Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis

Impact of cell lysis treatment before saliva metagenomic DNA extraction on the oral microbiome and the associated resistome

OBJECTIVES

The human oral microbiome, a complex ecosystem linked to oral and systemic health, harbors a diverse array of microbial populations, including antimicrobial resistance genes (ARGs). As a critical component of the One Health approach to tackle antibiotic resistance, comprehending the oral resistome's composition and diversity is imperative. The objective of this study was to investigate the impact of chemical cell lysis treatment using MetaPolyzyme on the detectability of the oral microbiome, resistome, and DNA quality and quantity.

MATERIALS AND METHODS

Saliva samples were collected from five healthy individuals, and each of the samples was subjected to DNA extraction with and without the treatment with MetaPolyzyme. Through metagenomic sequencing, we analyzed, assessed, and compared the microbial composition, resistome, and DNA characteristics between both groups of extracted DNA.

RESULTS

Our study revealed that MetaPolyzyme treatment led to significant shifts in the detectability of microbial composition, favoring Gram-positive bacteria, notably Streptococcus, over Gram-negative counterparts. Moreover, the MetaPolyzyme treatment also resulted in a distinct change in ARG distribution. This shift was characterized by an elevated proportion of ARGs linked to fluoroquinolones and efflux pumps, coupled with a reduction in the prevalence of tetracycline and β-lactam resistance genes when compared with the nontreated group. Alpha diversity analysis demonstrated altered species and ARG distribution without affecting overall diversity, while beta diversity analysis confirmed significant differences in the taxonomical composition and oral resistome between treated and nontreated groups.

CONCLUSIONS

These findings underscore the critical role of cell lysis treatment in optimizing oral metagenomic studies and enhance our understanding of the oral resistome's dynamics in the context of antimicrobial resistance.

Metabarcoding reveals unique microbial mat communities and evidence of biogeographic influence in low-oxygen, high-sulfur sinkholes and springs

High-sulfur, low-oxygen environments formed by underwater sinkholes and springs create unique habitats populated by microbial mat communities. To explore the diversity and biogeography of these mats, samples were collected from three sites in Alpena, Michigan, one site in Monroe, Michigan, and one site in Palm Coast, Florida. Our study investigated previously undescribed eukaryotic diversity in these habitats and further explored their bacterial communities. Mat samples and water parameters were collected from sulfur spring sites during the spring, summer, and fall of 2022. Cyanobacteria and diatoms were cultured from mat subsamples to create a culture-based DNA reference library. Remaining mat samples were used for metabarcoding of the 16S and rbcL regions to explore bacterial and diatom diversity, respectively. Analyses of water chemistry, alpha diversity, and beta diversity articulated a range of high-sulfur, low-oxygen habitats, each with distinct microbial communities. Conductivity, pH, dissolved oxygen, temperature, sulfate, and chloride had significant influences on community composition but did not describe the differences between communities well. Chloride concentration had the strongest correlation with microbial community structure. Mantel tests revealed that biogeography contributed to differences between communities as well. Our results provide novel information on microbial mat composition and present evidence that both local conditions and biogeography influence these unique communities.

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.

Isolation, identification, and significance of salivary Veillonella spp., Prevotella spp., and Prevotella salivae in patients with inflammatory bowel disease

The global prevalence of inflammatory bowel disease (IBD) is on the rise, prompting significant attention from researchers worldwide. IBD entails chronic inflammatory disorders of the intestinal tract, characterized by alternating flares and remissions. Through high-throughput sequencing, numerous studies have unveiled a potential microbial signature for IBD patients showing intestinal enrichment of oral-associated bacteria. Simultaneously, the oral microbiome can be perturbed by intestinal inflammation. Our prior investigation, based on 16S rRNA amplicon sequencing, underscored elevated abundance of Veillonella spp. and Prevotella spp. in the salivary microbiomes of IBD patients. Noteworthy, Prevotella salivae emerged as a distinct species significantly associated with IBD. P. salivae is an under-recognized pathogen that was found to play a role in both oral and systemic diseases. In this study, we delve deeper into the salivary microbiomes of both IBD patients and healthy controls. Employing diverse cultivation techniques and real-time quantitative polymerase chain reactions (RT-qPCR), we gauged the prevalence and abundance of Veillonella spp., Prevotella spp., and P. salivae. Our isolation efforts yielded 407 and 168 strains of Veillonella spp., as well as 173 and 90 strains of Prevotella spp., from the saliva samples of IBD patients and healthy controls, respectively. Veillonella-vancomycin agar emerged as the discerning choice for optimal Veillonella spp. cultivation, while Schaedler kanamycin-vancomycin agar proved to be the most suitable medium for cultivating Prevotella spp. strains. Comparing our RT-qPCR findings to the previous 16S rRNA amplicon sequencing data, the results corroborated the higher abundance of Veillonella spp., Prevotella spp., and P. salivae in the saliva of IBD patients compared to healthy controls. However, it's worth noting that in contrast to RT-qPCR, the 16S rRNA amplicon sequencing data revealed greater absolute abundance of all three bacterial groups in both IBD patients and controls.

Exploring the microbiome of two uterine sites in cows

Bacterial communities in the mammalian reproductive system can be rich and diverse, differing in structure and quantity depending on location. In addition, its microbiome is associated with the state of health of this tract and reproductive success. This study evaluated the microbiome composition of the uterine body (UB) and uterine horn mucosa (UH) samples using 16S rRNA sequencing of samples extracted from cows in the Amazon region. It was observed that four main phyla were shared between the uterine sites: Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Linear discriminant analysis effect size and heat tree analysis showed that members of Lachnospiraceae (NK3A20 group) and Oscillospiraceae were significantly more abundant in the UB than in UH. In addition, there are more unique genera in the UB than in the UH. A higher bacterial load in UB than in UH is expected because of the exposure to external factors of UB. However, comparing the site's communities through beta diversity did not generate well-defined clustering. Thus, it can be attributed to the closeness of the sites, which would make the niches similar ecologically and microbiologically. Therefore, this research provides knowledge to understand biomarkers in the prior reproduction period.

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

BACKGROUND

The development of sequencing technologies to evaluate bacterial microbiota composition has allowed new insights into the importance of microbial ecology. However, the variety of methodologies used among amplicon sequencing workflows leads to uncertainty about best practices as well as reproducibility and replicability among microbiome studies. Using a bacterial mock community composed of 37 soil isolates, we performed a comprehensive methodological evaluation of workflows, each with a different combination of methodological factors spanning sample preparation to bioinformatic analysis to define sources of artifacts that affect coverage, accuracy, and biases in the resulting compositional profiles.

RESULTS

Of the workflows examined, those using the V4-V4 primer set enabled the highest level of concordance between the original mock community and resulting microbiome sequence composition. Use of a high-fidelity polymerase, or a lower-fidelity polymerase with an increased PCR elongation time, limited chimera formation. Bioinformatic pipelines presented a trade-off between the fraction of distinct community members identified (coverage) and fraction of correct sequences (accuracy). DADA2 and QIIME2 assembled V4-V4 reads amplified by Taq polymerase resulted in the highest accuracy (100%) but had a coverage of only 52%. Using mothur to assemble and denoise V4-V4 reads resulted in a coverage of 75%, albeit with marginally lower accuracy (99.5%).

CONCLUSIONS

Optimization of microbiome workflows is critical for accuracy and to support reproducibility and replicability among microbiome studies. These considerations will help reveal the guiding principles of microbial ecology and impact the translation of microbiome research to human and environmental health.

