Biases during DNA extraction of activated sludge samples revealed by high throughput sequencing

Towards predicting the geographical origin of ancient samples with metagenomic data

Reconstructing the history-such as the place of birth and death-of an individual sample is a fundamental goal in ancient DNA (aDNA) studies. However, knowing the place of death can be particularly challenging when samples come from museum collections with incomplete or erroneous archives. While analyses of human DNA and isotope data can inform us about the ancestry of an individual and provide clues about where the person lived, they cannot specifically trace the place of death. Moreover, while ancient human DNA can be retrieved, a large fraction of the sequenced molecules in ancient DNA studies derive from exogenous DNA. This DNA-which is usually discarded in aDNA analyses-is constituted mostly by microbial DNA from soil-dwelling microorganisms that have colonized the buried remains post-mortem. In this study, we hypothesize that remains of individuals buried in the same or close geographic areas, exposed to similar microbial communities, could harbor more similar metagenomes. We propose to use metagenomic data from ancient samples' shotgun sequencing to locate the place of death of a given individual which can also help to solve cases of sample mislabeling. We used a k-mer-based approach to compute similarity scores between metagenomic samples from different locations and propose a method based on dimensionality reduction and logistic regression to assign a geographical origin to target samples. We apply our method to several public datasets and observe that individual samples from closer geographic locations tend to show higher similarities in their metagenomes compared to those of different origin, allowing good geographical predictions of test samples. Moreover, we observe that the genus Streptomyces commonly infiltrates ancient remains and represents a valuable biomarker to trace the samples' geographic origin. Our results provide a proof of concept and show how metagenomic data can also be used to shed light on the place of origin of ancient samples.

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.

Development of a multiplex droplet digital PCR assay for simultaneous detection and quantification of Escherichia coli, E. marmotae, and E. ruysiae in water samples

Escherichia coli are widely used by water quality managers as Fecal Indicator Bacteria, but current quantification methods do not differentiate them from benign, environmental Escherichia species such as E. marmotae (formerly named cryptic clade V) or E. ruysiae (cryptic clades III and IV). Reliable and specific techniques for their identification are required to avoid confounding microbial water quality assessments. To address this, a multiplex droplet digital PCR (ddPCR) assay targeting lipB (E. coli and E. ruysiae) and bglC (E. marmotae) was designed. The ddPCR performance was assessed using in silico analysis; genomic DNA from 40 local, international, and reference strains of target and non-target coliforms; and spiked water samples in a range relevant to water quality managers (1 to 1000 cells/100 mL). Results were compared to an analogous quantitative PCR (qPCR) and the Colilert method. Both PCR assays showed excellent sensitivity with a limit of detection of 0.05 pg/μL and 0.005 pg/μl for ddPCR and qPCR respectively, and of quantification of 0.5 pg/μL of genomic DNA. The ddPCR allowed differentiation and quantification of three Escherichia species per run by amplitude multiplexing and showed a high concordance with concentrations measured by Colilert once proportional bias was accounted for. In silico specificity testing underlined the possibility to further detect and distinguish Escherichia cryptic clade VI. Finally, the applicability of the ddPCR was successfully tested on environmental water samples where E. marmotae and E. ruysiae potentially confound E. coli counts based on the Most Probable Number method, highlighting the utility of this novel ddPCR as an efficient and rapid discriminatory test to improve water quality assessments.

Comparison of DNA extraction methods on different sample matrices within the same terrestrial ecosystem

Metataxonomic studies of ecosystem microbiotas require the simultaneous processing of samples with contrasting physical and biochemical traits. However, there are no published studies of comparisons of different DNA extraction kits to characterize the microbiotas of the main components of terrestrial ecosystems. Here, and to our knowledge for the first time, five DNA extraction kits were used to investigate the composition and diversity of the microbiota of a subset of samples typically studied in terrestrial ecosystems such as bulk soil, rhizosphere soil, invertebrate taxa and mammalian feces. DNA extraction kit was associated with changes in the relative abundance of hundreds of ASVs, in the same samples, resulting in significant differences in alpha and beta diversity estimates of their microbiotas. Importantly, the impact of DNA extraction kit on sample diversity varies according to sample type, with mammalian feces and soil samples showing the most and least consistent diversity estimates across DNA extraction kits, respectively. We show that the MACHEREY-NAGEL NucleoSpin® Soil kit was associated with the highest alpha diversity estimates, providing the highest contribution to the overall sample diversity, as indicated by comparisons with computationally assembled reference communities, and is recommended to be used for any large-scale microbiota study of terrestrial ecosystems.

Novel Techniques and Models for Studying the Role of the Gut Microbiota in Drug Metabolism

The gut microbiota, known as the second human genome, plays a vital role in modulating drug metabolism, significantly impacting therapeutic outcomes and adverse effects. Emerging research has elucidated that the microbiota mediates a range of modifications of drugs, leading to their activation, inactivation, or even toxication. In diverse individuals, variations in the gut microbiota can result in differences in microbe-drug interactions, underscoring the importance of personalized approaches in pharmacotherapy. However, previous studies on drug metabolism in the gut microbiota have been hampered by technical limitations. Nowadays, advances in biotechnological tools, such as microbially derived metabolism screening and microbial gene editing, have provided a deeper insight into the mechanism of drug metabolism by gut microbiota, moving us toward personalized therapeutic interventions. Given this situation, our review summarizes recent advances in the study of gut-microbiota-mediated drug metabolism and showcases techniques and models developed to navigate the challenges posed by the microbial involvement in drug action. Therefore, we not only aim at understanding the complex interaction between the gut microbiota and drugs and outline the development of research techniques and models, but we also summarize the specific applications of new techniques and models in researching gut-microbiota-mediated drug metabolism, with the expectation of providing new insights on how to study drug metabolism by gut microbiota.

Improving the efficiency of DNA extraction from iron incrustations and oilfield-produced water

The quantity and quality of DNA isolated from environmental samples are crucial for getting robust high-throughput sequencing data commonly used for microbial community analysis. The differences in the nature and physicochemical properties of environmental samples impact DNA yields, and therefore, an optimisation of the protocols is always recommended. For instance, samples collected from corroded areas contain high concentrations of metals, salts, and hydrocarbons that can interfere with several steps of the DNA extraction protocols, thereby reducing yield and quality. In this study, we compared the efficiency of commercially available DNA extraction kits and laboratory-adopted methods for microbial community analysis of iron incrustations and oilfield-produced water samples. Modifications to the kits manufacturers' protocols were included to maximise the yield and quality. For iron incrustations, the modified protocol for FastDNA Spin Kit for Soil yielded higher DNA and resulted in higher diversity, including the recovery of low-abundant and rare taxa in the samples, compared to DNeasy PowerSoil Pro Kit. The DNA extracted with modified phenol-chloroform methods yielded higher DNA but failed to pass quality control PCR for 16S sequencing with and without purification. The protocols mentioned here can be used to maximise DNA recovery from iron incrustations and oilfield-produced water samples.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Assessment of DNA extraction methods for human gut mycobiome analysis

