Reviews & Analysis

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.

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.

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.

The Integrative Genome Modeling (IGM) platform incorporates information from multiple, complementary experimental data sources to accurately simulate whole diploid genome structures. We show that such structures have high predictive power and give access to a large variety of structural observables for the characterization of the gene microenvironment.

RAPToR (real age prediction from transcriptome staging on reference) is a new, broadly applicable method that can precisely estimate the age of a sample from a reference transcriptome time series.

Bioluminescent phasor is a new technology for multiplexed, excitation-free imaging at the microscale using luciferase–luciferin pairs. This platform can readily unmix the broad, overlapping emission spectra of bioluminescent reporters, making possible the dynamic tracking of cellular and molecular features over prolonged time periods.

We developed a streamlined approach coupling microfabricated cell culture substrates, 3D single-objective light sheet imaging and artificial intelligence quantifications to characterize the variability of morphologies of small organoids. Arrayed organoids can be imaged in 3D at around 100 organoids per hour.

Adenosine-to-inosine RNA editing is a common post-transcriptional modification, but can be challenging to identify correctly from Illumina data. We show that Oxford Nanopore RNA sequencing, combined with deep learning models, can be used to accurately detect inosine-containing sites in native transcriptomes and to estimate the modification rate of each site.

Determining the functional properties of a protein from its structure is challenging. This study presents an interpretable deep learning model that directly learns function-bearing structural motifs from raw data, allowing accurate mapping of protein binding sites and antibody epitopes onto a protein structure.

Repository-scale analysis of hundreds of millions to billions of mass spectra is a challenging endeavor due to the complexity and volume of associated data. A deep neural network embedding method is presented that enables large-scale investigation of repeatedly observed yet consistently unidentified mass spectra.

Tangram, gimVI and SpaGE outperformed other integration methods for predicting the spatial distributions of RNA transcripts, while Cell2location, SpatialDWLS and RCTD were the top-performing methods for the cell type deconvolution of spots in histological sections.

Neuromechanical simulations enable the study of how interactions between organisms and their physical surroundings give rise to behavior. NeuroMechFly is an open-source neuromechanical model of adult Drosophila, with data-driven morphological biorealism that enables a synergistic cross-talk between computational and experimental neuroscience.

Counting of RNA molecules using unique molecular identifiers (UMIs) is ubiquitous in single-cell sequencing. Here, we introduce molecular spikes, a new type of RNA spike-ins with in-built UMIs. These versatile molecular spikes have many uses in experimental and computational method development and routine biological applications.

By providing challenges to the metagenomics community based on complex and realistic metagenome benchmark datasets, CAMI — the community-driven initiative for the Critical Assessment of Metagenome Interpretation — has created a comprehensive assessment of the performance of metagenomics software for common analyses. As part of its second contest, CAMI II, it evaluates ~5,000 submissions from 76 software programs and their different versions.

A simple and affordable technique passively clears and images whole mammalian bodies or large tissues. This technique is compatible with the use of endogeneous fluoresent proteins, without the loss of signal associated with other existing methods for whole-animal clearing.

A new single-objective light-sheet microscope has been developed that uses novel optics and imaging protocols to increase resolution without compromising imaging speed and volume.