Expanding Archaeal Diversity and Phylogeny: Past, Present, and Future.

The discovery of the Archaea is a major scientific hallmark of the twentieth century. Since then, important features of their cell biology, physiology, ecology, and diversity have been revealed. Over the course of some 40 years, the diversity of known archaea has expanded from 2 to about 30 phyla comprising over 20,000 species. Most of this archaeal diversity has been revealed by environmental 16S rRNA gene amplicon sequencing surveys using a broad range of universal and targeted primers. Of the few primers that target a large fraction of known archaeal diversity, all display a bias against recently discovered lineages, which limits studies aiming to survey overall archaeal diversity. Induced by genomic exploration of archaeal diversity, and improved phylogenomics approaches, archaeal taxonomic classification has been frequently revised. Due to computational limitations and continued discovery of new lineages, a stable archaeal phylogeny is not yet within reach. Obtaining phylogenetic and taxonomic consensus of archaea should be a high priority for the archaeal research community.

Integrated genomic and functional analyses of human skin-associated Staphylococcus reveal extensive inter- and intra-species diversity.

Human skin is stably colonized by a distinct microbiota that functions together with epidermal cells to maintain a protective physical barrier. Staphylococcus, a prominent genus of the skin microbiota, participates in colonization resistance, tissue repair, and host immune regulation in strain-specific manners. To unlock the potential of engineering skin microbial communities, we aim to characterize the diversity of this genus within the context of the skin environment. We reanalyzed an extant 16S rRNA amplicon dataset obtained from distinct body sites of healthy volunteers, providing a detailed biogeographic depiction of staphylococcal species that colonize our skin. S. epidermidis, S. capitis, and S. hominis were the most abundant staphylococcal species present in all volunteers and were detected at all body sites. Pan-genome analysis of isolates from these three species revealed that the genus-core was dominated by central metabolism genes. Species-restricted-core genes encoded known host colonization functions. The majority (~68%) of genes were detected only in a fraction of isolate genomes, underscoring the immense strain-specific gene diversity. Conspecific genomes grouped into phylogenetic clades, exhibiting body site preference. Each clade was enriched for distinct gene sets that are potentially involved in site tropism. Finally, we conducted gene expression studies of select isolates showing variable growth phenotypes in skin-like medium. In vitro expression revealed extensive intra- and inter-species gene expression variation, substantially expanding the functional diversification within each species. Our study provides an important resource for future ecological and translational studies to examine the role of shared and strain-specific staphylococcal genes within the skin environment.

An inhibitory immunoreceptor Allergin-1 regulates the intestinal dysbiosis and barrier function in mice.

The intestinal barrier consists of mucosal, epithelial, and immunological barriers and serves as a dynamic interface between the host and its environment. Disruption of the intestinal barrier integrity is a leading cause of various gastrointestinal diseases, such as inflammatory bowel disease. The homeostasis of the intestinal barrier is tightly regulated by crosstalk between gut microbes and the immune system; however, the implication of the immune system on the imbalance of gut microbes that disrupts barrier integrity remains to be fully elucidated. An inhibitory immunoglobulin-like receptor, Allergin-1, is expressed on mast cells and dendritic cells and inhibits Toll-like receptor (TLR)-2 and TLR-4 signaling in these cells. Since TLRs are major sensors of microbiota and are involved in local epithelial homeostasis, we investigated the role of Allergin-1 in maintaining intestinal homeostasis. Allergin-1-deficient (Milr1-/-) mice exhibited more severe dextran sulfate sodium (DSS)-induced colitis than did wild-type (WT) mice. Milr1-/- mice showed an enhanced intestinal permeability compared with WT mice even before DSS administration. Treatment of Milr1-/- mice with neomycin, but not ampicillin, restored intestinal barrier integrity. The 16S rRNA gene sequencing analysis demonstrated that Bifidobacterium pseudolongum was the dominant bacterium in Milr1-/- mice after treatment with ampicillin. Although the transfer of B. pseudolongum to germ-free WT mice had no effect on intestinal permeability, its transfer into ampicillin-treated WT mice enhanced intestinal permeability. These results demonstrated that Allergin-1 deficiency enhanced intestinal dysbiosis with expanded B. pseudolongum, which contributes to intestinal barrier dysfunction in collaboration with neomycin-sensitive and ampicillin-resistant microbiota.

