This publication has emanated from research conducted with the financial support of the Natural Environment Research Council (NERC) under grant number NERC NE/JO11959/1 and Science Foundation Ireland &#38; the Marie-Curie Action COFUND under Grant Number 11/SIRG/B2159awarded to CJS and the Eastern Academic Research Consortium (Eastern ARC).

1. DNA &#38; RNA Extraction from Marine Coastal Sediments
<ol>
	<li>Preparation of ribonuclease (RNAse)-free material and workspace
	<ol>
		<li>Prepare RNAse-free distilled water (dH2O) by treating with 0.1% diethylpyrocarbonate (DEPC) and incubate at 37 &#176;C O/N. Remove residual DEPC by autoclaving dH2O at 121 &#176;C for 15 min. Use DEPC treated dH2O to make all solutions.</li>
		<li>Bake all glassware at 180 &#176;C O/N. Remove plastic lids and rims, soak them in a solution of 2 M NaOH O/N, and rinse them with DEPC treated dH2O before use.</li>
		<li>Prepare a CTAB-Phosphate buffer solution as per Table 1.</li>
		<li>Prepare the PEG-NaCl precipitation solution as per Table 2.</li>
		<li>Clean all working surfaces (i.e., bench, microcentrifuge, fume-hood) and micropipettes using RNAse-decontaminating solution before starting. Wear gloves during the entire procedure.</li>
		<li>Use RNAse-free plasticware along with micropipette filter tips to avoid sample cross-contamination.</li>
	</ol>
	</li>
	<li>Environmental sample collection and storage
	<ol>
		<li>Collect coastal sediment during low tide using a sterile 50 ml falcon tube from the top 2.5 cm. Collect approximately 15-20 g of sediments. Carefully close the lid after sample collection. Transport immediately to the lab in a cooler at 4 &#176;C for immediate processing.</li>
		<li>Homogenize the sample by mixing with a sterile spatula and aliquot 0.5 g of wet weight sediment into a 2 ml bead beating tube. Aliquot additional replicates, flash-freeze by placing in liquid nitrogen. Store aliquots at -80 &#176;C. Caution: Wear protective gloves and safety goggles when handling liquid nitrogen. 
		Note: If the field site is not located close to a laboratory, aliquot 0.5 g of sediment into 2 ml sterile microcentrifuge tubes at the field site. Flash-freeze the tubes by putting them immediately into liquid nitrogen and transport to the laboratory. Store samples at -80 &#176;C until processing.</li>
	</ol>
	</li>
	<li>Co-Extraction of DNA and RNA from sediment 
	Note: The following protocol is a modified version of the Griffiths method6.
	<ol>
		<li>Add 500 &#181;l CTAB-Phosphate buffer and 500 &#181;l phenol:chloroform:isoamyl alcohol (25:24:1) to the 2 ml bead-lysing tube containing 0.5 g of sediment and invert the tube 5-10 times to homogenize the sample. 
		Caution: Perform this step in a fume-hood wearing appropriate protective gear (i.e., laboratory coat, gloves and safety goggles) at all times.</li>
		<li>Vortex at full speed for 2.5 min. Centrifuge at 16,000 x g for 10 min at 4 &#176;C.</li>
		<li>In a fume-hood extract the top aqueous layer and transfer to a new 1.5 ml sterile microcentrifuge tube. Keeping the samples on ice, add 500 &#181;l of ice-cold chloroform:isoamyl alcohol (24:1).</li>
		<li>Invert several times until an emulsion is visible. Centrifuge for 10 min at 16,000 x g at 4 &#176;C.</li>
		<li>In a fume-hood extract the top aqueous layer and place it in a new 1.5 ml sterile tube. Precipitate the nucleic acids by adding two volumes of 30% PEG- NaCl solution and mix well.</li>
		<li>Incubate on ice for 2 hr or leave samples at 4 &#176;C O/N.</li>
		<li>At the end of incubation centrifuge samples at 16,000 x g for 20 min at 4 &#176;C. 
		Note: A pellet may be visible at the bottom of the tube.</li>
		<li>Gently remove the supernatant using a micropipette, make sure not to disturb the pellet. Leave around 10 &#181;l of PEG solution in the tube and add 1 ml of ice-cold 70% ethanol.</li>
		<li>Centrifuge for 20 min at 16,000 x g at 4 &#176;C. Slowly remove ethanol with a micropipette taking care not to touch the pellet.</li>
		<li>Centrifuge for 5 sec and remove residual ethanol using a micropipette. Leave the pellet to air dry for approximately 5 min.</li>
		<li>Re-suspend the pellet in 50 &#181;l DEPC-treated H2O. Examine the quality and yield of DNA/RNA by agarose gel electrophoresis running 5 &#181;l on a 1% agarose gel19. Divide the nucleic acids into two aliquots, 15 &#181;l for DNA and 30 &#181;l for RNA.</li>
		<li>Store the DNA at -80 &#176;C until needed. Isolate RNA as outlined in the next section.</li>
	</ol>
	</li>
</ol>
2. Preparation of RNA and Quality Check of DNA-free RNA&#160;
<ol>
	<li>Digestion of DNA
	<ol>
		<li>Add 3 &#181;l of DNAse I Buffer and 1.5 &#181;l of DNAse I to 30 &#181;l volume of nucleic acids, incubate at 37 &#176;C for 30 min.</li>
		<li>Mix the DNAse Inactivation reagent by vortexing for 30 sec. Add 4.8 &#181;l of the solution to the sample. Incubate at RT for 5 min, occasionally tap the bottom of the tubes to mix the solution.</li>
		<li>Centrifuge at 10,000 x g for 90 sec at RT, transfer the supernatant (RNA) into a new tube, taking care not to transfer precipitate which can inhibit downstream reactions.</li>
	</ol>
	</li>
	<li>RNA quality check
	<ol>
		<li>Add 2 &#181;l of RNA to 18 &#181;l of sterile RNAse-free dH2O to dilute 1:10.
		<ol>
			<li>In separate PCR reactions, add 1 &#181;l of neat or 1:10 dilution of RNA to a sterile 0.5 ml PCR tube. Add PCR reaction components to amplify the 16S rRNA gene as per Table 3. Include a &#34;positive&#34; (e.g., DNA extracted from a pure bacterial culture), a &#34;PCR inhibitor&#34; control (i.e., 1 &#181;l of positive pure culture DNA and 1 &#181;l of neat extracted RNA) and a &#34;negative&#34; control of sterile&#160;RNAse-free dH2O.</li>
		</ol>
		</li>
		<li>Set the thermocycler with the following amplification parameters: 95 &#176;C 5 min, (95 &#176;C 30 sec, 57 &#176;C 30 sec, 72 &#176;C 1 min) x 35 cycles, 72 &#176;C 10 min.</li>
		<li>Run 10% of the PCR product on a 1% agarose gel at 85 V for 40 min. Repeat the DNAse I treatment if a PCR product is formed in the environmental RNA samples.</li>
	</ol>
	</li>
</ol>
3. Generation of First Strand cDNA from RNA
<ol>
	<li>Add the reagents as per Table 4 to a RNAse/DNAse free 0.2 ml PCR tube.</li>
	<li>Incubate the sample at 65 &#176;C 5 min. Place on ice for at least 1 min and then incubate at 25 &#176;C for 10 min.</li>
	<li>To the same tube add the reagents listed in Table 5.</li>
	<li>Incubate the sample at 55 &#176;C for 50 min. Inactivate the reaction at 72 &#176;C for 10 min.</li>
	<li>Store cDNA at -20 &#176;C until use.</li>
</ol>
4. Quantitative PCR
<ol>
	<li>Generation of DNA standards for qPCR
	<ol>
		<li>Amplify bacterial 16S rRNA sequence20 (or any other sequence of interest) from genomic DNA extracted from pure culture with q-PCR primers (1369F &#38; 1492R21).</li>
		<li>Purify the PCR product using a commercial kit according to manufacturer&#39;s instructions.</li>
		<li>Clone the purified PCR product into a 3&#39;-T overhang cloning vector system according to manufacturer&#39;s instructions.</li>
