Abstract
Breakthrough single-cell microalgae monitoring technology that minimizes costly culture collapses in industrial facilities through real-time early warning detection of various physiological stress conditions at single cell level.
Background
The global microalgae market is valued at $4.7 billion and growing at 8.2% CAGR. Industrial microalgae production facilities face a critical challenge – culture collapses that force complete facility shutdowns for 5-7 days, causing 5-20% losses annually. Current monitoring relies on visual inspection, or on real-time monitoring of extrinsic parameters (e.g., temperature, salinity, pH, pressure), which cannot detect problems upon initiation, but rather until collapse is already underway.
The Problem: When contamination or pathogen infection initiates, it arises with ca. 1% of cells showing stress indicators. By the time visual inspection detects the problem or real-time monitoring of extrinsic parameters suggests a potential issue, the entire culture is compromised, requiring complete facility shutdown and sterilization.
Market Need: The industry desperately needs an early warning system that can detect the first signs of culture stress at the single-cell level, allowing operators to isolate affected sections while maintaining production in healthy areas.
Our Innovation
A high-throughput single-cell analysis system that monitors microalgae health in real-time using advanced fluorescence detection, identifying contamination and stress before culture collapse occurs.
Revolutionary Capabilities:
- Ultra-early detection: Identifies stressed cells when only ca. 1% of population is affected
- Single-cell precision: Analyzes individual cells rather than bulk populations
- Real-time monitoring: Continuous analysis with immediate alerts
- Comprehensive physiological profiling using fluorescence lifetime, intensity, and brightness measurements at multiple spectral detection channels, following excitation at multiple wavelengths. Consequently, microalgae autofluorescence can be classified as unique Multiparameter signatures (UMPSs) in multidimensional parameter space
- Label-free detection: Uses natural autofluorescence – no sample preparation required
Key Advantages vs. Competition:
- 10x earlier detection than existing flow cytometry systems
- Minimal sample volume (420 µL/hour) for continuous monitoring
- Zero sample prep – direct analysis of culture samples
Technology
The system uses pulsed-interleaved laser excitations (488 and 640 nm) with three single-photon detectors and time-correlated single photon counting (TCSPC) to measure fluorescence lifetimes, intensities, and brightness ratios in individual cells flowing through a microfluidic channel.
Technical Innovation:
- Processes 100-1,000 (max. 3,600) cells per hour
- Picosecond-resolution fluorescence lifetime measurements
- Multi-dimensional parameter analysis distinguishes healthy cells from stressed cells
- Machine learning (ML) algorithms for automatic anomaly detection
Proven Applications:
- Culture Collapse Prevention: Early detection of contamination/infection before facility-wide spread
- Harvest Optimization: Real-time monitoring of carotenoid production for optimal harvest timing in cosmetics applications
Opportunity
Market Opportunity
Primary Market: Microalgae Production Facilities
- Target customers: Producers of nutraceuticals, cosmetics, biofuels, and food ingredients
- Value proposition: Prevent 5-20% annual losses from culture collapse
- ROI: System pays for itself by preventing a single major collapse event
Secondary Applications:
- Environmental water monitoring
- Aquaculture health assessment
- Research and development facilities
Commercial Potential:
- Licensing to established flow cytometry companies
- Direct sales to large-scale algae producers
- Service contracts for continuous monitoring
Patents and Publications
Patent Status: Provisional Patent Filed
Supporting Research: Harris, P.D., Ben Eliezer, N., Keren, N. and Lerner, E. (2024), Phytoplankton cell-states: multiparameter fluorescence lifetime flow-based monitoring reveals cellular heterogeneity. FEBS J, 291: 4125-4141. https://doi.org/10.1111/febs.17237
