Adriana Tomic

Tomic Lab is interested in understanding the signature of protective immunity in humans. The hallmark of protective immunity is the ability of the immune system to mount an effective response to a given pathogen. The immune system comprises multiple cell types that work together to develop an effective response. Which of myriad cell types are important in a particular response, however, is not well understood. 

In my group, we apply a systems-level analysis to measure all the aspects of an immune response. By applying systems-level analysis, we capture hundreds of parameters during an infection or vaccination to reveal protective signatures in a particular response. Using machine learning approaches, we identify patterns and extract knowledge from multidimensional data to reveal correlates of protection that other approaches may miss. Capturing hundreds of data points, our approach provides unprecedented resolution into the unique immunological ‘fingerprints’ that exist among individuals and across diseases. Finally, we then interrogate these immune cell profiles to define the specific immune cell profiles that track with favorable patient outcomes for influenza, RSV, and SARS-CoV-2, to name some of the applications in our ongoing projects. 

The long-term goal of our research is the standardization of the systems immunology approach, including the development of automated technology platforms for large-scale immunoassays, generating easy-to-use workflows for integration of multi-omics data based on AI, and establishment of cell culture models for testing human memory responses. Today, more than ever, we need to form tight interdisciplinary collaborations, and our research program aims to form a diverse and highly multidisciplinary group to bring different perspectives to tackle significant problems in the prevention of future pandemics and the improvement of next-generation of vaccines.

To learn more about our research, check out atomic-lab.org.

Selected Publications

1. Tomic A, Skelly DT, Ogbe A, O’Connor D, Pace M, Adland E, Alexander F, Ali M, Allott K, Azim Ansari M, Belij-Rammerstorfer S, Bibi S, Blackwell L, Brown A, Brown H, Cavell B, Clutterbuck EA, de Silva T, Eyre D, Lumley S, Flaxman A, Grist J, Hackstein CP, Halkerston R, Harding AC, Hill J, James T, Jay C, Johnson SA, Kronsteiner B, Lie Y, Linder A, Longet S, Marinou S, Matthews PC, Mellors J, Petropoulos C, Rongkard P, Sedik C, Silva-Reyes L, Smith H, Stockdale L, Taylor S, Thomas S, Tipoe T, Turtle L, Vieira VA, Wrin T, Pollard AJ, Lambe T, Conlon CP, Jeffery K, Travis S, Goulder P, Frater J, Mentzer AJ, Stafford L, Carroll MW, James WS, Klenerman P, Barnes E, Dold C, Dunachie SJ. Divergent trajectories of antiviral memory after SARS-CoV-2 infection. Nat Commun. 2022 Mar 10;13(1):1251. doi: 10.1038/s41467-022-28898-1. PubMed PMID: 35273178; PubMed Central PMCID: PMC8913789
2. COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. Cell. 2022 Mar 3;185(5):916-938.e58. doi: 10.1016/j.cell.2022.01.012. Epub 2022 Jan 21. PubMed PMID: 35216673; PubMed Central PMCID: PMC8776501
3. Tomic A, Tomic I, Waldron L, Geistlinger L, Kuhn M, Spreng RL, Dahora LC, Seaton KE, Tomaras G, Hill J, Duggal NA, Pollock RD, Lazarus NR, Harridge SDR, Lord JM, Khatri P, Pollard AJ, Davis MM. SIMON: Open-Source Knowledge Discovery Platform. Patterns (N Y). 2021 Jan 8;2(1):100178. doi: 10.1016/j.patter.2020.100178. eCollection 2021 Jan 8. PubMed PMID: 33511368; PubMed Central PMCID: PMC7815964.
4. Tomic A, Tomic I, Dekker CL, Maecker HT, Davis MM. The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system. Sci Data. 2019 Oct 21;6(1):214. doi: 10.1038/s41597-019-0213-4. PubMed PMID: 31636302; PubMed Central PMCID: PMC6803714.
5. Tomic A, Tomic I, Rosenberg-Hasson Y, Dekker CL, Maecker HT, Davis MM. SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses. J Immunol. 2019 Aug 1;203(3):749-759. doi: 10.4049/jimmunol.1900033. Epub 2019 Jun 14. PubMed PMID: 31201239; PubMed Central PMCID: PMC6643048.