		<li>Transform the vector containing the PCR insert into Escherichia coli JM109 competent cells according to manufacturer&#39;s instructions.</li>
		<li>Plate 50 &#181;l of transformation onto ampicillin (100 &#181;g/ml), X-gal (20 &#181;g/ml) and IPTG (0.5 mM) Luria Bertani agar plates (Tryptone 10 g/L, Yeast Extract 5 g/L, NaCl 10 g/L, Agar 15 g/L). Incubate O/N at 37 &#176;C.</li>
		<li>Select a single positive white transformant from the plate. Inoculate the positive transformant in 50 ml LB broth containing 100 &#181;g/ml ampicillin and incubate O/N shaking at 250 rpm at 37 &#176;C.</li>
		<li>From the O/N&#160;culture, isolate and purify the plasmid using a commercial kit according to manufacturer&#39;s instructions.</li>
		<li>Linearize the plasmid using an appropriate restriction enzyme that is capable of cutting the plasmid once (e.g., EcoRI).</li>
		<li>Analyze the purity of the plasmid by measuring the absorption ratio A260/A28019. If the ratio is below 1.8, re-extract the plasmid with phenol-chloroform19. Note: Pure DNA has a 1.8 ratio.</li>
		<li>Determine the concentration of plasmid DNA by absorbance at 260 nm using a spectrophotometer19. 
		Note: Alternatively, the accuracy of quantification can be improved by use of a fluorescent DNA-binding dye used in conjunction with a fluorometer.</li>
		<li>Sequence the plasmid insert to confirm the size of the target in bases. Calculate the amount (i.e., percentage) of insert DNA in the plasmid (e.g., in a 3,000 bp vector, a 123 bp DNA fragment is 3.9% of total DNA) and multiply it by the concentration obtained in 4.1.10, to determine the DNA concentration of the target (insert).</li>
		<li>Use the following equation to calculate the copies of target per &#181;l: 
		<img alt="Equation 1" src="/files/ftp_upload/54067/54067eq1.jpg" /></li>
		<li>Calculate the Target Molecular Weight (TMW) by multiplying the number of base pairs of the target DNA by the average molecular weight of double strand DNA (dsDNA, 660 Daltons per base pair).</li>
		<li>Dilute the target DNA in a range from 1010 to 102 copies using 2 &#181;l of DNA and 18 &#181;l of sterile dH2O. Mix each dilution well and spin down briefly before making the next dilution.</li>
	</ol>
	</li>
	<li>Generation of RNA standard curve for qPCR
	<ol>
		<li>From step 4.1.5, screen a number of white colonies (approximately 5) by colony PCR19 using the target reverse primer (i.e., R1492) and the forward vector plasmid primer M13F. 
		Note: This combination of primers will amplify inserts cloned in the correct sense orientation with a T7 promoter site upstream.</li>
		<li>Purify the PCR product using a commercial kit following manufacturer&#39;s instruction. Quantify the purified PCR product at 260 nm using a spectrophotometer.</li>
		<li>Add 200 ng of PCR product in a final volume of 20 &#181;l with 7.5 mM of each ribonucleotide, 1 T7 reaction buffer and 1 T7 polymerase enzyme for the in vitro transcription reaction.</li>
		<li>Incubate the reaction for 4 hr at 37 &#176;C. Add 1 unit of RNase-free DNase I to the reaction, incubate for 15 min at 37 &#176;C to remove DNA template.</li>
		<li>Recover the in vitro transcribed RNA by ethanol precipitation19 and quantify RNA yields using a fluorimeter or by absorbance at 260 nm.</li>
		<li>Calculate transcript number per &#181;l of RNA. Add the number of base pairs in the target RNA (e.g., 123 bases) to the length of the T7 promoter (153 bases) and multiply by the average molecular weight of RNA, 340 Daltons per base.</li>
		<li>Add 500 ng of quantified target RNA to a reverse transcriptase (RT) reaction as outlined in section 3. Serially dilute the cDNA as outlined in 4.1.13 for use as the standard curve.</li>
	</ol>
	</li>
	<li>Real-Time PCR
	<ol>
		<li>Thaw environmental DNA/cDNA samples, standards and qPCR reagents on ice. Protect the fluorogenic probe from light.</li>
		<li>Dilute the standards for the standard curve as outlined in 4.1.14. Make 1:10 dilutions of the environmental DNA/cDNA from neat to 10-3 by adding 2 &#181;l of sample to 18 &#181;l of sterile dH2O.</li>
		<li>Make a master mix reaction for the total number of reactions plus 10% as per Table 6 (primers and probe) and Table 7 (reaction mix). Mix well and briefly centrifuge.</li>
		<li>Add 19 &#181;l of master mix and 1 &#181;l of template (standard, environmental sample or water for negative control) to each well in a 96-well optical qPCR plate. Perform each reaction (standards, environmental samples and negative controls) in triplicate.</li>
		<li>Cover the 96-well plate with a q-PCR optical cover. Centrifuge the plate briefly. Load the plate into the heating block of the qPCR machine and close the lid.</li>
		<li>Open the qPCR manager software. Click the &#34;protocol tab&#34;, click &#34;create new&#34;, add the following amplification conditions: 3 min 95 &#176;C, (10 sec 95 &#176;C, 30 sec 60 &#176;C) x 40 cycles. Set sample volume to 20 &#181;l, click &#34;OK&#34; and save the protocol.</li>
		<li>Click the &#34;Plate&#34; tab. Under &#34;edit selected&#34; click &#34;select fluorophore&#34;, add the report dye for appropriate probe, e.g., fluorescein. Click &#34;OK&#34;.</li>
		<li>Highlight wells containing the standards, select &#34;standard&#34; from the &#34;sample type&#34; menu. Click &#34;replicate series&#34; to change &#34;replicate size&#34; to 3, click &#34;apply&#34;. Click &#34;dilution series&#34; to add calculated starting concentration for standard 1, indicate the dilution factor (10), select &#34;decreasing&#34; or &#34;increasing&#34; depending on the order the standard curve was added to the plate. Click &#34;apply&#34;.</li>
		<li>Highlight well positions containing the unknown samples, select &#34;unknown&#34; from the &#34;sample type&#34; drop down menu. Click &#34;replicate series&#34;, and change &#34;replicate size&#34; to 3. Click &#34;apply&#34;. Edit sample names under &#34;sample name&#34;. Repeat procedure for No Template Controls (NTC) wells.</li>
		<li>Click &#34;OK&#34; on the plate editor box and save file. Click &#34;start run&#34;.</li>
		<li>On completion of the run, the data analysis window will open. Click the &#34;quantification tab&#34; to display the standard curve, standard curve descriptors (Table 8) and amplification plots.</li>
		<li>Click on the &#34;quantification data&#34; tab for Cp values and corresponding starting quantity of gene (SQ) of unknown samples. Export table to spreadsheet software if required.</li>
		<li>Multiply gene abundances from unknown samples by the dilution factor, the quantity of sediment extracted from and the total volume nucleic acids were eluted in to obtain gene copies per gram of wet weight sediment. 
		Note: Elute DNA from 0.5 g of sediment in 50 &#181;l, dilute 1/10, add 1 &#181;l as template to a q-PCR reaction; calculate gene copies g-1 sediment by multiplying: gene copies &#181;l of DNA x dilution factor x elution volume x 2.</li>
	</ol>
	</li>
</ol>

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F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrated+metatrascriptomic+and+metagenomics+analyses+of+stratified+microbial+assemblages+in+the+open+ocean.">Integrated metatrascriptomic and metagenomics analyses of stratified microbial assemblages in the open ocean.</a> ISME J. 5, 999-1013 (2011).</li><li>Howe, A. C., Jansson, J. K., Malfatti, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tringe+S.G.,+Tiedje+J.M.,+&amp;+Brown+C.T.+Tackling+soil+diversity+with+the+assembly+of+large,+complex+metagenomes.">Tringe S.G., Tiedje J.M., &amp; Brown C.T. Tackling soil diversity with the assembly of large, complex metagenomes.</a> PNAS. 111 (13), 4904-4909 (2014).</li><li>Klaedtke, S., 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=Terroir+is+a+key+driver+of+seed-associated+microbial+assemblages.">Terroir is a key driver of seed-associated microbial assemblages.</a> Environ. Microbiol. , (2015).</li><li>Lueders, T., Wagner, B., Claus, P., Friedrich MW, . <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stable+isotope+probing+of+rRNA+and+DNA+reveals+a+dynamic+methylotroph+community+and+trophic+interactions+with+fungi+and+protozoa+in+oxic+rice+field+soil).">Stable isotope probing of rRNA and DNA reveals a dynamic methylotroph community and trophic interactions with fungi and protozoa in oxic rice field soil).</a> Environ. Microbiol. 6, 60-72 (2004).</li><li>Kunapuli, U., Lueders, T., Meckenstock, R. U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+stable+isotope+probing+to+identify+key+iron-reducing+microorganisms+involved+in+anaerobic+benzene+degradation.">The use of stable isotope probing to identify key iron-reducing microorganisms involved in anaerobic benzene degradation.</a> ISME J. 1, 643-653 (2007).</li><li>B&#252;rgmann, H., 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=Transcriptional+response+of+Silicibacter+pomeroyi+DSS-3+to+dimethylsulfoniopropionate+(DMSP).">Transcriptional response of Silicibacter pomeroyi DSS-3 to dimethylsulfoniopropionate (DMSP).</a> Environ. Microbiol. 9 (11), 2742-2755 (2007).</li><li>He, J. Z., 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=Geochip:+a+comprehensive+microarray+for+investigating+biogeochemical+ecological+and+environmental+processes.">Geochip: a comprehensive microarray for investigating biogeochemical ecological and environmental processes.</a> ISME J. 1, 67-77 (2007).</li></ol>

The authors have nothing to disclose.

The combination of DNA/RNA extraction with qPCR provides a fast, accurate, relatively cost-effective method for the sensitive quantification of gene and transcript abundances from a range of environmental samples, such as coastal sediments.
The initial nucleic acid extraction is the critical step to ensure a representative view of the microbial community present is achieved22. A number of limitations need to be considered for the extraction protocol: a) the achievement of total cell lysis, b) co-extraction of inhibitory compounds (e.g., humic acids or polyphenolics), c) contaminating DNA in the RNA fraction, d) rapid degradation of extracted nucleic acids when stored. Precautions must be taken in order to circumvent these limitations. For example, particular care has to be taken to ensure that the extraction of nucleic acids is optimized for the sample type (e.g., sediments, soil, wastewater, etc.). Significant improvements in nucleic acid yield and quality for both DNA and RNA can be achieved by carrying out preliminary experiments23. To minimize the effect of inhibitory compounds on PCR-based applications24, test a range of dilutions from the extracted DNA and RNA. To circumvent the rapid degradation of the extracted DNA/RNA from multiple freeze-thaw cycles and avoid possible loss of genetic information, store multiple small volume aliquots at -80 &#176;C.
When carefully designed, qPCR is a robust, highly reproducible and sensitive method. Notably, the methods for amplification and standard curve construction outlined in this protocol can be adapted for any gene target of interest, including other phylogenetic markers (i.e., archaeal 16S rRNA, fungal 18S rRNA) or genes involved in important functions in the environment. Known limitations in the use of qPCR are: a) the generation of reproducible high-quality standard curve for absolute quantification, b) the choice of primer/probes and optimization of q-PCR assay conditions, c) the use of low quality/sheared nucleic acids, d) the choice of the working dilution of DNA/RNA to avoid inhibition. Moreover, it has to be considered that qPCR technique provides gene/transcript abundances which may not equate to cell counts: this is particularly the case when 16S and 18S rRNA genes are targeted, as microorganisms have different copy numbers of the ribosomal gene in their genome25.
Poor quality standard curves will result in inaccurate quantification of the gene of interest. It is good practice to store a stock of high concentration standards in small aliquots from which fresh standard curves can be made. Do not store standard curves, always make fresh dilutions from a stock of the highest concentration each time. For accurate quantification of environmental samples ensure the range of concentrations of the standard curve spans the expected Cp values of the unknown samples. When quantifying transcripts, construct the standard curve from RNA not double stranded DNA. When possible, quantification of samples to be directly compared should be completed within a single assay to avoid inter-assay variation20. This may not always be possible. Therefore, to compare gene abundances generated between assays it is advisable to have a random sub-set of samples replicated between assays. A wide selection of primer and probe sets are currently available for qPCR targeting microbial taxa and functional groups15. Careful consideration is needed when selecting these to ensure both maximal coverage and specificity for the target group. If the reaction efficiency of a qPCR assay is not satisfactory, troubleshooting starts with testing different thermal cycling conditions (as annealing time and/or temperature) and/or reaction conditions, e.g., varying primer-probe concentrations. Once the q-PCR assay and reaction conditions are optimized, always conduct an initial test of a range of DNA/cDNA dilutions to determine the appropriate template concentration. Select the dilution range resulting in the highest copy number as the optimal template dilution for further assays.
Currently, next-generation sequencing technologies efficiently shed light on microbial community structure and functions in a plethora of environments26,27,28. However, these datasets are often based on end-point PCR amplicon libraries and therefore provide only semi-quantitative assessments of the abundance of particular taxa. Hence, the capability of real time PCR-based technique to target specific taxonomic markers (from higher domain down to strain level) allows efficient validation of the results obtained by next-generation sequencing. Moreover, qPCR has been successfully used in combination with other microbial ecology molecular methods such as stable isotope probing (SIP) or phylogenetic/functional microarrays. Combined with the former tool, qPCR can be used to quantify the metabolically active community29,30. When combined with microarray analysis, qPCR provides key quantitative interpretation of phylogenetic marker-based and functional gene surveys of environments31,32.
Therefore, whether used alone or in combination with other (often process-based) assessments of ecosystem function, quantitative PCR is an essential tool for microbial ecologists in the exploration of the elusive link between microbial communities and ecosystem functions.

