Zoonotic Spillover Pathways and Receptor Binding Evolution in Bat Reservoirs

Introduction

Bats (order Chiroptera) constitute a uniquely diverse reservoir for emerging zoonotic viruses, particularly coronaviruses and henipaviruses [1, 2]. The capacity of these viruses to cross species boundaries into intermediate or accidental hosts depends critically on molecular interactions between viral glycoproteins and host cell receptors [3, 4]. For coronaviruses, the spike (S) protein receptor-binding domain (RBD) engages host angiotensin-converting enzyme 2 (ACE2) or dipeptidyl peptidase 4 (DPP4, also known as CD26) depending on the viral genus [5, 6]. In bat reservoirs, extraordinary genetic diversity in ACE2 and other receptors has co-evolved with viral RBDs over millions of years [7, 8]. Understanding the structural basis of these interactions is essential for predicting spillover risk and for designing surveillance strategies [9, 10]. This article reviews the phylogenetic and structural determinants of receptor binding evolution in bats, emphasizing bioinformatic and biophysical approaches that map spillover pathways.

Bat ACE2 Structural Diversity and Evolutionary Selection

The ACE2 gene in bats exhibits exceptionally high diversity compared to other mammals, driven by long-term coevolution with coronaviruses [11]. Among bat species, ACE2 orthologs vary at critical contact residues that comprise the viral RBD binding interface [12, 13]. Crystal structures of ACE2 from horseshoe bats (Rhinolophus spp.) reveal that the N-terminal helix α1 and the loop between β3 and β4 contain species-specific substitutions that alter electrostatic and hydrophobic complementarity with sarbecovirus RBDs [14, 15]. For example, residues at positions 31, 34, 38, and 82 in bat ACE2 (human numbering) frequently differ from those in humans or other mammals, directly affecting binding affinity [16, 17]. Positive selection analyses using codon-based models (e.g., PAML) have identified multiple codons in bat ACE2 under diversifying selection, particularly in Rhinolophus and Myotis species [18, 19]. This selection pressure is consistent with an ongoing arms race between host receptor and viral spike [20].

In addition to ACE2, bats also exhibit variation in DPP4, the receptor for merbecoviruses (MERS-related coronaviruses) [9, 21]. Structural analyses of bat CD26 from seven species demonstrated that residues in the propeller blades IV and V differ among bat families, influencing MERS-CoV spike binding [22]. These differences can either restrict or enhance viral entry, providing a molecular filter for host range [5, 22].

Coronavirus Spike RBD Adaptation and Receptor Binding

Coronavirus spike RBDs undergo continuous structural evolution to accommodate receptor variability in bat populations [6, 23]. For sarbecoviruses, the RBD adopts a core structure with a receptor-binding motif (RBM) that directly contacts ACE2 [24, 18]. Structural dynamics simulations of bat coronavirus spike glycoproteins have revealed allosteric communication networks that modulate RBD conformational states [6]. The open (receptor-accessible) versus closed (inaccessible) conformations are regulated by hinge movements at the RBD–SD1 domain interface, and the stability of these states differs between bat host species [6, 25].

Biophysical binding studies using surface plasmon resonance and bio-layer interferometry have quantified the affinity of bat SARS-related coronavirus RBDs for ACE2 orthologs [17, 18]. The bat coronavirus RaTG13 RBD binds human ACE2 with approximately 10-fold lower affinity than SARS-CoV-2 RBD, but binds bat (Rhinolophus) ACE2 with high nanomolar affinity [18]. This affinity differential correlates with specific residues at positions 493, 498, and 501 in the RBM that are adapted to bat ACE2 [18, 26]. Conversely, the RBD of the highly divergent Ambecovirus subgenus uses a distinct binding mode that accommodates neotropical bat ACE2 variants [7].

For merbecoviruses, the RBD interacts with DPP4 through a β-sheet extension and a large loop region [5, 22]. Comparative analyses of MERS-related coronaviruses from European brown long-eared bats (Plecotus auritus) and Nathusius' pipistrelle (Pipistrellus nathusii) showed that residue substitutions in the RBD loop at positions 485-493 altered binding to bat CD26 orthologs [9, 21].

Species-Specific Binding Affinities and Spillover Potential

The ability of a bat coronavirus to infect a non-bat host depends not only on RBD–receptor affinity but also on post-entry replication barriers [12, 15]. Table 1 summarizes representative binding affinities of bat coronavirus RBDs for ACE2 from different mammalian species.

Table 1. Representative binding affinities (K_D, nM) of bat coronavirus RBDs for ACE2 orthologs.

These data indicate that bat-adapted RBDs generally bind bat ACE2 more tightly than human ACE2, but some sarbecoviruses (e.g., WIV1) can bind human ACE2 with moderate affinity, indicating a lower spillover barrier [15, 17]. Multiple sequence alignments of ACE2 across 25 bat species have identified a "spillover risk index" based on the presence of permissive residues at positions 38 (Asp/Glu) and 353 (Lys/Arg) that correlate with binding to human-adapted RBDs [20].

Zoonotic Spillover Pathways: From Bat to Intermediate Host to Spillover

Spillover events typically follow a pathway involving direct bat-to-human exposure or passage through an amplifying intermediate host [1, 3]. The henipavirus example illustrates this: Nipah virus spills from Pteropus bats to pigs or directly to humans through contaminated date palm sap [1, 3]. For coronaviruses, the palm civet (Paguma larvata) and the Malayan pangolin (Manis javanica) have been implicated as intermediate hosts for sarbecoviruses due to ACE2 homology with bats and humans [15, 28].

Bioinformatic analyses of viral metagenomes from individual bats in China and Brazil have revealed co-infection patterns that promote recombination and RBD shuffling among co-circulating coronaviruses [24, 10]. This genetic mixing can generate novel RBD architectures with shifted receptor tropism. Computational models of spike–ACE2 binding free energy changes (using software such as Rosetta or FoldX) allow prediction of which bat viruses have the highest risk of human adaptation [20, 29]. Figure 1 shows a decision tree for evaluating spillover risk based on RBD sequence and receptor compatibility.

flowchart TD
    A[Bat coronavirus isolated], > B{Sequence RBD region}
    B, > C[Compare to reference RBDs (e.g., SARS-CoV-2, MERS-CoV)]
    C, > D{Key RBM residues match?}
    D, >|Yes| E[Predictable ACE2/CD26 binding]
    D, >|No| F{Structural modeling of RBD-receptor complex}
    F, > G[Binding free energy evaluation]
    G, > H[Affinity above threshold?]
    H, >|Yes| I[High spillover risk: intermediate host required?]
    H, >|No| J[Low immediate zoonotic risk]
    I, > K[In vitro pseudovirus entry assays]
    I, > L[Ex vivo tissue explant testing]

This workflow integrates bioinformatics with experimental validation to prioritize surveillance in bat populations and at animal–human interfaces [2, 5, 19].

Computational and Structural Approaches to Define the Bat ACE2–RBD Interface

High-resolution structures (X-ray crystallography and cryo-EM) of bat ACE2 in complex with coronavirus RBDs have delineated the critical residue contacts [6, 22]. Table 2 lists key interface residues on bat ACE2 (Rhinolophus ferrumequinum) and their contribution to binding.

Table 2. Critical residues at the bat ACE2–RBD interface (Rhinolophus ferrumequinum numbering).

Homology modeling of bat ACE2 from Myotis myotis and Eptesicus fuscus using the Rhinolophus template reveals that substitutions at positions 42 and 353 can reduce RBD binding by 10–100 fold [20, 29]. These structural models are validated by mutagenesis and pseudovirus entry assays in bat cell lines [12, 17].

