ISABELLE IMBERT’S GROUP

RNA viruses are responsible for many (re-)emerging infectious diseases (Ebola, Zika, Dengue, Coronaviruses…). Unfortunately, most of the time, we have few weapons to fight them, due to a certain lack of detailed knowledge of their propagation cycle. Combining multidisciplinary approaches such as biochemistry, structural biology and cellular biology to artificial intelligence methods, we aim to dissect fascinating RNA virus replication machineries. These data will lay the groundwork for the discovery of new antiviral molecules. Indeed, viral replicases have already proved their worth with, as example, the development of therapies against HIV and HCV.

Reconstitution of the SARS-CoV replicative catalytic core

The successive emergence of three new and highly pathogenic Coronaviruses (CoVs): the Severe Acute Respiratory Syndrome-CoV (SARS-CoV) in 2003, the Middle East Respiratory Syndrome-CoV (MERS-CoV) in 2012 and the SARS-CoV-2, in 2020 reinforces the urgent needs of clinical options. While vaccines against the Covid-19 are available, there is a dearth of antiviral therapeutics. Indeed, an urgent need for therapeutics is amplified by the emerging of variants (e.g. BQ.1.1, XBB) that evade vaccines as well as monoclonal antibodies.

Interestingly, among (+) RNA viruses, coronaviruses stand out as having the largest (~30-kb) single-stranded RNA genome known to date associated paradoxically with low mutations rates. CoVs encode a huge replication/transcription machinery consisting, at least, of 16 viral nonstructural proteins (nsps). Thus, a central question is by which mechanisms, these viruses maintain their astonishingly large RNA genome. In the case of SARS-CoV, we showed that the viral RNA-dependent RNA polymerase (named nsp12) requires a processivity proteins complex formed by 2 other viral proteins (nsp7 and nsp8).

Since then, this property of a processivity factor for the viral RNA polymerase has been extended to all CoVs. Then, we demonstrated that the SARS-CoV polymerase complex in association with the viral nsp14 protein harboring a 3’-5’ exonuclease activity which is able to faithfully replicate its RNA genome.

Model of SARS-CoV processive replication complex

Indeed, this protein complex can selectively excise a misincorporated ribonucleotide at the 3’-end of the nascent RNA. Moreover, the SARS-CoV proofreading machinery is also able to excise erroneous mutagenic nucleotides inserted by the viral polymerase, such Ribavirin (a FDA-approved broad-spectrum antiviral drug). This feature provides part of the explanation for the ineffectiveness of Ribavirin on CoVs-infected patients.

In silico viral propagation modelling from single-cell to tissue
Modelling of complex biological systems is a growing field of research and a valuable tool for public health. Examples of applications include modelling the dynamics of virus transmission, predicting circulating strains in vaccine manufacturing or modelling the occurrence of resistance mutations after treatment with antivirals. We develop an integrative system using artificial intelligence approaches to model viral propagation from cell to tissue. The modeling and simulation theory aims to create a “virtual twin” of a system in order to understand changes, and test dynamic conditions in a risk-free environment. This theory involves two separate activities: (1) Modeling activity focuses on making a representation of a system from an observer’s point of view. It answers all the questions that the observer may have about the structure and function of the system; (2) While the second simulation activity focuses on executing the model to produce its behavior by modifying its inputs and parameters. We choose to use the Discrete Event System Specification (DEVS) formalism; (3) Then, an iterative process is engaged where in silico results are confronted with in vitro and ex vivo experimentations.

Simulation results will provide valuable support for new cutting-edge approaches to accurately analyze transcriptome dynamics at the single-cell level (Single-Cell RNA-Seq) as well as to quantify viruses released at the single-cell resolution (Viro-fluidic method). The latter combines microfluidic and virology at single-cell and single-virus resolutions. Indeed, real-time visualization and quantification of viruses released by a cell are crucial to further decipher infection processes. Kinetics studies at the single-cell level will circumvent the limitations of bulk assays with asynchronous virus replication.

Boundaries and structures prediction of Hepatitis E Virus (HEV) pORF1 polyprotein, forming the RNA genome replication machinery by AlphaFold2
The lack of knowledge of the functional domains of the pORF1 replicase required for HEV replication prevents structural and functional studies, which are essential for the development of specific antivirals. The recent release of the powerful machine-learning protein structure prediction software AlphaFold (AF2) allows to accurately predict the structure of proteins and their complexes. We applied AF2 to the pORF1 polyprotein of HEV (genotype 3) and reliably predicted the boundaries and structures of five domains or nonstructural domains (nsD1 to nsD5) that are interspaced by poorly structured linkers of variable lengths.

Boundaries and structures prediction of HEV pORF1 polyprotein (genotype 3), forming the viral RNA genome replication machinery by AlphaFold2. Five nonstructural domain (nsD) structures are reliably predicted. MTase, methyltransferase; ZnBD, Zinc-binding domain.