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. 2021 Apr 1;83(6):e23255. doi: 10.1002/ajp.23255

Variation in predicted COVID‐19 risk among lemurs and lorises

Amanda D Melin 1,2,3,✉, Joseph D Orkin 4, Mareike C Janiak 5, Alejandro Valenzuela 4, Lukas Kuderna 4, Frank Marrone III 6, Hasinala Ramangason 1, Julie E Horvath 7,8,9,10, Christian Roos 11, Andrew C Kitchener 12, Chiea Chuen Khor 13,14, Weng Khong Lim 15,16,17, Jessica G H Lee 18, Patrick Tan 13,15,17, Govindhaswamy Umapathy 19, Muthuswamy Raveendran 20, R Alan Harris 20, Ivo Gut 21, Marta Gut 21, Esther Lizano 4, Tilo Nadler 22, Dietmar Zinner 23,24,25, Minh D Le 26, Sivakumara Manu 19, Clément J Rabarivola 27, Alphonse Zaramody 27, Nicole Andriaholinirina 27, Steig E Johnson 1, Erich D Jarvis 28,29,30, Olivier Fedrigo 28,30, Dongdong Wu 31,32, Guojie Zhang 33,34,35, Kyle Kai‐How Farh 36, Jeffrey Rogers 20, Tomas Marques‐Bonet 4,37,38,39, Arcadi Navarro 4,37,38, David Juan 4, Paramjit S Arora 6, James P Higham 40,41,✉
PMCID: PMC8250314  PMID: 33792947

Abstract

The novel coronavirus SARS‐CoV‐2, which in humans leads to the disease COVID‐19, has caused global disruption and more than 2 million fatalities since it first emerged in late 2019. As we write, infection rates are at their highest point globally and are rising extremely rapidly in some areas due to more infectious variants. The primary target of SARS‐CoV‐2 is the cellular receptor angiotensin‐converting enzyme‐2 (ACE2). Recent sequence analyses of the ACE2 gene predict that many nonhuman primates are also likely to be highly susceptible to infection. However, the anticipated risk is not equal across the Order. Furthermore, some taxonomic groups show high ACE2 amino acid conservation, while others exhibit high variability at this locus. As an example of the latter, analyses of strepsirrhine primate ACE2 sequences to date indicate large variation among lemurs and lorises compared to other primate clades despite low sampling effort. Here, we report ACE2 gene and protein sequences for 71 individual strepsirrhines, spanning 51 species and 19 genera. Our study reinforces previous results while finding additional variability in other strepsirrhine species, and suggests several clades of lemurs have high potential susceptibility to SARS‐CoV‐2 infection. Troublingly, some species, including the rare and endangered aye‐aye (Daubentonia madagascariensis), as well as those in the genera Avahi and Propithecus, may be at high risk. Given that lemurs are endemic to Madagascar and among the primates at highest risk of extinction globally, further understanding of the potential threat of COVID‐19 to their health should be a conservation priority. All feasible actions should be taken to limit their exposure to SARS‐CoV‐2.

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Research Highlights

  • We used predominantly unpublished ACE2 gene sequences from 71 individuals across 51 species of strepsirrhines, to predict the infection risk presented by the SARS‐CoV‐2 coronavirus to different species of lemurs and lorises.

  • We converted the ACE2 gene sequences to protein sequences, and used protein‐protein interaction modeling to predict how amino acid residue differences between species are predicted to increase or decrease the binding affinity of the receptor to the virus.

  • We found great variation among strepsirrhines in their predicted binding affinity for SARS‐CoV‐2, with some groups, including members of the genera Daubentonia, Avahi, and Propithecus, predicted to be at high risk.

  • We use our data to highlight the risks posed by the SARS‐CoV‐2 virus to strepsirrhines, and discuss the implications of our results for conservation and captive care.

1. INTRODUCTION

On Friday, January 15, 2021, the two‐millionth human death officially attributed to COVID‐19 was documented by the Johns Hopkins University Coronavirus Resource Center (Dong et al., 2020; Santora & Wolfe, 2021). Since this date, the rates of infection by the virus responsible for this disease, SARS‐CoV‐2, have increased in most countries. As we write, we are reaching new global highs in active cases and witnessing the spread of new, more transmissible variants (Mahase, 2020; World Health Organization, 2020). As coordinated efforts within and across institutions, countries, and continents seek to identify treatments, develop vaccines, and curb the spread of this highly contagious virus, attention has also turned to the potential risks posed to nonhuman species (Damas et al., 2020; Liu et al., 2021; Melin et al., 2020; Wu et al., 2020). Zoonotic transfer of diseases from humans to nonhuman primates poses a major risk given the many physiological and genetic similarities shared within the Order Primates, and is a potentially grave risk to already endangered and fragmented populations (Gillespie & Leendertz, 2020).

In recent studies, the susceptibility of primates and other mammals to potential SARS‐CoV‐2 infection has been assessed by analysis of the gene sequences that code for the primary viral target, angiotensin‐converting enzyme‐2 (ACE2; Damas et al., 2020; Delgado Blanco et al., 2020; Liu et al., 2021; Melin et al., 2020). Receptor‐virus interaction models, including by members of the present authorship, have highlighted the likely susceptibility of many species, especially of apes and monkeys of Africa and Asia (Parvorder Catarrhini). Meanwhile, monkeys in the Americas (Parvorder Platyrrhini) are predicted to exhibit lower susceptibility (Liu et al., 2021; Melin et al., 2020). One striking feature of these analyses is the uniformity within these parvorders. Across the identified primary viral binding sites, catarrhines exhibit one set of amino acid residues, and platyrrhines another. Surprisingly, although gene sequences are only publicly available for a few strepsirrhine species (four lemurs and one galago), ACE2 variation in that suborder far exceeds variation present in the rest of the primate taxa examined to date (24 species spanning 21 genera and including tarsiers (1), platyrrhines (6), and catarrhines (14)). Of particular concern is the high sequence similarity at binding sites to human ACE2 of some lemur ACE2 proteins, including aye‐ayes (Daubentonia madagascariensis) and Coquerel's sifakas (Propithecus coquereli), which exhibited residues that are far more similar to those of humans and other catarrhines than to those present in platyrrhines (monkeys of the Americas; Melin et al., 2020).

These findings raise questions about the variability and molecular evolution of the ACE2 gene across Strepsirrhini, as well as about the potential susceptibility to initial infection by SARS‐CoV‐2 of different species across the suborder. Here, we expand substantially on previous reports of strepsirrhine ACE2 variation (Melin et al., 2020). We report 71 ACE2 gene sequences, including 66 from unpublished strepsirrhine genomes, spanning 39 lemuriform and 12 lorisiform species. For residue variants that have not been previously identified and assessed, we model the interactions between the translated ACE2 protein and the receptor‐binding domain of the SARS‐CoV‐2 spike protein to predict the susceptibility of species to initial infection by SARS‐CoV‐2. In doing so, we seek to improve our understanding of ACE2 variation and evolution, and to identify which strepsirrhine species are likely to be most at risk from the COVID‐19 pandemic. We recognize that disease development, progression, and pathogenesis in any given species will also be impacted by factors influencing the efficacy of viral cellular entry and taxon‐specific immune responses (Hoffmann et al., 2020; Li et al., 2021; Lukassen et al., 2020). Nonetheless, our hope is that our analysis of the initial susceptibility of different lemur and loris species to SARS‐CoV‐2 infection will help to inform decisions on how best to proceed with strepsirrhine research and management programs.

2. METHODS

2.1. Study species

We examine the ACE2 gene sequence of 71 individual strepsirrhines—66 newly sequenced individuals as part of the Primate Variation Genome Consortium (in preparation; Table S1), plus five obtained from publicly available genomes: Otolemur garnettii (Northern greater galago), accession no: XM_003791864.2, gene ID: 100951881; Propithecus coquereli (Coquerel's sifaka), accession no: XM_012638731.1, gene ID: 105805773; Microcebus murinus (gray mouse lemur) accession no: XM_020285237.1, gene ID: 105882317; Eulemur flavifrons (blue‐eyed black lemur), accession no: LGHW01000591.1, scaffold 590 (gene identified via BLAST); Daubentonia madagascariensis, (aye‐aye) accession no: PVJZ01006595.1, scaffold 13170, (gene identified via BLAST). In total, we analyze the ACE2 gene and protein sequences of 51 species (39 Lemuriformes and 12 Lorisiformes) and 19 genera (12 Lemuriformes and 7 Lorisiformes; Table 1 and S1). The number of individuals sampled per species ranges from 1 to 4, with 13 species having at least 2 individuals sampled. The number of samples per genus ranges from 1 to 17, with 13 genera having at least 2 individuals sampled (Table S1). In addition, we model the impact of residues at binding sites recently reported for Indri indri ACE2 protein (Damas et al., 2020), adding another genus of lemur to our survey. Detailed statistics for these newly generated genomes will be published upon their full release. ACE2 gene and protein sequences used in this study are included in Supplementary Materials. We confirm that this study followed all applicable laws and regulations of the countries in which it was conducted, that it was approved by all appropriate institutional committees, and that it conformed to the American Society of Primatologists Principles for the Ethical Treatment of Non Human Primates.

Table 1.

Results of computational protein‐protein interaction models predicting the impact of amino acid changes, relative to human ACE2 residues, at critical binding sites with SARS‐CoV‐2 receptor binding domain (RBD). Impacts of changes across the full complement of critical binding sites are presented in (A), single residue replacements are presented in (B)

(A)
Species Mutations (relative to human sequence) ΔΔG (kcal/mol)a Estimated decrease in binding efficiencyb
Homo sapiens 0
Avahi, Daubentonia, Propithecus M82T +0.9 5 fold
Eulemur, Hapalemur, Lemur, Prolemur, Varecia Q24E, M82T +1.4 10 fold
Indri H34N, M82N +2.7 100 fold
Monkeys (Americas) Y41H, Q42E, M42T +3.5 400 fold
Galago, Loris, Nycticebus, Otolemur H34R, D38E, Y41H, M82T +3.8 600 fold
Lepilemur, Microcebus, Mirza D30E, H34N, Y41H, M82T +4.0 800 fold
Arctocebus, Perodicticus Q24H, H34R, D38E, Y41H, M82T +4.2 1200 fold
Galagoides H34R, D38E, Y41H, M82T, Y83F +4.4 1700 fold
Cheirogaleus D30E, H34N, Y41H, M82T, K353Q +5.0 4500 fold
Carlito H34Q, Y41H, M82S, K353N +5.5 10000 fold
(B)
Mutation ΔΔG (kcal/mol)a
Q24L −0.7
Q24H 0.3
Q24E 0.5
D30E 0.7
H34R 0.8
H34N 1.0
H34L −0.5
H34Y −0.1
D38E 0.6
Y41H 1.9
Q42E 0.9
M82T 0.9
M82N 1.8
Y83F 0.6
K353Q 0.9
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a

Approximate predicted decrease in binding affinity of individual ACE2 proteins and SARS‐CoV‐2 RBD.

b

Mutations were analyzed with SSIPe server (https://zhanglab.ccmb.med.umich.edu/SSIPe/) and PDB file 6M0J.

This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

2.2. Gene alignments

We mapped reads from whole‐genome sequence (WGS) data to the closest available annotated reference assembly from among the set of partially unpublished (unp.) references (Daubentonia madagascariensis, (unp.) Galago moholi (unp.), Propithecus coquereli (GCF_000956105.1), Lemur catta (unp.), Loris tardigradus (unp.), Microcebus murinus (unp.), Nycticebus pygmaeus (unp.) and Otolemur garnettii (unp.). Briefly, after removing adapter sequences using cutadapt, we mapped the reads using bwa mem and processed and sorted alignments using samtools. We removed duplicates using biobambam, and added read groups for variant calling using picard. We called variants using GATK4 HaplotypeCaller (v 4.1.6) following best practice pipelines (https://gatk.broadinstitute.org). After applying a set of standard hard filters (Table S2), we extracted the coding regions of ACE2 gene sequences and introduced homozygous alternative calls to create the putative coding sequence of each individual. We extracted and aligned ACE2 gene sequences from the variant call files, which were then translated into protein sequences. The consensus sequences were manually inspected and corrected where needed to remove gene‐flanking regions. We manually verified the absence of indels and premature stop codons for each individual. We then aligned these 66 amino acid sequences using MAFFT (default settings) with those extracted from publicly available genomes (Melin et al., 2020). The full nucleotide and amino acid alignments used here are provided as tab‐delimited text files in the Supporting Information. Following alignment, we examined amino acid sequence variation within and across species along the length of the ACE2 protein, and specifically at the sites that are critical for SARS‐CoV‐2 binding.

2.3. Variation in ACE2 sequences at critical sites and impact on SARS‐CoV‐2 binding

Our method for identifying critical contact sites between the ACE2 protein and the receptor‐binding domain (RBD) of the SARS‐CoV‐2 spike protein is detailed in Melin et al. (2020). Briefly, we conducted alanine scanning mutagenesis to assess the contribution of each human ACE2 residue to protein‐protein complex formation with the SARS‐CoV‐2 RBD (Bogan & Thorn, 1998; Kortemme & Baker, 2002; Massova & Kollman, 1999). Alanine scanning is a commonly used method, and alanine is chosen because it is the smallest residue that may be incorporated without significantly impacting the protein backbone conformation (Kortemme et al., 2004). We defined critical residues as those that, upon mutation to alanine, decrease the binding energy by a threshold value ΔΔGbind ≥ 1.0 kcal/mol. Nine sites meet this criterion (Table S3). To be conservative, we also examined amino acid variation at additional sites that were identified as important by different but complementary methods: cryo‐EM and X‐ray crystallography structural analysis (Lan et al., 2020; Shang et al., 2020; Wang et al., 2020; Yan et al., 2020). While some of these sites overlap with the critical sites we identified using alanine scanning, three do not—alanine scanning also identifies these as binding sites, but with ΔΔGbind < 1.0 kcal/mol. To be conservative in the present analyses, as in Melin et al., 2020, we added these three sites to our nine sites for a total of 12 critical sites (Table S3). All computational alanine scanning mutagenesis analyses were performed using Rosetta (Jochim & Arora, 2010; Kortemme et al., 2004; Raj et al., 2013).

To model how variation in the ACE2 amino acid sequences across species affects the relative binding energy of the ACE2/SARS‐CoV‐2 interaction, we used the SSIPe program (Huang et al., 2020). This algorithm mutates selected residues and compares the resulting binding energy to that of human ACE2 bound to the SARS‐CoV‐2 RBD as a benchmark (PDB 6M0J). We modeled the full suite of amino acid changes occurring at critical binding sites for all unique ACE2 sequences. We further examined the predicted effect of each individual amino acid change (in isolation) on protein‐binding affinity to better understand each residue's contribution to variation in binding affinity.

3. RESULTS

We examined variation along the length of the ACE2 protein sequence for the 66 newly sequenced individuals and the ACE2 sequences from the five genomes available at NCBI. Sequences are conserved within, but are variable across, strepsirrhine genera. The mean pairwise amino acid sequence identity along the length of the ACE2 protein within genera is 99.25% (mean amino acid substitutions = 5.85). The mean amino acid sequence identity between lemur genera was 91.67%, and between lorisiform genera was 92.72%. When we focused solely on the critical binding sites, the pairwise amino acid identity at binding sites within genera was 100%, indicating an absence of any amino acid variation among species in the same genus in our study. Differences between genera are also present at the critical binding sites (Figure 1), especially among lemurs, where the mean pairwise amino acid sequence identity is 83.18%. The mean pairwise amino acid sequence identity at binding sites between lorisiform genera is 95.04%.

Figure 1.

Figure 1

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Amino acid composition of the ACE2 protein at sites that are critical for interacting with the SARS‐CoV‐2 receptor binding domain across examined strepsirrhine genera, with respect to the human ACE2 sequence. The phylogenetic relationship among studied species is presented centrally, with branch lengths representing approximate evolutionary distances. (ACE2 = angiotensin‐converting enzyme‐2)

We found three novel ACE2 variants not previously reported for any primate at three critical binding sites: H24 (Arctocebus, Perodicticus), F83 (Galagoides), and Q353 (Cheirogaleus). The remaining binding site variation is consistent with previous reports. The combination of residues (E24, T82) previously reported for Eulemur flavifrons, is also found in other species of Eulemur, as well as in Hapalemur, Lemur, and Prolemur. The critical binding site composition found in Indri indri (Damas et al., 2020) is not found in any of the genera we sequenced here. The residues at binding sites 37, 42, 355, and 357 are invariant across all strepsirrhines examined. None of the strepsirrhine ACE2 proteins are modeled to have a higher binding affinity to SARS‐CoV‐2 than the human (catarrhine) form (Table 1A). Among the 12 critical sites, the substitutions causing the starkest drop in viral‐receptor binding affinity relative to the human sequence are Y41H and M82N (Table 1B). The former substitution is found in all lorisoids and in sportive, dwarf, mouse, and giant mouse lemurs. The latter substitution is only identified in Indri indri, although a different substitution at the same site occurs in all other strepsirrhines (M82T). Other mutations had lesser effects (Table 1B).

