Primer, Pipelines, Parameters: Issues in 16S rRNA Gene Sequencing

Maize pollen carry bacteria that suppress a fungal pathogen that enters through the male gamete fertilization route

In flowering plants, after being released from pollen grains, the male gametes use the style channel to migrate towards the ovary where they fertilize awaiting eggs. Environmental pathogens exploit the style passage, resulting in diseased progeny seed. The belief is that pollen also transmits pathogens into the style. By contrast, we hypothesized that pollen carries beneficial microbes that suppress environmental pathogens on the style passage. No prior studies have reported pollen-associated bacterial functions in any plant species. Here, bacteria were cultured from maize (corn) pollen encompassing wild ancestors and farmer-selected landraces from across the Americas, grown in a common field in Canada for one season. In total, 298 bacterial isolates were cultured, spanning 45 genera, 103 species, and 88 OTUs, dominated by Pantoea, Bacillus, Pseudomonas, Erwinia, and Microbacterium. Full-length 16S DNA-based taxonomic profiling showed that 78% of bacterial taxa from the major wild ancestor of maize (Parviglumis teosinte) were present in at least one cultivated landrace. The species names of the bacterial isolates were used to search the pathogen literature systematically; this preliminary evidence predicted that the vast majority of the pollen-associated bacteria analyzed are not maize pathogens. The pollen-associated bacteria were tested in vitro against a style-invading Fusarium pathogen shown to cause Gibberella ear rot (GER): 14 isolates inhibited this pathogen. Genome mining showed that all the anti-Fusarium bacterial species encode phzF, associated with biosynthesis of the natural fungicide, phenazine. To mimic the male gamete migration route, three pollen-associated bacterial strains were sprayed onto styles (silks), followed by Fusarium inoculation; these bacteria reduced GER symptoms and mycotoxin accumulation in progeny seed. Confocal microscopy was used to search for direct evidence that pollen-associated bacteria can defend living silks against Fusarium graminearum (Fg); bacterial strain AS541 (Kluyvera intermedia), isolated from pollen of ancestral Parviglumis, was observed to colonize the susceptible style/silk entry points of Fg (silk epidermis, trichomes, wounds). Furthermore, on style/silk tissue, AS541 colonized/aggregated on Fg hyphae, and was associated with Fg hyphal breaks. These results suggest that pollen has the potential to carry bacteria that can defend the style/silk passage against an environmental pathogen - a novel observation.

The atmosphere: a transport medium or an active microbial ecosystem?

The atmosphere may be Earth's largest microbial ecosystem. It is connected to all of Earth's surface ecosystems and plays an important role in microbial dispersal on local to global scales. Despite this grand scale, surprisingly little is understood about the atmosphere itself as a habitat. A key question remains unresolved: does the atmosphere simply transport microorganisms from one location to another, or does it harbour adapted, resident, and active microbial communities that overcome the physiological stressors and selection pressures the atmosphere poses to life? Advances in extreme microbiology and astrobiology continue to push our understanding of the limits of life towards ever greater extremes of temperature, pressure, salinity, irradiance, pH, and water availability. Earth's atmosphere stands as a challenging, but potentially surmountable, extreme environment to harbour living, active, resident microorganisms. Here, we confront the current understanding of the atmosphere as a microbial habitat, highlighting key advances and limitations. We pose major ecological and mechanistic questions about microbial life in the atmosphere that remain unresolved and frame the problems and technical pitfalls that have largely hindered recent developments in this space, providing evidence-based insights to drive future research in this field. New innovations supported by rigorous technical standards are needed to enable progress in understanding atmospheric microorganisms and their influence on global processes of weather, climate, nutrient cycling, biodiversity, and microbial connectivity, especially in the context of rapid global change.

Quantitative Aggregation of Microbiome Sequencing Data Provides Insights into the Associations between the Skin Microbiome and Psoriasis

Although prior studies have reported distinct skin microbiome profiles associated with psoriasis, differences in methods and analyses limit generalizable conclusions. Individual studies have actually reported conflicting findings; for example, Propionibacterium and Staphylococcus have been significantly associated with both psoriatic lesions and healthy skin. Qualitative reviews have attempted to summarize this body of work, but there is great variability across the studies' findings and methods. To better unify these data, we created a meta-analysis of all publicly available datasets by utilizing a uniform bioinformatics pipeline and reference database to investigate associations of the skin microbiome in psoriasis. A total of 977 skin swab samples (341 lesional, 295 nonlesional, and 341 healthy) from 6 studies were analyzed. The aggregated analysis revealed a higher relative abundance of microorganisms, including Staphylococcus aureus and Corynebacterium simulans, among others, from patients with psoriasis than those from healthy swab samples; in addition, Cutibacterium acnes, Lawsonella unclassified, and S warneri were significantly higher in healthy samples. Furthermore, comparison of functional pathways predicted from 16S gene markers showed that L-ornithine biosynthesis and L-histidine biosynthesis were lower in psoriatic lesions than in healthy controls. Taken together, this meta-analysis allows for a more generalizable association between the skin microbiome and psoriasis.

Mock microbial community meta-analysis using different trimming of amplicon read lengths

Trimming of sequencing reads is a pre-processing step that aims to discard sequence segments such as primers, adapters and low quality nucleotides that will interfere with clustering and classification steps. We evaluated the impact of trimming length of paired-end 16S and 18S rRNA amplicon reads on the ability to reconstruct the taxonomic composition and relative abundances of communities with a known composition in both even and uneven proportions. We found that maximizing read retention maximizes recall but reduces precision by increasing false positives. The presence of expected taxa was accurately predicted across broad trim length ranges but recovering original relative proportions remains a difficult challenge. We show that parameters that maximize taxonomic recovery do not simultaneously maximize relative abundance accuracy. Trim length represents one of several experimental parameters that have non-uniform impact across microbial clades, making it a difficult parameter to optimize. This study offers insights, guidelines, and helps researchers assess the significance of their decisions when trimming raw reads in a microbiome analysis based on overlapping or non-overlapping paired-end amplicons.

Uterine microbial ecology and disease in cattle: A review

Due to the critical contribution of the uterine-associated microbiota in reproductive health, physiology, and performance, culture-independent methods have been increasingly employed to unravel key aspects of microbial ecology in the uterus of cattle. Nowadays, we know that bacterial diversity is crucial to maintain uterine health, however, there is still no consensus on the exact composition of a healthy uterine microbiota (or eubiosis). Generally, loss of bacterial diversity (or dysbiosis) contributes to the development of uterine infections, associated with increased relative abundances of Bacteroides, Fusobacterium, Trueperella, and Porphyromonas. Uterine infections are highly prevalent and gravely influence the profitability of cattle operations, animal welfare, and public health. Thus, understanding the dynamics of uterine microbial ecology is essential to develop effective strategies focused on preventing and mitigating the adverse effects of uterine dysbiosis as well as assisting in the process of restoring the core, healthy uterine microbiota. The aim of this review is to summarize research conducted in the microbial ecology of bovine uteri. We discuss the origin of the uterine microflora of healthy cows and the factors influencing its composition. In addition, we review the biology of specific pathogens that are known to increase in abundance during the occurrence of uterine disease. Lastly, we provide an overview of the bacterial biofilm in the bovine endometrium, and we briefly summarize the rationale for the use of probiotics to prevent uterine disease in cattle.

