CV

The Talavera-López Lab:

I am a committed and creative clinician-scientist with a strong background in computational biology, genome evolution and single-cell biology. I have over 12 years of experience in computational biology and seven years in single-cell multiomics, working with pathogens, animal models, and human tissues in health and disease.

My research group focuses on combining computational biology, machine learning and spatially-resolved single-cell multiomics to understand the cellular basis of health and disease. I am fascinated by how in mammals, a single-celled egg with its single genome can give rised to the organ complexity observed in the adult.

During my training in computational biology, I worked on large-scale comparative genomic projects (Nature, 2013). Throughout my PhD studies, I devised computational strategies for the characterisation of virulence mechanisms in parasites (eLife, 2022; PLoS NTDs 2014), studied the immune response during infection using single-cell biology (Cell Reports, 2021), and understood the genome evolution in tissue regeneration of Pleurodeles waltl (Nature Communications, 2017). During my postdoctoral research, I applied systems immunology to understand the immune response to Plasmodium spp. in the mouse spleen and circulatory blood during acute and chronic malaria (Scientific Reports, 2020). Later, I combined statistical and deep learning techniques with spatially resolved single-cell technologies to dissect gene regulatory networks of human cardiac function and its potential changes in cardiac tissue repair (Nature, 2020). At the onset of the COVID-19 pandemic, our team was the first to identify, using spatially-resolved single-cell data, the tissue localisation of the host receptors for SARS-CoV-2 (Nature Medicine, 2020). As an independent group leader, I use single-cell technologies and machine learning methods to link cellular behaviour to clinical data (bioRxiv, 2022), identifying biomarkers for early diagnosis, disease progression, and treatment response in Tuberculosis, HIV/AIDS and Malaria.

Positions, Scientific Appointments, and Honors

  • 2011 - 2012 Staff bioinformatician, Science for Life Laboratory, Stockholm, Sweden.
  • 2012 - 2016 PhD student, Karolinska Institutet, Stockholm, Sweden.
  • 2016 - 2018 Postdoctoral Fellow, Francis Crick Institute, London, UK
  • 2018 - 2021 Senior bioinformatician, Cellular Genetics - Wellcome Sanger Institute, Cambridge, UK.
  • 2021 - 2023 Group leader, Institute of Computational Biology, Helmholtz Munich, Munich, Germany.
  • 2023 - Present Junior Professor in Single Cell Biology, Julius Maximillian University and Max Planck for Systems Immunology, Würzburg, Germany.

Contributions to Science

Understanding how genome plasticity helps with organism adaptability:

During my early development as a scientist, I focused on understanding the mechanisms used by living organisms to adapt to their environments. Working as a bioinformatician at SciLifeLab in Stockholm, Sweden, I participated in the Picea abies genome project, the largest genome sequenced at that point. During that work, I pioneered phylogenetics and genome assembly methods to compare genomic features between P. abies and other conifers, identifying specific traits associated with weather resilience in conifers. This experience tested how genome plasticity may facilitate adaptability in blood-borne parasites to evade the immune system. As a result, during my PhD at Karolinska Institutet, I identified and characterised the genomic mechanisms used by Trypanosoma cruzi to produce novel variants of surface molecules to evade the host immune system. These projects allowed me to develop my ideas to study very complex and repetitive genomes, which led me to be the computational lead during the assembly and annotation of the Pleurodeles waltl genome, a model organism for tissue regeneration and repair and one of the largest genomes studies to date.

  • Nysted B et al. (2013) The Norway spruce genome sequence and conifer evolution. Nature.
  • Stocco P, Wagner G, Talavera-López C et al. (2014) Genome of the avirulent human - infective trypanosome - Trypanosoma rangeli. PLoS Negl. Trop. Dis.
  • Elewa A, Wang H, Talavera-López C et al. (2017) Reading and editing of the Pleurodeles waltl genome reveals novel features of tetrapod regeneration. Nature Communications.
  • Talavera-López C, Messenger L, Lewis MD et al. (2021) Repeat-driven generation of antigenic diversity in a major human pathogen, Trypanosoma cruzi. Front. Cell Infect. Microbiol.
  • Matos GM, Lewis MD, Talavera-López C et al. (2022) Microevolution of Trypanosoma cruzi reveals hybridization and clonal mechanism driving rapid genome diversification. eLife.

