Interaction networks of the molecular machines that decode, replicate, and maintain the integrity of the human genome

Ostm1 from Mouse to Human: Insights into Osteoclast Maturation

The maintenance of bone mass is a dynamic process that requires a strict balance between bone formation and resorption. Bone formation is controlled by osteoblasts, while osteoclasts are responsible for resorption of the bone matrix. The opposite functions of these cell types have to be tightly regulated not only during normal bone development, but also during adult life, to maintain serum calcium homeostasis and sustain bone integrity to prevent bone fractures. Disruption of the control of bone synthesis or resorption can lead to an over accumulation of bone tissue in osteopetrosis or conversely to a net depletion of the bone mass in osteoporosis. Moreover, high levels of bone resorption with focal bone formation can cause Paget’s disease. Here, we summarize the steps toward isolation and characterization of the osteopetrosis associated trans-membrane protein 1 (Ostm1) gene and protein, essential for proper osteoclast maturation, and responsible when mutated for the most severe form of osteopetrosis in mice and humans.

Stability and sub-cellular localization of DNA polymerase β is regulated by interactions with NQO1 and XRCC1 in response to oxidative stress

Protein–protein interactions regulate many essential enzymatic processes in the cell. Somatic mutations outside of an enzyme active site can therefore impact cellular function by disruption of critical protein–protein interactions. In our investigation of the cellular impact of the T304I cancer mutation of DNA Polymerase β (Polβ), we find that mutation of this surface threonine residue impacts critical Polβ protein–protein interactions. We show that proteasome-mediated degradation of Polβ is regulated by both ubiquitin-dependent and ubiquitin-independent processes via unique protein–protein interactions. The ubiquitin-independent proteasome pathway regulates the stability of Polβ in the cytosol via interaction between Polβ and NAD(P)H quinone dehydrogenase 1 (NQO1) in an NADH-dependent manner. Conversely, the interaction of Polβ with the scaffold protein X-ray repair cross complementing 1 (XRCC1) plays a role in the localization of Polβ to the nuclear compartment and regulates the stability of Polβ via a ubiquitin-dependent pathway. Further, we find that oxidative stress promotes the dissociation of the Polβ/NQO1 complex, enhancing the interaction of Polβ with XRCC1. Our results reveal that somatic mutations such as T304I in Polβ impact critical protein–protein interactions, altering the stability and sub-cellular localization of Polβ and providing mechanistic insight into how key protein–protein interactions regulate cellular responses to stress.

Investigating direct interaction between Escherichia coli topoisomerase I and RecA

Protein-protein interactions are of special importance in cellular processes, including replication, transcription, recombination, and repair. Escherichia coli topoisomerase I (EcTOP1) is primarily involved in the relaxation of negative DNA supercoiling. E. coli RecA, the key protein for homologous recombination and SOS DNA-damage response, has been shown to stimulate the relaxation activity of EcTOP1. The evidence for their direct protein-protein interaction has not been previously established. We report here the direct physical interaction between E. coli RecA and topoisomerase I. We demonstrated the RecA-topoisomerase I interaction via pull-down assays, and surface plasmon resonance measurements. Molecular docking supports the observation that the interaction involves the topoisomerase I N-terminal domains that form the active site. Our results from pull-down assays showed that ATP, although not required, enhances the RecA-EcTOP1 interaction. We propose that E. coli RecA physically interacts with topoisomerase I to modulate the chromosomal DNA supercoiling.

Discovering protein interactions and characterizing protein function using HaloTag technology

Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous proteomes, including those from viruses, bacteria, and yeast.  In comparison, analysis of the human proteome lags behind, partially due to the sheer number of proteins which must be studied, but also the complexity of networks and interactions these present. To specifically address the challenges of understanding the human proteome, we have developed HaloTag technology for protein isolation, particularly strong for isolation of multiprotein complexes and allowing more efficient capture of weak or transient interactions and/or proteins in low abundance.  HaloTag is a genetically encoded protein fusion tag, designed for covalent, specific, and rapid immobilization or labelling of proteins with various ligands. Leveraging these properties, numerous applications for mammalian cells were developed to characterize protein function and here we present methodologies including: protein pull-downs used for discovery of novel interactions or functional assays, and cellular localization. We find significant advantages in the speed, specificity, and covalent capture of fusion proteins to surfaces for proteomic analysis as compared to other traditional non-covalent approaches. We demonstrate these and the broad utility of the technology using two important epigenetic proteins as examples, the human bromodomain protein BRD4, and histone deacetylase HDAC1.  These examples demonstrate the power of this technology in enabling  the discovery of novel interactions and characterizing cellular localization in eukaryotes, which will together further understanding of human functional proteomics.              

