土壤宏蛋白质组学在土壤污染评价中的应用

土壤微生物指标是评价土壤污染程度的重要生物学指标之一.近年来,随着分子生物学的发展,应用宏基因组学、宏转录组学和宏蛋白质组学技术考察土壤微生物的生态功能成为土壤功能的研究热点.相对于宏基因组学和宏转录组学,土壤宏蛋白质组学是以土壤微生物基因的功能组分——蛋白质为直接研究对象,考察不同时空点提取出来的土壤蛋白质的变化规律,更有助于揭示土壤微生物的生态功能及其在污染物迁移转化过程中的作用,在评价土壤污染方面也更具潜力.目前,土壤宏蛋白质组学正处于起步阶段,而土壤蛋白质的提取方法是制约其发展的主要因素之一,因此本文综述了蛋白质作为土壤污染评价指标的优势,重点比较了不同土壤蛋白质提取方法的优劣,结合案例分析了蛋白质作为土壤污染评价指标的可行性及存在的问题,并对土壤宏蛋白质组学的发展进行展望.     

宏蛋白质组学:研究微生物群落的一种新策略

宏蛋白质组学是一种运用蛋白质组技术对特定微生物群落所产生的全部蛋白质进行大规模研究与分析的新技术。简要概述宏蛋白组学的产生、研究策略及其应用情况,并对其应用前景进行展望。     

宏蛋白质组学技术在废水生物处理工艺研究领域中的应用

随着后基因组时代的到来,宏蛋白质组学逐渐兴起并在生命科学基础领域和临床医药领域成功运用,宏蛋白质组学技术现已成为各研究领域炙手可热的方法之一.宏蛋白质组学技术在废水生物处理研究领域中的应用刚起步,但已展示其强大功能.本文主要综述近年来国内外宏蛋白质组学在废水生物处理研究领域的研究进展,回顾及总结了宏蛋白质组学的研究策略及应用,如鉴定功能性蛋白质/酶、揭示污染物的微生物降解途径、推断废水生物处理系统的关键代谢途径、及探讨不同污泥微生物群落微生态变化等.
     

宏蛋白质组学研究策略及应用

宏蛋白质组学是近年来出现的一种对天然环境微生态进行大规模蛋白质组学研究工作,其定义为对给定位点的环境微生物群落的所有蛋白质组成进行的即时的大规模的分析。以下将通过分析已有的宏蛋白质组学研究,并结合本研究组的研究经验,对本领域的研究策略、进展情况等加以综述。     

宏蛋白质组学——研究微生物群落基因表达的新技术

宏蛋白质组学是应用蛋白质组学技术对微生物群落进行研究的一项新技术,其定义为在特定的时间对微生物群落的所有蛋白质组成进行大规模鉴定。通过对宏蛋白质组学的研究策略、进展情况的综述、介绍,展望了宏蛋白组学在研究微生物群落基因表达中的应用前景。     

微生物蛋白质组学的定量分析

越来越多的微生物基因组序列数据为系统地研究基因的调节和功能创造了有利条件.由于蛋白质是具有生物功能的分子,蛋白质组学在微生物基因组的功能研究中异军突起、蓬勃发展.微生物蛋白质组学的基本原则是,用比较研究来阐明和理解不同微生物之间或不同生长条件下基因的表达水平.显而易见,定量分析技术是比较蛋白质组学中急需发展的核心技术.对蛋白质组学定量分析技术在微生物蛋白质组研究中的进展进行了综述.     

