Conducting a microbiome study.

Human microbiome research is an actively developing area of inquiry, with ramifications for our lifestyles, our interactions with microbes, and how we treat disease. Advances depend on carefully executed, controlled, and reproducible studies. Here, we provide a Primer for researchers from diverse disciplines interested in conducting microbiome research. We discuss factors to be considered in the design, execution, and data analysis of microbiome studies. These recommendations should help researchers to enter and contribute to this rapidly developing field.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the USA.

BACKGROUND: Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first three years of life and compared this interpolation to several common interpolation methods and pediatric growth models. METHODS: We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N = 97) then in a large, outpatient, pediatric sample (N = 14,695). RESULTS: The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22 kg [IQR:0.19; 90% < 0.43]; girls: 0.20 kg [IQR:0.17; 90% < 0.39]) and height (median RMSE: boys: 0.93 cm [IQR:0.53; 90% < 1.0]; girls: 0.91 cm [IQR:0.50;90% < 1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit. Interpolation with this equation had comparable (for weight) or lower (for height) mean RMSE compared to the best performing alternative models. CONCLUSIONS: A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis.

OBJECTIVE: Gestational diabetes mellitus (GDM) is a condition in which women without diabetes are diagnosed with glucose intolerance during pregnancy, typically in the second or third trimester. Early diagnosis, along with a better understanding of its pathophysiology during the first trimester of pregnancy, may be effective in reducing incidence and associated short-term and long-term morbidities. DESIGN: We comprehensively profiled the gut microbiome, metabolome, inflammatory cytokines, nutrition and clinical records of 394 women during the first trimester of pregnancy, before GDM diagnosis. We then built a model that can predict GDM onset weeks before it is typically diagnosed. Further, we demonstrated the role of the microbiome in disease using faecal microbiota transplant (FMT) of first trimester samples from pregnant women across three unique cohorts. RESULTS: We found elevated levels of proinflammatory cytokines in women who later developed GDM, decreased faecal short-chain fatty acids and altered microbiome. We next confirmed that differences in GDM-associated microbial composition during the first trimester drove inflammation and insulin resistance more than 10 weeks prior to GDM diagnosis using FMT experiments. Following these observations, we used a machine learning approach to predict GDM based on first trimester clinical, microbial and inflammatory markers with high accuracy. CONCLUSION: GDM onset can be identified in the first trimester of pregnancy, earlier than currently accepted. Furthermore, the gut microbiome appears to play a role in inflammation-induced GDM pathogenesis, with interleukin-6 as a potential contributor to pathogenesis. Potential GDM markers, including microbiota, can serve as targets for early diagnostics and therapeutic intervention leading to prevention.

Randomized Controlled-Feeding Study of Dietary Emulsifier Carboxymethylcellulose Reveals Detrimental Impacts on the Gut Microbiota and Metabolome.

BACKGROUND & AIMS: Epidemiologic and murine studies suggest that dietary emulsifiers promote development of diseases associated with microbiota dysbiosis. Although the detrimental impact of these compounds on the intestinal microbiota and intestinal health have been demonstrated in animal and in vitro models, impact of these food additives in healthy humans remains poorly characterized. METHODS: To examine this notion in humans, we performed a double-blind controlled-feeding study of the ubiquitous synthetic emulsifier carboxymethylcellulose (CMC) in which healthy adults consumed only emulsifier-free diets (n = 9) or an identical diet enriched with 15 g per day of CMC (n = 7) for 11 days. RESULTS: Relative to control subjects, CMC consumption modestly increased postprandial abdominal discomfort and perturbed gut microbiota composition in a way that reduced its diversity. Moreover, CMC-fed subjects exhibited changes in the fecal metabolome, particularly reductions in short-chain fatty acids and free amino acids. Furthermore, we identified 2 subjects consuming CMC who exhibited increased microbiota encroachment into the normally sterile inner mucus layer, a central feature of gut inflammation, as well as stark alterations in microbiota composition. CONCLUSIONS: These results support the notion that the broad use of CMC in processed foods may be contributing to increased prevalence of an array of chronic inflammatory diseases by altering the gut microbiome and metabolome (ClinicalTrials.gov, number NCT03440229).

Large-scale replicated field study of maize rhizosphere identifies heritable microbes.

