Rapid screening for ricin toxin on letter papers using surface enhanced Raman spectroscopy

A Glycoprotein-Based Surface-Enhanced Raman Spectroscopy-Lateral Flow Assay Method for Abrin and Ricin Detection

Abrin and ricin, both type II ribosome-inactivating proteins, are toxins of significant concern and are under international restriction by the Chemical Weapons Convention and the Biological and Toxin Weapons Convention. The development of a rapid and sensitive detection method for these toxins is of the utmost importance for the first emergency response. Emerging rapid detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and lateral flow assay (LFA), have garnered attention due to their high sensitivity, good selectivity, ease of operation, low cost, and disposability. In this work, we generated stable and high-affinity nanotags, via an efficient freezing method, to serve as the capture module for SERS-LFA. We then constructed a sandwich-style lateral flow test strip using a pair of glycoproteins, asialofetuin and concanavalin A, as the core affinity recognition molecules, capable of trace measurement for both abrin and ricin. The limit of detection for abrin and ricin was 0.1 and 0.3 ng/mL, respectively. This method was applied to analyze eight spiked white powder samples, one juice sample, and three actual botanic samples, aligning well with cytotoxicity assay outcomes. It demonstrated good inter-batch and intra-batch reproducibility among the test strips, and the detection could be completed within 15 min, indicating the suitability of this SERS-LFA method for the on-site rapid detection of abrin and ricin toxins.

Detection with NO Modification: (N═O)-Au Interactions for Instantaneous Label-Free Detection of N-Nitrosodiphenylamine

Increasing concerns have been raised about dangerous, yet nearly undetectable levels of nitrosamines in foods, medications, and drinking water. Their ubiquitous presence and carcinogenicity necessitates a method of sensitive and selective detection of these potent toxins. While the detection of two major nitrosamines─N-nitrosodimethylamine and N-nitrosodiethylamine─has seen success, low detection limits are scarcer for the other members of this class. One member, N-nitrosodiphenylamine (NDPhA), has had little progress not only in its detection in low quantities but also in its detection at all. NDPhA has unique difficulty in its identification due to its aromaticity, making it far more problematic to distinguish in the common GC-MS or LC-MS/MS methods used for nitrosamine sensing. Despite this detection barrier, it has been listed among the top 6 carcinogenic nitrosamines by the Food and Drug Administration as of 2023. Due to its evasive nature, a unique methodology must be applied to facilitate its sensitive identification. Herein, we describe the use of surface-enhanced Raman spectroscopy for the first account of liquid-phase detection of NDPhA using cysteamine-functionalized gold nanostars and a portable Raman spectrometer. Our methodology requires no chemical modification to the nitrosated structure as well as the usage of two well-understood biocompatible materials: cysteamine and gold nanoparticles.

Performance of Classification Models of Toxins Based on Raman Spectroscopy Using Machine Learning Algorithms

Rapid and accurate detection of protein toxins is crucial for public health. The Raman spectra of several protein toxins, such as abrin, ricin, staphylococcal enterotoxin B (SEB), and bungarotoxin (BGT), have been studied. Multivariate scattering correction (MSC), Savitzky-Golay smoothing (SG), and wavelet transform methods (WT) were applied to preprocess Raman spectra. A principal component analysis (PCA) was used to extract spectral features, and the PCA score plots clustered four toxins with two other proteins. The k-means clustering results show that the spectra processed with MSC and MSC-SG methods have the best classification performance. Then, the two data types were classified using partial least squares discriminant analysis (PLS-DA) with an accuracy of 100%. The prediction results of the PCA and PLS-DA and the partial least squares regression model (PLSR) perform well for the fingerprint region spectra. The PLSR model demonstrates excellent classification and regression ability (accuracy = 100%, Rcv = 0.776). Four toxins were correctly classified with interference from two proteins. Classification models based on spectral feature extraction were established. This strategy shows excellent potential in toxin detection and public health protection. These models provide alternative paths for the development of rapid detection devices.

Rapid and ultrasensitive detection of food contaminants using surface-enhanced Raman spectroscopy-based methods

With the globalization of food and its complicated networking system, a wide range of food contaminants is introduced into the food system which may happen accidentally, intentionally, or naturally. This situation has made food safety a critical global concern nowadays and urged the need for effective technologies capable of dealing with the detection of food contaminants as efficiently as possible. Hence, Surface-enhanced Raman spectroscopy (SERS) has been taken as one of the primary choices for this case, due to its extremely high sensitivity, rapidity, and fingerprinting interpretation capabilities which account for its competency to detect a molecule up to a single level. Here in this paper, we present a comprehensive review of various SERS-based novel approaches applied for direct and indirect detection of single and multiple chemical and microbial contaminants in food, food products as well as water. The aim of this paper is to arouse the interest of researchers by addressing recent SERS-based, novel achievements and developments related to the investigation of hazardous chemical and microbial contaminants in edible foods and water. The target chemical and microbial contaminants are antibiotics, pesticides, food adulterants, Toxins, bacteria, and viruses. In this paper, different aspects of SERS-based reports have been addressed including synthesis and use of various forms of SERS nanostructures for the detection of a specific analyte, the coupling of SERS with other analytical tools such as chromatographic methods, combining analyte capture and recognition strategies such as molecularly imprinted polymers and aptasensor as well as using multivariate statistical analyses such as principal component analysis (PCA)to distinguish between results. In addition, we also report some strengths and limitations of SERS as well as future viewpoints concerning its application in food safety.

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.

Biological Toxins as the Potential Tools for Bioterrorism

Biological toxins are a heterogeneous group produced by living organisms. One dictionary defines them as "Chemicals produced by living organisms that have toxic properties for another organism". Toxins are very attractive to terrorists for use in acts of bioterrorism. The first reason is that many biological toxins can be obtained very easily. Simple bacterial culturing systems and extraction equipment dedicated to plant toxins are cheap and easily available, and can even be constructed at home. Many toxins affect the nervous systems of mammals by interfering with the transmission of nerve impulses, which gives them their high potential in bioterrorist attacks. Others are responsible for blockage of main cellular metabolism, causing cellular death. Moreover, most toxins act very quickly and are lethal in low doses (LD50 < 25 mg/kg), which are very often lower than chemical warfare agents. For these reasons we decided to prepare this review paper which main aim is to present the high potential of biological toxins as factors of bioterrorism describing the general characteristics, mechanisms of action and treatment of most potent biological toxins. In this paper we focused on six most danger toxins: botulinum toxin, staphylococcal enterotoxins, Clostridium perfringens toxins, ricin, abrin and T-2 toxin. We hope that this paper will help in understanding the problem of availability and potential of biological toxins.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.