Abstract Objectives The presence of minority transmitted drug resistance mutations was assessed using ultra-deep sequencing and correlated with disease progression among recently HIV-1-infected individuals from Brazil. Methods Samples at baseline during recent infection and 1 year after the establishment of the infection were analysed. Viral RNA and proviral DNA from 25 individuals were subjected to ultra-deep sequencing of the reverse transcriptase and protease regions of HIV-1. Results Viral strains carrying transmitted drug resistance mutations were detected in 9 out of the 25 patients, for all major antiretroviral classes, ranging from one to five mutations per patient. Ultra-deep sequencing detected strains with frequencies as low as 1.6% and only strains with frequencies >20% were detected by population plasma sequencing (three patients). Transmitted drug resistance strains with frequencies <14.8% did not persist upon established infection. The presence of transmitted drug resistance mutations was negatively correlated with the viral load and with CD4+ T cell count decay. Conclusions Transmitted drug resistance mutations representing small percentages of the viral population do not persist during infection because they are negatively selected in the first year after HIV-1 seroconversion. Introduction The worldwide prevalence of transmitted drug resistance (TDR) ranges from 10% to 17% among individuals harbouring HIV-1 who are ART naive.1 The USA and European countries account for the highest levels of TDR, at 14.2%2 and 10.9%,3 respectively. In Brazil, the prevalence is considered intermediate, primarily ranging from 5% to 15% throughout the country.4 It has been previously reported that patients carrying TDR mutations reach viral suppression more slowly than patients infected with WT viruses alone after the initiation of ART5 and that patients carrying TDR mutations are also more prone to virological failure.6 Ultra-deep sequencing (UDS) technologies allow the detection of resistant strains present in the viral population with frequencies as low as 0.3%,7 suggesting that the prevalence of patients carrying TDR mutations is much greater when more sensitive sequencing techniques are employed than when conventional techniques are used.8 Here, the presence of TDR mutations was assessed among recently HIV-1-infected patients during acute infection and during established infection, before the initiation of therapy. Patients and methods Twenty-five patients from a previously described cohort9 of recently HIV-1-infected individuals were randomly selected for this study and samples collected between 2002 and 2009 were retrospectively analysed. The individuals were at least 18 years old at the time of recruitment, ART naive and diagnosed with recent HIV-1 infection based on the Serologic Testing Algorithm for Recent HIV Seroconversion (STARHS); therefore, all individuals were assigned to Fiebig stage 3.10 The patients’ diagnoses were confirmed by positive test results 6 months later. Individuals were antiretroviral free until their CD4+ T cell counts fell to levels <350 cells/mm3 of blood. Informed written consent was obtained from all patients and the study was approved by the ethics committee and the institutional review board of the Federal University of Sao Paulo (#0919/01). Plasma and PBMC samples from two timepoints of infection, recent (T1) and established (T2), were obtained, the average period between the two timepoints being 1.4 years (±0.15). Viral cDNA and proviral DNA were quantified by real-time PCR11 and independent nested PCR, containing specific primers for the protease (PR) and reverse transcriptase (RT1 and RT2); this was performed for each patient from cDNA and DNA samples, according to the 454 Amplicon Universal Tail Approach protocol (Roche). We used a minimum input of 1000 viral copies for each PCR, thus reaction volumes varied between 25 and 100 μL, and sample volumes varied between 2 and 10 μL. Whenever the viral input was <1000 viral copies, the maximum number of target cDNA present in the sample was submitted to new amplification. Details of the PCR components and thermocycling conditions are described in Table S1 (available as Supplementary data at JAC Online). Positive samples were submitted to a third round of