CRISPR-Cas-Based Antimicrobials: Design, Challenges, and Bacterial Mechanisms of Resistance

ACS Infectious Diseases, Journal Year: 2023, Volume and Issue: 9(7), P. 1283 - 1302

Published: June 22, 2023

The emergence of antibiotic-resistant bacterial strains is a source public health concern across the globe. As discovery new conventional antibiotics has stalled significantly over past decade, there an urgency to develop novel approaches address drug resistance in infectious diseases. use CRISPR-Cas-based system for precise elimination targeted populations holds promise as innovative approach antimicrobial agent design. CRISPR-Cas targeting celebrated its high versatility and specificity, offering excellent opportunity fight antibiotic pathogens by selectively inactivating genes involved resistance, biofilm formation, pathogenicity, virulence, or viability. strategy can enact effects two approaches: inactivation chromosomal curing plasmids encoding resistance. In this Review, we provide overview main systems utilized creation these antimicrobials, well highlighting promising studies field. We also offer detailed discussion about most commonly used mechanisms delivery: bacteriophages, nanoparticles, conjugative plasmids. Lastly, possible interference that should be considered during intelligent design approaches.

Language: Английский

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Evolution of triclosan resistance modulates bacterial permissiveness to multidrug resistance plasmids and phages

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: April 30, 2024

The horizontal transfer of plasmids has been recognized as one the key drivers for worldwide spread antimicrobial resistance (AMR) across bacterial pathogens. However, knowledge remain limited about contribution made by environmental stress on evolution AMR modulating acquisition and other mobile genetic elements. Here we combined experimental evolution, whole genome sequencing, reverse engineering, transcriptomics to examine if chromosomal triclosan (TCS) disinfectant correlated effects pathogen (Klebsiella pneumoniae) permissiveness phage susceptibility. Herein, show that TCS exposure increases evolvability K. pneumoniae evolve TCS-resistant mutants (TRMs) acquiring mutations altered expression several genes previously associated with antibiotic resistance. Notably, nsrR deletion conjugation four plasmids, enhances susceptibility various Klebsiella-specific phages through downregulation defense systems changes in membrane potential reactive oxygen species response. Our findings suggest unrestricted use imposes a dual impact augmenting both chromosomally horizontally acquired mechanisms.

Language: Английский

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The role of bacterial metabolism in antimicrobial resistance

Nature Reviews Microbiology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Language: Английский

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Ecological and evolutionary solutions to the plasmid paradox

Trends in Microbiology, Journal Year: 2021, Volume and Issue: 30(6), P. 534 - 543

Published: Nov. 27, 2021

Language: Английский

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Conjugation dynamics depend on both the plasmid acquisition cost and the fitness cost

Molecular Systems Biology, Journal Year: 2021, Volume and Issue: 17(3)

Published: March 1, 2021

Article1 March 2021Open Access Transparent processSource Data Conjugation dynamics depend on both the plasmid acquisition cost and fitness Hannah Prensky Department of Biology, Barnard College, New York, NY, USA Search for more papers by this author Angela Gomez-Simmonds Division Infectious Diseases, Medicine, Columbia University Irving Medical Center, Anne-Catrin Uhlemann Allison J Lopatkin Corresponding Author [email protected] orcid.org/0000-0003-0018-9205 Ecology, Evolution, Environmental University, Science Institute, Information Prensky1, Gomez-Simmonds2, Uhlemann2 *,1,3,4 1Department 2Division 3Department 4Data *Corresponding author. Tel: +1 212 853 2564; E-mail: Molecular Systems Biology (2021)17:e9913https://doi.org/10.15252/msb.20209913 PDFDownload PDF article text main figures. Peer ReviewDownload a summary editorial decision process including letters, reviewer comments responses to feedback. ToolsAdd favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Plasmid conjugation is major mechanism responsible spread antibiotic resistance. costs are known impact long-term growth microbial populations providing plasmid-carrying cells relative (dis)advantage compared plasmid-free counterparts. Separately, introduces an immediate, but transient, metabolic perturbation. However, these short-term effects subsequent has not previously been established. Here, we observed that de novo transconjugants grew significantly slower and/or with overall prolonged lag times, lineages had replicating several generations, indicating presence cost. These were general diverse incompatibility groups, well-characterized clinically captured plasmids, Gram-negative recipient strains species, experimental conditions. Modeling revealed modulate dynamics, validated published data. results suggest hours immediately following may play critical role in short- prevalence. This time frame particularly relevant microbiomes high plasmid/strain diversity considered be hot spots conjugation. Synopsis Quantification shows indicates short A novel framework quantifies independently effects. The magnitude potentially dictated initial energetic burden imposed newly acquired plasmid, as well host cells' ability accommodate given environment. Incorporating into mathematical model improves temporal predictions dynamics. window represent interval quantifying Introduction Horizontal gene transfer (HGT) conjugation, which refers DNA from donor through direct cell-to-cell contact (Frost Koraimann, 2010) (Fig 1A), predominant way bacteria mobilize exchange resistance genes (Maiden, 1998; Barlow, 2009). can occur via chromosomally integrated conjugative elements or autonomously plasmids. Plasmids, often encode one multiple (Holmes et al, 2016), primarily global dissemination since approximately half all plasmids (Smillie have broad ranges (Klumper 2015). Moreover, postulated prevalent complex communities (e.g., gut soil microbiomes) due local density, diversity, abundance strains/species along mobile genetic (Ogilvie 2012). Figure 1. Transconjugants exhibit Schematic whereby (D, blue) transferred (R, red), generating transconjugant (T, yellow). R D each resistant (A1 A2, respectively), sensitive other. (T) uniquely antibiotics. protocol involves mixing R, followed one-hour incubation at 25°C. Cells then diluted media containing A1 A2 over 96-well plate. OD600 T (aqua) adapted (gray), (RP4 transconjugants) initiated same number per well. Each curve biological replicate. Black dashed lines best-fits. Growth rate (left) (right) T, after 1 h re-grown 24 h. De rates statistically less than (gray) (P = 1.12e-08, Appendix Table S2) (red) 7.27e-09, S2). times greater 5.71e-08 (3.77e-09, replicates. All statistics done using one-way ANOVA Bonferroni correction. Left: 7.34e-05 4.95e-05 15 120 min, respectively). Right: Lag multiplied true T0 divided mean (Appendix Fig S1D non-normalized). normalized 1.30e-09 1.31e-09 After h, condition (E) was re-grown. identical 1.00 min). 0.69 P 0.48 described (E). data Source available online figure. [msb20209913-sup-0002-SDataFig1.zip] Download figure PowerPoint formation proliferation new HGT progeny (termed fundamentally governed two kinetic processes: efficiency) dynamics). Both efficiency extrinsic intrinsic factors. For example, cell's physiological state drastically alter certain orders (Lopatkin 2016b). Likewise, highly dependent functional benefit yield net positive negative rates. Measuring processes enabled accurate persistence simple, vitro communities, consisting few strains, thereby improving our understanding 2017). native bacterial consist hundreds species interact, grow, compete scales (Jorgensen 2014). Predicting fate settings remains challenge (Dunn 2019; Collins, 2020). It widely that, absence selection, exert their hosts. Fitness vary attributed plasmid. plasmid's typically quantified established lineage isolated clone), competition assays with, to, counterpart (Ponciano 2007). Previous studies shown population structure dynamics; costly out-competed, leading elimination, compensated mutations ameliorate burden, prolonging (Dahlberg Chao, 2003; Dionisio, 2005; Harrison 2015; Loftie-Eaton Separate costs, acquiring requires immediate adaptation altered regulation resource allocation (San Millan 2018)) therefore also impacts cellular metabolism. it plasmid-encoded stress response transiently expressed 20–40 min (Althorpe 1999; Baharoglu 2010); SOS accounts considerable component maintenance metabolism (Kempes recent work demonstrated overshoot expression only occurs recently generated (Fernandez-Lopez extent disruption suggests cost, considerably focused effects, refer Indeed, traditional measurements they soon quickly stabilize la Cruz, 2014); manifest such preceding exponential growth, renders quantification challenging. Overall, generality remain unknown. Given natural environments, shed insights fates mixed/competing populations. discovered exhibited transient reduced increased conjugation—a corresponding establishing efficiently fulfill incorporating improved across range demonstrate prevalence importance implications predicting dominant Results Acquisition RP4 To investigate how might affect sought compare (which undergone adaptation) those (and fully adapted). readily estimating efficiencies 2016a): donors (D) recipients (R) carrying unique mixed under conditions minimize growth. Since antibiotics, directly selected population, its tracked microplate reader 1B). procedure ideal purposes minimizes during window, ensuring dynamic characterization captures emergent phenotypic changes. In contrast, streaking mixtures onto dual agar plates; individual clones grown stored testing Rozwandowicz 2019). stably reproducible used quantify determine timescale compensatory (Harrison Hall Using approach, first well-established, large conjugal (~60 kb). We chose imposing cell, allows us distinguish between thereafter S1A). Briefly, Escherichia coli MG1655 S1A); expresses spectinomycin (Spec) resistance, D, carries encodes kanamycin (Kan) measure hour 25°C, 1,000× Spec-Kan liquid media, reader. parallel, incubated hour, 25°C) control any itself, subsequently comparable cell verified colony forming units (CFU) S1B). Strikingly, appeared grow 1C). curve-fitting Baranyi equation (Baranyi Roberts, 1994) T's lower, higher, 1D, S1C, 1.12e-08 5.71e-09, independent duration: similar trends 1E S1C). when restored 1F). Importantly, cases, recovered remained lower strain, retained 1D). Finally, method parameters three additional methods resulted qualitatively consistent S2, Although initially costly, identified protocol-related factors could account observations. First, adjust environment, possibly altering conjugation-specific subjected conditions, effect environmental Second, residual R/D test this, background media; approximates parental densities present experiment. Doing so did trajectory nor discrepancy S1D). there no appreciable density S1E), neither survived long enough conjugate window. conclude indeed acquire, time. Introducing quantitative metric That induced changes intuitive: interpretations associated replication/protein expression. perturbation nutrient shift (Madar 2013). Therefore, facilitate quantification, define rigorous would capture end, minimal suggested required reach predetermined threshold inclusive proxy 2A S3); study analogous "time threshold" (Bethke 2. (t*, orange) specified (T*, top purple) reached depends (T0, bottom purple), (µ, aqua) (λ, orange). Assuming subtraction, line represented shown. Representative standard generation generate curve, 10-fold increments measured (dark light gray T0). Circles indicate t* (purple line) T* (orange line). Aqua represents out-growth experiment (i.e., T). plotting against t*; black curve. decreasing gray); blue markers show 0.275 (t*). Standard blue. Error bars deviation True predicted CFU E. strain MG1655. Scatter points replicates, bar height average. K. pneumoniae (KPN) AL2425. four 2 [msb20209913-sup-0003-SDataFig2.zip] let T(t) describe time, µ maximum specific rate. Consistent previous literature (Métris 2006), extrapolating region horizontal axis geometric (λ), corresponds observable onset 2A). During phase, thus line: ln(T(t)) ln(T0) + µ(t-λ), where density. Under (t*) takes detection level (T*) inversely correlated T0. other words, predict unknown (Tpred) value, assuming T*, µ, λ constant 2B). Conversely, Tpred T0, determine, specifically changed. purposes, consider relating above. case, Tpred/T0 < 1) growth-specific consequences use rather t*, simultaneously Additionally, priori spanning avoids variability inherent manually diluting target number, As such, robust trustworthy method. utility confirming discrepancies Specifically, built 2C) based quantitated curves. Having counts, found 0.0143, right-tailed t-test), 2D), expected. note approximate does change Figs S4A B), earlier. Generality determined whether particular estimates different dilution factor, strain). S4C i), ii), factor iii-iv); indeed, 150×, 500×, 1,000×, 5,000× separate parallel S4D), systematic difference estimates. acquire Klebsiella pneumoniae(KPN), species-level 2E). drastic KPN solely function plasmids; strain/species-level attributes likely key Next, reasoned replication kb), coupled significant amount energy synthesize machinery upon acquisition, immense led inhibition, thus, MacLean, hypothesized mobilizable trans do themselves machinery, most result encoding reduces size production. FHR helper system (Dimitriu 2014), self-transmissible co-residing recognition sequence oriT. pR chloramphenicol RP4, exhibits S5). hypothesis, post-conjugation curves overlapped 3A). experiments match 3B, 0.34 0.86 two- one-tailed t-tests, Thus, induce More generally, confirm (T0 Tpred), artifacts detected metric. 3. Individual two-tailed variable glucose (glu) casamino acid (caa) concentrations. Values % w/v. concentrations (C). average, error deviation, red 0.4% 0.04% w/v, respectively. Y-axis (Tpred/T0) acids. six Representatives replicates (see S10 day-to-day variability). R1, R1drd, pRK100 0.93, 0.79, 0.28, whereas RIP113, R6K, R6Kdrd 6.79e-05, 7.57e-05, 0.037, respectively, t-test, S3A). clinical p41, p168, p193, p283 37°C 7.10e-05, 2.10e-05, 0.021, 1.90e-05, n 4, 3, 2, cases except p283, averages scatter least replicates; p193 30°C 2.80e-04, 2.72e-04, scattered ratio Tpred/T0. linear regression best fit, R2 0.01 (shown left). deviation; type listed S3A. 3 [msb20209913-sup-0004-SDataFig3.zip] pR-specific differences arise demand, substrate consumed converted biomass) (Chudoba 1992) costs. Intuitively, inefficiently growing excess (Russell Cook, 1995; Russell, 2007) applied plasmid-related demands, resulting devote bulk biomass production (Low Chase, 1999), reallocating demands increase modulating well-established yields inefficient (Liu, Basan 2015), exogenous amino supplementation (Akashi Gojobori, 2002; Waschina 2016). Adapting approach leveraged trade-off 2019), (CAA) (0, 0.01, 0.1% w/v) (0.4% w/v). higher CAA increases rate, included fourth combination (0.0

