Variants in STXBP3 are Associated with Very Early Onset Inflammatory Bowel Disease, Bilateral Sensorineural Hearing Loss and Immune Dysregulation

Background and aims: Very early onset inflammatory bowel disease [VEOIBD] is characterized by intestinal inflammation affecting infants and children less than 6 years of age. To date, over 60 monogenic aetiologies of VEOIBD have been identified, many characterized by highly penetrant recessive or dominant variants in underlying immune and/or epithelial pathways. We sought to identify the genetic cause of VEOIBD in a subset of patients with a unique clinical presentation. Methods: Whole exome sequencing was performed on five families with ten patients who presented with a similar constellation of symptoms including medically refractory infantile-onset IBD, bilateral sensorineural hearing loss and, in the majority, recurrent infections. Genetic aetiologies of VEOIBD were assessed and Sanger sequencing was performed to confirm novel genetic findings. Western analysis on peripheral blood mononuclear cells and functional studies with epithelial cell lines were employed. Results: In each of the ten patients, we identified damaging heterozygous or biallelic variants in the Syntaxin-Binding Protein 3 gene [STXBP3], a protein known to regulate intracellular vesicular trafficking in the syntaxin-binding protein family of molecules, but not associated to date with either VEOIBD or sensorineural hearing loss. These mutations interfere with either intron splicing or protein stability and lead to reduced STXBP3 protein expression. Knock-down of STXBP3 in CaCo2 cells resulted in defects in cell polarity. Conclusion: Overall, we describe a novel genetic syndrome and identify a critical role for STXBP3 in VEOIBD, sensorineural hearing loss and immune dysregulation.info:eu-repo/semantics/publishedVersio

Nutritional and Metabolic Requirements for the Infection of HeLa Cells by Salmonella enterica Serovar Typhimurium

Salmonella is the causative agent of a spectrum of human and animal diseases ranging from gastroenteritis to typhoid fever. It is a food - and water - borne pathogen and infects via ingestion followed by invasion of intestinal epithelial cells and phagocytic cells. In this study we employed a mutational approach to define the nutrients and metabolic pathways required by Salmonella enterica serovar Typhimurium during infection of a human epithelial cell line (HeLa). We deleted the key glycolytic genes, pfkA and pfkB to show that S. Typhimurium utilizes glycolysis for replication within HeLa cells; however, glycolysis was not absolutely essential for intracellular replication. Using S. Typhimurium strains deleted for genes encoding components of the phosphotransferase system and glucose transport, we show that glucose is a major substrate required for the intracellular replication of S. Typhimurium in HeLa cells. We also deleted genes encoding enzymes involved in the utilization of gluconeogenic substrates and the glyoxylate shunt and show that neither of these pathways were required for intracellular replication of S. Typhimurium within HeLa cells

Targeted Gene Panel Sequencing for Early-onset Inflammatory Bowel Disease and Chronic Diarrhea

Background: In contrast to adult-onset inflammatory bowel disease (IBD), where many genetic loci have been shown to be involved in complex disease etiology, early-onset IBD (eoIBD) and associated syndromes can sometimes present as monogenic conditions. As a result, the clinical phenotype and ideal disease management in these patients often differ from those in adult-onset IBD. However, due to high costs and the complexity of data analysis, high-throughput screening for genetic causes has not yet become a standard part of the diagnostic work-up of eoIBD patients. Methods: We selected 28 genes of interest associated with monogenic IBD and performed targeted panel sequencing in 71 patients diagnosed with eoIBD or early-onset chronic diarrhea to detect causative variants. We compared these results to whole-exome sequencing (WES) data available for 25 of these patients. Results: Target coverage was significantly higher in the targeted gene panel approach compared with WES, whereas the cost of the panel was considerably lower (approximately 25% of WES). Disease-causing variants affecting protein function were identified in 5 patients (7%), located in genes of the IL10 signaling pathway (3), WAS (1), and DKC1 (1). The functional effects of 8 candidate variants in 5 additional patients (7%) are under further investigation. WES did not identify additional causative mutations in 25 patients. Conclusions: Targeted gene panel sequencing is a fast and effective screening method for monogenic causes of eoIBD that should be routinely established in national referral centers.info:eu-repo/semantics/publishedVersio

Wastewater-Based Epidemiology: Global Collaborative to Maximize Contributions in the Fight against COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), a novel member of the Coronaviridae family, has been identified as the etiologic agent of an ongoing pandemic of severe pneumonia known as COVID-19. To date there have been millions of cases of COVID-19 diagnosed in 184 countries with case fatality rates ranging from 1.8% in Germany to 12.5% in Italy. Limited diagnostic testing capacity and asymptomatic and oligosymptomatic infections result in significant uncertainty in the estimated extent of SARS-CoV-2 infection. Recent reports have documented that infection with SARS-CoV-2 is accompanied by persistent shedding of virus RNA in feces in 27% to 89% of patients at densities from 0.8 to 7.5 log10 gene copies per gram. The presence of SARS-CoV-2 RNA in feces raises the potential to survey sewage for virus RNA to inform epidemiological monitoring of COVID-19, which we refer to as wastewater-based epidemiology (WBE), but is also known as environmental surveillance

Biomarkers in search of Precision Medicine in IBD

The completion of the human genome project in 2003 represented a major scientific landmark, ushering in a new era with hopes and expectations of fresh insights into disease mechanisms and treatments. In inflammatory bowel disease (IBD), many important discoveries soon followed, notably the identification of >200 genetic susceptibility loci and characterization of the gut microbiome. As “big data”, driven by advances in technology, becomes increasingly available and affordable, individuals with IBD and clinicians alike yearn for tangible outcomes from the promise of “precision medicine”—precise diagnosis, monitoring, and treatment. Here, we provide a commentary on the prospects and challenges of precision medicine and biomarkers in IBD. We focus on the three key areas where precision IBD will have the most impact: (1) disease susceptibility, activity, and behavior; (2) prediction of drug response and adverse effects; and (3) identification of subphenotypic mechanisms to facilitate drug discovery and selection of new treatments in IBD

Principal component analysis of multispectral images

Analiza zdjęć wielospektralnych sprowadza się często do modelowania matematycznego opartego o wielowymiarowe przestrzenie metryczne, w których umieszcza się pozyskane za pomocą sensorów dane. Tego typu bardzo intuicyjne, łatwe do zaaplikowania w algorytmice analizy obrazu postępowanie może skutkować zupełnie niepotrzebnym wzrostem niezbędnej do analiz zdjęć mocy obliczeniowej. Jedną z ogólnie przyjętych grup metod analizy zbiorów danych tego typu są metody analizy czynnikowej. Wpracy tej prezentujemy dwie z nich: Principal Component Analysis (PCA) oraz Simplex Shrink-Wrapping (SSW). Użyte jednocześnie obniżają znacząco wymiar zadanej przestrzeni metrycznej pozwalając odnaleźć w danych wielospektralnych charakterystyczne składowe, czyli przeprowadzić cały proces detekcji fotografowanych obiektów. W roku 2014 w Pracowni Przetwarzania Danych Instytutu Lotnictwa oraz Zakładzie Ochrony Lasu Instytutu Badawczego Leśnictwa metodykę tą równie skutecznie przyjęto dla analizy dwóch niezwykle różnych serii zdjęć wielospektralnych: detekcji głównych składowych powierzchni Marsa (na podstawie zdjęć wielospektralnych pozyskanych w ramach misji EPOXI, NASA) oraz oszacowania bioróżnorodności jednej z leśnych powierzchni badawczych projektu HESOFF.Mostly, analysis of multispectral images employs mathematical modeling based on multidimensional metric spaces that includes collected by the sensors data. Such an intuitive approach easily applicable to image analysis applications can result in unnecessary computing power increase required by this analysis. One of the groups of generally accepted methods of analysis of data sets are factor analysis methods. Two such factor analysis methods are presented in this paper, i.e. Principal Component Analysis (PCA ) and Simplex Shrink - Wrapping (SSW). If they are used together dimensions of a metric space can be reduced significantly allowing characteristic components to be found in multispectral data, i.e. to carry out the whole detection process of investigated images. In 2014 such methodology was adopted by Data Processing Department of the Institute of Aviation and Division of Forest Protection of Forest Research Institute for the analysis of the two very different series of multispectral images: detection of major components of the Mars surface (based on multispectral images obtained from the epoxy mission, NASA) and biodiversity estimation of one of the investigated in the HESOFF project forest complexes

Estimation of tree species diversity of forest stands based on their spectral reflectance

Evaluation of the forest landscape diversity was investigated based on the multispectral aerial images using iterative Principal Component Analysis (PCA) methodology. In 2014, we carried out several photogrammetric flights over the experimental plots establish in the Krotoszyn Plateau (central Poland) documenting the vegetation cycle of forest stands dominated by oaks. Aerial photos of the spatial resolution about 25 cm of forest area in Karczma Borowa Forest District in the range of visible light (460−650 nm) and near infrared (700−930 nm) were collected by multispectral Quercus 6 platform placed on the aircraft. The aim of the study was to evaluate the diversity of forest vegetation cover using remote sensing data based on spectral signatures of plants without complete classification of fractional vegetation cover and species identification in the field. Recursive PCA on data collection from the multispectral images helped to determine with the semi−automatic mode the number of land cover classes, including the classes of vegetation. Based on the radiometric data, the separation of inorganic matter from vegetation and diversity indicators of forest stands on the image area were evaluated. With the PCA method, along the most volatile vectors, the first division into land cover classes of vegetation was conducted. As a result of the first iteration of PCA, three classes of vegetation: deciduous trees, conifers and forest undergrowth was determined. In the second iteration, classes of forest vegetation were separated and interpreted as the area dominated by a single species of tree or shrub. The second iteration divided the deciduous plant image area in plots dominated by English oak stands with an admixture of birch and red oak. Based on the number of pixels in classes representing individual plant species, Shannon−Wiener (H) and Simpson (D) diversity indices were determined. By described methodology, it was found that the differences between the H and D indices for the imagery area after the first and second PCA iteration were small. The relevance of performing successive iterations of PCA analysis, and thus the full identification of species, in the context of diversity calculation should be the subject of further study