Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

RNA sequencing of exosomes secreted by fibroblast and Schwann cells elucidates mechanisms underlying peripheral nerve regeneration

JOURNAL/nrgr/04.03/01300535-202408000-00035/figure1/v/2023-12-16T180322Z/r/image-tiff Exosomes exhibit complex biological functions and mediate a variety of biological processes, such as promoting axonal regeneration and functional recovery after injury. Long non-coding RNAs (lncRNAs) have been reported to play a crucial role in axonal regeneration. However, the role of the lncRNA-microRNA-messenger RNA (mRNA)-competitive endogenous RNA (ceRNA) network in exosome-mediated axonal regeneration remains unclear. In this study, we performed RNA transcriptome sequencing analysis to assess mRNA expression patterns in exosomes produced by cultured fibroblasts (FC-EXOs) and Schwann cells (SC-EXOs). Differential gene expression analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and protein-protein interaction network analysis were used to explore the functions and related pathways of RNAs isolated from FC-EXOs and SC-EXOs. We found that the ribosome-related central gene Rps5 was enriched in FC-EXOs and SC-EXOs, which suggests that it may promote axonal regeneration. In addition, using the miRWalk and Starbase prediction databases, we constructed a regulatory network of ceRNAs targeting Rps5, including 27 microRNAs and five lncRNAs. The ceRNA regulatory network, which included Ftx and Miat, revealed that exsosome-derived Rps5 inhibits scar formation and promotes axonal regeneration and functional recovery after nerve injury. Our findings suggest that exosomes derived from fibroblast and Schwann cells could be used to treat injuries of peripheral nervous system.

Single high-dose intravenous injection of Wharton's jelly-derived mesenchymal stem cell exerts protective effects in a rat model of metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS) is a significant epidemiological problem worldwide. It is a pre-morbid, chronic and low-grade inflammatory disorder that precedes many chronic diseases. Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) could be used to treat MetS because they express high regenerative capacity, strong immunomodulatory properties and allogeneic biocompatibility. This study aims to investigate WJ-MSCs as a therapy against MetS in a rat model.

METHODS

Twenty-four animals were fed with high-fat high-fructose (HFHF) diet ad libitum. After 16 weeks, the animals were randomised into treatment groups (n = 8/group) and received a single intravenous administration of vehicle, that is, 3 × 106 cells/kg or 10 × 106 cells/kg of WJ-MSCs. A healthy animal group (n = 6) fed with a normal diet received the same vehicle as the control (CTRL). All animals were periodically assessed (every 4 weeks) for physical measurements, serum biochemistry, glucose tolerance test, cardiovascular function test and whole-body composition. Post-euthanasia, organs were weighed and processed for histopathology. Serum was collected for C-reactive protein and inflammatory cytokine assay.

RESULTS

The results between HFHF-treated groups and healthy or HFHF-CTRL did not achieve statistical significance (α = 0.05). The effects of WJ-MSCs were masked by the manifestation of different disease subclusters and continuous supplementation of HFHF diet. Based on secondary analysis, WJ-MSCs had major implications in improving cardiopulmonary morbidities. The lungs, liver and heart show significantly better histopathology in the WJ-MSC-treated groups than in the untreated CTRL group. The cells produced a dose-dependent effect (high dose lasted until week 8) in preventing further metabolic decay in MetS animals.

CONCLUSIONS

The establishment of safety and therapeutic proof-of-concept encourages further studies by improving the current therapeutic model.

Profile of the RNA in exosomes from astrocytes and microglia using deep sequencing: implications for neurodegeneration mechanisms

Glial cells play an important role in signal transduction, energy metabolism, extracellular ion homeostasis and neuroprotection of the central nervous system. However, few studies have explained the potential effects of exosomes from glial cells on central nervous system health and disease. In this study, the genes expressed in exosomes from astrocytes and microglia were identified by deep RNA sequencing. Kyoto Encyclopedia of Genes and Genomes analysis indicated that several pathways in these exosomes are responsible for promoting neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease and Huntington’s disease. Gene ontology analysis showed that extracellular exosome, mitochondrion and growth factor activity were enriched in exosomes from the unique astrocyte group, while extracellular exosome and mitochondrion were enriched in exosomes from the unique microglia group. Next, combined with the screening of hub genes, the protein-protein interaction network analysis showed that exosomes from astrocytes influence neurodegenerative diseases through metabolic balance and ubiquitin-dependent protein balance, whereas exosomes from microglia influence neurodegenerative diseases through immune inflammation and oxidative stress. Although there were differences in RNA expression between exosomes from astrocytes and microglia, the groups were related by the hub genes, ubiquitin B and heat shock protein family A (Hsp70) member 8. Ubiquitin B appeared to be involved in pleiotropic regulatory functions, including immune regulation, inflammation inhibition, protein catabolism, intracellular protein transport, exosomes and oxidative stress. The results revealed the clinical significance of exosomes from glia in neurodegenerative diseases. This study was approved by the Animal Ethics Committee of Nantong University, China (approval No. S20180102-152) on January 2, 2018.

