Mutagenic lesion bypass and two functionally different RecA proteins in Deinococcus deserti

RecA is essential for extreme radiation tolerance in Deinococcus radiodurans . Interestingly, Sahara bacterium Deinococcus deserti has three recA genes ( recA _C, recA _P1, recA _P3) that code for two different RecA proteins (RecA_C, RecA_P). Moreover, and in contrast to other sequenced Deinococcus species, D. deserti possesses homologues of translesion synthesis (TLS) DNA polymerases, including ImuY and DnaE2. Together with a lexA homologue, imuY and dnaE2 form a gene cluster similar to a widespread RecA/LexA-controlled mutagenesis cassette. After having developed genetic tools, we have constructed mutant strains to characterize these recA and TLS polymerase genes in D. deserti . Both RecA_C and RecA_P are functional and allow D. deserti to survive, and thus repair massive DNA damage, after exposure to high doses of radiation. D. deserti is mutable by UV, which requires ImuY, DnaE2 and RecA_C, but not RecA_P. RecA_C, but not RecA_P, facilitates induced expression of imuY and dnaE2 following UV exposure. We propose that the extra recA _P1 and recA _P3 genes may provide higher levels of RecA protein for efficient error-free repair of DNA damage, without further increasing error-prone lesion bypass by ImuY and DnaE2, whereas limited TLS may contribute to adaptation to harsh conditions by generating genetic variability.     

Major soluble proteome changes in Deinococcus deserti over the earliest stages following gamma-ray irradiation

Background

Deinococcus deserti VCD115 has been isolated from Sahara surface sand. This radiotolerant bacterium represents an experimental model of choice to understand adaptation to harsh conditions encountered in hot arid deserts. We analysed the soluble proteome dynamics in this environmentally relevant model after exposure to 3 kGy gamma radiation, a non-lethal dose that generates massive DNA damages. For this, cells were harvested at different time lapses after irradiation and their soluble proteome contents have been analysed by 2-DE and mass spectrometry.

Results

In the first stage of the time course we observed accumulation of DNA damage response protein DdrB (that shows the highest fold change ~11), SSB, and two different RecA proteins (RecA_P and RecA_C). Induction of DNA repair protein PprA, DNA damage response protein DdrD and the two gyrase subunits (GyrA and GyrB) was also detected. A response regulator of the SarP family, a type II site-specific deoxyribonuclease and a putative N-acetyltransferase are three new proteins found to be induced. In a more delayed stage, we observed accumulation of several proteins related to central metabolism and protein turn-over, as well as helicase UvrD and novel forms of both gyrase subunits differing in terms of isoelectric point and molecular weight.

Conclusions

Post-translational modifications of GyrA (N-terminal methionine removal and acetylation) have been evidenced and their significance discussed. We found that the Deide_02842 restriction enzyme, which is specifically found in D. deserti, is a new potential member of the radiation/desiccation response regulon, highlighting the specificities of D. deserti compared to the D. radiodurans model.     

耐辐射异常球菌DNA损伤与修复相关基因的比较基因组研究

耐辐射球菌 (Ｄｅｉｎｏｃｏｃｃｕｓｒａｄｉｏｄｕｒａｎｓ,ＤＲ)是Ａｎｄｅｒｓｏｎ等[1] 在 1 95 6年从灭菌处理的肉类中发现的一种非病原性红色球菌 ,该球菌对电离辐射 (存活最高剂量约 1 5ｋＧｙ,即普通真核生物的 1 0 0 0倍 )、紫外线、干燥、强氧化剂和一些化学诱变剂显示惊人的抗性[2～5] 。实验证实 ,由辐射引起的损伤ＤＮＡ在几十小时内能够完全修复[4 ,5] 。这种超强ＤＮＡ修复能力吸引人们去研究其潜在修复机制以及寻找与修复有关的特殊基因或酶 ,以便能应用基因工程的技术对放射性、重金属污染物进行生物修复 ,为癌症治疗尤其…     

Peptidoglycan Fine Structure of the Radiotolerant Bacterium Deinococcus radiodurans Sark

