ברצוננו להודות Helty Adisetiyo, PhD, Shangxin יאנג, PhD לפיתוח של הפרוטוקול. הכוללת תמיכה עבור הבינלאומי אימהי בילדים מתבגרים איידס קליניים ניסויים קבוצה (IMPAACT) סופק על ידי המכון הלאומי לאלרגיה ומחלות זיהומיות (NIAID) של במכון הלאומי של בריאות (NIH) תחת מספרי פרס UM1AI068632 (IMPAACT LOC), UM1AI068616 (IMPAACT SDMC), UM1AI106716 (IMPAACT LC), עם השתתפות במימון המכון הלאומי יוניס קנדי שרייבר של ובריאות הילד והתפתחות האדם (NICHD), את נבחרת המכון לבריאות הנפש (NIMH). התוכן הוא אך ורק באחריות המחברים, ואינם מייצגים בהכרח את הנופים הרשמי של NIH.

<ol>
	<li>Ahern, P. P., Faith, J. J., Gordon, J. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mining+the+human+gut+microbiota+for+effector+strains+that+shape+the+immune+system.">Mining the human gut microbiota for effector strains that shape the immune system.</a> Immunity. 40 (6), 815-823 (2014).</li><li>Postler, T. S., Ghosh, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Understanding+the+Holobiont:+How+Microbial+Metabolites+Affect+Human+Health+and+Shape+the+Immune+System.">Understanding the Holobiont: How Microbial Metabolites Affect Human Health and Shape the Immune System.</a> Cell Metab. , (2017).</li><li>Hall, M. 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=Inter-personal+diversity+and+temporal+dynamics+of+dental,+tongue,+and+salivary+microbiota+in+the+healthy+oral+cavity.">Inter-personal diversity and temporal dynamics of dental, tongue, and salivary microbiota in the healthy oral cavity.</a> NPJ Biofilms Microbiomes. 3, 2 (2017).</li><li>Perez Perez, G. I., 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=Body+Site+Is+a+More+Determinant+Factor+than+Human+Population+Diversity+in+the+Healthy+Skin+Microbiome.">Body Site Is a More Determinant Factor than Human Population Diversity in the Healthy Skin Microbiome.</a> PLoS One. 11 (4), e0151990 (2016).</li><li>Hamady, M., Knight, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbial+community+profiling+for+human+microbiome+projects:+Tools,+techniques,+and+challenges.">Microbial community profiling for human microbiome projects: Tools, techniques, and challenges.</a> Genome Res. 19 (7), 1141-1152 (2009).</li><li>Human Microbiome Project, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+framework+for+human+microbiome+research.">A framework for human microbiome research.</a> Nature. 486 (7402), 215-221 (2012).</li><li>Kim, 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=Optimizing+methods+and+dodging+pitfalls+in+microbiome+research.">Optimizing methods and dodging pitfalls in microbiome research.</a> Microbiome. 5 (1), 52 (2017).</li><li>Hugerth, L. W., Andersson, A. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysing+Microbial+Community+Composition+through+Amplicon+Sequencing:+From+Sampling+to+Hypothesis+Testing.">Analysing Microbial Community Composition through Amplicon Sequencing: From Sampling to Hypothesis Testing.</a> Front Microbiol. 8, 1561 (2017).</li><li>Caporaso, J. G., 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=Ultra-high-throughput+microbial+community+analysis+on+the+Illumina+HiSeq+and+MiSeq+platforms.">Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms.</a> ISME J. 6 (8), 1621-1624 (2012).</li><li>Pannaraj, P. 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=Association+Between+Breast+Milk+Bacterial+Communities+and+Establishment+and+Development+of+the+Infant+Gut+Microbiome.">Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome.</a> JAMA Pediatr. , (2017).</li><li>Ho, F. C., Wong, R. L., Lawton, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+colostral+and+breast+milk+cells.+A+light+and+electron+microscopic+study.">Human colostral and breast milk cells. A light and electron microscopic study.</a> Acta Paediatr Scand. 68 (3), 389-396 (1979).</li><li>Parmely, M. J., Beer, A. E., Billingham, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+studies+on+the+T-lymphocyte+population+of+human+milk.">In vitro studies on the T-lymphocyte population of human milk.</a> J Exp Med. 144 (2), 358-370 (1976).</li><li>Sabbaj, 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=Human+immunodeficiency+virus-specific+CD8(+)+T+cells+in+human+breast+milk.">Human immunodeficiency virus-specific CD8(+) T cells in human breast milk.</a> J Virol. 76 (15), 7365-7373 (2002).</li><li>Jimenez, E., 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+Analysis+of+Milk+of+Healthy+and+Mastitis-Suffering+Women.">Metagenomic Analysis of Milk of Healthy and Mastitis-Suffering Women.</a> J Hum Lact. 31 (3), 406-415 (2015).</li><li>Ghosh, M. 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>

