RNA-seq Differential Expression Analysis Research Articles

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma.

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

Abstract 4561: Mechanism of histone H3K27me3 demethylase therapy for restoring cisplatin sensitivity in refractory testicular cancer

Abstract Testicular germ cell tumors (TGCTs) can be cured at a high rate with standard cisplatin-based chemotherapy, but 15% of metastatic patients are cisplatin resistant/refractory and die from progressive disease. In prior work, we used de novo pharmacogenetic approaches leveraging a series of unique cisplatin resistant cell models that uncovered an important role for polycomb and histone H3K27me3 methylation in mediating TGCT sensitivity and resistance to cisplatin. Importantly, we demonstrated that pharmacological inhibition of H3K27 methylation with the EZH2 inhibitor GSK-126 conferred cisplatin resistance to parental cells while induction of H3K27 methylation with the histone lysine demethylase inhibitor GSK-J4 resulted in a high degree of cisplatin sensitization of TGCT tumors including cisplatin resistant TGCT cells. In order to elucidate mechanisms that account for the remarkable cisplatin sensitization effects of GSKJ4 in TGCTs, we used two distinct cisplatin resistant TGCT cell lines 2102EP-C1 and NT2D1-A4. Cells were pretreated for three days with either vehicle control or 1µM GSK-J4 to modulate H3K27me3 followed by treatment with vehicle control or 0.5µM cisplatin for 6 hours. RNA was extracted from cells after 24 hours of cisplatin removal. This treatment protocol was designed to capture “early” transcriptional responses to GSKJ4 sensitization before the onset of cell death. RNA-seq transcriptomic profiling and differential gene expression analysis revealed as expected a severely attenuated transcriptional response to cisplatin in cisplatin refractory cells that was restored with GSKJ4 pretreatment. Interestingly GSKJ4 alone resulted in a robust transcriptional response with a large overlap with gene changed with cisplatin alone, despite the fact that GSKJ4 alone did not affect cell proliferation or survival. However, GSKJ4 uniquely regulated a subset of genes and uniquely restored cisplatin response to a subset of genes which are candidates for driving the remarkable cisplatin sensitizing effects of GSKJ4 in TGCTs. Further enrichment and biological classification analysis of these distinct gene subsets are ongoing and will be presented. In summary, our data suggests mechanisms to account for why directly targeting H3K27 methylation with GSKJ4 appear highly effective in treating cisplatin resistant/refractory TGCTs and may provide biomarkers for future clinical investigation of this strategy. Citation Format: Doha Naguib Ahmed Mohamed Shokry, Ratnakar Singh, Mehwish Khan, Zeeshan Fazal, Raya Boyd, Christine Powell, Sarah J. Freemantle, Michael J. Spinella. Mechanism of histone H3K27me3 demethylase therapy for restoring cisplatin sensitivity in refractory testicular cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4561.

Abstract 1185: Novel association of an autoimmune-related axis and anti-CTLA-4-based toxicities in adjuvant immunotherapy-treated melanoma patients

