Genomics, Proteomics & Bioinformatics

The gut microbiota of intensive care unit (ICU) patients display extreme dysbiosis, which is associated with increased susceptibility to organ failure, sepsis and septic shock. However, this dysbiosis is hard to be characterized for each patient, owing to the highly dimensional complexity of gut microbiota. We thus tested whether the concept of enterotype can be applied to the gut microbiota of ICU patients, to describe the dysbiosis. We collected 131 fecal samples from a cohort of 64 ICU patients diagnosed with sepsis or septic shock, using 16S rRNA gene sequencing to dissect their gut microbiota compositions. We find that during the development of sepsis or septic shock, as well as various medical treatments, ICU patients always contain two patterns of dysbiotic microbiota named as ICU-enterotypes, which cannot be explained by the individual host properties such as age, gender and body mass index, as well as external stressors such as infection sites and antibiotic use. ICU-enterotype I comprised predominantly Bacteroides and an unclassified genus of family Enterobacteriaceae, while ICU-enterotype II comprised predominantly Enterococcus. Among more critically ill patients with acute physiology and chronic health evaluation (APACHE) II score > 18, samples of septic shock were more likely to present with ICU-enterotype I (p = 0.041). Additionally, ICU-enterotype I was correlated with high serum lactate level (p = 0.007). Therefore, different patterns of dysbiosis are correlated with different clinical outcomes, suggesting that the diagnosis of ICU-enterotypes as an independent clinical index is crucial. For this purpose, the microbial-based human index (MHI) classifier we proposed shows high precision and effectiveness in timely monitoring of ICU-enterotypes of an individual patient. Together, our work serves as the first step toward precision medicine for septic patients based on the gut microbiota profile.

We aimed to characterize the relationship of the oral microbiome with diabetes in Pakistan. Saliva samples were collected from diabetic patients (n = 49) and healthy individuals (n = 55). 16S metagenomics saliva was carried out by NGS technology. We observed that the phylum Firmicutes (p-value = 0.024 at 95% confidence interval) was significantly more abundant among diabetic patients than among the controls. We found that the abundance of phylum Actinobacteria did not significantly vary among both groups in contrast to a similar report from the USA (Long et al., 2017). On genus level, acidogenic bacteria Prevotella (p-value = 0.024) and Leptotrichia (p-value = 1.5 x 10-3); and aciduric bacteria Veillonella (p-value = 0.013) were found to be in higher abundance in diabetic patients. These bacteria are found in dental biofilm and involved in the metabolism of fermentable carbohydrates. Stratified analysis by gender revealed healthy and diabetic females to be more divergent. Abundance of Prevotella (p-value = 4.4 x 10-3) and Leptotrichia (p-value = 0.015) was significantly associated with male patients. A comparison of oral bacteriome between two groups revealed the dominance of acidogenic and aciduric bacteria in diabetics which suggested the involvement of these eubacteria in oral dysbacteriosis in diabetes mellitus.

Clinical staging diagnosis and progression tracking for ulcerative colitis (UC) is challenging as poor patient compliance of endoscopic biopsy, we aimed to explore a non-invasive integrative biochemical index to quantitative track and monitor pathological activity. Here we perform a study that integrates bile acid metabolomic profiling, metagenomic sequencing and clinical monitoring on serum and feacal samples from 24 active-state UC patients, 25 remission-state UC patients and 20 healthy volunteers from China. Besides known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with UC, we found several bile acid-transforming species, including 7-dehydroxygenase and 7/{beta}-dehydrogenase expressing microbiota, were significant correlated with UC pathological activity. We identified 7 microbial gene markers that differentiated active and remission-stage UC and healthy control microbiomes. Relevantly, decreased serum deoxycholic acid /cholic acid ratio and increased fecal ursodeoxycholic acid/chenodeoxycholic acid ratio were associated with pathological activity of UC. Moreover, receiver operating characteristic analysis based on serum/fecal bile acids ratios was much accurate in prediction of active and remission stage outcome. This species-specific temporal change and bile acid dysregulation pattern linked to disease severity indicating that integrated microbiome-bile acid profile maybe implied for disease activity prediction, and that targeting microbiome-mediated restoring gut flora and bile acids homeostasis may be implicative of therapy efficacy. Collectively, these insights will help improve clinical diagnosis and optimize existing medical treatments.

Very few 16S rRNA-based studies have conducted a simultaneous analysis to identify the impact of various dental and periodontal parameters and determine which of them have the greatest repercussion for the salivary microbiota. Consequently, this study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental, periodontal and global oral disease. Our global oral health scale was used to produce a convenience sample of 81 patients from 270 who were initially recruited. These subjects were assigned the following grades: 47 had a periodontal grade (PG) of 0 and dental grades (DGs) between 0-3, and 46 had a DG of 0 and PGs between 0-3. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 x 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the Phyloseq, DESeq2 and Microbiome packages. The impact on the salivary microbiota of the different DGs, PGs and global oral grades (GGs) was investigated in relation to: 1) indicators of alpha diversity and the structure of the bacterial community; and 2) the composition of the core microbiome and the results of differential abundance tests. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or global oral disease, especially in high grades. The non-specific microbiome core contains a greater number of more abundant species than the specific core of a particular dental or periodontal condition (health or pathology). The number of taxa in the salivary microbiota with differential abundances between the DGs, PGs or GGs represents, at most, a quarter of the bacterial community and are mainly non-core species. Supragingival dental parameters influence the microbiotas abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that global oral health has on salivary microbiome.

Currently,the treatment of chronic periodontitis (CP) still has challenges. This study aimed to identify novel drug targets for the treatment of chronic periodontitis in the druggable genome using the Mendelian randomization (MR) method.In this study,based on the list of 4479 drug gene targets,overlapping genes were selected in blood expression Quantitative Trait Loci(eQTL), which were then subjected to Two-Sample MR(TSMR) and validated Fusion Transcriptome-Wide Association Study(TWAS) with data from the Genome-Wide Association Study(GWAS) of CP to confirm drug genes genetically associated with CP and tested for multiplicity of effects using Summary-data-based Mendelian randomization(SMR) analysis and colocalisation. Finally, Phenome-Wide association study(PheWAS) was executed on the identified drug targets.We applied SMR,TSMR,Fusion TWAS,and a series of manners of co-localisation to assess the genetic association between drugable targets and CP. In conclusion,Metalloproteinase 25(MMP25)was considered the most promising drug target,in addition to which we maintained some confidence in TNFRSF18,CDC25B,STK10 and ACVR2B.Finally,the PheWAS-MR results showed that the possible side effects of applying MMP25 inhibitors were Otitis externa as well as some metabolic disorders,among others.In summary,we identified five potential CP drug targets using TSMR,Fusion TWAS,SMR,and co-localisation a series of methods,of which MMP25 passed all the tests.Such discovery offered an academic basis for future CP drug development and reduce drug development time and economic costs to some extent.

Betel nut addiction is recognized as the causative agent of oral microbiome dysbiosis and other systematic disorders. A number of betel nut preparations containing ingredients such as slaked lime, catechu extract and tobacco are being commonly used particularly in South Asia. The underlying variations in the oral microbiome due to usage of betel nut preparations are poorly understood. We evaluated salivary microbiome in response to chewing of betel nut preparation(s). In order to assess the microbiome dynamics, metagenomic analysis of 16S rRNA gene (V3-V4 hypervariable region) from salivary bacteria in chewers of betel nut preparation (n = 16) and non-chewers (n = 55) was carried out by Greengenes and SILVA ribosomal sequence databases. It was observed that Gutka chewers demonstrated lower alpha diversity and number of bacterial genera than the non-chewers. Taxonomic assignment on phylum level revealed Firmicutes (p-value = 0.042 at 95% confidence interval) to be significantly more abundant in Gutka chewers in comparison with non-chewers. Beta diversity analysis at genus level by weighted unifrac distance matrices unveiled both groups to be divergent from each other. On the genus level, Veillonella (p-value = 0.015), Streptococcus (p-value = 0.026), Leptotrichia (p-value = 0.022) and Serratia (p-value = 0.022) species appeared to be significantly more abundant in Gutka chewers in comparison to non-chewers. The present study suggests salivary dysbiosis in response to gutka chewing and concludes that gutka chewers possess higher abundance of acidogenic and aciduric bacteria. This study contributes additional information regarding oral microbiome variations with response to gutka consumption.

RNA Sequencing (RNA-Seq) can facilitate prompt and precise management of many illnesses, including infection, especially when coupled with PCR. To further optimize RNA-Seq for the purposes of creating a RNA-Seq-informed PCR test, identifying reliable RNA primer targets is paramount. Essential criteria for constructing RNA primer targets include high gene expression or stability of transcripts. We hypothesize that free energy evaluation and motif analysis can demonstrate gene expression level or stability of transcripts to construct ideal RNA primers for RNA-Seq-informed PCR that can expedite the diagnosis and treatment of infection. Whole blood samples were collected from patients diagnosed with COVID-19 in the ICU at Rhode Island Hospital, stored in Paxgene tubes to preserve the integrity of the specimens, and submitted for RNA-Seq by a commercial sequencing service (Azenta/Genewiz). After quality assurance and quality control (QA/QC) measures are performed, we used RNAfold from the ViennaRNA Package to calculate the minimum free energy (MFE) and ensemble free energy (EFE) values to compare the stability among different secondary structures constructed from RNA-Seq read sequences. Energy parameters for calculations were set at 37 degree Celsius and standard physiological conditions at pH 7.4. In our analysis, we utilized multiple statistical tools, such as analysis of variance, Games-Howell post hoc tests, and a negative binomial regression. Of the 676 reads that aligned with SARS-CoV-2, there were 137 unique sequences among all patients. Among the unique read sequences, the average MFE was -30.46 kcal/mol and the average EFE was -32.94 in kcal/mol. There were 6 genes with these unique read sequences, two of which -- nucleocapsid (N) gene and spike (S) gene -- coded for integral structural proteins. Notably, the mean MFE and EFE of N gene were significantly different from ORF1ab gene (p = 2.81e-7; p = 0.005) and ORF6 gene (p = 0.023; p = 0.03). Our motif analysis demonstrated 7 motifs that corresponded to destabilization of the RNA, and a single motif (MEME-28) that corresponded to stabilization of the RNA. Within the nucleocapsid (N) gene, we found that reads from different regions also differed in stability. Our results demonstrate that the stability of reads from different genes varies in SARS-CoV-2 infections. Free energy evaluation and motif analysis are viable approaches to determine RNA structure stability or levels of differential gene expression. Stable transcripts that are highly expressed can be ideal RNA primers to be used in conjunction with PCR to expedite the management of infection.

BackgroundUlcerative colitis (UC) and irritable bowel syndrome (IBS) are both chronic bowel diseases involving stress. To identify genes differentially expressed in UC and IBS, and to determine whether psychological stress can influence those gene expressions, we conducted this pilot study. MethodsPatients of UC, irritable bowel syndrome (IBS) and normal controls (NC) (n=5 in each group) were recruited. Perceived stress scale (PSS) was adopted to assess psychological stress level. Sigmoid mucosa samples were collected during colonoscopy. Differentially expressed genes (DEGs) of both mRNA and microRNA (DEG-mRNA and DEG-miRNA) were identified by RNA-Seq and microarray, respectively. Weighted gene co-expression network analysis (WGCNA), gene ontology, and microRNA target analysis were performed to identify regulatory relationships and pathways involved. Pearson correlation was performed to identify the relationship between DEGs and PSS score. ResultsIn total, 1,770 and 938 DEG-mRNAs, 107 and 3 DEG-miRNAs were identified in UC and IBS (nominal P<0.05), respectively. The transcriptome changes in UC and IBS were highly correlated but transcriptome severity was larger in UC. There were 268 overlapped DEG-mRNAs and 3 overlapped DEG-miRNAs between UC and IBS. Median PSS score was 27.5 (24.7, 40.0) in UC, 27.0 (17.5, 32.5) in IBS and 22.0 (12.0, 28.5) in NC. Five of the UCs DEG-mRNAs were significantly correlated to PSS scores, including SLC4A7, PLCB1, SPATA33, DECR2, RP11-792A8.4. There were no DEGs correlate with PSS scores in IBS. One module enriched for immunological pathways was upregulated in UC. Metabolic pathways were enriched in IBS. Within the UC-related co-expression module, we identified 18 DEG-mRNAs that were also targets of DEG-miRNA. ConclusionsIntegration of microRNA and mRNA expression profiles identified changes of gene expression in both UC and IBS. Although the two diseases have significant overlapped transcriptomic changes, they have distinct signature. Immunological pathways are involved prominently in UC while metabolic pathways in IBS. Psychological stress is uniquely associated with the transcriptome changes of UC.

Type 2 diabetes and its risk factors such as dyslipidemia and/or obesity enhance severe periodontitis with a poorly understood microbiome. Hence, the purpose of the present study was to describe and compare the subgingival microbiomes of Type 2 diabetes subjects classified by periodontal diseases, to determine the association between periodontal severity and metabolic condition. 71 DNA subgingival samples of 36 subjects were evaluated by Human Oral Microbiome Identification Microarray using 16S rRNA gene-probe. Blood chemistries were obtained to test hemoglobin, and serum lipid profile. Obesity classification was obtained by Body-Mass-Index. Kruskal-Wallis, Mann-Whitney, Spearmans correlation, and Multivariate ordinal logistic-regression (periodontal-severity) test were applied (IBM-SPSS-21/Stata 17). Our results suggest samples of subjects with Gingivitis (n=12) presented with higher Bacteroidetes proportion vs. Generalized Periodontitis grouped by severity Stage-I (n=17, NS), Stage-II (n=30, p<0.05), and Stage-III (n=12, p<0.05); and Generalized Periodontitis Stage-II presented higher Firmicutes proportion (p<0.05_MW_vs._Gingivitis). Human-Microbial-Taxon presented significant higher Score-levels (Levels), frequency (%), or Odds Ratio (OR) of *1Cardiobacterium valvarum_HMT-540, Fusobacterium Cluster-AE01 (Generalized Periodontitis-Stage-I vs. Gingivitis_p<0.001_Levels, OR: 9.1 and 4.7), *2Porphyromonas gingivalis HMT-619 (OR: 4.7), Porphyromonas pasteri_HMT-279 (Gingivitis vs. Generalized Periodontitis-Stage-I and II_p<0.01/p<0.001_Levels), *3Streptococcus constellatus_HMT-576/Streptococcus intermedius_HMT-644 (Generalized Periodontitis-Stages-II, III vs. Gingivitis_p<0.05_%), and {dagger}Saccharibacteria (TM7)[G-1]_bacterium_HMT-347,350_Gingivitis_p<0.05_Levels), some of the Human-Microbial-Taxon identified, presented correlation with total triglycerides ([&ge;]150mg/dl, 0.521), total lipids ([&ge;]800mg/dl, {dagger}0.478), and obesity (*10.279, *20.280, *30.312). The microbiome of Type 2 diabetes subjects with gingivitis presented the classical microbial profile with representative pathogenic species, while the Generalized Periodontitis Stage I-II subjects presented a microbiome with representative putative and saccharolytic species, some of them strongly associated with the poor control of lipid profile or obesity, and to periodontal-severity.

Recent studies have accumulated evidence that the intestinal environment is strongly correlated with host diet, which influences host health. A number of dietary products whose mechanisms of influence operate via the gut microbiota have been revealed, but they are still limited. Here, we investigated the dietary influence of Chlorella, a green alga commercially available as a dietary supplement. A randomized, double-blind, placebo-controlled crossover trial including 40 Japanese participants with constipation was performed and followed by integrated analysis of the gut microbiome, gut metabolome and blood parameters based on a metabologenomics approach. We revealed that the consumption of Chlorella increased the level of several dicarboxylic acids in faeces. Furthermore, the analysis showed that individuals with low concentrations of faecal propionate increased its concentration by Chlorella intake. In addition, increasing of blood folate levels were negatively correlated with defecation frequency at baseline. Our study suggested that the effect of Chlorella consumption varies by individuals depending on their intestinal environment, which illustrates the importance of stratified dietary management based on the intestinal environment in individuals.

Tube feeding (TF) is a common nutritional intervention in elderly patients. However, TF may change the composition and diversity of the gut microbiota, resulting in gastrointestinal symptoms such as diarrhea and constipation. This study investigated the impact of TF on the gut microbiota of Japanese individuals aged 60 years or older who had received TF for at least six months. Using 16S rRNA gene sequencing, the gut microbiota profiles of long-term TF (LTF) patients (LTFP) were compared with those of healthy controls (CON). The LTFP group exhibited a significant reduction in bacterial richness and diversity compared with the CON group. Taxonomic analysis revealed a marked decrease in the phylum Firmicutes (p = 0.0424), families such as Ruminococcaceae (p < 0.0001), Prevotellaceae (p = 0.0029), and Veillonellaceae (p = 0.0017), and genera including Roseburia (p = 0.0017) and Subdoligranulum (p = 0.0001) in LTFP group. Functional prediction analysis showed an enrichment of catabolic pathways in LTFP group, particularly of those related to nucleotide degradation and fermentation, whereas the CON group exhibited enriched biosynthetic and maintenance pathways. These findings suggest that LTF may lead to a dysbiotic gut environment, characterized by reduced short-chain fatty acid production and altered metabolic potential. Monitoring microbial changes during TF may be useful in guiding nutritional management strategies, including the use of prebiotics and probiotics, to support gut health and quality of life in elderly patients.

BackgroundDespite recent efforts, a single factor underlying the gut microbiota dysbiosis in intestinal diseases is not identified. We hypothesized that compromised intestinal barrier (CIB) could lead to increased host-derived contents including human cells in the gut, change its physio-metabolic properties, and globally alter gut microbiota and their metabolic capacities. ResultsConsistently, we found human DNA contents (HDCs), calculated as the percentage of metagenomic sequencing reads mapped to the human genome, were significantly elevated in colorectal cancer (CRC) patients; HDC correlated with microbial- and metabolic-pathway-biomarkers of CRC, and was the most important contributor to patient stratification. We found similar results in Crohns disease (CD); additionally, patients treated with diet and drug intervention showed reduced HDC levels over time, and were accompanied by reversing changes of many CD-signature species. ConclusionsOur results suggested that host-derived contents may have greater impact on gut microbiota than previously anticipated, and CIB could be an ideal treatment target that could reverse dysbiosis globally and precisely.

Dysregulation of the gut microbiota/gut hormone axis contributes to the pathogenesis of irritable bowel syndrome (IBS). Melatonin plays a beneficial role in gut motility and immunity. However, altered expression of local mucosal melatonin in IBS and its relationship with the gut microbiota remain unclear. Therefore, we aimed to detect the colonic melatonin levels and microbiota profiles in patients with diarrhea-predominant IBS (IBS-D) and explore their relationship in germ-free (GF) rats and BON-1 cells. Thirty-two IBS-D patients and twenty-eight healthy controls (HC) were recruited. Fecal specimens from IBS-D patients and HCs were separately transplanted into GF rats by gavage. The levels of colon mucosal melatonin were assessed by immunohistochemical methods, and fecal microbiota communities were analyzed using 16S rDNA sequencing. The effect of butyrate on melatonin synthesis in BON-1 cells was evaluated by ELISA. Melatonin levels were significantly increased in IBS-D patients compared with HC and were significantly negatively correlated with visceral sensitivity in IBS-D patients. GF rats inoculated with fecal microbiota from IBS-D patients had high colonic melatonin levels. Butyrate-producing Clostridium cluster XIVa species, such as Roseburia species and Lachnospira species, were positively related to colonic mucosal melatonin expression. Butyrate significantly increased melatonin secretion in BON-1 cells. Increased melatonin expression may be an adaptive protective mechanism in the development of IBS-D. Moreover, some Clostridium cluster XIVa species could increase melatonin expression via butyrate production. Modulation of the gut hormone/gut microbiota axis offers a promising target of interest for IBS in the future.

There are currently no preventative options for recurrent aphthous stomatitis, and the only available treatments are palliative. This is partly due to a poor understanding of its etiopathogenesis. In this case-control study, we characterized the salivary proteome of patients with recurrent aphthous stomatitis in the presence and absence of lesions. Through mass spectrometry-based proteomics and bioinformatics tools, we identified that the presence of oral ulcers is associated with several specific biological processes, including the metabolic pathways of vitamin B9, B12, nitrogen, selenium, and the bacterium Neisseria meningitidis. These changes occurred only in the presence of clinically visible lesions, and there were no relevant differences between patients in anatomical regions unaffected by ulcers. Additionally, using western blot and ELISA assays, we verified that carbonic anhydrase 1 (CA1, UniProtKB - P00915, CAH1_HUMAN) and hemoglobin subunit beta (HBB, UniProtKB - P68871, HBB_HUMAN) proteins are highly expressed during the ulcerative and remission phases of recurrent aphthous stomatitis. Our results cumulatively support saliva as an indicator of the pathophysiological changes, which occur during the clinical course of lesions. From a clinical perspective, we suggest that recurrent aphthous stomatitis is a condition triggered by temporary biological changes in people with lesions.

BackgroundDysbiosis, an imbalance of the intestinal microbiota in critically ill patients, reportedly contributes to poor outcomes. Controlling the disruption of intestinal homeostasis could be promising tactics for infectious complications in acute pancreatitis. To improve the mortality rate of severe acute pancreatitis with high frequency of infectious complications, it is warranted to elucidate the pathophysiology for development of new treatment strategies. We hypothesized that patients with severe acute pancreatitis would demonstrate gut dysbiosis, leading to an onset of infectious complications and poor outcomes. MethodsWe will conduct a prospective study to compare the sequential changes in intestinal microbiota using 16s RNA metagenomics and metabolomics between patients with severe acute pancreatitis and mild acute pancreatitis. We will enroll adult patients (18 years of age or older) diagnosed with acute pancreatitis and newly admitted to the hospitals for 48 hours or longer. We will exclude patients with inflammatory bowel disease, patients with diarrhea prior to admission, patients who have received antimicrobial agents for more than 1 week in the 2 months prior to admission. We will collect stool and blood samples on day 1 and 6. The primary outcome is changes in various parameters of the intestinal microbiota, protein concentration in stool, and metabolite concentration. The secondary outcomes include relationship between each parameter and short- and long-term prognosis, correlation of each parameter with treatment details and clinical course during ICU stay, and associations among the amount of diarrhea and alpha-diversity parameters, protein concentration in each stool, and metabolite concentration.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackground and aimsC_ST_ABSCertain diets often used to manage functional gastrointestinal symptoms in patients with irritable bowel syndrome (IBS). Personalized diet-induced microbiome modulation is being preferred method for symptom improvement in IBS. Although personalized nutritional therapies targeting gut microbiota using artificial intelligence (AI) promises a great potential, this approach has not been studied in patients with IBS. Therefore, in this study we investigated the efficacy of AI-based personalized microbiome diet in patients with IBS-Mix (M). MethodsThis study was designed as a pilot, open-labelled study. We enrolled consecutive IBS-M patients (n=25, 19 females, 46.06 {+/-} 13.11 years) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre- and post-intervention) and high-througput 16S rRNA sequencing was performed. Patients were divided into two groups based on age, gender and microbiome matched. Six weeks of AI-based microbiome diet (n=14) for group 1 and standard IBS diet (Control group, n=11) for group 2 were followed. AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. An algorithm assessing an IBS index score using microbiome composition attempted to design the optimized diets based on modulating microbiome towards the healthy scores. Baseline and post-intervention IBS-SSS (symptom severity scale) scores and fecal microbiome analyses were compared. ResultsThe IBS-SSS evaluation for both pre- and post-intervention exhibited significant improvement (p<0.02 and p<0.001 for the control and intervention groups, respectively). While the IBS-SSS evaluation changed to moderate from severe in 82% (14 out of 17) of the intervention group, no such change was observed in the control group. After 6-weeks of intervention, a major shift in microbiota profiles in terms of alfa- or beta-diversity was not observed in both groups. A trend of decrease in Ruminococcaceae family for the intervention group was observed (p=0.17). A statistically significant increase in Faecalibacterium genus was observed in the intervention group (p = 0.04). Bacteroides and putatively probiotic genus Propionibacterium were increased in the intervention group, however Prevotella was increased in the control group. The change (delta) values in IBS-SSS scores (before-after) intervention and control groups are significantly higher in the intervention group. ConclusionAI-based personalized microbiome modulation through diet significantly improves IBS-related symptoms in patients with IBS-M. Further large scale, randomized placebo-controlled trials with long-term follow-up (durability) are needed.

Sepsis, which is characterized by the failure of multiple organ, is the leading cause of death in intensive care units. Extensive research has emphasized a significant link between sepsis and the gut microbiota (GM). However, the causal relationship between these two factors, specifically the impact on 28-day mortality, remains unclear. We conducted a Mendelian randomization (MR) study utilizing genome-wide association study (GWAS) summary statistics. The primary analysis method used to establish the causal relationship was the inverse-variance weighted (IVW) method, along with four other MR methods. Furthermore, we assessed heterogeneity and horizontal pleiotropy using Cochrans Q test, MR-Egger intercept test, respectively. The IVW method showed that 7 GM, mainly including class Bacteroidia [odd ratio (OR) 1.565, 95% confidence interval (CI) 1.161-2.108, P = 0.003], genus Methanobrevibacter (OR 1.347, 95% CI 1.045-1.736, P = 0.022) and others were positively associated with 28-day sepsis mortality. Conversely, genetically predicted 4 GM, including class Lentisphaeria (OR 0.751, 95% CI 0.588-0.960, P = 0.022), genus Coprococcus2 (OR 0.537, 95% CI 0.315-0.917, P = 0.023), and others were negatively related to 28-day sepsis mortality. Heterogeneity and pleiotropy analyses also confirmed the robustness of our findings (all P > 0.05). Our study demonstrated a causal relationship between GM and 28-day mortality in sepsis using MR methods

ObjectiveChronic periodontitis has been proposed to be linked to coronavirus disease (COVID-19) on the basis of its inflammation mechanism. We aimed to evaluate this association by investigating the expression of Angiotensin Converting Enzyme-2 (ACE2) in periodontal compartments, which contain dysbiosis-associated pathogenic bacteria, and how it can be directly or indirectly involved in exacerbating inflammation in periodontal tissue. Material and MethodsThis observational clinical study included 23 adult hospitalized patients admitted to Universitas Indonesia Hospital with PCR-confirmed COVID-19, while 6 non-COVID-19 participants come to periodontal clinic were included as control. Using real time-PCR (qPCR) and gingival crevicular fluids (GCF) samples from COVID-19 patients with and without diabetes and periodontitis, we assessed the mRNA expression of angiotensin-converting enzyme 2 (ACE2), IL-6, IL-8, complement C3, and LL-37 as well as the relative proportion of Porphyromonas gingivalis, Fusobacterium nucleatum, and Veillonella parvula to represent the dysbiosis condition in periodontal microenvironment. All analyses were performed to determine their relationship. ResultsACE2 mRNA expression was detected in the GCF of periodontitis-COVID-19 patients with and without diabetes. However, only periodontitis-COVID-19 patients with diabetes showed a positive relationship between ACE2 expression and inflammatory conditions in the periodontal microenvironment. In addition, the interplay between pro-inflammatory cytokine (IL-6) and complement C3 could be used as a predictor of the severity of periodontal inflammation in COVID-19 patients with diabetes. ConclusionThe study data show that the SARS-CoV-2 entry gene is expressed in the GCF of patients with COVID-19, and its expression correlates with inflammatory markers.

This study explores the multi-level regulatory roles of the lactate metabolism gene network in oral cancer development using machine learning models. Machine learning analysis shows that lactate-related gene expression profiles can effectively distinguish treatment groups from controls (AUC=0.933), with SLC16A1 and KIF2C being key features. Genes like PFKP, LDHA, LDHB, LDHC, and VCAN are highlighted for their biological relevance. PFKP, involved in glycolytic metabolic regulation, is significantly upregulated in oral cancer patients, suggesting its role in tumor metabolic adaptation. VCAN, ranking sixth in feature importance, is associated with increased disease risk and may become a therapeutic target. EP300 exhibits a complex relationship with oral cancer, potentially acting as a tumor suppressor. Enrichment analysis links these genes to the HIF-1 signaling pathway and metabolic reprogramming. These findings advance the understanding of lactate metabolisms role in oral cancer and identify potential therapeutic targets.

The study explores the polymicrobial nature of primary endodontic infections using Illumina Next Generation Sequencing. Samples involved in research have been collected from root canals of the patients suffering from pulp and periapical inflammations with no history of endodontic interventions on affected teeth. The study revealed prevalence of different bacterial phyla, classes, orders, and species. Further work will show potential correlations between individual microbiotas and clinical diagnosis.