This project was support in part by Johns Hopkins University, Office of the Provost through the Gateway Science Initiative.

Note: Metagenomic DNA is purified from soil (Baltimore County, Maryland) using a commercially available soil genomic isolation kit (see Table of Materials). Using an UV spectrophotometer (see Table of Materials), the purified genomic DNA should have a 260/280 (nm) ratio &#62;1.8 and a 260/230 ratio between 2.0 - 2.2 to assure that the sample is free of contaminants. The amount of genomic DNA required for NS ranges from 200 ng to 2 &#181;g.
1. Rapid Library Preparation Method (Short Protocol)
NOTE: This is a short protocol. See Table of Materials for the rapid sequencing kit.
<ol>
	<li>In a 0.2 mL thin-walled tube (see Table of Materials) add 200 ng of high molecular weight DNA in a final of volume of 7.5 &#181;L of distilled water.</li>
	<li>Add 2.5 &#181;L of fragmentation mix (FM) from the rapid library preparation kit and mix gently by inversion. Pulse centrifuge to spin down (1,000 x g for 5 s).</li>
	<li>Place the sample in a thermocycler (see Table of Materials) for one round at 30 &#176;C for 1 min followed by 75 &#176;C for 1 min. Remove the tube and pulse centrifuge to spin down the sample.</li>
	<li>Add 1 &#181;L of rapid adapter and 0.2 &#181;L of blunt/TA ligase master mix, and then store the adapted and tethered library on ice. 
	NOTE: If using the short protocol proceed to step 8</li>
</ol>
2. Ligation Sequencing Protocol (Long Protocol): Metagenomic DNA Fragmentation
Note: See Table of Materials for the ligation sequencing kit.
<ol>
	<li>Dilute 1 &#181;g of purified genomic DNA to a final volume of 46 &#181;L in deionized water.</li>
	<li>Transfer the sample to a DNA fragmentation tube (see Table of Materials) and centrifuge for 1 min at room temperature at 8,000 x g using a microcentrifuge (see Table of Materials) to produce ~8 kb genomic fragments. Make sure all the liquid has passed into the collection tube.</li>
	<li>Invert the fragmentation tube, return to the centrifuge, and centrifuge for 1 min to collect the fragmented genomic DNA into the lower chamber.</li>
	<li>Transfer the fragmented genomic DNA to a sterile low-DNA binding 1.5 mL tube, and analyze a portion on a low percentage agarose gel (0.6%) to confirm fragmentation to &#62;30 kb.</li>
</ol>
3. Fragmented Genomic DNA End-preparation
<ol>
	<li>Using 800 ng of fragmented genomic DNA in 45 &#181;L of deionized water, add 7 &#181;L end-prep reaction buffer (see Table of Materials), 3 &#181;L enzyme mix (see Table of Materials), and 5 &#181;L of nuclease free water.</li>
	<li>Mix by inversion and pulse centrifuge (1,000 x g for 5 s).</li>
	<li>Transfer sample to a 0.2 mL thin-walled tube, and incubate sample for 5 min at 20 &#176;C, followed by incubation at 65 &#176;C for 5 min.</li>
	<li>Pulse centrifuge to bring contents to the bottom of the tube.</li>
	<li>Transfer sample to a 1.5 mL low-DNA binding microcentrifuge tube.</li>
	<li>Prepare magnetic beads (see table of materials). Add 60 &#181;L of resuspended beads to the end prep reaction from step 3.5 and mix by pipetting.</li>
	<li>Incubate on a rotator mixer at 100 rpm (see Table of Materials) for 5 min at room temperature.</li>
	<li>Pulse centrifuge the sample to pellet the beads, then place the sample next to magnet.</li>
	<li>Once the beads are adhered to the magnet, pipette off supernatant and discard.</li>
	<li>Remove the tube from the magnet and wash beads with 200 &#181;L of freshly prepared 70% ethanol by gently pipetting the sample up-and-down.</li>
	<li>Pulse centrifuge to pellet the beads and return to the magnet.</li>
	<li>Remove the supernatant and discard. Repeat the washing step again using 200 &#181;L of 70% ethanol.</li>
	<li>Pulse centrifuge the tube, return to the magnet and remove all the 70% ethanol wash.</li>
	<li>With the microcentrifuge tube lid open, allow the beads to air dry for 5 min at room temperature.</li>
	<li>Remove the tube from magnet and suspend the pellet in 31 &#181;L of sterile, nuclease-free water. Incubate for 2 min at room temperature.</li>
	<li>Return the tube to the magnet until all the beads have pelleted and the eluate is clear.</li>
	<li>Transfer the eluate to a 1.5 mL microcentrifuge tube. Using 1 &#181;L of sample, quantify the end-prepped DNA using a UV spectrophotometer at 260 nm (see Table of Materials). 
	Note: The percent recovery should be ~70% (700 ng) from a starting concentration of 1 &#181;g of genomic DNA.</li>
</ol>
4. Adapter and Tether Addition to End-prepped Genomic DNA Fragments
<ol>
	<li>Mix all the blunt/TA ligase master mix tubes by inversion, and then pulse centrifuge to bring contents to the bottom.</li>
	<li>Using 30 &#181;L of end-prepped DNA, add 20 &#181;L of adapter mix, and 50 &#181;L of blunt/TA ligation master mix.</li>
	<li>Mix by inversion, pulse centrifuge, and incubate for 10 min at room temperature.</li>
</ol>
5. Magnetic Bead Preparation
<ol>
	<li>Vortex the beads and then transfer 50 &#181;L of suspended beads to a 1.5 mL microfuge tube.</li>
	<li>Place the tube on the magnet to pellet the beads until the eluate clears.</li>
	<li>Remove the supernatant and discard.</li>
	<li>Add 100 &#181;L of bead binding buffer (see Table of Materials for bead kit) to the beads, vortex to resuspend the beads, pellet the beads on the magnet, remove the supernatant and discard. Repeat the washing with 100 &#181;L of binding buffer.</li>
	<li>Add 100 &#181;L of bead binding buffer to the washed beads. Vortex to resuspend the beads.</li>
</ol>
6. Library Purification
<ol>
	<li>Using a P200 micropipette, add 40 &#181;L of beads from the previous step to the adapted/tethered genomic DNA. Mix the sample carefully by pipetting.</li>
	<li>Incubate the sample on a rotator mixer at 100 rpm for 5 min at room temperature.</li>
