Identifying different types of microorganisms with terahertz spectroscopy

Rapid and sensitive detection of Staphylococcus aureus using a THz metamaterial biosensor based on aptamer-functionalized Fe3O4@Au nanocomposites

Staphylococcus aureus (S. aureus) poses a serious threat to global public health, necessitating the establishment of rapid and simple tools for its accurate identification. Herein, we developed a terahertz (THz) metamaterial biosensor based on aptamer-functionalized Fe3O4@Au nanocomposites for quantitative S. aureus assays in different clinical samples. Fe3O4@Au@Cys@Apt has the dual advantages of magnetism and a high refractive index in the THz range and was used to rapidly separate and enrich target bacteria in a complex environmental solution. Furthermore, conjugation to the nanocomposites significantly increased the resonance frequency shift of the THz metamaterial after target loading. Our results showed that the shifts in the metamaterial resonance frequency were linearly related to S. aureus concentrations ranging from 1.0 × 103 to 1.0 × 107 CFU/mL, with a detection limit of 4.78 × 102 CFU/mL. The biosensor was further applied to S. aureus detection in spiked human urine and blood with satisfactory recoveries (82.4-109.6%). Our approach also demonstrated strong concordance with traditional plate counting (R2 = 0.99306) while significantly lowering the analysis time from 24 h to <1 h. In conclusion, the proposed biosensor can not only perform culture-free and extraction-free detection of target bacteria but can also be easily extended to the determination of other pathogenic bacteria, rendering it suitable for various bacteria-related disease diagnoses.

Metasurface-Assisted Terahertz Sensing

Terahertz (THz) waves, which fall between microwaves and infrared bands, possess intriguing electromagnetic properties of non-ionizing radiation, low photon energy, being highly sensitive to weak resonances, and non-polar material penetrability. Therefore, THz waves are extremely suitable for sensing and detecting chemical, pharmaceutical, and biological molecules. However, the relatively long wavelength of THz waves (30~3000 μm) compared to the size of analytes (1~100 nm for biomolecules, <10 μm for microorganisms) constrains the development of THz-based sensors. To circumvent this problem, metasurface technology, by engineering subwavelength periodic resonators, has gained a great deal of attention to enhance the resonance response of THz waves. Those metasurface-based THz sensors exhibit high sensitivity for label-free sensing, making them appealing for a variety of applications in security, medical applications, and detection. The performance of metasurface-based THz sensors is controlled by geometric structure and material parameters. The operating mechanism is divided into two main categories, passive and active. To have a profound understanding of these metasurface-assisted THz sensing technologies, we review and categorize those THz sensors, based on their operating mechanisms, including resonators for frequency shift sensing, nanogaps for enhanced field confinement, chirality for handedness detection, and active elements (such as graphene and MEMS) for advanced tunable sensing. This comprehensive review can serve as a guideline for future metasurfaces design to assist THz sensing and detection.

Developing a Novel Terahertz Fabry-Perot Microcavity Biosensor by Incorporating Porous Film for Yeast Sensing

We present a novel terahertz (THz) Fabry-Perot (FP) microcavity biosensor that uses a porous polytetrafluoroethylene (PTFE) supporting film to improve microorganism detection. The THz FP microcavity confines and enhances fields in the middle of the cavity, where the target microbial film is placed with the aid of a PTFE film having a dielectric constant close to unity in the THz range. The resonant frequency shift increased linearly with increasing amount of yeasts, without showing saturation behavior under our experimental conditions. These results agree well with finite-difference time-domain (FDTD) simulations. The sensor's sensitivity was 11.7 GHz/μm, close to the optimal condition of 12.5 GHz/μm, when yeast was placed at the cavity's center, but no frequency shift was observed when the yeast was coated on the mirror side. We derived an explicit relation for the frequency shift as a function of the index, amount, and location of the substances that is consistent with the electric field distribution across the cavity. We also produced THz transmission images of yeast-coated PTFE, mapping the frequency shift of the FP resonance and revealing the spatial distribution of yeast.

Low-THz Vibrations of Biological Membranes

A growing body of work has linked key biological activities to the mechanical properties of cellular membranes, and as a means of identification. Here, we present a computational approach to simulate and compare the vibrational spectra in the low-THz region for mammalian and bacterial membranes, investigating the effect of membrane asymmetry and composition, as well as the conserved frequencies of a specific cell. We find that asymmetry does not impact the vibrational spectra, and the impact of sterols depends on the mobility of the components of the membrane. We demonstrate that vibrational spectra can be used to distinguish between membranes and, therefore, could be used in identification of different organisms. The method presented, here, can be immediately extended to other biological structures (e.g., amyloid fibers, polysaccharides, and protein-ligand structures) in order to fingerprint and understand vibrations of numerous biologically-relevant nanoscale structures.

