Continuous fungal treatment of non-sterile veterinary hospital effluent: pharmaceuticals removal and microbial community assessment

Source point treatment of effluents with a high load of pharmaceutical active compounds (PhACs), such as hospital wastewater, is a matter of discussion among the scientific community. Fungal treatments have been reported to be successful in degrading this type of pollutants and, therefore, the white-rot fungus Trametes versicolor was applied for the removal of PhACs from veterinary hospital wastewater. Sixty-six percent removal was achieved in a non-sterile batch bioreactor inoculated with T. versicolor pellets. On the other hand, the study of microbial communities by means of DGGE and phylogenetic analyses led us to identify some microbial interactions and helped us moving to a continuous process. PhAC removal efficiency achieved in the fungal treatment operated in non-sterile continuous mode was 44 % after adjusting the C/N ratio with respect to the previously calculated one for sterile treatments. Fungal and bacterial communities in the continuous bioreactors were monitored as well.

Saprotrophic fungi Hypholoma fasciculare effect on the fungal community associated to Castanea sativa

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Hydrocarbonoclastic bacteria: from bioremediation to bioenergy feedstock

Tese de Doutoramento em Engenharia Química e Biológica.

Effect of sulfate and iron (III) on LCFA degradation by a methanogenic community

[Excerpt] Under anaerobic conditions long chain fatty acids (LCFA) can be converted to methane by syntrophic bacteria and methanogenic archaea. LCFA degradation was also reported in the presence of alternative hydrogenotrophic partners, such as sulfate-reducing bacteria (SRB) and iron-reducing bacteria (IRB), which generally show higher affinity for H2 than methanogens and are more resistant to LCFA [1,2,3]. Their presence in a microbial culture degrading LCFA can be advantageous to reduce LCFA toxicity towards methanogens, although high concentrations of external electron acceptor (EEA) can lead to outcompetition of methanogens and cease methane production. In this work, we tested the effect of adding sub-stoichiometric concentrations of sulfate and iron(III) to methanogenic communities degrading LCFA. (...)

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.