Studying the tissue response to infection and how they reflect in circulatory blood:

My work on genome plasticity interested me in how the new adaptability generated will affect the immune response during host-pathogen interactions. After graduating from Karolinska Institutet, I started my postdoctoral studies in the lab of Jean Langhorne at the Francis Crick Institute in London, UK, to study the expression dynamics of surface molecules in Plasmodium chabaudi and how the immune response will evolve during infection in mice. Using systems immunology, my work identified distinctive interferon-gamma (INF-G) responses to the differential expression of cir genes, a superfamily of surface molecules in P. chabaudi. This work revealed that the immune response in the spleen, where most infection clearance occurs, is not reflected in the blood transcriptome. This finding has important implications in field studies identifying biomarkers for disease severity in blood.

  • Capuccini B, Lin J, Talavera-Lopez C et al. (2016) Transcriptomic profiling of microglia reveals signatures of cell activation and immune response, during experimental cerebral malaria. Scientific Reports.
  • Talavera-López C, Bediako Y, Lin J et al. (2019) Comparison of whole blood and spleen transcriptional signatures over the course of an experimental malaria infection. Scientific Reports.

Understanding cellular circuits in health and disease:

After working with host-pathogen interactions and single-cell biology revealing many cellular mechanisms, I decided to investigate how a given tissue responds to damage and infection. As a staff scientist to Sarah Teichmann at the Wellcome Sanger Institute, I applied my computational and clinical expertise to understand how cellular circuits change in health and disease. One of my first contributions was to help with the first comparison of lung cell states in health and asthma. My main project was to produce the first analysis of the cellular composition of the non-failing human heart, which I led in collaboration with an international team. In this work, I characterised the immune repertoire of the healthy human heart and how they are different in each anatomical region. While working on this project, the COVID-19 pandemic struck. In collaboration with an international team from the Human Cell Atlas, we identified the cell states expressing the SARS-CoV-2 receptors across multiple human organs and tissues. As part of my work at the Cellular Genetics Programme led by Sarah Teichmann, I collaborate with the development of novel tools for the analysis of large-scale, multimodal single-cell datasets while contributing to the accessibility of tools to analyse these data by participating in single-cell workshops at the EMBL - European Bioinformatics Institute, and contributing to the development of a Galaxy-powered portal to democratise single-cell data analysis.

  • Vieira Braga F, Kar G, Berg M et al. (2019) A cellular census of human lungs identifies novel cell states in health and in asthma. Nature Medicine.
  • Papatheodorou I, Moreno P, Manning J et al. (2020) Expression atlas update: from tissues to single cells. Nucleic Acids Res.
  • Sungnak W, Huang N, Becavin C, Berg M, Queen R, Litvinuková M, Talavera-López C et al (2020) SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes. Nature Medicine.
  • Talavera-López C et al (2020) Cells of the adult human heart. Nature.
  • Muus C, Luecken M, Eraslan G et al. (2021) Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics. Nature Medicine.
  • Moreno P, Huang N, Manning J et al. (2021) User-friendly, scalable tools and workflows for single cell RNA seq analysis. Nature Methods.
  • Gayoso A, López R, Xing G et al. (2022) A python library for probabilistic analysis of single cell omics data. Nature Biotechnology.
  • Kanemaru K, Cranley J, Muraro D, et al. (2023) Spatially resolved multiomics of human cardiac niches. Nature (In Press), bioRxiv.

Applying Artificial Intelligence and single-cell technologies to answer biological questions:

After completing my postdoctoral fellowship at the Wellcome Sanger Institute, I sought to gain more experience developing AI methods for spatially-resolved single-cell multiomics data and started my research group at the Institute of Computational Biology (ICB) - Helmholz Munich. At ICB, I developed software development skills with cutting-edge libraries for AI/ML, applying explainable AI models to single-cell data integration, and participating in large-scale model training for the Human Lung Cell Atlas project. During this time, I supervised five PhD students and a postdoc, further improving my management skills for developing computational tools to answer biological questions. In addition, I established direct collaborations with clinicians at the Department of Infectious Diseases and Tropical Medicine at the LMU-Klinikum. This experience allowed me to tailor software development to the direct needs of translational medicine to identify diagnostic biomarkers.

  • Lotfollahi M, Rybakov S, Hrovatin K, et al. (2023) Biologically informed deep learning to query gene programmes in single-cell atlases. Nature Cell Biology.
  • Sikkema L, Strobl D, Zappia L, et al. (2023) An integrated cell atlas of the human lung in health and disease. Nature Medicine.

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