[go: up one dir, main page]
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.4
4.1
Journals
Microorganisms
Special Issues
Soil Microbial Communities and Ecosystem Functions, 2nd Edition
share announcement

Soil Microbial Communities and Ecosystem Functions, 2nd Edition

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Environmental Microbiology".

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 9360

Special Issue Editor

Prof. Dr. Efimia M. Papatheodorou

E-Mail Website
Guest Editor
Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: soil microbial community structure and function; enzymes in soil; soil restoration; soil quality and agricultural practices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Soil microbial communities play essential roles in maintaining ecosystem functions such as litter decomposition, mineralization, nitrification and denitrification, exerting control on primary production, soil fertility and the emission of gases. Disturbances inducing changes in habitat connectivity, nutrient inputs and global environmental variables due to changes in land use and climate affect the composition and structure of soil microbial communities, with subsequent changes in ecosystem functions. However, the relationship between the community assemblage and a specific function or an index of multifunctionality could be affected by a variety of factors. These are variables used to assess community organization (functional diversity, species richness, composition, co-occurrence patterns), those referred to the taxonomic level of the community organization as well as variables that are related to the spatial scale of community (local, global or in the cross-boundary areas). Most studies have explored the relationship between species/taxa richness and functions, and there is a gap concerning the relationship between the co-occurrence patterns of microbes and the functionality of an ecosystem. Furthermore, information concerning the influence of the spatial scale of analysis or the temporal pattern of the environmental changes (constant or with oscillations) is very rare. Knowledge of the relationship between soil microbes and soil functionality could be extremely useful for conservation, restoration and management efforts.

In this Special Issue of Microorganisms, we invite authors to send their contributions concerning any aspect that could affect the relationship between microbial organization and soil functionality: metrics of analysis, spatial scale or different environmental conditions, as well as the influence of perturbations on the above-mentioned relationships. For this Special Issue, we welcome original research papers, review articles, and short communications. Research areas may include, but are not limited to, ecology, microbiology, and biogeography.

I look forward to receiving your contributions.

Prof. Dr. Efimia M. Papatheodorou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • soil functionality
  • functional diversity
  • soil microbial communities
  • disturbances
  • co-occurrence patterns
  • environmental oscillations
  • microbial assemblages

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2972 KiB  
Article
Soil Fungal Diversity and Community Structure of Russula griseocarnosa from Different Sites
by Zhen Li, Ruoxi Liang and Fei Yu
Microorganisms 2025, 13(3), 490; https://doi.org/10.3390/microorganisms13030490 (registering DOI) - 22 Feb 2025
Viewed by 179
Abstract
Russula griseocarnosa is an important ectomycorrhizal edible fungus whose economic and nutritional value are both high. To better understand which abiotic and biotic factors affect the growth of R. griseocarnosa, this study examined the mycosphere soil of R. griseocarnosa growing in five [...] Read more.
Russula griseocarnosa is an important ectomycorrhizal edible fungus whose economic and nutritional value are both high. To better understand which abiotic and biotic factors affect the growth of R. griseocarnosa, this study examined the mycosphere soil of R. griseocarnosa growing in five sites. The soil fungal communities of R. griseocarnosa from five sites of Fujian, Guangxi, and Yunnan Provinces were sequenced by Illumina MiSeq technology, and their community structure comprehensively analyzed in combination with a suite of soil physicochemical properties. The results revealed significantly greater levels of available potassium (AK), available nitrogen (AN), and available phosphorus (AP) in mycosphere soil than bulk soil, and that R. griseocarnosa prefers acidic soil, with Penicillium, Trichoderma, Talaromyces, Mortierella, Tolypocladium, Chloridium, Oidiodendron, and Umbelopsis being the main dominant fungal taxa. Different geographical sites had different indicator fungal genera, and the similarity of fungal communities in the mycosphere decreased with increasing geographical distance among them. Soil pH was the major abiotic factor influencing the structure of the mycosphere fungal communities. Management strategies such as nitrogen, potassium, phosphorus mixed fertilizer, and fungal fertilizer can promote the conservation and sustainable utilization of R. griseocarnosa. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Comparison of Chao (<b>A</b>) and Shannon (<b>B</b>) diversity indexes between mycosphere and bulk soil. Significant differences by * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. DPF, HTCF, JJF, YYF, and ZPF represent mycosphere soil in different geographical areas, and HTCFCK, JJFCK, YYFCK, and ZPCK represent bulk soil.</p> Full article ">Figure 2
<p>Comparison of fungi community composition between mycosphere and bulk soil. (<b>A</b>) Phylum level; (<b>B</b>) the top 30 genera. DPF, HTCF, JJF, YYF, and ZPF represent mycosphere soil in different geographical areas, and HTCFCK, JJFCK, YYFCK, and ZPCK represent bulk soil.</p> Full article ">Figure 3
<p>LEfSe analysis of mycosphere fungi at genus level. DPF, HTCF, JJF, YYF, and ZPF represent mycosphere soil in different geographical areas.</p> Full article ">Figure 4
<p>Canonical correspondence analysis (CCA) based on the relative abundance of fungal taxa at the OTU level and environmental factors. DPF, HTCF, JJF, YYF, and ZPF represent mycosphere soil in different geographical areas, and HTCFCK, JJFCK, YYFCK, and ZPCK represent bulk soil. AK, AN, AP, and SOC represent available potassium, available nitrogen, available phosphorus, and soil organic carbon, respectively.</p> Full article ">Figure 5
<p>Relationships between mycosphere fungal communities and environmental factors. (<b>A</b>) Variation partition analysis (VPA) of soil/site properties on fungal community. (<b>B</b>) Distance–decay curves of fungal communities.</p> Full article ">Figure 6
<p>Spearman correlation between the LEfSe-significant fungal genera and soil/site properties. Significant correlation was noted when * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 7
<p>Functional classification of the LEfSe-significant fungal genera. DPF, HTCF, JJF, YYF, and ZPF represent mycosphere soil in different geographical areas, and HTCFCK, JJFCK, YYFCK, and ZPCK represent bulk soil.</p> Full article ">
17 pages, 4908 KiB  
Article
Altitude’s Impact on the Rhizosphere Prokaryotic Communities of the Cretan Endemic Plant Petromarula pinnata (L.) A.DC.
by Rafaela Stagiopoulou, Ifigeneia Mellidou, Nikos Krigas and Effimia M. Papatheodorou
Microorganisms 2025, 13(1), 74; https://doi.org/10.3390/microorganisms13010074 - 3 Jan 2025
Viewed by 625
Abstract
The present study examined the effect of the three different altitudes on the enzymatic activity and the prokaryotic communities of the rhizosphere of Petromarula pinnata (L.) A.DC. (Campanulaceae), a vulnerable local endemic species of Crete (Greece). It was observed that the pH and [...] Read more.
The present study examined the effect of the three different altitudes on the enzymatic activity and the prokaryotic communities of the rhizosphere of Petromarula pinnata (L.) A.DC. (Campanulaceae), a vulnerable local endemic species of Crete (Greece). It was observed that the pH and N-acetylglucosaminidase (NAG) activity increased with altitude while the β-1,4-glucosidase (BG) activity fluctuated with increasing altitude. The prokaryotic community in the rhizosphere of P. pinnata was dominated at the phylum level by Proteobacteria, Actinobacteriota, Bacteroidota, and Firmicutes, as well as by Bacillus members at the genus level. The alpha diversity did not vary with altitude while the b-diversity varied significantly, reflecting differences in community composition in relation to altitudinal gradient. The NAG activity was positively associated with most of the predominant phyla, except for Proteobacteria. The BG enzyme activity appeared to be negatively associated with Proteobacteria, Chloroflexi, and Acidobacteriota. Based on online databases, the predicted functions of the community showed a clear distinction in relation to altitude. At lower altitude, functions related to quorum sensing among microbes were overrepresented, while at the higher altitude, the functions were more related to energy production and transfer. The results of this research contribute to the ex situ and in situ protection of the vulnerable populations of P. pinnata and provide information for understanding the effect of altitude on processes in the rhizosphere of a threatened local endemic species of Crete studied in its original habitats. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Rocky habitats (<b>A</b>,<b>B</b>) with mature (flowering) and non-flowering wild-growing individuals of the local endemic <span class="html-italic">Petromarula pinnata</span> sampled for above-ground (<b>C</b>) and below-ground parts with soil (<b>D</b>,<b>E</b>) at 450 m above sea level on Mt Thrypti, Crete Island, Greece (<b>F</b>) with panoramic view of the Aegean and the South Cretan Seas.</p> Full article ">Figure 2
