Aspergillus flavus, is a significant threat to human health and agricultural production. Histone 2-hydroxyisobutyrylation is a novel post-translational modification that regulates various biological processes, including secondary metabolism. In this study, we identified the novel histone 2-hydroxyisobutyryltransferase Afngg1 in A. flavus, and explored its role in cell growth, development and aflatoxin biosynthesis. Afngg1 gene deletion markedly decreased lysine 2-hydroxyisobutyrylation modification of histones H4K5 and H4K8 compared with the control strain. Additionally, Afngg1 deletion inhibited mycelial growth of A. flavus, and the number of conidia and hydrophobicity were significantly decreased. Notably, aflatoxin B1 biosynthesis and sclerotia production were completely inhibited in the ΔAfngg1 strain. Furthermore, the pathogenicity of the ΔAfngg1 strain infecting peanut and corn grains was also diminished, including reduced spore production and aflatoxin biosynthesis compared with A. flavus control and Afngg1 complementation strains. Transcriptome analysis showed that, compared with control strains, differentially expressed genes in ΔAfngg1 were mainly involved in chromatin remodelling, cell development, secondary metabolism and oxidative stress. These results suggest that Afngg1 is involved in histone 2-hydroxyisobutyrylation and chromatin modification, and thus affects cell development and aflatoxin biosynthesis in A. flavus. Our results lay a foundation for in-depth research on the 2-hydroxyisobutyrylation modification in A. flavus, and may provide a novel target for aflatoxin contamination prevention.Aflatoxin, a carcinogenic secondary metabolite produced by  Aspergillus flavus, one of the most abundant and widely distributed fungi on earth, is often found in pre- or post-harvest crops, and it causes serious economic losses [c losses ,2. It cac losses . It is ec losses . Aflatoxc losses . TherefoUstilaginoidea virens, mutation of the 2-hydroxyisobutyrylation modification site of mitogen-activated protein kinase UvSlt2 decreased UvSlt2 enzyme activity and significantly reduced the development and virulence of plant pathogenic fungi [Botrytis cinerea, Candida albicans, Fusarium oxysporum and Toxoplasma gondii [A. flavus, as well as aflatoxin biosynthesis [A. flavus, but the enzymes involved in histone 2-hydroxyisobutyrylation modification have not been reported in A. flavus. Herein, we identified histone 2-hydroxyisobutyryltransferase Afngg1 in A. flavus, and explored its underlying gene regulatory mechanisms using RNA sequencing (RNA-seq)-based transcriptional analysis.Histone post-translational modifications (HPTMs), including acetylation, phosphorylation, ubiquitination and 2-hydroxyisobutyrylation, play a crucial role in many cellular processes in eukaryotes, including secondary metabolite biosynthesis and chromatin regulation . Among tic fungi . Signifia gondii ,10,11,12ynthesis . These rCandida albicans histone acetyltransferase Ngg1, was found to be associated with histone 2-hydroxyisobutyrylation modification. Additionally, the functions of Afngg1 in cell development and aflatoxin B1 (AFB1) production were profiled, and the underlying regulatory mechanisms were investigated through transcriptome analysis. The findings suggest that Afngg1 is a potential target for the effective control of aflatoxin contamination.In this study, Afngg1, a homolog of A. flavus, we obtained homologous sequences by BLAST searching the NCBI database, and constructed phylogenetic trees to analyse their evolutionary relationships. The results revealed that Afngg1 in A. flavus is closely related to homologs in other fungi, and most similar to homolog in A. oryzae RIB40  domain was found in homologs of Afngg1 proteins in nine species  and chromatin remodelling complex subunits (mit1). Deletion of Afngg1 inhibited the expression of conidia-related genes wetA, abaA, brlA, stuA, vosA, fluG and con-6, and conidia hydrophobicity-related genes rodA and dewA. Additionally, ags1, ags2, MP65, chiB1, dcw1, ecm33, erg4, erg7 and erg5 genes related to cell wall and membrane formation were downregulated.Afngg1 deletion altered the expression of genes involved in chromatin remodelling, including histone deacetylases , polyketones (fluP and aurA), ustiloxin B  and gliotoxin  were also downregulated. Furthermore, afngg1 deletion inhibited the expression of catalase-related genes cta1, ctl-2 and cat.Secondary metabolism was also affected. The results showed that AFBA. flavus. Deletion of Afngg1 reduced the level of histone 2-hydroxyisobutyrylation modification, indicating that Afngg1 functions as a histone 2-hydroxyisobutyrylyltransferase. Additionally, Afngg1 plays a crucial role in the growth and development of A. flavus and the biosynthesis of aflatoxin, and its potential regulatory mechanisms were explored through transcriptome analysis.As an important post-translational modification, 2-hydroxyisobutyrylation plays a vital role in protein synthesis, transcriptional regulation and metabolism . In thisCandida albicans histone H3, and loss of Ngg1 greatly reduced the level of acetylation modification of histone H3 in Ngg1-A and Ngg1-B strains compared with wild-type strains [C. albicans acetyltransferase NGG1 in A. flavus, and identified K9ac and K14ac as the key sites for alteration of histone H3 acetylation. Notably, we also found that Afngg1 is associated with 2-hydroxyisobutyrylation of histone H4, and deletion of Afngg1 significantly reduced lysine 2-hydroxyisobutyrylation levels at the K5 and K8 sites of histone H4.Previous reports have shown that Ngg1 is required for histone H3 acetylation of  strains . HoweverFusarium graminearum, deletion of FgRpd3 led to increased acetylation of histone H4 [crl3 gene encoding histone deacetylase affects the growth of Penicillium brasilianum, and the production of many secondary metabolites [Afngg1, expression levels of clr3, RPD3, epl1 and mit1 genes related to chromatin remodelling were altered. Additionally, previous studies have shown that cobB, de-2-hydroxyisobutyrylation enzyme, is involved in regulating the growth and metabolism of prokaryotes [Afngg1 strain were reduced. These results suggest that Afngg1 may alter chromatin conformation, altering the accessibility of genes, thus affecting cell development and secondary metabolism of A. flavus.Histone modification plays a crucial role in altering chromatin structure, among which histone acetylation and 2-hydroxyisobutyrylation modification are important contributors to chromatin remodelling ,17. RPD3stone H4 . Additioabolites . As a chabolites . We founkaryotes . In humaA. flavus conidiogenesis genes is regulated by a cascade involving brlA, abaA and wetA [BrlA and abaA are key transcription factors, of which brlA initiates conidia formation, and abaA contributes to conidia development and also affects sclerotia formation and AFB1 production [StuA affects the expression of downstream genes by influencing brlA and abaA, and regulates sporulation [VosA, a member of the velvet protein family, co-regulates spore-specific genes with wetA, and is critical for spore maturation and dormancy [A. flavus conidia [FluG plays a balancing role in asexual and sexual development, and deletion of fluG can delay and reduce the formation of A. flavus conidia [fluG can also interact with velB or laeA to control the production of conidia and sclerotia [wetA, abaA, brlA, stuA, vosA, fluG and con-6 related to conidia were downregulated following deletion of Afngg1, mutant strain colonies were white, conidia production was decreased significantly and the strain no longer produced sclerotia. These results suggest that Afngg1 may regulate developmental balance, oxidative stress and conidia trehalose synthesis, and thereby affect the formation of conidia. Additionally, our experiment found that the ΔAfngg1 strain no longer produced sclerotia, consistent with the results of fluG deletion [rodA and dewA, which was confirmed by hydrophobic assay, and is reminiscent of the deletion of laeA in A. flavus [Recent studies have shown that fungal growth, development and production of secondary metabolites are regulated by post-translational modifications such as 2-hydroxyisobutyrylation . Expressand wetA . BrlA anoduction ,22. StuArulation . VosA, adormancy . Loss of conidia . FluG pl conidia ; fluG caclerotia . In the deletion . Transcr. flavus .Ags1 and Ags2 are involved in glucan synthesis, and growth was inhibited after Ags1 deletion [DCW1 is necessary for incorporation of cell wall glycoproteins into the cell wall, and deletion of the dcw1 gene in yeast led to cell wall abnormalities [MP65 encodes β-glucan mannoprotein, which is associated with cell wall integrity and biofilm formation [ecm33 and MP65 increased sensitivity to cell wall degraders and altered morphology [ags1, ags2, MP65, chiB1, dcw1 and ecm33 in the ΔAfngg1 strain were downregulated. Additionally, ergosterol is an important component of cell membranes, and we found that expression levels of genes associated with ergosterol biosynthesis such as erg4, erg7 and erg5 were significantly downregulated after deletion of Afngg1. These results suggest that Afngg1 may impede the synthesis of cell wall components such as glucan, reduce cell wall tolerance and cause cell wall defects.The fungal cell wall is a complex structure composed of chitin, dextran and other polymers that play an important role in fungal growth and survival . Ags1 andeletion . DCW1 ismalities . MP65 enormation . The GPIormation . One sturphology ,33. HereAflC (pksA) encodes a polyketone synthase that is involved in the conversion of acetate to norsolorinic acid, and AFB1 production can be significantly increased by upregulating aflC, aflR and aflK [AflX and AflQ encode oxidoreductases, and AflQ is involved in the formation of AFB1 precursor hydroxyl-methylsterigmatocystin, and it plays a role in the later stages of the biosynthetic pathway [aflQ expression and aflatoxin biosynthesis [AflW encodes a single monooxygenase that catalyses the conversion of hydroxyversicolorone to versiconal hemiacetal acetate [aflS encodes an esterase (AflJ) that interacts with nearby aflR genes to regulate the biosynthesis of aflatoxin [aflS deletion, expression levels of aflatoxin biosynthetic pathway genes including aflC, aflD, aflM and aflP were reduced 5–20-fold, and biosynthesis of aflatoxin intermediates was blocked [Afngg1 downregulated genes encoding enzymes related to the aflatoxin biosynthetic pathway, such as aflC, aflX, aflJ, aflQ, aflT and norA, indicating that Afngg1 can inhibit the biosynthesis of aflatoxin by regulating the expression of multiple genes in the gene cluster via chromatin modification. Our study also found that the ΔAfngg1 strain no longer produced AFB1, consistent with knockout of histone acetyltransferase AflGcnE [It has been reported that chromatin remodelling is closely related to the biosynthesis of aflatoxin . Aflatoxand aflK ,37. Both pathway ,39. Prevynthesis . AflW en acetate . Additioflatoxin . Followi blocked . In the  AflGcnE .Ustilaginoidea virens, and 18 genes form a gene cluster for the synthesis of ustiloxin B. Deletion of a