YAMP: a containerized workflow enabling reproducibility in metagenomics research

Nextflow4MS-DIAL: A Reproducible Nextflow-Based Workflow for Liquid Chromatography-Mass Spectrometry Metabolomics Data Processing

Reproducibility in untargeted metabolomics data processing remains a significant challenge due to software limitations and the complex series of steps required. To address these issues, we developed Nextflow4MS-DIAL, a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing, validated with publicly available data from MetaboLights (MTBLS733). Nextflow4MS-DIAL automates LC-MS data processing to minimize human errors from manual data handling. The workflow supports software containerization, ensuring computational reproducibility and enabling collaborative research. Nextflow4MS-DIAL is compatible with any Unix-like system and supports multiple job schedulers, offering flexibility and ease of use. The Nextflow4MS-DIAL workflow is available under the permissive MIT license: https://github.com/Nextflow4Metabolomics/nextflow4ms-dial.

Treatment response in rheumatoid arthritis is predicted by the microbiome: a large observational study in UK DMARD-naive patients

OBJECTIVES

Disease-modifying antirheumatic drugs (DMARDs) are a first-line treatment in rheumatoid arthritis (RA). Treatment response to DMARDs is patient-specific, dose efficacy is difficult to predict and long-term results are variable. The gut microbiota are known to play a pivotal role in prodromal and early-disease RA, manifested by Prevotella spp. enrichment. The clinical response to therapy may be mediated by microbiota, and large-scale studies assessing the microbiome are few. This study assessed whether microbiome signals were associated with, and predictive of, patient response to DMARD treatment. Accurate early identification of those who will respond poorly to DMARD therapy would allow selection of alternative treatment (e.g. biologic therapy) and potentially improve patient outcome.

METHODS

A multicentre, longitudinal, observational study of stool- and saliva microbiome was performed in DMARD-naive, newly diagnosed RA patients during introduction of DMARD treatment. Clinical data and samples were collected at baseline (n = 144) in DMARD-naive patients and at six weeks (n = 117) and 12 weeks (n = 95) into DMARD therapy. Samples collected (n = 365 stool, n = 365 saliva) underwent shotgun sequencing. Disease activity measures were collected at each timepoint and minimal clinically important improvement determined.

RESULTS

In total, 26 stool microbes were found to decrease in those manifesting a minimal clinically important improvement. Prevotella spp. and Streptococcus spp. were the predominant taxa to decline following six weeks and 12 weeks of DMARDs, respectively. Furthermore, baseline microbiota of DMARD-naive patients were indicative of future response.

CONCLUSION

DMARDs appear to restore a perturbed microbiome to a eubiotic state. Moreover, microbiome status can be used to predict likelihood of patient response to DMARD.

Abnormalities in gut virome signatures linked with cognitive impairment in older adults

Multiple emerging lines of evidence indicate that the microbiome contributes to aging and cognitive health. However, the roles of distinct microbial components, such as viruses (virome) and their interactions with bacteria (bacteriome), as well as their metabolic pathways (metabolome) in relation to aging and cognitive function, remain poorly understood. Here, we present proof-of-concept results from a pilot study using datasets (n = 176) from the Microbiome in Aging Gut and Brain (MiaGB) consortium, demonstrating that the human virome signature significantly differs across the aging continuum (60s vs. 70s vs. 80+ years of age) in older adults. We observed that the predominant virome signature was enriched with bacteriophages, which change considerably with aging continuum. Analyses of interactions between phages and the host bacteriome suggest that lytic or temperate relationships change distinctly across the aging continuum, as well as cognitive impairment. Interestingly, the phage-bacteriome-metabolome interactions develop unique patterns that are distinctly linked to aging and cognitive dysfunction in older adults. The phage-bacteriome interactions affect bacterial metabolic pathways, potentially impacting older adults' health, including the risk of cognitive decline and dementia. Further comprehension of these studies could provide opportunities to target the microbiome by developing phage therapies to improve aging and brain health in older adults.