<p>Soil characteristics (pH, water content, and organic carbon) of <span class="html-italic">Petromarula pinnata</span> at three different altitudes in eastern Crete. The letters a and b indicate the statistically significant differences between altitudes.</p> Full article ">Figure 3
<p>Enzyme activity (AP: alkaline phosphatase, NAG: N-acetylglucosaminidase, BG: β-1,4-glucosidase) in the rhizosphere soil of <span class="html-italic">Petromarula pinnata</span> at three different altitudes in eastern Crete. The letters a and b indicate statistically significant differences with respect to altitude as obtained by Tukey test.</p> Full article ">Figure 4
<p>Relative abundance of the top ten most abundant taxa of <span class="html-italic">Petromarula pinnata</span> rhizosphere samples at different altitudes in eastern Crete at the levels of phylum (<b>A</b>) and genus (<b>B</b>).</p> Full article ">Figure 5
<p>Alpha diversity indices ((<b>A</b>) Shannon index, (<b>B</b>) Chao1, (<b>C</b>) Simpson and (<b>D</b>) Observed taxa) in the rhizosphere microbial communities of <span class="html-italic">Petromarula pinnata</span> in relation to altitude.</p> Full article ">Figure 6
<p>Principal coordinate analysis (PCoA) of the rhizosphere microbial communities of <span class="html-italic">Petromarula pinnata</span> recorded at three different altitudes in eastern Crete, based on the Jaccard dissimilarity index, at the phylum (<b>A</b>) and the genus (<b>B</b>) levels.</p> Full article ">Figure 7
<p>(<b>A</b>) LEfSE analysis of the rhizosphere microbial communities of <span class="html-italic">Petromarula pinnata</span> at the genus level, at three different altitudes in eastern Crete. The LDA threshold was set at 3 and the <span class="html-italic">p</span>-value cut-off at 0.05. The dots represent the genera with statistical differences among the three altitudinal classes. Different colors represent the relative abundances of the specific genera in each altitude (red for high and blue for low abundances). (<b>B</b>) Log-transformed counts of putative microbial biomarkers for the lower, intermediate, and higher altitudes.</p> Full article ">Figure 8
<p>Heatmap showing predicted functions according to the COG library for prokaryotic communities in the rhizosphere of <span class="html-italic">Petromarula pinnata</span> at three different altitudes in eastern Crete. Only those showing significant differences in pairwise comparisons (<span class="html-italic">p</span> &lt; 0.05) are presented. More details are presented in <a href="#app1-microorganisms-13-00074" class="html-app">Supplementary Materials</a> <a href="#app1-microorganisms-13-00074" class="html-app">Table S3</a>.</p> Full article ">Figure 9
<p>Correlation analysis between the relative abundance of the dominant phyla, soil characteristics, and enzyme activities recorded in the microbial communities of the rhizosphere of <span class="html-italic">Petromarula pinnata</span>.</p> Full article ">
22 pages, 12908 KiB  
Article
Elevation Determines Fungal Diversity, and Land Use Governs Community Composition: A Dual Perspective from Gaoligong Mountains
by Zhuanfei Zeng, Ruilong Huang and Wei Li
Microorganisms 2024, 12(11), 2378; https://doi.org/10.3390/microorganisms12112378 - 20 Nov 2024
Viewed by 870
Abstract
Soil fungi are closely tied to their surrounding environment. While numerous studies have reported the effects of land-use practices or elevations on soil fungi, our understanding of how their community structure and diversity vary with elevation across different land-use practices remains limited. In [...] Read more.