Looking at taxon‐specific predictions based on the entire complement of amino acids at critical binding sites, the species predicted to be most susceptible to SARS‐CoV‐2 infection are in the genera Avahi, Propithecus, and Daubentonia (Table 1A). These taxa differ from humans at only one critical binding site, M82T, which is predicted to lower the binding affinity between the ACE2 receptor and the SARS‐CoV‐2 virus by five‐fold. These genera are followed by species in the genera Eulemur, Lemur, Prolemur, and Varecia, which differ in one additional (Q24E) substitution, which should further lower the binding affinity by two‐fold. In potentially promising results, we predict that the lorises, galagos, and dwarf, mouse, giant mouse, and sportive lemurs are far less susceptible to infection than humans. This is primarily due to a Y41H mutation (Figure 2), although additional changes in amino acids at binding sites further lower the affinity between their ACE2 and the RBD of the SARS‐CoV‐2 spike protein. The decreases in the modeled binding affinity range from 0.9 ΔΔG (kcal/mol) (Avahi, Propithecus, Daubentonia; predicted most susceptible) to 5.0 ΔΔG (kcal/mol) (Cheirogaleus, predicted least susceptible), relative to human ACE2 (Table 1A).

Figure 2.

Figure 2

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Model of human ACE2 in complex with SARS‐CoV‐2 RBD is presented in Panel (a). Three of the key ACE2 interfacial residues are highlighted in Panel (b). The dashed lines indicate predicted hydrogen bonding interactions. Interactions at three of the critical binding sites (41, 42, and 82) are shown for humans and other catarrhines (i.e., apes and monkeys in Africa and Asia). Changes in amino acids diminish these binding interactions. For example, substitution of tyrosine with histidine at site 41 in Panel (c) decreases the viral‐RBD binding affinity by removal of the potential hydrogen‐bonding interactions with T500 and N501. (ACE2 = angiotensin‐converting enzyme‐2; RBD = receptor‐binding domain)

4. DISCUSSION

We report ACE2 gene and protein sequences for 19 genera of strepsirrhine primates, spanning 51 species and 71 individuals, and examine these together with the Indri indri ACE2 protein. We confirm previous reports of the amino acid residue composition at viral binding sites for Daubentonia, Propithecus, Eulemur, Microcebus, and Otolemur (Damas et al., 2020; Melin et al., 2020). Additionally, we identified three novel variants at the following key binding sites: H24, F8, and Q353. These variants are modeled to be protective, are not found in species reported in the previous analyses of a small subset of strepsirrhine species (Melin et al., 2020), and were also not found among previous analyses of primates more generally. Relative to variation seen in catarrhines and platyrrhines, strepsirrhine ACE2 variation across genera at critical binding sites is remarkably high, especially among lemurs. In addition to reporting new ACE2 sequences spanning many strepsirrhine species, we also provide the first examination of intraspecific variation in ACE2 sequences outside of humans and vervet monkeys (Cao et al., 2020; Schmitt et al., 2020; Stawiski et al., 2020). Unlike Schmitt et al. (2020), who found an intraspecific polymorphism at a binding site (D30G), which might impact susceptibility of vervets to SARS‐CoV‐2 at the individual level, we find that ACE2 proteins are highly conserved within species and within genera, at least for the taxa examined. However, our intraspecific and intrageneric sample sizes (maximally n = 4 and n = 17, respectively) are small, and low‐to‐moderate levels of variation at ACE2 binding sites might be discovered as sampling increases. Still, our results broadly indicate that members of the same species and closely related species are likely to share similar initial susceptibility to SARS‐CoV‐2 infection. At higher taxonomic levels, there does appear to be a phylogenetic effect on susceptibility to SARS‐CoV‐2 infection among the strepsirrhines. Within families, there is broad sequence similarity at ACE2 critical binding sites. Accordingly, all unsampled species in the families Lemuridae and Indriidae are likely to be at high risk. The amino acid conservation within the family Cheirogaleidae (Cheirogaleus, Microcebus, Mirza) suggests that members of the genera Allocebus and Phaner, not sampled here, are likely at low risk. Similarly, we did not sample species in the genera Sciurocheirus, Euoticus, or Paragalago, but if they follow patterns of variation seen among other members of the family Galagidae (Galagoides, Galago, Otolemur) they should be at relatively low risk. However, given the difference in risk assessments within some members of the same family, for example, between Indri and the other Indriidae (Avahi and Propithecus), we caution the application of risk assessments across genera, especially when we do not have samples for representative species.

As with all studies based on predictive modeling, our results require experimental validation and should be interpreted with caution, especially those results which predict that some strepsirrhines might be at a lower risk. Additional limitations include that our study examined variation at sites identified to be critical for SARS‐CoV‐2 viral binding, but did not assess the impact of residues that are not in direct contact with the virus and which may still affect binding allosterically. In addition, we did not examine genetic variation or model the function of the protease (TMPRSS2), which facilitates viral entry post binding (Hoffmann et al., 2020), and which is anticipated to impact disease progression. We also emphasize that our approach investigates the likely initial susceptibility of species to SARS‐CoV‐2 infection. The severity of viral infection responses may differ between species and is related to variation in immune and other responses (Lukassen et al., 2020). Nonetheless, the results of in vivo infection studies conducted on haplorhine primates and other mammals strongly support the predictions of protein‐protein interaction models about the susceptibility of different species to SARS‐CoV‐2 and the development of COVID‐19‐like symptoms (Blair et al., 2020; Lu et al., 2020; Rockx et al., 2020; Shan et al., 2020; Shi et al., 2020), supporting the applicability of our results. An additional tangible contribution of our study is that it provides novel sequence data that can be used in site‐directed mutagenesis to recreate taxon‐specific ACE2 proteins for cellular assays (Guy et al., 2005). At the same time, results predicting high susceptibility among a large number of genera are sufficiently alarming as to warrant special care and attention when interacting with these species in wild and captive management settings, including zoological parks, where humans frequently come into contact with vulnerable species (e.g., in walk‐through lemur exhibits).

The predictions of our study suggest that, among the strepsirrhines, the lemurs of the families Indriidae, Daubentoniidae, and to a lesser extent Lemuridae, are likely to be particularly vulnerable to SARS‐CoV‐2 infection. Lemurs are considered to be among the most threatened vertebrates globally, with over 94% of extant species being threatened with extinction (IUCN, 2021; Schwitzer et al., 2014). High rates of deforestation which result from changing land‐use patterns coupled with high human population growth are among the most potent threats to lemur populations (Elmqvist et al., 2007; Harper et al., 2007). Besides habitat loss, these human‐induced disturbances are exposing wild lemur populations to novel interactions with humans and domestic animals, and in so doing increasing risks of disease outbreaks (Barrett et al., 2013). Current knowledge of the disease ecology of wild lemurs suggests that populations that are found in disturbed habitats and those living in areas with a high volume of tourists are at elevated risk of bearing pathogens found in humans, livestock, and other domestic animals (Bublitz et al., 2015; Junge et al., 2011; Rasambainarivo et al., 2013). Furthermore, lemurs in general, including many of the larger‐bodied species which are predicted to be most at risk of infection by SARS‐CoV‐2, are highly vulnerable to new diseases because they are considered to be immunologically naïve, and are unlikely to persist through a major epidemic outbreak (Junge, 2007).

Historically, conservationists in Madagascar have strived to implement integrative conservation programs to protect the biological uniqueness of the island while leveraging the sustainable development of local communities (e.g., Birkinshaw et al., 2013; Corson, 2017; Dolins et al., 2010; Wright et al., 2012). In addition to the considerable conservation obstacles exacerbated by frequent political unrest and extreme poverty (Schwitzer et al., 2014), initiatives in Madagascar now have the concern of a viral pandemic in the human population, which appears likely to pose a direct and serious risk to many lemurs. Recently, there has been an emergence of integrated conservation programs that include a human health component (e.g., Garchitorena et al., 2018; Mohan & Shellard, 2014), a necessary shift in a country with one of the lowest levels of healthcare system financing in the world (Barmania, 2015). This is particularly urgent given that COVID‐19 could potentially infect up to 30% of the human population (Evans et al., 2020). Furthermore, Madagascar lacks a legal framework to guide best research practices to limit exposure of lemur populations to diseases (in contrast, e.g., to great apes; see Gilardi et al., 2015). It is important that all stakeholders involved in the conservation of lemurs coordinate to draft such guidelines, which should include safeguards against the close contact between people and lemurs that occur as part of the successful and widespread community‐based conservation programs. Such a “One Health” approach is especially important during a global pandemic. At a minimum, these concerns should be carefully considered for the species identified as most susceptible to SARS‐CoV‐2.

In potentially more promising news, our results indicate that the vulnerability of the lorisoids—and indeed of many of the small‐bodied lemurs (e.g., mouse lemurs)—to SARS‐CoV‐2 infection may be substantially lower. Although the lorisoids as a group are more geographically widespread and (in relative terms) of lower conservation concern than the lemurs, many remain threatened and face critical challenges to their survival. Their cryptic, nocturnal habits may make the impact of emerging infectious diseases especially difficult to monitor in wild populations. Nonetheless, lower predicted susceptibility to SARS‐CoV‐2 is a potentially positive result.

Our results are also likely to be of interest and significance for zoos and captive research facilities around the world that house lemurs, lorises, and galagos. Given the close contact with humans in such environments (often indoors), extra precautions may be necessary, especially when interacting with the likely most at‐risk lemurs. These may include many of the measures suggested for those interacting with great ape and other catarrhine populations (Gilardi et al., 2015; Melin et al., 2020), such as: regular testing for SARS‐CoV‐2, requiring face masks for human researchers and caretakers, imposing quarantines on all individuals ahead of contact, and disinfecting clothes and footwear. The risk of COVID‐19 to nonhuman primates has been demonstrated in clinical trials (Lu et al., 2020) and recently exemplified when members of a captive gorilla group tested positive for SARS‐CoV‐2 after exposure to an asymptomatic keeper, and exhibited respiratory symptoms similar to COVID‐19 (San Diego Zoo, 2021). It is more difficult to assess the onset of and potential for other symptoms, such as anosmia, but loss of olfactory abilities could be devastating to lemurs and other primates which rely on their sense of smell to communicate, avoid predators, and select foods. Regardless of where species fall in the continuum of potential risk that we have presented here, we stress that it is prudent to take all feasible precautions when interacting with any primate.

Over the past year, scientists have mobilized with remarkable speed and effectiveness to address the COVID‐19 pandemic's impacts on humans, from developing and rolling out new tests, to designing and trialing vaccine candidates. The pandemic also raises major new challenges for field primatologists and other biologists, zookeepers, conservationists, and all those interested in the survival and welfare of primates (Bales, 2020; Douglas et al., 2020; Olival et al., 2020). Conservation efforts have already been severely impeded by the pandemic. National and global lock‐downs have made it difficult or impossible for conservationists, primatologists, and wildlife patrol teams to enter their field sites. Governments are preoccupied with efforts to curb the pandemic, and in some cases conservation funding support has been reduced due to financial difficulties and new priorities. While avoiding all contact with wild primates may be ideal from a zoonotic disease containment perspective, it is unlikely to be possible in practice, nor in the overall interest of their conservation (Reid, 2020; Trivedy, 2020). While we hope that our results will serve to inform conservation efforts, resolving the pressures that have resulted from the pandemic will require input from stakeholders with complementary ethical, scientific, and socioeconomic perspectives. It is our hope that as a community, we can rise to the challenge.

CONFLICT OF INTERESTS

The authors declare that there are no conflict of interests.

AUTHOR CONTRIBUTIONS

Amanda Melin: conceptualization (lead); formal analysis (supporting); funding acquisition (supporting); methodology (lead); project administration (lead); supervision (lead); validation (lead); writing‐original draft (lead); writing‐review & editing (lead). Joseph D. Orkin: conceptualization (equal); data curation (lead); formal analysis (lead); funding acquisition (supporting); investigation (lead); project administration (supporting); software (supporting); visualization (lead); writing‐original draft (equal); writing‐review & editing (equal). Mareike C. Janiak: data curation (lead); formal analysis (lead); funding acquisition (supporting); investigation (equal); writing‐original draft (equal); writing‐review & editing (equal). Alejandro Valenzuela: funding acquisition (supporting); investigation (equal); software (lead); writing review & editing (supporting). Lukas Kuderna: funding acquisition (supporting); investigation (equal); methodology (equal); software (lead); writing original draft (supporting); writing review & editing (supporting). Frank Marrone III: Formal analysis (lead); funding acquisition (supporting); methodology (supporting); visualization (lead); writing‐review & editing (supporting). Hasinala Ramangason: funding acquisition (supporting); writing original draft (equal); writing review & editing (supporting). Julie E. Horvath: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Christian Roos: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Andrew Kitchener: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Chiea Chuen Khor: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Weng Khong Lim: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Jessica G. H. Lee: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Patrick Tan: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Govindhaswamy Umapathy: funding acquisition (supporting); resources (supporting); writing‐review & editing (supporting). Muthuswamy Raveendran: funding acquisition (supporting); investigation (supporting); writing review & editing (supporting). R. Alan Harris: funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Ivo Gut: funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Marta Gut: funding acquisition (supporting); investigation (supporting); writing review & editing (supporting). Esther Lizano: funding acquisition (supporting); investigation (supporting); writing review & editing (supporting). Tilo Nadler: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Dietmar Zinner: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Minh D. Le: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Sivakumara Manu: Funding acquisition (supporting); resources (supporting); writing‐review & editing (supporting). Clément J. Rabarivola: Funding acquisition (supporting); resources (supporting); writing‐review & editing (supporting). Alphonse Zaramody: funding acquisition (supporting); resources (supporting); writing review & editing (supporting). Nicole Andriaholinirina: Funding acquisition (supporting); resources (supporting); writing‐review & editing (supporting). Steig Johnson: Funding acquisition (supporting); resources (supporting); writing original draft (supporting); writing review & editing (supporting). Erich D. Jarvis: Funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Olivier Fedrigo: funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Dongdong Wu: funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Guojie Zhang: funding acquisition (supporting); investigation (supporting); resources (supporting); writing review & editing (supporting). Kyle Kai‐How Farh: funding acquisition (lead); resources (supporting); writing review & editing (supporting). Jeffrey Rogers: funding acquisition (lead); resources (supporting); writing original draft (supporting); writing review & editing (supporting). Tomas Marques‐Bonet: conceptualization (supporting); funding acquisition (lead); project administration (lead); resources (lead); supervision (lead); writing original draft (supporting); writing review & editing (supporting). Arcadi Navarro: funding acquisition (supporting); methodology (equal); supervision (lead); writing review & editing (supporting). David Juan: funding acquisition (supporting); methodology (equal); supervision (equal); writing review & editing (supporting). Paramjit S. Arora: formal analysis (lead); funding acquisition (supporting); methodology (lead); validation (lead); visualization (lead); writing original draft (supporting); writing review & editing (supporting). James Higham: conceptualization (lead); funding acquisition (supporting); methodology (lead); project administration (lead); supervision (lead); visualization (equal); writing original draft (lead); writing review & editing (lead).

Supporting information

Supporting information.

Click here for additional data file. (22.6KB, docx)

Supporting information.

Click here for additional data file. (207.8KB, txt)

ACKNOWLEDGMENTS

We thank the people in the Primate Genome Variation Consortium and BGI Primate Reference Consortium for allowing us to publish partial gene information early due to the urgency for COVID‐19 research. We thank all persons and groups who shared samples for this study, including many samples from the Duke Lemur Center. This is Duke Lemur Center publication #1472. ADM is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant) and Canada Research Chairs Program. MCJ's postdoctoral appointment is supported by funding from the Natural Environment Research Council (NERC NE/T000341/1). IG and MG acknowledge the support of the Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III and the 2014–2020 Smart Growth Operating Program, to the EMBL partnership and cofinancing with the European Regional Development Fund (MINECO/FEDER, BIO2015‐71792‐P). We also acknowledge the support of the Centro de Excelencia Severo Ochoa, and the Generalitat de Catalunya through the Departament de Salut, Departament d'Empresa i Coneixement and the CERCA Programme. TMB is supported by funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 864203), BFU2017‐86471‐P (MINECO/FEDER, UE), “Unidad de Excelencia María de Maeztu”, funded by the AEI (CEX2018‐000792‐M), Howard Hughes International Early Career, Obra Social "La Caixa" and Secretaria d'Universitats i Recerca and CERCA Programme del Departament d'Economia i Coneixement de la Generalitat de Catalunya (GRC 2017 SGR 880). PSA thanks the National Institutes of Health (R35GM130333) for financial support. EL is supported by CGL2017‐82654‐P (MINECO/FEDER, UE). EDJ and OF's contributions were supported by funds from Howard Hughes Medical Institute and the Rockefeller University. Chris Smith drew the images for Figure 1. The authors would like to thank the Veterinary and Zoology staff at Wildlife Reserves Singapore for their help in obtaining the tissue samples, as well as the Lee Kong Chian Natural History Museum for storage and provision of the tissue samples. Finally, we thank two reviewers for quick and constructive comments, and Karen Bales for her supportive editorial oversight.

Melin, A. D. , Orkin, J. D. , Janiak, M. C. , Valenzuela, A. , Kuderna, L. , Marrone, F. , Ramangason, H. , Horvath, J. E. , Roos, C. , Kitchener, A. C. , Khor, C. C. , Lim, W. K. , Lee, J. G. H. , Tan, P. , Umapathy, G. , Raveendran, M. , Alan Harris, R. , Gut, I. , Gut, M. , …  Higham, J. P. (2021). Variation in predicted COVID‐19 risk among lemurs and lorises. Am J Primatol. 83, e23255. 10.1002/ajp.23255

Amanda D. Melin & Joseph D. Orkin contributed equally to this study.

Contributor Information

Amanda D. Melin, Email: amanda.melin@ucalgary.ca.

James P. Higham, Email: jhigham@nyu.edu.

DATA AVAILABILITY STATEMENT

All nucleotide and amino acid sequences used in this study are provided as supplemental text files.

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Associated Data

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Supplementary Materials

Supporting information.

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Supporting information.

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Data Availability Statement

All nucleotide and amino acid sequences used in this study are provided as supplemental text files.

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