scholarly journals Pervasive RNA secondary structure in the genomes of SARS-CoV-2 and other coronaviruses – an endeavour to understand its biological purpose

Author(s):  
P. Simmonds

ABSTRACTThe ultimate outcome of the COVID-19 pandemic is unknown and is dependent on a complex interplay of its pathogenicity, transmissibility and population immunity. In the current study, SARS coronavirus 2 (SARS-CoV-2) was investigated for the presence of large scale internal RNA base pairing in its genome. This property, termed genome scale ordered RNA structure (GORS) has been previously associated with host persistence in other positive-strand RNA viruses, potentially through its shielding effect on viral RNA recognition in the cell. Genomes of SARS-CoV-2 were remarkably structured, with minimum folding energy differences (MFEDs) of 15%, substantially greater than previously examined viruses such as HCV (MFED 7-9%). High MFED values were shared with all coronavirus genomes analysed created by several hundred consecutive energetically favoured stem-loops throughout the genome. In contrast to replication-association RNA structure, GORS was poorly conserved in the positions and identities of base pairing with other sarbecoviruses – even similarly positioned stem-loops in SARS-CoV-2 and SARS-CoV rarely shared homologous pairings, indicative of more rapid evolutionary change in RNA structure than in the underlying coding sequences. Sites predicted to be base-paired in SARS-CoV-2 showed substantially less sequence diversity than unpaired sites, suggesting that disruption of RNA structure by mutation imposes a fitness cost on the virus which is potentially restrictive to its longer evolution. Although functionally uncharacterised, GORS in SARS-CoV-2 and other coronaviruses represent important elements in their cellular interactions that may contribute to their persistence and transmissibility.

mBio ◽  
2020 ◽  
Vol 11 (6) ◽  
Author(s):  
P. Simmonds

ABSTRACT The ultimate outcome of the coronavirus disease 2019 (COVID-19) pandemic is unknown and is dependent on a complex interplay of its pathogenicity, transmissibility, and population immunity. In the current study, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was investigated for the presence of large-scale internal RNA base pairing in its genome. This property, termed genome-scale ordered RNA structure (GORS) has been previously associated with host persistence in other positive-strand RNA viruses, potentially through its shielding effect on viral RNA recognition in the cell. Genomes of SARS-CoV-2 were remarkably structured, with minimum folding energy differences (MFEDs) of 15%, substantially greater than previously examined viruses such as hepatitis C virus (HCV) (MFED of 7 to 9%). High MFED values were shared with all coronavirus genomes analyzed and created by several hundred consecutive energetically favored stem-loops throughout the genome. In contrast to replication-associated RNA structure, GORS was poorly conserved in the positions and identities of base pairing with other sarbecoviruses—even similarly positioned stem-loops in SARS-CoV-2 and SARS-CoV rarely shared homologous pairings, indicative of more rapid evolutionary change in RNA structure than in the underlying coding sequences. Sites predicted to be base paired in SARS-CoV-2 showed less sequence diversity than unpaired sites, suggesting that disruption of RNA structure by mutation imposes a fitness cost on the virus that is potentially restrictive to its longer evolution. Although functionally uncharacterized, GORS in SARS-CoV-2 and other coronaviruses represents important elements in their cellular interactions that may contribute to their persistence and transmissibility. IMPORTANCE The detection and characterization of large-scale RNA secondary structure in the genome of SARS-CoV-2 indicate an extraordinary and unsuspected degree of genome structural organization; this could be effectively visualized through a newly developed contour plotting method that displays positions, structural features, and conservation of RNA secondary structure between related viruses. Such RNA structure imposes a substantial evolutionary cost; paired sites showed greater restriction in diversity and represent a substantial additional constraint in reconstructing its molecular epidemiology. Its biological relevance arises from previously documented associations between possession of structured genomes and persistence, as documented for HCV and several other RNA viruses infecting humans and mammals. Shared properties potentially conferred by large-scale structure in SARS-CoV-2 include increasing evidence for prolonged infections and induced immune dysfunction that prevents development of protective immunity. The findings provide an additional element to cellular interactions that potentially influences the natural history of SARS-CoV-2, its pathogenicity, and its transmission.


