重离子束辐照诱变啤酒酵母线粒体DNA研究

摘要 II 5. 在不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株中扩增获得位 于第 12 染色体上的 SOF1 基因，而在同样的扩增体系中没有得到野生型 菌株的该基因。 6. 选取离子束辐照后筛选出来的呼吸缺陷型酵母菌株再次进行辐照，发现 其在低剂量范围（＜0.93Gy）辐照下非常敏感，而在高剂量范围（＞ 0.93Gy）又表现出一定程度的辐射抗性。 结论： 1. 离子束辐照酵母细胞，直接或间接作用于酵母线粒体DNA，导致线粒体 DNA损伤，形成呼吸缺陷的酵母菌株。 2. I 类内含子和 II 类内含子对于离子束辐照的敏感性不同： II 类内含子比较 稳定，II 类内含子可能利用自身编码的反转录酶通过目的DNA引导的反 转录机制对受到辐照损伤的II 类内含子进行修复。 3. 离子束辐照后 SOF1 基因可能发生了突变，影响酵母细胞的生长。 4. 呼吸缺陷型酵母菌株因其线粒体 DNA发生变化及线粒体功能的改变， 使 呼吸缺陷型酵母菌株在不同剂量区的离子束辐照下表现不同辐射敏感 性。目的： 研究啤酒酵母的线粒体 DNA 在重离子辐照作用下的突变效应及其突变机 理。 材料与方法： 利用兰州重离子研究装置(HIRFL)加速的氖、碳离子辐照酵母细胞，用 TTC 显色培养基筛选呼吸缺陷型酵母菌株，并用 mtDNA 限制性酶切手段分析其突变 规律。采用 PCR扩增并对目的产物测序的方法对辐照后线粒体DNA上的 I 类内 含子和 II类内含子进行研究。 结果： 1. TTC 显色实验表明：离子束辐照导致酵母线粒体上的电子传递链发生改 变，产生的还原氢减少，造成呼吸缺陷。 2. 利用限制性酶切实验对线粒体 DNA进行研究，结果表明：离子束辐照诱 变筛选出来的呼吸缺陷型酵母菌株其线粒体DNA变化明显： 主要表现为 酶切条带缺失严重。即使在同一注量下筛选出来的呼吸缺陷型酵母菌株， 其酶切图谱也不相同。 3. 通过 PCR 手段对辐照后酵母线粒体 DNA 碱基序列进一步进行分析，发 现经不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株，其I 类内含 子（ai4 and ai5）经设计不同引物进行扩增，没有获得目的条带，说明此 序列发生了突变，可能对离子束辐照比较敏感。 4. 经不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株，其 II 类内含 子（ai2）的碱基序列与野生型相比没有变化，表现出在离子束辐照作用 下比较稳定的特性。

经碳离子束诱变的甜高粱汁酒精发酵高产菌株的研究

为了选育出适合发酵甜高粱汁来生产酒精的酵母菌株，本论文以酒精酵母Saccharomyces cerevisiae YY为材料，利用兰州近代物理研究所重离子研究装置（HIRFL）产生的100MeV/u碳离子束对酒精酵母进行了辐照诱变。采用红四氮唑（TTC）作为筛选指示剂，初筛得到了5株产酒能力有所提高的突变酵母菌。通过甜高粱汁发酵，测定发酵液中酒精含量和残糖，复筛出产酒精能力比出发菌株有明显提高的诱变菌株T4。并对其发酵条件进行了优化，以期获得的结果能够为甜高粱汁工业化生产酒精提供参考数据。通过本论文的研究，得到以下初步结果： 1. 在甜高粱汁培养基中，酒精酵母YY的对数生长期在8-20h之间，此时菌体的生长繁殖比较旺盛，活力最佳，为辐照诱变的最佳时期。辐照后，菌体的存活率随辐照剂量的增加呈现出逐渐衰减的趋势。 2. 红四氮唑TTC是一种无色显色指示剂，活菌中所含的脱氢酶可将它还原成红色，因此可以根据菌落呈色的深浅判断酵母菌产酒精能力的高低，从而挑选出产酒能力较高的菌株。本试验用TTC双层培养基法初步筛选出了利用甜高粱汁发酵生产酒精能力较强的T4酵母菌株。 3. 对影响T4菌发酵甜高粱汁生产酒精的几个主要因素（甜高粱汁糖度、接种量、温度、pH、无机盐）进行了初步探讨研究，得出了T4菌发酵甜高粱汁生产酒精的最适条件为：甜高粱汁糖度22%，接种量10%，温度30oC,pH 4.5 ,无机盐加入量为:（NH4）2SO4 1g/L，KH2PO4 5g/L，MgSO4 3g/L。 4. 对发酵条件进行优化后的中试结果显示：出发菌株YY发酵甜高粱汁的时间为36h，酒精产量为8.6% (V/V) ，而T4突变菌甜高粱汁发酵液中的最终酒精含量可以达到9.8%，发酵时间仅为24h。因此，T4菌在工业应用中很有前景

