Quantitative cross-linking/mass spectrometry reveals subtle protein conformational changes.

Quantitative cross-linking/mass spectrometry (QCLMS) probes protein structural dynamics in solution by quantitatively comparing the yields of cross-links between different conformational statuses. We have used QCLMS to understand the final maturation step of the proteasome lid and also to elucidate the structure of complement C3(H2O). Here we benchmark our workflow using a structurally well-described reference system, the human complement protein C3 and its activated cleavage product C3b. We found that small local conformational changes affect the yields of cross-linking residues that are near in space while larger conformational changes affect the detectability of cross-links. Distinguishing between minor and major changes required robust analysis based on replica analysis and a label-swapping procedure. By providing workflow, code of practice and a framework for semi-automated data processing, we lay the foundation for QCLMS as a tool to monitor the domain choreography that drives binary switching in many protein-protein interaction networks.

Bistability in the Rac1, PAK, and RhoA Signaling Network Drives Actin Cytoskeleton Dynamics and Cell Motility Switches.

Dynamic interactions between RhoA and Rac1, members of the Rho small GTPase family, play a vital role in the control of cell migration. Using predictive mathematical modeling, mass spectrometry-based quantitation of network components, and experimental validation in MDA-MB-231 mesenchymal breast cancer cells, we show that a network containing Rac1, RhoA, and PAK family kinases can produce bistable, switch-like responses to a graded PAK inhibition. Using a small chemical inhibitor of PAK, we demonstrate that cellular RhoA and Rac1 activation levels respond in a history-dependent, bistable manner to PAK inhibition. Consequently, we show that downstream signaling, actin dynamics, and cell migration also behave in a bistable fashion, displaying switches and hysteresis in response to PAK inhibition. Our results demonstrate that PAK is a critical component in the Rac1-RhoA inhibitory crosstalk that governs bistable GTPase activity, cell morphology, and cell migration switches.

Proteomics of a fuzzy organelle: interphase chromatin.

Chromatin proteins mediate replication, regulate expression, and ensure integrity of the genome. So far, a comprehensive inventory of interphase chromatin has not been determined. This is largely due to its heterogeneous and dynamic composition, which makes conclusive biochemical purification difficult, if not impossible. As a fuzzy organelle, it defies classical organellar proteomics and cannot be described by a single and ultimate list of protein components. Instead, we propose a new approach that provides a quantitative assessment of a protein's probability to function in chromatin. We integrate chromatin composition over a range of different biochemical and biological conditions. This resulted in interphase chromatin probabilities for 7635 human proteins, including 1840 previously uncharacterized proteins. We demonstrate the power of our large-scale data-driven annotation during the analysis of cyclin-dependent kinase (CDK) regulation in chromatin. Quantitative protein ontologies may provide a general alternative to list-based investigations of organelles and complement Gene Ontology.

Nascent chromatin capture proteomics determines chromatin dynamics during DNA replication and identifies unknown fork components.

To maintain genome function and stability, DNA sequence and its organization into chromatin must be duplicated during cell division. Understanding how entire chromosomes are copied remains a major challenge. Here, we use nascent chromatin capture (NCC) to profile chromatin proteome dynamics during replication in human cells. NCC relies on biotin-dUTP labelling of replicating DNA, affinity purification and quantitative proteomics. Comparing nascent chromatin with mature post-replicative chromatin, we provide association dynamics for 3,995 proteins. The replication machinery and 485 chromatin factors such as CAF-1, DNMT1 and SUV39h1 are enriched in nascent chromatin, whereas 170 factors including histone H1, DNMT3, MBD1-3 and PRC1 show delayed association. This correlates with H4K5K12diAc removal and H3K9me1 accumulation, whereas H3K27me3 and H3K9me3 remain unchanged. Finally, we combine NCC enrichment with experimentally derived chromatin probabilities to predict a function in nascent chromatin for 93 uncharacterized proteins, and identify FAM111A as a replication factor required for PCNA loading. Together, this provides an extensive resource to understand genome and epigenome maintenance.

