Critical review: Microbially influenced corrosion of buried carbon steel pipes

International Biodeterioration & Biodegradation 93 (2014) 84e106

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Review

Critical review: Microbially influenced corrosion of buried carbon steel pipes K.M. Usher a, *, A.H. Kaksonen a, I. Cole b, D. Marney c a

CSIRO Land and Water, Private Bag No. 5, Wembley, Western Australia 6913, Australia CSIRO Materials Science and Engineering, Private Bag 33, Clayton South, Victoria 3169, Australia c CSIRO Land and Water, PO Box 56, Highett, Victoria 3190, Australia b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 December 2013 Received in revised form 8 May 2014 Accepted 12 May 2014 Available online

External corrosion of buried carbon steel pipes is a problem of global proportions, affecting a wide range of industries and services. Many factors affect corrosion rates. Biofilms may secrete enzymes and compounds that attack metal, alter local acidity and create differential aeration and galvanic cells. An important consideration is that biofilm metabolisms and enzymatic reactions are constantly in flux, altering the impact of microorganisms on corrosion rates, and thermodynamic equilibrium is not reached. Recent research demonstrates that some anaerobic microorganisms catalyse the oxidation of metallic iron and directly consume the electrons, with serious consequences for corrosion. This review examines relationships between soil characteristics, microbiology and corrosion processes, focussing on the impacts of microorganisms on external corrosion of buried carbon steel pipes. Techniques for improving the understanding of microbially influenced corrosion are considered and critiqued, with the aim of assisting those who work in the area of corrosion mitigation. © 2014 Elsevier Ltd. All rights reserved.

Keywords: Carbon steel Microbially influenced corrosion Buried steel External corrosion of pipes

Contents 1. 2.

3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Factors affecting MIC in soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1. Environmental factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2. Steel and corrosion products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.3. Microbiological factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3.1. Extracellular polymeric substances (EPS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3.2. Microbes and soil characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3.3. Biofilm growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Microbially influenced corrosion (MIC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1. Pure cultures vs mixed species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.2. MIC mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2.1. Galvanic cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2.2. Differential aeration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.3. Acidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.4. Volatile compounds and enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.5. Nanowires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.6. Direct consumption of electrons from steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3. MIC microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.3.1. Sulphate reducing bacteria (SRB) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.3.2. Sulphur oxidising microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3.3. Metal oxidising and reducing microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

* Corresponding author. Tel.: þ61 8 9333 6270; fax: þ61 8 9333 6211. E-mail address: [email protected] (K.M. Usher). http://dx.doi.org/10.1016/j.ibiod.2014.05.007 0964-8305/© 2014 Elsevier Ltd. All rights reserved.

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4.

5. 6.

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3.3.4. Methanogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3.5. Fungi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.3.6. Photosynthetic organisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Useful tools for MIC research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4.1. Genetic tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4.2. Fluorescence staining and optical microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.3. Metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.4. Electron microscopy and spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.5. Microsensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.6. Electrochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.6.1. Soil resistivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.6.2. Effect of applied currents and potentials on microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.6.3. Linear polarisation resistance (LPR) and electrochemical impedance spectroscopy (EIS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.6.4. Galvanic current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.6.5. Electrochemical noise (EN) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Case studies of buried carbon steel and iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 6.1. Experimental approaches e get real . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 6.2. Future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Uncited reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

1. Introduction Carbon steel is one of the most widely used materials for the transmission of water, petroleum products and chemicals (Baboian, 2005), and external corrosion of buried pipes is a major problem for these transmission pipeline systems (Jack et al., 1996). The consequences of pipe failure are borne by a wide range of industries and utilities and can include the costly loss of production, contamination of the environment, expensive and difficult repairs, suspension of critical services such as water supplies and serious safety hazards including public health risks due to contamination of water that can occur during a failure event. Corrosion is often considered an abiotic process controlled by physico-chemical/electrochemical processes (Little et al., 1991). This approach has largely determined both corrosion management and research, while microbiological contributions to the corrosion rates of buried pipes have often been overlooked. This perhaps is the reason that correlations between corrosion rates and soil characteristics have remained poor (Cole and Marney, 2012). Recently, increases in the rates of corrosion have been reported (Ringas and Robinson, 1987; Boothroyd and Boulton, 1998; Melchers, 2005, 2007), affecting buried steel and marine structures. However, this has not been quantified under controlled conditions. Higher corrosion rates may be caused by increases in the concentrations of nutrients from fertilisers such as nitrates (NO 3) and ammonium (NHþ 4 ), which can increase microbial growth rates (Little et al., 1991; Melchers, 2007), although NO 3 is also involved in ferrous iron oxidation (discussed later). Restrictions in the biocides that can be applied to infrastructure have been blamed by some for increased corrosion rates (Boothroyd and Boulton, 1998). Higher temperatures, for example during warmer summer months, are also known to increase biofilm growth rates, particularly when nutrient levels are high (Little et al., 1991). Future extreme weather events such as high temperatures and floods that are expected with climate change, together with greater nutrient availability from increased urban populations, are likely to result in further increases in microbially influenced corrosion (MIC) problems. Today, MIC, or biocorrosion, is an established field of research, but this has taken many years. In 1963 it was suggested that

microbes might affect corrosion rates when corroded pipes were observed in what was considered to be mildly corrosive soils (Fitzgerald, 1989). However, the significance of MIC was not widely recognised at this time. We now know that the involvement of microorganisms can increase corrosion rates by several orders of magnitude (Beech and Coutinho, 2003), and the understanding of the impacts of specific microorganisms on their environments, the interconnected functioning of natural microbial communities and the physical and chemical characteristics of biofilms has advanced significantly. Assisting this process are powerful new tools, such as advanced microscopy, spectroscopy and surface-analysis techniques, that have changed perceptions regarding the impact of microorganisms on materials (Beech et al., 2005). It is now accepted that microbial activities strongly influence iron redox chemistry in most environments (McLean et al., 2002; Weber et al., 2006; Gadd, 2010). Advances in the understanding of MIC from the increasing use of these tools, together with molecular identification and analytical techniques, were identified as one of the major reasons for the establishment of BIOCOR ITN, the European Union biocorrosion training network, in 2009. Despite progress there remain few studies of MIC of buried pipes that have been conducted in natural environments. Important challenges that have been identified in understanding MIC include the significance of different microbial populations for MIC, how enzymes within a biofilm affect corrosion and the transfer of electrons from zero valent metals to electron acceptors by metals trapped within biofilms (Beech and Sunner, 2004). There is an understanding that MIC can lead to severe damage through pitting, crevice corrosion and blistering (Mansfeld and Little, 1991; Campaignolle, 1997; Little et al., 2000) and MIC is thought to be a major cause of external corrosion of pipes in soil (Jack et al., 1996; Li et al., 2001). Despite protective coatings and cathodic protection buried pipes can fail prematurely (Jack et al., 1996; Li et al., 2001) and in some cases protective measures may promote MIC, for example, where protective tape forms an anaerobic environment in which sulphate reducing bacteria can grow (Hutchinson et al., 2004). MIC is thought to be responsible for at least 20% of the $276b annual corrosion costs experienced in the US, that is, about $55b annually (Corrosion costs and preventive strategies in the United States,

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2002). In Australia around 80% of the 260 000 km of water utility pipelines are buried, and 70% of these are composed of ferrous metal (Water Services Association of Australia, 2008e09), with damage caused by MIC estimated to be in the order of $6b annually (Javaherdashti and Vimpani, 2003). It is therefore important to advance our understanding of MIC in order to limit the costs and service disruptions associated with the risks of premature failure of infrastructure. This review aims to assist those who work in the area of corrosion mitigation, focussing on the impacts of microorganisms on external corrosion of buried carbon steel pipes, including the interactions between microbial species and between microbes and their environment. We review the factors that affect MIC, MIC mechanisms and microorganisms, and methods that can be used to research this area. For a recent review of corrosion electrochemistry and the effects non-microbial aspects of the environmental on corrosion of buried steel see Cole and Marney (2012). 2. Factors affecting MIC in soils 2.1. Environmental factors Soil is one of the most important habitats for life, and it is also one of the most dynamic and least understood habitats on earth (Handelsman et al., 1998; Hinsinger et al., 2009). It is heterogeneous in terms of physical, chemical and microbiological composition (Torsvik et al., 1996), and metals are a natural component of all soils as mobile ions and in minerals and organic compounds (Gadd, 2010). The rates of corrosion of unprotected buried pipes vary significantly in different locations (Ferguson and Nicholas, 1992). The corrosion rate can be predicted to some extent by an analysis of soil moisture, electrical resistivity and chemistry, including pH and the concentrations of ions (chloride, sulphate, sulphide), organic carbon, and oxygen (Mansfeld and Little, 1991; Li et al., 2001; Katano et al., 2003; Velazquez et al., 2009). The highest corrosion rates generally occur in poorly drained acidic clay soils (Velazquez et al., 2009; Sancy et al., 2010). Acid sulphate soils develop when soil containing sulphide minerals such as pyrite are exposed to oxygen by excavation or drainage; however, sulphate can also originate from weathering of other minerals, sea salt, volcanic sources and the atmosphere (Bao et al., 2004), as well as organic matter and fertilisers. To assist in determining corrosion risk a 10 point scoring system to categorise the corrosiveness of soils was published by the American Water Works Association (1999). Unfortunately, the correlation between soil properties and corrosion rates are often weak (Doyle et al., 2003; Kleiner et al., 2010; Cole and Marney, 2012), indicating that important additional factors influence corrosion rates in soil (Cole and Marney, 2012). One of these factors may be the microbial communities present. General environmental factors such as rainfall, soil moisture, temperature, water table levels and topography are known to affect the corrosion rates of buried pipes (Cole and Marney, 2012). Other factors that impact on failure rates include stray currents and external loads from the weight of soil and above-ground activities such as traffic (Ferguson and Nicholas, 1992; Rajani and Kleiner, 2001; Liu et al., 2012), and depth in the soil (Oguzie et al., 2004). Soil resistivity has received much attention as a possible key determinant of corrosion rates, with low resistivity soils thought to be more corrosive. However, resistivity is a function of soil moisture and the concentration of current-carrying soluble ions, and the usefulness of resistivity as a measure independent of soil moisture is not clear (Kleiner et al., 2010; Cole and Marney, 2012). Some studies have found little or no correlation between resistivity and corrosion rates (for example see Mughabghab and Sullivan, 1989;

Norin and Vinka, 2003; Ferreira et al., 2007), although other studies have found positive correlations (Doyle et al., 2003). 2.2. Steel and corrosion products Carbon steel is the most widely used engineering steel, but has poor corrosion resistance. Although buried carbon steel pipes are often coated to reduce corrosion, many fungi and bacteria degrade commonly used coatings such as polyurethane, and this may accelerate corrosion of the underlying steel (Gu, 2009). Degradation often commences with inconsistent adhesion between the coating and the metallic surface, providing a space where microbes can grow. The adhesives and primers applied with tape coatings can also be used as a source of nutrients, supporting microbial growth and causing deterioration of the coating (Jack et al., 1996). However, when holes and tears aren't present polyethylene coatings generally perform well, having a three-layer coating system (Kocks, 2008), particularly when used in conjunction with electrical cathodic protection. The advantages and disadvantages of other types of coatings are summarised by Javaherdashti and Vimpani (2003). The iron oxide layers that form as carbon steel corrodes in the presence of oxygen slows oxygen diffusion from the environment to the metal surface (Sancy et al., 2010) and alters the dynamics of corrosion reactions (Stratmann and Muller, 1994; Sherar et al., 2013). At locations where thick metal oxide layers adhere to the steel surface, oxygen reduction occurs within the layer rather than at the metal surface (Stratmann and Muller, 1994). At these locations reduction rates are accelerated when compared to clean steel (Evans and Taylor, 1972; Cole and Marney, 2012), thereby increasing the corrosion rates of the steel (Cornell and Schwertmann, 2004). The presence of metal oxides on surfaces increases microbial adhesion due to their charge, surface roughness and hydrophobicity (Li and Logan, 2004), and as a consequence tubercle formation may be increased as microorganisms colonise and precipitate more metals. Corrosion products on the external surfaces of buried cast iron water pipes have been reported to increase the corrosion rate by 10 times under laboratory conditions, as determined using electrochemical measurements, compared to internal surfaces (Sancy et al., 2010). The type of corrosion products formed on carbon steel depends on temperature, pH and the concentration Fe2þ, chlorides, carbonates, oxygen and sulphate ions in the environment (Cornell and Schwertmann, 2004; Neff et al., 2005). Iron oxyhydroxides, goethite (a-FeOOH), akaganeite (b-FeOOH), magnetite/maghemite and lepidocrocite (g-FeOOH) are frequently found as corrosion products (Johnston et al., 1978; Neff et al., 2005), with the latter also transforming to goethite, and at pH > 7 and with high concentrations of Fe2þ, to magnetite (Fe3O4) (Cornell and Schwertmann, 2004). Under certain conditions siderite (FeCO3) and other carbonates and chlorides develop (Neff et al., 2005). Silicates and organic carbon slow the transformation of iron oxides such as ferrihydrite to goethite (Tuhela et al., 1997). In anaerobic environments conductive phases such as magnetite (Cole and Marney, 2012), mackinawite (FeS), pyrite (FeS2) and greigite (Fe3S4) can form (see below under “Sulphate reducing bacteria”), with thick flaky layers accelerating corrosion (Videla et al., 1999) by the formation of galvanic cells (Jack et al., 1996). Sherar et al. (2011) reported that the morphology of corrosion products is dependent on the level of nutrients available to the biofilms on steel. However, thin adherent layers of iron sulphides can protect carbon steel. Pitting and uniform corrosion may be caused by different mechanisms (Baird, 2011; Cole and Marney, 2012), and similar soils in different areas can have different corrosion rates (Fitzgerald,

