1. Introduction
Plants are often subject to several environmental stresses which negatively influence their growth, development, and productivity. Drought is one of the most harmful abiotic stresses, particularly in the Mediterranean basin, where arid climate causes water scarcity and high evapotranspiration [
1,
2]. Severe droughts may directly reduce or eliminate yields, leading to a decline in crop productivity by up to 50–70%, which may affect 40% of the global population [
3]. Moreover, according to the World Health Organization, drought stress affects the livelihood of approximately 55 million people worldwide annually, and it is estimated that around 700 million people are at risk of displacement by 2030 because of droughts [
3]. Hence, better understanding the plants’ responses to environmental stresses is a key prerequisite for the improvement of their drought tolerance and yield under water deficit [
4]. Drought causes an array of morphological, physiological, biochemical, and molecular changes in plants [
5]. At the morphological level, it disturbs the appearance of plants by reducing the number of shoots, shoot length, leaf number, leaf area, and plant biomass, and also by changing their root length and biomass. At the physiological level, photosynthetic and transpiration rates tend to decrease as a result of stomatal closure under water deficit, which results in a low leaf relative water content (RWC). Moreover, they influence the photosynthesis by reducing leaf carbon dioxide assimilation, chlorophyll and carotenoid contents, and accessory pigments [
1,
5].
At the biochemical level, drought stress induces a high level of lipid peroxidation, lipoxygenase activity, aldehyde, proline, soluble sugar contents, and electrolyte leakage [
6,
7,
8]. At the molecular level, several regulatory gene products, such as CDPKs, MAPKs, HD-zip/bZIP, AP2/ERF, NAC, MYB, and WRKY, can cause changes in plants’ morphology or physiology by regulating signal transduction pathways or acting as transcription factors to regulate the expression of downstream genes and further enable plants to successfully survive under drought stress conditions [
5,
7]. To cope with the adverse effects of drought stress, plants trigger different adaptations, such as morphological and structural changes, the expression of drought-resistance genes, and the synthesis of phytohormones and osmotic regulatory substances to maintain growth and productivity under drought stress [
1,
5]. These adaptive strategies have evolved into three main survival mechanisms: stress avoidance, escape, and tolerance [
9]. Drought avoidance occurs when plants succeed in maintaining a satisfactory water status by increasing their water use efficiency [
10]; and this is also achieved by specialized adaptations in the plant’s architecture, such as the development or the reduction of specialized leaf surfaces to decrease the rate of transpiration and the increase in root length or density to use available water more efficiently [
4]. Drought escape is a classical adaptive mechanism which involves rapid plant development to enable the completion of the full life-cycle prior to a coming drought event [
11]. Drought stress tolerance is a result of the coordination of physiological and biochemical changes at the cellular and molecular levels: drought-tolerant plants are able to compensate decreased turgor using osmotic adjustment, or the production of metabolites that can help them repair drought-induced damage [
12,
13], or protein stabilization [
10] and by accumulation of an abundance of late embryogenesis proteins coupled with an efficient antioxidant system [
4]. Besides, the osmotic adjustment provided by the synthesis of osmoprotectants like proline, betaine, polyols, and soluble sugars may confer tolerance to drought by reducing the tissue osmotic potential and maintaining the water absorption from the external environment to maintain the cellular turgidity [
5,
12,
14]. The accumulation of osmoprotectants in plants is strongly correlated with the resistance or tolerance of plants to abiotic stresses under restricted water availability [
15,
16], since it contributes to adjusting the cellular osmotic potential, reducing the toxicity of reactive oxygen species, maintaining membrane integrity, and enzyme/protein stabilization [
1]. Hence, the identification of these compounds provides a promising connecting link that could bridge the gap between genotype and morpho-physiological traits. As osmotic regulating substances, soluble sugars and soluble protein content are considered as important indicators of the physiological status of plants related to drought tolerance [
17,
18]. Genes regulating the levels of osmoprotectants are highly stress-responsive and were among the first stress-inducible transcripts reported in the literature [
19]. In particular, the expression of these genes causes physiological and biochemical changes, i.e., an increase in sugar and soluble proteins contents, and changes in the composition of lipid membranes and the proline level [
20,
21]. Some of the regulatory genes of drought stress responses are transcription factors [
22] that can be strongly induced by water deficit stress and whose expression can regulate the expression of various genes associated with drought responses [
5].
Previous studies of the expression of
DREB1B genes were characterized in
Arabidopsis, soybean, rice, and other plant species [
23,
24], exploring the potential use of
DREB1B as candidate genes in responses to numerous stresses, mainly to salt and drought stress, although there is evidence for the regulation of their expression by drought in the roots of some plant species. Furthermore, a sequence analysis of these genes demonstrated that the candidate gene is a single-exon gene, while its duplication has generated a small multigene family during the evolution of species [
25].
Moreover, DREB proteins were shown to activate the expression of genes involved in osmoprotectant biosynthesis pathways, such as the LEA proteins or soluble sugars, which are related to improved salt and drought tolerance [
26]. These genes regulate osmoprotection, water and ion movements, a variety of functional and structural stress-induced proteins, signal perception and transduction, free radical scavenging, and many other components [
27].
Most legumes (Fabaceae) are sensitive to drought stress.
Medicago truncatula L. is an important forage leguminous plant of Mediterranean origin. It has several economic and ecological characteristics that made it a model forage crop in many farming systems and breeding programs for legume crops. Such characteristics include its small diploid sequenced genome (−500 Mb) [
28], its high efficiency of genetic transformation, a wide biological diversity, and its high conservation synteny with cultivated legumes such as
Lotus japonicus, alfalfa, soybean, and common bean [
29]. Additionally, the use of tolerant genotypes is one of the strategies to deal with water shortage in the agricultural sector. Selecting drought-tolerant cultivars by examining their performance under water deficit stress conditions will be useful in sustaining agricultural productivity under water limitations [
30]. Since plant performance is influenced by physiological and biochemical traits, these traits can be used as a tool to identify, screen, and select drought-tolerant plants.
In this context, the objective of the present study was to compare the effect of drought stress on plant growth and development, the antioxidant activity, and the osmoprotectant contents in the four lines of M. truncatula, aimed at selecting tolerant lines that can grow and yield satisfactorily in drought-prone areas. Moreover, an expression profiling of MtDREB1B in response to osmotic stress was carried out to provide insights into the molecular basis of drought tolerance mechanisms mediated by this gene in legumes.
4. Materials and Methods
4.1. Plant Material and Experimental Conditions
Four lines of M. truncatula, including two Tunisian lines TN1.11 and TN6.18, the reference line Jemalong A17 (JA17) from the Australian collection, and one Moroccan line A10 were used. The seeds collected from the pods of the selected lines were scarified using sandpaper Q60 to lift the integumentary inhibition, incubated in darkness at 4 °C for 72 h, and then transferred at 21 °C during 24 h for germination.
The germinated seeds were transplanted into black two-liter pots (Height 13.2 cm, Diameter 16.7 cm) of a sand and compost mixture (3:1. v/v) kept in a controlled growth chamber at the Center of Biotechnology of Borj Cedria, Tunisia, at a temperature of 24 °C (day) and 18 °C (night), a relative humidity of 60–80%, and a photoperiod of 16/8 h (day/night).
The plants were watered every 2 days with a Fahräeus nutrient solution [
68] until the sixth leaf stage, and then they were subjected to osmotic treatments (control: 100% field capacity (FC), 30% FC, and 100 mM NaCl). Six replicates per line and per treatment were used. In order to control the water content in the pots, weighing was carried out for each pot every two days, after which the plants were watered to maintain levels of 100% and 30% FC. Furthermore, osmotic stress (induced by 100 mM NaCl) was applied to plants as described by Hdira et al. [
32].
4.2. Growth Parameter Measurements and Physiological Assays
Several morpho-physiological parameters related to aerial parts and roots were measured for these four lines of M. truncatula at the flowering stage. They included the number of axes, length of stems, number of leaves, shoot fresh weight, shoot dry weight, length of roots, root fresh weight, root dry weight, ratio of root dry weight and aerial dry weight (RDW/ADW), and relative water content (RWC).
For the dry biomass measurement, the plant material was dried in an oven at 65 °C for 48 h.
