Perspective on “Diagnosing Microbiologically Influenced Corrosion: A State-of-the-Art Review,” B.J. Little, J.S. Lee, and R.I. Ray, Corrosion 62, 11 (2006): p. 1006-1017

“…plus ça change, plus c’est la même chose “ – the more things change, the more they stay the same…”

Jean-Baptiste Alphonse Karr (1849)

A persistent goal of microbiologically influenced corrosion (MIC) studies has been the development of analytical tools that can be used to diagnose MIC, i.e., differentiate MIC from abiotic corrosion. Little, et al.,¹  reviewed diagnostic techniques, their advantages and disadvantages, and, most importantly, their limitations. They concluded that there was no single indicator to diagnose MIC. Instead, diagnosis requires multiple types of evidence, e.g., microbiological, metallurgical, and chemical data. Little, et al.,¹  further acknowledged the fallacy of interpreting data from liquid culture enrichments to identify and quantify “corrosive” microorganisms as diagnostic for MIC. The authors identified two mineralogical indicators for MIC, i.e., unique mineralogy and sulfur isotope fractionation, particularly in sulfide-containing corrosion products. The following perspective addresses two questions related to Little, et al.:¹  What has changed and what has remained the same in our understanding of MIC diagnosis?

In 2006, lists of “corrosive” bacteria were constructed using data from enrichment cultures of solid and liquid samples associated with corrosion. Little and Lee²  published a list of 12 bacterial and one fungal species known to contribute to corrosion based on metabolism/respiration, i.e., acid production, sulfate reduction, and ferrous oxidation. Since that time, the list of microorganisms implicated in MIC has increased. There are reasons for the increase. Diagnostic enrichment culture media developed for the quantification and identification of specific groups of “corrosive” bacteria, e.g., acid-producing bacteria (APB), sulfate-reducing bacteria (SRB), anaerobic heterotrophs, and aerobic heterotrophs have been replaced with molecular microbiological methods (MMM).³  Liquid culture media were designed to detect viable microorganisms within putative groups, based on turbidity or color changes, and to quantify their numbers using dilution-to-extinction techniques. Instead of growing and counting microorganisms, MMM analyze the molecules that microorganisms possess or generate, including deoxyribonucleic acid (DNA), ribonucleic acid (RNA), proteins, lipids, and metabolites. MMM can provide information about microbial diversity, abundance, activity, and function of microorganisms associated with corrosion products. MMM discussed in this perspective include polymerase chain reaction (PCR), next-generation sequencing (NGS), metagenomics, and metabolomics.

The combination of PCR and NGS is used to identify and quantify the microbial community associated with MIC. PCR is a technique to synthesize and amplify specific short segments of DNA or RNA (primers). Enumeration requires quantitative PCR (qPCR) in which a fluorescent reporter molecule emits a signal when it binds to the amplified segment during each cycle of amplification. The signal is proportional to the amount of DNA or RNA in the starting sample. NGS sequencing can use either targeted or shotgun approaches. In targeted sequencing, primers are used to amplify and sequence specific genes, followed by the identification of the microorganisms that have the target gene.⁴  For example, Zhu, et al.,⁵  identified the genes responsible for dissimilatory sulfite reductase, nitrite reductase, and methyl-coenzyme M reductase targeted for the quantification of SRB, denitrifying bacteria, and methanogens, respectively. Sequencing the 16S ribosomal RNA (16S rRNA) gene, has been used to identify bacteria and archaea in corrosion products. Shotgun sequencing randomly breaks DNA into small fragments, sequences the fragments and reassembles the fragments using computational bioinformatics followed by identification of specific genes and microorganisms. Amplification is not performed before shotgun sequencing.

Taylor, et al.,⁶  compared data from MMM to demonstrate that enrichment cultures produced inaccurate representations of water and solid samples as demonstrated by the direct extraction of DNA. Similarly, Zhu, et al.,⁵  compared the results of qPCR assays and conventional growth tests and showed that the conventional growth tests severely underestimated the target bacteria in different growth media and did not accurately characterize the microbial community composition in pipeline samples. Lahme, et al.,⁷  noted that population sizes of methanogens and SRB established by culture techniques did not correlate with corrosivity in oilfield assets. Based on data from MMM, lists of putative microorganisms were expanded.

