Systems biology articles within Nature Communications

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  • Article
    | Open Access

    In metabolic engineering, releasing of carbon in the form of CO2 leads to significant decrease of atomic economy. Here, the authors construct a carbon-conserving pathway, which converts glucose into acetyl phosphate without carbon loss, with oscillatory system to improve production of multiple target compounds.

    • Likun Guo
    • , Min Liu
    •  & Guang Zhao

  • Article
    | Open Access

    Memory is a basic tenet of intelligent biological systems. Here the authors engineered a programmable and expandable iteration of recombinase-based synthetic memory (interception) that functions post-translation, resulting in faster recombination.

    • Andrew E. Short
    • , Dowan Kim
    •  & Corey J. Wilson

  • Article
    | Open Access

    Regulated subcellular localization changes control protein function. Here, the authors provide a seamless spatial proteomics pipeline for mapping whole-cell protein localization dynamics, which includes a scalable workflow and a software suite for automated data analysis and visualization.

    • Julia P. Schessner
    • , Vincent Albrecht
    •  & Georg H. H. Borner

  • Comment
    | Open Access

    Molecular chaperones establish essential protein-protein interaction networks. Modified versions of these assemblies are generally enriched in certain maladies. A study published in Nature Communications used epichaperomics to identify unique changes occurring in chaperone-formed protein networks during mitosis in cancer cells.

    • Mark R. Woodford
    • , Dimitra Bourboulia
    •  & Mehdi Mollapour

  • Article
    | Open Access

    Genetic code expansion is limited by the degeneracy of the 61 sense codons which encode for only 20 amino acids. Here, the authors show that by combining hyperaccurate ribosomes and in vitro transcribed tRNAs, dramatic and extensive breaking of sense codon degeneracy can be achieved.

    • Clinton A. L. McFeely
    • , Bipasana Shakya
    •  & Matthew C. T. Hartman

  • Article
    | Open Access

    The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.

    • Sandra Correa Córdoba
    • , Hao Tong
    •  & Zoran Nikoloski

  • Article
    | Open Access

    Mature fields of engineering use physics-based models to design systems that work reliably the first time. Here the authors show how a similar approach can be used to design and build a cellular-scale system, protein synthesis, from scratch.

    • Akshay J. Maheshwari
    • , Jonathan Calles
    •  & Drew Endy

  • Article
    | Open Access

    The heterogeneity of single cell responses during infection have been reported to influence disease outcome. Here, Pietilä et al characterize cellular heterogeneity during Herpes Simplex Virus 1 infection using a multimodal approach that resolves gene expression, proteomic and spatial details at the single cell level.

    • Maija K. Pietilä
    • , Jana J. Bachmann
    •  & Cornel Fraefel

  • Article
    | Open Access

    Senescence and quiescence are considered different cell states but are hard to distinguish. Here, single-cell imaging followed by immunostaining reveals that the intensities of senescence biomarkers are graded rather than binary, reflecting the duration of cell-cycle withdrawal rather than irreversible cell-cycle arrest.

    • Humza M. Ashraf
    • , Brianna Fernandez
    •  & Sabrina L. Spencer

  • Article
    | Open Access

    Chronic intestinal inflammatory diseases including ulcerative colitis and Crohn’s disease display extensive heterogeneity in the immunopathology, disease manifestation and response to treatment. Here the authors apply single cell transcriptomic and spatial molecular imaging, and characterise macrophage and neutrophils in samples from patients with inflammatory bowel diseases.

    • Alba Garrido-Trigo
    • , Ana M. Corraliza
    •  & Azucena Salas

  • Article
    | Open Access

    Bacterial two-component systems consist of a sensor histidine kinase (HK) that perceives a signal, and a cognate response regulator (RR) that modulates target gene expression. Here, the authors combine experiments and mathematical modelling to show that phosphorylated HKs can be sequestered by non-cognate RRs, which prevents responses to weak signals.

    • Gaurav D. Sankhe
    • , Rubesh Raja
    •  & Deepak Kumar Saini

  • Article
    | Open Access

    Plant-derived phenylpropanoids have diverse industrial applications ranging from flavours and fragrances to polymers and pharmaceuticals. Here the authors present a tripartite microbial coculture with mix-and-match flexibility and had improved stability within an engineered living material platform for de novo production of several plant-derived phenylpropanoids.

