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Microbiome Identification to Characterization: Pathogen Detection Webinar Series: Part 3
This document discusses the development of rapid detection methods for microbial and microbiome analysis and their applications to human health. It provides an overview of QIAGEN's microbial qPCR products and discusses focused metagenomics applications like screening for antibiotic resistance genes in the food supply and human gut. Limitations of current methods are outlined and the benefits of qPCR for rapid, specific, and sensitive microbial detection are described.
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Microbiome Identification to Characterization: Pathogen Detection Webinar Series: Part 3
- 1. Sample to Insight Developmentof Rapid Detection Methods for Microbial and Microbiome Analysis and Applications to Human Health Christine Davis Christine.Davis@QIAGEN.com 1
- 2. Sample to Insight Legaldisclaimer Microbial Identification 2 • QIAGEN products shown here are intended for molecular biology applications. These products are not intended for the diagnosis, prevention or treatment of a disease. • For up-to-date licensing information and product-specific disclaimers, see the respective QIAGEN kit handbook or user manual. QIAGEN kit handbooks and user manuals are available at www.QIAGEN.com or can be requested from QIAGEN Technical Services or your local distributor.
- 3. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 3 1 2 3 4 5 6
- 4. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 4 1 2 3 4 5 6
- 5. Sample to Insight Humansor superorganisms? Cellular composition of the organism Human Microbiota Estimations of the number of microbial cells that live in and on the human body, human cells are outnumbered by a factor of 10. Nomenclature: Microbiota are the microbes that live in a specific location, e.g. the human body, the gut, soil, etc. Metagenomics is the study of the collection of genomes derived from a specific sample or community. Microbes are microscopic organisms that can be either single or multicellular. Microbial Identification 5
- 6. Sample to Insight Microorganismscluster by body site Cataloguing efforts by the NIH Human microbiome project suggest: • ~10,000 organisms live with us • ~ 8 ×106 genes in this “second genome” Identifying microbiota in healthy individuals revealed: • Different body sites have unique communities • Race, Age, Gender, Weight or Ethnicity have an effect Microbial Identification 6
- 7. Sample to Insight Complexityand function of genomic content Function of microbiome enables individual survival • Each organism has developed genetic content for its own survival in a specific environment • Metabolism tuned to local nutrient sources • Virulence factors for stable colonization • Antibiotic resistance genes to metabolize toxins Microbial Identification 7
- 8. Sample to Insight Physiologicalassociations lead to new funding NIH funding across institutes for microbiome - related studies 2008 2013 Microbial Identification 8
- 9. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 9 1 2 3 4 5 6
- 10. Sample to Insight Currentmethods for microbial analysis • Culture • Gene cloning (Pan 16S rRNA) and sanger sequencing • Microarray • Next generation sequencing • 16S rRNA sequencing • Whole genome sequencing • MALDI • qPCR - Target dependent • 16S rRNA gene • Other relevant gene (antibiotic resistance gene, virulence factor gene) Microbial Identification 10
- 11. Sample to Insight Limitationsof current pathogen detection methods • Time consuming • (Involve multiple steps, 5-7 days) • Can not identify all pathogens • Majority are non-culturable • Culture conditions are different • Require extensive microbiological training and expertise • Varying protocols for identification • Waste generation Microbial Identification 11