Language: Английский

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Mobile Genetic Element Flexibility as an Underlying Principle to Bacterial Evolution

Annual Review of Microbiology, Journal Year: 2023, Volume and Issue: 77(1), P. 603 - 624

Published: July 12, 2023

Mobile genetic elements are key to the evolution of bacteria and traits that affect host ecosystem health. Here, we use a framework hierarchical modular system scales from genes populations synthesize recent findings on mobile (MGEs) bacteria. Doing so highlights role emergent properties flexibility, robustness, capacitance MGEs have Some their can be stored, shared, diversified across different MGEs, taxa bacteria, time. Collectively, these contribute maintaining functionality against perturbations while allowing changes accumulate in order diversify give rise new traits. These long challenged our abilities study them. Implementation technologies strategies allows for analyzed powerful ways.

Language: Английский

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The honeybee gut resistome and its role in antibiotic resistance dissemination

Integrative Zoology, Journal Year: 2023, Volume and Issue: 18(6), P. 1014 - 1026

Published: March 9, 2023

There is now general concern about widespread antibiotic resistance, and growing evidence indicates that gut microbiota critical in providing resistance. Honeybee an important pollinator; the incidence of resistance genes honeybee causes potential risks to not only its own health but also public animal health, for disseminator role, thus receiving more attention from public. Recent analysis results reveal serves as a reservoir genes, probably due antibiotics application history beekeeping horizontal gene transfer highly polluted environment. These accumulate could be transferred pathogen, even having spread during pollination, tending, social interactions, etc. Newly acquired traits may cause fitness reduction bacteria whereas facilitating adaptive evolution well. This review outlines current knowledge resistome emphasizes role dissemination.

Language: Английский

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Hijackers, hitchhikers, or co-drivers? The mysteries of mobilizable genetic elements

PLoS Biology, Journal Year: 2024, Volume and Issue: 22(8), P. e3002796 - e3002796

Published: Aug. 29, 2024

Mobile genetic elements shape microbial gene repertoires and populations. Recent results reveal that many, possibly most, mobile require helpers to transfer between genomes, which we refer as Hitcher Genetic Elements (hitchers or HGEs). They may be a large fraction of pathogenicity resistance genomic islands, whose mechanisms have remained enigmatic for decades. Together with their helper bacterial hosts, hitchers form tripartite networks interactions evolve rapidly within parasitism–mutualism continuum. In this emerging view genomes communities many questions arise. Which are being moved, by whom, how? How often costly hyper-parasites beneficial mutualists? What is the evolutionary origin hitchers? Are there key advantages associated hitchers’ lifestyle justify unexpected abundance? And why systematically smaller than helpers? essay, start answering these point ways ahead understanding principles, origin, mechanisms, impact in ecology evolution.

Language: Английский

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Vertical and horizontal gene transfer tradeoffs direct plasmid fitness

Molecular Systems Biology, Journal Year: 2022, Volume and Issue: 19(2)

Published: Dec. 27, 2022

Abstract Plasmid fitness is directed by two orthogonal processes—vertical transfer through cell division and horizontal conjugation. When considered individually, improvements in either mode of can promote how well a plasmid spreads persists. Together, however, the metabolic cost conjugation could create tradeoff that constrains evolution. Here, we present evidence for presence, consequences, molecular basis conjugation‐growth across 40 plasmids derived from clinical Escherichia coli pathogens. We discover most operate below efficiency threshold major growth effects, indicating strong natural selection vertical transfer. Below this threshold, E. demonstrates remarkable tolerance to over four orders magnitude change efficiency. This fades as nutrients become scarce attracts greater share host resources. Our results provide insight into evolutionary constraints directing strategies combat spread antibiotic resistance.

Language: Английский

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Tradeoff between lag time and growth rate drives the plasmid acquisition cost

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: April 24, 2023

Abstract Conjugative plasmids drive genetic diversity and evolution in microbial populations. Despite their prevalence, can impose long-term fitness costs on hosts, altering population structure, growth dynamics, evolutionary outcomes. In addition to costs, acquiring a new plasmid introduces an immediate, short-term perturbation the cell. However, due transient nature of this acquisition cost, quantitative understanding its physiological manifestations, overall magnitudes, population-level implications, remains unclear. To address this, here we track single colonies immediately following acquisition. We find that are primarily driven by changes lag time, rather than rate, for nearly 60 conditions covering diverse plasmids, selection environments, clinical strains/species. Surprisingly, costly plasmid, clones exhibiting longer times also achieve faster recovery rates, suggesting tradeoff. Modeling experiments demonstrate tradeoff leads counterintuitive ecological whereby intermediate-cost outcompete both low high-cost counterparts. These results suggest that, unlike dynamics not uniformly minimizing disadvantages. Moreover, lag/growth has clear implications predicting outcomes intervention strategies bacteria undergoing conjugation.

Language: Английский

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