Alternative RNA splicing and alternative transcription start/end in acute respiratory distress syndrome

Predicting Nonsense-mediated mRNA Decay from Splicing Events in Sepsis using RNA-Sequencing Data

Alternative splicing (AS) and nonsense-mediated mRNA decay (NMD) are highly conserved cellular mechanisms that modulate gene expression. Here we introduce NMD pipeline that computes how splicing events introduce premature termination codons to mRNA transcripts via frameshift, then predicts the rate of PTC-dependent NMD. We utilize whole blood, deep RNA-sequencing data from critically ill patients to study gene expression in sepsis. Statistical significance was determined as adjusted p value < 0.05 and |log2foldchange| > 2 for differential gene expression and probability >= 0.9 and |DeltaPsi| > 0.1 for AS. NMD pipeline was developed based on AS data from Whippet. We demonstrate that the rate of NMD is higher in sepsis and deceased groups compared to control and survived groups, which signify purposeful downregulation of transcripts by AS-NMD or aberrant splicing due to altered physiology. Predominance of non-exon skipping events was associated with disease and mortality states. The NMD pipeline also revealed proteins with potential novel roles in sepsis. Together, these results emphasize the utility of NMD pipeline in studying AS-NMD along with differential gene expression and discovering potential protein targets in sepsis.

LPS-induced TMBIM6 splicing drives endothelial necroptosis and aggravates ALI

BACKGROUND

The mechanism underlying necroptosis in pulmonary vessel endothelial cells (PVECs) resulting from long non-coding RNA (lncRNA)-induced alternative splicing (AS) of target genes in acute lung injury (ALI) remains unclear.

METHODS

Lipopolysaccharide (LPS)-induced expression of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and lncRNAs was analyzed via RT-PCR in PVECs. Full-transcriptome sequencing was used to detect AS-related mRNAs. The interaction between lncRNA MALAT1 and target gene transmembrane BAX inhibitor motif-containing 6 (TMBIM6) was verified using a dual-luciferase reporter system. Necroptosis was measured as protein levels of phosphorylated receptor-interacting serine/threonine kinase 1 (RIPK1), RIPK3, and mixed-lineage kinase domain-like (MLKL) proteins, as well as flow cytometer measurement. Antisense of MALAT1, TMBIM6, TMBIM6-225 and RIPK1 inhibitor were transfected into a rat model of LPS-induced ALI. Hematoxylin and eosin (H&E) and immunohistochemical staining were performed to evaluate lung injury.

RESULTS

LPS upregulated the expression of TNF-α, IL-1β, IL-6, p-RIPK1, p-RIPK3, p-MLKL, MALAT1, and TMBIM6-225 (an AS isoform of MALAT1-targeted gene TMBIM6) in PVECs. However, it downregulated the expression of TMBIM6. An antisense of MALAT1 inhibited TMBIM6-225 and downregulated p-MLKL. The pro-necroptotic effect of MALAT1 was verified in an LPS-induced MALAT1/shMALAT1-transfected ALI rat model in vivo. The necroptotic effect was reversed by treatment with necrostatin-1.

CONCLUSIONS

LPS-induced MALAT1 causes AS of TMBIM6, and the AS variant TMBIM6-225 aggravates ALI by promoting PVEC necroptosis via the p-RIPK1, p-RIPK3, and p-MLKL complex.

Genome-wide analysis of RNA-binding protein co-expression with alternative splicing events in acute respiratory distress syndrome following hematopoietic stem cell transplantation

Patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are at an increased risk of developing severe acute respiratory distress syndrome (ARDS), which is characterized by peripheral bilateral patchy lung involvement. The regulatory network of RNA-binding protein (RBP)-alternative splicing (AS) in ARDS following HSCT has not been investigated. We hypothesize that RBP-AS plays a regulatory role during HSCT-ARDS. The published ARDS transcriptome data after HSCT (GSE84439) were downloaded, and the transcriptome data of 13 mRNAs were obtained by sequencing the peripheral blood of 5 HSCT-ARDS patients and 8 ARDS patients through high-throughput sequencing technology. Systematic analysis of downloaded data was performed to obtain differentially expressed RBPs, and the differentially alternative spliced pre-mRNAs in HSCT-ARDS and control groups were used to explore the global gene RBP-AS regulatory network. A total of 1769 differentially expressed genes and 4714 regulated alternative splicing events were identified in peripheral blood from HSCT-ARDS, of which 254 genes had both differential expression and differential AS. In addition, 128 RBPs were identified, of which HDGF, PCBP2, RIOK3, CISD2, and TRIM21, DDX58, MOV10 showed significantly increased or decreased expression in the HSCT-ARDS. RBPs with decreased expression had antiviral activity, while those with increased expression were involved in ROS, fibrosis, and negative viral resistance. The RBP-RASE-RASG regulatory network is constructed. It is related to the dysregulation of antiviral immunomodulation, imbalance in ROS homeostasis and pro-pulmonary fibrosis, which are involved in the development of HSCT-ARDS.

Deep RNA sequencing of intensive care unit patients with COVID-19

COVID-19 has impacted millions of patients across the world. Molecular testing occurring now identifies the presence of the virus at the sampling site: nasopharynx, nares, or oral cavity. RNA sequencing has the potential to establish both the presence of the virus and define the host's response in COVID-19. Single center, prospective study of patients with COVID-19 admitted to the intensive care unit where deep RNA sequencing (> 100 million reads) of peripheral blood with computational biology analysis was done. All patients had positive SARS-CoV-2 PCR. Clinical data was prospectively collected. We enrolled fifteen patients at a single hospital. Patients were critically ill with a mortality of 47% and 67% were on a ventilator. All the patients had the SARS-CoV-2 RNA identified in the blood in addition to RNA from other viruses, bacteria, and archaea. The expression of many immune modulating genes, including PD-L1 and PD-L2, were significantly different in patients who died from COVID-19. Some proteins were influenced by alternative transcription and splicing events, as seen in HLA-C, HLA-E, NRP1 and NRP2. Entropy calculated from alternative RNA splicing and transcription start/end predicted mortality in these patients. Current upper respiratory tract testing for COVID-19 only determines if the virus is present. Deep RNA sequencing with appropriate computational biology may provide important prognostic information and point to therapeutic foci to be precisely targeted in future studies.

Deep RNA Sequencing of Intensive Care Unit Patients with COVID-19

PURPOSE

COVID-19 has impacted millions of patients across the world. Molecular testing occurring now identifies the presence of the virus at the sampling site: nasopharynx, nares, or oral cavity. RNA sequencing has the potential to establish both the presence of the virus and define the host's response in COVID-19.

METHODS

Single center, prospective study of patients with COVID-19 admitted to the intensive care unit where deep RNA sequencing (>100 million reads) of peripheral blood with computational biology analysis was done. All patients had positive SARS-CoV-2 PCR. Clinical data was prospectively collected.

RESULTS

We enrolled fifteen patients at a single hospital. Patients were critically ill with a mortality of 47% and 67% were on a ventilator. All the patients had the SARS-CoV-2 RNA identified in the blood in addition to RNA from other viruses, bacteria, and archaea. The expression of many immune modulating genes, including PD-L1 and PD-L2, were significantly different in patients who died from COVID-19. Some proteins were influenced by alternative transcription and splicing events, as seen in HLA-C, HLA-E, NRP1 and NRP2. Entropy calculated from alternative RNA splicing and transcription start/end predicted mortality in these patients.

CONCLUSIONS

Current upper respiratory tract testing for COVID-19 only determines if the virus is present. Deep RNA sequencing with appropriate computational biology may provide important prognostic information and point to therapeutic foci to be precisely targeted in future studies.

TAKE HOME MESSAGE

Deep RNA sequencing provides a novel diagnostic tool for critically ill patients. Among ICU patients with COVID-19, RNA sequencings can identify gene expression, pathogens (including SARS-CoV-2), and can predict mortality.

TWEET

Deep RNA sequencing is a novel technology that can assist in the care of critically ill COVID-19 patients & can be applied to other disease.