Biology subjects

Jordan, K. D.

Publications and source records attributed to Jordan, K. D..

3 recordsLinked to original sources

bioRxiv2018

The impact of data reduction and lossy image formats on electron microscope images

Recent advances in instrumentation and software for cryoEM have increased the applicability and utility of this method. Coupled with the adoption of automated pipelines, significant infrastructure support is required to sustain high throughput workflows. In particular, data generation rates may outpace the ability to deploy data storage and archival solutions. We have investigated what effects data compression and conversion to different file formats have on the ability to obtain high resolution cryoEM reconstructions. Standard lossless data compression strategies have a high impact on reducing the size of direct detector electron counting movie stacks, but provide more modest gains for aligned summed images. We show that EM images can be compressed using standard lossy methods to reduce file storage to 5-10% of the size of the original aligned sum or movie stack file and yet still retain enough information such that modern image processing pipelines will provide sub-2[A] reconstructions from the compressed data.

biophysics↗

bioRxiv2018

Benchmarking cryo-EM single particle analysis workflow

Cryo electron microscopy facilities running multiple instruments and serving users with varying skill levels need a robust and reliable method for benchmarking both the hardware and software components of their single particle analysis workflow. The workflow is complex, with many bottlenecks existing at the specimen preparation, data collection and image analysis steps; the samples and grid preparation can be of unpredictable quality, there are many different protocols for microscope and camera settings, and there is a myriad of software programs for analysis that can depend on dozens of settings chosen by the user. For this reason, we believe it is important to benchmark the entire workflow, using a standard sample and standard operating procedures, on a regular basis. This provides confidence that all aspects of the pipeline are capable of producing maps to high resolution. Here we describe benchmarking procedures using a test sample, rabbit muscle aldolase.

molecular biology↗

bioRxiv2018

High Resolution Single Particle Cryo-Electron Microscopy using Beam-Image Shift

Automated data acquisition is now used widely for the single-particle averaging approach to reconstruction of three-dimensional (3D) volumes of biological complexes preserved in vitreous ice and imaged in a transmission electron microscope (cryo-EM). Automation has become integral to this method because of the very large number of particle images required to be averaged in order to overcome the typically low signal-to-noise ratio of these images.\n\nFor optimal efficiency, all automated data acquisition software packages employ some degree of beam-image shift because this method is fast and accurate (+/- 0.1 m). Relocation to a targeted area under low-dose conditions can only be achieved using stage movements in combination with multiple iterations or long relaxation times, both reducing efficiency. It is, however, well known that applying beam-image shift induces beam-tilt and hence structure phase error. A {pi}/4 phase error is considered as the worst that can be accepted, and is used as an argument against the use of any beam-image shift for high resolution data collection.\n\nIn this study, we performed cryo-EM single-particle reconstructions on a T20S proteasome sample using applied beam-image shifts corresponding to beam tilts from 0 to 10 mrad. To evaluate the results we compared the FSC values, and examined the water density peaks in the 3D map. We conclude that the {pi}/4 phase error does not limit the validity of the 3D reconstruction from single-particle averaging beyond the {pi}/4 resolution limit.

biophysics↗