The Cognitive Cell: Bacterial Behavior Reconsidered
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Inter Scientific Inquiry • Nature • Technology • Evolution • Research
Inter Scientific InquIry • nature • technology • evolutIon • research vol. 5 - august 2018 INTER SCIENTIFIC CONTENIDO CONTENTS MENSAJE DEL RECTOR/ MESSAGE FROM THE CHANCELLOR………………………………………………………..1 MENSAJE DE LA DECANA DE ASUNTOS ACADÉMICOS/ MESSAGE FROM THE DEAN OF ACADEMIC AFFAIRS………………………………………………………………………………………………1 DESDE EL ESCRITORIO DE LA EDITORA/ FROM THE EDITOR’S DESK…………………………………………....2 INVESTIGACIÓN/ RESEARCH ARTICLES………………………………………………………………………….....3-19 Host plant preference of Danaus plexippus larvae in the subtropical dry forest in Guánica, Puerto Rico………………………………………………………………………………………………......…3 Preferencia de plantas hospederas por parte de las larvas de Danaus plexippus en el bosque seco de Guánica, Puerto Rico López, Laysa, Santiago, Jonathan, and Puente-Rolón, Alberto Predatory behavior and prey preference of Leucauge sp. in Mayaguez, Puerto Rico……….…...7 Comportamiento de depredación y preferencia de presa de arañas del género Leucauge en Mayaguez, Puerto Rico Geli-Cruz, Orlando, Ramos-Maldonado, Frank, and Puente-Rolón, Alberto Construction and screening of soil metagenomic libraries: identification of hydrolytic metabolic activity………………………………………………………………………..……..…………....13 Construcción y prueba de bibliotecas metagenómicas de suelo: identificación de actividad metabólica hidrolítica Jiménez-Serrano, Edgar, Justiniano-Santiago, Jeydien, Reyes, Yazmin, Rosa-Matos, Raquel, Vélez- Cardona, Wilmarie, Huertas-Meléndez, Stephanie and Pagán-Jiménez, María LA INVESTIGACIÓN EN EL CAMPUS/ RESEARCH ON CAMPUS ……………………………………………………20 -
(12) United States Patent (10) Patent No.: US 8,513,329 B2 Lake Et Al
USOO8513329B2 (12) United States Patent (10) Patent No.: US 8,513,329 B2 Lake et al. (45) Date of Patent: Aug. 20, 2013 (54) CHEMICAL ADDITIVES TO MAKE 6,296,889 B1 10/2001 Ott et al. POLYMERIC MATERALS 6,635,692 B1 10/2003 Christie et al. 7,037,983 B2 5/2006 Huang et al. BODEGRADABLE 7,053,130 B2 5/2006 Nagarajan 7,067,596 B2 6/2006 Bastioli et al. (75) Inventors: John Allen Lake, Cedar Crest, NM 7,265,160 B2 * 9/2007 Oka et al. ..................... 521 50.5 (US); Samuel David Adams, 7,368,503 B2 5/2008 Hale Albuquerque, NM (US) 7,369,503 B2 * 5/2008 Takahashi et al. ............ 370,236 s 7,560,266 B2 7/2009 Bramucci et al. 7,812,066 B2 10/2010 Takenaka et al. (73) Assignee: Bio-Tec Environmental, LLC, 7.816,424 B2 10/2010 Takahashi et al. Albuquerque, NM (US) 8.222,316 B2 7/2012 Lake et al. 2003. O157214 A1 8/2003 Bonsignore et al. (*) Notice: Subject to any disclaimer, the term of this 2004.0068059 Al 42004 Katayama et al. patent is extended or adjusted under 35 3.SSA A. 2. MEC. et ca.ea U.S.C. 154(b) by 158 days. 2005. O1541 14 A1 7, 2005 Hale 2005/O181157 A1 8, 2005 Otome (21) Appl. No.: 12/113,844 2005/0181158 A1 8/2005 Otome et al. 2005/0208095 A1 9, 2005 Hunter et al. (22) Filed: May 1, 2008 2007, OO 10632 A1 1/2007 Kaplanet al. -
Pulse Generation in the Quorum Machinery of Pseudomonas Aeruginosa
This is a repository copy of Pulse generation in the quorum machinery of Pseudomonas aeruginosa. White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/116745/ Version: Published Version Article: Alfiniyah, Cicik Alfiniyah, Bees, Martin Alan and Wood, Andrew James orcid.org/0000- 0002-6119-852X (2017) Pulse generation in the quorum machinery of Pseudomonas aeruginosa. Bulletin of Mathematical Biology. pp. 1360-1389. ISSN 1522-9602 https://doi.org/10.1007/s11538-017-0288-z Reuse This article is distributed under the terms of the Creative Commons Attribution (CC BY) licence. This licence allows you to distribute, remix, tweak, and build upon the work, even commercially, as long as you credit the authors for the original work. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Bull Math Biol (2017) 79:1360–1389 DOI 10.1007/s11538-017-0288-z ORIGINAL ARTICLE Pulse Generation in the Quorum Machinery of Pseudomonas aeruginosa Cicik Alfiniyah1,2 · Martin A. Bees1 · A. Jamie Wood1,3 Received: 28 September 2016 / Accepted: 3 May 2017 / Published online: 19 May 2017 © The Author(s) 2017. This article is an open access publication Abstract Pseudomonas aeruginosa is a Gram-negative bacterium that is responsible for a wide range of infections in humans. -
Major Evolutionary Transitions in Individuality COLLOQUIUM
PAPER Major evolutionary transitions in individuality COLLOQUIUM Stuart A. Westa,b,1, Roberta M. Fishera, Andy Gardnerc, and E. Toby Kiersd aDepartment of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom; bMagdalen College, Oxford OX1 4AU, United Kingdom; cSchool of Biology, University of St. Andrews, Dyers Brae, St. Andrews KY16 9TH, United Kingdom; and dInstitute of Ecological Sciences, Faculty of Earth and Life Sciences, Vrije Universiteit, 1081 HV, Amsterdam, The Netherlands Edited by John P. McCutcheon, University of Montana, Missoula, MT, and accepted by the Editorial Board March 13, 2015 (received for review December 7, 2014) The evolution of life on earth has been driven by a small number broken down into six questions. We explore what is already known of major evolutionary transitions. These transitions have been about the factors facilitating transitions, examining the extent to characterized by individuals that could previously replicate inde- which we can generalize across the different transitions. Ultimately, pendently, cooperating to form a new, more complex life form. we are interested in the underlying evolutionary and ecological For example, archaea and eubacteria formed eukaryotic cells, and factors that drive major transitions. cells formed multicellular organisms. However, not all cooperative Defining Major Transitions groups are en route to major transitions. How can we explain why major evolutionary transitions have or haven’t taken place on dif- A major evolutionary transition has been most broadly defined as a change in the way that heritable information is stored and ferent branches of the tree of life? We break down major transi- transmitted (2). We focus on the major transitions that lead to a tions into two steps: the formation of a cooperative group and the new form of individual (Table 1), where the same problems arise, transformation of that group into an integrated entity. -
Forms of Intelligence. Concept Cards for Co-Species Care
forms of intelligence. concept cards for co-species care. by kaajal modi 2 forms of intelligence. concept cards for co-species care. 3 contents. the cards. 4 card footnotes. 7 cross-species collaborators. 34 the team. 39 symbols & symbioses. 41 Forms of Intelligence is an ongoing project led by Knowle references. 47 West Media Centre exploring how expanded understandings of ‘intelligence’ can inspire the design and creation of new technologies and systems for the benefit of all. Commissioned by Knowle West Media Centre and Digital Cultures Research Centre © September 2020 4 forms of intelligence. concept cards for co-species care. 5 who are they for? the The cards are designed to act as conversation starters and inspirational prompts. for anyone involved in a making process. How often do you challenge yourself to stop and think cards. differently, to see from a different perspective, or think deeply about who or what is being impacted by your decisions? The cards are draw on different forms of animal, plant and microbial intelligence that often get overlooked in human- what are they? led projects and processes. They also invite you to reflect on The cards and this booklet were commissioned by Knowle the humans who are connected to these organisms, whether West Media Centre as part of the Forms of Intelligence directly, by working with them, or indirectly, by sharing land project, and were made by artist and researcher Kaajal Modi. and resources with them. The cards have been made in response to and are inspired by If you are looking for inspiration and ready to open your a series of collaborative workshops between eight people from mind to think more expansively about all living beings, then Knowle West, Bristol, Kent, and Colombia with expertise in these cards are for you. -
