Choice of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis

Non-significant influence between aerobic and anaerobic sample transport materials on gut (fecal) microbiota in healthy and fat-metabolic disorder Thai adults

Background

The appropriate sample handling for human fecal microbiota studies is essential to prevent changes in bacterial composition and quantities that could lead to misinterpretation of the data.

Methods

This study firstly identified the potential effect of aerobic and anaerobic fecal sample collection and transport materials on microbiota and quantitative microbiota in healthy and fat-metabolic disorder Thai adults aged 23-43 years. We employed metagenomics followed by 16S rRNA gene sequencing and 16S rRNA gene qPCR, to analyze taxonomic composition, alpha diversity, beta diversity, bacterial quantification, Pearson's correlation with clinical factors for fat-metabolic disorder, and the microbial community and species potential metabolic functions.

Results

Our study successfully obtained microbiota results in percent and quantitative compositions. Each sample exhibited quality sequences with a >99% Good's coverage index, and a relatively plateau rarefaction curve. Alpha diversity indices showed no statistical difference in percent and quantitative microbiota OTU richness and evenness, between aerobic and anaerobic sample transport materials. Obligate and facultative anaerobic species were analyzed and no statistical difference was observed. Supportively, the beta diversity analysis by non-metric multidimensional scale (NMDS) constructed using various beta diversity coefficients showed resembling microbiota community structures between aerobic and anaerobic sample transport groups (P = 0.86). On the other hand, the beta diversity could distinguish microbiota community structures between healthy and fat-metabolic disorder groups (P = 0.02), along with Pearson's correlated clinical parameters (i.e., age, liver stiffness, GGT, BMI, and TC), the significantly associated bacterial species and their microbial metabolic functions. For example, genera such as Ruminococcus and Bifidobacterium in healthy human gut provide functions in metabolisms of cofactors and vitamins, biosynthesis of secondary metabolites against gut pathogens, energy metabolisms, digestive system, and carbohydrate metabolism. These microbial functional characteristics were also predicted as healthy individual biomarkers by LEfSe scores. In conclusion, this study demonstrated that aerobic sample collection and transport (<48 h) did not statistically affect the microbiota and quantitative microbiota analyses in alpha and beta diversity measurements. The study also showed that the short-term aerobic sample collection and transport still allowed fecal microbiota differentiation between healthy and fat-metabolic disorder subjects, similar to anaerobic sample collection and transport. The core microbiota were analyzed, and the findings were consistent. Moreover, the microbiota-related metabolic potentials and bacterial species biomarkers in healthy and fat-metabolic disorder were suggested with statistical bioinformatics (i.e., Bacteroides plebeius).

Improved DNA Extraction and Amplification Strategy for 16S rRNA Gene Amplicon-Based Microbiome Studies

Next-generation sequencing technology has driven the rapid advancement of human microbiome studies by enabling community-level sequence profiling of microbiomes. Although all microbiome sequencing methods depend on recovering the DNA from a sample as a first critical step, lysis methods can be a major determinant of microbiome profile bias. Gentle enzyme-based DNA preparation methods preserve DNA quality but can bias the results by failing to open difficult-to-lyse bacteria. Mechanical methods like bead beating can also bias DNA recovery because the mechanical energy required to break tougher cell walls may shear the DNA of the more easily lysed microbes, and shearing can vary depending on the time and intensity of beating, influencing reproducibility. We introduce a non-mechanical, non-enzymatic, novel rapid microbial DNA extraction procedure suitable for 16S rRNA gene-based microbiome profiling applications that eliminates bead beating. The simultaneous application of alkaline, heat, and detergent ('Rapid' protocol) to milligram quantity samples provided consistent representation across the population of difficult and easily lysed bacteria equal to or better than existing protocols, producing sufficient high-quality DNA for full-length 16S rRNA gene PCR. The novel 'Rapid' method was evaluated using mock bacterial communities containing both difficult and easily lysed bacteria. Human fecal sample testing compared the novel Rapid method with a standard Human Microbiome Project (HMP) protocol for samples from lung cancer patients and controls. DNA recovered from both methods was analyzed using 16S rRNA gene sequencing of the V1V3 and V4 regions on the Illumina platform and the V1V9 region on the PacBio platform. Our findings indicate that the 'Rapid' protocol consistently yielded higher levels of Firmicutes species, which reflected the profile of the bacterial community structure more accurately, which was confirmed by mock community evaluation. The novel 'Rapid' DNA lysis protocol reduces population bias common to bead beating and enzymatic lysis methods, presenting opportunities for improved microbial community profiling, combined with the reduction in sample input to 10 milligrams or less, and it enables rapid transfer and simultaneous lysis of 96 samples in a standard plate format. This results in a 20-fold reduction in sample handling time and an overall 2-fold time advantage when compared to widely used commercial methods. We conclude that the novel 'Rapid' DNA extraction protocol offers a reliable alternative for preparing fecal specimens for 16S rRNA gene amplicon sequencing.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

Precision run-on sequencing (PRO-seq) for microbiome transcriptomics

Bacteria respond to environmental stimuli through precise regulation of transcription initiation and elongation. Bulk RNA sequencing primarily characterizes mature transcripts, so to identify actively transcribed loci we need to capture RNA polymerase (RNAP) complexed with nascent RNA. However, such capture methods have only previously been applied to culturable, genetically tractable organisms such as E. coli and B. subtilis. Here we apply precision run-on sequencing (PRO-seq) to profile nascent transcription in cultured E. coli and diverse uncultured bacteria. We demonstrate that PRO-seq can characterize the transcription of small, structured, or post-transcriptionally modified RNAs, which are often absent from bulk RNA-seq libraries. Applying PRO-seq to the human microbiome highlights taxon-specific RNAP pause motifs and pause-site distributions across non-coding RNA loci that reflect structure-coincident pausing. We also uncover concurrent transcription and cleavage of CRISPR guide RNAs and transfer RNAs. We demonstrate the utility of PRO-seq for exploring transcriptional dynamics in diverse microbial communities.

Impact of milk secretor status on the fecal metabolome and microbiota of breastfed infants

Maternal secretor status has been shown to be associated with the presence of specific fucosylated human milk oligosaccharides (HMOs), and the impact of maternal secretor status on infant gut microbiota measured through 16s sequencing has previously been reported. None of those studies have confirmed exclusive breastfeeding nor investigated the impact of maternal secretor status on gut microbial fermentation products. The present study focused on exclusively breastfed (EBF) Indonesian infants, with exclusive breastfeeding validated through the stable isotope deuterium oxide dose-to-mother (DTM) technique, and the impact of maternal secretor status on the infant fecal microbiome and metabolome. Maternal secretor status did not alter the within-community (alpha) diversity, between-community (beta) diversity, or the relative abundance of bacterial taxa at the genus level. However, infants fed milk from secretor (Se+) mothers exhibited a lower level of fecal succinate, amino acids and their derivatives, and a higher level of 1,2-propanediol when compared to infants fed milk from non-secretor (Se-) mothers. Interestingly, for infants consuming milk from Se+ mothers, there was a correlation between the relative abundance of Bifidobacterium and Streptococcus, and between each of these genera and fecal metabolites that was not observed in infants receiving milk from Se- mothers. Our findings indicate that the secretor status of the mother impacts the gut microbiome of the exclusively breastfed infant.