	<li>Place the sample on the magnet and allow the beads to settle. Pipette off the supernatant and discard.</li>
	<li>Resuspend the beads in 140 &#181;L of bead binding buffer by pipetting. Place the sample against the magnet, discard the supernatant, and wash again with another 140 &#181;L of bead binding buffer.</li>
	<li>Pulse centrifuge the tube, place the tube on the magnet for 2 min. Remove the remaining bead binding buffer from the pellet.</li>
</ol>
7. Elution of Library from Magnet Beads
<ol>
	<li>Resuspend the magnetic beads in 15 &#181;L of elution buffer by pipetting. Incubate the sample for 10 min at room temperature.</li>
	<li>Place the tube against the magnet to pellet the beads. When the solution clears, remove 15 &#181;L of eluate and transfer to a 1.5 mL microfuge tube, and place the sample on ice.</li>
	<li>Quantify the library using an UV spectrophotometer. 
	NOTE: The percent recovery should be ~25% (250 ng) from a starting concentration of 1 &#181;g of genomic DNA.</li>
</ol>
8. Starting a Run/Quality Control
<ol>
	<li>Remove the flow cell from packaging and attach the flow cell to the portable, real-time sequencer (see Table of Materials).</li>
	<li>Attach the sequencer to a computer via USB cable and start the sequencing software (see Table of Materials).</li>
	<li>Click &#34;Connect&#34; device through the sequencing software, select &#34;NC_Platform_QC.py&#34;, and click &#34;Start&#34;.</li>
	<li>The quality control (QC) takes approximately 6 - 7 min to complete; look for a &#39;sea of green&#39; (large areas of output) on the QC readout to confirm that there are enough active pores (&#62;800) for DNA sequencing.</li>
</ol>
9. Starting a Sequencing Run
<ol>
	<li>Open the sequencing program; a dialog box will appear. In the Sample ID box, name the sample.</li>
	<li>Click on the &#34;Flow Cell ID&#34; box and enter the code found on the sticker on the top of the flow cell.</li>
	<li>Open the flow cell lid and then slide the sample port cover to the right (clockwise) so that the sample port is visible. Once the port is open, check for a small bubble. Remove a few microliters of buffer including the bubble.</li>
	<li>Check to be sure that there is buffer across the sensor array.Make the priming buffer by mixing 480 &#181;L of running buffer with fuel mix (RBF-1, see the Table of Materials) (be sure to mix thoroughly first) with 520 &#181;L nuclease-free water.</li>
	<li>Add 800 &#181;L of the priming buffer to the priming port. Carefully lift the &#34;SpotOn&#34; cover to make it accessible.</li>
	<li>After 5 min, add an additional 200 &#181;L of priming buffer to the priming port.</li>
</ol>
10. Loading the Library
<ol>
	<li>Before preparing the library place the following reagents on ice: RBF-1 (from the sequencing kit), adapted and tethered library, and library loading beads (LLB; from the sequencing kit).</li>
	<li>To a 0.2 mL centrifuge tube, add 25.5 &#181;L of RBF and 12 &#181;L of nuclease-free water kept at room temperature.</li>
	<li>Mix the LLB by pipetting up-and-down. Add 26.5 &#181;L of the LLB to the 0.2 &#181;L tube. Mix the reagents by pipetting up-and-down. 
	NOTE: The LLB tends to settle out of the mixture.</li>
	<li>Add 11 &#181;L of the adapted and tethered library to the 0.2 &#181;L tube. Mix by inversion and spin down by pulse centrifugation.</li>
	<li>Add 75 &#181;L of sample from step 9.4 to the &#34;SpotOn&#34; port dropwise. Make sure that each drop flows into the port before adding the next.</li>
	<li>Carefully replace the sample port cover so that the bung enters the port, and replace the device lid.</li>
</ol>
11. Starting a Sequencing Software Protocol Script
<ol>
	<li>Open the dropdown menu under &#39;Select Program&#39; and select &#34;48 hour sequencing.&#34;</li>
	<li>Click on the &#34;Execute&#34; button to start the script.</li>
	<li>Check the results of the Mux scan reported in the notification stream for the number of active pores in the MUX scan. 
	&#8203;NOTE: This number may differ from the number of pores in the QC run and a large difference may indicate a problem.
	<ol>
		<li>If there is a significant reduction of active pores from the QC run, restart the software, and if there is still a significant difference, reboot the computer.</li>
	</ol>
	</li>
	<li>Check that the heatsink temperature is 34 &#176;C as reported by the sequencing software script. 
	NOTE: If the temperature is not at 34 &#176;C then there will not be enough active pores for the run.</li>
	<li>Check the histogram of read lengths to determine if the sequence lengths are expected and appropriate for the experimental design.</li>
	<li>Close the desktop agent using &#39;close x.&#39;&#160;Quit the sequencing software by closing down the web GUI. Disconnect the device from the computer.</li>
</ol>
12. Analysis of Run and Results
Note: During the sequencing run, the data can be monitored using the &#34;VIEW REPORT&#34; program using the desktop agent. During or after the run is complete, files are available in a FAST5 file format in the data &#8594; reads &#8594;&#160;pass folder (default). If this folder is open while sequencing is active, the computer may freeze.
<ol>
	<li>To view and manipulate sequences, download a &#34;HDFViewer&#34; .</li>
	<li>To view the sequencing files, directly open the HDF viewer &#8594;&#160;open Data folder &#8594;&#160;select All file types &#8594;&#160;select C: drive (default) &#8594;&#160;select data &#8594;&#160;select reads &#8594;&#160;select pass.</li>
	<li>Find and select the FASTQ file in the left dropdown menu; files will open and can be saved in FASTQ format. 
	NOTE: For the purpose of the student experiment, sequences of 350 nucleotides or longer were selected for further analysis. Output from the base calling allows the user to sort sequence reads based on size. FASTQ files can be analyzed via BLAST (NCBI) or other bioinformatics programs.</li>
</ol>

<ol>
	<li>Quick, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time,+portable+genome+sequencing+for+Ebola+surveillance.">Real-time, portable genome sequencing for Ebola surveillance.</a> Nature. 530 (7589), 228-232 (2016).</li><li>Greninger, A. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+metagenomics+identification+of+viral+pathogens+in+clinical+samples+by+real-time+nanopore+sequencing+analysis.">Rapid metagenomics identification of viral pathogens in clinical samples by real-time nanopore sequencing analysis.</a> Genome Med. 7, 99 (2015).</li><li>Quick, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+draft+sequencing+and+real-time+nanopore+sequencing+in+a+hospital+outbreak+of+Salmonella.">Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella.</a> Genome Biology. 16, 114 (2015).</li><li>Ashton, P. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MinION+nanopore+sequencing+identifies+the+position+and+structure+of+a+bacterial+antibiotic+resistance+island.">MinION nanopore sequencing identifies the position and structure of a bacterial antibiotic resistance island.</a> Nat Biotechnol. 33, 296-300 (2015).</li><li>Loman, N. J., Quick, J., Simpson, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+complete+bacterial+genome+assembled+de+novo.+using+only+nanopore+sequencing+data.">A complete bacterial genome assembled de novo. using only nanopore sequencing data.</a> Nat Method. 12, 733-735 (2015).</li><li>Hoenen, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanopore+Sequencing+as+a+Rapidly+Deployable+Outbreak+Tool.">Nanopore Sequencing as a Rapidly Deployable Outbreak Tool.</a> Emerg Infect Dis. 22 (2), 331-334 (2016).</li><li>Petrosino, J. F., Highlander, S., Luna, R. A., Gibbs, R. A., Versalovic, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metagenomic+pyrosequencing+and+microbial+identification.">Metagenomic pyrosequencing and microbial identification.</a> Clin Chem. 55 (5), 856-866 (2009).</li><li>Cummings, P. J., Ahmed, R., Durocher, J. A., Jessen, A., Vardi, T., Obom, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pyrosequencing+for+Microbial+Identification+and+Characterization.">Pyrosequencing for Microbial Identification and Characterization.</a> J. Vis. Exp. (78), e50405 (2013).</li><li>Rothberg, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+integrated+semi-conductor+device+that+enabling+non-optical+genome+sequencing.">An integrated semi-conductor device that enabling non-optical genome sequencing.</a> Nature. 475, 348-352 (2011).</li><li>Levene, M. J., Korlach, J., Turner, S. W., Foquet, M., Craighead, H. G., Webb, W. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zero-mode+Waveguides+for+Single-Molecule+Analysis+at+high+concentrations.">Zero-mode Waveguides for Single-Molecule Analysis at high concentrations.</a> Science. 299, 682-686 (2003).</li><li>Eid, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-Time+DNA+Sequencing+from+Single+Polymerase+Molecules.">Real-Time DNA Sequencing from Single Polymerase Molecules.</a> Science. 323, 133-138 (2009).</li><li>Stoddart, D., Heron, A. J., Mikhailova, E., Maglia, G., Bayley, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-nucleotide+discrimination+in+immobilized+DNA+oligonucleotides+with+a+biological+nanopore.">Single-nucleotide discrimination in immobilized DNA oligonucleotides with a biological nanopore.</a> PNAS. 106, 7702-7707 (2009).</li><li>Shendure, J., Hanlee, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next+generation+DNA+sequencing.">Next generation DNA sequencing.</a> Nat Biotechnol. 26, 1135-1145 (2008).</li><li>Daniel, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Metagenomics+of+Soil.">The Metagenomics of Soil.</a> Nat Rev Microbiol. 3, 470-478 (2005).</li></ol>

The authors have no disclosures.

Many next generation sequencing methods have been generated and each depends on sequencing by synthesis but the detection platforms for identifying nucleotides differ. NS, the most recent addition to the marketplace, uses a different method entirely, which does not require a sequencing reaction or labeled nucleotides. This method takes advantage of charge differential of already incorporated nucleotides as they pass through an electrified pore. The identification of each nucleotide occurs by modulation of the electrical current by the different bases as they pass through the nanopore. This multiplexed system allows the user to sequence many fragments at a time. By sequencing both strands of the DNA, the accuracy of the sequence is significantly increased and the sequencing software, which can be loaded onto a laptop computer, processes the signals and provides the sequence information that can be analyzed.
In pyrosequencing, a sequencing by synthesis (SBS) method, detection of the specific base incorporated into the template depends on the luciferase assay and the generation of chemiluminescent signals8. In ion semiconductor sequencing, the released hydrogen ion, which decreases the pH is detected by an ion sensor9. Single molecule real-time sequencing depends on the zero mode wave guide (ZMW)10, which illuminates for detection a florescent molecule tagged to the incorporated nucleotide. SBS uses a unique method to amplify the target DNA such that clusters of unique sequences are generated13. Detection of the added nucleotide is achieved when the fluorescence of the tagged nucleotide is recorded. NS on the other hand has unique advantage over other methods in that it requires limited technical resources, is portable, produces long sequencing reads, requires no prior DNA amplification, and can be operated at a reduced cost compared to other methods. Our students found the newer, rapid library prep protocol to be straightforward and amenable to a three hour lab class. Some of the issues we encountered were bubbles in the flow cell which were difficult to remove, it required significant computer power (one terabyte of storage), the current output of data is in a FAST5 file, and the sequencing flow cell has a limited shelf life before it deteriorates. In addition, other disadvantages of the NS Ligation sequencing protocol (long protocol) is that it requires several library preparation steps, requires expertise in molecular biology techniques, and generates reduced sequencing fidelity when compared to some sequencing methodologies3. However, recent advances with the new rapid library preparation kit requires only 10 min for library preparation and has demonstrated a reduced sequencing error rate. The new library preparation method was very amenable for use in a lab class.
There are several critical steps in the protocol, particularly in the QC of the flow cell. This includes performing an initial QC within five days of the receipt of the flow cell and using them within 8 weeks. Although we have used flow cells that were beyond 8 weeks, the number of open/active pores is greatly reduced. It is important that experiments are planned to fit a timeline where maximum use of the flow cells is achieved. We have used the cleaning protocol and reused the flow cells with success.
Investigating the metagenomics of soil represent an untapped genetic reservoir of microbial diversity. For example, one gram of soil is estimated to contain between 107&#160;- 109 prokaryotic cells14. Moreover, soil organisms are a main source of novel natural products, enzymes, and antibiotics. Thus, soil metagenomics DNA sequence analysis represents a valuable instructional tool for students at every level of education. The NS technology&#39;s ease of use and low cost make this system a very effective teaching tool. Students can sequence environmental samples, and upon completion of the sequence use available bioinformatics tools to identify and characterize microbes and metagenomics sequences in test samples. Using the NS technology, students have true hands-on experience, which has until now been out of reach for use in laboratory courses because of the advanced technical expertise and high reagent, equipment, and maintenance costs in other sequencing platforms. Recently, one of our students (J. Harrison, personal communication) reported the use of this technology in an environmental monitoring project of farm soils. We expect that there will be many more applications for this technology in the education space.

The goal of this procedure is to demonstrate the steps required for preparation of an environmental DNA library for sequencing, utilization of a nanopore flow cell sequencing device, and to perform analysis of the generated DNA sequences using system software and the National Center for Biotechnology Information (NCBI) bioinformatics tools to identify microbial species in soil. Currently, most DNA sequencing platforms require a major investment in technical training and complex instrumentation, which is not feasible in resource poor environments or in field applications. The nanopore sequencing (NS) platform eliminates these issues with a cost effective, simple to use library preparation protocol, and a portable device to sequence and analyze a variety of different types of nucleic acids1,3. We have incorporated the NS platform into several lab classes for master&#39;s degree students.
Nanopore technology for sequencing biomolecules has demonstrated wide applications in the life sciences, including identification of bacterial and viral pathogens1,2,6, environmental biodiversity studies, food safety monitoring, genomic analysis3,5, and characterization of bacterial antibiotic resistance4. NS is a fast and accurate method to sequence nucleic acids that is based on the principle of &#34;strand sequencing&#34; by detecting electrical disruption by individual nucleotide bases when single stranded DNA passes through a nanopore inserted into an electrified synthetic polymer membrane. The steps involved in preparing DNA for NS include genome fragmentation, end repair and 3&#39; dA-tailing of genomic fragments, adaptor and tether annealing to the DNA, DNA library purification, and loading the library into the nanopore flow cell device. Fragmentation of the genome into ~8 kb sizes is accomplished by centrifuging 1 - 2 &#181;g of genomic DNA through a g-tube fragmentation tube. The fragmented genomic ends are then repaired and tailed with poly dA using a commercially available kit. Single stranded adapter sequences, which are compatible with the nanopore motor protein, are added to DNA ends which are used to guide the DNA sequence through the nanopore (Figure 1). The tether sequences are required for DNA purification and for localizing the DNA molecules to the pore membrane. The hairpin is generated by ligating a hairpin adapter to one end of the dA tailed library. The hairpin structures at the DNA ends allows reading of the sense and antisense strands as the DNA passes through the nanopore (Figure 2). The prepared genomic library is then purified from the reaction by using streptavidin beads using a magnetic field, followed by loading the sample into the nanopore flow cell for analysis.
The sequenced DNA is assessed for quality and sequencing reads that are acceptable for analysis are then subjected to several bioinformatics tools to identify microbes. The sequences are &#34;translated&#34; into a FASTQ from a FAST5 format. In the FASTQ format, the sequences can then be used in BLAST analysis.

<table border="0" cellpadding="0" cellspacing="0" style="width:625px;" width="626">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Thermal Cycler</td>
			<td style="width:124px;">LifeECO</td>
			<td style="width:119px;">BTC42096</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Covaris g-TUBE</td>
			<td style="width:124px;">Covaris</td>
			<td align="right" style="width:119px;">520079</td>
			<td></td>
		</tr>
		<tr height="45">
			<td height="45" style="height:45px;">NEBNext End Repair Module</td>
			<td style="width:124px;">New England BioLab</td>
			<td style="width:119px;">E7546</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Eppendorf LoBind Centrifuge Tubes</td>
			<td style="width:124px;">Sigma-Aldrich</td>
			<td style="width:119px;">Z666505</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;">NEB Blunt/TA Ligase Master Mix</td>
			<td style="width:124px;">New England BioLab</td>
			<td style="width:119px;">MO367</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MyOne C1 Strepavidin Beads</td>
			<td style="width:124px;">Thermo Fisher</td>
			<td align="right">65001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Eppendorf microcentrifuge</td>
			<td style="width:124px;">Eppendorf</td>
			<td></td>
			<td>Model 5420</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Nanodrop UV spectrophotometer</td>
			<td style="width:124px;">Thermo Fisher</td>
			<td style="width:119px;">ND-2000</td>
			<td>Model 2000</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Belly Dancer Orbital Shaker</td>
			<td style="width:124px;">Sigma-Aldrich</td>
			<td style="width:119px;">Z768499</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Power Soil DNA Isolation Kit</td>
			<td style="width:124px;">MO BIO</td>
			<td style="width:119px;">12888-50</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Ligation Sequencing Kit 2D</td>
			<td style="width:124px;">Oxford Nanopore&#160;</td>
			<td style="width:119px;">SQK-LSK208</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Rapid Sequencing Kit for Genomic DNA</td>
			<td style="width:124px;">Oxford Nanopore&#160;</td>
			<td style="width:119px;">SQK-RAD002</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">End-Prep Reaction Buffer and enzyme mix (NEB Blunt/TA Ligase Naster Mix)</td>
			<td style="width:124px;">New England BioLab</td>
			<td style="width:119px;">MO367</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">AmPure XP Magnetic Beads</td>
			<td style="width:124px;">Beckman Coulter</td>
			<td style="width:119px;">A63880</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Basic Starter Pack&#160;</td>
			<td style="width:124px;">Oxford Nanopore&#160;</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">Includes MinION&#160; Sequencing Device and Flow Cell</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">MinKNOW software</td>
			<td style="width:124px;">Oxford Nanopore&#160;</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="126">
			<td height="126" style="height:126px;width:216px;">Rapid Sequencing Kit for Genomic DNA</td>
			<td style="width:124px;">Oxford Nanopore&#160;</td>
			<td style="width:119px;">SQK-RAD002</td>
			<td style="width:167px;">Includes Running Buffer with Fuel (RBF), Fragmentation Mix (FRM) Rapid Adapter (RAD) Library Lodaing Beads (LLB)</td>
		</tr>
	</tbody>
</table>

nanopore dna sequencing for metagenomic soil analysis

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA sequences identified using computer software. Nanopore DNA sequencing is a flexible technique that allows for rapid microbial genome sequencing to identify bacterial and viral species, to characterize bacterial strains, and to detect genetic mutations that confer resistance to antibiotics. The advantages of nanopore sequencing (NS) for life sciences include its low complexity, reduced cost, and rapid real-time sequencing of purified genomic DNA, PCR amplicons, cDNA samples, or RNA. NS is an example of "strand sequencing" which involves sequencing DNA by guiding a single stranded DNA molecule through a nanopore that is inserted into a synthetic polymer membrane. The membrane has an electrical current applied across it, so as the individual bases pass through the nanopore the electrical current is disrupted to varying degrees by the four nucleotide bases. The identification of each nucleotide occurs by detecting the characteristic modulation of the electrical current by the different bases as they pass through the nanopore. The NS system consists of a handheld, USB powered portable device and a disposable flow cell that contains a nanopore array. The portable device plugs into a standard laptop computer that reads and records the DNA sequence using computer software.

