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High-throughput discovery of combination therapies and engineering of CRISPR/therapeutic proteins

School of Biomedical Sciences

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Dr A Wong Applications accepted all year round Funded PhD Project (Students Worldwide)

About the Project

Our lab is interested in developing and applying state-of-the-art combinatorial genetics technologies to decipher the mechanisms behind complex diseases, including cancers and neurodegenerative disorders, and discover novel combination therapies. We are also interested in utilizing multiplexed screening pla to engineer genome-editing and therapeutic proteins in a high-throughput manner. Currently, the lab is recruiting PhD students to work on two projects:
Project 1
Many disease pathogeneses are contributed by multiple factors, involving a complex set of genes and pathways. Therefore, we believe that drug combination remedies can bring a larger therapeutic impact on patients. However, the conventional approaches for drug combination screens are not only expensive but also time-consuming; still, they only allow the testing of a limited number of drug combinations. The CombiGEM-CRISPR platform couples the versatile combinatorial genetics en masse technology and the programmable CRISPR-Cas9 system, and this allows high-throughput screening of genetic combinations mimicking the effect brought by drug combinations (Wong et al., Nature Biotechnology 2015; Wong et al., PNAS 2016).

This platform can rapidly assemble multiplex barcoded combinatorial genetic libraries, where each combination can be tracked based on their barcodes via high-throughput sequencing. To do drug combination screens, we design the guide RNAs (gRNA) targeting the drug-targeting genes and assigned a unique barcode to each of them, then we build a barcoded gRNA library and identify the combined gRNA knockouts that give us the desired phenotype by doing a Next-Generation Sequencing (NGS) of the barcodes. Using this approach, our lab has successfully found synergistic drug combinations using the CombiGEM-CRISPR platform on various types of cancers and neurodegenerative diseases and is interested in improving this platform and screening for combination remedies in other complex genetic diseases.
Project 2
Protein engineering often requires changing a combination of amino acid sites chosen based on their structural information to significantly improve the activity of the protein. However, as the number of combinations increases exponentially with each amino acid site included, the protein engineering process can get very labor-intensive. Furthermore, the conventional selection process of protein variants, which requires sequencing each positively selected clone and comparing the selected protein to the wild-type protein, has very limited throughput, and, therefore, hinders us from repeating the selection process in different selection conditions. This leaves us not knowing whether we have selected the best variant in the most optimal selection condition.

Our lab developed the CombiSEAL screening platform (G.C.G. Choi et al., Nature Methods, 2019) to overcome the concerns mentioned above. The CombiSEAL platform modularizes a protein into multiple segments to generate mutant variants, where each of them is identified by a unique barcode. These variants are then seamlessly ligated into the protein-coding sequence while the corresponding barcodes are concatenated after the coding sequence. By using NGS to sequence all these barcodes, we can get a quantitative readout for each variant; moreover, we can repeat the selection process of this barcoded library in multiple conditions until we find the most optimal condition.

The lab successfully identified multiple high-fidelity spCas9 variants by using the CombiSEAL platform (G.C.G. Choi et al., Nature Methods, 2019) and is interested in expanding the usage of the platform in engineering other gene-editing and therapeutic proteins.

The PhD projects provide vigorous training in high-throughput molecular biology, CRISPR-based genome editing, and NGS-based library screening and data analysis techniques. Interested candidates should email Dr. Alan Wong ([Email Address Removed]).

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Faculty information, funding opportunities and application deadlines:


1. Choi, C.G.G., Zhou, P., Yuen, T.L.C., Chan, K.C.B., Xu, F., Bao, S., Chu, H.Y., Thean, D., Tan, K., Wong, K.H., Zheng, Z., Wong, S.L.A. Combinatorial mutagenesis en masse optimizes SpCas9's genome-editing activities. Nature Methods 16, 722-730 (2019)

2. Wong, S.L.A., Choi, C.G.G., Lu, T.K. Deciphering combinatorial genetics. Annual Reviews of Genetics 50, 515-538 (2016).

3. Wong, S.L.A.*, Choi, C.G.G.*, Cui, C.H.*, Pregernig, G., Milani, P., Adam, M., Perli, S.D., Kazer, S.W., Gaillard, A., Hermann, M., Shalek, A.K., Fraenkel, E., Lu, T.K. Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM. Proceedings of National Academy of Sciences 113(9), 2544-2549 (2016).

4. Wong, S.L.A., Choi, C.G.G., Cheng, A.A., Purcell, O., Lu, T.K. Massively parallel high-order combinatorial genetics in human cells. Nature Biotechnology 33(9), 952-961 (2015).
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