Development of a microfluidic biosensor for detection of environmental mycobacteria
Introduction
For environmental engineers, microorganisms are important for a number of reasons. First, pathogenic microorganisms represent a threat to public health and must be eliminated from potable water; second, biocatalytic microorganisms are used to treat toxic pollutants (i.e., bioremediation) and thus should be encouraged to thrive; and third, nuisance microorganisms upset the reliable performance of bioprocesses. For environmental engineers, mycobacteria represent all three types. For instance, Gordonia (formerly Nocardia) amarae have been shown to be a causative agent for the formation of filamentous nuisance biological foam (e.g., nocardiafoam) on the surfaces of aeration basins, secondary clarifiers, and anaerobic digesters in municipal sewage treatment around the world [1], [2], [3]. The problem of nocardiafoam has been studied for more than 30 years, and the estimated total accumulative cost of incidences of nocardiafoam disrupting the acceptable performance of sewage treatment plants is of the order of 1 billion dollars [4].
Mycobacteria are slim, rod-shaped microorganisms that are 1–10 μm long [5] with a High Guanine plus Cytosine content of DNA (High G + C Gram positive bacteria). The mycobacteria include six distinct genera: Corynebacterium, Gordonia, Mycobacterium, Nocardia, Rhodococcus, and Tsukamurella [6]. Perhaps the most notable of these microorganisms are the pathogens Mycobacterium tuberculosis (i.e., the etiological agent of the disease “TB”) and Mycobacterium leprae (i.e., the etiological agent of the disease “leprosy”). Although TB was nearly eradicated during the 20th century, the occurrence of illness is rising, with more than 2 million annual deaths attributed to TB especially in less developed countries—the largest number of deaths attributed to a single cellular microorganism. This resurgence of TB is significantly more dangerous because the wide-spread use of antibiotics over the past 50 years has lead to the emergence of Mycobacterium demonstrating multiple-antibiotic resistance [7]. Furthermore, with the outbreak of human immunovirus (HIV)-induced acquired immunodeficiency syndrome (AIDS) in the industrialized world beginning in the 1980s, the infection of immunocompromised individuals with opportunistic pathogens belonging to the Mycobacterium avium complex (MAC) has risen dramatically [8], [9]. Although a historically well-known opportunistic pathogen, MACs generally do not infect individuals with healthy immune systems. Instead, individuals suffering from HIV infection, patients on a regimen of immuno-suppressant medication, as well as children and the elderly are the most commonly infected individuals. Because MAC infection primarily occurs due to oral ingestion, with inhalation as a secondary route, and because MACs are ubiquitous in nature the United States Environmental Protect Agency (US EPA) listed MACs as one often microbiological agents of interest on the Drinking Water Contaminant Candidate List (CCL) originally released in 1998 [10], [11] and updated in 2005 [12].
Due to their preeminent role in a variety of important environmental systems, robust, rapid, and easy-to-use technology to monitor mycobacteria is needed. The traditional methods to identify and monitor mycobacteria in environmental samples include direct observation using microscopy, often coupled with staining procedures or cultivation on semi-selective media [13], [14], [15]. Although these traditional methods have been used successfully to track mycobacteria in a variety of environmental samples, they suffer a number of limitations. For example, direct observation using microscopy requires significant training to recognize staining properties and the morphology of individual populations of microorganisms. Furthermore, it is accepted that the staining properties and morphology of microbial populations can change dramatically depending upon the environmental conditions experienced by the microorganisms. Thus, the robust nature of direct observation using microscopy can be questioned. Traditional cultivation of mycobacteria can require 3–5 weeks for the growth of colonies on agar surfaces. Obviously, such a turnaround time for an assay is extensive and cannot be classified as “rapid” by practical standards.
Alternatively, significant efforts have been invested in the development of molecular biology-based assays to identify and enumerate mycobacteria in environmental samples, including the detection of mycobacteria with antibodies [16], [17], [18], fluorescence in situ hybridization (FISH) targeting 16S ribosomal ribonucleic acid (16S rRNA) [16], [19], [20], [21], [22], and fatty acid methyl ester (FAME) analysis [23]. These methods show promise for identifying mycobacteria because they are sensitive, specific, and rapid. However, molecular biology-based techniques often lack the ability to distinguish between living and dead organisms, do not generate cultures that may be assayed subsequently for additional phenotypic traits (e.g., including antibiotic sensitivity), and are yet to be integrated into a user-friendly format. These drawbacks have caused cultivation to remain the primary means of screening for mycobacteria in clinical and environmental samples.
