PANTHER Classification System Research Articles

The molecular mechanisms of Abyssinone-I protect against Alzheimer’s disease: an in-silico study

There is limited available information regarding the biological activity of Abyssinone-I, apart from its recognized antioxidant and cytotoxic properties. So, we aimed to evaluate the molecular processes underlying the promising effect of Abyssinone-I on Alzheimer’s disease (AD). The Swiss Target Predictor, GeneCard, GeneMania, Metascape, SwissADME, Cytoscape, the Panther classification system, MIENTURNET, WebGestalt, PASS online, Autodock Vina, and molecular dynamic simulation were the main methods for this analysis. Abyssinone-I exhibits antioxidative, anti-inflammatory, and MAO inhibitory activities and maintains membrane integrity. These properties may target 79 proteins, four miRNAs (hsa-miR-128-3p, hsa-miR-124-3p, hsa-miR-16-5p, and hsa-miR-335-5p), three transcription factors (PPARG, MEF2B, and MYBL2), and two chromosomes (chr9q22.2, chr12q24.12). Key pathways affected include the amyloid-beta response, protein autophosphorylation, and dopamine metabolism. Among these, five hub targets (PPARG, mTOR, EGFR, ESR1, and MAPK1) were highlighted for their significant roles in AD pathogenesis. Despite its promising properties, abyssinone-I has low bioavailability and may interact with other drugs. Future in vivo and in vitro studies are necessary to validate these findings and optimize therapeutic usage. This study provides a foundation for Abyssinone-I as a potential AD treatment, pending further experimental confirmation.Graphical

The role of thioredoxin proteins in Mycobacterium tuberculosis probed by proteome-wide target profiling

Mycobacterium tuberculosis encounters diverse microenvironments, including oxidative assault (ROS and RNS), when it attempts to establish itself within its human host. Therefore, redox sensory and regulation processes are assumed significant importance, as these are essential processes for M. tuberculosis to survive under these hostile conditions. M. tuberculosis contains thioredoxin system to maintain redox homeostasis, which establish a balance between the thiol/dithiol couple.Still very less is known about it. In the present study, we attempted to capture the targets of all the M. tuberculosis thioredoxin proteins (viz., TrxB and TrxC) and a thioredoxin-like protein, NrdH, under aerobic and hypoxic conditions by performing thioredoxin trapping chromatography followed by mass spectrometry. We found that TrxC captured the maximum number of targets in both the physiological conditions and most of the targets of TrxB and NrdH showing overlap with targets of TrxC, indicating that TrxC acts as main thioredoxin. Further the PANTHER classification system provides involvement of targets in various metabolic processes and Gene Ontology analysis suggests that glutamine biosynthetic process and Fe–S cluster biosynthesis are the most enriched processes in the target list of TrxC and TrxB respectively. Also, we suggest that the thioredoxin system might play an important role under hypoxia by targeting those proteins which are responsible to sense and maintain hypoxic conditions. Furthermore, our studies establish a link between TrxB and iron-sulfur cluster biogenesis in M. tuberculosis. Ultimately, these findings open a new direction to target the thioredoxin system for screening new anti-mycobacterial drug targets.

Comparative analysis of transcriptional changes in zebrafish cep290 and bbs2 mutants by RNA-seq reveals upregulation of inflammatory and stress-related pathways.

Acute injury to the adult zebrafish retina triggers the release of pro-inflammatory cytokines and growth factors that stimulate multiple gene regulatory networks, which ultimately stimulate Müller glia to proliferate and regenerate neurons. In contrast, zebrafish carrying mutations in cep290 or bbs2 undergo progressive loss of cone photoreceptors and exhibit signs of microglia activation and inflammation, but the mutants fail to stimulate a regeneration response. To identify transcriptional changes that occur in zebrafish mutants undergoing progressive photoreceptor degeneration, RNA-seq transcriptional profiling was performed on cep290-/- and bbs2-/- retinas. The PANTHER Classification System was used to identify biological processes and signaling pathways that were differentially expressed between mutants and wild-type siblings during degeneration. As expected, genes associated with phototransduction were downregulated in cep290 and bbs2 mutants compared to wild-type siblings. Although both cep290 and bbs2 mutants undergo proliferation of rod precursors in response to retinal degeneration, the process of negatively regulating proliferation is enriched for upregulated genes, and this negative regulation may restrict proliferation of Müller glia and inhibit regeneration. A total of 815 differentially expressed genes (DEGs) were shared by cep290 and bbs2 retinas. Genes in pathways associated with inflammation, apoptosis, stress response, and PDGF signaling were overrepresented. Identifying the genes and biological pathways that are common in zebrafish models of inherited retinal degeneration provides a foundation for future studies on the mechanisms that regulate cell death as well as processes that prohibit Müller cell reprogramming or proliferation in a model capable of retinal regeneration. The pathways will provide targets for future interventions that may promote successful regeneration of lost photoreceptors.

