Characterization of microbial communities in lake ediments and peat samples using phospholipid fatty acid analysis

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CHARACTERIZATION OF MICROBIAL COMMUNITIES IN LAKE SEDIMENTS AND PEAT SAMPLES USING PHOSPHOLIPID FATTY ACID ANALYSIS

Adesanoye Isaac MSc Thesis Environmental Biology Department of Environmental Science Faculty of Science and Forestry University of Eastern Finland, Kuopio

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UNIVERSITY OF EASTERN FINLAND, Faculty of Science and Forestry

Department of Environmental Science, Environmental Biology Programme (EnvBio)

Adesanoye Isaac: CHARACTERIZATION OF MICROBIAL COMMUNITIES IN PROFILES OF LAKE SEDIMENT AND PEAT SAMPLES USING PHOSPHOLIPID FATTY ACIDS Master of Science thesis-43 pages

Supervisors: Christina Biasi (PhD) and Promise Mpamah (MSc) May, 2015

………...

Keywords: Phospholipid fatty acids; Fatty acid methyl ester; Soil; Sediment; Methanolic HCl;

Methanolic KOH; Microbial biomass ABSRACT

Phospholipid fatty acids (PLFAs) analysis were used to estimate microbial biomass and community structure in peat samples and lake sediments in Central and Southern Finland, respectively. The first study site (Lakkasuo) is a boreal peatland complex that was drained in 1961 to investigate the long-term effects of water-level drawdown, and the second study site (Alinen Mustarjärvi) is a nutrient-poor mesohumic lake that mixes from top to bottom during one mixing period each year.

PLFAs are essential component of microbial cellular membrane, making up relatively constant proportion of the microbes under natural conditions, and their fingerprints provide insight into microbial biomass and community structure of important bacterial and fungal species. PLFA extraction methods are not standardized and differ among published studies. Researchers have used either acid-catalyzed or base-catalyzed or a combination of both methods during the methylation stage, and there is the possibility that each method could produce different results.

The objectives of this study were to profile microbial communities in peat samples and lake sediments profiles, study their response to water-level drawdown (WLD) in peatlands, and to compare the two variants of extraction methods used.

Particularly, sampling depth had significant effect on all microbial communities. Generally, bacteria dominated in the upper surface layers of peat soil, and fungi were among the microbial groups with low relative abundance. Hydrology seemed to have limited influence on the

microbial community in peat soil. The monounsaturated fatty acids (MuFAs) predominated in peat surface layers, meanwhile saturated fatty acids (SaFAs) predominated in lake sediment. This

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distribution is probably due to prevalent oxic condition, and high carbon availability at peat surface profiles, and anoxic conditions coupled with high primary productivity in surface lake sediments which favour the growth of microbes. Additionally, there was no significant difference between the acid-catalyzed and base-catalyzed methylation methods used, however, the methods may differ with respect to how certain PLFAs eluted.

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ACKNOWLEDGEMENTS

This study was conducted at the Department of Environmental Science in the University of Eastern Finland, Kuopio.

I am sincerely grateful to my supervisor Christina Biasi (PhD) for her sacrifice, understanding, suggestions, and constructive criticisms for the completion of this master’s thesis. I will forever be grateful for the role you played.

I would like to thank Promise Mpamah (MSc.) for his assistance in the laboratory work and analysis of the results. You did more than enough and I sincerely appreciate your effort. I am also grateful to Prof. (Rtd.) Pertti Martikainen, Narasinha Shurpali (PhD), Jenie Gil, Saara Lind, and all in the biogeochemistry research group for your assistance and support during my study period in Finland.

My sincere appreciation goes to my family members, friends, here and abroad, and all well- wishers for your moral, social, and financial supports. Thank you all.

Finally, I am thankful to God Almighty for His love, protection and strength throughout my study period in Finland.

Sincerely grateful Adesanoye Isaac May, 2015 Kuopio, Finland

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ABBREVIATIONS

AMF Arbuscular mycorrhiza fungi BrFA Branched fatty acid

DNA Deoxyribonucleic acid FAME Fatty acid methyl ester MOB Methane oxidizing bacteria MuFA Monounsaturated fatty acid PCR Polymerase chain reaction PLFA Phospholipid fatty acid RNA Ribonucleic acid SaFA Saturated fatty acid TgYr^-1 Teragram per year WLD Water-level drawdown

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Peatlands remain a major reservoir of the world’s terrestrial organic carbon store covering about 3 % of the earth’s terrestrial surface, and this carbon store represents about one-third of global soil carbon (Rydin and Jeglum, 2006). Currently, the rate at which organic carbon is piling up in peatlands is approximately 96 TgYr^-1(Dean & Gorham, 1998). The anoxic conditions coupled with high acidity, limited nutrient, and cold environment generally slows down soil microbial activity and as a result, the rate at which organic matter breaks down in peatlands is very slow (Freemanet al., 2001).

However, peatlands do not only act as carbon store but also releases carbon into the atmosphere in form of carbon dioxide and methane (Gorham, 1991). Particularly, land use activities create imbalances in the nature of peatlands. For example, drainage has been found to increase the rate at which organic matter breaks down thereby enhancing carbon dioxide emissions, and affecting soil carbon pool (Peltoniemi, 2010).

The amount of organic carbon that is accumulating in lakes worldwide is approximately 42 TgYr^-1, and a large percentage of this carbon store is produced by phytoplanktons and aquatic macrophytes. Lake sediments are good repository of organic carbon because lakes tend to incorporate organic carbon into their sediments; therefore anaerobic break down of organic material is not uncommon in eutrophic lake sediments (Dean & Gorham, 1998; Blackburn, 1991). Availability of organic matter in sediments can be highly influenced by depth. For example, if the lake is deep, organic matter travelling through the water column will be thoroughly decomposed before they eventually settle down at the bottom of the lake. Therefore, availability of organic carbon is greater in shallow lakes than deep ones, and this in turn affects the size of the microbial biomass (Suess, 1980)

Peat deposits and lake sediments are important sites for the production of greenhouse gases due to activities of microorganisms (Bridghamet al, 1995; Liikanen, 2002). Microorganisms play crucial role in regulating the biogeochemical cycle, especially nutrient cycling, disintegration of organic matter, and soil formation (Garbevaet al, 2004). The challenge in microbial ecology lies in the identification of microbes, understanding their functioning and their behavioral pattern, and their interaction with each other and their environment (Rastogi & Sani, 2011). Although,

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certain soil microbes could be counted by direct microscopy, a lot of microbes have not been succesfully isolated and cultured. The normal culture method consumes time and does not provide sufficient information about the functionality, biomass, and structure of the microbial community (Whiteet al, 1993). This method also tends to show preference to a particular group of microorganism with respect to genetic diversity (Rastogi & Sani, 2011), due to selective culture conditions.

