Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reliable Strategy for Analysis of Complex Biosensor Data
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Chemical Sciences (from 2013).ORCID iD: 0000-0003-1819-1709
Show others and affiliations
2018 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 90, no 8, p. 5366-5374Article in journal (Refereed) Published
Abstract [en]

When using biosensors, analyte biomolecules of several different concentrations are percolated over a chip with immobilized ligand molecules that form complexes with analytes. However, in many cases of biological interest, e.g., in antibody interactions, complex formation steady-state is not reached. The data measured are so-called sensorgram, one for each analyte concentration, with total complex concentration vs time. Here we present a new four-step strategy for more reliable processing of this complex kinetic binding data and compare it with the standard global fitting procedure. In our strategy, we first calculate a dissociation graph to reveal if there are any heterogeneous interactions. Thereafter, a new numerical algorithm, AIDA, is used to get the number of different complex formation reactions for each analyte concentration level. This information is then used to estimate the corresponding complex formation rate constants by fitting to the measured sensorgram one by one. Finally, all estimated rate constants are plotted and clustered, where each cluster represents a complex formation. Synthetic and experimental data obtained from three different QCM biosensor experimental systems having fast (close to steady-state), moderate, and slow kinetics (far from steady-state) were evaluated using the four-step strategy and standard global fitting. The new strategy allowed us to more reliably estimate the number of different complex formations, especially for cases of complex and slow dissociation kinetics. Moreover, the new strategy proved to be more robust as it enables one to handle system drift, i.e., data from biosensor chips that deteriorate over time.

Place, publisher, year, edition, pages
American Chemical Society , 2018. Vol. 90, no 8, p. 5366-5374
Keywords [en]
Biosensors, Dissociation, Kinetics, Molecular biology, Analyte concentration, Complex concentration, Complex formation reactions, Dissociation kinetics, Experimental system, Global fitting procedures, Heterogeneous interactions, Numerical algorithms, Rate constants
National Category
Chemical Sciences Organic Chemistry Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kau:diva-67280DOI: 10.1021/acs.analchem.8b00504Scopus ID: 2-s2.0-85045627010OAI: oai:DiVA.org:kau-67280DiVA, id: diva2:1203848
Available from: 2018-05-04 Created: 2018-05-04 Last updated: 2018-07-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Samuelsson, JörgenFornstedt, Torgny

Search in DiVA

By author/editor
Samuelsson, JörgenFornstedt, Torgny
By organisation
Department of Engineering and Chemical Sciences (from 2013)
In the same journal
Analytical Chemistry
Chemical SciencesOrganic ChemistryBiochemistry and Molecular Biology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf