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A comprehensive evaluation of the morpho-biochemical and chemical constituent profiles in various wild mushroom species: Investigating their potential benefits and limitations
* Corresponding author E-mail address: nawroz.tahir@univsul.edu.iq (N Tahir)
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Received: ,
Accepted: ,
Abstract
Edible wild mushrooms contain substances that are nutritionally and biologically important for human consumption. There is a growing trend in the use of functional foods and traditional medicines derived from macrofungi owing to their numerous health benefits and rich nutrient content. However, there remains a substantial gap in detailed scientific knowledge. This study aimed to analyze the morpho-biochemical and chemical composition profiles, as well as evaluate the possible health benefits and risks of the biochemical constituents in cultivated and wild edible mushroom species collected from the Iraqi Kurdistan region. Significant variations were observed among the studied species in the morpho-biochemical characters. Amanita crocea (73.74 g), Amanita lividopallescens (58.54 g), and Amanita vittadinii (60.57 g) exhibited the highest mushroom weights. Pleurotus eryngii had the largest cap diameter (10.70 cm vertical, 9.04 cm horizontal). Wild species showed significantly higher biochemical traits, except for moisture content (MC). The chemical composition profiles varied among the species. Several bioactive compounds with health and pharmaceutical properties have been identified. Cultivated species contained the lowest number of compounds. A. lividopallescens had the highest concentrations of 9-octadecenoic acid (16.56%), 13-octadecenoic acid-methyl ester (11.15%), ergosterol (14.62%), and hexadecanoic acid-methyl ester (10.13%). Multivariate analysis grouped the 11 species into three major clusters. Nine potentially harmful compounds were detected in eight species. The study concluded that substantial variations existed in the traits examined among mushroom species. Wild species demonstrated superior biochemical traits and chemical compositions compared with cultivated mushrooms. By emphasizing research and cultivation methods, the potential of mushrooms as crucial components of nutrition and medicine can be realized, positively impacting health outcomes and contributing to sustainable agricultural practices.
Keywords
Bioactive content
Clustering analysis GC/MS
Macrofungi
Medicinal uses
Morphometric analysis
Nutritional values
1. Introduction
Mushrooms are interesting flowering structures of specialized fungi that possess enormous fruiting bodies and have complex development (Joseph B. Morton, 2021; Terry J. Gentry et al., 2021; Zhao, 2023). Mushrooms are members of the fungi kingdom and are referred to as macrofungi. All these organisms exist in different terrestrial biomes and are best exhibited in forests, where they have a functional abundance coupled with numerous important ecological functions. Various types of mushrooms have been known to establish symbiotic relationships with plants, in which case they are useful, and they also have important functions as coprophilic fungi, where they decompose organic materials and nutrients (Dance, 2017). Although cultivated mushrooms have a large following, wild mushrooms have a unique appeal and potential for enormous growth in the food industry (Barua et al., 2024; Zhao, 2023). Almost all wild mushrooms are deemed useful to humans, are accepted as being very beneficial to the immune system, and have powerful antioxidants (Ao and Deb, 2019; Sun et al., 2017). Certain species of mushrooms can be cooked in a wide variety of recipes, although many fungi are extremely poisonous. There are also other types of mushrooms that are known to be psychoactive, which means that they can change the recipient’s state of mind or do some other form of harm to humans or other organisms (Ab Rhaman, Siti Maryam Salamah et al., 2021; Mattos-Shipley et al., 2016).
The structure and form of mushrooms have set the ground for their name and classification, and the features of the types of mushrooms are greatly affected by their habitat. Differentiation between mushroom types has focused on morphological traits, and the morphological variation for some mushroom cultivars is variable and depends on several environmental factors, which complicate accurate characterization. Wild mushrooms also tend to be more heterogeneous than cultivated ones. Such genetic heterogeneity can be established using molecular markers and population genetic analysis, which assist in understanding the population structure and evolution of mushrooms. Thus, there appears to be a wide gap in scientific estimations regarding the classification and inventory of wild fruiting bodies, particularly those from tribal areas, for sustainable development initiatives (Zhang et al., 2021).
The chemical characteristics were offered as supplementary criteria to better delineate species that have received more attention than before. The amount of phenolic and flavonoid compounds found in mushrooms serves as a reason for the quantity of antioxidants present within their bodies. These substances greatly increase the nutritional value of mushrooms, but they can also be used for the treatment of ailments, such as inflammation and cancer (Latif et al., 2024). Isolation and quantification of bioactive metabolites from wild mushrooms can be achieved using an analytical method known as gas chromatography/mass spectrometry (GC/MS). Several compounds with antiviral, anticancer, and antimicrobial activities, including fatty acids, phenols, and other secondary metabolites, have recently been isolated from mushrooms using GC/MS (Fogarasi et al., 2024; Rijia et al., 2024).
