JoVE Journal > Immunology and Infection
Summary
Abstract
Introduction
Protocol
Results
Discussion
Disclosures
Acknowledgements
Materials
References
Automatic Translation
Immunology and Infection

Identifikation af sjældne bakterielle patogener ved 16S rRNA Gene Sequencing og MALDI-TOF MS

Published: July 11, 2016
doi:
10.3791/53176
, , ,
1Institut für Medizinische Mikrobiologie und Hygiene, Medizinische Fakultät Carl Gustav Carus,TU Dresden, 2Institut für Virologie, Medizinische Fakultät Carl Gustav Carus,TU Dresden

Summary

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.

Abstract

Der er en række sjældne, og derfor utilstrækkeligt beskrevet bakterielle patogener som indberettes til forårsage alvorlige infektioner, især hos immunkompromitterede patienter. I de fleste tilfælde kun få data, for det meste udgivet som case-rapporter, er tilgængelige, som undersøger betydningen af ​​sådanne patogener som et smitstof. Derfor, for at tydeliggøre den patogene karakter af sådanne mikroorganismer, er det nødvendigt at udføre epidemiologiske undersøgelser, som omfatter et stort antal af disse bakterier. De anvendes i en sådan undersøgelse overvågning metoder skal opfylde følgende kriterier: identifikation af stammerne skal være nøjagtig i henhold til den gældende nomenklatur, bør de være nemme at håndtere (robusthed), økonomisk i rutinediagnostik og de har til at generere sammenlignelige resultater blandt forskellige laboratorier. Generelt er der tre strategier til identifikation af bakteriestammer i en rutinemæssig indstilling: 1) fænotypisk identifikation kendetegner Biochemical og metaboliske egenskaber af bakterierne, 2) molekylære teknikker, såsom 16S rRNA-genet sekventering og 3) massespektrometri som en ny proteom tilgang. Da massespektrometri og molekylære metoder er de mest lovende værktøjer til identifikation af en lang række bakteriearter, er disse to metoder beskrevet. Forskud, begrænsninger og potentielle problemer, når du bruger disse teknikker diskuteres.

Introduction

Sikker identifikation af sjældne patogener i rutinediagnostikken hæmmes af, at de klassiske kulturelle og biokemiske metoder er besværlige og til tider tvivlsom. Endvidere er en diagnostisk mikrobiologiske laboratorium skal bearbejde et stort antal patogener, der spænder fra nogle få hundrede til flere tusinde, dagligt, hvilket kræver brug af automatiserede systemer. Ud over forvaltningen af ​​en høj daglig kapacitet, er der behov for nøjagtig identifikation af bakteriearter. Dette er berettiget, da de adskiller sig i deres antimikrobiel følsomhed mønster og derfor korrekt identifikation giver klinikeren med væsentlige oplysninger til at vælge passende antibiotika (f.eks Enterococcus spp., Acinetobacter spp.) 12,43.

Automatiserede mikrobielle identifikationssystemer (AMIS) anvende standardiserede sæt enzymatiske reaktioner til at karakterisere de metaboliske egenskaber af bakterielle isolater <sup> 13,15,16,26,27. Selvom de patroner, der bruges i disse systemer anvender et stort antal forskellige biokemiske reaktioner, fx 47 i GN kort af Amis anvendt i denne undersøgelse 52, denne strategi tillader sikker identifikation kun for et begrænset sæt af bakterier. Endvidere er databasen, et avanceret ekspertsystem, klart fokuseret på påvisning af relevante og yderst relevante bakterier af medicinsk betydning 13,15,16,36. Yderligere to systemer, er meget udbredt i laboratorier, gælder også denne biokemiske fremgangsmåde for bakteriel identifikation. Nylige undersøgelser viser en sammenlignelig identifikation nøjagtighed mellem amis anvendt i denne undersøgelse, og en af konkurrenterne (93,7% og 93,0%), mens den 3. Amis har en identifikation nøjagtighed på kun 82,4% på artsniveau 35. Sådanne uoverensstemmelser kan forklares ved kvaliteten af ​​de underliggende identifikation data referencer, versioner af kits og software, forskelle i metabolism og færdigheder af teknisk personale 35,36.

To automatiserede MALDI-TOF MS-systemer (MALDI-TOF mikrobielle identifikationssystem, mMIS) anvendes hovedsageligt. Disse systemer giver mulighed for påvisning af en lang række bakteriearter baseret på deres protein fingeraftryk massespektre. For eksempel databasen over de mMIS anvendte indeholder 6.000 referencespektrer. Identifikationssystemer baseret på massespektrometri tilbyder hurtig og pålidelig detektering af en bred vifte af mikroorganismer, herunder sjældne patogener 11,48,51. Til dato kun få direkte sammenligninger er tilgængelige mellem mMIS anvendt i denne undersøgelse og dens konkurrent 19,33. Ifølge Dæk et al. Begge systemer giver en tilsvarende høj identifikation nøjagtighed, men de mMIS anvendt i denne undersøgelse synes at være mere pålidelige til identifikation af arter 19.

