The evolution of function: a new method to assess the phylogenetic value of ribosomal sensitivity to antibiotics.

Thirty-five archaeal, bacterial and eukaryotic translational systems have been proved against forty different protein synthesis inhibitors with diverse domain and functional specificities. The inhibition curves generated in every ribosome-antibiotic combination had previously shown interesting similarities among organisms belonging to the same phylogenetic group. This opened the possibility of using such functional information for developing evolutionary studies. A new mathematical method based on the main data components analysis has been developed to extract most of the information contained in the inhibition curves. The phenograms obtained closely resemble those generated by the small ribosomal subunit rRNA sequence comparison and such functional clustering is also congruent when a particular subset of organisms and/or antibiotics is used. These results prove the phylogenetic value of our functional analysis and suggest that the ribosome represents an interesting intersection between genotypic and phenotypic (functional) information stored in organisms.     

The use of functional analysis of the ribosome as a tool to determine archaebacterial phylogeny

Forty different antibiotics with diverse kingdom and functional specificities were used to measure the functional characteristics of the archaebacterial translation apparatus. The resulting inhibitory curves, which are characteristic of the cell-free system analyzed, were transformed into quantitative values that were used to cluster the different archaebacteria analyzed. This cluster resembles the phylogenetic tree generated by 16S rRNA sequence comparisons. These results strongly suggest that functional analysis of an appropriate evolutionary clock, such as the ribosome, is of intrinsic phylogenetic value. More importantly, they indicate that the study of the nexus between genotypic and phenotypic (functional) information may shed considerable light on the evolution of the protein synthetic machinery.     

Deriving phylogenetic trees from the similarity analysis of metabolic pathways

MOTIVATION: Comparative analysis of metabolic pathways in different genomes can give insights into the understanding of evolutionary and organizational relationships among species. This type of analysis allows one to measure the evolution of complete processes (with different functional roles) rather than the individual elements of a conventional analysis. We present a new technique for the phylogenetic analysis of metabolic pathways based on the topology of the underlying graphs. A distance measure between graphs is defined using the similarity between nodes of the graphs and the structural relationship between them. This distance measure is applied to the enzyme-enzyme relational graphs derived from metabolic pathways. Using this approach, pathways and group of pathways of different organisms are compared to each other and the resulting distance matrix is used to obtain a phylogenetic tree. RESULTS: We apply the method to the Citric Acid Cycle and the Glycolysis pathways of different groups of organisms, as well as to the Carbohydrate metabolic networks. Phylogenetic trees obtained from the experiments were close to existing phylogenies and revealed interesting relationships among organisms.     

Phylogenetic comparison of metabolic capacities of organisms at genome level

Horizontal gene transfer (HGT) has been shown to widely spread in organisms by comparative genomic studies. However, its effect on the phylogenetic relationship of organisms, especially at a system level of different cellular functions, is still not well understood. In this work, we have constructed phylogenetic trees based on the enzyme, reaction, and gene contents of metabolic networks reconstructed from annotated genome information of 82 sequenced organisms. Results from different phylogenetic distance definitions and based on three different functional subsystems (i.e., metabolism, cellular processes, information storage and processing) were compared. Results based on the three different functional subsystems give different pictures on the phylogenetic relationship of organisms, reflecting the different extents of HGT in the different functional systems. In general, horizontal transfer is prevailing in genes for metabolism, but less in genes for information processing. Nevertheless, the major results of metabolic network-based phylogenetic trees are in good agreement with the tree based on 16S rRNA and genome trees, confirming the three domain classification and the close relationship between eukaryotes and archaea at the level of metabolic networks. These results strongly support the hypothesis that although HGT is widely distributed, it is nevertheless constrained by certain pre-existing metabolic organization principle(s) during the evolution. Further research is needed to identify the organization principle and constraints of metabolic network on HGT which have large impacts on understanding the evolution of life and in purposefully manipulating cellular metabolism.     

An overview of data models for the analysis of biochemical pathways

Biochemical pathways such as metabolic, regulatory or signal transduction pathways can be viewed as interconnected processes forming an intricate network of functional and physical interactions between molecular species in the cell. The amount of information available on such pathways for different organisms is increasing very rapidly. This is offering the possibility of performing various analyses on the structure of the full network of pathways for one organism as well as across different organisms, and has therefore generated interest in developing databases for storing and managing this information. Analysing these networks remains far from straightforward owing to the nature of the databases, which are often heterogeneous, incomplete or inconsistent. Pathway analysis is hence a challenging problem in systems biology and in bioinformatics. Various forms of data models have been devised for the analysis of biochemical pathways. This paper presents an overview of the types of models used for this purpose, concentrating on those concerned with the structural aspects of biochemical networks. In particular, the different types of data models found in the literature are classified using a unified framework. In addition, how these models have been used in the analysis of biochemical networks is described. This enables us to underline the strengths and weaknesses of the different approaches, as well as to highlight relevant future research directions.     

The vertebrate limb: a model system to study the Hox/HOM gene network during development and evolution.

The potential of the vertebrate limb as a model system to study developmental mechanisms is particularly well illustrated by the analysis of the Hox gene network. These genes are probably involved in the establishment of patterns encoding positional information. Their functional organisation during both limb and trunk development are very similar and seem to involve the progressive activation in time, along the chromosome, of a battery of genes whose products could differentially instruct those cells where they are expressed. This process may be common to all organisms that develop according to an anterior-posterior morphogenetic progression. The possible linkage of this system to a particular mechanism of segmentation as well as its phylogenetic implications are discussed.     

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks

Background  

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees.     

Evolution of metabolisms: a new method for the comparison of metabolic pathways using genomics information.

The abundance of information provided by completely sequenced genomes defines a starting point for new insights in the multilevel organization of organisms and their evolution. At the lowest level enzymes and other protein complexes are formed by aggregating multiple polypeptides. At a higher level enzymes group conceptually into metabolic pathways as part of a dynamic information-processing system, and substrates are processed by enzymes yielding other substrates. A method based on a combination of sequence information with graph topology of the underlying pathway is presented. With this approach pathways of different organisms are related to each other by phylogenetic analysis, extending conventional phylogenetic analysis of individual enzymes. The new method is applied to pathways related to electron transfer and to the Krebs citric acid cycle. In addition to providing a more comprehensive understanding of similarities and differences between organisms, this method indicates different evolutionary rates between substrates and enzymes.     

Expansion of genome coding regions by acquisition of new genes

As it is the case for non-coding regions, the coding regions of organisms can be expanded or shrunk during evolutionary processes. However, the dynamics of coding regions are expected to be more correlated with functional complexity and diversity than are the dynamics of non-coding regions. Hence, it is interesting to investigate the increase of diversity in coding regions – the origin and evolution of new genes – because this provides a new component to the genetic variation underlying the diversity of living organisms. Here, we examine what is known about the mechanisms responsible for the increase in gene number. Every mechanism affects genomes in a distinct way and to a different extent and it appears that certain organisms favor particular mechanisms. The detail of some interesting gene acquisitions reveals the extreme dynamism of genomes. Finally, we discuss what is known about the fate of new genes and conclude that many of the acquisitions are likely to have been driven by natural selection; they increase functional complexity, diversity, and/or adaptation of species. Despite this, the correlation between complexity of life and gene number is low and closely related species (with very similar life histories) can have very different number of genes. We call this phenomenon the G-value paradox.     

Compilation and analysis of intein sequences.

We have compiled a list of all the inteins (protein splicing elements) whose sequences have been published or were available from on-line sequence databases as of September 18, 1996. Analysis of the 36 available intein sequences refines the previously described intein motifs and reveals the presence of another intein motif, Block H. Furthermore, analysis of the new inteins reshapes our view of the conserved splice junction residues, since three inteins lack the intein penultimate His seen in prior examples. Comparison of intein sequences suggests that, in general, (i) inteins present in the same location within extein homologs from different organisms are very closely related to each other in paired sequence comparison or phylogenetic analysis and we suggest that they should be considered intein alleles; (ii) multiple inteins present in the same gene are no more similar to each other than to inteins present in different genes; (iii) phylogenetic analysis indicates that inteins are so divergent that trees with statistically significant branches cannot be generated except for intein alleles.     