Gut microbiome correlates with plasma lipids in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease. Disease pathophysiology is incompletely understood but evidence suggests gut dysbiosis occurs in ALS, linked to impaired gastrointestinal integrity, immune system dysregulation and altered metabolism. Gut microbiome and plasma metabolome have been separately investigated in ALS, but little is known about gut microbe-plasma metabolite correlations, which could identify robust disease biomarkers and potentially shed mechanistic insight. Here, gut microbiome changes were longitudinally profiled in ALS and correlated to plasma metabolome. Gut microbial structure at the phylum level differed in ALS versus control participants, with differential abundance of several distinct genera. Unsupervised clustering of microbe and metabolite levels identified modules, which differed significantly in ALS versus control participants. Network analysis found several prominent amplicon sequence variants strongly linked to a group of metabolites, primarily lipids. Similarly, identifying the features that contributed most to case versus control separation pinpointed several bacteria correlated to metabolites, predominantly lipids. Mendelian randomization indicated possible causality from specific lipids related to fatty acid and acylcarnitine metabolism. Overall, the results suggest ALS cases and controls differ in their gut microbiome, which correlates with plasma metabolites, particularly lipids, through specific genera. These findings have the potential to identify robust disease biomarkers and shed mechanistic insight into ALS.

METASEED: a novel approach to full-length 16S rRNA gene reconstruction from short read data.

BACKGROUND: With the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error level and structure, the analysis of such data demands some database of reference sequences. However, many taxa from complex and diverse environments, have poor representation in publicly available databases. In this paper, we propose the METASEED pipeline for the reconstruction of full-length 16S sequences from such environments, in order to improve the reference for the subsequent use of on-site sequencing. RESULTS: We show that combining high-precision short-read sequencing of both 16S and full metagenome from the same samples allow us to reconstruct high-quality 16S sequences from the more abundant taxa. A significant novelty is the carefully designed collection of metagenome reads that matches the 16S amplicons, based on a combination of uniqueness and abundance. Compared to alternative approaches this produces superior results. CONCLUSION: Our pipeline will facilitate numerous studies associated with various unknown microorganisms, thus allowing the comprehension of the diverse environments. The pipeline is a potential tool in generating a full length 16S rRNA gene database for any environment.

PrimerEvalPy: a tool for in-silico evaluation of primers for targeting the microbiome.

BACKGROUND: The selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions. It also allows the analysis of coverage for different taxonomic levels. RESULTS: As a case study, PrimerEvalPy was used to test the most commonly used primers in the literature against two oral 16S rRNA gene databases containing bacteria and archaea. The results showed that the most commonly used primer pairs in the oral cavity did not match those with the highest coverage. The best performing primer pairs were found for the detection of oral bacteria and archaea. CONCLUSIONS: This demonstrates the importance of a coverage analysis tool such as PrimerEvalPy to find the best primer pairs for specific niches. The software is available under the MIT licence at https://gitlab.citius.usc.es/lara.vazquez/PrimerEvalPy .

Machine learning based DNA melt curve profiling enables automated novel genotype detection.

Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening for novel genotypes remains challenging in part due to technological limitations. Towards addressing this challenge, we present an advancement in universal microbial high resolution melting (HRM) analysis that is capable of accomplishing both known genotype identification and novel genotype detection. Specifically, this novel surveillance functionality is achieved through time-series modeling of sequence-defined HRM curves, which is uniquely enabled by the large-scale melt curve datasets generated using our high-throughput digital HRM platform. Taking the detection of bacterial genotypes as a model application, we demonstrate that our algorithms accomplish an overall classification accuracy over 99.7% and perform novelty detection with a sensitivity of 0.96, specificity of 0.96 and Youden index of 0.92. Since HRM-based DNA profiling is an inexpensive and rapid technique, our results add support for the feasibility of its use in surveillance applications.

Multiomics Analysis Revealed Colorectal Cancer Pathogenesis.

Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and progression of CRC remains elusive. We performed 16S rRNA sequencing, metabolomics, and proteomic studies on samples from 85 CRC patients who underwent colonoscopy examination and found two distinct changed patterns of microbiome in CRC patients. The relative abundances of Catabacter and Mogibacterium continuously increased from intramucosal carcinoma to advanced stages, whereas Clostridium, Anaerostipes, Vibrio, Flavonifractor, Holdemanella, and Hungatella were significantly altered only in intermediate lesions. Fecal metabolomics analysis exhibited consistent increases in bile acids, indoles, and urobilin as well as a decrease in heme. Serum metabolomics uncovered the highest levels of bilin, glycerides, and nucleosides together with the lowest levels of bile acids and amino acids in the stage of intermediate lesions. Three fecal and one serum dipeptides were elevated in the intermediate lesions. Proteomics analysis of colorectal tissues showed that oxidation and autophagy through the PI3K/Akt-mTOR signaling pathway contribute to the development of CRC. Diagnostic analysis showed multiomics features have good predictive capability, with AUC greater than 0.85. Our overall findings revealed new candidate biomarkers for CRC, with potentially significant diagnostic and prognostic capabilities.

Cooperative role of AtRsmD and AtRimM proteins in modification and maturation of 16S rRNA in plastids.

Chloroplast pre-ribosomal RNA (rRNA) undergoes maturation, which is critical for ribosome assembly. While the central and auxiliary factors in rRNA maturation have been elucidated in bacteria, their mode of action remains largely unexplored in chloroplasts. We now reveal chloroplast-specific factors involved in 16S rRNA maturation, Arabidopsis thaliana orthologs of bacterial RsmD methyltransferase (AtRsmD) and ribosome maturation factor RimM (AtRimM). A forward genetic screen aimed to find suppressors of the Arabidopsis yellow variegated 2 (var2) mutant defective in photosystem II quality control found a causal nonsense mutation in AtRsmD. The substantially impaired 16S rRNA maturation and translation due to the mutation rescued the leaf variegation phenotype by lowering the levels of chloroplast-encoded proteins, including photosystem II core proteins, in var2. The subsequent co-immunoprecipitation coupled with mass spectrometry analyses and bimolecular fluorescence complementation assay found that AtRsmD interacts with AtRimM. Consistent with their interaction, loss of AtRimM also considerably impairs 16S rRNA maturation with decelerated m2 G915 modification in 16S rRNA catalyzed by AtRsmD. The atrimM mutation also rescued var2 mutant phenotypes, corroborating the functional interplay between AtRsmD and AtRimM towards modification and maturation of 16S rRNA and chloroplast proteostasis. The maturation and post-transcriptional modifications of rRNA are critical to assembling ribosomes responsible for protein translation. Here, we revealed that the cooperative regulation of 16S rRNA m2 G915 modifications by AtRsmD methyltransferase and ribosome assembly factor AtRimM contributes to 16S rRNA maturation, ribosome assembly, and proteostasis in chloroplasts.

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.

Suppression of UVB-Induced MMP-1 Expression in Human Skin Fibroblasts Using Lysate of Lactobacillus iners Derived from Korean Women's Skin in Their Twenties.

The process of skin aging is intricate, involving intrinsic aging, influenced by internal factors, and extrinsic aging, mainly caused by exposure to UV radiation, resulting in photoaging. Photoaging manifests as skin issues such as wrinkles and discoloration. The skin microbiome, a diverse community of microorganisms on the skin's surface, plays a crucial role in skin protection and can be affected by factors like humidity and pH. Probiotics, beneficial microorganisms, have been investigated for their potential to enhance skin health by regulating the skin microbiome. This can be accomplished through oral probiotics, impacting the gut-skin axis, or topical applications introducing live bacteria to the skin. Probiotics mitigate oxidative stress, suppress inflammation, and maintain the skin's extracellular matrix, ultimately averting skin aging. However, research on probiotics derived from human skin is limited, and there is no established product for preventing photoaging. The mechanism by which probiotics shield the skin microbiome and skin layers from UV radiation remains unclear. Recently, researchers have discovered Lactobacillus in the skin, with reports indicating a decrease in this microorganism with age. In a recent study, scientists isolated Lactobacillus iners KOLBM20 from the skin of individuals in their twenties and confirmed its effectiveness. A comparative analysis of genetic sequences revealed that strain KOLBM20 belongs to the Lactobacillus genus and closely relates to L. iners DSM13335(T) with a 99.20% similarity. Importantly, Lactobacillus iners KOLBM20 displayed anti-wrinkle properties by inhibiting MMP-1. This investigation demonstrated the inhibitory effect of KOLBM20 strain lysate on MMP-1 expression. Moreover, the data suggest that KOLBM20 strain lysate may prevent UVB-induced MMP-1 expression by inhibiting the activation of the ERK, JNK, and p38 signaling pathways induced by UVB. Consequently, KOLBM20 strain lysate holds promise as a potential therapeutic agent for preventing and treating skin photoaging.

