Sensor-integrated proteome on chip (SPOC) is the world’s first highly multiplexed kinetic proteomic biosensor. Our unique cell-free production combined with simultaneous capture-purification onto biosensors enables up to 1000 unique proteins per chip, reducing costs by 10x from traditional recombinant protein workflows. Using real-time SPR screening, we offer qualitative, quantitative, and kinetic data for thousands of proteins simultaneously to support drug discovery, biomarker discovery, vaccine development, plasma proteomics, and diagnostics.

Cell-free protein synthesis (CFPS) systems are versatile and can facilitate swift turnaround in design, production, and characterization of antibodies. We use CFPS combined with microfluidic systems for producing computationally designed proteins and affinity reagents for validating specific protein and peptide interactions without any purification. This approach utilizes microfluidics combined with fluorescent correlation spectroscopy, for screening interaction kinetics in real-time. We will present data for generating antibodies as well as porin studies, calcium channels, and other receptors of interest.

The production of antibodies is a time-consuming process. Cell-free protein synthesis (CFPS) offers a faster solution for protein expression, therefore its applicability with antibodies and antibody fragments was investigated. In the present study we focused on the expression of functional single-chain antibody fragments, and how the method could be used in a high-throughput assay format. Here we report on different CFPS methods and their applicability in downstream assays.

Cell-surface receptors pose challenges in expression and purification due to low levels, misfolding, and instability. We introduce a high-throughput ELISA fluorescence approach to rapidly assess multiple recombinant constructs. Utilizing small-scale expression, enzymatic biotinylation, and C-terminal His-tag capture, this approach efficiently prioritizes constructs for large-scale production. Testing truncation constructs across various protein families demonstrated its effectiveness, significantly saving time in identifying optimal candidates for downstream applications.

We introduce a systems engineering approach to protein expression in E. coli, leveraging standard two-stage expression bioprocesses across various scales, from microtiter plates to instrumented bioreactors. This approach facilitates the engineering of strains that operate beyond traditional growth-associated constraints, allowing for the application of advanced tools such as dynamic control over host proteins. We have used this to engineer novel E. coli strains that enhance the production of difficult-to-express proteins and genetically program downstream purification steps, dramatically lowering production costs.

The talk will focus on advances in optimizing small-scale, high-throughput protein production in an academic setting in the Institute of Protein Design (IPD) at the University of Washington. It will highlight a versatile approach that accommodates varying levels of automation, ensuring compatibility with available resources as well as recent work maturing and standardizing the method across different labs and buildings within the IPD.

The mammalian secretory pathway involves the coordinated function of >1000 proteins to synthesize, fold, modify and traffick more than a 1/3 of the protein-coding genome. While we harness this system for producing a vast array of native and heterologous proteins, it remains unclear why some proteins express well and others do not. We have developed large computational models of the secretory pathway, deployed omics and genome editing tools to probe and modify the system, and studied the expression of more than 1000 different secreted proteins in CHO cells. Here we will describe how we use these technologies to better understand protein secretion and enhance recombinant protein expression.

Biological systems can be programmed by modifying protein structure through amino acid sequence changes. Models, both proprietary and open source, can predict sequence changes to enhance biological outcomes. However, synthesizing both natural and model-generated sequences is still a challenge. A high-throughput combinatorial screening platform to assess translation followed by a production platform to purify proteins will generate the millions of data points needed to predict manufacturability across diverse protein classes.