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Production and packaging of a biological arsenal: evolution of centipede venoms under morphological constraint.

ABSTRACT: Venom represents one of the most extreme manifestations of a chemical arms race. Venoms are complex biochemical arsenals, often containing hundreds to thousands of unique protein toxins. Despite their utility for prey capture, venoms are energetically expensive commodities, and consequently it is hypothesized that venom complexity is inversely related to the capacity of a venomous animal to physically subdue prey. Centipedes, one of the oldest yet least-studied venomous lineages, appear to defy this rule. Although scutigeromorph centipedes produce less complex venom than those secreted by scolopendrid centipedes, they appear to rely heavily on venom for prey capture. We show that the venom glands are large and well developed in both scutigerid and scolopendrid species, but that scutigerid forcipules lack the adaptations that allow scolopendrids to inflict physical damage on prey and predators. Moreover, we reveal that scolopendrid venom glands have evolved to accommodate a much larger number of secretory cells and, by using imaging mass spectrometry, we demonstrate that toxin production is heterogeneous across these secretory units. We propose that the differences in venom complexity between centipede orders are largely a result of morphological restrictions of the venom gland, and consequently there is a strong correlation between the morphological and biochemical complexity of this unique venom system. The current data add to the growing body of evidence that toxins are not expressed in a spatially homogenous manner within venom glands, and they suggest that the link between ecology and toxin evolution is more complex than previously thought.

SUBMITTER: Undheim EA

PROVIDER: S-EPMC4386323 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Production and packaging of a biological arsenal: evolution of centipede venoms under morphological constraint.

Undheim Eivind A B EA Hamilton Brett R BR Kurniawan Nyoman D ND Bowlay Greg G Cribb Bronwen W BW Merritt David J DJ Fry Bryan G BG King Glenn F GF Venter Deon J DJ

Proceedings of the National Academy of Sciences of the United States of America 20150316 13

Venom represents one of the most extreme manifestations of a chemical arms race. Venoms are complex biochemical arsenals, often containing hundreds to thousands of unique protein toxins. Despite their utility for prey capture, venoms are energetically expensive commodities, and consequently it is hypothesized that venom complexity is inversely related to the capacity of a venomous animal to physically subdue prey. Centipedes, one of the oldest yet least-studied venomous lineages, appear to defy ...[more]

PMID: 25775536

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Project description:BACKGROUND: An important step in strain optimization is to identify reactions whose activities should be modified to achieve the desired cellular objective. Preferably, these reactions are identified systematically, as the number of possible combinations of reaction modifications could be very large. Over the last several years, a number of computational methods have been described for identifying combinations of reaction modifications. However, none of these methods explicitly address uncertainties in implementing the reaction activity modifications. In this work, we model the uncertainties as probability distributions in the flux carrying capacities of reactions. Based on this model, we develop an optimization method that identifies reactions for flux capacity modifications to predict outcomes with high statistical likelihood. RESULTS: We compare three optimization methods that select an intervention set comprising up- or down-regulation of reaction flux capacity: CCOpt (Chance constrained optimization), DetOpt (Deterministic optimization), and MCOpt (Monte Carlo-based optimization). We evaluate the methods using a Monte Carlo simulation-based method, MCEval (Monte Carlo Evaluations). We present two case studies analyzing a CHO cell and an adipocyte model. The flux capacity distributions required for our methods were estimated from maximal reaction velocities or elementary mode analysis. The intervention set selected by CCOpt consistently outperforms the intervention set selected by DetOpt in terms of tolerance to flux capacity variations. MCEval shows that the optimal flux predicted based on the CCOpt intervention set is more likely to be obtained, in a probabilistic sense, than the flux predicted by DetOpt. The intervention sets identified by CCOpt and MCOpt were similar; however, the exhaustive sampling required by MCOpt incurred significantly greater computational cost. CONCLUSIONS: Maximizing tolerance to variable engineering outcomes (in modifying enzyme activities) can identify intervention sets that statistically improve the desired cellular objective.

Dataset Information

Production and packaging of a biological arsenal: evolution of centipede venoms under morphological constraint.

Publications

Production and packaging of a biological arsenal: evolution of centipede venoms under morphological constraint.

Similar Datasets

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