Number Of Resistance Mutations Research Articles

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C.

Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.

Comprehensive Profiling of Mutations to Influenza Virus PB2 That Confer Resistance to the Cap-Binding Inhibitor Pimodivir.

Antivirals are used not only in the current treatment of influenza but are also stockpiled as a first line of defense against novel influenza strains for which vaccines have yet to be developed. Identifying drug resistance mutations can guide the clinical deployment of the antiviral and can additionally define the mechanisms of drug action and drug resistance. Pimodivir is a first-in-class inhibitor of the polymerase basic protein 2 (PB2) subunit of the influenza A virus polymerase complex. A number of resistance mutations have previously been identified in treated patients or cell culture. Here, we generate a complete map of the effect of all single-amino-acid mutations to an avian PB2 on resistance to pimodivir. We identified both known and novel resistance mutations not only in the previously implicated cap-binding and mid-link domains, but also in the N-terminal domain. Our complete map of pimodivir resistance thus enables the evaluation of whether new viral strains contain mutations that will confer pimodivir resistance.

Molecular Characterization of gyrA, parC and qepA Genes in Quinolone Resistant ESBL Producing E. Coli Isolated from Patients in HTAA, Kuantan

Introduction: Quinolone resistance and extended spectrum beta lactamase production has increased in E.coli and considered a serious problem worldwide. It is worth to monitor resistance mechanism in E.coli to provide guidance for optimizing antimicrobial treatments,control and spread of resistance. The objective of this study was to molecularly characterize gyrA, parC genes and plasmid mediated qepA efflux pump gene, in QR-ESBL E. coli isolates obtained from patients in HTAA, Kuantan. The antibiotic susceptibility profile was also studied. Materials and Method: 32 QR-ESBL and six quinolone-susceptible E. coli isolates from September 30 November,2018) included in the study. The isolates were reconfirmed with known phenotypic tests and antibiotic susceptibility test was performed. PCR and DNA sequencing were performed for the identification of mutations in quinolone resistance determining region. Result: Resistance to ampicillin, tetracycline, nalidixic acid was (100%) followed by cefotaxime (96.9%), ciprofloxacin (78.1%) trimethoprim sulfamethoxazole (75%), ceftazidime (56.3%), cefepime (43.8%) and gentamycin (25%). None of the isolates was resistant to piperacillin-tazobactam, amikacin, imipenem, meropenem, ertapenem, and colistin. PCR successfully amplified the gyrA and parC genes, however, qepA gene was not detected by PCR in the isolates. Majority of the isolates had point mutation in (QRDR) of GyrA at codons 83 and 87 and in ParC at codons 80 and 84. Two isolates had mutations outside of QRDR at codons 144 and 167 in ParC. Strong positive correlation was found between MIC levels of ciprofloxacin and the number of resistance mutations. Sequencing of 6 (QS-ESBL) E. coli revealed absence of resistance mutations. Conclusion: Quinolone resistance in the isolates was mainly due to mutations in gyrA, ParC genes. Acquisition of multidrug resistance genes through innate gene mutations and mobile genetic elements contribute to the emergence of (MDR). This study reinforces the importance of being vigilant in utilizing molecular techniques to monitor for emergence of resistance genes in different locations.

Population Genomics of Herbicide Resistance: Adaptation via Evolutionary Rescue.

The evolution of herbicide resistance in weed populations is a highly replicated example of adaptation surmounting the race against extinction, but the factors determining its rate and nature remain poorly understood. Here, we explore theory and empirical evidence for the importance of population genetic parameters-including effective population size, dominance, mutational target size, and gene flow-in influencing the probability and mode of herbicide resistance adaptation and its variation across species. We compiled data on the number of resistance mutations across populations for 79 herbicide-resistant species. Our findings are consistent with theoretical predictions that self-fertilization reduces resistance adaptation from standing variation within populations, but increases independent adaptation across populations. Furthermore, we provide evidence for a ploidy-mating system interaction that may reflect trade-offs in polyploids between increased effective population size and greater masking of beneficial mutations. We highlight the power of population genomic approaches to provide insights into the evolutionary dynamics of herbicide resistance with important implications for understanding the limits of adaptation.

WGS accurately predicts antimicrobial resistance in Escherichia coli.

The objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes. Seventy-six E. coli strains were isolated from farm cattle and measured for phenotypic resistance to 15 antimicrobials with the Sensititre(®) system. Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq. Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance. Over 30 resistance genes and a number of resistance mutations were identified among the E. coli isolates. Resistance genotypes correlated with 97.8% specificity and 99.6% sensitivity to the identified phenotypes. The majority of discordant results were attributable to the aminoglycoside streptomycin, whereas there was a perfect genotype-phenotype correlation for most antibiotic classes such as tetracyclines, quinolones and phenicols. WGS also revealed information about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance. WGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.

Abstract 1224: A patient derived xenograft (PDX) platform for development of next generation KIT kinase inhibitors in imatinib-resistant gastrointestinal stromal tumors (GIST)

Abstract Despite best efforts in the treatment of gastrointestinal stromal tumors (GIST), patients continue to face a poor prognosis. That said, introduction of imatinib into clinical practice has vastly improved outcomes for KIT positive patients. However, as with many kinases, resistance has developed into a clinical dilemma, rendering the drug ineffective. A number of resistance mutations have previously been identified including the well known D816 activating mutation. To overcome this challenge, we have established a set of GIST patient derived xenograft models to recapitulate the original patient tumor, including genetics of resistance. In this work, we show four primary GIST samples which were selected based on mutational and clinical profile. PDX models were developed in immunocompromised mice and were further characterized by immunohistochemistry, additional sequencing and pharmacological efficacy. We then evaluated the efficacy of chemotherapeutic agents in these models. We describe imatinib resistance mutations, and demonstrate in vivo efficacy of dasatinib over imatinib in the resistant GIST PDX model. Take together, this data validates these GIST PDX models as a novel platform for the evaluation of new drug candidates to better delay and circumvent resistance now found in the clinic. Citation Format: Chelsea Mullins, Jill Ricono, Patrick Carson, Gaston Habets, Rafe Shellooe, Hoa Nguyen, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair. A patient derived xenograft (PDX) platform for development of next generation KIT kinase inhibitors in imatinib-resistant gastrointestinal stromal tumors (GIST). [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1224. doi:10.1158/1538-7445.AM2014-1224

Interplay between plasmid-mediated and chromosomal-mediated fluoroquinolone resistance and bacterial fitness in Escherichia coli.

The aim of this study was to analyse the interplay among plasmid-mediated qnr genes, alone or in combination with multiple chromosomal-mediated fluoroquinolone (FQ) resistance determinants, susceptibility to FQs and bacterial fitness in an isogenic Escherichia coli collection. E. coli ATCC 25922 was used to modify or delete chromosomal genes. qnr genes were cloned into the pBK-CMV vector. The MICs of FQs were determined by microdilution. Mutant prevention concentration and frequency of mutants were evaluated. Bacterial fitness was analysed using ΔlacZ system competition assays using in vitro and in vivo models. The relationships between the number of resistance mutations and bacterial fitness were complex. With specific combinations of resistance mechanisms the addition of a new resistance mutation was shown to improve bacterial fitness. qnrA1 caused a decrease in fitness (7%-21%) while qnrS1 caused an increase in fitness (9%-21%) when combined with chromosomal mutations. We identified susceptible triple mutants in which the acquisition of a fourth resistance mutation significantly increased fitness and at the same time reached the clinical resistance level (the acquisition of qnrS1 in a S83L + D87N + ΔmarR genetic background). A strong correlation with the production of reactive oxygen species, as well as changes in susceptibility, was observed following treatment with ciprofloxacin. Our data indicate that there may be critical stages (depending on the genotype) in resistance development, including chromosomal- and plasmid-mediated mechanisms, at which some low-fitness mutants below the resistance breakpoint are able to evolve clinical resistance with just one or two mutations, and show increased fitness.

HIV Type 1 Antiretroviral Resistance Mutations in Subtypes B, C, and F in the City of São Paulo, Brazil

In Brazil, where three distinct HIV-1 subtypes (B, F, and C) cocirculate, a significant portion of the HIV-infected population has been exposed to antiretroviral drugs. This study analyzes the antiretroviral resistance profiles of HIV-1-infected individuals failing antiretroviral therapy. Genotypic resistance profiles of 2474 patients presenting virologic failure to antiretroviral therapy in the city of São Paulo, Brazil, were generated and analyzed. Resistance mutations to protease inhibitors and nucleoside reverse transcriptase inhibitors were less common in subtype C viruses, whereas nonnucleoside reverse transcriptase inhibitor resistance mutations were less common in subtype F viruses. The thymidine analog mutation pathway known as pathway 1 was more prevalent in subtype B viruses than in subtype C viruses, whereas pathway 2 was more prevalent in subtype C viruses. Selected resistance mutations varied according to subtype for all three classes of antiretrovirals. We describe two distinct pathways of nonnucleoside reverse transcriptase inhibitor resistance (to nevirapine and efavirenz). Although cross-resistance to etravirine should occur more frequently among individuals failing nevirapine treatment, the prevalence of cross-resistance to etravirine, darunavir, and tipranavir was found to be low. We found that increases in the number of resistance mutations will be related to increases in the viral load. Special attention should be given to resistance profiles in non-B subtype viruses. The accumulation of knowledge regarding such profiles in the developing world is desirable.

Atazanavir en terapias de rescate

Virological failure of antiretroviral treatment increases the morbidity and mortality associated with AIDS. With currently available drugs it is possible to achieve an HIV - PVL < 50 copies of aRNA/mL in a significant percentage of patients with virological failure, even in those who accumulate a considerable number of resistant mutations in the viral genome. Compliance continues to be the most significant cause of antiretroviral treatment failure. Atazanavir boosted with ritonavir has clear advantages over other protease inhibitors (PI), such as its administration once per day, low number of tablets and a good tolerance which helps in compliance, as well as a lower metabolic toxicity and a resistances profile different to other PIs. Boosted Atazanavir in rescue treatments would be strongly recommended in patients naive to a PI or when there are < 3 mutations in the basic genotype in positions: 10F/I/V, 16E, 33I/F/V, 46I/L, 60E, 84V, 85 V and 90M of the protease gene, particularly when the patient has problems of compliance to antiretroviral treatment or metabolic disorders, such as dyslipaemia, insulin resistance, fasting blood glucose changes, a cardiovascular risk at 10 years of > 10% or cardiovascular disease.

Predictive strength of Jonckheere's test for trend: an application to genotypic scores in HIV infection

A problem arising in studies on the human immunodeficiency virus (HIV) infection relate to one-sided tests with ordered alternatives as opposed to the more classical two-sided tests. Patients not having a resistance mutation may have a better virologic response to treatment than patients with a single mutation. In turn, those with a single mutation may have a better response to treatment than those patients having two mutations, and so on. In the presence of a continuous outcome, Jonckheere's test for ordered alternatives is well adapted to this situation. Such an analysis does not provide any measure of prediction or explained variation which can complement these results. A measure of strength of effect would be helpful in quantifying the degree of association between the genotypic score (number of mutations) and some continuous virological response. We suggest a simple measure of 'goodness of split' for Jonckheere's test for trend. Interestingly, the measure can be related to the non-parametric measure of association known as gamma. The variance formula for the measure studied here can be seen to differ from the known variance estimate of the gamma measure, and simulations show it to be more accurate. Expectation and variance under H(0) of the measure are provided and a large simulation study is presented. Methods are applied to a recent clinical data set involving HIV-1 infected patients where the number of resistance mutations are investigated as potential predictors of the amount of HIV-1 RNA reduction at week 4.

Protease inhibitor associated mutations compromise the efficacy of therapy in human immunodeficiency virus – 1 (HIV-1) infected pediatric patients: a cross-sectional study

BackgroundAlthough the introduction of combined therapy with reverse transcriptase and protease inhibitors has resulted in considerable decrease in HIV related mortality; it has also induced the development of multiple drug-resistant HIV-1 variants.The few studies on HIV-1 mutagenesis in HIV infected children have not evaluated the impact of HIV-1 mutations on the clinical, virological and immunological presentation of HIV disease that is fundamental to optimizing the treatment regimens for these patients.ResultsA cross sectional study was conducted to evaluate the impact of treatment regimens and resistance mutation patterns on the clinical, virological, and immunological presentation of HIV disease in 41 children (25 male and 16 female) at the Robert Wood Johnson Pediatric AIDS Program in New Brunswick, New Jersey. The study participants were symptomatic and had preceding treatment history with combined ARV regimens including protease inhibitors (PIs), nucleoside reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs). Fifteen (36.6%) children were treated with NRTI+NNRTI+ PI, 6 (14.6%) with NRTI+NNRTIs, 13 (31.7%) with NRTI+PIs, and the remaining 7 (17.1%) received NRTIs only.Combined ARV regimens did not significantly influence the incidence of NRTI and NNRTI associated mutations. The duration of ARV therapy and the child's age had no significant impact on the ARV related mutations. The clinico-immunological presentation of the HIV disease was not associated with ARV treatment regimens or number of resistance mutations. However, primary mutations in the protease (PR) gene increased the likelihood of plasma viral load (PVL) ≥ 10,000 copies/mL irrespective of the child's age, duration of ARV therapy, presence of NRTI and NNRTI mutation. Viremia ≥ 10,000 copies/mL was recorded in almost all the children with primary mutations in the PR region (n = 12/13, 92.3%) as compared with only 50.0% (n = 14/28) of HIV infected children without (PR-), P < 0.008. However, CD-4 T cells were not affected by the mutations in the PR gene of the HIV-1 isolates.ConclusionPrimary PR resistance mutations significantly increase the likelihood for high viral replication in pediatric patients with moderate/severe HIV-1 infection, which may affect the long-term clinical prognosis of the HIV infected children.

