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Screening of 1,076 compounds reveals 168 chemical pollutants with inhibitory effects on gut bacteria and genetic screens indicate commonality between pollutant and antibiotic resistance.

Here, the authors sample air and surfaces in hospital rooms of COVID-19 patients, detect SARS-CoV-2 RNA in air samples of two of three tested airborne infection isolation rooms, and find surface contamination in 66.7% of tested rooms during the first week of illness and 20% beyond the first week of illness.

Pathogenic variants in UNC13A underlie a novel neurodevelopmental syndrome, with three subtypes defined by distinct genotypes with varying clinical and functional impacts characterized in cellular and animal models.

Li et al. show that a Lamassu defense system protects bacteria from phage infection by activating a lethal tetrameric DNA-cutting enzyme. In the absence of phages, a protein clamp holds the enzyme as an inactive monomer, preventing self-damage.

Multi-omics profiling of diverse cancer cachexia models uncovers a multi-tissue metabolite-coordinated response associated with disease progression and links multi-tissue one-carbon metabolism to wasting.

u-Segment3D is a universal framework that translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data. It performs well across diverse datasets, including cells with complex morphologies.

Here, the authors apply a standardized system, called TXsystem, to transplant wild mouse gut microbiota into SPF mice, developing “TXwildlings” mice that stably retain natural microbiota and human-like immune traits, enhancing reproducibility and translational relevance.

Here, in a clinical trial, the authors show that CFTR-modulator therapy reshapes the lung and gut microbiomes in cystic fibrosis, reducing bacteria such as Staphylococcus in the lungs and Escherichia in stool, and showing that microbiome dysbiosis can be partially reversed.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The role of peroxisomes in skeletal muscle remains largely unexplored. Here, the authors show that peroxisomal dysfunction and disrupted crosstalk with mitochondria drive age-related muscle decline, underscoring the need to preserve peroxisomes for muscle health.

Immunotherapy is at an inflection point. After three decades of accelerating progress, immunotherapy is entering the realm of in vivo engineering. This Comment discusses the potential of in vivo engineering in addressing challenges met by ex vivo engineering efforts. Per a recent workshop organized by the National Institutes of Health, we highlight progress, the platform technologies fueling it, and elements of a road map and challenges ahead.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

Pietro Zambon and colleagues report a new hybrid-pixel detector for 100 keV cryo-electron microscopy. By using a gallium arsenide sensor and a super-resolution algorithm, they achieve high imaging performance, paving the way for more accessible high-resolution structural biology.

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

Integrated multi-omic analyses using samples from the TRACERx study highlight cross-talk between DNA hypermethylation and genomic lesions in non-small cell lung cancer.

The number of individuals in a given space influences animal interactions and network dynamics. Here the authors identify general rules underlying density dependence in animal networks and reveal some fundamental differences between spatial and social dynamics.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Covalent inhibitors are powerful entities in drug discovery. Now the amino acid selectivity and reactivity of a diverse electrophile library have been assessed proteome-wide using an unbiased workflow. This comparative analysis and the probes described could help guide the discovery and design of covalent ligands targeting residues beyond cysteine.

Natural products have historically made a major contribution to pharmacotherapy, but also present challenges for drug discovery, such as technical barriers to screening, isolation, characterization and optimization. This Review discusses recent technological developments — including improved analytical tools, genome mining and engineering strategies, and microbial culturing advances — that are enabling a revitalization of natural product-based drug discovery.

This study explores the use of quantum computing to address multi-objective optimization challenges. By using a low-depth quantum approximate optimization algorithm to approximate the optimal Pareto front of multi-objective weighted max-cut problems, the authors demonstrate promising results—both in simulation and on IBM Quantum hardware—surpassing classical approaches.

Targeting TGFBR1 in transplantable mouse colorectal tumor organoids improves response to anti-PD-L1 therapy. Mechanistically, TGF-β abrogates clonal expansion of T effector and memory phenotypes and indirectly inhibits T cell activity by regulating immunosuppressive tumor-associated macrophage activity.

One of the paradoxical phenomena of quantum mechanics is the quantum Cheshire Cat, consisting of the apparent spatial separation of a particle and one of its properties. Denkmayr et al.use neutron interferometry to prepare and evaluate the Cheshire Cat state of a neutron and its magnetic moment.

A connectome of the right optic lobe from a male fruitfly is presented together with an extensive collection of genetic drivers matched to a comprehensive neuron-type catalogue.

The micro isolation (MISO) method combines microfluidics-based protein purification with cryo-EM grid preparation, enabling cryo-EM structure determination of soluble and membrane proteins starting from less than 1 µg of a target protein.

Living plant collections hold an immense wealth of plant diversity and have critical educational, scientific and conservation roles. This Perspective examines current data management practices of living collections and advocates for higher data standards and a robust and inclusive global data ecosystem.

The discovery and mapping of causal variants in genome-wide association studies requires taking into consideration a range of confounding factors that can impact the results of the analysis. Here Stephanet al. propose a mixed random forest that captures nonlinear associations while accounting for population structure simultaneously.