This work has been funded in part with Federal funds from the National Institutes of Health, Office of Director, Innovator (No.: DP2OD06514) (PCS) and from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contracts (No:HHSN272200900018C, HHSN272200900049C and U19AI110818).

Ethics statement: Lassa fever patients were recruited for this study using protocols approved by human subjects committees at Tulane University, Harvard University, Broad Institute, Irrua Specialist Teaching Hospital (ISTH), Kenema Government Hospital (KGH), Oyo State Ministry of Health, Ibadan, Nigeria and Sierra Leone Ministry of Health. All patients were treated with a similar standard of care and were offered the drug Ribavirin, whether or not they decided to participate in the study. For Lassa fever (LF) patients, treatment with Ribavirin followed the currently recommended guidelines and was generally offered as soon as LF was strongly suspected.
Due to the severe outbreak for Ebola Virus Disease (EVD), patients could not be consented through our standard protocols. Instead use of clinical excess samples from EVD patients was evaluated and approved by Institutional Review Boards in Sierra Leone and at Harvard University. The Office of the Sierra Leone Ethics and Scientific Review Committee, the Sierra Leone Ministry of Health and Sanitation, and the Harvard Committee on the Use of Human Subjects have granted a waiver of consent to sequence and make publically available viral sequences obtained from patient and contact samples collected during the Ebola outbreak in Sierra Leone. These bodies also granted use of clinical and epidemiological data for de-identified samples collected from all suspected EVD patients receiving care during the outbreak response. The Sierra Leone Ministry of Health and Sanitation also approved shipments of non-infectious, non-biological samples from Sierra Leone to the Broad Institute and Harvard University for genomic studies of outbreak samples.
1. DNase-treatment of Sample RNA (Up to 55 &#181;l&#160;Extracted Total RNA, ~4 hr)
<ol>
	<li>Set up the DNase reaction in a 96-well PCR plate on ice in a biosafety cabinet as described in Table 1, Step 1.1 (total volume, 70 &#181;l/well). Note: A master mix can be prepared.</li>
	<li>Vortex gently and thoroughly, then centrifuge at 280 x g at RT for 1 min.</li>
	<li>Incubate at 37 &#176;C for 30 min.</li>
	<li>Cleanup using RNA Solid Phase Reversible Immobilization (SPRI) beads.
	<ol>
		<li>Warm RNA beads to RT for 30 min.</li>
		<li>Gently shake RNA beads bottle to resuspend any magnetic particles that may have settled. Add 1.8x volume (126 &#181;l) of RNA beads to DNase-treated RNA (70 &#181;l), mix by pipette 10 times and incubate for 5 min at RT&#160;(total volume in well, 196 &#181;l).</li>
		<li>Place mixture on the magnetic station. Wait for the solution to clear (5 - 10 min).</li>
		<li>Remove cleared solution while on the station by pipette and discard. While on station, wash beads by covering pellet with 70% ethanol and incubate for 1 min. Remove ethanol with pipette and discard. Repeat for a total of two washes. 
		Note: Using precisely 70% freshly prepared ethanol is critical, as a higher percentage will result in inefficient washing of smaller-sized molecules, whereas &#60;70% ethanol could cause loss of sample7.</li>
		<li>Keep plate on the station and leave open to air-dry. Note: Be sure to allow the beads to dry completely until beads begin to crack.</li>
		<li>Add 55 &#181;l&#160;of nuclease-free water to the plate to elute RNA. Remove plate from the station to mix the beads and water by pipetting thoroughly. Note: Alternatively, use less water (&#8804; 10 &#181;l) in order to concentrate the total RNA.</li>
		<li>Place plate back on the station. Wait until solution clears to transfer by pipette to new screw-cap tube for long-term storage (-80&#160;&#176;C). Place 5 &#181;l&#160;RNA in new 96-well PCR plate for depletion (step. 2.4).</li>
		<li>Optional: Save and dilute 1 &#181;l&#160;in 19 &#181;l&#160;water (1:20) for qRT-PCR of rRNA (e.g., 18S, 28S rRNA) (Table 2) and viral markers5.</li>
	</ol>
	</li>
</ol>
2. Selective Depletion of Ribosomal and Carrier RNA from Viral RNA Sample (~4 hr)
<ol>
	<li>Make 5x hybridization and 10x RNase H reaction buffers, and nuclease-free water with linear acrylamide carrier as described in Table 1.</li>
	<li>Set up hybridization reaction by combining RNA with rRNA depletion oligos (Table 3) and oligo(dT) on ice in a 96-well PCR plate as described in Table 1. 
	Note: A master mix can be prepared. 50 femtograms (fg) of a unique synthetic RNA (ERCCs8) can be added for tracking both the viral sequencing process and potential index read cross-contamination.
	<ol>
		<li>Vortex gently and thoroughly, then centrifuge at 280 x g at RT&#160;for 1 min. 
		Incubate at 95 &#176;C for 2 min, slow ramping to 45 &#176;C at -0.1 &#176;C per sec. Pause the thermocycler at 45 &#176;C.</li>
	</ol>
	</li>
	<li>Set up RNase H reaction mix on ice as described in Table 1, then preheat at 45 &#176;C for 2 min. Note: A master mix can be prepared.
	<ol>
		<li>Add the pre-heated RNase H mix to the hybridization reaction in plate while keeping the plate in the thermocycler at 45 &#176;C.</li>
		<li>Mix well by gentle pipetting 6 - 8 times. Incubate at 45 &#176;C for another 30 min. Place on ice.</li>
	</ol>
	</li>
	<li>Set up the DNase reaction mix on ice as described in Table 1. Note: A master mix can be prepared.
	<ol>
		<li>Add to the RNase H reaction in plate, vortex gently and thoroughly, then centrifuge at 280 x g at RT for 1 min. Incubate at 37 &#176;C for 30 min.</li>
		<li>Stop DNase reaction by adding 5 &#181;l&#160;0.5 M EDTA. Vortex gently and thoroughly, then centrifuge at 280 x g at RT&#160;for 1 min.</li>
	</ol>
	</li>
	<li>Cleanup using RNA beads (see step 1.3) using a 1.8x volume (144 &#181;l) beads. Elute in 11 &#181;l&#160;of nuclease-free water. Note: For safe cold storage, store depleted RNA samples at -80 &#176;C&#160;O/N.</li>
</ol>
3. cDNA Synthesis (~6 hr)
<ol>
	<li>Mix rRNA/carrier-depleted RNA with random primers on ice in a 96-well PCR plate as described in Table 1, vortex gently and thoroughly, then centrifuge at 280 x g at RT for 1 min.
	<ol>
		<li>Heat the mixture to 70 &#176;C for 10 min in a thermocycler. Immediately after heat denaturation, place the RNA on ice for 1 - 5 min. Do not allow the RNA to stand (even on ice) for longer than 5 min prior to the first-strand reaction.</li>
	</ol>
	</li>
	<li>Set up first-strand synthesis reaction mix on ice as described in Table 1. 
	Note: A master-mix may be prepared.
	<ol>
		<li>Add to RNA/random primer mix in plate, vortex gently and thoroughly, then centrifuge at 280 x g at RT&#160;for 1 min. Incubate at 22 - 25 &#176;C for 10 min.</li>