Iraqi Kurdistan has a variety of wild mushrooms, but they have been relatively less studied. To the best of our knowledge, no study has demonstrated the diversity and health benefits of wild mushrooms based on their biochemical profiles. Despite the numerous benefits of wild mushrooms, little is known about their biochemical properties and health risks. As a hypothesis for this study, we aimed to determine whether positive and negative effects can be discerned in wild mushrooms by analyzing their metabolic profiles. Understanding chemical makeup enables the use of wild mushrooms as food or bioactive resources and supports local economies in gastronomy and healthcare. The diverse applications of these resources would encourage improved habitat conservation and management.
In this study, we analyzed the genetic variation at levels of morpho-biochemical and chemical composition in a wild mushroom collection from different regions of Iraq’s Kurdistan and evaluated the possible health benefits and risks of its biochemical constituents. This study will help in the appropriate selection of mushrooms that researchers are interested in and that are believed to possess bioactivity and need to be dealt with sensitively to prevent harm. In summary, the combination of GC/MS profiling, genetic diversity measurement, and analysis of the other components, such as sugars, proteins, phenolics, and flavonoids, provides a more complete understanding of wild mushrooms. This sophisticated exploration contributes greatly to our understanding of the biological and ecological significance of mushrooms and widens their importance as bioactive agents in medicine and other sciences. More work in this direction must be done to understand the full potential of wild mushrooms and to consolidate their preservation.
2. Materials and Methods
2.1 Mushroom collection
During the late winter of February 2024, fruiting bodies were gathered from various mushroom species from different locations in the Kurdistan region of Iraq. The collection comprised 10 wild mushroom varieties and one cultivated species, as detailed in Table 1 and Fig. 1. Throughout the collection process, specimens were stored in bags and transported in a cooled container. Subsequently, they were refrigerated at 4°C upon arrival at the lab. Following the measurement of phenotypic characteristics, fresh fruiting bodies were processed for biochemical analysis by grinding 5 g samples using liquid nitrogen.
| Habitat | Species | Accession number | Location of collection | Latitude | Longitude |
|---|---|---|---|---|---|
| Wild | Agrocybe aegerita | PQ679358 | Qaladiza | 36.1809 | 45.1241 |
| Agrocybe dura | PQ680084 | Qaladiza | 36.1809 | 45.1241 | |
| Agaricus campestris | PQ679044 | Qaladiza | 36.1809 | 45.1241 | |
| Amanita crocea | PQ686237 | Dukan | 35.9496 | 44.9621 | |
| Pleurotus eryngii | PQ681292 | Dukan | 35.9496 | 44.9621 | |
| Amanita lividopallescens | PQ686317 | Zewe | 35.7459 | 45.2533 | |
| Pleurotus columbinus | PQ686965 | Zewe | 35.7459 | 45.2533 | |
| Agaricus pseudolutosus | PQ720781 | Ranya | 36.2391 | 44.8855 | |
| Amanita vittadinii | PQ721310 | Halabja | 35.1773 | 45.9857 | |
| Agaricus litoralis | PQ682616 | Basneh | 35.8890 | 45.5828 | |
| Cultivate | Agaricus bisporus | PQ895553 | Sulaimani Center-Farm | 35.5558 | 45.4351 |
- Fruiting bodies of 11 mushroom species were collected from different regions.
2.2 Morphological measurements of mushroom species
Measurements were taken for several characteristics of the samples (five replicates per sample), including stalk length, cap dimensions (vertical and horizontal), and fresh weight. A measuring ruler was employed to document the stalk length and cap diameter, and the results were recorded in centimeters. Stalk length was determined by measuring the distance from the ground level to its junction with the cap gill.
2.3 Biochemical measurement of mushroom samples
To determine the percentage of dry matter (DM) in the fresh fruiting body, a 10 g sample was prepared by chopping it into smaller pieces. The samples were kept in an electric oven and dried to a constant weight at 55 ± 1°C (Tahir et al., 2023b; Tahir et al., 2022). Three replicates were used for each sample. DM percentage was calculated using the following equation:
After calculating the DM of the different samples, the moisture content (MC) was computed with three replications using the following equation:
Diverse biochemical parameters were evaluated, using 0.10 g of freshly ground material from each mushroom species. The tissue samples were incubated with 1 mL of 80% methanol solution overnight and subsequently centrifuged at 10,000 rpm for 10 min. The supernatant obtained after centrifugation was used for biochemical analyses. These biochemical parameters included total phenolic content (TPC) (μg gallic acid/g tissue fresh weight), total flavonoid content (TFC) (μg quercetin/g tissue fresh weight), antioxidant activity, 2,2-diphenyle-1-picrylhydrazyl (μg trolox/g tissue fresh weight), and soluble sugar content, SSC (μg glucose/g tissue fresh weight). The methodologies for such biochemical assessments have been outlined in our previous study (Ahmad et al., 2020; Lateef et al., 2021; Tahir et al., 2024; Tahir et al., 2023a). To determine the protein (PC) relative to the fresh weight of the tissue, a fresh powdered sample (0.5 g) was prepared and mixed with 10 mL of 0.01N NaOH, followed by 20 min incubation in an ice bath. The samples were then centrifuged at 10,000 rpm for 15 min at 4°C. PC was quantified using the Lowry method (Walker, 1984; Waterborg and Matthews, 1984). For each measurement, three replicates were used per sample.