PCR in order to add the 454 UDS barcodes in each sample. UDS reactions were multiplexed with barcodes in such a way as to generate at least 2000 sequences for each sample. Third-round PCR products were purified using magnetic beads (Beckman Coulter) and submitted to a new quantification, using the Quant-it dsDNA Broad Range Assay Kit (Invitrogen), according to the manufacturer’s instructions. Amplified samples were diluted to 109 molecules/μL and pooled, according to Amplicon Library Preparation (Roche). UDS was carried out using GS Junior Titanium Series system (Roche). The DNA library was then submitted to emulsion PCR (emPCR), using the emPCR Reagents kit (Lib-A) (Roche), according to the manufactureŕs instructions. After emPCR, DNA beads were enriched and placed on a PicoTiter Plate (Roche) and submitted to UDS using the GS Junior equipment (Roche). UDS technologies are very error prone, especially at homopolymeric regions of the genome. Therefore, it is mandatory that all generated sequences undergo error correction and handling to avoid overestimation of the viral genetic diversity. The error rate of our system was estimated using three different plasmids (pHXB2r, pNL4.3 and pBaL), all containing full-genome HIV-1 sequences. The plasmids were submitted to nested PCR amplification and UDS of the V3 region under the same conditions as the study samples. Because the plasmids were all generated by sub-cloning and have known genome sequences, we considered that any alteration from the original sequence detected after UDS was an error. The presence of polymorphisms was analysed using Geneious R7 software (Biomatters), where the frequency of polymorphisms varied between 0.1% and 1.6%. Thus, we considered any diversity with a prevalence of ≤1.6% as an error and these sequences were excluded from the analysis. Therefore, all sequences carrying polymorphisms with frequencies ≤1.6% were corrected by returning to the consensus sequence. After the error correction step, duplicate sequences were extracted and the number of strains was normalized to the number of viral copies used as input for the first round of amplification. Population plasma sequencing was performed as previously described.12 The genotypic estimation of transmitted HIV-1 drug resistance was performed using the Calibrated Population Resistance tool (available at http://hivdb.stanford.edu). All statistical analyses were conducted with IBM® SPSS® Statistics, version 21.0 (IBM). The Shapiro–Wilk test was applied to verify normality. Parametric comparisons between two independent groups were performed with Student’s t-test, while non-parametric comparisons were performed with the Mann–Whitney test. When three independent groups were evaluated, the Kruskal–Wallis test was employed, and the significance of differences between groups was verified by the Mann–Whitney test considering the proper corrections. The correlations were assessed by a non-parametric Spearman’s ρ test. All reported P values are for a two-sided test and P values were considered significant when <0.05. Results and discussion Of note, one European study revealed that patients with TDR mutations were three times more likely to experience virological failure within the first year after antiretroviral initiation.13 In Brazil, the TDR mutation prevalence is 11.8%, according to a nationwide study of patients initiating HAART from 2009 to 2010. In the present study, 9 out the 25 patients evaluated by UDS were infected with TDR strains and the number of mutations varied from one to five per patient, whereas 3 out of the 25 patients had TDR mutations detected by population sequencing. The following NRTI resistance mutations were detected: M41L, D67N, K70R, M184I, M184V, K219E and T215S. Regarding NNRTI resistance mutations, K101E and K103N were detected. Mutations M46I and L67V, associated with resistance to PIs, were also detected. Therefore, 6.9% were resistant to NRTIs and 4.9% were resistant to NNRTIs, consistent with a worldwide trend among long-term-infected individuals.14 Nevertheless, the TDR prevalence in our study was significantly higher than the previous estimation in Brazil,4,15–19 although high levels of resistance have been detected in specific sites of the country,12,20 and the sample size of the current study