Conservation and diversity of the pollen microbiome of Pan-American maize using PacBio and MiSeq

Pollen is a vector for diversification, fitness-selection, and transmission of plant genetic material. The extent to which the pollen microbiome may contribute to host diversification is largely unknown, because pollen microbiome diversity within a plant species has not been reported, and studies have been limited to conventional short-read 16S rRNA gene sequencing (e.g., V4-MiSeq) which suffers from poor taxonomic resolution. Here we report the pollen microbiomes of 16 primitive and traditional accessions of maize (corn) selected by indigenous peoples across the Americas, along with the modern U.S. inbred B73. The maize pollen microbiome has not previously been reported. The pollen microbiomes were identified using full-length (FL) 16S rRNA gene PacBio SMRT sequencing compared to V4-MiSeq. The Pan-American maize pollen microbiome encompasses 765 taxa spanning 39 genera and 46 species, including known plant growth promoters, insect-obligates, plant pathogens, nitrogen-fixers and biocontrol agents. Eleven genera and 13 species composed the core microbiome. Of 765 taxa, 63% belonged to only four genera: 28% were Pantoea, 15% were Lactococcus, 11% were Pseudomonas, and 10% were Erwinia. Interestingly, of the 215 Pantoea taxa, 180 belonged to a single species, P. ananatis. Surprisingly, the diversity within P. ananatis ranged nearly 10-fold amongst the maize accessions analyzed (those with ≥3 replicates), despite being grown in a common field. The highest diversity within P. ananatis occurred in accessions that originated near the center of diversity of domesticated maize, with reduced diversity associated with the north-south migration of maize. This sub-species diversity was revealed by FL-PacBio but missed by V4-MiSeq. V4-MiSeq also mis-identified some dominant genera captured by FL-PacBio. The study, though limited to a single season and common field, provides initial evidence that pollen microbiomes reflect evolutionary and migratory relationships of their host plants.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

The gut-microbiome in adult Attention-deficit/hyperactivity disorder - A Meta-analysis

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition that persists into adulthood in the majority of individuals. While the gut-microbiome seems to be relevant for ADHD, the few publications on gut-microbial alterations in ADHD are inconsistent, in the investigated phenotypes, sequencing method/region, preprocessing, statistical approaches, and findings. To identify gut-microbiome alterations in adult ADHD, robust across studies and statistical approaches, we harmonized bioinformatic pipelines and analyses of raw 16S rRNA sequencing data from four adult ADHD case-control studies (N ADHD =312, N NoADHD =305). We investigated diversity and differential abundance of selected genera (logistic regression and ANOVA-like Differential Expression tool), corrected for age and sex, and meta-analyzed the study results. Converging results were investigated for association with hyperactive/impulsive and inattentive symptoms across all participants. Beta diversity was associated with ADHD diagnosis but showed significant heterogeneity between cohorts, despite harmonized analyses. Several genera were robustly associated with adult ADHD; e.g., Ruminococcus_torques_group (LogOdds=0.17, p fdr =4.42×10 -2 ), which was more abundant in adults with ADHD, and Eubacterium_xylanophilum_group (LogOdds= -0.12, p fdr =6.9 x 10 -3 ), which was less abundant in ADHD. Ruminococcus_torques_group was further associated with hyperactivity/impulsivity symptoms and Eisenbergiella with inattention and hyperactivity/impulsivity (p fdr <0.05). The literature points towards a role of these genera in inflammatory processes. Irreproducible results in the field of gut-microbiota research, due to between study heterogeneity and small sample sizes, stress the need for meta-analytic approaches and large sample sizes. While we robustly identified genera associated with adult ADHD, that might overall be considered beneficial or risk-conferring, functional studies are needed to shed light on these properties.

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.

A cross-sectional cohort study on the skin microbiota in patients with different acne durations

Acne is a chronic disease that often persists for years. Skin microbial communities play an essential role in the development of acne. However, limited information is available about the dynamic patterns of skin microbiota in acne. This study aimed to characterize microbial community changes in skin pores and surfaces of acne patients with varying disease time. In this study, a total of 70 skin samples from 22 subjects were collected and sequenced using 16S rRNA amplicon sequencing. Although microbial compositions in skin pores were similar over time, significant differences in microbial structure were observed on the skin surface, with the dominance of Cutibacterium in the first 3 years and replacement by Staphylococcus in 4-6 years. Lactobacillus and Acinetobacter were more abundant in the normal group and continuingly decreased with disease time on the skin surface. Microbial networks further revealed substantial increases in microbial interactions in the 4-6 years group in both skin surfaces and pores. These results demonstrate that the skin microbiota alters with the disease duration and may provide a potential guide in redirecting skin microbiota towards healthy states.

Loss of αβ but not γδ T cells in chickens causes a severe phenotype

The availability of genetically modified mice has facilitated the study of mammalian T cells. No model has yet been developed to study these cells in chickens, an important livestock species with a high availability of γδ T cells. To investigate the role of γδ and αβ T cell populations in birds, we generated chickens lacking these T cell populations. This was achieved by genomic deletion of the constant region of the T cell receptor γ or β chain, leading to a complete loss of either γδ or αβ T cells. Our results show that a deletion of αβ T cells but not γδ T cells resulted in a severe phenotype in KO chickens. The αβ T cell KO chickens exhibited granulomas associated with inflammation of the spleen and the proventriculus. Immunophenotyping of αβ T cell KO chickens revealed a significant increase in monocytes and expectedly the absence of CD4+ T cells including FoxP3+ regulatory T cells. Surprisingly there was no increase of γδ T cells. In addition, we observed a significant decrease in immunoglobulins, B lymphocytes, and changes in the bursa morphology. Our data reveal the consequences of T cell knockouts in chickens and provide new insights into their function in vertebrates.

Analysis of microbial composition and sharing in low-biomass human milk samples: a comparison of DNA isolation and sequencing techniques

Human milk microbiome studies are currently hindered by low milk bacterial/human cell ratios and often rely on 16S rRNA gene sequencing, which limits downstream analyses. Here, we aimed to find a method to study milk bacteria and assess bacterial sharing between maternal and infant microbiota. We tested four DNA isolation methods, two bacterial enrichment methods and three sequencing methods on mock communities, milk samples and negative controls. Of the four DNA isolation kits, the DNeasy PowerSoil Pro (PS) and MagMAX Total Nucleic Acid Isolation (MX) kits provided consistent 16S rRNA gene sequencing results with low contamination. Neither enrichment method substantially decreased the human metagenomic sequencing read-depth. Long-read 16S-ITS-23S rRNA gene sequencing biased the mock community composition but provided consistent results for milk samples, with little contamination. In contrast to 16S rRNA gene sequencing, 16S-ITS-23S rRNA gene sequencing of milk, infant oral, infant faecal and maternal faecal DNA from 14 mother-infant pairs provided sufficient resolution to detect significantly more frequent sharing of bacteria between related pairs compared to unrelated pairs. In conclusion, PS or MX kit-DNA isolation followed by 16S rRNA gene sequencing reliably characterises human milk microbiota, and 16S-ITS-23S rRNA gene sequencing enables studies of bacterial transmission in low-biomass samples.

Soil as a transdisciplinary research catalyst: from bioprospecting to biorespecting

The vast microbial biodiversity of soils is beginning to be observed and understood by applying modern DNA sequencing techniques. However, ensuring this potentially valuable information is used in a fair and equitable way remains a challenge. Here, we present a public engagement project that explores this topic through collaborative research of soil microbiomes at six urban locations using nanopore-based DNA sequencing. The project brought together researchers from the disciplines of synthetic biology, environmental humanities and microbial ecology, as well as school students aged 14-16 years old, to gain a broader understanding of views on the use of data from the environment. Discussions led to the transformation of 'bioprospecting', a metaphor with extractive connotations which is often used to frame environmental DNA sequencing studies, towards a more collaborative approach-'biorespecting'. This shift in terminology acknowledges that genetic information contained in soil arises as a result of entire ecosystems, including the people involved in its creation. Therefore, any use of sequence information should be accountable to the ecosystems from which it arose. As knowledge can arise from ecosystems and communities, science and technology should acknowledge this link and reciprocate with care and benefit-sharing to help improve the wellbeing of future generations.