The demonstration of EMIC sparked an expansion of the vocabulary related to MIC mechanisms. The abbreviation EET-MIC is now a synonym for EMIC and metabolic MIC (MMIC) is synonymous with CMIC. Theoretically, EET can be either direct (DEET) or mediated (MEET). DEET pathways provide direct connection to the electron donor, e.g., redox proteins (e.g., c-type cytochromes) bound at outer cell membranes or conductive appendages, e.g., pili.¹⁰  MEET is facilitated by electron shuttles between electron donors and acceptors through reversible redox reactions. Further refined terms include the following: direct iron-to-microbe electron transfer (DIMET), H₂-mediated iron-to-microbe electron transfer (HIMET), and shuttle-mediated iron-to-microbe electron transfer (SIMET).¹³ 

The list of putative microorganisms increased as the recognition of EET increased, but there were still no correlations between the numbers of causative microorganisms and the severity or likelihood of corrosion. Many microbes have genes for EET, but that does not mean that they will cause EET-MIC. Kotu, et al.,¹⁴  concluded that identification of community members without information regarding metabolic activity or the reverse, i.e., metabolic reactions without the community composition were “both inadequate for understanding MIC.”

These and similar observations led to an approach for linking microbial communities (microbiome) with metabolic reactions (metabolome). Recent MIC studies^15-16  identified microbial metabolites, e.g., carboxylic acids, amino acids, fatty acids, and fatty alcohols, as potential “biomarkers” or “footprints” of MIC. Duncan, et al.,¹⁷  and Lenhart, et al.,¹⁸  analyzed planktonic and sessile samples from the Alaskan North Slope oilfield and observed that the metabolites in samples from the two locations were different. Saturated and aromatic hydrocarbon compounds were present only in the sessile samples while alkyl succinates (products of anaerobic hydrocarbon degradation) were identified in the planktonic samples. Analyzing the planktonic and sessile metabolites separately led to the conclusion that fatty acids (byproducts of anaerobic hydrocarbon degradation) produced by planktonic microorganisms were used by sessile microorganisms.

Deutzmann, et al.,¹⁹  were among the first to conclude that the corrosiveness of certain microorganisms might depend, not on their numbers, but on the quantity and stability of extracellular redox-active enzymes. Tsurumaru, et al.,²⁰  demonstrated that [NiFe] hydrogenase (electron acceptor) secreted outside the cytoplasmic membrane, can make direct contact with Fe⁰ (electron donor), oxidize it, and generate hydrogen gas, i.e., Fe⁰ + 2 H⁺ → Fe²⁺ + H₂. The authors coined the term “MIC hydrogenase” for [NiFe] hydrogenase.

Despite the acknowledged paradigm shift from culture-based enumeration approaches to MMM,²²  many of the problems associated with diagnosing MIC have not changed. MMM techniques applied to MIC continue to deal almost exclusively with carbon steel in oil and gas environments and many of the observations relate to sulfide-producing procaryotes and methanogens. Because the operating conditions in oil and gas operations are not conducive to the growth of fungi and microalgae, there has been little progress in diagnosing MIC in natural multikingdom biofilms or MIC in other materials and environments.

Some criticisms of enrichment techniques for the identification and enumeration of microbial populations are detailed in Little, et al.,¹  A major limitation to diagnosing MIC based on metabolism (heterotrophic, lithotrophic, etc.) and respiration (aerobic, anaerobic, and facultative) is that microorganisms in natural environments exhibit nutritional flexibility that cannot be duplicated in a single liquid culture medium. Culture techniques depend on viable, culturable microorganisms. Turbidity and color changes in culture media were attributed to bacteria, ignoring the possibility that other microorganisms, e.g., archaea and fungi, were responsible for the observations. The result was the likelihood of both false negatives and false positives. Many microorganisms that cannot be detected in liquid culture are identifiable with MMM, e.g., thiosulfate reducers and methanogens. However, there are limitations to MMM methods.

Primer design/selection for targeted sequencing requires prior knowledge regarding the target microorganisms and cannot predict the presence or absence of nontarget species.⁴  Ben-Dov, et al.,²³  stress, “The choice of primers to be used in studies to assess the diversity of prokaryotes is not trivial.” Amplification bias has been reported in which some DNA sequences are amplified more than others, meaning that less abundant microorganisms can be overlooked.²⁴  To date the term “universal primer” is somewhat misleading. For example, no single variable region of the 16S rRNA gene can identify all community members.²⁵  PCR methods do not distinguish between live, resting, and dead cells or extracellular DNA.²⁶  Extracellular environmental DNA contamination can produce false positives in shotgun sequencing approaches.²⁷  The possibility of false negatives and false positives persist.

In both culture techniques and MMM, the results depend on the handling of the specimens, i.e., collection, fixation/preservation, and analysis techniques. The culture techniques have been adapted to use in the field. However, MMM techniques often require transportation to a laboratory setting, i.e., a lag time between collection and analysis. Rachel and Gieg²⁸  evaluated current practices to establish guidelines for “best practices.” If sample storage is required before MMM analysis, a chemical preservative should be added, and samples should be processed as soon as possible. Rachel and Gieg²⁸  demonstrated that not all preservatives were equally effective for all sample types.

Scott and Davies²⁹  documented the lack of reproducibility of six commercially available test kits specific for enumerating SRB. Identical samples were evaluated using identical test kits in six independent laboratories. Four of the test kits relied on culture techniques to establish numbers of SRB. Test kit data were compared with in-house techniques used by the investigating laboratories. Numbers of SRB varied “widely” among the test kits and between labs using the same kit. De Paula, et al.,³⁰  reported the results of a similar study in which multiple samples from several onshore oil wells were submitted to two independent laboratories for 16S rDNA taxonomic analyses. The results showed “significant differences” in an abundance of total organisms, taxonomic compositions, and the presence/absence of indicator microorganisms between the two laboratories (Table 1). The authors concluded that different primer sets significantly affected the results.

Table 1.

Top Two Most Abundant Organisms Identified by DNA Sequencing in Samples Processed by Independent Laboratories^(A)

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The search for MIC fingerprints,^1,22  footprints,^22,31  and biomarkers³²  continues. There has been a shift from the identification of unique microbiologically produced minerals and sulfur isotope fractionation to the characterization of metabolites resulting from microbial reactions. Most of the sulfide-containing minerals attributed to SRB in corrosion products are amorphous, i.e., difficult to detect with x-ray diffraction, and quickly oxidize if exposed to air. Demonstrations of isotope fractionation require an isotope ratio of the starting oxidized sulfur source in addition to the isotope ratio in the corrosion product. The analysis requires sophisticated laboratory equipment. Neither fingerprint was used in routine diagnoses. As previously indicated, the current trend to link the metabolome with the metagenome has produced some interesting correlations with corrosivity.

There are no simple thresholds for correlating microbiological parameters to MIC. The AMPP task group³³  responsible for preparing AMPP TM21465-2024³⁴ Molecular Microbiological Methods: Sample Handling and Laboratory Processing concluded that there was no scientific evidence to link the number of microorganisms to MIC, i.e., the numbers of specific microorganisms cannot be used to predict the risk of MIC, regardless of the methodology used to establish the numbers. Puentes-Cala, et al.,³⁵  noted the absence of MIC modeling algorithms combining operational and environmental variables with microbial data, stressing the limited usefulness of MMM data for decision-making.

• The introduction of new technology to existing fields of study is always accompanied by great expectations for progress. The application of MMM to MIC has improved the identification and enumeration of microorganisms, particularly bacteria and archaea, associated with MIC. The result is genomic information related to populations of microorganisms. It has taken years of research to recognize the benefits and limitations of this information. AMPP TM21465-2024 was developed to address sampling and processing standards for MMM. To date, there are no accepted practices for data interpretation and no threshold values for prediction or diagnosis. MMM results vary among laboratories conducting identical analyses on the same corrosion product. Consequently, it is difficult to claim progress in the diagnosis of MIC.

• The next frontier appears to be the coupling of genomic information with metabolomic information, relating the genome with corrosivity. Relationships between metabolomes and electrolytes have not been established. Real progress in diagnosis requires the recognition that MIC reactions are electrolyte-specific. Use of undefined media as electrolytes in corrosion experiments has produced data that cannot be reproduced, but that are overinterpreted, published, and cited, perpetuating the confusion related to MIC. Metadata, i.e., the data related to the data, e.g., electrolyte composition (minerals and growth stimulants), temperature, and method of deaeration, for exposures/experiments can determine the outcome and must be included in all reports and publications.

Diagnosing microbiologically influenced corrosion (MIC) after it has occurred requires a combination of microbiological, metallurgical, and chemical analyses. MIC investigations have typically attempted to 1) identify causative microorganisms in the bulk medium or associated with the corrosion products, 2) identify a pit morphology consistent with an MIC mechanism, and 3) identify a corrosion product chemistry that is consistent with the causative organisms. The following sections provide a discussion of available techniques, their advantages and disadvantages, and, most importantly, their limitations.

Editor’s Note: Originally published in Corrosion 62, 11 (2006): p. 1006-1017. When citing “Diagnosing Microbiologically Influenced Corrosion: A State-of-the-Art Review,” please cite the original version.

