Cellular signalling networks articles within Nature Communications

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  • Article
    | Open Access

    When stem cells develop into tissues intracellular signalling is rewired, errors in this process lead to cancer. Here, authors applied tools from differential geometry made by Albert Einstein’s General Relativity to understand and predict biological network rewiring in health and disease.

    • Anthony Baptista
    • , Ben D. MacArthur
    •  & Christopher R. S. Banerji

  • Article
    | Open Access

    Descriptive data in biomedical research are expanding rapidly, but functional validation methods lag behind. Here, authors present Logical Synthetic cis-regulatory DNA, a framework to design reporters that mark cellular states and pathways, showcasing its applicability to complex phenotypic states.

    • Carlos Company
    • , Matthias Jürgen Schmitt
    •  & Gaetano Gargiulo

  • Article
    | Open Access

    Age-associated myometrial dysfunction can cause complications during pregnancy and labor. Here, the authors report that aging myometrium is characterized by diminished contractile capillary cells, altered gene expression, and disrupted cellular communication leading to impaired angiogenesis, increased fibrosis and inflammation.

    • Paula Punzon-Jimenez
    • , Alba Machado-Lopez
    •  & Aymara Mas

  • Article
    | Open Access

    The functional heterogeneity of autophagy in endothelial cells during angiogenesis remains incompletely understood. Here, the authors apply a 3D angiogenesis-on-a-chip coupled with single-cell RNA sequencing to find distinct autophagy functions in two different endothelial cell populations during angiogenic sprouting.

    • Somin Lee
    • , Hyunkyung Kim
    •  & Noo Li Jeon

  • Article
    | Open Access

    Here, Ning et al report the cellular interactomes of Crimean-Congo haemorrhagic fever virus glycoproteins and uncover a host restriction factor HAX1 that hijacks the viral glycoproteins to mitochondria, disabling progeny virion packaging.

    • Shiyu Dai
    • , Yuan-Qin Min
    •  & Yun-Jia Ning

  • Article
    | Open Access

    A wide variety of tissues exhibit nested hierarchical organisation of cells in gene expression and activities. Here, authors present NeST, a method for spatial transcriptomics to identify such structures and uncover their functions via ligand-receptor communication, in both two and three dimensions.

    • Benjamin L. Walker
    •  & Qing Nie

  • Article
    | Open Access

    Multiple studies have characterised the tumour microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) using single-cell RNA-seq. Here, the authors integrate the data from such single-cell studies to provide a cohesive analysis of the PDAC TME, revealing cell types and interactions that are associated with PDAC phenotypes.

    • Ki Oh
    • , Yun Jae Yoo
    •  & Richard A. Moffitt

  • Article
    | Open Access

    Sepsis can cause organ damage through disparate immunological and metabolic processes. Here the authors demonstrate a proteomics-based scoring strategy for quantifying quantitative and organotypic changes in relationship to dosing, timing, and potential synergistic intervention combinations during sepsis.

    • Tirthankar Mohanty
    • , Christofer A. Q. Karlsson
    •  & Johan Malmström

  • Article
    | Open Access

    Changes in Psoriasis and other inflammatory skin diseases during severity stages can be investigated using single cell and spatial transcriptomics. Here the authors compare different inflammatory skin diseases to emphasise differences in immune cells and inflammatory markers particularly keratinocytes and fibroblasts.

    • Feiyang Ma
    • , Olesya Plazyo
    •  & Johann E. Gudjonsson

  • Article
    | Open Access

    Pathways can be activated through various signaling cascades depending on cell type. Here, the authors introduce MAYA, a computational method that can detect and score multiple modes of activation for each pathway, improving the granularity of pathway analysis for single-cell datasets.

    • Yuna Landais
    •  & Céline Vallot

  • Article
    | Open Access

    Multiregion sequencing is needed to better capture the heterogeneity of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Here, the authors analyse HCC and iCCA tumours with multiregion single-cell RNA-seq, revealing cellular dynamics and communication networks with immune cells.

    • Lichun Ma
    • , Sophia Heinrich
    •  & Xin Wei Wang

  • Article
    | Open Access

    Methods that analyse heterogeneity and compare tissue microenvironments using spatial omics data are challenging to develop. Here, the authors present SOTIP, a method that can perform spatial heterogeneity, spatial domain, and differential microenvironment analyses across multiple spatial omics modalities.

    • Zhiyuan Yuan
    • , Yisi Li
    •  & Michael Q. Zhang

  • Article
    | Open Access

    Mutations in BRCA1/2 are associated with a homologous recombination deficiency phenotype in BRCA-associated cancers. Reversion mutations can restore BRCA1/2 function and result in treatment resistance in these cancer-types. Here, the authors show that, in select cases, reversion mutations in BRCA1/2 can indicate prior BRCA-mediated tumorigenesis in non-canonical histologies.

