RUO
Geotrichum Fusobacterium Lodderomyces Anaerococcus Colletotrichum Edwardsiella Comamonas Pigmentiphaga Moellerella Nesterenkonia Listonella Udeniomyces Erysipelothrix Escherichia Streptomyces Bartonella Hafnia Terrimonas Pseudoxanthomonas Corynebacterium Streptococcus Aerococcus Saccharothrix Facklamia Schizosaccharomyces Tetragenococcus Lechevalieria Clavibacter Shimwellia Brachybacterium Leclercia Providencia Trabulsiella Xanthobacter Emericella Gardnerella Sporothrix Leuconostoc Pseudoclavibacter Alkalibacillus Debaryomyces Turicella Roseomonas Ruminococcus Scedosporium Dysgonomonas Staphylococcus Peptostreptococcus Paenibacillus Balneatrix Solibacillus Prototheca Cupriavidus Geobacillus Aspergillus Arthrobacter Mesorhizobium Acholeplasma Filobasidium Propioniferax Azohydromonas Chromobacterium Curtobacterium Kloeckera Austwickia Hyphomicrobium Cryptococcus Rummeliibacillus Budvicia Aquincola Enterobacter Sporobolomyces Brevundimonas Capnocytophaga Tatlockia Neisseria Salinivibrio Pullulanibacillus Arcanobacterium Tissierella Eggerthella Methanomonas Mucor Mobiluncus Caulobacter Helcococcus Psychrobacillus Campylobacter Blastomonas Wohlfahrtiimonas Thermoactinomyces Herminiimonas Tsukamurella Mycobacterium Bordetella Pichia Vibrio Iodobacter Tenacibaculum Listeria Plesiomonas Haloarcula Shewanella Paecilomyces Thauera Viridibacillus Yokenella Malassezia Novosphingobium Ornithobacterium Epidermophyton Oligella Paracoccus Aureobasidium Eubacterium Dietzia Salimicrobium Klebsiella Mycoplasma Variovorax Samsonia Schizophyllum Scopulariopsis Odoribacter Anaerotruncus Abiotrophia Burkholderia Sodalis Empedobacter Sphingopyxis Lactococcus Sphingobium Microsporum Peptoniphilus Vagococcus Beauveria Morganella Pasteurella Cedecea Bifidobacterium Micrococcus Propionimicrobium Starkeya Prevotella Histophilus Sphingomonas Acetobacter Francisella Photobacterium Propionibacterium Aneurinibacillus Arthrographis Aromatoleum Pediococcus Phoma Xenorhabdus Methylobacillus Fusarium Wolinella Bacteroides Zygosaccharomyces Cellulosimicrobium Helicobacter Rhizobium Terrabacter Ralstonia Butyricimonas Microsporum Castellaniella Borrelia Microbacterium Rheinheimera Wautersiella Saccharopolyspora Rahnella Nocardioides Gluconobacter Sphingobacterium Mannheimia Cohnella Aggregatibacter Cronobacter Lecythophora Riemerella Chaetomium Atopobium Rhizopus Acidovorax Rothia Kytococcus Chryseobacterium Alishewanella Gemella Methylobacterium Haemophilus Adlercreutzia Buttiauxella Weeksella Alloiococcus Bacillus Arxiozyma Halococcus Rhodotorula Pseudochrobactrum Leminorella Candidatus Xanthomonas Pectobacterium Brevibacterium Arthroderma Slackia Trueperella Inquilinus Brevibacillus Brachyspira Porphyromonas Aurantimonas Actinomyces Eikenella Kitasatospora Magnusiomyces Psychrobacter Acidiphilium Amycolatopsis Lactobacillus Marinibacillus Megamonas Dermatophilus Grimontia Acinetobacter Lysinibacillus Hanseniaspora Parvimonas Moesziomyces Legionella Aliivibrio Dermacoccus Exiguobacterium Virgibacillus Raoultella Gordonia Dialister Parabacteroides Cardiobacterium Stenotrophomonas Sporobolomyces Coprobacillus Sporosarcina Brenneria Rathayibacter Arsenophonus Penicillium Pseudomonas Rubrivivax Bilophila Alloscardovia Nocardia Halomonas Rhodococcus Bergeyella Malikia Actinocorallia Aeromonas Micromonospora Alcaligenes Alistipes Pannonibacter Dickeya Kocuria Ochrobactrum Agrococcus Gracilibacillus Chromohalobacter Yersinia Oerskovia Gallibacterium Erwinia Agromyces Filifactor Devosia Pragia Massilia Collinsella Finegoldia Phenylobacterium Methyloarcula Jonesia Pantoea Elizabethkingia Leifsonia Pseudozyma Streptosporangium