Abundance of ACVR1B transcript is elevated during septic conditions: Perspectives obtained from a hands-on reductionist investigation

Sepsis is a complex heterogeneous condition, and the current lack of effective risk and outcome predictors hinders the improvement of its management. Using a reductionist approach leveraging publicly available transcriptomic data, we describe a knowledge gap for the role of ACVR1B (activin A receptor type 1B) in sepsis. ACVR1B, a member of the transforming growth factor-beta (TGF-beta) superfamily, was selected based on the following: 1) induction upon in vitro exposure of neutrophils from healthy subjects with the serum of septic patients (GSE49755), and 2) absence or minimal overlap between ACVR1B, sepsis, inflammation, or neutrophil in published literature. Moreover, ACVR1B expression is upregulated in septic melioidosis, a widespread cause of fatal sepsis in the tropics. Key biological concepts extracted from a series of PubMed queries established indirect links between ACVR1B and "cancer", "TGF-beta superfamily", "cell proliferation", "inhibitors of activin", and "apoptosis". We confirmed our observations by measuring ACVR1B transcript abundance in buffy coat samples obtained from healthy individuals (n=3) exposed to septic plasma (n = 26 melioidosis sepsis cases)ex vivo. Based on our re-investigation of publicly available transcriptomic data and newly generated ex vivo data, we provide perspective on the role of ACVR1B during sepsis. Additional experiments for addressing this knowledge gap are discussed.

Dataset of dual RNA-seq mapping in visceral leishmaniasis: Inquiry on parasite transcripts in human blood transcriptome upon Leishmania infantum infection

This dataset is related to the article "Insight Into the Long Noncoding RNA and mRNA Coexpression Profile in the Human Blood Transcriptome Upon Leishmania infantum Infection" by S.R. Maruyama, C.A. Fuzo, A.E.R. Oliveira, L.A. Rogerio, N.T. Takamiya, G. Pessenda, E.V. de Melo, A.M. da Silva, A.R. Jesus, V. Carregaro, H.I. Nakaya, R.P. Almeida and J.S. da Silva. Frontiers in Immunology, 2022. Through the reuse of raw sequencing data, we generated original dataset by performing a dual RNA-seq mapping procedure to survey the parasite transcripts found in RNA-seq samples from blood of visceral leishmaniasis patients. Diseased patients with active infection displayed the highest number of reads mapped to L. infantum genome. Even after six months later of the treatment, when the patients were considered cured, parasite reads were still detected. Parasite reads were also detected in asymptomatic individuals. The original dual RNA-seq alignment read count data provided here can be further explored to evaluate either host or parasite transcripts.

Understanding the Mechanism of Diabetes Mellitus in a LRBA-Deficient Patient

The scope of this study is to show that DM in a LRBA-deficient patient with a stop codon mutation (c.3999 G > A) was not mediated through autoimmunity. We have evaluated the ability of the proband’s T cells to be activated by assessing their CTLA-4 expression. A nonsignificant difference was seen in the CTLA-4 expression on CD3+ T cells compared to the healthy control at basal level and after stimulation with PMA/ionomycin. Blood transcriptomic analysis have shown a remarkable increase in abundance of transcripts related to CD71+ erythroid cells. There were no differences in the expression of modules related to autoimmunity diseases between the proband and pooled healthy controls. In addition, our novel findings show that siRNA knockdown of LRBA in mouse pancreatic β-cells leads reduced cellular proinsulin, insulin and consequently insulin secretion, without change in cell viability in cultured MIN6 cells.

Insight Into the Long Noncoding RNA and mRNA Coexpression Profile in the Human Blood Transcriptome Upon Leishmania infantum Infection

Visceral leishmaniasis (VL) is a vector-borne infectious disease that can be potentially fatal if left untreated. In Brazil, it is caused by Leishmania infantum parasites. Blood transcriptomics allows us to assess the molecular mechanisms involved in the immunopathological processes of several clinical conditions, namely, parasitic diseases. Here, we performed mRNA sequencing of peripheral blood from patients with visceral leishmaniasis during the active phase of the disease and six months after successful treatment, when the patients were considered clinically cured. To strengthen the study, the RNA-seq data analysis included two other non-diseased groups composed of healthy uninfected volunteers and asymptomatic individuals. We identified thousands of differentially expressed genes between VL patients and non-diseased groups. Overall, pathway analysis corroborated the importance of signaling involving interferons, chemokines, Toll-like receptors and the neutrophil response. Cellular deconvolution of gene expression profiles was able to discriminate cellular subtypes, highlighting the contribution of plasma cells and NK cells in the course of the disease. Beyond the biological processes involved in the immunopathology of VL revealed by the expression of protein coding genes (PCGs), we observed a significant participation of long noncoding RNAs (lncRNAs) in our blood transcriptome dataset. Genome-wide analysis of lncRNAs expression in VL has never been performed. lncRNAs have been considered key regulators of disease progression, mainly in cancers; however, their pattern regulation may also help to understand the complexity and heterogeneity of host immune responses elicited by L. infantum infections in humans. Among our findings, we identified lncRNAs such as IL21-AS1, MIR4435-2HG and LINC01501 and coexpressed lncRNA/mRNA pairs such as CA3-AS1/CA1, GASAL1/IFNG and LINC01127/IL1R1-IL1R2. Thus, for the first time, we present an integrated analysis of PCGs and lncRNAs by exploring the lncRNA–mRNA coexpression profile of VL to provide insights into the regulatory gene network involved in the development of this inflammatory and infectious disease.

