Correlation between the facial skin microbiome and sensitive skin using the 2bRAD-M technique.

OBJECTIVE: This study aimed to expound on the correlation between facial skin microbiome and sensitive skin (SS) using a novel sequencing technique. METHODS: We applied the 2bRAD sequencing for the microbiome, which enables accurate characterization of the low-biomass microbiome at species resolution to profile facial skin microbes in SS and non-SS groups. Further, the bacterial colonies were isolated and cultured from skin surfaces to study the pro-inflammatory effect on human keratinocytes by ELISA. RESULTS: We accordingly identified 1142 genera and 4436 strains. In the SS group, the proportions of Actinomyces and Microbotryomycetes were significantly increased, whereas that of Acidimicrobiia was decreased. Kruskal-Wallis analysis revealed significant differences in 11 genera and 35 species, among which the proportions of Dermabacter, Chryseobacterium, Rhodotorula and Peptoniphilus A were increased in the SS group. Analysis of the top 10 genera revealed increased proportions of Cutibacterium, Corynebacterium and Staphylococcus. Moreover, the proportion of Dermabacter hominis was significantly increased by 18.9-fold in the SS group, whereas those of many Streptococcus strains were significantly decreased. Focus on the isolated bacterial colonies from skin surfaces, more yellow colonies were found in SS group when cultured in Tryptic Soy Broth medium for 48 h, and more interleukin-8 was detected on keratinocytes after yellow colonies stimulation, such as S.capitis, M.luteus. CONCLUSIONS: This study suggests that more SS-associated microorganisms can be identified using the 2bRAD technique even with a small sample size. Dermabacter hominis and Chryseobacterium was firstly reported with a significantly increase in SS, and the S.capitis, as well as M.luteus, but not S.aureus, may be associated with skin inflammation.

OBJECTIF: Cette étude visait à expliquer la corrélation entre le microbiome de la peau du visage et la peau sensible (PS) à l'aide d'une nouvelle technique de séquençage. MÉTHODES: Nous avons appliqué le séquençage 2bRAD pour le microbiome, ce qui nous a permis de caractériser précisément le microbiome à faible biomasse à la résolution des espèces pour profiler les microbes de la peau du visage dans les groupes PS et non­PS. En outre, les colonies bactériennes ont été isolées et cultivées à partir de surfaces cutanées pour étudier l'effet pro­inflammatoire sur les kératinocytes humains par ELISA. RÉSULTATS: Nous avons donc identifié 1 142 genres et 4 436 souches. Dans le groupe PS, on a pu constater des proportions d'Actinomyces et de microbotryomycètes significativement accrues, pour de moindres proportions d'Acidimicrobiia. L'analyse de Kruskal­Wallis a révélé des différences significatives dans 11 genres et 35 espèces, parmi lesquelles des proportions de Dermabacter, Chryseobacterium, Rhodotorula et Peptoniphilus A accrues dans le groupe PS. L'analyse des 10 principaux genres a montré une augmentation des proportions de Cutibacterium, Corynebacterium et Staphylococcus. En outre, la proportion de Dermabacter hominis a été multipliée par 18,9 dans le groupe PS, soit une augmentation significative, tandis que celle de nombreuses souches de Streptococcus s'est avérée significativement plus basse. En se concentrant sur les colonies bactériennes isolées des surfaces cutanées, plus de colonies jaunes ont été trouvées dans le groupe PS lorsqu'elles étaient cultivées dans du milieu de bouillon trypticase soja pendant 48 h, et davantage d'interleukine­8 a été détectée sur les kératinocytes après la stimulation des colonies jaunes comme S. capitis, M. luteus. CONCLUSIONS: Cette étude suggère que davantage de micro­organismes associés au PS peuvent être identifiés à l'aide de la technique 2bRAD, même avec un échantillon de petite taille. Dermabacter hominis et Chryseobacterium ont été rapportés avec une augmentation significative pour les PS, et S. capitis, ainsi que M. luteus, mais pas S. aureus, pouvant être associés à une inflammation cutanée.

The renal pelvis urobiome in the unilateral kidney stone patients revealed by 2bRAD-M.

BACKGROUND: The pathogenesis of kidney stone disease (KSD) is not fully understood, and potential contributing factors remain to be explored. Several studies have revealed that the urinary microbiome (urobiome) of stone formers was distinct from that of healthy individuals using 16S rRNA gene sequencing, most of which only provided microbial identification at the genus level. 2bRAD sequencing for Microbiome (2bRAD-M) is a novel sequencing technique that enables accurate characterization of the low-biomass microbiome at the species resolution. We aimed to apply 2bRAD-M to profile the renal pelvis urobiome of unilateral kidney stone patients and compared the urobiome with and without stone(s). METHOD: A total of 30 patients with unilateral stones were recruited, and their renal pelvis urine from both sides was collected. A ureteroscope was inserted into the renal pelvis with stone(s) and a ureteral catheter was placed into the ureteroscope to collect renal pelvis urine. This procedure was repeated again with new devices to collect the urine of the other side. 2bRAD-M was performed to characterize the renal pelvis urobiome of unilateral stone formers to explore whether microbial differences existed between the stone side and the non-stone side. RESULTS: The microbial community composition of the stone side was similar to that of the non-stone side. Paired comparison showed that Corynebacterium was increased and Prevotella and Lactobacillus were decreased in the stone side. Four species (Prevotella bivia, Lactobacillus iners, Corynebacterium aurimucosum, and Pseudomonas sp_286) were overrepresented in the non-stone side. 24 differential taxa were also identified between two groups by linear discriminant analysis effect size (LEfSe). Extensive and close connections among genera and species were observed in the correlation analysis. Moreover, a random forest classifier was constructed using specific enriched species, which can distinguish the stone side from the non-stone side with an accuracy of 71.2%. CONCLUSION: This first 2bRAD-M microbiome survey gave an important hint towards the potential role of urinary dysbiosis in KSD and provided a better understanding of mechanism of stone formation.

Gallbladder microbial species and host bile acids biosynthesis linked to cholesterol gallstone comparing to pigment individuals.

Gallstones are crystalline deposits in the gallbladder that are traditionally classified as cholesterol, pigment, or mixed stones based on their composition. Microbiota and host metabolism variances among the different types of gallstones remain largely unclear. Here, the bile and gallstone microbial species spectra of 29 subjects with gallstone disease (GSD, 24 cholesterol and 5 pigment) were revealed by type IIB restriction site-associated DNA microbiome sequencing (2bRAD-M). Among them (21 subjects: 18 cholesterol and 3 pigment), plasma samples were subjected to liquid chromatography-mass spectrometry (LC-MS) untargeted metabolomics. The microbiome yielded 896 species comprising 882 bacteria, 13 fungi, and 1 archaeon. Microbial profiling revealed significant enrichment of Cutibacterium acnes and Microbacterium sp005774735 in gallstone and Agrobacterium pusense and Enterovirga sp013044135 in the bile of cholesterol GSD subjects. The metabolome revealed 2296 metabolites, in which malvidin 3-(6''-malonylglucoside), 2-Methylpropyl glucosinolate, and ergothioneine were markedly enriched in cholesterol GSD subjects. Metabolite set enrichment analysis (MSEA) demonstrated enriched bile acids biosynthesis in individuals with cholesterol GSD. Overall, the multi-omics analysis revealed that microbiota and host metabolism interaction perturbations differ depending on the disease type. Perturbed gallstone type-related microbiota may contribute to unbalanced bile acids metabolism in the gallbladder and host, representing a potential early diagnostic marker and therapeutic target for GSD.

Interactions and effects of a stannous-containing sodium fluoride dentifrice on oral pathogens and the oral microbiome.

Numerous studies have investigated the effects of stannous ions on specific microbes and their efficacy in reducing dental plaque. Nonetheless, our understanding of their impact on the oral microbiome is still a subject of ongoing exploration. Therefore, this study sought to evaluate the effects of a stannous-containing sodium fluoride dentifrice in comparison to a zinc-containing sodium fluoride dentifrice and a control group on intact, healthy oral biofilms. Utilizing the novel 2bRAD-M approach for species-resolved metagenomics, and FISH/CLSM with probes targeting periodontal and caries associated species alongside Sn2+ and Zn2+ ions, we collected and analyzed in situ biofilms from 15 generally healthy individuals with measurable dental plaque and treated the biofilms with dentifrices to elucidate variations in microbial distribution. Although significant shifts in the microbiome upon treatment were not observed, the use of a stannous-containing sodium fluoride dentifrice primarily led to an increase in health-associated commensal species and decrease in pathogenic species. Notably, FISH/CLSM analysis highlighted a marked reduction in representative species associated with periodontitis and caries following treatment with the use of a stannous-containing sodium fluoride dentifrice, as opposed to a zinc-containing sodium fluoride dentifrice and the control group. Additionally, Sn2+ specific intracellular imaging reflected the colocalization of Sn2+ ions with P. gingivalis but not with other species. In contrast, Zn2+ ions exhibited non-specific binding, thus suggesting that Sn2+ could exhibit selective binding toward pathogenic species. Altogether, our results demonstrate that stannous ions could help to maintain a healthy oral microbiome by preferentially targeting certain pathogenic bacteria to reverse dysbiosis and underscores the importance of the continual usage of such products as a preventive measure for oral diseases and the maintenance of health.

2bRAD-M reveals the difference in microbial distribution between cancerous and benign ovarian tissues.

The development of ovarian cancer is closely related to various factors, such as environmental, genetic and microbiological factors. In previous research, bacteria were identified in human tumors by 16S rRNA sequencing. However, the microbial biomass in tumor tissue is too low and cannot be accurately identified by 16S rRNA sequencing. In our study, we employ 2bRAD sequencing for Microbiome (2bRAD-M), a new sequencing technology capable of accurately characterizing the low biomass microbiome (bacteria, fungi and archaea) at species resolution. Here we surveyed 20 ovarian samples, including 10 ovarian cancer samples and 10 benign ovarian samples. The sequencing results showed that a total of 373 microbial species were identified in both two groups, of which 90 species shared in the two groups. The Meta statistic indicated that Chlamydophila_abortus and CAG-873_sp900550395 were increased in the ovarian cancer tissues, while Lawsonella_clevelandensis_A, Ralstonia_sp001078575, Brevundimonas_aurantiaca, Ralstonia_sp900115545, Ralstonia_pickettii, Corynebacterium_kefirresidentii, Corynebacterium_sp000478175, Brevibacillus_D_fluminis, Ralstonia_sp000620465, and Ralstonia_mannitolilytica were more abundant in the benign ovarian tissues. This is the first use of 2bRAD-M technique to provide an important hint for better understanding of the ovarian cancer microbiome.

Identification of Two Clusters in Renal Pelvis Urobiome of Unilateral Stone Formers Using 2bRAD-M.

Urolithiasis is a common urological disease with increasing incidence and a high recurrence rate, whose etiology is not fully understood. The application of sequencing and culturomics has revealed that urolithiasis is closely related to the urinary microbiome (urobiome), shedding new light on the pathogenesis of stone formation. In this study, we recruited 30 patients with unilateral stones and collected their renal pelvis urine from both sides. Then, we performed 2bRAD-M, a novel sequencing technique that provides precise microbial identification at the species level, to characterize the renal pelvis urobiome of unilateral stone formers in the both sides. We first found that the urobiome in the stone side could be divided into two clusters (Stone1 and Stone2) based on distance algorithms. Stone2 harbored higher microbial richness and diversity compared to Stone1. The genera Cupriavidus and Sphingomonas were overrepresented in Stone1, whereas Acinetobacter and Pseudomonas were overrepresented in Stone2. Meanwhile, differential species were identified between Stone1 and Stone2. We further constructed a random forest model to discriminate two clusters which achieved a powerful diagnostic potential. Moreover, the urobiome of the non-stone side (Control1/2) was compared with that of the stone side (Stone1/2). Stone1 and Control1 showed different microbial community distributions, while Stone2 was similar to Control2 based on diversity analysis. We also identified differentially abundant species among all groups. We assumed that there might be different mechanisms of how microbiota contribute to stone formation in two clusters. Our findings might assist in the selection of suitable medical treatments for urolithiasis.

The bladder microbiome of NMIBC and MIBC patients revealed by 2bRAD-M.