Abstract Intro: Immune checkpoint inhibition (ICI) for metastatic unresectable melanoma has markedly improved survival, and has shown benefit as adjuvant (AT) and neoadjuvant (NAT) therapy. Although ICI treatments confer survival benefit, they frequently induce immune-related adverse events (irAEs), which are a substantial clinical problem, particularly in AT/NAT, where ICI is used in less advanced disease to prevent recurrence. As such, the biomarkers predicting irAE risk, in particular in AT/NAT, are urgently needed to improve patient outcomes. Methods: We assessed RNA from pre-treatment peripheral CD4+ and CD8+ T cells from adjuvant clinical trial patients (CheckMate-915; n=212 patients) treated with Nivolumab (n=130) or Ipilimumab/Nivolumab (Combo) (n=82). We performed RNA-seq differential expression analysis to identify baseline differences in the immune profiles of patients with no/mild toxicity (grade 0-2) versus severe toxicity (grade 3-5). Results: Gene ontology analysis of the differentially expressed genes (DEGs) among those with severe toxicity reveals significant enrichment of immune-related pathways (IL-2, IFN-gamma, T-cell receptors, Toll-like receptors). These are shared among cell types (CD4+/CD8+) and between treatments (Nivo/Combo). From predicted DEG protein-protein interactions, we identified a treatment- and cell-type-specific expression signature associated with irAE development in CD4+ cells from Combo-treated patients. This signature, involving genes in the spleen tyrosine kinase (SYK) pathway, correctly predicts severe irAE patients with 73% accuracy (chi-squared p-value=0.001). The signature also identifies patients with mild to moderate irAEs in organ systems previously found in autoimmune traits to be associated with SYK upregulation (including skin, GI, liver, and pancreas), with 96% of all predicted patients experiencing at least one of these SYK-related toxicities, and 79% experiencing two or more. Importantly, the signature is not associated with disease recurrence (p=0.79). Conclusions: We have identified baseline expression differences in key immune pathways in peripheral T cells from ICI-treated patients with severe irAEs, and defined an SYK-related gene signature correctly identifying over half of severe irAE patients in the Combo-treated cohort. This finding aligns with our previous work linking anti-CTLA-4 irAEs with a germline variant associated with high SYK expression. This gene signature may not only serve as a baseline biomarker of severe irAEs, but it may also help guide treatment decisions, reducing toxicity while retaining efficacy, which will be particularly important in the adjuvant setting. Citation Format: Kelsey R. Monson, Robert Ferguson, Joanna Handzlik, Jiahan Xiong, Sasha Dagayev, Leah Morales, Vylyny Chat, Anabelle Bunis, Chaitra Sreenivasaiah, Sonia Dolfi, Daniel Tenney, Iman Osman, Jeffrey Weber, Tomas Kirchhoff. Novel association of an autoimmune-related axis and anti-CTLA-4-based toxicities in adjuvant immunotherapy-treated melanoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1185.

Identifying Inflammatory Pathways That Promote RBC Alloimmunization in Patients with Sickle Cell Disease

Introduction: During red blood cell (RBC) transfusion, exposure to unmatched non-ABO antigens can lead to production of alloantibodies that promote potentially fatal hemolytic events. Patients with Sickle Cell Disease (SCD) have the highest incidence of RBC alloimmunization. Prior studies indicate that an altered immuno-regulatory and/or pro-inflammatory state may determine the risk of RBC alloimmunization. For example, one study reported that patients with SCD have inflammatory cytokine gene polymorphisms that could be associated with diverse disease presentations and alloimmunization. We previously reported that inflammatory type 1 interferons (IFNα/β) produced by innate immune cells are required for RBC alloimmunization in mice, while others have suggested that NFkB-induced cytokines play a role in murine transfusion models. However, the inflammatory factors that regulate RBC alloimmunization in patients with SCD are poorly understood. Alloimmunized patients with SCD also have elevated levels of anti-RBC autoantibodies, which facilitate erythrophagocytosis. Given the role of erythrophagocytosis by spleen macrophages in processing RBC antigens, we hypothesized that erythrophagocytosis of SCD RBCs may promote inflammatory pathways that regulate alloimmune responses. Methods: RBCs from control subjects (AA), and reticulocytes and mature RBCs from patients with SCD, were opsonized or not with anti-RBC antibodies (anti-RhD) and co-cultured for 3 hrs with human macrophages (hMac) differentiated from monocytes of healthy subjects. Phagocytosis of labeled RBCs was analyzed by flow cytometry. Bulk mRNA sequencing of co-cultured macrophages was performed to identify differential gene expression. Ingenuity Pathway Analysis (IPA) software was used to identify relevant pathways and upstream regulators of differentially expressed genes. To validate sequencing results, cytokine levels from co-culture supernatants were measured by multiplex cytokine assays. Results: Flow cytometric analysis revealed that opsonization was required for erythrophagocytosis in an FcR dependent manner. RNA-seq Differential Expression analysis of macrophages co-cultured with AA opsonized RBCs vs. non-opsonized RBCs identified 166 significantly upregulated and 24 downregulated genes (p<0.0001). IPA analysis revealed that the top 12 canonical pathways were related to inflammation, including TNF, IL-17, NF-kappa-B and NOD-like receptor signaling pathways. TNF signaling was the top predicted upstream regulator pathway with a fold enrichment score of 10.3 (16 genes) (p<0.0001). Co-cultures of mature RBCs from patients with SCD showed comparable results. When comparing macrophages from co-cultures of opsonized reticulocytes vs. non-opsonized reticulocytes from patients with SCD, 174 genes were upregulated and 31 were downregulated (p<0.0001). Pathway analysis also revealed unique signatures for opsonized reticulocytes from patients with SCD. The top 12 canonical pathways included TNF, NF-kappa-B and NOD-like receptor signaling pathways (Figure 1). The top predicted upstream regulators were TNF and the NF-kappa B signaling pathway with a fold enrichment score of 12.3 (22 genes) (p<0.0001) and 10.9 (18 genes), respectively (Figure 1). Finally, to validate the sequencing results, cytokines levels from supernatants of hMac co-cultures with the RBCs from the patients with SCD and control subjects were measured. Erythrophagocytosis of opsonized reticulocytes and AA RBCs, compared to non-opsonized co-cultures, led to production of NFκB-mediated cytokines, including TNF. Our results show that erythrophagocytosis of SCD RBCs promote NFκB-mediated TNF production. These results warrant further investigation of the role of NFκB-mediated inflammation in RBC alloimmunization in patients with SCD.

The synergistic negative effects of combined acidification and warming on the coral host and its symbiotic association with Symbiodiniaceae indicated by RNA-Seq differential expression analysis

The synergistic negative effects of combined acidification and warming on the coral host and its symbiotic association with Symbiodiniaceae indicated by RNA-Seq differential expression analysis

PyDESeq2: a python package for bulk RNA-seq differential expression analysis.

We present PyDESeq2, a python implementation of the DESeq2 workflow for differential expression analysis on bulk RNA-seq data. This re-implementation yields similar, but not identical, results: it achieves higher model likelihood, allows speed improvements on large datasets, as shown in experiments on TCGA data, and can be more easily interfaced with modern python-based data science tools. PyDESeq2 is released as an open-source software under the MIT license. The source code is available on GitHub at https://github.com/owkin/PyDESeq2 and documented at https://pydeseq2.readthedocs.io. PyDESeq2 is part of the scverse ecosystem.

Papillary and reticular fibroblasts generate distinct microenvironments that differentially impact angiogenesis.

Papillary and reticular dermis show distinct extracellular matrix (ECM) and vascularization corresponding to their specific functions. These characteristics are associated with gene expression patterns of fibroblasts freshly isolated from their native microenvironment. In order to assess the relevance of these fibroblast subpopulations in a tissue engineering context, we investigated their contribution to matrix production and vascularization using cell sheet culture conditions. We first performed RNA-seq differential expression analysis to determine whether several rounds of cell amplification and high-density culture affected their gene expression profile. Bioinformatics analysis revealed that expression of angiogenesis-related and matrisome gene signatures were maintained, resulting in papillary and reticular ECMs that differ in composition and structure. The impact of secreted or ECM-associated factors was then assessed using two independent 3D angiogenesis assays: -1/ a fibrin hydrogel-based assay allowing investigation of diffusible secreted factors, -2/ a scaffold-free cell-sheet based assay for investigation of fibroblast-produced microenvironment. These analyses revealed that papillary fibroblasts secrete highly angiogenic factors and produce a microenvironment characterised by ECM remodelling capacity and dense and branched microvascular network, whereas reticular fibroblasts produced more structural core components of the ECM associated with less branched and larger vessels. These features mimick the characteristics of both the ECM and the vasculature of dermis subcompartments. In addition to showing that skin fibroblast populations differentially regulate angiogenesis via both secreted and ECM factors, our work emphasizes the importance of papillary and reticular fibroblasts for engineering and modelling dermis microenvironment and vascularization. STATEMENT OF SIGNIFICANCE: Recent advances have brought to the forefront the central role of microenvironment and vascularization in tissue engineering for regenerative medicine and microtissue modelling. We have investigated the role of papillary and reticular fibroblast subpopulations using scaffold-free cell sheet culture. This approach provides differentiated cells conditions allowing the production of their own microenvironment. Analysis of gene expression profiles and characterisation of the matrix produced revealed strong and specific angiogenic properties that we functionally characterized using 3D angiogenesis models targeting the respective role of either secreted or matrix-bound factors. This study demonstrates the importance of cell-generated extracellular matrix and questions the importance of cell source and the relevance of hydrogels for developing physio-pathologically relevant tissue engineered substitutes.

