key: cord-291436-cu5o8ipw authors: Martínez-Hernández, Fernando; Isaak-Delgado, Ana Belem; Alfonso-Toledo, Jorge Alberto; Muñoz-García, Claudia Irais; Villalobos, Guiehdani; Aréchiga-Ceballos, Nidia; Rendón-Franco, Emilio title: Assessing the SARS-CoV-2 threat to wildlife: Potential risk to a broad range of mammals date: 2020-10-05 journal: Perspect Ecol Conserv DOI: 10.1016/j.pecon.2020.09.008 sha: doc_id: 291436 cord_uid: cu5o8ipw Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect animals, however, the whole range of potential hosts is still unknown. This work makes an assessment of wildlife susceptibility to SARS-CoV-2 by analyzing the similarities of Angiotensin Converting Enzyme 2 (ACE2) and Transmembrane Protease, Serine 2 (TMPRSS2) —both recognized as receptors and protease for coronavirus spike protein— and the genetic variation of the viral protein spike in the recognition sites. The sequences from different mammals, birds, reptiles, and amphibians, and the sequence from SARS-CoV-2 S protein were obtained from the GenBank. Comparisons of aligned sequences were made by selecting amino acids residues of ACE2, TMPRSS2 and S protein; phylogenetic trees were reconstructed using the same sequences. The species susceptibility was ranked by substituting the values of amino acid residues for both proteins. Our results ranked primates at the top, but surprisingly, just below are carnivores, cetaceans and wild rodents, showing a relatively high potential risk, as opposed to lab rodents that are typically mammals at lower risk. Most of the sequences from birds, reptiles and amphibians occupied the lowest ranges in the analyses. Models and phylogenetic trees outputs showed the species that are more prone to getting infected with SARS-CoV-2. Interestingly, during this short pandemic period, a high haplotypic variation was observed in the RBD of the viral S protein, suggesting new risks for other hosts. Our findings are consistent with other published results reporting laboratory and natural infections in different species. Finally, urgent measures of wildlife monitoring are needed regarding SARS-CoV-2, as well as measures for avoiding or limiting human contact with wildlife, and precautionary measures to protect wildlife workers and researchers; monitoring disposal of waste and sewage than can potentially affect the environment, and designing protocols for dealing with the outbreak. Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) is causing the biggest pandemic 52 of this century, and could potentially infect between 30 to 40% of the world´s populations (De 53 Soto et al., 2020) . Due to its high transmission rate and mortality, researches around the world 54 are trying to get some insight about its origin through the analysis of related-virus genes 55 sequences in humans and animals (Lu R et al., 2020) , and looking for Angiotensin-Converting 56 Enzyme 2 (ACE2) sequence similarities in animals, the putative receptor of this virus (Andersen 57 Probabilistic models were constructed based on the amino acid residue sequence for ACE2 and 186 TMPRSS2. Two models were created for the ACE2 receptor and the third model includes the 187 TMPRSS2. The significant residue amino acids for ACE2 that interact with the viral S protein, so The assignation of the PCSV was as follow: four amino acid properties were used (size, 205 hydrophobicity, charge and polarity), each one with three categories: 1) size (tiny, small and 206 large); 2) hydrophobicity (hydrophilic, moderate, hydrophobic); 3) charge (positive, neutral, 207 negative); and 4) polarity (polar, amphipathic, non-polar). For polarity, some amino acids are 208 reported in two categories (i.e., amphipathic and polar or non-polar), for these cases the higher 209 value was assigned. When human and animal showed the same amino acid residue the PCSV was 210 assigned as 1. We assumed that an amino acid residue substitution by a different amino acid 211 residue even sharing all the physical properties will give a 0.9 PCSV tops. Values for each physical 212 property were assigned as follows: for each similar physical property a 0.225 was assigned; if the 213 property was not the same but in the closest category 0.112 was assigned; and if the property 214 was neither of those it was assigned a 0. The PCSV for each amino acid residue position was the 215 sum of the values of the four categories. The minimum assigned value was 0.225 and the 216 maximum was 0.9 (S3 Table) . To find the total PCSV (tPCSV) for each animal species, the product 217 of all PCSV was calculated (S4 Table) . Protein sequences of the three genes described above were subjected to multiple alignments in 8 226 different data matrices: 1) ACE2 gene matrix; 2) TMPRSS2 gene matrix; 3) ACE2 PBD sites; 4) 227 TMPRSS2 proteolytic site; 5) gene matrix ACE2 and TMPRSS2; 6) matrix genes ACE2 PBD site 228 and TMPRSS2 proteolytic site; 7) Viral protein S PBD site; and 8) Viral protein S proteolytic site 229 J o u r n a l P r e -p r o o f 11 by TMPRSS2. All alignments were established using the Clustal W and Muscle algorithms 230 included in MEGA software version 7.0.26 (Tamura et al., 2011) . Phylogenetic reconstructions 231 were performed using the eight matrices by Bayesian approximations with Mr. Bayes software 232 version 3.2 (Huelsenbeck et al., 2001) . The analysis was performed for 2 million generations with 233 sampling trees every 100 generations. Trees with scores lower than those at the stationary phase 234 (burn-in) were discarded, and the trees that reached the stationary phase were collected and 235 used to build majority consensus trees. 236 237 The three models were consistent among them for most of the species, with some variation in the 240 rank of certain particular species (Fig 1) . Model 1 gave the most different results with respect to 241 the others. Most of the primates ranked in the first places, but interestingly, after that, carnivores, 242 cetaceans, and wild rodents showed a relatively high potential risk. Lab rat and mouse ranked in 243 the lowest places along with bats. 244 245 Reptiles, amphibians and birds ranked below mammals, with some exception. Birds such as 246 Empidonax traillii (Models 2 and 3), and Nothoprocta perdicaria (Model 1) classified to a level 247 similar to that of lab rodents and bats. Reptiles with the highest rank were Chelonia mydas 248 (Model 1), and Protobothrops mucrosquamatus (Models 2 and 3) even around some mammals 249 such as Mus musculus and Myotis lucifugus but below Rattus norvegicus. For Models 2 and 3 most 250 of the reptiles were at the bottom of the rank. Amphibians were at similar rank than reptiles in 251 Model 1, but for Models 2 and 3 were around reptiles. In particular, the highest rank was Xenopus 252 tropicalis (Model 2), and Rhinatrema bivittatum (Model 3; S5 Table) . The analyses with the surface glycoprotein S showed little genetic variation, so the trees were 271 observed with polytomies (data not show). However, both domains showed genetic variation for 272 the RBD region, 12 haplotypes identified (Fig 4A) , with H1 being the most frequent (98.5%), and 273 for the TMPRSS2 cut region 6 haplotypes were identified (Fig 4B) , being the most frequent H1 274 (99.6%). The other haplotypes presented unique frequencies. Actually, experimental evidence found between one species of NWp and two of OWp infected 312 with SARS-CoV-2, showed that the former presents higher frequency of viremia than the latter, 313 particularly 100% of six Callithrix jacchus individuals versus 44% of eighteen Macaca spp; but 314 they also found that viral loads and pathological lesions at microscopic level were greater in 315 Macaca spp. than in C. jacchus (Lu S., et al., 2020) ; also proved that NWp, at least the species C. (FIP), since feral cats were found prior to and during the outbreak and diagnostic test cross-344 reactivity with FIP (Bossart and Schwartz, 1990). However, the lack of molecular evidence in that 345 case and the existence of a short coronavirus sequence from another infected harbor seal left 346 more questions than answers, because there was no case-information but just the submitted 347 GenBank sequence (Schütze, 2016) . Interestingly, in our phylogenetic trees, these marine 348 mammalian species share the same clade with the feline species, which also supports this 349 hypothesis. People that inhabit or travel through the seacoast, or wastewater released by urban Other in silico studies using the docking approach showed that some carnivores, as Panthera 359 pardus, P. tigris, Puma concolor, Lyxn pardinus, and Crocuta crocuta, have also less free energy, 360 (which means more stable union, because less energy is available to make a structural change) 361 than humans, which means more affinity for the SARS-CoV-2 S-protein . The Another element of dissent, other than the host, is the virus per se. For example, the high 397 variation observed in the SARS-CoV-2 RBD region (Fig 4A) , during the five months that the 398 pandemic has lasted, made feasible the generation of new variants. These variations are non-399 synonymous mutations, which suggests a low pressure of natural selection that, in turn, can 400 impact over an elevated sequence diversity in this genomic region and, consequently, may 401 increase its hosts-species affinity. And in the case of the viral TMPRSS2 recognition region, a less 402 genetic variation was detected, since it is represented by 6 different haplotypes that have been 403 observed with numerous non-synonymous substitutions (Fig 4B) . However, for the viral 404 The SARS-CoV-2 impact on new wild hosts is uncertain. To date, this virus is considered by many 436 authors as a deadly pathogen for humans, but with varying degrees of severity . 437 However, its effects on animal health is almost unknown. In humans, the severity of the disease is 438 Once the virus enters in wild environments, social cohesion in animals could be a decisive factor 447 for an outbreak. Then, taking individuals proximity into consideration, Primate order are at the 448 greatest risk, not only because its receptor and protease homology, as we see in our models and 449 phylogenetic trees, but also for its social organization and troops´ fusion-fission dynamic (Sueur 450 et al., 2011) . However, high social cohesion also exists amongst some Carnivora and many 451 Cetacean species, even at interspecies level (Brakes, 2017; Gittleman, 1989) . In this sense, we 452 must emphasize that some scientist claim that airborne transmission is feasible through small 453 droplets exhaled by humans, being able to move freely tens of meters from its origin (Morawska 454 and Cao, 2020). The risk increases when social wild species are gathering in great numbers at 455 places where people go, like national parks, and sometimes even face crowded situations (Bath 456 and Enck, 2003) . 457 In order to prevent person to person disease spread, during this SARS-CoV-2 global health crisis 459 a quarantine in most of the world was imposed (Wilder-Smith and Freedman, 2020). The human 460 containment has resulted in the appearance of wild animals in some cities around world, and 461 their presence indicates that humans and wildlife are closer than ever (Lewis, 2020) . This 462 proximity exists even in natural areas, where ecotourism has become one of the major economic 463 activities, owing to wildlife observations . Although at the moment 464 ecotourism has collapsed by SARS-CoV-2 quarantine, it will be reactivated in the near future 465 aerosol exposure, and environmental exposure), and some mitigation strategies (minimize, 507 assess, and protect). At the same time this document provides some additional resource for 508 specific groups such as great apes, bats, felid, and small carnivores (OIE, 2020). We encourage to 509 review this document as a first step in the strategy to limit SARS-CoV-2 spread among wildlife. 510 However, we should keep in mind that transmission could occur, and we still need protocols for 511 monitoring and mitigation strategies once SARS-CoV-2 is detected. 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