Development of droplet digital PCR assays for methanogenic taxa and examination of methanogen communities in full-scale anaerobic digesters

Application of ddPCR for detection of Enterococcus spp. in coastal water quality monitoring

Droplet digital polymerase chain reaction (ddPCR) was evaluated for the detection of fecal indicator bacteria (FIB), Enterococcus spp., in San Diego County beach water samples collected under diverse conditions, from multiple pollution sources, as part of regulatory monitoring activities over 20 months. Two US EPA-approved methods, qPCR (EPA 1609.1) and Enterolert (SM9230D), were used as reference comparator methods. A total of 361 samples were assayed by both ddPCR and qPCR and yielded an acceptable Index of Agreement (IA) of 0.89, based on EPA Site-Specific analysis guidelines. A Pearson's correlation coefficient of r = 0.87 (p < 0.001), further indicated a strong relationship between the methods results. From the 361 samples, 185 split samples with ddPCR and Enterolert values within the limits of quantification, were used as a 'training' data set to derive an intrinsic copy number equation (ICE) for scaling ddPCR gene copy number to Enterolert most probable number (MPN). Of the 1993 samples that comprised the complete 'test' data set assayed by ddPCR and Enterolert, 1086 generated results that fell within the limits of quantification for Enterolert and yielded an overall IA of 0.64. Re-analysis using median as a measure of central tendency to account for significant skewing of Enterolert data yielded an IA of 0.72. Beach grouping-specific IA values ranged from 0.63 to 0.93. Pearson's correlation coefficient, r, ranged from 0.13 to 0.94 within beach groupings and generated a combined value of 0.60 for all groupings. Using the ICE, a ddPCR advisory threshold of 1413 DNA copy number/100 mL was empirically determined to be the equivalent to the California Enterolert beach action threshold of 104 MPN/100 mL, based on comparison with all 1993 paired ddPCR and Enterolert results. Using the 1413 DNA copy number/100 mL as a beach action threshold for ddPCR resulted in a 90.4% agreement with Enterolert (6.0% false negative and 3.7% false positive). Together these findings support the conclusion that ddPCR readouts align closely with Enterolert MPN for identifying FIB exceedance levels of Enterococcus spp. in coastal waters of San Diego, CA.

Impact of decreasing hydraulic retention times on the specific affinity of methanogens and their community structures in an anaerobic membrane bioreactor process treating low strength wastewater

Maximum specific growth rate (μ_max) and substrate saturation constant (K_s) are widely used in determining the growth of microorganisms. The ratio (μ_max/K_s), also referred to as specific affinity, a_A⁰, is a better parameter to assess the advantage in competition for substrates by bridging microbial growth and the kinetics of enzymatic substrate uptake, but is not well studied. This study investigated the effect of hydraulic retention time (HRT) on the a_A⁰ of anaerobic sludge from an anaerobic membrane bioreactor (AnMBR), associated microbial communities and the overall wastewater treatment performance. The AnMBR was fed with acetate wastewater (~500 mg COD/L) and operated at fixed solids retention time (45 d) while HRT continued to decrease. There was no significant difference in K_s (ranging from 170 to 243 mg COD/L) at different HRTs. However, a_A⁰ increased from (4.0 ± 0.2) × 10^-4 to (4.9 ± 0.2) × 10^-4 and to (6.5 ± 0.1) × 10^-4 L/mg COD/d as HRT decreased from 24 h to 12 h and further to 6 h, respectively. This was accompanied by the increase in acetoclastic methanogens (mainly Methanosaeta) from 3.85 × 10¹⁰, 8.82 × 10¹⁰ to 1.05 × 10¹¹ cells/L, respectively. The fraction of Methanosaeta in the anaerobic biomass increased from 33.67% to 61.08% as HRT decreased from 24 h to 6 h. Correspondingly, effluent quality was improved, as evidenced from the COD concentrations of 32 ± 6, 21 ± 4, and 13 ± 5 mg/L at the HRTs of 24 h, 12 h, and 6 h, respectively. The results confirm that microorganisms are able to adapt to growth conditions by adjusting their kinetic properties and suggest that short HRTs in the AnMBR favor the growth and accumulation of Methanosaeta with high specific affinity likely because they can compete for acetate at low concentrations by increasing substrate uptake rate and thus specific microbial growth rate.

