Membrane Lipids

Membrane lipids and their associated fatty acids are particularly useful biomarkers of the microbial community as they are essential components of every living cell and exhibit a large structural diversity coupled with a relatively high biological specificity.

The use of these compounds to identify microorganisms in situ is particularly appealing, since the same compounds are used extensively in bacterial taxonomy and hence there is a constantly growing database that can be used to interpret biomarkers. In addition, phospholipids are not found in storage products and are thought to be present only in viable microorganisms, because they are associated with the membranes of living cells and are believed to break down rapidly when the cells die. However, while Petersen et al. (1991) found a reduction in phospholipids during chloroform fumigation, this reduction was only 21-54% of their concentration before fumigation, indicating incomplete destruction of the phospholipid after cell death (supporting the findings of Tollefson and McKercher (1983)), although the authors speculated on the possibility that the chloroform did not kill all of the cells.

The PLFA technique involves extracting lipids from the soil with organic solvents based on the protocol reported by Bligh and Dyer (1959), followed by the separation of phospholipids from other lipids according to their polarities using solid phase extraction. The phospholipid fatty acids are then converted to fatty acid methyl esters (FAMEs), which are analyzed by gas chromatography in order to determine the types present and the quantities of each.

The PLFA extraction is time consuming and does not lend itself to practical environmental monitoring. In contrast to PLFA, a simpler method based on the direct extraction of fatty acids (MIDI 1995) can be used, which was originally designed to extract fatty acids and identify pure cultures of bacteria. In this method, the microbial cells in the soil are saponified by heating them in a strong aqueous alkali. Several studies have compared the MIDI and PLFA methods (Petersen et al. 2002; Steger et al. 2003; Drenovsky et al. 2004) and found that, although both extraction methods are able to differentiate between microbial communities that have undergone contrasting treatments, the MIDI method included a significant background of nonmicrobial material. Because of this concern, a less harsh method for the direct extraction of ester-linked fatty acid (ELFA) from soil has been developed, where a mildly alkaline reagent is used to lyse cells and release fatty acids as methyl esters from lipids. This method has been evaluated and successfully used to evaluate microbial communities in heavy metal polluted soils (Hinojosa et al. 2005).

Changes in fatty acid profiles are generally related to variations in the abundances of microbial groups. Thus, although analyzing fatty acids from soil does not permit detection at the species level, it can give an overall picture of the community structure and provide an estimate of overall changes.

The total amount of fatty acids has been used to assess changes in the microbial biomass in heavy metal polluted soils (Frostegard et al. 1991; Pennanen et al. 1996;

Hinojosa et al. 2005), as good correlations have generally been found between the total amount of phospholipids and the microbial biomass determined by other methods.

Species richness, evenness, and usually the Shannon-Weaver diversity index have also been calculated from fatty acid data for soil affected by metal pollution. These data can provide information on broad-scale changes in relative abundances and the dominance of certain microbial groups due to heavy metals. However, it cannot be used to measure species or genetic diversity. On the other hand, although a marker fatty acid may be abundant in one group of organisms, its concentration is often variable, making biomass calculations difficult. Moreover, some fatty acids used as specific markers for one group of organisms may occur in other groups in variable concentrations (Zelles 1997). For example, monounsaturated fatty acids (MUFAs) can occur in both Gram-negative and Gram-positive bacteria, but their relative contributions to the total fatty acid content in Gram-positive bacteria are typically very small. Thus, MUFAs can be used as general biomarkers for Gramnegative bacteria (Ratledge and Wilkinson 1988). On the other hand, since the outer membranes of Gram-negative bacteria are largely composed of lipopolysaccha-rides, which consist mainly of hydroxy-substituted fatty acids (OHFAs), it has been suggested that OHFAs could be used as a general indicator for Gram-negative bacteria in environmental samples. However, we should note that these fatty acids have also been found in Gram-positive bacteria, fungi, and plants (Zelles 1997). Different stress conditions, including heavy metal toxicity, have increased the abundance of Gram-negative bacterial fatty acids, and concomitantly decreased those in Gram-positive bacteria (Frostegard et al. 1993; Hinojosa et al. 2005). The enhanced survival of Gram-negative bacteria under stress conditions may be attributed to the presence of cyclo fatty acids in their membranes (also used as markers) and their outer lipopolysaccharide layers, which can resist the stress better. Furthermore, Gram-negative bacteria are considered to be fast-growing microorganisms that utilize a variety of C sources and can adapt quickly to a variety of C sources and environmental conditions (Ponder and Tadros 2002). Evidence for a similar shift in the response of the bacterial community to metal pollution has been found in studies reported by Hiroki (1992) and Frostegard et al. (1993).

However, an increase in the fatty acids commonly found in Gram-positive bacteria has also been observed in acidified soil polluted with heavy metals (Pennanen et al. 1996).

Bacterial "biomass" has been estimated by combining several fatty acid markers of both Gram-positive and Gram-negative bacteria (Frostegard and Baath 1996), whereas polyunsaturated fatty acids (represented mainly by 18:2w6,9c) are associated primarily with fungi (Guckert et al. 1985).

