Technology Development to Explore the Relationship Between Oral Health and the Oral Microbial Community

The human oral cavity contains a complex microbial community that, until recently, has not been well characterized. Studies using molecular tools have begun to enumerate and quantify the species residing in various niches of the oral cavity; yet, virtually every study has revealed additional new species, and little is known about the structural dynamics of the oral microbial community or how it changes with disease. Current estimates of bacterial diversity in the oral cavity range up to 700 species, although in any single individual this number is much lower. Oral microbes are responsible for common chronic diseases and are suggested to be sentinels of systemic human diseases. Microarrays are now being used to study oral microbiota in a systematic and robust manner. Although this technology is still relatively young, improvements have been made in all aspects of the technology, including advances that provide better discrimination between perfect-match hybridizations from non-specific (and closely-related) hybridizations. This review addresses a core technology using gel-based microarrays and the initial integration of this technology into a single device needed for system-wide studies of complex microbial community structure and for the development of oral diagnostic devices

Microfluidics: innovative approaches for rapid diagnosis of antibiotic-resistant bacteria

Correspondence: Surang Chankhamhaengdecha ([email protected]) The emergence of antibiotic-resistant bacteria has become a major global health concern. Rapid and accurate diagnostic strategies to determine the antibiotic susceptibility profile prior to antibiotic prescription and treatment are critical to control drug resistance. The standard diagnostic procedures for the detection of antibiotic-resistant bacteria, which rely mostly on phenotypic characterization, are time consuming, insensitive and often require skilled personnel, making them unsuitable for point-of-care (POC) diagnosis. Various molecular techniques have therefore been implemented to help speed up the process and increase sensitivity. Over the past decade, microfluidic technology has gained great momentum in medical diagnosis as a series of fluid handling steps in a laboratory can be simplified and miniaturized on to a small platform, allowing marked reduction of sample amount, high portability and tremendous possibility for integration with other detection technologies. These advantages render the microfluidic system a great candidate to be developed into an easy-to-use sample-to-answer POC diagnosis suitable for application in remote clinical settings. This review provides an overview of the current development of microfluidic technologies for the nucleic acid based and phenotypic-based detections of antibiotic resistance

Microfluidic platforms for cell cultures and investigations

This review covers several aspects of microfluidic devices used for culturing and monitoring of both adherent and non-adherent cells, including a multitude of applications. A comparison of available platforms with high throughput analysis, automation capability, interface to sensors and integration, is reported. Aspects, such as operational versatility of the devices, are scrutinized in terms of their analytical efficacy. It is found that due to multi-functionality capability of modern microfluidics, there is big amount of experimental data obtainable from a single device, allowing complex experimental control and efficient data correlation, particularly important when biomedical studies are considered. Hence several examples on cell culture and monitoring are given in this review, including details on design of microfluidic devices with their distinctive technological peculiarities

Advances in non-invasive biosensing measures to monitor wound healing progression

Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed

Diagnostic Biosensors for Detection of Blood-Derived Biomarkers

Standard diagnostic tools used from patient samples, specifically from blood draws, require specialized equipment, personnel, and facilities. Conventional techniques can often be very laborious and time consuming due to required sample preparation. The evident delay from sample collection to a patient’s result immensely impacts their outcome. The aims of this research are to design diagnostic biosensors that decrease time-to-results, minimize reagent and sample handling, and incorporate automated simple optical transduction and user interfaces for the detection of blood-derived biomarkers. Specifically, four biosensing detection mechanisms performed on 3 different point-of-care platforms will be discussed. First is a static loop-mediated isothermal amplification (LAMP) of nucleic acid aqueous droplet on a silicone chip platform immersed in mineral oil. The target-of-interest is a nucleic acid sequence as a biomarker for antibiotic resistant bacteria. The biosensing technique used related changes in interfacial tension (IFT) at the water-oil interface by measuring the change in contact angle (geometrical-effects) over time. Initially the system was characterized as a linear response in relation to concentration of bacteria in a buffer system down to the limit of detection (LOD) of 100 CFU per uL. Subsequently, with the addition of bacterial infected blood sample models, the system became a binary assay (i.e. yes or no) as low as 10 CFU per uL within 10 min of reaction. Secondly, a two-layered, paper microfluidic chip was utilized to quantify cancer cells from a buffy coat sample matrix by two detection mechanisms: 1) on-chip particle enumeration via smartphone microscope and 2) capillary flow dynamics via smartphone video processing. The assay resulted in a LOD as low as 1 cell per uL for the on-chip imaging aspect of platform and 0.1 cell per uL for the capillary flow analysis within 13 to 22s post application of blood sample. Lastly, the same concepts previously described in the first platform utilizes changes in IFT due to amplicon presence in an aqueous solution immersed in mineral oil. An emulsion LAMP platform was investigated to determine the relation between angle-dependent light scatter intensity (based off Mie scatter theory) and nucleic acid amplification progression. The phenomenon attributing to changes in light scatter intensities is due to the interfacial changes occurring in the emulsion droplets, where amplicon amount increases the IFT decreases, resulting in smaller diameter emulsions. Changes in light scatter intensity within 3 min of the reaction shows statistical difference in comparison to no target control (NTC) for 10^3 CFU per uL of bacteria dosed into aqueous sample. These four detection mechanisms and three platforms offer but a few alternatives as biosensing methods for blood-derived diagnostic biosensors

Integrated Electrochemical Biosensors for Detection of Waterborne Pathogens in Low-Resource Settings

