博文
SERS technology for metabolite-related biomarkers
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Volume 198, May 2026, 118735
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a
Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China
b
Key Laboratory of Emergency and Trauma, Ministry of Education, Key Laboratory of Haikou Trauma, Key Laboratory of Hainan Trauma and Disaster Rescue, The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, China
c
Engineering Research Center for Hainan Bio-Smart Materials and Bio-Medical Devices, Key Laboratory of Hainan Functional Materials and Molecular Imaging, College of Emergency and Trauma, Hainan Medical University, Haikou, 571199, China
Received 7 May 2025, Revised 17 November 2025, Accepted 9 February 2026, Available online 12 February 2026, Version of Record 17 February 2026.
https://doi.org/10.1016/j.trac.2026.118735
Highlights•SERS enables ultrasensitive, non-destructive detection of metabolic biomarkers.
•It overcomes precision and range limits of conventional diagnostics.
•Nanoprobes enable rapid disease identification and intervention.
Abstract
Metabolite-related biomarkers play crucial roles in the medical field, which can be used as diagnostic tools for disease diagnosis and therapeutic evaluation, even the mechanisms of diseases. Nevertheless, conventional diagnostic techniques might face restrictions regarding the range of metabolites they can detect and the precision of their measurements. Moreover, the handling, preparation, and preservation of specimens can greatly influence the analytical outcomes. The emergence of surface-enhanced Raman scattering (SERS) technology offers new advantages for the detection of metabolomic markers. Known for its high sensitivity and non-destructive detection methods, SERS uses metal nanoparticles to significantly amplify spectral signals, enabling the detection of low-abundance biomolecules. This review discusses the application of SERS technology in the design and development of nanoprobes for biological analysis and detection at various dimensions and levels of disease. These innovations are intended to overcome the constraints of conventional diagnostic techniques, facilitating the prompt identification and intervention for illnesses.
Surface-enhanced Raman scattering (SERS)
Metabolite-related biomarkers
Signal amplification
Biosensing
Disease diagnosis
1. Introduction
Cell metabolism involves a series of complex biological reactions, including pathways for cell growth and reproduction, as well as the maintenance of the cellular microenvironment. These aspects are interconnected and interdependent, together forming the cellular metabolic network. This network is regulated by intricate mechanisms that ensure cells can effectively adapt to environmental changes and carry out their biological functions. Key metabolite-related biomarkers involved in the occurrence and progression of diseases can serve as biological biomarkers for the physiological and pathological processes, allowing for accurate assessment of disease onset and progression [1]. The concentrations of metabolite-related biomarkers often change before abnormalities appear in tissue structure and function. Therefore, these metabolite-related biomarkers can indicate changes in structural, physiological, genetic, or biochemical parameters, providing insight into the presence, severity, or progression of diseases [2]. Metabolite-related biomarkers, detectable in body fluids or tissues, are substances whose production, release, or concentration changes are either directly linked to cellular metabolic processes or indirectly regulated by metabolic reprogramming. They encompass small molecule metabolites directly involved in metabolic pathways, as well as proteins, circulating tumor cells (CTCs), and circulating tumor DNA (ctDNA) exhibiting abnormal expression or secretion due to altered metabolism. These markers provide real-time insights into disease or tumor onset, progression, and prognosis, offering significant value for early diagnosis, therapeutic monitoring, and precision medicine. Generally, the abnormal expression of biomarkers may occur earlier than findings from clinical imaging, highlighting their potential for precise diagnosis in the field of disease diagnostics. By detecting metabolite-related biomarkers, we can gain insights into metabolic processes, allowing for the assessment of which may lead to better diagnosis, prognosis, drug screening and treatment.
The discovery of metabolite-related biomarkers primarily relies on techniques such as metabolomics, high-throughput analysis, bioinformatics analysis and so on. Metabolomics involves studying the entirety of metabolites within a biological organism and their changes, allowing for a broad screening of metabolic products in the organism. It enables comparative analysis of dysfunction of metabolic pathways and metabolites under different biological conditions or organisms, leading to the identification of new metabolite-related biomarkers [3]. High-throughput analytical techniques can quickly and accurately measure metabolite levels in a large number of samples. Utilizing technologies like mass spectrometry and nuclear magnetic resonance, multiple metabolites can be detected simultaneously, facilitating the discovery of metabolite biomarkers. Bioinformatics analysis integrates and analyzes data from genomics, transcriptomics, and proteomics to reveal key metabolites in metabolic pathways, further uncovering their functions and roles within living organism, thus providing insights for the discovery of metabolite-related biomarkers.
The changes of disease metabolites can reflect alterations in structural, physiological, genetic, or biochemical parameters, helping to accurately assess the presence and severity of diseases, thus demonstrating diagnostic potential [4]. Over the past decades, a number of techniques have been developed for the measurement and analysis of metabolite-related biomarkers. The mass spectrometry and nuclear magnetic resonance provide high sensitivity and molecular specificity for proteomic and metabolomic profiling, while flow cytometry and cytological testing allow cell-level characterization of disease states [[5], [6], [7]]. The nucleic acid amplification and sequencing approaches achieve the highly sensitive detection of genetic alternations and regulatory molecules [8]. Simultaneously, biosensing has emerged as a powerful strategy that converts biological recognition events into measurable signals through optical [9], electrochemical [10], piezoelectric [11], or solid-state transduction methods [12], which offer high sensitivity for target analytes. The application of these diverse techniques has greatly improved disease diagnosis, prognosis, and therapeutic monitoring. However, each method has its own drawbacks. Mass spectrometry and sequencing require complex sample preparation; imaging methods need special instrumentation systems and high cost. Moreover, the biosensors may be interfered from the complex matrix, unstable signal and reproducibility in real clinical applications. There limitations require the need for complementary and innovative approaches with high sensitivity and specificity, rapid response for real-time measurement in complex biological samples [13]. The application of these technologies facilitates more accurate disease diagnosis in clinical settings, allows for better monitoring of disease progression, and enables the development of targeted treatment plans. However, these traditional technologies still face some challenges in terms of sensitivity, stability, and complexity of operation. Moreover, disease biomarkers usually present in blood or tissue at very low concentrations, especially in the early stages, which complicates accurate detections. Hence, there is a pressing requirement for the creation of swift and highly responsive biomarker detection methods to enable early disease identification and to evaluate the prognosis effectively.
Surface-enhanced Raman scattering (SERS) is a highly sensitive spectroscopic technique that relies on plasmonic effects generated at the surfaces of metallic nanostructures (e.g., gold, silver) to dramatically enhance the Raman scattering signal from target molecules. When laser light is incident on the metal nanoparticles, it excites localized surface plasmon resonance, leading to a substantial enhancement of the electromagnetic field at the metal surface [[14], [15], [16]]. This enhanced electromagnetic field significantly boosts the Raman scattering signal of molecules adsorbed on the metal surface. Compared to fluorescence imaging, SERS offers several advantages: (1) high sensitivity: the localized surface plasmon resonance on noble metal surfaces can dramatically enhance Raman signals, achieving enhancement factors generally exceeding 109-1011, enabling detection at the single-molecule level; (2) high specificity: the molecular vibrational and rotational information presented in the SERS spectrum in a “fingerprint” form reveals molecular structures, allowing for the differentiation of target metabolites from other compounds; (3) multiplex detection capability: the narrow peak widths of SERS spectral peaks (with half-widths generally less than 1 nm) are a fraction of the widths of fluorescence spectral peaks, facilitating the detection of multiple components to the greatest extent possible, which allows for simultaneous detection of various targets at the same excitation wavelength.
In the practical application, the sensors’ performances are often limited by matrix effects (protein, lipids, electrolytes), batch-to-batch variability and calibration drift, which affect all the biosensors [[17], [18], [19]]. Electrochemical biosensors exhibit advantages of low-cost integration and continuous operation but suffer from the surface pollution and limited multiplex capability [[20], [21], [22]]. Label-free SPR provides real-time affinity signals with stable quantification, while the temperature control adds the complexity [23]. Although fluorescent/chemiluminescent assays exhibit high analytical sensitivity, the photobleaching and spectral cross-talk are the major obstacles for the complex samples [24,25]. In contrast, SERS methods realize the multiplex detection and label-free specificity due to the narrow spectral fingerprints, however, the substrate uniformity and standardized readouts are still the challenges for accurate quantitation.
In this review, we adopt a two-tier terminology to avoid ambiguity. First, we define metabolomic biomarkers as endogenous or exogenous small-molecule metabolites (generally <1–1.5 kDa) that serve as substrates, intermediates, or products of biochemical pathways. Examples include amino acids, sugars, nucleotides, organic acids, lipids, and xenobiotics. Second, we introduce the broader concept of metabolite-related biomarkers, which encompasses proteins, nucleic acids, and cells or vesicles that are not metabolites in the strict biochemical sense but are functionally or mechanistically linked to metabolism. For instance, enzymes and cytokines regulate metabolic fluxes, oncogenic DNA mutations reprogram metabolic pathways, and circulating tumor cells reflect metabolic plasticity in the tumor microenvironment. We include these entities in our review because SERS has been widely applied to their detection, and because they provide complementary information to metabolomic readouts. Throughout this article, we consistently distinguish between metabolomic biomarkers (small molecules) and metabolite-related biomarkers (macromolecules or cells linked to metabolism), thereby clarifying scope and preventing conflation. We focus on the latest advancements of SERS probes in bioanalytical research. To better comprehend the advantages of SERS technology in detecting bio-metabolites, we focus the comparisons on biosensor modalities rather than only laboratory platforms. Thus, we compare SERS with these modalities based on analytical performance, matrix tolerance, and portability. Furthermore, we also highlight the unique advantages in spectral fingerprint, barcodes, multiplex detection, and surgery guidance while point out the current drawbacks including substrate reproducibility, quantitative calibration, and clinical application. We then introduce the benefits of SERS detection technology. With the evolution of nanotechnology and the refinement of SERS probes, a variety of probes have been designed and developed for detecting different bio-metabolites. Finally, we summarize the future challenges and prospects of SERS probes in the bioanalytical research of bio-metabolites. The purpose of this analysis is to deepen the comprehension of SERS probes in detecting bioanalytes and facilitating future clinical testing applications.
https://blog.sciencenet.cn/blog-2438823-1522755.html
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