RESUMEN
Oxygen constitutes one of the strongest factors explaining microbial taxonomic variability in deep-sea sediments. However, deep-sea microbiome studies often lack the spatial resolution to study the oxygen gradient and transition zone beyond the oxic-anoxic dichotomy, thus leaving important questions regarding the microbial response to changing conditions unanswered. Here, we use machine learning and differential abundance analysis on 184 samples from 11 sediment cores retrieved along the Arctic Mid-Ocean Ridge to study how changing oxygen concentrations (1) are predicted by the relative abundance of higher taxa and (2) influence the distribution of individual Operational Taxonomic Units. We find that some of the most abundant classes of microorganisms can be used to classify samples according to oxygen concentration. At the level of Operational Taxonomic Units, however, representatives of common classes are not differentially abundant from high-oxic to low-oxic conditions. This weakened response to changing oxygen concentration suggests that the abundance and prevalence of highly abundant OTUs may be better explained by other variables than oxygen. Our results suggest that a relatively homogeneous microbiome is recruited to the benthos, and that the microbiome then becomes more heterogeneous as oxygen drops below 25 µM. Our analytical approach takes into account the oft-ignored compositional nature of relative abundance data, and provides a framework for extracting biologically meaningful associations from datasets spanning multiple sedimentary cores.
RESUMEN
The reconstruction of past climate variability using physical and geochemical parameters from lake sedimentary records is a well-established and widely used approach. These geological records are also known to contain large and active microbial communities, believed to be responsive to their surroundings at the time of deposition, and proceed to interact intimately with their physical and chemical environment for millennia after deposition. However, less is known about the potential legacy of past climate conditions on the contemporary microbial community structure. We analysed two Holocene-length (past 10 ka BP) sediment cores from the glacier-fed Ymer Lake, located in a highly climate-sensitive region on south-eastern Greenland. By combining physical proxies, solid as well as fluid geochemistry, and microbial population profiling in a comprehensive statistical framework, we show that the microbial community structure clusters according to established lithological units, and thus captures past environmental conditions and climatic transitions. Further, comparative analyses of the two sedimentary records indicates that the manifestation of regional climate depends on local settings such as water column depth, which ultimately constrains microbial variability in the deposited sediments. The strong coupling between physical and geochemical shifts in the lake and microbial variation highlights the potential of molecular microbiological data to strengthen and refine existing sedimentological classifications of past environmental conditions and transitions. Furthermore, this coupling implies that microbially controlled transformation and partitioning of geochemical species (e.g., manganese and sulphate) in Ymer lake today is still affected by climatic conditions that prevailed thousands of years back in time.