LOC-SERS: A Promising Closed System for the Identification of Mycobacteria

Surface-Enhanced Raman Spectroscopy at the Interface between Drug Discovery and Personalized Medicine

Personalized medicine and drug discovery are different, yet overlapping, fields, and information from each field is exchanged to improve the other. The current methods used for devising personalized therapeutic plans and developing drug discovery applications are costly, time-consuming, and complex; thus, their applicability is limited in both fields. However, surface-enhanced Raman spectroscopy (SERS) offers potential solutions to current challenges. This Mini-Review explores the utility of SERS in drug discovery and personalized medicine. The Mini-Review starts with a brief overview of these fields, including the main challenges and current methods, and then explores examples where SERS has been used to overcome some of the main challenges in both fields. It ends with brief conclusions, perspectives, and current challenges limiting the practical application of SERS.

On-Chip Photonic Detection Techniques for Non-Invasive In Situ Characterizations at the Microfluidic Scale

Microfluidics has emerged as a robust technology for diverse applications, ranging from bio-medical diagnostics to chemical analysis. Among the different characterization techniques that can be used to analyze samples at the microfluidic scale, the coupling of photonic detection techniques and on-chip configurations is particularly advantageous due to its non-invasive nature, which permits sensitive, real-time, high throughput, and rapid analyses, taking advantage of the microfluidic special environments and reduced sample volumes. Putting a special emphasis on integrated detection schemes, this review article explores the most relevant advances in the on-chip implementation of UV-vis, near-infrared, terahertz, and X-ray-based techniques for different characterizations, ranging from punctual spectroscopic or scattering-based measurements to different types of mapping/imaging. The principles of the techniques and their interest are discussed through their application to different systems.

Hybrid use of Raman spectroscopy and artificial neural networks to discriminate Mycobacterium bovis BCG and other Mycobacteriales

Even in the face of the COVID-19 pandemic, Tuberculosis (TB) continues to be a major public health problem and the 2nd biggest infectious cause of death worldwide. There is, therefore, an urgent need to develop effective TB diagnostic methods, which are cheap, portable, sensitive and specific. Raman spectroscopy is a potential spectroscopic technique for this purpose, however, so far, research efforts have focused primarily on the characterisation of Mycobacterium tuberculosis and other Mycobacteria, neglecting bacteria within the microbiome and thus, failing to consider the bigger picture. It is paramount to characterise relevant Mycobacteriales and develop suitable analytical tools to discriminate them from each other. Herein, through the combined use of Raman spectroscopy and the self-optimising Kohonen index network and further multivariate tools, we have successfully undertaken the spectral analysis of Mycobacterium bovis BCG, Corynebacterium glutamicum and Rhodoccocus erythropolis. This has led to development of a useful tool set, which can readily discern spectral differences between these three closely related bacteria as well as generate a unique spectral barcode for each species. Further optimisation and refinement of the developed method will enable its application to other bacteria inhabiting the microbiome and ultimately lead to advanced diagnostic technologies, which can save many lives.

Accessing Properties of Molecular Compounds Involved in Cellular Metabolic Processes with Electron Paramagnetic Resonance, Raman Spectroscopy, and Differential Scanning Calorimetry

In this work, we review some physical methods of macroscopic experiments, which have been recently argued to be promising for the acquisition of valuable characteristics of biomolecular structures and interactions. The methods we focused on are electron paramagnetic resonance spectroscopy, Raman spectroscopy, and differential scanning calorimetry. They were chosen since it can be shown that they are able to provide a mutually complementary picture of the composition of cellular envelopes (with special attention paid to mycobacteria), transitions between their molecular patterning, and the response to biologically active substances (reactive oxygen species and their antagonists-antioxidants-as considered in our case study).

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications

BACKGROUND

The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential.

AIM OF REVIEW

Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed.Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc.

Recent Progress of Surface-Enhanced Raman Spectroscopy for Bacteria Detection

There are various pathogenic bacteria in the surrounding living environment, which not only pose a great threat to human health but also bring huge losses to economic development. Conventional methods for bacteria detection are usually time-consuming, complicated and labor-intensive, and cannot meet the growing demands for on-site and rapid analyses. Sensitive, rapid and effective methods for pathogenic bacteria detection are necessary for environmental monitoring, food safety and infectious bacteria diagnosis. Recently, benefiting from its advantages of rapidity and high sensitivity, surface-enhanced Raman spectroscopy (SERS) has attracted significant attention in the field of bacteria detection and identification as well as drug susceptibility testing. Here, we comprehensively reviewed the latest advances in SERS technology in the field of bacteria analysis. Firstly, the mechanism of SERS detection and the fabrication of the SERS substrate were briefly introduced. Secondly, the label-free SERS applied for the identification of bacteria species was summarized in detail. Thirdly, various SERS tags for the high-sensitivity detection of bacteria were also discussed. Moreover, we emphasized the application prospects of microfluidic SERS chips in antimicrobial susceptibility testing (AST). In the end, we gave an outlook on the future development and trends of SERS in point-of-care diagnoses of bacterial infections.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

