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Noémie Lefrancq @noemielefrancq.bsky.social · Jul 3

For the first time, we found phylogenetic evidence of importations and local transmission of Macrolide-resistant #pertussis strains in France. Needs further monitoring!

Great work led by Valérie Bouchez, Carla Rodrigues and @sylvainbrisse.bsky.social!

Paper: shorturl.at/2Npmm

🦠 🧪 🛟

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Reposted by Noémie Lefrancq

Cécile Tran Kiem @ceciletk.bsky.social · Mar 5

Pathogen genomes can provide insights into underlying disease transmission patterns but new methods are needed to analyze large genome datasets. Our work using identical pathogen sequences to characterize fine scale SARS-CoV-2 transmission was just published in @nature.com tinyurl.com/bdzk9xjj 🥳

Fine-scale patterns of SARS-CoV-2 spread from identical pathogen sequences - Nature

The analysis of pairs of identical SARS-CoV-2 genome sequences enables characterization of transmission patterns between geographies and age groups.

tinyurl.com

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Reposted by Noémie Lefrancq

Moritz Kraemer @mugkraemer.bsky.social · Feb 20

AI is poised to accelerate understanding in infectious diseases, but its value needs to be demonstrated through close collaboration between research, industry, society, and policy.

Paper free to read: rdcu.be/eaxEw

Summary here: www.ox.ac.uk/news/2025-02...

Artificial intelligence for modelling infectious disease epidemics

Nature - This Perspective considers the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science.

rdcu.be

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 31

Thanks!

Reposted by Noémie Lefrancq

Richard Neher @neher.io · Jan 11

Building on the UShER tree of millions of SARS-CoV-2 genomes maintained by Angie Hinrichs, Hugh Haddox and Georg Angehrn (and others in @matsen.bsky.social lab and @jbloomlab.bsky.social) have looked into how the neutral mutation rate varies along the genome:

[1/N]

www.biorxiv.org/content/10.1...

The mutation rate of SARS-CoV-2 is highly variable between sites and is influenced by sequence context, genomic region, and RNA structure

RNA viruses like SARS-CoV-2 have a high mutation rate, which contributes to their rapid evolution. The rate of mutations depends on the mutation type (e.g., A→C, A→G, etc.) and can vary between sites ...

www.biorxiv.org

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 9

Yes, but the method will even go beyond simply MDR/non-MDR and find what precise clades are spreading differently in your population. That's exactly what we did in the paper for the dataset of Samara, Russia.

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Reposted by Noémie Lefrancq

Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Incredibly excited to share that our manuscript was just published in @nature.com ! What a way to start the new year! 🎉
https://buff.ly/4gyYCzx

We present phylowave, a framework that enables to learn the fitness dynamics of pathogens from phylogenies.

🧵 A thread... 1/n
#IDSky #IDModelling

Learning the fitness dynamics of pathogens from phylogenies - Nature

Phylowave, an innovative phylogenetic approach, can identify the main circulating pathogen lineages with increased fitness and the associated genetic changes, enabling the timely identification of…

buff.ly

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Reposted by Noémie Lefrancq

Prof Sam Illingworth @samillingworth.com · Jan 3

🦠🔍 Tracking Pathogen Evolution in Real Time

A new tool, 'phylowave', has been developed to help scientists track how viruses and bacteria evolve. It identifies new variants with increased fitness, offering insights into diseases like #COVID19 and flu.

🔗 www.nature.com/articles/s41...

#SciComm 🧪

Learning the fitness dynamics of pathogens from phylogenies - Nature

Phylowave, an innovative phylogenetic approach, can identify the main circulating pathogen lineages with increased fitness and the associated genetic changes, enabling the timely identification of eme...

www.nature.com

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

I am now working @ethzurich.bsky.social @ETH_BSSE with @tanjastadler.bsky.social and @neher.io with an ETH fellowship to develop more phylodynamic frameworks for large-scale datasets. Very excited to start this new year! 13/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Developing this was a journey! Many thanks to the people who helped me along the way! Loréna Duret, super master student, my supervisors @hsalje.bsky.social and @julianparkhill.bsky.social and colleagues at Institut Pasteur @sylvainbrisse.bsky.social Valérie Bouchez. 12/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Phylowave code is available on GitHub. While it is not packaged, it comes with a full readme and description of best practices. All you need to start is R and a timed phylogeny. If you have any questions or suggestions, feel free to open an issue/drop me a message! 11/n
https://buff.ly/3PEj32l

GitHub - noemielefrancq/Phylowave_Learning-fitness-dynamics-pathogens-in-phylogenies: Code for the paper "Learning the fitness dynamics of pathogens from phylogenies"

Code for the paper "Learning the fitness dynamics of pathogens from phylogenies" - noemielefrancq/Phylowave_Learning-fitness-dynamics-pathogens-in-phylogenies

github.com

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Importantly, phylowave is robust to uneven and limited observation. For example, we tested the framework on subsampled SARS-CoV-2 phylogenies of only 150 sequences and were still able to detect nearly all the lineages.

This makes phylowave applicable to a wide range of pathogens! 10/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

We tested phylowave using a simulation study. Its ability to recover lineages depends on the time between emergence and the dates of sequences, with lineages with only small fitness advantages requiring sequences covering longer time periods, as expected. 9/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

We show we can quantify the relative fitness of each lineage and identify genetic changes linked to the emergence of new, fitter lineages. This provides testable biological hypotheses about genetic variants in each pathogen that are driving the changes in population fitness of that pathogen. 8/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

We compared our lineage assignments with existing lineage definitions. We show we can recover the main known circulating lineages for each pathogen, as well as identify new lineages. For ex., phylowave detects three B. pertussis lineages with distinct index dynamics, not previously identified. 7/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

We applied phylowave to a broad set of viruses and bacteria: SARS-CoV-2, H3N2 influenza, Bordetella pertussis (bacterium causing whooping cough) and Mycobacterium tuberculosis. 6/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

We implemented a tree partitioning algorithm using generalised additive models that finds the set of lineages (i.e., groups of tips and nodes) that best explains the observed index dynamics. It allows for the automatic detection of circulating lineages based on differences in fitness. 5/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

The index is based on the expectation that nodes sampled from an emerging fitter lineage will be phylogenetically closer than the rest of the population at that time. Mathematically, we expect emerging fitter lineages to have different index dynamics than the rest of the population. 4/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Phylowave enables to scan time-resolved phylogenies and sheds light on changes in population composition. It works by assigning an epidemic success index to each node (internal or terminal).

Here is an example on a SARS-CoV-2 phylogeny from nextstrain, coloured by nextstrain clades. 3/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Existing methods to monitor the fitness of strains at the population level rely on pre-defined clade definitions, unlinked to underlying differences in fitness. We developed phylowave to tackle this issue and automatically detect lineages based on shared fitness and evolutionary relationships. 2/n

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Noémie Lefrancq @noemielefrancq.bsky.social · Jan 2

Incredibly excited to share that our manuscript was just published in @nature.com ! What a way to start the new year! 🎉
https://buff.ly/4gyYCzx

We present phylowave, a framework that enables to learn the fitness dynamics of pathogens from phylogenies.

🧵 A thread... 1/n
#IDSky #IDModelling

Learning the fitness dynamics of pathogens from phylogenies - Nature

Phylowave, an innovative phylogenetic approach, can identify the main circulating pathogen lineages with increased fitness and the associated genetic changes, enabling the timely identification of…

buff.ly

3 87 220

Noémie Lefrancq @noemielefrancq.bsky.social · Dec 16

Congratulations Charlotte!

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Reposted by Noémie Lefrancq

Zannah Salter @zannahdu.bsky.social · Dec 2

* rolls up newspaper *
No Guardian! Bad Guardian! An infection is not a microbiome! www.theguardian.com/lifeandstyle...

The brain microbiome: could understanding it help prevent dementia?

Long thought to be sterile, our brains are now believed to harbour all sorts of micro-organisms, from bacteria to fungi. How big a part do they play in Alzheimer’s and similar diseases?

www.theguardian.com

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Reposted by Noémie Lefrancq

Conrad Hackett @conradhackett.bsky.social · Nov 15

Disease prevalence in US states before & after vaccine introduction

Graphic from Edward Tufte
More graphics.wsj.com/infectious-d... 🧪

Graphic shows dramatic reduction in polio, rubella, mumps, measles, and hepatitis A cases after the introduction of vaccines for each disease.

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Noémie Lefrancq @noemielefrancq.bsky.social · Nov 25

Super resource to explore publicly available genome sequencing data! Currently supports H5N1, West Nile, RSV-A, RSV-B and SARS-CoV-2
GenSpectrum.org
#IDSky

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