Whole-proteome tree of life suggests a deep burst of organism diversity.

An organism tree of life (organism ToL) is a conceptual and metaphorical tree to capture a simplified narrative of the evolutionary course and kinship among the extant organisms. Such a tree cannot be experimentally validated but may be reconstructed based on characteristics associated with the organisms. Since the whole-genome sequence of an organism is, at present, the most comprehensive descriptor of the organism, a whole-genome sequence-based ToL can be an empirically derivable surrogate for the organism ToL. However, experimentally determining the whole-genome sequences of many diverse organisms was practically impossible until recently. We have constructed three types of ToLs for diversely sampled organisms using the sequences of whole genome, of whole transcriptome, and of whole proteome. Of the three, whole-proteome sequence-based ToL (whole-proteome ToL), constructed by applying information theory-based feature frequency profile method, an "alignment-free" method, gave the most topologically stable ToL. Here, we describe the main features of a whole-proteome ToL for 4,023 species with known complete or almost complete genome sequences on grouping and kinship among the groups at deep evolutionary levels. The ToL reveals 1) all extant organisms of this study can be grouped into 2 "Supergroups," 6 "Major Groups," or 35+ "Groups"; 2) the order of emergence of the "founders" of all of the groups may be assigned on an evolutionary progression scale; 3) all of the founders of the groups have emerged in a "deep burst" at the very beginning period near the root of the ToL-an explosive birth of life's diversity.

Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to cancer with a measure of probability. Of the triad of cancer-causing factors (inherited genomic susceptibility, environmental factors, and lifestyle factors), the inherited genomic component may be derivable from the recent public availability of a large body of whole-genome variation data. However, genome-wide association studies have so far showed limited success in predicting the inherited susceptibility to common cancers. We present here a multiple classification approach for predicting individuals' inherited genomic susceptibility to acquire the most likely phenotype among a panel of 20 major common cancer types plus 1 "healthy" type by application of a supervised machine-learning method under competing conditions among the cohorts of the 21 types. This approach suggests that, depending on the phenotypes of 5,919 individuals of "white" ethnic population in this study, (i) the portion of the cohort of a cancer type who acquired the observed type due to mostly inherited genomic susceptibility factors ranges from about 33 to 88% (or its corollary: the portion due to mostly environmental and lifestyle factors ranges from 12 to 67%), and (ii) on an individual level, the method also predicts individuals' inherited genomic susceptibility to acquire the other types ranked with associated probabilities. These probabilities may provide practical information for individuals, heath professionals, and health policymakers related to prevention and/or early intervention of cancer.

A genome Tree of Life for the Fungi kingdom.

Fungi belong to one of the largest and most diverse kingdoms of living organisms. The evolutionary kinship within a fungal population has so far been inferred mostly from the gene-information-based trees ("gene trees"), constructed commonly based on the degree of differences of proteins or DNA sequences of a small number of highly conserved genes common among the population by a multiple sequence alignment (MSA) method. Since each gene evolves under different evolutionary pressure and time scale, it has been known that one gene tree for a population may differ from other gene trees for the same population depending on the subjective selection of the genes. Within the last decade, a large number of whole-genome sequences of fungi have become publicly available, which represent, at present, the most fundamental and complete information about each fungal organism. This presents an opportunity to infer kinship among fungi using a whole-genome information-based tree ("genome tree"). The method we used allows comparison of whole-genome information without MSA, and is a variation of a computational algorithm developed to find semantic similarities or plagiarism in two books, where we represent whole-genomic information of an organism as a book of words without spaces. The genome tree reveals several significant and notable differences from the gene trees, and these differences invoke new discussions about alternative narratives for the evolution of some of the currently accepted fungal groups.

Empirical prediction of genomic susceptibilities for multiple cancer classes.

An empirical approach is presented for predicting the genomic susceptibility of an individual to the most likely one among nine traits, consisting of eight major cancer classes plus a healthy trait. We use four prediction methods by applying two supervised learning algorithms to two different descriptors of common genomic variations (the profiles of genotypes of SNPs and SNP syntaxes with low P values or low frequencies) of each individual genome from normal cells. All four methods made correct predictions substantially better than random predictions for most cancer classes, but not for some others. A combination of the four results using Bayesian inference better predicted overall than any individual method. The multiclass accuracy of the combined prediction ranges from 33% to 56% depending on cancer classes of testing sets, compared with 11% for a random prediction among nine traits. Despite limited SNP data available and the absence of rare SNPs in public databases, at present, the results suggest that the framework of this approach or its improvement can predict cancer susceptibility with probability estimates useful for making health decisions for individuals or for a population.

Inhibition of master transcription factors in pluripotent cells induces early stage differentiation.

The potential for pluripotent cells to differentiate into diverse specialized cell types has given much hope to the field of regenerative medicine. Nevertheless, the low efficiency of cell commitment has been a major bottleneck in this field. Here we provide a strategy to enhance the efficiency of early differentiation of pluripotent cells. We hypothesized that the initial phase of differentiation can be enhanced if the transcriptional activity of master regulators of stemness is suppressed, blocking the formation of functional transcriptomes. However, an obstacle is the lack of an efficient strategy to block protein-protein interactions. In this work, we take advantage of the biochemical property of seventeen kilodalton protein (Skp), a bacterial molecular chaperone that binds directly to sex determining region Y-box 2 (Sox2). The small angle X-ray scattering analyses provided a low resolution model of the complex and suggested that the transactivation domain of Sox2 is probably wrapped in a cleft on Skp trimer. Upon the transduction of Skp into pluripotent cells, the transcriptional activity of Sox2 was inhibited and the expression of Sox2 and octamer-binding transcription factor 4 was reduced, which resulted in the expression of early differentiation markers and appearance of early neuronal and cardiac progenitors. These results suggest that the initial stage of differentiation can be accelerated by inhibiting master transcription factors of stemness. This strategy can possibly be applied to increase the efficiency of stem cell differentiation into various cell types and also provides a clue to understanding the mechanism of early differentiation.

Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs).

A whole-genome phylogeny of the Escherichia coli/Shigella group was constructed by using the feature frequency profile (FFP) method. This alignment-free approach uses the frequencies of l-mer features of whole genomes to infer phylogenic distances. We present two phylogenies that accentuate different aspects of E. coli/Shigella genomic evolution: (i) one based on the compositions of all possible features of length l = 24 (∼8.4 million features), which are likely to reveal the phenetic grouping and relationship among the organisms and (ii) the other based on the compositions of core features with low frequency and low variability (∼0.56 million features), which account for ∼69% of all commonly shared features among 38 taxa examined and are likely to have genome-wide lineal evolutionary signal. Shigella appears as a single clade when all possible features are used without filtering of noncore features. However, results using core features show that Shigella consists of at least two distantly related subclades, implying that the subclades evolved into a single clade because of a high degree of convergence influenced by mobile genetic elements and niche adaptation. In both FFP trees, the basal group of the E. coli/Shigella phylogeny is the B2 phylogroup, which contains primarily uropathogenic strains, suggesting that the E. coli/Shigella ancestor was likely a facultative or opportunistic pathogen. The extant commensal strains diverged relatively late and appear to be the result of reductive evolution of genomes. We also identify clade distinguishing features and their associated genomic regions within each phylogroup. Such features may provide useful information for understanding evolution of the groups and for quick diagnostic identification of each phylogroup.

Cardiomyocytes from phorbol myristate acetate-activated mesenchymal stem cells restore electromechanical function in infarcted rat hearts.

Despite the safety and feasibility of mesenchymal stem cell (MSC) therapy, an optimal cell type has not yet emerged in terms of electromechanical integration in infarcted myocardium. We found that poor to moderate survival benefits of MSC-implanted rats were caused by incomplete electromechanical integration induced by tissue heterogeneity between myocytes and engrafted MSCs in the infarcted myocardium. Here, we report the development of cardiogenic cells from rat MSCs activated by phorbol myristate acetate, a PKC activator, that exhibited high expressions of cardiac-specific markers and Ca(2+) homeostasis-related proteins and showed adrenergic receptor signaling by norepinephrine. Histological analysis showed high connexin 43 coupling, few inflammatory cells, and low fibrotic markers in myocardium implanted with these phorbol myristate acetate-activated MSCs. Infarct hearts implanted with these cells exhibited restoration of conduction velocity through decreased tissue heterogeneity and improved myocardial contractility. These findings have major implications for the development of better cell types for electromechanical integration of cell-based treatment for infarcted myocardium.

