Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [¹H,¹H]-NOESY spectra during de novoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NMR.     

Fully automated sequence-specific resonance assignments of hetero- nuclear protein spectra

Full automation of the analysis of spectra is a prerequisite for high-throughput NMR studies in structural or functional genomics. Sequence-specific assignments often form the major bottleneck. Here, we present a procedure that yields nearly complete backbone and side chain resonance assignments starting from a set of heteronuclear three-dimensional spectra. Neither manual intervention, e.g., to correct lists obtained from peak picking before feeding these to an assignment program, nor protein-specific information, e.g., structures of homologous proteins, were required. By combining two earlier published procedures, AUTOPSY [Koradi et al. (1998) J. Magn. Reson., 135, 288–297] and GARANT [Bartels et al. (1996) J. Biomol. NMR, 7, 207–213], with a new program, PICS, all necessary steps from spectra analyses to sequence-specific assignments were performed fully automatically. Characteristic features of the present approach are a flexible design allowing as input almost any combination of NMR spectra, applicability to side chains, robustness with respect to parameter choices (such as noise levels) and reproducibility. In this study, automated resonance assignments were obtained for the 14 kD blue copper protein azurin from P. aeruginosa using five spectra: HNCACB, HNHA, HCCH-TOCSY, ¹⁵N-NOESY-HSQC and ¹³C-NOESY-HSQC. Peaks from these three-dimensional spectra were filtered and calibrated with the help of two two-dimensional spectra: ¹⁵N-HSQC and ¹³C-HSQC. The rate of incorrect assignments is less than 1.5% for backbone nuclei and about 3.5% when side chain protons are also considered.     

Automated Protein NMR Structure Determination Using Wavelet De-noised NOESY Spectra

A major time-consuming step of protein NMR structure determination is the generation of reliable NOESY cross peak lists which usually requires a significant amount of manual interaction. Here we present a new algorithm for automated peak picking involving wavelet de-noised NOESY spectra in a process where the identification of peaks is coupled to automated structure determination. The core of this method is the generation of incremental peak lists by applying different wavelet de-noising procedures which yield peak lists of a different noise content. In combination with additional filters which probe the consistency of the peak lists, good convergence of the NOESY-based automated structure determination could be achieved. These algorithms were implemented in the context of the ARIA software for automated NOE assignment and structure determination and were validated for a polysulfide-sulfur transferase protein of known structure. The procedures presented here should be commonly applicable for efficient protein NMR structure determination and automated NMR peak picking. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

红松结实量与松果可利用量对松鼠和花鼠贮食行为的影响

植物通过每隔几年产生大量种子的丰年策略提高贮食动物传播种子效率,但人为采摘活动降低了种子的可利用量,从而影响贮食动物行为及种群动态。为研究红松球果采摘如何通过降低松果可利用量而影响贮食动物行为,我们基于黑龙江凉水自然保护区2003-2012年红松结实量和采摘量的变化,比较分析了结实大小年间松鼠贮点大小、贮点深度、贮食密度和贮藏量、松鼠花鼠种群以及2010年和2011年花鼠洞穴贮藏量的差异。结果显示：结实大年松鼠的平均贮点大小显著高于小年,大贮点比例增加,贮食密度和贮藏量也明显高于结实小年,但随着结实量的增大,球果采摘量增加,使松果可利用量减少,由此结实大年2011年松鼠贮食密度并未随结实量增加而增加,反而低于2003年和2008年,松鼠遇见率也没有在该结实大年有所增长。而花鼠种群和洞穴松籽贮藏量在结实大年和小年间没有显著差异。研究表明红松球果采摘对松果可利用量和松鼠贮食行为有较大影响,应合理确定大年的采摘量以保证贮食动物的食物丰度,维系红松生态系统健康。     

The development of animal personality: relevance,concepts and perspectives

Recent studies of animal personality have focused on its proximate causation and its ecological and evolutionary significance, but have mostly ignored questions about its development, although an understanding of the latter is highly relevant to these other questions. One possible reason for this neglect is confusion about many of the concepts and terms that are necessary to study the development of animal personality. Here, we provide a framework for studying personality development that focuses on the properties of animal personality, and considers how and why these properties may change over time. We specifically focus on three dimensions of personality: (1) contextual generality at a given age or time, (2) temporal consistency in behavioural traits and in relationships between traits, and (3) the effects of genes and experience on the development of personality at a given age or life stage. We advocate using a new approach, contextual reaction norms, to study the contextual generality of personality traits at the level of groups, individuals and genotypes, show how concepts and terms borrowed from the literature on personality development in humans can be used to study temporal changes in personality at the level of groups and individuals, and demonstrate how classical developmental reaction norms can provide insights into the ways that genes and experiential factors interact across ontogeny to affect the expression of personality traits. In addition, we discuss how correlations between the effects of genes and experience on personality development can arise as a function of individuals' control over their own environment, via niche‐picking or niche‐construction. Using this framework, we discuss several widely held assumptions about animal personality development that still await validation, identify neglected methodological issues, and describe a number of promising new avenues for future research.     