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1989). Water distribution pipes (carbon steel and ductile iron) can have different rates of failure within a single segment of pipe where sand has been used as backfill. Some of this unpredictability has been attributed to imperfections in the metal and/or protective coating, as well as random soil chemistry variations; however, they may be caused by microorganisms, as soil harbours a wide range of species with high levels of genetic and functional diversity at very small scales (Nunan et al., 2003). Unfortunately, the large number of variables makes it difficult to determine direct causes and to evaluate possible interactions (Ferreira et al., 2007; Javaherdashti, 2008). Some metals such as stainless steel, titanium and aluminium form thin oxidised layers on the surface that passivate the metal and reduce corrosion rates. These are used in preference to carbon steel in applications where their higher corrosion resistance justifies their higher cost, however, even stainless steel often requires a coating to resist corrosion in soil (Cunat, 2002). 2.3. Microbiological factors Soil holds the most biodiversity on Earth (Hinsinger et al., 2009), and the largest populations of microorganisms in any habitat (Whitman et al., 1998; Hinsinger et al., 2009). A gram of soil may contain 1010 bacteria (not considering other microorganisms), consisting of over 4000 species (Torsvik et al., 1990; Hinsinger et al., 2009), and over 1 km of fungal hyphae (Young and Ritz, 2005). However, with only a few basic microbial shapes, visually there appears to be limited morphological diversity. Natural biofilms are composed of an immense variety of microorganisms including bacteria, fungi, archaea and eukaryotes. The metabolic abilities of microorganisms are also diverse, and the various impacts of bacteria alone may exceed that of multi-cellular organisms (Torsvik et al., 1996). There are many factors that affect the diversity and distribution of microbial species in a region, including biotic and abiotic factors such as ecosystem type, soil pH, nutrient levels, available oxygen, light levels and temperature (Fierer and Jackson, 2006). MIC microorganisms may be dispersed in the soil or attached to steel. Bacteria are the most studied of the MIC microorganisms. They form biofilms over soil particles (McLean et al., 2002) and on other moist surfaces, bound together by EPS. Steel and mineral surfaces are attractive for bacterial colonisation because they adsorb organic compounds that can be utilised by the microorganisms (Costerton et al., 1995; Landoulsi et al., 2011). Different researchers categorise the mechanisms of MIC in various ways, with many referring to “direct” and “indirect” mechanisms. “Direct” mechanisms are specific biochemical mechanisms, such as catalysing oxidation, that affect the fate of metals, while “indirect” mechanisms affect corrosion rates via more general microbial activities such as the binding of metals (Gadd, 2010). Gu (2012) defines three types of biocorrosion, two of which relate to steel. Type I is the removal of electrons from steel by electrogenic microorganisms via electron carriers or conductive pili (nanowires). Type II corrosion is caused by fermentative microorganisms that release organic acid byproducts that “accidently” oxidise steel, but which do not have a catalytic function (Xu et al., 2013). These microorganisms are typically heterotrophic (require organic carbon). Type III includes the degradation of organic materials such as polyurethane by heterotrophs (Gu, 2012). The mechanisms of MIC are discussed in detail below. It should also be emphasised that many microorganisms are motile and move towards energy sources and away from toxins (chemotaxis). In the context of MIC this means that, for example, soluble Fe2þ released from a corroding pipe can attract iron oxidising microbes to it. Fungi have networks of rapidly growing

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filaments that are directed towards food in a similar manner to the roots of plants, and also produce motile spores. However, in soil there may be only a few layers of water molecules over surfaces, restricting swimming, so bacteria move by other methods including gliding and twitching (Spormann, 1999). Some can glide at such speeds that their movements are readily observed under a microscope, and cells can be coordinated so that a swarm of bacteria move together to an energy source (Spormann, 1999). Once established, microorganisms significantly modify their local environment. Biofilms are composed primarily of water, and can therefore act as an electrolyte (Beech and Coutinho, 2003) while also affecting the speciation and precipitation of metals (McLean et al., 2002), and altering electrochemical reactions in ways that may either promote (Mansfeld and Little, 1991; Beech and Sunner, 2007), or reduce corrosion (Videla, 2011). 2.3.1. Extracellular polymeric substances (EPS) Biofilms consist of microorganisms held together with excreted slime, referred to as extracellular polymeric substances (EPS). EPS is composed of sticky, high molecular weight compounds (Bhaskar and Bhosle, 2006) and is abundantly produced by many microorganisms, rapidly coating the surface of steel in natural environments. This is illustrated in Fig. 1, in which cryo SEM was used to image the EPS on steel that had been buried in soil for 3 days. The negatively charged uronic acids, amino acids and nucleotides that are present in EPS can bind multivalent cations (Beech and Cheung, 1995; Beech and Gaylarde, 1999), leading to precipitation, chelation, adsorption, and complexation of metal ions, as well as changes in pH and Eh of the local environment. In addition, enzymes bound to cells or in the EPS can cause a number of reactions including oxidation and reduction, ion exchange along with methylation and demethylation (Francis, 1998; McLean et al., 2002; Hullebusch et al., 2004). Consequently, EPS is thought to be important in MIC and alterations in the percentage of protein, including enzymes, may affect corrosion rates. The composition of EPS, particularly the types of proteins/enzymes present, can also be affected by the presence of carbon steel (Zinkevich et al., 1996). Redox transformations and metal binding are important mechanisms of microbial resistance as all metals can be toxic above certain threshold levels (Gadd, 2010), with microbial species differing in their susceptibility (Gadd, 2010). Capsules around bacteria are also involved in precipitating metals and in detoxifying the environment (Ghiorse, 1984), with the presence of metals inducing capsule formation (McLean et al., 2002). 2.3.2. Microbes and soil characteristics Soil pH has an important effect on microbial diversity, with neutral soil harbouring the most diverse communities and acidic soil the least diverse (Fierer and Jackson, 2006). The particle sizes from which soil is composed are also an important characteristic that impacts on the corrosion rates of buried pipes, as particle sizes affect oxygen diffusion, solute transport and water holding ability (Cole and Marney, 2012). These variables also affect soil microbiology, controlling microbial numbers, distribution and diversity. For example, clay soils are composed of very fine particles that restrict oxygen and water diffusion (Chenu and Stotzky, 2002), alter levels of microbial predation (England et al., 1993) and lower the availability of growth substrates due to sorption (Jones and Edwards, 1998). Because oxygen diffusion is restricted in clay soils they may facilitate the growth of anaerobic microorganisms such as sulphate reducing bacteria, known to be involved in MIC (Doyle et al., 2003). However, a large percentage of clay soil may not be available for colonisation, as the majority of pores (spaces between particles) in clays are typically smaller than 10 nm (Sills et al., 1974), thereby excluding microorganisms.

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Fig. 1. Cryo SEM of microorganisms (black arrow) on a mild steel surface after 3 days in soil. Secreted extracellular polymeric substances (white arrow) surround them. (A) Scale bar ¼ 1 mm. (B) Scale bar ¼ 1 mm. Original image by K.M. Usher.

High levels of spatial and temporal heterogeneity in the distribution of bacterial species in soil have been reported from one location (Wang et al., 2011). In the subsoil bacteria are found clustered together around pores with few growing between pores (Nunan et al., 2003). Many bacteria produce antibiotics that inhibit competitors, creating boundaries between colonies in the soil (Torsvik et al., 1996). Soil microbiology and chemistry is further complicated by regions deep within soils that contain oxygen, introduced by animal burrows, such as worms, and in some cases by the roots of plants (Wang et al., 2011). Plant roots also exude organic substrates that increase microbial growth (Lynch and Whipps, 1990; Torsvik et al., 1996). With this level of complexity it is not surprising that our understanding of microbial distributions in soil is poor (Fierer and Jackson, 2006). 2.3.3. Biofilm growth Single microbial species have distinctly different physiological stages during biofilm formation, including attachment, maturation and dispersion, and their metabolism and protein output change at each stage (Sauer et al., 2002). This means that the impact of a species on the local environment, including impacts on steel, will change depending on the growth phase, and many bacteria in soil may be in a resting stage and not actively metabolising (Torsvik et al., 1996). The changing protein and enzyme profiles over time (Sauer et al., 2002) may lead to a lack of reproducibility of results even when using otherwise identical experimental conditions (Sommer et al., 1998), so growth phase should be considered when designed MIC experiments. Within a biofilm, microbial metabolisms depend on the position of cells in the biofilm matrix and the physical and chemical environment (Southey-Pillig et al., 2005; Stewart and Franklin, 2008). Oxygen, nutrients, waste products and other secreted products vary in concentration within biofilms, and affect the gene expression of microorganisms (Stewart and Franklin, 2008). The risk of MIC may be more directly related to the metabolic state and rate than the number of microbial cells or the presence of specific microbial species (Beech and Sunner, 2007). 3. Microbially influenced corrosion (MIC) It is important to understand that MIC is fundamentally different from abiotic corrosion because microbial cells and ecosystems depend on the inputs of energy from external sources, and no part of the process at any level is ever in thermodynamic equilibrium (Hamilton, 2003). This has significant implications for the design and interpretation of MIC experiments, because when examining community structure, metabolic states or enzymatic

reactions there are no actual steady states. Each result is a snapshot of a continually changing process, and there is never a single “reaction rate” that can be applied accurately across time and space; however, influences on reaction rates such as temperature can be studied. For example, enzymes with MIC activity that are secreted by bacteria can change significantly depending on the growth phase and levels of aeration (Busalmen et al., 2002). Nonetheless, there are a number of tools that can be applied in order to understand MIC. Despite knowledge of microbial processes that increase corrosion rates, details of how microorganisms interact with steel surfaces are not fully understood (Little et al., 2000; Jeffrey and Melchers, 2003; Mehanna et al., 2009). This is because of the large number of independent variables in natural systems (Javaherdashti, 2009) such as different energy sources, competing reactions (between inorganic and organic compounds and reduced and oxidised ions), and microorganisms altering metabolic pathways (Little et al., 2000). For example, mineral colloids in soil bind microbial enzymes and can substantially alter their performance (Huang et al., 2008), potentially changing their impact on steel. 3.1. Pure cultures vs mixed species To reduce the number of variables, fundamental MIC research is typically conducted on single species under simplified and controlled conditions in laboratories. However, natural communities affect electrochemical processes in ways that single species can't (Beech and Coutinho, 2003). Microorganisms release a variety of compounds to communicate with each other (quorum sensing: for review see Ng and Bassler, 2009; Teplitski et al., 2011) and alter their metabolisms in response to other bacteria in biofilms. This, combined with synergistic and competing metabolisms, results in natural biofilms functioning in ways that are not observed in species grown as monocultures (Little et al., 1991; Beech and Gaylarde, 1999). For example, Valencia-Cantero et al. (2003) demonstrated that the corrosion rates of carbon steel were significantly higher when cultured with a mix of bacterial isolates from a hot spring compared to corrosion rates from the same strains grown as pure cultures. Similar results were obtained by Pitonzo et al. (2004), who found higher corrosion rates of carbon steel from mixed communities compared to the same isolates separately. In addition, many anaerobic microbial communities transfer electrons between species (interspecies electron transfer) via redox chemicals, direct contact, nanowires (see below) or through conductive minerals such as magnetite (Kato et al., 2012). In this manner organic compounds such as acetate can be oxidised by one species with another species of microbe accepting the electrons

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and using them for nitrate reduction (Kato et al., 2012). Each species performs a half reaction (for energy generation) with naturally occurring conductive minerals such as magnetite and pyrite transferring electric currents between them, forming cooperative behaviours and communities (Kato et al., 2012). Hydrogen, formate, cysteine and possibly sulphur compounds can also act as electron shuttles to transfer electrons between species (Stams et al., 2006). Perhaps because of this inter-related functioning of natural communities, only 0.1e1% of bacteria in soil can be successfully grown as pure cultures (Torsvik et al., 1996). This must be remembered when research is conducted on single species and the results treated with caution, as the species are likely to behave significantly differently in the natural environment.

other microorganisms present in biofilms, such as diatoms (a eukaryote found in soils), also increase corrosion rates (Landoulsi et al., 2011). Although there have been reports of bacteria protecting steel via the formation of protective corrosion products (see Section 3.2.1), or the binding of oxygen to by-products of metabolism, the results were generally produced using pure cultures (or sometimes two species), and in real world environments where diverse microbial communities occur the protective effect may be reversed to a corrosive action (Dubiel et al., 2002). In natural environments corrosion is due to multiple species and mechanisms e in nature, no single microorganism or mechanism has been shown to be responsible for MIC (Beech and Sunner, 2007; Vukovic et al., 2009).