- 12. Sample to Insight NGSfor whole genome sequencing and 16s rRNA sequencing • Technical challenges • Higher costs • Not amenable to routine testing at this time • Complex data output • 2 days workflow • Good for discovery at strain and genus level microbiome research Sample Prep Assay Data Sequence- Level Statistics Biology of Interest Annotation & Comparative Analysis Annotation & Biological Interpretation Limitations of current pathogen detection methods Microbial Identification 12
- 13. Sample to Insight Specific •Only detects target sequence Sensitive • Can detect low copy numbers • High inhibitor tolerance Rapid • Easy to set up • Detection in under 3 hours Standardized • Automated protocols • Stable chemical design Benefits of real-time PCR for detection of microorganisms Microbial Identification 13
- 14. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 14 1 2 3 4 5 6
- 15. Sample to Insight 16SrRNA gene as a phylogenetic marker for bacterial ID Sequencing or real-time PCR (qPCR) • Classification from the variable sequences • 16s rRNA sequence similarity • 95% genus level, 97% species level, 99% strain level • Assay design approach • Use only sequences with taxonomy classified by the GreenGenes taxonomy • Fairly specific probe + fairly specific primer pair = specific assay (requires hydrolysis probe) Microbial Identification 15
- 16. Sample to Insight Performancetesting of each assay Dilution series testing for PCR efficiency and sensitivity Microbial Identification 16
- 17. Sample to Insight Determinesensitivity of a microbial assay • LOD, limit of detection, is the lowest amount of analyte (DNA molecule) in a sample that is able to be distinguished from a sample that contains no analyte • Often reported as colony forming units • LLOQ, lower limit of quantitation, is the lowest amount of analyte that can be distinguished from a sample with another amount of analyte • Often reported as gene copies, since colonies may contain multiple copies of a gene • LLOQ is especially useful for quantitation because it states the limit at which two samples can be quantified as opposed to simple qualification Microbial Identification 17
- 18. Sample to Insight Specificityof microbial DNA qPCR assays • To determine the specificity, each assay was tested against 119 genomic DNA from different bacteria and fungi • To facilitate testing, genomic DNA from different microbial species were pooled (pools of 10 different genomic DNA or one single pool of 119 genomic DNA ) and each assay was tested against the different pools • Each pool did not contain DNA from the same genus to facilitate the identification of any cross-reacting species • Each pool contained equivalent to 2000 genome copies for each microbial species. In addition, each assay was tested against human, mouse and rat genomic DNA • Specificity also determined in silico 22 24 26 28 30 32 34 36 38 40 1 2 3 4 5 6 7 8 9 10 11 CT Pool Staph/Strep complete Campylobacter spp. 1 Assay Microbial Identification 18
- 19. Sample to Insight GenomicDNA pools for specificity testing • Complete pool contains all genomic DNA for each species listed Pool1 Pool2 Pool3 Pool4 Acinetobacter baumannii Aeromonas hydrophila Alcaligenes faecalis subsp. Faecalis Aspergillus fumigatus Bacillus licheniformis Bartonella henselae Bordetella pertussis Brevundimonas diminuta Campylobacter jejuni subsp. Jejuni Candida albicans Candida glabrata Candida parapsilosis Citrobacter freundii Clostridium difficile Clostridium perfringens Clostridium thermocellum Corynebacterium glutamicum Enterobacter aerogenes Enterococcus faecalis Enterococcus faecium Fusobacterium nucleatum subsp. Nucleatum Geobacillus stearothermophilus Haemophilus influenzae Helicobacter pylori Legionella pneumophila subsp. Pneumophila Listeria monocytogenes Mycobacterium tuberculosis Neisseria meningitidis Pantoea agglomerans Pediococcus