A comparison of background correction methods for two-colour microarrays

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Behavioral and genetic correlates of heterogeneity in learning performance in individual honeybees, Apis mellifera

Learning an olfactory discrimination task leads to heterogeneous results in honeybees with some bees performing very well and others at low rates. Here we investigated this behavioral heterogeneity and asked whether it was associated with particular gene expression patterns in the bee's brain. Bees were individually conditioned using a sequential conditioning protocol involving several phases of olfactory learning and retention tests. A cumulative score was used to differentiate the tested bees into high and low performers. The rate of CS+ odor learning was found to correlate most strongly with a cumulative performance score extracted from all learning and retention tests. Microarray analysis of gene expression in the mushroom body area of the brains of these bees identified a number of differentially expressed genes between high and low performers. These genes are associated with diverse biological functions, such as neurotransmission, memory formation, cargo trafficking and development.

Exploring Imaging Genetic Markers of Alzheimer's Disease Based on a Novel Nonlinear Correlation Analysis Algorithm

Alzheimer's disease (AD) is an irreversible neurological disorder characterized by insidious onset. Identifying potential markers in its emergence and progression is crucial for early diagnosis and treatment. Imaging genetics typically merges genetic variables with multiple imaging parameters, employing various association analysis algorithms to investigate the links between pathological phenotypes and genetic variations, and to unearth molecular-level insights from brain images. However, most existing imaging genetics algorithms based on sparse learning assume a linear relationship between genetic factors and brain functions, limiting their ability to discern complex nonlinear correlation patterns and resulting in reduced accuracy. To address these issues, we propose a novel nonlinear imaging genetic association analysis method, Deep Self-Reconstruction-based Adaptive Sparse Multi-view Deep Generalized Canonical Correlation Analysis (DSR-AdaSMDGCCA). This approach facilitates joint learning of the nonlinear relationships between pathological phenotypes and genetic variations by integrating three different types of data: structural magnetic resonance imaging (sMRI), single-nucleotide polymorphism (SNP), and gene expression data. By incorporating nonlinear transformations in DGCCA, our model effectively uncovers nonlinear associations across multiple data types. Additionally, the DSR algorithm clusters samples with identical labels, incorporating label information into the nonlinear feature extraction process and thus enhancing the performance of association analysis. The application of the DSR-AdaSMDGCCA algorithm on real data sets identified several AD risk regions (such as the hippocampus, parahippocampus, and fusiform gyrus) and risk genes (including VSIG4, NEDD4L, and PINK1), achieving maximum classification accuracy with the fewest selected features compared to baseline algorithms. Molecular biology enrichment analysis revealed that the pathways enriched by these top genes are intimately linked to AD progression, affirming that our algorithm not only improves correlation analysis performance but also identifies biologically significant markers.

MYB24 orchestrates terpene and flavonol metabolism as light responses to anthocyanin depletion in variegated grape berries

Variegation is a rare type of mosaicism not fully studied in plants, especially fruits. We examined red and white sections of grape (Vitis vinifera cv. 'Béquignol') variegated berries and found that accumulation of products from branches of the phenylpropanoid and isoprenoid pathways showed an opposite tendency. Light-responsive flavonol and monoterpene levels increased in anthocyanin-depleted areas in correlation with increasing MYB24 expression. Cistrome analysis suggested that MYB24 binds to the promoters of 22 terpene synthase (TPS) genes, as well as 32 photosynthesis/light-related genes, including carotenoid pathway members, the flavonol regulator HY5 HOMOLOGUE (HYH), and other radiation response genes. Indeed, TPS35, TPS09, the carotenoid isomerase gene CRTISO2, and HYH were activated in the presence of MYB24 and MYC2. We suggest that MYB24 modulates ultraviolet and high-intensity visible light stress responses that include terpene and flavonol synthesis and potentially affects carotenoids. The MYB24 regulatory network is developmentally triggered after the onset of berry ripening, while the absence of anthocyanin sunscreens accelerates its activation, likely in a dose-dependent manner due to increased radiation exposure. Anthocyanins and flavonols in variegated berry skins act as effective sunscreens but for different wavelength ranges. The expression patterns of stress marker genes in red and white sections of 'Béquignol' berries strongly suggest that MYB24 promotes light stress amelioration but only partly succeeds during late ripening.

A link between energy metabolism and plant host adaptation states in the two-spotted spider mite, Tetranychus urticae (Koch)

Energy metabolism is a highly conserved process that balances generation of cellular energy and maintenance of redox homeostasis. It consists of five interconnected pathways: glycolysis, tricarboxylic acid cycle, pentose phosphate, trans-sulfuration, and NAD+ biosynthesis pathways. Environmental stress rewires cellular energy metabolism. Type-2 diabetes is a well-studied energy metabolism rewiring state in human pancreatic β-cells where glucose metabolism is uncoupled from insulin secretion. The two-spotted spider mite, Tetranychus urticae (Koch), exhibits a remarkable ability to adapt to environmental stress. Upon transfer to unfavourable plant hosts, mites experience extreme xenobiotic stress that dramatically affects their survivorship and fecundity. However, within 25 generations, mites adapt to the xenobiotic stress and restore their fitness. Mites' ability to withstand long-term xenobiotic stress raises a question of their energy metabolism states during host adaptation. Here, we compared the transcriptional responses of five energy metabolism pathways between host-adapted and non-adapted mites while using responses in human pancreatic islet donors to model these pathways under stress. We found that non-adapted mites and human pancreatic β-cells responded in a similar manner to host plant transfer and diabetogenic stress respectively, where redox homeostasis maintenance was favoured over energy generation. Remarkably, we found that upon host-adaptation, mite energy metabolic states were restored to normal. These findings suggest that genes involved in energy metabolism can serve as molecular markers for mite host-adaptation.

Exploring the Role of Different Cell-Death-Related Genes in Sepsis Diagnosis Using a Machine Learning Algorithm

Sepsis, a disease caused by severe infection, has a high mortality rate. At present, there is a lack of reliable algorithmic models for biomarker mining and diagnostic model construction for sepsis. Programmed cell death (PCD) has been shown to play a vital role in disease occurrence and progression, and different PCD-related genes have the potential to be targeted for the treatment of sepsis. In this paper, we analyzed PCD-related genes in sepsis. Implicated PCD processes include apoptosis, necroptosis, ferroptosis, pyroptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, and alkaliptosis. We screened for diagnostic-related genes and constructed models for diagnosing sepsis using multiple machine-learning models. In addition, the immune landscape of sepsis was analyzed based on the diagnosis-related genes that were obtained. In this paper, 10 diagnosis-related genes were screened for using machine learning algorithms, and diagnostic models were constructed. The diagnostic model was validated in the internal and external test sets, and the Area Under Curve (AUC) reached 0.7951 in the internal test set and 0.9627 in the external test set. Furthermore, we verified the diagnostic gene via a qPCR experiment. The diagnostic-related genes and diagnostic genes obtained in this paper can be utilized as a reference for clinical sepsis diagnosis. The results of this study can act as a reference for the clinical diagnosis of sepsis and for target discovery for potential therapeutic drugs.

Leucocyte-derived micro-RNAs as candidate biomarkers in Brugada syndrome

AIMS

Risk stratification for sudden cardiac death in patients with Brugada syndrome remains a major challenge. Contemporary risk prediction models have only modest predictive value. The aim of this study was to assess the role of micro-RNAs from peripheral blood as candidate biomarkers in Brugada syndrome.

METHODS AND RESULTS

In this prospective study, Brugada patients and unaffected control individuals were enrolled for analysis of leucocyte-derived microRNAs (miRNAs) levels. Expression levels of 798 different circulating miRNAs were analysed on the NanoString® nCounter platform. All results were cross-validated by using a quantitative polymerase chain reaction. Micro-RNA expression levels of Brugada patients were compared with clinical data. A total of 21 definite Brugada patients (38% with a history of ventricular arrhythmia or cardiac arrest) and 30 unaffected control individuals were included in the study. Micro-RNA analysis showed a distinct expression profile in Brugada patients with 42 differentially expressed markers (38 up-regulated, 4 down-regulated miRNAs). The symptom status of Brugada patients was associated with a distinct miRNA signature. Micro-RNAs 145-5p and 585-3p were significantly up-regulated in symptomatic Brugada patients (P = 0.04). Incorporating miRNAs 145-5p and 585-3p into a multivariable model demonstrated significantly increased symptom prediction (area under the curve = 0.96; 95% confidence interval: 0.88-1.00).

CONCLUSION

Brugada patients display a distinct miRNA expression profile compared with unaffected control individuals. There is also evidence that certain miRNAs (miR-145-5p and miR-585-3p) are associated with the symptom status of Brugada patients. The results suggest the principal utility of leucocyte-derived miRNAs as prognostic biomarkers for Brugada syndrome.

