Why do I sometimes detect heavy microbial contamination but no evidence that it is causing problems to my fuel system?
Explanations that I’ve provided in the last three articles provide some of the answers to this question. In this post I’ll address another issue – microbial activity. The various microbiological test methods I’ve described in this blog series have provide information about either whether microbes are present or what sorts of microbes are present. General culture tests and rapid methods determine whether microbes are present (see Parts 12, 13, 14 ). Typically, the raw data are assigned attribute scores – negligible, moderate or heavy contamination. This information is sufficient for routine condition monitoring. Selective growth media, enzyme-linked immunoabsorbent assays (ELISA – See Part 16) and genomic tests (see Part 17detect types of microbes (bacteria versus fungi, acid producers, sulfate reducers, etc.). Genomic testing can identify the types of microbes that are present more accurately and precisely that other methods can. However, none of these methods provide information about what microbes are doing.
Although methods can help determine what microbes are doing exist, they require more technical expertise than the previously mentioned tests. Moreover, the cost per test is still quite expensive ($500 to $1,000 per test). However, these emerging methods will be the tools we microbiologists will use to answer the question: “Why do I sometimes detect heavy microbial contamination but no evidence that it is causing problems to my fuel system?” and its complementary question: “Why do I sometimes observe substantial evidence of biodeterioration, but detect negligible to moderate microbial loads?”
Proteomics – the study of proteins
Proteins are long chains of amino acids. Proteins in cells are either enzymatic or structural. Enzymes are large protein molecules that function as cells’ machinery. The receive raw materials (i.e., nutrients) and produce products (i.e., cell building blocks). Proteomics uses analytical tools to determine what proteins are present in the sample. Each type of protein is only produced when the gene(s) that code for it are active. So, proteomics tells use which genes as active and which aren’t. This information can provide important clues as to what fuel system conditions might cause a nominally benign population to become aggressive.
Metabolomics – the study of what cells produce
As noted above, enzymes produce metabolites. Some metabolites are used to build new cells, others are used to maintain healthy, living cells, and many are excreted into the environment as waste products, signal molecules (this is how cells communicate) or external functional molecules (for examples include biosurfactants and extracellular polymeric substance – EPS, biofilm matrix). Metabolomic testing attempts to identify all of the metabolites produced by a microbial community. Indirect biodeterioration is caused by reactions between metabolites and the environment (i.e., fuel, fuel additives, and fuel system surfaces – in contrast, direct biodeterioration occurs when microbes use fuel or fuel additives as food). Metabolomics promises to tell us whether contaminant populations are producing metabolites that contribute to biodeterioration.
How do these omic tests help me answer my questions about the relationship between bioburden and biodeterioration?
Figure 1 illustrates the relationship among different types of microbiological tests. Each more sophisticated technology provides more detailed information about what is going on in the infected system.
In some respects, this is like zooming in using satellite imagery (figure 2). The high-altitude image (figure 2a) confirms that there is a land mass west of the Atlantic Ocean. This is analogous to microbiological tests used for routine condition monitoring. The next lower altitude image (figure 2b) shows that there are cities on this land mass. This is similar to the information obtain from genomic testing. Zooming in further, we see the general street layout of a city (Manhattan, NY in figure 2c). Knowing the street layout is similar to knowing which genes are active. As we approach ground level (figure 2d) we can see that the small dark spot just above the map pin in figure 2c is actually a reservoir (the Jacqueline Kennedy Onassis Reservoir) that is bordered by a path. Like metabolomic data, this image provides clues as to how the city functions.
State of the Art
We know that not all microbial contamination poses the same risk, but we don’t know why some populations cause more damage or cause damage more aggressively than others.
Before 2010, there were few reports of genomic tests on fuel system samples. The few pre-2010 studies depended on culture testing to recover microbes for genomic testing. Consequently, our understanding of fuel microbiology was based on culture test results. During the past decade, microbiologists have exploited genomic test methods to better understand the types of microbe present in fuel systems and the relative abundance of different types of microbes in a given population (microbiome). Methods for performing proteomic and metabolomic tests on fuel and fuel associated water samples are in development. It will be several more years before these methods can be used with confidence. These methods promise to tell us why sometimes microbial contamination is a greater problem than it is at other times.
Because we do not yet have a full understanding of the relationship between bioburden levels (i.e.: negligible, moderate and heavy) and biodeterioration risk, we set conservative limits. The expense of acting when moderate or heavy microbial contamination is detected is a fraction of the cost of failing to control microbial contamination adequately. A colleague once estimated that the cost of taking a commercial aircraft out of service and disinfecting its fuel system was approximately $2 million U.S. What’s the cost of an aircraft falling out of the sky after fuel can no longer reach the engine? The relationship is similar for land-based emergency generator systems. Corrective maintenance actions to control microbial contamination typically cost between $500 U.S. and $2,000 U.S. When emergency generators fail to operate, the cost can easily exceed $100,000 U.S./min – not to mention the potential for catastrophic loss of lives (hospitals), equipment (nuclear power plants), or both.
The relationship between microbial contamination and fuel or fuel system damage is variable. BCA’s Microbial Audit collects climate, engineering, maintenance, and different types of test data (gross observations, physical, chemical, and microbiological) in order to assess given fuel system’s biodeterioration risk. As I observed at the beginning of this post, sometimes I find heavy microbial loads but no evidence of damage. At other times, even though microbiological tests are negative, the other results indicate severe biodeterioration is occurring. Until we have sufficient proteomic and metabolomic data from which to develop better diagnostic models, the prudent approach will be to continue to rely on the existing control limits recommended in guidance documents such as the Energy Institute’s Guidelines for the Investigation of the Microbial Content of Liquid Fuels and for the Implementation of Avoidance and Remedial Strategies and the International Air Transportation Association’s Guidance Material on Microbiological Contamination in Aircraft Fuel Tanks. A third document – Guidelines on Detecting, Controlling, and Mitigating Microbial Growth in Oils and Fuels Used at Power Generation Facilities (Energy Institute) – is in press. I’ll share details once the document has been published.
For more details about understanding the relationship between microbiology test data and fuel or fuel system biodeterioration, please contact me at either email@example.com or call 609.306.5250.