Imaging Live Drosophila Brain with Two-Photon Fluorescence Microscopy Syeed Ehsan Ahmed University of Texas at El Paso, [email protected]

Total Page:16

File Type:pdf, Size:1020Kb

Imaging Live Drosophila Brain with Two-Photon Fluorescence Microscopy Syeed Ehsan Ahmed University of Texas at El Paso, Eshanahmed2012@Gmail.Com University of Texas at El Paso DigitalCommons@UTEP Open Access Theses & Dissertations 2017-01-01 Imaging Live Drosophila Brain With Two-Photon Fluorescence Microscopy Syeed Ehsan Ahmed University of Texas at El Paso, [email protected] Follow this and additional works at: https://digitalcommons.utep.edu/open_etd Part of the Biophysics Commons, and the Optics Commons Recommended Citation Ahmed, Syeed Ehsan, "Imaging Live Drosophila Brain With Two-Photon Fluorescence Microscopy" (2017). Open Access Theses & Dissertations. 397. https://digitalcommons.utep.edu/open_etd/397 This is brought to you for free and open access by DigitalCommons@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of DigitalCommons@UTEP. For more information, please contact [email protected]. IMAGING LIVE DROSOPHILA BRAIN WITH TWO-PHOTON FLUORESCENCE MICROSCOPY SYEED EHSAN AHMED Master’s Program in Physics APPROVED: Chunqiang Li, Ph.D., Chair Cristian E. Botez, Ph.D. Chuan Xiao, Ph.D. Charles Ambler, Ph.D. Dean of the Graduate School Copyright © by Syeed Ehsan Ahmed 2017 Dedication Dedicated to my beloved family and friends. Thank you for believing in me and helping me throughout my journey. IMAGING LIVE DROSOPHILA BRAIN WITH TWO-PHOTON FLUORESCENCE MICROSCOPY by SYEED EHSAN AHMED, B.Sc. in Physics THESIS Presented to the Faculty of the Graduate School of The University of Texas at El Paso in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Department of Physics THE UNIVERSITY OF TEXAS AT EL PASO August 2017 ACKNOWLEDGEMENTS All praise and worthiness goes to Almighty Merciful Allah who has given me the opportunity, strength and ability to complete this work. I would like to express my profound gratitude to my advisor, Dr. Chunqiang Li, for his mentorship, supervision and invaluable suggestions during my research. His continuous assessment and appropriate guidance enabled me to develop as a scientist and complete my research effectively. I would like to thank Dr. Cristian Botez for his enthusiasm and perseverance as the chair of the department of Physics and for the kindness and guidance he has showed during our interactions. I would also like to thank all my group members in the Biophotonics laboratory, especially Dr. Yu Ding for his constant support and guidance throughout my thesis work. I would like to take the opportunity to express my gratitude to all members of the faculty I have encountered from the Department of Physics at UTEP through their lectures, guidance and the support outside the classroom. And lastly, my sincerest gratitude goes to my parents and my family for their continuous support in every situation towards the completion of my thesis. v ABSTRACT Two-photon fluorescence microscopy is an imaging technique which delivers distinct benefits for in vivo cellular and molecular imaging. Cyclic adenosine monophosphate (cAMP), a second messenger molecule, is responsible for triggering many physiological changes in neural system. However, the mechanism by which this molecule regulates responses in neuron cells is not yet clearly understood. When cAMP binds to a target protein, it changes the structure of that protein. Therefore, studying this molecular structure change with fluorescence resonance energy transfer (FRET) imaging can shed light on the cAMP functioning mechanism. FRET is a non- radiative dipole-dipole coupling which is sensitive to small distance change in nanometer scale. In this study we have investigated the effect of dopamine in cAMP dynamics in vivo. In our study two-photon fluorescence microscope was used for imaging mushroom bodies inside live Drosophila melanogaster brain and we developed a method for studying the change in cyclic AMP level. vi TABLE OF CONTENTS ACKNOWLEDGEMENTS ………………………………………………………………...V ABSTRACT ………………………………………………………………………………...Vi TABLE OF CONTENTS …………………………………………………………………...Vii LIST OF TABLES …………………………………………………………………………..iX LIST OF FIGURES ………………………………………………………………………….X CHAPTER 1: TWO-PHOTON MICROSCOPY.............................................................................1 1.1 INTRODUCTION .........................................................................................................1 1.2 HISTORY OF TWO-PHOTON MICROSCOPY .........................................................2 1.3 THEORY OF TWO-PHOTON ABSORPTION ...........................................................3 1.4 EXPERIMENTAL SETUP OF TWO-PHOTON FLUORESCENCE MICROSCOPE ............................................................................................................15 1.4.1 LIGHT SOURCE ................................................................................................15 1.4.2 WAVEPLATE AND POLARIZER ...................................................................16 1.4.3 SCANNING PLATFORM..................................................................................17 1.4.4 DICHROIC MIRRORS ......................................................................................19 1.4.5 BANDPASS FILTERS .......................................................................................20 1.4.6 OBJECTIVE LENS ............................................................................................20 1.4.7 PHOTOMULTIPLIER TUBE (PMT) ................................................................22 1.4.8 THREE DIMENSIONAL STAGE .....................................................................23 1.5 ADVANTAGES OF TWO-PHOTON MICROSCOPY .............................................23 CHAPTER 2: LIVE IMAGING OF DROSOPHILA MELANOGASTER BRAIN USING TWO-PHOTON MICROSCOPY .........................................................................................27 2.1 INTRODUCTION ..............................................................................................27 2.2 FÖRSTER RESONANCE ENERGY TRANSFER (FRET) ..............................28 vii 2.3 PRINCIPLE OF FRET .......................................................................................28 2.3.1 THE RATE OF ENERGY TRANSFER 푘푇 .......................................................34 2.3.2 ENERGY TRANSFER EFFICIENCY E ...........................................................35 2.3.3 ORIENTATIONAL FACTOR 휅2 ......................................................................36 2.3.4 SPECTRAL OVERLAP INTEGRAL ................................................................37 2.4 CYCLIC ADENOSINE MONOPHOSPHATE (CAMP) ...................................38 2.5 DOPAMINE .......................................................................................................39 2.6 FLUOROPHORES (CFP-YFP PAIRS) .............................................................40 2.7 EXCHANGE PROTEIN ACTIVATED BY CYCLIC AMP (EPAC1) .............41 2.8 TWO-PHOTON IMAGING LIVE DROSOPHILA BRAIN USING FRET FOR CAMP DYNAMICS ..................................................................................42 2.8.1 SAMPLE PREPARATION ................................................................................42 2.8.2 EXPERIMENTAL METHOD ............................................................................44 2.8.3 IMAGE PROCESSING USING IMAGEJ .........................................................46 2.8.4 RESULTS ...........................................................................................................47 2.9 CONCLUSION ...................................................................................................53 REFERENCES ..............................................................................................................................54 VITA........................................................................................................................................57 viii LIST OF TABLES Table 1.1 – Lines per image corresponding to different frame rates ……………………………18 Table 2.1 – Composition of hemolymph like saline …………………………………………….43 Table 2.2 – Composition of Dopamine, molecular weight and preparation …………………….44 ix LIST OF FIGURES Figure 1.1 - Jablonski diagram of One-Photon Excitation ………………………………………3 Figure 1.2 - Jablonski diagram of Two-Photon Excitation ………………………………………4 Figure 1.3 - Probability density distribution of Eq. (1.27) ……………………………………....13 Figure 1.4 - Diagram of intensity controlling system …………………………………………...17 Figure 1.5 –Schematic of two-photon microscope developed at UTEP ………………………...20 Figure 1.6 - Focal plane of single-photon Vs two-photon fluorescence microscopy …………...24 Figure 1.7 - Comparison between confocal microscopy and two-photon microscopy …………25 Figure 