| Summary: | Permanently frozen soil, or permafrost, hosts a diversity of viable microbial life despite constant subzero temperatures, water stress, increased salinity, and low nutrient availability. Yet the metabolic strategies utilized by permafrost microorganisms that enable survival through millennia entrained in ice are minimally understood. To investigate community metabolic activity and functional potential through geologic time with no influx energy or new material, we applied extracellular enzyme assays coupled with metagenomic sequencing to a chronosequence of Pleistocene permafrost ranging in age from 19,000-33,000 years before present (Kyr). Extracellular enzyme assays revealed differences in community metabolic activity by age group and an overall decrease in total community activity across the chronosequence. We observed the highest activity in enzymes capable of hydrolyzing cellulose, peptidoglycan, and leucine compared to those that can hydrolyze lignocellulosic polysaccharides found in woody biomass. Similarly, results indicated that terminal polymeric cleavage (exolytic) activity was significantly higher than internal cleavage (endolytic) activity as each age category, which is likely driven by inaccessibility of nutrients within the static subzero soil matrix. Analyses of genes encoding carbohydrate-active enzymes revealed age-related patterns of functional domain distribution and abundance, with each age category harboring repertoires of significantly different enzymatic domains. Late-Pleistocene permafrost microbiota transition from a reliance on high-molecular weight detrital plant biomass (19Kyr), to utilization of storage carbohydrates and amino-sugars (27Kyr), to metabolism of peptidoglycan biopolymers of microbial origin and/or necromass (33Kyr). Enrichment of peptidoglycan-metabolic domains - involved in predation or nutrient scavenging - in the oldest permafrost samples is consistent with dormancy strategies that enable survival of microbes in extreme subzero conditions. Taken together, these data ...
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