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Qiuyang Deng,1,* Jinyong Zhang,2,* Min Zhang,1 Zhou Liu,3 Yuxin Zhong,1 Shiyi Liu,1 Ruiqin Cui,1 Yun Shi,2 Hao Zeng,2 Xiyao Yang,3 Chuchu Lin,4 Yutian Luo,5 Huaisheng Chen,5 Weiyuan Wu,6 Jinsong Wu,6 Tianle Zhang,7 Yuemei Lu,6 Xueyan Liu,5 Quanming Zou,2 Wei Huang1 1Bacteriology & Antibacterial Resistance Surveillance Laboratory, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 2National Engineering Research Center of Immunological Products, Department of Microbiology and Biochemical Pharmacy, College of Pharmacy, Army Medical University, Chongqing, People’s Republic of China; 3Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 4Department of Nosocomial Infection Control, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 5Intensive Care Unit, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 6Department of Clinical Microbiology, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 7Guangdong Medical University, Dongguan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei HuangBacteriology & Antibacterial Resistance Surveillance Laboratory, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of ChinaTel +86 7522942513Fax +86 7522942514Email whuang_sz@163.comQuanming Zou National Engineering Research Center of Immunological Products, Department of Microbiology and Biochemical PharmacyCollege of Pharmacy, Army Medical University, Chongqing 400038, People’s Republic of ChinaTel/Fax +86 2368752316Email qmzou2007@163.comObjective: We aimed to establish a tool for rapid identification of KL49 Acinetobacter baumannii.Methods: Based on the capsular polysaccharide (CPS) synthesis genes database, we investigated the distribution of K locus type 49 (KL49) genes in other KL types and established a rapid identification method for KL49. We collected 61 clinical carbapenem-resistant A. baumannii (CRAB) strains, identified KL49 by gtr100 detection, and used whole genome sequencing (WGS) for verification. A mouse pneumonia model was used to confirm the hypervirulence phenotype. We tested the presence of gtr100 gene in 165 CRAB strains from three provinces in China and evaluated the correlation of gtr100 carrying CRAB infection with mortality.Results: The gtr100 gene is the CPS synthesis gene found only in KL49. We screened out nine WGS-validated KL49 strains from 61 CRAB clinical strains using polymerase chain reaction (PCR) to detect the gtr100 gene. The survival rates of KL49 strains were significantly lower than nonKL49 strains in a mouse pneumonia model. The survival rates of LAC-4 gtr100 knockout strain decreased significantly. Analysis of phylogenetics showed the worldwide spread of KL49 A. baumannii. Infection of gtr100 carrying CRAB is an independent risk for mortality (OR, 10.76; 95%CI: 3.08– 37.55; p< 0.001).Conclusion: The hypervirulence phenotype of KL49 CRAB and the association with mortality highlight the urgent need for implementing control measures. The rapid identification assay has the potential to facilitate early medical intervention and worldwide surveillance.Keywords: Acinetobacter baumannii, hypervirulent, K locus, Kaptive, mortality

Qiuyang Deng,1,* Jinyong Zhang,2,* Min Zhang,1 Zhou Liu,3 Yuxin Zhong,1 Shiyi Liu,1 Ruiqin Cui,1 Yun Shi,2 Hao Zeng,2 Xiyao Yang,3 Chuchu Lin,4 Yutian Luo,5 Huaisheng Chen,5 Weiyuan Wu,6 Jinsong Wu,6 Tianle Zhang,7 Yuemei Lu,6 Xueyan Liu,5 Quanming Zou,2 Wei Huang1 1Bacteriology & Antibacterial Resistance Surveillance Laboratory, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 2National Engineering Research Center of Immunological Products, Department of Microbiology and Biochemical Pharmacy, College of Pharmacy, Army Medical University, Chongqing, People’s Republic of China; 3Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 4Department of Nosocomial Infection Control, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 5Intensive Care Unit, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 6Department of Clinical Microbiology, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of China; 7Guangdong Medical University, Dongguan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei HuangBacteriology & Antibacterial Resistance Surveillance Laboratory, Shenzhen Institute of Respiratory Diseases, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong 518020, People’s Republic of ChinaTel +86 7522942513Fax +86 7522942514Email whuang_sz@163.comQuanming Zou National Engineering Research Center of Immunological Products, Department of Microbiology and Biochemical PharmacyCollege of Pharmacy, Army Medical University, Chongqing 400038, People’s Republic of ChinaTel/Fax +86 2368752316Email qmzou2007@163.comObjective: We aimed to establish a tool for rapid identification of KL49 Acinetobacter baumannii.Methods: Based on the capsular polysaccharide (CPS) synthesis genes database, we investigated the distribution of K locus type 49 (KL49) genes in other KL types and established a rapid identification method for KL49. We collected 61 clinical carbapenem-resistant A. baumannii (CRAB) strains, identified KL49 by gtr100 detection, and used whole genome sequencing (WGS) for verification. A mouse pneumonia model was used to confirm the hypervirulence phenotype. We tested the presence of gtr100 gene in 165 CRAB strains from three provinces in China and evaluated the correlation of gtr100 carrying CRAB infection with mortality.Results: The gtr100 gene is the CPS synthesis gene found only in KL49. We screened out nine WGS-validated KL49 strains from 61 CRAB clinical strains using polymerase chain reaction (PCR) to detect the gtr100 gene. The survival rates of KL49 strains were significantly lower than nonKL49 strains in a mouse pneumonia model. The survival rates of LAC-4 gtr100 knockout strain decreased significantly. Analysis of phylogenetics showed the worldwide spread of KL49 A. baumannii. Infection of gtr100 carrying CRAB is an independent risk for mortality (OR, 10.76; 95%CI: 3.08– 37.55; p< 0.001).Conclusion: The hypervirulence phenotype of KL49 CRAB and the association with mortality highlight the urgent need for implementing control measures. The rapid identification assay has the potential to facilitate early medical intervention and worldwide surveillance.Keywords: Acinetobacter baumannii, hypervirulent, K locus, Kaptive, mortality

Klebsiella pneumoniae is a nosocomial pathogen, pointed out by the World Helth Organisation (WHO) as &ldquo, critical&rdquo, regarding the highly limited options of treatment. Lipopolysaccharide (LPS, O-antigen) and capsular polysaccharide (K-antigen) are its virulence factors and surface antigens, determining O- and K-serotypes and encoded by O- or K-loci. They are promising targets for antibody-based therapies (vaccines and passive immunization) as an alternative to antibiotics. To make such immunotherapy effective, knowledge about O/K-antigen structures, drift, and distribution among clinical isolates is needed. At present, the structural analysis of O-antigens is efficiently supported by bioinformatics. O- and K-loci-based genotyping by polymerase chain reaction (PCR) or whole genome sequencing WGS has been proposed as a diagnostic tool, including the Kaptive tool available in the public domain. We analyzed discrepancies for O2 serotyping between Kaptive-based predictions (O2 variant 2 serotype) and the actual phenotype (O2 variant 1) for two K. pneumoniae clinical isolates. Identified length discrepancies from the reference O-locus resulted from insertion sequences (ISs) within rfb regions of the O-loci. In silico analysis of 8130 O1 and O2 genomes available in public databases indicated a broader distribution of ISs in rfbs that may influence the actual O-antigen structure. Our results show that current high-throughput genotyping algorithms need to be further refined to consider the effects of ISs on the LPS O-serotype.

Multiply antibiotic-resistant Acinetobacter baumannii infections are a global public health concern and accurate tracking of the spread of specific lineages is needed. Variation in the composition and structure of capsular polysaccharide (CPS), a critical determinant of virulence and phage susceptibility, makes it an attractive epidemiological marker. The outer core (OC) of lipooligosaccharide also exhibits variation. To take better advantage of the untapped information available in whole genome sequences, we have created a curated reference database of 92 publicly available gene clusters at the locus encoding proteins responsible for biosynthesis and export of CPS (K locus), and a second database for 12 gene clusters at the locus for outer core biosynthesis (OC locus). Each entry has been assigned a unique KL or OCL number, and is fully annotated using a simple, transparent and standardized nomenclature. These databases are compatible with Kaptive, a tool for in silico typing of bacterial surface polysaccharide loci, and their utility was validated using (a) >630 assembled A. baumannii draft genomes for which the KL and OCL regions had been previously typed manually, and (b) 3386 A. baumannii genome assemblies downloaded from NCBI. Among the previously typed genomes, Kaptive was able to confidently assign KL and OCL types with 100 % accuracy. Among the genomes retrieved from NCBI, Kaptive detected known KL and OCL in 87 and 90 % of genomes, respectively, indicating that the majority of common KL and OCL types are captured within the databases; 13 of the 92 KL in the database were not detected in any publicly available whole genome assembly. The failure to assign a KL or OCL type may indicate incomplete or poor-quality genomes. However, further novel variants may remain to be documented. Combining outputs with multilocus sequence typing (Institut Pasteur scheme) revealed multiple KL and OCL types in collections of a single sequence type (ST) representing each of the two predominant globally distributed clones, ST1 of GC1 and ST2 of GC2, and in collections of other clones comprising >20 isolates each (ST10, ST25, and ST140), indicating extensive within-clone replacement of these loci. The databases are available at https://github.com/katholt/Kaptive and will be updated as further locus types become available.