Soil fungi are closely tied to their surrounding environment. While numerous studies have reported the effects of land-use practices or elevations on soil fungi, our understanding of how their community structure and diversity vary with elevation across different land-use practices remains limited. In the present study, by collecting soil samples from four different land uses in the Gaoligong Mountain area, namely shrublands (SLs), coffee plantations (CPs), cornfields (CFs), and citrus orchards (COs), and combining them with the changes in altitude gradients (low: 900 m, medium: 1200 m, high: 1500 m), high-throughput sequencing technology was used to analyze the composition and diversity of soil fungal communities based on the collected soil samples. The results showed that the interaction between land-use types and elevation significantly influenced the structure and diversity of fungal communities, although their relative importance in shaping fungal diversity or community structure varied. Specifically, elevation posed a stronger effect on fungal community alpha-diversity and functional guilds, whereas land-use types had a greater influence over fungal community composition. Our study reveals the individual and combined effects of land-use practices and elevation on the structure and diversity of soil fungal communities in the Gaoligong Mountain region, enhancing our understanding of the distribution patterns and driving mechanisms of soil fungal communities in this biodiversity-rich region. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Study area and sampling site.</p> Full article ">Figure 2
<p>Soil physicochemical properties with different land uses and altitudes in the Gaoligong Mountains. (Different letters indicate significant levels (<span class="html-italic">p</span> &lt; 0.05). At the same elevation, significant differences between different land uses are denoted by lowercase letters (e.g., a); at the same land use, significant differences between different elevations are denoted by uppercase letters (e.g., A). (<b>a</b>): pH. (<b>b</b>): TC, total carbon. (<b>c</b>): TN, total nitrogen. (<b>d</b>): TP, total phosphorus. (<b>e</b>): NH<sub>4</sub><sup>+</sup>-N, ammonium-nitrogen. (<b>f</b>): NO<sub>3</sub><sup>−</sup>-N, nitrate-nitrogen. (<b>g</b>): SOC, soil organic carbon. (<b>h</b>): DOC, dissolved organic carbon. (<b>i</b>): SWC, soil water content).</p> Full article ">Figure 3
<p>Relative abundance of soil fungal phyla (<b>a</b>) and fungal genera (<b>b</b>). (SL1, SL2, and SL3 correspond to low, medium, and high elevation shrublands, respectively, and the same applies to other land uses. SL: shrubland, CP: coffee plantation, CF: cornfield, CO: citrus orchard).</p> Full article ">Figure 4
<p>Alpha diversity of soil fungal community. ((<b>a</b>): Chao1 index; (<b>b</b>): ACE index; (<b>c</b>): Shannon index; (<b>d</b>): Simpson index). Lowercase letters indicate significant differences in alpha diversity of fungal communities between different land uses (<span class="html-italic">p</span> &lt; 0.05); uppercase letters indicate significant differences between different elevations (<span class="html-italic">p</span> &lt; 0.05). The values on the right side of each graph represent the F-value and significance results. ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 5
<p>PCoA analyses of the soil fungal community. ((<b>a</b>–<b>c</b>) correspond to 900 m, 1200 m and 1500 m).</p> Full article ">Figure 6
<p>Relative abundance of fungal trophic mode (<b>a</b>) and guild (<b>b</b>). SL1, SL2, and SL3 correspond to low, medium, and high-elevation shrublands, respectively, and the same applies to other land uses. SL: shrubland, CP: coffee plantation, CF: cornfield, CO: citrus orchard.</p> Full article ">Figure 7
<p>RDA analysis applied to soil fungal community data and soil physicochemical properties. ((<b>a</b>–<b>c</b>) correspond to 900 m, 1200 m and 1500 m).</p> Full article ">Figure 8
<p>Correlation between the 10 most abundant fungal phyla and the physicochemical properties. ((<b>a</b>–<b>c</b>) correspond to 900 m, 1200 m and 1500 m). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 9
<p>Heat map of the correlation between functional guild of fungi and physicochemical properties. ((<b>a</b>–<b>c</b>) correspond to 900 m, 1200 m and 1500 m). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. U-S: Undefined Saprotroph, Ep: Epiphyte, E-LSU: Endophyte-Litter Saprotroph-Soil Saprotroph-Undefined Saprotroph, Ar-M: Arbuscular Mycorrhizal, W-S: Wood Saprotroph, An-FU: Animal Pathogen-Fungal Parasite-Undefined Saprotroph, An-U: Animal Pathogen-Undefined Saprotroph, P-W: Plant Pathogen-Wood Saprotroph, P-U: Plant Pathogen-Undefined Saprotroph, E-LPU: Endophyte-Lichen Parasite-Plant Pathogen-Undefined Saprotroph.</p> Full article ">
17 pages, 4412 KiB  
Article
Comparison of Bacterial Communities in Five Ectomycorrhizal Fungi Mycosphere Soil
by Pi Chen, Zhen Li, Ning Cao, Rui-Xuan Wu, Zhao-Ren Kuang and Fei Yu
Microorganisms 2024, 12(7), 1329; https://doi.org/10.3390/microorganisms12071329 - 29 Jun 2024
Viewed by 1396
Abstract
Ectomycorrhizal fungi have huge potential value, both nutritionally and economically, but most of them cannot be cultivated artificially. To better understand the influence of abiotic and biotic factors upon the growth of ectomycorrhizal fungi, mycosphere soil and bulk soil of five ectomycorrhizal fungi [...] Read more.
