We would like to thank Helty Adisetiyo, PhD and Shangxin Yang, PhD for the development of the protocol.Overall support for the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT) was provided by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health (NIH) under Award Numbers UM1AI068632 (IMPAACT LOC), UM1AI068616 (IMPAACT SDMC) and UM1AI106716 (IMPAACT LC), with co-funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute of Mental Health (NIMH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

For all protocol steps, proper personal protective equipment (PPE) must be worn, and stringent contamination prevention approaches need to be taken. Observe flow of work from pre-amplification work areas to post-amplification work areas to minimize contamination of samples. All supplies used are sterile, free of RNase, DNase, DNA, and pyrogen. All pipette tips are filtered. A flowchart of the protocol steps is provided (Figure 1).
1. Sample Lysis
NOTE: Sample lysis and nucleic acid extraction are performed using a DNA/RNA extraction kit in a clean-room environment where both engineering and procedural controls are in place to minimize the introduction of environmental bacteria to the samples.
<ol>
	<li>Work area preparation
	<ol>
		<li>Clean the biosafety cabinet (BSC) work area with appropriate surface cleaner to eliminate any nucleic acid contamination.</li>
		<li>Turn on the temperature-controlled vortexer, and set it to 37 &#176;C.</li>
	</ol>
	</li>
	<li>Prepare guanidinium thiocyanate lysis buffer (see Table of Materials)
	<ol>
		<li>Check the lysis buffer for precipitates. Re-dissolve precipitates by warming at 37 &#176;C.</li>
		<li>Prepare 600 &#181;L of lysis buffer with 6 &#181;L &#946;-mercaptoethanol (&#946;-ME) for each sample. Consider an extra 20% volume per sample.</li>
	</ol>
	</li>
	<li>Sample preparation
	<ol>
		<li>If whole milk is frozen, thaw it on ice. Aliquot 5 mL of whole milk into a 15-mL or a 5-mL sterile tube in BSC and keep it on ice.</li>
		<li>Spin the 5-mL milk aliquot for 10 min at 5,000 x g at 4 &#176;C to pellet cells.</li>
		<li>Remove the fat layer, now the top layer in the tube, with a plastic spatula or large bore pipette tip.</li>
		<li>Without disturbing the pellet, remove all the supernatant except for 100 &#181;L.</li>
		<li>Wash the pellet by resuspending in 1 mL of sterile phosphate buffered saline (PBS).</li>
		<li>Prepare 1 negative control by adding 1 mL of sterile PBS to a 5-mL tube.</li>
		<li>Transfer the suspension to a clean 1.5-mL centrifuge tube, and spin in a microcentrifuge for 1 min (5,000 x g at room temperature (RT)).</li>
		<li>Use a 1,000 &#181;L sterile filtered pipette tip to discard the entire supernatant/fatty layer.</li>
		<li>If not extracting the same day, snap freeze the cell pellet by putting it in an ethanol/dry ice slurry, and immediately transfer it to the -80 &#176;C freezer.</li>
	</ol>
	</li>
	<li>Sample disruption and homogenization (bead-beating)
	<ol>
		<li>Add 600 &#181;L of lysis buffer containing &#946;-ME to the pellet, and transfer the suspension to a bead tube.</li>
		<li>Each extraction batch of 12 contains 10 samples, 1 negative control (prepared in step 3.7 above), and 1 positive control (prepared in the next step).
		<ol>
			<li>Prepare 1 positive control with lysis buffer and 20 &#181;L of the bacterial mock sample (the mock community used has a concentration, once extracted, of approximately 0.2 ng/&#181;L of DNA).</li>
		</ol>
		</li>
		<li>Vortex all bead tubes vigorously for 15 s.</li>
		<li>Heat samples on the temperature-controlled vortexer at 37 &#176;C for 10 min, with shaking at 700 -&#160;800 rpm.</li>
		<li>Load tubes into the automated sample disruptor adapter set.</li>
		<li>Bead beat for 1 min at 30 Hz.</li>
		<li>Disassemble the adaptor set and manually switch the adaptor set with the sample plates from the left robotic arm to the right robotic arm of the instrument.</li>
		<li>Bead beat for another 1 min at 30 Hz.</li>
		<li>Centrifuge tubes at 17,200 x g, for 3 min at 25 &#176;C.</li>
		<li>Remove all of the supernatant with a 200 &#181;L pipette, being careful not to get any of the fatty layer at the top of the sample or the bead residual at the bottom of the sample, and apply to a homogenizer column.</li>
		<li>Centrifuge homogenizer columns at maximum speed, 17,200 x g, for 3 min at 25 &#176;C.</li>
		<li>Transfer 350 &#181;L of eluate to a 2-mL manufacturer&#39;s microcentrifuge tube for use with the automated instrument for purification of DNA and RNA (do not use any other tube). Be careful not to transfer any residual fatty layer.</li>
		<li>If the flow-through volume is less than 350 &#181;L, add lysis buffer with &#946;-ME to a final volume of 350 &#181;L.</li>
		<li>Leave the samples at RT for up to 2 h before proceeding to nucleic acid isolation using the automated DNA purification instrument, or freeze at -80 &#176;C.</li>
	</ol>
	</li>
	<li>Cleaning work area
	<ol>
		<li>Clean all surfaces in use with a non-enzymatic decontamination solution, leave for 10 min, then spray with 70% ethanol and wipe down the surface.</li>
	</ol>
	</li>
</ol>
2. Isolate DNA/RNA
<ol>
	<li>Work area preparation
	<ol>
		<li>Turn on the heat block and set the temperature to 70 &#176;C.</li>
		<li>Turn on the temperature-controlled vortexer and set the temperature to 37 &#176;C.</li>
		<li>Warm up the elution buffer (EB) containing 10 mM Tris-Cl, pH 8.5, in a 50-mL tube to 70 &#176;C.</li>
		<li>Warm up 350 &#181;L of frozen sample lysates in 2 mL tubes at 37 &#176;C until completely thawed without any precipitate (approximately 10 min).</li>
	</ol>
	</li>
	<li>DNA purification
	<ol>
		<li>Vortex and centrifuge the 2-mL tubes with sample briefly (3000 x g for 10 s).</li>
		<li>Insert 2 mL tubes into the shaker following the automated DNA/RNA purification instrument&#39;s loading chart, per the manufacturer&#39;s instructions.</li>
		<li>Get the rotor adaptors and set them up on the tray based on the number of samples.</li>
