Evaluation of the Microba Community Profiler for Taxonomic Profiling of Metagenomic Datasets From the Human Gut Microbiome

Hormonal birth control is associated with altered gut microbiota β-diversity in physically active females across the menstrual cycle: a pilot trial

Understanding changes to gut microbiota composition in response to hormonal birth control (HBC) may provide insight into the microbial mechanisms underlying the metabolic effects of HBC, for example, altered short-chain fatty acid (SCFA) production. Athletes' unique physiological demands may interact with these microbial mechanisms in distinct ways; however, there is limited research on HBC and gut microbiota diversity and composition across different menstrual cycle phases in physically active females. A pilot cohort of physically active females using HBC (oral contraceptives, hormone-based intrauterine devices, or arm implants) and a control group not using HBC (n = 12 per group; 22 ± 2 yr, 24 ± 4 kg/m2 vs. 22 ± 4 yr, 23 ± 4 kg/m2; Ps ≥ 0.496) provided fecal samples alongside self-reported menstrual phase and circulating sex hormones. α-diversity (microbial richness and evenness) was assessed using the Shannon index whereas β-diversity (microbial composition differences) was analyzed using PERMANOVA based on Bray-Curtis dissimilarity. Circulating estrogen and luteinizing hormone increased from early (days 1-5) to mid-cycle (days 12-17) in both groups (time effect Ps ≤ 0.01), with greater changes in Control (Ps ≤ 0.046) than HBC (Ps ≥ 0.231). Although no menstrual phase effect was observed on either diversity measure (Ps ≥ 0.473), β-diversity differed between Control and HBC groups (P = 0.015), reflecting distinct gut microbiota profiles irrespective of menstrual phase. Seven taxa linked to SCFA production were less abundant in the HBC group (unadjusted Ps ≤ 0.046), though significance was lost after adjusting for multiple comparisons. These findings suggest that in physically active females, hormonal contraception influences gut microbial composition, which may have downstream effects on metabolism and performance.NEW & NOTEWORTHY This study is the first to investigate interactions between hormonal contraception and the gut microbiota in a cohort of physically active young females across the menstrual cycle. Our findings suggest that hormonal contraception may influence gut microbiota composition, potentially through a reduced relative abundance of short-chain fatty acid-producing taxa. Experimental studies are needed to confirm these associations and explore their potential implications for metabolism, health, and performance.

A decade of advances in human gut microbiome-derived biotherapeutics

Microbiome science has evolved rapidly in the past decade, with high-profile publications suggesting that the gut microbiome is a causal determinant of human health. This has led to the emergence of microbiome-focused biotechnology companies and pharmaceutical company investment in the research and development of gut-derived therapeutics. Despite the early promise of this field, the first generation of microbiome-derived therapeutics (faecal microbiota products) have only recently been approved for clinical use. Next-generation therapies based on readily culturable and as-yet-unculturable colonic bacterial species (with the latter estimated to comprise 63% of all detected species) have not yet progressed to pivotal phase 3 trials. This reflects the many challenges involved in developing a new class of drugs in an evolving field. Here we discuss the evolution of the live biotherapeutics field over the past decade, from the development of first-generation products to the emergence of rationally designed second- and third-generation live biotherapeutics. Finally, we present our outlook for the future of this field.

Predictive biomarkers of performance under stress: a two-phase study protocol to develop a wearable monitoring system

Understanding and predicting individual responses to common stressors is essential for optimising performance in high-stress environments. This article outlines a protocol for a study to identify biomarkers that predict performance under heat, musculoskeletal, psychosocial and sleep stress, for future integration into a wearable sensor system. In Phase I, healthy adults aged between 18 and 45 years (n=104) will be recruited for an intervention trial that involves exposure to one of the four stressors: heat, musculoskeletal, psychosocial or sleep deprivation. Biomarkers will be identified from molecular markers in biological samples (eg, blood, saliva, sweat and stool), physiological measures and psychological assessments to predict cognitive and physical performance under stress. A within-subjects design will determine changes in molecular and non-molecular markers before and after stress exposure. In Phase II, we will use the biomarkers identified in Phase I to develop a wearable sensor to predict and monitor human performance under stress.