pentosaceus Plesiomonas shigelloides Proteus mirabilis Rahnella aquatilis Ralstonia solanacearum Salmonella enterica subsp. enterica serovar Paratyphi A Serratia marcescens Vibrio cholerae Yersinia enterocolitica subsp. Enterocolitica Yersinia pestis Stenotrophomonas maltophilia Pool5 Pool6 Pool7 Pool8 Bacillus cereus Aggregatibacter actinomycetemcomitans Akkermansia muciniphila Anaerococcus prevotii Burkholderia cenocepacia Bacteroides thetaiotaomicron Bacteroides ureolyticus Bacteroides vulgatus Candida tropicalis Burkholderia cepacia Campylobacter coli Campylobacter concisus Corynebacterium diphtheriae Capnocytophaga gingivalis Cryptobacterium curtum Cryptococcus gattii Escherichia coli Enterobacter cloacae subsp. Cloacae Gardnerella vaginalis Lactobacillus jensenii Klebsiella pneumoniae Lactobacillus casei Lactobacillus gasseri Micrococcus luteus Ochrobactrum anthropi Methanobrevibacter smithii Mycoplasma pneumoniae Neisseria flava Pseudomonas aeruginosa Mycoplasma orale Porphyromonas gingivalis Prevotella intermedia Shigella flexneri Porphyromonas endodontalis Trichomonas vaginalis Ureaplasma parvum Yersinia pseudotuberculosis Treponema denticola Staphylococcus haemolyticus Streptococcus mitis Pool9 Pool10 Pool11 Staph/strep pool Aspergillus flavus Atopobium rimae Bacillus subtilis Staphylococcus aureus Bifidobacterium breve Bifidobacterium longum subsp. Infantis Bordetella parapertussis Staphylococcus epidermidis Campylobacter gracilis Campylobacter rectus Campylobacter upsaliensis Streptococcus agalactiae Cryptococcus neoformans Desulfovibrio desulfuricans Lactobacillus acidophilus Streptococcus gordonii Haemophilus ducreyi Klebsiella oxytoca Leptotrichia buccalis Streptococcus mitis Lactobacillus plantarum Lactobacillus reuteri Mycoplasma hominis Streptococcus mutans Mycobacterium smegmatis Mycoplasma genitalium Peptostreptococcus anaerobius Streptococcus pneumoniae Neisseria gonorrhoeae Parabacteroides distasonis Tannerella forsythia Streptococcus pyogenes Prevotella melaninogenica Proteus vulgaris Vibrio parahaemolyticus Streptococcus sanguinis Veillonella parvula Vibrio harvey Streptococcus agalactiae Microbial Identification 19
- 20. Sample to Insight Assayperformance in a metagenomic background Spike-in experiments test for specificity in a complex background Microbial Identification 20
- 21. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 21 1 2 3 4 5 6
- 22. Sample to Insight Focusedmetagenomics applications Screening for microbial genes in metagenomic samples Antibiotic resistance genes – from food to man Examples from the next wave of microbiome experiments Respiratory virus co-infection Relationships between microorganisms that permit colonization Profile changes in vaginal flora during bacterial vaginosis Microbial Identification 22
- 23. Sample to Insight Antibioticresistance 23,00 0 death s can be preve nted if.... Antibi otic- resist ant genes : how can we contr ol Antibi otic- resist ant bacte ria’s sicke n two millio n peopl e and 23,00 0 succu mb to it. Can we preve nt these death s? Yes we can. In Marc h of 2015, the nation al action plan for comb ating antibi otic- resist ant bacte ria was devel oped to comb at resist ance. One of the action plans was to impro ve surve illanc e capab ilities. Learn more about The Natio nal Actio n Plan 23,000 deaths can be prevented if.... Antibiotic-resistant genes: how can we control…… • CDC estimates: causes sickness in 2 million people and 23,000 deaths per year • March 2015, Obama Administration Releases National Action Plan to Combat Antibiotic-Resistant Bacteria • June 2 2015, Washington the National Cattlemen’s Beef Association participated in the White House Forum on Antibiotic Stewardship Microbial Identification 23
