References of "Nature Communications"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailInteractions between large molecules pose a puzzle for reference quantum mechanical methods
Yasmine S. Al-Hamdani; Péter R. Nagy; Andrea Zen et al

in Nature Communications (2021)

Detailed reference viewed: 32 (0 UL)
Full Text
Peer Reviewed
See detailA computer-guided design tool to increase the efficiency of cellular conversions
Del Sol Mesa, Antonio UL

in Nature Communications (2021)

Detailed reference viewed: 143 (24 UL)
Full Text
Peer Reviewed
See detailDynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature
Huziel E. Sauceda; Vassilev Galindo, Valentin UL; Stefan Chmiela et al

in Nature Communications (2021)

Detailed reference viewed: 36 (2 UL)
Full Text
Peer Reviewed
See detailCoulomb interactions between dipolar quantum fluctuations in van der Waals bound molecules and materials
Stoehr, Martin UL; Sadhukhan, Mainak; Al-Hamdani, Yasmine S. et al

in Nature Communications (2021), 12(1), 137

Mutual Coulomb interactions between electrons lead to a plethora of interesting physical and chemical effects, especially if those interactions involve many fluctuating electrons over large spatial scales ... [more ▼]

Mutual Coulomb interactions between electrons lead to a plethora of interesting physical and chemical effects, especially if those interactions involve many fluctuating electrons over large spatial scales. Here, we identify and study in detail the Coulomb interaction between dipolar quantum fluctuations in the context of van der Waals complexes and materials. Up to now, the interaction arising from the modification of the electron density due to quantum van der Waals interactions was considered to be vanishingly small. We demonstrate that in supramolecular systems and for molecules embedded in nanostructures, such contributions can amount to up to 6 kJ/mol and can even lead to qualitative changes in the long-range van der Waals interaction. Taking into account these broad implications, we advocate for the systematic assessment of so-called Dipole-Correlated Coulomb Singles in large molecular systems and discuss their relevance for explaining several recent puzzling experimental observations of collective behavior in nanostructured materials. [less ▲]

Detailed reference viewed: 151 (6 UL)
Full Text
Peer Reviewed
See detailLoss of Ambra1 promotes melanoma growth and invasion.
Di Leo, Luca; Bodemeyer, Valérie; Bosisio, Francesca M. et al

in Nature communications (2021), 12(1), 2550

Melanoma is the deadliest skin cancer. Despite improvements in the understanding of the molecular mechanisms underlying melanoma biology and in defining new curative strategies, the therapeutic needs for ... [more ▼]

Melanoma is the deadliest skin cancer. Despite improvements in the understanding of the molecular mechanisms underlying melanoma biology and in defining new curative strategies, the therapeutic needs for this disease have not yet been fulfilled. Herein, we provide evidence that the Activating Molecule in Beclin-1-Regulated Autophagy (Ambra1) contributes to melanoma development. Indeed, we show that Ambra1 deficiency confers accelerated tumor growth and decreased overall survival in Braf/Pten-mutated mouse models of melanoma. Also, we demonstrate that Ambra1 deletion promotes melanoma aggressiveness and metastasis by increasing cell motility/invasion and activating an EMT-like process. Moreover, we show that Ambra1 deficiency in melanoma impacts extracellular matrix remodeling and induces hyperactivation of the focal adhesion kinase 1 (FAK1) signaling, whose inhibition is able to reduce cell invasion and melanoma growth. Overall, our findings identify a function for AMBRA1 as tumor suppressor in melanoma, proposing FAK1 inhibition as a therapeutic strategy for AMBRA1 low-expressing melanoma. [less ▲]

Detailed reference viewed: 59 (3 UL)
Full Text
Peer Reviewed
See detailCritical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows
Van Den Bossche, Tim; Kunath, Benoît UL; Schallert, Kay et al

in Nature Communications (2021), 12(1), 7305

Abstract Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on ... [more ▼]

Abstract Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments. [less ▲]

Detailed reference viewed: 45 (0 UL)
Full Text
Peer Reviewed
See detailCommon diseases alter the physiological age-related blood microRNA profile.
Fehlmann, Tobias; Lehallier, Benoit; Schaum, Nicholas et al

in Nature communications (2020), 11(1), 5958

Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes in ... [more ▼]

Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes in age-related microRNAs by analyzing whole blood from 1334 healthy individuals. We observed a larger influence of the age as compared to the sex and provide evidence for a shift to the 5' mature form of miRNAs in healthy aging. The addition of 3059 diseased patients uncovered pan-disease and disease-specific alterations in aging profiles. Disease biomarker sets for all diseases were different between young and old patients. Computational deconvolution of whole-blood miRNAs into blood cell types suggests that cell intrinsic gene expression changes may impart greater significance than cell abundance changes to the whole blood miRNA profile. Altogether, these data provide a foundation for understanding the relationship between healthy aging and disease, and for the development of age-specific disease biomarkers. [less ▲]

Detailed reference viewed: 99 (2 UL)
Full Text
Peer Reviewed
See detailIntegration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance
Herold, Malte; Martinez Arbas, Susana UL; Narayanasamy, Shaman et al

in Nature Communications (2020)

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche ... [more ▼]

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts. [less ▲]

