Biology subjects

Mallam, A. L.

Publications and source records attributed to Mallam, A. L..

3 recordsLinked to original sources

bioRxiv2019

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are unable to handle heterogeneous mixtures of structures from many macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. Using this approach, we first group a large set of synthetic reprojections from 35 unique macromolecular structures ranging from [~]30 - 3000 kDa into individual homogenous classes. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing reconstruction methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort cryo-EM data from heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

biochemistry↗

bioRxiv2018

Systematic discovery of endogenous human ribonucleoprotein complexes

RNA-binding proteins (RBPs) play essential roles in biology and are frequently associated with human disease. While recent studies have systematically identified individual RBPs, their higher order assembly into Ribonucleoprotein (RNP) complexes has not been systematically investigated. Here, we describe a proteomics method for systematic identification of RNP complexes in human cells. We identify 1,428 protein complexes that associate with RNA, indicating that over 20% of known human protein complexes contain RNA. To explore the role of RNA in the assembly of each complex, we identify complexes that dissociate, change composition, or form stable protein-only complexes in the absence of RNA. Importantly, these data also provide specific novel insights into the function of well-studied protein complexes not previously known to associate with RNA, including replication factor C (RFC) and cytokinetic centralspindlin complex. Finally, we use our method to systematically identify cell-type specific RNA-associated proteins in mouse embryonic stem cells. We distribute these data as a resource, rna.MAP (rna.proteincomplexes.org) which provides a comprehensive dataset for the study of RNA-associated protein complexes. Our system thus provides a novel methodology for further explorations across human tissues and disease states, as well as throughout all domains of life.\n\nSummaryAn exploration of human protein complexes in the presence and absence of RNA reveals endogenous ribonucleoprotein complexes

systems biology↗

bioRxiv2018

Classification of Single Particles from Human Cell Extract Reveals Distinct Structures

Multi-protein complexes are necessary for nearly all cellular processes, and understanding their structure is required for elucidating their function. Current high-resolution strategies in structural biology are effective, but lag behind other fields (e.g. genomics and proteomics) due to their reliance on purified samples rather than characterizing heterogeneous mixtures. Here, we present a method combining single particle analysis by electron microscopy with protein identification by mass spectrometry to structurally characterize macromolecular complexes from extracts of human cells. We obtain three-dimensional structures of native proteasomes directly from ab initio classification of a heterogeneous mixture of protein complexes. In addition, we find an ~1 MDa size structure of unknown composition and reference our proteomics data to suggest possible identities. Our study shows the power of using a shotgun approach to electron microscopy (shotgun EM) when coupled with mass spectrometry as a tool to uncover the structures of macromolecular machines in parallel.

biochemistry↗