is rather small compared with the above-mentioned surveys using population sequencing. Furthermore, the current study analysed individuals during recent HIV infection whereas the above-mentioned surveys analysed individuals with long-standing HIV infections. At baseline, TDR mutations were detected in both plasma RNA and proviral DNA in 3/9 individuals, only in proviral DNA in 4/9 individuals and only in plasma RNA in 2/9 patients (Table 1). All three individuals harbouring mutations in both plasma RNA and PBMCs had the detected mutations at the follow-up timepoint (T2). All four patients harbouring mutations only in PBMCs and the two patients harbouring mutations detected only in the plasma at baseline reverted to WT at T2 (Table 1). Table 1. HIV-1 TDR mutations detected during recent infection among therapy-naive patients from Brazil (T1) and after an average of 1.4 years (±0.15) (T2) Subject Timepoint VL CD4 Mutations associated with transmitted antiretroviral resistancea NRTI (comp, %) NNRTI (comp, %) PI (comp, %) 1006b T1 1900 362 – K103N (BC, 1.9) – T2 17 000 423 – – – 1019 T1 47 400 542 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) T2 26 100 671 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) 1030 T1 32 600 519 – – M46I (BC, 10.4) T2 30 100 482 – – – 1109 T1 29 500 647 – – M46I (PL, 3.3) T2 92 906 – – – 1124 T1 5520 591 – K103N (PL, 100.0) – T2 4109 452 – K103N (BC, 100.0) – 2005 T1 3500 726 M41L (BC, 100.0) – – K70R (BC, 100.0) M184I (BC, 6.6) T2 19 700 299 – – – 2018b T1 31 900 268 M184V (BC, 60.0) K103N (BC, 100.0/PL, 86.8) – T2 345 399 – K103N (BC, 93.0/PL, 97.0) – 2043b T1 2040 596 T215S (PL, 4.5) – – T2 616 544 – – – 2054b T1 40 980 449 – – M46I (BC/PL, 14.8) T2 344 49 – – M46I (PL, 16.7) Subject Timepoint VL CD4 Mutations associated with transmitted antiretroviral resistancea NRTI (comp, %) NNRTI (comp, %) PI (comp, %) 1006b T1 1900 362 – K103N (BC, 1.9) – T2 17 000 423 – – – 1019 T1 47 400 542 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) T2 26 100 671 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) 1030 T1 32 600 519 – – M46I (BC, 10.4) T2 30 100 482 – – – 1109 T1 29 500 647 – – M46I (PL, 3.3) T2 92 906 – – – 1124 T1 5520 591 – K103N (PL, 100.0) – T2 4109 452 – K103N (BC, 100.0) – 2005 T1 3500 726 M41L (BC, 100.0) – – K70R (BC, 100.0) M184I (BC, 6.6) T2 19 700 299 – – – 2018b T1 31 900 268 M184V (BC, 60.0) K103N (BC, 100.0/PL, 86.8) – T2 345 399 – K103N (BC, 93.0/PL, 97.0) – 2043b T1 2040 596 T215S (PL, 4.5) – – T2 616 544 – – – 2054b T1 40 980 449 – – M46I (BC/PL, 14.8) T2 344 49 – – M46I (PL, 16.7) VL, HIV-1 RNA viral load in copies/mL; CD4, CD4+ T cell count in cells/mm3 of blood; comp, viral compartment; BC, PBMCs; PL, plasma. T1 refers to the timepoint at which the patients were recruited and diagnosed as recently infected with HIV-1 and T2 refers to the timepoint 1 year after recruitment, when HIV-1 infection is established. a According to the Calibrated Population Resistance tool. b Individuals who started ART with zidovudine, lamivudine and efavirenz after their CD4 T cell counts decreased to a level <350 cells/mm3, and VL and CD4 levels refer to a time before 12 weeks of treatment. Individual 2018 experienced virological treatment failure after 12 weeks of treatment, although other HAART-treated individuals acquired a VL below detection limits after 12 weeks of treatment. Table 1. HIV-1 TDR mutations detected during recent infection among therapy-naive patients from Brazil (T1) and after an average of 1.4 years (±0.15) (T2) Subject Timepoint VL CD4 Mutations associated with transmitted antiretroviral resistancea NRTI (comp, %) NNRTI (comp, %) PI (comp, %) 1006b T1 1900 362 – K103N (BC, 1.9) – T2 17 000 423 – – – 1019 T1 47 400 542 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) T2 26 100 671 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) 1030 T1 32 600 519 – – M46I (BC, 10.4) T2 30 100 482 – – – 1109 T1 29 500 647 – – M46I (PL, 3.3) T2 92 906 – – – 1124 T1 5520 591 – K103N (PL, 100.0) – T2 4109 452 – K103N (BC, 100.0) – 2005 T1 3500 726 M41L (BC, 100.0) – – K70R (BC, 100.0) M184I (BC, 6.6) T2 19 700 299 – – – 2018b T1 31 900 268 M184V (BC, 60.0) K103N (BC, 100.0/PL, 86.8) – T2 345 399 – K103N (BC, 93.0/PL, 97.0) – 2043b T1 2040 596 T215S (PL, 4.5) – – T2 616 544 – – – 