Unravelling the Impact of Cyclic Mechanical Stretch in Keratoconus-A Transcriptomic Profiling Study.

Biomechanical and molecular stresses may contribute to the pathogenesis of keratoconus (KC). We aimed to profile the transcriptomic changes in healthy primary human corneal (HCF) and KC-derived cells (HKC) combined with TGFβ1 treatment and cyclic mechanical stretch (CMS), mimicking the pathophysiological condition in KC. HCFs (n = 4) and HKCs (n = 4) were cultured in flexible-bottom collagen-coated 6-well plates treated with 0, 5, and 10 ng/mL of TGFβ1 with or without 15% CMS (1 cycle/s, 24 h) using a computer-controlled Flexcell FX-6000T Tension system. We used stranded total RNA-Seq to profile expression changes in 48 HCF/HKC samples (100 bp PE, 70-90 million reads per sample), followed by bioinformatics analysis using an established pipeline with Partek Flow software. A multi-factor ANOVA model, including KC, TGFβ1 treatment, and CMS, was used to identify differentially expressed genes (DEGs, |fold change| ≥ 1.5, FDR ≤ 0.1, CPM ≥ 10 in ≥1 sample) in HKCs (n = 24) vs. HCFs (n = 24) and those responsive to TGFβ1 and/or CMS. PANTHER classification system and the DAVID bioinformatics resources were used to identify significantly enriched pathways (FDR ≤ 0.05). Using multi-factorial ANOVA analyses, 479 DEGs were identified in HKCs vs. HCFs including TGFβ1 treatment and CMS as cofactors. Among these DEGs, 199 KC-altered genes were responsive to TGFβ1, thirteen were responsive to CMS, and six were responsive to TGFβ1 and CMS. Pathway analyses using PANTHER and DAVID indicated the enrichment of genes involved in numerous KC-relevant functions, including but not limited to degradation of extracellular matrix, inflammatory response, apoptotic processes, WNT signaling, collagen fibril organization, and cytoskeletal structure organization. TGFβ1-responsive KC DEGs were also enriched in these. CMS-responsive KC-altered genes such as OBSCN, CLU, HDAC5, AK4, ITGA10, and F2RL1 were identified. Some KC-altered genes, such as CLU and F2RL1, were identified to be responsive to both TGFβ1 and CMS. For the first time, our multi-factorial RNA-Seq study has identified many KC-relevant genes and pathways in HKCs with TGFβ1 treatment under CMS, suggesting a potential role of TGFβ1 and biomechanical stretch in KC development.

Secretome Analysis of Human Nasal Fibroblast Identifies Proteins That Promote Wound Healing.

Conditioned medium from cultured fibroblast cells is recognized to promote wound healing and growth through the secretion of enzymes, extracellular matrix proteins, and various growth factors and cytokines. The objective of this study was to profile the secreted proteins present in nasal fibroblast conditioned medium (NFCM). Nasal fibroblasts isolated from human nasal turbinates were cultured for 72h in Defined Keratinocytes Serum Free Medium (DKSFM) or serum-free F12: Dulbecco's Modified Eagle's Medium (DMEM) to collect conditioned medium, denoted as NFCM_DKSFM and NFCM_FD, respectively. SDS-PAGE was performed to detect the presence of protein bands, followed by MALDI-TOF and mass spectrometry analysis. SignalP, SecretomeP, and TMHMM were used to identify the secreted proteins in conditioned media. PANTHER Classification System was performed to categorize the protein according to protein class, whereas STRING 10 was carried out to evaluate the predicted proteins interactions. SDS-PAGE results showed the presence of various protein with molecular weight ranging from ~10kDa to ~260kDa. Four protein bands were identified using MALDI-TOF. The analyses identified 104, 83, and 7 secreted proteins in NFCM_FD, NFCM_DKSFM, and DKSFM, respectively. Four protein classes involved in wound healing were identified, namely calcium-binding proteins, cell adhesion molecules, extracellular matrix proteins, and signaling molecules. STRING10 protein prediction successfully identified various pathways regulated by secretory proteins in NFCM. In conclusion, this study successfully profiled the secreted proteins of nasal fibroblasts and these proteins are predicted to play important roles in RECs wound healing through various pathways.

