We thank Angelika Berg for laboratory assistance. This work was supported and financed by the Max Planck Society and the Jena School for Microbial Communication (JSMC).

1. Insect Rearing
<ol>
	<li>Purchase or obtain eggs clutches of Spodoptera littoralis from your own rearing. Maintain them in sterile Petri dishes at room temperature (RT) until hatching.</li>
	<li>Prepare the artificial diet for the insects rearing as follows:
	<ol>
		<li>Soak 500 g ground white beans overnight in 100 ml of water.</li>
		<li>Add 9.0 g ascorbic acid and 75 g agar to 1,000 ml distilled H2O and afterwards boil it.</li>
		<li>Let the mixture to cool down and when it solidifies (to a white waxy solid mixture) store it at 4 &#176;C until use.</li>
	</ol>
	</li>
	<li>Transfer the newly hatched larvae to a clean plastic box and rear them on the artificial diet at 23-25 &#176;C under a long-day regime with 16 hr of illumination and 8 hr of darkness. Change the food every day until the larvae go through all six larval instars.</li>
</ol>
2. 13C-labeling of DNA in Metabolically Active Gut Bacteria
<ol>
	<li>Dissolve 186.1 mg of fully 13C-labeled glucose with distilled and deionized water (ddH2O) and mix it well with 100 g of artificial diet for the SIP experiment. Ensure a final 13C-glucose concentration of 10 mM in the artificial diet. This mimics the in situ glucose concentration in the gut of S. littoralis larvae feeding on cotton plants according to Shao et al. (submitted).</li>
	<li>Transfer 9-15 healthy second instar larvae from the rearing box to sterile plastic Petri dishes (one larva per Petri dish) containing fresh 13C-glucose spiked artificial diet. Use artificial diet containing the same amount of native glucose (12C-glucose), as described, for feeding the control group.</li>
	<li>Renew the artificial diet frequently during the incubation period (1 day). Use rearing conditions as in step 1.3.</li>
	<li>Collect nine larvae from each treatment for later processing (DNA extraction). Each replicate is constituted by three individuals; make at least three replicates per treatment.</li>
</ol>
3. Insect Dissection
<ol>
	<li>Clean and disinfect the dissecting tools at the beginning of the work with ethanol 70% (Tools= Vannas scissors, forceps and scalpel with fine disposable blades).</li>
	<li>Take the insects with a soft forceps and wash their skin superficially with distilled water. Place them on ice for at least 30 min to anesthetize them.</li>
	<li>While still anesthetized place them at 0 &#176;C for 1 hr to kill them. Disinfect the dead insects superficially by immersing them in ethanol (70%) for a couple of minutes.</li>
	<li>Perform the insect dissection into a volume of approximately 15 ml of 1x PBS deposited on a sterile Petri dish (1XPBS= 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na2HPO4, 1.47 mM KH2PO4, adjust the pH to 7.4 , autoclave). Be sure of having the whole insect body fully immersed in the solution during the whole dissecting period.</li>
	<li>Begin the dissection by making an incision in the skin along the right and left sides of the insect, commence on the head and finish on the anus. Remove the whole skin, Malpighian tubules, and fat body. Change to fresh buffer before cutting open the gut. Section the gut in fore-, mid-, and hindgut when required. Store the tissue in the freezer (-80 to -20 &#176;C) until DNA extraction</li>
</ol>
4. DNA Extraction and Amplification
<ol>
	<li>Place the insect tissue in a 1.5 ml sterile centrifuge tube and dry all samples at 45 &#176;C in a vacuum concentrator device. Crush dried tissue with a sterile plastic pestle.</li>
	<li>Extract the genomic DNA using a suitable kit for soil DNA extraction. Transfer the dry tissue to the reaction tube of the kit and follow the instructions as indicated by the manufacturer.</li>
	<li>Determine the concentration of the final eluted DNA using a spectrophotometer.</li>
	<li>Verify a successful extraction of the microbial metagenomic DNA from the insect gut by preparing a diagnostic PCR assay using Eubacterial general primers 27f (5- AGAGTTTGATCCTGGCTCAG -3) and 1492r (5- GGTTACCTTGTTACGACTT -3). Set the PCR reaction as follows:
	<ol>
		<li>Set a 50 &#181;l reaction mixture containing 1x Buffer, 1.5 mM MgCl2, 10 mM four deoxynucleoside triphosphates (dNTPs), 2.5 U of Taq DNA Polymerase, 0.5 mM of each primer and 60 ng of the extracted DNA as template.</li>
		<li>Run the PCR reactions using a thermocycler as follows: initial denaturation at 94 &#176;C for 3 min; followed by 35 cycles: 94 &#176;C for 45 sec, annealing at 55 &#176;C for 30 sec, and extension at 72 &#176;C for 1 min. Use a final extension step at 72 &#176;C for 10 min.</li>
		<li>Verify the successful PCR amplification in a 1% agarose electrophoresis ethidium bromide (EB) stained gel (dissolve 1 g of agarose in 100 ml of 1x TAE buffer and stain with 1&#181;l EB ). Deposit 5 &#181;l of the PCR product + 1&#181;l of 6x loading dye into the gel pockets. (1x TAE=40 mM Tris-Base, 20 mM glacial acetic acid, 1 mM EDTA, adjust to pH 8).</li>
