High-Resolution Solution NMR Structure of the Minimal Active Domain of the Human Immunodeficiency Virus Type-2 Nucleocapsid Protein^†^,^‡

The retroviral nucleocapsid (NC) protein is a multifunctional protein essential for RNA genome packaging and viral infectivity. The NC protein, NCp8, of the human immunodeficiency virus type-II (HIV-2) is a 49 amino acid peptide containing two zinc fingers, of the type C-X2-C-X4-H-X4-C, connected by seven amino acid residues, called the “basic amino acid cluster.” It has been shown that the N-terminal zinc finger flanked by the basic amino acid cluster is the minimal active domain for the specific binding to viral RNA and other functions. However, the structure−activity relationships of NCp8 have not been investigated in detail. In the present study, the three-dimensional structure of a 29 amino acid peptide, including the minimal active domain (NCp8-f1), was determined by two-dimensional 1H NMR spectroscopy with simulated annealing calculations. A total of 15 converged structures of NCp8-f1 were obtained on the basis of 355 experimental constraints, including 343 distance constraints obtained from nuclear Overhauser effect connectivities, 12 torsion angle (φ, χ1) constraints, and four constraints for zinc binding. The root-mean-square deviation of the 15 converged structures was 0.29 ± 0.04 Å for the backbone atoms (N, Cα, C) and 1.27 ± 0.13 Å for all heavy atoms. Interestingly, the basic amino acid cluster itself was defined well, with a loop-like conformation in which three arginine residues in the cluster and one arginine residue in the zinc finger are located approximately in the same plane of the molecule and are exposed to the solvent. The structure−activity relationships are discussed on the basis of the comparison of this well-defined structure with those of other NC proteins

High-Yield Peptide-Extraction Method for the Discovery of Subnanomolar Biomarkers from Small Serum Samples

Serum proteins/peptides reflect physiological or pathological states in humans and are an attractive target for the discovery of disease biomarkers. However, the existence of high-abundance proteins and the large dynamic range of serum proteins/peptides make any quantitative analysis of low-abundance proteins/peptides challenging. Furthermore, analyses of peptides, including the cleaved fragments of proteins, are difficult because of carrier protein binding. Here, we developed a differential solubilization (DS) method to extract low-molecular-weight proteins/peptides in serum with good reproducibility and yield as compared to typical peptide-extraction methods such as organic solvent precipitation and ultrafiltration. Using the DS method combined with reverse-phase HPLC fractionation followed by MALDI-TOF-MS, we performed high-quality comparative analyses of more than 1500 peptides from 1 μL of serum samples, including low-abundance peptides in the subnanomolar range and containing many peptides bound to carrier proteins such as albumin. We applied this method and successfully discovered four new biomarker candidates of colon cancer, none of which have previously been observed in serum and one of which is a fragment of the protein zyxin that possibly originated from tumor cells. Our results indicate that serum peptide analyses based on the DS method should greatly contribute to the discovery of novel low-abundance biomarkers

MOESM1 of Fibrinogen alpha C chain 5.9Â kDa fragment (FIC5.9), a biomarker for various pathological conditions, is produced in post-blood collection by fibrinolysis and coagulation factors

Additional file 1. Analysis of FIC5.9 releasing in coagulation factor-deficient plasma. (A) Mass spectrum of coagulation-depleted plasma reactivated using an APTT reagent. Synthesized FIC5.9 is indicated with a red line and SI-labeled FIC5.9 peptide is indicated with a blue line. (B) Quantification of FIC5.9 released by coagulation reactivation. The relative intensity of FIC5.9 was calculated by comparison with the intensity of the internal standard (SI-FIC5.9). The error bars represent the standard error of the mean (SEM) for three experiments

The RNA Recognition Mechanism of Human Immunodeficiency Virus (HIV) Type 2 NCp8 Is Different from That of HIV-1 NCp7

