Volume 20 Issue 12, December 2023

Labs range in size, and no one size is likely to fit all. Here some researchers share their lab size experiences and preferences.

Research with human embryos and embryo models, this year’s Method of the Year, can be fraught. In contrast, digital embryos could be studied, even perturbed, in computational what-happens-when experiments.

The creation of multiple stem-cell-derived models of mammalian embryogenesis is opening many new doors to study human development and brings a need for scientists to demonstrate responsible dialog over the associated ethical issues.

In vivo developmental atlases provide a crucial reference for the new class of stem-cell-derived human embryo models, helping accelerate insights into the mechanisms of human development.

I discuss how recent advancements in lineage tracing methods have enabled rare insight into the cell fate and trajectory during development.

Advancements in methods that enable in vitro culture of mammalian embryos have become an essential way of investigating mammalian early embryonic development and modeling developmental and pregnancy-related disorders. Here, we discuss the recent method development in this space and analyze current challenges and future directions.

Recent methodological advances in measurements of geometry and forces in the early embryo and its models are enabling a deeper understanding of the complex interplay of genetics, mechanics and geometry during development.

Increasingly advanced in vitro stem-cell-derived human embryo models raise novel ethical questions and shed a light on long-standing questions regarding research on human embryos.

Advances will enable proteome-scale structure determination in cells.

Large language models are learning the language of genomics.

High-resolution connectomics of the human brain is the next frontier in neuroscience.

Advances in profiling chromosome structure help reveal the regulatory roles of gene organization.

Developments in nanopore-based peptide detection and sequencing show promise of a breakthrough.

New twists on established methods and multimodal imaging are poised to bridge gaps between cellular and organismal imaging.

Spatially resolved multimodal omics offers a collective way to capture molecular information in complex tissues.

Artificial ECMs enable recapitulation of tissue microenvironments.

DARLIN enables the generation of a massive diversity of barcodes for in vivo lineage tracing and the combination with single-cell multi-omics measurements.

A class of protein-based molecular shape probes move us closer toward the goal of a general, genetically encoded tagging system for cryogenic electron tomography.

Two new methods enable the study of the mechanics of tissue development.

A new method models mammary gland in vitro during physiological and pathological conditions.

Fluorescent actinometers enable the measurement of light intensity even in the depths of samples and over wide ranges of wavelengths and intensities. We introduce two protocols to quantitatively characterize the spatial distribution of light of various fluorescence imaging systems and to calibrate the illumination of commercially available instruments and light sources.

Cardinal v.3 is an open-source software for reproducible analysis of mass spectrometry imaging experiments, and includes data processing features such as mass recalibration, statistical analyses such as single-ion segmentation and rough annotation-based classification, and analyses of large-scale multitissue experiments.

An engineered RNA A-to-I deaminase (rABE) offers low sequence bias, high activity and low background for REMORA (RNA-encoded molecular recording in adenosines) and enables improved molecular recording of RNA–protein interactions.

Genetically encoded multimeric particles (GEMs) are 25-nm tags with recognizable structural signatures, which can be used to label specific proteins in mammalian cells to facilitate their subcellular localization in cryo-ET.

nextPYP is a turn-key framework for single-particle cryo-electron tomography that streamlines complex data analysis pipelines, from pre-processing of tilt series to high-resolution refinement, for efficient analysis and visualization of large datasets.

Adaptable, turn-on maturation (ATOM) biosensors use monobody or nanobody targeting to control fluorescent protein maturation for fluorescence in the presence of target biomolecules, enabling bright and specific cellular biosensing.

Two methods for fluorescence-based actinometry using organic dyes and photoconvertible fluorescent proteins enable rapid and precise measurement of light intensity at the sample in fluorescence microscopes.

DBlink uses deep learning to capture long-term dependencies between different frames in single-molecule localization microscopy data, yielding super spatiotemporal resolution videos of fast dynamic processes in living cells.

Enhanced super-resolution radial fluctuations (eSRRF) offers improved image fidelity and resolution compared to the popular SRRF method and further enables volumetric live-cell super-resolution imaging at high speeds.

DeepSeMi is a self-supervised denoising framework that can enhance SNR over 12 dB across diverse samples and imaging modalities. DeepSeMi enables extended longitudinal imaging of subcellular dynamics with high spatiotemporal resolution.

A pulsed illumination scheme renders stimulated Brillouin microscopy less phototoxic and allows imaging of the mechanical properties of sensitive samples such as single cells, Caenorhabditis elegans embryos, zebrafish larvae and organoids.

TubULAR is an in toto tissue cartography method for mapping complex dynamic surfaces

Foambryo is an analysis pipeline for three-dimensional force-inference measurements in developing embryos.

A deep learning-based method that uses microscopy images to stage embryos and analyze developmental time.

SegCLR automatically annotates segmented electron microscopy datasets of the brain with information such as cellular subcompartments and cell types, using a self-supervised contrastive learning approach.

A dynamic, hormone-responsive mammary gland organoid system that can mimic complex physiological processes in vitro.

MISCOs are spatially arranged ventral midbrain–striatum–cortical organoids that enable investigations into the human dopaminergic system.

A combination of hardware developments has increased the achievable spatial resolution in 7 Tesla human neuroimaging to about 0.4 mm.

A benchmarking study evaluates 11 mosaic single-nucleotide variant and insertion-deletion mutation detection approaches.