Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C464
  Reference Plasmid   NZ_CP018732.1
  Reference Plasmid Size   203385
  Reference Plasmid GC Content   0.59
  Reference Plasmid Mobility Type   mobilizable





Mutation sites in the plasmid cluster


The table lists mutations identified in the plasmid cluster.
Note: Mutations identified in this plasmid cluster are listed below. Click on a mutation ID to view full details..

mutid gname pos count tissue frequnt biotype consequence impact nucchange aachange
M0088723 BGLGADPG_00061 60389 3 Skin 0.38 protein_coding missense_variant MODERATE 69C>G Ile23Met
M0088724 BGLGADPG_00062 61929 3 Skin 0.38 protein_coding synonymous_variant LOW 1176G>A Gly392Gly
M0088725 BGLGADPG_00062 62352 4 Skin 0.50 protein_coding synonymous_variant LOW 1599A>G Glu533Glu
M0088726 BGLGADPG_00064 64172 3 Skin 0.38 protein_coding synonymous_variant LOW 273A>G Ser91Ser
M0088727 BGLGADPG_00064 64178 3 Skin 0.38 protein_coding missense_variant MODERATE 279C>G Asp93Glu
M0088728 BGLGADPG_00068 66564 3 Skin 0.38 protein_coding missense_variant MODERATE 227T>C Leu76Pro






Analysis of virulence factors contributing to bacterial pathogenicity


This table presents virulence factors identified within the plasmid cluster.
      Note: Virulence factor analysis was performed using VFDB. Genes in plasmid clusters showing strong homology (identity > 70%, coverage > 70%, E-value < 1e-5) to known virulence factors are listed.

Gene Name vf_gene_id vf_name identity evalue qstart qend query_coverage subject_coverage vf_category gene_description condition







        Analysis of biocide and heavy metal resistance genes to assess antimicrobial risk and environmental impact


This table presents biocides and heavy metals resistance genes identified within the plasmid cluster.
      Note: Analyzing biocide and heavy metal resistance genes based on BacMet to evaluate bacterial resistance risk and the potential impact of environmental heavy metal contamination. Genes in plasmid clusters showing strong homology (identity > 70%, subject coverage > 70%, E-value < 1e-5) to known biocide and heavy metal resistance genes are listed.

Gene Name compound identity evalue qstart qend query_coverage subject_coverage group
BGLGADPG_00051 Arsenic (As) 72.1 1.4e-86 34 241 0.8631 0.8966 experiment
BGLGADPG_00059 Copper (Cu) 93.5 9.8e-54 9 116 0.9310 1.0000 experiment
BGLGADPG_00062 Copper (Cu) 99 0 1 622 1.0016 1.0000 experiment
BGLGADPG_00063 Copper (Cu) 100 2.1e-242 1 422 1.0000 1.0000 experiment
BGLGADPG_00064 Copper (Cu) 99.2 6.6e-151 1 256 1.0000 1.0000 experiment
BGLGADPG_00066 Copper (Cu) 99.4 1.4e-99 1 174 1.0000 1.0000 experiment
BGLGADPG_00068 Copper (Cu) 99.2 2.5e-66 1 127 1.0000 1.0000 experiment
BGLGADPG_00069 Copper (Cu) 99.7 2.5e-165 1 309 1.0000 1.0000 experiment
BGLGADPG_00070 Copper (Cu) 71.9 0 1 808 1.0124 1.0582 experiment
AHMHBELD_00051 Arsenic (As) 72.1 1.4e-86 34 241 0.8631 0.8966 experiment
AHMHBELD_00059 Copper (Cu) 93.5 9.8e-54 9 116 0.9310 1.0000 experiment
AHMHBELD_00062 Copper (Cu) 99 0 1 622 1.0016 1.0000 experiment
AHMHBELD_00063 Copper (Cu) 100 2.1e-242 1 422 1.0000 1.0000 experiment
AHMHBELD_00064 Copper (Cu) 99.2 6.6e-151 1 256 1.0000 1.0000 experiment
AHMHBELD_00066 Copper (Cu) 99.4 1.4e-99 1 174 1.0000 1.0000 experiment
AHMHBELD_00068 Copper (Cu) 99.2 2.5e-66 1 127 1.0000 1.0000 experiment
AHMHBELD_00069 Copper (Cu) 99.7 2.5e-165 1 309 1.0000 1.0000 experiment
AHMHBELD_00070 Copper (Cu) 71.9 0 1 808 1.0124 1.0582 experiment
BGLGADPG_00051 Arsenic (As) 74.4 1.1e-95 8 241 0.9710 0.9873 prediction
BGLGADPG_00059 Copper (Cu) 100 2e-60 1 116 1.0000 1.0000 prediction
BGLGADPG_00062 Copper (Cu), Silver (Ag) 100 0 1 622 1.0000 1.0000 prediction
BGLGADPG_00063 Copper (Cu) 100 4.7e-240 1 422 1.0000 1.0000 prediction
BGLGADPG_00064 Copper (Cu) 99.2 1.5e-148 1 256 1.0000 1.0000 prediction
BGLGADPG_00066 Copper (Cu) 99.4 3.1e-97 1 174 1.0000 1.0000 prediction
BGLGADPG_00068 Copper (Cu) 100 8.7e-65 1 127 1.0000 1.0000 prediction
BGLGADPG_00069 Copper (Cu) 100 1.2e-163 1 309 1.0000 1.0000 prediction
BGLGADPG_00070 Copper (Cu) 100 0 1 808 1.0000 1.0000 prediction
AHMHBELD_00051 Arsenic (As) 74.4 1.1e-95 8 241 0.9710 0.9873 prediction
AHMHBELD_00059 Copper (Cu) 100 2e-60 1 116 1.0000 1.0000 prediction
AHMHBELD_00062 Copper (Cu), Silver (Ag) 100 0 1 622 1.0000 1.0000 prediction
AHMHBELD_00063 Copper (Cu) 100 4.7e-240 1 422 1.0000 1.0000 prediction
AHMHBELD_00064 Copper (Cu) 99.2 1.5e-148 1 256 1.0000 1.0000 prediction
AHMHBELD_00066 Copper (Cu) 99.4 3.1e-97 1 174 1.0000 1.0000 prediction
AHMHBELD_00068 Copper (Cu) 100 8.7e-65 1 127 1.0000 1.0000 prediction
AHMHBELD_00069 Copper (Cu) 100 1.2e-163 1 309 1.0000 1.0000 prediction
AHMHBELD_00070 Copper (Cu) 100 0 1 808 1.0000 1.0000 prediction






        Analyzing antimicrobial resistance genes to assess bacterial resistance to antibiotics and other antimicrobial agents


This table presents antimicrobial resistance genes identified within the plasmid cluster.
      Note: Antimicrobial resistance was performed using CARD. Genes in plasmid clusters showing strong homology (identity > 70%, coverage > 70%, E-value < 1e-5) to known antimicrobial resistance genes are listed.

Gene Name aro_accession identity evalue qstart qend query_coverage subject_coverage drug_class amr_gene_family resistance_mechanism






Analysis of pathogenicity genes to explore pathogen-host interactions


This table presents host pathogen-host interactions within the plasmid cluster.
      Note: Analyzing pathogenicity-related genes using PHI-base to understand pathogen virulence mechanisms and their impact on host interactions. Genes in plasmid clusters showing strong homology (identity > 70%, subject coverage > 70%, and E-value < 1e-5) to known pathogenicity-related genes are listed.

Gene Name phi_molconn_id host gene_name identity evalue qstart qend query_coverage subject_coverage host_descripton disease_name function phenotype_of_mutant






        Analyzing carbohydrate-active enzyme genes to uncover mechanisms of nutrient degradation


This table presents carbohydrate-active enzyme genes identified within the plasmid cluster.
      Note: Annotation of carbohydrate-active enzyme genes was performed using CAZy to explore mechanisms of nutrient breakdown and utilization. Genes in plasmid clusters showing strong homology (identity > 70%, subject coverage > 70%, and E-value < 1e−5) to known CAZyme genes are listed.

Gene Name cazy_id identity evalue qstart qend query_coverage subject_coverage
BGLGADPG_00186 APR27220.1|GH73 100 2.82e-188 1 268 1 1
AHMHBELD_00186 APR27220.1|GH73 100 2.82e-188 1 268 1 1





        Analyzing transport proteins to understand bacterial strategies for substrate uptake and detoxification


This table presents transport proteins within the plasmid cluster.
      Note: Investigation of transport proteins based on TCDB to uncover bacterial mechanisms of substrate transport and environmental detoxification. Genes in plasmid clusters showing strong homology (identity > 70%, subject coverage > 70%, and E-value < 1e−5) to known transport protein entries are listed.

Gene Name tcid identity evalue qstart qend query_coverage subject_coverage class_field class_term subclass subclass_term family family_term
BGLGADPG_00048 2.A.6.1.19 75.5 0 1 1056 0.9915 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
BGLGADPG_00063 1.B.76.1.1 100 7.7e-241 1 422 1.0000 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.76 The Copper Resistance Putative Porin (CopB) Family
AHMHBELD_00048 2.A.6.1.19 75.5 0 1 1056 0.9915 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
AHMHBELD_00063 1.B.76.1.1 100 7.7e-241 1 422 1.0000 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.76 The Copper Resistance Putative Porin (CopB) Family