This work was funded in part by the DOE Great Lakes Bioenergy Research Center (DOE BER Office of Science DE-FC02-07ER64494) and DOE OBP Office of Energy Efficiency and Renewable Energy (DE-AC05-76RL01830). The authors would like to acknowledge Anders Gurda for his patient and skillful contribution to videography and editing.

NOTE: Always wear appropriate personal protective equipment (PPE) throughout the procedure. To avoid potential sample contamination, do not touch glassware with bare hands. Wear appropriate gloves when running protocol steps that require handling of chloroform.
1. Preparations (2 Days for ~40 Samples)
<ol>
	<li>Collect soil into sterile bags and transport from the field in a cooler containing ice. If it is not possible to sieve fresh soil and freeze dry immediately, store the samples in a -80 &#176;C freezer until ready to start the analysis.</li>
	<li>Prepare soil by homogenizing. Remove roots and stones and break up clods by coarse sieving (e.g. 2 mm).</li>
	<li>Prepare for freeze drying by putting subsamples in an appropriate container as per instructions of the freeze dryer manual and freeze dry as soon as possible. Once soils are freeze dried, store in a sealed container with desiccant until extraction. It is best to store freeze dried soil at a minimum of -20 &#176;C but preferably at -80 &#176;C.</li>
	<li>In preparation for extraction, remove freeze dried soils from storage and grind to a flour-like consistency. Methods for grinding include ball mill, ball beater, and mortar and pestle. After grinding soil, store in a freezer (see 1.3). 
	NOTE: The amount of sample used for extraction depends on its organic matter content. A general guideline is to use 0.5 to 1 g of a soil that is 12 to 18% carbon by weight, and 3 to 5 g for a soil 1 to 3% carbon by weight.</li>
	<li>Pre-rinse 30 mL centrifuge tubes with hexane. Add approximately 2 to 3 mL of hexane to tubes and vortex for 5 sec. Decant hexane to another tube, and vortex. Hexane (2 to 3 mL) can be used to serially rinse six tubes. Store hexane-rinsed tubes inverted in the fume hood and dispose of used hexane in an appropriate waste container.</li>
	<li>Wrap the glassware in 2 to 3 layers of aluminum foil and place in the muffle furnace. Bake (muffle) glassware at 450 &#176;C for 4.5 h.</li>
	<li>Prepare reagents.
	<ol>
		<li>For the soil amount used, add chemicals in a 0.8:1:2 volume ratio for phosphate-buffer (P-buffer):CHCl3:MeOH.</li>
		<li>Prepare P-buffer solution: Phosphate-Buffer: 0.1 M, pH 7.0.
		<ol>
			<li>Add 61 mL of 1M K2HPO4 stock, sterile (chemical should be ACS certified grade or better). Add 39 mL of 1 M KH2PO4 stock, sterile (chemical should be ACS certified grade or better). Fill to 1000 mL&#160;with Type 1 water. Adjust pH to 7.0 with NaOH or HCl. Store unused solution for up to 7 d at ambient temperature or 30 days in a refrigerator.</li>
			<li>Alternatively, weigh out 10.62 g of K2HPO4 and 5.31 g of KH2PO4; dilute to 1 L with Type 1 water. Check pH, adjust if necessary.</li>
		</ol>
		</li>
		<li>Prepare Reagent 1, Saponification Reagent.
		<ol>
			<li>Dispense 300 mL of Type 1 water. Add 300 mL of CH3OH (HPLC grade or higher). Add 90.00 g of NaOH (certified ACS or better). Add NaOH pellets to the solution while stirring. Stir until the pellets dissolve. It is recommended to store this solution no longer than 30 d.</li>
		</ol>
		</li>
		<li>Prepare Reagent 2, Methylation Reagent.
		<ol>
			<li>Dispense 275 mL of CH3OH (HPLC grade or higher). Add 325 mL of certified 6.00 N HCL while stirring. It is recommended to store this solution no longer than 30 d.</li>
		</ol>
		</li>
		<li>Prepare Reagent 3, Extraction Reagent: 50 % C6H14 (Hexane), 50% C5H12O (MTBE).
		<ol>
			<li>In the fume hood, combine 200 mL of C6H14 (HPLC grade or higher) and 200 mL of C5H12O (HPLC grade or higher). Mix well; cap tightly. Store in flammables cabinet or fume hood for no longer than 1 year.</li>
		</ol>
		</li>
		<li>Prepare Reagent 4, Base wash Reagent.
		<ol>
			<li>Dispense 900 mL of Type 1 water to beaker. Add 10.80 g of NaOH (Certified ACS or better) while stirring. Stir until the pellets dissolve. It is recommended to store this solution no longer than 30 d.</li>
		</ol>
		</li>
		<li>Prepare stock solution of internal standard.
		<ol>
			<li>Weigh out 100 mg of 19:0 EE standard. Add to 50 mL of hexane-rinsed volumetric flask. Add ~15 mL of Hexane-MTBE solution (reagent 3) to flask, swirl to dissolve. Top off to 50 mL with Hexane-MTBE solution (reagent 3). Cap and swirl to mix. Transfer to hexane-rinsed glass tubes with PTFE lined caps and store at -20 &#176;C.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. DAY 1 - Extraction of Fatty Acids from Soil (4 to 5 h for ~40 Samples)
<ol>
	<li>Prepare three 5 to 10 mL dispensing pipettes for P-buffer, chloroform, and methanol. 
	NOTE: Less hazardous alternatives to chloroform have been proposed as extractants. These may result in equivalent lipid recovery rates 16,17, but are not evaluated in this protocol.</li>
	<li>Weigh freeze-dried soils into 30 mL centrifuge tubes and record soil mass.</li>
	<li>Make two blanks and include a check standard (a soil that has been extracted previously).</li>
	<li>In the fume hood, add the reagents to the soil in the centrifuge tube in the following order:&#160;P-buffer, CHCl3, and MeOH (Table 1). Allow the soils time to wet after the P-buffer addition before adding the CHCl3. Cap the centrifuge tubes tightly and cover to protect from light.</li>
	<li>Place them on the shaker horizontally making sure they are well-secured. With the speed setting on 280 rpm, shake for 1 h18.</li>
	<li>Prepare two 16 mm x 150 mm glass tubes for each sample as follows: Label the tube and add the same volume of CHCl3 and an equal volume of P-buffer.</li>
	<li>Remove the centrifuge tubes from the shaker and centrifuge for 10 min at 1,430 x g and 25 &#176;C. Phase separation should be visible in the glass tube.</li>
	<li>In the fume hood, decant the supernatant from the centrifuge tube into one of tubes prepared in step 2.6. Repeat steps 2.4 through 2.5 and decant the supernatant into the second tube.</li>
	<li>Securely cap all the16 mm &#215; 150 mm glass tubes with PTFE-lined caps and invert 10 x to mix.</li>
	<li>Allow the samples to stand undisturbed overnight to complete separation of the two phases. To do this, keep the samples in a dark cabinet/space or covered in aluminum foil at room temperature. It is acceptable to allow the extracts to separate over the weekend.
	<ol>
		<li>Alternatively, if one desires to move directly to the next step, or if samples get disturbed the next day, centrifuge samples for 10 min at 1,000 x g and 25 &#176;C. 
