OVERVIEW

Our primary long-term scientific goal is to understand and ultimately predict the conditions under which specific populations of marine microorganisms develop in nature. A fundamental requirement for attaining this objective is the correlation of environmental conditions with microorganismal abundances at the small spatial and temporal scales that are relevant to the organisms. This is not possible with extant technology and methodological approaches. Sampling the environment with high resolution and identifying microorganisms in-situ in near-real time will constitute revolutionary advances in the study of the ecology of marine microbial species. In addition, the rapid identification of aquatic microorganisms will be extremely valuable for the early detection of harmful organisms and the mitigation of their effects on the environment and the human population.

Our work is organized into two broad research areas focused on the development of technology for identifying target microbial taxa in natural water samples, and the application of this technology to in-situ, real-time studies of microbial assemblages and concomitant environmental parameters.  Our primary experimental model system is a specific single-celled microalga, Aureococcus anophagefferens.  A. anophagefferens is a harmful bloom-forming species responsible for “brown tides” in the middle Atlantic States of the U.S.and constitutes an excellent system for addressing generic issues that arise in monitoring of marine microorganisms. The first research area is concerned with adaptive sampling of environmental parameters and algal abundance using robotic sampling devices, and the second area with the detection and identification of marine microorganisms.

Significant Accomplishments

Navigation Algorithms

1. Experimental demonstration of an efficient, distributed algorithm for adaptive sampling
2. Experimental demonstration of a bacterium-inspired algorithm for robot navigation and homing with minimal computational requirements

Field instrumentation and network design and construction

3. Design and prototype development of an underwater mote-based submarine robot for experiments in adaptive sampling
4. Design and prototype development of a robot boat for surface operations in the field
   • Outfitted with basic sensors for pertinent environmental parameters Equipped for sensor directed navigation
   • Equipped for sensor guided sample collection
5. Design and prototype development of a wireless sensor network for small-scale sensing in aquatic ecosystems
   • Construction of 10 static nodes (presently underway) for sensing physical/chemical environmental parameters
   • Within-network data synthesis and decision making for directing a mobile sampler (boat)
   • Transmission of data to shore-based station

Experimental studies in laboratory test bed

1. Test bed experiment:  Artificial stimulation of a ‘brown tide’ (bloom of A. anophagefferens) in a thermally stratified column, and demonstration of predation effects in the test bed.
2. Test bed experiment:  Monitoring the diel (daily) vertical migration of a red tide dinoflagellate in a thermally stratified column.

Microorganism sensing, identification, enumeration

3. Development of a novel biological detection method for the harmful brown tide alga (Aureococcus anophagefferens): immuno-based flow cytometry.
   • Comparison of the flow cytometric approach with an ELISA (Enzyme-Linked Immunosorbent Assay), demonstrating the advantages of flow cytometry. Demonstration of correlation between flow cytometry and microscopy-based enumeration methods for A. anophagefferens.
   • Application of immuno-based flow-cytometry for routine laboratory detection and counting of brown tide algae.
4. Development of methods for attaching A. anophagefferens-directed antibodies to surfaces. This is a generic capability, useful for functionalizing the tips of AFMs (Atomic Force Microscopes) that are used in force sensing, and also for other applications, such as functionalization of nanowires. These methods can be generalized to other types of microorganisms for which monoclonal antibodies are available.
5. Demonstration of discrimination between brown tide algae immobilized on a surface and the surface itself, by using force-distance curves obtained with an AFM with a functionalized tip. This detection technique is sensitive to a single cell (brown tide alga). In principle, it can be generalized to any cell for which monoclonal antibodies are available.
6. Fabrication of nanowire and carbon nanotube devices that will serve as ultra-sensitive sensors for brown tide cells.
7. Demonstration of nanowire sensing principles for biomolecules and other materials.
8. Demonstration of the operation principle of using nanosensors to detect brown tide algae, where the presence of the algae is directly converted into electrical signals.

 

Research Objectives

 

Marine microorganisms such as viruses, bacteria, microalgae, and protozoa have a major impact on the ecology of the coastal ocean.  For example, blooms of harmful and/or toxic algae (e.g. red, brown and green tides) in aquatic ecosystems have increased dramatically on a global scale in recent years.  These events result in the loss of human life each year, and economic losses in the billions of dollars due to effects on fisheries and tourism. Likewise, the increasing encroachment of humans along coasts has resulted in the recognition of potential public health issues as a consequence of the introduction of pathogenic microorganisms into these waters from land runoff, storm drains and sewage outflow.  Similar concerns exist regarding the potential for contamination of drinking water supplies with harmful, pathogenic or nuisance microbial species.  Unfortunately, the environmental factors that stimulate the growth of such microorganisms are still poorly understood, and tests for their abundances are not sufficiently rapid to detect the onset of major outbreaks.

This application area has both scientific and technological/application objectives. Scientifically, we seek to better understand the ecology of marine microorganisms and to develop methods for in-situ observation. From the technological and application points of view, the goals are to predict events involving proliferation of marine microorganisms (e.g., algal blooms), rapidly detect harmful events, and intervene to mitigate the consequences of such events.

The laboratory work, when fully developed, will constitute a revolutionary step in the tools presently available for investigating the ecology of aquatic microorganisms. It will serve also as a test bed for initial investigations of the issues that arise in monitoring the coastal ocean, which is a major application of the research we propose. Imagine, for example, that a set of instrumented buoys is deployed in the Pacific Ocean, near the mouth of the Los Angeles river, to monitor the impact of the river effluent on the coastal ocean ecosystem. Effective strategies for tracking the microorganisms carried by the fresh water can be developed, simulated and assessed at a reduced scale, in a tank environment, by injecting into the tank a suitable flow and using a network of tethered and autonomous sensors.

This application area will also make major contributions to the science and engineering of sensor/actuator networks, because of the requirements it imposes on the network: (i) mobility – to track microorganisms and assess their abundance with a reasonable number of sensors, these must be mobile; (ii) size – to gather information at a spatial scale comparable to the size of the microorganisms and to avoid disturbing them (especially in the laboratory environment), the sensors must be very small; (iii) liquid environment – combined with the small sensor size, this raises many difficult issues in mobility, communications and power, which in turn strongly impact network algorithms and strategies; and (iv) sensing – in situ, real-time identification of microorganisms is an unsolved problem, which requires the development of new sensors. In addition, the M3 application involves all the algorithmic problems that characterize ENS technology, such as coordination, triggering, and so on.

Over the expected ten year duration of the CENS there will be major advances in nano and micro sensors and actuators, and in strategies and algorithms for programming distributed, physically-coupled systems. Many of these advances will come directly from CENS research. As the technology evolves, we plan to shrink the size of the sensors and actuators and increase their numbers in our experiments. Eventually, we hope to be able to demonstrate large groups of autonomous, mobile robots capable of identifying and tracking microorganisms in real time in the marine environment, while measuring the relevant environmental conditions at the required temporal and spatial scales. Most of what we will learn from our research in marine monitoring and single-cell identification is expected to be applicable to an even more important liquid environment – the circulatory system of higher organisms, including humans.