Genome-scale analysis of Streptomyces coelicolor A3(2) metabolism

Streptomyces are filamentous soil bacteria that produce more than half of the known microbial antibiotics. We present the first genome-scale metabolic model of a representative of this group--Streptomyces coelicolor A3(2). The metabolism reconstruction was based on annotated genes, physiological and biochemical information. The stoichiometric model includes 819 biochemical conversions and 152 transport reactions, accounting for a total of 971 reactions. Of the reactions in the network, 700 are unique, while the rest are iso-reactions. The network comprises 500 metabolites. A total of 711 open reading frames (ORFs) were included in the model, which corresponds to 13% of the ORFs with assigned function in the S. coelicolor A3(2) genome. In a comparative analysis with the Streptomyces avermitilis genome, we showed that the metabolic genes are highly conserved between these species and therefore the model is suitable for use with other Streptomycetes. Flux balance analysis was applied for studies of the reconstructed metabolic network and to assess its metabolic capabilities for growth and polyketides production. The model predictions of wild-type and mutants' growth on different carbon and nitrogen sources agreed with the experimental data in most cases. We estimated the impact of each reaction knockout on the growth of the in silico strain on 62 carbon sources and two nitrogen sources, thereby identifying the "core" of the essential reactions. We also illustrated how reconstruction of a metabolic network at the genome level can be used to fill gaps in genome annotation.     

融合基因芯片数据上下文特定网络的重构

目的在特定类型细胞或特定环境条件下,已有的全基因组代谢网络中的部分反应并不参与到实际的代谢过程中。为反映特定条件下生物体代谢系统的工作状态,本文提出一种重构上下文特定网络的新方法,用来构建特定条件下的代谢网络。方法首先根据基因芯片数据中蕴含的PACalls信息,南基因-酶-反应之间的调控关系,计算出在表达层面上为“Absent”状态的反应集合。然后使用一个？昆合整数规划模型,从全基因代谢网络中删除表达为“Absent”状态的反应及其关联反应,在满足计量平衡等约束条件下．寻找与表达层面吻合最优的网络,即为特定条件下的上下文特定网络。结果重构了肝脏和心脏两种组织的上下文特定网络。实验结果表明,两种组织的上下文特定网络存在很大差异性．尤其在某些具有组织特异性的代谢功能上,如胆汁酸合成等。结论融合基因芯片数据信息的上下文特定网络重构方法,能够有效构建反映特定条件下生物体代谢系统状态的上下文特定网络。     

Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling

Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.     

Functional genomics of genes with small open reading frames (sORFs) in S. cerevisiae

Genes with small open reading frames (sORFs; <100 amino acids) represent an untapped source of important biology. sORFs largely escaped analysis because they were difficult to predict computationally and less likely to be targeted by genetic screens. Thus, the substantial number of sORFs and their potential importance have only recently become clear. To investigate sORF function, we undertook the first functional studies of sORFs in any system, using the model eukaryote Saccharomyces cerevisiae. Based on independent experimental approaches and computational analyses, evidence exists for 299 sORFs in the S. cerevisiae genome, representing approximately 5% of the annotated ORFs. We determined that a similar percentage of sORFs are annotated in other eukaryotes, including humans, and 184 of the S. cerevisiae sORFs exhibit similarity with ORFs in other organisms. To investigate sORF function, we constructed a collection of gene-deletion mutants of 140 newly identified sORFs, each of which contains a strain-specific "molecular barcode," bringing the total number of sORF deletion strains to 247. Phenotypic analyses of the new gene-deletion strains identified 22 sORFs required for haploid growth, growth at high temperature, growth in the presence of a nonfermentable carbon source, or growth in the presence of DNA damage and replication-arrest agents. We provide a collection of sORF deletion strains that can be integrated into the existing deletion collection as a resource for the yeast community for elucidating gene function. Moreover, our analyses of the S. cerevisiae sORFs establish that sORFs are conserved across eukaryotes and have important biological functions.     