		<li>Label each rotor adaptor based on the sample&#39;s identification (ID).</li>
		<li>Cut off the lids and smooth the edges of individual spin columns for DNA and RNA.</li>
		<li>Insert the DNA spin column without the collection tube into the rotor adaptor. Discard the collection tube.</li>
		<li>Label 1.5 mL collection tubes, and insert into rotor adaptors.</li>
		<li>Set rotor adaptors into the centrifuge following the automated DNA/RNA purification instrument&#39;s loading chart.</li>
		<li>Insert manufacturer&#39;s 1,000 &#181;L filter-tips into tip racks.</li>
		<li>Add RNase-free water to a 2-mL manufacturer&#39;s microcentrifuge tube based on the number of samples (per specific machine protocol instructions).</li>
		<li>Insert the tube into tube slot &#34;A&#34; of microcentrifuge tube slots.</li>
		<li>Discard any reagent that is left over in reagent bottles and fill with a minimum volume of 10 mL.</li>
		<li>Insert reagent bottles into the reagent bottle rack (except EB bottle).</li>
		<li>Add warm EB from a 50-mL tube to the reagent bottle position 6.</li>
		<li>Check 1.5 mL tubes are placed tightly in the rotor adaptors.</li>
		<li>Close the instrument&#39;s lid and select: &#34;RNA&#34;&#8594; &#34;extraction kit&#34; &#8594; &#34;Animal, tissues and cells&#34; &#8594; &#34;kit&#39;s name 350 &#181;L Part A Custom DNA&#34; &#8594; Edit Elution Volume to 100 &#181;L (default) or 50 &#181;L for low biomass samples &#8594; &#34;Start.&#34;</li>
		<li>When complete, remove rotor adaptors out of the centrifuge and place them on the tray.</li>
		<li>Discard the DNA spin column from rotor adaptor position 3.</li>
		<li>Do NOT discard rotor adaptors, RNA is in position 2.</li>
		<li>Remove 1.5 mL collection tubes containing eluted DNA at position 3, and store in &#8722;20 &#176;C.</li>
		<li>Collect sample-containing tubes from the shaker and store in &#8722;20 &#176;C, if any sample is left over, otherwise discard.</li>
		<li>Continue with the protocol &#34;kit&#39;s name 350 &#181;L part B RNA&#34; for further purification of RNA.</li>
		<li>RNA purification will be done from the approximately 350 &#181;L flow-through that is in the middle position of the rotor adaptors.</li>
	</ol>
	</li>
	<li>RNA purification
	<ol>
		<li>Insert the RNA spin column without its collection tube and lid into the rotor adaptor.</li>
		<li>Label new 1.5 mL collection tubes and insert them into rotor adaptor as indicated in the manual.</li>
		<li>Set the rotor adaptors into the centrifuge following the automated DNA/RNA purification instrument&#39;s loading chart.</li>
		<li>Close the instrument&#39;s lid and select: &#34;RNA&#34; &#8594; &#34;Manufacturer&#39;s Kit&#34; &#8594; &#34;Animal, tissues and cells&#34; &#8594; &#34;Standard Part B RNA&#34; &#8594; &#34;Start.&#34;</li>
		<li>When completed, remove rotor adaptors out of the centrifuge and place them on the tray.</li>
		<li>Discard RNA spin column from position 3.</li>
		<li>Remove 1.5 mL collection tubes containing 30 &#181;L eluted RNA at position 3, and store at &#8722;80 &#176;C.</li>
		<li>Remove reagent bottles.</li>
		<li>Dispose of rotor adaptor contents through appropriate hazardous waste channels.</li>
	</ol>
	</li>
	<li>Clean work station
	<ol>
		<li>Spray all the automated DNA/RNA purification instrument&#39;s accessories, such as reagent racks, tray, and any other surface in use with a non-enzymatic decontamination solution, leave for 10 min and rinse with deionized (DI) water, then let them dry.</li>
		<li>Spray the automated instrument with only manufacturer approved non-enzymatic decontamination solution, wipe the inside of the centrifuge along with all surfaces in use, leave for 10 min, and then wipe with 70% ethanol. Do not use other types of decontamination solutions as they can damage the instrument.</li>
	</ol>
	</li>
</ol>
3. Targeted 16S PCR Set-up
NOTE: The set-up for the 16S PCR is carried out in a designated pre-amplification workspace located within the clean-room. The reagents and samples are prepared and then loaded onto a liquid handler to perform the PCR for each sample in triplicate (30 samples, which include true samples and extraction positive and negative controls, plus 2 PCR water controls in triplicate, for a total of 96 combined samples and controls). Once the PCR reactions are assembled and sealed, the sample plate is transferred to a thermal cycler located in a post-amplification area for cycling.
<ol>
	<li>Work area preparation
	<ol>
		<li>Clean the PCR workstation. Spray all surfaces in use with an RNase, DNase, DNA decontaminant, followed by DI water two times, and finally 70% ethanol.</li>
		<li>Prepare the 16S PCR Worksheet (see Targeted 16S PCR Worksheet) with an accurate sample list, and assign different barcoded primers to each sample9. Print out the worksheet and the plate maps (see Plate 1).</li>
	</ol>
	</li>
	<li>PCR master mix preparation 
	NOTE: 16S primer selection is based on the region of interest for the particular study, and may change by study or sample type. Therefore, before ordering primers, it is important to confirm what area of the 16S rRNA best amplifies the microbes of interest for the particular study. This protocol as written is for amplification of the 16S V4 region. If different primers/region are selected, then the annealing temperature in the thermal cycling may require adjustment.
	<ol>
		<li>Work in the PCR workstation to prepare everything.</li>
		<li>Take out 50 - 100 &#181;L of DNA samples from -20 &#176;C, and all the reagents needed, and thaw them on ice. Vortex and briefly spin down.</li>
		<li>The primers are pre-diluted to the working concentration of 5 &#181;M in a minimum volume of 20 &#181;L.</li>
		<li>Prepare the PCR master mix in the specific 5 mL tube with only the forward primer according to the calculation on the worksheet.</li>
	</ol>
	</li>
	<li>Preparing the robotic liquid handler for automated PCR setup
	<ol>
		<li>For samples, take out a 32-well instrument&#39;s sample adaptor, and load 50 - 100 &#181;L of DNA samples according to the 96-well plate map according to the manufacturer&#39;s instructions.
