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Mechanisms and Monitoring of Oil Reservoir Souring Control by Nitrate or Perchlorate Injection

  • Hans K. Carlson
  • Casey R. J. HubertEmail author
Living reference work entry
Part of the Handbook of Hydrocarbon and Lipid Microbiology book series (HHLM)

Abstract

Oil reservoir souring is the production of hydrogen sulfide by sulfate-reducing microorganisms (SRM) in oil fields. Anaerobic respiration of sulfate is supported by various electron donors in petroleum reservoir ecosystems. Nitrate addition results in souring control by stimulating dissimilatory nitrate-reducing microorganisms (NRM) that directly or indirectly utilize petroleum-derived SRM electron donors. The oxidative capacity of nitrate for this process depends on NRM physiology and whether nitrate is metabolized to fully reduced end products or is partially reduced to nitrite. Production of nitrite is beneficial because it inhibits SRM. In laboratory tests, similar to nitrate, perchlorate also results in inhibition of microbial sulfate reduction by stimulating dissimilatory perchlorate-reducing microorganisms (PRM). The intermediates of perchlorate respiration include the potent oxidants, chlorate, chlorite, and dioxygen, which, like nitrite, are also highly inhibitory of SRM. The two approaches to souring control have interesting similarities and differences with respect to mode of action, and we discuss ways in which they could have beneficial synergistic interactions in a co-treatment approach to souring control. Other oxyanion inhibitors of souring are an interesting area of future research, and we summarize data on their modes of action and impact on different microbial subpopulations. Oil companies use various microbiological surveillance tools to monitor the success of nitrate injection or other souring control strategies. SRM surveillance traditionally relies on cultivation-based testing but in recent years has expanded to include cultivation-independent molecular and isotopic methods for detection and quantification of both harmful and beneficial oil reservoir microbes.

1 Introduction

The petroleum industry’s growing awareness of microbes and microbiology is due in part to the detrimental effects caused by anaerobic sulfate-reducing microorganisms (SRM). Reservoir souring is caused by microbial reduction of sulfate to sulfide by sulfate-reducing bacteria or archaea in the presence of appropriate nutrients, substrates, or conditions that get introduced during oil recovery operations. For example, seawater injection for production pressure maintenance both introduces sulfate and alters the formation temperature near the injection well, creating conditions permissive for SRM. Negative consequences of souring are many and include health and safety concerns (H2S is a deadly gas), increased sulfur content in produced oil and gas, and SRM-influenced corrosion. Different souring control strategies exist. Sulfate removal from injection water by nanomembrane filtration has been demonstrated; however deployment is costly, technically challenging, and hence not widespread (Alkindi et al. 2013). More common are physical or chemical removal of H2S post production (Jensen and Webb 1995) and the application of biocides to kill or inhibit reservoir SRM (Telang et al. 1998; Greene et al. 2006). Oil companies have widely used nitrate injection technology for souring control (Torsvik and Sunde 2005), and perchlorate treatment is an alternative approach that is gaining recognition and is likely to be tested in the field soon (Coates 2014; Carlson et al. 2014). Adding nitrate or perchlorate stimulates dissimilatory nitrate-reducing microorganisms (NRM) or dissimilatory perchlorate-reducing microorganisms (PRM), respectively, which can prevent or reverse the souring reactions catalyzed by SRM (Fig. 1). The two approaches share some similarities, but there are also important differences as the physiology and ecology of the respiratory processes are distinct. Managing reservoir microbial communities in this way is the focus of the present chapter.
Fig. 1

(a) Souring control following nitrate injection can be achieved via biocompetitive exclusion of SRM electron donors by chemoorganotrophic NRM, or via direct oxidation of sulfide by chemolithotrophic sulfide-oxidizing NRM, as described in the text. Nitrite production by NRM can also inhibit SRM. At sufficiently high concentrations, nitrate can competitively inhibit sulfate reduction by SRM. (b) Souring control following perchlorate injection can be achieved via biocompetitive exclusion of SRM by chemoorganotrophic PRM. Sulfide is oxidized largely to elemental sulfur by PRM. Reactive chlorine and oxygen species produced by PRM are potent inhibitors of SRM. At sufficiently high concentrations, perchlorate can competitively inhibit sulfate reduction by SRM

Oil reservoirs represent complex microbial ecosystems featuring various interactions between different groups of anaerobes. These reduced environments are rich in electron donors but contain relatively few terminal electron acceptors. In this context, methanogenic degradation of petroleum hydrocarbons over long timescales is catalyzed in situ by consortia of reservoir microbes (Head et al. 2003). Secondary oil production (i.e., water injection to maintain in situ reservoir pressure and provide a water sweep of oil through the reservoir) can alter the microbial ecosystem dramatically by introducing oxidants – particularly sulfate when seawater is injected at offshore operations. Subsequent nitrate or perchlorate injection for souring control can affect the microbial ecology even further, resulting in interconnected anaerobic carbon, sulfur, nitrogen, and/or chlorine cycling. Understanding these cycles and the interactions between SRM and NRM/PRM is of critical importance for smart management of reservoir souring problems.

The importance of reservoir souring is reflected by an increasing body of primary scientific literature, much of which is cited in several good reviews of souring and souring control (Eckford and Fedorak 2004; Birkeland 2005; Thrasher and Vance 2005; Torsvik and Sunde 2005; Grigoryan and Voordouw 2008; Ollivier et al. 2009; Gieg et al. 2011). The current chapter will focus specifically on aspects of SRM, NRM, and PRM physiology that are relevant to reservoir souring and souring control (Sects. 2 and 3, respectively). Different strategies oil companies use for monitoring microorganisms in oil-field settings will also be discussed (Sect. 5).

2 Sulfate Reduction in Oil Reservoirs

Souring is a likely outcome following seawater injection into oil reservoirs, which brings the terminal electron acceptor sulfate into contact with various electron donors in the organic-rich petroleum hydrocarbon environment. Essential nutrients (N, P, etc.) may be present both in injected water and in the reservoir. Microorganisms are widely believed to be indigenous to oil reservoirs, but they may also be introduced with the injected water. Oil-field SRM detected and characterized to date are physiologically and phylogenetically diverse, ranging from mesophilic Deltaproteobacteria to hyperthermophilic archaea to spore-forming mesophilic, thermophilic, and halophilic Firmicutes (Ollivier et al. 2009; Gittel et al. 2009; Aüllo et al. 2013; Vigneron et al. 2017). The physiology of oil-field SRM (e.g.,temperature and substrate range) can provide clues as to whether they are indigenous to a given reservoir habitat or introduced (Magot 2005). The chief concern here however is the production of sulfide, which is problematic for the oil industry regardless of the provenance of the culprit SRM.

2.1 Electron Donors in Oil Reservoir Ecosystems

Electron donors for sulfate-reducing microorganisms in anoxic environments are often organic acids, alcohols, and hydrogen that may be by-products of fermentative degradation of complex organic compounds. Organic acids, alcohols, and hydrogen are utilized by several characterized SRM from oil-field environments (Birkeland 2005; Grigoryan and Voordouw 2008), and organic acid anions are detectable in oil reservoir fluids (e.g., Barth 1991). Other potential electron donors in oil reservoirs are obviously petroleum hydrocarbons. SRM that oxidize alkanes, cycloalkanes, and aromatic compounds anaerobically have been isolated from various environments (Widdel et al. 2009); however few of the SRM detected in or isolated from oil fields described so far share this phenotype (Harms et al. 1999; Magot 2005). Although future efforts may uncover more oil-field isolates that couple hydrocarbon oxidation to sulfate reduction, the paucity of examples to date questions whether in situ reservoir souring is driven directly by hydrocarbons or rather by other electron donors.

Alternatively, SRM could be indigenous reservoir inhabitants that have a different lifestyle prior to industrial oil recovery activities. Anaerobic biodegradation of oil in situ involves microbial consortia that degrade hydrocarbons into acetate and hydrogen that are consumed by methanogens (Zengler et al. 1999; Head et al. 2003; Jones et al. 2008). When sulfate is scarce or absent, some SRM carry out fermentative metabolism and can serve as syntrophic partners for methanogens (Bryant et al. 1977; Muyzer and Stams 2008). Such organisms may switch from fermentation to sulfate reduction following injection of sulfate-rich seawater into an oil reservoir. A related possibility is that introduction of sulfate to a previously methanogenic system results in the competitive exclusion of methanogens by acetate- or hydrogen-oxidizing SRM. In this scenario reservoir souring would be driven directly by small organic acids and hydrogen produced by ongoing biodegradation of petroleum hydrocarbons; i.e., the early steps in oil degradation pathways would not change, but these processes are enabled by end members consuming acetate and hydrogen via sulfate reduction rather than methanogenesis.

2.2 Limiting Factors that Inform Souring Control Strategies

The extent of reservoir souring in the presence of abundant sulfate depends on the amount of electron donors and trace nutrients present to support the growth of SRM. Souring may also be limited by the presence of toxic or inhibitory compounds in petroleum that interfere with SRM metabolism (Torsvik and Sunde 2005), and temperature, salinity, pH, and mineral scavenging must also be considered (Johnson et al. 2017; Pannekens et al. 2019). These limiting factors form the basis for industrial strategies to combat SRM activity. Traditionally the introduction of toxic biocides has been used to curb microbial growth, inhibiting SRM in particular. Biocides are also toxic for humans and marine life (Greene et al. 2006). Biocide effectiveness is dependent on proper dosing regimens and the degree to which target microbes develop biocide resistance (Sanders and Sturman 2005). Other oxyanion treatments, such as molybdate, have also been long considered as selective inhibitors of sulfate reduction (Postgate 1952), although their use has largely been limited to ecological studies (Oremland and Capone 1988). Nitrate injection technology is currently the most widely used approach in the oil industry to control souring and is primarily based on a strategy to deplete SRM electron donors via nitrate reduction instead of sulfate reduction. Perchlorate injection is a newer approach to souring control that is based on similar mechanisms. Both nitrate and perchlorate represent alternative, more energetically favorable electron acceptors and can outcompete SRM for electron donors and thus limit SRM growth through this biocompetitive exclusion. Nitrate reduction can additionally result in the accumulation of nitrite, and perchlorate reduction can result in the accumulation of chlorite, both of which are potent SRM inhibitors (Carlson et al. 2014) and are therefore similar to a biocide. Effects of nitrate and perchlorate addition on the microbial ecology of sour reservoirs are elaborated upon below.

