Network neighborhood analysis with the multi-node topological overlap measure

MOTIVATION: The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. RESULTS: The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. AVAILABILITY: An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).     

TILLING in the two-rowed barley cultivar 'Barke' reveals preferred sites of functional diversity in the gene HvHox1

Background

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis.

Findings

We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering.

Conclusion

Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/     

Bioactive peptide design using the Resonant Recognition Model

With a large number of DNA and protein sequences already known, the crucial question is to find out how the biological function of these macromolecules is "written" in the sequence of nucleotides or amino acids. Biological processes in any living organism are based on selective interactions between particular bio-molecules, mostly proteins. The rules governing the coding of a protein's biological function, i.e. its ability to selectively interact with other molecules, are still not elucidated. In addition, with the rapid accumulation of databases of protein primary structures, there is an urgent need for theoretical approaches that are capable of analysing protein structure-function relationships. The Resonant Recognition Model (RRM) [1, 2] is one attempt to identify the selectivity of protein interactions within the amino acid sequence. The RRM [1, 2] is a physico-mathematical approach that interprets protein sequence linear information using digital signal processing methods. In the RRM the protein primary structure is represented as a numerical series by assigning to each amino acid in the sequence a physical parameter value relevant to the protein's biological activity. The RRM concept is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. Once the characteristic frequency for a particular protein function/interaction is identified, it is possible then to utilize the RRM approach to predict the amino acids in the protein sequence, which predominantly contribute to this frequency and thus, to the observed function, as well as to design de novo peptides having the desired periodicities. As was shown in our previous studies of fibroblast growth factor (FGF) peptidic antagonists [2, 3] and human immunodeficiency virus (HIV) envelope agonists [2, 4], such de novo designed peptides express desired biological function. This study utilises the RRM computational approach to the analysis of oncogene and proto-oncogene proteins. The results obtained have shown that the RRM is capable of identifying the differences between the oncogenic and proto-oncogenic proteins with the possibility of identifying the "cancer-causing" features within their protein primary structure. In addition, the rational design of bioactive peptide analogues displaying oncogenic or proto-oncogenic-like activity is presented here.     

Investigations into the relationship between feedback loops and functional importance of a signal transduction network based on Boolean network modeling

Background  

A number of studies on biological networks have been carried out to unravel the topological characteristics that can explain the functional importance of network nodes. For instance, connectivity, clustering coefficient, and shortest path length were previously proposed for this purpose. However, there is still a pressing need to investigate another topological measure that can better describe the functional importance of network nodes. In this respect, we considered a feedback loop which is ubiquitously found in various biological networks.     

PhySIC_IST: cleaning source trees to infer more informative supertrees

Background  

Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees.     

Modular co-evolution of metabolic networks

Background  

The architecture of biological networks has been reported to exhibit high level of modularity, and to some extent, topological modules of networks overlap with known functional modules. However, how the modular topology of the molecular network affects the evolution of its member proteins remains unclear.     

Synonymy of two species of the genus <Emphasis Type="Italic">Platycephalus</Emphasis> and validity of <Emphasis Type="Italic">Platycephalus westraliae</Emphasis> (Teleostei: Platycephalidae)

The type specimens of platycephalid Platycephalus endrachtensis Quoy and Gaimard 1825 are regarded as being conspecific with Platycephalus arenarius Ramsay and Ogilby 1886, so the latter becomes a junior synonym. This species is characterized as having a caudal fin with four or more longitudinal dark bands and lacking a yellow blotch. It is also found that Platycephalus westraliae (Whitley 1938), which had been considered to be a junior synonym of Platycephalus bassensis Cuvier 1829, is a valid species. Specimens that recently had been mistakenly identified as “P. endrachtensis,” having the caudal fin with three or four longitudinal dark bands and a yellow blotch on the upper lobe, should be referred to P. westraliae.     

Exploring biological network structure with clustered random networks

Background  

Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions) and the extent of clustering (the tendency for a set of three nodes to be interconnected) are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics.     

MQ-HNCO-TROSY for the measurement of scalar and residual dipolar couplings in larger proteins: application to a 557-residue IgFLNa16-21

We describe a novel pulse sequence, MQ-HNCO-TROSY, for the measurement of scalar and residual dipolar couplings between amide proton and nitrogen in larger proteins. The experiment utilizes the whole 2T_N polarization transfer delay for labeling of ¹⁵N chemical shift in a constant time manner, which efficiently doubles the attainable resolution in ¹⁵N dimension with respect to the conventional HNCO-TROSY experiment. In addition, the accordion principle is employed for measuring (J + D)_NHs, and the multiplet components are selected with the generalized version of the TROSY scheme introduced by Nietlispach (J Biomol NMR 31:161–166, 2005). Therefore, cross peak overlap is diminished while the time period during which the ¹⁵N spin is susceptible to fast transverse relaxation associated with the anti-TROSY transition is minimized per attainable resolution unit. The proposed MQ-HNCO-TROSY scheme was employed for measuring RDCs in high molecular weight protein IgFLNa16-21 of 557 residues, resulting in 431 experimental RDCs. Correlations between experimental and back-calculated RDCs in individual domains gave relatively low Q-factors (0.19–0.39), indicative of sufficient accuracy that can be obtained with the proposed MQ-HNCO-TROSY experiment in high molecular weight proteins.     

Modeling the effects of a Staphylococcal Enterotoxin B (SEB) on the apoptosis pathway

Background  

The lack of detailed understanding of the mechanism of action of many biowarfare agents poses an immediate challenge to biodefense efforts. Many potential bioweapons have been shown to affect the cellular pathways controlling apoptosis [1–4]. For example, pathogen-produced exotoxins such as Staphylococcal Enterotoxin B (SEB) and Anthrax Lethal Factor (LF) have been shown to disrupt the Fas-mediated apoptotic pathway [2, 4]. To evaluate how these agents affect these pathways it is first necessary to understand the dynamics of a normally functioning apoptosis network. This can then serve as a baseline against which a pathogen perturbed system can be compared. Such comparisons can expose both the proteins most susceptible to alteration by the agent as well as the most critical reaction rates to better instill control on a biological network.     

Target selection of soluble protein complexes for structural proteomics studies

Background  

Protein expression in E. coli is the most commonly used system to produce protein for structural studies, because it is fast and inexpensive and can produce large quantity of proteins. However, when proteins from other species such as mammalian are produced in this system, problems of protein expression and solubility arise [1]. Structural genomics project are currently investigating proteomics pipelines that would produce sufficient quantities of recombinant proteins for structural studies of protein complexes. To investigate how the E. coli protein expression system could be used for this purpose, we purified apoptotic binary protein complexes formed between members of the Caspase Associated Recruitment Domain (CARD) family.     

Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples

Background  

HIV can evolve drug resistance rapidly in response to new drug treatments, often through a combination of multiple mutations [1–3]. It would be useful to develop automated analyses of HIV sequence polymorphism that are able to predict drug resistance mutations, and to distinguish different types of functional roles among such mutations, for example, those that directly cause drug resistance, versus those that play an accessory role. Detecting functional interactions between mutations is essential for this classification. We have adapted a well-known measure of evolutionary selection pressure (K _a /K _s ) and developed a conditional K _a /K _s approach to detect important interactions.     

Effects of sequence diversity and recombination on the accuracy of phylogenetic trees estimated by kSNP