		<ol>
			<li>For each PCR plate, set up 2 negative controls by placing 30 &#181;L of PCR water in a clean sample tube.</li>
			<li>Place all the samples on the 32-well instrument&#39;s sample adaptor with caps locked in open position.</li>
		</ol>
		</li>
		<li>For reverse primers9
		<ol>
			<li>Remove the cap of each reverse primer with specific barcode #&#39;s one at a time (change gloves in between to avoid cross-contamination).</li>
			<li>Place a maximum of 32 primers on the instrument&#39;s reagent adaptor.</li>
		</ol>
		</li>
		<li>Take out a 96-well PCR plate and label it with study name, sample number, date, and the technician&#39;s initials.</li>
		<li>Loading the robotic liquid handler
		<ol>
			<li>Place the reagent adaptor in position B1. In order to avoid an edge effect, carefully place one edge of the adaptor against the grip side, and slowly bring the other edge down. Make sure to push on all the corners of the adaptors.</li>
			<li>Place the sample adaptor in Position C1. Make sure to push on all the corners of the adaptors.</li>
			<li>Vortex the 5-mL master mix, open the cap, and place it in position A on the instrument&#39;s master mix and reagent block.</li>
			<li>Place the PCR plate on the 96-well instrument&#39;s adaptor that is intended to hold half skirted PCR plates.</li>
			<li>Start the run and save as a new file.</li>
			<li>Follow the prompts and check mark each prompt: one, tips are available, two, waste box is available, and three, start.</li>
		</ol>
		</li>
		<li>After the run is complete, verify there were no errors by checking the machine for error messages.</li>
		<li>Seal the plate with the 12 or 8 strip caps, vortex vigorously, and spin down for 1 min using a 96-well plate spinner, and place it on ice or in the refrigerator.</li>
		<li>Remove tubes containing reverse primers and samples.</li>
		<li>Take the 96-well plate to the post-amplification room and load the plate onto the thermal cycler and cycle according to the table of thermal-cycling conditions (see Table 1).</li>
	</ol>
	</li>
</ol>
4. Targeted 16S Post-PCR Quality Control Using Tape-based Platform for Gel Electrophoresis
NOTE: Post-PCR quality control (QC) and all subsequent steps are carried out in a designated post-amplification area of the lab. The DNA is analyzed in an automated DNA/RNA fragment analyzer.
<ol>
	<li>Work area preparation
	<ol>
		<li>Clean the workstation by spraying all surfaces in use with an RNase, DNase, DNA decontaminant, followed by DI water two times, and finally 70% ethanol.</li>
		<li>Gather all supplies and equipment needed.</li>
	</ol>
	</li>
	<li>Prepare reagents
	<ol>
		<li>Place sample buffer and ladder in the temperature-controlled vortexer at 25 &#176;C for a minimum of 30 min.</li>
	</ol>
	</li>
	<li>While the reagents are warming up, prepare PCR samples by pooling the 3 PCR replicates for each sample into a single tube</li>
	<li>Load samples on instrument.</li>
	<li>Briefly vortex and spin down tubes with pooled PCR product.</li>
	<li>Place the instrument&#39;s 96-well plate on a rack at RT and label it.</li>
	<li>Briefly vortex and spin down the sample buffer and ladder.</li>
	<li>Add 3 &#181;L sample buffer to each well of the 96 well plate (need at least 53 &#181;L/screen tape).</li>
	<li>Run an even number of samples; if there is odd number of samples, add 4 &#181;L of sample buffer to an empty well.</li>
	<li>Add 1 &#181;L of ladder to a ladder well.</li>
	<li>Following the map, add 1 &#181;L of pooled PCR product to its designated well.</li>
	<li>Cover plate with foil seal</li>
	<li>Vortex the plate using the instrument&#39;s vortexer and adaptor at 2,000 rpm for 1 min.</li>
	<li>Spin down to position the sample at the bottom of the tube, if there are bubbles spin down again.</li>
	<li>Launch the software.</li>
	<li>Load the screen tape and loading tips into the instrument.</li>
	<li>Load samples into the fragment analyzer with a 96-well adaptor.</li>
	<li>Set up a run with the controller software.</li>
	<li>Make sure to select even numbered wells.</li>
	<li>Write sample IDs.</li>
	<li>Check that all the wells of the screen tape are highlighted in gray.</li>
	<li>Make sure the analyzer recognizes all the pipette tips.</li>
	<li>Select start and specify a filename to save the results (study name, sample numbers, and date).</li>
	<li>Refer to the manufacturer&#39;s instruction for more details.</li>
	<li>After the run is complete, discard tip, screen tape, and tubes.</li>
	<li>Analyze data for 16S peak nM (between 315 - 450 bp for V4). This peak will vary depending on the primers selected.</li>
</ol>
5. Library Calculation, Pooling, Clean-up, and QC
<ol>
	<li>After determining amplicon size and molarity of all samples, pool the libraries to achieve the final desired volume and nM for the pooled library (see Sample Calculation).</li>
	<li>Clean-up and concentrate the pooled library using a silica-membrane-based purification kit for PCR products, according to the manufacturer&#39;s protocol (see Table of Materials).
	<ol>
		<li>Elute the DNA with a final volume of 50 &#181;L.</li>
	</ol>
	</li>
	<li>Measure the concentration of the cleaned library immediately by using a double stranded DNA high sensitivity kit for a fluorometer, according to the manufacturer&#39;s protocol.
	<ol>
		<li>Dilute 2 &#181;L of the pooled and cleaned library with 198 &#181;L of the dilution buffer plus dye (1:100 dilution).</li>
		<li>Record the measured value from the fluorometric device and convert it according to the dilution factor.</li>
	</ol>
	</li>
	<li>Using the concentration reading (ng/&#181;L) for the pooled library, calculate the library molarity in nM. Use 1 &#181;L undiluted library to measure the OD260/280 on a microvolume spectrophotometer. 
	NOTE: A value of 1.8 - 2.0 indicates adequate purity of the library.</li>
	<li>Store the final library at -20 &#176;C until ready for next generation sequencing.</li>
</ol>

