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Nerve agents such as VX, Tabun (GA), and Cyclosarin (GF) are lethal even in trace amounts. Their lethality in addition to being difficult to detect makes nerve agents a significant global security problem. To address this problem, surface-enhanced Raman spectroscopy (SERS) has in recent years shown to be a promising technique for rapid and non-destructive field detection of various harmful substances. However, the application of SERS to nerve agents has so far been limited by their inherently poor Raman scattering cross-section, with nerve agents such as GF being particularly difficult to detect. In this work, we present a novel custom-designed Raman probe molecule: 4-Thiophene Pyridine Amido Oxime (TPAO), which enables selective detection and discrimination of live nerve agents in liquid media at trace concentrations, even using portable Raman instruments with limited spectral resolution. We report a detection limit for GF downward 1 ppm, much lower than that found in previous studies. We further find that TPAO allows us to detect VX and GA at 1.1 and 2.1 ppm, respectively, in line with or slightly surpassing previous benchmarks. To demonstrate the specificity with which TPAO can be used to sense and discriminate between nerve agents, we use principal component analysis to quantify spectral differences between nerve agents and simulants. Lastly, we show the robustness of TPAO, demonstrating its ability to detect nerve agents in complex backgrounds and after rinsing procedures. Altogether, this work represents a significant step forward towards achieving rapid and selective field detection of live nerve agents using SERS.

Analyzing microscopy images of large growing cell samples using traditional methods is a complex and time-consuming process. In this work, we have developed an attention-driven UNet-enhanced model using deep learning techniques to efficiently quantify the position, area, and circularity of bacterial spores and vegetative cells from images containing more than 10,000 bacterial cells. Our attention-driven UNet algorithm has an accuracy of 96%, precision of 82%, sensitivity of 81%, and specificity of 98%. Therefore, it can segment cells at a level comparable to manual annotation. We demonstrate the efficacy of this model by applying it to a live-dead decontamination assay. The model is provided in three formats: Python code, a Binder that operates within a web browser without needing installation, and a Flask Web application for local use.

Harmful chemical and biological agents are a significant threat to health and prosperity worldwide. Recent years have seen an increase in wars and conflicts around the globe, raising concerns about the potential deployment of chemical and biological warfare agents. On a less speculative level, harmful chemicals such as narcotic substances cause immense humanitarian and economic damage through overdoses and associated healthcare costs, while microbes such as pathogenic bacteria and parasites cause hospital-acquired infections and food spoilage at a cost of approximately 1 trillion euros every year. To combat the threat of these harmful agents, we must thus develop rapid and effective detection and diagnostic methods for harmful agents, allowing us to effectively deploy specific treatments and preventative measures.

Classically, while there exist numerous methods for the detection of both harmful chemical and biological agents, they often come with limitations that inhibit their effectiveness. These inhibitions often take the form of bulky equipment that is difficult to apply in the field or time-consuming preparation and measurement processes.

In this thesis we will explore an alternative category of assays for detecting and characterizing harmful materials – optical spectroscopy. Optical spectroscopy is a category of material characterization methods that use light to probe a material. While probing the material, we receive a signal characteristic of the molecules, chemical, and biological structure of our material. These optical spectroscopic methods, such as Raman spectroscopy and fluorescence spectroscopy, can be used to characterize a material within the span of minutes or even seconds, making them ideal for detection applications. Furthermore, they can often be made portable or even handheld, making them a great tool for initial field indication of harmful materials, ahead of thorough lab analysis.

I sincerely hope the studies presented herein can serve as a stepping stone to future technologies and detection assays, capable of saving both money and lives. 

Bacterial spores are highly resilient and capable of surviving extreme conditions, making them a persistent threat in contexts such as disease transmission, food safety, and bioterrorism. Their ability to withstand conventional sterilization methods necessitates rapid and accurate detection techniques to effectively mitigate the risks they present. In this study, we introduce a surface-enhanced Raman spectroscopy (SERS) approach for detecting Bacillus thuringiensis spores by targeting calcium dipicolinate acid (CaDPA), a biomarker uniquely associated with bacterial spores. Our method uses probe sonication to disrupt spores, releasing their CaDPA, which is then detected by SERS on drop-dried supernatant mixed with gold nanorods. This simple approach enables the selective detection of CaDPA, distinguishing it from other spore components and background noise. We demonstrate detection of biogenic CaDPA from concentrations as low as 10³ spores/mL, with sensitivity reaching beyond CaDPA levels of a single spore. Finally, we show the method’s robustness by detecting CaDPA from a realistic sample of fresh milk mixed with spores. These findings highlight the potential of SERS as a sensitive and specific technique for bacterial spore detection, with implications for fields requiring rapid and reliable spore identification.

