Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

Separation of proteins by two-dimensional gel electrophoresis (2-DE) coupled with identification of proteins through peptide mass fingerprinting (PMF) by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is the widely used technique for proteomic analysis. This approach relies, however, on the presence of the proteins studied in public-accessible protein databases or the availability of annotated genome sequences of an organism. In this work, we investigated the reliability of using raw genome sequences for identifying proteins by PMF without the need of additional information such as amino acid sequences. The method is demonstrated for proteomic analysis of Klebsiella pneumoniae grown anaerobically on glycerol. For 197 spots excised from 2-DE gels and submitted for mass spectrometric analysis 164 spots were clearly identified as 122 individual proteins. 95% of the 164 spots can be successfully identified merely by using peptide mass fingerprints and a strain-specific protein database (ProtKpn) constructed from the raw genome sequences of K. pneumoniae. Cross-species protein searching in the public databases mainly resulted in the identification of 57% of the 66 high expressed protein spots in comparison to 97% by using the ProtKpn database. 10 dha regulon related proteins that are essential for the initial enzymatic steps of anaerobic glycerol metabolism were successfully identified using the ProtKpn database, whereas none of them could be identified by cross-species searching. In conclusion, the use of strain-specific protein database constructed from raw genome sequences makes it possible to reliably identify most of the proteins from 2-DE analysis simply through peptide mass fingerprinting.     

Quantitative trait loci for steady-state platelet count in mice

Platelet count in humans is a strongly genetically regulated trait, with approximately 85% of the interindividual variance in platelet numbers attributable to genetic factors. Inbred mouse strains also have strain-specific platelet count ranges. As part of a project to identify novel factors that regulate platelet count, we identified two inbred mouse strains, CBA/CaH and QSi5, with substantial differences in platelet count (mean values of 581 vs. 1062 × 10⁹/L). An F₂ intercross resource of 1126 animals was bred from these two parental strains for a genomewide scan for quantitative trait loci (QTL) for platelet count. QTL were identified on MMU1 (LOD 6.8, p < 0.0005) and MMU11 (LOD 11.2, p < 0.0005) by selectively genotyping animals from the extremes of the F₂ platelet count distribution. Three other QTL of suggestive statistical significance were also detected on MMU7, 13, and 17. It is noteworthy that no QTL were detected in the vicinity of the genes encoding thrombopoietin (Thpo), and its receptor (c-Mpl), both known to influence platelet production. Comparison of gene expression levels between the parental mouse strains by microarrays also showed little difference in the mRNA levels of these known candidate genes. These results represent the first published use of a genetic linkage-based approach in a mouse model toward the identification of genetic factors that regulate platelet count.     

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F₂ cross between CSS‐10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS‐10 and B6. We then produced congenic strains to fine‐map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121–129.068 Mb; build 37) appeared to account for all the difference between CSS‐10 and B6. The smaller congenic strain (Line 2: 127.277–129.068 Mb) was intermediate between CSS‐10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis‐eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F₂ crosses can be dissected into multiple smaller QTLs shows a weaknesses of two‐stage approaches that seek to use coarse mapping to identify large regions followed by fine‐mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine‐mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine‐mapping QTLs .     

Exome sequencing and arrayCGH detection of gene sequence and copy number variation between ILS and ISS mouse strains

It has been well documented that genetic factors can influence predisposition to develop alcoholism. While the underlying genomic changes may be of several types, two of the most common and disease associated are copy number variations (CNVs) and sequence alterations of protein coding regions. The goal of this study was to identify CNVs and single-nucleotide polymorphisms that occur in gene coding regions that may play a role in influencing the risk of an individual developing alcoholism. Toward this end, two mouse strains were used that have been selectively bred based on their differential sensitivity to alcohol: the Inbred long sleep (ILS) and Inbred short sleep (ISS) mouse strains. Differences in initial response to alcohol have been linked to risk for alcoholism, and the ILS/ISS strains are used to investigate the genetics of initial sensitivity to alcohol. Array comparative genomic hybridization (arrayCGH) and exome sequencing were conducted to identify CNVs and gene coding sequence differences, respectively, between ILS and ISS mice. Mouse arrayCGH was performed using catalog Agilent 1 × 244 k mouse arrays. Subsequently, exome sequencing was carried out using an Illumina HiSeq 2000 instrument. ArrayCGH detected 74 CNVs that were strain-specific (38 ILS/36 ISS), including several ISS-specific deletions that contained genes implicated in brain function and neurotransmitter release. Among several interesting coding variations detected by exome sequencing was the gain of a premature stop codon in the alpha-amylase 2B (AMY2B) gene specifically in the ILS strain. In total, exome sequencing detected 2,597 and 1,768 strain-specific exonic gene variants in the ILS and ISS mice, respectively. This study represents the most comprehensive and detailed genomic comparison of ILS and ISS mouse strains to date. The two complementary genome-wide approaches identified strain-specific CNVs and gene coding sequence variations that should provide strong candidates to contribute to the alcohol-related phenotypic differences associated with these strains.     

Differential profiles of genes expressed in neonatal brain of 129X1/SvJ and C57BL/6J mice: A database to aid in analyzing DNA microarrays using nonisogenic gene-targeted mice.