The experimental design and nanopore technology provided a fast and inexpensive method for students to sequence soil DNA. The representative run passed the quality control parameters with more than 800 pores available for sequencing. The run resulted in over 125,000 reads available for study with a median sequence length of 5.38 kb. Sequences are given a quality score and only those sequences with acceptable scores were then analyzed. As the output of the sequencing reaction is in FAST5 format, which is not accepted by programs such as BLAST (NCBI), the sequences were viewed in the HDF viewer which converts the sequences to FASTQ format, which is compatible for BLAST analysis. In future iterations of the software, the data will be available as a FASTQ format, eliminating the need for the HDF viewer. See Supplementary Figures 1, 2, and 3. 
Fifty sequences of over 350 nucleotides in length were subject to analysis by BLASTN (nucleotides against nucleotide database) or BLASTX (nucleotides translated into amino acid sequence) (NCBI) to identify organisms in the soil sample. Given the time constraints of the class and that the focus of the course is on laboratory methods and not bioinformatics, we have the students analyze sequences within these parameters. Our bioinformatics classes can use the data for development of pipeline analysis tools. This level of bioinformatics analysis is not covered in the laboratory based class. Table 1 is a list of the organisms that were identified with e values of less than 4 e-04. Generally, e-values less than 4 e-04 indicate strong similarity between the input sequence (query) and the matched sequence. The organisms identified by BLASTN (against the non-redundant (nr) database) are from a wide variety of species and are available for further genomic and protein analyses. This sample of soil, which came from a garden in Baltimore County, MD had never been tested, so there were no previous data from which to determine what organisms might be in the soil. BLASTN analysis (against the nr database) analysis also indicated there were sequences with no similarities in the nr database. To determine if these are truly novel sequences, further study is needed. Analysis of several sequences by BLASTX revealed several proteins from organisms not represented in the BLASTN analysis. Table 2 lists several possible proteins including endopeptidases, and ATPases-like proteins. Using this library of sequences, students have the opportunity to use more sophisticated bioinformatics tools to perform further analysis, if directed by the instructor.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55979/55979fig1.jpg" /> 
Figure 1: Genomic library preparation. Steps for preparation of genomic DNA library for sequencing using nanopore technology. This figure has been modified with the necessary permissions. <a href="https://cloudflare.jove.com/files/ftp_upload/55979/55979fig1large.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/55979/55979fig2.jpg" /> 
Figure 2. Schematic of DNA sequencing using a nanopore. DNA passing through a nanopore membrane with electrical signal generation and base identification. This figure has been modified with the necessary permissions. <a href="https://cloudflare.jove.com/files/ftp_upload/55979/55979fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Organism</td>
			<td>e value</td>
		</tr>
		<tr>
			<td>Streptomyces sp.</td>
			<td>3.00E-06</td>
		</tr>
		<tr>
			<td>Nocardoides sp.</td>
			<td>5.00E-04</td>
		</tr>
		<tr>
			<td>Gordonia sp.</td>
			<td>5.00E-04</td>
		</tr>
		<tr>
			<td>Hyphomicrobium nitrativorens</td>
			<td>1.00E-139</td>
		</tr>
		<tr>
			<td>Starkeya novella</td>
			<td>1.00E-31</td>
		</tr>
		<tr>
			<td>Hyphomicrobium denitrificans</td>
			<td>1.00E-30</td>
		</tr>
		<tr>
			<td>Fibomicrobium sp.</td>
			<td>5.00E-17</td>
		</tr>
		<tr>
			<td>Pseudomonas sp.</td>
			<td>2.00E-15</td>
		</tr>
		<tr>
			<td>Rhodothemus marinus</td>
			<td>1.00E-17</td>
		</tr>
		<tr>
			<td>Turneiella parva</td>
			<td>2.00E-24</td>
		</tr>
		<tr>
			<td>E. coli</td>
			<td>0.00E+00</td>
		</tr>
		<tr>
			<td>Bradyrhizobium sp.</td>
			<td>3.00E-30</td>
		</tr>
		<tr>
			<td>Gemmatirosa kalamazoonesis</td>
			<td>1.00E-20</td>
		</tr>
		<tr>
			<td>Burkholderia sp.</td>
			<td>8.00E-10</td>
		</tr>
		<tr>
			<td>Sphingomonas sp.</td>
			<td>8.00E-10</td>
		</tr>
		<tr>
			<td>Cellumonas sp.</td>
			<td>6.00E-11</td>
		</tr>
	</tbody>
</table>
Table 1: Selected results of BLASTN analysis. Soil metagenomics DNA sequences subjected to BLASTN similarity search against the NCBI non-redundant nucleotide database. The data reported have e-values of 4 x e-4 or less.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Protein&#160;</td>
			<td>Organism</td>
		</tr>
		<tr>
			<td>Hypothetical protein&#160;</td>
			<td>Acidobacter bacterium</td>
		</tr>
		<tr>
			<td>SAM dependent methyltransferase&#160;&#160;</td>
			<td>H. denitrificans</td>
		</tr>
		<tr>
			<td>ATPase&#160;</td>
			<td>&#160;Jannaschia sp.</td>
		</tr>
		<tr>
			<td>Endopeptidase&#160;</td>
			<td>Shigella sonnei</td>
		</tr>
		<tr>
			<td>Lysis protein&#160;</td>
			<td>E. coli</td>
		</tr>
	</tbody>
</table>
Table 2: Selected results of BLASTX analysis. Soil metagenomics DNA sequences subjected to BLASTX similarity search against the NCBI non-redundant protein database.
<img alt="Supplemental Figure 1" src="/files/ftp_upload/55979/55979supfig1.jpg" /> 
Supplemental Figure 1: Platform QC results. The results of the platform QC are presented. In the upper right corner are the results of the QC for active pores. Each quadrant of the flow cell is tested for active pores. The main page is dynamic and changes as each quadrant is tested. In this run, 1,414 single pores were detected. <a href="https://cloudflare.jove.com/files/ftp_upload/55979/55979supfig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Supplemental Figure 2" src="/files/ftp_upload/55979/55979supfig2.jpg" /> 
Supplemental Figure 2: Converting FAST5 files to FASTQ files. Here on the right side, is the output of the data from the sequencing run. Each line represents an individual sequence. The left side of the figure shows the highlighted sequence from the right side, in the HDF viewer that converts the sequence to a FASTQ file which can be used for further analysis. <a href="https://cloudflare.jove.com/files/ftp_upload/55979/55979supfig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Supplemental Figure 3" src="/files/ftp_upload/55979/55979supfig3.jpg" /> 
Supplemental Figure 3: Example of FASTQ sequence in HDF viewer. This sequence (read 803) is in a FASTQ file which converts the FAST5 data into nucleotides. <a href="https://cloudflare.jove.com/files/ftp_upload/55979/55979supfig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Nanopore DNA Sequencing for Metagenomic Soil Analysis at JoVE.com