Microarray analysis of hub genes, non-coding RNAs and pathways in lung after whole body irradiation in a mouse model

PURPOSE

Previous research has highlighted the impact of radiation damage, with cancer patients developing acute disorders including radiation induced pneumonitis or chronic disorders including pulmonary fibrosis months after radiation therapy ends. We sought to discover biomarkers that predict these injuries and develop treatments that mitigate this damage and improve quality of life.

MATERIALS AND METHODS

Six- to eight-week-old female C57BL/6 mice received 1, 2, 4, 8, 12 Gy or sham whole body irradiation. Animals were euthanized 48 h post exposure and lungs removed, snap frozen and underwent RNA isolation. Microarray analysis was performed to determine dysregulation of messenger RNA (mRNA), microRNA (miRNA), and long non-coding RNA (lncRNA) after radiation injury.

RESULTS

We observed sustained dysregulation of specific RNA markers including: mRNAs, lncRNAs, and miRNAs across all doses. We also identified significantly upregulated genes that can indicate high dose exposure, including Cpt1c, Pdk4, Gdf15, and Eda2r, which are markers of senescence and fibrosis. Only three miRNAs were significantly dysregulated across all radiation doses: miRNA-142-3p and miRNA-142-5p were downregulated and miRNA-34a-5p was upregulated. IPA analysis predicted inhibition of several molecular pathways with increasing doses of radiation, including: T cell development, Quantity of leukocytes, Quantity of lymphocytes, and Cell viability.

CONCLUSIONS

These RNA biomarkers might be highly relevant in the development of treatments and in predicting normal tissue injury in patients undergoing radiation treatment. We are conducting further experiments in our laboratory, which includes a human lung-on-a-chip model, to develop a decision tree model using RNA biomarkers.

Methodology to identify a gene expression signature by merging microarray datasets

A vast number of microarray datasets have been produced as a way to identify differentially expressed genes and gene expression signatures. A better understanding of these biological processes can help in the diagnosis and prognosis of diseases, as well as in the therapeutic response to drugs. However, most of the available datasets are composed of a reduced number of samples, leading to low statistical, predictive and generalization power. One way to overcome this problem is by merging several microarray datasets into a single dataset, which is typically a challenging task. Statistical methods or supervised machine learning algorithms are usually used to determine gene expression signatures. Nevertheless, statistical methods require an arbitrary threshold to be defined, and supervised machine learning methods can be ineffective when applied to high-dimensional datasets like microarrays. We propose a methodology to identify gene expression signatures by merging microarray datasets. This methodology uses statistical methods to obtain several sets of differentially expressed genes and uses supervised machine learning algorithms to select the gene expression signature. This methodology was validated using two distinct research applications: one using heart failure and the other using autism spectrum disorder microarray datasets. For the first, we obtained a gene expression signature composed of 117 genes, with a classification accuracy of approximately 98%. For the second use case, we obtained a gene expression signature composed of 79 genes, with a classification accuracy of approximately 82%. This methodology was implemented in R language and is available, under the MIT licence, at https://github.com/bioinformatics-ua/MicroGES.

Differentially deregulated microRNAs contribute to ultraviolet radiation-induced photocarcinogenesis through immunomodulation: An-analysis of microRNAs expression profiling

MicroRNAs (miRNAs) are short non-coding RNA molecules (18-25 nucleotides) that regulate several fundamental biological processes. Emerging evidence has shown more than 1500 miRNAs functions in the cell cycle, proliferation, apoptosis, oxidative stress, immune response, DNA damage, and epigenetics alterations. miRNAs are bidirectionally in nature and act as a tumor suppressor and as an oncogene through crosstalk between tumor cells and immune cells. Although the roles of miRNAs in several cancers are well studied, little is known about ultraviolet B (UVB) radiation-induced skin cancer. Here, we performed a comprehensive screening of 1281 miRNAs in tumor tissues and compared their expression with normal skin. Our results demonstrate that the expression levels of 587 miRNAs were altered in tumor tissues compared to their expression in normal skin. The expression of 337 miRNAs was upregulated from 1.5-12 folds, while the expression of 250 miRNAs was downregulated up to 1.5-10 folds in tumors. Further, intraperitoneal injection of a mimic of down-regulated miR-15b (30nM) and an inhibitor of upregulated miR-133a (20nM) protect UVB-induced suppression of contact hypersensitivity (CHS) response. In conclusion, we identified a network of altered miRNAs in tumors that can serve as prognostic biomarkers and therapeutic targets to manage photocarcinogenesis effectively.

Overnight Corticosterone and Gene Expression in Mouse Hippocampus: Time Course during Resting Period

The aim of the experiment was to test the effect of an elevated level of glucocorticoids on the mouse hippocampal transcriptome after 12 h of treatment with corticosterone that was administered during an active phase of the circadian cycle. Additionally, we also tested the circadian changes in gene expression and the decay time of transcriptomic response to corticosterone. Gene expression was analyzed using microarrays. Obtained results show that transcriptomic responses to glucocorticoids are heterogeneous in terms of the decay time with some genes displaying persistent changes in expression during 9 h of rest. We have also found a considerable overlap between genes regulated by corticosterone and genes implicated previously in stress response. The examples of such genes are Acer2, Agt, Apod, Aqp4, Etnppl, Fabp7, Fam107a, Fjx1, Fmo2, Galnt15, Gjc2, Heph, Hes5, Htra1, Jdp2, Kif5a, Lfng, Lrg1, Mgp, Mt1, Pglyrp1, Pla2g3, Plin4, Pllp, Ptgds, Ptn, Slc2a1, Slco1c1, Sult1a1, Thbd and Txnip. This indicates that the applied model is a useful tool for the investigation of mechanisms underlying the stress response.

Pathway and Network Analyses Identify Growth Factor Signaling and MMP9 as Potential Mediators of Mitochondrial Dysfunction in Severe COVID-19

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Blood transcriptome responses in patients correlate with severity of COVID-19 disease

Background

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state.

Aim

Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants.

Results

All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways.

Conclusions

Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

Humoral Immune Response Profile of COVID-19 Reveals Severity and Variant-Specific Epitopes: Lessons from SARS-CoV-2 Peptide Microarray

The amaranthine scale of the COVID-19 pandemic and unpredictable disease severity is of grave concern. Serological diagnostic aids are an excellent choice for clinicians for rapid and easy prognosis of the disease. To this end, we studied the humoral immune response to SARS-CoV-2 infection to map immunogenic regions in the SARS-CoV-2 proteome at amino acid resolution using a high-density SARS-CoV-2 proteome peptide microarray. The microarray has 4932 overlapping peptides printed in duplicates spanning the entire SARS-CoV-2 proteome. We found 204 and 676 immunogenic peptides against IgA and IgG, corresponding to 137 and 412 IgA and IgG epitopes, respectively. Of these, 6 and 307 epitopes could discriminate between disease severity. The emergence of variants has added to the complexity of the disease. Using the mutation panel available, we could detect 5 and 10 immunogenic peptides against IgA and IgG with mutations belonging to SAR-CoV-2 variants. The study revealed severity-based epitopes that could be presented as potential prognostic serological markers. Further, the mutant epitope immunogenicity could indicate the putative use of these markers for diagnosing variants responsible for the infection.

Microarray analysis identifies coding and non-coding RNA markers of liver injury in whole body irradiated mice

Radiation injury from medical, accidental, or intentional sources can induce acute and long-term hepatic dysregulation, fibrosis, and cancer. This long-term hepatic dysregulation decreases quality of life and may lead to death. Our goal in this study is to determine acute changes in biological pathways and discover potential RNA biomarkers predictive of radiation injury. We performed whole transcriptome microarray analysis of mouse liver tissue (C57BL/6 J) 48 h after whole-body irradiation with 1, 2, 4, 8, and 12 Gray to identify significant expression changes in mRNAs, lncRNAs, and miRNAs, We also validated changes in specific RNAs through qRT-PCR. We used Ingenuity Pathway Analysis (IPA) to identify pathways associated with gene expression changes. We observed significant dysregulation of multiple mRNAs across all doses. In contrast, miRNA dysregulation was observed upwards of 2 Gray. The most significantly upregulated mRNAs function as tumor suppressors: Cdkn1a, Phlda3, and Eda2r. The most significantly downregulated mRNAs were involved in hemoglobin synthesis, inflammation, and mitochondrial function including multiple members of Hbb and Hba. The most significantly upregulated miRNA included: miR-34a-5p, miR-3102-5p, and miR-3960, while miR-342-3p, miR-142a-3p, and miR-223-3p were most significantly downregulated. IPA predicted activation of cell cycle checkpoint control pathways and inhibition of pathways relevant to inflammation and erythropoietin. Clarifying expression of mRNA, miRNA and lncRNA at a short time point (48 h) offers insight into potential biomarkers, including radiation markers shared across organs and animal models. This information, once validated in human models, can aid in development of bio-dosimetry biomarkers, and furthers our understanding of acute pathway dysregulation.

