PMC:7151644 / 5579-10658 JSONTXT

{"target":"http://pubannotation.org/docs/sourcedb/PMC/sourceid/7151644","sourcedb":"PMC","sourceid":"7151644","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7151644","text":"2. Materials and methods\n\n2.1 Sick pangolins and sample collection\nDuring July to August 2018, four sick wild pangolins were sent to the Jinhua Wildlife Rescue Station of Zhejiang province, China (Fig. 1). At the station, these pangolins received laboratory and clinical examination and subsequent treatment. Although three of the animals died, one recovered following 2 weeks of treatment. Blood and tissue samples were collected from all four animals, and ticks were collected from two (Supplementary Table S1). Pangolins and ticks were initially identified to the species level by experienced field biologists and later confirmed by analyzing sequences of the mitochondrial cytochrome b (mt-cyt b) gene or mitochondrial 16S rDNA gene as described previously (Chen et al. 2012; Guo et al. 2013).\nFigure 1. Sampling locations (red circles) of sick pangolins from Zhejiang province, China. This study was reviewed and approved by the ethics committee of the National Institute for Communicable Disease Control and Prevention of the China Center for Disease Control and Prevention (CDC). All procedures for autopsy and sample collection were in strict according to the guidelines for the Laboratory Animal Use and Care from the China CDC (SYXK(Jing)2017-0021).\n\n2.2 RNA library construction, sequencing, and data analysis\nTotal RNA was extracted from blood, organ tissue, and fecal samples, as well as ticks, using Nucleo Spin RNA Blood (MN, Düren, Germany), RNeasy Plus Mini Kit (Qiagen, Valencia, California USA), RNeasy Plus Universal Mini Kit (Qiagen) and TRIzol LS Reagent (Invitrogen, Carlsbad, California, USA), respectively, following the manufacturer’s instructions. DNA was extracted using the DNeasy Blood and Tissue kit (Qiagen). For RNA library construction, aliquots of RNA solution were pooled in equal quantity (Supplementary Table S2). The SMARTer Stranded Total RNA-Seq Kit v2 (TaKaRa, Dalian, China) and KAPA RNA HyperPrep Kit with RiboErase (HMR; KAPA, Wilmington, Massachusetts, USA) was used to construct RNA libraries from blood, organ tissue, and fecal samples, respectively. Ribosomal (r) RNA was removed using the Ribo-Zero-Gold (HMR) Kit (Illumina, San Diego, California, USA). Paired-end (150 bp) sequencing of each RNA library was performed on the HiSeqX10 platform (Illumina).\nBioinformatic analyses of the sequencing reads were undertaken as described previously (Shi et al. 2016a). In brief, adaptor- and quality-filtered sequencing reads were assembled de novo using the Trinity program (version 2.5.1). Viral contigs were identified by comparison (using blastn and Diamond blastx) to the NCBI non-redundant nucleotide (nt) and protein (nr) database with e-values set to 1 × 10−10 and 1 × 10−4, respectively. Likely contaminating viral sequences were excluded from the meta-transcriptomic data (Supplementary Table S2) using methods described previously (Asplund et al. 2019). In addition, the high frequency of retrovirus sequences was also excluded, as the majority of them probably were host genes, and some of them might be contaminating viral sequences, such as alpharetroviral and gammaretroviral sequences probably linked to laboratory components (Asplund et al. 2019). Finally, the putative viruses present in the blood, liver, spleen, lung, and kidney samples were confirmed by PCR. The quantity of the transcripts mapped to each viral contig was determined using the RSEM program (Li et al. 2010) implemented in Trinity.