Structured illumination microscopy combined with machine learning for the high throughput analysis of virus structure
- University of Cambridge, United Kingdom
- Medimmune, United Kingdom
Abstract
Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools in the investigation of the structure of supramolecular assemblies such as viruses. Here, we report on a new methodology which combines Structured Illumination Microscopy (SIM) with machine learning algorithms to image and classify the structure of large populations of biopharmaceutical viruses with high resolution. The method offers information on virus morphology that can ultimately be linked with functional performance. We demonstrate the approach on viruses produced for oncolytic viriotherapy (Newcastle Disease Virus) and vaccine development (Influenza). This unique tool enables the rapid assessment of the quality of viral production with high throughput obviating the need for traditional batch testing methods which are complex and time consuming. We show that our method also works on non-purified samples from pooled harvest fluids directly from the production line.
Data availability
Analysis code for image segmentation, machine learning training, classification and structural analysis is available via GitHub (https://github.com/Romain-Laine/MiLeSIM). Source data files have been provided for Figures 4 and 5.
Article and author information
Author details
Funding
Engineering and Physical Sciences Research Council (EP/L015889/1)
- Romain F Laine
- Gemma Goodfellow
- Laurence J Young
- Clemens Kaminski
Medical Research Council (MR/K015850/1)
- Romain F Laine
- Gemma Goodfellow
- Laurence J Young
- Clemens Kaminski
Medical Research Council (MR/K02292X/1)
- Romain F Laine
- Gemma Goodfellow
- Laurence J Young
- Clemens Kaminski
Wellcome (3-3249/Z/16/Z)
- Romain F Laine
- Gemma Goodfellow
- Laurence J Young
- Clemens Kaminski
Engineering and Physical Sciences Research Council (EP/H018301/1)
- Romain F Laine
- Gemma Goodfellow
- Laurence J Young
- Clemens Kaminski
Biotechnology and Biological Sciences Research Council (BB/P027431/1)
- Romain F Laine
MedImmune (NA)
- Romain F Laine
- Gemma Goodfellow
- Jon Travers
- Danielle Carroll
- Oliver Dibben
- Helen Bright
Infinitus (NA)
- Clemens Kaminski
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Laine et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Structured illumination microscopy combined with machine learning for the high throughput analysis of virus structure
eLife 7:e40183.
https://doi.org/10.7554/eLife.40183