3 Nitrate Reduction and Perchlorate Reduction for the Control of Reservoir Souring

Nitrate is incorporated into waterflood regimes for many sour oil reservoirs to combat the activity of SRM. Like SRM, NRM can utilize various oil-derived electron donors, coupling their oxidation to the reduction of nitrate instead of sulfate. Hydrocarbons, organic acids, alcohols, and hydrogen can all be metabolized by different NRM. Furthermore, sulfide and other reduced sulfur compounds potentially present in the reservoir environment can also be coupled to the reduction of nitrate by chemolithotrophic NRM (e.g., nitrate-reducing sulfide-oxidizing microorganisms, NR-SOM) (Lahme et al. 2019). Hence nitrate reduction has the potential to prevent reservoir souring by competitive depletion of SRM substrates or by the direct oxidation of the harmful hydrogen sulfide (Fig. 1a). Thermodynamic modeling predicts that chemoorganotrophic NRM are favored over chemolithotrophic NR-SOM under reservoir conditions (Dolfing and Hubert 2017). Informed management of the sulfur cycle in nitrate-treated oil reservoirs depends on understanding and distinguishing between nitrate reduction pathways (Hubert et al. 2009). SRM activity can also be adversely affected by increased environmental redox potential due to the production of nitrate reduction intermediates (Nemati et al. 2001a). Nitrite is a main intermediate and has the added beneficial properties of inhibiting sulfate reduction directly as an alternative substrate of the dissimilatory sulfite reductase (Dsr) (Greene et al. 2003). Nitrate can also chemically scavenge sulfide that may be present (Sanders and Sturman 2005).

Perchlorate injection is an emerging approach to souring control that has many similarities with nitrate treatment. Perchlorate is utilized by perchlorate-reducing microorganisms (PRM) that can outcompete SRM for consumption of oil-derived electron donors (Coates et al. 1999; Carlström et al. 2013; Engelbrektson et al. 2018a, b). PRM can also oxidize sulfide, but primarily to elemental sulfur rather than to sulfur oxyanions (Gregoire et al. 2014; Mehta-Kolte et al. 2017). Elemental sulfur accumulation is a relevant consideration, given that it may be subsequently oxidized or reduced (Telang et al. 1999), and if it comes into contact with production facilities, it can exacerbate corrosion problems that are known to be associated with reservoir souring (Lahme and Hubert 2017; Lahme et al. 2019). While both nitrate and perchlorate can function as competitive inhibitors of sulfate reduction, perchlorate is a slightly more potent direct inhibitor of SRM (Carlson et al. 2014). Finally, reactive chlorine and oxygen species, like nitrite, are potent inhibitors of sulfate reduction (Carlson et al. 2014).

3.1 Chemoorganotrophic NRM, PRM, and Biocompetitive Exclusion

Depletion of SRM substrates by NRM as a souring control strategy is sometimes referred to as biocompetitive exclusion (Fig. 1a). This is based on nitrate reduction being more thermodynamically favorable than sulfate reduction when coupled to the oxidation of a given substrate. Oil-field NRM stimulated by nitrate injection may, like SRM, be indigenous to the reservoir or introduced during water injection. Nitrate injection technology has gained broad attention from the petroleum industry only recently, and fewer oil-field NRM have been isolated and characterized, compared to SRM. Unlike oil-field SRM described so far, many characterized chemoorganotrophic NRM from oil fields can oxidize hydrocarbon electron donors (Ollivier and Cayol 2005). In order for biocompetitive exclusion to be successful, the NRM must oxidize the same substrates that the SRM would otherwise couple to the reduction of sulfate. Petroleum reservoirs represent complex microbial ecosystems and substrate utilization patterns for anaerobic respiration by oil-field SRM, and NRM will not necessarily be identical (Grigoryan and Voordouw 2008). For example, in one low-temperature oil field in western Canada, it has been observed that NRM oxidize aromatic hydrocarbons, whereas SRM predominantly use organic acids (Agrawal et al. 2012).

Similar to NRM, PRM outcompete SRM for electron donors due to the favorable thermodynamics of perchlorate reduction over sulfate reduction. Perchlorate is widespread in the environment and is present both as a contaminant and as a natural product owing to photooxidative processes in the upper atmosphere. PRM are therefore ubiquitous in the environment and present in both marine and freshwater systems (Coates et al. 1999; Carlström et al. 2013). In general, PRM are less abundant than NRM most likely due to the fact that nitrate is usually present at several orders of magnitude higher concentrations. However, while denitrification (nitrate reduction to N2) provides five electrons per mole, perchlorate provides eight electrons per mole. Thus, from the standpoint of biocompetitive exclusion, fewer moles of perchlorate versus nitrate are required to consume the same amount of labile carbon sources and outcompete SRM if the nitrate reduction proceeds via denitrification. These points are well illustrated in flow-through column studies to assess the capacity of perchlorate and nitrate to inhibit sulfate reduction. While it takes longer for perchlorate to show an impact on sulfate reduction compared to nitrate, at equimolar concentrations, perchlorate is more effective than nitrate and inhibiting sulfate reduction (Coates 2014). Some oil-field NRM catalyze dissimilatory nitrate reduction to ammonia (DNRA) (Fig. 2a) (Hubert and Voordouw 2007), which also provides eight electrons per mole of nitrate. Further work is needed to address whether nitrate injection promotes DNRA or denitrification by NRM in different reservoir contexts.
Fig. 2

Nitrite production as a function of nitrate concentration in pure culture tests using nitrate-reducing Sulfurospirillum sp. strain KW (a) and Sulfurimonas sp. strain CVO (b), both isolated from the Coleville oil field in western Canada. Chemoorganotrophic DNRA by Sulfurospirillum was governed by initial concentrations of nitrate relative to lactate (a). Chemolithotrophic denitrification by Sulfurimonas was governed by initial concentrations of nitrate relative to sulfide. Initial conditions in culture media (the relative nitrate concentration) are expressed as the ratio of nitrate to either lactate (a) or sulfide (b) on the x axes. High initial nitrate doses always corresponded to a greater proportion of the nitrate ending up as nitrite in final products as indicated by regression lines. Results in (a) and (b) are adapted from Hubert and Voordouw (2007) and Greene et al. (2003), respectively, which describe the individual pure culture experiments in more detail

PRM are also capable of using a variety of organic acids as well as crude oil hydrocarbons as electron donors and carbon sources to support growth. Of note, because PRM produce oxygen as an obligate intermediate of their anaerobic metabolism, PRM are able to activate hydrocarbons through aerobic pathways in anoxic environments (Coates et al. 1998; Carlström et al. 2013). This capacity for oxygenic hydrocarbon degradation may give PRM an additional advantage over SRM in oil reservoir environments.

If SRM causing reservoir souring can switch their metabolism to reduce the injected nitrate instead of sulfate (Seitz and Cypionka 1986; Dalsgaard and Bak 1994; Plugge et al. 2002), then sulfide production will stop, and electron donor depletion is not necessary. However, not all oil-field SRM can reduce nitrate (Greene et al. 2003). Many SRM also have mechanisms for detoxifying reactive nitrogen species (e.g., nitrite, nitric oxide). Similarly, some thermophilic SRM have been shown to reduce perchlorate (Liebensteiner et al. 2013, 2014), although the exact mechanisms for this remain obscure.

3.2 Sulfide Oxidation by Chemolithotrophic NRM and PRM

Several NRM isolated from oil-field environments couple nitrate reduction to the oxidation of sulfide and other reduced sulfur compounds (Fig. 1b) making them potentially beneficial souring-control agents. The product of sulfide oxidation may be sulfur compounds of an intermediate oxidation state (e.g., elemental sulfur) or sulfate. Intermediate sulfur compounds are corrosive (Nemati et al. 2001b; Hubert et al. 2005; Lahme and Hubert 2017; Lahme et al. 2019), and their accumulation may be prevented if microbes that reduce or oxidize elemental sulfur are present (Telang et al. 1999; Gevertz et al. 2000). Complete conversion of sulfide back to sulfate allows further sulfate reduction to occur if SRM electron donors remain available. In principle nitrate can deplete these electron donors via cycling of reduced and oxidized sulfur compounds between chemolithotrophic NRM and sulfate or sulfur reducers (Fig. 1b). Hence, sulfide-oxidizing NRM can achieve the overall effect of biocompetitive exclusion in an indirect way that does not depend on oxidation of the exact SRM substrates that donate electrons to the souring reaction (Hubert et al. 2003). The ability of sulfide-oxidizing NRM to compete with chemoorganotrophic NRM for nitrate may determine the effectiveness of nitrate injection technology in instances where direct biocompetitive exclusion is precluded by resident SRM and NRM that oxidize different oil-derived substrates. Thermodynamic calculations suggest that chemoorganotrophs will outcompete chemolithotrophic NRM in souring control scenarios (Dolfing and Hubert 2017).

PRM are also innately capable of sulfide oxidation, but the products of the reaction are shifted toward elemental sulfur rather than sulfur oxyanions (Fig. 1) (Gregoire et al. 2014; Mehta-Kolte et al. 2017). This proceeds differently than sulfide oxidation by chemolithotrophic NRM in that PRM do not grow by sulfide oxidation; rather the intermediates and enzymes involved in perchlorate respiration are very reactive with sulfide (Mehta-Kolte et al. 2017). Organisms involved in the cycling of intermediate sulfur species are often observed co-enriched alongside PRM in marine sulfidogenic systems that have received perchlorate treatment to control souring (Coates 2014).