2.1 - Jablonski diagram illustrating FRET for TPE ……………………………………..26 Figure 2.2 – Energy transfer between D-A pair ………………………………………………...30 Figure 2.3 – FRET efficiency plot ………………………………………………………………36 Figure 2.4 – Emission and absorption spectra of D-A pair ……………………………………..38 Figure 2.5 – 2D skeletal formula of cAMP ……………………………………………………..39 Figure 2.6 – 2D skeletal formula of Dopamine …………………………………………………39 Figure 2.7 – (a) CFP and YFP spectral overlap with one-photon excitation (b) CFP and YFP emission for different TPE excitation wavelength ……………………………………………...41 Figure 2.8 – Cyclic AMP dependent Epac1 configuration ……………………………………42 Figure 2.9 - Schematic Illustration of In Vivo Preparation……………………………………...45 Figure 2.10 - Mushroom Bodies with Targeted Region (γ-lobe) (a) Bathed in Hemolymph like Solution and (b) Washed and again Bathed with Dopamine Solution…………………………..46 Figure 2.11 - (a) CFP (b) YFP
Recommended publications
  • The Chem Access Project from Bitmap Graphics to Fully Accessible Chemical Diagrams
    The Chem Access project From Bitmap Graphics to Fully Accessible Chemical Diagrams Volker Sorge Scientific Document Analysis Group Progressive Accessibility Solutions School of Computer Science Birmingham, UK University of Birmingham progressiveaccess.com 9th European e-Accessibility Forum, 2015, Paris, 8 June 2015 Motivation I Accessibility to STEM material is important issue for inclusive education I Diagrams are an important teaching means in STEM I Chemical diagrams (depictions of molecules) are ubiquitous in teaching from GCSE and A-levels teaching to undergrad curriculum chemistry, biosciences, life sciences. I Previous work on assistive technology for chemical diagrams I Require diagrams to be drawn in particular way or authoring environment I Need for specialist software to access and interact with diagrams I Additional hurdles for both authors and readers Goals I Make regular teaching material accessible I From inaccessible image to support for independent learning I Source independence I Do not rely on the benevolent, educated author I Platform independence I Use standard web technology (HTML5) I Accessible with all browsers, screen readers I Provide a seamless user experience without/very little interface I Support diverse material, for novices and experts alike Examples I Different representations of Aspirin molecule. Displayed formula. Skeletal formula. Structural formula. Examples I Or somewhat more complex. Procedure Input: A bitmap image of a molecule diagram 1. Image analysis and recognition 2. Generation of annotated SVG
    [Show full text]
  • 11.2 Alkanes
    11.2 Alkanes A large number of carbon compounds are possible because the covalent bond between carbon atoms, such as those in hexane, C6H14, are very strong. Learning Goal Write the IUPAC names and draw the condensed structural formulas and skeletal formulas for alkanes and cycloalkanes. Chemistry: An Introduction to General, Organic, and Biological Chemistry, Twelfth Edition © 2015 Pearson Education, Inc. Naming Alkanes Alkanes • are hydrocarbons that contain only C—C and C—H bonds • are formed by a continuous chain of carbon atoms • are named using the IUPAC (International Union of Pure and Applied Chemistry) system • have names that end in ane • use Greek prefixes to name carbon chains with five or more carbon atoms Chemistry: An Introduction to General, Organic, and Biological Chemistry, Twelfth Edition © 2015 Pearson Education, Inc. IUPAC Naming of First Ten Alkanes Chemistry: An Introduction to General, Organic, and Biological Chemistry, Twelfth Edition © 2015 Pearson Education, Inc. 1 Condensed Structural Formulas In a condensed structural formula, • each carbon atom and its attached hydrogen atoms are written as a group • a subscript indicates the number of hydrogen atoms bonded to each carbon atom The condensed structural formula of butane has four carbon atoms. CH3—CH2—CH2—CH3 butane Core Chemistry Skill Naming and Drawing Alkanes Chemistry: An Introduction to General, Organic, and Biological Chemistry, Twelfth Edition © 2015 Pearson Education, Inc. Condensed Structural Formulas Alkanes are written with structural formulas that are • expanded to show each bond • condensed to show each carbon atom and its attached hydrogen atoms Expanded Condensed Expanded Condensed Chemistry: An Introduction to General, Organic, and Biological Chemistry, Twelfth Edition © 2015 Pearson Education, Inc.