- 24. Sample to Insight Antibioticresistance genes in our food supply? Microbial Identification 24 • One potential source of acquiring antibiotic resistance genes is through the food-supply • Both livestock and feed may acquire antibiotic resistant bacteria through different mechanisms • Food can be exposed to antibiotic resistant bacteria through fertilizer originating from waste-water treatment plants. This, in addition to increasing administration of antibiotics to livestock can lead to food as being a potential source of antibiotic resistant genes • This may then lead to horizontal gene transfer to pathogenic enteropathogens leading to drug resistance in humans, therefore highlighting the importance of surveillance and prevention of antibiotic resistant genes in food
- 25. Sample to Insight Antibioticresistance gene reservoirs in the body Screening of the gut for presence of antibiotic resistance genes ErmB, mefA, and tetA were found in all or most of the stool samples tested, suggesting a common source. These antibiotic resistance genes have been reported to be isolated from bacterial strains originating from food, suggesting a possible source of origin. Microbial Identification 25
- 26. Sample to Insight Antibioticresistance genes in our food supply? Microbial Identification 26
- 27. Sample to Insight Presenceof antibiotic resistance genes in the food supply Species/gene Antibiotic classification / virulence factor gene description Also detects Sensitivity NTC QC check beef chicken pork carrot lettuce potato aadA1 Aminoglycoside- resistance 200 OK + + +/- CTX-M-1 Group Class A beta-lactamase Detects CTX-M-1 type 50 OK +/- ACC-1 group Class C beta-lactamase ACC-1,ACC-2,ACC-4 100 OK + + ACC-3 Class C beta-lactamase 30 OK + ACT-1 group Class C beta-lactamase ACT-1,ACT-2,ACT- 100 OK + + CFE-1 Class C beta-lactamase 50 OK +/- + FOX Class C beta-lactamase FOX-1,FOX-2,FOX- 3,FOX-4,FOX-5,FOX- 100 OK + + LAT Class C beta-lactamase LAT-1,LAT-3,LAT- 100 OK +/- MIR Class C beta-lactamase MIR-1,MIR-2,MIR-3,MIR- 30 OK + OXA-48 Group Class D beta-lactamase OXA-48,OXA-162,OXA- 50 OK +/- +/- OXA-51 Group Class D beta-lactamase OXA-51 group (65 100 OK +/- QnrB-1 group Fluoroquinolone resistance QnrB1,QnrB2,QnrB3,Qn rB6,QnrB7,QnrB9,QnrB 13,QnrB14,QnrB15,Qnr B16,QnrB17,QnrB18,Qn 20 OK + QnrB-5 group Fluoroquinolone QnrB5,QnrB10,QnrB19 40 OK + + QnrB-8 group Fluoroquinolone QnrB8,QnrB21,QnrB25, 20 OK + + ermB Macrolide Lincosamide 20 OK + + + ermC Macrolide Lincosamide 100 OK + + mefA Macrolide Lincosamide 100 OK + + + msrA Macrolide Lincosamide 100 OK + + + + +/- oprm Multidrug resistance 20 OK +/- tetA Tetracycline efflux 40 OK + + tetB Tetracycline efflux 30 OK + + + Staphylococcus aureus Staphylococcus aureus 100 OK + + + + +/- mecA Beta-lactam resistance 40 OK +/- + +/- lukF Panton-Valentine Staphylococcus aureus 20 OK spa Immunoglobulin G Staphylococcus aureus 200 OK + + + +/- Methicillin Resistant Staphylococcus aureus Methicilli nSensitive SA Methicilli nSensitive SA HA- Methicilli nResistant +/- +/- All the tested food samples contained multiple antibiotic resistance genes. ErmB, mefA and msrA were detected in all meat samples. Microbial Identification 27
- 28. Sample to Insight Validationof specificity for PCR array by pyrosequencing Microbial Identification 28
- 29. Sample to Insight Focusedmetagenomics applications Screening for microbial genes in metagenomic samples Antibiotic resistance genes – from food to man 29 Examples from the next wave of microbiome experiments Respiratory virus co-infection Relationships between microorganisms that permit colonization Profile changes in vaginal flora during bacterial vaginosis