幼龄期苦丁茶茶叶采摘初探

根据幼龄苦丁茶的生长生物学特性 ,结合茶树茶叶采摘原理 ,采取树龄—采摘面—采摘方法 3因素、 3水平的正交实验 ,探讨获取早期茶叶产量及促进形成良好树型树冠的途径。结果表明 ,实验各组合以三年生—全冠—留二叶的处理所获茶叶产量最高 ,植株分枝最多 ,冠高比较同龄对照植株大。     

肚倍在各生长期的主要成分含量变化分析

肚倍是一种商品化的五倍子,富含鞣质、没食子酸等重要成分,具有重要的药用价值及工业用途。研究不同生长发育时期五倍子主要成分的含量变化,探索变化规律对肚倍更深入的研究具有长远意义。本文以湖北省竹山县溢水镇东川苗圃、文峰乡肖家垭、德胜镇王家湾生产的肚倍为样品,每隔10天采摘一次,称重并测定其主要成分的含量,直至虫瘿成熟爆裂。经测定,3个产地的肚倍含有丰富的鞣质(约70.0%)、游离没食子酸(约5.0%)、1,2,3,4,6-五-O-没食子酰-β-葡萄糖(β-PGG,约6.0%)、可溶性总糖(约8.2%)、氨基酸(约7.5%)等,在不同的生长期,这些主要成分的含量无大的差异,而且主要的几种重金属元素铁(Fe)、锌(Zn)、铜(Cu)、钡(Ba)、铅(Pb)和砷(As)在生长过程中也不会累积,不影响采摘时间。综合考虑肚倍的生长情况和经济价值,肚倍适宜在其个头最大,即体积基本不再增长且未爆裂、无霉烂时采摘。     

Automated evaluation of chemical shift perturbation spectra: New approaches to quantitative analysis of receptor-ligand interaction NMR spectra

This paper presents new methods designed for quantitative analysis of chemical shift perturbation NMR spectra. The methods automatically trace the displacements of cross peaks between a perturbed test spectrum and the reference spectrum (or among a series of titration spectra), and measure the changes of chemical shifts, heights, and widths of the altered peaks. The methods are primary aimed at the (1)H-(15)N HSQC spectra of relatively small proteins (<15 kDa) assuming fast exchange between free and ligand-bound states on the chemical shift time scale, or for comparing spectra of free and fully bound states in the slow exchange situation. Using the (1)H-(15)N HSQC spectra from a titration experiment of the 74-residue Pex13p SH3 domain with a Pex14p peptide ligand (14 residues, K (d)= approximately 40 microM), we demonstrate the scope and limits of our automatic peak tracing (APET) algorithm for efficient scoring of high-throughput SAR by NMR type HSQC spectra, and progressive peak tracing (PROPET) algorithm for detailed analysis of ligand titration spectra. Simulated spectra with low signal-to-noise ratios (S/N ranged from 20 to 1) were used to demonstrate the reliability and reproducibility of the results when dealing with poor quality spectra. These algorithms have been implemented in a new software module, FELIX-Autoscreen, for streamlined processing, analysis and visualization of SAR by NMR and other high-throughput receptor/ligand interaction experiments.     

Hand preference and tool use in wild chimpanzees

The hand preference of chimpanzees in their natural habitat was studied at Bossou, Republic of Guinea, West Africa. The quantitative difference in left/right hand use was small in food picking and carrying. In contrast, the chimpanzees employed either the right or left hand in nutcracking behavior using a pair of stones. All adults and many adolescents and juveniles utilized one hand exclusively for holding a hammer stone. Left hand preference was more prevalent among adults. However, when adolescents and juveniles were included, there was no significant bias in the ratio of left/right handers. Nut-cracking behavior requires long-term learning of the fine manipulation of stones and nuts by both hands. Each hand has a separate role, and the hands work together in nut cracking. The differential and complementary use of both hands may be a prime factor promoting exclusive hand preference in chimpanzees comparable to that of humans.     

A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry

Background

Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field. However, recent most advanced types of LC-MS generate huge amounts of analytical data with high scan speed, high accuracy and resolution, which is often impossible to interpret manually. Moreover, there are still issues to be improved for recent label-free methods, such as how to reduce false positive/negatives of the candidate peaks, how to expand scalability and how to enhance and automate data processing. AB3D (A simple label-free quantitation algorithm for Biomarker Discovery in Diagnostics and Drug discovery using LC-MS) has addressed these issues and has the capability to perform label-free quantitation using MS1 for proteomics study.

Results

We developed an algorithm called AB3D, a label free peak detection and quantitative algorithm using MS1 spectral data. To test our algorithm, practical applications of AB3D for LC-MS data sets were evaluated using 3 datasets. Comparisons were then carried out between widely used software tools such as MZmine 2, MSight, SuperHirn, OpenMS and our algorithm AB3D, using the same LC-MS datasets. All quantitative results were confirmed manually, and we found that AB3D could properly identify and quantify known peptides with fewer false positives and false negatives compared to four other existing software tools using either the standard peptide mixture or the real complex biological samples of Bartonella quintana (strain JK31). Moreover, AB3D showed the best reliability by comparing the variability between two technical replicates using a complex peptide mixture of HeLa and BSA samples. For performance, the AB3D algorithm is about 1.2 - 15 times faster than the four other existing software tools.

Conclusions

AB3D is a simple and fast algorithm for label-free quantitation using MS1 mass spectrometry data for large scale LC-MS data analysis with higher true positive and reasonable false positive rates. Furthermore, AB3D demonstrated the best reproducibility and is about 1.2- 15 times faster than those of existing 4 software tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0376-0) contains supplementary material, which is available to authorized users.