Transcriptomics and network analysis highlight potential pathways in the pathogenesis of pterygium

Pterygium is a common ocular surface condition frequently associated with irritative symptoms. The precise identity of its critical triggers as well as the hierarchical relationship between all the elements involved in the pathogenesis of this disease are not yet elucidated. Meta-analysis of gene expression studies represents a novel strategy capable of identifying key pathogenic mediators and therapeutic targets in complex diseases. Samples from nine patients were collected during surgery after photo documentation and clinical characterization of pterygia. Gene expression experiments were performed using Human Clariom D Assay gene chip. Differential gene expression analysis between active and atrophic pterygia was performed using limma package after adjusting variables by age. In addition, a meta-analysis was performed including recent gene expression studies available at the Gene Expression Omnibus public repository. Two databases including samples from adults with pterygium and controls fulfilled our inclusion criteria. Meta-analysis was performed using the Rank Production algorithm of the RankProd package. Gene set analysis was performed using ClueGO and the transcription factor regulatory network prediction was performed using appropriate bioinformatics tools. Finally, miRNA-mRNA regulatory network was reconstructed using up-regulated genes identified in the gene set analysis from the meta-analysis and their interacting miRNAs from the Brazilian cohort expression data. The meta-analysis identified 154 up-regulated and 58 down-regulated genes. A gene set analysis with the top up-regulated genes evidenced an overrepresentation of pathways associated with remodeling of extracellular matrix. Other pathways represented in the network included formation of cornified envelopes and unsaturated fatty acid metabolic processes. The miRNA-mRNA target prediction network, also reconstructed based on the set of up-regulated genes presented in the gene ontology and biological pathways network, showed that 17 target genes were negatively correlated with their interacting miRNAs from the Brazilian cohort expression data. Once again, the main identified cluster involved extracellular matrix remodeling mechanisms, while the second cluster involved formation of cornified envelope, establishment of skin barrier and unsaturated fatty acid metabolic process. Differential expression comparing active pterygium with atrophic pterygium using data generated from the Brazilian cohort identified differentially expressed genes between the two forms of presentation of this condition. Our results reveal differentially expressed genes not only in pterygium, but also in active pterygium when compared to the atrophic ones. New insights in relation to pterygium’s pathophysiology are suggested.

Analysis of Small RNA Sequencing Data in Plants

Over the past decades, next-generation sequencing (NGS) has been employed extensively for investigating the regulatory mechanisms of small RNAs. Several bioinformatics tools are available for aiding biologists to extract meaningful information from enormous amounts of data generated by NGS platforms. This chapter describes a detailed methodology for analyzing small RNA sequencing data using different open source tools. We elaborate on various steps involved in analysis, from processing the raw sequencing reads to identifying miRNAs, their targets, and differential expression studies.

GROWTH AND EXPRESSION PATTERN OF GROWTH-RELATED GENES IN THE FAST-GROWING GIANT GOURAMI Osphronemus goramy

Growth improvement of the giant gourami through molecular assisted selection offers a breakthrough solution regarding the slow growth problem in culturing the fish species. However, gene molecular expression studies and gene mapping information are scarce for this species. This study aimed to evaluate the growth, expression of the growth-related genes and compare the gene expressions between fast-growing (FG) and slow-growing (SG) fish. The polymorphism screenings were also conducted within the GH sequence of the FG and SG populations. Fish growth was analyzed by measuring length and weight once a month. The expression levels of GH, IGF1, AMPK, ARS-I, ALT, and AST genes were analyzed using real-time PCR. Twenty-five days old fish were reared for 30 days. The fish were continuously reared separately based on their body weight (BW) for 85 days until reaching 140 days old. At the end of the rearing period, the BW growth rate of the FG population was 1.569-fold higher, and body length (BL) growth was 1.056-fold higher than the SG population. FG fish have higher gene expression than the SG fish, indicating the important role of gene expression in fish growth. The polymorphisms screening within the GH sequences showed no significant difference between FG and SG fish of giant gourami. These research results provide valuable information in developing the marker-assisted selection for growth traits in giant gourami.

PPIA and YWHAZ Constitute a Stable Pair of Reference Genes during Electrical Stimulation in Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are multipotent adult stem cells with great potential in regenerative medicine. One method for stimulating proliferation and differentiation of MSCs is via electrical stimulation (ES). A valuable approach for evaluating the response of MSCs to ES is to assess changes in gene expression, relative to one or more reference genes. In a survey of 25 publications that used ES on cells, 70% selected GAPDH as the reference gene. We conducted a study to assess the suitability of six potential reference genes on an immortalized human MSC line following direct current ES at seeding densities of 5000 and 10,000 cells/cm2. We employed three methods to validate the most stable reference genes from qRT-PCR data. Our findings show that GAPDH and ACTB exhibit reduced stability when seeded at 5000 cell/cm2. In contrast, we found that the most stable genes across both plating densities and stimulation regimes were PPIA and YWHAZ. Thus, in ES gene expression studies in MSCs, we support the use of PPIA and YWHAZ as an optimal reference gene pair, and discourage the use of ACTB and GAPDH at lower seeding densities. However, it is strongly recommended that similar verification studies are carried out based on cell type and different ES conditions.

