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Omics-Enabled Evaluation of Microbial Communities in Acidic Environmental Systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Omics-Enabled Evaluation of Microbial Communities in Acidic Environmental Systems./
作者:	Ayala, Diana K.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	209 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:	Dissertations Abstracts International83-03B.
標題:	Reactors. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28841684
ISBN:	9798460447855

Omics-Enabled Evaluation of Microbial Communities in Acidic Environmental Systems.
Ayala, Diana K.

Omics-Enabled Evaluation of Microbial Communities in Acidic Environmental Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 209 p.

Source: Dissertations Abstracts International, Volume: 83-03, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2021.

This item must not be sold to any third party vendors.

Mining activity accelerates the generation of an extremely toxic fluid known as acid mine drainage (AMD). AMD has low pH and high sulfate, iron, and other metal(loid)s content. Environments impacted by AMD are uninhabitable for most biota. However, acid-tolerant and acidophilic microorganisms thrive under AMD harsh conditions relying on sulfur and iron compounds as main electron donors and acceptors. They are resistant to metal toxicity and can even promote metal precipitation. Many of these microorganisms are now applied in greener technologies for mining and AMD remediation purposes. In the first part of this dissertation, I studied microbial communities responsible for ferrous iron oxidation in lab-scale low-pH reactors. Such reactors constitute a cost-effective alternative for the removal of iron, Fe(II), from AMD. Like many microbial reactors, their overall function can be affected by environmental perturbations such as changes in pH. However, reactors, previously operated by Dr. William Burgos's group at different pH values and Fe(II) concentrations, were shown to be stable with respect to the general rate of microbial Fe(II) oxidation. In chapter 2, I focused on studying biofilms collected at three different times from the reactors when operated under the same chemical conditions (e.g., pH = 2.7 and influent [Fe(II)] = 300 mg.L-1). The microbial communities had differential growth of multiple autotrophic Fe(II) oxidizers affiliated with Acidithiobacillus, Ferrovum, and Leptospirillum genera. Metagenomic analyses of these communities revealed differences in the metabolic potential of the dominant taxa for key metabolic functions such as Fe(II) oxidation, carbon fixation, oxygen reduction, nitrogen acquisition, and biofilm formation. The distinct metabolic potential of the autotrophic Fe(II) oxidizers allowed their access to different resources over time and coexistence in the biofilm. The distribution of key metabolic functions across the multiple coexisting taxa supported functional redundancy and imparted stability to the reactors with respect to Fe(II) oxidation at low pH. In the second part of this dissertation, I focused on microbial communities living in the acidic pit lake Cueva de la Mora (CM) located in the Iberian Pyrite Belt in Spain. CM is a stratified lake with dramatic physico-chemical gradients and increasing metal concentrations with depth. It is one of the most extensively characterized acidic pit lakes in the world. However, knowledge gaps existed with respect to active microbial activity shaping the unique geochemistry of CM and potentially contributing to the lake's natural attenuation. By using a combination of metagenomics and metatranscriptomics, I studied the in situ microbiology of this acidic pit lake from three perspectives: metal resistance (Chapter 3), element cycling (Chapter 4), and contributions to biosulfidogenesis (Chapter 5). CM has three distinct microbial communities characterizing the upper layer, chemocline, and deep layer of the lake. Chapter 3 described the microbial composition of each layer by shotgun metagenomics only. Chapter 4 included results from amplicon sequencing. The upper layer was dominated by the green algae Coccomyxa onubensis from the phylum Chlorophyta. Surprisingly, despite having very limited available light, C. onubensis was also present in the chemocline along with bacteria mainly from the phylum Proteobacteria. Desulfomonile spp. were the most abundant bacteria in the chemocline followed by taxa affiliated with the order Ca. Acidulodesulfobacterales (non-described previously). Until now, the deep layer was largely uncharacterized. Currently, the metagenomic analysis revealed abundance of the archaea Euryarchaeota along with bacteria from the superphylum Patescibacteria. Other abundant bacteria were part of the phyla Actinobacteria, Chloroflexi, and Nitrospirae. Findings with respect to microbial metal resistance in CM were described in Chapter 3. A database of 222 metal resistant genes (MRGs) was constructed and used to compare MRGs across the three communities representing each layer of the lake. Genes (from metagenomes) and transcripts (from metatranscriptomes) annotated as MRGs were quantified per layer and classified by mechanisms of resistance and metal(loid). Eukaryotes, bacteria, and archaea expressed different metal resistance strategies. Expression of genes involved in resistance to the most toxic metals was not correlated to dissolved metal concentrations, especially for As and Cu. Finally, MRG expression patterns were studied among in silico populations (represented by metagenome assembled genomes - MAGs) from the same depth, and differences in metal resistance mechanisms among members of the same community were found. Chapter 4 focused on the active roles of predominant phyla in carbon, sulfur, iron, and nitrogen cycling in CM. The green algae Coccomyxa onubensis were active in the upper layer and chemocline and provided organic carbon to the less abundant heterotrophic bacteria in the upper layer and chemocline. Organic carbon associated with settling ferric iron minerals dissolved in the deep layer might fuel the heterotrophic activity of the most abundant taxa in the deep layer: Thermoplasmatales (Euryarchaeota). Autotrophic activity was observed in the chemocline and deep layer mainly associated with bacteria from the phylum Proteobacteria, Actinobacteria, Chloroflexi, and/or Nitrospirae. As expected, microbial sulfide/sulfur oxidation was active in the chemocline associated with Desulfomonile and Ca. Acidulodesulfobacterium populations which were also involved in sulfate reduction. Sulfide/sulfur oxidation was surprisingly active in the deep layer associated with the most abundant taxa (Euryarchaeota) and other less abundant bacteria such as Actinobacteria populations. The abundance of transcripts involved in oxygen respiration in the deep layer was also unexpected and related to potential sulfur-oxidizing populations. Activity for microbial sulfate reduction in the deep layer was associated with uncultured taxa from Actinobacteria, Chloroflexi, Nitrospirae, Firmicutes, and Proteobacteria. Fe(II) oxidation was mainly observed in the chemocline contributed by Ferrovum, Leptospirillum, and Ca. Acidulodesulfobacterium taxa. Although expected in the chemocline, no genomic information was gathered to support activity for Fe(III) reduction. The deep layer had Fe(III) reduction activity associated with low abundant Geobacter bacteria. Nitrogen fixation, nitrate reduction, and ammonia oxidation were active in the chemocline with Ca. Acidulodesulfobacterium populations as main contributors. In contrast the upper layer presented active assimilatory nitrogen metabolisms associated with Coccomyxa, and the deep layer presented dissimilatory nitrate reduction associated with uncultured Actinobacteria and Proteobacteria. Chapter 5 described novel acidophilic populations involved in active biosulfidogenesis in the deep layer of CM. Biosulfidogenesis is the generation of sulfide by microbial reduction of oxidized sulfur compounds. Sulfide precipitates dissolved metals as metal-sulfides that can be removed from the system. Despite the high sulfate and metal concentrations of the deep layer of CM, biosulfidogenic taxa had not been reported before. In Chapter 5, I reconstructed eighteen high quality MAGs from the deep layer that represented abundant phyla such as Euryarchaeota, Parcubacteria, Actinobacteria, Chloroflexi, and Nitrospirae. A phylogenetic analysis of the MAGs revealed their novelty as no similar culture or uncultured genomes to the MAGs were found. Thirteen of these MAGs had at least one gene, and three MAGs presented most genes and transcripts involved in sulfate reduction. The three MAGs belonged to the Actinobacteria, Chloroflexi, and Nitrospirae phyla, with no previous representatives of acidophilic and mesophilic sulfate reducers.