Many strains among spore-forming bacteria species are associated with food spoilage, foodborne disease, and hospital-acquired infections. Understanding the impact of environmental conditions and decontamination techniques on the metabolic activity, viability, and biomarkers of these spores is crucial for combatting them. To distinguish and track spores and to understand metabolic mechanisms, spores must be labeled. Staining or genetic modification are current methods for this, however, these methods can be time-consuming, and affect the viability and function of spore samples. In this work, we investigate the use of heavy water for permanent isotope labeling of spores and Raman spectroscopy for tracking sporulation/germination mechanisms. We also discuss the potential of this method in observing decontamination. We find that steady-state deuterium levels in the spore are achieved after only ∼48 h of incubation with 30% D2O-infused broth and sporulation, generating Raman peaks at cell silent region of 2200 and 2300 cm−1. These deuterium levels then decrease rapidly upon spore germination in non-deuterated media. We further find that unlike live spores, spores inactivated using various methods do not lose these Raman peaks upon incubation in growth media, suggesting these peaks may be used to indicate the viability of a spore sample. We further observe several Raman peaks exclusive to deuterated DPA, a spore-specific chemical biomarker, at e.g. 988 and 2300 cm−1, which can be used to track underlying changes in spores involving DPA. In conclusion, permanent spore labeling using deuterium offers a robust and non-invasive way of labeling bacterial spores for marking, viability determination, and characterising spore activity.

Fentanyls are synthetic opioids up to 10,000 times more potent than morphine. Although initially developed for medical applications, fentanyl and its analogues have recently grown synonymous with the ongoing opioid epidemic. To combat the continued spread of these substances, there is a need for rapid and sensitive techniques for chemical detection. Surface-enhanced Raman spectroscopy (SERS) has the potential for trace detection of harmful chemical substances. However, vibrational spectra obtained by SERS often differ between SERS substrates, as well as compared with spectra from normal Raman (NR) spectroscopy. Herein, SERS and NR responses from two fentanyl analogues, carfentanil (CF) and thiofentanil (TF), were measured and analysed with support from density functional theory (DFT) modelling. Using commercially available silver nanopillar SERS substrates, the SERS signatures of samples diluted in acetonitrile between 0.01 and 1000 µg/mL were studied. Relative SERS peak intensities measured in the range of 220–1800 cm−1 vary with concentration, while SERS and NR spectra largely agree for CF at higher concentrations ((Formula presented.) 100 µg/mL). For TF, three distinct NR peaks at 262, 366 and 667 cm−1 are absent or strongly suppressed in the SERS spectrum, attributed to the lone-pair electrons of the thiophene's sulphur atom binding to the Ag surface. The concentration dependence of the Raman peak at (Formula presented.) 1000 cm−1, assigned to trigonal bending of the phenyl ring, approximately follows a Langmuir adsorption isotherm. This work elucidates similarities and differences between SERS and NR in fentanyl detection and discusses the chemical rationale behind these differences.

The ability to detect and inactivate spore-forming bacteria is of significance within, for example, industrial, healthcare, and defense sectors. Not only are stringent protocols necessary for the inactivation of spores but robust procedures are also required to detect viable spores after an inactivation assay to evaluate the procedure’s success. UV radiation is a standard procedure to inactivate spores. However, there is limited understanding regarding its impact on spores’ spectral and morphological characteristics. A further insight into these UV-induced changes can significantly improve the design of spore decontamination procedures and verification assays. This work investigates the spectral and morphological changes to Bacillus thuringiensis spores after UV exposure. Using absorbance and fluorescence spectroscopy, we observe an exponential decay in the spectral intensity of amino acids and protein structures, as well as a logistic increase in dimerized DPA with increased UV exposure on bulk spore suspensions. Additionally, using micro-Raman spectroscopy, we observe DPA release and protein degradation with increased UV exposure. More specifically, the protein backbone’s 1600–1700 cm^–1 amide I band decays slower than other amino acid-based structures. Last, using electron microscopy and light scattering measurements, we observe shriveling of the spore bodies with increased UV radiation, alongside the leaking of core content and disruption of proteinaceous coat and exosporium layers. Overall, this work utilized spectroscopy and electron microscopy techniques to gain new understanding of UV-induced spore inactivation relating to spore degradation and CaDPA release. The study also identified spectroscopic indicators that can be used to determine spore viability after inactivation. These findings have practical applications in the development of new spore decontamination and inactivation validation methods.