		NOTE: Subject all samples within a comparison group to the same phase separation standing time.</li>
	</ol>
	</li>
</ol>
3. DAY 2 - Isolation of Lipids (3 to 4 h for ~40 Samples)
<ol>
	<li>Turn on evaporation apparatus and solvent trap. Set evaporation apparatus to 33 &#176;C and preheat.</li>
	<li>Set up a vacuum aspirator in the hood: a side-arm flask connected to a vacuum pump, a length of high purity tubing and a glass pipet.</li>
	<li>Aspirate the top layer and interface (approximately 2/3 of the way down) of the two glass tubes, retaining the aqueous layer. Repeat the process&#160;using a clean pipet for each sample.</li>
	<li>Combine the aqueous layers of extract from the second tube with that in the first tube by carefully decanting. Ensure that the tube being decanting is free of scratches or cracks.</li>
	<li>Once the CHCl3 extracts are combined, inspect the liquid - it should be clear. If not add MeOH until clear.</li>
	<li>Dry down all the samples using the vacuum evaporation apparatus. Start with settings of temperature 33 &#176;C, vortex speed 26%, and pressure 400 mbar.</li>
	<li>Place the samples in the evaporation system and after 10 min slowly lower the pressure to 350 mbar.</li>
	<li>Monitor the progress and when the liquid level in the tube has reached the level of the heating block, decrease the pressure to 300 mbar.</li>
	<li>Continue to monitor the height of the remaining liquid and when it is approximately 1 cm in depth, decrease the pressure to 200 mbar.</li>
	<li>After samples have dried, remove samples and run the pump for 10 additional min to clear vapors.</li>
	<li>Cap the tubes tightly and store the lipids in a freezer at -80 &#176;C.</li>
	<li>Dispose of the aspirated liquid in accordance with applicable chemical safety regulations.</li>
</ol>
4. DAY 3 - Saponification and Methylation (6 to 7 h for ~40 Samples)
<ol>
	<li>Turn on the water baths. Set bath 1 to 95 &#176;C and bath 2 to 80 &#176;C.</li>
	<li>Set the pipet dispensers and ensure they are dispensing the correct volume. 
	Reagent 1: 1 mL per sample 
	Reagent 2: 2 mL per sample 
	Reagent 3: 1.25 mL per sample 
	Reagent 4: 3 mL per sample 
	NOTE: The heating process will build pressure in the tube. Do not use scratched, cracked, or chipped tubes.</li>
	<li>Using a pipet dispenser add 1.0 mL of Reagent 1 to the dried lipids. Cap tightly, vortex for 5 s and place in a rack.</li>
	<li>Place the rack of sample tubes into the 95 &#176;C water bath for 5min. Remove the rack of tubes from the bath and check the tubes for leaks, indicated by bubbles rising in the tube. Retighten or replace the caps of leaking tubes, and check again for cracks or chips. Continue heating the tubes in the water bath for an additional 10 min.</li>
	<li>Remove samples from bath 1 and place in bath 2 (80 &#176;C) and continue the incubation for another 15 min.</li>
	<li>Remove the tubes and cool the samples by placing the rack into a pan of tap water for cooling.</li>
	<li>Add 2 mL of Reagent 2 to each sample. Cap tightly and vortex for 5 to 10s.</li>
	<li>Place the rack into the 80 &#176;C water bath and incubate for 10 min.</li>
	<li>Remove the rack of tubes from the water bath and put into a pan of tap water for cooling. Agitate the rack of tubes to accelerate the cooling process. 
	NOTE: Do not exceed time and temperature. Too much heating could degrade FAMEs.</li>
	<li>Using the pipet dispenser add 1.25 mL of Reagent 3 to each sample tube to extract the fatty acid methyl esters. Cap tightly and put the tubes on the shaker for 10 min.</li>
	<li>After shaking, allow the rack of tubes sit for 10 min for the phases to separate. Transfer the organic phase (top layer) to a 16 mm x 100 mm glass test tube using a glass pipet.</li>
	<li>Repeat the extraction by again adding Reagent 3, shaking, allowing phases to separate, and transferring the top phase. 
	NOTE Do not transfer any of the bottom-phase. It is fine to leave a small amount of top phase in the tube.</li>
	<li>Using the pipet dispenser, add 3 mL of Reagent 4 to the 16 mm x 100 mm tubes.</li>
	<li>Cap the test tubes tightly and vortex for 20-30 s.</li>
	<li>After vortexing, centrifuge for 3 min at 1,000 &#215; g.</li>
	<li>Using a clean glass pipet, aspirate the top organic phase and transfer to a 4- mL amber vial.</li>
	<li>Turn on evaporation apparatus and solvent trap. Set evaporation apparatus to 30 &#176;C, the vortex speed to 26%, the vacuum to 200 mbar, and press preheat.</li>
	<li>Monitor the progress. After samples have dried, remove samples and run the pump for 10 additional min to clear vapors.</li>
	<li>Remove pipet from the reagent bottles 1 and 4 and pump through some dilute acid (e.g. 1% HCl), followed by D.I. water. Rinse the pipet used for Reagent 2 by pumping through D.I. water. In the hood, drain the solvent from the pipet used for Reagent 3 into an appropriate container and keep it in the hood until the solvent residues have evaporated.</li>
	<li>Store the pipets inverted, with the plungers removed to prevent sticking of the check valves.</li>
	<li>Use glass pipets once and then dispose in an appropriate container.</li>
	<li>In the hood, allow solvent residues on glassware to evaporate.</li>
	<li>Rinse glassware with clean water and detergent solution.</li>
</ol>
5. DAY 4 - Preparation of the Working Solution and Transfer of FAMEs to the GC Vials (2-3 h for ~40 Samples)
<ol>
	<li>Gather materials: 4 mL amber vials with dried samples; amber 2 mL GC vials;&#160;400 &#181;L flat bottom glass inserts and caps; 500 &#181;L glass syringe; 50 mL volumetric flask; Stock solution - Ethyl nonadecanoate (19:0 EE internal standard) in 50/50 hexane/MTBE (Reagent 3).</li>
	<li>Using the glass syringe, add 500 &#181;L of ethyl nonadecanoate (19:0 EE) stock solution to a 50-mL volumetric flask.</li>
	<li>Fill flask to volumetric score with Reagent 3.</li>
	<li>Cap flask and invert 5x to mix.</li>
	<li>Transfer 3 mL to a clean 4 mL vial for a working solution reservoir.</li>
	<li>Using the glass syringe, add 300 &#181;L of the working solution to each of the 4 mL vials containing the dried fatty acid methyl esters and cap.</li>
	<li>Vortex the sample for 15 s and set aside to stand for 15 min.</li>
	<li>Using a glass Pasteur pipet, carefully transfer the suspended fatty acid methyl esters to a 2 mL GC vial containing the 400 &#181;L insert.</li>
	<li>Store sealed GC vials in a -20 &#176;C freezer prior to analysis.</li>
	<li>Submit samples for GC analysis. 
	NOTE: The analysis must be carried out using a specific GC column and conditions which are described in Supplementary File S1. It is best that the GC analysis be completed within 2 weeks of methylation.</li>
</ol>