Cultivation independent methods such as DNA (Deoxyribonucleic acid)/RNA (Ribonucleic acid) sequencing and PLFAs have wider coverage for characterizing microbial community in soil samples. The basic mechanism behind DNA/RNA sequencing is polymerase chain reaction (PCR). This technique has the capacity to detect and amplify DNA/RNA segments that are unique to specific organism. The major advantages of this method are that it breaks the barrier of genetic diversity by identifying specific genetic constituent associated with a particular

microorganism, and can detect organisms with very low number in a sample. However, the disadvantages of this method are that the DNA strands could be easily adulterated by adulteration extraneous substances, fore-knowledge of sequence data is essential before developing primers, and primers are prone to biases during annealation (Bodelieret al, 2010;

Garibyan & Avashia, 2013).

PLFA analysis is a culture independent method for determining the structure of microbial community. Certain PLFAs are characteristics of specific functional groups of microbes which live in terrestrial and aquatic ecosystems. An advantage is that phospholipids are known to degrade rapidly after cell death and therefore represent living microbial community in soils (Whiteet al, 1993). PLFA analysis has advantage over other culture independent methods because it is quantitative and provides estimates with respect to viable biomass, structure and nutritional status of the microbial community. However, it provides limited information about microbial population species (Whiteet al, 1993).

Previous studies have used different PLFA extraction methods with slight variation in the final result from the different methods (Liu, 1994; Carrapiso & Garcia, 2000). The main difference in these methods is revealed in the methylation stage of the PLFA extraction. A lot of the studies have used either acidic or basic methylation or both (Chowdhury & Richard, 2012). This study investigated the use of PLFA to profile whole microbial community in peat samples and lake

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sediment comparing the two variants of modified Bligh and Dyer PLFA extraction method (White et al., 1979), which are acid-catalyzed or base-catalyzed extraction methods. By doing that, it compared two PLFA extraction methods which varied only in the methylation procedure, to see which affected the results more. Bligh and Dyer (1959) used a mixture of non-polar solvent (chloroform, methanol, and water) to extract lipids. This method was later modified by (White et al., 1979) using a single phase extraction of buffer, methanol, and chloroform in the ratio 0.8:2:1 (v/v/v). This way, if a soil sample is shakened with the single phase extractant, the lipids are dissolved and could easily be separated from the soil sample. I compared the microbial biomass/diversity of peat surface layer with that of lake sediment of about the same depth and investigated the effect of peat hydrology (drainage) on the microbial community composition.

Additionally, microbial fatty acid grouping was used in this study because fatty acids used to determine microbial biomass vary from those which describe the community structure.

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2.0 LITERATURE REVIEW 2.1 Peatlands

2.1.1 General characteristics

Peat is dead organic matter formed by accumulation of partially decomposed plant materials under anaerobic and water-saturated conditions (Jackson & Jackson, 2000). Peat formation is possible only when the amount of organic matter that is piling up is greater than the amount that is decomposing, and this phenomenon is largely controlled by varying climatic conditions of water and temperature. Peat formation, development and features are also influenced by a number of edaphic and biological factors such as soil microbes and nutrient availability (Franzen, 2006). The residues of dead plants and animals in peat remains undecomposed for many years because of the hydrological and anoxic conditions of the soil which tends to slow down microbial degradation of organic matter. The process of peat formation takes a long time, and it takes about 10 years before 1cm of peat could be formed (Kamal & Varma, 2008). Peats pile up to form peatlands because there is no balance between microbial decomposition and total primary production by plants. The former is as a result of plant tissues that resists microbial activities, availability of low nutrient, low pH, low temperature, and water saturation. These imbalances in the peat profile create an environment that is devoid of oxygen and as such slows down microbial metabolism (Jackson & Jackson, 2000).

Peat is made up of solid particulate matter as well as liquid and gaseous compounds under natural conditions. The solid portion comprises largely organic, but also mineral matter. The mineral matter may contain materials transported by water or wind into the peat during the process of proliferation, or by materials formed by partially decayed vegetation. The organic matter is the major component of the solid part and it is made up of humus and partially decayed vegetation. Peat must contain above 50% organic matter before it could be regarded as peat, although there are diverse opinions about the actual percentage of organic matter in peat (http://www.eolss.net/sample-chapters/c08/E3-04-06-01.pdf).

Peatlands can be classified as bog (ombotrophic) or fen (minerotrophic) based on nutrient composition. Bogs are poor in nutrient because they do not have enough access to groundwater but receives nutrients mainly from precipitation and fog. They are usually dominated by

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Sphagnum spp, shrubs, and sometimes trees, provided there is a long duration of low water table on the soil surface.Sphagnum spp are the major reason why organic matter piles up in bogs because they are partially decomposed, thrive under ombrogenous and anaerobic conditions, and their leaves produce acids. This creates a very acidic environment for bogs (NWWG, 1997). On the other hand, fens are rich in nutrient and are connected to the groundwater and surface water.

They have higher nutrient concentrations and pH compared to bogs. Fens that are situated in hydrological environment with very low dissolved minerals are nutrient-poor fens (Oligotrophic fens) and such fens are dominated bySphagnum spp and shrubs while fens that are located in environments with higher concentrations of dissolved minerals are nutrient-rich fens

(mesotrophic fens) and are dominated by sedges and brown mosses (NWWG, 1997).

