Evolutional History of HIV-1 in Korea: Sequence Analysis of env gene in HIV-1 Korean B Subtype from 2006 to 2011

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Evolutional History of HIV-1 in Korea: Sequence Analysis of env gene in HIV-1 Korean B Subtype from 2006 to 2011

Mee-Kyung Kee*
AFFILIATIONS
Division of Viral Disease Research, Center for Infectious Diseases Research, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Cheongju, Republic of Korea
International Tuberculosis Research Center, Seoul, Republic of Korea
Corresponding author (Address):
Mee-Kyung Kee, Division of Viral Disease Research, Center for Infectious Diseases Research, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, International Tuberculosis Research Center, Seoul, Republic of Korea, Tel: +82-10-3127-1368, Fax: +82-50-4341-1368, E-mail: keemeekyung@gmail.com
, Sangmi Ryou
AFFILIATIONS
Division of Clinical Research, Center for Emerging Virus Research, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Chungbuk, Republic of Korea
, Yoon-Seok Chung
AFFILIATIONS
Honam Regional Center for Disease Control and Prevention, Regional Centers for Disease Control and Prevention, Korea Disease Control and Prevention Agency, Gwangju, Republic of Korea
, Myeongsu Yoo
AFFILIATIONS
Division of Public Health Emergency Response Research, Director General for Public Health Emergency Preparedness, Korea Disease Control and Prevention Agency, Chungbuk, Republic of Korea
, Kisoon Kim
AFFILIATIONS
ivision of Viral Disease Research, Center for Infectious Diseases Research, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Cheongju, Republic of Korea
Department of Microbiology, Korea University Collegar of Medicine, Seoul, Republic of Korea
, Sangsoo Kim
AFFILIATIONS
Department of Bioinformatics and Life Science, Soongsil University, Seoul, Republic of Korea

Received Date: August 07, 2021 Accepted Date: September 07, 2021 Published Date: September 09, 2021

doi: 10.17303/jaid.2021.8.201

Citation:Sangmi Ryou (2021) Evolutional History of HIV-1 in Korea: Sequence Analysis of env gene in HIV-1 Korean B Subtype from 2006 to 2011. J HIV AIDS Infect Dis 8: 1-15.

Abstract

A previous molecular epidemiological study (1990–2005) reported that the transmission of Korean subtype B (Korean B), the human immunodeficiency virus (HIV)-1 variant, was predominant in Korea. We investigated the HIV-1 subtype diversity and evolutionary patterns of Korean B from 2006–2011.

Sequences of the env variable C2V3 region and epidemiological data were obtained from 392 newly diagnosed HIV-1-positive cases from 2006–2011. HIV-1 subtypes were determined, and genetic distances of sequence pairs were calculated by the Kimura two-parameter model. A phylogenetic tree was constructed using the maximum likelihood method. HIV-1 co-receptor usage was inferred by analyzing the V3 nucleotide sequence.The evolutionary rate was estimated by Bayesian inference and maximum clade credibility trees.

In Korea, subtype B (91.8%) was the most prevalent, and classified as Korean B (86.7%) and global subtype B (global B) (13.3%). The mean diversity of Korean B (0.097 ± 0.009) was lower than that of global B (0.127 ± 0.009) and subtype G (0.157 ± 0.013) (P < 0.01). GPGS (41.2%) was the predominant motif in the V3 loop in Korean B, global B (24.4%), and other subtypes (10.0%) (P < 0.001). CCR5 was more commonly used by HIV-1 than CXCR4 (95.5% vs. 5.0%) (P < 0.001). The estimated evolutionary rates of Korean B and the global B were 4.29 × 10−3 (95% highest posterior density (HPD): 3.10 × 10-3 – 5.49 × 10-3) and 7.46 × 10-4 (95% HPD: 1.39 × 10-7 – 2.42 × 10-3) substitutions/site/year, respectively (P < 0.0001).

Korean B accounts for most nationwide cases of HIV-1 in Korea. The present results provide novel insights to further the current understanding of the characteristics and dynamics of the HIV-1 epidemic in Korea. Continued research is needed to monitor the spread of the virus in Korea.

Keywords:env gene in HIV-1; HIV

List of Abbreviations:AIDS: Acquired Immune Deficiency Syndrome; HIV: Human Immunodeficiency Virus; HTS: Heterosexual; MSM: Men who have Sex with Men; CCR5: C-C chemokine receptor type 5; CXCR4: C-X-C chemokine receptor type 4

Introduction

The cumulative number of human immunodeficiency virus (HIV) cases in Korea since the first reported case of HIV infection in 1985 was reportedly 18,724 in 2019. The sex ratio was 9.9:1, and the proportion of foreigners was approximately 12.1%. Of all the cases, HIV infection through sexual contact accounted for > 99%. Although cases of HIV infection in Korea are relatively low compared to those in other countries, the number of newly diagnosed HIV cases is increasing annually. Furthermore, the number of HIV-infected young men has been increasing yearly since 2011 [1].

Previous studies on env gene sequences of HIV-1 revealed a unique strain of HIV-1 subtype B known as Korean clade B subtype (Korean subtype B; Korean B). Korean B accounted for over 80% of subtype B infection cases in Korea. A most recent common ancestor (MRCA) analysis revealed that HIV-1 subtype B originally emerged in 1961 in the United States, and Korean B evolved in 1967, and its prevalence gradually increased until the mid-1990s. The evolutionary rate of Korean B was estimated to be approximately 3−5-fold less than that of non-Korean B (global subtype B; global B) isolates [2-5].

Envelope glycoprotein gp120 contains constants (C1-C5) and variable (V1–V5) regions. Several amino acid residues in the V3 loop (amino acid residues 31-39) are highly conserved among HIV-1 variants owing to their functional importance. GPGQ is the most common tetrameric tip motif in the V3 loop among all HIV-1 subtypes, and GPGR is the predominant motif in subtype B in America and Africa. The substitution of proline (P) for tryptophan (W), creating the GWGR motif, has been reported in Brazil. In Korea, however, an unusual tetrameric tip motif, GPGS, is present in a slight majority of sequences [4,6]. The V3 loop of HIV-1 gp120 plays a key role in viral entry into target cells and influences tropism and biological phenotype. Furthermore, molecular recognition of chemokine receptors is predominantly mediated through the V3 loop fragment. Upon V3 loop-co-receptor interaction (CCR5 or CXCR4 or both), a series of rearrangements occur in the envelope glycoproteins, leading to the fusion of the host cell membrane and viral envelope [7-10].

Analysis of the env C2V3 sequence is useful for subtype determination and phylogenetic analysis, and is important for evaluating the regional circulation of the virus and developing effective strategies to prevent epidemics. Moreover, temporal monitoring of changes in the frequency of certain variants within different risk groups would facilitate the characterization of transmission clusters and networks to examine the diversity of HIV-1 [11,12].

In Korea, the previous study estimated the origin and evolution charecteristics for Korean HIV-1 subtype B using bayesian phylogenetic analysis. Those results suggested that the growth rate of prevalent HIV-1 strains in Korea was lower than in other countries and the evolution of HIV Korean clade B was relatevely slow [2]. Although genotype testing was routinely performed for the diagnosis of HIV-1 infection in Korea, few studies have focused on Korean B. In this study, to investigate the evolutionary history of HIV-1 subtype B in Korea, we successfully performed epidemiological and phylogenetic analyses based on env C2V3 sequences from HIV-1 infected Koreans over the past 6 years (2006-2011) and analyzed the HIV-1 subtype diversity and evolutionary patterns of Korean B.

Materials and methods

Study population

If HIV infections were confirmed in blood samples upon screening, blood samples of those individuals from the screening sites were sent to the Korea Center for Disease Control and Prevention (KCDC) [15]. KCDC collected blood samples and associated epidemiological data (date of diagnosis, date of birth, transmission route, the reason for HIV testing, marital status, HIV screening institute, CD4+ cell counts, and viral load) from newly diagnosed HIV-1-positive individuals. For the annual representation of newly diagnosed cases of HIV infection, the stratified sampling method was used to select approximately 10% (476 subjects) of 4,715 new Korean individuals on the basis of their demographic characteristics (sex and age) from 2006 to 2011. The sampling method has been changed for new cases of HIV seroconversion since 2012. A total of 392 cases with sequences from 476 blood samples were obtained. From the present epidemiological data, the transmission route was classified into three groups in accordance with self-reported risk factors: the heterosexual (HTS), men who have sex with men (MSM), and unknown. Bisexual individuals were included in the MSM group.

env amplification and sequencing

DNA was extracted, and the 1.2-kb env V1–V5 region (HXB2: nt 6556–7801) was amplified primer set (ed3/ed14, ed5/ed12) and sequenced with primer ed5 (6556–6581), ed12 (7822–7792), ed31 (6816–6844), ed33 (7359–7380), r25 (6873–6857), and v3f (7314–7334) as previously reported [5,16]. Direct sequencing was performed using the ABI Prism Big-Dye Terminator Cycle Sequencing 3.1 Ready Reaction Kit (Applied Biosystems, Foster City, CA, USA) with an automated sequencer (ABI Prism 3730 DNA sequencer; Applied Biosystems). V1V5 region sequence data did not cover the entire env V1V5 regions (it was a short read sequence of about 7 amino acids); hence, we used env C2V3 regions (HXB2: nt 6975-7520). In total, 392 env C2V3 sequences were used for further analysis.

Subtyping and data analysis

The HIV-1 subtype (n = 392) was determined by the Los Alamos database HIV BLAST search (https://www.hiv.lanl.gov) and by using REGA (HIV Bioinformatic Bioafrica). Genetic distances of pairs of env C2V3 sequences were calculated using the Kimura two-parameter model with MEGA v.6.0. A phylogenetic tree was constructed by the Maximum Likelihood method with 1000 bootstrap replicates. In this analysis, we used 384 sequences (8 sequences were excluded: 7 male, 1 female; 3 HTS, 4 MSM, 1 unknown; 1 Korean B, 6 global B, 1 subtype G) and 56 similar references which accounted for the HIV-1 subtype strains present in Korea. The most similar reference sequences were obtained from HIV BLAST in the Los Alamos database (Supplementary Material).

Characterization of the V3 loop

HIV-1 co-receptor usage was inferred from the V3 nucleotide sequence using Geno2Pheno (https://www.geno2pheno.org). Sequences with a false-positive rate < 10% were considered dual/mixed (X4/DM) tropic. In total, 379 samples were included in this analysis except for 13 sequences (12 male, 1 female; 7 HTS, 4 MSM, 2 unknown; 4 Korean B, 7 global B, 2 other subtypes), for which tropism could not be established.

Molecular clock signal analysis

We cleaned clock-likeness of dataset (392 isolates env C2V3 sequences and 140 downloaded from the Los Alamos HIV sequence database for references) by performing linear regression analysis between the parameters ‘root-to-tip divergence’ and ‘sampling data’ to maximize the correlation coefficient of R2 using TempEst v.1.5.3 [17]. One hundred fourteen sequences (fifty-three env C2V3 sequences and sixty-one references sequences) were considered outliers in the TempEst analysis and were excluded from further analysis.

Evolutionary analysis

To better understand the evolutionary dynamics of Korean B, the C2V3 sequences dataset (418 env C2V3 sequences, including 339 Korean isolates and 79 reference sequences) used to estimate the nucleotide substitution rate using Bayesian Markov chain Monet Carlo (MCMC) sampling implemented in the BEAST 1.10.4 [18] (Supplementary Material). As the substitution models, we selected independently best-fit models for this analysis using ModelFinder of IQ-TREE v.1.6.12 . [19] The best model was chosen as that with the lowest with the lowest Akaike’s information criterion (AIC) through MCMC (AICM). Using the lowest AIC model, Bayesian Evolutionary Analysis Utility (BEAUTi)-generated XML file was then imported into BEAST. We conducted independent runs to 300 million generation (1×107, 2×107 and 3×108 chain lengths) combinations under 4 clock and 6 tree models. To select the best combination of the molecular clock and tree prior, both path sampling and stepping-stone sampling were employed [20,21]. Effective sample sizes (ESS) from log files by multiple BEAST runs were assessed using Tracer version 1.7.1[22] where the effective sample size (ESS) was no less than 200. The Bayesian maximum clade credibility (MCC) tree was generated using TreeAnnotator v1.8.4, and then visualized using FigTree v1.4.32. To infer past population dynamics, we applied the best-fit model, a Uncorrelated relaxed - Bayesian skyline population (BSP) model [18] about 296 Korean B and 40 variants of global B (CH, Switzerland; CN, China; ES, Spain; FR, France; JP, Japan; NL, Netherlands; UK, United Kingdom; US, United States) in Korea, which was inferred by BEAST 1.10.4 and Tracer 1.7.1. The BSP method followed the MCMC procedure to estimate the distribution of generalized skyline plots and generate a posterior distribution of effective population size through time (or the effective number of infections in the case of viral epidemics) from the collected plots. The results of the Bayesian MCMC were used to calculate a marginal posterior distribution of the demographic inference, and estimated parameters included the effective population size at the most recent sampling, Ne (the effective number of prevalent infections).

