RESUMO
RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.
RESUMO
Western equine encephalitis virus (WEEV) is an arthropod-borne virus (arbovirus) that frequently caused major outbreaks of encephalitis in humans and horses in the early twentieth century, but the frequency of outbreaks has since decreased markedly, and strains of this alphavirus isolated in the past two decades are less virulent in mammals than strains isolated in the 1930s and 1940s1-3. The basis for this phenotypic change in WEEV strains and coincident decrease in epizootic activity (known as viral submergence3) is unclear, as is the possibility of re-emergence of highly virulent strains. Here we identify protocadherin 10 (PCDH10) as a cellular receptor for WEEV. We show that multiple highly virulent ancestral WEEV strains isolated in the 1930s and 1940s, in addition to binding human PCDH10, could also bind very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), which are recognized by another encephalitic alphavirus as receptors4. However, whereas most of the WEEV strains that we examined bind to PCDH10, a contemporary strain has lost the ability to recognize mammalian PCDH10 while retaining the ability to bind avian receptors, suggesting WEEV adaptation to a main reservoir host during enzootic circulation. PCDH10 supports WEEV E2-E1 glycoprotein-mediated infection of primary mouse cortical neurons, and administration of a soluble form of PCDH10 protects mice from lethal WEEV challenge. Our results have implications for the development of medical countermeasures and for risk assessment for re-emerging WEEV strains.
Assuntos
Vírus da Encefalite Equina do Oeste , Especificidade de Hospedeiro , Protocaderinas , Receptores Virais , Animais , Feminino , Humanos , Masculino , Camundongos , Aves/metabolismo , Aves/virologia , Doenças Transmissíveis Emergentes/epidemiologia , Doenças Transmissíveis Emergentes/virologia , Vírus da Encefalite Equina do Oeste/classificação , Vírus da Encefalite Equina do Oeste/metabolismo , Vírus da Encefalite Equina do Oeste/patogenicidade , Encefalomielite Equina/epidemiologia , Encefalomielite Equina/virologia , Proteínas Relacionadas a Receptor de LDL/metabolismo , Neurônios/metabolismo , Neurônios/virologia , Fenótipo , Protocaderinas/metabolismo , Receptores de LDL/metabolismo , Receptores de LDL/genética , Receptores Virais/metabolismo , Proteínas do Envelope Viral/metabolismo , Zoonoses Virais/epidemiologia , Zoonoses Virais/virologiaRESUMO
RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.