		<li>Run the gel using 1xTAE buffer at 300 V, 115 mA for ca. 20 min in an electrophoresis chamber. By using a gel documentation chamber (UV transilluminator connected to a digital camera and computer) observe the gel and compare the size of your final product with the also loaded gene marker; the correct size of the amplicons must be of approximately 1.5 kb.</li>
	</ol>
	</li>
	<li>Store the PCR products under deep freezing conditions, preferentially -80 &#176;C, until use.</li>
</ol>
5. DNA Separation-CsCl Gradient Ultracentrifugation
<ol>
	<li>Prepare the reagents for the gradients for ultracentrifugation as follows:
	<ol>
		<li>Prepare a 7.163 M cesium chloride (CsCl) solution by gradually dissolving 603.0 g of CsCl in ddH2O and fill up to a final volume of 500 ml.</li>
		<li>Accurately determine the density of the prepared CsCl solution by weighing a 1.0 ml aliquot on a three digit balance by triplicate. This usually ranges from 1.88 and 1.89 g/ml at RT.</li>
		<li>Prepare the gradient buffer (100 mM Tris, 100 mM KCl and 1 mM EDTA) by combining 50 ml of 1 M Tris-HCl (pH 8.0), 1 ml of 0.5 M EDTA (pH 8) and 3.75 g of KCl in a final volume of 500 ml using ddH2O. Filter (0.22 &#181;m) sterilize and autoclave this solution.</li>
	</ol>
	</li>
	<li>DNA Separation
	<ol>
		<li>Having determined the individual DNA concentration of the treated insects, measured as in point 4.3, pool those insects corresponding to a replicate together and normalize their DNA concentration to ensure that each one, equally contributes to the pooled sample. A final concentration of 500-5,000 ng of DNA (measure again the final concentration) is suitable for the ultracentrifugation process21.</li>
		<li>To set up the gradient medium, combine the quantified DNA, gradient buffer and 4.8 ml of 7.163 M CsCl solution together to a mixed volume of 6.0 ml in a sterile 15 ml screw-cap tube (generation of a gradient medium-DNA mixture).</li>
		<li>Carefully place the prepared gradient medium-DNA mixture into a 5.1 ml ultracentrifuge tube (fill in until the base of the tube neck) using a syringe and needle. Avoid pumping or forming any air bubbles. Include at least one blank gradient (using ddH2O instead of DNA) in each centrifuge run as a reference gradient.</li>
		<li>Balance tube pairs to within 10 mg of weight after each required gradient medium is filled into the respective ultracentrifuge tube. Seal the tube with a &#34;Tube Topper&#34; and ensure that the seal is leak-free by inverting the tube and applying moderate pressure by hand.</li>
		<li>Use a near vertical rotor with eight wells for holding 5.1 ml ultracentrifugation tubes for the ultracentrifugation. Carefully seal the rotor wells and load the rotor into the ultracentrifuge according to the manufacturer&#39;s instructions. Set the ultracentrifugation conditions: spin at 50,000 rpm (around 177,000 x g), temperature at 20 &#176;C, and ultracentrifugation running time for 40 hr with vacuum. Select maximum acceleration and the deceleration without brake.</li>
		<li>Once finished, carefully remove the tubes from the centrifuge rotor using forceps. Place them in a rack without disturbing the formed gradients within the tubes. Process the gradient fractionation samples as soon as possible to minimize any diffusion.</li>
	</ol>
	</li>
	<li>Retrieval of DNA from Isopycnic Separated Gradients by Fractionation
	<ol>
		<li>Use an accurate HPLC pump system to carry out the gradient fractionation, which equally separates the formed gradients from the ultracentrifuge tube top displacement method. Connect the HPLC pump (100% flow gradient) to the bottle filled with 1 L displacement ddH2O and tightly attach to the open pump tubing with a 23 G 1 in syringe needle. Add sufficient bromophenol blue dye to the ddH2O to give it a dark blue color. This facilitates the visualization of the interface between the gradient medium and the displacement of ddH2O.</li>
		<li>Set the pump to a flow rate of 850 &#181;l/min and equilibrate the system until a single drop of the blue-colored ddH2O emerges out of the syringe needle.</li>
		<li>Carefully fix the ultracentrifuge tube to a clamp stand and pierce the bottom of the tube with a syringe 23 G 1 in long needle. Connect the pump to the ultracentrifuge tube by inserting the needle attached to the pump tubing into the top of the tube, and collect drops from the bottom directly into sterile 1.5 ml microcentrifuge tubes. Collect a fraction every 30 sec, amounting to approximately 425 &#181;l per fraction and a total of 12 fractions per gradient. Note that the last fraction (fraction 12) usually contains the displacement ddH2O and should be discarded.</li>
		<li>After fractionation, measure the density of all separated fractions using an analytical balance as mentioned in step 5.1.2.</li>
		<li>Precipitate the DNA from each fraction (around 425 &#181;l) by first adding 1 &#181;l glycogen (20 &#181;g/&#181;l in ddH2O, autoclaved) as a carrier for the precipitation of low amount of DNA. Mix it well by inversion.</li>
		<li>Add two volumes (850 &#181;l) of polyethylene glycol (PEG) solution (dissolve 150 g of polyethylene glycol 6000 and 46.8 g of NaCl in ddH2O to a total volume of 500 ml. Filter, sterilize and autoclave. The PEG solution is 30% PEG 6000 and 1.6 M NaCl), and mix again by inverting ten times.</li>
		<li>Leave the tubes at RT for at least two hours (if necessary, overnight) to precipitate the DNA.</li>
		<li>Centrifuge the precipitates at 13,000 x g for 30 min at RT. A visible pellet should form.</li>
		<li>Carefully remove the supernatant with a pipette and wash the pellet with 500 &#181;l of 70% ethanol. Centrifuge under the same conditions for 10 min again.</li>
		<li>Carefully discard the supernatant and air-dry the pellet at RT for 15 min.</li>
		<li>Redissolve the dried DNA pellet in 30 &#181;l of ddH2O and mix well by gently tapping the tube. Quantify the DNA in each gradient fraction as in step 4.3 Store the samples under -20 or -80 &#176;C if long term storage is required.</li>
	</ol>
	</li>
</ol>
6. DNA Characterization by Pyrosequencing
<ol>
	<li>Ensure that the unlabeled native (12C) DNA occupies the density range from 1.705 g/ml to 1.720 g/ml, whereas 13C-labeled DNA has a density of around 1.720-1.735 g/ml. Note that both the native and 13C-labeled DNA extracted from environmental samples can span several gradient fractions. Expect the light DNA to be associated with fractions 9-11 and the heavy DNA to be associated with fractions 4-6.</li>
	<li>Combine key fractions to create a single &#34;compiled&#34; representative fraction according to the specific peak allocation of the density-resolved DNA. Alternatively, other means to examine the separated fractions by using the isotopic ratio mass spectrometry (IRMS)22 or a fingerprinting method, such as denaturing gradient gel electrophoresis (DGGE)23, can help to choose appropriate fractions before the sequencing.</li>
	<li>Perform pyrosequencing of the PCR-amplified bacterial 16S rRNA genes from the compiled heavy, middle and light fractions of each individual gradient. Using this method, identification of the lineage and relative abundance of metabolically active bacteria species in the SIP incubated samples is possible. Perform pyrosequencing as follows:
	<ol>
		<li>Perform amplicon pyrosequencing using a Roche 454 FLX instrument with Titanium reagents.</li>
		<li>Prepare barcoded amplicons for multiplexing using the fusion primer set Gray28F (5- GAGTTTGATCNTGGCTCAG -3) and Gray519r (5- GTNTTACNGCGGCKGCTG -3)24,25 extended with the respective primer Adaptor A/B and sample-specific multiplex identifiers (MID).</li>
		<li>Apply a one-step PCR with 30 cycles, using a Hot Start Taq polymerase, to generate the sequencing library.</li>
		<li>Sequence the amplicons based upon the supplier protocol, and extend the reads from the forward direction (Gray28F) as described in <a href="http://www.researchandtesting.com/">http://www.researchandtesting.com/</a>.</li>
	</ol>
	</li>
</ol>
7. Pyrosequencing Data Analysis
<ol>
	<li>Analyze the raw sequence reads generated by the 454 pyrosequencing with the &#34;quantitative insights into microbial ecology&#34;, QIIME software pipeline26. Perform the processing as follows:
	<ol>
		<li>Initially, convert the 454-machine-generated sff file to FASTA, QUAL and Flowgram files with the process_sff.py script.</li>
		<li>Validate the mapping file (based on check_id_map.py) and assign multiplexed reads to biological samples with the split_libraries.py script. Trim the low-quality ends with a sliding window size of 50 and an average quality cutoff parameter of 25, eliminate also short ambiguous sequences (the length &#60;200 bp) from the dataset.</li>
		<li>Denoise the 454 data using the denoise_wrapper.py.</li>
		<li>Next, cluster the high-quality reads into operational taxonomic units (OTUs) using the multiple OTU picking method (pick_otus.py with 97% sequence similarity cut-offs).</li>
		<li>Pick a representative sequence from each OTU using pick_rep_set.py.</li>
		<li>Assign taxonomy to the representative sequence set based on assign_taxonomy.py. Use the Ribosomal Database Project (RDP) classifier with a minimum confidence to record assignment set to 0.80.</li>
		<li>Align the representative sequence set against the prealigned Greengenes core 16S sequences using the algorithm PyNast (align_seqs.py with the minimum sequence identity percent set to 75).</li>
		<li>Additionally, deplete chimeras from further analysis by running identify_chimeric_seqs.py.</li>
		<li>Remove all gap positions (not useful for phylogenetic inference) with the lanemask template (filter_alignment.py) prior to building a phylogenetic tree (make_phylogeny.py).</li>
		<li>Finally, generate OTU tables with make_otu_table.py, describing the occurrence of bacterial phylotypes within each sample. Use the OTU table to construct the heatmap for comparing the bacterial abundance and activity.</li>
		<li>If required, compute the alpha and beta diversity within and between samples, respectively. In the same manner, rarefaction curves (graphs of diversity versus sequencing depth) and Principal Coordinates Analysis (PCoA) plots representing the relationships among microbial communities can be also prepared.</li>
	</ol>
	</li>
</ol>

