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Author
Fullola Company, Marc
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Abstract
Single cell analysis methods including microcopy, flow cytometry, and single cell omics are transforming biomedical research by providing insights into the identity and phenotypic properties of individual cells. While already highly valuable by themselves, these technologies could be even more powerful when synergized. To address how genetic variation functions both in health and disease, we developed a single-cell Whole Genome Sequencing (scWGS) strategy for novel system Interconnecting Robotic Imaging and Sequencing (IRIS), which has been designed to couple droplet-based molecular profiling using microfluidics with a machine-vision system allowing for cell detection and deterministic encapsulation. Leveraging high-resolution imaging and deterministic encapsulation, IRIS has the potential to provide an in-depth assessment of molecular cellular phenotypes, enabling us to identify driving forces of disorders including cancer.
In this study, we designed and optimized a hyperactive transposase-based biochemistry process to obtain genomic DNA libraries ready to sequence from single cells. The process includes an optimal cell lysis solution comprised of 1% Triton X-100, 0.5% Digitonin and 60 U/mL of thermolabile Proteinase K, and an optimal tagmentation time of 6 min. The droplet-based scWGS libraries provided by IRIS are highly specific, underscored by species identification and separation as obtained from a species mixing experiment. Quality control assessment demonstrated high purity reads, reaching coverages of 0.1x with 10 M reads per cell, low duplication rate and a proportional feature count.
Moreover, we complemented the study by processing patient-derived acute myeloid leukemic cells. The scWGS strategy enabled not only species identification but also to explore the heterogeneity of genomic aberrations on a per cell basis.
We next aim to integrate the fluidics with high-resolution camera, to couple, for the first time, the molecular profile and high-resolution image on a per cell basis. The direct multi-modal coupling would allow us to decipher characteristic cell features from flow-image data that rely on, for example, genomic aberrations such as copy number variations and single-nucleotide polymorphisms. In the future, we then envision to utilize the IRIS system as a unique clinical diagnostic tool.
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