Assessing Biodegradability of Chemical Compounds from Microbial Community Growth Using Flow Cytometry

Microalgal and activated sludge processing for biodegradation of textile dyes

The textile industry contributes substantially to water pollution. To investigate bioremediation of dye-containing wastewater, the decolorization and biotransformation of three textile azo dyes, Red HE8B, Reactive Green 27, and Acid Blue 29, were considered using an integrated remediation approach involving the microalga Chlamydomonas mexicana and activated sludge (ACS). At a 5 mg L-1 dye concentration, using C. mexicana and ACS alone, decolorization percentages of 39%-64% and 52%-54%, respectively, were obtained. In comparison, decolorization percentages of 75%-79% were obtained using a consortium of C. mexicana and ACS. The same trend was observed for the decolorization of dyes at higher concentrations, but the potential for decolorization was low. The toxic azo dyes adversely affect the growth of microalgae and at high concentration 50 mg L-1 the growth rate inhibited to 50-60% as compared to the control. The natural textile wastewater was also treated with the same pattern and got promising results of decolorization (90%). Moreover, the removal of BOD (82%), COD (72%), TN (64%), and TP (63%) was observed with the consortium. The HPLC and GC-MS confirm dye biotransformation, revealing the emergence of new peaks and the generation of multiple metabolites with more superficial structures, such as N-hydroxy-aniline, naphthalene-1-ol, and sodium hydroxy naphthalene. This analysis demonstrates the potential of the C. mexicana and ACS consortium for efficient, eco-friendly bioremediation of textile azo dyes.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

Environmental persistence assessment of heterocyclic polyaromatic hydrocarbons - Ultimate and primary biodegradability using adapted and non-adapted microbial communities

Heterocyclic polyaromatic hydrocarbons (heterocyclic PAHs) are of increasing concern and their environmental and human health impacts should be assessed due to their widespread presence and potential persistence in the environment. This study investigated the ultimate and primary biodegradability of ten heterocyclic PAHs, nine of which were found to be non-readily biodegradable. To generate a microbial community capable of degrading such compounds, a bacterial inoculum isolated from the effluent of a wastewater treatment plant (WWTP) was adapted to a mixture of heterocyclic PAHs for one year. Throughout the adaptation process, bacterial samples were collected at different stages to conduct primary biodegradation, ultimate biodegradation, and inoculum toxicity tests. Interestingly, after one year of adaptation, the community developed the ability to mineralize carbazole, but in the same time showed an increasing sensitivity to the toxic effects of benzo[c]carbazole. In two consecutive primary biodegradation experiments, degradation of four heterocycles was observed, while no biodegradation was detected for five compounds in any of the tests. Furthermore, the findings of this work were compared with predictions from in silico models regarding biodegradation timeframe and sorption, and it was found that the models were partially successful in describing these processes. The results of study provide valuable insights into the persistence of a representative group of heterocyclic PAHs in aquatic environments, which contributes to the hazard assessment of this particular class of substances.

mibPOPdb: An online database for microbial biodegradation of persistent organic pollutants

Microbial biodegradation of persistent organic pollutants (POPs) is an attractive, ecofriendly, and cost-efficient clean-up technique for reclaiming POP-contaminated environments. In the last few decades, the number of publications documenting POP-degrading microbes, enzymes, and experimental data sets has continuously increased, necessitating the development of a dedicated web resource that catalogs consolidated information on POP-degrading microbes and tools to facilitate integrative analysis of POP degradation data sets. To address this knowledge gap, we developed the Microbial Biodegradation of Persistent Organic Pollutants Database (mibPOPdb) by accumulating microbial POP degradation information from the public domain and manually curating published scientific literature. Currently, in mibPOPdb, there are 9215 microbial strain entries, including 184 gene (sub)families, 100 enzymes, 48 biodegradation pathways, and 593 intermediate compounds identified in POP-biodegradation processes, and information on 32 toxic compounds listed under the Stockholm Convention environmental treaty. Besides the standard database functionalities, which include data searching, browsing, and retrieval of database entries, we provide a suite of bioinformatics services to facilitate comparative analysis of users' own data sets against mibPOPdb entries. Additionally, we built a Graph Neural Network-based prediction model for the biodegradability classification of chemicals. The predictive model exhibited a good biodegradability classification performance and high prediction accuracy. mibPOPdb is a free data-sharing platform designated to promote research in microbial-based biodegradation of POPs and fills a long-standing gap in environmental protection research. Database URL: http://mibpop.genome-mining.cn/.

Synthetic Musk Fragrances in Water Systems and Their Impact on Microbial Communities

The presence of emerging contaminants in aquatic systems and their potential effects on ecosystems have sparked the interest of the scientific community with a consequent increase in their report. Moreover, the presence of emerging contaminants in the environment should be assessed through the “One-Health” approach since all the living organisms are exposed to those contaminants at some point and several works already reported their impact on ecological interactions. There are a wide variety of concerning emerging contaminants in water sources, such as pharmaceuticals, personal care products, house-care products, nanomaterials, fire-retardants, and all the vast number of different compounds of indispensable use in routine tasks. Synthetic musks are examples of fragrances used in the formulation of personal and/or house-care products, which may potentially cause significant ecotoxicological concerns. However, there is little-to-no information regarding the effect of synthetic musks on microbial communities. This study reviews the presence of musk fragrances in drinking water and their impact on aquatic microbial communities, with a focus on the role of biofilms in aquatic systems. Moreover, this review highlights the research needed for a better understating of the impact of non-pharmaceutical contaminants in microbial populations and public health.

Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data

Dynamic analysis of microbial composition is crucial for understanding community functioning and detecting dysbiosis. Compositional information is mostly obtained through sequencing of taxonomic markers or whole meta-genomes, which may be productively complemented by real-time quantitative community multiparametric flow cytometry data (FCM). Patterns and clusters in FCM community data can be distinguished and compared by unsupervised machine learning. Alternatively, FCM data from preselected individual strain phenotypes can be used for supervised machine-training in order to differentiate similar cell types within communities. Both types of machine learning can quantitatively deconvolute community FCM data sets and rapidly analyse global changes in response to treatment. Procedures may further be optimized for recurrent microbiome samples to simultaneously quantify physiological and compositional states.