Prof. Galardini<\/a><\/p><\/h2><\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What is this research project about?<\/h1><\/div><\/a><\/span><\/div>Assigning a putative function to all the genes encoded in bacterial pangenomes.<\/p>\n<\/div><\/div><\/div><\/div>What is this research project about?<\/h1><\/div>We usually think of genetic differences in the context of human genetics. And so we are familiar with the fact that two people differ on average at about five million sites in the genome \u2013 that is, at only about 0.8 per cent of the entire genome. But genetic variation in bacteria has a completely different dimension: For example, two strains of Escherichia coli<\/em> can differ in up to 60 percent of their genetic content.<\/p>\nThis means that each bacterial species has not only a single genome, but also a diverse ensemble of gene combinations called a pangenome. We want to investigate the influence of this great genetic diversity on bacterial phenotypes.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What’s the current status?<\/h1><\/div><\/div><\/div><\/div>Understanding how variations in genotype lead to variations in phenotype is an old topic in molecular biology. We are exploring how to better predict the phenotypic consequences of genetic variants in bacteria. This can be done with a combination of “forward-looking” mechanistic models, and “backward-looking” statistical genomics models.\nCertain bacterial species, such as E.coli<\/em>, have so-called open pangenomes. This means that new genes (“accessory genes”) are discovered when the genomes of new isolates are sequenced. Current functional genomics techniques cannot scale up fast enough to keep up with the flood of genes with unknown function that are being discovered every day.<\/p>\n<\/div><\/div><\/div><\/div><\/span><\/div><\/div>Studying how different bacterial strains adapt to the same selective pressure (e.g. antimicrobials).<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What are the project goals?<\/h1><\/div>Our goal is to develop methods to assign functions to accessory genes by computer. The wealth of data available for different types of bacteria, as well as advances in machine learning, are one possible way to solve this problem. Most importantly, it helps that our lab has access to a large collection of E.coli strains.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>How do we get there?<\/h1><\/div><\/div><\/div><\/div>It has been shown that the genetic variability between bacterial strains also affects genes that are indispensable for growth and reproduction. We suspect that these differences could also influence the ability to adapt to selection pressures, such as the use of antimicrobials. As we explore the influence of bacterial pangenomes on clinically relevant phenotypes, we are also investigating whether different genetic backgrounds make people more or less susceptible to developing antibiotic resistance.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div>Computational and experimental approaches to link genotypic to phenotypic variation.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Projectleader<\/h1><\/div>Project title: Influence of genetic diversity on the bacterial phenotype<\/h4><\/div><\/div><\/div><\/div><\/div><\/div><\/a><\/span><\/div><\/div><\/div><\/div>Prof. Dr. Marco Galardini<\/h3><\/div>Project: C4<\/a><\/h3><\/div><\/div><\/div><\/div>CV & VIDEO<\/span><\/a><\/div><\/div><\/div><\/div>\n<\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Project C4 Publications<\/h1><\/div>Publications 2025\n<\/strong>\nSuppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion – PubMed<\/a>\n<\/strong>M. Wende, L. Osbelt, L. Eisenhard, T. R. Lesker, B. F. Damaris, U. Mutukumarasamy, et al. Nat Commun<\/strong> 2025 Vol. 16 Issue 1 Pages 5426 Accession Number: 40593813 PMCID: PMC12215308 DOI: 10.1038\/s41467-025-61327-7\n<\/strong><\/p>\nmicroGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies<\/strong><\/a> J. Burgaya, B. F. Damaris, J. Fiebig and M. Galardini Microb Genom<\/strong> 2025 Vol. 11 Issue 2 Accession Number: 39932497 DOI: 10.1099\/mgen.0.001349<\/p>\n
Assigning a putative function to all the genes encoded in bacterial pangenomes.<\/p>\n<\/div>
