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Chloroplast Transit Peptides: Structure, Function and Evolution
reviews Chloroplast transit Although the first demonstration of precursor trans- port into chloroplasts was shown over two decades peptides: structure, ago3,4, only now is this area of cell biology becom- ing well understood. Many excellent reviews have been published recently on the evolution of plas- function and tids5, the evolution of organelle genomes6, the mechanism of gene transfer from organelles to the nucleus7 and the mechanism of protein import into evolution chloroplasts8,9. Proteins destined to plastids and other organ- elles share in common the requirement for ‘new’ Barry D. Bruce sequence information to facilitate their correct trafficking within the cell. Although in most cases this information resides in a cleavable, N-terminal sequence often collectively referred to as signal It is thought that two to three thousand different proteins are sequence, the different organelle-targeting se- targeted to the chloroplast, and the ‘transit peptides’ that act as quences have distinct properties and names: ‘signal peptides’ for the endoplasmic reticulum, chloroplast targeting sequences are probably the largest class of ‘presequences’ for the mitochondria and ‘transit peptides’ for chloroplasts and other plastids. This targeting sequences in plants. At a primary structural level, transit review focuses on recent progress in dissecting peptide sequences are highly divergent in length, composition and the role of the stromal-targeting domain of chloro- plast transit peptides. I will consider briefly the organization. An emerging concept suggests that transit peptides multitude of distinct functions that transit peptides contain multiple domains that provide either distinct or overlapping perform, provide an update on the limited struc- tural information of a number of transit peptides functions. -
Old Data and Friends Improve with Age: Advancements with the Updated Tools of Genenetwork
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.24.445383; this version posted May 25, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. Old data and friends improve with age: Advancements with the updated tools of GeneNetwork Alisha Chunduri1, David G. Ashbrook2 1Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India 2Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA Abstract Understanding gene-by-environment interactions is important across biology, particularly behaviour. Families of isogenic strains are excellently placed, as the same genome can be tested in multiple environments. The BXD’s recent expansion to 140 strains makes them the largest family of murine isogenic genomes, and therefore give great power to detect QTL. Indefinite reproducible genometypes can be leveraged; old data can be reanalysed with emerging tools to produce novel biological insights. To highlight the importance of reanalyses, we obtained drug- and behavioural-phenotypes from Philip et al. 2010, and reanalysed their data with new genotypes from sequencing, and new models (GEMMA and R/qtl2). We discover QTL on chromosomes 3, 5, 9, 11, and 14, not found in the original study. We narrowed down the candidate genes based on their ability to alter gene expression and/or protein function, using cis-eQTL analysis, and variants predicted to be deleterious. Co-expression analysis (‘gene friends’) and human PheWAS were used to further narrow candidates. -
Bacterial Cell Membrane
BACTERIAL CELL MEMBRANE Dr. Rakesh Sharda Department of Veterinary Microbiology NDVSU College of Veterinary Sc. & A.H., MHOW CYTOPLASMIC MEMBRANE ➢The cytoplasmic membrane, also called a cell membrane or plasma membrane, is about 7 nanometers (nm; 1/1,000,000,000 m) thick. ➢It lies internal to the cell wall and encloses the cytoplasm of the bacterium. ➢It is the most dynamic structure of a prokaryotic cell. Structure of cell membrane ➢The structure of bacterial plasma membrane is that of unit membrane, i.e., a fluid phospholipid bilayer, composed of phospholipids (40%) and peripheral and integral proteins (60%) molecules. ➢The phospholipids of bacterial cell membranes do not contain sterols as in eukaryotes, but instead consist of saturated or monounsaturated fatty acids (rarely, polyunsaturated fatty acids). ➢Many bacteria contain sterol-like molecules called hopanoids. ➢The hopanoids most likely stabilize the bacterial cytoplasmic membrane. ➢The phospholipids are amphoteric molecules with a polar hydrophilic glycerol "head" attached via an ester bond to two non-polar hydrophobic fatty acid tails. ➢The phospholipid bilayer is arranged such that the polar ends of the molecules form the outermost and innermost surface of the membrane while the non-polar ends form the center of the membrane Fluid mosaic model ➢The plasma membrane contains proteins, sugars, and other lipids in addition to the phospholipids. ➢The model that describes the arrangement of these substances in lipid bilayer is called the fluid mosaic model ➢Dispersed within the bilayer are various structural and enzymatic proteins, which carry out most membrane functions. ➢Some membrane proteins are located and function on one side or another of the membrane (peripheral proteins). -
Centrosome-Nuclear Envelope Tethering and Microtubule Motor
bioRxiv preprint doi: https://doi.org/10.1101/442368; this version posted October 12, 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-NC-ND 4.0 International license. Centrosome-nuclear envelope tethering and microtubule motor-based pulling forces collaborate in centrosome positioning during mitotic entry Vincent Boudreau1, Richard Chen1, Alan Edwards1, Muhammad Sulaimain1, Paul S. Maddox1* 1 Department of Biology, University of North Carolina at Chapel Hill * Direct all correspondence to this author at [email protected]. Centrosome positioning relative to the nucleus and cell nuclear envelope and at the cortex to ensure proper centrosome shape is highly regulated across cell types, during cell migration positioning (De Simone et al., 2016). Dynein regulators including and during spindle formation in cell division. Across most sexual- LIS-1 are also required for centrosome separation in the embryo ly reproducing animals, centrosomes are provided to the oocyte (Cockell et al., 2004), although their spatio-temporal contributions through fertilization and must be positioned properly to establish remain elusive. Despite our understanding of microtubule cyto- the zygotic mitotic spindle. How centrosomes are positioned in skeleton-based pulling forces, the contribution of key mitotic kinas- space and time through the concerted action of key mitotic en- es and phosphatases to centrosome positioning remains unclear. try biochemical regulators including Protein Phosphatase 2A The net effect of molecular regulators is a biophysical (PP2A-B55/SUR-6), biophysical regulators including Dynein mechanism required for positioning centrosomes during mitotic and the nuclear lamina is unclear. -
Title a New Centrosomal Protein Regulates Neurogenesis By
Title A new centrosomal protein regulates neurogenesis by microtubule organization Authors: Germán Camargo Ortega1-3†, Sven Falk1,2†, Pia A. Johansson1,2†, Elise Peyre4, Sanjeeb Kumar Sahu5, Loïc Broic4, Camino De Juan Romero6, Kalina Draganova1,2, Stanislav Vinopal7, Kaviya Chinnappa1‡, Anna Gavranovic1, Tugay Karakaya1, Juliane Merl-Pham8, Arie Geerlof9, Regina Feederle10,11, Wei Shao12,13, Song-Hai Shi12,13, Stefanie M. Hauck8, Frank Bradke7, Victor Borrell6, Vijay K. Tiwari§, Wieland B. Huttner14, Michaela Wilsch- Bräuninger14, Laurent Nguyen4 and Magdalena Götz1,2,11* Affiliations: 1. Institute of Stem Cell Research, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 2. Physiological Genomics, Biomedical Center, Ludwig-Maximilian University Munich, Germany. 3. Graduate School of Systemic Neurosciences, Biocenter, Ludwig-Maximilian University Munich, Germany. 4. GIGA-Neurosciences, Molecular regulation of neurogenesis, University of Liège, Belgium 5. Institute of Molecular Biology (IMB), Mainz, Germany. 6. Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d’Alacant, Spain. 7. Laboratory for Axon Growth and Regeneration, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 8. Research Unit Protein Science, Helmholtz Centre Munich, German Research Center for Environmental Health, Munich, Germany. 9. Protein Expression and Purification Facility, Institute of Structural Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 10. Institute for Diabetes and Obesity, Monoclonal Antibody Core Facility, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 11. SYNERGY, Excellence Cluster of Systems Neurology, Biomedical Center, Ludwig- Maximilian University Munich, Germany. 12. Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, USA 13. -
Bioinformatics Identi Cation of Prognostic Factors Associated With
Bioinformatics Identication of Prognostic Factors Associated with Breast Cancer Ying Wei Sichuan University https://orcid.org/0000-0001-8178-4705 Shipeng Zhang College of Pharmacy, North Sichuan Medical College Li Xiao West China School of Basic Medical Sciences and Forensic Medicine Jing Zou West China School of Basic Medical Sciences and Forensic Medicine Yingqing Fu West China School of Basic Medical Sciences and Forensic Medicine Yi Ye West China School of Basic Medical Sciences and Forensic Medicine Linchuan Liao ( [email protected] ) West China School of Basic Medical Sciences and Forensic Medicine https://orcid.org/0000-0003-3700-8471 Research Keywords: Breast cancer, Differentially expressed genes, miRNAs, Transcription factors, Bioinformatic analysis Posted Date: December 2nd, 2020 DOI: https://doi.org/10.21203/rs.3.rs-117477/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/23 Abstract Background: Breast cancer (BRCA) remains one of the most common forms of cancer