Molecular epidemiological characteristics of dengue virus carried by 34 patients in Guangzhou in 2018.

Dengue fever is a major worldwide public health problem that, as estimated by the WHO, causes epidemics in over 100 countries, resulting in hundreds of millions of dengue virus (DENV) infections every year. In China, dengue fever mainly occurs in coastal areas. Recurring dengue outbreaks were reported by Guangdong Province almost every year since the first epidemic in 1978. DENV infections persisted in Guangzhou in consecutive years since 2000, with the dengue epidemic reaching a historical peak in 2014. Because Guangzhou is one of the largest cities for opening up in China, understanding the epidemiological characteristics of dengue fever in the city can hopefully provide a significant basis for developing effective dengue prevention strategies. In this study, a total of 34 DENV strains, including 29 DENV-1 strains and 5 DENV-2 strains, were isolated from a blood samples drawn from patients who were diagnosed with dengue fever by hospitals in Guangzhou during 2018. To explore the epidemiological characteristics of dengue fever, the envelope (E) gene obtained from the isolates was amplified for phylogenetic analysis. The results from the phylogenetic analysis showed that DENV in Guangzhou was mainly imported from Southeast Asian countries. Additionally, propagation paths based on phylogeographical analysis suggested potential local dengue transmission in Guangzhou.

Introduction

Dengue fever, also known as "break-bone fever", is an acute mosquito-borne viral disease caused by dengue virus (DENV) [1]. Patients infected with DENV can have flu-like symptoms, including a high fever, headache, and vomiting, which generally last for ten days. In a small proportion of cases, the disease develops into dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS) [2, 3]. Dengue is principally spread by Aedes aegypti and Aedes albopictus mosquitoes in tropical and subtropical regions where the warm and humid climate indicates favorable mosquito habitat. In other words, dengue fever is also a seasonal infectious disease, and mosquito densities and climatic conditions are strongly associated with the incidence of dengue fever. In recent decades, dengue fever, as a growing threat to human health, has presented a tremendous challenge to health service providers throughout the world [4]. According to a published study, an estimated 390 million dengue infections occur in over 100 countries every year [3, 5]. Globally, the vast majority of the world population is exposed to DENV, making dengue one of the most dangerous vector-borne viral diseases worldwide [4]. Dengue outbreaks have a devastating effect on public health and economic sectors [3]. In the stricken areas, the disease leads to a slowdown in the local economy as it inflicts a significant health burden on the population, impairs people's quality of life and impedes the development of the tourist industry. With vector management as the primary means to control and prevent DENV transmission, it should be noted that improper use of insecticides is a waste of resources and a source of environmental pollution that threatens both human and environmental health [6, 7]. So it is important to know the structure of dengue virus.

DENV, as a member of the genus Flavivirus in the family Flaviviridae, is an enveloped, single-stranded, positive-sense RNA virus. The DENV genome is approximately 11,000 nucleotides in length and encodes three structural proteins, namely, the capsid (C), premembrane (prM), and envelope (E) proteins, and seven nonstructural (NS) proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B and NS5) in a single open reading frame (ORF). Specifically, the 5' end of the DENV genome encodes the C/prM/E proteins, while the 3' end encodes the seven NS protein[8]. There are five DENV serotypes, which are referred to as DENV-1, DENV-2, DENV-3, and DENV-4, and the distinctions between these serotypes are based on their antigenicity. Additionally, different serotypes can be further differentiated into different genotypes[9].

In fact, as early as 1978, a case of imported dengue fever was discovered in Xiamen, after which the Chinese mainland has experienced multiple dengue epidemics in the past few decades [10]. In addition to the coastal provinces in Southeast China and Taiwan that are mainly affected by the disease, an increasing geographic expansion to the inland is noted as the global climate changes [10, 11]. Guangdong Province has been declared a severe epidemic area by the Chinese Center for Disease Control and Prevention, as it has been frequently attacked by dengue fever since the first outbreak [12]. Despite the absence of reported dengue fever cases between 1982 and 1984, 1988 and 1989, and in 1994, 1996, and 1998, the disease has been a constant threat in Guangdong Province [13]. In Guangzhou, the capital city of Guangdong Province, dengue incidence, regardless of the number of DENV infections, has been reported every year since 2000 [14]. In 2014, Guangdong Province experienced its worst dengue outbreak on record, during which different DENV serotypes were detected in the DENV-infected patients [12, 15]. There were over 46000 dengue fever cases notified nationwide throughout the year, including up to 45230 cases and 76 imported cases reported by Guangdong Province, which exceeds the cumulative number of infections between 1990 and 2013 [14, 16].

DENV infections are simply classified as imported and autochthonous cases according to patients' recent travel records. Dengue epidemics refer to continued widespread outbreaks of dengue fever in areas where DENV affects a large population and is transmitted between people by the mosquitoes Aedes aegypti and Aedes albopictus. To date, there are no other DENV foci in mainland China, except for the reported natural focus in Yunnan Province [17]. As a result of rapid economic growth, thriving tourism, and the greenhouse effect, there were many patients infected with dengue fever in Guangdong Province, and a serious outbreak occurred in 2014. [18, 19]. The endemicity of dengue in Guangzhou has been heatedly discussed [20]. A previous study based on phylogenetic analysis suggested the presence of local dengue transmission in Guangzhou [10]. In the present study, DENV strains were isolated from blood samples drawn from DENV-infected patients who were diagnosed with dengue fever by hospitals in Guangzhou during 2018. We described the epidemiological characteristics of isolated DENV based on phylogenetic reconstruction and analysis using a dataset comprised of DENV sequences downloaded from the GenBank database and those obtained from genome sequencing.

Materials and methods

1. Sample collection

In this study, all patient samples were approved by the First Affiliated Hospital of Guangzhou University of Chinese Medicine and Guangdong Hospital of Traditional Chinese Medicine. All patients had fever > 37.5°C for less than 72 h. Anti-dengue IgM and IgG enzyme-linked immunosorbent assay (ELISA) kits were used to confirm dengue infection [21]. A total of 170 samples suspected of having dengue fever occurred during the 2018 outbreak. 55 blood samples were determined to be positive samples by hospital diagnosis.

Oral informed consent was obtained from all patients who were involved in this study.

2. Virus isolation, RNA extraction and serotyping

Dengue virus was isolated from 55 positive blood samples. To increase virus titer, each patient's serum was inoculated into an Aedes albopictus C6/36 cell line cultured in MEM with 10% FBS (Gibco, Carlsbad, CA, USA) and diluted 1:40 in fresh MEM. Next, the medium was added to C6/36 cells and incubated at 30°C for 2 h. Then, the residual inoculum was replaced with fresh MEM containing 2% FBS; the cells were maintained at 30°C in a humidified atmosphere of 5% CO2 for 5 to 7 days (until significant cytopathic effects (CPE) occurred). Simultaneously, the supernatants were collected for RNA extraction after centrifugation at 4000 rpm. These samples were stored at -80°C until needed.

Viral RNA was extracted from 200 μl of each supernatant using the QIAamp Viral RNA Mini Kit (Qiagen, Germany) as instructed by the manufacturer. Then, the RNA was reverse-transcribed into cDNA by reverse transcriptase at 37°C for 90 min and then at 70°C for 10 min. DENV serotyping was carried out by multiplex RT-PCR [22].

3. Sequencing

Using RNA as templates, RT-PCR was performed to amplify the envelope (E) gene. DENV-1 primers were designed for sequencing based on the DENV-1 standard Hawaii strain (GenBank accession number: KM204119) and DENV-2 strain (GenBank accession number: KM279569) [10, 22]. E gene sequences of 34 strains were obtained from the patient samples. The primers used in this article are listed in Tables 1 and 2. These sequences were uploaded to the GenBank database, and their IDs, i.e., the GenBank accession numbers of the sequences, are listed in Table 3.

Table 1

Primer sequence, and size of RT-PCR product and generated combination of primers.

Virus	Primer	Primer sequence (from 5′ to 3′)	Size of amplicon &Primer combination	Primer position
	Dcon-F	AGTTGTTAGTCTACGTGGACCGACA		1–25
DENV-1	DENV-1-R	CCCCGTAACACTTTGATCGCTCCATT	342 bp Dcon-F and DEN1-R	317–342
DENV-2	DENV-2-R	CGCCACAAGGGCCATGAACAG	251 bp Dcon-F and DEN2-R	231–251
DENV-3	DENV-3-R	GCACATGTTGATTCCAGAGGCTGTC	538 bp Dcon-F and DEN3-R	514–538
DENV-4	DENV-4-R	GTTTCCAATCCCATTCCTGAATGTGGTGT	754 bp Dcon-F and DEN4-R	726–754

Table 2

Primers used for amplifying and sequencing the complete DENV-1and DENV-2 envelope gene.

Reaction	Primer name	Sequence (from 5′ to 3′)	Primer position
Amplification & Sequencing	DENV1-E-F	TGCCATAGGAACATCCATCAC	863–883
	DENV1-E-R	TCCCAATGGCTGCTGATAGTC	2495–2462
	DENV2-E-F	AATGGCAGCAATCTTGGCATACACC	747–771
	DENV2-E-R	ACTGAGCGGATTCCACAAATGCCCT	2504–2480

Table 3

The 2018 Guangzhou dengue virus sequences information isolated and uploaded in this study.

ID	Accession	Serotype	Location	Collection date	Cluster
1–3	MK517719	DENV-1	Guangzhou	2018/9/20	Cluster I
3–8	MK517720	DENV-1	Guangzhou	2018/9/21	Cluster I
4–9	MK517721	DENV-1	Guangzhou	2018/9/21	Cluster I
5–18	MK517735	DENV-1	Guangzhou	2018/9/21	Cluster II
6–19	MK517740	DENV-1	Guangzhou	2018/9/22	Cluster I
7–26	MK517738	DENV-1	Guangzhou	2018/9/22	Cluster II
8–29	MK517744	DENV-1	Guangzhou	2018/9/23	Cluster III
9–32	MK517739	DENV-1	Guangzhou	2018/9/24	Cluster II
1–37	MK517743	DENV-1	Guangzhou	2018/9/24	Cluster III
2–40	MK517750	DENV-2	Guangzhou	2018/9/24	Cluster V
12–43	MK517746	DENV-1	Guangzhou	2018/9/24	Cluster III
3–44	MK517752	DENV-2	Guangzhou	2018/9/25	Cluster V
12–45	MK517747	DENV-1	Guangzhou	2018/9/25	Cluster III
15–48	MK517734	DENV-1	Guangzhou	2018/9/25	Cluster II
4–49	MK517748	DENV-2	Guangzhou	2018/9/25	Cluster IV
17–59	MK517722	DENV-1	Guangzhou	2018/9/26	Cluster I
18–61	MK517723	DENV-1	Guangzhou	2018/9/26	Cluster I
19–64	MK517725	DENV-1	Guangzhou	2018/9/26	Cluster I
20–66	MK517727	DENV-1	Guangzhou	2018/9/26	Cluster I
21–69	MK517730	DENV-1	Guangzhou	2018/9/26	Cluster I
22–81	MK517741	DENV-1	Guangzhou	2018/9/28	Cluster I
23–84	MK517729	DENV-1	Guangzhou	2018/9/28	Cluster I
24–89	MK517726	DENV-1	Guangzhou	2018/9/28	Cluster I
25–93	MK517724	DENV-1	Guangzhou	2018/9/28	Cluster I
26–94	MK517731	DENV-1	Guangzhou	2018/9/28	Cluster I
1–97	MK517733	DENV-1	Guangzhou	2018/10/1	Cluster II
27–107	MK517742	DENV-1	Guangzhou	2018/10/3	Cluster I
28–108	MK517745	DENV-1	Guangzhou	2018/10/3	Cluster III
31–134	MK517728	DENV-1	Guangzhou	2018/10/5	Cluster I
32–135	MK517732	DENV-1	Guangzhou	2018/10/5	Cluster I
5–141	MK517751	DENV-2	Guangzhou	2018/10/6	Cluster V
6–146	MK517749	DENV-2	Guangzhou	2018/10/6	Cluster IV
3–169	MK517736	DENV-1	Guangzhou	2018/10/8	Cluster II
4–170	MK517737	DENV-1	Guangzhou	2018/10/8	Cluster II

IDs in Table 1 are registration numbers when collecting blood samples; the clustering is distinguished according to ML trees.

4. Dataset

In the dataset, the new isolates and the sequences of DENV-1 and DENV-2 available from the GenBank database were aligned and adjusted using MAFFT v7.308 [23] and Aliview to remove those without a sampling date or geographic location (The length of the E gene sequence is 1485). Recombination Detection Program (RDP v4.36) was employed in recombination analysis with a wide range of recombination detection methods, including RDP, Chi-maera, BootScan, 3Seq, GENECONV, MaxChi, and SiScan [24]. To avoid redundancy, CD-HIT-EST (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi?cmd=cd-hit-est) was used to group sequences from outside China into clusters, with the nucleotide identity threshold of 100% [25]. A single sequence was randomly chosen from each cluster as a representative of all sequences that shared the same sampling date and geographic location.

5. Phylogenetic signal assessment and nucleotide substitution model selection

The accuracy of phylogenetic inference based on the nucleotide sequence dataset is subject to the saturation level of the phylogenetic signal. Substitution saturation is a crucial factor because a phylogenetic tree becomes meaningless if the aligned sequences in the dataset lose phylogenetic information due to substitution saturation. In the present study, the substitution saturation level of each dataset was assessed with DAMBE and Xia's test method [26].

Models of nucleotide substitution allow for the calculation of probabilities of change between nucleotides along the branches of a phylogenetic tree. On this basis, we used the Akaike information criterion (AIC) to select a best-fit model and created a maximum-likelihood tree (ML tree) with the model. Additionally, a maximum clade credibility (MCC) tree was generated using the Bayesian Information Criterion (BIC) for model selection. The best-fit models of nucleotide substitution were estimated with JModeltest v2.1.7 [27]. Subsequently, the IQ-TREE [28] was employed to determine the best-fit models since a massive quantity of sequences were deposited in a global dataset, which was beyond the capacity of JModeltest.

6. Phylogenetic tree reconstruction

In search of more information about the samples, we set up a global dataset that involved all samples and the DENV-1 and DENV-2 sequences available from the GenBank, except those being removed from the database as redundant sequences. Furthermore, ML trees were constructed with best-fit models in RAxML v8.0.9 [29], while the reliability of topology was evaluated using bootstrap values derived from 1000 repetitions. The ML trees were visualized with FigTree v1.4.2.

7. Phylogeographic analyses

According to the ML trees obtained from the global dataset, the newly isolated sample sequences in the DENV-1 and DENV-2 datasets were divided into different clusters (with the classification of clusters based on bootstrap values and the number of 70% as a cut-off for a "reliable" branch). A sample sequence was selected from each cluster for nucleotide BLAST on the NCBI web server, and 100 DENV sequences were downloaded from each BLAST run. On this basis, the sample sequence of Cluster III was set to match 1000 sequences to gather more biological information. The downloaded sequences and the samples were combined together and divided into four datasets for comparison on the MAFFT web server. Phylogenetic signals of these datasets were detected as described above.

Each dataset was analyzed with TempEst v1.5 to investigate its temporal signal and "clocklikeness" of ML phylogenies before applying the assumption of a molecular clock into the phylogenetic analysis [30]. ML trees generated by RAxML were inputted, and the sample dates of the sequences were defined. After estimation of the best-fitting root, a linear regression was performed on the root-to-tip distances of samples versus the date of the isolate, and significant outliers (sequences) were rejected as they did not fit into the assumption of the molecular clock.

The spatial diffusion of the time-scaled genealogy was modeled as a continuous-time Markov chain (CTMC) process with the program BEAST v1.8.3 [31]. The diffusion process along the phylogenies of the datasets for BLAST was estimated using the Bayesian stochastic search variable selection (BSSVS) procedure. The uncorrelated lognormal relaxed clock (ULRC) method was adopted to produce phylogenetic estimates. In addition, we chose a Bayesian skyline coalescent model to review the demographic history and ran the Bayesian MCMC chain for a bulk number of iterations to ensure process convergence. The BEAGLE package was used to speed up the calculation process [32]. The effective sample size (ESS) was calculated using TRACER [33], with all parameters showing ESS values > 200 after burn-in in the initial 10% iterations. The MCC tree was summarized using TreeAnnotator v1.8.2 at the burn-in rate of 10% and was visualized with FigTree v1.4. SPREAD v1.0.6 is used to generate the propagation path map. Import the files generated by the BEAST software into the SPREAD software, set the latitude and longitude of the location, and set the BF value to 3, and then generate the corresponding path map.

8. Group average distance calculation

We differentiated the DENV-1 and DENV-2 data sets based on genotypes. In order to avoid the impact of old viruses on genetic distance calculation, we only extracted the genotypes of sequence samples from Guangdong Province in the past five years. The MEGA software was used to compare sample sequences of different clusters and compare them to sequences not in the cluster.

Result

1. Sample information and serotypes

In 2018, a total of 170 blood samples were provided by the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, and 34 strains of dengue viruses were obtained from these blood samples, including 29 strains of DENV-1 and 5 strains of DENV-2. After gel electrophoresis analysis, the RT-PCR products were sequenced and uploaded to the GenBank database to obtain accession numbers. Details are shown in Fig 1 and Table 3. The original image of agarose gel electrophoresis is shown in S1 Fig.

Fig 1

Gel electrophoresis analysis of RT-PCR products.

According to the results from gel electrophoresis analysis of different samples given in the figure, there are 34 RT-PCR products; the sizes of the amplicons (ID 2–40, 3–44, 4–49, 5–141, and 6–146) are consistent with DENV-2, while the rest are consistent with DENV-1.

2. Phylogenetic signal assessment

The substitution saturation level of each dataset of the DENV E gene was assessed with DAMBE. The results of the assessment indicated that no subset experienced full substitution saturation.

3. Phylogenetic analysis and molecular clock tests

Obviously, the sample sequences were classified in independent clusters with high bootstrap values (70–100%), indicating robust support for the tree topology. DENV-1 was used to construct 3529 sequences of ML tree, and 3542 of DENV-2. From the ML tree of the global dataset, the sample sequences positive for DENV-1 were divided into three clusters, and the DENV-2 positive sample sequences were grouped into two clusters (for detailed clustering results, see Fig 2, Fig 3 and Table 1). Molecular clock tests were performed on the basis of the ML trees. A stable temporal structure was observed as the linear regression on the root-to-tip distances versus the data suggested a relatively high fitting degree, and R2 had a positive value, which enabled further study of the evolutionary process. The molecular clock detection maps are displayed on the corresponding MCC maps.

Fig 2

Maximum likelihood tree for global dataset reconstruction of DENV-1.

The maximum likelihood tree result of DENV-1 is shown in the figure. The sample sequence clusters under different branches, and the red blocks labeled in the branches in the figure are clusters of sample sequence clusters. Different color blocks outside the branches represent different genotypes.

Fig 3

Maximum likelihood tree for global dataset reconstruction of DENV-2.

The maximum likelihood tree result of DENV-2 is shown in the figure. The sample sequence clusters under different branches, and the blue blocks labeled in the branches in the figure are clusters of sample sequence clusters. Different color blocks outside the branches represent different genotypes.

4. Ancestral reconstruction and discrete paleogeography analysis

All sample sequences were clearly clustered into one branch (with the classification of branches based on posterior probabilities and the number of 0.8 and higher as trustworthy). In this study, all sample sequences in the first, second, and third clusters belonged to DENV-1. According to the MCC tree reconstructed from Cluster I, the 17 isolates were clustered in one branch (posterior probability = 0.9985), which is the same as the Thailand and Taiwanese 2015 sequences (posterior probability = 0.9998). Our paleogeography analysis results showed that the sample virus originated in Taiwan. In 2015, the virus affected the region radically and was later imported into Guangzhou between 2015 and 2018. The MCC tree of Cluster II indicated that the sample sequences were clustered in the branch (accession: MG767211) with a sequence obtained from Guangzhou in 2017 (posterior probability = 0.9999), with no other clusters in the same branch. The results from the paleogeography analysis suggested that Guangzhou was the location where the most recent common ancestor was found, while an earlier ancestor appeared in Singapore. The MCC tree of Cluster III suggested that the sample sequences were clustered in the same branch with the Taiwanese 2015 and 2016 sequences, as well as the cluster of the Singaporean 2016 sequences (posterior probability = 0.9992). Through paleogeography analysis, the sample virus might be spread along a propagation path and imported into Guangzhou from Taiwan in 2018 or before. The fourth and fifth clusters belonged to DENV-2. As shown in the MCC tree of Cluster IV, the sample sequences were clustered in the same branch with the Malaysian 2013 sequence (posterior probability = 0.9999), indicating that the most recent ancestor of the sample sequences emerged from Malaysia. According to the propagation path map, the sample virus entered Guangzhou during 2013–2018. The MCC tree of Cluster V suggested that the sample sequences were clustered in the same branch with the Indian 2015 sequences and the Taiwanese 2015 sequence cluster (posterior probability = 0.8465). According to the propagation path, the sample virus was imported into Guangzhou during 2015–2018. It is difficult to infer a highly accurate propagation path as no more sequences are available from the GenBank database. The propagation path map of all sample viruses is included in Fig 4. The MCC trees are shown in Figs 5–9.

Fig 4

The propagation path map of dengue virus in Guangzhou in 2018.

The propagation path map is drawn based on the paleogeography analysis. The red curves indicated that the clusters of sample sequences were belonged to DENV-1, while the blue curves belonged to DENV-2, which indicated the propagation path. The time beside the curves indicates the time range in which the virus strain is introduced, and the red flag indicates different locations.

Fig 5

Maximum clade credibility tree of the sequence of cluster I.

A| A root-to-tip analysis was performed in TempEst v1.5. An ML tree was built using the sample dataset to determine the R2 value; R2 > 0 indicates a positive correlation between the dataset and the molecular clock. B| Sequences from different geographic regions are represented by different colors. The location on the branch is the most recent ancestor position, and the value is the posterior probability. The purple branch indicates that Fujian Province is the most recent ancestor of the sequences; the green branch corresponds to Malaysia; the blue branch corresponds to Taiwan Province; and the red branch corresponds to Guangzhou. The dotted line box represents the sample sequence obtained in this experiment.

Fig 9

Maximum clade credibility tree of the sequence of cluster V.

A| A root-to-tip analysis was performed in TempEst v1.5. An ML tree was built using the sample dataset to determine the R2 value; R2 > 0 indicates a positive correlation between the dataset and the molecular clock. B| Sequences from different geographic regions are represented by different colors. The location on the branch is the most recent ancestor position, and the value is the posterior probability. The purple branch indicates that Malaysia is the most recent ancestor of the sequences; the green branch corresponds to India; the blue branch corresponds to Taiwan province; and the red branch corresponds to Guangzhou. The dotted line box represents the sample sequence obtained in this experiment.

Maximum clade credibility tree of the sequence of cluster II.

A| A root-to-tip analysis was performed in TempEst v1.5. An ML tree was built using the sample dataset to determine the R2 value; R2 > 0 indicates a positive correlation between the dataset and the molecular clock. B| Sequences from different geographic regions are represented by different colors. The location on the branch is the most recent ancestor position, and the value is the posterior probability. The blue branch indicates that Singapore is the most recent ancestor of the sequences; and the red branch corresponds to Guangzhou. The dotted line box represents the sample sequence obtained in this experiment.

Maximum clade credibility tree of the sequence of cluster III.

A| A root-to-tip analysis was performed in TempEst v1.5. An ML tree was built using the sample dataset to determine the R2 value; R2 > 0 indicates a positive correlation between the dataset and the molecular clock. B| Sequences from different geographic regions are represented by different colors. The location on the branch is the most recent ancestor position, and the value is the posterior probability. The green branch indicates that Singapore is the most recent ancestor of the sequences; the blue branch corresponds to Taiwan Province; and the red branch corresponds to Guangzhou. The dotted line box represents the sample sequence obtained in this experiment.

Maximum clade credibility tree of the sequence of cluster IV.

A| A root-to-tip analysis was performed in TempEst v1.5. An ML tree was built using the sample dataset to determine the R2 value; R2 > 0 indicates a positive correlation between the dataset and the molecular clock. B| Sequences from different geographic regions are represented by different colors. The location on the branch is the most recent ancestor position, and the value is the posterior probability. The purple branch indicates that Indonesia is the most recent ancestor of the sequences; the blue branch corresponds to Malaysia; the orange branch corresponds to Zhongshan City; the green branch corresponds to East Timor; and the red branch corresponds to Guangzhou. The dotted line box represents the sample sequence obtained in this experiment.

5. Average genetic distance comparison

The five sample clusters were compared with the genetic distances of the same genotype in clusters in 2014–2018. It can be seen from the table that the sequence of the DENV-2 two-cluster sample collected in this study differs greatly from the sequence of the same genotype. The sequence differences between other sample clusters and the same genotype are small. The data is presented in Table 4.

Table 4

Comparison of average genetic distances of different clusters.

	Species 1	Species 2	Distance
DENV 1-Genotype I	others-1	sample2	0.0205329387
	others-1	sample1	0.0189086126
	sample2	sample1	0.0202604556
DENV 1-Genotype V	others-2	sample3	0.0067526479
DENV 2-Cosmopolitan	others-3	sample4	0.0336621574
	sample4	sample5	0.0670677460
	sample5	others-3	0.0657505057

Others in the table indicates the non-sample sequence of the genotype in Guangdong Province from 2014 to 2018.

Discussion

In the present study, blood samples were drawn from DENV-infected patients who were diagnosed with dengue fever by hospitals in Guangzhou during 2018, and an analysis was performed on the DENV strains isolated from these blood samples. Through gel electrophoresis analysis, the isolated sequences were classified into two serotypes, namely, DENV-1 and DENV-2. Furthermore, DENV-1 strains were divided into three clusters, and the DENV-2 strains were divided into two clusters according to the ML trees. The ancestral reconstruction analysis showed that the sample sequences largely originated from Indonesia, Malaysia, Singapore, and Taiwan. This suggests that the dengue virus that we are popular in Guangzhou is still based on input. As the capital city of Guangdong Province and the trade center in Southeast China, Guangzhou is exposed to a relatively high risk of the disease, as DENV may enter the city along with imported goods and migrant workers. In addition, DENV continuously flows into China because Thailand, Malaysia, Singapore, and other Southeast Asian countries are popular destinations for Chinese tourists, especially those living in Guangdong Province. Therefore, entry-exit inspection and quarantine should be implemented effectively for dengue prevention and control. For instance, suspected and confirmed cases of DENV infection should be isolated and treated properly to reduce the risk of imported dengue fever. In addition, health education also plays an important role in dengue prevention and control. To reduce the risk of DENV infection, public health authorities should provide the necessary materials for tourists to gain a better understanding of dengue prevention and remind them not to visit an endemic area during epidemic seasons.

Interestingly, the results from the traceability analysis showed that the most recent common ancestor of the sequences of cluster II emerged from Guangzhou, and Cluster II and the Guangzhou 2017 isolate are in the same branch without any other foreign sequences. Moreover, they shared a common ancestral lineage to the Malaysian 2014 isolate, the Singaporean 2014 isolate, and the Zhongshan 2015 isolate in other branches. Phylogeographically, there are two possible propagation paths. First, the virus originated in Singapore and became an epidemic in the country before 2014; during the next year, it was imported into Zhongshan, and then in 2017, the disease flowed into Guangzhou from other cities in Guangdong Province; the Guangzhou 2018 isolates came from the virus imported into the city during 2017 as a result of local transmission. Second, the virus emerged from Singapore and was not introduced into Zhongshan until 2015; during 2017 and 2018, the virus was continuously imported into Guangzhou from Singapore or other countries and regions; the sample sequences were not clustered into a branch with the isolates from other countries because no related sequences were available in GenBank or the database had no sufficient patient isolates. Regarding the sources of spread or propagation, some DENV strains were imported from endemic countries and regions and caused dengue fever without further propagation in China; some evolved from imported strains and led to local epidemics during the year; others were localized strains after vertical transmission. Although no substantial evidence was found in this study to prove vertical transmission of DENV in Guangzhou, previous phylogenetic analyses indicated possible local transmission of dengue fever in the city.

Since Aedes albopictus is the main medium for DENV transmission, the localization of DENV largely depends on the formation of localized and virus-carrying eggs and the survival of DENV in the eggs and offspring mosquitoes through winter[34]. A previous study demonstrated that DENV can survive in eggs and spread to offspring mosquitoes. Transovarial transmission of DENV is strongly temperature-related as it determines whether the eggs and young offspring can wait out the winter season. As an example, Yunnan Province has reported the localization of DENV as it has a subtropical monsoon climate and provides a natural habitat for Aedes albopictus. Similar to Yunnan Province, Guangzhou has hot, humid summers and mild, dry winters, which create a favorable environment for the breeding of Aedes mosquitoes. Moreover, as the greenhouse effect continues to warm the planet slowly, overwintering becomes easier for mosquitoes. Peri-urban areas in Guangzhou have plenty of dirty gullies, open spaces, and rented houses that require effective management to improve the living environment. Additionally, local residents who like indoor and outdoor planting, fish farming, and water harvesting also provide places for mosquito breeding. To reduce mosquito breeding sites, effective urban sanitation management should be implemented. For example, stagnant water should be cleared in a timely manner to ensure the smooth operation and maintenance of the city's drainage system; in crowded places, mosquito prevention and control measures should be taken for the public good. Personal hygiene also plays a critical role in dengue prevention. Residents should avoid keeping fish and aquatic plants and regularly clean up stagnant water in their houses. An individual with a fever or other dengue fever-like symptoms should promptly seek medical attention. Hospitals should strive to improve the diagnostic accuracy and efficiency of dengue fever. Suspected DENV-infected patients should be isolated to prevent further transmission. We should pay closer attention to localized DENV in Guangzhou and strictly implement relevant dengue prevention and control measures.

Although the results of this study implied that vertical transmission of DENV might exist in Guangzhou, there is no solid evidence supporting the inference as no adequate sequences are available for analysis. The coverage of the sequence has a great impact on the study. Patients with dengue sometimes have negative infections. The patient is not aware that the infection with dengue virus has led to a decrease in the reported sequence, and a small number of viruses have not been sequenced and uploaded to the database. These can all lead to the wrong propagation path. Therefore, local centers for disease control and prevention should work closely with disease control and prevention departments of Southeast Asian countries to observe how DENV is prevalent in these countries, thereby identifying sources of propagation for DENV in China and exploring the epidemiological characteristics of dengue fever to provide a basis for dengue prevention strategies. As the Belt and Road Initiative moves forward, Asian, European and African countries expect to increase transport connections for international trade, strengthen people-to-people exchanges and remove barriers to investment and trade. Given that, the conventional entry-exit inspection and quarantine divided by national administrative regions is falling short, leading to an increased risk of dengue and Zika fever in the countries along the Belt and Road. There is an urgent need to raise public awareness about disease prevention and control, as well as intensified measures against dengue and Zika fever. It is necessary to establish joint prevention and control mechanisms for infectious diseases so that China and other relevant countries can work together to effectively combat infectious diseases and safeguard health security with their technologies and resources.

Original image of agarose gel electrophoresis.

(TIF)

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The kit for diagnosing dengue patients is used in hospitals.

(XLSX)

Click here for additional data file.

All accession numbers of the DENV-1 sequence used in this study.

(XLSX)

Click here for additional data file.

All accession numbers of the DENV-2 sequence used in this study.

(XLSX)

Click here for additional data file.

7 Aug 2019

PONE-D-19-19136

Molecular epidemiological characteristics of dengue virus carried by 34 patients in Guangzhou in 2018

PLOS ONE

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Additional Editor Comments (if provided):

This a phylogenetic study of dengue virus in China.  The population size is quite small; therefore, robust inferences are very difficult.  The phylogenetic analyses are well described and appropriate for this type of study.

It would have been very helpful for the authors to evaluate dengue virus from other years as well.  Restricting the study to a single year – even an outbreak year – limits usefulness of the data collected.  For instance, did the virus evolve in 2018 in such a way as to be different from previous years?  If so, what are the virologic differences across the viral genome?

Are other dengue virus sequences available from southern China in the years before 2018?  These should be included in the phylogenetic analyses.

Serum samples from 170 individuals with dengue were evaluated, so why are genotypic data presented for only 34?  How are these 34 different / similar to the 55 individuals with positive blood samples?

How large are the E gene sequences that were analyzed?  This should be stated explicitly.

Lines 150-152 state that a set of global dengue references were used.  How many DENV-1 and DENV-2 references were included?

How was the propagation path evaluated?  This part of the analysis is not described in the Methods.

For the 5 sequence clusters, the authors should calculate the median genetic distance and compare that to sequences that are not in clusters.  It is important for the readers to have some quantified measure of similarity / dissimilarity amongst sequences within a cluster.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

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Reviewer #1: No

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: No

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Liao et al. studied 34 DENV strains, including 29 DENV-1 strains and 5 DENV-2 strains, isolated from blood samples from dengue fever patients at Guangzhou in 2018. They amplified the envelope genes of these isolates by RT-PCR and performed phylogenetic analysis. The found DENV isolates of 2018 in Guangzhou were mainly imported from Southeast Asian countries. Propagation paths based on phylogeographical analysis suggested potential local DENV transmission in Guangzhou.

The authors have carried out RT-PCR, sequencing and phylogenetic analysis of E genes of 34 DENV strains isolated from DF patients at Guangzhou in 2018. Overall, the observation that DENV isolates in Guangzhou were mainly imported from Southeast Asian countries did not bring new insights to the field. The evidence of possible local DENV transmission in Guangzhou over the years was weak. Moreover, there several places in the introduction, methods and results need to be clarified. Several references were inappropriate or irrelevant. See specific comments. There should be addressed to improve this manuscript.

Specific comments:

1) Line 28: “, including 29 DENV-1 strains and 5 DENV-2 strains, isolated from a blood sample from…”? Should be blood samples.

2) Lines 55-59: “DENV, as a member of the genus Flavivirus in the family Flaviviridae, is an enveloped, single stranded, positive-sense RNA virus [8]. The DENV genome is approximately 11,000 nucleotides in length and encodes three structural proteins, namely, the capsid (C), premembrane (prM), and envelope (E) proteins, and seven nonstructural (NS) proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B and NS5) in a single open reading frame (ORF) [9,10].” References 8, 9 and 10 are not appropriate for the citation here.

3) Lines 60-63: “There are five DENV serotypes…classified into different subtypes [11]”? Five DENV serotypes are controversial due to lack of evidence in humans. Major literature states 4 DENV serotypes. There is no citation of 5 serotypes and Reference 11 is inappropriate here. Different subtypes?

4) Line 83: “Guangdong Province sees a continuous increase in the number of patients”?

5) Lines 69 to 77: They provided a review of DENV epidemiology in Guangdong up to 2014. What happened between 2015 and 2017 before their study in 2018?

6) Lines 99-100: “IgM and IgG enzyme-linked immunosorbent assay (ELISA) kits were used to confirm dengue infection”. Please describe which commercial kits were used or in-house assays.

7) Lines 100-101: “A total of 170 serum samples were available”. These are likely acute samples. Which days post onset of symptoms were the samples collected?

8) Lines 112-113: “The amplified PCR products…” What are the PCR conditions? Reference 24 was real-time RT-PCR and not relevant here.

9) Line 117: “DENV-2 standard Hawaii strains”?

10) Table 1 “Primer sequence, and size of RT-PCR product…” There is no information of the size of RT-PCR product. At least, the genome positions of primers should be presented. There is no reference of these.

11) Table 2: The genome positions of primers should be presented.

12) Lines 150-152: “…we set up a global dataset that involved all samples and DENV-1 and DENV-2 sequences available from the GenBank…”? How many sequences from the GenBank were selected in the analysis and what are selection criteria? Do they include representative sequences from different genotypes within each serotype?

13) Lines 201-202: “… the entropy-based index presented by Xia. The ….Iss14) Lines 336-338: “Since Aedes albopictus is the main medium for DENV transmission…eggs and offspring through winter [34]”. Aedes albopictus is the main medium for DENV? Reference 34 is about program interface and is an irrelevant citation.

15) Lines 332-333: “Others were localized strains after vertical transmission”. Vertical transmission has been reported to be very insufficient. Is vertical transmission the only mechanism to explain localized strains? How about silent transmission or sporadic cases plus under-reporting?

Reviewer #2: Liao et al . determined 34 DENV (29 DENV-1 and 5 DENV-2) sequences of E region from isolated virus in Guangzhou, Guangdong Province, China during 2018. They concluded that DENV in Guangzhou was mainly imported from Southeast Asian countries from the phylogenetic analysis but there are several points to be clarified before they reach to the conclusion.

Major concerns.

1. DENV-1 is sub-divided into five genotypes: U, II II, IV and V. DENV-2 is classified as six genotypes: Asian I, Asian II, Asian/American, Cosmopolitan, American and sylvatic. These genotypes should be assigned in Figure 2 and specify the genotypes the presented cluster I-V belongs to.

2. In Table 3, do location columns really indicate the place of infection?

Is there any questioner asking travel history?

3. There are several reports from China. (1) Lin F et al. (https://doi.org/10.1007/s00705-019-04266-1) already reported the DENV-2 genotype Cosmopolitan in same Guangdong province in 2015. (2) Yu H et al. https://doi.org/10.1038/s41598-019-43560-5.) also reported DENV-2 genotype Cosmopolitan in Zhejiang Province, in 2017. (3) Cao et al. (https://doi.org/10.1371/journal.pone.0213353) reported DENV-1 genotype I and V in 2015. (4) Zou et al. (https://doi.org/10.1371/journal.pntd.0007202) also reported DENV-1 genotype I and V in 2014. Many Asian I viruses were deposited to NCBI from China. Before reached to the conclusion that the origin of the virus isolated in this study derived from Southeast Asian countries, the author should pay more attention to the pre-existing Chinese viruses in phylogenetic analysis. Can you deny the possibility from Yunnan or other part of China?

4. The sequences used in molecular clock tests were deviated to recent sequences.

5. Did the author calculate the Bayes factor for phylogeographic reconstruction in Figure 3? What was the cut-off value?

6. In line 173, why the ULRC was selected?

7. In line 174, why the Bayesian skyline coalescent model was selected?

Minor points:

1. The lines in the phylogenetic tree were faint in Figure 2.

2. In line 61, the reference is required for DENV-5.

3. The accession numbers of the reference sequences used in Figure 2-8 should be listed in the supplemental tables.

**********

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Reviewer #1: No

Reviewer #2: No

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6 Oct 2019

Additional Editor Comments

1. It would have been very helpful for the authors to evaluate dengue virus from other years as well. Restricting the study to a single year – even an outbreak year – limits usefulness of the data collected. For instance, did the virus evolve in 2018 in such a way as to be different from previous years? If so, what are the virologic differences across the viral genome?

Answer: We calculated the genetic distance between the sample cluster and the non-sample cluster sequences of Guangdong Province in 2014-2018 and defined them to be compared under the same genotype. The results show that their genetic distance differences are not very significant. The dengue virus has been imported into Guangzhou for a long time, and the genetic distance difference between the sample clusters is not obvious. The dengue virus that is popular in Guangzhou is still based on input.

2. Are other dengue virus sequences available from southern China in the years before 2018?

These should be included in the phylogenetic analyses

Answer: Yes, we take your questions into account when building the ML tree. After searching for the sequence of dengue virus in Genbank, we separated the sequence into two data sets, DENV-1 and DENV-2. Sequences in the dataset are sorted out to remove invalid sequences (E gene is incomplete, no separation sites, no separation time, etc.) so that our dataset can contain many sequences from different countries. Our dataset contains sequences from other southern China, such as Yunnan (another region in China where dengue epidemics), Fujian, Taiwan, etc. The results of the analysis show that there are no clusters in the second cluster sequence that have other sequences in other provinces in China, and the calculation of the ancestral position also shows this result. The ancestors of other sample clusters showed that most of them were imported from Southeast Asian countries, which also indicates that the dengue virus prevalent in Guangzhou is still dominated by input.

3. Serum samples from 170 individuals with dengue were evaluated, so why are genotypic data

presented for only 34? How are these 34 different / similar to the 55 individuals with positive

blood samples?

Answer: This is not clearly described in the manuscript.. We collected 170 samples of suspected dengue patients from the hospital (not yet diagnosed), and then the hospital tested the 170 samples and determined that 55 of them were positive samples. We cultured 55 samples according to the hospital's test, and finally obtained only 34 dengue viruses and conducted subsequent studies. The changed part is in the 101-103 lines of the manuscript.

4. How large are the E gene sequences that were analyzed? This should be stated explicitly.

Answer: The E gene sequence was used for the study length of 1485. We have already added in the manuscript. The changed part is in the 130 lines of the manuscript.

5. Lines 150-152 state that a set of global dengue references were used. How many DENV-1

and DENV-2 references were included?

Answer: As with the answer to the second question, we downloaded a large number of sequences and processed them. The data set used to construct the ML tree of DENV-1 contains a total of 3529 sequences. The data set used to construct the ML tree of DENV-2 contains a total of 3542 sequences. The sequences number used to construct the ML tree will be written in the supplemental material. Already added this data in the article. The changed part is in the 214-215 lines of the manuscript.

6. How was the propagation path evaluated? This part of the analysis is not described in the

Methods.

Answer: The propagation path map is the result of the phylogeographic analyses. The BEAST software is used to calculate the nearest common ancestor position of each sequence, and the result is a "tree" file, a "log" file, and the like. SPREAD v1.0.6 software can read these files and generate a propagation path map. Related steps have been added to the manuscript. The changed part is in the 182-184 lines of the manuscript.

7. For the 5 sequence clusters, the authors should calculate the median genetic distance and

compare that to sequences that are not in clusters. It is important for the readers to have

some quantified measure of similarity / dissimilarity amongst sequences within a cluster.

Answer: This is a very good suggestion. In order to let readers know more about the dengue virus that was popular in Guangzhou in 2018, we used MEGA to analyze their genetic distance. First, we differentiated the DENV-1 and DENV-2 data sets based on genotypes. In order to avoid the influence of the old virus on the calculation of genetic distance, we only extracted the sequence of Guangdong Province for the past five years for the genotype of the sample sequence. Experimental methods and results are provided in the manuscript. The changed part is in the 185-189 lines and 316-319 lines of the manuscript.

Reviewer #1

1. Line 28: “, including 29 DENV-1 strains and 5 DENV-2 strains, isolated from a blood sample from…”? Should be blood samples.

Answer: This is a written error that has been corrected in the manuscript. “blood sample” has been modified to “blood samples” in the assay. We collected 170 samples of suspected dengue patients from the hospital (not yet diagnosed), and then the hospital tested the 170 samples and determined that 55 of them were positive samples. We cultured 55 samples according to the hospital's test, and finally obtained only 34 dengue viruses and conducted subsequent studies.

2. Lines 55-59: “DENV, as a member of the genus Flavivirus in the family Flaviviridae, is an enveloped, single stranded, positive-sense RNA virus [8]. The DENV genome is approximately 11,000 nucleotides in length and encodes three structural proteins, namely, the capsid (C), premembrane (prM), and envelope (E) proteins, and seven nonstructural (NS) proteins (NS1,NS2A, NS2B, NS3, NS4A, NS4B and NS5) in a single open reading frame (ORF) [9,10].”References 8, 9 and 10 are not appropriate for the citation here.

Answer: References 8, 9 and 10 has been modified to new 8 “Characterization of dengue virus resistance to brequinar in cell culture”. The changed part is in the 61 lines of the manuscript.61

3. Lines 60-63: “There are five DENV serotypes…classified into different subtypes [11]”? Five DENV serotypes are controversial due to lack of evidence in humans. Major literature states 4 DENV serotypes. There is no citation of 5 serotypes and Reference 11 is inappropriate here. Different subtypes?

Answer: The five serotypes have not been widely accepted and are only mentioned in a few articles, so we changed it to four serotypes. Different serotypes can be further differentiated into different genotypes. Reference has been changed to 9 “Niu C, Huang Y, Wang M, Huang D, Li J, Huang S, et al. Differences in the Transmission of Dengue Fever by Different Serotypes of Dengue Virus. Vector Borne Zoonotic Dis. 2019. doi: 10.1089/vbz.2019.2477. PubMed PMID: 31503521.” The changed part is in the 63-64 lines of the manuscript.

4. Line 83: “Guangdong Province sees a continuous increase in the number of patients”?

Answer: This is not clearly described in the manuscript. We have corrected the expression in the manuscript. As a result of rapid economic growth, thriving tourism, and the greenhouse effect, there were many patients infected with dengue fever in Guangdong Province, and a serious outbreak occurred in 2014. The changed part is in the 83-85 lines of the manuscript.

5. Lines 69 to 77: They provided a review of DENV epidemiology in Guangdong up to 2014.What happened between 2015 and 2017 before their study in 2018?

Answer: Guangdong Province is a coastal city in southern China and a city with a large population. The dengue virus is imported into Guangdong Province every year to cause an outbreak. In 2014, a serious outbreak broke out in Guangdong Province, and then there will be a small outbreak every year from 2015 to 2018. The following is an article about the report of Dengue cases in Guangdong Province from 2014 to 2018. For details, please see Figure 2 in the article. (Article name: Spatiotemporal analysis of the dengue outbreak in Guangdong Province, China). It can be seen from the figure that there are cases reported in Guangdong every year in the years after 2014, and the number of cases in 2016-2018 shows an increasing trend. The following figure is taken from the above paper.

6. Lines 99-100: “IgM and IgG enzyme-linked immunosorbent assay (ELISA) kits were used to confirm dengue infection”. Please describe which commercial kits were used or in-house assays.

Answer: The test kit used in hospitals is the Diagnostic Kit for Dengue Virus NS1 Antigen (ELISA) and the Dengue IgG/IgM Combo Test Card. The kit information is supplemented in the supplemental material.

Product Name Supplier

Dengue IgG/IgM Combo Test Card Xiamen Boson Biotech Co ,Ltd

Diagnostic Kit for Dengue Virus NS1 Antigen (ELISA) BEIJING WANTAI DRD CO., LTD

7. Lines 100-101: “A total of 170 serum samples were available”. These are likely acute samples. Which days post onset of symptoms were the samples collected?

