Spatial modelling of plant diversity from high-throughput environmental dna sequence data

National audienceThis paper considers a statistical modelling approach to investigate spatial cross-correlations between species in an ecosystem. A special feature is the origin of the data from high-troughput environmental DNA sequencing of soil samples. Here we use data collected at the Nourague CNRS Field Station in French Guiana. We describe bivariate spatial relationships in these data by a separable linear model of coregionalisation and estimate a cross-correlation parameter. Based on this estimate, we visualise plant taxa co-occurrence pattern in form of 'interaction graphs' which can be interpreted in terms of ecological interactions. Limitations of this approach are discussed along with possible alternatives.Cet article présente une approche statistique pour modéliser les corrélations spatiales entre espèces dans un écosystème. L'originalité réside dans la particularité des données, génerées par des séquençages à haut-débit de l'ADN environnemental d' echantillons de sol. Les données utilisées dans cet étude étaient recueillies à la station biologique CNRS des Nouragues, en Guyane Française. L' étude décrit les relations spatiales bivariées de ces données par un modèle linéaire de co-régionalisation séparable où l'on estime un paramètre de cross-corrélation. Sur la base de cette estimation, nous visualisons le modèle de co-occurrences sous forme de graphes d'interactions. Les limites de cette approche sont discutées ainsi que les alternatives possibles

The MCL1 inhibitor S63845 is tolerable and effective in diverse cancer models

Avoidance of apoptosis is critical for the development and sustained growth of tumours. The pro-survival protein myeloid cell leukemia 1 (MCL1) is overexpressed in many cancers, but the development of small molecules targeting this protein that are amenable for clinical testing has been challenging. Here we describe S63845, a small molecule that specifically binds with high affinity to the BH3-binding groove of MCL1. Our mechanistic studies demonstrate that S63845 potently kills MCL1-dependent cancer cells, including multiple myeloma, leukaemia and lymphoma cells, by activating the BAX/BAK-dependent mitochondrial apoptotic pathway. In vivo, S63845 shows potent anti-tumour activity with an acceptable safety margin as a single agent in several cancers. Moreover, MCL1 inhibition, either alone or in combination with other anti-cancer drugs, proved effective against several solid cancer-derived cell lines. These results point towards MCL1 as a target for the treatment of a wide range of tumours