Distribution of the new functional marker gene (pahE) of aerobic polycyclic aromatic hydrocarbon (PAHs) degrading bacteria in different ecosystems

Understanding the degradation potentials in PAHs-contaminated sites is significant for formulating effective bioremediation strategies. pahE encoding PAHs hydratase-aldolase has been proven as a better new functional marker gene of aerobic PAHs-degrading bacteria to assess the biodegradation potential of indigenous PAHs-degrading bacterial population. However, the distribution of pahE and its relationship with environmental factors remain unknown. The present study observed spatial variations in the diversity and abundance of pahE across oilfield soils, mangrove sediments, and urban roadside soils. nahE from Pseudomonas, bphE from Hyphomonas oceanitis, nagE from Comamonas testosterone, and novel pahE genes were widely present in these PAHs-polluted ecosystems. The abundance of pahE in PAHs-contaminated sites was in the range of 10⁵-10⁶ copies·g^-1 (dry weight). Redundancy analysis and Pearson's correlation analysis implied that the distribution of pahE in the PAHs-contaminated environment was mainly shaped by environmental factors such as PAHs pollution level, nutrient level, salinity, and water content. This work was the first to explore the distribution of the new functional marker gene (pahE) and its links with environmental parameters, which provided new insights into the ecophysiology and distribution of indigenous aerobic PAHs-degrading bacteria in contaminated sites.

Interaction between Host and Microbes in the Semen of Patients with Idiopathic Nonobstructive Azoospermia

Men with nonobstructive azoospermia (NOA) face the dual problems of low sperm count and low sperm quality. Most men with NOA without a clear cause are classified as having idiopathic NOA (iNOA). Previous studies found that microbes exist in semen, and the semen microbes of NOA men are different from those of normal men. However, the relevant mechanism is not clear. In this study, we answered the three questions of "who is there," "what is it doing," and "who is doing it" by combining 16s rRNA, nontargeted metabolome detection and metabolite traceability analysis. We found that the composition and interaction of seminal plasma microbes in the iNOA group changed. Metabolite traceability analysis and metabolic pathway analysis revealed that microbial abnormalities in the NOA group were closely related to the decrease of microbial degradation of toluene and the increase of metabolism of fructose or mannose. In addition, the metabolic relationship between microbes and the host in male semen in iNOA revealed that such microbes can produce harmful metabolites that affect sperm quality, the microbes compete with sperm for essential nutrients, and their presence reduces sperm production of essential nutrients. IMPORTANCE Idiopathic nonobstructive azoospermia is one of the great challenges in assisted reproductive therapy. Although microdissection testicular sperm extraction technology is currently available, many men with iNOA still face the problem of poor sperm retrieval and poor sperm quality. The role of seminal plasma microbes in male disease has been continuously investigated since semen was demonstrated to harbor commensal microbes. To our knowledge, this is the first detailed description of the microbe-host relationship in iNOA semen. This study is an important complement to research on the treatment and etiology of iNOA and the rationale for our ongoing research.

[Transcriptome analysis of tissue microbiota diversity in tumor and non-tumor lymph nodes]

BACKGROUND

Metagenomic studies in recent years have demonstrated that all tissues of the human body studied by genomic and transcriptomic sequencing methods, both in pathological processes and in normality, contain fragments of DNA and RNA from a variety of microorganisms. The composition of tissue microbiota and its relationship with development of pathological changes are still poorly understood, despite increasing number of studies in this area every year. In this study, gene expression of the lymph node microbiome in reactive follicular hyperplasia and follicular lymphoma was investigated.

OBJECTIVE

To study expression of lymph node microbiome genes in reactive follicular hyperplasia and follicular lymphoma.

MATERIAL AND METHODS

The work included 38 biopsy samples of lymph nodes with follicular lymphoma of different cytological subtypes and 10 biopsy samples of lymph nodes with reactive follicular hyperplasia. Verification of diagnosis was carried out using standard histological, histochemical and immunohistochemical methods. Using sequencing method, the transcriptome was examined. Statistical analysis and data visualization were performed using the R programming language (version 4.2.1).

RESULTS

Tumor lymph nodes are characterized by large Simpson and Shannon alpha diversity values (p-value = 0.026465 and p-value = 0.007122, respectively). Two clusters were discovered, characterized by different levels of relative abundance of microorganisms.

CONCLUSION

It has been proven that diversity of microorganisms present in tumor tissue and their number are statistically significantly higher than corresponding indicators in the lymph nodes with follicular hyperplasia.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias

Plankton metabarcoding is increasingly implemented in marine ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on microscopy (morphological). 18S rRNA gene is the most widely used marker for groups’ and species’ detection and classification within marine eukaryotic microorganisms. These datasets have commonly relied on the acquisition of organismal abundances directly from the number of DNA sequences (i.e. reads). Besides the inherent technical biases in metabarcoding, the largely varying 18S rRNA gene copy numbers (GCN) among marine protists (ranging from tens to thousands) is one of the most important biological biases for species quantification. In this work, we present a gene copy number correction factor (CF) for four marine planktonic groups: Bacillariophyta, Dinoflagellata, Ciliophora miscellaneous and flagellated cells. On the basis of the theoretical assumption that ‘1 read’ is equivalent to ‘1 GCN’, we used the GCN median values per plankton group to calculate the corrected cell number and biomass relative abundances. The species-specific absolute GCN per cell were obtained from various studies published in the literature. We contributed to the development of a species-specific 18S rRNA GCN database proposed by previous authors. To assess the efficiency of the correction factor we compared the metabarcoding, morphological and corrected relative abundances (in cell number and biomass) of 15 surface water samples collected in the Belgian Coastal Zone. Results showed that the application of the correction factor over metabarcoding results enables us to significantly improve the estimates of cell abundances for Dinoflagellata, Ciliophora and flagellated cells, but not for Bacillariophyta. This is likely to due to large biovolume plasticity in diatoms not corresponding to genome size and gene copy numbers. C-biomass relative abundance estimations directly from amplicon reads were only improved for Dinoflagellata and Ciliophora. The method is still facing biases related to the low number of species GCN assessed. Nevertheless, the increase of species in the GCN database may lead to the refinement of the proposed correction factor.

Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China

Reducing the application of chemical fertilizers can improve the quality and promote the sustainable use of cultivated land, which is part of the green and sustainable development of agriculture. Based on the 2019 China Rural Household Panel Survey data, this article evaluated the impact of cultivated-land-management scale on fertilizer reduction via the OLS regression method. The results showed that, after controlling for other factors, the scale of cultivated land management is a strong factor affecting the intensity of fertilizer application by Chinese farmers. According to the results of quantitative analysis, the amount of fertilizer applied per hectare decreased by 20.6% for every 1 ha increase in the average grain sown area per household. The study also found that employing workers in agricultural production and operation can help achieve the aim of fertilizer reduction, but the fact that the head of the household is male, the increase in total household income and the increase in the proportion of household agricultural labor are not conducive to fertilizer reduction. A mechanism-of-action test showed that the expansion of the scale of cultivated land management can drive the reduction of chemical-fertilizer use by urging farmers to adopt agricultural technology and mechanized fertilization. Extensive research found that the fragmentation of cultivated land increased the amount of fertilizer applied per hectare by farmers. Therefore, the fragmentation of cultivated fields is a barrier to decreasing fertilizer application.

Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses

Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3−V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results.

Microbial Biopesticides against Bacterial, Fungal and Oomycete Pathogens of Tomato, Cabbage and Chickpea

Biological control is an environmentally friendly approach that holds promise to complement or replace chemicals to effectively protect crop plants against pests and pathogens. Environmental samples with highly diverse and competitive microbiomes that harbor antagonistic microbes with diverse modes-of-action can provide a rich source of microbial biopesticides. In the current study, bacteria isolated from rhizosphere soil and food spoilage samples were subsequently screened against various plant fungal and oomycete pathogens in growth inhibition assays. These included the new potential biocontrol bacteria Corynebacterium flavescens, Sporosarcina aquimarina and Sporosarcina saromensis with anti-fungal and antioomycete activities. Potential candidates selected by preliminary screening in plant assays were then applied to tomato, cabbage and chickpea plants to control bacterial (Pseudomonas syringae pv. tomato), fungal (Alternaria brassicicola) and oomycete (Phytophtora medicaginis) phytopathogens. Ten potential microbial biopesticides were demonstrated to be effective against these diseases, and led to significant (p < 0.05) reductions in symptoms and/or pathogen DNA compared to mock-treated diseased plants. We conclude that new and effective microbial biopesticides to control crop pathogens can be rapidly isolated from biodiverse microbiomes, where bacteria may employ these features to effectively compete against each other.

Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding

Accuracy of PCR amplification is vital for obtaining reliable amplicon-sequencing results by metabarcoding. Here, we performed a comparative analysis of error profiles in the PCR products by 14 different PCR kits using a mock eukaryotic community DNA sample mimicking metabarcoding analysis. To prepare a mock eukaryotic community from the marine environment, equal amounts of plasmid DNA from 40 microalgal species were mixed and used for amplicon-sequencing by a high-throughput sequencing approach. To compare the differences in PCR kits used for this experiment, we focused on the following seven parameters: 1) Quality, 2) Chimera, 3) Blast top hit accuracy, 4) Deletion, 5) Insertion, 6) Base substitution and 7) Amplification bias amongst species. The results showed statistically significant differences (p &lt; 0.05) for all of the seven parameters depending on the PCR kits used. These differences may result from the different DNA polymerases included in each kit, although the result can also be influenced by PCR reaction conditions. Simultaneous analysis of several parameters suggested that kits containing KOD plus Neo (TOYOBO) and HotStart Taq DNA polymerase (BiONEER, CA, US) at the annealing temperature of 65 °C displayed better results in terms of parameters associated with chimeras, top hit similarity and deletions.

Centennial Review: Factors affecting the chicken gastrointestinal microbial composition and their association with gut health and productive performance

Maintenance of "gut health" is considered a priority in commercial chicken farms, although a precise definition of what constitutes gut health and how to evaluate it is still lacking. In research settings, monitoring of gut microbiota has gained great attention as shifts in microbial community composition have been associated with gut health and productive performance. However, microbial signatures associated with productivity remain elusive because of the high variability of the microbiota of individual birds resulting in multiple and sometimes contradictory profiles associated with poor or high performance. The high costs associated with the testing and the need for the terminal sampling of a large number of birds for the collection of gut contents also make this tool of limited use in commercial settings. This review highlights the existing literature on the chicken digestive system and associated microbiota; factors affecting the gut microbiota and emergence of the major chicken enteric diseases coccidiosis and necrotic enteritis; methods to evaluate gut health and their association with performance; main issues in investigating chicken microbial populations; and the relationship of microbial profiles and production outcomes. Emphasis is given to emerging noninvasive and easy-to-collect sampling methods that could be used to monitor gut health and microbiological changes in commercial flocks.

Impact of Bead-Beating Intensity on the Genus- and Species-Level Characterization of the Gut Microbiome Using Amplicon and Complete 16S rRNA Gene Sequencing

Bead-beating within a DNA extraction protocol is critical for complete microbial cell lysis and accurate assessment of the abundance and composition of the microbiome. While the impact of bead-beating on the recovery of OTUs at the phylum and class level have been studied, its influence on species-level microbiome recovery is not clear. Recent advances in sequencing technology has allowed species-level resolution of the microbiome using full length 16S rRNA gene sequencing instead of smaller amplicons that only capture a few hypervariable regions of the gene. We sequenced the v3-v4 hypervariable region as well as the full length 16S rRNA gene in mouse and human stool samples and discovered major clusters of gut bacteria that exhibit different levels of sensitivity to bead-beating treatment. Full length 16S rRNA gene sequencing unraveled vast species diversity in the mouse and human gut microbiome and enabled characterization of several unclassified OTUs in amplicon data. Many species of major gut commensals such as Bacteroides, Lactobacillus, Blautia, Clostridium, Escherichia, Roseburia, Helicobacter, and Ruminococcus were identified. Interestingly, v3-v4 amplicon data classified about 50% of Ruminococcus reads as Ruminococcus gnavus species which showed maximum abundance in a 9 min beaten sample. However, the remaining 50% of reads could not be assigned to any species. Full length 16S rRNA gene sequencing data showed that the majority of the unclassified reads were Ruminococcus albus species which unlike R. gnavus showed maximum recovery in the unbeaten sample instead. Furthermore, we found that the Blautia hominis and Streptococcus parasanguinis species were differently sensitive to bead-beating treatment than the rest of the species in these genera. Thus, the present study demonstrates species level variations in sensitivity to bead-beating treatment that could only be resolved with full length 16S rRNA sequencing. This study identifies species of common gut commensals and potential pathogens that require minimum (0-1 min) or extensive (4-9 min) bead-beating for their maximal recovery.

Gut microbiota and probiotic therapy in ADHD: A review of current knowledge

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by inattention, impulsivity and hyperactivity. The etiology of the disorder is multi-factorial, with a main focus on genetic factors. However, emerging research shows the involvement of changes and imbalances in the intestinal microbiota. Evidence for the influence of gut microbiota on brain development and neurogenesis is clear. We present a review of emerging research on the microbiota in the ADHD population. The aim of this study was to summarize the current state of knowledge on ADHD, to identify gaps in knowledge, as well as to indicate the directions of new research. Thanks to the researchers that would be possible to better understand the complexity of ADHD etiology, especially the role of the intestinal microbiota in the pathogenesis of the disorder. Pubmed, Scopus and Google Scholar databases were used while writing the review. Numerous studies show that probiotic supplementation can have a positive effect on the course of neurodevelopmental disorders, including ADHD. Unfortunately, clinical studies that were identified are mostly inconclusive, and more high-quality research is needed to produce robust evidence for therapy based on interventions targeting microbiota.

Application, release, ecotoxicological assessment of biocide in building materials and its soil microbial response

Biocides are used in building materials to protect the building against microbial colonization and biodeterioration. However, these biocides are introduced by gradual leaching into soils in proximity of the buildings. This review discusses the aspects and characteristics of biocides from building materials in terms of (i) in-situ leaching and simulation thereof in-vitro and in-field tests, (ii) persistence, as well as photolytic and biodegradation, and its influence on toxicological evaluation, and (iii) evaluation of terrestrial toxicity by conventional ecotoxicological tests and novel holistic testing approaches. These aspects are influenced by multiple parameters, out of which water availability, physicochemical properties of microhabitats, combination of biocidal building materials, soil parameters, and composition of the soil microbiome are of utmost relevance. Deeper understanding of this multiparametric system and development of comprehensive characterization methodologies remains crucial, as to facilitate realistic assessment of the environmental impact of biocides used in construction materials and the corresponding degradation byproducts.

A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes

Comprehensive microbial risk assessment requires high-throughput quantification of diverse microbial risks in the environment. Current metagenomic next-generation sequencing approaches can achieve high-throughput detection of genes indicative of microbial risks but lack quantitative capabilities. This study developed and tested a quantitative metagenomic next-generation sequencing (qmNGS) approach. Numerous xenobiotic synthetic internal DNA standards were used to determine the sequencing yield (Y_seq) of the qmNGS approach, which can then be used to calculate absolute concentration of target genes in environmental samples based on metagenomic sequencing results. The qmNGS approach exhibited excellent linearity as indicated by a strong linear correlation (r² = 0.98) between spiked and detected concentrations of internal standards. High-throughput capability of the qmNGS approach was demonstrated with artificial Escherichia coli mixtures and cattle manure samples, for which 95 ± 3 and 208 ± 4 types of antibiotic resistance genes (ARGs) were detected and quantified simultaneously. The qmNGS approach was further compared with quantitative real-time PCR (qPCR) and demonstrated comparable levels of accuracy and less variation for the quantification of six target genes (16S, tetO, sulI, tetM, ermB, and qnrS). IMPORTANCE Monitoring and comprehensive assessment of microbial risks in the environment require high-throughput gene quantification. The quantitative metagenomic NGS (qmNGS) approach developed in this study incorporated numerous xenobiotic and synthetic DNA internal standard fragments into metagenomic NGS workflow, which are used to determine a new parameter called sequencing yield that relates sequence base reads to absolute concentration of target genes in the environmental samples. The qmNGS approach demonstrated excellent method linearity and comparable performance as the qPCR approach with high-throughput capability. This new qmNGS approach can achieve high-throughput and accurate gene quantification in environmental samples and has the potential to become a useful tool in monitoring and comprehensively assessing microbial risks in the environment.

Discriminatory Detection of ssDNA by Surface-Enhanced Raman Spectroscopy (SERS) and Tree-Based Support Vector Machine (Tr-SVM)

We report label-free detection of 86-base single-stranded DNA (ssDNA) gene segments by surface-enhanced Raman spectroscopy (SERS). The use of a slippery liquid infused porous (SLIP) membrane induced aggregation of 43 nm gold nanoparticles and ssDNA upon pin-free droplet evaporation. The combined SLIPSERS approach generates significant numbers of SERS hot-spots and enabled detection at the 100 nM level of mecA and intI1 gene segments-two genes of interest in the context of antibiotic resistance. Tree-based multiclass support vector machine (Tr-SVM) classifiers were built to discriminate SERS spectra of 12 different gene sequences obtained by SLIPSERS: mecA, intI1, as well as analogues of mecA and intI1, respectively, with 2-10 base mismatches, and two random sequences. The trained predictive Tr-SVM classifiers correctly identified each gene sequence with a prediction accuracy of ∼90%. This study illustrates a novel means for discriminatory label-free SERS detection of ssDNA enabled by Tr-SVM.

A large-scale metagenomic survey dataset of the post-weaning piglet gut lumen

BACKGROUND

Early weaning and intensive farming practices predispose piglets to the development of infectious and often lethal diseases, against which antibiotics are used. Besides contributing to the build-up of antimicrobial resistance, antibiotics are known to modulate the gut microbial composition. As an alternative to antibiotic treatment, studies have previously investigated the potential of probiotics for the prevention of postweaning diarrhea. In order to describe the post-weaning gut microbiota, and to study the effects of two probiotics formulations and of intramuscular antibiotic treatment on the gut microbiota, we sampled and processed over 800 faecal time-series samples from 126 piglets and 42 sows.

RESULTS

Here we report on the largest shotgun metagenomic dataset of the pig gut lumen microbiome to date, consisting of >8 Tbp of shotgun metagenomic sequencing data. The animal trial, the workflow from sample collection to sample processing, and the preparation of libraries for sequencing, are described in detail. We provide a preliminary analysis of the dataset, centered on a taxonomic profiling of the samples, and a 16S-based beta diversity analysis of the mothers and the piglets in the first 5 weeks after weaning.

CONCLUSIONS

This study was conducted to generate a publicly available databank of the faecal metagenome of weaner piglets aged between 3 and 9 weeks old, treated with different probiotic formulations and intramuscular antibiotic treatment. Besides investigating the effects of the probiotic and intramuscular antibiotic treatment, the dataset can be explored to assess a wide range of ecological questions with regards to antimicrobial resistance, host-associated microbial and phage communities, and their dynamics during the aging of the host.

Refinement of 16S rRNA gene analysis for low biomass biospecimens

High-throughput phylogenetic 16S rRNA gene analysis has permitted to thoroughly delve into microbial community complexity and to understand host-microbiota interactions in health and disease. The analysis comprises sample collection and storage, genomic DNA extraction, 16S rRNA gene amplification, high-throughput amplicon sequencing and bioinformatic analysis. Low biomass microbiota samples (e.g. biopsies, tissue swabs and lavages) are receiving increasing attention, but optimal standardization for analysis of low biomass samples has yet to be developed. Here we tested the lower bacterial concentration required to perform 16S rRNA gene analysis using three different DNA extraction protocols, three different mechanical lysing series and two different PCR protocols. A mock microbiota community standard and low biomass samples (10⁸, 10⁷, 10⁶, 10⁵ and 10⁴ microbes) from two healthy donor stools were employed to assess optimal sample processing for 16S rRNA gene analysis using paired-end Illumina MiSeq technology. Three DNA extraction protocols tested in our study performed similar with regards to representing microbiota composition, but extraction yield was better for silica columns compared to bead absorption and chemical precipitation. Furthermore, increasing mechanical lysing time and repetition did ameliorate the representation of bacterial composition. The most influential factor enabling appropriate representation of microbiota composition remains sample biomass. Indeed, bacterial densities below 10⁶ cells resulted in loss of sample identity based on cluster analysis for all tested protocols. Finally, we excluded DNA extraction bias using a genomic DNA standard, which revealed that a semi-nested PCR protocol represented microbiota composition better than classical PCR. Based on our results, starting material concentration is an important limiting factor, highlighting the need to adapt protocols for dealing with low biomass samples. Our study suggests that the use of prolonged mechanical lysing, silica membrane DNA isolation and a semi-nested PCR protocol improve the analysis of low biomass samples. Using the improved protocol we report a lower limit of 10⁶ bacteria per sample for robust and reproducible microbiota analysis.

A Comparison of DNA Metabarcoding and Microscopy Methodologies for the Study of Aquatic Microbial Eukaryotes

The procedures and methodologies employed to study microbial eukaryotic plankton have been thoroughly discussed. Two main schools exist—one insisting on classic microscopy methodologies and the other supporting modern high-throughput sequencing (DNA metabarcoding). However, few studies have attempted to combine both these approaches; most studies implement one method while ignoring the other. This work aims to contribute to this discussion and examine the advantages and disadvantages of each methodology by comparing marine plankton community results from microscopy and DNA metabarcoding. The results obtained by the two methodologies do not vary significantly for Bacillariophyta, although they do for Dinoflagellata and Ciliophora. The lower the taxonomic level, the higher the inconsistency between the two methodologies for all the studied groups. Considering the different characteristics of microscopy-based identification and DNA metabarcoding, this work underlines that each method should be chosen depending on the aims of the study. DNA metabarcoding provides a better estimate of the taxonomic richness of an ecosystem while microscopy provides more accurate quantitative results regarding abundance and biomass. In any case, the combined use of the two methods, if properly standardized, can provide much more reliable and accurate results for the study of marine microbial eukaryotes.

Label-free chemiresistor biosensor based on reduced graphene oxide and M13 bacteriophage for detection of coliforms

Coliform bacteria are well known as informative indicators for bacterial contamination in water. This study presents a novel chemiresistor biosensor using M13 phage-modified reduced graphene oxide (rGO) for detection of Escherichia coli (E. coli), as coliform bacteria. M13 phage, as a biorecognition element, was immobilized on the rGO channel, so that it can bind to negatively charged E. coli bacteria, allowing the gating effect on the biosensor and the change in its resistance. The prepared materials and device were characterized using spectroscopic, microscopic, and electrical measurements. FTIR and XRD results proved the successful fabrication of GO and rGO nanosheets. AFM results showed that the prepared nanosheets were monolayer. The SEM micrographs of the M13-functionalized devices, soaked in two different concentrations of E. coli, confirmed the successful capturing of E. coli and that the signal change is concentration-dependent. As a result, a linear and specific response towards E. coli was observed and the limit of detection was determined to be 45 CFU/mL. Further, the proposed sensor system showed selectivity towards the tested coliforms. These results suggested this sensing system could be a promising tool for detecting coliforms with an economic, accurate, rapid, and directly applicable process.

Genotype by sequencing: An alternative new method to amplicon metabarcoding and shotgun metagenomics for the assessment of eukaryote biodiversity

The use of high-throughput DNA sequencing (HTS) has revolutionized the assessment of biodiversity in plant and animal communities. There are two main approaches to estimate the identity and the relative species abundance (RSA) in complex mixtures using HTS: amplicon metabarcoding and shotgun metagenomics. While amplicon metabarcoding targets one or a few genomic regions, shotgun metagenomics randomly explores the genome of the species. In this issue of Molecular Ecology Resources, Wagemaker et al. (2021) present a new method, multi-species Genotyping by Sequencing (msGBS), as an alternative middle ground between metabarcoding and metagenomics. They apply the technique to mixtures of plant roots and report the remarkable capacity of msGBS to estimate the RSA. If validated in other laboratories and biological communities, msGBS might become a third method to explore the biodiversity of biological communities, especially of plants, where current techniques are struggling to get sufficient taxonomic resolution.

Optimizing the quality of clinical studies on oral microbiome: A practical guide for planning, performing, and reporting

With this review, we aim to increase the quality standards for clinical studies with microbiome as an output parameter. We critically address the existing body of evidence for good quality practices in oral microbiome studies based on 16S rRNA gene amplicon sequencing. First, we discuss the usefulness of microbiome profile analyses. Is a microbiome study actually the best approach for answering the research question? This is followed by addressing the criteria for the most appropriate study design, sample size, and the necessary data (study metadata) that should be collected. Next, we evaluate the available evidence for best practices in sample collection, transport, storage, and DNA isolation. Finally, an overview of possible sequencing options (eg, 16S rRNA gene hypervariable regions, sequencing platforms), processing and data interpretation approaches, as well as requirements for meaningful data storage, sharing, and reporting are provided.

Real-Time Culture-Independent Microbial Profiling Onboard the International Space Station Using Nanopore Sequencing

For the past two decades, microbial monitoring of the International Space Station (ISS) has relied on culture-dependent methods that require return to Earth for analysis. This has a number of limitations, with the most significant being bias towards the detection of culturable organisms and the inherent delay between sample collection and ground-based analysis. In recent years, portable and easy-to-use molecular-based tools, such as Oxford Nanopore Technologies’ MinION™ sequencer and miniPCR bio’s miniPCR™ thermal cycler, have been validated onboard the ISS. Here, we report on the development, validation, and implementation of a swab-to-sequencer method that provides a culture-independent solution to real-time microbial profiling onboard the ISS. Method development focused on analysis of swabs collected in a low-biomass environment with limited facility resources and stringent controls on allowed processes and reagents. ISS-optimized procedures included enzymatic DNA extraction from a swab tip, bead-based purifications, altered buffers, and the use of miniPCR and the MinION. Validation was conducted through extensive ground-based assessments comparing current standard culture-dependent and newly developed culture-independent methods. Similar microbial distributions were observed between the two methods; however, as expected, the culture-independent data revealed microbial profiles with greater diversity. Protocol optimization and verification was established during NASA Extreme Environment Mission Operations (NEEMO) analog missions 21 and 22, respectively. Unique microbial profiles obtained from analog testing validated the swab-to-sequencer method in an extreme environment. Finally, four independent swab-to-sequencer experiments were conducted onboard the ISS by two crewmembers. Microorganisms identified from ISS swabs were consistent with historical culture-based data, and primarily consisted of commonly observed human-associated microbes. This simplified method has been streamlined for high ease-of-use for a non-trained crew to complete in an extreme environment, thereby enabling environmental and human health diagnostics in real-time as future missions take us beyond low-Earth orbit.

Eukaryotic and Prokaryotic Microbiota Interactions

The nature of the relationship between the communities of microorganisms making up the microbiota in and on a host body has been increasingly explored in recent years. Microorganisms, including bacteria, archaea, viruses, parasites and fungi, have often long co-evolved with their hosts. In human, the structure and diversity of microbiota vary according to the host’s immunity, diet, environment, age, physiological and metabolic status, medical practices (e.g., antibiotic treatment), climate, season and host genetics. The recent advent of next generation sequencing (NGS) technologies enhanced observational capacities and allowed for a better understanding of the relationship between distinct microorganisms within microbiota. The interaction between the host and their microbiota has become a field of research into microorganisms with therapeutic and preventive interest for public health applications. This review aims at assessing the current knowledge on interactions between prokaryotic and eukaryotic communities. After a brief description of the metagenomic methods used in the studies were analysed, we summarise the findings of available publications describing the interaction between the bacterial communities and protozoa, helminths and fungi, either in vitro, in experimental models, or in humans. Overall, we observed the existence of a beneficial effect in situations where some microorganisms can improve the health status of the host, while the presence of other microorganisms has been associated with pathologies, resulting in an adverse effect on human health.

Food Resource Sharing of Alder Leaf Beetle Specialists (Coleoptera: Chrysomelidae) as Potential Insect-Plant Interface for Horizontal Transmission of Endosymbionts

Recent studies suggest that endosymbionts of herbivore insects can be horizontally transferred to other herbivores feeding on the same host plants, whereby the plant acts as an intermediate stage in the chain of transmission. If this mechanism operates, it is also expected that insect communities sharing the same host plant will have higher chances to share their endosymbionts. In this study, we use a high-throughput 16S rRNA metabarcoding approach to investigate the presence, diversity, and potential sharing of endosymbionts in several species of leaf beetles (Coleoptera: Chrysomelidae) of a local community specialized on an alder diet in North America. Rickettsia and Wolbachia were predominant in the sample, with strong evidence for each species having their own dominant infection, of either or both types of bacteria. However, all species shared a much lower proportion of a particular Wolbachia type, compatible with the same strain dominant in one of the species of leaf beetles. Crucially, the same 16S rRNA haplotype of Wolbachia was found on alder leaf extracts. The combined evidence and the absence of this strain in a syntopic species of leaf beetle feeding on a different host plant support the hypothesis that at least the initial stages of the mechanism that would allow horizontal transmission of endosymbionts across species feeding on the same plant is possible. The accessibility and characteristics of endosymbiont associations of this system make it suitable for deeper analyses of their diversity and transmission in natural conditions.

The masking effect of extracellular DNA and robustness of intracellular DNA in anaerobic digester NGS studies: A discriminatory study of the total DNA pool

Most commonly, next generation sequencing-based microbiome studies are performed on the total DNA (totDNA) pool; however, this consists of extracellular- (exDNA) and intracellular (iDNA) DNA fractions. By investigating the microbiomes of different anaerobic digesters over time, we found that totDNA suggested lower species richness considering all and/or only common species and yielded fewer unique reads as compared to iDNA. Additionally, exDNA-derived sequences were more similar to those from totDNA than from iDNA and, finally, iDNA showed the best performance in tracking temporal changes in microbial communities. We postulate that abundant sequences present within the exDNA fraction mask the overall results of totDNA and provide evidence that exDNA has the potential to qualitatively bias microbiome studies at least in the anaerobic digester environment as it contains information about cells that were lysed hours or days ago. iDNA, however, was found to be more appropriate in providing reliable genetic information about potentially alive as well as rare microbes within the target habitat.

How the 'kitome' influences the characterization of bacterial communities in lepidopteran samples with low bacterial biomass

AIMS

We aimed to elucidate whether the DNA extraction kit and bacteria therein affect the characterization of bacterial communities associated with butterfly samples harbouring different bacterial abundancies.

METHODS AND RESULTS

We analysed bacteria associated with eggs of Pieris brassicae and with adults of this butterfly, which were either untreated or treated with antibiotics (ABs). Three DNA extraction kits were used. Regardless of the extraction kit used, PCR amplification of the bacterial 16S rRNA gene detected very low bacterial presence in eggs and AB-treated butterflies. In untreated butterflies, bacterial signal intensity varied according to the kit and primers used. Sequencing (MiSeq) of the bacterial communities in untreated and AB-treated butterflies revealed a low alpha diversity in untreated butterflies because of the dominance of few bacteria genera, which were detectable regardless of the kit. However, a significantly greater alpha diversity was found in AB-treated butterflies, evidencing a true bias of the results due to bacterial contaminants in the kit.

CONCLUSIONS

The so-called 'kitome' can impact the profiling of Lepidoptera-associated bacteria in samples with low bacterial biomass.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our study highlights the necessity of method testing and analysis of negative controls when investigating Lepidoptera-associated bacterial communities.

Evaluation of groundwater bacterial community composition to inform waterborne pathogen vulnerability assessments

Microbial water quality evaluations are essential for determining the vulnerability of subsurface drinking water sources to fecal pathogen intrusion. Rather than directly monitor waterborne pathogens using culture- or enumeration-based techniques, the potential of assessing bacterial community using 16S rRNA gene amplicon sequencing to support these evaluations was investigated. A framework for analyzing 16S rRNA gene amplicon sequencing results featuring negative-binomial generalized linear models is demonstrated, and applied to bacterial taxa sequences in purge water samples collected from a shallow, highly aerobic, unconfined aquifer. Bacterial taxa relevant as indicators of fecal source and surface connectivity were examined using this approach. Observed sequences of Escherichia, a genus suggestive of fecal source, were consistently detected but not confirmed by culture-based methods. On the other hand, episodic appearance of anaerobic taxa sequences in this highly aerobic environment, namely Clostridia and Bacteroides, warrants further investigation as potential indicators of fecal contamination. Betaproteobacteria sequences varied significantly on a seasonal basis, and therefore may be linked to understanding surface-water groundwater interactions at this site. However, sequences that are often encountered in surface water bodies (Cyanobacteria and Flavobacteriia) were notably absent or present at very low levels, suggesting that microbial transport from surface-derived sources may be rather limited. This work demonstrates the utility of 16S rRNA gene amplicon sequencing for contextualizing and complementing conventional microbial techniques, allowing for hypotheses about source and transport processes to be tested and refined.

Validation of an eDNA-based method for the detection of wildlife pathogens in water

Monitoring the occurrence and density of parasites and pathogens can identify high infection-risk areas and facilitates disease control and eradication measures. Environmental DNA (eDNA) techniques are increasingly used for pathogen detection due to their relative ease of application. Since many factors affect the reliability and efficacy of eDNA-based detection, rigorous validation and assessment of method limitations is a crucial first step. We evaluated an eDNA detection method using in situ filtration of large-volume water samples, developed to detect and quantify aquatic wildlife parasites by quantitative PCR (qPCR). We assessed method reliability using Batrachochytrium dendrobatidis, a pathogenic fungus of amphibians and the myxozoan Tetracapsuloides bryosalmonae, causative agent of salmonid proliferative kidney disease, in a controlled experimental setup. Different amounts of parasite spores were added to tanks containing either clean tap water or water from a semi-natural mesocosm community. Overall detection rates were higher than 80%, but detection was not consistent among replicate samples. Within-tank variation in detection emphasises the need for increased site-level replication when dealing with parasites and pathogens. Estimated parasite DNA concentrations in water samples were highly variable, and a significant increase with higher spore concentrations was observed only for B. dendrobatidis. Despite evidence for PCR inhibition in DNA extractions from mesocosm water samples, the type of water did not affect detection rates significantly. Direct spiking controls revealed that the filtration step reduced detection sensitivity. Our study identifies sensitive quantification and sufficient replication as major remaining challenges for the eDNA-based methods for detection of parasites in water.

An Improved hgcAB Primer Set and Direct High-Throughput Sequencing Expand Hg-Methylator Diversity in Nature

The gene pair hgcAB is essential for microbial mercury methylation. Our understanding of its abundance and diversity in nature is rapidly evolving. In this study we developed a new broad-range primer set for hgcAB, plus an expanded hgcAB reference library, and used these to characterize Hg-methylating communities from diverse environments. We applied this new Hg-methylator database to assign taxonomy to hgcA sequences from clone, amplicon, and metagenomic datasets. We evaluated potential biases introduced in primer design, sequence length, and classification, and suggest best practices for studying Hg-methylator diversity. Our study confirms the emerging picture of an expanded diversity of HgcAB-encoding microbes in many types of ecosystems, with abundant putative mercury methylators Nitrospirae and Chloroflexi in several new environments including salt marsh and peat soils. Other common microbes encoding HgcAB included Phycisphaerae, Aminicenantes, Spirochaetes, and Elusimicrobia. Combined with high-throughput amplicon specific sequencing, the new primer set also indentified novel hgcAB sequences similar to Lentisphaerae, Bacteroidetes, Atribacteria, and candidate phyla WOR-3 and KSB1 bacteria. Gene abundance data also corroborate the important role of two "classic" groups of methylators (Deltaproteobacteria and Methanomicrobia) in many environments, but generally show a scarcity of hgcAB+ Firmicutes. The new primer set was developed to specifically target hgcAB sequences found in nature, reducing degeneracy and providing increased sensitivity while maintaining broad diversity capture. We evaluated mock communities to confirm primer improvements, including culture spikes to environmental samples with variable DNA extraction and PCR amplification efficiencies. For select sites, this new workflow was combined with direct high-throughput hgcAB sequencing. The hgcAB diversity generated by direct amplicon sequencing confirmed the potential for novel Hg-methylators previously identified using metagenomic screens. A new phylogenetic analysis using sequences from freshwater, saline, and terrestrial environments showed Deltaproteobacteria HgcA sequences generally clustered among themselves, while metagenome-resolved HgcA sequences in other phyla tended to cluster by environment, suggesting horizontal gene transfer into many clades. HgcA from marine metagenomes often formed distinct subtrees from those sequenced from freshwater ecosystems. Overall the majority of HgcA sequences branch from a cluster of HgcAB fused proteins related to Thermococci, Atribacteria (candidate division OP9), Aminicenantes (OP8), and Chloroflexi. The improved primer set and library, combined with direct amplicon sequencing, provide a significantly improved assessment of the abundance and diversity of hgcAB+ microbes in nature.

Putative degraders of low-density polyethylene-derived compounds are ubiquitous members of plastic-associated bacterial communities in the marine environment

It remains unknown whether and to what extent marine prokaryotic communities are capable of degrading plastic in the ocean. To address this knowledge gap, we combined enrichment experiments employing low‐density polyethylene (LDPE) as the sole carbon source with a comparison of bacterial communities on plastic debris in the Pacific, the North Atlantic and the northern Adriatic Sea. A total of 35 operational taxonomic units (OTUs) were enriched in the LDPE‐laboratory incubations after 1 year, of which 20 were present with relative abundances > 0.5% in at least one plastic sample collected from the environment. From these, OTUs classified as Cognatiyoonia, Psychrobacter, Roseovarius and Roseobacter were found in the communities of plastics collected at all oceanic sites. Additionally, OTUs classified as Roseobacter, Pseudophaeobacter, Phaeobacter, Marinovum and Cognatiyoonia, also enriched in the LDPE‐laboratory incubations, were enriched on LDPE communities compared to the ones associated to glass and polypropylene in in‐situ incubations in the northern Adriatic Sea after 1 month of incubation. Some of these enriched OTUs were also related to known alkane and hydrocarbon degraders. Collectively, these results demonstrate that there are prokaryotes capable of surviving with LDPE as the sole carbon source living on plastics in relatively high abundances in different water masses of the global ocean.