Microorganisms are the corner-stone of the biosphere driving ecosystem function. The majority of microorganisms remain uncultured1. Therefore molecular based approaches are fundamental to advance our understanding of the diversity and function of microorganisms in the environment. Central to these approaches is the extraction of nucleic acids from environmental samples and the subsequent amplification of target genes using the Polymerase Chain Reaction (PCR).
The first step of DNA/RNA extraction aims to lyse the cell walls of the microbial community present, remove undesired non nucleic-acid molecules (e.g., organic and inorganic substances) and retain DNA/RNA in solution for further downstream analysis. Among several options available in the literature2,3,4,5, including a range of commercial extraction kits, the Griffiths method6 is widely employed7,8,9. It is cost-effective and particularly well suited to sediments as it uses a bead-beating step to lyse cells and incorporates steps to minimize the co-extraction of PCR inhibitors, such as humic acids, whilst simultaneously recovering DNA and RNA.
The second step uses the polymerase chain reaction (PCR) to amplify target genes, such as the 16S rRNA taxonomic marker, from the extracted nucleic acids. This approach has and continues to facilitate the exploration of the uncharacterized microbial black box10,11. However, end-point PCR-based methods suffer from various limitations that can bias the characterization of microbial communities12. To accurately quantify gene/transcript abundances, real-time PCR, also known as quantitative PCR (qPCR) must be used. qPCR exploits fluorescent reporter dye systems that track amplicon accumulation after every cycle of the PCR. This is significant as it means that quantification can occur during the early exponential phase, rather than the end-point, phase of the PCR reaction, when the amplicon yield is still directly proportional to the initial abundance of the target gene.
Two reporter systems are commonly used: an intercalating nucleic acid stain13 and the 5&#39; 3&#39; exonuclease activity of the DNA polymerase14. Since the former reporter system binds indistinctively to all double-stranded DNA, it may lead to an overestimation of the target sequence if unwanted non-specific amplicons or primer dimers by products occur. In order to circumvent this, extensive optimization of amplification may be required. In the latter system, template amplification is tracked using a combination of a 5&#39; nuclease activity of Taq polymerase that cleaves a fluorophore from an internal probe. This feature increases the specificity of the assay due to the utilization of a fluorogenic probe that binds only to the complementary target-specific sequence between the primer pair. With both chemistries quantification is achieved by determining the crossing-point (Cp) where the accumulation of PCR amplicons, as measured by an increase in fluorescence, is significantly above background fluorescence.
qPCR has been extensively used in microbial ecology to determine gene abundances in different environments15. Moreover, reverse transcription of RNA to cDNA is combined with qPCR and RT-qPCR to quantify gene expression. Hence, qPCR and RT-qPCR represent fast, effective methods for the quantification of gene and/or transcript numbers within environmental samples.
Microorganisms in coastal sediments drive various ecosystem processes, including the mineralization of organic matter, the degradation of pollutants and the biogeochemical cycling of macronutrients such as nitrogen16,17,18. The exhaustive understanding of these transformations requires a comprehensive account of the contributing microbial populations, including quantitative data on gene and transcript abundances. Here we introduce a series of thoroughly tested, streamlined and standardized protocols for the quantification of bacterial 16S rRNA gene and transcript abundances in coastal sediments. The protocol outlines sample collection, simultaneous DNA and RNA extraction, DNA-free RNA preparation, quality checking of extracted nucleic acids, generation of 16S rRNA-DNA and -RNA standards and quantification of environmental samples. Quantitative data derived from the methods described here are needed to shed light on microbial communities driving coastal ecosystems.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Diethylpyrocarbonate</td>
			<td>Sigma</td>
			<td>40718</td>
			<td>Toxic, open under chemical hood</td>
		</tr>
		<tr>
			<td>cetrimonium bromide (CTAB)</td>
			<td>Sigma</td>
			<td>52365</td>
			<td>Irritant, open under chemical hood</td>
		</tr>
		<tr>
			<td>potassium phosphate dibasic&#160;</td>
			<td>Sigma</td>
			<td>RES20765</td>
			<td></td>
		</tr>
		<tr>
			<td>potassium phosphate monobasic&#160;</td>
			<td>Sigma</td>
			<td>P9791</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenol:Chloroform:Isoamylalcohol pH 8</td>
			<td>Sigma</td>
			<td>P2069</td>
			<td>Equilibrate at pH 8 before using</td>
		</tr>
		<tr>
			<td>Chloroform:Isoamylalcohol&#160;</td>
			<td>Sigma</td>
			<td>25666</td>
			<td></td>
		</tr>
		<tr>
			<td>sodium chloride</td>
			<td>VWR</td>
			<td>1.06404.0500</td>
			<td></td>
		</tr>
		<tr>
			<td>polyethylenglycol 6000&#160;</td>
			<td>VWR</td>
			<td>528877-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol Molecular Grade</td>
			<td>Sigma</td>
			<td>E7148</td>
			<td></td>
		</tr>
		<tr>
			<td>Lysing Matrix E tubes</td>
			<td>MP Biomedical</td>
			<td>116914050&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>Turbo DNAse&#160;</td>
			<td>Ambion</td>
			<td>AM1907</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq polymerase</td>
			<td>Sigma</td>
			<td>D1806</td>
			<td></td>
		</tr>
		<tr>
			<td>dNTPs</td>
			<td>Bioline</td>
			<td>BIO-39028</td>
			<td></td>
		</tr>
		<tr>
			<td>SuperScript III</td>
			<td>Life Technologies</td>
			<td>18080044</td>
			<td></td>
		</tr>
		<tr>
			<td>Rnase Inhibitor</td>
			<td>Life Technologies</td>
			<td>10777019</td>
			<td></td>
		</tr>
		<tr>
			<td>RNAse/DNAse free 0.2 ml PCR tubes</td>
			<td>Sarstedt</td>
			<td>72.985.002</td>
			<td></td>
		</tr>
		<tr>
			<td>SureCleanPlus</td>
			<td>Bioline</td>
			<td>BIO-37047</td>
			<td></td>
		</tr>
		<tr>
			<td>pGEM Easy T Vector</td>
			<td>Promega</td>
			<td>A1360</td>
			<td></td>
		</tr>
		<tr>
			<td>E. coli JM109 competent cells</td>
			<td>Promega</td>
			<td>L2005</td>
			<td></td>
		</tr>
		<tr>
			<td>Tryptone</td>
			<td>Sigma</td>
			<td>T7293</td>
			<td></td>
		</tr>
		<tr>
			<td>Yeast Extract</td>
			<td>Sigma</td>
			<td>70161</td>
			<td></td>
		</tr>
		<tr>
			<td>Ampicillin</td>
			<td>Sigma</td>
			<td>59349</td>
			<td></td>
		</tr>
		<tr>
			<td>X-Gal</td>
			<td>Bioline</td>
			<td>BIO-37035</td>
			<td></td>
		</tr>
		<tr>
			<td>IPTG</td>
			<td>Bioline</td>
			<td>BIO-37036</td>
			<td></td>
		</tr>
		<tr>
			<td>Agar</td>
			<td>VWR</td>
			<td>20768.235</td>
			<td></td>
		</tr>
		<tr>
			<td>Plasmid Midi Kit</td>
			<td>Qiagen</td>
			<td>12143</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit</td>
			<td>Life Technologies</td>
			<td>Q33216</td>
			<td></td>
		</tr>
		<tr>
			<td>Quant-IT DNA HS Assay</td>
			<td>Life Technologies</td>
			<td>Q-33120</td>
			<td></td>
		</tr>
		<tr>
			<td>Quant-IT RNA HS Assay</td>
			<td>Life Technologies</td>
			<td>Q32855</td>
			<td></td>
		</tr>
		<tr>
			<td>MEGAshortscript &#160;kit</td>
			<td>Ambion</td>
			<td>AM1354</td>
			<td></td>
		</tr>
		<tr>
			<td>TaqMan SensiFast Probe Lo-ROX kit</td>
			<td>Bioline</td>
			<td>BIO-84002</td>
			<td></td>
		</tr>
		<tr>
			<td>qPCR machine</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

