Mutation “Fitness” as Key to Interrupting Viral Adaptation and Other Uses of CirSeq Data Analysis

 

A computational systems biology approach to virus-host circuitry aimed at discovering drug-able pathways in strand-specific viral adaptation to host is shedding light on new discovery methods and tools that can accelerate precision targeting of specialized conditions.

One of the major challenges in interrupting infection, especially when caused by RNA viruses,  is it’s rapid mutation rate, type of mutation and their effect on protein-protein interaction (PPI) and post translational modification (PTM). This mutation rate is significantly higher than NGS error rate, thus limiting our ability to reliably identify many of the mutating regions. CirSeq (2) is a novel technique that circularizes the viral RNA reads and uses a consensus method to verify mutations.

 

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mutationfitnesscirseq2

Applying this novel method to viral mutations, using computational tools and visualization methods, in-depth studies of drug-able pathways and interruption of viral adaptation or replication are possible and present new opportunities to study viruses as well as mutation-related diseases such as cancer. In cancer, a similar approach could be used as a measurement for classifying cancer sub-types and even quantifying it’s relative “aggressiveness”.

To commercialize this technology and discover it’s full potential, Pine Biotech is collaborating with leading research teams providing access to comprehensive computational tools and resources,  expert assistance and a visual interface that brings together different data outputs. Our main goal is to provide a flexible and user-friendly interface and a visual discovery environment where computational output is mapped on graphical representations of mutations and 3D structures they affect.

 

 

The virology tools are delivered in the context of a broader systems biology platform so that insight from initial output can be taken into other sections such as proteomics, structural biology and other data mining tools.

 

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We are excited to learn more about applications of the CirSeq method and analysis tools that can enhance our ability to gain deeper biological understanding and develop practical tools that will advance personalized treatment and prevention. We invite collaboration and partnerships, please reach out to us and schedule a demo and a discussion of your project.

  1. http://www.ncbi.nlm.nih.gov/pubmed/9343347
  2. http://www.nature.com/nature/journal/v505/n7485/full/nature12861.html
  3. post image modified fromhttp://sgugenetics.pbworks.com/w/page/61001794/Virus%20Life-cylce

Originally posted on LinkedIn.

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