Annotation Categories of the Plasmid Cluster







Summary of the plasmid cluster

Basic Information about the Plasmid Cluster

  Cluster Information   Plasmid Cluster ID   C1075
  Reference Plasmid   NZ_CP104393.1
  Reference Plasmid Size   1028198
  Reference Plasmid GC Content   0.40
  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
M0195640 HGPIINLA_00347 354124 3 Gut 0.09 protein_coding upstream_gene_variant MODIFIER -4454C>T None
M0195641 HGPIINLA_00355 356030 3 Gut 0.09 protein_coding missense_variant MODERATE 901A>C Thr301Pro
M0195642 HGPIINLA_00377 378565 4 Gut 0.12 protein_coding missense_variant MODERATE 311T>C Val104Ala






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
HGPIINLA_00136 VFG002162 BSH 78.1 3.5e-154 1 324 1.0 0.9969 Stress survival bile salt hydrolase experiment
HGPIINLA_00136 VFG006815 BSH 78.4 4.1e-154 1 324 1.0 0.9969 Stress survival bile salt hydrolase 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
HGPIINLA_00643 Arsenic (As) 75.8 2.9e-39 1 99 1.0000 0.7388 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
HGPIINLA_00697 PHI:124066 prdB 74 2.5e-61 1 150 1.0000 0.9668 rodents nosocomial diarrhea proline reductase reduced virulence
HGPIINLA_00698 PHI:124066 prdB 85.5 1.4e-34 1 83 1.0000 0.9668 rodents nosocomial diarrhea proline reductase reduced virulence
HGPIINLA_00817 PHI:7637 CspA 80 5.7e-26 1 65 0.9848 0.9848 bony fishes listeriosis cold shock protein reduced virulence
HGPIINLA_00960 PHI:8586 mntH1 76.2 7.3e-217 3 516 0.9828 0.9699 moths nosocomial infection divalent metal cation transporter unaffected pathogenicity






        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
HGPIINLA_00125 UXJ97578.1|GH0 100 0 1 1546 1 1
HGPIINLA_00149 UXK06336.1|GH73 100 0 1 656 1 1
HGPIINLA_00200 UXC27891.1|GH36 100 0 1 734 1 1
HGPIINLA_00245 UXJ97467.1|GH36 100 0 1 723 1 1
HGPIINLA_00246 UXC27934.1|GH13_31 100 0 1 541 1 1
HGPIINLA_00248 UXC27936.1|GH32 100 0 1 499 1 1
HGPIINLA_00305 UXC27990.1|GH1 100 0 1 474 1 1
HGPIINLA_00308 QZO10744.1|GH43_26 100 3.95e-252 1 323 1 1
HGPIINLA_00343 UXJ97378.1|GH1 100 0 1 466 1 1
HGPIINLA_00367 UXJ97357.1|GH13_31 100 0 1 571 1 1
HGPIINLA_00380 UXK06547.1|GH1 100 0 1 483 1 1
HGPIINLA_00408 UXJ98367.1|GH39 100 0 1 809 1 1
HGPIINLA_00411 UXC28087.1|GH1 100 0 1 477 1 1
HGPIINLA_00415 QZO10835.1|GH172 100 1.58e-285 1 372 1 1
HGPIINLA_00467 UXC28137.1|AA10 100 4.12e-141 1 192 1 1
HGPIINLA_00472 UXC28141.1|GT8 100 9.68e-215 1 288 1 1
HGPIINLA_00478 UXC28146.1|GT113 99.7 1.04e-245 1 336 1 0.9941
HGPIINLA_00484 UXC28152.1|GT4 100 0 1 481 1 1
HGPIINLA_00504 UXK06658.1|GH78 100 0 1 529 1 1
HGPIINLA_00542 UXC27259.1|GH16 100 0 1 658 1 1
HGPIINLA_00546 QZO10955.1|GH4 100 0 1 453 1 1
HGPIINLA_00564 QZO10966.1|GH4 100 0 1 442 1 1
HGPIINLA_00591 UXK06742.1|GT4 100 1.26e-302 1 416 1 1
HGPIINLA_00592 UXK06743.1|GT26 100 5.92e-172 1 241 1 1
HGPIINLA_00596 UXK06747.1|GT4 100 2.49e-253 1 346 1 1
HGPIINLA_00745 QXJ60949.1|GH38 98.2 0 1 873 1 1
HGPIINLA_00747 UXC27454.1|GH1 100 0 1 456 1 1
HGPIINLA_00753 UXK05957.1|GT2 100 1.54000014775894e-317 1 434 1 1
HGPIINLA_00780 QZO11158.1|GT8 100 8.91e-211 1 288 1 1
HGPIINLA_00798 UXK05991.1|GH73 100 3.73e-203 1 375 1 1
HGPIINLA_00874 UXC27571.1|GT2 100 3.51e-220 1 312 1 1
HGPIINLA_00889 UXC27585.1|CBM34|GH13_20 100 0 1 582 1 1
HGPIINLA_00914 UXC27610.1|GH3 100 0 1 765 1 1
HGPIINLA_00916 UXC27612.1|GH1 100 0 1 464 1 1
HGPIINLA_00918 UXC27614.1|GT51 100 0 1 855 1 1
HGPIINLA_00929 QZO10440.1|GT8 100 4.6e-211 1 284 1 1
HGPIINLA_00930 QZO11251.1|GT8 100 6.32e-217 2 296 0.9966 1
HGPIINLA_00981 UXJ97729.1|CBM50|GH73 100 8.17999998985288e-316 1 531 1 1
HGPIINLA_01002 UXJ97710.1|GH1 100 0 1 464 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
HGPIINLA_00272 4.A.6.1.19 70.5 3.7e-92 2 262 0.9962 0.9317 4 Group Translocators 4.A Phosphotransfer-driven Group Translocators (PTS) 4.A.6 The PTS Mannose-Fructose-Sorbose (Man) Family
HGPIINLA_00427 1.S.1.1.1 74.2 1.4e-30 1 89 0.9570 0.9468 1 Channels/Pores 1.S Bacterial Micro/NanoCompartment Shell Protein Pores 1.S.1 The Bacterial Microcompartment Shell/Pore-forming Protein-1 (BMC-SP1) Family
HGPIINLA_00558 4.A.5.1.2 75.4 1.7e-184 8 422 0.9811 0.9811 4 Group Translocators 4.A Phosphotransfer-driven Group Translocators (PTS) 4.A.5 The PTS Galactitol (Gat) Family
HGPIINLA_00910 2.A.3.7.7 72.9 1.4e-190 1 446 0.9429 0.9571 2 Electrochemical Potential-driven Transporters 2.A Porters (uniporters, symporters, antiporters) 2.A.3 The Amino Acid-Polyamine-Organocation (APC) Family