Biology subjects

Brun, P.

Publications and source records attributed to Brun, P..

8 recordsLinked to original sources

bioRxiv2024

Low Intestinal Doses of Botulinum Neurotoxins types A and B favour infection by Salmonella and Shigella without the flaccid paralysis of botulism

Botulism is a life-threatening disease characterized by a descending flaccid paralysis caused by a protein neurotoxin (BoNT) released by different anaerobic bacterial species of the genus Clostridium. The paralysis results from blockade of neurotransmitter release from the terminals of peripheral cholinergic, skeletal and autonomic neurons exerted by BoNT through the cleavage of SNARE proteins, which are essential for neuroexocytosis. Here, we investigated the effect of different doses of BoNT serotypes A and B, the serotypes most commonly associated with human botulism, on enteric nervous system neurons which play an important role in gut health and physiology. We found that BoNT/A and BoNT/B enter cholinergic neurons where they cleave SNARE proteins even at doses that do not cause signs of flaccid neuroparalysis. However, these low BoNT doses favour the invasion and infection of the mouse body by Salmonella thyphimurium and Shigella flexneri. This may have significant animal health implications.

neuroscience↗

bioRxiv2024

Comparative CNS Pharmacology of the Brutons Tyrosine Kinase (BTK) Inhibitor Tolebrutinib Versus Other BTK Inhibitor Candidates for Treating Multiple Sclerosis.

Tolebrutinib is a covalent BTK inhibitor designed and selected for potency and CNS exposure to optimize impact on BTK-dependent signaling in CNS-resident cells. We applied a translational approach to evaluate three BTK inhibitors in Phase 3 clinical development in MS with respect to their relative potency to block BTK-dependent signaling and exposure in the CNS, employing in vitro kinase, cellular activation assays, and pharmacokinetic sampling of cerebrospinal fluid (CSF) in the non-human primate cynomolgus to estimate the ability of these candidates (evobrutinib, fenebrutinib, and tolebrutinib) to block BTK-dependent signaling inside the CNS. In vitro kinase assays demonstrated that tolebrutinib reacted with BTK 65-times faster than evobrutinib, while fenebrutinib, a classical reversible antagonist with a Ki value of 4.7 nM and slow off-rate (1.54 x 10-5 s-1), also had an association rate 1760-fold slower (3.28 x 103 M-1 * s-1). Estimates of cellular potency were largely consistent with the in vitro kinase assays, with an estimated IC50 of 0.7 nM for tolebrutinib against 34.5 nM for evobrutinib and 2.9 nM for fenebrutinib. We then observed that evobrutinib, fenebrutinib, and tolebrutinib achieved similar levels of exposure in non-human primate CSF after oral doses of 10 mg/kg. However, tolebrutinib CSF exposure (4.8 ng/mL) (kp,uu CSF=0.40) exceeded the IC90 (the estimated concentration inhibiting 90% of kinase activity) value, while evobrutinib (3.2 ng/mL) (kp,uu CSF=0.13) and fenebrutinib (12.9 ng/mL) (kp,uu CSF=0.15) failed to reach the estimated IC90 values. We conclude that tolebrutinib is the only candidate that attained relevant CSF exposure in non-human primates. DISCLOSURESTT, PB, DO: Employees of Sanofi (may hold shares and/or stock options in the company). RGnone.

pharmacology and toxicology↗

bioRxiv2024

Evaluation of Autophagy in conjunctival fibroblasts

Vernal keratoconjunctivitis (VKC) is a serious eye allergy characterized by poorly understood pathogenic mechanisms and a lack of effective treatments. Autophagy, a process involved in both triggering and suppressing immune and inflammatory responses, plays a role in VKCs pathophysiology. Understanding autophagys involvement in VKC could lead to new treatment possibilities, such as utilizing specific topical substances to induce or inhibit autophagy and prevent severe complications of this eye condition. In our current protocol, we present a robust methodology established in our laboratory for studying autophagy in primary conjunctival fibroblasts. We assess autophagy through techniques like immunocytochemistry, immunoblotting, and qPCR.

cell biology↗

bioRxiv2023

Rank-based deep learning from citizen-science data to model plant communities

In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. We show that recasting multispecies distribution modeling as a ranking problem allows analyzing ubiquitous citizen-science observations with unprecedented efficiency. Based on 6.7M observations, we jointly modeled the distributions of 2477 plant species and species aggregates across Switzerland, using deep neural networks (DNNs). Compared to commonly-used approaches, multispecies DNNs predicted species distributions and especially community composition more accurately. Moreover, their setup allowed investigating understudied aspects of ecology: including seasonal variations of observation probability explicitly allowed approximating flowering phenology, especially for small, herbaceous species; reweighting predictions to mirror cover-abundance allowed mapping potentially canopy-dominant tree species nationwide; and projecting DNNs into the future allowed assessing how distributions, phenology, and dominance may change. Given their skill and their versatility, multispecies DNNs can refine our understanding of the distribution of plants and well-sampled taxa in general.

ecology↗

bioRxiv2022

Strategies for sampling pseudo-absences for species distribution models in complex mountainous terrain

