Identificazione delle Lamine di tipo A come nuovi substrati della protein chinasi Akt/PKB

Akt (also called PKB) is a 63 kDa serine/threonine kinase involved in promotion of cell survival, proliferation a nd metabolic responses downstream the phosphoinositide-3-kinase (PI 3-kinase) signaling pathway. In resting cells, Akt is a predominantly cytosolic enzyme; however generation of PI 3-kinase lipid products recruits Akt to the plasma membrane, resulting in a conformational change which confers full enzymatic activity through the phosphorylation of the membrane-bound protein at two residues, Thr308, and Ser473. Activated Akt redistributes to cytoplasm and nucleus, where phosphorylation of specific substrates occurs. Both the presence and the activity of Akt in the nucleus have been described. An interesting mechanism that mediates nuclear translocation of Akt has been described in human mature T-cell leukemia: the product of TCL1 gene, Tcl1, interacts with the PH domain of phosphorylated Akt, thus driving Akt to the nucleus. In this context, Tcl1 may act as a direct transporter of Akt or may contribute to the formation of a complex that promotes the transport of active Akt to the nucleus, where it can phosphorylate nuclear substrates. A well described nuclear substrate if Foxo. IGF-1 triggers phosphorylation of Foxo by Akt inside the nucleus, where phospho-Foxo associates to 14.3.3 proteins that, in turn, promote its export to the cytoplasm where it is sequestered. Remarkably, Foxo phosphorylation by Akt has been shown to be a crucial event in Akt-dependent myogenesis. However, most Akt nuclear substrates have so far remained elusive, as well as nuclear Akt functions. This lack of information prompted us to undertake a search of substrates of Akt in the nucleus, by the combined use of 2D-separation/mass spectrometry and anti-Akt-phosphosubstrate antibody. This study presents evidence of A-type lamins as novel nuclear substrates of Akt. Lamins are type V intermediate filaments proteins found in the nucleus of higher eukaryotes where, together with lamin-binding proteins, they form the lamina at the nuclear envelope, providing mechanical stability for the nuclear membrane. By coimmunoprecipitation, it is demonstrated here that endogenous lamin A and Akt interact, and that A-type lamins are phosphorylated by Akt both in vitro and in vivo. Moreover, by phosphoaminoacid analysis and mutagenesis, it is further demonstrated that Akt phosphorylates lamin A at Ser404, and, more importantly, that while lamin A/C phosphorylation is stable throughout the cell cycle, phosphorylation of the precursor prelamin A becomes detectable as cells enter the G2 phase, picking at G2/M. This study also shows that lamin phosphorylation by Akt creates a binding site for 14.3.3 adaptors which, in turn, promote prelamin A degradation. While this mechanism is in agreement with a general role of Akt in the regulation of a subset of its substrates, opposite to what has been described, degradation is not mediated through a ubiquitination and proteasomal mechanism but through a lysosomal pathway, as indicated by the reverting action of the lysosomal inhibitor cloroquine. Phosphorylation is a key event in the mitotic breakdown of the nuclear lamina. However, the kinases and the precise sites of phosphorylation are scarcely known. Therefore, these results represent an important breakthrough in this very significant but understudied area. The phosphorylation of the precursor protein prelamin A and its subsequent degradation at G2/M, when both the nuclear envelop and the nuclear lamina disassemble, can be view as part of a mechanism to dispose off the precursor that is not needed in this precise context. The recently reported finding that patients affected by Emery-Dreifuss muscular dystrophy carry a mutation at Arg 401, in the Akt phosphorylation motif, open new perspective that warrant further investigation in this very important field.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Studio della trasduzione del Segnale Nucleare Inositide-Dipendente: identificazione di eEF1A2 come nuovo Fosfosubstrato di PKC βI

Introduction Phospholipase Cb1 (PLC-β1) is a key player in the regulation of nuclear inositol lipid signaling and of a wide range of cellular functions, such as proliferation and differentiation (1,2,3). PLCb1 signaling depends on the cleavage of phosphatidylinositol 4,5-bisphosphate and the formation of the second messengers diacylglycerol and Inositol tris-phosphate which activate canonical protein kinase C (cPKC) isoforms. Here we describe a proteomic approach to find out a potential effector of nuclear PLC-b1 dependent signaling during insulin stimulated myogenic differentiation. Methods Nuclear lysates obtained from insulin induced C2C12 myoblasts were immunoprecipitated with anti-phospho-substrate cPKC antibody. Proteins, stained with Comassie blue, were excised, digested and subsequently analysed in LC-MS/MS. For peptide sequence searching, the mass spectra were processed and analyzed using the Mascot MS/MS ion search program with the NCBI database. Western blotting, GST-pull down and co-immunoprecipitation were performed to study the interaction between eEF1A2 and cPKCs. Site direct mutagenesis was performed to confirm the phosphorylated motif recognized by the antibody. Immunofluorescence analysis, GFP-tagged eEF1A2 vector and subcellular fractionation were performed to study nuclear localization and relative distribution of eEF1A2. Results We have previously shown that PLC-β1 is greatly increased at the nuclear level during insulin-induced myoblasts differentiation and that this nuclear localization is essential for induction of differentiation. Thus, nuclear proteins of insulin stimulated C2C12 myoblasts, were immunoprecipitated with an anti-phospho-substrate cPKC antibody. After Electrophoretic gel separation of proteins immunoprecipitated, several molecules were identified by LC-MS/MS. Among these most relevant and unexpected was eukaryotic elongation factor 1 alpha 2 (eEF1A2). We found that eEF1A2 is phosphorylated by PKCb1 and that these two molecules coimmunolocalized at the nucleolar level. eEF1A2 could be phosphorylated in many sites among which both threonine and serine residues. By site direct mutagenesis we demonstrated that it is the serine residue of the motif recognized by the antibody that is specifically phosphorylated by PKCb1. The silencing of PLCb1 gives rise to a reduction of expression and phosphorylation levels of eEF1A2 indicating this molecule as a target of nuclear PLCb1 regulatory network during myoblasts differentiation.