Soil microbes that colonize plant roots and are responsive to differences in plant genotype remain to be ascertained for agronomically important crops. From a very large-scale longitudinal field study of 27 maize inbred lines planted in three fields, with partial replication 5 y later, we identify root-associated microbiota exhibiting reproducible associations with plant genotype. Analysis of 4,866 samples identified 143 operational taxonomic units (OTUs) whose variation in relative abundances across the samples was significantly regulated by plant genotype, and included five of seven core OTUs present in all samples. Plant genetic effects were significant amid the large effects of plant age on the rhizosphere microbiome, regardless of the specific community of each field, and despite microbiome responses to climate events. Seasonal patterns showed that the plant root microbiome is locally seeded, changes with plant growth, and responds to weather events. However, against this background of variation, specific taxa responded to differences in host genotype. If shown to have beneficial functions, microbes may be considered candidate traits for selective breeding.

Experimental and analytical tools for studying the human microbiome.

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.

Accurate Estimation of Fungal Diversity and Abundance through Improved Lineage-Specific Primers Optimized for Illumina Amplicon Sequencing.

While high-throughput sequencing methods are revolutionizing fungal ecology, recovering accurate estimates of species richness and abundance has proven elusive. We sought to design internal transcribed spacer (ITS) primers and an Illumina protocol that would maximize coverage of the kingdom Fungi while minimizing nontarget eukaryotes. We inspected alignments of the 5.8S and large subunit (LSU) ribosomal genes and evaluated potential primers using PrimerProspector. We tested the resulting primers using tiered-abundance mock communities and five previously characterized soil samples. We recovered operational taxonomic units (OTUs) belonging to all 8 members in both mock communities, despite DNA abundances spanning 3 orders of magnitude. The expected and observed read counts were strongly correlated (r = 0.94 to 0.97). However, several taxa were consistently over- or underrepresented, likely due to variation in rRNA gene copy numbers. The Illumina data resulted in clustering of soil samples identical to that obtained with Sanger sequence clone library data using different primers. Furthermore, the two methods produced distance matrices with a Mantel correlation of 0.92. Nonfungal sequences comprised less than 0.5% of the soil data set, with most attributable to vascular plants. Our results suggest that high-throughput methods can produce fairly accurate estimates of fungal abundances in complex communities. Further improvements might be achieved through corrections for rRNA copy number and utilization of standardized mock communities. IMPORTANCE: Fungi play numerous important roles in the environment. Improvements in sequencing methods are providing revolutionary insights into fungal biodiversity, yet accurate estimates of the number of fungal species (i.e., richness) and their relative abundances in an environmental sample (e.g., soil, roots, water, etc.) remain difficult to obtain. We present improved methods for high-throughput Illumina sequencing of the species-diagnostic fungal ribosomal marker gene that improve the accuracy of richness and abundance estimates. The improvements include new PCR primers and library preparation, validation using a known mock community, and bioinformatic parameter tuning.

Nurture trumps nature in a longitudinal survey of salivary bacterial communities in twins from early adolescence to early adulthood.

Variation in the composition of the human oral microbiome in health and disease has been observed. We have characterized inter- and intra-individual variation of microbial communities of 107 individuals in one of the largest cohorts to date (264 saliva samples), using culture-independent 16S rRNA pyrosequencing. We examined the salivary microbiome in up to three time-points during 10 yr spanning adolescence, and determined the influence of human genotype, gender, age, and weight class. Participants, including 27 monozygotic and 18 dizygotic twin pairs, were sampled mainly at ages 12-13, 17-18, and 22-24, with a few sampled as early as 8 yr of age. In contrast to gut or skin microbiomes, there is a core genus-level salivary microbiome. Individuals are more similar to themselves and their co-twins in the 12-17 and in the 17-22 cohorts than to the whole sample population, but not over the 10 yr from 12 to 22; and monozygotic twin pairs are statistically not more similar than dizygotic twin pairs. The data are most consistent with shared environment serving as the main determinant of microbial populations. Twins resemble each other more closely than the whole population at all time-points, but become less similar to each other when they age and no longer cohabit. Several organisms have age-specific abundance profiles, including members of the genera Veillonella, Actinomyces, and Streptococcus. There is no clear effect of weight class and gender. The results of this work will provide a basis to further study oral microbes and human health.

Improved HF183 quantitative real-time PCR assay for characterization of human fecal pollution in ambient surface water samples.

Quantitative real-time PCR (qPCR) assays that target the human-associated HF183 bacterial cluster within members of the genus Bacteroides are among the most widely used methods for the characterization of human fecal pollution in ambient surface waters. In this study, we show that a current TaqMan HF183 qPCR assay (HF183/BFDrev) routinely forms nonspecific amplification products and introduce a modified TaqMan assay (HF183/BacR287) that alleviates this problem. The performance of each qPCR assay was compared in head-to-head experiments investigating limits of detection, analytical precision, predicted hybridization to 16S rRNA gene sequences from a reference database, and relative marker concentrations in fecal and sewage samples. The performance of the modified HF183/BacR287 assay is equal to or improves upon that of the original HF183/BFDrev assay. In addition, a qPCR chemistry designed to combat amplification inhibition and a multiplexed internal amplification control are included. In light of the expanding use of PCR-based methods that rely on the detection of extremely low concentrations of DNA template, such as qPCR and digital PCR, the new TaqMan HF183/BacR287 assay should provide more accurate estimations of human-derived fecal contaminants in ambient surface waters.

Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.

Seasonal restructuring of the ground squirrel gut microbiota over the annual hibernation cycle.

Many hibernating mammals suspend food intake during winter, relying solely on stored lipids to fuel metabolism. Winter fasting in these species eliminates a major source of degradable substrates to support growth of gut microbes, which may affect microbial community structure and host-microbial interactions. We explored the effect of the annual hibernation cycle on gut microbiotas using deep sequencing of 16S rRNA genes from ground squirrel cecal contents. Squirrel microbiotas were dominated by members of the phyla Bacteroidetes, Firmicutes, and Verrucomicrobia. UniFrac analysis showed that microbiotas clustered strongly by season, and maternal influences, diet history, host age, and host body temperature had minimal effects. Phylogenetic diversity and numbers of operational taxonomic units were lowest in late winter and highest in the spring after a 2-wk period of refeeding. Hibernation increased relative abundance of Bacteroidetes and Verrucomicrobia, phyla that contain species capable of surviving on host-derived substrates such as mucins, and reduced relative abundance of Firmicutes, many of which prefer dietary polysaccharides. Hibernation reduced cecal short-chain fatty acid and ammonia concentrations, and increased and decreased concentrations of acetate and butyrate, respectively. These results indicate that the ground squirrel microbiota is restructured each year in a manner that reflects differences in microbial preferences for dietary vs. host-derived substrates, and thus the competitive abilities of different taxa to survive in the altered environment in the hibernator gut.

Interleukin-1ß (IL-1ß) promotes susceptibility of Toll-like receptor 5 (TLR5) deficient mice to colitis.

BACKGROUND: The extent to which numerous strains of genetically engineered mice, including mice lacking Toll-like receptor 5 (T5KO), display colitis is environment dependent. Gut microbiota underlie much of the variation in phenotype. Accordingly, embryonic rederivation of T5KO mice ameliorated their spontaneous colitis despite only partially correcting elevated proinflammatory gene expression. It was postulated that endogenous anti-inflammatory pathways mediated the absence of overt inflammation in these mice when their gut microbiota were reset. Consequently, it was hypothesised that neutralisation of the anti-inflammatory cytokine interleukin 10 (IL-10) might induce uniform colitis in T5KO mice, and thus provide a practical means to study mechanisms underlying their inflammation. METHODS: Two distinct strains of non-colitic T5KO mice, as well as mice lacking MyD88, Toll-like receptor 4 (TLR4), IL-1 receptor (IL-1R) and various double knockouts (DKOs) were treated weekly for 4 weeks with 1 mg/mouse of IL-10 receptor neutralising antibody (IL-10R mAb) and colitis assayed 1 week later. The composition of the caecal microbiota was determined by 454 pyrosequencing of 16S rRNA genes. RESULTS: Anti-IL-10R mAb treatment led to severe uniform intestinal inflammation in both strains of T5KO mice. Such neutralisation of IL-10 signalling did not cause colitis in wild-type littermates nor mice lacking TLR4, MyD88 or IL-1R. The susceptibility of T5KO mice to this colitis model was not rescued by absence of TLR4 in that T4/T5 DKO mice displayed severe colitis in response to anti-IL-10R mAb treatment. IL-1ß signalling was crucial for this colitis model in that IL-1R/T5 DKOs were completely protected from colitis in response to IL-10R mAb treatment. Lastly, it was observed that blockade of IL-10R function was associated with changes in the composition of gut microbiota, which were observed in mice that were susceptible and resistant to IL-10R mAb-induced colitis. CONCLUSION: Regardless of whether they harbour a colitogenic microbiota, loss of TLR5 predisposes mice to colitis triggered by immune dysregulation via an IL-1ß-dependent pathway.

Fabrication and errors in the bibliographic citations generated by ChatGPT.

