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      Encoding information in synthetic metabolomes

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          Abstract

          Biomolecular information systems offer exciting potential advantages and opportunities to complement conventional semiconductor technologies. Much attention has been paid to information-encoding polymers, but small molecules also play important roles in biochemical information systems. Downstream from DNA, the metabolome is an information-rich molecular system with diverse chemical dimensions which could be harnessed for information storage and processing. As a proof of principle of small-molecule postgenomic data storage, here we demonstrate a workflow for representing abstract data in synthetic mixtures of metabolites. Our approach leverages robotic liquid handling for writing digital information into chemical mixtures, and mass spectrometry for extracting the data. We present several kilobyte-scale image datasets stored in synthetic metabolomes, which can be decoded with accuracy exceeding 99% using multi-mass logistic regression. Cumulatively, >100,000 bits of digital image data was written into metabolomes. These early demonstrations provide insight into some of the benefits and limitations of small-molecule chemical information systems.

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          Most cited references27

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          A 160-kilobit molecular electronic memory patterned at 10(11) bits per square centimetre.

          The primary metric for gauging progress in the various semiconductor integrated circuit technologies is the spacing, or pitch, between the most closely spaced wires within a dynamic random access memory (DRAM) circuit. Modern DRAM circuits have 140 nm pitch wires and a memory cell size of 0.0408 mum(2). Improving integrated circuit technology will require that these dimensions decrease over time. However, at present a large fraction of the patterning and materials requirements that we expect to need for the construction of new integrated circuit technologies in 2013 have 'no known solution'. Promising ingredients for advances in integrated circuit technology are nanowires, molecular electronics and defect-tolerant architectures, as demonstrated by reports of single devices and small circuits. Methods of extending these approaches to large-scale, high-density circuitry are largely undeveloped. Here we describe a 160,000-bit molecular electronic memory circuit, fabricated at a density of 10(11) bits cm(-2) (pitch 33 nm; memory cell size 0.0011 microm2), that is, roughly analogous to the dimensions of a DRAM circuit projected to be available by 2020. A monolayer of bistable, [2]rotaxane molecules served as the data storage elements. Although the circuit has large numbers of defects, those defects could be readily identified through electronic testing and isolated using software coding. The working bits were then configured to form a fully functional random access memory circuit for storing and retrieving information.
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            Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences

            Abstract Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.
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              Complexity of dopamine metabolism

              Parkinson’s disease (PD) coincides with a dramatic loss of dopaminergic neurons within the substantia nigra. A key player in the loss of dopaminergic neurons is oxidative stress. Dopamine (DA) metabolism itself is strongly linked to oxidative stress as its degradation generates reactive oxygen species (ROS) and DA oxidation can lead to endogenous neurotoxins whereas some DA derivatives show antioxidative effects. Therefore, DA metabolism is of special importance for neuronal redox-homeostasis and viability. In this review we highlight different aspects of dopamine metabolism in the context of PD and neurodegeneration. Since most reviews focus only on single aspects of the DA system, we will give a broader overview by looking at DA biosynthesis, sequestration, degradation and oxidation chemistry at the metabolic level, as well as at the transcriptional, translational and posttranslational regulation of all enzymes involved. This is followed by a short overview of cellular models currently used in PD research. Finally, we will address the topic from a medical point of view which directly aims to encounter PD.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – original draft
                Role: InvestigationRole: Writing – review & editing
                Role: Investigation
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2019
                3 July 2019
                : 14
                : 7
                : e0217364
                Affiliations
                [1 ] School of Engineering, Brown University, Providence, RI, United States of America
                [2 ] Department of Chemistry, Brown University, Providence, RI, United States of America
                University of Lincoln, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have submitted a provisional patent application (62/791,504) related to this work.

                Author information
                http://orcid.org/0000-0001-9791-704X
                Article
                PONE-D-19-06941
                10.1371/journal.pone.0217364
                6608926
                31269053
                692277e4-740f-447a-b8c6-707f3abe6d5e
                © 2019 Kennedy et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 March 2019
                : 10 May 2019
                Page count
                Figures: 5, Tables: 0, Pages: 12
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000185, Defense Advanced Research Projects Agency;
                Award ID: W911NF-18-2-0031
                Award Recipient :
                This research was supported by funding from the Defense Advanced Research Projects Agency (DARPA W911NF-18-2-0031) to BMR and JKR. The views, opinions and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolites
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolomics
                Medicine and Health Sciences
                Pharmacology
                Pharmacokinetics
                Drug Metabolism
                Physical Sciences
                Chemistry
                Analytical Chemistry
                Mass Spectrometry
                Matrix-Assisted Laser Desorption Ionization Mass Spectrometry
                Research and Analysis Methods
                Spectrum Analysis Techniques
                Mass Spectrometry
                Matrix-Assisted Laser Desorption Ionization Mass Spectrometry
                Computer and Information Sciences
                Information Theory
                Background Signal Noise
                Engineering and Technology
                Signal Processing
                Background Signal Noise
                Biology and life sciences
                Genetics
                DNA
                DNA metabolism
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA metabolism
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Protein Metabolism
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolic Pathways
                Custom metadata
                Mass spectra from this work may be downloaded from Metabolomics Workbench data repository (study ST001173). Raw data is also available from the Brown Digital Repository (DOI: 10.26300/jwv9-ew20).

                Uncategorized
                Uncategorized

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