Ectomycorrhizal fungi have huge potential value, both nutritionally and economically, but most of them cannot be cultivated artificially. To better understand the influence of abiotic and biotic factors upon the growth of ectomycorrhizal fungi, mycosphere soil and bulk soil of five ectomycorrhizal fungi (Calvatia candida, Russula brevipes, Leucopaxillus laterarius, Leucopaxillus giganteus, and Lepista panaeola) were used as research objects for this study. Illumina MiSeq sequencing technology was used to analyze the community structure of the mycosphere and bulk soil bacteria of the five ectomycorrhizal fungi, and a comprehensive analysis was conducted based on soil physicochemical properties. Our results show that the mycosphere soil bacteria of the five ectomycorrhizal fungi are slightly different. Escherichia, Usitatibacter, and Bradyrhizobium are potential mycorrhizal-helper bacteria of distinct ectomycorrhizal fungi. Soil water content, soil pH, and available potassium are the main factors shaping the soil bacterial community of the studied ectomycorrhizal fungi. Moreover, from the KEGG functional prediction and LEfSe analysis, there are significant functional differences not only between the mycosphere soil and bulk soil. ‘Biosynthesis of terpenoidsand steroids’, ‘alpha-Linolenic acid metabolism’, ‘Longevity regulating pathway-multiple species’, ‘D-Arginine and D-ornithine metabolism’, ‘Nitrotoluene degradation’ and other functions were significantly different in mycosphere soil. These findings have pivotal implications for the sustainable utilization of ectomycorrhizal fungi, the expansion of edible fungus cultivation in forest environments, and the enhancement of derived economic benefits. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Dilution curves for bacterial signature sequences. GA: <span class="html-italic">Calvatia candida</span>’s mycosphere soil, GACK: <span class="html-italic">Calvatia candida</span>’s bulk soil, GB: <span class="html-italic">Russula brevipes</span>’s mycosphere soil, GBCK: <span class="html-italic">Russula brevipes</span>’s bulk soil, GC: <span class="html-italic">Leucopaxillus laterarius</span>’s mycosphere soil, GCCK: <span class="html-italic">Leucopaxillus laterarius</span>’s bulk soil, GD: <span class="html-italic">Leucopaxillus giganteus</span>’s mycosphere soil, GDCK: <span class="html-italic">Leucopaxillus giganteus</span>’s bulk soil, GE: <span class="html-italic">Lepista panaeola</span>’s mycosphere soil, and GECK: <span class="html-italic">Lepista panaeola</span>’s bulk soil.</p> Full article ">Figure 2
<p>Comparison of Chao (<b>A</b>) and Shannon (<b>B</b>) indexes between mycosphere and bulk soil. GA: <span class="html-italic">Calvatia candida</span>, GB: <span class="html-italic">Russula brevipes</span>, GC: <span class="html-italic">Leucopaxillus laterarius</span>, GD: <span class="html-italic">Leucopaxillus giganteus</span>, and GE: <span class="html-italic">Lepista panaeola</span>. Significant differences by *** <span class="html-italic">p</span> ≤ 0.001. Data are mean ± SE (<span class="html-italic">n</span> = 3).</p> Full article ">Figure 3
<p>Comparison of Chao (<b>A</b>) and Shannon (<b>B</b>) indexes in mycosphere soil of five ectomycorrhizal fungi. GA: <span class="html-italic">Calvatia candida</span>, GB: <span class="html-italic">Russula brevipes</span>, GC: <span class="html-italic">Leucopaxillus laterarius</span>, GD: <span class="html-italic">Leucopaxillus giganteus</span>, and GE: <span class="html-italic">Lepista panaeola</span>. Data are mean ± SE (<span class="html-italic">n</span> = 3). Different lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 4
<p>Comparison of phyla between mycosphere and bulk soil. GA: <span class="html-italic">Calvatia candida</span>’s mycosphere soil, GACK: <span class="html-italic">Calvatia candida</span>’s bulk soil, GB: <span class="html-italic">Russula brevipes</span>’s mycosphere soil, GBCK: <span class="html-italic">Russula brevipes</span>’s bulk soil, GC: <span class="html-italic">Leucopaxillus laterarius</span>’s mycosphere soil, GCCK: <span class="html-italic">Leucopaxillus laterarius</span>’s bulk soil, GD: <span class="html-italic">Leucopaxillus giganteus</span>’s mycosphere soil, GDCK: <span class="html-italic">Leucopaxillus giganteus</span>’s bulk soil, GE: <span class="html-italic">Lepista panaeola</span>’s mycosphere soil, and GECK: <span class="html-italic">Lepista panaeola</span>’s bulk soil.</p> Full article ">Figure 5
<p>Community composition of five species of ectomycorrhizal fungi mycosphere and bulk soil bacteria at the top 50 genera level. GA: <span class="html-italic">Calvatia candida</span>’s mycosphere soil, GACK: <span class="html-italic">Calvatia candida</span>’s bulk soil, GB: <span class="html-italic">Russula brevipes</span>’s mycosphere soil, GBCK: <span class="html-italic">Russula brevipes</span>’s bulk soil, GC: <span class="html-italic">Leucopaxillus laterarius</span>’s mycosphere soil, GCCK: <span class="html-italic">Leucopaxillus laterarius</span>’s bulk soil, GD: <span class="html-italic">Leucopaxillus giganteus</span>’s mycosphere soil, GDCK: <span class="html-italic">Leucopaxillus giganteus</span>’s bulk soil, GE: <span class="html-italic">Lepista panaeola</span>’s mycosphere soil, and GECK: <span class="html-italic">Lepista panaeola</span>’s bulk soil.</p> Full article ">Figure 6
<p>Redundancy analysis of the top 50 genera and environmental factors. GA: <span class="html-italic">Calvatia candida</span>’s mycosphere soil, GACK: <span class="html-italic">Calvatia candida</span>’s bulk soil, GB: <span class="html-italic">Russula brevipes</span>’s mycosphere soil, GBCK: <span class="html-italic">Russula brevipes</span>’s bulk soil, GC: <span class="html-italic">Leucopaxillus laterarius</span>’s mycosphere soil, GCCK: <span class="html-italic">Leucopaxillus laterarius</span>’s bulk soil, GD: <span class="html-italic">Leucopaxillus giganteus</span>’s mycosphere soil, GDCK: <span class="html-italic">Leucopaxillus giganteus</span>’s bulk soil, GE: <span class="html-italic">Lepista panaeola</span>’s mycosphere soil, and GECK: <span class="html-italic">Lepista panaeola</span>’s bulk soil.</p> Full article ">Figure 7
<p>Spearman correlation between the top 50 genera and environmental factors. Significant differences by * 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. ** 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01.</p> Full article ">Figure 8
<p>Comparison of the KEGG function between mycosphere and bulk soil. (<b>A</b>) <span class="html-italic">Calvatia candida</span>, (<b>B</b>) <span class="html-italic">Russula brevipes</span>, (<b>C</b>) <span class="html-italic">Leucopaxillus laterarius</span>, (<b>D</b>) <span class="html-italic">Leucopaxillus giganteus</span>, and (<b>E</b>) <span class="html-italic">Lepista panaeola</span>.</p> Full article ">Figure 9
<p>The five kinds of ectomycorrhizal fungi have significantly different functions in mycosphere soil. GA: <span class="html-italic">Calvatia candida</span>, GB: <span class="html-italic">Russula brevipes</span>, GC: <span class="html-italic">Leucopaxillus laterarius</span>, GD: <span class="html-italic">Leucopaxillus giganteus</span>, and GE: <span class="html-italic">Lepista panaeola</span>.</p> Full article ">
20 pages, 2786 KiB  
Article
Arbuscular Mycorrhizal Fungi and Rhizobium Improve Nutrient Uptake and Microbial Diversity Relative to Dryland Site-Specific Soil Conditions
by Rosalie B. Calderon and Sadikshya R. Dangi
Microorganisms 2024, 12(4), 667; https://doi.org/10.3390/microorganisms12040667 - 27 Mar 2024
Cited by 3 | Viewed by 2144
Abstract
Arbuscular mycorrhizal fungi (AMF) and rhizobium play a significant role in plant symbiosis. However, their influence on the rhizosphere soil microbiome associated with nutrient acquisition and soil health is not well defined in the drylands of Montana (MT), USA. This study investigated the [...] Read more.
