Clinical Metagenomik

The Department of Viral Genomics at LIV has established a comprehensive pathogenomics platform for the data-driven identification, functional analysis, and molecular epidemiological tracking of infectious agents. In close collaboration with clinical partners at UKE, the platform is continuously being developed to address key challenges in modern healthcare more effectively in the future.

In addition to its application in the molecular surveillance of infectious agents—such as SARS-CoV-2 during the recent pandemic through the HHSurv program—we routinely use the platform to investigate complex clinical cases. These cases primarily involve critically ill patients receiving intensive care treatment. In such situations, we employ metagenomic diagnostic approaches to enable the rapid and comprehensive identification of infectious agents.

Unlike conventional diagnostic methods, which specifically target individual known pathogens, metagenomic diagnostics follows an agnostic approach that allows the simultaneous detection of viruses, bacteria, fungi, and parasites within a single analysis. Based on high-throughput sequencing, the method aims to comprehensively and unbiasedly characterize all genetic material present in a clinical sample. The resulting datasets are subsequently screened to identify clinically relevant pathogens. By combining complementary bioinformatic approaches—including k-mer–based classification, reference genome mapping, and de novo assembly followed by database comparison—both the sensitivity and specificity of agnostic pathogen detection are substantially improved.

Furthermore, the platform integrates methods for the detection of highly divergent as well as currently unknown pathogens. This approach is based on comprehensive sequence comparisons within patient cohorts, for example among outbreak-associated samples. As a result, it operates entirely independently of external databases and can, in principle, detect pathogens that exhibit no similarity to any previously known infectious agents.

The existing platform provides the foundation for the development of a future-proof, data-driven framework for infectious disease diagnostics. Key challenges include the enormous volume of sequencing data and the need to distinguish clinically relevant signals from background noise while ensuring rapid and resource-efficient data processing. As part of the platform’s ongoing development, we are therefore integrating artificial intelligence and advanced machine-learning approaches for the automated prioritization of potential pathogens, the incorporation of clinical context information, and the prediction of the pathogenic relevance of previously unknown sequences.

The availability of state-of-the-art infrastructure within LIV’s High-Throughput Sequencing and Scientific Computing technology platforms, together with the close integration of LIV and the University Medical Center Hamburg-Eppendorf (UKE), provides essential prerequisites for the further development and clinical implementation of metagenomic diagnostics.

By combining life sciences, digital technologies, and artificial intelligence to improve healthcare and strengthen pandemic preparedness and outbreak response, LIV’s pathogenomics platform directly addresses key objectives of Germany’s High-Tech Strategy.