Terahertz thermal curve analysis for label-free identification of pathogens

In this study, we perform a thermal curve analysis with terahertz (THz) metamaterials to develop a label-free identification tool for pathogens such as bacteria and yeasts. The resonant frequency of the metasensor coated with a bacterial layer changes as a function of temperature; this provides a unique fingerprint specific to the individual microbial species without the use of fluorescent dyes and antibodies. Differential thermal curves obtained from the temperature-dependent resonance exhibit the peaks consistent with bacterial phases, such as growth, thermal inactivation, DNA denaturation, and cell wall destruction. In addition, we can distinguish gram-negative bacteria from gram-positive bacteria which show strong peaks in the temperature range of cell wall destruction. Finally, we perform THz melting curve analysis on the mixture of bacterial species in which the pathogenic bacteria are successfully distinguished from each other, which is essential for practical clinical and environmental applications such as in blood culture.

A label-free sensing method has been developed for identifying hazardous pathogens based on their intrinsic properties. This was possible by interrogating the temperature-dependent dielectric constant of the microbes in the far-infrared range.

Moxa Wool in Different Purities and Different Growing Years Measured by Terahertz Spectroscopy

Moxa wool is a traditional Chinese herbal medicine, which can warm channels to dispel coldness. At present, there is no unified index to evaluate the purity and growing years of moxa wool in the market. Terpineol is one of the effective substances in the volatile oil of moxa wool. Here, we characterize the purity and growing years of moxa wool by studying terpineol. Gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography (HPLC) are the methods for monitoring terpineol at present, all of which have defects of complicated procedures. We established linear fitting to distinguish the different purities of moxa wool through the intensities (areas) of terpineol, the characteristic peaks, and the consequence presented; the coefficient of determination (R2) was higher than 0.90. Furthermore, based on the characteristic peak position of standard terpineol, the correlation model with the purity and growing year of moxa wool was set up, thereby differentiating the quality of moxa wool. We have built the partial least squares (PLS) model of the growing years of moxa wool with high accuracy, and the determination coefficient is greater than 0.98. In addition, we compare the quantitative accuracy of Raman spectroscopy with terahertz technology. Finally, a new method of terahertz spectroscopy to evaluate quality of moxa wool was found. It provides a new idea for the identification of inferior moxa wool in the market and a new method for identifying the quality of moxa wool in traditional Chinese medicine.

THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

The demand for rapid and accurate identification of microorganisms is growing due to considerable importance in all areas related to public health and safety. Here, we demonstrate a rapid and label-free strategy for the identification of microorganisms by integrating terahertz-attenuated total reflection (THz-ATR) spectroscopy with an automated recognition method based on multi-classifier voting. Our results show that 13 standard microbial strains can be classified into three different groups of microorganisms (Gram-positive bacteria, Gram-negative bacteria, and fungi) by THz-ATR spectroscopy. To detect clinical microbial strains with better differentiation that accounts for their greater sample heterogeneity, an automated recognition algorithm is proposed based on multi-classifier voting. It uses three types of machine learning classifiers to identify five different groups of clinical microbial strains. The results demonstrate that common microorganisms, once time-consuming to distinguish by traditional microbial identification methods, can be rapidly and accurately recognized using THz-ATR spectra in minutes. The proposed automatic recognition method is optimized by a spectroscopic feature selection algorithm designed to identify the optimal diagnostic indicator, and the combination of different machine learning classifiers with a voting scheme. The total diagnostic accuracy reaches 80.77% (as high as 99.6% for Enterococcus faecalis) for 1123 isolates from clinical samples of sputum, blood, urine, and feces. This strategy demonstrates that THz spectroscopy integrated with an automatic recognition method based on multi-classifier voting significantly improves the accuracy of spectral analysis, thereby presenting a new method for true label-free identification of clinical microorganisms with high efficiency.

Streptavidin-functionalized terahertz metamaterials for attomolar exosomal microRNA assay in pancreatic cancer based on duplex-specific nuclease-triggered rolling circle amplification

Exosomal microRNA (miRNA) is a promising non-invasive biomarker for liquid biopsies. Herein, we fabricated a terahertz (THz) metamaterial biosensor that comprises an array of gold (Au) discs surrounded by annular grooves for exosomal miRNA assays based on duplex-specific nuclease (DSN)-triggered rolling circle amplification (RCA). In this strategy, the target miRNA is captured by a probe P0 immobilized on magnetic beads (MBs); it then repeatedly releases a primer P1 under the action of DSN, which acts as a highly specific initiator of the subsequent RCA step utilizing biotin-dUTP. After target recycling and nucleic acid amplification, the biotinylated amplification products were captured by the streptavidin (SA)-functionalized THz metamaterials, and further conjugated to SA-modified AuNPs that permit formation of a trimeric complex of SA-biotinylated RCA products-AuNP. The complex population scales with the starting concentration of the target miR-21, resulting in a red shift of the resonance peak of the THz metamaterials. This biosensor can lead to highly specific and sensitive detection with one-base mismatch discrimination and a limit of detection (LOD) down to 84 aM. Significant distinctions are seen in the frequency shifts for exosomal miR-21 quantitation in clinical plasma samples between pancreatic cancer patients and healthy controls. The frequency shifts of the THz metamaterials are consistent versus the reverse transcription-polymerase chain reaction (RT-PCR) results, illustrating the applicability and accuracy of our assay in real clinical samples.