relevant gene led to a complete or substantial loss of ustiloxin B production in A. flavus [A. fumigatus [gliA greatly reduced the biosynthesis of glioxin [gliK significantly hindered efflux of glioxins, and increased sensitivity to exogenous glioxins [ustYa, ustO, ustC, ustP, ustQ, ustD, ustF2, gliK, gliA and gliC, which are responsible for the biosynthesis of ustiloxin B and gliatoxin, were downregulated. In addition, A. flavus produces a variety of polyketone-derived secondary metabolites, which are the most abundant of fungal secondary metabolites [PksP was found to be associated with the biosynthesis and virulence of A. fumigatus conidia pigments [Pks1 gene encodes a polyketone synthase involved in melanin biosynthesis [Flup resulted in decreased filament growth rate and conidial production in A. parasitica [fluP, pksP, aurA and Pks1 were downregulated. These results suggest that Afngg1 may play an important regulatory role in mycotoxin efflux and self-protection.Other secondary metabolic pathways are also affected. Ustiloxin B is a secondary metabolite of . flavus . Biosyntumigatus . Loss of glioxin , and delglioxins . Herein,abolites . PksP wapigments . The Pksynthesis . Deletiorasitica . The precat1 significantly increased intracellular ROS levels, which in turn increased oxidative stress levels and reduced aflatoxin biosynthesis and virulence [cat1, ctl-2 and cat were downregulated, suggesting that deletion of Afngg1 might prevent cells from clearing ROS in a timely manner, thereby diminishing their defences against oxidative stress, and inhibiting the biosynthesis of aflatoxin.Oxidative stress is often associated with the synthesis of fungal secondary metabolites. Biosynthesis of aflatoxin has been reported to be inhibited by increased reactive oxygen species (ROS) levels and decreased activity of antioxidant enzymes . Cells pirulence . In our A. flavus, and explored its potential roles in cell development and aflatoxin biosynthesis. The results indicated that deletion of Afngg1 reduced the degree of lysine 2-hydroxyisobutyrylation modification of histone H4, inhibited cell growth, conidia formation, sclerotia production and AFB1 production in A. flavus, and decreased hydrophobicity. RNA-seq was subsequently used to investigate the underlying regulatory mechanisms, and analysis of DEGs showed that genes associated with chromatin remodelling, cell development, oxygen stress and biosynthesis of aflatoxin, ustiloxin B and gliatoxin, were downregulated. Therefore, these results suggest that histone 2-hydroxyisobutyryltransferase Afngg1 affects chromosomal modification, alters gene expression and regulates the growth, development and aflatoxin biosynthesis of A. flavus. The findings enhance our understanding of the role of histone 2-hydroxyisobutyrylation in aflatoxin biosynthesis and fungal pathogenicity regulation, and provide potential targets for exploring new control strategies for A. flavus.In conclusion, we identified histone 2-hydroxyisobutyryltransferase Afngg1 in A. flavus CA14  served as a control strain, and the Afngg1 knockout strain (ΔAfngg1), Afngg1 complementation strain (ΔAfngg1-Com) and Afngg1-enhanced green fluorescence protein (eGFP) strain were derived in this study. Potato dextrose agar (PDA) was used to evaluate growth, conidia formation, cell hydrophobicity and aflatoxin B1 production, with appropriate amounts of uridine (10 mmol/L) added to the medium as needed. For sclerotia production, spore suspensions were maintained on PDA medium at 37 °C for 7 days in the dark. Each experiment was repeated three times.We used the protein sequence of Afngg1 to perform a BLAST search to identify homologous sequences in the National Center for Biotechnology Information (NCBI) database. Afngg1 domains were predicted by DOG 1.0 software . Afngg1 protein sequences were aligned by ClustalW using MEGA software , and a neighbour-joining phylogenetic tree was constructed . Afngg1 strains were constructed using homologous recombination with PCR primers listed in Afngg1 strain, primers ΔAfngg1-1F, ΔAfngg1-1R, ΔAfngg1-2F and ΔAfngg1-2R were used to amplify the 1.1 kb upstream and 1.5 kb downstream regions of Afngg1 fragments in the A. flavus genome, respectively. Meanwhile, primers pyrG-F and pyrG-R were used to amplify the pyrG selection marker. Fusion PCR was performed using primers ΔAfngg1-1F and ΔAfngg1-2R to generate a fragment containing the upstream and downstream segments, and the pyrG selection marker [A. flavus control strain according to previous methods [The Δn marker . The fus methods , and traAfngg1-Com strain was performed according to previous methods [Afngg1-Com-F and ΔAfngg1-Com-R were used to amplify a fragment including the promoter, coding sequence and terminator from A. flavus control strain genomic DNA, and this was ligated to the pPTRI plasmid following HindIII and SmaI restriction enzyme digestion. The resulting plasmid was transferred into A. flavus ΔAfngg1 protoplasts, and the ΔAfngg1-Com strain was confirmed by PCR. Construction of the  methods . PrimersAfngg1 protoplasts, and transformants were selected for verification.For construction of the Afngg1-eGFP strain, linker, eGFP and TglaA were sequentially connected next to the Afngg1 coding sequence without a stop codon, using primers Afngg1-eGFP-2F and Afngg1-eGFP-2R. The fragment was ligated to the pPTRI plasmid according to previous methods . The conA. flavus spore suspensions (106) were inoculated into Dextrose Peptone Yeast (DPY) liquid medium and cultured at 30 °C for 24 h. After collection, mycelia were washed with phosphate-buffered saline (PBS), stained with 4,6-diamidino-2-phenylindole for 10 min according to a previous method [To detect subcellular localisation of Afngg1, s method , and obsAfngg1 deletion on the acetylation level of histone H3 and the 2-hydroxyisobutyrylation level of histone H4 in A. flavus, A. flavus control and ΔAfngg1 strains were cultured on PDA medium at 30 °C for 72 h. Mycelia were frozen with liquid nitrogen and ground to a powder. An appropriate amount of each protein sample was mixed with sample buffer and protein lysis solution to make a final concentration of 1–2 mg/mL, and heated at 95 °C for 10 min prior to sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Proteins were transferred to a PVDF membrane, and this was blocked with 5% skimmed milk powder after transfer. For analysis of lysine acetylation of histone H3, anti-H3K9ac, anti-H3K14ac and anti-H3 were used as primary antibodies. For analysis of lysine 2-hydroxyisobutyrylation, anti-H4K5hib  and anti-H4K8hib  were used as primary antibodies. Goat anti-mouse IgGI  was used as secondary antibody, and chemiluminescent horseradish peroxidase (HRP) substrate (Millipore) was added and incubated for 2 min for signal detection. Meanwhile, protein gray scale analysis was performed using Image-Pro Plus software  according to a previous method [To explore the effect of s method .Afngg1 on the growth of A. flavus, 2 μL spore suspensions (106 spores/mL) of A. flavus control, ΔAfngg1 and ΔAfngg1-Com strains were separately inoculated in the centre of PDA plates and cultured at 30 °C for 5 days; then, the colony diameter was measured and conidial heads were counted under a stereoscopic microscope . Next, 6 mL sterile water was added to each Petri dish to harvest the mycelium, and the number of conidia was calculated using a hemocytometer. To assess the hydrophobicity of A. flavus mycelia, 20 μL sterile water and 20 μL 3% Bromophenol Blue solution were added to the edges of colonies of A. flavus control, ΔAfngg1 and ΔAfngg1-Com strains, cells were cultured at 30 °C for 2 days, and analysed by a stereoscopic microscope. Quantitative analysis of sclerotia production was performed at 37 °C for 7 days. After 7 days, 75% ethanol was sprayed to wash the medium and expose the sclerotia, and five holes were made along the diameter to count the number of sclerotia. Additionally, scanning electron microscopy (SEM) was used to photograph the conidia microstructure of A. flavus control, ΔAfngg1 and ΔAfngg1-Com strains as described previously [To investigate the effect of eviously .1 production analysis was carried out according to a previously described method [6 spores/mL) of A. flavus control, ΔAfngg1 and ΔAfngg1-Com strains were cultured in 50 mL Yeast Extract Sucrose (YES) liquid medium at 30 °C in the dark for 5 days. An equal volume of chloroform was added to extract aflatoxin from the 50 mL medium. After the chloroform was completely volatilised, the residue was dissolved in 1 mL methanol and then analysed by TLC. The AFB1 yield of A. flavus strains was evaluated using an AFB1 standard sample (0.1 mg/mL).AFBd method . Spore s6/mL spore suspensions of A. flavus control, ΔAfngg1 strain and ΔAfngg1-Com strain and cultured at 28 °C in the dark for 6 days, with water replenished each day. Sterile water was added to collect the spore suspension and the number of conidia was calculated using a hemocytometer according to a previous method [A peanut and corn infection experiment was performed as described previously . Peanut s method . Finallyp-value < 0.05 criteria were met. Genome Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out using FungiFun (https://sbi.hki-jena.de/FungiFun/FungiFun.cgi) (accessed on 15 August 2022) and the KEGG Automatic Annotation Sever (http://www.kegg.jp/ or http://www.genome.jp/kegg/) (accessed on 15 August 2022).Total RNA was extracted using Trizol reagent  following the manufacturer’s instructions. RNA quality and integrity analyses, cDNA library construction, and RNA-Seq were performed by Guangzhou Gene Denovo Biotechnology . The Pearson correlation coefficient was used to analyse the accuracy and reliability of the three biological duplicate samples. DESeq was used to analyse differences in FPKM value, and differences were considered statistically when log2(fold change) >1 and


