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Haas, Nikolaus A.; Kleideiter, Ulrich

doi:10.1055/b-0038-150719

Cited by 2 publications

(3 citation statements)

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“…Gene models for species used in the study were collected from publicly available data sources ( Supplemental Dataset 1 ). When protein sequences were not available, we generated sequences from transcriptome data using Transdecoder v5.5.0 (77), applying a minimum protein length of 50 amino acids and retaining only protein sequences with blast hits to any sequence in the Uniprot Taxonomic Divisions Plant database (https://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/taxonomic_divisions/). Then, the Transdecoder primary_transcript.fa script was used to extract only the longest translated protein sequence from the primary transcript for each gene to reduce the search space.…”

Section: Methodsmentioning

confidence: 99%

Photosynthesis drives retention of bacterial-like tRNA metabolism in plant organelles

DeTar,

Chustecki,

Martinez-Hottovy

et al. 2023

Preprint

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Eukaryotic nuclear genomes often encode distinct sets of protein translation machinery for function in the cytosol vs. organelles (mitochondria and plastids). This phenomenon raises questions about why multiple translation systems are maintained even though they are capable of comparable functions, and whether they evolve differently depending on the compartment where they operate. These questions are particularly interesting in land plants because translation machinery, including aminoacyl-tRNA synthetases (aaRS), is often dual-targeted to both the plastids and mitochondria. These two organelles have quite different metabolisms, with much higher rates of translation in plastids to supply the abundant, rapid-turnover proteins required for photosynthesis. Previous studies have indicated that plant organellar aaRS evolve more slowly compared to mitochondrial aaRS in other eukaryotes that lack plastids. Thus, we investigated the evolution of nuclear-encoded organellar and cytosolic translation machinery across a broad sampling of angiosperms, including non-photosynthetic (heterotrophic) plant species with reduced rates of plastid gene expression to test the hypothesis that translational demands associated with photosynthesis constrain the evolution of bacterial-like enzymes involved in organellar tRNA metabolism. Remarkably, heterotrophic plants exhibited wholesale loss of many organelle-targeted aaRS and other enzymes, even though translation still occurs in their mitochondria and plastids. These losses were often accompanied by apparent retargeting of cytosolic enzymes and tRNAs to the organelles, sometimes preserving aaRS-tRNA charging relationships but other times creating surprising mismatches between cytosolic aaRS and mitochondrial tRNA substrates. Our findings indicate that the presence of a photosynthetic plastid drives the retention of specialized systems for organellar tRNA metabolism.

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Section: Methodsmentioning

confidence: 99%

Photosynthesis drives retention of bacterial-like tRNA metabolism in plant organelles

DeTar,

Chustecki,

Martinez-Hottovy

et al. 2023

Preprint

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“…UniProtKB/Swiss-Prot was used as the database for the annotation. MGkit (Rubino et al 2014), AGAT (v1.1.0, Dainat et al 2021) and TransDecoder (v5.5.0, Haas 2018) were used to obtain only the annotated parts of the assembled contigs. The longest isoforms were selected using a custom python script.…”

Section: Methodsmentioning

confidence: 99%

“…70447 open reading frames, identified using TransDecoder (v5.5.0, Haas 2018), were selected from 150823 transcripts after filtering out transcripts that were present in a single sample or had a cumulative TPM of over 20000000. Of these, very large proteins (>800aa) were excluded, and 3D structures were generated for 66 973 proteins using ESMFold (Lin et al 2023).…”

Section: Methodsmentioning

confidence: 99%

Single-cell transcriptomics reveals functional insights into a non-model aquatic phytoflagellate and its metabolically linked bacterial community

Florenza,

Jeevannavar,

Divne

et al. 2023

Preprint

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Single-cell transcriptomics have rapidly become a standard tool for decoding cell identity, fate, and interactions in mammalian model organisms. Adopting these techniques to uncover functional dynamics in aquatic single-celled organisms holds huge potential, but evidence of their applicability to non-model, poorly understood microeukaryotes remains limited. In the present study, live Ochro-monas triangulata cells from fast and slow growth phases were FACS-sorted based on food vacuole staining and chlorophyll fluorescence, and single-cell transcriptomic libraries were prepared following the Smart-seq2 protocol. In total, 744 transcriptomes were Illumina sequenced. Lacking a reference genome, transcriptomes were assembled de novo using Trinity and resulting transcripts were annotated by BLAST using the Swiss-Prot database. Following read mapping, differential gene expression was evaluated using DESeq2 and metabolic maps were generated based on pathways from the KEGG Orthology database. Clustering the read counts revealed the identity of the two expected transcriptional states corresponding to each growth phase as well as a third distinct cluster of cells present in both growth phases. This cryptic group showed extensive downregulation of genes in pathways associated with ribosome-functioning, CO2 fixation and core carbohydrate catabolism such as glycolysis, β oxidation of fatty acids, and tricarboxylic acid cycle. Nevertheless, the biological underpinnings of this cluster, which would have remained unnoticed in an integrated approach, could not be clarified. Additionally, the possibility of using carry-over rRNA reads for taxonomic annotation was tested, which revealed specific individual-level bacterial communities associated with members within each cluster, as well as verified identification of 88% of the cells as O. triangulata. In conclusion, we demonstrate the power of single cell transcriptomics for metabolic mapping of microeukaryotes for which genomic reference resources might be limited, and thereby highlight its potential as a tool to gain access to microeukaryote dynamics and diversity in natural communities.

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Cited by 2 publications

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Photosynthesis drives retention of bacterial-like tRNA metabolism in plant organelles

Photosynthesis drives retention of bacterial-like tRNA metabolism in plant organelles

Single-cell transcriptomics reveals functional insights into a non-model aquatic phytoflagellate and its metabolically linked bacterial community

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