RNA Transcripts Research Articles

Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis.

We successfully employed a single cell RNA sequencing (scRNA-seq) approach to describe the cells and the communication networks characterizing granulomatous lymph nodes of TB patients. When mapping cells from individual patient samples, clustered based on their transcriptome similarities, we uniformly identify several cell types that known to characterize human and non-human primate granulomas. Whether high or low Mtb burden, we find the T cell cluster to be one of the most abundant. Many cells expressing T cell markers are clearly quantifiable within this CD3 expressing cluster. Other cell clusters that are uniformly detected, but that vary dramatically in abundance amongst the individual patient samples, are the B cell, plasma cell and macrophage/dendrocyte and NK cell clusters. When we combine all our scRNA-seq data from our current 23 patients (in order to add power to cell cluster identification in patient samples with fewer cells), we distinguish T, macrophage, dendrocyte and plasma cell subclusters, each with distinct signaling activities. The sizes of these subclusters also varies dramatically amongst the individual patients. In comparing FNA composition we noted trends in which T cell populations and macrophage/dendrocyte populations were negatively correlated with NK cell populations. In addition, we also discovered that the scRNA-seq pipeline, designed for quantification of human cell mRNA, also detects Mtb RNA transcripts and associates them with their host cell's transcriptome, thus identifying individual infected cells. We hypothesize that the number of detected bacterial transcript reads provides a measure of Mtb burden, as does the number of Mtb-infected cells. The number of infected cells also varies dramatically in abundance amongst the patient samples. CellChat analysis identified predominating signaling pathways amongst the cells comprising the various granulomas, including many interactions between stromal or endothelial cells and the other component cells, such as Collagen, FN1 and Laminin,. In addition, other more selective communications pathways, including MIF, MHC-1, MHC-2, APP, CD 22, CD45, and others, are identified as originating or being received by individual immune cell components.

Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change.

Extracellular signals induce changes to molecular programs that modulate multiple cellular phenotypes, including proliferation, motility, and differentiation status. The connection between dynamically adapting phenotypic states and the molecular programs that define them is not well understood. Here we develop data-driven models of single-cell phenotypic responses to extracellular stimuli by linking gene transcription levels to "morphodynamics" - changes in cell morphology and motility observable in time-lapse image data. We adopt a dynamics-first view of cell state by grouping single-cell trajectories into states with shared morphodynamic responses. The single-cell trajectories enable development of a first-of-its-kind computational approach to map live-cell dynamics to snapshot gene transcript levels, which we term MMIST, Molecular and Morphodynamics-Integrated Single-cell Trajectories. The key conceptual advance of MMIST is that cell behavior can be quantified based on dynamically defined states and that extracellular signals alter the overall distribution of cell states by altering rates of switching between states. We find a cell state landscape that is bound by epithelial and mesenchymal endpoints, with distinct sequences of epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET) intermediates. The analysis yields predictions for gene expression changes consistent with curated EMT gene sets and provides a prediction of thousands of RNA transcripts through extracellular signal-induced EMT and MET with near-continuous time resolution. The MMIST framework leverages true single-cell dynamical behavior to generate molecular-level omics inferences and is broadly applicable to other biological domains, time-lapse imaging approaches and molecular snapshot data.

Anticoronavirus activity of rhizome of Dryopteris crassirhizoma via multistage targeting of virus entry and viral proteases, Mpro and PLpro

