SPACE: STRING proteins as complementary embeddings.

Motivation: Representation learning has revolutionized sequence-based prediction of protein function and subcellular localization. Protein networks are an important source of information complementary to sequences, but the use of protein networks has proven to be challenging in the context of machine learning, especially in a cross-species setting.

Results: We leveraged the STRING database of protein networks and orthology relations for 1,322 eukaryotes to generate network-based cross-species protein embeddings.

ESCMID workshop: Artificial Intelligence and Machine Learning in Medical Microbiology Diagnostics.

Rapid advancements in artificial intelligence (AI) and machine learning (ML) offer significant potential to transform medical microbiology diagnostics, improving pathogen identification, antimicrobial susceptibility prediction and outbreak detection. To address these opportunities and challenges, the ESCMID workshop, "Artificial Intelligence and Machine Learning in Medical Microbiology Diagnostics", was held in Zurich, Switzerland, from June 2-5, 2025. The course featured expert lectures, practical sessions and panel discussions covering foundational ML concepts and deep learning architectures, data interoperability, quality control processes, model development and validation strategies.

Rbm8a deficiency causes hematopoietic defects by modulating Wnt/PCP signaling.

Thrombocytopenia-Absent Radius (TAR) syndrome is a rare congenital condition with reduced platelets, forelimb anomalies, and variable heart and kidney defects. TAR syndrome is caused by mutations in RBM8A/Y14, a component of the exon junction complex. How perturbing a general mRNA-processing factor causes the selective TAR Syndrome phenotypes remains unknown.

Preventing CpG hypermethylation in oocytes safeguards mouse development.

Except for regulatory CpG-island sequences, genomes of most mammalian cells are widely DNA-methylated. In oocytes, though, DNA methylation (DNAme) is largely confined to transcribed regions. The mechanisms restricting de novo DNAme in oocytes and their relevance thereof for zygotic genome activation and embryonic development are largely unknown.

The relative contribution of close-proximity contacts, shared classroom exposure and indoor air quality to respiratory virus transmission in schools.

Close-proximity interactions are considered a key risk factor for respiratory virus transmission, but their importance relative to shared space and air quality remains unclear. We conducted a six-week longitudinal study in a Swiss secondary school (67 students, aged 14-15). We detected 87 infections in saliva samples and recorded absences to identify plausible transmissions, excluding implausible ones through genomic analysis.

Characterizing influenza A virus lineages and clinically relevant mutations through high-coverage wastewater sequencing.

Influenza A virus poses significant public health challenges, causing seasonal outbreaks and pandemics. Its rapid evolution motivates continuous monitoring of circulating influenza genomes to inform vaccine and antiviral development. Wastewater-based surveillance offers an unbiased, cost-effective approach for genomic surveillance.

DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.

With rapid advancements in single-cell DNA sequencing (scDNA-seq), various computational methods have been developed to study evolution and call variants on single-cell level. However, modeling deletions remains challenging because they affect total coverage in ways that are difficult to distinguish from technical artifacts. We present DelSIEVE, a statistical method that infers cell phylogeny and single-nucleotide variants, accounting for deletions, from scDNA-seq data.

Whole Genome Sequencing Reveals How Plasticity and Genetic Differentiation Underlie Sympatric Morphs of Arctic Charr.

Salmonids have a remarkable ability to form sympatric morphs after postglacial colonisation of freshwater lakes. These morphs often differ in morphology, feeding and spawning behaviour. Here, we explored the genetic basis of morph differentiation in Arctic charr (n = 283) by first establishing a high-quality reference genome and then using this in whole genome sequencing of distinct morphs present in two Norwegian and two Icelandic lakes.

Model Quality Assessment for CASP16.

The CASP16 evaluation of model accuracy (EMA) experiment assessed the ability of predictors to estimate the accuracy of predicted models, with a particular emphasis on multimeric assemblies. Expanding on the CASP15 framework, CASP16 introduced a new evaluation mode (QMODE3) focused on selecting high-quality models from large-scale AlphaFold2-derived model pools generated by MassiveFold. Three primary evaluation tasks were therefore conducted: QMODE1 assessed global structure accuracy, QMODE2 focused on the accuracy of interface residues, and QMODE3 tested model selection performance.

Histopathology-based protein multiplex generation using deep learning.

Multiplexed protein imaging offers valuable insights into interactions between tumours and their surrounding tumour microenvironment, but its widespread use is limited by cost, time and tissue availability. Here we present HistoPlexer, a deep learning framework that generates spatially resolved protein multiplexes directly from standard haematoxylin and eosin (H&E) histopathology images. HistoPlexer jointly predicts multiple tumour and immune markers using a conditional generative adversarial architecture with custom loss functions designed to ensure pixel- and embedding-level similarity while mitigating slice-to-slice variations.

EdgeHOG: a method for fine-grained ancestral gene order inference at large scale.

Ancestral genomes are essential for studying the diversification of life from the last universal common ancestor to modern organisms. Methods have been proposed to infer ancestral gene order, but they lack scalability, limiting the depth to which gene neighbourhood evolution can be traced back. Here we introduce edgeHOG, a tool designed for accurate ancestral gene order inference with linear time complexity.

Unveiling the functional fate of duplicated genes through expression profiling and structural analysis.