Metagenomics: a new frontier for routine pathology testing of gastrointestinal pathogens

BACKGROUND

Accurate and comprehensive identification of enteropathogens, causing infectious gastroenteritis, is essential for optimal patient treatment and effective isolation processes in health care systems. Traditional diagnostic techniques are well established and optimised in low-cost formats. However, thorough testing for a wider range of causal agents is time consuming and remains limited to a subset of pathogenic organisms. Metagenomic next-generation sequencing (mNGS) allows the identification of all pathogens in a sample in a single test, without a reliance on culture or introduction of target selection bias. This study aims to determine the ability to routinely apply mNGS testing, in comparison to traditional culture or polymerase chain reaction (PCR) based tests, for the identification of causal pathogens for gastrointestinal infections.

RESULTS

The performance of mNGS, PCR and microscopy, culture and sensitivity (MCS) assays was established using 2,619 prospectively collected faecal samples from patients with symptomology indicative of infectious gastroenteritiss. Commonly experienced pathogens including Aeromonas spp, Campylobacter spp, Salmonella spp and Giardia spp, in single and co-infected patients, were used to establish test outcomes. When testing for these organisms, using the combined result from either or both PCR and MCS testing as the comparator, the mNGS assay had clinically acceptable sensitivity (89.2-100%). Further, the mNGS assay detected 14 additional enteropathogens, that were either not detected or not tested, by initial PCR/MCS testing.

CONCLUSIONS

The advantage of mNGS compared to other syndromic testing systems is the broad range of detectable targets and the ability to interrogate samples without clinician informed or assay specific bias. With the development of newer sequencing assays, it is now feasible to test for a wide range of target organisms in a sample using a single mNGS test. Overall, the mNGS based approach enabled pathogen detection that was comparable to conventional diagnostics and was shown to have the potential to be extended for the detection of many pathogens and genes of clinical interest. In conclusion, the mNGS assay offers an easy, sample to answer workflow with rapid detection of enteropathogens and has the potential to improve diagnosis, therapy and infection control precautions.

Impact of simulation and reference catalogues on the evaluation of taxonomic profiling pipelines

Microbiome profiling tools rely on reference catalogues, which significantly affect their performance. Comparing them is, however, challenging, mainly due to differences in their native catalogues. In this study, we present a novel standardized benchmarking framework that makes such comparisons more accurate. We decided not to customize databases but to translate results to a common reference to use the tools with their native environment. Specifically, we conducted two realistic simulations of gut microbiome samples, each based on a specific taxonomic profiler, and used two different taxonomic references to project their results, namely the Genome Taxonomy Database and the Unified Human Gastrointestinal Genome. To demonstrate the importance of using such a framework, we evaluated four established profilers as well as the impact of the simulations and that of the common taxonomic references on the perceived performance of these profilers. Finally, we provide guidelines to enhance future profiler comparisons for human microbiome ecosystems: (i) use or create realistic simulations tailored to your biological context (BC), (ii) identify a common feature space suited to your BC and independent of the catalogues used by the profilers and (iii) apply a comprehensive set of metrics covering accuracy (sensitivity/precision), overall representativity (richness/Shannon) and quantification (UniFrac and/or Aitchison distance).

Does Improving Depression Symptoms in Young Adults With Inflammatory Bowel Disease Alter Their Microbiome?

BACKGROUND

Patients with inflammatory bowel diseases (IBDs) are more likely to have depression and anxiety symptoms compared with healthy individuals and those with other chronic illnesses. Previous studies have shown a link between the microbiome composition and depression symptoms; however, many antidepressant medications have antibacterial activity confounding cross-sectional studies of these populations. Therefore, we aimed to determine whether we could detect longitudinal changes in the microbiome of a subset of patients who participated in a previously published mindfulness-based cognitive therapy (MBCT) study to improve depression symptoms in adolescents and young adults with IBD.

METHODS

Stool samples were collected at baseline and 8 weeks (n = 24 participants, 37 total samples, 13 paired samples). During this time, some participants achieved a 50% reduction in their depression symptoms either through MBCT or treatment as usual with their mental health team (responders). The microbiome composition and function of responders were compared with participants who did not improve their depression scores (nonresponders). Depression scores were determined using the depression, anxiety, and stress score (DASS-21), and metagenomic sequencing of stool samples was performed.

RESULTS

No difference in alpha diversity was found between responders and nonresponders. Beta diversity measures were similarly unchanged. Clinical features including fecal calprotectin, C-reactive protein, and serum IL-6 levels were unchanged.

