Classification of Highly Divergent Viruses from DNA/RNA Sequence Using Transformer-Based Models.

Viruses infect millions of people worldwide each year, and some can lead to cancer or increase the risk of cancer. As viruses have highly mutable genomes, new viruses may emerge in the future, such as COVID-19 and influenza. Traditional virology relies on predefined rules to identify viruses, but new viruses may be completely or partially divergent from the reference genome, rendering statistical methods and similarity calculations insufficient for all genome sequences. Identifying DNA/RNA-based viral sequences is a crucial step in differentiating different types of lethal pathogens, including their variants and strains. While various tools in bioinformatics can align them, expert biologists are required to interpret the results. Computational virology is a scientific field that studies viruses, their origins, and drug discovery, where machine learning plays a crucial role in extracting domain- and task-specific features to tackle this challenge. This paper proposes a genome analysis system that uses advanced deep learning to identify dozens of viruses. The system uses nucleotide sequences from the NCBI GenBank database and a BERT tokenizer to extract features from the sequences by breaking them down into tokens. We also generated synthetic data for viruses with small sample sizes. The proposed system has two components: a scratch BERT architecture specifically designed for DNA analysis, which is used to learn the next codons unsupervised, and a classifier that identifies important features and understands the relationship between genotype and phenotype. Our system achieved an accuracy of 97.69% in identifying viral sequences.

Alternative structures of RNA control gene expression and offer therapeutic strategies

RNA viruses are diverse and abundant pathogens responsible for numerous human ailments, from common colds to AIDS, SARS, Ebola, and other dangerous diseases. RNA viruses possess relatively compact genomes and have therefore evolved multiple mechanisms to maximize their coding capacities, often using overlapping reading frames. In this way, one RNA sequence can encode multiple proteins via mechanisms including alternative splicing and ribosomal frameshifting. Many such processes in gene expression involve the RNA folding into three-dimensional structures that can recruit ribosomes without initiation factors, hijack host proteins, cause ribosomes to frameshift, and expose or occlude regulatory protein binding motifs to ultimately control each key process in the viral life cycle. I will discuss the RNA structure of HIV-1 and SARS-CoV-2 and the importance of alternative conformations assumed by the same RNA sequence in controlling gene expression of viruses and bacteria.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

New Short RNA Motifs Potentially Relevant in the SARS-CoV-2 Genome

Background: The coronavirus disease has led to an exhaustive exploration of the SARS-CoV-2 genome. Despite the amount of information accumulated, the prediction of short RNA motifs encoding peptides mediating protein-protein or protein-drug interactions has received limited attention. Objective(s): The study aims to predict short RNA motifs that are interspersed in the SARS-CoV-2 genome. Method(s): A method in which 14 trinucleotide families, each characterized by being composed of triplets with identical nucleotides in all possible configurations, was used to find short peptides with biological relevance. The novelty of the approach lies in using these families to search how they are distributed across genomes of different CoV genera and then to compare the distributions of these families with each other. Result(s): We identified distributions of trinucleotide families in different CoV genera and also how they are related, using a selection criterion that identified short RNA motifs. The motifs were reported to be conserved in SARS-CoVs;in the remaining CoV genomes analysed, motifs contained, exclusively, different configurations of the trinucleotides A, T, G and A, C, G. Eighty-eight short RNA motifs, ranging in length from 12 to 49 nucleotides, were found: 50 motifs in the 1a polyprotein-encoding orf, 27 in the 1b polyprotein-encoding orf, 5 in the spike-encoding orf, and 6 in the nucleocapsid-encoding orf. Although some motifs (~27%) were found to be intercalated or attached to functional peptides, most of them have not yet been associated with any known functions. Conclusion(s): Some of the trinucleotide family distributions in different CoV genera are not random;they are present in short peptides that, in many cases, are intercalated or attached to functional sites of the proteome.Copyright © 2022 Bentham Science Publishers.

