# High-throughput screening reveals high diversity and widespread distribution of viruses in black soldier flies
(Hermetia illucens)

Robert D Pienaar, Salvador Herrero, Alexandra Cerqueira de Araujo,
Franciszek Krupa, Adly M M Abd-Alla, Elisabeth A Herniou

► To cite this version:

Robert D Pienaar, Salvador Herrero, Alexandra Cerqueira de Araujo, Franciszek Krupa, Adly M M Abd-Alla, et al.. High-throughput screening reveals high diversity and widespread distribution of viruses in black soldier flies (Hermetia illucens). Journal of Invertebrate Pathology, 2025, 211, pp.108322. 10.1016/j.jip.2025.108322. hal-05032657

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# High-throughput screening reveals high diversity and widespread distribution of viruses in black soldier flies (*Hermetia illucens*)

Robert D. Pienaar<sup>a,b,*</sup>, Salvador Herrero<sup>b</sup>, Alexandra Cerqueira de Araujo<sup>c</sup>, Franciszek Krupa<sup>d</sup>, Adly M.M. Abd-Alla<sup>d</sup>, Elisabeth A. Herniou<sup>a</sup>

## ARTICLE INFO

### Keywords:

* Virus discovery

* Metatranscriptomics

* Mass-reared insects

* Insects as food and feed

## ABSTRACT

Virus discovery in mass-reared insects is a growing topic of interest due to outbreak risks and for insect welfare concerns. In the case of black soldier flies (*Hermetia illucens*, BSF), pioneering bioinformatic studies have uncovered exogenous viruses from the orders *Ghabrivirales* and *Bunyavirales*, as well as endogenous viral elements from five virus families. This prompted further virome investigation of BSF metagenomes and metatranscriptomes, including from BSF individuals displaying signs and symptoms of disease. A high-throughput pipeline allowed the simultaneous investigation of 203 next generation sequencing datasets. This revealed the presence of seven viruses belonging to the families *Dicistroviridae*, *Iflaviridae*, *Rhabdoviridae*, *Solinviridae*, *Inseviridae*, *Lebotiviridae*, and an unclassified *Bunyavirales*. Here we describe five viruses, which were detected in BSF from multiple origins, outlining the diversity of naturally occurring viruses associated with BSF colonies. As this viral community may also include BSF pathogens, we developed molecular detection tools which could be used for viral surveillance, both in mass-reared and wild populations of BSF.

## 1. Introduction

Recent research advances in virus discovery have underlined the vast diversity and potential impact of viruses. Notably, high-throughput sequencing (HTS) has significantly enhanced our understanding of the insect virome and its rich diversity with over 2 600 unique viruses discovered in insects (Shi et al., 2016; Wu et al., 2020). However, insect viromes remain largely unexplored, including in economically important species like the black soldier fly (BSF, *Hermetia illucens* L. 1758) (Jensen and Lecocq, 2023; Joosten et al., 2020). This gap is especially critical given the rising use of BSF for sustainable waste management and for food and feed, as viral infections within insect mass-rearing facilities could pose a significant risk to productivity and sustainability (Bertola and Mutinelli, 2021; de Miranda et al., 2021a; Maciel-Vergara and Ros, 2017). Viruses have indeed caused mortalities in cricket mass-rearing facilities in which covert infections are widespread (de Miranda et al., 2021a,b; Duffield et al., 2021; Lim et al., 2024; Takacs et al., 2023). In this context, expanding viral surveillance tools is

essential to prevent disease risks.

Although BSF are considered resilient against pathogens, they could harbour viruses detrimental to their health (Jensen and Lecocq, 2023). Recently, paleovirological evidence has shed light on past virus interactions with BSF, with the identification of endogenous viral elements related to the families *Parvoviridae*, *Partitiviridae*, *Rhabdoviridae*, *Totiviridae* and *Ximnoviridae* (Pienaar et al., 2022). Data mining of BSF transcriptomes also revealed five exogenous viruses infecting BSF: Hermetia illucens totivirus 1 (HiTV1), Hermetia illucens inse-like virus 1, Hermetia illucens sigma-like virus 1, BSF nairovirus-like 1 and BSF uncharacterized bunyavirales 1 (Pienaar et al., 2022; Walt et al., 2023, 2024), although their impact remains undetermined. A recent taxonomical revision of viruses related to totiviruses, now places HiTV1 and the related endogenous sequence within the family *Lebotividae* (Sato et al., 2023). These preliminary studies highlighted the need for further characterization of the BSF virome, however perusing deep-sequencing data outputs from established virus discovery pipelines is usually time-consuming and requires specific expertise. This leads to viral sequences

<footnote><sup>a</sup> Institut de Recherche sur la Biologie de l'Insecte, UMR 7261 CNRS – Université de Tours 37200 Tours, France</footnote>

<footnote><sup>b</sup> Department of Genetics and University Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, 46100 Burjassot (Valencia), Spain</footnote>

<footnote><sup>c</sup> Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom</footnote>

<footnote><sup>d</sup> Insect Pest Control Laboratory, Joint FAO/IAEA Programme of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100 1400, Vienna, Austria</footnote>

<footnote>* Corresponding author.
E-mail address: robertdpienaar@gmail.com (R.D. Pienaar).</footnote>
being overlooked, a recurring issue in virus discovery (Cobbin et al., 2021; Obbard, 2018; Waite et al., 2022). A comprehensive high-throughput approach for screening deep-sequenced HTS samples could improve the efficiency and accuracy of viral sequence determination. One method involves screening datasets using mapping and cluster-based approaches, and then performing virus discovery on datasets positive for particular conserved viral domains, such as the RNA-dependent RNA polymerase (RdRP; Charon et al., 2022; Edgar et al., 2022; Olendraite et al., 2023; Walt et al., 2023; Wu et al., 2020). However, this approach initially restricts the search to few hallmark genes, which are not universally present in viruses and relies on the presence of enough viral-like sequences in the datasets to be clustered within current software limitations (Edgar, 2010; Li and Godzik, 2006). As other dipteran models such as *Ceratitis capitata* (Hernández-Pelegrín et al., 2024, 2022) and *Drosophila* spp. (Webster et al., 2016), host more viruses than BSF, this calls for a more comprehensive search of BSF datasets and for a broadened exploration of BSF from different sources.

Here we firstly aim to expand knowledge on the diversity of exoge-
nous virus candidates potentially pathogenic to BSF and on their fre-
quency of presence across different BSF populations. We thus sought to
(1) optimize approaches for more high-throughput screenings for vi-
ruses in large HTS dataset batches, (2) identify infectious candidates
among viral sequences circulating in BSF, (3) determine the frequency of
presence of these viruses in different BSF colonies, and (4) develop RT-
PCR and RT-qPCR screening methods for these newly discovered BSF
viruses. By doing so, this study intends to contribute to sustainable BSF
health in insect farming and develop approaches that could be applied
across different insect models.

## 2. Materials and methods

2.1. BSF sampling

A total of 74 BSF samples were investigated during this study from reared colonies. This includes 25 samples from company/research facilities in France, Netherlands and Spain, including some BSF at various life stages displaying signs and symptoms of disease. Additionally, 49 samples were obtained from three research colonies reared separately at IRBI (Université de Tours, France) and at CBP (Universitat de València, Spain). These 74 samples were all screened by RT-qPCR. Additionally, 36 of these samples were used for metatranscriptome analyses (NCBI bioprojects PRJNA1079553 and PRJNA841369, Table S1).

Furthermore, 167 sequence read archive (SRA) datasets from 15
bioprojects containing metatranscriptomic and metagenomic data ob-
tained from BSF were retrieved form NCBI using the keywords "Her-
metia + illucens" and "black + soldier + fly" (22nd October 2023,
Table S1).

## 2.2. RNA extraction and sequencing

Transcriptomes were obtained from 36 samples for this study. Total
RNA was extracted from 11 individual BSF larvae and adult samples
with the ZymoBIOMICS DNA/RNA Miniprep Kit (cat. R2002, ZYMO
Research, Freiburg, Germany). The RNA was quantified using the
Qubit™ 2.0 Fluorometer (Invitrogen, Waltham, MA, USA). Total RNA
preparations were sent for sequencing on an SP4 flow cell (2x 150 bp,
paired-end) on a NovaSeq 6000 (Illumina, San Diego, USA) at Eurofins
Genomics Germany GmbH (Ebersberg, Germany). The sequencing li-
brary preparations included purification by strand-specific cDNA library
construction using oligo-dT primers (Table S1). These transcriptomes
are archived under the NCBI bioproject PRJNA841369. Furthermore, 24
datasets comprising LncRNA and mRNA were sequenced together on a
NovaSeq 6000 (2x 150 bp, paired-end reads) by Novogene (Beijing,
China), and can be found under the NCBI bioproject PRJNA1079553.
Lastly, one sample received included for RT-qPCR analysis, was
extracted using the Trizol protocol as below and sent for sequencing

using a 101 bp paired-end read configuration (SRR28596310, from
PRJNA841369) at Macrogen, Inc (Seoul, South Korea).

Additionally, 38 BSF samples were prepared for RT-qPCR analysis using Tripure (ref. 11667157001, Roche, Basel, Switzerland) according to the Trizol (Invitrogen, Waltham, MA, USA) manufacturer's protocol, with the exception that the RNA pellet was centrifuged at 7600 × g for 10 min during the 75 % ethanol step. The RNA was quantified either by Qubit or Nanodrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA). Total RNA was treated with the DNase I, RNase-free kit (EN0521, Thermo Fisher Scientific, Waltham, MA, USA) before random hexamer-based cDNA synthesis using the PrimeScript RT Reagent Kit (Perfect Real Time; TAKRR037A, Takara Bio, Kusatsu, Japan).

## 2.3. Bioinformatic analyses pipelines

2.3.1. Virus and host database construction (PoolingScreen)

TaxonKit (v0.3.0, Shen and Ren, 2021) and SeqKit (v0.10.0, Shen et al., 2016) were used to extract viral (TaxID: 10239) and BSF (TaxID: 7108) proteins from the NCBI nr or nt database and create a host/viral database.