Genome-Inspired Chemical Exploration of Marine Fungus Aspergillus Fumigatus MF071
marine drugs Article Genome-Inspired Chemical Exploration of Marine Fungus Aspergillus fumigatus MF071 Jianying Han 1,2 , Miaomiao Liu 1 , Ian D. Jenkins 1, Xueting Liu 3, Lixin Zhang 2,3, Ronald J. Quinn 1,* and Yunjiang Feng 1,* 1 Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD 4111, Australia; jianying.han@griffithuni.edu.au (J.H.); miaomiao.liu@griffith.edu.au (M.L.); i.jenkins@griffith.edu.au (I.D.J.) 2 Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; [email protected] 3 State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China; [email protected] * Correspondence: r.quinn@griffith.edu.au (R.J.Q.); y.feng@griffith.edu.au (Y.F.); Tel.: +61-7-3735-6006 (R.J.Q.); +61-7-3735-8367 (Y.F.) Received: 8 June 2020; Accepted: 2 July 2020; Published: 6 July 2020 Abstract: The marine-derived fungus Aspergillus fumigatus MF071, isolated from sediment collected from the Bohai Sea, China, yielded two new compounds 19S,20-epoxy-18-oxotryprostatin A (1) and 20-hydroxy-18-oxotryprostatin A (2), in addition to 28 known compounds (3–30). The chemical structures were established on the basis of 1D, 2D NMR and HRESIMS spectroscopic data. This is the first report on NMR data of monomethylsulochrin-4-sulphate (4) and pseurotin H (10) as naturally occurring compounds. Compounds 15, 16, 20, 23, and 30 displayed weak antibacterial activity (minimum inhibitory concentration: 100 µg/mL). Compounds 18 and 19 exhibited strong activity against S. -
Macromolecular Networks and Intelligence in Microorganisms
HYPOTHESIS AND THEORY ARTICLE published: 22 July 2014 doi: 10.3389/fmicb.2014.00379 Macromolecular networks and intelligence in microorganisms Hans V. Westerhoff 1,2,3 †, Aaron N. Brooks 4,5 †, Evangelos Simeonidis 4,6 †, Rodolfo García-Contreras 7†, Fei He 8 , Fred C. Boogerd 1, Victoria J. Jackson 9 , Valeri Goncharuk 10,11,12 and Alexey Kolodkin 4,6 * 1 Department of Molecular Cell Physiology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands 2 Manchester Centre for Integrative Systems Biology, The University of Manchester, Manchester, UK 3 Synthetic Systems Biology, University of Amsterdam, Amsterdam, Netherlands 4 Institute for Systems Biology, Seattle, WA, USA 5 Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA 6 Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg 7 Departamento de Bioquímica, Instituto Nacional de Cardiología, Mexico City, Mexico 8 Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK 9 School of Computer Science, The University of Manchester, Manchester, UK 10 Netherlands Institute for Neuroscience, Amsterdam, Netherlands 11 Russian Cardiology Research Center, Moscow, Russia 12 Department of Medicine, Center for Alzheimer and Neurodegenerative Research, University of Alberta, Edmonton, AB, Canada Edited by: Living organisms persist by virtue of complex interactions among many components Kevin Bradley Clark, Veterans Affairs organized into dynamic, environment-responsive networks that span multiple scales and Greater Los Angeles Healthcare System, USA dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate Reviewed by: Francisca Fernández-Piñas, and interpret this information, and then activate a response. -
A Model of Symmetry Breaking in Collective Decision-Making
A Model of Symmetry Breaking in Collective Decision-Making Heiko Hamann1, Bernd Meyer2, Thomas Schmickl1, and Karl Crailsheim1 1 Artificial Life Lab of the Dep. of Zoology, Karl-Franzens University Graz, Austria {heiko.hamann, thomas.schmickl, karl.crailsheim}@uni-graz.at 2 FIT Centre for Research in Intelligent Systems, Monash University, Melbourne [email protected] Abstract. Symmetry breaking is commonly found in self-organized col- lective decision making. It serves an important functional role, specifi- cally in biological and bio-inspired systems. The analysis of symmetry breaking is thus an important key to understanding self-organized deci- sion making. However, in many systems of practical importance avail- able analytic methods cannot be applied due to the complexity of