# Development of a novel TB vaccine safer and more effective than BCG based on a precisely controlled replication-limited Mycobacterium tuberculosis engineered for optimal in vivo growth and clearance > **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $779,991 ## Abstract ABSTRACT Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is one of the world's leading causes of death. BCG, the only licensed vaccine against TB, is an attenuated bacterium highly homologous to Mtb, yet safe in immunocompetent individuals because it has lost several genes that confer virulence. BCG has good efficacy against TB in children, but poor efficacy against TB in adolescents and adults. Hence, a vaccine much more potent than BCG is clearly needed. However, any replacement vaccine will almost certainly need to be based on modified (e.g. recombinant) BCG or attenuated Mtb to preserve the substantial benefits of BCG. The goal of this project is to develop an attenuated Mtb mutant that is safer and more potent than BCG. Our novel strategy involves manipulating two key characteristics of live vaccines: (1) their initial period of growth in the host and (2) their rate of elimination. The inadequate protective efficacy induced by BCG and non-replicating Mtb mutants can be attributed, at least in part, to their lack of replication in the host. Prolonged persistence in the host is also a negative factor, resulting in the generation of primarily effector and effector memory T cells rather than central memory T cells, important for long-term immunity. We hypothesize that limited replication of an Mtb mutant for a brief period after immunization, mimicking the early stage of a natural Mtb infection, followed by rapid clearance will induce a potent immune response and yet avoid the negative inflammatory responses induced by prolonged Mtb infection. To achieve our goal, we first shall engineer an attenuated Mtb mutant defective in both of its iron acquisi- tion pathways - siderophore-mediated iron acquisition (SMIA) and heme-iron acquisition (HIA). Such a mutant will be unable to obtain iron from the host but can be pre-loaded in vitro with the precise amount of iron to allow optimal replication in the host. Thus, an Mtb ∆SMIA ∆HIA mutant will allow us to address the first important factor - controlling the extent of replication in the host. While growth of Mtb ∆SMIA ∆HIA in the host will cease once it exhausts its supply of iron, the organism may persist for a prolonged period. Thus, to address the second important factor, the rate of clearance from the host, we shall further modify Mtb ∆SMIA ∆HIA, via two approaches – 1) knocking out persistence genes and 2) conditional silencing of essential genes. While both should result in improved clearance, conditional silencing likely will result in faster clearance. We shall vaccin- ate mice with persistence and conditional silencing mutants and perform clearance and protective efficacy studies to determine the optimal replication and clearance. We expect a replication- and persistence-limited Mtb mutant with rapid clearance will be much more efficacious than BCG and, in contrast to BCG, safe even in an immunocompromised host. Once we have optimized the vaccine for protective immunity in mi... ## Key facts - **NIH application ID:** 10570976 - **Project number:** 5R01AI148122-03 - **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES - **Principal Investigator:** MARCUS AARON HORWITZ - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $779,991 - **Award type:** 5 - **Project period:** 2021-03-15 → 2026-02-28 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10570976 ## Citation > US National Institutes of Health, RePORTER application 10570976, Development of a novel TB vaccine safer and more effective than BCG based on a precisely controlled replication-limited Mycobacterium tuberculosis engineered for optimal in vivo growth and clearance (5R01AI148122-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10570976. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*