ABSTRACT
Biodiversity is measured from various perspectives. One of them, functional diversity, quantifies the heterogeneity in species traits and roles in an ecosystem. One important aspect of species roles is their interactions with other species, i.e. their network role. We therefore investigate here functional diversity from the network perspective. Species differ in their network positions in a food web, having different interaction patterns. We developed a measure for quantifying the diversity in species interaction patterns in a food web. We examined the relationship between interaction diversity and several global network properties for 92 food webs. Our results showed that high interaction diversity occurs in sparsely connected and less cohesive food webs. High interaction diversity also occurred in food webs with more clusters and high network modularity. We also quantified several conventional functional diversity indices and demonstrate that they show little or no correlation with interaction diversity. Our proposed diversity index therefore provides a measure complementary to current concepts of functional diversity.
Subject(s)
Ecosystem , Food Chain , BiodiversityABSTRACT
Bet-hedging-a strategy that reduces fitness variance at the expense of lower mean fitness among different generations-is thought to evolve as a biological adaptation to environmental unpredictability. Despite widespread use of the bet-hedging concept, most theoretical treatments have largely made unrealistic demographic assumptions, such as non-overlapping generations and fixed or infinite population sizes. Here, we extend the concept to consider overlapping generations by defining bet-hedging as a strategy with lower variance and mean per capita growth rate across different environments. We also define an opposing strategy-the rising-tide-that has higher mean but also higher variance in per capita growth. These alternative strategies lie along a continuum of biological adaptions to environmental fluctuation. Using stochastic Lotka-Volterra models to explore the evolution of the rising-tide versus bet-hedging strategies, we show that both the mean environmental conditions and the temporal scales of their fluctuations, as well as whether population dynamics are discrete or continuous, are crucial in shaping the type of strategy that evolves in fluctuating environments. Our model demonstrates that there are likely to be a wide range of ways that organisms with overlapping generations respond to environmental unpredictability beyond the classic bet-hedging concept.
Subject(s)
Adaptation, Biological/physiology , Animals , Biological Evolution , Demography , Population Density , Population DynamicsABSTRACT
Surgical interventions on the alveolar ridges aimed at facilitating orthodontic tooth movement have been extensively reported. However, unexpected events or complications still occur in daily practice. The purpose of this report was to present a novel 3-dimensional (3D) computer-assisted piezocision guide (CAPG) designed to be translucent for increased visibility, rigid for enhanced support during guidance, and porous for profuse irrigation during procedure. Such a design can function to minimize the risk of surgical complications. In this case, we present a novel 3D-printed CAPG to facilitate a minimally invasive periodontal accelerated osteogenic orthodontics (PAOO) procedure with a guide that provides accuracy, adequate visibility, and greater access for the coolant to reach the surgery site. By navigating the cone-beam computed tomography data, we precisely know the cortical bone thickness, root direction, and interrelations between anatomic structures in an individual situation, which allows us to design our cutting slot for the required length and depth according to the operator's knowledge. Finally, 3D printing was applied, transferring our surgical plan to fabricate the CAPG. Moreover, the well designed pores on the CAPG allow effective irrigation during the piezocision procedure. This minimally invasive procedure was uneventful, and no devitalized tooth or alveolar bone was found.
Subject(s)
Orthognathic Surgical Procedures/methods , Piezosurgery/methods , Printing, Three-Dimensional , Alveolar Process/surgery , Female , Humans , Malocclusion, Angle Class I/surgery , Middle Aged , Orthodontics, Corrective/methodsABSTRACT
The climatic variability hypothesis posits that the magnitude of climatic variability increases with latitude, elevation, or both, and that greater variability selects for organisms with broader temperature tolerances, enabling them to be geographically widespread. We tested this classical hypothesis for the elevational range sizes of more than 16,500 terrestrial vertebrates on 180 montane gradients. In support of the hypothesis, mean elevational range size was positively correlated with the scope of seasonal temperature variation, whereas elevational range size was negatively correlated with daily temperature variation among gradients. In accordance with a previous life history model and our extended versions of it, our findings indicate that physiological specialization may be favored under shorter-term climatic variability.
