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. 2022 Nov 7;12(1):18901.
doi: 10.1038/s41598-022-23487-0.

Characterization of bacterial diversity between two coastal regions with heterogeneous soil texture

Maryam Zakavi  1 , Hossein Askari  2 , Mohammad Shahrooei  3
Affiliations

Characterization of bacterial diversity between two coastal regions with heterogeneous soil texture

Maryam Zakavi et al. Sci Rep. .

Abstract

Studying microbial diversity and the effects of external factors on the microbiome could expand our understanding of environmental alterations. Silt and sand are mineral particles that form soil texture and even though most of the soils on earth contain a fraction of them and some other soils form almost by them, their effects on the microbiome remained to elucidate. In this study, the bacterial biodiversity of sand and silt clay soils was investigated. Furthermore, their effects on plant growth have been determined. Our data showed that biodiversity and biomass of microbiome are higher in silt-based soil. It is interesting that the pseudomonas genera only exist in silt-based soil while it is in the absence of sand-based soil. In contrast, B. thuringiensis could be found in sand-based soil while it is not found in silt texture. Our data also demonstrated that there are no significant changes in stress response between the two groups however, differential physiological changes in plants inoculated with silt and sand based bacterial isolates have been observed. This data could indicate that smaller size particles could contain more bacteria with higher biodiversity due to providing more surfaces for bacteria to grow.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Changes in biodiversity and biomass of microbiome in response to silt and sand-based soils (A). Colony counting of microbiome isolated from sampling locations (B). Diversity of microbiome isolates collected from locations A and B.
Figure 2
Figure 2
(A–C) Represented hierarchical cluster analysis of the effect of isolates on wheat, canola, and maize plants, respectively. Drown by CLUSTER and Treeview softwares. Hierarchical clustering was done based on Euclidian distance and the complete linkage method. Colors were indicated the type of isolates impacts on plants. Accordingly, red, green, and black colors showed positive, negative, and no-effect isolates, respectively. The horizontal axis indicates plant growth parameters: shoot density (ShD), root density (RD), root dry weight (RDW), root length (RL), shoot dry weight (ShDW), shoot length (ShL) and shoot/root weight (ShR). The vertical axis shows the assayed bacterial isolates.
Figure 3
Figure 3
Influence of bacterial isolates on the overall growth of wheat, canola, and maize (A) in comparison to uninoculated control condition (B).
Figure 4
Figure 4
PCA analysis of all growth parameters of wheat, maize, and canola treated by isolates collected from locations A (silt) and B (sand).
See this image and copyright information in PMC

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