The evolution of metabolic enzymes in Plasmodium and trypanosomatids as compared to Saccharomyces and Schizosaccharomyces

Understanding how the biological connectivity of genes and gene products affects evolution is an important aspect of understanding evolution. Genes encoding enzymes are frequently used to carry out such analyses. Interestingly, studies have shown that connectivity in the metabolic networks in parasitic protists, including Plasmodium falciparum and Trypanosoma brucei, have been substantially altered as compared to free living eukaryotes, such as Saccharomyces cerevisiae. Herein, we have determined K(a) values, which are a measure of the non-synonymous substitution rate, and used them to examine the differences between the evolution of genes in T. brucei, P. falciparum, S. cerevisiae, and Schizosaccharomyces pombe. All four organisms share similar traits with respect to the evolution of genes encoding metabolic enzymes. First, genes encoding metabolic enzymes have lower K(a) values than genes encoding non-metabolic proteins. In addition, perturbations of the metabolic network appear to have limited affects on the genes encoding enzymes near the perturbation. In most cases, there is a negative relationship between connectivity in the metabolic network of the gene product and the K(a) value for the gene, i.e. examining how much constraint there is on gene evolution when it is connected to many other genes. In addition, we find that the K(a) values of orthologs encoding for metabolic enzymes in each organism are significantly correlated, indicating similar patterns of non-synonymous substitutions. In total, our results indicate that the evolution of genes encoding metabolic enzymes do not tend to be greatly affected by changes in the metabolic network.     

Sequence-based approach for identification of cell wall proteins in Saccharomyces cerevisiae

Open reading frames (ORFs) in the genome of Saccharomyces cerevisiae were screened for cell wall proteins and extracellular proteins, using an in silico sequence analysis combined with biochemical examination. The selection criteria used in the sequence analysis were the presence of a signal sequence for secretion and the absence of any targeting and retention signal to/in intracellular components. By using the PSORT II program, 163 ORFs/proteins were selected as potential extracellular proteins, including cell wall proteins. Of these, 51 ORFs/proteins of unknown localization and more than 120 amino acids in size were further studied on their cellular localization. A hemagglutinin (HA) epitope was inserted in the most C-terminus of each protein and the resulting HA-tagged protein was expressed under the authentic promoter in yeast cells. Out of the 51 constructs, 35 gave protein bands on Western blots. Examination of proteins in fractionated samples identified 11 extracellular proteins; six proteins that were weakly associated with the cell wall and five proteins that were relatively tightly associated with the cell wall.     

Kaposi’s sarcoma: a computational approach through protein–protein interaction and gene regulatory networks analysis

Interactomic data for Kaposi’s Sarcoma Associated Herpes virus (KSHV)—the causative agent of vascular origin tumor called Kaposi’s sarcoma—is relatively modest to date. The objective of this study was to assign functions to the previously uncharacterized ORFs in the virus using computational approaches and subsequently fit them to the host interactome landscape on protein, gene, and cellular level. On the basis of expression data, predicted RNA interference data, reported experimental data, and sequence based functional annotation we also tried to hypothesize the ORFs role in lytic and latent cycle during viral infection. We studied 17 previously uncharacterized ORFs in KSHV and the host-virus interplay seems to work in three major functional pathways—cell division, transport, metabolic and enzymatic in general. Studying the host-virus crosstalk for lytic phase predicts ORF 10 and ORF 11 as a predicted virus hub whereas PCNA is predicted as a host hub. On the other hand, ORF31 has been predicted as a latent phase inducible protein. KSHV invests a lion’s share of its coding potential to suppress host immune response; various inflammatory mediators such as IFN-γ, TNF, IL-6, and IL-8 are negatively regulated by the ORFs while Il-10 secretion is stimulated in contrast. Although, like any other computational prediction, the study requires further validation, keeping into account the reproducibility and vast sample size of the systems biology approach the study allows us to propose an integrated network for host-virus interaction with good confidence. We hope that the study, in the long run, would help us identify effective dug against potential molecular targets.     

Simultaneous genotyping, gene-expression measurement, and detection of allele-specific expression with oligonucleotide arrays

Oligonucleotide microarrays provide a high-throughput method for exploring genomes. In addition to their utility for gene-expression analysis, oligonucleotide-expression arrays have also been used to perform genotyping on genomic DNA. Here, we show that in segregants from a cross between two unrelated strains of Saccharomyces cerevisiae, high-quality genotype data can also be obtained when mRNA is hybridized to an oligonucleotide-expression array. We were able to identify and genotype nearly 1000 polymorphisms at an error rate close to 3% in segregants and at an error rate of 7% in diploid strains, a performance comparable to methods using genomic DNA. In addition, we demonstrate how simultaneous genotyping and gene-expression profiling can reveal cis-regulatory variation by screening hundreds of genes for allele-specific expression. With this method, we discovered 70 ORFs with evidence for preferential expression of one allele in a diploid hybrid of two S. cerevisiae strains.     

Effect of afferent visual impulses on morphological and biochemical indices of the development of neurons of the optical,motor, and parietal cortex of the brain

We have demonstrated cytochemically that absence of visual impulsation from the time of birth causes two types of reconstruction in the cerebral structures. The first type is associated with reactions of a biochemical deficiency (in the optic and parietal cortex), the second with reactions of biochemical activation (in the motor cortex). We established that the changed organization of the metabolic processes is reversible provided that specific impulsation is resumed. This reconstruction is most complex for compensatorily activated neurons, and less complex for neurons showing signs of biochemical deficiency.Translated from Zhurnal Nevropatologii i Psikhiatrii imeni S. S. Korsakova, Vol. 82, No. 7, pp. 974–980, July, 1982.     

Isolation,heterological cloning and sequencing of the RPL28 gene in Kluyveromyces lactis

By virtue of heterologous functional complementation of the Saccharomyces cerevisiae Delta pdr5 mutant strain, using a Kluyveromyces lactis genomic library, three different K. lactis chromosomal inserts were obtained. Transformation of the S. cerevisiae Delta pdr1 Delta pdr3 mutant strain, hypersensitive to drugs, with isolated plasmids resulted in resistance to cycloheximide and fluconazole. Transformation of K. lactis host strains, using the cloned chromosomal fragments, led to an increased level of resistance to some mitochondrial inhibitors and azole antifungals. The nucleotide sequence of the cloned inserts revealed that two of them contain the drug efflux transporter gene Kl-PDR5 and the third contains a DNA segment homologous to chromosome VII of S. cerevisiae. Along with three novel ORFs, encoding two proteins of unknown molecular function and one putative hexose transporter, this segment also contained the Kl-RPL28 gene, found to be responsible for the cycloheximide resistance of heterologous transformants. This gene codes for the large subunit ribosomal protein (149 amino acids) that shares 89.9% identity with its S. cerevisiae counterpart. The coding region of Kl-RPL28 was found to be interrupted with one intron near the 5' end. The nucleotide sequence data reported in this paper were submitted to GenBank and assigned the accession number AF493565.     

Metabolic functions of duplicate genes in Saccharomyces cerevisiae

The roles of duplicate genes and their contribution to the phenomenon of enzyme dispensability are a central issue in molecular and genome evolution. A comprehensive classification of the mechanisms that may have led to their preservation, however, is currently lacking. In a systems biology approach, we classify here back-up, regulatory, and gene dosage functions for the 105 duplicate gene families of Saccharomyces cerevisiae metabolism. The key tool was the reconciled genome-scale metabolic model iLL672, which was based on the older iFF708. Computational predictions of all metabolic gene knockouts were validated with the experimentally determined phenotypes of the entire singleton yeast library of 4658 mutants under five environmental conditions. iLL672 correctly identified 96%-98% and 73%-80% of the viable and lethal singleton phenotypes, respectively. Functional roles for each duplicate family were identified by integrating the iLL672-predicted in silico duplicate knockout phenotypes, genome-scale carbon-flux distributions, singleton mutant phenotypes, and network topology analysis. The results provide no evidence for a particular dominant function that maintains duplicate genes in the genome. In particular, the back-up function is not favored by evolutionary selection because duplicates do not occur more frequently in essential reactions than singleton genes. Instead of a prevailing role, multigene-encoded enzymes cover different functions. Thus, at least for metabolism, persistence of the paralog fraction in the genome can be better explained with an array of different, often overlapping functional roles.     

基于主成分分析-神经网络的非编码RNA预测

预测非编码RNA对认识其调控功能具有重要意义。选择单核苷酸和二核苷酸出现频率作为神经网络分类特征,运用主成分分析方法降低输入数据的维数,去除数据间的相关性,采用Levenberg-Marquardt算法改善网络训练速度。对数据集的测试结果表明,此方法对细菌混合ncRNA的预测精度达到81.3%,对原核生物tRNA的预测精度达到93.3%,表明该方法能有效预测原核生物ncRNA。预测结果还发现两种古细菌的ORF序列在序列特征上与其它细菌和古细菌存在差别。     

Sexual behavior and its pheromonal regulation in ascosporogenous yeasts

We reviewed our investigations on sexual behaviors and interactions including sexual cell agglutination and pheromone action mainly in non-conventional yeasts, Hansenula anomala, H. wingei, Pichia amethionina, P. heedi, P. opuntiae, Saccharomyces kluyveri, S. globsus, S. exiguus, Saccharomycodes ludwigii. The techniques and genetic models including the cassette model and alpha 1-alpha 2 hypothesis which had been developed largely in S. cerevisiae were applicable to these yeasts in principle. The sexual agglutination was distinctly species-specific while sex pheromones were cross-reactive beyond species' barriers. The successful induction of heterothallic strains from homothallic strains in S. exiguus by mutagenesis enabled to the subsequent biochemical and genetical analysis of sexual behavior in the yeast. The phylogenetic consideration on sex differentiation is also included.     

