Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Effects of element complexes containing Fe, Zn and Mn on artificial morel’s biological characteristics and soil bacterial community structures

  • Qingya Liu ,

    Contributed equally to this work with: Qingya Liu, Huimei Liu

    Affiliation Key Laboratory of Bio-resources and Eco-environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, P.R. China

  • Huimei Liu ,

    Contributed equally to this work with: Qingya Liu, Huimei Liu

    Affiliation Key Laboratory of Bio-resources and Eco-environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, P.R. China

  • Ciqiong Chen,

    Affiliation Key Laboratory of Bio-resources and Eco-environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, P.R. China

  • Jinmei Wang,

    Affiliation Sichuan Tongfeng Science & Technology Co. Ltd, Chengdu, P.R. China

  • Yu Han,

    Affiliation Sichuan Tongfeng Science & Technology Co. Ltd, Chengdu, P.R. China

  • Zhangfu Long

    Lzf0028@163.com

    Affiliation Key Laboratory of Bio-resources and Eco-environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, P.R. China

Abstract

This study described the effects of elements (including Fe, Zn, Mn and their complexes) on the following factors in artificial morel cultivation: the characteristics of mycelia and sclerotia, soil bacterial community structures, yields and contents of microelements. The results indicated that the groups containing Mn significantly promoted mycelia growth rates, and all the experimental groups resulted in higher yields than the control (P<0.01), although their mycelia and sclerotia did not show obvious differences. It was also found that Proteobacteria, Chloroflexi, Bacteroides, Firmicutes, Actinobacteria, Acidobacteria and Nitrospirae were the dominated bacterial phyla. The Zn·Fe group had an unexpectedly high proportion (75.49%) of Proteobacteria during the primordial differentiation stage, while Pseudomonas also occupied a high proportion (5.52%) in this group. These results suggested that different trace elements clearly affected morel yields and soil bacterial community structures, particularly due to the high proportions of Pseudomonas during the primordial differentiation stage.

Introduction

Morchella spp (morel) is highly prized for its medicinal and nutritional qualities, such as antioxidant, anti-inflammatory and antitumor activities, as well as strengthening the immune response [1~4]. According to previous experiments, morel mycelia growth and fruit-body (ascocarp) formation are strongly affected by many factors, such as temperature, humidity, illumination, air, pH and nutrition. The first indoor cultivation of morels was reported by Ower [56], but a great breakthrough had not been achieved in large-scale application until 2010.

It is common practice to cover morels with soil during cultivation to support soil microbes that are responsible for the promotion of primordial differentiation and ascocarp growth. However, thus far, we have known very little about how soils affect the growth and development of morels. Nevertheless, it has been demonstrated that soil microbes are important components of soil ecosystems and that bacteria are widely distributed in soil [710]. Inorganic fertilizer is commonly used for farmland management and can affect the soil microbial community structure [11,12]. Trace elements are usually conducive to the metabolic efficacy of edible mushrooms, particularly Fe, Zn, Mn and Cu, and may significantly affect mushroom growth and development. It was found that artificial morel ascocarps are rich in Fe, Zn and Mn [13], while many edible fungi (including wild morels) can convert inorganic metals into organic metal compounds that can be easily utilized by human beings [14,15]. Each trace element has special physiological functions that can influence fungal growth rates and soil bacterial community structures [16,17].

A few studies have reported that trace elements found in fruit bodies differ by strain types and applied fertilizers [13,18,19]. Our previous studies also found that some trace elements (Fe, Zn and Cu) affected soil microflora, as well as mycelia growth rates and yields in morels [13,20]. However, little is known about how trace elements affect morel soil microbial community structures, and whether bacteria in the soil affect morel yield. This study primarily reports the effects of some trace elements (Fe, Zn, Mn and their complexes) on morel mycelia growth rates, yield and soil bacterial community structures. The objective of the study is to discover not only some relationships among trace elements, yield and bacteria but also whether trace elements or bacteria affect the development of morel.

Materials and methods

Strains and chemical agents

The strain used in this study was preserved at 4°C in the authors’ laboratory [20]. Zinc sulfate (ZnSO4∙7H2O), manganous sulfate (MnSO4∙4H2O), ferrous sulfate (FeSO4∙7H2O) and other chemical reagents were analytically pure and purchased from local chemical reagent companies.

Laboratory tests comparing the differences in mycelia growth

The stock culture of the experimental strain, which was preserved in a slant tube, was activated on PDA Petri dishes (potato 200 g/L, glucose 20 g/L, agar 18 g/L) and incubated under 18°C for four days. The mycelia plugs (6 mm in diameter) were sub-cultured in PDA media, which were treated with three single elements (including ZnSO4 (Zn), FeSO4 (Fe), MnSO4 (Mn)), three binary elemental complexes (including Zn∙Fe, Fe∙Mn and Zn∙Mn; w/w = 1:1) and one ternary complex (Zn·Fe·Mn; w/w/w = 1:1:1). Their final contents were 100 mg/L, while pure PDA media was used as the control group. Each group was triplicated and incubated under 18°C for 21 days. Mycelia growth and sclerotia formation were observed using a zoom stereo microscope (Leica, Germany). Mycelia growth rates were calculated using the formula reported by Liu et al (2015) [13] and were measured once a day until the mycelia had grown to the edge of the plates.

Outdoor planting experiment

The outdoor experimental field was in Longxing Town, Chongzhou, Sichuan, P.R. China, and each experimental plot was 10 m2 in size. The experimental strain was reactivated using PDA media and incubated under 16~18°C for 15 days and then was transferred into the newly sterile spawn media (packaged in a 450-mL bottle, containing 70% wheat grains, 15% sawdust, 10% chaff, 1% vermiculite and 4% pure soil at a natural pH value). After 15 days of cultivation under 18°C, there were many sclerotia adhering to the glass walls. Approximately one bottle of spawn per square meter (m2) were sowed in the experimental plots and covered with fine soil (3~5 cm in depth) to support the subsequent production of morels. It was necessary to build a sunshading net (2 meters above the ground) prior to seeding, and water mist was thoroughly sprinkled on the soil until two or three days after sowing when the soil moisture content reached 22%. About twenty days later, the frost-like sclerotia of the morels were covering the soil surface. The mycelia and sclerotia were observed by collecting the frost-like soil blocks and using a zoom stereo microscope (Leica, Germany). After the collection, nutritional bags containing the same solid spawn media were added to the soil (approximately 3 bags per square meter) to rejuvenate the mycelia. There were seven experimental groups of different elements, including three single elements (6 g/m2 of each element), three binary elemental complexes (3 g/m2 of each element) and a ternary elemental complex (2 g/m2 of the element). The trace elements were resolved in 5 L of pure water, with an equal volume of pure water used as the control. They were sprayed onto the soil surfaces one month after seeding. Soil samples were collected during the primordial differentiation stage and the ascocarp growth stage (approximately two and three months after seeding, respectively).

Soil bacterial community structures analyzed using high-throughput sequencing

DNA extraction and 16S rRNA MiSeq sequencing.

The soil genomic DNAs were extracted according to the previous report [21]. The universal primers 515F (5'-gtgccagcmgccgcggtaa-3') and 909R (5'-ccccgycaattcmtttragt-3') with a 12-nt unique barcode were used to amplify the V4 hyper variable regions of the 16S rRNA genes for pyrosequencing using a MiSeq sequencer [22,23]. Each sample was amplified in a 25 μL reaction and followed the program which reported by Tamaki et al [24]. Two PCR reactions were conducted for each sample, and their products were combined and subjected to electrophoresis using a 1.0% agarose gel. The bands with the correct size were separately excised and purified using the SanPrep DNA Gel Extraction Kit (Sangon Biotech, Shanghai, China). The products were quantified with a Nanodrop. All samples were pooled together at equal molar amounts. The sequencing samples were prepared using the TruSeq DNA kit (Illumina, Shanghai, China) according to manufacturer’s instructions. The purified library was diluted, denatured, re-diluted, and mixed with PhiX (equal to 30% of final DNA amount) according to the Illumina library preparation protocols. Then, the products were applied to an Illumina Miseq system for sequencing with 2×250 bp, using the Reagent Kit v2 (Illumina, Shanghai, China) as described in manufacturer’s manual.

Data analysis for bacteria community structures.

The sequence data were processed using QIIME Pipeline–Version 1.7.0 (http://qiime.org/). All sequence reads were trimmed and assigned to each sample based on their barcodes. High quality sequences (length > 150 bp, without ambiguous base ‘N’ and an average base quality score > 30) were used for downstream analysis. The sequences were clustered into operational taxonomic units (OTUs) at a 97% identity threshold. The aligned ITS gene sequences were used for a chimera check using the Uchime algorithm [25]. All samples were randomly resampled to 6,449 reads. We conducted alpha-diversity (phylogenetic distance whole tree, chao1 estimator of richness, observed species and Shannon’s diversity index) and beta-diversity (PCoA, UniFrac) analyses, and the rarefaction curves were generated from the observed species. Taxonomy was assigned using the Ribosomal Database Project Classifier [26].

Sequence accession numbers.

Sequence data have been deposited in the NCBI Sequence Read Archive (SRA) database with the accession number SRP093475.

Mineral determination of the morel ascocarp

When the ascocarps were close to maturity, the morels were carefully collected until the end of March, and the yields of all the groups were measured in triplicate. Randomly chosen morel ascocarps from each group were prepared by the acid digestion method described in the literature [19], and the contents of five microelements (including zinc, ferric, manganese, copper and selenium) were measured by the standard procedure using an inductively coupled plasma atomic emission spectrophotometer (ICPQ-1000, Shimadzu, Japan) according to the method described in our previous report [13]. Yields and microelements of ascocarp were analyzed using SPSS (Version 17).

