# PA21259, SBIR, Phase I, Improving T cell Responses in Vaccines:  Prediction and Validation Using Existing Databases, Immunoinformatics and In Vitro Assays

> **NIH ALLCDC R43** · EPIVAX, INC. · 2022 · $299,930

## Abstract

ABSTRACT
An efficacious vaccine response requires that the host generates a specific response to antigenic epitopes without any prior
knowledge of their composition. While intrinsic components of immunity such as Tregs regulate inflammatory mechanisms,
they may also impede protective immune responses to infection and vaccination. Regulatory T cells (Tregs) comprise one
of the major mechanisms underlying immunological homeostasis and self-tolerance and they play a role in suppressing
vaccine-induced immunity. We developed an immunoinformatic tool, JanusMatrix, that identifies bacterial and viral class
II T cell epitopes that may induce regulatory T cell responses. We propose to evaluate and validate the selection of Treg
epitopes by this tool by calibrating tolerance-associated determinants such as sequence homology with the human genome,
epitope presentation in the thymus, tissue-specific expression in immune privileged sites, abundance, and subcellular
location, to improve the precision of this tool for Treg epitope selection and exclusion in vaccine design. In Aim 1 we will
test the hypothesis that vaccine antigens have sequences that may induce tolerance, and these sequences can be uncovered
using our JanusMatrix tool. A JanusMatrix threshold has been established for “immunogenicity” and “tolerogenicity” based
on the extent of cross-conservation between a given T cell epitope and similar-HLA-binding T cell epitopes in the human
proteome. We will determine additional thresholds associated with protein prevalence, thymic expression, immune
privilege, subcellular location, and presence among HLA ligands presented in benign tissues to assess properties of the
protein in silico and link those characteristics to a JanusMatrix Score that would enable us to predict Tregitopes. In Aim 2,
we will test the new JanusMatrix thresholds by predicting Treg epitopes in an antigen associated with placental malaria and
assessing their immunosuppressive properties using a Tetanus Toxoid Bystander Suppression Assay (TTBSA). This project
will help to elucidate new thresholds to predict T reg inducing epitopes, leading to optimized Treg epitope selection and
exclusion in vaccine design.

## Key facts

- **NIH application ID:** 10603454
- **Project number:** 1R43IP001225-01
- **Recipient organization:** EPIVAX, INC.
- **Principal Investigator:** Mayara Grizotte-Lake
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2022
- **Award amount:** $299,930
- **Award type:** 1
- **Project period:** 2023-09-30 → 2024-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10603454

## Citation

> US National Institutes of Health, RePORTER application 10603454, PA21259, SBIR, Phase I, Improving T cell Responses in Vaccines:  Prediction and Validation Using Existing Databases, Immunoinformatics and In Vitro Assays (1R43IP001225-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10603454. Licensed CC0.

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