KEY WORDS: detection, methods, microbiologically influenced corrosion

For many years the first step in identifying corrosion as microbiologically influenced corrosion (MIC) was to determine the presence of specific groups of bacteria in the bulk medium (planktonic cells) or associated with corrosion products (sessile cells). There are four approaches:

• culture the organisms on solid or in liquid media

• extract and quantify a particular cell constituent

• demonstrate/measure some cellular activity

• demonstrate a spatial relationship between microbial cells and corrosion products using microscopy

The method most often used for detecting and enumerating groups of bacteria is the serial dilution to extinction method using selective culture media. To culture microorganisms, a small amount of liquid or a suspension of a solid (the inoculum) is added to a solution or solid that contains nutrients (culture medium). There are three considerations when growing microorganisms: type of culture medium, incubation temperature, and length of incubation. The present trend in culture techniques is to attempt to culture several physiological groups including aerobic, heterotrophic bacteria; facultative anaerobic bacteria; sulfate-reducing bacteria (SRB), and acid-producing bacteria (APB). Growth is detected as turbidity or a chemical reaction within the culture medium. Traditional SRB media contain sodium lactate as the carbon source.^1-2  When SRB are present in the sample, sulfate is reduced to sulfide, which reacts with iron (either in solution or solid) to produce black ferrous sulfide. Culture media are typically incubated over several days (30 days may be required for the growth of SRB). There have been several attempts to improve culture media and to grow higher numbers of bacteria or to shorten the time required for some indication of growth. A complex SRB medium was developed containing multiple carbon sources that can be degraded to both acetate and lactate. In comparison tests, the complex medium produced higher counts of SRB from waters and surface deposits among five commercially available media.³  Jhobalia, et al., developed an agar-based culture medium for accelerating the growth of SRB.⁴  The authors noted that over the range from 1.93 g/L to 6.50 g/L SRB grew best at the lowest sulfate concentration. Cowan developed a rapid culture technique for SRB based on rehydration of dried nutrients with water from the system under investigation.⁵  The author claimed that using system water reduced the acclimation period for microorganisms by ensuring that the culture medium had the same salinity as the system water used to prepare the inoculum. The author reported quantification of SRB within one to seven days.

The distinct advantage of culturing techniques to detect specific microorganisms is that low numbers of cells grow to easily detectable higher numbers in the proper culture medium. However, there are numerous limitations for the detection and enumeration of cells by culturing techniques. Several investigators have followed the changes in microflora as a function of water storage. Zobell and Anderson⁶  and Lloyd⁷  demonstrated that when water is stored in glass bottles, the bacterial numbers fall within the first few hours followed by an increase in the total bacterial population with a reduction in the number of species. If results from culturing techniques are to be related to the natural populations, culture media should be inoculated within hours of collection and the sample should be chilled during the interim. Under all circumstances culture techniques underestimate the organisms in a natural population.^8-9  Kaeberlein, et al., suggest that 99% of microorganisms from the environment resist cultivation in the laboratory.¹⁰  One major problem in assessing microorganisms in natural environments is that viable microorganisms can enter into a nonculturable state.¹¹  Another problem is that culture media cannot approximate the complexity of a natural environment. Growth media tend to be strain-specific. For example, lactate-based media sustain the growth of lactate-oxidizers, but not acetate-oxidizing bacteria. Incubating at one temperature is further selective. The type of medium used to culture microorganisms determines, to a large extent, the numbers and types of microorganisms that grow. Zhu, et al., demonstrated dramatic differences in the microbial population from a gas pipeline depending on the enumeration techniques.¹²  For example, using culture techniques SRB dominated the microflora in most pipeline samples. However, using culture-independent genetic techniques they found that methanogens were more abundant in most pipeline samples than denitrifying bacteria and that SRB were the least abundant bacteria. Similarly, Romero, et al., used genetic monitoring to identify bacterial populations in a seawater injection system.¹³  They found that some bacteria present in small amounts in the original waters were enriched in the culture process.

Biochemical assays have been developed for the detection of specific microorganisms associated with MIC. Unlike culturing techniques, biochemical assays for detecting and quantifying bacteria do not require growth of the bacteria. Instead, biochemical assays measure constitutive properties including adenosine triphosphate (ATP),¹⁴  phospholipid fatty acids (PLFA),¹⁵  cell-bound antibodies,¹⁶  and DNA.¹⁷  Adenosine-5’-phosphosulfate (APS) reductase¹⁸  and hydrogenase¹⁹  have been used to estimate SRB populations.