High-Density Blood Transcriptomics Reveals Precision Immune Signatures of SARS-CoV-2 Infection in Hospitalized Individuals

The immune response to COVID-19 infection is variable. How COVID-19 influences clinical outcomes in hospitalized patients needs to be understood through readily obtainable biological materials, such as blood. We hypothesized that a high-density analysis of host (and pathogen) blood RNA in hospitalized patients with SARS-CoV-2 would provide mechanistic insights into the heterogeneity of response amongst COVID-19 patients when combined with advanced multidimensional bioinformatics for RNA. We enrolled 36 hospitalized COVID-19 patients (11 died) and 15 controls, collecting 74 blood PAXgene RNA tubes at multiple timepoints, one early and in 23 patients after treatment with various therapies. Total RNAseq was performed at high-density, with >160 million paired-end, 150 base pair reads per sample, representing the most sequenced bases per sample for any publicly deposited blood PAXgene tube study. There are 770 genes significantly altered in the blood of COVID-19 patients associated with antiviral defense, mitotic cell cycle, type I interferon signaling, and severe viral infections. Immune genes activated include those associated with neutrophil mechanisms, secretory granules, and neutrophil extracellular traps (NETs), along with decreased gene expression in lymphocytes and clonal expansion of the acquired immune response. Therapies such as convalescent serum and dexamethasone reduced many of the blood expression signatures of COVID-19. Severely ill or deceased patients are marked by various secondary infections, unique gene patterns, dysregulated innate response, and peripheral organ damage not otherwise found in the cohort. High-density transcriptomic data offers shared gene expression signatures, providing unique insights into the immune system and individualized signatures of patients that could be used to understand the patient’s clinical condition. Whole blood transcriptomics provides patient-level insights for immune activation, immune repertoire, and secondary infections that can further guide precision treatment.

A human minisatellite hosts an alternative transcription start site for NPRL3 driving its expression in a repeat number-dependent manner

Minisatellites, also called variable number of tandem repeats (VNTRs), are a class of repetitive elements that may affect gene expression at multiple levels and have been correlated to disease. Their identification and role as expression quantitative trait loci (eQTL) have been limited by their absence in comparative genomic hybridization and single nucleotide polymorphisms arrays. By taking advantage of cap analysis of gene expression (CAGE), we describe a new example of a minisatellite hosting a transcription start site (TSS) which expression is dependent on the repeat number. It is located in the third intron of the gene nitrogen permease regulator like protein 3 (NPRL3). NPRL3 is a component of the GAP activity toward rags 1 protein complex that inhibits mammalian target of rapamycin complex 1 (mTORC1) activity and it is found mutated in familial focal cortical dysplasia and familial focal epilepsy. CAGE tags represent an alternative TSS identifying TAGNPRL3 messenger RNAs (mRNAs). TAGNPRL3 is expressed in red blood cells both at mRNA and protein levels, it interacts with its protein partner NPRL2 and its overexpression inhibits cell proliferation. This study provides an example of a minisatellite that is both a TSS and an eQTL as well as identifies a new VNTR that may modify mTORC1 activity.

Mining the Dynamic Genome: A Method for Identifying Multiple Disease Signatures Using Quantitative RNA Expression Analysis of a Single Blood Sample

Background: Blood has advantages over tissue samples as a diagnostic tool, and blood mRNA transcriptomics is an exciting research field. To realize the full potential of blood transcriptomic investigations requires improved methods for gene expression measurement and data interpretation able to detect biological signatures within the “noisy” variability of whole blood. Methods: We demonstrate collection tube bias compensation during the process of identifying a liver cancer-specific gene signature. The candidate probe set list of liver cancer was filtered, based on previous repeatability performance obtained from technical replicates. We built a prediction model using differential pairs to reduce the impact of confounding factors. We compared prediction performance on an independent test set against prediction on an alternative model derived by Weka. The method was applied to an independent set of 157 blood samples collected in PAXgene tubes. Results: The model discriminated liver cancer equally well in both EDTA and PAXgene collected samples, whereas the Weka-derived model (using default settings) was not able to compensate for collection tube bias. Cross-validation results show our procedure predicted membership of each sample within the disease groups and healthy controls. Conclusion: Our versatile method for blood transcriptomic investigation overcomes several limitations hampering research in blood-based gene tests.

Meta-analysis on blood transcriptomic studies identifies consistently coexpressed protein-protein interaction modules as robust markers of human aging

The bodily decline that occurs with advancing age strongly impacts on the prospects for future health and life expectancy. Despite the profound role of age in disease etiology, knowledge about the molecular mechanisms driving the process of aging in humans is limited. Here, we used an integrative network-based approach for combining multiple large-scale expression studies in blood (2539 individuals) with protein–protein Interaction (PPI) data for the detection of consistently coexpressed PPI modules that may reflect key processes that change throughout the course of normative aging. Module detection followed by a meta-analysis on chronological age identified fifteen consistently coexpressed PPI modules associated with chronological age, including a highly significant module (P = 3.5 × 10⁻³⁸) enriched for ‘T-cell activation’ marking age-associated shifts in lymphocyte blood cell counts (R² = 0.603; P = 1.9 × 10⁻¹⁰). Adjusting the analysis in the compendium for the ‘T-cell activation’ module showed five consistently coexpressed PPI modules that robustly associated with chronological age and included modules enriched for ‘Translational elongation’, ‘Cytolysis’ and ‘DNA metabolic process’. In an independent study of 3535 individuals, four of five modules consistently associated with chronological age, underpinning the robustness of the approach. We found three of five modules to be significantly enriched with aging-related genes, as defined by the GenAge database, and association with prospective survival at high ages for one of the modules including ASF1A. The hereby-detected age-associated and consistently coexpressed PPI modules therefore may provide a molecular basis for future research into mechanisms underlying human aging.

Longitudinal analysis of whole blood transcriptomes to explore molecular signatures associated with acute renal allograft rejection

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature.