Study of the environmental impact of insecticides by metabolic foot-printing approach - An introduction to the concept

HAL Id: hal-02713858

https://hal.archives-ouvertes.fr/hal-02713858

Submitted on 1 Jun 2020

HAL is a multi-disciplinary open access

archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives| 4.0 International License

Study of the environmental impact of insecticides by metabolic foot-printing approach - An introduction to

the concept

Chandrashekhar Patil, Amani Ben Jrad, Hikmat Ghosson, Delphine Raviglione, Marie-Virginie Salvia, Cédric Bertrand

To cite this version:

Study of the environmental impact of insecticides by

metabolic foot-printing approach

- An introduction to the concept.

Chandrashekhar Patil

1

, Amani Ben Jard

1

, Hikmat Ghosson

1

, Delphine Raviglione

1

, Marie-Virginie Salvia

1,2

, Cédric Bertrand

1,2 1 _{CRIOBE USR3278, Université de Perpignan Via Domitia, F66860, France.}

² Laboratoire d’excellence “CORAIL”, France

Context :

• Assessment of environmental pollution complex mixtures (new generation biological compounds, e.g. insecticides) is a major challenge.

• Evaluation of insecticides Half-life (t ½) is the time it takes for a certain amount of a pesticide to be reduced by half

• However, half-life dertermination does not apply if active substance is a complex mixture of compounds derived from biological sources (e.g. plant extract, microbs etc)

• Half-live values give restricted information as it does not describe all phenomena occuring such as the formation of by-products and the effect on biodiversity

• We propose an alternative approch: the resilience time, this value could be determined with kinetic study of meta-metabolome with EMF approach

Conclusion and perspectives

 Complex natural substances may be tested with this novel analytical protocol.

 It could potentially replace half life (t

_1/2

) concept with resilience time.

 Metabolomics approach may help to identify potential markers for environmental diagnosis of environmental contamination by pollutants.

 Characterization of selected markers from variables important in projection (VIP) of PLS DA are ongoing in our laboratory.

 Setting up of an experiment that mimics seminatural conditions (microclimatic chamber) with extended time and improving experimental and analytical parameters.

Bibliography

Patil C, Calvayrac C, Zhou Y, Romdhane S, Salvia MV, Cooper JF, Dayan FE, Bertrand C. Science of the Total Environment. 2016 Oct 1;566:552-8.

Salvia MV, Jrad AB, Raviglione D, Zhou Y, Bertrand C. Environmental Science and Pollution Research. 2017 Jun 28:1-7 Acknowledgement

This project has received funding from the European Union's Horizon 2020 research and innovation programme under

grant agreement No 746656 (Project: EnvFate) 0 1000000 2000000 3000000 4000000 5000000 6000000 7000000 8000000 0 20 40 60 80 100 120 140 160 Rel at iv e Inte nsit y Time (days) M622T973 Bti H2O 0 5000000 10000000 15000000 20000000 25000000 30000000 35000000 40000000 45000000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (days) M624T1015 Bti H20 0 200000 400000 600000 800000 1000000 1200000 1400000 1600000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (Days) M861T1045 Bti H2O 0 50000 100000 150000 200000 250000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (days) M405T1149 Bti H2O 0 5000 10000 15000 20000 25000 30000 35000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (days) M902T924 Cyp 0 100000 200000 300000 400000 500000 600000 700000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (days) M379T923 Cyp MeOH 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 200000 0 20 40 60 80 100 120 140 160 Rel at iv e int ensit y Time (days) M441T922 Cyp MeOH

PCA and MANOVA of each time

in Positive ion mode

Control

vs

Bti

After 150 days of incubation PCA

analysis still showed difference

between

EMF

of

treated

sediment by Bti and EMF of

Control sediment.

(Bti at 10 times of field dose)

PCA and MANOVA of each time

in Positive ion mode

Control

vs

alpha-cypermethrin

After 150 days of incubation PCA

analysis still showed

difference

profile between EMF of

treated

sediment by Cypermethrin and

EMF of Control sediment.

(α-Cypermethrin at 10 times of

field dose)

Partial-least squares discrimination analysis (PLS-DA) was performed as supervised method to identify important variables with discriminative power (VIP) at day15.

Partial-least squares discrimination analysis (PLS-DA) was performed as supervised method to identify important variables with discriminative power (VIP) at day15.

.

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ Type II MANOVA Tests: Pillai test statistic BT : Bti_Vs_Control H2O Values on the PCA plot represents percent (%) variability on the axis 1 and 2 respectively.

Half life (t

_1/2

)

Vs

Resilience time

Time

Time

Conc

en

tra

tio

n

Conc

en

tra

tio

n

Extractable sediment organic matter XENOMETABOLOME (Active ingredient +formulation ingredients + by products) MICROBIAL METABOLOME (Sediment meta-metabolome) 0 100000 200000 300000 400000 500000 600000 700000 0 20 40 60 80 100 120 140 160 Rela tiv e int ensity Time (days) M861T1045 Cyp MeOH P = 0.6137 P = 0.006083 ** _{P = 0.4758} P = 0.01735 * P = 0.363 P = 0.0003471 *** P = 0.0001319 *** P = 0.0268 * P = 8.176e-05 *** T0 T30 T15 T8 T4 T2 T150 T90 T60 21.21 14.11 22.72 16.82 24.67 17.10 29.89 16.55 18.56 22.25 30.14 14.60 22.26 15.09 18.27 14.99 23.79 16.30

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ Type II MANOVA Tests: Pillai test statistic BT : Bti_Vs_Control H2O Values on the PCA plot represents percent (%) variability on the axis 1 and 2 respectively.

P = 0.0001034 *** P = 8.146e-08 *** P = 4.309e-05 *** P = 4.993e-08 *** P = 1.473e-07 *** P = 1.46e-05 *** P = 3.669e-06 *** P = 1.602e-05 *** P = 5.997e-10 *** T0 T30 T15 T8 T4 T2 T150 T90 T60 34.28 38.08 28.46 31.24 _30.26 34.68 37.21 33.81 36.21 15.32 14.29 _13.10 12.05 13.22 13.72 17.50 16.26 16.12

Environmental Metabolic Foot-printing (EMF) approach

QIIME2 Metabolomics approach

Bti Exotoxin α-Cypermethrin

Meta-barcoding approach

Sediment Microcosm assay _{Sediment Microcosm assay}

1) Resilience time

2) Characterization of Environmental Markers

LCMS-QToF analysis

Data generation

Data analysis Data analysis

Organic extraction

Test Complex mixture

Real Fate…