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K., 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=Quantitation+of+human+immunodeficiency+virus+type+1+in+breast+milk.">Quantitation of human immunodeficiency virus type 1 in breast milk.</a> J Clin Microbiol. 41 (6), 2465-2470 (2003).</li><li>Lim, N. Y., Roco, C. A., Frostegard, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transparent+DNA/RNA+Co-extraction+Workflow+Protocol+Suitable+for+Inhibitor-Rich+Environmental+Samples+That+Focuses+on+Complete+DNA+Removal+for+Transcriptomic+Analyses.">Transparent DNA/RNA Co-extraction Workflow Protocol Suitable for Inhibitor-Rich Environmental Samples That Focuses on Complete DNA Removal for Transcriptomic Analyses.</a> Front Microbiol. 7, 1588 (2016).</li><li>Bender, J. M., 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=Maternal+HIV+infection+influences+the+microbiome+of+HIV-uninfected+infants.">Maternal HIV infection influences the microbiome of HIV-uninfected infants.</a> Sci Transl Med. 8 (349), 349ra100 (2016).</li><li>Cox, M. J., Cookson, W. O., Moffatt, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequencing+the+human+microbiome+in+health+and+disease.">Sequencing the human microbiome in health and disease.</a> Hum Mol Genet. 22 (R1), R88-R94 (2013).</li><li>Lauder, A. P., 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=Comparison+of+placenta+samples+with+contamination+controls+does+not+provide+evidence+for+a+distinct+placenta+microbiota.">Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota.</a> Microbiome. 4 (1), 29 (2016).</li><li>Salter, S. 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=Reagent+and+laboratory+contamination+can+critically+impact+sequence-based+microbiome+analyses.">Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.</a> BMC Biol. 12, 87 (2014).</li><li>Walker, A. 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=16S+rRNA+gene-based+profiling+of+the+human+infant+gut+microbiota+is+strongly+influenced+by+sample+processing+and+PCR+primer+choice.">16S rRNA gene-based profiling of the human infant gut microbiota is strongly influenced by sample processing and PCR primer choice.</a> Microbiome. 3, 26 (2015).</li><li>Glassing, A., Dowd, S. E., Galandiuk, S., Davis, B., Chiodini, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inherent+bacterial+DNA+contamination+of+extraction+and+sequencing+reagents+may+affect+interpretation+of+microbiota+in+low+bacterial+biomass+samples.">Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples.</a> Gut Pathog. 8, 24 (2016).</li><li>Kennedy, K., Hall, M. W., Lynch, M. D., Moreno-Hagelsieb, G., Neufeld, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluating+bias+of+illumina-based+bacterial+16S+rRNA+gene+profiles.">Evaluating bias of illumina-based bacterial 16S rRNA gene profiles.</a> Appl Environ Microbiol. 80 (18), 5717-5722 (2014).</li><li>Weiss, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracking+down+the+sources+of+experimental+contamination+in+microbiome+studies.">Tracking down the sources of experimental contamination in microbiome studies.</a> Genome Biol. 15 (12), 564 (2014).</li><li>Aho, V. T., 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=The+microbiome+of+the+human+lower+airways:+a+next+generation+sequencing+perspective.">The microbiome of the human lower airways: a next generation sequencing perspective.</a> World Allergy Organ J. 8 (1), 23 (2015).</li><li>Charlson, E. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Topographical+continuity+of+bacterial+populations+in+the+healthy+human+respiratory+tract.">Topographical continuity of bacterial populations in the healthy human respiratory tract.</a> Am J Respir Crit Care Med. 184 (8), 957-963 (2011).</li><li>Bittinger, K., 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=Improved+characterization+of+medically+relevant+fungi+in+the+human+respiratory+tract+using+next-generation+sequencing.">Improved characterization of medically relevant fungi in the human respiratory tract using next-generation sequencing.</a> Genome Biol. 15 (10), 487 (2014).</li><li>Jervis-Bardy, 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=Deriving+accurate+microbiota+profiles+from+human+samples+with+low+bacterial+content+through+post-sequencing+processing+of+Illumina+MiSeq+data.">Deriving accurate microbiota profiles from human samples with low bacterial content through post-sequencing processing of Illumina MiSeq data.</a> Microbiome. 3, 19 (2015).</li><li>Knights, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bayesian+community-wide+culture-independent+microbial+source+tracking.">Bayesian community-wide culture-independent microbial source tracking.</a> Nat Methods. 8 (9), 761-763 (2011).</li><li>Lazarevic, V., Gaia, N., Girard, M., Schrenzel, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Decontamination+of+16S+rRNA+gene+amplicon+sequence+datasets+based+on+bacterial+load+assessment+by+qPCR.">Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR.</a> BMC Microbiol. 16, 73 (2016).</li><li>Kurilshikov, A., Wijmenga, C., Fu, J., Zhernakova, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Host+Genetics+and+Gut+Microbiome:+Challenges+and+Perspectives.">Host Genetics and Gut Microbiome: Challenges and Perspectives.</a> Trends Immunol. 38 (9), 633-647 (2017).</li><li>. Mock microbial communities Available from: <a target="_blank" href="https://www.atcc.org/en/Products/Microbiome_Standards.aspx?utm_id=t170601524l1">https://www.atcc.org/en/Products/Microbiome_Standards.aspx?utm_id=t170601524l1</a> (2017)</li></ol>

