# High content glycomics analysis using next generation sequencing technology

> **NIH NIH R21** · STATE UNIVERSITY OF NEW YORK AT BUFFALO · 2020 · $238,105

## Abstract

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 u...

## Key facts

- **NIH application ID:** 9924616
- **Project number:** 5R21GM133195-02
- **Recipient organization:** STATE UNIVERSITY OF NEW YORK AT BUFFALO
- **Principal Investigator:** SRIRAM NEELAMEGHAM
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $238,105
- **Award type:** 5
- **Project period:** 2019-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9924616

## Citation

> US National Institutes of Health, RePORTER application 9924616, High content glycomics analysis using next generation sequencing technology (5R21GM133195-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9924616. Licensed CC0.

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