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, 3 (3), e77

Modeling the Mutualistic Interactions Between Tubeworms and Microbial Consortia


Modeling the Mutualistic Interactions Between Tubeworms and Microbial Consortia

Erik E Cordes et al. PLoS Biol.


The deep-sea vestimentiferan tubeworm Lamellibrachia luymesi forms large aggregations at hydrocarbon seeps in the Gulf of Mexico that may persist for over 250 y. Here, we present the results of a diagenetic model in which tubeworm aggregation persistence is achieved through augmentation of the supply of sulfate to hydrocarbon seep sediments. In the model, L. luymesi releases the sulfate generated by its internal, chemoautotrophic, sulfide-oxidizing symbionts through posterior root-like extensions of its body. The sulfate fuels sulfate reduction, commonly coupled to anaerobic methane oxidation and hydrocarbon degradation by bacterial-archaeal consortia. If sulfate is released by the tubeworms, sulfide generation mainly by hydrocarbon degradation is sufficient to support moderate-sized aggregations of L. luymesi for hundreds of years. The results of this model expand our concept of the potential benefits derived from complex interspecific relationships, in this case involving members of all three domains of life.


Figure 1
Figure 1. Ratio of Sulfide Supply to Sulfide Uptake Rate of L. luymesi Aggregations
Equilibrium line (1:1 ratio) and average, maximum, and minimum values for 1,000 iterations presented. Supply rate based on known sources without sulfate release by tubeworm roots shown in blue. Sulfide supply declines below demand after approximately 40 y. Supply rate including sulfate release from tubeworm roots shown in red, with sulfate release constrained by tubeworm symbionts' sulfide oxidation rate. Sulfide supply exceeds demand for the duration of the model.
Figure 2
Figure 2. Sources of Sulfide Available to Tubeworm Aggregations over Time in the Model
Sources of sulfide include advection and diffusion of sulfide from deep sources (yellow) or sulfate reduction using methane (blue), buried organic carbon (green), or C6+ hydrocarbons (dark grey) as electron donors. Sulfate is provided by diffusion from sediments surrounding the rhizosphere, diffusion at the sediment–water interface, and release from tubeworm roots.
Figure 3
Figure 3. Model Construction
Population model includes individual size-specific growth and mortality rates, and population size-specific recruitment rate. Growth rate was determined by in situ staining of tubeworm aggregations using a blue chitin stain (in situ photograph of stained aggregation demonstrating annual growth shown here) and collection after 12–14 mo. Diagenetic model included advection and diffusion of sulfate, sulfide, methane, bicarbonate, and hydrogen ions as well as organic carbon content of sediments. Fluxes across the rhizosphere (root system) boundary were compared to sulfide uptake rates for simulated aggregations to determine whether sulfide supply could match the required uptake rates of aggregations (for specific methodology see methods). HC, C6+ hydrocarbons; orgC, organic carbon; ox, oxidation reaction; red, reduction reaction.
Figure 4
Figure 4. L. luymesi Growth Rate
Size-specific growth of L. luymesi determined from stained tubeworms. Different colors indicate growth data from different aggregations. Blue points labeled “2000” are all from Bergquist et al. [26]. Other colored points refer to submersible dive numbers from 2003 when stained aggregations were collected. (A) Growth function and 95% confidence interval for size-specific growth. (B) Error function fitted to the residuals of the model.
Figure 5
Figure 5. Concentration Profiles of Sulfate, Sulfide, and DOC
Points represent average concentration at a given depth from 13 sediment cores taken around the periphery of tubeworm aggregations (see Materials and Methods and original data in [13,28]). Best-fitted line based on least squares fit of equation 9.
Figure 6
Figure 6. Sediment Porosity Values
Points represent average porosity at a given depth from 13 sediment cores taken around the periphery of tubeworm aggregations (see Materials and Methods and original data in [13,28]). Best-fitted line based on least squares fit of equation 9.

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