Keywords

10.1 Introduction

Molecular biological tools (MBTs) are a category of environmental molecular diagnostics (Busch-Harris et al. 2008), which provide essential information for evaluating ongoing and potential degradation of petroleum hydrocarbons (PHCs) by microorganisms. MBTs provide critical information for effective site characterization, remedy selection, performance monitoring, and site closure (Fig. 10.1).

Fig. 10.1
A 4-part info-graphic chart. It lists questions under the headings, characterization, remediation, monitoring, and closure. They are as follows. Multiple sources? Is biotic and or abiotic degradation occurring and the need for additional evidence to finalize closure?, respectively.

Adapted from Interstate Technology and Regulatory Council (ITRC 2013)

Questions MBTs can help answer. MNA refers to monitored natural attenuation.

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MBTs measure the organisms and genes involved in contaminant biodegradation and provide evidence for understanding changes in rates of abiotic and biotic degradative processes over background. MBTs complement conventional hydrogeological, chemical, and geochemical data, as part of a multiple lines of evidence approach to provide a comprehensive picture of the concentrations of contaminants and associated products, the redox status, electron acceptors, electron donors, microbiology, and degradation of contaminants. This multiple lines of evidence approach is critically important for selecting the appropriate remediation strategy, monitoring remediation effectiveness, and supporting transition to monitored natural source zone depletion (NSZD) and monitored natural attenuation (MNA). Natural attenuation processes are further discussed in Chaps. 5, 9, and 13. Details of active bioremediation approaches are presented in Chap. 14.

Here, we review MBT integration into site management and use case studies to highlight the critical evidence MBTs provide to decision-makers.

10.2 MBTs Used in PHC Investigation and Remediation

Several MBTs can be employed at contaminated sites—quantitative polymerase chain reaction (qPCR), qPCR arrays, reverse transcription-qPCR (RT-qPCR), stable isotope analysis methods such as stable isotope probing (SIP) and compound-specific isotope analysis (CSIA), or DNA sequencing (amplicon sequencing or metagenome sequencing)—to improve conceptual site models or aid in the remediation design or decision-making, as described below. The samples to be assayed are typically obtained using grab sampling or passive sampling approaches like in-situ microcosms (ISMs).

For nucleic acid-based MBTs, including qPCR, RT-qPCR, and DNA sequencing, groundwater sampling methods can significantly influence results (Alleman et al. 2005; Ritalahti et al. 2010). Therefore, the sampling protocol should be defined and maintained for the duration of the monitoring effort. At a minimum, sampling should use low-flow purging methods, and, immediately after sampling, the samples should be placed in coolers with ice packs and/or blue ice to ensure refrigeration at 4 °C until arrival at the analytical laboratory (Lebrón et al. 2011).

10.2.1 In-Situ Microcosms (ISMs)

ISMs sample subsurface conditions to assess biodegradation associated with natural attenuation (e.g., MNA) and enhance bioremediation, specifically biostimulation (i.e., addition of rate-limiting nutrients, electron acceptors, and electron donors). These data can be used to estimate amendment effectiveness prior to pilot- or full-scale biostimulation approaches (Taggart and Clark 2021). ISMs typically consist of a two- or three-unit assembly, one unit for assessing biodegradation associated with MNA and the second and third units for assessing biodegradation associated with various amendments for biostimulation. Each unit commonly consists of a length of slotted PVC pipe that hoses samplers to quantify geochemical parameters—including electron acceptors (nitrate and sulfate), dissolved gases (methane, ethene, and ethane), and chloride—concentration of PHCs and associated products, and microorganism genera and genes by a nucleic acid-based MBT (e.g., qPCR). The analyses are conducted after the ISM is incubated in a monitoring well for 30–60 days and can be used in combination with SIP or CSIA (Sects. 10.2.4 and 10.2.5 below; see also Chap. 11 for further details on CSIA). Successful ISM studies can provide in-situ biodegradation data and could be done to complement bench-, pilot-, or full-scale biostimulation design and implementation.

10.2.2 Quantitative Polymerase Chain Reaction (qPCR)

qPCR is used to quantify taxonomic groups (genera, species, and strains) and genes which encode enzymes capable of degrading PHCs in soil or groundwater. qPCR is now used instead of counting colonies on agar plates and other culture-based methods that recover a lower percentage of microbes. qPCR is accurate, sensitive to low microbial concentrations (detection limit as low as 10 cells/ml), and precise in detecting genes over a large dynamic range (~seven orders of magnitude) (Forootan et al. 2017).