2.1.2 Microbial composition of peat

Previous studies based on cultivation methods have been able to identify a broad range of bacteria and fungi in peatlands. This list include;Cytophaga, Pseudomonas, Bacillus, Actinomyces, Mycobacteruim, Clostridium, Nocardia, Micrococcus, Micromonospora, Achromobacter, and Chromobacterium. The fungi species includeTrichoderma, Mucor, Mastigomycotina, Cladosporium, Penicilliumetc. (Williams & Crawford, 1983). However, modern molecular methods have been able to provide wider coverage of microbial diversity in peatlands. Peatlands have a wide variety of microorganisms, and this difference in microbial composition is a function of how these microbes have been able to develop physiological and metabolic strategies to adapt to the prevailing environmental conditions in these wetlands. These conditions may include; temperature, nutrient levels, availability of oxygen, types of

predominant plant community, and pH (Andersenet al, 2013). Furthermore, Peltoniemiet al (2010) reported that depth, nature, hydrological condition of the wetland, and availability of substrate for litter decomposers can also influence the diversity of the microbial community.

Generally, bacteria showed increase in the lower layers of mesotrophic fen and moistest upper layer of bog, while fungi predominated parch regions. This distribution is due to availability of nutrient and oxygen in the fen and bog respectively. Additionally, fungi are very active under aerobic conditions (Thormann, 2006). However, with respect to low water table, Peltoniemiet al (2010) reported that minerotrophic peatland showed an increase in the amount of gram negative

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bacteria in the upper soil layer following WLD. This distribution was linked to oxygen availability in the upper layer of the soil. Jaatinenet al (2006) reported that actinobacteria showed increase in upper dry bog regions and a decrease in the upper layer of nutrient-rich fen, while there is an increase in the proportion of fungi community in the upper layer of nutrient-rich fen but a decrease in the upper surfaces of bog. The distribution of actinobacteria and the fungi community was linked with peat hydrology and decomposition rate.

2.1.3 Effect of drainage on abundance of microbes in peatlands

According to Laiho et al. (2006), the microbial community structure could be highly affected by water-saturated conditions in connection with other factors such as nutrient and oxygen

availability, and litter quality. The level of the water table controls oxygen layers in peat soils.

For example, in soil layers with high water table, the rate at which oxygen diffuses within the soil compartments is very slow compared to air (Silins & Rothwell, 1999). This condition lowers the respiration rate of microorganisms due to limited availability of oxygen, thus anaerobic decomposition of organic materials is slow (Bergman et al., 1999). Aerobic decomposers have been found to be directly affected by high water conditions in low supply of nutrient and lack of oxygen but indirectly by litter quality and vegetation types. However, litter quality has been shown to have the greatest effect on microbial community mostly in fungi (Strakova et al, 2011)

2.2 Lakes

2.2.1 General Characteristics

A lake may be described as a large area of water (usually freshwater) surrounded by land with no direct intrusion from the sea. Sometimes a lake may be cut-off such that it does not have any water inlet to feed it or outlet to drain it, and as such may have high salt content either from evaporation or from groundwater inlets. Lakes may appear in sequence, connected at multiple points by rivers or as a result of an extension in the breadth of a water body along a river pathway. Although, it may be somewhat difficult to differentiate between lakes and rivers, yet

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the major differences are revealed in water circulation patterns between both systems, and in the average time a particular molecule of water remains in a water body (WHO, 1996).

The origin and formation of lakes is diversified, while the vast majority of them are formed by natural agents others are formed by tectonic movements. For example, lakes may be formed by river or wind actions, by glacial or volcanic activity, by marine action or organic matter activity, and by tectonic movements or meteoritic impacts (http://www.eoearth.org/view/article/155066/).

Lakes are broadly classified based on their annual mixing patterns and trophic state. The classification of the former is as a result of climatic condition which is based on thermal stratification and mixing patterns of the lake, while the latter is based on nutrient availability consequent of eutrophication. Thermally stratified lakes are categorized into upper epilimnion (warm, less dense water), middle metalimnion (cold, dense water), and lower hypolimnion (colder, denser water). The annual mixing pattern classifies into amixis (no mixing), meromixis (complete mixing), and holomixis (partial mixing). The trophic level classifies into oligotrophic (low nutrient), mesotrophic (moderate nutrient), and eutrophic (high nutrient) (WHO, 1996).

Lake sediments from nutrient rich lakes usually have high organic and nutrient content because high deposition of organic material is positively correlated with lake nutrient condition.

Conversely, lake sediments from nutrient-poor lakes have low amount of autochtonous carbon.

Lake stratification can also influence the concentration of oxygen and nutrient availability in lake sediments. For example, during summer when there is thermal stratification of nutrient-rich lake, oxygen may be absent or present in low quantity due to this stratification, and this may lead to deposition of hydrogen sulphide in lake sediments. During winter when the lake water is well mixed, oxygen will be available throughout the lake; there will be high primary production and efficient break down of organic material resulting in infusion of considerable amount of nutrient in the sediment (Smetaceket al., 1991; Gu et al., 1996). Organic materials released by planktons (autochthonous) and from terrestrial environments (allochthonous) contribute to the

concentration of phosphorus in sediments and they are subject to physical, chemical, and biological changes in the lake after sedimenting. Studies revealed that under anoxic conditions, phytate is a major source via which phosphorus is released into sediments. Because primary production is relatively small in nutrient-poor lakes, the major channel through which

phosphorus and other nutrients are released into lake sediments are possibly allochthonous (Dean

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& Gorham, 1998; Goltermanet al., 1998). However, Foster & Lees (1998) reported that sorting and reduced concentration of coarse and moderately-sized particulate matter is more crucial to lake sediment average yield than organic matter and phosphorus content.

2.2.2 Microbial composition of lake sediment

Previous studies have revealed that microbial activity in lake sediment is greatly affected by the presence of organic matter and nutrient elements among other factors such as pH and redox potential (Smetacek et al., 1991; Jiang et al, 2006). Organic matter that accumulates at the bottom of the lake can be turned into minerals and gases by microorganisms thereby releasing nutrient into the water body and atmosphere. The physicochemical and biological processes in lake profiles support the diversity of microorganisms by providing suitable habitat that enhance their metabolic activities. Microbial communities from nutrient-rich sediments have been found to display high range of catabolic response to allochtonous carbon sources because of their ability to use different types of substrates, but nutrient-poor lake sediment showed reduced efficiency. Therefore, depending on the nutritional status (oligotrophic, mesotrophic, eutrophic) of inland waters, the sediments may not have the same organic matter content, and as such may have different microbial community (Zenget al, 2008; Torreset al., 2010). Stegeret al., 2011 also reported that the concentration of total phosphorus and seasonal changes can have

significant influence on the microbial community. For example, there was a wide difference in community structure in winter and spring; meanwhile it looks alike in summer and autumn.

