What's π-HuB project?

Humanity, the final frontier of life, is built upon the protein universe. In the last decade, our understanding of the human proteome has been greatly advanced. In 2020, the first high stringency blueprint of the Human Proteome Project (HPP) was established, covering over 90% of the human proteome, paralleling progress made by the Human Genome Project. In 2014, Nature published two seminal papers that review the initial version of the human proteome by applying mass spectrometry-based approaches to profile dozens of normal tissues and organs.

These advances were only beginning to scratch the surface, and there are still many challenges ahead. It is a twofold challenge: on the one hand, molecular diversification is particularly pronounced in the human proteome, which shapes trillions of cells in the body. On the other hand, an individual proteome is highly dynamic throughout their lifetime, and can be remodeled by multiple factors such as the microbiome, diet, and environment - all of which are linked to human health.

Here, we introduce π-HuB (the Proteomic Navigator of the Human Body) as the next generation of the Human Proteome Project. The letter π is the ratio of the circumference of a circle to its diameter, and has been used to represent the world since ancient times. Notably, Leonardo da Vinci's famous Vitruvian Man suggests the perfect squaring area is equal to two πs of the circle. π is also an irrational number, meaning its stages do not end or repeat - symbolizing the infinite dynamics of the human proteome.

The π-HuB project will be a long-term mission with four overarching goals. π-HuB aims to create a comprehensive understanding of the human body at the molecular level through proteomics. The first goal is to map out the spatial atlas of the human body by analyzing different levels of proteomic forms, from tissues and organs down to individual molecules. The second goal is to define the temporal space of human life by collecting population proteomics data across different stages of life and investigating how diet, microbiome and environment can influence proteomes. The third goal is to model a virtual state space called Meta-homo sapiens using deep learning-based multi-scale modeling techniques, and ultimately to be used for early disease diagnosis and interception.

In order to achieve our objectives, we must carefully establish or improve the project roadmap with regards to scientific strategies, development of deliverables and validation of next-generation proteomic technologies. This will require collaboration and discussion among a diverse group of multidisciplinary scientists from around the world. It is essential that we have access to state-of-the-art facilities and research teams capable of managing the vast amount of data and samples generated by this project. To this end, the Chinese team has developed a new infrastructure for the π-HuB project called OMNI-Wisdom. Our facility includes a data factory designed for high-throughput production of proteomic-centric multi-omics data. This data can be processed using cutting-edge computational approaches, including high-performance systems, automatic machine learning, and an explainable AI knowledge graph. Ultimately, these approaches are integrated to create an informatic pipeline that enables the automatic discovery of new biology and clinical practices.

Last year, we constructed a pilot version of a data factory for proteomics in Guangzhou, China. This facility can serve as one of the π-HuB data generation centers and is equipped with 17 advanced LC-MS/MS instruments.

The π-HuB project has garnered support from over 100 prominent experts from 20 different countries, including several Nobel Laureates. The list of supporters continues to grow, and numerous institutions and universities have signed MoUs indicating their interest in joining this significant endeavor.

Overall, we believe that the π-HuB project will play a pivotal role in biomedical research for the next three decades by providing an ultimate solution at the molecular level to improve human health and well-being.

You are applying

Laboratory staff of biological mass spectrometry platform

Full Name*


Resume uploading

The size cannot exceed 5M and supports word, pdf, and html


Our page uses cookies

We use cookies to personalize and enhance your browsing experience on our website. By clicking "Accept All", you agree to use cookies. You can read our Cookie Policy for more information.