Improving protein yield from mammalian cells by manipulation of stress response pathways

Monoclonal antibodies are a class of therapeutic that is an expanding area of the lucrative biopharmaceutical industry. These complex proteins are predominantly produced from large cultures of mammalian cells; the industry standard cell line being Chinese Hamster Ovary (CHO) cells. A number of optimisation strategies have led to antibody titres from CHO cells increasing by a hundred-fold, and it has been proposed that a further bottleneck in biosynthesis is in protein folding and assembly within the secretory pathway. To alleviate this bottleneck, a CHO-derived host cell line was generated by researchers at the pharmaceutical company UCB that stably overexpressed two critical genes: XBP1, a transcription factor capable of expanding the endoplasmic reticulum and upregulating protein chaperones; and Ero1α, an oxidase that replenishes the machinery of disulphide bond formation. This host cell line, named CHO-S XE, was confirmed to have a high yield of secreted antibody. The work presented in this thesis further characterises CHO-S XE, with the aim of using the information gained to lead the generation of novel host cell lines with more optimal characteristics than CHO-S XE. In addition to antibodies, it was found that CHO-S XE had improved production of two other secreted proteins: one with a simple tertiary structure and one complex multi-domain protein; and higher levels of a number of endogenous protein chaperones. As a more controlled system of gene expression to unravel the specific roles of XBP1 and Ero1α in the secretory properties of CHO-S XE, CHO cells with inducible overexpression of XBP1, Ero1α, or a third gene involved in the Unfolded Protein Response, GADD34, were generated. From these cell lines, it was shown that more antibody was secreted by cells with induced overexpression of XBP1; however, Ero1α and GADD34 overexpression did not improve antibody yield. Further investigation revealed that endogenous XBP1 splicing was downregulated in the presence of an abundance of the active form of XBP1. This result indicated a novel aspect of the regulation of the activity of IRE1, the stress-induced endoribonuclease responsible for XBP1 splicing. Overall, the work described in this thesis confirms that the overexpression of XBP1 has an enhancing effect on the secretory properties of CHO cells; information which could contribute to the development of host cells with a greater capacity for antibody production.

Integrated visual perception architecture for robotic clothes perception and manipulation

This thesis proposes a generic visual perception architecture for robotic clothes perception and manipulation. This proposed architecture is fully integrated with a stereo vision system and a dual-arm robot and is able to perform a number of autonomous laundering tasks. Clothes perception and manipulation is a novel research topic in robotics and has experienced rapid development in recent years. Compared to the task of perceiving and manipulating rigid objects, clothes perception and manipulation poses a greater challenge. This can be attributed to two reasons: firstly, deformable clothing requires precise (high-acuity) visual perception and dexterous manipulation; secondly, as clothing approximates a non-rigid 2-manifold in 3-space, that can adopt a quasi-infinite configuration space, the potential variability in the appearance of clothing items makes them difficult to understand, identify uniquely, and interact with by machine. From an applications perspective, and as part of EU CloPeMa project, the integrated visual perception architecture refines a pre-existing clothing manipulation pipeline by completing pre-wash clothes (category) sorting (using single-shot or interactive perception for garment categorisation and manipulation) and post-wash dual-arm flattening. To the best of the author’s knowledge, as investigated in this thesis, the autonomous clothing perception and manipulation solutions presented here were first proposed and reported by the author. All of the reported robot demonstrations in this work follow a perception-manipulation method- ology where visual and tactile feedback (in the form of surface wrinkledness captured by the high accuracy depth sensor i.e. CloPeMa stereo head or the predictive confidence modelled by Gaussian Processing) serve as the halting criteria in the flattening and sorting tasks, respectively. From scientific perspective, the proposed visual perception architecture addresses the above challenges by parsing and grouping 3D clothing configurations hierarchically from low-level curvatures, through mid-level surface shape representations (providing topological descriptions and 3D texture representations), to high-level semantic structures and statistical descriptions. A range of visual features such as Shape Index, Surface Topologies Analysis and Local Binary Patterns have been adapted within this work to parse clothing surfaces and textures and several novel features have been devised, including B-Spline Patches with Locality-Constrained Linear coding, and Topology Spatial Distance to describe and quantify generic landmarks (wrinkles and folds). The essence of this proposed architecture comprises 3D generic surface parsing and interpretation, which is critical to underpinning a number of laundering tasks and has the potential to be extended to other rigid and non-rigid object perception and manipulation tasks. The experimental results presented in this thesis demonstrate that: firstly, the proposed grasp- ing approach achieves on-average 84.7% accuracy; secondly, the proposed flattening approach is able to flatten towels, t-shirts and pants (shorts) within 9 iterations on-average; thirdly, the proposed clothes recognition pipeline can recognise clothes categories from highly wrinkled configurations and advances the state-of-the-art by 36% in terms of classification accuracy, achieving an 83.2% true-positive classification rate when discriminating between five categories of clothes; finally the Gaussian Process based interactive perception approach exhibits a substantial improvement over single-shot perception. Accordingly, this thesis has advanced the state-of-the-art of robot clothes perception and manipulation.