Peptidoglycan from Deinococcus radiodurans was analyzed by high-performance liquid chromatography and mass spectrometry. The monomeric subunit was: N-acetylglucosamine–N-acetylmuramic acid–l-Ala–d-Glu-(γ)–l-Orn-[(δ)Gly-Gly]–d-Ala–d-Ala. Cross-linkage was mediated by (Gly)₂ bridges, and glycan strands were terminated in (1→6)anhydro-muramic acid residues. Structural relations with the phylogenetically close Thermus thermophilus are discussed.The gram-positive bacterium Deinococcus radiodurans is remarkable because of its extreme resistance to ionizing radiation (14). Phylogenetically the closest relatives of Deinococcus are the extreme thermophiles of the genus Thermus (4, 11). In 16S rRNA phylogenetic trees, the genera Thermus and Deinococcus group together as one of the older branches in bacterial evolution (11). Both microorganisms have complex cell envelopes with outer membranes, S-layers, and ornithine-Gly-containing mureins (7, 12, 19, 20, 22, 23). However, Deinococcus and Thermus differ in their response to the Gram reaction, having positive and negative reactions, respectively (4, 14). The murein structure for Thermus thermophilus HB8 has been recently elucidated (19). Here we report the murein structure of Deinococcus radiodurans with similar detail.D. radiodurans Sark (23) was used in the present study. Cultures were grown in Luria-Bertani medium (13) at 30°C with aeration. Murein was purified and subjected to amino acid and high-performance liquid chromatography (HPLC) analyses as previously described (6, 9, 10, 19). For further analysis muropeptides were purified, lyophilized, and desalted as reported elsewhere (6, 19). Purified muropeptides were subjected to plasma desorption linear time-of-flight mass spectrometry (PDMS) as described previously (1, 5, 16, 19). Positive and negative ion mass spectra were obtained on a short linear ²⁵²californium time-of-flight instrument (BioIon AB, Uppsala, Sweden). The acceleration voltage was between 17 and 19 kV, and spectra were accumulated for 1 to 10 million fission events. Calibration of the mass spectra was done in the positive ion mode with H⁺ and Na⁺ ions and in the negative ion mode with H⁻ and CN⁻ ions. Calculated m/z values are based on average masses.Amino acid analysis of muramidase (Cellosyl; Hoechst, Frankfurt am Main, Germany)-digested sacculi (50 μg) revealed Glu, Orn, Ala, and Gly as the only amino acids in the muramidase-solubilized material. Less than 3% of the total Orn remained in the muramidase-insoluble fraction, indicating an essentially complete solubilization of murein.Muramidase-digested murein samples (200 μg) were analyzed by HPLC as described in reference 19. The muropeptide pattern (Fig. ​(Fig.1)1) was relatively simple, with five dominating components (DR5 and DR10 to DR13 [Fig. 1]). The muropeptides resolved by HPLC were collected, desalted, and subjected to PDMS. The results are presented in Table ​Table11 compared with the m/z values calculated for best-matching muropeptides made up of N-acetylglucosamine (GlucNAc), N-acetylmuramic acid (MurNAc), and the amino acids detected in the murein. The more likely structures are shown in Fig. ​Fig.1.1. According to the m/z values, muropeptides DR1 to DR7 and DR9 were monomers; DR8, DR10, and DR11 were dimers; and DR12 and DR13 were trimers. The best-fitting structures for DR3 to DR8, DR11, and DR13 coincided with muropeptides previously characterized in T. thermophilus HB8 (19) and had identical retention times in comparative HPLC runs. The minor muropeptide DR7 (Fig. ​(Fig.1)1) was the only one detected with a d-Ala–d-Ala dipeptide and most likely represents the basic monomeric subunit. The composition of the major cross-linked species DR11 and DR13 confirmed that cross-linking is mediated by (Gly)₂ bridges, as proposed previously (20). Open in a separate windowFIG. 1HPLC muropeptide elution patterns of murein purified from D. radiodurans. Muramidase-digested murein samples were subjected to HPLC analysis, and the A₂₀₄ of the eluate was recorded. The most likely structures for each muroeptide as deduced by PDMS are shown. The position of residues in brackets is the most likely one as deduced from the structures of other muropeptides but could not be formally demonstrated. R = GlucNac–MurNac–l-Ala–d-Glu-(γ)→.

TABLE 1

Calculated and measured m/z values for the molecular ions of the major muropeptides from D. radiodurans

Repair of Oxidized Bases in the Extremely Radiation-Resistant Bacterium Deinococcus radiodurans

Deinococcus radiodurans is able to resist and survive extreme DNA damage induced by ionizing radiation and many other DNA-damaging agents. It is believed that it possesses highly efficient DNA repair mechanisms. To characterize the repair pathway of oxidized purines in this bacteria, we have purified, from crude extracts, proteins that recognize these oxidized bases. We report here that D. radiodurans possesses two proteins excising the oxidized purines (formamidopyrimidine and 8-oxoguanine) by a DNA glycosylase–a purinic/apyrimidine lyase mechanism. Moreover, one of those proteins is endowed with a thymine glycol DNA glycosylase activity. One of these proteins could be the homolog of the Escherichia coli Fpg enzyme, which confirms the existence of a base excision repair system in this bacteria.     