Mass spectrometry approaches to study mammalian kinase and phosphatase associated proteins

Reversible phosphorylation events regulate critical aspects of cellular biology by affecting protein conformation, cellular localization, enzymatic activity and associations with interaction partners. Kinases and phosphatases interact not only with their substrates but also with regulatory subunits and other proteins, including scaffolds. In recent years, affinity purification coupled to mass spectrometry (AP-MS) has proven to be a powerful tool to identify protein-protein interactions (PPIs) involving kinases and phosphatases. In this review we outline general considerations for successful AP-MS, and describe strategies that we have used to characterize the interactions of kinases and phosphatases in human cells.

Examining the complexity of human RNA polymerase complexes using HaloTag technology coupled to label free quantitative proteomics

Efficient determination of protein interactions and cellular localization remains a challenge in higher order eukaryotes and creates a need for robust technologies for functional proteomics studies. To address this, the HaloTag technology was developed for highly efficient and rapid isolation of intracellular complexes and correlative in vivo cellular imaging. Here we demonstrate the strength of this technology by simultaneous capture of human eukaryotic RNA polymerases (RNAP) I, II, and III using a shared subunit, POLR2H, fused to the HaloTag. Affinity purifications showed successful isolation, as determined using quantitative proteomics, of all RNAP core subunits, even at expression levels near endogenous. Transient known RNAP II interacting partners were identified as well as three previously uncharacterized interactors. These interactions were validated and further functionally characterized using cellular imaging. The multiple capabilities of the HaloTag technology demonstrate the ability to efficiently isolate highly challenging multiprotein complexes, discover new interactions, and characterize cellular localization.

Transcription factories in the context of the nuclear and genome organization

In the eukaryotic nucleus, genes are transcribed in transcription factories. In the present review, we re-evaluate the models of transcription factories in the light of recent and older data. Based on this analysis, we propose that transcription factories result from the aggregation of RNA polymerase II-containing pre-initiation complexes assembled next to each other in the nuclear space. Such an aggregation can be triggered by the phosphorylation of the C-terminal domain of RNA polymerase II molecules and their interaction with various transcription factors. Individual transcription factories would thus incorporate tissue-specific, co-regulated as well as housekeeping genes based only on their initial proximity to each other in the nuclear space. Targeting genes to be transcribed to protein-dense factories that contain all factors necessary for transcription initiation and elongation through chromatin templates clearly favors a more economical utilization and better recycling of the transcription machinery.

The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

BACKGROUND

Apoptosis is a critical biological phenomenon, executed under the guidance of the Apoptotic Machinery (AM), which allows the physiologic elimination of terminally differentiated, senescent or diseased cells. Because of its relevance to BioMedicine, we have sought to obtain a detailed characterization of AM Omics in Homo sapiens, namely its Genomics and Evolution, Transcriptomics, Proteomics, Interactomics, Oncogenomics, and Pharmacogenomics.

METHODS

This project exploited the methodology commonly used in Computational Biology (i.e., mining of many omics databases of the web) as well as the High Throughput biomolecular analytical techniques.

RESULTS

In Homo sapiens AM is comprised of 342 protein-encoding genes (possessing either anti- or pro-apoptotic activity, or a regulatory function) and 110 MIR-encoding genes targeting them: some have a critical role within the system (core AM nodes), others perform tissue-, pathway-, or disease-specific functions (peripheral AM nodes). By overlapping the cancer type-specific AM mutation map in the fourteen most frequent cancers in western societies (breast, colon, kidney, leukaemia, liver, lung, neuroblastoma, ovary, pancreas, prostate, skin, stomach, thyroid, and uterus) to their transcriptome, proteome and interactome in the same tumour type, we have identified the most prominent AM molecular alterations within each class. The comparison of the fourteen mutated AM networks (both protein- as MIR-based) has allowed us to pinpoint the hubs with a general and critical role in tumour development and, conversely, in cell physiology: in particular, we found that some of these had already been used as targets for pharmacological anticancer therapy. For a better understanding of the relationship between AM molecular alterations and pharmacological induction of apoptosis in cancer, we examined the expression of AM genes in K562 and SH-SY5Y after anticancer treatment.

CONCLUSION

We believe that our data on the Apoptotic Machinery will lead to the identification of new cancer genes and to the discovery of new biomarkers, which could then be used to profile cancers for diagnostic purposes and to pinpoint new targets for pharmacological therapy. This approach could pave the way for future studies and applications in molecular and clinical Medicine with important perspectives both for Oncology as for Regenerative Medicine.

Steps towards a repertoire of comprehensive maps of human protein interaction networks: the Human Proteotheque Initiative (HuPI)

Defining human protein interaction networks has become essential to develop an overall, systems-based understanding of the molecular events that sustain cell growth in normal and disease conditions. To characterize protein interaction networks from human cells, we have undertaken the development of a systematic, unbiased technology pipeline that couples experimental and computational approaches. This discovery engine is central to the Human Proteotheque Initiative (HuPI), a multidisciplinary project aimed at building a repertoire of comprehensive maps of human protein interaction networks, the Human Proteotheque. The information contained in the Proteotheque is made publicly available through an interactive web site that can be consulted to visualize some of the fundamental molecular connections formed in human cells and to determine putative functions of previously uncharacterized proteins based on guilt by association. The process governing the evolution of HuPI towards becoming a repository of accurate and complete protein interaction maps is described.

Various members of the E2F transcription factor family interact in vivo with the corepressor alien

Proteins perform their activities in cells by the cooperation within protein complexes. For this reason, it is important to investigate protein-protein interactions to receive insights in physiological processes. A multitude of proteins are involved in the regulation of the cell cycle. Specific key factors participating here are members of the E2F transcription factors. Using an in vivo protein-protein complex detection assay, which comprises mass spectrometric and immunological techniques, we detected a number of known as well as new protein-protein interactions. We describe here for the first time protein complexes containing the corepressor Alien and members of the E2F transcription factor family. Furthermore, we assessed the functional relevance and show a repression of the transcriptional activity of E2F by Alien. Additionally, we detected new interactions that link endogenously expressed Alien with the tumor suppressor retinoblastoma protein (pRB) and with proteins involved in cell cycle regulation.

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein-protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.

Detection and Identification of Protein Interactions of S100 Proteins by ProteinChip Technology

The aim of this work was to establish an approach for identification of protein interactions. This assay used an anti-S100A8 antibody coupled on beads and incubated with cell extract. The bead eluates were analyzed using ProteinChip technology and subsequently subjected to an appropriate digestion. Molecular masses of digestion fragments were determined by SELDI-MS, and database analysis revealed S100A10 as interacting protein. This result was confirmed by co-immunoprecipitation and immunocapturing. Using S100A10 as new bait, a specific interaction with S100A7 was detectable.

Prediction of Multimolecular Assemblies by Multiple Docking

The majority of proteins function when associated in multimolecular assemblies. Yet, prediction of the structures of multimolecular complexes has largely not been addressed, probably due to the magnitude of the combinatorial complexity of the problem. Docking applications have traditionally been used to predict pairwise interactions between molecules. We have developed an algorithm that extends the application of docking to multimolecular assemblies. We apply it to predict quaternary structures of both oligomers and multi-protein complexes. The algorithm predicted well a near-native arrangement of the input subunits for all cases in our data set, where the number of the subunits of the different target complexes varied from three to ten. In order to simulate a more realistic scenario, unbound cases were tested. In these cases the input conformations of the subunits are either unbound conformations of the subunits or a model obtained by a homology modeling technique. The successful predictions of the unbound cases, where the input conformations of the subunits are different from their conformations within the target complex, suggest that the algorithm is robust. We expect that this type of algorithm should be particularly useful to predict the structures of large macromolecular assemblies, which are difficult to solve by experimental structure determination.