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aBIOTECH https://doi.org/10.1007/s42994-022-00091-4 aBIOTECH REVIEW Integrating multiomics data accelerates elucidation of plant primary and secondary metabolic pathways 1,2 1 1 2,3 Feng Zhu , Weiwei Wen , Yunjiang Cheng , Saleh Alseekh , 2,3& Alisdair R. Fernie National R&D Center for Citrus Preservation, Hubei Hongshan Laboratory, National Key Laboratory for Germplasm Innovation and Utilization for Fruit and Vegetable Horticultural Crops, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China Max Planck Institute of Molecular Plant Physiology, Am Mu¨ hlenberg 1, Potsdam-Golm 14476, Germany Center of Plant Systems Biology and Biotechnology, Plovdiv 4000, Bulgaria Received: 11 October 2022 / Accepted: 24 December 2022 Abstract Plants are the most important sources of food for humans, as well as supplying many ingredients that are of great importance for human health. Developing an understanding of the functional components of plant metabolism has attracted considerable attention. The rapid development of liquid chro- matography and gas chromatography, coupled with mass spectrometry, has allowed the detection and characterization of many thousands of metabolites of plant origin. Nowadays, elucidating the detailed biosynthesis and degradation pathways of these metabolites represents a major bottleneck in our understanding. Recently, the decreased cost of genome and transcriptome sequencing rendered it possible to identify the genes involving in metabolic pathways. Here, we review the recent research which integrates metabolomic with different omics methods, to comprehensively identify structural and regulatory genes of the primary and secondary metabolic pathways. Finally, we discuss other novel methods that can accelerate the process of identiﬁcation of metabolic pathways and, ultimately, identify metabolite function(s). Keywords Metabolome, Transcriptome, Genome, Crop improvement INTRODUCTION important bio-markers, reﬂecting the exact physiologi- cal status of the plant (Afendi et al. 2013; Fang et al. Metabolites are fundamental components of the plant 2019). Among these metabolites, some of them, such as cell. These compounds play vital roles not only in plants sugars, organic acids, and amino acids directly partici- as energy suppliers, signaling regulators, and enzyme pate in plant basic metabolism and maintain funda- cofactors, but also for human health, given that they mental biological processes, including functional supply carbohydrates, fatty acids, proteins, vitamins and macromolecule biosynthesis. Such metabolites are minerals, alongside bioactive secondary metabolites regarded as primary metabolites. Moreover, other (Canarini et al. 2019; Zaynab et al. 2019). Based on metabolites, such as polyphenols, terpenoids, and alka- former estimates, the plant kingdom produces some 1 loids, function as important regulators, not only of dif- million metabolites for different functions (Alseekh and ferent plant growth and development processes but also Fernie 2018). Moreover, these metabolites are the most against the biotic and abiotic stresses and further exhibit high bioactivities, thereby allowing them to augment defense to human inﬂammation, & Correspondence: firstname.lastname@example.org (A. R. Fernie) The Author(s) 2023 aBIOTECH cardiovascular diseases, and cancer. Such plant primary metabolites, such as amino acids and fatty acids metabolites are named as secondary metabolites or (Sweetlove et al. 2010; Zhao et al. 2021). specialized metabolites (Tiwari and Rana 2015; Tohge As an example, exogenously applied sugars can et al. 2014; Verpoorte and Memelink 2002). increase the fresh weight, vitamin C, soluble protein, Considering the diversity and importance of and sugar contents of pea sprouts (Tan et al. 2022). The metabolites, an important issue in metabolomic availability of cellular sugars reﬂects the plant’s carbon research is the development of a high-throughput and nutrient status, which then induces the functions of exact identiﬁcation and qualiﬁcation method. Recently, nutrition sensing, through such pathways as the hex- owing to the rapid innovation of liquid/gas chro- okinase glucose sensor, the trehalose 6-phosphate sig- matography and high-sensitive mass spectrometry, glo- nal, and the Target of Rapamycin kinase pathway, to bal analyses, conducted across different plant species, regulate plant growth