simultaneous dna-rna extraction from coastal sediments and quantification of 16s rrna genes and transcripts by real-time pcr

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of taxonomic and functional groups in environmental samples. Used in combination with a reverse transcriptase reaction (RT-q-PCR), it can also be employed to quantify gene transcripts. q-PCR makes use of highly sensitive fluorescent detection chemistries that allow quantification of PCR amplicons during the exponential phase of the reaction. Therefore, the biases associated with &#39;end-point&#39; PCR detected in the plateau phase of the PCR reaction are avoided. A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. First, a method for the co-extraction of DNA and RNA from coastal sediments, including the additional steps required for the preparation of DNA-free RNA, is outlined. Second, a step-by-step guide for the quantification of 16S rRNA genes and transcripts from the extracted nucleic acids via q-PCR and RT-q-PCR is outlined. This includes details for the construction of DNA and RNA standard curves. Key considerations for the use of RT-q-PCR assays in microbial ecology are included.

The extraction of good quality DNA and RNA from sediments is the first step in quantifying gene and transcript abundances. A successful extraction yields clear DNA and RNA bands as indicated in Figure 1 for sample A-C, where sharp 23S and 16S rRNA bands are visible in addition to the high molecular weight genomic DNA band.
<img alt="Figure 1" src="/files/ftp_upload/54067/54067fig1highres.jpg" width="400" /> 
Figure 1. DNA/RNA extraction. Typical results from DNA/RNA extraction from triplicate (A-B-C) 0.5 g coastal sediments. 5 &#181;l of DNA/RNA was run on a 1.4% agarose at 85 V for 40 min. A molecular marker in the 10,037-200 bp range was used. <a href="https://www.jove.com/files/ftp_upload/54067/54067fig1highres.jpg" target="_blank"> Please click here to view a larger version of this figure.</a>
To prepare RNA, a digestion of the co-extracted DNA is mandatory. This must be followed by 16S rRNA end-point PCR of the RNA to ensure that the DNA has been successfully removed. If the DNA has been completely removed only a band in the positive control is observed. It is important to use both neat and a 1:10 dilution of RNA to ensure inhibitors are not preventing the formation of a PCR product. RNA can now undergo the reverse transcriptase reaction to convert it to cDNA. This can be performed with either gene-specific primers or random hexamers. Typically, the reaction is carried out in a PCR machine, to ensure optimal temperature profile. This cDNA is used as template in the subsequent qPCR reaction. DNA and RNA is quantified to determine the template concentration used in each reaction.
A qPCR reaction protocol is outlined targeting 16S rRNA DNA. For 16S rRNA transcripts substitute the standard curve and template with cDNA. As unknown samples are quantified against the standard curve, it is imperative to ensure that the standard curve is of good quality. Figure 2 shows the preparation of (A), standard curves and environmental DNA dilutions, (B), amplification of the standard curve and environmental samples (C) conversion of standard curve to a linear regression and calculation of gene copy numbers. When a 10-fold dilution range is correctly prepared and amplified a 3.3 cycle difference between each standard dilution is seen (it takes 3.3 cycles for a ten-fold increase in template at 100% amplification efficiency) (Figure 2Bi). Standard curves descriptors, including the R2 values of 0.99 and PCR efficiencies within the range of 90 to 110% (Figure 2C) are desired. It is important to report Cp values from the no template control (NTC) if present. If this occurs a Cp cutoff for standards and unknown samples 3.3 cycles (i.e., a log fold) higher than the Cp value of the NTC is imposed20 (Figure 2Cii). Unknown template extracted from sediment DNA was quantified from neat, 10-1, 10-2 and 10-3 dilutions (B). The neat sample did not amplify, the Cp values of 10-1 to 10-3 dilutions were 24.12, 26.02 and 28.40 respectively. The NTC Cp was 30.5, an NCT cutoff of 27.2 was imposed. Converting gene abundances to g-1 wet weight sediment resulted in 2.5 x 107 and 7.1 x 107 for 10-1 and 10-2 respectively for the dilution range. 10-3 dilution Cp was below the NTC cutoff, and was therefore not used. In this case the 10-2 was selected as the optimal template dilution.
<img alt="Figure 2" src="/files/ftp_upload/54067/54067fig2highres.jpg" width="700" /> 
Figure 2. 16S rRNA gene qPCR amplification of standards and environmental DNA extracted from coastal sediments. Preparation of (A) i) DNA standard curve and ii) environmental DNA dilutions for qPCR amplification, (B) qPCR amplification of i) DNA standard curve and ii) environmental samples, Cp for each sample are shown. (C) i) Linear regression of standard curve with standard curve descriptors; ii) calculation of gene abundances from environmental samples. NTC: Negative Template Control. <a href="https://www.jove.com/files/ftp_upload/54067/54067fig2highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>CTAB</td>
			<td>5 g</td>
		</tr>
		<tr>
			<td>K2HPO4x3H2O</td>
			<td>2.58 g</td>
		</tr>
		<tr>
			<td>KH2PO4</td>
			<td>0.1 g</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>2.05 g</td>
		</tr>
		<tr>
			<td>dH2O</td>
			<td>up to 100 ml</td>
		</tr>
	</tbody>
</table>
Table 1. Preparation of CTAB-phosphate buffer.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>PEG 6000</td>
			<td>30 g</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>9.35 g</td>
		</tr>
		<tr>
			<td>dH2O</td>
			<td>up to 100 ml</td>
		</tr>
		<tr>
			<td colspan="2">Note: add PEG 6000 slowly under moderate heating and stirring of 50 ml of dH2O.</td>
		</tr>
	</tbody>
</table>
Table 2. Preparation of PEG-NaCl precipitation solution.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>Undiluted RNA / 1:10 diluted RNA</td>
			<td>1.0 &#181;l</td>
		</tr>
		<tr>
			<td>10x PCR Buffer</td>
			<td>5.0 &#181;l</td>
		</tr>
		<tr>
			<td>dNTPs 10 mM</td>
			<td>1.0&#160; &#181;l</td>
		</tr>
		<tr>
			<td>63F forward primer&#160;</td>
			<td>1.0 &#181;l</td>
		</tr>
		<tr>
			<td>CAG GCC TAA CAC ATG CAA GTC</td>
			<td></td>
		</tr>
		<tr>
			<td>518R reverse primer</td>
			<td>1.0 &#181;l</td>
		</tr>
		<tr>
			<td>ATT ACC GCG GCT GCT GG&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq polymerase</td>
			<td>0.4 &#181;l</td>
		</tr>
		<tr>
			<td>RNAse-free dH2O</td>
			<td>40.6 &#181;l</td>
		</tr>
	</tbody>
</table>
Table 3. DNA-free RNA quality check PCR master mix.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>RNA</td>
			<td>0.5-5 &#956;g</td>
		</tr>
		<tr>
			<td>dNTPs 10 mM</td>
			<td>1 &#181;l</td>
		</tr>
		<tr>
			<td>Reverse primer 10 &#956;M/ Random Hexamers 50 &#181;M</td>
			<td>1 &#181;l</td>
		</tr>
		<tr>
			<td>DEPC-H2O</td>
			<td>Up to 13 &#181;l</td>
		</tr>
	</tbody>
</table>
Table 4. cDNA synthesis reaction mix A.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>Buffer 5x</td>
			<td>4 &#181;l</td>
		</tr>
		<tr>
			<td>DTT&#160;</td>
			<td>1 &#181;l</td>
		</tr>
		<tr>
			<td>RNAse Inhibitor&#160;</td>
			<td>1 &#181;l</td>
		</tr>
		<tr>
			<td>Reverse Transcriptase</td>
			<td>1 &#181;l</td>
		</tr>
	</tbody>
</table>
Table 5. cDNA synthesis reaction mix B.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Target</td>
			<td>Primer name</td>
			<td>Sequence</td>
			<td>Annealing T (&#176;C)</td>
			<td>Reference</td>
		</tr>
		<tr>
			<td rowspan="3">16S rRNA bacteria</td>
			<td>Bact1369F</td>
			<td>CGG TGA ATA CGT TCY CGG</td>
			<td rowspan="3">56</td>
			<td rowspan="3">Suzuki et al. 2000 19</td>
		</tr>
		<tr>
			<td>Prok1492R</td>
			<td>GGW TAC CTT GTT ACG ACT T</td>
		</tr>
		<tr>
			<td>TM1389F (probe)</td>
			<td>CTT GTA CAC ACC GCC CGT C</td>
		</tr>
	</tbody>
</table>
Table 6. Primer and probes for 16S rRNA q-PCR assay.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Amount</td>
		</tr>
		<tr>
			<td>2x Master Mix</td>
			<td>10 &#956;l</td>
		</tr>
		<tr>
			<td>Forward primer (10 &#956;M)</td>
			<td>0.8 &#956;l</td>
		</tr>
		<tr>
			<td>Reverse primer (10 &#956;M)</td>
			<td>0.8 &#956;l</td>
		</tr>
		<tr>
			<td>Probe (10 &#956;M)</td>
			<td>0.4 &#956;l</td>
		</tr>
		<tr>
			<td>Water</td>
			<td>7.0 &#956;l</td>
		</tr>
		<tr>
			<td>Final volume</td>
			<td>19 &#956;l</td>
		</tr>
	</tbody>
</table>
Table 7. Real time PCR reaction mix.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Descriptor</td>
			<td>Significance</td>
		</tr>
		<tr>
			<td>Correlation coefficient (R2)</td>
			<td>A measure of the linearity of the standard curve. Ideally it should be R2=1. Value of R2=0.98-0.99 are acceptable.</td>
		</tr>
		<tr>
			<td>Slope (&#945;)</td>
			<td>A measure of reaction efficiency. Ideally it should be equivalent to -3.32. Value in the range between -3.58 and -3.1.</td>
		</tr>
		<tr>
			<td>Efficiency (=10(-1/slope)-1)</td>
			<td>If it is 100%, the templates doubles after each thermal cycle during exponential amplification. A good efficiency range is between 90 and 110%.</td>
		</tr>
		<tr>
			<td>Y Intercept (&#946;)</td>
			<td>The theoretical limit of detection of the reaction. Although not used to quantify reaction sensitivity, it is important when comparing different standard curves of the same target.</td>
		</tr>
	</tbody>
</table>
Table 8. qPCR reaction descriptors.