Since ATP is a compound found in all living matter, ATP assays estimate the total number of viable organisms in a sample. ATP assays are based on the luciferin-luciferase reaction where ATP provides the energy for the oxidation of luciferin by the enzyme luciferase. The procedure requires that a water sample be filtered to remove solids and salts that might interfere. A reagent is added to the filtered sample to lyse the cells and release the ATP. The reaction is sensitive to sulfide, some metals, and some types of biocides. Emitted light is measured with a photometer and the amount of light released during the reaction is directly related to the amount of ATP in the sample.

Biofilm community structure can be analyzed using cluster analysis of PLFA profiles.¹⁵  Phospholipids are found in the membranes of all cells. Under the conditions in natural communities, bacteria contain a relatively constant proportion of their biomass as phospholipids. Phospholipids are not found in storage lipids and have a relatively rapid turnover so that their assay gives a measure of the viable cellular biomass. The phosphate of the phospholipids or the glycerol-phosphate and acid-labile glycerol from phosphatidyl glycerol-like lipids can be assayed to increase the specificity and sensitivity of the phospholipids assay. The ester-linked fatty acids in the phospholipids are both the most sensitive and useful chemical measures of microbial biomass and community structure. PLFA profiles for natural biofilms have been shown to be more complex than profiles for laboratory biofilms. None of the laboratory profiles clustered closely with profiles from natural biofilms. Also, the PLFA profiles for attached bacteria clustered separately from profiles of the same bacteria in the bulk phase, suggesting that either the community or the physiology of attached bacteria differs from that of bulk phase bacteria. Despite the fact the PLFA analysis cannot provide an exact description of each species in a given environment, the analysis does provide a quantitative description of the microbiota in a particular environment. Analysis of other components of the phospholipids fraction give insight into community structure. For example, SRB contain lipids that can be used to identify at least a portion of the class. Dowling, et al., identified unusual fatty acids as biomarkers for two SRB: iso 17:1w7c and branched monoenoics for a hydrogen-oxidizing Desulfovibrio sp. and 10 methyl 16:0 for an acetate oxidizing Desulfobacter sp.²⁰ 

Both APS reductase, an intracellular enzyme found in all SRB, and hydrogenase, an enzyme present in some SRB (hydrogenase-positive), can be extracted from liquids or solids, including corrosion products and sludge. In a procedure to quantify APS reductase, cells are lysed to release the enzyme, added to an antibody reagent and exposed to a color-developing solution. In the presence of APS reductase a blue color appears whose intensity and development rate is proportional to the amount of enzyme and roughly to the number of cells from which the enzyme was extracted. Similarly, hydrogenase activity may be measured in a procedure where the enzyme is extracted from cells and exposed to hydrogen anerobically.¹⁹  The rationale for relating hydrogenase to MIC is that during corrosion in anaerobic environments, molecular hydrogen is produced at the cathode. Some, but not all SRB, are hydrogenase positive, meaning that they possess the enzyme required to oxidize molecular hydrogen. In the assay, hydrogenase reacts with hydrogen and reduces an indicator dye in solution. The activity of hydrogenase is established by the development and intensification of a blue color proportional to the rate of hydrogen uptake by the enzyme. The technique does not attempt to estimate specific numbers of SRB. Bryant, et al., suggested that hydrogenase levels were better indicators of MIC than numbers of SRB.²¹  Mara and Williams reported that hydrogenase was more important when the environment contained low concentrations of ferrous ions, but was less important in the presence of sufficient ferrous ions to precipitate the sulfide produced by SRB.²²  Other investigators found no relationship between levels of hydrogenase enzyme and the rate or extent of corrosion.²³ 

Roszak and Colwell reviewed techniques commonly used to detect microbial activities in natural environments, including transformations of radio-labeled metabolic precursors.¹¹  Phelps, et al.,²⁴  and Mittelman, et al.,²⁵  used uptake or transformation of ¹⁴ C-labeled metabolic precursors to examine activities of sessile bacteria in natural environments and in laboratory models. Phelps, et al., used a variety of ¹⁴ C-labeled compounds to quantify catabolic and anabolic bacterial activities associated with corrosion tubercles in steel natural gas transmission pipelines.²⁴  They demonstrated that organic acid was produced from hydrogen and carbon dioxide in natural gas by acetogenic bacteria, and that acidification could lead to enhanced corrosion of the steel. Mittelman, et al., used measurement of lipid biosynthesis from ¹⁴ C-acetate, in conjunction with measurements of microbial biomass and extracellular polymer, to study effects of differential fluid shear on physiology and metabolism of Alteromonas (formerly Pseudomonas) atlantica.²⁵  Increasing shear force increased the rate of total lipid biosynthesis, but decreased per cell biosynthesis. Increasing fluid shear also increased cellular biomass and greatly increased the ratio of extracellular polymer to cellular protein. Maxwell developed a radiorespirometric technique for measuring SRB activity on metal surfaces that involved two distinct steps: incubation of the sample with ³⁵ S sulfate and trapping the released sulfide.²⁶ 