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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+gut+bacteria+of+insects:+nonpathogenic+interactions.">The gut bacteria of insects: nonpathogenic interactions.</a> Annu. Rev. Entomol. 49, 71-92 (2004).</li><li>Neufeld, J. D., 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=DNA+stable-isotope+probing.">DNA stable-isotope probing.</a> Nat. Protoc. 2, 860-866 (2007).</li><li>Dumont, M. G., Murrell, J. C. <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+-+linking+microbial+identity+to+function.">Stable isotope probing - linking microbial identity to function.</a> Nat. Rev. Microbiol. 3, 499-504 (2005).</li></ol>

We have nothing to disclose.

The gut of most insects harbors a rich and complex microbial community; typically 107-109 prokaryotic cells lodge there, outnumbering the host&#39;s own cells in most cases. Thus, the insect gut is a &#34;hot spot&#34; for diverse microbial activities, representing multiple aspects of microbial relationships, from pathogenesis to obligate mutualism27. Although many studies have described an amazing variety of insect gut microbial communities, characterization of the metabolic activity of ...

Insect-bacterial symbiotic associations are known for a great number of insect species7. In these symbiotic associations, microorganisms play important roles in the growth and development of insects. Microbes have been shown to contribute to insect reproduction1, pheromone biosynthesis3, nutrition, including the synthesis of essential amino acids4, and digestion of inaccessible food to the host. Despite the vast variety of gut-bacterial associations, much less is known about the functional role they play in favor of the insect. Only in case of the termites, the symbiotic digestion of lignocellulose carried out by prokaryotes, protozoa, and fungi, has been widely studied8,9. In contrast to this, little is known about the symbiotic association present in the gut of generalist insects i.e. the cotton leafworm, Spodoptera littoralis. Moreover, due to their frequent shift of plant hosts, generalist insects and their gut associated bacterial communities are permanently exposed to new challenges linked to their feeding habits consuming plants with a plethora of phytochemicals. Beside this, the gut environment in lepidopterans, represents per se a harsh environment for the growth of bacteria because of the high gut pH10. Particularly in the case of S. littoralis, it ranges from 10.5 in the foregut, ca. 9 in the midgut to pH almost 7 in the hindgut11. On the other hand, the bacterial community associated with the gut of S. littoralis is simple. Tang, Freitak, et al.12 reported a maximum of 36 phylotypes belonging to a total of 7 different bacterial species as the only members of the bacterial community associated with this insect. Besides this, no complicated rearing procedure is required for the insect growth in the laboratory. Furthermore, this and the short life cycle of the insect facilitate multi-generational studies, turning this species into an ideal model system for studying gut-microbe interactions.
With the advent of PCR-based sequencing technologies, the number of studies dealing with gut biota of several organisms (i.e. humans, insects, or marine organisms) has increased. Moreover, the results are independent from isolation and cultivation of the gut harbored bacteria as in the past. Almost 99% of bacteria are not cultivable and the simulation of the environmental conditions prevailing in the gut is difficult12. By using PCR, 16S rRNA gene fragments (a widely used phylogenetic gene marker among bacteria) could be selectively amplified from a mixed DNA template of gut bacterial communities, sequenced, and cloned. With this information, the user is able to identify the bacterial species after retrieving the sequence information from public databases13,14. Nevertheless, the sequencing approaches to describe bacterial communities remain insufficient due to lack of information on the intrinsic metabolic contribution of the individual species within the community.
Stable-isotope probing (SIP) is a promising culture-free technique. It is often used in environmental microbiology to analyze microbial phylogenies linked to particular metabolic activities. This is achieved by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as phospholipid-derived fatty acids, DNA, and RNA5. When considering nucleic acids, the methodology is based upon the separation of 13C-labeled DNA or RNA from the unlabeled DNA by density-gradient ultracentrifugation6. Due to this direct connection between the DNA label and metabolic activity, a down&#173;stream molecular analysis of the nucleic acids identifies the species and provides information on metabolic activities. Moreover, combination of DNA-SIP and pyrosequencing as applied by Pilloni, von Netzer, et al.15, permits a particular simple and sensitive identification of the bacterial species present in the heavy 13C-labeled DNA fraction. Up to now, this technique has been applied to describe the bacterial communities involved in biogeochemical processes in the soil under aerobic16,17 and anaerobic conditions18,19. Besides of the use in environmental science, the technique has been applied in medical sciences as reported by Reichardt, et al.5, who described the metabolic activities of different phylogenetic groups of the human intestinal microbiota in response to a nondigestible carbohydrate.
Here we use 13C-glucose to &#39;label&#39; the DNA of the metabolically active bacterial species in the gut. Glucose is a sugar utilized by most bacterial species along the widespread Entner-Doudoroff (ED) pathway, although exceptions are known20. This justifies the use of 13C-glucose as a reliable metabolic probe that provides a link between metabolites of interest and the carbon source along established pathways. Depending on the scientific question, other substrates, i.e. 13C-methane, 13CO2, or plants raised under a 13CO2 atmosphere, can be used to address metabolic activities.
At this point, we present the protocol applied in the metabolic characterization of the gut bacterial community of a generalist insect, namely S. littoralis (Lepidoptera, Noctuidae). Moreover, the technique was coupled to pyrosequencing, which in turn allows the identification of insect gut bacterial community with high resolution and precision. As the main substrate, 13C-labeled glucose was utilized during the experiments.

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			<td height="21" style="height:21px;width:384px;">Dumont #5 Mirror Finish Forceps</td>
			<td style="width:203px;">Fine Science Tools</td>
			<td style="width:135px;">11251-23</td>
			<td style="width:151px;"> </td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Vannas Spring Scissors</td>
			<td>Fine Science Tools</td>
			<td>15000-00</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Speed Vacuum Concentrator 5301</td>
			<td>Eppendorf Germany</td>
			<td>5305 000.304</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Plastic pestle</td>
			<td>Carl Roth GmbH Co. Germany</td>
			<td>P986.1</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NanoVue spectrophotometer</td>
			<td>GE HealthCare, UK</td>
			<td>28-9569-58</td>
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		<tr height="21">
			<td height="21" style="height:21px;">Mastercycler pro/thermocycler</td>
			<td>Eppendorf Germany</td>
			<td>6321 000.515</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Agagel Standard Horizontal Gel Electrophoresis chamber</td>
			<td>Biometra</td>
			<td>Discontinued</td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;">Ultracentrifuge (Optima L-90K)</td>
			<td>Beckman</td>
			<td>A20684</td>
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		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Ultracentrifuge rotor (NVT 90)</td>
			<td>Beckman</td>
			<td>362752</td>
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			<td height="21" style="height:21px;">HPLC pump</td>
			<td>Agilent</td>
			<td>1100</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Quick-Seal, Polyallomer tube</td>
			<td>Beckman</td>
			<td>342412</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Transilluminator UVstar 15 </td>
			<td>Biometra</td>
			<td></td>
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		</tr>
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identification of metabolically active bacteria in the gut of the generalist spodoptera littoralis via dna stable isotope probing using 13c-glucose

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to identify commensal or mutualistic bacteria species. The latter ones, have been observed to serve multiple functions to the insect, i.e. helping in insect reproduction1, boosting the immune response2, pheromone production3, as well as nutrition, including the synthesis of essential amino acids4, among others. &#160; &#160;
Due to the importance of these associations, many efforts have been made to characterize the communities down to the individual members. However, most of these efforts were either based on cultivation methods or relied on the generation of 16S rRNA gene fragments which were sequenced for final identification. Unfortunately, these approaches only identified the bacterial species present in the gut and provided no information on the metabolic activity of the microorganisms.
To characterize the metabolically active bacterial species in the gut of an insect, we used stable isotope probing (SIP) in vivo employing 13C-glucose as a universal substrate. This is a promising culture-free technique that allows the linkage of microbial phylogenies to their particular metabolic activity. This is possible by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as DNA and RNA5. The incorporation of 13C isotopes into DNA increases the density of the labeled DNA compared to the unlabeled (12C) one. In the end, the 13C-labeled DNA or RNA is separated by density-gradient ultracentrifugation from the 12C-unlabeled similar one6. Subsequent molecular analysis of the separated nucleic acid isotopomers provides the connection between metabolic activity and identity of the species.
Here, we present the protocol used to characterize the metabolically active bacteria in the gut of a generalist insect (our model system), Spodoptera littoralis (Lepidoptera, Noctuidae). The phylogenetic analysis of the DNA was done using pyrosequencing, which allowed high resolution and precision in the identification of insect gut bacterial community. As main substrate, 13C-labeled glucose was used in the experiments. The substrate was fed to the insects using an artificial diet.

To achieve sufficient labeling of the metabolically active bacteria present in the insect gut, the insect must be exposed to the 13C-rich substrate for a previously optimized period sufficient to allow the separation of the labeled heavier fraction easily from the unlabeled lighter one. In our case, 13C-glucose was supplemented in the artificial diet at a final concentration of 10 mM for 1 day (Figure 1A). The same amount of normal glucose (Figure 1B) was supplied i...

Watch this Scientific Journal Video about Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose at JoVE.co

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

The active bacterial community associated with the gut of Spodoptera littoralis, was determined by stable-isotope-probing (SIP) coupled to pyrosequencing. Using this methodology, identification of the metabolically active bacteria species within the community was done with high resolution and precision.

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to ...

identification-metabolically-active-bacteria-gut-generalist

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15.3K Views.  Max Planck Institute for Chemical Ecology. The active bacterial community associated with the gut of Spodoptera littoralis, was determined by stable-isotope-probing (SIP) coupled to pyrosequencing. Using this methodology, identification of the metabolically active bacteria species within the community was done with high resolution and precision.