To Explore the Key Active Compounds and Therapeutic Mechanism of Guizhi Gancao Decoction in Coronary Heart Disease by Network Pharmacology and Molecular Docking.

Coronary heart disease (CHD) is the leading cause of death from cardiovascular disease and has become an important public health problem worldwide. Guizhi Gancao Decoction (GGD) has been shown to be used in the treatment of CHD with good efficacy, but its specific therapeutic mechanism and active ingredients have not been fully clarified. This study aims to identify the active compounds and key targets of GGD in the treatment of CHD, explore the therapeutic mechanism of GGD, and provide candidate compounds for anti-CHD drug development. The main compounds of GGD were determined by UPLC-MS/MS analysis and screened by SwissADME. The corresponding targets of GGD compounds were obtained from SwissTargetPrediction, and the targets of CHD were obtained from the HERB and GeneCards databases. The STRING 11.5 database was used to analyze the PPI (Protein-Protein Interactions) network of potential therapeutic targets of GGD compounds. Cytoscape 3.7.2 was used to construct target-related networks and find core targets. The GEO database was used to validate the differential expression of core targets. The PANTHER Classification System was used to functionally classify potential therapeutic targets for GGD. The GO biological process analysis and KEGG pathway analysis of targets were completed by DAVID 6.8 database. AutoDockTools 1.5.6 and PyMol 2.5.2 were used to perform molecular docking of core targets with the active GGD compounds. 7 active GGD compounds were obtained based on UPLC-MS/MS and pharmacological parameter evaluation, which corresponded to 131 CHD-related targets. Among them, EGFR, MAPK3, RELA, CCND1, ESR1, PTGS2, NR3C1, CYP3A4, MMP9, and PTPN11 were considered core targets. According to the targets related to CHD, glycyrrhetinic acid, liquiritigenin, and schisandrin are considered key active ingredients. GO biological process and KEGG analysis indicated that the potential targets of GGD in the treatment of CHD involve a variety of biological processes and therapeutic mechanisms. Molecular docking results showed that both the core targets and the corresponding compounds had the good binding ability. This study contributes to a more comprehensive understanding of the therapeutic mechanism and active ingredients of GGD for CHD and provides candidate compounds for drug development of CHD.

Identifying the tumor location-associated candidate genes in development of new drugs for colorectal cancer using machine-learning-based approach.

Numerous studies have been conducted to elucidate the relation of tumor proximity to cancer prognosis and treatment efficacy in colorectal cancer. However, the molecular pathways and prognoses of left- and right-sided colorectal cancers are different, and this difference has not been fully investigated at the genomic level. In this study, a set of data science approaches, including six feature selection methods and three classification models, were used in predicting tumor location from gene expression profiles. Specificity, sensitivity, accuracy, and Mathew's correlation coefficient (MCC) evaluation metrics were used to evaluate the classification ability. Gene ontology enrichment analysis was applied by the Gene Ontology PANTHER Classification System. For the most significant 50 genes, protein-protein interactions and drug-gene interactions were analyzed using the GeneMANIA, CytoScape, CytoHubba, MCODE, and DGIdb databases. The highest classification accuracy (90%) is achieved with the most significant 200 genes when the ensemble-decision tree classification model is used with the ReliefF feature selection method. Molecular pathways and drug interactions are investigated for the most significant 50 genes. It is concluded that a machine-learning-based approach could be useful to discover the significant genes that may have an important role in the development of new therapies and drugs for colorectal cancer.

