BackgroundThe bacterium E. coli is a major host for recombinant protein production of non-glycosylated products. Depending on the expression strategy, the recombinant protein can be located intracellularly. In many cases the formation of inclusion bodies (IBs), protein aggregates inside of the cytoplasm of the cell, is favored in order to achieve high productivities and to cope with toxic products. However, subsequent downstream processing, including homogenization of the cells, centrifugation or solubilization of the IBs, is prone to variable process performance or can be characterized by low extraction yields as published elsewhere. It is hypothesized that variations in IB quality attributes (QA) are responsible for those effects and that such attributes can be controlled by upstream process conditions. This contribution is aimed at analyzing how standard process parameters, such as pH and temperature (T) as well as different controlled levels of physiological parameters, such as specific substrate uptake rates, can vary IB quality attributes.ResultsClassical process parameters like pH and T influence the expression of analyzed IB. The effect on the three QAs titer, size and purity could be successfully revealed. The developed data driven model showed that low temperatures and low pH are favorable for the expression of the two tested industrially relevant proteins. Based on this knowledge, physiological control using specific substrate feeding rate (of glucose) qs,Glu is altered and the impact is tested for one protein.ConclusionsTime dependent monitoring of IB QA—titer, purity, IB bead size—showed a dependence on classical process parameters pH and temperature. These findings are confirmed using a second industrially relevant strain. Optimized process conditions for pH and temperature were used to determine dependence on the physiological parameters, the specific substrate uptake rate (qs,Glu). Higher qs,Glu were shown to have a strong influence on the analyzed IB QAs and drastically increase the titer and purity in early time stages. We therefore present a novel approach to modulate—time dependently—quality attributes in upstream processing to enable robust downstream processing.Electronic supplementary materialThe online version of this article (10.1186/s12934-018-0997-5) contains supplementary material, which is available to authorized users.