Building mitotic chromosomes.

Mitotic chromosomes are the iconic structures into which the genome is packaged to ensure its accurate segregation during mitosis. Although they have appeared on countless journal cover illustrations, there remains no consensus on how the chromatin fiber is packaged during mitosis. In fact, work in recent years has both added to existing controversies and sparked new ones. By contrast, there has been very significant progress in determining the protein composition of isolated mitotic chromosomes. Here, we discuss recent studies of chromosome organization and provide an in depth description of the latest proteomics studies, which have at last provided us with a definitive proteome for vertebrate chromosomes.

The protein composition of mitotic chromosomes determined using multiclassifier combinatorial proteomics.

Despite many decades of study, mitotic chromosome structure and composition remain poorly characterized. Here, we have integrated quantitative proteomics with bioinformatic analysis to generate a series of independent classifiers that describe the approximately 4,000 proteins identified in isolated mitotic chromosomes. Integrating these classifiers by machine learning uncovers functional relationships between protein complexes in the context of intact chromosomes and reveals which of the approximately 560 uncharacterized proteins identified here merits further study. Indeed, of 34 GFP-tagged predicted chromosomal proteins, 30 were chromosomal, including 13 with centromere-association. Of 16 GFP-tagged predicted nonchromosomal proteins, 14 were confirmed to be nonchromosomal. An unbiased analysis of the whole chromosome proteome from genetic knockouts of kinetochore protein Ska3/Rama1 revealed that the APC/C and RanBP2/RanGAP1 complexes depend on the Ska complex for stable association with chromosomes. Our integrated analysis predicts that up to 97 new centromere-associated proteins remain to be discovered in our data set.

Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry.

Higher-order multi-protein complexes such as RNA polymerase II (Pol II) complexes with transcription initiation factors are often not amenable to X-ray structure determination. Here, we show that protein cross-linking coupled to mass spectrometry (MS) has now sufficiently advanced as a tool to extend the Pol II structure to a 15-subunit, 670 kDa complex of Pol II with the initiation factor TFIIF at peptide resolution. The N-terminal regions of TFIIF subunits Tfg1 and Tfg2 form a dimerization domain that binds the Pol II lobe on the Rpb2 side of the active centre cleft near downstream DNA. The C-terminal winged helix (WH) domains of Tfg1 and Tfg2 are mobile, but the Tfg2 WH domain can reside at the Pol II protrusion near the predicted path of upstream DNA in the initiation complex. The linkers between the dimerization domain and the WH domains in Tfg1 and Tfg2 are located to the jaws and protrusion, respectively. The results suggest how TFIIF suppresses non-specific DNA binding and how it helps to recruit promoter DNA and to set the transcription start site. This work establishes cross-linking/MS as an integrated structure analysis tool for large multi-protein complexes.

Improved results in proteomics by use of local and peptide-class specific false discovery rates.

BACKGROUND: Proteomic protein identification results need to be compared across laboratories and platforms, and thus a reliable method is needed to estimate false discovery rates. The target-decoy strategy is a platform-independent and thus a prime candidate for standardized reporting of data. In its current usage based on global population parameters, the method does not utilize individual peptide scores optimally. RESULTS: Here we show that proteomic analyses largely benefit from using separate treatment of peptides matching to proteins alone or in groups based on locally estimated false discovery rates. Our implementation reduces the number of false positives and simultaneously increases the number of proteins identified. Importantly, single peptide identifications achieve defined confidence and the sequence coverage of proteins is optimized. As a result, we improve the number of proteins identified in a human serum analysis by 58% without compromising identification confidence. CONCLUSION: We show that proteins can reliably be identified with a single peptide and the sequence coverage for multi-peptide proteins can be increased when using an improved estimation of false discovery rates.