Application of SERS in the Detection of Fungi, Bacteria and Viruses

In this review, we report the recent advances of SERS in fungi, bacteria, and viruses. Firstly, we briefly introduce the advantage of SERS over fluorescence on virus identification and detection. Secondly, we review the feasibility analysis of Raman/SERS spectrum analysis, identification, and fungal detection on SERS substrates of various nanostructures with a signal amplification mechanism. Thirdly, we focus on SERS spectra for nucleic acid, pathogens for the detection of viruses and bacteria, and furthermore introduce SERS-based microdevices, including SERS-based microfluidic devices, and three-dimensional nanostructured plasmonic substrates.

Label-Free Sensing with Metal Nanostructure-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis

Surface-Enhanced Raman Spectroscopy (SERS) is a powerful analytical technique for the detection of small analytes with great potential for medical diagnostic applications. Its high sensitivity and excellent molecular specificity, which stems from the unique fingerprint of molecular species, have been applied toward the detection of different types of cancer. The noninvasive and rapid detection offered by SERS highlights its applicability for point-of-care (PoC) deployment for cancer diagnosis, screening, and staging, as well as for predicting tumor recurrence and treatment monitoring. This review provides an overview of the progress in label-free (direct) SERS-based chemical detection for cancer diagnosis with the main focus on the advances in the design and preparation of SERS substrates on the basis of metal nanoparticle structures formed via bottom-up strategies. It begins by introducing a synopsis of the working principles of SERS, including key chemometric approaches for spectroscopic data analysis. Then it introduces the advances of label-free sensing with SERS in cancer diagnosis using biofluids (blood, urine, saliva, sweat) and breath as the detection media. In the end, an outlook of the advances and challenges in cancer diagnosis via SERS is provided.

Dual-Approach Electrochemical Surface-Enhanced Raman Scattering Detection of Mycobacterium tuberculosis in Patient-Derived Biological Specimens: Proof of Concept for a Generalizable Method to Detect and Identify Bacterial Pathogens

The recent surge in infectious disease-causing pathogens, resulting in global catastrophe, has merited a pivotal quest toward point-of-care (POC) diagnostics. Mycobacterium tuberculosis (MTB) is still the top bacterium-based infectious disease-causing pathogen worldwide. In a concerted effort toward simplifying and decentralizing the discriminatory screening of MTB causing pathogens, electrochemical surface-enhanced Raman scattering (EC-SERS) was adopted to create a customized screening tool. The development strategy combined five key factors, including (i) a simplified Tollens'-based chemical synthesis method for bulk supply of silver nanoparticles, (ii) the deliberate surface modification of nanoparticles with carefully selected polyelectrolytes to resemble the conditioning layer usually found on a natural substratum, (iii) uniform SERS-active films formed through simple unprogrammed assembly, (iv) the controlled manipulation of the local electric field through applied voltage using a technique that does not conform to the limitations of classical EC-SERS, and (v) the inherent specificity of the target-specific SERS vibrational signature. The EC-SERS platform was able to discriminatively detect and identify TB-derived mycobacteria, including three clinically relevant MTB strains, TB-H37Rv, TB-HN878, and TB-CDC1551. Moreover, a customized voltage stepping protocol, compatible with either the inclusion of a short preincubation step or with in situ EC-SERS is illustrated. From the obtained SERS vibrational signatures, a band indicating a mode unique to TB-derived/TB-affiliated mycobacteria and thus not observed for other bacterial types used in this study was illustrated. Furthermore, provisional investigation, done as prelude for assessing the potential for translational adaptability of the EC-SERS technique toward POC clinical settings for sputum and urine specimens, was carried out.

