Département Chimie de l’environnement

Cyanobacteria produce toxic and bioactive secondary metabolites, posing risks to ecosystems and human health, yet their transformation pathways in surface waters remain unclear. We assessed biotransformation for 40 cyanopeptides including microcystins, anabaenopeptins and cyanopeptolins in surface waters and in situ enriched biofilm suspensions. In surface waters, most cyanopeptides did not degrade significantly over the course of 7 days. A wide range of biodegradability across cyanopeptides was apparent in biofilm suspensions from three rivers. Increasing the biofilm density shortened the lag time and increased initial removal of cyanopeptides. Increasing the initial cyanopeptide concentration lengthened the lag time and decreased their initial removal, supporting inhibitory effects of cyanopeptides toward enzymes involved in their own transformation. Transformation kinetics and product analysis demonstrated a structure–reactivity relationship across and within cyanopeptide classes. Anabaenopeptins were hydrolyzed at the C-terminus when arginine, tyrosine and (iso)leucine were present, but not when phenylalanine or tryptophan was present. Microcystins showed tetrapeptide formation when adda linked to arginine but not when it linked to alanine, leucine, or tyrosine. Oxidation of tyrosine and deamination of arginine residues showed an interdependence across cyanopeptide classes. These novel insights into biotransformation products and pathways of a wide range of cyanopeptides facilitate assessment of exposure scenarios in surface waters and inform about kinetics and product formation in biological water treatment.

Inferring coexistence metrics, such as niche and fitness differences, in changing environments is key for understanding the mechanism behind species coexistence and predicting its likelihood. However, it first requires estimating the per capita interactions between organisms and their intrinsic growth rates-parameters that are typically measured by isolating organisms from their natural context. Here, we first use weighted multivariate regression on the per capita growth rates of populations to estimate these key ecological parameters directly from time-series data of species-rich communities. Second, we infer niche differences and species resistance, which are two important metrics for understanding species coexistence. Our approach allows these metrics to vary over time and under different environmental conditions. We validate our approach using synthetic data and apply it to both experimental and observational data as a proof of concept. Experimental results show an expected allocative trade-off between grazing resistance and rapid growth in algae. Moreover, coexistence likelihood decreases, and coexistence balance is disturbed under stressful environmental conditions. Observational data suggests variations in intrinsic growth rates and per capita interactions among autotrophic guilds with respect to seasonal patterns. In addition, interactions between cyanobacteria with green algae and chrysophytes might indicate a potential cause for bloom development. Our approach offers a powerful toolbox to gain insight into the mechanisms underlying ecological dynamics, species coexistence, and community structures under varying environments. Such an understanding will help us address important ecological and evolutionary questions, such as explaining biodiversity patterns and solving the problem of cyanobacteria bloom.

Cyanobacterial blooms require monitoring, as they pose a threat to ecosystems and human health, especially by the release of toxins. Along with widely reported microcystins, cyanobacteria coproduce other bioactive metabolites; however, information about their dynamics in surface waters is sparse. We investigated dynamics across full bloom successions throughout a five-year lake monitoring campaign (Greifensee, Switzerland) spanning 150 sampling dates. We conducted extensive suspect screening of cyanobacterial metabolites using the database CyanoMetDB. Across all 850 samples, 35 metabolites regularly co-occurred. Microcystins were present in 70% of samples, with [d-Asp³,(E)-Dhb⁷]MC-RR reaching concentrations of 70 ng/L. Anabaenopeptins, meanwhile, were detected in 95% of all samples with concentrations of Oscillamide Y up to 100-fold higher than microcystins. Based on LC-MS response and frequency, we identified indicator metabolites exclusively produced by one of three cyanobacteria isolated from the lake, these being [d-Asp³,(E)-Dhb⁷]MC-RR from Planktothrix sp. G2020, Microginin 761B from Microcystis sp. G2011, and Ferintoic acid B from Microcystis sp. G2020. These indicators showed distinct temporal trends and peaking seasons that reflect the variance in either the abundance of the producing cyanobacteria or their toxin production dynamics. Our approach demonstrates that selecting high LC-MS response and frequent and species-specific indicator metabolites can be advantageous for cyanobacterial monitoring.