Functional Phylogeny: the Use of the Sensitivity of Ribosomes to Protein Synthesis Inhibitors as a Tool to Study the Evolution of Organisms

In order to study the functional phylogeny of organisms, forty different protein synthesis inhibitors with diverse domain and funcional specificities have been used to analyze forty archaeal, bacterial and eukaryotic translational systems. The inhibition curves generated with the different ribosome-antibiotic pairs have shown very interesting similarities among organisms belonging to the same phylogenetic group, confirming the feasibility of using such information in the development of evolutionary studies. A new method to extract most of the information contained in the inhibition curves is presented. Using a statistical treatment based on the principal components analysis of the data, we have defined coordinates for the organisms which have allowed us to perform a functional clustering of them. The phenograms obtained are very similar to those generated by 16/18S rRNA sequence comparison. These results prove the phylogenetic value of our functional analysis and suggest an interesting intersection between genotypic and phenotypic (functional) information.     

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.     

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.     

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.     

Refined phylogenetic profiles method for predicting protein-protein interactions

MOTIVATION: The increasing availability of complete genome sequences provides excellent opportunity for the further development of tools for functional studies in proteomics. Several experimental approaches and in silico algorithms have been developed to cluster proteins into networks of biological significance that may provide new biological insights, especially into understanding the functions of many uncharacterized proteins. Among these methods, the phylogenetic profiles method has been widely used to predict protein-protein interactions. It involves the selection of reference organisms and identification of homologous proteins. Up to now, no published report has systematically studied the effects of the reference genome selection and the identification of homologous proteins upon the accuracy of this method. RESULTS: In this study, we optimized the phylogenetic profiles method by integrating phylogenetic relationships among reference organisms and sequence homology information to improve prediction accuracy. Our results revealed that the selection of the reference organisms set and the criteria for homology identification significantly are two critical factors for the prediction accuracy of this method. Our refined phylogenetic profiles method shows greater performance and potentially provides more reliable functional linkages compared with previous methods.     

Neurobiological constraints and fly systematics: how different types of neural characters can contribute to a higher level dipteran phylogeny

Much uncertainty still exists regarding higher level phylogenetic relationships in the insect order Diptera, and the need for independent analyses is apparent. In this paper, I present a parsimony analysis that is based on details of the nervous system of flies. Because neural characters have received little attention in modern phylogenetic analyses and the stability of neural traits has been debated, special emphasis is given to testing the robustness of the analysis itself and to evaluating how neurobiological constraints (such as levels of neural processing) influence the phylogenetic information content. The phylogenetic study is based on 14 species in three nematoceran and nine brachyceran families. All characters used in the analysis are based on anatomical details of the neural organization of the fly visual system. For the most part they relate to uniquely identifiable neurons, which are cells or cell types that can be confidently recognized as homologues among different species and thus compared. Parsimony analysis results in a phylogenetic hypothesis that favors specific previously suggested phylogenetic relationships and suggests alternatives regarding other placements. For example, several heterodactylan families (Bombyliidae, Asilidae, and Dolichopodidae) are supported in their placement as suggested by Sinclair et al. (1993), but Tipulidae and Syrphidae are placed differently. Tipulidae are placed at a derived rather than ancestral position within the Nematocera, and Syrphidae are placed within the Schizophora. The analysis suggests that neural characters generally maintain phylogenetic information well. However, by "forcing" neural characters onto conventional phylogenetic analyses it becomes apparent that not all neural centers maintain such information equally well. For example, neurons of the second-order visual neuropil, the medulla, contain stronger phylogenetic "signal" than do characters of the deeper visual center, the lobula plate. These differences may relate to different functional constraints in the two neuropils.     

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.     