and is the most prominent driver of cancer-related death among women. The mechanistic basis for BRCA, however, remains incompletely understood. In particular, the relationships between driver mutations and signaling pathways in BRCA are poorly characterized, making it dicult to identify reliable clinical biomarkers that can be employed in diagnostic, therapeutic, or prognostic contexts. Methods: First, we downloaded publically available BRCA datasets (GSE45827, GSE42568, and GSE61304) from the Gene Expression Omnibus (GEO) database. We then compared gene expression proles between tumor and control tissues in these datasets using Venn diagrams and the GEO2R analytical tool. We further explore the functional relevance of BRCA-associated differentially expressed genes (DEGs) via functional and pathway enrichment analyses using the DAVID tool, and we then constructed a protein-protein interaction network incorporating DEGs of interest using the Search Tool for the Retrieval of Interacting Genes (STRING) database. -
The Endomembrane System and Proteins
Chapter 4 | Cell Structure 121 Endosymbiosis We have mentioned that both mitochondria and chloroplasts contain DNA and ribosomes. Have you wondered why? Strong evidence points to endosymbiosis as the explanation. Symbiosis is a relationship in which organisms from two separate species depend on each other for their survival. Endosymbiosis (endo- = “within”) is a mutually beneficial relationship in which one organism lives inside the other. Endosymbiotic relationships abound in nature. We have already mentioned that microbes that produce vitamin K live inside the human gut. This relationship is beneficial for us because we are unable to synthesize vitamin K. It is also beneficial for the microbes because they are protected from other organisms and from drying out, and they receive abundant food from the environment of the large intestine. Scientists have long noticed that bacteria, mitochondria, and chloroplasts are similar in size. We also know that bacteria have DNA and ribosomes, just like mitochondria and chloroplasts. Scientists believe that host cells and bacteria formed an endosymbiotic relationship when the host cells ingested both aerobic and autotrophic bacteria (cyanobacteria) but did not destroy them. Through many millions of years of evolution, these ingested bacteria became more specialized in their functions, with the aerobic bacteria becoming mitochondria and the autotrophic bacteria becoming chloroplasts. The Central Vacuole Previously, we mentioned vacuoles as essential components of plant cells. If you look at Figure 4.8b, you will see that plant cells each have a large central vacuole that occupies most of the cell's area. The central vacuole plays a key role in regulating the cell’s concentration of water in changing environmental conditions. -
The Basal Bodies of Chlamydomonas Reinhardtii Susan K
Dutcher and O’Toole Cilia (2016) 5:18 DOI 10.1186/s13630-016-0039-z Cilia REVIEW Open Access The basal bodies of Chlamydomonas reinhardtii Susan K. Dutcher1* and Eileen T. O’Toole2 Abstract The unicellular green alga, Chlamydomonas reinhardtii, is a biflagellated cell that can swim or glide. C. reinhardtii cells are amenable to genetic, biochemical, proteomic, and microscopic analysis of its basal bodies. The basal bodies contain triplet microtubules and a well-ordered transition zone. Both the mother and daughter basal bodies assemble flagella. Many of the proteins found in other basal body-containing organisms are present in the Chlamydomonas genome, and mutants in these genes affect the assembly of basal bodies. Electron microscopic analysis shows that basal body duplication is site-specific and this may be important for the proper duplication and spatial organization of these organelles. Chlamydomonas is an excellent model for the study of basal bodies as well as the transition zone. Keywords: Site-specific basal body duplication, Cartwheel, Transition zone, Centrin fibers Phylogeny and conservation of proteins Centrin, SPD2/CEP192, Asterless/CEP152; CEP70, The green lineage or Viridiplantae consists of the green delta-tubulin, and epsilon-tubulin. Chlamydomonas has algae, which include Chlamydomonas, the angiosperms homologs of all of these based on sequence conservation (the land plants), and the gymnosperms (conifers, cycads, except PLK4, CEP152, and CEP192. Several lines of evi- ginkgos). They are grouped together because they have dence suggests that CEP152, CEP192, and PLK4 interact chlorophyll a and b and lack phycobiliproteins. The green [20, 52] and their concomitant absence in several organ- algae together with the cycads and ginkgos have basal isms suggests that other mechanisms exist that allow for bodies and cilia, while the angiosperms and conifers have control of duplication [4]. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Par6c Is at the Mother Centriole and Controls Centrosomal Protein
