# Bioinformatics and Statistics

> **NIH NIH P01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $303,538

## Abstract

PROJECT SUMMARY
The overarching theme of this HIVRAD proposal is to utilize the SHIV/rhesus macaque (RM) model to
understand the virus-antibody coevolutionary pathways leading to the development of broadly neutralizing
antibodies (bNAbs), and then to translate what we learn into the design of an effective HIV-1 vaccine. SHIVs
that have been generated in the Shaw laboratory have been pre-selected as good candidates for V1V2 or V3
glycan bNAb induction; they will enable systematic and rigorous characterization of the evolutionary pathways
to bNAb breadth taken by different Envs in RMs and humans. We will characterize what is common, versus
what is distinctive, in bNAb development and HIV-1 Envelope (Env) evolution between human and rhesus
macaques (RMs), as well as between different RMs infected by the same SHIV. Our preliminary work shows
that in at least some cases, we can expect evolutionary pathways to coincide. In Core C, we will use
bioinformatics and analytical and statistical tools to map the extent to which Env and antibody (Ab) co-
evolutionary pathways are shared between hosts in early infection and throughout the course of SHIV
infections as neutralization breadth emerges. We will begin by testing for patterns of immunologically relevant
mutations in both the Ab lineages and Env quasispecies as they co-evolve. We will help in down-selection of
specific Envs and Abs from large sequence sets to provide a rational means of reagent selection for cloning
and immunological characterization. We will provide statistical comparisons of immune response data, linking
experimental immunological data to both Env and antibody sequence data, and perform signature analysis to
resolve which mutations are critical in terms of changing the immunological phenotype of a protein (e.g.
antibody sensitivity). This will provide data needed to make an informed selection regarding which Env
candidates to take forward as vaccine immunogens. We will use computational methods to help resolve the B
cell clonal activities that are contributing to polyclonal serological responses. We will help design polyvalent
sets of Env vaccines for a lineage-based approach. Finally, we will provide statistical support throughout the
project, including comparisons of vaccine group outcomes, and, if protection is observed, we will help define
the correlates of immune protection. We will deposit sequences with linked meta-data to relevant databases
upon publication, and make novel code written for this project publicly available.

## Key facts

- **NIH application ID:** 9880387
- **Project number:** 5P01AI131251-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Bette Tina Marie Korber
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $303,538
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9880387

## Citation

> US National Institutes of Health, RePORTER application 9880387, Bioinformatics and Statistics (5P01AI131251-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9880387. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*