Thus, qPCR determines the presence of target microbes and genes, their abundance (expressed as cells/mL), changes in their abundance over time or space, and whether they are present in sufficient quantities for bioremediation. At baseline, qPCR is used to assess microbial abundances pretreatment. In response to treatments, the growth of the microorganisms, measured as an increase in genera/species/strains or specific biodegradation genes, provides evidence supporting treatment effectiveness. Interpreting qPCR over space can be conceptualized as higher abundances of the microbes and contaminant-degrading genes in groundwater or soil impacted by PHC compared to background groundwater or soil, which provides direct evidence for biodegradation.

A single qPCR quantifies a single gene. However, PHCs at contaminated sites are typically complex mixtures of aliphatic, cyclic, and heterocyclic compounds that are potentially biodegraded via multiple genes in multiple anaerobic and aerobic pathways. Thus, the quantification of multiple genes can improve the assessment of biodegradation capacity at a site, depending on site-specific scenarios.

Although the microbes and genes quantified need to have been previously characterized and published, assays are commercially available for the quantification of numerous genes involved in degradation of contaminants of concern (COC). The current commercially available number of different gene targets with potential applicability to PHC-impacted sites is > 80, including more than 12 functional genes associated with polycyclic aromatic hydrocarbon (PAH) biodegradation (Table 10.1).

Table 10.1 Genes and microorganisms involved in the biodegradation of PHCs and other compounds. Abbreviations correspond to the naming convention used by most commercial laboratories. It is not an academic gene labeling convention
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qPCR assays can be multiplexed within a single-tube reaction containing multiple primer pairs and probes. However, these reactions can be prone to mis-priming, artifact amplification products, and erroneous results from cross-reactions. To overcome this risk, qPCR arrays can be used that consist of numerous individual reaction wells (64 per square) of nanoliter volume (33 nL); each reaction contains a single primer pair and probe and is monitored for reaction kinetics individually. Analysis of a broad spectrum of target genes simultaneously is particularly useful for assessing mixtures of contaminants or when evaluating the potential for multiple biodegradation pathways or treatments.

10.2.3 Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR)

RT-qPCR is a variation of qPCR that quantifies RNA transcripts expressed from genes. RT-qPCR not only confirms the presence of a target microorganism(s) or functional gene(s) (i.e., gene that produces an enzyme that degrades a contaminant) but also demonstrates microbes are active for biodegradation. For example, Methylibium petroleiphilum strain PM1 quantified by qPCR in the moderate range (103–104 cells/mL) often does not correlate with aerobic methyl tert-butyl ether (MTBE) biodegradation; rather moderate strain concentrations have been associated with low to moderate MTBE biodegradation (i.e., data in tertiles: low, moderate, and high) (Taggart and Clark 2021). Similarly, in aerobic biodegradation of BTEX compounds (benzene, toluene, ethylbenzene, and xylene), qPCR quantification of the genes encoding toluene dioxygenase and phenol hydroxylase can be high, but the genes’ expression can be low (Taggart and Clark 2021). Thus, site-specific scenarios, such as those described above, may indicate that RNA analysis should be performed.

10.2.4 Stable Isotope Probing (SIP)

SIP is an MBT which assesses biodegradation through the use of a synthetic stable isotope probe; i.e., the COC is synthesized with carbons replaced by 13C. This 13C-labeled stable isotope probe is absorbed to a matrix (e.g., the activated carbon in commercially available Bio-Sep® beads in an ISM) that is placed in monitoring wells. After 30–45 days, the matrix is retrieved, and the probe’s biodegradation by microbes from the aquifer that colonized the matrix is assessed by quantifying the 13C-labeled COC remaining and the quantity of 13C incorporated into microbial biomass—phospholipid fatty acids (PLFA) or nucleic acids (DNA and RNA)—and 13CO2 (i.e., dissolved inorganic carbon: carbon dioxide, bicarbonate, and carbonate). PLFA is a major component of bacterial cell membranes, and for contaminants microbes used as carbon sources, the incorporation of 13C from the stable isotope probe into PLFA indicates that the microbes have grown new cells (biomass). Additionally, carbon can be oxidized to CO2 (mineralization) through PHCs biodegradation. Therefore, the method can also be used to assess biodegradation by microbes that use the probe for energy, as a carbon source, or co-metabolite (i.e., not incorporated into biomass). The incorporation of 13C from the probe into either microbial biomass or CO2 provides conclusive evidence of biodegradation of PHCs in the subsurface.

