Switchgrass Metabolomics Reveals Striking Genotypic and Developmental Differences in Specialized Metabolic Phenotypes

Plant-inspired building blocks for future plastics

The transition from a linear fossil-based economy to a renewable circular economy requires a new approach to produce building blocks for plastics. This provides opportunities to reshape the plastic landscape and will positively impact the wide range of applications that make use of plastics. We propose that plant enzymes, which underlie the large biochemical diversity present in plant specialized metabolism, will facilitate the production of novel building blocks for new polymers via biotechnological processes. Thereby, plant-inspired plastic building blocks may enable the development of new plastics for targeted applications that can contribute to a future with renewable plastics.

Transcriptome and Metabolome Analyses Reveal the Molecular Mechanisms of Albizia odoratissima's Response to Drought Stress

Albizia odoratissima is a deciduous tree species belonging to the family Leguminosae. It is widely distributed in the southern subtropical and tropical areas of China and has important ecological and economic value. The growth and metabolic processes of A. odoratissima are affected by drought stress, but the molecular mechanisms remain unknown. Therefore, this study investigated the physicochemical properties, gene expression, and metabolites of A. odoratissima seedlings under drought stress. The results show that, in leaves of A. odoratissima seedlings, drought stress reduced the moisture content, chlorophyll content, photosynthetic efficiency, superoxide dismutase (SOD) activity, and gibberellin (GA) and indoleacetic acid (IAA) contents while increasing the catalase (CAT) and peroxidase (POD) activities and malondialdehyde (MDA), proline, soluble sugar, and soluble protein contents. Within the CK5 (Day 5 of control group) vs. T5 (Day 5 of drought treatment), CK10 vs. T10, CK15 vs. T15, and CK20 vs. T20 groups (CK: control group; T: drought treatment), a total of 676 differentially expressed genes (DEGs) were upregulated and 518 DEGs were downregulated, and a total of 228 and 143 differential accumulation metabolites (DAMs) were identified in the CK10 vs. T10 and CK20 vs. T20 groups. These were mainly involved in the amino acid and alkaloid metabolism pathways in the leaves of the A. odoratissima seedlings. In the amino acid and alkaloid biosynthesis pathways, the relative expression levels of the AoproA (Aod04G002740, ORTHODONTIC APPLIANCE), AoOAT (Aod07G015970, ORNITHINE-OXO-ACID TRANSAMINASE), and AoAOC3 (Aod12G005010/08G003360/05G023920/08G003000/08G003010, AMINE OXIDASE COPPER CONTAINING 3) genes increased, which concurrently promoted the accumulation of arginine, proline, piperine, cadaverine, and lysine. Furthermore, some key transcription factors in the response to drought were identified in the leaves using the weighted gene co-expression network analyses (WGCNA) method. These findings reveal that A. odoratissima seedlings respond to drought stress by improving the capacities of the antioxidant system and secondary metabolism.

Disentangling plant- and environment-mediated drivers of active rhizosphere bacterial community dynamics during short-term drought

Mitigating the effects of climate stress on crops is important for global food security. The microbiome associated with plant roots, the rhizobiome, can harbor beneficial microbes that alleviate stress, but the factors influencing their recruitment are unclear. We conducted a greenhouse experiment using field soil with a legacy of growing switchgrass and common bean to investigate the impact of short-term drought severity on the recruitment of active bacterial rhizobiome members. We applied 16S rRNA and 16S rRNA gene sequencing for both crops and metabolite profiling for switchgrass. We included planted and unplanted conditions to distinguish environment- versus plant-mediated rhizobiome drivers. Differences in community structure were observed between crops and between drought and watered and planted and unplanted treatments within crops. Despite crop-specific communities, drought rhizobiome dynamics were similar across the two crops. The presence of a plant more strongly explained the rhizobiome variation in bean (17%) than in switchgrass (3%), with a small effect of plant mediation during drought observed only for the bean rhizobiome. The switchgrass rhizobiome was stable despite changes in rhizosphere metabolite profiles between planted and unplanted treatments. We conclude that rhizobiome responses to short-term drought are crop-specific, with possible decoupling of plant exudation from rhizobiome responses.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Anti-fungal bioactive terpenoids in the bioenergy crop switchgrass (Panicum virgatum) may contribute to ecotype-specific microbiome composition

Plant derived bioactive small molecules have attracted attention of scientists across fundamental and applied scientific disciplines. We seek to understand the influence of these phytochemicals on rhizosphere and root-associated fungi. We hypothesize that - consistent with accumulating evidence that switchgrass genotype impacts microbiome assembly - differential terpenoid accumulation contributes to switchgrass ecotype-specific microbiome composition. An initial in vitro Petri plate-based disc diffusion screen of 18 switchgrass root derived fungal isolates revealed differential responses to upland- and lowland-isolated metabolites. To identify specific fungal growth-modulating metabolites, we tested fractions from root extracts on three ecologically important fungal isolates - Linnemania elongata, Trichoderma sp. and Fusarium sp. Saponins and diterpenoids were identified as the most prominent antifungal metabolites. Finally, analysis of liquid chromatography-purified terpenoids revealed fungal inhibition structure - activity relationships (SAR). Saponin antifungal activity was primarily determined by the number of sugar moieties - saponins glycosylated at a single core position were inhibitory whereas saponins glycosylated at two core positions were inactive. Saponin core hydroxylation and acetylation were also associated with reduced activity. Diterpenoid activity required the presence of an intact furan ring for strong fungal growth inhibition. These results inform future breeding and biotechnology strategies for crop protection with reduced pesticide application.

