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Classic reaction kinetics can explain complex patterns of antibiotic action.

ABSTRACT: Finding optimal dosing strategies for treating bacterial infections is extremely difficult, and improving therapy requires costly and time-intensive experiments. To date, an incomplete mechanistic understanding of drug effects has limited our ability to make accurate quantitative predictions of drug-mediated bacterial killing and impeded the rational design of antibiotic treatment strategies. Three poorly understood phenomena complicate predictions of antibiotic activity: post-antibiotic growth suppression, density-dependent antibiotic effects, and persister cell formation. We show that chemical binding kinetics alone are sufficient to explain these three phenomena, using single-cell data and time-kill curves of Escherichia coli and Vibrio cholerae exposed to a variety of antibiotics in combination with a theoretical model that links chemical reaction kinetics to bacterial population biology. Our model reproduces existing observations, has a high predictive power across different experimental setups (R(2) = 0.86), and makes several testable predictions, which we verified in new experiments and by analyzing published data from a clinical trial on tuberculosis therapy. Although a variety of biological mechanisms have previously been invoked to explain post-antibiotic growth suppression, density-dependent antibiotic effects, and especially persister cell formation, our findings reveal that a simple model that considers only binding kinetics provides a parsimonious and unifying explanation for these three complex, phenotypically distinct behaviours. Current antibiotic and other chemotherapeutic regimens are often based on trial and error or expert opinion. Our "chemical reaction kinetics"-based approach may inform new strategies, which are based on rational design.

SUBMITTER: Abel Zur Wiesch P

PROVIDER: S-EPMC4554720 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Classic reaction kinetics can explain complex patterns of antibiotic action.

Abel Zur Wiesch Pia P Abel Sören S Gkotzis Spyridon S Ocampo Paolo P Engelstädter Jan J Hinkley Trevor T Magnus Carsten C Waldor Matthew K MK Udekwu Klas K Cohen Ted T

Science translational medicine 20150501 287

Finding optimal dosing strategies for treating bacterial infections is extremely difficult, and improving therapy requires costly and time-intensive experiments. To date, an incomplete mechanistic understanding of drug effects has limited our ability to make accurate quantitative predictions of drug-mediated bacterial killing and impeded the rational design of antibiotic treatment strategies. Three poorly understood phenomena complicate predictions of antibiotic activity: post-antibiotic growth ...[more]

PMID: 25972005

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Project description:BackgroundElectrochemotherapy (ECT) has shown to be an effective treatment for cutaneous and subcutaneous Kaposi sarcoma (KS) lesions. However, no study has investigated the impact of ECT treatment on the kinetics of human herpesvirus type 8 (HHV8), which is considered the necessary causal agent of KS. We aimed to evaluate HHV8 viral load and expression levels in patients affected by classic KS who received one or more ECT treatments and have been followed semi annually for up to four years.MethodsA total of 27 classic KS patients were enrolled in this study. Tumour biopsies and blood samples were obtained before ECT treatment. Additional blood samples were collected at six month intervals for 12-48 months. HHV8 viral load and expression profiles of latent (ORF72 and ORF73) and lytic (K2, K8, K8.1, K10/K10.1, K10.5/K10.6 and ORF16) genes were assessed in all samples by real-time PCR. HHV8 ORF26 and K1 regions were amplified and subjected to direct nucleotide sequencing followed by phylogenetic analysis for variant identification.ResultsAll KS biopsies and 46.4% of peripheral blood mononuclear cells (PBMCs) collected before ECT treatment were positive for HHV8 DNA. Viral load ranged from 0.02 to 2.3 copies per cell in KS lesions and 3.0 × 10-7 to 6.9 × 10-4 copies per cell in PBMCs. Overall, latent ORF72 and ORF73 as well as lytic K2, K8 and K10/K10.1 were expressed in all KS biopsies. ORF16 mRNA was detected in 71.4% and both K8.1 and K10.5/K10.6 mRNAs in 57.1% of KS samples. The ORF72, ORF73 and K2 transcripts were amplified in 37.5%, 25% and 25% of PBMCs collected before ECT, respectively. After the first ECT session, complete response was achieved in 20 out of 27 (74.1%) patients and HHV8 DNA was detected in four out of 27 (14.8%) PBMC samples at six month follow up. Phylogenetic analysis of ORF26 amplimers showed that most viral variants belonged to A/C (82.3%), and few to C2 (5.9%) or C3 (11.8%) subtype. The K1/VR1 variants fell into A (33.3%) and C (66.7%) HHV8 clade. No correlation was found between HHV8 subtypes and ECT complete response.ConclusionsECT therapy has a significant effect on HHV8 kinetics in patients with classic KS. The complete remission of patients was accompanied by clearance of circulating virus.

Project description:Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH4 +-N, NO3 --N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

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Classic reaction kinetics can explain complex patterns of antibiotic action.

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Classic reaction kinetics can explain complex patterns of antibiotic action.

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