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

Comparison of the full-length sequence and sub-regions of 16S rRNA gene for skin microbiome profiling

The skin microbiome plays a pivotal role in human health by providing protective and functional benefits. Furthermore, its inherent stability and individual specificity present novel forensic applications. These aspects have sparked considerable research enthusiasm among scholars across various fields. However, the selection of specific 16S rRNA hypervariable regions for skin microbiome studies is not standardized and should be validated through extensive research tailored to different research objectives and targeted bacterial taxa. Notably, third-generation sequencing (TGS) technology leverages the full discriminatory power of the 16S gene and enables more detailed and accurate microbial community analyses. Here, we conducted full-length 16S sequencing of 141 skin microbiota samples from multiple human anatomical sites using the PacBio platform. Based on this data, we generated derived 16S sub-region data through an in silico experiment. Comparisons between the 16S full-length and the derived variable region data revealed that the former can provide superior taxonomic resolution. However, even with full 16S gene sequencing, limitations arise in achieving 100% taxonomic resolution at the species level for skin samples. Additionally, the capability to resolve high-abundance bacteria (TOP30) at the genus level remains generally consistent across different 16S variable regions. Furthermore, the V1-V3 region offers a resolution comparable with that of full-length 16S sequences, in comparison to other hypervariable regions studied. In summary, while acknowledging the benefits of full-length 16S gene analysis, we propose the targeting of specific sub-regions as a practical choice for skin microbial research, especially when balancing the accuracy of taxonomic classification with limited sequencing resources, such as the availability of only short-read sequencing or insufficient DNA.IMPORTANCESkin acts as the primary barrier to human health. Considering the different microenvironments, microbial research should be conducted separately for different skin regions. Third-generation sequencing (TGS) technology can make full use of the discriminatory power of the full-length 16S gene. However, 16S sub-regions are widely used, particularly when faced with limited sequencing resources including the availability of only short-read sequencing and insufficient DNA. Comparing the 16S full-length and the derived variable region data from five different human skin sites, we confirmed the superiority of the V1-V3 region in skin microbiota analysis. We propose the targeting of specific sub-regions as a practical choice for microbial research.

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status

Background

Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity.

Methods

In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea.

Results

The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique.

Conclusion

These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

Fecal microbiota transplantation: current challenges and future landscapes

SUMMARYGiven the importance of gut microbial homeostasis in maintaining health, there has been considerable interest in developing innovative therapeutic strategies for restoring gut microbiota. One such approach, fecal microbiota transplantation (FMT), is the main "whole gut microbiome replacement" strategy and has been integrated into clinical practice guidelines for treating recurrent Clostridioides difficile infection (rCDI). Furthermore, the potential application of FMT in other indications such as inflammatory bowel disease (IBD), metabolic syndrome, and solid tumor malignancies is an area of intense interest and active research. However, the complex and variable nature of FMT makes it challenging to address its precise functionality and to assess clinical efficacy and safety in different disease contexts. In this review, we outline clinical applications, efficacy, durability, and safety of FMT and provide a comprehensive assessment of its procedural and administration aspects. The clinical applications of FMT in children and cancer immunotherapy are also described. We focus on data from human studies in IBD in contrast with rCDI to delineate the putative mechanisms of this treatment in IBD as a model, including colonization resistance and functional restoration through bacterial engraftment, modulating effects of virome/phageome, gut metabolome and host interactions, and immunoregulatory actions of FMT. Furthermore, we comprehensively review omics technologies, metagenomic approaches, and bioinformatics pipelines to characterize complex microbial communities and discuss their limitations. FMT regulatory challenges, ethical considerations, and pharmacomicrobiomics are also highlighted to shed light on future development of tailored microbiome-based therapeutics.