    • Sierra M. Brooks
    • , Celeste Marsan
    •  & Hal S. Alper

  • Article
    | Open Access

    Identification and classification of cells in multiplexed microscopy remain challenging. Here, the authors propose CellSighter, which uses neural networks to perform cell classification directly on multiplexed images, thus leveraging the spatial expression characteristics of proteins.

    • Yael Amitay
    • , Yuval Bussi
    •  & Leeat Keren

  • Article
    | Open Access

    Deciduous trees exhibit autumn senescence driven by environmental seasonality. Here, the authors show that senescence timing in aspen tree genotypes depends on environmental changes but also on the ability of each genotype to sustain stress tolerance mediated by the phytohormone salicylic acid.

    • Jenna Lihavainen
    • , Jan Šimura
    •  & Stefan Jansson

  • Article
    | Open Access

    Post-acute sequelae of COVID-19 (PASC) has heterogenous presentation and complex etiology. Here the authors profile peripheral blood of patients with PASC and analyze by machine-learning to identify immune and serology features that allow the stratification of PASC into inflammatory and non-inflammatory types for better diagnosis and therapy-planning.

    • Matthew C. Woodruff
    • , Kevin S. Bonham
    •  & Ignacio Sanz

  • Article
    | Open Access

    Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here, the authors present a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks.

    • Matteo Mori
    • , Chuankai Cheng
    •  & Terence Hwa

  • Article
    | Open Access

    The degradation of PET using PETase enzymes has great potential but can face problems with incomplete degradation. Here, the authors identified two BHETases from the environment and engineered them to improve their hydrolysis efficiency for applications in dual-enzyme PET recycling and tandem chemical-enzymatic PET upcycling systems.

    • Anni Li
    • , Yijie Sheng
    •  & He Huang

  • Article
    | Open Access

    A problem in network biology is identification of context-specific networks. Here the authors report Multi-Omics Binary Integration via Lasso Ensembles (MOBILE) to nominate molecular features associated with cellular phenotypes and pathways, and use this to assess interferon-γ regulated PD-L1 expression.

    • Cemal Erdem
    • , Sean M. Gross
    •  & Marc R. Birtwistle

  • Article
    | Open Access

    Keystone taxa in ecological communities are native taxa that have an especially important role in the stability of their ecosystem. This study introduces a novel method for detecting keystones in microbial communities by comparing data with and without specific species.

    • Guy Amit
    •  & Amir Bashan

  • Article
    | Open Access

    In cancer, interactions between treatment-sensitive and resistant cells can influence the effectiveness of therapies. Here, the authors use experimental and mathematical models to explore interactions between ER+ breast cancer cell lineages that are sensitive or resistant to CDK4/6 inhibition, revealing the role of facilitative growth.

    • Rena Emond
    • , Jason I. Griffiths
    •  & Andrea H. Bild

  • Article
    | Open Access

    The ability to independently control the expression of different genes is important for quantitative biology. Here, the authors report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of a wide range of inducible transcriptional systems, including a new, highly light sensitive LOV-transcription factor.

    • Vojislav Gligorovski
    • , Ahmad Sadeghi
    •  & Sahand Jamal Rahi

  • Article
    | Open Access

    Epichaperomics allow the study of protein-protein interactions and their alterations, but probes have been limited to capturing HSP90 epichaperomes. Here, the authors introduce and validate a toolset of HSP70 epichaperome ligands, and use them in epichaperomics to identify a mechanism with which cancer cells can enhance the fitness of mitotic protein networks.

    • Anna Rodina
    • , Chao Xu
    •  & Gabriela Chiosis

  • 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

    Resource competition can be the cause of unintended coupling between co-expressed genetic constructs. Here the authors quantify the resource load imposed by different mammalian genetic components to identify construct designs with increased performance and reduced resource footprint.

    • Roberto Di Blasi
    • , Mara Pisani
    •  & Francesca Ceroni

  • Article
    | Open Access

    Predicting the evolution of engineered cell populations is an increasingly popular topic in biotechnology. Here the authors build a model that explores evolution in engineered cell populations which can generate hypotheses that could lead to important insights into strategies for assessing and mitigating the effects of evolution.

    • Duncan Ingram
    •  & Guy-Bart Stan

  • Article
    | Open Access

    The authors present a workflow integrating metabolic perturbations with protein structural analysis to identify drug off-targets, demonstrating how combining machine learning methods with mechanistic analyses can benefit off-target identification.

    • Sourav Chowdhury
    • , Daniel C. Zielinski
    •  & Eugene I. Shakhnovich

  • Article
    | Open Access

    A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, the authors develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters.

    • Aqib Hasnain
    • , Shara Balakrishnan
    •  & Enoch Yeung

  • Article
    | Open Access

    Ultrasensitive, real-time profiling of bio-analytes is a prerequisite for precision medicine. Here, the authors present a versatile bio-electronic interface (VIBE) to sense signaling cascade-guided receptor-ligand interactions and show that it can detect hormone levels in blood samples and differentiate individual metabolic conditions.

    • Preetam Guha Ray
    • , Debasis Maity
    •  & Martin Fussenegger

  • Article
    | Open Access

    In the variety of biological and social networks, the validation of experimental data is done by comparing an overlap with reference networks. The authors introduce a positive statistical benchmark corresponding to the best possible overlap between two networks to threshold and validate new experimental datasets.

    • Bingjie Hao
    •  & István A. Kovács

  • Article
    | Open Access

    Better understanding of a trade-off between the speed and accuracy of decision-making is relevant for mapping biological intelligence to machines. The authors introduce a brain-inspired learning algorithm to uncover dependencies in individual fMRI networks with features of neural activity and predict inter-individual differences in decision-making.

    • Michael Schirner
    • , Gustavo Deco
    •  & Petra Ritter

  • Article
    | Open Access

    Inflammatory skin diseases are frequently associated with dysregulation of cutaneous immunity. Here the authors perform human challenge with house dust mite allergen in patients with atopic dermatitis and explore the molecular network determining tolerance versus inflammation and identify a role for metallothioneins in the modulation of allergen induced inflammation.

    • Sofia Sirvent
    • , Andres F. Vallejo
    •  & Marta E. Polak

  • Article
    | Open Access

    Current methods to assess circadian biological parameters can be labor intensive. Here, the authors establish a method for estimating circadian entrainment characteristics using simple experiments and mathematical modeling, revealing the responsiveness of circadian rhythms to diverse stimuli in the mammalian circadian clock.

    • Kosaku Masuda
    • , Naohiro Kon
    •  & Arisa Hirano

  • Article
    | Open Access

    Here, Seelbinder et al. show high Candida levels in cancer patients’ stool to correlate with greater metabolically flexibility but less robust bacterial communities and, combined with machine learning models to predict Candida levels from bacterial data, suggest that lactate producing bacteria may fuel Candida overgrowth in the gut during dysbiosis.

    • Bastian Seelbinder
    • , Zoltan Lohinai
    •  & Gianni Panagiotou

  • Article
    | Open Access

    One of the main challenges hampering the development of kinetic models is the lack of kinetic parameters for many enzymatic reactions. Here, the authors introduce a framework to explore the catalytically optimal operating conditions of any complex enzyme mechanism from an evolutionary perspective.

    • Asli Sahin
    • , Daniel R. Weilandt
    •  & Vassily Hatzimanikatis

  • Article
    | Open Access

    It’s challenging to capture “hidden” drivers that may not be genetically-altered or differentially-expressed from omics data. Here the authors developed NetBID2, a comprehensive network-based toolbox with versatile features, enabling the integration of multi-omics data to expose such hidden drivers.

    • Xinran Dong
    • , Liang Ding
    •  & Jiyang Yu

  • Article
    | Open Access

    Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. Here the authors combine construction of over 20 synthetic gene regulatory networks with mathematical modeling to exemplify how gene regulatory networks provide robustness in face of mutations while enabling transitions to innovative phenotypes.

    • Javier Santos-Moreno
    • , Eve Tasiudi
    •  & Yolanda Schaerli

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