However, they added that microbial community composition looks more alike within seasons than within different lakes. Rajendranet al., 1995 revealed that microbial community in lake sediment can also differ with respect to depth as branched fatty acids (BrFAs) belonging to a group of microorganisms were abundant in the surface layer, while MuFAs representing

sedimentary bacteria communities were predominant in the deeper layers. Generally, the activity of bacteria is relatively low in sediments, although a larger percentage of facultative aerobe and anaerobes are active in deeper sediment layers. The fungi community has been found in both upper and deeper sediment layers, and their abundance in the pelagic zone has been connected with their ability to adapt under anoxic conditions. Similarly, Archael dominance has been observed relative to increasing depth in sediments, and their abundance have been linked to

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oxygen availability and pH (Baniulyte et al., 2009; Luo et al, 2005; Molari et al., 2012; Jiang et al., 2006). Recent studies have been able to identify certain groups of bacteria including

Proteobacteria,Actinobacteria,Verrucomicobra, andNitrospirae. The list also includes gram negative bacteria, gram positive bacteria, methane oxidizing bacteria, microeukaryotes, fungi, and archael (Zeng et al., 2008; Steger et al., 2011; Xuan et al., 2011; Haglund et al., 2003).

2.3 PLFAs

2.3.1 Microbial Membrane PLFAs

The fundamental structural constituents of microbial cell are the cell wall, cell membrane, nuclear DNA, and ribosomes. The eubacteria and eukarya has similar chemical membrane content in that they have PLFAs (an ester-type bond joining fatty acids to glycerol) meanwhile archaea has phospholipid ether lipids (an ether-type bond joining branched hydrocarbons to glycerol) (Loreset al., 2010). Cellular membranes of the archaea bacteria do not contain fatty acids in their phospholipids unlike those of true bacteria and eukaryotes, therefore these organisms are not discussed in this study.

The cell membrane is composed of a phospholipid bilayer, and a wide variety of fatty acids which are attached to glycerol with proteins are incorporated in the bilayer. Phospholipid molecules consist of a charged head group and a pair of non-polar fatty acid tails joined by a glycerol linkage. The structure of a phospholipid molecule is based on a glycerol with fatty acids, alcohol, and a phosphate group (Loreset al., 2010; Piotrowska-Seget & Mrozik, 2003).

Fig. 1 Schematic structure of a phospholipid (Freeman et al., 2002)

However, under definite environmental stress conditions, certain membrane lipids may be formed in order to resist the effect of the stress. For example, whenever phosphorus becomes a limiting factor for growth, some bacteria produce membrane lipids (glycolipids, sulfolipids,

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betaine lipids, or ornithine-containing lipids) that do not contain phosphorus. The most prolific types of lipids in most fungi are the triacylglycerols, but their amount differs based on species, developmental stage, and growth conditions. Fungi manufacture both saturated and unsaturated fatty acids with palmitic, oleic, and linoleic as the major saturated, monoenoic, and

polyunsaturated acids respectively (Gunstoneet al., 1994)

The total amount and diversity of PLFAs is a biological tool used as markers of viable microbial biomass and community structure in environmental samples. The cellular membrane of living organisms has PLFAs, and after cell death the phospholipid fraction is hydrolysed by enzymes to liberate the hydrophilic end. The remaining fraction is a diglyceride having similar fatty acid fingerprint as the phospholipid. Thus, fatty acids from both the diglyceride and the phospholipid fractions can be used to evaluate viable microbial biomass (White et al., 1979; Piotrowska-Seget

& Mrozik, 2003). PLFA analysis has been used to estimate the microbial community structure in agricultural soils (e.g. Bossio et al., 1998,), soil and sediments (e.g. Rajendran et al., 1994), and heavy-metal polluted soils (e.g. Baath et al., 1995).

2.3.2 PLFAs as microbial biomarkers

Microbial biomarkers are chemical constituent of microbes and they can be used to identify, measure, and shed light on microbial community biomass. They can be widely divided into two groups namely; General biomarkers and Specific biomarkers. The former measures total

microbial biomass while the later strongly suggests the presence of specific microorganism. For example, palmitic acid which appears in almost all lipids is a general biomarker while certain fatty acids of microbes are specific biomarkers (Salomonovaet al., 2003). There are certain conditions that should be met before a chemical compound could be used as specific biomarker for specific organism. This conditions may include; (1) The ability of the compound to be extracted and analyzed accurately. (2) The compound must be present in an appreciable amount within the microbial cells. (3) The amount of the compound should be just enough or higher to be able to quantify the microbe. (4) It should degrade rapidly in aging and drying cells (Tunlid &

White, 1992). (5) Importantly, the compound should be to a certain extent unique to a specific microbial group. Membrane lipids and fatty acids that are connected to them, e.g. PLFAs, are

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extremely important biomarkers because they are crucial part of all living cells; they are highly varied in structure, and are particularly specific in biological systems (Salomonovaet al., 2003).

Membrane lipids can provide useful information about the structure of the microbial community because the percentage composition of specific PLFAs varies substantially among specific groups of microbes. For example, even though MUFAs may be present in both Gram-negative and Gram-positive bacteria, their percentage composition to the total PLFA in Gram-positive bacteria is very small. Therefore, MUFAs can be used as general biomarkers for Gram-negative bacteria (Ratledge & Wilkinson, 1988). An overview of PLFAs used as biomarkers for specific microbial groups and fatty acid groups are given in tables 2 and 3, respectively. Zelles (1998) also noted that it is important to know the fatty acid composition of individual species of organism in a microbial community in an attempt to analyze the entire community fatty acid profile because a certain fatty acid may be erroneously used as a specific biomarker for a species since its existence has not been studied in other members of the same population. Usually, there are two methods commonly used to study microbial lipids namely; PLFA analysis and Total fatty acid methyl ester (total FAME) analysis (Green and Scow, 2000). PLFA analysis provides estimates with respect to viable biomass, structure and nutritional status of the microbial community whereas Total FAME analysis provides information of all saponifiable lipids (including PLFAs) present in the sample. Total FAME analysis is more productive in situations that require small biomass sample, however PLFA analysis is more satisfactory for studies of viable organisms and provides a steadier base for classifying microbial community composition (Whiteet al., 1993; Green & Scow, 2000).