Evidence of biodegradation from SIP is most commonly used together with changes in contaminant concentrations and contaminant-degrading microbes (determined by qPCR or RT-PCR) for supporting MNA as a site management strategy. An advantage of SIP is that the microbes or genes involved in the biodegradation do not need be known.

10.2.5 Compound-Specific Isotope Analysis (CSIA)

As further discussed in Chap. 11, CSIA measures the ratio of naturally occurring stable isotopes (e.g., 13C/12C, 2H/1H) of a contaminant as an indicator of abiotic degradation or biodegradation. Each element in a compound has a distinct isotopic ratio that is a function of the starting material, manufacturing process, and relative mechanisms of attenuation (e.g., biotic/abiotic degradation, volatilization). Isotopic ratios change (e.g., isotopic fractionation) as compounds degrade due to the slightly faster reaction of the lighter isotope, e.g., 12C reacts more quickly than 13C, resulting in the parent compound becoming enriched with 13C.

Isotope enrichment factors found at sites are compared with those from literature and reference databases that have been previously described for each contaminant. Reference databases also provide links to literature and can generate plots, such as contaminant-degradation (mole fractions), dual-isotope, and modified-Kuder plots.

For compounds that become isotopically enriched, CSIA can identify the occurrence and extent of degradation. In addition to the extent of degradation, CSIA can potentially provide information on contaminant sources and whether plumes consist of comingled contaminants.

However, CSIA is less sensitive in some scenarios. For compounds that exhibit lower isotopic fractionation, such as high-molecular-weight PAHs, fractionation often cannot be concluded until the parent contaminant is biodegraded by > 50–80%. Isotopic enrichment discriminates phase transfer processes poorly compared to biodegradation, although for low-molecular-weight volatile compounds, such as gasoline range hydrocarbons, heavier isotopes are preferentially vaporized (Imfeld et al. 2014). Lastly, contaminants dissolving into the groundwater (e.g., from NAPL) can in some circumstances mask isotope fractionation.

10.2.6 DNA Sequencing

DNA sequencing is used to study mixed communities of organisms by the analysis of their collective DNA. Communities can be analyzed using amplicon sequencing (i.e., 16S rRNA gene sequencing) or metagenome sequencing (i.e., metagenomics) to comprehensively survey the genera/species and genes at a site capable of contaminant biodegradation. Both DNA sequencing approaches provide insights to the large unculturable portion of microbial communities (Mason et al. 2012).

In amplicon sequencing, one gene—typically the 16S ribosomal RNA (rRNA) gene—is sequenced in essentially all the microorganisms in a sample. Primers are used to sequence from conserved regions (DNA sequences that are identical across taxonomic groups of interest) of the target gene and across hypervariable regions (DNA sequences that are different across taxonomic groups of interest) of the gene to capture variation in the target gene of multiple microorganisms. The presence of COC-degrading functional genes can be inferred for taxa (genera or species) with characterized and published genomes. For example, the 16S rRNA gene sequence is used to identify the presence and abundance of Methylibium spp., which contains a functional gene that degrades MTBE under aerobic conditions.

In contrast, metagenome sequencing attempts to identify the sequence of all genes of all organisms present in appreciable numbers in a sample. The DNA from a sample is converted to a library of fragments that is sequenced using high-throughput next generation sequencing (NGS). All sequences are aligned, annotated, and analyzed through comparison with several databases of genomes, genes, and proteins to assign and identify microbial community taxonomy, the genes, and to infer gene functions. Metagenome sequencing can identify genes with previously unknown sequences and genes, such as acetylene hydratase, encoded by diverse sequences across genera.