\n\n2.3 PCR and sequencing\nTotal RNA was reverse transcribed using a one-step RT-PCR kit (TaKaRa). The viral RNA in ticks was detected by nested PCR targeting the conserved regions of the RNA-dependent RNA polymerase (RdRp) gene of both the pestivirus and coltivirus. To recover complete viral genomes, primers were designed based on the assembled pestivirus and coltivirus contigs obtained by meta-transcriptomics (Supplementary Table S3). The genome termini were determined by 5ʹ/3ʹ RACE kits (TaKaRa).\nThe QIAquick Gel Extraction kit (Qiagen) was used to purify the PCR products before sequencing. Purified DNA \u003c700 bp in length was sequenced directly, while those larger than 700 bp were first cloned into a pMD18-T vector (TaKaRa), and then transformed into JM109-143 competent cells. For each sample, at least three clones were selected for sequencing.\n\n2.4 Phylogenetic analysis\nViral sequences were aligned using the E-INS-i algorithm implemented in MAFFT version 7 (Katoh and Standley 2013). Ambiguously aligned regions were then removed using the TrimAl program (Capella-Gutierrez et al. 2009). The best-fit model (LG+Γ) of aa sequence evolution was estimated using MEGA version 7.0 (Kumar et al. 2016). Phylogenetic trees were then estimated using the maximum likelihood (ML) method implemented in PhyML version 3.0 (Guindon et al. 2010) with bootstrap support values calculated from 1,000 replicate trees. Bootstrap values \u003e70 per cent were considered significant. Identities among nt and aa sequences were calculated using the MegAlign program implemented in the Lasergene software package v5.0 (DNAstar).","divisions":[{"label":"p","span":{"begin":3488,"end":3965}},{"label":"title","span":{"begin":0,"end":24}},{"label":"sec","span":{"begin":26,"end":1260}},{"label":"title","span":{"begin":26,"end":66}},{"label":"p","span":{"begin":67,"end":797}},{"label":"figure","span":{"begin":798,"end":890}},{"label":"label","span":{"begin":798,"end":807}},{"label":"caption","span":{"begin":809,"end":890}},{"label":"p","span":{"begin":809,"end":890}},{"label":"p","span":{"begin":891,"end":1260}},{"label":"sec","span":{"begin":1262,"end":3463}},{"label":"title","span":{"begin":1262,"end":1321}},{"label":"p","span":{"begin":1322,"end":2306}},{"label":"p","span":{"begin":2307,"end":3463}},{"label":"sec","span":{"begin":3465,"end":4319}},{"label":"title","span":{"begin":3465,"end":3487}},{"label":"p","span":{"begin":3966,"end":4319}},{"label":"title","span":{"begin":4321,"end":4346}}],"tracks":[{"project":"2_test","denotations":[{"id":"32296543-22560314-144433896","span":{"begin":774,"end":778},"obj":"22560314"},{"id":"32296543-23408889-144433897","span":{"begin":791,"end":795},"obj":"23408889"},{"id":"32296543-31059795-144433899","span":{"begin":2903,"end":2907},"obj":"31059795"},{"id":"32296543-31059795-144433900","span":{"begin":3203,"end":3207},"obj":"31059795"},{"id":"32296543-20022975-144433901","span":{"begin":3434,"end":3438},"obj":"20022975"},{"id":"32296543-23329690-144433902","span":{"begin":4455,"end":4459},"obj":"23329690"},{"id":"32296543-19505945-144433903","span":{"begin":4559,"end":4563},"obj":"19505945"},{"id":"32296543-27004904-144433904","span":{"begin":4668,"end":4672},"obj":"27004904"},{"id":"32296543-20525638-144433905","span":{"begin":4804,"end":4808},"obj":"20525638"}],"attributes":[{"subj":"32296543-22560314-144433896","pred":"source","obj":"2_test"},{"subj":"32296543-23408889-144433897","pred":"source","obj":"2_test"},{"subj":"32296543-31059795-144433899","pred":"source","obj":"2_test"},{"subj":"32296543-31059795-144433900","pred":"source","obj":"2_test"},{"subj":"32296543-20022975-144433901","pred":"source","obj":"2_test"},{"subj":"32296543-23329690-144433902","pred":"source","obj":"2_test"},{"subj":"32296543-19505945-144433903","pred":"source","obj":"2_test"},{"subj":"32296543-27004904-144433904","pred":"source","obj":"2_test"},{"subj":"32296543-20525638-144433905","pred":"source","obj":"2_test"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"2_test","color":"#93ecca","default":true}]}]}}