A tool for selective inline quantification of co‐eluting proteins in chromatography using spectral analysis and partial least squares regression

Abstract

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities.

Integrated development of up- and downstream processes supported by the Cherry-Tag™ for real-time tracking of stability and solubility of proteins

“…Most other proteins, however, are hard to distinguish spectrometrically. Few setups were reported for on-line analytics by multivariate data analysis of protein spectra (Brestrich et al, 2014;Dismer et al, 2013). However, quantitative protein analysis requires calibration experiments and a secondary analysis for the determination of single protein titers.…”

Real‐time monitoring and control of the load phase of a protein A capture step

“…The communication between Unicorn and Chromeleon was implemented analogous to the protocol published in (Brestrich et al, ). Shortly, Unicorn triggers the DAD data acquisition by sending a digital signal to a Matlab script (MathWorks, Natick, MA), which communicates with Chromeleon via a Visual Basics for Application Macro (Microsoft, Redmond, WA).…”

“…Another recently published UV/Vis‐based method for monitoring and control in protein chromatography applies UV/Vis absorption spectra instead of single wavelength measurements (Brestrich et al, , ). Different protein species exhibit distinct variations in their UV absorption spectra.…”

Downstream process development strategies for effective bioprocesses: Trends, progress, and combinatorial approaches

“… used near‐infrared spectral data for investigating complex feedstocks from an antibiotic production process. Deconvolution of protein spectra in the mid‐UV region was shown to be highly useful in determining protein concentrations from multi‐component mixtures . Brestrich et al.…”