ASVmaker: A New Tool to Improve Taxonomic Identifications for Amplicon Sequencing Data

The taxonomic assignment of sequences obtained by high throughput amplicon sequencing poses a limitation for various applications in the biomedical, environmental, and agricultural fields. Identifications are constrained by the length of the obtained sequences and the computational processes employed to efficiently assign taxonomy. Arriving at a consensus is often preferable to uncertain identification for ecological purposes. To address this issue, a new tool called "ASVmaker" has been developed to facilitate the creation of custom databases, thereby enhancing the precision of specific identifications. ASVmaker is specifically designed to generate reference databases for allocating amplicon sequencing data. It uses publicly available reference data and generates specific sequences derived from the primers used to create amplicon sequencing libraries. This versatile tool can complete taxonomic assignments performed with pre-trained classifiers from the SILVA and UNITE databases. Moreover, it enables the generation of comprehensive reference databases for specific genes in cases where no directly applicable database exists for taxonomic classification tools.

Mucosal Microbiome in Patients with Early Bowel Polyps: Inferences from Short-Read and Long-Read 16S rRNA Sequencing

Numerous studies have correlated dysbiosis in stool microbiota with colorectal cancer (CRC); however, fewer studies have investigated the mucosal microbiome in pre-cancerous bowel polyps. The short-read sequencing of variable regions in the 16S rRNA gene has commonly been used to infer bacterial taxonomy, and this has led, in part, to inconsistent findings between studies. Here, we examined mucosal microbiota from patients who presented with one or more polyps, compared to patients with no polyps, at the time of colonoscopy. We evaluated the results obtained using both short-read and PacBio long-read 16S rRNA sequencing. Neither sequencing technology identified significant differences in microbial diversity measures between patients with or without bowel polyps. Differential abundance measures showed that amplicon sequence variants (ASVs) associated with Ruminococcus gnavus and Escherichia coli were elevated in mucosa from polyp patients, while ASVs associated with Parabacteroides merdae, Veillonella nakazawae, and Sutterella wadsworthensis were relatively decreased. Only R. gnavus was consistently identified using both sequencing technologies as being altered between patients with polyps compared to patients without polyps, suggesting differences in technologies and bioinformatics processing impact study findings. Several of the differentially abundant bacteria identified using either sequencing technology are associated with inflammatory bowel diseases despite these patients being excluded from the current study, which suggests that early bowel neoplasia may be associated with a local inflammatory niche.

Midgut microbiota affects the intestinal barrier by producing short-chain fatty acids in Apostichopus japonicus

Introduction

The intestinal microbiota participates in host physiology and pathology through metabolites, in which short-chain fatty acids (SCFAs) are considered principal products and have extensive influence on intestine homeostasis. It has been reported that skin ulceration syndrome (SUS), the disease of Apostichopus japonicus caused by Vibrio splendidus, is associated with the alteration of the intestinal microbiota composition.

Method

To investigate whether the intestinal microbiota affects A. japonicus health via SCFAs, in this study, we focus on the SCFA profiling and intestinal barrier function in A. japonicus treated with V. splendidus.

Results and discussion

We found that V. splendidus could destroy the mid-intestine integrity and downregulate the expression of tight junction proteins ZO-1 and occludin in A. japonicus, which further dramatically decreased microorganism abundance and altered SCFAs contents. Specifically, acetic acid is associated with the largest number of microorganisms and has a significant correlation with occludin and ZO-1 among the seven SCFAs. Furthermore, our findings showed that acetic acid could maintain the intestinal barrier function by increasing the expression of tight junction proteins and rearranging the tight junction structure by regulating F-actin in mid-intestine epithelial cells. Thus, our results provide insights into the effects of the gut microbiome and SCFAs on intestine barrier homeostasis and provide essential knowledge for intervening in SUS by targeting metabolites or the gut microbiota.

Homemade Nucleic Acid Preservation Buffer Proves Effective in Preserving the Equine Faecal Microbiota over Time at Ambient Temperatures

The equine faecal microbiota is often assessed as a proxy of the microbial community in the distal colon, where the microbiome has been linked to states of health and disease in the horse. However, the microbial community structure may change over time if samples are not adequately preserved. This study stored equine faecal samples from n = 10 horses in four preservation treatments at room temperature for up to 150 h and assessed the resulting impact on microbial diversity and the differential abundance of taxa. Treatments included "COLD" (samples packaged with a cool pack), "CLX" (2% chlorhexidine digluconate solution), "NAP" (nucleic acid preservation buffer), and "FTA" (Whatman FTA™ cards). The samples were assessed using 16S rRNA gene sequencing after storage for 0, 24, 72, and 150 h at room temperature under the different treatments. The results showed effective preservation of diversity and community structure with NAP buffer but lower diversity (p = 0.001) and the under-representation of Fibrobacterota in the FTA card samples. The NAP treatment inhibited the overgrowth of bloom taxa that occurred by 72 h at room temperature. The COLD, CLX, and NAP treatments were effective in preserving the faecal microbiota for up to 24 h at room temperature, and the CLX and NAP treatments improved the yield of Patescibacteria and Fibrobacterota in some cases. The cold and CLX treatments were ineffective in preventing community shifts that occurred by 72 h at room temperature. These findings demonstrate the suitability of the COLD, NAP, and CLX treatments for the room temperature storage of equine faeces for up to 24 h and of NAP buffer for up to 150 h prior to processing.

Underpinning the ecological response of mixed chlorinated volatile organic compounds (CVOCs) associated with contaminated and bioremediated groundwaters: A potential nexus of microbial community structure and function for strategizing efficient bioremediation

Understanding the structure, dynamics, and functionality of microbial communities is essential for developing sustainable and effective bioremediation strategies, particularly for sites contaminated with mixed chlorinated volatile organic compounds (CVOCs), which can make the biodegradation process more complex and challenging. In this study, 16S rRNA amplicon sequencing revealed a significant change in microbial distribution in response to CVOCs contamination. The loss of sensitive taxa such as Proteobacteria and Acidobacteriota was observed, while CVOCs-resistant taxa such as Campilobacterota were found significantly enriched in contaminated sites. Additionally, varying abundances of crucial enzymes involved in the sequential biodegradation of CVOCs were expressed depending on the contamination level. Association analysis revealed that specific genera such as Sulfurospirillum, Azospira, Trichlorobacter, Acidiphilium, and Magnetospririllum could relatively survive under higher levels of CVOC contamination, whereas pH, ORP and temperature had a negative influence in their abundance and distribution. However, Dechloromonas, Thiobacillus, Pseudarcicella, Hydrogenophaga, and Sulfuritalea showed a negative relationship with CVOC contamination, highlighting their sensitivity towards CVOC contamination. These findings provide valuable insights into the relationship among ecological responses, the groundwater bacterial community, and their functionality in response to mixed CVOC contamination, offering a fundamental basis for developing effective and sustainable bioremediation strategies for CVOC-contaminated groundwater systems.

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.

Metabolic Dysfunction-Associated Fatty Liver Disease on Distinct Microbial Communities at the Bacterial Phylum Level

INTRODUCTION

Limited data are available on the correlation between microbial communities and metabolic dysfunction-associated fatty liver disease (MAFLD). This study aimed to evaluate the influence of MAFLD on diverse microbial communities.

METHODS

We recruited 43 patients with a nonviral liver disease. Enrolled patients were divided into two groups according to MAFLD criteria. The fecal microbial composition was evaluated using the variable V3-V4 region of the 16S ribosomal RNA region, which was amplified using polymerase chain reaction. First, we assessed the influence of MAFLD on distinct microbial communities at the bacterial phylum level. Next, the correlation between the microbial communities and diversity in patients with MAFLD was evaluated.