Valley Fever: Environmental Risk Factors and Exposure Pathways Deduced from Field Measurements in California

Coccidioidomycosis, also known as Valley fever, has been reported among military personnel in Coccidioides-endemic areas of the southwestern United States since World War II. In this study, the prevalence of Coccidioides was confirmed in different soil and dust samples collected near three military bases in California using DNA extraction and Polymerase Chain Reaction (PCR) methods. Analyses of physical and chemical parameters revealed no significant differences between Coccidioides-positive and -negative sites. Soil samples collected in the Mojave Desert (near Twentynine Palms MCAGCC) showed the highest percentage of Coccidioides-positive soil and dust samples. Samples from the San Joaquin Valley (near NAS Lemoore) showed the lowest percentage of positive samples and were restricted to remnants of semi-natural areas between agricultural fields. Our results suggest that soil disturbance around all three military bases investigated poses a potential Coccidioides exposure risk for military personnel and the public. We conclude that once lands have been severely disturbed from their original state, they become less suitable for Coccidioides growth. We propose a conceptual framework for understanding exposure where disturbance of soils that exhibit natural or remnants of native vegetation (Creosote and Salt Bush) generate a high risk of exposure to the pathogen, likely during dry periods. In contrast, Coccidioides-positive sites, when undisturbed, will not pose a high risk of exposure.

Analysis of Tick Surface Decontamination Methods

Various microbial pathogens have been found in ticks such as Ixodes ricinus. However, most studies assessed tick microbiomes without prior decontamination of the tick surface, which may alter the results and mislead conclusions regarding the composition of the tick-borne microbiome. The aim of this study was to test four different decontamination methods, namely (i.) 70% ethanol, (ii.) DNA Away, (iii.) 5% sodium hypochlorite and (iv.) Reactive Skin Decontamination Lotion (RSDL), which have been previously reported for tick surface and animal or human skin decontamination. To test the efficiency of decontamination, we contaminated each tick with a defined mixture of Escherichia coli, Micrococcus luteus, Pseudomonas fluorescens, dog saliva and human sweat. No contamination was used as a negative control, and for a positive control, a no decontamination strategy was carried out. After nucleic acid extraction, the recovery rate of contaminants was determined for RNA and DNA samples by qPCR and tick-borne microbiome analyses by bacterial 16S rRNA and 16S rRNA gene amplicon sequencing. Ticks treated with 5% sodium hypochlorite revealed the lowest number of contaminants followed by DNA Away, RSDL and 70% ethanol. Moreover, tick microbiomes after 5% sodium hypochlorite decontamination clustered with negative controls. Therefore, the efficiency of decontamination was optimal with 5% sodium hypochlorite and is recommended for upcoming studies to address the unbiased detection of tick-borne pathogens.

Gut enterotypes are stable during Bifidobacterium and Lactobacillus probiotic supplementation

The human gut microbiome has been classified into three distinct enterotypes (Bacteroides, Prevotella, and Ruminococcus). The relationship between probiotics and gut enterotype is not yet clear. Cayenne pepper is effective in vitro as a prebiotic for Bifidobacteria and Lactobacilli, so cayenne ingestion with probiotics may lead to more profound gut microbial shifts. We aimed to determine whether probiotics (with or without cayenne pepper) alter gut bacterial community composition and if these changes are associated with the original gut enterotype of the individual. A total of 27 adult participants provided three fecal samples: prior to probiotic treatment (baseline), post probiotic treatment (probiotic), and post probiotic plus cayenne pepper treatment (probiotic + cayenne). DNA was extracted, amplified, and the V4 region sequenced on the Illumina MiSeq platform using V2 chemistry. Sequence reads were processed in mothur and assigned using the SILVA reference by phylotype. Three enterotypes characterized the study population-Bacteroides (B; n = 6), Prevotella (P; n = 11), and Ruminoccocus (R; n = 10). There was no significant increase in probiotic genera in fecal samples after treatment periods. Alpha diversity scores were significantly lower in B-type but not in P- or R-type individuals after probiotic treatment. For the majority of individuals, their enterotype remained constant regardless of probiotic (and cayenne) treatment. This suggests that baseline gut community characteristics and enterotype classification influence responsiveness to probiotic treatment, but that enterotype is stable across administration of prebiotic and probiotics. PRACTICAL APPLICATION: A person's gut microbial community influences their responsiveness to probiotics and prebiotic ingredients. Consumers must understand that it is difficult to shift their gut microbiota even with simultaneous administration of prebiotic and probiotic. Greater understanding of these phenomena will enable consumers to choose the most efficacious products for their needs.

Microbial community analysis using high-throughput sequencing technology: a beginner's guide for microbiologists

Microbial communities present in diverse environments from deep seas to human body niches play significant roles in the complex ecosystem and human health. Characterizing their structural and functional diversities is indispensable, and many approaches, such as microscopic observation, DNA fingerprinting, and PCR-based marker gene analysis, have been successfully applied to identify microorganisms. Since the revolutionary improvement of DNA sequencing technologies, direct and high-throughput analysis of genomic DNA from a whole environmental community without prior cultivation has become the mainstream approach, overcoming the constraints of the classical approaches. Here, we first briefly review the history of environmental DNA analysis applications with a focus on profiling the taxonomic composition and functional potentials of microbial communities. To this end, we aim to introduce the shotgun metagenomic sequencing (SMS) approach, which is used for the untargeted ("shotgun") sequencing of all ("meta") microbial genomes ("genomic") present in a sample. SMS data analyses are performed in silico using various software programs; however, in silico analysis is typically regarded as a burden on wet-lab experimental microbiologists. Therefore, in this review, we present microbiologists who are unfamiliar with in silico analyses with a basic and practical SMS data analysis protocol. This protocol covers all the bioinformatics processes of the SMS analysis in terms of data preprocessing, taxonomic profiling, functional annotation, and visualization.

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.

Quantitative PCR provides a simple and accessible method for quantitative microbiota profiling

The use of relative abundance data from next generation sequencing (NGS) can lead to misinterpretations of microbial community structures, as the increase of one taxon leads to the concurrent decrease of the other(s) in compositional data. Although different DNA- and cell-based methods as well as statistical approaches have been developed to overcome the compositionality problem, and the biological relevance of absolute bacterial abundances has been demonstrated, the human microbiome research has not yet adopted these methods, likely due to feasibility issues. Here, we describe how quantitative PCR (qPCR) done in parallel to NGS library preparation provides an accurate estimation of absolute taxon abundances from NGS data and hence provides an attainable solution to compositionality in high-throughput microbiome analyses. The advantages and potential challenges of the method are also discussed.

DNA extraction approaches substantially influence the assessment of the human breast milk microbiome

In addition to providing nutritional and bioactive factors necessary for infant development, human breast milk contains bacteria that contribute to the establishment of commensal microbiota in the infant. However, the composition of this bacterial community differs considerably between studies. We hypothesised that bacterial DNA extraction methodology from breast milk samples are a substantial contributor to these inter-study differences. We tested this hypothesis by applying five widely employed methodologies to a mock breast milk sample and four individual human breast milk samples. Significant differences in DNA yield and purity were observed between methods (P < 0.05). Microbiota composition, assessed by 16S rRNA gene amplicon sequencing, also differed significantly with extraction methodology (P < 0.05), including in the contribution of contaminant signal. Concerningly, many of the bacterial taxa identified here as contaminants have been reported as components of the breast milk microbiome in other studies. These findings highlight the importance of using stringent, well-validated, DNA extraction methodologies for analysis of the breast milk microbiome, and exercising caution interpreting microbiota data from low-biomass contexts.

