applied microbiology research lab

Our Applied Microbiology Research Group focuses on the integration of genomics, metagenomics, proteomics and machine learning to understand and combat infectious diseases. We are driven by key questions such as:

• How can genomics enhance pathogen surveillance? 
• What bioinformatics solutions can bridge the gap between research and clinical microbiology? 
• How can AI-driven diagnostics advance early detection and treatment of multi-drug resistant and hypervirulent infections?

Through our diverse projects, we aim to improve molecular surveillance, optimize rapid diagnostics for resistant pathogens, and advance pathogen screening methods. Our research spans public health surveillance, evolution of antimicrobial resistance, zoonotic transmission, and machine learning applications in MALDI-TOF MS for high-resolution bacterial identification. Collaborating within Switzerland and globally, we aim to support clinical decision-making and public health interventions with cutting-edge scientific innovation.

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Our group is participating and co-developing in the Swiss Pathogen Surveillance Platform (www.SPSP.ch) to enhance the understanding of pathogen spread and transmission using genomics. Our validated IMM bioinformatic pipeline “IMMense” has been adapted and implemented at SPSP. We aim to optimize sequencing with for instance, an evaluation of the impact of sequencing efforts on surveillance outcomes for the SARS-CoV-2 pandemic. In addition, we also focus on improving and standardizing sequencing for molecular surveillance with external quality assessments.

Keywords: Pathogen Genomics, Surveillance, Data Analysis, Public Health

Key literature:

• How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort
  Wegner F et al., Microbiology Spectrum (2024)
• The Swiss Pathogen Surveillance Platform - towards a nation-wide One Health data exchange platform for bacterial, viral and fungal genomics and associated metadata
  Neves A et al., Microbial Genomics (2023)
• Investigation of an international water polo tournament in Czechia as a potential source for early introduction of the SARS-CoV-2 Omicron variant into Belgium, Switzerland and Germany, November 2021
  Rudin C et al., Eurosurveillance (2023)
• External Quality Assessment of SARS-CoV-2 Sequencing: an ESGMD-SSM Pilot Trial across 15 European Laboratories
  Wegner F et al., Journal of Clinical Microbiology (2022)
   

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Metagenome analysis for clinical microbiology applications

We apply rapid Oxford Nanopore sequencing technology to metagenomic sample types such as blood and stool for pathogen detection with associated predictions of AMR and invasiveness potential. This work aims to translate bioinformatics for the clinical microbiology lab through the development of easy-to-use sequence analysis pipelines and the identification of diagnostic and prognostic markers of disease.  

Keywords: Clinical microbiology, metagenomics, Nanopore sequencing 

MDR Pathogen Screening

Implementing rapid long-read shotgun metagenomic sequencing using the Oxford Nanopore Technology to diagnose multi-drug-resistant pathogens in a culture-independent manner. Aiming to reduce diagnosis turnaround time and contribute to long-term patient surveillance. 

Keywords: Pathogen Screening, Metagenomic Sequencing, Rapid Diagnosis, Drug Resistance  

Funding: https://data.snf.ch/grants/grant/192515, Bangerter Rhyner Foundation 

Key literature:

• Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics Purushothaman S et al., International Journal of Molecular Sciences (2022) 

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AMR evolution in the human gut microbiome

This large-scale project aims to uncover the dynamics of antimicrobial resistance (AMR) in stool samples and dissect factors influencing AMR evolution on single strain levels of E. coli and other bacteria. It uses samples from our unique patient cohort of stem cell transplantation recipients prone to Graft-vs-Host disease. Combining clinical data, diagnostics, and bioinformatics to enhance understanding and improve clinical decisions.  

Keywords: AMR Evolution, Gut Microbiome, Bioinformatics 

Funding: https://data.snf.ch/grants/grant/10001529; PHRT PhD student funding, Bangerter Rhyner Foundation 

Key collaborators: 

• Prof. Jörg Halter, University Hospital Basel 
• Prof. Simon Müller, University Hospital Basel 
• Prof. Nicholas Bokulich, ETH Zurich 
• Prof. Shana Sturla, ETH Zurich 

Key literature:  

• ESBL Displace: A Protocol for an Observational Study to Identify Displacing Escherichia coli Strain Candidates from ESBL-Colonized Travel Returners Using Phenotypic, Genomic Sequencing and Metagenome Analysis. Schweitzer, M. et al., Microbiology Research (2023) 

Development of a predictive computational model of microbial community dynamics after antibiotic perturbations from pairwise bacterial interactions 

Based on systematic pairwise interactions between intestinal commensals and pathogens, a computational model will be developed to predict community dynamics following antibiotic perturbations. By further studying the expression of antimicrobial resistance (AMR) genes, the project aims to integrate the influence of the microbial community on AMR and understand the conditions that favor pathogen overgrowth. 

