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With the development of high throughput technologies, there are more and more protein–protein interaction (PPI) networks available, which provide a need for efficient computational tools for network alignment. Network alignment is widely used to predict functions of certain proteins, identify conserved network modules, and study the evolutionary relationship across species or biological entities. However, network alignment is an NP-complete problem, and previous algorithms are usually slow or less accurate in aligning big networks like human vs. yeast. In this study, we proposed a fast yet accurate algorithm called Network Alignment by Integrating Biological Process (NAIGO). Specifically, we first divided the networks into subnets taking the advantage of known prior knowledge, such as gene ontology. For each subnet pair, we then developed a novel method to align them by considering both protein orthologous information and their local structural information. After that, we expanded the obtained local network alignments in a greedy manner. Taking the aligned pairs as seeds, we formulated the global network alignment problem as an assignment problem based on similarity matrix, which was solved by the Hungarian method. We applied NAIGO to align human and Saccharomyces cerevisiae S288c PPI network and compared the results with other popular methods like IsoRank, GRAAL, SANA, and NABEECO. As a result, our method outperformed the competitors by aligning more orthologous proteins or matched interactions. In addition, we found a few potential functional orthologous proteins such as RRM2B in human and DNA2 in S. cerevisiae S288c, which are related to DNA repair. We also identified a conserved subnet with six orthologous proteins EXO1, MSH3, MSH2, MLH1, MLH3, and MSH6, and six aligned interactions. All these proteins are associated with mismatch repair. Finally, we predicted a few proteins of S. cerevisiae S288c potentially involving in certain biological processes like autophagosome assembly.

Benzoxazinoids are secondary metabolites with plant defense properties and possible health-promoting effects in humans. In this study, the transcriptional activity of ScBx genes ( ScBx1-ScBx5 ; ScBx6-like ), involved in benzoxazinoid biosynthesis, was analyzed during germination and early seedling development in rye. Our results showed that ScBx genes had highest levels of expression at 24–30 h after germination, followed by a decrease at later stages. For ScBx1-ScBx5 genes expression was higher in shoots compared with root tissues and vice versa for ScBx6-like gene transcripts. Moreover, methylated forms of benzoxazinoids accumulated in roots rather than in shoots during seedling development, in particular reaching high levels of HMBOA-glc in roots. Chemical profiles of benzoxazinoid accumulation in the developing seedling reflected the combined effects of de novo biosynthesis of the compounds as well as the turnover of compounds either pre-stored in the embryo or de novo biosynthesized. Bioinformatic analysis, together with the differential distribution of ScBx6-like transcripts in root and shoot tissues, suggested the presence of a ZmBx6 homolog encoding a 2-oxoglutarate dependent dehydrogenase in rye. The ScBx6-like cDNA was expressed in E. coli for functional characterization in vitro . LC-MS/MS analysis showed that the purified enzyme was responsible for the oxidation of DIBOA-glc into TRIBOA-glc, strongly suggesting the ScBX6-like enzyme in rye to be a functional ortholog of maize ZmBX6. [ABSTRACT FROM AUTHOR]

A major goal in cancer medicine is to find selective drugs with reduced side effect. A pair of genes is called synthetic lethality (SL) if mutations of both genes will kill a cell while mutation of either gene alone will not. Hence, a gene in SL interactions with a cancer-specific mutated gene will be a promising drug target with anti-cancer selectivity. Wet-lab screening approach is still so costly that even for yeast only a small fraction of gene pairs has been covered. Computational methods are therefore important for large-scale discovery of SL interactions. Most existing approaches focus on individual features or machine-learning methods, which are prone to noise or overfitting. In this paper, we propose an approach named MetaSL for predicting yeast SL, which integrates 17 genomic and proteomic features and the outputs of 10 classification methods. MetaSL thus combines the strengths of existing methods and achieves the highest area under the Receiver Operating Characteristics (ROC) curve (AUC) of 87.1% among all competitors on yeast data. Moreover, through orthologous mapping from yeast to human genes, we then predicted several lists of candidate SL pairs in human cancer. Our method and predictions would thus shed light on mechanisms of SL and lead to discovery of novel anti-cancer drugs. In addition, all the experimental results can be downloaded from http://www.ntu.edu.sg/home/zhengjie/data/MetaSL. [ABSTRACT FROM AUTHOR]

Dietary restriction (DR) increases life span, health span and resistance to stress in a wide range of organisms. Work from a large number of laboratories has revealed evolutionarily conserved mechanisms that mediate the DR response. Here, we analyzed the genome-wide gene expression profiles of Caenorhabditis elegans under DR versus ad libitum conditions. Using the Ortho2ExpressMatrix tool, we searched for C. elegans orthologs of mouse genes that have been shown to be differentially expressed under DR conditions in nearly 600 experiments. Based on our bioinformatic approaches, we obtained 189 DR-responsive genes, and 45 of these are highly conserved from worm to man. Subsequent testing of sixteen genes that are up-regulated under DR identified eight genes that abolish the DR-induced resistance to heat stress in C. elegans. Further analyses revealed that fkb- 4, dod- 22 and ikb- 1 genes also abolish increased life span in response to DR. The identified genes that are necessary for the DR response are sensitive to certain stress signals such as metabolic perturbances ( dod- 22, fkb- 4 and nhr- 85), DNA damage ( ikb- 1), heat shock ( hsp- 12.6) and cancer-like overgrowth ( prk- 2 and tsp- 15). We propose that most of the DR-responsive genes identified are components of the recently discovered cellular surveillance-activated detoxification and defenses pathway, which is, among others, important for the survival of organisms in times of food deprivation. [ABSTRACT FROM AUTHOR]