When the contaminant-degrading genera and genes are not known, DNA sequencing can be used to understand how microbial community members change across a site spatially and temporally, and during or after remediation. Additionally, samples can be grouped by microbial composition and correlated with contaminant chemical compositions and geochemical data. Metagenomics can be useful when the function of species within a genus differs. For example, all Geobacter reduce iron, but only certain Geobacter species reduce sulfur (Rickard 2012). Thus, these functional differences within the genus Geobacter may not be distinguished based on amplicon sequencing (e.g., 16S RNA gene sequencing). As compared to metagenome sequencing, amplicon sequencing can identify more microbial species in a sample due to a greater depth of sequencing and with lower risk for false positives which can result from genome reassembly algorithms (Tovo et al. 2020). Although amplicon sequencing can also identify genera and species, it is only based on known genomes. Lastly, metagenome sequencing can identify functional genes encoding enzymes involved in biodegradation in genomes of unknown microorganisms.

Amplicon sequencing of samples from the Deepwater Horizon oil spill was performed to support the assessment of the fate and intrinsic biodegradation of hydrocarbons related to the release. Sequencing data were used to identify hydrocarbon-degrading bacteria, such as Oleispira antarctica, Thalassolituus oleivorans, and Oleiphilus messinensis, which were enriched within the PHC plume and aided in the biodegradation and attenuation of the oil spill (Hazen et al. 2010).

Both amplicon and metagenome sequencing are useful for understanding how microbial community compositions correlate with contaminant concentrations and geochemistry and change across a site spatially and temporally, and during or after remediation.

10.3 Selection of MBTs

10.3.1 QPCR Versus RT-QPCR

qPCR is commonly recommended as the standard baseline tool to assess the presence, absence, and concentration of COC-degradation-associated microorganisms and/or functional genes due to the quantitative nature and ease of handling DNA compared to RNA (used in RT-qPCR). qPCR is most useful when sampling across steep concentration gradients of COC and/or geochemistry. RT-qPCR is recommended in cases where quantification by qPCR has not correlated with the expected activity. For example, qPCR quantification of the DNA encoding toluene dioxygenase and phenol hydroxylase genes can be high, but the expression of the genes can be low (Taggart and Clark 2021). Thus, COC and/or geochemistry concentrations not correlating with gene concentrations may indicate that RNA analysis should be performed.

10.3.2 SIP Versus CSIA

SIP cannot detect abiotic degradation, so if abiotic degradation is occurring through the addition of zero valent iron (ZVI) or by the presence of naturally occurring minerals such as iron sulfides (FeS, pyrite), iron oxides (e.g., magnetite), green rust, or iron carbonate, then CSIA should be used. If the contaminants are used as both a carbon and energy source, then SIP may be the appropriate choice since some compounds exhibit lower isotopic fractionation during biodegradation (Mancini et al. 2003). SIP may be a better choice if the contaminants are BTEX and MTBE or tert-butyl alcohol (TBA) because it can be successfully employed in the presence of light non-aqueous phase liquid (LNAPL) or high COC concentrations that can confound CSIA results. If the plume is long and dilute, two-dimensional CSIA with carbon and hydrogen isotopes should be considered (Bouchard et al. 2018).

10.3.3 QPCR Versus qPCR Arrays Versus DNA Sequencing

If genera and genes that degrade a COC are known, such as those involved in aerobic and anaerobic degradation of PAH, they can be quantified by qPCR and reported as gene copies/mL. Individual genes can be quantified using qPCR or a qPCR array (See Sect. 10.2.1). If the genera and genes are not known or the goal is to comprehensively understand the microbial communities and how they change spatially (comparing different sampling wells), temporally (comparing samples of a well at different times), with remediation, COC composition, and geochemical data, then DNA sequencing should be used.

10.4 Case Studies

10.4.1 Transition to MNA at a Former Retail Gasoline Station

At a former gasoline station, mass reduction of contaminants by dual-phase extraction (DPE) and soil vapor extraction (SVE) reduced BTEX and MTBE concentrations to asymptotic levels where the mechanical remediation techniques were no longer effective. In assessing the potential for MNA or the need for bioremediation, most monitoring well data indicated decreasing concentrations of BTEX and MTBE, but the trend was inconclusive in one area. Therefore, more evidence was needed to evaluate the option of enhanced bioremediation prior to transition to MNA. qPCR arrays and SIP were used for this purpose (Fig. 10.2).

Fig. 10.2
A grouped bar chart of cells per milliliter that ranges from 1.0 E + 00 to 1.0 E + 06 for six different genes. The maximum concentration is for the P M 1 gene, which is in the range of 1.0 E + 04 to 1.0 E + 06.