3.3 Nitrate Reduction Pathways and Production of Nitrite by Oil-Field NRM

The ability of NRM to control reservoir souring via depletion of SRM electron donors according to the scheme in Fig. 1a depends on the oxidative capacity of nitrate, which in turn depends on the NRM physiology and whether nitrate is completely or partially reduced. Nitrate reduction can proceed according to two reaction pathways: DNRA (NO3 → NO2 → NH4+), which transfers eight electrons, or denitrification (NO3 → NO2 → NO → N2O → N2), which transfers five electrons. Hence, oxidation (depletion) of electron donors would require less nitrate if full DNRA rather than full denitrification were stimulated. NRM capable of both processes have been isolated from the same oil field (Gevertz et al. 2000; Hubert and Voordouw 2007), and the factors governing which group may be stimulated during nitrate injection to reservoirs remain unclear. An experimental comparison using non-oil-field strains from a culture collection showed DNRA was more energetically favorable than denitrification (Strohm et al. 2007), whereas thermodynamic modeling predicts denitrification is more energetically favorable (Dolfing and Hubert 2017). It has been suggested that DNRA may be the dominant pathway in environments where nitrate concentrations are low (Burgin and Hamilton 2007).

However, nitrate reduction by oil-field NRM does not necessarily always proceed fully to the end products N2 or NH4+. When nitrate is present in excess relative to NRM electron donors, nitrite may be the end product of nitrate reduction (Greene et al. 2003; Hubert and Voordouw 2007; Grigoryan et al. 2008). This is illustrated in NRM end-product plots for organic acid (lactate) oxidation by the DNRA-catalyzing Sulfurospirillum sp. strain KW and sulfide oxidation by the denitrifying Sulfurimonas sp. strain CVO (Fig. 2). The results show that lower nitrate doses may be more likely to be converted to fully reduced end products, whereas higher doses promote nitrite accumulation. Instances could exist where adding less nitrate transfers more electrons (oxidizes more substrate) than higher nitrate doses that would be converted mainly to nitrite. This suggests that depletion of SRM electron donors could be more efficient using a relatively low dose of nitrate in some cases. More souring control with less nitrate seems counterintuitive, and strategies based on the trends shown in Fig. 2 require a thorough understanding of the chemistry and microbiology in a particular setting.

Nitrite production can be advantageous in oil-field settings since nitrite strongly inhibits SRM (Fig. 1). An important benefit of partial nitrate reduction scenarios (e.g., higher nitrate doses; Fig. 2) could be the production of significant amounts of nitrite, which appears to be a common outcome of nitrate application at high temperature (Fida et al. 2016). Some oil-field NRM produce only nitrite as an end product (e.g., sulfide-oxidizing Arcobacter sp. strain FWKOB (Gevertz et al. 2000)). Nitrite specifically blocks the dissimilatory sulfite reductase (Dsr) that catalyzes the conversion of sulfite to sulfide in all SRM (Greene et al. 2003) and is a moderately selective inhibitor of SRM (Carlson et al. 2015). As a metabolic inhibitor, nitrite is similar to a biocide and is more effective against SRM at higher concentrations. Nitrite inhibition of Dsr depends on SRM cell density; larger SRM populations require correspondingly higher nitrite doses to prevent growth and sulfide production (Haveman et al. 2004). Another important factor is whether or not the SRM being targeted encode and express a periplasmic nitrite reductase (Nrf). This feature, possessed by some but not all SRM, is effectively a detoxification strategy to alleviate nitrite inhibition of normal Dsr action (Greene et al. 2003); Nrf does not allow SRM growth via dissimilatory nitrite reduction (Pereira et al. 2000).

Introducing high doses of nitrate to sour reservoirs may thus achieve multiple souring control effects. Reduction of nitrate to nitrite transfers two electrons, which would achieve oxidation and depletion of SRM substrates in proportion to the amount of added nitrate. This outcome would be complemented by a corresponding level of inhibitory nitrite (Fig. 2). For oil fields where souring control depends mainly on inhibition of SRM by nitrite, it may be less crucial to understand the nature and extent of SRM electron donors in situ. However, recent work suggests that nitrite production in many oil systems may be primarily controlled by the availability of labile monoaromatic hydrocarbons such as toluene (Suri et al. 2017) that can be oxidized by betaproteobacterial Azoarcus and Thauera spp. detected in different oil fields (Hubert and Voordouw 2007; Li et al. 2014; Suri et al. 2017). Nitrite inhibition would also be effective in situations where culprit SRM are known to have a broad substrate range (perhaps including oil hydrocarbons) and/or in reservoirs with many degradable electron donors (making them harder to exhaust via nitrate-reducing biocompetitive exclusion). Torsvik and Sunde (2005) have suggested that oil has limitless electron donors (for SRM and NRM) and that souring control mechanisms must therefore be based on SRM inhibition. As such, information on resident microbial communities will be important for developing nitrite inhibition strategies that depend on the amount of SRM biomass present, which can be estimated using quantitative assays (see Sect. 5). It may also be important to determine whether the SRM harbor nitrite reductase. Such information could be determined by pre-screening oil-field samples using molecular surveillance techniques prior to nitrate injection. If souring is caused by nitrite-resistant SRM, nitrite accumulation may be less successful, and a biocompetitive exclusion-based nitrate injection strategy for depleting bioavailable SRM electron donors should be considered. Recent work suggests that the extent of nitrite accumulation by NRM increases at high temperature (An et al. 2017) and salinity (Okpala et al. 2017). This could be due to inhibition of nitrite reductase enzymes at temperature and salinity extremes. The temperature sensitivity suggests that reinjection of hot production water could be used as a means of enhancing the efficacy of nitrate injection for souring control (An et al. 2017).

3.4 Perchlorate Reduction Pathways and Production of Oxygen and Reactive Chlorine Species by Perchlorate-Reducing Microorganisms

Perchlorate-reducing microorganisms are unique among respiratory anaerobes in that they can produce dioxygen under anaerobic conditions as an obligate intermediate in perchlorate reduction. All respiratory perchlorate-reducing microorganisms reduce perchlorate sequentially through the intermediates ClO4 → ClO3 → ClO2 → O2 → H2O (Youngblut et al. 2016b). Perchlorate (ClO4) is first reduced through two sequential two-electron reductions to chlorite (ClO2) by a perchlorate reductase (PcrA) protein (Youngblut et al. 2016a, b). In canonical PRM, perchlorate reductases form a monophyletic clade (Melnyk and Coates 2015), and biochemical studies suggest that although NarG nitrate reductases are capable of reducing perchlorate, the Km for the specialized perchlorate reductase enzyme is several orders of magnitude lower (Youngblut et al. 2016a). Thus, PRM are capable of accessing much lower concentrations of perchlorate compared with nitrate-reducing microorganisms. The chlorite produced by PcrA is an exceptionally reactive and toxic intermediate and is rapidly dismutated to dioxygen and chloride ion by chlorite dismutase (Cld). Chlorite dismutation does not yield energy but produces dioxygen, a very thermodynamically favorable electron acceptor and oxidant. There are also a number of other specialized mechanisms, whereby perchlorate-reducing microorganisms detoxify reactive chlorine species such as hypochlorite (HOCl) that are formed through side reactions as minor products of perchlorate reduction. The presence of an active methionine sulfoxide reductase system in conjunction with a highly expressed methionine-rich peptide is essential to cope with these species in model PRM (Melnyk et al. 2015).

The dioxygen produced through perchlorate reduction is utilized by PRM using the same cytochrome oxidase enzymes that are utilized under aerobic conditions (Melnyk et al. 2013). This oxygen is also available to the enzymes involved in aerobic hydrocarbon degradation (Carlström et al. 2015) and can potentially even be available to other organisms carrying out other aerobic metabolisms (Carlström et al. 2015; Clark et al. 2016) (Youngblut et al. 2016a; Barnum et al. 2018). The possibility of syntrophic perchlorate reduction has recently been demonstrated in pure culture (Clark et al. 2016), which suggests that PRM subpopulations could share the intermediates of perchlorate reduction. This could occur by exchange of either chlorite or dioxygen (Youngblut et al. 2016a). While this likely occurs at very low concentrations (low micromolar to nanomolar), both of these compounds are extremely potent inhibitors of SRM with IC50 values in that range (Carlson et al. 2015). Thus, as with NRM producing nitrite, PRM populations may exist that produce varying levels of chlorite and oxygen and thereby impact SRM to varying extents.

4 Alternative Oxyanion Treatment Strategies

Other oxyanion treatments for controlling reservoir souring have also been evaluated. While less is known about their application logistics and impact on complex microbial communities, considering the properties and impact of these other oxyanions on oil reservoir communities provides important points of comparison with nitrate and perchlorate and identifies scenarios where combined treatment strategies may work.

Nitrate and perchlorate can be effective inhibitors of microbial sulfate reduction in large part because of their capacity to serve as alternative electron acceptors and because NRM and PRM produce reactive nitrogen and chlorine species that are potent inhibitors of SRM (Fig. 1). However, both of these monovalent oxyanions can also function as competitive inhibitors of the ATP sulfurylase/sulfate adenylyltransferase (ATPS/Sat), and at sufficiently high concentrations, both compounds can function as direct, selective inhibitors of respiratory sulfate-reducing microorganisms (Carlson et al. 2014) (Fig. 3). Other oxyanions function as alternative substrates of the ATP sulfurylase and are activated to generate unstable adenosine 5′-phosphooxyanions with varying stabilities relative to adenosine 5′-phosphosulfate (APS) (Fig. 3).
Fig. 3

Mechanisms of inhibition of sulfate adenylyltransferase/ATP sulfurylase (Sat) by inorganic oxyanions. (a) The monovalent oxyanions perchlorate, chlorate, and nitrate are competitive inhibitors of Sat, competing with sulfate for binding to the active site. (b) The divalent oxyanions molybdate, tungstate, selenate, tellurate, arsenate, and chromate are all alternative substrates of the Sat and are converted into unstable adenosine-5’-phosphosulfate analogs that rapidly decompose to release free oxyanion again. This drives a futile cycle with the net result of depleting cytoplasmic ATP in SRM. (c) Monofluorophosphate forms a uniquely stable adenosine-5’-phosphosulfate analog that may also function as a competitive inhibitor of the APS reductase. Cytoplasmic fluoride release in SRM also contributes to the mechanism of inhibition

Molybdate and tungstate, the group IV oxyanions, are particularly potent inhibitors of SRM because they form very unstable APS analogs (Peck 1959; Renosto et al. 1993; Hanna et al. 2004; Carlson et al. 2015). This is similarly true for selenate and presumably also true for tellurate (Renosto et al. 1993; Hanna et al. 2004; Carlson et al. 2015) (Peck 1959). Chromate and arsenate are also futile substrates of the sulfate adenylyltransferase, but this can be counteracted by enzymatic mechanisms for their detoxification in many SRM (Lovley and Phillips 1994; Michel et al. 2001; Li and Krumholz 2007). The net impact of these futile substrates is rapid depletion of cytoplasmic ATP and regeneration of the inhibitory oxyanion.

