Comparison of prokaryotes between Mount Everest and the Mariana Trench

Abstract

Background Mount Everest and the Mariana Trench represent the highest and deepest places on Earth, respectively. They are geographically separated, with distinct extreme environmental parameters that provide unique habitats for prokaryotes. Comparison of prokaryotes between Mount Everest and the Mariana Trench will provide a unique perspective to understanding the composition and distribution of environmental microbiomes on Earth. Results Here, we compared prokaryotic communities between Mount Everest and the Mariana Trench based on shotgun metagenomic analysis. Analyzing 25 metagenomes and 1176 metagenome-assembled genomes showed distinct taxonomic compositions between Mount Everest and the Mariana Trench, with little taxa overlap, and significant differences in genome size, GC content, and predicted optimal growth temperature. However, community metabolic capabilities exhibited striking commonality, with > 90% of metabolic modules overlapping among samples of Mount Everest and the Mariana Trench, with the only exception for CO2 fixations (photoautotrophy in Mount Everest but chemoautotrophy in the Mariana Trench). Most metabolic pathways were common but performed by distinct taxa in the two extreme habitats, even including some specialized metabolic pathways, such as the versatile degradation of various refractory organic matters, heavy metal metabolism (e.g., As and Se), stress resistance, and antioxidation. The metabolic commonality indicated the overall consistent roles of prokaryotes in elemental cycling and common adaptation strategies to overcome the distinct stress conditions despite the intuitively huge differences in Mount Everest and the Mariana Trench. Conclusion Our results, the first comparison between prokaryotes in the highest and the deepest habitats on Earth, may highlight the principles of prokaryotic diversity: although taxa are habitat-specific, primary metabolic functions could be always conserved.

Deep-sea Bacteroidetes from the Mariana Trench specialize in hemicellulose and pectin degradation typically associated with terrestrial systems

“…Polysaccharide sources in the Mariana Trench waters are likely predominantly derived from phytoplankton biomass (especially dinoflagellates) [ 54 ] with potential coastal and land inputs [ 7 ]. After the utilization of labile forms like glucans during the sinking process, structurally complex cell wall polysaccharides including hemicelluloses and pectins accumulate in BH waters, providing an important carbon source for local heterotrophic microorganisms [ 2 , 12 , 13 , 15 ] and animals [ 1 , 55 ]. Genetic elements both inherently present and laterally transferred confer hadal microorganisms with specialized polysaccharide decomposition capabilities.…”

Depth shapes microbiome assembly and network stability in the Mariana Trench

“…Compared with archaea and microeukaryotes, bacteria and archaea contribute greatly to the stability of Mariana Trench microbiome networks, especially in upper bathypelagic waters. Similarly, the essential roles of predominant heterotrophs in recycling macromolecules and utilizing various carbon sources (e.g., peptides, hydrocarbons, carbohydrates, and aromatic compounds) are demonstrated in the Mariana Trench ( 43 – 45 ). The trench V-shaped topography enables the collection of particulate organic matter and heavy metals, such as selenium and arsenic, from the overlying water column, abyssal seafloor, and Earth’s upper crust ( 43 , 46 ).…”

“…These accumulation effects result in a greater content of organic matters and higher heterotrophic microbial degradation activities at the bottom axis than in adjacent slope sites in the trench ( 47 ). In addition, the functional redundancy that multiple bacterial taxa encode the same biological function ( 44 , 48 ) and cross-stress adaptation behaviors for coping with distinct environmental conditions ( 49 ) are also reported in the trench and other environments.…”

Microbial communities reveal niche partitioning across the slope and bottom zones of the challenger deep

“…Distances between samples were calculated by vegdist in the R package vegan using the Jaccard and Bray–Curtis distances (Oksanen et al, 2020 ). Genes per million reads (GPM) was used to normalize gene abundance data for metagenomic comparison, which is the method equivalent to transcripts per million (TPM) in transcriptomes (He et al, 2022 ; Liu et al, 2022 ; Zhou et al, 2022 ). Briefly, reads mapped to genes were normalized by gene length and total mapped number following the formula below: where and refer to the reads mapped to the gene and the length of the gene , respectively.…”