From basepairs to birdsongs: phylogenetic data in the age of genomics

Given the quantity of molecular data now available, including complete genomes for some organisms, one can ask whether there is a need for any data beyond complete genomic sequences for phylogenetic analysis. One reason to look beyond the genome is that not all character information is encoded in organismal genomes. We propose a hierarchy of characters that ranges from biologically transmitted but nongenomically encoded characters, such as bird songs, to characters that are genomically encoded. All of these characters can retain historical information and are potentially useful for phylogenetic analysis. In addition, a number of phenotypic levels that are expressions of the genome can be identified. The question whether it is worth including any of these levels if all of the underlying sequence data have been collected arises, since issues of redundancy occur. Utilization of phenotypic levels that are ultimately based on sequences may facilitate reconstructing homologies that are not evident from sequence data alone. We propose the use of simultaneous analysis of sequence data and as many levels of phenotypic characters as possible to take advantage of homology information that may be more easily recovered from the latter. A method that eliminates redundancy to the degree that it can be detected is proposed.     

Phylogenetic fate mapping: theoretical and experimental studies applied to the development of mouse fibroblasts

Mutations are an inevitable consequence of cell division. Similarly to how DNA sequence differences allow inferring evolutionary relationships between organisms, we and others have recently demonstrated how somatic mutations may be exploited for phylogenetically reconstructing lineages of individual cells during development in multicellular organisms. However, a problem with such "phylogenetic fate maps" is that they cannot be verified experimentally; distinguishing actual lineages within clonal populations requires direct observation of cell growth, as was used to construct the fate map of Caenorhabditis elegans, but is not possible in higher organisms. Here we employ computer simulation of mitotic cell division to determine how factors such as the quantity of cells, mutation rate, and the number of examined marker sequences contribute to fidelity of phylogenetic fate maps and to explore statistical methods for assessing accuracy. To experimentally evaluate these factors, as well as for the purpose of investigating the developmental origins of connective tissue, we have produced a lineage map of fibroblasts harvested from various organs of an adult mouse. Statistical analysis demonstrates that the inferred relationships between cells in the phylogenetic fate map reflect biological information regarding the origin of fibroblasts and is suggestive of cell migration during mesenchymal development.     

Distinct Protein Classes in Human Red Cell Proteome Revealed by Similarity of Phylogenetic Profiles

The minimal set of proteins necessary to maintain a vertebrate cell forms an interesting core of cellular machinery. The known proteome of human red blood cell consists of about 1400 proteins. We treated this protein complement of one of the simplest human cells as a model and asked the questions on its function and origins. The proteome was mapped onto phylogenetic profiles, i.e. vectors of species possessing homologues of human proteins. A novel clustering approach was devised, utilising similarity in the phylogenetic spread of homologues as distance measure. The clustering based on phylogenetic profiles yielded several distinct protein classes differing in phylogenetic taxonomic spread, presumed evolutionary history and functional properties. Notably, small clusters of proteins common to vertebrates or Metazoa and other multicellular eukaryotes involve biological functions specific to multicellular organisms, such as apoptosis or cell-cell signaling, respectively. Also, a eukaryote-specific cluster is identified, featuring GTP-ase signalling and ubiquitination. Another cluster, made up of proteins found in most organisms, including bacteria and archaea, involves basic molecular functions such as oxidation-reduction and glycolysis. Approximately one third of erythrocyte proteins do not fall in any of the clusters, reflecting the complexity of protein evolution in comparison to our simple model. Basically, the clustering obtained divides the proteome into old and new parts, the former originating from bacterial ancestors, the latter from inventions within multicellular eukaryotes. Thus, the model human cell proteome appears to be made up of protein sets distinct in their history and biological roles. The current work shows that phylogenetic profiles concept allows protein clustering in a way relevant both to biological function and evolutionary history.     

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.     

Normalizing temporal patterns to analyze sit-to-stand movements by using registration of functional data

Functional data analysis techniques provide an alternative way of representing movement and movement variability as a function of time. In particular, the registration of functional data provides a local normalization of time functions. This normalization transforms a set of curves, records of repeated trials, yielding a new set of curves that only vary in terms of amplitude. Therefore, main events occur at the "same time" for all transformed curves and interesting features of individual recordings remain after averaging processes. This paper presents an application of the registration process to the analysis of the vertical forces exerted on the ground by both feet during the sit-to-stand movement. This movement is particularly interesting in functional evaluations related to balance control, lower extremity dysfunction or low-back pain.     

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.     

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.     

