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.
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.
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.