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<li>Gutknecht, J. L. M., Field, C. B., Balser, T. C. <a target="_blank" href="http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2486.2012.02686.x/abstract">Microbial communities and their responses to simulated global change fluctuate greatly over multiple years.</a> Glob Change Biol. 18, 225-269 (2012).</li>
<li>Pei, Z., et al. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0038071716000511">Soil and tree species traits both shape soil microbial communities during early growth of Chinese subtropical forests.</a> Soil Biol Biochem. 96, 180-190 (2016).</li>
<li>Oates, L. G., Duncan, D. S., Sanford, G. R., Liang, C., Jackson, R. D. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0167880916304595">Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization.</a> Ag Ecosys Environ. 233, 396-403 (2016).</li>
<li>Bååth, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+use+of+neutral+lipid+fatty+acids+to+indicate+the+physiological+conditions+of+soil+fungi%5BTitle%5D)+AND+%22Microbial+Ecol%22%5BJournal%5D)">The use of neutral lipid fatty acids to indicate the physiological conditions of soil fungi.</a> Microbial Ecol. 45 (4), 373-383 (2003).</li>
<li>Ngosong, C., Gabriel, E., Ruess, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Use+of+the+signature+Fatty+Acid+16%3A1%CF%895+as+a+tool+to+determine+the+distribution+of+arbuscular+mycorrhizal+fungi+in+soil%5BTitle%5D)+AND+%22J+Lipids%22%5BJournal%5D)">Use of the signature Fatty Acid 16:1ω5 as a tool to determine the distribution of arbuscular mycorrhizal fungi in soil.</a> J Lipids. 2012, 236807(2012).</li>
<li>Sharma, M. P., Buyer, J. S. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0929139315300172">Comparison of biochemical and microscopic methods for quantification of arbuscular mycorrhizal fungi in soil and roots.</a> Appl Soil Ecol. 95, 86-89 (2015).</li>
<li>Oates, L. G., Balser, T. C., Jackson, R. D. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0929139312000984">Subhumid pasture soil microbial communities affected by presence of grazing, but not grazing management.</a> Appl Soil Ecol. 59, 20-28 (2012).</li>
<li>Liang, C. Potential legacy effects of biofuel cropping systems on soil microbial communities in southern Wisconsin, USA. Ag Sci. 2 (2), 131-137 (2011).</li>
<li>Herzberger, A. J., Duncan, D. S., Jackson, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Bouncing+Back+Plant-Associated+Soil+Microbes+Respond+Rapidly+to+Prairie+Establishment%5BTitle%5D)+AND+%22PloS+One%22%5BJournal%5D)">Bouncing Back Plant-Associated Soil Microbes Respond Rapidly to Prairie Establishment.</a> PloS One. 9 (12), 1-14 (2014).</li>
<li>Fraterrigo, J. M., Balser, T. C., Turner, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microbial+community+variation+and+its+relationship+with+nitrogen+mineralization+in+historically+altered+forests%5BTitle%5D)+AND+%22Ecology%22%5BJournal%5D)">Microbial community variation and its relationship with nitrogen mineralization in historically altered forests.</a> Ecology. 87 (3), 570-579 (2006).</li>
<li>Kao-Kniffin, J., Balser, T. C. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0038071706004068">Elevated CO2 differentially alters belowground plant and soil microbial community structure in reed canary grass-invaded experimental wetlands.</a> Soil Biol Biochem. 39 (2), 517-525 (2007).</li>
<li>Mentzer, J. L., Goodman, R. M., Balser, T. C. <a target="_blank" href="http://link.springer.com/article/10.1007/s11104-006-0032-1">Microbial response over time to hydrologic and fertilization treatments in a simulated wet prairie.</a> Plant Soil. 284 (1-2), 85-100 (2006).</li>
<li>Ushio, M., Wagai, R., Balser, T. C., Kitayama, K. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0038071708002241">Variations in the soil microbial community composition of a tropical montane forest ecosystem: Does tree species matter.</a> Soil Biol Biochem. 40 (10), 2699-2702 (2008).</li>
<li>Bartelt-Ryser, J., Joshi, J., Schmid, B., Brandl, H., Balser, T. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S1433831904000101">Soil feedbacks of plant diversity on soil microbial communities and subsequent plant growth.</a> Perspect Plant Ecol. 7 (1), 27-49 (2005).</li>
<li>Fichtner, A., von Oheimb, G., Härdtle, W., Wilken, C., Gutknecht, J. L. M. <a target="_blank" href="https://www.researchgate.net/publication/259572809_Effects_of_anthropogenic_disturbances_on_soil_microbial_communities_in_oak_forests_persist_for_more_than_100_years">Effects of anthropogenic disturbances on soil microbial communities in oak forests persist for more than 100 years.</a> Soil Biol Biochem. 70, 79-87 (2014).</li>
</ol>

