Probabilistic protein function prediction from heterogeneous genome-wide data

Dramatic improvements in high throughput sequencing technologies have led to a staggering growth in the number of predicted genes. However, a large fraction of these newly discovered genes do not have a functional assignment. Fortunately, a variety of novel high-throughput genome-wide functional screening technologies provide important clues that shed light on gene function. The integration of heterogeneous data to predict protein function has been shown to improve the accuracy of automated gene annotation systems. In this paper, we propose and evaluate a probabilistic approach for protein function prediction that integrates protein-protein interaction (PPI) data, gene expression data, protein motif information, mutant phenotype data, and protein localization data. First, functional linkage graphs are constructed from PPI data and gene expression data, in which an edge between nodes (proteins) represents evidence for functional similarity. The assumption here is that graph neighbors are more likely to share protein function, compared to proteins that are not neighbors. The functional linkage graph model is then used in concert with protein domain, mutant phenotype and protein localization data to produce a functional prediction. Our method is applied to the functional prediction of Saccharomyces cerevisiae genes, using Gene Ontology (GO) terms as the basis of our annotation. In a cross validation study we show that the integrated model increases recall by 18%, compared to using PPI data alone at the 50% precision. We also show that the integrated predictor is significantly better than each individual predictor. However, the observed improvement vs. PPI depends on both the new source of data and the functional category to be predicted. Surprisingly, in some contexts integration hurts overall prediction accuracy. Lastly, we provide a comprehensive assignment of putative GO terms to 463 proteins that currently have no assigned function.     

HER2 status in ovarian carcinomas: a multicenter GINECO study of 320 patients

Background

Despite a typically good response to first-line combination chemotherapy, the prognosis for patients with advanced ovarian cancer remains poor because of acquired chemoresistance. The use of targeted therapies such as trastuzumab may potentially improve outcomes for patients with ovarian cancer. HER2 overexpression/amplification has been reported in ovarian cancer, but the exact percentage of HER2-positive tumors varies widely in the literature. In this study, HER2 gene status was evaluated in a large, multicentric series of 320 patients with advanced ovarian cancer, including 243 patients enrolled in a multicenter prospective clinical trial of paclitaxel/carboplatin-based chemotherapy.

Methodology/Principal Findings

The HER2 status of primary tumors and metastases was evaluated by both immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) analysis of paraffin-embedded tissue on conventional slides. The prognostic impact of HER2 expression was analyzed. HER2 gene was overexpressed and amplified in 6.6% of analyzed tumors. Despite frequent intratumoral heterogeneity, no statistically significant difference was detected between primary tumors and corresponding metastases.

Conclusions/Significance

Our results show that the decision algorithm usually used in breast cancer (IHC as a screening test, with equivocal results confirmed by FISH) is appropriate in ovarian cancer. In contrast to previous series, HER2-positive status did not influence outcome in the present study, possibly due to the fact that patients in our study received paclitaxel/carboplatin-based chemotherapy. This raises the question of whether HER2 status and paclitaxel sensitively are linked.     

Myocontrol in aging

Myoelectric (EMG) signals are used in assistive technology for prostheses, computer and domestic control. An experimental study previously conducted with young participants was replicated with elderly persons in order to assess the effect of age on the ability to control myoelectric amplitude (or myocontrol). Participants performed pointing tasks as the myoelectric amplitude was captured by a surface electrode in two modalities (sustained: stabilize the amplitude after reaching the desired level; impulsion: return immediately to resting amplitude). There was a significant decrease of performance with Age. However, the patterns of performance of young and aged were noticeably similar. The Impulsion modality was difficult (high rates of failure) and the speed-accuracy trade-offs predicted by Fitts' law were absent (bow-shaped patterns as function of target amplitude instead of logarithmic increase). Conversely, the reach phase of the Sustained modality followed the predictions of Fitts' law. However, the slope of the regression line with Fitts' index of difficulty was quite steeper in aged than in young participants. These findings suggest that 1) all participants, young and aged, adapt their reaching strategies to the anticipated state (sustained amplitude or not) and/or to the difficulty of the task, 2) myocontrol in aged persons is more fragile, i.e., performance is markedly degraded as the difficulty of the task increases. However, when individual performance was examined, some aged individuals were found to perform as well as the young participants, congruently with the literature on good aging.     

Diversification of the insulin receptor family in the helminth parasite Schistosoma mansoni

Insulin signalling is a very ancient and well conserved pathway in metazoan cells, dependent on insulin receptors (IR) which are transmembrane proteins with tyrosine kinase activity. A unique IR is usually present in invertebrates whereas two IR members are found with different functions in vertebrates. This work demonstrates the existence of two distinct IR homologs (SmIR-1 and SmIR-2) in the parasite trematode Schistosoma mansoni. These two receptors display differences in several structural motifs essential for signalling and are differentially expressed in parasite tissues, suggesting that they could have distinct functions. The gene organization of SmIR-1 and SmIR-2 is similar to that of the human IR and to that of the IR homolog from Echinococcus multilocularis (EmIR), another parasitic platyhelminth. SmIR-1 and SmIR-2 were shown to interact with human pro-insulin but not with pro-insulin-like growth factor-1 in two-hybrid assays. Phylogenetic results indicated that SmIR-2 and EmIR might be functional orthologs whereas SmIR-1 would have emerged to fulfil specific functions in schistosomes.     

