Reviews & Analysis

The generation of a whole larval zebrafish brain electron microscopy volume in tandem with automated tools lays the groundwork for producing the first vertebrate brain connectome.

OCTOPUS is a bioengineered device for high-fidelity organoid cultures long term.

This Perspective describes common pitfalls that can occur when using light sheet microscopy and offers guidance for improved quantitative imaging with these instruments.

Light-Seq combines high resolution imaging with next generation sequencing of selected cell populations in fixed biological samples. Specifically, microscopically analyzed cells can be subjected to RNA expression profiling while keeping the sample intact for further assays, enabling cellular phenotypes and states to be assessed in the context of the original tissue.

An approach for integrating the wealth of heterogeneous brain data — from gene expression and neurotransmitter receptor density to structure and function — allows neuroscientists to easily place their data within the broader neuroscientific context.

This Review summarizes recent methodological advances in experimental and computational tools developed in studying RNA structures, which provides a bridge for communication between both experimentalists and computational experts.

RNA molecules designed by citizen scientists and probed in high-throughput experiments highlighted discrepancies among RNA folding algorithms in their ability to predict RNA structure ensembles. These datasets were used to train a new algorithm that demonstrated improved performance in a collection of independent datasets, including viral genomic RNAs and mRNAs probed in cells.

RNA comprises a substantial fraction of eukaryotic chromatin, but techniques to identify and map RNAs are cumbersome. We adapted existing tagmentation-based profiling techniques to enable chromatin-associated RNAs to be profiled in a simple workflow, enhancing the capability to identify regulatory RNAs.

BIONIC (Biological Network Integration using Convolutions) is a scalable deep learning network integration approach that learns and combines diverse data representations across a range of biological network types to consolidate knowledge of gene function. BIONIC outperforms existing integration approaches by capturing biological information more comprehensively and with greater accuracy than previously possible.

A genetically encoded green fluorescent sensor for oxytocin, MTRIA_OT, offers an opportunity to perform real-time recording of brain oxytocin dynamics in living animals.

TracX shows that fast proofreading of track assignments leads to improved cell tracking performance.

Joint profiling of multiple modalities in the same cell is challenging. We developed a method with a modular design to enable the simultaneous detection of chromatin accessibility and the transcriptome within single cells with flexible throughput.

A tissue engineering method using a 3D scaffolding enables the generation of an artificial human thymus from inducible pluripotent stem cells (iPSCs). The artificial thymus can be used to study human T cell development in hematopoietic humanized mice.

Advances in microscopy, computer vision and open source software are converging to usher in a new era of microscopes that control themselves.

Scanning transmission electron microscopy (STEM) techniques reveal atomic-resolution details of organic and inorganic materials. The application of STEM to biological vitrified specimens under low-dose cryogenic imaging conditions demonstrates that STEM also achieves near-atomic-resolution 3D structures of biological macromolecules.

In vivo, forces applied to molecular interactions between T cells and antigen-presenting cells are essential for specific foreign antigen recognition. A new technology, BATTLES, applies force to thousands of T cells interacting with tens of candidate antigens to identify antigens capable of efficient T cell activation. The method improves throughput over current methods that profile force-dependent interactions.

In this Perspective, technologies and challenges in the cardiac tissue engineering field are discussed and strategies to overcome these challenges are proposed.

Cell type-specific inference of differential expression (C-SIDE) is a statistical model that identifies which genes (within a determined cell type) are differentially expressed on the basis of spatial position, pathological changes or cell–cell interactions. C-SIDE facilitates differential expression analysis in spatial transcriptomics by jointly modeling cell type mixtures and spatially varying gene expression.

This Review covers advances in methods for studying metabolism at the subcellular level and how they have influenced our understanding of cancer biology.

PROBER is a fast and sensitive episome-based method to identify sequence-specific DNA-binding proteins from living cells using proximity proteomics. This method quantifies steady-state and inducible association of transcription factors and corresponding chromatin regulators to specific DNA sequences as well as binding quantitative trait loci present as a result of single nucleotide variants.