Spatial Biology and Genomics Core

Mass cytometry (Helios, a CyTOF System, Fluidigm) combines time-of-flight mass spectrometry with metal-labeling technology to enable break through discovery and comprehensive functional profiling applications. With 135 available detection channels, this technology enables you to fully study the functional complexity of biological systems at the single cell level including phosphoprotein-signaling analysis on subpopulations of cells.

Antibodies List

Helios, a CyTOF System

DVS panel designer web tool

Imaging Mass Cytometry (IMC) on the Hyperion Imaging System uniquely combines a precisely directed laser beam focused at 1 μm to collect biological samples stained with metal-tagged Maxpar® antibodies and directs these tags for analysis with proven CyTOF technology. Bringing together the high-multiplex capabilities of mass cytometry with imaging using metal-tagged antibodies allows simultaneous interrogation of 4 to 37 protein markers in tissues and tumors at subcellular resolution while preserving the information in tissue architecture and cell morphology. Now researchers can detect discrete signals from each ionized metal tag based on differences in mass instead of wavelength at 1 Da resolution, and in contrast to fluorescence results, get uniform staining with minimal background.

The SC2 Core has developed a Human Tumor Microenvironment Panel available for use with the IMC. Using this panel as a backbone, the core is able to customize this panel based on your project’s needs. Our IMC scientists can also assist with designing a whole new targeted panel for your specific project.

Antibodies List

Massively parallel sequencers (NextSeq and MiSeq, Illumina) allow you to analyze single-cell genomics, RNA sequencing, microbiomes (bacterial and fungal), shotgun metagenomics, targeted gene analysis, and microbial whole genomes.

Learn more about MiSeq

Learn more about NextSeq

Single Cell Technology - using the 10X Genomics Chromium System

The compact, sleek Chromium Controller has been designed to rapidly and efficiently automate highly parallel sample partitioning and molecular barcoding. The Chromium Controller allows a user to run any Chromium Solution (see list below of all the Chromium Solutions available from 10X Genomics), spanning from genome to single cell analysis.

The Chromium Single Cell Gene Expression Solution provides high-throughput, single cell expression measurements that enable discovery of gene expression dynamics and molecular profiling of individual cell types.

The Chromium Single Cell Immune Profiling Solution is a comprehensive approach to simultaneously examine the cellular context of the adaptive immune response and immune repertoires of hundreds to tens of thousands of T and B cells in human or mouse on a cell-by-cell basis.

The Chromium Single Cell CNV Solution provides a comprehensive, scalable solution for revealing genome heterogeneity and understanding clonal evolution. Study disease pathogenesis or characterize neuronal mosaicism at the single cell level.

The Chromium Single Cell ATAC (Assay for Transposase Accessible Chromatin) Solution accelerates the understanding of the regulatory landscape of the genome, thereby providing insights into cell variability. The chromatin profiling of tens of thousands of single cells in parallel allows researchers to see how chromatin compaction and DNA-binding proteins regulate gene expression at high resolution.

The Chromium Genome Solution provides long range information on a genome-wide scale, including variant calling, phasing and extensive characterization of genomic structure. Unlock critical genetic information for variants in heritable disorders, and discover key genomic alterations in cancer.

The Chromium Exome Solution uses the power of linked-reads to fully resolve genic phasing, structural variation, and detect variants in previously inaccessible and complex regions of the exome.

High-throughput, low volume real-time PCR (Biomark HD, Fluidigm) allows for up to 96 targets in 96 samples in a single run with minimal input RNA or DNA for gene expression, SNP, or CNV studies.  

Learn more about Biomark

Our bioinformatics team provides all of the latest bioinformatics resources and expertise required to derive meaningful results from data generated on all ‘omics’ platforms. We have extensive experience with many popular software packages for single-cell RNA-seq (kallisto, Monocle2, DESeq2), metagenomics (QIIME, Kraken, MetaPhlAn2), and mass cytometry (Cytobank) analyses. We have access to private Linux servers as well as the USC High Performance Computing Core to provide you with all of the computing resources you may need regardless of the size of your project.  We provide a whole suite of services including analysis of experiments performed elsewhere.

How to cite the Core in publications:

The ______ (select services: Next Generation sequencing, RNA Sequencing, Single Cell Sequencing, Microbiome Metagenetics, Mass Cytometry, Image Mass Cytometry) work was performed in the Spatial Biology and Genomics Core at The Saban Research Institute, Children's Hospital Los Angeles.

Recent Publications

1. J. M. Bender et al., Maternal HIV infection influences the microbiome of HIV-uninfected infants. Science translational medicine 8, 349ra100 (2016).

2. S. Yang et al., Investigation of a suspected nosocomial transmission of blaKPC3-mediated carbapenem-resistant Klebsiella pneumoniae by whole genome sequencing. Diagnostic microbiology and infectious disease 84, 337-342 (2016).

3. Y. Yang et al., Autophagic UVRAG Promotes UV-Induced Photolesion Repair by Activation of the CRL4(DDB2) E3 Ligase. Molecular cell 62, 507-519 (2016).

4. J. M. Bender et al., Quantification of variation and the impact of biomass in targeted 16S rRNA gene sequencing studies. Microbiome 6, 155 (2018).

5. I. Blazenovic et al., Effects of Gut Bacteria Depletion and High-Na(+) and Low-K(+) Intake on Circulating Levels of Biogenic Amines. Molecular nutrition & food research, e1801184 (2018).

6. N. T. Ho et al., Meta-analysis of effects of exclusive breastfeeding on infant gut microbiota across populations. Nature communications 9, 4169 (2018).

7. P. S. Pannaraj et al., Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome. JAMA pediatrics 171, 647-654 (2017).

8. V. L. Ha et al., The T-ALL related gene BCL11B regulates the initial stages of human T-cell differentiation. Leukemia 31, 2503-2514 (2017).

9. Rusha Bhandari, Paibel Aguayo-Hiraldo, Jemily Malvar, Kimberly Cheng, Amy Sacapano, Hisham Abdel-Azim, Yueh-Yun Chi, Gregory Wallace, Shahab Asgharzadeh, Sonata Jodele, Etan Orgel. Ultra-High Dose Vitamin D in Pediatric Hematopoietic Stem Cell Transplantation: A Nonrandomized Controlled Trial. 2021 Sep 6; S2666-6367(21)01217-3.