木薯果胶甲基酯酶抑制因子MePMEI1的生物信息学分析

为探讨木薯MePMEI1的分子结构特征。通过PCR扩增和测序技术及生物信息学分析工具对木薯MePMEI1基因进行克隆、测序及相关生物信息学分析。结果表明木薯MePMEI1基因编码区全长609 bp,编码202个氨基酸残基;MePMEI1基因编码蛋白分子量21.78 k D,理论等电点(pI)约为5.51;生物信息学预测发现,木薯MePMEI1蛋白是稳定的亲水蛋白;具有跨膜区为分泌蛋白;含有1个PMEI结构域,1个糖基化位点,31个磷酸化位点;二、三级结构以α螺旋和无规则卷曲为主。该蛋白的生物功能可能与细胞被膜、酶和生长因子等相关。木薯MePMEI1基因的生物信息学分析为进一步研究其遗传特性和生理生化机制提供了理论依据。     

木霉菌T23胶毒素合成基因的生物信息学分析与克隆

胶毒素是生防木霉菌重要的次生代谢产物之一。本研究以生防木霉菌T23为供试材料,旨在通过生物信息学技术及表达分析,挖掘木霉菌T23中胶毒素合成候选基因,探索木霉菌胶毒素合成的分子调控机制,可为新型生物农药的开发及应用提供理论依据。研究表明,木霉菌T23中胶毒素合成候选基因簇全长28 kb,簇内包含了8个基因,分别与烟曲霉胶毒素合成基因簇内的gliP、gliC、gliN、gliK、gliI、gliG、gliF、gliM高度同源。提取培养2 d、3 d、4 d、5 d的木霉菌T23菌丝的RNA,通过半定量RT-PCR技术探索各候选基因在木霉菌T23不同生长时期的表达情况,显示各基因在不同生长时期均有表达,属于组成型表达基因。成功克隆得到木霉菌T23中的gliP-T23基因并完成基因结构分析,该基因全长6 339 bp,由4个外显子和3个内含子组成,为后续的基因功能验证提供基础。     

细菌漆酶的生物信息学分析

漆酶是一种含铜的多酚氧化酶。本研究利用生物信息学分析工具对细菌的漆酶蛋白序列的基本性质、保守结构域、系统发育树以及结构等进行了分析。所分析细菌主要分布在变形菌门、放线菌和厚壁菌门。细菌漆酶的物理化学性质相似,但不同细菌来源的漆酶之间序列相似性较低,但其仍然具有容易识别的保守结构域特征。二级结构及三级结构具有明显的相似性。细菌漆酶的生物信息分析为其功能研究及在其他微生物中研究该类酶提供了基础。     

Molecular Characterization and Expression Analysis of ftr01, ftr42, and ftr58 in Zebrafish (Danio rerio)

Tripartite motif(TRIM) proteins were shown to play an important role in innate antiviral immunity. FinTRIM(ftr) is a new subset of TRIM genes that do not possess obvious orthologs in higher vertebrates. However, little is known about its function. In this study, we used bioinformatic analysis to examine the phylogenetic relationships and conserved domains of zebrafish(Danio rerio) ftr01, ftr42, and ftr58, as well as qualitative real-time PCR to examine their expression patterns in zebrafish embryonic fibroblast(ZF4) cells and zebrafish tissues. Sequence analysis showed that the three finTRIMs are highly conserved, and all contain a RING domain, B-box domain, and SPRY-PRY domain. In addition, ftr42 and ftr58 had one coiled-coil domain(CCD), whereas ftr01 had two CCDs. Tissue expression analysis revealed that the m RNA level of ftr01 was the highest in the liver, whereas those of ftr42 and ftr58 were the highest in the gill; the expression of thesefinTRIMs was clearly upregulated not in the eyes, but in the liver, spleen, kidney, gill, and brain of zebrafish following spring viremia of carp virus(SVCV) infection. Similarly, the expression of these three finTRIM genes also increased in ZF4 cells after SVCV infection. Our study revealed that ftr01, ftr42, and ftr58 may play an important role in antiviral immune responses, and these findings validate the need for more in-depth research on the finTRIM family in the future.     

DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics

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Highlights

• •Retention time shift can lead to inversion of elution order of peptides.
• •Global alignment methods are suboptimal for alignment of distant runs.
• •DIAlignR employs hybrid (global + local) RT alignment approach.
• •DIAlignR can align swapped peaks accurately across distant runs.

     

A comparative study of bacterial diversity based on culturable and culture-independent techniques in the rhizosphere of maize (Zea mays L.)

ObjectiveMaize is an important crop for fodder, food and feed industry. The present study explores the plant-microbe interactions as alternative eco-friendly sustainable strategies to enhance the crop yield.MethodologyBacterial diversity was studied in the rhizosphere of maize by culture-dependent and culture-independent techniques by soil sampling, extraction of DNA, amplification of gene of interest, cloning of desired fragment and library construction.ResultsCulturable bacteria were identified as Achromobacter, Agrobacterium, Azospirillum, Bacillus, Brevibacillus, Bosea, Enterobacter, Microbacterium, Pseudomonas, Rhodococcus, Stenotrophomonas and Xanthomonas genera. For culture-independent approach, clone library of 16S ribosomal RNA gene was assembled and 100 randomly selected clones were sequenced. Majority of the sequences were related to Firmicutes (17%), Acidobacteria (16%), Actinobacteria (17%), Alpha-Proteobacteria (7%), Delta-proteobacteria (4.2%) and Gemmatimonadetes (4.2%) However, some of the sequences (30%) were novel that showed no homologies to phyla of cultured bacteria in the database. Diversity of diazotrophic bacteria in the rhizosphere investigated by analysis of PCR-amplified nifH gene sequence that revealed abundance of sequences belonging to genera Azoarcus (25%), Aeromonas (10%), Pseudomonas (10%). The diazotrophic genera Azotobacter, Agrobacterium and Zoogloea related nifH sequences were also detected but no sequence related to Azospirillum was found showing biasness of the growth medium rather than relative abundance of diazotrophs in the rhizosphere.ConclusionThe study provides a foundation for future research on focussed isolation of the Azoarcus and other diazotrophs found in higher abundance in the rhizosphere.     

Will systems biology offer new holistic paradigms to life sciences?

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms.     

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications

Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOF mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process.     

High Performance Proteomics: 7th HUPO Brain Proteome Project Workshop March 7-9, 2007 Wellcome Trust Conference Centre, Hinxton, UK

The Wellcome Trust Conference Centre at Hinxton, UK, was the meeting place of the 7th HUPO Brain Proteome Project Workshop entitled "High Performance Proteomics". It started on Wednesday, March 7, 2007 with a steering committee meeting followed by a two days series of talks dealing with the standardization and handling of tissues, body fluids as well as of proteomics data. The presentation and accompanying vivid discussions created a picture of actual strategies and standards in recent proteomics.     

Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data

This study assesses the ability of a novel family of machine learning algorithms to identify changes in relative protein expression levels, measured using 2-D DIGE data, which support accurate class prediction. The analysis was done using a training set of 36 total cellular lysates comprised of six normal and three cancer biological replicates (the remaining are technical replicates) and a validation set of four normal and two cancer samples. Protein samples were separated by 2-D DIGE and expression was quantified using DeCyder-2D Differential Analysis Software. The relative expression reversal (RER) classifier correctly classified 9/9 training biological samples (p<0.022) as estimated using a modified version of leave one out cross validation and 6/6 validation samples. The classification rule involved comparison of expression levels for a single pair of protein spots, tropomyosin isoforms and alpha-enolase, both of which have prior association as potential biomarkers in cancer. The data was also analyzed using algorithms similar to those found in the extended data analysis package of DeCyder software. We propose that by accounting for sources of within- and between-gel variation, RER classifiers applied to 2-D DIGE data provide a useful approach for identifying biomarkers that discriminate among protein samples of interest.