Full-length 16S rRNA gene sequencing by PacBio improves taxonomic resolution in human microbiome samples.

BACKGROUND: Sequencing variable regions of the 16S rRNA gene (≃300 bp) with Illumina technology is commonly used to study the composition of human microbiota. Unfortunately, short reads are unable to differentiate between highly similar species. Considering that species from the same genus can be associated with health or disease it is important to identify them at the lowest possible taxonomic rank. Third-generation sequencing platforms such as PacBio SMRT, increase read lengths allowing to sequence the whole gene with the maximum taxonomic resolution. Despite its potential, full length 16S rRNA gene sequencing is not widely used yet. The aim of the current study was to compare the sequencing output and taxonomic annotation performance of the two approaches (Illumina short read sequencing and PacBio long read sequencing of 16S rRNA gene) in different human microbiome samples. DNA from saliva, oral biofilms (subgingival plaque) and faeces of 9 volunteers was isolated. Regions V3-V4 and V1-V9 were amplified and sequenced by Illumina Miseq and by PacBio Sequel II sequencers, respectively. RESULTS: With both platforms, a similar percentage of reads was assigned to the genus level (94.79% and 95.06% respectively) but with PacBio a higher proportion of reads were further assigned to the species level (55.23% vs 74.14%). Regarding overall bacterial composition, samples clustered by niche and not by sequencing platform. In addition, all genera with > 0.1% abundance were detected in both platforms for all types of samples. Although some genera such as Streptococcus tended to be observed at higher frequency in PacBio than in Illumina (20.14% vs 14.12% in saliva, 10.63% vs 6.59% in subgingival plaque biofilm samples) none of the differences were statistically significant when correcting for multiple testing. CONCLUSIONS: The results presented in the current manuscript suggest that samples sequenced using Illumina and PacBio are mostly comparable. Considering that PacBio reads were assigned at the species level with higher accuracy than Illumina, our data support the use of PacBio technology for future microbiome studies, although a higher cost is currently required to obtain an equivalent number of reads per sample.

Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases.

Taxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that have been developed and used for data analysis. This problem is compounded by different choices regarding which variable region of the 16S rRNA gene and which database is used for taxonomic identification. Therefore, this study employed the DADA2 algorithm to optimize the preprocessing of raw data obtained from the sequencing of activated sludge samples, using simultaneous analysis of three frequently used regions of 16S rRNA (V1-V3, V3-V4, V4-V5). Additionally, the study evaluated which variable region and which of the frequently used microbial databases for taxonomic classification (Greengenes2, Silva, RefSeq) more accurately classify OTUs into taxa. Adjusting the values of selected parameters of the DADA2 algorithm, we obtained the highest possible numbers of OTUs for each region. Regarding biodiversity within regions, the V3-V4 region had the highest Simpson and Shannon indexes, and the Chao1 index was similar to that of the V1-V3 region. Beta-biodiversity analysis revealed statistically significant differences between regions. When comparing databases for each of the regions studied, the highest numbers of taxonomic groups were obtained using the SILVA database. These results suggest that standardization of metabarcoding of short amplicons may be possible.

Comparing DNA isolation and sequencing strategies for 16S rRNA gene amplicon analysis in biofilm containing environments.

Bacteria are primarily responsible for biological water treatment processes in constructed wetland systems. Gravel in constructed wetlands serves as an essential substrate onto which complex bacterial biofilms may successfully grow and evolve. To fully understand the bacterial community in these systems it is crucial to properly isolate biofilms and process DNA from such substrates. This study looked at how best to isolate bacterial biofilms from gravel substrates in terms of bacterial richness. It considered factors including the duration of agitation during extraction, extraction temperature, and enzyme usage. Further, the 16S taxonomy data subsequently produced from Illumina MiSeq reads (using the SILVA 132 ribosomal RNA (rRNA) database on the DADA2 pipeline) were compared with the 16S data produced from Oxford Nanopore Technologies (ONT) MinION reads (using the NCBI 16S database on the EPI2ME pipeline). Finally, performance was tested by comparing the taxonomy data generated from the Illumina MiSeq and ONT MinION reads using the same (SILVA 132) database. We found no significant differences in the effective number of species observed when using different bacterial biofilm detachment techniques. However, enzyme treatment enhanced the total concentration of DNA. In terms of wetland community profiles, relative abundance differences within each sample type were clearer at the genus level. For genus-level taxonomic classification, MinION sequencing with the EPI2ME pipeline (NCBI database) produced bacterial abundance information that was poorly correlated with that from the Illumina MiSeq and DADA2 pipelines (SILVA132 database). When using the same database for each sequencing technology (SILVA132), the correlation between relative abundances at genus-level improved from negligible to moderate. This study provides detailed information of value to researchers working on constructed wetlands regarding efficient biofilm detachment techniques for DNA isolation and 16 s metabarcoding platforms for sequencing and data analysis.