Quantifying variation across 16S rRNA gene sequencing runs in human microbiome studies

Recent microbiome research has incorporated a higher number of samples through more participants in a study, longitudinal studies, and metanalysis between studies. Physical limitations in a sequencing machine can result in samples spread across sequencing runs. Here we present the results of sequencing nearly 1000 16S rRNA gene sequences in fecal (stabilized and swab) and oral (swab) samples from multiple human microbiome studies and positive controls that were conducted with identical standard operating procedures. Sequencing was performed in the same center across 18 different runs. The simplified mock community showed limitations in accuracy, while precision (e.g., technical variation) was robust for the mock community and actual human positive control samples. Technical variation was the lowest for stabilized fecal samples, followed by fecal swab samples, and then oral swab samples. The order of technical variation stability was inverse of DNA concentrations (e.g., highest in stabilized fecal samples), highlighting the importance of DNA concentration in reproducibility and urging caution when analyzing low biomass samples. Coefficients of variation at the genus level also followed the same trend for lower variation with higher DNA concentrations. Technical variation across both sample types and the two human sampling locations was significantly less than the observed biological variation. Overall, this research providing comparisons between technical and biological variation, highlights the importance of using positive controls, and provides semi-quantified data to better understand variation introduced by sequencing runs. KEY POINTS: • Mock community and positive control accuracy were lower than precision. • Samples with lower DNA concentration had increased technical variation across sequencing runs. • Biological variation was significantly higher than technical variation due to sequencing runs.

Interpretable machine learning decodes soil microbiome's response to drought stress

BACKGROUND

Extreme weather events induced by climate change, particularly droughts, have detrimental consequences for crop yields and food security. Concurrently, these conditions provoke substantial changes in the soil bacterial microbiota and affect plant health. Early recognition of soil affected by drought enables farmers to implement appropriate agricultural management practices. In this context, interpretable machine learning holds immense potential for drought stress classification of soil based on marker taxa.

RESULTS

This study demonstrates that the 16S rRNA-based metagenomic approach of Differential Abundance Analysis methods and machine learning-based Shapley Additive Explanation values provide similar information. They exhibit their potential as complementary approaches for identifying marker taxa and investigating their enrichment or depletion under drought stress in grass lineages. Additionally, the Random Forest Classifier trained on a diverse range of relative abundance data from the soil bacterial micobiome of various plant species achieves a high accuracy of 92.3 % at the genus rank for drought stress prediction. It demonstrates its generalization capacity for the lineages tested.

CONCLUSIONS

In the detection of drought stress in soil bacterial microbiota, this study emphasizes the potential of an optimized and generalized location-based ML classifier. By identifying marker taxa, this approach holds promising implications for microbe-assisted plant breeding programs and contributes to the development of sustainable agriculture practices. These findings are crucial for preserving global food security in the face of climate change.

Exploring the potential of Bacillus for crop productivity and sustainable solution for combating rice false smut disease

Rice false smut, which is caused by the soil-borne fungal pathogen Ustilaginoidea virens (U. virens), is one of the most threatening diseases in most of the rice-growing countries including India that causes 0.5-75% yield loss, low seed germination, and a reduction in seed quality. The assessment of yield loss helps to understand the relevance of disease severity and facilitates the implementation of appropriate management strategies. This study aimed to mitigate biotic stress in rice by employing a rhizobacterial-based bioformulation, which possesses diverse capabilities as both a plant growth promoter and a biocontrol agent against U. virens. Rhizobacteria were isolated from the soil of the rice rhizospheres from the healthy plant of the false smut affected zone. Furthermore, they were identified as Bacillus strains: B. subtilis (BR_4), B. licheniformis (BU_7), B. licheniformis (BU_8), and B. vallismortis (KU_7) via sequencing. Isolates were screened for their biocontrol potential against U. virens under in vitro conditions. The antagonistic study revealed that B. vallismortis (KU_7) inhibited U. virens the most (44.6%), followed by B. subtilis BR_4 (41.4%), B. licheniformis BU_7 (39.8%), and B. licheniformis BU_8 (43.5%). Various biochemical and plant growth promoting attributes, such as phosphate and Zn solubilization, IAA, ammonium, siderophore, and chitinase production, were also investigated for all the selected isolates. Furthermore, the potential of the isolates was tested in both in vitro and field conditions by employing talc-based bioformulation through bio-priming and root treatment. The application of bioformulation revealed a 20% decrease in disease incidence in plants treated with B. vallismortis (KU_7), a 60.5% increase in the biological yield, and a 45% increase in the grain yield. This eco-friendly approach not only controlled the disease but also improved the grain quality and reduced the chaffiness.

Global soil metagenomics reveals distribution and predominance of Deltaproteobacteria in nitrogen-fixing microbiome

BACKGROUND

Biological nitrogen fixation is a fundamental process sustaining all life on earth. While distribution and diversity of N2-fixing soil microbes have been investigated by numerous PCR amplicon sequencing of nitrogenase genes, their comprehensive understanding has been hindered by lack of de facto standard protocols for amplicon surveys and possible PCR biases. Here, by fully leveraging the planetary collections of soil shotgun metagenomes along with recently expanded culture collections, we evaluated the global distribution and diversity of terrestrial diazotrophic microbiome.

RESULTS

After the extensive analysis of 1,451 soil metagenomic samples, we revealed that the Anaeromyxobacteraceae and Geobacteraceae within Deltaproteobacteria are ubiquitous groups of diazotrophic microbiome in the soils with different geographic origins and land usage types, with particular predominance in anaerobic soils (paddy soils and sediments).

CONCLUSION

Our results indicate that Deltaproteobacteria is a core bacterial taxon in the potential soil nitrogen fixation population, especially in anaerobic environments, which encourages a careful consideration on deltaproteobacterial diazotrophs in understanding terrestrial nitrogen cycling. Video Abstract.

Estuarine mangrove niches select cultivable heterotrophic diazotrophs with diverse metabolic potentials-a prospective cross-dialog for functional diazotrophy

Introduction

Biological nitrogen fixation (BNF), an unparalleled metabolic novelty among living microorganisms on earth, globally contributes ~88-101 Tg N year-1 to natural ecosystems, ~56% sourced from symbiotic BNF while ~22-45% derived from free-living nitrogen fixers (FLNF). The success of symbiotic BNF is largely dependent on its interaction with host-plant, however ubiquitous environmental heterotrophic FLNFs face many limitations in their immediate ecological niches to sustain unhindered BNF. The autotrophic FLNFs like cyanobacteria and oceanic heterotrophic diazotrophs have been well studied about their contrivances acclimated/adapted by these organisms to outwit the environmental constraints for functional diazotrophy. However, FLNF heterotrophs face more adversity in executing BNF under stressful estuarine/marine/aquatic habitats.

Methods

In this study a large-scale cultivation-dependent investigation was accomplished with 190 NCBI accessioned and 45 non-accessioned heterotrophic FLNF cultivable bacterial isolates (total 235) from halophilic estuarine intertidal mangrove niches of Indian Sundarbans, a Ramsar site and UNESCO proclaimed World Heritage Site. Assuming ~1% culturability of the microbial community, the respective niches were also studied for representing actual bacterial diversity via cultivation-independent next-generation sequencing of V3-V4 rRNA regions.

Results

Both the studies revealed a higher abundance of culturable Gammaproteobacteria followed by Firmicutes, the majority of 235 FLNFs studied belonging to these two classes. The FLNFs displayed comparable selection potential in media for free nitrogen fixers and iron-oxidizing bacteria, linking diazotrophy with iron oxidation, siderophore production, phosphorus solubilization, phosphorus uptake and accumulation as well as denitrification.

Discussion

This observation validated the hypothesis that under extreme estuarine mangrove niches, diazotrophs are naturally selected as a specialized multidimensional entity, to expedite BNF and survive. Earlier metagenome data from mangrove niches demonstrated a microbial metabolic coupling among C, N, P, S, and Fe cycling in mangrove sediments, as an adaptive trait, evident with the co-abundant respective functional genes, which corroborates our findings in cultivation mode for multiple interrelated metabolic potential facilitating BNF in a challenging intertidal mangrove environment.

Research progress in isolation and identification of rumen probiotics

With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.

The effects of time-restricted eating and Ramadan fasting on gut microbiota composition: a systematic review of human and animal studies

CONTEXT

It is well known that the microbiome undergoes cyclical diurnal rhythms. It has thus been hypothesized that meal timing may affect gut microbial composition, function, and host health.