3.2. MIC mechanisms

3.2.1. Galvanic cells All microbial materials, such as EPS, capsules and cell walls, can adsorb metals, including those produced by fungi, cyanobacteria, algae and bacteria (Gadd, 2010). Sorption of metals to cells is likely to be important in all microbe-metal interactions (Barkay and Schaefer, 2001), and can lead to the formation of galvanic cells on steel surfaces (Fig. 2C, D). In addition to EPS, bacterial cell walls are chemically active and can efficiently precipitate and adsorb a variety of dissolved metal ions (Beveridge et al., 1983; McLean et al., 2002), assisted by a large surface area to volume ratio and high surface charge density (Langley and Beveridge, 1999). Work by Langley et al. (Langley and Beveridge, 1999) demonstrated that preferential deposition of copper, iron and lanthanum on cell walls occurs when biofilms

The diversity of microorganisms and their metabolic functions is enormous (Lee et al., 1995), and they affect metals in many ways (Fig. 2). The major mechanisms have been summarised as acid attack, fixing anodic sites, formation of differential aeration or chemical concentration cells and cathodic depolarisation (Javaherdashti and Vimpani, 2003), and to this should be added direct extraction and consumption of electrons from Fe0 in steel. It is has been recognised that bacteria play a significant role in the speciation and fate of metals (Lovley et al., 2006), dissolving minerals, transforming metals and causing mineral formation (Beveridge et al., 1983; McLean et al., 2002; Gadd, 2010). However, although MIC research has largely focused on the role of bacteria,

Fig. 2. Simplified schematic of some of the mechanisms by which microorganisms impact on buried mild steel pipes. (A) Anaerobic methanogens and sulphate reducing microorganisms extract electrons directly out of steel, producing Fe2þ. (B) Anaerobic iron oxidising microorganisms that utilise nitrate as an electron acceptor oxidise Fe2þ and produce Fe3þ which precipitates as iron oxides. (C) Anaerobic heterotrophic microorganisms reduce insoluble Fe3þ oxides, producing Fe2þ. (D) Anaerobic sulphate reducing microorganisms reduce sulphates, utilising them as terminal electron acceptors. They produce OH, PH3, H2S, FeS precipitates that can increase corrosion rates. Connecting lines indicate nanowires. (E) Heterotrophic microorganisms produce organic acids and enzymes that attack steel. They also consume oxygen, creating an oxygen gradient within biofilms with anoxic regions at the bottom, and recycle nutrients for other microorganisms. (F) Sulphur oxidising microorganisms produce sulphuric acid. (G) Neutrophilic iron oxidising bacteria with precipitated iron oxides forming a mat create differential aeration cells and galvanic cells. (H) Diatoms and cyanobacteria produce oxygen in the surface of soil, creating differential aeration cells and forming H2O2. Some plant roots release oxygen deeper in soil. (I) Other microorganisms. (J) Hydrogen peroxide produced by aerobic soil microorganisms attacks steel. This figure summarises mechanisms previously published in the following references: 3, 16, 17, 23, 38, 57, 59, 62, 65, 103, 108, 111, 112, 118, 121, 124, 125.

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were immersed in solution containing salts of these metals. The extent of metal binding and precipitation was affected both by the mode of growth of the biofilm and the surface reactivity, with metal binding being promoted by hydrophobic films. The formation of metal rich phases in the biofilm close to the metal substrate can induce a galvanic cell between the substrate and the biofilm. Metals adsorbed onto cells also alter the conductivity of low frequency currents (Konhauser, 2007). Bacteria that accumulate iron and manganese oxides on their surfaces are ubiquitous (Ghiorse, 1984) and include both Gramnegative and Gram-positive bacteria (Macrae and Edwards, 1972). These two groups have significantly different cell wall structures, but both contain free carboxyl and phosphoryl groups that bind metals. Beveridge and Fyfe (1985) found that the isolated cell walls of Gram-positive bacteria have greater metal binding capacity than Gram-negative cell walls, however, this finding was not supported when whole cells were used (Mullen et al., 1989). Many of the Fe and Mn depositing bacteria form large quantities of metalencrusted sheaths and stalks, and can occur as relatively large encrusted masses of cells in soil (Ghiorse, 1984). Figs. 3 and 4 illustrate extensive of iron encrustation on the stalks of microbial cells which can lead to the formation of galvanic cells on steel surfaces. As with bacterial metabolisms, bacterial cell walls are heterogeneous and can change composition in response to changing environmental conditions. The cell wall of a single bacterium can contain several lipopolysaccharides with different charges (Langley and Beveridge, 1999), and the continually changing composition of cell walls makes modelling of metal binding capacity difficult (McLean et al., 2002). For example, metal binding capacity can significantly increase when planktonic cells form biofilms because of alterations in cell wall composition (McLean et al., 2002) and localised pH, redox potential and solute concentrations created by biofilms (Barkay and Schaefer, 2001). The multiple mechanisms and interactions involved in the sorption of metal ions to live bacterial cells is not well understood, and even less is known about the transformation of metals and metal binding by archaea and fungi (Barkay and Schaefer, 2001). In addition to creating galvanic cells the binding of Fe from solution should lower its concentration (Banfield et al., 1999) around steel, which may cause increased corrosion reaction rates. Metal ions bound in EPS may also transfer electrons from Fe0 in steel to

Fig. 3. SEM of a clump of iron oxidising bacteria encrusted with iron oxides. Scale bar ¼ 1 mm. Original image by K.M. Usher.

oxygen (or another electron acceptor), accelerating corrosion (Beech and Sunner, 2004). Different bacterial species are associated with different metal precipitates (Emerson et al., 2010), which may be crystalline or amorphic. The diversity of bacterial cell walls, capsules, and EPS in natural biofilms creates a variety of charges, increasing the range of metals that can be bound and the total metal binding capacity (McLean et al., 2002). The minerals that are formed by microbial precipitation include metal sulphides (Beveridge et al., 1983) and iron and manganese oxides that can support cathodic reactions (hydrogen and oxygen reduction respectively). Thus, if such minerals are within the vicinity of anodic sites on the metal surfaces they can establish electrochemical cells, shifting the corrosion potential in a positive or negative direction, and moving the corrosion potential towards the pitting potential. Or, in the case of sulphides, moving the corrosion potential in a negative, more active direction (Little et al., 1998), and increasing corrosion rates (Lee and Characklis, 1993; McLean et al., 2002; Javaherdashti, 2008). Magnetite is commonly produced by anaerobic microorganisms (Konhauser, 1997). It is a semi-conductive precipitate, that can act as an electron acceptor (Zegeye et al., 2007), creating galvanic couples on carbon steel and causing galvanic corrosion (Chan, 2011). However, in laboratory settings iron carbonate scale can be protective (Chan, 2011), as can mackinawite, an iron nickel sulphide mineral (Gu, 2012). 3.2.2. Differential aeration Pitting corrosion is typical of MIC of carbon steels (Hardy and Brown, 1984; Li et al., 2001), and is considered the most severe type of corrosion (Velazquez et al., 2009). Pitting of steel has been observed to occur in regions covered by dense biofilms and not in neighbouring regions of scattered microbial attachment (Mehanna et al., 2009), suggesting the presence of biofilms is important for pit formation. For buried steel pipes corrosion is thought to be increased by differential aeration cells over short distances (Ferguson and Nicholas, 1992). The deposits and solid tubercles formed by MIC reduce oxygen diffusion to metal surfaces, enhancing corrosion by differential aeration (Kajiyama and Koyama, 1997; Rao et al., 2000; Videla and Herrera, 2004). However, differential aeration can also occur due to restricted oxygen diffusion through the biofilm itself (Little et al., 1991), assisted by the consumption of oxygen during bacterial respiration (Little et al., 1991; Stewart and Franklin, 2008). Fig. 1 illustrates the extent of EPS secreted by microbes, which covers the carbon steel surface, potentially limiting oxygen diffusion. Low oxygen regions underneath biofilms and deposits becomes anodic (Fig. 2G), while clean steel acts as a cathode, creating a flow of electrons towards the cathode and an aggressive form of corrosion (Gu, 2009). Anoxic regions can form with oxygen in close proximity, as oxygen may be introduced by animal burrows or released by ubiquitous photosynthetic microorganisms such as cyanobacteria and diatoms, where sufficient light is available (Fig. 2H, I). The depth to which light penetrates varies with soil type. Where differential aeration cells have formed, killing biofilms may not stop corrosion as the products of microbial metabolism may be the cause (Kuang et al., 2007). 3.2.3. Acidity In addition to causing differential aeration at the metal surface, EPS and other products of biofilms can increase corrosion rates by changing the local pH via hydrogen permeation (Biezma, 2001). Acid attack is an important cause of corrosion (Gu, 2009), with drops in pH associated with an increase in Fe release to solution (Barker et al., 1998). Acidity caused by microbes is an important cause of localised corrosion (Campaignolle, 1997; Rajasekar et al.,

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Fig. 4. (A) SEM of clumps of iron oxidising bacteria. (B) SEM EDS element map of iron encrustation on the bacteria, showing the same area as A. Bright areas indicate iron. Original image by K.M. Usher.

2010) (Fig. 2E, F), and even in aerobic environments the inner regions of biofilms become acidified due to low oxygen availability when carbon dioxide (CO2) from respiration or degradation of organic matter combines with water to form carbonic acid (Suflita et al., 2008). In addition, microorganisms produce a wide range of organic acid metabolites to obtain essential nutrients, and some, including oxalic, isocitric, citric, succinic, hydrobenzoic and coumaric acids that are produced by heterotrophic microorganisms (those requiring organic carbon for growth) are able to increase the solubilisation of metals from minerals (Francis, 1998). Organic acids can increase the mineral dissolution rate by 2e4 times compared to rainwater (Kurek, 2002), however, other than the effects of acidity, it is not clear how the different metabolites influence corrosion rates of steel. Fulvic (small molecular weight), and humic acids (high molecular weight) along with hydrogen ions (Hþ) released by microbes acidify the local environment; similarly fungi also play an important role in soil acidification (Gadd, 2010). Barker et al. (1998) found that pH decreased to between 3 and 4 near bacterial colonies growing inside cracks in a mineral, when solution pH was about 7, and pH values less than 3 were observed in a biofilm on corroding metal in a marine environment (Barker et al., 1998). Some sulphate reducing bacteria (SRB) and methanogens (methane-producing microorganisms) utilise hydrogen as an electron donor, so their growth and the subsequent corrosion caused by them may be increased by the presence of heterotrophs that increase hydrogen concentrations (Boopathy and Daniels, 1991). 3.2.4. Volatile compounds and enzymes Bacteria also produce a range of compounds such as ammonia (NH3), phosphine (PH3), hydrogen sulphide (H2S) (Fig. 2D), hydrogen peroxide (Fig. 2J) and enzymes that can attack metals (Fig. 2E). Hydrogen peroxide (H2O2) is a powerful oxidising agent that is secreted by aerobic soil microorganisms (Li et al., 2012). It can be stabilised by soil compounds and transported into the subsurface while retaining its reactivity (Watts et al., 2007), where it can potentially impact on steel. Some enzymes catalyse cathodic reactions (Beech et al., 2002), and can potentially facilitate oxygen reduction reactions, increasing corrosion rates (Beech et al., 2005). Enzymes secreted by microorganisms include hydrogenases, oxidoreductases (Beech and Gaylarde, 1999; Little et al., 2000; Busalmen et al., 2002; Lens et al., 2003; Beech and Sunner, 2007), lyases, catalases, phosphatases and esterases, however, their effects on corrosion rates is not well understood (Beech et al., 2005). A range of hydrogenases with Fe-active sites are made by microorganisms and can catalyse the oxidation of H2 and/or the reduction of Hþ. They

may increase corrosion by transferring electrons from steel (Da Silva et al., 2002; Gu, 2012), and possibly also by cathodic depolarisation (removal of hydrogen) (Beech and Coutinho, 2003), although the later mechanism is now largely discredited. While some enzymes are associated with the cell wall, others are found free in the EPS (Beech et al., 2005), where a wide range of enzyme activities have been reported. Enzymes can remain active in biofilms after the death of cells, contributing to corrosion (Beech et al., 2005). Some biofilm proteins enhance oxygen reduction and are electrically active, increasing the potential for corrosion (Busalmen et al., 2002; Landoulsi et al., 2008; Erable et al., 2010), and EPS can increase mineral dissolution by several orders of magnitude (Barker et al., 1998). A number of bacteria use metal ions or oxides as electron donors or acceptors, and cytochromes (proteins) in their cell walls facilitate this process (Gu, 2012), allowing them to utilise the flow of electrons for energy (Fig. 2A, B). This is discussed further below. 3.2.5. Nanowires Until recently it was thought that bacteria needed soluble electron donors or acceptors, or contact with metals or conductive metal-based compounds, to catalyse the chemical reactions from which they derive energy. However, some metal reducing and metal oxidising bacteria have recently been shown to have electrically conductive appendages, referred to as nanowires, that can exchange electrons directly with conductive metal-based compounds (Erable et al., 2010; Gu, 2012; Lovley, 2012). These conductive filaments, or pili, are made from proteins and can transfer electrons from cells to Fe3þ-bearing iron oxides (or other electron acceptors) that are a significant distance away (up to 10 mm, or 10 000 further than the size of a typical microbe) (Malvankar et al., 2011), reducing them (Gorby et al., 2006). Geobacter sulfurreducens, a metal reducing bacterium, has the highest conductivity known to date (Leang et al., 2013). Nanowires may be a common bacterial strategy for efficient energy extraction and distribution (Fig. 2B), and it has been suggested that they may create bridges between cells and distribute electrons between taxonomically diverse microorganisms in natural environments (Gorby et al., 2006; Lovley, 2012). Evidence supporting this has emerged recently, showing that Geobacter donate electrons via nanowires to Methanosaeta, an archaea (Rotaru et al., 2014). This research has generated widespread interest and is opening up new research fields including sustainable energy generation, biosensors and bioremediation (Erable et al., 2010). Further research into nanowires and the interactions amongst microorganisms in natural communities is necessary to understand biofilm functioning (Gorby et al., 2006), and

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biocorrosion and bioleaching are clearly research areas that would benefit from this research. However, not all pili are conductive (Lovley, 2012; Vargas et al., 2013), and although nanowire-like structures are often reported on electron microscopy images, many may not be conductive.

and may cycle iron locally (Emerson and Revsbech, 1994; Sobolev and Roden, 2001). Bacterial communities may recycle a number of energy sources (Brown et al., 1994; Hamilton, 2003), and some may be dependent on the presence of other species for their survival (Ghiorse, 1984).

