Biomedical subjects

Nicholas Hamilton

Publications and source records attributed to Nicholas Hamilton.

3 recordsLinked to original sources

PubMed2006

Visualisation of macropinosome maturation by the recruitment of sorting nexins.

We report that phosphoinositol-binding sorting nexin 5 (SNX5) associates with newly formed macropinosomes induced by EGF stimulation. We used the recruitment of GFP-SNX5 to macropinosomes to track their maturation. Initially, GFP-SNX5 is sequestered to discrete subdomains of the macropinosome; these subdomains are subsequently incorporated into highly dynamic, often branched, tubular structures. Time-lapse videomicroscopy revealed the highly dynamic extension of SNX5-labelled tubules and their departure from the macropinosome body to follow predefined paths towards the perinuclear region of the cell, before fusing with early endosomal acceptor membranes. The extension and departure of these tubular structures occurs rapidly over 5-10 minutes and is dependent upon intact microtubules. As the tubular structures depart from the macropinosome there is a reduction in the surface area and an increase in tension of the limiting membrane of the macropinosome. In addition to the recruitment of SNX5 to the macropinosome, Rab5, SNX1 and EEA1 are also recruited by newly formed macropinosomes, followed by the accumulation of Rab7. SNX5 forms heterodimers with SNX1 and this interaction is required for endosome association of SNX5. We propose that the departure of SNX5-positive tubules represents a rapid mechanism of recycling components from macropinosomes thereby promoting their maturation into Rab7-positive structures. Collectively these findings provide a detailed real-time characterisation of the maturation process of the macropinocytic endosome.

Antigens, Surface↗

PubMed2006

Phylogenetic identification of lateral genetic transfer events.

BACKGROUND: Lateral genetic transfer can lead to disagreements among phylogenetic trees comprising sequences from the same set of taxa. Where topological discordance is thought to have arisen through genetic transfer events, tree comparisons can be used to identify the lineages that may have shared genetic information. An 'edit path' of one or more transfer events can be represented with a series of subtree prune and regraft (SPR) operations, but finding the optimal such set of operations is NP-hard for comparisons between rooted trees, and may be so for unrooted trees as well. RESULTS: Efficient Evaluation of Edit Paths (EEEP) is a new tree comparison algorithm that uses evolutionarily reasonable constraints to identify and eliminate many unproductive search avenues, reducing the time required to solve many edit path problems. The performance of EEEP compares favourably to that of other algorithms when applied to strictly bifurcating trees with specified numbers of SPR operations. We also used EEEP to recover edit paths from over 19,000 unrooted, incompletely resolved protein trees containing up to 144 taxa as part of a large phylogenomic study. While inferred protein trees were far more similar to a reference supertree than random trees were to each other, the phylogenetic distance spanned by random versus inferred transfer events was similar, suggesting that real transfer events occur most frequently between closely related organisms, but can span large phylogenetic distances as well. While most of the protein trees examined here were very similar to the reference supertree, requiring zero or one edit operations for reconciliation, some trees implied up to 40 transfer events within a single orthologous set of proteins. CONCLUSION: Since sequence trees typically have no implied root and may contain unresolved or multifurcating nodes, the strategy implemented in EEEP is the most appropriate for phylogenomic analyses. The high degree of consistency among inferred protein trees shows that vertical inheritance is the dominant pattern of evolution, at least for the set of organisms considered here. However, the edit paths inferred using EEEP suggest an important role for genetic transfer in the evolution of microbial genomes as well.

Algorithms↗

PubMed2004

Protein contact prediction using patterns of correlation.

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two "windows" of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations.

Amino Acids↗