Results

The effects of trace elements on the mycelial growth rate and sclerotial formation

The growth rates of morel’s mycelia were clearly enhanced by the different elements (Table 1); in particular, the four groups that contained with Mn had greater growth rates than the control (19.87%~23.92%, P<0.05). Sclerotia were emerged first in Mn group (9 days after inoculation), and emerged last in Zn∙Mn group (16 days after inoculation). The order of the sclerotia emergence was: Mn>Zn>Zn∙Fe>Zn∙Fe∙Mn>Fe∙Mn>Fe>ck>Zn∙Mn.

thumbnail
Table 1. Effects of trace elements on mycelia growth and sclerotial formation.

https://doi.org/10.1371/journal.pone.0174618.t001

The morphology of mycelia and sclerotia under a zoom stereomicroscope

When mycelia covered approximately the whole plate (3 days after inoculation), the morphology of the mycelia were observed under a zoom stereomicroscope. The results (S1 Fig) demonstrated that the mycelia were wide, flat, and spirally twisted (approximately 12.5 μm), and no significant difference was found among the groups.

It was discovered that many bridged mycelial branches (S2 Fig) were finely formed, then sclerotia began to originate from the aggregated bridges. The sclerotia were initially white and changed color from faint yellow to brown when they matured (Fig 1). The mycelia grown in the soil were short, erect, and tufted before the sclerotia (in the form of a white fungal cream) covered the soil surface (Fig 2). It was also observed under the zoom stereomicroscope that there were many short vertical mycelia on the sclerotia surface.

thumbnail
Fig 1. Process of sclerotia formation in PDA media under stereomicroscope.

(A~ C) The sclerotia are in the early, middle and late stages, respectively (5x) and (D~F) represent the same stage under 16 ×; The color of sclerotia were from white to faint yellow and final in brown.

https://doi.org/10.1371/journal.pone.0174618.g001

thumbnail
Fig 2. Morphologies of mycelia and sclerotia on the soil surface under stereomicroscope.

(A~C) The morphology of mycelia under 1x, 16x, and 16x magnification of a zoom stereomicroscope, respectively; (D~F) The morphology of sclerotia under 5x, 10x, and 16x magnification of a zoom stereomicroscope, respectively. The morphology of mycelia and sclerotia between medium and soil showed significantly different.

https://doi.org/10.1371/journal.pone.0174618.g002

Effects of trace elements on soil bacterial community structures

Rarefaction curves and diversity indices.

The rarefaction curves were generated at a 97% identity threshold (S3 Fig), and the sequencing depth of samples from most groups was reached to a suitable degree. Bacterial sequences of morel-grown soils from experimental groups were also clustered into operational taxonomic units (OTUs) and other diversity indices (including Shannon and Chao1) were estimated (shown in S1 Table). The OTUs of most groups (except Zn∙Fe) were similar during the two sampling stages (2390.32 on average). The highest (6259.93) and lowest (2146.03) Chao1 indexes during primordial differentiation stage were found in groups with Fe and Zn∙Fe, respectively. The Chao1 indexes during the primordial differentiation stage (5413.37 on average) demonstrated the following trend: Fe>Fe∙Mn>Zn∙Mn>Zn>Mn>ck>Zn∙Fe∙Mn>Zn∙Fe. The Chao1 indexes of the single element and binary elements containing Mn were higher than that of ck. However, this trend was changed during the ascocarp growth stage; Chao1 indexes which higher than ck were found in experimental groups containing Zn, Mn or Fe∙Mn. The Shannon indexes (10.3 on averages) demonstrated the following trend during the primordial differentiation stage: Mn>Zn>Fe> Zn∙Mn>ck>Zn∙Fe∙Mn>Fe∙Mn>Zn∙Fe, while the highest (10.96) and the lowest (7.65) Shannon indexes were found in groups with Zn and Zn∙Fe.

Comparison of bacterial community structures at the phylum level.

The bacterial community structure was noticeably affected by different trace elements (Fig 3). Seven dominant bacterial phyla, including Proteobacteria, Chloroflexi, Bacteroidetes, Acidobacteria, Nitrospirae, Firmicutes and Actinobacteria, were found in all groups, and their total percentages ranged from 74.72% to 93.63% (Table 2). The total bacterial percentage was similar across groups, except for the Zn∙Fe group during the primordial differentiation stage. However, the proportions of each bacteria phylum clearly differed across groups. Proteobacteria and Chloroflexi were the first and second most dominant bacterial phyla in most groups; the total proportion of these two bacterial phyla ranged from 35.81% (Fe group) to 76.92% (Zn∙Fe group).

thumbnail
Fig 3. Histograms of soil bacteria richness.

571–578 represent the control (ck), Mn, Zn, Fe, Zn∙Fe, Fe∙Mn, Zn∙Mn and Zn∙Fe∙Mn groups, respectively, during the primordial differentiation stage. 579–586 represent the same groups of above during the ascocarp growth stage. The length of columns indicate the proportions of bacteria at the phylum level.

https://doi.org/10.1371/journal.pone.0174618.g003

thumbnail
Table 2. Proportions of predominant bacterial phyla in morel-grown soil.

https://doi.org/10.1371/journal.pone.0174618.t002

When the bacterial community structures of the experimental groups were compared with that of the control group during the primordial differentiation stage, Proteobacteria and Bacteroidetes proportions from most groups tended to be higher than those in ck, while Actinobacteria, Nitrospirae, and Acidobacteria were lower than ck. The highest proportion of Proteobacteria (32.34% on average) was found in the Zn∙Fe group (75.49%, 2.43~3.26 times higher than those of other groups), while the lowest proportion was found in the Fe group (23.14%). The highest proportion of Bacteroidetes (8.14%) was found in the Zn∙Mn group, while the lowest proportion was found in ck (4.09%); Bacteroidetes proportions from most experimental groups were higher (ranging from 9.78~99.02%) than that of ck during primordial differentiation stage. Alternatively, Actinobacteria and Nitrospirae proportions from all experimental groups were lower than ck, with the lowest proportions of these two phyla found in the Zn∙Fe group. Proportions of Acidobacteria in most groups (except Mn and Zn groups) were also lower than ck.

After comparing the proportions of predominant bacterial phyla in the primordial differentiation stage and the ascocarp growth stage, it was found that Proteobacteria, Bacteroidetes and Firmicutes increased for most groups during ascocarp stage, while Acidobacteria, Actinobacteria, Chloroflexi and Nitrospirae mostly decreased. The proportions of Bacteroidetes were rose across all groups during the ascocarp growth stage, an increase that ranged from 25.43% to 427.24% compared with that of primordial differentiation stage for each group. However, in the Zn∙Fe group, the proportions of Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Chloroflexi were higher in ascocarp stage than primordial differentiation stage, but the group in former stage produced lower proportions of Nitrospirae and Proteobacteria.

Bacterial community structure at genus level.

Since the most predominant bacteria in the grown soil came from the Proteobacteria phylum, the associated bacterial genera that was found in all groups were specially selected to also be analyzed in this study (Table 3). Three genera, including Rhodoplanes, Geobacter and Pseudomonas, were most predominant, with the genus Pseudomonas having the highest proportions in most groups. During the primordial differentiation stage, there was the largest number of Pseudomonas in the control group and all the groups which contained Mn, but three single-element groups (Zn, Fe and Mn) had higher proportions of Rhodoplanes though other experimental groups (binary and ternary complexes) had lower proportions than the control group. The proportions of Geobacter and three unknown genera (belonging to Comamonadaceae, Janthinobacterium and Syntrophobacteraceae) were lower in the ck group than most experimental groups. The group with Zn∙Fe (No.175) had the highest proportion of Acinetobacter (23.36%), Janthinobacterium (8.18%), and Pseudomonas (5.52%) during primordial differentiation stage.

thumbnail
Table 3. Predominant genera of Proteobacteria in morel-grown soil.

https://doi.org/10.1371/journal.pone.0174618.t003

During the ascocarp stage, Pseudomonas was also the dominated genus in groups with Zn (5.23%), Zn∙Fe∙Mn (4.15%), Zn∙Mn (2.83%), Fe (1.79%) and Ze∙Fe (1.12%). However, the control group had the highest proportion of Geobacter (1.75%) and Rhodoplanes (1.45%) which was higher than that of most experimental groups (except Fe∙Mn group, No.184).

Principal Coordinates Analysis (PCoA).

Using the weighted UniFrac distance metric, PCoA showed that 175 (Zn) had the greatest diversity, followed by 186 (Zn∙Fe∙Mn) and 182 (Mn) (S4 Fig). The dispersion levels of the groups within the ascocarp growth stage were higher than those of the groups during the primordial differentiation stage. There was a definite change in experimental groups, particularly in groups with Fe, Zn∙Fe, and Zn∙Fe∙Mn, respectively. The relative degrees of variance in those groups were as follows: Zn∙Fe>Zn∙Fe∙Mn>Fe>Zn∙Mn>Zn>Mn>Fe∙Mn>ck.

Yields and contents of microelements in morel ascocarp

The relative yields of artificial morel demonstrated the following trend: Zn∙Fe>Mn>Zn>Zn∙Mn>Fe∙Mn>Zn∙Fe∙Mn>Fe>ck (Fig 4). The yields from the groups that were sprayed with elements (including groups with Zn, Fe∙Mn, Zn∙Mn or Zn∙Fe∙Mn) were not significantly different, but the morel yields of all experimental groups were significantly higher than that of the control group (P<0.01). The contents of five microelements (including zinc, ferric, manganese, copper and selenium) were also determined (Table 4). Ferric content was the highest, while manganese and copper were the lowest mineral levels. The ascocarp with the highest content of selenium was found in the Zn∙Mn group, while zinc and ferric were lowest in the Zn∙Fe∙Mn group.

thumbnail
Fig 4. Morel yields of groups with different element treatments.

Values sharing a common capitalized letter (A-D) were not significant at P<0.01.

https://doi.org/10.1371/journal.pone.0174618.g004

thumbnail
Table 4. Contents of microelements in artificial morel ascocarp (mg/kg dw).

https://doi.org/10.1371/journal.pone.0174618.t004

Discussion

Thus far, large-scale planting of morels in China is usually field-based; therefore, yields are greatly affected by natural conditions and soil. Although some growers can cultivate morels indoors during the normal planting season, the production cost is still very high. Because morels must be planted in soil or covered with soil, it is very important to discover how the soil supports morel growth. It is well known that there are substantial amounts of microbes and nutrient elements in soil that are necessary for morel growth. Therefore, this study selected and applied those elements which were rich in the ascocarp of morel, such as Fe, Zn and Mn, to stimulate differences in morel growth and yield while comparing their effects on morel-grown soil community structures.

In this study, it was confirmed that there were not clear differences in mycelia characteristics among the control group and those treated with trace elements; they differed significantly in mycelia growth rates, yields and ascocarp mineral contents, especially in the Zn∙Mn group. The mycelia growth rates of experimental groups which contain Mn were higher than others; therefore, there was a synergetic effect between Zn and Mn. The earliest sclerotia, which is crucial to fruit body formation [5,6], first appeared in the Mn group, while Fe, Zn and their combination also had better effects on the formation of sclerotia. Those results suggested that a Zn∙Fe∙Mn complex is necessary for morel growth. However, some unexpected results of this experiment suggested that the three-element complex was not be prepared in the best proportions, so it is necessary to further study a suitable proportion for these three elements, even combined with other factors.

This study also demonstrated that artificial morel’s soil bacterial diversity and richness were significantly affected by different elements. Seven predominant phyla were found in all groups, including Proteobacteria, Chloroflexi, Actinobacteria, Acidobacteria, Nitrospirae, Bacteroidetes and Firmicutes. It is very interesting that Proteobacteria was found in the largest proportion at an unexpected level in the Zn∙Fe (75.49%, primordial differentiation stage) and Zn∙Fe∙Mn groups (39.46%, ascocarp growth stage), while the yields of these groups were also significantly higher than the control group. It has been reported that the secretions of some bacteria may promote morel growth [27], perhaps the increased Proteobacteria bacteria may have contributed to the improved ascocarp yield. Further analyses verified that Pseudomonas, Geobacter and Rhodoplanes were the main bacteria in Proteobacteria. We know that some strains of Pseudomonas had bio-control properties, such as killing parasitic fungi and some phytophagous nematodes [28], as well as stimulating hyphal growth, reducing ethylene production and inducing primordium formation of Agaricus bisporus [29]. However, Pseudomonas was the most common bacteria (5.52%) in the Zn∙Fe group (primordial differentiation stage), and this group also harvested the highest yield of ascocarps. Hence, we hypothesize that Pseudomonas may have such effect on morel primordial differentiation, which is the key to the formation of the fruit body throughout the morel life cycle [30]. On the other hand, Geobacter is usually associated with electron transport and conducive to oxidizing organic substrates [31], while Rhodoplanes was observed using organic compounds such as carbon sources and electron donors [32]. These bacteria could help organic compounds converted to carbon sources which can be utilized by morels.

Nitrospirae plays a key role in the nitrogen cycle [33], its nitrification supplies a nitrogen source for morel growth. It was lower than ck in most experimental groups, perhaps due to a decrease in the numbers of Nitrospirae strains requiring nitrogen. Chlorobacteria and Nitrospirae were also reported to be the dominant bacteria in activated sludge in wastewater treatment, which can degrade ammonia-nitrogen and organic chlorides [3436]. Acidobacteria plays an important role in maintaining the pH value [37,38] and influences metal uptake activity [39,40]. Bacteroidetes is important for degrading cellulose and chitin [4144]. On the other hand, morel is usually found growing in forests [45,46], where there are large amounts of fallen leaves that are high in cellulose. Consequently, these afore-mentioned bacteria played different roles for morel growth, and need further research in order to improve the development of morel.

The morel yields in this study were clearly correlated with soil bacterial diversity and richness; these differences were derived from different trace elements or their complexes. There are typically bountiful morel harvests in forests that have been subject to fire, which provides many trace elements via the ashes of trees and grasses [47,48]. Robbins also reported that minerals benefit morel growth [49]. We also measured the contents of five minerals in morel ascocarp and found greater amounts of those elements in experimental groups (except Zn∙Fe∙Mn) than the ck group. In addition, the yields of groups with trace elements were significantly higher than that of the control group (P<0.01), also indicating that trace elements can improve morel yields.

Fe was the largest microelement found in Morchella, and its average value (668.38 mg/kg) was similar to that of Craterellus odoratus [50]. A variety of studies from European countries have established intake estimates of Se ranging between 38 and 286 μg/day [51]. The average level (118.82 mg/kg) of Se is approximately 9.43 times higher than the amount found in Russula virescens [50]. The highest content of Cu in ascocarp in this study was measured at 51.43 mg/kg (group Mn) which is safe for consumption (less than 100 mg/kg) [52]. The contents of Mn and Zn in this study agreed with the report by Ayazs [53]. Though microelements were rich in the artificial morel ascocarp, they still complied with the standards declared by the EU Scientific Committee.

To date, the cultivation of morel still uses semi-artificial planting. This study demonstrated that trace elements affect not only the mycelia and sclerotia growth, the yields and mineral contents of ascocarp, but also bacterial community structures. Based on this research, further studies should focus on determining which types of microbes directly or indirectly affect ascocarp yield. Many similar research achievements and breakthroughs will thrust the morel industry to a new level.

Supporting information

S1 Fig. Mycelia characteristics of morels under a zoom stereomicroscope (16×).

The morphology of mycelia showed no obvious difference between the control group and treatment groups. Scale bars represent 100 μm.

https://doi.org/10.1371/journal.pone.0174618.s001

(TIF)

S2 Fig. Mycelia bridge on medium under stereomicroscope (16 ×).

Reticular formation was formed by hyphal branching.

https://doi.org/10.1371/journal.pone.0174618.s002

(TIF)

S3 Fig. Rarefaction curves (97% similarity).

https://doi.org/10.1371/journal.pone.0174618.s003

(TIF)

S4 Fig. Analyses of principal coordinates using weighted UniFrac.

Distance shows that the differences or similarities of soil bacteria community structures among different groups.

https://doi.org/10.1371/journal.pone.0174618.s004

(TIF)

S1 Table. Diversity indices calculated using a cutoff of 97% similarity.

https://doi.org/10.1371/journal.pone.0174618.s005

(DOC)

Acknowledgments

We thank the Sichuan Wan’an Agroicultural Technology and Development Co.Ltd who prepared the spawn for field experiment. We are also grateful for kind help of Cheng Chen and Fusheng Zhang who are from Sichuan University.

Author Contributions

  1. Conceptualization: ZFL.
  2. Data curation: QYL.
  3. Formal analysis: QYL.
  4. Funding acquisition: ZFL.
  5. Investigation: QYL HML JMW YH.
  6. Methodology: QYL HML.
  7. Project administration: ZFL QYL.
  8. Resources: ZFL.
  9. Supervision: ZFL QYL.
  10. Validation: QYL CQC JMW YH.
  11. Visualization: ZFL QYL.
  12. Writing – original draft: ZFL HML QYL.
  13. Writing – review & editing: ZFL QYL CQC HML.