A comprehensive analysis of mRNA expression profiles of Esophageal Squamous Cell Carcinoma reveals downregulation of Desmoglein 1 and crucial genomic targets

AIM

Esophageal Squamous Cell Carcinoma (ESCC) is a histological subtype of esophageal cancer that begins in the squamous cells in the esophagus. In only 19% of the ESCC-diagnosed patients, a five-year survival rate has been seen. This necessitates the identification of high-confidence biomarkers for early diagnosis, prognosis, and potential therapeutic targets for the mitigation of ESCC.

METHOD

We performed a meta-analysis of 10 mRNA datasets and identified consistently perturbed genes across the studies. Then, integrated with ESCC ATLAS to segregate 'core' genes to identify consequences of primary gene perturbation events leading to gene-gene interactions and dysregulated molecular signaling pathways. Further, by integrating with toxicogenomics data, inferences were drawn for gene interaction with environmental exposures, trace elements, chemical carcinogens, and drug chemicals. We also deduce the clinical outcomes of candidate genes based on survival analysis using the ESCC related dataset in The Cancer Genome Atlas.

RESULT

We identified 237 known and 18 novel perturbed candidate genes. Desmoglein 1 (DSG1) is one such gene that we found significantly downregulated (Fold Change =-1.89, p-value = 8.2e-06) in ESCC across six different datasets. Further, we identified 31 'core' genes (that either harbor genetic variants or are regulated by epigenetic modifications) and found regulating key biological pathways via adjoining genes in gene-gene interaction networks. Functional enrichment analysis showed dysregulated biological processes and pathways including "Extracellular matrix", "Collagen trimmer" and "HPV infection" are significantly overrepresented in our candidate genes. Based on the toxicogenomic inferences from Comparative Toxicogenomics Database we report the key genes that interacted with risk factors such as tobacco smoking, zinc, nitroso benzylmethylamine, and drug chemicals such as cisplatin, Fluorouracil, and Mitomycin in relation to ESCC. We also point to the STC2 gene that shows a high risk for mortality in ESCC patients.

CONCLUSION

We identified novel perturbed genes in relation to ESCC and explored their interaction network. DSG1 is one such gene, its association with microbiota and a clinical presentation seen commonly with ESCC hints that it is a good candidate for early diagnostic marker. Besides, in this study we highlight candidate genes and their molecular connections to risk factors, biological pathways, drug chemicals, and the survival probability of ESCC patients.

DNA methylation in human gastric epithelial cells defines regional identity without restricting lineage plasticity

BACKGROUND

Epigenetic modifications in mammalian DNA are commonly manifested by DNA methylation. In the stomach, altered DNA methylation patterns have been observed following chronic Helicobacter pylori infections and in gastric cancer. In the context of epigenetic regulation, the regional nature of the stomach has been rarely considered in detail.

RESULTS

Here, we establish gastric mucosa derived primary cell cultures as a reliable source of native human epithelium. We describe the DNA methylation landscape across the phenotypically different regions of the healthy human stomach, i.e., antrum, corpus, fundus together with the corresponding transcriptomes. We show that stable regional DNA methylation differences translate to a limited extent into regulation of the transcriptomic phenotype, indicating a largely permissive epigenetic regulation. We identify a small number of transcription factors with novel region-specific activity and likely epigenetic impact in the stomach, including GATA4, IRX5, IRX2, PDX1 and CDX2. Detailed analysis of the Wnt pathway reveals differential regulation along the craniocaudal axis, which involves non-canonical Wnt signaling in determining cell fate in the proximal stomach. By extending our analysis to pre-neoplastic lesions and gastric cancers, we conclude that epigenetic dysregulation characterizes intestinal metaplasia as a founding basis for functional changes in gastric cancer. We present insights into the dynamics of DNA methylation across anatomical regions of the healthy stomach and patterns of its change in disease. Finally, our study provides a well-defined resource of regional stomach transcription and epigenetics.

SH3BP2 Silencing Increases miRNAs Targeting ETV1 and Microphthalmia-Associated Transcription Factor, Decreasing the Proliferation of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Gain of function in receptor tyrosine kinases type III, KIT, or PDGFRA drives the majority of GIST. Previously, our group reported that silencing of the adaptor molecule SH3 Binding Protein 2 (SH3BP2) downregulated KIT and PDGFRA and microphthalmia-associated transcription factor (MITF) levels and reduced tumor growth. This study shows that SH3BP2 silencing also decreases levels of ETV1, a required factor for GIST growth. To dissect the SH3BP2 pathway in GIST cells, we performed a miRNA array in SH3BP2-silenced GIST cell lines. Among the most up-regulated miRNAs, we found miR-1246 and miR-5100 to be predicted to target MITF and ETV1. Overexpression of these miRNAs led to a decrease in MITF and ETV1 levels. In this context, cell viability and cell cycle progression were affected, and a reduction in BCL2 and CDK2 was observed. Interestingly, overexpression of MITF enhanced cell proliferation and significantly rescued the viability of miRNA-transduced cells. Altogether, the KIT-SH3BP2-MITF/ETV1 pathway deserves to be considered in GIST cell survival and proliferation.

Smaller p-values in genomics studies using distilled auxiliary information

Medical research institutions have generated massive amounts of biological data by genetically profiling hundreds of cancer cell lines. In parallel, academic biology labs have conducted genetic screens on small numbers of cancer cell lines under custom experimental conditions. In order to share information between these two approaches to scientific discovery, this article proposes a "frequentist assisted by Bayes" (FAB) procedure for hypothesis testing that allows auxiliary information from massive genomics datasets to increase the power of hypothesis tests in specialized studies. The exchange of information takes place through a novel probability model for multimodal genomics data, which distills auxiliary information pertaining to cancer cell lines and genes across a wide variety of experimental contexts. If the relevance of the auxiliary information to a given study is high, then the resulting FAB tests can be more powerful than the corresponding classical tests. If the relevance is low, then the FAB tests yield as many discoveries as the classical tests. Simulations and practical investigations demonstrate that the FAB testing procedure can increase the number of effects discovered in genomics studies while still maintaining strict control of type I error and false discovery rate.

Pro-MAP: a robust pipeline for the pre-processing of single channel protein microarray data

BACKGROUND

The central role of proteins in diseases has made them increasingly attractive as therapeutic targets and indicators of cellular processes. Protein microarrays are emerging as an important means of characterising protein activity. Their accurate downstream analysis to produce biologically significant conclusions is largely dependent on proper pre-processing of extracted signal intensities. However, existing computational tools are not specifically tailored to the nature of these data and lack unanimity.

RESULTS

Here, we present the single-channel Protein Microarray Analysis Pipeline, a tailored computational tool for analysis of single-channel protein microarrays enabling biomarker identification, implemented in R, and as an interactive web application. We compared four existing background correction and normalization methods as well as three array filtering techniques, applied to four real datasets with two microarray designs, extracted using two software programs. The normexp, cyclic loess, and array weighting methods were most effective for background correction, normalization, and filtering respectively.

CONCLUSIONS

Thus, here we provided a versatile and effective pre-processing and differential analysis workflow for single-channel protein microarray data in form of an R script and web application ( https://metaomics.uct.ac.za/shinyapps/Pro-MAP/ .) for those not well versed in the R programming language.

Symptomatic and asymptomatic domoic acid exposure in zebrafish (Danio rerio) revealed distinct non-overlapping gene expression patterns in the brain

Domoic acid (DA) is a naturally produced neurotoxin synthesized by marine diatoms in the genus Pseudo-nitzschia. DA accumulates in filter-feeders such as shellfish, and can cause severe neurotoxicity when contaminated seafood is ingested, resulting in Amnesic Shellfish Poisoning (ASP) in humans. Overt clinical signs of neurotoxicity include seizures and disorientation. ASP is a significant public health concern, and though seafood regulations have effectively minimized the human risk of severe acute DA poisoning, the effects of exposure at asymptomatic levels are poorly understood. The objective of this study was to determine the effects of exposure to symptomatic and asymptomatic doses of DA on gene expression patterns in the zebrafish brain. We exposed adult zebrafish to either a symptomatic (1.1 ± 0.2 μg DA/g fish) or an asymptomatic (0.31 ± 0.03 µg DA/g fish) dose of DA by intracelomic injection and sampled at 24, 48 and 168 h post-injection. Transcriptional profiling was done using Agilent and Affymetrix microarrays. Our analysis revealed distinct, non-overlapping changes in gene expression between the two doses. We found that the majority of transcriptional changes were observed at 24 h post-injection with both doses. Interestingly, asymptomatic exposure produced more persistent transcriptional effects - in response to symptomatic dose exposure, we observed only one differentially expressed gene one week after exposure, compared to 26 in the asymptomatic dose at the same time (FDR <0.05). GO term analysis revealed that symptomatic DA exposure affected genes associated with peptidyl proline modification and retinoic acid metabolism. Asymptomatic exposure caused differential expression of genes that were associated with GO terms including circadian rhythms and visual system, and also the neuroactive ligand-receptor signaling KEGG pathway. Overall, these results suggest that transcriptional responses are specific to the DA dose and that asymptomatic exposure can cause long-term changes. Further studies are needed to characterize the potential downstream neurobehavioral impacts of DA exposure.