In vitro adhesion, pilus expression, and in vivo amelioration of antibiotic-induced microbiota disturbance by Bifidobacterium spp. strains from fecal donors

ABSTRACT Fecal microbiota transplantation (FMT) is used routinely to treat recurrent Clostridioides difficile infection (rCDI) and investigated as a treatment for numerous conditions associated with gut microbiota alterations. Metagenomic analyses have indicated that recipient colonization by donor bacteria may be associated with favorable clinical outcomes. Bifidobacteria are abundant gut commensals associated with health. We have previously demonstrated that Bifidobacterium strains transferred in FMT can colonize recipients in long term, at least for a year, and recovered such strains by cultivation. This study addressed in vitro adhesion and pilus gene expression of long-term colonizing Bifidobacterium strains from FMT donors as well as in vivo colonization and capability to ameliorate antibiotic-induced microbiota disturbance. RNA-Seq differential gene expression analysis showed that the strongly adherent B. longum strains DY_pv11 and DX_pv23 expressed tight adherence and sortase-dependent pilus genes, respectively. Two B. longum strains, adherent DX_pv23 and poorly adhering DX_pv18, were selected to address in vivo colonization and efficacy to restore antibiotic-disturbed microbiota in C57BL/6 murine model. DX_pv23 colonized mice transiently with a rate comparable to that of the B. animalis BB-12 used as a reference. Although long-term colonization was not observed with any of the three strains, 16S rRNA gene profiling revealed that oral administration of DX_pv23 enhanced the recovery of antibiotic-disturbed microbiota to the original configuration significantly better than the other strains. The findings suggest that selected strains from FMT donors, such as DX_pv23 in this study, may have therapeutic potential by in vitro expression of colonization factors and boosting endogenous gut microbiota.

Discovering common pathogenic processes between COVID-19 and HFRS by integrating RNA-seq differential expression analysis with machine learning.

Zoonotic virus spillover in human hosts including outbreaks of Hantavirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) imposes a serious impact on the quality of life of patients. Recent studies provide a shred of evidence that patients with Hantavirus-caused hemorrhagic fever with renal syndrome (HFRS) are at risk of contracting SARS-CoV-2. Both RNA viruses shared a higher degree of clinical features similarity including dry cough, high fever, shortness of breath, and certain reported cases with multiple organ failure. However, there is currently no validated treatment option to tackle this global concern. This study is attributed to the identification of common genes and perturbed pathways by combining differential expression analysis with bioinformatics and machine learning approaches. Initially, the transcriptomic data of hantavirus-infected peripheral blood mononuclear cells (PBMCs) and SARS-CoV-2 infected PBMCs were analyzed through differential gene expression analysis for identification of common differentially expressed genes (DEGs). The functional annotation by enrichment analysis of common genes demonstrated immune and inflammatory response biological processes enriched by DEGs. The protein-protein interaction (PPI) network of DEGs was then constructed and six genes named RAD51, ALDH1A1, UBA52, CUL3, GADD45B, and CDKN1A were identified as the commonly dysregulated hub genes among HFRS and COVID-19. Later, the classification performance of these hub genes were evaluated using Random Forest (RF), Poisson Linear Discriminant Analysis (PLDA), Voom-based Nearest Shrunken Centroids (voomNSC), and Support Vector Machine (SVM) classifiers which demonstrated accuracy >70%, suggesting the biomarker potential of the hub genes. To our knowledge, this is the first study that unveiled biological processes and pathways commonly dysregulated in HFRS and COVID-19, which could be in the next future used for the design of personalized treatment to prevent the linked attacks of COVID-19 and HFRS.

Functional Annotation Routines Used by ABRF Bioinformatics Core Facilities - Observations, Comparisons, and Considerations.

