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. 2023 Mar 29:14:1147162.
doi: 10.3389/fmicb.2023.1147162. eCollection 2023.

Genome-resolved analyses of oligotrophic groundwater microbial communities along phenol pollution in a continuous-flow biodegradation model system

Affiliations

Genome-resolved analyses of oligotrophic groundwater microbial communities along phenol pollution in a continuous-flow biodegradation model system

Maryam Yavari-Bafghi et al. Front Microbiol. .

Abstract

Groundwater pollution is one of the major environmental concerns. The entrance of pollutants into the oligotrophic groundwater ecosystems alters native microbial community structure and metabolism. This study investigated the application of innovative Small Bioreactor Chambers and CaO2 nanoparticles for phenol removal within continuous-flow sand-packed columns for 6 months. Scanning electron microscopy and confocal laser scanning microscopy analysis were conducted to indicate the impact of attached biofilm on sand surfaces in bioremediation columns. Then, the influence of each method on the microbial biodiversity of the column's groundwater was investigated by next-generation sequencing of the 16S rRNA gene. The results indicated that the simultaneous application of biostimulation and bioaugmentation completely eliminated phenol during the first 42 days. However, 80.2% of phenol remained in the natural bioremediation column at the end of the experiment. Microbial diversity was decreased by CaO2 injection while order-level groups known for phenol degradation such as Rhodobacterales and Xanthomonadales dominated in biostimulation columns. Genome-resolved comparative analyses of oligotrophic groundwater prokaryotic communities revealed that Burkholderiales, Micrococcales, and Cytophagales were the dominant members of the pristine groundwater. Six-month exposure of groundwater to phenol shifted the microbial population towards increasing the heterotrophic members of Desulfobacterales, Pseudomonadales, and Xanthomonadales with the degradation potential of phenol and other hydrocarbons.

Keywords: biodiversity; bioremediation; metagenome; oligotrophic groundwater; phenol.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Schematic representation of column experiments. Column I: phenol removal in the abiotic condition by CaO2 nanoparticles (chemical), column II: natural bioremediation of phenol (blank), column III: phenol remediation by CaO2 nanoparticles and native groundwater microbial population (biostimulation), and column IV: phenol remediation by CaO2 nanoparticles and SBCs (biostimulation and bioaugmentation).
FIGURE 2
FIGURE 2
Remediation of phenol from groundwater in the column experiments. (A) Dissolved oxygen concentration (mg/L), (B) pH, (C) phenol removal (%), and (D) intrinsic microbial count (log CFU/mL). Abiotic column (▲), natural remediation column II (◆), biostimulation column III (■), and simultaneous biostimulation and bioaugmentation column IV (●). The red and orange dashed lines, respectively indicate 15 and 5 g CaO2 nanoparticles re-injection to provide the proper contaminant removal condition.
FIGURE 3
FIGURE 3
Acridine orange-stained confocal laser scanning microscopy (CLSM) images of biofilm thickness on the sand surface after 6 months. (A) Abiotic column I, (B) natural bioremediation column II, (C) biostimulation column III, and (D) biostimulation and bioaugmentation column IV.
FIGURE 4
FIGURE 4
Prokaryotic community composition of the groundwater samples according to the abundance of 16S rDNA gene reads in unassembled metagenomes. Rows are the name of samples (GW: unpolluted and R2: phenol polluted groundwater). Column names are microbial taxa at the phylum and order level. For some taxa with lower frequency, the sum of orders is displayed as others or in their corresponding higher taxonomic level. There are a total number of 34 taxa for both samples. Dendrograms represent the clustering of columns based on Pearson correlation. The figure was plotted using “circlize” and “ComplexHeatmap” packages in R.
FIGURE 5
FIGURE 5
Energy metabolism pathways modules present in recovered MAGs from the groundwater metagenomes. The columns represent the taxonomy recovered of MAGs. The color of each MAG indicates the MAG origin. The row shows the cluster of metabolic pathways. Reductive citrate cycle (Arnon–Buchanan cycle) (M00173), reductive acetyl-CoA pathway (Wood–Ljungdahl pathway) (M00377), and phosphate acetyltransferase-acetate kinase pathway (M00579). Methane oxidation, methanotroph (M00174), formaldehyde assimilation, serine pathway (M00346), formaldehyde assimilation, ribulose monophosphate pathway (M00345), and Acetyl-CoA pathway (M00422). Nitrogen fixation (M00175), assimilatory nitrate reduction (M00531), dissimilatory nitrate reduction (M00530), nitrification (M00528), and denitrification (M00529). Assimilatory sulfate reduction (M00176), dissimilatory sulfate reduction (M00596), and thiosulfate oxidation by SOX complex (M00595). For the presence of a module that has all the enzymes of a pathway the value 2 and for the module that lacks one of the enzymes of a pathway the value 1 is considered.
FIGURE 6
FIGURE 6
Hydrocarbon-degrading enzymes present in recovered MAGs from the groundwater metagenomes. Row names represent the taxonomy of recovered MAGs and their completeness is provided as a bar plot on the right side. The color indicates the MAG origin. Columns indicate the type of hydrocarbon and in the parenthesis is the name of the enzyme hydrolyzing this compound, followed by its corresponding KEGG orthologous accession number. The size of the dots indicates the presence or absence of each enzyme in each recovered MAG. The figure was plotted using the “reshape2” and “ggplot2” packages in RStudio.

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