Although chatbots such as ChatGPT can facilitate cost-effective text generation and editing, factually incorrect responses (hallucinations) limit their utility. This study evaluates one particular type of hallucination: fabricated bibliographic citations that do not represent actual scholarly works. We used ChatGPT-3.5 and ChatGPT-4 to produce short literature reviews on 42 multidisciplinary topics, compiling data on the 636 bibliographic citations (references) found in the 84 papers. We then searched multiple databases and websites to determine the prevalence of fabricated citations, to identify errors in the citations to non-fabricated papers, and to evaluate adherence to APA citation format. Within this set of documents, 55% of the GPT-3.5 citations but just 18% of the GPT-4 citations are fabricated. Likewise, 43% of the real (non-fabricated) GPT-3.5 citations but just 24% of the real GPT-4 citations include substantive citation errors. Although GPT-4 is a major improvement over GPT-3.5, problems remain.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the US.

Background and Objectives: Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated this equation could be used to interpolate missing growth data in children in the first three years of life. Methods: We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N=97) then in a large, outpatient, pediatric sample (N=14,695). Results: The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22kg [IQR:0.19; 90%<0.43]; girls: 0.20kg [IQR:0.17; 90%<0.39]) and height (median RMSE: boys: 0.93cm [IQR:0.53; 90%<1.0]; girls: 0.91cm [IQR:0.50;90%<1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit. Conclusions: A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

Game Changers: A participatory action research project for/with students with disabilities in school sport settings.

Introduction: Although school communities may be required to provide physical education opportunities for all students-including for those with disabilities-the same is not generally true with respect to school sport (i.e., participation in interscholastic or intramural sport programs). Hence, opportunities for inclusive school sport participation are consequently limited. Recognizing the need for continued attention and action in this area, we recently developed and piloted Game Changers-a participatory action research project. Together, 27 students with various cognitive and/or intellectual disabilities (i.e., student-participants), their schools' six physical education teachers and learning support teachers (i.e., champion-participants), four university researchers (i.e., researcher-participants), and two community partners [i.e., Physical and Health Education (PHE) Canada, Special Olympics Nova Scotia] engaged in the Game Changers project with three idealized goals: (a) to bring to the fore para/adapted/inclusive sport opportunities for all students; (b) to provide an empowering opportunity for students with disabilities to participate, make choices, and act as leaders in the development of sport programming; and (c) to engage youth with disabilities in sport as participants, leaders, mentors, and role models. Methods: Utilizing a mixed-methods design, data were collected from a variety of sources before the implementation of the Game Changers program, during its implementation, and once it was complete. These four data sources included the following: pre- and post-program survey for student-participants, pre- and post-program focus group interviews for student-participants, pre- and post-program focus group interviews for champion-participants, and school/sport observations. Results: The first cycle of this participatory action research project has yielded positive and informative findings. Strictly positive findings, among others, relate to the following: improving upon students' perceived competence and autonomy, inviting student voice, identifying and responding to sport participation barriers, and creating genuine sport opportunities within school settings. More undesirable yet informative findings, among others, relate to the following: unachieved intrinsic motivation and belonging, (un)sustainability of sport programs without "interventions" like Game Changers, recreation/leisure as "substitutes" for sport, and a continued want for authentic leadership and mentorship opportunities. Discussion: With these findings, we offer insights for future iterations of Game Changers (and programs like it) in similar school communities.

An approach to assess potential environmental mercury release, food web bioaccumulation, and human dietary methylmercury uptake from decommissioning offshore oil and gas infrastructure.

Subsea pipelines carrying well fluids from hydrocarbon fields accumulate mercury. If the pipelines (after cleaning and flushing) are abandoned in situ, their degradation may release residual mercury into the environment. To justify pipeline abandonment, decommissioning plans include environmental risk assessments to determine the potential risk of environmental mercury. These risks are informed by environmental quality guideline values (EQGVs) governing concentrations in sediment or water above which mercury toxicity may occur. However, these guidelines may not consider e.g., the bioaccumulation potential of methylated mercury. Therefore, EQGVs may not protect humans from exposure if applied as the sole basis for risk assessments. This paper outlines a process to assess the EQGVs' protectiveness from mercury bioaccumulation, providing preliminary insights to questions including how to (1) determine pipeline threshold concentrations, (2) model marine mercury bioaccumulation, and (3) determine exceedance of the methylmercury tolerable weekly intake (TWI) for humans. The approach is demonstrated with a generic example using simplifications to describe mercury behaviour and a model food web. In this example, release scenarios equivalent to the EQGVs resulted in increased marine organism mercury tissue concentrations by 0-33 %, with human dietary methylmercury intake increasing 0-21 %. This suggests that existing guidelines may not be protective of biomagnification in all circumstances. The outlined approach could inform environmental risk assessments for asset-specific release scenarios but must be parameterised to reflect local environmental conditions when tailored to local factors.

Psyllium Fiber Protects Against Colitis Via Activation of Bile Acid Sensor Farnesoid X Receptor.

