H2020Индивидуална стипендия2021–2023

OrganoidAlign · Comparative modelling of organoids in the age of single-cell transcriptomics

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2021-06-15 → 2023-07-11
Финансиране от ЕС: 212 934 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Органоидите (изкуствено отгледани тъкани) се сравняват с реални човешки тъкани чрез анализ на генетичните профили на техните единични клетки. Това помага да се разбере колко точно моделът имитира живия орган, което е важно за регенеративната медицина и биологията.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Comparative modelling of organoids in the age of single-cell transcriptomics

The OrganoidAlign project was initiated to develop a statistically-consistent and robust computational framework for comparing an in vitro organoid system to its in vivo reference tissue using their single cell transcriptomic (scRNA-seq) profiles. This is a fully data-driven interdisciplinary research project, where both computational and immunology expertise came together to design and develop relevant computational methods for comparative modelling of organoids at single-cell resolution. Organoids are three-dimensional self-assembling constructs of tissue that are grown in vitro by differentiating either from induced pluripotent stem cells (iPSCs) or primary adult stem cells. As proxies to their in vivo counterparts, organoids can act as model systems enabling mechanistic studies in vitro to understand human developmental biology, as well as to drive targeted cell engineering and regenerative medicine. Thus it is important to develop organoids that are more closely and accurately following the dynamics of their in vivo tissue reference, being faithful and reliable. As a rapidly advancing field, this has created a timely need for computational methods that can quantitatively assess the degree of recapitulation of an organoid compared to its in vivo reference, and infer matches and mismatches between them in terms of their expected cell type/state compositions and transcriptomics across their developmental time. This proposal aimed to develop computational methods to measure the reliability of an organoid based on its scRNA-seq profile under a statistical and information theoretic framework. This particularly addressed the computational problem of trajectory alignment. The main objective was to develop a Bayesian information-theoretic alignment framework that can capture the matches and mismatches between an organoid system and its in vivo tissue reference, using single-cell RNA sequencing data. Our main organoid system of focus was an in-house grown artificial thymus organoid (ATO) system which mimics T cell differentiation from iPSCs to mature Single Positive T cells.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

The OrganoidAlign action will develop a solid computational framework for comparative modelling of organoids in the age of single-cell transcriptomics. It will provide direct payoffs to both, tissue engineering and single-cell genomics fields. The overarching goal is to build a set of statistically rigorous and consistent probabilistic models for aligning a single-cell transcriptomic profile of an organoid against its in vivo tissue, for quantitatively evaluating its recapitulatory power. During the course of this action, a meticulous review will be conducted on the state-of-the-art single-cell data modelling and comparative analysis techniques prior to formulating the single-cell transcriptomic profile comparison problem in statistical learning theory. This will specifically focus on both cell clustering and cell trajectory inference methods. A new statistical framework will be implemented to accommodate a comprehensive comparison between a pair of in vitro and in vivo transcriptomic profiles. A rigorous scoring measure will be devised to quantify their alignment. Overall, the inference components under the proposed framework will facilitate the prediction of missing or outlying cellular attributes, transcriptional factors and signaling pathways in organoids compared to their in vivo tissues, informing directions of organoid protocol improvement. Overall, its outcomes will have potential contributions towards engineering more reliable in vitro tissue models, as well as reference profiling of organoids under the Human Cell Atlas project.

Оригинален текст от CORDIS (на английски).

Участници

GENOME RESEARCH LIMITED LBG · SAFFRON WALDENКоординаторОбединеното кралство