https://orcid.org/0009-0003-4160-6850
Figures
Abstract
Mosquitoes are the primary vectors of arthropod-borne pathogens. Aedes aegypti is one of the most widespread mosquito species worldwide, responsible for transmitting diseases such as Dengue, Zika, and Chikungunya, among other medically significant viruses. Characterizing the array of viruses circulating in mosquitoes, particularly in Aedes aegypti, is a crucial tool for detecting and developing novel strategies to prevent arbovirus outbreaks. In this study, we address the implementation of a sequencing and analysis pipeline based on the Oxford Nanopore Technologies MinION Mk1b system, for arboviral detection in field-caught mosquitoes from Argentina. Full genome of Humaita Tubiacanga Virus (HTV), Phasi Charoen-like Phasivirus (PCLV), Aedes aegypti totivirus (AaeTV) has been sequenced in three distinct regions of Argentina comprising Buenos Aires province, Santa Fe province and the northern province of Salta. Viral sequences enriched by SISPA and coupled with Nanopore sequencing can be a useful tool for viral surveillance, not only for detecting viruses that have a high impact on human and animal health, but also for detecting insect-specific viruses that could promote the transmission of arboviruses.
Author summary
Mosquitoes are well-known vectors of diseases that impact both human and animal health. Among them, the Aedes aegypti mosquito, distributed globally, is particularly notable for transmitting viruses such as Dengue, Zika, and Chikungunya. Developing robust surveillance methods and gaining a comprehensive understanding of the viruses these mosquitoes harbor is essential for preventing disease outbreaks. In this study, we employed Oxford Nanopore Technologies’ sequencing platform to detect viruses in mosquitoes collected from various regions of Argentina. Our findings revealed the presence of several viruses, including mosquito-specific viruses, across different parts of the country. This approach not only helps identify viruses that pose a direct threat to humans and animals but also those that exclusively affect mosquitoes, which may indirectly influence disease transmission dynamics. Our research provides a valuable surveillance tool that can be used not only to help prevent outbreaks but also to gather critical information during ongoing outbreaks.
Citation: Ripoll L, Iserte J, Cerrudo CS, Presti D, Serrat JH, Poma R, et al. (2025) Insect-specific RNA viruses detection in Field-Caught Aedes aegypti mosquitoes from Argentina using NGS technology. PLoS Negl Trop Dis 19(1): e0012792. https://doi.org/10.1371/journal.pntd.0012792
Editor: Geoffrey M. Attardo, University of California Davis, UNITED STATES OF AMERICA
Received: May 27, 2024; Accepted: December 17, 2024; Published: January 10, 2025
Copyright: © 2025 Ripoll et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data that support the findings of this study are publicly available from Sequence Read Archive (SRA) with the identifier PRJNA1116083. Sequence Raw fastq file of each samples Identifiers are: Pool 1 - SAMN41521924 Pool 2 - SAMN41521925 Pool 3 - SAMN41521926 Pool 4 - SAMN41521927 Pool 5 - SAMN41521928 Data was submitted on May 24th, 2024.
Funding: Financial support for this study was provided by the National Agency for Scientific and Technological Promotion (ANPCyT) (PICT N° 2018-01039 - Préstamo BID), granted to MB. LR is funded by the National Scientific and Technical Research Council (CONICET) of Argentina. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
The first hypothesis of arthropod-borne disease transmission was formulated more than hundred years ago [1]. Since that time, numerous diseases with high impact in the human health population have been found to be associated with mosquito-borne transmission [2–3]. The widespread of mosquitoes around the world, particularly the Aedes spp., modulated by anthropogenic activity and also driven by climate change makes the mosquito’s borne viruses a major public health threat [4–5].
