Molecular Authentication and Phytochemical Evaluation of Indigenous Germplasm of Genus Physalis for Sustainable Utilization

Abstract

Physalis species are used as an indigenous food and medicine in Kenya. However, species identification and an analysis of the health-promoting bioactive compounds and antioxidant properties are lacking. In this study, we report the molecular identification and mineral and phytochemical profiling of wild Physalis accessions. Leaf samples of 10 Physalis accessions were collected and used for species identification using nuclear ITS2 and plastid rbcL barcodes. Ripe fruits were collected from the same accessions and analyzed for mineral, total phenolic, tannin, and flavonoid contents, and antioxidant activities. The Physalis species were discriminated based on the ITS2 barcode and identified as Physalis purpurea. The genetic diversity, distance, and polymorphism of the ITS2 region of Physalis accessions were high due to the high rate of singleton and parsimony mutations. No genetic diversity, distance, or polymorphism was observed based on the rbcL barcode. The mineral content was significantly different (p < 0.05) for calcium, zinc, nickel, copper, and lithium among the Physalis accessions. No significant variation (p > 0.05) was found for phenolic acids or flavonoids, but the tannic acid content varied significantly (p < 0.05). DPPH free radical scavenging varied significantly (p < 0.05) among Physalis accessions. In conclusion, nuclear ITS2 was used to successfully identify the Physalis species of all the accessions as Physalis purpurea. The present study confirmed that Physalis purpurea has a significantly high mineral and phytochemical content and antioxidant activity. The findings from this study can be used to facilitate exploitation of Physalis purpurea in genetic breeding, their application in pharmaceutical, cosmetic, and nutritional value as well as conservation and sustainable use.

1. Introduction

Indigenous varieties adapted to a particular region are ideal resilient crops for climate change adaptation but are neglected and often lost due to the rapid domestication of commercial cultivars. Restoring such plant species would empower local farmers and provide huge economic and nutritional benefits. One such underutilized wild plant species is of the genus Physalis and belongs to the Nightshade (Solanaceae) family [1]. Physalis species are native to the Peruvian and Ecuadorian Andes region of South America; hence, it is referred to as the Peruvian gooseberry [2], although some are also native to Southeast Asia and Eurasia [3]. Studies of Physalis in China have identified five species including Physalis alkekengi, P. angulata, P. pubescens, P. peruviana, and P. minima and two variants of P. alkekengi [4]. Physalis species such as P. philadelphica, P. peruviana, and P. pubescens are grown in various parts of the world [5]. Physalis fruits are exported from several countries including Colombia, Australia, New Zealand, Great Britain, Zimbabwe, Kenya, Egypt, South Africa, Madagascar, and South East Asia [6,7]. The largest producer, consumer, and exporter of Physalis fruits is Colombia [7]. In Kenya, the fruits are seen in vast numbers as wild and self-propagating plants, commonly in farms during and after the harvesting of maize. Currently, there is growing commercial interest in this fruit crop because of its nutritional and pharmacological properties and health benefits. The key steps involved in the proper utilization of this indigenous plant species are accurate identification and authentication.

Taxonomic identification and morphological characterization are the most common methods of plant authentication, although they are limited by environmental or physiological factors and the developmental phase of the plant species [8]. Employing molecular tools such as DNA barcoding could be more successful in species identification. DNA barcoding requires a short universal DNA sequence that exhibits a sufficient level of variation to discriminate species [9,10]. The proposed plant DNA core barcodes from the Consortium for the Barcode of Life (CBOL) Plant Working Group comprise the chloroplast gene large subunit of ribulose bisphosphate carboxylase (rbcL) and matK with the trnH-psbA intergenic sequence and internal transcribed spacer (ITS), and a nuclear gene as the supplement barcode [11]. Chloroplast DNA barcodes such as matK and rbcL have been used in many phylogenetic and plant species identification analyses [12]. The nuclear internal transcribed spacer 2 (ITS2) barcode has also been demonstrated to exhibit 100% species identification and discrimination statistics in plants due to its high intra- and interspecific divergence [13]. Currently, there is lack of information on the genetic characterization of indigenous Physalis plants from the wild in Kenya.

The nutritional and phytochemical profiles of Physalis have been studied to a moderate level in the Andes [14]. The Physalis fruit contains fat and water-soluble vitamins (B-complex, C, A, E, and K), minerals (mainly phosphorus, magnesium, potassium, zinc, and calcium), sugars (e.g., sucrose, glucose, and fructose), fatty acids (palmitate, oleic, and gamma linoleic acid), phytosterols (sitosterol and stigmasterol), and fiber (pectin) [6,15]. The fruit pomace (skin and seed) contains 19.3% oil, 3.1% ash, 17.8% protein, 24.5% carbohydrates, and 28.7% crude fiber [14]. The phytochemicals found in Physalis include withanolides, physalins, carotenoids, phenolics, and flavonoids [15]. A review study states that the most studied phytochemicals are the polyphenolics, which have antioxidant properties and many health-related benefits [16]. The key polyphenolics include flavonoids, stilebenes, phenolic acids, coumarins, and tannins [17]. The Physalis plant’s high content of vitamins, minerals, and antioxidant phytochemicals gives it medicinal properties such as anti-inflammatory activity and this has been specifically determined for Physalis alkekengi species [18]. The characterization of the nutritional and bioactive properties of cultivated and wild fruits of Physalis peruviana growing in the northern Argentinian region identified several types of phytochemicals present in the plant, such as flavonoids and tannins [19]. However, the mineral composition, phytochemical profile, and antioxidant activities of wild fruits of Physalis growing in Kenya have not yet been characterized.

The aim of the current study was to identify and assess the rbcL and ITS2 gene barcodes to discriminate indigenous Physalis accessions collected from the forest. We also evaluated the mineral and phytochemical content, and antioxidant activities of ripe fruits to determine if they are nutrient-rich so that they could be used as sustainable resources for the development of biofortified crops and also promoted as a natural source of antioxidants.

2. Materials and Methods

2.1. Sampling of Plant Material

Leaves and mature fruits of Physalis plants were collected in April 2019 from Sorget forest in Londiani area of Kericho County, Kenya (Figure 1). The area is located at an elevation of 2528 m above sea level and latitude of 0.0684° S and a longitude of 35.5548° E.

The collected Physalis plant samples were identified by the taxonomist Mr. Patrick Mutiso and the samples were preserved in the University of Nairobi herbarium in the Department of Biology (Codes of Voucher Specimens: KP/UON2019/001- KP/UON2019/010). Ten Physalis plants were sampled for their fruits and leaves based on the availability and ripeness of the fruits. The maturity of the fruits was assessed based on the color of the fruit. Ripe fruits had a yellow to orange color. The leaves were used for the molecular identification of the plant species, while the fruits were used for the study of the nutritive value and functional attributes. The collected leaf and fruit samples were wrapped with aluminum foil, kept in an ice box and transferred to the Molecular Biology Laboratory in the Department of Biochemistry, University of Nairobi. The leaf samples were kept at −80 °C prior to genomic DNA extraction. The fruit samples were utilized immediately upon arrival at the laboratory for the extraction of phytochemicals and the determination of the mineral content.

2.2. Molecular Authentication of Physalis Plants

2.2.1. Isolation of Genomic DNA from Leaves of Physalis Accessions

Isolation of genomic DNA from leaves of Physalis accessions was performed using the Cetyl trimethylammonium bromide (CTAB) method [20]. RibonucleaseA (RNase, 0.6 mg/mL) was added to the DNA accessions followed by incubation at 37 °C in a water bath for 30 min to eliminate any contaminating RNA. The integrity of the extracted genomic DNA was verified using 0.8% (w/v) agarose gel stained with ethidium bromide (0.5 µg/mL) and viewed under UV transilluminator in Gel Doc^TM EZ Imaging System (BioRad, Hercules, CA, USA). DNA was stored at −20 °C until use in the molecular analysis.

2.2.2. Polymerase Chain Reaction (PCR) Amplification and Sequencing

Polymerase chain reaction (PCR) amplification was performed using the DNA barcoding primers rbcL and ITS2 (

Table 1. Oligonucleotide primers used for PCR amplification and optimum PCR cycling conditions.

Barcode Region	Primer Name	Primer Sequence (5′ to 3′)	PCR Conditions
ITS2	ITS2-F	CCTTATCATTTAGAGGAAGGAG	1 cycle of 94 °C 5 min; 30 cycles of 94 °C 30 s, 58 °C 45 s, and 72 °C 1 min; 72 °C 7 min
	ITS2-R	TCCTCCGCTTATTGATATGC
rbcL	rbcL-1-F	ATGTCACCACAAACAGAA	1 cycle of 94 °C 5 min; 30 cycles of 94 °C 30 s, 58 °C 45 s, 72 °C 1min; 72 °C 7 min
	rbcL-74-R	TCGCATGTACCTGCAGTAGC

). DNA amplification was conducted using a One Taq^® Hot start 2× master mix with standard buffer (New England Biolabs, Ipswich, MA, USA) following the manufacturer’s instructions. Amplification was conducted in a Veriti, 96-well Thermal Cycler (Thermo Fischer Scientific, Waltham, MA, USA). Optimization was performed in order to acquire the best conditions for PCR amplification. The annealing temperature for both primers was optimized at the following temperatures: 50 °C, 51 °C, 52 °C, 54 °C, 56 °C, and 58 °C. The best optimum cycling conditions for both primers were used for the PCR amplification of the DNA samples (Table 1). The amplicons were confirmed using 1% agarose gel stained with ethidium bromide (0.5 µg/mL) under a UV transilluminator in the Gel Doc^TM EZ Imaging System (BioRad, Hercules, CA, USA). Amplicons were cleaned using a gel clean up kit (Applied Biosystems, Thermo Fischer Scientific, Waltham, MA, USA) and sent for sanger sequencing at the University of Nairobi (UoN) Center of Excellence in HIV Medicine (CoEHM) using a 3730 s DNA analyzer (Thermo Fischer, Waltham, MA, USA).

2.3. Sequence and Phylogenetic Analysis

The sequences of each barcode were edited manually in the BioEdit software version 7.2.5.0 [21]. The edited sequences were compared with the available nucleotide sequences in the GenBank database. The sequences were blasted in the NCBI GenBank BLASTn database to determine the sequence homology with other deposited ITS2 and rbcL sequences (https://blast.ncbi.nlm.nih.gov/Blast.cgi; accessed on 10 February 2023). The identification of Physalis species was based on the least expected value (E-value), highest query coverage, and similarity percentage. The obtained sequences were also assembled and aligned using the MUSCLE algorithm. Multiple sequence alignment (MSA) of ITS2 and rbcL sequences in this study and the reference sequences retrieved from the NCBI database was performed using the MUSCLE software version 3.8 [22]. This MSA was used in the preparation of a phylogenetic tree. The ITS2 and rbcL sequences were also aligned separately using MUSCLE, and viewed and trimmed on Jalview version 2.11.2.6 to obtain uniform sequence lengths [23,24]. The MSAs performed separately for ITS2 and rbcL sequences were used in the genetic diversity, nucleotide polymorphism, neutrality test, and automatic barcode gap discovery (ABGD) analysis. All MSAs attained were compressed using ESPript 3 (http://espript.ibcp.fr; accessed on 12 February 2023) [25]. The ITS2 and rbcL sequences were submitted to NCBI GenBank through a web-based sequence submission tool and accession numbers were assigned.

Phylogenetic trees were constructed based on the Bayesian inference (BI) method using MrBayes version 3.2.7 (https://nbisweden.github.io/MrBayes/; accessed on 12 February 2023). Statistical analysis was performed using the posterior distribution of the model parameter, which was estimated using the Markov chain Monte Carlo (MCMC) method [26,27,28]. MCMC sampling was performed over 18,000,000 generations at a sampling frequency of 1000 and the first 25% (relburnin = yes burninfrac = 0.25) of samples were discarded when estimating the posterior probabilities of the trees. After 18,000,000 generations, the analysis was stopped when the average standard deviation of the split frequencies was less than 0.01 and tree parameters were summarized. The constructed phylogenetic trees were visualized and modified using the FigTree software version 1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/; accessed on 12 February 2023).

2.4. Analysis of Genetic Divergence

DNA divergence within Physalis accession populations based on ITS2 and rbcL sequences were determined using the DnaSP software version 6.12.03 [29]. The multiple sequence alignment (MSA) for Physalis accessions based on either the ITS2 or rbcL marker was uploaded into the software and various parameters for the divergence were determined. The number of polymorphic segregating sites (S), nucleotide diversity, and the total number of substitutions were assessed as outlined by the Jukes and Cantor algorithm on DnaSP.