In general, fungi appear to be more tolerant to heavy metals than bacteria (Doelman 1985; Frostegard et al. 1993). Nevertheless, a fungal marker decrease has been reported in field studies such as those of Pennanen et al. (1996) and Hinojosa et al. (2005). In the study of Pennanen et al. 1996, an assumption that fungal biomass was reduced due to heavy metal pollution was supported by microscopic measurements of fungal lengths and ergosterol content. The decrease in fungal PLFAs was partially explained by Cu, a common fungicide. Additionally, branching organisms are associated with larger pores and aggregates, which could make them more vulnerable to the soluble fractions of metals. Another factor is that the contact of hyphae with the metal pollutant likely affects the whole organism and thus a large biomass. This decrease in the amount of 18:2w6,9 was also attributed to a decrease in ectomycorrhizal hyphae, which in turn could be linked to damage to the fine roots because of pollution, as found by Helmisaari et al. (1995). These discrepancies in the effects of metals on fungi may also be explained by differences between field and laboratory studies (Rajapaksha et al. 2004).

The fatty acid 16:1w5c, known to be a major component of arbuscular mycor-rhizal fungi (Haack et al. 1994), has also been proposed as a valuable biomarker. However, this fatty acid is also produced by a select group of bacteria that includes Cytophaga, Flavobacterium, and Flexibacter. This fatty acid has been reported to decrease in response to heavy metal pollution (Frostegard et al. 1993; Hinojosa et al. 2005) and to increase after performing several types of restoration method (Frostegard et al. 1993; Hinojosa et al. 2005). Thus, 16:1w5c appears to be particularly responsive to environmental changes, and may be a good indicator of changes in microbial community structure.

The fungal-to-bacterial ratio can be determined directly from measurements of fungus-specific and bacterium-specific fatty acids, and has also been used as an index of the relative abundances of these two main groups of microbial decomposers in polluted soils (Frostegard and Baath 1996; Hinojosa et al. 2005).

The fatty acids 10Me16:0, 10Me17:0 and 10:Me18:0 are relatively common among studied species of Actinomycetales (Kroppenstedt 1992), and have been used as a marker for this group of microorganisms. However, results in the literature indicate that different actinomycetes respond differently to elevated heavy metal levels (Hiroki 1992). Despite the branching nature of actinomycetes, which could make them more susceptible to heavy metals, their responses to heavy metal pollution can vary greatly according to the soil type and the particular type of pollution, as reflected in the mixed response of this microbial group in studies performed so far.

The PLFA composition of microorganisms is also known to vary to some degree in response to environmental conditions such as chemical stress (Vestal and White 1989; Haack et al. 1994). The isomerization of cis-unsaturated fatty acids (16:1w7c, 18:1 w7c) to trans-unsaturated fatty acids (16:1 w7t, 18:1 w7t) is one such adaptation mechanism that is induced by environmental stress (Guckert et al. 1985). In pure culture studies, the trans/cis ratio of unsaturated fatty acids exhibited a strong increase at toxic metal concentrations (Heipieper et al. 1996). Similarly, in soil incubation studies, an increase in the trans/cis ratio of 16:1w7 in the presence of different metals has been documented (Frostegard et al. 1993). The mode of action of heavy metals is still not understood, but they seem to interact with the microbial membrane fatty acids, disturbing their conformations. Thus, for example, the initiation of the cis/trans isomerization system in response to the heavy metal allows microorganisms to counteract stress because the irans-unsaturated fatty acids are more stable than their cis counterparts.

Cyclopropyl fatty acids have also been shown to increase relative to their monoenoic precursors during prolonged stationary growth phases of some bacteria, and during growth under low carbon and oxygen concentrations, low pH, and high temperature (Guckert et al. 1985; Ratledge and Wilkinson 1988). Thus, increases in cy17:0 and cy19:0 relative to their respective metabolic precursors (16:1w7c and 18:1 w7c, respectively) may indicate physiological stress due to heavy metal pollution (Frostegard et al. 1993). The transformation of cis double bonds into a cyclopropane ring restricts overall mobility, which helps to reduce the impact of environmental stress on membrane fluidity.

Given the caveats mentioned above regarding the interpretation of fatty acid markers, whole fatty acid profiles are generally compared among samples using multivariate statistical techniques. These comparisons reflect differences in community composition due to different types and degrees of perturbations such as elevated levels of heavy metals. Various ordination techniques (e.g., principal components analysis, correspondence analysis, nonmetric multidimensional scaling) have been used to identify structure in the data set and to test hypotheses about both the structure and the underlying environmental variables related to this structure. These multivariate statistics have discriminated shifts in microbial community structure in soils polluted with metals (e.g., Frostegard et al. 1993; Hinojosa et al. 2005). The advantages and limitations of each approach should be considered when selecting the most appropriate statistical techniques (Rencher 2002).

Body Detox Made Easy

Body Detox Made Easy

What exactly is a detox routine? Basically a detox routine is an all-natural method of cleansing yourbr body by giving it the time and conditions it needs to rebuild and heal from the damages of daily life and the foods you eat and other substances you intake. There are many different types of known detox routines.

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