Volume electron microscopy

计算机科学 数据科学 领域(数学) 纳米技术 主流 材料科学 政治学 数学 法学 纯数学
作者
Christopher J. Peddie,Christel Genoud,Anna Kreshuk,Kimberly Meechan,Kristina D. Micheva,Kedar Narayan,Constantin Pape,Robert G. Parton,Nicole L. Schieber,Yannick Schwab,Benjamin Titze,Paul Verkade,Aubrey V. Weigel,Lucy Collinson
出处
期刊:Nature Reviews Methods Primers [Springer Nature]
卷期号:2 (1) 被引量:108
标识
DOI:10.1038/s43586-022-00131-9
摘要

Life exists in three dimensions, but until the turn of the century most electron microscopy methods provided only 2D image data. Recently, electron microscopy techniques capable of delving deep into the structure of cells and tissues have emerged, collectively called volume electron microscopy (vEM). Developments in vEM have been dubbed a quiet revolution as the field evolved from established transmission and scanning electron microscopy techniques, so early publications largely focused on the bioscience applications rather than the underlying technological breakthroughs. However, with an explosion in the uptake of vEM across the biosciences and fast-paced advances in volume, resolution, throughput and ease of use, it is timely to introduce the field to new audiences. In this Primer, we introduce the different vEM imaging modalities, the specialized sample processing and image analysis pipelines that accompany each modality and the types of information revealed in the data. We showcase key applications in the biosciences where vEM has helped make breakthrough discoveries and consider limitations and future directions. We aim to show new users how vEM can support discovery science in their own research fields and inspire broader uptake of the technology, finally allowing its full adoption into mainstream biological imaging. Volume electron microscopy techniques are high-resolution imaging approaches that reveal the 3D structure of cells, tissues and small model organisms at nanometre resolution. This Primer introduces the different imaging modalities, specialized sample processing and key applications in biosciences.
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