3.2.6. Direct consumption of electrons from steel The mechanism by which anaerobic microorganisms such as some sulphate reducing bacteria (SRB) and methanogens significantly increase corrosion rates has been controversial. In addition to the corrosive properties of their metabolic end products, it was thought that corrosion was increased via the use of chemically formed H2 as an electron donor by these microbes, causing cathodic depolarisation (Venzlaff et al., 2013). However, recent research has now convincingly demonstrated that microbial consumption of H2 on its own does not significantly increase corrosion rates (Mori et al., 2010; Enning et al., 2012; Venzlaff et al., 2013). Instead, highly corrosive SRB and methanogens utilise electrons directly from steel for energy, by oxidising Fe0 to Fe2þ (Dinh et al., 2004; Uchiyama et al., 2010; Enning et al., 2012; Venzlaff et al., 2013) (Fig. 2A). This has been referred to as “electrical microbially influenced corrosion” (EMIC) (Enning et al., 2012). The mechanism by which microorganisms take up electrons from solid phase materials is poorly understood (Rosenbaum et al., 2011; Bose et al., 2013), but this capability has been utilised in microbial fuel cells for some time (Lovley, 2008; Rosenbaum et al., 2011). The mechanism by which corrosion rates are increased by EMIC microorganisms has also not been confirmed, and may vary with species. Mori et al. (2010) suggested that an enzyme, most likely a hydrogenase, secreted by Methanococcus maripaludis may catalyse the oxidation of metallic iron, while Venzlaff et al. (2013) suggested that the consumption of electrons by EMIC microorganisms may drive the cathodic reaction. Although earlier studies showed that some microorganisms grew with Fe0 as the electron donor, the authors assumed that the microorganisms could only grow by utilising the H2 produced by corrosion (i.e. indirect electron uptake) (Daniels et al., 1987; Belay and Daniels, 1990), rather than directly consuming electrons. The implications of direct consumption of electrons from steel are important, including higher rates of corrosion and the requirement for microorganisms to be attached to the steel, or to a conductive crust on the steel (Enning et al., 2012). Nanowires may also play a role in transferring electrons from steel to microorganisms.

3.3.1. Sulphate reducing bacteria (SRB) Sulphate reducing bacteria (SRB) are most well-known and studied bacteria associated with high corrosion rates. Some archaea also reduce sulphate and for convenience are included as SRB. Many of these bacteria and archaea can also reduce other oxidised inorganic sulphur compounds, including elemental sulphur, utilising these as a terminal electron acceptors. This is a diverse group of autotrophic and heterotrophic microorganisms that are ubiquitous in soils, with the majority growing anaerobically. The heterotrophs use organic matter as a carbon source. Some SRB form spores which can remain dormant and viable even in aerobic soils (Rabenhorst and James, 1992), and SRB are commonly isolated from biofilms in aerated environments (Beech and Coutinho, 2003). SRB can readily take advantage of anaerobic regions created by aerobic biofilms, with serious consequences for buried steel (discussed below). Studies investigating the corrosion mechanisms of SRB typically use single species, but, as discussed earlier, the interactions of microorganisms with metal vary depending on the environment and products formed by the actions of communities (Vukovic et al., 2009). Li et al. (2001) reported corrosion rates more than 20 times higher in anaerobic soil when SRB were present, compared to abiotic controls. However, the relative contributions of the different mechanisms by which SRB corrode steel (described below) remains controversial (Yuan et al., 2013), and probably varies depending on the species of SRB present (Enning and Garrelfs, 2013). In dissimilatory reduction of sulphate by SRB H2S is formed and excreted from the cells (Lee et al., 1995; de Romero et al., 2005). H2S rapidly oxidises metallic iron to form iron sulphide, as per the net equation: H2S þ Fe0 / FeS þ H2 (Dinh et al., 2004; Sun and Nesic, 2007; Enning and Garrelfs, 2013). H2S is slightly soluble in water, forming HS (hydrosulfuric acid), and the proportion of dissolved sulphide is thought to be an important factor influencing the corrosion rate of carbon steel (Dall'Agnol et al., 2013). The resulting formation of H2 from H2S also causes hydrogen penetration of steel and cracking corrosion, known as embrittlement (Biezma, 2001; Koh et al., 2004). SRB have been found associated with cracks (Jack et al., 1996), which can concentrate protons in the confined space (Barker et al., 1998). SRB also produce phosphine (King and Miller, 1971; Glindemann et al., 1998), which causes aggressive chemical corrosion. A variety of microorganisms, including soil bacteria, mediate the reduction of phosphate (PO3 4 ) to phosphine (PH3) (Roels and Verstaete, 2001). A number of iron sulphides are formed from H2S made by SRB, including mackinawite, greigite, pyrrhotite, marcasite and pyrite (Lee et al., 1995; Enning and Garrelfs, 2013). The formation of adherent and protective films of iron sulphide from can theoretically reduce corrosion rates (Sun and Nesic, 2007), however, their effects in real-world situations remains controversial (Gu, 2012). Some believe that in practice sulphide films are not effective at preventing corrosion (Little et al., 2000; Xu et al., 2011) as growth of the film causes cracking and the formation of loose, porous films (Sun and Nesic, 2007; AlAbbas et al., 2013). Indeed, Bourdoiseau et al. (2010) found that in the continued presence of SRB FeS films transform to greigite or pyrite (FeS2) which readily flakes from the steel surface, breaking the protective film and allowing high corrosion rates to be re-established. Jack et al. (1996) suggested that cathodic protection may fail in the presence of iron sulphides, as the iron sulphides are protected

3.3. MIC microorganisms Many microorganisms are thought to be involved in MIC, including eukaryotes such as fungi, algae and diatoms, and microorganisms belonging to the domains archaea and bacteria. Archaea resemble bacteria, but they share many genes with eukaryotes. To date, bacteria have been the subject of the vast majority of the research on MIC. Within bacteria, the groups that are thought to have the greatest impact on corrosion are the sulphate-reducing bacteria (SRB), sulphur oxidising bacteria (SOB), iron oxidising/ reducing bacteria (IB), manganese-oxidising bacteria and bacteria that secrete organic acids or extracellular polymeric substances (Beech and Gaylarde, 1999; Little et al., 2000). In anaerobic regions of carbon steel where sulphate is present SRB are likely to dominate (Little et al., 1991) and be the major cause of corrosion. In nature these organisms are often found together in diverse communities, and as mentioned earlier, their cooperative metabolisms can lead to increased rates of corrosion (Jack et al., 1992; Beech and Gaylarde, 1999; Little et al., 2000). For example, a range of archaea and bacteria that are capable of reducing iron and others of oxidising iron are sometimes found in close association,

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instead of the pipe. A recent study also showed that an iron sulphide layer can adsorb corrosion inhibitors, rendering them less efficient (Sun et al., 2012). The galvanic cells created by iron sulphides (Vukovic et al., 2009) facilitate the transfer of electrons (Lee et al., 1995), with corrosion current densities of up to 3 mA/cm2 (mV vs SCE cathodic) and 3.5 mA/cm2 (mV vs SCE anodic) in high concentrations (>60 mg/L) of Fe2þ after three weeks (Lee et al., 1993; Little et al., 2000). However, iron sulphides require the action of SRB to maintain electrochemical activity (Li et al., 2001), with the composition, structure and conductivity of the corrosion products differing in the presence of SRB biofilms, compared to abiotic controls (AlAbbas et al., 2013). This may be because SRB use electrons from iron sulphides to reduce sulphates, maintaining the flow of electrons from steel (King and Miller, 1971; Jack et al., 1996; Vukovic et al., 2009), however, the process is not well understood and may occur via direct transfer of electrons, the formation of hydrogen or the dissociation of H2S (Jack, 2002). The most commonly found iron sulphides produced by MIC are mackinawite and greigite, and over time these may be transformed into marcasite and pyrite, which are highly corrosive (Jack et al., 1996). Mackinawite is not stable under natural environmental conditions, so it's presence may be an indicator of SRB (Vukovic et al., 2009). Some SRB are able to use ferric iron as an alternative electron acceptor (Park et al., 2011), and these may play an important role in soils (Burkhardt et al., 2011). In addition, it was proposed that SRB indirectly increase iron dissolution at the anode by the consumption of cathodic H2 (Lappin-Scott and Costerton, 1989; Little et al., 2000; Park et al., 2011), increasing cathodic depolarisation (Lee et al., 1995). However, the importance of this mechanism has been controversial (Dinh et al., 2004; de Romero et al., 2005; Uchiyama et al., 2010) (see Section 3.2.6), and recent studies have shown that some SRB and methanogens increase corrosion rates via the extraction and utilisation of electrons directly from Fe0 (Dinh et al., 2004; Venzlaff et al., 2013; Yu et al., 2013). Metal iron oxidation and consumption of electrons is probably a widespread microbial ability causing increased corrosion rates in a range of environments (Enning and Garrelfs, 2013), and may occur via outer membrane redox proteins (Dinh et al., 2004). It appears that consumption of H2 does not significantly increase corrosion rates (de Romero et al., 2005; Mori et al., 2010). 3.3.2. Sulphur oxidising microorganisms Sulphur oxidising bacteria and archaea oxidise elemental sulphur, H2S and mineral sulphides such as pyrite producing sulphate and corrosive sulphuric acid which increases acidity, hydrogen penetration and corrosion rates (Little et al., 2000). These microorganisms are phylogenetically diverse and may be aerobic or anaerobic, acidophilic (acid loving) or neutrophilic (live in neutral pH environments) (Friedrich et al., 2001). The presence of sulphur oxidising microorganisms may encourage the growth of SRB by producing the products necessary for their growth (e.g. sulphate), and “pods” containing an encapsulated consortia of syntrophic bacteria that regenerate their sulphur substrates (Norlund et al., 2009). 3.3.3. Metal oxidising and reducing microorganisms Metal oxidising and reducing microorganisms also contribute to MIC due to the effects of metal precipitates (Chamritski et al., 2004; Videla and Herrera, 2004) which accumulate on steel surfaces, and the dissolution of minerals, which release ions into the environment. Iron oxidising bacteria (IOB) and archaea can rapidly produce large amounts of iron oxide precipitates (Starosvetsky et al., 2001) and alter the acidity of their environment. Pits are initiated under