Biochemical and genomic identification of novel biomarkers in progressive sarcoidosis: HBEGF, eNAMPT, and ANG-2

Background

Progressive pulmonary fibrosis is a serious complication in subjects with sarcoidosis. The absence of reliable, non-invasive biomarkers that detect early progression exacerbates the difficulty in predicting sarcoidosis severity. To potentially address this unmet need, we evaluated a panel of markers for an association with sarcoidosis progression (HBEGF, NAMPT, IL1-RA, IL-6, IL-8, ANG-2). This panel encompasses proteins related to inflammation, vascular injury, cell proliferation, and fibroblast mitogenesis processes.

Methods

Plasma biomarker levels and biomarker protein expression in lung and lymph nodes tissues (immunohistochemical studies) from sarcoidosis subjects with limited disease and progressive (complicated) sarcoidosis were performed. Gene expression of the protein-coding genes included in this panel was analyzed using RNAseq in sarcoidosis granulomatous tissues from lung and lymph nodes.

Results

Except for IL-8, plasma levels of each biomarker—eNAMPT, IL-1RA, IL-6, ANG-2, and HBEGF—were significantly elevated in sarcoidosis subjects compared to controls. In addition, plasma levels of HBEGF were elevated in complicated sarcoidosis, while eNAMPT and ANG-2 were observed to serve as markers of lung fibrosis in a subgroup of complicated sarcoidosis. Genomic studies corroborated HBEGF and NAMPT among the top dysregulated genes and identified cytokine-related and fibrotic pathways in lung granulomatous tissues from sarcoidosis.

Conclusion

These findings suggest HBEGF, eNAMPT, and ANG-2 may serve as potential novel indicators of the clinical severity of sarcoidosis disease.

Potential genetic robustness of Prnp and Sprn double knockout mouse embryos towards ShRNA-lentiviral inoculation

The Shadoo and PrP prion protein family members are thought to be functionally related, but previous knockdown/knockout experiments in early mouse embryogenesis have provided seemingly contradictory results. In particular, Shadoo was found to be indispensable in the absence of PrP in knockdown analyses, but a double-knockout of the two had little phenotypic impact. We investigated this apparent discrepancy by comparing transcriptomes of WT, Prnp^0/0 and Prnp^0/0Sprn^0/0 E6.5 mouse embryos following inoculation by Sprn- or Prnp-ShRNA lentiviral vectors. Our results suggest the possibility of genetic adaptation in Prnp^0/0Sprn^0/0 mice, thus providing a potential explanation for their previously observed resilience.

Efficacy, T cell activation and antibody responses in accelerated Plasmodium falciparum sporozoite chemoprophylaxis vaccine regimens

Repeated direct venous inoculation of Plasmodium falciparum sporozoites (PfSPZ) together with antimalarial chemoprophylaxis (PfSPZ-CVac) is the most potent way to induce sterile immunity against P. falciparum infection in malaria-naive volunteers. However, established schedules are complex and long. Here, we tested two accelerated three-dose schedules (28- and 10-day regimen) assessing efficacy by controlled human malaria infection (CHMI) against placebo, comparing vaccine-specific T cell and antibody responses by antigen-reactive T cell enrichment (ARTE) and protein microarray, respectively. Both regimens were similarly efficacious (67 and 63% vaccine efficacy) but different in the induction of vaccine-specific T cells and antibodies. The 10-day regimen resulted in higher numbers of antigen-specific CD4+ effector memory pro-inflammatory T cells and a broader antibody response compared with the 28-day regimen. Usually in nature, P. falciparum liver stage lasts about 6.5 days. The short vaccination-interval of the 10-day regimen prolongs the time of continuous exposure to liver-stage parasites, which may explain the stronger response. Besides dose and number of vaccinations, duration of liver-stage exposure is a factor to optimize PfSPZ-CVac immunogenicity.

Regorafenib Reverses Temozolomide-Induced CXCL12/CXCR4 Signaling and Triggers Apoptosis Mechanism in Glioblastoma

Temozolomide (TMZ) monotherapy is known to be insufficient for resistant/relapsed glioblastoma (GBM), thus seeking a sensitization agent for TMZ is necessary. It was found that regorafenib may improve the overall survival of relapsed GBM patients. We aimed to discover whether regorafenib can enhance the anti-GBM effects of TMZ, and elucidate underlying mechanism. Our analysis of The Cancer Genome Atlas database revealed that the increased expression of CXCR4 is linked to poor survival of GBM patients. Additionally, TMZ treatment may trigger CXCR4/CXCL12 axis of GBM. We used two GBM cell lines, two primary GBM cells, and animal model to identify underlying mechanism and treatment efficacy of regorafenib combined with TMZ by cytotoxicity, apoptosis, reporter gene and invasion/migration assays, chemokine array, Western blotting, MRI, microarray, and immunohistochemistry. We observed that the chemokine CXCL-12 and its receptor CXCR4 regulate the resistance to TMZ, whereas the inhibition of CXCL-12/CXCR4 signaling sensitizes GBM cells to TMZ. The TMZ-induced CXCL-12/CXCR4 signaling, phosphor-extracellular signal-regulated kinases 1 and 2 (ERK1/2) and nuclear factor kappa light chain enhancer of activated B cells (NF-κB), and NF-κB-related proteins can effectively diminish when combining with regorafenib. Regorafenib significantly enhanced the TMZ-induced extrinsic/intrinsic apoptotic pathways, and facilitated the suppression of invasion and migration potential in GBM. Orthotopic tumor experiments demonstrated tumor size reduction and prolonged survival in combination group even with half-dose of TMZ. Our findings provide promising evidence that regorafenib may sensitize GBM to TMZ treatment through inhibition of the CXCL12/CXCR4/ERK/NF-κB signaling.

Bima A, Almukadi H, Ibrahim Kutbi H, Jayasheela Shetty P, Ahmad Shaik N, Banaganapalli B. Identifying Significant Genes and Functionally Enriched Pathways in Familial Hypercholesterolemia Using Integrated Gene Co-Expression Network Analysis

Familial hypercholesterolemia (FH) is a monogenic lipid disorder which promotes atherosclerosis and cardiovascular diseases. Owing to the lack of sufficient published information, this study aims to identify the potential genetic biomarkers for FH by studying the global gene expression profile of blood cells. The microarray expression data of FH patients and controls was analyzed by different computational biology methods like differential expression analysis, protein network mapping, hub gene identification, functional enrichment of biological pathways, and immune cell restriction analysis. Our results showed the dysregulated expression of 115 genes connected to lipid homeostasis, immune responses, cell adhesion molecules, canonical Wnt signaling, mucin type O-glycan biosynthesis pathways in FH patients. The findings from expanded protein interaction network construction with known FH genes and subsequent Gene Ontology (GO) annotations have also supported the above findings, in addition to identifying the involvement of dysregulated thyroid hormone and ErbB signaling pathways in FH patients. The genes like CSNK1A1, JAK3, PLCG2, RALA, and ZEB2 were found to be enriched under all GO annotation categories. The subsequent phenotype ontology results have revealed JAK3I, PLCG2, and ZEB2 as key hub genes contributing to the inflammation underlying cardiovascular and immune response related phenotypes. Immune cell restriction findings show that above three genes are highly expressed by T-follicular helper CD4⁺ T cells, naïve B cells, and monocytes, respectively. These findings not only provide a theoretical basis to understand the role of immune dysregulations underlying the atherosclerosis among FH patients but may also pave the way to develop genomic medicine for cardiovascular diseases.

Autoantibodies against cytoskeletons and lysosomal trafficking discriminate sarcoidosis from healthy controls, tuberculosis and lung cancers

Sarcoidosis is a systemic granulomatous disease of unknown etiology. Hypergammaglobulinemia and the presence of autoantibodies in sarcoidosis suggest active humoral immunity to unknown antigen(s). We developed a complex cDNA library derived from tissues of sarcoidosis patients. Using a high throughput method, we constructed a microarray platform from this cDNA library containing large numbers of sarcoidosis clones. After selective biopanning, 1070 sarcoidosis-specifc clones were arrayed and immunoscreend with 152 sera from patients with sarcoidosis and other pulmonary diseases. To identify the sarcoidosis classifiers two statistical approaches were conducted: First, we identified significant biomarkers between sarcoidosis and healthy controls, and second identified markers comparing sarcoidosis to all other groups. At the threshold of an False Discovery Rate (FDR) < 0.01, we identified 14 clones in the first approach and 12 clones in the second approach discriminating sarcoidosis from other groups. We used the classifiers to build a naïve Bayes model on the training-set and validated it on an independent test-set. The first approach yielded an AUC of 0.947 using 14 significant clones with a sensitivity of 0.93 and specificity of 0.88, whereas the AUC of the second option was 0.92 with a sensitivity of 0.96 and specificity of 0.83. These results suggest robust classifier performance. Furthermore, we characterized the informative phage clones by sequencing and homology searches. Large numbers of classifier-clones were peptides involved in cellular trafficking and cytoskeletons. These results show that sarcoidosis is associated with a specific pattern of immunoreactivity that can discriminate it from other diseases.

Analysis of Microarray Data from Medulloblastoma Tissue Samples

As a laboratory tool, microarray is used to detect the expression of thousands of genes at the same time. Typically, microscope slides have DNA microarrays that are printed with thousands of tiny spots in specified positions. Each spot contains a known DNA sequence or gene. These slides are commonly referred to as gene chips or DNA chips. The DNA molecules printed to each slide serve as probes to detect gene expression, which is also known as the transcriptome or the set of messenger RNA (mRNA) transcripts expressed by a group of genes. The goal of this chapter is to discuss the steps involved computational analysis of data after the completion of a typical microarray experiment.

Diverse Effect of Two Cytokinins, Kinetin and Benzyladenine, on Plant Development, Biotic Stress Tolerance, and Gene Expression

The plant hormones cytokinins affect a various array of plant growth and development processes as well as responses to biotic and abiotic stresses. In this study, the opposite effect of two different cytokinins kinetin (N⁶-furfuryladenine) and benzyladenine (BA) on development and on the tolerance of Arabidopsis and tobacco plants to virus, bacteria, and fungi infection was reported. Treatments of Arabidopsis and tobacco seedlings with saturated solutions of BA inhibited plant progress, while treatments with saturated water solution of kinetin promoted plant development. Furthermore, BA pre-treatments strongly reduced the number of TMV (Tobacco mosaic virus) lesions on tobacco and the tissue damage caused by the incompatible Pseudomonas bacteria on Arabidopsis and tobacco leaves. Similarly, BA pre-treatment significantly reduced the necrotic disease symptoms of Botrytis cinerea infection. Kinetin pre-treatments had a much weaker or no protective effect on the damage caused by the above pathogens. Accordingly, Arabidopsis gene expression profiles after treatments also showed that the two cytokinins have different effects on several plant processes. The gene expression results supported the more robust effect of BA, which up and downregulated more than 2000 genes, while only 436 genes were influenced by kinetin treatment. It is noteworthy that BA and kinetin treatment changed gene expressions in the same direction only in a relatively few cases (73 upregulated and 70 downregulated genes), and even 28 genes were regulated into the opposite directions by BA and kinetin. Both treatments had a strong effect on auxin and gibberellin-related genes, but only BA had a significant effect on cytokinin-induced processes. While kinetin exclusively activated the flavonoid synthesis genes, BA affected more significantly protein synthesis, photosynthesis, and plant defence-related genes. In conclusion, BA solution had sometimes the opposite and generally a much stronger effect than kinetin solution not only on the development and on biotic stress tolerance of tobacco and Arabidopsis plants but also on the gene expressions. The stronger protective effect of BA to necrotic stresses is probably due to its stronger senescence inhibitory effect on plant tissues, as supported by the stronger chlorophyll retardation of the BA-treated leaves.

The ENmix DNA methylation analysis pipeline for Illumina BeadChip and comparisons with seven other preprocessing pipelines

Background

Illumina DNA methylation arrays are high-throughput platforms for cost-effective genome-wide profiling of individual CpGs. Experimental and technical factors introduce appreciable measurement variation, some of which can be mitigated by careful “preprocessing” of raw data.

Methods

Here we describe the ENmix preprocessing pipeline and compare it to a set of seven published alternative pipelines (ChAMP, Illumina, SWAN, Funnorm, Noob, wateRmelon, and RnBeads). We use two large sets of duplicate sample measurements with 450 K and EPIC arrays, along with mixtures of isogenic methylated and unmethylated cell line DNA to compare raw data and that preprocessed via different pipelines.

Results

Our evaluations show that the ENmix pipeline performs the best with significantly higher correlation and lower absolute difference between duplicate pairs, higher intraclass correlation coefficients (ICC) and smaller deviations from expected methylation level in mixture experiments. In addition to the pipeline function, ENmix software provides an integrated set of functions for reading in raw data files from mouse and human arrays, quality control, data preprocessing, visualization, detection of differentially methylated regions (DMRs), estimation of cell type proportions, and calculation of methylation age clocks. ENmix is computationally efficient, flexible and allows parallel computing. To facilitate further evaluations, we make all datasets and evaluation code publicly available.

Conclusion

Careful selection of robust data preprocessing methods is critical for DNA methylation array studies. ENmix outperformed other pipelines in our evaluations to minimize experimental variation and to improve data quality and study power.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01207-1.

Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a devastating disease with a high clinical burden. The molecular signatures of IPF were analyzed to distinguish molecular subgroups and identify key driver genes and therapeutic targets.

Methods

Thirteen datasets of lung tissue transcriptomics including 585 IPF patients and 362 normal controls were obtained from the databases and subjected to filtration of differentially expressed genes (DEGs). A functional enrichment analysis, agglomerative hierarchical clustering, network-based key driver analysis, and diffusion scoring were performed, and the association of enriched pathways and clinical parameters was evaluated.

Results

A total of 2,967 upregulated DEGs was filtered during the comparison of gene expression profiles of lung tissues between IPF patients and healthy controls. The core molecular network of IPF featured p53 signaling pathway and cellular senescence. IPF patients were classified into two molecular subgroups (C1, C2) via unsupervised clustering. C1 was more enriched in the p53 signaling pathway and ciliated cells and presented a worse prognostic score, while C2 was more enriched for cellular senescence, profibrosing pathways, and alveolar epithelial cells. The p53 signaling pathway was closely correlated with a decline in forced vital capacity and carbon monoxide diffusion capacity and with the activation of cellular senescence. CDK1/2, CKDNA1A, CSNK1A1, HDAC1/2, FN1, VCAM1, and ITGA4 were the key regulators as evidence by high diffusion scores in the disease module. Currently available and investigational drugs showed differential diffusion scores in terms of their target molecules.

Conclusions

An integrative molecular analysis of IPF lungs identified two molecular subgroups with distinct pathobiological characteristics and clinical prognostic scores. Inhibition against CDKs or HDACs showed great promise for controlling lung fibrosis. This approach provided molecular insights to support the prediction of clinical outcomes and the selection of therapeutic targets in IPF patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01749-3.

Deep learning identifies erroneous microarray-based, gene-level conclusions in literature

More than 110 000 publications have used microarrays to decipher phenotype-associated genes, clinical biomarkers and gene functions. Microarrays rely on digital assaying the fluorescence signals of arrays. In this study, we retrospectively constructed raw images for 37 724 published microarray data, and developed deep learning algorithms to automatically detect systematic defects. We report that an alarming amount of 26.73% of the microarray-based studies are affected by serious imaging defects. By literature mining, we found that publications associated with these affected microarrays have reported disproportionately more biological discoveries on the genes in the contaminated areas compared to other genes. 28.82% of the gene-level conclusions reported in these publications were based on measurements falling into the contaminated area, indicating severe, systematic problems caused by such contaminations. We provided the identified published, problematic datasets, affected genes and the imputed arrays as well as software tools for scanning such contamination that will become essential to future studies to scrutinize and critically analyze microarray data.