		<li>Incubate at 55 &#176;C in an air incubator for 60 min. Place the plate on ice to terminate the reaction. Note: The use of an air incubator is recommended to create gradual warming of the first-strand reaction during which the primers anneal and the first strand begins to elongate.</li>
	</ol>
	</li>
	<li>Set up second-strand synthesis reaction mix on ice as described in Table 1. 
	Note: A master-mix may be prepared.
	<ol>
		<li>Add to the first-strand synthesis reaction in the&#160;plate, vortex gently and thoroughly, then centrifuge at 280 x g at RT for 1 min. Incubate for 2 hr at 16 &#176;C (keep lid at 25 &#176;C). Do not allow the temperature to rise above 16 &#176;C.</li>
		<li>Place the plate on ice, then inactivate reaction by adding 5 &#181;l&#160;of 0.5 M EDTA, mix gently and thoroughly, then centrifuge at 280 x g at RT for 1 min.</li>
	</ol>
	</li>
	<li>Cleanup with DNA beads (see step 1.3 for protocol) using 1.8x volume (153 &#181;l) of beads. Elute in 9 &#181;l&#160;of elution buffer (EB). Save 1 &#181;l&#160;for quantification. Use 1 ng of cDNA for subsequent steps. If cDNA concentration is too low to detect, use 4 &#181;l&#160;of cDNA for tagmentation (see step 4.1).</li>
	<li>For safe cold storage, store double-stranded cDNA at 4 &#176;C O/N or -20 &#176;C for long-term storage.</li>
</ol>
4. Library Preparation &#8212; DNA Library Construction (~4 hr)
<ol>
	<li>Transfer 4 &#181;l&#160;of cDNA to a 96-well plate and save the remaining cDNA for a second attempt if needed.</li>
	<li>Set up the tagmentation reaction on ice as described in Table 1. 
	Note: A master-mix may be prepared. To reduce background and overall cost, the total volume of the tagmentation reaction is reduced from 20 to 10 &#181;l. As cDNA is the limiting factor, the amount of ATM (i.e.,&#160;transposome) used in the reaction is also reduced to decrease the number of integration sites.
	<ol>
		<li>Add tagmentation mix to cDNA in the plate, vortex gently and thoroughly and centrifuge at 280 x g (at RT) for 1 min. Incubate at 55 &#176;C for 5 min, hold at 10 &#176;C.</li>
		<li>Once at 10 &#176;C, immediately add 2.5 &#181;l&#160;of Neutralize Tagment Buffer (NT) to end the reaction. Mix by pipetting up and down, then centrifuge at 280 x g (at RT) for 1 min.</li>
		<li>Incubate at RT for 5 min.</li>
	</ol>
	</li>
	<li>Set up PCR amplification reaction on ice as described in Table 1.
	<ol>
		<li>Vortex gently and thoroughly, then centrifuge at 280 x g at RT&#160;for 1 min.</li>
		<li>Perform PCR on thermocycler using the conditions described in Table 1. 
		Note: 12 cycles of PCR are suggested for 1 ng of tagmented cDNA; however, viral clinical samples often have undetectable amounts of cDNA. For low amounts of cDNA (&#60;1 ng), use up to 18 cycles of PCR to create enough library for sequencing.</li>
	</ol>
	</li>
	<li>Library preparation &#8212; cleanup and pooling for sequencing
	<ol>
		<li>Bring sample up to 50 &#181;l&#160;with EB.</li>
		<li>Cleanup with DNA beads (see step 1.3 for protocol) using 0.6x volume (30 &#181;l) beads. Elute in 15 &#181;l&#160;EB.</li>
		<li>Determine concentration of library (Figure 3) by conducting region analysis (150 to 1,000 bp) using bioanalyzer software9, excluding primer dimers (~120 bp) from region analysis. Note: Alternatively, qPCR can be used to quantify libraries 10.</li>
		<li>Pool libraries at the lowest molar concentration of 1 nM or greater. If library is below 1 nM, add a small volume of library to pool (~1x volume of other libraries) to capture sequence information from these libraries.</li>
		<li>Cleanup pool with 0.7x DNA beads as outlined above (see step 2). Elute in 15 &#181;l&#160;EB. Note: Volume of beads will depend on the final volume of the pool.</li>
		<li>Analyze pool9. Determine molar concentration by conducting region analysis (150 to 1,000 bp)9. Note: Alternatively, qPCR can be used to quantify library pool 10.</li>
		<li>Load sequencer at 10 pM library concentration to generate 101 bp, paired-end reads with dual barcode reads11.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 3" src="/files/ftp_upload/54117/54117fig3.jpg" /> 
Figure 3. Libraries Constructed from Ebola Virus Clinical Samples. Gel image of 4 representative Ebola virus (EBOV) libraries. Regions of library and primer dimers are shown. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/54117/54117fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+depletion+of+rRNA+enables+whole+transcriptome+profiling+of+archival+fixed+tissue.">Selective depletion of rRNA enables whole transcriptome profiling of archival fixed tissue.</a> PLoS One. 7, e42882 (2012).</li><li>Park, D. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ebola+Virus+Epidemiology,+Transmission,+and+Evolution+during+Seven+Months+in+Sierra+Leone.">Ebola Virus Epidemiology, Transmission, and Evolution during Seven Months in Sierra Leone.</a> Cell. 161, 1516-1526 (2015).</li><li>Andersen, K. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+Sequencing+Uncovers+Origins+and+Evolution+of+Lassa+Virus.">Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus.</a> Cell. 162, 738-750 (2015).</li><li>Matranga, C. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhanced+methods+for+unbiased+deep+sequencing+of+Lassa+and+Ebola+RNA+viruses+from+clinical+and+biological+samples.">Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples.</a> Genome Biol. 15, 519 (2014).</li><li>Tang, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-Seq+analysis+to+capture+the+transcriptome+landscape+of+a+single+cell.">RNA-Seq analysis to capture the transcriptome landscape of a single cell.</a> Nat Protoc. 5, 516-535 (2010).</li><li>Jiang, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synthetic+spike-in+standards+for+RNA-seq+experiments.">Synthetic spike-in standards for RNA-seq experiments.</a> Genome Res. 21, 1543-1551 (2011).</li><li>. Kapa Biosystems Available from: <a target="_blank" href="https://www.kapabiosystems.com/product-applications/products/next-generation-sequencing-2/library-quantification/">https://www.kapabiosystems.com/product-applications/products/next-generation-sequencing-2/library-quantification/</a> (2015)</li><li>. Illumina Technologies Available from: <a target="_blank" href="https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/miseq/preparing-libraries-for-sequencing-on-miseq-15039740-d.pdf">https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/miseq/preparing-libraries-for-sequencing-on-miseq-15039740-d.pdf</a> (2015)</li><li>Kircher, M., Sawyer, S., Meyer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double+indexing+overcomes+inaccuracies+in+multiplex+sequencing+on+the+Illumina+platform.">Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform.</a> Nucleic Acids Res. 40, 3 (2012).</li><li>Trombley, A. 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The authors have no competing financial interests.

The outlined approach enables robust, universal, rapid sequencing and was used for sequencing Ebola virus during the 2014 outbreak2,4. By coupling selective depletion and cDNA synthesis with tagmentation library construction, the overall process time was reduced by ~2 days from previous adapter ligation methods. More recently, this protocol was employed by international collaborators and others with great success15,16 and will be deployed to labs in West Africa to support local genomics-based research studies and diagnostics17.
The protocol described here uses random primers to prepare cDNA for viral RNA-seq libraries. Unlike previous viral RNA-seq approaches, it requires no a priori knowledge of sequence data or elaborate and time-consuming primer design for a specific virus or clade. The method can be applied to any viral RNA sample. For example, it was used to generate viral content from both Ebola and Lassa samples6. The protocol may also be used for host transcriptomic, metagenomic and pathogen discovery sequencing projects 1.
A critical step of the protocol is targeted RNase H digestion, a high-throughput, low cost method for removing unwanted carrier and host RNA from viral samples. The selective depletion step of the protocol uses many components and requires skill and accuracy. Extra time and care should be taken during the initial setup.
As most clinical serum and plasma samples often have very little nucleic acid material, contamination and sample loss are common. To avoid these issues, special care should be taken when using this protocol. First, RNA is highly susceptible to degradation; therefore all areas should be clean and free of nucleases. Second, to identify samples suitable for use in this protocol, qRT-PCR assays for both host RNA and virus should be used for quantification5,6. When comparing input amounts with sequencing results from the protocol, sequencing success (i.e.,&#160;generation of sufficient data for full viral assembly) correlated with samples that contained at least 100 pg total RNA and 1,000 copies of virus. Third, exposure to environmental sources of nucleic acids should be avoided. The protocol outlined here is done in a biosafety cabinet for safety precautions and for limiting environmental contaminants. Moreover, our group and others have noticed that commercial enzymes may be another source of contaminating bacterial nucleic acids in low input samples6,18. Use of a clean workspace (e.g., PCR hood, biosafety cabinet) and negative controls (e.g., water or buffer) will help alleviate and track contamination, respectively. For samples with &#60;100 pg of total RNA, only poly(rA) carrier RNA, not rRNA, should be depleted to ensure high quality sequencing results while limiting loss of material. For very low input samples, cDNA-amplification methods may be more suitable19, although poly(rA) carrier should be removed prior to the cDNA synthesis.
The depletion of host rRNA enriches for viral content in sequencing libraries and is applicable to different sample collections including serum or plasma, and multiple types of tissues from rodents and non-human primates5,6. In non-human organisms, reads aligning to 28S rRNA remained after depletion, suggesting 28S rRNA is less conserved between humans and other species6,20. When using this method with non-human isolates, it may be necessary to supplement with DNA oligos complementary to the divergent rRNA sequences of the specific host 3,21.
Since the protocol is unbiased, viral reads may represent only a small fraction of total library content. Although rRNA is the most abundant species of host RNA and only a small percentage of rRNA reads (&#60;1%) are found after selective depletion, all other host RNA (e.g., mRNA) will remain after depletion and may account for many sequencing reads from the sample. Therefore &#34;oversampling&#34; (i.e., oversequencing) individual libraries is required in order to have enough coverage for viral assembly and variant calls. For our studies, we attempt to sequence ~20 million reads per sample to have enough depth for analysis of viral genomic and associated variants as well as metagenomic content2,5. For metagenomic and pathogen discovery studies, it is important to note that contaminating host DNA is removed by DNase digestion. Therefore viruses and other pathogens that contain DNA genomes may be lost during the process, however RNA intermediates may still be sequenced.

Next generation sequencing of viruses from clinical sources can inform transmission and the epidemiology of infections, as well as help support novel diagnostic, vaccine and therapeutic development. cDNA synthesis using random primers has allowed the detection and assembly of genomes from divergent, co-infecting or even novel viruses1,2. As with other unbiased methods, unwanted contaminants occupy many sequencing reads and negatively impact sequencing results. Host and poly(rA) carrier RNA are contaminants present in many existing viral sample collections.
The protocol describes an efficient and cost-effective way of deep sequencing RNA virus genomes based on unbiased total RNA-seq. The method utilizes an RNase H selective depletion step3 to remove unwanted host ribosomal and carrier RNA. Selective depletion enriches for viral content (Figure 1) and improves the overall quality of sequencing data (Figure 2) from clinical samples. Moreover, tagmentation is applied to the protocol as it significantly reduces library construction time. These methods have been used to rapidly generate large datasets of Ebola and Lassa virus genomes2,4,5 and can be used to study a wide range of RNA viruses. Lastly, the approach is not limited to human samples; the utility of selective depletion was demonstrated on tissue samples collected from Lassa-infected rodents and non-human primate disease models5,6.
<img alt="Figure 1" src="/files/ftp_upload/54117/54117fig1.jpg" /> 
Figure 1. Total RNA Content Reflects Enrichment of Lassa Virus Content Using Selective Depletion. Starting overall content (RNA input) and enrichment of unique Lassa virus (LASV) reads (Library content) upon rRNA depletion from nine different clinical isolates. This figure has been modified from6. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/54117/54117fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54117/54117fig2.jpg" /> 
Figure 2. Higher Quality Sequencing After Carrier RNA Depletion. Median base qualities per sequencing cycle of poly(rA)-contaminated Lassa virus libraries (red) and control (no carrier observed in library, black) from QC report 13. Both read 1 and read 2 of paired end reads are merged in the library BAM file and the quality scores are shown at each base. This figure has been modified from6. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/54117/54117fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The viral RNA-seq protocol details construction of libraries directly from extracted RNA collected from clinical and biological samples. To ensure personal safety, all viral serum, plasma and tissue samples should be inactivated in appropriate buffers prior to RNA extraction. In some inactivation and extraction kits, carrier poly(rA) RNA is included; this will be removed during the initial RNase H selective depletion step. Based on complete recovery, the expected concentration of carrier RNA is 100 ng/&#181;l. In the protocol, 110 ng/&#181;l&#160;oligo dT RNA (1.1x carrier concentration) is used for depletion. If poly(rA) carrier is not present in the sample, then oligo(dT) should not be added prior to depletion.
The following protocol is designed for 24 reactions in PCR plate format (up to 250 &#181;l&#160;volume). An earlier version of this protocol was reported in Matranga, et al.6.

