Biology subjects

Dosch, J.

Publications and source records attributed to Dosch, J..

3 recordsLinked to original sources

bioRxiv2024

Tracing the taxonomic distribution of plant cell wall degrading enzymes across the tree of life using feature architecture aware orthology assignments

The decomposition of plant material is a key driver of the global carbon cycle, traditionally attributed to fungi and bacteria. However, some invertebrates also possess orthologs to bacterial or fungal cellulolytic enzymes, likely acquired via horizontal gene transfer. This reticulated mode of evolution necessitates ortholog searches in large taxon sets to comprehensively map the repertoire of plant cell wall degrading enzymes (PCDs) across the tree of life, a task surpassing capacities of current software. Here, we use fDOG, a novel profile-based ortholog search tool to trace 235 potential PCDs across more than 18,000 taxa. fDOG allows to start the ortholog search from a single protein sequence as a seed, it performs on par with state-of-the-art software that require the comparison of entire proteomes, and it is unique in routinely scoring protein feature architecture differences between the seed protein and its orthologs. Visualizing the presence-absence patterns of PCD orthologs using a UMAP highlights taxa where recent changes in the enzyme repertoire indicate a change in lifestyle. Three invertebrates have a particularly rich set of PCD orthologs encoded in their genome. Only few of the orthologs show differing protein feature architectures relative to the seed that suggest functional modifications. Thus, the corresponding species represent lineages within the invertebrates that may contribute to the global carbon cycle. This study shows how fDOG can be used to create a multi-scale view on the taxonomic distribution of a metabolic capacity that ranges from tree of life-wide surveys to individual feature architecture changes within a species.

bioinformatics↗

bioRxiv2022

FAS: Assessing the similarity between proteins using multi-layered feature architectures

MotivationExpert curation to differentiate between functionally diverged homologs and those that may still share a similar function routinely relies on the visual interpretation of domain architecture changes. However, the size of contemporary data sets integrating homologs from hundreds to thousands of species calls for alternate solutions. Scoring schemes to evaluate domain architecture similarities can help to automatize this procedure, in principle. But existing schemes are often too simplistic in the similarity assessment, many require an a-priori resolution of overlapping domain annotations, and those that allow overlaps to extend the set of annotations sources cannot account for redundant annotations. As a consequence, the gap between the automated similarity scoring and the similarity assessment based on visual architecture comparison is still too wide to make the integration of both approaches meaningful. ResultsHere, we present FAS, a scoring system for the comparison of multi-layered feature architectures integrating information from a broad spectrum of annotation sources. Feature architectures are represented as directed acyclic graphs, and redundancies are resolved in the course of comparison using a score maximization algorithm. A benchmark using more than 10,000 human-yeast ortholog pairs reveals that FAS consistently outperforms existing scoring schemes. Using three examples, we show how automated architecture similarity assessments can be routinely applied in the benchmarking of orthology assignment software, in the identification of functionally diverged orthologs, and in the identification of entries in protein collections that most likely stem from a faulty gene prediction. Availability and implementationFAS is available as python package: https://pypi.org/project/greedyFAS/

bioinformatics↗

bioRxiv2021

The evolutionary making of SARS-CoV-2

A mechanistic understanding of how SARS-CoV-2 (sarbecovirus, betacoronavirus) infects human cells is emerging, but the evolutionary trajectory that gave rise to this pathogen is poorly understood. Here we scan SARS-CoV-2 protein sequences in-silico for innovations along the evolutionary lineage starting with the last common ancestor of coronaviruses. SARS-CoV-2 substantially differs from viruses outside sarbecovirus both in its set of encoded proteins and in their domain architectures, indicating divergent functional demands. Within sarbecoviruses, sub-domain level profiling using predicted linear epitopes reveals how the primary interface between host cell and virus, the spike, was gradually reshaped. The only epitope that is private to SARS-CoV-2 overlaps with the furin cleavage site, a "switch" that modulates spikes conformational landscape in response to host-cell interaction. This cleavage site has fundamental relevance for both immune evasion and cell infection, and the apparently ongoing evolutionary fine-tuning of its use by SARS-CoV-2 should be monitored.

evolutionary biology↗