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Early prediction of inflammation by unprecedented unbiased linking of tissue molecular composition and structure

ABSTRACT: The identification of molecular signatures that aid early diagnosis of complex tissue pathologies, such as inflammatory diseases, poses a major scientific and clinical challenge due to their genetic and phenotypic heterogeneity. We have been able to unprecedentedly discover a distinct tissue state occurring before the onset of inflammatory clinical symptoms by integrating quantitative proteomics with advanced microscopy analyses. Through monitoring colonic extracellular matrix (ECM) remodeling in colitis animal models we have unexpectedly revealed that pre-symptomatic tissues display a unique ECM signature in terms of molecular composition, morphology and stiffness. By applying advanced computational analyses we were able to project quantitative proteomics data onto an axis correlating with spatially resolved tissue damage originating from the ECM. These results bridge the gap between tissue structure and composition while outlining the predictive power of the cellular microenvironment in early diagnostics of inflammatory diseases.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Colon

SUBMITTER: Tamar Geiger

LAB HEAD: Dr. Tamar Geiger

PROVIDER: PXD004740 | Pride | 2020-12-01

REPOSITORIES: Pride

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Project description:The periodontium are the tissues supporting and investing the tooth and consists of the periodontal ligament, the gingiva, the root cementum, and the alveolar bone. The functions of the cell populations in health and disease regarding the host-mediated tissue destruction are not well understood. To get a first idea, of which genes might play a distinct role in chronic periodontal disease in vivo, we compared the genom-wide gene expressions of chronic inflamed and healthy periodontal ligament cells by microarray analysis and validated the data by real-time RT-PCR. The expression rates of 14.239 genes were investigated and 3.018 of them were found differentially expressed by at least two-fold, the expression rates of 1.451 genes were significantly up-regulated and the expression rates of 1.567 genes were significantly down-regulated in inflamed PDL cells. We focused on mainly structural components, for example, laminins and integrins, as well as degrading enzymes, for example, MMPs and cathepsins. The molecular composition of the laminin network varies in chronic inflamed compared to healthy PDL cells in vivo. Furthermore, integrin alpha6beta4, together with laminin-332, might be involved in chronic periodontal inflammation. Findings that diverse keratins were upregulated in chronic disease indicate that the epithelial cell rests of Malassez might also be involved in chronic periodontal inflammation. Also cathepsin B and cathepsin C might participate in the connective tissue destruction. The microarray analysis has identified a profile of genes potentially involved in chronic periodontal inflammation in vivo. Further studies are needed to entirely understand cellular activities during chronic periodontal inflammation in vivo. Experiment Overall Design: Periodontal tissue was collected from 32 patients at the Dental Medical School of the University of Goettingen (12 men, 20 women, aged between 18 and 72 years) from March 2005 to Dezember 2005. The tissue probes were taken from teeth, either extracted for orthodontic reasons (healthy periodontium) or because of chronic periodontal lesions. The differentiation between both collectives was performed using clinical and radiological parameters (clinical attachment loss, increase in probing depth, and radiographic bone loss). A detailed anamnesis of each patient was explored. All patients were without a medical history and were not on medication. In addition, the tissue samples used in our study were only taken from non-smokers. The extracted teeth were immediately frozen and stored at -80Â°C. All patients who participated in the study were informed about the nature and aim of this project and gave their written informed consent. The study was approved according to the regulations of the Ethics Committee of the Medical Faculty of the University of Goettingen.

Project description:Our modern era is witnessing an increasing infertility rate worldwide. Although some of the causes can be attributed to our modern lifestyle (eg. persistent organic polluants, late pregnancy), our knowledge of the human ovarian tissue has remained limited and insufficient to reverse the infertility statistics. Indeed, all efforts have been focused on the endocrine and cellular function in support of the cell theory that dates back to the 18th century, while the human ovarian matrisome is still under-described. Therefore, hereby we provide the first systematic study focusing on the human ovarian matrisome and its remodeling during a woman lifetime, from prepuberty til menopause. We apply our matrisome tailored fractionation method, the DC-MaP strategy and mass spectrometry-based quantitative proteomics using TMT pro 16-plex isobaric labeling to delineate proteome-wide and ECM-specific shifts between prepubertal, reproductive-age and menopausal stages. Post-translational modifications, namely proline hydroxylation and advanced glycation ends products have also been detected at different intensities according to age. Matrisome age-biomarkers have been validated with lightsheet microscopy-based-3D imaging, following immunofluorescence and tissue clearing with an ovary-tailored protocol. We used machine learning and statistics to build a neural network that can predict predict the probability of a specific ovarian tissue matrisome to resemble to prepubertal, reproductive-age or menopausal tissue and potentially conclude its fertility potency or evaluate in the future the efficiency of ovarian rejuvenation treatments. We also used NLP medscan technology for advanced literature text-mining to predict all possible-connections between the extra- and intra-cellular compartments and how chemo-radiotherapy, known for its gonadotoxicity can also affect key matrisome proteins.This comprehensive proteomics analysis represents the ovarian proteomic codex and contributes to an improved understanding of the critical roles that ECM plays throughout ovarian life span. By publishing our proteomic data, we hope to open new avenues in fertility restoration, ovarian rejuvenation and reproductive tissue engineering

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Early prediction of inflammation by unprecedented unbiased linking of tissue molecular composition and structure

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