2.4 Chemical composition profile of methanolic mushroom extracts
The chemical components of the mushroom extract were identified using an Agilent 7890 B gas chromatograph and Agilent 5977 mass spectrometer (MSD, USA). The gas chromatograph was equipped with a splitless injector and an HP-5 asymmetrical methyl siloxane coated column (30 m × 0.25 mm × 0.25 µg), as previously described Tahir et al. (2022). With the Mass Hunter GC/MS Acquisition software and the Mass Hunter qualitative program scanning fragments in the range of 35 m/z to 650 m/z, the mass spectrometer was functioned. The retention indices of the extracts of various species were determined by comparing them to the recognized constituents listed in the NIST library (2005). The constituents’ peak area concentrations were computed using GC peak areas as the basis for calculation.
2.5 Statistical analysis
Significant differences (p ≤ 0.05 and p ≤ 0.01) among mushroom species were analyzed by one-way ANOVA with randomized complete block design (RCBD) and Duncan’s new multiple range tests using the XLSTAT software version 2022.3.1 (Addinsoft, New York, NY, USA). Multivariate and correlation analysis were performed using the JMP software version 18 (SAS Institute Inc., Cary, NC, USA). XLSTAT software version 2022.3.1 was used to generate the bar and radar charts.
3. Results
3.1 Morphological variation in mushroom species
Morphometric features, including the fresh weight of the sample (WS), stalk length (LS), cap vertical diameter (VDH), and cap horizontal diameter (HDH), were measured for selected mushrooms from the Iraqi Kurdistan region (Table 2). Mean comparison results showed significant differences among the 11 species. The measured characters ranged from 6.36 g (Agaricus campestris) to 73.74 g (Amanita crocea), from 2.37 cm (Agaricus bisporus) to 10.46 cm (Amanita lividopallescens), from 2.83 cm (Agaricus bisporus) to 9.12 cm (Amanita crocea), and from 4.27 cm (Agaricus litoralis) to 9.04 cm (Pleurotus eryngii) for WS, LS, VDH, and HDH, respectively
| Species | WS (g) | LS (cm) | VDH (cm) | HDH (cm) |
|---|---|---|---|---|
| Amanita crocea | 73.74 ± 1.50a | 10.28 ± 0.67a | 9.12 ± 0.78ab | 7.68 ± 0.72ab |
| Amanita vittadinii | 60.57 ± 1.88a | 6.84 ± 0.34b | 9.05 ± 0.73ab | 7.55 ± 0.63abc |
| Pleurotus eryngii | 35.41 ± 1.66ab | 5.54 ± 0.61bc | 10.70 ± 0.69a | 9.04 ± 0.57a |
| Amanita lividopallescens | 58.54 ± 1.01a | 10.46 ± 0.76a | 7.07 ± 0.51bc | 6.77 ± 0.37abc |
| Pleurotus columbinus | 42.68 ± 1.11ab | 4.61 ± 0.73bc | 7.63 ± 0.90abc | 6.44 ± 0.41abc |
| Agaricus pseudolutosus | 13.02 ± 0.74b | 3.29 ± 0.37c | 7.29 ± 0.84abc | 6.77 ± 0.26abc |
| Agrocybe dura | 11.04 ± 1.01b | 6.07 ± 0.74bc | 5.67 ± 0.53bcd | 4.78 ± 0.33bc |
| Agrocybe aegerita | 8.18 ± 1.03b | 5.41 ± 0.86bc | 4.83 ± 0.37cd | 4.79 ± 0.31bc |
| Agaricus litoralis | 28.07 ± 1.01b | 4.03 ± 0.61c | 4.66 ± 0.28cd | 4.25 ± 0.19c |
| Agaricus bisporus | 27.05 ± 0.89b | 2.37 ± 0.07c | 2.83 ± 0.08d | 4.91 ± 0.27bc |
| Agaricus campestris | 6.36 ± 0.47b | 2.81 ± 0.09c | 5.67 ± 0.31bcd | 4.61 ± 0.28bc |
WS, fresh sample weight; LS, stalk length; VDH, cap vertical diameter; HDH, cap horizontal diameter. Distinct alphabetic characters indicate statistically significant variance among the mean values (five replicates per species), as determined by Duncan’s Multiple-Range Test (p ≤ 0.05). Each value represents the mean ± standard error.
3.2 Relationship among mushroom species using morphometric traits
Hierarchical cluster analysis (HCA), principal component analysis (PCA), and scatter plot matrix were applied to search for similarities and hidden structures among samples. The results from the three approaches summarize the three clusters (Fig. 2). The first cluster (red color) includes three species from the genus Amanita: A. crocea, A. vittadinii, and A. lividopallescens (Figs. 2a, b, and d). The second cluster (green color) included three species: P. columbinus, P. eryngii, and A. pseudolutosus. The last group (blue color) comprises five species: A. dura, A. aegerita, A. litoralis, A. bisporus, and A. campestris. The first two PCA components explained 92.4% of the variability, whereas all the factors analyzed contributed significantly to the differentiation of the first component. From the analysis, it appears that the group 1 samples, which are three species of Amanita with high WS and LS values, had a positive loading on component 1, which was in the upper right quadrant of the plot, whereas the group 2 samples had larger cap diameter values (Figs. 2c and d). The largest distance measured (4.77) was between A. dura and A. crocea, and the smallest (0.32) was between A. dura and A. aegerita (Fig. 2e). The variation among the three groups accounted for by the HDH trait was the greatest (80.73%), followed by the WS trait (80.50%). In contrast, LS (71.56%) and VDH (71.67%) showed the least variation among the three groups (Fig. 2f). As shown in Fig. 2d, the four morphometric features were not strong enogh to completely separate the three groups.
- Relationships among mushroom species based on morphometric features. (a) Clustering of species using the AHC method; (b) Clustering of species using PCA plot; (c) Distribution of studied traits using PCA method; (d) Grouping of mushroom species using scatter plot; (e) Genetic distance among mushroom species; (f) Variation percentage explained by each trait for separation of the three groups. AHC: Agglomerative hierarchical clustering
3.3 Assessment of bioactive content differentiation in mushroom species
The present study results showed that the approximate composition of 11 mushroom species is presented in Table 3. All biochemical traits were observed, and a statistically significant difference was detected among all 11 species. In terms of fresh weight, TPC had a broad range of 121.89 to 253.85 µg/g. In this study, A. litoralis, A. aegerita, and A. campestris had the highest TPC levels, with TPC values of 253.85, 237.94, and 232.06 µg/g, respectively. A. dura on the other spectrum registered a 121.89 TPC. Antioxidant activity (DPPH) ranged from 237.84 to 575.92 µg/g. A. litoralis exhibited the highest DPPH activity at 575.92 µg/g, whereas A. dura exhibited the lowest DPPH activity of 237.84 µg/g. All mushroom species showed TFC ranging from 16.40 to 44.63 µg/g. A. bisporus recorded a TFC of 16.40 µg/g, whereas A. pseudolutosus, A. aegerita, and A. vittadinii recorded 44.63, 40.70, and 40.47 µg/g of TFC, respectively. The highest MC recorded was 94.17% for A. bisporus. In our comparison, the proportion of DM ranges from 5.83 to 11.92%. The highest MC (54.12%) was obtained for A. campestris, whereas the lowest MC (5.83% and 6.19%) was obtained for A. bisporus and A. pseudolutosus, respectively. Minor variations in protein content (PC) and soluble sugars (SSC) were observed among the different mushroom species. The highest levels of PC and SSC were detected in A. crocea (5.01 mg/g) and P. eryngii (1.12 µg/g), respectively.
| Species | TPC (µg/g FW) | DPPH (µg/g FW) | TFC (µg/g FW) | MC (%) | DM (%) | PC (mg/g FW) | SSC (µg/g FW) |
|---|---|---|---|---|---|---|---|
| Agaricus litoralis | 253.85 ± 2.13a | 575.92 ± 3.27a | 34.81 ± 1.44ab | 88.73 ± 1.79c | 11.27 ± 0.52a | 4.79 ± 0.48a | 0.71 ± 0.09b |
| Agrocybe aegerita | 237.94 ± 2.53ab | 411.59 ± 2.56ab | 40.70 ± 1.78ab | 90.05 ± 1.11bc | 9.95 ± 0.43ab | 4.29 ± 0.56a | 1.00 ± 0.08a |
| Amanita lividopallescens | 142.61 ± 1.09ab | 398.07 ± 2.72ab | 35.60 ± 1.23ab | 92.61 ± 1.72ab | 7.39 ± 0.52bc | 4.70 ± 0.53a | 0.79 ± 0.06b |
| Agaricus pseudolutosus | 158.30 ± 1.56ab | 284.35 ± 1.29b | 44.63 ± 1.99a | 93.81 ± 1.01a | 6.19 ± 0.42c | 4.57 ± 0.44a | 0.25 ± 0.03c |
| Amanita crocea | 146.76 ± 2.03ab | 363.37 ± 2.19ab | 33.60 ± 1.11ab | 90.19 ± 1.28bc | 9.81 ± 0.32ab | 5.01 ± 0.41a | 0.75 ± 0.08b |
| Pleurotus eryngii | 156.97 ± 1.71ab | 268.94 ± 2.67b | 34.44 ± 1.16ab | 88.62 ± 1,96c | 11.38 ± 0.54a | 4.43 ± 0.61a | 1.12 ± 0.07a |
| Agaricus campestris | 232.06 ± 2.36 ab | 379.75 ± 3.27ab | 37.25 ± 1.22ab | 88.08 ± 1.25c | 11.92 ± 0.25a | 3.87 ± 0.29a | 0.56 ± 0.03b |
| Amanita vittadinii | 128.57 ± 1.37ab | 276.12 ± 2.27b | 40.47 ± 1.12ab | 92.80 ± 1.89ab | 7.20 ± 0.58bc | 4.36 ± 0.48a | 0.64 ± 0.07b |
| Pleurotus columbinus | 142.25 ± 2.13ab | 279.16 ± 2.38b | 31.23 ± 1.44b | 92.76 ± 1.28ab | 7.24 ± 0.45bc | 4.33 ± 0.40a | 1.10 ± 0.08a |
| Agrocybe dura | 207.71 ± 2.09ab | 244.53 ± 2.57b | 32.82 ± 1.77b | 92.73 ± 1.28ab | 7.27 ± 0.39bc | 4.40 ± 0.37a | 0.97 ± 0.06a |
| Agaricus bisporus | 121.89 ± 1.24b | 237.84 ± 19.89b | 16.40 ± 0.67c | 94.17 ± 1.99a | 5.83 ± 0.22c | 1.37 ± 0.24 b | 0.25 ± 0.03c |
Different letters denote statistically significant differences between mean values (three replicates per species), as shown by Duncan’s multiple range test (p ≤ 0.05). Each value represents the mean ± standard error.
3.4 Analysis of relationships among mushroom species using biochemical markers
The data obtained from the agglomerative hierarchical clustering (AHC), and scatter matrix methods were condensed into three clusters (Figs. 3a-e). The first cluster (red) covered five species: A. crocea, P. eryngii, A. campestris, A. litoralis, and A. aegerita. The second cluster (green) contained five species: A. vittadinii, A. lividopallescens, P. columbinus, A. dura, and A. pseudolutosus. The final group (blue) includes the cultivated species, A. bisporus. The first two PCA components accounted for 75.9% of the variability. Based on the PCA plots in Figs. 3(b-d), it seems that the first AHC group of samples had high values of TPC, DPPH, TFC, DM, PC, and SSC, which had a positive loading on the first component in the right quadrant of the plot, and AHC group 2 samples had larger values of MC (Figs. 3c and d). The variation among the three groups accounted for by the PC trait was the greatest at 94.49%, followed by DM (91.03%) and MC (91.03%). In contrast, the SSC trait showed the least variation (25.39 %) among the three groups (Fig. 3f). The greatest distance recorded (5.11) was between A. lividopallescens and A. litoralis, while the smallest distance (0.48) was between A. dura and P. columbinus (Fig. 3g). During this analysis, MC and DM clearly separated the mushrooms into three groups.
- Relationships between mushroom species and biochemical parameters. (a) Clustering of species using the AHC method; (b) and (c) Clustering of species using PCA plot; (d) Distribution of studied traits using PCA method; (e) Grouping of mushroom species using scatter plot; (f) Variation percentage explained by each trait for the separation of three groups; and (g) Genetic distance among mushroom species.
3.5 Chemical composition profile and compounds relationship of different extracts
From the GC/MS analysis depicted in Fig. 4 and the supplementary file (Fig. S1), the number of detected bioactive compounds ranged from 8-76. The maximum number of detected compounds was recorded in Pleurotus, with 76 compounds in P. eryngii and 74 compounds in P. columbinus, whereas the minimum number of compounds was found in the cultivated species: A. bisporus (8) and A. litoralis (15).
- Number of compounds detected by GC/MS in 11 mushroom species.
The concentrations of the primary compounds of A. aegerita, A. dura, A. campestris, A. crocea, P. eryngii, A. lividopallescens, P. columbinus, A. pseudolutosus, A. vittadinii, A. bisporus, and A. litoralis were determined to be 1.03 (C14) to 20.79% (C18), 1.16 (C8) to 34.63% (C11), 1.47 (C4) to 26.88% (C3), 1.26 (C4) to 12.44% (C10), 1.03 (C2) to 12.43% (C18), 1.07 (C3) to 16.56% (C15), 1.01 (C12) to 14.50% (C17), 1.02 (C2) to 17.07% (C8), 1.06 (C1) to 19.11% (C15), 1.52 (C3) to 85.67% (C1), and 1.29 (C8) to 55.82% (C6), respectively (Fig. 5 and supplementary file, Table S1). Many different compounds were identified in the extracts of the 11 species, including five prevalent compounds, namely 9-octadecenoic acid, 13-octadecenoic acid-methyl ester, ergosterol, hexadecanoic acid-methyl ester, and hexadecanoic acid (Figs. 6a-e). For A. lividopallescens, the highest concentrations of 9-octadecenoic acid (16.56%), 13-octadecenoic acid-methyl ester (11.15%), ergosterol (14.62%), and hexadecanoic acid-methyl ester (10.13%) were observed, whereas A. vittadinii had the highest concentration of hexadecanoic acid (15.22%), followed by A. litoralis (13.08%). A. bisporus had the lowest values for 9-octadecenoic acid, 13-octadecenoic acid-methyl ester, ergosterol, and hexadecanoic acid-methyl ester. Based on the common compounds, a PCA model was created to identify the most important variables that explained the connections among the 11 mushroom species and to establish group patterns (Fig. 7). The first two principal components, which accounted for 90.80% of the total variability (70.40% and 20.40% for PC1 and PC2, respectively), divided the studied species into three groups (Fig. 7a). The first group (marked in blue) consisted of four species: A. crocea, A. lividopallescens, P. columbinus, and P. eryngii. The second group (marked in green) comprised two species: A. vittadinii and A. litoralis. The last group (marked in red) was comprised of five species: A. aegerita, A. dura, A. campestris, A. pseudolutosus, and A. bisporus. The first principal component was clearly identified as hexadecanoic acid-methyl ester (C2), ergosterol (C3), 13-octadecenoic acid-methyl ester (C4), and 9-octadecenoic acid (C5), while the second principal component was related to n-hexadecanoic acid (C1) (Fig. 7b).
- Concentrations of the major compounds detected in 11 mushroom species. (a) A. aegerita, (b) A. dura, (c) A. campestris, (d) A. crocea, (e) P. eryngii, (f) A. lividopallescens, (g) P. columbine, (h) A. pseudolutosus, (i) A. vittadinii, (j) A. bisporus, and (k) A. litoralis. The names of the compounds (labelled C) are provided in the supplementary file (Table S1).
- Concentration percentages of some common compounds in mushroom species. (a) 9-Octadecenoic acid, (b) 13-Octadecenoic acid, methyl ester, (c) Ergosterol, (d) Hexadecanoic acid methyl ester, and (e) Hexadecanoic acid.
- Relationship between the studied species and common compounds. (a) Distribution of different species on the PCA plot, (b) Distribution of common compounds on the two axes of the PCA plot. C1-C5 represent common compounds: C1: n-hexadecanoic acid, C2: hexadecanoic acid, methyl ester, C3: ergosterol, C4: 13-octadecenoic acid, methyl ester, and C5: 9-octadecenoic acid, (E).
3.6 Correlation among mushroom species based on the morpho-biochemical characters
The morpho-biochemical traits and common major compound correlation relationships were analyzed using Spearman’s correlation method. Results revealed nineteen significant correlations between traits, with three exhibiting a negative relationship (Fig. 8). Hexadecanoic acid-methyl ester (C2) showed a strong positive correlation with ergosterol (C3), 13-octadecenoic acid-methyl ester (C4), and 9-octadecenoic acid (C5) with the values of 0.81**, 0.99**, and 0.84**, respectively. The same was true for 9-octadecenoic acid (C5) and 13-octadecenoic acid-methyl ester (C4), which were positively correlated (0.85**). The case of ergosterol (C3) positively correlated with 9-octadecenoic acid (C5) and 13-octadecenoic acid-methyl ester (C4) was 0.80** and 0.68*, respectively. WS was positively associated with LS (0.76**) and HDH (0.64*). Similarly, there was a strong positive correlation between VDH and HDH (0.93**). A moderate negative correlation of VDH (-0.64*) and HDH (-0.65*) with TPC was stated. The TFC was positively correlated with PC, which was 0.79**. LS was positively correlated with C2 (0.76**), C3 (0.68*), C4 (0.78**), and C5 (0.68*).
- A heatmap showing the correlation among morpho-biochemical features.
3.7 Beneficial and risky health of mushroom species
Mushrooms are known to possess medicinal properties. In addition, they are low in fat and high in protein and vitamin contents. They are also an excellent source of minerals and other dietary fibers. Specific biochemical agents in mushrooms are what make them beneficial to humans. Such bioactive agents include polysaccharides, triterpenoids, low molecular weight proteins, glycoproteins, and immunomodulating compounds (Assemie and Abaya, 2022). According to the data of this study, mushrooms serve as a great source of nutraceuticals, along with many other benefits, such as anticancer, prebiotic, immunomodulatory, anti-inflammatory, cardiovascular, antimicrobial, and antidiabetic effects (Table S1). However, current research has detected potentially hazardous chemicals that are non-carcinogenic and cancerous in extracts from different species, which pose risks to human health, as highlighted in Tables 4 and 5.
