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

Details

Serval ID
serval:BIB_E4E8C7ED5B31
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Assessing Biodegradability of Chemical Compounds from Microbial Community Growth Using Flow Cytometry.
Journal
mSystems
Author(s)
Özel Duygan B.D., Rey S., Leocata S., Baroux L., Seyfried M., van der Meer J.R.
ISSN
2379-5077 (Print)
ISSN-L
2379-5077
Publication state
Published
Issued date
09/02/2021
Peer-reviewed
Oui
Volume
6
Number
1
Pages
e01143-20
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Compound biodegradability tests with natural microbial communities form an important keystone in the ecological assessment of chemicals. However, biodegradability tests are frequently limited by a singular focus either on the chemical and potential transformation products or on the individual microbial species degrading the compound. Here, we investigated a methodology to simultaneously analyze community compositional changes and biomass growth on dosed test compound from flow cytometry (FCM) data coupled to machine-learned cell type recognition. We quantified the growth of freshwater microbial communities on a range of carbon dosages of three readily biodegradable reference compounds, phenol, 1-octanol, and benzoate, in comparison to three fragrances, methyl jasmonate, myrcene, and musk xylene (as a nonbiodegradable control). Compound mass balances with between 0.1 to 10 mg C · liter <sup>-1</sup> phenol or 1-octanol, inferred from cell numbers, parent compound analysis, and CO <sub>2</sub> evolution, as well as use of <sup>14</sup> C-labeled compounds, showed between 6 and 25% mg C · mg C <sup>-1</sup> substrate incorporation into biomass within 2 to 4 days and 25 to 45% released as CO <sub>2</sub> In contrast, similar dosage of methyl jasmonate and myrcene supported slower (4 to 10 days) and less (2.6 to 6.6% mg C · mg C <sup>-1</sup> with 4.9 to 22% CO <sub>2</sub> ) community growth. Community compositions inferred from machine-learned cell type recognition and 16S rRNA amplicon sequencing showed substrate- and concentration-dependent changes, with visible enrichment of microbial subgroups already at 0.1 mg C · liter <sup>-1</sup> phenol and 1-octanol. In general, community compositions were similar at the start and after the stationary phase of the microbial growth, except at the highest used substrate concentrations of 100 to 1,000 mg C · liter <sup>-1</sup> Flow cytometry cell counting coupled to deconvolution of communities into subgroups is thus suitable to infer biodegradability of organic chemicals, permitting biomass balances and near-real-time assessment of relevant subgroup changes.IMPORTANCE The manifold effects of potentially toxic compounds on microbial communities are often difficult to discern. Some compounds may be transformed or completely degraded by few or multiple strains in the community, whereas others may present inhibitory effects. In this study, we benchmark a new method based on machine-learned microbial cell recognition to rapidly follow dynamic changes in aquatic communities. We further determine productive biodegradation upon dosing of a number of well-known readily biodegradable tester compounds at a variety of concentrations. Microbial community growth was quantified using flow cytometry, and the multiple cell parameters measured were used in parallel to deconvolute the community on the basis of similarity to previously standardized cell types. Biodegradation was further confirmed by chemical analysis, showing how distinct changes in specific populations correlate to degradation. The method holds great promise for near-real-time community composition changes and deduction of compound biodegradation in natural microbial communities.
Keywords
biodegradation, flow cytometry, freshwater, machine learning, microbial communities
Pubmed
Web of science
Open Access
Yes
Create date
22/02/2021 14:44
Last modification date
07/07/2021 6:36
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