Comparison of the concentrations of genes (cells/mL) involved in biodegradation of BTEX, MTBE, and TBA between monitoring wells showing decreasing COC trends (black bars) or no trend (white bars). RMO, toluene/benzene monooxygenases; PHE, phenol hydroxylase; BSS, benzylsuccinate synthase; BCR, benzoyl coenzyme A reductase; PM1, Methylibium petroleiphilum strain PM1 rRNA gene; TBA, tert-butyl alcohol hydroxylase

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A suite of genes involved in aerobic and anaerobic biodegradation of BTEX, PAHs, and other PHCs was quantified using a qPCR array (QuantArray®-Petro). Gene concentrations were compared between sampling wells with decreasing trends and those showing no trend (as defined by Mann–Kendall analysis), which showed that genes involved in BTEX (aerobic and anaerobic) and MTBE biodegradation were at higher concentrations (cells/mL) in the monitoring wells where the BTEX and MTBE were decreasing compared to the wells where there was no trend.

These concentrations of BTEX-, MTBE-, and TBA-degrading microorganisms and genes were compared to the Microbial Insights (MI) qPCR Database of almost one hundred thousand samples from sites from around the world (Microbial Insights Inc. 2021). In wells where the COCs were decreasing, PHE and RMO concentrations in most samples exceeded 70–95% of the samples in the database (Fig. 10.3). Conversely, in samples where low concentrations (ppb) of COCs were lingering and not decreasing, these gene concentrations were below the median of samples in the MI Database. Additionally, the benzylsuccinate synthase (BSS) gene, involved in anaerobic biodegradation of toluene and xylene, was detected only in monitoring wells with decreasing COC trends, and the concentration was relatively low (~35th percentile) in two of the three wells. Furthermore, the MTBE-utilizing strain PM1 and the TBA hydroxylase gene were higher than the median in all monitoring wells, but PM1 concentrations in wells with decreasing trends were in the upper quartile (75–95th percentiles) and TBA hydroxylase concentrations were high (>90th percentile).

Fig. 10.3
A vertical scatterplot of M I database percentiles that ranges from 0 to 100 percent versus 6 different genes. The maximum M I database percentiles are 100% for R M O, P H E, P M 1, and T B A, and the minimum is 0% for R M O and B S S genes.

Percentiles of gene concentration in the Microbial Insights Database for the concentrations of genes involved in biodegradation of BTEX, MTBE, or TBA in monitoring wells with decreasing COC trends (black circles) or no trend (white circles). Genes involved in degrading BTEX or MTBE and TBA: RMO, toluene/benzene monooxygenases; PHE, phenol hydroxylase; BSS, benzylsuccinate synthase; BCR, benzoyl coenzyme A reductase; PM1, Methylibium petroleiphilum strain PM1 rRNA gene; TBA, tert-butyl alcohol hydroxylase

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MBT data generated using a qPCR array provided an additional line of evidence to support transitioning from physical/chemical remediation (DPE and SVE) to MNA. However, the concentrations of genes involved in aerobic BTEX biodegradation were low in one area of the dissolved plume, indicating the potential for aerobic BTEX biodegradation was being limited by existing conditions in that portion of the site.

SIP using 13C-benzene and 13C-MTBE as probes was performed to obtain conclusive evidence of BTEX and MTBE biodegradation. The probes were adsorbed to powdered activated carbon (PAC) within Bio-Sep® beads (25% Nomex and 75% PAC). After incubation of the beads in the monitoring wells for 30 days, they were retrieved and analyzed by gas chromatography with a flame ionized detector (GC-FID) for the incorporation of 13C into biomass, i.e., PLFA. The SIP results conclusively demonstrated that 13C-benzene and 13C-MTBE were being biodegraded (Fig. 10.4).

Fig. 10.4
a. and b. 2 positive-negative bar graphs. It plots P L F A delta superscript 13 C of 0 over 00 for background, M W-1, and M W-5. The maximum P L F A delta superscript 13 C of 0 over 00 is approximately 500 for M W-5 in graph a, and is approximately 30 for M W-8 in graph b.

Incorporation of 13C from 13C-benzene and 13C-MTBE stable isotope probes (SIP) into biomass (PLFA). The δ13C value for most natural substrate/carbon sources is between − 20 and − 30‰ (or per mille). Thus, background PLFA δ13C values are around − 25‰ under natural conditions (white bars). For both benzene (a) and MTBE (b), the enrichment of 13C in PLFA (black bars) compared to background conclusively demonstrates in-situ biodegradation of these contaminants occurring under existing conditions in the aquifer

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In conclusion, in areas where the contaminant concentrations were trending downward, qPCR array data, along with historical COC and geochemical data, demonstrated high concentrations of BTEX- and MTBE-degrading microbes. Additionally, in these downward-trending areas, SIP conclusively demonstrated that benzene and MTBE were being degraded in situ. Further, the results were supported the transition from mechanical remediation to MNA at the site. The use of MBTs to aid site decision-making increased efficiency, reduced costs, and supported earlier site closure.

10.4.2 Oxygen Addition at a Former Retail Gasoline Station

Oxygen was added to the subsurface at a former gasoline station to enhance biodegradation of COCs (BTEX and MTBE) and decrease the time to closure. To assess the effectiveness of the oxygen addition, microorganisms capable of degrading the COCs were quantified before injection (baseline) and periodically after injection (performance monitoring). At baseline, a variety of genes responsible for aerobic BTEX biodegradation were present at relatively low to moderate concentrations in the MI qPCR Database (102–104 cells/bead); after oxygen addition, these genes increased by nearly 3 orders of magnitude (OoMs), demonstrating that the oxygen injection stimulated the growth of the aerobic BTEX degraders (Fig. 10.5).

Fig. 10.5
A double-bar graph of cells per biotrap bead that ranges from 1.0 E + 00 to 1.0 E + 08 for 14 genes. Each bar represents baseline and post-injection, respectively. The maximum concentration of cells per biotrap bead is in the range of 1.0 E + 06 to 1.0 E + 08.

Concentrations of BTEX-degrading genes and an MTBE-degrading strain (PM1) at baseline (white bars) and after injection of an oxygen-releasing product (black bars). Percentiles for sample concentrations in the MI Database are indicated above the bars

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The microorganisms were sampled from monitoring wells (MW-1 and MW-2, two source area wells) using Bio-Trap® samplers, and the genes involved in degrading the COCs were quantified using qPCR array (QuantArray®-Petro). After injection of the oxygen-releasing material, concentrations of ring hydroxylating toluene monooxygenase (RDEG, RMO) and phenol hydroxylase (PHE) genes increased as high as 2–3 orders of magnitude (OoM) in MW-1. Likewise, PHE, RDEG, and RMO concentrations increased more than one OoM in MW-2, demonstrating the growth of aerobic BTEX-degrading microbes. In both monitoring wells after injection, PHE and RDEG concentrations were > 90th percentile in the MI Database. Furthermore, other aromatic oxygenase genes not detected (ND) before injection increased dramatically (up to > 106 cells/bead) following injection (MW-2; TOL, EDO).

In response to the oxygen addition, genes associated with aerobic BTEX biodegradation degraders increased nearly three OoMs and the MTBE-degrading strain PM1 (M. petroleiphilum) increased more than one OoM, which provided a line of evidence that the enhanced bioremediation was successfully implemented and occurring. Thus, qPCR analyses were included in the performance monitoring program at this site to increase performance certainty.

10.4.3 Continuation of MNA at a Pipeline Release in a Remote Area

A former pipeline release in a remote area impacted the groundwater with BTEX, which appeared to decrease based on Mann–Kendall trend analysis. However, to reduce uncertainty due to heterogeneous subsurface conditions, additional evidence of BTEX biodegradation was needed to support the continuation of MNA. qPCR was used to quantify BSS and anaerobic benzene carboxylase (ABC) genes as part of the routine groundwater monitoring of the BTEX plume as well as background wells. The BSS gene can initiate anaerobic biodegradation of toluene (Biegert et al. 1996; Heider et al. 2016) and xylenes (Achong et al. 2001; Kniemeyer et al. 2003; Gieg and Toth 2020; Rabus et al. 2016), and ABC is suggested to initiate anaerobic benzene biodegradation (Abu Laban et al. 2010). During ongoing groundwater monitoring, samples from two background wells (MW-6 and MW-7) and three BTEX-impacted wells (MW-8, MW-9, and MW-10) were analyzed for the concentrations of BSS and ABC genes by qPCR, which indicated the growth of anaerobic BTEX degraders within the dissolved plume (Fig. 10.6).