ISBN: 9798460447855Subjects--Topical Terms:

3681735
Reactors.
Subjects--Index Terms:

Microbial communities

Omics-Enabled Evaluation of Microbial Communities in Acidic Environmental Systems.
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500 $a Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
500 $a Includes supplementary digital materials.
500 $a Advisor: Burgos, William;Macalady, Jennifer.
502 $a Thesis (Ph.D.)--The Pennsylvania State University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Mining activity accelerates the generation of an extremely toxic fluid known as acid mine drainage (AMD). AMD has low pH and high sulfate, iron, and other metal(loid)s content. Environments impacted by AMD are uninhabitable for most biota. However, acid-tolerant and acidophilic microorganisms thrive under AMD harsh conditions relying on sulfur and iron compounds as main electron donors and acceptors. They are resistant to metal toxicity and can even promote metal precipitation. Many of these microorganisms are now applied in greener technologies for mining and AMD remediation purposes. In the first part of this dissertation, I studied microbial communities responsible for ferrous iron oxidation in lab-scale low-pH reactors. Such reactors constitute a cost-effective alternative for the removal of iron, Fe(II), from AMD. Like many microbial reactors, their overall function can be affected by environmental perturbations such as changes in pH. However, reactors, previously operated by Dr. William Burgos's group at different pH values and Fe(II) concentrations, were shown to be stable with respect to the general rate of microbial Fe(II) oxidation. In chapter 2, I focused on studying biofilms collected at three different times from the reactors when operated under the same chemical conditions (e.g., pH = 2.7 and influent [Fe(II)] = 300 mg.L-1). The microbial communities had differential growth of multiple autotrophic Fe(II) oxidizers affiliated with Acidithiobacillus, Ferrovum, and Leptospirillum genera. Metagenomic analyses of these communities revealed differences in the metabolic potential of the dominant taxa for key metabolic functions such as Fe(II) oxidation, carbon fixation, oxygen reduction, nitrogen acquisition, and biofilm formation. The distinct metabolic potential of the autotrophic Fe(II) oxidizers allowed their access to different resources over time and coexistence in the biofilm. The distribution of key metabolic functions across the multiple coexisting taxa supported functional redundancy and imparted stability to the reactors with respect to Fe(II) oxidation at low pH. In the second part of this dissertation, I focused on microbial communities living in the acidic pit lake Cueva de la Mora (CM) located in the Iberian Pyrite Belt in Spain. CM is a stratified lake with dramatic physico-chemical gradients and increasing metal concentrations with depth. It is one of the most extensively characterized acidic pit lakes in the world. However, knowledge gaps existed with respect to active microbial activity shaping the unique geochemistry of CM and potentially contributing to the lake's natural attenuation. By using a combination of metagenomics and metatranscriptomics, I studied the in situ microbiology of this acidic pit lake from three perspectives: metal resistance (Chapter 3), element cycling (Chapter 4), and contributions to biosulfidogenesis (Chapter 5). CM has three distinct microbial communities characterizing the upper layer, chemocline, and deep layer of the lake. Chapter 3 described the microbial composition of each layer by shotgun metagenomics only. Chapter 4 included results from amplicon sequencing. The upper layer was dominated by the green algae Coccomyxa onubensis from the phylum Chlorophyta. Surprisingly, despite having very limited available light, C. onubensis was also present in the chemocline along with bacteria mainly from the phylum Proteobacteria. Desulfomonile spp. were the most abundant bacteria in the chemocline followed by taxa affiliated with the order Ca. Acidulodesulfobacterales (non-described previously). Until now, the deep layer was largely uncharacterized. Currently, the metagenomic analysis revealed abundance of the archaea Euryarchaeota along with bacteria from the superphylum Patescibacteria. Other abundant bacteria were part of the phyla Actinobacteria, Chloroflexi, and Nitrospirae. Findings with respect to microbial metal resistance in CM were described in Chapter 3. A database of 222 metal resistant genes (MRGs) was constructed and used to compare MRGs across the three communities representing each layer of the lake. Genes (from metagenomes) and transcripts (from metatranscriptomes) annotated as MRGs were quantified per layer and classified by mechanisms of resistance and metal(loid). Eukaryotes, bacteria, and archaea expressed different metal resistance strategies. Expression of genes involved in resistance to the most