Aerobic digestibility of waste aerobic granular sludge (AGS) assessed by respirometry, physical-chemical analyses, modeling and 16S rRNA gene sequencing.

Research has evolved on aerobic granular sludge (AGS) process, but still there are very few studies on the treatment of excess AGS sludge, with almost none considering its aerobic digestion. Here therefore, the aerobic digestibility of typical AGS sludge was assessed. Granules were produced from acetate-based synthetic wastewater (WW) and were subjected to aerobic digestion for 64 d. The stabilization process was monitored over time through physical-chemical parameters, oxygen uptake rates (OUR) and 16S rRNA gene sequencing. The microbial analyses revealed that the cultivated granules were dominated by slow-growing bacteria, mainly ordinary heterotrophic organisms with potential for polyhydroxyalkanoates (PHA) aerobic storage (PHA-OHOs), polyphosphate and glycogen accumulating organisms (PAOs and GAOs), fermentative anaerobes and nitrifiers (AOB and NOB). Differential abundance analysis of the bacterial data (before versus after digestion) discriminated between the most vulnerable microbiome genera and those most resistant to aerobic digestion. Furthermore, modeling of the stabilization process determined that the endogenous decay rate constant (bH) for the heterotrophs present in the granules was notably low; bH = 0.05 d-1 (average), four times less than for common activated sludge (AS), which is rated at 0.2 d-1. For first time, the research reveals another important feature of AGS sludge, i.e. the slow-decaying character of its bacteria (along with their known slow-growing character). This results in slower stabilization, need of bigger digesters and reconsideration of the specific OUR limits in biosolids regulations (SOUR limit of 1.5 mg/gTSS.h), for waste AGS compared to conventional waste AS. The study suggests that aerobic digestion of waste AGS (fully-granulated) could differ from that of conventional AS. Future work is needed on aerobic digestibility of real AGS sludges from municipal and industrial WWs, compared to synthetic WWs.

The copy number of the eukaryotic rRNA gene can be counted comprehensively.

Gene sequence has been widely used in molecular ecology. For instance, the ribosomal RNA (rRNA) gene has been widely used as a biological marker to understand microbial communities. The variety of the detected rRNA gene sequences reflects the diversity of the microorganisms existing in the analyzed sample. Their biomass can also be estimated by applying quantitative sequencing with information on rRNA gene copy numbers in genomes; however, information on rRNA gene copy numbers is still limited. Especially, the copy number in microbial eukaryotes is much less understood than that of prokaryotes, possibly because of the large and complex structure of eukaryotic genomes. In this study, we report an alternative approach that is more appropriate than the existing method of quantitative sequencing and demonstrate that the copy number of eukaryotic rRNA can be measured efficiently and comprehensively. By applying this approach widely, information on the eukaryotic rRNA copy number can be determined, and their community structures can be depicted and compared more efficiently.

Benchmarking a targeted 16S ribosomal RNA gene enrichment approach to reconstruct ancient microbial communities.

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Improved DNA Extraction and Amplification Strategy for 16S rRNA Gene Amplicon-Based Microbiome Studies.