Phylogenetic divergence of fish and mammalian metallothionein: relationships with structural diversification and organismal temperature

Metallothioneins (MTs) are nonenzymatic low molecular weight proteins, that play an important role in the homeostasis and detoxification of heavy metals in a large variety of organisms. These proteins are endowed with striking features, including an unusual amino acid composition characterized by the presence of 20 cysteines out of a total of 60 residues and absence of secondary structure elements. It is generally accepted that MTs underwent few modifications during evolution because of these structural and functional constraints. Such a conclusion is founded on the studies carried out mostly on MTs of mammalian origin. For such a reason, we have decided to compare the MTs of homeothermic and poikilothermic organisms, such as mammals and fish, with the specific aim to put in relation phylogenetic divergence and structural/functional adaptation to temperature. We have included in our analysis also Antarctic Notothenioids, a fish group characterized by genetic isolation and cold-adaptation to a particular harsh environment. We have determined the average hydropathic index of ancestral MT sequences and used them to infer the temperatures of the environment housing the hypothetical ancestor organisms. Finally, we have derived phylogenetic relationships of MT molecules from the pairwise comparison of their three-dimensional structures.     

Carbonic anhydrase inhibitors

Carbonic anhydrases (CAs, EC 4.2.1.1) are widespread enzymes in all organisms, catalyzing CO₂ hydration to bicarbonate and protons. Their inhibition is exploited clinically for decades for various classes of diuretics and systemically acting antiglaucoma agents. In the last years novel applications of CA inhibitors (CAIs) emerged, such as topically acting antiglaucoma, anticonvulsants, antiobesity, antipain, and antitumor agents/diagnostic tools. Such CAIs target diverse isozymes of the 13 catalytically active α-CA isoforms present in mammals. CAs belonging to the α-, β-, γ-, δ-, and ζ-families are found in many organisms all over the phylogenetic tree, and their inhibition was studied ultimately for some pathogenic protozoa (Plasmodium falciparum), fungi (Cryptococcus neoformans, Candida albicans, Candida glabrata, and Saccharomyces cerevisiae), and bacteria (Helicobacter pylori, Mycobacterium tuberculosis, and Brucella suis). Novel interesting chemotypes, in addition to the sulfonamide and sulfamate CAIs, such as coumarins, phenols, and fullerenes, were also reported recently, together with their mechanism of inhibition. This class of enzyme inhibitors shows promise for designing interesting pharmacological agents and understanding in detail protein–drug interactions at molecular level.     

A tree kernel to analyse phylogenetic profiles

MOTIVATION: The phylogenetic profile of a protein is a string that encodes the presence or absence of the protein in every fully sequenced genome. Because proteins that participate in a common structural complex or metabolic pathway are likely to evolve in a correlated fashion, the phylogenetic profiles of such proteins are often 'similar' or at least 'related' to each other. The question we address in this paper is the following: how to measure the 'similarity' between two profiles, in an evolutionarily relevant way, in order to develop efficient function prediction methods? RESULTS: We show how the profiles can be mapped to a high-dimensional vector space which incorporates evolutionarily relevant information, and we provide an algorithm to compute efficiently the inner product in that space, which we call the tree kernel. The tree kernel can be used by any kernel-based analysis method for classification or data mining of phylogenetic profiles. As an application a Support Vector Machine (SVM) trained to predict the functional class of a gene from its phylogenetic profile is shown to perform better with the tree kernel than with a naive kernel that does not include any information about the phylogenetic relationships among species. Moreover a kernel principal component analysis (KPCA) of the phylogenetic profiles illustrates the sensitivity of the tree kernel to evolutionarily relevant variations.     

Rapid ribosomal RNA sequencing and the phylogenetic analysis of protists

A newly described technique for rapidly obtaining the partial nucleotide sequence of ribosomal RNA is being applied to investigate phylogenetic relationships among living organisms. Alan Johnson and Peter Boverstock describe the importance of this method to parasitology in providing new information on the phylogenetic relationships of parasitic organisms previously placed in groups of convenience. The phylum Apicomplexo in particular, has been the object of much study using this technique, but the technology is likely to extend soon to the restructuring of the phylogenetic trees of many groups of parasites.     

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.