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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Rapid Detection of Microbes Using qPCR
1. Sample to Insight
Development of Rapid Detection Methods for Microbial and
Microbiome Analysis and Applications to Human Health
Christine Davis
Christine.Davis@QIAGEN.com
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Legal disclaimer
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
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
Questions
Microbial Identification 3
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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
Questions
Microbial Identification 4
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Humans or 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
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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
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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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9. 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
Questions
Microbial Identification 9
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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)
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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
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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
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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
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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
Questions
Microbial Identification 14
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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)
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Performance testing of each assay
Dilution series testing for PCR efficiency and sensitivity
Microbial Identification 16
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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
Microbial Identification 17
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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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40
1 2 3 4 5 6 7 8 9 10 11
CT
Pool
Staph/Strep
complete
Campylobacter spp. 1 Assay
Microbial Identification 18
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Assay performance in a metagenomic background
Spike-in experiments test for specificity in a complex background
Microbial Identification 20
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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
Questions
Microbial Identification 21
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Focused metagenomics 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
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Antibiotic resistance
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
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Antibiotic resistance 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
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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.
Microbial Identification 25
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Presence of 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
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Focused metagenomics applications
Screening for microbial genes in metagenomic samples
Antibiotic resistance genes – from food to man
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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
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Cervical flora: Gardnerella vaginalis positive vs. BV negative
Microbial Identification 33
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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.
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Cervical flora: Gardnerella vaginalis positive vs. BV negative
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Correlate qPCR assay performance with NGS results
Profiles of vaginal flora by qPCR and whole genome sequencing
Microbial Identification 35
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Focused metagenomics 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
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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
Microbial Identification 37
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Viral species 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
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
Questions
Microbial Identification 39
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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
Microbial Identification 40
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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
Microbial Identification 41
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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
QIAcube
QIAcube HT
QIAsymphony
QIAgility
Rotor-Gene Q
AutomationConsumables
Microbial Identification 42
Data analysis
Assays and
arrays
DNA isolation
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• 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
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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
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
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 parapsilosis
Candida glabrata
Candida albicans
Candida krusei
Mobiluncus curtisii
Mycoplasma genitalium
Ureaplasma urealyticum
Eikenella corrodens
Trichomonas vaginalis
Streptococcus agalactiae
Microbial Identification 45
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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
Microbial Identification 46
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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.
Microbial Identification 47
Data analysis
Detection by
qPCR
DNA isolation
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Layout of a microbial DNA qPCR array
Different arrays have different number of assays and samples
Microbial Identification 48
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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).
Microbial Identification 49
50. Sample to Insight
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Microbial Identification 50
51. Sample to Insight
Pathway-focused solutions for expression analysis
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Microbial DNA qPCR Arrays
Thank you
Microbial Identification 51
52. 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
Questions
Microbial Identification 52
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Thank you for coming
Any questions?
Contact us
Telephone: 888-503-3187
Email: brcsupport@QIAGEN.com
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Microbial Identification 53