Next-generation sequencing technology has driven the rapid advancement of human microbiome studies by enabling community-level sequence profiling of microbiomes. Although all microbiome sequencing methods depend on recovering the DNA from a sample as a first critical step, lysis methods can be a major determinant of microbiome profile bias. Gentle enzyme-based DNA preparation methods preserve DNA quality but can bias the results by failing to open difficult-to-lyse bacteria. Mechanical methods like bead beating can also bias DNA recovery because the mechanical energy required to break tougher cell walls may shear the DNA of the more easily lysed microbes, and shearing can vary depending on the time and intensity of beating, influencing reproducibility. We introduce a non-mechanical, non-enzymatic, novel rapid microbial DNA extraction procedure suitable for 16S rRNA gene-based microbiome profiling applications that eliminates bead beating. The simultaneous application of alkaline, heat, and detergent ('Rapid' protocol) to milligram quantity samples provided consistent representation across the population of difficult and easily lysed bacteria equal to or better than existing protocols, producing sufficient high-quality DNA for full-length 16S rRNA gene PCR. The novel 'Rapid' method was evaluated using mock bacterial communities containing both difficult and easily lysed bacteria. Human fecal sample testing compared the novel Rapid method with a standard Human Microbiome Project (HMP) protocol for samples from lung cancer patients and controls. DNA recovered from both methods was analyzed using 16S rRNA gene sequencing of the V1V3 and V4 regions on the Illumina platform and the V1V9 region on the PacBio platform. Our findings indicate that the 'Rapid' protocol consistently yielded higher levels of Firmicutes species, which reflected the profile of the bacterial community structure more accurately, which was confirmed by mock community evaluation. The novel 'Rapid' DNA lysis protocol reduces population bias common to bead beating and enzymatic lysis methods, presenting opportunities for improved microbial community profiling, combined with the reduction in sample input to 10 milligrams or less, and it enables rapid transfer and simultaneous lysis of 96 samples in a standard plate format. This results in a 20-fold reduction in sample handling time and an overall 2-fold time advantage when compared to widely used commercial methods. We conclude that the novel 'Rapid' DNA extraction protocol offers a reliable alternative for preparing fecal specimens for 16S rRNA gene amplicon sequencing.

Analysis of 16s rRNA Gene Sequencing in Feces: The Impact of Bariatric Surgery on the Gut Microbiota in Patients with Obesity.

PURPOSE: Obesity is a risk factor for many chronic diseases. This study aimed to investigate the effect of bariatric surgery on the gut microbiota from patients with obesity. MATERIALS AND METHODS: The microbiota composition from stool samples before and after bariatric surgery were identified using bacterial 16S rRNA gene sequencing. Based on the speed of weight loss, patients were classified as the slow-loss group and fast-loss group. The ɑ- and ß-diversity analysis was done to compare the species richness, evenness, and overall structure of the microbiota between different groups. Next, linear discriminant analysis effect size (LEfSe) and receiver operating characteristic (ROC) analysis were implemented to identify high-dimensional biomarkers and significantly different species of microbial taxa between different groups. Finally, the pathway analysis was inferred using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to predict the functional profiling of microbial communities. RESULTS: ß-diversity analysis suggested that species diversity of preoperative samples of slow-loss group was significantly higher than the fast-loss group. High levels of Oscillospira and Abiotrophia in the preoperative gut microbiota may lead to poor postoperative weight loss. For patients with poor postoperative weight loss due to changes in gut microbiota, the gut microbiota is mainly composed of Lactobacillus. For patients with good postoperative results, the gut microbiota is mainly composed of Escherichia, Robinsonella, and Dialister. In addition, multiple metabolic-related pathways were significantly different between the four groups. CONCLUSION: This comparative study revealed biomarker species based on microfloral composition in patients with obesity before and after bariatric surgery.

Correlation between bacterial microbiome and Legionella species in water from public bath facilities by 16S rRNA gene amplicon sequencing.

