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Zhong Y, Pan Q, Wang Y, Yu J, Li Y, Gu L, Hou M, Liang S, Guo J, Jiao X, Zhang Y. Development and Evaluation of a MinION Full-Length 16S rDNA Sequencing Analysis Pipeline for Rapid Diagnosis of Animal Gastrointestinal Diseases. Microorganisms 2025; 13:777. [PMID: 40284613 PMCID: PMC12029435 DOI: 10.3390/microorganisms13040777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2025] [Revised: 03/24/2025] [Accepted: 03/26/2025] [Indexed: 04/29/2025] Open
Abstract
Rapid and accurate detection of the causes of gastrointestinal diseases in farmed and companion animals is crucial for advancing livestock farming and safeguarding public health safety. Diseases caused by pathogenic bacteria infections often result in the overrepresentation of pathogens in the gut microbiota; however, gut microbiota dysbiosis without obvious pathogen overrepresentation can also lead to disorders such as inflammatory bowel disease (IBD). Traditional cultivation-based diagnostic methods are time-consuming and ineffective in identifying microbiota dysbiosis-associated diseases. In this study, we developed a sample-to-answer MinION full-length 16S rDNA sequencing analysis pipeline, accompanied by detailed bioinformatics scripts, for the rapid diagnosis of animal gastrointestinal diseases. The pipeline enables the detection of pathogens and microbiota dysbiosis-associated diseases in approximately six hours. The pipeline showed high sensitivity and specificity, as evident by the analysis of artificially contaminated samples, and accurately diagnosed bacterial infections in five cases, including chicken, duckling, and piglet samples from their respective farms, as well as a companion cat, outperforming traditional methods. It also rapidly identified IBD in five companion animals. The findings highlight the potential application of our developed sample-to-answer analysis pipeline in pathogen detection and the diagnosis of gut microbiota dysbiosis-related diseases in animals, thereby improving livestock health and public safety.
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Affiliation(s)
- Ying Zhong
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Qingyun Pan
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Yu Wang
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Jinyan Yu
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Yaomen Li
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Lifang Gu
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Meicun Hou
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Shenglong Liang
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Jia Guo
- Animal Hospital of Yangzhou University, Yangzhou University, Yangzhou 225009, China;
| | - Xinan Jiao
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Yunzeng Zhang
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou 225009, China; (Y.Z.); (Q.P.); (Y.W.); (J.Y.); (Y.L.); (L.G.); (M.H.); (S.L.)
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou 225009, China
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Cui L, Li P, Xu Q, Huang J, Gu X, Song M, Sun S. Antimicrobial resistance and clonal relationships of Salmonella enterica Serovar Gallinarum biovar pullorum strains isolated in China based on whole genome sequencing. BMC Microbiol 2024; 24:414. [PMID: 39425016 PMCID: PMC11487782 DOI: 10.1186/s12866-024-03296-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 04/07/2024] [Indexed: 10/21/2024] Open
Abstract
BACKGROUND Pullorum disease is a serious problem in many countries. Caused by Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum), it creates huge economic losses in the poultry industry. Although pullorum disease has been well-controlled in many developed countries, it is still a critical problem in developing countries. However, there is still a lack of information on S. Pullorum strains isolated from different regions and sources in China. The objective of this study was to supply the antimicrobial resistance patterns and clonal relationships of S. Pullorum from breeder chicken farms. METHODS In this study, a total of 114 S. Pullorum strains recovered from 11 provinces and municipalities in China between 2020 and 2021 were selected. These 114 S. Pullorum strains were analyzed using whole genome sequencing (WGS). Antimicrobial resistance (AMR) was tested both by genotypic prediction using the WGS method and using disc diffusion to assess phenotypic AMR. RESULTS These 114 sequenced S. Pullorum strains were divided into three sequence types (STs), the dominant STs was ST92 (104/114). Further core genome multi-locus sequence typing analysis indicated that 114 S. Pullorum strains may have a close relationship, which could be clonally transmitted among different provinces and municipalities. Our results showed a close relationship between the S. Pullorum strains found in different regions, indicating these strains may have been transmitted in China a long time ago. Nearly all S. Pullorum strains 94.74% (n = 108) were resistant to at least one antimicrobial class, and 35.96% of the examined Salmonella strains were considered multiple drug resistant. CONCLUSION Overall, this study showed that S. Pullorum strains in China have a close genetic relationship in terms of antimicrobial resistance, suggesting widespread clonal transmission.
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Affiliation(s)
- Lulu Cui
- College of Animal Medicine, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Peiyong Li
- College of Animal Medicine, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Qi Xu
- China Animal Disease Control Center, Beijing, 102618, China
| | - Jiaqi Huang
- College of Animal Medicine, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Xiaoxue Gu
- China Animal Disease Control Center, Beijing, 102618, China.
| | - Mengze Song
- College of Animal Medicine, Shandong Agricultural University, Tai'an, 271018, Shandong, China.
| | - Shuhong Sun
- College of Animal Medicine, Shandong Agricultural University, Tai'an, 271018, Shandong, China.
- Shandong Provincial Key Laboratory of Zoonoses, Shandong Agricultural University, Taian, 271018, Shandong, China.
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Su B, Du G, Hou S, Chen Z, Wu X, He G, Yuan J, Xie C. Antimicrobial Resistance Analysis and Whole-Genome Sequencing of Salmonella Isolates from Environmental Sewage - Guangzhou City, Guangdong Province, China, 2022-2023. China CDC Wkly 2024; 6:254-260. [PMID: 38633200 PMCID: PMC11018552 DOI: 10.46234/ccdcw2024.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 02/29/2024] [Indexed: 04/19/2024] Open
Abstract
What is already known about this topic? S.1,4,[5],12:i:- and S. Rissen are emerging serotypes of Salmonella that require close monitoring for antimicrobial resistance and containment of their spread. What is added by this report? The study aimed to identify antimicrobial resistance genes (ARGs) in S.1,4,[5],12:i:- and S. Rissen strains isolated from environmental sewage in Guangzhou City, Guangdong Province, China. A phylogenetic tree was constructed using single nucleotide polymorphism data to assess genetic relatedness among strains, offering insights for Salmonella infection outbreak investigations in the future. What are the implications for public health practice? It is crucial to implement strategies, such as integrating different networks, to control the spread of drug-resistant Salmonella. Novel technologies must be utilized to disinfect sewage and eliminate ARGs. Ensuring food safety and proper sewage disinfection are essential to curb the dissemination of Salmonella.
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Affiliation(s)
- Bihui Su
- Tuberculosis Management and Treatment Department, Guangzhou Chest Hospital, Guangzhou City, Guangdong Province, China
| | - Guanghong Du
- School of Public Health, Guangzhou Medical University, Guangzhou City, Guangdong Province, China
| | - Shuiping Hou
- Guangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China
| | - Zongqiu Chen
- Guangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China
| | - Xiaoying Wu
- Tuberculosis Management and Treatment Department, Guangzhou Chest Hospital, Guangzhou City, Guangdong Province, China
| | - Gang He
- Tuberculosis Management and Treatment Department, Guangzhou Chest Hospital, Guangzhou City, Guangdong Province, China
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China
| | - Chaojun Xie
- Office of the Director, Huadu District Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China
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Ayoola MB, Das AR, Krishnan BS, Smith DR, Nanduri B, Ramkumar M. Predicting Salmonella MIC and Deciphering Genomic Determinants of Antibiotic Resistance and Susceptibility. Microorganisms 2024; 12:134. [PMID: 38257961 PMCID: PMC10819212 DOI: 10.3390/microorganisms12010134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Salmonella spp., a leading cause of foodborne illness, is a formidable global menace due to escalating antimicrobial resistance (AMR). The evaluation of minimum inhibitory concentration (MIC) for antimicrobials is critical for characterizing AMR. The current whole genome sequencing (WGS)-based approaches for predicting MIC are hindered by both computational and feature identification constraints. We propose an innovative methodology called the "Genome Feature Extractor Pipeline" that integrates traditional machine learning (random forest, RF) with deep learning models (multilayer perceptron (MLP) and DeepLift) for WGS-based MIC prediction. We used a dataset from the National Antimicrobial Resistance Monitoring System (NARMS), comprising 4500 assembled genomes of nontyphoidal Salmonella, each annotated with MIC metadata for 15 antibiotics. Our pipeline involves the batch downloading of annotated genomes, the determination of feature importance using RF, Gini-index-based selection of crucial 10-mers, and their expansion to 20-mers. This is followed by an MLP network, with four hidden layers of 1024 neurons each, to predict MIC values. Using DeepLift, key 20-mers and associated genes influencing MIC are identified. The 10 most significant 20-mers for each antibiotic are listed, showcasing our ability to discern genomic features affecting Salmonella MIC prediction with enhanced precision. The methodology replaces binary indicators with k-mer counts, offering a more nuanced analysis. The combination of RF and MLP addresses the limitations of the existing WGS approach, providing a robust and efficient method for predicting MIC values in Salmonella that could potentially be applied to other pathogens.
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Affiliation(s)
- Moses B. Ayoola
- Department of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; (M.B.A.); (A.R.D.); (B.S.K.); (B.N.)
| | - Athish Ram Das
- Department of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; (M.B.A.); (A.R.D.); (B.S.K.); (B.N.)
| | - B. Santhana Krishnan
- Department of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; (M.B.A.); (A.R.D.); (B.S.K.); (B.N.)
| | - David R. Smith
- Department of Population Medicine, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA;
| | - Bindu Nanduri
- Department of Comparative Biomedical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; (M.B.A.); (A.R.D.); (B.S.K.); (B.N.)
| | - Mahalingam Ramkumar
- Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA
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Liao X, Deng R, Warriner K, Ding T. Antibiotic resistance mechanism and diagnosis of common foodborne pathogens based on genotypic and phenotypic biomarkers. Compr Rev Food Sci Food Saf 2023; 22:3212-3253. [PMID: 37222539 DOI: 10.1111/1541-4337.13181] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 04/22/2023] [Accepted: 05/06/2023] [Indexed: 05/25/2023]
Abstract
The emergence of antibiotic-resistant bacteria due to the overuse or inappropriate use of antibiotics has become a significant public health concern. The agri-food chain, which serves as a vital link between the environment, food, and human, contributes to the large-scale dissemination of antibiotic resistance, posing a concern to both food safety and human health. Identification and evaluation of antibiotic resistance of foodborne bacteria is a crucial priority to avoid antibiotic abuse and ensure food safety. However, the conventional approach for detecting antibiotic resistance heavily relies on culture-based methods, which are laborious and time-consuming. Therefore, there is an urgent need to develop accurate and rapid tools for diagnosing antibiotic resistance in foodborne pathogens. This review aims to provide an overview of the mechanisms of antibiotic resistance at both phenotypic and genetic levels, with a focus on identifying potential biomarkers for diagnosing antibiotic resistance in foodborne pathogens. Furthermore, an overview of advances in the strategies based on the potential biomarkers (antibiotic resistance genes, antibiotic resistance-associated mutations, antibiotic resistance phenotypes) for antibiotic resistance analysis of foodborne pathogens is systematically exhibited. This work aims to provide guidance for the advancement of efficient and accurate diagnostic techniques for antibiotic resistance analysis in the food industry.
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Affiliation(s)
- Xinyu Liao
- Department of Food Science and Nutrition, Zhejiang University, Hangzhou, Zhejiang, China
- School of Mechanical and Energy Engineering, NingboTech University, Ningbo, Zhejiang, China
- Future Food Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan, Zhejiang, China
| | - Ruijie Deng
- College of Biomass Science and Engineering, Healthy Food Evaluation Research Center, Sichuan University, Chengdu, Sichuan, China
| | - Keith Warriner
- Department of Food Science, University of Guelph, Guelph, Ontario, Canada
| | - Tian Ding
- Department of Food Science and Nutrition, Zhejiang University, Hangzhou, Zhejiang, China
- Future Food Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan, Zhejiang, China
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Dubey S, Ager-Wick E, Kumar J, Karunasagar I, Karunasagar I, Peng B, Evensen Ø, Sørum H, Munang’andu HM. Aeromonas species isolated from aquatic organisms, insects, chicken, and humans in India show similar antimicrobial resistance profiles. Front Microbiol 2022; 13:1008870. [PMID: 36532495 PMCID: PMC9752027 DOI: 10.3389/fmicb.2022.1008870] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/14/2022] [Indexed: 01/07/2024] Open
Abstract
Aeromonas species are Gram-negative bacteria that infect various living organisms and are ubiquitously found in different aquatic environments. In this study, we used whole genome sequencing (WGS) to identify and compare the antimicrobial resistance (AMR) genes, integrons, transposases and plasmids found in Aeromonas hydrophila, Aeromonas caviae and Aeromonas veronii isolated from Indian major carp (Catla catla), Indian carp (Labeo rohita), catfish (Clarias batrachus) and Nile tilapia (Oreochromis niloticus) sampled in India. To gain a wider comparison, we included 11 whole genome sequences of Aeromonas spp. from different host species in India deposited in the National Center for Biotechnology Information (NCBI). Our findings show that all 15 Aeromonas sequences examined had multiple AMR genes of which the Ambler classes B, C and D β-lactamase genes were the most dominant. The high similarity of AMR genes in the Aeromonas sequences obtained from different host species point to interspecies transmission of AMR genes. Our findings also show that all Aeromonas sequences examined encoded several multidrug efflux-pump proteins. As for genes linked to mobile genetic elements (MBE), only the class I integrase was detected from two fish isolates, while all transposases detected belonged to the insertion sequence (IS) family. Only seven of the 15 Aeromonas sequences examined had plasmids and none of the plasmids encoded AMR genes. In summary, our findings show that Aeromonas spp. isolated from different host species in India carry multiple AMR genes. Thus, we advocate that the control of AMR caused by Aeromonas spp. in India should be based on a One Health approach.
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Affiliation(s)
- Saurabh Dubey
- Section of Experimental Biomedicine, Department of Production Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Eirill Ager-Wick
- Section of Experimental Biomedicine, Department of Production Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Jitendra Kumar
- College of Fisheries, Acharya Narendra Deva University of Agriculture and Technology, Uttar Pradesh, India
| | - Indrani Karunasagar
- Nitte University Centre for Science Education and Research, Mangaluru, India
| | - Iddya Karunasagar
- Nitte University Centre for Science Education and Research, Mangaluru, India
| | - Bo Peng
- State Key Laboratory of Biocontrol, Guangdong Key Laboratory of Pharmaceutical Functional Genes, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Higher Education Mega Center, Guangzhou, China
| | - Øystein Evensen
- Department of Paraclinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Henning Sørum
- Department of Paraclinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Hetron M. Munang’andu
- Section of Experimental Biomedicine, Department of Production Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
- Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway
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