Specific Expansion of Protein Families in the Radioresistant Bacterium Deinococcus Radiodurans

Computer analysis of the complete genome of Deinococcus radioduransR1 reveals a number of protein families, which are over-represented in this organism, compared to most other bacteria with known genome sequences. These families include both previously characterized and uncharacterized proteins. Most of the families whose functions are known or could be predicted seem to be related to stress-response and elimination of damage products (cell-cleaning). The two most prominent family expansions are the Nudix (MutT) family of pyrophosphohydrolases and a previously unnoticed family of proteins related to Bacillus subtilisDinB that could possess a metal-dependent enzymatic activity whose exact nature remains to be determined. Several proteins of the expanded families, particularly the Nudix family, are fused to other domains and form multidomain proteins that are so far unique for Deinococcus. The domain composition of some of these proteins indicates that they could be involved in novel DNA-repair pathways. Such unique proteins are good targets for knock-out and gene expression studies, which are aimed to shed light on the unusual features of this interesting10.6pt bacterium.     

Integrating Genomics and Proteomics Data to Predict Drug Effects Using Binary Linear Programming

The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound''s effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound''s effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be used to elucidate potential mechanisms of a compound''s efficacy.     

Comparative Analysis of Genomics and Proteomics in Bacillus thuringiensis 4.0718

Bacillus thuringiensis is a widely used biopesticide that produced various insecticidal active substances during its life cycle. Separation and purification of numerous insecticide active substances have been difficult because of the relatively short half-life of such substances. On the other hand, substances can be synthetized at different times during development, so samples at different stages have to be studied, further complicating the analysis. A dual genomic and proteomic approach would enhance our ability to identify such substances, and particularily using mass spectrometry-based proteomic methods. The comparative analysis for genomic and proteomic data have showed that not all of the products deduced from the annotated genome could be identified among the proteomic data. For instance, genome annotation results showed that 39 coding sequences in the whole genome were related to insect pathogenicity, including five cry genes. However, Cry2Ab, Cry1Ia, Cytotoxin K, Bacteriocin, Exoenzyme C3 and Alveolysin could not be detected in the proteomic data obtained. The sporulation-related proteins were also compared analysis, results showed that the great majority sporulation-related proteins can be detected by mass spectrometry. This analysis revealed Spo0A~P, SigF, SigE(+), SigK(+) and SigG(+), all known to play an important role in the process of spore formation regulatory network, also were displayed in the proteomic data. Through the comparison of the two data sets, it was possible to infer that some genes were silenced or were expressed at very low levels. For instance, found that cry2Ab seems to lack a functional promoter while cry1Ia may not be expressed due to the presence of transposons. With this comparative study a relatively complete database can be constructed and used to transform hereditary material, thereby prompting the high expression of toxic proteins. A theoretical basis is provided for constructing highly virulent engineered bacteria and for promoting the application of proteogenomics in the life sciences.     

抗辐射茵(Deinococcus radiopugnance)的质粒pUE30的克隆及序列分析

抗辐射菌(Deinococcus radiopugnance)ATCC 19172株中存在约14.6 kb、8.7 kb、7.0 kb、3.65 kb、及2.45 kb等5种以上的隐秘性质粒,对其中的约2.45 kb的小型质粒pUE30进行了序列测定与分析,该质粒由2 467 bp的碱基对组成,其中包含了267 nt及1 068 nt的2个开放阅读框架(open reading frame,ORF)和一个AT-rich领域。经过与GenBank的数据库分析,其中267 nt的ORF(repC)与豆科根瘤菌(Rhizobium leguminosa-rum)及根癌农杆菌(Agrobacterium tumefaciens)由来的质粒的RepC蛋白质具有一定的同源性;1 068 nt的ORF(repD)与抗辐射菌(Deinococcus radiodurans)Sark株的质粒pUE10的RepU蛋白质、嗜热菌(Thermus sp.)ATCC27737株由来的质粒pMY1的RepA蛋白质具有较高的同源性。研究结果对于利用该小型质粒构建大肠杆菌-抗辐射菌属间的穿梭载体,表明抗辐射菌高效正确的DNA损伤修复机理等具有重要的意义。     

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB) with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be considered as pre-training for various applications of deep learning in bioinformatics. The related data is available at Life Language Processing Website: http://llp.berkeley.edu and Harvard Dataverse: http://dx.doi.org/10.7910/DVN/JMFHTN.