Back

Mechanism of high energy efficiency of carbon fixation by sulfur-oxidizing symbionts revealed by single-cell analyses and metabolic modeling

Kleiner, M.; Polerecky, L.; Lott, C.; Bergin, C.; Haeusler, S.; Liebeke, M.; Wentrup, C.; Musat, N.; Kuypers, M. M. M.; Dubilier, N.

2023-11-26 microbiology
10.1101/2023.11.25.568684 bioRxiv
Show abstract

In chemosynthetic symbioses between marine invertebrates and autotrophic sulfur-oxidizing bacteria the symbionts feed their host by producing organic compounds from CO2 using reduced sulfur compounds as an energy source. One such symbiosis, the gutless marine worm Olavius algarvensis harbors at least five bacterial symbionts of which four have the genetic potential for an autotrophic metabolism. In this study we combined single-cell analyses of CO2 fixation, CO2 release and bulk uptake, with measurements of O2 respiration, sulfur content, and polyhydroxyalkanoate content, as well as mathematical modelling to investigate how energy derived from sulfur oxidation drives carbon fluxes within the symbiosis and between the holobiont and its habitat. We found that under aerobic conditions without external energy sources only the primary symbiont, Ca. Thiosymbion algarvensis, fixed carbon. This symbiont relied on internal sulfur storage for energy production. Our model showed that the apparent efficiency of carbon fixation driven by sulfur oxidation in the symbiosis was higher than thermodynamically feasible if only stored sulfur was considered as source of energy and reducing equivalents. The model and additional calculations showed that reducing equivalents must be derived from a different source than energy. We identified the large amounts of polyhdroxyalkanoate stored by the symbiont as the likely source of reducing equivalents for carbon fixation in the symbiont which boosts the yield of sulfur-driven carbon fixation. The model also showed that heterotrophic carbon fixation by host tissue is not negligible and has to be considered when assessing transfer of carbon from the symbionts to the host.

Matching journals

The top 5 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.