The authors have nothing to disclose.

For the examination of multiple samples from experiments with many replicates and/or experimental units, researchers may find phospholipid fatty-acid analysis (PLFA) to be prohibitive in terms of time and materials25. With the PLFA method, cell membrane phospholipids are extracted, purified, and identified using the modified Bligh and Dyer26 two-phase aqueous-organic extraction. This is followed by solid-phase silica chromatography to separate lipids by polarity, and an alkaline methylation of phospholipid fatty acids into fatty acid methyl esters. In PLFA profiling lipid yield can be low but of a very high purity. Microbial ID introduced an alternate method, the fatty acid methyl-ester procedure (MIDI-FA). In the MIDI-FA method, all lipids are extracted directly from pure cultures or soil/sediment samples11,12,27 through saponification. This method has lower lipid loss and is rapid because it has none of the concentration or purification steps of the PLFA method. However, while the MIDI-FA method is quick and less expensive, because it was originally designed for identifying organisms in pure culture, there are no initial extraction or purification steps. Thus, it can include lipid-like compounds co-extracted from soil organic matter that distort the community signature27,28,29. Because this inclusion can also distort biomass measures, MIDI-FA has typically been used only to coarsely qualitatively describe soil lipids13.
The procedure we describe here combines the best of the two separate extraction procedures: 1) an extraction and concentration of lipids using the modified Bligh and Dyer26 method, and 2) the fatty acid methyl ester saponification, methylation, extraction, and base wash procedure developed commercially. This method was developed to achieve the benefits of both of these protocols while minimizing the disadvantages15. By performing the initial extraction and isolating the organic-soluble components (e.g. lipids) prior to performing MIDI-FA, and completing this with a purification step, this protocol offers a balance between speed and precision. Although this method may not be suitable when high purity is required (i.e., for 13C PLFA analysis) or when analyzing phospholipids and neutral lipids separately, in many cases it allows detection of microbial community responses to environmental conditions with greater sensitivity than DNA-based methods30,31,32,33. Membrane lipids decompose rapidly after cell death allowing them to reflect the living microbial community at the time of sampling5,7, in contrast with environmental DNA in which much of the information comes from dead or inactive organisms34. Given the high rate of dormancy observed among soil microorganisms35, the characterization of live biomass can be used to understand temporal plant-microbe interactions at a relatively fine temporal scale and lipid biomarkers can be used to assay the physiological status of the microbial community7. It has been shown that high throughput methods are required to assess microbial response in large field settings25, and while the method we propose here does not replicate the accuracy of PLFA biomarker profiling, it increases throughput while minimizing the variability realized with the MIDI-FA procedure. The method has proven to be an effective tool in addressing questions related to microbial community dynamics on a wide range of soils in large-scale agricultural and ecosystem studies36,37,38,42,43,44,45,46,47,48,49,50.
Lipid classes are combined with this method and there may be a loss of the information contained in those separate classes22,39, but combining the lipid classes may strengthen the power to detect the arbuscular mycorrhizal fungi origin of the 16:1 &#969;5c from both phospho- and neutral-lipids40. In addition, while the number of unknown fatty acids (which could be derived from non-living organic matter) may be higher with this method, it was shown to be lower than MIDI-FA and allows for treatment comparison of lipid profiles from studies with many samples where sample throughput capacity is a concern15. The neutral fraction is generally thought to derive primarily from storage lipids produced by fungi, though there may also be some smaller contribution from soil fauna41. In light of this, the method described here may yield results showing a greater contribution of the fungal lipids 18:2 &#969; 6,9c and 18:1 &#969; 9c than PLFA. The other lipids that tend to show up in the neutral fraction include some of the saturated fatty acids, e.g. 16:0, 18:0, 20:0.
There are different ways in which lipid data can be expressed and analyzed. The most common representations are abundance (nmol g-1 soil), mole fraction (nmol individual lipid nmol-1 total lipid), and mole percent (mole fraction*100). Normalized by the total lipids in a sample, mole fraction and mole percent are measures of the relative abundance of a given lipid. After an appropriate transformation, e.g., arcsine square-root, mole fraction is appropriate for use in analysis by principal components or redundancy analysis ordination. Abundance is the absolute amount of a given lipid extracted per gram of soil. Because the quantity of lipid per cell is reasonably constant, and the lipid extraction is highly efficient and comprehensive, total abundance is a good estimate of total lipids and the abundance of key indicators reflects the biomass of the ecological group it represents17. Finally, a good way to look at microbial community composition is to use multivariate analysis methods16, e.g., ordination methods such as nonmetric multidimensional scaling (NMDS - which does not need data transformation) or principal components analysis (PCA), can be useful for comparing the relative abundance of all lipid biomarkers.