OBJECTIVE

This review aims to examine the effects of time-restricted eating (TRE) and Ramadan fasting (RF) on the composition of the gut microbiota in animal and human studies. The associations between composition of microbiota and host metabolic parameters are also examined.

DATA SOURCES

A search was performed on the PubMed, Cochrane, Scopus, and Web of Science databases up to December 31, 2022. The search strategy was performed using the Medical Subject Heading (MeSH) terms "intermittent fasting" and "gastrointestinal microbiome" and the key words "Ramadan fasting" and "microbes."

DATA EXTRACTION

Seven human studies (4 TRE and 3 RF) and 9 animal studies (7 TRE, 2 RF-like) were retrieved.

DATA ANALYSIS

TRE and RF in human studies lead to an increase in gut microbial community alpha-diversity. In animal studies (both TRE and RF-like), fasting is not associated with improved alpha-diversity, but enhancement of microbial fluctuation is observed, compared with high-fat diet ad libitum groups. Within Firmicutes and Bacteroidetes phyla, no specific direction of changes resulting from fasting are observed in both animals and human. After TRE or RF, a greater abundance of the Faecalibacterium genus is observed in human studies; changes in Lactobacillus abundance are found in animal studies; and increases in Akkermansia are seen both in humans and in animals fed a feed-pellet diet. Only 2 human studies show a beneficial correlation between microbiota changes and host metabolic (HDL cholesterol) or anthropometric parameters (body mass index).

CONCLUSIONS

These findings support the importance of both regimens in improving the gut microbiota composition. However, based on results of animal studies, it can be suggested that diet remains the essential factor in forming the microbiota's environment.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021278918.

Synthesis of recovery patterns in microbial communities across environments

BACKGROUND

Disturbances alter the diversity and composition of microbial communities. Yet a generalized empirical assessment of microbiome responses to disturbance across different environments is needed to understand the factors driving microbiome recovery, and the role of the environment in driving these patterns.

RESULTS

To this end, we combined null models with Bayesian generalized linear models to examine 86 time series of disturbed mammalian, aquatic, and soil microbiomes up to 50 days following disturbance. Overall, disturbances had the strongest effect on mammalian microbiomes, which lost taxa and later recovered their richness, but not their composition. In contrast, following disturbance, aquatic microbiomes tended away from their pre-disturbance composition over time. Surprisingly, across all environments, we found no evidence of increased compositional dispersion (i.e., variance) following disturbance, in contrast to the expectations of the Anna Karenina Principle.

CONCLUSIONS

This is the first study to systematically compare secondary successional dynamics across disturbed microbiomes, using a consistent temporal scale and modeling approach. Our findings show that the recovery of microbiomes is environment-specific, and helps to reconcile existing, environment-specific research into a unified perspective. Video Abstract.

Current Trends and Challenges of Microbiome Research in Prostate Cancer

PURPOSE OF REVIEW

The role of the gut microbiome in prostate cancer is an emerging area of research interest. However, no single causative organism has yet been identified. The goal of this paper is to examine the role of the microbiome in prostate cancer and summarize the challenges relating to methodology in specimen collection, sequencing technology, and interpretation of results.

RECENT FINDINGS

Significant heterogeneity still exists in methodology for stool sampling/storage, preservative options, DNA extraction, and sequencing database selection/in silico processing. Debate persists over primer choice in amplicon sequencing as well as optimal methods for data normalization. Statistical methods for longitudinal microbiome analysis continue to undergo refinement. While standardization of methodology may help yield more consistent results for organism identification in prostate cancer, this is a difficult task due to considerable procedural variation at each step in the process. Further reproducibility and methodology research is required.

The Role of the Gut Microbiome in Health and Disease in the Elderly

PURPOSE OF REVIEW

Growing evidence supports the contribution of age in the composition and function of the gut microbiome, with specific findings associated with health in old age and longevity.

