This work was supported by NIH grants DP2DK116645 (to B.S.S.), Dunn Foundation pilot award and NASA grant 80NSSC22K0250 (to B.S.S.). This project was also supported by the Cytometry and Cell Sorting Core at Baylor College of Medicine with funding from the CPRIT Core Facility Support Award (CPRIT-RP180672), the NIH (S10 OD025251, CA125123, and RR024574), and the assistance of Joel M. Sederstrom, plus an instrumentation grant for the LPS NIH grant (S10 OD025251). Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440).

1. Preparation of microbiome mixture
<ol>
	<li>Stamp or streak out bacteria from a glycerol freezer stock onto a lysogeny broth (LB) plate, or appropriate growth medium, and grow overnight at an optimal temperature based on bacterial strains of interest (typically 25 &#176;C for C. elegans natural microbes).</li>
	<li>From the LB plate, use a single colony from each bacterial isolate (e.g., 12 bacteria of the CeMbio collection) to inoculate 800 &#181;L of LB medium in separate wells of a 1 mL ...

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The authors have no conflicts of interest to declare.

Flow vermimetry has been used to characterize C. elegans genes and pathways against pathogen colonization and toxicity in several studies21,22. Here, a high throughput amenable approach is presented that uses C. elegans to investigate how intestinal microbiomes modulate their host physiology. Compared to existing methods using colony forming units (CFU) or 16S rRNA amplicon sequencing9,16</sup...

Animal evolution is under constant microbial influence1. From diverse microbes in the environment, animal hosts acquire specific partners2 that extend the capabilities of the host and drive its physiology and susceptibility to disease3. For example, metagenomic analyses of the gut microbiome uncovered enriched metabolic classes of microbial genes that may confer greater energy harvest and storage in obese mice4, many of which are also found in the human gut microbiome5. There is still a great need to establish causal relationships and pinpoint the molecular determinants of the microbiome impact, though progress has been hampered by the microbiome complexities and tractability of host systems to large-scale screening.
The model organism C. elegans provides a platform to advance molecular understanding of links between microbiome and host physiology. C. elegans possesses 20 intestinal cells with a mucosal layer and villi structures. These cells are equipped with abundant chemoreceptor genes that sense microbial products and produce antimicrobial molecules that potentially regulate their gut colonizers6,7. This conserved biology of C. elegans has led to a tremendous number of discoveries in host signaling that regulate gut microbes, including insulin signaling, TGF-beta, and MAP Kinase8,9,10.
C. elegans utilize microbes as both their diet for growth during development and microbiome as adults. With old age, some microbes may over-accumulate in the gut lumen and the host-microbe relationship shifts from symbiosis to pathogenesis11. In their natural habitats, C. elegans encounters a wide array of bacterial species12,13. Sequencing 16S rDNA from representative samples collected in natural habitats (rotten fruits, plant stem, and animal vectors) revealed that the natural microbiome of C. elegans is dominated by four bacterial phyla: Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. Within these divisions lies great variation in the diversity and richness of bacteria based on the habitat12,13,14,15. Several defined communities have been established, including the 63-member (BIGbiome)16 and 12-member (CeMbio) collections representing the top microbiome genera created for the C. elegans research community17. Both microbiomes and component strains can have a diverse impact on the physiology of C. elegans such as body size, growth rates, and stress responses9,16,17. These studies provide resources and examples to establish C. elegans as a model for microbiome research.
Here a large particle sorter (LPS) based workflow (Figure 1) is presented that utilizes the C. elegans system to simultaneously measure microbiome composition and basic measures of host physiology at the population scale. From the microbial side, the workflow is adaptable to assemble a defined microbiome or single microbes to test the robustness and plasticity of the community with increasing microbial interactions. From the host side, the workflow enables high throughput assays to measure colonization levels of fluorescent microbes in the microbiome and host physiological readout in terms of development, body size, and reproduction. Taken together, the C. elegans microbiome model enables high throughput screens to pinpoint the metabolic and genetic determinants modulating host physiology.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>15 mL conical bottom centrifuge tubes</td>
			<td>VWR</td>
			<td>10026-076</td>
			<td></td>
		</tr>
		<tr>
			<td>96 deep-well plates (1 mL)</td>
			<td>Axygen</td>
			<td>P-DW-11-C</td>
			<td></td>
		</tr>
		<tr>
			<td>96 deep-well plates (2 mL)</td>
			<td>Axygen</td>
			<td>P-DW-20-C</td>
			<td></td>
		</tr>
		<tr>
			<td>96-well Costar plate</td>
			<td>Corning</td>
			<td>3694</td>
			<td></td>
		</tr>
		<tr>
			<td>Agar</td>
			<td>Millipore Sigma</td>
			<td></td>
			<td>Standard bacteriology agar is also sufficient.</td>
		</tr>
		<tr>
			<td>Aspirating manifold</td>
			<td>V&#38;P scientific</td>
			<td>VP1171A</td>
			<td></td>
		</tr>
		<tr>
			<td>Bleach</td>
			<td>Clorox</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bleach solution&#160;</td>
			<td></td>
			<td></td>
			<td>Mix Bleach with 5M Sodium hypochlorite 2:1 (v/v)</td>
		</tr>
		<tr>
			<td>Cell Imaging Multimode Reader</td>
			<td>Biotek</td>
			<td>Cytation 5</td>
			<td>Bacterial OD measurement</td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Thermo scientific&#160;</td>
			<td>Sorvall Legend XTR</td>
			<td>For 96 well plate and conical tubes</td>
		</tr>
		<tr>
			<td>Fluorescent Microscope</td>
			<td>Nikon</td>
			<td>TiE</td>
			<td></td>
		</tr>
		<tr>
			<td>ggplot: Various R Programming Tools for Plotting Data.</td>
			<td>R package</td>
			<td>Version 3.3.2</td>
			<td></td>
		</tr>
		<tr>
			<td>Large Particle Autosampler</td>
			<td>Union Biometrica</td>
			<td>LP Sampler</td>
			<td></td>
		</tr>
		<tr>
			<td>Large Particle Sorter</td>
			<td>Union Biometrica</td>
			<td>COPAS Biosorter</td>
			<td></td>
		</tr>
		<tr>
			<td>Levamisole</td>
			<td>Fisher</td>
			<td>AC187870100</td>
			<td></td>
		</tr>
		<tr>
			<td>Lysogeny Broth (LB)</td>
			<td>RPI</td>
			<td>L24066</td>
			<td>Standard LB home-made recipes using Bacto-tryptone, yeast extract, and NaCl are also sufficient.</td>
		</tr>
		<tr>
			<td>M9 solution&#160;</td>
			<td></td>
			<td></td>
			<td>22 mM KH2PO4 monobasic, 42.3 mM Na2HPO4, 85.6 mM NaCl, 1 mM MgSO4</td>
		</tr>
		<tr>
			<td>Nematode Growth Medium</td>
			<td>RPI</td>
			<td>N81800-1000.0</td>
			<td>1 mM CaCl2, 25 mM KPO4 pH 6.0, 1 mM MgSO4 added after autoclaving.</td>
		</tr>
		<tr>
			<td>RStudio</td>
			<td>GNU</td>
			<td>Version 1.3.1093</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hypochlorite</td>
			<td>Sigma-Aldrich</td>
			<td></td>
			<td>5M NaOH</td>
		</tr>
		<tr>
			<td>Stereo Microscope</td>
			<td>Nikon</td>
			<td>SMZ745</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile 10 cm diameter petri dishes</td>
			<td>Corning</td>
			<td>351029</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile 12-well plates</td>
			<td>VWR</td>
			<td>10062-894</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile 24-well plates</td>
			<td>VWR</td>
			<td>10062-896</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile 6 cm diameter petri dishes</td>
			<td>Corning</td>
			<td>351007</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>Sigma-Aldrich</td>
			<td>T8787</td>
			<td></td>
		</tr>
	</tbody>
</table>

application of flow vermimetry for quantification and analysis of the caenorhabditis elegans gut microbiome

The composition of the gut microbiome can have a dramatic impact on host physiology throughout the development and the life of the animal. Measuring compositional changes in the microbiome is crucial in identifying the functional relationships between these physiological changes. Caenorhabditis elegans has emerged as a powerful host system to examine the molecular drivers of host-microbiome interactions. With its transparent body plan and fluorescent-tagged natural microbes, the relative levels of microbes within the gut microbiome of an individual C. elegans animal can be easily quantified using a large particle sorter. Here we describe the procedures for the experimental setup of a microbiome, collection, and analysis of C. elegans populations in the desired life stage, operation, and maintenance of the sorter, and statistical analyses of the resulting datasets. We also discuss considerations for optimizing sorter settings based on the microbes of interest, the development of effective gating strategies for C. elegans life stages, and how to utilize sorter capabilities to enrich animal populations based on gut microbiome composition. Examples of potential applications will be presented as part of the protocol, including the potential for scalability to high-throughput applications.

Defining adult and larvae population gates 
Here, synchronized C. elegans L1s were grown on an NGM plate seeded with E. coli OP50 (Eco), a standard laboratory diet. C. elegans populations were collected for LPS analysis after 96 h or 120 h of growth at 20 &#176;C (Figure 2A). A dot plot of extinction (EXT, a proxy of body density) versus time-of-flight (TOF, a proxy of body length) creates two visually separated clouds of animals. Each dot rep...

Watch this Scientific Journal Video about Application of Flow Vermimetry for Quantification and Analysis of the Caenorhabditis elegans Gut Microbiome at JoVE.com

Application of Flow Vermimetry for Quantification and Analysis of the Caenorhabditis elegans Gut Microbiome

Caenorhabditis elegans is a powerful model to examine the molecular determinants driving host-microbiome interactions. We present a high throughput pipeline profiling the single animal levels of gut microbiome colonization together with key aspects of the C. elegans physiology.

Application of Flow Vermimetry for Quantification and Analysis of the Caenorhabditis elegans Gut Microbiome

The composition of the gut microbiome can have a dramatic impact on host physiology throughout the development and the life of the animal. Measuring ...

