Analysis of SARS-CoV-2 known and novel subgenomic mRNAs in cell culture, animal model, and clinical samples using LeTRS, a bioinformatic tool to identify unique sequence identifiers

Structural basis for the participation of the SARS-CoV-2 nucleocapsid protein in the template switch mechanism and genomic RNA reorganization

The COVID-19 pandemic has resulted in a significant toll of deaths worldwide, exceeding seven million individuals, prompting intensive research efforts aimed at elucidating the molecular mechanisms underlying the pathogenesis of SARS-CoV-2 infection. Despite the rapid development of effective vaccines and therapeutic interventions, COVID-19 remains a threat to humans due to the emergence of novel variants and largely unknown long-term consequences. Among the viral proteins, the nucleocapsid protein (N) stands out as the most conserved and abundant, playing the primary role in nucleocapsid assembly and genome packaging. The N protein is promiscuous for the recognition of RNA, yet it can perform specific functions. Here, we discuss the structural basis of specificity, which is directly linked to its regulatory role. Notably, the RNA chaperone activity of N is central to its multiple roles throughout the viral life cycle. This activity encompasses double-stranded RNA (dsRNA) annealing and melting and facilitates template switching, enabling discontinuous transcription. N also promotes the formation of membrane-less compartments through liquid-liquid phase separation, thereby facilitating the congregation of the replication and transcription complex. Considering the information available regarding the catalytic activities and binding signatures of the N protein-RNA interaction, this review focuses on the regulatory role of the SARS-CoV-2 N protein. We emphasize the participation of the N protein in discontinuous transcription, template switching, and RNA chaperone activity, including double-stranded RNA melting and annealing activities.

Improved sub-genomic RNA prediction with the ARTIC protocol

Viral subgenomic RNA (sgRNA) plays a major role in SARS-COV2's replication, pathogenicity, and evolution. Recent sequencing protocols, such as the ARTIC protocol, have been established. However, due to the viral-specific biological processes, analyzing sgRNA through viral-specific read sequencing data is a computational challenge. Current methods rely on computational tools designed for eukaryote genomes, resulting in a gap in the tools designed specifically for sgRNA detection. To address this, we make two contributions. Firstly, we present sgENERATE, an evaluation pipeline to study the accuracy and efficacy of sgRNA detection tools using the popular ARTIC sequencing protocol. Using sgENERATE, we evaluate periscope, a recently introduced tool that detects sgRNA from ARTIC sequencing data. We find that periscope has biased predictions and high computational costs. Secondly, using the information produced from sgENERATE, we redesign the algorithm in periscope to use multiple references from canonical sgRNAs to mitigate alignment issues and improve sgRNA and non-canonical sgRNA detection. We evaluate periscope and our algorithm, periscope_multi, on simulated and biological sequencing datasets and demonstrate periscope_multi's enhanced sgRNA detection accuracy. Our contribution advances tools for studying viral sgRNA, paving the way for more accurate and efficient analyses in the context of viral RNA discovery.

SARS-CoV-2 population dynamics in immunocompetent individuals in a closed transmission chain shows genomic diversity over the course of infection

BACKGROUND

SARS-CoV-2 remains rapidly evolving, and many biologically important genomic substitutions/indels have characterised novel SARS-CoV-2 lineages, which have emerged during successive global waves of the pandemic. Worldwide genomic sequencing has been able to monitor these waves, track transmission clusters, and examine viral evolution in real time to help inform healthcare policy. One school of thought is that an apparent greater than average divergence in an emerging lineage from contemporary variants may require persistent infection, for example in an immunocompromised host. Due to the nature of the COVID-19 pandemic and sampling, there were few studies that examined the evolutionary trajectory of SARS-CoV-2 in healthy individuals.

METHODS

We investigated viral evolutionary trends and participant symptomatology within a cluster of 16 SARS-CoV-2 infected, immunocompetent individuals with no co-morbidities in a closed transmission chain. Longitudinal nasopharyngeal swab sampling allowed characterisation of SARS-CoV-2 intra-host variation over time at both the dominant and minor genomic variant levels through Nimagen-Illumina sequencing.

RESULTS

A change in viral lineage assignment was observed in individual infections; however, there was only one indel and no evidence of recombination over the period of an acute infection. Minor and dominant genomic modifications varied between participants, with some minor genomic modifications increasing in abundance to become the dominant viral sequence during infection.

CONCLUSIONS

Data from this cohort of SARS-CoV-2-infected participants demonstrated that long-term persistent infection in an immunocompromised host was not necessarily a prerequisite for generating a greater than average frequency of amino acid substitutions. Amino acid substitutions at both the dominant and minor genomic sequence level were observed in immunocompetent individuals during infection showing that viral lineage changes can occur generating viral diversity.

Variations in the persistence of 5'-end genomic and subgenomic SARS-CoV-2 RNAs in wastewater from aircraft, airports and wastewater treatment plants

Wastewater sequencing has become a powerful supplement to clinical testing in monitoring SARS-CoV-2 infections in the post-COVID-19 pandemic era. While its applications in measuring the viral burden and main circulating lineages in the community have proved their efficacy, the variations in sequencing quality and coverage across the different regions of the SARS-CoV-2 genome are not well understood. Furthermore, it is unclear how different sample origins, viral extraction and concentration methods and environmental factors impact the reads sequenced from wastewater. Using high-coverage, amplicon-based, paired-end read sequencing of viral RNA extracted from wastewater collected directly from aircraft, pooled from different aircraft and airport buildings or from regular wastewater plants, we assessed the genome coverage across the sample groups with a focus on the 5'-end region covering the leader sequence and investigated whether it was possible to detect subgenomic RNA from viral material recovered from wastewater. We identified distinct patterns in the persistence of the different genomic regions across the different types of wastewaters and the existence of chimeric reads mapping to non-amplified regions. Our findings suggest that preservation of the 5'-end of the genome and the ability to detect subgenomic RNA reads, though highly susceptible to environment and sample processing conditions, may be indicative of the quality and amount of the viral RNA present in wastewater.

Computational methods in the analysis of SARS-CoV-2 in mammals: A systematic review of the literature

SARS-CoV-2 is an enveloped RNA virus that causes severe respiratory illness in humans and animals. It infects cells by binding the Spike protein to the host's angiotensin-converting enzyme 2 (ACE2). The bat is considered the natural host of the virus, and zoonotic transmission is a significant risk and can happen when humans come into close contact with infected animals. Therefore, understanding the interconnection between human, animal, and environmental health is important to prevent and control future coronavirus outbreaks. This work aimed to systematically review the literature to identify characteristics that make mammals suitable virus transmitters and raise the main computational methods used to evaluate SARS-CoV-2 in mammals. Based on this review, it was possible to identify the main factors related to transmissions mentioned in the literature, such as the expression of ACE2 and proximity to humans, in addition to identifying the computational methods used for its study, such as Machine Learning, Molecular Modeling, Computational Simulation, between others. The findings of the work contribute to the prevention and control of future outbreaks, provide information on transmission factors, and highlight the importance of advanced computational methods in the study of infectious diseases that allow a deeper understanding of transmission patterns and can help in the development of more effective control and intervention strategies.

Comparative analysis of bioinformatics tools to characterize SARS-CoV-2 subgenomic RNAs

During the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), positive-sense genomic RNA and subgenomic RNAs (sgRNAs) are synthesized by a discontinuous process of transcription characterized by a template switch, regulated by transcription-regulating sequences (TRS). Although poorly known about makeup and dynamics of sgRNAs population and function of its constituents, next-generation sequencing approaches with the help of bioinformatics tools have made a significant contribution to expand the knowledge of sgRNAs in SARS-CoV-2. For this scope to date, Periscope, LeTRS, sgDI-tector, and CORONATATOR have been developed. However, limited number of studies are available to compare the performance of such tools. To this purpose, we compared Periscope, LeTRS, and sgDI-tector in the identification of canonical (c-) and noncanonical (nc-) sgRNA species in the data obtained with the Illumina ARTIC sequencing protocol applied to SARS-CoV-2-infected Caco-2 cells, sampled at different time points. The three software showed a high concordance rate in the identification and in the quantification of c-sgRNA, whereas more differences were observed in nc-sgRNA. Overall, LeTRS and sgDI-tector result to be adequate alternatives to Periscope to analyze Fastq data from sequencing platforms other than Nanopore.

Analysis of SARS-CoV-2 Population Genetics from Samples Associated with Huanan Market and Early Cases Identifies Substitutions Associated with Future Variants of Concern

SARS-CoV-2 began spreading through human-to-human transmission first within China and then worldwide, with increasing sequence diversity associated with time and the further spread of the virus. The spillover events in the Huanan market were associated with two lineages of SARS-CoV-2 (lineages A and B). Infecting virus populations and those in infected individuals consist of a dominant genomic sequence and minor genomic variants; these latter populations can indicate sites on the genome that may be subject to mutational changes-either neutral or advantageous sites and those that act as a reservoir for future dominant variants-when placed under selection pressure. The earliest deposited sequences with human infections associated with the Huanan market shared very close homology with each other and were all lineage B. However, there were minor genomic variants present in each sample that encompassed synonymous and non-synonymous changes. Fusion sequences characteristic of defective RNA were identified that could potentially link transmission chains between individuals. Although all the individuals appeared to have lineage B as the dominant sequence, nucleotides associated with lineage A could be found at very low frequencies. Several substitutions (but not deletions) associated with much later variants of concern (VoCs) were already present as minor genomic variants. This suggests that low-frequency substitutions at the start of a pandemic could be a reservoir of future dominant variants and/or provide information on potential sites within the genome associated with future plasticity.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

sgRNAs: A SARS-CoV-2 emerging issue

Like for other coronaviruses, SARS-CoV-2 gene expression strategy is based on the synthesis of a nested set of subgenomic mRNA species (sgRNAs). These sgRNA are synthesized using a "discontinuous transcription" mechanism that relies on template switching at Transcription Regulatory Sequences (TRS). Both canonical (c-sgRNA) and non-canonical (nc-sgRNA, less numerous) subgenomic RNA species can be produced. Currently, sgRNAs are investigated on the basis of sequence data obtained through next generation sequencing (NGS), and bioinformatic tools are crucial for their identification, characterization and quantification. To date, few software have been developed to this aim, whose reliability and applicability to all the available NGS platforms need to be established, to build confidence on the information resulting from such tools. In fact, these information may be crucial for the in depth elucidation of viral expression strategy, particularly in respect of the significance of nc-sgRNAs, and for the possible use of sgRNAs as potential markers of virus replicative activity in infected patients.

The P323L substitution in the SARS-CoV-2 polymerase (NSP12) confers a selective advantage during infection

BACKGROUND

The mutational landscape of SARS-CoV-2 varies at the dominant viral genome sequence and minor genomic variant population. During the COVID-19 pandemic, an early substitution in the genome was the D614G change in the spike protein, associated with an increase in transmissibility. Genomes with D614G are accompanied by a P323L substitution in the viral polymerase (NSP12). However, P323L is not thought to be under strong selective pressure.

RESULTS

Investigation of P323L/D614G substitutions in the population shows rapid emergence during the containment phase and early surge phase during the first wave. These substitutions emerge from minor genomic variants which become dominant viral genome sequence. This is investigated in vivo and in vitro using SARS-CoV-2 with P323 and D614 in the dominant genome sequence and L323 and G614 in the minor variant population. During infection, there is rapid selection of L323 into the dominant viral genome sequence but not G614. Reverse genetics is used to create two viruses (either P323 or L323) with the same genetic background. L323 shows greater abundance of viral RNA and proteins and a smaller plaque morphology than P323.

CONCLUSIONS

These data suggest that P323L is an important contribution in the emergence of variants with transmission advantages. Sequence analysis of viral populations suggests it may be possible to predict the emergence of a new variant based on tracking the frequency of minor variant genomes. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions.

Screening and Analysis of Serum Protein Biomarkers Infected by Coronavirus Disease 2019 (COVID-19)

Coronavirus disease 2019 (COVID-19) has spread widely around the world, and in-depth research on COVID-19 is necessary for biomarkers and target drug discovery. This analysis collected serum from six COVID-19-infected patients and six healthy people. The protein changes in the infected and healthy control serum samples were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The differential protein signature in both groups was retrieved and analyzed by the Kyoto Encyclopedia of Gene and Genomes (KEGG), Gene ontology, COG/KOG, protein-protein interaction, and protein domain interactions tools. We shortlisted 24 differentially expressed proteins between both groups. Ten genes were significantly up-regulated in the infection group, and fourteen genes were significantly down-regulated. The GO and KEGG pathway enrichment analysis suggested that the chromosomal part and chromosome were the most enriched items. The oxytocin signaling pathway was the most enriched item of KEGG analysis. The netrin module (non-TIMP type) was the most enriched protein domain in this study. Functional analysis of S100A9, PIGR, C4B, IL-6R, IGLV3-19, IGLV3-1, and IGLV5-45 revealed that SARS-CoV-2 was closely related to immune response.