Direct toxicity assessment of toxic chemicals with electrochemical method

Electrochemical measurement of respiratory chain activity is a rapid and reliable screening for the toxicity on microorganisms. Here, we investigated in-vitro effects of toxin on Escherichia coli (E. coli) that was taken as a model microorganism incubated with ferricyanide. The current signal of ferrocyanide effectively amplified by ultramicroelectrode array (UMEA), which was proven to be directly related to the toxicity. Accordingly, a direct toxicity assessment (DTA) based on chronoamperometry was proposed to detect the effect of toxic chemicals on microorganisms. The electrochemical responses to 3,5-dichlorophenol (DCP) under the incubation times revealed that the toxicity reached a stable level at 60 min, and its 50% inhibiting concentration (IC50) was estimated to be 8.0 mg L-1. At 60 min incubation, the IC50 values for KCN and As2O3 in water samples were 4.9 mg L-1 and 18.3 mg L-1, respectively. But the heavy metal ions, such as Cu2+ Pb2+ and Ni2+, showed no obvious toxicity on E. coli.

Uncovering the rules for protein-protein interactions from yeast genomic data

Identifying protein-protein interactions is crucial for understanding cellular functions. Genomic data provides opportunities and challenges in identifying these interactions. We uncover the rules for predicting protein-protein interactions using a frequent pattern tree (FPT) approach modified to generate a minimum set of rules (mFPT), with rule attributes constructed from the interaction features of the yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regressions under various statistical measures. Our study indicates that mFPT outranks other methods in predicting the protein-protein interactions for the database used. We predict a new protein-protein interaction complex whose biological function is related to premRNA splicing and new protein-protein interactions within existing complexes based on the rules generated.

Fatty acid biosynthesis in eukaryotic photosynthetic microalgae: Identification of a microsomal delta 12 desaturase in Chlamydomonas reinhardtii

Polyunsaturated fatty acids (PUFAs) are important components of infant and adult nutrition because they serve as structural elements of cell membranes. Fatty acid desaturases are responsible for the insertion of double bonds into pre-formed fatty acid chains in reactions that require oxygen and reducing equivalents. In this study, the genome-wide characterization of the fatty acid desaturases from seven eukaryotic photosynthetic microalgae was undertaken according to the conserved histidine-rich motifs and phylogenetic profiles. Analysis of these genomes provided insight into the origin and evolution of the pathway of fatty acid biosynthesis in eukaryotic plants. In addition, the candidate enzyme from Chlamydomonas reinhardtii with the highest similarity to the microsomal Delta 12 desaturase of Chlorella vulgaris was isolated, and its function was verified by heterologous expression in yeast (Saccharomyces cerevisiae).

Molecular cloning and responsive expression to injury stimulus of a defender against cell death 1 (DAD1) gene from bay scallops Argopecten irradians

Apoptosis is an active process of cell death, which is an integral part of growth and development in multicellular organisms. The defender against cell death 1 (DAD1), the regulatory protein to inhibit the apoptosis process, was first cloned from the bay scallop Argopecten irradians by randomly sequencing a whole tissue cDNA library and rapid amplification of cDNA end (RACE). The full-length cDNA of the A. irradians DAD1 was 607 bp, consist of a 5'-terminal untranslated region (UTR) of 63 bp, a 3'-terminal UTR of 205 bp with a canonical polyadenylation signal sequence AATAAA and a poly (A) tail, and an open reading frame of 339 bp. The deduced amino acid sequence of the A. irradians DAD1 showed 75.5% identity to Araneus ventricosus, 74.5% to Drosophila melanogaster, and 73.6% to Homo sapiens, Sus scrofa, Mesocricetus auratus, Rattus norvegicus and Mus musculus. Excluding the Saccharomyces cerevisiae DAD1 homologue, all animal DAD1 including A. irradians DAD1 homologue formed a subgroup and all plant DAD1 proteins formed another subgroup in the phylogenetic analysis. The A. irradians DAD1 was expressed in all examined tissues including adductor muscle, mantle, gills, digestive gland, gonad and hemolymph, suggesting that A. irradians DAD1 is expressed in most body tissues. Furthermore, the mRNA expression levels of A. irradians DAD1 gene of hemolymph were particularly high after injury, suggesting that the gene is responsive to injury stimuli.

Data mining the yeast genome in a lazy functional language

Clare, A. and King R.D. (2003) Data mining the yeast genome in a lazy functional language. In Practical Aspects of Declarative Languages (PADL'03) (won Best/Most Practical Paper award).

Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics

Struyf, J., Dzeroski, S. Blockeel, H. and Clare, A. (2005) Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. In proceedings of the EPIA 2005 CMB Workshop

Functional genomic hypothesis generation and experimentation by a robot scientist

King R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S., Kell, D. B. and Oliver, S. G. (2004) Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427 (6971) p247-252

Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

Ferrochelatase is a conserved downstream target of the blue light-sensing White collar complex in fungi.

Light is a universal signal perceived by organisms, including fungi, in which light regulates common and unique biological processes depending on the species. Previous research has established that conserved proteins, originally called White collar 1 and 2 from the ascomycete Neurospora crassa, regulate UV/blue light sensing. Homologous proteins function in distant relatives of N. crassa, including the basidiomycetes and zygomycetes, which diverged as long as a billion years ago. Here we conducted microarray experiments on the basidiomycete fungus Cryptococcus neoformans to identify light-regulated genes. Surprisingly, only a single gene was induced by light above the commonly used twofold threshold. This gene, HEM15, is predicted to encode a ferrochelatase that catalyses the final step in haem biosynthesis from highly photoreactive porphyrins. The C. neoformans gene complements a Saccharomyces cerevisiae hem15Delta strain and is essential for viability, and the Hem15 protein localizes to mitochondria, three lines of evidence that the gene encodes ferrochelatase. Regulation of HEM15 by light suggests a mechanism by which bwc1/bwc2 mutants are photosensitive and exhibit reduced virulence. We show that ferrochelatase is also light-regulated in a white collar-dependent fashion in N. crassa and the zygomycete Phycomyces blakesleeanus, indicating that ferrochelatase is an ancient target of photoregulation in the fungal kingdom.

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Conservation, duplication, and loss of the Tor signaling pathway in the fungal kingdom.

BACKGROUND: The nutrient-sensing Tor pathway governs cell growth and is conserved in nearly all eukaryotic organisms from unicellular yeasts to multicellular organisms, including humans. Tor is the target of the immunosuppressive drug rapamycin, which in complex with the prolyl isomerase FKBP12 inhibits Tor functions. Rapamycin is a gold standard drug for organ transplant recipients that was approved by the FDA in 1999 and is finding additional clinical indications as a chemotherapeutic and antiproliferative agent. Capitalizing on the plethora of recently sequenced genomes we have conducted comparative genomic studies to annotate the Tor pathway throughout the fungal kingdom and related unicellular opisthokonts, including Monosiga brevicollis, Salpingoeca rosetta, and Capsaspora owczarzaki. RESULTS: Interestingly, the Tor signaling cascade is absent in three microsporidian species with available genome sequences, the only known instance of a eukaryotic group lacking this conserved pathway. The microsporidia are obligate intracellular pathogens with highly reduced genomes, and we hypothesize that they lost the Tor pathway as they adapted and streamlined their genomes for intracellular growth in a nutrient-rich environment. Two TOR paralogs are present in several fungal species as a result of either a whole genome duplication or independent gene/segmental duplication events. One such event was identified in the amphibian pathogen Batrachochytrium dendrobatidis, a chytrid responsible for worldwide global amphibian declines and extinctions. CONCLUSIONS: The repeated independent duplications of the TOR gene in the fungal kingdom might reflect selective pressure acting upon this kinase that populates two proteinaceous complexes with different cellular roles. These comparative genomic analyses illustrate the evolutionary trajectory of a central nutrient-sensing cascade that enables diverse eukaryotic organisms to respond to their natural environments.

Modulation of heat shock transcription factor 1 as a therapeutic target for small molecule intervention in neurodegenerative disease.

Neurodegenerative diseases such as Huntington disease are devastating disorders with no therapeutic approaches to ameliorate the underlying protein misfolding defect inherent to poly-glutamine (polyQ) proteins. Given the mounting evidence that elevated levels of protein chaperones suppress polyQ protein misfolding, the master regulator of protein chaperone gene transcription, HSF1, is an attractive target for small molecule intervention. We describe a humanized yeast-based high-throughput screen to identify small molecule activators of human HSF1. This screen is insensitive to previously characterized activators of the heat shock response that have undesirable proteotoxic activity or that inhibit Hsp90, the central chaperone for cellular signaling and proliferation. A molecule identified in this screen, HSF1A, is structurally distinct from other characterized small molecule human HSF1 activators, activates HSF1 in mammalian and fly cells, elevates protein chaperone expression, ameliorates protein misfolding and cell death in polyQ-expressing neuronal precursor cells and protects against cytotoxicity in a fly model of polyQ-mediated neurodegeneration. In addition, we show that HSF1A interacts with components of the TRiC/CCT complex, suggesting a potentially novel regulatory role for this complex in modulating HSF1 activity. These studies describe a novel approach for the identification of new classes of pharmacological interventions for protein misfolding that underlies devastating neurodegenerative disease.

Environmental and genetic determinants of colony morphology in yeast.

Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs.