This work was supported by Wellcome [207569/Z/17/Z, 224670/Z/21/Z], Newton funding from the Medical Research Council [MR/R025649/1] and the Philippines Department of Science and Technology (DOST), the UK Research and Innovation Global effort on COVID-19 [MR/V035444/1], the University of Glasgow Institutional Strategic Support Fund [204820], Medical Research Council New Investigator Award (KB) [MR/X002047/1], and International Partnership Development Fund, a DOST British Council-Philippines studentship (CB), a National Institute for Health Research [17/63/82] GemVi scholarship (GJ), and University of Glasgow studentships from the MVLS DTP (KC) [125638-06], the EPSRC DTP (RD) [EP/T517896/1], and the Wellcome IIB DTP (HF) [218518/Z/19/Z]. We are grateful to colleagues and collaborators who have supported this work: Daniel Streicker, Alice Broos, Elizabeth Miranda, DVM, Daria Manalo, DVM, Thumbi Mwangi, Kennedy Lushasi, Charles Kayuki, Jude Karlo Bolivar, Jeromir Bondoc, Esteven&#160;Balbin, Ronnel Tongohan, Agatha Ukande, Davis Kuchaka, Mumbua Mutunga, Lwitiko Sikana, and Anna Czupryna.

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

The authors have nothing to disclose.

An accessible RABV, nanopore-based, whole genome sequencing workflow was developed by Brunker et al.61, using resources from the ARTIC network46. Here, we present an updated workflow, with complete sample-to-sequence-to-interpretation steps. The workflow details the preparation of brain tissue samples for whole genome sequencing, presents a bioinformatics pipeline to process reads and generate consensus sequences, and highlights two rabies-specific tools to automate lineage assignment and determine phylogenetic context. The updated workflow also provides comprehensive instructions for the setup of appropriate computational and laboratory workspaces, with considerations for implementation in different contexts (including low-resource settings). We have demonstrated the successful implementation of the workflow in both academic and research institute settings in four RABV endemic LMICs with no or limited genomic surveillance capacity. The workflow has proven resilient to application across diverse settings, and comprehensible by users with varying expertise.
This workflow for RABV sequencing is the most comprehensive publicly available protocol (covering sample-to-sequence-to-interpretation steps) and specifically adapted to reduce both startup and running costs. The time and cost required for library preparation and sequencing with nanopore technology is greatly reduced relative to other platforms, such as Illumina61, and continual technology developments are improving sequence quality and accuracy to be comparable with Illumina62.
This protocol is designed to be resilient in diverse low-resource contexts. By referring to the troubleshooting and modifications guidance provided alongside the core protocol, users are supported to adapt the workflow to their needs. The addition of user-friendly bioinformatic tools to the workflow constitutes a major development to the original protocol, providing rapid and standardized methods that can be applied by users with minimal prior bioinformatics experience to interpret sequence data in local contexts. The capacity to do this in situ is often limited by the need to have specific programming and phylogenetic skills, which require an intensive and long-term skills training investment. While this skillset is important to thoroughly interpret sequence data, basic and accessible interpretation tools are equally desirable in order to capacitate local &#34;sequencing champions&#34;, whose core expertise may be wet lab based, enabling them to interpret and take ownership over their data.
As the protocol has been undertaken for a number of years in several countries, we now can provide guidance on how to optimize multiplex primer schemes to improve coverage and deal with accumulated diversity. Efforts have also been made to help users improve the cost-effectiveness or to allow for ease of procurement in a given region, which is typically a challenge for the sustainability of molecular approaches63. For example, in Africa (Tanzania, Kenya, and Nigeria), we opted for blunt/TA ligase master mix at the adapter ligation step, which was more readily available from local suppliers and a cheaper alternative to other ligation reagents.
From experience, there are several ways of reducing the cost per sample and per run. Reducing the number of samples per run (e.g., from 24 down to 12 samples) can extend the life of flow cells over multiple runs, whereas increasing the number of samples per run maximizes the time and reagents. In our hands, we were able to wash and reuse flow cells for one in every three sequencing runs, enabling an additional 55 samples to be sequenced. Washing the flow cell immediately after use, or if not possible, removing the waste fluid from the waste channel after every run, seemed to preserve the number of pores available for a second run. Taking into consideration the initial number of pores available in a flow cell, one run can also be optimized to plan how many samples to run in a particular flow cell.
Though the workflow aims to be as comprehensive as possible, with the addition of detailed guidance and signposted resources, the procedure is still complex and can be daunting for a new user. The user is encouraged to seek in-person training and support, ideally locally, or alternatively through external collaborators. In the Philippines for example, a project on capacity building within regional laboratories for SARS-CoV-2 genomic surveillance using ONT has developed core competencies among health care diagnosticians that are readily transferrable to RABV sequencing. Important steps, such as SPRI bead clean up, can be difficult to master without hands-on training, and ineffective clean up can damage the flow cell and compromise the run. Sample contamination is always a major concern when amplicons are being processed in the lab and can be difficult to eliminate. In particular, cross-contamination between samples is extremely difficult to detect during post-run bioinformatics. Good laboratory technique and practices, such as maintaining clean work surfaces, separating pre- and post-PCR areas, and incorporating negative controls, are imperative to ensure quality control. The fast pace of nanopore sequencing developments is both an advantage and disadvantage for routine RABV genomic surveillance. Continuing improvements to nanopore&#39;s accuracy, accessibility, and protocol repertoire widen and improve the scope for its application. However, the same developments make it challenging to maintain standard operating procedures and bioinformatic pipelines. In this protocol, we provide a document assisting the transition from older to current nanopore library preparation kits (Table of Materials).
A common roadblock to sequencing in LMICs is accessibility, including not only the cost but also the ability to procure consumables in a timely manner (in particular sequencing reagents, which are relatively new to procurement teams and suppliers) and computational resources, as well as simply having access to stable power and the internet. Using portable nanopore sequencing technology as the foundation of this workflow helps with many of these accessibility issues, and we have demonstrated the use of our protocol across a range of settings, conducting the full protocol and analysis in-country. Admittedly, procuring equipment and sequencing consumables in a timely manner remains a challenge and, in many instances, we were forced to carry or ship reagents from the UK. However, in some areas, we were able to rely entirely on local supply routes for reagents, benefiting from investment in SARS-CoV-2 sequencing (e.g., the Philippines) that has streamlined procurement processes and begun to normalize the application of pathogen genomics.
The need for a stable internet connection is minimized by one-time-only installs; for instance, GitHub repositories, software download, and nanopore sequencing itself only require internet access to start the run (not throughout) or can be performed completely offline with agreement from the company. If mobile data is available, a phone can be used as a hotspot to the laptop to begin the sequencing run, before disconnecting for the run duration. When routinely processing samples, data storage requirements can grow rapidly, and ideally data would be stored on a server. Otherwise, solid state drive (SSD) hard drives are relatively cheap to source.
While we recognize that there are still barriers to genomic surveillance in LMICs, increasing investment in building genomics accessibility and expertise (e.g., Africa Pathogen Genomics Initiative [Africa PGI])64 suggests that this situation will improve. Genomic surveillance is critical for pandemic preparedness6, and capacity can be established through routinizing the genomic surveillance of endemic pathogens such as RABV. Global disparities in sequencing capacities highlighted during the SARS-CoV-2 pandemic should be a driver of catalytic change to address these structural inequities.
This sample-to-sequence-to-interpretation workflow for RABV, including accessible bioinformatics tools, has the potential to be used to guide control measures targeting the goal of zero human deaths from dog-mediated rabies by 2030, and ultimately for the elimination of RABV variants. Combined with relevant metadata, genomic data generated from this protocol facilitates rapid RABV characterization during outbreak investigations and in the identification of circulating lineages in a country or region60,61,65. We illustrate our pipeline mostly using examples from dog-mediated rabies; however, the workflow is directly applicable to wildlife rabies. This transferability and low cost minimize the challenges in making routine sequencing easily available, not only for rabies but also for other pathogens46,66,67, to improve disease management and control.