Given the key role of microorganisms in nutrient cycling 1, modification of plant community composition 2, regulation of plant productivity 3, and decomposition of organic matter 4, understanding soil microbial communities is a vital to understanding terrestrial ecosystems.
Because of their relatively high abundance in soil, and their chemical signature, lipid biomarkers can be used to profile the dominant ecological groups comprising soil microbial communities 5. By quantifying lipid biomarkers that are characteristic of different microbial groups, we can estimate total lipids, and then separate these lipids into ecologically relevant groups such as Gram positive (Gm+) and Gram negative (Gm-) bacteria, arbuscular mycorrhizal (AM) and saprotrophic fungi, and actinomycetes 5,6,7,8.
There are many methods for characterizing aspects of microbial communities. The PLFA method is one commonly used to understand basic microbial community structure. It is an effective way to assess the relative abundance of microbial groups as well as total microbial biomass. Due to rapid lipid turnover, PLFA profiling also allows relatively fast detection of changes in the soil microbial community and gives information that allows comparison of ecosystem function, e.g., fungal:bacterial ratios to assess rates of nutrient cycling 1,9,10. However, while the PLFA extraction method is time honored and well respected, it is also time consuming and does not lend itself well to ecosystem-scale studies that require a large number of samples from field scale replicates11,12.
In contrast, the fatty acid methyl ester extraction method (MIDI-FA) has the potential to allow rapid throughput. In this method, samples are saponified, converted to FAMEs, extracted, and then analyzed. The MIDI-FA method is rapid but less discriminating than PLFA, which combines extraction of lipids with separation of different lipid classes13 (phospholipids, neutral lipids, and glycolipids).
In this protocol, we describe a method that combines elements of both PLFA and MIDI-FA lipid profiling. It employs extraction of lipids using the initial chloroform extraction steps of the modified Bligh and Dyer method, and then saponification and conversion to FAMEs. This provides a robust way to detect microbial community structure while excluding much of the background noise from non-microbial material 5,14. This method was developed to achieve a balance between both the PLFA and MIDI-FA protocols, i.e., retain most of the accuracy while increasing throughput to make it logistically and economically feasible to analyze lipids from large-scale studies with many samples15. By performing the initial extraction and isolating the organic-soluble components (e.g. lipids) prior to performing MIDI-FA, and completing this with a purification step, the protocol offers a balance between speed and precision.

<table><tbody><tr><td>RapidVap</td><td>Labconco</td><td>7900000</td><td>Evaporative system</td></tr><tr><td>RapidVap</td><td>Labconco</td><td>7491400</td><td>Sample block</td></tr><tr><td>Chem-resistant vacuum pump</td><td>Labconco</td><td>7584000</td><td>Vacuum pump</td></tr><tr><td>Chemical trap cannister</td><td>Labconco</td><td>7815300</td><td>Trap cannister</td></tr><tr><td>Solvent insert</td><td>Labconco</td><td>7515200</td><td>Solvent trap insert</td></tr><tr><td>Diaphragm pump</td><td>Welch</td><td>7398000</td><td>DryFast vacuum pump</td></tr><tr><td>Water bath</td><td>Fisher</td><td>15-462-15Q</td><td>2 well water bath</td></tr><tr><td>Gas chromatograph</td><td>Various</td><td>N/A</td><td>For sample analysis</td></tr><tr><td>Centrifuge</td><td>Various</td><td>N/A</td><td>For sample separation</td></tr><tr><td>Freeze Dryer</td><td>Various</td><td>N/A</td><td>For sample lyophilization</td></tr><tr><td>Repipet (6)</td><td>BrandTech</td><td>4720440</td><td>For dispensing reagents</td></tr><tr><td>Vortex</td><td>Fisher</td><td>02-215-365</td><td>Analog vortex mixer</td></tr><tr><td>Teflon centrifuge tubes</td><td>Thermo/Nalgene</td><td>3114-0030</td><td>Teflon sample tubes</td></tr><tr><td>Caps</td><td>Thermo/Nalgene</td><td>DS3131-0020</td><td>Caps for teflon tubes</td></tr><tr><td>Test tube</td><td>Corning</td><td>9825-16</td><td>16x100mm tubes</td></tr><tr><td>Test tube</td><td>Corning</td><td>9825-16xx</td><td>16x150mm tubes</td></tr><tr><td>Caps</td><td>Corning</td><td>9998-15</td><td>15-415 thread black phenolic caps w/PTFE liner</td></tr><tr><td>Pasteur pipets</td><td>Fisher</td><td>13-678-20B</td><td>14.6cm</td></tr><tr><td>500 uL glass syringe</td><td>Fisher</td><td>13684106LC</td><td>Hamilton 81217</td></tr><tr><td>Amber vials</td><td>Agilent</td><td>5182-0716</td><td>4mL Amber vials</td></tr><tr><td>Caps</td><td>Agilent</td><td>5182-0717</td><td>Blue screw caps</td></tr><tr><td>Inserts</td><td>Agilent</td><td>5181-3377</td><td>400uL flat bottom glass inserts</td></tr><tr><td>&lt;strong&gt;Standards&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>19:0 ethyl nonadecanoate (Ethyl nonadecanoate)</td><td>VWR</td><td>TCN0459-5G</td><td>Analytical standard</td></tr><tr><td>&lt;strong&gt;Chemicals&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Dipotassium phosphate (K2HPO4 - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Phosphate-Buffer</td></tr><tr><td>Potassium phosphate monobasic (KH2PO4 - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Phosphate-Buffer</td></tr><tr><td>Methanol (CH3OH - HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagents 1 &amp;amp; 2</td></tr><tr><td>Sodium hydroxide (NaOH - ACS grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagents 1 &amp;amp; 4</td></tr><tr><td>Hydrochloric acid (6N HCL)</td><td>Various</td><td>N/A</td><td>For making Reagent 2</td></tr><tr><td>Hexane (HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagent 3</td></tr><tr><td>MTBE (Methyl tert-butyl ether - HPLC grade or better)</td><td>Various</td><td>N/A</td><td>For making Reagent 3</td></tr></tbody></table>

