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

De-biasing microbiome sequencing data: bacterial morphology-based correction of extraction bias and correlates of chimera formation

INTRODUCTION

Microbiome amplicon sequencing data are distorted by multiple protocol-dependent biases from bacterial DNA extraction, contamination, sequence errors, and chimeras, hindering clinical microbiome applications. In particular, extraction bias is a major confounder in sequencing-based microbiome analyses, with no correction method available to date. Here, we suggest using mock community controls to computationally correct extraction bias based on bacterial morphological properties.

METHODS

We compared dilution series of 3 cell mock communities with an even or staggered composition. DNA of these mock, and additional skin microbiome samples, was extracted with 8 different extraction protocols (2 buffers, 2 extraction kits, 2 lysis conditions). Extracted DNA was sequenced (V1-V3 16S rRNA gene) together with corresponding DNA mocks.

RESULTS

Microbiome composition was significantly different between extraction kits and lysis conditions, but not between buffers. Independent of the extraction protocol, chimera formation increased with higher input cell numbers. Contaminants originated mostly from buffers, and considerable cross-contamination was observed in low-input samples. Comparing the microbiome composition of the cell mocks to corresponding DNA mocks revealed taxon-specific protocol-dependent extraction bias. Strikingly, this extraction bias per species was predictable by bacterial cell morphology. Morphology-based computational correction of extraction bias significantly improved resulting microbial compositions when applied to different mock samples, even with different taxa. Equivalent correction of the skin samples showed a substantial impact on microbiome compositions.

CONCLUSIONS

Our results indicate that higher DNA density increases chimera formation during PCR amplification. Furthermore, we show that computational correction of extraction bias based on bacterial cell morphology would be feasible using appropriate positive controls, thus constituting an important step toward overcoming protocol biases in microbiome analysis. Video Abstract.

Metagenomic global survey and in-depth genomic analyses of Ruminococcus gnavus reveal differences across host lifestyle and health status

Ruminococcus gnavus is a gut bacterium found in > 90% of healthy individuals, but its increased abundance is also associated with chronic inflammatory diseases, particularly Crohn's disease. Nevertheless, its global distribution and intraspecies genomic variation remain understudied. By surveying 12,791 gut metagenomes, we recapitulated known associations with metabolic diseases and inflammatory bowel disease. We uncovered a higher prevalence and abundance of R. gnavus in Westernized populations and observed bacterial relative abundances up to 83% in newborns. Next, we built a resource of R. gnavus isolates (N = 45) from healthy individuals and Crohn's disease patients and generated complete R. gnavus genomes using PacBio circular consensus sequencing. Analysis of these genomes and publicly available high-quality draft genomes (N = 333 genomes) revealed multiple clades which separated Crohn's-derived isolates from healthy-derived isolates. Presumed R. gnavus virulence factors could not explain this separation. Bacterial genome-wide association study revealed that Crohn's-derived isolates were enriched in genes related to mobile elements and mucin foraging. Together, we present a large R. gnavus resource that will be available to the scientific community and provide novel biological insights into the global distribution and genomic variation of R. gnavus.

Challenge of validation in whole-cell spike-in amplicon sequencing to comprehensively quantify food lactic acid bacteriota

Lactic acid bacteria (LAB) shape diverse communities in fermented foods. Developing comprehensive quantification methods for community structure will revolutionize our understanding of food LAB microbiome. For this purpose, 16S rRNA gene amplicon-based quantification, using spiked exogenous bacterial cells as an internal standard, shows potential for comprehensiveness and accuracy. We validated cell spike-in amplicon sequencing for quantifying LAB communities in food. Low efficiency of LAB DNA extraction underscores the importance of compensating for DNA loss by spiking internal standard cells. Quantitative equations generated using 15 selected LAB mock species showed positive relationships between the ratio of MiSeq read counts and the expected 16S rRNA gene copy numbers, with coefficients of determination (R2) ≥ 0.6823. The fold differences between observed and expected 16S copy numbers were within the range of 1/3 to 3-fold. Our validation highlights that accurate preparation of the LAB mock community is crucial for cell spike-in amplicon sequencing accuracy.

