Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks

In The Lancet Infectious Diseases, Katy Town and colleagues1 report findings of the first large-scale study in which phylogenomic, whole-genome sequencing (WGS) analysis of Neisseria gonorrhoeae isolates was used to identify molecular networks of transmission. The selection of this cutoff was somewh...

Full description

Saved in:
Bibliographic Details
Published in:The Lancet infectious diseases 2020-04, Vol.20 (4), p.391-392
Main Authors: Jolly, Ann M, Dillon, Jo-Anne R
Format: Article
Language:English
Subjects:
Disease transmission
Gene sequencing
Genomes
Gonorrhea
HIV
Human immunodeficiency virus
Infections
Infectious diseases
Molecular chains
Neisseria gonorrhoeae
Polymorphism
Public health
Sexually transmitted diseases
STD
Studies
Surveillance
Whole genome sequencing
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c388t-ffa9c2595176cea73bc8502b7cdb2992fbd8d5d663c98fd8976ff6f3e60ef7033
container_end_page 392
container_issue 4
container_start_page 391
container_title The Lancet infectious diseases
container_volume 20
creator Jolly, Ann M
Dillon, Jo-Anne R
description In The Lancet Infectious Diseases, Katy Town and colleagues1 report findings of the first large-scale study in which phylogenomic, whole-genome sequencing (WGS) analysis of Neisseria gonorrhoeae isolates was used to identify molecular networks of transmission. The selection of this cutoff was somewhat arbitrary and based on several previous, smaller studies. Because this research will inspire others to undertake similar studies, it will be interesting to understand how different populations and locations influence the selection of appropriate cutoffs to identify molecular chains of transmission. Town and colleagues accessed a remarkable centralised data resource—ie, GRASP information linked with Public Health England's Sexually Transmitted Infection Surveillance System, which collects clinical, sociodemographic, and other data.
doi_str_mv 10.1016/S1473-3099(19)30751-0
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2345505395</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1473309919307510</els_id><sourcerecordid>2345505395</sourcerecordid><originalsourceid>FETCH-LOGICAL-c388t-ffa9c2595176cea73bc8502b7cdb2992fbd8d5d663c98fd8976ff6f3e60ef7033</originalsourceid><addsrcrecordid>eNqFkUtPxCAUhYnR-P4JGhI3uqhCKaW4Mcb4SoyaqGtC6WVEO2WEVp1_LzOjLty4uuTmO4ebcxDaoeSQEloePdBCsIwRKfepPGBEcJqRJbSe1kVWFFwsz98LZA1txPhCCBWUFKtojVEpKsbzdfR2_zxt_Qg6P3YG60630-gi9hbfgosRgtN45DsfwrMHDcdY40lIbHTdCPfet9j6gPugzetsMxl63bt3mGuMN0a3OMLnkEYH_YcPr3ELrVjdRtj-npvo6eL88ewqu7m7vD47vckMq6o-s1ZLk3PJqSgNaMFqU3GS18I0dS5lbuumanhTlszIyjaVFKW1pWVQErCCMLaJ9he-6d63AWKv0tUG2lZ34IeoclZwTjiTPKF7f9AXP4SURaKKnJcpUjEz5AvKBB9jAKsmwY11mCpK1KwTNe9EzQJXVKp5J4ok3e63-1CPoflV_ZSQgJMFACmOdwdBReOgM9C4AKZXjXf_fPEF64ad5Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2425647473</pqid></control><display><type>article</type><title>Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks</title><source>ScienceDirect Journals</source><creator>Jolly, Ann M ; Dillon, Jo-Anne R</creator><creatorcontrib>Jolly, Ann M ; Dillon, Jo-Anne R</creatorcontrib><description>In The Lancet Infectious Diseases, Katy Town and colleagues1 report findings of the first large-scale study in which phylogenomic, whole-genome sequencing (WGS) analysis of Neisseria gonorrhoeae isolates was used to identify molecular networks of transmission. The selection of this cutoff was somewhat arbitrary and based on several previous, smaller studies. Because this research will inspire others to undertake similar studies, it will be interesting to understand how different populations and locations influence the selection of appropriate cutoffs to identify molecular chains of transmission. Town and colleagues accessed a remarkable centralised data resource—ie, GRASP information linked with Public Health England's Sexually Transmitted Infection Surveillance System, which collects clinical, sociodemographic, and other data.