RESULTS

Among the enrolled participants, the non-MAFLD and MAFLD groups consisted of 21 and 22 patients, respectively. Sequences were distributed among ten bacterial phyla. The relative abundance of Firmicutes was significantly higher in the MAFLD group than in the non-MAFLD group (p = 0.014). The microbial diversity was not significantly influenced by the presence of MAFLD (Chao-1 index: p = 0.215 and Shannon index: p = 0.174, respectively); nonetheless, the correlation coefficient between the abundances of Firmicutes and microbial diversity was higher in the non-MAFLD group than in the MAFLD group.

CONCLUSION

The presence of MAFLD increased the relative abundances of Firmicutes at the bacterial phylum level, which may cause the discrepancy between the abundances of Firmicutes and diversity in patients with MAFLD.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

Crohn's Disease Prediction Using Sequence Based Machine Learning Analysis of Human Microbiome

Human microbiota refers to the trillions of microorganisms that inhabit our bodies and have been discovered to have a substantial impact on human health and disease. By sampling the microbiota, it is possible to generate massive quantities of data for analysis using Machine Learning algorithms. In this study, we employed several modern Machine Learning techniques to predict Inflammatory Bowel Disease using raw sequence data. The dataset was obtained from NCBI preprocessed graph representations and converted into a structured form. Seven well-known Machine Learning frameworks, including Random Forest, Support Vector Machines, Extreme Gradient Boosting, Light Gradient Boosting Machine, Gaussian Naïve Bayes, Logistic Regression, and k-Nearest Neighbor, were used. Grid Search was employed for hyperparameter optimization. The performance of the Machine Learning models was evaluated using various metrics such as accuracy, precision, fscore, kappa, and area under the receiver operating characteristic curve. Additionally, Mc Nemar's test was conducted to assess the statistical significance of the experiment. The data was constructed using k-mer lengths of 3, 4 and 5. The Light Gradient Boosting Machine model overperformed over other models with 67.24%, 74.63% and 76.47% accuracy for k-mer lengths of 3, 4 and 5, respectively. The LightGBM model also demonstrated the best performance in each metric. The study showed promising results predicting disease from raw sequence data. Finally, Mc Nemar's test results found statistically significant differences between different Machine Learning approaches.

GLP-1 receptor agonists modulate blood glucose levels in T2DM by affecting Faecalibacterium prausnitzii abundance in the intestine

BACKGROUND

Glucagon-like peptide 1 (GLP-1) receptor agonists are a class of medications used to treat type 2 diabetes, including metformin, which is considered first-line therapy for type 2 diabetes. In recent years, GLP-1 receptor agonists (GLP-1 RAs) have been found to alter the composition and structure of gut flora and also promote the production of gut probiotics. However, there have been few clinical studies regarding the effects of GLP-1 RAs on gut flora. In this study, we investigated changes in the abundance of Lactobacillus delbrueckii (L delbrueckii) and Faecalibacterium prausnitzii (F prausnitzii) 1 week after administration of a GLP-1 RA in the clinical treatment of type 2 diabetes. The association with glycemic and body mass index (BMI) correlations was also explored.

METHODS

Twelve newly diagnosed patients with type 2 diabetes were examined for changes in the abundance of L delbrueckii and F prausnitzii by Fluorescence in Situ Hybridization 1 week after administration of GLP-1 RAs. Subjects BMI was measured and fasting glucose changes were detected using the glucose oxidase method, and Spearman correlation analysis was performed to explore their relevance.

RESULTS

There was no significant change in the abundance of L delbrueckii in the intestine (P = .695) and no significant correlation with BMI and fasting glucose levels (R = 0.134, P = .534) after the use of GLP-1 RA (R = -0.098, P = .647); F prausnitzii on the other hand had a significantly higher abundance (P = .002) and a significant negative correlation with fasting glucose level (R = -0.689, P < .001), but no significant correlation with BMI (R = -0.056, P = .796).

CONCLUSION

F prausnitzii may be one of the pathways through which glucose is regulated in the treatment of type 2 diabetes by GLP-1 RAs.

State of the Art for Diagnosis of Bacterial Vaginosis

Bacterial vaginosis (BV) is the most common cause of vaginal discharge among reproductive-age women. It is associated with multiple adverse health outcomes, including increased risk of acquisition of HIV and other sexually transmitted infections (STIs), in addition to adverse birth outcomes. While it is known that BV is a vaginal dysbiosis characterized by a shift in the vaginal microbiota from protective Lactobacillus species to an increase in facultative and strict anaerobic bacteria, its exact etiology remains unknown. The purpose of this minireview is to provide an updated overview of the range of tests currently used for the diagnosis of BV in both clinical and research settings. This article is divided into two primary sections: traditional BV diagnostics and molecular diagnostics. Molecular diagnostic assays, particularly 16S rRNA gene sequencing, shotgun metagenomic sequencing, and fluorescence in situ hybridization (FISH), are specifically highlighted, in addition to multiplex nucleic acid amplification tests (NAATs), given their increasing use in clinical practice (NAATs) and research studies (16S rRNA gene sequencing, shotgun metagenomic sequencing, and FISH) regarding the vaginal microbiota and BV pathogenesis. We also provide a discussion of the strengths and weaknesses of current BV diagnostic tests and discuss future challenges in this field of research.

Homemade blenderized tube feeding improves gut microbiome communities in children with enteral nutrition

Enteral nutrition for children is supplied through nasogastric or gastrostomy tubes. Diet not only influences nutritional intake but also interacts with the composition and function of the gut microbiota. Homemade blenderized tube feeding has been administered to children receiving enteral nutrition, in addition to ready-made tube feeding. The purpose of this study was to evaluate the oral/gut microbial communities in children receiving enteral nutrition with or without homemade blenderized tube feeding. Among a total of 30 children, 6 receiving mainly ready-made tube feeding (RTF) and 5 receiving mainly homemade blenderized tube feeding (HBTF) were analyzed in this study. Oral and gut microbiota community profiles were evaluated through 16S rRNA sequencing of saliva and fecal samples. The α-diversity representing the number of observed features, Shannon index, and Chao1 in the gut were significantly increased in HBTF only in the gut microbiome but not in the oral microbiome. In addition, the relative abundances of the phylum Proteobacteria, class Gammaproteobacteria, and genus Escherichia-Shigella were significantly low, whereas that of the genus Ruminococcus was significantly high in the gut of children with HBTF, indicating HBTF altered the gut microbial composition and reducing health risks. Metagenome prediction showed enrichment of carbon fixation pathways in prokaryotes at oral and gut microbiomes in children receiving HBTF. In addition, more complex network structures were observed in the oral cavity and gut in the HBTF group than in the RTF group. In conclusion, HBTF not only provides satisfaction and enjoyment during meals with the family but also alters the gut microbial composition to a healthy state.

Bacterial Diversity on Historical Audio-Visual Materials and in the Atmosphere of Czech Depositories

Microbial contamination in cultural heritage storage facilities is undoubtedly still a huge problem and leads to the biodeterioration of historical objects and thus the loss of information for future generations. Most studies focus on fungi that colonize materials, which are the primary agents of biodeterioration. However, bacteria also play crucial roles in this process. Therefore, this study focuses on identifying bacteria that colonize audio-visual materials and those present in the air in the archives of the Czech Republic. For our purposes, the Illumina MiSeq amplicon sequencing method was used. Using this method, 18 bacterial genera with an abundance of higher than 1% were identified on audio-visual materials and in the air. We also evaluated some factors that were assumed to possibly influence the composition of bacterial communities on audio-visual materials, of which locality was shown to be significant. Locality also explained most of the variability in bacterial community structure. Furthermore, an association between genera colonizing materials and genera present in the air was demonstrated, and indicator genera were evaluated for each locality. IMPORTANCE The existing literature on microbial contamination of audio-visual materials has predominantly used culture-based methods to evaluate contamination and has overlooked the potential impact of environmental factors and material composition on microbial communities. Furthermore, previous studies have mainly focused on contamination by microscopic fungi, neglecting other potentially harmful microorganisms. To address these gaps in knowledge, our study is the first to provide a comprehensive analysis of bacterial communities present on historical audio-visual materials. Our statistical analyses demonstrate the critical importance of including air analysis in such studies, as airborne microorganisms can significantly contribute to the contamination of these materials. The insights gained from this study are not only valuable in developing effective preventive measures to mitigate contamination but also valuable in identifying targeted disinfection methods for specific types of microorganisms. Overall, our findings highlight the need for a more holistic approach to understanding microbial contamination in cultural heritage materials.

Touching the (almost) untouchable: a minimally invasive workflow for microbiological and biomolecular analyses of cultural heritage objects

Microbiological and biomolecular approaches to cultural heritage research have expanded the established research horizon from the prevalent focus on the cultural objects' conservation and human health protection to the relatively recent applications to provenance inquiry and assessment of environmental impacts in a global context of a changing climate. Standard microbiology and molecular biology methods developed for other materials, specimens, and contexts could, in principle, be applied to cultural heritage research. However, given certain characteristics common to several heritage objects-such as uniqueness, fragility, high value, and restricted access, tailored approaches are required. In addition, samples of heritage objects may yield low microbial biomass, rendering them highly susceptible to cross-contamination. Therefore, dedicated methodology addressing these limitations and operational hurdles is needed. Here, we review the main experimental challenges and propose a standardized workflow to study the microbiome of cultural heritage objects, illustrated by the exploration of bacterial taxa. The methodology was developed targeting the challenging side of the spectrum of cultural heritage objects, such as the delicate written record, while retaining flexibility to adapt and/or upscale it to heritage artifacts of a more robust constitution or larger dimensions. We hope this tailored review and workflow will facilitate the interdisciplinary inquiry and interactions among the cultural heritage research community.

Potential role of intratumor bacteria outside the gastrointestinal tract: More than passengers

INTRODUCTION

Tumor-associated bacteria and gut microbiota have gained significant attention in recent years due to their potential role in cancer development and therapeutic response. This review aims to discuss the contributions of intratumor bacteria outside the gastrointestinal tract, in addition to exploring the mechanisms, functions, and implications of these bacteria in cancer therapy.

METHODS

We reviewed current literature on intratumor bacteria and their impact on tumorigenesis, progression, metastasis, drug resistance, and anti-tumor immune modulation. Additionally, we examined techniques used to detect intratumor bacteria, precautions necessary when handling low microbial biomass tumor samples, and the recent progress in bacterial manipulation for tumor treatment.

RESULTS

Research indicates that each type of cancer uniquely interacts with its microbiome, and bacteria can be detected even in non-gastrointestinal tumors with low bacterial abundance. Intracellular bacteria have the potential to regulate tumor cells' biological behavior and contribute to critical aspects of tumor development. Furthermore, bacterial-based anti-tumor therapies have shown promising results in cancer treatment.

CONCLUSIONS

Understanding the complex interactions between intratumor bacteria and tumor cells could lead to the development of more precise cancer treatment strategies. Further research into non-gastrointestinal tumor-associated bacteria is needed to identify new therapeutic approaches and expand our knowledge of the microbiota's role in cancer biology.

RESCUE: a validated Nanopore pipeline to classify bacteria through long-read, 16S-ITS-23S rRNA sequencing

Despite the advent of third-generation sequencing technologies, modern bacterial ecology studies still use Illumina to sequence small (~400 bp) hypervariable regions of the 16S rRNA SSU for phylogenetic classification. By sequencing a larger region of the rRNA gene operons, the limitations and biases of sequencing small portions can be removed, allowing for more accurate classification with deeper taxonomic resolution. With Nanopore sequencing now providing raw simplex reads with quality scores above Q20 using the kit 12 chemistry, the ease, cost, and portability of Nanopore play a leading role in performing differential bacterial abundance analysis. Sequencing the near-entire rrn operon of bacteria and archaea enables the use of the universally conserved operon holding evolutionary polymorphisms for taxonomic resolution. Here, a reproducible and validated pipeline was developed, RRN-operon Enabled Species-level Classification Using EMU (RESCUE), to facilitate the sequencing of bacterial rrn operons and to support import into phyloseq. Benchmarking RESCUE showed that fully processed reads are now parallel or exceed the quality of Sanger, with median quality scores of approximately Q20+, using the R10.4 and Guppy SUP basecalling. The pipeline was validated through two complex mock samples, the use of multiple sample types, with actual Illumina data, and across four databases. RESCUE sequencing is shown to drastically improve classification to the species level for most taxa and resolves erroneous taxa caused by using short reads such as Illumina.

Gut-microbiota in children and adolescents with obesity: inferred functional analysis and machine-learning algorithms to classify microorganisms

The fecal microbiome of 55 obese children and adolescents (BMI-SDS 3.2 ± 0.7) and of 25 normal-weight subjects, matched both for age and sex (BMI-SDS - 0.3 ± 1.1) was analysed. Streptococcus, Acidaminococcus, Sutterella, Prevotella, Sutterella wadsworthensis, Streptococcus thermophilus, and Prevotella copri positively correlated with obesity. The inferred pathways strongly associated with obesity concern the biosynthesis pathways of tyrosine, phenylalanine, tryptophan and methionine pathways. Furthermore, polyamine biosynthesis virulence factors and pro-inflammatory lipopolysaccharide biosynthesis pathway showed higher abundances in obese samples, while the butanediol biosynthesis showed low abundance in obese subjects. Different taxa strongly linked with obesity have been related to an increased risk of multiple diseases involving metabolic pathways related to inflammation (polyamine and lipopolysaccharide biosynthesis). Cholesterol, LDL, and CRP positively correlated with specific clusters of microbial in obese patients. The Firmicutes/Bacteroidetes-ratio was lower in obese samples than in controls and differently from the literature we state that this ratio could not be a biomarker for obesity.

Tomato Plant Microbiota under Conventional and Organic Fertilization Regimes in a Soilless Culture System

Tomato is the main vegetable cultivated under soilless culture systems (SCSs); production of organic tomato under SCSs has increased due to consumer demands for healthier and environmentally friendly vegetables. However, organic tomato production under SCSs has been associated with low crop performance and fruit quality defects. These agricultural deficiencies could be linked to alterations in tomato plant microbiota; nonetheless, this issue has not been sufficiently addressed. Thus, the main goal of the present study was to characterize the rhizosphere and phyllosphere of tomato plants cultivated under conventional and organic SCSs. To accomplish this goal, tomato plants grown in commercial greenhouses under conventional or organic SCSs were tested at 8, 26, and 44 weeks after seedling transplantation. Substrate (n = 24), root (n = 24), and fruit (n = 24) composite samples were subjected to DNA extraction and high-throughput 16S rRNA gene sequencing. The present study revealed that the tomato core microbiota was predominantly constituted by Proteobacteria, Actinobacteria, and Firmicutes. Remarkably, six bacterial families, Bacillaceae, Microbacteriaceae, Nocardioidaceae, Pseudomonadaceae, Rhodobacteraceae, and Sphingomonadaceae, were shared among all substrate, rhizosphere, and fruit samples. Importantly, it was shown that plants under organic SCSs undergo a dysbiosis characterized by significant changes in the relative abundance of Bradyrhizobiaceae, Caulobacteraceae, Chitinophagaceae, Enterobacteriaceae, Erythrobacteraceae, Flavobacteriaceae, Nocardioidaceae, Rhodobacteraceae, and Streptomycetaceae. These results suggest that microbial alterations in substrates, roots, and fruits could be potential factors in contributing to the crop performance and fruit quality deficiencies observed in organic SCSs.

