Using DNA Metabarcoding To Evaluate the Plant Component of Human Diets: a Proof of Concept

Detection and Quantification of Botanical Impurities in Commercial Oregano (Origanum vulgare) Using Metabarcoding and Digital PCR

DNA technology for food authentication is already well established, and with the advent of Next Generation Sequencing (NGS) and, more specifically, metabarcoding, compositional analysis of food at the molecular level has rapidly gained popularity. This has led to several reports in the media about the presence of foreign, non-declared species in several food commodities. As herbs and spices are attractive targets for fraudulent manipulation, a combination of digital PCR and metabarcoding by NGS was employed to check the purity of 285 oregano samples taken from the European market. By using novel primers and analytical approaches, it was possible to detect and quantify both adulterants and contaminants in these samples. The results highlight the high potential of NGS for compositional analysis, although its quantitative information (read count percentages) is unreliable, and other techniques are therefore needed to complement the sequencing information for assessing authenticity ('true to the name') of food ingredients.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

Administration of Bifidobacterium animalis subsp. lactis strain BB-12® in healthy children: characterization, functional composition, and metabolism of the gut microbiome

Introduction

The consumption of probiotics may influence children's gut microbiome and metabolome, which may reflect shifts in gut microbial diversity composition and metabolism. These potential changes might have a beneficial impact on health. However, there is a lack of evidence investigating the effect of probiotics on the gut microbiome and metabolome of children. We aimed to examine the potential impact of a two (Streptococcus thermophilus and Lactobacillus delbrueckii; S2) vs. three (S2 + Bifidobacterium animalis subsp. lactis strain BB-12) strain-supplemented yogurt.

Methods

Included in this study were 59 participants, aged one to five years old, recruited to phase I of a double-blinded, randomized controlled trial. Fecal samples were collected at baseline, after the intervention, and at twenty days post-intervention discontinuation, and untargeted metabolomics and shotgun metagenomics were performed.

Results

Shotgun metagenomics and metabolomic analyses showed no global changes in either intervention group's gut microbiome alpha or beta diversity indices, except for a lower microbial diversity in the S2 + BB12 group at Day 30. The relative abundance of the two and three intervention bacteria increased in the S2 and S2 + BB12 groups, respectively, from Day 0 to Day 10. In the S2 + BB12 group, the abundance of several fecal metabolites increased at Day 10, including alanine, glycine, lysine, phenylalanine, serine, and valine. These fecal metabolite changes did not occur in the S2 group.

Discussion

In conclusion, there were were no significant differences in the global metagenomic or metabolomic profiles between healthy children receiving two (S2) vs. three (S2 + BB12) probiotic strains for 10 days. Nevertheless, we observed a significant increase (Day 0 to Day 10) in the relative abundance of the two and three probiotics administered in the S2 and S2 + BB12 groups, respectively, indicating the intervention had a measurable impact on the bacteria of interest in the gut microbiome. Future research using longer probiotic intervention durations and in children at risk for gastrointestinal disorders may elucidate if functional metabolite changes confer a protective gastrointestinal effect.

A detailed workflow to develop QIIME2-formatted reference databases for taxonomic analysis of DNA metabarcoding data

Background

The DNA metabarcoding approach has become one of the most used techniques to study the taxa composition of various sample types. To deal with the high amount of data generated by the high-throughput sequencing process, a bioinformatics workflow is required and the QIIME2 platform has emerged as one of the most reliable and commonly used. However, only some pre-formatted reference databases dedicated to a few barcode sequences are available to assign taxonomy. If users want to develop a new custom reference database, several bottlenecks still need to be addressed and a detailed procedure explaining how to develop and format such a database is currently missing. In consequence, this work is aimed at presenting a detailed workflow explaining from start to finish how to develop such a curated reference database for any barcode sequence.

Results

We developed DB4Q2, a detailed workflow that allowed development of plant reference databases dedicated to ITS2 and rbcL, two commonly used barcode sequences in plant metabarcoding studies. This workflow addresses several of the main bottlenecks connected with the development of a curated reference database. The detailed and commented structure of DB4Q2 offers the possibility of developing reference databases even without extensive bioinformatics skills, and avoids ‘black box’ systems that are sometimes encountered. Some filtering steps have been included to discard presumably fungal and misidentified sequences. The flexible character of DB4Q2 allows several key sequence processing steps to be included or not, and downloading issues can be avoided. Benchmarking the databases developed using DB4Q2 revealed that they performed well compared to previously published reference datasets.

Conclusion

This study presents DB4Q2, a detailed procedure to develop custom reference databases in order to carry out taxonomic analyses with QIIME2, but also with other bioinformatics platforms if desired. This work also provides ready-to-use plant ITS2 and rbcL databases for which the prediction accuracy has been assessed and compared to that of other published databases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01067-5.

Mediterranean-Like Dietary Pattern Associations With Gut Microbiome Composition and Subclinical Gastrointestinal Inflammation

BACKGROUND & AIMS

Case-control studies have shown that patients with Crohn's disease (CD) have a microbial composition different from healthy individuals. Although the causes of CD are unknown, epidemiologic studies suggest that diet is an important contributor to CD risk, potentially via modulation of bacterial composition and gut inflammation. We hypothesized that long-term dietary clusters (DCs) are associated with gut microbiome compositions and gut inflammation. Our objectives were to identify dietary patterns and assess whether they are associated with alterations in specific gut microbial compositions and subclinical levels of gut inflammation in a cohort of healthy first-degree relatives (FDRs) of patients with CD.

METHODS

As part of the Genetic, Environmental, Microbial (GEM) Project, we recruited a cohort of 2289 healthy FDRs of patients with CD. Individuals provided stool samples and answered a validated food frequency questionnaire reflecting their habitual diet during the year before sample collection. Unsupervised analysis identified 3 dietary and 3 microbial composition clusters.

RESULTS

DC3, resembling the Mediterranean diet, was strongly associated with a defined microbial composition, with an increased abundance of fiber-degrading bacteria, such as Ruminococcus, as well as taxa such as Faecalibacterium. The DC3 diet was also significantly associated with lower levels of subclinical gut inflammation, defined by fecal calprotectin, compared with other dietary patterns. No significant associations were found between individual food items and fecal calprotectin, suggesting that long-term dietary patterns rather than individual food items contribute to subclinical gut inflammation. Additionally, mediation analysis demonstrated that DC3 had a direct effect on subclinical inflammation that was partially mediated by the microbiota.

CONCLUSIONS

Overall, these results indicated that Mediterranean-like dietary patterns are associated with microbiome and lower intestinal inflammation. This study will help guide future dietary strategies that affect microbial composition and host gut inflammation to prevent diseases.

A Guide to Dietary Pattern-Microbiome Data Integration

The human gut microbiome is linked to metabolic and cardiovascular disease risk. Dietary modulation of the human gut microbiome offers an attractive pathway to manipulate the microbiome to prevent microbiome-related disease. However, this promise has not been realized. The complex system of diet and microbiome interactions is poorly understood. Integrating observational human diet and microbiome data can help researchers and clinicians untangle the complex systems of interactions that predict how the microbiome will change in response to foods. The use of dietary patterns to assess diet-microbiome relations holds promise to identify interesting associations and result in findings that can directly translate into actionable dietary intake recommendations and eating plans. In this article, we first highlight the complexity inherent in both dietary and microbiome data and introduce the approaches generally used to explore diet and microbiome simultaneously in observational studies. Second, we review the food group and dietary pattern-microbiome literature focusing on dietary complexity-moving beyond nutrients. Our review identified a substantial and growing body of literature that explores links between the microbiome and dietary patterns. However, there was very little standardization of dietary collection and assessment methods across studies. The 54 studies identified in this review used ≥7 different methods to assess diet. Coupled with the variation in final dietary parameters calculated from dietary data (e.g., dietary indices, dietary patterns, food groups, etc.), few studies with shared methods and assessment techniques were available for comparison. Third, we highlight the similarities between dietary and microbiome data structures and present the possibility that multivariate and compositional methods, developed initially for microbiome data, could have utility when applied to dietary data. Finally, we summarize the current state of the art for diet-microbiome data integration and highlight ways dietary data could be paired with microbiome data in future studies to improve the detection of diet-microbiome signals.

The precautionary principle and dietary DNA metabarcoding: Commonly used abundance thresholds change ecological interpretation

Dietary DNA metabarcoding enables researchers to identify and characterize trophic interactions with a high degree of taxonomic precision. It is also sensitive to sources of bias and contamination in the field and laboratory. One of the earliest and most common strategies for dealing with such sensitivities has been to remove all low-abundance sequences and conduct ecological analyses based on the presence or absence of food taxa. Although this step is now often perceived to be necessary, evidence of its sufficiency is lacking and more attention to the risk of introducing other errors is needed. Using computer simulations, we demonstrate that common strategies to remove low-abundance sequences can erroneously eliminate true dietary sequences in ways that impact downstream inferences. Using real data from well-studied wildlife populations in Yellowstone National Park, we further show how these strategies can markedly alter the composition of dietary profiles in ways that scale-up to obscure ecological interpretations about dietary generalism, specialism, and composition. Although the practice of removing low-abundance sequences may continue to be a useful strategy to address research questions that focus on a subset of relatively abundant foods, its continued widespread use risks generating misleading perceptions about the structure of trophic networks. Researchers working with dietary DNA metabarcoding data-or similar data such as environmental DNA, microbiomes, or pathobiomes-should be aware of drawbacks and consider alternative bioinformatic, experimental, and statistical solutions.

Gut bless you: The microbiota-gut-brain axis in irritable bowel syndrome

Irritable bowel syndrome (IBS) is a common clinical label for medically unexplained gastrointestinal symptoms, recently described as a disturbance of the microbiota-gut-brain axis. Despite decades of research, the pathophysiology of this highly heterogeneous disorder remains elusive. However, a dramatic change in the understanding of the underlying pathophysiological mechanisms surfaced when the importance of gut microbiota protruded the scientific picture. Are we getting any closer to understanding IBS' etiology, or are we drowning in unspecific, conflicting data because we possess limited tools to unravel the cluster of secrets our gut microbiota is concealing? In this comprehensive review we are discussing some of the major important features of IBS and their interaction with gut microbiota, clinical microbiota-altering treatment such as the low FODMAP diet and fecal microbiota transplantation, neuroimaging and methods in microbiota analyses, and current and future challenges with big data analysis in IBS.

Using DNA metabarcoding to decipher the diet plant component of mammals from the Eastern Mediterranean region

Longevity of species populations depends largely on interactions among animals and plants in an ecosystem. Predation and seed dispersal are among the most important interactions necessary for species conservation and persistence, and diet analysis is a prerequisite tool to evaluate these interactions. Understanding these processes is crucial for identifying conservation targets and for executing efficient reforestation and ecological restoration. In this study, we applied a scat DNA metabarcoding technique using the P6-loop of the trnL (UAA) chloroplastic marker to describe the seasonal plant diet composition of 15 mammal species from a highly biodiverse Lebanese forest in the Eastern Mediterranean. We also recovered plant seeds, when present, from the scats for identification. The mammal species belong to 10 families from 5 different orders. More than 133 plant species from 54 plant families were detected and identified. Species from the Rosaceae, Poaceae, Apiaceae, Fabaceae, Fagaceae and Berberidaceae families were consumed by the majority of the mammals and should be taken into consideration in future reforestation and conservation projects. Our results showed that the DNA metabarcoding approach provides a promising method for tracking the dietary plant components of a wide diversity of mammals, yielding key insights into plant-animal interactions inside Lebanon’s forests.

Advances and Limitations of Next Generation Sequencing in Animal Diet Analysis

Diet analysis is a critical content of animal ecology and the diet analysis methods have been constantly improving and updating. Contrary to traditional methods of high labor intensity and low resolution, the next generation sequencing (NGS) approach has been suggested as a promising tool for dietary studies, which greatly improves the efficiency and broadens the application range. Here we present a framework of adopting NGS and DNA metabarcoding into diet analysis, and discuss the application in aspects of prey taxa composition and structure, intra-specific and inter-specific trophic links, and the effects of animal feeding on environmental changes. Yet, the generation of NGS-based diet data and subsequent analyses and interpretations are still challenging with several factors, making it possible still not as widely used as might be expected. We suggest that NGS-based diet methods must be furthered, analytical pipelines should be developed. More application perspectives, including nutrient geometry, metagenomics and nutrigenomics, need to be incorporated to encourage more ecologists to infer novel insights on they work.

Comprehensive coverage of human last meal components revealed by a forensic DNA metabarcoding approach

Stomach content analyses are a valuable tool in human forensic science to interpret perimortem events. While the identification of food components of plant and animal origin has traditionally been conducted by macro- and microscopical approaches in case of incomplete digestion, molecular methods provide the potential to increase sensitivity and taxonomic resolution. In particular, DNA metabarcoding (PCR-amplification and next generation sequencing of complex DNA mixtures) has seen a rapid growth in the field of wildlife ecology to assess species’ diets from faecal and gastric samples. Despite clear advantages, molecular approaches have not yet been established in routine human forensics to investigate the last meal components of deceased persons. In this pilot study we applied for the first time a DNA metabarcoding approach to assess both plant and vertebrate components of 48 human stomach content samples taken during medicolegal autopsies. We obtained a final dataset with 34 vertebrate and 124 vegetal unique sequences, that were clustered to 9 and 33 operational taxonomic units (OTUs), respectively. Our results suggest that this approach can provide crucial information about circumstances preceding death, and open promising perspectives for biomedical dietary surveys based on digested food items found in the gastrointestinal tract.

Conducting research on diet-microbiome interactions: A review of current challenges, essential methodological principles, and recommendations for best practice in study design

Diet is one of the strongest modulators of the gut microbiome. However, the complexity of the interactions between diet and the microbial community emphasises the need for a robust study design and continued methodological development. This review aims to summarise considerations for conducting high-quality diet-microbiome research, outline key challenges unique to the field, and provide advice for addressing these in a practical manner useful to dietitians, microbiologists, gastroenterologists and other diet-microbiome researchers. Searches of databases and references from relevant articles were conducted using the primary search terms 'diet', 'diet intervention', 'dietary analysis', 'microbiome' and 'microbiota', alone or in combination. Publications were considered relevant if they addressed methods for diet and/or microbiome research, or were a human study relevant to diet-microbiome interactions. Best-practice design in diet-microbiome research requires appropriate consideration of the study population and careful choice of trial design and data collection methodology. Ongoing challenges include the collection of dietary data that accurately reflects intake at a timescale relevant to microbial community structure and metabolism, measurement of nutrients in foods pertinent to microbes, improving ability to measure and understand microbial metabolic and functional properties, adequately powering studies, and the considered analysis of multivariate compositional datasets. Collaboration across the disciplines of nutrition science and microbiology is crucial for high-quality diet-microbiome research. Improvements in our understanding of the interaction between nutrient intake and microbial metabolism, as well as continued methodological innovation, will facilitate development of effective evidence-based personalised dietary treatments.

Host variables confound gut microbiota studies of human disease

Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false positives is exacerbated by wide interindividual heterogeneity in microbiota composition¹, probably due to population-wide differences in human lifestyle and physiological variables² that exert differential effects on the microbiota. Here we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and also identify human lifestyle and physiological characteristics that, if not evenly matched between cases and controls, confound microbiota analyses to produce spurious microbial associations with human diseases. We identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy participants and participants with a disease and that can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed differences in the microbiota and the incidence of spurious associations. On this basis, we present a list of host variables that we recommend should be captured in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving the members of the gut microbiota that are truly associated with human disease.

A Guide to Diet-Microbiome Study Design

Intense recent interest in understanding how the human gut microbiome influences health has kindled a concomitant interest in linking dietary choices to microbiome variation. Diet is known to be a driver of microbiome variation, and yet the precise mechanisms by which certain dietary components modulate the microbiome, and by which the microbiome produces byproducts and secondary metabolites from dietary components, are not well-understood. Interestingly, despite the influence of diet on the gut microbiome, the majority of microbiome studies published to date contain little or no analysis of dietary intake. Although an increasing number of microbiome studies are now collecting some form of dietary data or even performing diet interventions, there are no clear standards in the microbiome field for how to collect diet data or how to design a diet-microbiome study. In this article, we review the current practices in diet-microbiome analysis and study design and make several recommendations for best practices to provoke broader discussion in the field. We recommend that microbiome studies include multiple consecutive microbiome samples per study timepoint or phase and multiple days of dietary history prior to each microbiome sample whenever feasible. We find evidence that direct effects of diet on the microbiome are likely to be observable within days, while the length of an intervention required for observing microbiome-mediated effects on the host phenotype or host biomarkers, depending on the outcome, may be much longer, on the order of weeks or months. Finally, recent studies demonstrating that diet-microbiome interactions are personalized suggest that diet-microbiome studies should either include longitudinal sampling within individuals to identify personalized responses, or should include an adequate number of participants spanning a range of microbiome types to identify generalized responses.

Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration

The human gut is inhabited by trillions of microorganisms composing a dynamic ecosystem implicated in health and disease. The composition of the gut microbiota is unique to each individual and tends to remain relatively stable throughout life, yet daily transient fluctuations are observed. Diet is a key modifiable factor influencing the composition of the gut microbiota, indicating the potential for therapeutic dietary strategies to manipulate microbial diversity, composition, and stability. While diet can induce a shift in the gut microbiota, these changes appear to be temporary. Whether prolonged dietary changes can induce permanent alterations in the gut microbiota is unknown, mainly due to a lack of long-term human dietary interventions, or long-term follow-ups of short-term dietary interventions. It is possible that habitual diets have a greater influence on the gut microbiota than acute dietary strategies. This review presents the current knowledge around the response of the gut microbiota to short-term and long-term dietary interventions and identifies major factors that contribute to microbiota response to diet. Overall, further research on long-term diets that include health and microbiome measures is required before clinical recommendations can be made for dietary modulation of the gut microbiota for health.

Molecular Reconstruction of the Diet in Human Stool Samples

Understanding dietary effects on the gut microbial composition is one of the key questions in human microbiome research. It is highly important to have reliable dietary data on the stool samples to unambiguously link the microbiome composition to food intake. Often, however, self-reported diet surveys have low accuracy and can be misleading. Thereby, additional molecular biology-based methods could help to revise the diet composition. The article by Reese et al. [A. T. Reese, T. R. Kartzinel, B. L. Petrone, P. J. Turnbaugh, et al., mSystems 4(5):e00458-19, 2019, https://doi.org/10.1128/mSystems.00458-19] in a recent issue of mSystems describes a DNA metabarcoding strategy targeting chloroplast DNA markers in stool samples from 11 human subjects consuming both controlled and freely selected diets. The aim of this study was to evaluate the efficiency of this molecular method in detecting plant remains in the sample compared to the written dietary records. This study displays an important first step in implementing molecular dietary reconstructions in stool microbiome studies which will finally help to increase the accuracy of dietary metadata.