{
  "id": 4691130,
  "title": "Single-Cell Inference of Structural States Of Ribosomes",
  "url": "https://urgent.news/2026/08/31/single-cell-inference-of-structural-states-of-ribosomes",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-31T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.08.29.747780v1?rss=1"
  },
  "original_language": "en",
  "account": "Protein synthesis is a process that is continuously adjusted to govern cell growth, differentiation, and reactions to stress. Recent techniques in single-cell sequencing can identify the location of ribosomes on separate strands of genetic material, but they do not reveal the overall patterns of protein production across the entire genetic blueprint of a cell. In contrast, methods that analyze the broad translation landscape, like polysome profiling and a type of electron microscopy, fall short in providing single-cell detail or in handling large volumes of data. We present SCISSOR (Single-Cell Inference of Structural States of Ribosomes), a method that predicts the overall level of protein production in individual cells based on the varying protection of ribosomal RNA (rRNA) from enzymes that break it down. By combining these protection patterns with the ribosome's structure, SCISSOR uncovers several distinct ribosomal states and estimates their prevalence in tens of thousands of individual cells. Applying SCISSOR shows that the level of overall protein production varies in a predictable way throughout the cell cycle in human cells, and also changes as mouse intestinal stem cells transform into different types of epithelial cells. These discoveries expose new insights into how global protein production is controlled, insights that are not possible to obtain from methods that analyze individual genetic messages or ribosome distributions. This establishes a new approach for studying the control of global protein production at the level of single cells.",
  "summary": "Protein synthesis is dynamically regulated to control cell growth, differentiation, and stress responses. Recent single-cell sequencing methods can map ribosome positions on individual transcripts, but cannot capture the global translational states that coordinate protein synthesis across the transcriptome. In contrast, methods that measure the global translational landscape, such as polysome…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}