Unique tRNA Fragment Upregulation with SARS-CoV-2 but Not with SARS-CoV Infection.

Unlike other coronaviruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly infected the global population, with some suffering long-term effects. Thanks to extensive data on SARS-CoV-2 made available through global, multi-level collaborative research, investigators are getting closer to understanding the mechanisms of SARS-CoV-2 infection. Here, using publicly available total and small RNAseq data of Calu3 cell lines, we conducted a comparative analysis of the changes in tRNA fragments (tRFs; regulatory small noncoding RNAs) in the context of severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2 infections. We found extensive upregulation of multiple tRFs in SARS-CoV-2 infection that was not present in SARS-CoV or other virus infections our group has studied. By comparing the total RNA changes in matching samples, we identified significant downregulation of TRDMT1 (tRNA methyltransferase), only in SARS-CoV-2 infection, a potential upstream event. We further found enriched neural functions among downregulated genes with SARS-CoV-2 infection. Interestingly, theoretically predicted targets of the upregulated tRFs without considering mRNA expression data are also enriched in neural functions such as axon guidance. Based on a combination of expression data and theoretical calculations, we propose potential targets for tRFs. For example, among the mRNAs downregulated with SARS-CoV-2 infection (but not with SARS-CoV infection), SEMA3C is a theoretically calculated target of multiple upregulated tRFs and a ligand of NRP1, a SARS-CoV-2 receptor. Our analysis suggests that tRFs contribute to distinct neurological features seen in SARS-CoV-2.

Changes of Small Non-coding RNAs by Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. In the context of viral infections, small non-coding RNAs (sncRNAs) are known to play important roles in regulating the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK-RNA-seq, a modified next-generation sequencing (NGS), we found that sncRNA profiles in human nasopharyngeal swabs (NPS) samples are significantly impacted by SARS-CoV-2. Among impacted sncRNAs, tRFs are the most significantly affected and most of them are derived from the 5'-end of tRNAs (tRF5). Such a change was also observed in SARS-CoV-2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several small virus-derived ncRNAs (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3'-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.

Changes of small non-coding RNAs by severe acute respiratory syndrome coronavirus 2 infection.

The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. Small non-coding RNAs (sncRNAs) are known to play important roles in almost all biological processes. In the context of viral infections, sncRNAs have been shown to regulate the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK-RNA-seq, a modified next-generation sequencing (NGS), we recently found that nasopharyngeal swabs (NPS) samples from SARS-CoV-2 positive and negative subjects show a significant difference in sncRNA profiles. There are about 166 SARS-CoV-2-impacted sncRNAs. Among them, tRFs are the most significantly affected and almost all impacted tRFs are derived from the 5'-end of tRNAs (tRF5). Using a modified qRT-PCR, which was recently developed to specifically quantify tRF5s by isolating the tRF signals from its corresponding parent tRNA signals, we validated that tRF5s derived from tRNA GluCTC (tRF5-GluCTC), LysCTT (tRF5-LysCTT), ValCAC (tRF5-ValCAC), CysGCA (tRF5-CysGCA) and GlnCTG (tRF5-GlnCTG) are enhanced in NPS samples of SARS-CoV2 patients and SARS-CoV2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several sncRNAs derived from the virus (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3'-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.

Electronic DNA Analysis of CSF Cell-free Tumor DNA to Quantify Multi-gene Molecular Response in Pediatric High-grade Glioma.

PURPOSE: Pediatric high-grade glioma (pHGG) diagnosis portends poor prognosis and therapeutic monitoring remains difficult. Tumors release cell-free tumor DNA (cf-tDNA) into cerebrospinal fluid (CSF), allowing for potential detection of tumor-associated mutations by CSF sampling. We hypothesized that direct, electronic analysis of cf-tDNA with a handheld platform (Oxford Nanopore MinION) could quantify patient-specific CSF cf-tDNA variant allele fraction (VAF) with improved speed and limit of detection compared with established methods. EXPERIMENTAL DESIGN: We performed ultra-short fragment (100-200 bp) PCR amplification of cf-tDNA for clinically actionable alterations in CSF and tumor samples from patients with pHGG (n = 12) alongside nontumor CSF (n = 6). PCR products underwent rapid amplicon-based sequencing by Oxford Nanopore Technology (Nanopore) with quantification of VAF. Additional comparison to next-generation sequencing (NGS) and droplet digital PCR (ddPCR) was performed. RESULTS: Nanopore demonstrated 85% sensitivity and 100% specificity in CSF samples (n = 127 replicates) with 0.1 femtomole DNA limit of detection and 12-hour results, all of which compared favorably with NGS. Multiplexed analysis provided concurrent analysis of H3.3A (H3F3A) and H3C2 (HIST1H3B) mutations in a nonbiopsied patient and results were confirmed by ddPCR. Serial CSF cf-tDNA sequencing by Nanopore demonstrated correlation of radiological response on a clinical trial, with one patient showing dramatic multi-gene molecular response that predicted long-term clinical response. CONCLUSIONS: Nanopore sequencing of ultra-short pHGG CSF cf-tDNA fragments is feasible, efficient, and sensitive with low-input samples thus overcoming many of the barriers restricting wider use of CSF cf-tDNA diagnosis and monitoring in this patient population.

CERNA SEARCH METHOD IDENTIFIED A MET-ACTIVATED SUBGROUP AMONG EGFR DNA AMPLIFIED LUNG ADENOCARCINOMA PATIENTS.

Given the diverse molecular pathways involved in tumorigenesis, identifying subgroups among cancer patients is crucial in precision medicine. While most targeted therapies rely on DNA mutation status in tumors, responses to such therapies vary due to the many molecular processes involved in propagating DNA changes to proteins (which constitute the usual drug targets). Though RNA expressions have been extensively used to categorize tumors, identifying clinically important subgroups remains challenging given the difficulty of discerning subgroups within all possible RNA-RNA networks. It is thus essential to incorporate multiple types of data. Recently, RNA was found to regulate other RNA through a common microRNA (miR). These regulating and regulated RNAs are referred to as competing endogenous RNAs (ceRNAs). However, global correlations between mRNA and miR expressions across all samples have not reliably yielded ceRNAs. In this study, we developed a ceRNA-based method to identify subgroups of cancer patients combining DNA copy number variation, mRNA expression, and microRNA (miR) expression data with biological knowledge. Clinical data is used to validate identified subgroups and ceRNAs. Since ceRNAs are causal, ceRNA-based subgroups may present clinical relevance. Using lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) as an example, we focused on EGFR amplification status, since a targeted therapy for EGFR exists. We hypothesized that global correlations between mRNA and miR expressions across all patients would not reveal important subgroups and that clustering of potential ceRNAs might define molecular pathway-relevant subgroups. Using experimentally validated miR-target pairs, we identified EGFR and MET as potential ceRNAs for miR-133b in lung adenocarcinoma. The EGFR-MET up and miR-133b down subgroup showed a higher death rate than the EGFR-MET down and miR-133b up subgroup. Although transactivation between MET and EGFR has been identified previously, our result is the first to propose ceRNA as one of its underlying mechanisms. Furthermore, since MET amplification was seen in the case of resistance to EGFR-targeted therapy, the EGFR-MET up and miR-133b down subgroup may fall into the drug non-response group and thus preclude EGFR target therapy.