Aedes aegypti has its roots in a sylvan ancestor from sub-Saharan Africa, which made its way to West Africa in the late eighth century. It is likely that the mosquito was brought to the New World through the African slave trade, occurring between the fifteenth and seventeenth centuries [6]. This species is the primary vector of Dengue (DENV Serotypes 1–4), Zika (ZIKV), Chikungunya (CHKV) and Yellow Fever (YFV) [7]. Moreover, it has been established that mosquitoes serve as hosts for a broad spectrum of arboviruses and Insect-specific viruses (ISVs), specifically known as mosquito-specific viruses (MSVs). MSVs infect either mosquitoes or cells derived from mosquitoes. The identification of MSVs has significantly broadened our comprehension of viral diversity and has shed light on the intricate interactions between these viruses when they co-infect mosquitoes alongside arthropod-borne viruses (arboviruses) [8]. The presence of MSVs can either suppress or enhance the mosquito’s infection by arboviruses of significant human health importance [9–10]. For example, the presence of Phasi Charoen-like phasivirus (PCLV) and Humaita-Tubiacanga virus (HTV) in Aedes aegypti was recently shown to have a twofold increase in the chances of the mosquito being infected by Dengue virus [11].
The extensive adoption of high-throughput sequencing (HTS) has significantly influenced viromics studies. The widespread utilization of cost-effective and easily accessible massive parallel sequencing platforms has led to a substantial increase in viromic analyses in mosquito samples worldwide, particularly focusing on RNA viruses [12–13]. Regardless of the chosen sequencing platform for virome sequencing, these methods rely on the use of random priming and the amplification of viral sequences in combination with high-throughput sequencing tools [13]. These approaches serve as valuable tools for characterizing the mosquito virome and have led to the discovery of a high diversity of MSVs [14–18].
One of the widely adopted methods for enriching the viral RNA genome in a few steps is the Sequence-independent single primer amplification (SISPA) [19]. This technique involves the use of random oligos anchored to a barcode during the initial retrotranscription of the entire RNA from a sample. Subsequently, a second-strand synthesis is performed using the same primer employed in the first step. The result of these two steps is an unknown double-stranded DNA (dsDNA) sequence flanked by a barcode sequence. The third step encompasses the complete amplification of this product using the barcode primer. Subsequent sequencing of this product and further bioinformatic analysis contribute to viral detection or virome characterization [20–22].
Furthermore, SISPA is widely used couple to third generation sequencing platforms. The combination of both systems was employed for the precise identification of etiological agents, as well as for epidemiological monitoring and virome characterization in several types of samples [23–26].
This study aims to implement a SISPA based method coupled to Nanopore sequencing to monitor the distribution of mosquito-borne viruses, particularly Aedes aegypti, in Argentina. The main purpose is to provide a surveillance tool for the detection of circulating viruses specific to the vector and also viruses that have a significant impact on both human and animal health, as well as enabling the early detection of viral emergencies.
2. Material and Methods
2.1. Mosquito sample capture
Adult Aedes aegypti mosquitoes were captured and morphologically classified between December 2022 and May 2023 (Table 1) from three distinct regions across Argentina (Fig 1). These samples were collected during the Dengue and Chikungunya outbreak that occurred during that period. The first set of samples was acquired from the Buenos Aires metropolitan area, specifically in the city of Quilmes. The second set of samples was collected in the Northwest province of Salta during May 2023, encompassing the cities of Las Lajitas, Galpon, and Joaquín V. González. In both regions, samples were captured using a battery-powered aspirator. The specimens were stored in RNA stabilizer (PB-L, Argentina) for transportation.
The third collection site was the city of Santa Fe in the province of Santa Fe. Here Aedes aegypti eggs were collected using ovitraps and reared to the adult stage. In all cases, samples were grouped into pools and preserved in RNA stabilizer (PB-L, Argentina) for transportation. Upon arrival at the lab, RNA stabilizer was removed and samples were stored at -80° C degrees.
Each collection site shows the number of mosquitoes processed in each sample. Basemap data were sourced from Argenmap by the Instituto Geográfico Nacional de Argentina (IGN, https://www.ign.gob.ar) and OpenStreetMap (https://www.openstreetmap.org). Both datasets are provided under the Open Database License (ODbL, https://opendatacommons.org/licenses/odbl/1-0/).
2.2. Library preparation
2.2.1. Sample homogenization.
The mosquito samples were mixed with 300 μL of SM buffer (50 mM Tris, 10 mM MgSO4, 0.1 M NaCl, pH 7.5) and homogenized using a sterile polypropylene pestle. Subsequently, the pools were centrifuged at 12,000 xg for 10 minutes. The supernatant was then recovered to separate it from mosquito debris and other materials.