Public bath facilities are a major source of Legionella infections in Japan. In this study, we performed 16S rRNA gene amplicon sequencing to characterize the bacterial community in bath and shower water from public bath facilities, along with chemical parameters, and investigated the effect of the bacterial microbiome on the presence of Legionella species. Although no significant difference in bacterial community richness was observed between bath and shower water samples, there was a remarkable difference in the bacterial community structure between them. Distance-based redundancy analysis revealed that several factors (free residual chlorine, pH, and conductivity) were correlated with the bacterial community in bath water. The most abundant bacterial genera in the samples were Pseudomonas (13.7%) in bath water and Phreatobacter (13.6%) in shower water, as indicated by the taxonomic composition, and the dominant bacteria differed between these environmental samples. Legionella pneumophila was the most frequently detected Legionella species, with additional 15 other Legionella species detected in water samples. In Legionella-positive water samples, several unassigned and uncultured bacteria were enriched together. In addition, the co-occurrence network showed that Legionella was strongly interconnected with two uncultured bacteria. Corynebacterium and Sphingomonas negatively correlated with Legionella species. The present study reveals the ecology of Legionella species, especially their interactions with other bacteria that are poorly understood to date. IMPORTANCE: Public bath facilities are major sources of sporadic cases and outbreaks of Legionella infections. Recently, 16S rRNA gene amplicon sequencing has been used to analyze bacterial characteristics in various water samples from both artificial and natural environments, with a particular focus on Legionella bacterial species. However, the relationship between the bacterial community and Legionella species in the water from public bath facilities remains unclear. In terms of hygiene management, it is important to reduce the growth of Legionella species by disinfecting the water in public bath facilities. Our findings contribute to the establishment of appropriate hygiene management practices and provide a basis for understanding the potential health effects of using bath and shower water available in public bath facilities.

Optimized bacterial community characterization through full-length 16S rRNA gene sequencing utilizing MinION nanopore technology.

BACKGROUND: Accurate identification of bacterial communities is crucial for research applications, diagnostics, and clinical interventions. Although 16S ribosomal RNA (rRNA) gene sequencing is a widely employed technique for bacterial taxonomic classification, it often results in misclassified or unclassified bacterial taxa. This study sought to refine the full-length 16S rRNA gene sequencing protocol using the MinION sequencer, focusing on the V1-V9 regions. Our methodological enquiry examined several factors, including the number of PCR amplification cycles, choice of primers and Taq polymerase, and specific sequence databases and workflows employed. We used a microbial standard comprising eight bacterial strains (five gram-positive and three gram-negative) in known proportions as a validation control. RESULTS: Based on the MinION protocol, we employed the microbial standard as the DNA template for the 16S rRNA gene amplicon sequencing procedure. Our analysis showed that an elevated number of PCR amplification cycles introduced PCR bias, and the selection of Taq polymerase and primer sets significantly affected the subsequent analysis. Bacterial identification at genus level demonstrated Pearson correlation coefficients ranging from 0.73 to 0.79 when assessed using BugSeq, Kraken-Silva and EPI2ME-16S workflows. Notably, the EPI2ME-16S workflow exhibited the highest Pearson correlation with the microbial standard, minimised misclassification, and increased alignment accuracy. At the species taxonomic level, the BugSeq workflow was superior, with a Pearson correlation coefficient of 0.92. CONCLUSIONS: These findings emphasise the importance of careful selection of PCR settings and a well-structured analytical framework for 16S rRNA full-length gene sequencing. The results showed a robust correlation between the predicted and observed bacterial abundances at both the genus and species taxonomic levels, making these findings applicable across diverse research contexts and with clinical utility for reliable pathogen identification.

Investigation of the effect of oligo-xylulose on the intestinal flora under pressure overload in mice based on 16S rRNA gene sequencing.

The relationship between gut microbiota dysbiosis and heart failure has been drawing increasing attention. This study aimed to investigate the effects of oligo-xylulose (XOS) on the gut microbiota of mice with heart failure induced by pressure overload. A chronic heart failure mouse model was constructed by pressure overload, and XOS were administered in their diet. The gut microbiota was analyzed using 16S rRNA gene sequencing, and the effects of XOS on the microbiota composition were evaluated. . XOS supplementation improved the balance of intestinal microbiota in mice under pressure overload, increasing the abundance of beneficial bacteria, such as Bifidobacterium and Lactobacillus, while decreasing the abundance of harmful bacteria, such as Desulfovibrio and Enterococcus. XOS has potential as a dietary supplement to improve the balance of intestinal microbiota and benefit individuals with heart failure. The findings of this study suggest that modulating the gut microbiota could be a novel strategy for treating heart failure.

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.

Serovar-level identification of bacterial foodborne pathogens from full-length 16S rRNA gene sequencing.