利用EST序列构建Mascot本地数据库

对蛋白质质谱数据进行数据库比对和鉴定是蛋白质组学研究技术中的一个重要步骤。由于公共数据库蛋白质数据信息不全,有些蛋白质质谱数据无法得到有效的鉴定。而利用相关物种的EST序列构建专门的质谱数据库则可以增加鉴定未知蛋白的几率。本文介绍了利用EST序列构建Mascot本地数据库的具体方法和步骤,扩展了Mascot检索引擎对蛋白质质谱数据的鉴定范围,从数据库层面提高了对未知蛋白的鉴别几率,为蛋白质组学研究提供了一种较为实用的生物信息学分析技术。     

宏组学方法在污水处理系统中的应用进展

污水生物处理由微生物生理过程驱动,宏组学方法能够获得不同水平的分子信息,为认识污水处理系统中的微生物提供了新途径。本文对宏基因组学、宏转录组学、宏蛋白质组学与代谢组学等宏组学方法的发展进行综述,着重介绍各组学及整合宏组学在污水处理系统中的研究现状,并指出其应用前景。     

利用语义网技术实现的分布式异构食品微生物数据整合

随着高通量测序技术的迅速发展和食品微生物研究的逐步深入,产生了大量的数据和知识,且以不同的数据格式分布在各种数据库中。为了更好地支持食品微生物的相关研究,从各种分布式、异构的数据和知识中,进行数据提取与转换,并形成一个整合的数据平台显得尤为重要。FoodMicrobes数据库利用语义网技术,建立了一个食品微生物的整合型数据平台。该平台从各种开放的公共数据库,提取了与食品微生物相关的基因、基因组、基因功能、蛋白质序列与结构、代谢途径、文献、专利等信息,利用RDF的方法,对数据进行转换,并建立了数据之间的关联,实现了数据整合,是目前在食品微生物领域以语义网方式建立的第一个数据库。在该平台中,实现了将食品微生物的物种、菌株层面的宏观信息与基因组、蛋白质、代谢与功能等微观层面信息的贯通,并通过友好的数据检索界面,为用户进行食品微生物研究提供了重要的工具。     

HBV相关肝癌组织中微生物宏蛋白质组特征分析

越来越多的证据表明微生物菌群和肝脏疾病有着密切联系,但是HBV相关肝细胞癌(hepatitis B virus(HBV)-related hepatocellular carcinoma,HCC)人群肝脏组织内的微生物菌群种类和数量仍不清楚.本研究对来自165个HCC人群的肝癌组织和对应癌旁组织的质谱数据进行宏蛋白质组学层面的鉴定.结果显示,在肝癌组织中,绿弯菌门(Chloroflexi)、芽单胞菌门(Gemmatimonadetes)、黄单胞菌目(Xanthomonadales)、军团菌目(Legionellales)、颤藻目(Oscillatoriales)等微生物菌群数量出现显著上调.通过将鉴定的微生物蛋白质比对到COG(Clusters of Orthologous Groups)数据库来进行注释,本研究还发现了许多在肝癌组织中高表达的微生物功能分类.对比健康人群的肝脏组织的宏蛋白质组鉴定结果,本研究发现在HCC人群的肝脏组织中,变形菌门(Proteobacteria)的含量降低,厚壁菌门(Firmicutes)的含量升高.这项研究可以对肝脏微生物菌群的失调与HCC发生之间的研究提供更多启发.     

基于质谱的BLAST方法在金鱼胚胎蛋白质鉴定中的应用

未知基因组及蛋白质序列数据库有限的物种的蛋白质组学分析是当前一些非模式生物物种蛋白质组学研究领域的瓶颈之一.基于同源性搜索的BLAST方法（MS BLAST）,是近年新发展起来的一种用于未知基因组的蛋白质鉴定的搜索工具,已成功应用于许多未知基因组物种的蛋白质鉴定.SPITC化学辅助方法是本实验室建立的一种改进的de novo质谱测序方法.采用MS BLAST方法对经Mascot软件数据库搜索未能鉴定到的19个金鱼胚胎蛋白质进行鉴定,其中12个蛋白质是直接测序后进行MS BLAST搜索得到的结果,另外7个蛋白质是联合MS BLAST和SPITC衍生方法得到的鉴定结果.实验结果证明,采用MS BLAST方法进行蛋白质的跨物种鉴定具有可行性和可靠性,给蛋白质的跨物种鉴定提供了一条新的途径.     

Proteomic profiling and protein identification by MALDI-TOF mass spectrometry in unsequenced parasitic nematodes

Lack of genomic sequence data and the relatively high cost of tandem mass spectrometry have hampered proteomic investigations into helminths, such as resolving the mechanism underpinning globally reported anthelmintic resistance. Whilst detailed mechanisms of resistance remain unknown for the majority of drug-parasite interactions, gene mutations and changes in gene and protein expression are proposed key aspects of resistance. Comparative proteomic analysis of drug-resistant and -susceptible nematodes may reveal protein profiles reflecting drug-related phenotypes. Using the gastro-intestinal nematode, Haemonchus contortus as case study, we report the application of freely available expressed sequence tag (EST) datasets to support proteomic studies in unsequenced nematodes. EST datasets were translated to theoretical protein sequences to generate a searchable database. In conjunction with matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF-MS), Peptide Mass Fingerprint (PMF) searching of databases enabled a cost-effective protein identification strategy. The effectiveness of this approach was verified in comparison with MS/MS de novo sequencing with searching of the same EST protein database and subsequent searches of the NCBInr protein database using the Basic Local Alignment Search Tool (BLAST) to provide protein annotation. Of 100 proteins from 2-DE gel spots, 62 were identified by MALDI-TOF-MS and PMF searching of the EST database. Twenty randomly selected spots were analysed by electrospray MS/MS and MASCOT Ion Searches of the same database. The resulting sequences were subjected to BLAST searches of the NCBI protein database to provide annotation of the proteins and confirm concordance in protein identity from both approaches. Further confirmation of protein identifications from the MS/MS data were obtained by de novo sequencing of peptides, followed by FASTS algorithm searches of the EST putative protein database. This study demonstrates the cost-effective use of available EST databases and inexpensive, accessible MALDI-TOF MS in conjunction with PMF for reliable protein identification in unsequenced organisms.     

蛋白质组研究中离子阱串联质谱数据搜库结果解释方法

基于离子阱串联质谱仪的鸟枪法是一种高通量的蛋白质鉴定方法。得到的数据一般使用软件SEQUEST搜索蛋白质序列数据库,得到肽段鉴定列表以及相应的打分。为了得到蛋白质鉴定列表,还需要进行肽段鉴定结果的过滤和假阳性率的计算,然后根据肽段鉴定结果组装蛋白质列表。这两个问题目前还没有很好地解决。对已有的方法进行总结和比较,可以给搜库结果解释方法的选择提供参考,对数据质量控制方法的改进也有所帮助。     

Metaproteomics: studying functional gene expression in microbial ecosystems

The recent availability of extensive metagenomic sequences from various environmental microbial communities has extended the postgenomic era to the field of environmental microbiology. Although still restricted to a small number of studies, metaproteomic investigations have revealed interesting aspects of functional gene expression within microbial habitats that contain limited microbial diversity. These studies highlight the potential of proteomics for the study of microbial consortia. However, the application of proteomic investigations to complex microbial assemblages such as seawater and soil still presents considerable challenges. Nonetheless, metaproteomics will enhance the understanding of the microbial world and link microbial community composition to function.     

Evaluating the Impact of Different Sequence Databases on Metaproteome Analysis: Insights from a Lab-Assembled Microbial Mixture

