Amplicon Sequencing Analysis of Submerged Plant Microbiome Diversity and Screening for ACC Deaminase Production by Microbes

Abstract

Submerged plants can thrive entirely underwater, playing a crucial role in maintaining water quality, supporting aquatic organisms, and enhancing sediment stability. However, they face multiple challenges, including reduced light availability, fluctuating water conditions, and limited nutrient access. Despite these stresses, submerged plants demonstrate remarkable resilience through physiological and biochemical adaptations. Additionally, their interactions with microbial communities are increasingly recognized as pivotal in mitigating these environmental stresses. Understanding the diversity of these microbial communities is crucial for comprehending the complex interactions between submerged plants and their environments. This research aims to identify and screen microbes from submerged plant samples capable of producing 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase and to explore microbial diversity through metagenomic analysis. Microbes were isolated and screened for ACC deaminase production, and metagenomic techniques, including co-occurrence network analysis, were used to examine microbial diversity and interactions within the communities. ACC deaminase-producing microbes can significantly enhance plant metabolism under stress conditions. The identification of the culturable bacteria revealed that most of these microbes belong to the genera Pseudomonas, Bacillus, and Acinetobacter. A total of 177 microbial strains were cultured, with molecular identification revealing 79 reductant, 86 non-reductant, and 12 uncultured strains. Among 162 samples screened for ACC deaminase activity, 50 tested positive. To further understand microbial dynamics, samples were collected from both natural sources and artificial pond reservoirs to assess the impact of the location on flood-associated microbiomes in submerged plants. Metagenomic analysis was conducted on both the epiphytic and endophytic samples. By exploring the overall composition and dynamics of microbial communities associated with submerged plants, this research seeks to deepen our understanding of plant-microbe interactions in aquatic environments. The microbial screening helped to identify the diverse microbes associated with ACC deaminase activity in submerged plants and amplicon sequencing analysis paved the way towards identifying the impact of the location in shaping the microbiome and the diversity associated with endophytic and epiphytic microbes. Co-occurrence network analysis further highlighted the intricate interactions within these microbial communities. Notably, ACC deaminase activity was observed in plant-associated microbes across different locations, with distinct variations between epiphytic and endophytic populations as identified through co-occurrence network analysis.

Keywords: aquatic plants; co-occurrence network analysis; natural sources; stress tolerance.

Figure 1

Bar graphs illustrating the bacterial community compositions at different taxonomic levels across four samples (Endophytic A3 (EnA3), Endophytic H3 (EnH3), Epiphytic A3 (EpA3), Epiphytic H3 (EpH3)) at (a) the phylum level, (b) family level, and (c) genus level, depicting the shifts in microbial diversity and abundance.

Figure 2

(a) Bar chart illustrating the distribution of various species; the x-axis represents linear discriminant analysis (LDA) scores, indicating the discriminatory power of each species between the groups. Distinct colors represent diverse groups. (b) Horizontal bar chart comparing the relative abundance of species across three groups. The length of each bar represents the species’ abundance, with segments of distinct colors indicating the proportion of each species within each group. (c) Venn diagram depicting the overlap between four datasets labeled EnA3, EnH3, EpA3, and EpH3. The overlapping regions represent shared data points, with numerical values indicating the quantity of shared elements.

Figure 3

(a) Alpha diversity metric distribution: This plot illustrates the distribution of alpha diversity metrics among various sample groups. Each group is represented by a unique color and label on the x-axis, while the y-axis quantifies the alpha diversity metric. (b) Beta diversity PCoA scatter plot: this plot presents a two-dimensional ordination of samples based on beta diversity measures, providing a visual representation of the similarity or dissimilarity between microbial communities.

Figure 4

Co-occurrence networks of microbial communities: Four co-occurrence networks were constructed to analyze the relationships between microbial communities. Nodes in the networks represent individual OTUs (Operational Taxonomic Units), colored according to bacterial phyla. Edge colors indicate positive (red) and negative (blue) correlation coefficients. Spearman’s correlation coefficients (r > 0.6, p < 0.05) were used for network construction. The size of each node is proportional to its number of connections (degree).