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA ...

nanopore-dna-sequencing-for-metagenomic-soil-analysis

Research

JoVE Journal

Environment

30.1K Views.  Johns Hopkins University. Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.

Video: Nanopore DNA Sequencing for Metagenomic Soil Analysis

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes and soil organic matter formation to small-scale stable-isotope biomarker probing. Coupling multiple stable isotopes such as 13C with 15N, 18O or&#160;2H has the potential to reveal even more information about complex stoichiometric relationships during biogeochemical transformations. Isotope labeled plant material has been used in various studies of litter decomposition and soil organic matter formation1-4. From these and other studies, however, it has become apparent that structural components of plant material behave differently than metabolic components (i.e. leachable low molecular weight compounds) in terms of microbial utilization and long-term carbon storage5-7. The ability to study structural and metabolic components separately provides a powerful new tool for advancing the forefront of ecosystem biogeochemical studies. Here we describe a method for producing 13C and 15N labeled plant material that is either uniformly labeled throughout the plant or differentially labeled in structural and metabolic plant components.
Here, we present the construction and operation of a continuous 13C and 15N labeling chamber that can be modified to meet various research needs. Uniformly labeled plant material is produced by continuous labeling from seedling to harvest, while differential labeling is achieved by removing the growing plants from the chamber weeks prior to harvest. Representative results from growing Andropogon gerardii Kaw demonstrate the system&#39;s ability to efficiently label plant material at the targeted levels. Through this method we have produced plant material with a 4.4 atom%13C and 6.7 atom%15N uniform plant label, or material that is differentially labeled by up to 1.29 atom%13C and 0.56 atom%15N in its metabolic and structural components (hot water extractable and hot water residual components, respectively). Challenges lie in maintaining proper temperature, humidity, CO2 concentration,&#160;and light levels in an airtight 13C-CO2 atmosphere for successful plant production. This chamber description represents a useful research tool to effectively produce uniformly or differentially multi-isotope labeled plant material for use in experiments on ecosystem biogeochemical cycling.

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

This method explains how to build and operate a continuous 13C and 15N isotope labeling chamber for uniform or differential plant tissue labeling. Representative results from metabolic and structural labeling of Andropogon gerardii are discussed.

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes ...

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community&#8217;s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as ...

Air-sampled Filter Analysis for Endotoxins and DNA Content

Outdoor aerosol research commonly uses particulate matter sampled on filters. This procedure enables various characterizations of the collected particles to be performed in parallel. The purpose of the method presented here is to obtain a highly accurate and reliable analysis of the endotoxin and DNA content of bio-aerosols extracted from filters. The extraction of high molecular weight organic molecules, such as lipopolysaccharides, from sampled filters involves shaking the sample in a pyrogen-free water-based medium. The subsequent analysis is based on an enzymatic reaction that can be detected using a turbidimetric measurement. As a result of the high organic content on the sampled filters, the extraction of DNA from the samples is performed using a commercial DNA extraction kit that was originally designed for soils and modified to improve the DNA yield. The detection and quantification of specific microbial species using quantitative polymerase chain reaction (q-PCR) analysis are described and compared with other available methods.

Two complementary analyses of atmospheric biological particles from air sampled filters are described herein: the extraction and detection of endotoxin, and of DNA.

Outdoor aerosol research commonly uses particulate matter sampled on filters. This procedure enables various characterizations of the collected particles ...