kSNP v2 is a powerful tool for single nucleotide polymorphism (SNP) identification from complete microbial genomes and for estimating phylogenetic trees from the identified SNPs. kSNP can analyse finished genomes, genome assemblies, raw reads or any combination of those and does not require either genome alignment or reference genomes. This study uses sequence evolution simulations to evaluate the topological accuracy of kSNP trees and to assess the effects of diversity and recombination on that accuracy. The accuracies of kSNP trees are strongly affected by increasing diversity, with parsimony accuracy > maximum‐likelihood accuracy > neighbour‐joining accuracy. Accuracy is also strongly influenced by recombination; as recombination increases accuracy decreases. Reliable trees are arbitrarily defined as those that have ≥ 90% topological accuracy. It is determined that the best predictor of topological accuracy is the ratio of r/m, a measure of the effect of recombination, to FCK (the fraction of core kmers), a measure of diversity. Tools are available to allow investigators to determine both r/m and FCK, and the relationship between topological accuracy and the ratio of r/m to FCK is determined. The practical implication of this study is that kSNP is an effective tool for estimating phylogenetic trees from microbial genome sequences provided that both recombination and sequence diversity are within acceptable ranges.     

Validity of <Emphasis Type="Italic">Scolecenchelys aoki</Emphasis>, with a redescription of <Emphasis Type="Italic">Scolecenchelys gymnota</Emphasis> (Anguilliformes: Ophichthidae)

The myrophine ophichthid fishes (worm eels) Muraenichthys aoki Jordan and Snyder 1901 and Muraenichthys gymnotus Bleeker 1857 are redescribed as valid species of Scolecenchelys based on the types and non-type specimens collected from the Indo-Pacific. Because both species are similar to each other in having acute snouts, the posterior margin of the eye before the rictus, and their dorsal-fin origins located slightly posterior to a vertical line through the anus, Scolecenchelys aoki has usually been regarded as a junior synonym of Scolecenchelys gymnota. However, S. aoki is clearly distinguishable from S. gymnota by having a median groove on the ventral side of snout (absent in S. gymnota), uniserial maxillary teeth in smaller specimens (<200 mm TL; vs. biserial), three infraorbital sensory pores at postorbital area (vs. two), and more numerous vertebrae (56–65 in predorsal vs. 51–57; 53–58 in preanal vs. 47–52). Scolecenchelys aoki is restricted to Japanese waters and regarded as a senior synonym of Muraenichthys borealis Machida and Shiogaki 1990. Scolecenchelys gymnota is widely distributed in the Indo-Pacific, from South Africa and the Red Sea to Samoa, north to Okinawa, Japan. Sphagebranchus huysmani Weber 1913 and Muraenichthys fowleri Schultz 1943 are synonymized under S. gymnota.     

Electron self-exchange and self-amplified posttranslational modification in the hemoglobins from <Emphasis Type="Italic">Synechocystis</Emphasis> sp. PCC 6803 and <Emphasis Type="Italic">Synechococcus</Emphasis> sp. PCC 7002

Many heme proteins undergo covalent attachment of the heme group to a protein side chain. Such posttranslational modifications alter the thermodynamic and chemical properties of the holoprotein. Their importance in biological processes makes them attractive targets for mechanistic studies. We have proposed a reductively driven mechanism for the covalent heme attachment in the monomeric hemoglobins produced by the cyanobacteria Synechococcus sp. PCC 7002 and Synechocystis sp. PCC 6803 (GlbN) (Nothnagel et al. in J Biol Inorg Chem 16:539–552, 2011). These GlbNs coordinate the heme iron with two axial histidines, a feature that distinguishes them from most hemoglobins and conditions their redox properties. Here, we uncovered evidence for an electron exchange chain reaction leading to complete heme modification upon substoichiometric reduction of GlbN prepared in the ferric state. The GlbN electron self-exchange rate constants measured by NMR spectroscopy were on the order of 10²–10³ M⁻¹ s⁻¹ and were consistent with the proposed autocatalytic process. NMR data on ferrous and ferric Synechococcus GlbN in solution indicated little dependence of the structure on the redox state of the iron or cross-link status of the heme group. This allowed the determination of lower bounds to the cross-exchange rate constants according to Marcus theory. The observations illustrate the ability of bishistidine hemoglobins to undergo facile interprotein electron transfer and the chemical relevance of such transfer for covalent heme attachment.     

