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Journal of Arid Land
Journal of Arid Land  2024, Vol. 16 Issue (5): 699-724    DOI: 10.1007/s40333-024-0014-2     CSTR: 32276.14.s40333-024-0014-2
Research article     
Host plant traits play a crucial role in shaping the composition of epiphytic microbiota in the arid desert, Northwest China
ZHANG Jun1,2,3, ZHANG Yuanming1,2,3,*(), ZHANG Qi4
1State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2Xinjiang Key Laboratory of Biodiversity Conservation and Application in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
3Xinjiang Field Scientific Observation Research Station of Tianshan Wild Fruit Forest Ecosystem, Yili Botanical Garden, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
4College of Life Sciences, Shihezi University, Shihezi 832003, China
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Abstract  

Phyllosphere microorganisms are a crucial component of environmental microorganisms, highly influenced by host characteristics, and play a significant role in plant health and productivity. Nonetheless, the impact of host characteristics on shaping phyllosphere microbial communities of plants with different life forms remains ambiguous. Utilizing high-throughput sequencing technology, this study analyzed the diversity and community composition of phyllosphere epiphytic microorganisms (e.g., bacteria and fungi) of various plant life forms in the hinterland of the Gurbantunggut Desert, Northwest China. Functional annotation of prokaryotic taxa (FAPROTAX) and fungi function guild (FUNGuild) were employed to assess the ecological functions of microorganisms and to investigate the role of stochastic and deterministic processes in shaping phyllosphere microbial communities. Result showed a diverse array of phyllosphere epiphytic microorganisms in the desert plants, with Proteobacteria, Cyanobacteria, and Actinobacteriota dominating bacterial community, while Ascomycota and Basidiomycota were prevalent in fungal community. Comparison across different plant life forms highlighted distinct microbial communities, indicating strong filtering effects by plant characteristics. FAPROTAX prediction identified intracellular parasites (accounting for 27.44% of bacterial community abundance), chemoheterotrophy (10.12%), and phototrophy (17.41%) as the main functions of epiphytic bacteria on leaves of different life form plants. FUNGuild prediction indicated that phyllosphere epiphytic fungi primarily served as Saprotrophs (81.77%), Pathotrophs (17.41%), and Symbiotrophs (0.82%). Co-occurrence network analysis demonstrated a predominance of positive correlations among different microbial taxa. Raup-Crick dissimilarity index analysis revealed that deterministic processes predominantly influenced phyllosphere bacterial and fungal community assembly. Variance partitioning analysis and random forest modeling suggested that plant leaf functional traits significantly impacted both bacterial and fungal community composition, with fungal community composition showing a closer association with leaf nutrients and physiology compared with bacterial community composition. The distinct responses of bacterial and fungal communities to plant traits were attributed to the differing properties of bacteria and fungi, such as bacteria having higher potential dispersal rates and broader ecological niches than fungi. Overall, the results indicate that phyllosphere bacterial and fungal communities undergo similar community assembly processes, with fungi being more influenced by plant characteristics than bacteria. These findings offer novel insights into the ecology of phyllosphere microbial communities of desert plants.

Key words： phyllosphere epiphytic bacteria      phyllosphere epiphytic fungi      community structure      community diversity      functional diversity      plant life form      plant functional traits     
Received: 09 January 2024      Published: 31 May 2024
Corresponding Authors: *ZHANG Yuanming (E-mail: zhangym@ms.xjb.ac.cn)
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ZHANG Jun
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ZHANG Jun, ZHANG Yuanming, ZHANG Qi. Host plant traits play a crucial role in shaping the composition of epiphytic microbiota in the arid desert, Northwest China. Journal of Arid Land, 2024, 16(5): 699-724.

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http://jal.xjegi.com/10.1007/s40333-024-0014-2     OR     http://jal.xjegi.com/Y2024/V16/I5/699

Life form and code Species and code Base diameter
(cm)		 Plant height
(m)		 Crown area
(m2)
Tree (Tr) Haloxylon ammodendron (C.A.Mey.) Bunge (Ha) 1.55±0.23 1.25±0.25 0.51±0.14
Haloxylon periscum Bunge ex Boiss & Buhse (Hp) 1.51±0.31 1.24±0.32 0.54±0.13
Shrub (Sh) Calligonum caput-medusae Schrenk (Cc) 1.57±0.35 1.25±0.14 0.56±0.12
Calligonum leucocladum (Schrenk) Bunge (Cl) 1.52±0.24 1.24±0.23 0.55±0.09
Herb (He) Astragalus cognatus Schrenk (Ac) 1.48±0.32 1.19±0.21 0.56±0.11
Astragalus steinbergianus Sumn (As) 1.47±0.28 1.18±0.32 0.57±0.14
Table 1 Characteristics of various life-form plants
Fig. 1 Community structure of epiphytic bacterial communities (a) and fungal communities (b) of desert plants
Fig. 2 Abundance of epiphytic bacterial communities (a) and fungal communities (b) of different plant life forms at genus level. Bars are standard errors. He, herb; Sh, shrub; Tr, tree. The abbreviations are the same as in the following figures.
Fig. S1 Abundance of epiphytic bacterial communities (a) and fungal communities (b) of different plant species. Bars are standard errors. Ac, Astragalus cognatus Schrenk; As, Astragalus steinbergianus Sumn; Cc, Calligonum caput-medusae Schrenk; Cl, Calligonum leucocladum (Schrenk) Bunge; Ha, Haloxylon ammodendron (C. A. Mey.) Bunge; Hp, Haloxylon periscum Bunge ex Boiss & Buhse. The abbreviations are the same as in the following figures and tables.
Fig. 3 Alpha diversity of epiphytic bacterial communities (a-c) and fungal communities (d-f) of different plant life forms. Different lowercase letters indicate significant differences among different plant life forms at P<0.050 level. Boxes indicate the IQR (interquartile range, 75th to 25th of the data). The median value is shown as a line within the box. Lines extend to the most extreme value within 1.5×IQR.
Fig. S2 Alpha diversity of epiphytic bacterial communities (a-c) and fungal communities (d-f) of different plant species. Different lowercase letters indicate significant differences among different plant species at P<0.050 level. Boxes indicate the IQR (interquartile range, 75th to 25th of the data). The median value is shown as a line within the box. Lines extend to the most extreme value within 1.5×IQR.
Fig. 4 Venn diagram and principal coordinates analysis (PCoA) of epiphytic bacterial communities (a, b) and fungal communities (c, d). Ha, Haloxylon ammodendron (C. A. Mey.) Bunge; Hp, Haloxylon periscum Bunge ex Boiss & Buhse; Cc, Calligonum caput-medusae Schrenk; Cl, Calligonum leucocladum (Schrenk) Bunge; Ac, Astragalus cognatus Schrenk; As, Astragalus steinbergianus Sumn.
Fig. 5 Raup-Crick dissimilarity index and non-metric multi-dimensional dissimilarity (NMDS) index of phyllosphere epiphytic bacterial communities (a, b) and fungal communities (c, d) of different plant life forms. The median value is shown as a line within the box and outlier is shown as circle in Figure 5a and c.
Fig. S3 Raup-Crick dissimilarity index and non-metric multi-dimensional dissimilarity (NMDS) index of phyllosphere epiphytic bacterial communities (a and b) and fungal communities (c and d) of different plant species. Outlier is shown as circle in Figure S3a and c
Fig. S4 Co-occurrence networks of phyllosphere epiphytic bacteria (a-c) and fungi (d-f) of different plant life forms. He, herb; Sh, shrub; Tr, tree.
Fig. S5 Co-occurrence networks of phyllosphere epiphytic bacteria (a-f) and fungi (g-l) of different plant species
Bacterial network topological
characteristics		 He Sh Tr Fungal network topological
characteristics		 He Sh Tr
Total node 177 199 187 Total node 198 215 235
Total edge 1327 2087 6573 Total edge 945 898 3261
Positive edge percentage (%) 100.00 99.90 99.82 Positive edge percentage (%) 100.00 100.00 97.76
Average degree 14.994 20.975 70.299 Average degree 9.545 8.353 27.753
Average weighted degree 12.919 18.333 57.289 Average weighted degree 8.627 7.431 23.608
Average clustering coefficient 0.705 0.743 0.730 Average clustering coefficient 0.732 0.691 0.701
Average path length 4.462 3.985 1.809 Average path length 6.360 8.095 3.171
Modularity 0.464 0.572 0.206 Modularity 0.820 0.816 0.450
Number of weakly connected
component		 7 8 1 Number of weakly
connected components		 9 3 4
Network diameter 13 11 5 Network diameter 16 22 12
Graph density 8.5 10.6 37.8 Graph density 4.8 3.9 11.9
Table S1 Characteristics of co-occurrence networks of phyllosphere epiphytic microorganisms of different plant life forms
Network topological characteristics Ac As Cc Cl Ha Hp
Bacteria
Total node 68 63 103 136 63 30
Total edge 136 121 284 479 154 55
Positive edges percentage (%) 100.00 100.00 99.30 99.37 98.70 96.36
Average degree 4.000 3.841 5.515 7.044 4.889 3.667
Average weighted degree 3.974 3.816 5.471 6.949 4.868 3.655
Average clustering coefficient 0.830 0.779 0.843 0.687 0.971 0.940