Macrococcus Veillonella Sporolactobacillus Moraxella Clostridium Pandoraea Flavobacterium Halobacterium Taylorella Delftia Sinomonas Carnobacterium Myroides Exophiala Sporopachydermia Nocardiopsis Avibacterium Blautia Salmonella Weissella Herbaspirillum Ideonella Kingella Kluyvera Enterococcus Janthinobacterium Kerstersia Luteibacter Photorhabdus Proteus Arcobacter Actinobaculum Alternaria Citrobacter Dichelobacter Achromobacter Candida Ewingella Trichophyton Granulicatella Leptothrix Suttonella Dermabacter Hydrogenophaga Cellulomonas Azoarcus Trichosporon Tatumella Rhodospiridium Acidaminococcus Actinobacillus Serratia Halomonas Rhodococcus Bergeyella Malikia Actinocorallia Aeromonas Micromonospora Alcaligenes Alistipes Pannonibacter Dickeya Kocuria Ochrobactrum Agrococcus Gracilibacillus Chromohalobacter Yersinia Oerskovia Gallibacterium Erwinia Agromyces Filifactor Devosia Pragia Massilia Collinsella Finegoldia Phenylobacterium Methyloarcula Jonesia Pantoea Elizabethkingia Leifsonia Pseudozyma Streptosporangium Macrococcus Veillonella Sporolactobacillus Moraxella Clostridium Pandoraea Flavobacterium Halobacterium Taylorella Delftia Sinomonas Carnobacterium Myroides Exophiala Sporopachydermia Nocardiopsis Avibacterium Blautia Salmonella Weissella Herbaspirillum Ideonella Kingella Kluyvera Enterococcus Janthinobacterium Kerstersia Luteibacter Photorhabdus Proteus Arcobacter Actinobaculum Alternaria Citrobacter Dichelobacter Achromobacter Candida Ewingella Trichophyton Granulicatella Leptothrix Suttonella Dermabacter Hydrogenophaga Cellulomonas Azoarcus Trichosporon Tatumella Rhodospiridium Acidaminococcus Actinobacillus Serratia Sphingobacterium Mannheimia Cohnella Aggregatibacter Cronobacter Lecythophora Riemerella Chaetomium
MALDI Biotyper ® Subtyping Module Changing Microbiology For research use only. Not for use in clinical diagnostic procedures.
MALDI-TOF
Innovation with Integrity
tochange specifications without notice. Bruker © 03-2019, 1862837 Brukeris continually improving its products and reserves the right Fast Microorganism Identification Combined with Instant Typing
Over the past decade, the implementation of Bruker’s MALDI Biotyper in many microbiology labs worldwide has entirely changed microorganism identification. Its high discriminatory power permits the identification of thousands of different species, but some genera are still difficult to differentiate. Bruker has therefore developed the MBT Subtyping Module, allowing for automated differentiation of some species which are typically very difficult to distinguish.
And there’s more - the potential of MALDI-TOF mass spectrometry reaches beyond species identification and the MBT Subtyping Module is the first application exploring this potential. It combines the identification of important pathogens with automated subsequent detection of specific resistances in one automated workflow.
The principle
A prerequisite for the automated typing process is a high confidence identification of the bacterium in the MALDI Biotyper workflow. For species differentiation, the MBT Subtyping Module then looks for decisive peaks in the identified mass spectrum. For detection of specific resistances, the software searches for peaks associated with proteins related to antibiotic resistance and, if present, reports the respective bacterium as presumptive resistant. Seamless and Fast Workflow
Once the samples are directly transferred from the agar to the MALDI target plates, no additional sample preparation is required to obtain a typing result. When the bacterium has been identified, the software automatically performs the typing and result reporting.
1 2 3 4
Select an Transfer sample Create project and Spectrum instantly isolated colony directly and add start measurement matched against matrix* reference library to perform identification
6 5
Automated typing process after high confidence identification
* Only the direct transfer method should be used for resistance marker detection. Preparation procedures including extraction / washing steps risk removal of surface bound peptides / proteins. Final review and validation
DOI: 10.1128/JCM.00694-14 10.1128/JCM.00694-14 DOI:
Journal of Clinical Microbiology 2014:52(8):2804-2812. 2014:52(8):2804-2812. Microbiology Clinical of Journal
et al et ., ., Lau F. Anna
active surveillance and screening of patients. of screening and surveillance active
identification methods for laboratory testing, testing, laboratory for methods identification
not detected in time - demand efficient efficient demand - time in detected not
positive one. positive tance could spread rapidly between patients - if if - patients between rapidly spread could tance
KPC bla
This mechanism and the fact that CRKP resis- CRKP that fact the and mechanism This report this sample as a presumptive presumptive a as sample this report
spectrum. And, if present, the software will will software the present, if And, spectrum.
KPC bla related peak in the sample sample the in peak related in healthcare settings. settings. healthcare in then looks for the the for looks then
tal gene transfer, making it even more dangerous dangerous more even it making transfer, gene tal value must be ≥ 2.0. The MBT Subtyping Module Module Subtyping MBT The 2.0. ≥ be must value
- horizon by bacteria between exchanged be easily identification of the bacterium, i.e. the log(score) ID ID log(score) the i.e. bacterium, the of identification
KPC bla gene. This plasmid encoded resistance can can resistance encoded plasmid This gene. cess with the MALDI Biotyper is the successful successful the is Biotyper MALDI the with cess
- pro detection automated the for Prerequisite carbapenemase enzyme (KPC), encoded by the the by encoded (KPC), enzyme carbapenemase
K. pneumoniae pneumoniae K. by CRKP is the production of the the of production the is CRKP by
MALDI-TOF mass spectra. mass MALDI-TOF The most important mechanism of resistance resistance of mechanism important most The
peak at 11,109 m/z is clearly detectable in bacterial bacterial in detectable clearly is m/z 11,109 at peak result in high rates of morbidity and mortality. mortality. and morbidity of rates high in result
KPC bla . This specific specific This . related to the plasmid carrying carrying plasmid the to related observed, which is a major concern as infections infections as concern major a is which observed,
K. pneumoniae K. K. pneumoniae K. , , KPC-producing of spectra mass (CRKP) is is (CRKP) resistant carbapenem
et al et . (2014) discovered a peak in MALDI-TOF MALDI-TOF in peak a discovered (2014) . Lau In many countries a significant increase of of increase significant a countries many In
Enterobacteriaceae Enterobacteriaceae
KPC-producing of Detection
production, particularly in dairy cattle. dairy in particularly production,
currently of major concern in food animal animal food in concern major of currently
Surveillance and epidemiological studies are are studies epidemiological and Surveillance
of bacteria is also observed in livestock. livestock. in observed also is bacteria of
The rise of antimicrobial resistant strains strains resistant antimicrobial of rise The
nosocomial infections. infections. nosocomial
wounds or invasive devices are at great risk of of risk great at are devices invasive or wounds
where immunocompromised patients with open open with patients immunocompromised where
in hospitals, nursing homes and other facilities facilities other and homes nursing hospitals, in
Antibiotic resistant bacteria are troublesome troublesome are bacteria resistant Antibiotic
specific resistances in an automated workflow. automated an in resistances specific
MBT Subtyping Module enables fast detection of of detection fast enables Module Subtyping MBT
ated with antibiotic resistant microorganisms. The The microorganisms. resistant antibiotic with ated
- associ infections of risk the reduce to importance
prevention and control are therefore of high high of therefore are control and prevention
threat. health public global major a are Effective Effective
Antibiotic resistant bacteria are on the rise and and rise the on are bacteria resistant Antibiotic
Detection with MALDI Biotyper MALDI with Detection
Marker Resistance Instant
Results can easily be exported in a structured report, see details for positions A1 to A5. A5. to A1 positions for details see report, structured a in exported be easily can Results
column. column.
related peak in the Subtype Subtype the in peak related
KPC bla the detection of the the of detection the
with display of the result of of result the of display with
Enterobacteriaceae , , of run
Example of an identification identification an of Example
Serratia marcescens Serratia
Klebsiella variicola Klebsiella
12000 0 1150 11000 10500 10000 9500 9000
m/z 0 Klebsiella pneumoniae Klebsiella
Klebsiella oxytoca Klebsiella
Klebsiella aerogenes Klebsiella
Escherichia coli Escherichia
2000
Enterobacter ludwigii ludwigii Enterobacter
Enterobacter kobei Enterobacter
Enterobacter cloacae Enterobacter
Enterobacter asburiae Enterobacter
4000
Enterobacter aerogenes Enterobacter
Citrobacter freundii Citrobacter
ESBL (negative control) (negative ESBL
extended to the following species: following the to extended 6000
tive presence of KPC has been been has KPC of presence tive KPC bla related peak related with
[au]
the automated check for presump for check automated the -
Intens.
Spectra of Klebsiella pneumoniae pneumoniae Klebsiella of Spectra
Klebsiella pneumoniae Klebsiella producing producing , ,
KPC bla related peak in KPC- in peak related of the of
implemented automated detection detection automated implemented In addition to the already previously previously already the to addition In MRSA Subtyping
MRSA (Methicillin-Resistant Staphylococcus aureus) strains are genetically distinct from other strains of Staphylococcus aureus, and show multiple drug resistance to beta-lactam antibiotics.
Staphyloccocus aureus
As with the Enterobacteriaceae, successful iden- PSM-mec is variable, depending on regional tification of Staph. aureus is the prerequisite for epidemiology. Absence of this peak does not the subsequent resistance subtyping process. mean that the respective strain is not an MRSA, For Staph. aureus the module looks for identifica- but, if detected, it can be reliably considered as tion of the PSM-mec peak. PSM-mec is a sur- an MRSA positivity alert. face peptide and the proportion of MRSA with
Result report for Staph. aureus identification with indication of the presence of the PSM-mec peptide. Note that there is no indication for the ID with score value < 2.00. Bacteroides fragilis cfiA Subtyping
B. fragilis is the most frequently isolated anaerobic After successful identification, the MBT Subtyp- pathogen. Carbapenem resistance in B. fragilis ing Module looks for specific peaks associated is frequently associated with presence of the with the protein expressed by B. fragilis cfiA gene encoding for a metallo-beta-lactamase cfiA positive strains. If present, the best match conferring resistance to nearly all beta-lactam for the respective sample will be reported as a antibiotics. As a result, infections with B. fragilis presumptive cfiA positive strain. cfiA positive strains are difficult to treat.
Subtyping B. fragilis result table
Identification results for B. fragilis with indication of cfiA status for the best match
An Early Warning System
The MBT Subtyping Module quickly detects blaKPC expressing Enterobacteriaceae, PSM-mec car- rying MRSA and cfiA positive B. fragilis strains. Please note that negative results do not necessarily mean that these strains are susceptible but will require additional confirmation methods. Accurate Differentiation of Mycobacterium chimaera from Mycobacterium intracellulare
Mycobacterium chimaera very rarely causes Conventional identification methods suffer from infections in humans, but there have been recent the same limitation. reports about contamination of medical equip- ment used in heart surgery. There is a risk that After successful identification of the heater-cooler units used in open-heart surgery M. chimaera/intracellulare complex by may be contaminated with M. chimaera and the MALDI Biotyper, application of the MBT that exposure of patients to these units in the Subtyping Module allows - for the first time - operating theatre might lead to infections that fast and accurate differentiation of both species can appear months to years after surgery. Most by thorough comparison of characteristic mass reported infections are those of prosthetic valves spectrum peaks as described by Pranada et al. or vascular grafts. (2017). This differentiation will support further insights into the pathogenic role of M. chimaera Routine identification using MALDI-TOF mass and can contribute to epidemiological studies spectrometry is restricted to the identification of which might improve infection control in future. the M. chimaera/intracellulare complex because mass spectra of both species are very similar. Note: Prerequisite for the differentiation is the installed MBT Mycobacteria library version 4.0 or higher.
Result report of M. chimaera / intracellulare complex differentiation
Arthur B. Pranada et al., J Med Microbiol 2017:66:670-677. DOI: https://dx.doi.org/10.1099/jmm.0.000469
Elizabethkingia species differentiation species of report Result
in the Subtype column. Subtype the in
species differentiation result listed listed result differentiation species
Elizabethkingia species, with the the with species,
Example of an identification run of of run identification an of Example
species output. species
automatically activated to start searching for characteristic mass spectrum peaks and will generate a a generate will and peaks spectrum mass characteristic for searching start to activated automatically
Elizabethkingia After successful identification of one of the the of one of identification successful After species, the MBT Subtyping Module is is Module Subtyping MBT the species,
Subtyping Module. Subtyping
Elizabethkingia species has been further strengthened by another application of the MBT MBT the of application another by strengthened further been has species known three
In addition to recent improvements of the MALDI Biotyper reference library, the differentiation of the the of differentiation the library, reference Biotyper MALDI the of improvements recent to addition In
Elizabethkingia may vary depending on the species, identification to species level is desirable. desirable. is level species to identification species, the on depending vary may of
pathogen for which outbreaks have been reported over the last years. As the antimicrobial susceptibility susceptibility antimicrobial the As years. last the over reported been have outbreaks which for pathogen
E. anophelis E. anopheli E. miricola E. s, the latter has been described in 2011 only. only. 2011 in described been has latter the s, and is an emerging emerging an is
E. meningoseptica, meningoseptica, E. Elizabethkingia covers mainly three very difficult to distinguish species: distinguish to difficult very three mainly covers genus The
Elizabethkingia Species Differentiation Species
and risk managers. risk and
Listeria Listeria monocytogenes L. species is of great importance for food business operators operators business food for importance great of is species other from
Listeria Listeria spp. are widespread in the environment. Clear differentiation of the pathogenic pathogenic the of differentiation Clear environment. the in widespread are spp.
weakened immune systems are affected by this life-threatening infection. life-threatening this by affected are systems immune weakened
listeriosis. Particularly pregnant women and their newborns, adults aged 65 or older, and people with people and older, or 65 aged adults newborns, their and women pregnant Particularly listeriosis.
Listeria monocytogenes Listeria is a very important foodborne pathogen causing potentially fatal potentially causing pathogen foodborne important very a is Worldwide,
Differentiation
Listeria monocytogenes monocytogenes Listeria Facilitating Facilitating
labor-intensive workflows. workflows. labor-intensive plates (Certificate 2017LR75) (Certificate plates
Listeria monocytogenes Listeria direct sample transfer methods instead of more more of instead methods transfer sample direct agar various from
Listeria spp. Listeria bioinformatics. This allows easy-to-apply and fast fast and easy-to-apply allows This bioinformatics. and and of confirmation the for
reference spectra is performed by sophisticated sophisticated by performed is spectra reference MicroVal by validated method 16140-6 ISO the •
Listeria Listeria of the sample mass spectrum with the the with spectrum mass sample the of other gram-positive organisms gram-positive other
Listeria spp. Listeria monocytogenes Listeria With the MBT Subtyping Module comparison comparison Module Subtyping MBT the With and , and
confirmation and identification of of identification and confirmation
Module into the identification workflow. identification the into Module the for method #2017.10 AOAC-OMA the •
as it can be by implementing the MBT Subtyping Subtyping MBT the implementing by be can it as of the bioinformatics of of bioinformatics the of
cies. Additionally, differentiation is now as easy easy as now is differentiation Additionally, cies. The MBT Subtyping Module is an essential part part essential an is Module Subtyping MBT The
- spe new of addition the and evolution nomical
- taxo the with Library Reference Biotyper MALDI mal effort. mal
teomic levels. Bruker is continuously updating the the updating continuously is Bruker levels. teomic - mini with culture from directly workflow routine
L. monocytogenes L. - pro and genetic on relationships species close in the daily daily the in on testing ment
Listeria identification is challenging because of of because challenging is identification - imple to laboratories QC food e.g. enables This Order Information
Part-No. 1842250 The MBT Subtyping Module enables the automated detection of strain specific characteristics.
MBT Compass software (Part-No. 1843241) is prerequisite for the use of the MBT Subtyping Module.
Differentiation of Mycobacterium chimaera from M. intracellulare needs an installed MBT Mycobacteria library version 4.0 or higher.
.
MALDI Biotyper® is a registered trademark of Bruker Daltonik GmbH in the European Union, Japan and the USA.
Bruker Daltonik GmbH Bruker Scientific LLC Bremen · Germany Billerica, MA · USA Phone +49 (0) 421-2205-0 Phone +1 (978) 663-3660
[email protected] tochange specifications without notice. Bruker © 03-2019, 1862837 www.bruker.com/microbiology Brukeris continually improving its products and reserves the right