Evaluating the Reproducibility of Amplicon Sequencing Data Derived from Deep-Sea Cold Seep Sediment-Associated Microbiota

Benefiting from the rapid developments and wide applications of high-throughput sequencing, great advancements have been made in investigating microbiota, which are highly diverse and play key roles in both element cycling and the energy flow of ecosystems. There have been inherent limitations of amplicon sequencing that could introduce uncertainty and raise concerns about the accuracy and reproducibility of this technology. However, studies focusing on the reproducibility of amplicon sequencing are limited, especially in characterizing microbial communities in deep-sea sediments. To evaluate reproducibility, 118 deep-sea sediment samples were used for 16S rRNA gene sequencing in technical replicates (repeated measurements of the same sample) that demonstrate the variability of amplicon sequencing. The average occurrence-based overlaps were 35.98% and 27.02% between two and among three technical replicates, respectively, whereas their abundance-based overlaps reached 84.88% and 83.16%, respectively. Although variations of alpha and beta diversity indices were found between/among technical replicates, alpha diversity indices were similar across samples, and the average beta diversity indices were much smaller for technical replicates than among samples. Moreover, clustering methods (i.e., operational taxonomic units [OTUs] and amplicon sequence variants [ASVs]) were shown to have little impact on the alpha and beta diversity patterns of microbial communities. Taken together, although there are variations between/among technical replicates, amplicon sequencing is still a powerful tool with which to reveal diversity patterns of microbiota in deep-sea sediments. IMPORTANCE The reproducibility of amplicon sequencing is vital for whether the diversities of microbial communities could be accurately estimated. Thus, reproducibility influences the drawing of sound ecological conclusions. Nevertheless, few studies have focused on the reproducibility of microbial communities that are characterized by amplicon sequencing, and studies focusing on microbiota in deep-sea sediments have been especially lacking. In this study, we evaluated the reproducibility of amplicon sequencing targeting microbiota in deep-sea sediments of cold seep. Our results revealed that there were variations between/among technical replicates and that amplicon sequencing was still a powerful tool with which to characterize the diversities of microbial communities in deep-sea sediments. This study provides valuable guidelines for the reproducibility evaluation of future work in experimental design and interpretation.

The use of different 16S rRNA gene variable regions in biogeographical studies

16S rRNA gene amplicon sequencing is routinely used in environmental surveys to identify microbial diversity and composition of the samples of interest. The dominant sequencing technology of the past decade (Illumina) is based on the sequencing of 16S rRNA hypervariable regions. Online sequence data repositories, which represent an invaluable resource for investigating microbial distributional patterns across spatial, environmental or temporal scales, contain amplicon datasets from diverse 16S rRNA gene variable regions. However, the utility of these sequence datasets is potentially reduced by the use of different 16S rRNA gene amplified regions. By comparing 10 Antarctic soil samples sequenced for five different 16S rRNA amplicons, we explore whether sequence data derived from diverse 16S rRNA variable regions can be validly used as a resource for biogeographical studies. Patterns of shared and unique taxa differed among samples as a result of variable taxonomic resolutions of the assessed 16S rRNA variable regions. However, our analyses also suggest that the use of multi-primer datasets for biogeographical studies of the domain Bacteria is a valid approach to explore bacterial biogeographical patterns due to the preservation of bacterial taxonomic and diversity patterns across different variable region datasets. We deem composite datasets useful for biogeographical studies.

Microbial Diversity Biased Estimation Caused by Intragenomic Heterogeneity and Interspecific Conservation of 16S rRNA Genes

The 16S rRNA gene has been extensively used as a molecular marker to explore evolutionary relationships and profile microbial composition throughout various environments. Despite its convenience and prevalence, limitations are inevitable. Variable copy numbers, intragenomic heterogeneity, and low taxonomic resolution have caused biases in estimating microbial diversity. Here, analysis of 24,248 complete prokaryotic genomes indicated that the 16S rRNA gene copy number ranged from 1 to 37 in bacteria and 1 to 5 in archaea, and intragenomic heterogeneity was observed in 60% of prokaryotic genomes, most of which were below 1%. The overestimation of microbial diversity caused by intragenomic variation and the underestimation introduced by interspecific conservation were calculated when using full-length or partial 16S rRNA genes. Results showed that, at the 100% threshold, microbial diversity could be overestimated by as much as 156.5% when using the full-length gene. The V4 to V5 region-based analyses introduced the lowest overestimation rate (4.4%) but exhibited slightly lower species resolution than other variable regions under the 97% threshold. For different variable regions, appropriate thresholds rather than the canonical value 97% were proposed for minimizing the risk of splitting a single genome into multiple clusters and lumping together different species into the same cluster. This study has not only updated the 16S rRNA gene copy number and intragenomic variation information for the currently available prokaryotic genomes, but also elucidated the biases in estimating prokaryotic diversity with quantitative data, providing references for choosing amplified regions and clustering thresholds in microbial community surveys. IMPORTANCE Microbial diversity is typically analyzed using marker gene-based methods, of which 16S rRNA gene sequencing is the most widely used approach. However, obtaining an accurate estimation of microbial diversity remains a challenge, due to the intragenomic variation and low taxonomic resolution of 16S rRNA genes. Comprehensive examination of the bias in estimating such prokaryotic diversity using 16S rRNA genes within ever-increasing prokaryotic genomes highlights the importance of the choice of sequencing regions and clustering thresholds based on the specific research objectives.

The Role of Gut Microbiota in the Clinical Outcome of Septic Patients: State of the Art and Future Perspectives

Sepsis is a life-threatening multiple-organ dysfunction caused by a dysregulated host response to infection, with high mortality worldwide; 11 million deaths per year are attributable to sepsis in high-income countries. Several research groups have reported that septic patients display a dysbiotic gut microbiota, often related to high mortality. Based on current knowledge, in this narrative review, we revised original articles, clinical trials, and pilot studies to evaluate the beneficial effect of gut microbiota manipulation in clinical practice, starting from an early diagnosis of sepsis and an in-depth analysis of gut microbiota.

Lacticaseibacillus rhamnosus Strain GG (LGG) Regulate Gut Microbial Metabolites, an In Vitro Study Using Three Mature Human Gut Microbial Cultures in a Simulator of Human Intestinal Microbial Ecosystem (SHIME)

In the present research, we investigated changes in the gut metabolome that occurred in response to the administration of the Laticaseibacillus rhamnosus strain GG (LGG). The probiotics were added to the ascending colon region of mature microbial communities established in a human intestinal microbial ecosystem simulator. Shotgun metagenomic sequencing and metabolome analysis suggested that the changes in microbial community composition corresponded with changes to metabolic output, and we can infer linkages between some metabolites and microorganisms. The in vitro method permits a spatially-resolved view of metabolic transformations under human physiological conditions. By this method, we found that tryptophan and tyrosine were mainly produced in the ascending colon region, while their derivatives were detected in the transverse and descending regions, revealing sequential amino acid metabolic pathways along with the colonic tract. The addition of LGG appeared to promote the production of indole propionic acid, which is positively associated with human health. Furthermore, the microbial community responsible for the production of indole propionic acid may be broader than is currently known.

Selecting 16S rRNA Primers for Microbiome Analysis in a Host-Microbe System: The Case of the Jellyfish Rhopilema nomadica

Amplicon sequencing of the 16S rRNA gene is extensively used to characterize bacterial communities, including those living in association with eukaryotic hosts. Deciding which region of the 16S rRNA gene to analyze and selecting the appropriate PCR primers remains a major decision when initiating any new microbiome study. Based on a detailed literature survey of studies focusing on cnidarian microbiomes, we compared three commonly used primers targeting different hypervariable regions of the 16S rRNA gene, V1V2, V3V4, and V4V5, using the jellyfish Rhopilema nomadica as a model. Although all primers exhibit a similar pattern in bacterial community composition, the performance of the V3V4 primer set was superior to V1V2 and V4V5. The V1V2 primers misclassified bacteria from the Bacilli class and exhibited low classification resolution for Rickettsiales, which represent the second most abundant 16S rRNA gene sequence in all the primers. The V4V5 primer set detected almost the same community composition as the V3V4, but the ability of these primers to also amplify the eukaryotic 18S rRNA gene may hinder bacterial community observations. However, after overcoming the challenges possessed by each one of those primers, we found that all three of them show very similar bacterial community dynamics and compositions. Nevertheless, based on our results, we propose that the V3V4 primer set is potentially the most suitable for studying jellyfish-associated bacterial communities. Our results suggest that, at least for jellyfish samples, it may be feasible to directly compare microbial community estimates from different studies, each using different primers but otherwise similar experimental protocols. More generally, we recommend specifically testing different primers for each new organism or system as a prelude to large-scale 16S rRNA gene amplicon analyses, especially of previously unstudied host-microbe associations.

The Microbial Genetic Diversity and Succession Associated with Processing Waters at Different Broiler Processing Stages in an Abattoir in Australia

The high organic content of abattoir-associated process water provides an alternative for low-cost and non-invasive sample collection. This study investigated the association of microbial diversity from an abattoir processing environment with that of chicken meat. Water samples from scalders, defeathering, evisceration, carcass-washer, chillers, and post-chill carcass rinsate were collected from a large-scale abattoir in Australia. DNA was extracted using the Wizard^® Genomic DNA Purification Kit, and the 16S rRNA v3-v4 gene region was sequenced using Illumina MiSeq. The results revealed that the Firmicutes decreased from scalding to evisceration (72.55%) and increased with chilling (23.47%), with the Proteobacteria and Bacteroidota changing inversely. A diverse bacterial community with 24 phyla and 392 genera was recovered from the post-chill chicken, with Anoxybacillus (71.84%), Megamonas (4.18%), Gallibacterium (2.14%), Unclassified Lachnospiraceae (1.87%), and Lactobacillus (1.80%) being the abundant genera. The alpha diversity increased from scalding to chilling, while the beta diversity revealed a significant separation of clusters at different processing points (p = 0.01). The alpha- and beta-diversity revealed significant contamination during the defeathering, with a redistribution of the bacteria during the chilling. This study concluded that the genetic diversity during the defeathering is strongly associated with the extent of the post-chill contamination, and may be used to indicate the microbial quality of the chicken meat.

Protocol for microbiota analysis of a murine stroke model

Investigations on the microbiota in neurological diseases such as stroke are increasingly common; however, stroke researchers may have limited experience with designing such studies. Here, we describe a protocol to conduct a stroke microbiota study in mice, from experimental stroke surgery and sample collection to data analysis. We provide details on sample processing and sequencing and provide a reproducible data analysis pipeline. In doing so, we hope to enable researchers to conduct robust studies and facilitate identification of stroke-associated microbial signatures. For complete details on the use and execution of this protocol, please refer to Sorbie et al. (2022).1.

Periodontal treatment and microbiome-targeted therapy in management of periodontitis-related nonalcoholic fatty liver disease with oral and gut dysbiosis

A growing body of evidence from multiple areas proposes that periodontal disease, accompanied by oral inflammation and pathological changes in the microbiome, induces gut dysbiosis and is involved in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). A subgroup of NAFLD patients have a severely progressive form, namely nonalcoholic steatohepatitis (NASH), which is characterized by histological findings that include inflammatory cell infiltration and fibrosis. NASH has a high risk of further progression to cirrhosis and hepatocellular carcinoma. The oral microbiota may serve as an endogenous reservoir for gut microbiota, and transport of oral bacteria through the gastro-intestinal tract can set up a gut microbiome dysbiosis. Gut dysbiosis increases the production of potential hepatotoxins, including lipopolysaccharide, ethanol, and other volatile organic compounds such as acetone, phenol and cyclopentane. Moreover, gut dysbiosis increases intestinal permeability by disrupting tight junctions in the intestinal wall, leading to enhanced translocation of these hepatotoxins and enteric bacteria into the liver through the portal circulation. In particular, many animal studies support that oral administration of Porphyromonas gingivalis, a typical periodontopathic bacterium, induces disturbances in glycolipid metabolism and inflammation in the liver with gut dysbiosis. NAFLD, also known as the hepatic phenotype of metabolic syndrome, is strongly associated with metabolic complications, such as obesity and diabetes. Periodontal disease also has a bidirectional relationship with metabolic syndrome, and both diseases may induce oral and gut microbiome dysbiosis with insulin resistance and systemic chronic inflammation cooperatively. In this review, we will describe the link between periodontal disease and NAFLD with a focus on basic, epidemiological, and clinical studies, and discuss potential mechanisms linking the two diseases and possible therapeutic approaches focused on the microbiome. In conclusion, it is presumed that the pathogenesis of NAFLD involves a complex crosstalk between periodontal disease, gut microbiota, and metabolic syndrome. Thus, the conventional periodontal treatment and novel microbiome-targeted therapies that include probiotics, prebiotics and bacteriocins would hold great promise for preventing the onset and progression of NAFLD and subsequent complications in patients with periodontal disease.

Are neuromodulation interventions associated with changes in the gut microbiota? A systematic review

The microbiota-gut-brain axis (MGBA) refers to the bidirectional communication between the brain and the gut microbiota and recent studies have linked the MGBA to health and disease. Research has so far investigated this axis mainly from microbiota to brain but less is known about the other direction. One approach to examine the MGBA from brain to microbiota is through understanding if and how neuromodulation might impact microbiota. Neuromodulation encompasses a wide range of stimulation techniques and is used to treat neurological, psychiatric and metabolic disorders, like Parkinson's Disease, depression and obesity. Here, we performed a systematic review to investigate whether neuromodulation is associated with subsequent changes in the gut microbiota. Searches in PsycINFO and MEDLINE were performed up to March 2022. Included studies needed to be clinical or preclinical studies comparing the effects of deep brain stimulation, electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation or vagal nerve stimulation on the gut microbiota before and after treatment or between active and control groups. Seven studies were identified. Neuromodulation was associated with changes in relative bacterial abundances, but not with (changes in) α-diversity or β-diversity. Summarizing, currently reported findings suggest that neuromodulation interventions are associated with moderate changes in the gut microbiome. However, findings remain inconclusive due to the limited number and varying quality of included studies, as well as the large heterogeneity between studies. More research is required to more conclusively establish whether, and if so, via which mechanism(s) of action neuromodulation interventions might influence the gut microbiota.

The Development of the Bacterial Community of Brown Trout (Salmo trutta) during Ontogeny

Brown trout (Salmo trutta) is an important aquaculture species in Germany, but its production faces challenges due to global warming and a high embryo mortality. Climate factors might influence the fish's bacterial community (BC) and thus increase embryo mortality. Yet, knowledge of the physiological BC during ontogeny in general is scarce. In this project, the BC of brown trout has been investigated in a period from unfertilized egg to 95 days post fertilization (dpf) using 16S rRNA gene amplicon sequencing. Developmental changes differed between early and late ontogeny and major differences in BC occurred especially during early developmental stages. Thus, analysis was conducted separately for 0 to 67 dpf and from 67 to 95 dpf. All analyzed stages were sampled in toto to avoid bias due to different sampling methods in different developmental stages. The most abundant phylum in the BC of all developmental stages was Pseudomonadota, while only two families (Comamonadaceae and Moraxellaceae) occurred in all developmental stages. The early developmental stages until 67 dpf displayed greater shifts in their BC regarding bacterial richness, microbial diversity, and taxonomic composition. Thereafter, in the fry stages, the BC seemed to stabilize and changes were moderate. In future studies, a reduction in the sampling time frames during early development, an increase in sampling numbers, and an attempt for biological reproduction in order to characterize the causes of these variations is recommended.

Revealing the Tick Microbiome: Insights into Midgut and Salivary Gland Microbiota of Female Ixodes ricinus Ticks

The ectoparasite Ixodes ricinus is an important vector for many tick-borne diseases (TBD) in the northern hemisphere, such as Lyme borreliosis, rickettsiosis, human granulocytic anaplasmosis, or tick-borne encephalitis virus. As climate change will lead to rising temperatures in the next years, we expect an increase in tick activity, tick population, and thus in the spread of TBD. Consequently, it has never been more critical to understand relationships within the microbial communities in ticks that might contribute to the tick's fitness and the occurrence of TBD. Therefore, we analyzed the microbiota in different tick tissues such as midgut, salivary glands, and residual tick material, as well as the microbiota in complete Ixodes ricinus ticks using 16S rRNA gene amplicon sequencing. By using a newly developed DNA extraction protocol for tick tissue samples and a self-designed mock community, we were able to detect endosymbionts and pathogens that have been described in the literature previously. Further, this study displayed the usefulness of including a mock community during bioinformatic analysis to identify essential bacteria within the tick.

Bioinformatic Approaches for Describing the Oral Microbiota

Cultivation-independent (molecular) analysis of the oral microbiota can provide a comprehensive picture of microbial community composition, yet there is an at-times bewildering array of approaches that can be employed. This chapter introduces some of the key considerations when undertaking microbiota research and describes two alternative bioinformatic pipelines for conducting such studies. The descriptions are based on analysis of bacterial 16S ribosomal RNA gene sequences, but can be easily adapted for analysis of other microbial taxa such as fungi.

Noninvasive Fecal Cytokine and Microbiota Profiles Predict Commencement of Necrotizing Enterocolitis in a Proof-of-Concept Study

Background and Aims

Necrotizing enterocolitis (NEC) is a life-threatening disease and the most common gastrointestinal emergency in premature infants. Accurate early diagnosis is challenging. Modified Bell's staging is routinely used to guide diagnosis, but early diagnostic signs are nonspecific, potentially leading to unobserved disease progression, which is problematic given the often rapid deterioration observed. We investigated fecal cytokine levels, coupled with gut microbiota profiles, as a noninvasive method to discover specific NEC-associated signatures that can be applied as potential diagnostic markers.

Methods

Premature babies born below 32 weeks of gestation were admitted to the 2-site neonatal intensive care unit (NICU) of Imperial College hospitals (St. Mary's or Queen Charlotte's & Chelsea) between January 2011 and December 2012. During the NICU stay, expert neonatologists grouped individuals by modified Bell's staging (healthy, NEC1, NEC2/3) and fecal samples from diapers were collected consecutively. Microbiota profiles were assessed by 16S rRNA gene amplicon sequencing and cytokine concentrations were measured by V-Plex multiplex assays.

Results

Early evaluation of microbiota profiles revealed only minor differences. However, at later time points, significant changes in microbiota composition were observed for Bacillota (adj. P = .0396), with Enterococcus being the least abundant in Bell stage 2/3 NEC. Evaluation of fecal cytokine levels revealed significantly higher concentrations of IL-1α (P = .045), IL-5 (P = .0074), and IL-10 (P = .032) in Bell stage 1 NEC compared to healthy individuals.

Conclusion

Differences in certain fecal cytokine profiles in patients with NEC indicate their potential use as diagnostic biomarkers to facilitate earlier diagnosis. Additionally, associations between microbial and cytokine profiles contribute to improving knowledge about NEC pathogenesis.

Amplicon Sequencing Pipelines in Metagenomics

Taxonomic profiling among a large number of samples is a fundamental task during amplicon sequencing analysis. The heterogeneity and technical noises in the sample handling, library preparation, and sequencing present a major challenge to how the biological conclusions are drawn from the data analysis, and accordingly, many tools have been developed to address specific issues related to each step of the data analysis. Nowadays, several sophisticated computational pipelines with flexible parameters are made available to provide one-stop comprehensive solutions by integrating various tools, which significantly mitigate the burden imposed by the complexity of the metagenomics data analysis. This chapter discusses the best practices related to the data generation and describes bioinformatics approaches to achieving greater accuracy from data processing. It offers two independent stepwise pipelines using mothur and DADA2 in a parallel way, presents the basic principles in the key steps of the analysis, and enables the comparisons between the two pipelines straightforwardly.

Perspective: Human Milk Composition and Related Data for National Health and Nutrition Monitoring and Related Research

National health and nutrition monitoring is an important federal effort in the United States and Canada, and the basis for many of their nutrition and health policies. Understanding of child exposures through human milk (HM) remains out of reach due to lack of current and representative data on HM's composition and intake volume. This article provides an overview of the current national health and nutrition monitoring activities for HM-fed children, HM composition (HMC) and volume data used for exposure assessment, categories of potential measures in HM, and associated variability factors. In this Perspective, we advocate for a framework for collection and reporting of HMC data for national health and nutrition monitoring and programmatic needs, including a shared vision for a publicly available Human Milk Composition Data Repository (HMCD-R) to include essential metadata associated with HMC. HMCD-R can provide a central, integrated platform for researchers and public health officials for compiling, evaluating, and sharing HMC data. The compiled compositional and metadata in HMCD-R would provide pertinent measures of central tendency and variability and allow use of modeling techniques to approximate compositional profiles for subgroups, providing more accurate exposure assessments for purposes of monitoring and surveillance. HMC and related metadata could facilitate understanding the complexity and variability of HM composition, provide crucial data for assessment of infant and maternal nutritional needs, and inform public health policies, food and nutrition programs, and clinical practice guidelines.

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.

Comparison of Metagenomics and Metatranscriptomics Tools: A Guide to Making the Right Choice

The study of microorganisms is a field of great interest due to their environmental (e.g., soil contamination) and biomedical (e.g., parasitic diseases, autism) importance. The advent of revolutionary next-generation sequencing techniques, and their application to the hypervariable regions of the 16S, 18S or 23S ribosomal subunits, have allowed the research of a large variety of organisms more in-depth, including bacteria, archaea, eukaryotes and fungi. Additionally, together with the development of analysis software, the creation of specific databases (e.g., SILVA or RDP) has boosted the enormous growth of these studies. As the cost of sequencing per sample has continuously decreased, new protocols have also emerged, such as shotgun sequencing, which allows the profiling of all taxonomic domains in a sample. The sequencing of hypervariable regions and shotgun sequencing are technologies that enable the taxonomic classification of microorganisms from the DNA present in microbial communities. However, they are not capable of measuring what is actively expressed. Conversely, we advocate that metatranscriptomics is a "new" technology that makes the identification of the mRNAs of a microbial community possible, quantifying gene expression levels and active biological pathways. Furthermore, it can be also used to characterise symbiotic interactions between the host and its microbiome. In this manuscript, we examine the three technologies above, and discuss the implementation of different software and databases, which greatly impact the obtaining of reliable results. Finally, we have developed two easy-to-use pipelines leveraging Nextflow technology. These aim to provide everything required for an average user to perform a metagenomic analysis of marker genes with QIMME2 and a metatranscriptomic study using Kraken2/Bracken.