16S rRNA gene sequencing of mock microbial populations- impact of DNA extraction method, primer choice and sequencing platform

Aboveground plants determine the exchange of pathogens within air-phyllosphere-soil continuum in urban greenspaces

The microbiome in the air-phyllosphere-soil continuum of urban greenspaces plays a crucial role in re-connecting urban populations with biodiverse environmental microbiomes. However, little is known about whether plant type affects the airborne microbiomes, as well as the extent to which soil and phyllosphere microbiomes contribute to airborne microbiomes. Here we collected soil, phyllosphere and airborne microbes with different plant types (broadleaf tree, conifer tree, and grass) in urban parks. Despite the significant impacts of plant type on soil and phyllosphere microbiomes, plant type had no obvious effects on the diversity of airborne microbes but shaped airborne bacterial composition in urban greenspaces. Soil and phyllosphere microbiomes had a higher contribution to airborne bacteria in broadleaf trees (37.56%) compared to conifer trees (9.51%) and grasses (14.29%). Grass areas in urban greenspaces exhibited a greater proportion of potential pathogens compared to the tree areas. The abundance of bacterial pathogens in phyllosphere was significantly higher in grasses compared to broadleaf and conifer trees. Together, our study provides novel insights into the microbiome patterns in air-phyllosphere-soil continuum, highlighting the potential significance of reducing the proportion of extensively human-intervened grass areas in future urban environment designs to enhance the provision of ecosystem services in urban greenspaces.

Metagenomic insights into microorganisms and antibiotic resistance genes of waste antibiotic fermentation residues along production, storage and treatment processes

Antibiotic fermentation residue (AFR) is nutrient-rich solid waste generated from fermentative antibiotic production process. It is demonstrated that AFR contains high-concentration of remaining antibiotics, and thus may promote antibiotic resistance development in receiving environment or feeding farmed animals. However, the dominate microorganisms and antibiotic resistance genes (ARGs) in AFRs have not been adequately explored, hampering understanding on the potential antibiotic resistance risk development caused by AFRs. Herein, seven kinds of representative AFRs along their production, storage, and treatment processes were collected, and multiple methods including amplicon sequencing, metagenomic sequencing, and bioinformatic approaches were adopted to explore the biological characteristics of AFRs. As expected, antibiotic fermentation producer was found as the predominant species in raw AFRs, which were collected at the outlet of fermentation tanks. However, except for producer species, more environment-derived species persisted in stored AFRs, which were temporarily stored at a semi-open space. Lactobacillus genus, classified as Firmicutes phylum and Bacilli class, became predominant bacterial taxa in stored AFRs, which might attribute to its tolerance to high concentration of antibiotics. Results from metagenomic sequencing together with assembly and binning approaches showed that these newly-colonizing species (e.g., Lactobacillus genus) tended to carry ARGs conferring resistance to the remaining antibiotic. However, after thermal treatment, remaining antibiotic could be efficiently removed from AFRs, and microorganisms together with DNA could be strongly destroyed. In sum, the main risk from the AFRs was the remaining antibiotic, while environment-derived bacteria which tolerate extreme environment, survived in ARFs with high content antibiotics, and may carry ARGs. Thus, hydrothermal or other harmless treatment technologies are recommended to remove antibiotic content and inactivate bacteria before recycling of AFRs in pharmaceutical industry.

Falcon gut microbiota is shaped by diet and enriched in Salmonella

The gut microbiome is increasingly being appreciated as a master regulator of animal health. However, avian gut microbiome studies commonly focus on birds of economic importance and the gut microbiomes of raptors remain underexplored. Here we examine the gut microbiota of 29 captive falcons-raptors of historic importance-in the context of avian evolution by sequencing the V4 region of the 16S rRNA gene. Our results reveal that evolutionary histories and diet are significantly associated with avian gut microbiota in general, whereas diet plays a major role in shaping the falcon gut microbiota. Multiple analyses revealed that gut microbial diversity, composition, and relative abundance of key diet-discriminating bacterial genera in the falcon gut closely resemble those of carnivorous raptors rather than those of their closest phylogenetic relatives. Furthermore, the falcon microbiota is dominated by Firmicutes and contains Salmonella at appreciable levels. Salmonella presence was associated with altered functional capacity of the falcon gut microbiota as its abundance is associated with depletion of multiple predicted metabolic pathways involved in protein mass buildup, muscle maintenance, and enrichment of antimicrobial compound degradation, thus increasing the pathogenic potential of the falcon gut. Our results point to the necessity of screening for Salmonella and other human pathogens in captive birds to safeguard both the health of falcons and individuals who come in contact with these birds.

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.

Stable microbial community in compacted bentonite after 5 years of exposure to natural granitic groundwater

The Materials Corrosion Test (MaCoTe) at the Underground Research Laboratory in Grimsel, Switzerland, assesses the microbiology and corrosion behavior of engineered barrier components of a deep geological repository (DGR) for long-term disposal of high-level nuclear waste. Diversity and temporal changes of bentonite-associated microbial community profiles were assessed under DGR-like conditions for compacted Wyoming MX-80 bentonite (1.25 g/cm3 and 1.50 g/cm3 targeted dry densities) exposed to natural groundwater. Using culture-dependent and molecular techniques, samples taken from the outside layer of 5-year borehole modules revealed up to 66% and 23% of 16S rRNA gene sequences affiliated with Desulfosporosinus and Desulfovibrio, respectively. Putatively involved in sulfate reduction, these taxa were almost undetectable within the bentonite core. Instead, microbial profiles of the inner bentonite core were similar to uncompacted bentonite used to pack modules years earlier, and were consistent with a previously published 1-year time point, revealing no detectable microbial growth. Abundances of culturable aerobic and anaerobic heterotrophic bacteria in the uncompacted bentonite were relatively low, with less than 1,000 and 100 colony-forming units (CFUs) per gram dry weight, respectively. Nearly 5 years after emplacement, culturable heterotrophic bacterial CFUs and sulfate-reducing bacteria did not change significantly inside the bentonite core. Phospholipid fatty acid data indicated similar lipid abundance, and corresponding cell abundance estimates, for inner 5-year MaCoTe bentonite samples compared to those previously obtained for 1-year incubations. Collectively, our results provide complementary evidence for microbial stability inside highly compacted bentonite exposed to conditions that mimic engineered barrier components of a deep geological repository. IMPORTANCE The long-term safety of a deep geological repository for used nuclear fuel is dependent on the performance of the engineered and natural barriers. Microbial activity can produce chemical species that can influence the corrosion of the disposal containers for used nuclear fuel. Although previous studies have evaluated the microbiology of compacted bentonite clay within subsurface environments, these have been limited to relatively short incubations (i.e., 1 year). The current study provides a unique 5-year perspective that reinforces previous findings of growth inhibition for bentonite clay exposed to in situ subsurface conditions.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