Watch this Scientific Journal Video about Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR at JoVE.com

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. The methodology includes the co-extraction of DNA and RNA; preparation of DNA-free RNA; and 16S rRNA gene and transcript quantification via RT-q-PCR, including standard curve construction.

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of ...

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17.5K Views.  National University of Ireland Galway. A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. The methodology includes the co-extraction of DNA and RNA; preparation of DNA-free RNA; and 16S rRNA gene and transcript quantification via RT-q-PCR, including standard curve construction. 

Video: Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Laboratory-determined Phosphorus Flux from Lake Sediments as a Measure of Internal Phosphorus Loading

Eutrophication is a water quality issue in lakes worldwide, and there is a critical need to identify and control nutrient sources. Internal phosphorus (P) loading from lake sediments can account for a substantial portion of the total P load in eutrophic, and some mesotrophic, lakes. Laboratory determination of P release rates from sediment cores is one approach for determining the role of internal P loading and guiding management decisions. Two principal alternatives to experimental determination of sediment P release exist for estimating internal load: in situ measurements of changes in hypolimnetic P over time and P mass balance. The experimental approach using laboratory-based sediment incubations to quantify internal P load is a direct method, making it a valuable tool for lake management and restoration.
Laboratory incubations of sediment cores can help determine the relative importance of internal vs. external P loads, as well as be used to answer a variety of lake management and research questions. We illustrate the use of sediment core incubations to assess the effectiveness of an aluminum sulfate (alum) treatment for reducing sediment P release. Other research questions that can be investigated using this approach include the effects of sediment resuspension and bioturbation on P release.
The approach also has limitations. Assumptions must be made with respect to: extrapolating results from sediment cores to the entire lake; deciding over what time periods to measure nutrient release; and addressing possible core tube artifacts. A comprehensive dissolved oxygen monitoring strategy to assess temporal and spatial redox status in the lake provides greater confidence in annual P loads estimated from sediment core incubations.

Lake eutrophication is a water quality issue worldwide, making the need to identify and control nutrient sources critical. Laboratory determination of phosphorus release rates from sediment cores is a valuable approach for determining the role of internal phosphorus loading and guiding management decisions.

Eutrophication is a water quality issue in lakes worldwide, and there is a critical need to identify and control nutrient sources. Internal phosphorus (P) ...

Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples

Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA libraries are needed for optimal results from next-generation sequencing. Environmental samples such as water may have low quality and quantities of DNA as well as contaminants that co-precipitate with DNA. The mechanical and enzymatic processes involved in extraction and library preparation may further damage the DNA. Gel size selection enables purification and recovery of DNA fragments of a defined size for sequencing applications. Nevertheless, this task is one of the most time-consuming steps in the DNA library preparation workflow. The protocol described here enables complete automation of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments. 
In this study, we describe a high-throughput approach to prepare high quality DNA libraries from freshwater samples that can be applied also to other environmental samples. We used an indirect approach to concentrate bacterial cells from environmental freshwater samples; DNA was extracted using a commercially available DNA extraction kit, and DNA libraries were prepared using a commercial transposon-based protocol. DNA fragments of 500 to 800 bp were gel size selected using Ranger Technology, an automated electrophoresis workstation. Sequencing of the size-selected DNA libraries demonstrated significant improvements to read length and quality of the sequencing reads.

This manuscript describes an automated gel size selection approach for purifying DNA fragments for next-generation sequencing. The Ranger Technology provides complete automation of the entire process of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments allowing for high-throughput and high quality next-generation sequencing libraries.

Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA ...

Development of Sulfidogenic Sludge from Marine Sediments and Trichloroethylene Reduction in an Upflow Anaerobic Sludge Blanket Reactor

The importance of microbial sulfate reduction relies on the various applications that it offers in environmental biotechnology. Engineered sulfate reduction is used in industrial wastewater treatment to remove large concentrations of sulfate along with the chemical oxygen demand (COD) and heavy metals. The most common approach to the process is with anaerobic bioreactors in which sulfidogenic sludge is obtained through adaptation of predominantly methanogenic granular sludge to sulfidogenesis. This process may take a long time and does not always eliminate the competition for substrate due to the presence of methanogens in the sludge. In this work, we propose a novel approach to obtain sulfidogenic sludge in which hydrothermal vents sediments are the original source of microorganisms. The microbial community developed in the presence of sulfate and volatile fatty acids is wide enough to sustain sulfate reduction over a long period of time without exhibiting inhibition due to sulfide. 
This protocol describes the procedure to generate the sludge from the sediments in an upflow anaerobic sludge blanket (UASB) type of reactor. Furthermore, the protocol presents the procedure to demonstrate the capability of the sludge to remove by reductive dechlorination a model of a highly toxic organic pollutant such as trichloroethylene (TCE). The protocol is divided in three stages: (1) the formation of the sludge and the determination of its sulfate reducing activity in the UASB, (2) the experiment to remove the TCE by the sludge, and (3) the identification of microorganisms in the sludge after the TCE reduction. Although in this case the sediments were taken from a site located in Mexico, the generation of a sulfidogenic sludge by using this procedure may work if a different source of sediments is taken since marine sediments are a natural pool of microorganisms that may be enriched in sulfate reducing bacteria.

Microbial sulfate reduction is a process of great importance in environmental biotechnology. The success of the sulfidogenic reactors depends among other factors on the microbial composition of the sludge. Here, we present a protocol to develop sulfidogenic sludge from hydrothermal vents sediments in a UASB reactor for reductive dechlorination purposes.

The importance of microbial sulfate reduction relies on the various applications that it offers in environmental biotechnology. Engineered sulfate ...

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

This manuscript describes a duplex digital PCR assay (EntHF183 dPCR) for simultaneous quantification of Enterococcus spp. and the human fecal-associated HF183 marker. The EntHF183 duplex dPCR (referred as EntHF183 dPCR hereon) assay uses the same primer and probe sequences as its published individual quantitative PCR (qPCR) counterparts. Likewise, the same water filtration and DNA extraction procedures as performed prior to qPCR are followed prior to running dPCR. However, the duplex dPCR assay has several advantages over the qPCR assays. Most important, the dPCR assay eliminates the need for running a standard curve and hence, the associated bias and variability, by direct quantification of its targets. In addition, while duplexing (i.e. simultaneous quantification) Enterococcus and HF183 in qPCR often leads to severe underestimation of the less abundant target in a sample, dPCR provides consistent quantification of both targets, whether quantified individually or simultaneously in the same reaction. The dPCR assay is also able to tolerate PCR inhibitor concentrations that are one to two orders of magnitude higher than those tolerated by qPCR. These advantages make the EntHF183 dPCR assay particularly attractive because it simultaneously provides accurate and repeatable information on both general and human-associated fecal contamination in environmental waters without the need to run two separate qPCR assays. Despite its advantages over qPCR, the upper quantification limit of the dPCR assay with currently available instrumentation is approximately four orders of magnitude lower than that achievable by qPCR. Consequently, dilution is needed for measurement of high concentrations of target organisms such as those typically observed following sewage spills.

A Duplex Digital PCR Assay for Simultaneous Quantification of the Enterococcus spp. and the Human Fecal-associated HF183 Marker in Waters

This manuscript describes a duplex digital PCR assay that can be used to simultaneously quantify Enterococcus spp. and the HF183 genetic markers as indicators of general and human-associated fecal contamination in recreational waters.

This manuscript describes a duplex digital PCR assay (EntHF183 dPCR) for simultaneous quantification of Enterococcus spp. and the human fecal-associated ...

Extraction of Structural Extracellular Polymeric Substances from Aerobic Granular Sludge

To evaluate and develop methodologies for the extraction of gel-forming extracellular polymeric substances (EPS), EPS from aerobic granular sludge (AGS) was extracted using six different methods (centrifugation, sonication, ethylenediaminetetraacetic acid (EDTA), formamide with sodium hydroxide (NaOH), formaldehyde with NaOH and sodium carbonate (Na2CO3) with heat and constant mixing). AGS was collected from a pilot wastewater treatment reactor. The ionic gel-forming property of the extracted EPS of the six different extraction methods was tested with calcium ions (Ca2+). From the six extraction methods used, only the Na2CO3 extraction could solubilize the hydrogel matrix of AGS. The alginate-like extracellular polymers (ALE) recovered with this method formed ionic gel beads with Ca2+. The Ca2+-ALE beads were stable in EDTA, formamide with NaOH and formaldehyde with NaOH, indicating that ALE are one part of the structural polymers in EPS. It is recommended to use an extraction method that combines physical and chemical treatment to solubilize AGS and extract structural EPS.

The protocol provides a methodology to solubilize aerobic granular sludge in order to extract alginate-like extracellular polymers (ALE).

To evaluate and develop methodologies for the extraction of gel-forming extracellular polymeric substances (EPS), EPS from aerobic granular sludge (AGS) ...

Extraction of Organochlorine Pesticides from Plastic Pellets and Plastic Type Analysis

Plastic resin pellets, categorized as microplastics (&#8804;5 mm in diameter), are small granules that can be unintentionally released to the environment during manufacturing and transport. Because of their environmental persistence, they are widely distributed in the oceans and on beaches all over the world. They can act as a vector of potentially toxic organic compounds (e.g., polychlorinated biphenyls) and might consequently negatively affect marine organisms. Their possible impacts along the food chain are not yet well understood. In order to assess the hazards associated with the occurrence of plastic pellets in the marine environment, it is necessary to develop methodologies that allow for rapid determination of associated organic contaminant levels. The present protocol describes the different steps required for sampling resin pellets, analyzing adsorbed organochlorine pesticides (OCPs) and identifying the plastic type. The focus is on the extraction of OCPs from plastic pellets by means of a pressurized fluid extractor (PFE) and on the polymer chemical analysis applying Fourier Transform-InfraRed (FT-IR) spectroscopy. The developed methodology focuses on 11 OCPs and related compounds, including dichlorodiphenyltrichloroethane (DDT) and its two main metabolites, lindane and two production isomers, as well as the two biologically active isomers of technical endosulfan. This protocol constitutes a simple and rapid alternative to existing methodology for evaluating the concentration of organic contaminants adsorbed on plastic pieces.

