Biomedical subjects

Sara Light

Publications and source records attributed to Sara Light.

5 recordsLinked to original sources

PubMed2007

Evolution after gene duplication: models, mechanisms, sequences, systems, and organisms.

Gene duplication is postulated to have played a major role in the evolution of biological novelty. Here, gene duplication is examined across levels of biological organization in an attempt to create a unified picture of the mechanistic process by which gene duplication can have played a role in generating biodiversity. Neofunctionalization and subfunctionalization have been proposed as important processes driving the retention of duplicate genes. These models have foundations in population genetic theory, which is now being refined by explicit consideration of the structural constraints placed upon genes encoding proteins through physical chemistry. Further, such models can be examined in the context of comparative genomics, where an integration of gene-level evolution and species-level evolution allows an assessment of the frequency of duplication and the fate of duplicate genes. This process, of course, is dependent upon the biochemical role that duplicated genes play in biological systems, which is in turn dependent upon the mechanism of duplication: whole genome duplication involving a co-duplication of interacting partners vs. single gene duplication. Lastly, the role that these processes may have played in driving speciation is examined.

Animals↗

PubMed2006

What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae?

BACKGROUND: Most proteins interact with only a few other proteins while a small number of proteins (hubs) have many interaction partners. Hub proteins and non-hub proteins differ in several respects; however, understanding is not complete about what properties characterize the hubs and set them apart from proteins of low connectivity. Therefore, we have investigated what differentiates hubs from non-hubs and static hubs (party hubs) from dynamic hubs (date hubs) in the protein-protein interaction network of Saccharomyces cerevisiae. RESULTS: The many interactions of hub proteins can only partly be explained by bindings to similar proteins or domains. It is evident that domain repeats, which are associated with binding, are enriched in hubs. Moreover, there is an over representation of multi-domain proteins and long proteins among the hubs. In addition, there are clear differences between party hubs and date hubs. Fewer of the party hubs contain long disordered regions compared to date hubs, indicating that these regions are important for flexible binding but less so for static interactions. Furthermore, party hubs interact to a large extent with each other, supporting the idea of party hubs as the cores of highly clustered functional modules. In addition, hub proteins, and in particular party hubs, are more often ancient. Finally, the more recent paralogs of party hubs are underrepresented. CONCLUSION: Our results indicate that multiple and repeated domains are enriched in hub proteins and, further, that long disordered regions, which are common in date hubs, are particularly important for flexible binding.

Binding Sites↗

PubMed2005

Preferential attachment in the evolution of metabolic networks.

BACKGROUND: Many biological networks show some characteristics of scale-free networks. Scale-free networks can evolve through preferential attachment where new nodes are preferentially attached to well connected nodes. In networks which have evolved through preferential attachment older nodes should have a higher average connectivity than younger nodes. Here we have investigated preferential attachment in the context of metabolic networks. RESULTS: The connectivities of the enzymes in the metabolic network of Escherichia coli were determined and representatives for these enzymes were located in 11 eukaryotes, 17 archaea and 46 bacteria. E. coli enzymes which have representatives in eukaryotes have a higher average connectivity while enzymes which are represented only in the prokaryotes, and especially the enzymes only present in betagamma-proteobacteria, have lower connectivities than expected by chance. Interestingly, the enzymes which have been proposed as candidates for horizontal gene transfer have a higher average connectivity than the other enzymes. Furthermore, It was found that new edges are added to the highly connected enzymes at a faster rate than to enzymes with low connectivities which is consistent with preferential attachment. CONCLUSION: Here, we have found indications of preferential attachment in the metabolic network of E. coli. A possible biological explanation for preferential attachment growth of metabolic networks is that novel enzymes created through gene duplication maintain some of the compounds involved in the original reaction, throughout its future evolution. In addition, we found that enzymes which are candidates for horizontal gene transfer have a higher average connectivity than other enzymes. This indicates that while new enzymes are attached preferentially to highly connected enzymes, these highly connected enzymes have sometimes been introduced into the E. coli genome by horizontal gene transfer. We speculate that E. coli has adjusted its metabolic network to a changing environment by replacing the relatively central enzymes for better adapted orthologs from other prokaryotic species.

Bacteria↗

PubMed2005

Domain rearrangements in protein evolution.

Most eukaryotic proteins are multi-domain proteins that are created from fusions of genes, deletions and internal repetitions. An investigation of such evolutionary events requires a method to find the domain architecture from which each protein originates. Therefore, we defined a novel measure, domain distance, which is calculated as the number of domains that differ between two domain architectures. Using this measure the evolutionary events that distinguish a protein from its closest ancestor have been studied and it was found that indels are more common than internal repetition and that the exchange of a domain is rare. Indels and repetitions are common at both the N and C-terminals while they are rare between domains. The evolution of the majority of multi-domain proteins can be explained by the stepwise insertions of single domains, with the exception of repeats that sometimes are duplicated several domains in tandem. We show that domain distances agree with sequence similarity and semantic similarity based on gene ontology annotations. In addition, we demonstrate the use of the domain distance measure to build evolutionary trees. Finally, the evolution of multi-domain proteins is exemplified by a closer study of the evolution of two protein families, non-receptor tyrosine kinases and RhoGEFs.

Databases, Protein↗

PubMed2004

Network analysis of metabolic enzyme evolution in Escherichia coli.

BACKGROUND: The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc. RESULTS: Sequence comparison between all enzyme pairs was performed and the minimal path length (MPL) between all enzyme pairs was determined. We find a strong over-representation of homologous enzymes at MPL 1. We show that the functionally similar and functionally undetermined enzyme pairs are responsible for most of the over-representation of homologous enzyme pairs at MPL 1. CONCLUSIONS: The retrograde evolution model predicts that homologous enzymes pairs are at short metabolic distances from each other. In general agreement with previous studies we find that homologous enzymes occur close to each other in the network more often than expected by chance, which lends some support to the retrograde evolution model. However, we show that the homologous enzyme pairs which may have evolved through retrograde evolution, namely the pairs that are functionally dissimilar, show a weaker over-representation at MPL 1 than the functionally similar enzyme pairs. Our study indicates that, while the retrograde evolution model may have played a small part, the patchwork evolution model is the predominant process of metabolic enzyme evolution.

Algorithms↗