Gene duplication is a major evolutionary source of functional innovation. Following duplication events, gene copies (paralogues) may undergo various fates, including retention with functional modifications (such as subfunctionalization or neofunctionalization) or loss. When paralogues are retained, this results in complex orthology relationships, including one-to-many or many-to-many.

From literature to biodiversity data: mining arthropod organismal traits with machine learning.

The fields of taxonomy and biodiversity research have witnessed an exponential growth in published literature. This vast corpus of articles holds information on the diverse biological traits of organisms and their ecologies. However, access to and extraction of relevant data from this extensive resource remain challenging.

Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are unbiased and robust to differential shedding.

The COVID-19 pandemic has accelerated the development and adoption of wastewater-based epidemiology. Wastewater samples can provide genomic information for detecting and assessing the spread of SARS-CoV-2 variants in communities and for estimating important epidemiological parameters such as the selection advantage of a viral variant. However, despite demonstrated successes, epidemiological data derived from wastewater suffers from potential biases.

Effective description of Taylor dispersion in strongly corrugated channels.

We consider Taylor dispersion in periodic but highly corrugated channels. Exact analytical expressions for the long-time diffusion constant and drift along the channel are derived to next-to-leading order in the limit of a small channel period. Using these results, we show how an effective model for Taylor dispersion in porous media with tortuous pores can be framed in terms of dispersion in a uniform channel with absorption/desorption at its surface, an effective slip length for the flow at the surface, and an effective, universal, diffusion constant on the surface.

The BeeBiome data portal provides easy access to bee microbiome information.

Bees can be colonized by a large diversity of microbes, including beneficial gut symbionts and detrimental pathogens, with implications for bee health. Over the last few years, researchers around the world have collected a huge amount of genomic and transcriptomic data about the composition, genomic content, and gene expression of bee-associated microbial communities. While each of these datasets by itself has provided important insights, the integration of such datasets provides an unprecedented opportunity to obtain a global picture of the microbes associated with bees and their link to bee health.

Proteasome inhibition overcomes resistance to targeted therapies in B-cell malignancy models and in an index patient.

Treatment of B-cell malignancies with the PI3K inhibitor (PI3Ki) idelalisib often results in high toxicity and resistance, with limited treatment alternatives for relapsed/refractory patients since idelalisib is recommended as a later or last line therapy. To investigate resistance mechanisms and identify alternative treatments, we studied functional phenotypes of idelalisib-resistant B-cell malignancy models. The idelalisib-resistant KARPAS1718 model remained sensitive to Bcl-2 inhibitors (Bcl-2i), whereas the resistant VL51 model showed reduced sensitivity compared to parental cells.

The evolution of health data ecosystems: An international survey.

This paper reports the findings of an international survey of health data ecosystems (HDEs) in 12 countries plus the H3 Africa project using live, structured interviews with senior project team members under the auspices of Canada's All for One Precision Health Initiative. We note the high level of interest in HDEs around the world, as well as in Canada, despite the financial, jurisdictional, and other barriers that continue to hold back widespread data sharing. We present results detailing operational profiles for each of the 13 participants, including whether their healthcare systems are centralized (national) or decentralized (regional), project start date, funding, information technology (IT) infrastructure, and the extent to which participants have implemented a data-sharing mandate.

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects tissue and organ function. Since 2020, more than 50 spatially aware clustering (SAC) methods have been developed for this purpose.

Bayesian inference of fitness landscapes via tree-structured branching processes.

Motivation: The complex dynamics of cancer evolution, driven by mutation and selection, underlies the molecular heterogeneity observed in tumors. The evolutionary histories of tumors of different patients can be encoded as mutation trees and reconstructed in high resolution from single-cell sequencing data, offering crucial insights for studying fitness effects of and epistasis among mutations. Existing models, however, either fail to separate mutation and selection or neglect the evolutionary histories encoded by the tumor phylogenetic trees.

A Vision for VenomsBase: An Integrated Knowledgebase for the Study of Venoms and Their Applications.

Venoms are complex bioactive mixtures that have independently evolved across diverse animal lineages, including snails, insects, sea anemones, spiders, scorpions, and snakes. Despite the growing interest in venom research, data is fragmented across disparate databases which lack standardization and interoperability. A vision for the proposed VenomsBase platform presented here seeks to address these challenges by using the best practices approach in creating a centralized, open-access platform adhering to FAIR principles (Findable, Accessible, Interoperable, and Reproducible).

Chemical and mechanical patterning of tortoise skin scales occur in different regions of the head.

Vertebrate skin appendages are diverse micro-organs such as scales, feathers, and hair. These units typically develop from placodes, whose spatial patterning involves conserved chemical reaction-diffusion dynamics. Crocodile head scales are a spectacular exception to this paradigm, as they instead arise from a mechanically dominated process of compressive folding driven by constrained skin growth.

Engineered CD4 TCR T cells with conserved high-affinity TCRs targeting NY-ESO-1 for advanced cellular therapies in cancer.

While cancer immunotherapy has primarily focused on CD8 T cells, CD4 T cells are increasingly recognized for their role in antitumor immunity. The allele is found in 50% of Caucasians. In this study, we screened patients with melanoma for tumor-specific CD4 T cells and identified robust New York esophageal squamous cell carcinoma 1 (NY-ESO-1)/ CD4 T cell activity in both peripheral blood and tumor tissue.