Literature DB >> 31515292

Perspectives for Consideration in the Development of Microbial Cell Reference Materials.

Emma Allen-Vercoe1, Joseph Russell Carmical2, Samuel P Forry3, Mitchell H Gail4, Rashmi Sinha4.   

Abstract

Microbiome measurement and analyses benefit greatly from incorporation of reference materials as controls. However, there are many points to consider in defining an ideal whole-cell reference material standard. Such a standard would embody all the diversity and measurement challenges present in real samples, would be completely characterized to provide "ground truth" data, and would be inexpensive and widely available. This ideal is, unfortunately, not readily attainable because of the diverse nature of different sequencing projects. Some applications may benefit most from highly complex reference materials, while others will value characterization or low expense more highly. The selection of appropriate microbial whole-cell reference materials to benchmark and validate microbial measurements should be considered carefully and may vary among specific applications. In this article, we describe a perspective on the development of whole-cell microbial reference materials for use in metagenomics analyses. ©2019 American Association for Cancer Research.

Entities:  

Mesh:

Year:  2019        PMID: 31515292      PMCID: PMC6891190          DOI: 10.1158/1055-9965.EPI-19-0557

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  11 in total

Review 1.  Experimental models of the gut microbiome.

Authors:  Koen Venema; Pieter van den Abbeele
Journal:  Best Pract Res Clin Gastroenterol       Date:  2013-02       Impact factor: 3.043

Review 2.  Challenges for case-control studies with microbiome data.

Authors:  J Paul Brooks
Journal:  Ann Epidemiol       Date:  2016-04-07       Impact factor: 3.797

3.  Bacterial community variation in human body habitats across space and time.

Authors:  Elizabeth K Costello; Christian L Lauber; Micah Hamady; Noah Fierer; Jeffrey I Gordon; Rob Knight
Journal:  Science       Date:  2009-11-05       Impact factor: 47.728

4.  Consistent and correctable bias in metagenomic sequencing experiments.

Authors:  Michael R McLaren; Amy D Willis; Benjamin J Callahan
Journal:  Elife       Date:  2019-09-10       Impact factor: 8.140

5.  Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium.

Authors:  Rashmi Sinha; Galeb Abu-Ali; Emily Vogtmann; Anthony A Fodor; Boyu Ren; Amnon Amir; Emma Schwager; Jonathan Crabtree; Siyuan Ma; Christian C Abnet; Rob Knight; Owen White; Curtis Huttenhower
Journal:  Nat Biotechnol       Date:  2017-10-02       Impact factor: 54.908

6.  The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies.

Authors:  J Paul Brooks; David J Edwards; Michael D Harwich; Maria C Rivera; Jennifer M Fettweis; Myrna G Serrano; Robert A Reris; Nihar U Sheth; Bernice Huang; Philippe Girerd; Jerome F Strauss; Kimberly K Jefferson; Gregory A Buck
Journal:  BMC Microbiol       Date:  2015-03-21       Impact factor: 3.605

7.  Temporal variability is a personalized feature of the human microbiome.

Authors:  Gilberto E Flores; J Gregory Caporaso; Jessica B Henley; Jai Ram Rideout; Daniel Domogala; John Chase; Jonathan W Leff; Yoshiki Vázquez-Baeza; Antonio Gonzalez; Rob Knight; Robert R Dunn; Noah Fierer
Journal:  Genome Biol       Date:  2014-12-03       Impact factor: 13.583

8.  Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

Authors:  Susannah J Salter; Michael J Cox; Elena M Turek; Szymon T Calus; William O Cookson; Miriam F Moffatt; Paul Turner; Julian Parkhill; Nicholas J Loman; Alan W Walker
Journal:  BMC Biol       Date:  2014-11-12       Impact factor: 7.431

9.  The microbiome quality control project: baseline study design and future directions.

Authors:  Rashmi Sinha; Christian C Abnet; Owen White; Rob Knight; Curtis Huttenhower
Journal:  Genome Biol       Date:  2015-12-09       Impact factor: 13.583

10.  A Lot on Your Plate? Well-to-Well Contamination as an Additional Confounder in Microbiome Sequence Analyses.

Authors:  Alan W Walker
Journal:  mSystems       Date:  2019-06-25       Impact factor: 6.496

View more
  2 in total

1.  Workshop report: Toward the development of a human whole stool reference material for metabolomic and metagenomic gut microbiome measurements.

Authors:  Rupasri Mandal; Raul Cano; Cindy D Davis; David Hayashi; Scott A Jackson; Christina M Jones; Johanna W Lampe; Marie E Latulippe; Nancy J Lin; Katrice A Lippa; Paulina Piotrowski; Sandra M Da Silva; Kelly S Swanson; David S Wishart
Journal:  Metabolomics       Date:  2020-11-08       Impact factor: 4.290

2.  Characterization and Demonstration of Mock Communities as Control Reagents for Accurate Human Microbiome Community Measurements.

Authors:  Dieter M Tourlousse; Koji Narita; Takamasa Miura; Akiko Ohashi; Masami Matsuda; Yoshifumi Ohyama; Mamiko Shimamura; Masataka Furukawa; Ken Kasahara; Keishi Kameyama; Sakae Saito; Maki Goto; Ritsuko Shimizu; Riko Mishima; Jiro Nakayama; Koji Hosomi; Jun Kunisawa; Jun Terauchi; Yuji Sekiguchi; Hiroko Kawasaki
Journal:  Microbiol Spectr       Date:  2022-03-02
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.