RECENT FINDINGS

Current studies have associated certain microbiota, such as Butyricimonas, Akkermansia, and Odoribacter, with healthy aging and the ability to survive into extreme old age. Furthermore, emerging clinical and pre-clinical research have shown promising mechanisms for restoring a healthy microbiome in elderly populations through various interventions such as fecal microbiota transplant (FMT), dietary interventions, and exercise programs. Despite several conceptually exciting interventional studies, the field of microbiome research in the elderly remains limited. Specifically, large longitudinal studies are needed to better understand causative relationships between the microbiome and healthy aging. Additionally, individualized approaches to microbiome interventions based on patients' co-morbidities and the underlying functional capacity of their microbiomes are needed to achieve optimal results.

Comparison of treatment performance and microbial community evolution of typical dye wastewater by different combined processes

The degradation of typical dye wastewater is a focus of research in the printing and dyeing industry. In this study, a combined micro-electrolysis and microbial treatment method was established to treat refractory dye wastewater, and the pivotal factors in the microbial treatment were optimized. In the series and coupled modes, the removal rates of chroma reached 98.75% and 92.50%, and the removal rates of chemical oxygen demand (COD) reached 96.17% and 82.29%, respectively. The high-throughput sequencing results showed that the microbial communities in the microbial system varied at different treatment stages. From the culture stage to the domestication stage, the dominant phylum was Proteobacteria; however, the community abundance of microorganisms decreased. A combination of micro-electrolysis and biological methods can alter the characteristics of the microbial community, increase the number of dominant phyla, and increase the abundance of microorganisms. The degradation effect of the series mode and the overall strengthening effect of micro-electrolysis on the microorganisms were better than those of the coupled mode. In actual wastewater, the maximum removal rates of chroma, COD, total nitrogen (TN), ammonia nitrogen (NH3-N), and total phosphorus (TP) are 97.50%, 98.90%, 94.35%, 93.95%, and 91.17%, respectively. Three-dimensional fluorescence spectrum analysis showed that microbial processes could significantly degrade fluorescent components in wastewater, and methanogenic active enzymes in anaerobic processes could continue to react. The combined process can realize the efficient treatment of toxic dye wastewater by reducing the toxicity of wastewater and efficiently degrading organic matter, which has important guiding significance for the treatment of refractory dye wastewater.

Saliva sampling method influences oral microbiome composition and taxa distribution associated with oral diseases

Saliva is a readily accessible and inexpensive biological specimen that enables investigation of the oral microbiome, which can serve as a biomarker of oral and systemic health. There are two routine approaches to collect saliva, stimulated and unstimulated; however, there is no consensus on how sampling method influences oral microbiome metrics. In this study, we analyzed paired saliva samples (unstimulated and stimulated) from 88 individuals, aged 7-18 years. Using 16S rRNA gene sequencing, we investigated the differences in bacterial microbiome composition between sample types and determined how sampling method affects the distribution of taxa associated with untreated dental caries and gingivitis. Our analyses indicated significant differences in microbiome composition between the sample types. Both sampling methods were able to detect significant differences in microbiome composition between healthy subjects and subjects with untreated caries. However, only stimulated saliva revealed a significant association between microbiome diversity and composition in individuals with diagnosed gingivitis. Furthermore, taxa previously associated with dental caries and gingivitis were preferentially enriched in individuals with each respective disease only in stimulated saliva. Our study suggests that stimulated saliva provides a more nuanced readout of microbiome composition and taxa distribution associated with untreated dental caries and gingivitis compared to unstimulated saliva.

Global abundance patterns, diversity, and ecology of Patescibacteria in wastewater treatment plants

BACKGROUND

Microorganisms are responsible for nutrient removal and resource recovery in wastewater treatment plants (WWTPs), and their diversity is often studied by 16S rRNA gene amplicon sequencing. However, this approach underestimates the abundance and diversity of Patescibacteria due to the low coverage of commonly used PCR primers for this highly divergent bacterial phylum. Therefore, our current understanding of the global diversity, distribution, and ecological role of Patescibacteria in WWTPs is very incomplete. This is particularly relevant as Patescibacteria are considered to be associated with microbial host cells and can therefore influence the abundance and temporal variability of other microbial groups that are important for WWTP functioning.

