<Emphasis Type="Italic">Rhodotorula taiwanensis</Emphasis> sp. nov., a novel yeast species from a plant in Taiwan

A novel anamorphic yeast strain, A1-01^T, belonging to the genus Rhodotorula was isolated from a plant in Taiwan and analysed morphologically, physiologically and phylogenetically. Neither ballistoconidia nor sexual reproduction was observed. Sequence analysis of the 26S rRNA gene and the ITS region indicate that Rhodosporidium sphaerocarpum is the most closely related species, with 14 and 24 nucleotide substitutions, respectively. The novel species differed physiologically from R. sphaerocarpum in its ability to assimilate ethylamine and cadaverine, its inability to assimilate ethanol and nitrite. From these comparative analyses, the following novel yeast species is proposed: Rhodotorula taiwanensis sp. nov. with the type strain of A1-01^T (BCRC 23118^T = CBS 11729^T).     

Increased Risk of Chronic Kidney Disease in Rheumatoid Arthritis Associated with Cardiovascular Complications – A National Population-Based Cohort Study

Background and Objectives

There have been few large population-based studies of the association between rheumatoid arthritis (RA) and chronic kidney disease (CKD) and glomerulonephritis. This nationwide cohort study investigated the risks of developing CKD and glomerulonephritis in patients with RA, and the associated risks for cardiovascular complications.

Methods

From the Taiwan National Health Insurance Research Database, we identified a study cohort of 12,579 patients with RA and randomly selected 37,737 subjects without RA as a control cohort. Each subject was individually followed for up for 5 years, and the risk of CKD was analyzed using Cox proportional hazards regression models.

Results

During the follow-up period, after adjusting for traditional cardiovascular risk factors RA was independently associated with a significantly increased risk of CKD (adjusted hazard ratio [aHR] 1.31; 95% confidence interval [CI] 1.23–1.40) and glomerulonephritis (aHR 1.55; 95% CI 1.37–1.76). Increased risk of CKD was also associated with the use of non-steroidal anti-inflammatory drugs, cyclosporine, glucocorticoids, mycophenolate mofetil, and cyclophosphamide. Patients with comorbidities had even greater increased risk of CKD. Moreover, RA patients with concurrent CKD had significantly higher likelihood of developing ischemic heart disease and stroke.

Conclusions

RA patients had higher risk of developing CKD and glomerulonephritis, independent of traditional cardiovascular risk factors. Their increased risk of CKD may be attributed to glomerulonephritis, chronic inflammation, comorbidities, and renal toxicity of antirheumatic drugs. Careful monitoring of renal function in RA patients and tight control of their comorbid diseases and cardiovascular risk factors are warranted.     

A Novel Peptide Enhances Therapeutic Efficacy of Liposomal Anti-Cancer Drugs in Mice Models of Human Lung Cancer

Lung cancer is the leading cause of cancer-related mortality worldwide. The lack of tumor specificity remains a major drawback for effective chemotherapies and results in dose-limiting toxicities. However, a ligand-mediated drug delivery system should be able to render chemotherapy more specific to tumor cells and less toxic to normal tissues. In this study, we isolated a novel peptide ligand from a phage-displayed peptide library that bound to non-small cell lung cancer (NSCLC) cell lines. The targeting phage bound to several NSCLC cell lines but not to normal cells. Both the targeting phage and the synthetic peptide recognized the surgical specimens of NSCLC with a positive rate of 75% (27 of 36 specimens). In severe combined immunodeficiency (SCID) mice bearing NSCLC xenografts, the targeting phage specifically bound to tumor masses. The tumor homing ability of the targeting phage was inhibited by the cognate synthetic peptide, but not by a control or a WTY-mutated peptide. When the targeting peptide was coupled to liposomes carrying doxorubicin or vinorelbine, the therapeutic index of the chemotherapeutic agents and the survival rates of mice with human lung cancer xenografts markedly increased. Furthermore, the targeting liposomes increased drug accumulation in tumor tissues by 5.7-fold compared with free drugs and enhanced cancer cell apoptosis resulting from a higher concentration of bioavailable doxorubicin. The current study suggests that this tumor-specific peptide may be used to create chemotherapies specifically targeting tumor cells in the treatment of NSCLC and to design targeted gene transfer vectors or it may be used one in the diagnosis of this malignancy.     

MDD-carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs

Background

Carbonylation, which takes place through oxidation of reactive oxygen species (ROS) on specific residues, is an irreversibly oxidative modification of proteins. It has been reported that the carbonylation is related to a number of metabolic or aging diseases including diabetes, chronic lung disease, Parkinson’s disease, and Alzheimer’s disease. Due to the lack of computational methods dedicated to exploring motif signatures of protein carbonylation sites, we were motivated to exploit an iterative statistical method to characterize and identify carbonylated sites with motif signatures.

Results

By manually curating experimental data from research articles, we obtained 332, 144, 135, and 140 verified substrate sites for K (lysine), R (arginine), T (threonine), and P (proline) residues, respectively, from 241 carbonylated proteins. In order to examine the informative attributes for classifying between carbonylated and non-carbonylated sites, multifarious features including composition of twenty amino acids (AAC), composition of amino acid pairs (AAPC), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM) were investigated in this study. Additionally, in an attempt to explore the motif signatures of carbonylation sites, an iterative statistical method was adopted to detect statistically significant dependencies of amino acid compositions between specific positions around substrate sites. Profile hidden Markov model (HMM) was then utilized to train a predictive model from each motif signature. Moreover, based on the method of support vector machine (SVM), we adopted it to construct an integrative model by combining the values of bit scores obtained from profile HMMs. The combinatorial model could provide an enhanced performance with evenly predictive sensitivity and specificity in the evaluation of cross-validation and independent testing.

Conclusion

This study provides a new scheme for exploring potential motif signatures at substrate sites of protein carbonylation. The usefulness of the revealed motifs in the identification of carbonylated sites is demonstrated by their effective performance in cross-validation and independent testing. Finally, these substrate motifs were adopted to build an available online resource (MDD-Carb, http://csb.cse.yzu.edu.tw/MDDCarb/) and are also anticipated to facilitate the study of large-scale carbonylated proteomes.

     

Investigation and identification of protein carbonylation sites based on position-specific amino acid composition and physicochemical features

Background

Protein carbonylation, an irreversible and non-enzymatic post-translational modification (PTM), is often used as a marker of oxidative stress. When reactive oxygen species (ROS) oxidized the amino acid side chains, carbonyl (CO) groups are produced especially on Lysine (K), Arginine (R), Threonine (T), and Proline (P). Nevertheless, due to the lack of information about the carbonylated substrate specificity, we were encouraged to develop a systematic method for a comprehensive investigation of protein carbonylation sites.

Results

After the removal of redundant data from multipe carbonylation-related articles, totally 226 carbonylated proteins in human are regarded as training dataset, which consisted of 307, 126, 128, and 129 carbonylation sites for K, R, T and P residues, respectively. To identify the useful features in predicting carbonylation sites, the linear amino acid sequence was adopted not only to build up the predictive model from training dataset, but also to compare the effectiveness of prediction with other types of features including amino acid composition (AAC), amino acid pair composition (AAPC), position-specific scoring matrix (PSSM), positional weighted matrix (PWM), solvent-accessible surface area (ASA), and physicochemical properties. The investigation of position-specific amino acid composition revealed that the positively charged amino acids (K and R) are remarkably enriched surrounding the carbonylated sites, which may play a functional role in discriminating between carbonylation and non-carbonylation sites. A variety of predictive models were built using various features and three different machine learning methods. Based on the evaluation by five-fold cross-validation, the models trained with PWM feature could provide better sensitivity in the positive training dataset, while the models trained with AAindex feature achieved higher specificity in the negative training dataset. Additionally, the model trained using hybrid features, including PWM, AAC and AAindex, obtained best MCC values of 0.432, 0.472, 0.443 and 0.467 on K, R, T and P residues, respectively.

Conclusion

When comparing to an existing prediction tool, the selected models trained with hybrid features provided a promising accuracy on an independent testing dataset. In short, this work not only characterized the carbonylated substrate preference, but also demonstrated that the proposed method could provide a feasible means for accelerating preliminary discovery of protein carbonylation.

     

Molecular phylogeny of elopomorph fishes inferred from mitochondrial 12S ribosomal RNA sequences

Wang, C. H., Kuo, C. H., Mok, H. K. & Lee, S. C. (2003). Molecular phylogeny of elopomorph fishes inferred from mitochondrial 12S ribosomal RNA sequences. — Zoologica Scripta , 32 , 231–241.
Fishes of the superorder Elopomorpha include tenpounders ( Elops ), tarpon ( Megalops ), bonefishes ( Albula ), spiny eels ( Notacanthus ), apodes, and gulper eels; despite highly diversified morphological features, all undergo a leptocephalus larval stage and are thus treated (although with some dissenting views) as monophyletic. Following analysis of 12S rRNA sequences we present results that confirm a monophyletic Elopomorpha clearly separated from Clupeomorpha. Elops and Megalops share a common ancestor and are clustered in a subclade at the bottom of Elopomorpha. Albula and Notacanthus share a common ancestor forming the sister group to Anguilliformes. Saccopharyngiformes is not a sister group of Anguilliformes, as the single species sequenced here is nested deeply within the latter. Neither the suborder Congroidei nor the superfamily Congroidea within Anguilliformes are monophyletic.     

Differentiation of sourdough yeast species by a novel species-specific PCR assay

The objective of this study was to develop species-specific primer pairs based on the internal transcribed spacer region (ITS) of the ribosome DNA for species identification of the frequently found sourdough yeast species. Species-specific primers were designed by the alignment of sourdough yeast ITS sequences, which were then employed for PCR using the template DNA of sourdough yeast strains. PCR primers were shown to be specific for the following species: Issatchenkia orientalis (Candida krusei), C. humilis, Kazachstania exigua (C. holmii), Pichia anomala and P. subpelliculosa. Therefore, we conclude that our novel species-specific primers could be used to rapidly and accurately identify the most frequent sourdough yeast species using a PCR-based assay.