860 Research Article Par6c is at the mother centriole and controls centrosomal protein composition through a Par6a-dependent pathway Vale´rian Dormoy, Kati Tormanen and Christine Su¨ tterlin* Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697-2300, USA *Author for correspondence ([email protected]) Accepted 3 December 2012 Journal of Cell Science 126, 860–870 ß 2013. Published by The Company of Biologists Ltd doi: 10.1242/jcs.121186 Summary The centrosome contains two centrioles that differ in age, protein composition and function. This non-membrane bound organelle is known to regulate microtubule organization in dividing cells and ciliogenesis in quiescent cells. These specific roles depend on protein appendages at the older, or mother, centriole. In this study, we identified the polarity protein partitioning defective 6 homolog gamma (Par6c) as a novel component of the mother centriole. This specific localization required the Par6c C-terminus, but was independent of intact microtubules, the dynein/dynactin complex and the components of the PAR polarity complex. Par6c depletion resulted in altered centrosomal protein composition, with the loss of a large number of proteins, including Par6a and p150Glued, from the centrosome. As a consequence, there were defects in ciliogenesis, microtubule organization and centrosome reorientation during migration. Par6c interacted with Par3 and aPKC, but these proteins were not required for the regulation of centrosomal protein composition. Par6c also associated with Par6a, which controls protein recruitment to the centrosome through p150Glued. Our study is the first to identify Par6c as a component of the mother centriole and to report a role of a mother centriole protein in the regulation of centrosomal protein composition. -
Supplemental Information Proximity Interactions Among Centrosome
Current Biology, Volume 24 Supplemental Information Proximity Interactions among Centrosome Components Identify Regulators of Centriole Duplication Elif Nur Firat-Karalar, Navin Rauniyar, John R. Yates III, and Tim Stearns Figure S1 A Myc Streptavidin -tubulin Merge Myc Streptavidin -tubulin Merge BirA*-PLK4 BirA*-CEP63 BirA*- CEP192 BirA*- CEP152 - BirA*-CCDC67 BirA* CEP152 CPAP BirA*- B C Streptavidin PCM1 Merge Myc-BirA* -CEP63 PCM1 -tubulin Merge BirA*- CEP63 DMSO - BirA* CEP63 nocodazole BirA*- CCDC67 Figure S2 A GFP – + – + GFP-CEP152 + – + – Myc-CDK5RAP2 + + + + (225 kDa) Myc-CDK5RAP2 (216 kDa) GFP-CEP152 (27 kDa) GFP Input (5%) IP: GFP B GFP-CEP152 truncation proteins Inputs (5%) IP: GFP kDa 1-7481-10441-1290218-1654749-16541045-16541-7481-10441-1290218-1654749-16541045-1654 250- Myc-CDK5RAP2 150- 150- 100- 75- GFP-CEP152 Figure S3 A B CEP63 – – + – – + GFP CCDC14 KIAA0753 Centrosome + – – + – – GFP-CCDC14 CEP152 binding binding binding targeting – + – – + – GFP-KIAA0753 GFP-KIAA0753 (140 kDa) 1-496 N M C 150- 100- GFP-CCDC14 (115 kDa) 1-424 N M – 136-496 M C – 50- CEP63 (63 kDa) 1-135 N – 37- GFP (27 kDa) 136-424 M – kDa 425-496 C – – Inputs (2%) IP: GFP C GFP-CEP63 truncation proteins D GFP-CEP63 truncation proteins Inputs (5%) IP: GFP Inputs (5%) IP: GFP kDa kDa 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl 1-135136-424425-4961-424136-496FL Ctl Myc- 150- Myc- 100- CCDC14 KIAA0753 100- 100- 75- 75- GFP- GFP- 50- CEP63 50- CEP63 37- 37- Figure S4 A siCtl -
Introduction to the Cell Cell History Cell Structures and Functions
Introduction to the cell cell history cell structures and functions CK-12 Foundation December 16, 2009 CK-12 Foundation is a non-profit organization with a mission to reduce the cost of textbook materials for the K-12 market both in the U.S. and worldwide. Using an open-content, web-based collaborative model termed the “FlexBook,” CK-12 intends to pioneer the generation and distribution of high quality educational content that will serve both as core text as well as provide an adaptive environment for learning. Copyright ©2009 CK-12 Foundation This work is licensed under the Creative Commons Attribution-Share Alike 3.0 United States License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/us/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA. Contents 1 Cell structure and function dec 16 5 1.1 Lesson 3.1: Introduction to Cells .................................. 5 3 www.ck12.org www.ck12.org 4 Chapter 1 Cell structure and function dec 16 1.1 Lesson 3.1: Introduction to Cells Lesson Objectives • Identify the scientists that first observed cells. • Outline the importance of microscopes in the discovery of cells. • Summarize what the cell theory proposes. • Identify the limitations on cell size. • Identify the four parts common to all cells. • Compare prokaryotic and eukaryotic cells. Introduction Knowing the make up of cells and how cells work is necessary to all of the biological sciences. Learning about the similarities and differences between cell types is particularly important to the fields of cell biology and molecular biology.