Ribogenomics: the science and knowledge of RNA

Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples.

IMPORTANCE

Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

Regulation of the HIF switch in human endothelial and cancer cells

Hypoxia-inducible factors (HIFs) are transcription factors that reprogram the transcriptome for cells to survive hypoxic insults and oxidative stress. They are important during embryonic development and reprogram the cells to utilize glycolysis when the oxygen levels are extremely low. This metabolic change facilitates normal cell survival as well as cancer cell survival. The key feature in survival is the transition between acute hypoxia and chronic hypoxia, and this is regulated by the transition between HIF-1 expression and HIF-2/HIF-3 expression. This transition is observed in many human cancers and endothelial cells and referred to as the HIF Switch. Here we discuss the mechanisms involved in the HIF Switch in human endothelial and cancer cells which include mRNA and protein levels of the alpha chains of the HIFs. A major continuing effort in this field is directed towards determining the differences between normal and tumor cell utilization of this important pathway, and how this could lead to potential therapeutic approaches.

Decoding the ribosome's hidden language: rRNA modifications as key players in cancer dynamics and targeted therapies

Ribosomal RNA (rRNA) modifications, essential components of ribosome structure and function, significantly impact cellular proteomics and cancer biology. These chemical modifications transcend structural roles, critically shaping ribosome functionality and influencing cellular protein profiles. In this review, the mechanisms by which rRNA modifications regulate both rRNA functions and broader cellular physiological processes are critically discussed. Importantly, by altering the translational output, rRNA modifications can shift the cellular equilibrium towards oncogenesis, thus playing a key role in cancer development and progression. Moreover, a special focus is placed on the functions of mitochondrial rRNA modifications and their aberrant expression in cancer, an area with profound implications yet largely uncharted. Dysregulation in these modifications can lead to metabolic dysfunction and apoptosis resistance, hallmark traits of cancer cells. Furthermore, the current challenges and future perspectives in targeting rRNA modifications are highlighted as a therapeutic approach for cancer treatment. In conclusion, rRNA modifications represent a frontier in cancer research, offering novel insights and therapeutic possibilities. Understanding and harnessing these modifications can pave the way for breakthroughs in cancer treatment, potentially transforming the approach to combating this complex disease.

Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning

Ribonucleic acids (RNAs) play important roles in cellular regulation. Consequently, dysregulation of both coding and non-coding RNAs has been implicated in several disease conditions in the human body. In this regard, a growing interest has been observed to probe into the potential of RNAs to act as drug targets in disease conditions. To accelerate this search for disease-associated novel RNA targets and their small molecular inhibitors, machine learning models for binding affinity prediction were developed specific to six RNA subtypes namely, aptamers, miRNAs, repeats, ribosomal RNAs, riboswitches and viral RNAs. We found that differences in RNA sequence composition, flexibility and polar nature of RNA-binding ligands are important for predicting the binding affinity. Our method showed an average Pearson correlation (r) of 0.83 and a mean absolute error of 0.66 upon evaluation using the jack-knife test, indicating their reliability despite the low amount of data available for several RNA subtypes. Further, the models were validated with external blind test datasets, which outperform other existing quantitative structure-activity relationship (QSAR) models. We have developed a web server to host the models, RNA-Small molecule binding Affinity Predictor, which is freely available at: https://web.iitm.ac.in/bioinfo2/RSAPred/.

Multiomic Droplet-Based Assay for Ultralow Input Samples

The extraction and separation of cellular compounds are crucial steps in numerous biological protocols, particularly in multiomics studies, where several cellular modalities are examined simultaneously. While magnetic particle extraction is commonly used, it may not be applicable for ultralow input samples. Microfluidics has made possible the analysis of rare or low-materiality samples such as circulating tumor cells or single cells through miniaturization of numerous protocols. In this study, a microfluidics workflow for separating different cellular modalities from ultralow input samples is presented. This approach is based on magnetic tweezers technology, allowing the extraction and resuspension of magnetic particles between consecutive nanoliter droplets to perform multistep assays on small volumes. The ability to separate and recover mRNA and gDNA in samples containing less than 10 cells is demonstrated, achieving separation efficiency comparable to the one obtained with conventional pipetting but with a significantly lower amount of starting material, typically 1-2 orders of magnitude less.

Transcriptomic Profiling of Influenza A Virus-Infected Mouse Lung at Recovery Stage Using RNA Sequencing

Influenza A virus (IAV) is known to cause mild to severe respiratory illness. Under some conditions, the infection can lead to pneumonia (viral or bacterial), acute respiratory distress syndrome, and other complications that can be fatal, especially in vulnerable populations such as the elderly, young children, and individuals with underlying health conditions. Despite previous studies, little is known about the host immune response and neuroimmune interactions in IAV infection. Using RNA sequencing, we performed transcriptomic analysis of murine lung tissue 21 days post infection (dpi) with IAV (H1N1) in order to find the differentially expression genes (DEGs) related to the host immune response and neuroimmune interactions inside the lung during recovery. Among 792 DEGs, 434 genes were up-regulated, whereas 358 genes were down-regulated. The most prominent molecular functions of the up-regulated genes were related to the immune response and tissue repair, whereas a large proportion of the down-regulated genes were associated with neural functions. Although further molecular/functional studies need to be performed for these DEGs, our results facilitate the understanding of the host response (from innate immunity to adaptive immunity) and neuroimmune interactions in infected lungs at the recovery stage of IAV infection. These genes might have potential uses as mechanistic/diagnostic biomarkers and represent possible targets for anti-IAV therapies.

Data Mining of Microarray Datasets in Translational Neuroscience

Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

Possible Genetic Risks from Heat-Damaged DNA in Food

The consumption of foods prepared at high temperatures has been associated with numerous health risks. To date, the chief identified source of risk has been small molecules produced in trace levels by cooking and reacting with healthy DNA upon consumption. Here, we considered whether the DNA in food itself also presents a hazard. We hypothesize that high-temperature cooking may cause significant damage to the DNA in food, and this damage might find its way into cellular DNA by metabolic salvage. We tested cooked and raw foods and found high levels of hydrolytic and oxidative damage to all four DNA bases upon cooking. Exposing cultured cells to damaged 2'-deoxynucleosides (particularly pyrimidines) resulted in elevated DNA damage and repair responses in the cells. Feeding a deaminated 2'-deoxynucleoside (2'-deoxyuridine), and DNA containing it, to mice resulted in substantial uptake into intestinal genomic DNA and promoted double-strand chromosomal breaks there. The results suggest the possibility of a previously unrecognized pathway whereby high-temperature cooking may contribute to genetic risks.

Contribution of Nudt12 enzyme to differentially methylated dinucleotides of 5'RNA cap structure

Recent findings have substantially broadened our knowledge about the diversity of modifications of the 5'end of RNAs, an issue generally attributed to mRNA cap structure (m⁷GpppN). Nudt12 is one of the recently described new enzymatic activities involved in cap metabolism. However, in contrast to its roles in metabolite-cap turnover (e.g., NAD-cap) and NADH/NAD metabolite hydrolysis, little is known regarding its hydrolytic activity towards dinucleotide cap structures. In order to gain further insight into this Nudt12 activity, comprehensive analysis with a spectrum of cap-like dinucleotides was performed with respect to different nucleotide types adjacent to the (m⁷)G moiety and its methylation status. Among the tested compounds, GpppA, GpppA_m, and Gpppm⁶A_m were identified as novel potent Nudt12 substrates, with K_M values in the same range as that of NADH. Interestingly, substrate inhibition of Nudt12 catalytic activity was detected in the case of the GpppG dinucleotide, a phenomenon not reported to date. Finally, comparison of Nudt12 with DcpS and Nud16, two other enzymes with known activity on dinucleotide cap structures, revealed their overlapping and more specific substrates. Altogether, these findings provide a basis for clarifying the role of Nudt12 in cap-like dinucleotide turnover.