Orthoavulavirus that has caused multiple outbreaks among poultry in Egypt since 2011. This study aimed to observe the prevalence and genetic diversity of NDV prevailing in domestic and wild birds in Egyptian governorates. A total of 37 oropharyngeal swabs from wild birds and 101 swabs from domestic bird flocks including chickens, ducks, turkeys, and pelicans, were collected from different geographic regions within 13 governorates during 2019–2020. Virus isolation and propagation via embryonated eggs revealed 91 swab samples produced allantoic fluid containing haemagglutination activity, suggestive of virus presence. The use of RT-PCR targeted to the F gene successfully detected NDV in 85 samples. The geographical prevalence of NDV was isolated in 12 governorates in domestic birds, migratory, and non-migratory wild birds. Following whole genome sequencing, we assembled six NDV genome sequences (70–99% of genome coverage), including five full F gene sequences. All NDV strains carried high virulence, with phylogenetic analysis revealing that the strains belonged to class II within genotype VII.1.1. The genetically similar yet geographically distinct virulent NDV isolates in poultry and a wild bird may allude to an external role contributing to the dissemination of NDV in poultry populations across Egypt. One such contribution may be the migratory behaviour of wild birds; however further investigation must be implemented to support the findings of this study. Additionally, continued genomic surveillance in both wild birds and poultry would be necessary for monitoring NDV dissemination and genetic diversification across Egypt, with the aim of controlling the disease and protecting poultry production.Newcastle Disease Virus (NDV) genotype VII is a highly pathogenic  Paramyxoviridae, order Mononegavirales [Poultry in Egypt has become the substantial source of animal protein. Such a huge industry is challenged by several devastating pathogens. Newcastle Disease (ND) is one of the endemic diseases that still subtract from the outcome of poultry through continuous spread among poultry flocks, even within vaccinated populations. Avian Orthoavulavirus 1 (AOaV-1), also known as Newcastle Disease Virus (NDV), is an enveloped negative-sense, single-stranded RNA virus belonging to the family avirales ,3. The pavirales ; whereasavirales ,3,5.ND was first identified in Egypt in 1948 , with geMore than 250 domestic and wild bird species have been shown to be susceptible to NDV infection with varying clinical forms ,14,15,16The distinctive intermixing of migratory, free-living, and domesticated birds in Egypt might facilitate the direct transmission to commercial flocks and backyard populations, besides the evolution power of APMV-1 mutation . Egypt bThe frequency of virulent strains reported in wild birds on other continents is also increasing ,26,27, wThe available research investigating the dissemination and diversity of NDV across Egypt is limited, yet necessary for strategic planning for ND control. In this present study, we investigated the prevalence of NDV in domestic, migratory, and non-migratory birds, evaluating the genetic diversity and present genotypes within geographically distant governates in Egypt.The primary aim of this study was to monitor the genotypic diversity of NDV prevailing in domesticated and wild birds (migratory and non-migratory) in Egypt. The active surveillance of wild birds is difficult due to practical, logistical, and financial constraints; thus, we defined clear strategies to obtain samples that would provide us with robust sources of targeted NDV prevalence. Therefore, samples were mainly collected from domestic birds (semi-intensive housing system) that could potentially serve as “sentinels”, and from wild birds that could serve as a reservoir for virus persistence and transmission to poultry.The study was performed from September 2019 to December 2020 across different governorates (n = 13) within Egypt, including Dakahlia, Sharkia, Cairo, Suez, Sohag, Asyut, Port-Saied, North Sinai, South Sinai, Alexandria, Ismailia, Damietta, and Gharbia. Oropharyngeal swabs were collected from 101 flocks of domestic birds and 37 from migratory and non-migratory wild birds .Oropharyngeal swabs collected from the 101 flocks of domestic birds (pool of 3 swabs/flock) included chickens (n = 60), ducks (n = 38), pelicans (n = 2), and turkey (n = 1), of different ages and breeds . At the A total of 37 apparently healthy wild birds, including 14 different species, were captured randomly via traps, or collected from live-bird-markets (LBMs) in different governorates including North Sinai, Dakahlia, Port-Said, Ismailia, and Sharkia, Egypt . The trav/v) washed chicken red blood cells (RBCs). Allantoic fluids with positive HA activity were subjected to RT-PCR for NDV detection and sequencing.The oropharyngeal swab samples were centrifuged at 3000 rpm for 10 min, and the supernatants were filtered using 0.22 µm sterile filter. After aseptic examination, 200 µL of filtrate was inoculated to 10 day-old specific pathogen-free (SPF) embryonated chicken eggs (ECEs) via the allantoic cavity using a standard egg inoculation procedure . Three fTM, Loughborough, UK, catalogue no. 4268814) following the manufacturer’s instructions.Viral RNA was extracted either directly from oropharyngeal swabs or HA positive allantoic fluid using the QIAamp MinElute Virus Spin kit  following the manufacturer’s guidelines. As positive and negative control samples, the NDV vaccine strain (La Sota) and allantoic fluid from non-infected embryos were used, respectively. The extracted RNAs were reverse transcribed to cDNA using random primers and the assay was processed with the High-Capacity cDNA Reverse Transcription Kit . Cycling conditions were performed as a single cycle of initial denaturation at 95 °C for 3 min, followed by 30 cycles of 94 °C for 30 s (denaturation), 60 °C for 30 s , and 72 °C for 45 s (extension), then 72 °C for 7 min of final extension step. After amplification, the PCR products were resolved on a 1% agarose gel and stained with ethidium bromide; positive amplification products yielded a band size of approximately 306 bp. Additionally, the positive HA allantoic fluids were screened for the presence of influenza A virus using the primers targeting the conserved region of influenza’s M gene [The PCR amplification was performed using primers targeting the fusion (F) gene of NDV (forward: 5′-CACAGCAGGTCGGTGTAGAA-3′ and reverse: 5′-TCTCCAAATAGGTGGCACGC-3′) and conducted using 2X Dreams M gene .Extracted RNA was used in SISPA reaction as described previously . BrieflyA Nextera XT DNA kit  was used following manufacturer’s instructions to generate multiplexed paired-end sequencing libraries from 1 ng of dsDNA, using methods as previously described . Librarihttps://github.com/FelixKrueger/TrimGalore, accessed on 5 February 2019) [https://www.geneious.com, accessed on 5 February 2019) were used to reference genomes [The raw sequencing reads were analysed as described previously ,34. Briery 2019) . De novory 2019) ,37. Refery 2019) . Consens genomes .Complete coding sequences of F gene (n = 5) were used for comparative genetic analyses. To determine the genotypes of NDV viruses, we used previously published NDV reference strains  and the −1 to 10−9) were prepared from fresh infective allantoic fluid using a sterile phosphate-buffered saline. 0.1 mL from each dilution was inoculated through the allantoic sac route of five SPF ECEs at 9–10 days old. The inoculated eggs were incubated at 37 °C and examined daily for 5–7 days, recording rate of mortality. The embryonic MDT was determined as described by Alexander and Senne [The pathogenicity of the six sequenced NDV strains were assessed using mean death time (MDT) and intra cerebral pathogenicity index (ICPI). For the calculation of MDT, 10-fold serial dilutions  were intracerebrally injected with a volume of 50 µL of a 10-fold dilution, prepared from freshly allantoic fluid of each NDV strain. The inoculated chicks were monitored daily for 8 days post-inoculation. The observation welfare scoring the chicks’ observation and the value of ICPI was determined according to OIE .At the time of sampling, both migratory and non-migratory wild birds were apparently healthy with no clinical disease signs. However, the clinical disease signs were observed in the domestic birds. In chickens, ruffled feathers, greenish diarrhoea, and respiratory distress  were the predominant signs. Cyanosis of the head, comb, and wattles, as well as nervous distress, was also observed in some chickens; while in ducks, the predominant clinical signs were nervous distress and greenish diarrhoea. Furthermore, respiratory distress and diarrhoea were apparent in the turkey flock. The post-mortem examination of euthanized birds showed septicaemia and congestion in the internal organs and enteritis, with greenish intestinal contents in all examined birds. Haemorrhages were also observed in the caecal tonsils, the mucosa, and the glands, of the proventriculus of some chickens.The inoculation of SPF-ECEs with swab samples showed that some embryos died within 96 h. Among the infected embryos, 80.3% showed diffuse haemorrhages and congestion suggesting possible virus presence, either NDV and/or AIV. The tested harvested allantoic fluids (n = 138) revealed positive HA activity in 65.9% of samples (91/138). The positive HA samples were further confirmed by RT-PCR; NDV was detected in 93.4% (85/91) of the positive HA samples, which corresponded to 61.6% (85/138) of the total collected samples; 42% (58/138) were from domestic poultry flocks and 19.6% (27/138) were from wild birds. Finally, the total positive NDV samples of each population were 57.4% (58/101) and 72.9% (27/37) for domestic poultry and wild birds, respectively. From the 85 samples positive for NDV, 83.5% (71/85) were associated with a single infection with NDV, of which 71.8% (51/71) of these samples were from domestic poultry and 28.2% (20/71) wild birds, respectively. These corresponded to 51.4% (71/138) of total combined samples, 50.5% (51/101) of domestic poultry samples, and 54.1% (20/37) of wild bird samples, respectively. Further analysis showed the presence of AIV in 14.5% (20/138) of samples, either as a combined infection of both AIV and NDV 70% (14/20) from both domestic and wild bird samples (7 positive per each) or AIV alone in 30% (6/20) samples collected from domestic birds .Larus canus, Numenius minutus, Streptopelia turtur, Gallinula chloropus, Ardenna pacifica, Porphyrio madagascariensis, and Anthus rubescens reached 100%, followed by Corvus cornix with an incidence of 75% (6/8) (95% CI 34.91–96.61%) (The isolation of NDV in the different governorates (n = 13) of Egypt and the case number analysed (n/n) are shown in –96.61%) . Six isoOnly five full F gene sequences were included in phylogenetic analysis . Among tAll isolates belonged to class II and clustered with NDV isolates within genotype VII.1.1 . The phyThe comparative alignment of the complete F protein amino acid sequence of the isolated strains against each other revealed four frequent residue substitutions  at positions, 30, 90, 258, and 480, respectively, resulting in independent sequences .The global distribution of NDV and epidemiological analysis portrays genotype VII as the predominant genotype and is responsible for the fourth major NDV panzootic worldwide, with often fatal consequences following the infection of susceptible birds ,43. The The incidences of NDV among domestic birds were 65% and 47.4% in chicken and duck flocks, respectively; similar levels of NDV prevalence in domestic poultry (52.4%) were found in a cohort epidemiological study by Abozaid et al. . The obsPrevious studies suggest that wild birds may act not just as a reservoir of low virulence strains but may also play a critical role in the epidemiology of different variants NDV strains persisting in Africa, including virulent Newcastle Disease Virus (VNDV) strains responsible for poultry outbreaks ,48,49,50As NDV is an acute contagious disease affecting birds of all ages , the cliPhylogenetic analysis revealed that all sequences of the six examined strains of domestic poultry: NDV/Chicken/Egypt/NOR/ZU-NM76/2019, NDV/Chicken/Egypt/ALEX/ZU- NM93/2019, NDV/Chicken/Egypt/ALEX/ZU-NM97/2019, and NDV/Chicken Egypt/ALEX/ZU-NM99/2019, those from ducks: NDV/Duck/Egypt/DAK/ZU-NM09/2019 and NDV/Duck/Egypt/DAK/ZU-NM54/2019, and one from migratory wild birds: “NDV/Black-crowned_night_heron/Egypt/POR/ZU-NM85/2019” were velogenic and clustered together in class II within sub-genotype VII.1.1, with 98.013–100% nucleotide identity, complementary to findings from related studies ,63,64,65Few amino acid (aa) substitutions  were found in the entire length of F protein in APMV-1 isolates from chicken, duck, and wild birds, as compared with each other. Such substitutions have been proposed to influence the antigenicity as well as a change in the fusion protein confirmation ,74,75,76The results of this study observed a predominant isolation of NDV-VII.1.1 with the velogenic characteristic, from domestic and wild birds, with a high degree of genetic similarity across distinct governates in Egypt. As such, the data may suggest an interlinking role contributing to the maintenance and transmission cycle of NDV between and within domesticated poultry and wild birds situated in Egypt. Previous literature highlights the prevalence of NDV in wild birds driving dissemination across the governates and coupled with this study’s data, a stronger epidemiological picture can be formed, complementing the role of wild birds aiding such maintenance but also suggesting their role in recurring outbreaks in poultry ,78,79. A