The gut mycobiome plays an important role in the health and disease of the human gut, but its exact function is still under investigation. While there is a wealth of information available on the bacterial community of the human gut microbiome, research on the fungal community is still relatively limited. In particular, technical methodologies for mycobiome analysis, especially the DNA extraction method for human faecal samples, varied in different studies. In the current study, two commercial kits commonly used in DNA extraction, the QIAamp® Fast DNA Stool Mini Kit and DNeasy PowerSoil Pro Kit, and one manual method, the International Human Microbiome Standards Protocol Q, were compared. Furthermore, the effectiveness of two different bead-beating machines, the Mini-Beadbeater-16 and FastPrep-24TM 5G, was compared in parallel. A mock fungal community with a known composition of fungal strains was also generated and included to compare different DNA extraction methods. Our results suggested that the method using the DNeasy PowerSoil Pro Kit and Mini-Beadbeater-16 provides the best results to extract DNA from human faecal samples. Based on our data, we propose a standard operating procedure for DNA extraction from human faecal samples for mycobiome analysis.

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.

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.

Soil bacterial community composition is more stable in kiwifruit orchards relative to phyllosphere communities over time

BACKGROUND

Soil and phyllosphere (leaves and fruit) microbes play critical roles in the productivity and health of crops. However, microbial community dynamics are currently understudied in orchards, with a limited number incorporating temporal monitoring. We used 16S rRNA gene amplicon sequencing to investigate bacterial community temporal dynamics and community assembly processes on the leaves and fruit, and in the soil of 12 kiwifruit orchards across a cropping season in New Zealand.

RESULTS

Community composition significantly differed (P < 0.001) among the three sample types. However, the communities in the phyllosphere substrates more closely resembled each other, relative to the communities in the soil. There was more temporal stability in the soil bacterial community composition, relative to the communities residing on the leaves and fruit, and low similarity between the belowground and aboveground communities. Bacteria in the soil were more influenced by deterministic processes, while stochastic processes were more important for community assembly in the phyllosphere.

CONCLUSIONS

The higher temporal variability and the stochastic nature of the community assembly processes observed in the phyllosphere communities highlights why predicting the responsiveness of phyllosphere communities to environmental change, or the likelihood of pathogen invasion, can be challenging. The relative temporal stability and the influence of deterministic selection on soil microbial communities suggests a greater potential for their prediction and reliable manipulation.

Reduced immunomodulatory metabolite concentrations in peri-transplant fecal samples from heart allograft recipients

Background

Emerging evidence is revealing the impact of the gut microbiome on hematopoietic and solid organ transplantation. Prior studies postulate that this influence is mediated by bioactive metabolites produced by gut-dwelling commensal bacteria. However, gut microbial metabolite production has not previously been measured among heart transplant (HT) recipients.

Methods

In order to investigate the potential influence of the gut microbiome and its metabolites on HT, we analyzed the composition and metabolite production of the fecal microbiome among 48 HT recipients at the time of HT.

Results

Compared to 20 healthy donors, HT recipients have significantly reduced alpha, i.e. within-sample, microbiota diversity, with significantly lower abundances of key anaerobic commensal bacteria and higher abundances of potentially pathogenic taxa that have been correlated with adverse outcomes in other forms of transplantation. HT recipients have a wide range of microbiota-derived fecal metabolite concentrations, with significantly reduced levels of immune modulatory metabolites such as short chain fatty acids and secondary bile acids compared to healthy donors. These differences were likely due to disease severity and prior antibiotic exposures but were not explained by other demographic or clinical factors.

Conclusions

Key potentially immune modulatory gut microbial metabolites are quantifiable and significantly reduced among HT recipients compared to healthy donors. Further study is needed to understand whether this wide range of gut microbial dysbiosis and metabolite alterations impact clinical outcomes and if they can be used as predictive biomarkers or manipulated to improve transplant outcomes.

Metagenomics analysis reveals the effects of norfloxacin on the gut microbiota of juvenile common carp (Cyprinus carpio)

Norfloxacin (NOR) is an early third-generation quinolone antibiotic that has been widely used in animal husbandry and aquaculture because of its bactericidal properties. As an emerging contaminant, NOR may have toxic effects on fish. This study assessed the chronic toxicity (6 weeks) of 0 (control group), 100 ng/L (environmental concentration), and 1 mg/L NOR to the gut microbiota of juvenile common carp (Cyprinus carpio) based on metagenomic sequencing. Metagenomic analysis revealed that the Proteobacteria, Bacteroidetes, Fusobacteria, Firmicutes, and Actinobacteria were the dominant bacteria in the gut of common carp. The relative abundance of Actinobacteria was highest in the control group. The alpha diversity of the environmental concentration NOR was significantly lower than the control group. Principal coordinates analysis (PCoA) indicated that the bacterial community between the different groups formed clear separate clusters. NOR exposure adversely could affect immune function and some substance metabolic pathways in the gut microbiota of common carp. Furthermore, environmental concentrations of NOR produce antibiotic resistance genes (ARGs) in the gut microbiota, enhancing resistance to drugs. In conclusion, environmental concentrations of NOR could alter the composition, structure, and abundance of ARGs in the gut microbiota, thereby affecting the intestinal health of fish.

Evaluation of DNA Extraction Methods for Reliable Quantification of Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa

Detection and quantification of DNA biomarkers relies heavily on the yield and quality of DNA obtained by extraction from different matrices. Although a large number of studies have compared the yields of different extraction methods, the repeatability and intermediate precision of these methods have been largely overlooked. In the present study, five extraction methods were evaluated, using digital PCR, to determine their efficiency in extracting DNA from three different Gram-negative bacteria in sputum samples. The performance of two automated methods (GXT NA and QuickPick genomic DNA extraction kit, using Arrow and KingFisher Duo automated systems, respectively), two manual kit-based methods (QIAamp DNA mini kit; DNeasy UltraClean microbial kit), and one manual non-kit method (CTAB), was assessed. While GXT NA extraction kit and the CTAB method have the highest DNA yield, they did not meet the strict criteria for repeatability, intermediate precision, and measurement uncertainty for all three studied bacteria. However, due to limited clinical samples, a compromise is necessary, and the GXT NA extraction kit was found to be the method of choice. The study also showed that dPCR allowed for accurate determination of extraction method repeatability, which can help standardize molecular diagnostic approaches. Additionally, the determination of absolute copy numbers facilitated the calculation of measurement uncertainty, which was found to be influenced by the DNA extraction method used.

