Viability PCR MRAMA 2016 1
QIAGEN Supplier of diagnostic solutions Facts 1984 EXPERIENCE QIAGEN was founded in 1984 by scientists at Heinrich Heine University in Düsseldorf. $1,28 bn SALES QIAGEN's adjusted net sales in 2015 rose by 3% CER compared to the previous year. 4 600 35 EMPLOYEES QIAGEN has received several awards for being a first-class employer offering excellent development opportunities. LOCATIONS QIAGEN has branches in over 20 countries as well as over 70 commercial partners worldwide. 500 000 CUSTOMERS QIAGEN serves a global customer base in healthcare and life science research. >2 000 PATENTS In its quest for innovation and expansion, QIAGEN invests about 10% of its turnover in R&D.. 500 PRODUCTS QIAGEN markets a wide range of consumables and instruments. 2
Supplier of diagnostic solutions Germantown Regional HQ Americas Venlo Redwood City Germantown Aarhus Manchester Hombrechtikon Marseille Hilden Stockach Shanghai Regional HQ Asia Shanghai Shenzhen Hilden Operative HQ 3
Supplier of diagnostic solutions SOLUTIONS FROM SAMPLE TO INSIGHT Sampling technologies Assay technologies BIOLOGICAL SAMPLE Bioinformatics Automation VALUABLE MOLECULAR INSIGHTS 4
food safety testing range For GMO detection Screen 35S-pat Screen bar Screen CTP2-CP4EPSPS MON 810 Corn RR Soy Screen 35S Screen Nos Quant MON 810 Quant RR Soy Animal ID detection Cattle Chicken Pig Turkey Goat Sheep Ruminants Horse Vegetarian Plant ID detection Apricot Kernels Corn Soy
tion, Date food safety testing range Pathogen detection Manual or automated. Salmonella spp. Listeria spp. Listeria monocytogenes Campylobacter spp. Big 6 (VTEC stx1 / stx2) Cronobacter spp. Staphylococcus aureus Quant Legionella spp. Quant L. pneumophila Shigella spp. Yersinia enterocolitica Vibrio triple
Main issue with molecular testing in Food? Real-time PCR For detection of different pathogens in a variety of sample types Cannot differentiate between viable and non-viable cells Many regulations require viable cells rather than total cell DNA Viable cell detection Overnight culture (e.g. food samples) allows detection of living cells Shorter enrichment times may detect high non-viable cell loads 7
Introduction: areas of interest Differentiation of live and dead organisms Food microbiological safety testing e.g., microbiological approval before product release Water hygiene quality control e.g., quantification of live and dead legionella Environmental testing e.g., bacterial communities in water and soil Biomedical research e.g., monitoring of therapy progress, effectiveness of antibiotics Industrial/pharmaceutical hygiene and quality control e.g., testing of disinfection efficiency 8
Propidium monoazide: our choice Propidium monoazide Ethidium monoazide Photo-activatable anchor group (azide) 3 Positive charges Photo-activatable reaction moiety Two positive charges Membrane impermeable reagent High selectivity for dead cells Non-toxic for live cells Photo-activatable reaction moiety One positive charge Partially membrane permeable Less selective for dead cells Partially toxic for live cells 9
Propidium monoazide: mode of action + Live cell + Excess PMA in solution + + + + + + + LIGHT Inactivated excess PMA + activation + + + + + + + + PMA-masked dead cell DNA Dead cell DNA with intercalated PMA 10
Propidium monoazide: mode of action Discrimination of PMA-masked and unmasked DNA by real-time PCR Dead bacteria without PMA C T Dead bacteria with PMA Strongly suppressed amplification Signal of PMA treated bacteria is significantly shifted to higher C T values Difference between both real-time PCR signals: expected range of C T ~6 15 11
BLU-V Workflow 12
Proof-of-principle data: live/dead salmonella mixtures Starting point : live / dead mixtures without PMA treatment Live / dead mixtures processed in standardized lysis & extraction procedures All mixtures have the same DNA content and show the same C T value Real-time PCR is unable to distinguish between DNA from live or dead bacteria 13