Dear Editor,C. annuum L.) is an important vegetable crop worldwide [Pepper  with a late-maturing sweet pepper (16 L15) and then selfed the F1 generation for an additional six rounds (To construct a pepper recombinant inbred line (RIL) population, we generated an Fx rounds . We cultx rounds .qFC6.1) was located on LG 6 and contained 51 candidate genes, including capsanthin-capsorubin synthase (CCS) (Capana06g000615) [qFL3.1 on LG 3 and qFL7.1 on LG 7), four QTLs for FWD on LGs 2, 3, 6, and 11, and five QTLs for FWT .By performing RNA sequencing, RNA-seq analysis, and SNP marker development on fruits from all 148 RIL progenies, we obtained high-quality bin markers consisting of 78,605 SNPs and divided them into 12 linkage groups (LGs) corresponding to 12 chromosomes . These Scis-eQTLs and others as trans-eQTLs [cis-eQTLs, and those of 4082 genes were regulated by trans-eQTLs. A total of 574 genes had multiple trans-eQTLs, resulting in the detection of 4710 trans eQTLs, accounting for 63.6% of all eQTLs. Nine trans-eQTL hotspots were detected on the 12 LGs using the qtlhot package (https://CRAN.R-project.org/package=qtlhot) (LOD 3.43 and significance level of 0.01–0.1). They were located on LGs 1, 2, 3, 4, 6, 7, 9, 11, and 12, with LG6–1 containing a total of 645 genes.To identify the genes that regulate these traits, we carried out transcriptome-wide association studies (TWAS) on all RILs to detect correlations between gene expression and phenotype using the limix module . Among tns-eQTLs . The expcis pQTL sites and 73.2% of those were significantly associated with trans-acting sites. Seventeen protein hotspots coincided with eQTLs. The hotspot locus LG6–1 contained 455 proteins, suggesting that the LG6–1 region has complex regulatory relationships at both transcriptional and translational levels during pepper fruit development.We performed label-free proteome sequencing of all fruits in the RIL population and detected 7923 peptides, 7047 of which could be quantified. Based on proteome-wide association analysis (PWAS) of these peptides, 864 proteins were significantly associated with FC, and 855, 304, and 811 proteins were significantly associated with FWD, FL, and FWT, respectively . A similTo investigate the regulatory mechanisms of pepper fruit traits using multi-omics data, we performed a joint multiple histology analysis. We first identified the overlap of genes significantly associated with each trait in TWAS and PWAS and found that 37 genes were significantly associated with all four traits in the PWAS analysis , Fig.S3,CCS. Combined with the results of PWAS and TWAS, this approach enabled us to identify the upstream carotenoid biosynthesis genes 1-Deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) and phytoene desaturase (PDS) in the RIL population; these genes may also play an important role in the regulation of pepper fruit color.In addition to PWAS and TWAS, we also used metabolic pathway analysis to successfully localize the pepper fruit color gene In the present study, 12 significant QTL loci for pepper FC, FWD, FL, and FWT, and 80 significant trait-associated genes were identified through QTL mapping in an RIL population and association analysis of traits using multiple transcriptional and translational data. We used a relatively small population of RIL lines to effectively associate QTLs and important genes by TWAS and PWAS analysis. Integrated omics analyses can help us to understand the regulatory mechanism of pepper fruit development and to accelerate the mining and cloning of candidate genes. The QTLs detected in this study will be useful for selecting appropriate RILs for further marker-assisted selection when breeding hybrid peppers of diverse market types.Web_Material_uhac015Click here for additional data file.


Iron metabolism is considered to play the principal role in sepsis, but the key iron metabolism-related genetic signatures are unclear. In this study, we analyzed and identified the genetic signatures related to the iron-metabolism in sepsis by using a bioinformatics analysis of four transcriptomic datasets from the GEO database. A total of 21 differentially expressed iron metabolism-related signatures were identified including 9 transporters, 8 enzymes, and 4 regulatory factors. Among them, lipocalin 2 was found to have the highest diagnostic value as its expression showed significant differences in all the comparisons including sepsis vs healthy controls, sepsis vs non-sepsis diseases, and mild forms vs severe forms of sepsis. Besides, the cytochrome P450 gene CYP1B1 also showed diagnostic values for sepsis from the non-sepsis diseases. The CYP4V2, LTF, and GCLM showed diagnostic values for distinguishing the severe forms from mild forms of sepsis. Our analysis identified 21 sepsis-associated iron metabolism-related genetic signatures, which may represent diagnostic and therapeutic biomarkers of sepsis, and will improve our understanding of the molecular mechanism underlying the occurrence of sepsis. As the Iron is a crucial trace element that is essential for fundamental processes in both humans and bacteria. In sepsis, iron metabolism is altered, including increased iron transport and uptake into cells and decreased iron export. This intracellular sequestration of iron limits its availability to circulating pathogens, which serves as a conservative strategy against the pathogens .During iron metabolic biological process, iron participates in oxidation–reduction reactions, and catalyzes the reactive oxygen generation, therefore the increase in labile iron may cause oxidative injury and cell death, such as ferroptosis. Ferroptosis is a novel form of cell death characterized by the iron-dependent accumulation of lipid peroxides, the most prominent feature is plasma membrane damage caused by the generation of lipid peroxides . MoreoveIn the present study, we identified the genetic signatures related to the iron metabolism in sepsis by using a bioinformatics analysis of four transcriptomic datasets downloaded from the GEO database. A total of 21 differentially expressed iron metabolism-related signatures were identified, including 9 transporters, 8 enzymes, and 4 regulatory factors, among which lipocalin 2 (LCN2) showed consistent differences in all the comparisons including sepsis vs healthy groups, sepsis vs non-sepsis groups, and mild vs severe forms of sepsis. Our results identified the sepsis associated iron metabolism-related genetic signatures, which may represent diagnostic and therapeutic biomarkers of sepsis, and the knowledge of these genes will improve our understanding of the molecular mechanism underlying the occurrence of sepsis.22.1Iron metabolism-related genes were retrieved from 16 gene sets downloaded from the Molecular Signatures Database (MSigDB), including the GO_IRON_ION_BINDING, GO_2_IRON_2_SULFUR_CLUSTER_BINDING, GO_4_IRON_4_SULFUR_CLUSTER_BINDING, GO_IRON_ION_IMPORT, GO_IRON_ION_TRANSPORT, GO_IRON_COORDINATION_ENTITY_TRANSPORT, GO_RESPONSE_TO_IRON_ION, MODULE_540, GO_IRON_ION_HOMEOSTASIS, GO_CELLULAR_IRON_ION_HOMEOSTASIS, GO_HEME_BIOSYNTHETIC_PROCESS, HEME_BIOSYNTHETIC_PROCESS, GO_HEME_METABOLIC_PROCESS, HEME_METABOLIC_PROCESS, HALLMARK_HEME_METABOLISM, and REACTOME_IRON_UPTAKE_AND_TRANSPORT. A total of 514 genes were extracted from the iron metabolism-related gene sets after removing overlapping genes (Table S1).2.2Patient datasets were selected according to the following criteria: age ≥18 years, presence of control group , peripheral blood as samples for gene expression profiling, submission date within 5 years (2017–2022). Finally, four gene expression datasets were selected and downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) , includi2.3p-values of <0.05 and an absolute fold change >1.5 [Differentially expressed genes (DEGs) were calculated for each of the four datasets, between sepsis and control  samples using Limma package with a threshold of adjusted nge >1.5 . DEGs weHierarchical clustering was applied to explore the differences in expression patterns between samples of sepsis patients or healthy controls, and also between the differentially expressed iron metabolism-related genes, in the four datasets, respectively, using the heatmap package in R. The average linkage method was used to conduct the hierarchical clustering and Pearson correlation method was used to set the clustering distance.2.4Functional enrichment analysis of differentially expressed iron metabolism-related genes was based on Gene Ontology (GO) database from molecular function, cellular component, and biological process using R package ClusterProfiler . The PPI2.5p value < 0.05 was considered statistically significant.All statistical analyses in this study were conducted using R software (version 4.2.1). The receiver operating characteristic (ROC) analysis was performed and the area under curve (AUC) was calculated to evaluate the diagnostic performance of the genetic signatures. All the values of AUC with 95% confidence interval for the ROC analysis are listed in Tables S2 and S3. A two-tailed 33.1To identify the sepsis-associated genes, we first analyzed the DEGs in whole blood samples between sepsis and non-sepsis, and also between the severe forms and mild forms of sepsis. In GSE69063, we totally identified 5,294 DEGs among severe sepsis, mild sepsis, and healthy controls, by using 68 samples collected from 30 patients with mild sepsis, 27 patients with severe sepsis, and 11 healthy controls . In GSE154198, 4,040 DEGs were identified among sepsis, sepsis shock, and healthy controls, by using 79 samples collected from 20 patients with sepsis, 19 patients with sepsis shock, and 40 healthy subjects . In GSE134347, 2,166 DEGs were identified between sepsis and noninfectious controls, or between sepsis and healthy controls, by using 298 samples collected from 256 patients with sepsis, 59 patients with noninfectious disease, and 83 healthy subjects . In GSE185263, we totally identified 7,567 DEGs between sepsis and healthy controls, by using 392 samples collected from 345 patients with sepsis and 47 healthy subjects .Next we extracted the iron metabolism-related genes from the DEGs in the four GEO databases, and identified a total of 21 sepsis related iron metabolism-related genes which were differentially expressed simultaneously in all the four databases . Among tA fold-change represented color map was further built based on all the samples in the four GEO datasets, respectively, by using the 21 sepsis related iron metabolism-related genes . The exp3.2Functional enrichment analyses were performed to explore the functions of the 21 DEGs. These genes were significantly enriched in biological process including cellular modified amino acid metabolic process , mitochondrial depolarization , and molecular functions of iron ion binding , and mainly enriched in cellular component of mitochondrial or organelle membrane .