2.3.2. Virus discovery (PoolingScreen – A result collating screening pipeline and Lazypipe2)

A virus discovery pipeline (referred to as PoolingScreen, https://doi.org/10.5281/zenodo.14289390) was adapted to incorporate elements of the endogenous viral element discovery pipeline (Pienaar et al., 2022) and to improve the processing time of searching for viruses within a large collection of metatranscriptomic and metagenomic datasets (Fig. 1). These adaptations included using DIAMOND BLASTx (v2.0.15.153, Buchfink et al., 2021) instead of Virsorter2 (Guo et al., 2021) to classify contigs against a BSF protein and viral protein database generated from the NCBI nr database (downloaded 15th May 2022). Contigs with viral-like hits were extracted using an AWK script and reclassified against the entire NCBI nr database. Krona (Ondov et al., 2011) was used to visualize lineages of classified contigs after each classification step. Finally, viral contigs from each dataset were collated into one fasta file while maintaining their original sample information, and then assessed using CheckV (Nayfach et al., 2020) (Fig. 1, Fig. S1).

In parallel, Lazypipe2 (Plyusnin et al., 2023) was modified to process both metagenomic and metatranscriptomic datasets by coding an option to use rnaSPAdes instead of SPAdes and incorporating the "transcripts. fasta" output in the place of "contigs. fasta" and "hard_filtered_transcripts. fasta" output in the place of "scaffolds. fasta" (https://doi.org/10.5281/zenodo.14289071).

### 2.3.3. Mapping for coverage and plotting heatmaps

A contig for each virus candidate with complete open reading frames (ORFs) was chosen as a representative sequence, on which to map the sequence reads to assess presence and coverage of viruses in available BSF HTS datasets. Fastq files for each metatranscriptomic/metagenomic dataset were compressed to "GNU zip" format and the reads were trimmed using fastp v0.23.2 (Chen et al., 2018). Then the reads were mapped to the representative viral sequences using Bowtie2 v2.4.2 (Langmead and Salzberg, 2012). The mapped reads were imported into BAM format, sorted and indexed to extract mapped reads using samtools v1.9 (Li et al., 2009).

An R-script (R v4.2.2; R Core Team, 2022) was used to create a
 heatmap visualising the location of mapped reads of all the datasets
 simultaneously and the number of mapped reads, separately for each
 virus. For a virus to be considered present within a sequencing dataset, a
 threshold of 10 reads had to map across ORF regions. A second R-script
 was then used to generate a heatmap displaying the presence/absence of
 viruses within inspected BSF colonies and the output from the script was
 adjusted using Inkscape v1.1 to 1.2 (Harrington, B. et al (2004–2005),
 available at: inkscape.org). Finally, the co-circulation of viruses within
 BSF colonies and possibility of co-infections were evaluated through a
<figure><img src="image_4.png" /><figcaption>Fig. 1. Flowchart of the approach followed by PoolingScreen pipeline. Presenting the succession of software and scripts used in this pipeline, as well as the different outputs that can be obtained.</figcaption></figure>

co-occurrence analysis and tested using a two-tailed Fisher's exact test.

## 2.4. Viral genome annotation

Viral consensus sequences were annotated as previously (Pienaar et al., 2022), using ORF finder on Geneious Prime v2021.1—2023.1.1 (https://www.geneious.com) and BLASTp (RRID:SCR_001010). Additionally, Geneious InterProScan v2.0 and v2.1.0 (Quevillon et al., 2005) plugins and HHpred (Söding et al., 2005; Zimmermann et al., 2018) were used to cross-check BLASTp results. For the virus genome contigs, the mapped reads were viewed and the mean coverage was calculated using Geneious Prime. The annotations were exported as GFF files, and the coverage plots values were exported as csv files and imported into R to plot the genome annotations and coverage maps.

## 2.5. Phylogenetic analyses of viruses

Regions such as the *pol* and *gag* open reading frames (ORFs; *Ghab-rivirales*), the *L* ORF (*Rhabdoviridae*) and the RNA-dependent RNA po-lymerase (RdRP) conserved domain (*Picornavirales*) were utilized to construct phylogenetic trees. All alignments were performed using MaFFT v7.45 (G-INS-I, BLOSUM62) (Katoh and Standley, 2013), except the alignments for the *Ghabrivirales* ORFs for which BLOSUM30 was used to account for greater genetic distance between taxa. Subsequently, the alignments were trimmed so that the start and end positions were available for 98 % of taxa and positions with gaps encompassing over 10 % of the sequences removed. The maximum-likelihood trees were inferred using IQ-TREE 2 software v2.1.3 (Guindon et al., 2010; Kalyaanamoorthy et al., 2017; Minh et al., 2013, 2020). For the *Picor-navirales* and *Rhabdoviridae* trees, IQ-TREE 2 chose “Q.pfam + F + I + G4” as the model of best fit. For the *Ghabrivirales* tree, the *pol* and *gag* ORF alignments were then concatenated before the phylogenetic ana-lyses and the models “VT + F + R4” and “Q.pfam + F + R6” were selected for the *gag* and *pol* ORF partitions respectively by IQTREE 2. All

trees were visualized using an R-script.

## 2.6. Molecular detection assays

RT-qPCR and RT-PCR protocols were designed to detect BSF viruses. Primer sets for RT-qPCR and RT-PCR setups (Table S2, S3A) were designed using Primer3Plus and Primer3 v2.3.7 (Untergasser et al., 2012) with the default parameters. The product size was set between 100 and 200 bp, and the GC clamp was set to 1 for the RT-qPCR. Primer sets for RT-PCR assays were designed to amplify ~ 1 kb fragments (Table S4, S5).

