Development of an isotope dilution mass spectrometry assay for the quantification of insulin based on signature peptide analysis.

An isotope dilution mass spectrometry (IDMS) method that involves peptide-based protein analysis was developed to accurately quantify insulin. In this study, a signature peptide (GFFYTPK) obtained from tryptic digestion of insulin was selected as a surrogate for insulin. Then, the optimal conditions for signature peptide analysis through mass spectrometry detection and enzymatic digestion were determined. The analytical performance of this method was assessed and validated using porcine insulin-certified reference material. The linear range of the insulin calibration curve ranged from 0.05 ~ 2 mass ratios, with recoveries ranging from 96.15 to approximately 101.15%. The limit of detection was 0.19 ng/mL, and the limit of quantification was 0.63 ng/mL. The quantitative results corresponded well with a certified value that was obtained from measuring a porcine insulin reference material with amino acid-based IDMS. In addition, the target peptide GFFYTPK can be found in other species of insulin. This method was also applied for the quantification of human insulin-certified reference material. Finally, we applied the method to quantify the concentrations of simulated serum insulin. These findings suggested that this signature peptide-based IDMS approach can accurately quantify insulin levels, can assign a certified value to insulin reference materials, and has the potential to quantify serum insulin with traceable measurements.

The Development of an Isotope Dilution Mass Spectrometry Method for Interleukin-6 Quantification.

Inflammatory responses and tumor developments are closely related, with interleukin-6 (IL-6) playing important roles in both processes. IL-6 has been extensively identified as a potential tumor biomarker. This study developed an isotope dilution mass spectrometry (IDMS) method for quantifying IL-6 based on signature peptides. These peptides were screened by excluding those with missed cleavage or post-translational modification. The method's accuracy was verified using amino acid-based IDMS, in which purified IL-6 protein samples were quantified after hydrolyzing them into amino acids, and no significant difference was observed (p-value < 0.05). The method demonstrated good linearity and sensitivity upon testing. The specificity and matrix effect of the method were verified, and a precision study showed that the coefficient of variation was less than 5% for both the intra-day and inter-day tests. Compared to immunoassays, this method offers distinct advantages, such as the facilitation of multi-target analysis. Furthermore, the peptides used in this study are much more convenient for storage and operation than the antibodies or purified proteins typically used in immunoassays.

Traceability of Microplastic Fragments from Waste Plastic Express Packages Using Near-Infrared Spectroscopy Combined with Chemometrics.

The pollution from waste plastic express packages (WPEPs), especially microplastic (MP) fragments, caused by the blowout development of the express delivery industry has attracted widespread attention. On account of the variety of additives, strong complexity, and high diversity of plastic express packages (PEPs), the multi-class classification of WPEPs is a typical large-class-number classification (LCNC). The traceability and identification of microplastic fragments from WPEPs is very challenging. An effective chemometric method for large-class-number classification would be very beneficial for the comprehensive treatment of WPEP pollution through the recycling and reuse of waste plastic express packages, including microplastic fragments and plastic debris. Rather than using the traditional one-against-one (OAO) and one-against-all (OAA) dichotomies, an exhaustive and parallel half-against-half (EPHAH) decomposition, which overcomes the defects of the OAO's classifier learning limitations and the OAA's data proportion imbalance, is proposed for feature selection. EPHAH analysis, combined with partial least squares discriminant analysis (PLS-DA) for large-class-number classification, was performed on 750 microplastic fragments of polyethylene WPEPs from 10 major courier companies using near-infrared (NIR) spectroscopy. After the removal of abnormal samples through robust principal component analysis (RPCA), the root mean square error of cross-validation (RMSECV) value for the model was reduced to 0.01, which was 21.5% lower than that including the abnormal samples. The best models of PLS-DA were obtained using SNV combined with SG-17 smoothing and 2D (SNV+SG-17+2D); the latent variables (LVs), the error rates of Monte Carlo cross-validation (ERMCCVs), and the final classification accuracies were 6.35, 0.155, and 88.67% for OAO-PLSDA; 5.37, 0.103, and 87.33% for OAA-PLSDA; and 3.12, 0.054, and 96.00% for EPHAH-PLSDA. The results showed that the EPHAH strategy can completely learn the complex LCNC decision boundaries for 10 classes, effectively break the tie problem, and greatly improve the voting resolution, thereby demonstrating significant superiority to both the OAO and OAA strategies in terms of classification accuracy. Meanwhile, PLS-DA further maximized the covariance and data interpretation abilities between the potential variables and categories of microplastic debris, thereby establishing an ideal performance identification model with a recognition rate of 96.00%.

Dual Gene Detection of H5N1 Avian Influenza Virus Based on Dual RT-RPA.

The H5N1 avian influenza virus seriously affects the health of poultry and humans. Once infected, the mortality rate is very high. Therefore, accurate and timely detection of the H5N1 avian influenza virus is beneficial for controlling its spread. This article establishes a dual gene detection method based on dual RPA for simultaneously detecting the HA and M2 genes of H5N1 avian influenza virus, for the detection of H5N1 avian influenza virus. Design specific primers for the conserved regions of the HA and M2 genes. The sensitivity of the dual RT-RPA detection method for HA and M2 genes is 1 × 10-7 ng/µL. The optimal primer ratio is 1:1, the optimal reaction temperature is 40 °C, and the optimal reaction time is 20 min. Dual RT-RPA was used to detect 72 samples, and compared with RT-qPCR detection, the Kappa value was 1 (p value < 0.05), and the clinical sample detection sensitivity and specificity were both 100%. The dual RT-RPA method is used for the first time to simultaneously detect two genes of the H5N1 avian influenza virus. As an accurate and convenient diagnostic tool, it can be used to diagnose the H5N1 avian influenza virus.

An Immunochromatographic Test Strip for Rapid Quantitative Control of Monoclonal Antibodies against Programmed Cell Death Protein 1.

Cancer is one of the major public health challenges in the world, which is characterized by rapid progression and high mortality. Immunotherapy, represented by PD-1 monoclonal antibody, has significantly improved the efficacy of malignant tumors and has become one of the most popular immunotherapy methods at present. Therefore, there is an increasing demand for novel detection methods for PD-1 monoclonal antibodies. The aim of this work was to establish a rapid, simple, and sensitive immunochromatographic test strip (ICTS) based on the AuNPs enlargement for both visual and instrumental detection of the PD-1 monoclonal antibody concentration. The mixed solution of NH2OH·HCl and HAuCl4 was used as an enhancement solution to lower the detection limit and achieve higher sensitivity. A test strip reader was used to construct a visualized quantitative detection standard curve for the PD-1 monoclonal antibody concentration. The LOD was 1.58 ng/mL through a triple signal-to-noise ratio. The detection time was within 10 min. The constructed test strips can rapidly, accurately, and efficiently detect the concentration of PD-1 monoclonal antibody in real samples.

Prokaryotic Argonaute Proteins: A New Frontier in Point-of-Care Viral Diagnostics.

The recent pandemic of SARS-CoV-2 has underscored the critical need for rapid and precise viral detection technologies. Point-of-care (POC) technologies, which offer immediate and accurate testing at or near the site of patient care, have become a cornerstone of modern medicine. Prokaryotic Argonaute proteins (pAgo), proficient in recognizing target RNA or DNA with complementary sequences, have emerged as potential game-changers. pAgo present several advantages over the currently popular CRISPR/Cas systems-based POC diagnostics, including the absence of a PAM sequence requirement, the use of shorter nucleic acid molecules as guides, and a smaller protein size. This review provides a comprehensive overview of pAgo protein detection platforms and critically assesses their potential in the field of viral POC diagnostics. The objective is to catalyze further research and innovation in pAgo nucleic acid detection and diagnostics, ultimately facilitating the creation of enhanced diagnostic tools for clinic viral infections in POC settings.

Advances in Detection Techniques for the H5N1 Avian Influenza Virus.

Avian influenza is caused by avian influenza virus infection; the H5N1 avian influenza virus is a highly pathogenic subtype, affecting poultry and human health. Since the discovery of the highly pathogenic subtype of the H5N1 avian influenza virus, it has caused enormous losses to the poultry farming industry. It was recently found that the H5N1 avian influenza virus tends to spread among mammals. Therefore, early rapid detection methods are highly significant for effectively preventing the spread of H5N1. This paper discusses the detection technologies used in the detection of the H5N1 avian influenza virus, including serological detection technology, immunological detection technology, molecular biology detection technology, genetic detection technology, and biosensors. Comparisons of these detection technologies were analyzed, aiming to provide some recommendations for the detection of the H5N1 avian influenza virus.

Protected Geographical Indication Discrimination of Zhejiang and Non-Zhejiang Ophiopogonis japonicus by Near-Infrared (NIR) Spectroscopy Combined with Chemometrics: The Influence of Different Stoichiometric and Spectrogram Pretreatment Methods.

This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas ('non-Zhejiang'). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R2 reaching 0.9979, while that of the second derivative was the lowest with an R2 of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

Surface engineered bimetallic gold/silver nanoclusters for in situ imaging of mercury ions in living organisms.

Chemical sensing for the sensitive and reliable detection of mercury(II) ions (Hg2+) is of great importance in environmental protection, food safety, and biomedical applications. Due to the bio-enrichment property of Hg2+ in organisms, it is particularly meaningful to develop an effective tool that can in situ and rapidly monitor the level of Hg2+ in living organisms. In this work, we report ligand functionalized gold-silver bimetallic nanoclusters with bright red fluorescence as intracellular probes for imaging Hg2+ in living cells and zebrafish. The bimetallic nanoclusters of DTT-GSH@Au/AgNCs (DG-Au/AgNCs) with strong fluorescence that benefited from the synergistic effect of Au and Ag atoms were obtained through a one-pot synthesis method, incorporating glutathione (GSH) and dithiothreitol (DTT) as the reducers and functionalized ligands. Attractively, the bright red fluorescence of DG-Au/AgNCs could be rapidly and selectively quenched by Hg2+ within 1 min with a very low detection limit of 1.01 nM. Additionally, DG-Au/AgNCs had a great advantage in the detection of Hg2+ in living cells and zebrafish owing to its notably strong red fluorescence at 665 nm, which could avoid effectively auto-fluorescence interference from the organism. Such easily prepared bimetallic fluorescent nanoclusters would be expected to provide a noninvasive and sensitive approach in the detection of heavy metals in situ for environmental protection.

Low-Cost Detection of Methane Gas in Rice Cultivation by Gas Chromatography-Flame Ionization Detector Based on Manual Injection and Split Pattern.

Rice cultivation is one of the most significant human-created sources of methane gas. How to accurately measure the methane concentration produced by rice cultivation has become a major problem. The price of the automatic gas sampler used as a national standard for methane detection (HJ 38-2017) is higher than that of gas chromatography, which greatly increases the difficulty of methane detection in the laboratory. This study established a novel methane detection method based on manual injection and split pattern by changing the parameters of the national standard method without adding any additional automatic gas samplers. The standard curve and correlation coefficient obtained from the parallel determination of methane standard gas were y = 2.4192x + 0.1294 and 0.9998, respectively. Relative standard deviation (RSD, <2.82%), recycle rate (99.67−102.02%), limit of detection (LOD, 0.0567 ppm) and limit of quantification (LOQ, 0.189 ppm) of this manual injection method are satisfying, demonstrating that a gas chromatography-flame ionization detector (GC-FID), based on manual injection at a split ratio (SR) of 5:1, could be an effective and accurate method for methane detection. Methane gases produced by three kinds of low-methane rice treated with oxantel pamoate acid, fumaric acid and alcohol, were also collected and detected using the proposed manual injection approach Good peak shapes were obtained, indicating that this approach could also be used for quantification of methane concentration.

Smut fungal strategies for the successful infection.

The smut fungi include a large number of plant pathogens that establish obligate biotrophic relationships with their host. Throughout the whole life inside plant tissue, smut fungi keep plant cells alive and acquire nutrients via biotrophic interfaces. This mini-review mainly summarizes the interactions between smut fungi and their host plants during the infection process. Despite various strategies recruited by plants to defense invading pathogens, smut fungi successfully evolved an arsenal for colonization. Mating of two compatible haploids gives rise to parasitic mycelium, which can sense plant surface cues such as fatty acids and hydrophobic surface, and induce the formation of appressoria for surface penetration. Plants can recognize fungal invading and activate defense response, including callose and lignin deposition, programmed cell death, and SA signaling pathway. To suppress plant immunity and alter the metabolic pathway of host plants, a cocktail of effectors is secreted by smut fungi depending on the plant organ and cell type that is infected.

Mating-type loci of Ustilago esculenta are essential for mating and development.

Ustilago esculenta is closely related to the smut fungus Ustilago maydis and, in an endophytic-like life in the plant Zizania latifolia, only infects host stems and causes swollen stems to form edible galls called Jiaobai in China. In order to study its different modes of invasion and sites of symptom development from other smut fungi at the molecular level, we first characterized the a and b mating-type loci of U. esculenta. The a loci contained three a mating-type alleles, encoding two pheromones and one pheromone receptor per allele. The pheromone/receptor system controlled the conjugation formation, the initial step of mating, in which each pheromone was specific for recognition by only one mating partner. In addition, there are at least three b alleles identified in U. esculenta, encoding two subunits of heterodimeric homeodomain transcription factors bE and bW, responsible for hyphal growth and invasiveness. Hyphal formation, elongation and invasion after mating of two compatible partners occurred, only when a heterodimer complex was formed by the bE and bW proteins derived from different alleles. We also demonstrated that even with only one paired pheromone-pheromone receptor, the active b locus heterodimer triggered hyphal growth and infection.

Cloning and disruption of the UeArginase in Ustilago esculenta: evidence for a role of arginine in its dimorphic transition.

BACKGROUND: Ustilago esculenta, a typical dimorphic fungus could infect Zizania latifolia and induce host stem swollen to form an edible vegetable called Jiaobai in China. The strains differentiation especially in the mating ability and pathogenicity is closely related to different phenotypes of Jiaobai formed in the fields. Dimorphic switching, a tightly regulated processes, is essential for the pathogenetic development of dimorphic fungi. In responses to environment cues, dimorphic switching can be activated through two conserved cell signaling pathways-PKA and MAPK pathways. Previous study indicated that exogenous arginine could induce hyphal formation in several dimorphic fungi through hydrolysis by arginase, but inhibit the dimorphic transition of U. esculenta. We conducted this study to reveal the function of arginine on dimorphic transition of U. esculenta. RESULTS: In this study, we found that arginine, but not its anabolites, could slow down the dimorphic transition of U. esculenta proportionally to the concentration of arginine. Besides, UeArginase, predicated coding arginase in U. esculenta was cloned and characterized. UeArginase mutants could actually increase the content of endogenous arginine, and slow down the dimorphic transition on either nutritious rich or poor medium. Either adding exogenous arginine or UeArginase deletion lead to down regulated expressions of UePkaC, UePrf1, mfa1.2, mfa2.1, pra1 and pra2, along with an increased content of arginine during mating process. CONCLUSION: Results of this study indicated a direct role of arginine itself on the inhibition of dimorphic transition of U. esculenta, independent of its hydrolysis by UeArginase.

Cloning and Characterization of Two MAPK Genes UeKpp2 and UeKpp6 in Ustilago esculenta.

Ustilago esculenta, resembling a fungal endophyte in Zizania latifolia, inhibits the host plant flowering and induces the host stems to swell and form edible galls. It is well believed that when and how the fungus infects and proliferates in the host plants during the host development is of importance in the edible gall formation. Mitogen-activated protein kinases (MAPKs) have been found to play an important role in sensing environment cues and regulating infection. Two MAPK genes UeKpp2 and UeKpp6 from U. esculenta were cloned and suggested to be involved in the Fus3/Kss1 pathway by a phylogenetic analysis with the neighbor-joining method. Quantitative RT-PCR (qRT-PCR) analyses indicated that expression of UeKpp2 and UeKpp6 were induced during mating and infection processes, and their expression patterns displayed differentially under different carbon and nitrogen sources. In addition, subcellular localization of UeKpp2 or UeKpp6 fused with the reporter green fluoresce protein was observed by confocal laser scanning microscope, and yeast two-hybrid assays were carried out. Results showed that both UeKpp2 and UeKpp6 were located in cytoplasm and interacted with UePrf1, indicating their involvement in hyphal growth and host-pathogen regulation. Only UeKpp2 but not UeKpp6 interacted with the upstream MAPK kinase UeFuz7, implying an additional MAPK pathway, in which UeKpp6 involved, existed.

Investigation on the differentiation of two Ustilago esculenta strains - implications of a relationship with the host phenotypes appearing in the fields.

BACKGROUND: Ustilago esculenta, a pathogenic basidiomycete fungus, infects Zizania latifolia to form edible galls named Jiaobai in China. The distinct growth conditions of U. esculenta induced Z. latifolia to form three different phenotypes, named male Jiaobai, grey Jiaobai and white Jiaobai. The aim of this study is to characterize the genetic and morphological differences that distinguish the two U. esculenta strains. RESULTS: In this study, sexually compatible haploid sporidia UeT14/UeT55 from grey Jiaobai (T strains) and UeMT10/UeMT46 from white Jiaobai (MT strains) were isolated. Meanwhile, we successfully established mating and inoculation assays. Great differences were observed between the T and MT strains. First, the MT strains had a defect in development, including lower teliospore formation frequency and germination rate, a slower growth rate and a lower growth mass. Second, they differed in the assimilation of nitrogen sources in that the T strains preferred urea and the MT strains preferred arginine. In addition, the MT strains were more sensitive to external signals, including pH and oxidative stress. Third, the MT strains showed an infection defect, resulting in an endophytic life in the host. This was in accordance with multiple mutated pathogenic genes discovered in the MT strains by the non-synonymous mutation analysis of the genome re-sequencing data between the MT and T strains (GenBank accession numbers of the genome re-sequencing data: JTLW00000000 for MT strains and SRR5889164 for T strains). CONCLUSION: The MT strains appeared to have defects in growth and infection and were more sensitive to external signals compared to the T strains. They displayed an absolutely stable endophytic life in the host without an infection cycle. Accordingly, they had multiple gene mutations occurring, especially in pathogenicity. In contrast, the T strains, as phytopathogens, had a complete survival life cycle, in which the formation of teliospores is important for adaption and infection, leading to the appearance of the grey phenotype. Further studies elucidating the molecular differences between the U. esculenta strains causing differential host phenotypes will help to improve the production and formation of edible white galls.

A host plant genome (Zizania latifolia) after a century-long endophyte infection.

Despite the importance of host-microbe interactions in natural ecosystems, agriculture and medicine, the impact of long-term (especially decades or longer) microbial colonization on the dynamics of host genomes is not well understood. The vegetable crop 'Jiaobai' with enlarged edible stems was domesticated from wild Zizania latifolia (Oryzeae) approximately 2000 years ago as a result of persistent infection by a fungal endophyte, Ustilago esculenta. Asexual propagation via infected rhizomes is the only means of Jiaobai production, and the Z. latifolia-endophyte complex has been maintained continuously for two centuries. Here, genomic analysis revealed that cultivated Z. latifolia has a significantly smaller repertoire of immune receptors compared with wild Z. latifolia. There are widespread gene losses/mutations and expression changes in the plant-pathogen interaction pathway in Jiaobai. These results show that continuous long-standing endophyte association can have a major effect on the evolution of the structural and transcriptomic components of the host genome.

Carboxymethyl chitosan-modified UiO-66 for the rapid detection of fenpropathrin in grains.

Fenpropathrin residues in grain are potentially harmful to humans. Therefore, a fluorimetric lateral flow immunoassay using a zirconium-based organic skeleton (UiO-66) as a signal marker was developed for detecting fenpropathrin. Herein, carboxymethyl chitosan (CMCS) was used to modify UiO-66 and improve its water solubility to facilitate stable binding with sodium fluorescein (NaFL). This resulted in formation of a new fluorescent probe that is more suitable for lateral flow immunoassay (LFIA). The materials were characterized via electron microscopy, Fourier-transform infrared spectroscopy, and powder X-ray diffraction. CMCS and NaFL were successfully bound to UiO-66. Under optimized conditions, the constructed NaFL/UiO-66@CMCS-LFIA exhibited a good linear relationship within the range of 0.98-62.5 µg/L, with a detection limit of 3.91 µg/L. This probe was fourfold more sensitive than traditional colloidal gold nanoparticle-based LFIA. Finally, NaFL/UiO-66@CMCS-LFIA was successfully applied to detect fenpropathrin in wheat and maize samples. The detection limit was 1.56 µg/kg and recoveries ranged from 96.58 % to 118.56 %. This study provides a sensitive, stable, and convenient method for the rapid detection of pesticide residues.

Structural insights into IL-6 signaling inhibition by therapeutic antibodies.

Antibody inhibitors of the interleukin-6 (IL-6) signaling pathway, such as tocilizumab and sarilumab, have been used to treat rheumatoid arthritis, chimeric antigen receptor T cell-induced cytokine storm, and severe COVID-19 pneumonia. Here, we solve the cryogenic electron microscopy structures of sarilumab and tocilizumab in complex with IL-6R to resolutions of 3.2 and 3.3 Å, respectively. These structures reveal that both tocilizumab and sarilumab bind to the D3 domain of IL-6R. The binding surfaces of the two antibodies largely overlap, but the detailed interactions are different. Functional studies of various mutants show results consistent with our structural analysis of the antibodies and IL-6R interactions. Structural comparisons with the IL-6/IL-6R/gp130 complex indicate that sarilumab and tocilizumab probably inhibit IL-6/IL-6R signaling by competing for the IL-6 binding site. In summary, this work reveals the antibody-blocking mechanism of the IL-6 signaling pathway and paves the way for future antibody discovery.

Targeting autophagy drug discovery: Targets, indications and development trends.

Autophagy plays a vital role in sustaining cellular homeostasis and its alterations have been implicated in the etiology of many diseases. Drugs development targeting autophagy began decades ago and hundreds of agents were developed, some of which are licensed for the clinical usage. However, no existing intervention specifically aimed at modulating autophagy is available. The obstacles that prevent drug developments come from the complexity of the actual impact of autophagy regulators in disease scenarios. With the development and application of new technologies, several promising categories of compounds for autophagy-based therapy have emerged in recent years. In this paper, the autophagy-targeted drugs based on their targets at various hierarchical sites of the autophagic signaling network, e.g., the upstream and downstream of the autophagosome and the autophagic components with enzyme activities are reviewed and analyzed respectively, with special attention paid to those at preclinical or clinical trials. The drugs tailored to specific autophagy alone and combination with drugs/adjuvant therapies widely used in clinical for various diseases treatments are also emphasized. The emerging drug design and development targeting selective autophagy receptors (SARs) and their related proteins, which would be expected to arrest or reverse the progression of disease in various cancers, inflammation, neurodegeneration, and metabolic disorders, are critically reviewed. And the challenges and perspective in clinically developing autophagy-targeted drugs and possible combinations with other medicine are considered in the review.

Development of a Phage-Displayed Nanobody-Based Competitive Immunoassay for the Sensitive Detection of Soybean Agglutinin.

Soybean agglutinin (SBA) is a primary antinutritional factor in soybeans that can inhibit the growth of humans and mammals, disrupt the intestinal environment, and cause pathological changes. Therefore, detecting and monitoring SBA in foods is essential for safeguarding human health. In this paper, M13 phage-displayed nanobodies against SBA were isolated from a naive nanobody library. An M13 phage-displayed nanobody-based competitive enzyme-linked immunosorbent assay (P-cELISA) was then established for SBA analysis using biotinylated anti-M13 phage antibody (biotin-anti-M13) and streptavidin poly-HRP conjugate (SA-poly-HRP). The biotin-anti-M13@SA-poly-HRP probe can easily amplify the detection signal without the chemical modifications of phage-displayed nanobodies. The established P-cELISA presented a linear detection range of 0.56-250.23 ng/mL and a limit of detection (LOD) of 0.20 ng/mL, which was 12.6-fold more sensitive than the traditional phage-ELISA. Moreover, the developed method showed good specificity for SBA and acceptable recoveries (78.21-121.11%) in spiked wheat flour, albumen powder, and whole milk powder. This study proposes that P-cELISA based on biotin-anti-M13@SA-poly-HRP may provide a convenient and effective strategy for the sensitive detection of SBA.