National mass drug administration costs for lymphatic filariasis elimination

Background

Because lymphatic filariasis (LF) elimination efforts are hampered by a dearth of economic information about the cost of mass drug administration (MDA) programs (using either albendazole with diethylcarbamazine [DEC] or albendazole with ivermectin), a multicenter study was undertaken to determine the costs of MDA programs to interrupt transmission of infection with LF. Such results are particularly important because LF programs have the necessary diagnostic and treatment tools to eliminate the disease as a public health problem globally, and already by 2006, the Global Programme to Eliminate LF had initiated treatment programs covering over 400 million of the 1.3 billion people at risk.

Methodology/Principal Findings

To obtain annual costs to carry out the MDA strategy, researchers from seven countries developed and followed a common cost analysis protocol designed to estimate 1) the total annual cost of the LF program, 2) the average cost per person treated, and 3) the relative contributions of the endemic countries and the external partners. Costs per person treated ranged from $0.06 to $2.23. Principal reasons for the variation were 1) the age (newness) of the MDA program, 2) the use of volunteers, and 3) the size of the population treated. Substantial contributions by governments were documented – generally 60%–90% of program operation costs, excluding costs of donated medications.

Conclusions/Significance

MDA for LF elimination is comparatively inexpensive in relation to most other public health programs. Governments and communities make the predominant financial contributions to actual MDA implementation, not counting the cost of the drugs themselves. The results highlight the impact of the use of volunteers on program costs and provide specific cost data for 7 different countries that can be used as a basis both for modifying current programs and for developing new ones.     

SELDI-TOF-MS of saliva: methodology and pre-treatment effects

Interest in saliva as a diagnostic fluid for monitoring general health and for early diagnosis of disease has increased in the last few years. In particular, efforts have focused on the generation of protein maps of saliva using advanced proteomics technology. Surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a novel high throughput and extremely sensitive proteomic approach that allows protein expression profiling of large sets of complex biological specimens. In this study, large scale profiling of salivary proteins and peptides, ranging from 2 to 100kDa was demonstrated using SELDI-TOF-MS. Various methodological aspects and pre-analytical variables were analysed with respect to their effects on saliva SELDI-TOF-MS profiling. Results show that chip surface type and sample type (unstimulated versus stimulated) critically affect the amount and composition of detected salivary proteins. Factors that influenced normal saliva protein profiling were matrix composition, sample dilution and binding buffer properties. Delayed processing time experiments show certain new peptides evolving 3h post-saliva donation, and quantitative analyses indicate relative intensity of other proteins and peptides changing with time. The addition of protease inhibitors partly counteracted the destabilization of certain protein/peptide mass spectra over time suggesting that some proteins in saliva are subject to digestion by intrinsic salivary proteases. SELDI-TOF-MS profiles also changed by varying storage time and storage temperature whereas centrifugation speed and freeze-thaw cycles had minimal impact. In conclusion, SELDI-TOF-MS offers a high throughput platform for saliva protein and peptide profiling, however, (pre-)analytical conditions must be taken into account for valid interpretation of the acquired data.     

Antimicrobial Peptides and their Potential as Oral Therapeutic Agents

Dental caries (tooth decay) and periodontal diseases are the most prevalent bacterial infectious diseases of mankind, together affecting almost the entire population of the world. Both diseases are caused by oral bacteria that exist as components of a polymicrobial biofilm, known as dental plaque, on the tooth surface. The control of specific types of bacteria and/or total numbers of bacteria in dental plaque could lead to prevention or resolution of disease. Antimicrobial peptides isolated from a wide range of natural sources have been known for over 30 years yet little progress had been made in the therapeutic application of these peptides. This is due in part to the characteristics, including susceptibility to proteolysis, of the cationic amphipathic antimicrobial peptides that form the majority of peptides discovered to date. Bovine milk is a readily available source of a range of bioactive peptides. We have isolated and characterized a novel anionic antimicrobial peptide, Kappacin, from bovine milk. Antibacterial activity of the peptide is increased when it is complexed with zinc ions. We have demonstrated that a Kappacin:Zn²⁺ preparation is able to suppress the growth of oral cariogenic bacteria in a biofilm. The Kappacin:Zn²⁺ antibacterial complex may have potential as an additive to oral care products and other delivery vehicles for the control of oral disease.     

HbS-Savaria: The Anti-polymerization Effect of a Single Mutation in Human α-chains

Recombinant α-Savaria globin (α^S49R) was assembled with β^S chains by the alloplex intermediate pathway to generate tetrameric rHbS-Sarvaria (α₂^S49Rβ₂^E6V) that exhibited normal O₂ affinity and co-operatively at pH 7.4. Allosteric effectors, 2,3-DPG, L35, and NaCl increased O₂ affinity by 15%. Bohr effects were similar for rHbS-Savaria and HbS (0.38 ± 0.025 vs. 0.46 ± 0.03, respectively). The C_SAT of HbS increased from 16.7 ± 0.8 to 27.0 ± 1.0 g/dL. Co-polymerization demonstrated inhibition predominantly by the Cis-dimer. Molecular modeling indicated that the positive charge at α-49 generated a strong anion-binding site and reduced flexibility of the CD-region by restricting movement in the E and F helices. The molecular distance between Arg-49 and Asn-78 in the neighboring double strand decreased, and electrostatic repulsion between the inter-double strands increased, resulting in inhibition of polymerization. The Savaria mutation may be useful for the design of super-inhibitory α-chains and gene therapy of sickle cell anemia.     

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications

Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOF mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process.