Fig. 10.6
A bar graph of the concentration of cells per b d for sampling events. The maximum concentration of cells per b d is approximately 1.0 E + 038 for the sixth sampling event in M W-6. Below is a double-bar graph. Each bar represents B S S and A B C, with B S S having the maximum concentration.

Comparison of the concentrations of genes associated with anaerobic BTEX biodegradation (cells/bead) between background (upper panel) and impacted (lower panel) monitoring wells. Missing bars indicate that the sample was assayed but the gene was not detected. Percentiles for sample concentrations in the MI Database are indicated above the bars

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BSS genes for anaerobic toluene biodegradation were detected in only one of the background wells (MW-6) and only during two of the six sampling events. Conversely, BSS genes were detected in all BTEX-impacted wells (MW-8, MW-9, and MW-10) during all but one sampling event. Moreover, BSS gene concentrations (cells/bead) in impacted wells were high. BSS concentrations in MW-8 were higher than in 80–95% of samples in the MI Database, and in MW-9 and MW-10 were above the median, ranging between the 60 and 95th percentiles. Finally, ABC genes for anaerobic benzene biodegradation were occasionally detected in impacted monitoring well MW-9 at high concentrations.

The qPCR data indicated high concentrations of genes associated with anaerobic BTEX biodegradation in the dissolved plume, which, along with converging trends in contaminant concentrations and geochemistry, was a key factor in continuing MNA as an efficient and risk-based remediation approach.

Due to subsurface conditions and fluctuations (e.g., changes in depth to groundwater, potential influx of nutrients from nearby agricultural application), 16S rRNA gene sequencing (i.e., amplicon sequencing) was used to gain further evidence of PHC biodegradation along the plume. These phylogenetic data were analyzed by Principal Coordinate Analysis (PCoA) to visualize similarities in the microbial communities across the site and over time. On PCoA graphs, similar microbial communities cluster together and communities differing most from each other plot farthest apart. In the PCoA graph of communities sampled from monitoring wells at the pipeline-release site (Fig. 10.7), clustering is seen for the background wells (MW6 and MW7) on the right of the PCoA plot, and on the left, the microbial communities of the impacted wells (MW8, MW9, and MW10) cluster together, demonstrating their relatedness and their difference versus the background wells.

Fig. 10.7
A scatter plot of principal coordinate 2 ranging from negative 0.5 to 0.4 versus principal coordinate 1 that ranges from negative 0.4 to 0.6. The maximum values are plotted between (negative 0.4, 0.2) and (0.4, 0.2).

Principal coordinate analysis (PCoA) of the 16S rRNA gene amplicon sequencing data. The microbial communities of impacted and background monitoring wells (MW) are plotted. The numbers following the dash in the monitoring well designation indicate sequential sampling events. The black arrows trace the sequential sampling of MW10

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The microbial communities of background well MW7 and impacted well MW10 were compared. The background well’s (MW7) top genus was the facultative aerobe, Dechloromonas (~29% of total reads), while anaerobes like sulfate-reducing Desulfobulbus and potentially iron-reducing Geobacter were less abundant (~2%). Conversely, in the impacted well, Geobacter was the top genus (~34%), likely due to the anaerobic conditions in the dissolved plume, while Dechloromonas was much less abundant (~4%).

Changes in microbial communities over time can also be seen in the PCoA plot. For example, the first four samples from MW10 form a cluster while the fifth and sixth samples are separated, suggesting a shift in the microbial community with time (Fig. 10.7). The changes in microbial communities from sampling event one to six in MW10, shown in the PCoA plot, are shown as a stacked bar chart in Fig. 10.8. During the first three sampling events (MW10-1 to MW10-3), the community was diverse, but relatively stable in structure at the genus level from one sampling event to the next; Geobacter was the most abundant genus, comprising ~ 20–40% of total reads. Rhodoferax were consistently ~ 10% of total reads. At MW10-4, the microbial community composition changed more substantially: Geobacter remained the top genus (~35% of total reads), but the iron-reducing genus Albidiferax increased to over 21% of total reads, and Rhodoferax decreased while Polaromonas increased. By MW10-5, marked changes were evident, potentially resulting from fluctuating subsurface conditions: anaerobic Geobacter decreased from over 30 to ~ 3% of total reads, while aerobic and facultative microorganisms (Pseudomonas, Hydrogenophaga, Dechloromonas, and Polaromonas) were detected in a substantial proportion. Finally, by the last sampling event (MW10-6), Geobacter rebounded from MW10-5, Rhodoferax was the most abundant genus, and facultative anaerobic sulfur oxidizers (Sulfuritalea and Sulfuricurvum) were detected.