The resolution of variation within species is critical for interpreting and acting on many microbial measurements. In the key foodborne pathogens Salmonella and Escherichia coli, the primary subspecies classification scheme used is serotyping: differentiating variants within these species by surface antigen profiles. Serotype prediction from whole-genome sequencing (WGS) of isolates is now seen as comparable or preferable to traditional laboratory methods where WGS is available. However, laboratory and WGS methods depend on an isolation step that is time-consuming and incompletely represents the sample when multiple strains are present. Community sequencing approaches that skip the isolation step are, therefore, of interest for pathogen surveillance. Here, we evaluated the viability of amplicon sequencing of the full-length 16S rRNA gene for serotyping Salmonella enterica and E. coli. We developed a novel algorithm for serotype prediction, implemented as an R package (Seroplacer), which takes as input full-length 16S rRNA gene sequences and outputs serovar predictions after phylogenetic placement into a reference phylogeny. We achieved over 89% accuracy in predicting Salmonella serotypes on in silico test data and identified key pathogenic serovars of Salmonella and E. coli in isolate and environmental test samples. Although serotype prediction from 16S rRNA gene sequences is not as accurate as serotype prediction from WGS of isolates, the potential to identify dangerous serovars directly from amplicon sequencing of environmental samples is intriguing for pathogen surveillance. The capabilities developed here are also broadly relevant to other applications where intraspecies variation and direct sequencing from environmental samples could be valuable.IMPORTANCEIn order to prevent and stop outbreaks of foodborne pathogens, it is important that we can detect when pathogenic bacteria are present in a food or food-associated site and identify connections between specific pathogenic bacteria present in different samples. In this work, we develop a new computational technology that allows the important foodborne pathogens Escherichia coli and Salmonella enterica to be serotyped (a subspecies level classification) from sequencing of a single-marker gene, and the 16S rRNA gene often used to surveil bacterial communities. Our results suggest current limitations to serotyping from 16S rRNA gene sequencing alone but set the stage for further progress that we consider likely given the rapid advance in the long-read sequencing technologies and genomic databases our work leverages. If this research direction succeeds, it could enable better detection of foodborne pathogens before they reach the public and speed the resolution of foodborne pathogen outbreaks.

Enhanced phylogenetic insights into the microbiome of chronic rhinosinusitis through the novel application of long read 16S rRNA gene amplicon sequencing.

INTRODUCTION: 16S rRNA next generation sequencing (NGS) has been the de facto standard of microbiome profiling. A limitation of this technology is the inability to accurately assign taxonomy to a species order. Long read 16S sequencing platforms, including Oxford Nanopore Technologies (ONT), have the potential to overcome this limitation. The paranasal sinuses are an ideal niche to apply this technology, being a low biomass environment where bacteria are implicated in disease propagation. Characterising the microbiome to a species order may offer new pathophysiological insights. METHODOLOGY: Cohort series comparing ONT and NGS biological conclusions. Swabs obtained endoscopically from the middle meatus of 61 CRSwNP patients underwent DNA extraction, amplification and dual sequencing (Illumina Miseq (NGS) and ONT GridION). Agreement, relative abundance, prevalence, and culture correlations were compared. RESULTS: Mean microbiome agreement between sequencers was 61.4%. Mean abundance correlations were strongest at a familial/genus order and declined at a species order where NGS lacked resolution. The most significant discrepancies applied to Corynebacterium and Cutibacterium, which were estimated in lower abundance by ONT. ONT accurately identified 84.2% of cultured species, which was significantly higher than NGS. CONCLUSIONS: ONT demonstrated superior resolution and culture correlations to NGS, but underestimated core sinonasal taxa. Future application and optimisation of this technology can advance our understanding of the sinonasal microenvironment.

16S rRNA Gene Amplicon Analysis of Human Gut Microbiota.

The intestinal microbiota is associated with a variety of diseases, and there are a growing number of research reports on the gut microbiota. In addition, a new technique such as Nanopore sequencing has recently become available, making it easier to conduct research related to the gut microbiota. In this chapter, we introduce a technique used in gut microbiota analysis, from stool collection to sequencing with MinION.

Integration of 16 S rRNA gene sequencing, metabonomics and metagenome analysis to investigate the mechanism of Sparganium stoloniferum-Curcuma phaeocaulis in treating of endometriosis in rats.

BACKGROUND: Endometriosis is a gynecological disease that causes severe chronic pelvic pain and infertility in women. The therapeutic efficacy of the traditional herbal combination of Sparganium stoloniferum-Curcuma phaeocaulis (Sangleng-Ezhu, SL-EZ) in the treatment of endometriosis has been established. However, the precise mechanism by which this treatment exerts its effects remains elusive. METHODS: To gain further insights, UPLC-MS/MS was employed to identify the primary chemical constituents of SL-EZ in serum. Additionally, network pharmacology was utilized to analyze the active ingredients and their corresponding targets. Furthermore, the impact of SL-EZ on ectopic endometrial growth in endometrial implants was assessed using a rat model. The therapeutic mechanism of SL-EZ in rats with endometriosis was further investigated through the application of 16 S rRNA gene sequencing, metagenomic sequencing, and metabolomics. RESULTS: The primary compounds in serum were zederone, p-coumaric acid, dehydrocostus lactone, curdione, curcumol. The growth of ectopic lesions in a rat model was effectively inhibited by SL-EZ. In comparison to the control group, the endometriotic rats exhibited a decrease in α-diversity of the gut microbiota, an increase in the Firmicutes/Bacteroidetes ratio, and a reduction in the abundance of Ruminococcaceae. Following SL-EZ intervention, the potential probiotic strains Lactobacillus gasseri and Lactobacillus johnsonii were able to restore the intestinal microenvironment at the species level. The altered metabolites were significantly correlated with Verrucomicrobia, Proteobacteria, and Bacteroidetes. The metabolomic analysis demonstrated significant alterations in intestinal metabolites. And SL-EZ intervention also exerted regulatory effects on various metabolic pathways in gut microbiota, including aminoacyl-tRNA biosynthesis, monobactam biosynthesis, cyanoamino acid metabolism, glycine, serine and threonine metabolism, plant secondary metabolite biosynthesis, and amino acid biosynthesis. CONCLUSION: The identification of novel treatment formulations for endometriosis was achieved through the utilization of network pharmacology and gut microbiota analyses. Our findings revealed simultaneous alterations in the microbiota within the rat model of endometriosis. The therapeutic efficacy of SL-EZ in treating endometriosis is attributed to its ability to restore the gut microbiota and regulate metabolism. This investigation offers valuable insights into the therapeutic mechanisms of traditional Chinese medicine (TCM) for endometriosis.

Evolving Together: Cassandra Retrotransposons Gradually Mirror Promoter Mutations of the 5S rRNA Genes.

The 5S rRNA genes are among the most conserved nucleotide sequences across all species. Similar to the 5S preservation we observe the occurrence of 5S-related nonautonomous retrotransposons, so-called Cassandras. Cassandras harbor highly conserved 5S rDNA-related sequences within their long terminal repeats, advantageously providing them with the 5S internal promoter. However, the dynamics of Cassandra retrotransposon evolution in the context of 5S rRNA gene sequence information and structural arrangement are still unclear, especially: (1) do we observe repeated or gradual domestication of the highly conserved 5S promoter by Cassandras and (2) do changes in 5S organization such as in the linked 35S-5S rDNA arrangements impact Cassandra evolution? Here, we show evidence for gradual co-evolution of Cassandra sequences with their corresponding 5S rDNAs. To follow the impact of 5S rDNA variability on Cassandra TEs, we investigate the Asteraceae family where highly variable 5S rDNAs, including 5S promoter shifts and both linked and separated 35S-5S rDNA arrangements have been reported. Cassandras within the Asteraceae mirror 5S rDNA promoter mutations of their host genome, likely as an adaptation to the host's specific 5S transcription factors and hence compensating for evolutionary changes in the 5S rDNA sequence. Changes in the 5S rDNA sequence and in Cassandras seem uncorrelated with linked/separated rDNA arrangements. We place all these observations into the context of angiosperm 5S rDNA-Cassandra evolution, discuss Cassandra's origin hypotheses (single or multiple) and Cassandra's possible impact on rDNA and plant genome organization, giving new insights into the interplay of ribosomal genes and transposable elements.

Highly divergent morphology but a close molecular phylogenetic relationship between two little-known ciliate genera Actinobolina and Papillorhabdos (Protozoa: Ciliophora: Litostomatea) with description of two new species.