the scenario and consequentially the model. This applies specifically to self- organization in bio-inspired engineering. We propose a new modeling approach which allows us to formally analyze important properties of such processes. The core idea of our approach is to infer a compact model based on stochastic processes for a one-dimensional symmetry parameter. This enables us to analyze the fundamental properties of even complex collective decision making processes via Fokker–Planck theory. We are able to quantitatively address the effectiveness of symmetry breaking, the stability, the time taken to reach a consensus, and other parameters. This is demonstrated with two examples from swarm robotics. 1 Introduction Self-organization is one of the fundamental mechanism used in nature to achieve flexible and adaptive behavior in unpredictable environments [1]. Particularly collective decision making in social groups is often driven by self-organizing pro- cesses. -
Quorum Sensing
SBT1103 / MICROBIOLOGY / UNIT V / BIOTECH/BIOMED/BIOINFO II SEMESTER / I YEAR UNIT – V APPLICATIONS OF MICROBIOLOGY 1 SBT1103 / MICROBIOLOGY / UNIT V / BIOTECH/BIOMED/BIOINFO II SEMESTER / I YEAR Microbial ecology The great plate count anomaly. Counts of cells obtained via cultivation are orders of magnitude lower than those directly observed under the microscope. This is because microbiologists are able to cultivate only a minority of naturally occurring microbes using current laboratory techniques, depending on the environment.[1] Microbial ecology (or environmental microbiology) is the ecology of microorganisms: their relationship with one another and with their environment. It concerns the three major domains of life—Eukaryota, Archaea, and Bacteria—as well as viruses. Microorganisms, by their omnipresence, impact the entire biosphere. Microbial life plays a primary role in regulating biogeochemical systems in virtually all of our planet's environments, including some of the most extreme, from frozen environments and acidic lakes, to hydrothermal vents at the bottom of deepest oceans, and some of the most familiar, such as the human small intestine.[3][4] As a consequence of the quantitative magnitude of microbial life (Whitman and coworkers calculated 5.0×1030 cells, eight orders of magnitude greater than the number of stars in the observable universe[5][6]) microbes, by virtue of their biomass alone, constitute a significant carbon sink.[7] Aside from carbon fixation, microorganisms’ key collective metabolic processes (including -
AI-To-Microbe Architecture: Simulation, Intelligence, Consciousness
Dennis Dollens Universitat Internacional de Catalunya, Barcelona. ESARQ [email protected] AI-to-Microbe Architecture: Simulation, Intelligence, Consciousness Abstract Keywords This paper probes questions of how big machines— Metabolic Architecture, Artificial Intelligence (AI), buildings—can function as hybrid metabolic/AI ALife, Alan Turing, Ludwig Wittgenstein, Computational organisms. Focusing on AI, artificial life (ALife), and Simulation. microbial intelligence I look through the lens of Ludwig Wittgenstein’s Tractatus and Alan Turing’s algorithmic 1. Propositions Toward Metabolic plant simulations to source modernist theory for Architectures biointelligent architectures. I’m using scant records and testimony interpreted through each thinker’s writings, Research strategies to regulate exploratory sets of architecture, and/or simulations. This text is then a generative design actions are called upon here for device for considering ways-of-being within, and ways- reasoning the inclusion of AI, synthetic life, and bio- of-thinking about, theory/practice for the fusion of algorithmic generation into the production of metabolic architectures. These exploratory tactics underwrite biological-to-biosynthetic intelligences (microbes, plants, animals, AI, machines.) Resulting theory thereafter hypothesizing biointelligent buildings as parts of nature. supports the development of bioremedial environmental Therefore, to link theory and observation I evolve cleanup addressing climate change. My proposition then strategies for the investigation of matter and forces deploys biomimetic and laboratory data to nurture starting with symbolic languages to sort types of metabolically driven intelligences partnered with AI intelligence. in the production of architectures. That ontological pathway stems from machine learning, bio-surveillance, Specifically, concepts-terms such as “atomic facts,” and digital simulation at object, agent, and urban scales. -
