Volume 18 Issue 7, July 2021

A flight path into biology and fast 3D projection of sample dynamics.

Computing plays a critical role in the biological sciences but faces increasing challenges of scale and complexity. Quantum computing, a computational paradigm exploiting the unique properties of quantum mechanical analogs of classical bits, seeks to address many of these challenges. We discuss the potential for quantum computing to aid in the merging of insights across different areas of biological sciences.

Advances in adaptive optics combined with a twist on light field microscopy enable high-quality imaging.

Nanopore sequencing enables quantitative profiling of pseudouridine and 2′-O-methylation modifications in native RNAs.

GPCR-based opsins can be harnessed to inhibit neurotransmission via inhibitory G protein signaling.

BioID using organelle-specific bait proteins reveals the subcellular HEK293 proteome.

Lineage tracing using somatic mutations as barcodes helps decode human hematopoiesis.

Quantum computing promises plenty, such as how it can massively accelerate some bioinformatics calculations.

Co-fractionation mass spectrometry (CF-MS) has the potential to measure thousands of protein complexes in a single experiment, but the field is still in its infancy. A meta-analysis of CF-MS data yields a core CF-MS interactome and a tool allowing researchers to align new results to published data.

This review provides an overview of recent computational developments in scRNA-seq analysis and highlights packages and tools applied in executing these analyses.

This Review surveys ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC–HRMS), a highly sensitive, high-throughput technique that is used for analyzing a broad range of metabolites.

This Perspective, from a large group of metabolomics experts, provides best practices and simplified reporting guidelines for practitioners of liquid chromatography– and gas chromatography–mass spectrometry-based metabolomics.

Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to mass spectra deposited to public repositories or contained in public spectral libraries.

A deep-learning-based approach enables automatic identification of synaptically connected neurons in electron microscopy datasets of the fly brain.

QSIPrep is a software platform for processing of most diffusion MRI datasets and ensures that adequate workflows are used.

DecoID provides acquisition-independent, database-assisted deconvolution of metabolomic MS/MS spectra for improved metabolite identification.

Single-lysosome mass spectrometry (SLMS) integrates lysosomal patch-clamp recording and induced nanoESI/MS for concurrent metabolic and electrophysiological profiling of individual enlarged lysosomes.

SpaceM combines light microscopy and MALDI-imaging mass spectrometry to enable single-cell metabolic profiling of cultured cells. SpaceM reveals coexisting metabolic states of hepatocytes and aims to democratize single-cell metabolomics.

Meta-analysis of more than 200 co-fractionation mass spectrometry experiments provides expanded protein–protein interaction resources and helps establish optimal protocols for experimental design and data analysis.

ABEL-FRET combines anti-Brownian trapping for tether-free observation of biomolecules in solution with smFRET. ABEL-FRET offers ultrahigh resolution of FRET efficiency and enables simultaneous hydrodynamic profiling of molecular composition.

Super-resolution structured illumination microscopy reconstruction algorithms are described that can handle structured noise artifacts in two and three dimensions. The algorithms lack adjustable parameters and enhance objective representation of imaged objects.

Multiangle projection imaging accelerates volumetric imaging by up to two orders of magnitude and is readily implemented on diverse microscopes, including spinning disk confocal and light-sheet microscopes.