Purification and functional characterisation of rhiminopeptidase A, a novel aminopeptidase from the venom of Bitis gabonica rhinoceros

This study describes the discovery and characterisation of a novel aminopeptidase A from the venom of B. g. rhinoceros and highlights its potential biological importance. Similar to mammalian aminopeptidases, rhiminopeptidase A might be capable of playing roles in altering the blood pressure and brain function of victims. Furthermore, it could have additional effects on the biological functions of other host proteins by cleaving their N-terminal amino acids. This study points towards the importance of complete analysis of individual components of snake venom in order to develop effective therapies for snake bites

Epstein-Barr Virus Infection and Sporadic Breast Cancer Risk: A Meta-Analysis

BACKGROUND: A large number of epidemiological studies have evaluated the association between Epstein-Barr virus infection and breast carcinoma risk but results have been inconsistent. METHODOLOGY: Research using the polymerase chain reaction technique for detecting the Epstein-Barr virus was selected; 24 studies and 1535 cases were reviewed. Information on the study populations, sample types, publication calendar period and histological types of breast carcinoma were collected. An unconditional logistic regression model was used to analyze potential parameters related to the Epstein-Barr virus prevalence. A Kappa test was used to evaluate the consistency in detecting different Epstein-Barr virus DNA regions. Nine studies that included control groups and 1045 breast cancer cases were adopted in this meta-analysis. CONCLUSIONS: We found that 29.32% of the patients with breast carcinoma were infected with the Epstein-Barr virus. The prevalence of Epstein-Barr was highest in Asia (35.25%) and lowest in the USA (18.27%). Statistical analysis revealed a trend that showed lobular breast carcinoma might have the strongest association with Epstein-Barr virus infection. This meta-analysis showed a significant increase in breast malignancy risk in patients testing positive for the Epstein-Barr virus (OR = 6.29, 95% CI = 2.13-18.59). This result suggests that an Epstein-Barr virus infection is statistically associated with increased breast carcinoma risk

Microspatial variability in community structure and photophysiology of calcified macroalgal microbiomes revealed by coupling of hyperspectral and high-resolution fluorescence imaging

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The attached file is the published version of the article

Techniques for accurate protein identification in shotgun proteomic studies of human, mouse, bovine, and chicken lenses

Analysis of shotgun proteomics datasets requires techniques to distinguish correct peptide identifications from incorrect identifications, such as linear discriminant functions and target/decoy protein databases. We report an efficient, flexible proteomic analysis workflow pipeline that implements these techniques to control both peptide and protein false discovery rates. We demonstrate its performance by analyzing two-dimensional liquid chromatography separations of lens proteins from human, mouse, bovine, and chicken lenses. We compared the use of International Protein Index databases to UniProt databases and no-enzyme SEQUEST searches to tryptic searches. Sequences present in the International Protein Index databases allowed detection of several novel crystallins. An alternate start codon isoform of βA4 was found in human lens. The minor crystallin γN was detected for the first time in bovine and chicken lenses. Chicken γS was identified and is the first member of the γ-crystallin family observed in avian lenses

Population dynamics of a pathogen: the conundrum of vivax malaria

Building a mathematical model of population dynamics of pathogens within their host involves considerations of factors similar to those in ecology, as pathogens can prey on cells in the host. But within the multicellular host, attacked cell types are integrated with other cellular systems, which in turn intervene in the infection. For example, immune responses attempt to sense and then eliminate or contain pathogens, and homeostatic mechanisms try to compensate for cell loss. This review focuses on modeling applied to malarias, diseases caused by single-cell eukaryote parasites that infect red blood cells, with special concern given to vivax malaria, a disease often thought to be benign (if sometimes incapacitating) because the parasite only attacks a small proportion of red blood cells, the very youngest ones. However, I will use mathematical modeling to argue that depletion of this pool of red blood cells can be disastrous to the host if growth of the parasite is not vigorously check by host immune responses. Also, modeling can elucidate aspects of new field observations that indicate that vivax malaria is more dangerous than previously thought

AYUMS: an algorithm for completely automatic quantitation based on LC-MS/MS proteome data and its application to the analysis of signal transduction

BACKGROUND: Comprehensive description of the behavior of cellular components in a quantitative manner is essential for systematic understanding of biological events. Recent LC-MS/MS (tandem mass spectrometry coupled with liquid chromatography) technology, in combination with the SILAC (Stable Isotope Labeling by Amino acids in Cell culture) method, has enabled us to make relative quantitation at the proteome level. The recent report by Blagoev et al. (Nat. Biotechnol., 22, 1139–1145, 2004) indicated that this method was also applicable for the time-course analysis of cellular signaling events. Relative quatitation can easily be performed by calculating the ratio of peak intensities corresponding to differentially labeled peptides in the MS spectrum. As currently available software requires some GUI applications and is time-consuming, it is not suitable for processing large-scale proteome data. RESULTS: To resolve this difficulty, we developed an algorithm that automatically detects the peaks in each spectrum. Using this algorithm, we developed a software tool named AYUMS that automatically identifies the peaks corresponding to differentially labeled peptides, compares these peaks, calculates each of the peak ratios in mixed samples, and integrates them into one data sheet. This software has enabled us to dramatically save time for generation of the final report. CONCLUSION: AYUMS is a useful software tool for comprehensive quantitation of the proteome data generated by LC-MS/MS analysis. This software was developed using Java and runs on Linux, Windows, and Mac OS X. Please contact [email protected] if you are interested in the application. The project web page is

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

<p>Abstract</p> <p>Background</p> <p>Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments.</p> <p>Results</p> <p>In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of <it>Mycobacterium tuberculosis</it>, <it>Helicobacter pylori</it>, <it>Salmonella typhimurium </it>and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML.</p> <p>Conclusion</p> <p>The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk.</p

Application of the PM6 method to modeling the solid state

The applicability of the recently developed PM6 method for modeling various properties of a wide range of organic and inorganic crystalline solids has been investigated. Although the geometries of most systems examined were reproduced with good accuracy, severe errors were found in the predicted structures of a small number of solids. The origin of these errors was investigated, and a strategy for improving the method proposed

Azimuthal anisotropy and correlations at large transverse momenta in p+pp+p and Au+Au collisions at sNN\sqrt{s_{_{NN}}}= 200 GeV

Results on high transverse momentum charged particle emission with respect to the reaction plane are presented for Au+Au collisions at $\sqrt{s_{_{NN}}}$= 200 GeV. Two- and four-particle correlations results are presented as well as a comparison of azimuthal correlations in Au+Au collisions to those in $p+p$ at the same energy. Elliptic anisotropy, $v_2$, is found to reach its maximum at $p_t \sim 3$ GeV/c, then decrease slowly and remain significant up to $p_t\approx 7$ -- 10 GeV/c. Stronger suppression is found in the back-to-back high-$p_t$ particle correlations for particles emitted out-of-plane compared to those emitted in-plane. The centrality dependence of $v_2$ at intermediate $p_t$ is compared to simple models based on jet quenching.Comment: 4 figures. Published version as PRL 93, 252301 (2004