Rapid Reverse Purification DNA Extraction Approaches to Identify Microbial Pathogens in Wastewater

Wastewater monitoring became a promising solution in the early detection of outbreaks. Despite the achievements in the identification of pathogens in wastewater using real-time PCR, there is still a lack of reliable rapid nucleic acid extraction protocols. Therefore, in this study, samples were subjected to alkali, proteinase K and/or bead-beating followed by reverse purification magnetic beads-based separation. Wastewater samples spiked with S. aureus, E. coli and C. parvum were used as examples for Gram-positive and -negative bacteria and protozoa, respectively. All results were compared with a spin column technology as a reference method. Proteinase K with bead beating (vortexing with 0.1 mm glass beads for three minutes) was particularly successful for bacterial DNA extraction (three- to five-fold increase). The most useful extraction protocol for protozoa was pre-treatment with proteinase K (eight-fold increase). The selected methods were sensitive as far as detecting one bacterial cell per reaction for S. aureus, ten bacterial cells for E. coli and two oocysts for C. parvum. The extraction reagents are cold chain independent and no centrifuge or other large laboratory equipment is required to perform DNA extraction. A controlled validation trial is needed to test the effectiveness at field levels.

Grinding Beads Influence Microbial DNA Extraction from Organic-Rich Sub-Seafloor Sediment

Sub-seafloor sediment is the largest microbial habitat on Earth. The study of microbes in sub-seafloor sediment is largely limited by the technical challenge of acquiring ambient microbial DNA because of sediment heterogeneity. Changes in the extraction method, even just by one step, can affect the extraction yields for complicated sediment samples. In this work, sub-seafloor sediment samples from the Baltic Sea with high organic carbon content were used to evaluate the influence of different grinding beads on DNA extraction. We found that the grinding beads can affect the DNA extraction from the organic-matter- and biosiliceous-clay-rich samples. A mixture of 0.5-mm and 0.1-mm grinding beads exhibited higher DNA yields and recovered more unique taxa than other bead combinations, such as Stenotrophomonas from Gammaproteobacteria and Leptotrichia from Fusobacteria; therefore, these beads are more suitable than the others for DNA extraction from the samples used in this study. This advantage might be magnified in samples with high biomass. On the contrary, the use of only small beads might lead to underestimation for certain Gram-positive strains. Overall, the discovery of abundant widespread deep biosphere clades in our samples indicated that our optimized DNA extraction method successfully recovered the in situ microbial community.

Antimicrobial Resistance Monitoring of Water Environments: A Framework for Standardized Methods and Quality Control

Antimicrobial resistance (AMR) is a grand societal challenge with important dimensions in the water environment that contribute to its evolution and spread. Environmental monitoring could provide vital information for mitigating the spread of AMR; this includes assessing antibiotic resistance genes (ARGs) circulating among human populations, identifying key hotspots for evolution and dissemination of resistance, informing epidemiological and human health risk assessment models, and quantifying removal efficiencies by domestic wastewater infrastructure. However, standardized methods for monitoring AMR in the water environment will be vital to producing the comparable data sets needed to address such questions. Here we sought to establish scientific consensus on a framework for such standardization, evaluating the state of the science and practice of AMR monitoring of wastewater, recycled water, and surface water, through a literature review, survey, and workshop leveraging the expertise of academic, governmental, consulting, and water utility professionals.

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.

Granulation strategies applied to industrial wastewater treatment: from lab to full-scale

About one third of the industrial activated sludge (AS) plants worldwide suffer from bad settling sludge, often caused by filamentous bulking phenomena. The present study investigated the effectiveness of a sludge granulation/densification strategy, based only on a metabolic selection mechanism, to eliminate sludge bulking in a sequencing batch reactor (SBR) treating real industrial wastewater. The wastewater originated from a tank truck cleaning company transporting chocolate and beer. The proposed strategy involved the introduction of a slow unaerated/anaerobic feeding step in the SBR operation. On lab-scale, the new feeding strategy resulted in (1) excellent settling with a sludge volume index (SVI) decreasing from more than 300 mL·g^-1 to 100 mL·g^-1 and lower, (2) the elimination of sludge bulking genera and (3) the significant enrichment of glycogen-accumulating organisms (GAO), mainly Defluviicoccus and Candidatus Competibacter, and this in less than 80 days. The feeding strategy was then applied to the full-scale installation, yielding similar results: a stable average SVI of 37 mL·g^-1 was reached after approximately 150 days. Full granulation was however not reached, which warrants further optimization. The present study shows that the proposed strategy can easily be applied in existing SBR systems to solve the problem of sludge bulking.

Identification and profiling of microbial community from industrial sludge

The purpose of this study is to identify microbial communities in pulp and paper industry sludge and their metagenomic profiling on the basis of; phylum, class, order, family, genus and species level. Results revealed that the dominant phyla in 16S rRNA Illumina Miseq analysis inside sludge were Anaerolinea, Pseudomonas, Clostridia, Bacteriodia, Gammaproteobacteria, Spirochetia, Deltaproteobacteria, Spirochaetaceae, Prolixibacteraceae and some unknown microbial strains are also dominant. Metagenomics is a molecular biology-based technology that uses bioinformatics to evaluate huge gene sequences extracted from environmental samples to assess the composition and function of microbiota. The results of metabarcoding of the V3-V4 16S rRNA regions acquired from paired-end Illumina MiSeq sequencing were used to analyze bacterial communities and structure. The present work demonstrates the potential approach to sludge treatment in the open environment via the naturally adapted microorganism, which could be an essential addition to the disposal site. In summary, these investigations indicate that the indigenous microbial community is an acceptable bioresource for remediation or detoxification following secondary treatment. This research aims at understanding the structure of microbial communities and their diversity (%) in highly contaminated sludge to perform in situ bioremediation.

Cloning of DNA oligo pools for in vitro expression

Oligo library pools are powerful tools for systematic investigation of genetic and transcriptomic machinery such as promoter function and gene regulation, non-coding RNAs, or RNA modifications. Here, we provide a detailed protocol for cloning DNA oligo pools made up of tens of thousands of different constructs, aiming to preserve the complexity of the pools. This system would be suitable for expression in cell lines and can be followed up by next-generation sequencing analysis.

For complete details on the use and execution of this profile, please refer to Uzonyi et al. (2021).

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Restriction-based cloning of DNA pools

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Preservation of complexity of thousands of constructs

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Used to investigate genetic and transcriptomic machineries

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To be expressed in cell lines and follow up by NGS analysis

Potential influence of the microbiome environment in patients with biliary tract cancer and implications for therapy

Biliary tract cancers, including intra- and extra-hepatic cholangiocarcinoma as well as gallbladder cancer, are associated with poor prognosis and the majority of patients present with advanced-stage, non-resectable disease at diagnosis. Biliary tract cancer may develop through an accumulation of genetic and epigenetic alterations and can be influenced by microbial exposure. Furthermore, the liver and biliary tract are exposed to the gastrointestinal microbiome through the gut-liver axis. The availability of next-generation sequencing technology has led to an increase in studies investigating the relationship between microbiota and human disease. In particular, the interplay between the microbiome, the tumour micro-environment and response to systemic therapy is a prospering area of interest. Given the poor outcomes for patients with biliary tract cancer, this emerging field of research, through which new biomarkers may be identified, offers potential as a tool for early diagnosis, prognostication or even as a future therapeutic target. This review summarises the available evidence on the microbiome environment in patients with biliary tract cancer, including a discussion around confounding factors, implications for therapy and proposed future directions.

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.

Optimization of Protocol for Construction of Fungal ITS Amplicon Library for High-Throughput Illumina Sequencing to Study the Mycobiome of Aspen Leaves

High-Throughput Illumina Sequencing (HTS) can be used to study metagenomes, for example, those of importance for plant health. However, protocols must be optimized according to the plant system in question, the focal microorganisms in the samples, the marker genes selected, and the number of environmental samples. We optimized the protocol for metagenomic studies of aspen leaves, originating from varied genotypes sampled across the growing season, and consequently varying in phenolic composition and in the abundance of endo- and epiphytic fungal species. We optimized the DNA extraction protocol by comparing commercial kits and evaluating five fungal ribosomal specific primers (Ps) alone, and with extended primers that allow binding to sample-specific index primers, and we then optimized the amplification with these composite Ps for 380 samples. The fungal DNA concentration in the samples varied from 561 ng/µL to 1526 ng/µL depending on the DNA extraction kit used. However, binding to phenolic compounds affected DNA quality as assessed by Nanodrop measurements (0.63–2.04 and 0.26–2.00 absorbance ratios for 260/280 and 260/230, respectively), and this was judged to be more important in making our choice of DNA extraction kit. We initially modified the PCR conditions after determining the concentration of DNA extract in a few subsamples and then evaluated and optimized the annealing temperature, duration, and number of cycles to obtain the required amplification and PCR product bands. For three specific Ps, the extended Ps produced dimers and unexpected amplicon fragments due to nonspecific binding. However, we found that the specific Ps that targeted the ITS2 region of fungal rDNA successfully amplified this region for every sample (with and without the extension PP) resulting in the desired PCR bands, and also allowing the addition of sample-specific index primers, findings which were successfully verified in a second PCR. The optimized protocol allowed us to successfully prepare an amplicon library in order to subject the intended 380 environmental samples to HTS.

Integrating the human microbiome in the forensic toolkit: Current bottlenecks and future solutions

Over the last few years, advances in massively parallel sequencing technologies (also referred to next generation sequencing) and bioinformatics analysis tools have boosted our knowledge on the human microbiome. Such insights have brought new perspectives and possibilities to apply human microbiome analysis in many areas, particularly in medicine. In the forensic field, the use of microbial DNA obtained from human materials is still in its infancy but has been suggested as a potential alternative in situations when other human (non-microbial) approaches present limitations. More specifically, DNA analysis of a wide variety of microorganisms that live in and on the human body offers promises to answer various forensically relevant questions, such as post-mortem interval estimation, individual identification, and tissue/body fluid identification, among others. However, human microbiome analysis currently faces significant challenges that need to be considered and overcome via future forensically oriented human microbiome research to provide the necessary solutions. In this perspective article, we discuss the most relevant biological, technical and data-related issues and propose future solutions that will pave the way towards the integration of human microbiome analysis in the forensic toolkit.

The Requirement of Genetic Diagnostic Technologies for Environmental Surveillance of Antimicrobial Resistance

Antimicrobial resistance (AMR) is threatening modern medicine. While the primary cost of AMR is paid in the healthcare domain, the agricultural and environmental domains are also reservoirs of resistant microorganisms and hence perpetual sources of AMR infections in humans. Consequently, the World Health Organisation and other international agencies are calling for surveillance of AMR in all three domains to guide intervention and risk reduction strategies. Technologies for detecting AMR that have been developed for healthcare settings are not immediately transferable to environmental and agricultural settings, and limited dialogue between the domains has hampered opportunities for cross-fertilisation to develop modified or new technologies. In this feature, we discuss the limitations of currently available AMR sensing technologies used in the clinic for sensing in other environments, and what is required to overcome these limitations.

AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata

BACKGROUND

Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance.

RESULTS

Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis.

CONCLUSION

AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/ .

Comparison of gut microbiota between adults with autism spectrum disorder and obese adults

Background

Autism spectrum disorder (ASD) and obesity are serious global public health problems. Studies have shown that ASD children are at a higher risk of obesity than the general population. To investigate the gut microbe characteristics of adults ASD and obese adults, we compared the gut microbiota of adults with ASD to obese adults.

Methods

The fecal samples were collected from 21 adult patients with ASD and 21 obese adults, and V3–V4 regions of 16S rRNA genes were sequenced by high-throughput DNA sequencing. The gut microbiota of adults with ASD and obese adults was compared.

Results

We observed the proportion of Firmicutes/Bacteroidetes in ASD was significantly increased, with families Lachnospiraceae and Ruminococcaceae significantly enriched in adult ASD. Eighteen genera, including Lachnospiracea incertae sedis, Ruminococcus, Blautia, and Holdemanella were significantly increased in adult ASD, whereas Megamonas and Fusobacterium were significantly increased in obesity. At the species level, we found six species enriched in ASD and three species enriched in obesity, including Phascolarctobacterium succinatuten producing propionate. Dialister succinatiphilus may be as a biomarker for predicting obesity, as well as Prevotella copri may be a common-owned pathogens of ASD and obesity.

Conclusions

Some conflicting results have been reported in microbiota studies of ASD, which may be related to age and obesity. Thus, the body mass index should be evaluated before analyzing the gut microbiota of patients with ASD, as obesity is prevalent in these individuals and gut microbiota is severally affected by obesity.

Time to act-assessing variations in qPCR analyses in biological nitrogen removal with examples from partial nitritation/anammox systems

Quantitative PCR (qPCR) is broadly used as the gold standard to quantify microbial community fractions in environmental microbiology and biotechnology. Benchmarking efforts to ensure the comparability of qPCR data for environmental bioprocesses are still scarce. Also, for partial nitritation/anammox (PN/A) systems systematic investigations are still missing, rendering meta-analysis of reported trends and generic insights potentially precarious. We report a baseline investigation of the variability of qPCR-based analyses for microbial communities applied to PN/A systems. Round-robin testing was performed for three PN/A biomass samples in six laboratories, using the respective in-house DNA extraction and qPCR protocols. The concentration of extracted DNA was significantly different between labs, ranged between 2.7 and 328 ng mg^-1 wet biomass. The variability among the qPCR abundance data of different labs was very high (1-7 log fold) but differed for different target microbial guilds. DNA extraction caused maximum variation (3-7 log fold), followed by the primers (1-3 log fold). These insights will guide environmental scientists and engineers as well as treatment plant operators in the interpretation of qPCR data.