<table><tbody><tr><td>96-well PCR Plates</td><td>VWR</td><td>47743-953</td><td></td></tr><tr><td>Strips of Eight Caps</td><td>VWR</td><td>47745-512</td><td></td></tr><tr><td>Nuclease-free water</td><td>Ambion</td><td>AM9937</td><td>50 ml bottle</td></tr><tr><td>TURBO DNase</td><td>Ambion</td><td>AM2238</td><td>post RNA extraction step, 2 U/&amp;micro;l, buffer included</td></tr><tr><td>PCR cycler</td><td></td><td></td><td>any PCR cyclers&amp;nbsp;</td></tr><tr><td>Agencourt RNAClean XP SPRI beads&amp;nbsp;</td><td>Beckman Coulter Genomics</td><td>A63987</td><td>beads for RNA cleanup</td></tr><tr><td>Real Time qPCR system</td><td></td><td></td><td>any system</td></tr><tr><td>DynaMag-96 Side Skirted Magnet</td><td>Invitrogen</td><td>12027</td><td></td></tr><tr><td>70% Ethanol</td><td></td><td></td><td>prepare fresh</td></tr><tr><td>qRT-PCR primers</td><td>IDT DNA</td><td></td><td>see &lt;strong&gt;Table 2&lt;/strong&gt;</td></tr><tr><td>5 M NaCl&amp;nbsp;</td><td>Ambion</td><td>AM9760G</td><td></td></tr><tr><td>1 M Tris-HCl pH 7.4&amp;nbsp;</td><td>Sigma</td><td>T2663-1L</td><td></td></tr><tr><td>1 M Tris-HCl pH 7.5&amp;nbsp;</td><td>Invitrogen</td><td>15567-027</td><td></td></tr><tr><td>1 M MgCl&lt;sub&gt;2&lt;/sub&gt;&amp;nbsp;</td><td>Ambion</td><td>AM9530G</td><td></td></tr><tr><td>Linear acrylamide&amp;nbsp;</td><td>Ambion&amp;nbsp;</td><td>AM9520</td><td></td></tr><tr><td>DNA oligos covering entire rRNA region</td><td>IDT DNA</td><td></td><td>see &lt;strong&gt;Table 3&lt;/strong&gt;, order lab-ready at 100 &amp;micro;M</td></tr><tr><td>Oligo (dT)</td><td>IDT DNA</td><td></td><td>40 nt long, desalted</td></tr><tr><td>Hybridase Thermostable RNase H&amp;nbsp;</td><td>Epicentre</td><td>H39100</td><td></td></tr><tr><td>RNase-free DNase Kit&amp;nbsp;</td><td>Qiagen</td><td>79254</td><td>post selective depletion step</td></tr><tr><td>SUPERase-In RNase Inhibitor</td><td>Ambion</td><td>AM2694</td><td></td></tr><tr><td>Random Primers&amp;nbsp;</td><td>Invitrogen</td><td>48190-011</td><td>mostly hexamers</td></tr><tr><td>10 mM dNTP mix</td><td>New England Biolabs</td><td>N0447L</td><td></td></tr><tr><td>SuperScript III Reverse Transcriptase&amp;nbsp;</td><td>Invitrogen</td><td>18080-093</td><td>with first-strand buffer, DTT</td></tr><tr><td>Air Incubator</td><td></td><td></td><td>any air incubator cyclers&amp;nbsp;</td></tr><tr><td>NEBNext Second Strand Synthesis (dNTP-free) Reaction Buffer</td><td>New England Biolabs</td><td>B6117S</td><td>10x</td></tr><tr><td>&lt;em&gt;E. coli&lt;/em&gt; DNA Ligase</td><td>New England Biolabs</td><td>M0205L</td><td>10 U/&amp;mu;l</td></tr><tr><td>&lt;em&gt;E. coli&lt;/em&gt; DNA Polymerase I&amp;nbsp;</td><td>New England Biolabs</td><td>M0209L</td><td>10 U/&amp;mu;l</td></tr><tr><td>&lt;em&gt;E. coli&lt;/em&gt; RNase H</td><td>New England Biolabs</td><td>M0297L</td><td>2 U/&amp;mu;l</td></tr><tr><td>0.5 M EDTA</td><td>Ambion</td><td>AM9261</td><td></td></tr><tr><td>Agencourt AMPure XP SPRI beads</td><td>Beckman Coulter Genomics</td><td>A63881</td><td>beads for DNA cleanup</td></tr><tr><td>Elution Buffer&amp;nbsp;</td><td>Qiagen</td><td></td><td>10 mM Tris HCl, pH 8.5</td></tr><tr><td>Quant-iT dsDNA HS Assay Kit&amp;nbsp;</td><td>Invitrogen</td><td>Q32854</td><td></td></tr><tr><td>Qubit fluorometer&amp;nbsp;</td><td>Invitrogen</td><td>Q32857</td><td></td></tr><tr><td>Nextera XT DNA Sample Prep Kit&amp;nbsp;</td><td>Illumina</td><td>FC-131-1096</td><td></td></tr><tr><td>Nextera XT DNA Index Kit&amp;nbsp;</td><td>Illumina</td><td>FC-131-1001</td><td></td></tr><tr><td>Tapestation 2200</td><td>Agilent</td><td>G2965AA</td><td></td></tr><tr><td>High Sensitivity D1000 reagents</td><td>Agilent</td><td>5067-5585</td><td></td></tr><tr><td>High Sensitivity D1000 ScreenTape</td><td>Agilent</td><td>5067-5584</td><td></td></tr><tr><td>BioAnalyzer 2100&amp;nbsp;</td><td>Agilent</td><td>G2939AA</td><td></td></tr><tr><td>High Sensitivity DNA reagents</td><td>Agilent</td><td>5067-4626</td><td></td></tr><tr><td>Library Quantification Complete kit (Universal)</td><td>Kapa Biosystems</td><td>KK4824</td><td>alternative to tapestation, bioanalyzer for library quantification</td></tr></tbody></table>

