Computational biology and bioinformatics articles within Nature Communications

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  • Article
    | Open Access

    Previous work has investigated selection in the coding genome, but it is not as well characterized in the non-coding genome. By analyzing rare variants in 70k genome sequences from gnomAD, the authors detect very strong purifying selection ("ultraselection”) across the human genome, finding it in some microRNAs and coding sequences but generally rare in regulatory sequences.

    • Noah Dukler
    • , Mehreen R. Mughal
    •  & Adam Siepel

  • Article
    | Open Access

    Kinases are important drug targets, but predicting their activities from phosphoproteomics data remains challenging. While many existing prediction tools rely on phosphosite-specific quantitative data, Crowl et al. develop a kinase activity prediction algorithm that requires no phosphosite quantification.

    • Sam Crowl
    • , Ben T. Jordan
    •  & Kristen M. Naegle

  • Article
    | Open Access

    Wastewater surveillance could provide a means of monitoring SARS-CoV-2 prevalence that does not rely on testing individuals. Here, the authors report results from England’s national wastewater surveillance program, use it to estimate prevalence, and compare estimates with those from population-based prevalence surveys.

    • Mario Morvan
    • , Anna Lo Jacomo
    •  & Leon Danon

  • Article
    | Open Access

    The invention of the Fourier integral in the 19th century laid the foundation for modern spectral analysis methods. Here the authors develop frequency-based methods for analyzing the reaction mechanisms within living cells from distinctively noisy single-cell output trajectories and present forward engineering of synthetic oscillators and controllers.

    • Ankit Gupta
    •  & Mustafa Khammash

  • Article
    | Open Access

    Identifying the genetic drivers of clonal haematopoiesis (CH) has been challenging due to their low frequencies and a lack of adequate tools. Here, the authors use a reverse calling to detect blood somatic mutations and the IntOGen pipeline to identify CH drivers in large cancer genomics data sets based on signals of positive selection.

    • Oriol Pich
    • , Iker Reyes-Salazar
    •  & Nuria Lopez-Bigas

  • Article
    | Open Access

    Deep learning could be applied to the challenge of somatic variant calling in cancer by making use of large-scale genomic data. Here, the authors develop VarNet, a weakly supervised deep learning model for somatic variant calling in cancer with robust performance across multiple cancer genomics datasets.

    • Kiran Krishnamachari
    • , Dylan Lu
    •  & Anders Jacobsen Skanderup

  • Article
    | Open Access

    Triage is essential for the early diagnosis and reporting of emergency patients in the emergency department. Here, the authors develop an anomaly detection algorithm with a deep generative model that reprioritizes radiology worklists and provides lesion attention maps for brain CT images with critical findings.

    • Seungjun Lee
    • , Boryeong Jeong
    •  & Namkug Kim

  • Article
    | Open Access

    Myasthenia Gravis and thymoma are frequently associated with patients suffering from both diseases. Here the authors perform single cell sequencing of thymoma and find that there are autoimmune antigens such as neuromuscular proteins expressed aberrantly in neuromuscular mTECs in patients with both diseases.

    • Yoshiaki Yasumizu
    • , Naganari Ohkura
    •  & Hideki Mochizuki

  • Article
    | Open Access

    Super-enhancers and their associated transcription factor networks have been shown to influence ovarian cancer biology. Here, based on an integrated set of genomic and epigenomic datasets, the authors identify clinically relevant super-enhancers amplified in ovarian cancer patients and functionally validate their activity.

    • Michael R. Kelly
    • , Kamila Wisniewska
    •  & Hector L. Franco

  • Article
    | Open Access

    Genetic recombination can confound standard phylogenetic approaches. Here, the authors present a method to reconstruct virus recombination networks, and show the importance of recombination in shaping the ongoing evolution of SARS-like, MERS and 3 human seasonal coronaviruses.

    • Nicola F. Müller
    • , Kathryn E. Kistler
    •  & Trevor Bedford

  • Article
    | Open Access

    Soil microbial carbon is central to soil functions and services, but its spatial-temporal dynamics are unclear. Here the authors show global trends in soil microbial carbon, which suggests a global decrease in soil microbial carbon, mostly driven by temperature increases in northern areas.

    • Guillaume Patoine
    • , Nico Eisenhauer
    •  & Carlos A. Guerra

  • Article
    | Open Access

    A critical task in spatial transcriptomics analysis is to understand inherently spatial relationships among cells. Here, the authors present a deep learning framework to integrate spatial and transcriptional information, spatially extending pseudotime and revealing spatiotemporal organization of cells.