Divergent Metabolic Changes in Rhizomes of Lowland and Upland Switchgrass (Panicum virgatum) from Early Season through Dormancy Onset

High-biomass-yielding southerly adapted switchgrasses (Panicum virgatum L.) frequently suffer from unpredictable winter hardiness at more northerly sites arising from damage to rhizomes that prevent effective spring regrowth. Previously, changes occurring over the growing season in rhizomes sampled from a cold-adapted tetraploid upland cultivar, Summer, demonstrated a role for abscisic acid (ABA), starch accumulation, and transcriptional reprogramming as drivers of dormancy onset and potential keys to rhizome health during winter dormancy. Here, rhizome metabolism of a high-yielding southerly adapted tetraploid switchgrass cultivar, Kanlow-which is a significant source of genetics for yield improvement-was studied over a growing season at a northern site. Metabolite levels and transcript abundances were combined to develop physiological profiles accompanying greening through the onset of dormancy in Kanlow rhizomes. Next, comparisons of the data to rhizome metabolism occurring in the adapted upland cultivar Summer were performed. These data revealed both similarities as well as numerous differences in rhizome metabolism that were indicative of physiological adaptations unique to each cultivar. Similarities included elevated ABA levels and accumulation of starch in rhizomes during dormancy onset. Notable differences were observed in the accumulation of specific metabolites, the expression of genes encoding transcription factors, and several enzymes linked to primary metabolism.

Comparative transcriptomics and metabolomics reveal specialized metabolite drought stress responses in switchgrass (Panicum virgatum)

Switchgrass (Panicum virgatum) is a bioenergy model crop valued for its energy efficiency and drought tolerance. The related monocot species rice (Oryza sativa) and maize (Zea mays) deploy species-specific, specialized metabolites as core stress defenses. By contrast, specialized chemical defenses in switchgrass are largely unknown. To investigate specialized metabolic drought responses in switchgrass, we integrated tissue-specific transcriptome and metabolite analyses of the genotypes Alamo and Cave-in-Rock that feature different drought tolerance. The more drought-susceptible Cave-in-Rock featured an earlier onset of transcriptomic changes and significantly more differentially expressed genes in response to drought compared to Alamo. Specialized pathways showed moderate differential expression compared to pronounced transcriptomic alterations in carbohydrate and amino acid metabolism. However, diterpenoid-biosynthetic genes showed drought-inducible expression in Alamo roots, contrasting largely unaltered triterpenoid and phenylpropanoid pathways. Metabolomic analyses identified common and genotype-specific flavonoids and terpenoids. Consistent with transcriptomic alterations, several root diterpenoids showed significant drought-induced accumulation, whereas triterpenoid abundance remained predominantly unchanged. Structural analysis verified select drought-responsive diterpenoids as oxygenated furanoditerpenoids. Drought-dependent transcriptome and metabolite profiles provide the foundation to understand the molecular mechanisms underlying switchgrass drought responses. Accumulation of specialized root diterpenoids and corresponding pathway transcripts supports a role in drought stress tolerance.

Water-soluble saponins accumulate in drought-stressed switchgrass and may inhibit yeast growth during bioethanol production

BACKGROUND

Developing economically viable pathways to produce renewable energy has become an important research theme in recent years. Lignocellulosic biomass is a promising feedstock that can be converted into second-generation biofuels and bioproducts. Global warming has adversely affected climate change causing many environmental changes that have impacted earth surface temperature and rainfall patterns. Recent research has shown that environmental growth conditions altered the composition of drought-stressed switchgrass and directly influenced the extent of biomass conversion to fuels by completely inhibiting yeast growth during fermentation. Our goal in this project was to find a way to overcome the microbial inhibition and characterize specific compounds that led to this inhibition. Additionally, we also determined if these microbial inhibitors were plant-generated compounds, by-products of the pretreatment process, or a combination of both.

RESULTS

Switchgrass harvested in drought (2012) and non-drought (2010) years were pretreated using Ammonia Fiber Expansion (AFEX). Untreated and AFEX processed samples were then extracted using solvents (i.e., water, ethanol, and ethyl acetate) to selectively remove potential inhibitory compounds and determine whether pretreatment affects the inhibition. High solids loading enzymatic hydrolysis was performed on all samples, followed by fermentation using engineered Saccharomyces cerevisiae. Fermentation rate, cell growth, sugar consumption, and ethanol production were used to evaluate fermentation performance. We found that water extraction of drought-year switchgrass before AFEX pretreatment reduced the inhibition of yeast fermentation. The extracts were analyzed using liquid chromatography-mass spectrometry (LC-MS) to detect compounds enriched in the extracted fractions. Saponins, a class of plant-generated triterpene or steroidal glycosides, were found to be significantly more abundant in the water extracts from drought-year (inhibitory) switchgrass. The inhibitory nature of the saponins in switchgrass hydrolysate was validated by spiking commercially available saponin standard (protodioscin) in non-inhibitory switchgrass hydrolysate harvested in normal year.

CONCLUSIONS

Adding a water extraction step prior to AFEX-pretreatment of drought-stressed switchgrass effectively overcame inhibition of yeast growth during bioethanol production. Saponins appear to be generated by the plant as a response to drought as they were significantly more abundant in the drought-stressed switchgrass water extracts and may contribute toward yeast inhibition in drought-stressed switchgrass hydrolysates.