Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C238
  Reference Plasmid   KR827394.1
  Reference Plasmid Size   222486
  Reference Plasmid GC Content   0.55
  Reference Plasmid Mobility Type   conjugative





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
M0071126 BKPKMKFO_00167 137254 3 Skin 0.38 protein_coding synonymous_variant LOW 1476A>G Val492Val
M0071127 BKPKMKFO_00167 137419 3 Skin 0.38 protein_coding synonymous_variant LOW 1311C>G Ala437Ala
M0071128 BKPKMKFO_00167 137452 3 Skin 0.38 protein_coding synonymous_variant LOW 1278A>G Thr426Thr
M0071129 BKPKMKFO_00166 141100 4 Skin 0.50 protein_coding upstream_gene_variant MODIFIER -4882C>T None
M0071130 BKPKMKFO_00172 142426 4 Skin 0.50 protein_coding missense_variant MODERATE 121T>C Cys41Arg






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
BKPKMKFO_00166 Gold (Au) 76.1 1.8e-61 1 155 0.9748 1.0065 experiment
BKPKMKFO_00167 Copper (Cu), Gold (Au) 84.3 0 82 826 0.8965 0.9777 experiment
BKPKMKFO_00185 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 76.5 0 1 1032 0.9981 0.9990 experiment
BKPKMKFO_00186 Cobalt (Co), Nickel (Ni) 72.4 2.3e-173 14 467 0.9560 0.9520 experiment
BKPKMKFO_00186 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 72.4 2.3e-173 14 467 0.9560 0.9520 experiment
LOMEBGJK_00166 Gold (Au) 76.1 1.8e-61 1 155 0.9748 1.0065 experiment
LOMEBGJK_00167 Copper (Cu), Gold (Au) 84.3 0 82 826 0.8965 0.9777 experiment
LOMEBGJK_00185 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 76.5 0 1 1032 0.9981 0.9990 experiment
LOMEBGJK_00186 Cobalt (Co), Nickel (Ni) 72.4 2.3e-173 14 467 0.9560 0.9520 experiment
LOMEBGJK_00186 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 72.4 2.3e-173 14 467 0.9560 0.9520 experiment
BKPKMKFO_00166 Gold (Au) 76.8 1.1e-59 1 155 0.9748 1.0065 prediction
BKPKMKFO_00167 Copper (Cu), Gold (Au) 99.6 0 1 831 1.0000 1.0000 prediction
BKPKMKFO_00169 Nickel (Ni), Cobalt (Co) 100 7.3e-236 1 436 1.0000 1.0000 prediction
BKPKMKFO_00184 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 97.7 1.9e-203 1 387 1.0000 1.0000 prediction
BKPKMKFO_00185 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 100 0 1 1044 1.0000 1.0000 prediction
BKPKMKFO_00186 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 100 5.8e-255 1 477 1.0000 1.0000 prediction
LOMEBGJK_00166 Gold (Au) 76.8 1.1e-59 1 155 0.9748 1.0065 prediction
LOMEBGJK_00167 Copper (Cu), Gold (Au) 99.6 0 1 831 1.0000 1.0000 prediction
LOMEBGJK_00169 Nickel (Ni), Cobalt (Co) 100 7.3e-236 1 436 1.0000 1.0000 prediction
LOMEBGJK_00184 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 97.7 1.9e-203 1 387 1.0000 1.0000 prediction
LOMEBGJK_00185 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 100 0 1 1044 1.0000 1.0000 prediction
LOMEBGJK_00186 Triclosan [class: Phenolic compounds], n-hexane [class: Alkane], p-xylene [class: Aromatic hydrocarbons] 100 5.8e-255 1 477 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
BKPKMKFO_00166 ARO:3000504 79.5 3.69e-78 1 146 0.9182 0.9481 monobactam resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
BKPKMKFO_00185 ARO:3000801 76.4 0 1 1032 0.9981 0.9990 macrolide antibiotic resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
BKPKMKFO_00186 ARO:3000802 72.8 3.75e-211 19 465 0.9413 0.9374 macrolide antibiotic resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
BKPKMKFO_00190 ARO:3002791 100 2.73e-112 1 218 1.0000 1.0000 fluoroquinolone antibiotic quinolone resistance protein (qnr) antibiotic target protection
BKPKMKFO_00198 ARO:3000412 100 4.11e-186 1 271 1.0000 1.0000 sulfonamide antibiotic sulfonamide resistant sul antibiotic target replacement
LOMEBGJK_00166 ARO:3000504 79.5 3.69e-78 1 146 0.9182 0.9481 monobactam resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
LOMEBGJK_00185 ARO:3000801 76.4 0 1 1032 0.9981 0.9990 macrolide antibiotic resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
LOMEBGJK_00186 ARO:3000802 72.8 3.75e-211 19 465 0.9413 0.9374 macrolide antibiotic resistance-nodulation-cell division (RND) antibiotic efflux pump antibiotic efflux
LOMEBGJK_00190 ARO:3002791 100 2.73e-112 1 218 1.0000 1.0000 fluoroquinolone antibiotic quinolone resistance protein (qnr) antibiotic target protection
LOMEBGJK_00198 ARO:3000412 100 4.11e-186 1 271 1.0000 1.0000 sulfonamide antibiotic sulfonamide resistant sul antibiotic target replacement






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
BKPKMKFO_00046 PHI:11406 dsbC 97 3.6e-131 1 235 1.0000 1.0000 rodents pneumonia thiol:disulfide interchange protein reduced virulence
BKPKMKFO_00098 PHI:11588 PPECC33_0249 (Rhs1) 93.4 0 1 1295 0.9120 0.9104 primates infection classic rearrangement hotspot protein reduced virulence
LOMEBGJK_00046 PHI:11406 dsbC 97 3.6e-131 1 235 1.0000 1.0000 rodents pneumonia thiol:disulfide interchange protein reduced virulence
LOMEBGJK_00098 PHI:11588 PPECC33_0249 (Rhs1) 93.4 0 1 1295 0.9120 0.9104 primates infection classic rearrangement hotspot protein reduced virulence






        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
BKPKMKFO_00114 AIO10552.2|GH23 100 6.52e-238 9 346 0.9769 1
BKPKMKFO_00116 AIO10245.2|GH23 100 0 1 1204 1 1
BKPKMKFO_00119 QDC33125.1|GH23 100 5.28e-123 1 177 1 1
LOMEBGJK_00114 AIO10552.2|GH23 100 6.52e-238 9 346 0.9769 1
LOMEBGJK_00116 AIO10245.2|GH23 100 0 1 1204 1 1
LOMEBGJK_00119 QDC33125.1|GH23 100 5.28e-123 1 177 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
BKPKMKFO_00167 3.A.3.5.20 84.3 0 82 826 0.8965 0.9777 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.3 The P-type ATPase (P-ATPase) Superfamily
BKPKMKFO_00184 2.A.6.2.15 86.9 1.8e-180 1 387 1.0000 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
BKPKMKFO_00185 2.A.6.2.15 76.5 0 1 1032 0.9885 2.6462 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
BKPKMKFO_00186 2.A.6.2.15 72.4 8.6e-172 14 467 0.9518 1.1692 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
LOMEBGJK_00167 3.A.3.5.20 84.3 0 82 826 0.8965 0.9777 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.3 The P-type ATPase (P-ATPase) Superfamily
LOMEBGJK_00184 2.A.6.2.15 86.9 1.8e-180 1 387 1.0000 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
LOMEBGJK_00185 2.A.6.2.15 76.5 0 1 1032 0.9885 2.6462 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily
LOMEBGJK_00186 2.A.6.2.15 72.4 8.6e-172 14 467 0.9518 1.1692 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.6 The Resistance-Nodulation-Cell Division (RND) Superfamily