In contrast to the futile substrates, chromate and arsenate, monofluorophosphate forms a very stable APS analog (Hanna et al. 2004) that may also function as a competitive inhibitor of the APS reductase. Monofluorophosphate is also a selective inhibitor of SRM and functions in part by releasing toxic fluoride ion in the cytoplasm of SRM that are unable to distinguish between sulfate and monofluorophosphate (Carlson et al. 2015). The relatively low toxicity of monofluorophosphate to other organisms compared to the other inorganic oxyanions makes it an attractive option.

One consideration for the use of many of the divalent inorganic oxyanions is the potential for the formation of insoluble complexes with alkali earth metals such as Ca2+ and Mg2+ (Rowley and Stuckey 1956; Lide 2007). This could impact the ability of these inhibitors to move through reservoirs to reach target SRM populations but could also have the added effect of sequestering these inorganic oxyanions in mineral matrices that could then function to slowly release the inhibitor farther into the reservoirs. More research into the potential of other oxyanions for achieving souring control will shed light on these possibilities.

5 Monitoring SRM and NRM in Oil-Field Environments

The importance of SRM has led the petroleum industry to adopt different strategies for monitoring their occurrence in oil reservoirs and oil production facilities. Quantitative detection tools can provide useful information about SRM, e.g., before and after seawater injection and breakthrough which may allow SRM proliferation, or before and after biocide or nitrate treatments intended to curb SRM activity. Many souring control strategies depend on the inhibition and/or eradication of SRM; hence sensitive detection methods are useful for surveillance. Important considerations are the logistics of sample processing and the length of time until results are obtained and interpreted. Particular features relating to the microbial ecology of souring and nitrate addition, discussed above, may be important for correctly interpreting results when sulfide elimination is the objective. Advantages and disadvantages of different quantitative approaches are discussed below.

5.1 Cultivation-Based Monitoring

Traditionally the oil industry has employed most probable number (MPN) analyses, sometimes referred to as “bug bottles,” for quantification of various microbial groups. Oil-field samples (e.g., produced waters, metal coupons from injection or production facilities, etc.) are inoculated into a medium containing sulfate and appropriate electron donors as dilution series and, following an incubation period, are scored based on set criteria (e.g., blackening caused by reaction of produced sulfide in iron-containing growth media). Detection of growth can require up to 4 weeks for highest positive dilutions, which in principle were inoculated with one to nine individual target cells (assuming tenfold dilution series and proportional biomass distribution during transfers, i.e., no clumping of cells). Increased sensitivity may be achieved by incubating with radioactive 35S-labeled sulfate (Vester and Ingvorsen 1998). Similar methods, with appropriately selective growth media, can be employed for enumerating NRM, PRM, and other groups of oil-field microorganisms.

Detection of oil-field SRM based on the production of sulfide makes sense, since sulfide production is usually the problem in the first place. MPN testing generally does not return false-positive results; using appropriate SRM media, MPNs should reliably determine the minimum number of microbes capable of sulfate reduction that are present in a sample. A caveat to this would be samples with high concentrations of sulfide but low concentrations of SRM, underscoring the importance of incubating proper controls in parallel to SRM growth tubes. However, misinterpretation of positive results could occur, e.g., if SRM switch from fermentative metabolism to sulfate reduction, although they are not carrying out sulfate reduction in the reservoir, they may give a misleading result in the bug bottle tests. The necessary foreknowledge of media and incubation conditions that will successfully enrich reservoir microbes is a key drawback to MPN testing, given that most environmental microorganisms have not been successfully cultivated so far (Stewart 2012). The so-called unculturable fraction is often suggested to be 90 to 99% of the microbial diversity in a given environment. This ratio presumably holds true for SRM in oil-field environments; hence there is real potential for false negatives using this approach. Typical oil-field MPN counts are 104 to 105 SRM ml−1 produced water (Birkeland 2005).

Dilution to extinction, inherent to the MPN approach, offers the opportunity to obtain pure cultures of culturable organisms associated with selected phenotypes in oil-field samples (e.g., Voordouw et al. 1991). Molecular methods cannot substitute live cultures for the experimental characterization of microbial physiology (e.g., determining the range of relevant phenotypes for a single organism). Pure cultures also allow straightforward whole-genome sequencing. Information from whole genomes offers valuable clues as to the metabolic potential of an organism, e.g., in an oil reservoir context, whether reactions, such as sulfate reduction, nitrate reduction, perchlorate reduction, corrosion-associated metabolism, or hydrocarbon biodegradation, could be catalyzed. In addition to obtaining genomes from pure cultures, community DNA sequencing of metagenomes to obtain whole genomes, or single-cell genomics following cell sorting, offers other ways to access this information from environmental (e.g., oil field) samples (Bowers et al. 2017) without culturing. Despite these developments in genomics, petroleum microbiology will continue to benefit from renewed cultivation efforts that employ innovative techniques and various culture media (Giovannoni and Stingl 2007; McGenity 2016). Expanding the number and diversity of cultured and well-characterized oil-field microorganisms is a good reason to maintain dilution-to-extinction (MPN) testing in the oil industry, but this requires that analyses performed by operators and service providers do not end with enumeration and continue all the way to individual strain isolation, characterization, and sequencing. Employing a wider array of selective growth media would be beneficial for this kind of initiative.

High-throughput cultivation can help petroleum microbiologists address many of the challenges related to accessing culturable diversity noted above. Coupled with high-throughput 16S rRNA gene amplicon sequencing, high-throughput MPN cultivation has been shown to be successful in this regard (Justice et al. 2017). Once microbial isolates and enrichments are obtained, high-throughput cultivation can allow researchers to rapidly identify appropriate biocide or oxyanion dosing concentrations and develop tailored souring control strategies specific to a given reservoir environment (Carlson et al. 2015, 2017). In addition, approaches for continuous cultivation, such as chemostats, are promising for obtaining stable microbial communities carrying out complex metabolisms such as sulfur and nitrogen cycling (Kraft et al. 2014).

5.2 Cultivation-Independent Monitoring

In recent years the oil industry has started incorporating molecular microbiology into its surveillance. At the same time, research labs have undertaken many molecular characterizations of oil-field production fluids, increasing our understanding of reservoir microbial communities (Pham et al. 2009; Hubert et al. 2012; Lewin et al. 2014; Hu et al. 2016; Vigneron et al. 2017; Kim et al. 2018). While arguably more technically demanding than traditional MPN assays, molecular methods can provide quantitative results within hours to days rather than weeks. Differences on this timescale for managing oil production operations may translate into significant economic gain or loss. In this context it is essential to understand the reservoir microbial ecology in question, such that well-designed assays are implemented and their results interpreted correctly.

There are two main approaches used by molecular microbial ecologists for quantifying specific microbial groups of interest. Fluorescence in situ hybridization (FISH) of oligonucleotide probes to ribosomal RNA (rRNA) in viable cells after their fixation allows direct counting of active microorganisms by epifluorescence microscopy (Amann and Fuchs 2008). This approach has taxonomic specificity based on the probe sequence, whereas more general DNA-binding dyes (e.g., DAPI or SYBR Green) coupled with microscopy can provide a non-specific general cell count (though this can also count dead cells). These general stains are typically used in tandem with FISH so that organisms of interest can be considered relative to overall population estimates. A different approach is quantitative PCR (qPCR) where the progress of a PCR is optically monitored in real time using similar DNA-binding dyes (e.g., SYBR Green) such that the exponential growth in the fluorescence signal allows the initial number of target sequences in a sample to be extrapolated (Smith and Osborne 2008; McKew and Smith 2015; Shen and Voordouw 2015). Application of either technique for quantifying SRM or other microbial targets in oil-field samples requires careful selection of the genetic sequence(s) being targeted and the specificity of the oligonucleotide probe or primers being applied.

Non-quantitative molecular approaches that have been applied to oil-field samples include PCR-based amplicon libraries. In recent years, clone libraries, i.e., cloning amplicons into plasmid vectors for sequencing (e.g., Voordouw et al. 1996; Hubert et al. 2012) and denaturing gradient gel electrophoresis analysis of amplicons (Schwermer et al. 2008), have given way to next-generation sequencing approaches using different technology platforms, with the current state of the art for most researchers being the Illumina MiSeq platform (Dong et al. 2017; Vigneron et al. 2017). Amplicon libraries indicate the presence of some organisms but do not exclude the absence of others. Relative abundances of different taxonomic groups in amplicon libraries should be interpreted cautiously, because PCR primers tend to preferentially amplify certain taxa over others.

Maintaining up-to-date knowledge for oligonucleotide probes and PCR primers is an ongoing task given the rapid and regular discovery of new microbial diversity, both in oil fields and other environments. For example, one of the earliest FISH probes used for SRM detection in microbial ecology, SRB385, was designed to target some but not all known sulfate-reducing Deltaproteobacteria (Amann et al. 1990) at a time when 16S rRNA gene sequence databases and the molecular diversity of SRM (Vigneron et al. 2018) were more limited. This probe has gained attention from the oil industry for use in SRM surveillance. However, a quick and easy analysis of SRB385 in the context of currently known 16S rRNA diversity using free online resources reveals perfect matches to thousands of known 16S rRNA sequences affiliated with non-sulfate-reducing groups, including inferred fermentative, syntrophic, and nitrate-reducing bacteria.

Probe and primer sequences, like growth media for the MPN approach, represent the selective component of molecular detection assays. Careful design and testing are crucial to proper probe and primer applications in oil-field settings. The SRB385 example illustrates the potential to overestimate SRM abundance using oligonucleotides with broader than intended specificity. On the other hand, specific probes or primer sets for SRM 16S rRNA targets may also lead to underestimates due to less than intended coverage and specificity for the target group. As noted above, SRM are phylogenetically diverse, belonging to at least five bacterial and two archaeal phyla (Stahl et al. 2009). In cases where specific SRM known to plague a particular oil field are to be monitored, a 16S rRNA gene sequence corresponding to that particular organism or clade may represent a good molecular marker for quantitative surveillance. Multiple 16S rRNA assays are required to confidently screen for all known SRM.