Cutibacterium acnes-derived extracellular vesicles promote tumor growth in renal cell carcinoma.

Bacterial flora are present in various parts of the human body, including the intestine, and are thought to be involved in the etiology of various diseases such as multiple sclerosis, intestinal diseases, cancer, and uterine diseases. In recent years, the presence of bacterial 16S rRNA genes has been revealed in blood, which was previously thought to be a sterile environment, and characteristic blood microbiomes have been detected in various diseases. However, the mechanism and the origin of the bacterial information are unknown. In this study, we performed 16S rRNA metagenomic analysis of bacterial DNA in serum extracellular vesicles from five healthy donors and seven patients with renal cell carcinoma and detected Cutibacterium acnes DNA as a characteristic bacterial DNA in the serum extracellular vesicles of patients with renal cell carcinoma. In addition, C. acnes DNA was significantly reduced in postoperative serum extracellular vesicles from patients with renal cell carcinoma compared with that in preoperative serum extracellular vesicles from these patients and was also detected in tumor tissue and extracellular vesicles from tumor tissue-associated microbiota, suggesting an association between C. acnes extracellular vesicles and renal cell carcinoma. C. acnes extracellular vesicles were taken up by renal carcinoma cells to enhance their proliferative potential. C. acnes extracellular vesicles also exhibited tumor-promoting activity in a mouse model of renal cancer allografts with enhanced angiogenesis. These results suggest that extracellular vesicles released by C. acnes localized in renal cell carcinoma tissues act in a tumor-promoting manner.

NMN synbiotics intervention modulates gut microbiota and metabolism in APP/PS1 Alzheimer's disease mouse models.

Alzheimer's disease (AD) is a complex neurodegenerative condition with growing evidence implicating the gut microbiota in its pathogenesis. This study aimed to investigate the effects of NMN synbiotics, a combination of ß-nicotinamide mononucleotide (NMN), Lactobacillus plantarum, and lactulose, on the gut microbiota composition and metabolic profiles in APP/PS1 transgenic mice. Results demonstrated that NMN synbiotics led to a notable restructuring of the gut microbiota, with a decreased Firmicutes/Bacteroidetes ratio in the AD mice, suggesting a potential amelioration of gut dysbiosis. Alpha diversity indices indicated a reduction in microbial diversity following NMN synbiotics supplementation, while beta diversity analyses revealed a shift towards a more balanced microbial community structure. Functional predictions based on the 16S rRNA data highlighted alterations in metabolic pathways, particularly those related to amino acid and energy metabolism, which are crucial for neuronal health. The metabolomic analysis uncovered a significant impact of NMN synbiotics on the gut metabolome, with normalization of metabolic composition in AD mice. Differential metabolite functions were enriched in pathways associated with neurotransmitter synthesis and energy metabolism, pointing to the potential therapeutic effects of NMN synbiotics in modulating the gut-brain axis and synaptic function in AD. Immunohistochemical staining observed a significant reduction of amyloid plaques formed by Aß deposition in the brain of AD mice after NMN synbiotics intervention. The findings underscore the potential of using synbiotics to ameliorate the neurodegenerative processes associated with Alzheimer's disease, opening new avenues for therapeutic interventions.

Nutrient availability and plant phenological stage influence the substrate microbiome in container-grown Impatiens walleriana 'Xtreme Red'.