When possible, log10 primer efficiencies for RT-qPCR were calcu-lated using 5 to 7 dilution points of purified RT-PCR products (~1 kb in size) for detected viruses. Log2 dilutions were used for HiSgV since its abundance was relatively low. Additionally, log10 efficiencies were calculated using 7 dilution points for samples that tested positive for the corresponding virus candidate (Table S2B). For viruses detected by RT-qPCR, a representative product for each virus underwent Sanger sequencing at STAB Vida (Caparica, Portugal) to confirm positive detection of the target sequence. Afterwards, RT-qPCR conditions were optimized to improve the primer efficiencies (Table S3B).

## 2.7. Data and scripts availability

All scripts, including the R-scripts, and list of R package versions used for this paper can be found on Zenodo (https://doi.org/10.5281/zenodo.13975607) and in Table S6. PoolingScreen and HTS mapping visualisation scripts are maintained on Github (https://github.com/RobertPienaar/HT_virus-screening).
# 3. Results

## 3.1. BSFs host diverse RNA viruses

In total, 199 metatranscriptomic and 4 metagenomic samples collected from different BSF life stages, anatomy, or frass/diet were screened for the presence of viral sequences (Table S1). Sequencing depth ranged from 323 K (SRR9068903) to 99 M reads (SRR18283696) with an average of 34 M reads. The mean percentage of sequence reads corresponding to the BSF genome within each dataset was 90.05 % of the total reads. However, seven datasets from larval gut metagenomes or BSF frass (SRR21686212, SRR21686214, SRR21686215, SRR9068902, SRR9068904, SRR9068905 and SRR9068906) had fewer than 1 % (Table S1). In contrast, the only dataset from Gainsville diet (SRR9068903), had 35.34 % of the reads mapping to the BSF genome (Table S1).

The PoolingScreen pipeline detected contigs for seven insect viruses: Hermetia illucens insevirus (HiInV), Hermetia illucens crispavirus (HiCV), Hermetia illucens iflavirus (HiIfV), Hermetia illucens solinvirus (HiSvV), Hermetia illucens sigmavirus (HiSgV), Hermetia illucens lebotivirus (HiLbV) previously identified as Hermetia illucens toti-like virus 1 in Pienaar et al., (2022) and BSF uncharacterized bunyavirus-like 1 (BuBV1) (Table 1). Near-complete genomes were assembled for HiInV (5 839 nt), HiCV (9 364 nt), HiSvV (10 861 nt) as well as HiSgV (11 727 nt), and a partial RdRP fragment (1 127 nt) was obtained for HiIfV.

## 3.2. Structure of virus genomes and coverage maps

Hermetia illucens iflavirus had a 12x sequence coverage from which a genome fragment could be assembled (Fig. 2). The contigs of the other viruses had mean coverages ranging from 105x (HiSgV) to 147 343x (HiSvV) (Fig. 2, Fig. S2 and Fig. S3). Apart from the HiInV and HiIfV contigs, multiple putative proteins and conserved domains were annotated for HiSvV, HiCV and HiSgV (Fig. 2). Most conserved viral protein domains and families were found within the ORFs using InterProScan for HiInV, HiCV, HiIfV and HiSvV (Fig. 2). However, the putative major capsid-like protein region of HiSvV (probability: 99.22 %, E-value: 6.8e-10) was found using HHpred. For HiCV, a short motif “UGAUCU” 36 nt upstream of a “UUAC” motif suggests the presence of an internal ribosome entry site (IRES), typical of cripaviruses, in the untranslated region between the two polyprotein ORFs (Valles et al., 2017a) (Fig. 2).

For HiSgV, domains were found in the L and N ORFs, while ORFs M and G were respectively identified as matrix protein and glycoprotein. The ORF P between ORFs N and M, was labelled based on cross-reference to the sigmavirus genome structure on ICTV. While an additional “X” ORF can be found in some other sigmavirus genomes (Walker et al., 2022), it was not observed in the genome sequence of HiSgV.

## 3.3. Phylogeny of BSF viruses

Phylogenetic trees were inferred to determine the relationship of the newly discovered virus sequences and to assign them to taxonomical classification (Fig. 3, Fig. 4 and Fig. 5). Focusing on the two BSF viruses related to the order *Ghabrivirales*, we found that they belong to two recently established viral families *Lebotiviridae* (HiLbV) (Pienaar et al., 2022; Sato et al., 2023) and *Inseviridae* HiInV (Fig. 3; Walt et al., 2024). Both BSF viruses show significant sequence divergence to other viruses from these families suggesting they belong to new viral species. These two families are associated with insect hosts (Sato et al., 2023; Zhang et al., 2018), suggesting both viruses could be infectious to BSF.

Regarding the three rhabdovirus contigs of Hermetia illucens sigmavirus, they clustered with Hermetia illucens sigma-like virus 1 (Walt et al. 2024). The placement of HiSgV within the monophyletic *Sigmavirus* clade was well supported by bootstrap and SH-aLRT values (>90 and > 80, respectively) (Fig. 4) confirming it as the only member of *Mononegavirales* among the BSF virus candidates. The HiSgV is most closely related to other sigmaviruses infecting flies, but branch length suggests it belongs to a new species.

