Data on corneal proteome and differentially expressed corneal proteins in highly myopic chicks using a data independent quantification approach.
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ABSTRACT:
SUBMITTER: Kang BS
PROVIDER: S-EPMC6811982 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The retina plays an important regulatory role in ocular growth. To screen for new retinal candidate genes that could be involved in the inhibition of ocular growth, we used chick microarrays to analyze the changes in retinal mRNA expression after myopic defocus was imposed by positive lens-wear. Chicks were raised under a 12h-light/12h-dark cycle (light-onset: 8:00 am and light-offset: 8:00 pm) with unrestricted access to water and food. On the day prior to the experiment, velcro rings were glued to the feathers around the eye under diethylether anaesthesia. Four male white leghorn chicks, aged 9 days, wore +6.9D spectacle lenses over both eyes for 24 hours. Four untreated age-matched male chicks from the same batch served as controls. After decapitation of the chicks, the eyes were enucleated and the retina was prepared. The retinae from both eyes of each chick were pooled for RNA isolation. Keywords: gene expression comparison
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Project description:Data-independent acquisition (DIA) strategies provide a sensitive and reproducible alternative to data-dependent acquisition (DDA) methods for large-scale quantitative proteomic analyses. Unfortunately, DIA methods suffer from incompatibility with common multiplexed quantification methods, specifically stable isotope labeling approaches such as isobaric tags and stable isotope labeling of amino acids in cell culture (SILAC). Here we expand the use of neutron-encoded (NeuCode) SILAC to DIA applications (NeuCoDIA), producing a strategy that enables multiplexing within DIA scans without further convoluting the already complex MS(2) spectra. We demonstrate duplex NeuCoDIA analysis of both mixed-ratio (1:1 and 10:1) yeast and mouse embryo myogenesis proteomes. Analysis of the mixed-ratio yeast samples revealed the strong accuracy and precision of our NeuCoDIA method, both of which were comparable to our established MS(1)-based quantification approach. NeuCoDIA also uncovered the dynamic protein changes that occur during myogenic differentiation, demonstrating the feasibility of this methodology for biological applications. We consequently establish DIA quantification of NeuCode SILAC as a useful and practical alternative to DDA-based approaches.
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Project description:PurposeThe retina plays an important regulatory role in ocular growth. To screen for new retinal candidate genes that could be involved in the inhibition of ocular growth, we used chick microarrays to analyze the changes in retinal mRNA expression after myopic defocus was imposed by positive lens wear.MethodsFour male white leghorn chicks, aged nine days, wore +6.9D spectacle lenses over both eyes for 24 h. Four untreated age-matched male chicks from the same batch served as controls. The chicks were euthanized, and retinas from both eyes of each chick were pooled. RNA was isolated and labeled cRNA was prepared. These samples were hybridized to Affymetrix GeneChip Chicken Genome arrays with more than 28,000 characterized genes. After comparison of multiple normalization methods, GC-RMA and a false-discovery rate of 6% was chosen for normalization of the data. The expression of 16 candidate genes was further studied, using semiquantitative real-time RT-PCR. In addition, the expression of the mRNA of some of these candidate genes was assessed in chicks that wore either +6.9D lenses for 4 h or -7D lenses for 24 h.Results123 transcripts were found to be differentially expressed (p<0.05; at least 1.5-fold change in expression level), with an absolute mean fold-change of 1.97+/-1.16 (mean+/-standard deviation). Nine of the sixteen genes that were examined by real-time RT-PCR were validated. Regardless of whether positive or negative lenses were worn, six of these nine genes were regulated in the same direction after 24 h: arginyltransferase 1 (ATE1), E74-like factor 1 (ELF1), growth factor receptor-bound protein 2 (GRB2), SHQ1 homolog (S. cerevisiae) (SHQ1), spectrin, beta, non-erythrocytic 1 (SPTBN1), prepro-urotensin II-related peptide (pp-URP). Three genes responded differently to positive and negative lens treatment after 24 h: ATP-binding cassette, sub-family C, member 10 (ABCC10), CD226 molecule (CD226) and oxysterol binding protein 2 (OSBP2).ConclusionsThe validated genes that were regulated only by myopic defocus may represent elements in a pathway generating a "stop-signal" for eye growth. Some of the genes identified in this study have so far not been described in the retina. Further investigation of their function may improve the understanding of the signaling cascades in emmetropization. More general, published microarray data are variable among different animal models (mouse, chick, monkeys), tissues (retina, retina/retinal pigment epithelium), treatments (diffusers, lenses, lid-suture), as well as different treatment durations (hours, days), and comparisons remain difficult. That only a small number of common genes were found emphasizes the need for careful normalization of the experimental parameters.
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Project description:BackgroundThinning of the choroid has been linked with various ocular diseases, including high myopia (HM), which can lead to visual impairment. Although various artificial intelligence (AI) algorithms have been developed to quantify choroidal thickness (ChT), few patients with HM were included in their development. The choroid in patients with HM tends to be thinner than that of normal patients, making it harder to segment. Therefore, in this study, we aimed to develop and implement a novel deep learning algorithm based on a group-wise context selection network (GCS-Net) to automatically segment the choroid and quantify its thickness on swept-source optical coherence tomography (SS-OCT) images of HM patients.MethodsA total of 720 SS-OCT images were obtained from 40 HM eyes and 20 non-HM eyes and were used to develop a GCS-Net to segment the choroid. The intersection-over-union (IoU), Dice similarity coefficient (DSC), sensitivity, and specificity were used to assess the performance in relation to manually segmented ground truth. The independent test dataset included 3,192 images from 266 HM eyes. The ChT in the test dataset was measured manually and automatically at 9 different regions within the choroid. The average difference in the ChT between the 2 methods was calculated. The intraclass correlation coefficient (ICC) was calculated to evaluate the agreement between the 2 measurements.ResultsOur method reached an IoU, DSC, sensitivity, and specificity of 87.89%, 93.40%, 92.42%, and 99.82% in HM, respectively. The average difference in the ChT between the 2 measurements was 5.54±4.57 µm. The ICC was above 0.90 (P<0.001) for all regions of the choroid, indicating a very high level of agreement.ConclusionsThe GCS-Net proposed in our study provides a reliable and fast tool to quantify ChT in HM patients and could potentially be used as a tool for monitoring ChT in ocular diseases related to the choroid.
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