- 30. Sample to Insight Bacterialvaginosis 1 2 3 4 5 6 7 8 9 10 11 12 A Aerococcus christensenii Atopobium vaginae Bacteroides fragilis Bacteroides ureolyticus Campylobacter gracilis Campylobacter rectus Campylobacter showae Candida albicans Candida glabrata Candida krusei Candida parapsilosis Candida tropicalis B Capnocytophaga ochracea Capnocytophaga sputigena Corynebacterium aurimucosum Eggerthella sinensis Eikenella corrodens Fusobacterium nucleatum Gardnerella vaginalis Haemophilus influenzae Leptotrichia amnionii Mobiluncus curtisii Mobiluncus mulieris Mycoplasma genitalium C Mycoplasma hominis Parvimonas micra Prevotella bivia Prevotella disiens Prevotella intermedia Prevotella melaninogenica Prevotella nigrescens Pseudomonas aeruginosa Selenomonas noxia Sneathia sanguinegens Streptococcus agalactiae Streptococcus intermedius(1338) Streptococcus constellatus D Streptococcus mitis Treponema denticola Treponema socranskii Trichomonas vaginalis Ureaplasma parvum Ureaplasma urealyticum Mm.GAPDH Mm.HBB1 Pan Aspergillus/ Candida Pan Bacteria 1 Pan Bacteria 3 PPC E Aerococcus christensenii Atopobium vaginae Bacteroides fragilis Bacteroides ureolyticus Campylobacter gracilis Campylobacter rectus Campylobacter showae Candida albicans Candida glabrata Candida krusei Candida parapsilosis Candida tropicalis F Capnocytophaga ochracea Capnocytophaga sputigena Corynebacterium aurimucosum Eggerthella sinensis Eikenella corrodens Fusobacterium nucleatum Gardnerella vaginalis Haemophilus influenzae Leptotrichia amnionii Mobiluncus curtisii Mobiluncus mulieris Mycoplasma genitalium G Mycoplasma hominis Parvimonas micra Prevotella bivia Prevotella disiens Prevotella intermedia Prevotella melaninogenica Prevotella nigrescens Pseudomonas aeruginosa Selenomonas noxia Sneathia sanguinegens Streptococcus agalactiae Streptococcus intermedius(1338) Streptococcus constellatus H Streptococcus mitis Treponema denticola Treponema socranskii Trichomonas vaginalis Ureaplasma parvum Ureaplasma urealyticum Mm.GAPDH Mm.HBB1 Pan Aspergillus/ Candida Pan Bacteria 1 Pan Bacteria 3 PPC Microbial Identification 30
- 31. Sample to Insight MicrobialDNA qPCR arrays protocol Microbial Identification 31
- 32. Sample to Insight Identificationof microbes in bacterial vaginosis Microbial Identification 32
- 33. Sample to Insight Cervicalflora: Gardnerella vaginalis positive vs. BV negative Microbial Identification 33
- 34. Sample to Insight Insamples with high Gardnerella vaginalis abundance, there was an increase in co- occurrence of BV-associated microorganisms and decrease in abundance of the normal flora, Lactobacillus crispatus. Microbial Identification 34 Cervical flora: Gardnerella vaginalis positive vs. BV negative
- 35. Sample to Insight CorrelateqPCR assay performance with NGS results Profiles of vaginal flora by qPCR and whole genome sequencing Microbial Identification 35
- 36. Sample to Insight Focusedmetagenomics applications Screening for microbial genes in metagenomic samples Antibiotic resistance genes – from food to man Examples from the next wave of microbiome experiments Respiratory virus co-infection Relationships between microorganisms that permit colonization Profile changes in vaginal flora during bacterial vaginosis Microbial Identification 36
- 37. Sample to Insight Prevalenceof respiratory viruses in nasopharyngeal swabs • Number of cases where at least one virus was detected • Majority of cases were infected by one virus, but some were co-infected with two or three viral species Detection of respiratory viruses by qPCR array Viral co-infection Microbial Identification 37
- 38. Sample to Insight Viralspecies associated with co-infections Double co-infection Triple co-infection 5 6 9 10 11 12 14 21 25 30 36 46 49 52 8 16 38 40 60 hMPV + + + + hPIV-1 + + + + hPIV-2 + hPIV-3 + + + + + + + + + + + Influenza A + + + + + Influenza B + + + + + Rhinovirus + + + + + + + + + + + RSV + + • Rhinovirus and hPIV-3 most frequently occurred in both double and triple co- infections • No clear pattern of co-infections in this sample population Microbial Identification 38
- 39. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 39 1 2 3 4 5 6