Recent advances of nanotechnology in COVID 19: A critical review and future perspective

The global anxiety and economic crisis causes the deadly pandemic coronavirus disease of 2019 (COVID 19) affect millions of people right now. Subsequently, this life threatened viral disease is caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, morbidity and mortality of infected patients are due to cytokines storm syndrome associated with lung injury and multiorgan failure caused by COVID 19. Thereafter, several methodological advances have been approved by WHO and US-FDA for the detection, diagnosis and control of this wide spreadable communicable disease but still facing multi-challenges to control. Herein, we majorly emphasize the current trends and future perspectives of nano-medicinal based approaches for the delivery of anti-COVID 19 therapeutic moieties. Interestingly, Nanoparticles (NPs) loaded with drug molecules or vaccines resemble morphological features of SARS-CoV-2 in their size (60–140 nm) and shape (circular or spherical) that particularly mimics the virus facilitating strong interaction between them. Indeed, the delivery of anti-COVID 19 cargos via a nanoparticle such as Lipidic nanoparticles, Polymeric nanoparticles, Metallic nanoparticles, and Multi-functionalized nanoparticles to overcome the drawbacks of conventional approaches, specifying the site-specific targeting with reduced drug loading and toxicities, exhibit their immense potential. Additionally, nano-technological based drug delivery with their peculiar characteristics of having low immunogenicity, tunable drug release, multidrug delivery, higher selectivity and specificity, higher efficacy and tolerability switch on the novel pathway for the prevention and treatment of COVID 19. © 2022 The Author(s)

Ai-Driven Covid-19 Mrna Vaccine Degradation Prediction

Background/Objective: Messenger RNA (mRNA) vaccines have emerged as a promising treatment for the coronavirus disease-2019 (COVID-19) pandemic, but such a solution has its challenges. One such issue is the mRNA vaccine's molecular stability, which requires that it be kept under certain environmental conditions that restrict its global outreach in packages, such as disposable syringes, distributed worldwide using refrigeration. Designing an environmentally stable mRNA vaccine that can withstand shipment worldwide is a challenge, since a single slit or puncture can render the complete dose of the vaccine useless. If not kept under certain environmental conditions and left unmonitored, mRNA vaccines tend to degrade rapidly. To address this problem, agencies currently store mRNA vaccines under strict refrigeration, thus limiting their global reach. The objective was to develop a hybrid deep learning model that can efficiently predict mRNA vaccine degradation rate from RNA sequences, thus aiding researchers and scientists in designing and developing a more stable mRNA vaccine in the future Results: Research presented here discusses the capability of the in-house developed hybrid deep learning model. Conclusion(s): The model was developed with a performance of 0.2430 mean columnwise root-mean-squared error (MCRMSE) score on the test data.

In silico strategies to identify protein-protein interaction modulator in cell-to-cell transmission of SARS CoV2.

RNA sequence data from SARS CoV2 patients helps to construct a gene network related to this disease. A detailed analysis of the human host response to SARS CoV2 with expression profiling by high-throughput sequencing has been accomplished with primary human lung epithelial cell lines. Using this data, the clustered gene annotation and gene network construction are performed with the help of the String database. Among the four clusters identified, only 1 with 44 genes could be annotated. Interestingly, this corresponded to basal cells with p = 1.37e - 05, which is relevant for respiratory tract infection. Functional enrichment analysis of genes present in the gene network has been completed using the String database and the Network Analyst tool. Among three types of cell-cell communication, only the anchoring junction between the basal cell membrane and the basal lamina in the host cell is involved in the virus transmission. In this junction point, a hemidesmosome structure plays a vital role in virus spread from one cell to basal lamina in the respiratory tract. In this protein complex structure, different integrin protein molecules of the host cell are used to promote the spread of virus infection into the extracellular matrix. So, small molecular blockers of different anchoring junction proteins, such as integrin alpha 3, integrin beta 1, can provide efficient protection against this deadly viral disease. ORF8 from SARS CoV2 virus can interact with both integrin proteins of human host. By using molecular docking technique, a ternary complex of these three proteins is modelled. Several oligopeptides are predicted as modulators for this ternary complex. In silico analysis of these modulators is very important to develop novel therapeutics for the treatment of SARS CoV2.

