Plasmids and Their Hosts

Shintani, Masaki; Suzuki, Haruo

doi:10.1007/978-981-13-3411-5_6

Cited by 7 publications

(12 citation statements)

References 200 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Plasmids are extra-chromosomal DNA molecules found across all three Domains of Life. In bacteria, they are one of the main mediators of horizontal gene transfer (HGT) through the processes of conjugation and transformation 1–3 . Plasmids generally harbour non-essential genes that can modulate the fitness of their bacterial host.…”

Section: Introductionmentioning

confidence: 99%

“…Despite being widely used and informative, these typing schemes only work within a limited taxonomic range 7–9 . Replicon typing is dependent on the availability of prior experimental evidence and remains restricted to culturable bacteria from the family Enterobacteriaceae and several well-studied genera of gram-positive bacteria 1,10–12 . Furthermore, this approach can lead to ambiguous classification, even for experimentally validated replicons, as recently demonstrated by the discovery of compatible plasmids assigned to the same replicon type, which led to the further subdivision of the IncK type into IncK1 and IncK2 13 , and IncA/C type into IncA and IncC 14 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Large-scale network analysis captures biological features of bacterial plasmids

Acman

Dorp

Santini

et al. 2019

Preprint

View full text Add to dashboard Cite

11Most bacteria exchange genetic material through Horizontal Gene Transfer (HGT). The primary vehicles for HGT 12 are plasmids and plasmid-borne transposable elements, though their population structure and dynamics remain 13 poorly understood. Here, we quantified genetic similarity between more than 10,000 bacterial plasmids and 14 reconstructed a network based on their shared k-mer content. Using a community detection algorithm, we assigned 15 plasmids into cliques which are highly correlated with plasmid gene content, bacterial host range, GC content, as 16 well as replicon and mobility (MOB) type classifications. Resolving the plasmid population structure further 17 allowed identification of candidates for yet-undescribed replicon genes. Our work provides biological insights 18 into the dynamics of plasmids and plasmid-borne mobile elements, with the latter representing the main drivers 19 of HGT at broad phylogenetic scales. Our results illustrate the potential of network-based analyses for the bacterial 20 'mobilome' and open up the prospect of a natural, exhaustive classification framework for bacterial plasmids. 21 48 assignments and can cover a potentially wider taxonomic range, however they are not applicable to the 49 classification of non-mobilizable plasmids. These two typing schemes have inspired several in silico classification 50 tools, such as PlasmidFinder 12 , the plasmid MultiLocus Sequence Typing (MLST) database, and MOB-suite 15 . 51However, all of these tools intrinsically rely on the completeness of their reference sequence databases, which 52 typically lack representatives from understudied and/or unculturable bacterial hosts. 53As bacterial plasmids undergo extensive recombination and HGT, their evolutionary history is not well captured 54 by phylogenetic trees, which are designed for the analysis of point mutation in sequence alignments 16,17 . Network 55 models offer an attractive alternative given they can incorporate both horizontal and vertical inheritance 18 , and 56 can deal with point mutations as well as structural variants. Networks have gained much attention in the past 57 decade as an alternative method for studying prokaryotic evolution, including plasmids 3,8,18,19 . Plasmid gene-58 sharing networks have proven a useful means to track AMR and virulence dissemination yielding deeper insights 59 Results 76 A dataset of complete bacterial plasmids 77A dataset of complete bacterial plasmids was assembled comprising 10,696 sequences found in bacteria from 22 78 phyla and over 400 genera ( Supplementary Table 1, Figure 1A, and Supplementary Figure 1). The composition 79 of plasmid hosts reflects current research interests, with the Proteobacteria and Firmicutes phyla together 80 representing over 84% of plasmid sequences. In total, 510,463 different Coding Sequences (CDSs) were identified 81 in the plasmid dataset. 66.01% of the CDSs were predicted to encode a hypothetical protein, 27.9% had a known 82 product with Gene Ontology (GO) biological process annotation, with the remai...

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Large-scale network analysis captures biological features of bacterial plasmids

Acman

Dorp

Santini

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…lasmids are extra-chromosomal DNA molecules found across all three Domains of Life. In bacteria, they are considered one of the main mediators of horizontal gene transfer (HGT) through the processes of conjugation and transformation [1][2][3] . Plasmids generally harbour non-essential genes that can modulate the fitness of their bacterial host.…”

mentioning

confidence: 99%

Large-scale network analysis captures biological features of bacterial plasmids

et al. 2020

View full text Add to dashboard Cite

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial 'mobilome' and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids.

show abstract

“…Compensatory mutations in the bacterial chromosome (41,44,45) and in the plasmid (46)(47)(48)(49) might reduce the fitness cost of plasmid carriage, thus increasing the replication rate of the hosting microorganisms and the spread of plasmids. The emergence of compensatory mutations is certainly driven by the bacterial mutation frequency, but the effect of mutation might be asymmetrical if it occurs in the chromosome or plasmid given that mutated plasmids can horizontally disseminate more effectively than mutated chromosomes through vertical transmission and given the presence of several genes that can compensate the cost, which differs among bacterial hosts (47)(48)(49)(50)(51)(52)(53)(54). In our basic model, high mutation frequency for plasmid cost compensatory mutations was expected to influence not only plasmid cost compensation but also the selection of chromosomal mutants (for instance, fluoroquinolone-resistant mutants).…”

Section: Resultsmentioning

confidence: 99%

Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

Campos

Millán

Sempere

et al. 2020

Antimicrob Agents Chemother

View full text Add to dashboard Cite

Bacterial plasmids harboring antibiotic resistance genes are critical in the spread of antibiotic resistance. It is known that plasmids differ in their kinetic values, i.e., conjugation rate, segregation rate by copy number incompatibility with related plasmids, and rate of stochastic loss during replication. They also differ in cost to the cell in terms of reducing fitness and in the frequency of compensatory mutations compensating plasmid cost. However, we do not know how variation in these values influences the success of a plasmid and its resistance genes in complex ecosystems, such as the microbiota. Genes are in plasmids, plasmids are in cells, and cells are in bacterial populations and microbiotas, which are inside hosts, and hosts are in human communities at the hospital or the community under various levels of cross-colonization and antibiotic exposure. Differences in plasmid kinetics might have consequences on the global spread of antibiotic resistance. New membrane computing methods help to predict these consequences. In our simulation, conjugation frequency of at least 10−3 influences the dominance of a strain with a resistance plasmid. Coexistence of different antibiotic resistances occurs if host strains can maintain two copies of similar plasmids. Plasmid loss rates of 10−4 or 10−5 or plasmid fitness costs of ≥0.06 favor plasmids located in the most abundant species. The beneficial effect of compensatory mutations for plasmid fitness cost is proportional to this cost at high mutation frequencies (10−3 to 10−5). The results of this computational model clearly show how changes in plasmid kinetics can modify the entire population ecology of antibiotic resistance in the hospital setting.

show abstract

Plasmids and Their Hosts

Cited by 7 publications

References 200 publications

Large-scale network analysis captures biological features of bacterial plasmids

Large-scale network analysis captures biological features of bacterial plasmids

Large-scale network analysis captures biological features of bacterial plasmids

Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

Contact Info

Product

Resources

About