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Rob Knight  - - - 
Top co-authors See all
Peer Bork

681 shared publications

Structural and Computational Biology UnitEuropean Molecular Biology Laboratory Heidelberg Germany

Victor Nizet

468 shared publications

University of Rhode Island College of Pharmacy, Kingston, RI

K. M. Godfrey

435 shared publications

Medical Research Council Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD, UK

Gregor Reid

288 shared publications

University of Western Ontario, London, Canada

Pieter C Dorrestein

257 shared publications

Collaborative Mass Spectrometry Innovation Center; Skaggs School of Pharmacy and Pharmaceutical Sciences; University of California; San Diego, La Jolla California 92093 United States

Publication Record
Distribution of Articles published per year 
(1999 - 2018)
Total number of journals
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Publications See all
PREPRINT-CONTENT 0 Reads 0 Citations Quantifying and understanding well-to-well contamination in microbiome research Jeremiah J Minich, Jon G Sanders, Amnon Amir, Greg Humphrey,... Published: 14 March 2019
bioRxiv, doi: 10.1101/577718
DOI See at publisher website ABS Show/hide abstract
Microbial sequences inferred as belonging to one sample may not have originated from that sample. Such contamination may arise from laboratory or reagent sources or from physical exchange between samples. This study seeks to rigorously assess the behavior of this often-neglected between-sample contamination. Using unique bacteria each assigned a particular well in a plate, we assess the frequency at which sequences from each source appears in other wells. We evaluate the effects of different DNA extraction methods performed in two labs using a consistent plate layout including blanks, low biomass, and high biomass samples. Well-to-well contamination occurred primarily during DNA extraction, and to a lesser extent in library preparation, while barcode leakage was negligible. Labs differed in the levels of contamination. DNA extraction methods differed in their occurrences and levels of well-to-well contamination, with robotic methods having more well-to-well contamination while manual methods having higher background contaminants. Well-to-well contamination was observed to occur primarily in neighboring samples, with rare events up to 10 wells apart. The effect of well-to-well was greatest in samples with lower biomass, and negatively impacted metrics of alpha and beta diversity. Our work emphasizes that sample contamination is a combination of crosstalk from nearby wells and background contaminants. To reduce well-to-well effects, samples should be randomized across plates, and samples of similar biomass processed together. Researchers should evaluate well-to-well contamination in study design and avoid removal of taxa or OTUs appearing in negative controls, as many will be microbes from other samples rather than reagent contaminants.ImportanceMicrobiome research has uncovered magnificent biological and chemical stories across nearly all areas of life science, at times creating controversy when findings reveal fantastic descriptions of microbes living and even thriving in once thought to be sterile environments. Scientists have refuted many of these claims because of contamination, which has led to robust requirements including use of controls for validating accurate portrayals of microbial communities. In this study, we describe a previously undocumented form of contamination, well-to-well contamination and show that contamination primarily occurs during DNA extraction rather than PCR, is highest in plate-based methods as compared to single tube extraction, and occurs in higher frequency in low biomass samples. This finding has profound importance on the field as many current techniques to ‘decontaminate’ a dataset simply relies on an assumption that microbial reads found in blanks are contaminants from ‘outside’ namely the reagents or consumables.
Article 0 Reads 0 Citations Environmental toxicants in breast milk of Norwegian mothers and gut bacteria composition and metabolites in their infant... Nina Iszatt, Stefan Janssen, Virissa Lenters, Cecilie Dahl, ... Published: 27 February 2019
Microbiome, doi: 10.1186/s40168-019-0645-2
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Early disruption of the microbial community may influence life-long health. Environmental toxicants can contaminate breast milk and the developing infant gut microbiome is directly exposed. We investigated whether environmental toxicants in breastmilk affect the composition and function of the infant gut microbiome at 1 month. We measured environmental toxicants in breastmilk, fecal short-chain fatty acids (SCFAs), and gut microbial composition from 16S rRNA gene amplicon sequencing using samples from 267 mother-child pairs in the Norwegian Microbiota Cohort (NoMIC). We tested 28 chemical exposures: polychlorinated biphenyls (PCBs), polybrominated flame retardants (PBDEs), per- and polyfluoroalkyl substances (PFASs), and organochlorine pesticides. We assessed chemical exposure and alpha diversity/SCFAs using elastic net regression modeling and generalized linear models, adjusting for confounders, and variation in beta diversity (UniFrac), taxa abundance (ANCOM), and predicted metagenomes (PiCRUSt) in low, medium, and high exposed groups. PBDE-28 and the surfactant perfluorooctanesulfonic acid (PFOS) were associated with less microbiome diversity. Some sub-OTUs of Lactobacillus, an important genus in early life, were lower in abundance in samples from infants with relative “high” (> 80th percentile) vs. “low” (< 20th percentile) toxicant exposure in this cohort. Moreover, breast milk toxicants were associated with microbiome functionality, explaining up to 34% of variance in acetic and propionic SCFAs, essential signaling molecules. Per one standard deviation of exposure, PBDE-28 was associated with less propionic acid (− 24% [95% CI − 35% to − 14%] relative to the mean), and PCB-209 with less acetic acid (− 15% [95% CI − 29% to − 0.4%]). Conversely, PFOA and dioxin-like PCB-167 were associated with 61% (95% CI 35% to 87%) and 22% (95% CI 8% to 35%) more propionic and acetic acid, respectively. Environmental toxicant exposure may influence infant gut microbial function during a critical developmental window. Future studies are needed to replicate these novel findings and investigate whether this has any impact on child health. The online version of this article (10.1186/s40168-019-0645-2) contains supplementary material, which is available to authorized users.
PREPRINT-CONTENT 0 Reads 0 Citations Red Sea SAR11 and Prochlorococcus Single-cell Genomes Reflect Globally Distributed Pangenomes Luke R. Thompson, Mohamed Fauzi Haroon, Ahmed A. Shibl, Matt... Published: 14 February 2019
bioRxiv, doi: 10.1101/549816
DOI See at publisher website
Article 0 Reads 0 Citations Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome Robert A. Quinn, Sandeep Adem, Robert H. Mills, William Coms... Published: 13 February 2019
Microbiome, doi: 10.1186/s40168-019-0636-3
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Studies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood. Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity. The CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung. In cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen’s persistence by providing its preferred carbon source. The online version of this article (10.1186/s40168-019-0636-3) contains supplementary material, which is available to authorized users.
Article 0 Reads 0 Citations Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease Robert H. Mills, Yoshiki Vázquez-Baeza, Qiyun Zhu, Lingjing ... Published: 12 February 2019
mSystems, doi: 10.1128/msystems.00337-18
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn’s disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual’s fecal microbiome associated with clinical consequences.
PREPRINT-CONTENT 0 Reads 0 Citations Age and sex-dependent patterns of gut microbial diversity in human adults Jacobo De La Cuesta-Zuluaga, Scott T Kelley, Yingfeng Chen, ... Published: 08 February 2019
doi: 10.1101/544270
DOI See at publisher website