Plasmonic nanosensors for point-of-care biomarker detection

Advancement of materials along with their fascinating properties play increasingly important role in facilitating the rapid progress in medicine. An excellent example is the recent development of biosensors based on nanomaterials that induce surface plasmon effect for screening biomarkers of various diseases ranging from cancer to Covid-19. The recent global pandemic re-confirmed the trend of real-time diagnosis in public health to be in point-of-care (POC) settings that can screen interested biomarkers at home, or literally anywhere else, at any time. Plasmonic biosensors, thanks to its versatile designs and extraordinary sensitivities, can be scaled into small and portable devices for POC diagnostic tools. In the meantime, efforts are being made to speed up, simplify and lower the cost of the signal readout process including converting the conventional heavy laboratory instruments into lightweight handheld devices. This article reviews the recent progress on the design of plasmonic nanomaterial-based biosensors for biomarker detection with a perspective of POC applications. After briefly introducing the plasmonic detection working mechanisms and devices, the selected highlights in the field focusing on the technology's design including nanomaterials development, structure assembly, and target applications are presented and analyzed. In parallel, discussions on the sensor's current or potential applicability in POC diagnosis are provided. Finally, challenges and opportunities in plasmonic biosensor for biomarker detection, such as the current Covid-19 pandemic and its testing using plasmonic biosensor and incorporation of machine learning algorithms are discussed.

Advances in droplet microfluidics for SERS and Raman analysis

Raman spectroscopy can realize qualitative and quantitative characterization, and surface-enhanced Raman spectroscopy (SERS) can further enhance its detection sensitivity. In combination with droplet microfluidics, some significant but insurmountable limitations of SERS and Raman spectroscopy can be overcome to some extent, thus improving their detection capability and extending their application. During the past decade, these systems have constantly developed and demonstrated a great potential in more applications, but there is no new review systematically summarizing the droplet microfluidics-based Raman and SERS analysis system since the first related review was published in 2011. Thus, there is a great need for a new review to summarize the advances. In this review, we focus on droplet microfluidics-based Raman and SERS analysis, and summarize two mainstream research directions on this topic up to now. The one is SERS or Raman detection in the moving droplet microreactors, including analysis of molecules, single cells and chemical reaction processes. The other one is SERS active microparticle fabrication via microfluidic droplet templates covering polymer matrix and photonic crystal microparticles. We also comment on the advantages, disadvantage and correlation resolution of droplet microfluidics for SERS or Raman. Finally, we summarize these systems and illustrate our perspectives for future research directions in this field.

Machine learning analysis of SERS fingerprinting for the rapid determination of Mycobacterium tuberculosis infection and drug resistance

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Handheld Raman spectrometer is able to generate SERS spectra with sufficient quality for Mycobacterium tuberculosis detection.

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It is feasible to accurately discriminate Mtb-positive sputum from Mtb-negative sputum through SERS spectrometry.

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Pulmonary and extra-pulmonary Mtb strains were able to be accurately distinguished via SERS spectral analysis.

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Profiling of antibiotic resistance of Mtb strains was successfully achieved through machine learning analysis of SERS spectra.

Over the past decades, conventional methods and molecular assays have been developed for the detection of tuberculosis (TB). However, these techniques suffer limitations in the identification of Mycobacterium tuberculosis (Mtb), such as long turnaround time and low detection sensitivity, etc., not even mentioning the difficulty in discriminating antibiotics-resistant Mtb strains that cause great challenges in TB treatment and prevention. Thus, techniques with easy implementation for rapid diagnosis of Mtb infection are in high demand for routine TB diagnosis. Due to the label-free, low-cost and non-invasive features, surface enhanced Raman spectroscopy (SERS) has been extensively investigated for its potential in bacterial pathogen identification. However, at current stage, few studies have recruited handheld Raman spectrometer to discriminate sputum samples with or without Mtb, separate pulmonary Mtb strains from extra-pulmonary Mtb strains, or profile Mtb strains with different antibiotic resistance characteristics. In this study, we recruited a set of supervised machine learning algorithms to dissect different SERS spectra generated via a handheld Raman spectrometer with a focus on deep learning algorithms, through which sputum samples with or without Mtb strains were successfully differentiated (5-fold cross-validation accuracy = 94.32%). Meanwhile, Mtb strains isolated from pulmonary and extra-pulmonary samples were effectively separated (5-fold cross-validation accuracy = 99.86%). Moreover, Mtb strains with different drug-resistant profiles were also competently distinguished (5-fold cross-validation accuracy = 99.59%). Taken together, we concluded that, with the assistance of deep learning algorithms, handheld Raman spectrometer has a high application potential for rapid point-of-care diagnosis of Mtb infections in future.

Recent advances in antibiotic resistance diagnosis using SERS: focus on the “Big 5” challenges

SERS for antibiotic resistance diagnosis.

Microfluidics as a Novel Technique for Tuberculosis: From Diagnostics to Drug Discovery

Tuberculosis (TB) remains a global healthcare crisis, with an estimated 5.8 million new cases and 1.5 million deaths in 2020. TB is caused by infection with the major human pathogen Mycobacterium tuberculosis, which is difficult to rapidly diagnose and treat. There is an urgent need for new methods of diagnosis, sufficient in vitro models that capably mimic all physiological conditions of the infection, and high-throughput drug screening platforms. Microfluidic-based techniques provide single-cell analysis which reduces experimental time and the cost of reagents, and have been extremely useful for gaining insight into monitoring microorganisms. This review outlines the field of microfluidics and discusses the use of this novel technique so far in M. tuberculosis diagnostics, research methods, and drug discovery platforms. The practices of microfluidics have promising future applications for diagnosing and treating TB.