CONCLUSIONS

In this small longitudinal study, we were not able to detect longitudinal changes in the microbiome associated with improvement in depression scores. Follow-up studies that are sufficiently powered to detect changes in the microbiome are required to confirm our results.

Gastrointestinal, Behaviour and Anxiety Outcomes in Autistic Children Following an Open Label, Randomised Pilot Study of Synbiotics vs Synbiotics and Gut-Directed Hypnotherapy

Alterations of the microbiome-gut-brain (MGB) axis have been associated with autism spectrum disorder (ASD) and disorders of gut-brain interaction (DGBI). DGBI are highly prevalent in autistic children and are associated with worsening behaviour and anxiety. Treatments such as probiotics, prebiotics and gut-directed hypnotherapy (GDH) have shown efficacy in improving gut symptoms in children. The primary objective of the study was to compare changes in gastrointestinal (GI) scores following a 12-week intervention of synbiotics (prebiotic + probiotic) +/- GDH with a follow-up at 24 weeks. Secondary objectives included changes in behavioural and anxiety symptoms, while changes in gut microbiome composition were assessed as an exploratory objective. Children diagnosed with ASD aged 5.00-10.99 years (n = 40) were recruited and randomised (1:1) to a 12-week intervention of either synbiotics (SYN group) or synbiotics + GDH (COM group). Both the SYN and COM group experienced significant reductions in total GI scores post-intervention and at follow-up (p < 0.001), with no superiority of the COM treatment over the SYN treatment. The COM group showed beneficial reductions in anxiety scores (p = 0.002) and irritability behaviours (p < 0.001) which were not present in the SYN group. At follow-up, only those in the COM group maintained significant reductions in GI pain scores (p < 0.001). There were significant changes in gut microbiota such as increases in Bifidobacterium animalis and Dialister in both groups over time. In conclusion, synbiotics with or without GDH may help support standard care for autistic children who suffer comorbid DGBI. The trial was prospectively registered at clinicialtrials.gov on 16 November 2020 (NCTO4639141).

Rapid species-level metagenome profiling and containment estimation with sylph

Profiling metagenomes against databases allows for the detection and quantification of microorganisms, even at low abundances where assembly is not possible. We introduce sylph, a species-level metagenome profiler that estimates genome-to-metagenome containment average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. On the Critical Assessment of Metagenome Interpretation II (CAMI2) Marine dataset, sylph was the most accurate profiling method of seven tested. For multisample profiling, sylph took >10-fold less central processing unit time compared to Kraken2 and used 30-fold less memory. Sylph's ANI estimates provided an orthogonal signal to abundance, allowing for an ANI-based metagenome-wide association study for Parkinson disease (PD) against 289,232 genomes while confirming known butyrate-PD associations at the strain level. Sylph took <1 min and 16 GB of random-access memory to profile metagenomes against 85,205 prokaryotic and 2,917,516 viral genomes, detecting 30-fold more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate containment ANI estimation even for low-coverage genomes.

Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities

Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.

Absence of association between maternal adverse events and long-term gut microbiome outcomes in the Australian autism biobank

Introduction

Maternal immune activation (MIA) and prenatal maternal stress (MatS) are well-studied risk factors for psychiatric conditions such as autism and schizophrenia. Animal studies have proposed the gut microbiome as a mechanism underlying this association and have found that risk factor-related gut microbiome alterations persist in the adult offspring. In this cross-sectional study, we assessed whether maternal immune activation and prenatal maternal stress were associated with long-term gut microbiome alterations in children using shotgun metagenomics.

Methods

This cross-sectional study included children diagnosed with autism (N = 92), siblings without a diagnosis (N = 42), and unrelated children (N = 40) without a diagnosis who were recruited into the Australian Autism Biobank and provided a faecal sample. MIA exposure was inferred from self-reported data and included asthma/allergies, complications during pregnancy triggering an immune response, auto-immune conditions, and acute inflammation. Maternal stress included any of up to 9 stressful life events during pregnancy, such as divorce, job loss, and money problems. Data were analysed for a total of 174 children, of whom 63 (36%) were born to mothers with MIA and 84 (48%) were born to mothers who experienced maternal stress during pregnancy (where 33 [19%] experienced both). Gut microbiome data was assessed using shotgun metagenomic sequencing of the children's faecal samples.

