Objective : To use linear PCR fragment containing antibiotic resistance cassette to carry out homologous recombination and replacement of target gene fragment of Acinetobacter baumannii to achieve rapid gene knockout and functional verification． Methods: Acinetobacter baumannii Ab4294 was used as the research object，and the upper (901 bp) and lower ( 1 028 bp) reaches of fim gene cluster (4 980 bp in length) were amplified by PCR , which was used as the recombinant homologous arm．Kanamycin antibiotic resistance cassette (KanR) was ampli- fied from pUC57 plasmid．The above three fragments were connected by overlapping extended PCR technique，and the connected fragments were transformed into wild Acinetobacter baumannii strains．The gene deletion mutant was screened，and the plasmid complement strain was constructed．The phenotype of the obtained strains was identi- fied，and the function of fim gene cluster was explored. Results : A mutant strain of Acinetobacter baumannii Ab4294 with deletion of fim gene cluster was successfully constructed by homologous substitution of linear PCR frag- ment containing antibiotic resistance cassette．Compared with the wild strain，the growth curve of the deletion strain had no significant difference ，and the rubbing ability significantly decreased ，and the phenotype recovered after complementing the gene cluster． Conclusion The fim family genes of Acinetobacter baumannii Ab4294 is success- fully knocked out by homologous substitution of linear PCR fragment containing antibiotic resistance cassette，which encodes the product involved in the motile movement of Acinetobacter baumannii.

Objective:To investigate the characteristics of nasal flora and the pathogenic role of differential microbiome in patients with allergic rhinitis (AR) and non-allergic rhinitis (nAR).Methods:Thirty-five patients with AR who attended the rhinology outpatient clinic of the Second Hospital of Harbin Medical University from February to July 2022 were selected. A total of 35 nAR patients were selected as the test group, and 20 cases of healthy people with physical examination at the same period were selected as the control group, including 39 males and 51 females, aged 8 to 55 years. 16SrDNA High-throughput sequencing was used to analyze the relative abundance from nasal flora in the three groups of subjects. Alpha diversity index analysis was conducted with R software, and differences between groups were analyzed with LEfSe, Metastats, and t tests. At the same time, the role of microbiome and its relationship with environmental factors were analyzed with R software. Results:There was a significant difference in the bacterial composition of the samples from the three groups, with the relative abundance of Staphylococcus aureus ( P=0.032) and Corynebacterium proinquum ( P=0.032) within the AR group being significantly higher than that of the nAR group, and that of Lactobacillus murinus, Lactobacillus kunkeei, and Alcaligenes faecalis ( P value was 0.016, 0.005, and 0.001, respectively) being significantly lower than that of the nAR group. The relative abundance of Ackermannia muciniphila within the nAR group was higher than that of the control group ( P=0.009). Correlation analysis of environmental factors showed a negative correlation between Lactobacillus kunkeei and IgE ( P=0.044), and a positive correlation between Lactobacillus murinus and age ( P=0.019). AR and nAR random forest prediction models were constructed for the five genera, respectively, and the area under the curve (AUC) of the models of Streptococcus-SP-FF10, Pseudoalteromonas luteoviolacea, Pseudomonas parafulva, Acinetobacter ursingii, and Azotobacter chroococcum in the AR group was 100% (95%CI: 100% to 100%). The AUC for the Pseudomonas parafulva, Azotobacter chroococcum, Closoridium baratii, Turicibacter-SP-H121, and Streptococcus lutetiensis models in the nAR group was 98.4% (95%CI: 94.9% to 100%). Conclusions:The distribution of nasal flora in AR patients, nAR patients and healthy subjects is significantly different, and the changes of bacterial flora abundance are significantly related to the occurrence of AR and nAR. Combined detection of microbiota has the potential to diagnose AR and nAR patients.