The functional annotation of gene lists is a common analysis routine required for most genomics experiments, and bioinformatics core facilities must support these analyses. In contrast to methods such as the quantitation of RNA-Seq reads or differential expression analysis, our research group noted a lack of consensus in our preferred approaches to functional annotation. To investigate this observation, we selected 4 experiments that represent a range of experimental designs encountered by our cores and analyzed those data with 6 tools used by members of the Association of Biomolecular Resource Facilities (ABRF) Genomic Bioinformatics Research Group (GBIRG). To facilitate comparisons between tools, we focused on a single biological result for each experiment. These results were represented by a gene set, and we analyzed these gene sets with each tool considered in our study to map the result to the annotation categories presented by each tool. In most cases, each tool produces data that would facilitate identification of the selected biological result for each experiment. For the exceptions, Fisher's exact test parameters could be adjusted to detect the result. Because Fisher's exact test is used by many functional annotation tools, we investigated input parameters and demonstrate that, while background set size is unlikely to have a significant impact on the results, the numbers of differentially expressed genes in an annotation category and the total number of differentially expressed genes under consideration are both critical parameters that may need to be modified during analyses. In addition, we note that differences in the annotation categories tested by each tool, as well as the composition of those categories, can have a significant impact on results.

Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis

When profiling blood samples by RNA-sequencing (RNA-seq), RNA from haemoglobin (Hgb) can account for up to 70% of the transcriptome. Due to considerations of sequencing depth and power to detect biological variation, Hgb RNA is typically depleted prior to sequencing by hybridisation-based methods; an alternative approach is to deplete reads arising from Hgb RNA bioinformatically. In the present study, we compared the impact of these two approaches on the outcome of differential gene expression analysis performed using RNA-seq data from 58 human tuberculosis (TB) patient or contact whole blood samples–29 globin kit-depleted and 29 matched non-depleted—a subset of which were taken at TB diagnosis and at six months post-TB treatment from the same patient. Bioinformatic depletion of Hgb genes from the non-depleted samples (bioinformatic-depleted) substantially reduced library sizes (median = 57.24%) and fewer long non-coding, micro, small nuclear and small nucleolar RNAs were captured in these libraries. Profiling published TB gene signatures across all samples revealed inferior correlation between kit-depleted and bioinformatic-depleted pairs when the proportion of reads mapping to Hgb genes was higher in the non-depleted sample, particularly at the TB diagnosis time point. A set of putative “globin-fingerprint” genes were identified by directly comparing kit-depleted and bioinformatic-depleted samples at each timepoint. Two TB treatment response signatures were also shown to have decreased differential performance when comparing samples at TB diagnosis to six months post-TB treatment when profiled on the bioinformatic-depleted samples compared with their kit-depleted counterparts. These results demonstrate that failure to deplete Hgb RNA prior to sequencing has a negative impact on the sensitivity to detect disease-relevant gene expression changes even when bioinformatic removal is performed.

SlERF.J2 reduces chlorophyll accumulation and inhibits chloroplast biogenesis and development in tomato leaves

Chlorophyll metabolism and chloroplast biogenesis in tomato (Solanum lycopersicum) leaves contribute to photosynthesis; however, their molecular mechanisms are poorly understood. In this study, we found that overexpression of SlERF.J2 (ethylene transcription factor) resulted in a decrease in leaf chlorophyll content and reduced accumulation of starch and soluble sugar. The slerf.j2 knockout mutant showed no apparent change. Further observation of tissue sections and transmission electron microscopy (TEM) showed that SlERF.J2 was involved in chlorophyll accumulation and chloroplast formation. RNA-seq of mature SlERF.J2-OE leaves showed that many genes involved in chlorophyll biosynthesis and chloroplast formation were significantly downregulated compared with those in WT leaves. Genome global scanning of the ERF TF binding site combined with RNA-seq differential gene expression and qRT-PCR detection analysis showed that COP1 was a potential target gene of SlERF.J2. Tobacco transient expression technology, a dual-luciferase reporter system and Y1H technology were employed to verify that SlERF.J2 could bind to the COP1 promoter. Notably, overexpression of SlERF.J2 in Nr mutants resulted in impaired chloroplast biogenesis and development. Taken together, our findings demonstrated that SlERF.J2 plays an essential role in chlorophyll accumulation and chloroplast formation, laying a foundation for enhancing plant photosynthesis.

