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Updated: Oct 28, 2026

An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
Published on: September 15, 2015
A global mitochondrial genomic atlas illuminates freshwater microeukaryote diversity
Lucas Serra Moncadas1, Hans-Joachim Ruscheweyh2,3, Jason Woodhouse4
1Limnological Station, Department of Plant and Microbial Biology, University of Zurich, Kilchberg, Switzerland.
Abstract:
Environmental genomics has transformed our view of the microbial world, yet progress remains largely prokaryote-centric. Among microbial eukaryotes, inconsistent marker choice and limited species-level resolution blunt diversity estimates and hinder cross-study synthesis. Consequently, regional‑to‑global gradients in richness, turnover, and phylogenetic structure remain poorly resolved. Here we establish a global mitogenome-based framework that converts shotgun metagenomes into species‑resolved, phylogeny‑anchored inventories. From 3,400 metagenomes spanning 362 lakes on seven continents, we reconstruct ~20,000 mitochondrial metagenome-assembled genomes (mitoMAGs), densely populating previously sparse branches of the eukaryotic tree-notably SAR (Stramenopiles-Alveolata-Rhizaria), Cryptophyceae, and Haptista. An empirically calibrated 98.1% mitoMAG‑identity threshold delineates species and tethers community profiles to an evolutionary backbone. On this backbone, coverage‑standardized inventories recover canonical ecological patterns: mesotrophic richness peaks, surface-layer expansion of phylogenetic breadth, and spring maxima with the strongest surface-deep coupling at vernal mixing; supporting the framework. Treating mitoMAGs as primer‑free barcodes yields a single, species‑level, phylogeny‑aware currency that renders richness, evenness, and phylogenetic breadth directly comparable across datasets, depths, seasons, and regions. By placing microbial eukaryotes on an analytical footing comparable to prokaryotes, the resulting atlas brings their diversity into reach and lays the groundwork for future high-throughput, species-aware monitoring and ecological forecasting.
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