Subject(s)
Climate , Global Warming , Seasons , Temperature , Vertebrates/physiology , AnimalsABSTRACT
BACKGROUND: Microbial interactions are ubiquitous in nature. Recently, many similarity-based approaches have been developed to study the interaction in microbial ecosystems. These approaches can only explain the non-directional interactions yet a more complete view on how microbes regulate each other remains elusive. In addition, the strength of microbial interactions is difficult to be quantified by only using correlation analysis. RESULTS: In this study, a rule-based microbial network (RMN) algorithm, which integrates regulatory OTU-triplet model with parametric weighting function, is being developed to construct microbial regulatory networks. The RMN algorithm not only can extrapolate the cooperative and competitive relationships between microbes, but also can infer the direction of such interactions. In addition, RMN algorithm can theoretically characterize the regulatory relationship composed of microbial pairs with low correlation coefficient in microbial networks. Our results suggested that Bifidobacterium, Streptococcus, Clostridium XI, and Bacteroides are essential for causing abundance changes of Veillonella in gut microbiome. Furthermore, we inferred some possible microbial interactions, including the competitive relationship between Veillonella and Bacteroides, and the cooperative relationship between Veillonella and Clostridium XI. CONCLUSIONS: The RMN algorithm provides the reconstruction of gut microbe networks, and can shed light on the dynamical interactions of microbes in the infant intestinal tract.
Subject(s)
Algorithms , Computational Biology/methods , Gastrointestinal Microbiome , Microbial Interactions , Humans , Infant , Models, Biological , RNA, Ribosomal, 16S/geneticsABSTRACT
The impact of social influence causes people to adopt the behaviour of others when interacting with other individuals. The effects of social influence can be direct or indirect. Direct social influence is the result of an individual directly influencing the opinion of another, while indirect social influence is a process taking place when an individual's opinion and behaviour is affected by the availability of information about others' actions. Such indirect effect may exhibit a more significant impact in the on-line community because the internet records not only positive but also negative information, for example on-line written text comments. This study focuses on indirect social influence and examines the effect of preceding information on subsequent users' opinions by fitting statistical models to data collected from an on-line bulletin board. Specifically, the different impacts of information on approval and disapproval comments on subsequent opinions were investigated. Although in an anonymous situation where social influence is assumed to be at minimum, our results demonstrate the tendency of on-line users to adopt both positive and negative information to conform to the neighbouring trend when expressing opinions. Moreover, our results suggest unequal effects of the local approval and disapproval comments in affecting the likelihood of expressing opinions. The impact of neighbouring disapproval densities was stronger than that of neighbouring approval densities on inducing subsequent disapproval relative to approval comments. However, our results suggest no effects of global social influence on subsequent opinion expression.
Subject(s)
Internet , Social Behavior , Humans , Models, Statistical , TaiwanABSTRACT
To assess the role of human disturbances in species' extinction requires an understanding of the species population history before human impact. The passenger pigeon was once the most abundant bird in the world, with a population size estimated at 3-5 billion in the 1800s; its abrupt extinction in 1914 raises the question of how such an abundant bird could have been driven to extinction in mere decades. Although human exploitation is often blamed, the role of natural population dynamics in the passenger pigeon's extinction remains unexplored. Applying high-throughput sequencing technologies to obtain sequences from most of the genome, we calculated that the passenger pigeon's effective population size throughout the last million years was persistently about 1/10,000 of the 1800's estimated number of individuals, a ratio 1,000-times lower than typically found. This result suggests that the passenger pigeon was not always super abundant but experienced dramatic population fluctuations, resembling those of an "outbreak" species. Ecological niche models supported inference of drastic changes in the extent of its breeding range over the last glacial-interglacial cycle. An estimate of acorn-based carrying capacity during the past 21,000 y showed great year-to-year variations. Based on our results, we hypothesize that ecological conditions that dramatically reduced population size under natural conditions could have interacted with human exploitation in causing the passenger pigeon's rapid demise. Our study illustrates that even species as abundant as the passenger pigeon can be vulnerable to human threats if they are subject to dramatic population fluctuations, and provides a new perspective on the greatest human-caused extinction in recorded history.
Subject(s)
Columbidae/physiology , Extinction, Biological , Animals , Chromosome Mapping , Food Supply , Genome/genetics , Geography , Markov Chains , Population Density , Population Dynamics , Quercus/physiology , United StatesABSTRACT
BACKGROUND: A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. RESULTS: We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. CONCLUSIONS: A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.