Arbuscular mycorrhizal fungi (AMF) and rhizobium play a significant role in plant symbiosis. However, their influence on the rhizosphere soil microbiome associated with nutrient acquisition and soil health is not well defined in the drylands of Montana (MT), USA. This study investigated the effect of microbial inoculants as seed treatment on pea yield, nutrient uptake, potential microbial functions, and rhizosphere soil microbial communities using high-throughput sequencing of 16S and ITS rRNA genes. The experiment was conducted under two contrasting dryland conditions with four treatments: control, single inoculation with AMF or Rhizobium, and dual inoculations of AMF and Rhizobium (AMF+Rhizobium). Our findings revealed that microbial inoculation efficacy was site-specific. AMF+Rhizobium synergistically increased grain yield at Sidney dryland field site (DFS) 2, while at Froid site, DFS 1, AMF improved plant resilience to acidic soil but contributed a marginal yield under non-nutrient limiting conditions. Across dryland sites, the plants’ microbial dependency on AMF+Rhizobium (12%) was higher than single inoculations of AMF (8%) or Rhizobium (4%) alone. Variations in microbial community structure and composition indicate a site-specific response to AMF and AMF+Rhizobium inoculants. Overall, site-specific factors significantly influenced plant nutrient uptake, microbial community dynamics, and functional potential. It underscores the need for tailored management strategies that consider site-specific characteristics to optimize benefits from microbial inoculation. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>The influence of microbial inoculants on (<b>a</b>) plant grain yield and (<b>b</b>) microbial dependency (%) based on plant biomass and grain yield at contrasting dryland site conditions. Error bars indicate standard error of the mean from five replications. Bars with common letters are not significantly different based on Wilcoxon tests at 0.05% probability level.</p> Full article ">Figure 2
<p>The effect of microbial inoculants on grain nutrient content (%) and plant nutrient uptake (kg/ha): carbon (<b>a</b>,<b>b</b>), nitrogen (<b>c</b>,<b>d</b>), and phosphorus (<b>e</b>,<b>f</b>) at two dryland field sites. The vertical bars in the least square means denote confidence intervals. Lines with common letters are not significantly different based on LSD tests at 0.05% probability level. Asterisk indicates dryland field site with significantly higher grain nutrient content and plant nutrient uptake, ** denotes significance level at <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 3
<p>Effect of microbial inoculants on nutrient dynamics at contrasting dryland sites. Comparison of the initial soil nutrients vs. the effect of microbial inoculants on soil nutrient residuals after pea cropping between sites: soil N (<b>a</b>) and soil P residuals (<b>b</b>). Comparison of the plant nutrient uptake vs. the soil nutrient residuals across sites: plant N uptake vs. soil N residual (<b>c</b>) and grain P uptake vs. soil P residual (<b>d</b>). The vertical bars in the least square means denote confidence intervals. Lines with common letters are not significantly different based on LSD tests at 0.05% probability level. Asterisk indicates dryland field site or comparison between plant nutrient uptake and soil nutrient residual with significantly high nutrient levels, ** denotes significance level at <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 4
<p>Site-specific effect response to microbial inoculation on microbial diversity. Alpha-diversity of bacterial (<b>a</b>) and fungal communities (<b>b</b>) was calculated as observed number of species per sample and visualized using box-plots. Beta-diversity of microbial communities among treatments at the two sites for the bacterial (<b>c</b>) and fungal communities (<b>d</b>), and between site comparisons for bacterial (<b>e</b>) and fungal communities (<b>f</b>). Beta diversity was calculated using the Bray–Curtis index and visualized using principal coordinate analysis (PCoA) ordination plots. The different groups are highlighted by ellipses showing a 95% confidence range and colored areas correspond to the bacterial and fungal community structure of the different treatments and sites.</p> Full article ">Figure 5
<p>Taxabar plots showing the microbial community profiles of bacterial (<b>a</b>) and fungal communities (<b>b</b>) at the phylum level of the different treatments. Heatmap showing the microbial community pattern at the phylum and order taxonomic level composition of the bacterial (<b>c</b>) and fungal communities (<b>d</b>) at two dryland field conditions.</p> Full article ">Figure 6
<p>The heat tree showing the microbial communities of AMF and AMF+Rhizobium associated with increased crop performance in DFS 1 and DFS 2, respectively. The taxonomic differences between AMF-treated bacterial (<b>a</b>) and fungal communities vs. the control (<b>b</b>) in DFS 1; and AMF+Rhizobium-treated bacterial (<b>c</b>) and fungal communities vs. the control (<b>d</b>) in DFS 2. The heat tree analysis leverages the hierarchical structure of taxonomic classifications quantitatively using the median abundance and statistically using the non-parametric Wilcoxon Rank Sum test [<a href="#B56-microorganisms-12-00667" class="html-bibr">56</a>]. The indicated taxa with red nodes were significantly abundant in the microbial-treated plants, while green and blue nodes were significantly sparse in the bacterial and fungal communities of the microbial-treated plants compared to the untreated control.</p> Full article ">Figure 7
<p>Impact of microbial inoculants on the relative abundance of potential microbial functions: functional profile of bacterial communities relative to C, N, and P nutrient cycling genes (<b>a</b>) predicted using Tax4Fun2 based on the 16S rRNA genes according to the KEGG Ortholog groups (KOs). Ecophysiological functions of fungal communities (<b>b</b>) relative to nutrient cycling, plant-microbe interaction, and soil health based on the FungalTraits database. Asterisk indicates microbial function with signficant difference between sites. * and ** denote significance levels at <span class="html-italic">p</span> ≤ 0.05 and <span class="html-italic">p</span> ≤ 0.001, respectively.</p> Full article ">
16 pages, 2917 KiB  
Article
Afforestation-Induced Shifts in Soil Bacterial Diversity and Community Structure in the Saihanba Region
by Kai-Chuan Huang, Wen Zhao, Jun-Ning Li, Reyila Mumin, Chang-Ge Song, Hao Wang, Yi-Fei Sun and Bao-Kai Cui
Microorganisms 2024, 12(3), 479; https://doi.org/10.3390/microorganisms12030479 - 27 Feb 2024
Cited by 2 | Viewed by 2014
Abstract
Afforestation plays a pivotal role in ecosystem restoration, exemplified by the Saihanba Mechanized Forest Farm, the world’s largest planted forest; however, the assembly mechanisms and interactions of soil microbial communities in such forests remain inadequately understood. This study aimed to elucidate the impact [...] Read more.