–5)  .3.3p < 0.05) in all the four datasets. The performance of the ROC in terms of sepsis vs healthy controls was analyzed, and all the AUC are listed in Table S2. The ROC curve of the top eight iron metabolism-related genes including SLC22A4, TSPO, NFE2, FLVCR2, LCN2, BCL2, FTO, and CYP4V2 are shown in To explore the diagnostic values of these genetic signatures in distinguishing sepsis from healthy controls, the expression levels of the 21 iron metabolism-related genes were compared between sepsis and healthy controls for the four GEO datasets, respectively . As expep < 0.05). Then, we compared the expressions of the 21 genes between sepsis and noninfectious disease in GSE134347 datasets (p < 0.05). These results from the two datasets indicated that LCN2 and CYP1B1 expressions simultaneously distinguished sepsis from healthy controls, and also from uncomplicated infectious and noninfectious diseases. Further ROC analysis suggested the AUC of LCN2 and CYP1B1 in diagnosis between sepsis and uncomplicated infectious or noninfectious diseases were both >0.66 . Additionally, when compared to sepsis shock, we found TPSO, GCLM, CYP1B1, LCN2, and LTF were up-regulated and the FTO and CYP4V2 were down-regulated in the sepsis (p < 0.05). These results from the two datasets indicated that GCLM, LCN2, LTF, and CYP4V2 expressions could consistently distinguish severe forms of sepsis from mild forms of sepsis. Further ROC analysis suggested that the AUC of GCLM, LCN2, LTF, and CYP4V2 in diagnosis between severe forms and mild forms of sepsis were all >0.65  is an enzyme, which oxidizes mainly omega-6 and omega-3 fatty acids, to generate a number of bioactive lipid metabolites. ALOX15 has been reported to play an important role in oxidative and inflammatory responses, as its metabolite 12(S)-HETE is a potent, pro-inflammatory chemoattractant for neutrophils and leukocytes . BCL2 isFerroptosis has been widely reported to be involved in sepsis occurrence and development . CarboniInterestingly, two transcriptional factors were identified as up-regulated genes in sepsis from our analysis: NFE2 and ELL2. NFE2 plays a pivotal role in the transcription control of erythroid-specific genes, including β-globin, and is necessary for the transcriptional activation of heme biosynthetic enzymes PBGD3 and FECH . NFE2 isIn addition to the above genetic signatures, we also identified several membrane transporters, which were all up-regulated in sepsis, including SLC22A4, TPSO, and ATP6V1C1. Among them, SLC22A4 (or OCTN1) belongs to a small sub-family of organic cation transporters. It is expressed in several districts including peritoneum, and involved in control of inflammatory processes that are critical in this district . TSPO isFrom our analysis, there are also several other iron metabolism-related genes up-regulated in sepsis. CLIC2, as the least investigated CLIC family member, is expressed in normal blood vessel endothelial cells, while involving in the maintenance of the vascular barrier functions . And CISIn conclusion, we identified the genetic signatures related to the iron-metabolism in sepsis by using a bioinformatics analysis of the blood transcriptomic datasets. A total of 21 iron metabolism-related signatures were identified including 9 transporters, 8 enzymes, and 4 regulatory factors, among which LCN2 showed consistent differences between sepsis and healthy groups, sepsis and non-sepsis groups, and mild and severe forms of sepsis. These iron metabolism-related genetic signatures may represent diagnostic and therapeutic biomarkers of sepsis, and the knowledge of these genes will improve our understanding of the molecular mechanism underlying the occurrence of sepsis.


MOGAT1 and CPT1A. Furthermore, DHQ had a tendency to decrease hepatic cholesterol contents by reducing the mRNA levels of cholesterol synthesis genes such as FDPS and HMGCS1. 16S rRNA sequencing analysis indicated that DHQ significantly decreased the richness of Lactococcus, Lachnoclostridium, and Eubacterium_xylanophilum_group. Correlation analysis further demonstrated that these bacteria, Lactococcus and Eubacterium_xylanophilum_group in particular, had significantly positive correlation with lipid and cholesterol synthesis genes, and negative correlation with fatty acid oxidation genes. In conclusion, DHQ could improve hepatic lipid dysmetabolism potentially by improved gut microbial community, which may be used as an intervention strategy in hepatic metabolism diseases.Dihydroquercetin (DHQ) is a natural flavonoid with multiple bioactivities, including hepatoprotective effects. This study aimed to investigate whether DHQ improved lipid dysmetabolism in the body, especially in the liver, and whether there is a relationship between hepatic metabolism and altered gut flora in high-fat diet (HFD)-induced mice. HFD-induced mice were given 50 mg/kg body weight DHQ intragastrically for 10 weeks. The data showed that DHQ reduced body weight, the weight of the liver and white adipose tissue as well as serum leptin, LPS, triglyceride and cholesterol levels. RNA-seq results indicated that DHQ down-regulated lipogenesis-related genes and up-regulated fatty acid oxidation-related genes, including  Hepatic metabolic disorder is considered as a risk factor for metabolism problems, including hyperglycemia, hyperlipidemia, obesity, and fatty liver diseases, which is increasingly common worldwide . If not Firmicutes levels and decreased Bacteroidetes levels in dextran sodium sulfate (DSS)-caused colitis mice [Firmicutes/Bacteroidetes ratio and changed the richness of some genus such as Lactobacillus, Dubosiella, and Bacteroidetes in DSS-induced mice [DHQ , a kind of secondary metabolite, was generally distributed in Douglas fir, silybum marianum, and onions ,7. It hatis mice . Our preced mice . Besidesced mice . In lighThus, in this study, we aim to investigate the regulatory effects of DHQ on hepatic lipid metabolic genes through transcriptomics technology in HFD-induced mice. Moreover, using 16S rRNA gene sequencing method, this study sought to investigate how DHQ supplementation affected gut microbiota composition, and further revealed the relationship between lipid metabolic-related indexes and gut microbiota through correlation analysis. This study would offer theoretical evidence to develop strategic approach to prevent and treat hepatic metabolism-associated disorders, as well as provide new insights for the application of DHQ as a green additive in animal husbandry.DHQ was acquired from Shanghai Yuanye Bio-Technology Co., Ltd.  with the purity of 99.50%. The standard chow diet  and the HFD  were provided from Beijing Keao Xieli Feed Co., Ltd. . Energy intake was calculated according to the following formula:3PO4 in H2O) and solvent B (acetonitrile). The separation was preformed on a Hyper 0DS2 C18 column . Moreover, column temperature was 25 °C and detection was conducted at 286 nm. After detection, the purity of DHQ was 99.50% and showed in Through high performance liquid chromatograph (HPLC) detection, the purity of DHQ was defined using a HPLC system . Elution solvents were solvent A  mice were acquired from Peking University Health Science Center . They were raised in animal house with free access to diet and water under a controlled environment at 21 ± 2 °C and a 12/12 h light/dark cycle. After a week of adaptation, mice were randomly allocated to 3 groups (n = 8/group). Mice in HFD+DHQ group were fed a HFD with gavage of 50 mg/kg body weight DHQ (dissolved in corn oil). Mice in CON and HFD groups were received with SD and HFD separately, with the same volume of corn oil intragastrically. The body weight and feed intake of them were measured every week. After 10 weeks, blood materials were obtained via orbital blooding and then the mice were killed through cervical dislocation. Liver weight and white adipose tissues weight  was weighed and recorded. Liver tissue was quickly taken out and frozen in liquid nitrogen for future analysis. For histopathology analysis, part of liver was cut and fixed in 4% paraformaldehyde. Feces were obtained and quickly stored in liquid nitrogen for 16S rRNA sequencing.Part of the liver was fixed with 4% paraformaldehyde, then dehydrated and embedded in paraffin. A section was cut and placed on a slide. After deparaffinization and hydration, the sections were stained with H&E for microscopy. Images were obtained with inverted fluorescence microscope (Leica DMI3000B) .After the centrifugation of blood at 3000 rpm and 4 °C for 10 min, the serum samples were collected for future biochemical analysis. The contents of total triglyceride (TG) and total cholesterol (TC) in serum and hepatic tissue, as well as serum low-density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C) were identified through automatic biochemical analyzer . The levels of leptin, insulin, and LPS in serum were identified by ELISA assay according to the manufacturers’ manuals . Moreover, the homeostasis model assessment of insulin resistance (HOMA-IR) was employed to estimate insulin resistance based on the following formula:® reagent  and genomic DNA was removed with DNase I . The RNA quality and purity were determined by 2100 Bioanalyser  and Nanodrop2000 . Then, sequencing library was constructed for further analysis with high-quality RNA samples . Messenger RNA is separated from total RNA using oligo (dT) beads and then segmented using fragmentation buffer. Double-stranded cDNA was synthesized by reverse transcriptase and subjected to terminal-repair, phosphorylation, and “A” base addition. After PCR for 15 cycles and quantified by TBS380, sequencing was performed with the Illumina NovaSeq 6000 sequencer (2 × 150 bp read length). CASAVA base calling was employed to transform sequencing images signal to sequencing data pattern. By SeqPrep (https://github.com/jstjohn/SeqPrep (accessed on 25 December 2021)), and Sickle (https://github.com/najoshi/sickle (accessed on 25 December 2021)) programs, the clean data reads were remained following quality assessment and low quality filtering of raw reads. Then, mapped