Mechanistic insight of the potential of geraniol against Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) as a neurodegenerative disease occupies 3/5–4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstanding neuroprotective effects as well as ameliorating influence in memory impairment. Therefore, the present study aims to elucidate the potential of geraniol against AD by network pharmacology-based approach combined with molecular modeling study.Materials and methodsFirstly, we evaluated the druggability of geraniol by ADME method. Then, we obtained the geraniol targets and AD-related targets from multiple open data sources. Afterward, we calculated the intersection through a Venn diagram to find common targets, and via Panther classification system to categorize them. In order to gain a macroscopic understanding of these common targets, we carried out GO terms and KEGG pathways enrichment analyses, according to which we constructed a compound–target–pathway–disease network. In addition, we built a preliminary PPI network which was further analyzed both functionally and topologically. Consequently, five hub targets were sorted out. Finally, we conducted molecular docking and molecular dynamic simulation to validate our findings.ResultsIn the present study, the pharmacological properties of geraniol were assessed according to ADME and Lipinski’s rule, which demonstrate promising druggability. Then, from 10,972 AD-related targets and 33 geraniol targets, 29 common targets were identified, among which 38.1% of them are metabolite interconversion enzymes, 23.8% are protein modifying enzymes, 33.3% are transmembrane receptors, and the rest are transporters. Enrichment analyses hint that geraniol is involved in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction. We also built a preliminary PPI network to investigate the interplay between these targets and their extensive interactions. Then, by functionally clustering the preliminary PPI network, we gained a cluster of proteins which formed a subnetwork with score of 8.476, and 22 nodes. Its results of GO terms and KEGG pathways enrichment analyses once again suggests that geraniol actively participates in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction, which are believed to be strongly associated with AD pathogenesis. Besides, topological analyses of the preliminary PPI network helped find 5 hub targets (i.e., CHRM3, PRKCA, PRKCD, JAK1, JAK2). To verify their interaction with geraniol molecule, we conducted molecular docking, and found that CHRM3 possesses the highest affinity in binding, indicating that geraniol molecules are closely bound to each hub target, and CHRM3 may serve as a key target of geraniol against AD. It was then further confirmed by molecular dynamic simulation, the result of which supports our hypothesis.ConclusionThe present study shares a mechanistic insight of the potential of geraniol against AD, giving a reference to future experimental studies.

Differential proteome and functional analysis of NSCLC cell lines in response to Tualang honey treatment

Ethnopharmacological relevanceHoney's therapeutic and nutrition effects have been discovered for centuries. Traditionally, it is applied as a health supplement as well as an alternative treatment for a variety of medical issues ranging from wound healing to anticancer therapy. Tualang honey (TH) is a natural sweet substance produced by Apis dorsata, naturally has a dark brown appearance from its high polyphenolic compounds. TH has been reported to show anticancer effects on various types of cancers including breast, oral, leukemia, cervical and lung cancer through several pathways. The detailed molecular mechanism of anticancer activity of TH as a chemopreventive and therapeutic agent is an interesting endeavor to understand. Aim of the studyDespite the anticancer effects of Tualang honey (TH) on various types of cancer have been widely reported, the exact molecular mechanism underlying its' anticancer action remains unpublished. Thus, this study aimed to investigate changes that occur on the proteome profile and the functional analysis of proteins with differential abundances within non-small cell lung cancer (NSCLC) cells that were treated with TH and discover the plausible molecular mechanism governing its’ anticancer action. Materials and methodsNSCLC cell lines (H23 and A549) were treated with 3.6% and 3.1% v/v of TH for 24 h, respectively. Protein extracts were obtained from control NSCLC cells and TH-treated NSCLC cells. Label-free quantitative proteomic analysis was subsequently performed in nanoACQUITY UPLC with quadrupole-time of flight (Q-TOF) Synapt G2 HDMS mass spectrometer system to identify and quantify proteins of TH-treated NSCLC cells. The gene ontology (GO) PANTHER classification system was performed to categorize the identified proteins based on their protein class, biological processes, and pathway. Meanwhile, the STRING functional protein association network database was used to analyze the functional protein-protein interaction and associated pathways of significantly different proteins of NSCLC cells. ResultsA total of 634 and 554 proteins were identified from H23 and A549 cell lines where 88 differential proteins were upregulated and 103 were downregulated in TH-treated H23 cells, whilst 66 differential proteins were upregulated and 61 were downregulated in TH-treated A549 cells. Differently expressed proteins of NSCLC were observed to be associated with the cell cycle, apoptosis, and VEGFA-VEGFR signaling pathway. TH modulated these signaling pathways through downregulation of ELAVL1, H3F3A and PCNA proteins. Three potential protein markers were significantly downregulated in NSCLC cells such as HRAS, HSPB1, and TUBA1C when treated with TH. ConclusionsOur findings suggested the anticancer activity of TH on NSCLC cells through modulation of pertinent cancer-related proteins that are associated with cell proliferation, apoptosis inhibition, and induction of angiogenesis.