    • Yonina R. Murciano-Goroff
    • , Alison M. Schram
    •  & Alexander Drilon

  • Article
    | Open Access

    KRAS wildtype metastatic pancreatic ductal adenocarcinoma (mPDAC) could represent a distinct molecular entity from other PDACs. Here, the authors analyse KRAS wildtype mPDAC tumours using genomics and transcriptomics and find molecular similarities with cholangiocarcinomas.

    • James T. Topham
    • , Erica S. Tsang
    •  & Daniel J. Renouf

  • 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

    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 diseases are caused by disruptions to the network of biochemical reactions that allow cells to respond to external signals. Here Nilsson et al develop a method to simulate cellular signaling using artificial neural networks to predict cellular responses and activities of signaling molecules.

    • Avlant Nilsson
    • , Joshua M. Peters
    •  & Douglas A. Lauffenburger

  • Article
    | Open Access

    Chronic obstructive pulmonary disease is a leading cause of death worldwide, while our understanding of cell-specific mechanisms underlying its pathobiology remains incomplete. Here the authors perform scRNA-seq of human lung tissue to identify transcriptional changes in alveolar niche cells associated with the disease.

    • Maor Sauler
    • , John E. McDonough
    •  & Ivan O. Rosas

  • Article
    | Open Access

    Ordinary differential equation (ODE) models are widely used to understand multiple processes. Here the authors show how the concept of mini-batch optimization can be transferred from the field of Deep Learning to ODE modelling.

    • Paul Stapor
    • , Leonard Schmiester
    •  & Jan Hasenauer

  • Article
    | Open Access

    Complex biomolecular networks are fundamental to the functioning of living systems, both at the cellular level and beyond. In this paper, the authors develop a systems framework to elucidate the interplay of networks and the spatial localisation of network components.

    • Govind Menon
    •  & J. Krishnan

  • Article
    | Open Access

    Our ability to interpret single-cell multivariate signaling responses is still limited. Here the authors introduce fractional response analysis (FRA), involving fractional cell counting, capable of deconvoluting heterogeneous multivariate responses of cellular populations.

    • Karol Nienałtowski
    • , Rachel E. Rigby
    •  & Michał Komorowski

  • Article
    | Open Access

    Network motif models focus on small sub-networks in biological systems to quantitatively describe overall behavior but they often overlook time delays. Here, the authors systematically examine the most common network motifs via delay differential equations (DDE), often leading to more concise descriptions.

    • David S. Glass
    • , Xiaofan Jin
    •  & Ingmar H. Riedel-Kruse

  • Article
    | Open Access

    Oncogenic KRAS signalling is required for tumor initiation; however KRAS-dependency at advanced stages is less understood. Here, the authors show that, in established KRAS-driven pancreatic cancer, KRAS-ablation does not affect intrinsic tumorigenic capacity but elicits antitumor immune response, highlighting the importance of KRAS-driven immune suppression in tumor maintenance.

    • Irene Ischenko
    • , Stephen D’Amico
    •  & Nancy C. Reich

  • Article
    | Open Access

    Understanding how cells discriminate between stimuli is an ongoing challenge. Here, the authors propose a mathematical framework for inferring the mutual information encoded in temporal signaling dynamics and use it to study how information is transmitted over time in response to different stimuli in NFκB, MAPK and p53 signaling pathways.

    • Ying Tang
    • , Adewunmi Adelaja
    •  & Alexander Hoffmann

  • Article
    | Open Access

    Kinases drive fundamental changes in cell state, but predicting kinase activity based on substrate-level changes can be challenging. Here the authors introduce a computational framework that utilizes similarities between substrates to robustly infer kinase activity.

    • Serhan Yılmaz
    • , Marzieh Ayati
    •  & Mehmet Koyutürk

  • Article
    | Open Access

    Single-cell methods record molecule expressions of cells in a given tissue, but understanding interactions between cells remains challenging. Here the authors show by applying systems biology and machine learning approaches that they can infer and analyze cell-cell communication networks in an easily interpretable way.

    • Suoqin Jin
    • , Christian F. Guerrero-Juarez
    •  & Qing Nie

  • Article
    | Open Access

    Bulk and single-cell transcriptomic data can be a source of novel insights into how cells interact with each other. Here the authors develop ICELLNET, a global, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles.

    • Floriane Noël
    • , Lucile Massenet-Regad
    •  & Vassili Soumelis

  • Article
    | Open Access

    Single cell expression data allows for inferring cell-cell communication between cells expressing ligands and those expressing their cognate receptors. Here the authors present an updated and curated database of ligand-receptor pairs and a Python-based toolkit to construct and analyse communication networks from single cell and bulk expression data.

    • Rui Hou
    • , Elena Denisenko
    •  & Alistair R. R. Forrest

  • Article
    | Open Access

    Single-cell technologies are increasingly prominent in clinical applications, but predictive modelling with such data in large cohorts has remained computationally challenging. We developed a new algorithm, ‘VoPo’, for predictive modelling and visualization of single cell data for translational applications.

