Optimization of Mass Spectrometric Parameters in Data Dependent Acquisition for Untargeted Metabolomics on the Basis of Putative Assignments.

Optimization of mass spectrometric parameters for a data dependent acquisition (DDA) experiment is essential to increase the MS/MS coverage and hence increase metabolite identifications in untargeted metabolomics. We explored the influence of mass spectrometric parameters including mass resolution, radio frequency (RF) level, signal intensity threshold, number of MS/MS events, cycle time, collision energy, maximum ion injection time (MIT), dynamic exclusion, and automatic gain control (AGC) target value on metabolite annotations on an Exploris 480-Orbitrap mass spectrometer. Optimal annotation results were obtained by performing ten data dependent MS/MS scans with a mass isolation window of 2.0 m/z and a minimum signal intensity threshold of 1 × 104 at a mass resolution of 180,000 for MS and 30,000 for MS/MS, while maintaining the RF level at 70%. Furthermore, combining an AGC target value of 5 × 106 and MIT of 100 ms for MS and an AGC target value of 1 × 105 and an MIT of 50 ms for MS/MS scans provided an improved number of annotated metabolites. A 10 s exclusion duration and a two stepped collision energy were optimal for higher spectral quality. These findings confirm that MS parameters do influence metabolomics results, and propose strategies for increasing metabolite coverage in untargeted metabolomics. A limitation of this work is that our parameters were only optimized for one RPLC method on single matrix and may be different for other protocols. Additionally, no metabolites were identified at level 1 confidence. The results presented here are based on metabolite annotations and need to be validated with authentic standards.

Azole antifungal resistance in fungal isolates from wastewater treatment plant effluents.

Wastewater treatment plants (WWTPs) can be significant sources of antifungal resistant fungi, which can disseminate further in the environment by getting into rivers together with effluents discharged from WWTPs and pose a risk for human health. In this study, the presence of azole resistance was determined in fungal isolates from treated effluents of two WWTPs using the standard microdilution method from Clinical and Laboratory Standards Institute (CLSI). A total of 41 fungal isolates representing 23 fungal species and 16 fungal genera were obtained. Fungal genera related to the known human and/or plant pathogens such as Aspergillus, Fusarium, and Candida were detected. Among the observed species, the susceptibility of Aspergillus fumigatus and Fusarium oxysporum was tested against fluconazole (FCZ), ketoconazole (KTZ), itraconazole (ITZ), and voriconazole (VCZ). The isolate A. fumigatus was susceptible to KTZ, ITZ, and VCZ, while it showed resistance against FCZ. On the contrast, the isolate F. oxysporum showed resistance to KTZ, ITZ, and VCZ. Comparatively, VCZ showed highest activity against both A. fumigatus and F. oxysporum. Analysis of the gene Cyp51A for the A. fumigatus isolate showed no evidence of drug resistance that could be related to point mutations and/or tandem repeats in the gene. To the best of our knowledge, this is the first susceptibility test study on A. fumigatus and F. oxysporum isolates from the WWTPs of South Africa. In conclusion, this study indicated an urgent need for thorough investigation with larger group of fungal isolates from different regions of South Africa to broadly understand the role of WWTPs in the dissemination of azole antifungal drug resistance.

Occurrence and risk assessment of azole antifungal drugs in water and wastewater.

The occurrence of azole antifungals in the environment presents one of the emerging concerns due to their ecotoxicological threat as well as their potential contribution to the evolution of drug resistant fungi in the environment. In this study, the occurrence of eight commonly prescribed azole antifungal drugs was seasonally determined in influent and effluent water samples from three wastewater treatment plants and a drinking water treatment plant in South Africa. In addition, the risk quotient (RQ) method was employed to investigate the potential ecological and human health risks associated with their presence in the wastewater and/or drinking water. Clotrimazole, econazole, fluconazole, itraconazole, ketoconazole and miconazole were detected at least once in the water samples, while posaconazole and voriconazole were not detected in any of the samples for all seasons at which the samples were collected. Fluconazole was detected at higher frequency (about 96%) with a concentration up to 9959.0 ng L-1. Clotrimazole had the second highest frequency of detection (about 33%) with a concentration up to 143.3 ng L-1. Statistically significant temporal variation in clotrimazole (p < 0.05) and spatial variation in fluconazole (p < 0.05) were observed. In general, the preliminary ecological risk assessment based on risk quotient (RQ) calculation indicated that there is currently no high risk against aquatic organisms (Algae, Daphnia and Fish) related to the azole antifungals. Meanwhile, human health risk assessment demonstrated that fluconazole represented high risk in drinking water. Furthermore, risk estimates showed a potential for the detected concentrations of fluconazole and itraconazole in water samples to pose moderate to high risk for development of antifungal drug resistance. Some of the azole antifungal drugs are ubiquitous in the wastewater and future monitoring and validation studies should be conducted for those drugs that seem to pose human health and ecological risks.

Diversity, Co-occurrence and Implications of Fungal Communities in Wastewater Treatment Plants.

Three wastewater treatment plants (WWTPs) located in Gauteng province in South Africa were investigated to determine the diversity, co-occurrence and implications of their fungal communities using illumina sequencing platform and network analysis. Phylogenetic taxonomy revealed that members of the fungal communities were assigned to 6 phyla and 361 genera. Basidiomycota and Ascomycota were the most abundant phyla, dominated by the genera Naumovozyma, Pseudotomentella, Derxomyces, Ophiocordyceps, Pulchromyces and Paecilomyces. Phylogenetic analysis revealed the existence of fungal OTUs related to class lineages such as Agaricomycetes, Eurotiomycetes and Sordariomycetes indicating new fungal diversity in WWTPs. Dominant and rare fungal genera that can potentially be used in bioremediation such as Trichoderma, Acremonium, Talaromyces, Paecilomyces, cladophialophora and Saccharomyces were detected. Conversely, genera whose members are known to be pathogenic to human and plant such as Olpidium, Paecilomyces, Aspergillus, Rhodotorula, Penicillium, Candida, Synchytrium, Phyllosticta and Mucor were also detected in all WWTPs. Phylotype analysis confirmed that some fungal phylotypes were highly similar to the reported fungal pathogens of concern. Co-occurrence network analysis revealed that the fungal genera such as Minimedusa, Glomus, Circinella, Coltricia, Caloplaca, Phylosticta, Peziza, Candida, and Hydnobolites were the major networking hub in the WWTPs. The overall results in this study highlighted that WWTPs represent a potential source of beneficial fungi for bioremediation of pollutants in the ecosystem and the need to consider human and plant fungal pathogens during safety evaluation of treated wastewater for reuse.

Target quantification of azole antifungals and retrospective screening of other emerging pollutants in wastewater effluent using UHPLC -QTOF-MS.

The information acquired by high resolution quadrupole-time of flight mass spectrometry (QTOF-MS) allows target analysis as well as retrospective screening for the presence of suspect or unknown emerging pollutants which were not included in the target analysis. Targeted quantification of eight azole antifungal drugs in wastewater effluent as well as new and relatively simple retrospective suspect and non-target screening strategy for emerging pollutants using UHPLC-QTOF-MS is described in this work. More than 300 (parent compounds and transformation products) and 150 accurate masses were included in the retrospective suspect and non-target screening, respectively. Tentative identification of suspects and unknowns was based on accurate masses, peak intensity, blank subtraction, isotopic pattern (mSigma value), compound annotation using data bases such as KEGG and CHEBI, and fragmentation pattern interpretation. In the targeted analysis, clotrimazole, fluconazole, itraconazole, ketoconazole and posaconazole were detected in the effluent wastewater sample, fluconazole being with highest average concentration (302.38 ng L-1). The retrospective screening resulted in the detection of 27 compounds that had not been included in the target analysis. The suspect compounds tentatively identified included atazanavir, citalopram, climbazole, bezafibrate estradiol, desmethylvenlafaxine, losartan carboxylic acid and cetirizine, of which citalopram, estradiol and cetirizine were confirmed using a standard. Carbamazepine, atrazine, efavirenz, lopinavir, fexofenadine and 5-methylbenzotriazole were among the compounds detected following the non-targeted screening approach, of which carbamazepine was confirmed using a standard. Given the detection of the target antifungals in the effluent, the findings are a call for a wide assessment of their occurrence in aquatic environments and their role in ecotoxicology as well as in selection of drug resistant fungi. The findings of this work further highlights the practical benefits obtained for the identification of a broader range of emerging pollutants in the environment when retrospective screening is applied to high resolution and high accuracy mass spectrometric data.