The quest for absolute abundance: The use of internal standards for DNA-based community ecology

To characterize microbiomes and other ecological assemblages, ecologists routinely sequence and compare loci that differ among focal taxa. Counts of these sequences convey information regarding the occurrence and relative abundances of taxa, but provide no direct measure of their absolute abundances, due to the technical limitations of the sequencing process. The relative abundances in compositional data are inherently constrained and difficult to interpret. The incorporation of internal standards (ISDs; colloquially referred to as 'spike-ins') into DNA pools can ameliorate the problems posed by relative abundance data and allow absolute abundances to be approximated. Unfortunately, many laboratory and sampling biases cause ISDs to underperform or fail. Here, we discuss how careful deployment of ISDs can avoid these complications and be an integral component of well-designed studies seeking to characterize ecological assemblages via sequencing of DNA.

The microbiome driving anaerobic digestion and microbial analysis

The microbiome residing in anaerobic digesters drives the anaerobic digestion (AD) process to convert various feedstocks to biogas as a renewable source of energy. This microbiome has been investigated in numerous studies in the last century. The early studies used cultivation-based methods and analysis to identify the four guilds (or functional groups) of microorganisms. Molecular biology techniques overcame the limitations of cultivation-based methods and allowed the identification of unculturable microorganisms, revealing the high diversity of microorganisms involved in AD. In the past decade, omics technologies, including metataxonomics, metagenomics, metatranscriptomics, metaproteomics, and metametabolomics, have been or start to be used in comprehensive analysis and studies of biogas-producing microbiomes. In this chapter, we reviewed the utilities and limitations of these analysis methods, techniques, and technologies when they were used in studies of biogas-producing microbiomes, as well as the new information on diversity, composition, metabolism, and syntrophic interactions of biogas-producing microbiomes. We also discussed the current knowledge gaps and the research needed to further improve AD efficiency and stability.

Specific affinity and relative abundance of methanogens in acclimated anaerobic sludge treating low-strength wastewater

Kinetic parameters affecting effluent water quality including half saturation constant (K_s), maximum specific growth rate (μ_max), and specific affinity ([Formula: see text], defined as μ_max/K_s) were investigated using three types of anaerobic sludge (raw anaerobic digestion sludge referred to as unacclimated sludge, unacclimated sludge after endogenous decay, and sludge acclimated to low-strength wastewater in an anaerobic membrane bioreactor (AnMBR) for 360 days). Long-term acclimation to low-strength wastewater resulted in sludge with high specific affinity (1.6 × 10^-3 L/mg COD/day for acclimated sludge compared to 4.1 × 10^-4 L/mg COD/day for unacclimated sludge). The μ_max values for unacclimated sludge and acclimated sludge were 0.08 and 0.07 day^-1, respectively. The K_s values for unacclimated sludge and acclimated sludge were 194 ± 81 mg COD/L and 45 ± 13 mg COD/L, respectively. Although the K_s of unacclimated sludge after endogenous decay increased to 772 ± 74 mg COD/L, μ_max increased to 0.35 day^-1 as well, resulting in no statistically significant difference of [Formula: see text] between the two types of unacclimated sludge. Overall, [Formula: see text] is a better indicator than μ_max or K_s alone for determining effluent water quality, as effluent substrate concentration is approximately inversely proportional to the specific affinity. 16S rRNA sequencing data analysis indicated a high abundance (85.8% of total archaea) of Methanosaeta in the microbial community after long-term acclimation. High [Formula: see text] associated with the enrichment of Methanosaeta appears to ensure successful anaerobic treatment of low-strength wastewater.

Assessing Methanogenic Archaeal Community in Full Scale Anaerobic Sludge Digester Systems in Dubai, United Arab Emirates

Introduction:

Anaerobic digestion for methane production comprises of an exceptionally diverse microbial consortium, a profound understanding about which is still constrained. In this study, the methanogenic archaeal communities in three full-scale anaerobic digesters of a Municipal Wastewater Treatment Plant were analyzed by Fluorescence in situ hybridization and quantitative real-time Polymerase Chain Reaction (qPCR) technique.

Methods & Materials:

Fluorescence in situ hybridization (FISH) was performed to detect and quantify the methanogenic Archaea in the sludge samples whereas qPCR was carried out to support the FISH analysis. Multiple probes targeting domain archaea, different orders and families of Archaea were used for the studies.

Results and Discussion:

In general, the aceticlastic organisms (Methanosarcinaceae & Methanosaetaceae) were more abundant than the hydrogenotrophic organisms (Methanobacteriales, Methanomicrobiales, Methanobacteriaceae & Methanococcales). Both FISH and qPCR indicated that family Methanosaetaceae was the most abundant suggesting that aceticlastic methanogenesis is probably the dominant methane production pathway in these digesters.

Conclusion:

Future work involving high-throughput sequencing methods and correlating archaeal communities with the main operational parameters of anaerobic digesters will help to obtain a better understanding of the dynamics of the methanogenic archaeal community in wastewater treatment plants in United Arab Emirates (UAE) which in turn would lead to improved performance of anaerobic sludge digesters.