Strain-specific differences in gene expression have been observed among various inbred mouse strains. Two strains that are commonly used in gene-targeting research today are the 129 substrains, which are used to produce ES cell lines, and C57BL/6J, which is used for the extensive backcrosses required to produce isogenic knockout mice. When F2 nonisogenic littermates are assessed using DNA microarrays, one must determine whether the expression profiles obtained resulted either from specific alteration(s) induced by the targeted gene mutation or from gene expression differences related to the genetic background of the parent mouse strains. In the present study, we report the differential expression profile of genes expressed in neonatal brains and adult spleen and liver of 129X1/SvJ and C57BL/6J strains of mice. These comprehensive profiles were assessed using two types of Agilent Mouse Oligo Microarrays (development and standard) and were compiled into a publicly available database. Researchers can use this database to determine whether their microarray findings represent strain-specific differences in gene expression by comparing their data with those cataloged in our database. This database is useful for effectively analyzing DNA microarray data from nonisogenic littermates, and would help researchers avoid time-consuming backcrosses and confirmatory experiments requiring the use of many mice.     

Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database

Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.     

冠突散囊菌野生型与△veA突变菌株的差异蛋白研究

为了分离和鉴定冠突散囊菌野生型与veA基因缺失菌株的差异表达蛋白,寻找并比较与veA基因相关的产孢蛋白,为进一步研究丝状真菌产孢机理打下基础。经veA基因缺失,利用双向电泳技术分离差异表达蛋白,经凝胶银染显色后,Bio-Rad凝胶扫描仪扫描,Imagemaster图像软件分析,差异蛋白点进行质谱鉴定。所获肽序列与生物信息数据库匹配,在NCBI及Uniprot数据库中查找蛋白质信息,并归纳分析。结果显示,野生型菌株中出现表达上调的蛋白点77个,veA缺失型菌株中出现表达上调的蛋白点有116个,得到鉴定的30个功能各异的蛋白点,其中大多数蛋白与代谢相关。     

Comparative proteomic analysis of early salt stress responsive proteins in roots and leaves of rice

Growth and productivity of rice (Oryza sativa L.) are severely affected by salinity. Understanding the mechanisms that protect rice and other important cereal crops from salt stress will help in the development of salt‐stress‐tolerant strains. In this study, rice seedlings of the same genetic species with various salt tolerances were studied. We first used 2DE to resolve the expressed proteome in rice roots and leaves and then used nanospray liquid chromatography/tandem mass spectrometry to identify the differentially expressed proteins in rice seedlings after salt treatment. The 2DE assays revealed that there were 104 differentially expressed protein spots in rice roots and 59 in leaves. Then, we identified 83 proteins in rice roots and 61 proteins in rice leaves by MS analysis. Functional classification analysis revealed that the differentially expressed proteins from roots could be classified into 18 functional categories while those from leaves could be classified into 11 functional categories. The proteins from rice seedlings that most significantly contributed to a protective effect against increased salinity were cysteine synthase, adenosine triphosphate synthase, quercetin 3‐O‐methyltransferase 1, and lipoxygenase 2. Further analysis demonstrated that the primary mechanisms underlying the ability of rice seedlings to tolerate salt stress were glycolysis, purine metabolism, and photosynthesis. Thus, we suggest that differentially expressed proteins may serve as marker group for the salt tolerance of rice.     

Screening of differentially expressed miRNAs related to muscle strain and their target gene

Muscle strain is one of the most common muscle injuries seen in the office of a practicing physician. To get a better understanding of this injury, we identified the differentially expressed miRNAs in muscle stem cells collected from injured muscle tissues of mouse. In this study, we downloaded the gene expression microarray (GSE26780) from Gene Expression Omnibus database. The dataset contained a total of 12 samples (murine muscle stem cells), including normal controls and samples collected from tissues at different time points after the injury. Differentially expreesed miRNAs were identified by LIMMA package and target genes of mmu-miR-143 were found by TargetScan. Then, a protein-protein interaction (PPI) network was constructed for the products of these target genes by using KUPS. Finally, Cytoscape and its plugins were used to identify and analyze the modules in this network. According to the results, 121, 136 and 148 differentially expressed miRNAs were identified in injured samples at each time point, and among them, 60 miRNAs were overlapping between all three groups. The expression values of mmu-miR-143 were most significantly altered over time at 36–72 h after the injury. Therefore, 510 target genes of mmu-miR-143 were found and a PPI network for the products of these target genes was constructed. Moreover, two modules were identified in the PPI network. Together with the previous studies, we suppose that proteins in module B, most of which are collagens or integrins, most likely participate in healing of strain injuries through cell adhesion processes.     

Analysis of cDNA sequences from mouse testis

Few mammalian proteins involved in chromosome structure and function during meiosis have been characterized. As an approach to identify such proteins, cDNA clones expressed in mouse testis were analyzed by sequencing and Northern blotting. Various cDNA library screening methods were used to obtain the clones. First, hybridization with cDNA from testis or brain allowed selection of either negative or differentially expressed plaques. Second, positive plaques were identified by screening with polyclonal antisera to prepubertal testis nuclear proteins. Most clones were selected by negative hybridization to correspond to a low abundance class of mRNAs. A PCR-based solid-phase DNA sequencing protocol was used to rapidly obtain 306 single-pass cDNA sequences totaling more than 104 kb. Comparison with nucleic acid and protein databases showed that 56% of the clones have no significant match to any previously identified sequence. Northern blots indicate that many of these novel clones are testis-enriched in their expression. Further evidence that the screening strategies were appropriate is that a high proportion of the clones which do have a match encode testisenriched or meiosis-specific genes, including the mouse homolog of a rat gene that encodes a synaptonemal complex protein.The nucleotide sequence data reported in this paper have been submitted to Genbank and have been assigned the accession numbers L26606–1.26848.