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iron oxide deposits on carbon steel (Starosvetsky et al., 2001), due to differential aeration cells (deposits are anodic sites, with the clean steel cathodic). Deposits can also create anaerobic regions that encourage the growth of SRB. The combined effects of IOB and SRB can cause greater corrosion rates than IOB alone (Xu et al., 2007). In addition, biologically produced Fe3þ may combine with Cl to form a highly corrosive iron chloride solution (Videla and Herrera, 2004; Javaherdashti, 2008) that can become concentrated under rust tubercles (clumps of corrosion products) (Tatnall, 1981). In the presence of water FeCl3 undergoes hydrolysis, producing Fe(OH)3, Cl and Hþ, and resulting in an acidic, corrosive solution. While some iron oxidisers gain energy from the process of oxidising iron, others may oxidise metals to detoxify their environment, or as a means to encapsulate themselves in minerals for protection from oxygen, UV (in sun-exposed situations such as seeps) or attack from other microorganisms (Ghiorse, 1984). Iron oxidisers often become heavily encrusted with iron precipitates in regions with high dissolved iron concentrations, forming thick iron oxide mats with vacated bacterial shells below the growth zone (Emerson and Revsbech, 1994; Emerson et al., 2010). Iron oxidisers typically utilise Fe2þ, however, nitrate reducing microorganisms have recently been implicated in catalysing the oxidation of Fe0 (Xu et al., 2013) (also, see Section 3.3.4). Because Fe2þ oxidises rapidly and abiotically at circumneutral pH, it is generally thought that aerobic iron oxidising bacteria and archaea require microaerobic environments to be able to utilise this energy source (Emerson et al., 2010), although this has been questioned (Sobolev and Roden, 2001). Emerson and Revsbech (1994) found neutrophilic iron oxidisers growing in regions where the oxygen concentration was 50% of air saturation, which is not considered to be microaerobic. A broad diversity of neutrophilic iron oxidisers belonging to the Proteobacteria, including Gallionella and Leptothrix, are widely distributed, living in anoxiceoxic transition zones (Emerson and Revsbech, 1994; Weber et al., 2006). Iron oxidising microorganisms that require low pH (less than pH 3; acidophilic) for growth also utilise energy from the flow of electrons when Fe2þ is oxidised to Fe3þ using a process mediated by a chain of membrane-bound cytochromes (Rohwerder et al., 2003). Although oxygen is usually the electron acceptor when iron is oxidised, some acidophilic iron 4þ oxidising microorganisms are also able to use Fe3þ, NO as 3 or Mn terminal electron acceptors in anoxic conditions. Redox couples used as electron carriers can sometimes transfer electrons from anoxic to aerated regions where oxygen acts as the terminal electron acceptor (Brown et al., 1994; Hamilton, 2003). Recently, neutrophilic anaerobic iron oxidising microorganisms that use NO 3 as an electron acceptor were discovered (Chaudhuri et al., 2001; Weber et al., 2001, 2006; Miot et al., 2009). These are capable of oxidising Fe2þ in insoluble minerals, as well as aqueous Fe2þ, and have been found in a variety of habitats (Weber et al., 2001). Unlike Fe2þ, Mn2þ does not oxidise abiotically at neutral pH, so microbial oxidation of dissolved Mn2þ can occur in aerobic environments. Manganese oxidisers are diverse, occurring in Grampositive bacteria, a-, b- and g-proteobacteria and fungi (Hamilton, 2003; Miyata et al., 2006). In addition, many iron oxidisers can also oxidise manganese. Oxygen or hydrogen peroxide are the terminal electron acceptors, and the oxidation product is Mn4þ which precipitates rapidly due to the low solubility of MnO2 (Hamilton, 2003). Mn oxides are some of the strongest naturally occurring oxidising agents in the environment (Landoulsi et al., 2008), acting as Lewis acids and accepting electrons (Huang et al., 2008) and participating in numerous redox and interfacial reactions (Hamilton, 2003). MnO2 is reduced to Mn2þ by accepting two

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electrons from metal dissolution (Gu et al., 2009). It promotes corrosion by the creation of differential aeration cells, oxidation of ferrous oxides, lowering the redox potential and increasing the corrosion potential above the pitting potential, leading to pitting corrosion (Dickinson and Lewandowski, 1996). Growth of Leptothrix discophora, an Mn oxidiser, ennobles stainless steel, increasing the open circuit potential to þ375 mV via the deposition of MnO2 (Gu, 2009). Other anaerobic microorganisms reduce insoluble Fe3þ and Mn4þ oxides, utilising them as respiratory terminal electron acceptors and organic carbon compounds or elemental sulphur as electron donors (Weber et al., 2006; Lovley et al., 2006). Metal reducing microorganisms may increase corrosion by altering minerals adhering to alloyed steel (Little et al., 1998), removing passivating layers (Videla et al., 2008) and by increasing the concentration of Fe2þ and ferrous sulphide formed by mixed communities (Obuekwe et al., 1981). However, their role in MIC has been controversial (Videla et al., 2008), with some reports of a protective effect using pure cultures (Dubiel et al., 2002). Many fermentative and sulphate reducing microorganisms have metal reducing capabilities as a result of metabolites such as formate and H2S, or the production of metal chelators including siderophores, oxalate, citrate, humic acids and tannins (Gadd, 2010). However, the mechanisms by which electrons are transferred is not well understood (Lovley et al., 2006). The activities of these microorganisms generate aqueous Fe2þ and Mn2þ and solid Fe2þ-bearing minerals such as magnetite, siderite and vivianite (Lovley et al., 2006), and mixed valence minerals (Weber et al., 2006). 3.3.4. Methanogens Many microorganisms release methane (CH4) as a by-product of metabolism (methanogenic), and methanogenic archaea are increasingly being found in association with MIC in anaerobic environments (Usher et al., 2014). Several studies have found high numbers of methanogenic archaea associated with pitting corrosion of steel pipes (Larsen et al., 2010; Park et al., 2011). Like SRB, methanogens often utilise H2 formed by the corrosion of steel (Boopathy and Daniels, 1991) and can cause and a significant increase in corrosion rate in anaerobic conditions (Daniels et al., 1987). However, some methanogens can also utilise Fe0 in carbon steel as an electron source, growing with metallic iron as the sole source of energy (Daniels et al., 1987; Uchiyama et al., 2010). Some of these microorganisms have been shown to corrode mild steel at a significant rate, increasing iron dissolution by almost 10 times and liberating Fe2þ (Uchiyama et al., 2010). They are probably phylogenetically diverse (Uchiyama et al., 2010) and may be important contributors to the corrosion of buried steel pipes (Daniels et al., 1987). It seems likely that in anaerobic environments in soil they co-exist with anaerobic iron oxidising microorganisms that use 2þ NO 3 as electron acceptors, as these efficiently remove toxic Fe from the vicinity as insoluble Fe3þ precipitates. Increasing pollution from NO 3 may therefore be directly responsible for observed increases in corrosion rates through the combined activities of these microorganisms. 3.3.5. Fungi Fungi are eukaryotic soil microorganisms that have extensive vegetative phase networks in soil called the mycelium. Mycelium release exudates including enzymes, glycoproteins and organic chelators such as oxalic and citric acids and siderophores (Leake et al., 2004). They grow in a wide pH range (Das et al., 2009) and are extremely resistant to drying, remaining active at moisture levels too low for bacteria, and also form desiccation-resistant spores (Little et al., 2001). Fungi are implicated in major mineral

weathering (Leake et al., 2004) and in MIC of carbon steel, including coated cables where they may be introduced as contaminants in non-sterile lubricants (Little et al., 2001). The localised corrosion and cracking that occurs in their presence is thought to be caused by the organic acids produced as they degrade hydrocarbons in lubricants (Little et al., 2001). Fungi consume oxygen, helping to create anaerobic sites for SRB, and some organic compounds they release can encourage the growth of SRB. They adsorb metals on their cell walls and EPS (Das et al., 2009), potentially creating galvanic cells on steel, and some can reduce ferric iron (Ottow and Von Klopotek, 1969) and sulphur (Das et al., 2009). However, fungi also produce a range of antibacterial compounds and some could, in theory, reduce bacterial numbers around steel. The potential of fungi to reduce corrosion in this way has not been studied. 3.3.6. Photosynthetic organisms A range of photosynthetic microorganisms occur in soil, including cyanobacteria and algae. The depth to which light penetrates soil depends on soil characteristics such as particle size (Benvenuti, 1995), and cyanobacteria have highly efficient photosynthetic apparatus and can photosynthesise in light levels at 1% of surface sunlight (Furnas and Crosbie, 1999). However, typically little light penetrates beyond 5 mm depth, so the impact of cyanobacteria on buried steel is likely to be limited. However, diatoms, a eukaryotic algae, are common in soils (Van de Vijver and Beyens, 1998), and although they are typically photosynthetic some can function in very low, or no light (Furnas and Crosbie, 1999; Landoulsi et al., 2011). Algae also adsorb metals on their cell walls and their EPS (Das et al., 2009), and so could create galvanic cells if in contact with steel. In addition, photosynthetically produced organic carbon can be a nutrient source for SRB (Das et al., 2009) and other heterotrophic MIC microbes. Where sufficient light is available for photosynthesis diatoms produce oxygen and H2O2, which have the potential to increase corrosion rates (Landoulsi et al., 2011). The root tips and young roots of plants adapted to growing in saturated, anoxic zones continuously release oxygen into the root zone, changing redox gradients from a typical 250 mV to þ500 mV at the root surface (Stottmeister et al., 2003). The quantity of oxygen released is dependent on the species of plant, its stage of growth, plant size, pH, redox potential and a number of other factors (Sorrell and Armstrong, 1994; Stottmeister et al., 2003). Plants that are capable of transporting oxygen into the root zone include some trees, and where roots of these species are in close proximity to steel buried in saturated soil there is the potential for differential aeration to occur, together with increased rates of corrosion. 4. Useful tools for MIC research Progress in understanding how soil microorganisms function as corrosion agents or promoters has been hampered by the difficulties of studying these communities in complex soil matrices without disturbing and destroying them, and most soil microbiology research is based on reductionist studies which have questionable relevance to corrosion in the real world (Leake et al., 2004). The presence of soil introduces a range of challenges for many analytical techniques (Table 1). 4.1. Genetic tools Genetic tools are used to determine the composition of microbial communities and have significantly advanced the field of environmental microbiology (Beveridge et al., 1996). They can be used to analyse extracted samples or microorganisms in situ within

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Table 1 MIC techniques. A summary of some of the most widely applied techniques from each discipline that have been applied in biofilm research and MIC studies, including their applications and limitations or advantages over related techniques. Unless referenced these represent the views of the authors. Method

Techniques

Application

Advantages

Limitations

Genomics

16S RNA sequencing

Identification

May not resolve closely related species

Database matching and phylogenetic trees DGGE, T-RFLP

Identification, evolutionary relationships Community fingerprinting

Determines which microbes are present Determines phylogeny of microbes

FISH

Spatial relationships of specific species Spatial organisation of microbes, pH gradients etc. Spatial relationships of microbes Spatial relationships of microbes

Microscopy

Fluorescent stains CLSM TPE

Spectroscopy

TEM

Imaging of cell structures in cross sections etc

SEM

Surface topography of samples and microbes Imaging of biofilm surface Analysis of all elements present, mapping of distribution Analysis of all elements present, mapping of distribution Analysis of specific elements, mapping of distribution

Epi-illumination LM SEM-EDS STEM-EDS EFTEM (TEM)

EELS (TEM) WDS (SEM) XRD

Metabolomics

Analysis of all elements present, oxidation state Analysis and mapping of specific element Bulk analysis of composition

Raman

Analysis of chemical bonding and composition

NMR

Biochemical composition

GCeMS, LCeMS

Biochemical composition

ESI, MALDI

Analysis of large biological molecules, good resolution Quantify and map elemental distributions Biochemical composition, element mapping Ionic species, redox, þ O2, NO 3 , NH4 , CO2, CH4 O2, pH, CO2, NH3, ionic species glucose, CH4, NO 3 , NO Uniform corrosion rates and mechanisms Uniform corrosion rates Pitting corrosion

LA-ICP-MS, LDPI-MS SIMS Microsensors

Electrochemical

Electrochemistry

Fibre-optic Biosensors EIS LPR EN

natural biofilms. In the past naturally occurring microorganism were isolated and cultured in the laboratory, then analysed to determine their identity and function. However, the current understanding of microbial community functioning has lead to a shift away from isolates towards total community analysis. This has been enabled by advances in genetic tools, and encouraged by the low success rate of isolating and culturing microorganisms from natural samples (Torsvik et al., 1996). Sampling for these techniques is simple, requiring the use of sterile tools and vials in which to place environmental samples quickly followed by storage at 80  C to prevent the degradation of DNA. This is typically followed by DNA extraction and polymerase chain reaction (PCR) to amplify the genes of interest. The most widely used DNA method is Sanger sequencing of the ribosomal RNA genes, which has been used to identify bacteria and

Separation of PCR products from species in mixed communities Determine how species interact with each other and with sample Sample preparation simple Ability to focus within biofilms Penetration of photons greater than CLSM Very high resolution imaging

High resolution imaging of biofilm surface No sample preparation High sensitivity surface analysis, distribution of elements Very high sensitivity, distribution of all elements Very high sensitivity, maps of element distribution within single microbes Very high sensitivity, element distribution and oxidation state High sensitivity surface analysis, no overlapping element peaks Determination of crystal structure and chemical composition Good for wet samples, portable models available. No sample preparation Detailed information on structure, useful for organic molecules

Sequence may not be on database May not resolve closely related species or highly complex communities Autofluorescence from soil components may interfere Autofluorescence from soil components may interfere Limited depth penetration Penetration limited in soil Samples typically require embedding and sectioning. Sectioning of microbes in soil matrix difficult. Microbes require serial dehydration and critical point drying to preserve structure Limited resolution Overlapping peaks for some elements, lower sensitivity for light elements Overlapping peaks for some elements. Ultra-thin specimens required (sectioning) Overlapping peaks for some elements. Ultra-thin specimens required (sectioning) Ultra-thin specimens required Time consuming, single element analysed at a time Not spatially resolved Resolution and sensitivity not high compared to EM Sensitivity not very high Many metabolites have low volatility, creating ionisation problems Experimental artefacts can occur with living biofilms

Can map living biofilms Identification of metabolites may be difficult Calibration may be difficult, cross reactions, consume reactant they measure Larger tip diameter, don't consume reactant Interpretation of results may be difficult Impacts on biofilm functioning Not suitable for MIC-type corrosion Data analysis can be complex and inconclusive

archaea in many different scientific fields (Lens et al., 2003). The 16S subunit is the most widely sequenced RNA prokaryote gene, but the 23S subunit can also be useful, and equivalent genes, the 18S and 28S, are used to identify eukaryotic microorganisms. Sequences are imported into the online database GenBank, which hosts publicly available DNA sequences, and allows comparisons to other microbial sequences using search tools such as Basic Local Alignment Search Tool (BLAST) to infer phylogenetic relationships. Phylogenetic trees can be constructed to obtain further information on the evolutionary relationships of the microorganisms. Sequences, combined with other techniques such as cloning, denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP), are used to follow changes in community composition over time. DGGE has been widely used for microbial ecology studies, but it is sometimes

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difficult to obtain good sequences from highly diverse environments (Nocker et al., 2007) such as soils. It has been applied to identify corrosion-causing bacteria and their diversity (for example see Dar et al., 2005). Denaturing high-performance liquid chromatography is a more recently developed technique that requires less manipulation of PCR products and provides better reproducibility than DGGE (Nocker et al., 2007), and PCR products from mixed communities can be separated for sequencing (Domann et al., 2003; Goldenberg et al., 2005). These tools permit metagenomic analyses to be performed in which the microbes present in an environmental sample such as soil can be identified without the necessity for culturing (Handelsman et al., 1998). Relatively recently developed sequencing methods, 454 sequencing and Illumina sequencing (also referred to as “pyrosequencing”), enable large numbers of parallel sequencing reactions to run at the same time, with higher throughput of samples than the Sanger method. Although sequencing costs for these methods have been high, they are now within the range of most laboratories. The technology does not require cloning or other methods to separate DNA from different species and reduces the number of PCR reactions required per sample, reducing bias and making this technology ideal for metagenomic research (Rothberg and Leamon, 2008). However, where microbial identification from mixed communities is sought, only relatively short 16S rDNA sequences (400e500 bp) are currently available. In addition to identifying microbes these new sequencing methods make it possible to screen communities for genes for particular functions, for example iron oxidation, an approach that may prove particularly effective for future MIC studies. While identification of microbes is useful, even distantly related microbes are capable of exchanging genes (Nelson et al., 1999), complicating the task of understanding mechanisms. These techniques are beginning to be applied to MIC in soil (Jang et al., 2012) and to MIC generally (Park et al., 2011). 4.2. Fluorescence staining and optical microscopy Fluorescent stains such as DAPI and Sytox that bind to DNA or other components of microbial cells can be used to visualise the distribution of microorganisms in freshly obtained samples. Sample preparation is simple, however, excessive background fluorescence from soil minerals, plant material and organic matter complicates their use in soil microbiology (O'Donnell et al., 2007), and biofilms may themselves be autofluorescent. These obstacles may be overcome with the use of fluorescent probes with excitation/emission spectra outside the autofluorescence range. In addition, once the identity of the microbes present in a biofilm is known, in situ DNA hybridisation using fluorescence stains (FISH) can be used to study the biofilm structure. Species-specific DNA probes may be labelled directly with fluorochromes and enzymes (alkaline phosphatise, horseradish peroxidise) or indirectly with haptens (Lens et al., 2003). Confocal laser scanning microscopy (CLSM) and fluorescence microscopy are used for visualising the probes and can determine the distribution of specific species of microorganisms on samples (Little et al., 2006), and the spatial relationships between species within hydrated biofilms. Low numbers of target genes and poor accessibility of probes due to the 3D structure of soil are problems that are encountered using FISH for soil microbiology studies (O'Donnell et al., 2007), and CLSM only has a depth penetration to 20e40 mm (Vroom et al., 1999). Two-photon excitation microscopy (TPE) excites fluorescent tags with two (near) infrared photons, resulting in greater depth of visualisation, and has been successfully used to study living biofilms (Vroom et al., 1999). pH gradients within biofilms can also be analysed using a fluorescent probe that shifts in excitation upon binding Hþ.

4.3. Metabolomics Metabolomics has been defined as the study of “the total biochemical complement of a cell or particular organ”, and usually refers to small-molecule metabolite profiles (Theodoridis et al., 2011). Metabolomics can elucidate enzymatic pathways, the spatial distribution of compounds produced by microorganisms, and the ways in which changing environmental factors affect microbial metabolisms (Tang, 2011). Metabolomics techniques may prove to be powerful tools for studying MIC, but have only recently begun to be applied to this field. They can be used to quantify a number of known metabolites, obtain a “fingerprint” to observe patterns in metabolite production or to identify subsets of metabolites (Dettmer et al., 2007). A variety of methods are available, including secondary ion mass spectrometry (SIMS), however many SIMS techniques result in extensive ion fragmentation, making identification of metabolites impossible (Beech et al., 2005; Lee et al., 2010). The main metabolomics methods currently used are nuclear magnetic resonance spectroscopy (NMR), liquid chromatographyemass spectroscopy (LCeMS) and gas chromatographyemass spectroscopy (GCeMS). Sample preparation varies with the method used. NMR has been widely used, and sample preparation is minimal, but it is less sensitive than MS techniques (Tang, 2011). However, none of these techniques have all of the desired characteristics, such as giving reproducible, unbiased results that are highly sensitive to all metabolites with minimal sample preparation, and multiple techniques are usually required for analyses (Theodoridis et al., 2011). All MS-based methods require efficient desorption and ionisation of metabolites, after which ions are separated by mass analysers and detected (Dettmer et al., 2007). Good sample preparation is critical, and usually involves quenching to halt metabolism, cell harvesting, cell lysis and metabolite extraction (Lee et al., 2010). Many metabolites have low volatility and need to be chemically modified before analysis, but this modification is not well-suited to large thermally labile molecules or for those lacking derivatisable groups (Lee et al., 2010). This limitation of GCeMS will affect results from MIC metabolomic experiments, and emphasises the need for the application of multiple techniques. Recent developments in mass spectrometry, including electrospray ionisation (ESI) and matrix-assisted laser desorption/ionisation (MALDI) enable analysis of large biological molecules at good resolution (Gasper et al., 2008; Lee et al., 2010; Theodoridis et al., 2011), Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and laser desorption post-ionisation-mass spectrometry (LDPI-MS) can quantify and map elemental distributions in biofilms (Gasper et al., 2008). However, where biomarkers are being sought (for example, for MIC) a number of different platforms should be applied to analyse samples (Theodoridis et al., 2011). 4.4. Electron microscopy and spectroscopy Electron microscopy (EM) and spectroscopy techniques; including scanning electron microscopy (SEM) and transmission electron microscopy (TEM), have been fundamentally important in establishing the composition of biofilms and the distribution of microorganisms and their relationships to corrosion products at different time points (McLean et al., 2002; Little et al., 2006). EM imaging of microorganisms can reveal great surface detail and spatial relationships to corrosion products, which sometimes precipitate on the surface of microorganisms. SEM can produce excellent high resolution images of biofilms on surfaces, and can also be used to map elements (see below). Because it is conducted at high vacuum samples must be fully

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dehydrated before imaging, and consideration must be given to the protocols used. Preservation, dehydration in ethanol and criticalpoint drying are necessary to preserve the structure of microorganims during dehydration, as they are composed largely of water and collapse if the sample is not treated appropriately. It is essential that samples remain hydrated prior to undertaking preservation then remain in ethanol until critical-point drying. The application of a conductive film is usually necessary to prevent charging of the sample. SEM instruments equipped with an In Lens detector produce significantly superior resolution compared to Secondary Electron (SE) detectors when used at short working distances of 4e5 mm and low accelerating voltages. However, SE detectors may be the only detector on instruments used primarily for spectroscopy of geological/mineral samples rather than for biological samples. The increased resolution from using an In Lens detector provides important information on surface details of microorganisms, and higher magnification is possible, yet there remain few published MIC images using this method. Environmental SEM and Cryo SEM are useful for imaging hydrated samples. Cryo SEM maintains samples at liquid nitrogen temperatures following plunging into liquid nitrogen. After subliming surface water crystals and applying a conductive coating, biofilms can be imaged in their hydrated state, free of the effects of chemical treatments. These methods are preferred for imaging EPS, which is typically lost during the dehydration steps required for normal SEM. Higher resolution images can be obtained with Cryo SEM compared to Environmental SEM because Cryo SEM is not constrained by working distance, contrast and magnification that environmental SEMs are subject to under low vacuum. However, the method requires more preparation using specialised equipment. Spectroscopy methods using SEM or TEM can identify the chemical composition of corrosion products (Little et al., 2006) together with the spatial association of precipitates with microbes and steel. SEM spectroscopy methods include energy dispersive Xray spectroscopy (EDS) and wavelength dispersive X-ray spectroscopy using (WDS). WDS only analyses one element at a time, but does not suffer from the overlapping peaks and artefacts sometimes generated with EDS. EDS can also be performed on some TEM's with the benefit of higher resolution and sensitivity that comes with higher beam energies. Other TEM spectroscopy methods include energy-filtered transmission electron microscopy (EFTEM), EDS in Scanning TEM mode (STEM), and electron energyloss spectroscopy (EELS). EELS can be used to determine the oxidation state of elements, and is sensitive to carbon and light elements. These methods have been applied successfully to bacteria (Usher et al., 2010), and sample preparation may be as simple as drying pelagic microbes onto a carbon-coated TEM grid, followed by washing and drying, or extensive fixing, dehydrating, embedding, sectioning, mounting and staining of sections to obtain ultra-thin cross-sections of microbial communities. However, the latter method can create artefacts in the distribution and oxidation state of elements. A range of other spectroscopy methods are available, however, access to the instruments is often expensive and difficult. Raman spectroscopy, and the related method infrared spectroscopy, have been successfully applied for the identification of corrosion products (Sherar et al., 2013), and have also shown to be able to identify bacterial species (Beveridge et al., 1996). Raman and infrared spectroscopy generally do not require sample preparation, and the equipment is more readily available than some other equipment, however, to our knowledge these methods have not been used for identifying MIC. Raman spectroscopy typically shines laser light on samples, with shifts in the energy of the scattered light providing

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information about the vibrational modes in the system, and the molecular bonds. Raman provides better spatial resolution (Xie et al., 2006) and results than infrared (IR) spectroscopy when wet samples are being analysed (Beveridge et al., 1996), as water absorbs IR but only weakly absorbs Raman spectra (Xie et al., 2006). A number of variations of Raman, such as Surface-Enhanced Resonance Raman Spectroscopy, can be used to enhance resolution and signal intensity. 4.5. Microsensors Microsensors can provide chemical and physical information within living biofilms, allowing studies of oxygen consumption, nitrification and cycling processes such as coupled sulphate reduction and sulphide oxidation (Santegoeds et al., 1998; Lee et al., þ 2011). Microsensor probes include pH, O2, NO 3 , NH4 , CO2, CH4, PO3 , total chlorine and redox potential (Santegoeds et al., 1998 and 4 refs therein; Lee et al., 2011), and are electrochemical (potentiometric, amperometric or impedance probes) or fibre-optic. However, many of these probes are not commercially available, and making them can be time consuming and difficult (Klimant et al., 1995; Rolletschek et al., 2009). Fibre-optic probes measure light absorption, reflection and fluorescence when an analyte reacts with an indicator (Klimant et al., 1995; Lewandowski and Beyenal, 2003). They have been developed for oxygen, pH, NH3, CO2, and some ionic species (Klimant et al., 1995 and refs therein). Amperometric microelectrodes are popular with biofilm researchers and can measure the concentration of dissolved gases, ions and organic molecules. They measure the current generated from the transfer of electrons between redox couples (Lewandowski and Beyenal, 2003); these methodologies rely on the application of a voltage potential ramp and the subsequent measurement of the current. These probes therefore consume the reactant they measure and as a consequence affect living biofilms. The extent of this effect will depend on the experimental design. Potentiometric probes measure membrane potentials and can be ion-selective, for example sulphide microelectrodes (Lewandowski and Beyenal, 2003). They are often used together with redox potential measurements, but are difficult to calibrate (Lewandowski and Beyenal, 2003). Redox microelectrode readings depend on pH and the rate at which redox couples equilibrate on platinum electrodes. Ion-selective microelectrodes are sensitive to all ions in the biofilm, but the spatial distribution of ions has an unknown effect on measurements (Lewandowski and Beyenal, 2003). pH microelectrodes can be made with membranes, glass tips or metal oxide tips, however, glass pH microelectrodes are usually too large for use with biofilms (Lewandowski and Beyenal, 2003). Oxygen is an important parameter in biofilm functioning, and oxygen microsensors have been widely applied in microbiology. Probes can be microelectrodes (Clarke-type) or fibre optic. Fibre optic sensors have a number of advantages, including stability over time and the fact that they do not consume oxygen while operating (Klimant et al., 1995; Rolletschek et al., 2009), however, the tips are often too large to be useful for studying small regions within biofilms (Klimant et al., 1995). Clarke-type oxygen microelectrodes can be made with tips of 10 mm or less in diameter (Rolletschek et al., 2009), but cross reactions occur with high levels of CO2 and H2S (Klimant et al., 1995). Recently, automated 2-dimensional stages coupled to oxygen microsensors and a data acquisition system has revealed pockets of oxygen within deeper anaerobic layers of biofilms (Yu et al., 2004). Micro-biosensors using biological material immobilised on sensing tips have been applied to measure glucose, CH4, NO 3 and NO. However, correct calibration and careful experimental