Flow cytometric quantification, sorting and sequencing of methanogenic archaea based on F420 autofluorescence

Background

The widely established production of CH₄ from renewable biomass in industrial scale anaerobic reactors may play a major role in the future energy supply. It relies on methanogenic archaea as key organisms which represent the bottleneck in the process. The quantitative analysis of these organisms can help to maximize process performance, uncover disturbances before failure, and may ultimately lead to community-based process control schemes. Existing qPCR and fluorescence microscopy-based methods are very attractive but can be cost-intensive and laborious.

Results

In this study we present an autofluorescence-based, flow cytometric method for the fast low-cost quantification of methanogenic archaea in complex microbial communities and crude substrates. The method was applied to a methanogenic enrichment culture (MEC) and digester samples (DS). The methanogenic archaea were quantified using the distinct fluorescence of their cofactor F₄₂₀ in a range from 3.7 × 10⁸ (± 3.3 × 10⁶) cells mL⁻¹ and 1.8 x 10⁹ (± 1.1 × 10⁸) cells mL⁻¹. We evaluated different fixation methods and tested the sample stability. Stable abundance and fluorescence intensity were recorded up to 26 days during aerobic storage in PBS at 6 °C. The discrimination of the whole microbial community from the ubiquitous particle noise was facilitated by SYBR Green I staining and enabled calculation of relative abundances of methanogenic archaea of up to 9.64 ± 0.23% in the MEC and up to 4.43 ± 0.74% in the DS. The metaprofiling of the mcrA gene reinforced the results.

Conclusions

The presented method allows for fast and reliable quantification of methanogenic archaea in microbial communities under authentic digester conditions and can thus be useful for process monitoring and control in biogas digesters.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0793-7) contains supplementary material, which is available to authorized users.

Schrödinger's microbes: Tools for distinguishing the living from the dead in microbial ecosystems

While often obvious for macroscopic organisms, determining whether a microbe is dead or alive is fraught with complications. Fields such as microbial ecology, environmental health, and medical microbiology each determine how best to assess which members of the microbial community are alive, according to their respective scientific and/or regulatory needs. Many of these fields have gone from studying communities on a bulk level to the fine-scale resolution of microbial populations within consortia. For example, advances in nucleic acid sequencing technologies and downstream bioinformatic analyses have allowed for high-resolution insight into microbial community composition and metabolic potential, yet we know very little about whether such community DNA sequences represent viable microorganisms. In this review, we describe a number of techniques, from microscopy- to molecular-based, that have been used to test for viability (live/dead determination) and/or activity in various contexts, including newer techniques that are compatible with or complementary to downstream nucleic acid sequencing. We describe the compatibility of these viability assessments with high-throughput quantification techniques, including flow cytometry and quantitative PCR (qPCR). Although bacterial viability-linked community characterizations are now feasible in many environments and thus are the focus of this critical review, further methods development is needed for complex environmental samples and to more fully capture the diversity of microbes (e.g., eukaryotic microbes and viruses) and metabolic states (e.g., spores) of microbes in natural environments.

Characterization of Aspergillus section Nigri species populations in vineyard soil using droplet digital PCR

Identification of populations of Aspergillus section Nigri species in environmental samples using traditional methods is laborious and impractical for large numbers of samples. We developed species-specific primers and probes for quantitative droplet digital PCR (ddPCR) to improve sample throughput and simultaneously detect multiple species in each sample. The ddPCR method was used to distinguish Aspergillus niger, Aspergillus welwitschiae, Aspergillus tubingensis and Aspergillus carbonarius in mixed samples of total DNA. Relative abundance of each species measured by ddPCR agreed with input ratios of template DNAs. Soil samples were collected at six time points over two growing seasons from two raisin vineyards in Fresno County, California. Aspergillus section Nigri strains were detected in these soils in the range of 10² -10⁵  CFU g^-1 . Relative abundance of each species varied widely among samples, but in 52 of 60 samples, A. niger was the most abundant species, ranging from 38 to 88% of the total population. In combination with total plate counts, this ddPCR method provides a high-throughput method for describing population dynamics of important potential mycotoxin-producing species in environmental samples.

SIGNIFICANCE AND IMPACT OF THE STUDY

This is the first study to demonstrate the utility of ddPCR as a means to quantify species of Aspergillus section Nigri in soil. This method eliminates the need for isolation and sequence identification of individual fungal isolates, and allows for greater throughput in measuring relative population sizes of important (i.e. mycotoxigenic) Aspergillus species within a population of morphologically indistinguishable species.