Field-based detection of bacteria using nanopore sequencing: Method evaluation for biothreat detection in complex samples

From pathogen detection to genome or plasmid closure, the utility of the Oxford Nanopore Technologies (ONT) MinION for microbiological analysis has been well documented. The MinION's small footprint, portability, and real-time analytic capability situates it well to address challenges in the field of unbiased pathogen detection, as a component of a security investigation. To this end, a multicenter evaluation of the effect of alternative analytical approaches on the outcome of MinION-based sequencing, using a set of well-characterized samples, was explored in a field-based scenario. Three expert scientific response groups evaluated known bacterial DNA extracts as part of an international first responder (Chemical, Biological, Radiological) training exercise. Samples were prepared independently for analysis using the Rapid and/or Rapid PCR sequencing kits as per the best practices of each of the participating groups. Analyses of sequence data were in turn conducted using varied approaches including ONTs What's in my pot (WIMP) architecture and in-house computational pipelines. Microbial community composition and the ability of each approach to detect pathogens was compared. Each group demonstrated the ability to detect all species present in samples, although several organisms were detected at levels much lower than expected with some organisms even falling below 1% abundance. Several 'contaminant' near neighbor species were also detected, at low abundance. Regardless of the sequencing approach chosen, the observed composition of the bacterial communities diverged from the input composition in each of the analyses, although sequencing conducted using the rapid kit produced the least distortion when compared to PCR-based library preparation methods. One of the participating groups generated drastically lower sequencing output than the other groups, likely attributed to the limited computer hard drive capacity, and occasional disruption of the internet connection. These results provide further consideration for conducting unbiased pathogen identification within a field setting using MinION sequencing. However, the benefits of this approach in providing rapid results and unbiased detection must be considered along with the complexity of sample preparation and data analytics, when compared to more traditional methods. When utilized by trained scientific experts, with appropriate computational resources, the MinION sequencing device is a useful tool for field-based pathogen detection in mixed samples.

Integration of 168,000 samples reveals global patterns of the human gut microbiome

Understanding the factors that shape variation in the human microbiome is a major goal of research in biology. While other genomics fields have used large, pre-compiled compendia to extract systematic insights requiring otherwise impractical sample sizes, there has been no comparable resource for the 16S rRNA sequencing data commonly used to quantify microbiome composition. To help close this gap, we have assembled a set of 168,484 publicly available human gut microbiome samples, processed with a single pipeline and combined into the largest unified microbiome dataset to date. We use this resource, which is freely available at microbiomap.org, to shed light on global variation in the human gut microbiome. We find that Firmicutes, particularly Bacilli and Clostridia, are almost universally present in the human gut. At the same time, the relative abundance of the 65 most common microbial genera differ between at least two world regions. We also show that gut microbiomes in undersampled world regions, such as Central and Southern Asia, differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America. Moreover, humans in these overlooked regions likely harbor hundreds of taxa that have not yet been discovered due to this undersampling, highlighting the need for diversity in microbiome studies. We anticipate that this new compendium can serve the community and enable advanced applied and methodological research.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.

Human microbiome myths and misconceptions

Over the past two decades, interest in human microbiome research has increased exponentially. Regrettably, this increased activity has brought with it a degree of hype and misinformation, which can undermine progress and public confidence in the research. Here we highlight selected human microbiome myths and misconceptions that lack a solid evidence base. By presenting these examples, we hope to draw increased attention to the implications of inaccurate dogma becoming embedded in the literature, and the importance of acknowledging nuance when describing the complex human microbiome.

Comparison of DNA extraction methods for 16S rRNA gene sequencing in the analysis of the human gut microbiome

The gut microbiome is widely analyzed using high-throughput sequencing, such as 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing (SMS). DNA extraction is known to have a large impact on the metagenomic analyses. The aim of this study was to compare DNA extraction protocols for 16S sequencing. In that context, four commonly used DNA extraction methods were compared for the analysis of the gut microbiota. Commercial versions were evaluated against modified protocols using a stool preprocessing device (SPD, bioMérieux) upstream DNA extraction. Stool samples from nine healthy volunteers and nine patients with a Clostridium difficile infection were extracted with all protocols and 16S sequenced. Protocols were ranked using wet- and dry-lab criteria, including quality controls of the extracted genomic DNA, alpha-diversity, accuracy using a mock community of known composition and repeatability across technical replicates. SPD improved overall efficiency of three of the four tested protocols compared with their commercial version, in terms of DNA extraction yield, sample alpha-diversity, and recovery of Gram-positive bacteria. The best overall performance was obtained for the S-DQ protocol, SPD combined with the DNeasy PowerLyser PowerSoil protocol from QIAGEN. Based on this evaluation, we strongly believe that the use of such stool preprocessing device improves both the standardization and the quality of the DNA extraction in the human gut microbiome studies.

Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil

Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9-90.5%; species: 70.9-85.2% Bray-Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.

Effects of a wholegrain-rich diet on markers of colonic fermentation and bowel function and their associations with the gut microbiome: a randomised controlled cross-over trial

Background

Diets rich in whole grains are associated with health benefits. Yet, it remains unclear whether the benefits are mediated by changes in gut function and fermentation.

Objective

We explored the effects of whole-grain vs. refined-grain diets on markers of colonic fermentation and bowel function, as well as their associations with the gut microbiome.

Methods

Fifty overweight individuals with increased metabolic risk and a high habitual intake of whole grains (~69 g/day) completed a randomised cross-over trial with two 8-week dietary intervention periods comprising a whole-grain diet (≥75 g/day) and a refined-grain diet (<10 g/day), separated by a washout period of ≥6  weeks. A range of markers of colonic fermentation and bowel function were assessed before and after each intervention.

Results

The whole-grain diet increased the levels of faecal butyrate (p = 0.015) and caproate (p = 0.013) compared to the refined-grain diet. No changes in other faecal SCFA, BCFA or urinary levels of microbial-derived proteolytic markers between the two interventions were observed. Similarly, faecal pH remained unchanged. Faecal pH did however increase (p = 0.030) after the refined-grain diet compared to the baseline. Stool frequency was lower at the end of the refined-grain period compared to the end of the whole-grain diet (p = 0.001). No difference in faecal water content was observed between the intervention periods, however, faecal water content increased following the whole-grain period compared to the baseline (p = 0.007). Dry stool energy density was unaffected by the dietary interventions. Nevertheless, it explained 4.7% of the gut microbiome variation at the end of the refined-grain diet, while faecal pH and colonic transit time explained 4.3 and 5%, respectively. Several butyrate-producers (e.g., Faecalibacterium, Roseburia, Butyriciococcus) were inversely associated with colonic transit time and/or faecal pH, while the mucin-degraders Akkermansia and Ruminococcaceae showed the opposite association.

Conclusion

Compared with the refined-grain diet, the whole-grain diet increased faecal butyrate and caproate concentrations as well as stool frequency, emphasising that differences between whole and refined grains affect both colonic fermentation and bowel habits.