Conclusions

The evolutionary interplay between bat coronavirus spikes and host receptors (ACE2 and DPP4) constitutes a key determinant of zoonotic spillover risk. Structural diversity in bat ACE2, particularly at residues 31–42 and 353–355, creates a heterogeneous receptor landscape that has shaped RBD adaptation over deep evolutionary time. Bioinformatics approaches that integrate phylogenetic selection analyses, structural modeling, and binding free energy calculations can predict which bat coronaviruses have the greatest potential for human adaptation. Continued surveillance in bat reservoirs, combined with functional characterization of RBD–receptor interactions, will be essential for early detection of future spillover threats.

References

[1] Wang X, Zhang W. Henipaviruses at the threshold: preparedness in the era of recurrent spillover. Emerg Microbes Infect. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42261208/

[2] Gupta N, Smielewska A, Felix Drexler J, et al. Avian Influenza in Humans: Virology, Transmission, and Clinical Priorities. QJM. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42213088/

[3] Grzybek M, Mundt B, Kant R, et al. Nipah virus preparedness in a One Health framework: Implications for Europe. One Health. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42206023/

[4] Mazumder S, Kapoor S, Kaur H, et al. Bioinformatics-driven genome-wide identification of viral miRNAs in high spillover bat coronaviruses and their target genes in human. Arch Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42060194/

[5] Hudu SA, Jimoh AO. Operational zoonotic containment of Middle East respiratory syndrome coronavirus in Saudi Arabia: An implementation-oriented One Health genomic framework. Vet World. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42046671/

[6] Balogun TA, Kearns FL, Calvó-Tusell C, et al. Structural dynamics and allosteric communication of a SARS-like bat coronavirus spike glycoprotein. Biophys J. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42026866/

[7] Wallau GDL, Barbier E, Machado LC, et al. Ambecovirus, a novel Betacoronavirus subgenus circulating in neotropical bats, sheds new light on bat-borne coronaviruses evolution. Virus Evol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41492410/

[8] Hemnani M, Karatas M, Cruz AVS, et al. Metagenomic analysis of viral diversity in Portuguese bats. Vet Res Commun. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40974374/

[9] Johnston CM, Gunalan V, Baagøe HJ, et al. Characterization of a MERS-related betacoronavirus in Danish brown long-eared bats (Plecotus auritus). Virol J. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40826422/

[10] Silvério BS, Guilardi MD, Martins JO, et al. Coronavirus Cryptic Landscape and Draft Genome of a Novel CoV Clade Related to MERS From Bats Circulating in Northeastern Brazil. J Med Virol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/39825725/

[11] Frank HK, Enard D, Boyd SD. Exceptional diversity and selection pressure on coronavirus host receptors in bats compared to other mammals. Proc Biol Sci. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/35892217/

[12] Aicher SM, Streicher F, Chazal M, et al. Species-Specific Molecular Barriers to SARS-CoV-2 Replication in Bat Cells. J Virol. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/35862713/

[13] Li L, Zhang L, Zhou J, et al. Epidemiology and Genomic Characterization of Two Novel SARS-Related Coronaviruses in Horseshoe Bats from Guangdong, China. mBio. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/35467426/

[14] Fernandes AP, Águeda-Pinto A, Pinheiro A, et al. Evolution of CCR5 and CCR2 Genes in Bats Showed Multiple Independent Gene Conversion Events. Viruses. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/35215768/

[15] Stout AE, Guo Q, Millet JK, et al. Viral and Host Attributes Underlying the Origins of Zoonotic Coronaviruses in Bats. Comp Med. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/34635199/

[16] Lee SY, Chung CU, Park JS, et al. Genetic diversity of bat coronaviruses and comparative genetic analysis of MERS-related coronaviruses in South Korea. Transbound Emerg Dis. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/34536059/

[17] Guo H, Hu B, Si HR, et al. Identification of a novel lineage bat SARS-related coronaviruses that use bat ACE2 receptor. Emerg Microbes Infect. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/34263709/

[18] Liu K, Pan X, Li L, et al. Binding and molecular basis of the bat coronavirus RaTG13 virus to ACE2 in humans and other species. Cell. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/34139177/

[19] Na EJ, Lee SY, Kim HJ, et al. Comparative genetic analyses of Korean bat coronaviruses with SARS-CoV and the newly emerged SARS-CoV-2. J Vet Sci. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/33522164/

[20] Wei Y, Aris P, Farookhi H, et al. Predicting mammalian species at risk of being infected by SARS-CoV-2 from an ACE2 perspective. Sci Rep. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/33462320/

[21] Speranskaya AS, Artiushin IV, Samoilov AE, et al. Identification and Genetic Characterization of MERS-Related Coronavirus Isolated from Nathusius' Pipistrelle (Pipistrellus nathusii) near Zvenigorod (Moscow Region, Russia). Int J Environ Res Public Health. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/36834395/

[22] Yuan Y, Qi J, Peng R, et al. Molecular Basis of Binding between Middle East Respiratory Syndrome Coronavirus and CD26 from Seven Bat Species. J Virol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/31776269/

[23] Agusi ER, Schön J, Allendorf V, et al. SARS-CoV and SARS-CoV-2 cross-reactive antibodies in domestic animals and wildlife in Nigeria suggest circulation of sarbecoviruses. One Health. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38533194/

[24] Wang J, Pan YF, Yang LF, et al. Individual bat virome analysis reveals co-infection and spillover among bats and virus zoonotic potential. Nat Commun. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/37429936/

[25] Malik YS, Ansari MI, Kattoor JJ, et al. Evolutionary and codon usage preference insights into spike glycoprotein of SARS-CoV-2. Brief Bioinform. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/33377145/

[26] Guo H, Hu BJ, Yang XL, et al. Evolutionary Arms Race between Virus and Host Drives Genetic Diversity in Bat Severe Acute Respiratory Syndrome-Related Coronavirus Spike Genes. J Virol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32699095/

[27] Zhao X, Chen D, Szabla R, et al. Broad and Differential Animal Angiotensin-Converting Enzyme 2 Receptor Usage by SARS-CoV-2. J Virol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32661139/

[28] Xiao K, Zhai J, Feng Y, et al. Isolation of SARS-CoV-2-related coronavirus from Malayan pangolins. Nature. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32380510/

[29] Choudhury A, Mukherjee S. In silico studies on the comparative characterization of the interactions of SARS-CoV-2 spike glycoprotein with ACE-2 receptor homologs and human TLRs. J Med Virol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32383269/

[30] Wan Y, Shang J, Graham R, et al. Receptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS Coronavirus. J Virol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/31996437/

[31] Panati K, Tatireddygari VRA, Narala VR. An Overview on COVID-19 Pandemic: from Discovery to Treatment. Infect Disord Drug Targets. 2021. URL: https://pubmed.ncbi.nlm.nih.gov/33167846/

[32] Boni MF, Lemey P, Jiang X, et al. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat Microbiol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32724171/

[33] Lvov DK, Alkhovsky SV. [Source of the COVID-19 pandemic: ecology and genetics of coronaviruses (Betacoronavirus: Coronaviridae) SARS-CoV, SARS-CoV-2 (subgenus Sarbecovirus), and MERS-CoV (subgenus Merbecovirus).]. Vopr Virusol. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32515561/

[34] Lu R, Zhao X, Li J, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020. URL: https://pubmed.ncbi.nlm.nih.gov/32007145/

[35] Schad J, Voigt CC. Adaptive evolution of virus-sensing toll-like receptor 8 in bats. Immunogenetics. 2016. URL: https://pubmed.ncbi.nlm.nih.gov/27502317/ *** Disclaimer: This article is for educational and informational purposes only. It is not intended to substitute for professional veterinary advice, diagnosis, treatment, or regulatory guidance. Always consult a licensed veterinarian or qualified specialist regarding animal health, disease diagnosis, and therapeutic decisions.