Keywords: Bacterial Interactions, Synthetic Gut Community,  AMR expression, Computational Biology, Transcriptomics 

Funding: https://data.snf.ch/grants/grant/10001529; PHRT PhD student funding, Bangerter Rhyner Foundation 

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Linking dog and cat oral bacteria to human health. In this collaborative project, we collect Capnocytophaga strains from patients and pets across the globe. Using state-of-the-art genomics and multi-omics approaches, we will take a closer look at the pathogen evolution and virulence of these rare zoonotic bacteria. To do this we have formed the Global Capnocytophaga Consortium. 

Keywords: Zoonotic Pathogen, Genomics, Bacterial Virulence

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Prediction of bacterial virulence and invasiveness from MALDI-TOF MS

Combining MALDI-TOF MS mass spectra with machine learning and bacterial genome-wide association studies. Our objective is to develop a diagnostic approach for early bacterial virulence risk assessment to complement AMR profiling, ultimately supporting clinical decision making and promoting antibiotic stewardship. Further, we aim to discover novel biomarkers with potential for research and the diagnostic industry.

Keywords: MALDI-TOF MS, Bacterial Virulence, Machine Learning, Clinical Decision-Making

Funding: https://data.snf.ch/grants/grant/213019

Key literature:​

• Bacterial genome-wide association study substantiates papGII of Escherichia coli as a major risk factor for urosepsis
  Cuénod A et al., Genome Medicine (2023)
• Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning
  Weis C et al., Nature Medicine (2022)
• Whole-genome sequence-informed MALDI-TOF MS diagnostics reveal importance of Klebsiella oxytoca group in invasive infections: a retrospective clinical study
  Cuénod A et al., Genome Medicine (2021)

Machine learning in MALDI-TOF MS

Focusing on the enhancing MALDI-TOF MS analysis for improved species identification of bacteria by integrating machine learning techniques. This project aims to boost the resolution and accuracy of MALDI-TOF MS for species identification and generate a new type of database.

Keywords: MALDI-TOF MS, Machine Learning, Bacterial Identification

Funding: https://data.snf.ch/grants/grant/213019

Key literature:

• Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning
  Weis C et al., Nature Medicine (2022)
• Factors Associated With MALDI-TOF Mass Spectral Quality of Species Identification in Clinical Routine Diagnostics
  Cuénod A et al., Frontiers in cellular and infection microbiology (2021)

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In order to manage the many studies and associated samples, our technical team supports the group with sample registration, aliquoting and biobank management. The team also performs DNA extraction, PCRs, and 16S RNA sequencing. 

Keywords: Biobanking, Teamwork, Study Management

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Impact of Interferon lambda signaling on B-cell functions

In this SNF Ambizione funded project, we explored the impact of Interferon lambda on B-cell functions, especially in the context of influenza vaccination in immunosuppressed patients. We determined the specific gene expression patterns induced by Interferon lambda in synergy with IgM driven stimulation (PhD thesis, Mohameedyaseen Syedbasha). In a SystemsX funded iPhD project, we used mathematical modelling to understand the humoral immune response induced by influenza vaccination in more detail (PhD thesis, Janina Linnik).

Humoral immunity to pathogens

Flu vaccination significantly reduces the burden of influenza infection in a population. In certain risk groups, however, vaccination success is limited. In two large independent SNF-funded multi-center studies, we are measuring the pre- to post-vaccine humoral immune response towards influenza vaccination, and  have established a protocol to determine haemagglutination inhibition assays (paper Kaufmann L et al.). The immune response is correlated to clinical factors such as degree of immunosuppression but also to genotypic variants in genes modulating the B-cell functionality. We also use computational modelling to understand the factors influencing the immune response.

Projects include:

• Cohort of solid organ transplant recipients vaccinated against influenza (STOP-FLU trial, SNF IICT grant)
• Cohort of hematopoietic transplant recipients vaccinated against influenza (SNF Ambizione grant)

Transmission of bacterial pathogens

In various projects, we have described: 

• a Switzerland-wide nosocomial outbreak of Burkholderia stabilis
• an outbreak of Methicillin-resistant Staphylococcus aureus in refugees
• an outbreak of Vancomycin resistant Enterococcus in the region of Bern
• new species e.g. Mycobacterium basiliense
• Corynebacterium diphtheriae in refugees
• an outbreak of Legionella pneumophila showing links to air-conditioner cooling towers
• unusual cases including Blastobotrys raffinosifermentans
• Shigella sonnei as a sexually transmitted pathogen
• molecular epidemiological links of Campylobacter spp. isolates from human infections, chicken meat and environmental samples (in preparation, Seth-Smith HMB et al.)
• ongoing evolution of Chlamydia trachomatis LGV (in preparation, Seth-Smith HMB et al.)