This work was funded by the UK Medical Research Council (grant to P.B. MR/L008157/1); R.J. was supported by a Marie Curie Intra-European Fellowship (H2020-MSCA-IF-2015-703639); P.M.B. was supported by a studentship from the UK Medical Research Council and King&#39;s College London Doctoral Training Partnership in Biomedical Sciences (MR/N013700/1).

Experiments described here were performed using 6-8 weeks old wild-type (C57BL6/J) mice maintained in a specific pathogen free (SPF) facility. All animal experiments were approved by the King&#8217;s College London and the Francis Crick Institute Animal Welfare and Ethical Review Body and the United Kingdom Home Office. Prior to beginning any animal procedure, ensure that the appropriate permissions are obtained through the local institution/organization.
1. Administration of Antibiotics
NOTE: Two alternative methods for antibiotic treatment are provided: oral gavage (step 1.1) and administration of antibiotics via drinking water (step 1.2).
<ol>
	<li>Oral gavage
	<ol>
		<li>Prepare stocks of individual antibiotics by dissolving them in autoclaved water at the following concentrations: Ampicillin at 100 mg/mL, Gentamicin at 100 mg/mL, Neomycin at 100 mg/mL, Metronidazole at 10 mg/mL and Vancomycin at 100 mg/mL. Filter sterilize using a 0.45 &#181;m filter. Aliquot and store at -20 &#176;C.</li>
		<li>Prepare a cocktail of antibiotics by mixing the stocks prepared above. For a volume of 1 mL mix 50 &#181;L of Ampicillin (5 mg/mL final), 50 &#181;L of Gentamicin (5 mg/mL final), 50 &#181;L of Neomycin (5 mg/mL final), 500 &#181;L of Metronidazole (5 mg/mL final), 25 &#181;L of Vancomycin (2.5 mg/mL final) and 325 &#181;L of water. Prepare the cocktail fresh before use.</li>
		<li>Load the antibiotic mix into a sterile 1 mL syringe and fix&#160;an appropriate gauge gavage needle (20 G for 15&#8211;20 g mice) while eliminating any bubbles.</li>
		<li>Gavage mice with 200 &#181;L of antibiotic mix.
		<ol>
			<li>Grab the skin over the mouse shoulder firmly, stretch the head and neck to straighten the esophagus. Direct the ball-tip of the feeding needle along the roof of the mouth and toward the back of the pharynx. Then, gently pass it down into the esophagus and inject the 200 &#956;L solution.</li>
		</ol>
		</li>
		<li>Administer the antibiotic cocktail once daily for the duration of the experiment.</li>
	</ol>
	</li>
	<li>Antibiotics in the Drinking Water 
	CAUTION: Carefully monitor mouse weight daily for the first two weeks of antibiotic administration in the drinking water.
	<ol>
		<li>Prepare a cocktail of antibiotics by dissolving the following in 1 L of autoclaved water: 1 g of Ampicillin (1 g/L final), 1 g of Neomycin (1 g/L final), 1 g of Metronidazole (1 g/L final), 0.5 g of Vancomycin (0.5 g/L final) and 8 sachets (0.75 g each) of artificial sweetener (60 g/L final). Shake until dissolved. Store at 4 &#176;C. 
		NOTE: Sweetener is added to hide the flavor of antibiotics and prevent mice dehydration. While several sweetener brands may work, the final concentration required may be different for each specific brand.</li>
		<li>Fill the antibiotic cocktail into a water bottle (~100 mL/bottle) and place the bottle on a mouse cage. 
		NOTE: Use brown bottles or cover the bottles with foil to protect antibiotics from light.</li>
		<li>Replace the antibiotic cocktail with fresh stock twice a week for the duration of the experiment.</li>
	</ol>
	</li>
</ol>
2. Collection of Fecal Samples from Stool, Ileum Content, and Ileum Wall
<ol>
	<li>Weigh and label 2 mL autoclaved tubes for sample collection.</li>
	<li>For collection of fresh stool samples, place each mouse in a restrainer and collect fecal pellets directly from the anus in a collection tube. 
	NOTE: Samples can also be obtained by placing mice in a clean autoclaved cage, and collecting stool samples with clean sterilized forceps.</li>
	<li>Euthanize the mice with CO2 asphyxiation followed by cervical dislocation.</li>
	<li>Lay a mouse carcass with the abdomen fully exposed and spray the abdominal area with 70% ethanol.</li>
	<li>Using sterilized forceps and scissors, make a transverse incision in the abdomen to expose the peritoneum without damaging any internal tissues. Lift the peritoneum and make an incision to expose the intestines.</li>
	<li>Remove the intestines (from colon to stomach) with the forceps and scissors and place it in a sterile Petri dish.</li>
	<li>Carefully use forceps to tease the small intestine (SI) away from the mesenteric arteries and fat. Extend the intestine and place it on a clean lab wipe.</li>
	<li>With a ruler, measure and cut 4 cm of the distal ileum of the SI (the closest part to the cecum). Cut and discard the 1 cm of intestine proximal to the cecum. There will be a 3 cm portion of ileum left which will be used to collect intestinal bacteria.</li>
	<li>Hold the ileum portion (3 cm) over a 2 mL sterile tube. Collect the intestinal content by directly extruding the intestine and colleting the sample in the tube. This sample will have bacteria from the ileum content.</li>
	<li>Prepare a 20 mL syringe with cold phosphate buffered saline (PBS) and flush the ileum portion (discard the flow-through).</li>
	<li>Place the ileum portion on a clean paper towel&#160;and open it longitudinally with scissors.</li>
	<li>Scrape the inside of the ileum wall with a scalpel.</li>
	<li>Collect any bacteria on the scalpel by washing the scalpel with 1 mL of PBS over a clean centrifuge tube. Spin at 8,000 &#215; g for 5 min to pellet the bacteria and discard the supernatant. This sample will contain bacteria from the ileum wall. 
	NOTE: Fecal samples from stool, ileum content and wall can be frozen and stored at -80 &#176;C until use.</li>
	<li>Weigh the tubes containing the samples from stool and ileum content, and subtract the weight from the empty tubes (from step 2.1) to obtain the fecal weight in each sample.</li>
	<li>Extract bacterial DNA from stool, ileum content and ileum wall samples using commercially available kits. Store DNA samples at -20 &#176;C until use.</li>
</ol>
3. Quantification of Intestinal Microbiota by qPCR
NOTE: This procedure includes the generation of a standard (step 3.1) and the method for qPCR set-up for standard and fecal samples (step 3.2)
<ol>
	<li>Generation of a standard for qPCR
	<ol>
		<li>Use polymerase chain reaction (PCR) to amplify the 16S rRNA gene from the genomic DNA extracted from a bacterial culture using the reagents13 and PCR conditions detailed in Table 1.</li>
		<li>Run the PCR product on a 1.5% agarose gel and purify the DNA band using a commercially available DNA extraction kit.</li>
		<li>Ligate the purified DNA fragment using a cloning kit (see the Table of Materials, use a vector containing antibiotic resistance markers and &#946;-galactosidase (LacZ) gene fusion for blue/white colony selection) and transform DH10 competent E. coli following the manufacturer&#8217;s instructions. Plate transformation onto Ampicillin (100 &#181;g/mL), X-gal (20 &#181;g/mL) Luria Bertani (LB) agar plates (10 g/L Tryptone, 5 g/L Yeast Extract, 10 g/L NaCl, 15 g/L Agar). Incubate overnight (O/N) at 37 &#176;C.</li>
		<li>Select a single positive (white) colony from the plate. Inoculate it in 5 mL LB broth containing 100 &#181;g/mL Ampicillin and incubate O/N at 37 &#176;C, shaking at 250 rpm.</li>
		<li>From the O/N culture, isolate and purify the plasmid using a commercial miniprep kit according to manufacturer&#39;s instructions. 
		NOTE: It is important to sequence the plasmid insert at this stage, to ensure that the plasmid contains only one copy of the 16S rRNA gene and to determine its length in base-pairs (bp).</li>
		<li>Linearize the plasmid with a restriction enzyme which cuts the plasmid only once.</li>