The authors have nothing to disclose.

Targeted next-generation sequencing of 16S rRNA is a widely used, rapid technique for microbiome characterization18. However, many factors, including batch effects, environmental contamination, sample cross-contamination, sensitivity, and reproducibility can adversely affect experimental results and confound their interpretation7,19,20. To best facilitate robust 16S analyses, microbiome workflows must inc...

The microbial communities that colonize humans are believed to be critically important to human health and disease influencing metabolism, immune development, susceptibility to disease, and responses to vaccination and drug therapy1,2. Efforts to understand the influence of the microbiota on human health currently emphasize the identification of microbes associated with defined anatomic compartments (i.e., skin, gut, oral, etc.), as well as localized sites within these compartments3,4. Underpinning these investigative efforts is the rapid emergence and increased accessibility of next-generation sequencing (NGS) technologies that provide a massively parallel platform for analysis of the microbial genetic content (microbiome) of a sample. For many physiological samples, the associated microbiome is both complex and abundant (i.e., stool), but, for some samples, the microbiome is represented by low microbial biomass (i.e., human milk, lower respiratory tract) where sensitivity, experimental artefacts, and possible contamination become major issues. The common challenges of microbiome studies and appropriate experimental design have been the subject of multiple review articles5,6,7,8.
Presented herein is a robust NGS experimental pipeline based on targeted sequencing of the rRNA 16S V4 region9 to characterize the microbiome of human milk. Microbiome analysis of human milk is complicated not only by an inherently low microbial biomass10, but additionally by high levels of human DNA background11,12,13,14 and potential carryover of PCR inhibitors15,16 in extracted nucleic acid. This protocol relies on commercially available extraction kits and semi-automated platforms that can help minimize variability across sample preparation batches. It incorporates a well-defined bacterial mock community that is processed alongside samples as a quality control to validate each step in the protocol and provide an independent metric of pipeline robustness. Although the protocol as described is specific to the human milk samples, it is readily adaptable to other sample types including stool, rectal, vaginal, skin, areolar, and oral swabs10,17, and can serve as a starting point for researchers who wish to perform microbiome analyses.