BACKGROUND: The microbiome plays a fundamental role in plant health and performance. Soil serves as a reservoir of microbial diversity where plants attract microorganisms via root exudates. The soil has an important impact on the composition of the rhizosphere microbiome, but greenhouse ornamental plants are commonly grown in soilless substrates. While soil microbiomes have been extensively studied in traditional agriculture to improve plant performance, health, and sustainability, information about the microbiomes of soilless substrates is still limited. Thus, we conducted an experiment to explore the microbiome of a peat-based substrate used in container production of Impatiens walleriana, a popular greenhouse ornamental plant. We investigated the effects of plant phenological stage and fertilization level on the substrate microbiome. RESULTS: Impatiens plants grown under low fertilization rates were smaller and produced more flowers than plants grown under optimum and high fertilization. The top five bacterial phyla present in the substrate were Proteobacteria, Actinobacteria, Bacteriodota, Verrucomicrobiota, and Planctomycetota. We found a total of 2,535 amplicon sequence variants (ASV) grouped into 299 genera. The substrate core microbiome was represented by only 1.8% (48) of the identified ASV. The microbiome community composition was influenced by plant phenological stage and fertilizer levels. Phenological stage exhibited a stronger influence on microbiome composition than fertilizer levels. Differential abundance analysis using DESeq2 identified more ASVs significantly affected (enriched or depleted) in the high fertilizer levels at flowering. As observed for community composition, the effect of plant phenological stage on microbial community function was stronger than fertilizer level. Phenological stage and fertilizer treatments did not affect alpha-diversity in the substrate. CONCLUSIONS: In container-grown ornamental plants, the substrate serves as the main microbial reservoir for the plant, and the plant and agricultural inputs (fertilization) modulate the microbial community structure and function of the substrate. The differences observed in substrate microbiome composition across plant phenological stage were explained by pH, total organic carbon (TOC) and fluoride, and across fertilizer levels by pH and phosphate (PO4). Our project provides an initial diversity profile of the bacteria occurring in soilless substrates, an underexplored source of microbial diversity.

Gut microbiome features and metabolites in non-alcoholic fatty liver disease among community-dwelling middle-aged and older adults.

BACKGROUND: The specific microbiota and associated metabolites linked to non-alcoholic fatty liver disease (NAFLD) are still controversial. Thus, we aimed to understand how the core gut microbiota and metabolites impact NAFLD. METHODS: The data for the discovery cohort were collected from the Guangzhou Nutrition and Health Study (GNHS) follow-up conducted between 2014 and 2018. We collected 272 metadata points from 1546 individuals. The metadata were input into four interpretable machine learning models to identify important gut microbiota associated with NAFLD. These models were subsequently applied to two validation cohorts [the internal validation cohort (n = 377), and the prospective validation cohort (n = 749)] to assess generalizability. We constructed an individual microbiome risk score (MRS) based on the identified gut microbiota and conducted animal faecal microbiome transplantation experiment using faecal samples from individuals with different levels of MRS to determine the relationship between MRS and NAFLD. Additionally, we conducted targeted metabolomic sequencing of faecal samples to analyse potential metabolites. RESULTS: Among the four machine learning models used, the lightGBM algorithm achieved the best performance. A total of 12 taxa-related features of the microbiota were selected by the lightGBM algorithm and further used to calculate the MRS. Increased MRS was positively associated with the presence of NAFLD, with odds ratio (OR) of 1.86 (1.72, 2.02) per 1-unit increase in MRS. An elevated abundance of the faecal microbiota (f__veillonellaceae) was associated with increased NAFLD risk, whereas f__rikenellaceae, f__barnesiellaceae, and s__adolescentis were associated with a decreased presence of NAFLD. Higher levels of specific gut microbiota-derived metabolites of bile acids (taurocholic acid) might be positively associated with both a higher MRS and NAFLD risk. FMT in mice further confirmed a causal association between a higher MRS and the development of NAFLD. CONCLUSIONS: We confirmed that an alteration in the composition of the core gut microbiota might be biologically relevant to NAFLD development. Our work demonstrated the role of the microbiota in the development of NAFLD.