		<li>Purify the linearized plasmid using a commercially available kit.</li>
		<li>Determine the concentration of the plasmid by measuring absorbance at 260 nm using a spectrophotometer.</li>
		<li>Calculate the number of plasmid copies/&#181;L of sample using the following formula14: 
		number of copies = (amount * 6.022 &#215; 1023) / (length * 1 &#215; 109 * 650) 
		where amount is the DNA concentration obtained in step 3.1.8 (in ng/&#181;L); and length is the total length of the plasmid (with the insert) in bp. The number of copies will be obtained as copies/&#181;L. 
		NOTE: There are online tools based on the above formula that enable easy calculation of the number of plasmid copies.</li>
		<li>Aliquot and store the standard as needed at -20 &#176;C until use.</li>
	</ol>
	</li>
	<li>qPCR Set-up for Standard and Fecal Samples
	<ol>
		<li>Thaw the qPCR standard (from step 3.1.10), fecal samples DNA (from step 2.15) and qPCR reagents (from a commercially available kit) on ice. 
		NOTE: qPCR reagents used in this example include the SYBR Green qPCR reaction mix and forward and reverse primers (Table 2).</li>
		<li>Dilute the standard in sterile DNA-free water in a range from 107 to 102 copies/&#181;L (e.g., 1/5 serial dilutions from 107 to 6.4 x 102 copies/&#181;L). Dilute fecal sample DNA to 1/2, 1/5, 1/10.</li>
		<li>Make a master mix reaction for the total number of reactions plus 1 (Table 2).</li>
		<li>Mix 30 &#181;L of the master mix and 5 &#181;L of template (standard, sample or water for negative control)</li>
		<li>Add 10 &#181;L of this mix to each well in a 384-well optical qPCR plate. Perform each reaction in triplicate.</li>
		<li>Seal the qPCR place, centrifuge briefly and load the plate on the qPCR machine programmed with the following cycling conditions: 95 &#176;C for 20 min followed by 40 cycles of 95 &#176;C for 15 s and 60 &#176;C for 1 min.</li>
		<li>Obtain CT values for standard and samples.</li>
		<li>Generate a standard curve by plotting the CT values for the standards versus the logarithm of the copy number of the plasmid (as calculated in step 3.1.9). Perform lineal regression of the standard curve.</li>
		<li>Calculate the 16S rDNA copy numbers for fecal samples by interpolating CT values (obtained in step 3.2.2) in the standard curve. 
		NOTE: 16S rDNA copy numbers for each sample should be corrected considering the dilution factor of the sample (as prepared in step 3.2.2), the final volume nucleic acids that were eluted (in step 2.15) and the quantity of fecal sample (calculated in step 2.14) to obtain gene copies per gram of feces.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Belkaid, Y., Hand, T. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+the+microbiota+in+immunity+and+inflammation.">Role of the microbiota in immunity and inflammation.</a> Cell. 157 (1), 121-141 (2014).</li><li>Hooper, L. V., Littman, D. R., Macpherson, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interactions+between+the+microbiota+and+the+immune+system.">Interactions between the microbiota and the immune system.</a> Science. 336 (6086), 1268-1273 (2012).</li><li>Ubeda, C., Pamer, E. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antibiotics,+microbiota,+and+immune+defense.">Antibiotics, microbiota, and immune defense.</a> Trends in Immunology. 33 (9), 459-466 (2012).</li><li>Dethlefsen, L., Huse, S., Sogin, M. L., Relman, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+pervasive+effects+of+an+antibiotic+on+the+human+gut+microbiota,+as+revealed+by+deep+16S+rRNA+sequencing.">The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing.</a> PLoS Biology. 6 (11), e280 (2008).</li><li>Reikvam, D. 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=Depletion+of+murine+intestinal+microbiota:+effects+on+gut+mucosa+and+epithelial+gene+expression.">Depletion of murine intestinal microbiota: effects on gut mucosa and epithelial gene expression.</a> PLoS One. 6 (3), e17996 (2011).</li><li>Hill, D. A., 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=Metagenomic+analyses+reveal+antibiotic-induced+temporal+and+spatial+changes+in+intestinal+microbiota+with+associated+alterations+in+immune+cell+homeostasis.">Metagenomic analyses reveal antibiotic-induced temporal and spatial changes in intestinal microbiota with associated alterations in immune cell homeostasis.</a> Mucosal Immunology. 3 (2), 148-158 (2010).</li><li>Fraher, M. H., O'Toole, P. W., Quigley, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Techniques+used+to+characterize+the+gut+microbiota:+a+guide+for+the+clinician.">Techniques used to characterize the gut microbiota: a guide for the clinician.</a> Nature Reviews Gastroenterology &amp; Hepatology. 9 (6), 312-322 (2012).</li><li>Eckburg, P. B., 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=Diversity+of+the+human+intestinal+microbial+flora.">Diversity of the human intestinal microbial flora.</a> Science. 308 (5728), 1635-1638 (2005).</li><li>Sokol, 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=Low+counts+of+Fecalibacterium+prausnitzii+in+colitis+microbiota.">Low counts of Fecalibacterium prausnitzii in colitis microbiota.</a> Inflammatiry Bowel Diseases. 15 (8), 1183-1189 (2009).</li><li>Bartosch, S., Fite, A., Macfarlane, G. T., McMurdo, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+bacterial+communities+in+feces+from+healthy+elderly+volunteers+and+hospitalized+elderly+patients+by+using+real-time+PCR+and+effects+of+antibiotic+treatment+on+the+fecal+microbiota.">Characterization of bacterial communities in feces from healthy elderly volunteers and hospitalized elderly patients by using real-time PCR and effects of antibiotic treatment on the fecal microbiota.</a> Applied Environmental Microbiology. 70 (6), 3575-3581 (2004).</li><li>Ubeda, C., 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=Vancomycin-resistant+Enterococcus+domination+of+intestinal+microbiota+is+enabled+by+antibiotic+treatment+in+mice+and+precedes+bloodstream+invasion+in+humans.">Vancomycin-resistant Enterococcus domination of intestinal microbiota is enabled by antibiotic treatment in mice and precedes bloodstream invasion in humans.</a> Journal of Clinical Investigation. 120 (12), 4332-4341 (2010).</li><li>Saez de Guinoa, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CD1d-mediated+lipid+presentation+by+CD11c(+)+cells+regulates+intestinal+homeostasis.">CD1d-mediated lipid presentation by CD11c(+) cells regulates intestinal homeostasis.</a> EMBO Journal. 37 (5), (2018).</li><li>Kruglov, A. A., 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=Nonredundant+function+of+soluble+LTalpha3+produced+by+innate+lymphoid+cells+in+intestinal+homeostasis.">Nonredundant function of soluble LTalpha3 produced by innate lymphoid cells in intestinal homeostasis.</a> Science. 342 (6163), 1243-1246 (2013).</li><li>Wilhelm, J., Pingoud, A., Hahn, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+PCR-based+method+for+the+estimation+of+genome+sizes.">Real-time PCR-based method for the estimation of genome sizes.</a> Nucleic Acids Research. 31 (10), e56 (2003).</li><li>Kembel, S. W., Wu, M., Eisen, J. A., Green, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Incorporating+16S+gene+copy+number+information+improves+estimates+of+microbial+diversity+and+abundance.">Incorporating 16S gene copy number information improves estimates of microbial diversity and abundance.</a> PLoS Computational Biology. 8 (10), e1002743 (2012).</li><li>Yang, Y. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+16S+rRNA+Gene-Targeted+Group-Specific+Primers+for+Real-Time+PCR+Analysis+of+Predominant+Bacteria+in+Mouse+Feces.">Use of 16S rRNA Gene-Targeted Group-Specific Primers for Real-Time PCR Analysis of Predominant Bacteria in Mouse Feces.</a> Applied Environmental Microbiology. 81 (19), 6749-6756 (2015).</li></ol>