2.3.3 Esterification and Transesterification of PLFAs

The most common method used for measuring fatty acids in lipid containing biological samples is gas chromatography. Gas chromatography measures volatile methylated fatty acids after the lipid has been derivatized. This process is achieved by the transformation of saponifiable lipids to their corresponding less polar FAMES by adding excess methanol and a catalyst. The process of using methanol to derivatize fatty acids is called methylation (Chowdhury & Dick, 2012).

Methylation occurs when an alcohol breaks an ester bond using an acid or a base as a catalyst.

Catalysts such as methanolic potassium or sodium hydroxide cannot esterify unesterified fatty

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acids but can quickly transesterify lipids at lower temperatures, meanwhile acid catalyst such as methanolic hydrochloric acid can both transesterify complex lipids and esterify unesterified fatty acids (Christie, 1993). However, studies have shown that unesterified fatty acids (belonging to the neutral lipid fraction) could be retained by the silicic acid column during the separation of extracted lipids into neutral lipids, glycolipids and phospholipids. This retention could adulterate the glycolipids and phospholipids that would elute later, and this could affect the efficiency of the methylation procedure. This behavior of the silicic acid column could not be detected in base catalyzed methylation because of its bias towards unesterified fatty acids. But, the unselective nature of the acid catalyzed methylation allows for possible contamination of the glycolipid and phospholipid fractions with unesterified fatty acids (Dickson et al., 2009).

The suitable reaction condition for esterification of carboxylic acids and transesterification of esters during acid catalyzed methylation is excess supply of alcohol and limited supply of water.

This is because water is a stronger electron donor than methanol and as such can result in incomplete esterification process. A number of studies have employed either acid or base catalyzed methylation during PLFA extractions, but there is no explanation to validate the efficacy of these available methods.

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Table 1. The major extraction methods used by various authors to extract fatty acids from environmental samples. (Adapted from Chowdhury and Dick, 2012)

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Table 2:PLFA biomarkers used in this study for microbial taxonomic grouping

Microbial group Related genus/genera Possible biomarkers References Heterotrophic bacteria

Gram-negative bacteria Polynucleobacter sp. 18:1 7c Taipaleet al. 2009 Gram-positive bacteria Micrococcus sp.,

Tetraspaera sp.,

i-14:0, a-15:0, i-15:0, a-

17:0 Taipaleet al. 2009

and Actinobacterium sp.

Methanotrophic bacteria

Type I (MOB I) Methylobacter sp., 16:1 8c, Bowmanet al. 1993;

Methylomonas sp. 16:1 6c Taipaleet al. 2009 Type II (MOB II) Methylosinus sp., 18:1 8c, Bowmanet al. 1993;

Methylocella sp. 18:1 7c Fungi

Fungi (Excluding AMF) Acremonium sp. 18:2 6

Frostegard and Baath 1996

Table 3: PLFA biomarkers used in this study for microbial fatty acid grouping

PLFA/FA Groups

Possible Biomarker PLFAs

Branched fatty acids/BrFA

Sum: i13:0, a13:0, i14:0, i15:0, a15:0, i16:0, i17:0, a17:0, i18:0, i19:0, a19:0

Cyclopropyl fatty acids/Cyclo FA Sum: cyl19:1 Mono unsaturated fatty

acids/MuFA

Sum: 16:1 9, 16:1 8, 16;1 7, 16:1 6, 16:1 5, 17:1, 18:1 8, 18:1 7, 18:1 5

16-MuFA Sum: 16:1 9, 16:1 8, 16:1 7, 16:1 6, 16:1 5

18-MuFA Sum: 18:1 8, 18:1 7, 18:1 5

Saturated fatty acids/SaFA Sum: 14:0, 16:0, 17:0, 18:0, 21:0

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2.4 Objectives of the study

Diverse studies have revealed PLFA patterns in peatlands with much emphasis on relationship between plant community composition and PLFA fingerprints (Borga et al., 1994). Several studies on microbial communities in lake sediments have focused much on microbial activity than diversity (Torres et al., 2010). Additionally, the effect of drainage on microbial community composition has not been sufficiently studied, and there is a need to link microbial diversity with ecosystem functioning. In this study we linked characteristics of different ecosystems with different microbial communities, and emphasis was placed on measuring variation in PLFA composition between the two ecosystems with regard to depth and drainage. Furthermore, we aimed at comparing the effect of PLFA methylation catalyst types used on soil samples.

Thus, the objectives of the thesis were:

To find out the importance of peat hydrology in microbial composition

To use PLFA to profile microbial community in peat and lake sediment profiles

To compare the two variants of modified Bligh and Dyer PLFA extraction methods used

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3.0 MATERIALS AND METHODS 3.1 Research sites and soil sampling

The study sites include a peatland complex (Lakkasuo) and lake sediment (Alinen Mustajarvi).

The peatland complex is located in central Finland (61ô48’N, 24ô19’E, ca. 150 m.a.s.l) with a mean depth of 1.3 m (Laineet al., 2004). Mean annual temperature and precipitation is 3ôC and 700 mmy^-1 respectively (Murphy et al., 2009). About half of the peatland was drained in

1961.The drainage effect could be used to analyze the effects of long-term effects of a

continuous water-level drawdown. The peatland has different plant communities with different nutrient status, and our study was done in the minerotrophic fen site with pH ranging between 5.3-5.9.