BACKGROUND & AIMS: Fiber-rich foods promote health, but mechanisms by which they do so remain poorly defined. Screening fiber types, in mice, revealed psyllium had unique ability to ameliorate 2 chronic inflammatory states, namely, metabolic syndrome and colitis. We sought to determine the mechanism of action of the latter. METHODS: Mice were fed grain-based chow, which is naturally rich in fiber or compositionally defined diets enriched with semi-purified fibers. Mice were studied basally and in models of chemical-induced and T-cell transfer colitis. RESULTS: Relative to all diets tested, mice consuming psyllium-enriched compositionally defined diets were markedly protected against both dextran sulfate sodium- and T-cell transfer-induced colitis, as revealed by clinical-type, histopathologic, morphologic, and immunologic parameters. Such protection associated with stark basal changes in the gut microbiome but was independent of fermentation and, moreover, maintained in mice harboring a minimal microbiota (ie, Altered Schaedler Flora). Transcriptomic analysis revealed psyllium induced expression of genes mediating bile acids (BA) secretion, suggesting that psyllium's known ability to bind BA might contribute to its ability to prevent colitis. As expected, psyllium resulted in elevated level of fecal BA, reflecting their removal from enterohepatic circulation but, in stark contrast to the BA sequestrant cholestyramine, increased serum BA levels. Moreover, the use of BA mimetics that activate the farnesoid X receptor (FXR), as well as the use of FXR-knockout mice, suggested that activation of FXR plays a central role in psyllium's protection against colitis. CONCLUSIONS: Psyllium protects against colitis via altering BA metabolism resulting in activation of FXR, which suppresses pro-inflammatory signaling.

Longitudinal comparison of the developing gut virome in infants and their mothers.

The human gut virome and its early life development are poorly understood. Prior studies have captured single-point assessments with the evolution of the infant virome remaining largely unexplored. We performed viral metagenomic sequencing on stool samples collected longitudinally from a cohort of 53 infants from age 2 weeks to 3 years (80.7 billion reads), and from their mothers (9.8 billion reads) to examine and compare viromes. The asymptomatic infant virome consisted of bacteriophages, nonhuman dietary/environmental viruses, and human-host viruses, predominantly picornaviruses. In contrast, human-host viruses were largely absent from the maternal virome. Previously undescribed, sequence-divergent vertebrate viruses were detected in the maternal but not infant virome. As infants aged, the phage component evolved to resemble the maternal virome, but by age 3, the human-host component remained dissimilar from the maternal virome. Thus, early life virome development is determined predominantly by dietary, infectious, and environmental factors rather than direct maternal acquisition.

PrimerProspector: de novo design and taxonomic analysis of barcoded polymerase chain reaction primers.

MOTIVATION: PCR amplification of DNA is a key preliminary step in many applications of high-throughput sequencing technologies, yet design of novel barcoded primers and taxonomic analysis of novel or existing primers remains a challenging task. RESULTS: PrimerProspector is an open-source software package that allows researchers to develop new primers from collections of sequences and to evaluate existing primers in the context of taxonomic data. AVAILABILITY: PrimerProspector is open-source software available at http://pprospector.sourceforge.net CONTACT: rob.knight@colorado.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Investigating the dynamics of methylmercury bioaccumulation in the Beaufort Sea shelf food web: a modeling perspective.

High levels of methylmercury (MeHg) have been reported in Arctic marine biota, posing health risks to wildlife and human beings. Although MeHg concentrations of some Arctic species have been monitored for decades, the key environmental and ecological factors driving temporal trends of MeHg are largely unclear. We develop an ecosystem-based MeHg bioaccumulation model for the Beaufort Sea shelf (BSS) using the Ecotracer module of Ecopath with Ecosim, and apply the model to explore how MeHg toxicokinetics and food web trophodynamics affect bioaccumulation in the BSS food web. We show that a food web model with complex trophodynamics and relatively simple MeHg model parametrization can capture the observed biomagnification pattern of the BSS. While both benthic and pelagic production are important for transferring MeHg to fish and marine mammals, simulations suggest that benthic organisms are primarily responsible for driving the high trophic magnification factor in the BSS. We illustrate ways of combining empirical observations and modelling experiments to generate hypotheses about factors affecting food web bioaccumulation, including the MeHg elimination rate, trophodynamics, and species migration behavior. The results indicate that population dynamics rather than MeHg elimination may determine population-wide concentrations for fish and lower trophic level organisms, and cause large differences in concentrations between species at similar trophic levels. This research presents a new tool and lays the groundwork for future research to assess the pathways of global environmental changes in MeHg bioaccumulation in Arctic ecosystems in the past and the future.