Answer: Our samples were taken from the hospital and the hospital sampled suspected dengue patients on the day they visited the clinic. All patients had fever > 37.5 °C for less than 72 h.We have added the description to the article. The changed part is in the 99-100 lines of the manuscript.

8. Lines 112-113: “The amplified PCR products…” What are the PCR conditions? Reference 24 was real-time RT-PCR and not relevant here.

Answer: We may don't have a clear statement in the manuscript. RNA was reverse-transcribed into cDNA. Then DENV serotyping was carried out by multiplex RT-PCR. The changed part is in the 114-115 lines of the manuscript.

9. Line 117: “DENV-2 standard Hawaii strains”?

Answer: This is not clearly described in the manuscript. it is written like DENV-1. Now DNVE-2 strains GenBank accession number has been modified to KM279569. The changed part is in the 118-119 lines of the manuscript.

10. Table 1 “Primer sequence, and size of RT-PCR product…” There is no information of the size of RT-PCR product. At least, the genome positions of primers should be presented. There is no reference of these.

Answer: Size of RT-PCR product and genome positions of primers were added to table 1. references are labeled in the method.

11. Table 2: The genome positions of primers should be presented.

Answer: genome positions of primers were added to table 2.

12. Lines 150-152: “…we set up a global dataset that involved all samples and DENV-1 and DENV-2 sequences available from the GenBank…”? How many sequences from the GenBank were selected in the analysis and what are selection criteria? Do they include representative sequences from different genotypes within each serotype?

Answer: 3,529 sequences of DENV-1 were used for the study, and 3,542 sequences of DENV-2 were used for the study. Our dataset downloads all DENV-1 and DENV-2 sequences from genbank and screens the downloaded sequences (removing sequences with incomplete information such as lack of acquisition time and location, missing E gene sequences). The sequence of the data set is representative.

13. Lines 201-202: “… the entropy-based index presented by Xia. The ….Iss

Answer: The DAMBE software is used to calculate the base substitution saturation of the sequence. This calculation program was designed by the designer (Xia) of the DAMBE software. The changed part is in the 210-211 lines of the manuscript.

14. Lines 336-338: “Since Aedes albopictus is the main medium for DENV transmission…eggs and offspring through winter [34]”. Aedes lbopictus is the main medium for DENV? Reference 34 is about program interface and is an irrelevant citation.

Answer: Aedes albopictus is the main medium for DENV; The reference is not appropriate and has been changed to new article -“Guo X, Zhao T, Dong Y, Lu B. Survival and replication of dengue-2 virus in diapausing eggs of Aedes albopictus (Diptera: Culicidae). J Med Entomol. 2007;44(3):492-7. doi: 10.1603/0022-2585(2007)44[492:sarodv]2.0.co;2. PubMed PMID: 17547236.” The changed part is in the 363 lines of the manuscript.

15. Lines 332-333: “Others were localized strains after vertical transmission”. Vertical transmission has been reported to be very insufficient. Is vertical transmission the only mechanism to explain localized strains? How about silent transmission or sporadic cases plus under-reporting?

Answer: It is undeniable that the sequence does have a great impact on the experimental results. The data set used in this study consisted of downloading all dengue virus data from genbank and screening out the invalid sequences. The data set contained a large number of sequences to study. For traceability we also used blast to find kinship sequences, and the results presented a continuous cross-year epidemic. The coverage of the sequence has a great impact on the study, such as silent transmission or sporadic cases plus insufficient reporting, which may lead to false inter-annual transmission. We have already described this in the discussion of the manuscript. The changed part is in the 385-388 lines of the manuscript.

Reviewer #2

1. DENV-1 is sub-divided into five genotypes: I, II III, IV and V. DENV-2 is classified as six genotypes: Asian I, Asian II, Asian/American, Cosmopolitan, American and sylvatic. These genotypes should be assigned in Figure 2 and specify the genotypes the presented cluster I-V belongs to.

Answer: We have modified the map to mark the genotype. Thank you very much for your suggestion

2. In Table 3, do location columns really indicate the place of infection? Is there any questioner asking travel history?

Answer: Yes, we asked about the travel situation of 34 patients. They did not travel before suffering from dengue fever.

3. Many Asian I viruses were deposited to NCBI from China. Before reached to the conclusion that the origin of the virus isolated in this study derived from Southeast Asian countries, the author should pay more attention to the pre-existing Chinese viruses in phylogenetic analysis. Can you deny the possibility from Yunnan or other part of China?

Answer: The data set used to construct the maximum likelihood tree in this study was downloaded from NCBI and can be used for all DENV-1 and DENV-2 sequences analyzed, including Chinese sequences, and we screened these large numbers of sequences. Finally, the database used in the study was formed. The data set contains Chinese sequences such as Yunnan Province, Fujian Province, and Taiwan Province. The results in such a data set show that the sample sequence is not clustered with other Chinese sequences in a cluster. So the results of the ancestral position did not show that they were from other provinces in China.

4. The sequences used in molecular clock tests were deviated to recent sequences.

Answer: Molecular clock detection is based on sequences in the data set. As we mentioned in the manuscript, the dataset we used to build the MCC tree will be detected by the molecular clock before the tree is reconstructed. The sequences contained in these data sets were obtained after BLAST, and they were sampled at different years, but most of them were sequences in recent years, so the results of molecular clock detection showed that they were biased toward the recent sequences. So we also used a uncorrelated lognormal relaxed clock when building the MCC tree.

5. Did the author calculate the Bayes factor for phylogeographic reconstruction in Figure 3?What was the cut-off value?

Answer: Yes, we counted it. Bayes factor cut-off is 3.

6. In line 173, why the ULRC was selected?

Answer: Uncorrelated lognormal relaxed clock (ULRC) is a molecular clock model used by BEAST software to calculate phylogenetic trees. In the study, we examined the molecular clock for the data set. The structure shows that the data set does not exhibit a strict molecular clock shape, so we chose this model.

7. In line 174, why the Bayesian skyline coalescent model was selected?

Answer: The Bayesian skyline coalescent model was used to construct the Bayesian skyline plot of the dataset. We used this model because we wanted to explore the population dynamics of the dataset. This mo model is not used to build the MCC tree, so it does not affect our construction of the MCC tree.

Submitted filename: Response to Editor and Reviewers 917-2.docx

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21 Oct 2019

Molecular epidemiological characteristics of dengue virus carried by 34 patients in Guangzhou in 2018

PONE-D-19-19136R1

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25 Oct 2019

PONE-D-19-19136R1

Molecular epidemiological characteristics of dengue virus carried by 34 patients in Guangzhou in 2018

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