Synthetic Cells from Scratch: 100+ Asian Teams Unveil 10‑Year Roadmap

Four technical barriers

Metabolic shutdown – cell‑free systems depend on externally supplied ATP, NADH and other energy carriers, which are rapidly depleted. A synthetic cell must generate its own energy from basic precursors.

Ribosome paralysis – functional ribosomes require many chaperones, RNA modifications and spatial compartmentalisation. In artificial systems assembled ribosomes are largely defective, halting protein synthesis.

Biophysical coupling – newly synthesised lipids must be precisely added to the expanding membrane, and membrane curvature and division must be coordinated; these physical rules remain unsolved.

Spatiotemporal cell‑cycle loss – DNA replication, chromosome segregation and cytokinesis must be tightly synchronised. Current artificial environments lack multi‑layered regulation, leading to chaotic replication without division.

Roadmap phases

Phase 1 – ProtoCell construction

Parallel development of four core modules (metabolism, genome replication & segregation, division machinery, membrane system) followed by integration into a “ProtoCell”. Design targets include:

Stable phospholipid vesicles 1–50 µm in diameter, structural stability > 7 days.

Minimal genome ≥ 200 genes with a replication error rate of 1–5 per 10⁶ bp.

≥ 90 % expression of essential proteins/RNAs.

Engineered membrane transport for nutrient influx and waste efflux.

Phase 2 – AutoCell evolution

Transform the ProtoCell into an “AutoCell” capable of sustained self‑maintenance, autonomous replication, directed evolution and collective behaviour. Key quantitative goals:

More than ten consecutive, coordinated growth‑division cycles.

Cell‑size coefficient of variation < 15 %.

Replacement of external components with genome‑encoded machines, e.g., self‑regenerating ribosomes.

Hardware architecture: Central factory + distributed workstations

A unified biological chassis, standardised protocols, online coordination and resource‑allocation mechanisms enable large‑scale data acquisition. The data feed predictive models and an evolutionary library.

Single‑syncell omics workflow

Simultaneous capture of genome, transcriptome, proteome and metabolome from individual synthetic cells, combined with morphological and functional imaging, to map causal links between molecular composition and cellular behaviour.

Relevant links

Nature Biotechnology article: https://www.nature.com/articles/s41587-026-03153-w

SynCell Asia website: https://syncellasia.org/

Press coverage: https://phys.org/news/2026-06-scientists-unveil-ten-year-roadmap.html

Code example

来源：ScienceAI
本文
约2000字
，建议阅读
5
分钟
用AI+自动化填补人工合成细胞的空缺。