Three of the BSF virus candidates are distant relatives belonging to the order *Picornavirales*, HiCV (Dicistroviridae), HiLV (Iflaviridae) and HiSvV (Solinviridae) are distantly related to each other but were all within the order *Picornavirales* (Fig. 5). Within the *Solinviridae*, HiSvV belongs to the same clade as *Invictavirus solenopsis* (Solenopsis invicta virus 3) and *Nyfulvavirus nylanderiae* (Nylanderia fulva virus 1), supporting its classification within the family, hence we named it Hermetia illucens solinvirus. High bootstrap and SH-aLRT values supported the placement of the HiCV within the *Cripavirus* genus of the *Dicistroviridae* and HiIfV within the genus *Iflavirus* (*Iflaviridae*). HiCV showed close relationship to Bactrocera dorsalis crispavirus (BdCV), and Bactrocera tryoni dicistrovirus (BtDV) 1 and 2, with branch lengths of less than 0.15 nucleotide substitutions per codon site (Fig. 5) suggesting that these isolates could belong to the same species based on current species demarcation criteria for *Dicistroviridae*. The translated ORFs of BdCV genome (9 117 nt) was > 95 % similar at the amino acid level to those of HiCV (9 364 nt), despite the genome being shorter by 247 nt. Both HiIfV and HiSvV are more distantly related to their closest relatives, indicating they likely represent new viral species.

## 3.4. Widespread screening of BSF virus candidates and colony haplotyping

Following the identification of eight viruses associated with BSF (this study; Pienaar et al., 2022; Walt et al., 2023, 2024), it was then essential to determine their global frequency of presence in BSF colonies (Fig. 6 and Fig. S6 to S9). Two approaches were undertaken. First, we mapped the eight virus genomes against 203 BSF HTS datasets, and second, we screened by RT-qPCR 74 samples (including 36 samples for which HTS datasets were also available). RT-qPCR/PCR primer sets were developed

<table><caption>**Table 1**

List of exogenous virus sequences found in BSF metatranscriptomes.</caption><thead><tr><th>Virus name</th><th>Acronym</th><th>Viral Order</th><th>Viral Family</th><th>Genome Type</th><th>Assembly<sup>§</sup></th><th>Length (nt)</th><th>Coverage<sup>¥</sup> (x)</th></tr></thead><tbody><tr><td>Hermetia illucens lebotivirus<sup>§</sup></td><td>HiLbV</td><td>Ghabrivirales</td><td>Lebotiviridae</td><td>dsRNA</td><td>nc</td><td>7 247</td><td>54</td></tr><tr><td>Hermetia illucens insevirus<sup>*</sup></td><td>HiInV</td><td>Ghabrivirales</td><td>Inseviridae</td><td>dsRNA</td><td>nc</td><td>5 839</td><td>111</td></tr><tr><td>Hermetia illucens crispavirus</td><td>HiCV</td><td>Picornavirales</td><td>Dicistroviridae</td><td>+ssRNA</td><td>nc</td><td>9 364</td><td>622</td></tr><tr><td>Hermetia illucens iflavirus</td><td>HiIfV</td><td>Picornavirales</td><td>Iflaviridae</td><td>+ssRNA</td><td>p</td><td>1 127</td><td>12</td></tr><tr><td>Hermetia illucens solinvirus</td><td>HiSvV</td><td>Picornavirales</td><td>Solinviridae</td><td>+ssRNA</td><td>nc</td><td>10 861</td><td>147 343</td></tr><tr><td>Hermetia illucens sigmavirus<sup>*</sup></td><td>HiSgV</td><td>Mononegavirales</td><td>Rhabdoviridae</td><td>-ssRNA</td><td>nc</td><td>11 727</td><td>105</td></tr><tr><td>BSF nairovirus-like 1<sup>#</sup></td><td>BNaV1</td><td>Bunyavirales</td><td>Nairoviridae</td><td>-ssRNA</td><td>3 seg</td><td>922 - 4 543</td><td>NA</td></tr><tr><td>BSF uncharacterized bunyavirales 1<sup>#</sup></td><td>BuBV1</td><td>Bunyavirales</td><td>Non-assigned</td><td>-ssRNA</td><td>2 seg</td><td>853 - 5 696</td><td>NA</td></tr></tbody></table>

Viruses previously identified: <sup>§</sup> as Hermetia illucens toti-like virus 1 in Pienaar et al., (2022), in <sup>#</sup>Walt et al., (2023) and *as Hermetia illucens insevirus virus 1 in Walt et al. (2024). <sup>§</sup> Completeness of the genome assembly, nc: near complete, p: partial, seg: number of segments; <sup>¥</sup> Mean read coverage of the assembled representative viral contigs using reads deriving from their original transcriptomic dataset; NA: data not available.
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Genomic annotation of five newly discovered viruses. Green arrows indicate open reading frames (ORFs) and yellow boxes represent protein families and conserved domains of putative proteins. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

for a cost-effective identification of the viral infections. Four out of the six viruses (HiSvV, HiSgV, HiInV and HiLbV) were successfully detected using the primer sets that have been designed and employed for the assessment of viral presence in multiple samples. No specific amplification was found yet for HiCV and HiIfV primer sets while testing the available colonies.

With a 60 % detection rate across colonies, the insevirus, HiInV was the most frequent virus in the datasets (Fig. 6). In several colonies for which more than 4 datapoints were available, all samples tested positive for HiInV (C004, C006, C007, C017, C0018; Fig. 6A). Of note, in colonies C011 and C012, which were sampled multiple years, HiInV detection varied, suggesting possible sampling bias. Although the sigmavirus HiSgV was detected in 40 % of the colonies, its presence among 56.1 % of samples within positive colonies was near to that of HiInV (55.1 %) which was detected in 60 % of the colonies. The lebotivirus HiLbV was detected in 28 % of colonies, among which it was present in 73.2 % of the samples from these positive colonies. Four other viruses (HiSvV, HiCv, HiIfV, BuBV1) could be detected in 1 to 3 colonies, however, BNaV1 could not be detected in the datasets (Fig. 6A and Fig. S9).