RESULTS

Here, we evaluated the in silico coverage of widely used 16S rRNA gene-targeted primer pairs and redesigned a primer pair targeting the V4 region of bacterial and archaeal 16S rRNA genes to expand its coverage for Patescibacteria. We then experimentally evaluated and compared the performance of the original and modified V4-targeted primers on 565 WWTP samples from the MiDAS global sample collection. Using the modified primer pair, the percentage of ASVs classified as Patescibacteria increased from 5.9 to 23.8%, and the number of detected patescibacterial genera increased from 560 to 1576, while the detected diversity of the remaining microbial community remained similar. Due to this significantly improved coverage of Patescibacteria, we identified 23 core genera of Patescibacteria in WWTPs and described the global distribution pattern of these unusual microbes in these systems. Finally, correlation network analysis revealed potential host organisms that might be associated with Patescibacteria in WWTPs. Interestingly, strong indications were found for an association between Patescibacteria of the Saccharimonadia and globally abundant polyphosphate-accumulating organisms of the genus Ca. Phosphoribacter.

CONCLUSIONS

Our study (i) provides an improved 16S rRNA gene V4 region-targeted amplicon primer pair inclusive of Patescibacteria with little impact on the detection of other taxa, (ii) reveals the diversity and distribution patterns of Patescibacteria in WWTPs on a global scale, and (iii) provides new insights into the ecological role and potential hosts of Patescibacteria in WWTPs. Video Abstract.

The DTC microbiome testing industry needs more regulation

Tests lack analytical and clinical validity, requiring more federal oversight to prevent consumer harm.

Transcriptome analysis of Edwardsiella piscicida during intracellular infection reveals excludons are involved with the activation of a mitochondrion-like energy generation program

Phylogenetic evidence suggests a shared ancestry between mitochondria and modern Proteobacteria, a phylum including several genera of intracellular pathogens. Studying these diverse pathogens, particularly during intracellular infection of their hosts, can reveal characteristics potentially representative of the mitochondrial-Proteobacterial ancestor by identifying traits shared with mitochondria. While transcriptomic approaches can provide global insights into intracellular acclimatization by pathogens, they are often limited by excess host RNAs in extracts. Here, we developed a method employing magnetic nanoparticles to enrich RNA from an intracellular Gammaproteobacterium, Edwardsiella piscicida, within zebrafish, Danio rerio, fin fibroblasts, enabling comprehensive exploration of the bacterial transcriptome. Our findings revealed that the intracellular E. piscicida transcriptome reflects a mitochondrion-like energy generation program characterized by the suppression of glycolysis and sugar transport, coupled with upregulation of the tricarboxylic acid (TCA) cycle and alternative import of simple organic acids that directly flux into TCA cycle intermediates or electron transport chain donors. Additionally, genes predicted to be members of excludons, loci of gene pairs antagonistically co-regulated by overlapping antisense transcription, are significantly enriched in the set of all genes with perturbed sense and antisense transcription, suggesting a general but important involvement of excludons with intracellular acclimatization. Notably, genes involved with the activation of the mitochondrion-like energy generation program, specifically with metabolite import and glycolysis, are also members of predicted excludons. Other intracellular Proteobacterial pathogens appear to employ a similar mitochondrion-like energy generation program, suggesting a potentially conserved mechanism for optimized energy acquisition from hosts centered around the TCA cycle.IMPORTANCEPhylogenetic evidence suggests that mitochondria and Proteobacteria, a phylum encompassing various intracellular pathogens, share a common ancestral lineage. In this study, we developed a novel method employing magnetic nanoparticles to explore the transcriptome of an aquatic Gammaproteobacterium, Edwardsiella piscicida, during intracellular infection of host cells. We show that the strategy E. piscicida uses to generate energy strikingly mirrors the function of mitochondria-energy generators devoid of glycolytic processes. Notably, several implicated genes are members of excludons-gene pairs antagonistically co-regulated by overlapping antisense transcription. Other intracellular Proteobacterial pathogens appear to adopt a similar mitochondrion-like energy generation program, indicating a possibly conserved strategy for optimized energy acquisition from hosts centered around the tricarboxylic acid cycle.

Bifidobacterium longum modifies a nutritional intervention for stunting in Zimbabwean infants

Child stunting is an indicator of chronic undernutrition and reduced human capital. However, it remains a poorly understood public health problem. Small-quantity lipid-based nutrient supplements (SQ-LNS) have been widely tested to reduce stunting, but have modest effects. The infant intestinal microbiome may contribute to stunting, and is partly shaped by mother and infant histo-blood group antigens (HBGA). We investigated whether mother-infant fucosyltransferase status, which governs HBGA, and the infant gut microbiome modified the impact of SQ-LNS on stunting at age 18 months among Zimbabwean infants in the SHINE Trial ( NCT01824940 ). We found that mother-infant fucosyltransferase discordance and Bifidobacterium longum reduced SQ-LNS efficacy. Infant age-related microbiome shifts in B. longum subspecies dominance from infantis , a proficient human milk oligosaccharide utilizer, to suis or longum , proficient plant-polysaccharide utilizers, were partly influenced by discordance in mother-infant FUT2+/FUT3- phenotype, suggesting that a "younger" microbiome at initiation of SQ-LNS reduces its benefits on stunting.

Considerations for the inclusion of metabarcoding data in the plant protection product risk assessment of the soil microbiome

There is increasing interest in further developing the plant protection product (PPP) environmental risk assessment, particularly within the European Union, to include the assessment of soil microbial community composition, as measured by metabarcoding approaches. However, to date, there has been little discussion as to how this could be implemented in a standardized, reliable, and robust manner suitable for regulatory decision-making. Introduction of metabarcoding-based assessments of the soil microbiome into the PPP risk assessment would represent a significant increase in the degree of complexity of the data that needs to be processed and analyzed in comparison to the existing risk assessment on in-soil organisms. The bioinformatics procedures to process DNA sequences into community compositional data sets currently lack standardization, while little information exists on how these data should be used to generate regulatory endpoints and the ways in which these endpoints should be interpreted. Through a thorough and critical review, we explore these challenges. We conclude that currently, we do not have a sufficient degree of standardization or understanding of the required bioinformatics and data analysis procedures to consider their use in an environmental risk assessment context. However, we highlight critical knowledge gaps and the further research required to understand whether metabarcoding-based assessments of the soil microbiome can be utilized in a statistically and ecologically relevant manner within a PPP risk assessment. Only once these challenges are addressed can we consider if and how we should use metabarcoding as a tool for regulatory decision-making to assess and monitor ecotoxicological effects on soil microorganisms within an environmental risk assessment of PPPs. Integr Environ Assess Manag 2024;20:337-358. © 2023 SETAC.

GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis

Amplicon-based 16S ribosomal RNA sequencing remains a widely used method to profile microbial communities, especially in low biomass samples, due to its cost-effectiveness and low-complexity approach. Reference databases are a mainstay for taxonomic assignments, which typically rely on popular databases such as SILVA, Greengenes, Genome Taxonomy Database (GTDB), or Ribosomal Database Project (RDP). However, the inconsistency of the nomenclature across databases and the presence of shortcomings in the annotation of these databases are limiting the resolution of the analysis. To overcome these limitations, we created the GSR database (Greengenes, SILVA, and RDP database), an integrated and manually curated database for bacterial and archaeal 16S amplicon taxonomy analysis. Unlike previous integration approaches, this database creation pipeline includes a taxonomy unification step to ensure consistency in taxonomical annotations. The database was validated with three mock communities, two real data sets, and a 10-fold cross-validation method and compared with existing 16S databases such as Greengenes, Greengenes 2, GTDB, ITGDB, SILVA, RDP, and MetaSquare. Results showed that the GSR database enhances taxonomical annotations of 16S sequences, outperforming current 16S databases at the species level, based on the evaluation of the mock communities. This was confirmed by the 10-fold cross-validation, except for Greengenes 2. The GSR database is available for full-length 16S sequences and the most commonly used hypervariable regions: V4, V1-V3, V3-V4, and V3-V5.IMPORTANCETaxonomic assignments of microorganisms have long been hindered by inconsistent nomenclature and annotation issues in existing databases like SILVA, Greengenes, Greengenes2, Genome Taxonomy Database, or Ribosomal Database Project. To overcome these issues, we created Greengenes-SILVA-RDP database (GSR-DB), accurate and comprehensive taxonomic annotations of 16S amplicon data. Unlike previous approaches, our innovative pipeline includes a unique taxonomy unification step, ensuring consistent and reliable annotations. Our evaluation analyses showed that GSR-DB outperforms existing databases in providing species-level resolution, especially based on mock-community analysis, making it a game-changer for microbiome studies. Moreover, GSR-DB is designed to be accessible to researchers with limited computational resources, making it a powerful tool for scientists across the board. Available for full-length 16S sequences and commonly used hypervariable regions, including V4, V1-V3, V3-V4, and V3-V5, GSR-DB is a go-to database for robust and accurate microbial taxonomy analysis.

