Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Revisiting the Zingiberales: Using Multiplexed Exon Capture to Resolve Ancient and Recent Phylogenetic Splits in a Charismatic Plant Lineage

The Zingiberales are an iconic order of monocotyledonous plants comprising eight families with distinctive and diverse floral morphologies and representing an important ecological element of tropical and subtropical forests. While the eight families are demonstrated to be monophyletic, phylogenetic relationships among these families remain unresolved. Neither combined morphological and molecular studies nor recent attempts to resolve family relationships using sequence data from whole plastomes has resulted in a well-supported, family-level phylogenetic hypothesis of relationships. Here we approach this challenge by leveraging the complete genome of one member of the order, Musa acuminata, together with transcriptome information from each of the other seven families to design a set of nuclear loci that can be enriched from highly divergent taxa with a single array-based capture of indexed genomic DNA. A total of 494 exons from 418 nuclear genes were captured for 53 ingroup taxa. The entire plastid genome was also captured for the same 53 taxa. Of the total genes captured, 308 nuclear and 68 plastid genes were used for phylogenetic estimation. The concatenated plastid and nuclear dataset supports the position of Musaceae as sister to the remaining seven families. Moreover, the combined dataset recovers known intra- and inter-family phylogenetic relationships with generally high bootstrap support. This is a flexible and cost effective method that gives the broader plant biology community a tool for generating phylogenomic scale sequence data in non-model systems at varying evolutionary depths

Recent trends in molecular diagnostics of yeast infections : from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside

Indonesian Herb Extracts Inhibit the Replication of Bovine Respiratory Syncytial Virus: In Vitro Study

Bovine respiratory syncytial virus (BRSV) is highly prevalent in cattle. It is a major viral cause of bovine respiratory disease complex, which is associated with morbidity, mortality and substantial economic impact. Currently available treatments are only symptomatic, but no specific treatments are available for BRSV infection. This study aimed to identify new antiviral agents against BRSV, which could be used to control bovine respiratory disease complex in cattle with Indonesian herb extracts. Ethanol extracts prepared from Indonesian herbs including Andrographis paniculata, Phyllanthus niruri, Curcuma aeruginosa, and Curcuma xanthorrhiza were evaluated for anti-BRSV activity in A549 cells. The cytotoxicity of the herb extracts was evaluated using a CCK-8 cell viability assay. Antiviral activities of the herb extracts were examined using cell activity and cytopathic assays. The effect on virus production was evaluated by qRT-PCR and plaque-formation assays. Extracts of Curcuma xanthorrhiza (125 μg/ml), Andrographis paniculata (250 μg/ml), and Phyllanthus niruri (62.5 μg/ml) inhibited BRSV activity in A549 in pre-, simultaneously-, and post-infection treatment assays, respectively, as measured by the selective index. Reduction of BRSV activities by the herb extracts correlated with inhibition of viral gene expression and inhibition of plaque formation in a concentration- and time-dependent manner. Our findings suggest that these herb extracts have sufficient potency to be used not only as a therapeutic agent but also as a preventive agent to limit BRSV infection

Common and Distinct Components in Data Fusion

In many areas of science multiple sets of data are collected pertaining to the same system. Examples are food products which are characterized by different sets of variables, bio-processes which are on-line sampled with different instruments, or biological systems of which different genomics measurements are obtained. Data fusion is concerned with analyzing such sets of data simultaneously to arrive at a global view of the system under study. One of the upcoming areas of data fusion is exploring whether the data sets have something in common or not. This gives insight into common and distinct variation in each data set, thereby facilitating understanding the relationships between the data sets. Unfortunately, research on methods to distinguish common and distinct components is fragmented, both in terminology as well as in methods: there is no common ground which hampers comparing methods and understanding their relative merits. This paper provides a unifying framework for this subfield of data fusion by using rigorous arguments from linear algebra. The most frequently used methods for distinguishing common and distinct components are explained in this framework and some practical examples are given of these methods in the areas of (medical) biology and food science.Comment: 50 pages, 12 figure

Digoxin Inhibits Retinoblastoma through Suppressing a Non-canonical TGFβ Signaling Pathway.

