Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data

Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target not only microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared with traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMP Benchmark is available at http://BioGenies.info/AMPBenchmark

Dense matter with eXTP

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Science, the eXTP mission is expected to be launched in the mid 2020s.Comment: Accepted for publication on Sci. China Phys. Mech. Astron. (2019

Mycobacterium abscessus Phospholipase C Expression Is Induced during Coculture within Amoebae and Enhances M. abscessus Virulence in Mice

International audienceMycobacterium abscessus is a pathogenic, rapidly growing mycobacterium involved in pulmonary and cutaneo-mucous infections worldwide, to which cystic fibrosis patients are exquisitely susceptible. The analysis of the genome sequence of M. abscessus showed that this bacterium is endowed with the metabolic pathways typically found in environmental microorganisms that come into contact with soil, plants, and aquatic environments, where free-living amoebae are frequently present. M. abscessus also contains several genes that are characteristically found only in pathogenic bacteria. One of them is MAB_0555 , encoding a putative phospholipase C (PLC) that is absent from most other rapidly growing mycobacteria, including Mycobacterium chelonae and Mycobacterium smegmatis . Here, we report that purified recombinant M. abscessus PLC is highly cytotoxic to mouse macrophages, presumably due to hydrolysis of membrane phospholipids. We further showed by constructing and using an M. abscessus PLC knockout mutant that loss of PLC activity is deleterious to M. abscessus intracellular survival in amoebae. The importance of PLC is further supported by the fact that M. abscessus PLC was found to be expressed only in amoebae. Aerosol challenge of mice with M. abscessus strains that were precultured in amoebae enhanced M. abscessus lung infectivity relative to M. abscessus grown in broth culture. Our study underlines the importance of PLC for the virulence of M. abscessus . Despite the difficulties of isolating M. abscessus from environmental sources, our findings suggest that M. abscessus has evolved in close contact with environmental protozoa, which supports the argument that amoebae may contribute to the virulence of opportunistic mycobacteria

Dense matter with eXTP

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Sciences, the eXTP mission is expected to be launched in the mid 2020s