Marine organisms often form symbiotic relationships with various microorganisms to adapt and thrive in harsh environments. These symbiotic microbes contribute to host survival by providing nutrition, modulating the hosts’ immune system, and supporting overall physiological stability. Advances in high-throughput sequencing technologies have enabled a deeper understanding of the structure and function of symbiotic microbial communities, as well as host-microbe interactions. Notably, symbiotic bacteria associated with marine invertebrates such as corals and sponges are recognized as a potential source of useful bioactive compounds, including antibiotics and enzymes. However, obtaining high-quality microbial DNA from host tissues still remains a technical challenge due to the presence of unknown substances. This study focuses on optimizing sample preparation and DNA extraction procedures and additional purification to improve the recovery of microbial DNA while minimizing host DNA contamination. Comparison between several methods was conducted using sponge samples to evaluate DNA quality and microbial recovery. A sample designated as 2110BU-001 was collected from the east coast of the Republic of Korea and used for culture-independent microbial cell isolation. Total bacterial DNA was extracted by using a manual Phenol-Chloroform protocol and three commercial kits. DNA extracted using the standard manual method showed both the highest yield and the largest fragment size. However, PCR (Polymerase chain reaction) test showed that quality of manually extracted DNA was not enough for sequencing. Therefore, the quality of DNA was improved through additional purification steps. Briefly, host eukaryotic cells were removed by mechanical process and almost only bacterial DNA was successfully obtained by combination of manual extraction method and further purification processes. The established protocol was successfully introduced to extraction of metagenomic DNA from mussel and jellyfish microbiomes, indicating that it can be widely applied to various marine organisms.
This study aimed to determine if the microbiota in four different oral sites and the oral health status differ between patients with primary Sjögren’s syndrome (pSS), non-pSS sicca symptoms, and healthy controls. All participants underwent an interview and clinical oral examination. Stimulated whole saliva (SWS), supragingival plaque (SGP), buccal mucosa tissue (BLM), and tongue scrape (TGS) samples from 23 pSS patients, 36 patients with sicca symptoms, not fulfilling the classification criteria for pSS (non-pSS sicca), and 21 age-matched healthy controls (HC) were analyzed using V3–V4 16S rRNA gene amplicon sequencing, and determination of amplicon sequence variants (ASVs). PSS and non-pSS sicca patients did not differ with respect to oral health status, saliva flow rates, abundance of predominant genera, relative abundance on genus level or bacterial diversity in any of the oral sites. Both patient groups differed significantly from the healthy control group in the abundance of 61 ASVs across all sites. The alpha-diversity was lower in SGP from non-pSS sicca patients (p = 0.019), and in TGS from pSS patients (p = 0.04). The proportion of variation in the beta-diversity across all four sites could be explained by the diagnosis (pSS, non-pSS sicca, and HC). However, subgrouping of patients according to their stimulated salivary flow rates (SWS > 0.7 ml/min versus SWS ≤ 0.7 ml/min), revealed significantly different abundance of three ASVs in SWS, 11 in SGP, and six in TGS. Our findings suggest that hyposalivation rather than pSS itself modifies the microbial composition in oral site-specific patterns leading to oral diseases.
Gout is an inflammatory arthritis resulting from the deposition of monosodium urate crystals. Urate-lowering therapies for gout have limitations, including side effects and limited efficacy, highlighting the need for novel therapeutic approaches to improve patient outcomes. In this context, our research team conducted a microbiome analysis of fecal samples from healthy individuals and gout patients, identifying Bifidobacterium as a key biomarker. Subsequently, we isolated and identified this strain, B. longum PMC72, and demonstrated its efficacy in a gout mouse model. In potassium oxonate (PO)-induced hyperuricemia mice, PMC72 significantly alleviated nausea, gait disturbances, ankle inflammation, and improved renal health. These effects were associated with marked reductions in oxidative stress markers, including serum uric acid, blood urea nitrogen, hepatic xanthine oxidase, and malondialdehyde (MDA) levels in serum, liver, and joint samples, as well as the downregulation of inflammation and uric acid transport-related gene expression in kidney samples. These benefits were comparable to those treated with Febuxostat, a standard urate-lowering therapy for gout. Furthermore, gut microbiome analysis revealed that PMC72 restored dysbiosis induced by hyperuricemia, contrasting with the reduced microbial diversity observed with febuxostat alone, and showed a complete recovery to eubiosis when combined with Febuxostat. These findings position PMC72 as a promising microbial therapeutic candidate for gout management, demonstrating significant development potential and serving as a benchmark for reverse translational microbiome-based therapeutic research.
Synbiotics have become a new-age treatment tool for limiting the progression of metabolic dysfunction-associated steatotic liver disease; however, inclusive comparisons of various synbiotic treatments are still lacking. Here, we have explored and evaluated multiple synbiotic combinations incorporating three distinctive prebiotics, lactitol, lactulose and fructooligosaccharides. Of the synbiotic treatments evaluated, a combination of fructooligosaccharides and probiotics (FOS+Pro) exhibited superior protection against western diet-induced liver degeneration. This synbiotic (FOS+Pro) combination resulted in the lowest body weight gains, liver weights and liver/body weight ratios. The FOS+Pro synbiotic combination substantially alleviated liver histopathological markers and reduced serum AST and cholesterol levels. FOS+Pro ameliorated hepatic inflammation by lowering expression of proinflammatory markers including TNF-α, IL-1β, IL-6, and CCL2. FOS+Pro significantly improved steatosis by restricting the expression of lipid metabolic regulators (ACC1, FAS) and lipid transporters (CD36) in the liver. These findings are critical in suggesting that synbiotic treatments are capable of restraining western diet-induced metabolic dysfunction in the liver. Additionally, this study demonstrated that adding probiotic strains amplified the effectiveness of fructooligosaccharides but not all prebiotics.
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This review explores current advancements in microbiome functional analysis enabled by next-generation sequencing technologies, which have transformed our understanding of microbial communities from mere taxonomic composition to their functional potential. We examine approaches that move beyond species identification to characterize microbial activities, interactions, and their roles in host health and disease. Genome-scale metabolic models allow for in-depth simulations of metabolic networks, enabling researchers to predict microbial metabolism, growth, and interspecies interactions in diverse environments. Additionally, computational methods for predicting metabolite profiles offer indirect insights into microbial metabolic outputs, which is crucial for identifying biomarkers and potential therapeutic targets. Functional pathway analysis tools further reveal microbial contributions to metabolic pathways, highlighting alterations in response to environmental changes and disease states. Together, these methods offer a powerful framework for understanding the complex metabolic interactions within microbial communities and their impact on host physiology. While significant progress has been made, challenges remain in the accuracy of predictive models and the completeness of reference databases, which limit the applicability of these methods in under-characterized ecosystems. The integration of these computational tools with multi-omic data holds promise for personalized approaches in precision medicine, allowing for targeted interventions that modulate the microbiome to improve health outcomes. This review highlights recent advances in microbiome functional analysis, providing a roadmap for future research and translational applications in human health and environmental microbiology.
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Systemic sclerosis (SSc) is a chronic autoimmune disorder characterised by skin fibrosis and internal organ involvement. Disruptions in the microbial communities on the skin may contribute to the onset of autoimmune diseases that affect the skin. However, current research on the skin microbiome in SSc is lacking. This study aimed to investigate skin microbiome associated with disease severity in SSc. Skin swabs were collected from the upper limbs of 46 healthy controls (HCs) and 36 patients with SSc. Metagenomic analysis based on the 16S rRNA gene was conducted and stratified by cutaneous subtype and modified Rodnan skin score (mRSS) severity. Significant differences in skin bacterial communities were observed between the HCs and patients with SSc, with further significant variations based on subtype and mRSS severity. The identified biomarkers were Bacteroides and Faecalibacterium for patients with diffuse cutaneous SSc with high mRSS (≥ 10) and Mycobacterium and Parabacteroides for those with low mRSS (< 10). Gardnerella, Abies, Lactobacillus, and Roseburia were the biomarkers in patients with limited cutaneous SSc (lcSS) and high mRSS, whereas Coprococcus predominated in patients with lcSS and low mRSS. Cutaneous subtype analysis identified Pediococcus as a biomarker in the HCs, whereas mRSS analysis revealed the presence of Pseudomonas in conjunction with Pediococcus. In conclusion, patients with SSc exhibit distinct skin microbiota compared with healthy controls. Bacterial composition varies by systemic sclerosis cutaneous subtype and skin thickness.
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