data was acquired after aligning the clean data to the mouse genome with HISAT2 (http://ccb.jhu.edu/software/hisat2/index.shtml (accessed on 25 December 2021)) analysis. Following transcripts assembly using StringTie (http://ccb.jhu.edu/software/stringtie/ (accessed on 25 December 2021)), RSEM ) software was used for quantification based on transcripts per million reads (TPM). Differential expression genes (DEGs) between groups were determined with DESeq2. Genes were defined to be significantly differentially expressed with p-adjust < 0.05 and fold change (FC) ≥ 2 (for up-regulation) or ≤0.5 (for down-regulation).Liver tissues from the CON, HFD, and HFD+DHQ groups were stored in liquid nitrogen and entrusted to Majorbio Bio-Pharm Technology Co., Ltd.  for transcriptomics analysis. Following the manufacturer’s instructions, total RNA was extracted with Trizol−ΔΔCt method. The RT-PCR was performed on an Applied Biosystems 7500 RT-PCR System . Specific primers were synthesized in Sangon Biotech Co., Ltd.  and exhibited in Biochemical reagents, including Trizol  reagent, chloroform, isopropanol, and 75% ethanol solution, were used to isolate total RNA of liver tissues. Then, RNA concentrations were detected with the NanoDrop 2000 . After removing the possible DNA contaminations, the reverse transcription was conducted using PrimeScript RT reagent kits . Next, qRT-PCR was conducted in accordance with the manual of the manufacturer with KAPA SYBR FAST qPCR Master Mix kit. Briefly, reactions were carried out in triplicate for each sample in a 10 μL volume consisting of 5 μL KAPA SYBR FAST qPCR Master Mix Universal, 0.4 μL PCR forward primer, 0.4 μL PCR reverse primer, 0.2 μL ROX low, 1 μL cDNA, and 3 μL PCR-grade water following the instruction of the manufacturer . β-actin was designed as internal control and each result of target genes was normalized to β-actin and relatively quantified with 2® Spin Kit for Soil . Then, the quality of total genome DNA was analyzed with 1% agarose gel. Its purity and concentration were identified by NanoDrop 2000 UV-vis spectrophotometer . PCR amplification of hypervariable region V3-V4 in the bacteria 16S ribosomal RNA gene was performed using specific primers  with an ABI GeneAmp® 9700 PCR thermocycler . The PCR product was checked with 2% agarose gel, followed with purification, quantification, and homogenization with AxyPrep DNA Gel Extraction Kit  and Quantus™ Fluorometer  based on the manufacturer’s requirements. After that, purified amplicons were sequenced with an Illumina MiSeq PE300 platform  at Majorbio Bio-Pharm Technology Co., Ltd.  based on the standard protocols. The sequences were quality-filtered and merged, then clustered to operational taxonomic units (OTUs) with 97% similarity using the UPARSE software ). Alpha diversity, including Simpson, Shannon, and Chao indices, was conducted by the Mothur version 1.30.2. Beta diversity was determined through calculating the weighted Unifrac distance and visualized by principal co-ordinates analysis (PCoA).Microbial community total genome DNA of feces was extracted with the FastDNAPearson’s correlation analysis was carried out between gut microbiota and hepatic lipid metabolic parameters.p < 0.05 was considered to be significant statistically.Statistical analyses were processed through one-way analysis of variance (ANOVA) with Duncan test . The data were expressed as the mean ± SEM. p < 0.05) (p < 0.05) (p < 0.05). Meanwhile, HFD increased the ratios of the weight of inguinal, epididymal, and perirenal adipose tissue to the body weight (p < 0.05). However, supplementation with DHQ significantly decreased inguinal and perirenal fat indices, while failed to affect epididymal fat indices  B,C. Duri < 0.05) D,E. Furt < 0.05) F. Compar indices F,H.p < 0.05), and tend to reduce insulin level and HOMA-IR, as shown in p > 0.05). Moreover, serum LPS levels were significantly increased in mice fed with a HFD than normal group, which could be reversed by DHQ (p < 0.05) (p < 0.05) (p < 0.05). There was no significant difference in LDL-C contents of serum among CON, HFD, and HFD+DHQ groups  D. Simult < 0.05) E,F. BesiQ groups G,H.p < 0.05), and had a tendency to decrease the TC level (p > 0.05).As a critical organ for body metabolism, the liver is susceptible to high fat or high energy diet. In this study, pathological observations showed that HFD resulted in the hepatic abnormal accumulation of lipid droplets, which was suppressed after DHQ treatment A. ConsisConsidering that DHQ intervention could attenuate hepatic lipid deposition caused by HFD, we next investigated the effect of DHQ on the mRNA levels of hepatic genes associated with lipid metabolism based on RNA sequencing methods. As shown in p-adjust < 0.05 and FC ≥ 2 (for up-regulation) or ≤−2 (for down-regulation) was conducted to define the number of DEGs. Volcano plots were generated to visualize the distribution of DEGs in the CON and HFD, the HFD and HFD+DHQ groups. There were 577 DEGs (240 being up-regulated and 337 being down-regulated) were determined in the HFD-fed mice than the CON mice. Meanwhile, 31 genes in total have been significantly differentially expressed with 20 being up-regulated and 11 being down-regulated in the HFD+DHQ group, compared to the HFD group  result demonstrated that the samples of the HFD group were significantly separated from the CON group, while the gene clustering from the HFD+DHQ group was closer to the CON group A. A striFD group B,D.To characterize the functional results of DEGs provoked by the HFD and DHQ, KEGG and GO analysis was performed. By matching altered genes to the KEGG database, DEGs were functionally annotated in metabolism, human diseases, and organismal systems. As shown in 1-acylglycerol-3-phosphate O-acyltransferase 1 (AGPAT1), diacylglycerol O-acyltransferase 2 (DGAT2), monoacylglycerol O-acyltransferase 1 (MOGAT1), Mid1 interacting protein 1 (MID1IP1), acyl-CoA thioesterase 11 (ACOT11), fatty acid synthase (FASN), sterol regulatory element binding transcription factor 1 (SREBF1), and MLX interacting protein-like (MLXIPL) involved in lipogenesis, which was reversed by DHQ supplementation. Meanwhile, the expression of carnitine palmitoyltransferase 1a (CPT1A), enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase (EHHADH), long-chain acyl-Coenzyme A dehydrogenase (ACADL), CYP4A10, CYP4A14, and CYP4A31 related to fatty acid oxidation were decreased in mice fed with a HFD than those of normal diet, which also could be reversed with DHQ. Moreover, HFD and DHQ altered the mRNA expression of genes associated with lipid transport, including CD36 molecule (CD36), solute carrier family 27, member 5 (SLC27A5), and microsomal triglyceride transfer protein (MTTP)  A.acetyl-CoA acetyltransferase 2 (ACAT2), farnesyl diphosphate synthetase (FDPS), 3-hydroxy-3-methylglutaryl-CoA synthase 1 (HMGCS1), 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), isopentenyl-diphosphate delta isomerase (IDI1), lanosterol synthase (LSS), methylsterol monooxygenase 1 (MSMO1), mevalonate diphosphate decarboxylase (MVD), NAD(P) dependent steroid dehydrogenase-like (NSDHL), squalene epoxidase (SQLE), acetoacetyl-CoA synthetase (AACS), and sterol-C5-desaturase (SC5D) involved in cholesterol synthesis, while ACAT2, FDPS, HMGCS1, MVD, NSDHL, AACS, and SC5D levels were down-regulated after DHQ administration to HFD-fed mice. Notably, DHQ also changed the genes related to cholesterol transport and cholesterol homeostasis such as peroxisome proliferator activated receptor gamma (PPARG), ATP binding cassette subfamily G member 1 (ABCG1), apolipoprotein A-IV (APOA4), CYP39A1, neutral cholesterol ester hydrolase 1 (NCEH1), and sterol O-acyltransferase 2 (SOAT2)  B. Besidephosphoenolpyruvate carboxykinase 1 (PCK1), lipin 2 (LPIN2), glycerophosphocholine phosphodiesterase 1 (GPCPD1), CYP4A32, abhydrolase domain containing 2 (ABHD2), sphingomyelin phosphodiesterase 3 (SMPD3), elongation of very long chain fatty acid elongase 2 (ELOVL2), Fibrinogen-like protein 1 (FGL1), and CPT1A. Relative to the CON group, several genes were markedly down-regulated in the HFD group, including PCK1, LPIN2, GPCPD1, CYP4A32, ABHD2, SMPD3, ELOVL2, FGL1, and CPT1A (p < 0.05). Meanwhile, it was found that DHQ significantly enhanced the expression of LPIN2, GPCPD1, CYP4A32, ELOVL2, and FGL1 for mice induced by HFD (p < 0.05)  A. In bri < 0.05) B,C. Diffp < 0.05), while displayed tenuous effect on the Shannon and Chao indexes than CON group. Moreover, DHQ had no significant impact on Simpson, Shannon, and Chao indexes in the HFD-fed mice. Then, β-diversity was evaluated via principal co-ordinates analysis (PCoA) based on Bray-Curtis distance. It was showed that the CON group showed an obvious separation in microbiota structure compared with the HFD and HFD+DHQ groups. Meanwhile, there is also a discrepancy in the make-up of gut bacteria between the HFD and HFD+DHQ groups, revealing that the gut micorbial community in mice fed with a HFD was influenced by DHQ , which can be reversed by DHQ, although not significantly (p > 0.05) . Noteworthy, the alterations were reversed after DHQ supplementation. In particular, the richness of Lactococcus, Lachnoclostridium, and Eubacterium_xylanophilum_group was significantly reduced by DHQ in HFD-caused mice  E. In addQ groups E. At thesed mice .Streptococcus was significantly positively associated with serum insulin, LPS, TC, and hepatic TG levels. The richness of Lactococcus and Enterorcoccus had positive relationship with body weight, serum leptin, insulin, LPS, TC, and hepatic TG levels. Moreover, the relative richness of unclassified_f_Lachnospiraceae and Eubacterium_xylanophilum_group showed positive correlation with the amounts of leptin, TC in serum, and TG in liver. Furthermore, the relative abundance of Lachnoclostridium correlated positively with body weight, serum leptin, LPS, TG, and hepatic TG, TC levels. Besides, it is clear that the relative abundance of Coriobacteriaceae_UCG-002 had negative correlation with serum LPS, TG and hepatic TG levels. Meanwhile, the correlation analysis between flora and key genes in the hepatic transcriptome data was performed. The results indicated that the relative abundance of Streptococcus and Eubacterium_xylanophilum_group was significantly positively related to MOGAT1, MID1IP1, ACAT2, FDPS, and MVD, but significantly negatively correlated with CPT1A expression. The richness of Lactococcus and Enterorcoccus showed positive correlation with the expression of DGAT2, MOGAT1, MID1IP1, MLXIPL, ACAT2, FDPS, HMGCS1, MVD, and NSDHL, but negative correlation with CPT1A and CYP4A10 expression. Furthermore, there was a positive relationship between the richness of unclassified_f_Lachnospiraceae and the expression of FDPS, HMGCS1, MVD and NSDHL in the liver. In addition, the proportion of Lachnoclostridium had positively correlation with MID1IP1, FDPS, HMGCS1, and MVD mRNA levels.The relevance of the altered gut microbiota and lipid metabolism-associated indicators were evaluated by Pearson’s correlation analysis and visualized through heatmap . As demoLipid metabolic disorder is emerging as an epidemic