The relative water content (RWC) was estimated as follows:
where LFW, LDW, and LTW are the fresh, dry, and turgid weight of leaves, respectively.
For each line, four leaves were excised from plants under the three treatments, immediately weighed (LFW), and then floated overnight in water to gain turgidity. Turgid leaves were then weighed (LTW) and dried at 80 °C for 48 h.
4.3. Biochemical Analyses
Malondialdehyde (MDA), soluble sugars, and protein contents were determined, in the leaves and roots of the tested lines under the three treatments, as described by Hdira et al. [
32]. Three replicates per line and per treatment were used. Lipid peroxidation was quantified as MDA content and was determined according to the method of Verma and Dubey [
69] by measuring the absorbance of supernatant at 532 nm, and the value for non-specific absorption at 600 nm was subtracted.
The soluble sugar content was estimated based on the reliable colorimetric method described by Yemm and Willis [
70] using a solution of ethanol with a concentration of 80% with anthrone–sulfuric acid. The concentration of total proteins was estimated based on the Bradford protocol [
71] using bovine serum albumin as a standard.
4.4. Database Search and Identification of DREB1B in M. truncatula
To better understand the specific response of
M. truncatula lines, under osmotic stress conditions, we selected one of the members of the
MtDREB family, namely
DREB1B. The expression of this gene was analyzed using qRT-PCR in four contrasting lines, namely TN6.18 and JA17 (tolerant lines), TN1.11 (a moderately tolerant line), and A10 (sensitive line) in different plant parts (leaves, stems, and roots). The
DREB1B data in
M. truncatula were obtained from the
Medicago Hapmap PHYTOZOMEv13 database (
https://phytozomenext.jgi.doe.gov/info/Mtruncatula_Mt4_0v1, accessed on February 2016) and NCBI Blast+2.2.28 (
http://blast.jcvi.org/Medicago-Blast/index.cgi, accessed on February 2016) by using search queries for the “
DREB1B” and “
Medicago truncatula” keywords. The results of the search were used on blast against the
M. truncatula genome (
M. truncatula Genome Project v4.0;
http://www.jcvi.org/medicago/, accessed on February 2016) [
72] with the parameter values ≤ 1E
−3 and more than 80% of coverage. We used the Pfam database (
http://pfam.xfam.org/, accessed on February 2016) [
73] to confirm the reliability of the candidate gene
DREB1B based on the presence of a conserved AP2 domain.
4.5. RNA Extraction, cDNA Synthesis, and RT-qPCR Analysis
The total RNA extraction was from different tissues of the studied lines, as described by Zeng and Yang [
74]. The evaluation of the total extracted RNA and cDNA synthesis was performed as described by Hdira et al. [
32]. The quantification of the level of
DREB1B transcripts in the different tissues of plants under control treatment and stress conditions was carried out using quantitative real time and was detected with SYBR Green (Roche, Mannheim, Germany) as described by Hdira et al. [
32]. Three replicates per line and per treatment were used in all analyses.
4.6. Statistical Analyses
The obtained data were analyzed using a three-way ANOVA, with repeated measures using SPSS statistical software (version 17.0 SPSS Inc., Chicago, IL, USA). Only traits showing a significant interaction of line × treatment were retained for the remaining statistical analyses.
A comparison of the means of the analyzed parameters was performed using the Duncan’s Multiple Range Test at 5% level of probability.
The broad-sense heritability (
H2) of measured parameters was estimated as the ratio of genetic variance to the sum of genetic (Vg) and environmental (Ve) variances [
75]:
The phenotypic correlations between the measured traits for
M. truncatula lines under control and drought stress were estimated by calculating the Pearson correlation coefficient (r) using Proc Correlate in the SPSS software. The significance level was set at 0.05 and adjusted for multiple comparisons by Bonferroni correction [
76].
The drought susceptibility index (DSI) of each trait was calculated to identify genotypes differing in their response to drought.
To analyze the responses of the studied lines under the two treatments (control and drought stress), the DSI values were subjected to a hierarchical cluster analysis (HCA) using XLSTAT software (Version 2014.5.03. Addinsoft, Paris, France).