Metaproteomics enables the investigation of the protein repertoire expressed by complex microbial communities. However, to unleash its full potential, refinements in bioinformatic approaches for data analysis are still needed. In this context, sequence databases selection represents a major challenge.This work assessed the impact of different databases in metaproteomic investigations by using a mock microbial mixture including nine diverse bacterial and eukaryotic species, which was subjected to shotgun metaproteomic analysis. Then, both the microbial mixture and the single microorganisms were subjected to next generation sequencing to obtain experimental metagenomic- and genomic-derived databases, which were used along with public databases (namely, NCBI, UniProtKB/SwissProt and UniProtKB/TrEMBL, parsed at different taxonomic levels) to analyze the metaproteomic dataset. First, a quantitative comparison in terms of number and overlap of peptide identifications was carried out among all databases. As a result, only 35% of peptides were common to all database classes; moreover, genus/species-specific databases provided up to 17% more identifications compared to databases with generic taxonomy, while the metagenomic database enabled a slight increment in respect to public databases. Then, database behavior in terms of false discovery rate and peptide degeneracy was critically evaluated. Public databases with generic taxonomy exhibited a markedly different trend compared to the counterparts. Finally, the reliability of taxonomic attribution according to the lowest common ancestor approach (using MEGAN and Unipept software) was assessed. The level of misassignments varied among the different databases, and specific thresholds based on the number of taxon-specific peptides were established to minimize false positives. This study confirms that database selection has a significant impact in metaproteomics, and provides critical indications for improving depth and reliability of metaproteomic results. Specifically, the use of iterative searches and of suitable filters for taxonomic assignments is proposed with the aim of increasing coverage and trustworthiness of metaproteomic data.     

Endospores of halophilic bacteria of the family Bacillaceae isolated from non-saline Japanese soil may be transported by Kosa event (Asian dust storm)

Background

Natural microbial communities are extremely complex and dynamic systems in terms of their population structure and functions. However, little is known about the in situ functions of the microbial communities.

Results

This study describes the application of proteomic approaches (metaproteomics) to observe expressed protein profiles of natural microbial communities (metaproteomes). The technique was validated using a constructed community and subsequently used to analyze Chesapeake Bay microbial community (0.2 to 3.0 μm) metaproteomes. Chesapeake Bay metaproteomes contained proteins from pI 4–8 with apparent molecular masses between 10–80 kDa. Replicated middle Bay metaproteomes shared ~92% of all detected spots, but only shared 30% and 70% of common protein spots with upper and lower Bay metaproteomes. MALDI-TOF analysis of highly expressed proteins produced no significant matches to known proteins. Three Chesapeake Bay proteins were tentatively identified by LC-MS/MS sequencing coupled with MS-BLAST searching. The proteins identified were of marine microbial origin and correlated with abundant Chesapeake Bay microbial lineages, Bacteroides and α-proteobacteria.

Conclusion

Our results represent the first metaproteomic study of aquatic microbial assemblages and demonstrate the potential of metaproteomic approaches to link metagenomic data, taxonomic diversity, functional diversity and biological processes in natural environments.     

Flying blind,or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification

Mass spectrometry‐based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph‐based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.     

Comparative metaproteomics and diversity analysis of human intestinal microbiota testifies for its temporal stability and expression of core functions

The human intestinal tract is colonized by microbial communities that show a subject-specific composition and a high-level temporal stability in healthy adults. To determine whether this is reflected at the functional level, we compared the faecal metaproteomes of healthy subjects over time using a novel high-throughput approach based on denaturing polyacrylamide gel electrophoresis and liquid chromatography-tandem mass spectrometry. The developed robust metaproteomics workflow and identification pipeline was used to study the composition and temporal stability of the intestinal metaproteome using faecal samples collected from 3 healthy subjects over a period of six to twelve months. The same samples were also subjected to DNA extraction and analysed for their microbial composition and diversity using the Human Intestinal Tract Chip, a validated phylogenetic microarray. Using metagenome and single genome sequence data out of the thousands of mass spectra generated per sample, approximately 1,000 peptides per sample were identified. Our results indicate that the faecal metaproteome is subject-specific and stable during a one-year period. A stable common core of approximately 1,000 proteins could be recognized in each of the subjects, indicating a common functional core that is mainly involved in carbohydrate transport and degradation. Additionally, a variety of surface proteins could be identified, including potential microbes-host interacting components such as flagellins and pili. Altogether, we observed a highly comparable subject-specific clustering of the metaproteomic and phylogenetic profiles, indicating that the distinct microbial activity is reflected by the individual composition.