Whole-proteome phylogeny of prokaryotes by feature frequency profiles: An alignment-free method with optimal feature resolution.

We present a whole-proteome phylogeny of prokaryotes constructed by comparing feature frequency profiles (FFPs) of whole proteomes. Features are l-mers of amino acids, and each organism is represented by a profile of frequencies of all features. The selection of feature length is critical in the FFP method, and we have developed a procedure for identifying the optimal feature lengths for inferring the phylogeny of prokaryotes, strictly speaking, a proteome phylogeny. Our FFP trees are constructed with whole proteomes of 884 prokaryotes, 16 unicellular eukaryotes, and 2 random sequences. To highlight the branching order of major groups, we present a simplified proteome FFP tree of monophyletic class or phylum with branch support. In our whole-proteome FFP trees (i) Archaea, Bacteria, Eukaryota, and a random sequence outgroup are clearly separated; (ii) Archaea and Bacteria form a sister group when rooted with random sequences; (iii) Planctomycetes, which possesses an intracellular membrane compartment, is placed at the basal position of the Bacteria domain; (iv) almost all groups are monophyletic in prokaryotes at most taxonomic levels, but many differences in the branching order of major groups are observed between our proteome FFP tree and trees built with other methods; and (v) previously "unclassified" genomes may be assigned to the most likely taxa. We describe notable similarities and differences between our FFP trees and those based on other methods in grouping and phylogeny of prokaryotes.

On whole-genome demography of world's ethnic groups and individual genomic identity.

All current categorizations of human population, such as ethnicity, ancestry and race, are based on various selections and combinations of complex and dynamic common characteristics, that are mostly societal and cultural in nature, perceived by the members within or from outside of the categorized group. During the last decade, a massive amount of a new type of characteristics, that are exclusively genomic in nature, became available that allows us to analyze the inherited whole-genome demographics of extant human, especially in the fields such as human genetics, health sciences and medical practices (e.g., 1,2,3), where such health-related characteristics can be related to whole-genome-based categorization. Here we show the feasibility of deriving such whole-genome-based categorization. We observe that, within the available genomic data at present, (a) the study populations form about 14 genomic groups, each consisting of multiple ethnic groups; and (b), at an individual level, approximately 99.8%, on average, of the whole autosomal-genome contents are identical between any two individuals regardless of their genomic or ethnic groups.

Alignment-free genome comparison with feature frequency profiles (FFP) and optimal resolutions.

For comparison of whole-genome (genic + nongenic) sequences, multiple sequence alignment of a few selected genes is not appropriate. One approach is to use an alignment-free method in which feature (or l-mer) frequency profiles (FFP) of whole genomes are used for comparison-a variation of a text or book comparison method, using word frequency profiles. In this approach it is critical to identify the optimal resolution range of l-mers for the given set of genomes compared. The optimum FFP method is applicable for comparing whole genomes or large genomic regions even when there are no common genes with high homology. We outline the method in 3 stages: (i) We first show how the optimal resolution range can be determined with English books which have been transformed into long character strings by removing all punctuation and spaces. (ii) Next, we test the robustness of the optimized FFP method at the nucleotide level, using a mutation model with a wide range of base substitutions and rearrangements. (iii) Finally, to illustrate the utility of the method, phylogenies are reconstructed from concatenated mammalian intronic genomes; the FFP derived intronic genome topologies for each l within the optimal range are all very similar. The topology agrees with the established mammalian phylogeny revealing that intron regions contain a similar level of phylogenic signal as do coding regions.

Whole-proteome phylogeny of large dsDNA virus families by an alignment-free method.