We present a new approach to segment and classify bacterial spore layers from Transmission Electron Microscopy (TEM) images using a hybrid Convolutional Neural Network (CNN) and Random Forest (RF) classifier algorithm. This approach utilizes deep learning, with the CNN extracting features from images, and the RF classifier using those features for classification. The proposed model achieved 73% accuracy, 64% precision, 46% sensitivity, and 47% F1-score with test data. Compared to other classifiers such as AdaBoost, XGBoost, and SVM, our proposed model demonstrates greater robustness and higher generalization ability for non-linear segmentation. Our model is also able to identify spores with a damaged core as verified using TEMs of chemically exposed spores. Therefore, the proposed method will be valuable for identifying and characterizing spore features in TEM images, reducing labor-intensive work as well as human bias.

Bacterial spores are problematic in agriculture, the food industry, and healthcare, with the fallout costs from spore-related contamination being very high. Spores are difficult to detect since they are resistant to many of the bacterial disruption techniques used to bring out the biomarkers necessary for detection. Because of this, effective and practical spore disruption methods are desirable. In this study, we demonstrate the efficiency of a compact microfluidic lab-on-chip built around a coplanar waveguide (CPW) operating at 2.45 GHz. We show that the CPW generates an electric field hotspot of ∼10 kV/m, comparable to that of a commercial microwave oven, while using only 1.2 W of input power and thus resulting in negligible sample heating. Spores passing through the microfluidic channel are disrupted by the electric field and release calcium dipicolic acid (CaDPA), a biomarker molecule present alongside DNA in the spore core. We show that it is possible to detect this disruption in a bulk spore suspension using fluorescence spectroscopy. We then use laser tweezers Raman spectroscopy (LTRS) to show the loss of CaDPA on an individual spore level and that the loss increases with irradiation power. Only 22% of the spores contain CaDPA after exposure to 1.2 W input power, compared to 71% of the untreated control spores. Additionally, spores exposed to microwaves appear visibly disrupted when imaged using scanning electron microscopy (SEM). Overall, this study shows the advantages of using a CPW for disrupting spores for biomarker release and detection.

Species belonging to the Bacillus cereus group form endospores (spores) whose surface is decorated with micrometers-long and nanometers-wide endospore appendages (Enas). The Enas have recently been shown to represent a completely novel class of Gram-positive pili. They exhibit remarkable structural properties making them extremely resilient to proteolytic digestion and solubilization. However, little is known about their functional and biophysical properties. In this work, we apply optical tweezers to manipulate and assess how wild type and Ena-depleted mutant spores immobilize on a glass surface. Further, we utilize optical tweezers to extend S-Ena fibers to measure their flexibility and tensile stiffness. Finally, by oscillating single spores, we examine how the exosporium and Enas affect spores’ hydrodynamic properties. Our results show that S-Enas (μm long pili) are not as effective as L-Enas in immobilizing spores to glass surfaces but are involved in forming spore to spore connections, holding the spores together in a gel-like state. The measurements also show that S-Enas are flexible but tensile stiff fibers, which support structural data suggesting that the quaternary structure is composed of subunits arranged in a complex to produce a bendable fiber (helical turns can tilt against each other) with limited axial fiber extensibility. Lastly, the results show that the hydrodynamic drag is 1.5-times higher for wild type spores expressing S- and L-Enas compared to mutant spores expressing only L-Enas or ”bald spores” lacking Ena, and 2-times higher compared to spores of the exosporium deficient strain. This study unveils novel findings on the biophysics of S- and L-Enas, their role in spore aggregation, binding of spores to glass, and their mechanical behavior upon exposure to drag forces.