Chunxiang Zheng

Cross-linking measurements of in vivo protein complex topologies.

Identification and measurement of in vivo protein interactions pose critical challenges in the goal to understand biological systems. The measurement of structures and topologies of proteins and protein complexes as they exist in cells is particularly challenging, yet critically important to improve understanding of biological function because proteins exert their intended function only through the structures and interactions they exhibit in vivo. In the present study, protein interactions in E. coli cells were identified in our unbiased cross-linking approach, yielding the first in vivo topological data on many interactions and the largest set of identified in vivo cross-linked peptides produced to date. These data show excellent agreement with protein and complex crystal structures where available. Furthermore, our unbiased data provide novel in vivo topological information that can impact understanding of biological function, even for cases where high resolution structures are not yet available.

Protein interactions, post-translational modifications and topologies in human cells.

The unique and remarkable physicochemical properties of protein surface topologies give rise to highly specific biomolecular interactions, which form the framework through which living systems are able to carry out their vast array of functions. Technological limitations undermine efforts to probe protein structures and interactions within unperturbed living systems on a large scale. Rapid chemical stabilization of proteins and protein complexes through chemical cross-linking offers the alluring possibility to study details of the protein structure to function relationships as they exist within living cells. Here we apply the latest technological advances in chemical cross-linking combined with mass spectrometry to study protein topologies and interactions from living human cells identifying a total of 368 cross-links. These include cross-links from all major cellular compartments including membrane, cytosolic and nuclear proteins. Intraprotein and interprotein cross-links were also observed for core histone proteins, including several cross-links containing post-translational modifications which are known histone marks conferring distinct epigenetic functions. Excitingly, these results demonstrate the applicability of cross-linking to make direct topological measurements on post-translationally modified proteins. The results presented here provide new details on the structures of known multi-protein complexes as well as evidence for new protein-protein interactions.

In Vivo Identification of the Outer Membrane Protein OmcA–MtrC Interaction Network in Shewanella oneidensis MR-1 Cells Using Novel Hydrophobic Chemical Cross-Linkers

Outer membrane (OM) cytochromes OmcA (SO1779) and MtrC (SO1778) are the integral components of electron transfer used by Shewanella oneidensis for anaerobic respiration of metal (hydr)oxides. Here the OmcA-MtrC interaction was identified in vivo using a novel hydrophobic chemical cross-linker (MRN) combined with immunoprecipitation techniques. In addition, identification of other OM proteins from the cross-linked complexes allows first visualization of the OmcA-MtrC interaction network. Further experiments on omcA and mtrC mutant cells showed OmcA plays a central role in the network interaction. For comparison, two commercial cross-linkers were also used in parallel, and both resulted in fewer OM protein identifications, indicating the superior properties of MRN for identification of membrane protein interactions. Finally, comparison experiments of in vivo cross-linking and cell lysate cross-linking resulted in significantly different protein interaction data, demonstrating the importance of in vivo cross-linking for study of protein-protein interactions in cells.

XLink-DB: database and software tools for storing and visualizing protein interaction topology data

As large-scale cross-linking data becomes available, new software tools for data processing and visualization are required to replace manual data analysis. XLink-DB serves as a data storage site and visualization tool for cross-linking results. XLink-DB accepts data generated with any cross-linker and stores them in a relational database. Cross-linked sites are automatically mapped onto PDB structures if available, and results are compared to existing protein interaction databases. A protein interaction network is also automatically generated for the entire data set. The XLink-DB server, including examples, and a help page are available for noncommercial use at http://brucelab.gs.washington.edu/crosslinkdbv1/ . The source code can be viewed and downloaded at https://sourceforge.net/projects/crosslinkdb/?source=directory .

In Vivo Application of Photocleavable Protein Interaction Reporter Technology

In vivo protein structures and protein-protein interactions are critical to the function of proteins in biological systems. As a complementary approach to traditional protein interaction identification methods, cross-linking strategies are beginning to provide additional data on protein and protein complex topological features. Previously, photocleavable protein interaction reporter (pcPIR) technology was demonstrated by cross-linking pure proteins and protein complexes and the use of ultraviolet light to cleave or release cross-linked peptides to enable identification. In the present report, the pcPIR strategy is applied to Escherichia coli cells, and in vivo protein interactions and topologies are measured. More than 1600 labeled peptides from E. coli were identified, indicating that many protein sites react with pcPIR in vivo. From those labeled sites, 53 in vivo intercross-linked peptide pairs were identified and manually validated. Approximately half of the interactions have been reported using other techniques, although detailed structures exist for very few. Three proteins or protein complexes with detailed crystallography structures are compared to the cross-linking results obtained from in vivo application of pcPIR technology.

In vivo protein interaction network analysis reveals porin-localized antibiotic inactivation in Acinetobacter baumannii strain AB5075

The nosocomial pathogen Acinetobacter baumannii is a frequent cause of hospital-acquired infections worldwide and is a challenge for treatment due to its evolved resistance to antibiotics, including carbapenems. Here, to gain insight on A. baumannii antibiotic resistance mechanisms, we analyse the protein interaction network of a multidrug-resistant A. baumannii clinical strain (AB5075). Using in vivo chemical cross-linking and mass spectrometry, we identify 2,068 non-redundant cross-linked peptide pairs containing 245 intra- and 398 inter-molecular interactions. Outer membrane proteins OmpA and YiaD, and carbapenemase Oxa-23 are hubs of the identified interaction network. Eighteen novel interactors of Oxa-23 are identified. Interactions of Oxa-23 with outer membrane porins OmpA and CarO are verified with co-immunoprecipitation analysis. Furthermore, transposon mutagenesis of oxa-23 or interactors of Oxa-23 demonstrates changes in meropenem or imipenem sensitivity in strain AB5075. These results provide a view of porin-localized antibiotic inactivation and increase understanding of bacterial antibiotic resistance mechanisms.

Dynamic proteome response of Pseudomonas aeruginosa to tobramycin antibiotic treatment

Genetically susceptible bacteria become antibiotic tolerant during chronic infections, and the mechanisms responsible are poorly understood. One factor that may contribute to differential sensitivity in vitro and in vivo is differences in the time-dependent tobramycin concentration profile experienced by the bacteria. Here, we examine the proteome response induced by subinhibitory concentrations of tobramycin in Pseudomonas aeruginosa cells grown under planktonic conditions. These efforts revealed increased levels of heat shock proteins and proteases were present at higher dosage treatments (0.5 and 1 μg/ml), while less dramatic at 0.1 μg/ml dosage. In contrast, many metabolic enzymes were significantly induced by lower dosages (0.1 and 0.5 μg/ml) but not at 1 μg/ml dosage. Time course proteome analysis further revealed that the increase of heat shock proteins and proteases was most rapid from 15 min to 60 min, and the increased levels sustained till 6 h (last time point tested). Heat shock protein IbpA exhibited the greatest induction by tobramycin, up to 90-fold. Nevertheless, deletion of ibpA did not enhance sensitivity to tobramycin. It seemed possible that the absence of sensitization could be due to redundant functioning of IbpA with other proteins that protect cells from tobramycin. Indeed, inactivation of two heat shock chaperones/proteases in addition to ibpA in double mutants (ibpA/clpB, ibpA/PA0779 and ibpA/hslV) did increase tobramycin sensitivity. Collectively, these results demonstrate the time- and concentration-dependent nature of the P. aeruginosa proteome response to tobramycin and that proteome modulation and protein redundancy are protective mechanisms to help bacteria resist antibiotic treatments.

XLinkDB 2.0: Integrated, large-scale structural analysis of protein crosslinking data.

MOTIVATION Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein-protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. AVAILABILITY AND IMPLEMENTATION XLinkDB 2.0 can be found here, including documentation and help: http://xlinkdb.gs.washington.edu/ CONTACT : jimbruce@uw.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Role of the tumor suppressor IQGAP2 in metabolic homeostasis: possible link between diabetes and cancer

Deficiency of IQGAP2, a scaffolding protein expressed primarily in liver leads to rearrangements of hepatic protein compartmentalization and altered regulation of enzyme functions predisposing development of hepatocellular carcinoma and diabetes. Employing a systems approach with proteomics, metabolomics and fluxes characterizations, we examined the effects of IQGAP2 deficient proteomic changes on cellular metabolism and the overall metabolic phenotype. Iqgap2−/−mice demonstrated metabolic inflexibility, fasting hyperglycemia and obesity. Such phenotypic characteristics were associated with aberrant hepatic regulations of glycolysis/gluconeogenesis, glycogenolysis, lipid homeostasis and futile cycling corroborated with corresponding proteomic changes in cytosolic and mitochondrial compartments. IQGAP2 deficiency also led to truncated TCA-cycle, increased anaplerosis, increased supply of acetyl-CoA for de novo lipogenesis, and increased mitochondrial methyl-donor metabolism necessary for nucleotides synthesis. Our results suggest that changes in metabolic networks in IQGAP2 deficiency create a hepatic environment of a ‘pre-diabetic’ phenotype and a predisposition to non-alcoholic fatty liver disease which has been linked to the development of hepatocellular carcinoma.

Integrating cross-linking experiments with ab initio protein-protein docking.

Ab initio protein-protein docking algorithms often rely on experimental data to identify the most likely complex structure. We integrated protein-protein docking with the experimental data of chemical cross-linking followed by mass spectrometry. We tested our approach using 19 cases that resulted from an exhaustive search of the Protein Data Bank for protein complexes with cross-links identified in our experiments. We implemented cross-links as constraints based on Euclidean distance or void-volume distance. For most test cases, the rank of the top-scoring near-native prediction was improved by at least twofold compared with docking without the cross-link information, and the success rate for the top 5 predictions nearly tripled. Our results demonstrate the delicate balance between retaining correct predictions and eliminating false positives. Several test cases had multiple components with distinct interfaces, and we present an approach for assigning cross-links to the interfaces. Employing the symmetry information for these cases further improved the performance of complex structure prediction.