Dataset Information

Kinetic titration series with biolayer interferometry.

ABSTRACT: Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1-42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations.

SUBMITTER: Frenzel D

PROVIDER: S-EPMC4167697 | biostudies-other | 2014

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Kinetic titration series with biolayer interferometry.

Frenzel Daniel D Willbold Dieter D

PloS one 20140917 9

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1-42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential i ...[more]

PMID: 25229647

Similar Datasets

Project description:Stabilizing the folded state of metastable and/or aggregation-prone proteins through exogenous ligand binding is an appealing strategy for decreasing disease pathologies caused by protein folding defects or deleterious kinetic transitions. Current methods of examining binding of a ligand to these marginally stable native states are limited because protein aggregation typically interferes with analysis. Here, we describe a rapid method for assessing the kinetic stability of folded proteins and monitoring the effects of ligand stabilization for both intrinsically stable proteins (monomers, oligomers, and multidomain proteins) and metastable proteins (e.g., low Tm) that uses a new GroEL chaperonin-based biolayer interferometry (BLI) denaturant pulse platform. A kinetically controlled denaturation isotherm is generated by exposing a target protein, immobilized on a BLI biosensor, to increasing denaturant concentrations (urea or GuHCl) in a pulsatile manner to induce partial or complete unfolding of the attached protein population. Following the rapid removal of the denaturant, the extent of hydrophobic unfolded/partially folded species that remains is detected by an increased level of GroEL binding. Because this kinetic denaturant pulse is brief, the amplitude of binding of GroEL to the immobilized protein depends on the duration of the exposure to the denaturant, the concentration of the denaturant, wash times, and the underlying protein unfolding-refolding kinetics; fixing all other parameters and plotting the GroEL binding amplitude versus denaturant pulse concentration result in a kinetically controlled denaturation isotherm. When folding osmolytes or stabilizing ligands are added to the immobilized target proteins before and during the denaturant pulse, the diminished population of unfolded/partially folded protein manifests as a decreased level of GroEL binding and/or a marked shift in these kinetically controlled denaturation profiles to higher denaturant concentrations. This particular platform approach can be used to identify small molecules and/or solution conditions that can stabilize or destabilize thermally stable proteins, multidomain proteins, oligomeric proteins, and, most importantly, aggregation-prone metastable proteins.

Project description:MotivationThe MS2-MCP (MS2 coat protein) live imaging system allows for visualization of transcription dynamics through the introduction of hairpin stem-loop sequences into a gene. A fluorescent signal at the site of nascent transcription in the nucleus quantifies mRNA production. Computational modelling can be used to infer the promoter states along with the kinetic parameters governing transcription, such as promoter switching frequency and polymerase loading rate. However, modelling of the fluorescent trace presents a challenge due its persistence; the observed fluorescence at a given time point depends on both current and previous promoter states. A compound state Hidden Markov Model (cpHMM) was recently introduced to allow inference of promoter activity from MS2-MCP data. However, the computational time for inference scales exponentially with gene length and the cpHMM is therefore not currently practical for application to many eukaryotic genes.ResultsWe present a scalable implementation of the cpHMM for fast inference of promoter activity and transcriptional kinetic parameters. This new method can model genes of arbitrary length through the use of a time-adaptive truncated compound state space. The truncated state space provides a good approximation to the full state space by retaining the most likely set of states at each time during the forward pass of the algorithm. Testing on MS2-MCP fluorescent data collected from early Drosophila melanogaster embryos indicates that the method provides accurate inference of kinetic parameters within a computationally feasible timeframe. The inferred promoter traces generated by the model can also be used to infer single-cell transcriptional parameters.Availability and implementationPython implementation is available at https://github.com/ManchesterBioinference/burstInfer, along with code to reproduce the examples presented here.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Kinetic titration series with biolayer interferometry.

Publications

Kinetic titration series with biolayer interferometry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets