Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem.
We have constructed a conceptual model of biogeochemical cycles and metabolic and microbial community shifts within a hot spring ecosystem via coordinated analysis of the "Bison Pool" (BP) Environmental Genome and a complementary contextual geochemical dataset of ~75 geochemical parameters. 2,321 16S rRNA clones and 470 megabases of environmental sequence data were produced from biofilms at five sites along the outflow of BP, an alkaline hot spring in Sentinel Meadow (Lower Geyser Basin) of Yellowstone National Park. This channel acts as a >22 m gradient of decreasing temperature, increasing dissolved oxygen, and changing availability of biologically important chemical species, such as those containing nitrogen and sulfur. Microbial life at BP transitions from a 92 °C chemotrophic streamer biofilm community in the BP source pool to a 56 °C phototrophic mat community. We improved automated annotation of the BP environmental genomes using BLAST-based Markov clustering. We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. This assignment yields high genome coverage in dominant community members, facilitating reconstruction of nearly complete metabolic profiles and in-depth analysis of the relation between geochemical and metabolic changes along the outflow. We show that changes in environmental conditions and energy availability are associated with dramatic shifts in microbial communities and metabolic function. We have also identified an organism constituting a novel phylum in a metabolic "transition" community, located physically between the chemotroph- and phototroph-dominated sites. The complementary analysis of biogeochemical and environmental genomic data from BP has allowed us to build ecosystem-based conceptual models for this hot spring, reconstructing whole metabolic networks in order to illuminate community roles in shaping and responding to geochemical variability.
School of Natural Sciences, University of California Merced, Merced, California, United States of America.
Wesley D
WD
Swingley
D'Arcy R
DR
Meyer-Dombard
Everett L
EL
Shock
Eric B
EB
Alsop
Heinz D
HD
Falenski
Jeff R
JR
Havig
Jason
J
Raymond
D017753:Ecosystem; D014644:Genetic Variation; D016678:Genome / Q000235:genetics; D005844:Geology; D045482:Hot Springs / Q000382:microbiology; D008390:Markov Chains; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D056186:Metagenomics / Q000379:methods*; D058458:Nitrogen Cycle; D011506:Proteins / Q000235:genetics; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA; D014131:Trace Elements / Q000032:analysis; D014959:Wyoming
D011506:Proteins; D012336:RNA, Ribosomal, 16S; D014131:Trace Elements