Tilsvarende adressering molekylære teknikker velbevarede men også distinkte gener ( <em> fx 16S rDNA eller rpoB) tillader en klar arter identifikation 3,22,61. Blandt disse, 16S rDNA er den mest udbredte housekeeping-genet på grund af sin tilstedeværelse i alle bakterier 34. Dens funktion er uændret og endelig med omtrent 1500 bp, den er lang nok til at være egnet til bioinformatik 14,34. Mange forskere anser 16S rRNA-genet analyse som "gold-standard" for bakteriel identifikation 21. Dette skyldes det faktum, at kun få laboratorier anvender DNA-DNA-hybridisering teknikker til dato for identifikation af sjældne eller nye bakterier 14,34. Derudover flere og flere databaser er tilgængelige, som kan anvendes til 16S rRNA-genet analyse 50. har det imidlertid tages i betragtning, at 16S rDNA baserede påvisningssystemer har en begrænset følsomhed sammenlignet med standard-PCR-protokoller. Desuden er den molekylære tilgang er sofistikeret, tidskrævende og kræver højtuddannet personale samtdedikerede laboratoriefaciliteter og er derfor ikke let implementeres i rutinediagnostik 55. Endvidere er det blevet vist, at kombinationen af ​​mindst to forskellige metoder til bakteriel identifikation fører til meget nøjagtige stamme identifikation. Kombinationen af ​​MALDI-TOF MS og 16S rDNA-sekventering muliggør identifikation af et stort antal forskellige bakteriearter med stor nøjagtighed. For nylig kombinationen af MALDI-TOF MS og 16S rRNA-genet analyse blev præsenteret for bakteriel identifikation studere epidemiologiske spørgsmål og sjældne patogener 56.

Protocol

1. Ekstraktion af bakteriel DNA Fremstilling af PBS-opløsning Afvej 1,65 g Na 2 HPO 4 x 2H 2 O, 0,22 g NaH 2 PO 4 x 2H 2 O og 8,80 g NaCl i en kolbe og fyld op med destilleret vand til et slutvolumen på 1000 ml. Justere pH til 7,4. For den endelige anvendelse filtreres gennem et bakterie-bevis (0,22 um) filter. DNA Ekstraktion af gramnegative bakterier Streak patienten materiale på passende kulturmedier …

Representative Results

MALDI-TOF MS er en hidtil ukendt, hurtig og billig fremgangsmåde til mikrobiologiske rutinediagnostik. Bakteriearter identifikation ved MALDI-TOF MS producerer spektre hovedsagelig består af ribosomale proteiner, men også andre "meget konserverede proteiner med hus-føring funktioner påvirket til en minimal grad af miljøforhold" 17 .Den database over denne mMIS indeholder et stort sæt af henvisning spektre og endda bakterier, der sjældent findes i kliniske iso…

Discussion

Både MALDI-TOF MS og 16S rRNA-genet sekventering giver mulighed for at identificere et stort antal forskellige bakterier. MALDI-TOF MS er en hurtig og billig metode, som er let at håndtere og store databaser af bakteriel massespektre er tilgængelige. Derfor MALDI-TOF MS er en hurtig, omkostningseffektiv og pålidelig metode til at foretage screening undersøgelser fokuserede på sjældne bakterielle patogener 17,20,39,51. I et prospektivt studie, der sammenlignede MALDI-TOF MS med andre fænotypiske identi…

Disclosures

The authors have nothing to disclose.

Acknowledgements

The authors would like to thank Prof. Enno Jacobs for his continuing support.

