of the metabolic strategies pursued by the organisms at different growth rates.[11] [12]

Competition for single and multiple resources, the evolution of resource acquisition and utilization pathways, cross-feeding/symbiosis,[13] [14] antagonism, predation, and competition among predators have all been studied in ecology and evolutionary biology using chemostats.[15] [16] [17]

Industry

Chemostats are frequently used in the industrial manufacturing of ethanol. In this case, several chemostats are used in series, each maintained at decreasing sugar concentrations. The chemostat also serves as an experimental model of continuous cell cultures in the biotechnological industry.

Technical concerns

Continuous efforts to remedy each defect lead to variations on the basic chemostat quite regularly. Examples in the literature are numerous.

Experimental design considerations

Parameter choice and setup

[22]

Steady state growth

[22]

Mutation

[22]

Single takeover

[22]

Successive takeovers

[22]

Variations

Fermentation setups closely related to the chemostats are the turbidostat, the auxostat and the retentostat. In retentostats, culture liquid is also removed from the bioreactor, but a filter retains the biomass. In this case, the biomass concentration increases until the nutrient requirement for biomass maintenance has become equal to the amount of limiting nutrient that can be consumed.

See also

External links

  1. http://www.pererikstrandberg.se/examensarbete/chemostat.pdf
  2. https://web.archive.org/web/20060504172359/http://www.rpi.edu/dept/chem-eng/Biotech-Environ/Contin/chemosta.htm
  3. A final thesis including mathematical models of the chemostat and other bioreactors
  4. A page about one laboratory chemostat design
  5. Comprehensive chemostat manual (Dunham lab). Procedures and principles are general.

Notes and References

  1. Novick A, Szilard L . Description of the Chemostat . Science . 112 . 2920 . 715–6 . 1950 . 14787503 . 10.1126/science.112.2920.715. 1950Sci...112..715N .
  2. James TW . Continuous Culture of Microorganisms . Annual Review of Microbiology . 15 . 27–46 . 1961 . 10.1146/annurev.mi.15.100161.000331.
  3. D Herbert . R Elsworth . RC Telling . The continuous culture of bacteria; a theoretical and experimental study. J. Gen. Microbiol. . 14 . 3 . 601–622 . 1956. 10.1099/00221287-14-3-601 . 13346021. free .
  4. Becks L, Hilker FM, Malchow H, Jürgens K, Arndt H . Experimental demonstration of chaos in a microbial food web . Nature . 435 . 7046 . 1226–9 . 2005 . 15988524 . 10.1038/nature03627. 2005Natur.435.1226B . 4380653 .
  5. Pavlou S, Kevrekidis IG . Yannís G. Kevrekidis . Microbial predation in a periodically operated chemostat: a global study of the interaction between natural and externally imposed frequencies . Math Biosci . 108 . 1 . 1–55 . 1992 . 1550993 . 10.1016/0025-5564(92)90002-E.
  6. Wichman HA, Millstein J, Bull JJ . Adaptive Molecular Evolution for 13,000 Phage Generations: A Possible Arms Race . Genetics . 170 . 1 . 19–31 . 2005 . 15687276 . 10.1534/genetics.104.034488 . 1449705.
  7. Dykhuizen DE, Dean AM . Evolution of specialists in an experimental microcosm . Genetics . 167 . 4 . 2015–26 . 2004 . 15342537 . 10.1534/genetics.103.025205 . 1470984.
  8. Wick LM, Weilenmann H, Egli T . The apparent clock-like evolution of Escherichia coli in glucose-limited chemostats is reproducible at large but not at small population sizes and can be explained with Monod kinetics . Microbiology . 148 . Pt 9 . 2889–902 . 2002 . 12213934 . 10.1099/00221287-148-9-2889 . free .
  9. Jones LE, Ellner SP . Effects of rapid prey evolution on predator-prey cycles . J Math Biol . 55 . 4 . 541–73 . 2007 . 17483952 . 10.1007/s00285-007-0094-6. q-bio/0609032 . 16927689 .
  10. Schlegel HG, Jannasch HW . Enrichment cultures . Annu. Rev. Microbiol. . 21 . 49–70 . 1967 . 4860267 . 10.1146/annurev.mi.21.100167.000405 .
  11. Varma. A.. Palsson. B. O.. 1994-10-01. Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110.. Applied and Environmental Microbiology. en. 60. 10. 3724–3731. 10.1128/aem.60.10.3724-3731.1994. 0099-2240. 7986045. 201879. 1994ApEnM..60.3724V.
  12. Fernandez-de-Cossio-Diaz. Jorge. Leon. Kalet. Mulet. Roberto. 2017-11-13. Characterizing steady states of genome-scale metabolic networks in continuous cell cultures. PLOS Computational Biology. 13. 11. e1005835. 10.1371/journal.pcbi.1005835. 29131817. 5703580. 1553-7358. 1705.09708. 2017PLSCB..13E5835F . free .
  13. Daughton CG, Hsieh DP . Parathion utilization by bacterial symbionts in a chemostat . Appl. Environ. Microbiol. . 34 . 2 . 175–84 . 1977 . 10.1128/aem.34.2.175-184.1977 . 410368 . 242618. 1977ApEnM..34..175D .
  14. Pfeiffer T, Bonhoeffer S . Evolution of cross-feeding in microbial populations . Am. Nat. . 163 . 6 . E126–35 . 2004 . 15266392 . 10.1086/383593. 31110741 .
  15. G. J. Butler . G. S. K. Wolkowicz . Gail Wolkowicz . Predator-mediated competition in the chemostat . J Math Biol . 24 . 2 . 67–191 . July 1986 . 10.1007/BF00275997. 120858390 .
  16. Dykhuizen DE, Hartl DL . Selection in chemostats . Microbiol. Rev. . 47 . 2 . 150–68 . June 1983 . 10.1128/mr.47.2.150-168.1983 . 6308409 . 281569.
  17. Dykhuizen DE, Hartl DL . Evolution of Competitive Ability in Escherichia coli . Evolution . 35 . 3 . 581–94 . May 1981 . 10.2307/2408204 . 2408204. 28563589 .
  18. Bonomi A, Fredrickson AG . Protozoan feeding and bacterial wall growth . . 18 . 2 . 239–52 . 1976 . 1267931 . 10.1002/bit.260180209. 41343643 .
  19. de Crécy E, Metzgar D, Allen C, Pénicaud M, Lyons B, Hansen CJ, de Crécy-Lagard V . Development of a novel continuous culture device for experimental evolution of bacterial populations . . 77 . 2 . 489–96 . 2007 . 17896105 . 10.1007/s00253-007-1168-5. 25787277 .
  20. Zhang Z, Boccazzi P, Choi HG, Perozziello G, Sinskey AJ, Jensen KF . Microchemostat-microbial continuous culture in a polymer-based, instrumented microbioreactor . Lab Chip . 6 . 7 . 906–13 . 2006 . 16804595 . 10.1039/b518396k.
  21. Van Hulle SW, Van Den Broeck S, Maertens J, Villez K, Schelstraete G, Volcke EI, Vanrolleghem PA . Practical experiences with start-up and operation of a continuously aerated lab-scale SHARON reactor . . 68 . 2 Pt A . 77–84 . 2003 . 15296140 .
  22. Wides A, Milo R . Understanding the Dynamics and Optimizing the Performance of Chemostat Selection Experiments . 2018 . 1806.00272. q-bio.PE .