Test of an Improved DNA and RNA Purification Protocol—Importance of Proteinase K and Co-Purified Small RNAs

Optimized and reliable DNA/RNA extraction protocols are a vital tool in clinical practice in the context of molecular testing. Here, we present our successful attempt to enhance the quantity of RNA isolated from clinical specimens, which we originally found challenging (breast and testis). We compared several purification methods with special focus on two AllPrep system-based protocols (QIAGEN). Our data suggest that addition of proteinase K may markedly increase RNA and, in some cases, also DNA yield. The extraction kit used, AllPrep DNA/RNA/miRNA universal kit, provides RNA amounts comparable with the phenol-chloroform extraction method; however, part of the final yield consisted of small RNAs, visible as a thick band in the bioanalyzer gel-like image (5S peak). The 5S peak, albeit in some cases dominating the bioanalyzer image, plays only a small role in RT-qPCR analysis, and Qubit or NanoDrop measurements can still be used as a reliable estimate of starting amounts of mRNA for downstream analyses. In conclusion, we showed that implementing a protocol containing a step of proteinase K digestion markedly increases RNA yield. The AllPrep DNA/RNA/miRNA Universal Kit can be successfully used for simultaneous extraction of DNA and total RNA, irrespective of the tissue of origin, and does not present inconveniences related to phenol-chloroform extraction.

A cap 0-dependent mRNA capture method to analyze the yeast transcriptome

Analysis of the protein coding transcriptome by the RNA sequencing requires either enrichment of the desired fraction of coding transcripts or depletion of the abundant non-coding fraction consisting mainly of rRNA. We propose an alternative mRNA enrichment strategy based on the RNA-binding properties of the human IFIT1, an antiviral protein recognizing cap 0 RNA. Here, we compare for Saccharomyces cerevisiae an IFIT1-based mRNA pull-down with yeast targeted rRNA depletion by the RiboMinus method. IFIT1-based RNA capture depletes rRNA more effectively, producing high quality RNA-seq data with an excellent coverage of the protein coding transcriptome, while depleting cap-less transcripts such as mitochondrial or some non-coding RNAs. We propose IFIT1 as a cost effective and versatile tool to prepare mRNA libraries for a variety of organisms with cap 0 mRNA ends, including diverse plants, fungi and eukaryotic microbes.

Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth

The growth rate hypothesis (GRH) posits that variation in organismal stoichiometry (C:P and N:P ratios) is driven by growth-dependent allocation of P to ribosomal RNA. The GRH has found broad but not uniform support in studies across diverse biota and habitats. We synthesise information on how and why the tripartite growth-RNA-P relationship predicted by the GRH may be uncoupled and outline paths for both theoretical and empirical work needed to broaden the working domain of the GRH. We found strong support for growth to RNA (r²  = 0.59) and RNA-P to P (r²  = 0.63) relationships across taxa, but growth to P relationships were relatively weaker (r²  = 0.09). Together, the GRH was supported in ~50% of studies. Mechanisms behind GRH uncoupling were diverse but could generally be attributed to physiological (P accumulation in non-RNA pools, inactive ribosomes, translation elongation rates and protein turnover rates), ecological (limitation by resources other than P), and evolutionary (adaptation to different nutrient supply regimes) causes. These factors should be accounted for in empirical tests of the GRH and formalised mathematically to facilitate a predictive understanding of growth.

Comprehensive analyses of transcriptomes induced by Lyme spirochete infection to CNS model system

BACKGROUND

Lyme disease is a zoonotic disease caused by infection with Borrelia burgdorferi (Bb), the involvement of the nervous system in Lyme disease is usually referred to as Lyme neuroborreliosis (LNB). LNB has diverse clinical manifestations, most commonly including meningitis, Bell's palsy, and encephalitis. However, the molecular pathogenesis of neuroborreliosis is still poorly understood. Comprehensive transcriptomic analysis following Bb infection could provide new insights into the pathogenesis of LNB and may identify novel biomarkers or therapeutic targets for LNB diagnosis and treatment.

METHODS

In the present study, we pooled transcriptomic dataset of Macaca mulatta (rhesus) from our laboratory and the human astrocyte dataset GSE85143 from the Gene Expression Omnibus database to screen common differentially expressed genes (DEGs) in the Bb infection group and the control group. Functional and enrichment analyses were applied for the DEGs. Protein-Protein Interaction network, and hub genes were identified using the Search Tool for the Retrieval of Interaction Genes database and the CytoHubba plugin. Finally, mRNA expression of hub genes was validated in vitro and ex vivo from Bb infected models and normal controls by quantitative reverse transcription PCR (qRT-PCR).

RESULTS

A total of 80 upregulated DEGs and 32 downregulated DEGs were identified. Among them, 11 hub genes were selected. The pathway enrichment analyses on 11 hub genes revealed that the PI3K-Akt signaling pathway was significantly enriched. The mRNA levels of ANGPT1, TLR6, SREBF1, LDLR, TNC, and ITGA2 in U251 cells and/or rhesus brain explants by exposure to Bb were validated by qRT-PCR.

CONCLUSION

Our study suggested that TLR6, ANGPT1, LDLR, SREBF1, TNC, and ITGA may be candidate mammal biomarkers for LNB, and the TLR6/PI3K-Akt signaling pathway may play an important role in LNB pathogenesis.

The hypoxia-induced changes in miRNA-mRNA in RNA-induced silencing complexes and HIF-2 induced miRNAs in human endothelial cells

The cellular adaptive response to hypoxia relies on the expression of hypoxia-inducible factors (HIFs), HIF-1 and HIF-2. HIFs regulate global gene expression changes during hypoxia that are necessary for restoring oxygen homeostasis and promoting cell survival. In the early stages of hypoxia, HIF-1 is elevated, whereas at the later stages, HIF-2 becomes the predominant form. What governs the transition between the two HIFs (the HIF switch) and the role of miRNAs in this regulation are not completely clear. Genome-wide expression studies on the miRNA content of RNA-induced silencing complexes (RISC) in HUVECs exposed to hypoxia compared to the global miRNA-Seq analysis revealed very specific differences between these two populations. We analyzed the miRNA and mRNA composition of RISC at 2 h (mainly HIF-1 driven), 8 h (HIF-1 and HIF-2 elevated), and 16 h (mainly HIF-2 driven) in a gene ontology context. This allowed for determining the direct impact of the miRNAs in modulating the cellular signaling pathways involved in the hypoxic adaptive response. Our results indicate that the miRNA-mRNA RISC components control the adaptive responses, and this does not always rely on the miRNA transcriptional elevations during hypoxia. Furthermore, we demonstrate that the hypoxic levels of the vast majority of HIF-1-dependent miRNAs (including miR-210-3p) are also HIF-2 dependent and that HIF-2 governs the expression of 11 specific miRNAs. In summary, the switch from HIF-1 to HIF-2 during hypoxia provides an important level of miRNA-driven control in the adaptive pathways in endothelial cells.

Using total RNA quality metrics for time since deposition estimates in degrading bloodstains

The physicochemical changes occurring in biomolecules in degrading bloodstains can be used to approximate the time since deposition (TSD) of bloodstains. This would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has traditionally targeted mRNA and miRNA. Bovine blood with ACD-A anticoagulant was deposited and stored in plastic microcentrifuge tubes at 21 or 4°C and tested over different timepoints spanning 1 week. Total RNA was extracted from each sample and analyzed using automated high sensitivity gel electrophoresis. Nine RNA metrics were visually assessed and quantified using linear and mixed models. The RNA Integrity Number equivalent (RINe) and DV200 were not influenced by the addition of anticoagulant and demonstrated strong negative trends over time. The RINe model fit was high (R²  = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200. This suggests that these standardized metrics can be directly compared between scenarios and individuals, with DV200 having an inflection point at approximately 28 h. This study provides a novel approach for blood TSD research, revealing metrics that are not affected by inter-individual variation, and improving our understanding of the rapid RNA degradation occurring in bloodstains.

