Chung-Yen Lin

Hubba: hub objects analyzer—a framework of interactome hubs identification for network biology

One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba.

In silico analysis of crustacean hyperglycemic hormone family.

Through multiple sequence alignment and phylogenetic analysis, the subgrouping of the crustacean hyperglycemic hormone (CHH) family was updated using the most complete, nonredundant sequence data set. All sequences from insects were clustered into a distinct subbranch with characters closer to CHH subfamily I. Several sequences that are controversial in their nomenclature and classification are discussed. The motif configuration of CHHs differs from that of molt-inhibiting hormone or gonad-inhibiting hormone in both N and C termini. These two motifs approach each other in tertiary structure models, and the motif preference reveals the critical roles of these regions in functional specificity. Two types of exon organizations of the CHH family genes were observed. Four-exon Chh genes were found in a wide range of pan-crustacean (crustacean and hexapod) taxa, except for the penaeid species, from which the 3-exon Chh genes were reported. Meanwhile, the 3-exon structure was found in the Mih gene and Moih genes from one brachyuran species. Combining gene scan skill and exon splicing rules found in this study, we define three more novel sequences from two insect genomes. The pattern of the exon-exon junction within the mature peptide segment is preserved in all CHH family members.

Cloning of Two Crustacean Hyperglycemic Hormone Isoforms in Freshwater Giant Prawn (Macrobrachium rosenbergii): Evidence of Alternative Splicing

A full-length chh cDNA was cloned from the eyestalk of Macrobrachium rosenbergii. The 991-bp cDNA contains an open reading frame of 408 bp that encodes the prepro-CHH. The tissue-specific expression pattern was examined by reverse transcriptase-polymerase chain reaction. Positive signals were detected in the eyestalk, heart, gills, antennal glands, and thoracic ganglion but not in muscle and hepatopancreas. However, two types of products were observed. The nucleotide sequences revealed the existence of 2 chh transcripts, named chh and chh-l, respectively. Direct sequence evidence suggests that these two isoforms come from a Chh gene transcribed in an alternative splicing manner. The Mar-Chh gene consists of 4 exons. The eyestalk transcript (chh) contains exons I, II, and IV, whereas the chh-l transcript in heart, gills, antennal glands, and thoracic ganglion contains all 4 exons. The appearance of exon III in chh-l cDNA changes the sequence content in the latter half of the mature peptide, starting within the codon of the 40th residue, arginine. The amino acid sequence deduced from exon III matched no homologue in public protein databases, while the 2 cysteine residues in this segment preserved the positional conservation characters of CHH neuropeptide family members. The common organization of Chh genes between palaemonid, brachyuran, and astacus crustaceans suggests that the Chh gene has a 4-exon structure in these species.

cytoHubba: identifying hub objects and sub-networks from complex interactome

BackgroundNetwork is a useful way for presenting many types of biological data including protein-protein interactions, gene regulations, cellular pathways, and signal transductions. We can measure nodes by their network features to infer their importance in the network, and it can help us identify central elements of biological networks.ResultsWe introduce a novel Cytoscape plugin cytoHubba for ranking nodes in a network by their network features. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, Maximal Clique Centrality and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. Among the eleven methods, the new proposed method, MCC, has a better performance on the precision of predicting essential proteins from the yeast PPI network.ConclusionsCytoHubba provide a user-friendly interface to explore important nodes in biological networks. It computes all eleven methods in one stop shopping way. Besides, researchers are able to combine cytoHubba with and other plugins into a novel analysis scheme. The network and sub-networks caught by this topological analysis strategy will lead to new insights on essential regulatory networks and protein drug targets for experimental biologists. According to cytoscape plugin download statistics, the accumulated number of cytoHubba is around 6,700 times since 2010.

High-throughput profiling of influenza A virus hemagglutinin gene at single-nucleotide resolution

Genetic research on influenza virus biology has been informed in large part by nucleotide variants present in seasonal or pandemic samples, or individual mutants generated in the laboratory, leaving a substantial part of the genome uncharacterized. Here, we have developed a single-nucleotide resolution genetic approach to interrogate the fitness effect of point mutations in 98% of the amino acid positions in the influenza A virus hemagglutinin (HA) gene. Our HA fitness map provides a reference to identify indispensable regions to aid in drug and vaccine design as targeting these regions will increase the genetic barrier for the emergence of escape mutations. This study offers a new platform for studying genome dynamics, structure-function relationships, virus-host interactions, and can further rational drug and vaccine design. Our approach can also be applied to any virus that can be genetically manipulated.