Fig. 10.8
6 vertically stacked bars. Each stack represents the genus of the different bacteria in bars that are labeled M W 10-1, M W 10-2, M W 10-3, M W 10-4, M W 10-5, and M W 10-6.

Stacked bar chart of the topmost genera identified in monitoring well 10 (MW10) samples over time (from the hierarchical cluster dendrogram)

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In conclusion, DNA sequencing revealed that microbial communities in the impacted areas were markedly different than background communities. Moreover, the community composition at the impacted wells changed over time, likely as a consequence of the fluctuations in subsurface conditions that were observed. Geobacter spp. were typically detected at the highest relative abundances in monitoring wells within the dissolved plume. Although at least one species of Geobacter is capable of anaerobic BTEX biodegradation, most cannot; therefore, Geobacter presence even in high relative proportions does not indicate the potential for BTEX biodegradation. However, supplementing the amplicon sequencing data with qPCR data, which indicated a 4–5 OoM increase in the concentration of genes involved in anaerobic biodegradation of BTEX (BSS and ABC genes) in impacted wells compared to background wells, provided greater clarity to the occurrence of anaerobic BTEX biodegradation across the plume. Lastly, decreasing concentrations of BTEX and qPCR and amplicon sequencing data provided additional evidence that biodegradation was a mechanism of attenuation at the site and supported ongoing implementation of MNA.

10.5 Cost Considerations in MBT Selection

Wilson et al. (Wilson et al. 2004) obtained information on remediation costs for petroleum-impacted sites from the Clu-In Database (http://cluin.org/), maintained by the U.S. EPA, and used it to identify average and median remediation cost per site. The mean (median) costs (in USD) for these cleanups, adjusted for cumulative inflation annually from 2004 to 2021, was $580,516 ($286,717) for all the combined 112 sites, $352,784 ($261,000) for the service station sites, $1,488,557 ($348,000) for the public drinking water sites, and $2,765,150 ($791,700) for the industrial sites. The average cost for application of MBTs at a PHC-contaminated site is roughly $10,000 per event for stable isotope probing and qPCR arrays on 5 monitoring locations.

10.6 Summary

MBTs provide additional lines of evidence during site characterization, remedy selection, performance monitoring, and site closure. Although each MBT provides valuable information, MBTs should be selected based on specific questions as outlined in Fig. 10.1 that need to be developed depending on site-specific needs and conditions and then addressed. Additionally, MBTs should be analyzed in conjunction with other traditional site data, such as hydrogeologic, contaminant, and geochemical data, to increase certainty associated with biogeochemical processes governing contaminant attenuation.

10.7 Future Directions

The information gained from MBTs is increasingly being used by practitioners around the world (Taggart and Clark 2021). However, the link between the abundance of microorganisms with genetic potential to degrade compounds and their rates of degradation is an important frontier of research. Pushing forward to refine rates of degradation, catalyzed by knowledge exchanged between disciplines (e.g., molecular biologists and geologists), will make MBT data of higher value in optimizing corrective action plans.

Additionally, metabolomics is a new tool for the environmental restoration industry that may become an integral part of site screening and design. In environmental restoration, metabolomics measures small (molecular weight < 1000) water-soluble compounds that are microbial metabolic products, such as corrinoids, electron-shuttling compounds, signaling compounds for organismal communication, and anabolic and catabolic pathway intermediates—providing insights into microbial activity and function that complement nucleic acid-targeted qPCR data. Metabolomics can target the quantification of specific indicator molecules or can identify patterns in complex metabolome datasets that correlate with specific microbial processes (e.g., sulfate reduction) or overall activity of the microbiome. A cost-effective and user-friendly MBT with these capabilities may further reduce site assessment and remediation costs and be an asset to the industry.