unbiased deep sequencing of rna viruses from clinical samples

Here we outline a next-generation RNA sequencing protocol that enables de novo assemblies and intra-host variant calls of viral genomes collected from clinical and biological sources. The method is unbiased and universal; it uses random primers for cDNA synthesis and requires no prior knowledge of the viral sequence content. Before library construction, selective RNase H-based digestion is used to deplete unwanted RNA &#8212; including poly(rA) carrier and ribosomal RNA &#8212; from the viral RNA sample. Selective depletion improves both the data quality and the number of unique reads in viral RNA sequencing libraries. Moreover, a transposase-based &#39;tagmentation&#39; step is used in the protocol as it reduces overall library construction time. The protocol has enabled rapid deep sequencing of over 600 Lassa and Ebola virus samples-including collections from both blood and tissue isolates-and is broadly applicable to other microbial genomics studies.

The described protocol enables the generation of high quality sequencing reads from low-input viral RNA samples while enriching for unique viral content. As shown in Figure 1, the protocol enriched unique Lassa virus content at least five-fold in all samples (compared to non-depleted controls) with at least one million copies of 18S rRNA (~100 pg total RNA). Likewise, sequencing success also correlated with the amount of virus within a given sample. Using qRT-PCR as a surrogate for viral quantity, samples that contained ~1,000 or more viral genome copies most often created full assemblies (data not shown). Moreover, depletion of poly(rA) carrier reduces homopolymer sequences of A and T in libraries, resulting in cleaner preparations and ensuring better quality sequencing reads (Figure 2). Final libraries from low input viral clinical samples often have a broad fragment length from 150 to 1,000 bp (Figure 3).
After sequencing, to reduce sample misidentification and crosstalk between libraries within a pool12, only index reads with a base quality score of 25 (q25) and ensure zero mismatches are kept during the demultiplexing process. Viral genomes are assembled using a bioinformatics pipeline specific for divergent viruses2,4-6. These tools are available at https://github.com/broadinstitute/viral-ngs or through commercial cloud platforms4.
<table border="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Step 1.1: DNase reaction</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume per reaction (&#181;l)</td>
		</tr>
		<tr>
			<td>10x DNase buffer</td>
			<td>7</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>6</td>
		</tr>
		<tr>
			<td>Extracted viral RNA</td>
			<td>55</td>
		</tr>
		<tr>
			<td>DNase (2 U/&#181;l)</td>
			<td>2</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>70</td>
		</tr>
		<tr>
			<td>Step 2.1: 5x Hybridization buffer</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume for 1 ml (&#181;l)</td>
		</tr>
		<tr>
			<td>5 M NaCl</td>
			<td>200</td>
		</tr>
		<tr>
			<td>1 M Tris-HCl (pH 7.4)</td>
			<td>500</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>300</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>1,000</td>
		</tr>
		<tr>
			<td>Step 2.1: 10x RNase H reaction buffer</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume for 1 ml (&#181;l)</td>
		</tr>
		<tr>
			<td>5 M NaCl</td>
			<td>200</td>
		</tr>
		<tr>
			<td>1 M Tris-HCl (pH 7.5)</td>
			<td>500</td>
		</tr>
		<tr>
			<td>1 M MgCl2</td>
			<td>200</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>500</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>1,000</td>
		</tr>
		<tr>
			<td>Step 2.1: Water with linear acrylamide</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume for 1 ml buffer (&#181;l)</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>992</td>
		</tr>
		<tr>
			<td>Linear acrylamide (5 mg/ml)</td>
			<td>8</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>1,000</td>
		</tr>
		<tr>
			<td colspan="2">Step 2.2: Hybridization reaction for selective depletion</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume per reaction (&#181;l)</td>
		</tr>
		<tr>
			<td>5x Hybridization Buffer</td>
			<td>2</td>
		</tr>
		<tr>
			<td>rRNA-depletion oligo mix (100 &#181;M)</td>
			<td>1.22</td>
		</tr>
		<tr>
			<td>Oligo(d)T (550 ng/&#181;l)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>DNase-treated total RNA&#160;</td>
			<td>up to 5</td>
		</tr>
		<tr>
			<td>Spike-in RNA (This is optional)</td>
			<td>0.5</td>
		</tr>
		<tr>
			<td>Water (with linear acrylamide)</td>
			<td>bring up to 10 total</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>10</td>
		</tr>
		<tr>
			<td colspan="2">Step 2.3: RNase H reaction for selective depletion</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume per reaction (&#181;l)</td>
		</tr>
		<tr>
			<td>10x RNase H Reaction Buffer&#160;&#160;&#160;&#160;&#160;&#160;&#160;</td>
			<td>2</td>
		</tr>
		<tr>
			<td>Water (with linear acrylamide)</td>
			<td>5</td>
		</tr>
		<tr>
			<td>Thermostable RNase H (5 U/&#181;l)</td>
			<td>3</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>10</td>
		</tr>
		<tr>
			<td colspan="2">Step 2.4: DNase reaction post selective depletion</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume per reaction (&#181;l)</td>
		</tr>
		<tr>
			<td>10x DNase Buffer</td>
			<td>7.5</td>
		</tr>
		<tr>
			<td>Water (with linear acrylamide)</td>
			<td>44.5</td>
		</tr>
		<tr>
			<td>RNase inhibitor (20 U/&#181;l)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>RNase-free DNase I (2.72 U/&#181;l)&#160;</td>
			<td>2</td>
		</tr>
		<tr>
			<td>Total volume (with RNase H reaction)</td>
			<td>75</td>
		</tr>
		<tr>
			<td colspan="2">Step 3.1:&#160; cDNA synthesis, random primer hybridization</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume per reaction (&#181;l)</td>
		</tr>
		<tr>
			<td>rRNA/carrier-depleted RNA</td>
			<td>10</td>
		</tr>
		<tr>
			<td>3 &#181;g random primer</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>11</td>
		</tr>
		<tr>
			<td>Step 3.2: First strand cDNA synthesis reaction</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume (&#181;l)</td>
		</tr>
		<tr>
			<td>5x First-Strand Reaction Buffer</td>
			<td>4</td>
		</tr>
		<tr>
			<td>0.1 M DTT</td>
			<td>2</td>
		</tr>
		<tr>
			<td>10 mM dNTP mix</td>
			<td>1</td>
		</tr>
		<tr>
			<td>RNase inhibitor (20 U/&#181;l)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Reverse transcriptase (add last)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Total volume (with RNA above)</td>
			<td>20</td>
		</tr>
		<tr>
			<td colspan="2">Step 3.3: Second strand cDNA synthesis reaction</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume (&#181;l)</td>
		</tr>
		<tr>
			<td>RNase-free water</td>
			<td>43</td>
		</tr>
		<tr>
			<td>10x Second-Strand Reaction Buffer</td>
			<td>8</td>
		</tr>
		<tr>
			<td>10 mM dNTP mix</td>
			<td>3</td>
		</tr>
		<tr>
			<td>E. coli DNA Ligase (10 U/&#181;l)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>E. coli DNA Polymerase I (10 U/&#181;l)</td>
			<td>4</td>
		</tr>
		<tr>
			<td>E. coli RNase H (2 U/&#181;l)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Total volume (with 1st strand reaction)</td>
			<td>80</td>
		</tr>
		<tr>
			<td>Step 4.2:&#160; Tagmentation reaction</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume (&#181;l)</td>
		</tr>
		<tr>
			<td>Amplicon Tagment Mix (ATM)</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Tagment DNA Buffer (TD)</td>
			<td>5</td>
		</tr>
		<tr>
			<td>Total volume (with cDNA)</td>
			<td>10</td>
		</tr>
		<tr>
			<td>Step 4.3: Library PCR reaction</td>
			<td></td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Volume (&#181;l)</td>
		</tr>
		<tr>
			<td>PCR Master Mix (NPM)</td>
			<td>7.5</td>
		</tr>
		<tr>
			<td>Index 1 primer (i7)</td>
			<td>2.5</td>
		</tr>
		<tr>
			<td>Index 2 primer (i5)</td>
			<td>2.5</td>
		</tr>
		<tr>
			<td>Total volume (with tagmented cDNA)</td>
			<td>25</td>
		</tr>
		<tr>
			<td>Step 4.3.2: Library PCR conditions</td>
			<td></td>
		</tr>
		<tr>
			<td>72 &#176;C, 3 min</td>
			<td></td>
		</tr>
		<tr>
			<td>95 &#176;C, 30 sec</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">up to 18 cycles-10 sec at 95 &#176;C, 30 sec at 55 &#176;C, 30 sec at 72 &#176;C</td>
		</tr>
		<tr>
			<td>72 &#176;C, 5 min</td>
			<td></td>
		</tr>
		<tr>
			<td>10 &#176;C, forever</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 1: Reaction set-up and buffers. Step-by-step tables with contents of all buffers and reaction mixes.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Oligo Name</td>
			<td>Sequence (5&#39; to 3&#39;)</td>
		</tr>
		<tr>
			<td>Ebola KGH FW</td>
			<td>GTCGTTCCAACAATCGAGCG</td>
		</tr>
		<tr>
			<td>Ebola KGH RV</td>
			<td>CGTCCCGTAGCTTTRGCCAT</td>
		</tr>
		<tr>
			<td>Ebola KULESH FW</td>
			<td>TCTGACATGGATTACCACAAGATC</td>
		</tr>
		<tr>
			<td>Ebola KULESH RV</td>
			<td>GGATGACTCTTTGCCGAACAATC</td>
		</tr>
		<tr>
			<td>Lassa SL FW</td>
			<td>GTA AGC CCA GCD GYA AAB CC</td>
		</tr>
		<tr>
			<td>Lassa SL RV</td>
			<td>AAG CCA CAG AAA RCT GGS AGC A</td>
		</tr>
		<tr>
			<td>18S rRNA FW</td>
			<td>TCCTTTAACGAGGATCCATTGG</td>
		</tr>
		<tr>
			<td>18S rRNA RV</td>
			<td>CGAGCTTTTTAACTGCAGCAACT</td>
		</tr>
	</tbody>
</table>
Table 2: qRT-PCR Primers Sequences. Primers used for measuring host (18S rRNA) and viral (Ebola and Lassa) content. &#39;KGH&#39; is Kenema Government Hospital in Sierra Leone, where the Ebola primers were tested 2. &#39;Kulesh&#39; is the investigator who designed the primer set 14.
Table 3: Ribosomal RNA (rRNA) Depletion Oligos. 195 50-nucleotide&#160;long sequences complementary to human rRNA for selective depletion step6. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/54117/Table_3.xlsx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Unbiased Deep Sequencing of RNA Viruses from Clinical Samples at JoVE.com

