Why did Entelechon decide to add protein quantification to its portfolio? The reason, Giegerich explained, is the mounting competition from Asia for low-cost gene synthesis services. “It’s a second chance to stay on the market,” he said.
As Quantification Methods Grow, Entelechon Develops Service Based on Concatenated Reference Peptides
As absolute quantification methods gain ground in proteomics, Entelechon, a small German company, is developing a protein-quantification service based on a method that uses concatenated reference peptides.
The method, called QconCAT, promises to deliver large numbers of labeled peptide standards at low cost and could also be used for diagnostic applications, according to the company.
“The biggest market may be in diagnostics,” Gerhard Giegerich, Entelechon’s head of protein production, told ProteoMonitor this week.
Entelechon, which spun out from Regensburg University in 1999, provides gene synthesis services and is currently expanding its business into protein expression and quantification. The 15-employee company said this month it received a 3-year, €400,000 ($505,000) grant from the German government to cover half of its expected development cost for QconCAT.
QconCAT, the absolute quantification method Entelechon is about to commercialize, was developed by scientists at the Universities of Liverpool and Manchester and reported a year ago in Nature Methods. Entelechon, based in Regensburg in southern Germany, and the UK researchers have jointly filed a patent application with the European Patent Office entitled “Artificial protein method for an absolute quantification of proteins and uses thereof.”
In their paper, the researchers reported constructing an artificial gene encoding a protein that consists of a string of tryptic peptides, or concatenated peptides, each of which is unique for a different skeletal muscle protein from chicken. After expressing and purifying this so-called QCAT protein from E. coli, they digested the protein with trypsin and analyzed the fragments by mass spectrometry. They also used a metabolically labeled version of the QCAT protein for quantification experiments.
At the time, Entelechon synthesized the QCAT gene for the UK team as a service. Following the project, the two groups decided to commercialize the method together.
According to Giegerich, a major advantage of the QconCAT method is cost: It is less expensive to express a protein containing reference peptides in E. coli than chemically synthesize the same peptides. Also, because the concatamer protein contains the peptides in equimolar amounts, the researchers need to quantify it only once rather than having to quantify every single peptide.
A concatamer protein containing up to 50 reference peptides will typically cost around €20,000, according to Markus Fischer, Entelechon’s managing director. For that price, the customer will receive a purified, isotope-labeled protein, quality-controlled by mass spec after a trypsin digest.
“Most of the price depends on what the customer needs on the protein expression side,” Fischer said, referring to purity. The turnaround time will be eight weeks at first but the company is “hoping to speed up the process,” he said.
In addition, since the concatamer protein is added before the sample is enzymatically digested, the efficiency of the digest would no longer be a concern, according to Christoph Borchers, a professor at the University of North Carolina at Chapel Hill.
“Spiking in an isotopically labeled protein is an elegant way to normalize the difference in the digestion efficiency,” he told ProteoMonitor in an e-mail message. Borchers has developed an affinity-based peptide chip technology that can be used for quantitative proteomics (PM 01/05/06).
Entelechon is already providing custom-built genes encoding concatenated peptide standards as a worldwide service and is currently gearing up its equipment to be able to provide customers with purified QCAT proteins “in the very near future,” according to Giegerich.
Approximately six months from now, the company also hopes to provide a full quantification service that will include mass spec analysis in collaboration with TopLab and OMX, two Munich-based proteomics companies.
According to Giegerich, Entelechon’s main competitor for QconCAT is Sigma-Aldrich’s AQUA peptides, “but they use synthetic peptides” instead of peptides expressed in E. coli, he said. Sigma charges $500 for each labeled custom AQUA peptide, according to the company’s website.
The AQUA method for absolute quantification, commercialized by Sigma in April 2005, was originally developed by Steven Gygi at Harvard (see PM 02/06/2003).
In addition, QconCAT will compete to some extent with Applied Biosystems’ ICAT and iTRAQ reagents, “which might be used with synthetic peptides to get semiquantitative [data],” Giegerich added.
Entelechon sees the most important market for QconCAT in diagnostics, where the method could provide reference standards to measure proteomic biomarkers, as well as in biotechnology for optimizing protein production. In addition, the firm wants to market the service for basic research as well as drug discovery, according to Giegerich.
Near term, Entelechon plans to use the recent government funding for three projects: It aims to develop a number of concatamer proteins that could serve as international standards and plans to work on this with the Human Proteome Organization or other standardization efforts.
“If we have one QconCAT that encompasses a lot of different points in the mass spectra, and we know the amount of peptide, it will be useful to compare different labs and methods, a real quality standard,” said Giegerich.
Secondly, in order to prove that QconCAT can be useful for diagnostics, company researchers want to develop a set of peptide standards to be used as a diagnostic for rheumatology. To that end, they are collaborating with a number of European rheumatology research groups, including one in Regensburg.
Finally, Entelechon is working on a bioinformatics-based method “to streamline the process of designing QconCATs,” Fischer said. “We want to have a prediction method which gives us a fairly accurate prediction of whether a peptide is suitable for MS or not,” he added. At the moment, he said, there is no such tool publicly available.