The authors have nothing to disclose.

Here we provide experimental protocols for oral administration of antibiotics to mice and quantification of fecal bacteria by qPCR. The combination of antibiotics used in this protocol (containing ampicillin, gentamicin, neomycin, metronidazole and vancomycin) targets both Gram-positive and Gram-negative bacteria, offering bactericidal activity against a full spectrum of bacteria. Both oral gavage and administration of antibiotics in the drinking water greatly decrease fecal bacterial load5,6,12. Moreover, both treatments have a profound effect on the phenotype of the mice as they develop several characteristics typical of germ-free mice including reduced spleen size and enlarged cecum. The selection of a particular method for antibiotic administration may possibly depend on the length of the experiment as the oral gavage method requires daily administration of antibiotics, being more labor-intensive and possibly causing more discomfort to the animals in the long-run.
For administration of antibiotics in the drinking water, caution must be taken with the addition of the sweetener to the antibiotic mixture as this is a crucial factor to keep mice from dehydration. Several groups have shown how administration of antibiotics in drinking water (without addition of sweetener) leads to very severe and rapid weight-loss with all mice losing more than 20% of initial body weight within the first few days of the experiment5,6. In our protocol, the use of the saccharine-based sweetener seemed to be sufficient to mask the antibiotic taste in the water and mice lost weight in the first few days after antibiotic administration, but recovered their weights quickly after that (Figure 1). Nonetheless, in our experiments 5-10% of mice still reach the human end-point of &#62;20% loss of baseline body weight and needed to be euthanized. We have also tested sucralose-based sweeteners which completely failed to prevent mice dehydration (100% of mice lost &#62;20% of weight) while other authors have published similar failures for aspartame-based sweeteners5,6. Added to this, the age, genetic background and general health status of the mice used for the experiments should be considered, as they may influence weight-loss and animal well-being during antibiotic treatment. Thus, careful monitoring of mice weight and general health status should be performed daily during the first two weeks of oral antibiotic administration.
qPCR methods provide a fast and cost-effective approach for quantification of 16S rRNA in fecal samples. However, some limitations should be considered regarding this technique including: i) the requirement for a reliable high-quality standard; ii) the design and efficiency of the qPCR primers; iii) the fact that microorganisms may have different copy numbers of the 16S rRNA gene, thus gene copies may not directly equal cell counts15. Nonetheless, qPCR is a robust and sensitive method which enables rapid analysis of fecal samples. This method can be particularly useful to quickly validate the effect of various treatments (including antibiotics) in fecal bacterial loads as detailed here. Moreover, although we provide a protocol for quantification of total 16S rRNA, this method can be easily adapted (by designing specific primers16) to enable identification of individual bacterial taxa, thus providing both quantitative and qualitative information about microbiome size and composition.
In summary, we have provided two protocols for oral antibiotic treatment of mice and a qPCR-based method to quantify antibiotic-induced changes in fecal bacteria. Although these protocols can be further optimized and combined with other approaches according to individual experimental needs, they may serve as quick, cost-effective and reliable tools to manipulate the murine intestinal microbiota and to study of the effects of antibiotic treatment in intestinal homeostasis and disease.

