Kooperativer Bibliotheksverbund

UID:

Umfang: 1 online resource (290 pages)

Ausgabe: First edition.

ISBN: 9780443135323 , 0443135320

Inhalt: This book, 'Metagenomics in Effluent Treatment Plant', edited by Maulin P. Shah, provides an in-depth exploration of the application of metagenomics in the analysis and improvement of wastewater treatment processes. It covers topics such as the degradation of polycyclic aromatic hydrocarbons by bacterial communities, the analysis of complex microbial communities in soil and wastewater, and gene prediction through metagenomics. The book also delves into the role of microbial communities in industrial wastewater remediation and their impact on environmental changes. Aimed at researchers and practitioners in environmental microbiology and wastewater management, the book discusses current challenges, methodologies, and future perspectives in the field.

Anmerkung: Front Cover -- Microbial Metagenomics in Effluent Treatment Plant -- Copyright Page -- Contents -- List of contributors -- 1 Polycyclic aromatic hydrocarbon degradation by bacterial communities: a sustainable approach -- 1.1 Introduction -- 1.2 Genetics of polycyclic aromatic hydrocarbon-degrading bacteria -- 1.3 Conclusion and future perspectives -- References -- 2 Analysis of complex microbial communities in soil and wastewater treatment processes -- 2.1 Introduction -- 2.1.1 Anaerobic digestion and composting -- 2.2 Value of researching microbial communities in waste-transformation procedures -- 2.3 Cooccurrence network analysis for the characterization of microbial communities -- 2.3.1 Antibiotic resistance gene and microbial genotoxin detection by metagenomics in a natural setting -- 2.3.2 Antibiotics are being filtered out of wastewater -- 2.3.3 Toxic byproduct -- 2.4 Research aimed toward Phylogenetic Fingerprinting of the Whole Communities -- 2.4.1 Wastewater treatment plant microbiological diversity -- 2.4.2 The microbial mechanism for metal tolerance -- 2.5 Conclusion -- List of abbreviations -- References -- 3 Response of microbial community to environment changes -- 3.1 Introduction -- 3.1.1 Elevated CO2 -- 3.2 Effect of drought on soil microbes drought -- 3.3 Alpha diversity of microbes in carbon, nitrogen, and phosphorous cycle -- 3.4 Effect of excess rain and water on soil microbes -- 3.5 Different communities of soil microbes -- 3.6 Rise in temperature -- 3.7 Microbes in the soil and the rising incidence of fires -- 3.8 Biochemical properties of soil -- 3.9 Effect of microbes on gaseous exchange -- 3.10 Adapting to climate change through soil microbiome manipulation -- 3.10.1 Carbon cycle and soil microbes -- 3.10.2 Effect of biotic factors on soil rhizosphere. , 3.11 Recent developments in molecular methods for analyzing the soil microbiome -- 3.12 Changes in plant-microbe interaction caused by global warming -- 3.13 Case study: drought impacts on microbial communities in both minimally and heavily managed grassland -- 3.14 Case study microorganism -- 3.14.1 Heavy rainfall -- 3.15 Conclusion -- Abbreviations -- References -- 4 Gene prediction through metagenomics -- 4.1 Introduction -- 4.2 Genomics versus metagenomics -- 4.3 Gene prediction in Eukaryotes versus prokaryotes -- 4.4 Significance of metagenomics -- 4.5 Methods of gene prediction -- 