Ethnopharmacological relevanceThe rhizome of Dryopteris crassirhizoma Nakai (Dryopteridaceae, RDC), a traditional East Asian herbal medicine, possesses a broad spectrum of medicinal properties, including anti-inflammatory, anticancer, antibacterial, and antiviral activities. Aim of the studyThis study investigates the 30% ethanolic extract of RDC's antiviral potential against human coronavirus OC43 (HCoV-OC43), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its variants infections. Materials and methodsA 30% ethanolic extract of RDC or its components, filixic acid ABA (PubChem CID: 15081408) and dryocrassin ABBA (PubChem CID: 3082025) were treated with Human Coronavirus infection (HCoV-OC43, SARS-CoV-2 and its variants). The base peak chromatogram of RDC was evaluated using UPLC-Q/TOF Mass to identify the RDC, and the quantitative analysis of RDC compounds was performed using LC-MS/MS. A cytopathic effect (CPE) reduction assay, Western blot, immunofluorescence staining of viral protein expression, and qRT-PCR were performed to quantify the viral RNA copy numbers and determine the antiviral activity. The time-of-addition assay, the virus attachment, penetration, and virucidal assays, and SARS-CoV-2 Mpro and PLpro activity assay were used to elucidate the mode of action. ResultsRDC exhibited dose-dependent inhibition of HCoV-OC43–induced cytopathic effects, reducing viral RNA copy numbers and viral protein levels. Time-of-addition assays indicated that RDC targets the early stages of the HCoV-OC43 life cycle, inhibiting virion attachment and penetration with virucidal activity. Notably, filixic acid ABA and dryocrassin ABBA, constituents of RDC, reduced HCoV-OC43 viral RNA loads. Furthermore, RDC effectively blocked viral entry in pseudotyped lentivirus assays, involving spike proteins of SARS-CoV-2 Delta plus and South Africa variants, as well as control lentiviral particles expressing vesicular stomatitis virus glycoprotein G. Additionally, RDC demonstrated inhibition of SARS-CoV-2 infection and its variants by targeting viral proteases, namely main protease (Mpro) and papain-like protease (PLpro). ConclusionsThese findings underscore RDC's multistage approach to targeting viral infections by impeding virus entry and inhibiting viral protease activity. Therefore, RDC holds promise as a potent, broad-spectrum anticoronaviral therapeutic agent.

Varying the ratio of Lys: Met through enhancing methionine supplementation improved milk secretion ability through regulating the mRNA expression in bovine mammary epithelial cells under heat stress.

The ratio of lysine (Lys) to methionine (Met) with 3.0: 1 is confirmed as the "ideal" profile for milk protein synthesis, but whether this ratio is suitable for milk protein synthesis under HS needs to be further studied. To evaluate the molecular mechanism by which HS and Lys to Met ratios affect mammary cell functional capacity, an immortalized bovine mammary epithelial cell line (MAC-T) is incubated with 5 doses of Met while maintaining a constant concentration of Lys. The MAC-T cells was treated for 6 h as follow: Lys: Met 3.0: 1 (control 37°C and IPAA 42°C) or treatments under HS (42°C) with different ratios of Lys: Met at 2.0: 1 (LM20), 2.5: 1 (LM25), 3.5: 1 (LM35) and 4.0: 1 (LM40). RNA sequencing was used to assess transcriptome-wide alterations in mRNA abundance. The significant difference between control and other groups was observed base on PCA analysis. A total of 2048 differentially expressed genes (DEGs) were identified in the IPAA group relative to the control group. Similarly, 226, 306, 148, 157 DEGs were detected in the LM20, LM25, LM35 and LM40 groups, respectively, relative to the IPAA group. The relative mRNA abundance of HSPA1A was upregulated and anti-apoptotic genes (BCL2L1 and BCL2) was down-regulated in the IPAA group, compared to the control group (p < 0.05). Compared with the IPAA group, the relative mRNA abundance of anti-apoptotic genes and casein genes (CSN1S2 and CSN2) was up-regulated in the LM25 group (p < 0.05). The DEGs between LM25 and IPAA groups were associated with the negative regulation of transcription RNA polymerase II promoter in response to stress (GO: 0051085, DEGs of BAG3, DNAJB1, HSPA1A) as well as the mTOR signaling pathway (ko04150, DEGs of ATP6V1C2, WNT11, WNT3A, and WNT9A). Several DEGs involved in amino acids metabolism (AFMID, HYKK, NOS3, RIMKLB) and glycolysis/gluconeogenesis (AFMID and MGAT5B) were up-regulated while DEGs involved in lipolysis and beta-oxidation catabolic processes (ALOX12 and ALOX12B) were down-regulated. These results suggested that increasing Met supply (Lys: Met at 2.5: 1) may help mammary gland cells resist HS-induced cell damage, while possibly maintaining lactation capacity through regulation of gene expression.