and development processes have identiﬁed many thousands of metabolites (Obata (Smeekens et al. 2010). et al. 2020; Peng et al. 2017). To advance knowledge In addition, 2-oxo-glutarate is an important inter- concerning metabolites, improving our understanding mediate in the TCA cycle but can also be converted to of metabolic pathways of biosynthesis and catabolism glutamate that can then be transferred to other amino has recently attracted considerable attention. Indeed, acids (Garcı´a-Gutie´rrez et al. 2018; Liepman and Olsen many advances have been achieved by incorporating 2003). Moreover, isotope labeling experiments have large-scale genome and transcriptome analyses (Li et al. demonstrated that pyruvate, the key component of 2020; Zhu et al. 2022a). glycolysis, is the immediate precursor for the synthesis In this review, we summarize the importance of of alanine (Kennedy and Laetsch 1974). The accumula- metabolites and the proﬁling methods to study the tion of some primary metabolites, such as proline, can different kinds of metabolites. We also stress the signiﬁcantly enhance plant tolerance against the abiotic importance of research that integrates the combination stresses resulting from the global climatic change of metabolomic, genomic and transcriptomic datasets. (Ghosh et al. 2022). Besides sugars, organic acids and We then discuss other efﬁcient strategies to better amino acids, fatty acids, and their derived lipids, are decode the primary and secondary pathways of various predominant components of both the plasma membrane crops. and photosynthetic membranes (Li et al. 2016). Simi- larly, fatty acid metabolism also affects both cuticular wax biosynthesis and pollen fertility, which are impor- IMPORTANCE OF THE PLANT METABOLOME tant processes for plant adaption to a terrestrial envi- AND RESEARCH STRATEGIES EMPLOYED FOR ITS ronment and propagation (Millar et al. 1999; Wang et al. EVALUATION 2022b; Zhang et al. 2021a). As mentioned above, metabolites can be divided into Secondary metabolites two major classes, primary metabolites and secondary metabolites (Wang et al. 2022a); however, the distinc- Based on their molecular structures and biological tion between these is, at times, blurred (Erb and functions, secondary metabolites can be divided into Kliebenstein 2020;Fa`bregas and Fernie 2021). Both various classes, such as terpenoids, polyphenols, alka- classes play important roles in plant development, loids, non-ribosomal polypeptides, and enzyme cofac- response to stress, and reproduction. However, the tors (Tohge et al. 2014; Verpoorte and Memelink 2002). proﬁling methods used to obtain information on their Given that their sessile character has considerably lim- levels are slightly different. ited the communication of plants with other plants and animals, some metabolites of the terpenoids, such as Primary metabolites terpenes, are volatile and play important roles in the communication between plants with pollinators, seed As the most well-studied primary metabolites, organic dispersers, and signal transduction between different acids and sugars are the key components of the tricar- plants (Dudareva et al. 2013). Another example is the boxylic acid cycle (TCA cycle) and glycolysis pathways representative C40 terpenoids; these carotenoids play (Krebs 1970). These pathways not only provide the vital roles in plant photosynthesis, photoprotection, and main energy source, and some components used for the development, and are important in the synthesis of generation of signaling molecules, but also produce pigments associated with fruit appearance quality different substrates for the synthesis of other important (Nisar et al. 2015). The Author(s) 2023 aBIOTECH Polyphenols are the most studied secondary develop tomato fruit with enhanced anthocyanin levels, metabolites, and are derived from phenylalanine, via the scientists generated transgenic plants expressing two shikimate/phenylpropanoid pathway. After condensa- transcription factors from snapdragon (Del and Ros1), tion with malonyl-CoA, and modiﬁcations including thereby enhancing, threefold, the hydrophilic antioxi- methylation and glucuronidation, phenylalanine can be dant capacity in the fruit; feeding these transgenic transferred to representative polyphenols. such as tomato fruit to cancer-susceptible mice signiﬁcantly quercetin 3-O-rutinoside (rutin) and anthocyanin. extend their life span (Butelli et al. 