Evaluation of DNA extraction methods and direct PCR in metabarcoding of mock and marine bacterial communities

Recent advances in new molecular biology methods and next-generation sequencing (NGS) technologies have revolutionized metabarcoding studies investigating complex microbial communities from various environments. The inevitable first step in sample preparation is DNA extraction which introduces its own set of biases and considerations. In this study, we assessed the influence of five DNA extraction methods [B1: phenol/chloroform/isoamyl extraction, B2 and B3: isopropanol and ethanol precipitations, respectively-both modifications of B1, K1: DNeasy PowerWater Kit (QIAGEN), K2: modified DNeasy PowerWater Kit (QIAGEN) and direct PCR approach (P) that completely circumvents this step on community composition and DNA yield of mock and marine sample communities from the Adriatic Sea]. B1-B3 methods generally produced higher DNA yields and more similar microbial communities, but with higher interindividual variability. Each method demonstrated significant differences in a specific community structure, where rare taxa seem to play a crucial role. There was not one superior method closest to the theoretically expected mock community composition, they all demonstrated skewed ratios, but in a similar way which might be attributed to other factors, such as primer bias or 16S rRNA gene count for specific taxa. Direct PCR represents an interesting approach when high throughput in sample processing is required. We emphasize the importance of making a cautious decision about the choice of the extraction method or direct PCR approach, but even more importantly its consistent application throughout the study.

Learning from mistakes: challenges in finding holobiont factors from environmental samples and the importance of methodological consistency

The cause of harmful algal blooms has been a mystery, but research to elucidate its mechanism has progressed over the years thanks to genetic technologies. We have monitored toxic algae and its associated bacteria as a community, the so-called 'holobiont' in Chilean coastal waters for years from the perspective of bacteria as an algal bloom driver. This review describes the challenges of holobiont monitoring, specifically with respect to standardizing and compliance with the monitoring protocols to collect reliable and sustainable data. Further, we suggest adopting the high-throughput sequencing (HTS) standard operating procedure (SOP) by the International Human Microbiome to improve the quality and consistency of holobiont monitoring in the harmful algal world.

A Brief History of Microbial Study and Techniques for Exploring the Gastrointestinal Microbiome

Over the past 20 years, the study of microbial communities has benefited from simultaneous advancements across several fields resulting in a high-resolution view of human consortia. Although the first bacterium was described in the mid-1600s, the interest in community membership and function has not been a focus or feasible until recent decades. With strategies such as shotgun sequencing, microbes can be taxonomically profiled without culturing and their unique variants defined and compared across phenotypes. Approaches such as metatranscriptomics, metaproteomics, and metabolomics can define the current functional state of a population through the identification of bioactive compounds and significant pathways. Prior to sample collection in microbiome-based studies it is critical to evaluate the requirements of downstream analyses to ensure accurate processing and storage for generation of high data quality. A common pipeline for the analysis of human samples includes approval of collection protocols and method finalization, patient sample collection, sample processing, data analysis, and visualization. Human-based microbiome studies are inherently challenging but with the application of complementary multi-omic strategies there is an unbounded potential for discovery.

Optimizing DNA Extraction from Pediatric Stool for Diagnosis of Tuberculosis and Use in Next-Generation Sequencing Applications

The WHO has endorsed the use of stool samples for diagnosis of tuberculosis (TB) in children, and targeted next-generation sequencing (tNGS) of stool has been shown to support diagnosis and provide information about drug susceptibility (DS). Optimizing extraction of DNA from stool for sequencing is critical to ensure high diagnostic sensitivity and accurate DS information. Human stool samples were spiked with various concentrations of Mycobacterium bovis bacillus Calmette-Guérin (BCG), and DNA was extracted from the samples using four different DNA extraction kits. Each sample was subjected to quantitative PCR for identifying Mycobacterium tuberculosis complex bacteria and underwent further analysis to assess the overall DNA yield, fragment length, and purity. This same process was performed with 10 pediatric participants diagnosed with pulmonary TB, and the samples underwent tNGS. The FastDNA spin kit for soil showed the best results on model samples spiked with known quantities of BCG, compared to the other extraction methods evaluated. For clinical samples, the FastDNA and PowerFecal Pro DNA (PowerFecal) kits both showed an increase in the overall DNA quantity, M. tuberculosis-specific DNA quantity, and successful targeted sequencing when testing was performed on stool samples, compared to the two other kits. Three samples extracted via PowerFecal and three samples extracted via FastDNA (from different patients) provided successful sequencing data, with an average depth of coverage of the rpoB region for FastDNA of 298 (range, 107 to 550) and for PowerFecal of 310 (range, 182 to 474), results that were comparable to one another (P = 0.946). The PowerFecal Pro and FastDNA spin kits were superior for extracting DNA from pediatric stool samples for tNGS. IMPORTANCE This is the first study to compare Mycobacterium tuberculosis DNA extraction techniques from pediatric stool samples for use with sequencing technologies. It provides an important starting point for other researchers to isolate quality DNA for this purpose to further the field and to continue to optimize protocols and approaches.

The Contribution of the Human Oral Microbiome to Oral Disease: A Review

The oral microbiome is an emerging field that has been a topic of discussion since the development of next generation sequencing and the implementation of the human microbiome project. This article reviews the current literature surrounding the oral microbiome, briefly highlighting most recent methods of microbiome characterization including cutting edge omics, databases for the microbiome, and areas with current gaps in knowledge. This article also describes reports on microorganisms contained in the oral microbiome which include viruses, archaea, fungi, and bacteria, and provides an in-depth analysis of their significant roles in tissue homeostasis. Finally, we detail key bacteria involved in oral disease, including oral cancer, and the current research surrounding their role in stimulation of inflammatory cytokines, the role of gingival crevicular fluid in periodontal disease, the creation of a network of interactions between microorganisms, the influence of the planktonic microbiome and cospecies biofilms, and the implications of antibiotic resistance. This paper provides a comprehensive literature analysis while also identifying gaps in knowledge to enable future studies to be conducted.

The structural discrepancy between the small and large gut microbiota of Asiatic toad (Bufo gargarizans) during hibernation

Hibernating amphibians are suitable for the research on the adaptation of gut microbiota to long-term fasting and cold stresses. However, the previous studies mainly focus on the large or whole gut microbiota but not the small gut microbiota. To test the structural discrepancy between the small and large gut microbiota during hibernation, we performed two independent batches of 16S rRNA gene amplicon sequencing to profile the small and large gut microbiota of hibernating Asiatic toad (Bufo gargarizans) from two wild populations. Both batches of data revealed that Proteobacteria, Bacteroidetes, and Firmicutes were the three most dominant phyla in the small and large gut microbiota. Three core OTUs with 100% occurrence in all gut microbiotas were annotated as Pseudomonas. A significant structural discrepancy was detected between the small and large gut microbiota. For instance, Proteobacteria assembled in the small intestine with a higher proportion than it did in the large intestine, but Bacteroidetes and Firmicutes assembled in the large intestine with a higher proportion than they did in the small intestine. The large gut microbiota exhibited higher diversity than the small gut microbiota. Nevertheless, a severe batch effect existed in the structural analysis of the gut microbiotas. The large gut microbiota showed a better resistance to the batch effect than the small gut microbiota did. This study provides preliminary evidence that microbes assemble in the small and large intestines of amphibians with discrepant patterns during hibernation.