The microbiological outcomes of culture-negative blood specimens using 16S rRNA broad-range PCR sequencing: a retrospective study in a Canadian province from 2018 to 2022.

Broad-range 16S rRNA PCR and sequencing of 1,183 blood specimens from 853 unique patients yielded an interpretable sequence and bacterial identification in 29%, 16S rRNA amplification with uninterpretable sequences in 53%, and no amplification in 18%. This study highlights the potential utility of this technique in identifying fastidious gram-negative and anaerobic bacteria but the frequent recovery of environmental and contaminant organisms argues for its judicious use. IMPORTANCE: The existing literature focuses on its performance compared to blood cultures in patients with sepsis, leaving a gap in the literature regarding other blood specimens in suspected infectious syndrome across the severity spectrum. We aimed to characterize its microbiological outcomes and provide insight into its potential clinical utility.

Broad-range amplification and sequencing of the rpoB gene: a novel assay for bacterial identification in clinical microbiology.

The rpoB gene has been proposed as a promising phylogenetic marker for bacterial identification, providing theoretically improved species-level resolution compared to the 16S rRNA gene for a range of clinically important taxa. However, its utility in diagnostic microbiology has been limited by the lack of broad-range primers allowing for its amplification from most species with a single PCR assay. Here, we present an assay for broad-range partial amplification and Sanger sequencing of the rpoB gene. To reduce cross-reactivity and allow for rpoB amplification directly from patient samples, primers were based on the dual priming oligonucleotide principle. The resulting amplicon is ~550 base pairs in length and appropriate for species-level identification. Systematic in silico evaluation of a wide selection of taxa demonstrated improved resolution within multiple important genera, including Enterococcus, Fusobacterium, Mycobacterium, Streptococcus, and Staphylococcus species and several genera within the Enterobacteriaceae family. Broad-range rpoB amplification and Sanger sequencing of 115 bacterial isolates provided unambiguous species-level identification for 97 (84%) isolates, as compared to 57 (50%) using a clinical 16S rRNA gene assay. Several unresolved taxonomic matters disguised by the low resolution of the 16S rRNA gene were revealed using the rpoB gene. Using a collection of 33 clinical specimens harboring bacteria and assumed to contain high concentrations of human DNA, the rpoB assay identified the pathogen in 29 specimens (88%). Broad-range rpoB amplification and sequencing provides a promising tool for bacterial identification, improving discrimination between closely related species and making it amenable for use in culture-based and culture-independent diagnostic approaches.

The universally conserved nucleotides of the small subunit ribosomal RNAs.

The ribosomal RNAs, along with their substrates the transfer RNAs, contain the most highly conserved nucleotides in all of biology. We have assembled a database containing structure-based alignments of sequences of the small-subunit rRNAs from organisms that span the entire phylogenetic spectrum, to identify the nucleotides that are universally conserved. In its simplest (bacterial and archaeal) forms, the small-subunit rRNA has ∼1500 nt, of which we identify 140 that are absolutely invariant among the 1961 species in our alignment. We examine the positions and detailed structural and functional interactions of these universal nucleotides in the context of a half century of biochemical and genetic studies and high-resolution structures of ribosome functional complexes. The vast majority of these nucleotides are exposed on the subunit interface surface of the small subunit, where the functional processes of the ribosome take place. However, only 40 of them have been directly implicated in specific ribosomal functions, such as contacting the tRNAs, mRNA, or translation factors. The roles of many other invariant nucleotides may serve to constrain the positions and orientations of those nucleotides that are directly involved in function. Yet others can be rationalized by participation in unusual noncanonical tertiary structures that may uniquely allow correct folding of the rRNA to form a functional ribosome. However, there remain at least 50 nt whose universal conservation is not obvious, serving as a metric for the incompleteness of our understanding of ribosome structure and function.

Analysis of differences in intestinal flora associated with different BMI status in colorectal cancer patients.