2008 ◽  
Vol 82 (23) ◽  
pp. 11824-11836 ◽  
Author(s):  
Matthew Davis ◽  
Selena M. Sagan ◽  
John P. Pezacki ◽  
David J. Evans ◽  
Peter Simmonds

ABSTRACT By the analysis of thermodynamic RNA secondary structure predictions, we previously obtained evidence for evolutionarily conserved large-scale ordering of RNA virus genomes (P. Simmonds, A. Tuplin, and D. J. Evans, RNA 10:1337-1351, 2004). Genome-scale ordered RNA structure (GORS) was widely distributed in many animal and plant viruses, much greater in extent than RNA structures required for viral translation or replication, but in mammalian viruses was associated with host persistence. To substantiate the existence of large-scale RNA structure differences between viruses, a large set of alignments of mammalian RNA viruses and rRNA sequences as controls were examined by thermodynamic methods (to calculate minimum free energy differences) and by algorithmically independent RNAz and Pfold methods. These methods produced generally concordant results and identified substantial differences in the degrees of evolutionarily conserved, sequence order-dependent RNA secondary structure between virus genera and groups. A probe hybridization accessibility assay was used to investigate the physical nature of GORS. Transcripts of hepatitis C virus (HCV), hepatitis G virus/GB virus-C (HGV/GBV-C), and murine norovirus, which are predicted to be structured, were largely inaccessible to hybridization in solution, in contrast to the almost universal binding of probes to a range of unstructured virus transcripts irrespective of G+C content. Using atomic force microscopy, HCV and HGV/GBV-C RNA was visualized as tightly compacted prolate spheroids, while under the same experimental conditions the predicted unstructured poliovirus and rubella virus RNA were pleomorphic and had extensively single-stranded RNA on deposition. Bioinformatic and physical characterization methods both identified fundamental differences in the configurations of viral genomic RNA that may modify their interactions with host cell defenses and their ability to persist.


Author(s):  
P. Simmonds ◽  
L. Cuypers ◽  
W.L. Irving ◽  
J. McLauchlan ◽  
G.S. Cooke ◽  
...  

ABSTRACTMechanisms underlying the ability of hepatitis C virus (HCV) to establish persistent infections and induce progressive liver disease remain poorly understood. HCV is one of several positive-stranded RNA viruses capable of establishing persistence in their immunocompetent vertebrate hosts, an attribute associated with formation of large scale RNA structure in their genomic RNA. We developed novel methods to analyse and visualise genome-scale ordered RNA structure (GORS) predicted from the increasingly large datasets of complete genome sequences of HCV. Structurally conserved RNA secondary structure in coding regions of HCV localised exclusively to polyprotein ends (core, NS5B). Coding regions elsewhere were also intensely structured based on elevated minimum folding energy difference (MFED) values, but the actual stem-loop elements involved in genome folding were structurally entirely distinct, even between subtypes 1a and 1b. Dynamic remodelling was further evident from comparison of HCV strains in different host genetic background. Significantly higher MFED values, greater suppression of UpA dinucleotide frequencies and restricted diversification were found in subjects with the TT genotype of the rs12979860 SNP in the IFNL4 gene compared to the CC (non-expressing) allele. These structural and compositional associations with expression of interferon-λ4 were recapitulated on a larger scale by higher MFED values and greater UpA suppression of genotype 1 compared to genotype 3a, associated with previously reported HCV genotype-associated differences in hepatic interferon-stimulated gene induction. Associations between innate cellular responses with HCV structure and further evolutionary constraints represents an important new element in RNA virus evolution and the adaptive interplay between virus and host.


Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1765-1778
Author(s):  
Gregory J Budziszewski ◽  
Sharon Potter Lewis ◽  
Lyn Wegrich Glover ◽  
Jennifer Reineke ◽  
Gary Jones ◽  
...  

Abstract We have undertaken a large-scale genetic screen to identify genes with a seedling-lethal mutant phenotype. From screening ~38,000 insertional mutant lines, we identified >500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for >200 mutants, molecularly characterized 54 mutants, and provided a detailed description for 22 of them. Most of the seedling-lethal mutants seem to affect chloroplast function because they display altered pigmentation and affect genes encoding proteins predicted to have chloroplast localization. Although a high level of functional redundancy in Arabidopsis might be expected because 65% of genes are members of gene families, we found that 41% of the essential genes found in this study are members of Arabidopsis gene families. In addition, we isolated several interesting classes of mutants and genes. We found three mutants in the recently discovered nonmevalonate isoprenoid biosynthetic pathway and mutants disrupting genes similar to Tic40 and tatC, which are likely to be involved in chloroplast protein translocation. Finally, we directly compared T-DNA and Ac/Ds transposon mutagenesis methods in Arabidopsis on a genome scale. In each population, we found only about one-third of the insertion mutations cosegregated with a mutant phenotype.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jingru Zhou ◽  
Yingping Zhuang ◽  
Jianye Xia

Abstract Background Genome-scale metabolic model (GSMM) is a powerful tool for the study of cellular metabolic characteristics. With the development of multi-omics measurement techniques in recent years, new methods that integrating multi-omics data into the GSMM show promising effects on the predicted results. It does not only improve the accuracy of phenotype prediction but also enhances the reliability of the model for simulating complex biochemical phenomena, which can promote theoretical breakthroughs for specific gene target identification or better understanding the cell metabolism on the system level. Results Based on the basic GSMM model iHL1210 of Aspergillus niger, we integrated large-scale enzyme kinetics and proteomics data to establish a GSMM based on enzyme constraints, termed a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO). The results show that enzyme constraints effectively improve the model’s phenotype prediction ability, and extended the model’s potential to guide target gene identification through predicting metabolic phenotype changes of A. niger by simulating gene knockout. In addition, enzyme constraints significantly reduced the solution space of the model, i.e., flux variability over 40.10% metabolic reactions were significantly reduced. The new model showed also versatility in other aspects, like estimating large-scale $$k_{{cat}}$$ k cat values, predicting the differential expression of enzymes under different growth conditions. Conclusions This study shows that incorporating enzymes’ abundance information into GSMM is very effective for improving model performance with A. niger. Enzyme-constrained model can be used as a powerful tool for predicting the metabolic phenotype of A. niger by incorporating proteome data. In the foreseeable future, with the fast development of measurement techniques, and more precise and rich proteomics quantitative data being obtained for A. niger, the enzyme-constrained GSMM model will show greater application space on the system level.


2019 ◽  
Vol 113 (11) ◽  
pp. 678-684 ◽  
Author(s):  
I-Ching Sam ◽  
Magelda Montoya ◽  
Chong Long Chua ◽  
Yoke Fun Chan ◽  
Andrew Pastor ◽  
...  

Abstract Background Zika virus (ZIKV) is believed to be endemic in Southeast Asia. However, there have been few Zika cases reported to date in Malaysia, which could be due to high pre-existing levels of population immunity. Methods To determine Zika virus (ZIKV) seroprevalence in Kuala Lumpur, Malaysia, 1085 serum samples from 2012, 2014–2015 and 2017 were screened for anti-ZIKV antibodies using a ZIKV NS1 blockade-of-binding assay. Reactive samples were confirmed using neutralization assays against ZIKV and the four dengue virus (DENV) serotypes. A sample was possible ZIKV seropositive with a ZIKV 50% neutralization (NT50) titre ≥20. A sample was probable ZIKV seropositive if, in addition, all DENV NT50 titres were <20 or the ZIKV NT50 titre was >4-fold greater than the highest DENV NT50 titre. Results We found low rates of possible ZIKV seropositivity (3.3% [95% confidence interval {CI} 2.4 to 4.6]) and probable ZIKV seropositivity (0.6% [95% CI 0.3 to 1.4]). Possible ZIKV seropositivity was independently associated with increasing age (odds ratio [OR] 1.04 [95% CI 1.02 to 1.06], p<0.0001) and male gender (OR 3.5 [95% CI 1.5 to 8.6], p=0.005). Conclusions The low ZIKV seroprevalence rate, a proxy for population immunity, does not explain the low incidence of Zika in dengue-hyperendemic Kuala Lumpur. Other factors, such as the possible protective effects of pre-existing flavivirus antibodies or reduced transmission by local mosquito vectors, should be explored. Kuala Lumpur is at high risk of a large-scale Zika epidemic.


2017 ◽  
Vol 63 (4) ◽  
pp. 287-295 ◽  
Author(s):  
Ying Zhang ◽  
Dongmei Yan ◽  
Lin Xia ◽  
Xin Zhao ◽  
George Osei-Adjei ◽  
...  

Bacterial noncoding RNAs (ncRNA) regulate diverse cellular processes, including virulence and environmental fitness. The malS 5′ untranslated region (named malS-5′UTR) was identified as a regulatory ncRNA that increases the invasive capacity of Salmonella enterica serovar Typhi. An IntaRNA search suggested base pairing between malS-5′UTR and hisG mRNA, a key gene in the histidine biosynthetic pathway. Overexpression of malS-5′UTR markedly reduced bacterial growth in minimal medium without histidine. Overexpression of malS-5′UTR increased mRNA from his operon genes, independently of the bax gene, and decreased HisG protein in Salmonella Typhi. RNA structure analysis showed base pairing of the malS-5′UTR RNA with the hisG mRNA across the ribosome binding site. Thus, we propose that malS-5′UTR inhibited hisG translation, probably by base pairing to the Shine–Dalgarno sequence.


Science ◽  
2021 ◽  
pp. eabi8870
Author(s):  
Saba Parvez ◽  
Chelsea Herdman ◽  
Manu Beerens ◽  
Korak Chakraborti ◽  
Zachary P. Harmer ◽  
...  

CRISPR-Cas9 can be scaled up for large-scale screens in cultured cells, but CRISPR screens in animals have been challenging because generating, validating, and keeping track of large numbers of mutant animals is prohibitive. Here, we report Multiplexed Intermixed CRISPR Droplets (MIC-Drop), a platform combining droplet microfluidics, single-needle en masse CRISPR ribonucleoprotein injections, and DNA barcoding to enable large-scale functional genetic screens in zebrafish. The platform can efficiently identify genes responsible for morphological or behavioral phenotypes. In one application, we show MIC-Drop can identify small molecule targets. Furthermore, in a MIC-Drop screen of 188 poorly characterized genes, we discover several genes important for cardiac development and function. With the potential to scale to thousands of genes, MIC-Drop enables genome-scale reverse-genetic screens in model organisms.


2021 ◽  
Author(s):  
Victoria SA. Momyer ◽  
Samantha Dixon ◽  
Q. John Liu ◽  
Brian Wee ◽  
Tiffany Y. Chen ◽  
...  

Given the ongoing transmission and emergence of SARS-Cov-2 variants globally, it is critical to have a timely assessment on individuals' immune responses as well as population immunity. Important questions such as the durability of COVID-19 immunity or the efficacy of vaccines require large datasets to generate meaningful insights. However, due to the complexity and relatively high-cost of many immunity assays and the needs for blood-drawing specialists, these assays were mostly limited to small-scale clinical studies. Our work demonstrated the potential of a non-invasive, inexpensive and data-driven solution for large-scale immunity surveillance and for predictive modeling of vaccine efficacy. Combining a proprietary saliva processing method and an ultra-sensitive digital detection technology, we were able to rapidly gather information regarding personalized immune response following infection or vaccination, monitor temporal evolution, and optimize predictive models for variant protection.


2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Georg Basler ◽  
Alisdair R. Fernie ◽  
Zoran Nikoloski

Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.


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