pathological process with promoting the incidence and progression of fatty liver diseases, seriously endangering people’s health . In the Lipid metabolism imbalance induced by HFD is often concomitant with the increase of body weight and fat storage ,17. A reLeptin, an adipocyte-secreted hormone, is required for maintaining energy balance through mediating processes involved in food intake and expenditure . InsulinWhen fed with long-term high fat or carbohydrate diets, lipids are generally deposited in hepatic tissue, resulting in metabolic liver dysfunction, and eventually developing into NAFLD or hepatic fibrosis . In the AGPAT1, DGAT2, MOGAT1, MID1IP1, ACOT11, FASN, SREBF1, and MLXIPL in the liver required from RNA-seq analysis. AGPAT1, DGAT2, and MOGAT1 are implicated in triglyceride synthesis, while MID1IP1, ACOT11, and FASN are associated with fatty acid synthesis [SREBF1 and MLXIPL played important effects in promoting the transcription of lipogenic genes, such as FASN [MOGAT1, MID1IP1, and ACOT11 mRNA levels in hepatic tissue were greatly lessened by DHQ in mice fed with a HFD . MOGAT1 is involved in converting monoacylglycerol to diacylglycerol, which was overexpressed in the livers of obese mice suffering from hepatic steatosis [MOGAT1 gene deficiency decreased weight gain and hepatic fat mass as well as improved glucose tolerance and insulin signaling in obese mice fed with a diet containing high energy [MOGAT1, MID1IP1, and ACOT11 expression caused by DHQ supplementation may be greatly responsible for the decrease of triglyceride content in hepatic tissue. Furthermore, various genes, including ACADL, CPT1A, EHHADH, CYP4A10, CYP4A14, and CYP4A31, were down-regulated in mice fed with a HFD, whereas DHQ supplementation inhibited these changes. CPT1A, EHHADH, and ACADL are implicated in β-oxidation of fatty acid, while CYP4A10, CYP4A14, and CYP4A31 were involved in ω-oxidation of fatty acid [CPT1A, EHHADH, ACADL, CYP4A10, CYP4A14, and CYP4A31 resulting from DHQ supplementation contributed to the enhancement of fatty acid oxidation, which could further explain the smaller hepatic TG accumulation in mice fed with a HFD. CD36 and SLC27A5 are fatty acid translocases capable of mediating fatty acid uptake into the liver [CD36 and SLC27A5 in the livers of HFD-fed mice, which promoted the decrease of fatty acid uptake in hepatic tissue. Altogether, these results suggested that DHQ reduced triglyceride level and alleviated lipid deposition in hepatic tissue potentially through regulating adipogenesis, fatty acid oxidation, and fatty acid transport-related genes.As a principal regulator of lipid metabolism, the liver is implicated in modulating lipid synthesis and utilization, fatty acid metabolism, and cholesterol homeostasis, etc. . Previouynthesis ,36,37. T as FASN . Howeverteatosis . It was h energy . MID1IP1h energy . ACOT11,h energy . Here, ttty acid ,44,45. Ohe liver . In the ACAT2, FDPS, HMGCS1, HMGCR, IDI1, LSS, MSMO1, MVD, MVK, NSDHL, SQLE, AACS, and SC5D, which were involved in de novo cholesterol synthesis [ACAT2, FDPS, HMGCS1, MVD, NSDHL, AACS, and SC5D was down-regulated, which promoted cholesterol decrease in mice fed with a HFD here. Moreover, genes associated with cholesterol transport such as PPARG were altered by HFD feeding, whereas these alterations were reverted following DHQ treatment. PPARG is known to be implicated in cholesterol efflux and helps maintain intracellular cholesterol homeostasis [PPARG, which partially maybe explain the reason for the decreased cholesterol level in the livers of HFD-fed mice. CYP39A1 was expressed in the hepatic endoplasmic reticulum and participated in bile acid synthesis [CYP39A1 in HFD-fed mice, which produced positive activities on cholesterol clearance. Altogether, these results suggested that administration of DHQ could improve cholesterol homeostasis in hepatic tissues of HFD-fed mice, mainly through mediating cholesterogenic genes. Notably, the reliability of RNA-seq data was verified by qRT-PCR for randomly selected genes.In addition to the beneficial effect on triglyceride homeostasis, cholesterol metabolism was also affected by DHQ in this study. In fact, it was shown that excess lipid accumulation in the liver could disturb cholesterol metabolism, causing the dysregulation of cholesterol synthetic pathways, bile acid metabolism, and cholesterol export ,48. In tynthesis ,50. Howeeostasis . In the ynthesis , which iynthesis . Here, DFirmicutes in feces collected from the HFD-fed mice, which was in agreement with many former studies [Lachnoclostridium and unclassified_f_Lachnospiraceae within the family Lachnospiraceae, which was potentially pathogenic bacteria and reported to be linked with diet-induced metabolic diseases in humans and mouse models [Lachnospiraceae was involved in the alleviation of alcoholic fatty liver [Lachnoclostridium and tended to reduce unclassified_f_Lachnospiraceae richness, which contributed to the improvement of hepatic lipid metabolism. Moreover, in the HFD-fed mice, DHQ significantly suppressed the increased amount of sequence assigned to Eubacterium_xylanophilum_group, which was abundant in obese mice according to a previous study [Eubacterium_xylanophilum_group may be a potential bacterium related to metabolic disorder, but its role is unclear and needs further exploration. Meanwhile, HFD significantly lowered the richness of Coriobacteriaceae_UCG_002, which is a member of the Coriobacteriaceae family and had a negative effect on cholesterol and triglycerides homeostasis [Coriobacteriaceae_UCG_002 elevation was associated with the development of NAFLD [Coriobacteriaceae_UCG_002 richness. We speculated that different experimental period and materials might result in this inconsistent result due to the susceptibility and dynamic changes of intestinal flora. Additionally, the proportion of Streptococcus, Lactococcus, and Enterococcus was abundant in the HFD-fed mice. When treated with DHQ, Lactococcus richness was significantly decreased, as Streptococcus and Enterococcus richness displayed a decreasing trend. They were identified as LPS-producing bacteria [Streptococcus, Lactococcus, and Enterococcus relative abundance [Lachnoclostridium, Lactococcus and Eubacterium_xylanophilum_group.Indeed, gut bacteria had a crucial implication for the regulation of hepatic lipid metabolism . Previou studies ,60. Howee models ,62,63. Zty liver . Similarus study . This meeostasis . It has of NAFLD . Surprisbacteria ,68,69. Cbundance . Taken tStreptococcus, Lactococcus, and Enterorcoccus had significant positive correlation with serum insulin, LPS, TC, and hepatic TG contents. Streptococcus, Lactococcus, and Enterorcoccus were recognized as the predominant genus in subjects with obesity or fatty liver disorders [unclassified_f_Lachnospiraceae and Lachnoclostridium was relevant for the increase of hepatic TG content [unclassified_f_Lachnospiraceae and Lachnoclostridium had a positive relationship with serum leptin and hepatic TG levels. As described in previous findings, the relative abundance of Eubacterium_xylanophilum_group had a positive correlation with body mass index and HOMA-IR [Eubacterium_xylanophilum_group was here found to be positively correlated with the content of leptin, TC in serum, and TG in the liver. Simultaneously, the correlation analysis between flora and key genes associated with hepatic lipid metabolism from transcriptome data was conducted. It was shown that the relative abundance of Streptococcus had a positive correlation with lipogenic genes MOGAT1, MID1IP1, and MLXIPL, but had a negative correlation with fatty acid oxidation genes CPT1A and CYP4A10. Moreover, Lactococcus and Enterorcoccus were positively correlated with DGAT2, MOGAT1, MID1IP1, and MLXIPL, but negatively correlated with CPT1A and CYP4A10. Meanwhile, we also found that Eubacterium_xylanophilum_group richness showed a positive relationship with MOGAT1 and MID1IP1 expression, while it was negatively correlated with CPT1A. This means that Streptococcus, Lactococcus, Enterorcoccus, and the Eubacterium_xylanophilum_group are pivotal bacteria that promoted lipid accumulation in the liver. Furthermore, Lactococcus, Enterorcoccus, and Eubacterium_xylanophilum_group had positive correlation with cholesterol synthesis genes ACAT2, FDPS, HMGCS1, MVD, and NSDHL mRNA levels. Besides, the relative abundance of unclassified_f_Lachnospiraceae was positively correlated with FDPS, HMGCS1, MVD, and NSDHL expression and Lachnoclostridium was positively correlated with FDPS, HMGCS1, and MVD expression in the liver. The data proved that these bacteria might produce adverse effects on cholesterol homeostasis and contribute to excess hepatic cholesterol accumulation, especially Lactococcus, and the Eubacterium_xylanophilum_group. Collectively, the new information here contributed to understanding the improved hepatic lipid metabolism followed by DHQ supplementation, at least in part, was mediated by the alterations of gut microbiota.To further explain whether the DHQ-alleviated hepatic lipid metabolic dysregulation was associated with gut microbiota, Pearson’s correlation analysis was performed between lipid metabolic parameters and altered intestinal bacteria. In this work, the results showed that the relative abundance of isorders ,68,69. M content . In keep HOMA-IR , suggestLactococcus and the Eubacterium_xylanophilum_group. In conclusion, these results demonstrated that DHQ has the potential to be used as an effective dietary supplement in preventing and treating hepatic lipid metabolism disorders, providing a possible approach to human therapy for fatty liver.In the present study, we showed that the treatment of DHQ inhibited the synthesis of lipids and cholesterol, promoted fatty acid oxidation, which was associated with the reduced deleterious bacteria, especially