4.6 Models and algorithms -- 4.7 MetaGUN for metagenomic fragments based on a machine learning approach of support vector machine -- 4.7.1 Architecture of MetaGUN algorithm -- 4.8 Glimmer -- 4.9 Algorithm structure -- 4.10 Ab initio gene identification in metagenomic sequences -- 4.11 Heuristic system of model parameters derivation -- 4.12 Orphelia -- 4.12.1 Metaprodigal -- 4.12.2 MGC -- 4.13 Metageneannotator -- 4.14 Predictions on short genomic sequences -- 4.15 Predictions on long genomic sequences -- 4.16 Applications of metagenomics -- 4.17 Agriculture -- 4.18 Biofuel -- 4.19 Biotechnology -- 4.20 Ecology -- 4.21 Environmental remediation -- 4.22 Gut microbe characterization -- 4.23 Infectious disease diagnosis -- 4.24 Arbovirus surveillance -- 4.25 Forensics -- 4.26 Drug discovery -- 4.27 Enzymes -- References -- Further reading -- 5 Elevating taxonomic profiling: the role and impact of bioinformatics software -- 5.1 Introduction -- 5.2 Metagenomics and taxonomy profiling -- 5.2.1 Importance of bioinformatics software -- 5.2.2 Taxonomic profiling -- 5.2.3 Metagenomic categorization -- 5.3 Basic techniques and tools -- 5.4 Types of taxonomic profiling -- 5.4.1 Taxonomic dependent method -- 5.4.1.1 Assembly-based taxonomic profiling of microbiome. , 5.4.1.2 Compositional approaches for metagenomic binning -- 5.4.1.3 Mapping-based recruitment of metagenomic reads -- 5.4.1.4 Marker-based taxonomic profiling -- 5.4.2 Taxonomic independent method -- 5.5 Metagenomic data analysis and interpretation -- 5.5.1 16S rRNA data analysis -- 5.5.2 Species-level metagenomic data analysis -- 5.5.3 Strain-level metagenomic data analysis -- 5.6 Application of metagenomics -- 5.6.1 Agricultural sector -- 5.6.2 Biofuel sector -- 5.6.3 Biotechnology sector -- 5.6.4 Pharmacology sector -- 5.7 Discussion and conclusion -- References -- Further reading -- 6 Industrial wastewater remediation by using microbial communities -- 6.1 Introduction of microbial populations -- 6.2 Different source of water toxicity -- 6.2.1 Commercial garbage -- 6.2.2 Sewage and wastewaters -- 6.2.3 Marine disposal -- 6.2.4 Oil leaks -- 6.2.5 Chemical fertilizers and pesticides -- 6.3 Recent progress for wastewater treatment -- 6.4 Advantages of microbial population in wastewater and solid waste treatment -- 6.4.1 Aerobic bacteria -- 6.4.2 Anaerobic bacteria -- 6.4.3 Facultative bacteria -- 6.4.4 Divvying up the water and waste -- 6.4.5 Cleaning up and purification -- 6.4.6 Challenges -- 6.4.7 The Danish plant survey -- 6.5 A comparative study with different substrate -- 6.6 Further improvements needed -- 6.7 Conclusions -- References -- 7 Microbial populations, function, and impact on environmental changes -- 7.1 Introduction -- 7.2 Role of metagenomics -- 7.2.1 Functional genes involved in the biogeochemical cycle -- 7.2.2 Each ecological cycle involves microorganisms -- 7.2.2.1 Carbon cycle -- 7.2.2.2 Microbes in methane production -- 7.2.2.3 Nitrogen cycle -- 7.2.2.4 Microbes in the sulfur cycle -- 7.2.2.5 Microbes in the phosphorus cycle -- 7.2.3 Microbes' contribution to bioremediation -- 7.2.3.1 Biodegradation. , 7.2.3.2 Metal detoxification -- 7.2.4 Bioremediation by microbial enzymes -- 7.2.4.1 Oxidoreductases -- 7.2.4.2 Oxygenases -- 7.2.4.3 Laccases -- 7.2.4.4 Peroxidases -- 7.2.4.5 Hydrolases -- 7.2.4.6 Lipases -- 7.2.4.7 Cellulases -- 7.2.4.8 Proteases -- 7.2.5 Functions of uncultured bacteria for soil enrichment -- 7.2.6 Low-complexity communities metagenomics -- 7.2.7 Enrichment-based metagenomics -- 7.2.7.1 In bioremediation -- 7.2.7.2 Plant-microbial interactions benefits -- 7.3 By reducing the availability of iron through the release of siderophores (low molecular weight), PGPR bacteria inhibit ... -- 7.4 Impact on microbes -- 7.4.1 Impact due to oil leakage -- 7.4.2 Agricultural practices alter functional genes -- 7.4.3 Increasing atmospheric CO2 levels -- 7.5 Conclusion -- References -- 8 Microbial bioremediation of industrial waste through traditional and omics approaches: challenges and future perspective -- 8.1 Introduction -- 8.2 Health risks associated with toxic contaminants -- 8.3 Microbes involved in bioremediation -- 8.4 Genetically engineered microbes for bioremediation -- 8.5 Omics-based tools for efficient bioremediation -- 8.5.1 Metagenomics -- 8.5.2 Metabolomics -- 8.5.3 Metatranscriptomics -- 8.6 Challenges in the implementation of bioremediation -- 8.7 Conclusion -- References -- 9 Oral metagenomics changes the game in carcinogenesis -- 9.1 Introduction -- 9.2 Oral microbiota and cancer -- 9.3 Oral metagenomics leads to oral megabank -- 9.4 Oral metagenomics applications -- 9.4.1 Oral metagenomics in cancer screening -- 9.4.2 Oral metagenomics in cancer therapeutics -- 9.4.3 Oral metagenomics in cancer precision medicine -- 9.4.4 Oral metagenomics in advanced research -- 9.4.5 Dental wastewater and cancer -- 9.5 Conclusion -- References -- 10 Probiotics and metagenomics' role in oral health -- 10.1 Introduction. , 10.1.1 Oral disease -- 10.1.2 Dental caries -- 10.1.3 Periodontal diseases -- 10.1.4 Cancer of the lips and oral cavity -- 10.2 Effector strain -- 10.3 Biotics and oral health -- 10.3.1 Probiotics -- 10.3.2 Prebiotics -- 10.3.3 Symbiotic and postbiotics -- 10.4 Molecular analysis of oral microbial -- 10.4.1 Preomics era -- 10.4.2 Early omics era -- 10.4.3 Metaomics -- 10.5 Oral health and metagenomics -- 10.6 Metagenomic and metabolic pathways -- 10.7 Engineering probiotics -- 10.8 Opportunities in oral metagenomics -- 10.9 Search for potential probiotics through metagenomics -- 10.10 Microbial metagenomics in dental wastewater treatment -- 10.11 Conclusion -- References -- 11 Metagenomics: a tool for haunting abandoned microbial community -- 11.1 Introduction -- 11.2 From genomics to metagenomics -- 11.2.1 Challenges in the metagenomic sequencing of data -- 11.2.2 The function of contigs and data integrity -- 11.3 Metagenomic gene prediction -- 11.4 Metagenomics: discovery of new dimensions of the virus world -- 11.5 Machine-learning tools for metagenomics gene prediction -- 11.5.1 Glimmer -- 11.5.2 GeneMarkS -- 11.5.3 MetaGeneMark -- 11.5.4 MetaGeneAnnotator -- 11.5.5 Prodigal -- 11.6 Data analysis -- 11.7 Use of orphelia for metagenomic gene prediction -- 11.8 Concluding remarks and future prospects -- References -- 12 Microbe-mediated mercury bioremediation for wastewater treatment -- 12.1 Introduction -- 12.2 Hg-resistant bacteria-mediated bioremediation -- 12.3 Genetically engineered bacteria-mediated bioremediation -- 12.4 Conclusion and future perspectives -- Acknowledgment -- References -- Index -- Back Cover.