Inflammasome formation by neutrophils during COVID-19

Type I interferons (IFN-I) induce the expression of several interferon-stimulated genes (ISGs), which provide antiviral capacity to host cells, including neutrophils. COVID-19 hyperinflammatory state involves an elevated neutrophilic response and can be aggravated by a heightened IFN-I response, associated with disease progression and severity. Numerous studies have proven significant inflammasome activation during SARS-CoV- 2 infection in patient circulating monocytes. However, despite the increased neutrophil counts seen in severe COVID-19 and the previously demonstrated capacity of these immune cells to form inflammasomes, little is known concerning the formation of these multiprotein complexes by neutrophils during acute COVID-19. Therefore, the aim of this study was to investigate neutrophil inflammasome formation and the possible role played by IFN-I. We found that COVID-19 isolated neutrophils exhibited a significant upregulation of ISGs and inflammasome genes in mature neutrophils, shown by RNA sequence and quantitative PCR, compared to healthy controls (HC). In vitro assays consisted of priming with lipopolysaccharide (LPS) or IFNa, and activating with nigericin, followed by measurements of IL-1β and caspase-1 levels. HC neutrophils responded to both priming signals, whereas COVID-19 neutrophils did not. After nigericin, both HC and COVID-19 neutrophils responded with a similar fold in IL-1β and caspase-1 levels. In conclusion, COVID-19 neutrophils showed upregulated inflammasome genes and increased inflammasome formation. Given the significant upregulation of ISGs and the demonstrated ability of IFN to prime neutrophils, a lack of response in COVID-19 neutrophils to priming signals suggests these cells were already primed, with IFN most likely playing a role.

CRISPR gene editing: a revolution in progress

CRISPR is a gene editing technique that has revolutionised research and has the potential to transform the treatment of many diseases. This article discusses the principles of the technique, its therapeutic applications and potential safety issues.

Comparison of two RT PCR methods with two different genes for detection of severe acute respiratory syndrome coronavirus 2 (SARS-COV2)

Background-aim: World Health Organization (WHO) announced that diagnostic testing for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2) should be performed by real-time reverse transcriptase-polymerase chain reaction (RT-PCR). Most of these methods use different gene props and therefore the sensitivity and specificity of each method may different. In this study, we have compared two RT-PCR methods using two different genes for detection SARS-COV2. Methods: A total of random 40 nasopharyngeal swab samples were collected, transported and received in iced box shipment. All samples were performed on two separate semi-automated PCR systems (Qiagen and Abbott m2000). For Qiagen method, 200uL from each sample were added in 96-well QiAcube plate which loaded in QiAcube HT (SN:019658;Qiagen, Germany) to extract RNA. Following extraction, master mix prepared using SARS-COV2-RT-PCR kit 1.0 (REF: 821005;Altona, Germany) for 44 samples including 40 patient samples, two negative controls using nuclease-free water (with and without internal control), and two positive controls (with and without internal control). Extraction elute of each sample (20uL) added to master mix (10uL) to have a total volume of 30uL which uploaded into Rotor-Gene Q (SN:R0219307;Qiagen, Germany). The primer pair used to amplify S gene and E gene in SARS-COV2. Amplifications were done as follow: reverse transcriptase (20 minutes at 55oC);initial denaturation (2 minutes at 95oC);45 cycles of denaturation (15 seconds at 95oC), annealing for (45 seconds at 55oC), and extension (15 seconds at 72oC). Results reported as valid for internal control less than 35 cycle threshold (CT). The Abbott m2000 System uses SARS-CoV-2 assay was a dual target assay for the RdRp and N genes. All 40 samples were extracted using m2000sp (Abbott, United States) as recommend by manufacture using 100uL. An RNA sequence that was unrelated to the SARS-CoV-2 target sequence was introduced into each specimen at the beginning of sample preparation. This unrelated RNA sequence was simultaneously amplified by RT-PCR and serves as an internal control (IC) to demonstrate that the process has proceeded correctly for each sample. Following extraction, master mix (20uL) added to extraction elute of each sample (30uL) to have a total volume of 50uL which uploaded into m2000rp (Abbott, United States). Amplification were done as follow: reverse transcriptase (25 minutes at 55oC);initial denaturation (5 minutes at 94oC);40 cycles of denaturation (20 seconds at 94oC), annealing for (55 seconds at 55oC), and extension (15 seconds at 72oC). Result: All samples had valid extraction process with a CT value of internal control between 26.97 to 28.89. A total of 30 samples displayed positive results and 10 samples exhibited negative results with 100% agreement for both methods. This has resulted with a 100% accuracy between both methods. Conclusions: Both semi-automated methods from Qiagen and Abbott are comparable and accurate despite different technology and different primer genes.

Proteomic approaches define rocaglates as translation remodelers with multiple protein targets

Intro: Deregulated protein synthesis is a common trait across solid and hematologic malignancies and an attractive target for cancer therapy. Rocaglates compounds that inhibit eukaryotic initiation factor 4A1 (eIF4A1), the essential DEAD-box RNA helicase that resolves mRNA 5'UTR secondary structures during cap-dependent translation initiation. Rocaglates' unique mechanism of action causes sequence-selective mRNA binding by eIF4A1, clamping the inactive helicase onto the transcript. This suppresses translation globally and affects many oncogenic and pro-survival transcripts in particular. Zotatifin, the first-in class synthetic rocaglate, is currently in Phase I clinical trials for the treatment of solid tumors and as an antiviral against SARS-CoV2. Currently, eIF4A1 and DDX3 are the only reported targets of rocaglate-mediated RNA clamping. Employing unbiased proteomic approaches, we have discovered that rocaglates, thought to act as pure eIF4A/translation inhibitors, extensively remodel the translation machinery and translatome. Additionally, mass-spec interrogation for proteins interacting with specific RNA sequences reveals novel targets of rocaglate-mediated, sequence-specific RNA clamping. Methods: We conducted original mass-spectrometry analyses of translational reprogramming by rocaglates. TMT-pSILAC assessed acute changes in protein production, while MATRIX, which captures high-resolution profiles of the translation machinery, revealed translation factors that drive reprogramming in response to rocaglate exposure. We validated results biochemically, in cellulo, and in vivo using patient-derived xenograft (PDX) mouse models. To probe existing and novel rocaglate RNA-clamping targets, we developed unbiased “clampome” assays - in cellulo protein-RNA-pull downs followed by mass-spec analysis of proteins with increased binding to RNA in the presence of rocaglates. Results: We find rocaglates, including zotatifin, have effects far more complex than simple “translational inhibition” as currently defined. Indeed, translatome analysis by TMT-pSILAC revealed myriad up-regulated proteins that drive hitherto unrecognized cytotoxic mechanisms. The GEF-H1 guanine exchange factor, for example, drives anti-survival RHOA/JNK activation, suggesting novel candidate biomarkers of rocaglate clinical outcomes. Translation-machinery analysis by MATRIX identifed rocaglate-induced dependence on specific translation factors including eEF1ϵ1 that drive remodeling. Novel rocaglate RNA-binding targets revealed by clampome studies remain under detailed evaluation as mediators of drug activities. Discussion: Our original proteome-level interrogation revealed that the complete cellular response to these historical “translation inhibitors” is mediated by comprehensive translational landscape remodeling. Effects on a broader suite of RNA binding proteins than eIF4A1 alone we suggest mediate the potent antitumor activities of these unique compounds, elucidation of which permits development of novel precision approaches to targeted translational deregulation in cancer.

Immune cell profiling of patients with COVID-19 with mild, severe and prognosis states revealed by single-cell RNA sequencing

Objective: To construct single-cell transcription landscape of peripheral blood mononuclear cells (PBMCs) of patients with mild, severe and prognosis states of corona virus disease 2019 (COVID-19), and to analyze the relationship between disease progression and host immune response. Methods: Single-cell RNA sequence (scRNA-seq) data of healthy controls and for severe, mild, early recovery stage and later recovery stage PBMCs of patients with COVID-19 were obtained from public databases. After the cells were clustered according to the expression profile of each cell, the cell subtypes of each cluster were determined according to the known cell markers, and the proportion of each cell subtype was counted.The differentially expressed genes of each cell subtype were analyzed. Results: After quality control, the 115 334 PBMCs were classified into 22 cell subsets.Among them, CD14+ monocytes, inflammatory monocytes, naïve B cells and intermediate memory B cells significantly increased in PBMCs of severe patients.The proportion of proliferative CD8+ T/NK cells significantly increased in T cells of severe patients.XCL1+NK cells significantly decrease in PBMCs of severe patients.The proportion of cDC2 cells and pDC cells were significantly increased in PBMCs of recovery patients.With the remission and recovery of the disease, the proportion of NK cells in PBMCs increased gradually.The genes related to leukocyte activation and immune regulation were upregulated in both disease stage and recovery stage. Conclusion: The cell proportion and expression profile of PBMCs in patients with mild, severe and prognosis states of COVID-19 varied greatly. © 2022, Editorial Department of Fudan University Journal of Medical Sciences. All right reserved.

Mammary Tissue Host-Microbiome Interactions in Breast Cancer Development

Through this project we will determine the role of the mammary tissue microbiome in breast cancer development using 16S ribosomal RNA sequencing and dual-transcriptomic sequencing. In the first two years of this project we have selected and received 165 samples from the Susan G. Komen and Indiana University Simon Cancer Center TissueBanks. We completed 16S rRNA sequencing on DNA isolated from all samples in this cohort and note a distinct microbial compositional signature that is associated with breast cancer development. We anticipate submitting this work for publication by February 2021. Due to COVID-19, the RNA isolations from these samples have been delayed until we can return to campus. We anticipate completing RNA isolations in Summer 2021 and will begin our analysis of the RNA sequencing data in Fall 2021. Regardless of these delays, the project is well underway. Results from this work will be key in characterizing host-microbiome cross-talk in the pathogenesis of breast tumor development.

Integrated Molecular Pathogenesis of Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a heterogeneous clinical syndrome that represents the end-stage of chronic interstitial lung diseases. Dozens of different occupational, environmental, immune and genetic risk factors have been associated with PF, and through the past several decades, risk factor exposures have been the driving force in the diagnostic classification of PF, thus in the current paradigm, there are dozens of different diagnoses of pulmonary fibrosis. This emphasis on distinction has focused much attention on the most common form of this syndrome (Idiopathic Pulmonary Fibrosis, IPF), which comprises only 20 of PF patients. Today there are2 modestly effective FDA-approved treatments for IPF;however, for the 80 of PF patients with other diagnoses, there are no known effective treatments.

Understanding and Targeting Pulmonary Arteriovenous Malformations Using Repurposed Drugs

Hereditary hemorrhagic telangiectasia (HHT) is a genetic disease characterized by multiple arteriovenous malformations(AVMs) which are direct connections between arteries and veins, bypassing the capillary bed. Severe epistaxis (nosebleeds) is the most common symptom, yet visceral AVMs in the brain (1-10%), lung (15-45%), liver and gastrointestinal tract cause significant morbidity and mortality due to embolic stroke, cerebral abscess, migraines, hemorrhagic stroke, seizures and life-threatening bleeding complications. In order to reduce the morbidity and mortality associated with HHT, we need a better understanding of HHT development and novel treatment approaches. Our aims are: Aim 1: To understand the cellular and molecular mechanisms of PAVM development in mice and to identify the cell behaviors and populations that give rise to PAVMs. Aim 2: To identify and target pathological downstream signaling in endothelial cells derived from iPSCs (iPSC-ECs)from HHT patients with visceral AVMs. Aim 3: To target pathological downstream signaling with repurposed drugs to prevent and reverse PAVMs in the mouse model. The short-term impact will be a better understanding of how AVMs form in the lung and potentially in other organs. The long-term impact will be the identification of potential novel treatments for AVMs.

Single Nucleus Expression Profiling of Human Sciatic Nerve After Traumatic Amputation: Predicting Pain and Functional Outcomes

A majority of service members who undergo traumatic amputation develop chronic phantom or chronic residual limb pain with 10-15% of these patients developing severe, disabling, long-term pain. 30-40% of traumatic amputees, however, have no clinically significant chronic pain. We believe this dichotomy of outcome is the key to understanding the development of chronic neuropathic pain after nerve injury. Preclinical studies using rodent models have provided some insights into the pathological sequelae of nerve injury, but this knowledge has not resulted in successful translation to the clinic. Recent evidence suggests that interspecies differences are a major barrier to successful translation, since rodent sensory neurons diverge considerably from their human counterparts. Accordingly, in order to better understand the pathological processes that lead to neuropathic pain after nerve injury, it is necessary to comprehensively study injured human nerves. Our colleagues at Walter Reed National Military Medical Center spent three years obtaining sciatic nerve samples from service members undergoing primary amputation revision surgery after suffering traumatic amputation on the battlefield. These unique samples allow, for the first time, study of nerve regeneration and neuroinflammation in humans during the days following traumatic amputation. Utilizing bulk tissue and single nuclei RNA-sequencing and unbiased global proteomics of the distal portion of sciatic nerve collected 1-14 days after initial traumatic amputation, we aim to establish the distinctive transcriptional, protein and glial/immune cell profile of injured sciatic nerve during injury and regeneration.