To improve culture-based techniques for monitoring specific microbial populations in environmental samples, we have developed a novel approach using microfabrication to create devices to rapidly screen for mycobacteria. Rather than using molecular biology-based assays to identify mycobacteria, we have miniaturized the culture-based assay to rapidly identify individual microbial populations adhered to a semi-selective surface material inside a microfluidic microchannel. In this paper we present the development of such a microfluidic biosensor and the application of this approach to rapid detection of mycobacteria in samples removed from a municipal activated sludge sewage treatment system.
Section snippets
Sensor design
The principle of the biosensor is schematically illustrated in Fig. 1. Microorganisms in the environment are often present in multi-specie populations arranged in flocs or biofilms. A sample collected from the environment (e.g., an activated sludge sewage treatment system) is first processed using chemical or physical procedures to disaggregate the microorganisms to release single, planktonic cells. The cell suspension is then incubated using available selective culturing conditions to isolate
Paraffin deposition and patterning
Paraffin was deposited and patterned by lift-off on a 3 in. diameter 1 mm thick cyclic olefin copolymer (COC) wafer using positive AZ P4620 photoresist (Clariant Inc.). The process is illustrated in Fig. 3. After cleaning with isopropyl alcohol, the COC wafer was spin coated with a 20 μm thick layer of AZ P4620. The photoresist was soft baked in a 65 °C oven for 12 min. Following standard UV exposure, the resist was developed in AZ400K developer diluted with water in a ratio of 1:3.5 (v:v). Paraffin
Results and discussion
The microfluidic culture-based sensor consists of a microchannel fabricated in COC containing paraffin islands used for bating and culturing bacteria. The final device formed from two 1-mm thick COC substrates had dimensions approximately 2 cm × 3 cm (Fig. 6). The microchannel was 1 mm in width, 15 mm in length, and 110 μm in height, while input and output ports were 600 μm in diameter. The three paraffin islands inside the microchannel were spaced at 2 mm, each being 800 μm wide, 1.5 mm long, and 5 μm
Conclusions
Micromachining technologies have been used to fabricate a culture-based microfluidic biochip. The rationale for developing this new technology is that a culture-based biochip will have faster turnaround time and will be more sensitive to detecting different types of mycolic acid containing actinomycetes as compared with existing assays. By miniaturizing culturing, we envision that multiple specific assays can be placed in parallel on a single device to enhance confidence in results by
Acknowledgements
The authors would like to acknowledge the support from the National Science Foundation (BES-0116912 and BES-0428600) and Emerging Concepts Inc.
Gaoshan Jing received his BS in biomedical engineering from Zhejiang University, Hangzhou, China, in 1998 and MS in Biophysics from Tsinghua University, Beijing, China, in 2001. In 2004, he received his MS in electrical engineering from University of Cincinnati, Cincinnati, Ohio. He is currently a research assistant in the Department of Electrical and Computer Engineering at Lehigh University, Bethlehem, PA. His research interests include MEMS sensors for biological applications.
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Gaoshan Jing received his BS in biomedical engineering from Zhejiang University, Hangzhou, China, in 1998 and MS in Biophysics from Tsinghua University, Beijing, China, in 2001. In 2004, he received his MS in electrical engineering from University of Cincinnati, Cincinnati, Ohio. He is currently a research assistant in the Department of Electrical and Computer Engineering at Lehigh University, Bethlehem, PA. His research interests include MEMS sensors for biological applications.
Amy Polaczyk received her BSc in biology from Morehead State University and a MSc from the University of Cincinnati in Environmental Science. She is currently pursuing a PhD at the University of North Carolina at Charlotte. Her research interests are drinking water treatment and development of rapid, quantitative methods for detection of microorganisms in water matrices.
Daniel B. Oerther received his PhD in environmental engineering from the University of Illinois, Urbana-Champaign. He is currently an Associate Professor in the Department of Civil and Environmental Engineering at the University of Cincinnati. His research interests include molecular microbial ecology of engineered bioprocesses, development of quantitative analytical methods to identify and enumerate environmental microorganisms, and sustainable development in urban settings and emerging global economies.
Ian Papautsky is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Cincinnati. He received his PhD in bioengineering from the University of Utah, Salt Lake City. His research focuses on applying microelectromechanical systems (MEMS) technologies to biology, medicine, and environmental systems. His research interests include polymer microfabrication technologies, sensors for point-of-use/point-of-care applications in environmental and biomedical engineering, polymer micro/nano fluidic systems, and plastic biochips/lab-on-a-chip systems.