Database Mining to Unravel the Ecology of the Phylum Chloroflexi in Methanogenic Full Scale Bioreactors

Although microbial communities of anaerobic bioreactors have been extensively studied using DNA-based tools, there are still several knowledge gaps regarding the microbiology of the process, in particular integration of all generated data is still limited. One understudied core phylum within anaerobic bioreactors is the phylum Chloroflexi, despite being one of the most abundant groups in anaerobic reactors. In order to address the abundance, diversity and phylogeny of this group in full-scale methanogenic reactors globally distributed, a compilation of 16S ribosomal RNA gene sequence data from 62 full-scale methanogenic reactors studied worldwide, fed either with wastewater treatment anaerobic reactors (WTARs) or solid-waste treatment anaerobic reactors (STARs), was performed. One of the barriers to overcome was comparing data generated using different primer sets and different sequencing platforms. The sequence analysis revealed that the average abundance of Chloroflexi in WTARs was higher than in STARs. Four genera belonging to the Anaerolineae class dominated both WTARs and STARs but the core populations were different. According to the phylogenetic analysis, most of the sequences formed clusters with no cultured representatives. The Anaerolineae class was more abundant in reactors with granular biomass than in reactors with disperse biomass supporting the hypothesis that Anaerolineae play an important role in granule formation and structure due to their filamentous morphology. Cross-study comparisons can be fruitfully used to understand the complexity of the anaerobic digestion process. However, more efforts are needed to standardize protocols and report metadata information.

Current ocular microbiome investigations limit reproducibility and reliability: Critical review and opportunities

Enthusiasm for research describing microbial communities using next-generation sequencing (NGS) has outpaced efforts to standardize methodology. Without consistency in the way research is carried out in this field, the comparison of data between studies is near impossible and the utility of results remains limited. This holds true for bacterial microbiome research of the ocular surface, and other sites, in both humans and animals. In addition, the ocular surface remains under-explored when compared to other mucosal sites. Low bacterial biomass samples from the ocular surface lead to further technical challenges. Taken together, two major problems were identified: (1) Normalization of the workflow in studies utilizing NGS to investigate the ocular surface bacteriome is necessary in order to propel the field forward and improve research impact through cross-study comparisons. (2) Current microbiome profiling technology was developed for high bacterial biomass samples (such as feces or soil), posing a challenge for analyses of samples with low bacterial load such as the ocular surface. This article reviews the challenges and limitations currently facing ocular microbiome research and provides recommendations for minimum reporting standards for veterinary ophthalmologists and clinician scientists to limit inter-study variation, improve reproducibility, and ultimately render results from these studies more impactful. The move toward normalization of methodology will expedite and maximize the potential for microbiome research to translate into meaningful discovery and tangible clinical applications.

Evaluation of the Abundance of Fungi in Wastewater Treatment Plants Using Quantitative PCR (qPCR)

Assessment of the abundance of fungi in environmental samples by quantitative PCR (qPCR) of community DNA is often a difficult task due to biases introduced during PCR amplification, resulting from the differences associated with length polymorphism and the varying number of copies of the rRNA operon among fungal species, the lack of specificity of the primers targeting the different regions of the rRNA operon, or their insufficient coverage of the fungal lineages. To overcome those limitations, it is crucial to test and select the specific primers sets which provide the more accurate approximation to the quantification of the targeted fungal populations in a given set of samples. Fungi are a significant fraction of the microbiota in wastewater treatment plants (WWTPs), but the activated sludge microbial communities comprise many other eukaryotic microorganisms whose molecular markers are often coamplified by primers initially designed as fungal-specific. Here, the use of the FungiQuant primer set is recommended for the quantification of fungal molecular markers (18S rRNA genes) by qPCR in activated sludge samples and the full protocol is described.

Diversity of gut microbiomes in marine fishes is shaped by host-related factors

Microorganisms in the gastrointestinal tract of animals play vital roles in food digestion, homeostasis and immune response regulation. Globally, there are 33,700 fish species, representing almost half of all vertebrate diversity and a wide range of physiologies, ecologies and life histories. To investigate gut microbiomes with high coverage, we performed 16S rRNA gene amplicon sequencing with 115 samples of 20 common marine fish species. The fish gut microbiome is a remarkably simple community with low microbial diversity (a maximum of 300 amplicon sequence variants only) and has up to 70% of unknown species in some fish species. The gut microbial community structure was significantly shaped by the combined influence of host-associated factors, including the fish taxon (p < .001, R2  = 0.16, ω2  = 0.04), feeding habit (p < .001, R2  = 0.06, ω2  = 0.02) and trophic level (p < .01, R2  = 0.04, ω2  = 0.01), although the influence was subtle with a small effect size. The core gut microbiomes of different feeding habits were also previously discovered in animal-associated and corresponding habitat samples. Certain energy metabolism pathways were enriched in herbivore/omnivore and zooplanktivore/zoobenthivore fishes, whereas lipid metabolism and glycan metabolism were enriched in zoobenthivore/piscivore fishes. Moreover, substantial taxonomic variability was found between the gut microbiomes of fish and animals, indicated by their low degree of shared microbiota. The data and observations reported herein pave the way for further investigations on the co-evolution of fish gut microbiomes and their hosts, the physiological functions of gut microorganisms and the development of probiotics for improving the nutrition and health of aquaculture fish species.

Effects of Chemical and Mechanical Lysis on Microbial DNA Yield, Integrity, and Downstream Amplicon Sequencing of Rumen Bacteria and Protozoa

QIAamp Fast DNA Stool Mini Kit (QIAGEN, Valencia, CA, United States) and RBB + C (Yu and Morrison, 2004) methodologies are widely employed to extract microbial DNA from rumen samples and can exhibit different efficiencies of obtaining DNA yield, quality, and downstream amplicon sequence analysis. No study has conducted to investigate the contributions of chemical and mechanical lysis on DNA extraction, which included chemical lysis from QIAamp Fast DNA Stool Mini Kit (QIA) and RBB + C (YM), bead (BB), and sand beating (SB). Effects of chemical lysis and bead beating (BB) were investigated by conducting a 2 × 2 factorial-designed experiment with four methodologies, including QIA without (QIA−) and with BB (QIA + BB), and YM without (YM−) and with BB (YM + BB). Comparisons between bead and sand were conducted by comparing methodologies of YM + BB and YM + SB. Comparing with QIA, YM had lower (P ≤ 0.10) OD_260/280 and diversity of ZOTUs and length polymorphism of protozoal amplicons but harvested greater (P ≤ 0.086) DNA from fibrolytic bacteria such as Ruminococcaceae lineages. Including BB increased (P = 0.001) total DNA yield without affecting (P ≥ 0.55) OD_260/280 and richness of bacterial ZOTUs but decreased (P ≤ 0.08) richness of both ZOTUs and length polymorphism of protozoal amplicon. Bead beating and SB showed no difference (P ≥ 0.19) in DNA yield and quality and bacterial and protozoal community. In summary, chemical lysis provided by RBB + C and QIAamp Fast DNA Stool Mini Kit should be better to extract DNA for analyzing bacterial and protozoal community, respectively. Sand can be an alternative beater for DNA extraction, and mechanical lysis is not recommended for protozoal community analysis.