The vast sequence divergence among different virus groups has presented a great challenge to alignment-based sequence comparison among different virus families. Using an alignment-free comparison method, we construct the whole-proteome phylogeny for a population of viruses from 11 viral families comprising 142 large dsDNA eukaryote viruses. The method is based on the feature frequency profiles (FFP), where the length of the feature (l-mer) is selected to be optimal for phylogenomic inference. We observe that (i) the FFP phylogeny segregates the population into clades, the membership of each has remarkable agreement with current classification by the International Committee on the Taxonomy of Viruses, with one exception that the mimivirus joins the phycodnavirus family; (ii) the FFP tree detects potential evolutionary relationships among some viral families; (iii) the relative position of the 3 herpesvirus subfamilies in the FFP tree differs from gene alignment-based analysis; (iv) the FFP tree suggests the taxonomic positions of certain "unclassified" viruses; and (v) the FFP method identifies candidates for horizontal gene transfer between virus families.

Whole-genome phylogeny of mammals: evolutionary information in genic and nongenic regions.

Ten complete mammalian genome sequences were compared by using the "feature frequency profile" (FFP) method of alignment-free comparison. This comparison technique reveals that the whole nongenic portion of mammalian genomes contains evolutionary information that is similar to their genic counterparts--the intron and exon regions. We partitioned the complete genomes of mammals (such as human, chimp, horse, and mouse) into their constituent nongenic, intronic, and exonic components. Phylogenic species trees were constructed for each individual component class of genome sequence data as well as the whole genomes by using standard tree-building algorithms with FFP distances. The phylogenies of the whole genomes and each of the component classes (exonic, intronic, and nongenic regions) have similar topologies, within the optimal feature length range, and all agree well with the evolutionary phylogeny based on a recent large dataset, multispecies, and multigene-based alignment. In the strictest sense, the FFP-based trees are genome phylogenies, not species phylogenies. However, the species phylogeny is highly related to the whole-genome phylogeny. Furthermore, our results reveal that the footprints of evolutionary history are spread throughout the entire length of the whole genome of an organism and are not limited to genes, introns, or short, highly conserved, nongenic sequences that can be adversely affected by factors (such as a choice of sequences, homoplasy, and different mutation rates) resulting in inconsistent species phylogenies.

Protein production and purification.

In selecting a method to produce a recombinant protein, a researcher is faced with a bewildering array of choices as to where to start. To facilitate decision-making, we describe a consensus 'what to try first' strategy based on our collective analysis of the expression and purification of over 10,000 different proteins. This review presents methods that could be applied at the outset of any project, a prioritized list of alternate strategies and a list of pitfalls that trip many new investigators.

Capturing hammerhead ribozyme structures in action by modulating general base catalysis.

We have obtained precatalytic (enzyme-substrate complex) and postcatalytic (enzyme-product complex) crystal structures of an active full-length hammerhead RNA that cleaves in the crystal. Using the natural satellite tobacco ringspot virus hammerhead RNA sequence, the self-cleavage reaction was modulated by substituting the general base of the ribozyme, G12, with A12, a purine variant with a much lower pKa that does not significantly perturb the ribozyme's atomic structure. The active, but slowly cleaving, ribozyme thus permitted isolation of enzyme-substrate and enzyme-product complexes without modifying the nucleophile or leaving group of the cleavage reaction, nor any other aspect of the substrate. The predissociation enzyme-product complex structure reveals RNA and metal ion interactions potentially relevant to transition-state stabilization that are absent in precatalytic structures.

Chemicals that modulate stem cell differentiation.

Important cellular processes such as cell fate are likely to be controlled by an elaborate orchestration of multiple signaling pathways, many of which are still not well understood or known. Because protein kinases, the members of a large family of proteins involved in modulating many known signaling pathways, are likely to play important roles in balancing multiple signals to modulate cell fate, we focused our initial search for chemical reagents that regulate stem cell fate among known inhibitors of protein kinases. We have screened 41 characterized inhibitors of six major protein kinase subfamilies to alter the orchestration of multiple signaling pathways involved in differentiation of stem cells. We found that some of them cause recognizable changes in the differentiation rates of two types of stem cells, rat mesenchymal stem cells (MSCs) and mouse embryonic stem cells (ESCs). Among many, we describe the two most effective derivatives of the same scaffold compound, isoquinolinesulfonamide, on the stem cell differentiation: rat MSCs to chondrocytes and mouse ESCs to dopaminergic neurons.

Discovery of a selective inhibitor of oncogenic B-Raf kinase with potent antimelanoma activity.

BRAF(V600E) is the most frequent oncogenic protein kinase mutation known. Furthermore, inhibitors targeting "active" protein kinases have demonstrated significant utility in the therapeutic repertoire against cancer. Therefore, we pursued the development of specific kinase inhibitors targeting B-Raf, and the V600E allele in particular. By using a structure-guided discovery approach, a potent and selective inhibitor of active B-Raf has been discovered. PLX4720, a 7-azaindole derivative that inhibits B-Raf(V600E) with an IC(50) of 13 nM, defines a class of kinase inhibitor with marked selectivity in both biochemical and cellular assays. PLX4720 preferentially inhibits the active B-Raf(V600E) kinase compared with a broad spectrum of other kinases, and potent cytotoxic effects are also exclusive to cells bearing the V600E allele. Consistent with the high degree of selectivity, ERK phosphorylation is potently inhibited by PLX4720 in B-Raf(V600E)-bearing tumor cell lines but not in cells lacking oncogenic B-Raf. In melanoma models, PLX4720 induces cell cycle arrest and apoptosis exclusively in B-Raf(V600E)-positive cells. In B-Raf(V600E)-dependent tumor xenograft models, orally dosed PLX4720 causes significant tumor growth delays, including tumor regressions, without evidence of toxicity. The work described here represents the entire discovery process, from initial identification through structural and biological studies in animal models to a promising therapeutic for testing in cancer patients bearing B-Raf(V600E)-driven tumors.

Structure of human Brn-5 transcription factor in complex with CRH gene promoter.

The Brn-5 protein, highly expressed in human brain, belongs to the POU family; a class of transcription factors involved in a wide variety of biological processes ranging from programming of embryonic stem cells to cellular housekeeping. This functional diversity is conferred by two DNA-binding subdomains that can assume several configurations due to a bipartite arrangement of POU-specific (POU(S)) and POU-homeo (POU(H)) subdomains separated by a linker region. The crystal structure of human Brn-5 transcription factor in complex with corticotrophin-releasing hormone (CRH) gene promoter reveals an unexpected recognition mode of the protein to its cognate DNA. Moreover, the structure also shows the role of the linker in allowing diverse configurations that can be assumed by the two subdomains.

PDB Editor: a user-friendly Java-based Protein Data Bank file editor with a GUI.

The Protein Data Bank file format is the format most widely used by protein crystallographers and biologists to disseminate and manipulate protein structures. Despite this, there are few user-friendly software packages available to efficiently edit and extract raw information from PDB files. This limitation often leads to many protein crystallographers wasting significant time manually editing PDB files. PDB Editor, written in Java Swing GUI, allows the user to selectively search, select, extract and edit information in parallel. Furthermore, the program is a stand-alone application written in Java which frees users from the hassles associated with platform/operating system-dependent installation and usage. PDB Editor can be downloaded from http://sourceforge.net/projects/pdbeditorjl/.

High-throughput T7 LIC vector for introducing C-terminal poly-histidine tags with variable lengths without extra sequences.

Immobilized metal ion affinity chromatography (IMAC) has become one of the most popular protein purification methods for recombinant proteins with a hexa-histidine tag (His-tag) placed at the C- or N-terminus of proteins. Nevertheless, there are always difficult proteins that show weak binding to the metal chelating resin and thus low purity. These difficulties are often overcome by increasing the His-tag to 8 or 10 histidines. Despite their success, there are only few expression vectors available to easily clone and test different His-tag lengths. Therefore, we have modified Escherichia coli T7 expression vector pET21a to accommodate ligation-independent cloning (LIC) that will allow easy and efficient parallel cloning of target genes with different His-tag lengths using a single insert. Unlike most LIC vectors available commercially, our vectors will not translate unwanted extra sequences by engineering the N-terminal linker to anneal before the open reading frame, and the C-terminal linker to anneal as a His-tag.