</description><identifier>ISSN: 1473-3099</identifier><identifier>EISSN: 1474-4457</identifier><identifier>DOI: 10.1016/S1473-3099(19)30751-0</identifier><identifier>PMID: 31978352</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Disease transmission ; Gene sequencing ; Genomes ; Gonorrhea ; HIV ; Human immunodeficiency virus ; Infections ; Infectious diseases ; Molecular chains ; Neisseria gonorrhoeae ; Polymorphism ; Public health ; Sexually transmitted diseases ; STD ; Studies ; Surveillance ; Whole genome sequencing</subject><ispartof>The Lancet infectious diseases, 2020-04, Vol.20 (4), p.391-392</ispartof><rights>2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license</rights><rights>2020. The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. This work is published under http://creativecommons.org/licenses/by-nc-nd/3.0/ (theLicense”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c388t-ffa9c2595176cea73bc8502b7cdb2992fbd8d5d663c98fd8976ff6f3e60ef7033</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31978352$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jolly, Ann M</creatorcontrib><creatorcontrib>Dillon, Jo-Anne R</creatorcontrib><title>Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks</title><title>The Lancet infectious diseases</title><addtitle>Lancet Infect Dis</addtitle><description>In The Lancet Infectious Diseases, Katy Town and colleagues1 report findings of the first large-scale study in which phylogenomic, whole-genome sequencing (WGS) analysis of Neisseria gonorrhoeae isolates was used to identify molecular networks of transmission. The selection of this cutoff was somewhat arbitrary and based on several previous, smaller studies. Because this research will inspire others to undertake similar studies, it will be interesting to understand how different populations and locations influence the selection of appropriate cutoffs to identify molecular chains of transmission. Town and colleagues accessed a remarkable centralised data resource—ie, GRASP information linked with Public Health England's Sexually Transmitted Infection Surveillance System, which collects clinical, sociodemographic, and other data.</description><subject>Disease transmission</subject><subject>Gene sequencing</subject><subject>Genomes</subject><subject>Gonorrhea</subject><subject>HIV</subject><subject>Human immunodeficiency virus</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>Molecular chains</subject><subject>Neisseria gonorrhoeae</subject><subject>Polymorphism</subject><subject>Public health</subject><subject>Sexually transmitted diseases</subject><subject>STD</subject><subject>Studies</subject><subject>Surveillance</subject><subject>Whole genome sequencing</subject><issn>1473-3099</issn><issn>1474-4457</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkUtPxCAUhYnR-P4JGhI3uqhCKaW4Mcb4SoyaqGtC6WVEO2WEVp1_LzOjLty4uuTmO4ebcxDaoeSQEloePdBCsIwRKfepPGBEcJqRJbSe1kVWFFwsz98LZA1txPhCCBWUFKtojVEpKsbzdfR2_zxt_Qg6P3YG60630-gi9hbfgosRgtN45DsfwrMHDcdY40lIbHTdCPfet9j6gPugzetsMxl63bt3mGuMN0a3OMLnkEYH_YcPr3ELrVjdRtj-npvo6eL88ewqu7m7vD47vckMq6o-s1ZLk3PJqSgNaMFqU3GS18I0dS5lbuumanhTlszIyjaVFKW1pWVQErCCMLaJ9he-6d63AWKv0tUG2lZ34IeoclZwTjiTPKF7f9AXP4SURaKKnJcpUjEz5AvKBB9jAKsmwY11mCpK1KwTNe9EzQJXVKp5J4ok3e63-1CPoflV_ZSQgJMFACmOdwdBReOgM9C4AKZXjXf_fPEF64ad5Q</recordid><startdate>202004</startdate><enddate>202004</enddate><creator>Jolly, Ann M</creator><creator>Dillon, Jo-Anne R</creator><general>Elsevier Ltd</general><general>Elsevier Limited</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0TZ</scope><scope>3V.</scope><scope>7QL</scope><scope>7RV</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8C2</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope></search><sort><creationdate>202004</creationdate><title>Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks</title><author>Jolly, Ann M ; Dillon, Jo-Anne R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-ffa9c2595176cea73bc8502b7cdb2992fbd8d5d663c98fd8976ff6f3e60ef7033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Disease transmission</topic><topic>Gene sequencing</topic><topic>Genomes</topic><topic>Gonorrhea</topic><topic>HIV</topic><topic>Human immunodeficiency virus</topic><topic>Infections</topic><topic>Infectious diseases</topic><topic>Molecular chains</topic><topic>Neisseria gonorrhoeae</topic><topic>Polymorphism</topic><topic>Public health</topic><topic>Sexually transmitted diseases</topic><topic>STD</topic><topic>Studies</topic><topic>Surveillance</topic><topic>Whole genome sequencing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jolly, Ann M</creatorcontrib><creatorcontrib>Dillon, Jo-Anne R</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Pharma and Biotech Premium PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>ProQuest Nursing and Allied Health Source</collection><collection>Virology and AIDS Abstracts</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database (Proquest)</collection><collection>Lancet Titles</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>The Lancet infectious diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jolly, Ann M</au><au>Dillon, Jo-Anne R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks</atitle><jtitle>The Lancet infectious diseases</jtitle><addtitle>Lancet Infect Dis</addtitle><date>2020-04</date><risdate>2020</risdate><volume>20</volume><issue>4</issue><spage>391</spage><epage>392</epage><pages>391-392</pages><issn>1473-3099</issn><eissn>1474-4457</eissn><abstract>In The Lancet Infectious Diseases, Katy Town and colleagues1 report findings of the first large-scale study in which phylogenomic, whole-genome sequencing (WGS) analysis of Neisseria gonorrhoeae isolates was used to identify molecular networks of transmission. The selection of this cutoff was somewhat arbitrary and based on several previous, smaller studies. Because this research will inspire others to undertake similar studies, it will be interesting to understand how different populations and locations influence the selection of appropriate cutoffs to identify molecular chains of transmission. Town and colleagues accessed a remarkable centralised data resource—ie, GRASP information linked with Public Health England's Sexually Transmitted Infection Surveillance System, which collects clinical, sociodemographic, and other data.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>31978352</pmid><doi>10.1016/S1473-3099(19)30751-0</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1473-3099
ispartof The Lancet infectious diseases, 2020-04, Vol.20 (4), p.391-392
issn 1473-3099
1474-4457
language eng
recordid cdi_proquest_miscellaneous_2345505395
source ScienceDirect Journals
subjects Disease transmission
Gene sequencing
Genomes
Gonorrhea
HIV
Human immunodeficiency virus
Infections
Infectious diseases
Molecular chains
Neisseria gonorrhoeae
Polymorphism
Public health
Sexually transmitted diseases
STD
Studies
Surveillance
Whole genome sequencing
title Phylogenomic analysis of Neisseria gonorrhoeae: a promising tool for tracking putative gonococcal sexual networks
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T13%3A31%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Phylogenomic%20analysis%20of%20Neisseria%20gonorrhoeae:%20a%20promising%20tool%20for%20tracking%20putative%20gonococcal%20sexual%20networks&rft.jtitle=The%20Lancet%20infectious%20diseases&rft.au=Jolly,%20Ann%20M&rft.date=2020-04&rft.volume=20&rft.issue=4&rft.spage=391&rft.epage=392&rft.pages=391-392&rft.issn=1473-3099&rft.eissn=1474-4457&rft_id=info:doi/10.1016/S1473-3099(19)30751-0&rft_dat=%3Cproquest_cross%3E2345505395%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c388t-ffa9c2595176cea73bc8502b7cdb2992fbd8d5d663c98fd8976ff6f3e60ef7033%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2425647473&rft_id=info:pmid/31978352&rfr_iscdi=true