Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C71
  Reference Plasmid   CP026283.1
  Reference Plasmid Size   125961
  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
M0143599 LIBGLDHH_00027 32383 3 Gut 0.30 protein_coding upstream_gene_variant MODIFIER -4987G>T None
M0143600 LIBGLDHH_00035 33194 3 Gut 0.30 protein_coding missense_variant MODERATE 160A>G Ile54Val
M0143601 LIBGLDHH_00036 33456 3 Gut 0.30 protein_coding missense_variant MODERATE 1301C>G Thr434Arg






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
LIBGLDHH_00076 VFG034679 Ibes 71.9 5.2e-183 1 459 0.9957 0.9978 Invasion Cu(+)/Ag(+) efflux RND transporter outer membrane channel CusC experiment
LIBGLDHH_00055 VFG017870 Icm/dot type IVB locus 77.9 1.6e-90 1 208 0.9905 0.9952 Effector delivery system ParA family protein prediction
LIBGLDHH_00076 VFG034652 Ibes 71.9 3e-182 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
LIBGLDHH_00064 Mercury (Hg) 96.2 2.7e-39 1 78 1.0000 1.0000 experiment
LIBGLDHH_00065 Mercury (Hg) 90.9 6.4e-56 1 121 1.0000 1.0000 experiment
LIBGLDHH_00066 Mercury (Hg) 88.6 3.8e-276 2 560 0.9982 0.9964 experiment
LIBGLDHH_00068 Mercury (Hg) 94.5 2e-41 1 91 1.0000 1.0000 experiment
LIBGLDHH_00069 Mercury (Hg) 100 8.9e-63 1 116 1.0000 1.0000 experiment
LIBGLDHH_00070 Mercury (Hg) 88.7 5.5e-73 1 151 1.0000 1.0000 experiment
LIBGLDHH_00073 Silver (Ag) 80.4 1.6e-61 1 143 1.0000 1.0000 experiment
LIBGLDHH_00074 Silver (Ag) 92.7 9.3e-255 1 491 1.0081 0.9960 experiment
LIBGLDHH_00075 Silver (Ag) 93 1e-115 1 226 1.0088 1.0000 experiment
LIBGLDHH_00076 Silver (Ag) 97.6 1e-250 1 461 1.0000 1.0000 experiment
LIBGLDHH_00077 Silver (Ag) 98.9 3.1e-47 28 117 0.7692 0.9375 experiment
LIBGLDHH_00078 Silver (Ag) 98.4 3.2e-243 1 430 1.0000 1.0000 experiment
LIBGLDHH_00079 Silver (Ag) 99.4 0 1 1048 1.0000 1.0000 experiment
LIBGLDHH_00082 Silver (Ag) 98.3 0 1 813 1.0012 0.9879 experiment
LIBGLDHH_00086 Copper (Cu) 100 0 1 605 1.0000 1.0000 experiment
LIBGLDHH_00087 Copper (Cu) 100 1.5e-175 1 296 1.0000 1.0000 experiment
LIBGLDHH_00088 Copper (Cu) 100 4.9e-67 1 126 1.0000 1.0000 experiment
LIBGLDHH_00089 Copper (Cu) 99.7 2.5e-165 1 309 1.0000 1.0000 experiment
LIBGLDHH_00090 Copper (Cu) 100 1.7e-126 1 226 1.0000 1.0000 experiment
LIBGLDHH_00091 Copper (Cu) 99.4 1.5e-262 1 466 1.0000 1.0000 experiment
LIBGLDHH_00092 Copper (Cu), Silver (Ag) 89.6 1e-63 1 144 1.0000 1.0000 experiment
LIBGLDHH_00118 Arsenic (As), Antimony (Sb) 85.1 4.8e-71 1 141 1.0000 1.0000 experiment
LIBGLDHH_00119 Arsenic (As) 90.9 1.6e-213 5 433 0.9908 1.0000 experiment
LIBGLDHH_00120 Arsenic (As) 91 1.7e-45 1 89 0.7607 0.7607 experiment
LIBGLDHH_00121 Arsenic (As) 91.4 4.3e-125 1 232 1.0000 1.0000 experiment
LIBGLDHH_00064 Mercury (Hg) 98.7 5.1e-39 1 78 1.0000 1.0000 prediction
LIBGLDHH_00065 Mercury (Hg) 99.2 4e-59 1 121 1.0000 1.0000 prediction
LIBGLDHH_00066 Mercury (Hg), Phenylmercury Acetate [class: Organo-mercury] 100 4.69999999999822e-312 1 560 1.0000 1.0000 prediction
LIBGLDHH_00068 Mercury (Hg) 100 3.7e-41 1 91 1.0000 1.0000 prediction
LIBGLDHH_00069 Mercury (Hg) 100 2e-60 1 116 1.0000 1.0000 prediction
LIBGLDHH_00070 Mercury (Hg) 99.3 7.9e-81 1 151 1.0000 1.0000 prediction
LIBGLDHH_00073 Silver (Ag) 83.2 1.3e-61 1 143 1.0000 1.0000 prediction
LIBGLDHH_00074 Silver (Ag) 100 8.1e-276 1 491 1.0000 1.0000 prediction
LIBGLDHH_00075 Silver (Ag) 100 1.7e-124 1 226 1.0000 0.9658 prediction
LIBGLDHH_00076 Silver (Ag) 100 1.6e-254 1 461 1.0000 0.8986 prediction
LIBGLDHH_00077 Silver (Ag) 100 1.6e-60 1 117 1.0000 1.0000 prediction
LIBGLDHH_00078 Silver (Ag) 100 3.2e-244 1 430 1.0000 1.0000 prediction
LIBGLDHH_00079 Silver (Ag) 100 0 1 1048 1.0000 1.0000 prediction
LIBGLDHH_00082 Silver (Ag) 100 0 1 813 1.0000 1.0000 prediction
LIBGLDHH_00086 Copper (Cu) 100 0 1 605 1.0000 0.9967 prediction
LIBGLDHH_00087 Copper (Cu) 100 3.5e-173 1 296 1.0000 0.9900 prediction
LIBGLDHH_00088 Copper (Cu) 100 1.1e-64 1 126 1.0000 1.0000 prediction
LIBGLDHH_00089 Copper (Cu) 100 4.4e-163 1 309 1.0000 1.0000 prediction
LIBGLDHH_00090 Copper (Cu) 100 3.9e-124 1 226 1.0000 0.9741 prediction
LIBGLDHH_00091 Copper (Cu) 100 3.7e-262 1 466 1.0000 1.0000 prediction
LIBGLDHH_00092 Copper (Cu), Silver (Ag) 99.3 6e-70 1 144 1.0000 1.0000 prediction
LIBGLDHH_00118 Arsenic (As) 87.9 1.3e-69 1 141 1.0000 1.0000 prediction
LIBGLDHH_00119 Arsenic (As), Antimony (Sb) 99.3 4.1e-231 1 433 1.0000 0.9516 prediction
LIBGLDHH_00120 Arsenic (As) 95.3 9.9e-55 1 106 0.9060 1.0000 prediction
LIBGLDHH_00121 Arsenic (As) 100 8.6e-135 1 232 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
LIBGLDHH_00129 PHI:6268 lacZ 96.5 0 1 1024 1.0000 1.0000 rodents urinary tract infection beta-galactosidase 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
LIBGLDHH_00129 ATM08382.1|GH2 100 0 1 1024 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
LIBGLDHH_00025 2.A.53.3.1 74.4 2.8e-202 1 496 1.0000 0.9980 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.53 The Sulfate Permease (SulP) Family
LIBGLDHH_00064 1.A.72.5.1 80.8 7.5e-33 1 78 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
LIBGLDHH_00068 1.A.72.3.1 94.5 7.4e-40 1 91 1.0000 1.0000 1 Channels/Pores 1.A α-Type Channels 1.A.72 The Mercuric Ion Pore (Mer) Superfamily
LIBGLDHH_00069 1.A.72.3.1 94 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
LIBGLDHH_00076 1.B.17.3.4 97.6 3.8e-249 1 461 1.0000 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.17 The Outer Membrane Factor (OMF) Family
LIBGLDHH_00079 2.A.6.1.3 99.4 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
LIBGLDHH_00082 3.A.3.5.4 98.3 0 1 813 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
LIBGLDHH_00084 1.A.34.1.3 100 1.1e-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
LIBGLDHH_00087 1.B.76.1.5 100 5.7e-174 1 296 1.0000 1.0000 1 Channels/Pores 1.B β-Barrel Porins 1.B.76 The Copper Resistance Putative Porin (CopB) Family
LIBGLDHH_00089 9.B.62.1.1 99.7 9.5e-164 1 309 1.0000 1.0000 9 Incompletely Characterized Transport Systems 9.B Putative transport proteins 9.B.62 The Copper Resistance (CopD) Family
LIBGLDHH_00119 3.A.4.1.1 88.1 2.5e-210 5 433 0.9908 1.0000 3 Primary Active Transporters 3.A P-P-bond-hydrolysis-driven transporters 3.A.4 The Arsenite-Antimonite (ArsAB) Efflux Family
LIBGLDHH_00123 2.A.51.1.7 77.4 6.3e-168 1 376 0.9377 0.9666 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.51 The Chromate Ion Transporter (CHR) Family
LIBGLDHH_00130 2.A.1.5.1 99.3 2.1e-230 1 416 0.9976 0.9976 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.1 The Major Facilitator Superfamily (MFS)