    • Honglei Ren
    • , Benjamin L. Walker
    •  & Qing Nie

  • Comment
    | Open Access

    Diversity is a creative force that broadens views and enhances ideas; it increases productivity as well as the impact of our science, making our respective organisations more agile and timely. Equality of opportunity is a key to success for any research organisation. Here we argue that every research organisation, whether in academia or in industry, needs to have better inclusion policies to harness the benefits of diversity in research. Drawing from our personal experiences and perspectives as women in science, we share our suggestions on how to promote inclusion in academia and create a better research culture for all. Our shared experiences highlight the many hurdles women in science face on a daily basis. We stress that rules and regulations, as well as education for awareness, will play critical role in this much needed shift from a male-dominated scientific culture that dates from Victorian times to a modern focus on gender equality in science. The key ingredients of this new culture will be flexibility, transparency, fairness and thoughtfulness.

    • Sarah A. Teichmann
    • , Muzlifah Haniffa
    •  & Jasmin Fisher

  • Article
    | Open Access

    Non-human primates are attractive laboratory animal models that can accurately reflect some developmental and pathological features of humans. Here the authors chart a reference cell map of cynomolgus monkeys using both scATAC-seq and scRNA-seq data across multiple organs, providing insights into the molecular dynamics and cellular heterogeneity of this organism.

    • Jiao Qu
    • , Fa Yang
    •  & Dijun Chen

  • Article
    | Open Access

    After acute injury, kidneys either successfully repair/regenerate or become fibrotic. Here the authors use scRNA-seq to study adaptive/maladaptive kidney regeneration and identify proinflammatory/fibrotic proximal tubule cells with pharmacologically targetable pyroptosis/ferroptosis signatures.

    • Michael S. Balzer
    • , Tomohito Doke
    •  & Katalin Susztak

  • Article
    | Open Access

    The original tumor location can be unclear for metastatic tumors. Here, the authors show that DNA sequencing of whole genomes can be used to classify metastatic tumors using a machine learning model, Cancer of Unknown Primary Location Resolver, in order to improve diagnosis and inform treatment decisions.

    • Luan Nguyen
    • , Arne Van Hoeck
    •  & Edwin Cuppen

  • Article
    | Open Access

    Few genetic biomarkers are known for cancer immunotherapy. Here the authors identify recurrently-mutated genes and pathways associated with treatment response and develop a classifier using tumour whole exome sequencing and clinical features.

    • Zoran Z. Gajic
    • , Aditya Deshpande
    •  & Neville E. Sanjana

  • Article
    | Open Access

    Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Here the authors analyse the locations of thousands of human disease mutations and their predicted effects on protein structure and show that,while loss-of-function mutations tend to be highly disruptive, non-loss-of-function mutations are in general much milder at a protein structural level.

    • Lukas Gerasimavicius
    • , Benjamin J. Livesey
    •  & Joseph A. Marsh

  • Article
    | Open Access

    Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, aimed at democratization and standardization, the authors describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets.

    • Amir Pandi
    • , Christoph Diehl
    •  & Tobias J. Erb

  • Article
    | Open Access

    Although deep learning-based computer-aided diagnosis systems have recently achieved expert level performance, developing a robust model requires large, high-quality data with annotations. Here, the authors present a framework which can improve the performance of vision transformer simultaneously with self-supervision and self-training.

    • Sangjoon Park
    • , Gwanghyun Kim
    •  & Jong Chul Ye

  • Article
    | Open Access

    The authors provide a litmus test for the recognition mechanism of transiently binding proteins based on nuclear magnetic resonance and find a conformational selection binding mechanism through concentration-dependent kinetics of ubiquitin and SH3.

    • Kalyan S. Chakrabarti
    • , Simon Olsson
    •  & Christian Griesinger

  • Article
    | Open Access

    Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical-stage antibody that displays high levels of on- and off-target binding.

    • Emily K. Makowski
    • , Patrick C. Kinnunen
    •  & Peter M. Tessier

  • Article
    | Open Access

    Folded proteins are composed of secondary structures, α-helices and β-sheets, that are generally assumed to be stable. Here, the authors combine computational prediction with experimental validation to show that many sequence-diverse NusG protein domains switch completely from α-helix to β-sheet folds.

    • Lauren L. Porter
    • , Allen K. Kim
    •  & Marie-Paule Strub

  • Article
    | Open Access

    Genome-scale metabolic models have been widely used for quantitative exploration of the relation between genotype and phenotype. Here the authors present GECKO 2, an automated framework for continuous and version controlled update of enzyme-constrained models of metabolism, producing an interesting catalogue of high-quality models for diverse yeasts, bacteria and human metabolism, aiming to facilitate their use in basic science, metabolic engineering and synthetic biology purposes.

    • Iván Domenzain
    • , Benjamín Sánchez
    •  & Jens Nielsen

  • Article
    | Open Access

    Unbiased screen of random sequences identified many short IRES-like elements to drive circular RNA translation and hundreds of rolling circle translation events, suggesting a pervasive cap-independent translation in human transcriptome.