toxic metals was not correlated to dissolved metal concentrations, especially for As and Cu. Finally, MRG expression patterns were studied among in silico populations (represented by metagenome assembled genomes - MAGs) from the same depth, and differences in metal resistance mechanisms among members of the same community were found. Chapter 4 focused on the active roles of predominant phyla in carbon, sulfur, iron, and nitrogen cycling in CM. The green algae Coccomyxa onubensis were active in the upper layer and chemocline and provided organic carbon to the less abundant heterotrophic bacteria in the upper layer and chemocline. Organic carbon associated with settling ferric iron minerals dissolved in the deep layer might fuel the heterotrophic activity of the most abundant taxa in the deep layer: Thermoplasmatales (Euryarchaeota). Autotrophic activity was observed in the chemocline and deep layer mainly associated with bacteria from the phylum Proteobacteria, Actinobacteria, Chloroflexi, and/or Nitrospirae. As expected, microbial sulfide/sulfur oxidation was active in the chemocline associated with Desulfomonile and Ca. Acidulodesulfobacterium populations which were also involved in sulfate reduction. Sulfide/sulfur oxidation was surprisingly active in the deep layer associated with the most abundant taxa (Euryarchaeota) and other less abundant bacteria such as Actinobacteria populations. The abundance of transcripts involved in oxygen respiration in the deep layer was also unexpected and related to potential sulfur-oxidizing populations. Activity for microbial sulfate reduction in the deep layer was associated with uncultured taxa from Actinobacteria, Chloroflexi, Nitrospirae, Firmicutes, and Proteobacteria. Fe(II) oxidation was mainly observed in the chemocline contributed by Ferrovum, Leptospirillum, and Ca. Acidulodesulfobacterium taxa. Although expected in the chemocline, no genomic information was gathered to support activity for Fe(III) reduction. The deep layer had Fe(III) reduction activity associated with low abundant Geobacter bacteria. Nitrogen fixation, nitrate reduction, and ammonia oxidation were active in the chemocline with Ca. Acidulodesulfobacterium populations as main contributors. In contrast the upper layer presented active assimilatory nitrogen metabolisms associated with Coccomyxa, and the deep layer presented dissimilatory nitrate reduction associated with uncultured Actinobacteria and Proteobacteria. Chapter 5 described novel acidophilic populations involved in active biosulfidogenesis in the deep layer of CM. Biosulfidogenesis is the generation of sulfide by microbial reduction of oxidized sulfur compounds. Sulfide precipitates dissolved metals as metal-sulfides that can be removed from the system. Despite the high sulfate and metal concentrations of the deep layer of CM, biosulfidogenic taxa had not been reported before. In Chapter 5, I reconstructed eighteen high quality MAGs from the deep layer that represented abundant phyla such as Euryarchaeota, Parcubacteria, Actinobacteria, Chloroflexi, and Nitrospirae. A phylogenetic analysis of the MAGs revealed their novelty as no similar culture or uncultured genomes to the MAGs were found. Thirteen of these MAGs had at least one gene, and three MAGs presented most genes and transcripts involved in sulfate reduction. The three MAGs belonged to the Actinobacteria, Chloroflexi, and Nitrospirae phyla, with no previous representatives of acidophilic and mesophilic sulfate reducers.
520 $a These populations were predicted to be actively contributing to biosulfidogenesis in the deep layer. In accordance with Chapter 4 findings, MAGs representing some of the abundant populations in the deep layer had predicted activity for oxidation of sulfur compounds. These results suggest that CM has the potential of natural attenuation of metals by biosulfidogenesis, but such potential is diminished by cryptic sulfur cycling.
590 $a School code: 0176.
650 4 $a Reactors. $3 3681735
650 4 $a Phosphorus. $3 671778
650 4 $a Principal components analysis. $3 565921
650 4 $a Phylogenetics. $3 3561778
650 4 $a Oxidation. $3 714629
650 4 $a Bubbles. $3 1530439
650 4 $a Biofilms. $3 660574
650 4 $a Cytochrome. $3 3683768
650 4 $a Carbon. $3 604057
650 4 $a Bacteria. $3 550366
650 4 $a Taxonomy. $3 3556303
650 4 $a Genomes. $3 592593
650 4 $a Metabolism. $3 541349
650 4 $a Annotations. $3 3561780
650 4 $a Genes. $3 600676
650 4 $a Respiration. $3 610890
650 4 $a Microorganisms. $3 666946
650 4 $a Kinases. $3 3558077
650 4 $a Dehydrogenases. $3 3563094
650 4 $a Motility. $3 3683769
650 4 $a Nitrogen. $3 1314426
650 4 $a Microbiology. $3 536250
650 4 $a Biogeochemistry. $3 545717
650 4 $a Environmental science. $3 677245
650 4 $a Environmental engineering. $3 548583
650 4 $a Mining. $3 3544442
653 $a Microbial communities
653 $a Acid mine drainage
653 $a Environmental remediation
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