Short-term treatment with multi-drug regimens combining BRAF/MEK-targeted therapy and immunotherapy results in durable responses in Braf-mutated melanoma

Targeted and immunotherapy regimens have revolutionized the treatment of advanced melanoma patients. Despite this, only a subset of patients respond durably. Recently, combination strategies of BRAF/MEK inhibitors with immune checkpoint inhibitor monotherapy (α-CTLA-4 or α-PD-1) have increased the rate of durable responses. Based on evidence from our group and others, these therapies appear synergistic, but at the cost of significant toxicity. We know from other treatment paradigms (e.g. hematologic malignancies) that combination strategies with multi-drug regimens (>4 drugs) are associated with more durable disease control. To better understand the mechanism of these improved outcomes, and to identify and prioritize new strategies for testing, we studied several multi-drug regimens combining BRAF/MEK targeted therapy and immunotherapy combinations in a Braf-mutant murine melanoma model (Braf^V600E/Pten^−/−). Short-term treatment with α-PD-1 and α-CTLA-4 monotherapies were relatively ineffective, while treatment with α-OX40 demonstrated some efficacy [17% of mice with no evidence of disease, (NED), at 60-days]. Outcomes were improved in the combined α-OX40/α-PD-1 group (42% NED). Short-term treatment with quadruplet therapy of immunotherapy doublets in combination with targeted therapy [dabrafenib and trametinib (DT)] was associated with excellent tumor control, with 100% of mice having NED after combined DT/α-CTLA-4/α-PD-1 or DT/α-OX40/α-PD-1. Notably, tumors from mice in these groups demonstrated a high proportion of effector memory T cells, and immunologic memory was maintained with tumor re-challenge. Together, these data provide important evidence regarding the potential utility of multi-drug therapy in treating advanced melanoma and suggest these models can be used to guide and prioritize combinatorial treatment strategies.

Early Transcriptomic Response to Burn Injury: Severe Burns Are Associated With Immune Pathway Shutdown

Burn injury induces a systemic hyperinflammatory response with detrimental side effects. Studies have described the biochemical changes induced by severe burns, but the transcriptome response is not well characterized. The goal of this work is to characterize the blood transcriptome after burn injury. Burn patients presenting to a regional center between 2012 and 2017 were prospectively enrolled. Blood was collected on admission and at predetermined time points (hours 2, 4, 8, 12, and 24). RNA was isolated and transcript levels were measured with a gene expression microarray. To identify differentially regulated genes (false-discovery rate ≤0.1) by burn injury severity, patients were grouped by TBSA above or below 20% and statistically enriched pathways were identified. Sixty-eight patients were analyzed, most patients were male with a median age of 41 (interquartile range, 30.5-58.5) years, and TBSA of 20% (11%-34%). Thirty-five patients had % TBSA injury ≥20%, and this group experienced greater mortality (26% vs 3%, P = .008). Comparative analysis of genes from patients with </≥20% TBSA revealed 1505, 613, 380, 63, 1357, and 954 differentially expressed genes at hours 0, 2, 4, 8, 12, and 24, respectively. Pathway analysis revealed an initial up-regulation in several immune/inflammatory pathways within the ≥20% TBSA groups followed by shutdown. Severe burn injury is associated with an early proinflammatory immune response followed by shutdown of these pathways. Examination of the immunoinflammatory response to burn injury through differential gene regulation and associated immune pathways by injury severity may identify mechanistic targets for future intervention.

Regulation and Role of αE Integrin and Gut Homing Integrins in Migration and Retention of Intestinal Lymphocytes during Inflammatory Bowel Disease

Adhesion molecules are upregulated in inflamed intestinal mucosa in IBD patients.

Baseline β7 expression does not impact αE induction or gene expression in T cells.

Phospho-SMAD3 is increased in inflamed mucosa in IBD.

Targeting interactions between α4β7 integrin and endothelial adhesion molecule MAdCAM-1 to inhibit lymphocyte migration to the gastrointestinal tract is an effective therapy in inflammatory bowel disease (IBD). Following lymphocyte entry into the mucosa, a subset of these cells expresses αEβ7 integrin, which is expressed on proinflammatory lymphocytes, to increase cell retention. The factors governing lymphocyte migration into the intestinal mucosa and αE integrin expression in healthy subjects and IBD patients remain incompletely understood. We evaluated changes in factors involved in lymphocyte migration and differentiation within tissues. Both ileal and colonic tissue from active IBD patients showed upregulation of ICAM-1, VCAM-1, and MAdCAM-1 at the gene and protein levels compared with healthy subjects and/or inactive IBD patients. β1 and β7 integrin expression on circulating lymphocytes was similar across groups. TGF-β1 treatment induced expression of αE on both β7⁺ and β7⁻ T cells, suggesting that cells entering the mucosa independently of MAdCAM-1/α4β7 can become αEβ7⁺. ITGAE gene polymorphisms did not alter protein induction following TGF-β1 stimulation. Increased phospho-SMAD3, which is directly downstream of TGF-β, and increased TGF-β–responsive gene expression were observed in the colonic mucosa of IBD patients. Finally, in vitro stimulation experiments showed that baseline β7 expression had little effect on cytokine, chemokine, transcription factor, and effector molecule gene expression in αE⁺ and αE⁻ T cells. These findings suggest cell migration to the gut mucosa may be altered in IBD and α4β7⁻, and α4β7⁺ T cells may upregulate αEβ7 in response to TGF-β once within the gut mucosa.

Nkx3-1 and Fech genes might be switch genes involved in pituitary non-functioning adenoma invasiveness

Non-functioning pituitary adenomas (NFPAs) are typical pituitary macroadenomas in adults associated with increased mortality and morbidity. Although pituitary adenomas are commonly considered slow-growing benign brain tumors, numerous of them possess an invasive nature. Such tumors destroy sella turcica and invade the adjacent tissues such as the cavernous sinus and sphenoid sinus. In these cases, the most critical obstacle for complete surgical removal is the high risk of damaging adjacent vital structures. Therefore, the development of novel therapeutic strategies for either early diagnosis through biomarkers or medical therapies to reduce the recurrence rate of NFPAs is imperative. Identification of gene interactions has paved the way for decoding complex molecular mechanisms, including disease-related pathways, and identifying the most momentous genes involved in a specific disease. Currently, our knowledge of the invasion of the pituitary adenoma at the molecular level is not sufficient. The current study aimed to identify critical biomarkers and biological pathways associated with invasiveness in the NFPAs using a three-way interaction model for the first time. In the current study, the Liquid association method was applied to capture the statistically significant triplets involved in NFPAs invasiveness. Subsequently, Random Forest analysis was applied to select the most important switch genes. Finally, gene set enrichment (GSE) and gene regulatory network (GRN) analyses were applied to trace the biological relevance of the statistically significant triplets. The results of this study suggest that "mRNA processing" and "spindle organization" biological processes are important in NFAPs invasiveness. Specifically, our results suggest Nkx3-1 and Fech as two switch genes in NFAPs invasiveness that may be potential biomarkers or target genes in this pathology.

Apobec1 complementation factor overexpression promotes hepatic steatosis, fibrosis, and hepatocellular cancer

The RNA-binding protein Apobec1 complementation factor (A1CF) regulates posttranscriptional ApoB mRNA editing, but the range of RNA targets and the long-term effect of altered A1CF expression on liver function are unknown. Here we studied hepatocyte-specific A1cf-transgenic (A1cf+/Tg), A1cf+/Tg Apobec1-/-, and A1cf-/- mice fed chow or high-fat/high-fructose diets using RNA-Seq, RNA CLIP-Seq, and tissue microarrays from human hepatocellular cancer (HCC). A1cf+/Tg mice exhibited increased hepatic proliferation and steatosis, with increased lipogenic gene expression (Mogat1, Mogat2, Cidea, Cd36) associated with shifts in polysomal RNA distribution. Aged A1cf+/Tg mice developed spontaneous fibrosis, dysplasia, and HCC, and this development was accelerated on a high-fat/high-fructose diet and was independent of Apobec1. RNA-Seq revealed increased expression of mRNAs involved in oxidative stress (Gstm3, Gpx3, Cbr3), inflammatory response (Il19, Cxcl14, Tnfα, Ly6c), extracellular matrix organization (Mmp2, Col1a1, Col4a1), and proliferation (Kif20a, Mcm2, Mcm4, Mcm6), and a subset of mRNAs (including Sox4, Sox9, Cdh1) were identified in RNA CLIP-Seq. Increased A1CF expression in human HCC correlated with advanced fibrosis and with reduced survival in a subset with nonalcoholic fatty liver disease. In conclusion, we show that hepatic A1CF overexpression selectively alters polysomal distribution and mRNA expression, promoting lipogenic, proliferative, and inflammatory pathways leading to HCC.

