2021-present   Principal Investigator, CAS Center for Excellence in Molecular Plant Sciences, CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Shanghai, China

2016-2021   Postdoc, Max-Planck-Institute for Chemical Ecology, Jena, Germany

2012-2016   Ph.D in metabolomics, Max-Planck-Institute for Chemical Ecology, Jena, Germany

2009-2012   M.S. in bioinformatics, Tongji University, Shanghai, China

1. A novel GLV-phenolamide mediates nonhost resistance of a native tobacco against leafhopper pests. Although much is known about plant traits that function in nonhost resistance against pathogens, little is known about nonhost resistance against herbivores, despite its agricultural importance. Using an unbiased forward-genetics approach based on the screening of a 26-parent Nicotiana attenuata recombinant inbred line population in natural habitat with native herbivores wedded with unbiased transcriptomic and mass spectrometry–based metabolomic analyses of reverse-genetics lines, we identified a new defense metabolite, produced by a novel biosynthetic pathway that represents the biochemical union of so-called “direct” (caffeoylputrescine: CP) and “indirect” (GLV:(Z)-3-hexenal) defense metabolism when probed by Empoasca leafhoppers.

2. Navigating metabolic diversity and function in plant specialized metabolism. We developed a cheminformatics and computational MS/MS strategy for the systematic exploration of plant specialized metabolism diversity. The workflow combines the strengths of data-independent MS/MS acquisition (idMS/MS) to capture specialized metabolism diversity from a dataset at a global scale and computational MS to accelerate the structural annotations of the compounds collected; and brings together the analysis of genomics, transcriptomics and metabolomics using an information theory statistical framework. Using this framework, we quantified metabolite variance found both within plant parts and among natural accessions in elicitation kinetic experiments, and networked the metabolite variance data with transcriptomic data, to reveal how natural selection has sculpted the distributions of these metabolites in the intra- and inter-species scales.

Our research seeks to understand how plants make use of complex blends of structurally diverse metabolites to adapt to the changing environment.

Plants are master synthetic chemists, capable of synthesizing a plethora of structurally diverse specialized metabolites. The plant kingdom contains somewhere on the order of one hundred thousand to one million chemically unique structures. Those structurally diverse specialized metabolites are central players in plants’ adaptations to their environments and in particular in their defense against enemies and recruitment of beneficial microbes.

Mass spectrometry (MS)-based untargeted metabolomics, which empowers the collection of vast amounts of structural information of biological samples, has now become a critical technique for the global chemical analysis of plant biology. Over the past years, our goal was to develop a working and useable synthesis of unbiased computational metabolomics, multi-omics techniques, molecular biology and natural history-driven approaches. The objective of this synthesis was to explore the holistic “metabolic space” that plants produce when attacked and digested by herbivores, and when they recruit fungal and bacterial microbiomes, so that metabolism-centered biological and ecological questions could be rigorously addressed.

1. Li J.^*, Baldwin I.T.^*, and Li D.^* (2022). Harmonizing biosynthesis with post-ingestive modifications to understand the ecological functions of plant natural products. Natural Product Reports 39, 1383-1392

2. Bai Y.^*, Yang C., Halitschke R., et al. Baldwin I.T.^* and Li D.^* (2022). Natural history-guided omics reveals plant defensive chemistry against leafhopper pests. Science 375:eabm2948

3. Li D.^*, and Gaquerel E^*. (2021). Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity. Annual review of plant biology 72:1.

4. Li J., Halitschke R., Li D., Paetz C., Su H., Heiling S., Xu S.^*, and Baldwin I.T.^* (2021). Controlled hydroxylations of diterpenoids allow for plant chemical defense without autotoxicity. Science 371, 255-260.

5. Li D., Halitschke R., Baldwin I.T.^*, and Gaquerel E.^* (2020). Information theory tests critical predictions of plant defense theory for specialized metabolism. Science Advances, 6:eaaz0381

6. Wang M., Sch?fer M., Li D., Halitschke R., Dong C., et al. (2018) Blumenols as effective shoot markers for root symbiosis with arbuscular mycorrhizal fungi. eLife 7:e37093.

7. Li D., Heiling S., Baldwin I.T., and Gaquerel E.^* (2016). Illuminating a plant's tissue-specific metabolic diversity using computational metabolomics and information theory. PNAS 113(47), E7610-E7618.

8. Li D., Baldwin I.T., and Gaquerel E.^* (2016). Beyond the Canon: Within-Plant and Population-Level Heterogeneity in Jasmonate Signaling Engaged by Plant-Insect Interactions. Plants 5(1): 14.

9. Li D., Baldwin I.T., and Gaquerel E.^* (2015). Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis. PNAS 112(30), E4147-E4155.