Ecological diversity and associated volatilome of typical mountain Caciotta cheese from Italy

Traditional products are particularly appreciated by consumers and among these products, cheese is a major contributor to the Italian mountainous area economics. In this study, shotgun metagenomics and volatilomics were used to understand the biotic and abiotic factors contributing to mountain Caciotta cheese typicity and diversity. Results showed that the origin of cheese played a significant role; however, curd cooking temperature, pH, salt concentration and water activity also had an impact. Viral communities exhibited higher biodiversity and discriminated cheese origins in terms of production farms. Among the most dominant bacteria, Streptococcus thermophilus showed higher intraspecific diversity and closer relationship to production farm when compared to Lactobacillus delbrueckii. However, despite a few cases in which the starter culture was phylogenetically separated from the most dominant strains sequenced in the cheese, starter cultures and dominant cheese strains clustered together suggesting substantial starter colonization in mountain Caciotta cheese. The Caciotta cheese volatilome contained prominent levels of alcohols and ketones, accompanied by lower proportions of terpenes. Volatile profile not only demonstrated a noticeable association with production farm but also significant differences in the relative abundances of enzymes connected to flavor development. Moreover, correlations of different non-homologous isofunctional enzymes highlighted specific contributions to the typical flavor of mountain Caciotta cheese. Overall, this study provides a deeper understanding of the factors shaping typical mountain Caciotta cheese, and the potential of metagenomics for characterizing and potentially authenticating food products.

Comparative genomic analysis of Microcystis strain diversity using conserved marker genes

Microcystis-dominated cyanobacterial harmful algal blooms (cyanoHABs) have a global impact on freshwater environments, affecting both wildlife and human health. Microcystis diversity and function in field samples and laboratory cultures can be determined by sequencing whole genomes of cultured isolates or natural populations, but these methods remain computationally and financially expensive. Amplicon sequencing of marker genes is a lower cost and higher throughput alternative to characterize strain composition and diversity in mixed samples. However, the selection of appropriate marker gene region(s) and primers requires prior understanding of the relationship between single gene genotype, whole genome content, and phenotype. To identify phylogenetic markers of Microcystis strain diversity, we compared phylogenetic trees built from each of 2,351 individual core genes to an established phylogeny and assessed the ability of these core genes to predict whole genome content and bioactive compound genotypes. We identified single-copy core genes better able to resolve Microcystis phylogenies than previously identified marker genes. We developed primers suitable for current Illumina-based amplicon sequencing with near-complete coverage of available Microcystis genomes and demonstrate that they outperform existing options for assessing Microcystis strain composition. Results showed that genetic markers can be used to infer Microcystis gene content and phenotypes such as potential production of bioactive compounds , although marker performance varies by bioactive compound gene and sequence similarity. Finally, we demonstrate that these markers can be used to characterize the Microcystis strain composition of laboratory or field samples like those collected for surveillance and modeling of Microcystis-dominated cyanobacterial harmful algal blooms.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

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.