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design that takes into account interfering factors such as electromagnetic noise are necessary, and interpretation of results may be difficult (Lens et al., 2003). Some researchers use computer assisted micromanipulation for probing consecutive depths into biofilms. 4.6. Electrochemistry Electrochemical techniques have a long and distinguished record for improving the understanding of corrosion rates and mechanisms (Hardy and Brown, 1984; Franklin et al., 1991b; Li et al., 2001, 2007) and have also been applied to the study of MIC (Mansfeld and Little, 1991). In fact, the majority of MIC studies apply electrochemistry techniques, including measurements of the corrosion potential, redox potential, polarisation resistance, electrochemical impedance, electrochemical noise, and polarisation curves including pitting scans (Mansfeld and Little, 1991). In all cases sterile abiotic controls are required to determine the effects of the microorganisms used, but sterile controls are not generally reported. It may be difficult to maintain the sterility of these controls over time, and experimenters may not be aware of appropriate sterility measures. These methods have often been developed in response to an engineering need to estimate the in-service lifetime of infrastructure. However, the simplified conditions and accelerated testing used in laboratories does not reflect what occurs to pipes buried in natural soil (Baboian, 1990; Miranda et al., 2006). A similar criticism has been made of the simplified laboratory experiments used to investigate the relationships between plants and microorganisms (Ohkama-Ohtsu and Wasaki, 2010). In addition, corrosion rates change over time, so short term values obtained using electrochemistry techniques may not be good indications of long term pipe deterioration (Dafter, 2011). The results may be particularly inaccurate and misleading when relatively short test times are used and where there is high resistivity in complicated systems, for example in soils (Macdonald and McKubre, 1981; Roberge, 2007), and corrosion rates determined by electrochemistry techniques sometimes do not match actual rates of corrosion (for example see Starosvetsky et al., 2001; Norin and Vinka, 2003; Dall'Agnol et al., 2013). Additional problems with MIC electrochemistry experiments may occur, as researchers typically investigate the corrosion effects of purified cell extracts and redox proteins, or single microbial species, to understand electron transfer mechanisms (Ringas and Robinson, 1987; Roberge, 2007; Marsili et al., 2008), and as discussed earlier this significantly alters the behaviour of microorganisms. A lack of reproducibility in electrochemistry experiments can also be caused by differences in the age of the cultures used, which affects the electrochemical efficiency of cells, and by different strains of the same species (Pons et al., 2011). Other alterations such as polishing the surface of metal coupons are necessary for the reproducibility of electrochemical tests, but alter the efficiency of electron transfer (Marsili et al., 2008). Polished coupons are not representative of service products and it is well established that even small differences in surface roughness alters the attachment behaviour of bacteria and biofilm formation (Beech et al., 1994; Katsikogianni and Missirlis, 2004 and refs therein; Li and Logan, 2004; Gu, 2009; Gadd, 2010), key steps for MIC. Because surface roughness is so important for attachment of microbes, polishing of metal equipment is used by food and pharmaceutical industries to reduce disinfection costs (Gu, 2009). Other factors including the carbon source typically supplied as food for bacteria (Rainha and Fonseca, 1997), such as yeast extract, are known to interfere with electrochemical measurements (Little et al., 2008). Electrochemistry techniques have not been found to

be useful for monitoring corrosion rates in MIC experiments due to complex media and the formation of uneven films and precipitates on the metal surface (Cord-Ruwisch, 1996). Experiments aiming to replicate MIC should use continuous flow systems and low levels of carbon to reduce problems associated with a build-up of excreted metabolites if artefacts are to be avoided (Dowling et al., 1988). Studying MIC is particularly difficult because of the specific and localised effects of microbes (Mansfeld and Little, 1992; Campaignolle, 1997) and the behaviour of a system must be analysed to establish which electrochemical technique should be applied, because significant errors can be made (Gonzalez et al., 2005). Many MIC electrochemistry studies do not draw conclusions regarding the mechanism of corrosion (Vukovic et al., 2009), only finding differences in the rate of corrosion (for example see Ringas and Robinson, 1987; Rainha and Fonseca, 1997; Kuang et al., 2007). However, MIC depends on multiple variables so the value of the corrosion potential will not on its own provide useful information on the corrosion rate (Gonzalez et al., 2005). The complexity of corrosion mechanisms and the intricacies of the many different corrosion tests, including the limitations, are often not understood, and may be applied inappropriately. Given the problems associated with the use of electrochemistry techniques in studying MIC, questions relating to corrosion rates may be best answered using the traditional methods of weight loss (as per “Standard practice for preparing, cleaning, and evaluating corrosion test specimens”) combined with pit depth analysis. However, electrochemistry analyses may be useful for analysing the effects of EPS (for example Beech et al., 1998) and purified microbial enzymes on corrosion rates when combined with other analyses. 4.6.1. Soil resistivity Soil resistivity is a function of soil moisture, the concentration of current-carrying soluble ions and the physical structure of the soil. Under standardised conditions impedance is proportional to particle size due to differences in the amount of capillary water trapped between particles, as this is more easily polarised compared to water films on particles, and resistivity increases with particle size (Buehler et al., 2006). The larger particles sizes (and greater resistivity) of sand compared to clay in natural soil explain why sand has long been used to backfill around buried pipes (Dafter, 2011). Because natural soils typically have heterogeneous particle sizes, this can result in noisy data and difficulties interpreting electrochemistry tests results (Dafter, 2011). Perhaps for this reason many studies that apply electrochemistry techniques to investigate corrosion rates in soil use artificial soils or solutions made to simulate soils (for example, Chu et al., 2004), but electrochemical tests under these conditions may not match corrosion rates in real soils, and therefore may not be relevant (Cole and Marney, 2012). For example, Castro et al. (2004) found that adding crushed rock to agar (simulated soil) increased the corrosion rate of carbon steel in MIC experiments. Even using saturated soil for electrochemistry experiments is likely to change the results as soil moisture is important in determining the corrosion rate of buried steel (Gupta and Gupta, 1979). This is particularly likely to be the case when MIC is being investigated, and also in experiments that are not investigating MIC, but in which the components have not been sterilised or maintained in a sterile condition. 4.6.2. Effect of applied currents and potentials on microorganisms The interpretation of MIC experiments using electrochemistry techniques can be difficult, as abiotic corrosion mechanisms may appear to be MIC mechanisms, artefacts can be created by the use of applied potentials or currents (Franklin et al., 2000), and the

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methods may interfere with the transport of electrons by microbes (Gu, 2012). An impact of applied potentials or currents on biofilms is perhaps not surprising, as microorganisms (and all life) depend on energy captured by the transfer of electrons in redox reactions, and electrochemistry techniques interfere with these processes. In addition, healthy bacteria have an electric field surrounding the cell that is important in the initial stages of attachment (Palmer et al., 2007), created by ionised functional groups on their surface (Konhauser, 2007). After initial attachment bacteria form covalent bonds with the inorganic surfaces they are on, and electron transfer between the cell surface and the substratum is thought to play an important role in this (Palmer et al., 2007). The use of applied potentials or currents interferes with the pH and protonation of cell surfaces and alters the ability of microbes to attach to surfaces (Little et al., 1986), with membrane depolarisation causing increased adhesion (Schubert et al., 1978). The surface charge of a substrate such as steel is also very likely to alter bacterial attachment (Palmer et al., 2007) and the adsorption of ionic compounds including EPS (Takehara and Fukuzaki, 2002), and is affected by applied currents and potentials. Some studies have suggested that small AC potentials do not adversely affect bacterial numbers or metabolism (Franklin et al., 1991a). However, other studies show that, in addition to altering adhesion behaviour, imposed currents or potentials impact on biofilms (Dowling et al., 1988) because of microbial susceptibility to a number of factors including redox processes (Bressel et al., 2003), pH and the movement of ions (Miyanaga et al., 2007) even at low magnitude (Costerton et al., 1994; Jass et al., 1995; Stoodley et al., 1997). Large applied potentials can kill bacteria and remove biofilms by producing bubbles of oxygen or hydrogen, the production of biocides such as H2O2, or inducing the unfolding or oxidation of ~o et al., 2003, 2005; adsorbed proteins at oxidising potentials (Gia Marsili et al., 2008). The use of cathodic protection of pipelines with large impressed currents can decrease the viability of some bacteria (Miyanaga et al., 2007) and Marsili et al. (2008) showed that electron transfer processes in the SRB species G. sulfurreducens are voltage dependant and affected by use of an open circuit potential. However, the effects may differ with the type of bacteria involved (Kajiyama and Okamura, 1999) and although there may be adverse effects on some species, protective currents may act as an important energy source for other bacteria and aid their growth (CordRuwisch et al., 1987; Lovley, 2000, 2012). So, while cathodic protection is typically effective while operational, given the potentially beneficial effects on the growth of MIC microbes, failure in cathodic systems may lead to corrosion rates exceeding those observed on unprotected pipes. de Romero et al. (2006) reported that iron sheet polarised at 1000 mV vs SCE supported the growth of SRB, with subsequent corrosion occurring, and Guezennec (1994) showed that SRB cell counts on mild steel buried in marine sediments increased with cathodic protection, with SRB appearing to benefit from cathodically produced hydrogen. A similar observation was made by CordRuwisch (1996) for cathodically protected oil pipes. Little et al. (1986) reported that polarisation of titanium affected bacterial attachment, with a negative potential increasing attachment. Another study found that crevices in high alloy stainless steels immersed in sea water only formed when a potential was applied to biofilms, and crevassing was absent when either the biofilm or the potential were not present (Machuca et al., 2012). This suggests that applied potentials affect biofilms, and can significantly alter the results of corrosion experiments. Fungi hyphae grow towards electric fields and currents and generate their own endogenous D.C. and A.C. currents created by the flow of protons throughout their network of filaments (Gow

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and Morris, 1995). Applied fields have been shown to dramatically affect the growth of fungi (McGillivray and Gow, 1986). 4.6.3. Linear polarisation resistance (LPR) and electrochemical impedance spectroscopy (EIS) Linear polarisation resistance (LPR) and electrochemical impedance spectroscopy (EIS) are commonly used for studying corrosion rates. When uniform corrosion is the main mechanism these techniques are valuable tools. However, they are not considered ideal for studying localised corrosion such as pitting and crevice corrosion (Mansfeld and Little, 1991; Campaignolle, 1997; Li et al., 2001; Roberge, 2007) because the results are mean values over the whole sample surface (Keddam, 2006). Unfortunately, MIC causes non-uniform thinning (Hardy and Brown, 1984) such as pitting, and effective electrochemistry testing methods for the localised corrosion caused by MIC are needed (Li et al., 2001). Sometimes differences are reported between corrosion rates obtained from electrochemistry methods and those obtained by weight loss and pit depth analysis (for example see Morikawa, 2006; Kear et al., 2006). Polarisation resistance is frequently applied to obtain continuous corrosion rates, but significant errors in interpretation can occur, particularly in low conductivity systems (Mansfeld and Little, 1991). EIS is the most commonly used alternating current method applied to aqueous biological interfaces (Marsili et al., 2008) and can provide information on corrosion processes such as diffusion, adsorption and capacitive control. EIS using microprobes placed into small defined zones where the corrosion reaction is occurring, such as a scratch, have been applied (Keddam, 2006). However, in complex systems EIS suffers from limitations, including a significant change in impedance characteristics over time, that can give misleading results (Gonzalez et al., 2005). EIS on active metals may take very long measurement times (e.g. 30 days) to reach steady state conditions suitable for measurements (Sancy et al., 2010), and measurement times are much longer, so LPR is often used in preference (Gonzalez et al., 2005). In addition, for active (readily corroded) metals the complexity of the data can make the interpretation of EIS impossible (Gonzalez et al., 2005). The results of studies using EIS to investigate MIC on buried pipes have been qualitative and no models for impedance were presented for the systems found (Mansfeld and Little, 1992). 4.6.4. Galvanic current Pitting corrosion by MIC has been investigated using galvanic polarisation to create artificial galvanic cells and preconditioning of the electrodes by applying a galvanic current. After turning off the current the naturally flowing galvanic current was measured using a zero-resistance ammeter (Campaignolle, 1997). However, Mansfeld and Little (1991) concluded that calculation of the corrosion rate is difficult using galvanic current as it measures the increase in the current of the anode due to coupling with the cathode. As large differences between corrosion rates as determined by weight loss and galvanic current have been observed, it may be simpler to use traditional weight loss techniques (Baboian et al., 1974). 4.6.5. Electrochemical noise (EN) Electrochemical noise (EN) analysis is a useful method for analysing pitting corrosion and does not impose a current. However, as with EIS, data analysis can be complicated and inconclusive. An expert analysis and thorough understanding of all the factors in the system being studied are required to obtain useful results (Cottis, 2001). Many EN experiments don't accurately reproduce localised corrosion (Yang et al., 2002), and the pitting index obtained may not correlate with the onset of pitting. In addition, the pitting