Idiopathic Pulmonary Fibrosis, a Disease Initiated by Mucociliary Dysfunction

The overarching goal of this Program is to develop the scientific knowledge needed to predict and prevent the progression of IPF. We postulate that IPF is caused by recurrent injury/repair/regeneration at the bronchoalveolar junction secondary to overexpression of MUC5B, mucociliary dysfunction, retention of particles, ER stress, and disruption of normal reparative and regenerative mechanisms in the distal lung. During the first year of funding, we have (1) obtained local and DoD approvals for human and animal research;(2) enrolled 26 first degree relatives of individuals with IPF and completed all study procedures for Project 1;(3) performed ChIP, MNase, and TF binding assays to show that MUC5B promoter region is hyperchippable and that HIF1 and GCF bind in this region (Project 2);(4) imported and bred new strains of mice (St3gal3, Fut2, Ern2, Ift88, and Arl13b) in Projects 3 and 4;(5) developed and assessed the amounts and glycosylation of Muc5b in mouse models at baseline, and identified changes in polymer size and migration after inflammatory challenge (Project 3);(6) identified 10 weeks post-injury as a key timepoint for increased ciliogenesis in Muc5b Tg mice and began characterization of ciliogenesis in human lung, and (7) presented findings at two international conferences and published two manuscripts.

RNA Sequence Based Prediction of Coronavirus Using Machine Learning

The detection of the virus is a basic concern for the doctors and the virology for over a decades due to the dynamic behavior and mutations of the virus makes it difficult to detect the virus and study its behaviors. Latest computational techniques enables scientists to crate models that are proficient of learning patterns from the data as well as used to make predictions for unseen data.. As machine learning techniques predicts the corona viruses by allowing for their differing genetic purposeful characteristics, we propose machine learning supported coronavirus prediction method Novel-COV-2 Predictor wherever RNA sequences of SARSCoV-1, MERS, and SARS-CoV-2 are used to instruct a classifier so that it can expect any indefinite sequence of these viruses. The RNA sequence is given in the form of the large text files. Consequently, it becomes a text classification complexity. We convert these data in the text files into numerical data using the count vectorization and utilize machine learning to create a model to know the patterns. In this regard, we have considered Support Vector Machine (SVM) algorithm to evaluate and so that SARSCoV-2 can be predicted as untimely as potential to save human life. © 2021 IEEE.

Promising Assays for Examining a Putative Role of Ribosomal Heterogeneity in COVID-19 Susceptibility and Severity.

The heterogeneity of ribosomes, characterized by structural variations, arises from differences in types, numbers, and/or post-translational modifications of participating ribosomal proteins (RPs), ribosomal RNAs (rRNAs) sequence variants plus post-transcriptional modifications, and additional molecules essential for forming a translational machinery. The ribosomal heterogeneity within an individual organism or a single cell leads to preferential translations of selected messenger RNA (mRNA) transcripts over others, especially in response to environmental cues. The role of ribosomal heterogeneity in SARS-CoV-2 coronavirus infection, propagation, related symptoms, or vaccine responses is not known, and a technique to examine these has not yet been developed. Tools to detect ribosomal heterogeneity or to profile translating mRNAs independently cannot identify unique or specialized ribosome(s) along with corresponding mRNA substrate(s). Concurrent characterizations of RPs and/or rRNAs with mRNA substrate from a single ribosome would be critical to decipher the putative role of ribosomal heterogeneity in the COVID-19 disease, caused by the SARS-CoV-2, which hijacks the host ribosome to preferentially translate its RNA genome. Such a protocol should be able to provide a high-throughput screening of clinical samples in a large population that would reach a statistical power for determining the impact of a specialized ribosome to specific characteristics of the disease. These characteristics may include host susceptibility, viral infectivity and transmissibility, severity of symptoms, antiviral treatment responses, and vaccine immunogenicity including its side effect and efficacy. In this study, several state-of-the-art techniques, in particular, chemical probing of ribosomal components or rRNA structures, proximity ligation to generate rRNA-mRNA chimeras for sequencing, nanopore gating of individual ribosomes, nanopore RNA sequencing and/or structural analyses, single-ribosome mass spectrometry, and microfluidic droplets for separating ribosomes or indexing rRNAs/mRNAs, are discussed. The key elements for further improvement and proper integration of the above techniques to potentially arrive at a high-throughput protocol for examining individual ribosomes and their mRNA substrates in a clinical setting are also presented.