BACKGROUND: Overweight is known to be an important risk factor for colorectal cancer (CRC), and the differences in intestinal flora among CRC patients with different BMI status have not been clearly defined. The purpose of this study was to elucidate the differences in the abundance, composition and biological function of intestinal flora in CRC patients with different BMI status. METHOD: A total of 170 CRC patients were included and grouped according to the BMI data of CRC patients. BMI ≥ 24 kg/m2 was defined as overweight group, and BMI within the range of 18.5-23.9 kg/m2 was defined as normal weight group. Preoperative stool collection of patients in both groups was used for 16S rRNA sequencing. Total RNA was extracted from 17 CRC tumor tissue samples for transcriptome sequencing, and then CIBERSORT algorithm was used to convert the transcriptome data into the relative content matrix of 22 kinds of immune cells, and the correlation between different intestinal flora and immune cells and immune-related genes under different BMI states was analyzed. Finally, we identified BMI-related differential functional pathways and analyzed the correlation between these pathways and differential intestinal flora. RESULT: There was no significant difference in α diversity and ß diversity analysis between overweight group and normal weight group. Partial least square discriminant analysis (PLS-DA) could divide the flora into two different clusters according to BMI stratification. A total of 33 BMI-related differential flora were identified by linear discriminant effect size analysis (LEfSe), among which Actinomyces, Desulfovibrio and Bacteroides were significantly enriched in overweight group. ko00514: Other types of O-glycan biosynthesis are significantly enriched in overweight group. There was a significant positive correlation between Clostridium IV and Macrophages M2 and T cells regulatory (Tregs). There was a significant negative correlation with Dendritic cells activated and T cells CD4 memory activated. CONCLUSIONS: The richness and diversity of intestinal flora of CRC patients may be related to different BMI status, and the enrichment of Actinomyces, Desulphurvibrio and Bacteroides may be related to overweight status of CRC patients. The tumor microenvironment in which BMI-related differential flora resides has different immune landscapes, suggesting that some intestinal flora may affect the biological process of CRC by regulating immune cell infiltration and immune gene expression, but further experiments are needed to confirm this.

Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer.

BACKGROUND: The aim of this study was to assess the microbial variations and biomarkers in the vaginal and oral environments of patients with human papillomavirus (HPV) and cervical cancer (CC) and to develop novel prediction models. MATERIALS AND METHODS: This study included 164 samples collected from both the vaginal tract and oral subgingival plaque of 82 women. The participants were divided into four distinct groups based on their vaginal and oral samples: the control group (Z/KZ, n = 22), abortion group (AB/KAB, n = 17), HPV-infected group (HP/KHP, n = 21), and cervical cancer group (CC/KCC, n = 22). Microbiota analysis was conducted using full-length 16S rDNA gene sequencing with the PacBio platform. RESULTS: The vaginal bacterial community in the Z and AB groups exhibited a relatively simple structure predominantly dominated by Lactobacillus. However, CC group shows high abundances of anaerobic bacteria and alpha diversity. Biomarkers such as Bacteroides, Mycoplasma, Bacillus, Dialister, Porphyromonas, Anaerococcus, and Prevotella were identified as indicators of CC. Correlations were established between elevated blood C-reactive protein (CRP) levels and local/systemic inflammation, pregnancy, childbirth, and abortion, which contribute to unevenness in the vaginal microenvironment. The altered microbial diversity in the CC group was confirmed by amino acid metabolism. Oral microbial diversity exhibited an inverse pattern to that of the vaginal microbiome, indicating a unique relationship. The microbial diversity of the KCC group was significantly lower than that of the KZ group, indicating a link between oral health and cancer development. Several microbes, including Fusobacterium, Campylobacter, Capnocytophaga, Veillonella, Streptococcus, Lachnoanaerobaculum, Propionibacterium, Prevotella, Lactobacillus, and Neisseria, were identified as CC biomarkers. Moreover, periodontal pathogens were associated with blood CRP levels and oral hygiene conditions. Elevated oral microbial amino acid metabolism in the CC group was closely linked to the presence of pathogens. Positive correlations indicated a synergistic relationship between vaginal and oral bacteria. CONCLUSION: HPV infection and CC impact both the vaginal and oral microenvironments, affecting systemic metabolism and the synergy between bacteria. This suggests that the use of oral flora markers is a potential screening tool for the diagnosis of CC.