Microbiome Identification to Characterization: Pathogen Detection Webinar Series: Part 3

Sample to Insight

Development of Rapid Detection Methods for Microbial and Microbiome Analysis and Applications to Human Health

Christine Davis [email protected]

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Sample to Insight

Microbial Identification 2

Legal disclaimer

• 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.

http://www.qiagen.com/

Sample to Insight

Agenda

Humans or 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

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Agenda









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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.


Sample to Insight

Microorganisms cluster 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


Sample to Insight

Complexity and 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


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Physiological associations lead to new funding

NIH funding across institutes for microbiome - related studies

2008

2013


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Agenda









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Current methods 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)


Sample to Insight

Limitations of 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


Sample to Insight

NGS for 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


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


Sample to Insight

Agenda









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16S rRNA 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)


Sample to Insight

Performance testing of each assay

Dilution series testing for PCR efficiency and sensitivity


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Determine sensitivity 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


Sample to Insight

Specificity of 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

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Pool

CTSt

aph/

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p

com

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Campylobacter spp. 1 Assay


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Genomic DNA pools for specificity testing

• Complete pool contains all genomic DNA for each species listed

Pool1 Pool2 Pool3 Pool4Acinetobacter baumanni i Aeromonas hydrophi l a Alca l igenes faeca l i s s ubsp. Faecal i s As pergi l lus fumigatusBaci l lus l i cheni formis Bartonel la hens elae Bordetel la pertus s i s Brevundimonas diminutaCampylobacter jejuni subs p. Jejuni Candi da a l bicans Candida glabrata Candida paraps i los i sCi trobacter freundi i Clostridi um diffi ci l e Clos tri dium perfringens Cl ostridium thermocel l umCorynebacterium glutamicum Enterobacter aerogenes Enterococcus faecal i s Enterococcus faeciumFusobacterium nucleatum subs p. Nucleatum Geobaci l lus s tearothermophilus Haemophilus infl uenzae Hel icobacter pyloriLegionel la pneumophi la s ubs p. Pneumophi la Listeria monocytogenes Mycobacteri um tuberculos i s Neis s eria meni ngitidisPantoea agglomerans Pediococcus pentosa ceus Ples iomonas s hi gel loides Proteus mirabi l is

Rahnel l a aquati l i s Ral s toni a s ol anacearumSalmonel la enterica s ubsp. enterica s erovar Paratyphi A Serratia marces cens

Vibri o cholerae Yers inia enterocol itica s ubsp. Enterocol iti ca Yers inia pes tis Stenotrophomonas ma ltophi l i aPool5 Pool6 Pool7 Pool8

Baci l lus cereus Aggregatibacter actinomycetemcomitans Akkermansia muciniphi l a Anaerococcus prevotiiBurkhol deria cenocepacia Bacteroi des theta iotaomicron Bacteroides ureolyti cus Bacteroides vul gatusCandida tropica l i s Burkholderia cepacia Campylobacter col i Campyl obacter conci susCorynebacterium diphtheriae Capnocytophaga gi ngiva l i s Cryptobacterium curtum Cryptococcus gatti iEscherichia col i Enterobacter cloacae subs p. Cloacae Gardnerel la vagi na l i s Lactobaci l lus jens eni iKlebs iel la pneumoniae Lactobaci l l us cas ei Lactobaci l lus gas s eri Micrococcus luteusOchrobactrum anthropi Methanobrevibacter s mithi i Mycoplas ma pneumoniae Neis s eria fl avaPseudomonas aeruginosa Mycoplasma ora le Porphyromonas gingiva l i s Prevotel la intermediaShigel la fl exneri Porphyromonas endodonta l i s Trichomonas vagina l i s Ureaplasma parvumYers i nia ps eudotuberculos is Treponema denticola Staphylococcus haemolyti cus Streptococcus mitis

Pool9 Pool10 Pool11 Staph/strep poolAspergi l lus fl avus Atopobium rimae Baci l lus s ubtil is Staphyl ococcus aureusBifi dobacterium breve Bifi dobacterium longum subs p. Infantis Bordetel la parapertus s is Staphyl ococcus epidermidis Campylobacter graci l i s Campylobacter rectus Campylobacter upsa l iens is Streptococcus aga lactiae Cryptococcus neoformans Des ul fovibrio des ulfuricans Lactobaci l lus aci dophi lus Streptococcus gordoni i Haemophi lus ducreyi Klebs iel la oxytoca Leptotrichia buccal i s Streptococcus mitis Lactobaci l lus plantarum Lactobaci l l us reuteri Mycoplas ma hominis Streptococcus mutans Mycobacterium s megmatis Mycoplasma genita l i um Peptos treptococcus anaerobius Streptococcus pneumoniae Neiss eria gonorrhoeae Parabacteroides di stasonis Tannerel la forsythia Streptococcus pyogenes Prevotel la melani nogenica Proteus vul garis Vibrio parahaemolyticus Streptococcus s anguini s Vei l l onel la parvul a Vibrio harvey Streptococcus aga lactiae


Sample to Insight

Assay performance in a metagenomic background

Spike-in experiments test for specificity in a complex background


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Agenda









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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 colonizationProfile changes in vaginal flora during bacterial vaginosis


Sample to Insight

Antibiotic resistance

23,000 deaths can be prevented if....

Antibiotic-resistant genes: how can we controlAntibiotic-resistant bacteria’s sicken two million people and 23,000 succumb to it. Can we prevent these deaths? Yes we can. In March of 2015, the national action plan for combating antibiotic-resistant bacteria was developed to combat resistance. One of the action plans was to improve surveillance capabilities. Learn more about The National Action 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


https://www.whitehouse.gov/the-press-office/2015/03/27/fact-sheet-obama-administration-releases-national-action-plan-combat-ant




Sample to Insight

Antibiotic resistance genes in our food supply?


