Our Research
The advent of molecular biology has propelled biology at the forefront of modern science. Technological advances such as rapid and inexpensive DNA sequencing are paving the way for precision medicine and synthetic biology to become ubiquitous in clinical and industrial applications. Basic research is needed to spearhead the development of these technologies into everyday practice.
Microbiology is one of the areas that could benefit the most from this technological acceleration. For instance, the rise of antimicrobial resistance (AMR) requires the development of new approaches aimed at predicting evolution of resistance and prevent it. Sequencing-based surveillance and evolutionary models informing smarter treatment strategies are therefore urgently needed. At the same time, the recognition of the role of the microbiome on human health and as a possible treatment strategy for infections requires a deeper ecological and functional understanding. In particular, the design of treatments is predicated on knowing the molecular and metabolic functions encoded in the genomes of each member of the microbiome. In short, we need to greatly improve the functional and evolutionary interpretation of genomic sequences, at the same time as they are being produced. These challenges can be effectively tackled using a data-intensive approach, favored by high-throughput molecular techniques and computational biology.
Our Research
The advent of molecular biology has propelled biology at the forefront of modern science. Technological advances such as rapid and inexpensive DNA sequencing are paving the way for precision medicine and synthetic biology to become ubiquitous in clinical and industrial applications. Basic research is needed to spearhead the development of these technologies into everyday practice.
Microbiology is one of the areas that could benefit the most from this technological acceleration. For instance, the rise of antimicrobial resistance (AMR) requires the development of new approaches aimed at predicting evolution of resistance and prevent it. Sequencing-based surveillance and evolutionary models informing smarter treatment strategies are therefore urgently needed. At the same time, the recognition of the role of the microbiome on human health and as a possible treatment strategy for infections requires a deeper ecological and functional understanding. In particular, the design of treatments is predicated on knowing the molecular and metabolic functions encoded in the genomes of each member of the microbiome. In short, we need to greatly improve the functional and evolutionary interpretation of genomic sequences, at the same time as they are being produced. These challenges can be effectively tackled using a data-intensive approach, favored by high-throughput molecular techniques and computational biology.
Prof Dr Marco Galardini
We study how the high plasticity of the genomes of bacterial pathogens influences their pathogenicity and their resistance to antimicrobials.
Marco Galardini is a computational biologist with a taste for microbiology. He did his bachelor and master studies in Italy at the university of Florence and Bologna, and his PhD in the lab of Marco Bazzicalupo. He then did two postdocs: one in the lab of Pedro Beltrao at EMBL-EBI, and one in the lab of Mo Khalil at Boston University. He leads the Microbial Pangenomes Lab at TWINCORE since October 2020.
His current focus is on developing computational methods to study the genetic determinants of bacterial virulence and antimicrobial resistance and the empirical study of the evolution of resistance. His professorship in Hannover is funded by the RESIST Cluster of Excellence.
Selected Publications
- Burgaya, J., Damaris, B. F., Fiebig, J., & Galardini, M. (2025). microGWAS: A computational pipeline to perform large-scale bacterial genome-wide association studies. Microbial Genomics, 11(2), 001349. DOI: 10.1099/mgen.0.001349
- Mulkern, A. J., Vu, T.-H., Popella, L., Kerrinnes, T., Đurica-Mitić, S., Barquist, L., Vogel, J., & Galardini, M. (2024). A systematic identification of resistance determinants to antisense antibiotics suggests adaptation strategies dependent on the delivery peptide (p. 2024.10.29.620885). bioRxiv. DOI: 10.1101/2024.10.29.620885
- Innocenti, G., Obara, M., Costa, B., Jacobsen, H., Katzmarzyk, M., Cicin-Sain, L., Kalinke, U., & Galardini, M. (2024). Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections. Genome Biology, 25(1), 228. DOI: 10.1186/s13059-024-03355-y
- Burgaya, J.*, Marin, J.*, Royer, G., Condamine, B., Gachet, B., Clermont, O., Jaureguy, F., Burdet, C., Lefort, A., Lastours, V. de, Denamur, E.*, Galardini, M.*, Blanquart, F.* (2023). The bacterial genetic determinants of Escherichia coli capacity to cause bloodstream infections in humans. PLOS Genetics, 19(8), e1010842. DOI: 10.1371/journal.pgen.1010842
- Denamur, E., Condamine, B., Esposito-Farèse, M., Royer, G., Clermont, O., Laouenan, C., … & Galardini, M.* (2022). Genome wide association study of human bacteremia Escherichia coli isolates identifies genetic determinants for the portal of entry but not fatal outcome. PLoS Genetics. 2022;18(3):e1010112. DOI: 10.1371/journal.pgen.1010112
A complete list of publications can be found here.
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