    [Show full text]
  • Arxiv:2001.11604V2 [Cs.PL] 6 Sep 2020 of Trigger Conditions, Having an in Situ Infrastructure That Simplifies Results They Desire
    DIVA: A Declarative and Reactive Language for in situ Visualization Qi Wu* Tyson Neuroth† Oleg Igouchkine‡ University of California, Davis, University of California, Davis, University of California, Davis, United States United States United States Konduri Aditya§ Jacqueline H. Chen¶ Kwan-Liu Ma|| Indian Institute of Science, India Sandia National Laboratories, University of California, Davis, United States United States ABSTRACT for many applications. VTK [61] also partially adopted this ap- The use of adaptive workflow management for in situ visualization proach, however, VTK is designed for programming unidirectional and analysis has been a growing trend in large-scale scientific simu- visualization pipelines, and provides limited support for highly dy- lations. However, coordinating adaptive workflows with traditional namic dataflows. Moreover, the synchronous dataflow model is procedural programming languages can be difficult because system somewhat difficult to use and does not always lead to modular pro- flow is determined by unpredictable scientific phenomena, which of- grams for large scale applications when control flows become com- ten appear in an unknown order and can evade event handling. This plicated [19]. Functional reactive programming (FRP) [19,24,48,53] makes the implementation of adaptive workflows tedious and error- further improved this model by directly treating time-varying values prone. Recently, reactive and declarative programming paradigms as first-class primitives. This allowed programmers to write reac- have been recognized as well-suited solutions to similar problems in tive programs using dataflows declaratively (as opposed to callback other domains. However, there is a dearth of research on adapting functions), hiding the mechanism that controls those flows under these approaches to in situ visualization and analysis.
    [Show full text]
  • A Dynamic Multidimensional Visualization Method for Social Networks
    PsychNology Journal, 2008 Volume 6, Number 3, 291 – 320 SIM: A dynamic multidimensional visualization method for social networks Maria Chiara Caschera*¨, Fernando Ferri¨ and Patrizia Grifoni¨ ¨CNR-IRPPS, National Research Council, Institute of Research on Population and Social Policies, Rome (Italy) ABSTRACT Visualization plays an important role in social networks analysis to explore and investigate individual and groups behaviours. Therefore, different approaches have been proposed for managing networks patterns and structures according to the visualization purposes. This paper presents a method of social networks visualization devoted not only to analyse individual and group social networking but also aimed to stimulate the second-one. This method provides (using a hybrid visualization approach) both an egocentric as well as a global point of view. Indeed, it is devoted to explore the social network structure, to analyse social aggregations and/or individuals and their evolution. Moreover, it considers and integrates features such as real-time social network elements locations in local areas. Multidimensionality consists of social phenomena, their evolution during the time, their individual characterization, the elements social position, and their spatial location. The proposed method was evaluated using the Social Interaction Map (SIM) software module in the scenario of planning and managing a scientific seminars cycle. This method enables the analysis of the topics evolution and the participants’ scientific interests changes using a temporal layers sequence for topics. This knowledge provides information for planning next conference and events, to extend and modify main topics and to analyse research interests trends. Keywords: Social network visualization, Spatial representation of social information, Map based visualization.
    [Show full text]
  • Locality-Dependent Training and Descriptor Sets for QSAR Modeling
    Locality-Dependent Training and Descriptor Sets for QSAR Modeling Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Bryan Christopher Hobocienski Graduate Program in Chemical Engineering The Ohio State University 2020 Dissertation Committee Dr. James Rathman, Advisor Dr. Bhavik Bakshi Dr. Jeffrey Chalmers Copyrighted by Bryan Christopher Hobocienski 2020 Abstract Quantitative Structure-Activity Relationships (QSARs) are empirical or semi-empirical models which correlate the structure of chemical compounds with their biological activities. QSAR analysis frequently finds application in drug development and environmental and human health protection. It is here that these models are employed to predict pharmacological endpoints for candidate drug molecules or to assess the toxicological potential of chemical ingredients found in commercial products, respectively. Fields such as drug design and health regulation share the necessity of managing a plethora of chemicals in which sufficient experimental data as to their application-relevant profiles is often lacking; the time and resources required to conduct the necessary in vitro and in vivo tests to properly characterize these compounds make a pure experimental approach impossible. QSAR analysis successfully alleviates the problems posed by these data gaps through interpretation of the wealth of information already contained in existing databases. This research involves the development of a novel QSAR workflow utilizing a local modeling strategy. By far the most common QSAR models reported in the literature are “global” models; they use all available training molecules and a single set of chemical descriptors to learn the relationship between structure and the endpoint of interest.