Highly Sensitive Detection of Human Pluripotent Stem Cells by Loop-Mediated Isothermal Amplification

For safe regenerative medicines, contaminated or remaining tumorigenic undifferentiated cells in cell-derived products must be rigorously assessed through sensitive assays. Although in vitro nucleic acid tests offer particularly sensitive tumorigenicity-associated assays, the human pluripotent stem cell (hPSC) detectability is partly constrained by the small input amount of RNA per test. To overcome this limitation, we developed reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays that are highly gene specific and robust against interfering materials. LAMP could readily assay microgram order of input sample per test and detected an equivalent model of 0.00002% hiPSC contamination in a simple one-pot reaction. For the evaluation of cell-derived total RNA, RT-LAMP detected spiked-in hPSCs among hPSC-derived trilineage cells utilizing multiple pluripotency RNAs. We also developed multiplex RT-LAMP assays and further applied for in situ cell imaging, achieving specific co-staining of pluripotency proteins and RNAs. Our attempts uncovered the utility of RT-LAMP approaches for tumorigenicity-associated assays, supporting practical applications of regenerative medicine.

MicroRNAs: master regulators in host-parasitic protist interactions

MicroRNAs (miRNAs) are a group of small non-coding RNAs present in a wide diversity of organisms. MiRNAs regulate gene expression at a post-transcriptional level through their interaction with the 3' untranslated regions of target mRNAs, inducing translational inhibition or mRNA destabilization and degradation. Thus, miRNAs regulate key biological processes, such as cell death, signal transduction, development, cellular proliferation and differentiation. The dysregulation of miRNAs biogenesis and function is related to the pathogenesis of diseases, including parasite infection. Moreover, during host-parasite interactions, parasites and host miRNAs determine the probability of infection and progression of the disease. The present review is focused on the possible role of miRNAs in the pathogenesis of diseases of clinical interest caused by parasitic protists. In addition, the potential role of miRNAs as targets for the design of drugs and diagnostic and prognostic markers of parasitic diseases is also discussed.

Anomalous HIV-1 RNA, How Cap-Methylation Segregates Viral Transcripts by Form and Function

The acquisition of m7G-cap-binding proteins is now recognized as a major variable driving the form and function of host RNAs. This manuscript compares the 5'-cap-RNA binding proteins that engage HIV-1 precursor RNAs, host mRNAs, small nuclear (sn)- and small nucleolar (sno) RNAs and sort into disparate RNA-fate pathways. Before completion of the transcription cycle, the transcription start site of nascent class II RNAs is appended to a non-templated guanosine that is methylated (m7G-cap) and bound by hetero-dimeric CBP80-CBP20 cap binding complex (CBC). The CBC is a nexus for the co-transcriptional processing of precursor RNAs to mRNAs and the snRNA and snoRNA of spliceosomal and ribosomal ribonucleoproteins (RNPs). Just as sn/sno-RNAs experience hyper-methylation of m7G-cap to trimethylguanosine (TMG)-cap, so do select HIV RNAs and an emerging cohort of mRNAs. TMG-cap is blocked from Watson:Crick base pairing and disqualified from participating in secondary structure. The HIV TMG-cap has been shown to license select viral transcripts for specialized cap-dependent translation initiation without eIF4E that is dependent upon CBP80/NCBP3. The exceptional activity of HIV precursor RNAs secures their access to maturation pathways of sn/snoRNAs, canonical and non-canonical host mRNAs in proper stoichiometry to execute the retroviral replication cycle.

