Back

Sulfur-fueled chemolithoautotrophs replenish organic carbon inventory in groundwater

Taubert, M.; Heinze, B. M.; Overholt, W. A.; Azemtsop, G.; Houhou, R.; Jehmlich, N.; von Bergen, M.; Roesch, P.; Popp, J.; Kuesel, K.

2021-01-26 microbiology
10.1101/2021.01.26.428071 bioRxiv
Show abstract

The current understanding of organic carbon inputs into ecosystems lacking photosynthetic primary production is predicated on data and inferences derived almost entirely from metagenomic analyses. The elevated abundances of putative chemolithoautotrophs in groundwaters suggest that dark CO2 fixation is an integral component of subsurface trophic webs. To understand the impact of autotrophically-fixed carbon, the flux of CO2-derived carbon through various subpopulations of subsurface microbiota must first be resolved, both quantitatively and temporally. Here, we implement novel stable isotope cluster analysis to render a time-resolved and quantitative evaluation of 13CO-derived carbon flow through a groundwater microbiome stimulated with reduced sulfur compounds. We demonstrate that mixotrophs, not obligate chemolithoautotrophs, were the most abundant active organisms in groundwater microcosms. Species of Hydrogenophaga, Polaromonas, Dechloromonas, and other metabolically versatile mixotrophs drove the recycling of organic carbon and, when chance afforded, supplemented their carbon requirements via chemolithoautotrophy and uptake of available organic compounds. Mixotrophic activity facilitated the replacement of 43 and 80% of total microbial carbon stores with 13C in just 21 and 70 days, respectively. This opportunistic "utilize whatever pathways net the greatest advantage in fitness" strategy may explain the great abundances of mixotrophs in other oligotrophic habitats, like the upper ocean and boreal lakes.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.