    [Show full text]
  • 6-Michalek Et Al.Indd
    The negotiation position amid member states of the EU Vyjednávací pozice mezi členskými státy P. MICHÁLEK, P. RYMEŠOVÁ, L. MÜLLEROVÁ, H. CHAMOUTOVÁ, K. CHAMOUTOVÁ Czech University of Agriculture, Prague, Czech Republic Abstract: The European integration process is very important and it has been paid attention to for the last 15 years. The abstract deals with the negotiation field and position in the structure of the current expanded EU. For better orientation in this equivocal situation, a modern cartography method of relationship in the arbitrary group called dynamic sociometry was used. The method is based on classical sociometry Morena and furthermore it uses the instrument of fuzzy set, typo- logy and structural analysis. The output of this method is a sociomap. The map holds information on the relative closeness or the distance of individual elements, their configuration but also some quality information. The graphic chart is similar to a topographic map. In our case, the sociomap was created from the data of foreign business among the member coun- tries. The following analysis of the sociomap we detected and described characteristic features of the analysed group. It consists of formal and informal links in the group, the role and the position of each member within the group, the structure and relations in the group. In the concrete, we attained data to answer the questions about the present climate in interre- lationships in the EU, which means the relationships among the members as the whole entities but also the relationships separately among members themselves. The position analysis of the Czech Republic in the system of the created sociomaps was considered as very important.
    [Show full text]
  • Answers DRAWING ORGANIC STRUCTURES
    Chemguide – answers DRAWING ORGANIC STRUCTURES 1. (i) C3H8 H H H (ii) fully displayed: H C C C H H H H more usual structural: CH3CH2CH3 (iii) skeletal: (Actually, it is probably unlikely you would ever write a skeletal formula for something this small.) 2. There are only two distinct compounds in these structures. If you think of them using the simplified structural formulae, they are: CH2Cl.CH2Cl (B, D, E and F) and CH3CHCl2 (A and C) It is really important that you can see this, and you mustn't leave this topic until you do. In terms of models, the two structures are: In both cases, you can rotate around the carbon-carbon bond to give an infinite variety of other shapes, some of which are represented in the diagrams in the question. You have to remember that the displayed formulae have been squashed flat and tidied up so that everything is nicely spread out. If you have problems with this, then you really need to play with some models. If you can't afford proper models, then make them out of children's coloured modelling clay (Plasticene, or your local equivalent) and some used matchsticks. 3. D and F are the same. All the others are different. Suppose you had some models – two structures would be different if you would have to take your models to pieces to convert one structure into another. If all you have to do is to rotate some bonds, then they are the same. In both D and F, the longest chain you can find in the molecule has 5 carbons.
    [Show full text]
  • Deepscreen: High Performance Drug-Target Interaction Prediction with Convolutional Neural Networks Using 2-D Structural Compound
    bioRxiv preprint doi: https://doi.org/10.1101/491365; this version posted December 9, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. DEEPScreen: High Performance Drug-Target Interaction Prediction with Convolutional Neural Networks Using 2-D Structural Compound Representations† Ahmet Sureyya Rifaioglu1,2, Volkan Atalay1,3,*, Maria Jesus Martin4, Rengul Cetin-Atalay3, Tunca Doğan3,4,* 1 Department of Computer Engineering, METU, Ankara, 06800, Turkey 2 Department of Computer Engineering, İskenderun Technical University, Hatay, 31200, Turkey 3 KanSiL, Department of Health Informatics, Graduate School of Informatics, METU, Ankara, 06800, Turkey 4 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, CB10 1SD, UK * Corresponding authors Contact information of the corresponding authors: [email protected], [email protected] Abstract The identification of physical interactions between drug candidate chemical substances and target biomolecules is an important step in the process of drug discovery, where the standard procedure is the systematic screening of chemical compounds against pre-selected target proteins. However, experimental screening procedures are expensive and time consuming, therefore, it is not possible to carry out comprehensive tests. Within the last decade, computational approaches have been developed with the objective of aiding experimental studies by predicting novel drug-target interactions (DTI), via the construction and application of statistical models. In this study, we propose a large-scale DTI interaction prediction system, DEEPScreen, for early stage drug discovery, using convolutional deep neural networks.