Weitere Ausg.: ISBN 9780443135316

Weitere Ausg.: ISBN 0443135312

Sprache: Englisch

UID:

Umfang: 1 online resource (290 pages)

Ausgabe: 1st ed.

ISBN: 0-443-13532-0

Anmerkung: Front Cover -- Microbial Metagenomics in Effluent Treatment Plant -- Copyright Page -- Contents -- List of contributors -- 1 Polycyclic aromatic hydrocarbon degradation by bacterial communities: a sustainable approach -- 1.1 Introduction -- 1.2 Genetics of polycyclic aromatic hydrocarbon-degrading bacteria -- 1.3 Conclusion and future perspectives -- References -- 2 Analysis of complex microbial communities in soil and wastewater treatment processes -- 2.1 Introduction -- 2.1.1 Anaerobic digestion and composting -- 2.2 Value of researching microbial communities in waste-transformation procedures -- 2.3 Cooccurrence network analysis for the characterization of microbial communities -- 2.3.1 Antibiotic resistance gene and microbial genotoxin detection by metagenomics in a natural setting -- 2.3.2 Antibiotics are being filtered out of wastewater -- 2.3.3 Toxic byproduct -- 2.4 Research aimed toward Phylogenetic Fingerprinting of the Whole Communities -- 2.4.1 Wastewater treatment plant microbiological diversity -- 2.4.2 The microbial mechanism for metal tolerance -- 2.5 Conclusion -- List of abbreviations -- References -- 3 Response of microbial community to environment changes -- 3.1 Introduction -- 3.1.1 Elevated CO2 -- 3.2 Effect of drought on soil microbes drought -- 3.3 Alpha diversity of microbes in carbon, nitrogen, and phosphorous cycle -- 3.4 Effect of excess rain and water on soil microbes -- 3.5 Different communities of soil microbes -- 3.6 Rise in temperature -- 3.7 Microbes in the soil and the rising incidence of fires -- 3.8 Biochemical properties of soil -- 3.9 Effect of microbes on gaseous exchange -- 3.10 Adapting to climate change through soil microbiome manipulation -- 3.10.1 Carbon cycle and soil microbes -- 3.10.2 Effect of biotic factors on soil rhizosphere. , 3.11 Recent developments in molecular methods for analyzing the soil microbiome -- 3.12 Changes in plant-microbe interaction caused by global warming -- 3.13 Case study: drought impacts on microbial communities in both minimally and heavily managed grassland -- 3.14 Case study microorganism -- 3.14.1 Heavy rainfall -- 3.15 Conclusion -- Abbreviations -- References -- 4 Gene prediction through metagenomics -- 4.1 Introduction -- 4.2 Genomics versus metagenomics -- 4.3 Gene prediction in Eukaryotes versus prokaryotes -- 4.4 Significance of metagenomics -- 4.5 Methods of gene prediction -- 4.6 Models and algorithms -- 4.7 MetaGUN for metagenomic fragments based on a machine learning approach of support vector machine -- 4.7.1 Architecture of MetaGUN algorithm -- 4.8 Glimmer -- 4.9 Algorithm structure -- 4.10 Ab initio gene identification in metagenomic sequences -- 4.11 Heuristic system of model parameters derivation -- 4.12 Orphelia -- 4.12.1 Metaprodigal -- 4.12.2 MGC -- 4.13 Metageneannotator -- 4.14 Predictions on short genomic sequences -- 4.15 Predictions on long genomic sequences -- 4.16 Applications of metagenomics -- 4.17 Agriculture -- 4.18 Biofuel -- 4.19 Biotechnology -- 4.20 Ecology -- 4.21 Environmental remediation -- 4.22 Gut microbe characterization -- 4.23 Infectious disease diagnosis -- 4.24 Arbovirus surveillance -- 4.25 Forensics -- 4.26 Drug discovery -- 4.27 Enzymes -- References -- Further reading -- 5 Elevating taxonomic profiling: the role and impact of bioinformatics software -- 5.1 Introduction -- 5.2 Metagenomics and taxonomy profiling -- 5.2.1 Importance of bioinformatics software -- 5.2.2 Taxonomic profiling -- 5.2.3 Metagenomic categorization -- 5.3 Basic techniques and tools -- 5.4 Types of taxonomic profiling -- 5.4.1 Taxonomic dependent method -- 5.4.1.1 Assembly-based taxonomic profiling of microbiome. , 5.4.1.2 Compositional approaches for metagenomic binning -- 5.4.1.3 Mapping-based recruitment of metagenomic reads -- 5.4.1.4 Marker-based taxonomic profiling -- 5.4.2 Taxonomic independent method -- 5.5 Metagenomic data analysis and interpretation -- 5.5.1 16S rRNA data analysis -- 5.5.2 Species-level metagenomic data analysis -- 5.5.3 Strain-level metagenomic data analysis -- 5.6 Application of metagenomics -- 5.6.1 Agricultural sector -- 5.6.2 Biofuel sector -- 5.6.3 Biotechnology sector -- 5.6.4 Pharmacology sector -- 5.7 Discussion and conclusion -- References -- Further reading -- 6 Industrial wastewater remediation by using microbial communities -- 6.1 Introduction of microbial populations -- 6.2 Different source of water toxicity -- 6.2.1 Commercial garbage -- 6.2.2 Sewage and wastewaters -- 6.2.3 Marine disposal -- 6.2.4 Oil leaks -- 6.2.5 Chemical fertilizers and pesticides -- 6.3 Recent progress for wastewater treatment -- 6.4 Advantages of microbial population in wastewater and solid waste treatment -- 6.4.1 Aerobic bacteria -- 6.4.2 Anaerobic bacteria -- 6.4.3 Facultative bacteria -- 6.4.4 Divvying up the water and waste -- 6.4.5 Cleaning up and purification -- 6.4.6 Challenges -- 6.4.7 The Danish plant survey -- 6.5 A comparative study with different substrate -- 6.6 Further improvements needed -- 6.7 Conclusions -- References -- 7 Microbial populations, function, and impact on environmental changes -- 7.1 Introduction -- 7.2 Role of metagenomics -- 7.2.1 Functional genes involved in the biogeochemical cycle -- 7.2.2 Each ecological cycle involves microorganisms -- 7.2.2.1 Carbon cycle -- 7.2.2.2 Microbes in methane production -- 7.2.2.3 Nitrogen cycle -- 7.2.2.4 Microbes in the sulfur cycle -- 7.2.2.5 Microbes in the phosphorus cycle -- 7.2.3 Microbes' contribution to bioremediation -- 7.2.3.1 Biodegradation. , 7.2.3.2 Metal detoxification -- 7.2.4 Bioremediation by microbial enzymes -- 7.2.4.1 Oxidoreductases -- 7.2.4.2 Oxygenases -- 7.2.4.3 Laccases -- 7.2.4.4 Peroxidases -- 7.2.4.5 Hydrolases -- 7.2.4.6 Lipases -- 7.2.4.7 Cellulases -- 7.2.4.8 Proteases -- 7.2.5 Functions of uncultured bacteria for soil enrichment -- 7.2.6 Low-complexity communities metagenomics -- 7.2.7 Enrichment-based metagenomics -- 7.2.7.1 In bioremediation -- 7.2.7.2 Plant-microbial interactions benefits -- 7.3 By reducing the availability of iron through the release of siderophores (low molecular weight), PGPR bacteria inhibit ... -- 7.4 Impact on microbes -- 7.4.1 Impact due to oil leakage -- 7.4.2 Agricultural practices alter functional genes -- 7.4.3 Increasing atmospheric CO2 levels -- 7.5 Conclusion -- References -- 8 Microbial bioremediation of industrial waste through traditional and omics approaches: challenges and future perspective -- 8.1 Introduction -- 8.2 Health risks associated with toxic contaminants -- 8.3 Microbes involved in bioremediation -- 8.4 Genetically engineered microbes for bioremediation -- 8.5 Omics-based tools for efficient bioremediation -- 8.5.1 Metagenomics -- 8.5.2 Metabolomics -- 8.5.3 Metatranscriptomics -- 8.6 Challenges in the implementation of bioremediation -- 8.7 Conclusion -- References -- 9 Oral metagenomics changes the game in carcinogenesis -- 9.1 Introduction -- 9.2 Oral microbiota and cancer -- 9.3 Oral metagenomics leads to oral megabank -- 9.4 Oral metagenomics applications -- 9.4.1 Oral metagenomics in cancer screening -- 9.4.2 Oral metagenomics in cancer therapeutics -- 9.4.3 Oral metagenomics in cancer precision medicine -- 9.4.4 Oral metagenomics in advanced research -- 9.4.5 Dental wastewater and cancer -- 9.5 Conclusion -- References -- 10 Probiotics and metagenomics' role in oral health -- 10.1 Introduction. , 10.1.1 Oral disease -- 10.1.2 Dental caries -- 10.1.3 Periodontal diseases -- 10.1.4 Cancer of the lips and oral cavity -- 10.2 Effector strain -- 10.3 Biotics and oral health -- 10.3.1 Probiotics -- 10.3.2 Prebiotics -- 10.3.3 Symbiotic and postbiotics -- 10.4 Molecular analysis of oral microbial -- 10.4.1 Preomics era -- 10.4.2 Early omics era -- 10.4.3 Metaomics -- 10.5 Oral health and metagenomics -- 10.6 Metagenomic and metabolic pathways -- 10.7 Engineering probiotics -- 10.8 Opportunities in oral metagenomics -- 10.9 Search for potential probiotics through metagenomics -- 10.10 Microbial metagenomics in dental wastewater treatment -- 10.11 Conclusion -- References -- 11 Metagenomics: a tool for haunting abandoned microbial community -- 11.1 Introduction -- 11.2 From genomics to metagenomics -- 11.2.1 Challenges in the metagenomic sequencing of data -- 11.2.2 The function of contigs and data integrity -- 11.3 Metagenomic gene prediction -- 11.4 Metagenomics: discovery of new dimensions of the virus world -- 11.5 Machine-learning tools for metagenomics gene prediction -- 11.5.1 Glimmer -- 11.5.2 GeneMarkS -- 11.5.3 MetaGeneMark -- 11.5.4 MetaGeneAnnotator -- 11.5.5 Prodigal -- 11.6 Data analysis -- 11.7 Use of orphelia for metagenomic gene prediction -- 11.8 Concluding remarks and future prospects -- References -- 12 Microbe-mediated mercury bioremediation for wastewater treatment -- 12.1 Introduction -- 12.2 Hg-resistant bacteria-mediated bioremediation -- 12.3 Genetically engineered bacteria-mediated bioremediation -- 12.4 Conclusion and future perspectives -- Acknowledgment -- References -- Index -- Back Cover.

Weitere Ausg.: ISBN 0-443-13531-2

Sprache: Englisch