Posttranscriptional regulation of cellulose synthase genes by small RNAs derived from cellulose synthase antisense transcripts

Transcriptional regulatory mechanisms governing plant cell wall biosynthesis are incomplete. Expression programs that activate wall biosynthesis are well understood, but mechanisms that control the attenuation of gene expression networks remain elusive. Previous work has shown that small RNAs (sRNAs) derived from the HvCESA6 (Hordeum vulgare, Hv) antisense transcripts are naturally produced and are capable of regulating aspects of wall biosynthesis. Here, we further test the hypothesis that CESA-derived sRNAs generated from CESA antisense transcripts are involved in the regulation of cellulose and broader cell wall biosynthesis. Antisense transcripts were detected for some but not all members of the CESA gene family in both barley and Brachypodium distachyon. Phylogenetic analysis indicates that antisense transcripts are detected for most primary cell wall CESA genes, suggesting a possible role in the transition from primary to secondary cell wall biosynthesis. Focusing on one antisense transcript, HvCESA1 shows dynamic expression throughout development, is correlated with corresponding sRNAs over the same period and is anticorrelated with HvCESA1 mRNA expression. To assess the broader impacts of CESA-derived sRNAs on the regulation of cell wall biosynthesis, transcript profiling was performed on barley tissues overexpressing CESA-derived sRNAs. Together, the data support the hypothesis that CESA antisense transcripts function through an RNA-induced silencing mechanism, to degrade cis transcripts, and may also trigger trans-acting silencing on related genes to alter the expression of cell wall gene networks.

Analysis of lncRNA-miRNA-mRNA expression pattern in heart tissue after total body radiation in a mouse model

Background

Radiation therapy is integral to effective thoracic cancer treatments, but its application is limited by sensitivity of critical organs such as the heart. The impacts of acute radiation-induced damage and its chronic effects on normal heart cells are highly relevant in radiotherapy with increasing lifespans of patients. Biomarkers for normal tissue damage after radiation exposure, whether accidental or therapeutic, are being studied as indicators of both acute and delayed effects. Recent research has highlighted the potential importance of RNAs, including messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) as biomarkers to assess radiation damage. Understanding changes in mRNA and non-coding RNA expression will elucidate biological pathway changes after radiation.

Methods

To identify significant expression changes in mRNAs, lncRNAs, and miRNAs, we performed whole transcriptome microarray analysis of mouse heart tissue at 48 h after whole-body irradiation with 1, 2, 4, 8, and 12 Gray (Gy). We also validated changes in specific lncRNAs through RT-qPCR. Ingenuity Pathway Analysis (IPA) was used to identify pathways associated with gene expression changes.

Results

We observed sustained increases in lncRNAs and mRNAs, across all doses of radiation. Alas2, Aplnr, and Cxc3r1 were the most significantly downregulated mRNAs across all doses. Among the significantly upregulated mRNAs were cell-cycle arrest biomarkers Gdf15, Cdkn1a, and Ckap2. Additionally, IPA identified significant changes in gene expression relevant to senescence, apoptosis, hemoglobin synthesis, inflammation, and metabolism. LncRNAs Abhd11os, Pvt1, Trp53cor1, and Dino showed increased expression with increasing doses of radiation. We did not observe any miRNAs with sustained up- or downregulation across all doses, but miR-149-3p, miR-6538, miR-8101, miR-7118-5p, miR-211-3p, and miR-3960 were significantly upregulated after 12 Gy.

Conclusions

Radiation-induced RNA expression changes may be predictive of normal tissue toxicities and may indicate targetable pathways for radiation countermeasure development and improved radiotherapy treatment plans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02998-w.

Identification of Key Genes and Pathways associated with Endometriosis by Weighted Gene Co-expression Network Analysis

Background: Endometriosis is a common gynecological disorder with high rates of infertility and pelvic pain. However, its pathogenesis and diagnostic biomarkers remain unclear. This study aimed to elucidate potential hub genes and key pathways associated with endometriosis in ectopic endometrium (EC) and eutopic endometrium (EU). Material and Method: EC and EU-associated microarray datasets were obtained from the gene expression omnibus (GEO) database. Gene set enrichment analysis was performed to obtain further biological insight into the EU and EC-associated genes. Weighted gene co-expression network analysis (WGCNA) was performed to find clinically significant modules of highly-correlated genes. The hub genes that belong to both the weighted gene co-expression network and protein-protein interaction (PPI) network were identified using a Venn diagram. Results: We obtained EC and EU-associated microarray datasets GSE7305 and GSE120103. Genes in the EC were mainly enriched in the immune response and immune cell trafficking, and genes in the EU were mainly enriched in stress response and steroid hormone biosynthesis. PPI networks and weighted gene co-expression networks were constructed. An EC-associated blue module and an EU-associated magenta module were identified, and their function annotations revealed that hormone receptor signaling or inflammatory microenvironments may promote EU passing through the oviducts and migrating to the ovarian surfaces, and adhesion and immune correlated genes may induce the successful ectopic implantation of the endometrium (EC). Twelve hub genes in the EC and sixteen hub genes in the EU were recognized and further validated in independent datasets. Conclusion: Our study identified, for the first time, the hub genes and enrichment pathways in the EC and EU using WGCNA, which may provide a comprehensive understanding of the pathogenesis of endometriosis and have important clinical implications for the treatment and diagnosis of endometriosis.

Differential lncRNA expression profiling of cognitive function in middle and old aged monozygotic twins using generalized association analysis

Cognitive impairment is the most prominent symptom in neurodegenerative disorders affecting quality of life and mortality. However, despite years of research, the molecular mechanism underlying the regulation of cognitive function and its impairment is poorly understood. This study aims to elucidate the role of long non-coding RNAs (lncRNAs) expression and lncRNA-mRNA interaction networks, by analyzing lncRNA expression in whole blood samples of 400 middle and old aged monozygotic twins in association with cognitive function using both linear models and a generalized correlation coefficient (GCC) to capture the diverse patterns of correlation. We detected 13 probes (p < 1e-03) displaying nonlinear and 7 probes (p < 1e-03) showing linear correlations. After combining the results, we identified 20 lncRNA probes with p < 1e-03. The top lncRNA probes were annotated to genes, along with the non-coding MALAT1, that play roles in neurodegenerative diseases. The top lncRNAs were linked to functional clusters including peptidyl-glycine modification, vascular smooth muscle cells, mitotic spindle organization and protein tyrosine phosphatase. In addition, mapping of the top significant lncRNAs to the lncRNA-mRNA interaction network detected significantly enriched biological pathways involving neuroactive ligand-receptor interaction, proteasome and chemokines. We show that GCC served as a complementary approach in detecting lncRNAs missed by the conventional linear models. A combination of GCC and linear models identified lncRNAs of diverse patterns of association enriched for GO biological and molecular functions meaningful in cognitive performance and cognitive decline. The novel lncRNA regulatory network further contributed to detect significant pathways implicated in cognition.

Mapping Autoantibodies in Children With Acute Rheumatic Fever

Background

Acute rheumatic fever (ARF) is a serious sequela of Group A Streptococcus (GAS) infection associated with significant global mortality. Pathogenesis remains poorly understood, with the current prevailing hypothesis based on molecular mimicry and the notion that antibodies generated in response to GAS infection cross-react with cardiac proteins such as myosin. Contemporary investigations of the broader autoantibody response in ARF are needed to both inform pathogenesis models and identify new biomarkers for the disease.

Methods

This study has utilised a multi-platform approach to profile circulating autoantibodies in ARF. Sera from patients with ARF, matched healthy controls and patients with uncomplicated GAS pharyngitis were initially analysed for autoreactivity using high content protein arrays (Protoarray, 9000 autoantigens), and further explored using a second protein array platform (HuProt Array, 16,000 autoantigens) and 2-D gel electrophoresis of heart tissue combined with mass spectrometry. Selected autoantigens were orthogonally validated using conventional immunoassays with sera from an ARF case-control study (n=79 cases and n=89 matched healthy controls) and a related study of GAS pharyngitis (n=39) conducted in New Zealand.

Results

Global analysis of the protein array data showed an increase in total autoantigen reactivity in ARF patients compared with controls, as well as marked heterogeneity in the autoantibody profiles between ARF patients. Autoantigens previously implicated in ARF pathogenesis, such as myosin and collagens were detected, as were novel candidates. Disease pathway analysis revealed several autoantigens within pathways linked to arthritic and myocardial disease. Orthogonal validation of three novel autoantigens (PTPN2, DMD and ANXA6) showed significant elevation of serum antibodies in ARF (p < 0.05), and further highlighted heterogeneity with patients reactive to different combinations of the three antigens.

Conclusions

The broad yet heterogenous elevation of autoantibodies observed suggests epitope spreading, and an expansion of the autoantibody repertoire, likely plays a key role in ARF pathogenesis and disease progression. Multiple autoantigens may be needed as diagnostic biomarkers to capture this heterogeneity.