Alinen Mustarjavi is a nutrient poor meso-humic lake that mixes from top to bottom during one mixing period each year because of uniform temperature and density throughout the lake. The lake is located in southern Finland having a surface area of 0.7 ha, maximum depth of 6.5 m, and a pH ranging from 5.3-5.8. The amount of macrophytes in the lake is low, and one-third of the shoreline is covered bySphagnum spp. More information about the lake is available in Rask and Arvola (1985).

Three replicates of soil samples were collected at five depths (0-25 cm, 25-50 cm, 50-100 cm, 110-135 cm, 135-160 cm) from the fen site and at four depths (0-2 cm, 2-4 cm, 4-6 cm, 6-8 cm) from Alinen Mustarjavi. Subsamples of the upper 5 cm of the sediment were taken with a syringe for PLFA analysis, and each replicate was well mixed and kept cold and in the dark during transport to the laboratory. The samples were stored at -20^oC prior to PLFA analysis.

3.2 PLFA analysis 3.2.1 Extraction

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Extraction of PLFAs from soil samples was carried out using the modified Bligh and Dyer extraction method (Whiteet al., 1979). About 2 grams (dry weight) of freeze-dried soil was added to 35 mL extraction tubes, and 7.5 mL of chloroform, 6 mL of methanol, and 15 mL of 50 mM phosphate buffer (pH 7.40) were added in the ratio 1:0.8:2 (v/v/v). The samples were mixed thoroughly and closed carefully under nitrogen stream. After shaking overnight at 200 rpm, 500- µL of PC 15:0 internal standard was added and the samples were centrifuged for 15 minutes at 2500 rpm. The supernatant was removed to a decanter glass, and the volume was measured.

Appropriate volumes of chloroform and 50-mM phosphate buffer were added to each sample to get the ratio of chloroform: methanol: phosphate buffer (1:1:0.9; v/v/v). The samples were then transferred into new glass tubes (35 mL), vortexed and centrifuged at 2500 rpm for 5 minutes.

The lower organic phase was collected, and evaporated under a stream of nitrogen. A miniature silicic acid column chromatography was used to separate the total lipid extract into three lipid classes (neutral lipids, glycolipids, and phospholipids). The dried lipid material in the column was dissolved in 100 µL of chloroform, and neutral lipids were eluted with 10 mL of chloroform, glycolipids with 20 mL of acetone, and phospholipids with 10 mL of methanol. The

phospholipid eluate was evaporated under nitrogen flow.

3.2.2 Base catalyzed methylation

The dried phospholipid samples were dissolved in 1 mL of methanol:toluene (1:1, v/v) and 1 mL of freshly prepared 0.2 M methanolic KOH. The mixture was vortexed and heated in an oven (with the lid) at 35^oC for 15 minutes. The samples were allowed to cool at room temperature, and 2 mL of hexane-chloroform (4:1) was added. The samples were neutralized with 1 mL of 1 M acetic acid, and 2 ml of nanopure water. The phases were separated by centrifugation at 2000 rpm for 5 minutes, and the upper hexane layer was transferred to a conical 9 ml test tube. This step was repeated two times more with the addition of 2 mL of hexane-chloroform. The combined hexane fractions were dried under nitrogen stream, and the samples were stored for further analysis.

3.2.3 Acid catalyzed methylation

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The dried phospholipid samples were dissolved in 1 mL of toluene and methylated using 2 mL of freshly prepared methanolic HCl. The samples were shaken to mix the solvent, and the tubes were flushed under nitrogen stream. The samples were incubated overnight at 50^oC on a water bath. After cooling, 2 mL of 2 % KHCO3 and 5 mL of hexane:diethyl ether (1:1, v/v) was added, and the vials were gently shaken. The samples were centrifuged at 1500 rpm for 2 minutes, and the upper organic layer was separated. This step was repeated with addition of 5 mL hexane:

diethyl ether, and the combined hexane fractions were evaporated under nitrogen stream. The samples were then stored for further analysis.

3.2.4 PLFA and FAME analysis and gas chromatography

The residue sample obtained from both methylation methods after drying under nitrogen stream were dissolved in 300µL of hexane, and then transferred to GC-insert for further analysis. FAME standard solutions were prepared, analytical blanks were extracted with each set of sample, and the PLFAs were quantified using GC-MS analysis. The FAMEs were detected using Agilent 7890A GC equipped with Agilent 5975C mass spectrometer. The column used was a DB 5 (30 m *0.25 mm*0.33 µm) capillary column, and Helium was used as the carrier gas. Samples were injected in the splitless mode with an initial oven temperature of 50ôC. The temperature was increased to 140ôC at 30ôC/min, raised to 320ôC at 5ôC/min, and to a final temperature of 320

oC for 20 minutes.

The fatty acids nomenclature are indicated by total number of carbon atoms in the chain, number of double bonds, and the position of the double bond from the methyl end of the molecule.Cis andtrans geometry are designated by suffixesc andt. The prefixesa,i andme represents anteiso,iso, and mid-chain methyl branching, respectively and cy indicates a cyclopropane fatty acids. The peaks of the fatty acids were identified based on their peak retention time. The PLFA biomarkers and microbial group assignments are summarized in tables 2 and 3.

3.3 Statistical analysis

Statistical analysis was conducted with the IBM statistical SPSS 21 for Windows (SPSS Chicago, 2010 IL, USA). Acid and base-catalyzed methylation data were tested using

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independent sample T-test, and microbial and fatty acid group data were tested using Two-way Anova.

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4.0 RESULTS

4.1 Effect of methylation catalyst types on PLFA yield and general trends in PLFA abundance

The total number of PLFAs identified and quantified in the soil sample were 56 all having between 12 to 21 carbon atoms. There was no significant difference in the absolute concentration of both methylation procedures used, although the base catalyzed methylation showed higher standard error margin (Independent sample t-test: p> 0.05, Table 3). Five major microbial groups were identified from the peat soils including gram-positive and gram-negative bacteria, methane- oxidizing bacteria (type I and type II), and fungi (see below for more details). To some extent the base methylation yielded higher absolute concentration of PLFA for all represented microbial groups in natural peat, while acid catalyzed methylation yielded higher in drained peat (Two-way Anova: p> 0.05, Figure 1, surface layer). This pattern was similar over the whole peat profiles, except that there was insufficient data for the base methylation in drained peat. Additionally, the absolute concentration of PLFAs significantly decreased with depth in both natural and drained peat (p< 0.05, Table 3)

Table 3:Comparison of acid and base catalyzed methylation in total PLFA yield of soil samples taken from Lakkasuo peatland. (n=3).

Total amount of PLFAs (µg/gdw) Depth

(cm)

Acid methylation Base methylation

Natural Drained Natural Drained

Mean STDev Mean STDev Mean STDev Mean STDev

0-25 758.26 198.12 682.27 255.92 1029.41 746.85 543.50 340.14 25-50 458.22 98.82 443.19 129.25 431.85 352.76 454.12 168.33 50-100 479.53 182.44 381.69 194.81 571.93 423.24

110-135 390.92 124.04 426.57 141.75 403.95 218.69 135-160 369.31 114.14

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Fig. 1. Comparison of acid and base catalyzed methylation in natural and drained soil. Data show the means of surface peat layers (±SE, n=3).

Table 4.Comparison of peat and sediment surface layer. Total PLFA (µg/gdw), n=3.

Acid Methylation (Peat) Sediment

Depth (cm) Natural Drained

Mean STDev Mean STDev Mean STDev

0-25 758.26 198.12 682.27 255.92 499.10 282.80

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4.2 Total PLFA concentrations of natural and drained peat soil vs. lake sediment including relative abundance of microbial groups and fatty acid groups

Relative concentrations of gram-negative and (MOB) methane oxidizing bacteria (Type I and Type II) were significantly higher in drained than natural peat (Two-way Anova: p<0.05, Figure 2). Similarly, relative concentration of MOB II is higher than MOB I, and gram-positive bacteria dominated fungi in both natural and drained peat (Two-way Anova: p<0.05, Figure 2).

Additionally, relative concentrations of gram-negative and MOB (Type II) was significantly higher in peat (both natural and drained) compared to sediment (Figure 2). Sediment had significantly higher absolute concentration of PLFA per unit mass of sediment at surface layer (Independent sample t-test: p<0.05, Table 4) and for all represented microbial groups when compared with the drained and natural peat (Two-way Anova: p<0.05, Figure 2). However, there was no significant difference (p>0.05) in absolute PLFA concentrations between the drained and natural peat. Comparison of microbial community structures (as well as fatty acid groups, see below) was done only for surface layers of both peat and sediment layers using the acid- catalyzed methylation (Figures 2, 3). Generally, the sediment sample is more similar to natural peat with exception of the MOBs.

A total of 17 MuFAs and 27 SaFAs were recorded in this study from all the soil samples. The MuFAs were unsaturated with a double bond at different carbon positions, while the SaFAs were saturated with a single bond. MuFAs and SaFAs could have straight, cyclic or branched carbon chains. MuFAs are common in gram-negative aerobes, gram-positive, and MOB, while SaFAs are found in anaerobic eubacteria. BrFA are commonly found in gram-positive and gram- negative bacteria.

The relative abundance of drained and natural peat did not differ significantly (Two-way Anova:

p>0.05, Figure 3). However, relative abundance concentrations of PLFA were significantly higher in peat (both drained and natural) for MuFA and BrFA, while SaFA constituted the majority of PLFAs in sediment (Two-way Anova: p<0.05, Figure 3). Again, absolute

concentrations of all distinguished fatty acid groups were significantly higher in lake sediment compared to both natural and drained peat soils (Figure 3).

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Fig. 2. Comparison of total PLFA concentration of major microbial groups in peat and sediment.

Data show mean values of surface layers (±SE, n=3).

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Fig. 3. Comparison of total PLFA concentrations of fatty acid groups in peat and sediment. Data shows mean values of surface layers (±SE, n=3).

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5.0 DISCUSSION

In this study, there is no significant difference in terms of absolute concentration in both the base and acid catalyzed methylation methods used, although the methods may differ with respect to the way certain PLFAs eluted. This is in contrast with the previous studies where it was reported that difference in both methylation methods can significantly affect the concentrations of fatty acids (Chowdhury & Rick, 2012). Acid catalyzed methylation seems to be more efficient because it shows lower margin error compared to base catalyzed methylation. Studies have shown that the former method is not bias during esterification and transesterification processes, it has unreserved capacity to methylate all fatty acids including free fatty acids, fatty acid salts, amides and fatty acid esters (Christie, 1993). For example, it takes unesterified fatty acids from simple lipid form to phospholipid form and methylates them into fatty acid methyl esters by esterification. Whereas, base catalyzed methylation is biased towards unesterified fatty acids in that it does not esterify them and it selectively transesterify ester-linked phospholipids to free fatty acids during hydrolysis. This may lead to loss of phospholipid- derived fatty acid methyl esters (Christie, 1993; Chowdhury & Rick, 2012), or higher variability in the results as shown here.

My results indicated that MuFAs predominated in peat surface layer compared to sediment. This result is consistent with the report of Sundh et al., (1997) that the abundance of MuFAs is possible at peat surfaces and they indicate the presence of aerobic eubacteria. These aerobic bacteria are typical of gram-negative bacteria including the methanotrophs (Type I and type II), and actinobacteria species (gram-positive). Overall, the relative abundance of gram-negative bacteria and MOBs (sum of MOB I and MOB II) was also higher in peat than sediment as shown by the microbial markers (Figure 2). Aerobic bacteria have been found in oxic peat surface layers where they are actively involved in the breakdown of organic materials. They are capable of releasing minerals even from recalcitrant chemical compounds (Dedysh et al., 2006; Given &

Dickinson, 1975; Peltoniemi, 2010). Bossio & Scow (1998) studied a fen site and came up with the report that abundance of MuFAs in peat samples could be linked to substrate containing high concentrations of carbon. Jaatinen et al., (2007) added that peat surface layers are rich in oxygen, and this correlates positively with microbial abundance on peat surfaces. Therefore, the higher MUFA concentration observed at the upper layer of our peat samples suggests the bioavailability

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of organic carbon in upper, vegetated peat layers and the prevailing oxic conditions at the surface layers, even at natural conditions.

