Intro

Welcome to the proteome2pathogen web application developed by TNO and HORAIZON technology bv. This application is being developed to enable reliable identification of microorganisms, potentially causing human infectious disease. The identification is based on analysis of the bacterial proteome.

A complex task in microbiology is to be able to unravel the causative agent, especially if it may not be one of the most usual suspects of a particular infection. Furthermore, for some bacteria discrimination between species is cumbersome with existing conventional methods. TNO is developing an alternative methodology to assist in reliable identification of pathogens. By using proteomic liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and the proteome2pathogen web application, unreliable, incorrect or uncertain results are becoming a thing of the past.

The developed web application relies on a two-step workflow: a genus-level search followed by a species-level search. This strategy enables the rapid identification of microorganisms based on the analyzed proteome. Thus far, this method has mainly been validated using bacteria from simulated blood culture flasks (Berendsen et al. IJMM, 2019, Berendsen et al. Future Micro. 2017). The list of microorganisms in the database can be found in our publication (Berendsen et al. IJMM, 2019). Proteomes from bacterial colonies derived from agar-plates are also suited for analyses. Future releases of the webtool will include antimicrobial resistance detection.

Details of the method are described in the web application itself and in our recent published paper (Berendsen et al. IJMM, 2019). We hope you will find the app. useful and it will help you to identify your bacteria of interest accurately.

Best regards from, TNO and HORAIZON technology bv.

Disclaimer: The use of the proteome2pathogen is at own risk; The tool is for research purposes only; TNO and HORAIZON do not accept any liability to any disadvantage or damage that use of the proteome2pathogen app may cause.

Proteomics

High-end proteome analytical tools are realizing a quantum leap in medical diagnostics. The potential of these tools is also demonstrated for microbiological diagnostics. Whereas several technologies are being applied for genomic analyses, proteomics offer additional and largely complementary information. Having a high feasibility for automation, robust proteome analyzers have a huge potential to become used routinely for microbiology diagnostic purposes. The challenge is to create easy-to-use instruments and accompanying software. Creating methods with a fixed number of procedures and integrated data algorithms for the analysis of the MS-data tailored to the diagnostic questions relevant for clinical microbiology diagnostics are likely to be the next game changer in this area.

Current analyzers are able to rapidly assess the proteome in a sample. With a few developmental steps in the field of simplification and standardization, introduction in clinical microbiology is only hampered by the lack of automated data interpretation. Until now proteome analysis of micro-organisms is cumbersome because existing data analysis software is developed from the premise that the proteome of one particular type of eukaryotic cell is studied. Therefore, it was our goal to realize a microbiology tuned proteome interpreter. To help you interpret complex microbiologic proteomics data and provide trustworthy answers to the (research) question that preceded the analysis. Our first achievement is the developed web application on this website, which is tailored to identify human bacterial pathogens. We can imagine that a similar approach in other fields of microbiology (e.g. food-, water-, plant-microbiology or contamination control) precise identification of bacteria can be crucial, as well. Or you may have another research question or application in mind, which can perhaps be analyzed with a similar proteomic analysis approach. TNO and HORAIZON are open to all types of collaborations and / or co-developing project in the field of proteomics and identification of micro-organisms.

Background

TNO

TNO connects people and knowledge to create innovations that boost the sustainable competitive strength of industry and well-being of society. This is our mission and it is what drives us, the 2,600 professionals at TNO, in our work every day.

Department CBRN protection

Within the Defense, Safety and Security field of TNO a dedicated department focuses on Chemical, Biological, Radiological and Nuclear (CBRN) Protection. Regarding Biological protection TNO offers support in the procurement, development and evaluation of biological detection and identification systems. Facilities at TNO enables validation of identifications systems of all types of bacteria varying from environmental to highly pathogenic bacteria. Next, ongoing research projects are focused on improving diagnostics of (highly) pathogenic microorganisms using mass-spectrometry and other innovative approaches.

HORAIZON bv.

We simplify the complexity of biomedical analytics and build models that make data-driven decisions in minutes, not months. We provide specialized technical know-how and tools to model, integrate, cleanse, prepare, analyze and visualize big biomedical data. HORAIZON has developed a portfolio of state-of-the-art machine learning techniques that allow highly efficient, parallelized analysis of the data in cloud environment and visualization of the results.

From developing personalized treatment strategies to solving complex business problems, we believe that the world’s most challenging issues can be solved with data. Get in touch with us to discover how our predictive models can add value to your business.

Contact Us

This proteome2pathogen web application is a test version and perhaps particular pathogens might be missing which should be included in the database. If detected it would be appreciated to e-mail us the name of the missing species names and a link to the annotated genome sequence.

Next, we are curious to your experiences as a user.

proteome2pathogen@gmail.com

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