scholarly journals Antibiotic interactions shape short-term evolution of resistance in E. faecalis

2019 ◽  
Author(s):  
Ziah Dean ◽  
Jeff Maltas ◽  
Kevin B. Wood
Keyword(s):  
Drug Resistance ◽  
Bacterial Infections ◽  
Response Surfaces ◽  
Drug Combinations ◽  
Cross Resistance ◽  
Multi Drug Resistance ◽  
Trade Offs ◽  
Drug Concentrations ◽  
Wide Range ◽  
Growth Adaptation

ABSTRACTAntibiotic combinations are increasingly used to combat bacterial infections. Multidrug therapies are a particularly important treatment option for E. faecalis, an opportunistic pathogen that contributes to high-inoculum infections such as infective endocarditis. While numerous synergistic drug combinations for E. faecalis have been identified, much less is known about how different combinations impact the rate of resistance evolution. In this work, we use high-throughput laboratory evolution experiments to quantify adaptation in growth rate and drug resistance of E. faecalis exposed to drug combinations exhibiting different classes of interactions, ranging from synergistic to suppressive. We identify a wide range of evolutionary behavior, including both increased and decreased rates of growth adaptation, depending on the specific interplay between drug interaction and cross resistance. For example, selection in a dual-lactam combination leads to accelerated growth adaptation compared to selection with the individual drugs, even though the resulting resistance profiles are nearly identical. On the other hand, populations evolved in an aminoglycoside and -lactam combination exhibit decreased growth adaptation and resistant profiles that depend on the specific drug concentrations. We show that the main qualitative features of these evolutionary trajectories can be explained by simple rescaling arguments that correspond to geometric transformations of the two-drug growth response surfaces measured in ancestral cells. The analysis also reveals multiple examples where resistance profiles selected by drug combinations correspond to (nearly) optimized linear combinations of those selected by the component drugs. Our results highlight trade-offs between drug interactions and collateral effects during the evolution of multi-drug resistance and emphasize evolutionary benefits and disadvantages of particular drug pairs targeting enterococci.

Interactions between antimicrobial drugs

1968 ◽  
Vol 6 (13) ◽  
pp. 49-51
Keyword(s):  
Drug Resistance ◽  
Bacterial Infections ◽  
Mixed Infections ◽  
Neonatal Infections ◽  
Antimicrobial Drugs ◽  
Single Drug ◽  
Wide Range ◽  
Severe Infections ◽  
Pathogenic Organisms

Treatment with a single drug is appropriate for most bacterial infections. A combination of antimicrobial drugs is indicated only in a limited number of circumstances, of which the most clearly defined is the prevention of drug resistance, as in the therapy of tuberculosis. It may be necessary to use antibiotic combinations in mixed infections, or as a temporary measure in the treatment of severe infections before bacteriological findings are available; for example, in severe neonatal infections in which a wide range of potentailly pathogenic organisms have to be considered.

Computational Coevolution of Antiviral Drug Resistance

1998 ◽  
Vol 4 (1) ◽  
pp. 41-59 ◽  
Author(s):  
Christopher D. Rosin ◽  
Richard K. Belew ◽  
Garrett M. Morris ◽  
Arthur J. Olson ◽  
David S. Goodsell
Keyword(s):  
Drug Resistance ◽  
Broad Class ◽  
Antiviral Drug ◽  
Resistant Mutant ◽  
Approximate Model ◽  
Cross Resistance ◽  
Resistance Mutations ◽  
Wide Range ◽  
Antiviral Drug Resistance ◽  
Mutant Forms

An understanding of antiviral drug resistance is important in the design of effective drugs. Comprehensive features of the interaction between drug designs and resistance mutations are difficult to study experimentally because of the very large numbers of drugs and mutants involved. We describe a computational framework for studying antiviral drug resistance. Data on HIV-1 protease are used to derive an approximate model that predicts interaction of a wide range of mutant forms of the protease with a broad class of protease inhibitors. An algorithm based on competitive coevolution is used to find highly resistant mutant forms of the protease, and effective inhibitors against such mutants, in the context of the model. We use this method to characterize general features of inhibitors that are effective in overcoming resistance, and to study related issues of selection pathways, cross-resistance, and combination therapies.

Further studies on the use of chicken embryo infections for the study of drug resistance in Eimeria tenella

Parasitology ◽  
1976 ◽  
Vol 73 (3) ◽  
pp. 275-282 ◽  
Author(s):  
H. D. Chapman
Keyword(s):  
Drug Resistance ◽  
Drug Concentration ◽  
Chicken Embryo ◽  
The Other ◽  
Cross Resistance ◽  
Drug Resistant ◽  
Mutagenic Agent ◽  
Development Of Resistance ◽  
Drug Concentrations ◽  
Resistant Lines

Infections in the chicken embryo have been used to study the development of drug resistance in an embryo adapted strain of E. tenella. Resistance was developed to decoquinate, clopidol and robenidine by serially passaging this strain, but evidence for the development of resistance to amprolium was inconclusive. Resistance to decoquinate developed more readily than to the other drugs. Attempts to increase resistance to clopidol, robenidine and amprolium by increasing the sporozoite inoculum and by the use of a mutagenic agent were unsuccesful. No cross-resistance was found between the 4 drugs.Drug resistant lines of the Houghton strain (H) of E. tenella, made resistant to the 4 anticoccidial drugs by passage in chickens, were found to be resistant when evaluated using chicken embryo infections. Lines made resistant to decoquinate were not controlled by any concentration of this drug, suggesting that resistance, once developed, was absolute and not dependent on drug concentration. Lines made resistant to robenidine, clopidol and amprolium, however, were controlled by higher drug concentrations suggesting that in this case resistance was dependent on drug concentration.

scholarly journals Comparison of imatinib mesylate, dasatinib (BMS-354825), and nilotinib (AMN107) in an N-ethyl-N-nitrosourea (ENU)–based mutagenesis screen: high efficacy of drug combinations

Blood ◽  
2006 ◽  
Vol 108 (7) ◽  
pp. 2332-2338 ◽  
Author(s):  
Heather A. Bradeen ◽  
Christopher A. Eide ◽  
Thomas O'Hare ◽  
Kara J. Johnson ◽  
Stephanie G. Willis ◽  
...  
Keyword(s):  
Imatinib Mesylate ◽  
Novel Mutation ◽  
Kinase Domain ◽  
Drug Combinations ◽  
Cross Resistance ◽  
Abl Kinase ◽  
Drug Concentrations ◽  
Trough Levels ◽  
Maximal Suppression

Abstract BMS-354825 (dasatinib) and AMN107 (nilotinib) are potent alternate Abl inhibitors with activity against many imatinib mesylate–resistant BCR-ABL kinase domain (KD) mutants, except T315I. We used N-ethyl-N-nitrosourea (ENU)–exposed Ba/F3-p210BCR-ABL cells to compare incidence and types of KD mutants emerging in the presence of imatinib mesylate, dasatinib, and nilotinib, alone and in dual combinations. Although ENU is expected to induce mutations in multiple proteins, resistant clones were almost exclusively BCR-ABL KD mutant at relevant concentrations of nilotinib and dasatinib, consistent with a central role of KD mutations for resistance to these drugs. Twenty different mutations were identified with imatinib mesylate, 10 with nilotinib (including only 1 novel mutation, E292V) and 9 with dasatinib. At intermediate drug levels the spectrum narrowed to F317V and T315I for dasatinib and Y253H, E255V, and T315I for nilotinib. Thus, cross-resistance is limited to T315I, which is also the only mutant isolated at drug concentrations equivalent to maximal achievable plasma trough levels. With drug combinations maximal suppression of resistant clone outgrowth was achieved at lower concentrations compared with single agents, suggesting that such combinations may be equipotent to higher-dose single agents. However, sequencing uniformly revealed T315I, consistent with the need for a T315I inhibitor, to completely block resistance.

scholarly journals Quantifying antiviral activity optimizes drug combinations against hepatitis C virus infection

2017 ◽  
Vol 114 (8) ◽  
pp. 1922-1927 ◽  
Author(s):  
Yoshiki Koizumi ◽  
Hirofumi Ohashi ◽  
Syo Nakajima ◽  
Yasuhito Tanaka ◽  
Takaji Wakita ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Antiviral Activity ◽  
Viral Replication ◽  
Quantitative Information ◽  
Drug Combinations ◽  
Lower Probability ◽  
Multiple Drug ◽  
Drug Concentrations

With the introduction of direct-acting antivirals (DAAs), treatment against hepatitis C virus (HCV) has significantly improved. To manage and control this worldwide infectious disease better, the “best” multidrug treatment is demanded based on scientific evidence. However, there is no method available that systematically quantifies and compares the antiviral efficacy and drug-resistance profiles of drug combinations. Based on experimental anti-HCV profiles in a cell culture system, we quantified the instantaneous inhibitory potential (IIP), which is the logarithm of the reduction in viral replication events, for both single drugs and multiple-drug combinations. From the calculated IIP of 15 anti-HCV drugs from different classes [telaprevir, danoprevir, asunaprevir, simeprevir, sofosbuvir (SOF), VX-222, dasabuvir, nesbuvir, tegobuvir, daclatasvir, ledipasvir, IFN-α, IFN-λ1, cyclosporin A, and SCY-635], we found that the nucleoside polymerase inhibitor SOF had one of the largest potentials to inhibit viral replication events. We also compared intrinsic antiviral activities of a panel of drug combinations. Our quantification analysis clearly indicated an advantage of triple-DAA treatments over double-DAA treatments, with triple-DAA treatments showing enhanced antiviral activity and a significantly lower probability for drug resistance to emerge at clinically relevant drug concentrations. Our framework provides quantitative information to consider in designing multidrug strategies before costly clinical trials.

scholarly journals Exceptions to the rule: Why does resistance evolution not undermine antibiotic therapy in all bacterial infections?

2021 ◽  
Author(s):  
Amrita Bhattacharya ◽  
Anton Aluquin ◽  
David A Kennedy
Keyword(s):  
Public Health ◽  
Drug Resistance ◽  
Antibiotic Resistance ◽  
Bacterial Infections ◽  
Bacterial Pathogens ◽  
Human Microbiome ◽  
Systematic Analysis ◽  
Resistance Evolution ◽  
Wide Range ◽  
Public Health Challenges

Antibiotic resistance poses one of the greatest public health challenges of the 21st century. Yet not all pathogens are equally affected by resistance evolution. Why? Here we examine what underlies variation in antibiotic resistance across human bacterial pathogens and the drugs used to treat them. We document the observed prevalence of antibiotic resistance for ′pathogen x drug′ combinations across 57 different human bacterial pathogens and 53 antibiotics from 15 drug classes used to treat them. Using AIC-based model selection we analyze 14 different traits of bacteria and antibiotics that are believed to be important in resistance evolution. Using these data, we identify the traits that best explain observed variation in resistance evolution. Our results show that nosocomial pathogens and indirectly transmitted pathogens are significantly associated with increased prevalence of resistance whereas zoonotic pathogens, specifically those with wild animal reservoirs, are associated with reduced prevalence of resistance. We found partial support for associations between drug resistance and gram classification, human microbiome reservoirs, horizontal gene transfer, and documented human-to human transfer. Global drug use, time since drug discovery, mechanism of drug action, and environmental reservoirs did not emerge as statistically robust predictors of drug resistance in our analyses. To the best of our knowledge this work is the first systematic analysis of resistance across such a wide range of human bacterial pathogens, encompassing the vast majority of common bacterial pathogens. Insights from our study may help guide public health policies and future studies on resistance control.

scholarly journals Emerging Therapeutic Strategies to Overcome Drug Resistance in Multiple Myeloma

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1686
Author(s):  
Lorraine N. Davis ◽  
Daniel W. Sherbenou
Keyword(s):  
Multiple Myeloma ◽  
Drug Resistance ◽  
Proteasome Inhibitors ◽  
Cross Resistance ◽  
Multi Drug Resistance ◽  
Immunomodulatory Drugs ◽  
Drug Conjugates ◽  
Plasma Cell Neoplasm ◽  
Drug Classes ◽  
Malignant Plasma Cell