2.5. Determination of Genetic Distance within Physalis Accessions

Intraspecific genetic distances and the overall mean distance of Physalis accessions based on the ITS2 and rbcL sequences were determined using the Kimura 2 parameter (K2P) model with the gamma distribution and a gamma parameter of 0.27 using MEGA version 11.0 [30]. Sequence genetic distance was determined using multiple sequence alignments for Physalis accessions based on ITS2 and rbcL markers.

2.6. Nucleotide Polymorphism and Neutrality Tests

DNA polymorphisms of the ITS2 and rbcL sequences were assessed in all the Physalis accessions. The DNA sequence Polymorphism (DnaSP) software version 6.12.03 was utilized in the DNA polymorphism analysis for ITS2 and rbcL sequences of all Physalis accessions. The DNA polymorphism parameters determined were polymorphic segregating sites, singleton and parsimony informative sites, the nucleotide diversity, and the average number of nucleotide differences.

Tajima’s neutrality test for both ITS2 and rbcL sequences of Physalis accessions were determined to estimate the frequency of mutations among species [31]. The Tajima’s neutrality test determined the Tajima D value among the ITS2 and rbcL sequences of Physalis accessions using the MEGA 11.0 software [32,33]. The analysis involved nine and ten ITS2 and rbcL sequences of Physalis accessions, respectively. The codon positions included were 1st + 2nd + 3rd + noncoding for the rbcL gene sequences. All ambiguous positions were eliminated for each sequence pair (pairwise deletion option) in both the analysis based on ITS2 and rbcL genes. There were a total of 399 and 614 positions in the final dataset for both the ITS2 and rbcL genes, respectively. The MSAs utilized in this analysis were similar those utilized for genetic diversity and DNA polymorphism studies based on ITS2 and rbcL sequences.

2.7. Analysis of DNA Barcoding Gap and Intraspecific Distance

In order to delimit the Physalis species based on their intraspecific divergence within a population, the automatic barcode gap discovery (ABGD) method described by [34] was utilized in this study. Multiple sequence alignments utilized in genetic diversity analysis were also utilized for the ABGD analysis of ITS2 and rbcL sequences of Physalis accessions. The ITS2 and rbcL multiple sequence alignments were separately inputted into the ABGD website (https://bioinfo.mnhn.fr/abi/public/abgd/abgdweb.html; accessed on 17 February 2023) and the distance analysis was performed based on the K80 Kimura measure of distance. The default value for the relative gap width (X) was set at 1.5. Moreover, p values of intraspecific divergence were set at a prior minimum (P_min) and prior maximum (P_max) divergence of intraspecific diversity of 0.001 and 0.1, respectively. Default settings were utilized for all other parameters.

2.8. Analysis of Mineral Content in Ripe Fruits

The analysis of macrominerals (calcium (Ca), magnesium (Mg), potassium (K), and sodium (Na)) and trace elements (iron (Fe), zinc (Zn), manganese (Mn), copper (Cu), lithium (Li), and nickel (Ni)) was performed according to the method described by [35]. All the analyses were performed in triplicate. Each fruit sample (1 g) was digested in 5 mL of nitric acid, which was made up to 25 mL using distilled water. The mixture was heated on a hot plate until a third of the volume was left, which was filtered with Whatman filter paper No. 1. The filtrate was appropriately diluted and analyzed for mineral elements using an atomic absorption spectrophotometer (AAS) (Shimadzu, Kyoto, Japan). The wavelengths used for the analysis of each mineral were as follows: Ca—422.42 nm; Zn—213.52 nm; Cu—324.53 nm; Na—588.88 nm; Mg—285.04 nm; Fe—248.23 nm; K—766.74 nm; Ni—231.90 nm; Mn—27.03 nm; Li—670.85 nm. The results were expressed in ppm (1 ppm = 1 mg/L) of a sample of dry weight (DW). All the experiments were carried out three times with different fruit accessions.

2.9. Determination of Phytochemical Content

2.9.1. Estimation of Total Polyphenol Content (TPC)

The estimation of phenol in fruit extracts was assayed using the Folin Ciocalteau method [36]. In a test tube with 2.25 mL of 10% Folin Ciocalteau reagent, 1 mL of filtrate of ethanolic fruit extract was added, mixed thoroughly, and allowed to settle at 23 ± 2 °C for 5 min. To the mixture, 2.25 mL of sodium bicarbonate solution (60 g/L) was added, vortexed, and incubated at 23 ± 2 °C for 90 min. The absorbance was measured at 725 nm using a spectrophotometer (Shimadzu, Kyoto, Japan). A blank was prepared using the same method, but the fruit extract was replaced with sterile distilled water. A standard curve was used to determine the phenol content using gallic acid. All the experiments were carried out three times with different fruit accessions. The TPC was assessed as mg/mL of gallic acid equivalents per gram of fruit extract.

2.9.2. Estimation of Total Tannin Content (TTC)

The content of tannins in the fruit samples was assayed using the Folin Ciocalteau method [36]. In a test tube, 0.25 mL of 10% Folin Ciocalteau reagent was added to 0.1 mL of ethanolic fruit extracts and vortexed. The mixture was allowed to settle at 23 ± 2 °C for 5 min, and then 1.25 mL of sodium hydroxide was added and the mixture was incubated at room temperature for 40 min. Absorbance was measured at 725 nm using a spectrophotometer. A blank was prepared using the same method, but the fruit sample was replaced with sterile distilled water. A standard curve was then prepared for the estimation of the tannin content from Physalis fruits using tannic acid. All the experiments were carried out three times with different fruit accessions. The TTC was assessed as mg/mL of tannic acid equivalents per gram of fruit extract.

2.9.3. Estimation of Total Flavonoid Content (TFC)

The determination of the flavonoid content in the fruit extracts was performed using the aluminum chloride (AlCl₃) colorimetric method [37]. In a test tube, 1 mL of ethanolic Physalis fruit extract was added to 4 mL of water and 0.3 mL of 5% sodium nitrate solution. The content was mixed thoroughly followed by the addition of 0.6 mL of aluminum chloride. The mixture was mixed thoroughly and incubated for 6 min at 23 ± 2 °C before the addition of 2 mL sodium hydroxide. A precipitate was formed on mixing, which was centrifuged and the absorbance of the supernatant was measured at 510 nm. A blank was prepared using the same method, but the fruit extract was replaced with sterile distilled water. A standard curve was prepared for the estimation of the flavonoid content using rutin. All the experiments were carried out three times with different fruit accessions. The TFC was assessed as mg/mL of rutin equivalents per gram of fruit extract.

2.10. Estimation of Antioxidant Activity

The antioxidant activity was measured using 2, 2-diphenyl-2-picrylhydrazyl (DPPH) and hydrogen peroxide radical scavenging in vitro assays. The DPPH radical scavenging (RS) assay was performed based on the radical degradation method described by [38] with some modifications. The sample extracts (0.5 mL) were mixed with 0.1 mM DPPH radical solution (0.3 mL) prepared in an ethanol solution. Color change from deep violet to light yellow was observed and the absorbance was measured at 517 nm using a UV-Vis spectrophotometer after 100 min of reaction in the dark. The blank was prepared using 3.3 mL of ethanol and 0.5 mL of the sample. A control was prepared using 3.5 mL of absolute ethanol and 0.3 mL of the DPPH radical solution and the absorbance was measured. The percentage inhibition of the DPPH radical of the sample extract relative to the control was used to determine the antioxidant capacity using the equation:

$$\mathrm{AA}\%=100-\left(\frac{\mathrm{Abs} \mathrm{sample}-\mathrm{Abs} \mathrm{blank}}{\mathrm{Abs} \mathrm{control}}\right)\ast 100$$

The hydrogen peroxide scavenging assay was performed using a method determined by [39] with a few modifications. In a test tube, 0.5 mL of the sample extract was mixed with 4 mL of 4 mM hydrogen peroxide solution prepared in 0.1 M phosphate buffer (pH 7.4). The mixture was incubated for 10 min at room temperature and the absorbance was measured at 230 nm using a UV-Vis spectrophotometer. A blank was prepared using phosphate buffer and sample extract. A control was prepared using phosphate buffer and hydrogen peroxide and the absorbance was measured. The hydrogen peroxide radical scavenging (HRS) activity percentage was calculated using the equation:

$$\mathrm{HRS}\%=\left(\frac{\mathrm{Abs} \mathrm{control}-\mathrm{Abs} \mathrm{sample}}{\mathrm{Abs} \mathrm{control}}\right)\ast 100$$

2.11. Statistical Analysis

The results for the antioxidant activity, and mineral and phytochemical content of the Physalis accessions obtained were reported as mean ± standard deviation (SD) using SPSS version 20 [40]. All the measurements were performed in triplicate. One-way analysis of variance (ANOVA) was performed using the statistical software SPSS version 20 [40]. The means from all analyses were separated by Tukey’s HDS multiple comparisons test at α = 0.05. A regression and correlation analysis was also performed to determine the impact of polyphenols on the antioxidant activity. Regression was analyzed using the statistical software SPSS version 20 [40] while correlation studies were analyzed using Microsoft excel version 2016.

3. Results

3.1. Amplification and Sequencing Success Rate

The PCR amplification results in both ITS2 and rbcL regions achieved success rates of 100% (

Table 2. Efficiency of PCR amplification and sequencing for Physalis accessions based on ITS2 and rbcL DNA barcode regions.

Barcode Region	Samples Tested (n)	Number of Amplicons Produced	Number of Sequences Produced	Amplification Efficiency (%)	Sequencing Efficiency (%)	Alignment Length (bp)	Mean Sequence Length (bp)	GC Content (%)
ITS2	10	10	9	100	99	663	561	61.1
rbcL	10	10	10	100	100	730	616	43.1

). The lengths of the ITS2 and rbcL sequences were in the range of 301–663 bp and 520–733 bp, respectively. The average lengths of ITS2 and rbcL sequences were 561 bp and 616 bp, respectively. The GC contents of the ITS2 and rbcL sequences were in the ranges of 60–65.2% and 42.7–43.9%, respectively. The average GC content of ITS2 sequences was 61.1%, which was significantly higher than that of the rbcL sequences (43.1%). The sequencing success rate was 99% and 100% for ITS2 and rbcL sequences, respectively (Table 2).

3.2. Species Discrimination Based on BLASTn Analysis

According to the BLASTn analysis of ITS-2 sequences, seven of the nine Physalis accessions were identified as Physalis purpurea, and one was identified as Physalis peruviana and one as Physalis aff philadelphica (Supplementary Table S1). The BLASTn analysis of rbcL sequences identified all the Physalis accessions as Physalis minima (Supplementary Table S1). The percentage identity for the nine Physalis accessions based on ITS2 sequences ranged from 86.00 to 94.4%. The percentage identity for 10 Physalis accessions based on rbcL sequences ranged from 99.86 to 100%. Eight out of the ten rbcL sequences of Physalis accessions gave a 100% sequence similarity with Physalis minima (NC_048515.1 from the GenBank). Two accessions (OQ507154.1 and OQ507156.1) were also identified as Physalis minima (NC_048515.1 from the GenBank) with a similarity identity of 99.59 and 99.86%, respectively (Supplementary Table S1).

3.3. Multiple Sequence Alignment

The multiple sequence alignment of combined ITS2 and rbcL gene sequences and retrieved sequences from the BLASTn analysis based on MUSCLE had a sequence length of 730 bp. The MSA is presented in Supplementary Figure S1. A high rate of substitution mutations was noted for the ITS2 sequences, while very few substitutions, deletions, and insertion mutations were noted for the rbcL sequences.

The MSA of ITS2 sequences of the nine Physalis accessions had a sequence length of 399 bp (Supplementary Figure S2). There was a high rate of substitution and deletion mutation within this MSA. A deletion point mutation was observed at position 10 of the MSA whereby, in Physalis accessions OQ372026.1 and OQ372023.1, the nucleotide thymine was deleted while all other accessions contained a thymine at this position. Another deletion point mutation was noted at position 46 of the MSA whereby guanine was deleted for the Physalis accessions OQ372023.1, OQ372026.1, OQ372027.1, and OQ372029.1. These Physalis accessions also had a deletion macrolesion mutation of eight nucleotides from position 179 to 187. Both transition and transversion point mutations were also identified in the alignment. At position 107 of this MSA, there was a transition point mutation for the Physalis accession OQ372023.1, whereby guanine replaced adenine. A transversion point mutation was observed at position 119 for the Physalis accession OQ372023.1 whereby guanine replaced the thymine found on all other sequences. Insertion mutations were not identified on this MSA. The multiple alignment of rbcL sequences of 10 Physalis accessions had a sequence length of 614 bp (Supplementary Figure S3). There were no deletions, insertions or substitution mutations noted in this MSA. All Physalis accessions had similar sequences with the key difference being the length of the sequences.

3.4. Physalis Species Identification Based on Phylogenetic Analysis

The phylogram tree was constructed based on Bayesian inference and the combination of ITS2 and rbcL sequences. Based on rbcL sequences, all the Physalis accessions were clustered together as indicated by colour red in Figure 2. The rbcL sequences did not form clades with their reference sequences on the phylogram and there was no species discrimination. The species names (Physalis minima) of the accessions indicated in the phylogram were based on the BLASTn analysis. Based on the ITS2 gene sequences, the Physalis accessions were identified with a percentage posterior probability of 100 as Physalis purpurea (Figure 2) and the sequences were deposited in GenBank with accession numbers OQ372021.1–OQ372029.1.

3.5. Intraspecific Divergence of Physalis Accessions

DNA divergence was determined based on the number of polymorphic (segregating) sites (S), nucleotide diversity, and the total number of substitutions. Based on ITS2 gene sequences, nucleotide diversity, the total number of nucleotide substitutions, and the number of polymorphic (segregating) sites were 0.27629, 134, and 124, respectively. There was no nucleotide diversity (0), nucleotide substitutions (0.00000), or polymorphic segregating sites (0) among the Physalis accessions based on rbcL gene sequences.

3.6. Genetic Distance within Physalis Accessions

The genetic distance within Physalis accessions based on ITS2 and rbcL gene sequences was assessed. The overall average genetic distance among the Physalis accessions based on ITS2 gene sequences was 1.67 ± 0.77, while there was no genetic distance based on rbcL gene sequences. The mean average genetic distance within (intraspecific) Physalis species was 1.67 ± 0.84 and 0 based on ITS2 and rbcL gene sequences, respectively.

3.7. Nucleotide Polymorphism and Genetic Diversity of Physalis Accessions

There were 124 segregating sites identified with ITS2 gene sequences, while no segregating sites were recorded for the rbcL gene sequences (

Table 3. DNA polymorphism of Physalis accessions based on ITS2 and rbcL markers.

	ITS2			rbcL
Polymorphic sites/Segregation sites (S)	124	Position in the gene	Variants	0	Positions in the gene	Variants
Singleton	21	49,58,90,107,116,117,118,119,120,125,138,139,144,158,162,164,172, 219,225,237,239	2	0		2
Parsimony informative sites	103	23,24,25,30,32,33,37,38,48,51,59,61,62,64,65,66,67,68, 69,71,7377,79, 81,82,84,85,88,91,93,94,95,97,99,100, 101,102,108,109,111,112,114, 126,129,132,136,140, 146,148,157,160,161,166,169,174,176,192, 193, 194,196,197,198,199,204,206,207,209,212,216,217,218,220,221,223, 227,228,229,230,232,234,235,240,241, 245,246,248,251,253,254, 255, 256,257,259   28,36,52,110,113,123,137,165,173,244	2             3	0		2             3
Nucleotide diversity (Pi)	0.27629			0.00000
Average number of nucleotide differences (k)	61.889			0.000
Sequence length (base pairs)	399			614
Number of sequences	9			10

). The lack of segregating polymorphic sites within a population is an indication that all plants within this population are identical. The high number of polymorphic segregating sites for the ITS2 Physalis gene sequences is an indication that this gene is highly diverse among the Physalis accessions and has undergone differentiation. There were 21 singleton and 103 parsimony sites identified among the segregating sites of Physalis accessions based on the ITS2 gene sequences.

3.8. Tajima’s Neutrality Test

Tajima’s neutrality test was performed for both the ITS2 and rbcL gene sequences to assess the selection and nucleotide diversity of the Physalis accessions. The number of segregating sites (S) for ITS2 and rbcL were 180 and 0, respectively. The Tajima values of the Physalis accessions based on the ITS2 and rbcL gene sequences were 0.779171 and 0, respectively. The Tajima D of the ITS2 sequences indicated a negative selection pressure in the Physalis population. The nucleotide diversity of the ITS2 and rbcL sequences based on Tajima’s test was 0.190894 and 0, respectively, indicating a variation in the ITS2 barcode region of Physalis accessions.

3.9. Genetic Differences and Barcoding Gap Analysis

Automatic barcode gap discovery (ABGD) results generated by the K80 Kimura measure of distance (K2P) based on the ITS2 gene sequences for Physalis accessions were used to assess the presence of a barcoding gap. The rbcL gene sequences for Physalis accessions were not able to provide results on barcoding as there was no variation in the sequences at an intraspecific and interspecific level. Based on the ITS2 gene sequences, all pairwise distances were ranked by increasing the distance values from 0.02 to 0.70 and three barcoding gaps were detected (Figure 3). The first and smallest barcode gap was observed between distances of 0.15 (15%) and 0.18 (18%) (Figure 3). The second and largest barcode gap was evident between the distances of 0.22 (22%) and 0.44 (44%) (Figure 3). The third barcode gap was found between the distances of 0.59 (59%) and 0.70 (70%).

3.10. Mineral Analysis

The mineral content of Physalis accessions was determined for macro- and microminerals (

Table 4. Macromineral content of fruits of Physalis accessions collected from the same environmental conditions. Data are expressed as mean ± SD of three independent accessions. CV: coefficient of variation; n = 3; means followed by single letters in a column differ significantly at a 5% level of significance.

Sample ID	ITS Accession Number in the GenBank	Ca (ppm)	Na (ppm)	K (ppm)	Mg (ppm)
L1	OQ507152.1	145.493 ± 6.087 aa	445.378 ± 51.116 aa	352.941 ± 24.758 aa	61.056 ± 93.957 aa
L2	OQ372021.1	58.700 ± 7.451 a	275.910 ± 18.080 aa	247.549 ± 8.947 aa	24.247 ± 20.009 aa
L3	OQ372022.1	121.803 ± 26.283 aa	175.070 ± 49.239 aa	497.549 ± 14.036 aa	13.604 ± 6.519 aa
L4	OQ372023.1	77.778 ± 2.618 aa	208.687 ± 81.942 aa	470.588 ± 11.725 aa	8.342 ± 6.455 aa
L5	OQ372024.1	81.132 ± 9.804 aa	263.306 ± 14.761 aa	811.275 ± 77.914 aa	71.532 ± 43.883 aa
L6	OQ372025.1	140.042 ± 26.804 aa	441.176 ± 21.091 aa	681.372 ± 37.395 aa	24.346 ± 22.820 aa
L7	OQ372026.1	131.447 ± 3.328 aa	456.583 ± 47.782 aa	450.981 ± 12.484 aa	19.381 ± 9.648 aa
L9	OQ372028.1	147.170 ± 23.966 aa	410.364 ± 25.673 aa	823.530 ± 24.961 aa	61.520 ± 48.887 aa
L10	OQ372029.1	133.962 ± 22.440 aa	380.952 ± 10.052 aa	414.216 ± 22.517 aa	21.169 ± 17.301 aa
	Mean	128.121 ± 20.976	377.46 ± 14.193	527.778 ± 26.526	33.911 ± 29.942
	CV	16.372%	39.000%	49.363%	88.296%

and

Table 5. Trace element content in fruits of Physalis accessions.

Sample ID	Accession Number	Fe (ppm)	Zn (ppm)	Ni (ppm)	Cu (ppm)	Li (ppm)	Mn (ppm)
L1	OQ507151.1	4.597 ± 3.081 aa	17.534 ± 3.369 aa	0.214 ± 0.000 aa	0.015 ± 0.006 aa	0.035 ± 0.022 aa	0.565 ± 0.258 aa
L2	OQ372021.1	6.398 ± 2.543 aa	7.618 ± 2.702 aa	0.166 ± 0.083 aa	0.158 ± 0.050 aa	0.079 ± 0.060 aa	0.491 ± 0.205 aa
L3	OQ372022.1	5.806 ± 2.864 aa	8.538 ± 4.987 aa	0.357 ± 0.124 aa	0.270 ± 0.079 aa	0.019 ± 0.004 aa	1.139 ± 0.467 aa
L4	OQ372023.1	5.780 ± 2.215 aa	84.663 ± 37.191 a	1.048 ± 0.527 a	0.427 ± 0.413 aa	0.203 ± 0.091 a	0.954 ± 0.423 aa
L5	OQ372024.1	6.317 ± 1.391 aa	7.771 ± 0.176 aa	0.167 ± 0.109 aa	1.322 ± 0.468 aa	0.021 ± 0.013 aa	2.102 ± 0.135 aa
L6	OQ372025.1	6.129 ± 1.268 aa	35.276 ± 24.020 aa	0.428 ± 0.189 aa	1.809 ± 1.523 a	0.010 ± 0.008 aa	1.250 ± 0.074 aa
L7	OQ372026.1	6.640 ± 1.341 aa	7.311 ± 1.240 aa	0.476 ± 0.289 aa	1.089 ± 0.161 aa	0.022 ± 0.010 aa	1.454 ± 0.158 aa
L9	OQ372028.1	8.145 ± 1.218 aa	37.270 ± 36.851 aa	0.929 ± 0.500 aa	1.072 ± 0.116 aa	0.014 ± 0.005 aa	1.954 ± 0.434 aa
L10	OQ372029.1	6.989 ± 0.492 aa	13.293 ± 2.609 aa	0.357 ± 0.124 aa	0.402 ± 0.522 aa	0.018 ± 0.000 aa	1.870 ± 0.181 aa
	Mean	6.311 ± 1.824	24.364 ± 12.572	0.460 ± 0.216	0.810 ± 0.371	0.047 ± 0.024	1.309 ± 0.482
	CV	28.902%	51.601%	46.957%	45.802%	51.064%	36.822%

Data are expressed as mean ± SD of three independent accessions. CV: coefficient of variation; n = 3; means followed by single letters in a column differ significantly at a 5% level of significance.

, Supplementary Figure S4). The highest macromineral content among the Physalis accessions was noted for potassium at a mean of 527.778 ± 260.526, while the lowest was the magnesium content at a mean of 33.911 ± 29.942 (Table 4). Sodium and calcium contents were at moderate levels in Physalis accessions with means of 377.46 ± 147.193 and 128.121 ± 20.976, respectively (Table 4).

The micromineral content of Physalis accessions was also determined (Table 5). The highest micromineral content was noted for zinc at a mean of 24.364 ± 12.572 (Table 5). The lowest micromineral content was noted for lithium at a mean of 0.047 ± 0.024 (Table 5). A moderate micromineral content was noted for iron, manganese, copper, and nickel (Table 5).

3.11. Phytochemical Content and In Vitro Antioxidant Activity

The ripened fruits of Physalis accessions were assessed for phytochemical (total phenolic acid, tannic acid, and flavonoid) content and antioxidant activities (

Table 6. Phytochemical content and radical scavenging activities of different indigenous Physalis accessions collected from the same environmental conditions.