Revisiting the Non-Coding Nature of Pospiviroids

Viroids are small, circular, highly structured pathogens that infect a broad range of plants, causing economic losses. Since their discovery in the 1970s, they have been considered as non-coding pathogens. In the last few years, the discovery of other RNA entities, similar in terms of size and structure, that were shown to be translated (e.g., cirRNAs, precursors of miRNA, RNA satellites) as well as studies showing that some viroids are located in ribosomes, have reignited the idea that viroids may be translated. In this study, we used advanced bioinformatic analysis, in vitro experiments and LC-MS/MS to search for small viroid peptides of the PSTVd. Our results suggest that in our experimental conditions, even though the circular form of PSTVd is found in ribosomes, no produced peptides were identified. This indicates that the presence of PSTVd in ribosomes is most probably not related to peptide production but rather to another unknown function that requires further study.

Accurate Prediction of Protein Sequences for Proteogenomics Data Integration

This book chapter discusses proteogenomics data integration and provides an overview into the different omics layer involved in defining the proteome of a living organism. Various aspects of genome variability affecting either the sequence or abundance level of proteins are discussed in this book chapter, such as the effect of single-nucleotide variants or larger genomic structural variants on the proteome. Next, various sequencing technologies are introduced and discussed from a proteogenomics data integration perspective such as those providing short- and long-read sequencing and listing their respective advantages and shortcomings for accurate protein variant prediction using genomic/transcriptomics sequencing data. Finally, the various bioinformatics tools used to process and analyze DNA/RNA sequencing data are discussed with the ultimate goal of obtaining accurately predicted sample-specific protein sequences that can be used as a drop-in replacement in existing approaches for peptide and protein identification using popular database search engines such as MSFragger, SearchGUI/PeptideShaker.

[PCR analysis of the expression of chromosome 18 genes in human liver tissue: interindividual variability]

Using human chromosome 18 (Ch18) genes as an example, a PCR analysis of the interindividual variability of gene expression in liver tissue was performed. Although the quantitative profiles of the Ch18 transcriptome, expressed in the number of cDNA copies per single cell, showed a high degree of correlation between donors (Pearson correlation coefficients ranged from 0.963 to 0.966), the expression of the significant number of genes (from 13% to 19%, depending on the method of experimental data normalization) varied by more than 4-fold when comparing donors pairwise. At the same time, the proportion of differentially expressed genes increased with a decrease in the level of their expression. It is shown that the higher quantitative variability of low-abundance transcripts is mainly not technical, but biological. Bioinformatic analysis of the interindividual variability of the differential expression of chromosome 18 genes in human liver tissue did not reveal any statistically significant groups of genes related to certain biological processes that indicated a rather transient nature of the interindividual variability of their expression, probably reflecting the response of cells of an individual to specific external stimuli.

Accurate detection and quantification of SARS-CoV-2 genomic and subgenomic mRNAs by ddPCR and meta-transcriptomics analysis

SARS-CoV-2 replication requires the synthesis of a set of structural proteins expressed through discontinuous transcription of ten subgenomic mRNAs (sgmRNAs). Here, we have fine-tuned droplet digital PCR (ddPCR) assays to accurately detect and quantify SARS-CoV-2 genomic ORF1ab and sgmRNAs for the nucleocapsid (N) and spike (S) proteins. We analyzed 166 RNA samples from anonymized SARS-CoV-2 positive subjects and we observed a recurrent and characteristic pattern of sgmRNAs expression in relation to the total viral RNA content. Additionally, expression profiles of sgmRNAs, as determined by meta-transcriptomics sequencing of a subset of 110 RNA samples, were highly correlated with those obtained by ddPCR. By providing a comprehensive and dynamic snapshot of the levels of SARS-CoV-2 sgmRNAs in infected individuals, our results may contribute a better understanding of the dynamics of transcription and expression of the genome of SARS-CoV-2 and facilitate the development of more accurate molecular diagnostic tools for the stratification of COVID-19 patients.

Oranger et al use digital droplet PCR to develop an assay that provides a dynamic snapshot of the levels of SARS-CoV-2 sub-genomic messanger RNA in infected individuals. This has the potential to improve diagnostic accuracy for COVID-19

Messenger RNA enrichment using synthetic oligo(T) click nucleic acids

Enrichment of mRNA is a key step in a number of molecular biology techniques, particularly in the rapidly growing field of transcriptomics. Currently, mRNA is isolated using oligo(thymine) DNA (oligo(dT)) immobilized on solid supports, which binds to the poly(A) tail of mRNA to pull the mRNA out of solution through the use of magnets or centrifugal filters. Here, a simple method to isolate mRNA by complexing it with synthetic click nucleic acids (CNAs) is described. Oligo(T) CNA bound efficiently to mRNA, and because of the insolubility of CNA in water, >90% of mRNA was readily removed from solution using this method. Simple washing, buffer exchange, and heating steps enabled mRNA's enrichment from total RNA, with a yield of 3.1 ± 1.5% of the input total RNA by mass, comparable to the yield from commercially available mRNA enrichment beads. Further, the integrity and activity of mRNA after CNA-facilitated pulldown and release was evaluated through two assays. In vitro translation of EGFP mRNA confirmed the translatability of mRNA into functional protein and RT-qPCR was used to amplify enriched mRNA from total RNA extracts and compare gene expression to results obtained using commercially available products.

From whole-mount to single-cell spatial assessment of gene expression in 3D

Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics.

Low RIN Value for RNA-Seq Library Construction from Long-Term Stored Seeds: A Case Study of Barley Seeds

Seed aging is a complex biological process and its fundamentals and mechanisms have not yet been fully recognized. This is a key issue faced by research teams involved in the collection and storage of plant genetic resources in gene banks every day. Transcriptomic changes associated with seed aging in the dry state have barely been studied. The aim of the study was to develop an efficient protocol for construction of RNA-Seq libraries from long-term stored seeds with very low viability and low RNA integrity number (RIN). Here, barley seeds that have almost completely lost their viability as a result of long-term storage were used. As a control, fully viable seeds obtained in the course of field regeneration were used. The effectiveness of protocols dedicated to RNA samples with high and low RIN values was compared. The experiment concluded that library construction from low viable or long-term stored seeds with degraded RNA (RIN < 3) should be carried out with extraordinary attention due to the possibility of uneven degradation of different RNA fractions.

S. P, Tennyson J. Prediction and experimental confirmation of banana bract mosaic virus encoding miRNAs and their targets

Background

Potyviridae is the largest plant infecting family under the monophyletic group Riboviria, infects many of the food, fodder and ornamental crops. Due to the higher mutation and recombination rate, potyvirids are evolving rapidly, adapting to the environmental chaos and expanding their hosts. Virus control measures are need to be updated as the economic importance of potyvirids is massive. microRNAs (miRNAs) are well known for their functional importance in eukaryotes and many viruses. Regardless of its biogenesis, whether canonical or noncanonical, microRNA centric antivirus approaches attract the researchers to the hopeful future of next-generation broad-spectrum antiviral measures.

Methods

In this study, we predicted and screened banana bract mosaic virus (BBrMV) encoding miRNAs by computation approaches and their targets on banana transcriptome using plant small RNA target analysis server (psRNAtarget). The target gene functions were annotated by Blast2GO. The predicted BBrMV miRNAs were experimentally screened by stem-loop RT-PCR.

Results

The results showed that, among the predicted BBrMV miRNAs, miRNA2 is conserved throughout BBrMV isolates and has multiple virus-specific target transcripts. In addition, primary experimental validation for the predicted miRNAs revealed that miRNA2 exists in the BBrMV infected banana leaf samples.

Conclusions

The existence of BBrMV miRNA2 is confirmed by stem-loop RT-PCR followed by cloning and sequencing. The presence of miRNA of Potyviridae is rarely addressed and would definitely spread the hope to understand the virus infectious cycle. Our report would also help to better understand and manipulate potyviral infections.