    [Show full text]
  • Molecular Binding Kinetics of CYP P450 by Using the Infinitesimal Generator Approach
    Molecular Binding Kinetics of CYP P450 by Using the Infinitesimal Generator Approach Master thesis by Paula Breitbach Matrikelnr. 337500 Technical University Berlin First Supervisor: PD Dr. Konstantin Fackeldey Second Supervisor: PD Dr. Marcus Weber May 18, 2018 Eidesstattliche Erkl¨arung Hiermit erkl¨areich, dass ich die vorliegende Arbeit selbstst¨andigund eigenh¨andig sowie ohne unerlaubte fremde Hilfe und ausschließlich unter Verwendung der aufgef¨uhrten Quellen und Hilfsmittel angefertigt habe. Die selbstst¨andigeund eigenst¨andigeAnfertigung versichert an Eides statt: Ort, Datum Unterschrift ii Zusammenfassung Wir betrachten das Enzym CYP 3A4, dass f¨urden Stoffwechsel vieler Medikamente und Xenobiotika verantwortlich ist. Es geh¨ortzur Familie der Cytochromen P450, deren Mit- glieder alle einen ¨ahnlichen Aufbau aufweisen, jedoch auf verschiedene Liganden spezifiziert sind. Die katalysierte Reaktion ist bekannt, aber der Weg, den die Liganden zum aktiven Zentrum nehmen, ist noch weitgehend ungekl¨art.Das aktive Zentrum liegt im Inneren des Enzyms und ist nur ¨uber verschiedene Zugangskan¨aleerreichbar, die jedoch meist durch Residuen des CYPs blockiert sind. Wir untersuchen mit mathematischen Methoden f¨ur7 Liganden den Weg an die Bindestelle im aktiven Zentrum. Da vollst¨andigeSimulationen zu zeitintensiv sind, verfolgen wir einen Netzwerkansatz. Die Bewegungen des Liganden k¨onnenals stetige Trajektorie eines stochastischen Prozesses modelliert werden. Wir betrachten den infinitesimalen Genera- tor des Prozesses. Dann diskretisieren wir den Zustandsraum gem¨aßeiner Voronoi Zer- legung, die durch um das CYP verteilte Ligandenpositionen definiert ist. Nach Fackeldey, Lie und Weber [9] berechnen wir Ubergangsraten¨ zwischen einzelnen Ligandenpositionen. Daf¨urm¨ussenwir nur die Interaktionsenergie zwischen CYP und Ligand der jeweiligen Po- sition ermitteln. Dies k¨onnenwir mit Simulationen erreichen.
    [Show full text]
  • Leicester Grammar School's
    Leicester Grammar School’s Refeezing the Arctic An article discussing the plausibility of refreezing the Arctic to combat Climate Change — Page 4 Left-Handed genes An article that discusses the discovery of a genetic marker for left-handedness — Page 8 More inside... ISSUE 7 ADVENT TERM 2019 1 A Message from the Team: This academic year marks a change in the editorial team for our school’s Young Scientist Journal (YSJ) as the previous year 12 team have taken over from the departing year 13s as “ they have embarked on the next stage of their education. We would like to take this opportunity to thank Marcus and Zain not only for their dedication and hard work in sustaining the YSJ ethos, but for also guiding us through this transition. Looking to the future, LGS YSJ looks to focus at attracting and fostering the interest of science in all years. We would like to get more people involved with the journal, especially from the younger years. The team is also looking for more people to help compose articles; whether that be keen photographers to take photos for backgrounds or covers, or IT and Publishing experts who could help us refresh the journal’s layout and design. A reminder to all budding scientists throughout the school of all ages that any input, whether that be writing an article or helping to design the layout of the magazine, is much appreciated and valued. If you would like to get involved, then please do not hesitate to contact [email protected] or come and speak to any members of the team.
