RESUMO
In recent years, the function of noncoding RNAs (ncRNAs) as regulatory molecules of cell physiology has begun to be better understood. Advances in viral molecular biology have shown that host ncRNAs, cellular factors, and virus-derived ncRNAs and their interplay are strongly disturbed during viral infections. Nevertheless, the folding of RNA virus genomes has also been identified as a critical factor in regulating canonical and non-canonical functions. Due to the influence of host ncRNAs and the structure of RNA viral genomes, complex molecular and cellular processes in infections are modulated. We propose three main categories to organize the current information about RNA-RNA interactions in some well-known human viruses. The first category shows examples of host ncRNAs associated with the immune response triggered in viral infections. Even though miRNAs introduce a standpoint, they are briefly presented to keep researchers moving forward in uncovering other RNAs. The second category outlines interactions between virus-host ncRNAs, while the third describes how the structure of the RNA viral genome serves as a scaffold for processing virus-derived RNAs. Our grouping may provide a comprehensive framework to classify ncRNA-host-cell interactions for emerging viruses and diseases. In this sense, we introduced them to organize DENV-host-cell interactions.
Assuntos
Vírus da Dengue , Genoma Viral , RNA não Traduzido , RNA Viral , Vírus da Dengue/genética , Vírus da Dengue/fisiologia , Humanos , RNA não Traduzido/genética , RNA não Traduzido/metabolismo , RNA Viral/genética , RNA Viral/metabolismo , Interações Hospedeiro-Patógeno/genética , Dengue/virologia , MicroRNAs/genética , MicroRNAs/metabolismo , AnimaisRESUMO
In recent years, a population of small RNA fragments derived from non-coding RNAs (sfd-RNAs) has gained significant interest due to its functional and structural resemblance to miRNAs, adding another level of complexity to our comprehension of small-RNA-mediated gene regulation. Despite this, scientists need more tools to test the differential expression of sfd-RNAs since the current methods to detect miRNAs may not be directly applied to them. The primary reasons are the lack of accurate small RNA and ncRNA annotation, the multi-mapping read (MMR) placement, and the multicopy nature of ncRNAs in the human genome. To solve these issues, a methodology that allows the detection of differentially expressed sfd-RNAs, including canonical miRNAs, by using an integrated copy-number-corrected ncRNA annotation was implemented. This approach was coupled with sixteen different computational strategies composed of combinations of four aligners and four normalization methods to provide a rank-order of prediction for each differentially expressed sfd-RNA. By systematically addressing the three main problems, we could detect differentially expressed miRNAs and sfd-RNAs in dengue virus-infected human dermal microvascular endothelial cells. Although more biological evaluations are required, two molecular targets of the hsa-mir-103a and hsa-mir-494 (CDK5 and PI3/AKT) appear relevant for dengue virus (DENV) infections. Here, we performed a comprehensive annotation and differential expression analysis, which can be applied in other studies addressing the role of small fragment RNA populations derived from ncRNAs in virus infection.
RESUMO
Whether RNA-RNA interactions of cytoplasmic RNA viruses, such as Betacoronavirus, might end in the biogenesis of putative virus-derived small RNAs as miRNA-like molecules has been controversial. Even more, whether RNA-RNA interactions of wild animal viruses may act as virus-derived small RNAs is unknown. Here, we address these issues in four ways. First, we use conserved RNA structures undergoing negative selection in the genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 circulating in different bat species, intermediate animals, and human hosts. Second, a systematic literature review was conducted to identify Betacoronavirus-targeting hsa-miRNAs involved in lung cell infection. Third, we employed sophisticated long-range RNA-RNA interactions to refine the seed sequence homology of hsa-miRNAs with conserved RNA structures. Fourth, we used high-throughput RNA sequencing of a Betacoronavirus-infected epithelial lung cancer cell line (Calu-3) to validate the results. We proposed nine potential virus-derived small RNAs: two vsRNAs in SARS-CoV (Bats: SB-vsRNA-ORF1a-3p; SB-vsRNA-S-5p), one vsRNA in MERS-CoV (Bats: MB-vsRNA-ORF1b-3p), and six vsRNAs in SARS-CoV-2 (Bats: S2B-vsRNA-ORF1a-5p; intermediate animals: S2I-vsRNA-ORF1a-5p; and humans: S2H-vsRNA-ORF1a-5p, S2H-vsRNA-ORF1a-3p, S2H-vsRNA-ORF1b-3p, S2H-vsRNA-ORF3a-3p), mainly encoded by nonstructural protein 3. Notably, Betacoronavirus-derived small RNAs targeted 74 differentially expressed genes in infected human cells, of which 55 upregulate the molecular mechanisms underlying acute respiratory distress syndrome (ARDS), and the 19 downregulated genes might be implicated in neurotrophin signaling impairment. These results reveal a novel small RNA-based regulatory mechanism involved in neuropathogenesis that must be further studied to validate its therapeutic use.
Assuntos
COVID-19 , Quirópteros , Neoplasias Pulmonares , MicroRNAs , Coronavírus da Síndrome Respiratória do Oriente Médio , Animais , Humanos , SARS-CoV-2/genética , Neoplasias Pulmonares/genética , MicroRNAs/genética , Linhagem Celular , Pulmão , Fatores de Crescimento NeuralRESUMO
A structural analysis over various spike proteins from three highly pathogenic Betacoronavirus was done to understand their structural differences. The proteins were modeled using crystal structures from SARS-CoV, MERS-CoV, and other Betacoronavirus that infect bats and pangolins. The group was split in two sets; the first set corresponds to the non-mutated spike proteins, while the second set corresponds to mutated spike variants alpha, beta, gamma, delta, omicron and mu; five of them classified as variants of concern and the last one as variant of interest. A conformational space exploration was carried out for every protein by using molecular dynamic simulations. Root mean square fluctuations, principal component and cross-correlation analysis were carried out over the dynamics to analyze the flexibility and rigidity of every protein in comparison to the wild type Spike protein from the SARS-CoV-2. The obtained results indicate that the proteins, which are not spread among humans, have smooth movements compared to those of SARS-CoV-2 and its variants. In addition, a relationship between the speed of the virulence and the movement of the protein can explain the behavior of delta and omicron variants.
Assuntos
SARS-CoV-2 , Glicoproteína da Espícula de Coronavírus , Humanos , Simulação de Dinâmica Molecular , Mutação , SARS-CoV-2/genética , Glicoproteína da Espícula de Coronavírus/química , Coronavírus Relacionado à Síndrome Respiratória Aguda Grave , Coronavírus da Síndrome Respiratória do Oriente Médio , AnimaisRESUMO
Zika virus (ZIKV), without a vaccine or an effective treatment approved to date, has globally spread in the last century. The infection caused by ZIKV in humans has changed progressively from mild to subclinical in recent years, causing epidemics with greater infectivity, tropism towards new tissues and other related symptoms as a product of various emergent ZIKV-host cell interactions. However, it is still unknown why or how the RNA genome structure impacts those interactions in differential evolutionary origin strains. Moreover, the genomic comparison of ZIKV strains from the sequence-based phylogenetic analysis is well known, but differences from RNA structure comparisons have barely been studied. Thus, in order to understand the RNA genome variability of lineages of various geographic distributions better, 410 complete genomes in a phylogenomic scanning were used to study the conservation of structured RNAs. Our results show the contemporary landscape of conserved structured regions with unique conserved structured regions in clades or in lineages within circulating ZIKV strains. We propose these structures as candidates for further experimental validation to establish their potential role in vital functions of the viral cycle of ZIKV and their possible associations with the singularities of different outbreaks that lead to ZIKV populations to acquire nucleotide substitutions, which is evidence of the local structure genome differentiation.
RESUMO
Lima bean (Phaseolus lunatus L.), one of the five domesticated Phaseolus bean crops, shows a wide range of ecological adaptations along its distribution range from Mexico to Argentina. These adaptations make it a promising crop for improving food security under predicted scenarios of climate change in Latin America and elsewhere. In this work, we combine long and short read sequencing technologies with a dense genetic map from a biparental population to obtain the chromosome-level genome assembly for Lima bean. Annotation of 28,326 gene models show high diversity among 1917 genes with conserved domains related to disease resistance. Structural comparison across 22,180 orthologs with common bean reveals high genome synteny and five large intrachromosomal rearrangements. Population genomic analyses show that wild Lima bean is organized into six clusters with mostly non-overlapping distributions and that Mesomerican landraces can be further subdivided into three subclusters. RNA-seq data reveal 4275 differentially expressed genes, which can be related to pod dehiscence and seed development. We expect the resources presented here to serve as a solid basis to achieve a comprehensive view of the degree of convergent evolution of Phaseolus species under domestication and provide tools and information for breeding for climate change resiliency.
Assuntos
Aclimatação/genética , Produtos Agrícolas/genética , Phaseolus/genética , Melhoramento Vegetal , Locos de Características Quantitativas , Argentina , Mapeamento Cromossômico , Mudança Climática , Domesticação , Genes de Plantas/genética , México , Dispersão Vegetal , RNA-Seq , Sementes , SinteniaRESUMO
Lo que se conoce tradicionalmente como análisis del transcriptoma comprende la caracterización y cuantificación del conjunto de RNAs transcritos en la célula. En los primeros años, los estudios del transcriptoma se enfocaron principalmente a RNA mensajeros o RNA codificantes. Más recientemente, debido a avances en la tecnología de secuenciammiento de última generación, los estudios del transcriptoma se han extendido a RNAs no codificantes. Estas moléculas presentan gran variedad de funciones en la regulación celular. Una caracterización completa del conjunto de ncRNAs no es alcanzable con las aproximaciones disponibles. Hoy en día la identificación de RNAs no codificantes y de sus RNA pequeños derivados, es un tema de vital importancia en el análisis genético. Uno de los avances recientes en el estudio del transcriptoma por ejemplo, se enfoca en la biología de RNA de interferencia y su aplicación clínica. Durante los últimos años se han desarrollado continuamente la capacidad de cómputo, eficiencia y capacidad de almacenamiento para modelar y procesar grandes volúmenes de información producto de secuenciamiento de última generación. Como consecuencia, esta revisión presenta el análisis del transcriptoma desde una perspectiva histórica unida a la modelación computacional de RNA no codificantes de datos de bibliotecas de RNAs pequeños.
What is commonly known about transcriptome studies encompass the characterization and quantification of the complete set of RNA transcripts produced by a cell. In its early days these analysis mainly focused on examination of messenger RNAs or coding RNAs. More recently, due to advances in next-generation sequencing technologies, transcriptome analysis has expanded to non-conding RNAs (ncRNAs). These molecules exhibit high variety of functions in cell regulation. Through characterization of complete sets of ncRNAs is not attainable with current approaches. At present de novo identification of ncRNAs and ncRNA-derived small RNAs is a major issue in genetic analysis. One of the most important recent advances of transcriptome analysis focuses, for example, on RNA interference (RNAi) biology and its clinical application. High-performance computing, storage capability and computational modeling have been continuously developed during last years to process and model large amounts of products of next generation sequencing methods. As consequence this review describes transcriptome sequencing analysis from a historical perspective to its link to computational approaches to model ncRNAs from small RNA library data.