2054b T1 40 980 449 – – M46I (BC/PL, 14.8) T2 344 49 – – M46I (PL, 16.7) Subject Timepoint VL CD4 Mutations associated with transmitted antiretroviral resistancea NRTI (comp, %) NNRTI (comp, %) PI (comp, %) 1006b T1 1900 362 – K103N (BC, 1.9) – T2 17 000 423 – – – 1019 T1 47 400 542 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) T2 26 100 671 D67N (BC/PL, 100.0) K101E (BC/PL, 100.0) M46I (BC/PL, 100.0) K219E (BC/PL, 100.0) L67V (BC/PL, 100.0) 1030 T1 32 600 519 – – M46I (BC, 10.4) T2 30 100 482 – – – 1109 T1 29 500 647 – – M46I (PL, 3.3) T2 92 906 – – – 1124 T1 5520 591 – K103N (PL, 100.0) – T2 4109 452 – K103N (BC, 100.0) – 2005 T1 3500 726 M41L (BC, 100.0) – – K70R (BC, 100.0) M184I (BC, 6.6) T2 19 700 299 – – – 2018b T1 31 900 268 M184V (BC, 60.0) K103N (BC, 100.0/PL, 86.8) – T2 345 399 – K103N (BC, 93.0/PL, 97.0) – 2043b T1 2040 596 T215S (PL, 4.5) – – T2 616 544 – – – 2054b T1 40 980 449 – – M46I (BC/PL, 14.8) T2 344 49 – – M46I (PL, 16.7) VL, HIV-1 RNA viral load in copies/mL; CD4, CD4+ T cell count in cells/mm3 of blood; comp, viral compartment; BC, PBMCs; PL, plasma. T1 refers to the timepoint at which the patients were recruited and diagnosed as recently infected with HIV-1 and T2 refers to the timepoint 1 year after recruitment, when HIV-1 infection is established. a According to the Calibrated Population Resistance tool. b Individuals who started ART with zidovudine, lamivudine and efavirenz after their CD4 T cell counts decreased to a level <350 cells/mm3, and VL and CD4 levels refer to a time before 12 weeks of treatment. Individual 2018 experienced virological treatment failure after 12 weeks of treatment, although other HAART-treated individuals acquired a VL below detection limits after 12 weeks of treatment. The main advantage of our study is the sequencing methodology used, confirming the efficiency of UDS technologies in detecting viral strains with frequencies <20%, which is the best scenario for population sequencing using Sanger methodologies, and the majority of published studies on TDR to date were performed using population sequencing methods. Detection limits as low as 0.3%–0.5% have been reported for the detection of TDR mutations,7,21 and although the detection limit of our system was higher (1.6%), careful precautions against overestimation of the viral population were made, as described in the Patients and methods section. Notably, individuals 1006, 1030, 1109, 2043 and 2054 presented only minority TDR populations, with prevalence <20% (Table 1). Moreover, only TDR strains with frequencies >20% in the plasma were detected by both sequencing technologies in our study. We further characterized the persistence of the TDR mutations during the established infection time period (T2). Of the five patients infected with minority TDR strains, the resistant strains were fixed only in the viral population in Patient 2054, with a slight increase in prevalence (14.8% in T1 to 16.7% in T2) but with the disappearance of detectable TDR strains in the PBMCs at T2. In all other patients infected with TDR strains corresponding to <14.8% of the viral population at baseline, the minority strains were negatively selected during recent infection. Interestingly, Patient 2043 presented the revertant T215S at T1, which disappeared at T2. Moreover, individual 1124 harboured only K103N strains in the plasma at T1, yet at T2 this TDR mutation was no longer detected in the plasma but only in the PBMC compartment, suggesting that these strains were negatively selected in the circulating viral population and remained integrated in the host cell genomes. In contrast, individual 2005, presenting majority strains harbouring M41L and K70R and minority populations with M184I mutations in the PBMCs at T1, did not present any TDR mutation in either the plasma or the PBMCs at T2. The viral population of individual 2018 consisted of mainly K103N viral strains in the PBMCs (100%) and plasma (86.8%) and these strains remained as the majority when the T2 sequences were analysed. In addition, in the same patient, mutation M184V, present in 60% of the PBMC viral population during T1, was negatively selected at T2 (Table 1). Our results indicate that many TDR mutations representing small subsets of the viral population do not persist during infection due to their negative selection in the first year after HIV-1 seroconversion. Strains with a very high prevalence of TDR mutations, on the other hand, could persist and be fixed in the viral population. It has been demonstrated that there is a genetic bottleneck during HIV primary infection, where 76% of infections start with only one HIV strain, whereas 24% of infections start with between two and six HIV strain.22 It is conceivable that, in the case of a mixture of strains harbouring antiretroviral resistance mutations with antiretroviral-naive HIV strains, the TDR strain may become a minority in the HIV quasispecies population with the tendency to disappear, if this TDR strain presents lower replication capacity than the co-transmitted HIV-naive viruses as a result of a fitness cost related to antiretroviral resistance mutations. Notably, one individual had the so-called revertant mutation T215S without the presence of T215Y or T215F, thus arguing for the transmission of revertants and not true revertant mutations, which implies, in this case, the absence of cross-resistance to NRTIs. Interestingly, mutations were detected in both the plasma and PBMCs in three patients at T1 and these mutations were likely to persist. On the other hand, mutations present only in the plasma in two individuals and only in PBMCs in three individuals at T1 were not detected by UDS at T2, thus confirming that in the presence of mixtures of resistant and WT strains, selection will occur for the strains with better replicative fitness despite their presence in the plasma or PBMCs. The high prevalence of mixtures of WT and TDR strains revealed by more sensitive UDS tools also argues for the need to reconsider the true size of the genetic bottleneck upon HIV transmission and the need for highly sensitive genotyping tools to identify TDR mutations. Furthermore, a fitness cost of TDR mutations was confirmed, as shown by the lower viral loads among patients harbouring TDR mutations. Although in some cases the minority populations of TDR strains were no longer detected by UDS in T2, this fact does not necessarily mean that these TDR strains are no longer present or that treatment may not be impaired by its presence. In fact, low-frequency HIV-1 drug resistance mutations, particularly involving NNRTI resistance, have been significantly associated with increased risk of virological failure with first-line ART, especially when adherence to ART is low.5,23 When the prevalence of TDR mutations detected by UDS was compared with the prevalence detected by conventional sequencing methodologies, the latter showed resistant strains only in patients 1019, 1124 and 2018.12 Notably, the TDR strains corresponded to most of the viral population in these patients, indicating the higher sensitivity of UDS methodologies in detecting minority resistant viral strains. To evaluate the impact of TDR mutations on HIV-1 disease progression, patients were classified as having or not having mutations at T1 and different disease progression parameters, such as viral load and CD4+ T cell count, were measured. The mean HIV-1 viral load among patients with TDR mutations was log10 3.6 copies/mL (±0.6 copies/mL), significantly lower than the mean detected among patients with no TDR mutations (log10 4.2 ± 0.7 copies/mL) (Student’s t-test, t23 = −2.269; P = 0.033). Also, the mean CD4+ T cell count among patients with TDR mutations was higher (759.0 ± 388.0 cells/mm3 of blood) than the mean count for patients carrying no TDR mutation (550.1 ± 152.0 cells/mm3 of blood). Although this difference was not statistically significant (Mann–Whitney test, U = 52.0; P = 0.202), one can argue about the validity of using statistical comparisons in such a small, non-probabilistic sample. As individuals remained antiretroviral-free until their CD4 counts fell to a level <3500 cells/mm3 of blood , the further impact of TDR mutations on the CD4+ T cell count decay was investigated and an intermediate negative correlation was detected (Spearman’s ρ test, ρ = −0.450; P = 0.024), possibly due to the lower HIV-1 viral load among individuals harbouring TDR mutations. Unfortunately, the impact of specific TDR mutations on viral loads or CD4+ T cell count or decay was not possible due to the small sample size of this