a lipid extraction and analysis method for characterizing soil microbes in experiments with many samples

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial communities, a relatively precise but effort-intensive technique to assay microbial community composition is phospholipid fatty acid (PLFA) analysis. PLFA was developed to analyze phospholipid biomarkers, which can be used as indicators of microbial biomass and the composition of broad functional groups of fungi and bacteria. It has commonly been used to compare soils under alternative plant communities, ecology, and management regimes. The PLFA method has been shown to be sensitive to detecting shifts in microbial community composition.
An alternative method, fatty acid methyl ester extraction and analysis (MIDI-FA) was developed for rapid extraction of total lipids, without separation of the phospholipid fraction, from pure cultures as a microbial identification technique. This method is rapid but is less suited for soil samples because it lacks an initial step separating soil particles and begins instead with a saponification reaction that likely produces artifacts from the background organic matter in the soil. 
This article describes a method that increases throughput while balancing effort and accuracy for extraction of lipids from the cell membranes of microorganisms for use in characterizing both total lipids and the relative abundance of indicator lipids to determine soil microbial community structure in studies with many samples. The method combines the accuracy achieved through PLFA profiling by extracting and concentrating soil lipids as a first step, and a reduction in effort by saponifying the organic material extracted and processing with the MIDI-FA method as a second step.

The data tables from the reports can be collated into a spreadsheet or database. After adjusting for response factor (a correction factor that normalizes the response for different chain lengths), peak areas can be compared with the peak area of external or internal standards to arrive at a concentration in the extract. By dividing through by the mass of soil extracted, the data can be expressed as mass of FAME per gram of soil or, by using the molecular weight of each FAME, the more commonly reported nmol per gram of soil. The sum of microbial FAMEs is indicative of total microbial biomass, and can be compared among treatments (Figure 1). Certain FAMEs can also be associated with particular microbial groups such as Gram-positive or Gram-negative bacteria, actinomycetes, arbuscular mycorrhizal fungi, and saprotrophic fungi 19,20,21,22,23,24. Ratios of the mass of specific biomarkers can reflect the relative abundance of these groups (Figure 2). Overall FAME abundance patterns create community-level fingerprints, which allow comparison of microbial community dissimilarity through multivariate techniques such as ordination (Figure 3). In contrast with most DNA-based approaches, community-level lipid data can be analyzed either as relative or absolute abundances. If total biomass differs substantially among samples, these two approaches will give very different results; the ecological questions underlying the experiment should determine which approach is used.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55310/55310fig1.jpg" /> 
Figure 1: Total FAME biomass. Comparison of total FAME biomarker biomass (nmol g-1 soil) from continuous corn, fertilized prairie, and unfertilized prairie. <a href="http://cloudflare.jove.com/files/ftp_upload/55310/55310fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55310/55310fig2.jpg" /> 
Figure 2: FAME biomass of bacteria and fungi. Treatment comparison of bacterial and fungal FAME biomarker biomass (nmol g-1 soil) from continuous corn, fertilized prairie, and unfertilized prairie.Fungal and bacterial mass from absolute abundance. Average (sum f/sum b). <a href="http://cloudflare.jove.com/files/ftp_upload/55310/55310fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55310/55310fig3.jpg" /> 
Figure 3: Non-metric Dimensional Scaling of FAME lipid biomarkers. Comparison of overall microbial community using absolute abundance profiles of all microbial FAME lipid biomarkers. In this example, continuous corn and unfertilized prairie communities separated and are very far apart while some fertilized prairie samples have microbial communities that resemble those from corn, and others resemble the unfertilized prairie. <a href="http://cloudflare.jove.com/files/ftp_upload/55310/55310fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/55310/55310table1.jpg" /> 
Table 1: The solvent type, proportions added g-1 soil, and their order of addition. This is important for proper extraction and separation of the organic and aqueous phases.
Supplementary File S1: <a href="http://cloudflare.jove.com/files/ftp_upload/55310/S1_GC_analysis.docx" target="_blank">Please click here to download.</a>

Watch this Scientific Journal Video about A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples at JoVE.com

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

The article describes a method that increases throughput while balancing effort and accuracy for extraction of lipids from the cell membranes of microorganisms for use in characterizing both total lipids and the relative abundance of indicator lipids to determine soil microbial community structure in studies with many samples.