2008). Among the polyphenols, ﬂavonoids are the most studied Alkaloids contain at least one nitrogen atom in a class and generally contain two aromatic rings. The heterocyclic ring and exhibit alkali-like properties. different modiﬁcations, on these aromatic rings, led to Steroidal glycoalkaloids (SGAs) are special alkaloids the super diversity of the ﬂavonoids, which have been accumulating in different plant organs, such as leaves, estimated to contain over 6000 compounds (Go´rniak roots, ﬂowers, fruit and tubers of the Solanaceae family et al. 2019). Recently, scientists reported that, in Ara- (Alseekh et al. 2020). For example, a-tomatine is the bidopsis ﬂowers, a high accumulation of a class of predominantly accumulated SGA in immature tomato phenylacylated-ﬂavonols (saiginols) was attributed to fruit and is toxic for insects, fungi, and humans, thereby protecting the Brassicaceae ﬂower from damage caused making it an efﬁcient protection mechanism to reduce by the UV light in sunshine (Tohge et al. 2016) (Fig. 1). unripen fruit loss. Subsequently, during ripening, a- As important cereals of the human diet, the three grass tomatine can be detoxiﬁed, via a series of hydroxylation crops, maize, rice, and wheat, accumulate some special and modiﬁcation reactions, to produce the human ﬂavonoids, such as glycosylated ﬂavones. These health-promoting chemicals, the esculeosides (Alseekh metabolites also function as UV protectors in these et al. 2015; Fujiwara et al. 2007; Itkin et al. 2011, 2013; crops (Peng et al. 2017) (Fig. 1). Szymanski et al. 2020) (Fig. 2). Besides their importance in food, ﬂavonoids also present in many human beverages, such as tea, and play Metabolite evaluation methods important roles for human health. For example, as a main bioactive ingredient in green tea, epigallocatechin- Given the importance of different metabolites, the 3-gallate (EGCG), can repress the infection of inﬂuenza research community has played great attention to the virus and other representative viruses, such as HCV and methods used in their characterization; here, gas chro- HIV-1, and also affect human-pathogenic yeast strains matography–mass spectrometry (GC–MS) and liquid by affecting the folic acid metabolism of bacteria and chromatograph-mass spectrometry (LC–MS) are the widely used methods. As some primary metabolites are fungi (Steinmann et al. 2013). In addition, it is well known that the representative ﬂavonoids, the antho- small molecular weight components, which can be cyanins, play vital roles in human protection against a easily volatilized after derivatization, gas chromatogra- broad range of diseases (Ciuma˘rnean et al. 2020). To phy-mass spectrometry (GC–MS) is widely used to Fig. 1 Representative decoded ﬂavonoids-related genes addressed in the present review. Purple and blue-marked genes were identiﬁed in Zhang et al. (2020), Peng et al. (2017) and Tohge et al. (2016). Kae- 00 00 3G6 Sin-7R: ﬂavonol-3-O-(2 - O-rhamnosyl-6 -O-sinapoyl) glucoside-7-O-rhamnoside The Author(s) 2023 aBIOTECH resuspended, using a suitable solution, such as butanol– methanol mixture or 50% methanol. The resuspended solutions are then directly loaded onto the LC–MS for separation in a liquid phase and electrospray ionization (ESI) prior to detection by a high-sensitive MS, such as an Exactive high-resolution Orbitrap-type MS. Owing to the variation of LC pump pressure and mass spectra characteristics, it is impractical to build a uni- versal library containing the retention time and mass spectra information for metabolite annotation derived from different labs. In general, based on machine char- acteristics, an individual-speciﬁc LC–MS reference library is established by a lab, through integrating the retention times and mass spectra information for the standard components, useful mass spectra datasets (such as Lipid Maps, http://www.lipidmaps.org/index. html and ReSpect database, http://spectra.psc.riken.jp/ menta.cgi/respect/search/fragment) and information in the public domain (Luzarowska et al. 2020; Wang et al. 2019). In summary, the highly sensitive and accurate metabolite identiﬁcation method, based on the GC/LC– MS, allows construction of a solid foundation for the study of primary and secondary metabolism, whilst a comprehensive deﬁnition of the key genes and regula- tors of these pathways generally needs more informa- Fig. 2 Representative decoded steroidal glycoalkaloids-related tion