Rhizobacteria and their metabolites as a promising green approach for the treatment of pesticide contaminated agricultural soils

Pesticides are employed to control and manage pest populations at tolerable levels. Pesticides are classified especially according to their chemical structure, toxicity, environmental persistence and target organisms. The massive use of these pollutants in addition to their toxic potential seriously threatens ecosystems and humans. For this reason, the development of green bioremediation processes is necessary. The ability of several microorganisms to bioremediate pesticides is mainly based on their biodegradation activity. Though bacteria have been proved to be efficient biodegraders and bioremediators, some fungi and archae could biodegrade recalcitrant pesticides too. The bioremediation of pesticide-contaminated agricultural sites may be optimized by considering the prevalent environmental conditions, the microorganisms that solubilize and degrade the pesticides most effectively, the variables that affect the biodegradation rate and the chemical structure of pesticides. This chapter explores the importance of pesticides as persistent organic pollutants in agricultural soils, particularly in the plants rhizospheric area and further illustrates the recent advances in pesticide microbial bioremediation, with emphasis on the metabolic potential of pseudomonads as a representative model of pesticide-degrading microorganisms.

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One step towards bioremediating a heavily polluted river: Metagenomic insights on the function of microbial community

10.1101/675876 ◽

2019 ◽

Author(s):

Luz Breton-Deval ◽

Ayixon Sanchez-Reyes ◽

Alejandro Sánchez-Flores ◽

Katy Juárez ◽

Patricia Mussali-Galante

Keyword(s):

Microbial Community ◽

Broad Spectrum ◽

Water Samples ◽

Shotgun Sequencing ◽

Metabolic Potential ◽

Polluted River ◽

Future Design ◽

Functional Potential ◽

One Step ◽

Bioremediation Processes

ABSTRACTThe objective of this study is to understand the functional potential of the microbial community related to bioremediation activity and its relationship with the pollution of each site to enhance the future design of more accurate bioremediation processes. Water samples were collected at four sampling sites along the Apatlaco River (S1-S4), and a whole metagenome shotgun sequencing was performed to know and understand the microbial community involved in bioremediation. Additionally, HMMER was used for searching sequence homologs related to PET and polystyrene biodegradation and metal transformation in Apatlaco River metagenomes. The Apatlaco River is characterized by the presence of a broad spectrum of microorganisms with the metabolic potential to carry out bioremediation activities. Every site along the Apatlaco River has a particular community to perform bioremediation activities. The first site S1 has Thiomonas, Polaromonas, Pedobacter, and Myroides, S2 has Pedobacter, Myroides, Pseudomonas and Acinetobacter, S3, Thiomonas, Myroides, Pseudomonas, Acinetobacter and Aeromonas; S4, Thiomonas, Myroides and Pseudomonas, Thauera.Furthermore, every site is rich in specific enzymes such as S1 has dioxygenase and dehydrogenase, which can degrade Catechol, Biphenyl, Naphthalene, and Phthalate. While, S2 and S3 are rich in dioxygenase and decarboxylating dehydrogenases to degrade Toluene, Fluorobenzoate, Xylene, Phenylpropanoate, and Phenol. S3 also has monooxygenases which degrade Benzene, and all the earlier mentioned enzymes were also found at S4.

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Microbial bioremediation processes for radioactive waste

Korean Journal of Chemical Engineering ◽

10.1007/s11814-015-0128-5 ◽

2015 ◽

Vol 32 (9) ◽

pp. 1720-1726 ◽

Cited By ~ 10

Author(s):

Changhyun Roh ◽

ChanKyu Kang ◽

Jonathan R. Lloyd

Keyword(s):

Radioactive Waste ◽

Microbial Bioremediation ◽

Bioremediation Processes

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Synthesis, Properties of Biodegradable Poly(Butylene Succinate-co-Butylene 2-Methylsuccinate) and Application for Sustainable Release

Materials ◽

10.3390/ma12091507 ◽

2019 ◽

Vol 12 (9) ◽

pp. 1507 ◽

Cited By ~ 3

Author(s):

Jiarui Han ◽

Jiaxin Shi ◽

Zhining Xie ◽

Jun Xu ◽

Baohua Guo

Keyword(s):

Chemical Structure ◽

Degree Of Crystallinity ◽

Burst Release ◽

Agricultural Field ◽

Biodegradation Rate ◽

Release Process ◽

Butylene Succinate ◽

Synthesis Properties ◽

Biodegradable Poly ◽

Methylsuccinic Acid

A novel biobased and biodegradable polyester, i.e., poly(butylene succinate-co-butylene 2-methylsuccinate) (P(BS-BMS)) was synthesized by succinic acid (SA), 2-methylsuccinic acid (MSA), and 1,4-butanediol (BDO) via a typically two-step esterification and polycondensation procedure. The chemical structure and macromolecular weight of obtained copolymers were characterized by 1H NMR, 13C NMR, and GPC. The melting temperature and degree of crystallinity were also studied by DSC, and it was found that the values were gradually decreased with increasing of MSA content, while the thermal stability remained almost unchanged which was tested by TGA. In addition, the biodegradation rate of the P(BS-BMS) copolymers could be controlled by adjusting the ratio of SA and MSA, and such biodegradability could make P(BS-BMS) copolymers avoid microplastic pollution which may be brought to the environment for applications in agricultural field. When we applied P(BS-BMS) copolymers as pesticide carriers which were prepared by premix membrane emulsification (PME) method for controlling Avermectin delivery, an improvement of dispersion and utilization of active ingredient was obviously witnessed. It showed a burst release process first followed by a sustained release of Avermectin for a long period, which had a great potential to be an effective and environmental friendly pesticide-release vehicle.