Free-living litostomatean ciliates, prominent microeukaryote predators commonly encountered in freshwater and marine habitats, play vital roles in maintaining energy flow and nutrient cycles. Nevertheless, understanding their biodiversity and phylogenetic relationships remains challenging due to insufficient morphological information and molecular data. As a new contribution to this group, three haptorian ciliates, including two new species (Actinobolina bivacuolata sp. nov. and Papillorhabdos foissneri sp. nov.) and the insufficiently described type species, Actinobolina radians, were isolated from wetlands around Lake Weishan, China and investigated by a combination of living morphology, stained preparations, and 18S rRNA gene sequence data. An illustrated key of the valid species within the two genera is provided. In addition, we reveal the phylogenetic positions of these two genera for the first time. Although they differ in all key morphologic characters such as general appearance (ellipsoidal with numerous tentacles vs. cylindrical), extrusomes (stored in tentacles vs. anchored to pellicle), circumoral kinety (present vs. absent), composition of somatic kineties (kinetosome clusters vs. monokinetids), and number of dorsal brush rows (1 vs. 4), they both cluster in a fully supported clade in the phylogenetic tree, which indicates that the biodiversity and additional molecular markers of this group need further exploration.

Comparison of 16S rRNA gene sequencing microbiota among children with serological IgE-mediated food hypersensitivity.

BACKGROUND: We hypothesized that specific food hypersensitivity (FH) in children is linked to specific gut microbiota. The aim of our study was to quantify and evaluate differences in gut microbial composition among children with different IgE-mediated FH. METHODS: Children (n = 81) aged 18 to 36 months were enrolled, fecal samples of 57 children with FH and 24 healthy children were evaluated using next-generation sequencing. Individual microbial diversity and composition were analyzed via targeting the 16 S rRNA gene hypervariable V3-V5 regions. RESULTS: Children with IgE-mediated FH (in milk, egg white, soy) had significantly lower gut microbiota diversity and richness than healthy children. Children with IgE-mediated FH exhibited relatively high abundances of Firmicutes and relative underrepresentation of the phylum Bacteroidetes. We observed significant increases in relative abundances of Ruminococcaceae, Clostridiaceae, and Erysipelotrichaceae (p < 0.01, compared to control) in children with milk hypersensitivity and of Clostridiaceae and Erysipelotrichaceae (p < 0.01) in children with peanut hypersensitivity. We also found significant increases in the numbers of Clostridiaceae, Lachnospiraceae and Pasteurellaceae (p < 0.01) in children with egg white hypersensitivity. CONCLUSIONS: These findings identify early evidence of different gut microbiota development/ differentiation in children with food hypersensitivity. Specific food hypersensitivities may be associated with compositional changes in intestinal microbiota. IMPACT: These findings identify early evidence of different gut microbiota development/differentiation in children with food hypersensitivity. We built a gut microbial profile that could identify toddlers at risk for food hypersensitivity. Children with enriched Firmicutes (phylum) with partial different families may be associated with food hypersensitivity. Enriched family Clostridiaceae, Ruminococcaceae, Lachnospiraceae, or Erysipelotrichaceae in gut microbiota may be associated with specific food hypersensitivities (such as milk, egg white, peanut) in children.

Acidic growth conditions stabilize the ribosomal RNA gene cluster and extend lifespan through noncoding transcription repression.

Blackcurrant (Ribes nigrum L.) is a classical fruit that has long been used to make juice, jam, and liqueur. Blackcurrant extract is known to relieve cells from DNA damage caused by hydrogen peroxide (H2 O2 ), methyl methane sulfonate (MMS), and ultraviolet (UV) radiation. We found that blackcurrant extract (BCE) stabilizes the ribosomal RNA gene cluster (rDNA), one of the most unstable regions in the genome, through repression of noncoding transcription in the intergenic spacer (IGS) which extended the lifespan in budding yeast. Reduced formation of extrachromosomal circles (ERCs) after exposure to fractionated BCE suggested that acidity of the growth medium impacted rDNA stability. Indeed, alteration of the acidity of the growth medium to pH ~4.5 by adding HCl increased rDNA stability and extended the lifespan. We identified RPD3 as the gene responsible for this change, which was mediated by the RPD3L histone deacetylase complex. In mammals, as inflammation sites in a tissue are acidic, DNA maintenance may be similarly regulated to prevent genome instability from causing cancer.