<table><tbody><tr><td>AllPrep RNA/DNA Mini Kit</td><td>Qiagen</td><td>80204</td><td>DNA/RNA extraction kit</td></tr><tr><td>Eliminase</td><td>Fisher Scientific</td><td>435532</td><td>RNase, DNase, DNA decontaminant</td></tr><tr><td>Thermo Mixer</td><td>Fisher Scientific</td><td></td><td>temperature-controlled vortexer</td></tr><tr><td>Buffer RLT plus</td><td>Qiagen</td><td>1053393</td><td>guanidinium thiocyanate lysis buffer/ Part of Allprep kit</td></tr><tr><td>&amp;szlig;-Mercaptoethanol</td><td>Sigma Aldrich</td><td>63689-25ML-F</td><td>&amp;szlig;-ME is a reducing agent that will irreversibly denature RNases by reducing disulfide bonds</td></tr><tr><td>LME Beads</td><td>MP Biomedicals</td><td>116914050</td><td>bead tube</td></tr><tr><td>QIAgen TissueLyzer</td><td>Qiagen</td><td>85300</td><td>automated sample disruptor adapter set</td></tr><tr><td>QIAshredder column</td><td>Qiagen</td><td>79654</td><td></td></tr><tr><td>QIAgen RB tube</td><td></td><td></td><td>manufacturer&#039;s microcentrifuge tube in kit</td></tr><tr><td>QIAcube and related plasticware</td><td>Qiagen</td><td>9001292</td><td>automated DNA/RNA purification instrument</td></tr><tr><td>DNA exitus plus</td><td>Applichem</td><td>A7089</td><td>non-enzymatic decontamination solution</td></tr><tr><td>EB Buffer</td><td>Qiagen</td><td>19086</td><td>elution buffer</td></tr><tr><td>QIAgility and related plasticware</td><td>Qiagen</td><td>9001532</td><td>robotic liquid handler</td></tr><tr><td>PCR water</td><td>MO BIO</td><td>17000-</td><td></td></tr><tr><td>5PRIME HotMasterMix</td><td>Quantabio</td><td>2200400</td><td></td></tr><tr><td>Barcoded reverse primers</td><td>Eurofin</td><td>No Catalog #&#039;s</td><td>designed and ordered</td></tr><tr><td>96 well PCR plate</td><td>USA scientific</td><td>1402-9708</td><td></td></tr><tr><td>Tapestation 2200 and related plasticware</td><td>Agilent</td><td>G2964AA</td><td>automated DNA/RNA fragment analyzer</td></tr><tr><td>D1000 reagents for Tapestation</td><td>Agilent</td><td>5067-5585</td><td>Sample buffer and ladder are part of this kit</td></tr><tr><td>OneStep PCR Inhibitor Removal Kit</td><td>Zymo Research</td><td>50444470</td><td>PCR inhibitor removal is done per the manufacturer&#039;s instructions.</td></tr><tr><td>QIAquick PCR Purification Kit</td><td>Qiagen</td><td>28104</td><td>DNA clean up kit: silica-membrane-based purification of PCR products</td></tr><tr><td>Qubit dsDNA HS Assay Kit</td><td>Thermo Fisher</td><td>Q32854</td><td>dimethylsulfoxide-based dilution buffer and dye are part of this kit.</td></tr><tr><td>Qubit Fluorometer</td><td>Thermo Fisher</td><td>Q33216</td><td></td></tr><tr><td>NanoDrop</td><td>Thermo Fisher</td><td></td><td>microvolume spectrophotometer</td></tr><tr><td>MiSeq 300 V2 kit</td><td>Illumina</td><td>15033624/15033626</td><td></td></tr><tr><td>MiSeq</td><td>Illumina</td><td>No Catalog #&#039;s</td><td>next generation sequencer</td></tr></tbody></table>

a method for targeted 16s sequencing of human milk samples

Studies of microbial communities have become widespread with the development of relatively inexpensive, rapid, and high throughput sequencing. However, as with all these technologies, reproducible results depend on a laboratory workflow that incorporates appropriate precautions and controls. This is particularly important with low-biomass samples where contaminating bacterial DNA can generate misleading results. This article details a semi-automated workflow to identify microbes from human breast milk samples using targeted sequencing of the 16S ribosomal RNA (rRNA) V4 region on a low- to mid-throughput scale. The protocol describes sample preparation from whole milk including: sample lysis, nucleic acid extraction, amplification of the V4 region of the 16S rRNA gene, and library preparation with quality control measures. Importantly, the protocol and discussion consider issues that are salient to the preparation and analysis of low-biomass samples including appropriate positive and negative controls, PCR inhibitor removal, sample contamination by environmental, reagent, or experimental sources, and experimental best practices designed to ensure reproducibility. While the protocol as described is specific to human milk samples, it is adaptable to numerous low- and high-biomass sample types, including samples collected on swabs, frozen neat, or stabilized in a preservation buffer.

The protocol presented here includes important quality control (QC) steps to ensure that the data generated meet benchmarks for protocol sensitivity, specificity, and contamination control. The protocol&#39;s first QC step follows PCR amplification of the 16S V4 region (Figure 2). One &#181;L of PCR product from each sample was analyzed by electrophoresis to confirm that it was within the expected size range of 315 - 450 bp (Figure 2</str...

Watch this Scientific Journal Video about A Method for Targeted 16S Sequencing of Human Milk Samples at JoVE.com

A Method for Targeted 16S Sequencing of Human Milk Samples

A semi-automated workflow is presented for targeted sequencing of 16S rRNA from human milk and other low-biomass sample types.

Studies of microbial communities have become widespread with the development of relatively inexpensive, rapid, and high throughput sequencing. However, as ...

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Research

JoVE Journal

Immunology and Infection

9.8K Views.  University of California at Los Angeles. Een semi-geautomatiseerde workflow wordt gepresenteerd voor gerichte sequentiebepaling van het 16S rRNA van menselijke melk en andersoortige laag-biomassa monster.

Video: A Method for Targeted 16S Sequencing of Human Milk Samples

Analysis of Fucosylated Human Milk Trisaccharides in Biotechnological Context Using Genetically Encoded Biosensors

Human milk oligosaccharides (HMOs) are complex carbohydrate components of human breast milk that exhibit plentiful benefits on infant health. However, optimization of their biotechnological synthesis is limited by the relatively low throughput of detection and quantification of monosaccharide and linkages. Conventional techniques of glycan analysis include chromatographic/mass-spectrometric methods with throughput on the order of hundreds of samples per day without automation. We demonstrate here, a genetically encoded bacterial biosensor for the high-throughput, linkage-specific detection and quantification of the fucosylated HMO structures, 2&#8217;-fucosyllactose and 3-fucosyllactose, which we achieved via heterologous expression of fucosidases. As the presence of lactose in milk or in biotechnological processes could lead to false positives, we also demonstrate the reduction of signal from lactose using different strategies. Due to the high throughput of this technique, many reaction conditions or bioreactor parameters could be assayed in parallel in a matter of hours, allowing for the optimization of HMO manufacturing.

We describe here the high-throughput detection and quantification of fucosylated human milk oligosaccharides (HMOs) using a whole-cell biosensor. We also demonstrate here, the adaptation of this platform towards analysis of HMO production strains, focusing on improving the signal to noise ratio.

Human milk oligosaccharides (HMOs) are complex carbohydrate components of human breast milk that exhibit plentiful benefits on infant health. However, ...

Biochemistry

Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS

There are a number of rare and, therefore, insufficiently described bacterial pathogens which are reported to cause severe infections especially in immunocompromised patients. In most cases only few data, mostly published as case reports, are available which investigate the role of such pathogens as an infectious agent. Therefore, in order to clarify the pathogenic character of such microorganisms, it is necessary to conduct epidemiologic studies which include large numbers of these bacteria. The methods used in such a surveillance study have to meet the following criteria: the identification of the strains has to be accurate according to the valid nomenclature, they should be easy to handle (robustness), economical in routine diagnostics and they have to generate comparable results among different laboratories. Generally, there are three strategies for identifying bacterial strains in a routine setting: 1) phenotypic identification characterizing the biochemical and metabolic properties of the bacteria, 2) molecular techniques such as 16S rRNA gene sequencing and 3) mass spectrometry as a novel proteome based approach. Since mass spectrometry and molecular approaches are the most promising tools for identifying a large variety of bacterial species, these two methods are described. Advances, limitations and potential problems when using these techniques are discussed.

Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and molecular techniques (16S rRNA gene sequencing) permit the identification of rare bacterial pathogens in routine diagnostics. The goal of this protocol lies in the combination of both techniques which leads to more accurate and reliable data.

There are a number of rare and, therefore, insufficiently described bacterial pathogens which are reported to cause severe infections especially in ...

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.

Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the ...

Biology

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.

Using the cystic fibrosis airway as an example, the manuscript presents a comprehensive workflow comprising a combination of metagenomic and metatranscriptomic approaches to characterize the microbial and viral communities in animal-associated samples.

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and ...

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

There is a growing appreciation for the role of microbial communities as critical modulators of human health and disease. High throughput sequencing technologies have allowed for the rapid and efficient characterization of bacterial communities using 16S rRNA gene sequencing from a variety of sources. Although readily available tools for 16S rRNA sequence analysis have standardized computational workflows, sample processing for DNA extraction remains a continued source of variability across studies. Here we describe an efficient, robust, and cost effective method for extracting nucleic acid from swabs. We also delineate downstream methods for 16S rRNA gene sequencing, including generation of sequencing libraries, data quality control, and sequence analysis. The workflow can accommodate multiple samples types, including stool and swabs collected from a variety of anatomical locations and host species. Additionally, recovered DNA and RNA can be separated and used for other applications, including whole genome sequencing or RNA-seq. The method described allows for a common processing approach for multiple sample types and accommodates downstream analysis of genomic, metagenomic and transcriptional information.

We describe an efficient, robust, and cost effective method for extracting nucleic acid from swabs for characterization of bacterial communities using 16S rRNA gene amplicon sequencing. The method allows for a common processing approach for multiple sample types and accommodates a number of downstream analytic processes.

There is a growing appreciation for the role of microbial communities as critical modulators of human health and disease. High throughput sequencing ...

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 ...

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

The human intestinal microbiome plays a central role in protecting cells from injury, in processing energy and nutrients, and in promoting immunity. Deviations from what is considered a healthy microbiota composition (dysbiosis) may impair vital functions leading to pathologic conditions. Recent and ongoing research efforts have been directed toward the characterization of associations between microbial composition and human health and disease.
Advances in high-throughput sequencing technologies enable characterization of the gut microbial composition. These methods include 16S rRNA-amplicon sequencing and shotgun sequencing. 16S rRNA-amplicon sequencing is used to profile taxonomical composition, while shotgun sequencing provides additional information about gene predictions and functional annotation. An advantage in using a targeted sequencing method of the 16S rRNA gene variable region is its substantially lower cost compared to shotgun sequencing. Sequence differences in the 16S rRNA gene are used as a microbial fingerprint to identify and quantify different taxa within an individual sample.
Major international efforts have enlisted standards for 16S rRNA-amplicon sequencing. However, several studies report a common source of variation caused by batch effect. To minimize this effect, uniformed protocols for sample collection, processing, and sequencing must be implemented. This protocol proposes the integration of broadly used protocols starting from fecal sample collection to data analyses. This protocol includes a column-free, direct-PCR approach that enables simultaneous handling and DNA extraction of large numbers of fecal samples, along with PCR amplification of the V4 region. In addition, the protocol describes the analysis pipeline and provides a script using the latest version of QIIME (QIIME 2 version 2017.7.0 and DADA2). This step-by-step protocol is aimed to guide those interested in initiating the use of 16S rRNA-amplicon sequencing in a robust, reproductive, easy to use, detailed way.

This manuscript describes a detailed standardized protocol of high-throughput 16S rRNA-amplicon sequencing. The protocol introduces an integrated, uniformed, feasible, and inexpensive protocol starting from fecal sample collection through data analyses. This protocol enables analysis of large numbers of samples with rigorous standards and several controls.

The human intestinal microbiome plays a central role in protecting cells from injury, in processing energy and nutrients, and in promoting immunity. ...

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Quasi-metagenomics sequencing refers to the sequencing-based analysis of modified microbiomes of food and environmental samples. In this protocol, microbiome modification is designed to concentrate genomic DNA of a target foodborne pathogen contaminant to facilitate the detection and subtyping of the pathogen in a single workflow. Here, we explain and demonstrate the sample preparation steps for the quasi-metagenomics analysis of Salmonella enterica from representative food and environmental samples including alfalfa sprouts, ground black pepper, ground beef, chicken breast and environmental swabs. Samples are first subjected to the culture enrichment of Salmonella for a shortened and adjustable duration (4&#8211;24 h). Salmonella cells are then selectively captured from the enrichment culture by immunomagnetic separation (IMS). Finally, multiple displacement amplification (MDA) is performed to amplify DNA from IMS-captured cells. The DNA output of this protocol can be sequenced by high throughput sequencing platforms. An optional quantitative PCR analysis can be performed to replace sequencing for Salmonella detection or assess the concentration of Salmonella DNA before sequencing.

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Here, we present a protocol to prepare DNA samples from food and environmental microbiomes for concerted detection and subtyping of Salmonella through quasimetagenomic sequencing. The combined use of culture enrichment, immunomagnetic separation (IMS), and multiple displacement amplification (MDA) allows effective concentration of Salmonella genomic DNA from food and environmental samples.&#160;

Quasi-metagenomics sequencing refers to the sequencing-based analysis of modified microbiomes of food and environmental samples. In this protocol, ...

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 ...

Restoring Pasteurized Donor Milk Microbiota Using Mother's Own Milk

Individualized Reconstitution of Human Milk Microbiota: A Feasible Approach in Real-World Settings

Mother&#39;s own milk (MOM) is the most complete nutritional resource for newborns. In cases where mothers are unable to produce sufficient milk or cannot breastfeed, the preferred alternative is pasteurized donor human milk (PDM), which is routinely provided by human milk banks. PDM offers a superior range of nutritional and immunological elements compared to any commercially available formula. However, to ensure biosafety, PDM undergoes pasteurization, a process that inactivates commensal microbiota and reduces certain bioactive compounds. This study presents a protocol designed to restore the microbiota of PDM using MOM as a microbial source, adapting the approach to a real-world clinical setting.
The protocol was implemented in a clinical trial conducted at a maternity hospital and its associated human milk bank, with the aim of providing personalized donor milk to preterm infants whose mothers cannot produce sufficient milk. The methodology involves inoculating PDM with 10% of MOM, followed by incubation at 37 &#176;C for 4 h. Microbiological analysis demonstrated successful bacterial growth in the inoculated milk (IM) post incubation, with the microbiota profile of the reconstituted milk (RM) closely resembling that of MOM, indicating effective microbiota restoration. These results suggest that the reconstitution protocol is feasible for implementation in neonatal care, with the potential to enhance the nutritional and immunological quality of PDM, thereby supporting the health and development of non-breastfed newborns.

The article describes a protocol for reconstituting pasteurized donor milk microbiota using the mother's own milk microbiota in practical, real-world settings. It demonstrates effective bacterial growth and microbiome modulation, supporting the feasible application of this procedure within the routine care of a maternity hospital and its associated human milk bank.

Mother&#39;s own milk (MOM) is the most complete nutritional resource for newborns. In cases where mothers are unable to produce sufficient milk or cannot ...

A Method for Targeted 16S Sequencing of Human Milk Samples

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