Quantitative microbiome profiling links gut community variation to microbial load

By D. Vandeputte, Gunter Kathagen, K. D'hoe, Sara Vieira-Silva, M. Valles-Colomer, J. Sabino, Jun Wang, R. Tito, Lindsey De Commer, Youssef Darzi and 3 more. Nature, 2017

1,043 citations recorded by the source corpus.

Subfields: Molecular Biology, Physiology, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/7cefc3e5de888c3f5c297adc34ef2985a878df1c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. R. Ross
2. Peer Bork
3. Patrice D Cani
4. Jeroen Raes
5. Yang Bai
6. C. Hill
7. A. Shkoporov
8. K. Peay

In Physiology

1. Hannele Yki-Järvinen
2. Jeroen Raes
3. R. Ross
4. Patrice D Cani

Citations in the corpus

• Quantitative PCR provides a simple and accessible method for quantitative microbiota profiling (2020, background): “Of note, none of the clinical trials published during the past year (except the ones specifically addressing the compositionality problem [5, 6]) utilized quantitative microbiome profiling.”
• Current challenges and best-practice protocols for microbiome analysis (2019, neutral): “replicates existing under similar conditions [36].”
• Human gut microbiome: hopes, threats and promises (2018, background): “63 This study strongly argues that most previous studies, which have primarily been based on the investigation of the relative proportions of microbes, have probably not been able to capture the essence of the problem.”
• Management of Rheumatoid Arthritis: An Overview (2021, result): “According to the results of the studies, Prevotella copri, Collinsella and Lactobacillus salivarius were found to be more abundant in RA patients, while Bacteroides, Faecalibacterium, Veillonella and Haemophilus were lower in quantity [76,79].”
• The Human Gut Microbiome: From Association to Modulation. (2018, background): “In some, such as in the case of colorectal cancer (Zeller et al., 2014) or arthritis (Scher et al., 2013; Tito et al., 2017; Zhang et al., 2015b), individual marker taxa are associated to the disease, whereas effects on overall composition aremild.”
• Core microbiomes for sustainable agroecosystems (2018, background): “In addition, relative abundance data obtained from high-throughput sequencing should be used with caution as they provide less information than absolute abundance data in inferring microorganism– microorganism and microorganism–host interactions 79 .”
• Integrating quantitative morphological and qualitative molecular methods to analyse soil nematode community responses to plant range expansion (2018, background): “Arguably most importantly, diversity analyses such as HTS provide only relative abundance data and do not provide information on absolute (nematode) numbers (Vandeputte et al., 2017).”
• Gut microbiome analysis as a tool towards targeted non-invasive biomarkers for early hepatocellular carcinoma (2018, methodology): “Stool moisture is a key covariate in microbiome space and marker construction, 24 33 thus we further combined the stool moisture with the 30 OTUs markers as key variables to construct the final POD model and compared the diagnosis potential of the two POD models among the different cohorts.”