Video: Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

Extracting DNA from the Gut Microbes of the Termite (Zootermopsis Angusticollis) and Visualizing Gut Microbes

Termites are among the few animals known to have the capacity to subsist solely by consuming wood.  The termite gut tract contains a dense and species-rich microbial population that assists in the degradation of lignocellulose predominantly into acetate, the key nutrient fueling termite metabolism (Odelson &amp; Breznak, 1983).  Within these microbial populations are bacteria, methanogenic archaea and, in some ("lower") termites, eukaryotic protozoa. Thus, termites are excellent research subjects for studying the interactions among microbial species and the numerous biochemical functions they perform to the benefit of their host.  The species composition of microbial populations in termite guts as well as key genes involved in various biochemical processes has been explored using molecular techniques (Kudo et al., 1998; Schmit-Wagner et al., 2003; Salmassi &amp; Leadbetter, 2003). These techniques depend on the extraction and purification of high-quality nucleic acids from the termite gut environment.  The extraction technique described in this video is a modified compilation of protocols developed for extraction and purification of nucleic acids from environmental samples (Mor  et al., 1994; Berthelet et al., 1996; Purdy et al., 1996; Salmassi &amp; Leadbetter, 2003; Ottesen et al. 2006) and it produces DNA from termite hindgut material suitable for use as template for polymerase chain reaction (PCR).

Extracting DNA from the Gut Microbes of the Termite Zootermopsis Angusticollis and Visualizing Gut Microbes

This video illustrates the technique for extracting DNA from the species of microbes resident in the termite hindgut. The preparation of a wet mount slide, which is useful for visualizing the gut microbial community is also illustrated, and a tour through the species-rich gut environment is given.

Termites are among the few animals known to have the capacity to subsist solely by consuming wood.  The termite gut tract contains a dense and ...

DNA Stable-Isotope Probing (DNA-SIP)

DNA stable-isotope probing (DNA-SIP) is a powerful technique for identifying active microorganisms that assimilate particular carbon substrates and nutrients into cellular biomass. As such, this cultivation-independent technique has been an important methodology for assigning metabolic function to the diverse communities inhabiting a wide range of terrestrial and aquatic environments. Following the incubation of an environmental sample with stable-isotope labelled compounds, extracted nucleic acid is subjected to density gradient ultracentrifugation and subsequent gradient fractionation to separate nucleic acids of differing densities. Purification of DNA from cesium chloride retrieves labelled and unlabelled DNA for subsequent molecular characterization (e.g. fingerprinting, microarrays, clone libraries, metagenomics). This JoVE video protocol provides visual step-by-step explanations of the protocol for density gradient ultracentrifugation, gradient fractionation and recovery of labelled DNA. The protocol also includes sample SIP data and highlights important tips and cautions that must be considered to ensure a successful DNA-SIP analysis.

DNA Stable-Isotope Probing DNA-SIP

DNA stable-isotope probing is a cultivation-independent method to identify and characterize active communities of microorganisms that are capable of utilizing specific substrates. Assimilation of substrate enriched in heavy isotope leads to incorporation of labelled atoms into microbial biomass. Density gradient ultracentrifugation retrieves labelled DNA for downstream molecular analyses.

DNA stable-isotope probing (DNA-SIP) is a powerful technique for identifying active microorganisms that assimilate particular carbon substrates and ...

Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans

Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in cellular and mammalian models. Here, we describe detailed methods to perform stable isotopic profiling of intermediary metabolism and metabolic flux in the nematode, Caenorhabditis elegans. Methods are described for profiling whole worm free amino acids, labeled carbon dioxide, labeled organic acids, and labeled amino acids in animals exposed to stable isotopes either from early development on nematode growth media agar plates or beginning as young adults while exposed to various pharmacologic treatments in liquid culture. Free amino acids are quantified by high performance liquid chromatography (HPLC) in whole worm aliquots extracted in 4% perchloric acid. Universally labeled 13C-glucose or 1,6-13C2-glucose is utilized as the stable isotopic precursor whose labeled carbon is traced by mass spectrometry in carbon dioxide (both atmospheric and dissolved) as well as in metabolites indicative of flux through glycolysis, pyruvate metabolism, and the tricarboxylic acid cycle. Representative results are included to demonstrate effects of isotope exposure time, various bacterial clearing protocols, and alternative worm disruption methods in wild-type nematodes, as well as the relative extent of isotopic incorporation in mitochondrial complex III mutant worms (isp-1(qm150)) relative to wild-type worms. Application of stable isotopic profiling in living nematodes provides a novel capacity to investigate at the whole animal level real-time metabolic alterations that are caused by individual genetic disorders and/or pharmacologic therapies.

Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans

Stable isotopic profiling by gas chromatography mass spectrometric analysis of intermediary metabolic flux is described in the nematode, Caenorhabditis elegans. Methods are detailed for assessing isotopic enrichment in carbon dioxide, organic acids, and amino acids following isotope exposure either during development on agar plates or during adulthood in liquid culture.

Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in ...

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.
Telomerase is a specialized reverse transcriptase1 that adds short DNA repeats, called telomeres, to the 3' end of linear chromosomes2 that serve to protect them from end-to-end fusion and degradation. Following DNA replication, a short segment is lost at the end of the chromosome3 and without telomerase, cells continue dividing until eventually reaching their Hayflick Limit4. Additionally, telomerase is dormant in most somatic cells5 in adults, but is active in cancer cells6 where it promotes cell immortality7.
The minimal telomerase enzyme consists of two core components: the protein subunit (TERT), which comprises the catalytic subunit of the enzyme and an integral RNA component (TER), which contains the template TERT uses to synthesize telomeres8,9. Prior to 2008, only structures for individual telomerase domains had been solved10,11. A major breakthrough in this field came from the determination of the crystal structure of the active12, catalytic subunit of T. castaneum telomerase, TcTERT1.
Here, we present methods for producing large quantities of the active, soluble TcTERT for structural and biochemical studies, and the reconstitution of the telomerase RNP complex in vitro for telomerase activity assays. An overview of the experimental methods used is shown in Figure 1.

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more ...

Visualization of DNA Replication in the Vertebrate Model System DT40 using the DNA Fiber Technique

Maintenance of replication fork stability is of utmost importance for dividing cells to preserve viability and prevent disease. The processes involved not only ensure faithful genome duplication in the face of endogenous and exogenous DNA damage but also prevent genomic instability, a recognized causative factor in tumor development.
Here, we describe a simple and cost-effective fluorescence microscopy-based method to visualize DNA replication in the avian B-cell line DT40. This cell line provides a powerful tool to investigate protein function in vivo by reverse genetics in vertebrate cells1. DNA fiber fluorography in DT40 cells lacking a specific gene allows one to elucidate the function of this gene product in DNA replication and genome stability. Traditional methods to analyze replication fork dynamics in vertebrate cells rely on measuring the overall rate of DNA synthesis in a population of pulse-labeled cells. This is a quantitative approach and does not allow for qualitative analysis of parameters that influence DNA synthesis. In contrast, the rate of movement of active forks can be followed directly when using the DNA fiber technique2-4. In this approach, nascent DNA is labeled in vivo by incorporation of halogenated nucleotides (Fig 1A). Subsequently, individual fibers are stretched onto a microscope slide, and the labeled DNA replication tracts are stained with specific antibodies and visualized by fluorescence microscopy (Fig 1B). Initiation of replication as well as fork directionality is determined by the consecutive use of two differently modified analogues. Furthermore, the dual-labeling approach allows for quantitative analysis of parameters that influence DNA synthesis during the S-phase, i.e. replication structures such as ongoing and stalled forks, replication origin density as well as fork terminations. Finally, the experimental procedure can be accomplished within a day, and requires only general laboratory equipment and a fluorescence microscope.

DT40, a model vertebrate genetic system, provides a powerful tool to analyze protein function. Here we describe a simple method that allows qualitative analysis of parameters that influence DNA synthesis during the S-phase in DT40 cells at the single molecule level.

Maintenance of replication fork stability is of utmost importance for dividing cells to preserve viability and prevent disease. The processes involved not ...

Robust 3D DNA FISH Using Directly Labeled Probes

3D DNA FISH has become a major tool for analyzing three-dimensional organization of the nucleus, and several variations of the technique have been published. In this article we describe a protocol which has been optimized for robustness, reproducibility, and ease of use. Brightly fluorescent directly labeled probes are generated by nick-translation with amino-allyldUTP followed by chemical coupling of the dye. 3D DNA FISH is performed using a freeze-thaw step for cell permeabilization and a heating step for simultaneous denaturation of probe and nuclear DNA. The protocol is applicable to a range of cell types and a variety of probes (BACs, plasmids, fosmids, or Whole Chromosome Paints) and allows for high-throughput automated imaging. With this method we routinely investigate nuclear localization of up to three chromosomal regions.

We describe a robust and versatile protocol for analyzing nuclear architecture by 3D DNA FISH using directly labeled fluorescent probes.

3D DNA FISH has become a major tool for  analyzing three-dimensional organization of the nucleus, and several variations  of the technique have been ...

Identification of Post-translational Modifications of Plant Protein Complexes

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to infection via the recruitment and activation of immune complexes. Activation of immune complexes is associated with post-translational modifications (PTMs) of proteins, such as phosphorylation, glycosylation, or ubiquitination. Understanding how these PTMs are choreographed will lead to a better understanding of how resistance is achieved.
Here we describe a protein purification method for nucleotide-binding leucine-rich repeat (NB-LRR)-interacting proteins and the subsequent identification of their post-translational modifications (PTMs). With small modifications, the protocol can be applied for the purification of other plant protein complexes. The method is based on the expression of an epitope-tagged version of the protein of interest, which is subsequently partially purified by immunoprecipitation and subjected to mass spectrometry for identification of interacting proteins and PTMs.
This protocol demonstrates that: i). Dynamic changes in PTMs such as phosphorylation can be detected by mass spectrometry; ii). It is important to have sufficient quantities of the protein of interest, and this can compensate for the lack of purity of the immunoprecipitate; iii). In order to detect PTMs of a protein of interest, this protein has to be immunoprecipitated to get a sufficient quantity of protein.