Aims: Retinoblastoma is a childhood ocular tumor rapidly developing from the immature cells of the retina due to loss of functional retinoblastoma protein. Digoxin, a cardiac glycoside, has been reported to be effective in inducing apoptosis, cell cycle arrest, and cytotoxic effects on human cancers. In this regard, the present study aims to investigate whether digoxin could suppress retinoblastoma cancer through the regulation of transforming growth factor-β (TGF-β) signaling pathway. Methodology: The effects of digoxin on Y-79 cells, retinoblastoma cancer cell line, were investigated using MTT (3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazoli-umbromide) and BrdU (bromodeoxyuridine) assays to measure cellular cytotoxicity effects and cell apoptosis, respectively. Also, a qPCR assay was employed to analyze the mRNA expression levels of TGFβ signaling pathway including C-MYC, P21, P15, TGFβRI, TGFβRII, and SMAD2, 3, and 4 genes. Results: The results of the cell function assays revealed that digoxin inhibited the cell viability and proliferation of Y-79 cells. In addition, it was found that digoxin significantly suppressed C-MYC expression and enhanced the expression of P21, P15, SMAD2 and SMAD4 genes in a dose-and time-dependent manner. However, the obtained results could not detect any significant effect of digoxin on TGFβRI, TGFβRII and SMAD3 genes. Conclusion: Taken together, the findings of the present study suggest that digoxin could be a potential therapeutic agent in the treatment of retinoblastoma by regulating the cell cycle genes via a non-canonical TGF-β signaling pathway

Comparison of codon usage measures and their applicability in prediction of microbial gene expressivity

BACKGROUND: There are a number of methods (also called: measures) currently in use that quantify codon usage in genes. These measures are often influenced by other sequence properties, such as length. This can introduce strong methodological bias into measurements; therefore we attempted to develop a method free from such dependencies. One of the common applications of codon usage analyses is to quantitatively predict gene expressivity. RESULTS: We compared the performance of several commonly used measures and a novel method we introduce in this paper – Measure Independent of Length and Composition (MILC). Large, randomly generated sequence sets were used to test for dependence on (i) sequence length, (ii) overall amount of codon bias and (iii) codon bias discrepancy in the sequences. A derivative of the method, named MELP (MILC-based Expression Level Predictor) can be used to quantitatively predict gene expression levels from genomic data. It was compared to other similar predictors by examining their correlation with actual, experimentally obtained mRNA or protein abundances. CONCLUSION: We have established that MILC is a generally applicable measure, being resistant to changes in gene length and overall nucleotide composition, and introducing little noise into measurements. Other methods, however, may also be appropriate in certain applications. Our efforts to quantitatively predict gene expression levels in several prokaryotes and unicellular eukaryotes met with varying levels of success, depending on the experimental dataset and predictor used. Out of all methods, MELP and Rainer Merkl's GCB method had the most consistent behaviour. A 'reference set' containing known ribosomal protein genes appears to be a valid starting point for a codon usage-based expressivity prediction

Aquaglyceroporins are differenctially expressed in beige and white adipocytes

Browning of white adipocytes has been proposed as a powerful strategy to overcome metabolic complications, since brown adipocytes are more catabolic, expending energy as a heat form. However, the biological pathways involved in the browning process are still unclear. Aquaglyceroporins are a sub-class of aquaporin water channels that also permeate glycerol and are involved in body energy homeostasis. In the adipose tissue, aquaporin-7 (AQP7) is the most representative isoform, being crucial for white adipocyte fully differentiation and glycerol metabolism. The altered expression of AQP7 is involved in the onset of obesity and metabolic disorders. Herein, we investigated if aquaglyceroporins are implicated in beige adipocyte differentiation, similar to white cells. Thus, we optimized a protocol of murine 3T3-L1 preadipocytes browning that displayed increased beige and decreased white adipose tissue features at both gene and protein levels and evaluated aquaporin expression patterns along the differentiation process together with cellular lipid content. Our results revealed that AQP7 and aquaporin-9 (AQP9) expression was downregulated throughout beige adipocyte differentiation compared to white differentiation, which may be related to the beige physiological role of heat production from oxidative metabolism, contrasting with the anabolic/catabolic lipid metabolism requiring glycerol gateways occurring in white adipose cells