New iFlpMosaics Toolkit Enhances Gene Research and Disease Insights

A team at the Centro Nacional de Investigaciones Cardiovasculares (CNIC) has developed a comprehensive set of innovative genetic tools and mouse lines, called iFlpMosaics, designed to enhance the study of gene function and its implications in health and disease.

The groundbreaking study, led by Dr. Rui Benedito and published in Nature Methods, presents a pioneering approach that overcomes critical limitations of existing methods for generating genetic mosaics. These innovations will enable scientists to more accurately investigate the effects of somatic mutations on cellular biology and disease.

The study highlights the iFlpMosaics toolkit's utility across different experimental setups, detailing how it allows scientists to track the effects of single or multiple gene deletions within the same tissue. This advance opens the way to deeper insight into the function of genes in cell biology, regeneration, and disease.

Understanding gene function is pivotal for the progress of biomedical research. Traditional biomedical genetic studies compare cells from distinct mutant and control animals, a method that often fails to account for the differing epigenetic landscapes and tissue microenvironments within each animal. "This disparity can lead to confusing results, complicating the interpretation of gene function," explained Dr. Benedito.

The iFlpMosaics toolkit is unburdened by these shortcomings and allows researchers to induce genetic mosaics with high throughput and precision, making it easier to study cell-autonomous gene function directly within the same organism.

Our work with these new genetic tools highlights the importance of generating genetic mosaics from identical progenitor cells, within the same animal, if we want to fully understand the function of different genes in multiple cell types during organ development or in disease models."

Dr. Irene García González, first author on the study

Current technologies for inducing genetic mosaics, such as MADM (Mosaic Analysis with Double Markers) or Cre-dependent mosaics, are hampered by technical issues related to low efficiency or reliability. The iFlpMosaics toolkit overcomes these issues, offering a robust platform for the ratiometric induction and clonal tracking of fluorescently labeled wildtype and mutant cells.

The toolkit not only enhances the understanding of genetic mutations in tissue development and disease processes, but also facilitates the study of complex interactions between cells within their microenvironment.

"iFlpMosaics offers a big step forward for researchers studying diseases caused by somatic mutations, such as cancer and vascular malformations" said Dr. Rui Benedito. "It's precision and versatility provide an important resource for anyone seeking a better understanding of gene function in normal organ development and function, as well as in disease settings."

The study was funded by the European Research Council (ERC) through Starting Grant AngioGenesHD (638028) and Consolidator Grant AngioUnrestUHD (101001814), the Spanish Ministry of Science, Innovation, and Universities (SAF2017-89299-P y PID2020-120252RB-I00), and the la Caixa Foundation (HR19-00120 and HR22-00316 AngioHeart).

Source:
Journal reference:

Garcia-Gonzalez, I., et al. (2024). iFlpMosaics enable the multispectral barcoding and high-throughput comparative analysis of mutant and wild-type cells. Nature Methods. doi.org/10.1038/s41592-024-02534-w.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Genetic Mutation in the Inherited DNA Found to Drive Breast Cancer Metastasis