Honors & Awards
Marie Sklodowska-Curie Fellowship, European Comission Program EU’s Horizon 2020 (2018)
Best PhD Award, Hannover Medical School (2017)
Travel grant for International Congress of Immunology, Melbourne, Australia, EU Federation of Immunological Societies (EFIS) (2016)
Travel grant for the Annual meeting of the Society, German Virological Society (2016)
Travel grant for Annual Meeting of Middle-European Societies for Immunology and Allergology, University of Rijeka Foundation (2013)
Diploma, University of Ljubljana (2010)
Doctor of Philosophy, Hanover School of Medicine (2016)
Mark Davis, Postdoctoral Faculty Sponsor
Current Research and Scholarly Interests
Marie Curie Fellow in systems immunology, applying machine learning to understand how vaccines work, specifically focused on human immunology and data-driven research. Co-developer of SIMON, an open source platform for the application of machine learning to biological and clinical data.
The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.
2019; 6 (1): 214
Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first attempts have revealed a high level of complexity in establishing influenza immunity, and many different cellular and molecular components are involved. Of note is that the previously identified correlates of protection fail to account for the majority of individual responses across different age groups and influenza seasons. Challenges remain from the small sample sizes in most studies and from often limited data sets, such as transcriptomic data. Here we report the creation of a unified database, FluPRINT, to enable large-scale studies exploring the cellular and molecular underpinnings of successful antibody responses to influenza vaccines. Over 3,000 parameters were considered, including serological responses to influenza strains, serum cytokines, cell phenotypes, and cytokine stimulations. FluPRINT, facilitates the application of machine learning algorithms for data mining. The data are publicly available and represent a resource to uncover new markers and mechanisms that are important for influenza vaccine immunogenicity.
View details for DOI 10.1038/s41597-019-0213-4
View details for PubMedID 31636302
SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.
Journal of immunology (Baltimore, Md. : 1950)
Machine learning holds considerable promise for understanding complex biological processes such as vaccine responses. Capturing interindividual variability is essential to increase the statistical power necessary for building more accurate predictive models. However, available approaches have difficulty coping with incomplete datasets which is often the case when combining studies. Additionally, there are hundreds of algorithms available and no simple way to find the optimal one. In this study, we developed Sequential Iterative Modeling "OverNight" (SIMON), an automated machine learning system that compares results from 128 different algorithms and is particularly suitable for datasets containing many missing values. We applied SIMON to data from five clinical studies of seasonal influenza vaccination. The results reveal previously unrecognized CD4+ and CD8+ T cell subsets strongly associated with a robust Ab response to influenza Ags. These results demonstrate that SIMON can greatly speed up the choice of analysis modalities. Hence, it is a highly useful approach for data-driven hypothesis generation from disparate clinical datasets. Our strategy could be used to gain biological insight from ever-expanding heterogeneous datasets that are publicly available.
View details for DOI 10.4049/jimmunol.1900033
View details for PubMedID 31201239
Activation of Innate and Adaptive Immunity by a Recombinant Human Cytomegalovirus Strain Expressing an NKG2D Ligand
2016; 12 (12)
Development of an effective vaccine against human cytomegalovirus (HCMV) is a need of utmost medical importance. Generally, it is believed that a live attenuated vaccine would best provide protective immunity against this tenacious pathogen. Here, we propose a strategy for an HCMV vaccine that aims at the simultaneous activation of innate and adaptive immune responses. An HCMV strain expressing the host ligand ULBP2 for the NKG2D receptor was found to be susceptible to control by natural killer (NK) cells, and preserved the ability to stimulate HCMV-specific T cells. Infection with the ULBP2-expressing HCMV strain caused diminished cell surface levels of MHC class I molecules. While expression of the NKG2D ligand increased the cytolytic activity of NK cells, NKG2D engagement in CD8+ T cells provided co-stimulation and compensated for lower MHC class I expression. Altogether, our data indicate that triggering of both arms of the immune system is a promising approach applicable to the generation of a live attenuated HCMV vaccine.
View details for DOI 10.1371/journal.ppat.1006015
View details for Web of Science ID 000392202100014
View details for PubMedID 27907183
View details for PubMedCentralID PMC5131914
Inflammatory monocytes and NK cells play a crucial role in DNAM-1-dependent control of cytomegalovirus infection
JOURNAL OF EXPERIMENTAL MEDICINE
2016; 213 (9): 1835-1850
The poliovirus receptor (PVR) is a ubiquitously expressed glycoprotein involved in cellular adhesion and immune response. It engages the activating receptor DNAX accessory molecule (DNAM)-1, the inhibitory receptor TIGIT, and the CD96 receptor with both activating and inhibitory functions. Human cytomegalovirus (HCMV) down-regulates PVR expression, but the significance of this viral function in vivo remains unknown. Here, we demonstrate that mouse CMV (MCMV) also down-regulates the surface PVR. The m20.1 protein of MCMV retains PVR in the endoplasmic reticulum and promotes its degradation. A MCMV mutant lacking the PVR inhibitor was attenuated in normal mice but not in mice lacking DNAM-1. This attenuation was partially reversed by NK cell depletion, whereas the simultaneous depletion of mononuclear phagocytes abolished the virus control. This effect was associated with the increased expression of DNAM-1, whereas TIGIT and CD96 were absent on these cells. An increased level of proinflammatory cytokines in sera of mice infected with the virus lacking the m20.1 and an increased production of iNOS by inflammatory monocytes was observed. Blocking of CCL2 or the inhibition of iNOS significantly increased titer of the virus lacking m20.1. In this study, we have demonstrated that inflammatory monocytes, together with NK cells, are essential in the early control of CMV through the DNAM-1-PVR pathway.
View details for DOI 10.1084/jem.20151899
View details for Web of Science ID 000382520900014
View details for PubMedID 27503073
View details for PubMedCentralID PMC4995080
Cytomegalovirus m154 Hinders CD48 Cell-Surface Expression and Promotes Viral Escape from Host Natural Killer Cell Control
2014; 10 (3)
Receptors of the signalling lymphocyte-activation molecules (SLAM) family are involved in the functional regulation of a variety of immune cells upon engagement through homotypic or heterotypic interactions amongst them. Here we show that murine cytomegalovirus (MCMV) dampens the surface expression of several SLAM receptors during the course of the infection of macrophages. By screening a panel of MCMV deletion mutants, we identified m154 as an immunoevasin that effectively reduces the cell-surface expression of the SLAM family member CD48, a high-affinity ligand for natural killer (NK) and cytotoxic T cell receptor CD244. m154 is a mucin-like protein, expressed with early kinetics, which can be found at the cell surface of the infected cell. During infection, m154 leads to proteolytic degradation of CD48. This viral protein interferes with the NK cell cytotoxicity triggered by MCMV-infected macrophages. In addition, we demonstrate that an MCMV mutant virus lacking m154 expression results in an attenuated phenotype in vivo, which can be substantially restored after NK cell depletion in mice. This is the first description of a viral gene capable of downregulating CD48. Our novel findings define m154 as an important player in MCMV innate immune regulation.
View details for DOI 10.1371/journal.ppat.1004000
View details for Web of Science ID 000337470300043
View details for PubMedID 24626474
View details for PubMedCentralID PMC3953435
- Superior induction and maintenance of protective CD8 T cells in mice infected with mouse cytomegalovirus vector expressing RAE-1 gamma PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2013; 110 (41): 16550-16555