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Liquid Native MALDI Mass Spectrometry for the Detection of Protein-Protein Complexes.

ABSTRACT: Native mass spectrometry (MS) encompasses methods to keep noncovalent interactions of biomolecular complexes intact in the gas phase throughout the instrument and to measure the mass-to-charge ratios of supramolecular complexes directly in the mass spectrometer. Electrospray ionization (ESI) in nondenaturing conditions is now an established method to characterize noncovalent systems. Matrix-assisted laser desorption/ionization (MALDI), on the other hand, consumes low quantities of samples and largely tolerates contaminants, making it a priori attractive for native MS. However, so-called native MALDI approaches have so far been based on solid deposits, where the rapid transition of the sample through a solid state can engender the loss of native conformations. Here we present a new method for native MS based on liquid deposits and MALDI ionization, unambiguously detecting intact noncovalent protein complexes by direct desorption from a liquid spot for the first time. To control for aggregation, we worked with HUαβ, a heterodimer that does not spontaneously rearrange into homodimers in solution. Screening through numerous matrix solutions to observe first the monomeric protein, then the dimer complex, we settled on a nondenaturing binary matrix solution composed of acidic and basic organic matrices in glycerol, which is stable in vacuo. The role of temporal and spatial laser irradiation patterns was found to be critical. Both a protein-protein and a protein-ligand complex could be observed free of aggregation. To minimize gas-phase dissociation, source parameters were optimized to achieve a conservation of complexes above 50% for both systems. Graphical Abstract ᅟ.

SUBMITTER: Beaufour M

PROVIDER: S-EPMC6153977 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: Recent advances in molecular biology have led to the accumulation of large amounts of data on protein-protein interaction networks in different species. An important challenge for the analysis of these data is to extract functional modules such as protein complexes and biological processes from networks which are characterised by the present of a significant number of false positives. Various computational techniques have been applied in recent years. However, most of them treat protein interaction as binary. Co-complex relations derived from affinity purification/mass spectrometry (AP-MS) experiments have been largely ignored. METHODS: This paper presents a new algorithm for detecting protein complexes from AP-MS data. The algorithm intends to detect groups of prey proteins that are significantly co-associated with the same set of bait proteins. We first construct AP-MS data as a bipartite network, where one set of nodes consists of bait proteins and the other set is composed of prey proteins. We then calculate pair-wise similarities of bait proteins based on the number of their commonly shared neighbours. A hierarchical clustering algorithm is employed to cluster bait proteins based on the similarities and thus a set of 'seed' clusters is obtained. Starting from these 'seed' clusters, an expansion process is developed to identify prey proteins which are significantly associated with the same set of bait proteins. Then, a set of complete protein complexes is derived. In application to two real AP-MS datasets, we validate biological significance of predicted protein complexes by using curated protein complexes and well-characterized cellular component annotation from Gene Ontology (GO). Several statistical metrics have been applied for evaluation. RESULTS: Experimental results show that, the proposed algorithm achieves significant improvement in detecting protein complexes from AP-MS data. In comparison to the well-known MCL algorithm, our algorithm improves the accuracy rate by about 20% in detecting protein complexes in both networks and increases the F-Measure value by about 50% in Krogan_2006 network. Greater precision and better accuracy have been achieved and the identified complexes are demonstrated to match well with existing curated protein complexes. CONCLUSIONS: Our study highlights the significance of taking co-complex relations into account when extracting protein complexes from AP-MS data. The algorithm proposed in this paper can be easily extended to the analysis of other biological networks which can be conveniently represented by bipartite graphs such as drug-target networks.

Project description:Ortholog protein complexes are responsible for equivalent functions in different organisms. However, during evolution, each organism adapts to meet its physiological needs and the environmental challenges imposed by its niche. This selection pressure leads to structural diversity in protein complexes, which are often difficult to specify, especially in the absence of high-resolution structures. Here, we describe a multilevel experimental approach based on native mass spectrometry (MS) tools for elucidating the structural preservation and variations among highly related protein complexes. The 20S proteasome, an essential protein degradation machinery, served as our model system, wherein we examined five complexes isolated from different organisms. We show that throughout evolution, from the Thermoplasma acidophilum archaeal prokaryotic complex to the eukaryotic 20S proteasomes in yeast (Saccharomyces cerevisiae) and mammals (rat - Rattus norvegicus, rabbit - Oryctolagus cuniculus and human - HEK293 cells), the proteasome increased both in size and stability. Native MS structural signatures of the rat and rabbit 20S proteasomes, which heretofore lacked high-resolution, three-dimensional structures, highly resembled that of the human complex. Using cryoelectron microscopy single-particle analysis, we were able to obtain a high-resolution structure of the rat 20S proteasome, allowing us to validate the MS-based results. Our study also revealed that the yeast complex, and not those in mammals, was the largest in size and displayed the greatest degree of kinetic stability. Moreover, we also identified a new proteoform of the PSMA7 subunit that resides within the rat and rabbit complexes, which to our knowledge have not been previously described. Altogether, our strategy enables elucidation of the unique structural properties of protein complexes that are highly similar to one another, a framework that is valid not only to ortholog protein complexes, but also for other highly related protein assemblies.

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Liquid Native MALDI Mass Spectrometry for the Detection of Protein-Protein Complexes.

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