The mammalian gastrointestinal mucosa is a unique environment colonized by a highly complex mixture of microorganisms that establish a mutualistic relationship with the host. The defense system of the intestinal mucosa comprises an epithelial layer and a plethora of immune cells that restrict commensals within the intestine while preserving their number and diversity. Conversely, commensal organisms are required for the development of a fully functional immune system. While interactions between host and commensal bacteria are normally beneficial, it is becoming increasingly clear that dysregulated immune system-microbiota crosstalk can favor the development of chronic inflammatory diseases, such asinflammatory bowel disease, arthritis or asthma1,2.
The gut microbiota can be altered by various factors, but perhaps the most drastic changes are induced by antibiotic treatment that severely alters both the size and composition of bacterial communities3,4. While the benefits of antibiotics to treat infections are unquestionable, the microbiota changes induced by antibiotic exposure in humans can also modify immune defenses which can lead to detrimental effects on health. For instance, antibiotic treatment in humans has been linked to an increased risk of Clostridium difficile-induced diarrhea, asthma and certain types of cancer3. Antibiotic treatment in mice recapitulates the impact and long-term alterations found in gut communities of antibiotic-treated patients, and has enabled investigation of the mechanistic links between changes in microbial communities and immune cell function. However, several reports have shown that administration of antibiotics on the drinking water ad libitum results in very noticeable weight loss as mice refrain from drinking water, presumably due to its foul taste5,6. Thus, in these models the severe dehydration concomitant to oral antibiotic administration may complicate the interpretation of experiments aiming to identify the effect of antibiotic treatment in immune cell function.
Several approaches can be used to explore the size and composition of microbial communities in the intestinal compartment7. Next generation sequencing technologies have provided invaluable data on this matter8, however these methods are relatively expensive and require expert bioinformatic analyses for interpretation of the data. On the other hand, traditional microbiological culture methods allow detection of the bacterial species, but they have low sensitivity and a large fraction of commensal bacteria (particularly anaerobes) are very difficult or impossible to cultivate with currently available methods8. Quantitative polymerase chain reaction (qPCR) techniques are being used increasingly for quantification and identification of fecal bacterial species, as they provide a fast and reliable culture-independent measure of total microbial load. Accordingly, qPCR methods have proved useful to study changes in the microbiota associated with age or with progression of several diseases including inflammatory bowel disease9,10. In line with this, qPCR methods provide a fast and cost-effective approach to validate the effect of various treatments (including antibiotics) in fecal bacterial loads and microbiota composition10,11,12.
Here, we present a detailed step-by-step account of two distinct protocols for oral antibiotic administration to mice, fecal sample collection, DNA extraction, preparation of standards and quantification of bacteria in fecal samples by qPCR. These protocols provide a reliable method to manipulate the intestinal microbiota in mice and to study of the effects of antibiotic treatment in intestinal homeostasis and disease.

<table><tbody><tr><td>Ampicillin sodium salt</td><td>Sigma-Aldrich (Merck)</td><td>A9518</td><td></td></tr><tr><td>Neomycnin trisulfate salt hydrate</td><td>Sigma-Aldrich (Merck)</td><td>N1876</td><td></td></tr><tr><td>Metronidazole</td><td>Sigma-Aldrich (Merck)</td><td>M3761</td><td></td></tr><tr><td>Vancomycin hydrochloride</td><td>Sigma-Aldrich (Merck)</td><td>V2002</td><td></td></tr><tr><td>Gentamicin sulfate salt</td><td>Sigma-Aldrich (Merck)</td><td>G3632</td><td></td></tr><tr><td>Tryptone</td><td>Sigma-Aldrich (Merck)</td><td>T7293</td><td></td></tr><tr><td>Yeast Extract</td><td>Sigma-Aldrich (Merck)</td><td>Y1625</td><td></td></tr><tr><td>NaCL</td><td>Sigma-Aldrich (Merck)</td><td>S7653</td><td></td></tr><tr><td>Sweetener Sweet&#039;n Low</td><td>Sweet&#039;N Low</td><td></td><td>Available in the UK from Amazon.co.uk</td></tr><tr><td>X-Gal (5-brom-4-chloro-3-indoyl B-D-galactopyranoside)</td><td>Fisher scientific</td><td>10234923</td><td></td></tr><tr><td>Phosphate Buffered Saline&amp;nbsp;</td><td>Thermo Fisher Scientific (Gibco)</td><td>10010023</td><td></td></tr><tr><td>Ultrapure Agarose</td><td>Thermo Fisher Scientific (Invitrogen)</td><td>16500500</td><td></td></tr><tr><td>RT-PCR grade water</td><td>Thermo Fisher Scientific (Invitrogen)</td><td>AM9935</td><td></td></tr><tr><td>Phusion High-Fidelity DNA Polymerase</td><td>New England BioLabs</td><td>M0530</td><td></td></tr><tr><td>Deoxynucleotide (dNTP) Solution Mix</td><td>New England BioLabs</td><td>N0447</td><td></td></tr><tr><td>iTaq Universal SYBR Green Supermix</td><td>Bio-Rad</td><td>1725124</td><td>with ROX</td></tr><tr><td>TOPO TA cloningTM for sequencing</td><td>Thermo Fisher Scientific (Invitrogen)</td><td>450030</td><td></td></tr><tr><td>QIAamp fast DNA Stool mini kit&amp;nbsp;</td><td>Qiagen</td><td>51604</td><td></td></tr><tr><td>QIAprep spin Miniprep kit</td><td>Qiagen</td><td>27106</td><td></td></tr><tr><td>QIAquick gel&amp;nbsp; extraction kit</td><td>Qiagen</td><td>28704</td><td></td></tr><tr><td>Syringe filter 0.45 &amp;micro;m</td><td>Fisher scientific</td><td>10460031</td><td></td></tr><tr><td>Swann-MortonTM Carbon steel sterile scalpel blades</td><td>Fisher scientific</td><td>11792724</td><td></td></tr><tr><td>Syringe (1 mL)</td><td>BD Plastipak</td><td>303172</td><td></td></tr><tr><td>Syringe (20 mL)</td><td>BD Plastipak</td><td>300613</td><td></td></tr><tr><td>1.5 mL Crystal clear microcentriguge tube</td><td>StarLab</td><td>E1415-1500</td><td></td></tr><tr><td>2 mL Ultra high recovery microcentrifuge tube</td><td>StarLab</td><td>I1420-2600</td><td></td></tr><tr><td>Oral dosing needles 20 G x 38 mm curved (pk/3)</td><td>Vet-Tech</td><td>DE008A</td><td></td></tr><tr><td>Sterilin petri dish 50 mm&amp;nbsp;</td><td>Scientific Laboratory Supplies</td><td>PET2020</td><td></td></tr><tr><td>Absolute qPCR plate seals</td><td>Thermo Fisher Scientific</td><td>AB1170</td><td></td></tr><tr><td>MicroAmpTM optical 384-well plate&amp;nbsp;</td><td>Thermo Fisher Scientific (Applied Biosystems)</td><td>4309849</td><td></td></tr><tr><td>ViiA7TM 7 real-time PCR system with 384-well block</td><td>Thermo Fisher Scientific (Applied Biosystems)</td><td>4453536</td><td></td></tr><tr><td>Spectrophotometer (Nanodrop 1000)</td><td>Thermo Fisher Scientific</td><td>ND-1000</td><td></td></tr><tr><td>Labnet Prism microcentrifuge</td><td>Labnet</td><td>C2500</td><td></td></tr><tr><td>MultiGene Optimax Thermal cycler</td><td>Labnet</td><td>TC9610</td><td></td></tr></tbody></table>

