Monkeypox viruses circulate in distantly related small mammal species and only diversified recently

doi:10.21203/rs.3.rs-414280/v2

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Monkeypox viruses circulate in distantly related small mammal species and only diversified recently

https://doi.org/10.21203/rs.3.rs-414280/v2

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We determined a near complete and complete monkeypox virus (Mpox) genome in an elephant shrew (Petrodromus tetradactylus), a squirrel (Funisciurus bayonii), and produced shorter sequencesobtained from two rats (Stochomys longicaudatus, Cricetomys sp. 2) originating from the Democratic Republic of the Congo. We also ran a series of molecular clock analyses that all agree on a recent, clearly post Dahomey gap opening diversification of Mpox. This suggests that, besides squirrels, a number of rodents and elephant shrews are involved in Mpox ecology, whose current genomic diversity and distribution was likely shaped in the last 1,000 years.

Terrestrial Ecology

Evolutionary Biology

monkeypox virus

virus genomes

Human monkeypox is a zoonotic disease caused by monkeypox virus (Mpox), a member of the Orthopoxvirus (OPXV) genus in the Poxviridae family. The clinical presentation generally resembles smallpox: after a mean incubation time of 8 days (4-14 days), most patients first experience fever and a few days later a characteristic rash^1,2. Case fatality rate is usually low in adults, but can reach well over 10% in children. A total of 24,400 cases are recorded between 1970-2018, the majority in the Democratic Republic of the Congo (DRC)³. The virus naturally occurs in Africa where two genetic clades have been discerned: a West African clade (Mpox-WA) that is only found in countries situated west of Cameroon, and a Congo Basin (Mpox-CB) clade only observed in Central Africa^1,2,4. In recent years, a significant increase in confirmed cases was noted in the DRC (up to 2,500 cases a year in 2013)³. While the Mpox-CB was generally considered to be more virulent and transmissible in humans (based on a low sample size)⁵, the recent Nigerian outbreak (2017-2018) provided evidence of increased virulence of Mpox-WA⁶. The rising incidence and human-to-human transmission for both strains in endemic areas highlight the need for a better understanding of the eco-epidemiological drivers of the disease³.

The presumptive animal source of primary human infections remains unidentified and the virus’ natural reservoir cryptic⁷. Mpox has only been isolated and their genome completely sequenced from three African endemic wild mammal species: a Thomas’s rope squirrel (Funisciurus anerythrus) in DRC, a sooty mangabey (Cercocebus atys atys) from the Taï National Park (TNP) in Côte d’Ivoire and a western chimpanzee (Pan troglodytes verus) also from TNP ^8–10. Whereas primates are assumed to be incidental hosts (not required for or contributing significantly to viral maintenance), different species of rodents such as Cricetomys, Graphiurus, Funisciurus and Heliosciurus spp. are considered to be potential natural hosts (required for viral maintenance) and maybe reservoirs (sources of infection for humans and other mammals) . However, empirical data to support these claims is scarce and mainly based on serological data or DNA amplicons without confirmation by sequencing^11–15.

Since 2010 we have been monitoring the biodiversity of small mammals and their pathogens in several areas in the Ituri and Tshopo provinces of the DRC. A subset (n=255) of samples (selection of samples that were completely submerged in ethanol, Supplementary excel file: 1), including tissues collected from rodents (n=96), shrews (n=92), elephant shrew (n=1) and bats (n=66) over a period of six years, was tested for the presence of Mpox DNA using two PCR assays targeting different viral genes (P4A and haemagglutinin). Five positives were confirmed by Sanger sequencing^16,17. Tissues from individuals representing four rodent species (Funisciurus anerythrus, Funisciurus bayonii, Stochomys longicaudatus and Cricetomys sp. 2 sensu¹⁸) and one elephant shrew (Petrodromus tetradactylus) contained Mpox DNA. By applying in-solution hybridization capture and high-throughput sequencing¹⁰, we successfully retrieved two complete Mpox genomes from F. anerythrus and P. tetradactylus, and one partial genome (59%) from F. bayonii. Therefore, Mpox appears to naturally circulate in multiple, distantly-related rodent species from at least three different families (Sciuridae, Muridae and Nesomyidae), as well as in elephant shrews (order Macroscelidea). While some of these detection events may reflect dead-end infections (e.g. elephant shrews), they are compatible with the hypothesis that Mpox has a broad host range and possibly a complex multi-host ecology¹⁹. The ability to infect multiple host species is also known for other OPXVs, including the well-studied cowpox virus (CPXV), which infects at least three rodent species (Microtus agrestis, Myodes glareolus and Apodemus sylvaticus) in the UK, sometimes leading to spillover into bovids¹⁴. Because OPXVs are relatively stable in the environment and able to infect susceptible hosts via multiple routes (respiratory, mucosal and parenteral), cross-species transmission of OPXVs is likely facilitated by indirect transmission and might happen frequently ¹⁹.

Although Mpox is able to infect multiple hosts, it does not necessarily imply that all hosts contribute to viral maintenance. In fact, it is often suggested that the majority of transmission events and pathogen maintenance are associated to one of a few key host species (e.g. the reservoir hosts, which are responsible for the majority of cross-species transmission events)²⁰. Consequently, much of the apparent complexity of such multi-host systems could be simplified by focussing on one or two key hosts within the small mammal community. The key position of these hosts may be the outcome of separate characteristics such as infection prevalence, population density and transmissibility²⁰. For example, while A. sylvaticus or M. agrestis populations can maintain CPXV in the absence of other mammal species (potentially due to their high population abundance), its transmission in M. glareolus populations largely depends on the presence A. sylvaticus or M. agrestis in the wildlife community²¹. It is possible that the maintenance of Mpox also depends on one or two key animal reservoirs (i.e. animals that need to be present in the wildlife community for the virus to survive), and that other species serve as auxiliary hosts. The results reported here add to the limited evidence suggesting that squirrels of the genus Funisciurus are potential key reservoirs for Mpox. Of all rodents, these hosts have shown the highest seroprevalence and have allowed for virus isolation and whole genome sequencing from multiple individuals^11,12,15. Within this genus, F. anerythrus perhaps sticks out as a particularly plausible key reservoir due to its social behaviour (more interaction with conspecifics) and higher densities than any other species of African tree squirrel, both characteristics facilitating intra-species viral transmission²².

Nevertheless, the fact that Mpox was first isolated from a Funisciurus squirrel might have biased our view on Mpox ecology, as most follow-up studies targeted squirrels. Similarly, the multimammate mouse (Mastomys natalensis) was for a long-time assigned to be the sole Lassa arenavirus (LASV) reservoir, as the virus was first isolated from this rodent species which is highly abundant around houses in areas where the disease is endemic. However, recent studies detected LASV in rodent communities without the multimammate mouse²³. This suggests that the status of ‘reservoir’ might often depend on the ecological circumstances or the sampling design of the study. For example, it might be that Mpox transmission is maintained by Funisciurus squirrels in areas where these are abundant, while other species may be involved in viral maintenance in areas where Funisciurus squirrels are less abundant, or absent.

Maximum likelihood (ML) and Bayesian phylogenetic analyses revealed that the Mpox found in the squirrel and elephant shrew are closely related to each other and fall within the diversity of Mpox strains found in humans in Central Africa (Fig 1), with the time to the most recent common ancestor (tMRCA) with the closest published genomes dated to 1959. Similarly, ML analyses performed on the partial Mpox genome found in the F. bayonii sample showed that it clusters with other Mpox-CB strains (Supplementary Fig. 2). Generating new sequences provided an opportunity to reassess the standing hypothesis that Mpox diversification essentially reflects ancient vicariance events (VE) caused by climate-induced forest contractions, such as the opening of the Dahomey gap (2,500 BC or the Last Glacial Maximum 19,000 BC)².

To test this notion, we ran a series of molecular clock analyses. After we validated the presence of a temporal signal in our dataset (Supplementary table 2), we used standard tip date-calibrated strict or relaxed molecular clock models in a Bayesian framework to estimate Mpox root age. We obtained similar estimates, with a time to the most recent common ancestor of all Mpox genomes around 600 y (root age: median 1434 AD). In these analyses, VE dates did not fall into the 95% HPD [767 AD-1818 AD], but to formally exclude these root ages we estimated the marginal likelihoods of models with tip date calibration only or a combination of tip date- and root age at VE-calibration. In all cases, models with enforced root age at VE were decisively rejected by Bayes factor comparisons (2ln BF>62; Supplementary table 3).

