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dc.contributor.authorRobinson, J. A.
dc.contributor.authorCharacklis, William G.
dc.date.accessioned2017-07-31T19:49:06Z
dc.date.available2017-07-31T19:49:06Z
dc.date.issued1984-06
dc.identifier.citationRobinson JA, Characklis WG, "Simultaneous estimation of Vmax, Km, and the rate of endogenous substrate production (R) from substrate depletion data," Microb Ecol 1984 10(2):165-178en_US
dc.identifier.issn0043-1355
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/13445
dc.description.abstractThe nonlinear and 3 linearized forms of the integrated Michaelis-Menten equation were evaluated for their ability to provide reliable estimates of uptake kinetic parameters, when the initial substrate concentration (So) is not error-free. Of the 3 linearized forms, the one where t/(So - S) is regressed against ln(S0/S)/(So - S) gave estimates of Vmax and Km closest to the true population means of these parameters. Further, this linearization was the least sensitive of the 3 to errors (±1%) in So. Our results illustrate the danger of relying on r2 values for choosing among the 3 linearized forms of the integrated Michaelis-Menten equation. Nonlinear regression analysis of progress curve data, when So is not free of error, was superior to even the best of the 3 linearized forms. The integrated Michaelis-Menten equation should not be used to estimate Vmax and Km when substrafe production occurs concomitant with consumption of added substrate. We propose the use of a new equation for estimation of these parameters along with a parameter describing endogenous substrate production (R) for kinetic studies done with samples from natural habitats, in which the substrate of interest is an intermediate. The application of this new equation was illustrated for both simulated data and previously obtained H2 depletion data. The only means by which Vmax, Km, and R may be evaluated from progress curve data using this new equation is via nonlinear regression, since a linearized form of this equation could not be derived. Mathematical components of computer programs written for fitting data to either of the above nonlinear models using nonlinear least squares analysis are presenteden_US
dc.titleSimultaneous estimation of Vmax, Km, and the rate of endogenous substrate production (R) from substrate depletion dataen_US
dc.typeArticleen_US
mus.citation.extentfirstpage165en_US
mus.citation.extentlastpage178en_US
mus.citation.issue2en_US
mus.citation.journaltitleWater Researchen_US
mus.citation.volume10en_US
mus.identifier.categoryEngineering & Computer Scienceen_US
mus.identifier.doi10.1007/bf02011423en_US
mus.relation.collegeCollege of Engineeringen_US
mus.relation.departmentCenter for Biofilm Engineering.en_US
mus.relation.departmentChemical & Biological Engineering.en_US
mus.relation.departmentChemical Engineering.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.relation.researchgroupCenter for Biofilm Engineering.en_US
mus.data.thumbpage6en_US


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