Alternatively, qPCR-based detection of metabolic genes of SRM such as the dissimilarity sulfite reductase (dsrAB) offers another strategy for specific detection of these organisms (Müller et al. 2015; Vigneron et al. 2018). While metabolic genes offer good targets for specific qPCR assays, FISH targeting metabolic genes has also been developed (Moraru et al. 2010; Barrero Canosa et al. 2017). Abundances of genes encoding enzymes catalyzing various steps in nitrate reduction pathways (Sect. 3.3) have also been assessed by qPCR in different environmental samples (Henry et al. 2006; Smith et al. 2007, 2017). Similarly, perchlorate reduction genes can also be detected in amplicon libraries (Bender et al. 2004) and in metagenomes (Barnum et al. 2018). Sulfide-oxidizing microorganisms that contain homologous aps and dsr genes to those in SRM and catalyze reverse reactions (Stahl et al. 2007) could potentially complicate interpretation of results from SRM metabolic gene assays from oil-field environments, especially in situations where, in response to SRM activity, nitrate injection stimulates sulfide-oxidizing NRM (Figs. 1b and 2b). Targeting dsr may hold more promise in this regard since it forms distinct clades in sulfate reducers and sulfide oxidizers (Loy et al. 2009), whereas aps from these two groups are phylogenetically interspersed (Stahl et al. 2007). Other caveats of dsr used as an oil-field marker are its occurrence among some fermentative and syntrophic Desulfotomaculum spp. that may have lost the ability to reduce sulfate (Plugge et al. 2002; Imachi et al. 2006) and the fact that some SRM are also capable of nitrate reduction (Seitz and Cypionka 1986; Dalsgaard and Bak 1994; Plugge et al. 2002). These organisms, if present, would still respond to dsr-based detection assays (or MPN assays using SRM growth medium) even when displaying these non-sulfate-reducing phenotypes in situ. Assays that monitor real-time generation of cDNA reverse transcribed from mRNA using a dsr-specific primer (Chin et al. 2008) could offer a work-around to avoid false-positive results from organisms not expressing their dsr; the success of this strategy would depend on sampling and RNA extraction protocols relative to the short half-life of microbial mRNA (Frias-Lopez et al. 2008). Despite the alternatives that various metabolic gene targets offer for molecular surveillance, in oil-field microbiology, as in many other subdisciplines of microbial ecology, 16S rRNA genes (for amplicon diversity surveys and qPCR) remain widely used biomarkers.

Another culture-independent strategy to monitor the activity of SRM in situ, rooted in biogeochemistry rather than in molecular biology, is to measure the isotopic shift in sulfate to detect sulfur cycling in the reservoir relative to injection waters (Hubert et al. 2009; Hubbard et al. 2014). While hydrogen sulfide production, sulfate consumption, or the presence of SRM may be difficult to detect, isotopic methods to measure the imprint of sulfur cycling via sulfate isotopic composition are extremely sensitive and can be used to detect early-stage souring. Adopting isotopic fractionation as a monitoring approach could give oil-field operators time to focus resources on problem reservoirs and implement the other approaches outlined above to identify actionable solutions and to monitor the efficacy of nitrate, perchlorate, or other treatments.

The best molecular monitoring will always result from a combination of various strategies including those discussed above. However, comprehensive approaches may not always be compatible with the important and “real-world” objectives of rapidly generating results that can inform field operators concerned with maintaining high oil production rates while minimizing harmful effects of souring. In some instances, thorough early-stage characterization that includes MPN enumerations and strain isolation may allow probe or primer selection for targeting important microorganisms known to be present, and responsive to perturbations, in a particular oil reservoir. In addition, microbial diversity assessments through amplicon library and/or metagenome sequencing are highly recommended as early as possible in the oil reservoir production life cycle, i.e., initial formation water samples obtained from production fluids during primary production, before injection of other fluids like seawater that can trigger reservoir souring by SRM. Similar microbiological analysis of the injection fluids is also recommended for a more thorough assessment of whether or not signatures in microbial diversity profiles are likely to represent organisms indigenous to the subsurface. Routine testing using carefully developed molecular strategies can be complemented by occasional H2S-based MPN assays, stable isotope analyses, and additional SRM probe/primer sets to introduce degrees of quality assurance for the overall surveillance strategy.

6 Research Needs

Many oil companies have a good understanding of reservoir souring caused by SRM and have in recent years started introducing nitrate to alleviate souring problems at different production operations. In order for nitrate injection technology to be employed successfully in the years ahead, a more robust understanding of the underlying microbial ecology will be needed. The industry must move beyond a simple awareness that nitrate can work and gain the ability to distinguish NRM-based souring control mechanisms (Fig. 1) in different settings. This understanding will be instructive for troubleshooting instances when nitrate addition stops working at given production operations. We may learn that reservoir microbial ecology relevant for oil production is largely specific for given oil fields. However, as more case studies are undertaken, common patterns will likely emerge. In this respect, case studies involving perchlorate are needed to assess its efficacy in the field, and these can be compared to nitrate injection case studies. Developing and applying the suite of surveillance tools discussed in Sect. 5, particularly the newer molecular methods and next-generation sequencing strategies, will continue to be an important and exciting feature of modern petroleum microbiology. The critical task of designing appropriate probes and primers for oil fields will parallel the practical goal of seeing these techniques adopted as routine aspects of microbiological monitoring by oil producers. Meeting these challenges will require a successful collaboration between microbiologists and oil producers seeking an improved understanding of microbial ecology in subsurface petroleum habitats.

Notes

Acknowledgments

The authors wish to acknowledge the financial support from the Campus Alberta Innovates Program to CRJH and from the UC Berkeley Energy Biosciences Institute to HKC.