Red Cabbage Juice-Mediated Gut Microbiota Modulation Improves Intestinal Epithelial Homeostasis and Ameliorates Colitis

Gut microbiota plays a crucial role in inflammatory bowel diseases (IBD) and can potentially prevent IBD through microbial-derived metabolites, making it a promising therapeutic avenue. Recent evidence suggests that despite an unclear underlying mechanism, red cabbage juice (RCJ) alleviates Dextran Sodium Sulfate (DSS)-induced colitis in mice. Thus, the study aims to unravel the molecular mechanism by which RCJ modulates the gut microbiota to alleviate DSS-induced colitis in mice. Using C57BL/6J mice, we evaluated RCJ's protective role in DSS-induced colitis through two cycles of 3% DSS. Mice were daily gavaged with PBS or RCJ until the endpoint, and gut microbiota composition was analyzed via shotgun metagenomics. RCJ treatment significantly improved body weight (p ≤ 0.001), survival in mice (p < 0.001) and reduced disease activity index (DAI) scores. Further, RCJ improved colonic barrier integrity by enhancing the expression of protective colonic mucins (p < 0.001) and tight junction proteins (p ≤ 0.01) in RCJ + DSS-treated mice compared to the DSS group. Shotgun metagenomic analysis revealed an enrichment of short-chain fatty acids (SCFAs)-producing bacteria (p < 0.05), leading to increased Peroxisome Proliferator-Activated Receptor Gamma (PPAR-γ) activation (p ≤ 0.001). This, in turn, resulted in repression of the nuclear factor κB (NFκB) signaling pathway, causing decreased production of inflammatory cytokines and chemokines. Our study demonstrates colitis remission in a DSS-induced mouse model, showcasing RCJ as a potential modulator for gut microbiota and metabolites, with promising implications for IBD prevention and treatment.

Unique trans-kingdom microbiome structural and functional signatures predict cognitive decline in older adults

The prevalence of age-related cognitive disorders/dementia is increasing, and effective prevention and treatment interventions are lacking due to an incomplete understanding of aging neuropathophysiology. Emerging evidence suggests that abnormalities in gut microbiome are linked with age-related cognitive decline and getting acceptance as one of the pillars of the Geroscience hypothesis. However, the potential clinical importance of gut microbiome abnormalities in predicting the risk of cognitive decline in older adults is unclear. Till now the majority of clinical studies were done using 16S rRNA sequencing which only accounts for analyzing bacterial abundance, while lacking an understanding of other crucial microbial kingdoms, such as viruses, fungi, archaea, and the functional profiling of the microbiome community. Utilizing data and samples of older adults with mild cognitive impairment (MCI; n = 23) and cognitively healthy controls (n = 25). Our whole-genome metagenomic sequencing revealed that the gut of older adults with MCI harbors a less diverse microbiome with a specific increase in total viruses and a decrease in bacterial abundance compared with controls. The virome, bacteriome, and microbial metabolic signatures were significantly distinct in subjects with MCI versus controls. Selected bacteriome signatures show high predictive potential of cognitive dysfunction than virome signatures while combining virome and metabolic signatures with bacteriome boosts the prediction power. Altogether, the results from our pilot study indicate that trans-kingdom microbiome signatures are significantly distinct in MCI gut compared with controls and may have utility for predicting the risk of developing cognitive decline and dementia- debilitating public health problems in older adults.

A metagenomic catalog for exploring the plastizymes landscape covering taxa, genes, and proteins

There are significant environmental and health concerns associated with the current inefficient plastic recycling process. This study presents the first integrated reference catalog of plastic-contaminated environments obtained using an insilico workflow that could play a significant role in discovering new plastizymes. Here, we combined 66 whole metagenomic data from plastic-contaminated environment samples from four previously collected metagenome data with our new sample. In this study, an integrated plastic-contaminated environment gene, protein, taxa, and plastic degrading enzyme catalog (PDEC) was constructed. These catalogs contain 53,300,583 non-redundant genes and proteins, 691 metagenome-assembled genomes, and 136,654 plastizymes. Based on KEGG and eggNOG annotations, 42% of recognized genes lack annotations, indicating their functions remain elusive and warrant further investigation. Additionally, the PDEC catalog highlights hydrolases, peroxidases, and cutinases as the prevailing plastizymes. Ultimately, following multiple validation procedures, our effort focused on pinpointing enzymes that exhibited the highest similarity to the introduced plastizymes in terms of both sequence and three-dimensional structural aspects. This encompassed evaluating the linear composition of constituent units as well as the complex spatial conformation of the molecule. The resulting catalog is expected to improve the resolution of future multi-omics studies, providing new insights into plastic-pollution related research.