Assessment of Post-Radiation Time Effect on Gene Expression Profiles of Saccharomyces cerevisiae Samples After Appling a UV Laser

Introduction: Widespread application of lasers in different fields of medicine implies more investigations into the molecular mechanism of laser effects on the human body. Network analysis of the dysregulated genes of Saccharomyces cerevisiae samples are irradiated by a UV laser and harvested 30 minutes after radiation compared with a 15-minute group is the aim of this research. Methods: The significant dysregulated genes interacted via the STRING database, and the central nodes were determined by "Networkanalyzer" application of Cytoscape software. The critical genes and the related biological terms were identified via action map analysis and gene ontology assessment. Results: The gene expression profiles of the samples with 30-minute post-radiation time were different from the samples with 15 minutes of post-radiation time. 9 potent central genes, 50% of which were similar to the nodes of the 15-minute group, were identified. The terms "positive regulation of telomere maintenance" were targeted in the two sample groups. Conclusion: In spite of large alteration in the gene expression profiles of the samples, the results indicated that the main affected biological term for the 15-minute and 30-minute groups was similar.

Unearthing of Key Genes Driving the Pathogenesis of Alzheimer's Disease via Bioinformatics

Alzheimer’s disease (AD) is a neurodegenerative disease with unelucidated molecular pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis of AD. The AD datasets of GSE118553 and GSE131617 were collected from the NCBI GEO database. The weighted gene coexpression network analysis (WGCNA), differential gene expression analysis, and functional enrichment analysis were performed to reveal the hub genes and verify their role in AD. Hub genes were validated by machine learning algorithms. We identified modules and their corresponding hub genes from the temporal cortex (TC), frontal cortex (FC), entorhinal cortex (EC), and cerebellum (CE). We obtained 33, 42, 42, and 41 hub genes in modules associated with AD in TC, FC, EC, and CE tissues, respectively. Significant differences were recorded in the expression levels of hub genes between AD and the control group in the TC and EC tissues (P < 0.05). The differences in the expressions of FCGRT, SLC1A3, PTN, PTPRZ1, and PON2 in the FC and CE tissues among the AD and control groups were significant (P < 0.05). The expression levels of PLXNB1, GRAMD3, and GJA1 were statistically significant between the Braak NFT stages of AD. Overall, our study uncovered genes that may be involved in AD pathogenesis and revealed their potential for the development of AD biomarkers and appropriate AD therapeutics targets.

Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity

Experiments based on metabolomics represent powerful approaches to the experimental verification of the integrity of food. In particular, high-resolution non-targeted analyses, which are carried out by means of liquid chromatography-mass spectrometry systems (LC-MS), offer a variety of options. However, an enormous amount of data is recorded, which must be processed in a correspondingly complex manner. The evaluation of LC-MS based non-targeted data is not entirely trivial and a wide variety of strategies have been developed that can be used in this regard. In this paper, an overview of the mandatory steps regarding data acquisition is given first, followed by a presentation of the required preprocessing steps for data evaluation. Then some multivariate analysis methods are discussed, which have proven to be particularly suitable in this context in recent years. The publication closes with information on the identification of marker compounds.

Fold-Change Compression: An Unexplored But Correctable Quantitative Bias Caused by Nonlinear Electrospray Ionization Responses in Untargeted Metabolomics

The nonlinear signal response of electrospray ionization (ESI) presents a critical limitation for mass spectrometry (MS)-based quantitative analysis. In the field of metabolomics research, this issue has largely remained unaddressed; MS signal intensities are usually directly used to calculate fold changes for quantitative comparison. In this work, we demonstrate that, due to the nonlinear ESI response, signal intensity ratios of a metabolic feature calculated between two samples may not reflect their real metabolic concentration ratios (i.e., fold-change compression), implying that conventional fold-change calculations directly using MS signal intensities can be misleading. In this regard, we developed a quality control (QC) sample-based signal calibration workflow to overcome the quantitative bias caused by the nonlinear ESI response. In this workflow, calibration curves for every metabolic feature are first established using a QC sample injected in serial injection volumes. The MS signals of each metabolic feature are then calibrated to their equivalent QC injection volumes for comparative analysis. We demonstrated this novel workflow in a targeted metabolite analysis, showing that the accuracy of fold-change calculations can be significantly improved. Furthermore, in a metabolomic comparison of the bone marrow interstitial fluid samples from leukemia patients before and after chemotherapy, an additional 59 significant metabolic features were found with fold changes larger than 1.5, and an additional 97 significant metabolic features had fold changes corrected by more than 0.1. This work enables high-quality quantitative analysis in untargeted metabolomics, thus providing more confident biological hypotheses generation.

Genome-Wide Transcriptional and Functional Analysis of Human T Lymphocytes Treated with Benzo[α]pyrene

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed environmental contaminants, known to affect T lymphocytes. However, the molecular targets and pathways involved in their immunotoxic effects in human T lymphocytes remain unknown. Here, we analyzed the gene expression profile of primary human T lymphocytes treated with the prototypical PAH, benzo[α]pyrene (B[α]P), using a microarray-based transcriptome analysis. After a 48 h exposure to B[α]P, we identified 158 genes differentially expressed in T lymphocytes, including not only genes well-known to be affected by PAHs such as the cytochromes P450 (CYP) 1A1 and 1B1, but also others not previously shown to be targeted by B[α]P such as genes encoding the gap junction beta (GJB)-2 and 6 proteins. Functional enrichment analysis revealed that these candidates were significantly associated with the aryl hydrocarbon (AhR) and interferon (IFN) signaling pathways; a marked alteration in T lymphocyte recruitment was also observed. Using functional tests in transwell migration experiments, B[α]P was then shown to significantly decrease the chemokine (C-X-C motif) ligand 12-induced chemotaxis and transendothelial migration of T lymphocytes. In total, this study opens the way to unsuspected responsive pathway of interest, i.e., T lymphocyte migration, thus providing a more thorough understanding of the molecular basis of the immunotoxicity of PAHs.

Whole genome shotgun sequencing revealed highly polymorphic genome regions and genes in Escherichia coli O157:H7 isolates collected from a single feedlot

Escherichia coli serotype O157:H7 continues to pose a serious health threat to human beings. Cattle, a major reservoir of the pathogen, harbor E. coli O157:H7 in their gastrointestinal tract and shed variable concentrations of E. coli O157:H7 into the environment. Genetic characterization of cattle-shed E. coli O157 strains is of interest to the livestock industry, food business, and public health community. The present study applied whole genome shotgun sequencing (WGS) and single nucleotide variant (SNV) calling to characterize 279 cattle-shed E. coli O157:H7 strains isolated from a single feedlot located in southwestern region of the US. More than 4,000 SNVs were identified among the strains and the resultant phylogenomic tree revealed three major groups. Using the Sakai strain genome as reference, more than 2,000 SNVs were annotated and a detailed SNV map generated. Results clearly revealed highly polymorphic loci along the E. coli O157:H7 genome that aligned with the prophage regions and highly variant genes involved in processing bacterial genetic information. The WGS data were further profiled against a comprehensive virulence factor database (VFDB) for virulence gene identification. Among the total 285 virulence genes identified, only 132 were present in all the strains. There were six virulence genes unique to single isolates. Our findings suggested that the genome variations of the E. coli O157:H7 were mainly attributable to dynamics of certain phages, and the bacterial strains have variable virulence gene profiles, even though they came from a single cattle population, which may explain the differences in pathogenicity, host prevalence, and transmissibility by E. coli O157:H7.

Independent prognostic genes and mechanism investigation for colon cancer

PROPOSE

We aimed to explore the potential molecular mechanism and independent prognostic genes for colon cancer (CC).

METHODS

Microarray datasets GSE17536 and GSE39582 were downloaded from Gene Expression Omnibus. Meanwhile, the whole CC-related dataset were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNA (DEMs) were identified between cancer tissue samples and para-carcinoma tissue samples in TCGA dataset, followed by the KEGG pathway and GO function analyses. Furthermore, the clinical prognostic analysis including overall survival (OS) and disease-free survival (DFS) were performed in all three datasets.

