Biology subjects

Ettema, T.

Publications and source records attributed to Ettema, T..

5 recordsLinked to original sources

bioRxiv2025

WitChi: Efficient Detection and Pruning of Compositional Bias in Phylogenomic Alignments Using Empirical Chi-Squared Testing

Convergent evolution, where unrelated taxa independently evolve similar nucleotide or amino acid compositions, can introduce compositional bias into biological sequence data. Such biases distort phylogenetic inference, particularly in deep or unevenly sampled phylogenomic datasets. While composition-aware models can mitigate this issue, their computational demands often preclude their use in large-scale analyses. We present WitChi, a computationally efficient tool for identifying and removing compositionally biased alignment columns using empirical significance testing. WitChi calculates taxon-specific chi-squared ({chi}{superscript 2}) scores and compares them to null distributions derived from permutations within alignment columns that preserve the phylogenetic structure of the alignment. Sites most responsible for deviation from the expected null are iteratively pruned using one of three scoring algorithms until the bias is no longer statistically detectable. Z-scores and p-values are provided for both taxa and alignments, offering interpretable metrics of the magnitude of compositional bias. Pruning of simulated compositional heterogeneous alignments show that WitChi reliably restores correct topologies under standard, compositionally stationary models. In benchmarks, WitChi outperforms BMGEs stationary-based trimming while scaling linearly with taxon number. Applied to the archaeal GTDB r220 dataset (5,869 taxa; 10,101 sites), WitChi completes pruning in under one hour on four CPU cores. The resulting phylogeny recovers key clades previously resolved only by in-depth analyses using complex models of sequence evolution. WitChi provides an efficient, scalable solution for detecting and removing compositional bias in phylogenomic datasets comprising thousands to tens of thousands of taxa, enabling more accurate phylogenetic inference across the tree of life.

bioinformatics↗

bioRxiv2025

Phylogenomic analyses reveal that Panguiarchaeum is a clade of genome-reduced Asgard archaea

The Asgard archaea are a diverse archaeal phylum important for our understanding of cellular evolution because they include the lineage that gave rise to eukaryotes. Recent phylogenomic work has focused on characterising the diversity of Asgard archaea in an effort to identify the closest extant relatives of eukaryotes. However, resolving archaeal phylogeny is challenging, and the positions of two recently-described lineages - Njordarchaeales and Panguiarchaeales - are uncertain, in ways that directly bear on hypotheses of early evolution. In initial phylogenetic analyses, these lineages branched either with Asgards or with the distantly-related Korarchaeota, and it has been suggested that their genomes may be affected by metagenomic contamination. Resolving this debate is important because these clades include genome-reduced lineages that may help inform our understanding of the evolution of symbiosis within Asgard archaea. Here, we performed phylogenetic analyses revealing that the Njordarchaeales and Pangiuarchaeales constitute the new class Njordarchaeia within Asgard archaea. We found no evidence of metagenomic contamination affecting phylogenetic analyses. Njordarchaeia exhibit hallmarks of adaptations to (hyper-)thermophilic lifestyles, including biased sequence compositions that can induce phylogenetic artifacts unless adequately modelled. Panguiarchaeum is metabolically distinct from its relatives, with reduced metabolic potential and various auxotrophies. Phylogenetic reconciliation recovers a complex common ancestor of Asgard archaea that encoded the Wood-Ljungdahl pathway. The subsequent loss of this pathway during the reductive evolution of Panguiarchaeum may have been associated with the switch to a symbiotic lifestyle based on H2-syntrophy. Thus, Panguiarchaeum may contain the first obligate symbionts within Asgard archaea.

evolutionary biology↗

bioRxiv2022

The late ISC pathway interactome reveals mitosomal-cytoplasmic crosstalk in Giardia intestinalis

