Organelles in the ointment: improved detection of cryptic mitochondrial reads resolves many unknown sequences in cross-species microbiome analyses
Artikel i vetenskaplig tidskrift, 2024

The genomes of mitochondria and chloroplasts contain ribosomal RNA (rRNA) genes, reflecting their ancestry as free-living bacteria. These organellar rRNAs are often amplified in microbiome studies of animals and plants. If identified, they can be discarded, merely reducing sequencing depth. However, we identify certain high-abundance organeller RNAs not identified by common pipelines, which may compromise statistical analysis of microbiome structure and diversity. We quantified this by reanalyzing 7459 samples from seven 16S rRNA studies, including microbiomes from 927 unique animal genera. We find that under-annotation of cryptic mitochondrial and chloroplast reads affects multiple of these large-scale cross-species microbiome comparisons, and varies between host species, biasing comparisons. We offer a straightforward solution: supplementing existing taxonomies with diverse organelle rRNA sequences. This resolves up to 97% of unique unclassified sequences in some entire studies as mitochondrial (14% averaged across all studies), without increasing false positive annotations in mitochondria-free mock communities. Improved annotation decreases the proportion of unknown sequences by >= 10-fold in 2262 of 7459 samples (30%), spanning five of seven major studies examined. We recommend leveraging organelle sequence diversity to better identify organelle gene sequences in microbiome studies, and provide code, data resources and tutorials that implement this approach.

animal microbiomes

mitochondria

mitochondrial diversity

microbiome analysis

amplicon sequencing

Författare

Dylan Sonett

University of Washington

Tanya Brown

University of Texas at Tyler

University of Washington

Johan Bengtsson Palme

Göteborgs universitet

Chalmers, Life sciences, Systembiologi

Jacqueline L. Padilla-Gamino

University of Washington

Jesse R. Zaneveld

University of Washington

Isme Communications

27306151 (eISSN)

Vol. 4 1 ycae114

Ämneskategorier (SSIF 2011)

Mikrobiologi

Bioinformatik och systembiologi

Genetik

DOI

10.1093/ismeco/ycae114

PubMed

39660011

Mer information

Senast uppdaterat

2025-09-16