• 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

Sample to Insight

Antibiotic resistance 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.


Sample to Insight

Antibiotic resistance genes in our food supply?


Sample to Insight

Presence of antibiotic resistance genes in the food supply

Species/geneAntibiotic classification / virulence factor gene description Also detects Sensitivity

NTC QC check beef chicken pork carrot lettuce potato

aadA1Aminoglycoside-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 +/- +

FOXClass 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,QnrB6,QnrB7,QnrB9,QnrB13,QnrB14,QnrB15,QnrB16,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 eff lux 40 OK + +tetB Tetracycline eff lux 30 OK + + +Staphylococcus aureus Staphylococcus aureus 100 OK + + + + +/-mecA Beta-lactam resistance 40 OK +/- + +/-lukF Panton-Valentine Staphylococcus aureus 20 OKspa Immunoglobulin G Staphylococcus aureus 200 OK + + + +/-

Methicillin Resistant Staphylococcus aureus

Met

hici

llin

Sens

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SA

Met

hici

llin

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SA HA

-M

ethi

cilli

n Re

sista

nt

+/- +/-

All the tested food samples contained multiple antibiotic resistance genes. ErmB, mefA and msrA were detected in all meat samples.


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Validation of specificity for PCR array by pyrosequencing


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Sample to Insight

Bacterial vaginosis

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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 Capnocytophagaochracea

Capnocytophagasputigena

Corynebacteriumaurimucosum

Eggerthella sinensis

Eikenella corrodens

Fusobacteriumnucleatum

Gardnerella vaginalis

Haemophilus influenzae

Leptotrichia amnionii

Mobiluncus curtisii

Mobiluncus mulieris

Mycoplasma genitalium

C Mycoplasma hominis Parvimonas micra Prevotella bivia Prevotella

disiensPrevotella intermedia

Prevotellamelaninogenica

Prevotella nigrescens

Pseudomonasaeruginosa

Selenomonas noxia

Sneathia sanguinegens

Streptococcusagalactiae

Streptococcusintermedius(1338)

Streptococcusconstellatus

D Streptococcus mitis

Treponema denticola

Treponema socranskii

Trichomonas vaginalis

Ureaplasma parvum

Ureaplasmaurealyticum Mm.GAPDH Mm.HBB1

PanAspergillus/

CandidaPan 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 Capnocytophagaochracea

Capnocytophagasputigena

Corynebacteriumaurimucosum

Eggerthella sinensis

Eikenella corrodens

Fusobacteriumnucleatum

Gardnerella vaginalis

Haemophilus influenzae

Leptotrichia amnionii

Mobiluncus curtisii

Mobiluncus mulieris

Mycoplasma genitalium

G Mycoplasma hominis Parvimonas micra Prevotella bivia Prevotella

disiensPrevotella intermedia

Prevotellamelaninogenica

Prevotella nigrescens

Pseudomonasaeruginosa

Selenomonas noxia

Sneathia sanguinegens

Streptococcusagalactiae

Streptococcusintermedius(1338)

Streptococcusconstellatus

H Streptococcus mitis

Treponema denticola

Treponema socranskii

Trichomonas vaginalis

Ureaplasma parvum

Ureaplasmaurealyticum Mm.GAPDH Mm.HBB1

PanAspergillus/

CandidaPan Bacteria 1 Pan Bacteria 3 PPC


Sample to Insight

Microbial DNA qPCR arrays protocol


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Identification of microbes in bacterial vaginosis


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Cervical flora: Gardnerella vaginalis positive vs. BV negative


Sample to Insight

In samples 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.


Cervical flora: Gardnerella vaginalis positive vs. BV negative

Sample to Insight

Correlate qPCR assay performance with NGS results

Profiles of vaginal flora by qPCR and whole genome sequencing


Sample to Insight








Sample to Insight

Prevalence of 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


Sample to Insight

Viral species associated with co-infections

Double co-infection Triple co-infection5 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


Sample to Insight

Agenda









Questions


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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


Sample to Insight

Microbial DNA 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


Sample to Insight

Sample to 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

QIAcubeQIAcube HT

QIAsymphony

QIAgility

Rotor-Gene QAut

omat

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Con

sum

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s


Data analysisAssays and arrays

DNA isolation

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


NGS runNGS library preparation

Sample Preparation

NGS software

Validation of PCR

Sample disruption

Sample to Insight

Microbial qPCR 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

MicrobialqPCR on any instrument

Tube format Plate formatMicrobial 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

CustomArrays

Choose 8- 384 species or genes with controls on any plate format

Sample to Insight

Microbial qPCR 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 parapsilosisCandida glabrataCandida albicansCandida kruseiMobiluncus curtisiiMycoplasma genitaliumUreaplasma urealyticumEikenella corrodensTrichomonas vaginalisStreptococcus agalactiae


Sample to Insight

Health Care 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


Sample to Insight

Microbial DNA 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.


Data analysisDetection by qPCRDNA isolation

Sample to Insight

Layout of a microbial DNA qPCR array

Different arrays have different number of assays and samples


Sample to Insight

Custom microbial 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).


Sample to Insight

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genes

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qPCR assays, NGS panels, qPCR arrays and custom

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Pathway-focused solutions for expression analysis

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Microbial DNA qPCR Arrays

Thank youMicrobial Identification 51

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Agenda









Questions


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Thank you for coming

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Microbiome Identification to Characterization: Pathogen Detection Webinar Series: Part 3