PhyloMagnet: fast and accurate screening of short-read meta-omics data using gene-centric phylogenetics

A Mitosome With Distinct Metabolism in the Uncultured Protist Parasite Paramikrocytos canceri (Rhizaria, Ascetosporea)

Ascetosporea are endoparasites of marine invertebrates that include economically important pathogens of aquaculture species. Owing to their often-minuscule cell sizes, strict intracellular lifestyle, lack of cultured representatives and minimal availability of molecular data, these unicellular parasites remain poorly studied. Here, we sequenced and assembled the genome and transcriptome of Paramikrocytos canceri, an endoparasite isolated from the European edible crab Cancer pagurus. Using bioinformatic predictions, we show that P. canceri likely possesses a mitochondrion-related organelle (MRO) with highly reduced metabolism, resembling the mitosomes of other parasites but with key differences. Like other mitosomes, this MRO is predicted to have reduced metabolic capacity and lack an organellar genome and function in iron-sulfur cluster (ISC) pathway-mediated Fe-S cluster biosynthesis. However, the MRO in P. canceri is uniquely predicted to produce ATP via a partial glycolytic pathway and synthesize phospholipids de novo through the CDP-DAG pathway. Heterologous gene expression confirmed that proteins from the ISC and CDP-DAG pathways retain mitochondrial targeting sequences that are recognized by yeast mitochondria. This represents a unique combination of metabolic pathways in an MRO, including the first reported case of a mitosome-like organelle able to synthesize phospholipids de novo. Some of these phospholipids, such as phosphatidylserine, are vital in other protist endoparasites that invade their host through apoptotic mimicry.

A Guide to Gene-Centric Analysis Using TreeSAPP

Gene-centric analysis is commonly used to chart the structure, function, and activity of microbial communities in natural and engineered environments. A common approach is to create custom ad hoc reference marker gene sets, but these come with the typical disadvantages of inaccuracy and limited utility beyond assigning query sequences taxonomic labels. The Tree-based Sensitive and Accurate Phylogenetic Profiler (TreeSAPP) software package standardizes analysis of phylogenetic and functional marker genes and improves predictive performance using a classification algorithm that leverages information-rich reference packages consisting of a multiple sequence alignment, a profile hidden Markov model, taxonomic lineage information, and a phylogenetic tree. Here, we provide a set of protocols that link the various analysis modules in TreeSAPP into a coherent process that both informs and directs the user experience. This workflow, initiated from a collection of candidate reference sequences, progresses through construction and refinement of a reference package to marker identification and normalized relative abundance calculations for homologous sequences in metagenomic and metatranscriptomic datasets. The alpha subunit of methyl-coenzyme M reductase (McrA) involved in biological methane cycling is presented as a use case given its dual role as a phylogenetic and functional marker gene driving an ecologically relevant process. These protocols fill several gaps in prior TreeSAPP documentation and provide best practices for reference package construction and refinement, including manual curation steps from trusted sources in support of reproducible gene-centric analysis. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating reference packages Support Protocol 1: Installing TreeSAPP Support Protocol 2: Annotating traits within a phylogenetic context Basic Protocol 2: Updating reference packages Basic Protocol 3: Calculating relative abundance of genes in metagenomic and metatranscriptomic datasets.

Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade

Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data.

Single cell genomics reveals plastid-lacking Picozoa are close relatives of red algae

The endosymbiotic origin of plastids from cyanobacteria gave eukaryotes photosynthetic capabilities and launched the diversification of countless forms of algae. These primary plastids are found in members of the eukaryotic supergroup Archaeplastida. All known archaeplastids still retain some form of primary plastids, which are widely assumed to have a single origin. Here, we use single-cell genomics from natural samples combined with phylogenomics to infer the evolutionary origin of the phylum Picozoa, a globally distributed but seemingly rare group of marine microbial heterotrophic eukaryotes. Strikingly, the analysis of 43 single-cell genomes shows that Picozoa belong to Archaeplastida, specifically related to red algae and the phagotrophic rhodelphids. These picozoan genomes support the hypothesis that Picozoa lack a plastid, and further reveal no evidence of an early cryptic endosymbiosis with cyanobacteria. These findings change our understanding of plastid evolution as they either represent the first complete plastid loss in a free-living taxon, or indicate that red algae and rhodelphids obtained their plastids independently of other archaeplastids.