המחברים אין לחשוף.

רצף יישוב הדור הבא של מטוסי אף-16 rRNA היא טכניקה בשימוש נרחב, מהיר microbiome אפיון18. עם זאת, גורמים רבים, כולל אפקטים אצווה, זיהום סביבתי, זיהום, לדוגמה, רגישות הפארמצבטית יכול להשפיע לרעה להשפיע על תוצאות הניסוי, וחיסול7,שלהם פרשנות19 , 20<...

הקהילות אותן מיקרוביאלי לישוב בני האדם מאמינים כי חשובה ביותר לבריאות האדם ומחלות המשפיעים על חילוף החומרים, פיתוח המערכת החיסונית, נטייה למחלות, תגובות חיסון התרופות, טיפול1, 2. מאמצים כדי להבין את השפעת microbiota על בריאות האדם כיום מדגישים את הזיהוי של מיקרובים המשויכות מוגדרים תאים אנטומיים (כלומר, עור, בטן, אוראלי, וכו '), כמו גם אתרי מקומי בתוך אלה3,תאים4. המאמצים האלה החקירות לגורם המרכזי עליו מושתתת היא התפתחותה המהירה של נגישות מוגברת של טכנולוגיות הדור הבא רצפי (הגדרות) המספקים פלטפורמה בנפט במקביל לניתוח של התוכן הגנטי מיקרוביאלית (microbiome) של מדגם. לדוגמאות פיזיולוגיים רבים, microbiome המשויך הוא מורכב וגם בשפע (קרי, צואה), אבל עבור כמה דוגמאות, microbiome מיוצג על-ידי ביומסה מיקרוביאלית נמוך (כלומר, חלב, מערכת הנשימה התחתונה) שבו רגישות, חפצי אמנות ניסויית, זיהום אפשרי להפוך את הנושאים העיקריים. האתגרים המשותפים של microbiome לימודי עיצוב ניסיוני המתאים כבר הנושא של מספר סקירת מאמרים5,6,7,8.
שהוצגו במסמך זה צינור ניסיוני חזק המיתרים מבוסס על רצף יישוב של rRNA 16 שכבת ביטול v4 של אזור9 כדי לאפיין את microbiome של חלב. ניתוח Microbiome של חלב אינו מורכב רק על ידי נמוך מטבעו ביומסה מיקרוביאלית של10, אך בנוסף על ידי גבוהה רמות של דנ א אנושי רקע11,12,13,14 ו דחויים פוטנציאלי של PCR מעכבי15,16 בחומצות שחולצו. פרוטוקול זה מסתמך על ערכות חילוץ זמינים מסחרית, פלטפורמות חצי אוטומטיים כדי לסייע במזעור השתנות לאורך אצוות הכנת המדגם. הוא כולל קהילה מדומה חיידקי מוגדרים היטב, שמעובד לצד דוגמאות כמו בקרת איכות כדי לאמת כל שלב בפרוטוקול ולספק מדד עצמאית של צינור חוסן. אמנם הפרוטוקול כפי שתואר ספיציפית דגימות חלב, ניתנת להתאמה בקלות סוגים אחרים דוגמת כולל צואה, בפי הטבעת, בנרתיק, עור, מטליות מונטגומרי, אוראלי10,17, והוא יכול לשמש נקודת מוצא חוקרים המעוניינים לבצע ניתוח microbiome.