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Dangerous Chemical Agents: General and Odonto-Stomatological Aspects with Importance in Forensic Toxicology

Revista de Chimie ◽

10.37358/rc.19.5.7225 ◽

2019 ◽

Vol 70 (5) ◽

pp. 1829-1834

Author(s):

Tatiana Iov ◽

Mihnea Costescu ◽

Madalina Diac ◽

Daniel Tabian ◽

Sofia Mihaela David ◽

...

Keyword(s):

Chemical Structure ◽

Harmful Effect ◽

Forensic Toxicology ◽

Essential Elements ◽

Negative Effects ◽

Potential Toxicity ◽

Light Industry ◽

Chemical Agents ◽

Metal Poisoning ◽

Toxic Potential

In the heavy and light industry, the food and pharmaceutical industry, there are chemicals that contain metals with high toxic potential. Toxicity of metals is due to the harmful effect in certain forms and doses. Some metals become toxic when they form soluble compounds or in a certain chemical structure at certain doses (eg lead, mercury and candium). Not only heavy metals are toxic metals, there are also light metals that can become toxic, some of which are essential elements (iron, selenium, copper, chromium, zinc) and metals used therapeutically in medicine (aluminum, bismuth, gold, gallium, lithium and silver) may have negative effects when administered in large quantities or the elimination from the human body is deficient. Metal poisoning occurs through nutrition, medication, environmental factors. Most professional pollutants with intraoral manifestations appear in the heavy industry. The oral cavity is an entry gate for various toxic pathogens, so intoxications can be detected early due to the manifestations inside the mouth.

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SPECIFICITY OF IMMUNE MODULATING EFFECT OF YERSINIA PESTIS ENDOTOXIN

Journal of microbiology epidemiology immunobiology ◽

10.36233/0372-9311-2016-3-104-112 ◽

2016 ◽

pp. 104-112

Author(s):

V. I. Tynyanova ◽

V. P. Zyuzina ◽

G. V. Demidova ◽

E. P. Sokolova

Keyword(s):

Immune Response ◽

Yersinia Pestis ◽

Chemical Structure ◽

Inflammatory Cytokine ◽

Signal Pathways ◽

Toxic Shock ◽

Temperature Dependent ◽

Infectious Process ◽

Toxic Potential ◽

Pro Inflammatory Cytokines

Literature and own data on mechanisms of realization of lipopolysaccharide (LPS) toxic potential of Yersinia pestis in the conditions of a macroorganism are analyzed. 2 modifications of LPS are examined - temperature dependent changes of chemical structure of polymers and a change in their conformation under the effect of micro- and macroorganism factors. A special attention is paid to comparative study of toxic and immune modulating properties of the specified LPS forms. Both LPS forms are concluded to activate TLR4/MD2 receptor, inducing synthesis of 2 types of cytokines - pro-inflammatory and interferons. However, dominance of their signal pathways and cross-regulation of the transduced signal are mirrored, and as a result the initial form of LPS initiates interferon synthesis, and conformationally changed - pro-inflammatory cytokines. Results of the experiments are summarized in 2 schemes of signal transfer by TLR4/MD2 receptor under the effect of 2 forms of Y. pestis LPS. Variations of cytokine-inducing properties of the initial and conformationally-altered forms of Y. pestis LPS corresponds to the immune response of the organism at each stage of the infectious process: late inflammatory response by interferon type is characteristic for intra-cellular cycle of plague development, and pro-inflammatory cytokine hyper-production is observed at the terminal stage of infection-toxic shock.

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Estimating environmental pollution by xenobiotic chemicals using QSAR (QSBR) models based on artificial intelligence

Water Science & Technology ◽

10.2166/wst.1998.0303 ◽

1998 ◽

Vol 37 (8) ◽

pp. 9-18 ◽

Cited By ~ 2

Author(s):

B. Kompare

Keyword(s):

Artificial Intelligence ◽

Chemical Structure ◽

Quantitative Structure ◽

Topological Properties ◽

Environmental Persistence ◽

Structure Activity ◽

Connectivity Indices ◽

Quantitative Structure Activity Relationships ◽

The Given ◽

Xenobiotic Chemicals

An attempt was made to construct QSAR (Quantitative Structure-Activity Relationships) or QSBR (Quantitative Structure-Biodegradation Relationships) formulae and models for predicting biodegradability of chemicals in aqueous aerobic environment with machine learning (ML) tools of artificial intelligence (AI). Inverse of biodegradability is environmental persistence, from which possible dynamics of soil, groundwater and water pollution can be inferred. We tried to predict the biodegradability with several programs that can learn from examples and construct decision or regression trees and/or can construct equations. Besides the given basic topological properties, the main contribution was inclusion of connectivity indices. Above all, normalization of properties to molecular weight or the number of carbon atoms significantly improved prediction. The obtained results are comparable (or better) to the best achieved results with other approaches. Contrary to the statistical methods, ML tools present the information (learned knowledge) in a compact, easily understandable manner which can help identify and understand the key properties of chemicals and mechanisms important for assessing biodegradation (and thus possible environmental contamination) from chemical structure only.

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