To further investigate the robustness of our tip-based estimation, we then verified whether a sampling bias in our dataset, such as that arising from intense sampling of similar sequences during an outbreak (e.g. the recent 2017-2018 Nigerian outbreak), may have led to an underestimation of Mpox root age, as was for example recently shown for Zaire ebolaviruses²⁴. To test for this, we analyzed phylogeny-informed subsamples of our dataset (from 49 sequences to 24, 12, and 6). We found that the temporal signal detected in the complete dataset was maintained in all subsampled datasets (Supplementary table 4). Bayesian molecular clock analyses using tip-dating failed at converging for the smallest dataset but provided interpretable results for the two others. Median root date estimates were pushed back by about 350 y (medians: 1046 and 1099 AD, respectively) and their 95% HPD still included the estimate derived from the complete dataset ([201 BC-1718 AD] and [660 BC-1842 AD], respectively), suggesting within-outbreak sampling did not significantly upwardly bias our root age estimate or, to the very least, not to the point of rescuing the VE hypothesis.

Molecular dating based on tip date calibration sometimes dramatically underestimates deep viral divergence times²⁵. These estimates then often disagree with those produced using alternative hypotheses based on ancient node calibration. The underlying conflict of short- and long-term substitution rates is known as the time-dependency of molecular rates (TDMR)²⁶. If the actual root age of Mpox corresponded to one of the VE dates, TDMR would be a likely explanation for the incompatibility of tip date- and root age at VE-calibration (Supplementary tables 2 and 3) and we would expect that a model accounting for this phenomenon would retrieve a more ancient diversification date. Therefore, we also implemented the recently published prisoner of war model (PoW). PoW explicitly models the decay of evolutionary rates due to saturation, is thought to be applicable to all major viral families including poxviruses (with appropriate parametrization), and does not require tip or node calibration²⁷. Using this model to rescale a Mpox ultrametric tree, we estimated the root age to be about 150y older than our initial estimate (1307 AD [95% HPD 1255-1364 AD]). Altogether, molecular clock analyses using different datasets and modeling approaches provide remarkably congruent estimates of Mpox root age, all comprised between 600 and 1000 years ago. This suggests that the geographic partitioning of Mpox genomic diversity into the Mpox-WA and Mpox-CB clades was not driven by the Dahomey gap opening or the Last Glacial Maximum.

In conclusion, the presence of Mpox DNA in diverse forest dwelling rodents and elephant shrews and new molecular clock analyses shed a new light on the ecology and evolution of Mpox. Mpox might well have a more complex ecology than often assumed and routinely navigate multiple host species. The recent divergence of the Mpox-WA and -CB lineages could still be due to a climatic event, e.g. the Medieval Warm Period (700-1,100BP)²⁸, but other mechanisms might also have played a role, especially considering Mpox broader potential host range. For example, these viruses may have circulated in distinct host communities and specialized on hosts now strictly endemic to a single region (e.g. F. bayonii has only been found in the DRC and Angola)²². A more accurate reconstruction of the ecological and evolutionary processes that have shaped Mpox diversity and distribution will likely require the implementation of large-scale, longitudinal studies of small mammal communities in WA and CB. Such are necessary to confirm the hypothesis that Funisciurus squirrels are indeed key Mpox natural reservoirs, or to support the hypothesis of ‘combined maintenance’ in the wildlife community.

Small mammals were trapped at different locations in Ituri and Tshopo provinces of the DRC between 2010 and 2016 using Sherman live traps, pit falls and mist nets (2,074 rodents, 992 insectivores and 525 bats). Captured animals were humanely euthanised (using isoflurane) and necropsied in situ. Tissue samples (kidney, liver and spleen) were stored in 75% ethanol and shipped to the University of Antwerp (Belgium), where samples were stored in the dark at room temperate. DNA was extracted from a mixture of different organs (spleen, kidney and liver) using the NucleoSpin tissue kit (Machery Nagel, Düren, Germany) according to the manufacturer’s instructions. Species identification was done based on morphological measurements and confirmed with mitochondrial DNA cytochrome b sequencing using L7 and H6 primers and 16S rRNA for shrews. The sequences obtained were compared with known sequences from GenBank and the African Mammalia database (http://projects.biodiversity.be/africanmammalia).

For Mpox screening, a TaqMan Real-time PCR targeting the OPXV P4A gene of all orthopoxviruses was performed in duplo on a subset of samples (see supplementary data1)¹⁷. Positives were confirmed using a conventional PCR targeting a 270bp fragment of the Mpox haemagglutinin (HA) gene¹⁶, Sanger sequenced and shipped to Robert-Koch Institute for whole genome sequencing as described in Patrono et al¹⁰. In short, Illumina-compatible libraries were built from fragmented DNA (250ng DNA in 50 µl EDTA TE buffer) using the NEBNext Ultra II kit and quantified using the KAPA HiFi library quantification kit. To increase the relative amount of Mpox DNA in the libraries with respect to background DNA, two rounds of 24h hybridization capture at 65°C were performed on all samples using 2-fold tiling 80-mer RNA baits (MYBaits®) designed to target orthopoxviruses ¹⁰. The enriched pool was diluted to 4nM and sequenced on a NextSeq platform (2x150 bp). Raw NGS reads were processed following the pipeline described in Patrono et al¹⁰ with an additional step to merge paired reads using the ClipAndMerge tool from Eager²⁹. Sequences KJ642616 and JX878411 were used for reference-based mapping to either a West African or Congo Basin clade Mpox genome, respectively. Since the two ends of MPOX genomes are inverted terminal repeats (ITRs) that contain many repetitive regions and indels, which can lead to difficult or erroneous assembly, the right ITR was removed from both reference sequences (from position 190,375 and 191567 in the KJ642616 and JX878411 sequence, respectively). Consensus sequences were called at positions covered by at least 20 reads (95% agreement) for Mpox from F. anerythrus and C. littoralis, whereas for F. bayonii calling was set to at least 2 reads (less on-target reads were obtained for this genome). For phylogenetic analyses, we downloaded all publicly available Mpox complete genomes from the National Center for Biotechnology Information (NCBI) database (n=61) and added the two complete genome sequences herein generated (accession numbers: MT724770 and MT724772). Genomes (n=63) were aligned using MAFFT v7 and conserved blocks were selected using GBlocks in Seaview v452, resulting in an alignment of 178,345 positions (see supplementary file: GBlocks). Upon removal of sites containing ambiguities (n=2,618), the alignment was reduced to variable sites (n=2,176) by stripping all identical sites (n=173,551) and collapsed to unique sequences (n=50) with the online tool FaBox v1.453. We ran recombination analyses with RDP4³⁰ and removed minor recombining fragments. We then ran exploratory phylogenetic analyses, to determine whether a temporal signal was likely to exist in this dataset. For this we used PhyML v.3 with smart model selection³¹ (GTR) to obtain an unrooted maximum likelihood (ML) tree (Supplementary Fig 1). A first analysis of the resulting tree in TempEst³² identified one outlier sequence (AF380338) that showed a suspiciously long branch; upon removal of this sequence a moderate temporal signal was detected (Rsq=0.33).

We continued by running formal molecular clock analyses in a Bayesian framework using BEAST v1.10.4³³. We assumed a coalescent tree shape prior (constant population size), performed multiple Bayesian Markov chain Monte Carlo (BMCMC) runs and checked multiple run convergence as well as appropriate sampling of the posterior (effective sample size > 200) using Tracer v1.7³⁴. We first wanted to confirm the presence of a temporal signal. To do this, we applied a recently suggested approach whereby for the same dataset for which tip dates are available the fits of two models are compared, one of which is informed by these tip dates (heterochronous model) while the other is not (isochronous model)³⁵. We estimated model marginal likelihoods using a generalized stepping-stone procedure and compared models using Bayes factors (BF); we considered support for one of the competing models was decisive where 2lnBF>10³⁶. We implemented the two most extreme forms of molecular clocks, i.e. a strict molecular clock where a single substitution rate is applied across the entire phylogeny and an uncorrelated relaxed clock where the substitution rate is allowed to vary from branch to branch and is drawn from a lognormal distribution. BF comparison showed the presence of a temporal signal under both models (Table S1). Maximum clade credibility (MCC) trees were generated using TreeAnnotator v1.10.4, using combined tree files generated with LogCombiner v1.10.4 (softwares are distributed with BEAST)³³. ITol v5 was used for tree visualization (https://itol.embl.de/). Branch robustness was assessed through posterior probabilities. For the root age enforcement, we modified the treeModel.rootHeight prior in Biuti by selecting a lognormal distribution and specifying the mean and standard deviation values (3750 and 340 for the Dahomey Gap, and 22500 and 1900 for the Last Glacial Maximum). Sub-sampled datasets were selected using the online Phylogenetic Diversity Analyzer v1.0.3 tool on the TempEST-rooted tree with 49 sequences. Pruned trees with 24, 12 and 6 leaves were generated using the Ape package v5.6 in RStudio v2021.09.1. To run the Prisoner of War (PoW) model, we followed the methods by Ghafari et al.²⁷ and first generated an ultrametric distance tree in BEAST using the HKY model and a strict molecular clock (without using tip dates). To transform this tree into a time tree, we ran the PoW R script available in Github (https://github.com/mg878/PoW_model) and specified the mean fastest evolutionary rate (µ_max) for poxviruses provided in Ghafari et al. (0.6 x 10E-3 s.s.y) and the short-term evolutionary rate estimated in our initial analyses (3.196 x 10E-6 s.s.y). We used TreeAnnotator v1.10.4 to build a MCC tree and find the estimated median and 95% HPD node heights. The resulting tree was visualized in Figtree.

For the F. bayonii partial genome sequence, we ran ML analyses in PhyML as described above (Supplementary Fig 2).

Data availability statement

Sequence data that support the findings of this study have been deposited in GenBank with the accession codes: MT724770 - MT724772 and as a supplementary file: consensus and mapping sequences.

Ethical statement and transfer of samples

There is no IACUC linked to the sampling of animals because there was no dedicated animal ethical committee in the DRC at the time of sampling. However, the research protocols of the different projects (COBIMFO, VLIR UOS, VLIR IS) have been submitted and approved by the owner (University of Antwerp, Belgium) and addressee (the Institute of Public Health in Kinshasa) institutional scientific boards. The research permits and authorizations were granted by the University of Kisangani Biodiversity Surveillance Center (CSB [Centre de Surveillance de la Biodiversité] – in French) who has the scientific authority to do so. All “movement of personal” (called “ordre de Mission”) were signed and approved by the local authorities at each field site. Material transfer agreements (MTA) were issued by the University of Kisangani, Biodiversity Surveillance Center (CSB [Centre de Surveillance de la Biodiversité] – in French). None of the animal species sampled are listed on the CITES Red List of protected species nor on the national list of protected fauna of the DRC; hence no CITES permit was needed prior to shipping. All animals were captured using live traps and humanely euthanized (isofluorane) following the 2013 AVMA Guidelines for the Euthanasia of Animals and Sikes and Gannon 2007 (J Mammal. 88:809–23).

Author contributions

Conceived the study: JM, AL, LVP, SC, EV and HL. Wrote the paper: JM, AL, LVP, SC. EV. Performed the field work: AL, PB, PM, CM, SN, FvP. Performed the Laboratory work: JM, LVP, RvV, NvH, FvP and SG. Performed the phylogenetic analyses: LVP and SC. Supervised field and laboratory work: AL, JJ-MT, MM, EB, SC, FL, HL, EV. All authors read and approved the final manuscript.

Competing/Conflict of Interest declaration

No potential conflict of interest was reported by the authors.

Funding

The research was funded by the VLIR-UOS South Initiative project 'Strengthening Academic Capacity to Respond and React to Monkeypox Epidemics: Discrimination and Origin of Eruptive Fevers in the Democratic Republic of Congo (DRC)'; BELSPO SSD project’ Congo Basin Integrated Monitoring For Forest Carbon Mitigation And Biodiversity’ (COBIMFO), the EU- Biodiversa BIODIV-AFREID (FWO G0G2119N), Anne Laudisoit own funds (Epulu 2012 & Hembe 2014). Joachim Mariën is currently a research assistant of Research Foundation Flanders (FWO). SG was supported by an EMBO long term postdoctoral fellowship (ALTF-328) and an OUTGOING [Pegasus]² Marie Skłodowska-Curie Fellowship of the Research Foundation - Flanders (12T1117N) during this work. EVECO is part of the Antwerp Consortium of Excellence VAX-IDEA.

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Monkeypox viruses circulate in distantly related small mammal species and only diversified recently

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