Evaluation and optimization of PCR primers for selective and quantitative detection of marine ANME subclusters involved in sulfate-dependent anaerobic methane oxidation

Anaerobic methane oxidation coupled to arsenate reduction in paddy soils: Insights from laboratory and field studies

Anaerobic methane oxidation (AOM) coupled to nitrate, sulfate and iron has been most extensively studied. Recently, AOM coupled with arsenate reduction (AOM-AsR) was demonstrated in laboratory microcosm incubation, however whether AOM-AsR is active in the field conditions remains elusive. Here, we used 13C-labeled methane (13CH4) to investigate the AOM-AsR process in both anaerobic microcosms and field conditions with identical soils. Our results revealed the occurrence of AOM-AsR in the field, but AOM-AsR in the field was not as active as that which occurred in the laboratory (AOM-AsR contributed approximately 33.87% and 80.76% of total As release in the field and laboratory studies, respectively). This occurred because the laboratory setting provided a more suitable condition for the AOM-AsR process. Moreover, the results suggested that the relative abundance of mcrA from the ANME-2d was the most abundant. Our results clearly demonstrate that the AOM-AsR is active in both the laboratory and field conditions. Moreover, the results highlight the potential risk the AOM-AsR for pose for As contamination in rice paddies.

Development of real-time PCR methods for the quantification of Methanoculleus, Methanosarcina and Methanobacterium in anaerobic digestion

Anaerobic digestion is a growing technology to manage organic waste and produce bioenergy. To promote this technology, it is essential to know, at the molecular level, the dynamics of microbial communities, specifically the methanogenic community. In the present study, three primer pairs were selected from seven primer pairs which were designed and tested with different concentrations and conditions to detect Methanosarcina, Methanoculleus and Methanobacterium by real-time PCR based on the SYBR Green System. The functionality of the developed methods was demonstrated by the high linear relationship of the standard curves, and the specificity of each primer was empirically verified by testing DNA isolated from methane-producing and non-producing strains. These assays also exhibited good repeatability and reproducibility, which indicates the robustness of the methods. The described primers were successfully used to investigate the methanogenic communities of 10 samples from an anaerobic co-digestion. The genus Methanosarcina was the dominant methanogenic group.

Elemental sulfur-based autotrophic denitrification in stoichiometric S0/N ratio: Calibration and validation of a kinetic model

The inclusion of S⁰ hydrolysis in a kinetic model of autotrophic denitrification has been recently proposed; however the model has not been calibrated or validated yet. Thus, a new methodology was developed and applied to calibrate and validate this kinetic model for the first time. An inoculum adapted from a poultry wastewater treatment plant at stoichiometric S⁰/NO₃^- ratio was used. The model was calibrated with batch data (initial nitrate concentrations of 50 and 6.25 mg NO₃^--N/L) at an S⁰/N ratio = 2.29 mg S/mg N and validated with seven different batch data. The sensitivity analysis showed that the most sensitive parameters are related to S⁰ hydrolysis. The kinetic model was successfully calibrated with the new methodology and validated, with Theil inequality coefficient values lower than 0.21. Thus, the proposed model and methodology were proved to be well suited for the simulation of elemental sulfur-based autotrophic denitrification in batch systems.

Taxonomic classification and abundance estimation using 16S and WGS-A comparison using controlled reference samples

The assessment of microbiome biodiversity is the most common application of metagenomics. While 16S sequencing remains standard procedure for taxonomic profiling of metagenomic data, a growing number of studies have clearly demonstrated biases associated with this method. By using Whole Genome Shotgun sequencing (WGS) metagenomics, most of the known restrictions associated with 16S data are alleviated. However, due to the computationally intensive data analyses and higher sequencing costs, WGS based metagenomics remains a less popular option. Selecting the experiment type that provides a comprehensive, yet manageable amount of information is a challenge encountered in many metagenomics studies. In this work, we created a series of artificial bacterial mixes, each with a different distribution of skin-associated microbial species. These mixes were used to estimate the resolution of two different metagenomic experiments - 16S and WGS - and to evaluate several different bioinformatics approaches for taxonomic read classification. In all test cases, WGS approaches provide much more accurate results, in terms of taxa prediction and abundance estimation, in comparison to those of 16S. Furthermore, we demonstrate that a 16S dataset, analysed using different state of the art techniques and reference databases, can produce widely different results. In light of the fact that most forensic metagenomic analysis are still performed using 16S data, our results are especially important.

Harnessing a methane-fueled, sediment-free mixed microbial community for utilization of distributed sources of natural gas

Harnessing the metabolic potential of uncultured microbial communities is a compelling opportunity for the biotechnology industry, an approach that would vastly expand the portfolio of usable feedstocks. Methane is particularly promising because it is abundant and energy‐rich, yet the most efficient methane‐activating metabolic pathways involve mixed communities of anaerobic methanotrophic archaea and sulfate reducing bacteria. These communities oxidize methane at high catabolic efficiency and produce chemically reduced by‐products at a comparable rate and in near‐stoichiometric proportion to methane consumption. These reduced compounds can be used for feedstock and downstream chemical production, and at the production rates observed in situ they are an appealing, cost‐effective prospect. Notably, the microbial constituents responsible for this bioconversion are most prominent in select deep‐sea sediments, and while they can be kept active at surface pressures, they have not yet been cultured in the lab. In an industrial capacity, deep‐sea sediments could be periodically recovered and replenished, but the associated technical challenges and substantial costs make this an untenable approach for full‐scale operations. In this study, we present a novel method for incorporating methanotrophic communities into bioindustrial processes through abstraction onto low mass, easily transportable carbon cloth artificial substrates. Using Gulf of Mexico methane seep sediment as inoculum, optimal physicochemical parameters were established for methane‐oxidizing, sulfide‐generating mesocosm incubations. Metabolic activity required >∼40% seawater salinity, peaking at 100% salinity and 35 °C. Microbial communities were successfully transferred to a carbon cloth substrate, and rates of methane‐dependent sulfide production increased more than threefold per unit volume. Phylogenetic analyses indicated that carbon cloth‐based communities were substantially streamlined and were dominated by Desulfotomaculum geothermicum. Fluorescence in situ hybridization microscopy with carbon cloth fibers revealed a novel spatial arrangement of anaerobic methanotrophs and sulfate reducing bacteria suggestive of an electronic coupling enabled by the artificial substrate. This system: 1) enables a more targeted manipulation of methane‐activating microbial communities using a low‐mass and sediment‐free substrate; 2) holds promise for the simultaneous consumption of a strong greenhouse gas and the generation of usable downstream products; and 3) furthers the broader adoption of uncultured, mixed microbial communities for biotechnological use.