Meles meles). The full-length genome of this novel strain was obtained by a sequence-independent single-primer amplification procedure in combination with Oxford Nanopore Technologies sequencing platform. On sequence analysis, the badger PV could be considered the prototype of a new species, proposed as Sakobuvirus B, classified within the still poorly characterized genus Sakobuvirus. The finding of this study poses interesting questions about the genetic diversity of these viruses, suggesting that the PV host range could be wider than expected.A molecular survey was performed to investigate the gut virome of wild mustelids and sciurids found dead in Northwestern Italy. Using pan-picornavirus primer pair, we discovered a new picornavirus (PV) in the intestinal content of a European badger (Meles meles). By enrichment with a sequence-independent single-primer amplification (SISPA) approach and deep sequencing with Oxford Nanopore Technologies (ONT) platform, the genome sequence of a novel picornavirus strain, Badger/3A-2019/ITA, was reconstructed. On comparison based on the polyprotein sequences, the virus was distantly related  to the feline picornavirus strain FFUP1, identified in 2012 in Portugal and classified into genus Sakobovirus within the species Sakobuvirus A. Upon phylogenetic, pairwise homology, and distance analyses performed on the P1, 2Chel, 3Cpro, and 3Dpol proteins and the complete genomic sequence, the badger picornavirus may be considered a member of a new sakobuvirus species, which we propose as Sakobuvirus B. The recent development of unbiased metagenomic next-generation sequencing has provided a richer view of the wild animal virome making it necessary to expand the knowledge about virus diversity in wildlife, as well as to monitor their potential transmission to domestic animals or humans. In the present study, by screening collections of enteric specimens from wild animals, a novel picornavirus was identified in the intestinal content of a badger ( Picornaviridae includes important human and animal pathogens, associated with a wide range of diseases and, in some cases, with zoonotic potential. Picornaviruses (PVs) are small, icosahedral, non-enveloped viruses, with highly diverse positive-sense single-stranded RNA genomes with lengths ranging from 6.7 to 10.1 kb. The viral genome is predicted to encode a single polyprotein that is processed by viral proteinases to produce the structural proteins 1A, 1B, 1C, and 1D, also referred to as VP4, VP2, VP3, and VP1, and the non-structural proteins (NSPs) 2Apro, 2B, 2Chel, and 3A, 3BVPg, 3Cpro, 3Dpol -3′-UTR as the feline SaKoV-A strain FFUP1. The complete 3′-UTR was 169 nt long, whilst a 372 nt-long portion of the 5′-UTR was determined, shorter than the 5′-UTR region (591-nt) of SaKoV-A. Downstream the 5′-UTR, a single ORF of 7272 nt in length, encoding a large polyprotein of 2423 amino acids (aa), was mapped. The putative translation initiation codon (AUG) of the strain SaKoV/Badger/3A-2019/ITA (corresponding to position 592–594 of feline SaKoV-A), was predicted at nt position 373–375, located in a weak Kozak consensus (GNNAUGC) [1401GAPGVGKS1408) and helicase motif DDxxQ (1452DDIGQ1456) of the 2C, and the 2115KDE2117, 2245PSG2247, 2283YGDD2286 and 2332FLKR2335 motifs of the 3D protein. In the complete coding region, the strain SaKoV/Badger/3A-2019/ITA shared the highest identity to feline SaKoV-A (58.7% nt and 59.7% aa) and to the wild boar sakobuvirus strain WBSA (54.3% nt and 56.2% aa identities). Genetic similarities were also found to PVs of the genus Kobuvirus (49.8% nt and 43.0% aa identities), Salivirus (46.8% nt and 38.5% aa identities), and Passerivirus (45.5% nt and 37.1% aa identities). The complete genome of the strain SaKoV/Badger/3A-2019/ITA (GenBank under accession no. OP293080) was reconstructed using ONT. Out of 6,638,705 filtered reads obtained, 2,598,992 were classified as viral. Of these, 1,930,717 sequences were mapped to the feline SaKoV-A strain FFUP1 generating a single contig of 7813-nt in length with a depth of coverage of 1284489.5. The genome of the strain 3A-2019/ITA showed the same organization 5′-UTR-[L-1AB-1C-1D-2APicornaviridae Study Group  for establishing a new picornavirus genus is a significant divergence of the orthologous protein sequences, exceeding 66% for P1  and 64% for NSPs 2Chel, 3Cpro and 3Dpol. Conversely, no criteria are currently available for picornavirus species demarcation within the genus Sakobuvirus, although strains of different species are expected to display a significant divergence of P1, 2Chel, 3Cpro, and 3Dpol proteins and to form distinct monophyletic groups in the phylogenetic tree [hel, 3Cpro, and 3Dpol, respectively, supporting the classification of the badger PV within the genus Sakobuvirus. On the other hand, maximum likelihood-based phylogenetic trees constructed on the P1, 2Chel, 3Cpro/3Dpol proteins yielded similar topologies  in an additional fecal sample collected from a diarrhoeic cat, with an overall prevalence of 3.6% (2/55) [Sakobuvirus A, a new putative species within the genus Sakobuvirus was identified in 2013 during a metagenomic study aimed to investigate the fecal virome composition of two species of fur seals found deceased along the shore of Rio Grande do Sul (Brazil) [Information on the epidemiology of sakobuviruses is still limited. The first identification of these novel PVs was documented in Portugal in 2012 on the metagenomic analysis of a fecal sample collected from a clinically healthy cat . The vir% (2/55) . With ex(Brazil) . All theA growing number of novel PVs have been recently identified in wild and domestic animals in association with enteric disease. However, for many of them, epidemiological surveys are still limited, making difficult to achieve any firm conclusions on their enteropathogenic role ,25,26,27Finally, gathering data on the virome of wild animals is pivotal to depict a baseline of virus diversity in wildlife and assess the possible threat to animal welfare and conservation and, eventually, to assess possible risks for public health.


The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) system is widely used as a genome-editing tool in various organisms, including plants, to elucidate the fundamental understanding of gene function, disease diagnostics, and crop improvement. Among the CRISPR/Cas systems, Cas9 is one of the widely used nucleases for DNA modifications, but manipulation of RNA at the post-transcriptional level is limited. The recently identified type VI CRISPR/Cas systems provide a platform for precise RNA manipulation without permanent changes to the genome. Several studies reported efficient application of Cas13 in RNA studies, such as viral interference, RNA knockdown, and RNA detection in various organisms. Cas13 was also used to produce virus resistance in plants, as most plant viruses are RNA viruses. However, the application of CRISPR/Cas13 to studies of plant RNA biology is still in its infancy. This review discusses the current and prospective applications of CRISPR/Cas13-based RNA editing technologies in plants. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) systems are found in prokaryotes such as archaea (~80%) and bacteria ~40%) . CRISPR 0% . CRISClass 1 Cas systems comprise types I, III, and IV with diverse variants and effector complexes, whereas class 2 Cas systems consist of types II, V, and VI with an effector module containing a single multifunctional protein . A typicA single multifunctional Cas13 effector protein contains two higher eukaryotes and prokaryotes nucleotide-binding domains (HEPN) that provide RNase activity. The Cas13 protein, when associated with crRNA, forms an RNA-guided RNA targeting complex to recognize and cleave ssRNA targets. Based on Cas13 phylogeny, features, and functional characterization, this system is further classified into six subtypes: VI-A , VI-B , VI-C , VI-D (Cas13d), and recently, VI-X (Cas13X) and VI-Y (Cas13Y) ,18,19,20Leptotrichia shahii (Lsh) . Ho. HoBergeuirement . Cas13b Fusobacterium perfoetens (FpeCas13c).Cas13c is not as functionally characterized compared to other types of Cas13. However, the known characteristics, such as the presence of DR on the 5′ end of crRNA and the spacer length 28–30 nt), are similar to that of Cas13a and Cas13d  19,28].,28.19,28–30 nt, aRuminococcus flavefaciens XPD3002 (CasRx/RfxCas13d) is a prominent homolog for multiple organisms [Cas13d is the smallest of Cas13a-d and is one of the most efficient type VI systems for RNA targeting ,22 Tabl. The Casrganisms ,30,31. Irganisms . Type VIType VI CRISPR/Cas systems provide various applications in various organisms through different RNA technologies such as RNA interference, RNA detection, RNA editing, and RNA targeting ,37,38. CTurnip Mosaic Virus (TuMV) RNA genome, targeting its helper component proteinase (HC-Pro) and coat protein (CP) sequences in Nicotiana benthamiana and Arabidopsis thaliana, respectively [potato virus Y (PVY), tobacco mosaic virus (TMV), southern rice black-streaked dwarf virus (SRBSDV), and rice stripe mosaic virus (RSMV) in various plants [RNA interference (RNAi) is an innate antiviral immunity mechanism that has been successfully used to combat various plant viruses. Nevertheless, the availability of such antiviral strategies is still limited to specific virus groups. Many viruses readily mutate and have developed different counter-defense mechanisms, leading to the rapid emergence of new antiviral approaches. The recently developed CRISPR/Cas13 is a promising tool for engineering plant immunity against a broad range of RNA viruses that constitute a majority of plant viruses a. Althouectively ,41  that binds to target RNA but lacks endonuclease activity , allowinAlternative splicing is a process regulating gene expression in which exons of a gene are spliced to form multiple alternative transcripts. The CRISPR/Cas13 system can regulate RNA splicing pathways by introducing point mutations into the 5′ and 3′ ends of a splice donor site (GU) and a splice acceptor site (AG), respectively, resulting in mis-splicing and losing targeted splice variants. Konerrman et al.  demonstrAgrobacterium sp. strain CP4 (CP4 EPSPS), in a mixture of soybeans (The target RNA recognition and binding abilities of CRISPR/Cas13 provide means for its application in various functional and diagnostic studies. Previously, Abudayyeh et al.  harnessesoybeans . This plCRISPR/Cas technology has become a powerful genome-editing tool due to its applications in various fields for genetic alterations, disease diagnostics, and crop improvement. For the past decade, the DNA targeting CRISPR/Cas9 system has evolved into a remarkable tool for its implementation in various DNA technologies such as gene knockout, gene activation, gene editing, gene therapy, and DNA detection in multiple organisms ,65,66,67In addition, targeting non-coding RNA such as long non-coding RNA, microRNA, and circular RNA in plants using CRISPR/Cas13 can become a promising tool to study their role in plants. Previously, targeting non-coding RNA in plants was performed using CRISPR/Cas9 at the DNA level to find their roles in plant growth, development, and stress responses ,70,71,72Though CRISPR/Cas13 can be used to target ssRNA in many organisms, the RNA targeting and RNA binding in Cas13 have constraints, some of which might limit its use. One major limitation is the collateral activity of Cas13 that causes non-specific RNA cleavage ,77,78. TRNA targeting and editing in plants using CRISPR/Cas13 systems can provide great insights into plant transcriptomic studies. CRISPR/Cas13 application in plants has mainly been to impart tolerance against plant viruses. However, it is also emerging as a prominent tool to target mRNA, circRNA, and other non-coding RNAs. In addition, nucleic acid detection using CRISPR/Cas13 is gaining attention in many recent studies for its high specificity, especially in viral diagnostics. Though Cas13 has a few limitations such as a PFS requirement and non-specific collateral activity affecting its editing efficiency, orthologs such as LwaCas13a, PspCas13b, RfxCas13d can be used to avoid the PFS preference, and collateral RNA cleavage of Cas13 has not been observed in plants yet. Therefore, based on current applications and future perspectives, CRISPR/Cas13 systems can potentially emerge into a robust RNA targeting platform in plants, providing novel opportunities in modern agricultural applications.