Multiple myeloma is a malignant plasma cell neoplasm that remains incurable and is ultimately fatal when patients acquire multi-drug resistance. Thus, advancing our understanding of the mechanisms behind drug resistance in multi-relapsed patients is critical for developing better strategies to extend their lifespan. Here, we review the understanding of resistance to the three key drug classes approved for multiple myeloma treatment: immunomodulatory drugs, proteasome inhibitors, and monoclonal antibodies. We consider how the complex, heterogenous biology of multiple myeloma may influence the acquisition of drug resistance and reflect on the gaps in knowledge where additional research is needed to improve our treatment approaches. Fortunately, many agents are currently being evaluated preclinically and in clinical trials that have the potential to overcome or delay drug resistance, including next-generation immunomodulatory drugs and proteasome inhibitors, novel small molecule drugs, chimeric antigen receptor T cells, antibody-drug conjugates, and bispecific antibodies. For each class, we discuss the potential of these strategies to overcome resistance through modifying agents within each class or new classes without cross-resistance to currently available drugs.

scholarly journals Characterization and in vitro Analysis of Probiotic-Derived Peptides Against Multi Drug Resistance Bacterial Infections

2020 ◽  
Vol 11 ◽  
Author(s):  
Aninda Mazumdar ◽  
Yazan Haddad ◽  
Vishma Pratap Sur ◽  
Vedran Milosavljevic ◽  
Sukanya Bhowmick ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Bacterial Infections ◽  
Multi Drug Resistance ◽  
Vitro Analysis ◽  
In Vitro Analysis

scholarly journals Nitrofurantoin and fosfomycin for the carbapenem resistant Enterobacteriales and multi drug resistant uropathogens: are the choices still same?

2020 ◽  
Vol 7 (10) ◽  
pp. 3980
Author(s):  
Nusrat Perween ◽  
Asfia Sultan ◽  
Anees Akhtar ◽  
Fatima Khan ◽  
Meher Rizvi ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Bacterial Infections ◽  
Methicillin Resistance ◽  
Financial Burden ◽  
Treatment Options ◽  
Multi Drug Resistance ◽  
Cross Sectional ◽  
Beta Lactamases ◽  
Carbapenem Resistant ◽  
Single Organism

Background: Urinary tract infection (UTI) is one of the most common bacterial infections, affecting 150 million people each year worldwide with substantial clinical and financial burden. With upcoming multi drug resistance (MDR) and carbepenem resistance among uropathogens there is urgent need to explore other new or old treatment options like nitrofurantoin and fosfomycin trometamol.Methods: This is a cross-sectional (descriptive study) conducted over 6 month’s period from October 2019 to March 2020. Out of 9045 urine samples, 1788 (19.8%) were positive (1721 samples with single organism and 67 samples with 2 organisms). Total 1855 isolates were identified and antimicrobial susceptibility was performed by Kirby-Bauer method and VITEK 2 system. Methicillin‑resistant Staphylococcus aureus (MRSA), vancomycin resistant enterococci (VRE), multi drug resistance (MDR) and metallo‑beta‑lactamases (MBL) production was detected.Results: E. coli 41.8% was found commonest followed by enterococcus species (21.6%). Methicillin resistance was 66% while 1.8% were VRE. 429 (34.5%) were CRE (carbapenem resistant enterobacteriales) out of which, 154 (36%) were MBL while 188 (44%) were detected as serine carbapenemase producers via modified carbapenem inactivation method (mCIM) and EDTA-modified carbapenem inactivation method (eCIM) testing. Among 742 (40%) MDR, fosfomycin was effective in 611 (82.3%) while 331 (77.1%) of the CRE isolates were susceptible to fosfomycin.Conclusions: Fosfomycin should be reserved for MDR and nitrofurantoin should be used cautiously otherwise resistance will increase to these drugs in the coming days.

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