PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 12618043

Effect of organic carbon shock loading on endogenous denitrification in sequential batch reactors.

F Rodríguez Mora·G Ferrara de Giner·A Rodríguez Andara·J Lomas Esteban
View original source ↗Export metadata ↓

Abstract

This work was focused on the performance evaluation of sequential batch reactors (SBR) treating sewage, through a process of endogenous biological denitrification. Different operational conditions were carried out, and the behaviour under the effects of organic shock loading was examined. Three laboratory scale reactors were operated simultaneously and fed with similar wastewater. The substratum was molasses and nitrate, as carbon and nitrogen sources, respectively. The three reactors were operated during different aeration periods (0, 15 and 30 min). Sudden changes (shock loading) in organic matter concentration were performed during the experiment. Thus, influent load was quickly increased threefold in relation to the original concentration. Results indicated that SBR reactors withstand adequately moderate shock loading. With regard to substratum degradation, nitrate elimination achieved was approximately 80%, while denitrification rate was approximately 0.87 mgg(-1)h(-1).

Explore related subjects

Biodegradation, EnvironmentalBioreactorsCarbonMolassesNitratesSewageWater PollutantsJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

F Rodríguez Mora, G Ferrara de Giner, A Rodríguez Andara, J Lomas Esteban. 2003. Effect of organic carbon shock loading on endogenous denitrification in sequential batch reactors.. https://doi.org/10.1016/s0960-8524(02)00316-4

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Fungi to the rescue: recent advances, mechanistic insights and omics-based perspectives in heavy metal mycoremediation.

Heavy metal (HM) contamination arising from rapid industrialization poses critical threats to global ecosystem integrity and public health. Conventional physicochemical approaches are limited by high costs, incomplete removal, and toxic waste generation, necessitating sustainable alternatives. Mycoremediation, which harnesses the remarkable, diverse capacities of fungi to tolerate and mitigate HM stress through sophisticated biological mechanisms, has emerged as a promising and sustainable approach to address HM pollution. This review examines the sources and ecotoxicological impacts of HM pollution, alongside the intracellular and extracellular mechanisms underlying fungal tolerance and removal, including biosorption, precipitation, membrane transport, antioxidant defense, chelation, bioaccumulation, and biotransformation. It further synthesizes fungal-based bioremediation strategies, while examining how metagenomic, metatranscriptomic, transcriptomic, proteomic, and metabolomic approaches are advancing understanding of fungal community structure and active detoxification pathways. This work uniquely integrates community- and isolate-level multi-omics data, explicitly bridges mechanistic understanding with omics-driven insights, and extends this into translational roadmap for applied bioremediation.

Biodegradation, Environmental↗
PubMed2026

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental↗
PubMed2026

Discovering hidden candidate plastic-degrading enzymes: Combined multi-omics and machine learning strategy.

Plastic pollution poses a major threat to the stability of natural ecosystems as well as human health. Microbial enzymes have long been considered a potential resource for targeted biodegradation but, except for a few successful cases, the discovery of efficient enzymes has proved challenging. Aiming to accelerate the process, we propose an approach combining metagenomics, metatranscriptomics and semi-supervised learning that selects promising plastic-degrading candidate enzymes from the proteome of relevant microorganisms. Tested on a dataset of over 10,000 microbial proteins, ranking models consistently prioritize known plastic-degrading enzymes, achieving an area under the cumulative distribution function curve above 0.96, with leave-one-family-out cross-validation indicating that performance is largely retained across protein families. As a case study, this work focuses on mixed microbial cultures exposed for extended periods to polyethylene, polyethylene terephthalate, and polyurethane substrates. The prevalent species after selective enrichment were functionally characterized, finding Rhodococcus aetherivorans as the most relevant species in two of the five cultures under investigation. Among the top-ranked proteins, several have high structural similarity with known enzymes despite not being identified by sequence similarity search. Moreover, according to metatranscriptomics results, several of these enzymes were found to be expressed at the same level or above that of annotated enzymes, suggesting that they may have functional relevance. Overall, this work highlights the potential of integrating multi-omics with data-driven methods for enzyme discovery and for accelerating the development of biotechnological solutions to plastic pollution.

Biodegradation, Environmental↗