Statistical analysis

Graphs were generated using Prism 5 software (GraphPad, La Jolla, CA, USA). Significant differences were discerned through t-test, one-way analysis of variance (ANOVA) and Tukey’s multiple comparisons post-hoc test. Statistical analysis was performed using SAS 9.4. Chi-square test and Fischer exact (Freeman-Holton) test were used to examine differences for each variable. Statistical significance was set at 0.05 for all cases.

Results

Population characteristics and Subtype classification

We collected DNA sequences from the env C2V3 region of 392 individuals, newly diagnosed as HIV-1-positive between 2006 and 2011. Table 1 shows the epidemiological and subtype characteristics of the 392 populations during these six years. The samples were classified in accordance with sex, age, transmission route, CD4+ cell counts, and HIV-1 subtypes. Most of the individuals in the population were males (n = 366 [93.4%]). Regarding the transmission route, the proportion of MSM cases was 40.6%. Furthermore, as a major immunological indicator of the stage of HIV-1 disease progression, CD4+ cell counts were < 200 cell/mm3 (n = 74 [23.6%]), 200‒349 cell/mm3 (n = 100 [31.9%]), 350‒499 cell/mm3 (n = 79 [25.2%]), and ≥ 500 cell/mm3 (n = 60 [19.2%]), respectively. Subtype B was detected in 91.8% of the total studied population; the remaining 8.2% accounted for subtype CRF01_AE (4.1%), G (1.8%), and other subtypes (2.3%).

Table 2 shows the characteristics of HIV-1 subtype in 392 HIV-infected individuals classified in accordance with sex and transmission route from 2006 through 2011. Subtype B was divided into Korean B, and global B. Korean B (79.6%) was predominant in our study population and accounted for 86.7% (312/360) of subtype B. Males with Korean B were significantly greater than females with Korean B (81.1% vs. 57.7%, P < 0.001), and the Korean B were significantly more prevalent in the MSM group (86.2%) than in the HTS group (76.8%) (P < 0.001).

Sequence analysis

Pairwise genetic distances were determined on the basis of env C2V3 sequences (n = 384) using the Kimura two-parameter model. In the overall population, genetic distances displayed an increasing trend in diagnosis year (P = 0.011) (Figure 1A). Based on the subtype, the genetic distance of Korean B was lower significantly than those of the other subtypes (P < 0.001 vs. global B and P < 0.01 vs. subtype G; Figure 1B). There was no significant difference in the genetic distance by sex (P > 0.05) and by transmission route (P = 0.131).

For 384 sequences and the 56 reference sequences, the result of the maximum likelihood analysis shows that three major taxa (subtype B cluster, subtype AE clusters, and other subtype clusters) were observed among the Korean isolates. This revealed that Korean B formed distinct clusters (70% bootstrap value) (Figure 2). However, no specific epidemiologic characteristic, including age, transmission routes, or diagnosis year, was associated with clustering in this analysis (data not shown).

Sequence analysis

Viral subtype diversity and co-receptor tropism were analyzed based on env V3 sequences (n = 379) using Gene2Pheno. Overall, we identified 34 tetrameric motifs at the tip of the V3 loop; of these, GPGS (41.2%) was predominant among Korean B isolates (P < 0.001). Upon co-receptor usage prediction analysis, CCR5 and CXCR4 viruses of Korean B were 98.1% and 1.9%, respectively. CCR5 accounted for a significantly greater proportion in the Korean B than in the global B isolates (P < 0.001) (Table 3). Furthermore, CCR5 variants of Korean B contained the GPGS motif (41.4%; 125/302) (data not shown).

Evolutionary Dynamics of env C2V3

The Tempest analysis of molecular clock structure revealed a correlation in the C2V3 gene (R2 = 0.160). Residual mean squared values was 9.44 x 10-4. Genomic substitution rate estimates of env C2V3 genes (n=418) were obtained by Bayesian MCMC coalescent analyses, as implemented in BEAST. The best fitting nucleotide substitution model was identified as the TVM+F+R6 model (AIC value (6298.17) and BIC value (66427.8)). The lowest AICM values were obtained with the strict clock and coalescent constant size tree models (3 × 108 chain length) that were used to generate the MCC tree. The Bayesian phylogenetic tree were reconstructed employing the best fit model as maximum clade credibility tree in Supplementary File S1. By Maximum likelihood analysis, the one major Korean B cluster (including global B isolates) was analyzed. Genomic substitution rate for the C2V3 genes was estimated to be 4.53 x 10-3 substitutions/site/year (95% highest posterior density (HPD):3.94 x 10-3–5.16 x 10-3 substitutions/site/year).

The estimated evolutionary rates of Korean B and the global B were 4.29 × 10−3 (95% HPD: 3.10 × 10-3 – 5.49 × 10-3) and 7.46 × 10−4 (95% HPD: 1.39 × 10-7 – 2.42 × 10-3) substitutions/site/year using the coalescent bayesian skyline tree models, respectively (P < 0.0001). The mean MRCA of the Korean B subtype was 1985.2 (95% HPD: 1977.8‒1991.9), as determined using a Bayesian model.

Estimating demographic history

To analyze evolutionary rates for 296 Korean B variants and 40 global B variants, we performed Bayesian skyline plot analysis with Uncorrelated relaxed clock model and Bayesian Skyline Tree model (Chain length, 3 × 108) (Figure 3). Our results showed that the effective population size (number of infected individuals) of HIV-1 virus experienced four major stage since 1992. This analysis for effective population size showed that the size of the Korean B cluster increased steadily until approximately 2000, followed by an exponential growth from 2000 to 2002 and a stationary phase up to 2011 (Figure 3). The population history of global B clusters in Korea was estimated to approach a stationary phase.

Discussion

We characterized the HIV-1 env C2V3 region of isolates from newly diagnosed Koreans with HIV infection from 2006 to 2011 in Korea. According to phylogenetic analyses to evaluate the molecular epidemiological characteristics of HIV-1 infections, the proportion of subtype B was 91.8%, and Korean B in subtype B was predominant (86.7%). CRF07_BC and CRF02_AG were newly detected in this study. Our previous molecular analysis of HIV-1 from 1985 to 2005 revealed the diversity of HIV-1 in Korea, including subtypes B (80.0%), A (8.1%), CRF01_AE (7.0%), G (3.0%), and C (1.4%), with subtypes D, F, and H detected in each isolate. The proportion of Korean B in this study was similar to that previously reported (87.3%) [5]. The Korean B strain had been the predominant strain for 26 years since 1985 in Korea.

The first report regarding HIV phylogenetics in Korea was published in 1998 [23], 13 years after the first HIV case was identified. This study analyzed the nef gene in 46 HIV-1-infected Koreans and identified that Korean B isolates formed a distinct monophyletic clade within HIV-1 subtype B, which was not related to any of the sequences reported from other countries available in the Los Alamos Database or GenBank. Korean B presumpresumably originated from strains in the USA through a founder effect [12,24,25]. Subsequently, several studies consistently reported this unique Korean clade B (KCB, Korean B) by analyzing various genes such as nef [23,26], env [4,24], vif [26], and pol [27,28].

Variability in the V3 loop tip motif is potentially associated with HIV-1 co-receptor usage and disease progression. GPGQ is the most common tetrameric tip motif in the V3 loop among all HIV-1 subtypes, and most subtype B isolates have a high proportion of GPGR, and some have an alternate motif such as GWGR [6,29]. The Korean B was distinguished by the high proportion of GPGS (41.2%). Furthermore, most Korean B isolates were predicted as R5 variants (98.1%). R5 virus infections are predominant in individuals positive for HIV-1 subtype B or who are in the early disease stages of HIV infection (80–90%) [10,30].

X4 viruses emerging in later stages of HIV-1 infection are associated with more rapid depletion of CD4+ T cells [31]. However, in the present study, there were no differences not only among CD4+ cell counts but also subtypes, transmission routes, and age in X4 virus-infected cases. The GPGR motif was present in most of the X4 virus-infected cases [32]; therefore, we speculated that the GPGS variant of Korean B is less pathogenic than other HIV-1 isolates. HIV diversity impacts most aspects of the HIV pandemic, including diagnosis, pathogenesis, transmission, clinical treatment, and vaccine development. Although variation has been observed in different genes and in different regions of the same gene, the variability within a subtype is 8–17% in comparison with 17–35% between subtypes [33,34]. Sequence diversity allows for more rapid adaptation to a changing environment and contributes to the evolution of HIV-1.

Our results estimated that HIV-1 Korean B and global subthype B have evolution rates 4.29 × 10−3 and 7.46 × 10−4 substitutions/site/year, respectively. These results indicated that Korean B and global B have evolved independently in Korea. Furthermore, Korean B of 2006-2011 in this study evolved more slowly than Korean B of 1990-2005 in the previous study [2]. In subtype B, the evolutionary rate of the env V3 region was estimated as 2.3–6.7 × 10−3 nucleotide substitutions/site/year, while that for the entire env gene was approximately 1.0–1.7 × 10−3 nucleotide substitutions/site/year [35]. This discrepancy is probably related to the exact gene region examined herein, alignment, substitution model, homogeneity of datasets, population size, and transmission route of HIV-1 epidemic. In such cases, the evolutionary rate depends on the intra-host evolution rate or bottleneck effects, and antiretroviral treatment influences the evolution of subtype B viruses [36,37]. Although HIV transmission in Korea primarily occurs through sexual contacts, the virus is also transmitted through networks with high rates of partner exchanges, including injection drug use in Europe and the Americas [38,39]. In Korea, global B variants emerged approximately 10 years before Korean B variants, and their prevalence increased between the 1960s and 1990s, having stabilized since the late 1990s [2]. We suggest that global B was more heterogeneously disseminated and less efficient than Korean B.

In the phylogenetic tree analysis of the env C2V3 gene, Korean B formed a distinct monophyletic clade within HIV-1 subtype B. Furthermore, no association with risk factors of HIV transmission or geographic dissemination was observed in the epidemic clusters. Even in newly diagnosed individuals, it was often difficult to accurately determine the time and duration of infection, which is problematic because infection time affects genetic distance and, consequently, the evolutionary rate of HIV-1.

This study has two limitations. First, the transmission route was determined based on self-reported sexual behavior, which may not always be accurate. In particular, as the present study population comprised newly diagnosed cases, we expected

a low proportion of individuals in the MSM group because some individuals in this group did not wish to reveal their sexual orientation [40]. The Korea HIV/AIDS cohort study reported a higher percentage for an individual in the MSM group than the present study [41,42]. Therefore, our results should be interpreted with caution. The second limitation is the partial genome-based HIV-1 analysis. To date, many epidemiological studies have been conducted using phylogenetic analysis of small portions of the genome sequence, however, recombination and sequence diversity of a complex genome cannot be completely characterized when partial genome sequences are used for HIV-1 subtyping. Although viral diversity in southeast Asia is quite complex owing to the constant traveling or migration between countries in this region, CRF or URF strains may be present, we did not identify any recombinant strains in this study. We recently reported recombinant form of nearly full-length HIV-1 sequence genome [43]. Such events affect most aspects of the HIV pandemic; therefore, further studies are needed to improve the resolution of the HIV-1 genomic diversity and transmission dynamics.

Conclusions

Korean B accounts for most nationwide cases of HIV-1 in Korea. The present results provide novel insights to further the current understanding of the current characteristics and dynamics of the HIV-1 epidemic in Korea. Further continuous studies are required to monitor the spread of the virus in Korea.

Acknowledgments

This research was supported by an intramural grant of the Korea National Institute of Health (2017-NI51003-). S.R. and M-K.K conceived and designed the study, analyzed and interpreted the data, and wrote the original manuscript. Y-S.J. contributed to study conception. M.Y. analyzed and formatted the data. K.K. and S.K. interpreted the results, and critically reviewed the manuscript. All authors read and approved the final article.

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Tables at a glance

CommentsTable 1 CommentsTable 2 CommentsTable 3 CommentsTable S1 CommentsTable S2

Figures at a glance

CommentsFigure 1 CommentsFigure 2 CommentsFigure 3 CommentsSupplementary Figure 1