Project Areas
Project Area A
Tools for Virus Sequence and Regulation
Project Area A focuses on the development of bioinformatics tools for nucleic acid sequences. This includes tools for assembly, annotation, genomics, alignments, phylogeny, transcriptomics, and optimizing anti-viral RNA sequences. With the explosion of publicly available virus sequence data, there is a pressing need for specialized tools to analyze these vast datasets accurately. General-purpose sequence analysis tools are often insufficient due to the unique characteristics of viruses. Challenges include accurately representing different virus variants (haplotypes), generating genomic multiple sequence alignments, and annotating virus genomes effectively.
We aim to study the host response to viral infections at the transcriptome level and uncover specific signaling pathways for individual viruses. The COVID-19 pandemic has driven efforts to predict the severity of viral infections using machine learning and sequence data, but these efforts have faced challenges and limitations. We aim to develop computational methods that offer a more nuanced and thorough understanding of viruses, bridging the gap between raw sequence data and diagnosis.
A01: Do the shape and size of quasispecies reflect the host range of viruses?
Viruses exist as dynamic populations of closely related viral genomes arising from mutations, known as quasispecies. We hypothesise that viruses use their quasispecies to expand their evolutionary potential, making them critical for adaptation to new hosts and for resistance to host defences or immunity. To address these fundamental questions at the core of our project, we will develop and apply a novel suite of computational tools based on Sequence Variation Graphs (SVGs). SVGs are increasingly utilised for population structure analysis in higher organisms, but their application in virology is limited due to the high mutation rates and genomic diversity of viruses…
Project Leaders
Prof. Dr. Bas E. Dutilh
FSU Jena, Institute of Biodiversity
Viral ecology and omics
Prof. Dr. Kirsten Küsel
FSU Jena, Institute of Biodiversity
Microbial ecology, biodiversity
A02: Phylogeny of functional sequence elements in viral genomes
To date, no standardised, comprehensive tool is available to detect different types of viral FSEs from omics data and analyse their conservation; existing phylogenetics approaches focus only on protein- genes. In this project, we will close this gap by developing tools to identify FSEs that are conserved in sequence and/or structure for (1) reconstructing their evolutionary histories; (2) incorporating them into robust virus phylogenies; and (3) predicting potential functional roles. As recombination is an important evolutionary process that affects many viruses, we will…
Project Leaders
Prof. Dr. Caroline Friedel
LMU Munich, Institute of Informatics
Virus-Host Transcriptomics, novel functional elements in viral genomes, virus annotation and viral RNA decay
Dr. Denise Kühnert
MPI-GEA
Phylodynamics, molecular epidemiology
A03: Detecting time-resolved and virulence-associated host responses to viral infection
Understanding the cell’s transcriptional response to virus infections is crucial for comprehending the host’s molecular defence, the pathogen’s strategies to circumvent these mechanisms, and hence the viral capability to cause severe disease (i.e. their virulence). However, currently available methods are not sufficient to accurately determine the cellular transcription response, especially for viruses that cause a global host cell shut-off. Thus, we aim to develop tools for (i) normalisation of reads to accurately measure the host transcription shut-off imposed by viruses and…
Project Leaders
Prof. Dr. Steve Hoffmann
Leibniz FLI, Jena
Analysis of big and multidimensional biological data sets
Prof. Dr. Friedemann Weber
JLU Giessen, Institute of Virology
RNA viruses, innate immune response
A04: Small RNAs to probe, decode, and optimise phage-host interactions
Regulatory RNAs have emerged as powerful tools in synthetic biology due to their programmability and ability to modulate gene expression with high specificity. Among these, small RNAs (sRNAs) that act through base-pairing interactions offer a versatile platform for controlling molecular processes in both prokaryotic and eukaryotic systems. Indeed, synthetic regulatory RNAs have already shown potential in metabolic engineering, gene regulation, and diagnostics. However, despite their broad regulatory utility, synthetic regulatory RNAs have not yet been broadly applied to antiviral strategies, especially those targeting RNA-RNA interactions relevant during viral infection. In viruses, RNA structures and RNA-mediated gene regulation are closely linked to replication and host manipulation, making them attractive targets for RNA-based interference. However, rationally designing effective synthetic RNAs remains a major challenge due to the complexity of RNA folding, target recognition, and the dynamic nature of virus host interactions. Recent advances in the design of synthetic regulatory RNAs and machine learning, particularly neural networks (NN), now offer a path towards predictive modelling of these interactions. Furthermore, integrating experimental feedback into model training holds promise for accelerating the design-test-learn cycle of the synthetic biology toolbox. In this project, we aim to close this gap by systematically and adaptively optimising antiviral RNAs that target viral and/or host RNAs that are required for virus infection and replication…
