Literature DB >> 4091549

Effect of bacterial density and substrate concentration on yield coefficients.

M Seto, M Alexander.   

Abstract

Measurements were made of the yield coefficient during the aerobic metabolism of glucose by a heterogeneous bacterial mixture. Expressed in terms of carbon, the coefficient was approximately 0.48. The value did not vary with initial bacterial densities ranging from 0.4 pg to 40 micrograms of cell carbon per ml and with glucose concentrations ranging from 43 pg to 100 micrograms of carbon per ml. Under all these circumstances, about 44% of the glucose carbon was converted to CO2, and 7.4% was excreted as organic products. The significance of uncharacterized organic substrates contaminating the medium to the coefficients calculated for low glucose concentrations is discussed.

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Year:  1985        PMID: 4091549      PMCID: PMC238712          DOI: 10.1128/aem.50.5.1132-1136.1985

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  10 in total

1.  The growth of micro-organisms in relation to their energy supply.

Authors:  T BAUCHOP; S R ELSDEN
Journal:  J Gen Microbiol       Date:  1960-12

2.  Some considerations on the energetics of bacterial growth.

Authors:  J C SENEZ
Journal:  Bacteriol Rev       Date:  1962-06

3.  Growth of bacteria in inorganic medium at different levels of airborne organic substances.

Authors:  A Geller
Journal:  Appl Environ Microbiol       Date:  1983-12       Impact factor: 4.792

4.  Assessing biomass and production of bacteria in eutrophic lake mendota, wisconsin.

Authors:  C Pedrós-Alió; T D Brock
Journal:  Appl Environ Microbiol       Date:  1982-07       Impact factor: 4.792

5.  Kinetics and extent of mineralization of organic chemicals at trace levels in freshwater and sewage.

Authors:  R V Subba-Rao; H E Rubin; M Alexander
Journal:  Appl Environ Microbiol       Date:  1982-05       Impact factor: 4.792

Review 6.  Utilization of energy for growth and maintenance in continuous and batch cultures of microorganisms. A reevaluation of the method for the determination of ATP production by measuring molar growth yields.

Authors:  A H Stouthamer; C Bettenhaussen
Journal:  Biochim Biophys Acta       Date:  1973-02-12

7.  The maintenance energy of bacteria in growing cultures.

Authors:  S J Pirt
Journal:  Proc R Soc Lond B Biol Sci       Date:  1965-10-12

8.  Effect of dissolved oxygen on growth yield and aldolase activity in chemostat culture of Azotobacter vinelandii.

Authors:  S Nagai; Y Nishizawa; M Onodera; S Aiba
Journal:  J Gen Microbiol       Date:  1971-05

Review 9.  Energy yields and growth of heterotrophs.

Authors:  W J Payne
Journal:  Annu Rev Microbiol       Date:  1970       Impact factor: 15.500

10.  Models for mineralization kinetics with the variables of substrate concentration and population density.

Authors:  S Simkins; M Alexander
Journal:  Appl Environ Microbiol       Date:  1984-06       Impact factor: 4.792

  10 in total
  5 in total

1.  Estimation of the yield coefficient of Pseudomonas sp. strain DP-4 with a low substrate (2,4-dichlorophenol [DCP]) concentration in a mineral medium from which uncharacterized organic compounds were eliminated by a non-DCP-degrading organism.

Authors:  M Tarao; M Seto
Journal:  Appl Environ Microbiol       Date:  2000-02       Impact factor: 4.792

2.  Kinetics and yields of pesticide biodegradation at low substrate concentrations and under conditions restricting assimilable organic carbon.

Authors:  Damian E Helbling; Frederik Hammes; Thomas Egli; Hans-Peter E Kohler
Journal:  Appl Environ Microbiol       Date:  2013-12-06       Impact factor: 4.792

3.  Toluene induction and uptake kinetics and their inclusion in the specific-affinity relationship for describing rates of hydrocarbon metabolism.

Authors:  B R Robertson; D K Button
Journal:  Appl Environ Microbiol       Date:  1987-09       Impact factor: 4.792

4.  Investment in secreted enzymes during nutrient-limited growth is utility dependent.

Authors:  Brent Cezairliyan; Frederick M Ausubel
Journal:  Proc Natl Acad Sci U S A       Date:  2017-08-28       Impact factor: 11.205

5.  Deep reinforcement learning for the control of microbial co-cultures in bioreactors.

Authors:  Neythen J Treloar; Alex J H Fedorec; Brian Ingalls; Chris P Barnes
Journal:  PLoS Comput Biol       Date:  2020-04-10       Impact factor: 4.475

  5 in total

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