Subject(s)
Enzymes/metabolism , Systems Biology/methods , Chemotaxis , Escherichia coli/cytology , Escherichia coli/enzymology , Kinetics , Models, BiologicalABSTRACT
Numerous materials have been proposed for bone tissue engineering. In this study, a newly designed hybrid composite scaffold composed of poly (D,L-lactide-co-glycolide) and a naturally bioceramic hybrid material, nanonized pearl powder, were prepared and the biological activities and physical properties of the scaffold for bone tissue engineering were evaluated. It is a composite consisting calcium carbonate crystal in an aragonite structure, embedded in an organic matrix. Peral contains one or more signal molecules capable of stimulating bone formation. The nanonized pearl powder is considered as a promising osteoinductive biomaterial. This biomaterial is biocompatible and shows osteogenic activity. In this study, the designed biohybrid of nanonized pearl powder/poly (lactide-co-glycolide) (NPP/PLGA) biocomposite scaffolds would employ biodegradable material as MC3T3-E1 cells seeded scaffolds. Therefore, the biocomposite scaffolds would be used to culture with MC3T3-E1 cells under spinner bioreactor in vitro. Furthermore, it also detailed how these tissues were characterized, qualitatively and quantitatively, with scanning electron microscopy and biochemical testing. The identity and the mode of action of these molecules on the osteoblast differentiation were analyzed. This study indicates that the efficiency of nanonized pearl powders in bone cell differentiation are certainly different from that of proteins. Further sudy will look forward to manufacturing the promising new generation bone substitute, three dimensional biocomposite scaffolds to replace the implant and autogeneous bone graft, which combines basic research and clinical application.
Subject(s)
Biocompatible Materials/chemistry , Osteogenesis , Polyglactin 910/chemistry , Tissue Engineering , Tissue Scaffolds/chemistry , 3T3 Cells , Animals , Bioreactors , Bone Regeneration , Calcium Carbonate/chemistry , Cell Differentiation , Collagen Type I/chemistry , Lactic Acid/chemistry , Mice , Microscopy, Electron, Scanning , Nanoparticles/chemistry , Osteoblasts/cytology , Osteoblasts/metabolism , Osteocalcin/chemistry , Osteopontin/chemistry , Polyglycolic Acid/chemistry , Polylactic Acid-Polyglycolic Acid Copolymer , PowdersABSTRACT
This study was designed to assess how bicyclists (30 men, 30 women) responded to right-turning motorised vehicles, which is a risky situation for bicyclists, and employed a scenario in which a motorcycle made a right turn in front of a bicyclist. The factors of speed difference and cut-in time gap were generated to objectively investigate steering control, speed, and the associated collisions in a bicycle simulator. There was no effect for sex, but as expected, for shorter cut-in time gaps, the steering angles were smaller (deflected to the right to avoid the passing motorcycle), the speeds were lower, and the variations in the steering angle and speed were larger. Variations in the steering angle and speed were unexpectedly lower for larger speed differences than for smaller speed differences. Response patterns comprised 5 patterns: early response and quickly depress the brake, last-moment response and slowly depress the brake, late response and quickly depress the brake, very late response and quickly depress the brake, and no response. Larger speed differences and the no-response pattern resulted in two collisions. Individuals with less experience may not have associated speed differences with potential dangers.
Subject(s)
Bicycling/psychology , Computer Simulation , Motorcycles , Psychomotor Performance , Accidents, Traffic/psychology , Adult , Analysis of Variance , Female , Humans , Male , Reaction Time , Students/psychology , Young AdultABSTRACT
In order to better understand several cellular processes, it is helpful to study how various components make up the system. This systems perspective is supported by several modelling tools including network analysis. Networks of protein-protein interactions (PPI networks) offer a way to depict, visualize and quantify the functioning and relative importance of particular proteins in cell function. The toolkit of network analysis ranges from the local indices describing individual proteins (as network nodes) to global indicators of system architecture, describing the total interaction system (as the whole network). We briefly introduce some of these network indices and present a case study where the connectedness and potential functional relationships between certain disease proteins are inferred. We argue that network analysis can be used, in general, to improve databases, to infer novel functions, to quantify positional importance and to support predictions in pathogenesis studies. The systems perspective and network analysis can be of particular importance in studying diseases with complex molecular processes.
Subject(s)
Protein Interaction Maps , Animals , Computational Biology , Disease , HumansABSTRACT
Identifying important species for maintaining ecosystem functions is a challenge in ecology. Since species are components of food webs, one way to conceptualize and quantify species importance is from a network perspective. The importance of a species can be quantified by measuring the centrality of its position in a food web, because a central node may have greater influence on others in the network. A species may also be important because it has a unique network position, such that its loss cannot be easily compensated. Therefore, for a food web to be robust, we hypothesize that central species must be functionally redundant in terms of their network position. In this paper, we test our hypothesis by analysing the Prince William Sound ecosystem. We found that species centrality and uniqueness are negatively correlated, and such an observation is also carried over to other food webs.