Mechanism analysis of repeatedly steamed and sundried Rehmanniae Radix Praeparata in delaying brain aging in ovariectomized mice based on proteomics

The present study explored the effect and mechanism of repeatedly steamed and sundried Rehmanniae Radix Praeparata(RRP) in delaying brain aging in ovariectomized mice. After ovariectomy, the mice were randomly divided into a model group, an estradiol valerate group(0.3 mg·kg~(-1)), and low-(1.0 g·kg~(-1)), medium-(2.0 g·kg~(-1)), and high-dose(4.0 g·kg~(-1)) RRP groups, and a sham operation group was also set up, with 15 mice in each group. One week after the operation, intragastric administration was carried out for 15 consecutive weeks. The step-down test and Morris water maze test were used to detect the behavioral changes of mice. HE staining and Nissl staining were used to observe the morphological changes of mouse brain tissues. Immunohistochemistry was used to detect the expression of Aβ and ER_β in mouse brain tissues. The serum estrogen levels and cholinesterase and cholinesterase transferase levels in brain tissues of mice were detected by assay kits. The extracted hippocampal protein was detected by the Nano-ESI-LC-MS system, identified by the Protein Discovery, and analyzed quantitatively and qualitatively by the SIEVE. The PANTHER Classification System was used for GO analysis and KEGG pathway enrichment analysis of the differential proteins. Compared with the sham operation group, the model group showed decreased learning and memory ability, shortened step-down latency(P<0.05), prolonged escape latency(P<0.05), reduced platform crossings and residence time in the target quadrant, scattered nerve cells in the hippocampus with enlarged intercellular space, increased expression of Aβ-positive cells(P<0.05), declining expression of ER_β-positive cells and estrogen level(P<0.05), and weakened cholinergic function(P<0.05). Compared with the model group, the RRP groups showed improved learning and memory ability, prolonged step-down latency(P<0.05), increased estrogen level(P<0.05), neatly arranged nerve cells in the hippocampus with complete morphology, declining Aβ-positive cells, and elevated expression of ER_β-positive cells. A total of 146 differential proteins were screened out by proteomics, and KEGG pathway enrichment yielded 75 signaling pathways. The number of proteins involved in the dopaminergic synapse signaling pathway was the largest, with 13 proteins involved. In summary, RRP can delay brain aging presumedly by increasing the level of estrogen, mediating the dopaminergic synapse signaling pathway, and improving cholinergic function.

Analysis of RAGE Proteome and Interactome in Lung Adenocarcinoma Using PANTHER and STRING Databases.

Adenocarcinoma accounts for about 40% of all lung cancers. Histological studies indicate a loss of expression of the Receptor for Advanced Glycation End-products (RAGE) in lung adenocarcinoma cells compared to neighboring non-malignant tissue. Gene silencing of RAGE in human lung adenocarcinoma cells was performed and then cells were subjected to LC-MS/MS (n = 3, FDR < 1%). Differentially expressed proteins were analyzed using the PANTHER Classification System and STRING Interactome, identifying functions and protein-protein interaction networks. We observed expression of dominant-negative (DN-) RAGE, an isoform lacking the critical intracellular signaling tail observed in the full length (FL-) RAGE. Proteomic analysis suggests DN-RAGE likely plays a crucial role in cell polarity, metastases, and in cell-cell or cell-matrix complexes through focal adhesion or adherens junction formation. DN-RAGE may also regulate the expression of FL-RAGE and may provide a "switch" that could transition from a pro-inflammatory to a migratory cell as vimentin expression increased along with a reduction in cell polarity proteins. STRING interactome analysis identified seven protein-protein interaction networks involved in the regulation of gene expression, cell organization, cytoskeletal changes, sub-membrane plaque formation, as well as cytokinesis, cell shape, and motility. Suggesting expression of DN-RAGE may contribute to metastases and the development of advanced cancer.

The influence of adalimumab treatment on the systemic gene expression in patients with psoriatic arthritis - preliminary report.

