Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Triple-drug therapies have transformed HIV from a fatal condition to a chronic one. These therapies should prevent HIV drug resistance evolution, because one or more drugs suppress any partially resistant viruses. In practice, such therapies drastically reduced, but did not eliminate, resistance evolution. In this article, we reanalyze published data from an evolutionary perspective and demonstrate several intriguing patterns about HIV resistance evolution - resistance evolves (1) even after years on successful therapy, (2) sequentially, often via one mutation at a time and (3) in a partially predictable order. We describe how these observations might emerge under two models of HIV drugs varying in space or time. Despite decades of work in this area, much opportunity remains to create models with realistic parameters for three drugs, and to match model outcomes to resistance rates and genetic patterns from individuals on triple-drug therapy. Further, lessons from HIV may inform other systems.

Download Full-text

Impact of an Intervention to Control Imipenem-Resistant Acinetobacter baumannii and Its Resistance Mechanisms: An 8-Year Survey

Frontiers in Microbiology ◽

10.3389/fmicb.2020.610109 ◽

2021 ◽

Vol 11 ◽

Cited By ~ 1

Author(s):

Lida Chen ◽

Pinghai Tan ◽

Jianming Zeng ◽

Xuegao Yu ◽

Yimei Cai ◽

...

Keyword(s):

Drug Resistance ◽

Acinetobacter Baumannii ◽

Bacterial Resistance ◽

Efflux Pump ◽

Resistance Mechanism ◽

Resistance Mechanisms ◽

Multi Drug Resistance ◽

Minimal Inhibitory Concentrations ◽

Resistance Rates ◽

The Impact

BackgroundThis study aimed to examine the impact of an intervention carried out in 2011 to combat multi-drug resistance and outbreaks of imipenem-resistant Acinetobacter baumannii (IRAB), and to explore its resistance mechanism.MethodsA total of 2572 isolates of A. baumannii, including 1673 IRAB isolates, were collected between 2007 and 2014. An intervention was implemented to control A. baumannii resistance and outbreaks. Antimicrobial susceptibility was tested by calculating minimal inhibitory concentrations (MICs), and outbreaks were typed using pulsed-field gel electrophoresis (PFGE). Resistance mechanisms were explored by polymerase chain reaction (PCR) and whole genome sequencing (WGS).ResultsFollowing the intervention in 2011, the resistance rates of A. baumannii to almost all tested antibiotics decreased, from 85.3 to 72.6% for imipenem, 100 to 80.8% for ceftriaxone, and 45.0 to 6.9% for tigecycline. The intervention resulted in a decrease in the number (seven to five), duration (8–3 months), and departments (five to three) affected by outbreaks; no outbreaks occurred in 2011. After the intervention, only blaAMPC (76.47 to 100%) and blaTEM–1 (75.74 to 96.92%) increased (P < 0.0001); whereas blaGES–1 (32.35 to 3.07%), blaPER–1 (21.32 to 1.54%), blaOXA–58 (60.29 to 1.54%), carO (37.50 to 7.69%), and adeB (9.56 to 3.08%) decreased (P < 0.0001). Interestingly, the frequency of class B β-lactamase genes decreased from 91.18% (blaSPM–1) and 61.03% (blaIMP–1) to 0%, while that of class D blaOXA–23 increased to 96.92% (P < 0.0001). WGS showed that the major PFGE types causing outbreaks each year (type 01, 11, 18, 23, 26, and 31) carried the same resistance genes (blaKPC–1, blaADC–25, blaOXA–66, and adeABC), AdeR-S mutations (G186V and A136V), and a partially blocked porin channel CarO. Meanwhile, plasmids harboring blaOXA–23 were found after the intervention.ConclusionThe intervention was highly effective in reducing multi-drug resistance of A. baumannii and IRAB outbreaks in the long term. The resistance mechanisms of IRAB may involve genes encoding β-lactamases, efflux pump overexpression, outer membrane porin blockade, and plasmids; in particular, clonal spread of blaOXA–23 was the major cause of outbreaks. Similar interventions may also help reduce bacterial resistance rates and outbreaks in other hospitals.

Download Full-text

On the relationship between drug’s size, cell membrane mechanical properties and high levels of multi drug resistance: a comparison to published data

European Biophysics Journal ◽

10.1007/s00249-008-0385-x ◽

2008 ◽

Vol 38 (4) ◽

pp. 537-546 ◽

Cited By ~ 27

Author(s):

Cyril Rauch

Keyword(s):

Mechanical Properties ◽

Drug Resistance ◽

Cell Membrane ◽

Multi Drug Resistance ◽

Published Data ◽

The Relationship ◽

Membrane Mechanical Properties

Download Full-text

The clarifying role of time series data in the population genetics of HIV

10.1101/495275 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alison F Feder ◽

Pleuni S Pennings ◽

Dmitri A Petrov

Keyword(s):

Time Series ◽

Drug Resistance ◽

Population Genetics ◽

Time Series Data ◽

Hiv Treatment ◽

Series Data ◽

Adaptive Landscape ◽

Resistance Evolution ◽

Hiv Drugs ◽

Traditional Population

HIV can evolve remarkably quickly in response to anti-retroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate them. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al. 2016), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. We interpret this as evidence that resistance to early HIV drugs that failed quickly and predictably was driven by soft sweeps while evolution of resistance to better drugs is both less frequent and when it takes place it is associated with harder sweeps due to an effectively lower HIV population mutation rate (θ). Recently, Harris et al. 2018 have proposed an alternative interpretation: the signal could be due to an increase in the selective benefit of mutations conferring resistance to better drugs. Therefore, better drugs lead to faster sweeps with less opportunity for recombination to rescue diversity. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.

Download Full-text

Competition delays multi-drug resistance evolution during combination therapy

Journal of Theoretical Biology ◽

10.1016/j.jtbi.2020.110524 ◽

2021 ◽

Vol 509 ◽

pp. 110524

Author(s):

Ernesto Berríos-Caro ◽

Danna R. Gifford ◽

Tobias Galla

Keyword(s):

Drug Resistance ◽

Combination Therapy ◽

Multi Drug Resistance ◽

Resistance Evolution

Download Full-text

Establishment and multi drug resistance evolution of ST235 Pseudomonas aeruginosa strains in the intensive care unit of a Colombian hospital

Research in Microbiology ◽

10.1016/j.resmic.2014.10.011 ◽

2014 ◽

Vol 165 (10) ◽

pp. 852-856 ◽

Cited By ~ 6

Author(s):

Elena Martinez ◽

Javier Escobar Pérez ◽

Francisco Buelvas ◽

Catalina Tovar ◽

Natasha Vanegas ◽

...

Keyword(s):

Intensive Care Unit ◽

Pseudomonas Aeruginosa ◽

Drug Resistance ◽

Intensive Care ◽

Multi Drug Resistance ◽

Resistance Evolution

Download Full-text

Drug-sensitivity test and analysis of drug-resistant mutations in Mycobacterium tuberculosis isolates from Kashgar, China

European Journal of Inflammation ◽

10.1177/20587392211041437 ◽

2021 ◽

Vol 19 ◽

pp. 205873922110414

Author(s):

Zhongchen Ma ◽

Tianhao Sun ◽

Xinyu Bai ◽

Xiang Ji ◽

Qian Zhang ◽

...

Keyword(s):

Drug Resistance ◽

Mycobacterium Tuberculosis ◽

Dna Sequencing ◽

High Sensitivity ◽

Drug Susceptibility ◽

Resistance Rate ◽

Clinical Isolates ◽

Multi Drug Resistance ◽

Drug Resistant ◽

Resistance Rates

Introduction In recent years, drug-resistant Mycobacterium tuberculosis strains have gradually become widespread. Most drug resistance is related to specific mutations. We investigated M. tuberculosis drug resistance in the Kashgar area, China. Methods The drug-susceptibility test was conducted to clinical isolates of M. tuberculosis. Genomic-sequencing technology was used for the drug-resistant strains and the significance of DNA sequencing as a rapid aid for drug-resistance detection and the diagnosis method was evaluated. Results The resistance rates of clinical isolates to rifampicin (RFP), isoniazid (INH), streptomycin (SM), ethambutol (EMB), and ofloxacin (OFX) were, respectively, 4.4%, 12.3%, 8.8%, 2.6%, and 3.5%. The single- and multi-drug resistance rates were, respectively, 80.0% and 20.0%. The resistance genes RopB, katG, InhA, RpsL, rrs, gyrA, and embB displayed codon mutations, while InhA was mutated in its promoter region. Kappa scores, evaluating the consistency between DNA sequencing and the resistance ratio methods for the detection of isolates’ resistance to RFP, INH, SM, OFX, and EMB, were 1, 0.955, 0.721, 0.796, and 1, respectively. Conclusion The resistance rate of INH and SM is relatively high in the Kashgar area. Detection of mutations in RopB, katG, InhA, RpsL, rrs, gyrA, and embB by DNA sequencing can predict drug resistance of M. tuberculosis strains with high sensitivity and specificity, and can be used for diagnosis.

Download Full-text