Quorum Sensing in Bacteria
17 Aug 2001 12:48 AR AR135-07.tex AR135-07.SGM ARv2(2001/05/10) P1: GDL Annu. Rev. Microbiol. 2001. 55:165–99 Copyright c 2001 by Annual Reviews. All rights reserved QUORUM SENSING IN BACTERIA Melissa B. Miller and Bonnie L. Bassler Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544-1014; e-mail: [email protected], [email protected] Key Words autoinducer, homoserine lactone, two-component system, cell-cell communication, virulence ■ Abstract Quorum sensing is the regulation of gene expression in response to fluctuations in cell-population density. Quorum sensing bacteria produce and release chemical signal molecules called autoinducers that increase in concentration as a function of cell density. The detection of a minimal threshold stimulatory con- centration of an autoinducer leads to an alteration in gene expression. Gram-positive and Gram-negative bacteria use quorum sensing communication circuits to regulate a diverse array of physiological activities. These processes include symbiosis, virulence, competence, conjugation, antibiotic production, motility, sporulation, and biofilm for- mation. In general, Gram-negative bacteria use acylated homoserine lactones as au- toinducers, and Gram-positive bacteria use processed oligo-peptides to communicate. Recent advances in the field indicate that cell-cell communication via autoinducers occurs both within and between bacterial species. Furthermore, there is mounting data suggesting that bacterial autoinducers elicit specific responses from host organisms. Although the nature of the chemical signals, the signal relay mechanisms, and the target genes controlled by bacterial quorum sensing systems differ, in every case the ability to communicate with one another allows bacteria to coordinate the gene expression, and therefore the behavior, of the entire community. -
A Biophysical Limit for Quorum Sensing in Biofilms
A biophysical limit for quorum sensing in biofilms Avaneesh V. Narlaa , David Bruce Borensteinb, and Ned S. Wingreenc,d,1 aDepartment of Physics, University of California San Diego, La Jolla, CA 92092; bPrivate address, Maplewood NJ, 07040; cDepartment of Molecular Biology, Princeton University, Princeton, NJ 08544; and dLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544 Edited by E. Peter Greenberg, University of Washington, Seattle, WA, and approved April 8, 2021 (received for review November 1, 2020) Bacteria grow on surfaces in complex immobile communities against chemicals and predators, and facilitating horizontal gene known as biofilms, which are composed of cells embedded in transfer. an extracellular matrix. Within biofilms, bacteria often interact In simple models of biofilms that incorporate realistic with members of their own species and cooperate or compete reaction-diffusion effects, Xavier and Foster (19) found that with members of other species via quorum sensing (QS). QS is matrix production allows cells to push descendants outward a process by which microbes produce, secrete, and subsequently from a surface into a more O2-rich environment. Consequently, detect small molecules called autoinducers (AIs) to assess their they found that matrix production provides a strong competitive local population density. We explore the competitive advantage advantage to cell lineages by suffocating neighboring nonpro- of QS through agent-based simulations of a spatial model in ducing cells (19). Building upon this work, Nadell et al. (20) which colony expansion via extracellular matrix production pro- showed that strategies that employ QS to deactivate matrix vides greater access to a limiting diffusible nutrient.