Sample ID	Accession	TPC (mg GAE/g DW)	TTC (mg Tannic Acid/g DW)	TFC (mg Rutin/g DW)	DPPH RSA %	HRS Activity %
L1	OQ507152.1	0.092 ± 0.053 aa	0.158 ± 0.004 a	0.145 ± 0.073 aa	29.846 ± 13.537 a	64.131 ± 9.962 aa
L2	OQ372021.1	0.059 ± 0.040 aa	0.126 ± 0.045 aa	0.072 ± 0.020 aa	94.095 ± 0.182 aa	52.174 ± 9.962 aa
L3	OQ372022.1	0.024 ± 0.025 aa	0.099 ± 0.039 aa	0.070 ± 0.017 aa	75.862 ± 2.970 aa	30.435 ± 18.827 aa
L4	OQ372023.1	0.035 ± 0.026 aa	0.115 ± 0.067 aa	0.063 ± 0.040 aa	44.868 ± 6.556 a	6.159 ± 7.863 aa
L5	OQ372024.1	0.034 ± 0.008 aa	0.184 ± 0.015 a	0.096 ± 0.026 aa	67.539 ± 17.427 a	41.667 ± 12.120 aa
L6	OQ372025.1	0.081 ± 0.051 aa	0.047 ± 0.022 aa	0.071 ± 0.051 aa	73.088 ± 9.318 aa	59.420 ± 44.952 aa
L7	OQ372026.1	0.060 ± 0.016 aa	0.049 ± 0.039 aa	0.058 ± 0.034 aa	95.045 ± 7.149 aa	53.623 ± 26.721 aa
L8	OQ372027.1	0.082 ± 0.011 aa	0.061 ± 0.023 aa	0.097 ± 0.069 aa	96.156 ± 3.924 aa	8.696 ± 7.609 aa
L9	OQ372028.1	0.060 ± 0.027 aa	0.041 ± 0.015 aa	0.128 ± 0.038 aa	97.344 ± 2.263 aa	62.319 ± 8.786 aa
L10	OQ372029.1	0.080 ± 0.071 aa	0.072 ± 0.016 aa	0.152 ± 0.089 aa	89.666 ± 16.692 aa	39.131 ± 20.738 aa
	Mean	0.061 ± 0.033	0.095 ± 0.029	0.095 ± 0.046	76.351 ± 8.002	41.776 ± 16.754
	CV	54.098%	30.526%	48.421%	10.481%	40.104%

Data are expressed as the mean ± SD of three independent accessions. CV: coefficient of variation; n = 3; TPC: total phenol content; TTC: total tannin content; TFC: total flavonoid content; DPPH RSA: 2, 2-diphenyl-2-picrylhydrazyl radical scavenging activity; HRSA: hydrogen peroxide radical scavenging activity. Means followed by a single letter in a column differ significantly at a 5% level of significance.

and Supplementary Figures S5 and S6). The phytochemical contents and antioxidant activities did not change significantly (p > 0.05) among the Physalis accessions (Table 6). The TPC of different Physalis accessions did not change considerably, ranging from 0.024 ± 0.025 to 0.092 ± 0.053 mg GAE/g DW (Table 6). Physalis accessions L1 and L5 recorded significantly higher TTC compared with the other eight accessions (Table 6). The TFC of the different Physalis accessions did not change significantly and ranged from 0.058 ± 0.034 to 0.152 ± 0.089 mg Rutin/g DW. Two different chemical assays (DPPH and HRS) were performed to assess the antioxidant activity of Physalis accessions (Table 6 and Supplementary Figure S6). The DPPH and HRS values obtained for the antioxidant property did not show significant differences (p > 0.05) among the different Physalis accessions (Table 6). The DPPH and HRS among the different Physalis accessions ranged from 29.846 ± 13.537 to 97.344 ± 2.263% and 8.696 ± 7.609 to 64.131 ± 9.962%, respectively (Table 6).

3.12. Correlation Analysis between Phytochemical Contents and Antioxidant Activities

Correlation and regression studies were performed to assess the effect of each phytochemical compound (phenolic acid, tannins, and flavonoids) on the radical scavenging activity of Physalis accessions (

Table 7. Correlation and regression analysis of phytochemical content and radical scavenging activity of different Physalis accessions from the same environmental conditions.

Polyphenol Content	Correlation Coefficient (r) for DPPH RSA	Correlation Coefficient (r) for HRSA	ANOVA (p Value) for Hypothesis Testing of Slope of Regression Line for DPPH RSA	ANOVA (p Value) for Hypothesis Testing of Slope of Regression Line for HRSA
Phenolics	0.327	0.3599	0.928	0.307
Tannins	−0.6316	−0.0374	0.050	0.918
Flavonoids	−0.1150	0.2877	0.752	0.420

). DPPH radical scavenging was largely facilitated by the phenolic acid content, with a correction of r = 0.327, while flavonoids and tannins had a negative correlation (Table 7). Hydrogen peroxide radical scavenging was largely facilitated by phenolic acids and flavonoids at a correlation value of r = 0.3599 and 0.2877, while tannins had a negative correlation (Table 7). The regression analysis showed that all phytochemicals (phenolic acids, tannins, and flavonoids) had a linear relationship to the radical scavenging of DPPH and hydrogen peroxide radicals (Table 7).

4. Discussion

DNA barcoding is relatively fast in terms of species identification and discrimination [41]. DNA barcodes such as rbcL, matK, psbA-tnrH, and ITS2 are very efficient in identifying unknown plant species, with ITS2 being among the best DNA barcodes for species identification and discrimination [13,41]. Based on BLASTn and the phylogenetic analysis of ITS2 and rbcL gene sequences, the Physalis accessions used in the current study were all confirmed to belong to the genus Physalis.

The results of this study showed that the used barcode regions have different abilities of species discrimination and identification. ITS2 was proposed as a core barcode for seed plants by the Consortium for the Barcode of Life (CBOL) Plant Working Group [42]. It was clear that the Physalis accessions used in the current study were identified as Physalis purpurea based on ITS2 barcode. The phylogenetic tree was able to discriminate the Physalis accessions and had reliable clades with a posterior probability of 80%. Species discrimination based on the rbcL gene was not possible as there was no formation of clades on the Bayesian inference phylogenetic tree. The high conservation of the rbcL barcode gene in Physalis accessions makes it a less ideal candidate for DNA barcoding when compared to other barcode genes such as ITS2 [43]. The ability of ITS2 to emerge as a better barcode than rbcL is clearly supported in other studies on Physalis and other plants [2,13,41].

The rbcL barcode gene of Physalis accessions under study did not display genetic distance, diversity, or polymorphism. This is an indication that there were no genetic differences between the Physalis accessions used. Therefore, the rbcL barcode is highly conserved in some species of Physalis, which has also been reported in other studies [44,45]. The ITS2 barcode gene showed genetic variation among the Physalis accessions and a high nucleotide diversity of 0.27629 was observed. This has also been reported in the DNA barcoding and identification of Solanaceae plants [43]. The genetic distance observed among the Physalis accessions in this study based on ITS2 concurs with the results of previous studies where the ITS2 barcode region was reported to have a high genetic variation due to its high rate of mutation [46]. A high intraspecies variation was observed based on the ITS2 sequences, which supports the successful identification of Physalis accessions based on the ITS2 barcode region. The Tajima D value of Physalis accessions based on the ITS2 gene was 0.779171, an indication that the gene had a low level of low-frequency mutations and a balancing selection within the population [47]. Three barcode gaps were identified for the ITS2 gene sequences among Physalis accessions based on the ABGD method. The presence of barcode gaps is crucial for species delimitation and forms the basis for plant species identification and discrimination [48].