Afforestation plays a pivotal role in ecosystem restoration, exemplified by the Saihanba Mechanized Forest Farm, the world’s largest planted forest; however, the assembly mechanisms and interactions of soil microbial communities in such forests remain inadequately understood. This study aimed to elucidate the impact of different afforestation tree species, namely Larix gmelinii var. principis-rupprechtii, Picea asperata, and Pinus sylvestris var. mongolica, on soil bacterial diversity and community structure in comparison to grassland. Sixty soil samples were collected at a 20 cm depth, and high-throughput sequencing was employed to identify bacterial communities and assess their interactions with environmental factors. A total of 6528 operational taxonomic units (OTUs) were identified, with Solirubrobacter, Conexibacter, Bacillus, Massilia, Gaiella, Acidibacter, and Vicinamibacter being the dominant genera. Afforestation significantly impacted soil bacterial alpha diversity, with notable influence from key soil chemical properties, including available phosphorus (AP), cation exchange capacity (CEC), and the carbon-to-nitrogen ratio of soil organic matter (SOM-C/N). The Mantel test highlighted pH, the Normalized Difference Vegetation Index (NDVI), and spatial variable (dbMEM) as primary environmental factors influencing dominant bacterial genera. The bacterial community structure demonstrated deterministic homogeneous selection, wherein SOM-C/N emerged as a significant factor influencing the dissimilarity of soil bacterial communities. Furthermore, plantation soils exhibited a more complex network structure than grassland soil, highlighting the crucial role of bacterial communities in vegetation changes and providing valuable insights into their response to environmental factors during the reforestation process. Full article
(This article belongs to the Special Issue Soil Microbial Communities and Ecosystem Functions, 2nd Edition)
►▼ Show Figures

Figure 1

Figure 1
<p>Geographical location map of sampling sites. The sampling sites are located in Saihanba Mechanized Forest Farm, Hebei Province, China.</p> Full article ">Figure 2
<p>Alpha diversity of bacterial community across four vegetation types ((<b>a</b>): rarefaction curve; (<b>b</b>): Shannon index; (<b>c</b>): chao1 index; (<b>d</b>): Pielou index). Different lowercase letters indicate significant differences among the four vegetation types at <span class="html-italic">p</span> &lt; 0.05 based on Tukey’s HSD.</p> Full article ">Figure 3
<p>Structural differences of bacterial community across four vegetation types ((<b>a</b>): Venn diagram; (<b>b</b>): principal coordinate analysis; (<b>c</b>): distribution of Beta Nearest Taxon Index (βNTI); (<b>d</b>): distance–decay relationship, the blue line represents least squares linear regression, with the regression coefficients tested using a <span class="html-italic">t</span>-test (R<sup>2</sup> = 0.25, <span class="html-italic">p</span> &lt; 0.001)).</p> Full article ">Figure 4
<p>Redundancy analysis (RDA) of bacterial communities at the dominant genus and environmental variables. Red lines and arrows indicated dominant genera, and blue color represented environmental factors. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 5
<p>Network heat map between dominant functional groups and environmental factors. The connecting lines’ colors represent the significance level of functional groups concerning environmental factors. The grid colors and numbers depict the correlation magnitude between environmental factors. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 6
<p>Co-occurrence networks of bacterial OTUs in four vegetations types (GL, grassland; LF, <span class="html-italic">L. gmelinii</span> forest; SF, <span class="html-italic">P. asperata</span> forest; PF, <span class="html-italic">P. sylvestris</span> forest). Nodes are colored based on modularity class, and sizes reflect the degree of connection. Edge thickness represents Spearman (<span class="html-italic">R</span> &gt; |0.6|) and significant (<span class="html-italic">p</span> &lt; 0.05) correlations.</p> Full article ">
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop