Cargando…

Optimizing the Substrate Uptake Rate of Solute Carriers

The diversity in solute carriers arose from evolutionary pressure. Here, we surmised that the adaptive search for optimizing the rate of substrate translocation was also shaped by the ambient extracellular and intracellular concentrations of substrate and co-substrate(s). We explored possible soluti...

Descripción completa

Detalles Bibliográficos
Autores principales: Schicker, Klaus, Farr, Clemens V., Boytsov, Danila, Freissmuth, Michael, Sandtner, Walter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850955/
https://www.ncbi.nlm.nih.gov/pubmed/35185619
http://dx.doi.org/10.3389/fphys.2022.817886
_version_ 1784652720917970944
author Schicker, Klaus
Farr, Clemens V.
Boytsov, Danila
Freissmuth, Michael
Sandtner, Walter
author_facet Schicker, Klaus
Farr, Clemens V.
Boytsov, Danila
Freissmuth, Michael
Sandtner, Walter
author_sort Schicker, Klaus
collection PubMed
description The diversity in solute carriers arose from evolutionary pressure. Here, we surmised that the adaptive search for optimizing the rate of substrate translocation was also shaped by the ambient extracellular and intracellular concentrations of substrate and co-substrate(s). We explored possible solutions by employing kinetic models, which were based on analytical expressions of the substrate uptake rate, that is, as a function of the microscopic rate constants used to parameterize the transport cycle. We obtained the defining terms for five reaction schemes with identical transport stoichiometry (i.e., Na(+): substrate = 2:1). We then utilized an optimization algorithm to find the set of numeric values for the microscopic rate constants, which provided the largest value for the substrate uptake rate: The same optimized rate was achieved by different sets of numerical values for the microscopic rate constants. An in-depth analysis of these sets provided the following insights: (i) In the presence of a low extracellular substrate concentration, a transporter can only cycle at a high rate, if it has low values for both, the Michaelis–Menten constant (K(M)) for substrate and the maximal substrate uptake rate (V(max)). (ii) The opposite is true for a transporter operating at high extracellular substrate concentrations. (iii) Random order of substrate and co-substrate binding is superior to sequential order, if a transporter is to maintain a high rate of substrate uptake in the presence of accumulating intracellular substrate. Our kinetic models provide a framework to understand how and why the transport cycles of closely related transporters differ.
format Online
Article
Text
id pubmed-8850955
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-88509552022-02-18 Optimizing the Substrate Uptake Rate of Solute Carriers Schicker, Klaus Farr, Clemens V. Boytsov, Danila Freissmuth, Michael Sandtner, Walter Front Physiol Physiology The diversity in solute carriers arose from evolutionary pressure. Here, we surmised that the adaptive search for optimizing the rate of substrate translocation was also shaped by the ambient extracellular and intracellular concentrations of substrate and co-substrate(s). We explored possible solutions by employing kinetic models, which were based on analytical expressions of the substrate uptake rate, that is, as a function of the microscopic rate constants used to parameterize the transport cycle. We obtained the defining terms for five reaction schemes with identical transport stoichiometry (i.e., Na(+): substrate = 2:1). We then utilized an optimization algorithm to find the set of numeric values for the microscopic rate constants, which provided the largest value for the substrate uptake rate: The same optimized rate was achieved by different sets of numerical values for the microscopic rate constants. An in-depth analysis of these sets provided the following insights: (i) In the presence of a low extracellular substrate concentration, a transporter can only cycle at a high rate, if it has low values for both, the Michaelis–Menten constant (K(M)) for substrate and the maximal substrate uptake rate (V(max)). (ii) The opposite is true for a transporter operating at high extracellular substrate concentrations. (iii) Random order of substrate and co-substrate binding is superior to sequential order, if a transporter is to maintain a high rate of substrate uptake in the presence of accumulating intracellular substrate. Our kinetic models provide a framework to understand how and why the transport cycles of closely related transporters differ. Frontiers Media S.A. 2022-02-03 /pmc/articles/PMC8850955/ /pubmed/35185619 http://dx.doi.org/10.3389/fphys.2022.817886 Text en Copyright © 2022 Schicker, Farr, Boytsov, Freissmuth and Sandtner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Schicker, Klaus
Farr, Clemens V.
Boytsov, Danila
Freissmuth, Michael
Sandtner, Walter
Optimizing the Substrate Uptake Rate of Solute Carriers
title Optimizing the Substrate Uptake Rate of Solute Carriers
title_full Optimizing the Substrate Uptake Rate of Solute Carriers
title_fullStr Optimizing the Substrate Uptake Rate of Solute Carriers
title_full_unstemmed Optimizing the Substrate Uptake Rate of Solute Carriers
title_short Optimizing the Substrate Uptake Rate of Solute Carriers
title_sort optimizing the substrate uptake rate of solute carriers
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850955/
https://www.ncbi.nlm.nih.gov/pubmed/35185619
http://dx.doi.org/10.3389/fphys.2022.817886
work_keys_str_mv AT schickerklaus optimizingthesubstrateuptakerateofsolutecarriers
AT farrclemensv optimizingthesubstrateuptakerateofsolutecarriers
AT boytsovdanila optimizingthesubstrateuptakerateofsolutecarriers
AT freissmuthmichael optimizingthesubstrateuptakerateofsolutecarriers
AT sandtnerwalter optimizingthesubstrateuptakerateofsolutecarriers