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

This protocol describes a rapid and broadly applicable method for unbiased RNA-sequencing of viral samples from human clinical isolates.

Here we outline a next-generation RNA sequencing protocol that enables de novo assemblies and intra-host variant calls of viral genomes collected from ...

unbiased-deep-sequencing-of-rna-viruses-from-clinical-samples

Universidad de Cartagena UDEC

Research

JoVE Journal

Medicine

16.8K Views.  Broad Institute of MIT and Harvard. This protocol describes a rapid and broadly applicable method for unbiased RNA-sequencing of viral samples from human clinical isolates.

Video: Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Using a Pan-Viral Microarray Assay (Virochip) to Screen Clinical Samples for Viral Pathogens

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence of novel viral pathogens, such as SARS coronavirus and 2009 pandemic H1N1 influenza virus, that are not detectable by traditional methods. To address these challenges, we have previously developed and validated a pan-viral microarray platform called the Virochip with the capacity to detect all known viruses as well as novel variants on the basis of conserved sequence homology1. Using the Virochip, we have identified the full spectrum of viruses associated with respiratory infections, including cases of unexplained critical illness in hospitalized patients, with a sensitivity equivalent to or superior to conventional clinical testing2-5. The Virochip has also been used to identify novel viruses, including the SARS coronavirus6,7, a novel rhinovirus clade5, XMRV (a retrovirus linked to prostate cancer)8, avian bornavirus (the cause of a wasting disease in parrots)9, and a novel cardiovirus in children with respiratory and diarrheal illness10. The current version of the Virochip has been ported to an Agilent microarray platform and consists of ~36,000 probes derived from over ~1,500 viruses in GenBank as of December of 2009. Here we demonstrate the steps involved in processing a Virochip assay from start to finish (~24 hour turnaround time), including sample nucleic acid extraction, PCR amplification using random primers, fluorescent dye incorporation, and microarray hybridization, scanning, and analysis.

Using a Pan-Viral Microarray Assay Virochip to Screen Clinical Samples for Viral Pathogens

The Virochip is a pan-viral microarray designed to simultaneously detect all known viruses as well as novel viruses on the basis of conserved sequence homology. Here we demonstrate how to run a Virochip assay to analyze clinical samples for the presence of both known and unknown viruses.

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence ...

Immunology and Infection

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Amplifying viral genes and quantifying HIV-1 RNA in HIV-1 infected individuals with viral loads below the limit of detection by standard assays (below 50-75 copies/ml) is necessary to gain insight to viral dynamics and virus host interactions in patients who naturally control the infection and those who are on combination antiretroviral therapy (cART). 
Here we describe how to amplify viral genomes by single genome sequencing (the SGS protocol) 13, 19 and how to accurately quantify HIV-1 RNA in patients with low viral loads (the single-copy assay (SCA) protocol) 12, 20. 
The single-copy assay is a real-time PCR assay with sensitivity depending on the volume of plasma being assayed. If a single virus genome is detected in 7 ml of plasma, then the RNA copy number is reported to be 0.3 copies/ml. The assay has an internal control testing for the efficiency of RNA extraction, and controls for possible amplification from DNA or contamination. Patient samples are measured in triplicate.
The single-genome sequencing assay (SGS), now widely used and considered to be non-labor intensive 3, 7, 12, 14, 15,is a limiting dilution assay, in which endpoint diluted cDNA product is spread over a 96-well plate. According to a Poisson distribution, when less than 1/3 of the wells give product, there is an 80% chance of the PCR product being resultant of amplification from a single cDNA molecule. SGS has the advantage over cloning of not being subjected to resampling and not being biased by PCR-introduced recombination 19. However, the amplification success of SCA and SGS depend on primer design. Both assays were developed for HIV-1 subtype B, but can be adapted for other subtypes and other regions of the genome by changing primers, probes, and standards.

Quantifying levels of HIV-1 RNA in plasma and sequencing single HIV-1 genomes from individuals with viral loads below the limit of detection (50-75 copies/ml) is difficult. Here we describe how to extract and quantify plasma viral RNA using a real time PCR assay that reliably measures HIV-1 RNA down to 0.3 copies/ml and how to amplify viral genomes by single genome sequencing, from samples with very low viral loads.

Amplifying viral genes and quantifying HIV-1 RNA in HIV-1 infected individuals with viral loads below the limit of detection by standard assays (below ...

High-throughput, Automated Extraction of DNA and RNA from Clinical Samples using TruTip Technology on Common Liquid Handling Robots

TruTip is a simple nucleic acid extraction technology whereby a porous, monolithic binding matrix is inserted into a pipette tip. The geometry of the monolith can be adapted for specific pipette tips ranging in volume from 1.0 to 5.0 ml. The large porosity of the monolith enables viscous or complex samples to readily pass through it with minimal fluidic backpressure. Bi-directional flow maximizes residence time between the monolith and sample, and enables large sample volumes to be processed within a single TruTip. The fundamental steps, irrespective of sample volume or TruTip geometry, include cell lysis, nucleic acid binding to the inner pores of the TruTip monolith, washing away unbound sample components and lysis buffers, and eluting purified and concentrated nucleic acids into an appropriate buffer. The attributes and adaptability of TruTip are demonstrated in three automated clinical sample processing protocols using an Eppendorf epMotion 5070, Hamilton STAR and STARplus liquid handling robots, including RNA isolation from nasopharyngeal aspirate, genomic DNA isolation from whole blood, and fetal DNA extraction and enrichment from large volumes of maternal plasma (respectively).

TruTip is a simple nucleic acid extraction technology whereby a porous, monolithic binding matrix is inserted into a pipette tip. Consequently, the sample preparation format is compatible with most liquid handling instruments, and can be used for many medium to high-throughput clinical applications and sample types.

TruTip is a simple nucleic acid extraction  technology whereby a porous, monolithic binding matrix is inserted into a  pipette tip. The geometry of the ...

Bioengineering

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...

Genetics

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Whole genome sequencing can be used to characterize and to trace viral outbreaks. Nanopore-based whole genome sequencing protocols have been described for several different viruses. These approaches utilize an overlapping amplicon-based approach which can be used to target a specific virus or group of genetically related viruses. In addition to confirmation of the virus presence, sequencing can be used for genomic epidemiology studies, to track viruses and unravel origins, reservoirs and modes of transmission. For such applications, it is crucial to understand possible effects of the error rate associated with the platform used. Routine application in clinical and public health settings require that this is documented with every important change in the protocol. Previously, a protocol for whole genome Usutu virus sequencing on the nanopore sequencing platform was validated (R9.4 flowcell) by direct comparison to Illumina sequencing. Here, we describe the method used to determine the required read coverage, using the comparison between the R10 flow cell and Illumina sequencing as an example.

We previously validated a protocol for amplicon-based whole genome Usutu virus (USUV) sequencing on a nanopore sequencing platform. Here, we describe the methods used in more detail and determine the error rate of the nanopore R10 flow cell.

Whole genome sequencing can be used to characterize and to trace viral outbreaks. Nanopore-based whole genome sequencing protocols have been described for ...

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Wastewater-based epidemiology has emerged as a promising and efficacious surveillance system for SARS-CoV-2 and other infectious diseases in many nations. The process typically involves wastewater concentration, nucleic acid extraction, amplification of selected genomic segments, and detection and quantification of the amplified genomic segment. This methodology can similarly be leveraged to detect and quantify infectious agents, such as SARS-CoV-2, in air samples. Initially, SARS-CoV-2 was presumed to spread primarily through close personal contact with droplets generated by an infected individual while speaking, sneezing, coughing, singing, or breathing. However, a growing number of studies have reported the presence of SARS-CoV-2 RNA in the air of healthcare facilities, establishing airborne transmission as a viable route for the virus. This study presents a composite of established protocols to facilitate environmental detection, quantification, and sequencing of viruses from both wastewater and air samples.

This protocol aims to quantify SARS-CoV-2 RNA in wastewater and air samples to be used for wastewater-based epidemiology studies and to assess the exposure risk to SARS-CoV-2 in indoor and outdoor aerosols. This protocol also describes a tiled amplicon long-template sequencing approach for SARS-CoV-2 whole genome characterization.

Wastewater-based epidemiology has emerged as a promising and efficacious surveillance system for SARS-CoV-2 and other infectious diseases in many nations. ...

