Meet the 2025 JCJC laureates

By Yoan Emritloll, Head of National Division - GO 

Dr. Guilherme Dias de Melo and Dr. Anna Zhukova are laureates of the 2025 Young Researchers call for proposals (ANR JCJC) 

What is your background and current research focus?    

Guilherme: I am a veterinarian graduated from the São Paulo State University in Brazil and an associate researcher on the Lyssavirus, Epidemiology, and Neuropathology team at the Pasteur Institute in Paris. I have experience in the pathogenesis of central nervous system infections caused by neglected and emerging pathogens, with training in comparative neuropathology. My research focus is to understand the basis and consequences of neurotropism, which includes viral axonal transport, brain infection, behavioral changes and long-term post-infection sequelae. 

Anna: My initial training is in computer science, software engineering and mathematics. Over the last decade I have been applying these skills to develop mathematical models and tools for analysis of pathogenepidemics, with a particular focus on HIV. The field I am working in is called phylodynamics. It combines pathogen genome data with mathematical modelling to estimate epidemiological parameters, such as the number of secondary infections Re. The advantage of phylodynamics with respect to classical epidemiology is that we can reconstruct pathogen transmission history directly from sequence data without the need of collecting costly and sensitive contact-tracing information. In the era of rapidly growing sequence data, it is particularly pertinent. 

Tell us a bit about your grant: how did it come to fruition and what are the main objectives?   

Guilherme: The N3CoV project is the consequence of the LongNeuroCovid project (2022-2024), that was selected by ANRS-MIE, financed by FRM, and labeled as a National Research Priority by the French National Orientation Committee for Therapeutic Trials and other research on COVID-19 (CAPNET). The LongNeuroCovid project aimed to determine whether SARS-CoV-2 persistence or central nervous system inflammation was the underlying cause of persistent symptoms in patients with long Covid.  

Now, digging into the neuropathogenesis of long Covid, the N3CoV primary goals are more precise. The project aims to understand how infection affects neurogenesis and neuronal communication. Additionally, it seeks to identify the structures and pathways affected by the spread and persistence of SARS-CoV-2 in the brain and to determine how the virus triggers neurodegenerative processes. This project will use cutting-edge techniques, such as microelectrode arrays, microfluidics, and spatial transcriptomics under infectious conditions, to bridge hamster and human biology to identify common molecular signatures and potential therapeutic targets. 

The successful application of the N3CoV is also the result of positive collaboration with Divya Unni from the Grants Office, who supported me throughout the grant-writing process. 

Anna: Since I started working in phylodynamics, I have been fascinated by how much pathogen sequences can tell us about the epidemic spread.  Over the years I have worked on different aspects of several pathogens in different countries. For example, in collaboration with the colleagues from Institut Pasteur and the virologists from Institute of Tropical Medicine Pedro Kourí,  I studied where and when a particular HIV recombinant form was introduced to Cuba and the reasons it became so wide-spread there but not in the rest of the world. Together with the Collaborative HIV, Anti-HIV Drug Resistance Network, we studied the spread of HIV drug resistance in the UK. Our methods can identify and locate the drug resistanceclusters and help target health interventions (e.g., awareness campaigns) towards them.  

However, in the globally connected world of nowadays, focusing on one particular country can be misleading. What prevents us from doing a global analysis are the computational bottlenecks. Current methods are only applicable to datasets of up to thousands of sequences, while orders of magnitude more are available. The goal of the EmPaTHIc project is to break this bottleneck. We will develop new scalable methods and tools and apply them to analyze hundreds of thousands of publicly available HIV sequences. Understanding the factors driving the global and local epidemics’ spread will then help  design – or refine – health policies. 

What are your hopes for the outcomes of this project?    

Guilherme: COVID-19 remains a contemporary global public health issue, with more than 770 million cases reported to date, including more than 7 million deaths in terms of acute infection. Long Covid is a new entity affecting COVID-19 survivors. It is a disabling condition estimated to affect 10-20% of people infected by SARS-CoV-2, which is equivalent to 2 million people in France. Recognizing long Covid as a "real" problem and identifying the ensuing mechanisms would be game-changing for the patients. It would render possible the ‘biological’ classification of this disease, facilitate patient care by the healthcare system, and finally pave the way for biomarkers identification and development of specific treatments. 

Anna: The goal is to develop a novel methodology, then apply it to reconstruct the largest HIV-1 phylogenetic network to date (100s times larger than any existing one). It will permit tracing the virus dispersion between countries over time and identification of its key drivers (risk groups, drug-resistance patterns, migration, etc.) We will compare different countries and track changes over time alongside evolving health policies, pinpointing promising public health approaches.  

This project will highlight how genomic data can inform public health strategies, emphasizing the value of more systematic HIV-1 sequence collection and centralization, which is currently limited in some contexts (e.g., France). Our open-source tools will remain locally installable and available in various formats, enabling researchers with different backgrounds to analyze sensitive data without sharing them externally. 

Finally, the project will train new scientists (PhD and Master’s students) in phylodynamics, mathematical modeling, deep learning, and HIV-1 analysis.