Comparison of different media for the detection of denitrifying and nitrate reducing bacteria in mesotrophic aquatic environments by the most probable number method

The cultivation based characterization of microbial communities and the quantification of certain functional bacterial groups is still an essential part of microbiology and microbial ecology. For plate count methods meanwhile low strength media are recommended, since they cover a broader range of different species and result in higher counts compared to established high strength media. For liquid media, as they are used for most probable number (MPN) quantifications, comparisons between high and low strength media are rare. In this study we compare the performance of different high and low strength media for the MPN quantification of nitrate reducing and denitrifying bacteria in two different fresh water environments. We also calculated the cell specific turnover rates of several denitrifying cultures previously enriched in high and low strength media from three different fresh water environments and a waste water treatment plant. For fresh water samples, our results indicate that high strength media detect higher MPN of denitrifying bacteria and in equal MPN of nitrate reducing bacteria compared to low strength media, which is in contrary to plate count techniques. For sediment samples, high and low strength media performed equal. The cell specific turnover rate was independent from the enrichment media and the media of the performance test. The cause of the lower denitrifyer MPN in low strength media remains, however, unclear. The results are important for further MPN quantifications of bacteria in nutrient poor environments and for calculations of nitrogen turnover rates by kinetical models using the number of metabolic active cells as one parameter.

MIMOSA: Algorithms for Microbial Profiling

A significant goal of the study of metagenomes obtained from an environment is to find the microbial diversity and the abundance of each organism in the community. Phylotyping and binning methods which address this problem generally operate using either marker sequences or by classifying each genome fragment individually. However, these approaches might not use all the information contained in the metagenome. We propose an approach based on a Multiple Input Multiple Output (MIMO) communication system model. Results from two different implementations of this approach, one using DNA-DNA hybridization simulations and one using short read mapping are evaluated using simulated and actual metagenomes and compared with other methods of phylotyping. The proposed approaches generally performed better under different scenarios including pathogen detection tasks of community complexity and low and high sequencing coverage while being highly computationally effective. The resulting framework can be integrated to metagenome analysis pipelines for phylogenetic diversity estimation. The approach is modular so that techniques other than hybridization simulations and short read mapping may be integrated. We have observed that even for low coverage samples, the method provides accurate estimates. Therefore, the use of the proposed strategy could enable the task of exploring biodiversity with limited resources.

Establishing What Constitutes a Healthy Human Gut Microbiome: State of the Science, Regulatory Considerations, and Future Directions

On December 17, 2018, the North American branch of the International Life Sciences Institute (ILSI North America) convened a workshop "Can We Begin to Define a Healthy Gut Microbiome Through Quantifiable Characteristics?" with >40 invited academic, government, and industry experts in Washington, DC. The workshop objectives were to 1) develop a collective expert assessment of the state of the evidence on the human gut microbiome and associated human health benefits, 2) see if there was sufficient evidence to establish measurable gut microbiome characteristics that could serve as indicators of "health," 3) identify short- and long-term research needs to fully characterize healthy gut microbiome-host relationships, and 4) publish the findings. Conclusions were as follows: 1) mechanistic links of specific changes in gut microbiome structure with function or markers of human health are not yet established; 2) it is not established if dysbiosis is a cause, consequence, or both of changes in human gut epithelial function and disease; 3) microbiome communities are highly individualized, show a high degree of interindividual variation to perturbation, and tend to be stable over years; 4) the complexity of microbiome-host interactions requires a comprehensive, multidisciplinary research agenda to elucidate relationships between gut microbiome and host health; 5) biomarkers and/or surrogate indicators of host function and pathogenic processes based on the microbiome need to be determined and validated, along with normal ranges, using approaches similar to those used to establish biomarkers and/or surrogate indicators based on host metabolic phenotypes; 6) future studies measuring responses to an exposure or intervention need to combine validated microbiome-related biomarkers and/or surrogate indicators with multiomics characterization of the microbiome; and 7) because static genetic sampling misses important short- and long-term microbiome-related dynamic changes to host health, future studies must be powered to account for inter- and intraindividual variation and should use repeated measures within individuals.

Non-lytic M13 phage-based highly sensitive impedimetric cytosensor for detection of coliforms

A highly sensitive and selective non-lytic M13 phage-based electrochemical impedance spectroscopy (EIS) cytosensor for early detection of coliforms is introduced for the first time. Gold nanoparticles were electrochemically deposited on the surface of glassy carbon electrode, and the M13 phage particles were immobilized on them using 3-mercaptopropionic acid linker and zero-length crosslinking chemistry (EDC/NHS). Next, the sensor surface was blocked to avoid non-specific binding. The M13-EIS cytosensor was tested for detection of F⁺ pili Escherichia coli species, using XL1-Blue and K12 strains, as examples of coliforms. The selectivity against non-host strains was demonstrated using Pseudomonas Chlororaphis. The binding of E. coli to the M13 phage on the cytosensor surface increased the charge transfer resistance, enabling detection of coliforms. The biosensor achieved a limit of detection (LOD) of 14 CFU/mL, the lowest reported to-date using EIS-phage sensors, and exhibited a high selectivity towards the tested coliforms. The SEM micrographs confirmed the successful capturing of E. coli on the M13-based EIS cytosensor. Moreover, the sensor showed almost the same sensitivity in the simulated river water samples as in phosphate buffer, reflecting its applicability to real samples. On the other hand, this sensor system exhibited high stability under harsh environmental conditions of pH (3.0-10.0) and temperature as high as 45 °C for up to two weeks. Overall, this sensor system has excellent potential for real field detection of fecal coliforms.

Spiking a Silty-Sand Reference Soil with Bacterial DNA: Limits and Pitfalls in the Discrimination of Live and Dead Cells When Applying Ethidium Monoazide (EMA) Treatment

In the present study, EMA (ethidium monoazide) treatment was applied to a silty-sand reference soil prior to DNA extraction to enable a differentiation between dead and living cells. For this purpose, a reference soil was spiked with Listeria monocytogenes cells or cell equivalents, respectively. With the purpose of evaluating optimum treatment conditions, different EMA concentrations have been tested. However, the results remained largely inconclusive. Furthermore, varied dark incubation periods allowing EMA to penetrate dead cells did not allow the selective removal of DNA from membrane-compromised cells in downstream analyses. In contrast to undiluted soil, an effect of EMA treatment during DNA extraction could be observed when using a 1:10 dilution of the reference soil; however, the effect has not been sufficiently selective to act on heat-treated cells only. Although the application of EMA to soil requires further evaluation, the procedure harbors future potential for improving DNA-based approaches in microbial ecology studies.

Bacterial community composition of biofilms in milking machines of two dairy farms assessed by a combination of culture-dependent and -independent methods

Dairy biofilms as a source of contamination of milk and its products are of great concern in the dairy industry. For a reliable risk assessment, knowledge about the microbial community composition of biofilms in the milking systems of dairy farms must be improved. In this work, swab samples of milking machine biofilms of two dairy farms were investigated by a combination of culture-dependent and -independent methods. Spots in the milking system with enhanced microbial colonization were identified by quantification on selective and non-selective media. In addition, stainless steel coupons were placed into the piping system of a milking machine, removed after several milking intervals, and investigated for colonization by cultivation and culture-independently. Isolates were differentiated and identified by a combination of chemotaxonomical methods and 16S rRNA sequencing. The culture-independent approach involved treatment of the samples with the viability dye propidium monoazide prior to direct DNA-extraction by enzymatic cell lysis and cloning to exclude bias from dead biomass. The milking equipment retainers and the outlet of the milk bulk tank were identified as highly colonized spots on both farms. A high bacterial diversity was detected covering the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Presence of biofilms was demonstrated on several materials including stainless steel and plastic, which are frequently used in milking machines, but also in dairy processing plants. Growth of mainly Gram-positive bacteria with high percentages of the phylum Actinobacteria was detected on the stainless steel coupons after exposition in the milking system for two to three days. Knowledge about the heterogenic microbial load on different parts of the milking machines and the stainless steel coupons will help to identify primary colonizers of the milking system, to assess the risk potential of biofilms for raw milk, to improve sanitation processes and to identify parts of the milking machine, which should be improved by hygienic design.