We describe here a protocol for the purification and characterization of plant protein complexes. We demonstrate that by immunoprecipitating a single protein within a complex, so we can identify its post-translational modifications and its interacting partners.

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to ...

Chromatin Immunoprecipitation Assay for the Identification of Arabidopsis Protein-DNA Interactions In Vivo

Intricate gene regulatory networks orchestrate biological processes and developmental transitions in plants. Selective transcriptional activation and silencing of genes mediate the response of plants to environmental signals and developmental cues. Therefore, insights into the mechanisms that control plant gene expression are essential to gain a deep understanding of how biological processes are regulated in plants. The chromatin immunoprecipitation (ChIP) technique described here is a procedure to identify the DNA-binding sites of proteins in genes or genomic regions of the model species Arabidopsis thaliana. The interactions with DNA of proteins of interest such as transcription factors, chromatin proteins or posttranslationally modified versions of histones can be efficiently analyzed with the ChIP protocol. This method is based on the fixation of protein-DNA interactions in vivo, random fragmentation of chromatin, immunoprecipitation of protein-DNA complexes with specific antibodies, and quantification of the DNA associated with the protein of interest by PCR techniques. The use of this methodology in Arabidopsis has contributed significantly to unveil transcriptional regulatory mechanisms that control a variety of plant biological processes. This approach allowed the identification of the binding sites of the Arabidopsis chromatin protein EBS to regulatory regions of the master gene of flowering FT. The impact of this protein in the accumulation of particular histone marks in the genomic region of FT was also revealed through ChIP analysis.

Chromatin Immunoprecipitation Assay for the Identification of Arabidopsis Protein-DNA Interactions In Vivo

Chromatin immunoprecipitation is a powerful technique for the identification of DNA binding sites of Arabidopsis proteins in vivo. This procedure includes chromatin cross-linking and fragmentation, immunoprecipitation with selective antibodies against the protein of interest, and qPCR analysis of bound DNA. We describe a simple ChIP assay optimized for Arabidopsis plants.

Intricate gene regulatory networks orchestrate biological processes and developmental transitions in plants. Selective transcriptional activation and ...

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of diverse libraries of retroviral integration sites using ligation-mediated PCR (LM-PCR) amplification and next-generation sequencing (NGS), (2) mapping the genomic location of each virus-host junction using BEDTools, and (3) analyzing the data for statistical relevance. Genomic DNA extracted from infected cells is fragmented by digestion with restriction enzymes or by sonication. After suitable DNA end-repair, double-stranded linkers are ligated onto the DNA ends, and semi-nested PCR is conducted using primers complementary to both the long terminal repeat (LTR) end of the virus and the ligated linker DNA. The PCR primers carry sequences required for DNA clustering during NGS, negating the requirement for separate adapter ligation. Quality control (QC) is conducted to assess DNA fragment size distribution and adapter DNA incorporation prior to NGS. Sequence output files are filtered for LTR-containing reads, and the sequences defining the LTR and the linker are cropped away. Trimmed host cell sequences are mapped to a reference genome using BLAT and are filtered for minimally 97% identity to a unique point in the reference genome. Unique integration sites are scrutinized for adjacent nucleotide (nt) sequence and distribution relative to various genomic features. Using this protocol, integration site libraries of high complexity can be constructed from genomic DNA in three days. The entire protocol that encompasses exogenous viral infection of susceptible tissue culture cells to integration site analysis can therefore be conducted in approximately one to two weeks. Recent applications of this technology pertain to longitudinal analysis of integration sites from HIV-infected patients.

We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of ...

Experimental Protocol for Using Drosophila As an Invertebrate Model System for Toxicity Testing in the Laboratory

Emergent properties and external factors (population-level and ecosystem-level interactions, in particular) play important roles in mediating ecologically-important endpoints, though they are rarely considered in toxicological studies. D. melanogaster is emerging as a toxicology model for the behavioral, neurological, and genetic impacts of toxicants, to name a few. More importantly, species in the genus Drosophila can be utilized as a model system for an integrative framework approach to incorporate emergent properties and answer ecologically-relevant questions in&#160;toxicology research. The aim of this paper is to provide a protocol for exposing species in the genus Drosophila to pollutants to be used as a model system for a range of phenotypic outputs and ecologically-relevant questions. More specifically, this protocol can be used to 1) link multiple biological levels of organization and understand the impact of toxicants on both individual- and population-level fitness; 2) test the impact of toxicants at different stages of developmental exposure; 3) test multigenerational and evolutionary implications of pollutants; and 4) test multiple contaminants and stressors simultaneously.

Experimental Protocol for Using Drosophila As an Invertebrate Model System for Toxicity Testing in the Laboratory

In this paper, we provide a detailed protocol for exposing species in the genus Drosophila to pollutants with the goal of studying the impact of exposure on a range of phenotypic outputs at different developmental stages and for more than one generation.