Microglia at sites of atrophy restrict the progression of retinal degeneration via galectin-3 and Trem2

Outer retinal degenerations, including age-related macular degeneration (AMD), are characterized by photoreceptor and retinal pigment epithelium (RPE) atrophy. In these blinding diseases, macrophages accumulate at atrophic sites, but their ontogeny and niche specialization remain poorly understood, especially in humans. We uncovered a unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and human AMD. In disease models, conditional deletion of galectin-3 in microglia led to phagocytosis defects and consequent augmented photoreceptor death, RPE damage, and vision loss, indicating protective roles. Mechanistically, Trem2 signaling orchestrated microglial migration to atrophic sites and induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection but in a galectin-3-dependent manner. In elderly human subjects, we identified this highly conserved microglial population that expressed galectin-3 and Trem2. This population was significantly enriched in the macular RPE-choroid of AMD subjects. Collectively, our findings reveal a neuroprotective population of microglia and a potential therapeutic target for mitigating retinal degeneration

Design and Efficiency of a Domestic Sewage Treatment System with Microorganism- membrane on Island Based on Entropy Theory

Abstract: Domestic sewage treatment by water drainage network plus septic tank is not suitable on very small islands because of traffic and urban infrastructure problem. This study deals with a microorganism-membrane domestic sewage treatment system on small islands, which can degrade and clean the domestic sewage locally by effective microorganism and membrane system and makes the emission in market. Eight kinds of commercial complex microorganisms decompose powder were chosen to analysis the activities of protease, lipase, cellulose and amylase. And relating model based on entropy theory was constructed to evaluate the effect of enzyme activity, then the best commercial complex microorganism decompose powder was confirmed. The designed microorganismmembrane wastewater treatment system was applied to treat domestic sewage on a small island. The results showed that the removal rate of organic matters including the five-day Biological Oxygen Demand (BOD 5 ), Chemical Oxygen Demand (COD) and ammonia nitrogen (NH 3 -N) reached more than 98%. The removal rate of Total Dissolved Salts (TDS) of the outlet water was higher than 99%. This system was especially suitable for small islands domestic wastewater treatment

methodology development and applications of protein-protein interaction prediction

Les interactions protéine-protéine (IPP) jouent un rôle essentiel dans le vivant. Mon travail de thèse s’est concentré sur développement de méthodes bio-informatiques pour la prédiction et la modélisation structurale des IPP. Mon objectif était d'améliorer le pouvoir prédictif des méthodes permettant de prédire les structures d’assemblages macromoléculaires (docking) et d'aborder les problèmes rencontrés par les biologistes sur des cas réels d’interactions.Pour obtenir des modèles de protéines isolées de meilleure qualité, j’ai tout d’abord développé le serveur HHalign-Kbest basé sur des algorithmes d’alignements sous-optimaux. Ensuite, dans le domaine du « docking », j’ai élaboré le serveur InterEvDock qui prend en compte les informations de coévolution entre protéines. Les validations en aveugle montrent que ce serveur atteint de meilleures performances que d’autres serveurs de référence lorsque l’information évolutive est disponible.Afin de tester plus à fond nos méthodes, nous avons participé au concours CAPRI - un concours international pour la prédiction des interactions protéiques. Sur les sessions couvrant la période 2013-2016, notre groupe s’est classé 1er. Enfin, j'ai développé un jeu de données d’apprentissage et de test, PPI4DOCK. Il contient un très grand nombre de cibles de complexes (plus de 1000) et permettra d'améliorer les méthodes de docking à partir des structures expérimentales ou de modèles.En termes d'applications, je me investis dans différents projets collaboratifs, qui touchent des domaines aussi variés que, la recherche de partenaires pour le chaperon d’histone Asf1; la prédiction des modes d’interaction entre CENP-F et Nup133 dans le contexte de la mitose et de Exo70 et Abi dans celui de la régulation de la mobilité cellulaire; la simulation des modes de liaison entre le complexe Ku et ses partenaires peptidiques, dans les voies de réparation de l'ADN.Protein-protein interactions (PPIs) play essential roles in life. My PhD work aimed at developing advanced bioinformatics methods in the field of PPI prediction at the structural scale. My goal was to improve the predictive power of methods which model the structures of macromolecular assemblies (docking) and to tackle real-life problems faced by biologists.First, I developed HHalign-Kbest server using algorithms for the search of suboptimal solutions to gain better-quality models. Second, in the field of protein docking, I built InterEvDock server which can take co-evolutionary information into account. It yields better performance than other state-of-the-art servers. In order to further test our methods, we participated in CAPRI – an international challenge for prediction of protein interactions. Over years 2013-2016, our group ranked 1st at the 6th CAPRI evaluation meeting. At last, I developed a realistic benchmark dataset PPI4DOCK, largest dataset so far, in order to improve docking methods for the scientific community.In terms of applications, I was involved in a variety of collaborative projects with different labs. As representative examples, I searched for binding partners of the histone chaperone Asf1; I studied the CENP-F/Nup133 interaction in the context of mitosis and the Exo70/Abi interaction related to cell mobility regulation; I also simulated the binding modes of multiple peptides, partners of Ku complex involved in DNA repair pathway

PPI4DOCK: Large scale assessment of the use of homology models in free docking over more than 1000 realistic targets.

International audienceProtein-protein docking methods are of great importance for understanding interactomes at the structural level. It has become increasingly appealing to use not only experimental structures but also homology models of unbound subunits as input for docking simulations. So far we are missing a large scale assessment of the success of rigid-body free docking methods on homology models. We explored how we could benefit from comparative modeling of unbound subunits to expand docking benchmark datasets. Starting from a collection of 3157 non-redundant, high X-ray resolution heterodimers, we developed the PPI4DOCK benchmark containing 1417 docking targets based on unbound homology models. Rigid-body docking by Zdock showed that for 1208 cases (85.2%), at least one correct decoy was generated, emphasizing the efficiency of rigid-body docking in generating correct assemblies. Overall, the PPI4DOCK benchmark contains a large set of realistic cases and provides new ground for assessing docking and scoring methodologies. Benchmark sets can be downloaded from http://biodev.cea.fr/interevol/ppi4dock/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

HHalign-Kbest: exploring sub-optimal alignments for remote homology comparative modeling.

International audienceThe HHsearch algorithm, implementing a hidden Markov model (HMM)-HMM alignment method, has shown excellent alignment performance in the so-called twilight zone (target-template sequence identity with ∼20%). However, an optimal alignment by HHsearch may contain small to large errors, leading to poor structure prediction if these errors are located in important structural elements.HHalign-Kbest server runs a full pipeline, from the generation of suboptimal HMM-HMM alignments to the evaluation of the best structural models. In the HHsearch framework, it implements a novel algorithm capable of generating k-best HMM-HMM suboptimal alignments rather than only the optimal one. For large proteins, a directed acyclic graph-based implementation reduces drastically the memory usage. Improved alignments were systematically generated among the top k suboptimal alignments. To recognize them, corresponding structural models were systematically generated and evaluated with Qmean score. The method was benchmarked over 420 targets from the SCOP30 database. In the range of HHsearch probability of 20-99%, average quality of the models (TM-score) raised by 4.1-16.3% and 8.0-21.0% considering the top 1 and top 10 best models, respectively.http://bioserv.rpbs.univ-paris-diderot.fr/services/HHalign-Kbest/ (source code and server)[email protected] data are available at Bioinformatics online