The gut microbiome plays important roles in shaping host's physiology. This protocol, in particular, allows for high throughput assessment of fluorescent gut microbe colonization levels in single, cellular animals on a large scale. One major benefit of this method is the ability to monitor the gut microbiome of live animals in real time, which allows for the identification and correlation of any changes with the host's physiology.Demonstrating the procedure will be Dana Blackburn, a research associate from my laboratory. Begin by washing the worms off the bacterial lawn with one to two milliliters of M9-TX. Transfer the worms to a sterilized two milliliter 96 well deep plate.Pellet them at 300 G for one minute and remove the liquid using an aspirating manifold. Using a 1.2 milliliter multi-channel pipette, add 1.8 milliliters of M9-TX to each well of the deep well plate mixed by pipetting a couple of times and centrifuge at 300 G for one minute. After the final wash, bring the volume in each well to 100 microliters, using the aspirating manifold.Add 100 microliters of 10 millimolar levamisole and M9-T to each well, and allow the worms to paralyze for five minutes. Then add 4%bleach solution to each well for two minutes to reduce bacterial clumps. After the bleach treatment, add M9-TX into each well of the plate to wash the worms.Centrifuge the plate and aspirate to a final volume of 100 microliters after the second wash. Transfer the worms to a flat bottom 96 well plate, containing 150 microliters of 10 millimole of levamisole and M9-TX. Keep the worm density at 50 to 100 worms per well and split the worms into multiple wells if the population is too crowded.Turn on the air compressor, computer and LPS instrument. Check and empty the waste tank. Check and refill sheath and water tanks if the volume is low.Ensure the 250 micrometers fluidic and optical core assembly is in place. Connect and turn on the autosampler. Open the autosampler instrument software to open the autosampler and the LPS software.On the LPS software window, go to file and click new experiment, then select file again and click new sample check. Enable lasers to turn on 488 and 561 nanometer lasers if it has not been done already. Now create templates for acquisition dot plots, using time of flight, extinction and fluorescent channels in the LPS software window.Right click within the body of a graph to modify the scaling. Next, load the control samples. On the autosampler window, select prime, go to file, click open script to select the correct built-in script and click okay.Go to plate template on the sampler software menu to select the desired wells for analysis. After loading and securing the plate onto the autosampler stage, press run plate on the autosampler window and save the file when prompted, then click the store current data button on the top ribbon in the LPS software window and save the data again. Open the LPS software.Navigate to file and select new experiment, then go back to file and click new sample. Create a dot plot with the time of flight on the X axis and extinction on the Y axis. Create another dot plot with the time of flight on the X axis and red on the Y axis.Ensure to check enable lasers to activate the 488 and the 561 nanometer lasers. Position the control sample tube on the sample port, then click acquire within the acquire and dispense dialogue box. When prompted, ensure to save the file.Once enough worms have been measured to differentiate populations, select abort in the dot plot showing the time of flight versus extinction. Draw a gate around the area representing the adult population. Then navigate to view, click gating hierarchy and check that the fluorescent gates are correctly listed under the adult population gate.In the time of flight versus red dot plot, create gates around the high and low red value areas to highlight the regions of interest showing microbiome colonization in adult worms. Once settings are optimized, proceed to file and click save experiment, then click file and select save sample. To load the collection apparatus, select load plate A to allow the collection stage to move into a position primed for loading either a collection tube or a 96 well plate.For dispensing to a 96 well plate, go to the setup section and select plates, then click on calibrated plates and choose 96 well plate. Next, select the wells to which the worms will be sorted and input the number of objects to be sorted into each well. Be sure to specify the gated regions of interest as well.If there are multiple gated regions being sorted into the same plate, ensure to check the box marked gate each well. Click okay to save the changes. After sorting numbers and assigning the locations, load the sample onto the sample port and click on the fill plate buttons from the acquire and dispense dialogue box to initiate dispensing into a 96 well plate.Higher extension and time of flight values are observed in adults compared to larvae. Progenies from two day old adults were dominated by L1 and L2 stages, while most progeny from three day old adults reached L3 and L4 stages. When grown on E.coli, the time of flight and extension values increased on day three compared to day two.When grown on ochrobactrum, BH three and mixed cultures, cenor abdidas allegands showed differences in time of flight and extension values. Increased ochrobactrum BH3 colonization was observed in the mixed condition than in ochrobactrum BH3 alone. In contrast, green, fluorescent values indicated lower OP50 colonization in the mixed condition than in OP50 alone.The worms are heavily skewed toward the Y axis, suggesting OP50 colonization is low in most worms, while levels of ochrobactrum, BH3 colonization are evenly distributed in the population. The relationship between ochrobactrum, BH3 colonization levels and host's development such as body density and the differences in reproduction patterns was also observed. The three-day old adults grown on the two member mix, microbiome exhibited a wide range of RFP intensity, indicating individual variations in ochrobactrum colonization within the group.RFP images of the wells containing 15 sorted and individual worms from high and low RFP gates are shown. The most important thing is to remember to use appropriate controls for all of the steps to ensure that the protocol and the machine are working properly. In real time, animals with specific features can be used to isolate strains from host or microbial mutant pools to identify genes that regulate post microbe interactions.Isolated animals can also be used for single animal or enriched phenotypic pool based downstream analyses, like RNA-seq or the like. Really, the opportunities are truly endless.

application-flow-vermimetry-for-quantification-analysis

Research

JoVE Journal

Biology

620 visualizações.  Baylor College of Medicine. O microbioma intestinal desempenha papéis importantes na formação da fisiologia do hospedeiro. Este protocolo, em particular, permite a avaliação de alto rendimento dos níveis de colonização por micróbios intestinais fluorescentes em animais celulares únicos em larga escala. Um grande benefício desse método é a capacidade de monitorar o microbioma intestinal de animais vivos em tempo real, o que permite a identificação e correlação de quaisquer alterações com a fisiologia d...