Recent Advances Towards Point-Of-Care Applications of Surface-Enhanced Raman Scattering Sensing

The ability to accurately diagnose at the point of care is crucial in many pathologies. However, current standard diagnostic practices can only be performed in specialized health or laboratory settings. To move diagnostic methods from a specialized lab to the point of care many alternate methods have been developed and proposed. Among them surface-enhanced Raman scattering (SERS) sensing offers advantageous features, such as simultaneous detection of multiple biotargets and increased accuracy. Many groups have been working towards the translation of SERS sensing methods from the lab to the point of need. In this mini review, we discuss interesting and recent developments in this effort, focusing on how different sensing mechanism can be used in point-of-care testing applications of SERS.

Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.

Point-of-care diagnostics for infectious diseases: From methods to devices

The current widespread of COVID-19 all over the world, which is caused by SARS-CoV-2 virus, has again emphasized the importance of development of point-of-care (POC) diagnostics for timely prevention and control of the pandemic. Compared with labor- and time-consuming traditional diagnostic methods, POC diagnostics exhibit several advantages such as faster diagnostic speed, better sensitivity and specificity, lower cost, higher efficiency and ability of on-site detection. To achieve POC diagnostics, developing POC detection methods and correlated POC devices is the key and should be given top priority. The fast development of microfluidics, micro electro-mechanical systems (MEMS) technology, nanotechnology and materials science, have benefited the production of a series of portable, miniaturized, low cost and highly integrated POC devices for POC diagnostics of various infectious diseases. In this review, various POC detection methods for the diagnosis of infectious diseases, including electrochemical biosensors, fluorescence biosensors, surface-enhanced Raman scattering (SERS)-based biosensors, colorimetric biosensors, chemiluminiscence biosensors, surface plasmon resonance (SPR)-based biosensors, and magnetic biosensors, were first summarized. Then, recent progresses in the development of POC devices including lab-on-a-chip (LOC) devices, lab-on-a-disc (LOAD) devices, microfluidic paper-based analytical devices (μPADs), lateral flow devices, miniaturized PCR devices, and isothermal nucleic acid amplification (INAA) devices, were systematically discussed. Finally, the challenges and future perspectives for the design and development of POC detection methods and correlated devices were presented. The ultimate goal of this review is to provide new insights and directions for the future development of POC diagnostics for the management of infectious diseases and contribute to the prevention and control of infectious pandemics like COVID-19.

Wavelength-dependent label-free identification of isolated nontuberculous mycobacteria using surface-enhanced Raman spectroscopy

We investigated the effect of Raman excitation wavelengths on the surface-enhanced Raman spectroscopy (SERS)-based identification of isolated nontuberculous mycobacteria (NTM). The SERS spectra with 3 commonly used excitation wavelengths, 532, 638, and 785 nm, were compared across 6 representative NTM species that primarily cause human NTM infections in Korea and the United States; these species were identified. The statistical differences among NTM SERS spectra at each Raman excitation wavelength were verified using 1-way analysis of variance, and the 6 NTM species were identified using principal components-linear discriminant analysis with leave-one-out cross validation. The identification accuracies with aromatic amino acid biomarkers were 99.3%, 91.3%, and 90.7% for 532, 638, and 785 nm, respectively. We believe that the proposed SERS protocol with aromatic amino acid biomarkers at the 532-nm Raman excitation wavelength will enable fast and accurate identification of NTM compared to previous identification methods.

Sensible Functional Linear Discriminant Analysis Effectively Discriminates Enhanced Raman Spectra of Mycobacterium Species

Tuberculosis caused by Mycobacterium tuberculosis complex (MTBC) is one of the major infectious diseases in the world. Identification of MTBC and differential diagnosis of nontuberculous mycobacteria (NTM) species impose challenges because of their taxonomic similarity. This study describes a differential diagnosis method using the surface-enhanced Raman scattering (SERS) measurement of molecules released by Mycobacterium species. Conventional principal component analysis and linear discriminant analysis methods successfully separated the acquired spectrum of MTBC from those of NTM species but failed to distinguish between the spectra of different NTM species. A novel sensible functional linear discriminant analysis (SLDA), projecting the averaged spectrum of a bacterial specie to the subspace orthogonal to the within-species random variation, thereby eliminating its influence in applying linear discriminant analysis, was employed to effectively discriminate not only MTBC but also species of NTM. The successful demonstration of this SERS-SLDA method opens up new opportunities for the rapid differentiation of Mycobacterium species.

Towards a point-of-care SERS sensor for biomedical and agri-food analysis applications: a review of recent advancements

The growing demand for reliable and robust methodology in bio-chemical sensing calls for the continuous advancement of sensor technologies. Over the last two decades, surface-enhanced Raman spectroscopy (SERS) has emerged as one of the most promising analytical techniques for sensitive and trace analysis or detection in biomedical and agri-food applications. SERS overcomes the inherent sensitivity limitation associated with Raman spectroscopy, which provides vibrational "fingerprint" spectra of molecules that makes it unique and versatile among other spectroscopy techniques. This paper comprehensively reviews the recent advancements of SERS for biomedical, food and agricultural applications over the last 6 years, and we envision that, in the near future, some of these platforms have the potential to be translated as a point-of-care and rapid sensor for real-life end-user applications. The merits and limitations of various SERS sensor designs are analysed and discussed based on critical features such as sensitivity, specificity, usability, repeatability and reproducibility. We conclude by highlighting the opportunities and challenges in the field while stressing the technological gaps to be addressed in realizing commercially viable point-of-care SERS sensors for practical biomedical and agri-food technological applications.

Tuberculosis diagnostics: overcoming ancient challenges with modern solutions

Rapid, sensitive, accurate and portable diagnostics are a mainstay of modern medicine. Tuberculosis is a disease that has been with us since time immemorial and, despite the fact that it can be treated and cured, it still remains the world's biggest infectious killer, taking the lives of millions annually. There have been important developments in the diagnostic devices for tuberculosis however, these are often prone to error, expensive, lack the necessary sensitivity or accuracy and, crucially, not sufficiently portable and thus not applicable in the remote, rural areas, where they are most needed. Modern solutions have been emerging in the past decade, seeking to overcome many of the inhibiting issues in this field by utilising recent advances in molecular biology, genetics and sequencing or even completely ‘reinventing the wheel’, by developing novel and unprecedented diagnostic techniques. In this mini review, the issues and challenges arising from the historical methods of diagnosing tuberculosis are discussed, followed by outlaying their particular lack of appropriateness for regions of the world where tuberculosis still remains endemic. Subsequently, more recent developments of new methods and technological advancements as ‘modern weapons’ in the battle to defeat this disease and associated challenges are reviewed, and finally an outlook is presented, highlighting the future of the modern solutions under development, which are envisioned to lay the platform for improvements in delivering timely intervention, reduce immense expense and burden on healthcare systems worldwide, while saving millions of lives and eventually, may enable the eradication of this ancient disease.

Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques

The rapid, highly sensitive, and accurate detection of bacteria is the focus of various fields, especially food safety and public health. Surface-enhanced Raman spectroscopy (SERS), with the advantages of being fast, sensitive, and nondestructive, can be used to directly obtain molecular fingerprint information, as well as for the on-line qualitative analysis of multicomponent samples. It has therefore become an effective technique for bacterial detection. Within this progress report, advances in the detection of bacteria using SERS and other compatible techniques are discussed in order to summarize its development in recent years. First, the enhancement principle and mechanism of SERS technology are briefly overviewed. The second part is devoted to a label-free strategy for the detection of bacterial cells and bacterial metabolites. In this section, important considerations that must be made to improve bacterial SERS signals are discussed. Then, the label-based SERS strategy involves the design strategy of SERS tags, the immunomagnetic separation of SERS tags, and the capture of bacteria from solution and dye-labeled SERS primers. In the third part, several novel SERS compatible technologies and applications in clinical and food safety are introduced. In the final part, the results achieved are summarized and future perspectives are proposed.

Pharmaceutical Application of Tablet Film Coating

Tablet film coating is a common but critical process providing various functionalities to tablets, thereby meeting diverse clinical needs and increasing the value of oral solid dosage forms. Tablet film coating is a technology-driven process and the evolution of coated dosage forms relies on advancements in coating technology, equipment, analytical techniques, and coating materials. Although multiple coating techniques are developed for solvent-based or solvent-free coating processes, each method has advantages and disadvantages that may require continuous technical refinement. In the film coating process, intra- and inter-batch coating uniformity of tablets is critical to ensure the quality of the final product, especially for active film coating containing active pharmaceutical ingredients in the coating layer. In addition to experimental evaluation, computational modeling is also actively pursued to predict the influence of operation parameters on the quality of the final product and optimize process variables of tablet film coating. The concerted efforts of experiments and computational modeling can save time and cost in optimizing the tablet coating process. This review provides a brief overview of tablet film coating technology and modeling approaches with a focus on recent advancements in pharmaceutical applications.