    • Xiaojuan Fan
    • , Yun Yang
    •  & Zefeng Wang

  • Article
    | Open Access

    Morphology of metabolosomes affects the encapsulated pathway performance. Here, the authors combine experimental characterizations with structural and kinetic modeling to reveal how the shell protein PduN changes the morphology of 1,2-propanediol utilization (Pdu) metabolosome and how this morphology shift impacts Pdu function.

    • Carolyn E. Mills
    • , Curt Waltmann
    •  & Danielle Tullman-Ercek

  • Article
    | Open Access

    The impact of germline variants on somatic alterations in cancer remains to be explored in large-scale datasets. Here, the authors study the association of rare germline variants with somatic mutational processes in more than 15,000 tumors, and reveal that damaging variants in newly-identifed genes are prevalent in the population.

    • Mischan Vali-Pour
    • , Solip Park
    •  & Fran Supek

  • Article
    | Open Access

    Despite the availability of chromatin conformation capture experiments, discerning the relationship between the 1D genome and 3D conformation remains a challenge. Here, the authors propose a method that produces low-dimensional latent representations that summarize intra-chromosomal Hi-C contacts.

    • Kevin B. Dsouza
    • , Alexandra Maslova
    •  & Maxwell W. Libbrecht

  • Article
    | Open Access

    High transduction rates of viral vectors ensure good gene delivery; however multiple integration events can occur in the same cell. Here the authors use correlations between repeated measurements of integration site abundances to estimate their mutual similarity and identify clusters of co-occurring sites.

    • Sebastian Wagner
    • , Christoph Baldow
    •  & Ingmar Glauche

  • Article
    | Open Access

    Cellular contexts such as disease state, organismal life stage and tissue microenvironment, shape intercellular communication, and ultimately affect an organism’s phenotypes. Here, the authors present Tensor-cell2cell, an unsupervised method for deciphering context-driven intercellular communication.

    • Erick Armingol
    • , Hratch M. Baghdassarian
    •  & Nathan E. Lewis

  • Article
    | Open Access

    Many transcriptomic profiles have been deposited in public archives but are underused for the interpretation of experiments. Here the authors report GenomicSuperSignature for interpreting new transcriptomic datasets through comparison to public archives, without high-performance computing requirements.

    • Sehyun Oh
    • , Ludwig Geistlinger
    •  & Sean Davis

  • Article
    | Open Access

    It is unclear if the molecular profiles of pancreatic ductal adenocarcinoma (PDAC) preclinical models remain stable during propagation. Here, the authors characterise clonal evolution throughout propagation in PDAC cell lines and a patient-derived organoid using single-cell genomics, transcriptomics and epigenomics.

    • Maria E. Monberg
    • , Heather Geiger
    •  & Anirban Maitra

  • Article
    | Open Access

    Hong Kong experienced a severe wave of SARS-CoV-2 in early 2022. Here, the authors use genomic and serosurveillance data and show that this wave was dominated by the Omicron BA.2 sublineage, and that low protective immunity, particularly in older age groups, contributed to its severity.

    • Lin-Lei Chen
    • , Syed Muhammad Umer Abdullah
    •  & Kelvin Kai-Wang To

  • Article
    | Open Access

    Here, the authors generated an artificial RNA molecule, or aptamer, specific for the Amyotrophic Lateral Sclerosis protein TDP-43. By interacting avidly with its target, the aptamer can be exploited to track TDP-43 phase transition in vitro and in cells.

    • Elsa Zacco
    • , Owen Kantelberg
    •  & Gian Gaetano Tartaglia

  • Article
    | Open Access

    In the era of single-cell sequencing, there is a growing need to extract insights from data with clustering methods. Here, inspired by forest fire dynamics, the authors devise an algorithm that can cluster single-cell data with minimal prior assumptions and can compute a non-parametric posterior probability for each data point.

    • Zhanlin Chen
    • , Jeremy Goldwasser
    •  & Mark Gerstein

  • Article
    | Open Access

    Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Here the authors present “HarmonizR”, a tool for missing data tolerant experimental variance reduction in large, integrated but independently generated datasets without data imputation, adjustable for individual dataset modalities, correction algorithm, and user preferences.

    • Hannah Voß
    • , Simon Schlumbohm
    •  & Christoph Krisp

  • Article
    | Open Access

    Stable-isotope tracing allows quantifying metabolic activity by measuring isotopically labeled metabolites, but its metabolome coverage has been limited. Here, the authors develop a global isotope tracing approach with metabolome-wide coverage and use it to characterize metabolic activities in aging Drosophila.

    • Ruohong Wang
    • , Yandong Yin
    •  & Zheng-Jiang Zhu

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