Examining Different Analysis Protocols Targeting Hospital Sanitary Facility Microbiomes

Indoor spaces exhibit microbial compositions that are distinctly dissimilar from one another and from outdoor spaces. Unique in this regard, and a topic that has only recently come into focus, is the microbiome of hospitals. While the benefits of knowing exactly which microorganisms propagate how and where in hospitals are undoubtedly beneficial for preventing hospital-acquired infections, there are, to date, no standardized procedures on how to best study the hospital microbiome. Our study aimed to investigate the microbiome of hospital sanitary facilities, outlining the extent to which hospital microbiome analyses differ according to sample-preparation protocol. For this purpose, fifty samples were collected from two separate hospitals-from three wards and one hospital laboratory-using two different storage media from which DNA was extracted using two different extraction kits and sequenced with two different primer pairs (V1-V2 and V3-V4). There were no observable differences between the sample-preservation media, small differences in detected taxa between the DNA extraction kits (mainly concerning Propionibacteriaceae), and large differences in detected taxa between the two primer pairs V1-V2 and V3-V4. This analysis also showed that microbial occurrences and compositions can vary greatly from toilets to sinks to showers and across wards and hospitals. In surgical wards, patient toilets appeared to be characterized by lower species richness and diversity than staff toilets. Which sampling sites are the best for which assessments should be analyzed in more depth. The fact that the sample processing methods we investigated (apart from the choice of primers) seem to have changed the results only slightly suggests that comparing hospital microbiome studies is a realistic option. The observed differences in species richness and diversity between patient and staff toilets should be further investigated, as these, if confirmed, could be a result of excreted antimicrobials.

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.

Mechanisms, therapeutic implications, and methodological challenges of gut microbiota and cardiovascular diseases: a position paper by the ESC Working Group on Coronary Pathophysiology and Microcirculation

The human gut microbiota is the microbial ecosystem in the small and large intestines of humans. It has been naturally preserved and evolved to play an important role in the function of the gastrointestinal tract and the physiology of its host, protecting from pathogen colonization, and participating in vitamin synthesis, the functions of the immune system, as well as glucose homeostasis and lipid metabolism, among others. Mounting evidence from animal and human studies indicates that the composition and metabolic profiles of the gut microbiota are linked to the pathogenesis of cardiovascular disease, particularly arterial hypertension, atherosclerosis, and heart failure. In this review article, we provide an overview of the function of the human gut microbiota, summarize, and critically address the evidence linking compositional and functional alterations of the gut microbiota with atherosclerosis and coronary artery disease and discuss the potential of strategies for therapeutically targeting the gut microbiota through various interventions.

Novel Virus Identification through Metagenomics: A Systematic Review

Metagenomic Next Generation Sequencing (mNGS) allows the evaluation of complex microbial communities, avoiding isolation and cultivation of each microbial species, and does not require prior knowledge of the microbial sequences present in the sample. Applications of mNGS include virome characterization, new virus discovery and full-length viral genome reconstruction, either from virus preparations enriched in culture or directly from clinical and environmental specimens. Here, we systematically reviewed studies that describe novel virus identification through mNGS from samples of different origin (plant, animal and environment). Without imposing time limits to the search, 379 publications were identified that met the search parameters. Sample types, geographical origin, enrichment and nucleic acid extraction methods, sequencing platforms, bioinformatic analytical steps and identified viral families were described. The review highlights mNGS as a feasible method for novel virus discovery from samples of different origins, describes which kind of heterogeneous experimental and analytical protocols are currently used and provides useful information such as the different commercial kits used for the purification of nucleic acids and bioinformatics analytical pipelines.

Pre-transplant Ratio of Firmicutes/Bacteroidetes of Gut Microbiota as a Potential Biomarker of Allograft Rejection in Renal Transplant Recipients

The advent of technologies has made allogenic transplantation a potential curative therapy for end-stage renal diseases, but the episodes of rejection still remain as one of the challenges in the post-transplant scenario. In the recent years, several human and animal studies have elucidated that gut microbial dysbiosis is closely linked with allogenic transplantation and post-transplant complications. But most of the studies focused on the use of high through-put sequencing technologies to analyze gut microbiota despite of its high cost, analysis and time constraints. Hence, in this work we aimed to study the impact of the two dominant gut phyla Firmicutes and Bacteroidetes on 38 renal transplant recipients, before and after transplantation and to find its association with allograft rejection. Significant changes (p<0.01) were observed in the relative abundances of the phyla Firmicutes and Bacteroidetes at pre- and post-transplant period. We have also found that the recipients who had an increase in Firmicutes/Bacteroidetes (F/B) ratio before transplant were highly prone to rejection in the first-year post-transplant. The Receiver Operating Characteristic (ROC) curve analysis has shown that the ratio of F/B were able to discriminate between rejection and non-rejection cases with an Area under the ROC Curve (AUC) of 0.91. Additionally, we observed that the ratio of F/B have reduced during the time of rejection postulating that gut microbial dysbiosis has more association with rejection. Thus, the assessment of F/B ratio using qPCR would be of a more practical approach for diagnosis and monitoring of graft function in a cost-effective and timely manner.

Developing whole cell standards for the microbiome field

BACKGROUND

Effective standardisation of the microbiome field is essential to facilitate global translational research and increase the reproducibility of microbiome studies. In this study, we describe the development and validation of a whole cell reference reagent specific to the gut microbiome by the UK National Institute for Biological Standards and Control. We also provide and test a two-step reporting framework to allow microbiome researchers to quickly and accurately validate choices of DNA extraction, sequencing, and bioinformatic pipelines.

RESULTS

Using 20 strains that are commonly found in the gut, we developed a whole cell reference reagent (WC-Gut RR) for the evaluation of the DNA extraction protocols commonly used in microbiome pipelines. DNA was first analysed using the physicochemical measures of yield, integrity, and purity, which demonstrated kits widely differed in the quality of the DNA they produced. Importantly, the combination of the WC-Gut RR and the three physicochemical measures allowed us to differentiate clearly between kit performance. We next assessed the ability of WC-Gut RR to evaluate kit performance in the reconstitution of accurate taxonomic profiles. We applied a four-measure framework consisting of Sensitivity, false-positive relative abundance (FPRA), Diversity, and Similarity as previously described for DNA reagents. Using the WC-Gut RR and these four measures, we could reliably identify the DNA extraction kits' biases when using with both 16S rRNA sequencing and shotgun sequencing. Moreover, when combining this with complementary DNA standards, we could estimate the relative bias contributions of DNA extraction kits vs bioinformatic analysis. Finally, we assessed WC-Gut RR alongside other commercially available reagents. The analysis here clearly demonstrates that reagents of lower complexity, not composed of anaerobic and hard-to-lyse strains from the gut, can artificially inflate the performance of microbiome DNA extraction kits and bioinformatic pipelines.

CONCLUSIONS

We produced a complex whole cell reagent that is specific for the gut microbiome and can be used to evaluate and benchmark DNA extractions in microbiome studies. Used alongside a DNA standard, the NIBSC DNA-Gut-Mix RR helps estimating where biases occur in microbiome pipelines. In the future, we aim to establish minimum thresholds for data quality through an interlaboratory collaborative study. Video Abstract.

The Effects of DNA Extraction Kits and Primers on Prokaryotic and Eukaryotic Microbial Community in Freshwater Sediments

DNA based sequencing technology has revolutionized the field of microbial ecology and environmental studies. However, biases can be introduced at all experimental steps and, thus, affect the interpretation of microbial community. So far, previous studies on the biases introduced from the key steps of DNA extraction and primer sets mainly focused on the bacterial communities in soil or sediment samples, while little is known about the effect on the eukaryotic microbial communities. Here, we studied the effects of three different DNA extraction kits on both prokaryotic and micro-eukaryotic communities by 16S and 18S rRNA gene amplicon sequencing, and further disentangled the influence of primer choice on the micro-eukaryotic communities. Our results showed that the FastDNA SPIN Kit for Soil and DNeasy PowerSoil Kit produced much higher DNA yield with good reproducibility, and observed more eukaryotic OTUs compared to the MinkaGene DNA extraction kit, but all three kits exhibited comparable ability in recovering bacterial alpha diversity. Of the two primer sets, both targeting the V4 region of the 18S rRNA gene, the TAR primer set detected higher number of unique OTUs than the EK primer set, while the EK primer set resulted in longer amplicons and better reproducibility between replicates. Based on our findings, we recommend using the DNeasy PowerSoil Kit with the EK primer set to capture the abundant micro-eukaryotic taxa from freshwater sediment samples. If a more complete picture of the eukaryotic microbial community is desired, the TAR primer set in combination with the FastDNA SPIN Kit is more efficient in this study.

The standardisation of the approach to metagenomic human gut analysis: from sample collection to microbiome profiling

In recent years, the number of metagenomic studies increased significantly. Wide range of factors, including the tremendous community complexity and variability, is contributing to the challenge in reliable microbiome community profiling. Many approaches have been proposed to overcome these problems making hardly possible to compare results of different studies. The significant differences between procedures used in metagenomic research are reflected in a variation of the obtained results. This calls for the need for standardisation of the procedure, to reduce the confounding factors originating from DNA isolation, sequencing and bioinformatics analyses in order to ensure that the differences in microbiome composition are of a true biological origin. Although the best practices for metagenomics studies have been the topic of several publications and the main aim of the International Human Microbiome Standard (IHMS) project, standardisation of the procedure for generating and analysing metagenomic data is still far from being achieved. To highlight the difficulties in the standardisation of metagenomics methods, we thoroughly examined each step of the analysis of the human gut microbiome. We tested the DNA isolation procedure, preparation of NGS libraries for next-generation sequencing, and bioinformatics analysis, aimed at identifying microbial taxa. We showed that the homogenisation time is the leading factor impacting sample diversity, with the recommendation for a shorter homogenisation time (10 min). Ten minutes of homogenisation allows for better reflection of the bacteria gram-positive/gram-negative ratio, and the obtained results are the least heterogenous in terms of beta-diversity of samples microbial composition. Besides increasing the homogenisation time, we observed further potential impact of the library preparation kit on the gut microbiome profiling. Moreover, our analysis revealed that the choice of the library preparation kit influences the reproducibility of the results, which is an important factor that has to be taken into account in every experiment. In this study, a tagmentation-based kit allowed for obtaining the most reproducible results. We also considered the choice of the computational tool for determining the composition of intestinal microbiota, with Kraken2/Bracken pipeline outperforming MetaPhlAn2 in our in silico experiments. The design of an experiment and a detailed establishment of an experimental protocol may have a serious impact on determining the taxonomic profile of the intestinal microbiome community. Results of our experiment can be helpful for a wide range of studies that aim to better understand the role of the gut microbiome, as well as for clinical purposes.

Opportunities and challenges of using metagenomic data to bring uncultured microbes into cultivation

Although there is now an extensive understanding of the diversity of microbial life on earth through culture-independent metagenomic DNA sequence analyses, the isolation and cultivation of microbes remains critical to directly study them and confirm their metabolic and physiological functions, and their ecological roles. The majority of environmental microbes are as yet uncultured however; therefore, bringing these rare or poorly characterized groups into culture is a priority to further understand microbiome functions. Moreover, cultivated isolates may find utility in a range of applications, such as new probiotics, biocontrol agents, and agents for industrial processes. The growing abundance of metagenomic and meta-transcriptomic sequence information from a wide range of environments provides more opportunities to guide the isolation and cultivation of microbes of interest. In this paper, we discuss a range of successful methodologies and applications that have underpinned recent metagenome-guided isolation and cultivation of microbe efforts. These approaches include determining specific culture conditions to enrich for taxa of interest, to more complex strategies that specifically target the capture of microbial species through antibody engineering and genome editing strategies. With the greater degree of genomic information now available from uncultivated members, such as via metagenome-assembled genomes, the theoretical understanding of their cultivation requirements will enable greater possibilities to capture these and ultimately gain a more comprehensive understanding of the microbiomes. Video Abstract.

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.

Differences in the gut microbiome composition of Korean children and adult samples based on different DNA isolation kits

Recent studies have revealed that the composition of human gut microbiota varies according to region, race, age, diet, living environment, and sampling and DNA extraction method. The purpose of this study was to broaden our understanding of the intestinal microbial composition of Koreans by conducting a 16S rRNA amplicon sequencing on 78 Korean samples composed of adults, children, normal and obese groups. We compared the microbiome composition and diversity of these groups at different levels including the phylum and genus level using two different stool DNA extraction kits of QIAamp® PowerFecal® DNA Kit (Qiagen, Hilden, Germany) and CT Max Fecal DNA Kit (Ct bio, Korea). We found that Ct bio (Ct) kit recovered higher DNA yields and OTUs than QIAamp® PowerFecal® DNA Kit (Qia). The Ct kit, which adopted more rigorous bead beating method, detected the most Gram-positive (G+) bacteria, Firmicutes, at the Phylum level, whereas the Qia kit, which used a less rigorous cell lysis method, found the most Gram-negative (G-) bacteria, Bacteroidetes. The Firmicutes-to-Bacteroidetes (F/B) ratio showed no significant difference between the obese and the normal groups of same kit; however, they were significantly different with two different kits. There was a difference in the intestinal flora between healthy Korean adults and children. The taxa that differed significantly between the adults and children were Bacteroides, Bifidobacterium, Prevotella, and Subdoligranulum. There was no significant difference in the intestinal flora between the normal weight group and the obese group in adults and children, respectively. This is probably because the difference in body mass index (BMI) between the sample groups collected in this study is statistically significant, but it is not large enough to show a clear difference in the flora. Therefore, these results should be interpreted with caution while considering the BMI values and Korean obesity criterion together.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

Advancements in next-generation sequencing technology have dramatically reduced the cost and increased the ease of microbial whole genome sequencing. This approach is revolutionizing the identification and analysis of foodborne microbial pathogens, facilitating expedited detection and mitigation of foodborne outbreaks, improving public health outcomes, and limiting costly recalls. However, next-generation sequencing is still anchored in the traditional laboratory practice of the selection and culture of a single isolate. Metagenomic-based approaches, including metabarcoding and shotgun and long-read metagenomics, are part of the next disruptive revolution in food safety diagnostics and offer the potential to directly identify entire microbial communities in a single food, ingredient, or environmental sample. In this review, metagenomic-based approaches are introduced and placed within the context of conventional detection and diagnostic techniques, and essential considerations for undertaking metagenomic assays and data analysis are described. Recent applications of the use of metagenomics for food safety are discussed alongside current limitations and knowledge gaps and new opportunities arising from the use of this technology.

HIGHLIGHTS

Considerations and best practices in animal science 16S ribosomal RNA gene sequencing microbiome studies

Microbiome studies in animal science using 16S rRNA gene sequencing have become increasingly common in recent years as sequencing costs continue to fall and bioinformatic tools become more powerful and user-friendly. The combination of molecular biology, microbiology, microbial ecology, computer science, and bioinformatics-in addition to the traditional considerations when conducting an animal science study-makes microbiome studies sometimes intimidating due to the intersection of different fields. The objective of this review is to serve as a jumping-off point for those animal scientists less familiar with 16S rRNA gene sequencing and analyses and to bring up common issues and concerns that arise when planning an animal microbiome study from design through analysis. This review includes an overview of 16S rRNA gene sequencing, its advantages, and its limitations; experimental design considerations such as study design, sample size, sample pooling, and sample locations; wet lab considerations such as field handing, microbial cell lysis, low biomass samples, library preparation, and sequencing controls; and computational considerations such as identification of contamination, accounting for uneven sequencing depth, constructing diversity metrics, assigning taxonomy, differential abundance testing, and, finally, data availability. In addition to general considerations, we highlight some special considerations by species and sample type.

Molecular diagnostics of Salmonella and Campylobacter in human/animal fecal samples remain feasible after long-term sample storage without specific requirements

Rapid advances in the development of sequencing technologies, numbers of commercial providers and diminishing costs have made DNA-based identification and diagnostics increasingly accessible to doctors and laboratories, eliminating the need for local investments in expensive technology and training or hiring of skilled technicians. However, reliable and comparable molecular analyses of bacteria in stool samples are dependent on storage and workflow conditions that do not introduce post-sampling bias, the most important factor being the need to keep the DNA at a stable detectable level. For that reason, there may remain other prohibitively costly requirements for cooling or freezing equipment or special chemical additives.

This study investigates the diagnostic detectability of Salmonella and Campylobacter DNA in human, pig and chicken stool samples, stored at different temperatures and with different preservation methods. Stool samples were spiked with 10⁶ CFU/mL of both Salmonella and Campylobacter strains stored at −20 °C, 5 °C and 20 °C (Room temperature, RT) and treated with either RNAlater, EDTA or Silica/ethanol. DNA was extracted at 9 different time points within 30 days and quantified by Qubit (total DNA) and qPCR (Salmonella and Campylobacter DNA). We found no statistically significant differences among the different preservation methods, and DNA from both species was easily detected at all time points and at all temperatures, both with and without preservation. This suggests that infections by these bacteria can be diagnosed and possibly also analysed in further detail simply by taking a stool sample in any suitable sealed container that can be transported to laboratory analysis without special storage or preservation requirements. We briefly discuss how this finding can benefit infection control in both developed and developing countries.

Gut microbiome and its meta-omics perspectives: profound implications for cardiovascular diseases

Cardiovascular diseases (CVDs) still remain the leading concern of global health, accounting for approximately 17.9 million deaths in 2016. The pathogenetic mechanisms of CVDs are multifactorial and incompletely understood. Recent evidence has shown that alterations in the gut microbiome and its associated metabolites may influence the pathogenesis and progression of CVDs such as atherosclerosis, heart failure, hypertension, and arrhythmia, yet the underlying links are not fully elucidated. Owing to the progress in next-generation sequencing techniques and computational strategies, researchers now are available to explore the emerging links to the genomes, transcriptomes, proteomes, and metabolomes in parallel meta-omics approaches, presenting a panoramic vista of culture-independent microbial investigation. This review aims to outline the characteristics of meta-omics pipelines and provide a brief overview of current applications in CVDs studies which can be practical for addressing crucial knowledge gaps in this field, as well as to shed its light on cardiovascular risk biomarkers and therapeutic intervention in the near future.

ddPCR allows 16S rRNA gene amplicon sequencing of very small DNA amounts from low-biomass samples

BACKGROUND

One limiting factor of short amplicon 16S rRNA gene sequencing approaches is the use of low DNA amounts in the amplicon generation step. Especially for low-biomass samples, insufficient or even commonly undetectable DNA amounts can limit or prohibit further analysis in standard protocols.

RESULTS

Using a newly established protocol, very low DNA input amounts were found sufficient for reliable detection of bacteria using 16S rRNA gene sequencing compared to standard protocols. The improved protocol includes an optimized amplification strategy by using a digital droplet PCR. We demonstrate how PCR products are generated even when using very low concentrated DNA, unable to be detected by using a Qubit. Importantly, the use of different 16S rRNA gene primers had a greater effect on the resulting taxonomical profiles compared to using high or very low initial DNA amounts.

CONCLUSION

Our improved protocol takes advantage of ddPCR and allows faithful amplification of very low amounts of template. With this, samples of low bacterial biomass become comparable to those with high amounts of bacteria, since the first and most biasing steps are the same. Besides, it is imperative to state DNA concentrations and volumes used and to include negative controls indicating possible shifts in taxonomical profiles. Despite this, results produced by using different primer pairs cannot be easily compared.

Bovine Milk Microbiota: Comparison among Three Different DNA Extraction Protocols To Identify a Better Approach for Bacterial Analysis

The bovine udder is colonized by a huge quantity of microorganisms that constitute the intramammary ecosystem, with a specific role in modulating not only udder homeostasis and mastitis susceptibility, but also the quality of the dairy products. However, generating high-quality bacterial DNA can be critical, especially starting from a complex biological matrix like milk, characterized by high fat, protein, and calcium contents. Here, bacterial DNA was recovered from a commercial ultra-high-temperature (UHT) milk sample artificially spiked with a predetermined mock community composition and from three bulk tank milk (raw milk) samples. The DNA was isolated using three different protocols to evaluate the effect of the extraction procedures on the milk microbiota composition. In the mock community experiment, the bacterial profiles generated by the three DNA extraction protocols were profoundly different, with the genera Staphylococcus, Lactobacillus, Listeria, and Salmonella underestimated by all the protocols. Only one protocol revealed values close to the expected abundances for Escherichia/Shigella spp., Bacillus spp., Enterococcus spp., and Pseudomonas spp. On the other hand, the nonspiked UHT milk sample exhibited a similar microbiota composition, revealing the prevalence of Acinetobacter spp., for all the DNA extraction protocols. For the raw milk samples, the three DNA extraction kits performed differently, revealing significant separations in both the microbial richness (alpha diversity) and composition (beta diversity). Our study highlights the presence of significant differences among these procedures, probably due to the different DNA extracting capacities and to the different properties of the milk samples, revealing that the selection of DNA extraction protocol is a critical point.

IMPORTANCE The advance of high-throughput technologies has increased our knowledge of the world of microorganisms, especially of microbial populations inhabiting living animals. This study provides evidence that milk, as other complex sources, could be critical for generating high-quality DNA for microbiota analysis. In addition, it demonstrates that the microbial population highlighted by metagenomic studies changes in relation to different DNA extraction procedures, revealing that attention should be paid especially when comparing different studies.

Symbiosis and Dysbiosis of the Human Mycobiome

The influence of microbiological species has gained increased visibility and traction in the medical domain with major revelations about the role of bacteria on symbiosis and dysbiosis. A large reason for these revelations can be attributed to advances in deep-sequencing technologies. However, the research on the role of fungi has lagged. With the continued utilization of sequencing technologies in conjunction with traditional culture assays, we have the opportunity to shed light on the complex interplay between the bacteriome and the mycobiome as they relate to human health. In this review, we aim to offer a comprehensive overview of the human mycobiome in healthy and diseased states in a systematic way. The authors hope that the reader will utilize this review as a scaffolding to formulate their understanding of the mycobiome and pursue further research.

MetaGeneBank: a standardized database to study deep sequenced metagenomic data from human fecal specimen

BACKGROUND

Microbiome big data from population-scale cohorts holds the key to unleash the power of microbiomes to overcome critical challenges in disease control, treatment and precision medicine. However, variations introduced during data generation and processing limit the comparisons among independent studies in respect of interpretability. Although multiple databases have been constructed as platforms for data reuse, they are of limited value since only raw sequencing files are considered.

DESCRIPTION

Here, we present MetaGeneBank, a standardized database that provides details on sample collection and sequencing, and abundances of genes, microbiota and molecular functions for 4470 raw sequencing files (over 12 TB) collected from 16 studies covering over 10 types of diseases and 14 countries using a unified data-processing pipeline. The incorporation of tools that enable browsing and searching with descriptive attributes, gene sequences, microbiota and functions makes the database user-friendly. We found that the source of specimen contributes more than sequencing centers or platforms to the variations of microbiota. Special attention should be paid when re-analyzing sequencing files from different countries.

CONCLUSIONS

Collectively, MetaGeneBank provides a gateway to utilize the untapped potential of gut metagenomic data in helping fighting against human diseases. With the continuous updating of the database in terms of data volume, data types and sample types, MetaGeneBank would undoubtedly be the benchmarking database in the future in respect of data reuse, and would be valuable in translational science.

Exploring Semi-Quantitative Metagenomic Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol

The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed for characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenge. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Here, we propose a computational and experimental protocol for whole-genome semi-quantitative metagenomic studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatics protocol to analyze ONT sequences taxonomically and functionally and optimized preanalytic protocols, including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities, which reflect naturally occurring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina, and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. This protocol can be implemented in a clinical or research setting, bringing rapid personalized whole-genome profiling of target microbiome species.

Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations

Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal material over three timepoints. We demonstrated that spot sampling of stool results in variable detection of some microbial members, and inconsistent levels of SCFA; therefore, sample homogenization prior to subsequent analysis or subsampling is recommended. We also identify a trend in microbial and metabolite composition that shifts over two consecutive stool collections less than 25 h apart. Lastly, we show significant differences in bacterial composition that result from collecting stool samples in OMNIgene·Gut tube (DNA Genotec) or Stool Nucleic Acid Collection and Preservation Tube (NORGEN) compared to immediate freezing. To assist with planning fecal sample collection and storage procedures for microbiome investigations with multiple analyses, we recommend participants to collect the first full bowel movement of the day and freeze the sample immediately after collection.

Optimized bacterial DNA isolation method for microbiome analysis of human tissues

Recent advances in microbiome sequencing have rendered new insights into the role of the microbiome in human health with potential clinical implications. Unfortunately, the presence of host DNA in tissue isolates has hampered the analysis of host‐associated bacteria. Here, we present a DNA isolation protocol for tissue, optimized on biopsies from resected human colons (~2–5 mm in size), which includes reduction of human DNA without distortion of relative bacterial abundance at the phylum level. We evaluated which concentrations of Triton and saponin lyse human cells and leave bacterial cells intact, in combination with DNAse treatment to deplete released human DNA. Saponin at a concentration of 0.0125% in PBS lysed host cells, resulting in a 4.5‐fold enrichment of bacterial DNA while preserving the relative abundance of Firmicutes, Bacteroidetes, γ‐Proteobacteria, and Actinobacteria assessed by qPCR. Our optimized protocol was validated in the setting of two large clinical studies on 521 in vivo acquired colon biopsies of 226 patients using shotgun metagenomics. The resulting bacterial profiles exhibited alpha and beta diversities that are similar to the diversities found by 16S rRNA amplicon sequencing. A direct comparison between shotgun metagenomics and 16S rRNA amplicon sequencing of 15 forceps tissue biopsies showed similar bacterial profiles and a similar Shannon diversity index between the sequencing methods. Hereby, we present the first protocol for enriching bacterial DNA from tissue biopsies that allows efficient isolation of all bacteria. Our protocol facilitates analysis of a wide spectrum of bacteria of clinical tissue samples improving their applicability for microbiome research.

Evaluation of three different concentration and extraction methods for recovery efficiency of human adenovirus and human rotavirus virus A

Routine wastewater treatment plants (WWTPs) effluents monitoring is essential because of enteric viruses' low infectious dose beyond molecular detectability. In current study methods for concentration and extraction, inter-method compatibility and recovery efficiency of spiked human adenovirus (HAdV) and human rotavirus A (RVA) were evaluated. For virus concentration, polyethylene glycol precipitation (PEG), charged membrane-based adsorption/elution (CMAE), and glass wool-based concentration (GW) methods were used. Nucleic acid was extracted by PowerViral™ Environmental RNA/DNA Isolation (POW), ZymoBIOMICS™ RNA extraction (ZYMO) and Wizard® Genomic DNA Purification (WGDP) and samples were analyzed by Real-Time PCR. CMAE method yielded significantly higher concentrations for both ARQ (Armored-RNA Quant) and RVA compared to PEG (P =  0.001 and 0.003) and GW (P <  0.0001). Highest HAdV concentration was obtained by PEG (P =  0.001 and < 0.0001) in relation to CMAE and GW. ZYMO yielded a significantly higher ARQ and RVA concentrations (P =  0.03 and 0.0057), whereas significantly higher concentration was obtained by POW for HAdV (P =  0.032). CMAE × ZYMO achieved the highest recovery efficiencies for ARQ (69.77 %) and RVA (64.25, respectively, while PEG × POW present efficiency of 9.7 % for HAdV. These findings provide guidance for understanding of method-related biases for viral recovery efficiency.

Optimisation of sample storage and DNA extraction for human gut microbiota studies​

Background

New developments in next-generation sequencing technologies and massive data received from this approach open wide prospects for personalised medicine and nutrition studies. Metagenomic analysis of the gut microbiota is paramount for the characterization of human health and wellbeing. Despite the intensive research, there is a huge gap and inconsistency between different studies due to the non-standardised and biased pipeline. Methodical and systemic understanding of every stage in the process is necessary to overcome all bottlenecks and grey zones of gut microbiota studies, where all details and interactions between processes are important.

Results

Here we show that an inexpensive, but reliable iSeq 100 platform is an excellent tool to perform the analysis of the human gut microbiota by amplicon sequencing of the 16 S rRNA gene. Two commercial DNA extraction kits and different starting materials performed similarly regarding the taxonomic distribution of identified bacteria. DNA/RNA Shield reagent proved to be a reliable solution for stool samples collection, preservation, and storage, as the storage of faecal material in DNA/RNA Shield for three weeks at different temperatures and thawing cycles had a low impact on the bacterial distribution.

Conclusions

Altogether, a thoroughly elaborated pipeline with close attention to details ensures high reproducibility with significant biological but not technical variations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02233-y.

Evaluation of commercially available DNA extraction kits for the analysis of the broiler chicken cecal microbiota

16S rRNA gene amplicon sequencing is a state of the art technology to analyze bacterial communities via microbiome profiling. Choosing an appropriate DNA extraction protocol is crucial for characterizing the microbial community and can be challenging, especially when preliminary knowledge about the sample matrix is scarce. The aim of the present study was to evaluate seven commercial DNA extraction kits suitable for 16S rRNA gene amplicon sequencing of the bacterial community of the chicken cecum, taking into account different criteria such as high technical reproducibility, high bacterial diversity and easy handling. The DNA extraction kits differed strongly with respect to extractable DNA quantity, DNA quality, technical reproducibility and bacterial diversity determined after 16S rRNA gene amplicon sequencing and subsequent bioinformatic and biostatistical data processing. While some of the DNA extraction protocols under-represented specific bacterial community members, the removal of PCR inhibitors supported technical reproducibility and subsequently enhanced the recovered bacterial diversity from the chicken cecum community. In conclusion, the removal of PCR inhibitors from the sample matrix seemed to be one of the main drivers for a consistent representation of the bacterial community even of low abundant taxa in chicken cecum samples.

The Importance of Objective Stool Classification in Fecal 1H-NMR Metabolomics: Exponential Increase in Stool Crosslinking Is Mirrored in Systemic Inflammation and Associated to Fecal Acetate and Methionine

Past studies strongly connected stool consistency-as measured by Bristol Stool Scale (BSS)-with microbial gene richness and intestinal inflammation, colonic transit time and metabolome characteristics that are of clinical relevance in numerous gastro intestinal conditions. While retention time, defecation rate, BSS but not water activity have been shown to account for BSS-associated inflammatory effects, the potential correlation with the strength of a gel in the context of intestinal forces, abrasion, mucus imprinting, fecal pore clogging remains unexplored as a shaping factor for intestinal inflammation and has yet to be determined. Our study introduced a minimal pressure approach (MP) by probe indentation as measure of stool material crosslinking in fecal samples. Results reported here were obtained from 170 samples collected in two independent projects, including males and females, covering a wide span of moisture contents and BSS. MP values increased exponentially with increasing consistency (i.e., lower BSS) and enabled stratification of samples exhibiting mixed BSS classes. A trade-off between lowest MP and highest dry matter content delineated the span of intermediate healthy density of gel crosslinks. The crossectional transects identified fecal surface layers with exceptionally high MP and of <5 mm thickness followed by internal structures with an order of magnitude lower MP, characteristic of healthy stool consistency. The MP and BSS values reported in this study were coupled to reanalysis of the PlanHab data and fecal 1H-NMR metabolomes reported before. The exponential association between stool consistency and MP determined in this study was mirrored in the elevated intestinal and also systemic inflammation and other detrimental physiological deconditioning effects observed in the PlanHab participants reported before. The MP approach described in this study can be used to better understand fecal hardness and its relationships to human health as it provides a simple, fine scale and objective stool classification approach for the characterization of the exact sampling locations in future microbiome and metabolome studies.

Toward Best Practice in Livestock Microbiota Research: A Comprehensive Comparison of Sample Storage and DNA Extraction Strategies

Understanding the roles of microorganisms in the animal gastrointestinal microenvironment is highly important for the development of effective strategies to manage and manipulate these microbial communities. In order to guide future animal gut microbiota research projects and standardization efforts, we have conducted a systematic comparison of 10 currently used sample preservation and DNA extraction approaches for pig and chicken microbiota samples and quantified their effects on bacterial DNA yield, quality, integrity, and on the resulting sequence-based bacterial composition estimates. The results showed how key stages of conducting a microbiota study, including the sample storage and DNA extraction, can substantially affect DNA recovery from the microbial community, and therefore, biological interpretation in a matrix-dependent manner. Our results highlight the fact that the influence of storage and extraction methods on the resulting microbial community structure differed by sample type, even within the same species. As the effects of these technical steps are potentially large compared with the real biological variability to be explained, standardization is crucial for accelerating progress in the area of livestock microbiota research. This study provided a framework to assist future animal gut microbiota research projects and standardization efforts.

Methods for exploring the faecal microbiome of premature infants: a review

The premature infant gut microbiome plays an important part in infant health and development, and recognition of the implications of microbial dysbiosis in premature infants has prompted significant research into these issues. The approaches to designing investigations into microbial populations are many and varied, each with its own benefits and limitations. The technique used can influence results, contributing to heterogeneity across studies. This review aimed to describe the most common techniques used in researching the preterm infant microbiome, detailing their various limitations. The objective was to provide those entering the field with a broad understanding of available methodologies, so that the likely effects of their use can be factored into literature interpretation and future study design. We found that although many techniques are used for characterising the premature infant microbiome, 16S rRNA short amplicon sequencing is the most common. 16S rRNA short amplicon sequencing has several benefits, including high accuracy, discoverability and high throughput capacity. However, this technique has limitations. Each stage of the protocol offers opportunities for the injection of bias. Bias can contribute to variability between studies using 16S rRNA high throughout sequencing. Thus, we recommend that the interpretation of previous results and future study design be given careful consideration.

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

A cross-sectional analysis from the Mykinso Cohort Study: establishing reference ranges for Japanese gut microbial indices

The purpose of this study was to establish reference ranges for gut microbial indices by collecting real-world Japanese microbiome data from a Mykinso cohort. Although several large cohort studies have focused on the human gut microbiome, large cohort studies of the gut microbiome from Japanese populations are scarce, especially from healthy or non-diseased individuals. We collected stool samples and original survey lifestyle information from 5,843 Japanese individuals through the Mykinso gut microbiome testing service. From the obtained 16S rRNA sequence data derived from stool samples, the ratio and distribution of each taxon were analyzed. The relationship between different epidemiological attributes and gut microbial indicators were statistically analyzed. The qualitative and quantitative indicators of these common gut microbiota were confirmed to be strongly correlated with age, sex, constipation/diarrhea, and history of lifestyle-related diseases. Therefore, we set up a healthy sub-cohort that controlled for these attribute factors and defined reference ranges from the distribution of gut microbial index in that population. Taken together, these results show that the gut microbiota of Japanese people had high beta-diversity, with no single "typical" gut microbiota type. We believe that the reference ranges for the gut microbial indices obtained in this study can be new reference values for determining the balance and health of the gut microbiota of an individual. In the future, it is necessary to clarify the clinical validity of these reference values by comparing them with a clinical disease cohort.

Gut microbial diversity during pregnancy and early infancy: an exploratory study in the Indian population

The gut microbial community is known to influence the human health and disease state and is shaped by various factors since birth. It is now evident that understanding the alterations in these commensal microbes during crucial stages of life is of utmost importance to determine and predict the health status of an individual. To study the gut microbiota in two such vital stages, pregnancy and infancy, we analyzed gut microbial communities from 20 mother-infant dyads at different stages of pregnancy and early infancy. In total, we analyzed 80 fecal samples for profiling the gut microbial community using 16S rRNA gene-based sequencing. We observed no significant alterations in the gut bacterial diversity during pregnancy; however, significant alterations were observed during the period from birth to six months in infants, with a reduction in Staphylococcus and Enterococcus and an increase in Bifidobacterium and Streptococcus with a more stable microbial community at the age of six months.