Rapid detection of the aspergillosis biomarker triacetylfusarinine C using interference-enhanced Raman spectroscopy

Triacetylfusarinine C (TAFC) is a siderophore produced by certain fungal species and might serve as a highly useful biomarker for the fast diagnosis of invasive aspergillosis. Due to its renal elimination, the biomarker is found in urine samples of patients suffering from Aspergillus infections. Accordingly, non-invasive diagnosis from this easily obtainable body fluid is possible. Within our contribution, we demonstrate how Raman microspectroscopy enables a sensitive and specific detection of TAFC. We characterized the TAFC iron complex and its iron-free form using conventional and interference-enhanced Raman spectroscopy (IERS) and compared the spectra with the related compound ferrioxamine B, which is produced by bacterial species. Even though IERS only offers a moderate enhancement of the Raman signal, the employment of respective substrates allowed lowering the detection limit to reach the clinically relevant range. The achieved limit of detection using IERS was 0.5 ng of TAFC, which is already well within the clinically relevant range. By using an extraction protocol, we were able to detect 1.4 μg/mL TAFC via IERS from urine within less than 3 h including sample preparation and data analysis. We could further show that TAFC and ferrioxamine B can be clearly distinguished by means of their Raman spectra even in very low concentrations.

Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy

Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria. Graphical abstract.

Present and Future of Surface-Enhanced Raman Scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

"Three-in-One" SERS Adhesive Tape for Rapid Sampling, Release, and Detection of Wound Infectious Pathogens

The traditional colony culture method for detection of pathogens is subjected to the laborious and tedious experimental procedure, which limits its application in point-of-care (POC) testing and quick diagnosis. This work designs an intelligent adhesive tape as a "three-in-one" platform for rapid sampling, photocontrolled release, and surface-enhanced Raman scattering (SERS) detection of pathogens from infected wounds. This tape is constructed by encapsulating densely packed gold nanostars as SERS substrates between two pieces of graphene and modified with a synthetic o-nitrobenzyl derivative molecule to form an artificial biointerface for highly efficient pathogen capture via electrostatic interaction. The captured targets can be conveniently released onto a solid culture medium by UV cleavage of o-nitrobenzyl moiety for pathogen growth and in situ SERS detection. As a proof of strategy, this "three-in-one" platform has been used for detecting the concurrent infection of Pseudomonas aeruginosa and Staphylococcus aureus by pasting the tape on a skin burn wound. The impressive detection performance with an analytical time of only several hours for these pathogens at an early growth stage demonstrates its great potential as a POC testing device for health care.

Microfluidics and Surface-Enhanced Raman Spectroscopy: A Perfect Match for New Analytical Tools

In this perspective article, we emphasize the combination of Surface-Enhanced Raman Spectroscopy (SERS) and Microfluidic devices. SERS approaches have been widely studied and used for multiple applications including trace molecules detection, in situ analysis of biological samples and monitoring or, all of them with good results, however still with limitations of the technique, for example regarding with improved precision and reproducibility. These implications can be overcome by microfluidic approaches. The resulting coupling Microfluidics - SERS (MF-SERS) has recently gained increasing attention by creating thundering opportunities for the analytical field. For this purpose, we introduce some of the strategies developed to implement SERS within microfluidic reactor along with a brief overview of the most recent MF-SERS applications for biology, health and environmental concerns. Eventually, we will discuss future research opportunities of such systems.

Plasmonic-based platforms for diagnosis of infectious diseases at the point-of-care

Infectious diseases such as HIV-1/AIDS, tuberculosis (TB), hepatitis B (HBV), and malaria still exert a tremendous health burden on the developing world, requiring rapid, simple and inexpensive diagnostics for on-site diagnosis and treatment monitoring. However, traditional diagnostic methods such as nucleic acid tests (NATs) and enzyme linked immunosorbent assays (ELISA) cannot be readily implemented in point-of-care (POC) settings. Recently, plasmonic-based biosensors have emerged, offering an attractive solution to manage infectious diseases in the developing world since they can achieve rapid, real-time and label-free detection of various pathogenic biomarkers. Via the principle of plasmonic-based optical detection, a variety of biosensing technologies such as surface plasmon resonance (SPR), localized surface plasmon resonance (LSPR), colorimetric plasmonic assays, and surface enhanced Raman spectroscopy (SERS) have emerged for early diagnosis of HIV-1, TB, HBV and malaria. Similarly, plasmonic-based colorimetric assays have also been developed with the capability of multiplexing and cellphone integration, which is well suited for POC testing in the developing world. Herein, we present a comprehensive review on recent advances in surface chemistry, substrate fabrication, and microfluidic integration for the development of plasmonic-based biosensors, aiming at rapid management of infectious diseases at the POC, and thus improving global health.