Proof-of-principle data: dead cell controls C T 40 35 30 25 20 15 10 Dead cells x 10 6 0.2 1 1.8 2 0.2 1 1.8 2 Without PMA With PMA Dead control samples: with and without PMA Both sample sets: same titration of dead bacteria content Without PMA: C T titration according to the increase in starting material With PMA: successful suppression of amplification down to <10 target copies 14
Proof-of-principle data: live / dead salmonella mixtures 30 Live cells 30 Live/dead mixtures 25 25 C T 20 C T 20 15 15 10 10 Live (x10 6 ) 2.0 1.8 1.0 0.2 Dead (x10 6 ) 0.0 0.0 0.0 0.0 Live (x10 6 ) 2.0 1.8 1.0 0.2 Dead (x10 6 ) 0.0 0.2 1.0 1.8 Live cells treated with PMA (left) Mixtures of live / dead cells treated with PMA (right) Dead cells are undetected 15
Examples 16
Ct value Environmental swabs: Live and heat-killed controls Quantitation of PMA masking of dead cells in mixture 40 -PMA +PMA 38 36 34 32 30 28 26 live live/dead 1:10 live/dead 1:100 dead Ct values of PMA treated cells increase as portion of dead cells increase Demonstrates quantitative masking 17
Ct value Environmental swabs: Live, heat-killed and after disinfection Effect of sanitizers on detection of dead salmonella 40 -PMA +PMA 38 36 34 32 30 28 26 live dead EtOH Quat. Ammon. Sod. Hypo.Cl All sanitizers showed detectable decreased viability as demonstrated by masking of signal with PMA treatment 18
Norm. Fluoro. Environmental swabs: Live, heat-killed and after disinfection Example: Treatment with Quaternary Ammonium 0,4 Green channel: Salmonella spp. target 0,6 0,5 Yellow channel: Internal amplification control 0,3 0,2 0,1 0,0 Threshold Live +/-PMA QA -PMA QA +PMA 0,4 0,3 0,2 0,1 0,0 Threshold 5 10 15 20 25 30 35 40 45 Cycle 5 10 15 20 25 30 35 40 45 Cycle Following treatment with Quaternary ammonium: all cells were killed as demonstrated by the complete masking of the signal with PMA treatment 19
copies Environmental swabs: Live, heat-killed and after disinfection Reduction in detectable copy number with heat killing and disinfection 1000 -PMA +PMA 100 10 1 live dead EtOH Quart. Ammon. Sod. Hypo.Cl Effect of disinfection treatments can be quantified by comparison to salmonella standard curve 20
Campylobacter detection in chicken production and processing 21
Effects of exposure to stress on PMA-qPCR based Campylobacter enumeration in broiler carcass rinses C. jejuni C. coli A. Duarte et al. Food Microbiology 48 (2015) 182-190 PMA masks PCR signal from dead Campylobacter, but not live Campylobacter 22
Listeria detection in cheese manufacture Use of PMA to decrease detection of Listeria phage 23
Listeria detection in cheese manufacture Listeria phage and pathogenic Listeria interaction Listeria phage inhibits Listeria growth on cheese surface Listeria phage grown in L. innocua Trace DNA from phage culture present in final product Poor discrimination between contaminating naked DNA and pathogenic Listeria bacteria Studies tested use of PMA to mask naked Listeria spp signal 24
Results: cheese cultures spiked with L. mono (1) L. species detection Light blue bars: No PMA treatment. Dark blue bars: Cultures treated with PMA Blue arrows: Complete signal masking. Star: positive culture, live cell signal not masked by PMA. Detected Listeria spp signals completely masked or shifted by PMA treatment Signal not from living bacteria but from contaminating naked DNA 25
Results: cheese cultures spiked with L. mono (2) L. species detection Viability curves for phage-treated Mozzarella cheese cultured with L.mono followed by treatment with or without PMA. PMA treatment masks signal from naked DNA 26
Results: Listeria phage study Listeria spp detected in uninoculated cheese culture Listeria spp signals masked or shifted by PMA treatment Source is therefore contaminating naked DNA Not from infectious pathogenic bacteria Use of viability-qpcr allows discrimination between contamination with Listeria phage-derived naked DNA and contamination with pathogenic Listeria 27
BluV Makes a difference! Check website http://www.qiagen.com/de/products/catalog/automatedsolutions/sample-prep/blu-v-system/ menjuto@werfen.com Sebastien.lopez@qiagen.com 28