    • Natalie Stanley
    • , Ina A. Stelzer
    •  & Nima Aghaeepour

  • Article
    | Open Access

    Proteome activity has a major role in cancer progression and response to drugs. Here, the authors use comprehensive proteomic and phosphoproteomic data, in conjunction with drug-sensitivity screens, to generate a community resource consisting of landscapes of pathway and kinase activity across different cell lines

    • Martin Frejno
    • , Chen Meng
    •  & Bernhard Kuster

  • Article
    | Open Access

    Predicting an individual's response to therapy is an important goal for precision medicine. Here, the authors use an algorithm that takes into account the interaction type and directionality of signalling pathways in protein–protein interactions and find that their pathway analysis can predict essential genes, which may be a target for therapy.

    • Rotem Ben-Hamo
    • , Adi Jacob Berger
    •  & Ravid Straussman

  • Article
    | Open Access

    Segregation of an MSH1 RNAi transgene produces non-genetic memory that displays transgenerational inheritance in Arabidopsis. Here, the authors compare memory and non-memory full-sib progenies to show the involvement of DNA methylation reprogramming, involving the RdDM pathway, in transition to a heritable memory state.

    • Xiaodong Yang
    • , Robersy Sanchez
    •  & Sally A. Mackenzie

  • Article
    | Open Access

    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.

    • Matthew A. Reyna
    • , David Haan
    •  & Christian von Mering

  • Article
    | Open Access

    How reproducible human kidney organoids derived from different iPSC lines are, and how faithful they are to human kidney tissue remain unclear. Here, the authors use four human iPSC lines to derive kidney organoids and show how organoid composition is reproducible, comparable to human tissue and of improved quality after transplantation.

    • Ayshwarya Subramanian
    • , Eriene-Heidi Sidhom
    •  & Anna Greka

  • Article
    | Open Access

    Multi-omic profiling is a powerful approach to dissecting molecular mechanisms in disease. Here the authors generate whole proteome, phosphoproteome and transcriptome profiles from two mouse models of high-grade glioma driven by different oncogenes, and validate identified master regulators with a CRISPR screen.

    • Hong Wang
    • , Alexander K. Diaz
    •  & Junmin Peng

  • Article
    | Open Access

    The fraction of protein-protein interactions (PPIs) that can be disrupted without fitness effect is unknown. Here, the authors model how disease-causing mutations and common mutations carried by healthy people perturb the interactome, and estimate that <20% of human PPIs are completely dispensable.

    • Mohamed Ghadie
    •  & Yu Xia

  • Article
    | Open Access

    The directions of most human protein-protein interactions (PPIs) remain unknown. Here, the authors use cancer genomic and drug response data to infer the direction of signal flow in the human PPI network and show that the directed network improves drug target and cancer driver gene prioritization.

    • Dana Silverbush
    •  & Roded Sharan

  • Article
    | Open Access

    The genetic and pathogenetic basis of heart failure is incompletely understood. Here, the authors present a high-fidelity tissue collection from rapidly preserved failing and non-failing control hearts which are used for eQTL mapping and network analysis, resulting in the prioritization of PPP1R3A as a heart failure gene.

    • Pablo Cordero
    • , Victoria N. Parikh
    •  & Euan A. Ashley

  • Article
    | Open Access

    Genome-wide association studies (GWAS) have so far uncovered more than 200 loci for multiple sclerosis (MS). Here, the authors integrate data from various sources for a cell type-specific pathway analysis of MS GWAS results that specifically highlights the involvement of the immune system in disease pathogenesis.

    • Lohith Madireddy
    • , Nikolaos A. Patsopoulos
    •  & Sergio E. Baranzini

  • Article
    | Open Access

    Synergistic interactions may arise between regulators in complex molecular networks. Here, the authors develop OptiCon, a computational method for de novo identification of synergistic key regulators and investigate their potential roles as candidate targets for combination therapy.

    • Yuxuan Hu
    • , Chia-hui Chen
    •  & Kai Tan

  • Article
    | Open Access

    Protein phosphorylation has various regulatory functions. Here, the authors map 241 phosphorylation hotspot regions across 40 eukaryotic species, showing that they are enriched at interfaces and near catalytic residues, and enable the discovery of functionally important phospho-sites.

    • Marta J. Strumillo
    • , Michaela Oplová
    •  & Pedro Beltrao

  • Article
    | Open Access

    With the increasing obtainability of multi-OMICs data comes the need for easy to use data analysis tools. Here, the authors introduce Metascape, a biologist-oriented portal that provides a gene list annotation, enrichment and interactome resource and enables integrated analysis of multi-OMICs datasets.

    • Yingyao Zhou
    • , Bin Zhou
    •  & Sumit K. Chanda

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