Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C706
  Reference Plasmid   NZ_CP049911.1
  Reference Plasmid Size   242290
  Reference Plasmid GC Content   0.58
  Reference Plasmid Mobility Type   non-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
M0099074 IKFCJDKM_00142 137012 10 Skin 0.20 protein_coding upstream_gene_variant MODIFIER -4648T>G None






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
IKFCJDKM_00132 Mercury (Hg) 100 1.7e-79 1 144 1.0000 1.0000 experiment
IKFCJDKM_00133 Mercury (Hg) 99.1 6.8e-63 1 116 1.0000 1.0000 experiment
IKFCJDKM_00134 Mercury (Hg) 100 2.7e-43 1 91 1.0000 1.0000 experiment
IKFCJDKM_00135 Mercury (Hg) 90.9 3.3e-288 1 561 1.0000 1.0000 experiment
IKFCJDKM_00136 Mercury (Hg) 98.3 7.8e-62 1 121 1.0000 1.0000 experiment
IKFCJDKM_00137 Mercury (Hg) 100 1.3e-41 1 78 1.0000 1.0000 experiment
EPAGMEJK_00132 Mercury (Hg) 100 1.7e-79 1 144 1.0000 1.0000 experiment
EPAGMEJK_00133 Mercury (Hg) 99.1 6.8e-63 1 116 1.0000 1.0000 experiment
EPAGMEJK_00134 Mercury (Hg) 100 2.7e-43 1 91 1.0000 1.0000 experiment
EPAGMEJK_00135 Mercury (Hg) 90.9 3.3e-288 1 561 1.0000 1.0000 experiment
EPAGMEJK_00136 Mercury (Hg) 98.3 7.8e-62 1 121 1.0000 1.0000 experiment
EPAGMEJK_00137 Mercury (Hg) 100 1.3e-41 1 78 1.0000 1.0000 experiment
IKFCJDKM_00014 Mercury (Hg) 92.4 1.2e-249 117 618 0.5180 0.8355 prediction
IKFCJDKM_00015 Mercury (Hg) 82.1 9.6e-229 121 633 0.8123 0.8555 prediction
IKFCJDKM_00032 Mercury (Hg) 83.5 8.8e-228 121 622 0.5612 0.8372 prediction
IKFCJDKM_00037 Mercury (Hg) 100 3.9e-44 6 99 0.9495 1.0000 prediction
IKFCJDKM_00038 Mercury (Hg) 70.8 9.3e-36 1 106 1.0000 0.8618 prediction
IKFCJDKM_00039 Mercury (Hg) 81.7 1.4e-50 12 137 0.8690 0.9065 prediction
IKFCJDKM_00099 Benzylkonium Chloride (BAC) [class: Quaternary Ammonium Compounds (QACs)], Ethidium Bromide [class: Phenanthridine], Acriflavine [class: Acridine], Chlorhexidine [class: Biguanides], Pyronin Y [class: Xanthene], Rhodamine 6G [class: Xanthene], Methyl Viologen [class: Paraquat], Tetraphenylphosphonium (TPP) [class: Quaternary Ammonium Compounds (QACs)], 4,6-diamidino-2-phenylindole (DAPI) [class: Diamindine], Acridine Orange [class: Acridine], Sodium Dodecyl Sulfate (SDS) [class: Organo-sulfate], Sodium Deoxycholate (SDC) [class: Acid], Crystal Violet [class: Triarylmethane], Cetrimide (CTM) [class: Quaternary Ammonium Compounds (QACs)], Cetylpyridinium Chloride (CPC) [class: Quaternary Ammonium Compounds (QACs)], Dequalinium [class: Quaternary Ammonium Compounds (QACs)] 84.5 1.1e-44 1 110 1.0000 1.0000 prediction
IKFCJDKM_00132 Mercury (Hg) 100 3.9e-77 1 144 1.0000 1.0000 prediction
IKFCJDKM_00133 Mercury (Hg) 100 7e-61 1 116 1.0000 1.0000 prediction
IKFCJDKM_00134 Mercury (Hg) 100 6.3e-41 1 91 1.0000 1.0000 prediction
IKFCJDKM_00135 Mercury (Hg), Phenylmercury Acetate [class: Organo-mercury] 100 0 1 561 1.0000 1.0000 prediction
IKFCJDKM_00136 Mercury (Hg) 100 1.6e-60 1 121 1.0000 1.0000 prediction
IKFCJDKM_00137 Mercury (Hg) 100 3e-39 1 78 1.0000 1.0000 prediction
IKFCJDKM_00168 Mercury (Hg) 92.4 1.2e-249 117 618 0.5180 0.8355 prediction
IKFCJDKM_00247 Mercury (Hg) 83.5 6.5e-228 121 622 0.7556 0.8372 prediction
EPAGMEJK_00014 Mercury (Hg) 92.4 1.2e-249 117 618 0.5180 0.8355 prediction
EPAGMEJK_00015 Mercury (Hg) 82.1 9.6e-229 121 633 0.8123 0.8555 prediction
EPAGMEJK_00032 Mercury (Hg) 83.5 8.8e-228 121 622 0.5612 0.8372 prediction
EPAGMEJK_00037 Mercury (Hg) 100 3.9e-44 6 99 0.9495 1.0000 prediction
EPAGMEJK_00038 Mercury (Hg) 70.8 9.3e-36 1 106 1.0000 0.8618 prediction
EPAGMEJK_00039 Mercury (Hg) 81.7 1.4e-50 12 137 0.8690 0.9065 prediction
EPAGMEJK_00099 Benzylkonium Chloride (BAC) [class: Quaternary Ammonium Compounds (QACs)], Ethidium Bromide [class: Phenanthridine], Acriflavine [class: Acridine], Chlorhexidine [class: Biguanides], Pyronin Y [class: Xanthene], Rhodamine 6G [class: Xanthene], Methyl Viologen [class: Paraquat], Tetraphenylphosphonium (TPP) [class: Quaternary Ammonium Compounds (QACs)], 4,6-diamidino-2-phenylindole (DAPI) [class: Diamindine], Acridine Orange [class: Acridine], Sodium Dodecyl Sulfate (SDS) [class: Organo-sulfate], Sodium Deoxycholate (SDC) [class: Acid], Crystal Violet [class: Triarylmethane], Cetrimide (CTM) [class: Quaternary Ammonium Compounds (QACs)], Cetylpyridinium Chloride (CPC) [class: Quaternary Ammonium Compounds (QACs)], Dequalinium [class: Quaternary Ammonium Compounds (QACs)] 84.5 1.1e-44 1 110 1.0000 1.0000 prediction
EPAGMEJK_00132 Mercury (Hg) 100 3.9e-77 1 144 1.0000 1.0000 prediction
EPAGMEJK_00133 Mercury (Hg) 100 7e-61 1 116 1.0000 1.0000 prediction
EPAGMEJK_00134 Mercury (Hg) 100 6.3e-41 1 91 1.0000 1.0000 prediction
EPAGMEJK_00135 Mercury (Hg), Phenylmercury Acetate [class: Organo-mercury] 100 0 1 561 1.0000 1.0000 prediction
EPAGMEJK_00136 Mercury (Hg) 100 1.6e-60 1 121 1.0000 1.0000 prediction
EPAGMEJK_00137 Mercury (Hg) 100 3e-39 1 78 1.0000 1.0000 prediction
EPAGMEJK_00168 Mercury (Hg) 92.4 1.2e-249 117 618 0.5180 0.8355 prediction
EPAGMEJK_00247 Mercury (Hg) 83.5 6.5e-228 121 622 0.7556 0.8372 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
IKFCJDKM_00142 ARO:3000410 100 2e-198 6 283 0.9823 0.9964 sulfonamide antibiotic sulfonamide resistant sul antibiotic target replacement
IKFCJDKM_00146 ARO:3000174 94.6 2.91e-260 1 391 1.0000 1.0000 tetracycline antibiotic major facilitator superfamily (MFS) antibiotic efflux pump antibiotic efflux
IKFCJDKM_00148 ARO:3002660 99.6 1.07e-205 1 278 1.0000 1.0000 aminoglycoside antibiotic APH(6) antibiotic inactivation
IKFCJDKM_00152 ARO:3005043 100 4.13e-278 1 404 1.0000 1.0000 phenicol antibiotic major facilitator superfamily (MFS) antibiotic efflux pump antibiotic efflux
EPAGMEJK_00142 ARO:3000410 100 2e-198 6 283 0.9823 0.9964 sulfonamide antibiotic sulfonamide resistant sul antibiotic target replacement
EPAGMEJK_00146 ARO:3000174 94.6 2.91e-260 1 391 1.0000 1.0000 tetracycline antibiotic major facilitator superfamily (MFS) antibiotic efflux pump antibiotic efflux
EPAGMEJK_00148 ARO:3002660 99.6 1.07e-205 1 278 1.0000 1.0000 aminoglycoside antibiotic APH(6) antibiotic inactivation
EPAGMEJK_00152 ARO:3005043 100 4.13e-278 1 404 1.0000 1.0000 phenicol antibiotic major facilitator superfamily (MFS) antibiotic efflux pump antibiotic efflux






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
IKFCJDKM_00154 PHI:9804 int 97.3 1.2e-13 1 37 0.1098 1.0000 rodents gastroenteritis integrase reduced virulence
EPAGMEJK_00154 PHI:9804 int 97.3 1.2e-13 1 37 0.1098 1.0000 rodents gastroenteritis integrase 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
IKFCJDKM_00220 QIL84344.1|GH23 100 3.41e-108 1 159 1 1
EPAGMEJK_00220 QIL84344.1|GH23 100 3.41e-108 1 159 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
IKFCJDKM_00133 1.A.72.3.1 92.2 6.5e-57 1 116 1.0000 1.2747 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
IKFCJDKM_00134 1.A.72.3.1 94.5 2.2e-39 1 91 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
IKFCJDKM_00137 1.A.72.5.1 76 3e-29 1 75 0.9615 0.9615 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
IKFCJDKM_00152 2.A.1.2.110 92.8 4e-202 1 404 1.0000 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.1 The Major Facilitator Superfamily (MFS)
EPAGMEJK_00133 1.A.72.3.1 92.2 6.5e-57 1 116 1.0000 1.2747 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
EPAGMEJK_00134 1.A.72.3.1 94.5 2.2e-39 1 91 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
EPAGMEJK_00137 1.A.72.5.1 76 3e-29 1 75 0.9615 0.9615 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
EPAGMEJK_00152 2.A.1.2.110 92.8 4e-202 1 404 1.0000 1.0000 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.1 The Major Facilitator Superfamily (MFS)