Mitochondrial metabolism is entirely dependent on the biosynthesis of the [4Fe-4S] clusters, which are part of the subunits of the respiratory chain. The mitochondrial late ISC pathway mediates the formation of these clusters from simpler [2Fe-2S] molecules and transfers them to client proteins. Here, we characterized the late ISC pathway in one of the simplest mitochondria, mitosomes, of the anaerobic protist Giardia intestinalis that lost the respiratory chain and other hallmarks of mitochondria. Identification of the late ISC interactome revealed unexpected involvement of the aerobic marker protein BolA and specific interaction of IscA with the outer mitosomal membrane. Although we confirmed that the synthesis of the Fe-S cluster remained the only metabolic role of mitosomes, we also showed that mitosomes lack client proteins that require the [4Fe-4S] cluster. Instead, by knocking out the bolA gene from the G. intestinalis genome, we showed that, unlike aerobic mitochondria, the late ISC mitosomal pathway is involved in the assembly of cytosolic [4Fe-4S] clusters. Thus, this work reveals an unexpected link between the formation of mitochondrial and cytosolic [4Fe- 4S] clusters. This may either be a consequence of mitochondrial adaptation to life without oxygen, or it represents a general metabolic coupling that has not been previously observed in the complex mitochondrial metabolism of aerobes.

cell biology↗

bioRxiv2021

Characterisation of the Ubiquitin-ESCRT pathway in Asgard archaea sheds new light on origins of membrane trafficking in eukaryotes

The ESCRT machinery performs a critical role in membrane remodelling events in all eukaryotic cells, including in membrane trafficking, membrane repair, cytokinetic abscission, in viral egress, and in the generation of extracellular vesicles. While the machinery is complex in modern day eukaryotes, where it comprises dozens of proteins, the system has simpler and more ancient origins. Indeed, homologues of ESCRT-III and the Vps4 ATPase, the proteins that execute the final membrane scission reaction, play analogous roles in cytokinesis and potentially in extracellular vesicle formation in TACK archaea where ESCRT-I and II homologues seem to be absent. Here, we explore the phylogeny, structure, and biochemistry of homologues of the ESCRT machinery and the associated ubiquitylation system found in genome assemblies of the recently discovered Asgard archaea. In these closest living prokaryotic relatives of eukaryotes, we provide evidence for the ESCRT-I and II sub-complexes being involved in the ubiquitin-directed recruitment of ESCRT-III,_as it is in eukaryotes. This analysis suggests a pre-eukaryotic origin for the Ub-coupled ESCRT system and a likely path of ESCRT evolution via a series of gene duplication and diversification events.

cell biology↗

bioRxiv2019

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

MotivationMetagenomic and metatranscriptomic sequencing analyses have become increasingly popular tools for producing massive amounts of short-read data, often used for the reconstruction of draft genomes or the detection of (active) genes in microbial communities. Unfortunately, sequence assemblies of such datasets generally remain a computationally challenging task. Frequently, researchers are only interested in a specific group of organisms or genes; yet, the assembly of multiple datasets only to identify candidate sequences for a specific question is sometimes prohibitively slow, forcing researchers to select a subset of available datasets to address their question. Here we present PhyloMagnet, a workflow to screen meta-omics datasets for taxa and genes of interest using gene-centric assembly and phylogenetic placement of sequences.\n\nResultsUsing PhyloMagnet, we could identify up to 87% of the genera in an in vitro mock community with variable abundances, while the false positive predictions per single gene tree ranged from 0% to 23%. When applied to a group of metagenomes for which a set of MAGs have been published, we could detect the majority of the taxonomic labels that the MAGs had been annotated with. In a metatranscriptomic setting the phylogenetic placement of assembled contigs corresponds to that of transcripts obtained from transcriptome assembly.\n\nAvailabilityPhyloMagnet is built using Nextflow, available at github.com/maxemil/PhyloMagnet and is developed and tested on Linux. It is released under the open source GNU GPL license and documentation is available at phylomagnet.readthedocs.io. Version 0.5 of PhyloMagnet was used for all benchmarks experiments.

bioinformatics↗