The primary goal of psoriasis treatment is to reduce the inflammatory response and associated complications. In severe cases of psoriasis that are resistant to local treatment (e.g., keratolytic preparations) and at least two types of general treatment methods (e.g., retinoids and cyclosporine A), biological therapy is used. This study aimed to assess the systemic effects of adalimumab at a given stage of treatment in patients with psoriatic arthritis and evaluate how the drug can improve the clinical condition of the patients. The study group consisted of patients with diagnosed psoriatic arthritis, while the control group consisted of individuals from whom peripheral blood mononuclear cells were obtained. The effects of the administration of adalimumab were assessed by analyzing the gene expression using oligonucleotide microarrays. The apoptosis process was found to be one of the overrepresented categories (the PANTHER classification system 13.1 program, overrepresentation test, p < 0.05). The dermatological indexes decreased, indicating an improvement in the clinical conditions of the patients 3 months after the first dose of adalimumab. We found that adalimumab affects apoptosis, which is crucial in the development and course of psoriasis. The differential gene expression in peripheral blood mononuclear cells of patients with psoriatic arthritis indicated the potential systemic effects of adalimumab therapy. The analyses of dermatological (the Psoriasis Area and Severity Index, body surface area and Dermatology Life Quality Index) and inflammatory (Biernacki's reaction) parameters revealed the effectiveness of the therapy.

155 Effects of sustained hyperprolactinemia in late gestation on the mammary parenchymal transcriptome of gilts

Abstract The study objective was to determine the effects of hyperprolactinemia on the mammary parenchymal transcriptome in late-pregnant gilts. Gilts were divided into 3 groups on day 90 of gestation to receive IM injections of 1) canola oil (CTL, n = 18) until day 109 of gestation, 2) domperidone (dopamine antagonist) until day 96 (T7, n = 17) or, 3) domperidone until day 109 (T20, n = 17). Mammary glands were collected on day 110 and parenchymal tissue was sampled for transcriptomic analyses. Total RNA was isolated from 6 CTL and 6 T20 gilts for microarray analysis. The GeneChip® Porcine Gene 1.0 ST Array (19,202 genes) was used for hybridization. Array quality control, data normalization and expression level analyses were performed with the Affymetrix Expression Console and Transcriptome Analysis Console (TAC) software. Using a threshold cut-off of 1.5 fold (P &amp;lt; 0.05), a total of 313 upregulated and 480 downregulated gene transcripts were identified in T20 vs CTL gilts. A qPCR validation analysis of selected upregulated (n = 13) and downregulated (n = 13) genes was conducted on all animals (CTL, T7, T20). The MIXED procedure of SAS was used for statistical analyses. All selected genes were validated for the CTL vs T20 comparison (P &amp;lt; 0.01). Only 4 selected genes (CAMK1G, COL9A1, P2RX7, TDRD1) were downregulated in the T7 treatment (vs CTL, P &amp;lt; 0.05). Functional analyses of differentially expressed genes were performed using the PANTHER classification system. The top upregulated Biological Process enriched GO terms were Inflammatory Response (GO:0006954) and Response to Lipid (GO:0033993). The Positive Regulation of Cell Population Proliferation (GO:0008284) and Regulation of Cellular Catabolic Process (GO:0031329) GO terms were identified for downregulated genes. Results suggest that a sustained hyperprolactinemia during late-pregnancy (T20 treatment) may increase mammary inflammatory response and reduce cell proliferation.

PSIV-11 Effects of very low-dose antibiotics on gene expression profiles in ileal mucosa of weaned pigs infected with a pathogenic E. coli

Abstract Our previous studies have shown that supplementation of low-dose antibiotic growth promoter (AGP) exacerbated growth performance and systemic inflammation of weaned pigs infected with pathogenic Escherichia coli (E. coli). The objective of this experiment, which is extension of our previous report, was to investigate the effect of low-dose AGP on gene expression in ileal mucosa of weaned pigs experimentally infected with F18 E. coli. Thirty-four pigs (6.88 ± 1.03 kg BW) were individually housed in disease containment rooms and randomly allotted to one of three treatments (9 to 13 pigs/treatment). The three dietary treatments were control diet (control), and 2 additional diets supplemented with 0.5 or 50 mg/kg of AGP (carbadox), respectively. The experiment lasted 18 d [7 d before and 11 d after first inoculation (d 0)]. The F18 E. coli inoculum was orally provided to all pigs with the dose of 1010 cfu/3 mL for 3 consecutive days. Total RNA [4 to 6 pigs/treatment on d 5; 5 to 7 pigs/treatment on 11 post-inoculation (PI)] was extracted from ileal mucosa to analyze gene expression profiles by Batch-Tag-Seq. The modulated differential gene expression were defined by 1.5-fold difference and a cutoff of P &amp;lt; 0.05 using limma-voom package. All processed data were statistically analyzed and evaluated by PANTHER classification system to determine the biological process function of genes in these lists. Compared to control, supplementation of recommended-dose AGP down-regulated genes related to inflammatory responses on d 5 and 11 PI; whereas, feeding low-dose AGP up-regulated genes associated with negative regulation of metabolic process on d 5, but down-regulated the genes related to immune responses on d 11 PI. The present observations support adverse effects of low-dose AGP in our previous study, indicated by exacerbated the detrimental effects of E. coli infection on pigs’ growth rate, diarrhea and systemic inflammation.

Targeting Aberrant Chromatin in Chronic Lymphocytic Leukemia

Targeting Aberrant Chromatin in Chronic Lymphocytic Leukemia

Protein Composition of the Subretinal Fluid Suggests Selective Diffusion of Vitreous Proteins in Retinal Detachment.

PurposeTo study the proteome of the subretinal fluid (SRF) from rhegmatogenous retinal detachment (RRD) in search for novel markers for improved diagnosis and prognosis of RRD.MethodsHuman undiluted SRF obtained during vitrectomy for primary RRD using a 41-gauge needle (n = 24) was analyzed and compared to vitreous humor from 2-day postmortem eyes (n = 20). Sample preparation underwent nanoflow liquid chromatography–tandem mass spectrometry. Label-free quantification (LFQ) using MaxQuant was used to determine differentially expressed proteins between SRF and vitreous humor. The intensity-based absolute quantification (iBAQ) was used to rank proteins according to their molar fractions within groups. Identification of proteins beyond the quantitative level was performed using the Mascot search engine.ResultsThe protein concentration of the control vitreous humor was lower and more consistent (1.2 ± 0.4 mg) than that of the SRF (17.9 ± 22 mg). The iBAQ analysis showed high resemblance between SRF and vitreous humor, except for crystallins solely identified in vitreous humor. The LFQ analysis found 38 protein misregulations between SRF and vitreous humor of which the blood coagulation pathway was found to be enriched using the PANTHER Classification System. Combined, the iBAQ, LFQ, and Mascot analysis found an overlap only in chitinase-3-like protein 1 and galectin-3-binding protein unique to the SRF.ConclusionsThe proteome of the SRF was highly represented by proteins involved in proteolysis. Such proteins can possibly serve as targets in modulating the effects of SRF in RD.Translational RelevanceTo identify potential novel biomarkers for therapeutic targeting in RD.

Genome-wide methylation profiles in monozygotic twins with discordance for ovarian carcinoma.

Ovarian cancer is a disease that is generally diagnosed at an advanced stage, and has poor survival. Monozygotic (MZ) twins are considered to be good research models for investigating the epigenetic changes associated with diseases. In the present study, the involvement of epigenetic mechanisms in ovarian cancer etiology were evaluated using the MZ twin model. Whole-genome methylation patterns were investigated in a BRCA1 gene mutation-carrying family comprising MZ twins, only one of whom had ovarian cancer, and other healthy siblings. Whole-genome methylation patterns were assessed in peripheral blood DNA using Infinium MethylationEPIC BeadChips on an Illumina iScan device. The hypermethylated and hypomethylated genes were detected between cases and controls in four different comparison groups in order to evaluate the differences in methylation levels according to cancer diagnosis and BRCA mutation status. The obtained results showed that the differential methylations in 12 different genes, namely PR/SET domain 6, cytochrome B5 reductase 4, ZNF714, OR52M1, SEMA4D, CHD1L, CAPZB, clustered mitochondria homolog, RB-binding protein 7, chromatin repair factor, ankyrin repeat domain 23, RIB43A domain with coiled-coils 1 and C6orf227, were associated with ovarian cancer. Biological functional analysis of the genes detected in the study using the PANTHER classification system revealed that they have roles in biological processes including ‘biologic adhesion’, ‘regulation’, ‘cellular components organization’, ‘biogenesis’, ‘immune system functioning’, ‘metabolic functioning’ and ‘localization’. Overall, the present study suggested that epigenetic differences, such as methylation status, could be used as a non-invasive biological markers for the early diagnosis and follow-up of ovarian cancer.