Laser trapping of Ag nanoparticles to enhance Raman spectroscopy in aqueous media

Laser trapping (LT) of metallic nanoparticles (NPs) is an approach that has the potential to enhance Raman spectroscopy in aqueous media. In this paper, we report the LT of multiple 60-nm Ag NPs using a tightly focused 1064-nm Gaussian laser beam. The dynamic process (trapping and escaping) of the individual Ag NPs were recorded using a charge coupled device (CCD) camera in backscattering illumination mode. We found that up to four Ag NPs could be simultaneously trapped; however, they were unstable in the laser trap due to Brownian motion and NP-NP interactions. However, after mixing Ag NPs with Bacillus subtilis, more of the Ag NPs could be trapped together with the bacteria. Furthermore, a 532-nm solid-state laser beam was used to activate Raman scattering of the Ag NPs + Bacillus subtilis sample. Based on repetitive measurements, the Raman spectra of the Ag NPs + Bacillus subtilis sample were enhanced and the results were consistent. Our work suggests that LT of metallic NPs can be used to enhance Raman spectroscopy in aqueous media. We believe that the enhanced Raman spectroscopy will be useful for real-time biological assays.

Development of a PAT tool for monitoring the Wurster coater performance

Real-time process analytical technology (PAT) is proposed as an effective approach for monitoring the performance of a Wurster coater. The coater was used for coating of 0.78 mm pharmaceutical pellets. The coating solution consisted of Hydroxypropyl methylcellulose/Poly ethylene glycol. During the coating process, small amounts of pellets (∼2 g) were sampled at 10 min. intervals and the pressure fluctuations were recorded at the same time. The signals were analyzed using the wavelet transform (WT) and decomposed into different sub-signals. Principal component analysis (PCA) was employed to the energies of these sub-signals, whose outliers were eliminated using the Mahalanobis distance method. The reference coating thickness data were obtained via spectrophotometry during the coating process. The partial least squares (PLS) regression was incorporated with the PCA for the development of a model for prediction of the coating thickness. The PLS regression revealed that the pressure fluctuations can be used to evaluate the thickness with a good precision. This study demonstrated the applicability of pressure fluctuations for the prediction of the coating thickness. This method can be regarded as a new robust, fast and non-intrusive PAT approach for monitoring the coating process which can be easily used by engineers and practitioners.

Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) has recently gained increasing attention for the detection of trace quantities of biomolecules due to its excellent molecular specificity, ultrasensitivity, and quantitative multiplex ability. Specific single or multiple biomarkers in complex biological environments generate strong and distinct SERS spectral signals when they are in the vicinity of optically active nanoparticles (NPs). When multivariate chemometrics are applied to decipher underlying biomarker patterns, SERS provides qualitative and quantitative information on the inherent biochemical composition and properties that may be indicative of healthy or diseased states. Moreover, SERS allows for differentiation among many closely-related causative agents of diseases exhibiting similar symptoms to guide early prescription of appropriate, targeted and individualised therapeutics. This review provides an overview of recent progress made by the application of SERS in the diagnosis of cancers, microbial and respiratory infections. It is envisaged that recent technology development will help realise full benefits of SERS to gain deeper insights into the pathological pathways for various diseases at the molecular level.

Simultaneous quantification of multiple bacterial metabolites using surface-enhanced Raman scattering

We combine liquid–liquid extraction, SERS detection and partial least squares analysis for simultaneous quantification of bacterial metabolites in E. coli supernatant.

Identification of mycolic acid forms using surface-enhanced Raman scattering as a fast detection method for tuberculosis

Background

Tuberculosis (TB) is the ninth leading cause of death worldwide and the leading cause from a single infectious agent, based on the WHO Global Tuberculosis Report in 2017. TB causes massive health care burdens in many parts of the world, specifically in the resource constrained developing world. Most deaths from TB could be prevented with cost effective early diagnosis and appropriate treatment.

Purpose

Conventional TB detection methods are either too slow as it takes a few weeks for diagnosis or they lack the specificity and accuracy. Thus the objective of this study was to develop a fast and efficient detection for TB using surface enhanced Raman scattering (SERS) technique.

Methods

SERS spectra for different forms of mycolic acids (MAs) that are both synthetic origin and actual extracts from the mycobacteria species were obtained by label-free direct detection mode. Similarly, we collected SERS spectra for γ-irradiated whole bacteria (WB). Measurements were done using silver (Ag) coated silicon nanopillar (Ag SNP) as SERS substrate.

