Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C694
  Reference Plasmid   NZ_CP048383.1
  Reference Plasmid Size   254268
  Reference Plasmid GC Content   0.52
  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
M0172733 DIBNBMMM_00178 168110 3 Gut 0.43 protein_coding missense_variant MODERATE 280A>G Thr94Ala






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
DIBNBMMM_00072 VFG034679 Ibes 72.1 2.3e-183 1 459 0.9957 0.9978 Invasion Cu(+)/Ag(+) efflux RND transporter outer membrane channel CusC experiment
DIBNBMMM_00072 VFG034652 Ibes 72.1 4.6e-183 1 459 0.9957 0.9978 Invasion Cu(+)/Ag(+) efflux RND transporter outer membrane channel CusC prediction







        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
DIBNBMMM_00039 Arsenic (As), Antimony (Sb), Bismuth (Bi) 100 8.1e-64 1 117 1.0000 1.0000 experiment
DIBNBMMM_00040 Arsenic (As), Antimony (Sb) 98.3 1.6e-67 1 120 1.0000 1.0000 experiment
DIBNBMMM_00041 Arsenic (As), Antimony (Sb) 99.1 0 1 583 1.0000 1.0000 experiment
DIBNBMMM_00042 Arsenic (As), Antimony (Sb) 99.5 2e-232 1 429 1.0000 1.0000 experiment
DIBNBMMM_00043 Arsenic (As), Antimony (Sb) 99.3 3.5e-77 1 141 1.0000 1.0000 experiment
DIBNBMMM_00053 Mercury (Hg) 100 1.3e-41 1 78 1.0000 1.0000 experiment
DIBNBMMM_00054 Mercury (Hg) 100 1.9e-63 1 121 1.0000 1.0000 experiment
DIBNBMMM_00055 Mercury (Hg) 98.4 5.00000000001703e-313 1 561 1.0000 1.0000 experiment
DIBNBMMM_00056 Mercury (Hg) 100 2.7e-43 1 91 1.0000 1.0000 experiment
DIBNBMMM_00057 Mercury (Hg) 100 4.4e-62 1 116 1.0000 1.0000 experiment
DIBNBMMM_00058 Mercury (Hg) 100 7.1e-78 1 144 1.0000 1.0000 experiment
DIBNBMMM_00069 Silver (Ag) 92.3 1.4e-70 1 143 1.0000 1.0000 experiment
DIBNBMMM_00070 Silver (Ag) 94.5 8.2e-259 1 491 1.0081 0.9960 experiment
DIBNBMMM_00071 Silver (Ag) 95.2 1.1e-117 1 226 1.0088 1.0000 experiment
DIBNBMMM_00072 Silver (Ag) 99.1 1.5e-254 1 461 1.0000 1.0000 experiment
DIBNBMMM_00073 Silver (Ag) 98.9 3.1e-47 28 117 0.7692 0.9375 experiment
DIBNBMMM_00074 Silver (Ag) 98.4 3.2e-243 1 430 1.0000 1.0000 experiment
DIBNBMMM_00075 Silver (Ag) 99 0 1 1048 1.0000 1.0000 experiment
DIBNBMMM_00077 Silver (Ag) 94.2 0 1 812 1.0025 0.9879 experiment
DIBNBMMM_00082 Copper (Cu) 97 0 1 605 1.0000 1.0000 experiment
DIBNBMMM_00083 Copper (Cu) 96.3 5.6e-170 4 299 0.9900 1.0000 experiment
DIBNBMMM_00084 Copper (Cu) 100 4.9e-67 1 126 1.0000 1.0000 experiment
DIBNBMMM_00085 Copper (Cu) 96.6 2.3e-152 1 292 1.0000 0.9450 experiment
DIBNBMMM_00086 Copper (Cu) 96.5 8.7e-123 1 226 1.0000 1.0000 experiment
DIBNBMMM_00087 Copper (Cu) 95.7 2e-254 1 466 1.0000 1.0000 experiment
DIBNBMMM_00088 Copper (Cu), Silver (Ag) 85.4 9.3e-62 1 144 1.0000 1.0000 experiment
DIBNBMMM_00089 Arsenic (As), Antimony (Sb), Bismuth (Bi) 94 1.2e-59 1 117 1.0000 1.0000 experiment
DIBNBMMM_00090 Arsenic (As), Antimony (Sb) 92.5 3.2e-63 1 120 1.0000 1.0000 experiment
DIBNBMMM_00091 Arsenic (As), Antimony (Sb) 96.6 8.09999999999992e-311 1 565 0.9965 0.9691 experiment
DIBNBMMM_00154 Antimony (Sb), Arsenic (As), Glycerol [class: Alcohol] 80.6 9.9e-126 1 267 1.0037 0.9537 experiment
DIBNBMMM_00039 Arsenic (As) 100 1.9e-61 1 117 1.0000 1.0000 prediction
DIBNBMMM_00040 Arsenic (As) 100 4.4e-66 1 120 1.0000 1.0000 prediction
DIBNBMMM_00041 Arsenic (As), Antimony (Sb) 100 0 1 583 1.0000 1.0000 prediction
DIBNBMMM_00042 Arsenic (As), Antimony (Sb) 99.8 6.9e-231 1 428 0.9977 1.0000 prediction
DIBNBMMM_00043 Arsenic (As) 100 1.6e-75 1 141 1.0000 1.0000 prediction
DIBNBMMM_00053 Mercury (Hg) 100 3e-39 1 78 1.0000 1.0000 prediction
DIBNBMMM_00054 Mercury (Hg) 100 4.3e-61 1 121 1.0000 1.0000 prediction
DIBNBMMM_00055 Mercury (Hg), Phenylmercury Acetate [class: Organo-mercury] 99.6 0 1 561 1.0000 1.0000 prediction
DIBNBMMM_00056 Mercury (Hg) 98.9 1.1e-40 1 91 1.0000 1.0000 prediction
DIBNBMMM_00057 Mercury (Hg) 100 1e-59 1 116 1.0000 0.8657 prediction
DIBNBMMM_00058 Mercury (Hg) 100 1.6e-75 1 144 1.0000 1.0000 prediction
DIBNBMMM_00069 Silver (Ag) 100 8e-75 1 143 1.0000 1.0000 prediction
DIBNBMMM_00070 Silver (Ag) 99.2 6.4e-273 1 491 1.0000 0.9959 prediction
DIBNBMMM_00071 Silver (Ag) 99.6 6.6e-124 1 226 1.0000 1.0000 prediction
DIBNBMMM_00072 Silver (Ag) 99.8 2.4e-253 1 461 1.0000 1.0000 prediction
DIBNBMMM_00073 Silver (Ag) 100 1.6e-60 1 117 1.0000 1.0000 prediction
DIBNBMMM_00074 Silver (Ag) 100 3.2e-244 1 430 1.0000 1.0000 prediction
DIBNBMMM_00075 Silver (Ag) 99.9 0 1 1048 1.0000 0.9905 prediction
DIBNBMMM_00077 Silver (Ag) 99 0 1 812 1.0000 1.0000 prediction
DIBNBMMM_00082 Copper (Cu) 100 0 1 605 1.0000 1.0000 prediction
DIBNBMMM_00083 Copper (Cu) 98.3 6.6e-172 2 299 0.9967 1.0000 prediction
DIBNBMMM_00084 Copper (Cu) 100 1.1e-64 1 126 1.0000 1.0000 prediction
DIBNBMMM_00085 Copper (Cu) 98.3 8.8e-153 1 292 1.0000 0.9450 prediction
DIBNBMMM_00086 Copper (Cu) 100 1e-124 1 226 1.0000 1.0000 prediction
DIBNBMMM_00087 Copper (Cu) 100 1.1e-261 1 466 1.0000 1.0000 prediction
DIBNBMMM_00088 Copper (Cu), Silver (Ag) 88.9 6.6e-61 1 144 1.0000 1.0000 prediction
DIBNBMMM_00089 Arsenic (As) 100 8.3e-62 1 117 1.0000 1.0000 prediction
DIBNBMMM_00090 Arsenic (As) 100 4.4e-66 1 120 1.0000 1.0000 prediction
DIBNBMMM_00091 Arsenic (As), Antimony (Sb) 100 0 1 565 0.9965 0.9691 prediction
DIBNBMMM_00136 Iron (Fe), Nickel (Ni) 75.8 1.8e-117 1 256 1.0000 1.0000 prediction
DIBNBMMM_00154 Antimony (Sb), Arsenic (As), Glycerol [class: Alcohol] 81 2.7e-124 1 267 1.0037 0.9537 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





        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
DIBNBMMM_00026 2.A.33.1.2 97.1 4e-204 1 382 0.9974 0.9974 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.33 The NhaA Na+:H+ Antiporter (NhaA) Family
DIBNBMMM_00041 3.A.4.1.1 85.7 5e-283 1 581 0.9966 1.3543 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.4 The Arsenite-Antimonite (ArsAB) Efflux Family
DIBNBMMM_00042 3.A.4.1.1 93.9 1.5e-220 1 429 1.0000 1.0000 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.4 The Arsenite-Antimonite (ArsAB) Efflux Family
DIBNBMMM_00053 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
DIBNBMMM_00056 1.A.72.3.1 100 1e-41 1 91 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
DIBNBMMM_00057 1.A.72.3.1 100 1.7e-60 1 116 1.0000 1.2747 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
DIBNBMMM_00072 1.B.17.3.4 99.1 5.6e-253 1 461 1.0000 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.17 The Outer Membrane Factor (OMF) Family
DIBNBMMM_00075 2.A.6.1.3 99 0 1 1048 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
DIBNBMMM_00077 3.A.3.5.4 94.2 0 1 812 1.0000 0.9879 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.3 The P-type ATPase (P-ATPase) Superfamily
DIBNBMMM_00080 1.A.34.1.3 99.6 1.9e-135 1 245 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.34 The <i>Bacillus</i> Gap Junction-like Channel-forming Complex (GJ-CC) Family
DIBNBMMM_00083 1.B.76.1.5 96.3 2.1e-168 4 299 0.9900 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.76 The Copper Resistance Putative Porin (CopB) Family
DIBNBMMM_00085 9.B.62.1.1 96.6 8.7e-151 1 292 1.0000 0.9450 9 Incompletely Characterized Transport Systems 9.B Putative transport proteins 9.B.62 The Copper Resistance (CopD) Family
DIBNBMMM_00091 3.A.4.1.1 86.4 1.8e-277 1 565 0.9965 1.3170 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.4 The Arsenite-Antimonite (ArsAB) Efflux Family
DIBNBMMM_00154 1.A.8.1.1 80.6 3.7e-124 1 267 1.0000 0.9537 1 Channels/Pores 1.A α-Type Channels 1.A.8 The Major Intrinsic Protein (MIP) Family