We usually think of genetic differences in the context of human genetics. And so we are familiar with the fact that two people differ on average at about five million sites in the genome \u2013 that is, at only about 0.8 per cent of the entire genome. But genetic variation in bacteria has a completely different dimension: For example, two strains of Escherichia coli<\/em> can differ in up to 60 percent of their genetic content.<\/p>\nThis means that each bacterial species has not only a single genome, but also a diverse ensemble of gene combinations called a pangenome. We want to investigate the influence of this great genetic diversity on bacterial phenotypes.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What’s the current status?<\/h1><\/div><\/div><\/div><\/div>Understanding how variations in genotype lead to variations in phenotype is an old topic in molecular biology. We are exploring how to better predict the phenotypic consequences of genetic variants in bacteria. This can be done with a combination of “forward-looking” mechanistic models, and “backward-looking” statistical genomics models.\nCertain bacterial species, such as E.coli<\/em>, have so-called open pangenomes. This means that new genes (“accessory genes”) are discovered when the genomes of new isolates are sequenced. Current functional genomics techniques cannot scale up fast enough to keep up with the flood of genes with unknown function that are being discovered every day.<\/p>\n<\/div><\/div><\/div><\/div><\/span><\/div><\/div>Studying how different bacterial strains adapt to the same selective pressure (e.g. antimicrobials).<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What are the project goals?<\/h1><\/div>Our goal is to develop methods to assign functions to accessory genes by computer. The wealth of data available for different types of bacteria, as well as advances in machine learning, are one possible way to solve this problem. Most importantly, it helps that our lab has access to a large collection of E.coli strains.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>How do we get there?<\/h1><\/div><\/div><\/div><\/div>It has been shown that the genetic variability between bacterial strains also affects genes that are indispensable for growth and reproduction. We suspect that these differences could also influence the ability to adapt to selection pressures, such as the use of antimicrobials. As we explore the influence of bacterial pangenomes on clinically relevant phenotypes, we are also investigating whether different genetic backgrounds make people more or less susceptible to developing antibiotic resistance.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div>Computational and experimental approaches to link genotypic to phenotypic variation.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Projectleader<\/h1><\/div>Project title: Influence of genetic diversity on the bacterial phenotype<\/h4><\/div><\/div><\/div><\/div><\/div><\/div><\/a><\/span><\/div><\/div><\/div><\/div>Prof. Dr. Marco Galardini<\/h3><\/div>Project: C4<\/a><\/h3><\/div><\/div><\/div><\/div>CV & VIDEO<\/span><\/a><\/div><\/div><\/div><\/div>\n<\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Project C4 Publications<\/h1><\/div>Publications 2025\n<\/strong>\nSuppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion – PubMed<\/a>\n<\/strong>M. Wende, L. Osbelt, L. Eisenhard, T. R. Lesker, B. F. Damaris, U. Mutukumarasamy, et al. Nat Commun<\/strong> 2025 Vol. 16 Issue 1 Pages 5426 Accession Number: 40593813 PMCID: PMC12215308 DOI: 10.1038\/s41467-025-61327-7\n<\/strong><\/p>\nmicroGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies<\/strong><\/a> J. Burgaya, B. F. Damaris, J. Fiebig and M. Galardini Microb Genom<\/strong> 2025 Vol. 11 Issue 2 Accession Number: 39932497 DOI: 10.1099\/mgen.0.001349<\/p>\n
This means that each bacterial species has not only a single genome, but also a diverse ensemble of gene combinations called a pangenome. We want to investigate the influence of this great genetic diversity on bacterial phenotypes.<\/p>\n<\/div>
Understanding how variations in genotype lead to variations in phenotype is an old topic in molecular biology. We are exploring how to better predict the phenotypic consequences of genetic variants in bacteria. This can be done with a combination of “forward-looking” mechanistic models, and “backward-looking” statistical genomics models.\nCertain bacterial species, such as E.coli<\/em>, have so-called open pangenomes. This means that new genes (“accessory genes”) are discovered when the genomes of new isolates are sequenced. Current functional genomics techniques cannot scale up fast enough to keep up with the flood of genes with unknown function that are being discovered every day.<\/p>\n<\/div><\/div><\/div><\/div><\/span><\/div><\/div>Studying how different bacterial strains adapt to the same selective pressure (e.g. antimicrobials).<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>What are the project goals?<\/h1><\/div>Our goal is to develop methods to assign functions to accessory genes by computer. The wealth of data available for different types of bacteria, as well as advances in machine learning, are one possible way to solve this problem. Most importantly, it helps that our lab has access to a large collection of E.coli strains.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>How do we get there?<\/h1><\/div><\/div><\/div><\/div>It has been shown that the genetic variability between bacterial strains also affects genes that are indispensable for growth and reproduction. We suspect that these differences could also influence the ability to adapt to selection pressures, such as the use of antimicrobials. As we explore the influence of bacterial pangenomes on clinically relevant phenotypes, we are also investigating whether different genetic backgrounds make people more or less susceptible to developing antibiotic resistance.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div>Computational and experimental approaches to link genotypic to phenotypic variation.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Projectleader<\/h1><\/div>Project title: Influence of genetic diversity on the bacterial phenotype<\/h4><\/div><\/div><\/div><\/div><\/div><\/div><\/a><\/span><\/div><\/div><\/div><\/div>Prof. Dr. Marco Galardini<\/h3><\/div>Project: C4<\/a><\/h3><\/div><\/div><\/div><\/div>CV & VIDEO<\/span><\/a><\/div><\/div><\/div><\/div>\n<\/div><\/div><\/path><\/svg><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Project C4 Publications<\/h1><\/div>Publications 2025\n<\/strong>\nSuppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion – PubMed<\/a>\n<\/strong>M. Wende, L. Osbelt, L. Eisenhard, T. R. Lesker, B. F. Damaris, U. Mutukumarasamy, et al. Nat Commun<\/strong> 2025 Vol. 16 Issue 1 Pages 5426 Accession Number: 40593813 PMCID: PMC12215308 DOI: 10.1038\/s41467-025-61327-7\n<\/strong><\/p>\nmicroGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies<\/strong><\/a> J. Burgaya, B. F. Damaris, J. Fiebig and M. Galardini Microb Genom<\/strong> 2025 Vol. 11 Issue 2 Accession Number: 39932497 DOI: 10.1099\/mgen.0.001349<\/p>\n
Studying how different bacterial strains adapt to the same selective pressure (e.g. antimicrobials).<\/p>\n<\/div>
Our goal is to develop methods to assign functions to accessory genes by computer. The wealth of data available for different types of bacteria, as well as advances in machine learning, are one possible way to solve this problem. Most importantly, it helps that our lab has access to a large collection of E.coli strains.<\/p>\n<\/div><\/div><\/div>
It has been shown that the genetic variability between bacterial strains also affects genes that are indispensable for growth and reproduction. We suspect that these differences could also influence the ability to adapt to selection pressures, such as the use of antimicrobials. As we explore the influence of bacterial pangenomes on clinically relevant phenotypes, we are also investigating whether different genetic backgrounds make people more or less susceptible to developing antibiotic resistance.<\/p>\n<\/div>
Computational and experimental approaches to link genotypic to phenotypic variation.<\/p>\n<\/div>
Publications 2025\n<\/strong>\nSuppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion – PubMed<\/a>\n<\/strong>M. Wende, L. Osbelt, L. Eisenhard, T. R. Lesker, B. F. Damaris, U. Mutukumarasamy, et al. Nat Commun<\/strong> 2025 Vol. 16 Issue 1 Pages 5426 Accession Number: 40593813 PMCID: PMC12215308 DOI: 10.1038\/s41467-025-61327-7\n<\/strong><\/p>\nmicroGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies<\/strong><\/a> J. Burgaya, B. F. Damaris, J. Fiebig and M. Galardini Microb Genom<\/strong> 2025 Vol. 11 Issue 2 Accession Number: 39932497 DOI: 10.1099\/mgen.0.001349<\/p>\n
microGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies<\/strong><\/a> J. Burgaya, B. F. Damaris, J. Fiebig and M. Galardini Microb Genom<\/strong> 2025 Vol. 11 Issue 2 Accession Number: 39932497 DOI: 10.1099\/mgen.0.001349<\/p>\n