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

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

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

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

Metagenomics reveals novel microbial signatures of farm exposures in house dust

Indoor home dust microbial communities, important contributors to human health, are shaped by environmental factors, including farm-related exposures. Advanced metagenomic whole genome shotgun sequencing (WGS) improves detection and characterization of microbiota in the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). We hypothesized that the improved characterization of indoor dust microbial communities by WGS will enhance detection of exposure-outcome associations. The objective of this study was to identify novel associations of environmental exposures with the dust microbiome from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota. These findings can inform the design of future studies in environmental health.

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.

Metagenomics reveals novel microbial signatures of farm exposures in house dust

Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes , and Proteobacteria . The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium , and Pseudomonas , was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.

Meat Consumption and Gut Microbiota: a Scoping Review of Literature and Systematic Review of Randomized Controlled Trials in Adults

Emerging research indicates the importance of gut microbiota in mediating the relationship between meat intake and human health outcomes. We aimed to assess the state of available scientific literature on meat intake and gut microbiota in humans (PROSPERO, International Prospective Register of Systematic Reviews, CRD42020135649). We first conducted a scoping review to identify observational and interventional studies on this topic. Searches were performed for English language articles using PubMed, Cochrane Library, Scopus, and CINAHL (Cumulated Index to Nursing and Allied Health Literature) databases from inception to August 2021 and using keywords related to meat (inclusive of mammalian, avian, and aquatic subtypes) and gut microbiota. Of 14,680 records, 85 eligible articles were included in the scoping review, comprising 57 observational and 28 interventional studies. One prospective observational study and 13 randomized controlled trials (RCTs) were identified in adults without diagnosed disease. We included the 13 RCTs, comprising 18 comparisons, in the systematic review to assess the effects of higher and lower intakes of total meat and meat subtypes on the gut microbiota composition. The bacterial composition was differentially affected by consuming diets with and without meat or with varied meat subtypes. For example, higher meat intake tended to decrease population sizes of genera Anerostipes and Faecalibacterium, but it increased the population size of Roseburia across studies. However, the magnitude and directionality of most microbial responses varied, with inconsistent patterns of responses across studies. The data were insufficient for comparison within or between meat subtypes. The paucity of research, especially among meat subtypes, and heterogeneity of findings underscore the need for more well-designed prospective studies and full-feeding RCTs to address the relationships between and effects of consuming total meat and meat subtypes on gut microbiota, respectively.

Optimization of Molecular Methods for Detecting Duckweed-Associated Bacteria

The bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains and in the context of complex bacterial communities. Quantitative methods that can resolve closely related bacteria within complex communities can lead to a better understanding of plant-microbe interactions. However, current methods often lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study duckweed-associated bacteria. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed-bacterium associations, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed-bacterium associations present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root-frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe associations within plant-microbial communities.

MinION Sequencing of Yeast Mock Communities To Assess the Effect of Databases and ITS-LSU Markers on the Reliability of Metabarcoding Analysis

Microbial communities play key roles both for humans and the environment. They are involved in ecosystem functions, maintaining their stability, and provide important services, such as carbon cycle and nitrogen cycle. Acting both as symbionts and as pathogens, description of the structure and composition of these communities is important. Metabarcoding uses ribosomal DNA (rDNA) (eukaryotic) or rRNA gene (prokaryotic) sequences for identification of species present in a site and measuring their abundance. This procedure requires several technical steps that could be source of bias producing a distorted view of the real community composition. In this work, we took advantage of an innovative "long-read" next-generation sequencing (NGS) technology (MinION) amplifying the DNA spanning from the internal transcribed spacer (ITS) to large subunit (LSU) that can be read simultaneously in this platform, providing more information than "short-read" systems. The experimental system consisted of six fungal mock communities composed of species present at various relative amounts to mimic natural situations characterized by predominant and low-frequency species. The influence of the sequencing platform (MinION and Illumina MiSeq) and the effect of different reference databases and marker sequences on metagenomic identification of species were evaluated. The results showed that the ITS-based database provided more accurate species identification than LSU. Furthermore, a procedure based on a preliminary identification with standard reference databases followed by the production of custom databases, including only the best outputs of the first step, is proposed. This additional step improved the estimate of species proportion of the mock communities and reduced the number of ghost species not really present in the simulated communities. IMPORTANCE Metagenomic analyses are fundamental in many research areas; therefore, improvement of methods and protocols for the description of microbial communities becomes more and more necessary. Long-read sequencing could be used for reducing biases due to the multicopy nature of rDNA sequences and short-read limitations. However, these novel technologies need to be assessed and standardized with controlled experiments, such as mock communities. The interest behind this work was to evaluate how long reads performed identification and quantification of species mixed in precise proportions and how the choice of database affects such analyses. Development of a pipeline that mitigates the effect of the barcoding sequences and the impact of the reference database on metagenomic analyses can help microbiome studies go one step further.

Diversity of enterobacterales in sediments of lagoons with fish farming activity and analysis of antibiotic resistance

The use of antibiotics in fish production can induce bacterial populations to develop resistance to multiple antibiotics and transfer antibiotic resistance genes to other bacteria, including clinically relevant bacteria. This study evaluated the diversity of Enterobacterales in sediment from lagoons with fish farming activity and analyzed antibiotic resistance in the central region of Peru. Sediment samples were collected from four fish-active ponds and transported to the laboratory for analysis. Bacterial diversity was analyzed using DNA sequencing and antibiotic resistance was tested using the disk diffusion method. The results showed variability of bacterial diversity in the ponds with fish farming activity. Simpson's index indicated that the Habascocha lagoon is the most diverse in bacterial species of the order Enterobacterales (0.8), but the least dominant. The Shannon-Wiener index revealed that it is the most diverse (2.93) and the Margalef index revealed that species richness in this lagoon is high (5.72). Similarity percentage analysis (SIMPER) allowed the identification of the main Enterobacterales with the highest percentage contribution in the frequencies of individuals. In general, the Enterobacterales species isolated showed multi-resistance to the antibiotics used and Escherichia coli was the most resistant.

Microbiome-Based Stain Analyses in Crime Scenes

Recent advances in next-generation sequencing technologies (NGS) coupled with machine learning have demonstrated the potential of microbiome-based analyses in applied areas such as clinical diagnostics and forensic sciences. Particularly in forensics, microbial markers in biological stains left at a crime scene can provide valuable information for the reconstruction of crime scene cases, as they contain information on bodily origin, the time since deposition, and donor(s) of the stain. Importantly, microbiome-based analyses provide a complementary or an alternative approach to current methods when these are limited or not feasible. Despite the promising results from recent research, microbiome-based stain analyses are not yet employed in routine casework. In this review, we highlight the two main gaps that need to be addressed before we can successfully integrate microbiome-based analyses in applied areas with a special focus on forensic casework: one is a comprehensive assessment of the method's strengths and limitations, and the other is the establishment of a standard operating procedure. For the latter, we provide a roadmap highlighting key decision steps and offering laboratory and bioinformatic workflow recommendations, while also delineating those aspects that require further testing. Our goal is to ultimately facilitate the streamlining of microbiome-based analyses within the existing forensic framework to provide alternate lines of evidence, thereby improving the quality of investigations.

Fine-scale evaluation of two standard 16S rRNA gene amplicon primer pairs for analysis of total prokaryotes and archaeal nitrifiers in differently managed soils

The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.

Oral Microbiome in Nonsmoker Patients with Oral Cavity Squamous Cell Carcinoma, Defined by Metagenomic Shotgun Sequencing

Objectives: Smoking is the commonest cause of oral cavity squamous cell carcinoma (OC-SCC), but the etiology of OC-SCC in nonsmokers is unknown. Our primary goal was to use metagenomic shotgun sequencing (MSS) to define the taxonomic composition and functional potential of oral metagenome in nonsmokers with OC-SCC. Methods: We conducted a case-control study with 42 OC-SCC case and 45 control nonsmokers. MSS was performed on DNA extracted from mouthwash samples. Taxonomic analysis and pathway analysis were done using MetaPhlAn2 and HUMAnN2, respectively. Statistical difference was determined using the Mann-Whitney test controlling false discovery rate. Results: There was no significant difference in age, sex, race, or alcohol consumption between OC-SCC and control patients. There was a significant difference in beta diversity between OC-SCC and controls. At the phylum level, Bacteroidetes and Synergistetes were overly represented in OC-SCC while Actinobacteria and Firmicutes were overly represented in controls. At the genus level, Fusobacterium was overly represented in OC-SCC compared with controls, while Corynebacterium, Streptococcus, Actinomyces, Cryptobacterium, and Selenomonas were overly represented in controls. Bacterial pathway analysis identified overrepresentation in OC-SCC of pathways related to metabolism of flavin, biotin, thiamin, heme, sugars, fatty acids, peptidoglycans, and tRNA and overrepresentation of nucleotides and essential amino acids in controls. Conclusions: The oral microbiome in nonsmoker patients with OC-SCC is significantly different from that of nonsmoker control patients in taxonomic compositions and functional potentials. Our study's MSS findings matched with previous 16S-based methods in taxonomic differentiation but varied greatly in functional differentiation of microbiomes in OC-SCC and controls.

Age-Related Changes, Influencing Factors, and Crosstalk Between Vaginal and Gut Microbiota: A Cross-Sectional Comparative Study of Pre- and Postmenopausal Women

Objective: The ideal vaginal environment is maintained by Lactobacillus species, which keep the vagina clean and free of infections, boost fertility and immunity. Age-related decline in estrogen affects Lactobacillus population, leading to dominance of nonoptimal species and increased diversity in vaginal microbiota. In this study, we compared the differences between the vaginal microbiota of pre- and postmenopausal women. We also examined the relationships between vaginal and gut microbiota, their relationships with sex hormones and equol-producing ability. Materials and Methods: This was a cross-sectional study of 35 premenopausal and 35 postmenopausal women (age range: 27-76 years). We compared parameters such as the composition of the gut and vaginal microbiota, vaginal pH, estradiol, follicular stimulating hormone, and urinary equol concentration. Results: In the vaginal microbiota of premenopausal women, Lactobacillus species constituted ∼71.98%, and nonoptimal species constituted ∼16.87%. They were 10.08% and 26.78%, respectively, in the vaginal microbiota of postmenopausal women. The proportion of Lactobacillus was significantly low, whereas microbial diversity and vaginal pH were significantly high (p < 0.0001) in postmenopausal women. The compositions of the vaginal microbiota were significantly different in pre- and postmenopausal women. However, such differences were not noticeable in the gut microbiota. Urinary equol production had no significant correlation with vaginal microbiota, although it had significant relationships with gut microbiota in postmenopausal women. In both groups, the proportions of vaginal Lactobacillus were inversely correlated with vaginal microbial diversity and vaginal pH. Conclusion: Postmenopausal women had significantly low Lactobacillus and high nonoptimal species in their vaginal flora, whereas such age-related differences were not identified in gut microbiota. Urinary equol concentration had significant correlation with gut microbiota in postmenopausal women only. This study was registered with the University Hospital Medical Information Network (UMIN) Clinical Trial Registry (Trial registration No.: UMIN000043944).

The diagnostic potential and barriers of microbiome based therapeutics

High throughput technological innovations in the past decade have accelerated research into the trillions of commensal microbes in the gut. The 'omics' technologies used for microbiome analysis are constantly evolving, and large-scale datasets are being produced. Despite of the fact that much of the research is still in its early stages, specific microbial signatures have been associated with the promotion of cancer, as well as other diseases such as inflammatory bowel disease, neurogenerative diareses etc. It has been also reported that the diversity of the gut microbiome influences the safety and efficacy of medicines. The availability and declining sequencing costs has rendered the employment of RNA-based diagnostics more common in the microbiome field necessitating improved data-analytical techniques so as to fully exploit all the resulting rich biological datasets, while accounting for their unique characteristics, such as their compositional nature as well their heterogeneity and sparsity. As a result, the gut microbiome is increasingly being demonstrating as an important component of personalised medicine since it not only plays a role in inter-individual variability in health and disease, but it also represents a potentially modifiable entity or feature that may be addressed by treatments in a personalised way. In this context, machine learning and artificial intelligence-based methods may be able to unveil new insights into biomedical analyses through the generation of models that may be used to predict category labels, and continuous values. Furthermore, diagnostic aspects will add value in the identification of the non invasive markers in the critical diseases like cancer.

Meta-analysis of larvae of the black soldier fly (Hermetia illucens) microbiota based on 16S rRNA gene amplicon sequencing

Black soldier fly larvae (BSFL) belong to the most widely reared insects as an alternative protein source at industrial scale. Bacteria in the larval gut can provide benefits for the animal, though some bacteria can also be pathogenic for the insect. Accurate characterization of the BSFL microbiota is important for the production of BSFL in terms of yield and microbiological safety. In this study, 16S ribosomal RNA gene sequence data sets from 11 studies were re-analysed to gain better insights in the BSFL gut microbiota, potential factors that influence their composition, and differences between the gut and the whole larvae microbiota. A core gut microbiota was found consisting of members of Enterococcus, Klebsiella, Morganella, Providencia, and Scrofimicrobium. Further, the factors 'Study', 'Age' and 'Feed' (i.e. rearing substrate of the larvae) significantly affected the microbiota gut composition. When compared to whole larvae, a significantly lower diversity was found for gut samples, suggesting that the larvae harboured additional microbes on their cuticle or in the insect body. Universal choices in insect sample type, primer selection and bio-informatics analysis pipeline can strengthen future meta-analyses and improve our understanding of the BSFL gut microbiota towards the optimization of insect rearing conditions and substrates.

16S ribosomal RNA-depletion PCR and its application in cause analysis of yogurt package shrinkage

Fermentative bacteria, the main microbiota in yogurt, interfere with the detection of unintended bacterial contaminants. The removal of fermentative bacteria and enrichment of unintended bacterial contaminants is a challenging task in bacterial detection. The present study developed a new 16S rRNA-depletion PCR for such enrichment and detection. Specifically, a single-guide RNA was designed and synthesized based on the 16S rRNA sequence of Streptococcus thermophilus, with the highest DNA abundance in the yogurt. The CRISPR-Cas9 system was used to specifically cleave and remove the genomic DNA of the fermentative bacteria, followed by PCR amplification. This method improved the detection sensitivity, simplified the operation steps, and reduced the detection cost of PCR analysis. We also used the 16S rRNA-depletion PCR to amplify and detect the unintended bacterial contaminants in yogurts with shrunken packages and analyzed the underlying reasons to prevent this issue of product quality.

The Core Human Microbiome: Does It Exist and How Can We Find It? A Critical Review of the Concept

The core microbiome, which refers to a set of consistent microbial features across populations, is of major interest in microbiome research and has been addressed by numerous studies. Understanding the core microbiome can help identify elements that lead to dysbiosis, and lead to treatments for microbiome-related health states. However, defining the core microbiome is a complex task at several levels. In this review, we consider the current state of core human microbiome research. We consider the knowledge that has been gained, the factors limiting our ability to achieve a reliable description of the core human microbiome, and the fields most likely to improve that ability. DNA sequencing technologies and the methods for analyzing metagenomics and amplicon data will most likely facilitate higher accuracy and resolution in describing the microbiome. However, more effort should be invested in characterizing the microbiome’s interactions with its human host, including the immune system and nutrition. Other components of this holobiontic system should also be emphasized, such as fungi, protists, lower eukaryotes, viruses, and phages. Most importantly, a collaborative effort of experts in microbiology, nutrition, immunology, medicine, systems biology, bioinformatics, and machine learning is probably required to identify the traits of the core human microbiome.

Phylogenies of the 16S rRNA gene and its hypervariable regions lack concordance with core genome phylogenies

BACKGROUND

The 16S rRNA gene is used extensively in bacterial phylogenetics, in species delineation, and now widely in microbiome studies. However, the gene suffers from intragenomic heterogeneity, and reports of recombination and an unreliable phylogenetic signal are accumulating. Here, we compare core gene phylogenies to phylogenies constructed using core gene concatenations to estimate the strength of signal for the 16S rRNA gene, its hypervariable regions, and all core genes at the intra- and inter-genus levels. Specifically, we perform four intra-genus analyses (Clostridium, n = 65; Legionella, n = 47; Staphylococcus, n = 36; and Campylobacter, n = 17) and one inter-genus analysis [41 core genera of the human gut microbiome (31 families, 17 orders, and 12 classes), n = 82].

RESULTS

At both taxonomic levels, the 16S rRNA gene was recombinant and subject to horizontal gene transfer. At the intra-genus level, the gene showed one of the lowest levels of concordance with the core genome phylogeny (50.7% average). Concordance for hypervariable regions was lower still, with entropy masking providing little to no benefit. A major factor influencing concordance was SNP count, which showed a positive logarithmic association. Using this relationship, we determined that 690 ± 110 SNPs were required for 80% concordance (average 16S rRNA gene SNP count was 254). We also found a wide range in 16S-23S-5S rRNA operon copy number among genomes (1-27). At the inter-genus level, concordance for the whole 16S rRNA gene was markedly higher (73.8% - 10th out of 49 loci); however, the most concordant hypervariable regions (V4, V3-V4, and V1-V2) ranked in the third quartile (62.5 to 60.0%).

CONCLUSIONS

Ramifications of a poor phylogenetic performance for the 16S rRNA gene are far reaching. For example, in addition to incorrect species/strain delineation and phylogenetic inference, it has the potential to confound community diversity metrics if phylogenetic information is incorporated - for example, with popular approaches such as Faith's phylogenetic diversity and UniFrac. Our results highlight the problematic nature of these approaches and their use (along with entropy masking) is discouraged. Lastly, the wide range in 16S rRNA gene copy number among genomes also has a strong potential to confound diversity metrics. Video Abstract.

Variation in Rumen Bacteria of Lacaune Dairy Ewes From One Week to the Next

Bacteria are the most abundant microorganisms in the rumen microbiota and play essential roles, mainly fermenting plant compounds that yield fatty acids. In this study, we aimed at assessing stability of both bacterial composition and of its associations with rumen and milk fatty acids phenotypes over a 1-week period. The study was performed using 118 Lacaune dairy ewes from the INRAE Experimental Unit of La Fage. Rumen and milk samples were obtained from the ewes twice, 1 week apart, and microbiota composition, volatile and long-chain fatty acid concentrations were analyzed. Bacterial composition was assessed using 16S rRNA gene sequencing, and microbiota and fatty acids were analyzed as compositional data. As we worked with relative abundances expressed in a constrained space, the centered log-ratio transformation enabled to transform data to work with multivariate analyses in the Euclidian space. Bacterial composition differed between the 2 weeks of sampling, characterized by different proportions of the two main phyla, Bacteroidetes and Firmicutes. The repeatability of the operational taxonomic units (OTUs) was low, although it varied significantly. However, 66 of them presented a repeatability of over 0.50 and were particularly associated with fatty acid phenotypes. Even though the OTUs from the same bacterial families presented similar correlations to fatty acids in both weeks, only a few OTUs were conserved over the 2 weeks. We proved with the help of sequencing data that there is significant change in microbial composition over a week in terms of abundance of different families of bacteria. Further studies are required to determine the impact of bacterial composition alterations over 1 week, and the specificities of the highly repeatable OTUs.

Anthropogenic Intensity-Determined Assembly and Network Stability of Bacterioplankton Communities in the Le'an River

Bacterioplankton are essential components of riverine ecosystems. However, the mechanisms (deterministic or stochastic processes) and co-occurrence networks by which these communities respond to anthropogenic disturbances are not well understood. Here, we integrated niche-neutrality dynamic balancing and co-occurrence network analysis to investigate the dispersal dynamics of bacterioplankton communities along human activity intensity gradients. Results showed that the lower reaches (where intensity of human activity is high) had an increased composition of bacterioplankton communities which induced strong increases in bacterioplankton diversity. Human activity intensity changes influenced bacterioplankton community assembly via regulation of the deterministic-stochastic balance, with deterministic processes more important as human activity increases. Bacterioplankton molecular ecological network stability and robustness were higher on average in the upper reaches (where there is lower intensity of human activity), but a human activity intensity increase of about 10%/10% can reduce co-occurrence network stability of bacterioplankton communities by an average of 0.62%/0.42% in the dry and wet season, respectively. In addition, water chemistry (especially NO₃^–-N and Cl^–) contributed more to explaining community assembly (especially the composition) than geographic distance and land use in the dry season, while the bacterioplankton community (especially the bacterioplankton network) was more influenced by distance (especially the length of rivers and dendritic streams) and land use (especially forest regions) in the wet season. Our research provides a new perspective of community assembly in rivers and important insights into future research on environmental monitoring and classified management of aquatic ecosystems under the influence of human activity.

Fast quantification of gut bacterial species in cocultures using flow cytometry and supervised classification

A bottleneck for microbial community experiments with many samples and/or replicates is the fast quantification of individual taxon abundances, which is commonly achieved through sequencing marker genes such as the 16S rRNA gene. Here, we propose a new approach for high-throughput and high-quality enumeration of human gut bacteria in a defined community, combining flow cytometry and supervised classification to identify and quantify species mixed in silico and in defined communities in vitro. We identified species in a 5-species in silico community with an F1 score of 71%. In addition, we demonstrate in vitro that our method performs equally well or better than 16S rRNA gene sequencing in two-species cocultures and agrees with 16S rRNA gene sequencing data on the most abundant species in a four-species community. We found that shape and size differences alone are insufficient to distinguish species, and that it is thus necessary to exploit the multivariate nature of flow cytometry data. Finally, we observed that variability of flow cytometry data across replicates differs between gut bacterial species. In conclusion, the performance of supervised classification of gut species in flow cytometry data is species-dependent, but is for some combinations accurate enough to serve as a faster alternative to 16S rRNA gene sequencing.

Application of MinION Amplicon Sequencing to Buccal Swab Samples for Improving Resolution and Throughput of Rumen Microbiota Analysis

The Illumina MiSeq platform has been widely used as a standard method for studying the rumen microbiota. However, the low resolution of taxonomic identification is the only disadvantage of MiSeq amplicon sequencing, as it targets a part of the 16S rRNA gene. In the present study, we performed three experiments to establish a high-resolution and high-throughput rumen microbial profiling approach using a combination of MinION platform and buccal swab sample, which is a proxy for rumen contents. In experiment 1, rumen contents and buccal swab samples were collected simultaneously from cannulated cattle (n = 6) and used for microbiota analysis using three different analytical workflows: amplicon sequencing of the V3–V4 region of the 16S rRNA gene using MiSeq and amplicon sequencing of near full-length 16S rRNA gene using MinION or PacBio Sequel II. All reads derived from the MinION and PacBio platforms were classified at the species-level. In experiment 2, rumen fluid samples were collected from beef cattle (n = 28) and used for 16S rRNA gene amplicon sequencing using the MinION platform to evaluate this sequencing platform for rumen microbiota analysis. We confirmed that the MinION platform allowed species-level taxa assignment for the predominant bacterial groups, which were previously identified at the family- and genus-level using the MiSeq platform. In experiment 3, buccal swab samples were collected from beef cattle (n = 30) and used for 16S rRNA gene amplicon sequencing using the MinION platform to validate the applicability of a combination of the MinION platform and buccal swab samples for rumen microbiota analysis. The distribution of predominant bacterial taxa in the buccal swab samples was similar to that in the rumen samples observed in experiment 2. Based on these results, we concluded that the combination of the MinION platform and buccal swab samples may be potentially applied for rumen microbial analysis in large-scale studies.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

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

HIGHLIGHTS

Comparing Published Gut Microbiome Taxonomic Data Across Multinational Studies

BACKGROUND

Nurse researchers are well poised to study the connection of the microbiome to health and disease. Evaluating published microbiome results can assist with study design and hypothesis generation.

OBJECTIVES

This article aims to present and define important analysis considerations in microbiome study planning and to identify genera shared across studies despite methodological differences. This methods article will highlight a workflow that the nurse scientist can use to combine and evaluate taxonomy tables for microbiome study or research proposal planning.

METHODS

We compiled taxonomy tables from 13 published gut microbiome studies that had used Ion Torrent sequencing technology. We searched for studies that had amplified multiple hypervariable (V) regions of the 16S rRNA gene when sequencing the bacteria from healthy gut samples.

RESULTS

We obtained 15 taxonomy tables from the 13 studies, comprised of samples from four continents and eight V regions. Methodology among studies was highly variable, including differences in V regions amplified, geographic location, and population demographics. Nevertheless, of the 354 total genera identified from the 15 data sets, 25 were shared in all V regions and the four continents. When relative abundance differences across the V regions were compared, Dorea and Roseburia were statistically different. Taxonomy tables from Asian subjects had increased average abundances of Prevotella and lowered abundances of Bacteroides compared with the European, North American, and South American study subjects.

DISCUSSION

Evaluating taxonomy tables from previously published literature is essential for study planning. The genera found from different V regions and continents highlight geography and V region as important variables to consider in microbiome study design. The 25 shared genera across the various studies may represent genera commonly found in healthy gut microbiomes. Understanding the factors that may affect the results from a variety of microbiome studies will allow nurse scientists to plan research proposals in an informed manner. This work presents a valuable framework for future cross-study comparisons conducted across the globe.

The 16S rRNA lung microbiome in mechanically ventilated patients: a methodological study

PURPOSE

Characterization of the respiratory tract bacterial microbiome is in its infancy when compared to the gut microbiota. To limit bias mandates a robust methodology. Specific amplification of the hypervariable (V) region of the 16SrRNA gene is a crucial step. Differences in accuracy exist for one V region to another depending on the sampled environment. We aimed to assess the impact of the primer sequences targeting the V4 region currently used for gut microbiota studies in respiratory samples. Materials and methods: The original 515 F-806R primer pair targets the V4 region of the 16SrRNA gene. We compared two different 515 F-806R primer pairs before Illumina 250 paired-end sequencing for bacterial microbiome analyses of respiratory samples from critically-ill ventilated patients. "S-V4" for "Stringent V4" primer pair is used in two ongoing international projects "the Integrative Human microbiome project (iHMP)" and "the Earth microbiome project (EMP)." "R-V4" for "Relaxed V4" primer pair has been modified to reduce biases against specific environmental taxa. The optimal method was determined by concordance with conventional microbiology. Results: Twenty samples from three patients who developed a ventilator-associated pneumonia (VAP) and four who did not (control ventilated patients) were sequenced. Highly different results were obtained. "S-V4" provided the best agreement with the conventional microbiology for endotracheal aspirate: 89% as compared to 56% for "R-V4." The main difference related to poor Enterobacteriaceae detection with "R-V4" primers. Conclusions: Accuracy of the bacterial lung microbiome composition was highly dependent on the primers used for amplification of the 16 s rRNA hypervariable sequence. This work validates for future lung microbiome studies the use of the 515 F-806R "S-V4" primer pair associated to Illumina® MiSeq paired-end sequencing.

Putative Familial Transmissible Bacteria of Various Body Niches Link with Home Environment and Children's Immune Health

Owing to their significant impact on children's long-term health, familial factors in the microbiomes of children have attracted increasing attention. However, the mechanism underlying microbiome transmission across generations remains unclear. A significantly lower alpha diversity was observed in the gut flora of children than in the gut flora of parents and grandparents; the alpha diversity of oral and skin microbiota was relatively higher in children than in their predecessors. Gut, oral, and skin microbiome was more similar between family members than between unrelated individuals. Meanwhile, 55.05%, 61.09%, and 76.73% of amplicon sequence variants (ASVs) in children's gut, oral, and skin microbiomes, respectively, were transmitted from all family members. Among these, the most transmissible ASVs belonged to Methylophilaceae, Solimonadaceae, Neisseriaceae, and Burkholderiaceae, which were defined as "putative familial transmissible bacteria." Furthermore, we found that the time spent with parents/grandparents and children's dietary preferences were important factors that influenced the proportion of the transmissible microbiome. Moreover, the majority of transmissible ASVs (85.06%), especially those of Ruminococcaceae and Lachnospiraceae, were significantly associated with the immune indices, such as CD3⁺, CD4⁺, CD8⁺, IgG, and IgA. IMPORTANCE Our study revealed that the children's microbiota was partially transmitted from their family members and specific putative transmissible ASVs were associated with the immune system of children. These findings suggest that home life plays a key role in the shaping of young children's microbiomes and has long-term health benefits.

Lung Microbiome in Critically Ill Patients

The historical hypothesis of sterility of the lungs was invalidated over a decade ago when studies demonstrated the existence of sparse but very diverse bacterial populations in the normal lung and the association between pulmonary dysbiosis and chronic respiratory diseases. Under mechanical ventilation, dysbiosis occurs rapidly with a gradual decline in diversity over time and the progressive predominance of a bacterial pathogen (mainly Proteobacteria) when lung infection occurs. During acute respiratory distress syndrome, an enrichment in bacteria of intestinal origin, mainly Enterobacteriaceae, is observed. However, the role of this dysbiosis in the pathogenesis of ventilator-associated pneumonia and acute respiratory distress syndrome is not yet fully understood. The lack of exploration of other microbial populations, viruses (eukaryotes and prokaryotes) and fungi is a key issue. Further analysis of the interaction between these microbial kingdoms and a better understanding of the host−microbiome interaction are necessary to fully elucidate the role of the microbiome in the pathogenicity of acute diseases. The validation of a consensual and robust methodology in order to make the comparison of the different studies relevant is also required. Filling these different gaps should help develop preventive and therapeutic strategies for both acute respiratory distress syndrome and ventilator-associated pneumonia.

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

BACKGROUND

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

RESULTS

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

CONCLUSION

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

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.

Clinical Parasitology and Parasitome Maps as Old and New Tools to Improve Clinical Microbiomics

A growing body of evidence shows that dysbiotic gut microbiota may correlate with a wide range of disorders; hence, the clinical use of microbiota maps and fecal microbiota transplantation (FMT) can be exploited in the clinic of some infectious diseases. Through direct or indirect ecological and functional competition, FMT may stimulate decolonization of pathogens or opportunistic pathogens, modulating immune response and colonic inflammation, and restoring intestinal homeostasis, which reduces host damage. Herein, we discuss how diagnostic parasitology may contribute to designing clinical metagenomic pipelines and FMT programs, especially in pediatric subjects. The consequences of more specialized diagnostics in the context of gut microbiota communities may improve the clinical parasitology and extend its applications to the prevention and treatment of several communicable and even noncommunicable disorders.

Host species identity shapes the diversity and structure of insect microbiota

As for most of the life that inhabits our planet, microorganisms play an essential role in insect nutrition, reproduction, defence, and support their host in many other functions. More recently, we assisted to an exponential growth of studies describing the taxonomical composition of bacterial communities across insects' phylogeny. However, there is still an outstanding question that needs to be answered: Which factors contribute most to shape insects' microbiomes? This study tries to find an answer to this question by taking advantage of publicly available sequencing data and reanalysing over 4000 samples of insect-associated bacterial communities under a common framework. Results suggest that insect taxonomy has a wider impact on the structure and diversity of their associated microbial communities than the other factors considered (diet, sex, life stage, sample origin and treatment). However, when specifically testing for signatures of codiversification of insect species and their microbiota, analyses found weak support for this, suggesting that while insect species strongly drive the structure and diversity of insect microbiota, the diversification of those microbial communities did not follow their host's phylogeny. Furthermore, a parallel survey of the literature highlights several methodological limitations that need to be considered in the future research endeavours.

Human- and infrastructure-associated bacteria in greywater

Greywater, the wastewater from sinks, showers and laundry, is an understudied environment for bacterial communities. Most greywater studies focus on quantifying pathogens, often via proxies used in other wastewater, like faecal indicator bacteria; there is a need to identify more greywater-appropriate surrogates, like Staphylococcus sp. Sequencing-based studies have revealed distinct communities in different types of greywater as well as in different parts of greywater infrastructure, including biofilms on pipes, holding tanks and filtration systems. The use of metagenomic sequencing provides high resolution on both the taxa and genes present, which may be of interest in cases like identifying pathogens and surrogates relevant to different matrices, monitoring antibiotic resistance genes and understanding metabolic processes occurring in the system. Here, we review what is known about bacterial communities in different types of greywater and its infrastructure. We suggest that wider adoption of environmental sequencing in greywater research is important because it can describe the entire bacterial community along with its metabolic capabilities, including pathways for removal of nutrients and organic materials. We briefly describe a metagenomic dataset comparing different types of greywater samples in a college dormitory building to highlight the type of questions these methods can address. Metagenomic sequencing can help further the understanding of greywater treatment for reuse because it allows for identification of new pathogens or genes of concern.

Experimental test of microbiome protection across pathogen doses reveals importance of resident microbiome composition

The commensal microbes inhabiting a host tissue can interact with invading pathogens and host physiology in ways that alter pathogen growth and disease manifestation. Prior work in house finches (Haemorhous mexicanus) found that resident ocular microbiomes were protective against conjunctival infection and disease caused by a relatively high dose of Mycoplasma gallisepticum. Here, we used wild-caught house finches to experimentally examine whether protective effects of the resident ocular microbiome vary with the dose of invading pathogen. We hypothesized that commensal protection would be strongest at low M. gallisepticum inoculation doses because the resident microbiome would be less disrupted by invading pathogen. Our five M. gallisepticum dose treatments were fully factorial with an antibiotic treatment to perturb resident microbes just prior to M. gallisepticum inoculation. Unexpectedly, we found no indication of protective effects of the resident microbiome at any pathogen inoculation dose, which was inconsistent with the prior work. The ocular bacterial communities at the beginning of our experiment differed significantly from those previously reported in local wild-caught house finches, likely causing this discrepancy. These variable results underscore that microbiome-based protection in natural systems can be context dependent, and natural variation in community composition may alter the function of resident microbiomes in free-living animals.

The Species-Level Composition of the Fecal Bifidobacterium and Lactobacillus Genera in Indonesian Children Differs from That of Their Mothers

The infant gut microbiota plays a critical role in early life growth and derives mainly from maternal gut and breast milk. This study aimed to analyze the differences in the gut microbiota, namely Bifidobacterium and Lactobacillus communities at species level among breast milk as well as maternal and infant feces at different time points after delivery. Fifty-one mother–infant pairs from Indonesia were recruited, and the breast milk and maternal and infant feces were collected and analyzed by high throughput sequencing (16S rRNA, Bifidobacterium groEL and Lactobacillus groEL genes). PCoA results showed bacterial composition was different among breast milk and maternal and infant feces within the first two years. The abundance of Bifidobacterium and Bacteroides were significantly higher in infant feces compared to their maternal feces from birth to two years of age, and maternal breast milk within six months after birth (p < 0.05), whereas the abundance of Blautia, Prevotella, and Faecalibacterium was higher in maternal feces compared to that in breast milk within six months and infant feces within one year after birth, respectively (p < 0.05). The relative abundances of Bacteroides and Lactobacillus was higher and lower in infant feces compared to that in maternal feces only between one and two years of age, respectively (p < 0.05). For Bifidobacterium community at species level, B. adolescentis, B. ruminantium, B. longum subsp. infantis, B. bifidum, and B. pseudolongum were identified in all samples. However, the profile of Bifidobacterium was different between maternal and infant feces at different ages. The relative abundances of B. adolescentis and B. ruminantium were higher in maternal feces compared to those in infant feces from birth to one year of age (p < 0.05), while the relative abundances of B. longum subsp. infantis and B. bifidum were higher in infant feces compared to those in maternal feces beyond three months, and the relative abundance of B. pseudolongum was only higher in infant feces between three and six months (p < 0.05). For Lactobacillus community, L. paragasseri showed higher relative abundance in infant feces when the infant was younger than one year of age (p < 0.05). This study showed bacterial composition at the genus level and Bifidobacterium and Lactobacillus communities at the species level were stage specific in maternal breast milk as well as and maternal and infant feces.

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.

Assessing the effect of treated erythromycin fermentation residue on antibiotic resistome in soybean planting soil: In situ field study

As a by-product in the pharmaceutical industry, antibiotic fermentation residue is expected to be able to be utilized after effectively removing the antibiotics. However, evaluation of the effect of fermentation residue application on soil, especially the in situ environmental consequences considering not only the antibiotic resistance gene (ARG) abundance but also the resistome risk, has still not been sufficiently evaluated. Herein, the impact of treated erythromycin fermentation residue (EFR) on the resistome and risk score in soybean planting soil was investigated. Treated EFR application with dosages of 3750 kg (EFR250) and 7500 kg (EFR500) per hm2 soil did not increase the diversity (Shannon index, 2.84-3.38) or relative abundance (0.086-0.142 copies/16S rRNA gene) of the soil resistome compared with the Control (CK: 2.92-3.2, 0.088-0.096 copies/16S rRNA gene). Soil resistome risk scores calculated by metagenomic assembly, showing the dissemination potential of ARGs, ranged from 22.9 to 25.0, and were also not significantly different between treated EFR amended soil and the Control. Notably, the diversity of the resistome increased at the sprout stage (Mann-Whitney U test, P < 0.05) and the abundance of some ARG types (macrolide-lincosamide-streptogramin, aminoglycoside and tetracycline, etc.) shifted along the course of soybean growth (Kruskal-Wallis test, P < 0.05). Structural equation model analysis showed that the soybean growth period affected the composition of ARGs by affecting the microbial community, which was further supported by Procrustes analysis (P < 0.05) and metagenomic binning. Our findings emphasized that soil ARG abundance and resistome risk did not increase during one-time field application of treated EFR at the studied dosage. Comprehensive consideration including resistome risk and multiple influencing factors also should be given for further assessment of fermentation residue application.

Evaluation of Three Prokaryote Primers for Identification of Prokaryote Community Structure and Their Abode Preference in Three Distinct Wetland Ecosystems

The ultimate role of prokaryote (bacteria and archaea), the decomposer of the wetland ecosystem, depends on its community structure and its interaction with the environment. The present study has used three universal prokaryote primers to compare prokaryote community structure and diversity of three distinctly different wetlands. The study results revealed that α-diversity indices and phylogenetic differential abundance patterns did not differ significantly among primers, but they did differ significantly across wetlands. Microbial community composition revealed a distinct pattern for each primer in each wetland. Overall comparison of prokaryote communities in sediments of three wetlands revealed the highest prokaryote richness and diversity in Bhomra (freshwater wetland) followed by Malencho (brackish-water wetland) and East Kolkata wetland (EKW) (sewage-fed wetland). Indicator genus analysis identified 21, 4, and 29 unique indicator genera, having preferential abode for Bhomra, EKW, and Malencho, respectively. Prediction of potential roles of these microbes revealed a preference for sulfate-reducing microbes in Malencho and methanogens in Bhomra. The distinct phylogenetic differential abundance pattern, microbial abode preference, and their potential functional role predict ecosystem variables shaping microbial diversity. The variation in community composition of prokaryotes in response to ecosystem variables can serve as the most sensitive bioindicator of wetland ecosystem assessment and management.

Gut microbiota-mediated immunomodulation in tumor

Tumor immunity consists of various types of cells, which serve an important role in antitumor therapy. The gastrointestinal tract is colonized by trillions of microorganisms, which form the gut microbiota. In addition to pathogen defense and maintaining the intestinal ecosystem, gut microbiota also plays a pivotal role in various physiological processes. Recently, the association between these symbionts and cancer, ranging from oncogenesis and cancer progression to resistance or sensitivity to antitumor therapies, has attracted much attention. Metagenome analysis revealed a significant difference between the gut microbial composition of cancer patients and healthy individuals. Moreover, modulation of microbiome could improve therapeutic response to immune checkpoint inhibitors (ICIs). These findings suggest that microbiome is involved in cancer pathogenesis and progression through regulation of tumor immunosurveillance, although the exact mechanisms remain largely unknown. This review focuses on the interaction between the microbiome and tumor immunity, with in-depth discussion regarding the therapeutic potential of modulating gut microbiota in ICIs. Further investigations are warranted before gut microbiota can be introduced into clinical practice.

Analysis of the Bacterial Flora of Sensitive Facial Skin Among Women in Guangzhou

Background

Sensitive skin (SS) is easily irritated by various environmental stimuli, and epidemiological surveys surprisingly find that self-perceived SS is widespread worldwide.

Objective

To investigate whether SS is linked to changes in the skin bacterial population using 16S rRNA sequencing and bioinformatic analysis.

Patients and Methods

According to both the Huaxi SS Questionnaire and Lactic Acid Stimulation Test, 60 female volunteers in Guangzhou were classified into normal skin (NS) and SS groups. Skin barrier parameters were assessed by the CK skin tester. The DNA of the bacterial flora on the facial skin surface was extracted and was subjected to 16S rRNA sequencing.

Results

The skin hydration was significantly lower in the SS group compared to the NS group (P =0.032). Based on 16S rRNA sequencing and bioinformatic analysis, the number of operational taxonomic units (OTUs) significantly decreased in the SS group (P =0.0235, SS vs NS). The relative abundance of Neisseriaceae in SS group decreased significantly (P <0.05, SS vs NS), while that of Neisseria (within the Neisseriaceae family) increased significantly (P <0.05, SS vs NS).

Conclusion

SS is accompanied by a decrease in species diversity and richness, which may be relevant to the weakening of the microbial barrier (due to the increase of Neisseria or the decrease of Neisseriaceae). Thus, corresponding treatment for Neisseriaceae may be a new idea in the treatment of SS.

Choice of 16S ribosomal RNA primers affects the microbiome analysis in chicken ceca

We evaluated the effect of applying different sets of 16S rRNA primers on bacterial composition, diversity, and predicted function in chicken ceca. Cecal contents from Ross 708 birds at 1, 3, and 5 weeks of age were collected for DNA isolation. Eight different primer pairs targeting different variable regions of the 16S rRNA gene were employed. DNA sequences were analyzed using open-source platform QIIME2 and the Greengenes database. PICRUSt2 was used to determine the predicted function of bacterial communities. Changes in bacterial relative abundance due to 16S primers were determined by GLMs. The average PCR amplicon size ranged from 315 bp (V3) to 769 bp (V4–V6). Alpha- and beta-diversity, taxonomic composition, and predicted functions were significantly affected by the primer choice. Beta diversity analysis based on Unweighted UniFrac distance matrix showed separation of microbiota with four different clusters of bacterial communities. Based on the alpha- and beta-diversity and taxonomic composition, variable regions V1–V3(1) and (2), and V3–V4 and V3–V5 were in most consensus. Our data strongly suggest that selection of particular sets of the 16S rRNA primers can impact microbiota analysis and interpretation of results in chicken as was shown previously for humans and other animal species.