Background: Bladder cancer (BCa) is the most common malignancy of the urinary tract which can be divided into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), and their microbial differences are not fully understood. This study was conducted by performing 2bRAD sequencing for Microbiome (2bRAD-M) on NMIBC and MIBC tissue samples to investigate the microbiota differences between NMIBC and MIBC individuals. Methods: A total of 22 patients with BCa, including 7 NMIBC and 15 MIBC, were recruited. Tumor tissues were surgically removed as samples and DNA was extracted. Type IIB restriction endonucleases were used to enzymatically cleave the microbial genome for each microbe's tag and map it to species-specific 2bRAD markers to enable qualitative and quantitative studies of microbes between MIBC and NMIBC tissues. Results: A total of 527 species were detected. The microbial diversity of NMIBC tissues was significantly higher than that of MIBC tissues. Microbial composition of the two tumor tissues was similar, where Ralstonia_sp000620465 was the most dominant species. 4 species (Acinetobacter_guillouiae, Anoxybacillus_A_rupiensis, Brevibacillus_agri and Staphylococcus_lugdunensis) were enriched in NMIBC, while Ralstonia_mannitolilytica, Ralstonia_pickettii, and Ralstonia_sp000620465 were overrepresented in MIBC. 252 discriminatory character taxa were also revealed by linear discriminant analysis effect sizea (LEfSe). Species importance point plots identified Ralstonia_sp000620465, Cutibacterium_acnes and Ralstonia_pickettii as the three most important species between the two groups. Meanwhile, functional annotation analysis showed 3011 different COGs and 344 related signaling pathways between MIBC and NMIBC microbiome. Conclusion: This first 2bRAD-M microbiome study on MIBC and NMIBC tissues revealed significant differences in the microbial environment between the two groups, which implies a potential association between tumor microbial dysbiosis and BCa, and provides a possible target and basis for subsequent studies on the mechanisms of BCa development and progression.

Both symbionts and environmental factors contribute to shape the microbiota in a pest insect, Sogatella furcifera.

Introduction: Bacterial symbionts are prevalent in arthropods globally and play a vital role in the fitness and resistance of hosts. While several symbiont infections have been identified in the white-backed planthopper Sogatella furcifera, the impact of environmental factors on the microbiota within S. furcifera remains elusive. Methods: In this study, a total of 142 S. furcifera individuals from 18 populations were collected from 14 locations across six countries (China, Thailand, Myanmar, Cambodia, Vietnam, and Laos) analyzed with 2bRAD-M sequencing, to examine the effects of symbionts on the microbiota in the S. furcifera population, as well as the vital effects of environmental factors on the bacterial communities. Results and discussion: Based on the results, in S. furcifera, the presence of symbionts Wolbachia and Cardinium negatively influenced the abundance of other bacteria, including Enterobacter, Acinetobacter, and Lysinibacillus, while Wolbachia infection significantly decreased the diversity of the microbial community. Moreover, several environmental factors, including longitude, latitude, temperature, and precipitation, affected the abundance of symbionts and microbiota diversity in S. furcifera. These results collectively highlight the vital role of Wolbachia in S. furcifera microbiota, as well as the intricate effects of environmental factors on the bacterial communities of S. furcifera.

Microbial signatures of neonatal bacterial meningitis from multiple body sites.

As a common central nervous system infection in newborns, neonatal bacterial meningitis (NBM) can seriously affect their health and growth. However, although metagenomic approaches are being applied in clinical diagnostic practice, there are some limitations for whole metagenome sequencing and amplicon sequencing in handling low microbial biomass samples. Through a newly developed ultra-sensitive metagenomic sequencing method named 2bRAD-M, we investigated the microbial signatures of central nervous system infections in neonates admitted to the neonatal intensive care unit. Particularly, we recruited a total of 23 neonates suspected of having NBM and collected their blood, cerebrospinal fluid, and skin samples for 2bRAD-M sequencing. Then we developed a novel decontamination method (Reads Level Decontamination, RLD) for 2bRAD-M by which we efficiently denoised the sequencing data and found some potential biomarkers that have significantly different relative abundance between 12 patients that were diagnosed as NBM and 11 Non-NBM based on their cerebrospinal fluid (CSF) examination results. Specifically, we discovered 11 and 8 potential biomarkers for NBM in blood and CSF separately and further identified 16 and 35 microbial species that highly correlated with the physiological indicators in blood and CSF. Our study not only provide microbiological evidence to aid in the diagnosis of NBM but also demonstrated the application of an ultra-sensitive metagenomic sequencing method in pathogenesis study.