References

  1. Agrawal A, Park HS, Nathoo S et al (2012) Toluene depletion in produced oil contributes to souring control in a field subjected to nitrate injection. Environ Sci Technol 46:1285–1292.  https://doi.org/10.1021/es203748bCrossRefPubMedGoogle Scholar
  2. Alkindi A, Prince-Wright R, Moore WR et al (2013) Challenges for waterflooding in a Deepwater environment. SPE Prod Oper 23:404–410.  https://doi.org/10.2118/118735-PACrossRefGoogle Scholar
  3. Amann R, Fuchs BM (2008) Single-cell identification in microbial communities by improved fluorescence in situ hybridization techniques. Nat Rev Microbiol 6:339–348.  https://doi.org/10.1038/nrmicro1888CrossRefPubMedGoogle Scholar
  4. Amann RI, Binder BJ, Olson RJ et al (1990) Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl Environ Microbiol 56:1919–1925PubMedPubMedCentralGoogle Scholar
  5. An BA, Shen Y, Voordouw G (2017) Control of sulfide production in high salinity bakken shale oil reservoirs by halophilic bacteria reducing nitrate to nitrite. Front Microbiol 8:1164.  https://doi.org/10.3389/fmicb.2017.01164CrossRefPubMedPubMedCentralGoogle Scholar
  6. Aüllo T, Ranchou-Peyruse A, Ollivier B, Magot M (2013) Desulfotomaculum spp. and related gram-positive sulfate-reducing bacteria in deep subsurface environments. Front Microbiol 4:362.  https://doi.org/10.3389/fmicb.2013.00362CrossRefPubMedPubMedCentralGoogle Scholar
  7. Barnum TP, Figueroa IA, Carlström CI et al (2018) Genome-resolved metagenomics identifies genetic mobility, metabolic interactions, and unexpected diversity in perchlorate-reducing communities. ISME J 115:E00E11–E01581.  https://doi.org/10.1038/s41396-018-0081-5CrossRefGoogle Scholar
  8. Barrero Canosa J, Moraru C, Zeugner L et al (2017) Direct-geneFISH: a simplified protocol for the simultaneous detection and quantification of genes and rRNA in microorganisms. Environ Microbiol 19:70–82.  https://doi.org/10.1111/1462-2920.13432CrossRefPubMedGoogle Scholar
  9. Barth T (1991) Organic acids and inorganic ions in waters from petroleum reservoirs, Norwegian continental shelf: a multivariate statistical analysis and comparison with American reservoir formation waters. Appl Geochem 6:1–15.  https://doi.org/10.1016/0883-2927(91)90059-XCrossRefGoogle Scholar
  10. Bender KS, Rice MR, Fugate WH et al (2004) Metabolic primers for detection of (per)chlorate-reducing bacteria in the environment and phylogenetic analysis of cld gene sequences. Appl Environ Microbiol 70:5651–5658.  https://doi.org/10.1128/AEM.70.9.5651-5658.2004CrossRefPubMedPubMedCentralGoogle Scholar
  11. Birkeland N-K (2005) Sulfate-reducing bacteria and archaea. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 35–54CrossRefGoogle Scholar
  12. Bowers RM, Kyrpides NC, Stepanauskas R et al (2017) Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol 35:725–731.  https://doi.org/10.1038/nbt.3893CrossRefPubMedPubMedCentralGoogle Scholar
  13. Bryant MP, Campbell LL, Reddy CA, Crabill MR (1977) Growth of Desulfovibrio in lactate or ethanol media low in sulfate in association with H2-utilizing methanogenic bacteria. Appl Environm Microbiol 33:1162–1169Google Scholar
  14. Burgin AJ, Hamilton SK (2007) Have we overemphasized the role of denitrification in aquatic ecosystems? A review of nitrate removal pathways. Front Ecol Environ 5:89–96.  https://doi.org/10.1890/1540-9295(2007)5[89:HWOTRO]2.0.CO;2CrossRefGoogle Scholar
  15. Carlson HK, Kuehl JV, Hazra AB et al (2014) Mechanisms of direct inhibition of the respiratory sulfate-reduction pathway by (per)chlorate and nitrate. ISME J 9:1295–1305.  https://doi.org/10.1038/ismej.2014.216CrossRefPubMedPubMedCentralGoogle Scholar
  16. Carlson HK, Stoeva MK, Justice NB et al (2015) Monofluorophosphate is a selective inhibitor of respiratory sulfate-reducing microorganisms. Environ Sci Technol 49:3727–3736.  https://doi.org/10.1021/es505843zCrossRefPubMedGoogle Scholar
  17. Carlson HK, Mullan MR, Mosqueda LA et al (2017) High-throughput screening to identify potent and specific inhibitors of microbial sulfate reduction. Environ Sci Technol 51:7278–7285.  https://doi.org/10.1021/acs.est.7b00686CrossRefPubMedGoogle Scholar
  18. Carlström CI, Wang O, Melnyk RA et al (2013) Physiological and genetic description of dissimilatory perchlorate reduction by the novel marine bacterium Arcobacter sp. strain CAB. mBio 4:e00217–e00213.  https://doi.org/10.1128/mBio.00217-13CrossRefPubMedPubMedCentralGoogle Scholar
  19. Carlström CI, Loutey D, Bauer S et al (2015) (Per)Chlorate-reducing bacteria can utilize aerobic and anaerobic pathways of aromatic degradation with (per)chlorate as an electron acceptor. mBio 6:e02287–e02214.  https://doi.org/10.1128/mBio.02287-14CrossRefPubMedPubMedCentralGoogle Scholar
  20. Chin K-J, Sharma ML, Russell LA et al (2008) Quantifying expression of a dissimilatory (bi)sulfite reductase gene in petroleum-contaminated marine harbor sediments. Microb Ecol 55:489–499.  https://doi.org/10.1007/s00248-007-9294-2CrossRefPubMedGoogle Scholar
  21. Clark IC, Youngblut M, Jacobsen G et al (2016) Genetic dissection of chlorate respiration in Pseudomonas stutzeri PDA reveals syntrophic (per)chlorate reduction. Environ Microbiol 18:3342–3354.  https://doi.org/10.1111/1462-2920.13068CrossRefPubMedGoogle Scholar
  22. Coates JD (2014) Inhibition of microbial sulfate reduction in a flow-through column system by (per)chlorate treatment. 1–11.  https://doi.org/10.3389/fmicb.2014.00315/abstract
  23. Coates JD, Bruce RA, Haddock JD (1998) Anoxic bioremediation of hydrocarbons. Nature 396:730–730.  https://doi.org/10.1038/25470CrossRefPubMedGoogle Scholar
  24. Coates JD, Michaelidou U, Bruce RA et al (1999) Ubiquity and diversity of dissimilatory (per)chlorate-reducing bacteria. Appl Environ Microbiol 65:5234–5241PubMedPubMedCentralGoogle Scholar
  25. Dalsgaard T, Bak F (1994) Nitrate reduction in a sulfate-reducing bacterium, Desulfovibrio desulfuricans, isolated from rice paddy soil: sulfide inhibition, kinetics, and regulation. Appl Environ Microbiol 60:291–297PubMedPubMedCentralGoogle Scholar
  26. Dolfing J, Hubert CRJ (2017) Using thermodynamics to predict the outcomes of nitrate-based oil reservoir souring control interventions. Front Microbiol 8:2575.  https://doi.org/10.3389/fmicb.2017.02575
  27. Dong X, Kleiner M, Sharp CE, et al (2017) Fast and simple analysis of MiSeq amplicon sequencing data with MetaAmp. bioRxiv:131631.  https://doi.org/10.1101/131631
  28. Eckford RE, Fedorak PM (2004) Chapter 11 Using nitrate to control microbially-produced hydrogen sulfide in oil field waters. In: Petroleum biotechnology – developments and perspectives. Elsevier, Oxford, pp 307–340CrossRefGoogle Scholar
  29. Engelbrektson AL, Cheng Y, Hubbard CG, Jin YT, Arora B, Tom LM, Hu P, Grauel AL, Conrad ME, Andersen GL, Ajo-Franklin JB, Coates JD (2018a) Attenuating Sulfidogenesis in a soured continuous flow column system with perchlorate treatment. Front Microbiol 9:1575.  https://doi.org/10.3389/fmicb.2018.01575CrossRefPubMedPubMedCentralGoogle Scholar
  30. Engelbrektson A, Briseno V, Liu Y, Figueroa I, Yee M, Shao GL, Carlson H, Coates JD (2018b) Mitigating Sulfidogenesis with simultaneous perchlorate and nitrate treatments. Front Microbiol 9:2305.  https://doi.org/10.3389/fmicb.2018.02305CrossRefPubMedPubMedCentralGoogle Scholar
  31. Fida TT, Chen C, Okpala G, Voordouw G (2016) Implications of limited thermophilicity of nitrite reduction for control of sulfide production in oil reservoirs. Appl Environ Microbiol 82:4190–4199.  https://doi.org/10.1128/AEM.00599-16CrossRefPubMedPubMedCentralGoogle Scholar
  32. Frias-Lopez J, Shi Y, Tyson GW et al (2008) Microbial community gene expression in ocean surface waters. Proc Natl Acad Sci 105:3805–3810.  https://doi.org/10.1073/pnas.0708897105CrossRefPubMedGoogle Scholar
  33. Gevertz D, Telang AJ, Voordouw G, Jenneman GE (2000) Isolation and characterization of strains CVO and FWKO B, two novel nitrate-reducing, sulfide-oxidizing bacteria isolated from oil field brine. Appl Environ Microbiol 66:2491–2501.  https://doi.org/10.1128/AEM.66.6.2491-2501.2000CrossRefPubMedPubMedCentralGoogle Scholar
  34. Gieg LM, Jack, TR, Foght JM (2011) Appl Microbiol Biotechnol 92:263.  https://doi.org/10.1007/s00253-011-3542-6
  35. Giovannoni S, Stingl U (2007) The importance of culturing bacterioplankton in the “omics” age. Nat Rev Micro 5:820–826.  https://doi.org/10.1038/nrmicro1752CrossRefGoogle Scholar
  36. Gittel A, Sørensen KB, Skovhus TL et al (2009) Prokaryotic community structure and sulfate reducer activity in water from high-temperature oil reservoirs with and without nitrate treatment. Appl Environ Microbiol 75:7086–7096.  https://doi.org/10.1128/AEM.01123-09CrossRefPubMedPubMedCentralGoogle Scholar
  37. Greene EA, Hubert C, Nemati M et al (2003) Nitrite reductase activity of sulphate-reducing bacteria prevents their inhibition by nitrate-reducing, sulphide-oxidizing bacteria. Environ Microbiol 5:607–617.  https://doi.org/10.1046/j.1462-2920.2003.00446.xCrossRefPubMedGoogle Scholar
  38. Greene EA, Brunelle V, Jenneman GE, Voordouw G (2006) Synergistic inhibition of microbial sulfide production by combinations of the metabolic inhibitor nitrite and biocides. Appl Environ Microbiol 72:7897–7901.  https://doi.org/10.1128/AEM.01526-06CrossRefPubMedPubMedCentralGoogle Scholar
  39. Gregoire P, Engelbrektson A, Hubbard CG et al (2014) Control of sulfidogenesis through bio-oxidation of H2S coupled to (per)chlorate reduction. Environ Microbiol Rep 6:558–564CrossRefGoogle Scholar
  40. Grigoryan A, Voordouw G (2008) Microbiology to help solve our energy needs. Ann N Y Acad Sci 1125:345–352.  https://doi.org/10.1196/annals.1419.004CrossRefPubMedGoogle Scholar
