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Chede, A.

Publications and source records attributed to Chede, A..

2 recordsLinked to original sources

An evolutionary optimum amid moderate heritability in prokaryotic cell size

We investigated the distribution and evolution of prokaryotic cell size based on a compilation of 5380 species. Size spans four orders of magnitude, from 100 nm (Mycoplasma) to more than 1 cm (Thiomargarita), however most species congregate heavily around the mean. The distribution approximates but is distinct from log-normality. Comparative phylogenetics suggested that size is heritable, yet the phylogenetic signal is moderate, and the degree of heritability is independent of taxonomic scale (i.e. fractal). Evolutionary modeling indicated the presence of an optimal cell size, corresponding to a coccus 0.70 {micro}m in diameter, to which most species gravitate. Analyses of 1361 species with sequenced genomes showed that genomic traits contribute to size evolution moderately and synergistically. In light of our results, scaling theory, and empirical evidence, we discuss potential drivers that may expand or shrink cells around the optimum and propose a stability landscape model for prokaryotic cell size.

evolutionary biology↗

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

Exploring metagenomic contigs and "binning" them are essential for delineating functional and evolutionary guilds within microbial communities. Despite available automated binners, researchers often find human involvement necessary to achieve representative results. We present BinaRena, an interactive graphic interface dedicated to aiding human operators to explore contigs via customizable visualization and to associate them with bins based on various data types, including sequence metrics, coverage profiles, taxonomic assignments and functional annotations. Binning plans can be edited, inspected and compared visually or using algorithms. Completeness and redundancy of user-selected contigs can be calculated real-time. We show that BinaRena facilitated biological pattern discovery, hypothesis generation and bin refinement in a tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely-related populations from human gut samples. It significantly improved overall binning quality after curation using a simulated marine dataset. BinaRena is an installation-free, client-end web application for researchers of all levels.

bioinformatics↗