The nucleocapsid (NC) protein of HIV, which contains two CCHC-type zinc fingers connected by a linker, is a multifunctional protein involved in many of the critical steps of the HIV life cycle. HIV-1 and HIV-2 contain NC proteins NCp7 and NCp8, respectively. The amino acid sequences of both NC proteins are 67% identical. For NCp7, the important elements for RNA binding were found to be the first zinc finger flanked by the linker, as the minimal active domain, and the 310 helix in the N-terminus, as the secondary active domain. However, for the NCp8 counterpart in HIV-2, the mechanism for binding to viral RNA has not yet been clarified. In this study, we determined NCp8’s three-dimensional structure for the first time and examined the dynamic behavior and chemical shift perturbation as a function of the concentration of viral RNA SL3. Moreover, the specific binding activities of NCp8 and the NCp8-derived peptides with SL3 were examined by a native polyacrylamide gel electrophoresis assay. These results indicate that the RNA recognition mechanism for NCp8 is different from that of NCp7 and that the hydrophobic cleft in the second zinc finger acts as a secondary active domain instead of the 310 helix in NCp7. Furthermore, the flexibility of the linker is limited by the hydrogen bond between the first zinc finger (Asn11) and the linker (Arg27), which makes it possible for the sites around Trp10 in the minimal active domain and the secondary active domain to form the binding surface

Serotyping in heterozygous combinations.

<p>Figure shows representative ion chromatograms of the wild-type (E3/E3) and all heterozygous combinations (E2/E3, E3/E4, E2/E4). Tryptic peptide polymorphisms correspond to each ApoE isoform. As described under “ApoE serotyping” in the <b>Materials and Methods</b>, the correlation between ApoE genotypes and isoforms enables determination of the genotype from the blood ApoE isoform combination.</p

Apolipoprotein E resequencing and its application to serotyping.

<p>(<b>A</b>) ApoE resequencing. Figure shows a representative result of wild-type ApoE amino acid sequence determination (sequence coverage = 93.6%, excluding the 18-residue signal peptide) using Orbitrap LC-MS/MS. Black highlighting denotes the determined sequence. Amino acid residues C112 and R158, which demonstrate polymorphism in ApoE2 (C158) and ApoE4 (R112), are circled. Amino acids are represented by their one-letter codes. (<b>B</b>) Tryptic peptide polymorphisms and ion chromatograms. Mutations in amino acid residues 112 and 158, which were covered by protein resequencing, cause peptide fragment polymorphisms. The R158C mutation (ApoE2) results in the cLAVYQAGAR peptide, where the C112R mutation (ApoE4) yields the LGADMEDVR peptide. Figure shows representative chromatograms for the doubly charged ions extracted from subjects with E2/E3 and E3/E4 heterozygous combinations. The calculated and observed monoisotopic masses for each peptide are indicated. (<b>C</b>) Corresponding MS/MS spectra for each peptide in (<b>B</b>). Polymorphic peptide sequences from subjects with heterozygous combinations were confirmed by MS/MS. The b- and y-ions are labeled. In (<b>B</b>) and (<b>C</b>), lower-case “c” represents alkylated cysteine residues. C. mass = calculated mass; O. mass = observed mass; Da = dalton.</p

Comparison of <i>APOE</i> genotypes with results of APOE protein resequencing and serotyping.

<p>The serotypes agreed with the genotypes for all enrolled subjects.</p><p>n = number of subject; SD = standard deviation; N.D. = not determined.</p

PACT/PRKRA and p53 regulate transcriptional activity of DMRT1

Abstract The transcription factor DMRT1 (doublesex and mab-3 related transcription factor) has two distinct functions, somatic-cell masculinization and germ-cell development in some vertebrate species, including mouse and the African clawed frog Xenopus laevis. However, its transcriptional regulation remains unclear. We tried to identify DMRT1-interacting proteins from X. laevis testes by immunoprecipitation with an anti-DMRT1 antibody and MS/MS analysis, and selected three proteins, including PACT/PRKRA (Interferon-inducible double-stranded RNA dependent protein kinase activator A) derived from testes. Next, we examined the effects of PACT/PRKRA and/or p53 on the transcriptional activity of DMRT1. In transfected 293T cells, PACT/PRKRA and p53 significantly enhanced and repressed DMRT1-driven luciferase activity, respectively. We also observed that the enhanced activity by PACT/PRKRA was strongly attenuated by p53. Moreover, in situ hybridization analysis of Pact/Prkra mRNA in tadpole gonads indicated high expression in female and male germline stem cells. Taken together, these findings suggest that PACT/PRKRA and p53 might positively and negatively regulate the activity of DMRT1, respectively, for germline stem cell fate.</div

Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

Since LC–MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n = 9) or low-risk (n = 9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n = 9) or low-risk (n = 7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n = 9) or low-risk (n = 8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n = 12) or low-risk (n = 12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers

Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples

Since LC–MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n = 9) or low-risk (n = 9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n = 9) or low-risk (n = 7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n = 9) or low-risk (n = 8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n = 12) or low-risk (n = 12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers