scholarly journals Microbial community structure in aquifers associated with arsenic: analysis of 16S rRNA and arsenite oxidase genes

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10653
Author(s):  
Prinpida Sonthiphand ◽  
Pasunun Rattanaroongrot ◽  
Kasarnchon Mek-yong ◽  
Kanthida Kusonmano ◽  
Chalida Rangsiwutisak ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Distribution Patterns ◽  
Community Structures ◽  
Shallow Aquifers ◽  
Aquifer Management ◽  
Microbial Distribution ◽  
Oxidation Reduction ◽  
Microbial Community Structures ◽  
Arsenite Oxidizing Bacteria

The microbiomes of deep and shallow aquifers located in an agricultural area, impacted by an old tin mine, were explored to understand spatial variation in microbial community structures and identify environmental factors influencing microbial distribution patterns through the analysis of 16S rRNA and aioA genes. Although Proteobacteria, Cyanobacteria, Actinobacteria, Patescibacteria, Bacteroidetes, and Epsilonbacteraeota were widespread across the analyzed aquifers, the dominant taxa found in each aquifer were unique. The co-dominance of Burkholderiaceae and Gallionellaceae potentially controlled arsenic immobilization in the aquifers. Analysis of the aioA gene suggested that arsenite-oxidizing bacteria phylogenetically associated with Alpha-, Beta-, and Gamma proteobacteria were present at low abundance (0.85 to 37.13%) and were more prevalent in shallow aquifers and surface water. The concentrations of dissolved oxygen and total phosphorus significantly governed the microbiomes analyzed in this study, while the combination of NO3--N concentration and oxidation-reduction potential significantly influenced the diversity and abundance of arsenite-oxidizing bacteria in the aquifers. The knowledge of microbial community structures and functions in relation to deep and shallow aquifers is required for further development of sustainable aquifer management.

scholarly journals The Microbial Community Structure in Petroleum-Contaminated Sediments Corresponds to Geophysical Signatures

2007 ◽  
Vol 73 (9) ◽  
pp. 2860-2870 ◽  
Author(s):  
Jonathan P. Allen ◽  
Estella A. Atekwana ◽  
Eliot A. Atekwana ◽  
Joseph W. Duris ◽  
D. Dale Werkema ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Contaminated Sediments ◽  
Microbial Populations ◽  
Rrna Gene ◽  
Community Structures ◽  
Microbial Community Structures ◽  
Gene Libraries ◽  
Cost Efficient

ABSTRACT The interdependence between geoelectrical signatures at underground petroleum plumes and the structures of subsurface microbial communities was investigated. For sediments contaminated with light non-aqueous-phase liquids, anomalous high conductivity values have been observed. Vertical changes in the geoelectrical properties of the sediments were concomitant with significant changes in the microbial community structures as determined by the construction and evaluation of 16S rRNA gene libraries. DNA sequencing of clones from four 16S rRNA gene libraries from different depths of a contaminated field site and two libraries from an uncontaminated background site revealed spatial heterogeneity in the microbial community structures. Correspondence analysis showed that the presence of distinct microbial populations, including the various hydrocarbon-degrading, syntrophic, sulfate-reducing, and dissimilatory-iron-reducing populations, was a contributing factor to the elevated geoelectrical measurements. Thus, through their growth and metabolic activities, microbial populations that have adapted to the use of petroleum as a carbon source can strongly influence their geophysical surroundings. Since changes in the geophysical properties of contaminated sediments parallel changes in the microbial community compositions, it is suggested that geoelectrical measurements can be a cost-efficient tool to guide microbiological sampling for microbial ecology studies during the monitoring of natural or engineered bioremediation processes.

Revealing microbial community structures in large- and small-scale activated sludge systems by barcoded pyrosequencing of 16S rRNA gene

2012 ◽  
Vol 66 (10) ◽  
pp. 2155-2161 ◽  
Author(s):  
Purnika Damindi Ranasinghe ◽  
Hiroyasu Satoh ◽  
Mamoru Oshiki ◽  
Kenshiro Oshima ◽  
Wataru Suda ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Microbial Community ◽  
16S Rrna ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Small Scale ◽  
Rrna Gene ◽  
Community Structures ◽  
Microbial Community Structures ◽  
Insight Into

The diversity of bacterial groups in activated sludge from large- and small-scale wastewater treatment plants was explored by barcoded pyrosequencing of 16S rRNA gene. Activated sludge samples (three small and 17 large scale) were collected from 12 wastewater treatment plants to clarify precise taxonomy and relative abundances. DNA was extracted, and amplified by 4 base barcoded 27f/519r primer set. The 454 Titanium (Roche) pyrosequences were obtained and analyses performed by Quantitative Insight Into Microbial Ecology (QIIME) with around 100,000 reads. Sequence statistics were computed, while constructing a phylogenetic tree and heatmap. Computed results explained total microbial diversity at phylum and class level and resolution was further extended to Operational Taxonomic Unit (OTU) based taxonomic assignment for investigating community distribution based on individual sample. Composition of sequence reads were compared and microbial community structures for large- and small-scale treatment plants were identified as major phyla (Proteobacteria and Bacteroidetes) and classes (Betaproteobacteria and Bacteroidetes). Also, family level breakdowns were explained and differences in family Nitrospiraceae and phylum Actinobacteria found at their species level were also illustrated. Thus, the pyrosequencing method provides high resolution insight into microbial community structures in activated sludge that might have been unnoticed with conventional approaches.

scholarly journals Microbial Population Changes during Bioremediation of an Experimental Oil Spill

1999 ◽  
Vol 65 (8) ◽  
pp. 3566-3574 ◽  
Author(s):  
Sarah J. MacNaughton ◽  
John R. Stephen ◽  
Albert D. Venosa ◽  
Gregory A. Davis ◽  
Yun-Juan Chang ◽  
...  
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
Oil Spill ◽  
Phospholipid Fatty Acid ◽  
Community Structures ◽  
Gram Negative ◽  
Dgge Analysis ◽  
16S Rdna Pcr ◽  
Microbial Community Structures ◽  
Plfa Analysis

ABSTRACT Three crude oil bioremediation techniques were applied in a randomized block field experiment simulating a coastal oil spill. Four treatments (no oil control, oil alone, oil plus nutrients, and oil plus nutrients plus an indigenous inoculum) were applied. In situ microbial community structures were monitored by phospholipid fatty acid (PLFA) analysis and 16S rDNA PCR-denaturing gradient gel electrophoresis (DGGE) to (i) identify the bacterial community members responsible for the decontamination of the site and (ii) define an end point for the removal of the hydrocarbon substrate. The results of PLFA analysis demonstrated a community shift in all plots from primarily eukaryotic biomass to gram-negative bacterial biomass with time. PLFA profiles from the oiled plots suggested increased gram-negative biomass and adaptation to metabolic stress compared to unoiled controls. DGGE analysis of untreated control plots revealed a simple, dynamic dominant population structure throughout the experiment. This banding pattern disappeared in all oiled plots, indicating that the structure and diversity of the dominant bacterial community changed substantially. No consistent differences were detected between nutrient-amended and indigenous inoculum-treated plots, but both differed from the oil-only plots. Prominent bands were excised for sequence analysis and indicated that oil treatment encouraged the growth of gram-negative microorganisms within the α-proteobacteria andFlexibacter-Cytophaga-Bacteroides phylum. α-Proteobacteria were never detected in unoiled controls. PLFA analysis indicated that by week 14 the microbial community structures of the oiled plots were becoming similar to those of the unoiled controls from the same time point, but DGGE analysis suggested that major differences in the bacterial communities remained.

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