Target-responsive triplex aptamer nanoswitch enables label-free and ultrasensitive detection of antibody in human serum via lighting-up RNA aptamer transcriptions

Accurate and sensitive monitoring of the concentration change of anti-digoxigenin (Anti-Dig) antibody is of great importance for diagnosing infectious and immunological diseases. Combining a novel triplex aptamer nanoswitch and the high signal-to-noise ratio of lighting-up RNA aptamer signal amplification, a label-free and ultrasensitive fluorescent sensing approach for detecting Anti-Dig antibodies is described. The target Anti-Dig antibodies recognize and bind with the nanoswitch to open its triplex helix stem structure to release Taq DNA polymerase and short ssDNA primer simultaneously, which activates the Taq DNA polymerase to initiate downstream strand extension of ssDNA primer to yield specific dsDNA containing RNA promoter sequence. T7 RNA polymerase recognizes and binds to these promoter sequences to initiate RNA transcription reaction to produce many RNA aptamer sequences. These aptamers can recognize and bind with Malachite Green (MG) dye specifically and produce highly amplified fluorescent signal for monitoring Anti-Dig antibodies from 50 pM to 50 nM with a detection limit down to 33 pM. The method also exhibits high selectivity for Anti-Dig antibodies and can be used to discriminate trace Anti-Dig antibodies in diluted serum samples. Our method is superior to many immunization-based Anti-Dig antibody detection methods and thus holds great potential for monitoring disease progression and efficacy.

Novel triplex nucleic acid lateral flow immunoassay for rapid detection of Nipah virus, Middle East respiratory syndrome coronavirus and Reston ebolavirus

We report the development of a triplex nucleic acid lateral flow immunoassay (NALFIA) for the detection of the genomes of Nipah virus (NiV), Middle East respiratory syndrome coronavirus (MERS-CoV) and Reston ebolavirus (REBOV), which are intended for screening bats as well as other hosts and reservoirs of these three viruses. Our triplex NALFIA is a two-step assay format: the target nucleic acid in the sample is first amplified using tagged primers, and the tagged dsDNA amplicons are captured by antibodies immobilized on the NALFIA device, resulting in signal development from the binding of a streptavidin-colloidal gold conjugate to a biotin tag on the captured amplicons. Triplex amplification of the N gene of NiV, the UpE gene of MERS-CoV, and the Vp40 gene of REBOV was optimized, and three compatible combinations of hapten labels and antibodies were identified for end point detection. The lowest RNA copy numbers detected by the triplex NALFIA were 8.21e4 for the NiV N target, 7.09e1 for the MERS-CoV UpE target, and 1.83e4 for the REBOV Vp40 target. Using simulated samples, the sensitivity and specificity for MERS-CoV and REBOV targets were estimated to be 100%, while the sensitivity and specificity for the NiV target were 91% and 93.3%, respectively. The compliance rate between triplex NALFIA and real-time RT‒PCR was 92% for the NiV N target and 100% for the MERS-CoV UpE and REBOV Vp40 targets.

A novel virus-like particles vaccine induces broad immune protective against deltacoronavirus in piglets

Coronaviruses (CoVs) comprise a group of important human and animal pathogens that threaten public health because of their interspecies transmission potential to humans. However, virus-like particles (VLPs) constitute versatile tools in CoVs vaccine development due to their favorable immunological characteristics. Here, we engineered the VLPs composed of the spike (S), membrane (M), and envelope (E) structural proteins of the Porcine deltacoronavirus (PDCoV) and examined their immune responses in mice. Neutralization assays and flow Cytometry demonstrated that PDCoV VLPs induced highly robust neutralizing antibodies (NAbs) and elicited cellular immunity. To assess the protective efficacy of VLPs in newborn piglets, pregnant sows received vaccinations with either a PDCoV-inactivated vaccine or VLPs at 40 and 20 days before delivery. Five days post-farrowing, piglets were orally challenged with the PDCoV strain. Severe diarrhea, high viral RNA copies, and substantial intestinal villus atrophy were detected in piglets born to unimmunized sows. However, piglets from sows immunized with VLPs exhibited high NAbs titers and markedly reduced microscopic damage to the intestinal tissues, with no piglet showing diarrhea. Hence, the results indicate that the VLPs are a potential clinical candidate for PDCoV vaccination, while the strategy may serve as a platform for developing other coronavirus vaccines.