Average path length 1.678 1.587 1.741 2.649 1.116 1.293
Modularity 0.768 0.624 0.791 0.590 0.764 0.297
Number of weakly connected component 14 16 20 22 14 10
Network diameter 6 4 5 7 3 3
Graph density 6.0 6.2 5.4 5.2 7.9 12.6
Fungi
Total node 136 134 121 131 115 118
Total edge 780 478 575 456 176 517
Positive edges percentage (%) 99.74 99.79 100.00 99.56 100.00 97.49
Average degree 11.471 7.134 9.504 6.692 3.061 8.763
Average weighted degree 11.307 7.054 9.402 6.886 3.042 8.683
Average clustering coefficient 0.811 0.763 0.928 0.782 0.766 0.833
Average path length 2.098 1.790 1.217 1.895 1.296 1.832
Modularity 0.620 0.828 0.785 0.768 0.885 0.418
Number of weakly connected component 10 18 21 18 33 23
Network diameter 7 6 4 6 4 6
Graph density 8.5 5.4 7.9 5.4 2.7 7.5
Table S2 Characteristics of co-occurrence networks of phyllosphere epiphytic microorganisms of different plant species
Fig. 6 Function prediction of epiphytic bacterial communities (a) and fungal communities (b) of different plant life forms
Fig. S6 Function prediction of phyllosphere epiphytic bacterial communities (a) and fungal communities (b) of different plant species
Fig. S7 Functional traits of different plant leaves. Different lowercase letters indicate significant differences among different plant species at P<0.050 level. (a), LA (leaf area); (b), BL (blade length); (c), BW (blade width); (d), SLA (specific leaf area); (e), TC (total carbon); (f), TN (total nitrogen); (g), TP (total phosphorus); (h), TK (total potassium); (i), SS (soluble sugar); (j), ST (starch); (k), TPH (total phenol); (l), TF (total flavone). Boxes indicate the IQR (interquartile range, 75th to 25th of the data). The median value is shown as a line within the box. Lines extend to the most extreme value within 1.5×IQR. Outlier is shown as circle.
Bacterial/fungal community property LA (cm2) BL (cm) BW (cm) SLA (cm2/g) TC (mg/g) TN (mg/g)
Bacteria
Abundance 0.312
P=0.001		 0.526
P=0.001		 0.486
P=0.001		 0.640
P=0.001		 0.313
P=0.001		 0.177
P=0.004
Alpha diversity -0.094
P=0.812		 -0.039
P=0.667		 -0.091
P=0.836		 -0.096
P=0.975		 0.068
P=0.203		 0.029
P=0.325
Community composition 0.161
P=0.353		 0.203
P=0.242		 0.122
P=0.484		 0.011
P=0.964		 -0.244
P=0.171		 0.074
P=0.683
Fungi
Abundance 0.291
P=0.001		 0.326
P=0.001		 0.370
P=0.001		 0.406
P=0.001		 0.195
P=0.002		 0.265
P=0.001
Alpha diversity -0.124
P=0.982		 0.150
P=0.016		 -0.070
P=0.842		 0.006
P=0.398		 0.435
P=0.001		 -0.056
P=0.775
Community composition 0.373
P=0.032		 -0.472
P=0.001		 0.522
P=0.001		 0.434
P=0.010		 0.531
P=0.001		 0.174
P=0.312
Bacterial/fungal community property TP (mg/g) TK (mg/g) SS (mg/g) ST (mg/g) TPH (mg/g) TF (mg/g)
Bacteria
Abundance 0.298
P=0.001		 0.227
P=0.001		 0.039
P=0.224		 0.149
P=0.003		 0.496
P=0.001		 0.419
P=0.001
Alpha diversity -0.101
P=0.960		 0.009
P=0.374		 0.571
P=0.001		 0.383
P=0.001		 -0.036
P=0.687		 -0.078
P=0.925
Community composition -0.232
P=0.182		 0.272
P=0.114		 -0.601
P=0.001		 0.382
P=0.021		 -0.222
P=0.201		 0.011
P=0.933
Fungi
Abundance 0.406
P=0.001		 0.227
P=0.003		 0.400
P=0.001		 0.514
P=0.001		 0.142
P=0.016		 0.036
P=0.221
Alpha diversity -0.006
P=0.496		 0.138
P=0.027		 0.198
P=0.005		 0.11
P=0.030		 0.072
P=0.092		 0.025
P=0.291
Community composition 0.763
P=0.001		 0.373
P=0.031		 0.072
P=0.691		 0.494
P=0.001		 -0.242
P=0.164		 -0.183
P=0.302
Table 2 Spearman's correlation coefficient between bacterial and fungal community properties and leaf functional traits
Fig. 7 Variance partitioning analysis and hierarchical segmentation results of canonical analysis of epiphytic bacterial communities (a) and fungal communities (b)
Fig. 8 Importance of random forest modelling environmental factors in predicting epiphytic bacterial communities (a) and fungal communities (b). MSE, mean squared error, *, P<0.050 level.
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