2.2.2. RNase and DNase treatment.
The supernatant was treated with 1 U of DNase I (PB-L), 10 U of RNase A (PB-L), and 10X DNase buffer (PB-L) were added to 133 μL of the supernatants to a final volume of 150 μL, followed by incubation at 37°C for 1 h, in order to digest host genomic DNA and the non-enveloped and free RNA.
2.2.3. RNA extraction and purification.
After removing free nucleic acid and host DNA, the total remaining enveloped and encapsulated RNA was extracted and purified using Bio-Zol (PB-L) following the manufacturer’s instructions. The total RNA was then resuspended in 15 μL of nuclease-free water.
2.2.4. First strand synthesis.
The total RNA obtained after the prior purification step was reverse transcribed using Nonamer-anchored barcode primers (Table 2) and M-MLV reverse transcriptase (PB-L). For denaturation, 1 μL of 100 μM primers was added separately to 5 μL of RNA extraction and incubated at 65°C for 5 min, followed by placement on ice for 5 min. Then was added 40 U of RNase inhibitor (PB-L), 200 U of M-MLV, 1 μL of 10 mM dNTPs, 4 μL of 5X first-strand buffer, and nuclease-free water was added to reach a final volume of 20 μL. The reaction was incubated 10 min at 25°C followed by 60 min at 42°C.
2.2.5. Second strand synthesis.
After the first strand synthesis, 1 μL of RNase H (New England Biolabs—NEB) was added to the retrotranscription product to eliminate any remaining RNA hybridizing to the cDNA, followed by an incubation at 37° C for 60 minutes. The second strand synthesis utilized 5 U of Klenow Exo (5’-3’-) (NEB), 2 μL of 100 μM Nonamer-anchored barcode (Table 2), 1 μL of 10 mM dNTPs, 2 μL of 10X Buffer NEB 2 (NEB), 8 μL of cDNA from the previous step, and nuclease-free water, to reach a final volume of 20 μL. The reaction included incubation at 4° C for 10 minutes, followed by a second step at 25° C for 10 minutes, a third step at 37° C for 60 minutes, and a final step at 75° C for 10 minutes. Subsequently, to eliminate ssDNA and free phosphate, the reaction was incubated with 10 U of Thermolabile Exonuclease I (NEB), 1 U of Thermolabile Shrimp Alkaline Phosphatase (NEB), in 1X CutSmart Buffer (NEB), in afinal volume of 50 μL. The reaction was incubated at 37° C for 60 minutes, followed by a heat denaturation at 75° C for 10 minutes.
2.2.6. Sequence-independent single primer amplification (SISPA).
The reaction was performed adding 10 μL of dscDNA from the previous reaction, 2.5 μL of 10 mM dNTPs, 1.5 μL of 50 mM MgCl2, 2.5 μL of 10 μM of the corresponding phosphorylated barcode primer for each sample (Table 2), 2.5 U of Taq Pegasus (PB-L), 5 μL 10X Taq Pegasus Buffer, and nuclease-free water, reaching a final volume of 50 μL. The reaction involved an initial denaturation step at 92° C for 5 minutes, followed by 30 cycles of 92° C for 15 seconds, 55° C for 15 seconds, and 72° C for 2 minutes, with a final extension step at 72° C for 5 minutes. Gel electrophoresis on a 2% agarose gel was used to visualize the effective amplification of each sample and estimate the average fragment size post amplification. After verification, all samples were subsequently purified using the Attractor System (PB-L). The DNA was eluted in 20 μL of nuclease-free water, and the purified products were quantified using the Qubit 3.0 with the Quant-iT dsDNA Broad-Range Assay Kit (Thermo Fisher Scientific).
2.3. Sequencing
Each sample of barcoded amplicons resulting from SISPA was pooled in equimolar quantities for sequencing adapter ligation. For the sequence adapter ligation 10 fmol of each sample were pooled and ligated to sequencing adapters using SQK-LSK109 kit from Oxford Nanopore Technologies (ONT). Adapter ligated libraries were loaded onto the SpotON flow-cell (R.9.4.1) and sequencing was performed using the MinION Mk1B system (ONT) and sequencing runs were performed for about 24 h using Min-KNOW software (ONT) with a cutoff of Q = 7 and reads ≧ 200 pb.