quantitative polymerase chain reaction-based analyses of murine intestinal microbiota after oral antibiotic treatment

The gut microbiota has a central influence on human health. Microbial dysbiosis is associated with many common immunopathologies such as inflammatory bowel disease, asthma and arthritis. Thus, understanding the mechanisms underlying microbiota-immune system crosstalk is of crucial importance. Antibiotic administration, while aiding pathogen clearance, also induces drastic changes in the size and composition of intestinal bacterial communities which can have an impact on human health. Antibiotic treatment in mice recapitulates the impact and long-term changes in human microbiota from antibiotic treated patients, and enables investigation of the mechanistic links between changes in microbial communities and immune cell function. While several methods for antibiotic treatment of mice have been described, some of them induce severe dehydration and weight-loss complicating the interpretation of the data. Here, we provide two protocols for oral antibiotic administration which can be used for long-term treatment of mice without inducing major weight-loss. These protocols make use of a combination of antibiotics that target both Gram-positive and Gram-negative bacteria and can be provided either ad libitum in the drinking water or by oral gavage. Moreover, we describe a method for the quantification of microbial density in fecal samples by qPCR which can be used to validate the efficacy of the antibiotic treatment. The combination of these approaches provides a reliable methodology for the manipulation of the intestinal microbiota and the study of the effects of antibiotic treatment in mice.

Here we provide two alternative protocols for oral antibiotic treatment of mice. Figure 1 shows percentage of body-weight (related to original base line weight for each animal) in mice treated with antibiotics either by oral gavage (red) or in the drinking water (blue) for 10 consecutive days. No noticeable weight-loss is found in mice that receive antibiotics by oral gavage. However, when mice are treated with antibiotics ad libitum in the drinking water, they lose weight (~10%) within the first few days of antibiotic administration, but recover normal weight gain thereafter (Figure 1). Nonetheless, around 5-10% of mice receiving antibiotics in the drinking water can reach &#62;20% weight loss within the first week of treatment, in which case they are euthanized.
The quantification of bacteria in fecal samples requires the use of an adequate standard curve which is obtained by plotting the log of copy number for the standard (as calculated in step 3.2.2) versus the CT values obtained from qPCR (step 3.2.7). Figure 2A shows a representative example from a standard curve which meets the standard curve performance criteria with a R2 value of 0.99827, a slope of -3.09 and a efficiency ((-1 + 10^(-1/slope))*100) of 110%. R2 values of 0.99 and PCR efficiencies within the range of 90 to 110% are preferred. Within the linear range, the regression analysis equation enables quantification of the 16S rDNA abundance within the fecal samples. Figure 2B shows the number of 16S rDNA copies in fecal stool, SI content and SI wall. In Figure 2B data are shown as 16S rDNA copies/g of fecal sample for fecal stool and SI content. For SI wall, data are presented as total number of 16S rDNA copies obtained from bacteria recovered from the 3 cm of SI wall (as the quantity of starting material is too small to obtain a precise weight).
To evaluate the effect of antibiotics on the density of bacteria in fecal samples, mice were treated with antibiotics by oral gavage daily for 10 days (days 1 to 10) and stool samples were collected before (day 0), at different time-points during antibiotic treatment (days 5 and 10), and 7 days after stopping antibiotic administration (day 17; Figure 3A). As shown in Figure 3B, antibiotic treatment induces a strong decrease in the number of 16S rDNA copies/g of feces detected at days 5 and 10, while the density of bacteria in the feces recovered to normal levels (comparable to pre-treatment) 1 week after antibiotic administration was stopped (day 17).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58481/58481fig1.jpg" /> 
Figure 1: Administration of antibiotics. Mice received antibiotics either by oral gavage (red) or in the drinking water (blue) for 10 consecutive days. Plot shows weights of mice throughout the duration of the experiments relative to original weight before antibiotic administration (day 0). Data are shown as mean &#177; SEM. <a href="https://www.jove.com/files/ftp_upload/58481/58481fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58481/58481fig2.jpg" /> 
Figure 2: 16S rRNA gene qPCR amplification of standards and fecal samples. (A) Linear regression of standard curve with standard curve descriptors. (B) Calculation of gene abundances from fecal samples. Data are shown as mean &#177; SEM. <a href="https://www.jove.com/files/ftp_upload/58481/58481fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58481/58481fig3.jpg" /> 
Figure 3: Fecal bacteria during antibiotic treatment. (A) Schematic of the schedule for antibiotic administration by oral gavage (Ab) and sample collection as depicted with *. (B) 16S rDNA copies per gram of feces in stool samples from mice collected at the indicated days. Data are shown as mean &#177; SEM. <a href="https://www.jove.com/files/ftp_upload/58481/58481fig3large.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>Volume</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA</td>
			<td>8 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Buffer 10X</td>
			<td>2 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>dNTPs (10mM)</td>
			<td>0.4 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Eubacteria - F primer (10 mM)</td>
			<td>1 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Eubacteria - R primer (10 mM)</td>
			<td>1 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq Polimerase</td>
			<td>0.2 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>H2O</td>
			<td>7.4 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>20 &#181;L</td>
			<td></td>
		</tr>
		<tr>
			<td>Primer sequences</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Eubacteria - F primer</td>
			<td>5&#39; ACTCCTACGGGAGGCAGCAGT 3&#39;</td>
			<td></td>
		</tr>
		<tr>
			<td>Eubacteria - R primer</td>
			<td>5&#39; ATTACCGCGGCTGCTGGC 3&#39;</td>
			<td></td>
		</tr>
		<tr>
			<td>Cycling conditions</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Temperature</td>
			<td>Time</td>
			<td>Cycles</td>
		</tr>
		<tr>
			<td>94 &#176;C</td>
			<td>5 min</td>
			<td>1x</td>
		</tr>
		<tr>
			<td>94 &#176;C</td>
			<td>30 s</td>
			<td>30x</td>
		</tr>
		<tr>
			<td>60 &#176;C</td>
			<td>30 s</td>
			<td>30x</td>
		</tr>
		<tr>
			<td>72 &#176;C</td>
			<td>1 min</td>
			<td>30x</td>
		</tr>
		<tr>
			<td>72 &#176;C</td>
			<td>5 min</td>
			<td>1x</td>
		</tr>
		<tr>
			<td>4 &#176;C</td>
			<td>&#8734;</td>
			<td>1x</td>
		</tr>
	</tbody>
</table>
Table 1: PCR reagents and conditions. This table provides the reagents and PCR cycling conditions to amplify 16S rRNA gene from bacterial culture for generation of a standard to use in the qPCR assays. Primer sequences were originally published by Kruglov et al.13.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Volume</td>
		</tr>
		<tr>
			<td>SYBR Green master mix (2x)</td>
			<td>17.5 &#181;L</td>
		</tr>
		<tr>
			<td>Eubacteria - F primer (10 mM)</td>
			<td>0.7 &#181;L</td>
		</tr>
		<tr>
			<td>Eubacteria - R primer (10 mM)</td>
			<td>0.7 &#181;L</td>
		</tr>
		<tr>
			<td>H2O</td>
			<td>11.1 &#181;L</td>
		</tr>
	</tbody>
</table>
Table 2: qPCR master mix. The volumes shown (final volume 35 &#181;L) are for a single sample to be run on triplicate (10 &#181;L each) on a 384-well qPCR plate (accounting for 5 &#181;L extra for pipetting error). The amount may be scaled up according to the number of samples to be analyzed.

Watch this Scientific Journal Video about Quantitative Polymerase Chain Reaction-based Analyses of Murine Intestinal Microbiota After Oral Antibiotic Treatment at JoVE.com

Quantitative Polymerase Chain Reaction-based Analyses of Murine Intestinal Microbiota After Oral Antibiotic Treatment

Here we provide detailed protocols for the oral administration of antibiotics to mice, collection of fecal samples, DNA extraction and quantification of fecal bacteria by qPCR.

The gut microbiota has a central influence on human health. Microbial dysbiosis is associated with many common immunopathologies such as inflammatory ...

quantitative-polymerase-chain-reaction-based-analyses-murine

Research

JoVE Journal

Immunology and Infection

12.8K Views.  King's College London. Here we provide detailed protocols for the oral administration of antibiotics to mice, collection of fecal samples, DNA extraction and quantification of fecal bacteria by qPCR.

Video: Quantitative Polymerase Chain Reaction-based Analyses of Murine Intestinal Microbiota After Oral Antibiotic Treatment

Reducing Research Animal Stress with Micropipette-Guided Drug Administration

Use of Micropipette-Guided Drug Administration as an Alternative Method to Oral Gavage in Rodent Models

Oral gavage (OG) with the use of a cannula attached to a syringe is one of the most common methods used to deliver precise dosing of compounds to the stomach of research animals. Unfortunately, this method comes with difficulties for both the operator and the research animal. Studies have shown that OG may lead to complications, including esophagitis, perforation of the esophagus, and inadvertent tracheal drug administration. In addition, OG is associated with increased plasma and fecal corticosterone levels (due to stress), altered blood pressure, and increased heart rate, which could negatively influence or bias study results. A previously developed alternative method termed micropipette-guided drug administration (MDA) incentivizes the animal to consume treatments readily in a minimally invasive manner. Herein, we present examples of the use of the MDA technique with treatments reconstituted in different vehicles and demonstrate effective delivery of the varied treatments to multiple different mouse strains. We further demonstrate that MDA is a technique that decreases the timing and invasiveness of drug administration and does not affect the gut microbiome composition as assessed by quantitative analysis of core gut microbial species. Overall, MDA may offer a less stressful and effective alternative to OG.

Here, we describe micropipette-guided drug administration (MDA) as an alternative method to oral gavage that incentivizes the research animal to ingest treatments readily with minimal stress and discomfort.

Oral gavage (OG) with the use of a cannula attached to a syringe is one of the most common methods used to deliver precise dosing of compounds to the ...

Cancer Research

A Protocol to Characterize the Morphological Changes of Clostridium difficile in Response to Antibiotic Treatment

Assessment of antibiotic action with new drug development directed towards anaerobic bacteria is difficult and technically demanding. To gain insight into possible MOA, morphologic changes associated with antibiotic exposure can be visualized using scanning electron microscopy (SEM). Integrating SEM imaging with traditional kill curves may improve our insight into drug action and advance the drug development process. To test this premise, kill curves and SEM studies were conducted using drugs with known but different MOA (vancomycin and metronidazole). C. difficile cells (R20291) were grown with or without the presence of antibiotic for up to 48 h. Throughout the 48 h interval, cells were collected at multiple time points to determine antibiotic efficacy and for imaging on the SEM. Consistent with previous reports, vancomycin and metronidazole had significant bactericidal activity following 24 h of treatment as measured by colony-forming unit (CFU) counting. Using SEM imaging we determined that metronidazole had significant effects on cell length (&#62; 50% reduction in cell length for each antibiotic; P&#60; 0.05) compared to controls and vancomycin. While the phenotypic response to drug treatment has not been documented previously in this manner, they are consistent with the drug&#39;s MOA demonstrating the versatility and reliability of the imaging and measurements and the application of this technique for other experimental compounds.

