CDKN2A mutations and MC1R variants in Italian patients with single or multiple primary melanoma

We evaluated the contribution of germline CDKN2A mutations and MC1R variants to the development of melanoma in a hospital-based study of single (SPM, n = 398) and multiple primary melanoma (MPM, n = 95). The overall frequency of CDKN2A mutations was 15.2%, and four-fold higher in MPM than in SPM cases (OR = 4.27; 95% CI 2.43-7.53). The likelihood of identifying a CDKN2A mutation increased with family history of melanoma and younger age at diagnosis in MPM cases. Compared to SPM patients, the risk of harboring a CDKN2A mutation rose as the number of primary melanomas increased and was not influenced by family history. The G101W and E27X founder mutations were the most common. Several other mutations (W15X, Q50X, R58X, A68L, A127P and H142R) were detected for the first time in Italian patients. One novel mutation, T77A, was identified. Several non-coding variants with unknown functional significance were also found (5'UTR -25C > T, -21C > T, -67G > C, IVS1 +37G > C); the novel 5'UTR -21C > T variant was not detected in controls. The CDKN2A A148T polymorphism was more frequent in MPM patients than in the control population (15.7% versus 6.6%). Compared to the SPM patients, MPM cases had a 2-fold increased probability of being MC1R variant carriers and a higher probability of carrying two or more variants. No specific association was observed between the type of variant and the number of melanomas, suggesting that the number rather than the type of MC1R variant increases the risk of MPM. We observed no interaction between CDKN2A status and the presence of MC1R variants. The high frequency of CDKN2A mutations in our MPM cases, independent of their family history, is of relevance to genetic counseling and testing in our population.     

Local interactions in protein folding determined through an inverse folding model

We adopt a model of inverse folding in which folding stability results from the combination of the hydrophobic effect with local interactions responsible for secondary structure preferences. Site-specific amino acid distributions can be calculated analytically for this model. We determine optimal parameters for the local interactions by fitting the complete inverse folding model to the site-specific amino acid distributions found in the Protein Data Bank. This procedure reduces drastically the influence on the derived parameters of the preference of different secondary structures for buriedness, which affects local interaction parameters determined through the standard approach based on amino acid propensities. The quality of the fit is evaluated through the likelihood of the observed amino acid distributions given the model and the Bayesian Information Criterion, which indicate that the model with optimal local interaction parameters is strongly preferable to the model where local interaction parameters are determined through propensities. The optimal model yields a mean correlation coefficient r = 0.96 between observed and predicted amino acid distributions. The local interaction parameters are then tested in threading experiments, in combination with contact interactions, for their capacity to recognize the native structure and structures similar to the native against unrelated ones. In a challenging test, proteins structurally aligned with the Mammoth algorithm are scored with the effective free energy function. The native structure gets the highest stability score in 100% of the cases, a high recognition rate comparable to that achieved against easier decoys generated by gapless threading. We then examine proteins for which at least one highly similar template exists. In 61% of the cases, the structure with the highest stability score excluding the native belongs to the native fold, compared to 60% if we use local interaction parameters derived from the usual amino acid propensities and 52% if we use only contact interactions. A highly similar structure is present within the five best stability scores in 82%, 81%, and 76% of the cases, for local interactions determined through inverse folding, through propensity, and set to zero, respectively. These results indicate that local interactions improve substantially the performances of contact free energy functions in fold recognition, and that similar structures tend to get high stability scores, although they are often not high enough to discriminate them from unrelated structures. This work highlights the importance to apply more challenging tests, as the recognition of homologous structures, for testing stability scores for protein folding.     

Nanoelectrode ensembles as recognition platform for electrochemical immunosensors

In this study we demonstrate the possibility to prepare highly sensitive nanostructured electrochemical immunosensors by immobilizing biorecognition elements on nanoelectrode ensembles (NEEs) prepared in track-etch polycarbonate membranes. The gold nanodisk electrodes act as electrochemical transducers while the surrounding polycarbonate binds the antibody-based biorecognition layer. The interaction between target protein and antibody is detected by suitable secondary antibodies labelled with a redox enzyme. A redox mediator, added to the sample solution, shuttles electrons from the nanoelectrodes to the biorecognition layer, so generating an electrocatalytic signal. This allows one to fully exploit the highly improved signal-to-background current ratio, typical of NEEs. In particular, the receptor protein HER2 was studied as the target analyte. HER2 detection allows the identification of breast cancer that can be treated with the monoclonal antibody trastuzumab. NEEs were functionalized with trastuzumab which interacts specifically with HER2. The biorecognition process was completed by adding a primary antibody and a secondary antibody labelled with horseradish peroxidase. Hydrogen peroxide was added to modulate the label electroactivity; methylene blue was the redox mediator generating voltammetric signals. NEEs functionalized with trastuzumab were tested to detect small amounts of HER2 in diluted cell lysates and tumour lysates.     

A glycine-arginine domain in control of the human MRE11 DNA repair protein

Human MRE11 is a key enzyme in DNA double-strand break repair and genome stability. Human MRE11 bears a glycine-arginine-rich (GAR) motif that is conserved among multicellular eukaryotic species. We investigated how this motif influences MRE11 function. Human MRE11 alone or a complex of MRE11, RAD50, and NBS1 (MRN) was methylated in insect cells, suggesting that this modification is conserved during evolution. We demonstrate that PRMT1 interacts with MRE11 but not with the MRN complex, suggesting that MRE11 arginine methylation occurs prior to the binding of NBS1 and RAD50. Moreover, the first six methylated arginines are essential for the regulation of MRE11 DNA binding and nuclease activity. The inhibition of arginine methylation leads to a reduction in MRE11 and RAD51 focus formation on a unique double-strand break in vivo. Furthermore, the MRE11-methylated GAR domain is sufficient for its targeting to DNA damage foci and colocalization with gamma-H2AX. These studies highlight an important role for the GAR domain in regulating MRE11 function at the biochemical and cellular levels during DNA double-strand break repair.     

A one dimensional moving bed biofilm reactor model for nitrification of municipal wastewaters

This work presents a one-dimensional model of a moving bed bioreactor (MBBR) process designed for the removal of nitrogen from raw wastewaters. A comprehensive experimental strategy was deployed at a semi-industrial pilot-scale plant fed with a municipal wastewater operated at 10–12 °C, and surface loading rates of 1–2 g filtered COD/m² d and 0.4–0.55 g NH₄-N/m² d. Data were collected on influent/effluent composition, and on measurement of key variables or parameters (biofilm mass and maximal thickness, thickness of the limit liquid layer, maximal nitrification rate, oxygen mass transfer coefficient). Based on time-course variations in these variables, the MBBR model was calibrated at two time-scales and magnitudes of dynamic conditions, i.e., short-term (4 days) calibration under dynamic conditions and long-term (33 days) calibration, and for three types of carriers. A set of parameters suitable for the conditions was proposed, and the calibrated parameter set is able to simulate the time-course change of nitrogen forms in the effluent of the MBBR tanks, under the tested operated conditions. Parameters linked to diffusion had a strong influence on how robustly the model is able to accurately reproduce time-course changes in effluent quality. Then the model was used to optimize the operations of MBBR layout. It was shown that the main optimization track consists of the limitation of the aeration supply without changing the overall performance of the process. Further work would investigate the influence of the hydrodynamic conditions onto the thickness of the limit liquid layer and the “apparent” diffusion coefficient in the biofilm parameters.

     

Sequence- and position-dependent tagging protects extracellular-regulated kinase 3 protein from 26S proteasome-mediated degradation