Red cabbage juice-mediated gut microbiota modulation improves intestinal epithelial homeostasis and ameliorates colitis

Gut microbiota plays a crucial role in inflammatory bowel disease (IBD) and has therapeutic benefits. Thus, targeting the gut microbiota is a promising therapeutic approach for IBD treatment. We recently found that red cabbage juice (RCJ) ameliorates dextran sulfate sodium (DSS)-induced colitis in mice. However, the underlying mechanisms remain unknown. The current study investigated the modulation of gut microbiota in response to treatment with RCJ to ameliorate the DSS colitis. The initial results demonstrated that mice treated with DSS + RCJ showed increased body weight and decreased diarrhea and blood in feces compared to the DSS alone group. RCJ ameliorated colitis by regulating the intestinal barrier function by reducing the number of apoptotic cells, improving colonic protective mucin, and increasing tight junction protein in RCJ + DSS groups compared to the DSS group. Short-gun metagenomic analysis revealed significant enrichment of short-chain fatty acid (SCFAs)-producing bacteria (Butyrivibrio, Ruminococcaceae, Acetatifactor muris, Rosburia Sp. CAG:303 , Dorea Sp. 5-2) increased PPAR-© activation, leading to repression of the nuclear factor κB (NFκB) signaling pathway, thus decreasing the production of crucial inflammatory cytokines and chemokines in the RCJ + DSS groups compared to the DSS group. Pathway abundance analysis showed an increased abundance of the SCFA pathway, reduced histidine degradation ( Bacteroides sartorii, and Bacteroides caecimuris ), and LCFA production in the RCJ+DSS treated group, suggesting the promotion of good colonic health. Furthermore, increased T-reg (FOXP3+) cells in the colon were due to SCFAs produced by the gut microbiota, which was corroborated by an increase in IL-10, a vital anti-inflammatory cytokine. Thus, our study provides the first evidence that RCJ ameliorates colonic inflammation by modulating the gut microbiota.

Genetic and gut microbiome determinants of SCFA circulating and fecal levels, postprandial responses and links to chronic and acute inflammation

Short-chain fatty acids (SCFA) are involved in immune system and inflammatory responses. We comprehensively assessed the host genetic and gut microbial contribution to a panel of eight serum and stool SCFAs in two cohorts (TwinsUK, n = 2507; ZOE PREDICT-1, n = 328), examined their postprandial changes and explored their links with chronic and acute inflammatory responses in healthy individuals and trauma patients. We report low concordance between circulating and fecal SCFAs, significant postprandial changes in most circulating SCFAs, and a heritable genetic component (average h2: serum = 14%(SD = 14%); stool = 12%(SD = 6%)). Furthermore, we find that gut microbiome can accurately predict their fecal levels (AUC>0.71) while presenting weaker associations with serum. Finally, we report different correlation patterns with inflammatory markers depending on the type of inflammatory response (chronic or acute trauma). Our results illustrate the breadth of the physiological relevance of SCFAs on human inflammatory and metabolic responses highlighting the need for a deeper understanding of this important class of molecules.

Gut metagenome profile of the Nunavik Inuit youth is distinct from industrial and non-industrial counterparts

Comparative metagenomics studies have highlighted differences in microbiome community structure among human populations over diverse lifestyles and environments. With their unique environmental and historical backgrounds, Nunavik Inuit have a distinctive gut microbiome with undocumented health-related implications. Using shotgun metagenomics, we explored the taxonomic and functional structure of the gut microbiome from 275 Nunavik Inuit ranging from 16 to 30-year-old. Whole-metagenome analyses revealed that Nunavik Inuit youths have a more diverse microbiome than their non-industrialized and industrialized counterparts. A comparison of k-mer content illustrated the uniqueness of the Nunavik gut microbiome. Short-chain fatty acids producing species, and carbohydrates degradation pathways dominated Inuit metagenomes. We identified a taxonomic and functional signature unique to the Nunavik gut microbiome contrasting with other populations using a random forest classifier. Here, we show that the Nunavik Inuit gut microbiome exhibits high diversity and a distinct community structure.

Analysis and Interpretation of metagenomics data: an approach

Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8-10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process.

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome

BACKGROUND

Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits.

RESULTS

According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17 ± 0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18 ± 11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41 ± 0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30 ± 0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed than an increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation.

CONCLUSIONS

Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).

Physiologic colonic uptake of 18F-FDG on PET/CT is associated with clinical response and gut microbiome composition in patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICI) represent the backbone treatment for advanced non-small cell lung cancer (NSCLC). Emerging data suggest that increased gut microbiome diversity is associated with favorable response to ICI and that antibiotic-induced dysbiosis is associated with deleterious outcomes. 18F-FDG physiologic colonic uptake on PET/CT increases following treatment with antibiotics (ATB) and could act as a surrogate marker for microbiome composition and predict prognosis. The aim of this study was to determine if 18F-FDG physiologic colonic uptake prior to ICI initiation correlates with gut microbiome profiling and clinical outcomes in patients with advanced NSCLC.

METHODS

Seventy-one patients with advanced NSCLC who underwent a PET/CT prior to ICI were identified. Blinded colonic contouring was performed for each colon segment and patients were stratified according to the median of the average colon SUVmax as well as for each segment in low vs. high SUVmax groups. Response rate, progression-free survival (PFS), and overall survival (OS) were compared in the low vs. high SUVmax groups. Gut microbiome composition was analyzed for 23 patients using metagenomics sequencing.

RESULTS

The high colon SUVmax group had a higher proportion of non-responders (p = 0.033) and significantly shorter PFS (4.1 vs. 11.3 months, HR 1.94, 95% CI 1.11-3.41, p = 0.005). High caecum SUVmax correlated with numerically shorter OS (10.8 vs. 27.6 months, HR 1.85, 95% CI 0.97-3.53, p = 0.058). Metagenomics sequencing revealed distinctive microbiome populations in each group. Patients with low caecum SUVmax had higher microbiome diversity (p = 0.046) and were enriched with Bifidobacteriaceae, Lachnospiraceae, and Bacteroidaceae.

CONCLUSIONS

Lower colon physiologic 18F-FDG uptake on PET/CT prior to ICI initiation was associated with better clinical outcomes and higher gut microbiome diversity in patients with advanced NSCLC. Here, we propose that 18F-FDG physiologic colonic uptake on PET/CT could serve as a potential novel marker of gut microbiome composition and may predict clinical outcomes in this population.

Applying artificial intelligence in the microbiome for gastrointestinal diseases: A review

For a long time, gut bacteria have been recognized for their important roles in the occurrence and progression of gastrointestinal diseases like colorectal cancer, and the ever-increasing amounts of microbiome data combined with other high-quality clinical and imaging datasets are leading the study of gastrointestinal diseases into an era of biomedical big data. The "omics" technologies used for microbiome analysis continuously evolve, and the machine learning or artificial intelligence technologies are key to extract the relevant information from microbiome data. This review intends to provide a focused summary of recent research and applications of microbiome big data and to discuss the use of artificial intelligence to combat gastrointestinal diseases.

MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline

BACKGROUND

Microbial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community's constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems.

RESULTS

Here we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality.

CONCLUSIONS

MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.

Interplay between the human gut microbiome and host metabolism

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.

Conducting metagenomic studies in microbiology and clinical research

Owing to the increased cost-effectiveness of high-throughput technologies, the number of studies focusing on the human microbiome and its connections to human health and disease has recently surged. However, best practices in microbiology and clinical research have yet to be clearly established. Here, we present an overview of the challenges and opportunities involved in conducting a metagenomic study, with a particular focus on data processing and analytical methods.

YAMP: a containerized workflow enabling reproducibility in metagenomics research

YAMP ("Yet Another Metagenomics Pipeline") is a user-friendly workflow that enables the analysis of whole shotgun metagenomic data while using containerization to ensure computational reproducibility and facilitate collaborative research. YAMP can be executed on any UNIX-like system and offers seamless support for multiple job schedulers as well as for the Amazon AWS cloud. Although YAMP was developed to be ready to use by nonexperts, bioinformaticians will appreciate its flexibility, modularization, and simple customization.