A Protocol to Characterize the Morphological Changes of Clostridium difficile in Response to Antibiotic Treatment

Antibiotic efficacy is most commonly determined by conducting killing kinetic studies and measuring colony forming units (CFUs). By integrating scanning electron microscopy (SEM) with these standard methods, we can distinguish the pharmacological effects of treatment between different antibiotics.

Assessment of antibiotic action with new drug development directed towards anaerobic bacteria is difficult and technically demanding. To gain insight into ...

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota

The emerging role of the gut microbiome in several human diseases demands a breakthrough of new tools, techniques and technologies. Such improvements are needed to decipher the utilization of microbiome modulators for human health benefits. However, the large-scale screening and optimization of modulators to validate microbiome modulation and predict related health benefits may be practically difficult due to the need for large number of animals and/or human subjects. To this end, in vitro or ex vivo models can facilitate preliminary screening of microbiome modulators. Herein, it is optimized and demonstrated an ex vivo fecal microbiota culture system that can be used for examining the effects of various interventions of gut microbiome modulators including probiotics, prebiotics and other food ingredients, aside from nutraceuticals and drugs, on the diversity and composition of the human gut microbiota. Inulin, one of the most widely studied prebiotic compounds and microbiome modulators, is used as an example here to examine its effect on the healthy fecal microbiota composition and its metabolic activities, such as fecal pH and the fecal levels of organic acids including lactate and short-chain fatty acids (SCFAs). The protocol may be useful for studies aimed at estimating the effects of different interventions of modulators on fecal microbiota profiles and at predicting their health impacts.

This protocol describes an in vitro batch-culture fermentation system of human fecal microbiota, using inulin (a well-known prebiotic and one of the most widely studied microbiota modulators) to demonstrate the use of this system in estimating effects of specific interventions on fecal microbiota composition and metabolic activities.

The emerging role of the gut microbiome in several human diseases demands a breakthrough of new tools, techniques and technologies. Such improvements are ...

Analysis of Interactions between Endobiotics and Human Gut Microbiota Using In Vitro Bath Fermentation Systems

Human intestinal microorganisms have recently become an important target of research in promoting human health and preventing diseases. Consequently, investigations of interactions between endobiotics (e.g., drugs and prebiotics) and gut microbiota have become an important research topic. However, in vivo experiments with human volunteers are not ideal for such studies due to bioethics and economic constraints. As a result, animal models have been used to evaluate these interactions in vivo. Nevertheless, animal model studies are still limited by bioethics considerations, in addition to differing compositions and diversities of microbiota in animals vs. humans. An alternative research strategy is the use of batch fermentation experiments that allow evaluation of the interactions between endobiotics and gut microbiota in vitro. To evaluate this strategy, bifidobacterial (Bif) exopolysaccharides (EPS) were used as a representative xenobiotic. Then, the interactions between Bif EPS and human gut microbiota were investigated using several methods such as thin-layer chromatography (TLC), bacterial community compositional analysis with 16S rRNA gene high-throughput sequencing, and gas chromatography of short-chain fatty acids (SCFAs). Presented here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems. Importantly, this protocol can also be modified to investigate general interactions between other endobiotics and gut microbiota.

Described here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems.

Human intestinal microorganisms have recently become an important target of research in promoting human health and preventing diseases. Consequently, ...

Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging

Measuring the localization of microbes within their in vivo context is an essential step in revealing the functional relationships between the microbiota and the vertebrate gut. The spatial landscape of the gut microbiota is tightly controlled by physical features - intestinal mucus, crypts, and folds - and is affected by host-controlled properties such as pH, oxygen availability, and immune factors. These properties limit the ability of commensal microbes and pathogens alike to colonize the gut stably. At the micron-scale, microbial organization determines the close-range interactions between different microbes as well as the interactions between microbes and their host. These interactions then affect large-scale organ function and host health.
This protocol enables the visualization of the gut microbiota spatial organization from distances between cells to organ-wide scales. The method is based on fixing gut tissues while preserving intestinal structure and mucus properties. The fixed samples are then embedded, sectioned, and stained to highlight specific bacterial species through fluorescence in situ hybridization (FISH). Host features, such as mucus and host cell components, are labeled with fluorescently labeled lectins. Finally, the stained sections are imaged using a confocal microscope utilizing tile-scan imaging at high magnification to bridge the micron to centimeter length scales. This type of imaging can be applied to intestinal sections from animal models and biopsies from human tissues to determine the biogeography of the microbiota in the gut in health and disease.

Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging

This streamlined protocol details a workflow to detect and image bacteria in complex tissue samples, from fixing the tissue to staining microbes with fluorescent in situ hybridization.

Measuring the localization of microbes within their in vivo context is an essential step in revealing the functional relationships between the microbiota ...

Analysis of Fecal Microbiota Dynamics in Lupus-Prone Mice Using a Simple, Cost-Effective DNA Isolation Method

Gut microbiota has an important role in educating the immune system. This relationship is extremely important for understanding autoimmune diseases that are not only driven by genetic factors, but also environmental factors that can trigger the onset and/or worsen the disease course. A previously published study on the dynamics of the gut microbiota in lupus-prone MRL/lpr female mice showed how changes of the gut microbiota can alter disease progression. Here, a protocol is described for extracting representative samples from the gut microbiota for studies of autoimmunity. Microbiota samples are collected from the anus and processed, from which the DNA is extracted using a phenol-chloroform method and purified by alcohol precipitation. After PCR is performed, purified amplicons are sequenced using a Next Generation Sequencing platform at Argonne National Laboratory. Finally, the 16S ribosomal RNA gene sequencing data is analyzed. As an example, data obtained from gut microbiota comparisons of MRL/lpr mice with or without CX3CR1 are shown. Results showed significant differences in genera containing pathogenic bacteria such as those in the phylum Proteobacteria, as well as the genus Bifidobacterium, which is considered part of the healthy commensal microbiota. In summary, this simple, cost-effective DNA isolation method is reliable and can help the investigation of gut microbiota changes associated with autoimmune diseases.

This protocol provides a simple, cost-effective DNA isolation method for the analysis of murine gut microbiota alterations during the development of autoimmune disease.

Gut microbiota has an important role in educating the immune system. This relationship is extremely important for understanding autoimmune diseases that ...

A Method to Assess Bacteriocin Effects on the Gut Microbiota of Mice

Very intriguing questions arise with our advancing knowledge on gut microbiota composition and the relationship with health, particularly relating to the factors that contribute to maintaining the population balance. However, there are limited available methodologies to evaluate these factors. Bacteriocins are antimicrobial peptides produced by many bacteria that may confer a competitive advantage for food acquisition and/or niche establishment. Many probiotic lactic acid bacteria (LAB) strains have great potential to promote human and animal health by preventing the growth of pathogens. They can also be used for immuno-modulation, as they produce bacteriocins. However, the antagonistic activity of bacteriocins is normally determined by laboratory bioassays under well-defined but over-simplified conditions compared to the complex gut environment in humans and animals, where bacteria face multifactorial influences from the host and hundreds of microbial species sharing the same niche. This work describes a complete and efficient procedure to assess the effect of a variety of bacteriocins with different target specificities in a murine system. Changes in the microbiota composition during the bacteriocin treatment are monitored using compositional 16S rDNA sequencing. Our approach uses both the bacteriocin producers and their isogenic non-bacteriocin-producing mutants, the latter giving the ability to distinguish bacteriocin-related from non-bacteriocin-related modifications of the microbiota. The fecal DNA extraction and 16S rDNA sequencing methods are consistent and, together with the bioinformatics, constitute a powerful procedure to find faint changes in the bacterial profiles and to establish correlations, in terms of cholesterol and triglyceride concentration, between bacterial populations and health markers. Our protocol is generic and can thus be used to study other compounds or nutrients with the potential to alter the host microbiota composition, either when studying toxicity or beneficial effects.

Bacteriocins are believed to play a key role in defining microbial diversity in different ecological niches. Here, we describe an efficient procedure to assess how bacteriocins affect gut microbiota composition in an animal model.

Very intriguing questions arise with our advancing knowledge on gut microbiota composition and the relationship with health, particularly relating to the ...

Biology

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome&#8217;s role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Described here is a simplified standard operating procedure for microbiome profiling using 16S rRNA metagenomic sequencing and analysis using freely available tools. This protocol will help researchers who are new to the microbiome field as well as those requiring updates on methods to achieve bacterial profiling at a higher resolution.

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the ...

Fecal Microbiota Transplantation and Detection of Prevalence of IgA-Coated Bacteria in the Gut

Gut microbiota exert pleiotropic roles in human health and disease. Fecal microbiota transplantation (FMT) is an effective method to investigate the biological function of intestinal bacteria as a whole or at the species level. Several different FMT methods have been published. Here, we present an FMT protocol that successfully depletes gut microbiota in a matter of days, followed by transplantation of fecal microbiota from fresh or frozen donor intestinal contents to conventional mice. Real time-PCR is applied to test the efficacy of bacterial depletion. Sequencing of the 16S ribosomal RNA (rRNA) is then applied to test the relative abundance and identity of gut microbiota in recipient mice. We also present a flow cytometry-based detection method of immunoglobulin A (IgA)-coated bacteria in the gut.

We established an efficient way to deplete intestinal bacteria in three days, and subsequently transplant fecal microbiota via gavage of fecal fluid prepared from fresh or frozen intestinal contents in mice. We also present an optimized method to detect the frequency of IgA-coated bacteria in the gut.

Gut microbiota exert pleiotropic roles in human health and disease. Fecal microbiota transplantation (FMT) is an effective method to investigate the ...

Specimen Collection and Analysis of the Duodenal Microbiome

Shifts in the microbiome have been correlated with the physiology and pathophysiology of many organ systems both in humans and in mouse models. The gut microbiome has been typically studied through fecal specimen collections. The ease of obtaining fecal samples has resulted in many studies that have revealed information concerning the distal luminal gastrointestinal tract. However, few studies have addressed the importance of the microbiome in the proximal gut. Given that the duodenum is a major site for digestion and absorption, its microbiome is relevant to nutrition and liver disease and warrants further investigation. Here we detail a novel method for sampling the proximal luminal and mucosal gut microbiome in human subjects undergoing upper endoscopy by obtaining duodenal aspirate and biopsies. Specimen procurement is facile and unaffected by artifacts such as patient preparatory adherence, as might be the case in obtaining colonic samples during colonoscopy. The preliminary results show that the luminal and mucosal microbiomes differ significantly, which is likely related to environmental conditions and barrier functions. Therefore, a combination of duodenal aspirate and biopsies reveal a more comprehensive picture of the microbiome in the duodenum. Biopsies are obtained from the descending and horizontal segments of the duodenum, which are anatomically close to the liver and biliary tree. This is important in studying the role of bile acid biology and the gut-liver axis in liver disease. Biopsies and aspirate can be used for 16S ribosomal RNA sequencing, metabolomics, and other similar applications.

In this manuscript, we discuss a novel method to sample and analyze the duodenal microbiome. This method provides an accurate depiction of microbial diversity and composition in the duodenum and could be useful for further investigation of the duodenal microbiome.

Shifts in the microbiome have been correlated with the physiology and pathophysiology of many organ systems both in humans and in mouse models. The gut ...

Quantitative Polymerase Chain Reaction-based Analyses of Murine Intestinal Microbiota After Oral Antibiotic Treatment

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Use of Micropipette-Guided Drug Administration as an Alternative Method to Oral Gavage in Rodent Models

A Protocol to Characterize the Morphological Changes of Clostridium difficile in Response to Antibiotic Treatment

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota

Analysis of Interactions between Endobiotics and Human Gut Microbiota Using In Vitro Bath Fermentation Systems

Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging

Analysis of Fecal Microbiota Dynamics in Lupus-Prone Mice Using a Simple, Cost-Effective DNA Isolation Method

A Method to Assess Bacteriocin Effects on the Gut Microbiota of Mice

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Fecal Microbiota Transplantation and Detection of Prevalence of IgA-Coated Bacteria in the Gut

Specimen Collection and Analysis of the Duodenal Microbiome