Hyperglycaemic effects of dopamine in tiger shrimp, Penaeus monodon

Abstract The presence and the physiological functions of biogenic amines as neuroregulators mediating the release of neurohormones have been documented in crustaceans. The possible involvement and the stimulatory pathway of dopamine in hyperglycaemia of the tiger shrimp, Penaeus monodon , were investigated. Two isoforms of crustacean hyperglycaemic hormone (CHH), CHH1 and CHH2, were identified. They were equally potent in the diabetic effect, and showed a great similarity in their amino acid composition profile, which is however, distinct from those reported from other crustacean species, such as the shore crab, Mexican crayfish and American lobster. Thus, species variation in the amino acid composition of CHH exists among the crustaceans. Dopamine was found to mimic the action of CHH in inducing hyperglycaemia in intact shrimps, but not in bilaterally eyestalk-ablated individuals. The hyperglycaemic response of shrimps that were treated with the agonist and antagonist to D 1 and D 2 receptors, suggest that dopamine functions as a neuroregulator, which in turn stimulates the release of CHH mainly through D 1 receptors in tiger shrimps.

POWER: PhylOgenetic WEb Repeater—an integrated and user-optimized framework for biomolecular phylogenetic analysis

POWER, the PhylOgenetic WEb Repeater, is a web-based service designed to perform user-friendly pipeline phylogenetic analysis. POWER uses an open-source LAMP structure and infers genetic distances and phylogenetic relationships using well-established algorithms (ClustalW and PHYLIP). POWER incorporates a novel tree builder based on the GD library to generate a high-quality tree topology according to the calculated result. POWER accepts either raw sequences in FASTA format or user-uploaded alignment output files. Through a user-friendly web interface, users can sketch a tree effortlessly in multiple steps. After a tree has been generated, users can freely set and modify parameters, select tree building algorithms, refine sequence alignments or edit the tree topology. All the information related to input sequences and the processing history is logged and downloadable for the users reference. Furthermore, iterative tree construction can be performed by adding sequences to, or removing them from, a previously submitted job. POWER is accessible at .

A Review of the Major Penaeid Shrimp EST Studies and the Construction of a Shrimp Transcriptome Database Based on the ESTs from Four Penaeid Shrimp

By economic value, shrimp is currently the most important seafood commodity worldwide, and these animals are often the subject of scientific research in shrimp farming countries. High throughput methods, such as expressed sequence tags (ESTs), were originally developed to study human genomics, but they are now available for studying other important organisms, including shrimp. ESTs are short sequences generated by sequencing randomly selected cDNA clones from a cDNA library. This is currently the most efficient and powerful method for providing transcriptomic data for organisms with an uncharacterized genome. This review will summarize the sixteen major shrimp EST studies that have been conducted to date. In addition, we analyzed the EST data downloaded from NCBI dbEST for the four major penaeid shrimp species and constructed a database to host all of these EST data as well as our own analysis results. This database provides the shrimp aquaculture research community with an outline of the shrimp transcriptome as well as a tool for shrimp gene identification.

PALM: A Paralleled and Integrated Framework for Phylogenetic Inference with Automatic Likelihood Model Selectors

Background Selecting an appropriate substitution model and deriving a tree topology for a given sequence set are essential in phylogenetic analysis. However, such time consuming, computationally intensive tasks rely on knowledge of substitution model theories and related expertise to run through all possible combinations of several separate programs. To ensure a thorough and efficient analysis and avert tedious manipulations of various programs, this work presents an intuitive framework, the phylogenetic reconstruction with automatic likelihood model selectors (PALM), with convincing, updated algorithms and a best-fit model selection mechanism for seamless phylogenetic analysis. Methodology As an integrated framework of ClustalW, PhyML, MODELTEST, ProtTest, and several in-house programs, PALM evaluates the fitness of 56 substitution models for nucleotide sequences and 112 substitution models for protein sequences with scores in various criteria. The input for PALM can be either sequences in FASTA format or a sequence alignment file in PHYLIP format. To accelerate the computing of maximum likelihood and bootstrapping, this work integrates MPICH2/PhyML, PalmMonitor and Palm job controller across several machines with multiple processors and adopts the task parallelism approach. Moreover, an intuitive and interactive web component, PalmTree, is developed for displaying and operating the output tree with options of tree rooting, branches swapping, viewing the branch length values, and viewing bootstrapping score, as well as removing nodes to restart analysis iteratively. Significance The workflow of PALM is straightforward and coherent. Via a succinct, user-friendly interface, researchers unfamiliar with phylogenetic analysis can easily use this server to submit sequences, retrieve the output, and re-submit a job based on a previous result if some sequences are to be deleted or added for phylogenetic reconstruction. PALM results in an inference of phylogenetic relationship not only by vanquishing the computation difficulty of ML methods but also providing statistic methods for model selection and bootstrapping. The proposed approach can reduce calculation time, which is particularly relevant when querying a large data set. PALM can be accessed online at http://palm.iis.sinica.edu.tw.

A quantitative high-resolution genetic profile rapidly identifies sequence determinants of hepatitis C viral fitness and drug sensitivity.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.