Techniques for analyzing microbial metabolic activity at localized sites have been developed. Franklin, et al., incubated microbial biofilms with ¹⁴ C-metabolic precursors and autoradiographed the biofilms to localize biosynthetic activity on corroding metal surfaces.²⁷  The localized uptake of labeled compounds was related to localized electrochemical activities associated with corrosion reactions.

Reporter genes can signal when the activity of a specific metabolic pathway is induced. King, et al., engineered the incorporation of a promotorless cassette of lux genes into specific operons of Pseudomonas to induce bioluminescence during degradation of naphthalene.²⁸  Using reporter genes, Marshall demonstrated that bacteria immobilized at surfaces exhibit physiological properties not found in the same organisms in the aqueous phase.²⁹  Some genes are turned on at solid surfaces despite not being expressed in liquid or on solid media. It is also likely that other genes are turned off at surfaces. They further demonstrated gene transfers within biofilms even in the absence of imposed selection pressure.

Genetic techniques using ribosomal RNA (rRNA) or their genes (rDNA) have been used to identify and quantify microbial populations in natural environments.^30-32  These techniques involve amplification of 16S rRNA gene sequences by polymerase chain reaction (PCR) amplification of extracted and purified nucleic acids. The PRC products can be evaluated using community fingerprinting techniques such as denaturing gradient gel electrophoresis (DGGE). Each DGGE band is representative of a specific bacterial population and the number of distinctive bands is indicative of microbial diversity. The PCR products can also be sequenced, and the sequences are compared to the sequences in the Genbank database,⁽¹⁾ which allows the identity of the species within an environmental sample. Horn, et al., identified the constituents of the microbial community within a proposed nuclear waste repository using the following two techniques:³³ 

• isolation of DNA from growth culture and subsequent identification by 16S rDNA genes

• isolation of DNA directly from environmental samples followed by subsequent identification of the amplified 16S rDNA genes (Table 1 and Figure 1)

Comparison of the data from the two techniques demonstrates that culture-dependent approaches underestimated the complexity of microbial communities. Zhu, et al., used genetic techniques to characterize the types and abundance of bacterial species in gas pipeline samples and made similar observations.^34-35  Another example of genetic techniques is the fluorescent in situ hybridization (FISH), which uses the specific fluorescent dye-labeled oligonucleotide probes to selectively identify and visualize SRB both in established and developing multispecies biofilms.³² 

Using light microscopy and proper staining, investigators have demonstrated a relationship between an unusual variety of copper corrosion and gelatinous, polysaccharide-containing biofilms.^36-37  Blue water (also called copper by-product release or cuprosolvency) is observed in copper tubing, primarily in soft waters after a stagnation period of several hours to days and is typically associated with copper concentrations of 2 mg/L to 20 mg/L. This phenomenon is distinct from other types of copper corrosion in that it does not significantly compromise the integrity of the tube, but instead leads to copper contamination and coloring of the water.

Immunofluorescence techniques have been developed for the identification of specific bacteria in biofilms.^38-39  Epifluorescence cell surface antibody (ECSA) methods for detecting SRB are based on the binding between SRB-specific antibodies and the SRB cells, and subsequent detection of SRB-specific antibodies with a secondary antibody through two approaches. First, the secondary antibodies can be linked to a fluorochrome that enables bacterial cells marked with the secondary antibody to be viewed with an epifluorescence microscope. Second, the secondary antibodies can be conjugated with an enzyme (alkaline phosphatase) that then can be reacted with a colorless substrate to produce a visible color proportional to the quantity of SRB present. Detection limits for the field test are 10,000 SRB mm⁻² filter area. The color reagent used for field tests is unstable at room temperature and tends to bind nonspecifically with antibodies adsorbed directly at active sites on the filter, creating a false positive that may interfere with the detection of SRB at levels below 10,000 cells mm⁻². Antigenic structures of marine and terrestrial strains are distinctly different and therefore antibodies to either strain did not react with the other.