Transcriptional profiles of Streptococcus pneumoniae associated with adaptation to the nasopharynx environment

Streptococcus pneumoniae is a major cause of global morbidity and mortality. It behaves as a commensal in the host nasopharynx, but can become pathogenic, invading the lungs, blood, and meninges. As such, identification of pneumococcal virulence and colonisation factors remains a major research objective. We previously described an experimental evolution approach for the identification of pneumococcal genes that make niche-specific contributions to fitness and virulence. Sequential passage of pneumococci through mouse models of nasopharyngeal-carriage and pneumonia was performed, generating bacterial lineages adapted to the nasopharynx and lungs, respectively. Using RNA-Seq differential gene expression analysis, this study compared the transcriptomic profile of a nasopharynx-evolved pneumococcal lineage that showed evidence of enhanced nasopharyngeal colonisation potential, with a lab-adapted ancestor strain. Here, we describe how the genomic adaptations acquired by this lineage, and which we have demonstrated facilitate survival in the nasopharynx, can influence bacterial gene expression. One key finding was the identification of five adjacent upregulated genes, representing a putative pneumococcal operon. These poorly characterised genes are predicted to encode a carbohydrate-scavenging pathway. Expression of the operon within the nasopharynx may facilitate sugar acquisition from host glycoproteins. Of note, the nasopharynx evolved pneumococcal lineage carries a single nucleotide insertion mutation immediately adjacent to the -10 element of the operon predicted promotor sequence. This may contribute to increased operon gene expression in the nasopharynx-adapted pneumococcus, thereby enhancing colonisation potential. Confirmatory mechanistic investigations are underway, which will aid the identification of pneumococcal virulence factors involved in the commensal to pathogen switch.

Transcriptomic changes induced by applications of a commercial extract of Ascophyllum nodosum on tomato plants

Extracts of Ascophyllum nodosum are commonly used as commercial biostimulants in crop production. To further understand the seaweed extract-induced phenomena in plants, a transcriptomic study was conducted. RNA-seq differential gene expression analysis of tomato plants treated with a commercial A. nodosum extract formulation (Stimplex) revealed the up-regulation of 635 and down-regulation of 456 genes. Ontology enrichment analysis showed three gene categories were augmented, including biological processes, cellular components, and molecular functions. KEGG pathway analysis revealed that the extract had a strong influence on the expression of genes involved in carbon fixation, secondary metabolism, MAPK-signalling, plant hormone signal transduction, glutathione metabolism, phenylpropanoid and stilbenoid metabolism, and plant-pathogen interactions. qRT-PCR validation analysis using 15 genes established a strong correlation with the RNA sequencing results. The activities of defence enzymes were also significantly enhanced by seaweed extract treatment. Furthermore, AN-SWE treated tomato plants had significantly higher chlorophyll and growth hormone content and showed improved plant growth parameters and nutrient profiles than the control. It is postulated that seaweed extract-induced gene regulation was responsible for favourable plant responses that enabled better growth and tolerance to stress conditions. This study provides evidence at the transcriptomic level for the positive effects of foliar application of the Ascophyllum nodosum extract (Stimplex) observed in treated tomato plants.

IL32 overexpression is driven by DNA hypomethylation and contributes to an extracellular matrix (ECM) remodeling phenotype in EpCAM‐/CD49f‐enriched breast cancer cells

