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MALDI-TOF Autof ms 1000

Autof ms 1000

A Revolution in Microbiology

Identification of microorganisms to the species level is the principle objective in Microbiology1. For many years, such a feat has been accomplished through laborious biochemical assays. While advancements in nucleic acid sequencing technologies have enabled highly specific detection rates of microorganisms, these technologies are too time-consuming and costly to be commonplace2.

Hardy Diagnostics is proud to introduce

The Autof ms 1000*

The Autof ms 1000 provides automated, high-speed and high-confidence identification and taxonomical laser-induced classification of bacteria, yeasts, fungi, and filamentous fungi based on proteomic fingerprinting. Numerous studies have demonstrated the higher accuracy, faster time-to-result, and lower cost provided by MALDI-TOF technology when compared to classical methods3,4,5.

Features:

  • Faster time-to-result when compared to conventional methods and PCR6
  • Accuracy similar to nucleic acid sequencing technologies7
  • Cost effective8
  • Robust, intuitive software, supporting 21 CFR part 11
  • Installation Qualification/Operation Qualification-Performance Verification support
  • LIMS/LIS connectivity and support
  • Database of approximately 5,000 species created with over 15,000 strains
  • Can identify 96 samples in less than 20 minutes hands-on time

*Autof ms 1000 is manufactured
by Autobio Diagnostics Co. LTD. for Hardy Diagnostics

*For Research Use Only. Not for use in clinical diagnostic procedures.

Overview

Principle of MALDI-TOF

Mass Spectrometry is an analytical technique that ionizes—facilitates phase transition from solution to gas—molecules to assume transient electrical charges. The molecule’s mass (m) to charge (z) ratio (m/z) is measured, and a molecular weight can be ascertained1,2. Mass Spectrometry was limited in application to chemical compounds, but the advent of MALDI-TOF technology has increased the breadth of suitability to render the analysis of macromolecules, such as proteins, a possible feat2. MALDI (Matrix-Assisted Laser Desorption/Ionization) technology is a method of “soft ionization,” which minimizes the degree of molecular fragmentation and preserves sample integrity. Applications in proteomics research have paved the way for MALDI-TOF’s zenith: Microbial Identification.

Microbial samples are prepared by mixing with a solution of matrix (CHCA – α-Cyano-4-hydroxycinnamic acid), an organic compound capable of absorbing ultraviolet light (N2 laser light, λ = 337 nm) and converting the UV light to heat energy, and introduced into a high vacuum environment. When the matrix and sample are added together and allowed to dry, the mixture crystallizes, entrapping the sample in the same lamellar crystal. Laser irradiation of the mixture causes rapid heating of the matrix, which transitions into a gaseous state along with the microbial proteins. Gaseous-state peptides are converted to ions, electrically charged particles, through proton transfer with the matrix2. The protonated ions are accelerated through an electrical field and separated by a voltage potential (V0) difference on the basis of each ion’s mass-to-charge (m/z) ratio. The acceleration of ions through the flight tube takes place in a high-vacuum environment to ensure the ions obtain free flight to the mass analyzer (detector). The ions can then be detected by the MALDI-TOF ms to determine their respective molecular weights (Da).

References

1. Olshina, M. A., & Sharon, M. (2016). Mass Spectrometry: A Technique of Many Faces. Quarterly reviews of biophysics49, e18. https://doi.org/10.1017/S0033583516000160

2. Singhal, N., Kumar, M., Kanaujia, P. K., & Virdi, J. S. (2015). MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Frontiers in microbiology6, 791. https://doi.org/10.3389/fmicb.2015.00791

Database

The Autof ms 1000 has the most expansive database in the industry.
Created with more than 15,000 strains, each with more than 5 reference spectra, averaging more than 10 strains per species,
the database of the Autof ms 1000 provides highly accurate results.

 

Local database includes a total of 1,003 Genus, 4,943 Species, and 15,993 Strains.

Gram +

Gram –

Yeast

Filamentous_Fungi-crop

Filamentous Fungi

Mycobacteria-crop

Mycobacteria

As part of the parnership, Hardy Diagnostics and Autobio Diagnostics Co. LTD. is constantly augmenting the Autof ms 1000 database. New strains and species are constantly being added, improving upon the reliability and accuracy of the system.

The Autof ms 1000 database contains a multitude of reference strains from:

Varying geographic regions of the world

Different specimens

Different culture media types

Different growth conditions

 

Criteria that captures the natural phylogenetic diversity within a species

Workflow

The Autof ms 1000 workflow requires minimal hands-on time

Single Workflow

The Autof ms 1000 workflow has been designed to be efficient, easy, and applicable for any isolate, whether it be bacteria, yeasts, or molds. The minimal hands-on time required to prepare each isolate allows preparation, acquisition, and data analysis of a total 96-cell sample target plate in under 20 minutes.

