Maskiton: Interactive, web-based classification of single-particle electron microscopy images

Abstract

Electron microscopy (EM) is an important tool for determining the composition, arrangement and structure of biological macromolecules. When studying structurally heterogeneous samples using EM, classification is a critical step toward achieving higher resolution and identifying biologically significant conformations. We have developed an interactive, web-based tool, called Maskiton, for creating custom masks and performing 2D classifications on aligned single-particle EM images. The Maskiton interface makes it considerably easier and faster to explore the significance of heterogeneity in single-particle datasets. Maskiton features include: resumable uploads to facilitate transfer of large datasets to the server, custom mask creation in the browser, continual progress updates, and interactive viewing of classification results. To demonstrate the value of this tool, we provide examples of its use on several experimental datasets and include analyses of the independent terminus mobility within the Ltn1 E3 ubiquitin ligase, the in vitro assembly of 30S ribosomal subunits, and classification complexity reduction within Immunoglobulin M. This work also serves as a proof-of-concept for the development of future cross-platform, interactive user interfaces for electron microscopy data processing.