A Protocol for Collecting and Constructing Soil Core Lysimeters

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the landscape has complex and varied soil morphology, an accompanying disparity in flow paths for leachate through the soil macropore and matrix structure is present. The rate of flow through these paths is further affected by antecedent soil moisture. Lysimeters are used to quantify flow rate, volume of water and concentration of nutrients leaching downward through soils. While many lysimeter designs exist, accurately determining the volume of water and mass balance of nutrients is best accomplished with bounded lysimeters that leave the natural soil structure intact. 
Here we present a detailed method for the extraction and construction of soil core lysimeters equipped with soil moisture sensors at 5 cm and 25 cm depths. Lysimeters from four different Coastal Plain soils (Bojac, Evesboro, Quindocqua and Sassafras) were collected on the Delmarva Peninsula and moved to an indoor climate controlled facility. Soils were irrigated once weekly with the equivalent of 2 cm of rainfall to draw down soil nitrate-N concentrations. At the end of the draw down period, poultry litter was applied (162 kg TN ha-1) and leaching was resumed for an additional five weeks. Total recovery of applied irrigation water varied from 71% to 85%. Nitrate-N concentration varied over the course of the study from an average of 27.1 mg L-1 before litter application to 40.3 mg L-1 following litter application. While greatest flux of nutrients was measured in soils dominated by coarse sand (Sassafras) the greatest immediate flux occurred from the finest textured soil with pronounced macropore development (Quindocqua).

A detailed method for extraction and assembly of intact soil core lysimeters and their use for study of leachate and associated loss of nutrients from surface applied poultry litter is demonstrated.

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the ...

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Protocols for Quantifying Transferable Pesticide Residues in Turfgrass Systems

Plant canopies in established turfgrass systems can intercept an appreciable amount of sprayed pesticides, which can be transferred through various routes onto humans. For this reason, transferable pesticide residue experiments are required for registration and re-registration by the United States Environmental Protection Agency (USEPA). Although such experiments are required, limited specificity is required pertaining to experimental approach. Experimental approaches used to assess pesticide transfer to humans including hand wiping with cotton gloves, modified California roller (moving a roller of known mass over cotton cloth) and soccer ball roll (ball wrapped with sorbent strip) over three treated turfgrass species (creeping bentgrass, hybrid bermudagrass and tall fescue maintained at 0.4, 5 and 9 cm, respectively) are presented. The modified California roller is the most extensively utilized approach to date, and is best suited for use at low mowing heights due to its reproducibility and large sampling area. The soccer ball roll is a less aggressive transfer approach; however, it mimics a very common occurrence in the most popular international sport, and has many implications for nondietary pesticide exposure from hand-to-mouth contact. Additionally, this approach may be adjusted for other athletic activities with limited modification. Hand wiping is the best approach to transfer pesticides at higher mowing heights, as roller-based approaches can lay blades over; however, it is more subjective due to more variable sampling pressure. Utility of these methods across turfgrass species is presented, and additional considerations to conduct transferable pesticide residue research in turfgrass systems are discussed.

Transferable pesticide residue experiments in turfgrass systems are integral components of human risk exposure assessments. Experimental approaches to measure transferable residues should be adjusted to the human interaction of interest and turfgrass system dynamics. Three transferable pesticide residue protocols are presented and the suitability across three turfgrass systems is discussed.

Plant canopies in established turfgrass systems can intercept an appreciable amount of sprayed pesticides, which can be transferred through various routes ...

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 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 ...

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonate (CaCO3) profiles. The objective is to describe a simple conceptual model and detailed protocol for repeatable field and laboratory measurements of these quantities. Here, accurate elevation is measured using a ground-based differential global positioning system (GPS); other data acquisition methods could be applied to the same basic method. Soil samples are collected from prescribed depth intervals and analyzed in the lab using an efficient and precise modified pressure-calcimeter method for quantitative analysis of inorganic carbon concentration. Standard statistical methods are applied to point data, and representative results show significant correlations between changes in soil surface layer CaCO3 and changes in elevation consistent with the conceptual model; CaCO3 generally decreased in depositional areas and increased in erosional areas. Maps are derived from point measurements of elevation and soil CaCO3 to aid analyses. A map of erosional and depositional patterns at the study site, a rain-fed winter wheat field cropped in alternating wheat-fallow strips, shows the interacting effects of water and wind erosion affected by management and topography. Alternative sampling methods and depth intervals are discussed and recommended for future work relating soil erosion and deposition to soil CaCO3.

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonates. Repeatable methods for field and laboratory measurements of these quantities and data analysis methods are described here.

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes ...

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA

Traditional methods of identifying fungal exposures in occupational environments, such as culture and microscopy-based approaches, have several limitations that have resulted in the exclusion of many species. Advances in the field over the last two decades have led occupational health researchers to turn to molecular-based approaches for identifying fungal hazards. These methods have resulted in the detection of many species within indoor and occupational environments that have not been detected using traditional methods. This protocol details an approach for determining fungal diversity within air samples through genomic DNA extraction, amplification, sequencing, and taxonomic identification of fungal internal transcribed spacer (ITS) regions. ITS sequencing results in the detection of many fungal species that are either not detected or difficult to identify to species level using culture or microscopy. While these methods do not provide quantitative measures of fungal burden, they offer a new approach to hazard identification and can be used to determine overall species richness and diversity within an occupational environment.

Determining the fungal diversity within an environment is a method utilized in occupational health studies to identify health hazards. This protocol describes DNA extraction from occupational air samples for amplification and sequencing of fungal ITS regions. This approach detects many fungal species that can be overlooked by traditional assessment methods.

Traditional methods of identifying fungal exposures in occupational environments, such as culture and microscopy-based approaches, have several ...

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 ...