1.Astragalus polysaccharide regulates exosomes derived from breast cancer cells and its effects on macrophage polarization and antitumor effects
Chenjuan Guan ; Caixia Xie ; Xiaojiao Zheng ; Nana Bao ; Lu Wang ; Wenhui Bai ; Shu Qiao ; Haonan Zhang
Acta Universitatis Medicinalis Anhui 2025;60(10):1790-1798
Objective:
To investigate the effects and mechanisms of Astragalus Polysacharin(APS) on the proliferation and metastasis of breast cancer cells by regulating miR-107 and miR-346-mediated macrophage polarization in breast cancer-derived exosomes.
Methods:
Forty 8-week-old female BALB/c mice were selected and breast cancer xenograft models and 4T1 transplanted tumor models were established. The mice were divided into the control group and the APS group. The APS group mice received daily intragastric administration of APS for 25 days, while the control group mice were given the same amount of normal saline. After all treatments were completed, the mice were euthanized, and tumor tissues were isolated. Western blot and flow cytometry were used to detect the expressions of proliferating cell nuclear antigen(PCNA), Ki-67, CD206, CD163, inducible nitric-oxide synthase(iNOS), and CD86. The apoptosis of single-cell suspensions in tumor tissues was analyzed. Human breast cancer cell line MDA-MB-231 was cultured and stimulated with APS, and exosomes from the cell culture medium were collected. The proliferation, migration, and invasion of cells were detected by CCK-8 assay, scratch assay, permeability chamber cell invasion assay, and qRT-PCR. Differentially expressed genes were screened by bioinformatics.
Results :
By measuring the expressions of molecules related to breast cancer cell proliferation and metastasis, it was shown that APS treatment reduced the expressions of proliferation-related proteins(PCNA and Ki-67) and metastasis-related proteins(Vimentin) in MDA-MB-231 xenograft tumor tissues; and the polarization of tumor-associated macrophages was observed. APS treatment of 4T1 transplanted tumor tissues could reduce the number of M2 macrophages and increase the number of M1 macrophages, resulting in a decrease in the ratio of M2/M1 macrophages and an increase in cell apoptosis in 4T1 transplanted tumor tissues. The expressions of related proteins iNOS and CD86 increased, and CD206 and CD163 decreased. After APS treatment, the exosomes produced by MDA-MB-231 reduced the polarization of M2 macrophages and affected the expressions of miR-107 and miR-346.
Conclusion
APS inhibits the polarization of M2 macrophages by regulating the expression of miR-107 or miR-346 in breast cancer cell-derived exosomes, ultimately inhibiting the proliferation and metastasis of breast cancer cells.
2.Study on establishment of UPLC fingerprint and determination of 12 components in Aiye standard decoction
Yifei MA ; Xiangyuan ZHOU ; Yuanyuan XIE ; Zhenyu LI ; Minyou HE ; Yong LIU ; Wenhui LUO ; Xian QIU ; Qiong LUO ; Roushan CHEN ; Xiangdong CHEN ; Dongmei SUN
International Journal of Traditional Chinese Medicine 2025;47(10):1425-1431
Objective:To establish a quality control method for Aiye standard decoction.Methods:The ultra performance liquid chromatogrphy (UPLC) column Waters ACQUITY HSS T3 C18 (2.1 mm×150 mm,1.8 μm) was used to gradient elution by acetonitrile and 0.1% formic acid in water. 16 batches of Aiye standard decoction fingerprints were established by UPLC and the common peaks were determined in the fingerprints. The contents of 12 components were determined. The 16 batches of Aiye standard decoction were analyzed by similarity calculation, hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for analysis of differential components of Artemisiae Argyi Folium from different origins.Results:A total of 13 common peaks were marked in the fingerprints of 16 batches of Aiye standard decoction, 12 of which were identified by comparison with reference substance, including chlorogenic acid, sochlorogenic acid A, neochlorogenic acid, cryptochlorogenic acid, caffeic acid,1,3-O-Dicaffeoylquinic acid, schaftoside, isochlorogenic acid B,1,5-O-Dicaffeoylquinic acid, isochlorogenic acid C, jaceosidin and eupatilin. Similarity evaluation, PCA and HCA all classified the 16 batches of Aiye standard decoction into 2 categories. Orthogonal partial least squares discriminant analysis screened 5 differential biomarkers from 13 common peaks. The content determination results showed that the phenolic compounds and flavonoids in samples from Hubei were significantly higher than that in samples from other areas.Conclusion:This method can effectively analyze the differences in the quality of Aiye standard decoction from different origins, and provide reference for the formulation of quality standards for Aiye standard decoction and related preparations.
3.Prioritization of potential drug targets for diabetic kidney disease using integrative omics data mining and causal inference
Junyu ZHANG ; Jie PENG ; Chaolun YU ; Yu NING ; Wenhui LIN ; Mingxing NI ; Qiang XIE ; Chuan YANG ; Huiying LIANG ; Miao LIN
Journal of Pharmaceutical Analysis 2025;15(8):1787-1799
Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22%(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.
4.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
5.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
6.Research progress of medical image fusion methods based on deep learning
Yi ZHANG ; Liu LIU ; Meng WANG ; Wenhui XIE
Chinese Journal of Nuclear Medicine and Molecular Imaging 2025;45(10):637-640
Medical image fusion technology combines the advantages of different modal medical images to provide more comprehensive and precise imaging information, widely applied in clinical diagnosis and disease research. Traditional fusion methods rely on signal processing techniques, but they have significant limitations, especially in multi-modal image fusion, where extracting deep semantic information is challenging. With the introduction of deep learning, image fusion effects have been significantly enhanced through technologies such as convolutional neural networks (CNN), generative adversarial networks (GAN), deep feature extractors, and self-attention mechanisms. However, deep learning methods still face challenges such as data scarcity, modal heterogeneity, high computational resource requirements, mode collapse, and training instability. This paper analyzes these issues and explores corresponding solutions as well as potential future development directions.
7.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
8.Inhibition of WAC alleviates the chondrocyte proinflammatory secretory phenotype and cartilage degradation via H2BK120ub1 and H3K27me3 coregulation.
Peitao XU ; Guiwen YE ; Xiaojun XU ; Zhidong LIU ; Wenhui YU ; Guan ZHENG ; Zepeng SU ; Jiajie LIN ; Yunshu CHE ; Yipeng ZENG ; Zhikun LI ; Pei FENG ; Qian CAO ; Zhongyu XIE ; Yanfeng WU ; Huiyong SHEN ; Jinteng LI
Acta Pharmaceutica Sinica B 2025;15(8):4064-4077
Several types of arthritis share the common feature that the generation of inflammatory mediators leads to joint cartilage degradation. However, the shared mechanism is largely unknown. H2BK120ub1 was reportedly involved in various inflammatory diseases but its role in the shared mechanism in inflammatory joint conditions remains elusive. The present study demonstrated that levels of cartilage degradation, H2BK120ub1, and its regulator WW domain-containing adapter protein with coiled-coil (WAC) were increased in cartilage in human rheumatoid arthritis (RA) and osteoarthritis (OA) patients as well as in experimental RA and OA mice. By regulating H2BK120ub1 and H3K27me3, WAC regulated the secretion of inflammatory and cartilage-degrading factors. WAC influenced the level of H3K27me3 by regulating nuclear entry of the H3K27 demethylase KDM6B, and acted as a key factor of the crosstalk between H2BK120ub1 and H3K27me3. The cartilage-specific knockout of WAC demonstrated the ability to alleviate cartilage degradation in collagen-induced arthritis (CIA) and collagenase-induced osteoarthritis (CIOA) mice. Through molecular docking and dynamic simulation, doxercalciferol was found to inhibit WAC and the development of cartilage degradation in the CIA and CIOA models. Our study demonstrated that WAC is a key factor of cartilage degradation in arthritis, and targeting WAC by doxercalciferol could be a viable therapeutic strategy for treating cartilage destruction in several types of arthritis.
9.Prioritization of potential drug targets for diabetic kidney disease using integrative omics data mining and causal inference.
Junyu ZHANG ; Jie PENG ; Chaolun YU ; Yu NING ; Wenhui LIN ; Mingxing NI ; Qiang XIE ; Chuan YANG ; Huiying LIANG ; Miao LIN
Journal of Pharmaceutical Analysis 2025;15(8):101265-101265
Diabetic kidney disease (DKD) with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression. Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials. In this study, we integrated large-scale plasma proteomics, genetic-driven causal inference, and experimental validation to identify prioritized targets for DKD using the UK Biobank (UKB) and FinnGen cohorts. Among 2844 diabetic patients (528 with DKD), we identified 37 targets significantly associated with incident DKD, supported by both observational and causal evidence. Of these, 22% (8/37) of the potential targets are currently under investigation for DKD or other diseases. Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)-were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLR family pyrin domain containing 3 (NLRP3)-caspase-1-gasdermin D (GSDMD) apoptotic axis. Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.
10.Screening and characterization of camelid-derived nanobodies against hemoglobin.
Ning ZHONG ; Wenhui LEI ; Zuying LIU ; Xiaoxiao XIE ; Lingjing ZHANG ; Tengchuan JIN ; Minjie CAO ; Yulei CHEN
Chinese Journal of Biotechnology 2025;41(4):1515-1534
Hemoglobin, the principal protein in red blood cells, is crucial for oxygen transport in the bloodstream. The quantification of hemoglobin concentration is indispensable in medical diagnostics and health management, which encompass the diagnosis of anemia and the screening of various blood disorders. Immunological methods, based on antigen-antibody interactions, are distinguished by their high sensitivity and accuracy. Consequently, it is necessary to develop hemoglobin-specific antibodies characterized by high specificity and affinity to enhance detection accuracy. In this study, we immunized a Bactrian camel (Camelus bactrianus) with human hemoglobin and subsequently constructed a nanobody library. Utilizing a solid-phase screening method, we selected nanobodies and evaluated the binding activity of the screened nanobodies to hemoglobin. Initially, human hemoglobin was used to immunize a Bactrian camel. Following four immunization sessions, blood was withdrawn from the jugular vein, and a nanobody library with a capacity of 2.85×108 colony forming units (CFU) was generated. Subsequently, ten hemoglobin-specific nanobody sequences were identified through three rounds of adsorption-elution-enrichment assays, and these nanobodies were subjected to eukaryotic expression. Finally, enzyme-linked immunosorbent assay and biolayer interferometry were employed to evaluate the stability, binding activity, and specificity of these nanobodies. The results demonstrated that the nanobodies maintained robust binding activity within the temperature range of 20-40 ℃ and exhibited the highest binding activity at pH 7.0. Furthermore, the nanobodies were capable of tolerating a 10% methanol solution. Notably, among the nanobodies tested, VHH-12 displayed the highest binding activity to hemoglobin, with a half maximal effective concentration (EC50) of 10.63 nmol/L and a equilibrium dissociation constant (KD) of 2.94×10-7 mol/L. VHH-12 exhibited no cross-reactivity with a panel of eight proteins, such as ovalbumin and bovine serum albumin, while demonstrating partial cross-reactivity with hemoglobin derived from porcine, goat, rabbit, and bovine sources. In this study, a hemoglobin-specific high-affinity nanobody was successfully isolated, demonstrating potential applications in disease diagnosis and health monitoring.
Animals
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Camelus/immunology*
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Single-Domain Antibodies/immunology*
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Hemoglobins/immunology*
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Humans
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Peptide Library


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