More than 783 million people worldwide are currently without access to clean and safe water. Approximately 1 in 5 cases of mortality due to waterborne diseases involve children, and over 1.5 million cases of waterborne disease occur every year. In the developing world, this makes waterborne diseases the second highest cause of mortality. Such cases of waterborne disease are thought to be caused by poor sanitation, water infrastructure, public knowledge, and lack of suitable water monitoring systems. Conventional laboratory-based techniques are inadequate for effective on-site water quality monitoring purposes. This is due to their need for excessive equipment, operational complexity, lack of affordability, and long sample collection to data analysis times. In this review, we discuss the conventional techniques used in modern-day water quality testing. We discuss the future challenges of water quality testing in the developing world and how conventional techniques fall short of these challenges. Finally, we discuss the development of electrochemical biosensors and current research on the integration of these devices with microfluidic components to develop truly integrated, portable, simple to use and cost-effective devices for use by local environmental agencies, NGOs, and local communities in low-resource settings

Point-of-Care Detection Devices for Healthcare

With recent technological advances in multiple research fields such as materials science, micro-/nano-technology, cellular and molecular biology, bioengineering and the environment, much attention is shifting toward the development of new detection tools that not only address needs for high sensitivity and specificity but fulfil economic, environmental, and rapid point-of-care needs for groups and individuals with constrained resources and, possibly, limited training. Miniaturized fluidics-based platforms that precisely manipulate tiny body fluid volumes can be used for medical, healthcare or even environmental (e.g., heavy metal detection) diagnosis in a rapid and accurate manner. These new detection technologies are potentially applicable to different healthcare or environmental issues, since they are disposable, inexpensive, portable, and easy to use for the detection of human diseases or environmental issues—especially when they are manufactured based on low-cost materials, such as paper. The topics in this book (original and review articles) would cover point-of-care detection devices, microfluidic or paper-based detection devices, new materials for making detection devices, and others

Microscale methods to investigate and manipulate multispecies biological systems

The continuing threats from viral infectious diseases highlight the need for new tools to study viral interactions with host cells. Understanding how these viruses interact and respond to their environment can help predict outbreaks, shed insight on the most likely strains to emerge, and determine which viruses have the potential to cause significant human illness. Animal studies provide a wealth of information, but the interpretation of results is confounded by the large number of uncontrolled or unknown variables in complex living systems. In contrast, traditional tissue culture approaches have provided investigators a valuable platform with a high degree of experimental control and flexibility, but the static nature of flask-based cell culture makes it difficult to study viral evolution. Serial passaging introduces un-physiological perturbations to cell and virus populations by drastically reducing the number of species with each passage. Low copy, high fitness viral variants maybe eliminated, while in vivo these variants would be essential in determining the virus’ evolutionary fate. Bridging technologies are urgently needed to mitigate the unrealistic dynamics in static flask-based cultures, and the complexity and expense of in vivo experiments. This thesis details the development of a continuous perfusion platform capable of more closely mimicking in vivo cell-virus dynamics, while surpassing the experimental control and flexibility of standard cell culture. First, a microfluidic flow through acoustic device is optimized to enable efficient and controllable separation of cells and viruses. Repeatable isolation of cell and virus species is demonstrated with both a well-characterized virus, Dengue Virus (DENV), and the novel Golden Gate Virus. Next, a platform is built around this device to enable controllable, automated, continuous cell culture. Beads are used to assess system performance and optimize operation. Subsequently, the platform is used to culture both murine hybridoma (4G2) and human monocyte (THP-1) cell lines for over one month, and demonstrate the ability to manipulate population dynamics. Finally, we use the platform to establish a multispecies culture with THP-1 cells and Sindbis Virus (SINV). This work integrates distinct engineering feats to create a platform capable of enhancing existing cell virus studies and opening the door to a variety of high-impact investigations

Development of a cell-based lab-on-a-chip sensor for detection of oral cancer biomarkers

textOral cancer is the sixth most common cancer worldwide and has been marked by high morbidity and poor survival rates that have changed little over the past few decades. Beyond prevention, early detection is the most crucial determinant for successful treatment and survival of cancer. Yet current methodologies for cancer diagnosis based upon pathological examination alone are insufficient for detecting early tumor progression and molecular transformation. Development of new diagnostic tools incorporating tumor biomarkers could enhance early detection by providing molecular-level insight into the biochemical and cellular changes associated with oral carcinogenesis. The work presented in this doctoral dissertation aims to address this clinical need through the development of new automated cellular analysis methods, incorporating lab-on-a-chip sensor techniques, for examination of molecular and morphological biomarkers associated with oral carcinogenesis. Using the epidermal growth factor receptor (EGFR) as a proof-of-principle biomarker, the sensor system demonstrated capacity to support rapid biomarker analysis in less than one-tenth the time of traditional methods and effectively characterized EGFR biomarker over-expression in oral tumor-derived cell lines. Successful extension from in vitro tumor cell lines to clinically relevant exfoliative brush cytology was demonstrated, providing a non-invasive method for sampling abnormal oral epithelium. Incorporation of exfoliative cytology further helped to define the important assay and imaging parameters necessary for dual molecular and morphological analysis in adherent epithelium. Next, this new sensor assay and method was applied in a small pilot study in order to secure an initial understanding of the diagnostic utility of such biosensor systems in clinical settings. Four cellular features were identified as useful indicators of cancerous or pre-cancerous conditions including, the nuclear area and diameter, nuclear-to-cytoplasm ratio, and EGFR biomarker expression. Further examination using linear regression and ROC curve analysis identified the morphological features as the best predictors of disease while a combination of all features may be ideal for classification of OSCC and pre-malignancy with high sensitivity and specificity. Further testing in a larger sample size is necessary to validate this regression model and the LOC sensor technique, but shows strong promise as a new diagnostic tool for early detection of oral cancer.Chemistry and Biochemistr