The results also showed that the relative PLFA concentration of MOB II is significantly higher than MOB I in peat (Figure 2). Their occurrences have been proven in peat soils with MOB II dominating in ombrotrophic bogs and MOB I in minerotrophic fens (Fisk et al. 2003; Edwards et al., 1998; Hanson & Hanson., 1996). Surprisingly, my result indicated that MOB II is more abundant in minerotrophic fen. Bodelier et al., (2013) tried to link activity of methanotrophs to their abundance in a riparian wetland soil and came up with the findings that although MOB I were active in this soil, MOB II have been found to be more abundant. The ultimate question under recent research is how MOB II remain the most abundant MOB in certain wetland soils yet MOB I is actively dominating (Ho et al., 2013). It appears as if more studies should be directed towards peatland soils in attempt to link the activities of MOB I and MOB II to their abundance.

In our peat soils, fungi were among the microbial groups with lowest relative abundance (Figure 2). This contrasts other studies which have shown that fungi are the major aerobic decomposers in surface layer of peat soils, and their abundance and activities predominates that of bacteria possibly due to their tolerance of low pH (Thormann, 2006; Nilsson & Rulcker, 1992; Williams

& Crawford, 1983). However, studies have revealed that actinobacteria species belonging to the phylum of gram-positive bacteria may have competitive advantage over fungi in a minerotrophic fen with low acidity in peat soils (Peltoniemi., 2010). Perssonet al., (1991) reported that the abundance and activity of the microbial community in a soil ecosystem could be favoured by high pH because increased pH tends to enhance the release of organic materials in a way that microbes could easily utilize them, and as such substrate availability is enhanced under high pH soil conditions. Perhaps, high pH in a nutrient-rich fen favours the abundance of bacteria community compare to fungi, and this could be the reason why our results showed higher relative PLFA concentrations in MOB II, gram-negative and gram-positive bacteria compared to fungi.

Comparatively, relative concentration of SaFA is higher in lake sediment compared to natural and drained peat, and this could be due to high primary productivity in the lake euphotic zone and anoxic conditions prevalent at deeper sediment layers which favour their growth. Studies have revealed that breakdown of organic matter via anaerobic processes is possible in nutrient-

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rich euxinic sediments (Rajendran et al., 1994). Sundh et al., (1997) linked the abundance of SaFAs in peat samples to the presence of mainly gram-positive and gram-negative anaerobic bacteria, and Dedysh et al., (2005) noted thatMethylocella spp belonging to MOB II are facultative and can utilize single and multi-carbon compounds. The activities of facultative anaerobic bacteria have been well documented in literatures where they become very active in deeper sediment layers (Zinder, 1993). However, their activity and community structure is sharpened by their ability to compete for hydrogen, carbon dioxide, and acetate. This is partly because their activities are greatly influenced by substrate availability, and accumulation of their metabolic end products (Stams, 1994).

In this study, the PLFA concentrations of both drained and natural peatland significantly decreased with depth (Table 3). This agrees with other studies that total PLFA concentrations could decrease with peat depth (Sundh et al., 1997). Generally, drainage has been found to increase the thickness of oxygen layer and enhance substrate availability in peat surface layers.

However, bulk density increases with depth mostly in fen sites after drainage, which decreases gas diffusion rates thereby resulting in decreased oxygen levels and increased stress in deep peat layers (Jaatinen et al., 2005). Additionally, substrate quality has been found to generally decrease with depth with the rate of decomposition (Hogg, 1993). This trend that was noticed in my results could be due to decreased oxygen levels, increased stress, and decreased substrate quality in deeper peat layers.

Studies have revealed that nutrient cycles of peatlands are susceptible to changes in water levels, which are triggered by climate and anthropogenic activities such as land-use (Peltoniemi, 2010).

Additionally, lowering of water table causes peatland drying and encourages changes in plant community composition which in turn affects the rate of organic matter breakdown (Peltoniemi, 2010). However, my results showed that there is no significant difference in the PLFA

concentrations of natural and drained peat for fatty acid groups, and only some trends were detected for microbial biomarkers towards more methane oxidizing groups in drained peatlands, likely a result of higher oxygen availability. Overall, there were surprisingly low effects due to drainage. The effect of low water table is dependent on site type even though their combined effect on microbial community composition is relatively low (Peltoniemi, 2010). One reason for the lack of major differences in PLFA concentrations between drained and natural peatlands

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could be because hydrology has limited influence on microbial community abundance compared to other factors such as peatland type, litter quality, and variable among microbes. In another study done simultaneously with this one, the microbial community composition has been found to correlate positively with site type (Mpamah et al., in preparation). Additionally, activity of microbes may be affected but not abundance.

Lake sediment had higher PLFA (absolute) concentration per unit mass of soil at surface layer compared to peat and this could be because absolute abundance values only expresses

concentrations of biomarkers based on weight. This may not be an accurate way to measure microbial community composition because biomarkers differ with respect to weight

(http://cse.ksu.edu/REU/S14/elias940/index.html).

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6.0 CONCLUSIONS

My results are suggesting that certain PLFAs are better eluted depending on the methylation procedure. Even though overall PLFA yield was not affected, the results were much more variable with base compared to acid methylation method. The acid methylation procedure was thus the preferred method for the peat soils. However, it may not be the preferred method for any other material. It is thus crucial to know the nature of the lipids in the sample before deciding on what type of methylation method to use.

This study also demonstrated important differences in microbial abundance of lake sediment and peat soils. The abundance of the microbial community in these two ecosystems was dependent on their physicochemical properties. The high carbon content in peat and anoxic conditions in deeper lake sediment layers were important factors driving the activities and abundance of the microbial community. E.g. MOB profited from aerobic soil conditions, while fatty acid groups indicating anaerobic microbes dominated in anaerobic sediments. Surprisingly, relatively small changes were detected as a result of peatland drainage, which is known to cause dramatic changes in soil carbon cycling. This is likely due to other factors overruling the effect of

drainage, e.g. changes in plant community structures. Further study is needed in peatland soils to link the activities of MOBs with their abundance. PLFA compared to other culture-independent methods is a useful tool in the profiling of the microbial communities in lake sediments and peat soils.

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Characterization of microbial communities in lake ediments and peat samples using phospholipid fatty acid analysis

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