- 40. Sample to Insight Microbiology:From identification to characterization 16S rRNA gene - Conserved region - Variable region Microbial qPCR assays and arrays for identification and profiling use probes and primers against 16srRNA variable region. Largest microbiome portfolio; experimentally verified 580 assays. Select 8 to 384 microbial species for simultaneous detection and profiling. Integrated controls ensure reliability of results. 95 Can detect as low as 10 copy numbers; data available. Content Custom Control Sensitivity Microbial Identification 40
- 41. Sample to Insight MicrobialDNA qPCR arrays and assays Profile or identify the presence of microbial DNA (from bacteria, fungi, virus, protist, antibiotic resistance and virulance factors) Identification experiment answers the following question: Are any of these microbes or genes present in the sample? • Must be compared against a known negative sample • Run NTC as one sample • Answers are Yes or No Profiling experiment answers the following question: Have the amounts of any of these microbes or genes changed? • Must be compared against a reference sample • Answers are fold change Microbial Identification 41
- 42. Sample to Insight Sampleto Insight : Microbial qPCR assays and arrays • Mericon Bacteria Kit • QIAmp UCP Pathogen Mini Kit • QIAmp DNA Stool Mini Kit • QIAmp UCP PurePathogen Blood Kit • QIAmp DNA Mini Kit • Magttract HMW kit • Microbial DNA qPCR Arrays • Microbial DNA qPCR Assay Kits • Microbial DNA qPCR Assays • Microbial aPCR Multi-Assay Kits • Custom Microbial DNA qPCR Arrays • GeneGlobe Data Analysis Center QIAcube QIAcube HT QIAsymphony QIAgility Rotor-Gene Q AutomationConsumables Microbial Identification 42 Data analysis Assays and arrays DNA isolation
- 43. Sample to Insight •Pathogen Lysis Tubes Microbial NGS (microbiome / pathogen): QIAGEN product line • QC assays kits to detect species specefic gDNA and microbial DNA: Pan bacteria, Pan fungal, Pan aspergillus, hgDNA, mgDNA etc. • GeneRead DNA Library Prep Kits (Life, ILMN) • GeneRead Size Selection Kit • GeneRead Library Quant System Software • CLC Bio Genomics workbench • Microbial Genome Finishing module For human microbiome NGS • QIAamp DNA Microbiome Kit If depletion of human gDNA is not necessary • QIAamp UCP Pathogen Mini Kit For genome finishing (starting with culture) • Magattract HMW DNA Kit Limited primary sample material • Repli-g Single Cell Kit • QIAamp metagenomics stool, soil Kit (depletion of inhibitors) Predesigned & custom arrays / assays for verification and focused microbiome analyses • Microbial DNA qPCR Arrays • Microbial DNA qPCR Multi-Assay Kits • Microbial DNA qPCR Assay Kits • Microbial DNA qPCR Assays (see as well „microbial detection / identification by PCR“ workflow) TissueLyserII; TissueLyser LT; TissueRuptor QIAcube; QIAxpert QIAcube 2014 Any Instrument/ RGQ Microbial Identification 43 NGS run NGS library preparation Sample Preparation NGS software Validation of PCR Sample disruption
- 44. Sample to Insight MicrobialqPCR portfolio Start with any sample type Health Care Industry Food and Vet industry QIAmp DNA mini kit; QIAmp UCP Pathogen detection kit; mericon Food kit Microbial DNA extraction Microbial qPCR on any instrument Tube format Plate format Microbial Identification 44 Stool, tissue, blood, cells Vaginal fluid, hospital swabs Dairy, meat, seafood Vegetables, beer, food samples Assay Kits: Starter kit: Detection of one microbial species or antibiotic resistance gene for 20 samples in a tube Arrays: Application based detection of up to 96 microbial species or genes on any plate format Assays: Detection of one microbial species or antibiotic resistance genes for 100 samples in a tube Custom Arrays Choose 8- 384 species or genes with controls on any plate format