Subject(s)
Biota , Ecology/methods , Food Chain , Animals , Models, Biological , Population Dynamics , Predatory Behavior , Species Specificity , Statistics, NonparametricABSTRACT
BACKGROUND: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the ones connecting heart disease and obesity. RESULTS: We quantified their overlap, and based on the identified topological patterns, we inferred the structural disease-relatedness of several proteins. Literature data provide a functional look of them, well supporting our findings. For example, the inferred structurally important role of the PDZ domain-containing protein GIPC1 in diabetes is supported despite the lack of this information in the Online Mendelian Inheritance in Man database. Several key mediator proteins identified here clearly has pleiotropic effects, supported by ample evidence for their general but always of only secondary importance. CONCLUSIONS: We suggest that studying central nodes in mediator networks may contribute to better understanding and quantifying pleiotropy. Network analysis provides potentially useful tools here, as well as helps in improving databases.
Subject(s)
Diabetes Mellitus/genetics , Genetic Pleiotropy , Heart Diseases/genetics , Protein Interaction Maps , Diabetes Mellitus/metabolism , Heart Diseases/metabolism , HumansABSTRACT
A robust food web is one which suffers few secondary extinctions after primary species losses. While recent research has shown that a food web with parasitism is less robust than one without, it still remains unclear whether the reduction in robustness is due to changes in network complexity or unique characteristics associated with parasitism. Here, using several published food webs, simulation experiments with different food web models and extinction scenarios were conducted to elucidate how such reduction can be achieved. Our results show that, regardless of changes in network complexity and preferential parasitism, the reduction in food web robustness is mainly due to the life cycle constraint of parasites. Our findings further demonstrate that parasites are prone to secondary extinctions and that their extinctions occur earlier than those involving free-living species. These findings suggest that the vulnerable nature of parasites to species loss makes them highly sensitive indicators of food web integrity.
Subject(s)
Extinction, Biological , Food Chain , Host-Parasite Interactions , Animals , Computer SimulationABSTRACT
Due to the structural complexity of nature, it is not always easy to identify topologically importance species in an ecosystem. In the past decade, several studies in ecology have developed methods for measuring species importance basing on direct and indirect inter-specific interactions. Here, by extending a previously developed methodology, we present an approach that can quantify the interaction structure of a food web and consequently the topological importance of species when the food web is viewed as a signed digraph. The basic principle behind our approach is to determine the sign and strength of direct and indirect interactions for all pathways up to a predefined number of steps. Our approach mainly differs from the previous methodology in that we are able to quantify the strength of inter-specific interaction as well as in what way species interact with each other, as it can explicitly quantify a wide range of ecological interactions such as cascading effect, indirect food supply effect, apparent and exploitive competitions in the same framework. This then allows us to quantify the topological importance of a species and examine whether it is a predominately positive or negative interactor in a food web. Furthermore, our analysis reveals that positive and negative effects from one species on others eventually cancel each other out for longer pathways resulting in stable interaction structure. Applications of our methodology include providing a more informative index for conservation biologists, and the potential use of interaction structure derived from our approach in food web robustness studies is also discussed.
Subject(s)
Food Chain , Models, Biological , Algorithms , Animals , Biomass , Cluster Analysis , Ecology/methods , Ecosystem , Oceans and Seas , TaiwanABSTRACT
INTRODUCTION: The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated. METHODS: First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F=E(b) function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC(36) can be calculated from a(t), and we use the injury probability P as a function of HIC(36,) as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results. RESULTS: Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions. CONCLUSION: Simulation results can be used to supplement insufficient real crash data, in particular DeltaV, and injury risk results from police crash reports. IMPACT ON INDUSTRY: The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.
Subject(s)
Health Care Costs/statistics & numerical data , Models, Statistical , Risk Assessment/statistics & numerical data , Wounds and Injuries/economics , Humans , TaiwanABSTRACT
BACKGROUND: Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. RESULTS: Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. CONCLUSION: Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene-encoded proteins are attached to the core at more peripheral positions of the networks.