| Toxic compounds | A. aegerita | A. dura | A. campestris | A. crocea | P. eryngii | A. lividopallescens | P. columbinus | A. pseudolutosus | A. vittadinii | A. bisporus | A. litoralis |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 4-Methyl-2,4-bis(p-hydroxyphenyl) pent-1-ene, 2TMS derivative | - | 34.63 | 1.67 | 11.22 | 4.90 | - | - | - | 5.18 | 5.45 | - |
| Carbonyl sulfide | - | - | 26.88 | - | - | - | - | - | 5.99 | - | - |
| Methane-d, trichloro- | - | - | - | 1.26 | - | - | - | - | - | - | |
| Benzene, 1-methyl-2-nitroso- | - | - | - | - | 1.03 | - | - | - | - | - | - |
| Conhydrin | - | - | - | - | - | 1.43 | - | - | - | - | - |
| 6,8-Dodecadien-1-ol (6Z,8E) | - | - | - | - | - | 3.36 | - | - | - | - | - |
| Ethane, 1,2-dibromo- | - | - | - | - | - | - | - | 3.29 | - | - | - |
| Tolycaine | - | - | - | - | - | - | - | 17.07 | - | - | - |
| Compounds | Health risk | References |
|---|---|---|
| 4-Methyl-2,4-bis(p-hydroxyphenyl) pent-1-ene, 2TMS derivative | Hormonal activities, toxic effects on insulin-producing cells in the pancreas, strong estrogen-like properties that could affect the progression of breast cancer, and harmful impacts on pulmonary function through the promotion of cell death | (Huang et al., 2021; Liu et al., 2016) |
| Carbonyl sulfide | Characteristics of thiocarbamate herbicides. These compounds are metabolized into hydrogen sulfide, a substance capable of inducing harmful effects on cellular respiration and causing neurotoxicity | (Andrew R. Bartholomaeus and Victoria S. Haritos, 2005; DeMartino et al., 2017) |
| Methane-d, trichloro- | Toxicological effects | (Lontoh and Semrau, 1998) |
| Benzene, 1-methyl-2-nitroso- | Genotoxicity and carcinogenic potential | (Noriega et al., 2022) |
| Conhydrin | Neurotoxic properties | (Hotti and Rischer, 2017) |
| 6,8-Dodecadien-1-ol (6Z,8E) | Potential applications in pest management | (Bahetjan et al., 2023) |
| Ethane, 1,2-dibromo- | Genotoxic effects leading to carcinogenic potential | (Iyer and Makris, 2010) |
| Tolycaine | Anesthetic, convulsions, and potential antimicrobial properties | (Sawaki et al., 2000) |
4. Discussion
Numerous studies have demonstrated that extracts from various mushroom species contain substantial amounts of bioactive compounds such as phenols, flavonoids, alkaloids, terpenoids, tannins, steroids, and cardiac glycosides, and these compounds have been linked to a range of biological activities (Assemie and Abaya, 2022; Fogarasi et al., 2024). The composition of cultivated mushroom species is well documented; however, wild edible mushrooms remain under-researched, and to our knowledge, the bioactive contents of ten wild species have not been previously reported. Wild mushrooms exhibit higher levels of soluble carbohydrates (SSC) and PC than cultivated varieties (A. bisporus). Furthermore, significant variations in SSC and PC were observed among different wild mushroom species. These differences can be attributed to several factors, including the genetic composition and environmental conditions of mushroom growth (Stojek et al., 2024). Reactive oxygen species (ROS) are major contributors to various health issues, making the search for natural antioxidants crucial. Phenolic compounds play a significant role in antioxidant activity, with mushroom extracts showing a strong correlation between the phenolic content and antioxidant properties (Effiong et al., 2024; Ruth W. Mwangi et al., 2022). Our study of 11 species has revealed substantial differences in biochemical contents. Wild mushroom species had higher TPC, TFC, and antioxidant activity (DPPH) than their cultivated counterparts, which may be attributed to genetic makeup, geographical, and environmental factors. The results indicated an inverse relationship between TPC and cap diameter growth, suggesting that high phenolic accumulation inhibits cap expansion (Ashti et al., 2018; Tahir et al., 2024). Generally, low levels of certain phenolic compounds can positively influence growth, but their effects are detrimental at high concentrations. Earlier, some researchers studied the morphology and biochemical and biological activity of several mushroom species, and a variety of results were obtained with respect to species and environmental conditions (Chaudhary et al., 2023; Chechan et al., 2020; Hayat et al., 2024; Khumlianlal et al., 2022; Krümmel et al., 2022; Ouali et al., 2023; Senila et al., 2024).
A positive correlation was observed between LS and several common major compounds, including 9-octadecenoic acid, 13-octadecenoic acid-methyl ester, ergosterol, and hexadecanoic acid-methyl ester. The current scientific literature lacks extensive documentation on the correlation between mushroom stalk length and the presence of certain compounds. Cultivated mushroom varieties exhibit a higher MC than their wild counterparts. This increase in MC decreases the nutritional value (Bhardwaj et al., 2024).
The decrease in water content and increase in the accumulation of DM in wild mushrooms suggest higher levels of bioactive compounds, which subsequently increase the overall quality of mushrooms.