Understanding Gene Expression and Transcriptome Profiling of COVID-19: An Initiative Towards the Mapping of Protective Immunity Genes Against SARS-CoV-2 Infection

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease’s potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.

Tomato SlBES1.8 influences leaf morphogenesis by mediating gibberellin metabolism and signaling

Leaf morphogenetic activity determines its shape diversity. However, our knowledge to the regulatory mechanism in maintaining leaf morphogenetic capacity is still limited. In tomato, gibberellin (GA) negatively regulates leaf complexity by shortening the morphogenetic window. We here reported a tomato BRI1-EMS-SUPPRESSOR 1 (BES1) transcription factor, SlBES1.8, that promoted the simplification of leaf pattern in a similar manner as GA functions. Enhanced level of SlBES1.8 dramatically decreased the sensibility of tomato to GA whereas increased the sensibility to the GA biosynthesis inhibitor, PAC. In line with the phenotypic observation, the endogenous bioactive GA contents were increased in OE-SlBES1.8 lines, which certainly promoted the degradation of the GA signaling negative regulator, SlDELLA. Moreover, transcriptomic analysis uncovered a set of overlapping genomic targets of SlBES1.8 and GA, and most of them were regulated in the same way. Expression studies showed the repression of SlBES1.8 to the transcriptions of two GA deactivated genes, SlGA2ox2 and SlGA2ox6, and one GA receptor, SlGID1b-1. Further experiments confirmed the direct regulation of SlBES1.8 to their promoters. On the other hand, SlDELLA physically interacted with SlBES1.8 and further inhibited its transcriptional regulation activity by abolishing SlBES1.8-DNA binding. Conclusively, by mediating GA deactivation and signaling, SlBES1.8 greatly influenced tomato leaf morphogenesis.

mCherry contains a fluorescent protein isoform that interferes with its reporter function

Fluorescent proteins are essential reporters in cell biology and molecular biology. Here, we reveal that red-fluorescent proteins possess an alternative translation initiation site that produces a short functional protein isoform. The short isoform creates significant background fluorescence that biases the outcome of expression studies. Our investigation identifies the short protein isoform, traces its origin, and determines the extent of the issue within the family of red fluorescent protein. Our analysis shows that the short isoform defect of the red fluorescent protein family may affect the interpretation of many published studies. Finally, we provide a re-engineered mCherry variant that lacks background expression as an improved tool for imaging and protein expression studies.

A success targeted nano delivery to lung cancer cells with multi-walled carbon nanotubes conjugated to bromocriptine

In this research, a new nano drug-based multi-walled carbon nanotubes (MWCNTs) was prepared and evaluated qualitatively. Bromocriptine (BRC) was conjugated to functionalized carbon nanotubes. Then, the CHNS, FT-IR, SEM, and RAMAN tests for characterization of the conjugated drug were done. The nanofluid-containing nano-drug was evaluated on lung cancer cells (A549 & QU-DB) and MRC5 by MTT and flow cytometry tests. Then, the gene expression studies of dopamine receptor genes were done before and after nano-drug treatment. After that, a western blotting test was carried out for further investigation of dopamine receptors protein production. Finally, Bax and Bcl-2 secretion were measured by the ELISA method in cells affected by MWCNTs-BRC Nf compared to untreated cells. The results showed that the nano-drug had a significant lethal effect on cancer cells, while it had no toxicity on MRC5. Also, the nano-drug could significantly induce apoptosis in lung cancer cells at a lower dose compared to the drug alone. In this study, a targeted nano-drug delivery system was designed, and its performance was evaluated based on neurotransmitter pathways, and the results showed that it may be useful in the treatment of lung cancer. However, additional studies on animal models are underway.

Validation of reference genes for quantitative PCR in the forest pest, Ips calligraphus

The six-spined ips, Ips calligraphus, is a North American bark beetle that can exploit most eastern North American Pinus species and can cause mortality. Biotic and abiotic disturbances weaken trees, creating breeding substrate that promotes rapid population growth. Management historically relied on silvicultural practices, but as forests become increasingly stressed, innovative management is needed. Manipulation of the cellular RNA interference (RNAi) pathway to induce gene silencing is an emerging means of insect suppression, and is effective for some bark beetles. Quantitative PCR (qPCR) is a powerful tool for analysis of gene expression, and is essential for examining RNAi. To compare gene expression among individuals, stably expressed reference genes must be validated for qPCR. We evaluated six candidate reference genes (18s, 16s, 28s, ef1a, cad, coi) for stability under biotic (beetle sex, developmental stage, and host plant), and abiotic (temperature, photoperiod, and dsRNA exposure) conditions. We used the comprehensive RefFinder tool to compare stability rankings across four algorithms. These algorithms identified 18s, 16s, and 28s as the most stably expressed. Overall, 16s and 28s were selected as reference genes due to their stability and moderate expression levels, and can be used for I. calligraphus gene expression studies using qPCR, including those evaluating RNAi.