Biological systems are typically robust since many different biochemical reaction pathways and processes partially control system stability. In some instances, loss of a single pathway results in compensatory contributions from others to maintain system-status. In others, many different biological pathways partially contribute to regulating a single function, with complete functional loss only being observed upon loss or knocking-out of all individual contributors. Large-scale experimental and computational interrogation of biological assemblies is necessary in order to develop a systems-level understanding. The scope of such investigations has been vastly enhanced in recent years with the development of new multiplex tools based on next-generation sequencing (NGS). This is commonly enabled by the tagging of individual cells, monoclonal antibodies or other antigen binders with oligonucleotide barcodes or unique molecular identifiers (UMIs). Such barcodes/UMIs can be followed independently using NGS. In addition, it is now possible to develop CRISPR based knockout libraries and screens targeting the entire genomes, or a subset of genes related to a certain function (e.g. cellular glycosylation). This project aims to combine recent advances in NGS and CRISPR-Cas9 by addressing the hypothesis that ?the combined use of CRISPR-Cas to knockout genes in large scale combined with NGS to measure related cell-system response can inform us of system properties at an unprecedented scale?. We test this possibility using examples from the Glycosciences.
The specific aims are:
Aim 1. To develop ?Lectin-Tag- seq?, a method to assay the glycome of individual cells in complex mixtures. Here, a panel of lectins and related mAbs are tagged with uniquely barcoded oligonucleotides. The simultaneous binding of these reagents to diverse cell types in human blood and breast tissue is measured at a large scale using NGS. The lectin binding specificity of a vast number of carbohydrate binding proteins is now available in literature, and thus bioinformatics analysis will be applied to relate the lectin-binding measurements on individual cells to glycan epitopes and potential carbohydrate structures that exist on the single cells.
Aim 2. To develop ?CRISPR-Tag-seq? in order to simultaneously measure, at a single cell level, the sgRNA editing a given cell and the corresponding changes in multiplex lectin/mAb binding profiles. Here, a glycogene-CRISPR library targeting 347 genes regulating cellular glycosylation is introduced into breast cancer cells. The effects of such biochemical pathway perturbations are related to lectin binding on individual cells. Mathematical analysis is performed to analyze the effect of sgRNA perturbations. All data will be available to the research community at our website VirtualGlycome.org. In the long run, methods developed in this project can be extended to additional cell types and biological problems to ultimately streamline and simplify our understanding of the mammalian glycome.

Public Health Relevance

There is a need to develop a systems level understanding of cell and tissue assemblies during the transition from normal human physiology to pathology. This project aims to combine two recent advanced technologies, Next Generation Sequencing and CRISPR-Cas genome editing, along with mathematical modeling to achieve such understanding. It will result in a novel method to profile the binding of a panel of lectins to mixed cell populations and tissue, and a technology to identify detailed biochemical pathways regulating such binding.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21GM133195-02
Application #
9924616
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Sammak, Paul J
Project Start
2019-05-01
Project End
2021-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
State University of New York at Buffalo
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
038633251
City
Amherst
State
NY
Country
United States
Zip Code
14228