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Mathis, C.

Publications and source records attributed to Mathis, C..

2 recordsLinked to original sources

Bioinformatic analysis reveals mechanisms underlying parasitoid venom evolution and function

Introduction Introduction Methods Results and Discussion Conclusions References Parasitoid wasps are a numerous and diverse group of insects that obligately infect other arthropod species. These wasps lay their eggs either on the surface or within the body cavity of their hosts, and the resulting offspring exploit the hosts resources to complete their development [1]. Many parasitoids also introduce venom gland derived proteins or polydnaviruses into the host during infection. These factors act through a variety of mechanisms to manipulate host biology in order to increase the fitness of the developing parasitoid offspring [2-4]. Many hosts mount immune responses to parasitoid infection, and accordingly, parasitoids have evolved multiple venom genes that encode immunom ...

genomics

Universal Scaling in Biochemical Networks

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes, and 8,658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical networks to random chemical networks reveals the observed biological scaling is not solely a product of the biochemistry shared across life on Earth. Instead, it emerges due to how the global inventory of biochemical reactions is partitioned into individuals. We show the three domains of life are topologically distinguishable, with > 80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Taken together our results point to a deeper level of organization in biochemical networks than what has been understood so far.

systems biology