A genetical metabolomics approach for bioprospecting plant biosynthetic gene clusters

Beyond co-expression: pathway discovery for plant pharmaceuticals

Plant natural products have been an important source of medicinal molecules since ancient times. To gain access to the whole diversity of these molecules for pharmaceutical applications, it is important to understand their biosynthetic origins. Whilst co-expression is a reliable tool for identifying gene candidates, a variety of complementary methods can aid in screening or refining candidate selection. Here, we review recently employed plant biosynthetic pathway discovery approaches, and highlight future directions in the field.

Unraveling the evolutionary dynamics of the TPS gene family in land plants

Terpenes and terpenoids are key natural compounds for plant defense, development, and composition of plant oil. The synthesis and accumulation of a myriad of volatile terpenoid compounds in these plants may dramatically alter the quality and flavor of the oils, which provide great commercial utilization value for oil-producing plants. Terpene synthases (TPSs) are important enzymes responsible for terpenic diversity. Investigating the differentiation of the TPS gene family could provide valuable theoretical support for the genetic improvement of oil-producing plants. While the origin and function of TPS genes have been extensively studied, the exact origin of the initial gene fusion event - it occurred in plants or microbes - remains uncertain. Furthermore, a comprehensive exploration of the TPS gene differentiation is still pending. Here, phylogenetic analysis revealed that the fusion of the TPS gene likely occurred in the ancestor of land plants, following the acquisition of individual C- and N- terminal domains. Potential mutual transfer of TPS genes was observed among microbes and plants. Gene synteny analysis disclosed a differential divergence pattern between TPS-c and TPS-e/f subfamilies involved in primary metabolism and those (TPS-a/b/d/g/h subfamilies) crucial for secondary metabolites. Biosynthetic gene clusters (BGCs) analysis suggested a correlation between lineage divergence and potential natural selection in structuring terpene diversities. This study provides fresh perspectives on the origin and evolution of the TPS gene family.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

Review: Metabolomics as a prediction tool for plants performance under environmental stress

Metabolomics as a diagnosis tool for plant performance has shown good features for breeding and crop improvement. Additionally, due to limitations in land area and the increasing climate changes, breeding projects focusing on abiotic stress tolerance are becoming essential. Nowadays no universal method is available to identify predictive metabolic markers. As a result, research aims must dictate the best method or combination of methods. To this end, we will introduce the key aspects to consider regarding growth scenarios and sampling strategies and discuss major analytical and data treatment approaches that are available to find metabolic markers of plant performance.