The FGGY carbohydrate kinase family: insights into the evolution of functional specificities

Function diversification in large protein families is a major mechanism driving expansion of cellular networks, providing organisms with new metabolic capabilities and thus adding to their evolutionary success. However, our understanding of the evolutionary mechanisms of functional diversity in such families is very limited, which, among many other reasons, is due to the lack of functionally well-characterized sets of proteins. Here, using the FGGY carbohydrate kinase family as an example, we built a confidently annotated reference set (CARS) of proteins by propagating experimentally verified functional assignments to a limited number of homologous proteins that are supported by their genomic and functional contexts. Then, we analyzed, on both the phylogenetic and the molecular levels, the evolution of different functional specificities in this family. The results show that the different functions (substrate specificities) encoded by FGGY kinases have emerged only once in the evolutionary history following an apparently simple divergent evolutionary model. At the same time, on the molecular level, one isofunctional group (L-ribulokinase, AraB) evolved at least two independent solutions that employed distinct specificity-determining residues for the recognition of a same substrate (L-ribulose). Our analysis provides a detailed model of the evolution of the FGGY kinase family. It also shows that only combined molecular and phylogenetic approaches can help reconstruct a full picture of functional diversifications in such diverse families.     

Protein-SIP enables time-resolved analysis of the carbon flux in a sulfate-reducing,benzene-degrading microbial consortium

Benzene is a major contaminant in various environments, but the mechanisms behind its biodegradation under strictly anoxic conditions are not yet entirely clear. Here we analyzed a benzene-degrading, sulfate-reducing enrichment culture originating from a benzene-contaminated aquifer by a metagenome-based functional metaproteomic approach, using protein-based stable isotope probing (protein-SIP). The time-resolved, quantitative analysis of carbon fluxes within the community supplied with either ¹³C-labeled benzene or ¹³C-labeled carbonate yielded different functional groups of organisms, with their peptides showing specific time dependencies of ¹³C relative isotope abundance indicating different carbon utilization. Through a detailed analysis of the mass spectrometric (MS) data, it was possible to quantify the utilization of the initial carbon source and the metabolic intermediates. The functional groups were affiliated to Clostridiales, Deltaproteobacteria and Bacteroidetes/Chlorobi. The Clostridiales-related organisms were involved in benzene degradation, putatively by fermentation, and additionally used significant amounts of carbonate as a carbon source. The other groups of organisms were found to perform diverse functions, with Deltaproteobacteria degrading fermentation products and Bacteroidetes/Chlorobi being putative scavengers feeding on dead cells. A functional classification of identified proteins supported this allocation and gave further insights into the metabolic pathways and the interactions between the community members. This example shows how protein-SIP can be applied to obtain temporal and phylogenetic information about functional interdependencies within microbial communities.     

Pimarane diterpenes: Natural source,stereochemical configuration,and biological activity

Plants and fungi are seemingly inexhaustible sources of interesting natural products with remarkable structural and biological diversity. One of the most important groups is the terpenes, ubiquitous natural products that are generated by 2 now well‐established biosynthetic pathways: the older mevalonate and the more recently discovered 1‐deoxyxylulose‐5‐phosphate. Among the diterpenes, the pimarane diterpenes are a very representative subgroup with several and interesting biological activities resulting from different functional group modifications. In this review, we outline the method of their structure determination, mainly spectroscopic results, their absolute configuration, and structure‐activity relationships, were reported, as well as the mode of action for selected examples from plants, marine organisms, and fungi. The pimarane, isopimarane, and ent‐pimarane diterpenes covered in this review have a wide range of biological activities including antimicrobial, antifungal, antiviral, phytotoxic, phytoalexin, cytotoxicity, and antispasmodic and relaxant effects.     

What's in the mix: phylogenetic classification of metagenome sequence samples

Metagenomics is a novel field which deals with the sequencing and study of microbial organisms or viruses isolated directly from a particular environment. This has already provided a wealth of information and new insights for the inhabitants of various environmental niches. For a given sample, one would like to determine the phylogenetic provenance of the obtained fragments, the relative abundance of its different members, their metabolic capabilities, and the functional properties of the community as a whole. To this end, computational analyses are becoming increasingly indispensable tools. In this review, we focus on the problem of determining the phylogenetic identity of the sample fragments, a procedure known as 'binning'. This step is essential for the reconstruction of the metabolic capabilities of individual organisms or phylogenetic clades of a community, and the study of their interactions.     

Genome manipulation by homologous recombination in Drosophila.

By utilising a cell's recombinational machinery, researchers in many different model organisms have been able to perform gene targeting experiments in which specific sequence alterations are introduced into virtually any endogenous gene. Not only can functional knock-outs be generated by gene targeting, interesting alleles with mutations encoding specific amino acid replacements can also be made. A practical gene targeting method has only recently become available for Drosophila. This article reviews the Drosophila gene targeting method, with emphases placed on different approaches that are being used to generate different mutations.     