Unravelling the role of Set2 protein domains in H3K36 methylation in Saccharomyces cerevisiae

Histone methylation plays a crucial role in gene expression and chromatin structure regulation. In Saccharomyces cerevisiae, the Set2 protein is responsible for the methylation of histone H3 at lysine 36 (H3K36), which is associated with transcriptional regulation, RNA processing, and DNA repair. This study investigates the specific functions of individual domains within the yeast Set2 protein by utilizing PCR-based domain deletions and subsequent western blot analysis to assess their impact on H3K36 methylation status. The results demonstrate that the SET domain alone is sufficient for H3K36 dimethylation, while optimal trimethylation necessitates the presence of additional domains, including the central autoinhibitory domain. Furthermore, the SRI domain is found to be essential for both di- and trimethylation when considering the full-length Set2 protein. These findings underscore the critical role of Set2 domains in modulating Set2 enzymatic activity.

Rapid and portable quantification of HIV RNA via a smartphone-enabled digital CRISPR device and deep learning

For the 29.8 million people in the world living with HIV/AIDS and receiving antiretroviral therapy, it is crucial to monitor their HIV viral loads. To this end, rapid and portable diagnostic tools that can quantify HIV RNA are critically needed. We report herein a rapid and quantitative digital CRISPR-assisted HIV RNA detection assay that has been implemented within a portable smartphone-based device as a potential solution. Specifically, we first developed a fluorescence-based reverse transcription recombinase polymerase amplification (RT-RPA)-CRISPR assay that can efficiently detect HIV RNA at 42 °C. We then implemented this assay within a commercial stamp-sized digital chip, where RNA molecules were quantified as strongly fluorescent digital reaction wells. The isothermal reaction condition and the strong fluorescence in the digital chip simplified the design of thermal and optical modules, allowing us to engineer a palm-size device measuring 70 × 115 × 80 mm and weighing less than 0.6 kg. We also capitalized the smartphone by developing a custom app to control the device, perform the digital assay, and capture fluorescence images throughout the assay using the smartphone's camera. Moreover, we trained and verified a deep learning-based algorithm for analyzing fluorescence images and identifying positive digital reaction wells with high accuracy. Using our smartphone-enabled digital CRISPR device, we successfully detected as low as 75 copies of HIV RNA in just 15 min, showing its potential toward monitoring of HIV viral loads and aiding the global effort to combat the HIV/AIDS epidemic.

RNA N6-methyladenosine methylation in influenza A virus infection.

Influenza A virus (IAV) is a negative-sense single-stranded RNA virus that causes acute lung injury and acute respiratory distress syndrome, posing a serious threat to both animal and human health. N6-methyladenosine (m6A), a prevalent and abundant post-transcriptional methylation of RNA in eukaryotes, plays a crucial regulatory role in IAV infection by altering viral RNA and cellular transcripts to affect viral infection and the host immune response. This review focuses on the molecular mechanisms underlying m6A modification and its regulatory function in the context of IAV infection and the host immune response. This will provide a better understanding of virus-host interactions and offer insights into potential anti-IAV strategies.

Assessing the prevalence of FRNA bacteriophages and their correlation with SARS-CoV-2 RNA in the wastewater of Mumbai city

ABSTRACT Bacteriophages have been explored as indicators of the presence of human viruses in water. F+ coliphages are of particular interest due to their abundance in wastewater and some groups surviving the treatment process. This study assessed the prevalence of F+ coliphages and FRNA bacteriophage (FRNAPH) groups in the wastewaters of Mumbai city and explored its correlation with the presence of SARS-CoV-2. Wastewater samples (raw = 63, treated = 99) collected from three wastewater treatment plants (WWTPs) were assessed for F+ coliphages, FRNAPH groups and SARS-CoV-2. Of the 63 raw wastewater samples, 92% were positive for F+ coliphages and FRNAPH, while SARS-CoV-2 was detected in 76% of samples; FRNAPH GI RNA was the most prevalent (96.82%) followed by FRNAPH GII (77.77%), FRNAPH GIII (36.50%), and FRNAPH GIV (4.76%). A significant correlation was observed between the occurrence of SARS-CoV-2 and F+ coliphages, FRNAPH GII and FRNAPH GIII RNA copies and also between F+ coliphages and FRNAPH GII and GIII. These observations suggest that F+ coliphages, FRNAPH GII and GIII can be explored further as indicators of SARS-CoV-2 in wastewaters. Also, F+ coliphage detection may be a cost-effective and practical approach for monitoring virus elimination during wastewater treatment.