Considering the four viruses that occurred in more than 8 samples (HiLbV, HiInV, HiSgV and BuBV1), some viruses were detected simultaneously infecting the same samples. Interestingly, the co-occurrence of HiInV and HiSgV (9.1 %), was higher than expected (3.0 %) according to their individual frequency in the dataset (Fisher's exact test: odds ratio of 11.98, *p* < 0.001). In contrast, a similar number of cases were detected each for HiLbV and HiInV. However, only 8 samples showed a co-infection between HiLbV and HiInV, and their co-occurrence was lower than expected (4.8 %; Fisher's exact test: odds ratio of 0.57, *p* >

0.05). Additionally, BuBV1 did not co-occur with any of the other viruses.

Combining meta-omic and RT-qPCR screening data showed the presence of viruses in BSF colonies from China, France, Germany, Italy and the USA, but not in colonies from Canada, Japan or the Netherlands. In 2022, no viruses were detected in samples from colony C024 from Spain (Fig. 6A). However, HiInV was detected in two metatranscriptomic datasets, SRR28204394 (C024) and SRR28204391 (C024), related to a 2023 infection experiment using BSF from colonies C024 and C017 (PRJNA1079553) (Fig. 6A and Fig. S8B). The presence of HiInV genetic material was confirmed by RT-qPCR in SRR28204391 (Table S1 and Fig. S8B).

## 4. Discussion

This study brought the total number of BSF-associated exogenous viruses to eight candidate species belonging to the orders *Ghabrivirales* (*Inseviridae* and *Lebotirviridae*), *Picornavirales* (*Iflaviridae*, *Solinviriridae* and *Dicistroviridae*), *Mononegavirales* (*Rhabdoviridae*), and *Bunyavirales* (*Nairoviridae*, and unclassified). From our new datasets, a single near-complete contig for HiSgV was assembled encompassing all five ORFs, confirming a recent report of this BSF virus in the USA (Walt et al., 2024). This study also introduced alternative *in silico* high-throughput screening approaches enabling the detection of seven of the eight virus sequences in all currently available datasets. Additionally, we developed RT-PCR and RT-qPCR protocols to survey six viruses. We found that BSF viruses were widely distributed with only five out of the 25 examined colonies testing negative for all eight viruses. While data
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Phylogeny of the order Ghabrivirales showing the relationships of the two viral sequences found in BSF (in bold). Branch supports are given by bootstrap (node circle size) and Shimodaira-Hasegawa-like approximate likelihood ratio test (SH-aLRT; node circle colour) values. Sequence accession numbers can be found in Table S7.</figcaption></figure>

mining could introduce sampling biases due to the availability of accessible datasets and the reliability of the metadata, using widely dispersed samples does provide invaluable data on virus and host interactions. The frequency of virus presence within colonies could be inferred based on the number and spatial distribution of the samples. Infections from HiLbV, HiInV and HiSgV are likely common across facilities, while HiSvV, HiCV and HilfV are more sporadic. Moreover, HiInV presence could reach a frequency of 100 % within BSF populations.

The combination of RT-qPCR with the HTS dataset analysis demonstrated that the HTS screening approaches used in this study were sensitive enough to detect low levels of viral infections in datasets.

### 4.1. *Vivrome diversity and novel discoveries*

A large-scale and comprehensive screening of BSF datasets showed that seven of the eight RNA virus candidates can be considered to infect BSF, including five newly discovered viruses. The identification of an exogenous rhabdovirus (HiSgV) and an insevirus (HiInV) parallels the previous finding of endogenous rhabdovirus and totivirus-like sequences in BSF genomes (Pienaar et al., 2022). This suggests recurring interactions between these virus families and BSF. Of note, the short endogenized RhabdoEVE sequence showed low sequence similarity to any known rhabdovirus (55 % similarity; Pienaar et al., 2022), and little homology with HiSgV which therefore represents a distinct species from the rhabdovirus previously endogenized in the BSF genome.
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Phylogeny of Hermetia illucens sigmavirus relative to *Rhabdoviridae*. The sequences were rooted using the *Novirhabdovirus* clade. Branch supports are given by bootstrap (node circle size) and Shimodaira-Hasegawa-like approximate likelihood ratio test (SH-aLRT; node circle colour) values. A tree with un collapsed clades can be found in the supplementary data (Fig. S4). Accession numbers of the sequences used and taxa within the collapsed clades can be found in Table S9.</figcaption></figure>

The identification of a cripavirus (HiCV, *Dicistroviridae*), an iflavirus (HiIFV, *Iflaviridae*) and a solinvivirus (HiSvV, *Solinviridae*) added the order *Picornavirales* to the virome of BSF. Although the HiIFV contig was short, it was included in the BSF virome as it contained the RdRP region, which would allow for future screening activity. The relatedness of HiCV to the *Bractocera* spp. cripavirus sequences could suggest ecological interactions between the hosts BSF, *B. dorsalis* and *B. tryoni* and these viruses. However, further investigations are needed as the consensus genome of HiCV is longer than the reference genomes of the viruses identified in *Bractocera* spp.

## 4.2. Potential pathogenicity of identified viruses

The viral families *Dicistroviridae*, *Iflaviridae*, *Rhabdoviridae* and *Solinviridae* contain many members described as insect pathogens (Brown et al., 2019; Valles et al., 2017b, 2017a; Walker et al., 2022). Notably, HiSvV was found in colonies in which signs of disease (e.g. high mortality) were reported at the time of sampling. Nevertheless, infections for

most members of these viral families remain latent and unnoticed until certain events trigger high levels of mortality (Maciel-Vergara and Ros, 2017; Martin and Brettell, 2019). While the triggers of disease outbreaks are not well understood for *Dicistroviridae*, *Iflaviridae* and *Solinviridae*, in general, high viral loads within the host has been associated with disease (Allen and Ball, 1996; de Miranda et al., 2010; Martin and Brettell, 2019; Valles and Porter, 2015). Since the transmission of these viruses may be both horizontal and vertical (de Miranda et al., 2010; Morrow et al., 2023; Valles et al., 2016; Valles and Hashimoto, 2009), this should be considered when mitigating disease outbreaks.

In *Drosophila*, sigmaviruses are only known to transmit vertically. Although infections can remain asymptomatic (Longdon et al., 2017, 2011a, 2011b), they can increase sensitivity to CO₂, and cause mortalities (Lhéritier, 1958; Longdon et al., 2009). Although more investigations are required on HiSgV, monitoring and controlling CO₂ levels could be beneficial to BSF colony health.

While little is known about inseviruses and lebotviruses, there are some reports of pathogenic interactions within the *Betatotivirinae*
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Phylogeny of the *Picornavirales* showing the relationship of three BSF viruses to arthropod infecting *Dicistroviridae*, *Iflaviridae* and *Solinviviridae* families. *Secoviridae* were used as outgroup. Names of viruses found in BSF are in bold. Viruses with dipteran hosts were highlighted using a silhouette of a fly. Branch supports are given by bootstrap (node circle size) and Shimodaira-Hasegawa-like approximate likelihood ratio test (SH-aLRT; node circle colour) values. All displayed Bootstrap values are higher than 40. A tree with all of the clades shown is available in the supplementary data (Fig. S5). Accession numbers of the sequences used can be found in Table S10.</figcaption></figure>
A

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

B

<table><thead><tr><th colspan="2">Virus</th><th>HiLbV</th><th>HiInV</th><th>HiSgV</th><th>HiSvV</th><th>HiCV</th><th>HiIfV</th><th>BuBV1</th></tr></thead><tbody><tr><td colspan="2">Positive samples, n=241</td><td>21.6%</td><td>22.4%</td><td>13.3%</td><td>1.2%</td><td>0.8%</td><td>0.4%</td><td>3.7%</td></tr><tr><td colspan="2">Positive colonies, n=25</td><td>28%</td><td>60%</td><td>40%</td><td>8%</td><td>8%</td><td>4%</td><td>4%</td></tr><tr><td colspan="2">Frequency of positive samples in positive colonies<sup>†</sup></td><td>73.2%</td><td>55.1%</td><td>56.1%</td><td>27.3%</td><td>NA</td><td>NA</td><td>36%</td></tr></tbody></table>

C

<figure><img src="image_12.png" /><figcaption>Fig. 6. Screening of BSF virus candidates naturally occurring among 241 datasets representing 25 BSF colonies. (A) Detection screening of viral-like sequences in BSF HTS datasets and RT-qPCR amplification. Mapped reads found in HTS metatranscriptomes and metagenomes from different bioprojects are shown in the top panel and results obtained using RT-qPCR detection are shown in the bottom panel. "C###" represented the colony number. The "Numbers" column depicts the number of samples/datasets from each colony where at least one virus was detected. The orange dots indicate which BSF sample collections included some individuals with signs/symptoms of disease. (B) Frequency of virus discovered in samples and colonies and viral frequency among positive colonies. †The frequency of positive samples in positive colonies was only calculated when > 2 positive samples were available among > 8 samples for pooled positive colonies; and (C) Co-occurrence of viruses detected in > 8 BSF samples, numbers indicate how many samples were positive out of the 241 tested; and percentages the frequency of co-occurrence among samples. The greyed boxes in the co-occurrence depict the total number of samples within the data that the viruses were detected in. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

(Ghabrivirales). For example, the pistovirid piscine myocarditis virus, causes mortality in salmon. Additionally, four other viruses have been found to co-occur with mortalities in aquaculture fish (Haugland et al., 2011; Louboutin et al., 2023). This suborder can also cause disease and mortalities in arthropods such as shrimp (artivirid, paneid shrimp

infectious myonecrosis virus) and crayfish (cherax giardiavirus-like virus) (Edgerton et al., 1994, 2002; Edgerton and Owens, 1999; Poulos et al., 2006). In contrast, lebotiviruses have been described to co-occur with some benefits to insect hosts, such as increased offspring survival of Leptopilina boulardi (Martinez et al., 2016). Studies so far
suggest that transmission of *Ghabrivirales* primarily occurs vertically rather than horizontally (Martinez et al., 2016; Zhang et al., 2018). Since these viruses can cause asymptomatic and symptomatic infections, they should not be overlooked when found in diseased individuals.

