Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C950
  Reference Plasmid   NZ_CP083572.1
  Reference Plasmid Size   138030
  Reference Plasmid GC Content   0.41
  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
M0104921 BEJFFNDL_00027 32798 4 Skin 0.15 protein_coding missense_variant MODERATE 215C>T Thr72Met
M0104922 BEJFFNDL_00027 32803 4 Skin 0.15 protein_coding missense_variant MODERATE 220T>G Leu74Val
M0104923 BEJFFNDL_00027 32926 4 Skin 0.15 protein_coding missense_variant MODERATE 343A>G Lys115Glu
M0104924 BEJFFNDL_00028 33146 5 Skin 0.19 protein_coding missense_variant MODERATE 146T>C Leu49Pro
M0104925 BEJFFNDL_00028 33314 3 Skin 0.11 protein_coding missense_variant MODERATE 314G>A Arg105Gln
M0104926 BEJFFNDL_00028 33437 5 Skin 0.19 protein_coding missense_variant MODERATE 437C>T Ala146Val
M0104927 BEJFFNDL_00028 33449 5 Skin 0.19 protein_coding missense_variant MODERATE 449A>T Gln150Leu
M0104928 BEJFFNDL_00028 33532 5 Skin 0.19 protein_coding missense_variant MODERATE 532A>G Thr178Ala
M0104929 BEJFFNDL_00028 33568 5 Skin 0.19 protein_coding missense_variant MODERATE 568C>G Gln190Glu
M0104930 BEJFFNDL_00028 33841 5 Skin 0.19 protein_coding missense_variant MODERATE 841G>A Glu281Lys
M0104931 BEJFFNDL_00028 33985 6 Skin 0.22 protein_coding missense_variant MODERATE 985A>G Asn329Asp
M0104932 BEJFFNDL_00028 34088 6 Skin 0.22 protein_coding missense_variant MODERATE 1088T>A Leu363Gln
M0104933 BEJFFNDL_00028 34175 6 Skin 0.22 protein_coding missense_variant MODERATE 1175C>T Thr392Ile
M0104934 BEJFFNDL_00029 34449 5 Skin 0.19 protein_coding missense_variant MODERATE 122A>G His41Arg
M0104935 BEJFFNDL_00029 34475 6 Skin 0.22 protein_coding missense_variant MODERATE 148T>C Tyr50His
M0104936 BEJFFNDL_00029 34477 4 Skin 0.15 protein_coding stop_gained HIGH 150T>G Tyr50*
M0104937 BEJFFNDL_00029 34484 4 Skin 0.15 protein_coding missense_variant MODERATE 157G>A Glu53Lys
M0104938 BEJFFNDL_00029 34648 3 Skin 0.11 protein_coding missense_variant MODERATE 321T>G His107Gln
M0104939 BEJFFNDL_00029 34682 6 Skin 0.22 protein_coding missense_variant MODERATE 355A>G Ile119Val
M0104940 BEJFFNDL_00029 34737 6 Skin 0.22 protein_coding missense_variant MODERATE 410C>T Thr137Ile
M0104941 BEJFFNDL_00029 34844 6 Skin 0.22 protein_coding missense_variant MODERATE 517G>A Val173Ile
M0104942 BEJFFNDL_00029 35000 6 Skin 0.22 protein_coding missense_variant MODERATE 673C>A Gln225Lys
M0104943 BEJFFNDL_00030 35922 3 Skin 0.11 protein_coding missense_variant MODERATE 376A>G Ile126Val
M0104944 BEJFFNDL_00030 36564 5 Skin 0.19 protein_coding missense_variant MODERATE 1018C>A Pro340Thr
M0104945 BEJFFNDL_00030 37221 5 Skin 0.19 protein_coding missense_variant MODERATE 1675T>G Leu559Val
M0104946 BEJFFNDL_00030 37353 5 Skin 0.19 protein_coding missense_variant MODERATE 1807G>A Glu603Lys
M0104947 BEJFFNDL_00030 37428 5 Skin 0.19 protein_coding missense_variant MODERATE 1882A>G Ile628Val
M0104948 BEJFFNDL_00030 38303 3 Skin 0.11 protein_coding synonymous_variant LOW 2757C>T Pro919Pro
M0104949 BEJFFNDL_00031 39115 3 Skin 0.11 protein_coding synonymous_variant LOW 342T>C Asn114Asn
M0104950 BEJFFNDL_00031 39138 3 Skin 0.11 protein_coding missense_variant MODERATE 365G>A Gly122Glu
M0104951 BEJFFNDL_00031 39157 5 Skin 0.19 protein_coding synonymous_variant LOW 384T>C Val128Val
M0104952 BEJFFNDL_00031 39158 5 Skin 0.19 protein_coding missense_variant MODERATE 385G>A Gly129Ser
M0104953 BEJFFNDL_00031 39159 5 Skin 0.19 protein_coding missense_variant MODERATE 386G>T Gly129Val
M0104954 BEJFFNDL_00031 39170 4 Skin 0.15 protein_coding missense_variant MODERATE 397A>G Ile133Val
M0104955 BEJFFNDL_00031 39395 5 Skin 0.19 protein_coding missense_variant MODERATE 622C>A His208Asn
M0104956 BEJFFNDL_00031 39513 3 Skin 0.11 protein_coding missense_variant MODERATE 740G>A Arg247Lys
M0104957 BEJFFNDL_00029 34673 3 Skin 0.11 protein_coding missense_variant MODERATE 346G>A Val116Ile
M0104958 BEJFFNDL_00029 34739 5 Skin 0.19 protein_coding missense_variant MODERATE 412G>C Val138Leu
M0104959 BEJFFNDL_00090 93722 3 Skin 0.11 protein_coding upstream_gene_variant MODIFIER -798A>T None
M0104960 BEJFFNDL_00092 94028 3 Skin 0.11 protein_coding missense_variant MODERATE 283G>A Gly95Ser
M0104961 BEJFFNDL_00093 94463 3 Skin 0.11 protein_coding missense_variant MODERATE 304C>A His102Asn
M0104962 BEJFFNDL_00093 94897 3 Skin 0.11 protein_coding synonymous_variant LOW 738C>T Gly246Gly
M0104963 BEJFFNDL_00110 120888 3 Skin 0.11 protein_coding upstream_gene_variant MODIFIER -3741T>G None
M0104964 BEJFFNDL_00110 120931 3 Skin 0.11 protein_coding upstream_gene_variant MODIFIER -3784A>C 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
BEJFFNDL_00043 Mercury (Hg) 90.9 6.4e-56 1 121 1.0000 1.0000 experiment
BEJFFNDL_00044 Mercury (Hg) 91.1 4.6e-290 1 561 1.0000 1.0000 experiment
BEJFFNDL_00045 Mercury (Hg) 79.4 3.5e-61 1 141 1.0000 1.0000 experiment
BEJFFNDL_00048 Mercury (Hg) 88.7 5.5e-73 1 151 1.0000 1.0000 experiment
BEJFFNDL_00034 Arsenic (As) 100 9e-230 1 387 1.0000 1.0000 prediction
BEJFFNDL_00036 Arsenic (As) 75.5 1e-98 3 234 0.9957 0.9708 prediction
BEJFFNDL_00037 Arsenic (As) 94.2 2.5e-178 1 346 1.0000 1.0000 prediction
BEJFFNDL_00043 Mercury (Hg) 99.2 4e-59 1 121 1.0000 1.0000 prediction
BEJFFNDL_00044 Mercury (Hg), Phenylmercury Acetate [class: Organo-mercury] 99.8 0 1 561 1.0000 1.0000 prediction
BEJFFNDL_00045 Mercury (Hg) 80.1 7.2e-60 1 141 1.0000 1.0000 prediction
BEJFFNDL_00048 Mercury (Hg) 99.3 7.9e-81 1 151 1.0000 1.0000 prediction
BEJFFNDL_00070 Nickel (Ni), Cobalt (Co) 84.4 3e-197 1 435 1.0000 1.0000 prediction
BEJFFNDL_00078 Copper (Cu), Gold (Au) 71 5e-293 7 749 0.9933 0.9031 prediction
BEJFFNDL_00088 Copper (Cu) 100 0 1 791 1.0000 1.0000 prediction
BEJFFNDL_00091 Cadmium (Cd), Zinc (Zn) 82.7 4.6e-109 1 226 1.0000 0.9869 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
BEJFFNDL_00078 PHI:8812 CopA (ABUW_2707) 76.6 0 6 748 0.9893 0.9708 rodents nosocomial infection copper-translocating P-type ATPase unaffected pathogenicity
BEJFFNDL_00081 PHI:8812 CopA (ABUW_2707) 73.2 7e-17 1 56 1.0000 0.9708 rodents nosocomial infection copper-translocating P-type ATPase unaffected pathogenicity
BEJFFNDL_00083 PHI:10395 copD (ABUW_3327) 73.7 1.6e-120 1 293 1.0000 1.0000 moths nosocomial infection copper resistance D reduced virulence
BEJFFNDL_00084 PHI:10398 copC (ABUW_3326) 79.4 1.4e-52 1 126 1.0000 1.0000 moths nosocomial infection copper resistance protein reduced virulence
BEJFFNDL_00090 PHI:10394 cusS (ABUW_3324) 74 3.4e-197 1 457 0.9807 0.9978 moths nosocomial infection sensor kinase reduced virulence
BEJFFNDL_00091 PHI:10397 cusR (ABUW_3323) 95.1 2.5e-121 1 226 1.0000 0.9956 moths nosocomial infection DNA-binding response regulator reduced virulence
BEJFFNDL_00093 PHI:10392 pcoA (ABUW_3228) 71.8 3.5e-266 1 627 1.0000 1.0000 moths nosocomial infection copper resistance protein A reduced virulence
BEJFFNDL_00094 PHI:10396 copB (ABUW_3320) 70.8 5.2e-122 1 306 1.0000 1.0000 moths nosocomial infection autotransporter domain-containing 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





        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
BEJFFNDL_00032 2.A.53.3.1 72 1.6e-197 1 492 0.9939 0.9898 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.53 The Sulfate Permease (SulP) Family
BEJFFNDL_00083 9.B.62.1.6 73.7 3.6e-120 1 293 1.0000 1.0000 9 Incompletely Characterized Transport Systems 9.B Putative transport proteins 9.B.62 The Copper Resistance (CopD) Family