2.4. Bioinformatic pipeline
To obtain the genomic sequences of the viruses present in the different samples, an ad hoc bioinformatic pipeline, described below, was generated based on Python script. Raw Reads in Fast5 format were converted to POD5 format using POD5 Tools (v. 0.2.4). Basecalling and conversion to FastQ format was performed using Dorado (v. 0.3.4, https://github.com/nanoporetech/dorado; accessed in September 2023) with a quality cutoff of Q = 10. Basecalling model used was dna_r9.4.1_e8_sup@v3.6. The reads were trimmed and demultiplexed using Oxford Nanopore Technologies Guppy barcoder.
Identification of viral related reads was performed through many local BLASTN [27] searches. The first search was made against the complete non redundant virus database (nt_viruses). Then, against bacterial, and eukaryotic rRNA databases (16S_ribosomal_RNA, 18S_fungal_sequences, 28S_fungal_sequence, ITS_eukaryotic_sequences, LSU_eukaryote_rRNA, LSU_prokaryote_rRNA). Finally, against the human genome (GRCh38.p14) and Aedes aegypti genome assembly AaegL5.0. For date accession and full links to databases see S1 Table. In all the cases we use a cut-off e-value of 1e-5.
In order to avoid the inclusion of reads derived from endogenous viral elements (EVEs) from Aedes aegypti, we performed the following: The BLASTN hits matching the viral database were filtered using the results from the hits to the rRNA, Aedes aegypti genome assembly AaegL5.0 and human databases. When a viral hit matched any of the latter, the bit score value from BLASTN was used to make a decision. If the bit score of the viral hit is greater than the rRNA, Aedes aegypti AaegL5.0 or human hit the read is included; otherwise is discarded (S2 Table). The filtered reads were divided by organism, based on the species TaxID of the target (S3 Table). Viral hits were mapped against a reference using Minimap2 (v. 2.24) indicating to the software that the reads used in the alignment to a reference genome are noisy long reads from ONT (-x map-ont option). The other parameters of Minimap2 (v.2.24) were set by default [28]. BAM files were generated using Samtools (v. 1.17) [29]. Coverage at each position was computed using the Samtools (v. 1.17) coverage tool and then the histograms were generated with SigmaPlot (v. 11.0). Viral consensus sequences were obtained from the BAM files in FASTA format using Samtools (v. 1.17). Due to the possibility of collapsing viral quasispecies during reference alignment, the frequency of each base was evaluated, position by position, in each of the fully assembled viral segments. This was done with the aim of visualizing SNP frequency in each assembly.
2.5. Phylogeny inference
For each novel viral genome, phylogenetic inference was performed using previously established gene or protein sequences for identification (or taxonomic assignment) according to the literature. In all cases, a search for similar sequences was conducted using the GenBank virus database and BLASTPor BLASTN, as appropriate. Clustal Omega was employed to generate the alignments [30] and sequence identity percentage matrices were recovered to perform comparative analyses (Tabla Sup_Identidad). Phylogenetic inference was carried out using the Maximum Likelihood (ML) method, utilizing IQ-TREE 2.1.2 [31] and selecting “ModelFinder + tree reconstruction + ultrafast bootstrap (1000 replicates)” for the analysis. Finally, the iTOL server 6.8.2 [32] was utilized for annotation and tree visualization.
3. Results
3.1. Sequencing results
The sequencing was performed in three separate events. The first event involved the five original samples, the second event included the same samples along with an additional third sequencing batch comprising samples from mosquitoes collected in the localities of Las Lajitas, Santa Fe, and Joaquín V. González. The reads resulting from these three sequencing events were merged into a FastQ file per locality. Subsequently, filtering using BLASTN was conducted, and a FastQ file per locality containing only the viral hits was obtained (Table 3). Top BLAST hit for each read per locality is shown in S3 Table.