A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer

Cervical cancer is the fourth most common cancer in women worldwide. The current approaches still have limitations in predicting the therapy outcome of each individual because of cancer heterogeneity. The goal of this study was to establish a gene expression signature that could help when choosing the right therapeutic method for the treatment of advanced-stage cervical cancer. The 666 patients were collected from four independent datasets. The 70-gene expression signature was established using univariate Cox proportional hazard regression analysis. The 70-gene signature was significantly different between low- and high-risk groups in the training dataset (p = 4.24e−6) and in the combined three validation datasets (p = 4.37e−3). Treatment of advanced-stage cancer patients in the high-risk group with molecular-targeted therapy combined with chemoradiotherapy yielded a better survival rate than with only chemoradiotherapy (p = 0.0746). However, treatment of the patients in the low-risk group with the combined therapy resulted in significantly lower survival (p = 0.00283). Functional classification of 70 genes revealed involvement of the angiogenesis pathway, specifically phosphatidylinositol 3-kinase signaling (p = 0.040), extracellular matrix organization (p = 0.0452), and cell adhesion (p = 0.011). The 70-gene signature could predict the prognosis and indicate an optimal therapeutic modality in molecular-targeted therapy or chemotherapy for advanced-stage cervical cancer.

An in-silico approach to study the possible interactions of miRNA between human and SARS-CoV2

BackgroundThe progressive SARS-CoV2 outbreaks worldwide have evoked global investigation. Despite the numerousin-silico approaches, the virus-host relationship remains a serious concern. MicroRNAs are the small non-coding RNAs that help in regulating gene profiling. The current study utilized miRNA prediction tools along with the PANTHER classification system to demonstrate association and sequence similarities shared between miRNAs of SARS-CoV2 and human host. MethodAn in-silico approach was carried out using Vmir analyzer to predict miRNAs from SARS-CoV2 viral genomes. Predicted miRNAs from SARS-CoV2 viral genomes were used for effective hybridization sequence identification along the nucleotide similarities with human miRNAs from miRbase database. Further, it was proceeded to analyze the gene ontology using miRDB with PANTHER classification. ResultBased on the prediction and analysis, we have identified 22 potential miRNAs from five genomes of SARS-CoV2 linked with 12 human miRNAs. Analysis of human miRNAs hsa-mir-1267, hsa-mir-1-3p, hsa-mir-5683 were found shared between all the five viral SARS-CoV2 miRNAs. Further, PANTHER classification analyzed the gene-ontology being carried by these associations showed that 44 genes were involved in biological functions that includes genes specific for signaling pathway, immune complex generation, enzyme binding with effective role in the virus-host relationship. ConclusionOur analysis concludes that the genes identified in this study can be effective in analyzing the virus-host interaction. It also provides a new direction to understand viral pathogenesis with a probable new way to link, that can be used to understand and relate the miRNAs of the virus to the host conditions.

Identification of Candidate Biomarkers for Idiopathic Thrombocytopenic Purpura by Bioinformatics Analysis of Microarray Data.

Idiopathic Thrombocytopenic Purpura (ITP) is a multifactorial disease with decreased count of platelet that can lead to bruising and bleeding manifestations. This study was intended to identify critical genes associated with chronic ITP. The gene expression profile GSE46922 was downloaded from the Gene Expression Omnibus database to recognize Differentially Expressed Genes (DEGs) by R software. Gene ontology and pathway analyses were performed by DAVID. The biological network was constructed using the Cytoscape. Molecular Complex Detection (MCODE) was applied for detecting module analysis. Transcription factors were identified by the PANTHER classification system database and the gene regulatory network was constructed by Cytoscape. One hundred thirty-two DEGs were screened from comparison newly diagnosed ITP than chronic ITP. Biological process analysis revealed that the DEGs were enriched in terms of positive regulation of autophagy and prohibiting apoptosis in the chronic phase. KEGG pathway analysis showed that the DEGs were enriched in the ErbB signaling pathway, mRNA surveillance pathway, Estrogen signaling pathway, and Notch signaling pathway. Additionally, the biological network was established, and five modules were extracted from the network. ARRB1, VIM, SF1, BUB3, GRK5, and RHOG were detected as hub genes that also belonged to the modules. SF1 also was identified as a hub-TF gene. To sum up, microarray data analysis could perform a panel of genes that provides new clues for diagnosing chronic ITP.