Chan Zuckerberg Biohub 6 articles published in JoVE Biochemistry "Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome Akul Naik1, Sanjeeva Srivastava1,2, Arun P. Wiita1,3,4 1Department of Laboratory Medicine, University of California, San Francisco, 2Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, 3Deptartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 4Chan Zuckerberg Biohub Here, we describe a proteomics workflow for characterization of the cell surface proteome of various cell types. This workflow includes cell surface protein enrichment, subsequent sample preparation, analysis using an LC-MS/MS platform, and data processing with specialized software. Developmental Biology Antibody Uptake Assay for Tracking Notch/Delta Endocytosis During the Asymmetric Division of Zebrafish Radial Glia Progenitors Xiang Zhao1,2, Su Guo2,3 1Chan Zuckerberg Biohub, 2Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, 3Programs in Human Genetics and Biological Sciences, University of California San Francisco This work develops an antibody uptake assay for imaging intra-lineage Notch/DeltaD signaling in dividing radial glia progenitors of the embryonic zebrafish brain. Biology Particle Templated Emulsification enables Microfluidic-Free Droplet Assays Daniel W. Weisgerber1, Makiko N. Hatori1, Adam R. Abate1,2 1Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, 2Chan Zuckerberg Biohub Water-in-oil droplet assays are useful for analytical chemistry, enzyme evolution, and single cell analysis, but typically require microfluidics to form the droplets. Here, we describe particle templated emulsification, a microfluidic-free approach to perform droplet assays. Bioengineering High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing Jesse Q. Zhang1,2, Kai-Chun Chang1, Leqian Liu1, Zev J. Gartner3,5, Adam R. Abate1,4,5 1Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, 2University of California Berkeley-UCSF Graduate Program in Bioengineering, University of California San Francisco, 3Department of Pharmaceutical Chemistry, University of California San Francisco, 4California Institute for Quantitative Biosciences, University of California San Francisco, 5Chan Zuckerberg Biohub A bottleneck in the ‘design-build-test’ cycle of microbial engineering is the speed at which we can perform functional screens of strains. We describe a high-throughput method for strain screening applied to hundreds to thousands of yeast cells per experiment that utilizes droplet-based RNA sequencing. Genetics Enhanced Genome Editing with Cas9 Ribonucleoprotein in Diverse Cells and Organisms Behnom Farboud*1,2, Erin Jarvis*1, Theodore L. Roth*3,4,5,6, Jiyung Shin*1,3, Jacob E. Corn1,3, Alexander Marson3,5,6,7,8,9, Barbara J. Meyer1,2, Nipam H. Patel1,10, Megan L. Hochstrasser3 1Department of Molecular Cell Biology, University of California, Berkeley, 2Howard Hughes Medical Institute, University of California, Berkeley, 3Innovative Genomics Institute, University of California, Berkeley, 4Biomedical Sciences Graduate Program, University of California, San Francisco, 5Department of Microbiology and Immunology, University of California, San Francisco, 6Diabetes Center, University of California, San Francisco, 7Chan Zuckerberg Biohub, 8Department of Medicine, University of California, San Francisco, 9UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 10Department of Integrative Biology, University of California, Berkeley Utilizing a preassembled Cas9 ribonucleoprotein complex (RNP) is a powerful method for precise, efficient genome editing. Here, we highlight its utility across a broad range of cells and organisms, including primary human cells and both classic and emerging model organisms. Bioengineering An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing Benjamin Demaree1,2, Daniel Weisgerber1, Freeman Lan1,2, Adam R. Abate1,2,3 1Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, 2UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, 3Chan Zuckerberg Biohub Single-cell sequencing reveals genotypic heterogeneity in biological systems, but current technologies lack the throughput necessary for the deep profiling of community composition and function. Here, we describe a microfluidic workflow for sequencing >50,000 single-cell genomes from diverse cell populations.