Basal‐like breast cancers typically correspond with increased enrichment of EpCAM‐/CD49f‐ cancer stem cells (CSC) and a propensity toward metastasis. However, the molecular mechanisms underlying these general characteristics are not well understood. To provide further insight concerning CSCs and their intrinsic metastatic mechanisms, we compared the 450K DNA methylation profile of EpCAM‐/CD49f‐ poor breast cancer cell lines to that of EpCAM‐/CD49f‐ enriched breast cancer cell lines. From our results, we were able to determine and highlight IL32 as a gene whose promoter is hypomethylated in EpCAM‐/CD49f‐ enriched cell lines. The hypomethylated IL32 promoter corresponded with increased IL32 expression in both cell lines and basal‐like breast cancer patients from The Cancer Genome Atlas (TCGA) database. Interestingly, increased IL32 expression preferentially occurred for the IL32‐beta transcript and corresponds with previous reports demonstrating that IL32‐beta is not secreted from the cell like other canonical interleukins and preferentially localizes to the mitochondria in breast cancer cells. Additionally, expression of the beta‐transcript could be suppressed when CSC‐enriched cells were treated with the BET‐bromodomain inhibitor JQ1. Because of this phenomenon, we sought to determine the effects of suppressing IL32 in the EpCAM‐/CD49f‐ enriched cell line SUM159PT via siRNA‐mediated knockdown and subsequent RNAseq differential expression analysis. From our results, we determined that transcripts involved in extracellular matrix (ECM) organization and collagen/integrin interaction were preferentially affected by IL32 silencing. Additionally, IL32 suppression decreased the invasiveness of SUM159PT based on an ECM‐matrix cell invasion assay. Collectively, our results reflect the notion that differential IL32 expression by promoter hypomethylation in breast CSCs plays a role in ECM remodeling for purposes of breast cancer cell invasion and metastasis.

The Role of the Two-Component QseBC Signaling System in Biofilm Formation and Virulence of Hypervirulent Klebsiella pneumoniae ATCC43816.

Hypervirulent Klebsiella pneumoniae (hvKP) is an evolving infectious pathogen associated with high mortality. The convergence of hypervirulence and multidrug resistance further challenges the clinical treatment options for K. pneumoniae infections. The QseBC two-component system (TCS) is a component of quorum-sensing regulatory cascade and functions as a global regulator of biofilm growth, bacterial motility, and virulence in Escherichia coli. However, the functional mechanisms of QseBC in hvKP have not been reported, and we aim to examine the role of QseBC in regulating virulence in hvKP strain ATCC43816. The CRISPR-Cas9 system was used to construct qseB, qseC, and qseBC knockout in ATCC43816. No significant alterations in the growth and antibiotic susceptibility were detected between wild-type and mutants. The deletion of qseC led to an increase of biofilm formation, resistance to serum killing, and high mortality in the G. mellonella model. RNAseq differential gene expression analysis exhibited that gene-associated biofilm formation (glgC, glgP, glgA, gcvA, bcsA, ydaM, paaF, ptsG), bacterial type VI secretion system (virB4, virB6, virB10, vgrG, hcp), and biosynthesis of siderophore (entC, entD, entE) were significantly upregulated in comparison with the wild-type control. In addition, qseB, ygiW (encode OB-family protein), and AraC family transcriptional regulator IT767_23090 genes showed highest expressions in the absence of QseC, which might be related to increased virulence. The study provided new insights into the functional importance of QseBC in regulating the virulence of hvKP.

Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis

RNA sequencing (RNA-seq) is a widely adopted affordable method for large scale gene expression profiling. However, user-friendly and versatile tools for wet-lab biologists to analyse RNA-seq data beyond standard analyses such as differential expression, are rare. Especially, the analysis of time-series data is difficult for wet-lab biologists lacking advanced computational training. Furthermore, most meta-analysis tools are tailored for model organisms and not easily adaptable to other species. With RNfuzzyApp, we provide a user-friendly, web-based R shiny app for differential expression analysis, as well as time-series analysis of RNA-seq data. RNfuzzyApp offers several methods for normalization and differential expression analysis of RNA-seq data, providing easy-to-use toolboxes, interactive plots and downloadable results. For time-series analysis, RNfuzzyApp presents the first web-based, fully automated pipeline for soft clustering with the Mfuzz R package, including methods to aid in cluster number selection, cluster overlap analysis, Mfuzz loop computations, as well as cluster enrichments. RNfuzzyApp is an intuitive, easy to use and interactive R shiny app for RNA-seq differential expression and time-series analysis, offering a rich selection of interactive plots, providing a quick overview of raw data and generating rapid analysis results. Furthermore, its assignment of orthologs, enrichment analysis, as well as ID conversion functions are accessible to non-model organisms.

