A new approach based on targeted pooled DNA sequencing identifies novel mutations in patients with Inherited Retinal Dystrophies

Inherited retinal diseases (IRD) are a heterogeneous group of diseases that mainly affect the retina; more than 250 genes have been linked to the disease and more than 20 different clinical phenotypes have been described. This heterogeneity both at the clinical and genetic levels complicates the identification of causative mutations. Therefore, a detailed genetic characterization is important for genetic counselling and decisions regarding treatment. In this study, we developed a method consisting on pooled targeted next generation sequencing (NGS) that we applied to 316 eye disease related genes, followed by High Resolution Melting and copy number variation analysis. DNA from 115 unrelated test samples was pooled and samples with known mutations were used as positive controls to assess the sensitivity of our approach. Causal mutations for IRDs were found in 36 patients achieving a detection rate of 31.3%. Overall, 49 likely causative mutations were identified in characterized patients, 14 of which were first described in this study (28.6%). Our study shows that this new approach is a cost-effective tool for detection of causative mutations in patients with inherited retinopathies.This work was supported by grants from the National Institute of Health Carlos III (Institute of Health Carlos III/ISCIII) (CP10/00572, PI13/02621 and RD16/0008/0027 to JRE, PI17/01413 to CI, and a Research Intensification Contract to ALdM); the Basque Government's Industry Department (SAIOTEK: SAIO11-PE11BN002; and SAIO12-PC12BN001 to JRE), a grant from the Mutua Madrilena Foundation and support from the Retinitis Pigmentosa Patients of Gipuzkoa Foundation (BEGISARE). JR-E is a Miguel Servet II Fellow, National Institute of Health Carlos III (ISCIII). MEI was supported by grants from the Basque Government's Department of Education (DEDUC14/309). OB is supported by funding from the Retinitis Pigmentosa Patients of Gipuzkoa Foundation (BEGISARE) and a grant from the Mutua Madrilena Foundation. AA was supported by grants from the Fundacion Jesus de Gangoiti Barrera and from the Basque Government's Departments of Industry and Education (SAIOTEK-11BN002/PC12BN001/DEPLC13/002). CI is partially supported by a Research Intensification Contract (INTBIO15/001). The authors are grateful to Xabier Elcoroaristizabal and Marta Fernandez-Mercado for their helpful advice on developing the base-calling setup. Maribel Gomez; Naiara Telletxea and Nahikari Pastoriza at the Basque Biobank for isolating DNA samples; and Dr. Carmen Ayuso for kindly providing control samples. We also give special thanks to all patients with IRD and their families involved in the study

The use of mixed collagen-Matrigel matrices of increasing complexity recapitulates the biphasic role of cell adhesion in cancer cell migration: ECM sensing, remodeling and forces at the leading edge of cancer invasion

The migration of cancer cells is highly regulated by the biomechanical properties of their local microenvironment. Using 3D scaffolds of simple composition, several aspects of cancer cell mechanosensing (signal transduction, EMC remodeling, traction forces) have been separately analyzed in the context of cell migration. However, a combined study of these factors in 3D scaffolds that more closely resemble the complex microenvironment of the cancer ECM is still missing. Here, we present a comprehensive, quantitative analysis of the role of cell-ECM interactions in cancer cell migration within a highly physiological environment consisting of mixed Matrigel-collagen hydrogel scaffolds of increasing complexity that mimic the tumor microenvironment at the leading edge of cancer invasion. We quantitatively show that the presence of Matrigel increases hydrogel stiffness, which promotes ß1 integrin expression and metalloproteinase activity in H1299 lung cancer cells. Then, we show that ECM remodeling activity causes matrix alignment and compaction that favors higher tractions exerted by the cells. However, these traction forces do not linearly translate into increased motility due to a biphasic role of cell adhesions in cell migration: at low concentration Matrigel promotes migration-effective tractions exerted through a high number of small sized focal adhesions. However, at high Matrigel concentration, traction forces are exerted through fewer, but larger focal adhesions that favor attachment yielding lower cell motility

Muscular and tendon degeneration after achilles rupture: new insights into future repair strategies

Achilles tendon rupture is a frequent injury with an increasing incidence. After clinical surgical repair, aimed at suturing the tendon stumps back into their original position, the repaired Achilles tendon is often plastically deformed and mechanically less strong than the pre-injured tissue, with muscle fatty degeneration contributing to function loss. Despite clinical outcomes, pre-clinical research has mainly focused on tendon structural repair, with a lack of knowledge regarding injury progression from tendon to muscle and its consequences on muscle degenerative/regenerative processes and function. Here, we characterize the morphological changes in the tendon, the myotendinous junction and muscle belly in a mouse model of Achilles tendon complete rupture, finding cellular and fatty infiltration, fibrotic tissue accumulation, muscle stem cell decline and collagen fiber disorganization. We use novel imaging technologies to accurately relate structural alterations in tendon fibers to pathological changes, which further explain the loss of muscle mechanical function after tendon rupture. The treatment of tendon injuries remains a challenge for orthopedics. Thus, the main goal of this study is to bridge the gap between clinicians'' knowledge and research to address the underlying pathophysiology of ruptured Achilles tendon and its consequences in the gastrocnemius. Such studies are necessary if current practices in regenerative medicine for Achilles tendon ruptures are to be improved

ABCA4 c.6480-35A>G, a novel branchpoint variant associated with Stargardt disease

Introduction: Inherited retinal dystrophies (IRDs) can be caused by variants in more than 280 genes. The ATP-binding cassette transporter type A4 (ABCA4) gene is one of these genes and has been linked to Stargardt disease type 1 (STGD1), fundus flavimaculatus, cone–rod dystrophy (CRD), and pan-retinal CRD. Approximately 25% of the reported ABCA4 variants affect RNA splicing. In most cases, it is necessary to perform a functional assay to determine the effect of these variants.Methods: Whole genome sequencing (WGS) was performed in one Spanish proband with Stargardt disease. The putative pathogenicity of c.6480-35A>G on splicing was investigated both in silico and in vitro. The in silico approach was based on the deep-learning tool SpliceAI. For the in vitro approach we used a midigene splice assay in HEK293T cells, based on a previously established wild-type midigene (BA29) containing ABCA4 exons 46 to 48. Through the analysis of WGS data, we identified two candidate variants in ABCA4 in one proband: a previously described deletion, c.699_768+342del (p.(Gln234Phefs*5)), and a novel branchpoint variant, c.6480-35A>G. Segregation analysis confirmed that the variants were in trans. For the branchpoint variant, SpliceAI predicted an acceptor gain with a high score (0.47) at position c.6480-47. A midigene splice assay in HEK293T cells revealed the inclusion of the last 47 nucleotides of intron 47 creating a premature stop codon and allowed to categorize the variant as moderately severe. Subsequent analysis revealed the presence of this variant as a second allele besides c.1958G>A p.(Arg653His) in an additional Spanish proband in a large cohort of IRD cases.Conclusion: A splice-altering effect of the branchpoint variant, confirmed by the midigene splice assay, along with the identification of this variant in a second unrelated individual affected with STGD, provides sufficient evidence to classify the variant as likely pathogenic. In addition, this research highlights the importance of studying non-coding regions and performing functional assays to provide a conclusive molecular diagnosis

Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis

Microfluidic devices are becoming mainstream tools to recapitulate in vitro the behavior of cells and tissues. In this study, we use microfluidic devices filled with hydrogels of mixed collagen-Matrigel composition to study the migration of lung cancer cells under different cancer invasion microenvironments. We present the design of the microfluidic device, characterize the hydrogels morphologically and mechanically and use quantitative image analysis to measure the migration of H1299 lung adenocarcinoma cancer cells in different experimental conditions. Our results show the plasticity of lung cancer cell migration, which turns from mesenchymal in collagen only matrices, to lobopodial in collagen-Matrigel matrices that approximate the interface between a disrupted basement membrane and the underlying connective tissue. Our quantification of migration speed confirms a biphasic role of Matrigel. At low concentration, Matrigel facilitates migration, most probably by providing a supportive and growth factor retaining environment. At high concentration, Matrigel slows down migration, possibly due excessive attachment. Finally, we show that antibody-based integrin blockade promotes a change in migration phenotype from mesenchymal or lobopodial to amoeboid and analyze the effect of this change in migration dynamics, in regards to the structure of the matrix. In summary, we describe and characterize a robust microfluidic platform and a set of software tools that can be used to study lung cancer cell migration under different microenvironments and experimental conditions. This platform could be used in future studies, thus benefitting from the advantages introduced by microfluidic devices: precise control of the environment, excellent optical properties, parallelization for high throughput studies and efficient use of therapeutic drugs.We would like to acknowledge the support of the Spanish Ministry of Economy and Competitiveness, under grants number DPI2012-38090-C03-02 and DPI2015-64221-C2-2-R (COS), TEC2013-48552-C2-1-R, TEC2016-78052-R, TEC2015-73064-EXP (AMB) and the Torres Quevedo program PTQ-11-04778 (RP); the Spanish Ministry of Health (FIS PI13/02313) (AR); the Czech Science Foundation, under grant number 302/12/G157 (MK, MMaška); and the European Research Council (ERC) through project ERC-2012-StG 306751 (JMGA)

Population-based multicase-control study in common tumors in Spain (MCC-Spain): rationale and study design

Introduction: We present the protocol of a large population-based case-control study of 5 common tumors in Spain (MCC-Spain) that evaluates environmental exposures and genetic factors. Methods: Between 2008-2013, 10,183 persons aged 20-85 years were enrolled in 23 hospitals and primary care centres in 12 Spanish provinces including 1,115 cases of a new diagnosis of prostate cancer, 1,750 of breast cancer, 2,171 of colorectal cancer, 492 of gastro-oesophageal cancer, 554 cases of chronic lymphocytic leukaemia (CLL) and 4,101 population-based controls matched by frequency to cases by age, sex and region of residence. Participation rates ranged from 57% (stomach cancer) to 87% (CLL cases) and from 30% to 77% in controls. Participants completed a face-to-face computerized interview on sociodemographic factors, environmental exposures, occupation, medication, lifestyle, and personal and family medical history. In addition, participants completed a self-administered food-frequency questionnaire and telephone interviews. Blood samples were collected from 76% of participants while saliva samples were collected in CLL cases and participants refusing blood extractions. Clinical information was recorded for cases and paraffin blocks and/or fresh tumor samples are available in most collaborating hospitals. Genotyping was done through an exome array enriched with genetic markers in specific pathways. Multiple analyses are planned to assess the association of environmental, personal and genetic risk factors for each tumor and to identify pleiotropic effects. Discussion: This study, conducted within the Spanish Consortium for Biomedical Research in Epidemiology & Public Health (CIBERESP), is a unique initiative to evaluate etiological factors for common cancers and will promote cancer research and prevention in Spain.The study was partially funded by the “Accion Transversal del Cancer”, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI08/0533, PI08/1359, PS09/00773, PS09/01286, PS09/01903, PS09/02078, PS09/01662, PI11/01403, PI11/01889, PI11/00226, PI11/01810, PI11/02213, PI12/00488, PI12/00265, PI12/01270, PI12/00715, PI12/00150), by the Fundación Marqués de Valdecilla (API 10/09), by the ICGC International Cancer Genome Consortium CLL, by the Junta de Castilla y León (LE22A10-2), by the Consejería de Salud of the Junta de Andalucía (PI-0571), by the Conselleria de Sanitat of the Generalitat Valenciana (AP 061/10), by the Recercaixa (2010ACUP 00310), by the Regional Government of the Basque Country by European Commission grants FOOD-CT- 2006-036224-HIWATE, by the Spanish Association Against Cancer (AECC) Scientific Foundation, by the The Catalan Government DURSI grant 2009SGR1489

The Cell Tracking Challenge: 10 years of objective benchmarking

The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a signifcant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset repository with new datasets that increase its diversity and complexity, and the creation of a silver standard reference corpus based on the most competitive results, which will be of particular interest for data-hungry deep learning-based strategies. Furthermore, we present the up-to-date cell segmentation and tracking leaderboards, an in-depth analysis of the relationship between the performance of the state-of-the-art methods and the properties of the datasets and annotations, and two novel, insightful studies about the generalizability and the reusability of top-performing methods. These studies provide critical practical conclusions for both developers and users of traditional and machine learning-based cell segmentation and tracking algorithms.Web of Science2071020101