Karyopherin binding interactions and nuclear import mechanism of nuclear pore complex protein Tpr

Background  

Tpr is a large protein with an extended coiled-coil domain that is localized within the nuclear basket of the nuclear pore complex. Previous studies [1] involving antibody microinjection into mammalian cells suggested a role for Tpr in nuclear export of proteins via the CRM1 export receptor. In addition, Tpr was found to co-immunoprecipitate with importins α and β from Xenopus laevis egg extracts [2], although the function of this is unresolved. Yeast Mlp1p and Mlp2p, which are homologous to vertebrate Tpr, have been implicated in mRNA surveillance to retain unspliced mRNAs in the nucleus[3, 4]. To augment an understanding of the role of Tpr in nucleocytoplasmic trafficking, we explored the interactions of recombinant Tpr with the karyopherins CRM1, importin β and importin α by solid phase binding assays. We also investigated the conditions required for nuclear import of Tpr using an in vitro assay.     

Use of weighted reference panels based on empirical estimates of ancestry for capturing untyped variation

Many association methods use a subset of genotyped single nucleotide polymorphisms (SNPs) to capture or infer genotypes at other untyped SNPs. We and others previously showed that tag SNPs selected to capture common variation using data from The International HapMap Consortium (Nature 437:1299–1320, 2005), The International HapMap Consortium (Nature 449:851–861, 2007) could also capture variation in populations of similar ancestry to HapMap reference populations (de Bakker et al. in Nat Genet 38:1298–1303, 2006; González-Neira et al. in Genome Res 16:323–330, 2006; Montpetit et al. in PLoS Genet 2:282–290, 2006; Mueller et al. in Am J Hum Genet 76:387–398, 2005). To capture variation in admixed populations or populations less similar to HapMap panels, a “cosmopolitan approach,” in which all samples from HapMap are used as a single reference panel, was proposed. Here we refine this suggestion and show that use of a “weighted reference panel,” constructed based on empirical estimates of ancestry in the target population (relative to available reference panels), is more efficient than the cosmopolitan approach. Weighted reference panels capture, on average, only slightly fewer common variants (minor allele frequency > 5%) than the cosmopolitan approach (mean r ² = 0.977 vs. 0.989, 94.5% variation captured vs. 96.8% at r ² > 0.8), across the five populations of the Multiethnic Cohort, but entail approximately 25% fewer tag SNPs per panel (average 538 vs. 718). These results extend a recent study in two Indian populations (Pemberton et al. in Ann Hum Genet 72:535–546, 2008). Weighted reference panels are potentially useful for both the selection of tag SNPs in diverse populations and perhaps in the design of reference panels for imputation of untyped genotypes in genome-wide association studies in admixed populations. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Rhythmic Oscillations in Quantitative EEG Measured During a Continuous Performance Task

The objective of the present investigation was to determine if cyclic variations in human performance recorded during a 30 min continuous performance task would parallel cyclic variations in right-hemisphere beta-wave activity. A fast fourier transformation was performed on the quantitative electroencephalogram (qEEG) and the performance record of each participant (N = 62), producing an individual periodogram for each outcome measure. An average periodogram was then produced for both qEEG and performance by combining (averaging) the amplitudes associated with each periodicity in the 62 original periodograms. Periodicities ranging from 1.00 to 2.00 min and from 4.70 to 5.70 min with amplitudes greater than would be expected due to chance were retained (Smith et al. 2003). The results of the present investigation validate the existence of cyclic variations in human performance that have been identified previously (Smith et al. 2003) and extend those findings by implicating right-hemisphere mediated arousal in the process (Arruda et al. 1996, 1999, 2007). Significant cyclic variations in left-hemisphere beta-wave activity were not observed. Taken together, the findings of the present investigation support a model of sustained attention that predicts cyclic changes in human performance that are the result of cyclic changes in right-hemisphere arousal.

Measuring Fit of Sequence Data to Phylogenetic Model: Gain of Power Using Marginal Tests

Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197–200, 1982) to the present. We compare the general log-likelihood ratio (the G or G ² statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P ~ 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4 ^t patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P ≪ 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.