Optimization of a Method for the Concentration of Genetic Material in Bacterial and Fungal Communities on Fresh Apple Peel Surfaces

Apples are the most consumed fruit in the United States and have recently been shown to exhibit some vulnerability to contamination across the supply chain. It is unclear what role a fruit microbiome analysis may serve in future food safety programs interested in understanding changes in the product and the processing environment. Ultimately, sample integrity is key if any of these approaches are to be employed; low microbial loads on apple surfaces, the inability to sample the entire surface, and inefficiency of removal may act as barriers to achieving high-quality DNA. As such, the objective of this study was to identify a reproducible method to concentrate and quantify bacterial and fungal DNA from fresh apple surfaces. Five methods were evaluated: two variations of wash solutions for bath sonication, wash filtration, epidermis excision, and surface swabbing. Epidermis excision returned the highest mean DNA quantities, followed by the sonicated washes and wash filtration. Surface swabbing was consistently below the limit of detection. Based on the quantity of host DNA contamination in surface excision, the sonicated wash solution containing a surfactant presents the greatest opportunity for consistent, high-yielding DNA recovery from the entire apple surface.

Efficiency of chemical versus mechanical disruption methods of DNA extraction for the identification of oral Gram-positive and Gram-negative bacteria

Objective

Clinical diagnostics often requires the detection of multiple bacterial species in limited clinical samples with a single DNA extraction method. This study aimed to compare the bacterial DNA extraction efficiency of two lysis methods automated with the MagNA-Pure LC instrument. The samples included five oral bacterial species (three Gram-positive and two Gram-negative) with or without human saliva background.

Methods

Genomic DNA (gDNA) was extracted from bacterial cultures by bead-beating lysis (BMP) or chemical lysis (MP), followed by automated purification and measurement by quantitative PCR.

Results

For pure bacterial cultures, the MP method yielded higher quantities of extracted DNA and a lower detection limit than the BMP method, except where the samples contained high numbers of Gram-positive bacteria. For bacterial cultures with a saliva background, no difference in gDNA extraction efficacy was observed between the two methods.

Conclusions

The efficiency of a bacterial DNA extraction method is not only affected by the bacterial cell wall structure but also by the sample milieu. The MP method provided superior gDNA extraction efficiency when the samples contained a single bacterial species, whereas either of the BMP and MP methods could be applied with similar efficiencies to samples containing multiple species of bacteria.

Optimizing 16S rRNA gene profile analysis from low biomass nasopharyngeal and induced sputum specimens

BACKGROUND

Careful consideration of experimental artefacts is required in order to successfully apply high-throughput 16S ribosomal ribonucleic acid (rRNA) gene sequencing technology. Here we introduce experimental design, quality control and "denoising" approaches for sequencing low biomass specimens.

RESULTS

We found that bacterial biomass is a key driver of 16S rRNA gene sequencing profiles generated from bacterial mock communities and that the use of different deoxyribonucleic acid (DNA) extraction methods [DSP Virus/Pathogen Mini Kit® (Kit-QS) and ZymoBIOMICS DNA Miniprep Kit (Kit-ZB)] and storage buffers [PrimeStore® Molecular Transport medium (Primestore) and Skim-milk, Tryptone, Glucose and Glycerol (STGG)] further influence these profiles. Kit-QS better represented hard-to-lyse bacteria from bacterial mock communities compared to Kit-ZB. Primestore storage buffer yielded lower levels of background operational taxonomic units (OTUs) from low biomass bacterial mock community controls compared to STGG. In addition to bacterial mock community controls, we used technical repeats (nasopharyngeal and induced sputum processed in duplicate, triplicate or quadruplicate) to further evaluate the effect of specimen biomass and participant age at specimen collection on resultant sequencing profiles. We observed a positive correlation (r = 0.16) between specimen biomass and participant age at specimen collection: low biomass technical repeats (represented by < 500 16S rRNA gene copies/μl) were primarily collected at < 14 days of age. We found that low biomass technical repeats also produced higher alpha diversities (r = - 0.28); 16S rRNA gene profiles similar to no template controls (Primestore); and reduced sequencing reproducibility. Finally, we show that the use of statistical tools for in silico contaminant identification, as implemented through the decontam package in R, provides better representations of indigenous bacteria following decontamination.

CONCLUSIONS

We provide insight into experimental design, quality control steps and "denoising" approaches for 16S rRNA gene high-throughput sequencing of low biomass specimens. We highlight the need for careful assessment of DNA extraction methods and storage buffers; sequence quality and reproducibility; and in silico identification of contaminant profiles in order to avoid spurious results.

Intraindividual Variation and Personal Specificity of Salivary Microbiota

Salivary microbiota is a typical habitat of the human microbiome. This study intended to use salivary microbiota as a model aiming to systematically address the influence of collection methods and temporal dynamics on the human microbiota compared to personal specificity. We carried out a supervised short-term longitudinal study to evaluate the influence of the change of collection methods and sampling time point on salivary microbiota in 10 systemically and orally healthy individuals with certain confounding factors (sex, oral and general health state, medication history, physical exercise, diet, and oral hygiene behavior) controlled before and during the sampling period. The microbial profiles were analyzed by 16S rDNA V3 to V4 hypervariable region amplicon sequencing. The taxonomic structure represented by the dominant species and the weighted UniFrac distance algorithm were used to demonstrate the individual specificity and the intraindividual variation introduced by the change of collection method and sampling time point. The findings suggested individual specificity existed in salivary microbiota from individuals with similar oral and general health status. The intraindividual variation brought by the change of collection method or sampling time point might introduce remarkable perturbation with the personal specificity. Insights into the intraindividual variation and personal specificity of salivary microbiota will enhance our understanding in salivary microbiota-related research. We recommend keeping collection conditions consistent within a study to avoid interference brought by the sampling. The strategy of repeated sampling at multiple time points as representative samples, as well as thorough interpretation of the complex relationships and causality between microbiome composition and disease without the interference of temporal dynamics, is optimal for research exploring the relationship between the salivary microbiome and disease.

Tendentious effects of automated and manual metagenomic DNA purification protocols on broiler gut microbiome taxonomic profiling

Here, we developed protocols to improve sensitivity, rigor and comparability of 16S rRNA gene amplification-based next-generation sequencing (NGS) results. A thorough study was performed by evaluating extraction efficiency with respect to the yield, purity, fragmentation of the purified DNA, and sequencing metrics considering the number of quality reads, amplicon sequence variants (ASVs), community structure and biodiversity. We identified batch-effects that significantly bias broiler gastrointestinal tract (GIT) community compositions and made recommendations to improve sensitivity, consistency, and cross-study comparability. We found that the purity of the extracted nucleic acid had a strong effect on the success rate of downstream library preparations. The preparation of stool bacterial suspensions from feces showed a significant positive influence on community biodiversity by enriching Gram-negative bacteria and cataloguing low abundant taxa with greater success than direct processing of fecal material. Applications relying on the automated Roche MagNa Pure 24 magnetic-bead based method provided results with high consistency therefore it seems to be the optimal choice in large-scale studies for investigating broiler GIT microbiota.

Method Validation for Extraction of DNA from Human Stool Samples for Downstream Microbiome Analysis

Background: A formal method validation for biospecimen processing in the context of accreditation in laboratories and biobanks is lacking. A previously optimized stool processing protocol was validated for fitness-for-purpose for downstream microbiome analysis. Materials and Methods: DNA extraction from human stool was validated with various collection tubes, stabilizing solutions and storage conditions in terms of fitness-for-purpose for downstream microbiome analysis, robustness, and sample stability. Acceptance criteria were based on accurate identification of a reference material, homogeneity of extracted samples, and sample stability in a 2-year period. Results: The automated DNA extraction using the chemagic™ Magnetic Separation Module I (MSM I) extracted 8 out of 8 bacteria in the ZymoBIOMICS^® Microbial Community Standard. Seven tested stabilizing solutions (OMNIgene^®•GUT, RNAlater^®, AquaStool™, RNAssist, PerkinElmer SEB lysis buffer, and DNA Genotek's CP-150) were all compatible with the chemagic MSM I and showed no significant difference in microbiome alpha diversity and no significant difference in the overall microbiome composition compared to the baseline snap-frozen stool sample. None of the stabilizing solutions showed intensive polymerase chain reaction (PCR) inhibition in the SPUD assay. However, when we take into account more stringent criteria which include a higher double-stranded DNA yield, higher DNA purity, and absence of PCR inhibition, we recommend the use of OMNIgene•GUT, RNAlater, or AquaStool as alternatives to rapid freezing of samples. The highest sample homogeneity was achieved with RNAlater- and OMNIgene•GUT -stabilized samples. Sample stability after a 2-year storage in -80°C was seen with OMNIgene•GUT -stabilized samples. Conclusions: We validated a combination of a stool processing method with various collection methods, suitable for downstream microbiome applications. Sample collection, storage conditions and DNA extraction methods can influence the microbiome profile results. Laboratories and biobanks should ensure that these conditions are systematically recorded in the scope of accreditation.

Consistent Metagenome-Derived Metrics Verify and Delineate Bacterial Species Boundaries

There is controversy about whether bacterial diversity is clustered into distinct species groups or exists as a continuum. To address this issue, we analyzed bacterial genome databases and reports from several previous large-scale environment studies and identified clear discrete groups of species-level bacterial diversity in all cases. Genetic analysis further revealed that quasi-sexual reproduction via horizontal gene transfer is likely a key evolutionary force that maintains bacterial species integrity. We next benchmarked over 100 metrics to distinguish these bacterial species from each other and identified several genes encoding ribosomal proteins with high species discrimination power. Overall, the results from this study provide best practices for bacterial species delineation based on genome content and insight into the nature of bacterial species population genetics.

Longstanding questions relate to the existence of naturally distinct bacterial species and genetic approaches to distinguish them. Bacterial genomes in public databases form distinct groups, but these databases are subject to isolation and deposition biases. To avoid these biases, we compared 5,203 bacterial genomes from 1,457 environmental metagenomic samples to test for distinct clouds of diversity and evaluated metrics that could be used to define the species boundary. Bacterial genomes from the human gut, soil, and the ocean all exhibited gaps in whole-genome average nucleotide identities (ANI) near the previously suggested species threshold of 95% ANI. While genome-wide ratios of nonsynonymous and synonymous nucleotide differences (dN/dS) decrease until ANI values approach ∼98%, two methods for estimating homologous recombination approached zero at ∼95% ANI, supporting breakdown of recombination due to sequence divergence as a species-forming force. We evaluated 107 genome-based metrics for their ability to distinguish species when full genomes are not recovered. Full-length 16S rRNA genes were least useful, in part because they were underrecovered from metagenomes. However, many ribosomal proteins displayed both high metagenomic recoverability and species discrimination power. Taken together, our results verify the existence of sequence-discrete microbial species in metagenome-derived genomes and highlight the usefulness of ribosomal genes for gene-level species discrimination.

IMPORTANCE There is controversy about whether bacterial diversity is clustered into distinct species groups or exists as a continuum. To address this issue, we analyzed bacterial genome databases and reports from several previous large-scale environment studies and identified clear discrete groups of species-level bacterial diversity in all cases. Genetic analysis further revealed that quasi-sexual reproduction via horizontal gene transfer is likely a key evolutionary force that maintains bacterial species integrity. We next benchmarked over 100 metrics to distinguish these bacterial species from each other and identified several genes encoding ribosomal proteins with high species discrimination power. Overall, the results from this study provide best practices for bacterial species delineation based on genome content and insight into the nature of bacterial species population genetics.

Culture-Dependent and -Independent Analyses Reveal the Diversity, Structure, and Assembly Mechanism of Benthic Bacterial Community in the Ross Sea, Antarctica

The benthic bacterial community in Antarctic continental shelf ecosystems are not well-documented. We collected 13 surface sediments from the Ross Sea, a biological hotspot in high-latitude maritime Antarctica undergoing rapid climate change and possible microflora shift, and aimed to study the diversity, structure and assembly mechanism of benthic bacterial community using both culture-dependent and -independent approaches. High-throughput sequencing of 16S rRNA gene amplicons revealed 370 OTUs distributed in 21 phyla and 284 genera. The bacterial community was dominated by Bacteroidetes, Gamma- and Alphaproteobacteria, and constituted by a compact, conserved and positively-correlated group of anaerobes and other competitive aerobic chemoheterotrophs. Null-model test based on βNTI and RCBray indicated that stochastic processes, including dispersal limitation and undominated fractions, were the main forces driving community assembly. On the other hand, environmental factors, mainly temperature, organic matter and chlorophyll, were significantly correlated with bacterial richness, diversity and community structure. Moreover, metabolic and physiological features of the prokaryotic taxa were mapped to evaluate the adaptive mechanisms and functional composition of the benthic bacterial community. Our study is helpful to understand the structural and functional aspects, as well as the ecological and biogeochemical role of the benthic bacterial community in the Ross Sea.

Is a vegan or a vegetarian diet associated with the microbiota composition in the gut? Results of a new cross-sectional study and systematic review

It is assumed that diet influences the composition of gut microbiota, which in turn may affect human health status. This systematic review aimed to summarize associations of a vegan or vegetarian diet with the composition of microbiota. A literature search was conducted in PubMed and Embase for eligible human studies with vegan or vegetarian diets as an exposure and microbiota composition as an outcome in healthy adults. Furthermore, data from our cross-sectional study with vegan participants were included. Out of sixteen included studies, six investigated the association between gut microbiota composition in both vegans and in vegetarians, six in vegans and four studies in vegetarians compared to omnivores, respectively. Among 5 different phyla, 28 families, 96 genera and 177 species, Bacteroides, Bifidobacterium and Prevotella were the most reported genera, followed by the species Prevotella copri, Faecalibacterium prausnitzii and Escherichia coli in all diets. No consistent association between a vegan diet or vegetarian diet and microbiota composition compared to omnivores could be identified. Moreover, some studies revealed contradictory results. This result could be due to high microbial individuality, and/or differences in the applied approaches. Standardized methods with high taxonomical and functional resolutions are needed to clarify this issue.

Storage media and not extraction method has the biggest impact on recovery of bacteria from the oral microbiome

Next Generation sequencing has greatly progressed the exploration of the oral microbiome’s role in dental diseases, however, there has been little focus on the effect of sample storage conditions and their interaction with DNA extraction method. Dental plaque samples collected from 20 healthy participants were pooled and stored in either 75% ethanol or Bead solution for up to 6-months at −80 °C, prior to DNA extraction with either QIAamp (non-bead beating) or PowerSoil (bead-beating) kit, followed by Illumina sequencing of 16S rRNA gene. We found that storage media and not extraction method had the biggest influence on the diversity and abundance of the oral microbiota recovered. Samples stored in Bead solution, independent of the extraction kit, retrieved higher diversity (PowerSoil p = 1.64E-07, QIAamp p = 0.0085) and had dissimilar overall ecologies as indicated by lower level of shared diversity (PowerSoil p = 0.0000237, QIAamp p = 0.0088). Comparatively, samples stored in Bead solution and extracted with PowerSoil recovered a higher abundance of Streptococcus species. These data indicate that Bead solution can preserve the oral microbiome in dental plaque reliably, for periods of up to 6-months at −80 °C, and is compatible, with either a bead-beating or non-bead beating DNA extraction method.

Rapid start-up of partial nitritation in aerobic granular sludge bioreactor and the analysis of bacterial community dynamics

The rapid start-up of the partial nitritation process in a laboratory-scale aerobic granular sludge-sequencing batch reactor was successful by controlling low dissolved oxygen and gradually increasing the influent ammonia levels. The microbial community dynamics were analyzed by high-throughput sequencing and quantitative polymerase chain reaction. The microbial communities were significantly affected by the different influent NH₄⁺-N concentrations (77.84, 119.42, 170.31, and 252.21 mg/L) in Phases I, II, III, and IV. The sludge Shannon index in Phases I, II, III, and IV was 3.9, 4.39, 3.47, and 2.13, respectively, which was higher than that of the inoculated sludge (1.62). The dominant class transformed from Alphaproteobacteria and Gammaproteobacteria in Phase I to Betaproteobacteria in Phase IV. Furthermore, Sphingobacteria and Clostridia were the dominant bacteria in Phases III and IV. The quantitative polymerase chain reaction (qPCR) results suggested that Nitrosomonadaceae_uncultured belonging to ammonia-oxidizing bacterium was the dominant species, but the relative abundance of nitrite-oxidizing bacteria (mainly Nitrospira and Nitrobacter) was extremely rare in Phase IV. Furthermore, Thauera, Denitratisoma, and Planctomycetacia were the dominant functional nitrogen removal microbes in Phases III and IV. Some nitrogen removal pathways such as partial nitritation, denitrification, and anaerobic ammonium oxidation co-existed in the partial nitritation process.

Storage and handling of human faecal samples affect the gut microbiome composition: A feasibility study

Human gut microbiome analysis through faecal sampling typically involves five stages: sample collection, storage, DNA extraction, next generation sequencing and bioinformatics analysis. Of these, the first three are considered irreversible. This feasibility study describes an assessment of methodologies used for faecal DNA extraction and sample handling, using the parameters DNA yield, purity and resultant microbial profile. Six DNA extraction techniques, including commercially available kits and manual protocols were compared on human faecal samples (n = 3). Different extraction techniques produced significant variance in DNA yield (range 2.7-164 ng/mg faeces) and microbial diversity profiles, with considerable variation in phyla dominance (Firmicutes (P < 0.001), Bacteroidetes (P = 0.003), Actinobacteria (P = 0.003), One-way ANOVA). The most effective method, with the highest DNA yield, was a simple and inexpensive extraction technique named MetaHIT. Using this method, DNA was extracted from separate faecal samples (n = 3) and had been aliquoted to seven storage conditions including three stabilizing buffers and three temperature conditions, for a period of 120-h, with storage at -80 °C as a control treatment. DNA yield and purity was not statistically different between the control and remaining treatments. 16S rDNA-based diversity profile was largely comparable across the treatments with only minor differences in genera between samples stored at room temperature in air and - 80 °C control. Overall these results suggest that the choice of DNA extraction method has a greater influence on the resultant microbial diversity profile than the short-term storage method.

DNA extraction and amplicon production strategies deeply inf luence the outcome of gut mycobiome studies

Microbial ecology studies are often performed through extraction of metagenomic DNA followed by amplification and sequencing of a marker. It is known that each step may bias the results. These biases have been explored for the study of bacterial communities, but rarely for fungi. Our aim was therefore to evaluate methods for the study of the gut mycobiome. We first evaluated DNA extraction methods in fungal cultures relevant to the gut. Afterwards, to assess how these methods would behave with an actual sample, stool from a donor was spiked with cells from the same cultures. We found that different extraction kits favour some species and bias against others. In terms of amplicon sequencing, we evaluated five primer sets, two for ITS2 and one for ITS1, 18S and 28S rRNA. Results showed that 18S rRNA outperformed the other markers: it was able to amplify all the species in the mock community and to discriminate among them. ITS primers showed both amplification and sequencing biases, the latter related to the variable length of the product. We identified several biases in the characterisation of the gut mycobiome and showed how crucial it is to be aware of these before drawing conclusions from the results of these studies.

Comparison of DNA Extraction Efficiency and Reproducibility of Different Aeration Diffuser Biofilms Using Bead-Beating Protocol

An existing bead-beating DNA extraction protocol was employed to compare the DNA extraction recovery and fragment quality of 6 different aeration diffuser biofilms. Escherichia coli, Gordonia amarae, and mixed liquor were used as controls. The fraction of total DNAbiofilm decreased monotonically with increasing number of beat beatings (BB) when the amount of DNA present was sufficient (>4 μgDNA/cm2), excluding the ceramic disk. While controls required only 2 BBs, 3 out of 5 BBs achieved ≥70% of total DNA (70.3 ± 1.7%) for 5 out of 6 biofilms. Quantitative polymerase chain reaction (PCR) analyses of 353 and 1,505 basepair (bp) amplicons from pure culture extracts showed target copy numbers were not degraded for the first 2 BBs, but the third BB decreased amplicon concentrations by 0.65 and 1.12 log for E. coli, and 0.39 and 0.40 log for G. amarae, respectively. The 353 bp fragment amplification from biofilm samples showed minimal degradation for the first 3 BBs. PCR and gel electrophoresis confirmed integrity of amplified 1,505 bp DNA fragments over the 5 BBs, except in the EDPM (75 mm diameter, tube) diffuser biofilm (4.98 ± 0.62 μgDNA/cm2). Taken together, this study showed type of diffuser membrane biofilms had no effects on extraction efficiency, but low DNA concentrations reduced extraction performance.