A green alga Desmodesmus sp. JSC3 is a lutein producer that appears high in lutein production in batch culture under 200μmol·m−2·s−1 condition using 1g∙L−1 sodium nitrate as nitrogen source. Because ...lutein content increased as growth advanced with the maximum (5.18mg∙g−1) on day 6, comparative transcriptome and physiological analyses on day 1, 6, and 8 were thus employed to uncover the molecular mechanisms for lutein production in this lutein producer. The gene set enrichment analysis using the False Discovery Rate (FDR) test showed that chlorophyll synthesis and photosynthesis were significantly changed when lutein accumulated. The up-regulation of the carotenogenesis genes explains the preference of this alga in lutein accumulation by enhancing lycopene synthesis and promoting metabolic flux towards synthesis of α-carotene and then hydroxylation of the β- and ε-ring of α-carotene, in the late exponential growth period (4–6days). Chlorophyll content and the expression of the genes encoding the enzymes in tetrapyrrole biosynthesis also increased during 0–6days, although chlorophyll a/chlorophyll b ratio decreased on day 6 due to light attenuation caused by high cell density. Photosynthetic activity and the expression of the genes encoding light-harvesting complex (LHC) proteins increased during 0–4days but decreased after that due to nitrogen deficiency (up-regulation of high-affinity nitrate transporter gene and low medium nitrate concentration). It suggests that LHC synthesis and photosynthesis are sensitive to nitrogen deficiency occurring on day 6 while pigment synthesis remains active. Because the expression of the genes encoding LHC-like proteins (early light-inducible proteins) that bind lutein and chlorophyll increased on day 6, LHC-like proteins could be temporarily stores of accumulating pigments. In conclusion, coordinate up-regulation of LHC-like proteins with pigment synthesis for the acclimation to decreasing light availability is believed as the molecular mechanism for high lutein production in Desmodesmus sp. JSC3.
A genetic interaction refers to the deviation of phenotypes from the expected when perturbing two genes simultaneously. Studying genetic interactions help clarify relationships between genes, such as ...compensation and masking, and identify gene groups of functional modules. Recently, several genome-scale experiments for measuring quantitative (positive and negative) genetic interactions have been conducted. The results revealed that genes in the same module usually interact with each other in a consistent way (pure positive or negative); this phenomenon was designated as monochromaticity. Monochromaticity might be the underlying principle that can be utilized to unveil the modularity of cellular networks. However, no appropriate quantitative measurement for this phenomenon has been proposed.
In this study, we propose the monochromatic index (MCI), which is able to quantitatively evaluate the monochromaticity of potential functional modules of genes, and the MCI was used to study genetic landscapes in different cellular subsystems. We demonstrated that MCI not only amend the deficiencies of MP-score but also properly incorporate the background effect. The results showed that not only within-complex but also between-complex connections present significant monochromatic tendency. Furthermore, we also found that significantly higher proportion of protein complexes are connected by negative genetic interactions in metabolic network, while transcription and translation system adopts relatively even number of positive and negative genetic interactions to link protein complexes.
In summary, we demonstrate that MCI improves deficiencies suffered by MP-score, and can be used to evaluate monochromaticity in a quantitative manner. In addition, it also helps to unveil features of genetic landscapes in different cellular subsystems. Moreover, MCI can be easily applied to data produced by different types of genetic interaction methodologies such as Synthetic Genetic Array (SGA), and epistatic miniarray profile (E-MAP).
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Predicting disulfide connectivity precisely helps towards the solution of protein structure prediction. In this study, a descriptor derived from the sequential distance between oxidized cysteines ...(denoted as DOC) is proposed. An approach using support vector machine (SVM) method based on weighted graph matching was further developed to predict the disulfide connectivity pattern in proteins. When DOC was applied, prediction accuracy of 63% for our SVM models could be achieved, which is significantly higher than those obtained from previous approaches. The results show that using the non-local descriptor DOC coupled with local sequence profiles significantly improves the prediction accuracy. These improvements demonstrate that DOC, with a proper scaling scheme, is an effective feature for the prediction of disulfide connectivity. The method developed in this work is available at the web server PreCys (prediction of cys–cys linkages of proteins). Availability: Contact: cykao@csie.ntu.edu.tw Supplementary information: Supplementary data, detailed results, tables and information are available at
Mitochondrial dysfunction is associated with various aging diseases. The copy number of mtDNA in human cells may therefore be a potential biomarker for diagnostics of aging. Here we propose a new ...computational method for the accurate assessment of mtDNA copies from whole genome sequencing data.
Two families of the human whole genome sequencing datasets from the HapMap and the 1000 Genomes projects were used for the accurate counting of mitochondrial DNA copy numbers. The results revealed the parental mitochondrial DNA copy numbers are significantly lower than that of their children in these samples. There are 8%~21% more copies of mtDNA in samples from the children than from their parents. The experiment demonstrated the possible correlations between the quantity of mitochondrial DNA and aging-related diseases.
Since the next-generation sequencing technology strives to deliver affordable and non-biased sequencing results, accurate assessment of mtDNA copy numbers can be achieved effectively from the output of whole genome sequencing. We implemented the method as a software package MitoCounter with the source code and user's guide available to the public at http://sourceforge.net/projects/mitocounter/.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Midbody, a transient organelle-like structure, is known as central for abscission and is indispensable for termination of cytokinesis. Here, we used the midbody proteome inventories to construct the ...potential midbody protein−protein interaction (PPI) network. To delineate novel regulators participating in cytokinesis, the z-score, a standard statistic score, rather than hub degree was implemented to prioritize the novel hubs. Of these hubs, KIAA0133, SEPT1, KIAA1377, and CRMP-1 were localized to the midbody, whereas HTR3A and ICAM2 were associated with the cleavage furrow as examined by immunofluorescence. Knockdown of SEPT1 and KIAA1377 resulted in increasing numbers of cytokinesis defect cells, suggesting these newly identified hubs play critical roles in cytokinesis progression. Moreover, ectopic expression of CRMP-1 mutant in which Aurora-A phosphorylation sites have been replaced with Ala results in a cytokinesis defect. This subproteome network construction not only sheds light on the intimate interactions of the midbody proteomes, but also prioritizes novel hubs or protein complexes that may govern the process of cytokinesis.
Neighboring genes in the eukaryotic genome have a tendency to express concurrently, and the proximity of two adjacent genes is often considered a possible explanation for their co-expression ...behavior. However, the actual contribution of the physical distance between two genes to their co-expression behavior has yet to be defined. To further investigate this issue, we studied the co-expression of neighboring genes in zebrafish, which has a compact genome and has experienced a whole genome duplication event. Our analysis shows that the proportion of highly co-expressed neighboring pairs (Pearson's correlation coefficient R>0.7) is low (0.24% approximately 0.67%); however, it is still significantly higher than that of random pairs. In particular, the statistical result implies that the co-expression tendency of neighboring pairs is negatively correlated with their physical distance. Our findings therefore suggest that physical distance may play an important role in the co-expression of neighboring genes. Possible mechanisms related to the neighboring genes' co-expression are also discussed.
Metagenomics enables the study of unculturable microorganisms in different environments directly. Discriminating between the compositional differences of metagenomes is an important and challenging ...problem. Several distance functions have been proposed to estimate the differences based on functional profiles or taxonomic distributions; however, the strengths and limitations of such functions are still unclear. Initially, we analyzed three well-known distance functions and found very little difference between them in the clustering of samples. This motivated us to incorporate suitable normalizations and phylogenetic information into the functions so that we could cluster samples from both real and synthetic data sets. The results indicate significant improvement in sample clustering over that derived by rank-based normalization with phylogenetic information, regardless of whether the samples are from real or synthetic microbiomes. Furthermore, our findings suggest that considering suitable normalizations and phylogenetic information is essential when designing distance functions for estimating the differences between metagenomes. We conclude that incorporating rank-based normalization with phylogenetic information into the distance functions helps achieve reliable clustering results.
The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease ...markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level.
Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO http://ehco.iis.sinica.edu.tw, to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25%) from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network) by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs.
This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Motivation: Disulfide bonds play an important role in protein folding. A precise prediction of disulfide connectivity can strongly reduce the conformational search space and increase the accuracy in ...protein structure prediction. Conventional disulfide connectivity predictions use sequence information, and prediction accuracy is limited. Here, by using an alternative scheme with global information for disulfide connectivity prediction, higher performance is obtained with respect to other approaches. Result: Cysteine separation profiles have been used to predict the disulfide connectivity of proteins. The separations among oxidized cysteine residues on a protein sequence have been encoded into vectors named cysteine separation profiles (CSPs). Through comparisons of their CSPs, the disulfide connectivity of a test protein is inferred from a non-redundant template set. For non-redundant proteins in SwissProt 39 (SP39) sharing less than 30% sequence identity, the prediction accuracy of a fourfold cross-validation is 49%. The prediction accuracy of disulfide connectivity for proteins in SwissProt 43 (SP43) is even higher (53%). The relationship between the similarity of CSPs and the prediction accuracy is also discussed. The method proposed in this work is relatively simple and can generate higher accuracies compared to conventional methods. It may be also combined with other algorithms for further improvements in protein structure prediction. Availability: The program and datasets are available from the authors upon request. Contact: cykao@csie.ntu.edu.tw
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