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Marine deep subsurface sediment is often a microbial environment under energy-limited conditions. However, microbial life has been found to persist and even thrive in deep subsurface environments. The Mariana forearc represents an ideal location for determining how microbial life can withstand extreme conditions including pH 10–12.5 and depleted nutrients. The International Ocean Discovery Program Expedition 366 to the Mariana Convergent Margin sampled three serpentinizing seamounts located along the Mariana forearc chain with elevated concentrations of methane, hydrogen, and sulfide. Across all three seamount summits, the most abundant transcripts were for cellular maintenance such as cell wall and membrane repair, and the most abundant metabolic pathways were the Entner–Doudoroff pathway and tricarboxylic acid cycle. At flank samples, sulfur cycling involving taurine assimilation dominated the metatranscriptomes. The in situ activity of these pathways was supported by the detection of their metabolic intermediates. All samples had transcripts from all three domains of Bacteria, Archaea, and Eukarya, dominated by Burkholderiales, Deinococcales, and Pseudomonales, as well as the fungal group Opisthokonta. All samples contained transcripts for aerobic methane oxidation (pmoABC) and denitrification (nirKS). The Mariana forearc microbial communities show activity not only consistent with basic survival mechanisms, but also coupled metabolic reactions.

Polar permafrost is at the forefront of climate change, yet only a few studies have enriched the native methane-producing microbes that might provide positive feedbacks to climate change. Samples Ant1 and Ant2, collected in Antarctic Miers Valley from permafrost sediments, with and without biogenic methane, respectively, were evaluated for methanogenic activity and presence of methanogens. After a one-year incubation of both samples under anaerobic conditions, methane production was observed only at room temperature in microcosm Ant1 with CO2/H2 (20/80) as carbon and energy sources and was monitored during the subsequent 10 years. The concentration of methane in the headspace of microcosm Ant1 changed from 0.8% to a maximum of 45%. Archaeal 16S rRNA genes from microcosm Ant1 were related to psychrotolerant Methanosarcina lacustris. Repeated efforts at achieving a pure culture of this organism were unsuccessful. Metagenomic reads obtained for the methane-producing microcosm Ant1 were assembled and resulted in a 99.84% complete genome affiliated with the genus Methanosarcina. The metagenome assembled genome contained cold-adapted enzymes and pathways suggesting that the novel uncultured Methanosarcina sp. Ant1 is adapted to sub-freezing conditions in permafrost. This is the first methanogen genome reported from the 15 000 years old permafrost of the Antarctic Dry Valleys.

Two common quantification methods for subseafloor microorganisms are catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) and quantitative PCR (qPCR). Using these methods, we quantified Bacteria and Archaea in Baltic Sea basin sediments (IODP Exp. 347) down to 90 mbsf, testing the following hypotheses in an inter-laboratory comparison: 1) proteinase K permeabilization of Archaeal cell walls increases CARD-FISH accuracy, and 2) qPCR varies by more than an order of magnitude between laboratories using similar protocols. CARD-FISH counts did not differ between permeabilization treatments, demonstrating that proteinase K did not increase accuracy of CARD-FISH counts. However, 91% of these counts were below the quantification limit of 1.3 × 107 cells cm−3. For qPCR, data varied between laboratories, but were largely within the same order of magnitude if the same primers were used, with 88% of samples being above the quantification limit. Copy number values were elevated by preparing a sediment slurry before DNA extraction: 3.88 ×106 to 2.34 ×109 16S rRNA gene copies cm−3 vs. 1.39 × 107 to 1.87 × 109 total cells cm−3. By qPCR, Bacteria were more abundant than Archaea, although they usually were within the same order of magnitude. Overall, qPCR is more sensitive than CARD-FISH, but both require optimization to consistently achieve both precision and accuracy.

For accurate quantification of DNA and RNA from environmental samples, yield loss during nucleic acid purification has to be minimized. Quantitative PCR (qPCR) and reverse transcription (RT)-qPCR require a trade-off between maximizing yield and removing inhibitors. We compared DNA and RNA yield and suitability for quantitative SYBR Green PCR and RT-PCR using the UltraClean and PowerSoil extraction kits and a bead-beating protocol with phenol/chloroform extraction steps. Purification methods included silica-column-based procedures from the MoBio kits, RNeasy MinElute, WizardPlus miniprep columns, and an acrylamide gel extraction. DNA and RNA purification with WizardPlus and RNeasy, respectively, led to significant losses of nucleic acids and archaeal 16S rRNA or 16S rRNA gene, as measured with RiboGreen or PicoGreen, and RT-qPCR or qPCR. Extraction and purification of DNA with the MoBio DNA UltraClean and DNA PowerSoil kits also decreased the yields slightly, relative to gel purification, in all sediments, except those from the deep sea in the Gulf of Mexico. Organic matter in humic-rich sediments may bind to these silica columns, reducing their nucleic acid-loading capacity. Purification with gel extraction cleans up organic-rich sediment samples sufficiently for quantitative analysis while avoiding the yield loss associated with commonly used silica columns.