A deep learning method to predict bacterial ADP-ribosyltransferase toxins.

ADP-ribosylation is a critical modification involved in regulating diverse cellular processes, including chromatin structure regulation, RNA transcription, and cell death. Bacterial ADP-ribosyltransferase toxins (bARTTs) serve as potent virulence factors that orchestrate the manipulation of host cell functions to facilitate bacterial pathogenesis. Despite their pivotal role, the bioinformatic identification of novel bARTTs poses a formidable challenge due to limited verified data and the inherent sequence diversity among bARTT members. We proposed a deep learning-based model, ARTNet, specifically engineered to predict bARTTs from bacterial genomes. Initially, we introduced an effective data augmentation method to address the issue of data scarcity in training ARTNet. Subsequently, we employed a data optimization strategy by utilizing ART-related domain subsequences instead of the primary full sequences, thereby significantly enhancing the performance of ARTNet. ARTNet achieved a Matthew's correlation coefficient (MCC) of 0.9351 and an F1-score (macro) of 0.9666 on repeated independent test datasets, outperforming three other deep learning models and six traditional machine learning models in terms of time efficiency and accuracy. Furthermore, we empirically demonstrated the ability of ARTNet to predict novel bARTTs across domain superfamilies without sequence similarity. We anticipate that ARTNet will greatly facilitate the screening and identification of novel bARTTs from bacterial genomes. ARTNet is publicly accessible at http://www.mgc.ac.cn/ARTNet/. The source code of ARTNet is freely available at https://github.com/zhengdd0422/ARTNet/.

Retroviral PBS-segment sequence and structure: Orchestrating early and late replication events

An essential regulatory hub for retroviral replication events, the 5’ untranslated region (UTR) encodes an ensemble of cis-acting replication elements that overlap in a logical manner to carry out divergent RNA activities in cells and in virions. The primer binding site (PBS) and primer activation sequence initiate the reverse transcription process in virions, yet overlap with structural elements that regulate expression of the complex viral proteome. PBS-segment also encompasses the attachment site for Integrase to cut and paste the 3’ long terminal repeat into the host chromosome to form the provirus and purine residues necessary to execute the precise stoichiometry of genome-length transcripts and spliced viral RNAs. Recent genetic mapping, cofactor affinity experiments, NMR and SAXS have elucidated that the HIV-1 PBS-segment folds into a three-way junction structure. The three-way junction structure is recognized by the host’s nuclear RNA helicase A/DHX9 (RHA). RHA tethers host trimethyl guanosine synthase 1 to the Rev/Rev responsive element (RRE)-containing RNAs for m7-guanosine Cap hyper methylation that bolsters virion infectivity significantly. The HIV-1 trimethylated (TMG) Cap licenses specialized translation of virion proteins under conditions that repress translation of the regulatory proteins. Clearly host-adaption and RNA shapeshifting comprise the fundamental basis for PBS-segment orchestrating both reverse transcription of virion RNA and the nuclear modification of m7G-Cap for biphasic translation of the complex viral proteome. These recent observations, which have exposed even greater complexity of retroviral RNA biology than previously established, are the impetus for this article. Basic research to fully comprehend the marriage of PBS-segment structures and host RNA binding proteins that carry out retroviral early and late replication events is likely to expose an immutable virus-specific therapeutic target to attenuate retrovirus proliferation.Graphical abstract

Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community on which methods are the most effective or how to process the data. To circumvent this, we performed a large-scale study using various machine-learning techniques. First, we took a closer look at existing datasets and filtered out some patients to assert data collection quality. The final data collection included platelet RNA samples acquired from 1397 cancer patients (17 types of cancer) and 354 asymptomatic, presumed healthy, donors. Then, we assessed an array of different machine-learning models and techniques (e.g., feature selection of RNA transcripts) in pan-cancer detection and multiclass classification. Our results show that simple logistic regression performs the best, reaching a 68% cancer detection rate at a 99% specificity level, and multiclass classification accuracy of 79.38% when distinguishing between five cancer types. In summary, by revisiting classical machine-learning models, we have exceeded the previously used method by 5% and 9.65% in cancer detection and multiclass classification, respectively. To ease further research, we open-source our code and data processing pipelines (https://gitlab.com/jopekmaksym/improving-platelet-rna-based-diagnostics), which we hope will serve the community as a strong baseline.

Single-molecule reconstruction of eukaryotic factor-dependent transcription termination

Factor-dependent termination uses molecular motors to remodel transcription machineries, but the associated mechanisms, especially in eukaryotes, are poorly understood. Here we use single-molecule fluorescence assays to characterize in real time the composition and the catalytic states of Saccharomyces cerevisiae transcription termination complexes remodeled by Sen1 helicase. We confirm that Sen1 takes the RNA transcript as its substrate and translocates along it by hydrolyzing multiple ATPs to form an intermediate with a stalled RNA polymerase II (Pol II) transcription elongation complex (TEC). We show that this intermediate dissociates upon hydrolysis of a single ATP leading to dissociation of Sen1 and RNA, after which Sen1 remains bound to the RNA. We find that Pol II ends up in a variety of states: dissociating from the DNA substrate, which is facilitated by transcription bubble rewinding, being retained to the DNA substrate, or diffusing along the DNA substrate. Our results provide a complete quantitative framework for understanding the mechanism of Sen1-dependent transcription termination in eukaryotes.

Topological Spectra and Entropy of Chromatin Loop Networks

The 3D folding of a mammalian gene can be studied by a polymer model, where the chromatin fiber is represented by a semiflexible polymer which interacts with multivalent proteins, representing complexes of DNA-binding transcription factors and RNA polymerases. This physical model leads to the natural emergence of clusters of proteins and binding sites, accompanied by the folding of chromatin into a set of topologies, each associated with a different network of loops. Here, we combine numerics and analytics to first classify these networks and then find their relative importance or statistical weight, when the properties of the underlying polymer are those relevant to chromatin. Unlike polymer networks previously studied, our chromatin networks have finite average distances between successive binding sites, and this leads to giant differences between the weights of topologies with the same number of edges and nodes but different wiring. These weights strongly favor rosettelike structures with a local cloud of loops with respect to more complicated nonlocal topologies. Our results suggest that genes should overwhelmingly fold into a small fraction of all possible 3D topologies, which can be robustly characterized by the framework we propose here. Published by the American Physical Society 2024

Novel Anti-Enterovirus A71 Compounds Discovered by Repositioning Antivirals from the Open-Source MMV Pandemic Response Box.

The open-source drug library, namely, MMV Pandemic Response Box, contains 153 antiviral agents, a chemically and pharmacologically diverse mixture of early-stage, emerging anti-infective scaffolds, and mature compounds currently undergoing clinical development. Hence, the Pandemic Response Box might contain compounds that bind and interfere with target molecules or cellular pathways that are conserved or shared among the closely related viruses with enterovirus A71 (EV-A71). This study aimed to screen antiviral agents included in the Pandemic Response Box for repurposing to anti-EV-A71 activity and investigate the inhibitory effects of the compounds on viral replication. The compounds' cytotoxicity and ability to rescue infected cells were determined by % cell survival using an SRB assay. The hit compounds were verified for anti-EV-A71 activity by virus reduction assays for viral RNA copy numbers, viral protein synthesis, and mature particle production using qRT-PCR, Western blot analysis, and CCID50 assay, respectively. It was found that some of the hit compounds could reduce EV-A71 genome replication and protein synthesis. D-D7 (2-pyridone-containing human rhinovirus 3C protease inhibitor) exhibited the highest anti-EV-A71 activity. Even though D-D7 has been originally indicated as a polyprotein processing inhibitor of human rhinovirus 3C protease, it could be repurposed as an anti-EV-A71 agent.

Modeling the structure and DAP5-binding site of the FGF-9 5'-UTR RNA utilized in cap-independent translation.

Cap-independent or eukaryotic initiation factor (eIF) 4E-independent, translation initiation in eukaryotes requires scaffolding protein eIF4G or its homolog, death-associated protein 5 (DAP5). eIF4G associates with the 40S ribosomal subunit, recruiting the ribosome to the RNA transcript. A subset of RNA transcripts, such as fibroblast growth factor 9 (FGF-9), contain 5' untranslated regions (5' UTRs) that directly bind DAP5 or eIF4GI. For viral mRNA, eIF recruitment usually utilizes RNA structure, such as a pseudoknot or stem-loops, and the RNA-helicase eIF4A is required for DAP5- or 4G-mediated translation, suggesting these 5' UTRs are structured. However, for cellular IRES-like translation, no consensus RNA structures or sequences have yet been identified for eIF binding. However, the DAP5-binding site within the FGF-9 5' UTR is unknown. Moreover, DAP5 binds to other, dissimilar 5' UTRs, some of which require an unpaired, accessible 5' end to stimulate cap-independent translation. Using SHAPE-seq, we modeled the 186 nt FGF-9 5'-UTR RNA's complex secondary structure in vitro. Further, DAP5 footprinting, toeprinting, and UV cross-linking experiments identify DAP5-RNA interactions. Modeling of FGF-9 5'-UTR tertiary structure aligns DAP5-interacting nucleotides on one face of the predicted structure. We propose that RNA structure involving tertiary folding, rather than a conserved sequence or secondary structure, acts as a DAP5-binding site. DAP5 appears to contact nucleotides near the start codon. Our findings offer a new perspective in the hunt for cap-independent translational enhancers. Structural, rather than sequence-specific, eIF-binding sites may act as attractive chemotherapeutic targets or as dosage tools for mRNA-based therapies.

Isoform and pathway-specific regulation of post-transcriptional RNA processing in human cells.

Steady-state levels of RNA transcripts are controlled by their rates of synthesis and degradation. Here we used nascent RNA Bru-seq and BruChase-seq to profile RNA dynamics across 16 human cell lines as part of ENCODE4 Deeply Profiled Cell Lines collection. We show that RNA turnover dynamics differ widely between transcripts of different genes and between different classes of RNA. Gene set enrichment analysis (GSEA) revealed that transcripts encoding proteins belonging to the same pathway often show similar turnover dynamics. Furthermore, transcript isoforms show distinct dynamics suggesting that RNA turnover is important in regulating mRNA isoform choice. Finally, splicing across newly made transcripts appears to be cooperative with either all or none type splicing. These data sets generated as part of ENCODE4 illustrate the intricate and coordinated regulation of RNA dynamics in controlling gene expression to allow for the precise coordination of cellular functions.

Assessment of long-term stored specimens in the Siriraj Hospital colorectal cancer biobank for RNA sequencing and profiling

Abstract Objectives Biobanks play an important role in advancing cancer research, yet concerns persist regarding the molecular integrity of long-term stored samples. This study assessed fresh frozen (FF) tissues and formalin-fixed paraffin-embedded (FFPE) tissues from the Siriraj Hospital colorectal cancer (CRC) biobank collected during two distinct periods (2011–2012 and 2020–2021). Methods In 2022, FF and FFPE primary cancer tissues from 75 CRC patients were evaluated. RNA sequencing (RNA-Seq) analyzed comprehensive gene expression profiles in FF tissues preserved at −80 °C, while nCounter profiling elucidated cancer-specific RNA transcripts in FFPE tissues stored at ambient temperature. Comparative analyses were conducted between specimens from 2011 to 2012 and 2020–2021. Results The FF tissues stored for approximately 10.5 years were well-suited for RNA-Seq compared to the intact tissues preserved for 1.5 years. Despite consistencies in RNA quantity, RNA integrity, amount of sequencing reads, and CRC gene signature, gene enrichment analysis revealed the decreased ribosome biogenesis, spliceosome and antifolate resistance pathways in the 2011–2012 group. Moreover, the FFPE tissues also showed no alteration in RNA quantity between the two periods, and the nCounter profiling demonstrated comparable CRC-specific gene counts in spite of the significant reduction of raw counts in the 2011–2012 group. Conclusions We report that FF tissues from CRC patients, stored for 10 years, are viable for whole transcriptome RNA-Seq, despite altered pathways such as ribosome biogenesis, spliceosome, and antifolate resistance. Moreover, 10-year-stored FFPE CRC tissues remain suitable for specific RNA profiling using the nCounter pan-cancer panel, despite a significant reduction in raw counts. These findings underscore the enduring contribution of biobanks to molecular research, highlighting their value a decade post-collection.