Environment

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

Nanoliter scale real-time PCR uses spatial multiplexing to allow multiple assays to be run in parallel on a single plate without the typical drawbacks of combining reactions together. We designed and evaluated a panel based on this principle to rapidly identify the presence of common disease agents in dogs and horses with acute respiratory illness. This manuscript describes a nanoscale diagnostic PCR workflow for sample preparation, amplification, and analysis of target pathogen sequences, focusing on procedures that are different from microliter scale reactions. In the respiratory panel presented, 18 assays were each set up in triplicate, accommodating up to 48 samples per plate. A universal extraction and pre-amplification workflow was optimized for high-throughput sample preparation to accommodate multiple matrices and DNA and RNA based pathogens. Representative data are presented for one RNA target (influenza A matrix) and one DNA target (equine herpesvirus 1). The ability to quickly and accurately test for a comprehensive, syndrome-based group of pathogens is a valuable tool for improving efficiency and ergonomics of diagnostic testing and for acute respiratory disease diagnosis and management.

High-throughput testing of DNA and RNA based pathogens by nanoscale PCR is described using a syndromic canine and equine respiratory PCR panel.

Nanoliter scale real-time PCR uses spatial multiplexing to allow multiple assays to be run in parallel on a single plate without the typical drawbacks of ...

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes

This metagenome approach is used to identify plant viruses with circular DNA genomes and their transcripts. Often plant DNA viruses that occur in low titers in their host or cannot be mechanically inoculated to another host are difficult to propagate to achieve a greater titer of infectious material. Infected leaves are ground in a mild buffer with optimal pH and ionic composition recommended for purifying most bacilliform Para retroviruses. Urea is used to break up inclusion bodies that trap virions and to dissolve cellular components. Differential centrifugation provides further separation of virions from plant contaminants. Then proteinase K treatment removes the capsids. Then the viral DNA is concentrated and used for next-generation sequencing (NGS). The NGS data are used to assemble contigs which are submitted to NCBI-BLASTn to identify a subset of virus sequences in the generated dataset. In a parallel pipeline, RNA is isolated from infected leaves using a standard column-based RNA extraction method. Then ribosome depletion is carried out to enrich for a subset of mRNA and virus transcripts. Assembled sequences derived from RNA sequencing (RNA-seq) were submitted to NCBI-BLASTn to identify a subset of virus sequences in this dataset. In our study, we identified two related full-length badnavirus genomes in the two datasets. This method is preferred to another common approach which extracts the aggregate population of small RNA sequences to reconstitute plant virus genomic sequences. This latter metagenomic pipeline recovers virus related sequences that are retro-transcribing elements inserted into the plant genome. This is coupled to biochemical or molecular assays to further discern the actively infectious agents. The approach documented in this study, recovers sequences representative of replicating viruses that likely indicate active virus infection.

Here we present a new approach to identify plant viruses with double-strand DNA genomes. We use standard methods to extract DNA and RNA from infected leaves and carry out next-generation sequencing. Bioinformatic tools assemble sequences into contigs, identify contigs representing virus genomes and assign genomes to taxonomic groups.

This metagenome approach is used to identify plant viruses with circular DNA genomes and their transcripts. Often plant DNA viruses that occur in low ...

Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs

To control community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the 2020 global pandemic, most countries implemented strategies based on direct human testing, face covering, and surface disinfection. Under the assumption that the main route of transmission includes aerosols and respiratory droplets, efforts to detect SARS-CoV-2 in fomites have focused on locations suspected of high prevalence (e.g., hospital wards, cruise ships, and mass transportation systems). To investigate the presence of SARS-CoV-2 on surfaces in the urban environment that are rarely cleaned and&#160;seldomly disinfected, 350 citizens were enlisted from the greater San Diego County. In total, these citizen scientists collected 4,080 samples. An online platform was developed to monitor sampling kit delivery and pickup, as well as to collect sample data. The sampling kits were mostly built from supplies available in pandemic-stressed stores. Samples were processed using reagents that were easy to access despite the recurrent supply shortage. The methods used were highly sensitive and resistant to inhibitors that are commonly present in environmental samples. The proposed experimental design and processing methods were successful at engaging numerous citizen scientists who effectively gathered samples from diverse surface areas. The workflow and methods described here are relevant to survey the urban environment for other viruses, which are of public health concern and pose a threat for&#160;future pandemics.

A citizen science project was designed to recruit San Diego residents to collect environmental samples for SARS-CoV-2. A multilingual web-based platform was created for data submission using a user-friendly mobile device interface. A laboratory information management system facilitated the collection of thousands of geographically diverse samples with real-time outcome tracking.

To control community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the 2020 global pandemic, most countries ...

Biology

A Nanopore-Based Genomic Approach to Control Rabies in Low-Income Countries

Whole Genome Sequencing for Rapid Characterization of Rabies Virus Using Nanopore Technology

Genomic data can be used to track the transmission and geographic spread of infectious diseases. However, the sequencing capacity required for genomic surveillance remains limited in many low- and middle-income countries (LMICs), where dog-mediated rabies and/or rabies transmitted by wildlife such as vampire bats pose major public health and economic concerns. We present here a rapid and affordable sample-to-sequence-to-interpretation workflow using nanopore technology. Protocols for sample collection and the diagnosis of rabies are briefly described, followed by details of the optimized whole genome sequencing workflow, including primer design and optimization for multiplex polymerase chain reaction (PCR), a modified, low-cost sequencing library preparation, sequencing with live and offline base calling, genetic lineage designation, and phylogenetic analysis. Implementation of the workflow is demonstrated, and critical steps are highlighted for local deployment, such as pipeline validation, primer optimization, inclusion of negative controls, and the use of publicly available data and genomic tools (GLUE, MADDOG) for classification and placement within regional and global phylogenies. The turnaround time for the workflow is 2-3 days, and the cost ranges from $25 per sample for a 96 sample run to $80 per sample for a 12 sample run. We conclude that setting up rabies virus genomic surveillance in LMICs is feasible and can support progress toward the global goal of zero dog-mediated human rabies deaths by 2030, as well as enhanced monitoring of wildlife rabies spread. Moreover, the platform can be adapted for other pathogens, helping to build a versatile genomic capacity that contributes to epidemic and pandemic preparedness.

Author Spotlight: A Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings 

Here, we present a rapid and cost-effective workflow for characterizing rabies virus (RABV) genomes using nanopore technology. The workflow is intended to support genomics-informed surveillance at a local level, providing information on circulating RABV lineages and their placement within regional phylogenies to guide rabies control measures.

Genomic data can be used to track the transmission and geographic spread of infectious diseases. However, the sequencing capacity required for genomic ...