A HPLC-based Method for Counting the Genome Copy Number of Cells Allows the Production of a High-quality Mock Community of Bacterial Cells

Improving the reliability of a metagenomic sequencing ana-lysis requires the use of control samples, known as mock communities. Therefore, mock communities must be prepared with high accuracy and reproducibility, which is particularly challenging for cellular mock communities. In the present study, we prepared a cellular mock community consisting of bacterial strains representative of the human and surrounding environmental microbiomes to demonstrate the suitability of a HPLC-based method that measures the genome number of cells. This method proved to be more accurate and reproducible for preparing cellular mock communities than traditional cell counting-based enumeration methods.

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

Microbiologic surveys for Baijiu fermentation are affected by experimental design

The traditional Chinese alcoholic beverage Baijiu is produced by spontaneous fermentation of grains under anaerobic conditions. While numerous studies have used metagenomic technology to investigate the microbiome of Baijiu brewing, the microbial succession mechanism of Baijiu brewing has not been fully clarified, and metagenomic strategies for microecology surveys have not been comprehensively evaluated. Using the fermentation process of strong-flavor Baijiu as a model, we compared the data for bacterial communities based on short read 16S rRNA variable regions, V3-V4, and full-length 16S regions, V1-V9, to whole metagenomic shotgun sequencing (WMS) to measure the effect of technology selection on phylogenetic and functional profiles. The results showed differences in bacterial compositions and their relation to volatiles and physicochemical variables between sequencing methods. Furthermore, the percentage of V3-V4 sequences assigned to species level was higher than the percentage of V1-V9 sequences according to SILVA taxonomy, but lower according to NCBI taxonomy (P < 0.05). In both SILVA and NCBI taxonomies, the relative abundances of bacterial communities at both the genus and family levels were more positively correlated with WMS data in the V3-V4 dataset than in the V1-V9 dataset. The WMS identified changes in abundances of multiple metabolic pathways during fermentation (P < 0.05), including "starch and sucrose metabolism," "galactose metabolism," and "fatty acid biosynthesis." Although functional predictions derived from 16S data show similar patterns to WMS, most metabolic pathway changes are uncorrelated (P > 0.05). This study provided new technical and biological insights into Baijiu production that may assist in selection of methodologies for studies of fermentation systems.

Considerations for the inclusion of metabarcoding data in the plant protection product risk assessment of the soil microbiome

There is increasing interest in further developing the plant protection product (PPP) environmental risk assessment, particularly within the European Union, to include the assessment of soil microbial community composition, as measured by metabarcoding approaches. However, to date, there has been little discussion as to how this could be implemented in a standardized, reliable, and robust manner suitable for regulatory decision-making. Introduction of metabarcoding-based assessments of the soil microbiome into the PPP risk assessment would represent a significant increase in the degree of complexity of the data that needs to be processed and analyzed in comparison to the existing risk assessment on in-soil organisms. The bioinformatics procedures to process DNA sequences into community compositional data sets currently lack standardization, while little information exists on how these data should be used to generate regulatory endpoints and the ways in which these endpoints should be interpreted. Through a thorough and critical review, we explore these challenges. We conclude that currently, we do not have a sufficient degree of standardization or understanding of the required bioinformatics and data analysis procedures to consider their use in an environmental risk assessment context. However, we highlight critical knowledge gaps and the further research required to understand whether metabarcoding-based assessments of the soil microbiome can be utilized in a statistically and ecologically relevant manner within a PPP risk assessment. Only once these challenges are addressed can we consider if and how we should use metabarcoding as a tool for regulatory decision-making to assess and monitor ecotoxicological effects on soil microorganisms within an environmental risk assessment of PPPs. Integr Environ Assess Manag 2024;20:337-358. © 2023 SETAC.

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.

Benchmarking DNA isolation methods for marine metagenomics

Metagenomics is a powerful tool to study marine microbial communities. However, obtaining high-quality environmental DNA suitable for downstream sequencing applications is a challenging task. The quality and quantity of isolated DNA heavily depend on the choice of purification procedure and the type of sample. Selection of an appropriate DNA isolation method for a new type of material often entails a lengthy trial and error process. Further, each DNA purification approach introduces biases and thus affects the composition of the studied community. To account for these problems and biases, we systematically investigated efficiency of DNA purification from three types of samples (water, sea sediment, and digestive tract of a model invertebrate Magallana gigas) with eight commercially available DNA isolation kits. For each kit-sample combination we measured the quantity of purified DNA, extent of DNA fragmentation, the presence of PCR-inhibiting contaminants, admixture of eukaryotic DNA, alpha-diversity, and reproducibility of the resulting community composition based on 16S rRNA amplicons sequencing. Additionally, we determined a "kitome", e.g., a set of contaminating taxa inherent for each type of purification kit used. The resulting matrix of evaluated parameters allows one to select the best DNA purification procedure for a given type of sample.

Innovations in genomic antimicrobial resistance surveillance

Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance and epidemiology; however, routine adoption of these technologies is challenging, particularly in low-income and middle-income countries. As part of a wider series of workshops and online consultations, a group of experts in AMR pathogen genomics and computational tool development conducted a situational analysis, identifying the following under-used innovations in genomic AMR surveillance: clinical metagenomics, environmental metagenomics, gene or plasmid tracking, and machine learning. The group recommended developing cost-effective use cases for each approach and mapping data outputs to clinical outcomes of interest to justify additional investment in capacity, training, and staff required to implement these technologies. Harmonisation and standardisation of methods, and the creation of equitable data sharing and governance frameworks, will facilitate successful implementation of these innovations.

Gut microbiome in intracranial aneurysm growth, subarachnoid hemorrhage, and cerebral vasospasm: a systematic review with a narrative synthesis

Intracranial aneurysms (IA) are the most common cerebral vascular pathologies. Their rupture leads to the most dangerous subtype of stroke-aneurysmal subarachnoid hemorrhage (aSAH), which may be followed by cerebral vasospasm and ischemic sequelae. Recently, an imbalance within the intestinal microbiota, referred to as dysbiosis, was suggested to play a role in the formation, progression, and rupture of IA. As no systematic review on this topic exists, considering the significance of this matter and a lack of effective prophylaxis against IA or cerebral vasospasm, we aim to sum up the current knowledge regarding their associations with intestinal microbiome, identify the gaps, and determine future prospects. Scientific databases were systematically and independently searched by two authors from inception to 1st May 2023 for original articles regarding the role of intestinal microbiota in intracranial aneurysmal growth, aSAH occurrence, as well as in cerebral vasospasm following aSAH. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was followed in an abstraction process. The STROBE tool was applied to assess the risk of bias. This research was funded by the National Science Centre, Poland (grant number 2021/41/N/NZ2/00844). Of 302 records, four studies were included that fully met eligibility criteria. Studies reported (1) that the relative abundance of Hungatella hathewayi is a protective factor against aneurysm growth and rupture, resulting from the reduced inflammation and extracellular matrix remodeling in the cerebral arterial wall and from reduced metalloproteinase-mediated degradation of smooth muscle cells in cerebral vessels. (2) Relative abundance of Campylobacter ureolyticus is associated with aSAH. (3) No article has evaluated microbiota in relation to cerebral vasospasm following aSAH although there is an ongoing study. We concluded that intestinal microbiota might be a potential target for diagnostic and therapeutic tools to improve the management of cerebral aneurysms. However, more studies of prospective design are needed.

Establishing reference material for the quest towards standardization in environmental microbial metagenomic studies

Breakthroughs in DNA-based technologies, especially in metagenomic sequencing, have drastically enhanced researchers' ability to explore environmental microbiome and the associated interplays within. However, as new methodologies are being actively developed for improvements in different aspects, metagenomic workflows become diversified and heterogeneous. Through a single-variable control approach, we quantified the microbial profiling variations arising from 6 common technical variables associated with metagenomic workflows for both simple and complex samples. The incurred variations were constantly the lowest in replicates of DNA isolation and DNA sequencing library construction. Different DNA extraction kits often caused the highest variation among all the tested variables. Additionally, sequencing run batch was an important source of variability for targeted platforms. As such, the development of an environmental reference material for complex environmental samples could be beneficial in benchmarking accrued non-biological variability within and between protocols and insuring reliable and reproducible sequencing outputs immediately upstream of bioinformatic analysis. To develop an environment reference material, sequencing of a well-homogenized environmental sample composed of activated sludge was performed using different pre-analytical assays in replications. In parallel, a certified mock community was processed and sequenced. Assays were ranked based on the reconstruction of the theoretical mock community profile. The reproducibility of the best-performing assay and the microbial profile of the reference material were further ascertained. We propose the adoption of our complex environmental reference material, which could reflect the degree of diversity in environmental microbiome studies, to facilitate accurate, reproducible, and comparable environmental metagenomics-based studies.

Prospecting for Zoonotic Pathogens by Using Targeted DNA Enrichment

More than 60 zoonoses are linked to small mammals, including some of the most devastating pathogens in human history. Millions of museum-archived tissues are available to understand natural history of those pathogens. Our goal was to maximize the value of museum collections for pathogen-based research by using targeted sequence capture. We generated a probe panel that includes 39,916 80-bp RNA probes targeting 32 pathogen groups, including bacteria, helminths, fungi, and protozoans. Laboratory-generated, mock-control samples showed that we are capable of enriching targeted loci from pathogen DNA 2,882‒6,746-fold. We identified bacterial species in museum-archived samples, including Bartonella, a known human zoonosis. These results showed that probe-based enrichment of pathogens is a highly customizable and efficient method for identifying pathogens from museum-archived tissues.

Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Benchmarking second and third-generation sequencing platforms for microbial metagenomics

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.

Insight into co-hosts of nitrate reduction genes and antibiotic resistance genes in an urban river of the qinghai-tibet plateau

Microbial co-hosts of nitrate reduction genes (NRGs) and antibiotic resistance genes (ARGs) have been recently reported, but their ecology and biochemical role in urban waterways remain largely unknown. Here, we collected 29 surface water and 29 sediment samples in the Huangshui River on the Qinghai-Tibet Plateau during the wet and dry season, and 11 water samples from wastewater treatment plants and wetlands along the river. Using metagenomic sequencing, we retrieved 278 medium-to-high-quality metagenome-assembled genomes (MAGs) of NRG-ARG co-hosts, mainly belonging to the phyla Proteobacteria, Actinobacteriota, and Bacteroidota. Of microorganisms carrying ARGs, a high proportion (75.3%‒94.9%) also encoded NRGs, supporting nitrate reducing bacteria as dominant hosts of ARGs. Seasonal changes in antibiotic levels corresponded to significant variation in the relative abundance of NRG-ARG co-host in both water and sediments, resulting in a concomitant change in antibiotic resistance pathways. In contrast, the contribution of NRG-ARG co-hosts to nitrate reduction was stable between seasons. We identify specific antibiotics (e.g., sulphonamides) and microbial taxa (e.g., Acinetobacter and Hafnia) that may disproportionately impact these relationships to serve as a basis for laboratory investigations into bioremediation strategies. Our study suggests that highly abundant nitrate reducing microorganisms in contaminated environments may also directly impact human health as carriers of antibiotic resistance.