Commercial interest in plants of the genus Physalis has been rising worldwide due to its nutritional value, edible fruits, and the current and potential medicinal uses [2]. The Physalis accessions were investigated for mineral content and the analysis revealed that P. purpurea fruits are rich in potassium, sodium, calcium, and magnesium, which concurs with reports from other studies on the wild edible fruits of Physalis [49]. Based on these findings, this fruit can be used as an alternative for the daily intake of minerals, which are essential for human health. Potassium is important to the function of the cardiovascular system in humans [50]. Potassium/sodium balance is fundamental for the transmission of electrical impulses in the heart [51]. Magnesium is an important mineral in protein synthesis, oxidative phosphorylation, the regulation of body temperature and muscle contractions, and it is a cofactor for many enzymes [52]. Calcium is also another important element required for blood clotting, growth, bone formation, cell metabolism, and heart function [53,54]. The Physalis fruits also contain trace elements including zinc, iron, copper, nickel, lithium, and manganese. Low levels of iron and nickel in Physalis have also been reported in other studies [49,55]. Zinc is important in the catalytic activity of enzymes, cellular signaling, and facilitates the modification of the structures of DNA and RNA, proteins, and cellular membranes [56]. Iron is an essential vitamin that is required in small amounts for DNA synthesis, oxygen transportation, and the electron transport chain [57]. Copper is also an essential element that is required in small amounts for facilitating lung elasticity, neurovascularization, the metabolism of iron, adequate growth, energy metabolism, reactive oxygen species detoxification, and cardiovascular integrity [58,59]. The functions of nickel in animals are not well known [60]. However, in plants and bacteria it is required as a cofactor for the enzymes involved in growth and germination in plants [60]. Lithium is an essential element in the physiological regulation of mood [61]. Manganese is required as a cofactor for enzymes that perform cholesterol, carbohydrate, and protein metabolism [62]. The presence of minerals in plant accessions can be linked to their medicinal properties as well [63]. Our analyses show the potential of Physalis purpurea as an excellent mineral supplement in nutraceuticals. Though little attention is given to this wild fruit, our findings indicate a richness of nutrients and its potential application as a nutritional supplement.

The Physalis accessions were rich in phytochemicals such as phenols, tannins, and flavonoids, which have also been identified in the genus in other previous studies [64]. The levels of these different types of phytochemicals were different in the Physalis accessions, an indication of the existence of different cultivars within Physalis purpurea. Variation in phytochemical secondary metabolites in plants, such as phenolic acid and flavonoids, has been linked to environmental stress during growth and development [65]. Ecologically limiting factors like lighting, carbon dioxide, soil salinity, temperature, and soil fertility can affect the biochemical and physiological responses of plants and their secondary metabolite production [66]. Abiotic stressors lead to fluctuations in the chemical constituents of plants, selectively altering the content of secondary metabolites such as phytochemicals [65]. Soil salinity, an abiotic stressor for plants, has been shown to cause the accumulation of secondary metabolites such as flavonoids in plants as a response to nutritional imbalance, decreased photosynthesis, and the uptake of nutrients [67]. Flavonoid accumulation when plants are under stress due to the increased salinity of soils provides a curative effect for affected plants [68]. The tannin and flavonoid contents were the highest among the phytochemicals identified in the Physalis accessions studied. Previous studies observed the highest phytochemical content to be phenols followed by tannins and the lowest being flavonoids [69,70]. The concentration of phenols might have varied in this study as compared to others due to the geographical variations, environmental/abiotic stressors, the method of extraction of phenols, the sugars present, and the carotenoid and ascorbic acid contents [65,71,72]. The presence of phenols has been associated with antioxidant properties and, therefore, the ability to scavenge for free reactive oxygen species is facilitated by phytochemicals [69,73]. According to the radical scavenging activity assays conducted, the fruit extracts of Physalis accessions scavenged free radicals such as DPPH and hydrogen peroxide due to the presence of phytochemicals. Phenolic and flavonoid contents in plants are important for their antioxidant properties, which allow them to scavenge reactive free radicals by donating hydrogen atoms to the free radicals [74].

Correlation studies of the polyphenol content and the ability of polyphenols to promote radical scavenging have shown a linear relationship between phenolic and flavonoid contents in relation to radical scavenging capacity [75]. In this study, the correlation analysis showed a positive correlation between the phenolic content and the DPPH radical scavenging activity. However, a negative correlation was observed for the tannin and flavonoid contents (r = −0.1150) and the DPPH radical scavenging activity. This is an indication that the phenolic content of P. purpurea contributed more towards the DPPH radical scavenging activity than tannins and flavonoids. This concurs with similar studies on the role of phenolic content from the genus Physalis in DPPH radical scavenging [76]. Phenol and flavonoid contents showed a moderate correlation to the hydrogen peroxide scavenging capability. This concurs with other studies showing that phenol and flavonoid contents contribute towards hydrogen peroxide scavenging activity [72]. The presence of tannins in the Physalis accessions did not show any DPPH radical and hydrogen peroxide scavenging activities. However, tannic acid in other plant studies has been shown to have radical scavenging activity against DPPH radicals and hydrogen peroxide [76,77].

5. Conclusions

The Physalis accessions used in the current study were identified as Physalis purpurea based on the ITS2 barcode region. The high genetic variation among the Physalis accessions based on the ITS2 sequences allowed for the clear identification of Physalis species as Physalis purpurea. There was no genetic variation among the rbcL sequences of Physalis, an indication that the gene is relatively conserved. The study confirmed that the fruits of Physalis purpurea contained a high content of minerals, including calcium, sodium, magnesium, and potassium. The fruits were also rich in phenolic acids, tannins, and flavonoids, and exhibited antioxidant properties. The phenolic compounds and flavonoids were the major contributors to the radical scavenging activity of the Physalis purpurea fruits. Therefore, the underutilized Physalis purpurea can be used as an excellent source of antioxidants for the management of oxidative stress-induced human diseases.