Results

We report the SERS based detection of MA, which is a biomarker for mycobacteria species including Mycobacterium tuberculosis. For the first time, we also establish the SERS spectral characterization of the three major forms of MA - αMA, methoxy-MA, and keto-MA, in bacterial extracts and also in γ-irradiated WB. We validated our findings by mass spectrometry. SERS detection of these three forms of MA could be useful in differentiating pathogenic and nonpathogenic Mycobacterium spp.

Conclusions

We have demonstrated the direct detection of three major forms of MA - αMA, methoxy-MA, and keto-MA, in two different types of MA extracts from MTB bacteria, namely delipidated MA and undelipidated MA and finally in γ-irradiated WB. In the near future, this study could pave the way for a fast and efficient detection method for TB, which is of high clinical significance.

Detection and Characterization of Antibiotic-Resistant Bacteria Using Surface-Enhanced Raman Spectroscopy

This mini-review summarizes the most recent progress concerning the use of surface-enhanced Raman spectroscopy (SERS) for the detection and characterization of antibiotic-resistant bacteria. We first discussed the design and synthesis of various types of nanomaterials that can be used as the SERS-active substrates for biosensing trace levels of antibiotic-resistant bacteria. We then reviewed the tandem-SERS strategy of integrating a separation element/platform with SERS sensing to achieve the detection of antibiotic-resistant bacteria in the environmental, agri-food, and clinical samples. Finally, we demonstrated the application of using SERS to investigate bacterial antibiotic resistance and susceptibility as well as the working mechanism of antibiotics based on spectral fingerprinting of the whole cells.

Analysis of Biomolecules Based on the Surface Enhanced Raman Spectroscopy

Analyzing biomolecules is essential for disease diagnostics, food safety inspection, environmental monitoring and pharmaceutical development. Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for detecting biomolecules due to its high sensitivity, rapidness and specificity in identifying molecular structures. This review focuses on the SERS analysis of biomolecules originated from humans, animals, plants and microorganisms, combined with nanomaterials as SERS substrates and nanotags. Recent advances in SERS detection of target molecules were summarized with different detection strategies including label-free and label-mediated types. This comprehensive and critical summary of SERS analysis of biomolecules might help researchers from different scientific backgrounds spark new ideas and proposals.

Interference-Enhanced Raman Spectroscopy as a Promising Tool for the Detection of Biomolecules on Raman-Compatible Surfaces

Raman spectroscopy in combination with appropriate sample preparation strategies, for example, enrichment of bacteria on metal surfaces, has been proven to be a promising approach for rapidly diagnosing infectious diseases. Unfortunately, the fabrication of the required chip substrates is usually very challenging due to the lack of feasible instruments that can be used for quality control in the surface modification process. The intrinsically weak Raman signal of the biomolecules, employed for the enrichment of the micro-organisms on the chip surface, does not allow for monitoring of the successful immobilization by means of a Raman spectroscopic approach. Within this contribution, we demonstrate how a simple modification of a plain aluminum surface enables enhancement (or a decrease, if desired) of the Raman signal of molecules deposited on that surface. The manipulation of the Raman signal strength is achieved via exploiting interference effects that occur, if the highly reflective aluminum surface is modified with thin layers of transparent dielectrics like aluminum oxide. The thicknesses of these layers were determined by theoretical considerations and calculations. For the first time, it is shown that the interference effects can be used for the detection of biomolecules as well by investigating the siderophore ferrioxamine B. The observed degree of enhancement was approximately 1 order of magnitude. Moreover, the employed aluminum/aluminum oxide layers have been thoroughly characterized using atomic force and scanning electron microscopy as well as X-ray reflectometry and UV-Vis measurements.

Facing Challenges in Real-Life Application of Surface-Enhanced Raman Scattering: Design and Nanofabrication of Surface-Enhanced Raman Scattering Substrates for Rapid Field Test of Food Contaminants

Surface-enhanced Raman scattering (SERS) is capable of detecting a single molecule with high specificity and has become a promising technique for rapid chemical analysis of agricultural products and foods. With a deeper understanding of the SERS effect and advances in nanofabrication technology, SERS is now on the edge of going out of the laboratory and becoming a sophisticated analytical tool to fulfill various real-world tasks. This review focuses on the challenges that SERS has met in this progress, such as how to obtain a reliable SERS signal, improve the sensitivity and specificity in a complex sample matrix, develop simple and user-friendly practical sensing approach, reduce the running cost, etc. This review highlights the new thoughts on design and nanofabrication of SERS-active substrates for solving these challenges and introduces the recent advances of SERS applications in this area. We hope that our discussion will encourage more researches to address these challenges and eventually help to bring SERS technology out of the laboratory.