    [Show full text]
  • Development of the Chick Wing and Leg Neuromuscular Systems
    1 Development of the chick wing and leg neuromuscular systems and their 2 plasticity in response to changes in digit numbers 3 4 Maëva Luxey1,#, Bianka Berki1,#, Wolf Heusermann2, Sabrina Fischer1, & Patrick Tschopp1,* 5 6 1DUW Zoology, University of Basel, Vesalgasse 1, CH-4051, Basel, Switzerland; 2IMCF 7 Biozentrum, University of Basel, Basel, Switzerland 8 9 #Equally contributing 10 11 *Corresponding author: Patrick Tschopp 12 Tel.: +41 61 207 56 49 13 [email protected] 14 15 16 17 RUNNING TITLE: 18 Autopod nerve and muscle plasticity 19 20 21 KEY WORDS: 22 Limb musculoskeletal apparatus, Autopod evolution, Limb neuromuscular 3D-atlas, light- 23 sheet microscopy, Polydactyly, Forelimb - hindlimb differences. 24 1 25 SUMMARY STATEMENT / HIGHLIGHTS: Using light-sheet microscopy and 26 3D-nerve and -muscle reconstructions, we uncover a differential plasticity in the limb 27 neuromuscular system’s ability to adapt to changes in digit numbers. 28 2 29 ABSTRACT 30 The tetrapod limb has long served as a paradigm to study vertebrate pattern formation. 31 During limb morphogenesis, a number of distinct tissue types are patterned and subsequently 32 must be integrated to form coherent functional units. For example, the musculoskeletal 33 apparatus of the limb requires the coordinated development of the skeletal elements, 34 connective tissues, muscles and nerves. Here, using light-sheet microscopy and 3D- 35 reconstructions, we concomitantly follow the developmental emergence of nerve and muscle 36 patterns in chicken wings and legs, two appendages with highly specialized locomotor 37 outputs. Despite a comparable flexor/extensor-arrangement of their embryonic muscles, 38 wings and legs show a rotated innervation pattern for their three main motor nerve branches.
    [Show full text]
  • Machine Learning Methods for Life Sciences: Intelligent Data Analysis in Bio- and Chemoinformatics
    Machine Learning Methods for Life Sciences: Intelligent Data Analysis in Bio- and Chemoinformatics vorgelegt von Diplom-Physiker Johannes Mohr aus Berlin Von der Fakult¨at IV - Elektrotechnik und Informatik der Technischen Universit¨at Berlin zur Erlangung des akademischen Grades Doktor der Naturwissenschaften Dr. rer. nat. genehmigte Dissertation Promotionsausschuss: Vorsitzender: Prof. Dr.-Ing. J¨org Raisch Berichter: Prof. Dr. rer. nat. Klaus Obermayer Berichter: Prof. Dr. rer. nat. Sepp Hochreiter Tag der wissenschaftlichen Aussprache: 19.12.2008 Berlin 2009 D 83 This thesis is dedicated with love to my wife Sambu and my daughter Yumi. Zusammenfassung In den letzten Jahren haben die experimentellen Techniken innerhalb der Lebenswis- senschaften rapide Fortschritte gemacht. Zus¨atzlich hat die Integration von Methoden verschiedener Disziplinen zur Bildung neuer Forschungsgebiete gefuhrt,¨ wie genetische Bildgebung, molekulare Medizin und biologische Psychologie. Der experimentelle Fort- schritt wurde von einem wachsenden Bedarf an intelligenter Datenanalyse begleitet, deren Ziel es ist, einen gegebenen Datensatz unter Einbeziehung von Dom¨anenwissen auf die meistversprechende Art und Weise zu analysieren. Dies schließt die Repr¨asenta- tion der Daten, die Auswahl der Variablen, die Vorverarbeitung, die Modellannahmen, die Wahl der Methoden fur¨ Pr¨adiktion, Modellselektion und Regularisierung ebenso ein wie die Interpretation der Ergebnisse. Das Thema der vorliegenden Arbeit ist die intelligente Datenanalyse in den Bereichen Bioinformatik
    [Show full text]