Purification of plasmid DNA with polymer-salt aqueous two-phase system: Optimization using response surface methodology

Abstract

An experimental design was used to optimize plasmid purification from an alkaline lysate of Escherichia coli cells using PEG-sodium citrate aqueous two-phase systems (ATPS), and to evaluate the influence of pH, PEG molecular weight, tie line length, phase volume ratio, and lysate load. To build the mathematical model and minimize the number of experiments for the design parameters, response surface methodology (RMS) with an orthogonal rotatable central composite design was defined based on the conditions found for the highest purification by preliminary tests. The adequacy of the calculated models for the plasmid recovery and remaining RNA were confirmed by means of variance analysis and additional experiments. Analysis of contours of constant response as a function of pH, PEG molecular weight, tie line length, and cell lysate load for three different phase volume ratios revealed different effects of these five factors on the studied parameters. Plasmid recovery of 99% was predicted for a system with PEG 400, pH 6.9, tie line length of 38.7%, phase volume ratio of 1.5, and lysate load of 10% (v/v). Under these conditions the predicted RNA removal was 68%.

Optimization of PEG–salt aqueous two-phase systems by design of experiments

“…These replicated experiments are called center-points because they are performed in the center of the experimental region located between the high and low levels, thus increasing the factor levels, at which the center level is denoted by 0 in a design matrix [13]. Hence, center-points characterize experimental runs at the center level of each factor range [6,19]. Furthermore, the pure error of the replicated center-point experiments is used to estimate the statistical significance of the calculated values of each factor, and thus evaluate the background variability of the process [6,19,20].…”

“…In recent years, the use of RSM has gained importance in the evaluation of biotechnological processes and has become an innovative method in several research studies [17,28,29]. Furthermore, this approach is used as an effective statistical technique in order to determine the optimal operating conditions and significant independent factors or their interactions with the dependent output responses in multivariate complex systems, such as PEG-salt ATPS, thus enhancing the output responses for the optimization of these systems considering the partitioning of biomolecules, and consequently designing complex processes occurring in ATPS [2,11,17,19,[30][31][32]. Moreover, RSM is a useful and promising tool for establishing a statistical model to predict output responses or partitioning target parameters of ATPS by a correlation of the measured output response factors to the input factors, thus modelling a process, such as the separation and purification of biomolecules in ATPS [2,[32][33][34][35][36].…”

“…Furthermore, it is composed of the following three building blocks according to [9,13,19]: 2) Replicated center-points…”

“…The CCC design circumscribes experimental runs by star/axial points located at a level outside of the low and high factor settings of the composite design, thus facilitating curvature modelling and investigating each factor at five levels [6,11,13,19,30]. For instance, the CCC design for three factors (e.g., x 1 , x 2 , and x 3 ) is containing eight corner experiments, six axial experiments and, at least, three replicated center-points (Fig.…”

Utilização de sistemas poliméricos de duas fases aquosas (SPDFA) compostos por polietileno glicol/ácido poliacrílico (PEG/APA) para extração de ácido clavulânico

“…Rahimpour et al, (2006) presented two different aqueous two-phase systems to be optimal for plasmid yield recovery (100% pDNA and 32% RNA) and one for RNA depletion (78% pDNA and 23% RNA), both using PEG 400-citrate ATPS systems. However, a better separation of pDNA and RNA (83%) was achieved by Wiendahl et al, (2012) using PEG-PO 4 system and genetic algorithms.…”