Confocal laser scanning microscopy (CLSM) permits one to create three-dimensional images, determine surface contour in minute detail, and accurately measure critical dimensions by mechanically scanning the object with laser light. A sharply focused image of a single horizontal plane within a specimen is formed while light from out-of-focus areas is repressed from view. The process is repeated again and again at precise intervals on horizontal planes and the visual data from all images are compiled to create a single, multidimensional view of the subject. Geesey, et al., used CLSM to produce three-dimensional images of bacteria within scratches, milling lines, and grain boundaries.⁴⁰ 

Atomic force microscopy (AFM) uses a microprobe mounted on a flexible cantilever to detect surface topography by scanning at a subnanometer scale. Repulsion by electrons overlapping at the tip of the microprobe cause deflections of the cantilever that can be detected with a laser beam. The signal is read by a feedback loop to maintain a constant tip displacement by varying voltage to a piezoelectric control. The variations in the voltage mimic the topography of the sample and, together with the movement of the microprobe in the horizontal plane, are converted to an image. Telegdi, et al., imaged microorganisms associated with corrosion on several substrata.⁴¹ 

Many of the conclusions about biofilm development, composition, distribution, and relationship to substratum/corrosion products have been derived from traditional scanning electron microscopy (SEM) and transmission electron microscopy (TEM). SEM has been used to image SRB from corrosion products on Type 904L (UNS N08904),^42,(2) microorganisms in corroding gas pipelines,³⁵  and iron-oxidizing Gallionella in water distribution systems.⁴³  TEM has been used to demonstrate that bacteria are intimately associated with sulfide minerals and that on copper-containing surfaces the bacteria were found between alternate layers of corrosion products and attached to the base metal.⁴⁴ 

There are fundamental problems in attempting to diagnose MIC by establishing a spatial relationship between numbers and types of microorganisms in the bulk medium and those associated with corrosion products using any of the techniques previously described. Zintel, et al., established that there were no relationships between the presence, type, or levels of planktonic or sessile bacteria and the occurrence of pits.⁴⁹  Because microorganisms are ubiquitous, the presence of bacteria or other microorganisms does not necessarily indicate a causal relationship with corrosion. In fact, microorganisms can nearly always be cultured from natural environments. Little, et al.,⁵⁰  reported that electrochemical polarization could influence the number and types of bacteria associated with the surface.⁵⁰  Artificial crevices created in Type 304 (UNS S30400) stainless steel in abiotic seawater were associated with large numbers of bacteria after 5-day exposures to natural seawater. Bacteria did not cause the crevice; instead, bacteria were attracted to the anodic site. Several other investigators have made similar observations. For example, de Sánchez and Schiffrin demonstrated that Cu(II) and titanium ions were strong attractants for Pseudomonas.⁵¹  Detection or demonstration of bacteria associated with corrosion is not diagnostic for MIC.

Pope completed a study of gas pipelines to determine the relationship between the extent of MIC and the levels/activities of SRB.⁵²  He concluded that there was no relationship. Instead he found large numbers of APB and organic acids, particularly lactic acid, and identified the following metallurgical features in carbon steel:

• large craters from 5 cm to 8 cm or greater in diameter surrounded by uncorroded metal (Figure 6)

• cup-type hemispherical pits on the pipe surface or in the craters (Figure 7)

• striations or contour lines in the pits or craters running parallel to the longitudinal pipe axis (rolling direction) (Figure 8)

• tunnels at the ends of the craters also running parallel to the longitudinal axis of the pipe (Figure 9)

Pope reported that these metallurgical features were “fairly definitive for MIC.”⁵²  However, the author did not advocate diagnosis of MIC based solely on pit morphology. Subsequent research has demonstrated that these features can be produced by abiotic reactions⁵³  and cannot be used to independently diagnose MIC.

Analyses for corrosion product chemistry can range from simple field tests to mineralogy and isotope fractionation. Field tests for solids and corrosion products typically include pH and a qualitative analysis for the presence of sulfides and carbonates. A drop of dilute hydrochloric acid placed on a small portion of the corrosion product will indicate the presence of carbonates if noticeable bubbling occurs. If a rotten egg smell is present following acid treatment, sulfides are present in the corrosion product. Sulfides can be verified by exposing a piece of lead acetate paper to the acidified corrosion product and watching for a color change from white to brown.

Elements in corrosion deposits can provide information as to the cause of corrosion. Energy-dispersive x-ray analysis (EDS) coupled with SEM can be used to determine the elemental composition of corrosion deposits. Because all living organisms contain ATP, a phosphorus peak in an EDS spectrum can be related to cells associated with the corrosion products. Other potential sources of phosphorus, e.g., phosphate water treatments, must be eliminated. The activities of SRB and manganese-oxidizing bacteria produce surface-bound sulfur and manganese, respectively. Chloride is typically found in crevices and pits and cannot be directly related to MIC. There are several limitations for EDS surface chemical analyses. Samples for EDS cannot be evaluated after heavy metal coating; therefore, EDS spectra must be collected prior to heavy metal coating. It is difficult or impossible to match spectra with exact locations on images. This is not a problem with the ESEM because nonconducting samples can be imaged directly, meaning that EDS spectra can be collected of an area that is being imaged by ESEM. Little, et al., documented the changes in surface chemistry as a result of solvent extraction of water, a requirement for SEM (Table 2).⁴⁵  Other shortcomings of SEM/EDS include peak overlap. Peaks for sulfur overlap peaks for molybdenum and the characteristic peak for manganese coincides with the secondary peak for chromium. Wavelength dispersive spectroscopy can be used to resolve overlapping EDS peaks. Peak heights cannot be used to determine the concentration of elements. It is also impossible to determine the form of an element with EDS. For example, a high-sulfur peak may indicate sulfide, sulfate, or elemental sulfur.

Table 2.

Weight Percent of Elements Found on Commercially Pure Copper Surfaces After Exposure to Estuarine Water for 4 Months and Sequential Treatment with Acetone and Xylene⁴⁵ 

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McNeil, et al., used mineralogical data determined by x-ray crystallography, thermodynamic stability diagrams (Pourbaix), and the simplexity principle for precipitation reactions to evaluate corrosion product mineralogy.⁶¹  They concluded that many sulfides under near-surface natural environmental conditions could only be produced by microbiological action on specific precursor metals. They reported that djurleite, spinonkopite, and the high-temperature polymorph of chalcocite were mineralogical fingerprints for the SRB-induced corrosion of copper-nickel alloys. They also reported that the stability or tenacity of sulfide corrosion products determined their influence on corrosion.

The stable isotopes of sulfur (³² S and ³⁴ S), naturally present in any sulfate source, are selectively metabolized during sulfate reduction by SRB and the resulting sulfide is enriched in ³² S.⁶³  The ³⁴ S accumulates in the starting sulfate as the ³² S is removed and becomes concentrated in the sulfide. Little, et al., demonstrated sulfur isotope fractionation in sulfide corrosion deposits resulting from activities of SRB within biofilms on copper surfaces.^64 32 S accumulated in sulfide-rich corrosion products and ³⁴ S was concentrated in the residual sulfate in the culture medium. Accumulation of the lighter isotope was related to surface derivatization or corrosion as measured by weight loss. Use of this technique to identify SRB-related corrosion requires sophisticated laboratory procedures.

• The following are required for an accurate diagnosis of MIC: a sample of the corrosion product or affected surface that has not been altered by collection or storage, identification of a corrosion mechanism, identification of microorganisms capable of growth and maintenance of the corrosion mechanism in the particular environment, and demonstration of an association of the microorganisms with the observed corrosion. Three types of evidence are used to diagnosis MIC: metallurgical, chemical, and biological. The objective is to have three independent types of measurements that are consistent with a mechanism for MIC.

• It is essential in diagnosing MIC to demonstrate a spatial relationship between the causative microorganisms and the corrosion phenomena. However, that relationship cannot be independently interpreted as MIC. Pitting caused by MIC can initiate as small pits that have the same size and characteristics of the causative organisms. These features are not obvious to the unaided eye and are most often observed with an electron or atomic force microscope. MIC does not produce a macroscopic, unique, metallographic feature. Metallurgical features previously thought to be unique to MIC, e.g., hemispherical pits in 300 series stainless steel localized at weld or tunneling in carbon steel, are consistent with some mechanisms for MIC, but cannot be interpreted independently. Bacteria do produce corrosion products that could not be produced abiotically in near-surface environments, resulting in isotope fractionation and mineralogical fingerprints. The result is corrosion where none could be anticipated based on the composition of the bulk medium, e.g., low-chloride waters, and corrosion rates that are exceptionally fast. Development of sophisticated genetic and imaging techniques has made it possible to more accurately characterize microorganisms and their spatial relationships to corrosion products and localized corrosion. However, the requirements for diagnosing MIC have not changed.