from both genomic and transcriptomic analyses. genes addressed in the present review. Red genes were identiﬁed in Itkin et al. (2013), Itkin et al. (2011), Szyman´ ski et al. (2020), and Li et al. (2022). GAME: Glycoalkaloid Metabolism INTEGRATION OF GENOME AND METABOLOME TO DECODE GENES INVOLVED IN THE PRIMARY analyze the primary metabolite contents (Obata and AND SECONDARY METABOLISM Fernie 2012). The extracted and dried metabolite mix- ture is ﬁrst derivatized, by methoxyamine-hydrochlo- The one gene–one enzyme hypothesis of George Wells ride/pyridine and N-methyl-N-(trimethylsilyl) Beadle indicated that the individual gene-encoded triﬂuoracet-amide, and then analyzed by GC–MS (Salem enzymes play important roles in the biosynthesis and et al. 2016). To determine the exact metabolite of each catabolism of metabolites (Horowitz 2014), whilst not fraction, the small fragments are detected by time-of- entirely applicable in plants, due to the commonality of ﬂight (TOF)-MS, which can quickly and precisely scan multiple isoforms of the same enzyme, there remains the fragment m/z information. With the help of the some value in the combined comprehensive analysis of established metabolite datasets, such as the Golm the association of genome and metabolome variations, metabolic databases (GMD) (Kind et al. 2009; Kopka which we anticipate will still accelerate elucidation of et al. 2005), efﬁcient annotation and analysis of the the metabolic pathways. During evolution and the relative metabolite content can be analyzed, based on domestication of crops, variations in genes that encode the retention time, mass spectra and peak area for enzymes may change their amino acid sequence and information. directly affect enzyme activity. Therefore, to decode the The reverse phase column exhibits the highly efﬁ- important genes involved in primary and secondary cient separation capacity for similar-structured and a metabolism, scientists traditionally carried out cDNA broad range of metabolites. Their coupling to LC–MS cloning using secondary metabolite-rich tissue or tis- systems has been employed to identify thousands of sues collected from crosses derived from two parents fatty acids-derived lipids, carotenoids, polyphenols and with extreme phenotypes, and then conducted map- alkaloid metabolites (Rupasinghe and Roessner 2018; based cloning analysis of the biparental populations (Shi Salem et al. 2016). The dry-extracted mixture is et al. 2020; Wang et al. 2008). Based on the analysis of The Author(s) 2023 aBIOTECH amino acid content and quantitative trait locus (QTL) secondary metabolites. Using a metabolic genome-wide mapping of 190 recombinant inbred lines (RILs), some association study (mGWAS), based on 840 metabolites 80 individual QTL were identiﬁed for content of 19 and some 6.4 million single-nucleotide polymorphisms amino acids, with a relatively strong QTL cluster, com- (SNPs) for a 529 diverse rice accessions panel, identiﬁed prised of 19 individual QTL, being detected on chro- 2947 lead SNPs that were associated with 598 mosome 1 (Wang et al. 2008). metabolites, with ﬁve candidate genes being further Although many QTL have been identiﬁed using RILs, validated with functions in secondary metabolite path- such a population, which segregates concurrently for ways (Chen et al. 2014). many QTL dispersed throughout the genome, may cause In addition to SNPs and small indels, structural huge variances in the following statistical analysis and, variations (SVs), such as a big insertion, deletion, copy thereby, reduce the effects of one another, to limit the number variation and chromosomal change, also play genetic resolution of these quantitative traits (Zamir important roles in plant metabolism (Hollox et al. 2022; 2001). To resolve this limitation, introgression lines Voichek and Weigel 2020). However, the short sequence (ILs), which cover the entire genome and each line length of the ﬁrst- and second-generation sequencing segregates for a single region, have been used for QTL method signiﬁcantly limited the identiﬁcation of the SVs mapping. In such analyses, the phenotype variations are in a population genome. In recent years, the develop- associated with the introduced-targeted segment, which ment of a third-generation sequencing method has sig- assists in focusing on the analysis of QTL and genes niﬁcantly increased the sequencing read lengths to over located in the introduced-targeted segment, and this can 10,000 bp, and has become the ideal method for gen- signiﬁcantly improve the efﬁciency of QTL identiﬁcation ome SV detection (Lee et al. 2016). Based on this (Eshed and Zamir 1995; Schauer et al. 2006). method, Alonge et al. (2020) identiﬁed more than As an example, total soluble content of tomato fruit is 200,000 SVs for 100 diverse wild and domesticated a complex phenotype and the analysis, among a popu- tomato accessions and identiﬁed several associations lation of 76 segmental ILs of wild species Solanum between SVs with important fruit quality, such as fruit pennellii into the cultivated tomato (S. lycopersicum smoky volatile content and fruit size. M82), identiﬁed a ﬂower- and fruit-speciﬁc invertase (LIN5), located in the QTL-Brix9-2-5 (Fridman et al. 2004). In addition, the same population of ILs was used INTEGRATION OF TRANSCRIPTOME to identify 338 putative mQTL for ﬂavonoids and ster- AND METABOLOME TO DECODE GENES INVOLVED oidal glycoalkaloids in the tomato seed (Alseekh et al. IN PRIMARY AND SECONDARY METABOLISM 2020). The above-mentioned populations were based on the Earlier studies indicated that genomic variation located genetic resources from two genotypes; however, during in a coding region could change the encoded protein the evolution and domestication of crops, hundreds, or amino acid sequence and, thereby, affect protein func- even thousands of genotypes of each crop have been tion. Moreover, other variations located within the pro- created, which contain more abundant genetic and moter or an intergenic region can also signiﬁcantly metabolic variations for identiﬁcation of metabolism- affect gene expression and by this manner lead to related genes. In addition, the development of next variation in metabolite abundance across a population generation sequence methods reduced the cost and (Ye et al. 2017; Zhu et al. 2022a). With the development made it practical to carry out genome sequencing of of low-cost second-generation sequencing methods, a hundreds, or even thousands, of genotypes. Therefore, vast torrent of transcriptome and metabolome data recently, many association studies have been performed have been analyzed to decode the key genes involved in to explore metabolic and natural population genetic primary and secondary metabolism (Karlova et al. 2011; variations (Chen et al. 2014). As there are millions of Zhu et al. 2017, 2020). variations, within the genome of a population, this As the biosynthesis and catabolism of metabolites complicates the identiﬁcation of the exact association results from the ordered sequence of a series of between a speciﬁc metabolite and a speciﬁc genomic enzymes and their associated regulators, the expression region. To overcome this problem, a genome-wide of these genes may exhibit a similar trend with each association study (GWAS) can be used to explore the other and also with the metabolite content (Omranian connection between a plant metabolite and genetic et al. 2015). Therefore, a comprehensively integrated variation (Mountjoy et al. 2021; Ozaki et al. 2002). analysis of metabolome and transcriptome can be car- Rice, as one of the most important crops for human ried out to detect the high correlation between an food, supplies not only carbohydrates but also unknown gene expression with the levels of The Author(s) 2023 aBIOTECH metabolites, and the tightly co-expressed unknown information for samples (de Souza et al. 2020; Seydel genes with the known function enzyme genes. These 2021). Recently, in human cells, based on the gas cluster correlation analyses can indicate that an unknown gene ion beam secondary ion mass spectrometry (GCIB- may be involved in the interesting metabolite pathway, SIMS) method, Pareek et al. (2020) successfully visual- following a method known as the ‘‘guilt-by-association’’ ized the in situ three-dimensional sub-micrometer approach (Li et al. 2020; Yonekura-Sakakibara et al. chemical imaging of de novo purine biosynthesis and 2008). One example of this approach was the evaluation identiﬁed the enzyme interaction structure, of the of the ﬂavonol pathway of wild and cultivated tomato purinosome, which can channel the pathway and, (Tohge et al. 2020). This study increased the number of thereby, increase the pathway ﬂux yielding purine metabolites recognized in this pathway in tomato from biosynthetic efﬁciency. Moreover, ginsenosides are the 22 to 44. Similarly, the