The primary source of contamination was from the Aedes aegypti transcriptome, posing a significant challenge due to the high presence of EVEs encoded within the Aedes aegypti genome. Including reads derived from EVEs could lead to errors or misinterpretations regarding the biological origin of these viral elements, potentially resulting in reference mapping of viruses that are not truly present in the sample. Additionally, Aedes aegypti rRNA and bacterial rRNA were prominent sources of contamination; all rRNA-derived reads were filtered out to mitigate this. Finally, contamination from the human genome was also detected, although it was less problematic for the subsequent steps.
After completing all filtering steps, we determined the N50 for each dataset. Despite the capability of nanopore sequencing systems to generate long reads, the N50 for most reads was close to 300 bases in several cases. The only dataset with a higher N50 was from Las Lajitas, with an N50 of 731 (Table 3).
After using BLASTN against the viral database each read making viral hit was counted.
3.2. Partially and fully assembled virus genomes
The reference mapping using viral hits resulted in partial coverage in some cases and complete coverage of viruses in others (Table 4). One of the viruses with the highest presence in the samples is the Phasi Charoen-like Phasivirus (PCLV), which was found and fully assembled across the three regions where mosquitoes were captured. It was fully assembled with high coverage degree and depth in three cities comprising Quilmes, Santa Fe and Joaquín V. Gonzalez. It was partially assembled in the city of Las Lajitas.
The coverage of reads across the reference genomes in the fully sequenced viruses was observed. The three segments of PCLV were mapped in the three regions (Salta, Buenos Aires, and Santa Fe), each showing >97% sequence coverage (Table 4). BAM coverage plots show that the sequence close to the 5’ and 3’ ends are the least covered, but the rest of the genome are fully sequenced and mapped against the reference sequence (Fig 2).
Sequencing reads from different samples were mapped on to the reference sequences for S (small, NC_038263.1), M (medium, NC_038261.1) and L (large, NC_038262.1) segments, respectively, retrieved from GenBank. The X-axis indicates genome position, Y axis indicates sequencing depth. Below each graph, the ORFs of each segment are schematically represented. Collection sites are indicated with different colors.
Among other viruses detected, we have fully mapped and assembled Humaita Tubiacanga Virus (HTV) and Aedes aegypti totivirus (AaTV) (Fig 3). Both genomic segments of HTV were fully sequenced in the samples of Quilmes and Santa Fe. Capsid and RdRp segments showed coverage above 97%, but the assembly from Santa Fe has low mean depth (<18). In the case of AaTV, it was mapped and assembled in the sample belonging to Las Lajitas with a sequence coverage above 99%. AaTV was partially detected in samples from Quilmes, Santa Fe, Galpón and Joaquín V. González city. Only one sample showed the presence of partial genomic regions of Dengue virus serotype 2, from Las Lajitas in the province of Salta.
In order to determine if there is a high grade of SNP’s or collapsed cuasi species, for the fully covered genomes (above 97% of coverage and >12 mean depth) we evaluated the base frequency at each position in the BAM files generated after the reference sequence alignment. The base frequency distribution at each position is above 0.8 in most cases. While there are positions where the frequency falls below this value, the trend indicates that, position by position, the sequences show a high percentage of conservation. Several SNPs are observed compared to the reference sequence, exhibiting variability relative to it. Despite this, within the alignment, the frequency of SNPs is low (S1 Document).
Sequencing reads from different samples were mapped on to the reference sequences for Humaita Tubiacanga Virus–RdRp (MN053809.1), Humaita Tubiacanga Virus–Capsid (MN053810.1), retrieved from GenBank. The X-axis indicates genome position, Y axis indicates sequencing depth. Below each graph, the ORFs of each segment are schematically represented. Collection sites are indicated with different colors.
3.3. Phasi Charoen-like phasivirus
Phasi Charoen-like phasivirus (PCLV) is one of the most prevalent viruses in the Aedes aegypti virome. It belongs to the phlebovirus genus of the Phenuiviridae family. PCLV, in conjunction with Humaita Tubiacanga virus (HTV), has been shown to enhance arbovirus replication in mosquitoes and further the transmission of clinically important arboviruses such as Zika virus and Dengue virus [11].
PCLV has a negative-stranded ssRNA genome consisting of three segments called L, M, and S. Segment S has a size of 1.3 kb and encodes the nucleocapsid gene; segment M has a length of 3.8 kb, encoding the glycoprotein gene; and segment L has a size of 6.8 kb, encoding the RNA-dependent RNA polymerase gene [33]. We detected, reference-mapped, and assembled all three segments of this virus in three distinct regions of Argentina: Quilmes in Buenos Aires province, the City of Santa Fe in Santa Fe province, and Joaquin V. González in Salta Province. Phylogenetic analysis was conducted using the full nucleotide sequence of the three genomic segments, revealing that the three PCLV isolates obtained in Argentina are grouped in a clade with maximum consistency values (100 bootstrapping), being even separated from the isolates obtained in Brazil (S4 Table and Fig 4). For the three segments (S, M and L), an identity percentage greater than 98.0% was observed among the three Argentine isolates (98.0–99.8); while, when compared with the rest of the reported sequences, the identity values varied depending on the segment analyzed. In the case of the L segment, RdRp gene, identity values between 95.2–96.9 were mostly obtained; and only with four isolates from Brazil and Kenya (MT913597.1, OR270147.1, MT361069.1, OR270144.1) values greater than 97% identity (97.0–97.3) were found (See S7 Table for identity matrix). For the M segment, the percentage of identity with the rest of the reported sequences was 92.9–96.6; while for the S segment the greatest variability was observed, with identity percentages from 43.3 to 96.5. These results allow us to hypothesize that the Argentine isolates belong to an isolated clade, exhibiting a very close evolutionary relationship between themselves.
Maximum-likelihood tree based on the nucleotide sequences of full-length S (Panel A), M (Panel B) and L (Panel C) genomic segments of PCVL virus. Prototypes and sequences obtained in this work were used. Each virus is identified by the genome ID (Genbank), the name of the virus with its corresponding strain or isolate, and the country of origin in parentheses. The three Argentine PCLV isolations, identified in this study, are in red. Bootstrap values greater than 50 are indicated. Maximum-likelihood phylogenetic tree was inferred using the GTR+F+R2 model and 1000 replicates in every case.
3.4. Humaita-Tubiacanga virus
HTV is a newly detected virus that has not yet been taxonomically classified. Its genome consists of two segments: one segment of 2.8 Kb encodes an RNA-dependent RNA polymerase, and the other of 1.5 Kb encodes the capsid protein. In this study, we detected and assembled the full genome of HTV from mosquito samples collected in Quilmes city, Buenos Aires province. The 1533 nt fragment encodes a 433 amino acid protein that presents a 99% similarity with the capsid protein (AKP18619) of the first Brazilian HTV isolate (KR003801) [34]. The 2808 nt fragment encodes two main open reading frames. An open reading frame encoding a 460 amino acid protein that presents a 98% similarity with a protein of the Brazilian HTV (AKP18618), annotated as "replicase" in this genome but as a hypothetical protein in the other GenBank genomes. The functional characterization with InterProScan server (https://www.ebi.ac.uk/interpro/) allows us to assume that this hypothetical protein is a peptidase (Peptidase S1, PA clan, IPR009003). The other ORF encodes a 505 amino acid protein that presents a 98% similarity with the RdRp from Kenya isolate (WDR17589). Phylogenetic analysis of RdRp amino acid sequence, obtained by in silico translation of the genomic segments, shows that Quilmes isolated sequence grouped in a separate clade with the first sequence of HTV isolated in Brazil (S5 Table and Fig 5). These two sequences have a similarity percentage of 98.42%, while the identity percentage varies between 95.45 and 98.39 with the rest of sequences. However, it should be noted that all HTV sequences show a high conservation (similarity values of 95.45–100, excluding the outgroup).
Maximum-likelihood tree based on full-length RNA-dependent RNA polymerase (RdRp) aminoacidic sequences from Humaita-Tubiacanga virus prototypes and the genome obtained in this work. Each virus is identified by the genome ID (Genbank), the name of the virus with its corresponding strain or isolate, and the country of origin in parentheses. The Argentinian HTV isolate, identified in this study, is in red. Bootstrap values greater than 50 are indicated. Maximum-likelihood phylogenetic tree was inferred using the HIVb (HIV between-patient matrix HIV-Bm) + F + I model and 1000 replicates.