Results

In our cohort, MIA, but not MatS, was associated with ASD. Variance component analysis revealed no associations between any of the gut microbiome datasets and neither MIA nor MatS. After adjusting for age, sex, diet and autism diagnosis, there was no significant difference between groups for bacterial richness, α-diversity or β-diversity. We found no significant differences in species abundance in the main analyses. However, when stratifying the cohort by age, we found that Faecalibacterium prausnitzii E was significantly decreased in MIA children aged 11-17.

Discussion

Consistent with previous findings, we found that children who were born to mothers with MIA were more likely to be diagnosed with autism. Unlike within animal studies, we found negligible microbiome differences associated with MIA and maternal stress. Given the current interest in the microbiome-gut-brain axis, researchers should exercise caution in translating microbiome findings from animal models to human contexts and the clinical setting.

The Gut and the Translocated Microbiomes in HIV Infection: Current Concepts and Future Avenues

It is widely acknowledged that HIV infection results in disruption of the gut's mucosal integrity partly due a profound loss of gastrointestinal CD4+ T cells that are targets of the virus. In addition, systemic inflammation and immune activation that drive disease pathogenesis are reduced but not normalized by antiretroviral therapy (ART). It has long been postulated that through the process of microbial translocation, the gut microbiome acts as a key driver of systemic inflammation and immune recovery in HIV infection. As such, many studies have aimed at characterizing the gut microbiota in order to unravel its influence in people with HIV and have reported an association between various bacterial taxa and inflammation. This review assesses both contra-dictory and consistent findings among several studies in order to clarify the overall mechanisms by which the gut microbiota in adults may influence immune recovery in HIV infection. Independently of the gut microbiome, observations made from analysis of microbial products in the blood provide direct insight into how the translocated microbiome may drive immune recovery. To help better understand strengths and limitations of the findings reported, this review also highlights the numerous factors that can influence microbiome studies, be they experimental methodologies, and host-intrinsic or host-extrinsic factors. Altogether, a fuller understanding of the interplay between the gut microbiome and immunity in HIV infection may contribute to preventive and therapeutic approaches.

Effects of a prebiotic formulation on the composition of the faecal microbiota of people with functional constipation

PURPOSE

Prebiotics are defined as substances which selectively promote beneficial gut microbes leading to a health benefit for the host. Limited trials have been carried out investigating their effect on the microbiota composition of individuals afflicted by functional constipation with equivocal outcomes. In a 21-day randomised, controlled clinical trial involving 61 adults with functional constipation, a prebiotic formulation with partially hydrolysed guar gum and acacia gum as its main ingredients, significantly increased complete spontaneous bowel motions in the treatment group. This follow-up exploratory analysis investigated whether the prebiotic was associated with changes to the composition, richness, and diversity of the faecal microbiota.

METHODS

Participants provided a faecal specimen at baseline and on day 21 of the intervention period. Whole genome metagenomic shotgun sequencing comprehensively assessed taxonomic and functional composition of the microbiota.

RESULTS

Linear mixed effects regression models adjusted for potential confounders showed a significant reduction in species richness of 28.15 species (95% CI - 49.86, - 6.43) and Shannon diversity of 0.29 units (95% CI - 0.56, - 0.02) over the trial period in the prebiotic group. These changes were not observed in the control group, and functional composition was unchanged in both groups.

CONCLUSION

In adults with functional constipation, the intake of a prebiotic formulation was associated with a decline of species richness and Shannon diversity. Further research regarding the associations between prebiotics and the composition and function of the gut microbiota is warranted.

Enhancing Clinical Utility: Utilization of International Standards and Guidelines for Metagenomic Sequencing in Infectious Disease Diagnosis

Metagenomic sequencing has emerged as a transformative tool in infectious disease diagnosis, offering a comprehensive and unbiased approach to pathogen detection. Leveraging international standards and guidelines is essential for ensuring the quality and reliability of metagenomic sequencing in clinical practice. This review explores the implications of international standards and guidelines for the application of metagenomic sequencing in infectious disease diagnosis. By adhering to established standards, such as those outlined by regulatory bodies and expert consensus, healthcare providers can enhance the accuracy and clinical utility of metagenomic sequencing. The integration of international standards and guidelines into metagenomic sequencing workflows can streamline diagnostic processes, improve pathogen identification, and optimize patient care. Strategies in implementing these standards for infectious disease diagnosis using metagenomic sequencing are discussed, highlighting the importance of standardized approaches in advancing precision infectious disease diagnosis initiatives.

Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines

Shotgun metagenomic sequencing comprehensively samples the DNA of a microbial sample. Choosing the best bioinformatics processing package can be daunting due to the wide variety of tools available. Here, we assessed publicly available shotgun metagenomics processing packages/pipelines including bioBakery, Just a Microbiology System (JAMS), Whole metaGenome Sequence Assembly V2 (WGSA2), and Woltka using 19 publicly available mock community samples and a set of five constructed pathogenic gut microbiome samples. Also included is a workflow for labelling bacterial scientific names with NCBI taxonomy identifiers for better resolution in assessing results. The Aitchison distance, a sensitivity metric, and total False Positive Relative Abundance were used for accuracy assessments for all pipelines and mock samples. Overall, bioBakery4 performed the best with most of the accuracy metrics, while JAMS and WGSA2, had the highest sensitivities. Furthermore, bioBakery is commonly used and only requires a basic knowledge of command line usage. This work provides an unbiased assessment of shotgun metagenomics packages and presents results assessing the performance of the packages using mock community sequence data.

Reintroducing a keystone bioturbator can facilitate microbial bioremediation in urban polluted sediments

Anthropogenic environmental stressors have significantly reduced biodiversity and the capacity of remnant natural habitats to deliver ecosystem functions and services in urban areas. To mitigate these impacts and recover biodiversity and function, ecological restoration strategies are needed. While habitat restoration is proliferating in rural and peri-urban areas, strategies purposely designed to succeed under the environmental, social and political pressures of urban areas are lacking. Here, we propose that ecosystem health in marine urban areas can be improved by restoring biodiversity to the most dominant habitat, unvegetated sediments. We reintroduced a native ecosystem engineer, the sediment bioturbating worm Diopatra aciculata, and assessed their effects on microbial biodiversity and function. Results showed that worms can affect the diversity of microbes, but effects varied between locations. Worms caused shifts in microbial community composition and function at all locations. Specifically, the abundance of microbes capable of chlorophyll production (i.e. benthic microalgae) increased and the abundance of microbes capable of methane production decreased. Moreover, worms increased the abundances of microbes capable of denitrification in the site with lowest sediment oxygenation. Worms also affected microbes capable of degrading the polycyclic aromatic hydrocarbon toluene, although the direction of that effect was site-specific. This study provides evidence that a simple intervention such as the reintroduction of a single species can enhance sediment functions important for the amelioration of contamination and eutrophication, although further studies are needed to understand the variation in outcomes between sites. Nevertheless, restoration strategies targeting unvegetated sediments provide an opportunity to combat anthropogenic stressors in urban ecosystems and may be used for precondition before more traditional forms of habitat restoration such as seagrass, mangrove and shellfish restoration.

From defaults to databases: parameter and database choice dramatically impact the performance of metagenomic taxonomic classification tools

In metagenomic analyses of microbiomes, one of the first steps is usually the taxonomic classification of reads by comparison to a database of previously taxonomically classified genomes. While different studies comparing metagenomic taxonomic classification methods have determined that different tools are 'best', there are two tools that have been used the most to-date: Kraken (k-mer-based classification against a user-constructed database) and MetaPhlAn (classification by alignment to clade-specific marker genes), the latest versions of which are Kraken2 and MetaPhlAn 3, respectively. We found large discrepancies in both the proportion of reads that were classified as well as the number of species that were identified when we used both Kraken2 and MetaPhlAn 3 to classify reads within metagenomes from human-associated or environmental datasets. We then investigated which of these tools would give classifications closest to the real composition of metagenomic samples using a range of simulated and mock samples and examined the combined impact of tool-parameter-database choice on the taxonomic classifications given. This revealed that there may not be a one-size-fits-all 'best' choice. While Kraken2 can achieve better overall performance, with higher precision, recall and F1 scores, as well as alpha- and beta-diversity measures closer to the known composition than MetaPhlAn 3, the computational resources required for this may be prohibitive for many researchers, and the default database and parameters should not be used. We therefore conclude that the best tool-parameter-database choice for a particular application depends on the scientific question of interest, which performance metric is most important for this question and the limit of available computational resources.

Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.

Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets

BACKGROUND

Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.

RESULTS

Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.

CONCLUSIONS

Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments

BACKGROUND

Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes.

RESULTS

We present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies.