Extracellular-regulated kinase 3, an atypical member of the mitogen-activated protein kinase subfamily of extracellular-regulated kinases, was originally identified in 1991. Little is known about the biochemical properties, regulation, and biological functions of this protein kinase, partially due to the unstable nature of endogenous and low ectopical expression level of the protein. Here, we report that a single C-terminal c-myc tag increases the half-life of ectopic expressed tagged extracellular-regulated kinase 3 approximately four times compared to the reported 30 min half-life time for the endogenous protein and ectopic expressed extracellular-regulated kinase 3 deprived of its c-myc tag. These findings indicate that this C-terminal tag stabilizes the extracellular-regulated kinase 3. The stabilizing effect of the C-terminal c-myc tag is observed in all cell types tested, but is position- and tag sequence-dependent as neither N-terminal c-myc tag nor C-terminal HA tag stabilize the protein. The c-myc tag on extracellular-regulated kinase 3 did not interfere with its kinase activity, nor did it abrogate its ability to interacts with its bona fide substrate mitogen-activated protein kinase-activated protein kinase 5, indicating that tagging did not alter the known biological properties of the protein. Stabilization of the tagged extracellular-regulated kinase 3 protein probably results from reduced ubiquitination. In conclusion, position and sequence specific tagging should provide an easy and useful tool to generate a more stable protein that can functionally substitute the endogenous unstable protein. A stabilized variant may facilitate studies on the biological role of the protein.     

Nanoprecipitation versus emulsion-based techniques for the encapsulation of proteins into biodegradable nanoparticles and process-related stability issues

The goal of this study was to investigate the entrapment of 3 different model proteins (tetanus toxoid, lysozyme, and insulin) into poly(D,L-lactic acid) and poly(D,L-lactic-co-glycolic acid) nanoparticles and to address process-related stability issues. For that purpose, a modified nanoprecipitation method as well as 2 emulsion-based encapsulation techniques (ie, a solid-in oil-in water (s/o/w) and a double emulsion (w₁/o/w₂) method) were used. The main modification of nanoprecipitation involved the use of a wide range of miscible organic solvents such as dimethylsulfoxide and ethanol instead of the common acetone and water. The results obtained showed that tetanus toxoid and lysozyme were efficiently incorporated by the double emulsion procedure when ethyl acetate was used as solvent (>80% entrapment efficiency), whereas it was necessary to use methylene chloride to achieve high insulin entrapment efficiencies. The use of the s/o/w method or the formation of a more hydrophobic protein-surfactant ion pair did not improve protein loading. The nanoprecipitation method led to a homogenous population of small nanoparticles (with size ranging from ≈130 to 560 nm) and in some cases also improved experimental drug loadings, especially for lysozyme (entrapment efficiency >90%). With respect to drug content determination, a simple and quick matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method provided results very close to those obtained by reverse phase-high-performance liquid chromatography. With respect to protein stability, the duration and intensity of sonication were not a concern for tetanus toxoid, which retained more than 95% of its antigenicity after treatment for 1 minute. Only a high methylene chloride:water ratio was shown to slightly decrease toxoid antigenicity. Finally, no more than 3.3% of A21 desamido insulin and only traces of covalent insulin dimer were detected in nanoparticles. In conclusion, both the double emulsion and nanoprecipitation methods allowed efficient protein encapsulation. MALDI-TOF MS allowed accurate drug content determination. The manufacturing processes evaluated did not damage the primary structure of insulin. Published: December 1, 2005     

Principal eigenvector of contact matrices and hydrophobicity profiles in proteins

With the aim of studying the relationship between protein sequences and their native structures, we adopted vectorial representations for both sequence and structure. The structural representation was based on the principal eigenvector of the fold's contact matrix (PE). As has been recently shown, the latter encodes sufficient information for reconstructing the whole contact matrix. The sequence was represented through a hydrophobicity profile (HP), using a generalized hydrophobicity scale that we obtained from the principal eigenvector of a residue-residue interaction matrix, and denoted as interactivity scale. Using this novel scale, we defined the optimal HP of a protein fold, and, by means of stability arguments, predicted to be strongly correlated with the PE of the fold's contact matrix. This prediction was confirmed through an evolutionary analysis, which showed that the PE correlates with the HP of each individual sequence adopting the same fold and, even more strongly, with the average HP of this set of sequences. Thus, protein sequences evolve in such a way that their average HP is close to the optimal one, implying that neutral evolution can be viewed as a kind of motion in sequence space around the optimal HP. Our results indicate that the correlation coefficient between N-dimensional vectors constitutes a natural metric in the vectorial space in which we represent both protein sequences and protein structures, which we call vectorial protein space. In this way, we define a unified framework for sequence-to-sequence, sequence-to-structure and structure-to-structure alignments. We show that the interactivity scale is nearly optimal both for the comparison of sequences to sequences and sequences to structures.