This project houses all the publicly available datasets generated by the Hi-IMPAcTB consortium over the course of its 7+ years.

What is Hi-IMPAcTB?

Hi-IMPAcTB is an ambitious endeavor bringing together a team of international, interdisciplinary researchers to improve our understanding of host-pathogen interactions in the context of tuberculosis (TB). Funded by a multi-center contract from the NIH, the long-term goal of the consortium is to enable principled vaccine design by improving our understanding of the protective versus non-protective immunological host response to infection with TB’s causal agent the bacterium Mycobacterium tuberculosis (Mtb). Hi-IMPAcTB is one of three centers receiving funding from NIAID to enable this vision. See here for more details.

The Data.

Using multi-modal data from lungs and blood in mice, non-human primates (NHPs) and humans the consortium aims to understand the range of immunological responses observed in each species and their association with TB disease outcome.

This involves the characterization of various components of the immune system and the interactions between them using (1) multi-parameter flow cytometery/CyToF and (2) single cell sequencing (including TCR sequencing) to understand changes in cellular composition and state after infection with Mtb. That is complemented by (3) systems serology data which allows profiling the humoral immune response which recent evidence suggests might play an overlooked role in the Mtb response, as well as (4) a range of innate immune profiling assays which allow the characterization of macrophages, neutrophils and other non-adaptive immune cell types that play a role in determining disease outcome. (5) PET-CT imaging allows tracking disease development in live animals and in humans, and (6) Immunohistochemistry/fluorescence and (7) spatial transcriptomics allow the spatial profiling of tissues of interest. (8) Using a genetically barcoded clinical strain of Mtb, we can also trace the establishment of persistent TB lesions and determine bacterial dissemination from the lung (the original site of exposure) to other tissues of interest such as lymphnodes.

A notable advantage is the consortium’s ability to use a range of interventions in NHPs and genetically diverse mouse strains to untangle correlation/association from causation in the context of immune protection against disease. This is especially important given that most common laboratory mouse strains do not closely recapitulate the disease response seen in humans. Another is that we profile patients with a range of clinical presentations of TB disease, reflecting a more nuanced appreciation for a spectrum of disease states.

Whenever possible, data is deposited in an appropriate public repository and linked here with all relevant metadata to enable FAIR sharing.

The role of Data Science.

Given the complexity of the data, clinicians, experimental biologists, and computational biologists within the consortium work closely to integrate and analyze the data to inform our understanding of the complex host response to Mtb in association with clinically-relevant outcomes. This involves the adoption of existing statistical and mathematical frameworks, and the development of new tools adapted to handling the specific design of animal and clinical studies in the consortium. Emerging hypotheses can then be tested in vivo, and the new data subsequently used to refine model performance in a virtuous cycle that we hope will enable the identification of clinically-relevant vaccination strategies.

All the original code used to analyze any of our data is publicly deposited and linked to on FAIRDOMHUB in the context in which it was used.

The Team.

The data and code in this project primarily comes from the following Hi-IMPAcTB laboratories:

  1. Fortune Lab (co-lead PI), Harvard University, USA.
  2. Flynn Lab (co-lead PI), University of Pittsburg, USA.
  3. Boom Lab (co-lead PI), Case Western Reserve University, USA*
  4. Mayanja-Kizza Lab, Makerere University, Uganda*
  5. Bryson Lab, MIT, USA.
  6. Lauffenburger Lab, MIT, USA
  7. Shalek Lab, MIT, USA.
  8. BioMicro Center, MIT, USA
  9. Systems Serology Lab, Ragon Institute, USA
  10. Behar Lab, University of Massachussets Worcester, USA
  11. Sassetti Lab, University of Massachusets Worcester, USA
  12. Seshadri Lab, University of Washington, USA
  13. Nemes Lab, University of Cape Town/SATVI, South Africa
  14. Waltzl Lab, Stellenbosch University, South Africa
  15. Wong Lab, AHRI, South Africa

*Participants in the Uganda-CWRU partnership.

FAIRDOM PALs: No PALs for this Project

Project created: 13th Jan 2021

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