Open AccessFlocculation increases the efficacy of depth filtration during the downstream processing of recombinant pharmaceutical proteins produced in tobacco
Author(s) -
Buyel Johannes F.,
Fischer Rainer
Publication year - 2014
Publication title -
plant biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.525
H-Index - 115
eISSN - 1467-7652
pISSN - 1467-7644
DOI - 10.1111/pbi.12132
Subject(s) - flocculation , turbidity , downstream processing , filtration (mathematics) , filter (signal processing) , chromatography , centrifugation , shear rate , cross flow filtration , sedimentation , chemical engineering , pulp and paper industry , materials science , biology , chemistry , composite material , rheology , membrane , sediment , ecology , statistics , mathematics , computer science , engineering , computer vision , paleontology , genetics
Summary Flocculation is a cost‐effective method that is used to improve the efficiency of clarification by causing dispersed particles to clump together, allowing their removal by sedimentation, centrifugation or filtration. The efficacy of flocculation for any given process depends on the nature and concentration of the particulates in the feed stream, the concentration, charge density and length of the flocculant polymer, the shear rate, the properties of the feed stream (e.g. pH and ionic strength) and the properties of the target products. We tested a range of flocculants and process conditions using a design of experiments approach to identify the most suitable polymers for the clarification step during the production of a HIV ‐neutralizing monoclonal antibody (2G12) and a fluorescent marker protein (DsRed) expressed in transgenic tobacco leaves. Among the 23 different flocculants we tested, the greatest reduction in turbidity was achieved with Polymin P, a branched, cationic polyethylenimine with a charge density of 13.0 meq/g. This flocculant reduced turbidity by more than 90% under a wide range of process conditions. We developed a model that predicted its performance under different process conditions, and this enabled us to increase the depth filter capacity three–sevenfold depending on the process scale, depth filter type and plant species. The costs of filter consumables were reduced by more than 50% compared with a process without flocculant, and there was no loss of recovery for either 2G12 or DsRed.