Partitioning the phytochemical landscape
Creators: name: Philbin, Casey S.
name: Richards, Lora A.
name: Marion, Zachary H.
name: Glassmire, Andrea E.
name: Massad, Tara Joy
name: Harrison, Joshua G.
name: Su'ad A. Yoon
name: Chalyavi, Farzaneh
name: Tucker, Matthew J.
name: Criag D. Dodson
name: Forister, Matthew L.
name: Dyer, Lee A.
name: Jeffrey, Christopher S.
Publisher: name: F1000 Research Limited
Year: 2018

description: Background/Question/Methods:<br>The importance of phytochemistry to multi-trophic interactions has long been known, but most studies are restricted to an individual compound or class of compounds. Advances in metabolomics techniques have subsequently facilitated the simultaneous study of multiple compounds and classes within a given multi-trophic system. Although metabolomics techniques are information-rich, methods for establishing functional relationships between plant-animal interactions, the metabolome, and abiotic factors are limited and still being developed. One fruitful approach is to apply a chemical diversity framework to metabolomics data, analogous to species diversity within plots and landscapes. Chemical diversity can manifest itself in a multitude of ways, the simplest of which is compositional complexity, the number and relative concentrations of secondary metabolites being expressed by an individual. However, when considering evolutionary and energetic tradeoffs, it is important to also consider structural complexity. Establishing a framework which allows the comparison of changes in structural complexity vis-à-vis compositional complexity is essential to elucidating how evolutionary pressures affect phytochemical diversity. Essential to this framework is understanding how different analytical methods influence and are influenced by structural complexity. This study investigates various methods of calculating compositional and structural diversity and evaluates these measures within and between chemical analytical methods.<br><br>Results/Conclusions:<br>Phytochemical analyses of several tropical and temperate plant systems were undertaken using one or a combination of the following methods: LC-MS, GC-MS, FT-IR, and NMR. Known structures within these plant systems were compared <i>in silico</i> to determine which aspects of structural complexity are being captured by each analytical method. A framework for comparing compositional and structural complexity was then developed based on ecological concepts of community diversity: the entire metabolome serves as our landscape and each phytochemical is its own plot within that landscape. Taking this concept further, the diversity of signals derived from a single phytochemical represents the structural complexity of that compound within a given spectroscopic method. Generally speaking, increased diversity of spectroscopic signals can be attributed to the stages of biosynthetic diversification: 1. increased molecular mass (chain elongation), 2. loss of symmetry (cyclization), 3. increased functionality (oxidation). These structural changes either come at a cost to the organism in carbon or require additional biosynthetic machinery. A framework which considers tradeoffs between structural and compositional complexity could bridge the gap between existing hypotheses regarding the evolution of phytochemical diversity, and could lead to a more sophisticated model for chemically mediated interaction within communities and ecosystems.