RESULTS

A total of 633 up- and 321 down-regulated mRNAs were revealed in TCGA dataset. The up-regulated mRNAs were mainly assembled in functions including extracellular matrix and pathways including Wnt signaling. The down-regulated mRNAs were mainly assembled in functions like Digestion and pathways like Drug metabolism. Furthermore, up-regulation of UL16-binding protein 2 (ULBP2) was associated with OS in CC patients. A total of 12 DEMs including Surfactant Associated 2 (SFTA2) were potential DFS prognostic genes in CC patients. Meanwhile, the GRP and Transmembrane Protein 37 (TMEM37) were two outstanding independent DFS prognostic genes in CC.

CONCLUSIONS

ULBP2 might be a potential novel OS prognostic biomarker in CC, while GRP and TMEM37 could be served as the independent DFS prognostic genes in CC. Furthermore, functions including extracellular matrix and digestion, as well as pathways including Wnt signaling and drug metabolism might play important roles in the process of CC.

Tracking Cancer Genetic Evolution using OncoTrack

It is difficult for existing methods to quantify, and track the constant evolution of cancers due to high heterogeneity of mutations. However, structural variations associated with nucleotide number changes show repeatable patterns in localized regions of the genome. Here we introduce SPKMG, which generalizes nucleotide number based properties of genes, in statistical terms, at the genome-wide scale. It is measured from the normalized amount of aligned NGS reads in exonic regions of a gene. SPKMG values are calculated within OncoTrack. SPKMG values being continuous numeric variables provide a statistical metric to track DNA level changes. We show that SPKMG measures of cancer DNA show a normative pattern at the genome-wide scale. The analysis leads to the discovery of core cancer genes and also provides novel dynamic insights into the stage of cancer, including cancer development, progression, and metastasis. This technique will allow exome data to also be used for quantitative LOH/CNV analysis for tracking tumour progression and evolution with a higher efficiency.

Genomewide comparison of the inducible transcriptomes of nuclear receptors CAR, PXR and PPARα in primary human hepatocytes

The ligand-activated nuclear receptor pregnane X receptor (PXR, NR1I2) and the constitutive androstane receptor (CAR, NR1I3) are two master transcriptional regulators of many important drug metabolizing enzymes and transporter genes (DMET) in response to xenobiotics including many drugs. The peroxisome proliferator-activated receptor alpha (PPARα, NR1C1), the target of lipid lowering fibrate drugs, primarily regulates fatty acid catabolism and energy-homeostasis. Recent research has shown that there are substantial overlaps in the regulated genes of these receptors. For example, both CAR and PXR also modulate the transcription of key enzymes involved in lipid and glucose metabolism and PPARα also functions as a direct transcriptional regulator of important DMET genes including cytochrome P450s CYP3A4 and CYP2C8. Despite their important and widespread influence on liver metabolism, comparative data are scarce, particularly at a global level and in humans. The major objective of this study was to directly compare the genome-wide transcriptional changes elucidated by the activation of these three nuclear receptors in primary human hepatocytes. Cultures from six individual donors were treated with the prototypical ligands for CAR (CITCO), PXR (rifampicin) and PPARα (WY14,643) or DMSO as vehicle control. Genomewide mRNA profiles determined with Affymetrix microarrays were analyzed for differentially expressed genes and metabolic functions. The results confirmed known prototype target genes and revealed strongly overlapping sets of coregulated but also distinctly regulated and novel responsive genes and pathways. The results further specify the role of PPARα as a regulator of drug metabolism and the role of the xenosensors PXR and CAR in lipid metabolism and energy homeostasis. This article is part of a Special Issue entitled: Xenobiotic nuclear receptors: New Tricks for An Old Dog, edited by Dr. Wen Xie.

A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays

Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods. Previous comparisons have come to sometimes contradictory conclusions, which we suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, we carried out a parallel nested experiment performed simultaneously on the two technologies that systematically split variation into four stages (treatment, biological variation, library preparation and chip/lane noise), allowing a separation and comparison of the sources of variation in a well-controlled cellular system, Saccharomyces cerevisiae. With this novel dataset, we demonstrate that power and accuracy are more dependent on per-gene read depth in RNA-Seq than they are on fluorescence intensity in microarrays. However, we carried out quantitative PCR validations which indicate that microarrays may demonstrate greater systematic bias in low-intensity genes than in RNA-seq.