  41. Grigoryan AA, Cornish SL, Buziak B et al (2008) Competitive oxidation of volatile fatty acids by sulfate- and nitrate-reducing bacteria from an oil field in Argentina. Appl Environ Microbiol 74:4324–4335.  https://doi.org/10.1128/AEM.00419-08CrossRefPubMedPubMedCentralGoogle Scholar
  42. Hanna E, Ng KF, MacRae IJ et al (2004) Kinetic and stability properties of Penicillium chrysogenum ATP sulfurylase missing the C-terminal regulatory domain. J Biol Chem 279:4415–4424.  https://doi.org/10.1074/jbc.M311317200CrossRefPubMedGoogle Scholar
  43. Harms G, Zengler K, Rabus R et al (1999) Anaerobic oxidation of o-xylene, m-xylene, and homologous alkylbenzenes by new types of sulfate-reducing bacteria. Appl Environ Microbiol 65:999–1004PubMedPubMedCentralGoogle Scholar
  44. Haveman SA, Greene EA, Stilwell CP et al (2004) Physiological and gene expression analysis of inhibition of Desulfovibrio vulgaris Hildenborough by nitrite. J Bacteriol 186:7944–7950.  https://doi.org/10.1128/JB.186.23.7944-7950.2004CrossRefPubMedPubMedCentralGoogle Scholar
  45. Head IM, Jones DM, Larter SR (2003) Biological activity in the deep subsurface and the origin of heavy oil. Nature 426:344–352.  https://doi.org/10.1038/nature02134CrossRefPubMedGoogle Scholar
  46. Henry S, Bru D, Stres B et al (2006) Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ genes in soils. Appl Environ Microbiol 72:5181–5189.  https://doi.org/10.1128/AEM.00231-06CrossRefPubMedPubMedCentralGoogle Scholar
  47. Hu P, Tom L, Singh A et al (2016) Genome-resolved metagenomic analysis reveals roles for candidate phyla and other microbial community members in biogeochemical transformations in oil reservoirs. mBio 7:e01669–e01615.  https://doi.org/10.1128/mBio.01669-15CrossRefPubMedPubMedCentralGoogle Scholar
  48. Hubbard CG, Cheng Y, Engelbrekston A et al (2014) Isotopic insights into microbial sulfur cycling in oil reservoirs. Front Microbiol 5:480.  https://doi.org/10.3389/fmicb.2014.00480CrossRefPubMedPubMedCentralGoogle Scholar
  49. Hubert C, Voordouw G (2007) Oil field souring control by nitrate-reducing Sulfurospirillum spp. that outcompete sulfate-reducing bacteria for organic electron donors. Appl Environ Microbiol 73:2644–2652.  https://doi.org/10.1128/AEM.02332-06CrossRefPubMedPubMedCentralGoogle Scholar
  50. Hubert C, Nemati M, Jenneman G, Voordouw G (2003) Containment of biogenic sulfide production in continuous up-flow packed-bed bioreactors with nitrate or nitrite. Biotechnol Prog 19:338–345.  https://doi.org/10.1021/bp020128fCrossRefPubMedGoogle Scholar
  51. Hubert C, Nemati M, Jenneman G, Voordouw G (2005) Corrosion risk associated with microbial souring control using nitrate or nitrite. Appl Microbiol Biotechnol 68:272–282.  https://doi.org/10.1007/s00253-005-1897-2CrossRefPubMedGoogle Scholar
  52. Hubert C, Voordouw G, Mayer B (2009) Elucidating microbial processes in nitrate- and sulfate-reducing systems using sulfur and oxygen isotope ratios: the example of oil reservoir souring control. Geochim Cosmochim Acta 73:3864–3879.  https://doi.org/10.1016/j.gca.2009.03.025CrossRefGoogle Scholar
  53. Hubert CRJ, Oldenburg TBP, Fustic M, Gray ND, Larter SR, Penn K, Rowan AK, Seshadri R, Sherry A, Swainsbury R, Voordouw G, Voordouw J, Head IM (2012) Massive dominance of Epsilonproteobacteria in formation waters from a Canadian oil sands reservoir containing severely biodegraded oil. Environ Microbiol 14:387–404CrossRefGoogle Scholar
  54. Imachi H, Sekiguchi Y, Kamagata Y et al (2006) Non-sulfate-reducing, syntrophic bacteria affiliated with Desulfotomaculum cluster I are widely distributed in methanogenic environments. Appl Environ Microbiol 72:2080–2091.  https://doi.org/10.1128/AEM.72.3.2080-2091.2006CrossRefPubMedPubMedCentralGoogle Scholar
  55. Jensen AB, Webb C (1995) Treatment of H2S-containing gases: a review of microbiological alternatives. Enzym Microb Technol 17:2–10.  https://doi.org/10.1016/0141-0229(94)00080-BCrossRefGoogle Scholar
  56. Johnson RJ, Folwell BD, Wirekoh A et al (2017) Reservoir souring – latest developments for application and mitigation. J Biotechnol 256:57–67.  https://doi.org/10.1016/j.jbiotec.2017.04.003CrossRefPubMedGoogle Scholar
  57. Jones DM, Head IM, Gray ND et al (2008) Crude-oil biodegradation via methanogenesis in subsurface petroleum reservoirs. Nature 451:176–180.  https://doi.org/10.1038/nature06484CrossRefPubMedGoogle Scholar
  58. Justice NB, Sczesnak A, Hazen TC, Arkin AP (2017) Environmental selection, dispersal, and organism interactions shape community assembly in high-throughput enrichment culturing. Appl Environ Microbiol 83:e01253–e01217.  https://doi.org/10.1128/AEM.01253-17CrossRefPubMedPubMedCentralGoogle Scholar
  59. Kim DD, O'Farrell C, Toth CRA, Montoya O, Gieg LM, Kwon TH, Yoon S (2018) Microbial community analyses of produced waters from high-temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs. Microb Biotechnol 11:788–796CrossRefGoogle Scholar
  60. Kraft B, Tegetmeyer HE, Sharma R et al (2014) Nitrogen cycling. The environmental controls that govern the end product of bacterial nitrate respiration. Science 345:676–679.  https://doi.org/10.1126/science.1254070CrossRefPubMedGoogle Scholar
  61. Lahme S, Hubert C (2017) Corrosion risks associated with (bio)chemical processes in sour systems due to nitrate injection or oxygen ingress. In: Enning DE, Skovhus TL, Lee J (eds) Microbiologically influenced corrosion in the upstream oil and gas industry. Taylor and Francis, Boca Raton, pp 87–109. ISBN: 978-149872660-3; 978-149872656-6CrossRefGoogle Scholar
  62. Lahme S, Enning DE, Callbeck CM, Menendez Vega D, Curtis TP, Head IM, Hubert CRJ (2019) Metabolites of an oil field sulfide-oxidizing nitrate-reducing Sulfurimonas sp. cause severe corrosion. Appl Environ Microbiol 85(3):01891–01818.  https://doi.org/10.1128/AEM.01891-18CrossRefGoogle Scholar
  63. Lewin A, Johansen J, Wentzel A et al (2014) The microbial communities in two apparently physically separated deep subsurface oil reservoirs show extensive DNA sequence similarities. Environ Microbiol 16:545–558.  https://doi.org/10.1111/1462-2920.12181CrossRefPubMedGoogle Scholar
  64. Li X, Krumholz LR (2007) Regulation of arsenate resistance in Desulfovibrio desulfuricans G20 by an arsRBCC operon and an arsC gene. J Bacteriol 189:3705–3711.  https://doi.org/10.1128/JB.01913-06CrossRefPubMedPubMedCentralGoogle Scholar
  65. Li G, Gao P, Wu Y et al (2014) Microbial abundance and community composition influence production performance in a low-temperature petroleum reservoir. Environ Sci Technol 48:5336–5344.  https://doi.org/10.1021/es500239wCrossRefPubMedGoogle Scholar
  66. Lide DD (2007) CRC handbook of chemistry and physics, 88th edn. CRC Press, Boca Raton, pp 1–59Google Scholar
  67. Liebensteiner MG, Pinkse MWH, Schaap PJ et al (2013) Archaeal (per)chlorate reduction at high temperature: an interplay of biotic and abiotic reactions. Science 340:85–87.  https://doi.org/10.1126/science.1233957CrossRefPubMedGoogle Scholar
  68. Liebensteiner MG, Tsesmetzis N, Stams AJM, Lomans BP (2014) Microbial redox processes in deep subsurface environments and the potential application of (per)chlorate in oil reservoirs. Front Microbiol 5:428.  https://doi.org/10.3389/fmicb.2014.00428CrossRefPubMedPubMedCentralGoogle Scholar
  69. Lovley DR, Phillips EJP (1994) Reduction of chromate by Desulfovibrio vulgaris and its c3 cytochrome. Appl Environ Microbiol 60:726–728PubMedPubMedCentralGoogle Scholar
  70. Loy A, Duller S, Baranyi C et al (2009) Reverse dissimilatory sulfite reductase as phylogenetic marker for a subgroup of sulfur-oxidizing prokaryotes. Environ Microbiol 11:289–299.  https://doi.org/10.1111/j.1462-2920.2008.01760.xCrossRefPubMedPubMedCentralGoogle Scholar
  71. Magot M (2005) Indigenous microbial communities in oil fields. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 21–34CrossRefGoogle Scholar
  72. McGenity TJ (2016) Introduction to the isolation and cultivation of microbes involved in the hydrocarbon cycle. In: Hydrocarbon and lipid microbiology protocols, 2nd edn. Springer Berlin Heidelberg, Berlin/Heidelberg, pp 1–25Google Scholar
  73. McKew BA, Smith CJ (2015) Real-time PCR approaches for analysis of hydrocarbon-degrading bacterial communities. In: Hydrocarbon and lipid microbiology protocols. Springer Berlin Heidelberg, Berlin/Heidelberg, pp 45–64CrossRefGoogle Scholar
  74. Mehta-Kolte MG, Loutey D, Wang O et al (2017) Mechanism of H2S oxidation by the dissimilatory perchlorate-reducing microorganism Azospira suillum PS. mBio 8:e02023–e02016.  https://doi.org/10.1128/mBio.02023-16CrossRefPubMedPubMedCentralGoogle Scholar
  75. Melnyk RA, Coates JD (2015) The perchlorate reduction genomic island: mechanisms and pathways of evolution by horizontal gene transfer. BMC Genomics 16:616.  https://doi.org/10.1186/s12864-015-2011-5CrossRefGoogle Scholar
  76. Melnyk RA, Clark IC, Liao A, Coates JD (2013) Transposon and deletion mutagenesis of genes involved in perchlorate reduction in Azospira suillum PS. mBio 5:e00769–e00713.  https://doi.org/10.1128/mBio.00769-13CrossRefPubMedPubMedCentralGoogle Scholar
  77. Melnyk RA, Youngblut MD, Clark IC et al (2015) Novel mechanism for scavenging of hypochlorite involving a periplasmic methionine-rich peptide and methionine sulfoxide reductase. mBio 6:e00233–15–e00233–18.  https://doi.org/10.1128/mBio.00233-15CrossRefPubMedPubMedCentralGoogle Scholar
  78. Michel C, Brugna M, Aubert C et al (2001) Enzymatic reduction of chromate: comparative studies using sulfate-reducing bacteria: key role of polyheme cytochromes c and hydrogenases. Appl Microbiol Biotechnol 55:95–100.  https://doi.org/10.1007/s002530000467CrossRefPubMedGoogle Scholar
  79. Moraru C, Lam P, Fuchs BM et al (2010) GeneFISH – an in situ technique for linking gene presence and cell identity in environmental microorganisms. Environ Microbiol 12:3057–3073.  https://doi.org/10.1111/j.1462-2920.2010.02281.xCrossRefPubMedGoogle Scholar
  80. Müller AL, Kjeldsen KU, Rattei T et al (2015) Phylogenetic and environmental diversity of DsrAB-type dissimilatory (bi)sulfite reductases. ISME J 9:1152–1165.  https://doi.org/10.1038/ismej.2014.208CrossRefPubMedGoogle Scholar
  81. Muyzer G, Stams AJM (2008) The ecology and biotechnology of sulphate-reducing bacteria. Nat Rev Micro 6:441.  https://doi.org/10.1038/nrmicro1892CrossRefGoogle Scholar
  82. Nemati M, Jenneman GE, Voordouw G (2001a) Mechanistic study of microbial control of hydrogen sulfide production in oil reservoirs. Biotechnol Bioeng 74:424–434.  https://doi.org/10.1002/bit.1133CrossRefPubMedGoogle Scholar
  83. Nemati M, Jenneman GE, Voordouw G (2001b) Impact of nitrate-mediated microbial control of souring in oil reservoirs on the extent of corrosion. Biotechnol Prog 17:852–859.  https://doi.org/10.1021/bp010084vCrossRefPubMedGoogle Scholar
  84. Okpala GN, Chen C, Fida T, Voordouw G (2017) Effect of thermophilic nitrate reduction on sulfide production in high temperature oil reservoir samples. Front Microbiol 8:1573.  https://doi.org/10.3389/fmicb.2017.01573CrossRefPubMedPubMedCentralGoogle Scholar
  85. Ollivier B, Cayol J-L (2005) Fermentative, iron-reducing, and nitrate-reducing microorganisms. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 71–88CrossRefGoogle Scholar
  86. Ollivier B, Cayol J-L, Fauque G (2009) Sulphate-reducing bacteria from oil field environments and deep-sea hydrothermal vents. In: Barton LL, Hamilton WA (eds) Sulphate-reducing bacteria. Cambridge University Press, Cambridge, pp 305–328Google Scholar
  87. Oremland RS, Capone DG (1988) Use of “specific” inhibitors in biogeochemistry and microbial ecology. In: Advances in microbial ecology. Springer US, Boston, pp 285–383CrossRefGoogle Scholar
  88. Pannekens M, Kroll L, Müller H, Tall Mbow F, Meckenstock RU (2019) Oil reservoirs, an exceptional habitat for microorganisms. New Biotechnol 49:1–9CrossRefGoogle Scholar
  89. Peck HD (1959) THE ATP-DEPENDENT REDUCTION OF SULFATE WITH HYDROGEN IN EXTRACTS OF DESULFOVIBRIO DESULFURICANS. Proc Natl Acad Sci 45:701–708.  https://doi.org/10.1073/pnas.45.5.701CrossRefPubMedGoogle Scholar
  90. Pereira IA, LeGall J, Xavier AV, Teixeira M (2000) Characterization of a heme c nitrite reductase from a non-ammonifying microorganism, Desulfovibrio vulgaris Hildenborough. Biochim Biophys Acta 1481:119–130CrossRefGoogle Scholar
  91. Pham VD, Hnatow LL, Zhang S et al (2009) Characterizing microbial diversity in production water from an Alaskan mesothermic petroleum reservoir with two independent molecular methods. Environ Microbiol 11:176–187.  https://doi.org/10.1111/j.1462-2920.2008.01751.xCrossRefPubMedGoogle Scholar
  92. Plugge CM, Balk M, Stams AJM (2002) Desulfotomaculum thermobenzoicum subsp. thermosyntrophicum subsp. nov., a thermophilic, syntrophic, propionate-oxidizing, spore-forming bacterium. IJSEB 52:391–399.  https://doi.org/10.1099/00207713-52-2-391CrossRefGoogle Scholar
  93. Postgate JR (1952) Competitive and noncompetitive inhibitors of bacterial sulphate reduction. J Gen Microbiol 6:128–142.  https://doi.org/10.1099/00221287-6-1-2-128CrossRefPubMedGoogle Scholar
  94. Renosto F, Patel HC, Martin RL et al (1993) ATP sulfurylase from higher plants: kinetic and structural characterization of the chloroplast and cytosol enzymes from spinach leaf. Arch Biochem Biophys 307:272–285.  https://doi.org/10.1006/abbi.1993.1590CrossRefPubMedGoogle Scholar
  95. Rowley HH, Stuckey JE (1956) Preparation and properties of calcium monofluorophosphate dihydrate. J Am Chem Soc 78:4262–4263.  https://doi.org/10.1021/ja01598a022CrossRefGoogle Scholar
  96. Sanders PF, Sturman PJ (2005) Biofouling in the oil industry. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 171–198CrossRefGoogle Scholar
  97. Schwermer CU, Lavik G, Abed RMM et al (2008) Impact of nitrate on the structure and function of bacterial biofilm communities in pipelines used for injection of seawater into oil fields. Appl Environ Microbiol 74:2841–2851.  https://doi.org/10.1128/AEM.02027-07CrossRefPubMedPubMedCentralGoogle Scholar
  98. Seitz H-JR, Cypionka H (1986) Chemolithotrophic growth of Desulfovibrio desulfuricans with hydrogen coupled to ammonification of nitrate or nitrite. Arch Microbiol 146:63–67.  https://doi.org/10.1007/BF00690160CrossRefGoogle Scholar
  99. Shen Y, Voordouw G (2015) Primers for dsr genes and most probable number method for detection of sulfate-reducing bacteria in oil reservoirs. In: Hydrocarbon and lipid microbiology protocols. Springer Berlin Heidelberg, Berlin/Heidelberg, pp 35–43CrossRefGoogle Scholar
  100. Smith CJ, Nedwell DB, Dong LF, Osborn AM (2007) Diversity and abundance of nitrate reductase genes (narG and napA), nitrite reductase genes (nirS and nrfA), and their transcripts in estuarine sediments. Appl Environ Microbiol 73:3612–3622.  https://doi.org/10.1128/AEM.02894-06CrossRefPubMedPubMedCentralGoogle Scholar
  101. Smith CJ, Osborne AM (2008) Advantages and limitations of quantitative PCR(Q-PCR)-based approaches in microbial ecology. FEMS Microbiol Ecol 67:6–20Google Scholar
  102. Smith CJ, McKew BA, Coggan A, Whitby C (2017) Primers: functional genes for nitrogen-cycling. In: McGenity TJ et al (eds) Hydrocarbon and lipid microbiology protocols, Springer protocols handbooks, pp 207–241.  https://doi.org/10.1007/8623_2015_184
  103. Stahl DA, Loy A, Wagner M (2007) Molecular strategies for studies of natural populations of sulphate-reducing microorganisms. In: Barton LL, Hamilton WA (eds) Sulphate-reducing bacteria. Cambridge University Press, Cambridge, pp 39–116CrossRefGoogle Scholar
  104. Stahl DA, Loy A, Wagner M (2009) Molecular strategies for studies of natural populations of sulphate-reducing microorganisms. In: Barton LL, Hamilton WA (eds) Sulphate-reducing bacteria. Cambridge University Press, Cambridge, pp 39–116Google Scholar
  105. Stewart EJ (2012) Growing unculturable bacteria. J Bacteriol 194:4151–4160.  https://doi.org/10.1128/JB.00345-12CrossRefPubMedPubMedCentralGoogle Scholar
  106. Strohm TO, Griffin B, Zumft WG, Schink B (2007) Growth yields in bacterial denitrification and nitrate ammonification. Appl Environ Microbiol 73:1420–1424.  https://doi.org/10.1128/AEM.02508-06CrossRefPubMedPubMedCentralGoogle Scholar
  107. Suri N, Voordouw J, Voordouw G (2017) The effectiveness of nitrate-mediated control of the oil field sulfur cycle depends on the toluene content of the oil. Front Microbio 8:956.  https://doi.org/10.3389/fmicb.2017.00956CrossRefGoogle Scholar
  108. Telang AJ, Ebert S, Foght JM et al (1998) Effects of two diamine biocides on the microbial community from an oil field. Can J Microbiol 44:1060–1065.  https://doi.org/10.1139/cjm-44-11-1060CrossRefGoogle Scholar
  109. Telang AJ, Jenneman GE, Voordouw G (1999) Sulfur cycling in mixed cultures of sulfide-oxidizing and sulfate- or sulfur-reducing oil field bacteria. Can J Microbiol 45:905–913.  https://doi.org/10.1139/cjm-45-11-905CrossRefGoogle Scholar
  110. Thrasher DR, Vance I (2005) Reservoir souring: mechanisms and prevention. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 123–142Google Scholar
  111. Torsvik T, Sunde E (2005) Microbial control of hydrogen sulfide production in oil reservoirs. In: Petroleum microbiology. American Society of Microbiology, Washington DC, pp 201–213Google Scholar
  112. Vester F, Ingvorsen K (1998) Improved most-probable-number method to detect sulfate-reducing bacteria with natural media and a radiotracer. Appl Environ Microbiol 64:1700–1707PubMedPubMedCentralGoogle Scholar
  113. Vigneron A, Alsop EB, Lomans BP et al (2017) Succession in the petroleum reservoir microbiome through an oil field production lifecycle. ISME J 11:2141–2154.  https://doi.org/10.1038/ismej.2017.78CrossRefPubMedPubMedCentralGoogle Scholar
  114. Vigneron A, Cruaud P, Alsop E, de Rezende JR, Head IM (2018) Beyond the tip of the iceberg; A new view of the diversity of sulfite- and sulfate-reducing microorganisms. ISME J 12:2096–2099CrossRefGoogle Scholar
  115. Voordouw G, Armstrong SM, Reimer MF et al (1996) Characterization of 16S rRNA genes from oil field microbial communities indicates the presence of a variety of sulfate-reducing, fermentative, and sulfide-oxidizing bacteria. Appl Environ Microbiol 62:1623–1629PubMedPubMedCentralGoogle Scholar
  116. Voordouw G, Voordouw JK, Karkhoff-Schweizer RR, Fedorak PM, Westlake DWS (1991) Reverse Sample Genome Probing, a New Technique for Identification of Bacteria in Environmental Samples by DNA Hybridization, and Its Application to the Identification of Sulfate-Reducing Bacteria in Oil Field Samples. Appl Environ Microbiol 57(11):3070–3078Google Scholar
  117. Widdel F, Musat F, Knittel K, Galushko A (2009) Anaerobic degradation of hydrocarbons with sulphate as electron acceptor. In: Barton LL, Hamilton WA (eds) Sulphate-reducing bacteria. Cambridge University Press, Cambridge, pp 265–304Google Scholar
  118. Youngblut MD, Tsai C-L, Clark IC et al (2016a) Perchlorate reductase is distinguished by active site aromatic gate residues. J Biol Chem 291:9190–9202.  https://doi.org/10.1074/jbc.M116.714618CrossRefPubMedPubMedCentralGoogle Scholar
  119. Youngblut MD, Wang O, Barnum TP, Coates JD (2016b) (Per)chlorate in biology on earth and beyond. Annu Rev Microbiol 70:435–457.  https://doi.org/10.1146/annurev-micro-102215-095406CrossRefPubMedGoogle Scholar
  120. Zengler K, Richnow HH, Rosselló-Mora R et al (1999) Methane formation from long-chain alkanes by anaerobic microorganisms. Nature 401:266–269.  https://doi.org/10.1038/45777CrossRefPubMedGoogle Scholar

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Authors and Affiliations

  1. 1.Environmental Genomics and Systems Biology DivisionLawrence Berkeley National LabBerkeleyUSA
  2. 2.Department of Biological SciencesUniversity of CalgaryCalgaryCanada

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