Speech can propagate pathogens

Speech is a potent route for viral transmission in the COVID-19 pandemic. Informed mitigation strategies are difficult to develop since no aerosolization mechanism has been visualized yet in the oral cavity nor has the relationship of speech to the exhaled flow been documented. In two recent studies, Manouk Abkarian together with Prof. Howard A. Stone from Princeton University in the USA have explored with high-speed imaging how phonation of common stop-consonants like 'P' or 'B', form and extend salivary filaments in a few milliseconds as moist lips open or when the tongue separates from the teeth. Both saliva viscoelasticity and airflow associated with the plosion of stop-consonants are essential for stabilizing and subsequently forming centimeter-scale thin filaments, tens of microns in diameter, that break into speech droplets [1] (see Figure A).

In collaboration with Simon Mendez from the university of Montpellier, these researchers showed that these plosive consonants induce starting jets and vortex rings that drive meter-long transport of exhaled air, tying this drop-formation mechanism to transport associated with speech [2]; the transport features, including phonetics, are demonstrated using order-of-magnitude estimates, numerical simulations, and laboratory experiments (see Figure B). These authors believe that these works will inform thinking about the role of ventilation, aerosol transport in disease transmission for humans and other animals, and yield a better understanding of ''aerophonetics.''

This research is being continued with the Metropolitan Opera Orchestra ("MET Orchestra") in New York, as part of a project to identify the safest conditions for continuing this prestigious orchestra's activity (Figure C).

[1] Speech can produce jet-like transport relevant to asymptomatic spreading of virus. M. Abkarian, S. Mendez, N. Xue, F. Yang, H. A. Stone, Proceedings of the National Academy of Sciences, le 25 septembre 2020 DOI : https://doi.org/10.1073/pnas.201215611710.1073/pnas.2012156117

[2] Stretching and break-up of saliva filaments during speech: a route for pathogen aerosolization and its potential mitigation. M. Abkarian, H. A. Stone, Physical Review Fluids, le 2 octobre 2020 DOI: https://doi.org/10.1103/PhysRevFluids.5.102301

Abkarian speech2

Figure (A) Close up of a mouth saying 'Pa'. (B) Average Flow Velocity indicating a conical jet-like structure when saying 'Peter Piper picked a peck', (C) CO2 exhaled air flow from a Mezzo Soprano Singer singing 'Oror' an Armenian Lullaby.


External links

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Intagram with the MET Orchestra

How chemical pollutants can become more harmful when combined

So-called endocrine disruptors — environmental pollutants that can cause reproductive, metabolic, or neurological disorders — target the pregnane X receptor (PXR), a nuclear receptor unique for its sensitivity to a wide range of compounds. Recent studies have demonstrated that PXR, in its heterodimeric form with the retinoid X receptor (RXR), can mediate both harmful effects in response to xenobiotics, although the mechanisms by which pollutants activate PXR are still being investigated. Vanessa Delfosse, Tiphaine Huet, Deborah Harrus, Meritxell Granell, Maxime Bourguet, et al. utilize cell-based, biophysical, structural, and in vivo approaches to identify novel mixtures of chemicals, whose constituents have low individual affinity for PXR but combine synergistically to robustly activate the receptor. As an extension of their previous work, which showed that binary cocktails of xenobiotics synergistically activate RXR–PXR, the authors describe previously unreported binding mechanisms, substantiating the versatility of PXR's ligand binding domain and the receptor's role in sensing a diverse array of chemicals. Furthermore, the study shows that environmental compounds targeting RXR can boost the activity of two synergizing PXR ligands. The findings suggest that certain chemicals such as endocrine disruptors or pharmaceuticals, at levels deemed individually safe, can potentially interact synergistically and disrupt critical cell signaling.

Cocktail Perturb Endoc2

Inserm press release:

Link to the article: https://www.pnas.org/content/118/1/e2020551118

Quantifying ribosome traffic from profiling data

A non-equilibrium analysis model was developed for inferring the relative rates of translation initiation and elongation rates from ribosome profiling data.

One of the greatest challenges in modelling mRNA translation is to identify coding sequence features determining protein synthesis rates. Recent technical advances such as ribosome profiling allow probing translation at codon resolution, and make quantitative studies of transcript efficiency more accessible. We have developed a method called NEAR that integrates experimental ribosome profiling data and a well known non-equilibrium model of ribosome traffic. Our approach provides biological insights of traffic control and infers the kinetics of ribosomes on each transcript. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.



Reference: Juraj Szavits-Nossan & Luca Ciandrini. Inferring efficiency of translation initiation and elongation from ribosome profiling. Nucleic Acids Res, 2020



Programming history-dependent logic in cellular populations

Genetic programs operating in a history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities.

In this paper, researchers from the synthetic biology group at the CBS implemented robust, and scalable history-dependent programs by distributing the computational labor across a cellular population. The group also developed automated workflows that researchers can use to streamline program design and optimization.

These history-dependent cellular programs will support many applications using cellular populations for material engineering, biomanufacturing, and healthcare.

These results have been published in Nature Communications. Together with a 'Behind the paper' blog post shared in Nature Bioengineering Community.


link to the paper:


link to the blog post:


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