The nucleotide and partial amino acid sequences of rat fetuin

Fetuins are among the major plasma proteins, yet their biological role has remained elusive. Here we report the molecular cloning of rat fetuin and the sequence analysis of a full-length clone, RF619 of 1456 bp with an open reading frame of 1056 bp encoding 352 amino acid residues. The coding part of RF619 was identical with the cDNA sequence of the natural inhibitor of the insulin receptor tyrosine kinase from rat (pp63) except for four substitutions and a single base insertion causing divergence of the predicted protein sequences. Partial amino acid sequences of rat plasma fetuin were in agreement with the predictions based on the RF619 cDNA. Purified rat fetuin inhibited the insulin receptor tyrosine kinase in vitro. Therefore, we conclude that RF619 and pp63 cDNA encode the same protein, i.e. authentic rat fetuin which is a functional tyrosine kinase inhibitor

Application of multiple statistical tests to enhance mass spectrometry-based biomarker discovery

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry-based biomarker discovery has long been hampered by the difficulty in reconciling lists of discriminatory peaks identified by different laboratories for the same diseases studied. We describe a multi-statistical analysis procedure that combines several independent computational methods. This approach capitalizes on the strengths of each to analyze the same high-resolution mass spectral data set to discover consensus differential mass peaks that should be robust biomarkers for distinguishing between disease states.</p> <p>Results</p> <p>The proposed methodology was applied to a pilot narcolepsy study using logistic regression, hierarchical clustering, t-test, and CART. Consensus, differential mass peaks with high predictive power were identified across three of the four statistical platforms. Based on the diagnostic accuracy measures investigated, the performance of the consensus-peak model was a compromise between logistic regression and CART, which produced better models than hierarchical clustering and t-test. However, consensus peaks confer a higher level of confidence in their ability to distinguish between disease states since they do not represent peaks that are a result of biases to a particular statistical algorithm. Instead, they were selected as differential across differing data distribution assumptions, demonstrating their true discriminatory potential.</p> <p>Conclusion</p> <p>The methodology described here is applicable to any high-resolution MALDI mass spectrometry-derived data set with minimal mass drift which is essential for peak-to-peak comparison studies. Four statistical approaches with differing data distribution assumptions were applied to the same raw data set to obtain consensus peaks that were found to be statistically differential between the two groups compared. These consensus peaks demonstrated high diagnostic accuracy when used to form a predictive model as evaluated by receiver operating characteristics curve analysis. They should demonstrate a higher discriminatory ability as they are not biased to a particular algorithm. Thus, they are prime candidates for downstream identification and validation efforts.</p

Serum Apolipoproteins C-I and C-III Are Reduced in Stomach Cancer Patients: Results from MALDI-Based Peptidome and Immuno-Based Clinical Assays

Finding new peptide biomarkers for stomach cancer in human sera that can be implemented into a clinically practicable prediction method for monitoring of stomach cancer. We studied the serum peptidome from two different biorepositories. We first employed a C8-reverse phase liquid chromatography approach for sample purification, followed by mass-spectrometry analysis. These were applied onto serum samples from cancer-free controls and stomach cancer patients at various clinical stages. We then created a bioinformatics analysis pipeline and identified peptide signature discriminating stomach adenocarcinoma patients from cancer-free controls. Matrix Assisted Laser Desorption/Ionization–Time of Flight (MALDI-TOF) results from 103 samples revealed 9 signature peptides; with prediction accuracy of 89% in the training set and 88% in the validation set. Three of the discriminating peptides discovered were fragments of Apolipoproteins C-I and C-III (apoC-I and C-III); we further quantified their serum levels, as well as CA19-9 and CRP, employing quantitative commercial-clinical assays in 142 samples. ApoC-I and apoC-III quantitative results correlated with the MS results. We then employed apoB-100-normalized apoC-I and apoC-III, CA19-9 and CRP levels to generate rules set for stomach cancer prediction. For training, we used sera from one repository, and for validation, we used sera from the second repository. Prediction accuracies of 88.4% and 74.4% were obtained in the training and validation sets, respectively. Serum levels of apoC-I and apoC-III combined with other clinical parameters can serve as a basis for the formulation of a diagnostic score for stomach cancer patients

Biochemistry Instructors’ Views toward Developing and Assessing Visual Literacy in Their Courses

Biochemistry instructors are inundated with various representations from which to choose to depict biochemical phenomena. Because of the immense amount of visual know-how needed to be an expert biochemist in the 21st century, there have been calls for instructors to develop biochemistry students’ visual literacy. However, visual literacy has multiple aspects, and determining which area to develop can be quite daunting. Therefore, the goals of this study were to determine what visual literacy skills biochemistry instructors deem to be most important and how instructors develop and assess visual literacy skills in their biochemistry courses. In order to address these goals, a needs assessment was administered to a national sample of biochemistry faculty at four-year colleges and universities. Based on the results of the survey, a cluster analysis was conducted to group instructors into categories based on how they intended to develop visual literacy in their courses. A misalignment was found between the visual literacy skills that were most important and how instructors developed visual literacy. In addition, the majority of instructors assumed these skills on assessments rather than explicitly testing them. Implications focus on the need for better measures to assess visual literacy skills directly

An Expanded Set of Amino Acid Analogs for the Ribosomal Translation of Unnatural Peptides

BACKGROUND: The application of in vitro translation to the synthesis of unnatural peptides may allow the production of extremely large libraries of highly modified peptides, which are a potential source of lead compounds in the search for new pharmaceutical agents. The specificity of the translation apparatus, however, limits the diversity of unnatural amino acids that can be incorporated into peptides by ribosomal translation. We have previously shown that over 90 unnatural amino acids can be enzymatically loaded onto tRNA. METHODOLOGY/PRINCIPAL FINDINGS: We have now used a competition assay to assess the efficiency of tRNA-aminoacylation of these analogs. We have also used a series of peptide translation assays to measure the efficiency with which these analogs are incorporated into peptides. The translation apparatus tolerates most side chain derivatives, a few alpha,alpha disubstituted, N-methyl and alpha-hydroxy derivatives, but no beta-amino acids. We show that over 50 unnatural amino acids can be incorporated into peptides by ribosomal translation. Using a set of analogs that are efficiently charged and translated we were able to prepare individual peptides containing up to 13 different unnatural amino acids. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that a diverse array of unnatural building blocks can be translationally incorporated into peptides. These building blocks provide new opportunities for in vitro selections with highly modified drug-like peptides