Project Leaders
Prof. Dr. Manja Marz
FSU Jena, Institute for Computer Science
Virus bioinformatics, RNA bioinformatics, HTS data analysis
Prof. Dr. Kai Papenfort
FSU Jena, Institute for Microbiology
Microbial gene regulation
Project Area B
Tools for Virus Interaction and Structure
Project Area B focuses on developing bioinformatics tools for viral structures, interactions, and functions, such as the identification of novel virus-specific metabolites, RNA secondary structures, structural drug design, surveillance, and structural network components. VirusREvolution aims to complement genomic and transcriptomic data with structural information to gain a comprehensive understanding of viruses. Four types of structural tools are being developed:
- A tool for chemical structures and small molecules.
- A tool for RNA secondary structures.
- A tool for protein 3D structures.
- A tool for computational structures for surveillance and modeling of viruses and their evolution.
By combining these different types of data, the project seeks to provide a holistic view of viruses and their interactions with hosts, including various omics data such as transcripts, metabolites, and proteins. The project recognizes that even subtle changes in RNA or DNA sequences, or in metabolite or protein structures, can lead to significant changes in the virus’s behavior and phenotype. For instance, minor chemical modifications can drastically alter the perception of smells or the binding of small molecules to sensory neurons.
A01: Do the shape and size of quasispecies reflect the host range of viruses?
Prof. Dr. Manja Marz
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A02: Important Research
Prof. Dr. Manja Marz
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A03: Another round of important research
Prof. Dr. Manja Marz
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A04: Very important research
Prof. Dr. Manja Marz
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Project Area C
Tools for Virus Visualization and Morphology
Project Area C focuses on developing photonic instrumentation to directly visualize and morphologically characterize viruses, as well as screen and sort for viral properties. The need for direct visualization of viruses and the observation of their molecular details has become increasingly apparent, especially in the context of antiviral research. Recent developments in observation technologies, such as electron microscopy (EM), super-resolution optical microscopy (SRM), and near-field microscopy, have enabled the characterization of individual viruses at nanometer-scale resolution. These advancements are supported by the growing capabilities of computer technology and artificial intelligence algorithms for analyzing microscopy data efficiently. However, these techniques are complex, often require specific protocols, and may not offer sufficient information.
There is a pressing need for simplifying the technology, potentially through label-free approaches and multimodal readouts. Techniques like transmission microscopy and Raman spectroscopy have shown potential for characterizing cellular infections but are limited by spatial resolution and specificity. Advanced data analysis methods involving artificial intelligence algorithms, multimodal and super-resolution microscopy approaches, and near-field techniques like tip-enhanced Raman spectroscopy have shown promise but require further optimization.
The development of multimodal and cost-effective instrumentation is expected to pave the way for efficient characterization and differentiation of vital viral properties, particularly infectivity, and for sorting viruses based on these properties.
A01: Do the shape and size of quasispecies reflect the host range of viruses?
Prof. Dr. Manja Marz
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A02: Important Research
Prof. Dr. Manja Marz
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A03: Another round of important research
Prof. Dr. Manja Marz
Enter Abstract Text Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat. Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi.
A04: Very important research
Prof. Dr. Manja Marz
Enter Abstract Text Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat. Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi.