Identifying the genetic profile of single cells has important value to both research and practical applications, and achievements in this field can help understand the great variability among different cells. 

But unlike successes in studying the genetic profile of a single cell, decoding the protein profile of a single cell has yet to be achieved. This would be a significant milestone – from both research and clinical perspectives – since an accurate sensing of proteins levels can help diagnosing diseases at an early stage when their levels are too low to be detected by current tests. For example, such mapping may help in distinguishing among different tumors and make possible treatment to be optimally tailored to the specific case

In what is regarded as a significant breakthrough, researchers at the Technion-Israel Institute of Technology in Haifa, together with overseas partners, present novel technologies for decoding the protein profile of single cells. A perspective paper that details the international group’s latest methods developments in the area, was recently published in the prestigious journal Nature Methods under the title: “The emerging landscape of single-molecule protein sequencing technologies.” 

The collaborative manuscript presented here was led by Prof. Chirlmin Joo (Delft University in the Netherlands), Dr. Javier Alfaro (University of Gdansk in Poland), and Prof. Amit Meller of the Faculty of Biomedical Engineering (the Technion), after a successful international conference SMPS19 (Single-Molecule Proteins Sequencing), a successful international conference organized by Meller and held in Jerusalem in two years ago.

In the paper, the researchers describe the future technologies of protein sequencing and identification on the individual molecular level, along with innovations in existing methods such as mass spectrometry. One such example is technology developed in Meller’s lab, involving nanometric sensors that include nano-channels and nano-pores to allow the direct sensing of individual proteins. The proteins are labelled with fluorescent dyes, and as they flow through the sensor, a sophisticated optical system can read the markers. 

The optical signal is processed and analyzed using a deep learning-based system, also developed in the lab, making it possible for the protein to be identified. This and other such technologies will lead to a deeper understanding of biological processes and the development of highly sensitive medical tests that will enable the early diagnosis of a variety of diseases, the researchers concluded.

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