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potential provides information on the tendency to pit, but not on the rate at which pits propagate (Mansfeld and Little, 1991). As mentioned previously, where electrochemistry methods are applied to investigate MIC appropriate controls must be run. These include a biotic control that does not have a current/potential applied, a sterile abiotic control that has the current/potential applied, and an alternative way to measure corrosion such as weight loss coupons or pit depth analysis. 5. Case studies of buried carbon steel and iron Many publications investigate how various soil characteristics affect the corrosion rates of buried steel (Kleiner et al., 2010; Cole and Marney, 2012), however, there are few studies investigating MIC of buried low carbon steel or mild steel, despite the serious economic losses involved (Booth et al., 1967; Jack et al., 1996; Roberge, 2007). For this reason we review MIC of buried low carbon steel, ductile cast iron and grey iron below. Buried carbon steel pipes are typically coated, sometimes with antimicrobial compounds added, and cathodic protection may also be used. Only Hussain et al. (2013) and the related study in the same laboratory (see below) identified the genera or species present, and these were laboratory strains that were added to the experiments, rather than naturally occurring bacteria. The lack of identification in the remaining studies limits the knowledge obtained. For example, SRB were implicated in a study of soil-based MIC of ductile iron (Kasahara and Kajiyama, 1985), and of archaeological mazeilles et al., 2010) based on iron nails (Novakova et al., 1997; Re analysis of corrosion products. Microbial identification was not performed in these studies. Trivedi et al. (2013) also did not identify the microorganisms in their cultures and in the field. They found that zeolite (sodium exchanged, copper impregnated) coated mild steel suffered little corrosion after 30 days buried in the field, however, only one coupon and one un-coated control were used for this part of their experiment. Bano and Qazi (2011) reported that cultures of Bacillus thuringiensis could be protective to mild steel coupons buried in soil and maintained under laboratory conditions for 50, 100 and 150 days. However, interpretation of the results is difficult due to the highly variable levels of chloride reported in experimental containers at different time points, demonstrating that levels were not consistent across experimental containers. Research from the same laboratory later contradicted the B. thuringiensis results (Hussain et al., 2013) for trials without added nutrients running for 30 months. However, an analysis of the soil chemistry was not conducted in the later study and it is not known if chlorine levels varied between experimental batches. The effects of added nutrients on corrosion rates differed for the controls in these papers (one positive, the other a negative effect), and statistical analyses showing the significance of weight loss were not conducted for either paper despite variations within the same treatment. SRB and acid-producing bacteria were implicated in high corrosion rates of buried polyethylene-coated steel pipes with cathodic protection by Li et al. (2000). Corrosion was found to be highest where disbonding of the coating had occurred, and SRB from these sites were cultured. Li et al. (2001) reported that ruptured FeS films made by SRB on low carbon steel in soil created galvanic corrosion. This was analysed by electrochemistry methods. Srikanth et al. (2005) investigated the cause of serious corrosion problems of a buried mild steel pipes coated in bitumen. SRB and acid producing bacteria could not be cultured from the sites, however, samples for inoculating cultures were not maintained anaerobically, which would have resulted in the death of most anaerobic bacteria. The authors concluded that corrosion resulted from stray currents.

Kajiyama and Koyama (1997) reported that high levels of FeS made by SRB correlated with higher corrosion rates. The authors measured environmental factors on ductile cast iron that had been buried in sandy marine sediment for 17 years. SRB were cultured from samples taken from the site, and numbers of iron bacteria estimated from microscopy observations. Dial gauges were used to measure corrosion depths, and corrosion products were analysed. They observed FeS minerals, SRB and iron bacteria in most samples. As FeS was not naturally found in the sediment, it was concluded that it was generated by SRB. The authors suggested that iron bacteria also contributed to the corrosion rates via the formation of tubercles. Doyle et al. (2003) drew similar conclusions from studies of cast iron pipes in Toronto, where the higher sulphide content of soil in some regions was correlated with higher corrosion rates. King et al. (1986) investigated soil based corrosion of ductile and grey iron pipes and also correlated corrosion rates with the activities of SRB via analysis of corrosion products. Kajiyama and Okamura (1999) found that cathodic protection at recommended values of e 0.95 VCueCuSO4 increased the numbers of SRB, but succeeded in protecting the carbon steel. The authors investigated the effects of cathodic polarisation protection on the numbers of iron bacteria and SRB in different soils, over 90 days. Bacteria were classified by microscopy observations and corrosion rates determined by weight loss and pit depths. This study demonstrated the importance of maintaining cathodic protection once installed, because SRB numbers were increased by its use. 6. Conclusions Controversy has arisen around some of the mechanisms of MIC, the most prominent of which is the hypothesis of “cathodic depolarisation” by SRB. According to this hypothesis SRB oxidise H2 (formed from the oxidation of iron) to reduce sulphate (LappinScott and Costerton, 1989), thus removing the kinetic “bottleneck” and significantly increasing corrosion rates. This indirect electron transfer process was backed up by a series of electrochemistry experiments (Enning and Garrelfs, 2013). However, by 1985 there was mounting evidence showing that this hypothesis did not stand up to rigorous testing (Hamilton, 1985). Studies continue to demonstrate that cathodic depolarisation does not and cannot explain the significant corrosive effects of some SRB (Dinh et al., 2004; de Romero et al., 2005; Venzlaff et al., 2013), but the hypothesis is still occasionally cited. While the question of cathodic depolarisation has been resolved, the effects of iron sulphide films on steel remains controversial (Enning and Garrelfs, 2013). Newman et al. (1992) found that abiotic FeS films can be protective, however the authors acknowledged that the structure of FeS films produced in the presence of SRB is likely to be different in character. Hansson et al. (2006) showed that the abiotic FeS film on iron in alkaline solutions was porous and cracked after 5 days, as also reported by Shoesmith et al. (1980) in acidic abiotic solutions. However, the latter authors reported some passivation by FeS at pH 7. These experiments are relatively short-term, and in the absence of microorganisms cannot reflect what occurs in the field. As discussed earlier in Section 3.3.1, many authors believe that in the continuing presence of SRB protective effects of sulphide films are reversed as the film alters, cracks and becomes corrosive. For example, Bourdoiseau et al. (2010) reported that FeS films are transformed to greigite or pyrite by SRB, whereby the film flakes from the steel surface and allows high corrosion rates to be re-established. The classification of the corrosive effects of microorganisms, which have traditionally been defined as “indirect” effects of metabolism, is another point of difference amongst researchers.

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Hence the term “microbially influenced corrosion” is used, as opposed to “microbially induced corrosion”. However, new experimental approaches have demonstrated that the most severe corrosion is due to microorganisms directly oxidising metallic iron for energy (as outlined in Section 3.2.6) and the term “microbially induced corrosion” is more correct in some situations. Perhaps it is time that the term “microbially induced corrosion” is reintroduced. Understanding soil-based MIC, including how to mitigate and plan for it, is of considerable economic, environmental and public health importance, affecting many industries and utilities worldwide. However, research in this area remains difficult due to the complexity of the soil environment and the interactions between diverse microorganisms, and consequently there are few useful publications for understanding real-world corrosion of buried steel (Cole and Marney, 2012). The relative paucity of soil-based MIC research leaves the field open to innovative new approaches to investigating the phenomenon, and there is much potential for researchers with initiative who wish to make an impact. 6.1. Experimental approaches e get real MIC researchers need to “get real” with their experimental designs. A move away from studying single species on artificially polished surfaces in artificial media is long overdue, and by implication this means a move away from the electrochemistry techniques that have been the mainstay of MIC research for 30 years or more. We lack a fundamental understanding of how natural microbial communities behave in soil, and which combinations of microorganisms are likely to be problematic for steel. Indeed, it is difficult to see practical outcomes from the many years of MIC research, at least for soil-based MIC. For buried pipes preventative measures such as coatings and higher grade alloys can be taken, but we cannot currently match the investment to the need. We still lack the knowledge to be able to predict MIC of buried steel. This understanding of natural microbial communities will require extensive sequencing as well as microscopy methods such as FISH to label species and determine how microorganisms interact in complex communities. With affordable pyrosequencing we now have the tools to make real progress, comparing the makeup of corroding and non-corroding communities, and combining this with knowledge about their metabolisms. It is essential to include archaea as well as bacteria in analyses, and fungi should be included where possible. Together with new microsensor technology, and possibly metabolomics techniques, important advances in understanding MIC can be made. Weight loss coupons remain an important method for determining corrosion rates, particularly for longer-term soil-based corrosion of low carbon steel where individual pits cannot be measured. In addition to considering the effects of multiple interactions, the impact of experimental methods on microbial health and activities must be considered. Some microsensors adversely impact on biofilms and are therefore not appropriate for monitoring the effects of living microorganisms. The application of electrochemistry techniques to MIC is also problematic due to the sensitivity of microorganisms to applied potentials and currents, the heterogeneity of soil particle sizes, high resistivity of soil, necessity to modify experimental surfaces and a paucity of methods to investigate pitting corrosion. Electrochemistry techniques may be useful for determining the corrosion effects of isolated components, such as purified microbial enzymes in soil-free tests. However, an approach based on an analysis of different aspects of natural communities is important in order to understand community structure, cooperative interactions between microorganisms and the effects of the environment on biofilm functioning.

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6.2. Future directions We are only now beginning to appreciate that some microorganisms can extract and consume electrons directly from steel for energy and growth (EMIC), but their prevalence and diversity in natural environments is largely unknown. EMIC microorganisms are known to increase corrosion rates significantly, and this area should be the focus of future research. Natural communities need to be tested for the ability to oxidise Fe0 and to survive without other electron donors. When positive results are obtained the species need to be identified. The ability of EMIC microorganisms to pass electrons on to other species within biofilms should also be investigated. The transfer of electrons between microorganisms is a new area of research and further surprises are likely to be in store. These types of symbioses could in theory negate the need for EMIC SRBs to access electron acceptors such as sulphate, if electrons are passed to a methanogen (or other microorganism), and ultimately CO2 is reduced. It seems likely that interspecies electron transfer could significantly increase corrosion rates, and we have only just scratched the surface of how electron transfer mechanisms such as conductive materials and nanowires function within biofilms. Acknowledgements This work was funded by CSIRO through Office of Chief Executive (OCE) Post Doctoral Fellowship scheme and Water for a Healthy Country Flagship. These bodies did not have a role in the design or preparation of this paper. The authors acknowledge Dr Peta Clode and the facilities, scientific and technical assistance of the National Imaging Facility at the Centre for Microscopy, Characterisation & Analysis, The University of Western Australia, a facility funded by the University, State and Commonwealth Governments. The authors also thank the anonymous reviewers for their contributions. References AlAbbas, F.M., Williamson, C., Bhola, S.M., Spear, J.R., Olson, D.L., Mishra, B., Kakpovbia, A.E., 2013. Influence of sulfate reducing bacterial biofilm on corrosion behavior of low-alloy, high-strength steel (API-5L X80). Int. Biodeterior. Biodegr. 78, 34e42. ANSI/AWWA C105/A21.5-99, 1999. American National Standard for Polyethylene Encasement for Ductile-Iron Pipe Systems. American Water Works Association, Denver, CO. Baboian, R., 1990. Corrosion Testing and Evaluation: Silver Anniversary Volume. ASTM International. Baboian, R., 2005. Corrosion Tests and Standards: Application and Interpretation. ASTM International, West Conshohocken, Penn. Baboian, R., 1974. Electrochemical techniques for predicting galvanic corrosion. In: Robert, B., et al. (Eds.), Materials Engineering Congress. American Society for Testing and Materials, Detroit, USA, p. 312. Baird, G.M., 2011. The Epidemic of Corrosion, Part 1: Examining Pipe Life. AWWA: The American Water Works Association, pp. 14e21. Banfield, J.F., Barker, W.W., Welch, S.A., Taunton, A., 1999. Biological impact on mineral dissolution: application of the lichen model to understanding mineral weathering in the rhizosphere. Proc. Natl. Acad. Sci. U.S.A. 96, 3404e3411. Bano, A.S., Qazi, J.I., 2011. Soil buried mild steel corrosion by Bacillus cereus-SNB4 and its inhibition by Bacillus thuringiensis-SN8. Pak. J. Zool. 43, 555e562. Bao, H., Jenkins, K.A., Khachaturyan, M., Díaz, G.C., 2004. Different sulfate sources and their post-depositional migration in Atacama soils. Earth Planet. Sci. Lett. 224, 577e587. Barkay, T., Schaefer, J., 2001. Metal and radionuclide bioremediation: issues, considerations and potentials. Curr. Opin. Microbiol. 4, 318e323. Barker, W.W., Welch, S.A., Chu, S., Banfield, J.F., 1998. Experimental observations of the effects of bacteria on aluminosilicate weathering. Am. Mineral. 83, 1551e1563. Basic Local Alignment Search Tool. NCBI. http://blast.ncbi.nlm.nih.gov/Blast.cgi (accessed 07.05.14.). Beech, I.B., Cheung, C.W.S., 1995. Interactions of exopolymers produced by sulphatereducing bacteria with metal ions. Int. Biodeterior. Biodegr. 35, 59e72. Beech, I.B., Coutinho, C.M.L.M., 2003. In: Lens, P., et al. (Eds.), Biofilms in Medicine, Industry and Environmental Biotechnology. IWA Publishing, London, pp. 115e131.

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Abbreviations DGGE: denaturing gradient gel electrophoresis EDS: energy dispersive X-ray spectroscopy EELS: electron energy-loss spectroscopy EFTEM: energy-filtered transmission electron microscopy EIS: electrochemical impedance spectroscopy EPS: extracellular polymeric substances EM: electron microscopy FISH: fluorescence in situ hybridisation IB: iron oxidising/reducing bacteria LPR: linear polarisation resistance MIC: microbially influenced corrosion RFLP: restriction fragment length polymorphism SEM: scanning electron microscopy SRB: sulphate reducing bacteria SOB: sulphur oxidising bacteria TEM: transmission electron microscopy STEM EDS: TEM energy dispersive X-ray spectroscopy in scanning mode