Early and Accurate Categorization and Identification of the Pathogen Infection
The detection of pathogens is important to the prevention and identification of health problems and for a better lifestyle. The growth of this market is chiefly credited to the high prevalence of infectious diseases, technological advances, growing concern for safety; government initiatives, bioterrorism surveillance and high healthcare expenditure are expected to provide the required impetus for the growth of this market (Persistence Market Research, 2020).
Most rapid pathogen detection methods, PCR amplification or microarrays, rely on prior exact sequence knowledge of the potential pathogen and other detection methods rely on the ability to cultivate the pathogen (microbial cultures). In many cases both are not available or possible.
A novel approach for pathogen identification, overcoming the requirement for cultivation and the prior exact sequence of the pathogen, was developed.
This three step approach includes:
• alignment of short-RNA reads, generated by deep sequencing, against the human reference genome;
• subtraction and assembly of the remaining unmapped reads; and,
• categorization and identification of the pathogen infection based on nucleic acid databases.
Our method proves to be a useful tool for both sample contamination detection and pathogen identification using a calculated and cost-effective sample preparation and an easily-implemented computational pipeline appropriate for all types of current sequencing platforms. We envision early and accurate detection of pathogen infection using short RNA reads to accelerate.
Rapid pathogen detection in hospitals includes detection of bacteria, viruses, fungi and parasites. Since in some settings, or with particular patients, these infections are life threatening the potential applications and clinical relevance is immense. For example, immuno-suppressed bone marrow transplantation patients are constantly monitored for potential infections. Similarly, neonatal wards are at a continuous risk of being infected and transmitted between the newborns.
We have run our detection algorithm on a set of virus and bacterial infections in cells lines. We have tested our method on clinical samples derived from patients. We have tested several preparation protocols and several deep sequencing platforms. We have rewritten the algorithm to detect minute amounts of reads and to score them for advanced processing.
Patent application filed by Ramot in the EU and China.
Isakov O, Modai S, Shomron N. Pathogen detection using short-RNA deep sequencing subtraction and assembly. Bioinformatics. 2011 Aug 1;27(15):2027-30.
Isakov O, Ronen R, Kovarsky J, Gabay A, Gan I, Modai S, Shomron N. Novel insight into the non-coding repertoire through deep sequencing analysis. Nucleic Acids Res. 2012 Jun;40(11):e86.