References

  1. 1. Park KM, Kwon KM, Lee SH. Evaluation of the antioxidant activities and tyrosinaseIinhibitory property from mycelium culture extracts. Evid Based Complement Alternat Med. 2015:
  2. 2. Su CA, Xu XY, Liu DY, Wu M, Zeng FQ, Zeng MY, et al. Isolation and characterization of exopolysaccharide with immunomodulatory activity from fermentation broth of Morchella conica. DARU J Pharm Sci. 2013; 21(1):5.
  3. 3. Nitha B, Meera CR, Janardhanan KK. Anti-inflammatory and antitumour activities of cultured mycelium of morel mushroom, Morchella esculenta. Current Science. 2007; 92(2): 235–239
  4. 4. Kanwal HK, Acharya K, Ramesh G, Reddy MS. Molecular characterization of Morchella species from the western Himalayan region of India. Current Microbiology. 2011; 62(4): 1245–1252. pmid:21188589
  5. 5. Ower R. Notes on the development of the morel ascocarp: Morchella esculenta. Mycologia. 1982; 74(1): 142–144
  6. 6. Ower R, Mills GL, Malachowski JA. Cultivation of Morchella. US Patent. 1986; No.4594809
  7. 7. Rousk J, Frey SD. Revisiting the hypothesis that fungal-to-bacterial dominance characterizes turnover of soil organic matter and nutrients. Ecological Monographs. 2015; 85(3): 457–472
  8. 8. Schlesinger WH, Andrews JA. Soil respiration and the global carbon cycle. Biogeochemistry. 2000; 48(1): 7–20.
  9. 9. Hartman WH, Richardson CJ. Differential nutrient limitation of soil microbial biomass and metabolic quotients (qCO2): is there a biological stoichiometry of soil microbes? PLoS One. 2013; 8(3): e57127 pmid:23526933
  10. 10. Lin YT, Hu HW, Whitaman WB, Coleman DC, Chiu CY. Comparision of soil bacterial communities in a natural hardwood forest and coniferous plantations in perhumid subtropical low mountains. Botanical studies. 2014; 55:50.
  11. 11. Zhang XY, Dong WY, Dai XQ, Schaeffer S, Yang FT, Radosevich M, et al. Responses of absolute and specific soil enzyme activities to long term additions of organic and mineral fertilizer. Sci Total Environ. 2015; 536(1): 59–67.
  12. 12. Li JJ, Zheng Y, Yan JX, Li HJ, Wang X, He JZ, et al. Effects of different regeneration scenarios and fertilizer treatments on soil microbial ecology in reclaimed opencast mining areas on the Loess Plateau China. PloS One. 2013; 8(5): e63275 pmid:23658819
  13. 13. Liu HM, Xu JJ, Li X, Zhang Y, Yin AQ, Wang JM, et al. Effects of microelemental fertilizers on yields, mineral element levels and nutritional compositions of the artificially cultivated Morchella conica. Scientia Horticulturae. 2015; 189(1): 86–93
  14. 14. Michelot D, Siobud E, Dore J, Viel C, Poirier F. Update of metal content profiles in mushrooms—toxicological implications and tentative approach to the mechanisms of bioaccumulation. Toxicon. 1998; 36(12): 1997–2012 pmid:9839683
  15. 15. Falandysz J, Borovička J. Macro and trace mineral constituents and radionuclides in mushrooms: health benefits and risks. Appl Microbiol Biotechnol. 2013; 97(2): 477–501. pmid:23179616
  16. 16. Tekeste Z, Amare B, Asfaw F, Fantahun B, Van NN, Nishikawa T, et al. Determination of trace elements in Ethiopian, Vietnamese, and Japanese women using high-resolution IC-PMS. Nutrition. 2015; 31(10): 1243–1246 pmid:26333889
  17. 17. Qiu GM, Li W, Li XK, Zhou W. Biological function of REE in plants & microbes. J. Rare Earth. 2005; 23(6): 645–652
  18. 18. Sarikurkcu C, Tepe B, Solak MH, Cetinkaya S. Metal concentrations of wild edible mushrooms from Turkey. Ecol Food Nutr. 2012; 51(4):346–363 pmid:22794131
  19. 19. Liu H, Zhang J, Li T, Shi Y, Wang Y. Mineral Element Levels in Wild Edible Mushrooms from Yunnan, China. Biol Trace Elem Res. 2012; 147(1): 341–345.
  20. 20. Li X, Chen ZZ, Peng CC, Han Y, Xu JG, Long ZF. Effect of different ferric fertilizers on planting Morchella conica fruit yields and analyses of the microflora and bioactivities of its grown soil. Afr J Microb Res. 2013; 7(39): 4707–4716.
  21. 21. Cheng XY, Li WJ, Wang Y, Yang HM, Lou K. Endophytic bacterial diversity in Glycyrrhiza inflata Bat. from Xinjiang by culture-independent method. Acta Microbiol Sinica. 2009; 49(6): 718–725 (in Chinese)
  22. 22. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011; 108(25): 4516–4522
  23. 23. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012; 6(8):1621–1624 pmid:22402401
  24. 24. Tamaki H, Wright CL, Li XZ, Lin XY, Hwang CC, Wang SP, et al. Analysis of 16S rRNA Amplicon Sequencing Options on the Roche/454 Next-Generation Titanium Sequencing Platform. PLOS ONE. 2011; 6(9): e25263. pmid:21966473
  25. 25. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011; 27(16): 2194–2200. pmid:21700674
  26. 26. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naïve bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007; 73(16): 5261–5267. pmid:17586664
  27. 27. Pion M, Spangenberg JE, Simon A, Bindschedler S, Flury C, Chatelain A, et al. Bacterial farming by the fungus Morchella crassipes. Proc Biol Sci. 2013; 280(1773).
  28. 28. Haas D, Keel C. Regulation of antibiotic production in root-colonizing Pseudomonas spp. and relevance for biological control of plant disease. Annu Rev Phytopathol. 2003; 41:117–153 pmid:12730389
