Fast and reliable alignment and classification of biological macromolecules in electron microscopy images

In the last century, immense progress has been made to charter and understand a wide range of biological phenomena. The origin of genetic inheritance was determined, showing that DNA holds genes that determine the architecture of proteins, utilized by the cell for most functions. Mapping of the human genome eventually revealed around 20000 genes, showing a vast complexity of biology at its most fundamental level. To study the molecular structure, function and regulation of proteins, spectroscopic techniques and microscopy are employed. Until just over a decade ago, the determination of atomic detail of biomolecules like proteins was limited to those that were small or possible to crystallize. However recent technological advances in cryogenic electron microscopy (cryo-EM) now allows it to routinely reach resolutions where it can provide a wealth of new information on molecular biological phenomena by permitting new targets to be structurally characterized. In cryo-EM, biological molecules are suspended in thin vitreous sheet of ice and imaged in projection. Collecting millions of such images permits the reconstruction of the original molecular structure, by appropriate alignment and averaging of the particle images. This however requires immense computational effort, which just a few years ago was prohibitive to full use of the image data. In this thesis, I describe the development of fast algorithms for processing of cryo-EM data, utilizing GPUs by exposing the inherent parallelism of its alignment and classification. The acceleration of this processing has changed how biological research can utilize cryo-EM data. The drastically reduced processing time now allows more extensive processing, development of new and more demanding processing tools, and broader access to cryo-EM as a method for biological investigation. As an example of what is now possible, I show the processing of the fungal pyruvate dehydrogenase complex (PDC), which poses unique processing challenges. Through extensive processing, new biological information can be inferred, reconciling numerous previous findings from biochemical research. The processing of PDC also exemplifies current limitations to established.At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.