Detailed reference viewed: 175 (20 UL)
Full Text
Peer Reviewed
See detailDevelopmental GABA polarity switch and neuronal plasticity in Bioengineered Neuronal Organoids
Zafeiriou, Maria-Patapia; Bao, Guobin; Hudson, James et al

in Nature Communications (2020), 11(1), 3791

Detailed reference viewed: 104 (0 UL)
Full Text
Peer Reviewed
See detailGene regulatory network inference from sparsely sampled noisy data
Aalto, Atte UL; Viitasaari, Lauri; Ilmonen, Pauliina et al

in Nature Communications (2020), 11

The complexity of biological systems is encoded in gene regulatory networks. Unravelling this intricate web is a fundamental step in understanding the mechanisms of life and eventually developing ... [more ▼]

The complexity of biological systems is encoded in gene regulatory networks. Unravelling this intricate web is a fundamental step in understanding the mechanisms of life and eventually developing efficient therapies to treat and cure diseases. The major obstacle in inferring gene regulatory networks is the lack of data. While time series data are nowadays widely available, they are typically noisy, with low sampling frequency and overall small number of samples. This paper develops a method called BINGO to specifically deal with these issues. Benchmarked with both real and simulated time-series data covering many different gene regulatory networks, BINGO clearly and consistently outperforms state-of-the-art methods. The novelty of BINGO lies in a nonparametric approach featuring statistical sampling of continuous gene expression profiles. BINGO’s superior performance and ease of use, even by non-specialists, make gene regulatory network inference available to any researcher, helping to decipher the complex mechanisms of life. [less ▲]

Detailed reference viewed: 203 (22 UL)
Full Text
Peer Reviewed
See detailManipulating magnetoelectric energy landscape in multiferroics
Huang, Yen-Lin; Nikonov, Dmitri; Addiego, Christopher et al

in Nature Communications (2020)

Detailed reference viewed: 26 (2 UL)
Full Text
Peer Reviewed
See detailChemical instability at chalcogenide surfaces impacts chalcopyrite devices well beyond the surface
Colombara, Diego UL; Elanzeery, Hossam UL; Nicoara, Nicoleta et al

in Nature Communications (2020)

Detailed reference viewed: 246 (5 UL)
Full Text
Peer Reviewed
See detailEvent-related functional MRI of awake behaving pigeons at 7T
Behroozi, M.; Helluy, X.; Ströckens, F. et al

in Nature Communications (2020), 11(1),

Detailed reference viewed: 41 (0 UL)
Full Text
Peer Reviewed
See detailA three-order-parameter bistable magnetoelectric multiferroic metal
Urru, Andrea; Ricci, Francesco; Filippetti, Alessio et al

in Nature Communications (2020)

Detailed reference viewed: 20 (0 UL)
Full Text
Peer Reviewed
See detailMachine learning for chemical discovery
Tkatchenko, Alexandre UL

in Nature Communications (2020)

Detailed reference viewed: 136 (2 UL)
Full Text
Peer Reviewed
See detailThe atypical chemokine receptor ACKR3/CXCR7 is a broad-spectrum scavenger for opioid peptides.
Meyrath, Max; Szpakowska, Martyna; Zeiner, Julian et al

in Nature communications (2020), 11(1), 3033

Endogenous opioid peptides and prescription opioid drugs modulate pain, anxiety and stress by activating opioid receptors, currently classified into four subtypes. Here we demonstrate that ACKR3/CXCR7 ... [more ▼]

Endogenous opioid peptides and prescription opioid drugs modulate pain, anxiety and stress by activating opioid receptors, currently classified into four subtypes. Here we demonstrate that ACKR3/CXCR7, hitherto known as an atypical scavenger receptor for chemokines, is a broad-spectrum scavenger of opioid peptides. Phylogenetically, ACKR3 is intermediate between chemokine and opioid receptors and is present in various brain regions together with classical opioid receptors. Functionally, ACKR3 is a scavenger receptor for a wide variety of opioid peptides, especially enkephalins and dynorphins, reducing their availability for the classical opioid receptors. ACKR3 is not modulated by prescription opioids, but we show that an ACKR3-selective subnanomolar competitor peptide, LIH383, can restrain ACKR3's negative regulatory function on opioid peptides in rat brain and potentiate their activity towards classical receptors, which may open alternative therapeutic avenues for opioid-related disorders. Altogether, our results reveal that ACKR3 is an atypical opioid receptor with cross-family ligand selectivity. [less ▲]

Detailed reference viewed: 99 (2 UL)
Full Text
Peer Reviewed
See detailFrom quantum to continuum mechanics in the delamination of atomically-thin layers from substrates
Hauseux, Paul; Nguyen, Thanh-Tung; Ambrosetti, Alberto et al

in Nature Communications (2020)

Detailed reference viewed: 118 (15 UL)
Full Text
Peer Reviewed
See detailUnifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
Schütt, Kristof; Gastegger, Michael; Tkatchenko, Alexandre UL et al

in Nature Communications (2019), 10(1), 5024

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate ... [more ▼]

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of freedom of a molecule, which limits their applicability for reactive chemistry and chemical analysis. Here we present a deep learning framework for the prediction of the quantum mechanical wavefunction in a local basis of atomic orbitals from which all other ground-state properties can be derived. This approach retains full access to the electronic structure via the wavefunction at force-field-like efficiency and captures quantum mechanics in an analytically differentiable representation. On several examples, we demonstrate that this opens promising avenues to perform inverse design of molecular structures for targeting electronic property optimisation and a clear path towards increased synergy of machine learning and quantum chemistry. [less ▲]

Detailed reference viewed: 240 (4 UL)
Full Text
Peer Reviewed
See detailData driven discovery of cyber physical systems
Yuan, Ye; Tang, Xiuchuan; Zhou, Wei et al

in Nature Communications (2019)

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved ... [more ▼]

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber- physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance. [less ▲]

Detailed reference viewed: 69 (6 UL)