Innovation Beyond the State-of-the-Art (Part of the Medical University Graz)
This project delivers a novel, integrated biological monitoring framework that surpasses conventional chemical-based wastewater assessment. Standard monitoring approaches rely on targeted chemical analysis, overlooking the complex biological effects of contaminant mixtures. Our system uniquely combines:
Effect-directed HPTLC bioassays for genotoxicity, mutagenicity, endocrine disruption, and general toxicity
High-resolution microplastic detection as well as microbial monitoring via flow cytometry
Culture-based antimicrobial resistance screening and DNA-based microbiome profiling to determine community composition
The inclusion of a laboratory-scale reverse osmosis pilot further evaluates mitigation strategies, bridging monitoring and actionable treatment innovation. This integrated framework enables detection of emerging PMOCs, transformation products, and microbiological risks invisible to standard monitoring. By uniting chemical, microbial, and functional endpoints into a biological quality gate, the project establishes a first-of-its-kind predictive early-warning system for European wastewater management under climate-stressed conditions, setting a new benchmark for environmental and public health protection.
Concept and Editorial methodology
Conceptual Approach
Wastewater treatment plants receive thousands of anthropogenic chemicals from domestic, industrial, agricultural, and medical sources. During treatment, additional transformation products may form, particularly in advanced oxidation or adsorption stages, retaining biological activity despite apparent removal.
The project introduces an effect-directed bioanalytical monitoring framework to identify toxicologically active fractions in complex mixtures. Wastewater systems are also reservoirs of microbial communities, including antimicrobial resistant bacteria. Chemical stressors may select for resistant populations and alter microbial community composition.
A laboratory-scale reverse osmosis pilot plant will test removal of biologically active chemicals and microbial contaminants. All data, including toxicity profiles, microbial abundance, resistance patterns, and microbiome composition, will be integrated into predictive models linking chemical stressors to microbial outcomes.
1. Direct Matrix Application
Samples will be introduced without enrichment, preserving highly polar, mobile, and labile compounds for analysis.
2. Chromatographic Separation
HPTLC separates compounds spatially, enabling effect-directed localization of biologically active fractions.
3. Multi-Endpoint Bioanalytical Screening
Plates are analyzed with:
HPTLC-umuC assay - genotoxicity
HPTLC-Ames assay - mutagenicity
pYES/pYAS assays - endocrine activity
Aliivibrio fischeri luminescence inhibition - general toxicity
This generates spatial toxicity maps, revealing active contaminant zones.
4. Microplastic Detection via Flow Cytometry:
load and size composition of microplastic
collection of the plastic fraction
larger fragments are used for associated microplastic microbiome
5. Microbial Monitoring by Flow Cytometry
Flow cytometry quantifies:
total and viable bacterial cells
stressed or membrane-compromised populations
dynamic changes across treatment stages
high and low DNA fractions oft he bacterial population
6. Culture-Based Screening and Microbiome Analysis
Culture-based screening identifies resistant populations (e.g., ESBL-producing E. coli, carbapenem-resistant organisms).
Microbiome analysis complements this by:
Cultivation based determination of antibiotic resistance (Cephalosporins, Carbapenems, Fluoroquinolones)
Metabiom analytic of cultivated resistant population
DNA extraction from wastewater samples
High-throughput sequencing via a service provider
Automated bioinformatic analysis to determine community composition and diversity
This enables linkage between toxicity profiles, microbial load, resistant populations, and microbial diversity.
7. Reverse Osmosis Pilot
A laboratory-scale RO pilot tests removal of:
toxicologically active fractions
bacterial and resistant populations
Samples pre- and post-RO will be analyzed across all endpoints.
8. Integrated Toxicity-Resistance-Microbiome Data Analysis
Multivariate statistics and machine learning will explore relationships between contaminant mixture toxicity, microbial abundance, AMR occurrence, and microbiome composition, supporting predictive environmental risk assessment.
Work Package: Biological Quality Gate, Pilots, Stress Tests, Cross-Pilot Validation
Duration: Month 12 - Month 48
Task 1 - Pilot Site Establishment
Three WWTPs:
Gössendorf (Austria) - reference municipal
Leibnitz (Austria) - advanced treatment
Milano (Italy) - high-load metropolitan (just for giving an example)
Sampling at: influent, secondary effluent, post-ozonation, post-activated carbon, final effluent.
Task 2 - Biological Quality Gate
Integrates:
HPTLC bioassays
Flow cytometry microbial monitoring
Culture-based AMR detection
Microbiome profiling
Identifies stages where residual biological activity or resistant populations persist.
Task 3 - Stress Testing
Evaluate system under:
drought/low-flow conditions
stormwater contamination pulses
influent fluctuations
advanced treatment variability
Task 4 - Reverse Osmosis Pilot Experiments
Evaluate RO removal of toxic, microbial, and resistant fractions, and assess microbiome shifts.
Task 5 - Cross-Pilot Validation and Data Integration
Compare results across WWTPs and integrate:
toxicity profiles
microbial load
AMR occurrence
microbiome composition
treatment parameters
Develop predictive models linking chemical stressors to microbial outcomes.
Deliverables
DWP-X.1 Pilot monitoring protocol (Month 18)
DWP-X.2 Biological quality gate evaluation (Month 36)
DWP-X.3 Cross-pilot validation & guidelines (Month 48)
DWP-X.4 Reverse osmosis pilot evaluation (Month 42)
DWP-X.5 Integrated toxicity-resistance-microbiome modelling framework (Month 46)
Milestones
MS-X1 First coordinated pilot monitoring campaign completed (Month 18)
MS-X2 Biological quality gate implemented (Month 30)
MS-X3 RO pilot operational (Month 36)
MS-X4 Cross-pilot validation completed (Month 42)
MS-X5 Predictive relationships between toxicity, AMR, and microbiome shifts identified (Month 44)