Materials

CHROMASOLV, HPLC grade water, 1 L Sigma-Aldrich Chemie, München, Germany 270733
Tissue Lyser LT Qiagen, Hilden, Germany 85600 Oscillating Homogenizer
Glass-beads 1,0mm VWR International, Darmstadt, Germany 412-2917
Thermomixer 5436 Eppendorf, Hamburg, Germany 2050-100-05
QIAamp DNA Mini Kit (250) Qiagen, Hilden, Germany 51306
Taq PCR Core Kit (1000 U) Qiagen, Hilden, Germany 201225
Forward Primer TPU1 (5´-AGA GTT TGA TCM TGG CTC AG-3’) biomers.net GmbH, Ulm, Germany  –
Reverse Primer RTU4 (5´-TAC CAG GGT ATC TAA TCC TGT T-3´) biomers.net GmbH, Ulm, Germany  –
Mastercycler  Eppendorf, Hamburg, Germany -  Thermocylcer
Reaction tube 1.5 mL SARSTEDT, Nümbrecht, Germany 72,692
Reaction tube 2 mL SARSTEDT, Nümbrecht, Germany 72,693,005
PCR 8er-CapStrips Biozym Scientific, Hessisch Oldendorf, Germany 711040X
PCR 8er-SoftStrips Biozym Scientific, Hessisch Oldendorf, Germany 711030X
Sharp R-ZV11  Sharp Electronics, Hamburg, Germany – Microwave
Titriplex III (EDTA Na2-salt dehydrate; 1 kg) Merck, Darmstadt, Germany 1084211000
SeaKem LE Agarose Biozym Scientific, Hessisch Oldendorf, Germany 849006
(2 x 500 g)
SmartLadder SF – 100 to 1000 bp Eurogentec, Lüttich, Belgium MW-1800-04
Bromphenol blue (25 g) Sigma-Aldrich Chemie, München, Germany B0126
Xylene cyanol FF (10 g) Sigma-Aldrich Chemie, München, Germany X4126
ComPhor L Maxi  Biozym, Hessisch Oldendorf, Germany –
Ethidium bromide solution 1 %(10 mL) Carl Roth, Karlsruhe, Germany 2218.1
Gel Doc 2000 Bio-Rad Laboratories, München, Germany – Gel-documentation system 
ExoSAP-IT (500 reactions) Affymetrix UK, Wooburn Green, High Wycombe, United Kingdom 78201
Buffer (10 x) with EDTA  Life Technologies, Darmstadt, Germany 402824
BigDye Terminator Kit v1.1 Life Technologies, Darmstadt, Germany 4337450
Hi-Di formamide (25 mL) Life Technologies, Darmstadt, Germany 4311320
DyeEx 2.0 Spin Kit (250) Qiagen, Hilden, Germany 63206
3130 Genetic Analyzer Life Technologies, Darmstadt, Germany – Sequenzer
MicroAmp optical 96-well reaction plate with barcode Life Technologies, Darmstadt, Germany 4306737
3130 Genetic Analyzer, plate base 96-well Life Technologies, Darmstadt, Germany 4317237
3130 Genetic Analyzer, plate retainer 96-well Life Technologies, Darmstadt, Germany 4317241
3130 Genetic Analyzer, well plate septa Life Technologies, Darmstadt, Germany 4315933
3130 Genetic Analyzer, POP-7 Polymer, 7 mL Life Technologies, Darmstadt, Germany 4352759
3130 Genetic Analyzer, 4-Capillary Array, 50 cm Life Technologies, Darmstadt, Germany 4333466
Sequencing Analysis Software 5.4 Life Technologies, Darmstadt, Germany –
microflex (the MALDI TOF MS maschine) Bruker Daltonik, Bremen, Germany –
MALDI Biotyper (the MALDI TOF MS system) Bruker Daltonik, Bremen, Germany – our mMIS
VITEK MS  bioMérieux, Nürtingen, Germany  2nd mMis 
flexControl 3.4 (control software) Bruker Daltonik, Bremen, Germany –
Biotyper Realtime Classification 3.1 (RTC), (analysis software) Bruker Daltonik, Bremen, Germany –
α-cyano-4-hydroxycinnamic acid, HCCA, 1 g Bruker Daltonik, Bremen, Germany 201344
Peptide Calibration Standard II Bruker Daltonik, Bremen, Germany 222570
MSP 96 target polished steel Bruker Daltonik, Bremen, Germany 8224989
peqgreen  peqlab  37-5010
MALDI Biotyper Galaxy  Bruker Daltonik, Bremen, Germany Part No. 1836007 
Vitek 2  bioMérieux, Nürtingen, Germany  our aMis 
MicroScan  Beckman Coulter  2nd aMis 
BD Phoenix™ Automated Microbiology System BD 3rd aMis 
Staphylococcus aureus subsp. aureus Rosenbach (ATCC® 25923™) ATCC  postive control for PCR 
DOWNLOAD MATERIALS LIST

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Keywords: 16S RRNA Gene SequencingMALDI-TOF MSRare Bacterial PathogensMyroidesOdoratimimusBacterial DNA Extraction16S RRNA PCRSanger SequencingMALDI-TOF MS AnalysisMALDI Biotyper SoftwareBacterial IdentificationDiagnostic Microbiology
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Schröttner, P., Gunzer, F., Schüppel, J., Rudolph, W. W. Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS. J. Vis. Exp. (113), e53176, doi:10.3791/53176 (2016).
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