O_LIPredictions from species distribution models (SDMs) that rely on presence-only data are strongly influenced by how pseudo-absences are derived. However, which strategies to generate pseudo-absences give rise to faithful SDMs in complex mountainous terrain, and whether species-specific or generic strategies perform better remain open questions. C_LIO_LIHere, across 500 plant species, we investigated comprehensively how predictions of SDMs at a 93 m spatial resolution are influenced by pseudo-absence strategies, using the complex topography of the Swiss mountains as a model system. We used five generic (random, equal-stratified, proportional-stratified, target, density) and three species-specific (target specific, density specific and geographic specific) approaches to derive pseudo-absence data. We conducted performance tests for each of our eight strategies in combination with (a) spatial bias, generated within our occurrence dataset on sites with highest sampling density, to investigate how this common bias problem influences the performance of pseudo-absence sampling strategies, and (b) a new approach to reduce model extrapolation in environmental space by including background data from all environmental conditions of the study area. SDMs were evaluated against an independent and well-sampled dataset of true presences and absences. C_LIO_LIThe random, the density (generic), and the geographic specific (species-specific) strategies consistently performed best, even in cases of strong spatial sampling bias in the occurrence data. Including a background of environmentally stratified pseudo-absences improved predictions of species distributions towards environmental extremes, and significantly reduced spatial extrapolations of model predictions in environmental space. C_LIO_LIOur results indicate that both generic and species-specific pseudo-absence strategies allow estimating robust SDMs and we provide clear recommendations which strategies to choose in complex terrain and when presence data are prone to high sampling bias. In datasets with strong sampling bias, most pseudo-absence strategies produce extrapolation problems and we additionally recommend environmentally stratified pseudo-absences in these cases. Overall, in species rich datasets the use of complex and computationally demanding, species-specific pseudo-absence strategies may not always be justified compared to simpler generic approaches. C_LI

ecology↗

bioRxiv2021

A novel effective live-attenuated human metapneumovirus vaccine candidate produced in the serum-free suspension DuckCelt-T17 cell platform

Human metapneumovirus (HMPV) is a major pediatric respiratory pathogen for which there is currently no specific treatment or licensed vaccine. Different strategies have been evaluated to prevent this infection, including the use of live-attenuated vaccines (LAVs). However, further development of LAV approaches is often hampered by the lack of highly efficient and scalable cell-based production systems that support worldwide vaccine production. In this context, avian cell lines cultivated in suspension are currently competing with traditional cell platforms used for viral vaccine manufacturing. We investigated whether the DuckCelt(R)-T17 avian cell line (Vaxxel) we previously described as an efficient production system for several influenza strains could also be used to produce a new HMPV LAV candidate (Metavac(R)), an engineered SH gene-deleted mutant of the A1/C-85473 strain of HMPV. To that end, we characterized the operational parameters of multiplicity of infection (MOI), cell density, and trypsin addition to achieve optimal production of the LAV Metavac(R) in the DuckCelt(R)-T17 cell line platform. We demonstrated that the DuckCelt(R)-T17 cell line is permissive and is well adapted to the production of the wild-type A1/C-85473 HMPV and the Metavac(R) vaccine candidate. Moreover, our results confirmed that the LAV candidate produced in DuckCelt(R)-T17 cells conserves its advantageous replication properties in LLC-MK2 and 3D-reconstituted human airway epithelium models, as well as its capacity to induce efficient neutralizing antibodies in a mouse model. Our results suggest that the DuckCelt(R)-T17 avian cell line is a very promising platform for scalable in-suspension serum-free production of the HMPV-based LAV candidate Metavac(R).

immunology↗

bioRxiv2020

Transcriptional profiling of immune and inflammatory responses in the context of SARS-CoV-2 fungal superinfection in a human airway epithelial model

Superinfections of bacterial/fungal origin are known to affect the course and severity of respiratory viral infections. An increasing number of evidence indicate a relatively high prevalence of superinfections associated with COVID-19, including invasive aspergillosis, but the underlying mechanisms remain to be characterized. In the present study, to better understand the biological impact of superinfection we sought to determine and compare the host transcriptional response to SARS-CoV-2 versus Aspergillus superinfection, using a model of reconstituted humain airway epithelium. Our analyses reveal that both simple infection and superinfection induce a strong deregulation of core components of innate immune and inflammatory responses, with a stronger response to superinfection in the bronchial epithelial model compared to its nasal counterpart. Our results also highlight unique transcriptional footprints of SARS-CoV-2 Aspergillus superinfection, such as an imbalanced type I/type III IFN, and an induction of several monocyte- and neutrophil associated chemokines, that could be useful for the understanding of Aspergillus-associated COVID-19 and but also management of severe forms of aspergillosis in this specific context.

microbiology↗

bioRxiv2020

Characterization and treatment of SARS-CoV-2 in nasal and bronchial human airway epithelia

In the current COVID-19 pandemic context, proposing and validating effective treatments represents a major challenge. However, the lack of biologically relevant pre-clinical experimental models of SARS-CoV-2 infection as a complement of classic cell lines represents a major barrier for scientific and medical progress. Here, we advantageously used human reconstituted airway epithelial models of nasal or bronchial origin to characterize viral infection kinetics, tissue-level remodeling of the cellular ultrastructure and transcriptional immune signatures induced by SARS-CoV-2. Our results underline the relevance of this model for the preclinical evaluation of antiviral candidates. Foremost, we provide evidence on the antiviral efficacy of remdesivir and the therapeutic potential of the remdesivir-diltiazem combination as a rapidly available option to respond to the current unmet medical need imposed by COVID-19. One Sentence SummaryNew insights on SARS-CoV-2 biology and drug combination therapies against COVID-19.

microbiology↗