Methodology challenges in studying human gut microbiota – effects of collection, storage, DNA extraction and next generation sequencing technologies

Panek, Michał; Paljetak, Hana Čipčić; Barešić, Anja; Perić, Mihaela; Matijašić, Mario; Lojkić, Ivana; Bender, Darija Vranešić; Krznarić, Željko; Verbanac, Donatella

doi:10.1038/s41598-018-23296-4

Cited by 149 publications

(136 citation statements)

References 49 publications

Supporting

Mentioning

130

Contrasting

Unclassified

Order By: Relevance

“…Broadly used, ordination has played a critical role in associating microbial structure with specific features or phenotypes of interest, but has also proven to be overly sensitive to normalization and study bias (e.g. technological noise, DNA preparation protocol, sequencing error) (42).…”

Section: Current Methods For Dimensionality Reductionmentioning

confidence: 99%

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

Tataru

David

2019

Preprint

View full text Add to dashboard Cite

Microbiomes are complex ecological systems that play crucial roles in understanding natural phenomena from human disease to climate change. Especially in human gut microbiome studies, where collecting clinical samples can be arduous, the number of taxa considered in any one study often exceeds the number of samples ten to one hundred-fold. This discrepancy decreases the power of studies to identify meaningful differences between samples, increases the likelihood of false positive results, and subsequently limits reproducibility. Despite the vast collections of microbiome data already available, biome-specific patterns of microbial structure are not currently leveraged to inform studies. Instead, most microbiome survey studies focus on differential abundance testing per taxa in pursuit of specific biomarkers for a given phenotype. This methodology assumes differences in individual species, genera, or families can be used to distinguish between microbial communities and ignores community-level response. In this paper, we propose to leverage public microbiome databases to shift the analysis paradigm from a focus on taxonomic counts to a focus on comprehensive properties that more completely characterize microbial community members' function and environmental relationships. We learn these properties by applying an embedding algorithm to quantify taxa co-occurrence patterns in over 18,000 samples from the American Gut Project (AGP) microbiome crowdsourcing effort. The resulting set of embeddings transforms human gut microbiome data from thousands of taxa counts to a latent variable landscape of only one hundred "properties", or contextual relationships. We then compare the predictive power of models trained using properties, normalized taxonomic count 1 data, and another commonly used dimensionality reduction method, Principal Component Analysis in categorizing samples from individuals with inflammatory bowel disease (IBD) and healthy controls. We show that predictive models trained using property data are the most accurate, robust, and generalizable, and that property-based models can be trained on one dataset and deployed on another with positive results. Furthermore, we find that these properties can be interpreted in the context of current knowledge; properties correlate significantly with known metabolic pathways, and distances between taxa in "property space" roughly correlate with their phylogenetic distances. Using these properties, we are able to extract known and new bacterial metabolic pathways associated with inflammatory bowel disease across two completely independent studies.More broadly, this paper explores a reframing of the microbiome analysis mindset, from taxonomic counts to comprehensive community-level properties. By providing a set of pre-trained embeddings, we allow any V4 16S amplicon study to leverage and apply the publicly informed properties presented to increase the statistical power, reproducibility, and generalizability of analysis. References

show abstract

Section: Current Methods For Dimensionality Reductionmentioning

confidence: 99%

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

Tataru

David

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Finally, studies of mucosal immunity and gut inflammation should include measurements of the microbiota. There are multiple methods to sequence and measure the microbiota (172)(173)(174); a full discussion is beyond our scope. However, investigations that account for microbiota community structure should take the Anna Karenina hypothesis into account: healthy microbiotas are similar, but transitions to an unhealthy microbiota are stochastic and may be difficult to detect (2).…”

Section: Tools and Areas Of Consideration For Ecoimmunological Studiesmentioning

confidence: 99%

The Costs of Living Together: Immune Responses to the Microbiota and Chronic Gut Inflammation

Kirschman

Milligan-Myhre

2019

Appl Environ Microbiol

View full text Add to dashboard Cite

While the vertebrate microbiota is critical to the normal function of many host traits, hosts may expend a large amount of energy to constrain and interface with their microbiota via their immune system to avoid the high fitness costs associated with gut dysbiosis, pathobionts, and opportunistic pathogens. All jawed vertebrates share mucosal immunity dedicated to isolating the microbiota, and a breakdown of this system can result in chronic gut inflammation. In humans, chronic gut inflammation negatively affects growth and development. There is little information available on the prevalence of chronic gut inflammation in wild animals, but given that animals with different life histories emphasize different immune responses, it follows that wild animals may vary in their susceptibility to chronic gut inflammation, and most animals will experience signaling that can lead to this state. These can be top-down signals originating from sources like the central nervous system or bottom-up signals originating from changes in the gut microbiota. The sources of these signals might include stress, developmental transitions, food restriction, and dietary shifts. Here, we briefly discuss host-microbiota interactions from the perspective of life history theory and ecoimmunology, focusing on the mucosal immune system and chronic gut inflammation. We also include future directions for research and the tools necessary to investigate them.

show abstract

“…High‐throughput sequencing (HTS) technologies (also known as next generation sequencing—NGS) have revolutionized the study of microbial diversity. HTS is currently used in multidisciplinary fields in academic, clinical, and industrial settings, particularly to identify mammal species or to study microbial diversity in soils, freshwater, human guts, wastewater treatment facilities, and others (Jones et al, 2009; Nam, Jung, Roh, Kim, & Bae, 2011; Panek et al, 2018; Roh et al, 2009; Ronholm, 2018; Ye & Zhang, 2011; Zhang et al, 2018). This technology enables the characterization of microbial diversity but also allows a better knowledge about the functions, activities, and dynamics of microbial communities thriving in their natural environments (Zhou et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Assessment of microbiota present on a Portuguese historical stone convent using high‐throughput sequencing approaches

et al. 2020

View full text Add to dashboard Cite

The study performed on the stone materials from the Convent of Christ revealed the presence of a complex microbial ecosystem, emphasizing the determinant role of microorganisms on the biodecay of this built cultural heritage. In this case study, the presence of Rubrobacter sp., Arthrobacter sp., Roseomonas sp., and Marinobacter sp. seems to be responsible for colored stains and biofilm formation while Ulocladium sp., Cladosporium sp., and Dirina sp. may be related to structural damages. The implementation of high‐throughput sequencing approaches on the Convent of Christ's biodecay assessment allowed us to explore, compare, and characterize the microbial communities, overcoming the limitations of culture‐dependent techniques, which only identify the cultivable population. The application of these different tools and insights gave us a panoramic view of the microbiota thriving on the Convent of Christ and signalize the main biodeteriogenic agents acting on the biodecay of stone materials. This finding highlighted the importance of performing metagenomic studies due to the improvements and the reduced amount of sample DNA needed, promoting a deeper and more detailed knowledge of the microbiota present on these dynamic repositories that support microbial life. This will further enable us to perform prospective studies in quarry and applied stone context, monitoring biogenic and nonbiogenic agents, and also to define long‐term mitigation strategies to prevent biodegradation/biodeterioration processes.

show abstract

Methodology challenges in studying human gut microbiota – effects of collection, storage, DNA extraction and next generation sequencing technologies

Cited by 149 publications

References 49 publications

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

The Costs of Living Together: Immune Responses to the Microbiota and Chronic Gut Inflammation

Assessment of microbiota present on a Portuguese historical stone convent using high‐throughput sequencing approaches

Contact Info

Product

Resources

About