spatio-temporal metabolome and main bioactive metabolites of popular traditional Chi- transcriptome data of 20 major tomato tissues and nese medicines, Panax ginseng. Based on matrix-as- growth stages were recently integrated to build the sisted laser desorption/ionization time-of-ﬂight mass MicroTom Metabolic Network and identiﬁed several spectrometry imaging (MALDI-TOF-MSI), Bai et al. novel transcription factors, such as SlERF.G3-like, (2016) used a novel approach to identify ﬁve different SlbHLH114, regulating the biosynthesis of ﬂavonoids localization types of ginsenosides. Given that different and steroidal glycoalkaloids (Li et al. 2020). ginsenosides have varied pharmacological effects and Population scale transcriptome data can provide can reﬂect the ages of the ginseng root, this method can insight into the expression of genes in different geno- provides important cues for the component-speciﬁc types, and can be integrated with genome variations to extraction and the illustration of bioactive metabolites reﬂect the effect of genetic variance on a gene expres- biosynthesis regulation of pharmacological research of sion phenotype; this is the so-called eQTL (Zhu et al. herbs. 2018, 2022b). Recently, Wen et al. (2018) analyzed mGWAS and eQTL in four independent tissues derived from different maize accessions. Based on these large- CONCLUSIONS scale data, 36 loci were identiﬁed, and four genes were validated to be involved in trehalose, aspartate, and In this review, we have summarized the importance of aromatic amino acid pathways. In addition, the mGWAS metabolite functions and proﬁling methods for method was employed to identify CsANR, CsF3 5’H and metabolites alongside the combined analysis of genome CsMYB5 as important tea genes involved in biosynthesis and metabolome, or transcriptome and metabolome, or of catechins (Zhang et al. 2020) (Fig. 1). the combination of all three omics, to decode the key genes and regulators of plant primary and secondary pathways (Fig. 3). Although these studies have demon- NEW METHODS TO DECODE GENES INVOLVED strated the power of the integrated omics analysis, these IN PRIMARY AND SECONDARY METABOLISM strategies are based on accessibility to a large number of natural populations and the inherent genetic varia- Recently, with transcriptome and metabolome technol- tion. They can, therefore, not be applied to some non- ogy development, single cell and spatial transcriptomics crop plant species, such as certain medicinal plants, or methods have been established with the potential to even crop species such as banana for which the level of provide new insights into metabolism, at a more precise genetic variance is not available in natural populations level, for both crop and non-crop plant species (Xia et al. to facilitate mGWAS analysis. Moreover, using omics 2022; Zhang et al. 2021b, c). Under the regulation of methods remains technically difﬁcult for illustrating the transcriptional, post-transcriptional, or feedback regu- regulatory mechanism of metabolite synthesis within lation, metabolite accumulation also exhibits different special cell types. However, this limitation is beginning patterns within various cell types within the same tis- to be addressed by the integration of newly developed sue. With the developments and advances in MS, optical technologies, such as spatial- transcriptomics and spectroscopy, and the ﬂuorescence biosensors, it is metabolomics and, given the large interest in this slowly becoming practical to simultaneously measure research frontier, it seems appropriate to anticipate that hundreds of metabolites in a single cell (Zenobi 2013). this limitation will soon be addressed. Irrespective of The mass spectrometry imaging methods, such as these restrictions, the integration of different multi- secondary ion mass spectrometry and matrix-assisted omics data can remarkably accelerate the process laser desorption/ionization, are widely used technolo- towards a complete understanding of the pathway gies to obtain spatially resolved metabolome The Author(s) 2023 aBIOTECH Fig. 3 Pipeline of the integrated analysis of metabolome/genome/ transcriptome to identify the primary and secondary pathways and genes. 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aBIOTECH – Springer Journals
Published: Mar 1, 2023
Keywords: Metabolome; Transcriptome; Genome; Crop improvement
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