A set of external reference controls/probes that enable quality assurance between different microarray platforms

RNA external standards, although important to ensure equivalence across many microarray platforms, have yet to be fully implemented in the research community. In this article, a set of unique RNA external standards (or RNA standards) and probe pairs that were added to total RNA in the samples before amplification and labeling are described. Concentration-response curves of RNA external standards were used across multiple commercial DNA microarray platforms and/or quantitative real-time polymerase chain reaction (RT-PCR) and next-generation sequencing to identify problematic assays and potential sources of variation in the analytical process. A variety of standards can be added in a range of concentrations spanning high and low abundances, thereby enabling the evaluation of assay performance across the expected range of concentrations found in a clinical sample. Using this approach, we show that we are able to confirm the dynamic range and the limit of detection for each DNA microarray platform, RT-PCR protocol, and next-generation sequencer. In addition, the combination of a series of standards and their probes was investigated on each platform, demonstrating that multiplatform calibration and validation is possible.

Essential O2-responsive genes of Pseudomonas aeruginosa and their network revealed by integrating dynamic data from inverted conditions

Identification of the gene network through which Pseudomonas aeruginosa PAO1 (PA) adapts to altered oxygen-availability environments is essential for a better understanding of stress responses and pathogenicity of PA. We performed high-time-resolution (HTR) transcriptome analyses of PA in a continuous cultivation system during the transition from high oxygen tension to low oxygen tension (HLOT) and the reversed transition from low to high oxygen tension (LHOT). From those genes responsive to both transient conditions, we identified 85 essential oxygen-availability responsive genes (EORGs), including the expected ones (arcDABC) encoding enzymes for arginine fermentation. We then constructed the regulatory network for the EORGs of PA by integrating information from binding motif searching, literature and HTR data. Notably, our results show that only the sub-networks controlled by the well-known oxygen-responsive transcription factors show a very high consistency between the inferred network and literature knowledge, e.g. 87.5% and 83.3% of the obtained sub-network controlled by the anaerobic regulator (ANR) and a quorum sensing regulator RhIR, respectively. These results not only reveal stringent EORGs of PA and their transcription regulatory network, but also highlight that achieving a high accuracy of the inferred regulatory network might be feasible only for the apparently affected regulators under the given conditions but not for all the expressed regulators on a genome scale.

PLAU inferred from a correlation network is critical for suppressor function of regulatory T cells

Human FOXP3(+)CD25(+)CD4(+) regulatory T cells (Tregs) are essential to the maintenance of immune homeostasis. Several genes are known to be important for murine Tregs, but for human Tregs the genes and underlying molecular networks controlling the suppressor function still largely remain unclear. Here, we describe a strategy to identify the key genes directly from an undirected correlation network which we reconstruct from a very high time-resolution (HTR) transcriptome during the activation of human Tregs/CD4(+) T-effector cells. We show that a predicted top-ranked new key gene PLAU (the plasminogen activator urokinase) is important for the suppressor function of both human and murine Tregs. Further analysis unveils that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways. Our study demonstrates the potential for identifying novel key genes for complex dynamic biological processes using a network strategy based on HTR data, and reveals a critical role for PLAU in Treg suppressor function.

Expansion of the silkworm GMC oxidoreductase genes is associated with immunity

The glucose-methanol-choline (GMC) oxidoreductases constitute a large gene family in insects. Some of these enzymes play roles in developmental or physiological process, such as ecdysteroid metabolism. However, little is known about the functional diversity of the insect GMC family. Here, we identified 43 GMC genes in the silkworm genome, the largest number of GMC genes among all the insect genomes sequenced to date. Similar to the other insects, there is a highly conserved GMC cluster within the second intron of the silkworm flotillin-2 (flo-2) gene. However, the silkworm GMC genes outside of the conserved GMC cluster have experienced a large expansion. Phylogenetic analysis suggested that the silkworm GMCβ subfamily contained 22 copies and made a major contribution to expansion of the silkworm GMC genes. Eighteen of the 22 members of the silkworm GMCβ subfamily are located outside of the conserved GMC cluster, and are known as silkworm expansion genes (SEs). Relative-rate tests showed that SEs evolved significantly faster than the GMCβ genes inside the conserved GMC cluster. Accordingly, the third position GC content (GC3s) and codon bias of SEs are significantly different from those of the GMCβ genes in the conserved GMC cluster. The elevated evolutionary rate of the silkworm GMCβ genes outside of the conserved GMC cluster may reflect the evolution of function diversity. At least 24 of the 43 silkworm GMC genes were differently transcribed and expressed in a tissue- or stage-specific manner during the larval stage. Strikingly, microarray data revealed that four different pathogens upregulated most of the silkworm GMCβ genes. Furthermore, RNA interference of representative upregulated GMCβ genes reduced the survival rate of the silkworm when infected by pathogens. Taken together, the results suggested that expansion of the silkworm GMC oxidoreductase genes is associated with immunity.