PathoGenetix and Applied Maths Sign Agreement
News Jun 27, 2013
PathoGenetix, Inc. and Applied Maths, NV have signed an agreement to link the RESOLUTION Microbial Genotyping System with the BioNumerics software suite to offer a dramatically improved time-to-answer and shortened decision making time in pathogen outbreak investigations, traceback and epidemiological response.
The fully automated and integrated solution will confirm and identify pathogens in complex mixtures in just five hours, allow rapid sharing of outbreak information among public health and food safety laboratories, and enable comparison to strain data from other typing systems such as pulsed field gel electrophoresis (PFGE).
PathoGenetix, Inc., developer of an automated system for rapid bacterial identification, and Applied Maths, NV, a leader in bioinformatics and analytical solutions for public health and research laboratories, have signed a collaborative agreement to integrate the RESOLUTION™ Microbial Genotyping System with the BioNumerics™ software suite.
The end-to-end automated solution will integrate rapid pathogen strain typing with advanced data management and networking tools, and enable sharing and comparison of outbreak strain data among public health or food safety testing labs.
The collaboration also will enable serotype and strain type information generated by the RESOLUTION System to be compared to data sets generated by other identification methods such as pulsed field gel electrophoresis (PFGE) or whole genome sequencing (WGS).
PathoGenetix’s RESOLUTION System is based on Genome Sequence Scanning™ (GSS™) technology initially developed to detect bio-threat pathogens in environmental samples.
This breakthrough genotyping technology isolates and analyzes microbial DNA directly from complex mixtures, without the need for a pure culture.
Rapid throughput scanning and proprietary software generate genomic barcodes based on the underlying sequence, and compare them to an onboard database to provide molecular serotype and strain type information for all target bacteria present in the sample at detectable levels.
The typing resolution is comparable to PFGE, the current standard for pathogen identification in foodborne illness outbreak investigations.
The RESOLUTION System’s ability to work from a mixed sample could enable it to provide critical strain information in a culture independent diagnostics environment.
“The RESOLUTION System with BioNumerics software will offer public health and food testing labs the ability to seamlessly integrate, curate and compare new outbreak strain information with their existing PFGE and whole genome sequence data sets,” said PathoGenetix president Ann Merrifield.
“With time-to-results reduced to just five hours, and a seamless connection to existing strain databases and laboratory tools, we can shorten outbreak investigation and response, and improve public health,” Merrifield said.
Applied Maths’ BioNumerics is a turnkey software suite for integrative biological data management and comparative analysis that includes data mining, clustering, identification and statistical applications.
BioNumerics software is currently in use in thousands of public and private research sites and laboratories worldwide, and is the cornerstone for numerous national and international research projects and epidemiological surveillance networks.
“We’re excited to work with PathoGenetix to link its breakthrough microbial identification technology with the BioNumerics software suite,” said Koen Janssens, chief executive officer of Applied Maths. “By working directly from a complex sample rather than a cultured isolate, and by automating pathogen identification from sample preparation to data analysis, our integrated solution will simplify laboratory workflows and dramatically reduce the time required to identify pathogenic organisms in epidemiological investigations.”
The architecture of each person’s brain is unique, and differences may influence how quickly people can complete various cognitive tasks.o learn more, scientists are developing a new tool — computational models of the brain — to simulate how the structure of the brain may impact brain activity and, ultimately, human behavior.READ MORE