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.
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.
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.
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 downstream 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 'label' 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.
1. Insect Rearing
2. 13C-labeling of DNA in Metabolically Active Gut Bacteria
3. Insect Dissection
4. DNA Extraction and Amplification
5. DNA Separation-CsCl Gradient Ultracentrifugation
6. DNA Characterization by Pyrosequencing
7. Pyrosequencing Data Analysis
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 in the artificial diet of the control insects. As mentioned before, separation of the DNA fractions (heavier from lighter) is the basis of the whole process. Therefore, the first step to be performed is the extraction of DNA from the tissue of interest; in this case, the bacterial community associated with the insect gut. To confirm its quality it is important to run an electrophoresis gel to determine if any DNA at all was obtained from the analyzed tissue. In Figure 1C, it is observable a strong band of genomic DNA at the top of the image confirming the positive DNA extraction. In addition, it is necessary to perform a diagnostic PCR, using bacterial universal primers, to determine the presence of bacterial DNA (Figure 1D). This positive result is important to decide if further continue with the separation of the extracted metagenomic DNA.
After ultracentrifugation, once the quantity of the DNA in each separated fraction is confirmed, and the measurement of the density is done, plot the average fraction density in g/ml over fraction number to confirm the proper gradient formation in tubes, which normally covers a density range from 1.690 g/ml (for fraction 12 or 11) to 1.760 g/ml (for fraction 1). Quantitative pyrosequencing is performed directly on the representative SIP gradients to reveal species lineage and relative abundance (Figure 2). Here we sequenced the heavy fractions from both the 13C-glucose amended sample and the unlabeled control, which served for profiling active populations in the community. After sequencing, a total of 120,045 high quality reads with an average length of 404 nucleotides were generated. The pyrosequencing profile showed an increased abundance of certain species including Enterococcus and Pantoea in the labeled sample (13C-labeled DNA, Figure 3) compared with that in the control group (12C Control DNA, Figure 3). Therefore those bacteria are considered to be metabolically active, and merit further study.
Figure 1. 13C-glucose feeding experiment, DNA extraction and PCR amplification of the bacterial 16S rRNA gene. (A) 13C-glucose amended artificial diet consumed by Spodoptera littoralis larvae. (B) Native glucose (12C-glucose) amended artificial diet consumed by larvae from the same batch of insects used in (A), which serves as the control. (C) Typical metagenomic DNA extract from the gut tissue of larvae in the 13C-glucose treatment group and in the 12C-glucose control group. Three biological replicates (lane 1, 2 and 3) are included in each group. M stands for 1 kb DNA marker. (D) PCR amplification with a universal bacterial primer set generates the correct 1.5 kb 16S rRNA gene products by using the extracted metagenomic DNA as the template. Lanes 1 is the PCR positive control. Lane 2 and 3 represent the 13C-glucose treated sample and the 12C-glucose control, respectively. Click here to view larger image.
Figure 2. Outline of a Pyro-SIP experiment involving CsCl density gradient ultracentrifugation and fraction characterization with pyrosequencing of the separated DNA. H= higher abundance, L= lower abundance. Click here to view larger image.
Figure 3. Bacterial diversity and relative abundance in the heavy fractions of the native glucose fed larvae (12C-control DNA) and 13C-glucose fed larvae (13C-labeled DNA). Click here to view larger image.
The gut of most insects harbors a rich and complex microbial community; typically 107-109 prokaryotic cells lodge there, outnumbering the host's own cells in most cases. Thus, the insect gut is a "hot spot" 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 gut microbiota is rare. Stable isotope probing approaches offer now a possibility for distinguishing the active members from a complex microbiota background independent of cultivation and even in vivo. We applied this valuable tool to study the gut microbiota in an insect model system, cotton leaf worm (Spodoptera littoralis). Since glucose is the dominant sugar in the gut of cotton leafworm, in this demonstration we fed the larvae with an artificial diet spiked with an extra but physiological dose of 13C-glucose to track the metabolically active bacteria in the gut flora. An identical incubation established with native glucose provided a critical control for subsequent comparison to ensure that any apparent labeling of nucleic acid was not an artifact of the method itself, such as high G+C content in DNA contributing to separation. The near in situ concentration of glucose additionally reduced experimental bias. Other considerations related to a rigorous experimental setup of the DNA-SIP study has been discussed elsewhere28,29. The gut bacteria normally are metabolically highly active and have short generation time compared to the microorganisms from most terrestrial and aquatic environments. Thus a 24 hr continuously feeding caused already a significant labeling. Note that a large amount of host genomic DNA was also coextracted from the gut tissues, which should be taking into consideration when discussing the results.
The typical gradient fraction characterization relies on the low-resolution fingerprinting methods, such as terminal restriction fragment length polymorphism (T-RFLP), and time consuming clone library construction to link the data. It is only recently that the advent of high-throughput second generation sequencing technique allows for rapid, cost-effective, and detailed analysis of complex microbial communities. Here we applied this new technology to directly survey the genetic composition of density gradient fractions and identify metabolically active bacteria, which gave enhanced sensitivity compared with the gel electrophoresis-based methods, and facilitated subsequent phylogenic classification. By comparing equivalent heavy fractions from both the 13C-labeled and 12C-control samples, we find that Pantoea and Enterococcus became labeled upon isotope probing. Once the metabolically active bacteria have been identified, other analysis such as the fluorescence in situ hybridization (FISH) using specific probes and metagenomic analysis of the labeled DNA recovered from active community members can be conducted to provide a comprehensive insight into the true symbionts associated with the host. Based on the established system here, other 13C-labeled carbon sources could also be fed into the host to dissect the bacteria involved in the targeted gut metabolic pathway, for instance, labeling the cellulose to identify active bacteria involved in the host digestion process. With the development of such new approaches, the role of insect gut microbiota will become more apparent than currently.
Collectively, the protocol described here represents a straightforward, rapid, and effective method for determining metabolic activities of the gut microbiota, which further could be applied to assess the specific role of bacterial symbionts in the host nutrition, detoxification, and defense.
The authors have nothing to disclose.
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).
Dumont #5 Mirror Finish Forceps | Fine Science Tools | 11251-23 | |
Vannas Spring Scissors | Fine Science Tools | 15000-00 | |
Speed Vacuum Concentrator 5301 | Eppendorf Germany | 5305 000.304 | |
Plastic pestle | Carl Roth GmbH Co. Germany | P986.1 | |
NanoVue spectrophotometer | GE HealthCare, UK | 28-9569-58 | |
Mastercycler pro/thermocycler | Eppendorf Germany | 6321 000.515 | |
Agagel Standard Horizontal Gel Electrophoresis chamber | Biometra | Discontinued | |
Ultracentrifuge (Optima L-90K) | Beckman | A20684 | |
Ultracentrifuge rotor (NVT 90) | Beckman | 362752 | |
HPLC pump | Agilent | 1100 | |
Quick-Seal, Polyallomer tube | Beckman | 342412 | |
Transilluminator UVstar 15 | Biometra |