# Core 1 - Research Technology Core

> **NIH NIH P50** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2021 · $162,305

## Abstract

ABSTRACT
In this program on lupus pathogenesis, we seek to understand the pathways that drive autoimmunity. The
Research Technology Core (Core 1) is dedicated to providing standardized means for the study of these B cell
and antibody responses, and for investigations of the host relationship with commensal bacteria in the gut.
The Core will provide services that have customized to the needs of each of the Projects. Through
centralization of these facilities, we will provide services that provide economies of scale and efficiency. These
methods are state-of-the-art and are otherwise not available from NYU Core facilities or from commercial
vendors.
The Research Technology Core will perform already validated assays in four areas:
i) Autoantibody surveys from serum and fecal samples.
ii) Isolation of fecal bacteria coated in the bowel by endogenously produced IgA.
iii) Microbiome analyses by 16S rRNA methods by Next Generation Sequencing.
iv) Large-scale BCR transcript repertoire libraries.
Herein, we will support studies for all three Projects of the contributions of specific antibody/B-cell clones from
the initial breach of immune tolerance, and in the transition from preclinical to overt clinical disease, and during
the later phase of ongoing disease process characterized by self-perpetuation of autoimmune disease.

## Key facts

- **NIH application ID:** 10249211
- **Project number:** 5P50AR070591-05
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Gregg Joshua Silverman
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $162,305
- **Award type:** 5
- **Project period:** 2017-09-22 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10249211

## Citation

> US National Institutes of Health, RePORTER application 10249211, Core 1 - Research Technology Core (5P50AR070591-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10249211. Licensed CC0.

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