Functional Versatility and Molecular Diversity of the Metabolic Map of Escherichia coli

We have analyzed the known metabolic enzymes of Escherichia coli in relation to their biochemical reaction properties and their involvement in biochemical pathways. All enzymes involved in small-molecule metabolism and their corresponding protein sequences have been extracted from the EcoCyc database. These 548 metabolic enzymes are clustered into 405 protein families according to sequence similarity. In this study, we examine the functional versatility within enzyme families in terms of their reaction capabilities and pathway participation. In addition, we examine the molecular diversity of reactions and pathways according to their presence across enzyme families. These complex, many-to-many relationships between protein sequence and biochemical function reveal a significant degree of correlation between enzyme families and reactions. Pathways, however, appear to require more than one enzyme type to perform their complex biochemical transformations. Finally, the distribution of enzyme family members across different pathways provides support for the "recruitment" hypothesis of biochemical pathway evolution.     

Identification of programmed translational -1 frameshifting sites in the genome of Saccharomyces cerevisiae

Frameshifting is a recoding event that allows the expression of two polypeptides from the same mRNA molecule. Most recoding events described so far are used by viruses and transposons to express their replicase protein. The very few number of cellular proteins known to be expressed by a -1 ribosomal frameshifting has been identified by chance. The goal of the present work was to set up a systematic strategy, based on complementary bioinformatics, molecular biology, and functional approaches, without a priori knowledge of the mechanism involved. Two independent methods were devised. The first looks for genomic regions in which two ORFs, each carrying a protein pattern, are in a frameshifted arrangement. The second uses Hidden Markov Models and likelihood in a two-step approach. When this strategy was applied to the Saccharomyces cerevisiae genome, 189 candidate regions were found, of which 58 were further functionally investigated. Twenty-eight of them expressed a full-length mRNA covering the two ORFs, and 11 showed a -1 frameshift efficiency varying from 5% to 13% (50-fold higher than background), some of which corresponds to genes with known functions. From other ascomycetes, four frameshifted ORFs are found fully conserved. Strikingly, most of the candidates do not display a classical viral-like frameshift signal and would have escaped a search based on current models of frameshifting. These results strongly suggest that -1 frameshifting might be more widely distributed than previously thought.     

Application of DNA typing methods and genetic analysis to epidemiology and taxonomy of Saccharomyces isolates.

We have previously described differences in phenotype and virulence among clinical and nonclinical isolates of Saccharomyces. To further characterize these isolates, a comparison of restriction fragment length polymorphism (RFLP) patterns and genetic analysis were done. The cellular DNA of each of 49 clinical and 11 nonclinical isolates of Saccharomyces was digested with the endonuclease EcoRI, and the resultant fragments were separated by electrophoresis. Sixty isolates were grouped on the basis of the presence (group B) or absence (group A) of a 3-kb band. Group A contained 43 isolates (35 clinical and 8 nonclinical isolates) in 31 discernible subgroups, and group B had 17 isolates (14 clinical and 3 nonclinical isolates) in 10 subgroups. Interestingly, six of eight known vaginal isolates were group B, with four of those six being identical. Virulence of isolates was associated with membership in group A (P = 0.03). Comparison of known members of sibling species within the genus Saccharomyces, which cannot be distinguished by standard biochemical tests, showed that S. paradoxus, S. bayanus, and S. cerevisiae could be differentiated by RFLP analysis. Genetic analysis of the isolates forming viable spores showed that most group A isolates were diploid and members of the species S. cerevisiae. Those group A and B isolates unable to form viable spores may be diploid hybrids between Saccharomyces species. The group B isolates that formed viable spores were tetraploid and may also be interspecific hybrids. Overall, clinical isolates of Saccharomyces were very heterogeneous and exhibited little clonality. RFLP pattern analysis could be a useful method of demonstrating transmission in patients with infection or between environmental sources and patients.