Metabolomics of dates (Phoenix dactylifera) reveals a highly dynamic ripening process accounting for major variation in fruit composition

Abstract

Background: Dates are tropical fruits with appreciable nutritional value. Previous attempts at global metabolic characterization of the date metabolome were constrained by small sample size and limited geographical sampling. In this study, two independent large cohorts of mature dates exhibiting substantial diversity in origin, varieties and fruit processing conditions were measured by metabolomics techniques in order to identify major determinants of the fruit metabolome.

Results: Multivariate analysis revealed a first principal component (PC1) significantly associated with the dates' countries of production. The availability of a smaller dataset featuring immature dates from different development stages served to build a model of the ripening process in dates, which helped reveal a strong ripening signature in PC1. Analysis revealed enrichment in the dry type of dates amongst fruits with early ripening profiles at one end of PC1 as oppose to an overrepresentation of the soft type of dates with late ripening profiles at the other end of PC1. Dry dates are typical to the North African region whilst soft dates are more popular in the Gulf region, which partly explains the observed association between PC1 and geography. Analysis of the loading values, expressing metabolite correlation levels with PC1, revealed enrichment patterns of a comprehensive range of metabolite classes along PC1. Three distinct metabolic phases corresponding to known stages of date ripening were observed: An early phase enriched in regulatory hormones, amines and polyamines, energy production, tannins, sucrose and anti-oxidant activity, a second phase with on-going phenylpropanoid secondary metabolism, gene expression and phospholipid metabolism and a late phase with marked sugar dehydration activity and degradation reactions leading to increased volatile synthesis.

Conclusions: These data indicate the importance of date ripening as a main driver of variation in the date metabolome responsible for their diverse nutritional and economical values. The biochemistry of the ripening process in dates is consistent with other fruits but natural dryness may prevent degenerative senescence in dates following ripening. Based on the finding that mature dates present varying extents of ripening, our survey of the date metabolome essentially revealed snapshots of interchanging metabolic states during ripening empowering an in-depth characterization of underlying biology.

Fig. 1

Images of dates. a A subset of 14 mature dates representing the 14 countries sampled in this study and reflecting diversity in phenotype. b Immature dates from two date samples 93-BSDN-MA and 91-BLZ-MA from the second sample collection. Each fruit is labeled with an ID featuring a letter that indicates its rank by extent of ripening relative to the remaining fruits within the sample (refer to methods). c Summary of the date metabolomics datasets measured by Metabolon: 10 fruits from the first sample collection were measured again with fruits from the second sample collection to account for batch measurement effect. All fruits from the first collection were considered mature (shown in green) whilst some fruits from the second sample collection displayed a phenotype indicative of ongoing ripening (refer to methods) and were therefore considered immature (shown in yellow). DS1 has the suffix ‘-bolon’ attached to distinguish it from the MetaSysX measurement of the same fruits from the first sample collection. The second sample collection was only measured by Metabolon

Fig. 2

PCA analysis of metabolomics data from mature dates. a PC1 scores from DS1-bolon and DS1-sysX are highly concordant. b & c PC1 scores plotted against PC2 scores for DS1-bolon and DS2-mature respectively. The color of the circular symbols indicates the corresponding date sample country of production and follows the country-color code on the geographical map shown on the top of the figure. The square symbols were added to indicate the median PC1/PC2 coordinates per country and follow the same color code. Countries are denoted by their ISO Alpha-2 international code. The US unique date sample from the first collection has been omitted to keep the geographical map simple. PC1 scores have been negated so that the order of the countries follows that on the map (West/East left/right respectively). With both datasets, a significant association between PC1 scores and the country of production, expressed as an ordinal variable (refer to methods), was found. PC2 from both datasets showed no significant association

Fig. 3

PC1 from DS2-mature is associated with the ripening process. a PC1 scores from DS2-immature. Fruits from varying stages of ripening from the same sample are shown on the same line. Each fruit is labelled with an identifier featuring a letter indicative of its extent of ripening relative to the other fruits within the sample as judged by eye. The ordering of the letters is well captured by the PC1 scores and occasional discrepancies occur when the fruits featured very similar PC1 scores. Density analysis of the PC1 scores, showing on top of (a) indicates that the fruits can be assigned to three developmental classes, denoted as class 1 (light green), class 2 (light pink) and class 3 (light blue) by increasing ripening maturity. b An OPLS-DA classifier trained on class 2 versus 3 was used to calculate class prediction scores for all DS2 samples including the batch1&2 samples which were measured in separate batches once with dates from the first sample collection and again with dates from the second sample collection. c A scatter plot of PC1 scores and OPLS-DA class prediction scores from the DS2-mature samples indicates a significant correlation

Fig. 4

The O2PLS-DA model for predicting the ripening states of DS1-bolon samples. a A scatter plot of the O2PLS-DA predicted scores versus the PC1 scores from DS1-bolon indicating a significant correlation level. b The O2PLS-DA class prediction scores (x-axis) for all 186 measured metabolic profiles listed sequentially on the y-axis within their respective datasets. The batch1&2 samples served (excluding sample 11) as the training set for the O2PLS-DA classifier. The DS2-immature samples are predicted correctly within their predefined development classes as initially revealed by the PCA analysis: class1 (light green), class2 (light pink), class3 (light blue). The symbols color code reflects the level of the dates endogenous sucrose level expressed in standard deviation units from the mean, calculated for each batch separately. Only samples with high sucrose level are labelled with their IDs for clarity. c Density plot of the O2PLS-DA class prediction scores for the DS1-bolon and DS2-mature datasets

Fig. 5

Heatmap analysis based on DS2-mature data. Showing the abundance level of metabolites arranged in biological classes by increasing PC1 loading values (y-axis) along date samples arranged by increasing PC1 scores (x-axis). Metabolite classes are shown to the left in different colours to reflect various biochemical phases of the ripening process in dates: (brown) early ripening Khalal, (green) ripening underway corresponding to Rutab and (red) over-ripening. The positive range of PC1 shows increased discolouration amongst dates many of which belong to the dry type (black framed rectangles). The soft type (highlighted in purple rectangles) is enriched at the negative range. Information on the dry/soft phenotype is variety specific and was collected from the literature where possible. Low moisture fruits and relatively moist fruits appear randomly scattered along PC1

Fig. 6

Standardized abundance levels of selected metabolites in DS2-bolon date samples ordered by PC1 scores. a Pheophorbide A, a marker of chlorophyll degradation. b 3-deoxyoctulosonate, a structural component of rhamnogalacturonan II species of pectin and a marker of cell wall hydrolysis. Samples with missing values were assigned a minimum value indicated by a red dashed line

Fig. 7

Boxplots of PC2 loading values arranged by metabolic class. a DS1-bolon, b DS2-mature. The classification of metabolites follows that developed for PC1 (refer to methods). For both datasets, metabolite classes sphingoids and lysophospholipids (pointed at with a red arrow) appeared to underlie the effect captured by PC2. Classes with less than three metabolites were not considered; these consisted of tannins and dipeptides for DS1-bolon and polyamines, methoxycinnamates and benzenoid VOCs, energy and amines for DS2-bolon. The star in each box indicates the median loading value per metabolic class