Ability of different lopinavir genotypic inhibitory quotients to predict 48-week virological response in highly treatment-experienced HIV-infected patients receiving lopinavir/ritonavir

The genotypic inhibitory quotient (GIQ) is the ratio between drug concentration and the number of resistance mutations. However, as different resistance scores can be calculated for the same protease inhibitor, the ability of a GIQ to predict the virological outcome may vary depending on the resistance score used as the denominator. Forty-four highly treatment-experienced HIV-infected patients failing on their current regimen were treated with a lopinavir/ritonavir-containing combination for at least 48 weeks. Three GIQs were calculated for each patient: the denominator of the first (GIQ-A) was the lopinavir/ritonavir score calculated using the mutations listed by IAS-USA as being related to lopinavir/ritonavir resistance; the denominator of the second (GIQ-B) was the total number of mutations related to resistance to any protease inhibitor as reported by IAS-USA; and the denominator of the third (GIQ-C) was the lopinavir/ritonavir score proposed by Parkin et al. The median (IQR) of the GIQ-A, B, and C was 4.69 (3.83-9.76), 0.97 (0.74-1.62), and 1.02 (0.68-2.52), respectively. At week 48, the median decrease in HIV-RNA was 1.09 (0.32-2.34) log(10) copies/ml (P < 0.0001), with 13 subjects (29.5%) attaining undetectable levels. All of the GIQs independently predicted the change in viral load from baseline and undetectable HIV-RNA at week 48. The partial R(2) of GIQ-C was greater than that of GIQ-B, which was greater than that of GIQ-A. All of the GIQs were independent predictors of the 48-week virological response. The predictive value of the GIQ for lopinavir/ritonavir may vary depending on the algorithm used to score drug resistance.

Mutation rate and evolution of fluoroquinolone resistance in Escherichia coli isolates from patients with urinary tract infections.

Escherichia coli strains from patients with uncomplicated urinary tract infections were examined by DNA sequencing for fluoroquinolone resistance-associated mutations in six genes: gyrA, gyrB, parC, parE, marOR, and acrR. The 54 strains analyzed had a susceptibility range distributed across 15 dilutions of the fluoroquinolone MICs. There was a correlation between the fluoroquinolone MIC and the number of resistance mutations that a strain carried, with resistant strains having mutations in two to five of these genes. Most resistant strains carried two mutations in gyrA and one mutation in parC. In addition, many resistant strains had mutations in parE, marOR, and/or acrR. No (resistance) mutation was found in gyrB. Thus, the evolution of fluoroquinolone resistance involves the accumulation of multiple mutations in several genes. The spontaneous mutation rate in these clinical strains varied by 2 orders of magnitude. A high mutation rate correlated strongly with a clinical resistance phenotype. This correlation suggests that an increased general mutation rate may play a significant role in the development of high-level resistance to fluoroquinolones by increasing the rate of accumulation of rare new mutations.

Mutation patterns of the reverse transcriptase and protease genes in human immunodeficiency virus type 1-infected patients undergoing combination therapy: survey of 787 sequences.

The aim of the present study was to evaluate the resistance-associated mutations in 302 human immunodeficiency virus type 1 (HIV-1)-infected patients receiving combination therapy and monitored in Marseille, France, hospitals from January 1997 to June 1998. In the reverse transcriptase (RT) gene, the most frequent mutations were found at codons 215 (53%), 41 (34%), and 67, 70, 184, and 210 (>20%). One deletion and two insertions in the beta3-beta4 hairpin loop of the finger subdomain (codon 69) were detected. Interesting associations and/or exclusions of specific mutations were observed. In 96% of RT genes, a mutation at codon 70 (most frequently, K70R) was associated with a wild-type genotype at position 210 (P < 10(-5)). Similarly, a mutation at codon 210 (most frequently, L210W) was generally associated with mutations at codons 41 (92%) and 215 (96%) but not at codon 219 (16%) or codon 70 (4%) (P < 10(-5)). In the protease gene, the most prevalent mutations were at codons 63 (84%), followed by codons 10, 36, 71, 77, and 93 (ca. 20%). As for RT, pairwise associations of mutations were observed. Analysis of the mutation patterns for patients with undetectable HIV-1 loads revealed a high proportion (65%) of wild-type RT genotypes but only 18% wild-type protease genotypes. For patients with high viral loads (>100,000 copies/ml), more than 50% of the RT and protease genes displayed three or more mutations. The significant correlation between the level of viremia in plasma and the number of resistance mutations in the protease (P = 0.007) and RT (P = 0.00078) genes strengthens the importance of defining the genotype of the predominant HIV-1 quasispecies before initiating antiretroviral therapy.