Literature DB >> 30820491

CRISPRs for Strain Tracking and Their Application to Microbiota Transplantation Data Analysis.

Tony J Lam1, Yuzhen Ye1.   

Abstract

CRISPR-Cas systems are adaptive immune systems naturally found in bacteria and archaea. Prokaryotes use these immune systems to defend against invaders, which include phages, plasmids, and other mobile genetic elements. Relying on the integration of spacers derived from invader sequences (protospacers) into CRISPR loci (forming spacers flanked by repeats), CRISPR-Cas systems are able to store the memory of past immunological encounters. While CRISPR-Cas systems have evolved in response to invading mobile genetic elements, invaders have also developed mechanisms to avoid detection. As a result of an arms race between CRISPR-Cas systems and their targets, CRISPR arrays typically undergo rapid turnover of spacers through the acquisition and loss events. Additionally, microbiomes of different individuals rarely share spacers. Here, we present a computational pipeline, CRISPRtrack, for strain tracking based on CRISPR spacer content, and we applied it to fecal transplantation microbiome data to study the retention of donor strains in recipients. Our results demonstrate the potential use of CRISPRs as a simple yet effective tool for donor-strain tracking in fecal transplantation and as a general purpose tool for quantifying microbiome similarity.

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Year:  2019        PMID: 30820491      PMCID: PMC6390457          DOI: 10.1089/crispr.2018.0046

Source DB:  PubMed          Journal:  CRISPR J        ISSN: 2573-1599


  60 in total

1.  The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA.

Authors:  Josiane E Garneau; Marie-Ève Dupuis; Manuela Villion; Dennis A Romero; Rodolphe Barrangou; Patrick Boyaval; Christophe Fremaux; Philippe Horvath; Alfonso H Magadán; Sylvain Moineau
Journal:  Nature       Date:  2010-11-04       Impact factor: 49.962

Review 2.  CRISPR-Based Typing and Next-Generation Tracking Technologies.

Authors:  Rodolphe Barrangou; Edward G Dudley
Journal:  Annu Rev Food Sci Technol       Date:  2016-01-11

Review 3.  The Significance of Mutualistic Phages for Bacterial Ecology and Evolution.

Authors:  Nancy Obeng; Akbar Adjie Pratama; Jan Dirk van Elsas
Journal:  Trends Microbiol       Date:  2016-01-27       Impact factor: 17.079

4.  A putative viral defence mechanism in archaeal cells.

Authors:  Reidun K Lillestøl; Peter Redder; Roger A Garrett; Kim Brügger
Journal:  Archaea       Date:  2006-08       Impact factor: 3.273

5.  MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

Authors:  Dinghua Li; Chi-Man Liu; Ruibang Luo; Kunihiko Sadakane; Tak-Wah Lam
Journal:  Bioinformatics       Date:  2015-01-20       Impact factor: 6.937

6.  A metagenome-wide association study of gut microbiota in type 2 diabetes.

Authors:  Junjie Qin; Yingrui Li; Zhiming Cai; Shenghui Li; Jianfeng Zhu; Fan Zhang; Suisha Liang; Wenwei Zhang; Yuanlin Guan; Dongqian Shen; Yangqing Peng; Dongya Zhang; Zhuye Jie; Wenxian Wu; Youwen Qin; Wenbin Xue; Junhua Li; Lingchuan Han; Donghui Lu; Peixian Wu; Yali Dai; Xiaojuan Sun; Zesong Li; Aifa Tang; Shilong Zhong; Xiaoping Li; Weineng Chen; Ran Xu; Mingbang Wang; Qiang Feng; Meihua Gong; Jing Yu; Yanyan Zhang; Ming Zhang; Torben Hansen; Gaston Sanchez; Jeroen Raes; Gwen Falony; Shujiro Okuda; Mathieu Almeida; Emmanuelle LeChatelier; Pierre Renault; Nicolas Pons; Jean-Michel Batto; Zhaoxi Zhang; Hua Chen; Ruifu Yang; Weimou Zheng; Songgang Li; Huanming Yang; Jian Wang; S Dusko Ehrlich; Rasmus Nielsen; Oluf Pedersen; Karsten Kristiansen; Jun Wang
Journal:  Nature       Date:  2012-09-26       Impact factor: 49.962

7.  Diversity and evolution of class 2 CRISPR-Cas systems.

Authors:  Sergey Shmakov; Aaron Smargon; David Scott; David Cox; Neena Pyzocha; Winston Yan; Omar O Abudayyeh; Jonathan S Gootenberg; Kira S Makarova; Yuri I Wolf; Konstantin Severinov; Feng Zhang; Eugene V Koonin
Journal:  Nat Rev Microbiol       Date:  2017-01-23       Impact factor: 60.633

8.  Phage response to CRISPR-encoded resistance in Streptococcus thermophilus.

Authors:  Hélène Deveau; Rodolphe Barrangou; Josiane E Garneau; Jessica Labonté; Christophe Fremaux; Patrick Boyaval; Dennis A Romero; Philippe Horvath; Sylvain Moineau
Journal:  J Bacteriol       Date:  2007-12-07       Impact factor: 3.490

9.  The highly dynamic CRISPR1 system of Streptococcus agalactiae controls the diversity of its mobilome.

Authors:  Maria-José Lopez-Sanchez; Elisabeth Sauvage; Violette Da Cunha; Dominique Clermont; Elisoa Ratsima Hariniaina; Bruno Gonzalez-Zorn; Claire Poyart; Isabelle Rosinski-Chupin; Philippe Glaser
Journal:  Mol Microbiol       Date:  2012-07-27       Impact factor: 3.501

10.  CRISPR adaptation biases explain preference for acquisition of foreign DNA.

Authors:  Asaf Levy; Moran G Goren; Ido Yosef; Oren Auster; Miriam Manor; Gil Amitai; Rotem Edgar; Udi Qimron; Rotem Sorek
Journal:  Nature       Date:  2015-04-13       Impact factor: 49.962

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  3 in total

1.  Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis.

Authors:  Byron J Smith; Yvette Piceno; Martin Zydek; Bing Zhang; Lara Aboud Syriani; Jonathan P Terdiman; Zain Kassam; Averil Ma; Susan V Lynch; Katherine S Pollard; Najwa El-Nachef
Journal:  Sci Rep       Date:  2022-04-01       Impact factor: 4.379

2.  Diversity and dynamics of the CRISPR-Cas systems associated with Bacteroides fragilis in human population.

Authors:  Tony J Lam; Kate Mortensen; Yuzhen Ye
Journal:  BMC Genomics       Date:  2022-08-11       Impact factor: 4.547

Review 3.  Mechanisms underpinning the efficacy of faecal microbiota transplantation in treating gastrointestinal disease.

Authors:  Jonathan P Segal; Benjamin H Mullish; Mohammed N Quraishi; Tariq Iqbal; Julian R Marchesi; Harry Sokol
Journal:  Therap Adv Gastroenterol       Date:  2020-09-03       Impact factor: 4.409

  3 in total

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