CONCLUSIONS

We developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.

expam-high-resolution analysis of metagenomes using distance trees

Summary

Shotgun metagenomic sequencing provides the capacity to understand microbial community structure and function at unprecedented resolution; however, the current analytical methods are constrained by a focus on taxonomic classifications that may obfuscate functional relationships. Here, we present expam, a tree-based, taxonomy agnostic tool for the identification of biologically relevant clades from shotgun metagenomic sequencing.

Availability and implementation

expam is an open-source Python application released under the GNU General Public Licence v3.0. expam installation instructions, source code and tutorials can be found at https://github.com/seansolari/expam.

Supplementary information

Supplementary data are available at Bioinformatics online.

Effect of a reduced fat and sugar maternal dietary intervention during lactation on the infant gut microbiome

Objective

A growing body of literature has shown that maternal diet during pregnancy is associated with infant gut bacterial composition. However, whether maternal diet during lactation affects the exclusively breastfed infant gut microbiome remains understudied. This study sets out to determine whether a two-week of a reduced fat and sugar maternal dietary intervention during lactation is associated with changes in the infant gut microbiome composition and function.

Design

Stool samples were collected from four female and six male (n = 10) infants immediately before and after the intervention. Maternal baseline diet from healthy mothers aged 22–37 was assessed using 24-h dietary recall. During the 2-week dietary intervention, mothers were provided with meals and their dietary intake was calculated using FoodWorks 10 Software. Shotgun metagenomic sequencing was used to characterize the infant gut microbiome composition and function.

Results

In all but one participant, maternal fat and sugar intake during the intervention were significantly lower than at baseline. The functional capacity of the infant gut microbiome was significantly altered by the intervention, with increased levels of genes associated with 28 bacterial metabolic pathways involved in biosynthesis of vitamins (p = 0.003), amino acids (p = 0.005), carbohydrates (p = 0.01), and fatty acids and lipids (p = 0.01). Although the dietary intervention did not affect the bacterial composition of the infant gut microbiome, relative difference in maternal fiber intake was positively associated with increased abundance of genes involved in biosynthesis of storage compounds (p = 0.016), such as cyanophycin. Relative difference in maternal protein intake was negatively associated with Veillonella parvula (p = 0.006), while positively associated with Klebsiella michiganensis (p = 0.047). Relative difference in maternal sugar intake was positively associated with Lactobacillus paracasei (p = 0.022). Relative difference in maternal fat intake was positively associated with genes involved in the biosynthesis of storage compounds (p = 0.015), fatty acid and lipid (p = 0.039), and metabolic regulator (p = 0.038) metabolic pathways.

Conclusion

This pilot study demonstrates that a short-term maternal dietary intervention during lactation can significantly alter the functional potential, but not bacterial taxonomy, of the breastfed infant gut microbiome. While the overall diet itself was not able to change the composition of the infant gut microbiome, changes in intakes of maternal protein and sugar during lactation were correlated with changes in the relative abundances of certain bacterial species.

Clinical trial registration: Australian New Zealand Clinical Trials Registry (ACTRN12619000606189).

RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties

Metagenomic classifiers are widely used for the taxonomic profiling of metagenomics data and estimation of taxa relative abundance. Small subunit rRNA genes are a gold standard for phylogenetic resolution of microbiota, although the power of this marker comes down to its use as full-length. We aimed at identifying the tools that can efficiently lead to taxonomic resolution down to the species level. To reach this goal, we benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then compiled the best tools (BBTools, FastQC, SortMeRNA, MetaRib, EMIRGE, VSEARCH, BBMap and QIIME 2’s Sklearn classifier) to build a pipeline called RiboTaxa. Using metagenomics datasets, RiboTaxa gave the best results compared to other tools (i.e. Kraken2, Centrifuge, METAXA2, phyloFlash, SPINGO, BLCA, MEGAN) with precise taxonomic identification and relative abundance description without false positive detection (F-measure of 100% and 83.7% at genus level and species level, respectively). Using real datasets from various environments (i.e. ocean, soil, human gut) and from different approaches (e.g. metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not discerned by current bioinformatics analysis opening new biological perspectives in human and environmental health.

Characterization and Demonstration of Mock Communities as Control Reagents for Accurate Human Microbiome Community Measurements

Standardization and quality assurance of microbiome community analysis by high-throughput DNA sequencing require widely accessible and well-characterized reference materials. Here, we report on newly developed DNA and whole-cell mock communities to serve as control reagents for human gut microbiota measurements by shotgun metagenomics and 16S rRNA gene amplicon sequencing. The mock communities were formulated as near-even blends of up to 20 bacterial species prevalent in the human gut, span a wide range of genomic guanine-cytosine (GC) contents, and include multiple strains with Gram-positive type cell walls. Through a collaborative study, we carefully characterized the mock communities by shotgun metagenomics, using previously developed standardized protocols for DNA extraction and sequencing library construction. Further, we validated fitness of the mock communities for revealing technically meaningful differences among protocols for DNA extraction and metagenome/16S rRNA gene amplicon library construction. Finally, we used the mock communities to reveal varying performance of metagenome-based taxonomic profilers and the impact of trimming and filtering of sequencing reads on observed species profiles. The latter showed that aggressive preprocessing of reads may result in substantial GC-dependent bias and should thus be carefully evaluated to minimize unintended effects on species abundances. Taken together, the mock communities are expected to support a myriad of applications that rely on well-characterized control reagents, ranging from evaluation and optimization of methods to assessment of reproducibility in interlaboratory studies and routine quality control.

IMPORTANCE Application of high-throughput DNA sequencing has greatly accelerated human microbiome research and its translation into new therapeutic and diagnostic capabilities. Microbiome community analyses results can, however, vary considerably across studies or laboratories, and establishment of measurement standards to improve accuracy and reproducibility has become a priority. The here-developed mock communities, which are available from the NITE Biological Resource Center (NBRC) at the National Institute of Technology and Evaluation (NITE, Japan), provide well-characterized control reagents that allow users to judge the accuracy of their measurement results. Widespread and consistent adoption of the mock communities will improve reproducibility and comparability of microbiome community analyses, thereby supporting and accelerating human microbiome research and development.

Synbiotics Easing Renal Failure by Improving Gut Microbiology II (SYNERGY II): A Feasibility Randomized Controlled Trial

Synbiotics have emerged as a therapeutic strategy for modulating the gut microbiome and targeting novel cardiovascular risk factors, including uremic toxins indoxyl sulfate (IS) and p-cresyl sulfate (PCS). This study aims to evaluate the feasibility of a trial of long-term synbiotic supplementation in adults with stage 3-4 chronic kidney disease (CKD). Adult participants with CKD and estimated glomerular filtration rate (eGFR) of 15-60 mL/min/1.73 m²) were recruited between April 2017 and August 2018 to a feasibility, double-blind, placebo-controlled, randomized trial of synbiotic therapy or matched identical placebo for 12 months. The primary outcomes were recruitment and retention rates as well as acceptability of the intervention. Secondary outcomes were treatment adherence and dietary intake. Exploratory outcomes were evaluation of the cardiovascular structure and function, serum IS and PCS, stool microbiota profile, kidney function, blood pressure, and lipid profile. Of 166 potentially eligible patients, 68 (41%) were recruited into the trial (synbiotic n = 35, placebo n = 33). Synbiotic and placebo groups had acceptable and comparable 12-month retention rates (80% versus 85%, respectively, p = 0.60). Synbiotic supplementation altered the stool microbiome with an enrichment of Bifidobacterium and Blautia spp., resulting in a 3.14 mL/min/1.73 m² (95% confidence interval (CI), -6.23 to -0.06 mL/min/1.73 m², p < 0.01) reduction in eGFR and a 20.8 µmol/L (95% CI, 2.97 to 38.5 µmol/L, p < 0.01) increase in serum creatinine concentration. No between-group differences were observed in any of the other secondary or exploratory outcomes. Long-term synbiotic supplementation was feasible and acceptable to patients with CKD, and it modified the gastrointestinal microbiome. However, the reduction in kidney function with synbiotics warrants further investigation.

Autism-related dietary preferences mediate autism-gut microbiome associations

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

Diet Quality and Protein-Bound Uraemic Toxins: Investigation of Novel Risk Factors and the Role of Microbiome in Chronic Kidney Disease

OBJECTIVE

This study aims to explore the associations between diet quality, uraemic toxins, and gastrointestinal microbiota in the chronic kidney disease (CKD) population.

METHODS

This is a baseline cross-sectional study of adults with CKD participating in a randomized controlled trial of prebiotic and probiotic supplementation. Dietary intake was measured using a seven-day diet history method, administered by a specialist dietitian. Diet quality was assessed using plant-based diet index (PDI) (overall PDI, healthy PDI, and unhealthy PDI), food group analysis, protein intake, fiber intake, and dietary protein-to-fiber ratio. Serum uraemic toxins (free and total; indoxyl sulfate and p-cresyl sulfate) were determined by ultraperformance liquid chromatography. Gastrointestinal microbiota richness, diversity, composition, and functional capacity were analyzed via metagenomic sequencing.

RESULTS

Sixty-eight adults [median age: 70 (interquartile range: 58-75) years, 66% male] with an estimated glomerular filtration rate of 34 ± 11 mL/min/1.73 m² were included, with 40 participants completing the optional fecal substudy. Dietary fiber intake was associated with lower levels of total indoxyl sulfate, whereas the healthy plant-based diet index was associated with lower levels of free p-cresyl sulfate. A higher protein-to-fiber ratio was associated with an increased relative abundance of unclassified members of order Oscillospirales. Intake of vegetables and whole grains was correlated with Subdoligranulum formicile, whereas an unclassified Prevotella species was correlated with potatoes and food items considered discretionary, including sweet drinks, sweet desserts, and animal fats.

CONCLUSIONS

Diet quality may influence uraemic toxin generation and gut microbiota diversity, composition, and function in adults with CKD. Well-designed dietary intervention studies targeting the production of uraemic toxins and exploring the impact on gut microbiome are warranted in the CKD population.

Critical evaluation of faecal microbiome preservation using metagenomic analysis

The ability to preserve microbial communities in faecal samples is essential as increasing numbers of studies seek to use the gut microbiome to identify biomarkers of disease. Here we use shotgun metagenomics to rigorously evaluate the technical and compositional reproducibility of five room temperature (RT) microbial stabilisation methods compared to the best practice of flash-freezing. These methods included RNALater, OMNIGene-GUT, a dry BBL swab, LifeGuard, and a novel method for preserving faecal samples, a Copan FLOQSwab in an active drying tube (FLOQSwab-ADT). Each method was assessed using six replicate faecal samples from five participants, totalling 180 samples. The FLOQSwab-ADT performed best for both technical and compositional reproducibility, followed by RNAlater and OMNIgene-GUT. LifeGuard and the BBL swab had unpredictable outgrowth of Escherichia species in at least one replicate from each participant. We further evaluated the FLOQSwab-ADT in an additional 239 samples across 10 individuals after storage at -20 °C, RT, and 50 °C for four weeks compared to fresh controls. The FLOQSwab-ADT maintained its performance across all temperatures, indicating this method is an excellent alternative to existing RT stabilisation methods.

Characteristics of the gastrointestinal microbiota in paired live kidney donors and recipients

BACKGROUND

There are few studies that have examined whether dysbiosis occurs in kidney donors and transplant recipients following kidney transplant surgery.

AIM

To ascertain whether changes occur in the gastrointestinal microbiota of the kidney donor and recipient following kidney transplantation.

METHODS

Kidney transplant recipients and their donors were prospectively enrolled in a pilot study to collect one faecal sample prior to, and another faecal sample between four to eight weeks following surgery. Gastrointestinal microbiota richness, Shannon diversity measures and functional assessments of kidney donors and recipients were analysed via metagenomic sequencing.

RESULTS

The study included 12 donors (median age 56 years, 6 females) and 12 recipients (median age 51 years, 3 females). Donor microbiota showed no significant changes in gastrointestinal microbiota richness, Shannon diversity, or functional assessments before and after nephrectomy. Recipient microbiota was altered post-transplant, reflected in reductions of the mean (±SD) richness values (156 ± 46.5 to 116 ± 38.6, p = 0.002), and Shannon diversity (3.57 ± 0.49 to 3.14 ± 0.52, p = 0.007), and a dramatic increase in Roseburia spp. abundance post-transplant (26-fold increase from 0.16 ± 0.0091 to 4.6 ± 0.3; p = 0.006; FDR = 0.12). Functionally, the post-transplant microbial community shifted towards those taxa using the glycolysis pathway (1.2-fold increase; p = 0.02; FDR = 0.26) for energy metabolism, while those functions involved with reactive oxygen species degradation decreased (2.6-fold; p = 0.006; FDR = 0.14).

CONCLUSION

Live donor kidney transplantation and standard care post-transplant result in significant alterations in gut microbiota richness, diversity, composition and functional parameters in kidney transplant recipients but not in their kidney donors.