The rabies virus (RABV) is a lyssavirus in the Rhabdoviridae family that causes a fatal neurological disease in mammals1. Although rabies is 100% preventable by vaccination, it remains a major public health and economic concern in endemic countries. Of the 60,000 human rabies deaths estimated to occur each year, over 95% are in Africa and Asia where dogs are the primary reservoir2. In contrast, dog vaccination has led to the elimination of dog-mediated rabies across Western Europe, North America, and much of Latin America. In these regions, reservoirs of rabies are now restricted to wildlife, such as bats, raccoons, skunks, and wild canids3. Across Latin America, the common vampire bat is a problematic source of rabies due to regular spillover transmission from bats to both humans and livestock during nightly blood feeding4. The annual global economic impact of rabies is estimated to be $8.6 billion, with livestock losses accounting for 6%5.
Sequence data from viral pathogens combined with metadata on the timing and source of infections can provide robust epidemiological insights6. For RABV, sequencing has been used to investigate the origin of outbreaks7,8, identify host associations with wildlife or domestic dogs8,9,10,11,12, and trace sources of human cases13,14. Outbreak investigations using phylogenetic analysis have indicated that rabies emerged in the formerly rabies-free province of Bali, Indonesia, through a single introduction from the nearby endemic areas of Kalimantan or Sulawesi15. Meanwhile, in the Philippines, an outbreak on Tablas Island, Romblon Province was proven to be introduced from the main island of Luzon16. Viral genomic data have also been used to better understand pathogen transmission dynamics required for targeting control measures geographically. For example, genomic characterization of RABV illustrates the geographic clustering of clades17,18,19, co-circulation of lineages20,21,22, human-mediated viral movement17,23,24, and metapopulation dynamics25,26.
Disease monitoring is one important function of genomic surveillance that has been enhanced with the global increase in sequencing capacity in response to the SARS-CoV-2 pandemic. Genomic surveillance has supported the real-time tracking of SARS-COV-2 variants of concern27,28 and associated countermeasures6. Advances in accessible sequencing technology, such as nanopore technology, have led to improved and more affordable protocols for the rapid sequencing of both human29,30,31,32 and animal33,34,35 pathogens. However, in many rabies endemic countries, there are still barriers to operationalizing pathogen genomic surveillance, as shown by global disparities in SARS-CoV-2 sequencing capacity36. Limitations in laboratory infrastructure, supply chains, and technical knowledge make the establishment and routinization of genomic surveillance challenging. In this paper, we demonstrate how an optimized, rapid, and affordable whole genome sequencing workflow can be deployed for RABV surveillance in resource-limited settings.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Brand name</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing software 
			(MinKnow)</td>
			<td>Oxford Nanopore Technologies</td>
			<td>https://community.nanoporetech.com/downloads</td>
			<td></td>
		</tr>
		<tr>
			<td>Bioinformatics tool kit 
			(Guppy)</td>
			<td>Oxford Nanopore Technologies</td>
			<td>https://community.nanoporetech.com/docs/prepare/library_prep_protocols/Guppy-protocol/v/gpb_2003_v1_revao_14dec2018</td>
			<td></td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Thermal cycler 
			(miniPCR&#8482; mini16 thermal cycler)</td>
			<td>Cambio</td>
			<td>MP-QP-1016-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Homogenizer 
			(Precellys Evolution Touch Homogenizer)</td>
			<td>Bertin Instruments</td>
			<td>EQ02520-300</td>
			<td></td>
		</tr>
		<tr>
			<td>Cold Racks (0.2-0.5mL) 
			(PCR Mini-cooler with transparent lid)</td>
			<td>BRAND&#160;</td>
			<td>781260</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipettor</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F1000L, 1000 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10030</td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F100L, 100 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10024</td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F10L, 10 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10020</td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F1L, 1 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10025</td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F20L, 20 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10021</td>
			<td></td>
		</tr>
		<tr>
			<td>(Pipetman L Fixed F250L, 250 uL)</td>
			<td>Gilson&#160;</td>
			<td>SKU: FA10026</td>
			<td></td>
		</tr>
		<tr>
			<td>Fluorometer 
			(Qubit&#160; 4 Fluorometer)&#160;</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>Q33238</td>
			<td></td>
		</tr>
		<tr>
			<td>Laptop&#160; 
			(Any brand with ~2 GB of drive space, minimum of 512 GB storage space, msi installer [GPU])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge 
			(Refrigerated centrifuge)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>75004081</td>
			<td></td>
		</tr>
		<tr>
			<td>Vortex mixer 
			(Basic vortex mixer)&#160;</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>88882011</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnetic rack 
			(DynaMag -2 Magnet)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>12321D</td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing device 
			(MinION)</td>
			<td>Oxford Nanopore Technologies</td>
			<td>MinION Mk1B</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA Extraction&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>RNA extraction kit 
			(Qiagen RNEasy Mini Kit 250)</td>
			<td>Qiagen</td>
			<td>74106</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA stabilizing reagents&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(RNA later)&#160;</td>
			<td>Invitrogen</td>
			<td>AM7020</td>
			<td></td>
		</tr>
		<tr>
			<td>(DNA/RNA Shield)</td>
			<td>Zymo Research</td>
			<td>R1100-50</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Nuclease-free Water 
			(Nuclease-free Water [not&#160; DEPC-treated])</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>AM9937</td>
			<td></td>
		</tr>
		<tr>
			<td>Master mix for first strand cDNA synthesis 
			(LunaScript RT SuperMix Kit)</td>
			<td>New England Biolabs</td>
			<td>E3010S</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA amplification master mix 
			(Q5&#174; Hot Start High-Fidelity 2X Master Mix [NEB])</td>
			<td>New England Biolabs</td>
			<td>M0494L</td>
			<td></td>
		</tr>
		<tr>
			<td>Primer (Scheme) 
			(Custom DNA oligos)</td>
			<td>Invitrogen</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>SPRI Bead Clean-up</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>SPRI beads 
			(Aline Biosciences PCR Clean DX )</td>
			<td>Cambio</td>
			<td>AL-AC1003-50</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol, Pure Absolute, &#62;99.8% (GC) [Riedel-De Haen]</td>
			<td>Merck</td>
			<td>818760</td>
			<td></td>
		</tr>
		<tr>
			<td>Short Fragment buffer 
			(SFB expansion pack)</td>
			<td>Oxford Nanopore Technologies</td>
			<td>EXP-SFB001</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA Quantification</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DNA quantification kit 
			(Qubit&#174; dsDNA HS Assay Kit)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>Q32854</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA quantification assay tubes 
			(Qubit&#8482; Assay Tubes)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr>
			<td>End Prep and barcoding 
			(Qubit&#8482; Assay Tubes)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>End Prep master mix 
			(NEBNext Ultra End Repair/dA-Tailing Module)</td>
			<td>New England Biolabs</td>
			<td>E7546L</td>
			<td></td>
		</tr>
		<tr>
			<td>Barcoding kit</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 9&#160;</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 9&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native Barcoding Expansion 1-12)</td>
			<td></td>
			<td>EXP-NBD104&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native Barcoding Expansion 13-24)&#160;</td>
			<td></td>
			<td>EXP-NBD114&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native Barcoding Expansion 96)</td>
			<td></td>
			<td>EXP-NBD196</td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 14</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 14</td>
			<td></td>
		</tr>
		<tr>
			<td>(not compatible)&#160;</td>
			<td></td>
			<td>(not compatible)&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native Barcoding Kit 24 V14)</td>
			<td></td>
			<td>SQK-NBD114.24</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native Barcoding Kit 96 V14)</td>
			<td></td>
			<td>SQK-NBD114.96</td>
			<td></td>
		</tr>
		<tr>
			<td>Ligation mastermix 
			(Blunt/TA Ligase Master Mix)</td>
			<td>New England Biolabs</td>
			<td>M0367S</td>
			<td></td>
		</tr>
		<tr>
			<td>Adapter Ligation</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Adapter ligation master mix</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(NEBNext&#160; Quick Ligation Module)</td>
			<td>New England Biolabs</td>
			<td>E6056S&#160;&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>(NEBNext Ultra II Ligation Module)&#160;</td>
			<td>New England Biolabs</td>
			<td>E7595S</td>
			<td></td>
		</tr>
		<tr>
			<td>(Blunt/TA Ligase Master Mix)</td>
			<td>New England Biolabs</td>
			<td>M0367S</td>
			<td></td>
		</tr>
		<tr>
			<td>Adapter mix</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 9&#160;</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 9 
			EXP-AMII001</td>
			<td></td>
		</tr>
		<tr>
			<td>(Adapter Mix II [AMII])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 14</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 14 
			EXP-NBA114</td>
			<td></td>
		</tr>
		<tr>
			<td>(Native adapter [NA])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flowcell priming kit</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 9&#160;</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 9 
			EXP-FLP002</td>
			<td></td>
		</tr>
		<tr>
			<td>(Flush Buffer [FB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(Flush Tether [FT])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 14</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 14 
			EXP-FLP004</td>
			<td></td>
		</tr>
		<tr>
			<td>(Flow Cell Flush [FCF])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(Flow Cell Tether [FCT])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ligation Sequencing Kit&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 9&#160;</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 9 
			SQK-LSK109</td>
			<td></td>
		</tr>
		<tr>
			<td>Adapter Mix 
			(Adapter Mix [AMX])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ligation Buffer 
			(Ligation buffer [LNB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Short Fragment Buffer 
			(Short Fragment buffer [SFB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing Buffer 
			(Sequencing Buffer [SQB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Elution Buffer 
			(Elution buffer [EB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Loading Beads 
			(Loading Beads [LB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing Tether 
			(Sequencing Tether [SQT])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 14</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 14 
			SQK-LSK114</td>
			<td></td>
		</tr>
		<tr>
			<td>Adapter Mix 
			(Ligation Adapter [LA])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ligation Buffer 
			(Ligation buffer [LNB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Short Fragment Buffer 
			(Short Fragment buffer [SFB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing Buffer 
			(Sequencing Buffer [SB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Elution Buffer 
			(Elution buffer [EB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Loading Beads 
			(Loading Beads [LIB])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing Tether 
			(Flow Cell Tether [FCT])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Library solution 
			(Library solution [LIS])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flush buffer 
			(Flow Cell Flush [FCF])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flow Cell&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 9&#160;</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 9 
			FLO-MIN106D</td>
			<td></td>
		</tr>
		<tr>
			<td>(Flow Cell&#160; [R9.4.1])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>*Chemistry 14</td>
			<td>Oxford Nanopore Technologies</td>
			<td>*Chemistry 14 
			FLO-MIN114</td>
			<td></td>
		</tr>
		<tr>
			<td>(Flow Cell&#160; [R10.4.1])</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flow Cell wash&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Flowcell wash kit 
			(Flow cell wash kit)</td>
			<td>Oxford Nanopore Technologies</td>
			<td>EXP-WSH004</td>
			<td></td>
		</tr>
		<tr>
			<td>Consummables&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Surface decontaminant&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>(DNA Away Surface Decontaminant, Squeeze Bottle [Molecular Bio])</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>7010PK</td>
			<td></td>
		</tr>
		<tr>
			<td>(RNase Away Surface Decontaminant, Bottle [Molecular Bio])</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>7002PK</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR 8-Tube Strip 0.2ml, individual cap 
			(PCR 8-Tube Strip 0.2ml, with Individual attached Flat Caps, Sterile, DNAse/RNAse, Pyrogen Free,Natural [Greiner])</td>
			<td>Greiner</td>
			<td>608281</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR Tube 0.2ml 
			(PCR Tube 0.2ml, Natural [Domed Cap] Bagged in 500s, Non-Sterile [Greiner])</td>
			<td>Greiner</td>
			<td>671201</td>
			<td></td>
		</tr>
		<tr>
			<td>1000&#181;L Filter Tips (500) 
			(Stacked 1000&#181;L Filter Tips [500])</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>11977724</td>
			<td></td>
		</tr>
		<tr>
			<td>100&#181;L Filter Tips (1000)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>11947724</td>
			<td></td>
		</tr>
		<tr>
			<td>10&#181;L Filter Tips (1000) 
			(Stacked 100&#181;L Filter Tips [1000])</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>11907724</td>
			<td></td>
		</tr>
		<tr>
			<td>Reinforced tubes&#160; tubes (2ml)&#160; with screw caps and o-rings 
			(Fisherbrand&#8482;&#160;Bulk tubes)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>15545809</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge tube (1.5ml) 
			(1.5 ml Eppendorf Tubes [500])</td>
			<td>Eppendorf</td>
			<td>1229888</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA LoBind Tubes&#160; (1.5ml) 
			(DNA LoBind Tubes)</td>
			<td>Thermofisher scientific/Fisher scientific</td>
			<td>10051232</td>
			<td></td>
		</tr>
		<tr>
			<td>Cryobabies labels</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Gloves (S/M/L)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Paper towel</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

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 

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

Our research uses advanced genomics to enhance pathogen surveillance in low and middle-income countries. And this helps us empower local researchers to answer five big questions, who, what, where, why, and when. And this can inform practical solutions on the ground.We use nanopore technology to decentralize sequencing. It's ease of use, portability, and cheaper costs relative to other platforms makes it ideal for low-resource settings. And the ability to rapidly sequence at the sample source means that we can do surveillance at the animal-human environment interface.We face challenges in obtaining whole genomes from samples with varying quality. Often, submissions from remote areas would be transported in poor storage conditions. And also, we have limited expertise in bioinformatic tools that would be useful in interpreting data.So these tools would be like MADDOG and drug-V GLUE. This could be used in interpreting data in a universal way to help initiate control. We're trying to demonstrate how they optimize the protocol for rapid sequences or for whole genomic sequences of rabies and to see how it can be adapted and be used in the low-income countries for sequencing of rabies so as to answer different questions on how it really is circulating, what is circulating, and when is it circulating?And this information are necessary for rabies elimination strategies. Viral genomic surveillance is now more accessible. However, guidance for data analysis and interpretation for local control efforts is more limited.Our protocol offers an end-to-end pipeline, empowering local scientists with frontline surveillance capabilities. Greater availability of viral genomes and methods for interpreting these data allows researchers to translate epidemiological insight into actionable information for government ministries or disease control programs and guide the decision-making process.

The sample-to-sequence-to-interpretation workflow for RABV described in this protocol has been used successfully in different laboratory conditions in endemic countries, such as Tanzania, Kenya, Nigeria, and the Philippines (Figure 4). The protocol was used on different sample types and conditions (Table 6): fresh and frozen brain tissue, cDNA and RNA extracts from brain tissue transported under cold chain for extended periods, and FTA cards with brain tissue smears.
Live basecalling using RAMPART (Figure 5) shows the almost real-time generation of reads and the percent coverage per sample. This is particularly useful in deciding when to stop the run and save the flow cell for reuse. Variation in run time was observed, with some finished in 2 h, while others could take more than 12 h for an adequate depth of coverage (x100) to be reached. We can also view regions with poor amplification; for example, Figure 6 shows a snapshot of one sequencing run where coverage profiles show some amplicons with very low amplification, indicating potentially problematic primers. By investigating these poorly amplifying regions more thoroughly, we have been able to identify primer mismatches, which will enable us to redesign and improve individual primers. Some primer schemes have shown more mismatches than others. This is observed in the East Africa primer scheme, as compared to the Philippines, in line with the targeted diversity, as the East Africa scheme aims to capture a much broader diversity.
RABV-GLUE42, a general-purpose resource for RABV genome data management, and MADDOG60, a lineage classification and nomenclature system, were used to compile and interpret resulting RABV sequences. Table 7 shows the major and minor clades circulating in each country assigned using RABV-GLUE. Also shown is a higher resolution classification of local lineages following the MADDOG assignment.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65414/65414fig01.jpg" /> 
Figure 1: Sample-to-sequence-to-interpretation workflow for RABV. Summarized steps are shown for (A) sample preparation, (B) PCR and library preparation, and (C) sequencing and bioinformatics up to analysis and interpretation. <a href="https://www.jove.com/files/ftp_upload/65414/65414fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65414/65414fig02.jpg" /> 
Figure 2: Primer scheme schematic. Annealing positions along the &#39;index reference genome&#39; (dark purple) for pairs of forward and reverse primers (half arrows), which are assigned in two separate pools: A (red) and B (green). Primer pairs generate 400 bp overlapping amplicons (blue) which are numbered sequentially along the index reference genome in the format &#39;scheme_name_X_DIRECTION&#39;, where &#39;X&#39; is a number referring to the amplicon generated by the primer and &#39;DIRECTION&#39; is either &#39;LEFT&#39; or &#39;RIGHT&#39;, describing the forward or reverse respectively. Odd or even values of &#39;X&#39; determine the pool (A or B, respectively). <a href="https://www.jove.com/files/ftp_upload/65414/65414fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65414/65414fig04.jpg" /> 
Figure 3: Nanopore flow cell48. Blue labels illustrate the different parts of the flow cell, including the priming port cover which covers the priming port where the priming solution is added, the SpotON sample port cover covering the sample port where the sample is added in a dropwise fashion, the waste ports 1 and 2, and the flow cell ID. <a href="https://www.jove.com/files/ftp_upload/65414/65414fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65414/65414fig03.jpg" /> 
Figure 4: Map showing the location where RABV sequencing was conducted using the optimized workflow in 2021 and 2022. Bubble size and color correspond to the number of sequences per location, where smaller and darker is fewer, while larger and lighter is more. <a href="https://www.jove.com/files/ftp_upload/65414/65414fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65414/65414fig05v2.jpg" /> 
Figure 5: Screenshot of RAMPART visualization in web browser. Barcode names are replaced by sample names according to the bioinformatic setup. The top three panels show summary plots for the whole run: depth of coverage of mapped reads for each barcode per nucleotide position on the index reference genome (top left, colored by barcode), summed mapped reads from all barcodes over time (top middle), and mapped reads per barcode (top right, colored by barcode). Lower panels show rows of plots per barcoded. From left to right: the depth of coverage of mapped reads per nucleotide position on the index reference genome (left), length distribution of mapped reads (middle), and proportion of nucleotide positions on the index reference genome which have obtained a 10x, 100x and 1,000x coverage of mapped reads over time (right). <a href="https://www.jove.com/files/ftp_upload/65414/65414fig05largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65414/65414fig06v2.jpg" /> 
Figure 6: An example read coverage across the genome for a rabies virus sample from the Philippines sequenced using the protocol.&#160;Read coverage at each nucleotide position in the genome is shown, alongside the position of the overlapping amplicons (1-41) used to generate the library. Spikes in the depth of coverage correspond to areas of amplicon overlap. Amplicons with a low depth of coverage correspond to areas of amplicon overlap. Amplicons with a low depth of coverage are highlighted in red indicating problematic regions that may require&#160;optimization. <a href="https://www.jove.com/files/ftp_upload/65414/65414fig06largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Table 1: Master mix and thermal cycler conditions for cDNA preparation. <a href="https://www.jove.com/files/ftp_upload/65414/Table 1.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Master mix and thermal cycler conditions for multiplex PCR. <a href="https://www.jove.com/files/ftp_upload/65414/Table 2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 3: Master mix and thermal cycler conditions for end-prep reaction. <a href="https://www.jove.com/files/ftp_upload/65414/Table 3.xlsx" target="_blank">Please click here to download this Table.</a>
Table 4: Master mix and thermal cycler conditions for barcoding. <a href="https://www.jove.com/files/ftp_upload/65414/Table 4.xlsx" target="_blank">Please click here to download this Table.</a>
Table 5: Adapter ligation master mix and final library dilution for sequencing. <a href="https://www.jove.com/files/ftp_upload/65414/Table-5_revised.zip" target="_blank">Please click here to download this Table.</a>
Table 6: The number of rabies virus whole genome sequences generated and the type of samples used in different countries using the sample-to-sequence-to-interpretation workflow. <a href="https://www.jove.com/files/ftp_upload/65414/Table 6.xlsx" target="_blank">Please click here to download this Table.</a>
Table 7: Major and minor clade assignments from RABV-GLUE and lineage assignments from MADDOG for sequences generated using the workflow. <a href="https://www.jove.com/files/ftp_upload/65414/Table 7.xlsx" target="_blank">Please click here to download this Table.</a>
Supplementary File 1: Primer scheme design and optimization, and amplicon read depth analysis. <a href="https://www.jove.com/files/ftp_upload/65414/Supplementary File 1.docx" target="_blank">Please click here to download this File.</a>
Supplementary File 2: Computational setup <a href="https://www.jove.com/files/ftp_upload/65414/Supplementary File 2.docx" target="_blank">Please click here to download this File.</a>
Supplementary File 3: RABV WGS protocol worksheet <a href="https://www.jove.com/files/ftp_upload/65414/Supplementary File 3- Worksheet.xlsx" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about A Cost-Effective Genomic Workflow for Advancing Rabies Control in Resource-Limited Settings at JoVE.com

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 ...

whole-genome-sequencing-for-rapid-characterization-rabies-virus-using

Research

JoVE Journal

Biology

Sample Preparation, RNA Extraction, PCR Clean Up, and Quantification for Whole Genome Sequencing of Rabies Virus (RABV)

Prepare two ceramic beads tubes by filling a two milliliter PCR tube with an approximately 200 microliter tube full of 1.4 millimeter ceramic beads and label the tube accordingly before transferring them inside the sterile hood. Add the recommended volume of lysis buffer provided in the RNA extraction kit to the labeled PCR tube. Get approximately a three millimeter cube from the brain sample confirmed with rabies infection using a wooden applicator and put it into a labeled tube with sample ID and 100 microliters of nuclease-free water into the tube labeled negative control.Disrupt the brain tissue manually using a wooden applicator stick and then vortex at maximum speed until complete tissue homogenization is achieved. Next, centrifuge the homogenized lysate. Transfer the supernatant to a newly labeled micro centrifuge tube using a pipette and use it for further RNA extraction steps, CDNA preparation, and PCR amplification.After the CDNA preparation and PCR amplification using primer pools A and B, perform PCR cleanup and quantification in the post PCR area. Aliquot SPRI beads into micro centrifuge tubes from the main bottle. These can be also prepared in advance.Store the tubes at four degrees celsius or keep them in a cold rack or ice. Next, warm the SPRI bead aliquot at approximately 20 degrees Celsius and thoroughly vortex to re-suspend the beads in the entire solution. Then in the 1.5 milliliter tubes, combine the primer pool A and primer pool B PCR products for each sample.Add water to bring the volume to 25 microliters if required before adding 25 microliters of SPRI beads to each combined product and mixing it. Incubate the mixture at room temperature for 10 minutes with occasional inverting or flicking of the tubes. Next, place the tubes on a magnetic rack until the separation of beads and solution.Once done, discard the supernatant without disturbing the bead pellet. Then give two washes of 30 seconds using freshly prepared 200 microliters of 80%ethanol and discard the ethanol. After the second wash, remove all traces of ethanol using a 10 microliter pipette tip.Air dry the pellet until trace ethanol has evaporated and the pellet changes from shiny to matte. Re-suspend the beads in 15 microliters of nuclease-free water to recover the cleaned DNA product and incubate at room temperature for 10 minutes. Separate the beads from the solution on a magnetic rack.After transferring the supernatant to a fresh 1.5 milliliter tube, prepare a one to 10 dilution of each sample in nuclease-free water. Measure the DNA concentration of each diluted sample with a highly sensitive and specific fluorimeter, following the manufacturer's instructions.

Sequencing, Live and Offline Basecalling, Analysis, and Interpretation of Rabies Virus (RABV) Genome

Begin the priming and loading the quality checked flow cell by flipping back the sequencing device lid and sliding the priming port cover clockwise, visualizing the priming port. To remove air bubbles, set a P 1000 pipette to 200 microliters and insert the pipette tip vertically into the priming port. Turn the wheel until a small volume entering the pipette tip is seen.Load 800 microliters of pre-prepared flow cell priming mix into the flow cell via the priming port to avoid introducing bubbles. Lift the sample port cover and load 200 microliters of the remaining priming mix into the flow cell via the priming port. To ensure the mixing of the loading beads, resuspend the library master mix by pipetting and dropwise, load 75 microliters to the flow cell via the sample port.Replace the sample port cover gently ensuring the bung enters the sample port. Close the priming port and replace the sequencing device lid. For live base calling, use Rampart.Use the Arctic RabV environment and work in the directory created for the Rampart output. Then type the Rampart command to navigate to the required paths. First, the Rampart specific scheme protocol, and next base called path, the mino fastq pass output folder for the run.Open a browser window and navigate to local host 3000 in the URL box. Wait for sufficient data to be base called before results appear on the screen. The top three panels show summary plots for the whole run.Plot one shows the depth of coverage of mapped reads for each barcode per nucleotide position on the index reference genome. Plot two shows mapped reads from all barcodes over time, and plot three shows mapped reads per barcode. Lower panels show rows of plots per barcode.The left shows the depth of coverage of mapped reads per nucleotide position on the index reference genome. The length distribution of mapped reads is in the middle. The proportion of nucleotide positions on the index reference genome obtaining 10x, 100x, and 1000x coverage of mapped reads over time is seen in the right corner.For lineage assignment of consensus sequences, use MadDog. Pull the MadDog repository from GitHub to ensure working with the latest version. Create a folder within the previously created local MadDog repository.Inside the folder, add the fastA file containing the consensus sequences. Also, add a metadata file to the folder. Ensure that this file is a CSV with four columns called ID, country, year and assignment.Pull the MadDog repository from GitHub to ensure working with the latest version. In the command line interface, activate the conda environment with a conda activate MADDOG command. In the command line interface, navigate to the MadDog repository folder.First, perform lineage assignment on sequences to check for potential abnormalities and identify if running the longer lineage designation step is appropriate by running the sh assignment. sh command. When prompted, enter Y to confirm that the repository is pulled and working with MadDog's latest version.When prompted, enter the folder name containing the fastA file within the MadDog repository. When the lineage assignment is complete, check the output file in the folder. If the output is as expected and multiple sequences are assigned to the same lineage, then run the lineage designation.While running lineage designation, delete the assignment output file just created. In the terminal inside the MadDog repository folder, run the command sh designation.sh. When prompted, enter Y to indicate that the repository is pulled and the work is being done with the most up-to-date version of MadDog.When prompted, enter the folder name within the MadDog repository folder containing the fastA file and metadata. The sample to sequence to interpretation workflow for rabies virus RABV was successfully used in different laboratory conditions in endemic countries such as Tanzania, Kenya, Nigeria, and the Philippines. The live base calling using Rampart showed the real-time generation of reads and the percent coverage per sample.A lineage classification and nomenclature system, MadDog, used to compile and interpret resulting RABV sequences showed the higher resolution classification of local lineages following the MadDog assignment.

2.7K Views.  University of Glasgow.  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.

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

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