Diet-regulated production of PDGFcc by macrophages controls energy storage

The mechanisms by which macrophages regulate energy storage remain poorly understood. We identify in a genetic screen a platelet-derived growth factor (PDGF)/vascular endothelial growth factor (VEGF)-family ortholog, Pvf3, that is produced by macrophages and is required for lipid storage in fat-body cells of Drosophila larvae. Genetic and pharmacological experiments indicate that the mouse Pvf3 ortholog PDGFcc, produced by adipose tissue-resident macrophages, controls lipid storage in adipocytes in a leptin receptor- and C-C chemokine receptor type 2-independent manner. PDGFcc production is regulated by diet and acts in a paracrine manner to control lipid storage in adipose tissues of newborn and adult mice. At the organismal level upon PDGFcc blockade, excess lipids are redirected toward thermogenesis in brown fat. These data identify a macrophage-dependent mechanism, conducive to the design of pharmacological interventions, that controls energy storage in metazoans.

Global Gene Expression Profiling and Transcription Factor Network Analysis of Cognitive Aging in Monozygotic Twins

Cognitive aging is one of the major problems worldwide, especially as people get older. This study aimed to perform global gene expression profiling of cognitive function to identify associated genes and pathways and a novel transcriptional regulatory network analysis to identify important regulons. We performed single transcript analysis on 400 monozygotic twins using an assumption-free generalized correlation coefficient (GCC), linear mixed-effect model (LME) and kinship model and identified six probes (one significant at the standard FDR < 0.05 while the other results were suggestive with 0.18 ≤ FDR ≤ 0.28). We combined the GCC and linear model results to cover diverse patterns of relationships, and meaningful and novel genes like APOBEC3G, H6PD, SLC45A1, GRIN3B, and PDE4D were detected. Our exploratory study showed the downregulation of all these genes with increasing cognitive function or vice versa except the SLC45A1 gene, which was upregulated with increasing cognitive function. Linear models found only H6PD and SLC45A1, the other genes were captured by GCC. Significant functional pathways (FDR < 3.95e-10) such as focal adhesion, ribosome, cysteine and methionine metabolism, Huntington's disease, eukaryotic translation elongation, nervous system development, influenza infection, metabolism of RNA, and cell cycle were identified. A total of five regulons (FDR< 1.3e-4) were enriched in a transcriptional regulatory analysis in which CTCF and REST were activated and SP3, SRF, and XBP1 were repressed regulons. The genome-wide transcription analysis using both assumption-free GCC and linear models identified important genes and biological pathways implicated in cognitive performance, cognitive aging, and neurological diseases. Also, the regulatory network analysis revealed significant activated and repressed regulons on cognitive function.

The global gene expression outline of the bovine blastocyst: reflector of environmental conditions and predictor of developmental capacity

Background

Morphological evaluation of embryos has been used to screen embryos for transfer. However, the repeatability and accuracy of this method remains low. Thus, evaluation of an embryo’s gene expression signature with respect to its developmental capacity could provide new opportunities for embryo selection. Since the gene expression outline of an embryo is considered as an aggregate of its intrinsic characteristics and culture conditions, we have compared transcriptome profiles of in vivo and in vitro derived blastocysts in relation to pregnancy outcome to unravel the discrete effects of developmental competence and environmental conditions on bovine embryo gene expression outlines. To understand whether the gene expression patterns could be associated with blastocyst developmental competency, the global transcriptome profile of in vivo (CVO) and in vitro (CVT) derived competent blastocysts that resulted in pregnancy was investigated relative to that of in vivo (NVO) and in vitro (NVT) derived blastocysts which did not establish initial pregnancy, respectively while to unravel the effects of culture condition on the transcriptome profile of embryos, the transcriptional activity of the CVO group was compared to the CVT group and the NVO group was compared to the NVT ones.

Results

A total of 700 differentially expressed genes (DEGs) were identified between CVO and NVO blastocysts. These gene transcripts represent constitutive regions, indel variants, 3′-UTR sequence variants and novel transcript regions. The majority (82%) of these DEGs, including gene clusters like ATP synthases, eukaryotic translation initiation factors, ribosomal proteins, mitochondrial ribosomal proteins, NADH dehydrogenase and cytochrome c oxidase subunits were enriched in the CVO group. These DEGs were involved in pathways associated with glycolysis/glycogenesis, citrate acid cycle, pyruvate metabolism and oxidative phosphorylation. Similarly, a total of 218 genes were differentially expressed between CVT and NVT groups. Of these, 89%, including TPT1, PDIA6, HSP90AA1 and CALM, were downregulated in the CVT group and those DEGs were overrepresented in pathways related to protein processing, endoplasmic reticulum, spliceasome, ubiquitone mediated proteolysis and steroid biosynthesis. On the other hand, although both the CVT and CVO blastocyst groups resulted in pregnancy, a total of 937 genes were differential expressed between the two groups. Compared to CVO embryos, the CVT ones exhibited downregulation of gene clusters including ribosomal proteins, mitochondrial ribosomal protein, eukaryotic translation initiation factors, ATP synthases, NADH dehydrogenase and cytochrome c oxidases. Nonetheless, downregulation of these genes could be associated with pre and postnatal abnormalities observed after transfer of in vitro embryos.

Conclusion

The present study provides a detailed inventory of differentially expressed gene signatures and pathways specifically reflective of the developmental environment and future developmental capacities of bovine embryos suggesting that transcriptome activity observed in blastocysts could be indicative of further pregnancy success but also adaptation to culture environment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07693-0.

A genome-wide screen reveals microRNAs in peripheral sensory neurons driving painful diabetic neuropathy

ABSTRACT

Diabetes is a leading cause of peripheral neuropathy (diabetic peripheral neuropathy, DPN), and uncontrolled long-lasting hyperglycemia leads to severe complications. A major proportion of diabetics develop excruciating pain with a variable course. Mechanisms leading to painful DPN are not completely understood and treatment options limited. We hypothesized that epigenetic modulation at the level of microRNA (miRNA) expression triggered by metabolic imbalance and nerve damage regulates the course of pain development. We used clinically relevant preclinical models, genome-wide screening, in silico analyses, cellular assays, miRNA fluorescent in situ hybridization, in vivo molecular manipulations, and behavioral analyses in the current study. We identified miRNAs and their targets that critically impact on nociceptive hypersensitivity in painful DPN. Our analyses identify miR-33 and miR-380 expressed in nociceptive neurons as critical denominators of diabetic pain and miR-124-1 as a mediator of physiological nociception. Our comprehensive analyses on the putative mRNA targets for miR-33 or miR-124-1 identified a set of mRNAs that are regulated after miR-33 or miR-124-1 overexpression in dorsal root ganglia in vivo. Our results shed light on the regulation of DPN pathophysiology and implicate specific miRNAs as novel therapeutic targets for treating painful DPN.

protGear: A protein microarray data pre-processing suite

Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data. Published guidelines to limit technical variability whilst maintaining important biological variation favour DNA-based microarrays that often differ fundamentally in their experimental design. Rigorous tools to guide background correction, the quantification of within-sample variation, normalisation, and batch correction specifically for protein microarrays are limited, require extensive investigation and are not centrally accessible.

Here, we develop a generic one-stop-shop pre-processing suite for protein microarrays that is compatible with data from the major protein microarray scanners. Our graphical and tabular interfaces facilitate a detailed inspection of data and are coupled with supporting guidelines that enable users to select the most appropriate algorithms to systematically address bias arising in customized experiments. The localization and distribution of background signal intensities determine the optimal correction strategy. A novel function overcomes the limitations in the interpretation of the coefficient of variation when signal intensities are at the lower end of the detection threshold. We demonstrate essential considerations in the experimental design and their impact on a range of algorithms for normalization and minimization of batch effects.

Our user-friendly interactive web-based platform eliminates the need for prowess in programming. The open-source R interface includes illustrative examples, generates an auditable record, enables reproducibility, and can incorporate additional custom scripts through its online repository. This versatility will enhance its broad uptake in the infectious disease and vaccine development community.

Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response

The addition of HER2-targeted agents to neoadjuvant chemotherapy has dramatically improved pathological complete response (pCR) rates in early-stage, HER2-positive breast cancer. Nonetheless, up to 50% of patients have residual disease after treatment, while others are likely overtreated. Here, we performed multiplex spatial proteomic characterization of 122 samples from 57 HER2-positive breast tumors from the neoadjuvant TRIO-US B07 clinical trial sampled pre-treatment, after 14-21 d of HER2-targeted therapy and at surgery. We demonstrated that proteomic changes after a single cycle of HER2-targeted therapy aids the identification of tumors that ultimately undergo pCR, outperforming pre-treatment measures or transcriptomic changes. We further developed and validated a classifier that robustly predicted pCR using a single marker, CD45, measured on treatment, and showed that CD45-positive cell counts measured via conventional immunohistochemistry perform comparably. These results demonstrate robust biomarkers that can be used to enable the stratification of sensitive tumors early during neoadjuvant HER2-targeted therapy, with implications for tailoring subsequent therapy.