3.5. Aedes aegypti totivirus
Aedes aegypti totivirus (AaTV) is an unclassified virus belonging to the Totiviridae family. This virus has a dsRNA genome of 7.9 Kbp which encodes for a capsid protein and an overlapped ORF encoding for an RNA-dependent RNA polymerase [35]. In this study, we have recovered the full genome of AaTV (7976 nucleotides) from mosquito samples captured in Las Lajitas, Province of Salta. Using the nucleotide sequence of the RNA-dependent RNA polymerase, we constructed a maximum likelihood phylogenetic tree comparing our sequence with isolates from Brazil, USA, Guadeloupe Island, and Ghana (S6 Table). The tree shows three distinctive clades, previously identified [35], formed by the Guadeloupe Island and USA isolates (denominated A, B, and C); and a fourth clade composed of the isolates from Brazil and from Las Lajitas obtained in this work (Fig 6). Las Lajitas and Brazilian isolates make up a new clade (100 bootstrap), clearly separated from clades A and B. The percentage of identity between these two sequences is 98.5%; while identity percentage varies between 89.5–94.8 with the rest of sequences. In this case, it is also important to mention that when the complete identity matrix is analyzed, identity percentages greater than 98% only occur when comparing sequences from the same clade. This supports the proposal that the South American isolates would belong to another new clade. Furthermore, in this new reported genome the 3 characteristic ORFs were detected; 915-amino acid protein has a similarity percentage of 97% with an RdRp of Aedes aegypti totivirus (QEM39153.1),. The two other ORFs encoding proteins of 906 and 471 amino acids, and presenting 97% similarity with the capsid protein (QEM39152) and 96% similarity with a hypothetical protein (QEM39144) of Aedes aegypti totivirus, respectively. No similarity was detected with the amino acid sequence from Brazil because it was not annotated in the database. According to these evolutionary analyses, it could be inferred that the South American isolates come from an ancestor that clearly differs from those from which clades A and B arise. However, to confirm these proposals, more analysis of genomic comparisons should be carried out.
Maximum-likelihood tree based on full-length RNA-dependent RNA polymerase (RdRp) nucleotide sequences from Totivirus prototypes and the genome obtained in this work. Each virus is identified by the genome ID (Genbank), the name of the virus with its corresponding strain or isolate, and the country of origin in parentheses. The Argentinian Totivirus isolate, identified in this study, are in red. The branches of each main phylogenetic clades (A, B, C) are colored. Bootstrap values greater than 50 are indicated. Maximum-likelihood phylogenetic tree was inferred using the General Time Reversible (GTR) +F + G4 distribution model, Gamma shape alpha of 0.1301 and 1000 replicates.
4. Discussion
This work aimed to characterize the virome of wild mosquitoes from Argentina using nanopore-based NGS technology. For this, adult mosquitoes and eggs were collected during the year 2022–2023 in different regions of Argentina (Salta, Buenos Aires and Santa Fe). We implement a scheme to process the samples and select the fraction containing viral particles and budding vesicles. To identify the RNA virome from mosquitoes, a methodology based on SISPA was implemented. Subsequently, libraries compatible with nanopore NGS technology were built. Finally, the data obtained was analyzed bioinformatically using a pipeline designed ad-hoc, based on genomic identification and assembly using reference databases.
The bioinformatic analysis comprised thorough filtering steps including BLASTN against several ribosomal gene databases. This was necessary because several reads were found with homology to a single virus-specific genomic region and to some ribosomal genomic sequences. This indicates that the procedure used to extract and purify viral RNA must be more exhaustive when depleting circulating RNA. Subsequently, the data was filtered with the human genome database, since various reads with homology with human genes were found. Also a final filtering step was conducted against the Aedes aegypti genome assembly AaegL5.0. This was an essential step in order to avoid the inclusion of reads derived from the endogenous viral elements integrated in the mosquito genome.
The implementation of our workflow, combining SISPA methodology with Nanopore sequencing and a bioinformatics pipeline designed for its analysis, allowed us to identify the presence of several ISVs in mosquitoes from different areas of Argentina. From the samples collected in northern Argentina, specifically in Galpón, Las Lajitas and Joaquín V. González in Salta, we proceeded to work only with the isolates from the latter two locations due to the higher number of reads. In Joaquín V. González isolate the complete genome sequence of PCLV was obtained, while in Las Lajitas we obtained partial genomic segments with more than 50% coverage in the 3 segments. Likewise, AaTV was completely sequenced in Las Lajitas isolate, almost completely in the Joaquín V. González isolate (93% coverage, 8.28 mean depth) and detected in low proportion in samples from El Galpón (59% coverage). In addition, in Joaquín V. González isolate we obtained a sequence corresponding to a fragment of the HTV genome. Phylogenetic and sequence identity analyses allowed us to determine that “Las Lajitas” AaTV isolate is more related to the Brazilian isolate, forming a new South American isolate clade separated from the rest. Similarly, PCLV Joaquín V. González isolate appears to be more ancestrally related to other Argentine isolates than other countries. Furthermore, the characterization of the PCLV L segment allowed us to directly link the Argentine samples with one of the Brazilian isolates. Finally, it is important to mention that a genomic region of Dengue virus serotype 2 was partially detected in Las Lajitas isolate, a location with reported Dengue outbreaks. Particularly in Salta Province DENV 2 was reported as the primary circulating serotype during the 1st and 14th epidemiological week of 2023.
On the other hand, of the sample collected from Quilmes we detected the full genomic sequence of HTV and PCLV, while we obtained a partial genomic sequence of AaTV (32%). The PCLV genome has similar characteristics to those of the genome obtained in Joaquín V. González, and forms a clade with the other Argentine samples closely related to one Brazilian isolate. Remarkably, Quilmes isolate was the only one in which the complete HTV genome was recovered. The two genomic segments presented a higher percentage of identity with the segments of the only HTV isolated in Brazil, and the phylogenetic analysis of the RdRp amino acid sequence links both isolates through a node. Additionally, the samples from Santa Fe also contained the full genomic sequences of PCLV. The presence of this virus in Santa Fe isolate, corresponding to adult mosquitoes reared from eggs collected in 2022, suggests a possible vertical transmission mechanism; as these adult specimens were raised in the laboratory from eggs collected using ovitraps. Vertical transmission of several ISVs, such as Cell fusing agent virus (CFAV) and PCLV, has already been documented [36–37]. AaTV was detected in the Santa Fe isolate but obtaining only partial genome sequences.
It is important to highlight that the methodology presented in this work is practical and suitable for understanding the mosquito virome. Therefore, it could be used as a tool for characterizing the viral diversity present in mosquitoes, not only for detecting viruses that have a high impact on human and animal health, but also for detecting ISV’s; which would be interesting given their ability to interact with arbovirus transmission.
Supporting information
S1 Document. Base frequency distribution plot per complete assembled viral genome.
https://doi.org/10.1371/journal.pntd.0012792.s001
(DOCX)
S1 Table. Date accession and full links to databases.
https://doi.org/10.1371/journal.pntd.0012792.s002
(XLSX)
S4 Table. Accession number of Phasi charoen-like Phasivirus sequences involved in phylogeny inference.
https://doi.org/10.1371/journal.pntd.0012792.s005
(XLSX)
S5 Table. Accession number of Humaita Tubiacanga viral sequences involved in phylogeny inference.
https://doi.org/10.1371/journal.pntd.0012792.s006
(XLSX)
S6 Table. Accession number of Aedes aegypti Totivirus viral sequences involved in phylogeny inference.
https://doi.org/10.1371/journal.pntd.0012792.s007
(XLSX)
Acknowledgments
We gratefully acknowledge the support and funding provided by the Argentinean public university system, the National University of Quilmes, the National Agency for Scientific and Technological Promotion (ANPCyT), and the National Scientific and Technical Research Council (CONICET) of Argentina. Their continuous support has been fundamental in facilitating our research endeavors and contributing to the advancement of science and knowledge.
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