<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

מחקרים של קהילות מיקרוביאלי הפכו נרחבת עם הפיתוח של רצפי התפוקה יחסית זול, מהיר וגבוה. עם זאת, כמו עם כל הטכנולוגיות הללו, תוצאות לשחזור תלויות שזרימת עבודה במעבדה משלבת אמצעי הזהירות המתאימים ופקדים. דבר זה חשוב במיוחד עם דגימות נמוך-ביומסה איפה לזיהום חיידקי ה-DNA ניתן להפיק תוצאות מטעות. מאמר זה מפרט זרימת עבודה אוטומטית למחצה כדי לזהות חיידקים מדגימות חלב בשד האנושי באמצעות רצף יישוב של אזור V4 ribosomal RNA (rRNA) 16 בסולם נמוך - עד אמצע - throughput. הפרוטוקול מתאר הכנת הדוגמא של חלב מלא כולל: לטעום פירוק, חילוץ חומצת גרעין, הגברה של אזור V4 של מטוסי אף-16 rRNA ג'ין, וכן ספריית הכנה עם אמצעי בקרה. חשוב, הפרוטוקול ואת הדיון לשקול סוגיות שאינן בולטות הכנה, ניתוח דוגמאות נמוך-ביומסה לרבות הפקדים המתאימים חיוביים ושליליים, הסרת המעכב PCR, דוגמת זיהום על ידי הסביבה, מגיב, או מקורות ניסיוני, ושיטות עבודה מומלצות ניסיוני, שנועדו להבטיח הפארמצבטית. בעוד הפרוטוקול כפי שמתואר ספיציפית דגימות חלב, זה יכולת הסתגלות רבים סוגי דגימה ביומסה נמוכה ולא גבוהה, כולל דוגמאות שנאספו על דגימות, קפוא מסודר, או התייצב במאגר שימור.

פרוטוקול המוצג כאן כולל שלבים חשובים בקרת איכות (QC) כדי להבטיח כי הפגישה נתונים שנוצרו ובחינות עבור פרוטוקול בקרת רגישות, ירידה לפרטים, זיהום. הצעד הראשון של הפרוטוקול QC בעקבות PCR הגברה של אזור V4 16 (איור 2). µL אחד של מוצר ה-PCR של כל מדגם נותחה על ידי אלקטרופורז...

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

זרימת עבודה אוטומטית למחצה מוצג עבור רצף יישוב של rRNA מטוסי אף-16 מ חלב וסוגים אחרים של הדגימה נמוך-ביומסה.

שיטה של מטוסי אף-16 יישוב רצף של דגימות חלב

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. זרימת עבודה אוטומטית למחצה מוצג עבור רצף יישוב של rRNA מטוסי אף-16 מ חלב וסוגים אחרים של הדגימה נמוך-ביומסה.

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.

ניתוח של האדם Fucosylated Trisaccharides חלב בהקשר ביוטכנולוגי באמצעות גנטית מקודד ביולוגיים

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.

זיהוי של חיידקים פתוגנים נדירים לפי 16S rRNA ג&#39;ין סידור MALDI-TOF MS

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.

רצף של הדור הבא של 16S ריבוזומלי amplicons ג&#39;ין RNA

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.

טיהור הלא טהור: Metagenomes הרצף וMetatranscriptomes מדוגמאות הקשורים בבעלי חיים מורכבות

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.

הפקת חומצות גרעין יעיל 16S rRNA ג&#39;ין רצף עבור בקטריאלי קהילת אפיון

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.

שיטה להעריך אפקטים Bacteriocin על מיקרוביוטה המעיים של עכברים

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.

פרוטוקול מודרך לקבלת צואה אפיון חיידקים על ידי מטוסי אף-16 rRNA-אמפליקון רצף

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;

ניתוח קוואזי-metagenomic של סלמונלה מזון, סביבתית דגימות

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.

אנליזה microbiota באמצעות שני שלבים PCR ו-הדור הבא של 16 rRNA גן רצף

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

<meta charset="utf8"></head><body>שחזור מיקרוביוטה של חלב תורם מפוסטר באמצעות חלב אם

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.

<meta charset="utf8"></head><body>בנייה מחדש אישית של מיקרוביוטה של חלב אם: גישה ישימה בסביבות בעולם האמיתי

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.

בנייה מחדש אישית של מיקרוביוטה של חלב אם: גישה ישימה בסביבות בעולם האמיתי

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 ...

שיטה של מטוסי אף-16 יישוב רצף של דגימות חלב

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