### 4.3. Efficiency of screening and diagnostic approaches

The study of BSF viruses is still in its early stages, however, foundational knowledge of diverse interactions with viruses has been established (Pienaar et al., 2022; Walt et al., 2023, 2024). Using a dual de novo-based strategy with PoolingScreen and Lazypipe2, this study identified five virus candidates and confirmed two partially characterized viruses (HiLBV and BuBV1). PoolingScreen, by relaxing the specificity from hallmark genes like RdRP to all viral like proteins, detected viral fragments missed by Lazypipe2, although with increased false positives. This highlights the need for balance between sensitivity and specificity in high-throughput virus discovery. Notably, no insect-associated DNA viruses were found in BSF. This is unlikely to have resulted from analytical bias, as PoolingScreen could detect both RNA and DNA viruses previously identified in wild bee transcriptomes (PRJNA411946; Schoonvaere et al., 2018). This could also reflect the low frequency of presence of such viruses in BSF populations. Indeed, in *Drosophila melanogaster* the first naturally occurring large dsDNA virus was only discovered in 2015 (Webster et al., 2015) and is found at relatively low prevalence in natural populations (Wallace et al., 2021). It is therefore possible that DNA viruses could be found in BSF with increased sampling effort, including by surveying wild populations.

Virome studies face challenges in initial viral sequence detection, but expanding genetic databases (Cobbin et al., 2021) and improved virus discovery pipelines (Plyusnin et al., 2023; Guo et al., 2021; Budkina et al., 2021) are enhancing detection accuracy. To validate virus candidates, it is critical to identify core viral genes, but manually processing individual pipeline outputs can be labour-intensive. To address this, PoolingScreen specifically streamlines high-throughput output handling by combining datasets with easy traceability. This approach enhances screening efficiency, aligning with increased HTS production (Goodwin et al., 2016; Moshiri et al., 2022). In addition, the semi-automatic mapping-based screening pipeline allows for rapid screening of samples for known viruses and verify if mapped reads span across the viral genome, including CDS regions (Fig. S6 to S9) to confirm their genuine presence within datasets. This was observed when screening for BuBV1 and BNaV1, both of which have some regions with a high level of identity with other organisms and each other (Fig. S9, Tables S11 to S13), which could induce false positives.

### 4.4. Surveillance and sustainable application

While the susceptibility of BSF to viral diseases remains an open question (Jensen and Lecocq, 2023), the new list of the exogenous viruses can promote viral surveillance in BSF. The high-throughput PoolingScreen approach is valuable for underexplored mass-reared models for which HTS data is available. As HTS technology remains too costly for routine screening, we also developed more cost-effective RT-(q)PCR screening tools for BSF viruses.

BSF viruses are diverse and widely distributed in rearing facilities across the Northern Hemisphere and will likely be found on all continents as more data becomes available. An interaction between viral presence within colonies and the genetic background of hosts could be expected. However, regardless of their geographical origin, most of the BSF colonies screened belonged to the same COI major haplotype (Fig. S10), as previously established (Guilliet et al., 2022; Kaya et al., 2021; Ståhls et al., 2020). The viral distribution pattern was therefore unlikely influenced by the genetic background of the flies. This further demonstrates that viruses are naturally occurring in rearing facilities, and that better surveillance and management networks should be implemented within the BSF industry. Furthermore, this highlights the

need to increase sampling effort as wild BSF populations may host and co-evolve with other viruses, which could one day be transferred to the mass-reared colonies.

### 4.5. Conclusion

This study provides a diverse library of eight viruses likely infecting BSF and lays the foundation for viral surveillance in large-scale BSF rearing facilities. However, further studies are required to determine the impact of these viruses on BSF health both in a mass-rearing context and in the wild. A long-standing issue in mass-rearing facilities is that pathogenic agents may cause covert infections. The development of routine diagnostic tools would accelerate our understanding of viral ecology and disease etiology in BSF.

#### Use of AI statement

During the preparation of this work the authors used ChatGPT v4 (OpenAI) for improving BASH and R-scripts and language editing. The authors have reviewed and fully edited the manuscript and take full responsibility for the content of the publication.

#### Credit authorship contribution statement

**Robert D. Pienaar:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Salvador Herrero:** Writing – review & editing, Supervision, Project administration, Investigation, Funding acquisition, Conceptualization. **Alexandra Cerqueira de Araujo:** Writing – review & editing, Methodology, Formal analysis. **Franciszek Krupa:** Writing – review & editing, Formal analysis. **Adly M.M. Abd-Alla:** Writing – review & editing, Methodology, Formal analysis, Data curation. **Elisabeth A. Herniou:** Writing – review & editing, Writing – original draft, Supervision, Project administration, Investigation, Funding acquisition, Formal analysis, Conceptualization.

#### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

#### Acknowledgements

This study was primarily supported by the INSECT DOCTORS program, funded under the European Union Horizon 2020 Framework Programme for Research and Innovation (Marie Sklodowska-Curie Grant agreement 859850). Salvador Herrero's research in BSF is also supported by the TED2021-130679B-I00 grant, funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. We would like to thank Fang Shiang Lim for his assistance in the database construction script and the Insect Doctors consortium for feedback, as well as the PST ASB and PCE platforms located at IRBI. Lastly, we would like to thank the BSF rearing facilities for allowing the use of genetic data from healthy and diseased samples.

### Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jip.2025.108322.

#### Data availability

Data will be made available on request.
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