study. Four out of 9 individuals from the group with TDR mutations (Table 1), compared with 10 of 16 individuals without TDR mutations, started ART during follow-up using fixed-dose combination treatment with zidovudine/lamivudine and efavirenz after a decrease in their CD4+ T cell counts to a level <350 cells/mm3 of blood (Fisher’s exact test; P = 0.2). One individual from each group experienced antiretroviral virological failure (Fisher’s exact test; P = 0.5). Patient 1006 started treatment after the second analysed timepoint (T2; Table 1). Patient 2018, also from the TDR group, started ART with a viral load of 25 600 copies/mL and, not surprisingly, due to the presence of NRTI and NNRTI mutations, this individual experienced virological failure and was re-suppressed with a boosted PI-based therapy. ART initiation for this patient was before the T2 analysis and, as the patient was still viraemic at T2, a change in the resistance profile was not attributed to the selective pressure imposed by antiretroviral drugs. Patient 1004 from the non-TDR group started treatment with a viral load of 23 800 copies/mL and never suppressed viraemia due to low adherence to ART. Notably, Patient 2043 from the TDR group started treatment with a viral load of 37 200 copies/mL and presented frequent viral load blips of <200 copies/mL (data on file). This patient also started treatment before T2 and, like all other individuals, Patient 2043 was still viraemic at T2 with no evidence of further selection of antiretroviral resistance-related mutations. Patient 2054 also started ART immediately before T2, was still viraemic during T2 and ART did not contribute to selection of new resistance-related mutations (Table 1). The prevalence of TDR mutations among recently infected patients in Brazil was assessed by UDS to investigate two different compartments (plasma and PBMCs) and compare the results with the prevalence obtained using population sequencing. Moreover, the persistence of the resistant viral strains was assessed on average 1 year later. Finally, the presence of TDR mutations was correlated with disease progression parameters, such as viral load and CD4+ T cell count decay before ART initiation. We recognize that the sample size in the present study is limited, particularly with regard to evaluating the response to ART vis a vis minority TDR mutations. We also recognize that, as samples collection in this study included a fairly long period of time, including the years between 2002 and 2009, which may not reflect the current epidemiological picture of TDR. However, this report has been able to confirm the prevalence of minority TDR strains in different compartments and provide insight into the dynamics of drug resistance mutations and their impact on the viral loads and CD4 levels in newly HIV-1-infected individuals. Acknowledgements We thank Dr Will Fischer (Los Alamos National Laboratory, Los Alamos, NM, USA) for useful discussions on UDS analysis and for kindly providing Perl scripts. Funding This work was supported by the Sao Paulo Research Foundation (FAPESP) (2011/12156–0 research grant to R. S. D. and 2011/50238–8 PhD fellowship to A. R. L.). Transparency declarations None to declare. Supplementary data Table S1 is available as Supplementary data at JAC Online. References 1 Rhee SY , Blanco JL , Jordan MR et al. Geographic and temporal trends in the molecular epidemiology and genetic mechanisms of transmitted HIV-1 drug resistance: an individual-patient- and sequence-level meta-analysis . PLoS Med 2015 ; 12 : e1001810 . Google Scholar CrossRef Search ADS PubMed 2 Poon AF , Aldous JL , Mathews WC et al. Transmitted drug resistance in the CFAR network of integrated clinical systems cohort: prevalence and effects on pre-therapy CD4 and viral load . PLoS One 2011 ; 6 : e21189. Google Scholar CrossRef Search ADS PubMed 3 Frentz D , Boucher CA , van de Vijver DA. Temporal changes in the epidemiology of transmission of drug-resistant HIV-1 across the world . AIDS Rev 2012 ; 14 : 17 – 27 . Google Scholar PubMed 4 de Moraes Soares CM , Vergara TR , Brites C et al. 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Journal of Antimicrobial Chemotherapy – Oxford University Press
Published: Apr 19, 2018
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