Analysis of the kinesin superfamily: insights into structure and function

Kinesin superfamily proteins (KIFs) are key players or 'hub' proteins in the intracellular transport system, which is essential for cellular function and morphology. The KIF superfamily is also the first large protein family in mammals whose constituents have been completely identified and confirmed both in silico and in vivo. Numerous studies have revealed the structures and functions of individual family members; however, the relationships between members or a perspective of the whole superfamily structure until recently remained elusive. Here, we present a comprehensive summary based on a large, systematic phylogenetic analysis of the kinesin superfamily. All available sequences in public databases, including genomic information from all model organisms, were analyzed to yield the most complete phylogenetic kinesin tree thus far, comprising 14 families. This comprehensive classification builds on the recently proposed standardized nomenclature for kinesins and allows systematic analysis of the structural and functional relationships within the kinesin superfamily.     

Quartet MaxCut: A fast algorithm for amalgamating quartet trees

Accurate phylogenetic reconstruction methods are inherently computationally heavy and therefore are limited to relatively small numbers of taxa. Supertree construction is the task of amalgamating small trees over partial sets into a big tree over the complete taxa set. The need for fast and accurate supertree methods has become crucial due to the enormous number of new genomic sequences generated by modern technology and the desire to use them for classification purposes. In particular, the Assembling the Tree of Life (ATOL) program aims at constructing the evolutionary history of all living organisms on Earth. When dealing with unrooted trees, a quartet - an unrooted tree over four taxa - is the most basic piece of phylogenetic information. Therefore, quartet amalgamation stands at the heart of any supertree problem as it concerns combining many minimal pieces of information into a single, coherent, and more comprehensive piece of information.We have devised an extremely fast algorithm for quartet amalgamation and implemented it in a very efficient code. The new code can handle over a hundred millions of quartet trees over several hundreds of taxa with very high accuracy.     

Phylogenetic Analysis of Metabolic Pathways

The information provided by completely sequenced genomes can yield insights into the multi-level organization of organisms and their evolution. At the lowest level of molecular organization individual enzymes are formed, often through assembly of multiple polypeptides. At a higher level, sets of enzymes group into metabolic networks. Much has been learned about the relationship of species from phylogenetic trees comparing individual enzymes. In this article we extend conventional phylogenetic analysis of individual enzymes in different organisms to the organisms' metabolic networks. For this purpose we suggest a method that combines sequence information with information about the underlying reaction networks. A distance between pathways is defined as incorporating distances between substrates and distances between corresponding enzymes. The new analysis is applied to electron-transfer and amino acid biosynthesis networks yielding a more comprehensive understanding of similarities and differences between organisms. Received: 14 August 2000 / Accepted: 4 January 2001     

Reconstructing evolutionary relationships from functional data: a consistent classification of organisms based on translation inhibition response

The last two decades have witnessed an unsurpassed effort aimed at reconstructing the history of life from the genetic information contained in extant organisms. The availability of many sequenced genomes has allowed the reconstruction of phylogenies from gene families and its comparison with traditional single-gene trees. However, the appearance of major discrepancies between both approaches questions whether horizontal gene transfer (HGT) has played a prominent role in shaping the topology of the Tree of Life. Recent attempts at solving this controversy and reaching a consensus tree combine molecular data with additional phylogenetic markers. Translation is a universal cellular function that involves a meaningful, highly conserved set of genes: both rRNA and r-protein operons have an undisputed phylogenetic value and rarely undergo HGT. Ribosomal function reflects the concerted expression of that genetic network and consequently yields information about the evolutionary paths followed by the organisms. Here we report on tree reconstruction using a measure of the performance of the ribosome: antibiotic sensitivity of protein synthesis. A large database has been used where 33 ribosomal systems belonging to the three major cellular lineages were probed against 38 protein synthesis inhibitors. Different definitions of distance between pairs of organisms have been explored, and the classical algorithm of bootstrap evaluation has been adapted to quantify the reliability of the reconstructions obtained. Our analysis returns a consistent phylogeny, where archaea are systematically affiliated to eukarya, in agreement with recent reconstructions which used information-processing systems. The integration of the information derived from relevant functional markers into current phylogenetic reconstructions might facilitate achieving a consensus Tree of Life.