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial ...

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20.0K Views.  University of Wisconsin - Madison. The article describes a method that increases throughput while balancing effort and accuracy for extraction of lipids from the cell membranes of microorganisms for use in characterizing both total lipids and the relative abundance of indicator lipids to determine soil microbial community structure in studies with many samples.

Video: A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Analysis of Fatty Acid Content and Composition in Microalgae

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of microalgal biomass. These fatty acids can be present in different acyl-lipid classes. Especially the fatty acids present in triacylglycerol (TAG) are of commercial interest, because they can be used for production of transportation fuels, bulk chemicals, nutraceuticals (&omega;-3 fatty acids), and food commodities. To develop commercial applications, reliable analytical methods for quantification of fatty acid content and composition are needed. Microalgae are single cells surrounded by a rigid cell wall. A fatty acid analysis method should provide sufficient cell disruption to liberate all acyl lipids and the extraction procedure used should be able to extract all acyl lipid classes.
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This method does not provide information about the relative abundance of different lipid classes, but can be extended to separate lipid classes from each other.
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A method for the determination of fatty acid content and composition in microalgae based on mechanical cell disruption, solvent based lipid extraction, transesterification, and quantification and identification of fatty acids using gas chromatography is described. A tripentadecanoin internal standard is used to compensate for the possible losses during extraction and incomplete transesterification.

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of ...

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually ...

Biochemistry

Extraction and Analysis of Microbial Phospholipid Fatty Acids in Soils

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about the overall structure of terrestrial microbial communities. PLFA profiling has been extensively used in a range of ecosystems as a biological index of overall soil quality, and as a quantitative indicator of soil response to land management and other environmental stressors.
The standard method presented here outlines four key steps: 1. lipid extraction from soil samples with a single-phase chloroform mixture, 2. fractionation using solid phase extraction columns to isolate phospholipids from other extracted lipids, 3. methanolysis of phospholipids to produce fatty acid methyl esters (FAMEs), and 4. FAME analysis by capillary gas chromatography using a flame ionization detector (GC-FID). Two standards are used, including 1,2-dinonadecanoyl-sn-glycero-3-phosphocholine (PC(19:0/19:0)) to assess the overall recovery of the extraction method, and methyl decanoate (MeC10:0) as an internal standard (ISTD) for the GC analysis.

Phospholipid fatty acids provide information about the structure of soil microbial communities. We present methods for extraction from soil samples with a single-phase chloroform mixture, fractionation of extracted lipids using solid phase extraction columns, and methanolysis to produce fatty acid methyl esters, which are analyzed by capillary gas chromatography.

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about ...

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled Earth-system processes. Such knowledge is imperative in improving predictions of hydro-biogeochemical cycles, especially under climate change scenarios. We present an experimental method, designed to capture sub-surface heterogeneity of an initially homogeneous soil system. This method is based on destructive sampling of a soil lysimeter designed to simulate a small-scale hillslope. A weighing lysimeter of one cubic meter capacity was divided into sections (voxels) and was excavated layer-by-layer, with sub samples being collected from each voxel. The excavation procedure was aimed at detecting the incipient heterogeneity of the system by focusing on the spatial assessment of hydrological, geochemical, and microbiological properties of the soil. Representative results of a few physicochemical variables tested show the development of heterogeneity. Additional work to test interactions between hydrological, geochemical, and microbiological signatures is planned to interpret the observed patterns. Our study also demonstrates the possibility of carrying out similar excavations in order to observe and quantify different aspects of soil-development under varying environmental conditions and scale.

This study presents an excavation method for investigating subsurface hydrological, geochemical, and microbiological heterogeneity of a soil lysimeter. The lysimeter simulates an artificial hillslope which was initially under homogeneous condition and had been subjected to approximately 5,000 mm of water over eight cycles of irrigation in an 18-month period.

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled ...

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The purpose of this manuscript is to provide detail on how to rapidly sample soil, rhizosphere, and endosphere of replicated field trials and analyze changes that may occur in the microbial communities due to sample type, treatment, and plant genotype. The experiment used to demonstrate these methods consists of replicated field plots containing two, pure, warm-season grasses (Panicum virgatum and Andropogon gerardii) and a low-diversity grass mixture (A. gerardii, Sorghastrum nutans, and Bouteloua curtipendula). Briefly, plants are excavated, a variety of roots are cut and placed in phosphate buffer, and then shaken to collect the rhizosphere. Roots are brought to the laboratory on ice and surface sterilized with bleach and ethanol (EtOH). The rhizosphere is filtered and concentrated by centrifugation. Excavated soil from around the root ball is placed into plastic bags and brought to the lab where a small amount of soil is taken for DNA extractions. DNA is extracted from roots, soil, and rhizosphere and then amplified with primers for the V4 region of the 16S rRNA gene. Amplicons are sequenced, then analyzed with open access bioinformatics tools. These methods allow researchers to test how the microbial community diversity and composition varies due to sample type, treatment, and plant genotype. Using these methods along with statistical models, the representative results demonstrate there are significant differences in microbial communities of roots, rhizosphere, and soil. Methods presented here provide a complete set of steps for how to collect field samples, isolate, extract, quantify, amplify, and sequence DNA, and analyze microbial community diversity and composition in replicated field trials.

Excavation of plant roots from the field as well as processing of samples into endosphere, rhizosphere, and soil are described in detail, including DNA extraction and data analysis methods. This paper is designed to enable other laboratories to use these techniques for the study of soil, endosphere, and rhizosphere microbiomes.

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The ...

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

A protocol is presented for simultaneously extracting metabolites, proteins, and lipids from a single soil sample, allowing reduced sample preparation times and enabling multi-omic mass spectrometry analyses of samples with limited quantities.

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and ...

Chemistry

Determination of Total Lipid and Lipid Classes in Marine Samples

Lipids are largely composed of carbon and hydrogen and, therefore, provide a greater specific energy than other organic macromolecules in the sea. Being carbon- and hydrogen-rich they are also hydrophobic and can act as a solvent and absorption carrier for organic contaminants and thus can be drivers of pollutant bioaccumulation in marine ecosystems. Their hydrophobic nature facilitates their isolation from seawater or biological specimens: marine lipid analysis begins with sampling and then extraction in non-polar organic solvents, providing a convenient method for their separation from other substances in an aquatic matrix.
If seawater has been sampled, the first step usually involves separation into operationally defined &#39;dissolved&#39; and &#39;particulate&#39; factions by filtration. Samples are collected and lipids isolated from the sample matrix typically with chloroform for truly dissolved matter and colloids, and with mixtures of chloroform and methanol for solids and biological specimens. Such extracts may contain several classes from biogenic and anthropogenic sources. At this time, total lipids and lipid classes may be determined. Total lipid can be measured by summing individually determined lipid classes which customarily have been chromatographically separated. Thin-layer chromatography (TLC) with flame ionization detection (FID) is regularly used for the quantitative analysis of lipids from marine samples. TLC-FID furnishes synoptic lipid class information and, by summing classes, a total lipid measurement.
Lipid class information is especially useful when combined with measurements of individual components e.g., fatty acids and/or sterols, after their release from lipid extracts. The wide variety of lipid structures and functions means they are used broadly in ecological and biogeochemical research assessing ecosystem health and the degree of influence by anthropogenic impacts. They have been employed to measure substances of dietary value to marine fauna (e.g., aquafeeds and/or prey), and as an indicator of water quality (e.g., hydrocarbons).

This protocol is for the determination of lipids in seawater and biological specimens. Lipids in filtrates are extracted with chloroform or mixtures of chloroform and methanol in the case of solids. Lipid classes are measured by rod thin-layer chromatography with flame ionization detection and their sum gives the total lipid content.

Lipids are largely composed of carbon and hydrogen and, therefore, provide a greater specific energy than other organic macromolecules in the sea. Being ...

Extraction of High Molecular Weight Genomic DNA from Soils and Sediments

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with nutrient and energy flow within terrestrial ecosystems. Cultivation-independent environmental genomic, also known as metagenomic, approaches promise unprecedented access to this genetic information with respect to pathway reconstruction and functional screening for high value therapeutic and biomass conversion processes. However, the soil microbiome still remains a challenge largely due to the difficulty in obtaining high molecular weight DNA of sufficient quality for large insert library production. Here we introduce a protocol for extracting high molecular weight, microbial community genomic DNA from soils and sediments. The quality of isolated genomic DNA is ideal for constructing large insert environmental genomic libraries for downstream sequencing and screening applications. 
The procedure starts with cell lysis. Cell walls and membranes of microbes are lysed by both mechanical (grinding) and chemical forces (&beta;-mercaptoethanol). Genomic DNA is then isolated using extraction buffer, chloroform-isoamyl alcohol and isopropyl alcohol. The buffers employed for the lysis and extraction steps include guanidine isothiocyanate and hexadecyltrimethylammonium bromide (CTAB) to preserve the integrity of the high molecular weight genomic DNA. Depending on your downstream application, the isolated genomic DNA can be further purified using cesium chloride (CsCl) gradient ultracentrifugation, which reduces impurities including humic acids. The first procedure, extraction, takes approximately 8 hours, excluding DNA quantification step. The CsCl gradient ultracentrifugation, is a two days process. During the entire procedure, genomic DNA should be treated gently to prevent shearing, avoid severe vortexing, and repetitive harsh pipetting.

A methodology to isolate high molecular weight and high quality genomic DNA from soil microbial community is described.

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with ...

Biology

Sonication Extraction of Lipid Biomarkers from Sediment

Source: Laboratory of Jeff Salacup&#160;- University of Massachusetts Amherst
The material comprising the living &#34;organic&#34; share of any ecosystem (leaves, fungi, bark, tissue; Figure 1) differs fundamentally from the material of the non-living &#34;inorganic&#34; share (rocks and their constituent minerals, oxygen, water, metals). Organic material contains carbon linked to a series of other carbon and hydrogen molecules (Figure 2), which distinguishes it from inorganic material. Carbon&#39;s wide valency range (-4 to +4) allows it to form up to four separate covalent bonds with neighboring atoms, usually C, H, O, N, S, and P. It can also share up to three covalent bonds with a single other atom, such as the triple bond in the often-poisonous cyanide, or nitrile, group. Over the past 4.6 billion years, this flexibility has led to an amazing array of chemical structures, which vary in size, complexity, polarity, shape, and function. The scientific field of organic geochemistry is concerned with the identification and characterization of the whole range of detectable organic compounds, called biomarkers, produced by life on this planet, as well as others, through geologic time.
<img alt="Figure 1" src="/files/ftp_upload/10055/10055fig1.jpg" /> 
Figure 1. Organic material, such as trees, leaves, and moss, are chemically and visually distinct from inorganic material, such as pavement.

Source: Laboratory of Jeff Salacup&#160;- University of Massachusetts Amherst
The material comprising the living &#34;organic&#34; share of any ecosystem ...