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      Global Profiling of Lysine Acetylation in Borrelia burgdorferi B31 Reveals Its Role in Central Metabolism

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          Abstract

          The post-translational modification of proteins has been shown to be extremely important in prokaryotes. Using a highly sensitive mass spectrometry-based proteomics approach, we have characterized the acetylome of B. burgdorferi. As previously reported for other bacteria, a relatively low number (5%) of the potential genome-encoded proteins of B. burgdorferi were acetylated. Of these, the vast majority were involved in central metabolism and cellular information processing (transcription, translation, etc.). Interestingly, these critical cell functions were targeted during both ML (mid-log) and S (stationary) phases of growth. However, acetylation of target proteins in ML phase was limited to single lysine residues while these same proteins were acetylated at multiple sites during S phase. To determine the acetyl donor in B. burgdorferi, we used mutants that targeted the sole acetate metabolic/anabolic pathway in B. burgdorferi (lipid I synthesis). B. burgdorferi strains B31-A3, B31-A3 Δ ackA (acetyl-P - and acetyl-CoA -) and B31-A3 Δ pta (acetyl-P + and acetyl-CoA -) were grown to S phase and the acetylation profiles were analyzed. While only two proteins were acetylated in the Δ ackA mutant, 140 proteins were acetylated in the Δ pta mutant suggesting that acetyl-P was the primary acetyl donor in B. burgdorferi. Using specific enzymatic assays, we were able to demonstrate that hyperacetylation of proteins in S phase appeared to play a role in decreasing the enzymatic activity of at least two glycolytic proteins. Currently, we hypothesize that acetylation is used to modulate enzyme activities during different stages of growth. This strategy would allow the bacteria to post-translationally stimulate the activity of key glycolytic enzymes by deacetylation rather than expending excessive energy synthesizing new proteins. This would be an appealing, low-energy strategy for a bacterium with limited metabolic capabilities. Future work focuses on identifying potential protein deacetylase(s) to complete our understanding of this important biological process.

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          Genomic sequence of a Lyme disease spirochaete, Borrelia burgdorferi.

          The genome of the bacterium Borrelia burgdorferi B31, the aetiologic agent of Lyme disease, contains a linear chromosome of 910,725 base pairs and at least 17 linear and circular plasmids with a combined size of more than 533,000 base pairs. The chromosome contains 853 genes encoding a basic set of proteins for DNA replication, transcription, translation, solute transport and energy metabolism, but, like Mycoplasma genitalium, it contains no genes for cellular biosynthetic reactions. Because B. burgdorferi and M. genitalium are distantly related eubacteria, we suggest that their limited metabolic capacities reflect convergent evolution by gene loss from more metabolically competent progenitors. Of 430 genes on 11 plasmids, most have no known biological function; 39% of plasmid genes are paralogues that form 47 gene families. The biological significance of the multiple plasmid-encoded genes is not clear, although they may be involved in antigenic variation or immune evasion.
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            PROSITE: a documented database using patterns and profiles as motif descriptors.

            Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.
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              Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space.

              Biological systems that perform multiple tasks face a fundamental trade-off: A given phenotype cannot be optimal at all tasks. Here we ask how trade-offs affect the range of phenotypes found in nature. Using the Pareto front concept from economics and engineering, we find that best-trade-off phenotypes are weighted averages of archetypes--phenotypes specialized for single tasks. For two tasks, phenotypes fall on the line connecting the two archetypes, which could explain linear trait correlations, allometric relationships, as well as bacterial gene-expression patterns. For three tasks, phenotypes fall within a triangle in phenotype space, whose vertices are the archetypes, as evident in morphological studies, including on Darwin's finches. Tasks can be inferred from measured phenotypes based on the behavior of organisms nearest the archetypes.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                31 August 2018
                2018
                : 9
                : 2036
                Affiliations
                [1] 1Laboratory of Bacteriology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health , Hamilton, MT, United States
                [2] 2CNRS UMR 6270 Polymères, Biopolymères, Surfaces Laboratory, Université de Rouen , Mont-Saint-Aignan, France
                [3] 3PISSARO Proteomic Facility, Institut de Recherche et d’Innovation Biomédicale , Mont-Saint-Aignan, France
                [4] 4Department of Chemistry and Biochemistry, Middlebury College , Middlebury, VT, United States
                Author notes

                Edited by: Catherine Ayn Brissette, University of North Dakota, United States

                Reviewed by: Azad Eshghi, UVic Genome BC Protein Centre, Canada; Dan Drecktrah, University of Montana, United States

                *Correspondence: Frank C. Gherardini, fgherardini@ 123456niaid.nih.gov

                †Present address: Sébastien Bontemps-Gallo, Center for Infection and Immunity of Lille, U1019-UMR8204, Institut Pasteur de Lille, Inserm, Université of Lille, CNRS, Lille, France

                This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2018.02036
                6127242
                30233522
                cfec1a44-eed9-4102-ab84-34609be6f418
                Copyright © 2018 Bontemps-Gallo, Gaviard, Richards, Kentache, Raffel, Lawrence, Schindler, Lovelace, Dulebohn, Cluss, Hardouin and Gherardini.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 03 July 2018
                : 13 August 2018
                Page count
                Figures: 7, Tables: 1, Equations: 0, References: 81, Pages: 15, Words: 0
                Funding
                Funded by: Division of Intramural Research, National Institute of Allergy and Infectious Diseases 10.13039/100006492
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                lyme disease,borrelia,acetylation,metabolism,regulation-post-translational
                Microbiology & Virology
                lyme disease, borrelia, acetylation, metabolism, regulation-post-translational

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