Bone Marrow Biopsy T Cell Aggregates and Cytokine Transcriptional Signatures Predict Sustained Response to CAR T-Cell Therapy in B-ALL

BackgroundCAR T-cell therapies directed against CD19 (CAR19) are used to treat relapsed/refractory (R/R) B-acute lymphoblastic leukemia (B-ALL) and show high complete remission (CR) rates compared to salvage chemotherapy. However, subsets of patients do not respond or relapse after initial CR. While previous work has demonstrated the importance of CAR T cell immunophenotype and vector integration site in long term CAR19 responders, there are currently no clinically applicable predictors of response. Given the importance of the B-ALL tumor microenvironment in mediating chemoresistance, inflammatory signaling and recruitment of immune effectors to the leukemic bone marrow, we hypothesized that the pre-CAR19 infusion bone marrow biopsy immune microenvironment may predict CAR19 responses.MethodsPatients treated with CAR19 for R/R B-ALL from 2012-2017 were retrospectively identified. Marrow core biopsies were collected immediately prior to CAR19 infusion (pre-CAR) and at one month post-infusion (post-CAR). Bone marrow biopsy slides immunohistochemically stained for CD3 were digitally scanned, analyzed algorithmically for T-cell infiltration and assessed qualitatively for interstitial T cell aggregates of >5 cells (Leica Aperio ImageScope). B-ALL involvement was determined by bone marrow aspirate counts and minimal residual disease (MRD) flow cytometry. Targeted RNA sequencing-based gene expression profiling (EdgeSeq Immuno-Oncology Panel, HTG Diagnostics) was performed on pre- and post-treatment biopsies, with differential expression assessed by DESeq2 within HTG Reveal software, and further analyses conducted using Metascape.ResultsWe identified 143 bone marrow core biopsies (84 pre-treatment, 59 post-treatment) from 84 R/R B-ALL patients treated with CAR19. Pre-CAR B-ALL marrow involvement ranged from 0-95% (median: 67.5%), and the dataset included patients with relapses occurring between 1-33 months following CAR therapy (median: 6 months).Pre-CAR CD3+ T cell aggregates were significantly increased in CAR19 Sustained Responders (SR) compared to Non-Responders (NR) (92.3% versus 50%, p=0.007) and eventual relapses (CD19+: 40%, p= 0.002 and CD19-: 61.5%, p=0.019) (Figure 1A-B). A lack of T cell aggregates in pre-CAR marrow biopsies showed a sensitivity of 45.8% and a specificity of 92.3% in distinguishing NRs and eventual relapses from SRs. In one month post-CAR marrow biopsies, T cell aggregates continued to show higher frequency in SRs compared to eventual CD19+ relapses (100% versus 42.9%, p=0.007) and NRs (50%, p=0.04).Pre-CAR marrow T cell infiltration was also significantly greater in SRs compared to NRs (2146 CD3+ T cells per biopsy versus 850, p=0.038) and eventual CD19- relapses (1086, p=0.022), and trended toward a significant increase compared to eventual CD19+ relapses (1056, p=0.063) (Figure 1C). Pre-CAR marrow T cells of < 920 per biopsy showed a sensitivity of 45.8% and a specificity of 92.3% in distinguishing NRs and relapses from SRs (Figure 1D).RNAseq differential gene expression analysis of pre-CAR marrow biopsies revealed a chemokine axis of CXCL9, CXCL13, CXCR5, CXCL5, CXCL2 and CCL1 in SR that was deficient in patients with eventual relapse (Figure 1E). By contrast, NRs and eventual relapses showed a pre-CAR transcriptional signature reflecting Th2 (IL5RA, IL13) and Th17 (IL17A, IL23R) skewing, in addition to higher IL2, IFNG and IL6 transcripts.ConclusionThese immunohistochemical and transcriptional findings support a pivotal role for the peri-infusion bone marrow microenvironment in long-term responses to CAR19 therapy in B-ALL. A deficiency of marrow T cell aggregates and marrow-infiltrating T cells pre-CAR shows high specificity in distinguishing NRs and eventual relapses from SRs to CAR19, and marrow T cell aggregates are a persistent feature of SRs at one month post-CAR infusion. SR to CAR19 is also associated with elevated marrow expression of a suite of immune chemoattractants which may enhance the ability of infused CAR T cells and other effectors to infiltrate the B-ALL microenvironment. Combined assessment of bone marrow T cell infiltrates and transcriptional profiling could be used to improve the sensitivity and specificity of predictive algorithms for responses to CAR19 therapy. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.