    • Unique Rapid Identification function displays a test result in 0.1 seconds for a single sample
    • Average identification (acquisition and data analysis) time for 96 samples is 17.5 minutes
    • Batch function available to edit and identify samples in a fully customizable format
    •  Access to LIMS/LIS system. Reports release automatically

No prior experience with mass spectrometry required!

Intuitive Software

Easy-to-use software provides a friendly user experience. The Autof acquirer has been designed to comply with the rigors and standards of a regulated working environment.

    • Authentication
    • User management
    • Data archiving
    • Audit trail, including timestamps

The Autof Acquirer automates the entire process from spectral acquisition to report generation. Reports include a summary of sample locations, names, descriptions, and confidence scores.

The results are presented in an easy-to-read, color-coded scheme that make for simple interpretations.

Autof ms 1000 results can be exported in a format that a LIMS can easily read.

Data can be downloaded as an EXCEL, TXT, or other file format for further analysis.

Laboratories that need to create their own local database can do so in a companion software application.

Technical Specifications

Sample Target Slide
96 cell stainless steel target slide with reusable magnetic holder

Sample In/Out
Fully automated sample introduction mechanism
Target Slide Platform is an X-Y stage controlled by a stepper linear actuator
Stepper linear actuator produces 5 μm with each step (10 μm repeatability) for precise target slide positioning

Ion Source
Matrix-Assisted Laser Desorption/Ionization
Cleaning-free ion source
Delayed-extraction technology: 0 ~ 1000 ns
Variable ion source voltage: 0 ~ +20 kV

Detector
Typical multiplier gain 106 at 2800kV
Pulse width for a single ion event (FWHM): <2.35 ns
Peak current output for linear operations: 10 mA

Vacuum
Mechanical Pump and Turbomolecular Pump establish up to a 10-7 mbar vacuum

Mass resolution
1) Single protein

Angiotensinogen: m/z= 1760.01 (M+H)+, mass resolution ≥3600
Cytochrome C: m/z= 12362.96 (M+H)+, mass resolution ≥800

2) Mixed protein
Insulin: m/z= 5808.57 (M+H)+, mass resolution ≥400
Myoglobin M2+: m/z= 8477.14 (M+2H)2+, mass resolution ≥600
Cytochrome C: m/z= 12362.96 (M+H)+, mass resolution ≥700

Dimensions
Height: 1250mm
Depth: 705mm
Width: 450mm
Weight: 101kg

Sample Viewing system
Monochromatic CCD camera provides real-time video feed of the sample
Footage feed on display in the Sample Viewing Area from the software interface

Laser
337 nm Nitrogen laser, fixed focus, 400 million shots (10-year average life expectancy)
Pulse width: 2.5 ns
Frequency: 1-60 Hz, adjustable

Mass Analyzer
Linear Flight Tube: 1050 mm

Filter
0.01 μm high precision filter – 99.99% of pathogenic microorganisms are filtered after processing

Performance Data

Frequently Asked Questions

What are the limitations of MALDI-TOF ms applications?

Due to the close genetic relationship between some microbial species and among some microbial complex groups, when using MALDI TOF mass spectrometry, the identification results may be prone to errors1. Additional confirmatory assays are required in such situations. The Autof ms 1000 has been designed to alert end-users when additional confirmatory measures are required.

The following table is an exposition of some error-prone species/complexes when utilizing MALDI-TOF ms technology.

Can MALDI-TOF ms detect viruses?

The process for viral detection by MALDI-TOF mass spectrometry is more complicated than that of bacteria and fungi13. There are two main methods: (1) Protein detection, which is to identify the characteristic proteins of the virions in the mass spectra directly from a cell culture (currently no such database exists for Autof ms 1000; users must build by themselves); (2) Nucleic acid molecule detection: this method is mainly based on the combination of multiplex PCR and mass spectrometry. The principle is to first enrich the viral nucleic acid material by PCR, then add specific primers for the virus to be detected, and realize single-base extension through sequence-specific primers to obtain product fragments, which can be detected on mass spectrometry after desalting. The method can be used for the detection of respiratory viruses, influenza viruses, enteroviruses, human papilloma viruses, etc., and has the advantages of high throughput, low cost, and high sensitivity14.

What is the process for Quality Control of the Autof ms 1000?

Note: Please calibrate the Autof ms 1000 before performing quality control. Quality control should be carried out once a week. The results of the quality control report should be printed and archived.

What is the Limit of Detection (LoD) for analysis by Autof ms 1000 MALDI-TOF?

105 to 106 sample / target

What are the advantages and disadvantages of MALDI TOF ms technology compared with other microbial detection methods?

Table reference14

References

1. Rychert, J. (2019, July 02). Benefits and limitations of MALDI-TOF mass Spectrometry for the identification of microorganisms. Retrieved March 25, 2021, from https://www.infectiologyjournal.com/articles/benefits-and-limitations-of-malditof-mass-spectrometry-for-the-identification-of-microorganisms.html

2. Paauw, A., Jonker, D., Roeselers, G., Heng, J. M., Mars-Groenendijk, R. H., Trip, H., Molhoek, E. M., Jansen, H. J., van der Plas, J., de Jong, A. L., Majchrzykiewicz-Koehorst, J. A., & Speksnijder, A. G. (2015). Rapid and reliable discrimination between Shigella species and Escherichia coli using MALDI-TOF mass spectrometryInternational journal of medical microbiology : IJMM305(4-5), 446–452. https://doi.org/10.1016/j.ijmm.2015.04.001

3. Wong, K., Dhaliwal, S., Bilawka, J., Srigley, J. A., Champagne, S., Romney, M. G., Tilley, P., Sadarangani, M., Zlosnik, J., & Chilvers, M. A. (2020). Matrix-assisted laser desorption/ionization time-of-flight MS for the accurate identification of Burkholderia cepacia complex and Burkholderia gladioli in the clinical microbiology laboratory. Journal of medical microbiology69(8), 1105–1113. https://doi.org/10.1099/jmm.0.001223

4. Garrigos, T., Neuwirth, C., Chapuis, A., Bador, J., Amoureux, L., & Collaborators (2021). Development of a database for the rapid and accurate routine identification of Achromobacter species by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases27(1), 126.e1–126.e5. https://doi.org/10.1016/j.cmi.2020.03.031

5. Hong, E., Bakhalek, Y., & Taha, M. K. (2019). Identification of Neisseria meningitidis by MALDI-TOF MS may not be reliableClinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases25(6), 717–722. https://doi.org/10.1016/j.cmi.2018.09.015

6. Shell, W. S., Sayed, M. L., Allah, F., Gamal, F., Khedr, A. A., Samy, A. A., & Ali, A. (2017). Matrix-assisted laser desorption-ionization-time-of-flight mass spectrometry as a reliable proteomic method for characterization of Escherichia coli and Salmonella isolates. Veterinary world10(9), 1083–1093. https://doi.org/10.14202/vetworld.2017.1083-1093

7. Pavlovic, M., Konrad, R., Iwobi, A. N., Sing, A., Busch, U., & Huber, I. (2012). A dual approach employing MALDI-TOF MS and real-time PCR for fast species identification within the Enterobacter cloacae complexFEMS microbiology letters328(1), 46–53. https://doi.org/10.1111/j.1574-6968.2011.02479.x

8. Karger, A., Stock, R., Ziller, M. et al. Rapid identification of Burkholderia mallei and Burkholderia pseudomalleiby intact cell Matrix-assisted Laser Desorption/Ionisation mass spectrometric typingBMC Microbiol 12, 229 (2012). https://doi.org/10.1186/1471-2180-12-229

9. Rychert, J. (2019, July 02). Benefits and limitations of MALDI-TOF mass Spectrometry for the identification of microorganisms. Retrieved March 25, 2021, from https://www.infectiologyjournal.com/articles/benefits-and-limitations-of-malditof-mass-spectrometry-for-the-identification-of-microorganisms.html

10. Jeong, S., Hong, J. S., Kim, J. O., Kim, K. H., Lee, W., Bae, I. K., Lee, K., & Jeong, S. H. (2016). Identification of Acinetobacter Species Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry. Annals of laboratory medicine36(4), 325–334. https://doi.org/10.3343/alm.2016.36.4.325

11. Vávrová, A., Balážová, T., Sedláček, I., Tvrzová, L., & Šedo, O. (2015). Evaluation of the MALDI-TOF MS profiling for identification of newly described Aeromonas spp. Folia microbiologica60(5), 375–383. https://doi.org/10.1007/s12223-014-0369-4

12. De Lappe, N., Lee, C., O’Connor, J., & Cormican, M. (2014). Misidentification of Listeria monocytogenes by the Vitek 2 system. Journal of clinical microbiology52(9), 3494–3495. https://doi.org/10.1128/JCM.01725-14

13. Majchrzykiewicz-Koehorst, J. A., Heikens, E., Trip, H., Hulst, A. G., de Jong, A. L., Viveen, M. C., Sedee, N. J., van der Plas, J., Coenjaerts, F. E., & Paauw, A. (2015). Rapid and generic identification of influenza A and other respiratory viruses with mass spectrometry. Journal of virological methods213, 75–83. https://doi.org/10.1016/j.jviromet.2014.11.014

14. Singhal, N., Kumar, M., Kanaujia, P. K., & Virdi, J. S. (2015). MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Frontiers in microbiology6, 791. https://doi.org/10.3389/fmicb.2015.00791

15. Buchan, B. W., & Ledeboer, N. A. (2014). Emerging technologies for the clinical microbiology laboratory. Clinical microbiology reviews27(4), 783–822. https://doi.org/10.1128/CMR.00003-14

16. Rychert, J. (2019, July 02). Benefits and limitations of MALDI-TOF mass Spectrometry for the identification of microorganisms. Retrieved March 25, 2021, from https://www.infectiologyjournal.com/articles/benefits-and-limitations-of-malditof-mass-spectrometry-for-the-identification-of-microorganisms.html

17. Liu, H., Du, Z., Wang, J., & Yang, R. (2007). Universal sample preparation method for characterization of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry. Applied and environmental microbiology73(6), 1899–1907. https://doi.org/10.1128/AEM.02391-06

18. Singhal, N., Kumar, M., Kanaujia, P. K., & Virdi, J. S. (2015). MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis. Frontiers in microbiology6, 791. https://doi.org/10.3389/fmicb.2015.00791


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References

1. Baron EJ. Classification. In: Baron S, editor. Medical Microbiology. 4th edition. Galveston (TX): University of Texas Medical Branch at Galveston; 1996. Chapter 3. Available from: https://www.ncbi.nlm.nih.gov/books/NBK8406/

2. Deng, J., Fu, L., Wang, R., Yu, N., Ding, X., Jiang, L., Fang, Y., Jiang, C., Lin, L., Wang, Y., & Che, X. (2014). Comparison of MALDI-TOF MS, gene sequencing and the Vitek 2 for identification of seventy-three clinical isolates of enteropathogensJournal of thoracic disease6(5), 539–544. https://doi.org/10.3978/j.issn.2072-1439.2014.02.20

3. Florio, W., Tavanti, A., Barnini, S., Ghelardi, E., & Lupetti, A. (2018). Recent Advances and Ongoing Challenges in the Diagnosis of Microbial Infections by MALDI-TOF Mass SpectrometryFrontiers in microbiology9, 1097. https://doi.org/10.3389/fmicb.2018.01097

4. Xu, S., Zhou, C., Zhang, P., Feng, C., Zhang, T., Sun, Z., Zhuang, H., Chen, H., Chang, Q., Jiang, R., Li, H., & Ni, Y. (2020). Diagnostic Performance of MALDI-TOF MS Compared to Conventional Microbiological Cultures in Patients with Suspected EndophthalmitisOcular immunology and inflammation28(3), 483–490. https://doi.org/10.1080/09273948.2019.1583346

5. Patel, T. S., Kaakeh, R., Nagel, J. L., Newton, D. W., & Stevenson, J. G. (2016). Cost Analysis of Implementing Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Plus Real-Time Antimicrobial Stewardship Intervention for Bloodstream Infections. Journal of clinical microbiology55(1), 60–67. https://doi.org/10.1128/JCM.01452-16

6. Xu, S., Zhou, C., Zhang, P., Feng, C., Zhang, T., Sun, Z., Zhuang, H., Chen, H., Chang, Q., Jiang, R., Li, H., & Ni, Y. (2020). Diagnostic Performance of MALDI-TOF MS Compared to Conventional Microbiological Cultures in Patients with Suspected Endophthalmitis. Ocular immunology and inflammation28(3), 483–490. https://doi.org/10.1080/09273948.2019.1583346

7. Florio, W., Tavanti, A., Barnini, S., Ghelardi, E., & Lupetti, A. (2018). Recent Advances and Ongoing Challenges in the Diagnosis of Microbial Infections by MALDI-TOF Mass SpectrometryFrontiers in microbiology9, 1097. https://doi.org/10.3389/fmicb.2018.01097

8. Patel, T. S., Kaakeh, R., Nagel, J. L., Newton, D. W., & Stevenson, J. G. (2016). Cost Analysis of Implementing Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Plus Real-Time Antimicrobial Stewardship Intervention for Bloodstream Infections. Journal of clinical microbiology55(1), 60–67. https://doi.org/10.1128/JCM.01452-16