The dependency of species and the environmental context of the organism bring about an important relationship between phytochemical compounds such as TPC, TFC, and antioxidant activity. In this study, PC and TFC were found to be positively correlated. Increased protein levels may be associated with changes in the concentration of flavonoids, suggesting that high protein levels may include those associated with flavonoid biosynthesis.
Cluster analysis plays a crucial role in facilitating interspecific mapping studies by enhancing our understanding of genetic diversity (Eltaher et al., 2018). A dendrogram and PCA plot revealed a significant variety of mushroom taxa. This species diversity suggests a rich genetic pool and a high level of genetic variation. Along with morphological features, the horizontal cap diameter emerged as the most distinguishing feature among the three clusters. Similarly, DM and PC were the most useful biochemical traits that differentiated the three clusters obtained from the biochemical data.
GC/MS appraisal showed that the wild species had more identified compounds than their cultivated species, which was not surprising. This species difference may be due to the genetic composition and environmental features of the biotopes of wild species, which are sometimes considered stressful (Munir et al., 2023). The main compounds found in various species of mushrooms, especially in wild ones, exhibit multidimensional biological and pharmaceutical attributes, including antimicrobial, antioxidant, cytotoxic, antitumor, anticancer, anti-inflammatory, and antiandrogenic activities. The activities of these compounds have been well clarified through extensive research. Hexadecanoic acid demonstrated anti-inflammatory and antimicrobial properties (Ganesan et al., 2024; Shaaban et al., 2021). The methyl ester of 13-octadecenoic acid exhibits antioxidant, hypocholesterolemic, anti-inflammatory, and anticancer activities (Krishnamoorthy and Subramaniam, 2014). Research has shown that 9-octadecenoic acid offers multiple health benefits. It has been found to improve cardiovascular health, reduce inflammation, inhibit cancer growth, enhance immune system function, and protect nerve cells. These diverse effects highlight the compound’s potential therapeutic applications across various medical fields (Piccinin et al., 2019). Ergosterol, another compound of interest, maintains membrane integrity, acts as a precursor of vitamin D2, exhibits antimicrobial and anti-inflammatory actions, and exerts neuroprotective effects (Rangsinth et al., 2023). Due to its minimal sugar content, A. pseudolutosus and A. bisporus may be beneficial for people struggling with obesity, diabetes, or heart-related issues.
The rising incidence of mushroom poisoning has become a notable health concern, as indicated by the growing number of worldwide reports (Nieminen and Mustonen, 2020). Eight toxic compounds were found in the listed species using GC/MS analysis, which included the following: 4-Methyl-2-4-bis(o-hydroxyphenyl) pent-1-ene 2TMS derivative, carbonyl sulfide, methane-d, trichloro-, benzene, 1-methyl-2-nitroso-, conhydrin, 6,8-Dodecadien-1-ol (6Z,8E), ethane, 1,2-dibromo-, and tolycaine. These substances exhibit estrogenic activity, thiocarbamate herbicide properties, neurotoxicity, genotoxic and carcinogenic potentials, anesthetic effects, and convulsant properties.
5. Conclusions
This research has shown that edible mushrooms are an excellent source of nutrients, including proteins, dietary, and secondary metabolites. The evaluated wild mushrooms had high levels of TPC, TFC, antioxidant activity (DPPH), PC, DM, ergosterol, and fatty acids. The potential toxicity observed in these representative wild mushroom species necessitates caution regarding their regular consumption, as the accumulation of these toxic compounds may result in various adverse health outcomes. A. litoralis and A. aegerita were especially distinguishable as dietary and health-beneficial mushrooms, as they had the highest TPC, TFC, DDPH, and PC contents but low amounts of fatty acids and their derivatives. Notably, there are no potentially harmful toxins in these species, which makes them suitable for human nutrition. This study integrated information regarding the composition, taxonomy, and biological activities of edible wild and cultivated mushrooms from the Iraqi Kurdistan region. Therefore, integrated solutions for the sustainable management of these valuable bioresources are needed. This includes the preservation of these resources and their surroundings, the improvement of commercial profit-oriented cultural practices, and the assessment of biotechnological potential.
Furthermore, wild edible mushrooms require comprehensive studies, especially regarding their mineral and heavy metal constituents.
CRediT authorship contribution statement
Nawroz A. Tahir: supervision, resources, project administration, writing – review and editing, writing – original draft, software, methodology, formal analysis, conceptualization, and validation. Kazhan M. Sleman: data curation, methodology, and investigation, writing – review and editing, visualization.
Declaration of competing interest
The authors declare that they have no competing financial interests or personal relationships that could have influenced the work presented in this paper
Data availability
All information has been included in the primary manuscript document, as well as in the supplementary file.
Footnote: This work forms part of Kazhan Mahmood Sleman’s MSc project proposal.
Declaration of Generative AI and AI-assisted technologies in the writing process
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
Supplementary data
Supplementary material to this article can be found online at https://dx.doi.org/10.25259/JKSUS_423_2025.
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