- 45. Sample to Insight MicrobialqPCR DNA assays More than 580 qPCR identification assays available for identification of: Bacteria Fungus Parasites Virus Protist Antibiotic resistance genes Virulence factors Control assays Available Assays Popular assays by Industry: Lactobacillus brevis Lactobacillus buchneri Lactobacillus coryniformis Lactobacillus curvatus Lactobacillus lindneri Megasphaera cerevisiae Pectinatus cerevisiiphilus Pectinatus frisingensis Pediocococcus damnosus Beer Spoilage Bacteria Women Health Candida parapsilosis Candida glabrata Candida albicans Candida krusei Mobiluncus curtisii Mycoplasma genitalium Ureaplasma urealyticum Eikenella corrodens Trichomonas vaginalis Streptococcus agalactiae Microbial Identification 45
- 46. Sample to Insight HealthCare industry & academic research Microbial qPCR DNA arrays 16 cataloged qPCR arrays available for any sample type and instruments. • Lab verified assays and controls for microbial species on a plate Women Health • Vaginal Flora • Bacterial Vaginosis* Infectious Disease • Respiratory Infection • Intestinal Infection • Sepsis • Urinary Tract Infections Hospital Research • Oral Disease • Metabolic Disorder (Gut research)* • Antibiotic Resistance Genes* Food and Vet Industry • Food Testing: Meat • Food Testing: Seafood • Food Testing: Dairy • Food Testing: Poultry • Food Testing: Vegetable • Antibiotic Resistance Genes* • Water Analysis • Biodefence * Custom array for Beer Spoilage bacteria* * Most popular array Custom arrays available for all assays Microbial Identification 46
- 47. Sample to Insight MicrobialDNA qPCR array Pre-printed assays profile up to 90 different species/genes • PCR plates (either 96-well or 384-well) are pre-printed with primers and probes. • Each numbered well is a separate assay that tests the same sample. • Integrated control assays: • Host assays detect genomic DNA to test sample collection • Pan A/C is a pan- Aspergillus/Candida assay that detects the presence of fungal rRNA • PanB1 and PanB2 detect bacterial 16S rRNA to determine bacterial load in the sample • PPC is a positive PCR control reaction that tests if the PCR reactions failed from PCR inhibitors from the sample, etc. Microbial Identification 47 Data analysis Detection by qPCR DNA isolation
- 48. Sample to Insight Layoutof a microbial DNA qPCR array Different arrays have different number of assays and samples Microbial Identification 48
- 49. Sample to Insight Custommicrobial qPCR DNA arrays Complete freedom for the custom to build their own Microbial qPCR Array. • Choose 8-384 microbial species, antibiotic resistant genes or virulence factors from the 580 assay list and place it on the plate according to your interest along with the controls and pan assays( for normalizing the data). Microbial Identification 49
- 50. Sample to Insight Interestedin a pathway or genes Browse by research area Browse by biology Pathway central qPCR assays, NGS panels, qPCR arrays and custom products Customer journey on GeneGlobe at a glance Interested in a research area or biology Interested in Gene expression, Genotyping or Gene regulation products Browse by products GeneGlobe lists Array and assay finder Complimentary Data Analysis Microbial Identification 50
- 51. Sample to Insight Pathway-focusedsolutions for expression analysis http://www.geneglobe.com http://www.QIAGEN.com/ Microbial DNA qPCR Arrays Thank you Microbial Identification 51
- 52. Sample to Insight Agenda Humansor superorganisms? • Introduction to the microbiome Cataloging our “second genome” • Limitations of current methodologies Identify and profile relevant targets • How to design assays for the microbiome Focused metagenomics applications Overview of QIAGEN’s microbial qPCR products Questions Microbial Identification 52 1 2 3 4 5 6
- 53. Sample to Insight Thankyou for coming Any questions? Contact us Telephone: 888-503-3187 Email: brcsupport@QIAGEN.com qiawebinars@QIAGEN.com Microbial Identification 53