  29. 29. Chen SC, Qiu CW, Huang T, Zhou WW, Qi YC, Gao YQ et al. Effect of 1-aminocyclopropane-1-carboxylic acid deaminase producing bacteria on the hyphal growth and primordium initiation of Agaricus bisporus. Fungal Ecology. 2013; 6(1): 110–118
  30. 30. Volk TJ, Leonard TJ. Cytology of the Life cycle of Morchella. Mycological Research. 1990; 94(3): 399–406.
  31. 31. Bond DR, Lovley DR. Electricity production by Geobacter sulfurreducens attached to electrodes. Appl Environ Microbiol. 2003; 69(3): 1548–1555 pmid:12620842
  32. 32. Lakshmi KV, Sasikala Ch, Ramana ChV. Rhodoplanes pokkaliisoli sp. nov., a phototrophic alphaproteo bacterium isolated from a waterlogged brackish paddy soil. Int J Syst Evol Microbiol. 2009; 59(9): 2153–2157
  33. 33. Tian M, Liu HH, Shen X, Zhao FQ, Chen S, Yao YJ. Biodiversity and function analyses of BIOLAK activated sludge metagenome. Environmental science.2015; 36(5): 1739–1748 (in Chinese)
  34. 34. Li A, Chu Y, Wang X, Ren L, Yu J, Liu XL, et al. A pyrosequencing-based metagenomic study of methane-producing microbial community in solid-state biogas reactor. Biotechnol Biofuels. 2013; 6(1): 1–17
  35. 35. Nelson MC, Morrison M, Yu Z. A meta-analysis of the microbial diversity observed in anaerobic digesters. Bioresour Technol. 2011; 102(4): 3730–3739. pmid:21194932
  36. 36. Gupta P, Sangwan N, Lal R,Vakhlu J. Bacterial diversity of Drass, cold desert in western Himalaya, and its comparison with Antarctic and Arctic. Arch Microbiol. 2015; 197(6): 851–860 pmid:26055487
  37. 37. Long YH, Xie L, Liu N, Yan X, Li MH, Fan MZ, et al. Comparison of gut-associated and nest-associated microbial communities of a fungus-growing termite (Odontotermes yunnanensis). Insect Sci. 2010; 17(3): 265–276
  38. 38. Jones RT, Robeson MS, Lauber CL, Hamady M, Knight R, Fierer N. A comprehensive survey of soil acidobacterial diversity using pyrosequencing and clone library analyses. ISMEJ. 2009; 3(4): 442–453.
  39. 39. Mladenka P, Macakova K, Filipsky T, Zatloukalova L, Jahodar L, Bovicelli P, et al. In vitro analysis of iron chelating activity of flavonoids. J Inorg Biochem. 2011; 105(5): 693–701 pmid:21450273
  40. 40. Yang LQ, Huang B, Mao MC, Yao LP, Hickethier M, Hu WY. Trace metal accumulation in soil and their phytoavailability as affected by greenhouse types in north China. Environ Sci Pollut Res Int. 2015; 22(9): 6679–6686 pmid:25422117
  41. 41. Hirsch P, Ludwig W, Hethke C, Sittig M, Hoffmann B, Gallikowski CA. Hymenobacter roseosalivarius gen. nov., sp. nov. from continental Antarctic soils and sandstone: bacteria of the Cytophaga/Flavobacterium/Bacteroides line of phylogenetic descent. Syst Appl Microbiol.1998; 21(3): 374–383 pmid:9841127
  42. 42. Sigurbjörnsdóttir MA, Heiðmarsson S, Jónsdóttir AR, Vilhelmsson O. Novel bacteria associated with Arctic seashore lichens have potential roles in nutrient scavenging. Can J Microbiol. 2014; 60(5): 307–317. pmid:24802938
  43. 43. Ponpium P, Ratanakhanokchai K, Kyu KL. Isolation and properties of a cellulosome-type multienzyme complex of the thermophilicBacteroides sp. strain P-1. Enzyme Microb Technol. 2000; 26(5–6): 459–465 pmid:10713221
  44. 44. Xu Q, Bayer EA, Goldman M, Kenig R, Shoham Y, Lamed R. Architecture of the Bacteroides cellulosolvens cellulosome: description of a cell surface-anchoring scaffoldin and a family 48 cellulase. J Bacteriol. 2004; 186(4):968–977 pmid:14761991
  45. 45. Pilz D, McLain R, Alexander S, Villarreal-Ruiz L, Berch S, Wurtz TL, et al. Ecology and management of morels harvested from the forests of Western North America. General Technical Report PNW-GTR-710. Portland: US Department of Agriculture, Forest Service, Pacific Northwest Research Station; 2007. pp161
  46. 46. Mortimer PE, Karunarathna SC, Li QH, Gui H, Yang XQ, Yang XF, et al. Prized edible Asian mushrooms: ecology, conservation and sustainability. Fungal Diversity. 2012; 56(1):31–47
  47. 47. Parks CG, Schmitt CL. Wild edible mushrooms in the Blue Mountains: resource and issues. USDA Forest Service- General Technical Report PNW. 1997(393)
  48. 48. McFarlane EM, Pilz D, Weber NS. High-elevation gray morels and other Morchella species harvested as non-timber forest products in Idaho and Montana. Mycologist. 2005; 19(2):62–68
  49. 49. Robbins WJ, Hervey A. Manganese, calcium and filtrate factor for Morchella crassipes. Mycologia. 1965; 57(2): 262–274
  50. 50. Sanmee R, Dell B, Lumyong P, Izumori K, Lumyong S. Nutritive value of popular wild edible mushrooms from northern Thailand. Food Chemistry. 2003; 82(4): 527–532
  51. 51. Nasreddine L, Parent-Massin D. Food contamination by metals and pesticides in the European Union. Should we worry?. Toxicology Letters. 2002; 127(1–3): 29–41 pmid:12052638
  52. 52. Kalac P. Svoboda L. A review of trace element concentrations in edible mushrooms. Food Chemistry. 2002; 69(3): 273–281.
  53. 53. Ayaz FA, Torun H, Colak A, Sesli E, Millson M, Glew RH. Macro- and Microelement contents of fruiting bodies of wild-edible mushrooms growing in the east Black Sea region of Turkey. Food Nutri Sci. 2011; 2(2): 53–59