Microplastics act as vector of potentially toxic organic contaminants with unpredictable effects. This protocol describes an alternative methodology for assessing the levels of organochlorine pesticides adsorbed on plastic pellets and identifying the polymer chemical structure. The focus is on pressurized fluid extraction and attenuated total reflectance Fourier transform infrared spectroscopy.

Plastic resin pellets, categorized as microplastics (&#8804;5 mm in diameter), are small granules that can be unintentionally released to the environment ...

Extraction and Characterization of Surfactants from Atmospheric Aerosols

Surface-active compounds, or surfactants, present in atmospheric aerosols are expected to play important roles in the formation of liquid water clouds in the Earth&#39;s atmosphere, a central process in meteorology, hydrology, and for the climate system. But because specific extraction and characterization of these compounds have been lacking for decades, very little is known on their identity, properties, mode of action and origins, thus preventing the full understanding of cloud formation and its potential links with the Earth&#39;s ecosystems.
In this paper we present recently developed methods for 1) the targeted extraction of all the surfactants from atmospheric aerosol samples and for the determination of 2) their absolute concentrations in the aerosol phase and 3) their static surface tension curves in water, including their Critical Micelle Concentration (CMC). These methods have been validated with 9 references surfactants, including anionic, cationic and non-ionic ones. Examples of results are presented for surfactants found in fine aerosol particles (diameter &#60;1 &#956;m) collected at a coastal site in Croatia and suggestions for future improvements and other characterizations than those presented are discussed.

Methods are presented for the targeted extraction of surfactants present in atmospheric aerosols and the determination of their absolute concentrations and surface tension curves in water, including their Critical Micelle Concentration (CMC).

Surface-active compounds, or surfactants, present in atmospheric aerosols are expected to play important roles in the formation of liquid water clouds in ...

Preparation of Authigenic Pyrite from Methane-bearing Sediments for In Situ Sulfur Isotope Analysis Using SIMS

Different sulfur isotope compositions of authigenic pyrite typically result from the sulfate-driven anaerobic oxidation of methane (SO4-AOM) and organiclastic sulfate reduction (OSR) in marine sediments. However, unravelling the complex pyritization sequence is a challenge because of the coexistence of different sequentially formed pyrite phases. This manuscript describes a sample preparation procedure that enables the use of secondary ion mass spectroscopy (SIMS) to obtain in situ &#948;34S values of various pyrite generations. This allows researchers to constrain how SO4-AOM affects pyritization in methane-bearing sediments. SIMS analysis revealed an extreme range in &#948;34S values, spanning from -41.6 to +114.8&#8240;, which is much wider than the range of &#948;34S values obtained by the traditional bulk sulfur isotope analysis of the same samples. Pyrite in the shallow sediment mainly consists of 34S-depleted framboids, suggesting early diagenetic formation by OSR. Deeper in the sediment, more pyrite occurs as overgrowths and euhedral crystals, which display much higher SIMS &#948;34S values than the framboids. Such 34S-enriched pyrite is related to enhanced SO4-AOM at the sulfate-methane transition zone, postdating OSR. High-resolution in situ SIMS sulfur isotope analyses allow for the reconstruction of the pyritization processes, which cannot be resolved by bulk sulfur isotope analysis.

Preparation of Authigenic Pyrite from Methane-bearing Sediments for In Situ Sulfur Isotope Analysis Using SIMS

Analyses of the sulfur isotopic composition (&#948;34S) of pyrite from methane-bearing sediments have typically focused on bulk samples. Here, we applied secondary ion mass spectroscopy to analyze the &#948;34S values of various pyrite generations to understand the diagenetic history of pyritization.

Different sulfur isotope compositions of authigenic pyrite typically result from the sulfate-driven anaerobic oxidation of methane (SO4-AOM) and ...

On-Site Molecular Detection of Soil-Borne Phytopathogens Using a Portable Real-Time PCR System

On-site diagnosis of plant diseases can be a useful tool for growers for timely decisions enabling the earlier implementation of disease management strategies that reduce the impact of the disease. Presently in many diagnostic laboratories, the polymerase chain reaction (PCR), particularly real-time PCR, is considered the most sensitive and accurate method for plant pathogen detection. However, laboratory-based PCRs typically require expensive laboratory equipment and skilled personnel. In this study, soil-borne pathogens of potato are used to demonstrate the potential for on-site molecular detection. This was achieved using a rapid and simple protocol comprising of magnetic bead-based nucleic acid extraction, portable real-time PCR (fluorogenic probe-based assay). The portable real-time PCR approach compared favorably with a laboratory-based system, detecting as few as 100 copies of DNA from Spongospora subterranea. The portable real-time PCR method developed here can serve as an alternative to laboratory-based approaches and a useful on-site tool for pathogen diagnosis.

Rapid and accurate detection of plant pathogens on-site, especially soil-borne pathogens, is crucial to prevent further inoculum production and proliferation of plant diseases in the field. The method developed here using a portable real-time PCR detection system enables on-site diagnosis under field conditions.

On-site diagnosis of plant diseases can be a useful tool for growers for timely decisions enabling the earlier implementation of disease management ...

Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris

The ubiquitous presence of plastic debris in the ocean is widely recognized by the public, scientific communities, and government agencies. However, only recently have microplastics in freshwater systems, such as rivers and lakes, been quantified. Microplastic sampling at the surface usually consists of deploying drift nets behind either a stationary or moving boat, which limits the sampling to environments with low levels of suspended sediments and floating or submerged debris. Previous studies that employed drift nets to collect microplastic debris typically used nets with &#8805;300 &#181;m mesh size, allowing plastic debris (particles and fibers) below this size to pass through the net and elude quantification. The protocol detailed here enables: 1) sample collection in environments with high suspended loads and floating or submerged debris and 2) the capture and quantification of microplastic particles and fibers &lt;300 &#181;m. Water samples were collected using a peristaltic pump in low-density polyethylene (PE) containers to be stored before filtering and analysis in the lab. Filtration was done with a custom-made microplastic filtration device containing detachable union joints that housed nylon mesh sieves and mixed cellulose ester membrane filters. Mesh sieves and membrane filters were examined with a stereomicroscope to quantify and separate microplastic particulates and fibers. These materials were then examined using a micro-attenuated total reflectance Fourier transform infrared spectrometer (micro ATR-FTIR) to determine microplastic polymer type. Recovery was measured by spiking samples using blue PE particulates and green nylon fibers; percent recovery was determined to be 100% for particulates and 92% for fibers. This protocol will guide similar studies on microplastics in high velocity rivers with high concentrations of sediment. With simple modifications to the peristaltic pump and filtration device, users can collect and analyze various sample volumes and particulate sizes.

Most microplastic research to date has occurred in marine systems where suspended solid levels are relatively low. Focus is now shifting to freshwater systems, which may feature high sediment loads and floating debris. This protocol addresses collecting and analyzing microplastic samples from aquatic environments that contain high suspended solid loads.

The ubiquitous presence of plastic debris in the ocean is widely recognized by the public, scientific communities, and government agencies. However, only ...