Subject(s)
Computational Biology/methods , Gene Regulatory Networks/genetics , Protein Interaction Mapping , Proteins/genetics , Databases, Genetic , Gene Expression Profiling , Humans , Proteins/metabolismABSTRACT
This study aimed to evaluate the ability of the health food supplement Cordyceps sinensis (CS) to ameliorate suppressive effects of chemotherapy on bone marrow function as a model for cancer treatment. Mice were treated with Taxol (17 mg/kg body wt) one day before oral administration of a hot-water extract of CS (50 mg/kg daily) that was given daily for 3 weeks. White blood cell counts in peripheral blood of mice receiving Taxol were at 50% of normal levels on day 28 but had recovered completely in mice treated with CS. In vitro assays showed that CS enhanced the colony-forming ability of both granulocyte macrophage colony forming unit (GM-CFU) and osteogenic cells from bone marrow preparations and promoted the differentiation of bone marrow mesenchymal stromal cells into adipocytes, alkaline phosphatase-positive osteoblasts, and bone tissue. This result could be attributed to enhanced expression of Cbfa1 (core binding factor a) and BMP-2 (bone morphogenetic protein) with concurrent suppression of ODF (osteoclast differentiation factor/RANK [receptor activator of NF-kappaB]) ligand. In summary, CS enhances recovery of mice from leukopenia caused by Taxol treatment. It appears to do so by protecting both hematopoietic progenitor cells directly and the bone marrow stem cell niche through its effects on osteoblast differentiation.
Subject(s)
Antineoplastic Agents, Phytogenic/adverse effects , Cordyceps , Dietary Supplements , Leukopenia , Paclitaxel/adverse effects , Animals , Antineoplastic Agents, Phytogenic/therapeutic use , Bone Marrow Cells/cytology , Bone Marrow Cells/metabolism , Cell Differentiation , Cells, Cultured , Hematopoietic Stem Cells/cytology , Hematopoietic Stem Cells/physiology , Humans , Leukopenia/chemically induced , Leukopenia/drug therapy , Mesenchymal Stem Cells/cytology , Mesenchymal Stem Cells/physiology , Mice , Mice, Inbred C57BL , Neoplasms/drug therapy , Osteoclasts/physiology , Paclitaxel/therapeutic use , Stromal Cells/cytology , Stromal Cells/physiologyABSTRACT
Oscillatory gene expression plays an important role in somite segmentation during the early developmental stages of vertebrates. Recent experimental studies have shown that microRNA can regulate gene expression by stimulating degradation of mRNA and/or repression of translation. In this communication, we incorporate miRNA into a previous mathematical model of gene expression with delayed negative feedback and demonstrate how this modified model can elucidate the possible effect of miRNA on the oscillatory gene expression. Our finding suggests that miRNA maybe a destabilizing or stabilizing factor in the dynamics of gene expression depending on the severity of its effect on mRNA degradation. Our finding provides testable hypothesis for experimental biologists to further investigate miRNA's increasing functional roles in regulating cellular processes and development.
Subject(s)
Basic Helix-Loop-Helix Transcription Factors/genetics , Basic Helix-Loop-Helix Transcription Factors/physiology , Feedback, Physiological , Gene Expression Regulation , MicroRNAs/analysis , Animals , Gene Expression , Gene Expression Profiling , Mice , Models, Statistical , Models, Theoretical , Oscillometry , RNA, Messenger/metabolism , Time FactorsABSTRACT
BACKGROUND: A metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node; closeness centrality, which measures how close a node is to others; and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes. RESULTS: Enzyme phylogenetic profile correlates best with betweenness centrality and also quite closely with degree, but poorly with closeness centrality. Both betweenness and closeness centralities are non-local measures of topological importance and it is intriguing that they have contrasting power of predicting phylogenetic profile in bacterial species. We speculate that redundancy in an enzyme network may be reflected by betweenness centrality but not by closeness centrality. We also discuss factors influencing the correlation between phylogenetic profile and topological importance. CONCLUSION: Our analysis falsifies the hypothesis that phylogenetic profile of enzymes is independent of enzyme network importance. Our results show that phylogenetic profile correlates better with degree and betweenness centrality, but less so with closeness centrality. Enzymes that occur in many bacterial species tend to be those that have high network importance. We speculate that this phenomenon originates in mechanisms driving network evolution. Closeness centrality reflects phylogenetic profile poorly. This is because metabolic networks often consist of distinct functional modules and some are not in the centre of the network. Enzymes in these peripheral parts of a network might be important for cell survival and should therefore occur in many bacterial species. They are, however, distant from other enzymes in the same network.