CAIM: coverage-based analysis for identification of microbiome.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic approach. In this study, we developed a new bioinformatics tool, coverage-based analysis for identification of microbiome (CAIM), for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count-based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consistently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similarity of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and 44 primary liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

Unraveling the role of gut microbiota by fecal microbiota transplantation in rat model of kidney stone disease.

Emerging research on the microbiome highlights the significant role of gut health in the development of kidney stones, indicating that an imbalance in gut bacteria or dysbiosis can influence the formation of stones by altering oxalate metabolism and urinary metabolite profiles. In particular, the overabundance of specific bacteria such as Enterococcus and Oxalobacter spp., which are known to affect oxalate absorption, is observed in patients with urolithiasis. This study investigates the effects of gut dysbiosis on urolithiasis through fecal microbiota transplantation (FMT) from patients to rats and its impact on urinary mineral excretion and stone formation. Fecal samples from eight patients with calcium oxalate stones and ten healthy volunteers were collected to assess the gut microbiome. These samples were then transplanted to antibiotic-pretreated Wistar rats for a duration of four weeks. After transplantation, we evaluated changes in the fecal gut microbiome profile, urinary mineral excretion rates, and expression levels of intestinal zonula occluden-1 (ZO-1), SLC26A6 and renal NF-κB. In humans, patients with urolithiasis exhibited increased urinary calcium and oxalate levels, along with decreased citrate excretion and increased urinary supersaturation index. The fecal microbiota showed a notable abundance of Bacteroidota. In rodents, urolithiasis-FMT rats showed urinary disturbances similar to patients, including elevated pH, oxalate level, and supersaturation index, despite negative renal pathology. In addition, a slight elevation in the expression of renal NF-κB, a significant intestinal SLC26A6, and a reduction in ZO-1 expression were observed. The gut microbiome of urolithiasis-FMT rats showed an increased abundance of Bacteroidota, particularly Muribaculaceae, compared to their healthy FMT counterparts. In conclusion, the consistent overabundance of Bacteroidota in both urolithiasis patients and urolithiasis-FMT rats is related to altered intestinal barrier function, hyperoxaluria, and renal inflammation. These findings suggest that gut dysbiosis, characterized by an overgrowth of Bacteroidota, plays a crucial role in the pathogenesis of calcium oxalate urolithiasis, underscoring the potential of targeting the gut microbiota as a therapeutic strategy.

Sensitivity and specificity of Nanopore sequencing for detecting carbapenem and 3rd-generation cephalosporin-resistant Enterobacteriaceae in urine samples: Real-time simulation with public antimicrobial resistance gene database.

Objectives: To evaluate the accuracy of beta-lactamase gene detection directly from urine samples by Nanopore sequencing. Methods: DNA was extracted from bacterial pellets in spun urine. The purified DNA was then sequenced in native form by a Nanopore sequencer (MinION) to identify the organisms and beta-lactamase genes. Results were compared to routine urine cultures and standard antimicrobial susceptibility tests (AST). Results: We processed 60 urine samples of which routine cultures grew Enterobacteriaceae, including 28 carbapenem-resistant (CRE), 17 extended-spectrum beta-lactamase (ESBL) or AmpC producing, and 15 non-ESBL/AmpC phenotypes. We excluded 7 samples with extremely low DNA amounts (<1 ng/µl) for a final case of 53 in total. The sensitivity of antimicrobial resistance gene detection within 6 h, the optimal duration from real-time simulation, of Nanopore sequencing for the diagnosis of carbapenem-resistant and ceftriaxone-resistant phenotypes was 73.9 % (95%CI 56.0-91.9 %) and 81.1 % (95%CI 68.5-93.7 %), while the specificity was 96.7 % (95%CI 90.2-100.0 %) and 56.3 % (95%CI 31.9-80.6 %), respectively. The median times for MinION to generate DNA reads containing carbapenemase and ESBL/AmpC genes were 93 min (IQR 17-245.5) and 99 min (IQR 31.25-269.75) after sequencing commencement, respectively. Conclusions: Nanopore sequencing can identify bacterial genotypic resistance in urine and may enable clinicians to adjust antimicrobial therapy earlier than routine AST.

Treatment with Gac Fruit Extract and Probiotics Reduces Serum Trimethylamine N-Oxide in Chronic Kidney Disease Rats.

Chronic kidney disease (CKD) affects more than 850 million people worldwide, contributing to morbidity and mortality, particularly through cardiovascular disease (CVD). The altered composition in CKD patients leads to increased production and absorption of uremic toxins such as trimethylamine (TMA) and its oxidized form, trimethylamine N-oxide (TMAO), which are associated with cardiovascular risks. This study investigated the potential of supplementary interventions with high-carotenoid-content gac fruit extract and probiotics to mitigate serum TMAO by modulating the gut microbiota. We conducted an animal study involving 48 male Wistar rats, divided into six groups: the control, CKD control, and four treatment groups receiving gac fruit extract, carotenoid extract, or combinations with Ligilactobacillus salivarius and Lactobacillus crispatus and Lactobacillus casei as a standard probiotic. CKD was induced in rats using cisplatin and they were supplemented with choline to enhance TMA production. The measures included serum creatinine, TMAO levels, gut microbiota composition, and the expression of fecal TMA lyase and intestinal zonula occluden-1 (ZO-1). CKD rats showed increased TMA production and elevated serum levels of TMAO. Treatment with gac fruit extract and selective probiotics significantly altered the composition of the gut microbiota by decreasing Actinobacteriota abundance and increasing the abundance of Bacteroides. This combination effectively promoted ZO-1 expression, reduced fecal TMA lyase, and subsequently lowered serum TMAO levels, demonstrating the therapeutic potential of these interventions. Our results highlight the benefits of gac fruit extract combined with probiotics for the effective reduction in serum TMAO levels in rats with CKD, supporting the further exploration of dietary and microbial interventions to improve outcomes in patients with CKD.

Single and Mixed Strains of Probiotics Reduced Hepatic Fat Accumulation and Inflammation and Altered Gut Microbiome in a Nonalcoholic Steatohepatitis Rat Model.

As gut dysbiosis has been implicated in the pathogenesis of nonalcoholic steatohepatitis (NASH), probiotic supplementation might be a potential treatment for this condition. The aim of this study was to evaluate the effects of single- and mixed-strain probiotics on the severity of NASH induced by a high-fat, high-fructose (HFHF) diet and their mechanisms of action. Male Sprague-Dawley rats were divided into four groups (n = 7 per group): control group, NASH group, NASH + single-strain group, and NASH + mixed-strain group. In the single-strain and mixed-strain groups, rats received Lactobacillus plantarum B7 and Lactobacillus rhamnosus L34 + Lactobacillus paracasei B13 by oral gavage once daily, respectively. The duration of the study was 6 weeks. Liver tissue was used for histopathology, hepatic fat content was assessed by Oil Red O staining and hepatic free fatty acid (FFA), and hepatic TLR4 and CD14 expression were assessed by immunohistochemistry. Fresh feces was collected for gut microbiota analysis. Liver histology revealed a higher degree of fat accumulation, hepatocyte ballooning, and lobular inflammation in the NASH group, which improved in probiotics-treated groups. The amounts of hepatic fat droplets and hepatic FFA levels were more pronounced in the NASH group than in the control and treatment groups. Serum TNF- α levels were significantly higher in the NASH group than in control and probiotic groups. The expression of CD14 and TLR4 increased in the NASH group as compared with the control and probiotics-treated groups. Alpha diversity was reduced in the NASH group, but increased in both treatment groups. The relative abundance of Lactobacillus significantly decreased in the NASH group, but increased in both treatment groups. The relative abundance of Akkermansia significantly increased in the NASH group, but decreased in both treatment groups. In conclusion, both single-strain and mixed-strain probiotics could improve NASH histology by suppressing inflammatory responses in the liver, with this improvement potentially being associated with changes in the gut microbiota.

Distinct Gut Microbial Signature and Host Genetic Variants in Association with Liver Fibrosis Severity in Patients with MASLD.

Gut microbiota might affect the severity and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to characterize gut dysbiosis and clinical parameters regarding fibrosis stages assessed by magnetic resonance elastography. This study included 156 patients with MASLD, stratified into no/mild fibrosis (F0-F1) and moderate/severe fibrosis (F2-F4). Fecal specimens were sequenced targeting the V4 region of the 16S rRNA gene and analyzed using bioinformatics. The genotyping of PNPLA3, TM6SF2, and HSD17B13 was assessed by allelic discrimination assays. Our data showed that gut microbial profiles between groups significantly differed in beta-diversity but not in alpha-diversity indices. Enriched Fusobacterium and Escherichia_Shigella, and depleted Lachnospira were found in the F2-F4 group versus the F0-F1 group. Compared to F0-F1, the F2-F4 group had elevated plasma surrogate markers of gut epithelial permeability and bacterial translocation. The bacterial genera, PNPLA3 polymorphisms, old age, and diabetes were independently associated with advanced fibrosis in multivariable analyses. Using the Random Forest classifier, the gut microbial signature of three genera could differentiate the groups with high diagnostic accuracy (AUC of 0.93). These results indicated that the imbalance of enriched pathogenic genera and decreased beneficial bacteria, in association with several clinical and genetic factors, were potential contributors to the pathogenesis and progression of MASLD.

Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach.

Long non-coding RNAs (lncRNAs), which are RNA sequences greater than 200 nucleotides in length, play a crucial role in regulating gene expression and biological processes associated with cancer development and progression. Liver cancer is a major cause of cancer-related mortality worldwide, notably in Thailand. Although machine learning has been extensively used in analyzing RNA-sequencing data for advanced knowledge, the identification of potential lncRNA biomarkers for cancer, particularly focusing on lncRNAs as molecular biomarkers in liver cancer, remains comparatively limited. In this study, our objective was to identify candidate lncRNAs in liver cancer. We employed an expression data set of lncRNAs from patients with liver cancer, which comprised 40 699 lncRNAs sourced from The CancerLivER database. Various feature selection methods and machine-learning approaches were used to identify these candidate lncRNAs. The results showed that the random forest algorithm could predict lncRNAs using features extracted from the database, which achieved an area under the curve (AUC) of 0.840 for classifying lncRNAs between early (stage 1) and late stages (stages 2, 3, and 4) of liver cancer. Five of 23 significant lncRNAs (WAC-AS1, MAPKAPK5-AS1, ARRDC1-AS1, AC133528.2, and RP11-1094M14.11) were differentially expressed between early and late stage of liver cancer. Based on the Gene Expression Profiling Interactive Analysis (GEPIA) database, higher expression of WAC-AS1, MAPKAPK5-AS1, and ARRDC1-AS1 was associated with shorter overall survival. In conclusion, the classification model could predict the early and late stages of liver cancer using the signature expression of lncRNA genes. The identified lncRNAs might be used as early diagnostic and prognostic biomarkers for patients with liver cancer.

CAIM: Coverage-based Analysis for Identification of Microbiome.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic (WMS) approach. In this study, we developed a new bioinformatics tool, CAIM, for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consitently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similality of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and primary 44 liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

Single-Nucleotide Polymorphisms of Growth Hormone Gene and Its Relationship with Growth Traits in Black Bengal Goats.

The single-nucleotide polymorphisms (SNPs) of the growth hormone (GH) gene could be related to growth traits, particularly in farm animals. This study aimed to identify the SNPs of the GH gene (A781G and A1575G) in Black Bengal (BB) goats in Thailand. Seventy-seven BB goats of both sexes were recruited, and their genotypes were identified. Preweaning growth at birth (weight, W0; height, H0; length, L0; and chest girth, C0) and at 10 weeks postpartum (W10, H10, L10, and C10), including average daily gain (ADG) at 0-4 weeks (ADG0-4W), 4-8 weeks (ADG4-8W), and 8-12 weeks (ADG8-12W), was compared among the different genotypes in goats born from twin litter-size dams. The results showed one genotype, CC, for A1575G and three genotypes, AA, AB, and BB, for A781G. The AA gene had significantly higher W10 than AB (p < 0.05) and BB (p < 0.05). The AA had significantly higher L10 than AB (p < 0.05), while C10 was only higher in male goats (p < 0.01). The ADG4-8W of the AA genotype was significantly higher than the BB genotype (p < 0.01). We came to the conclusion that A781G is associated with growth traits during the preweaning period, while the AA genotype showed better performance than the other genotypes.

Gut Microbiota in Patients with Non-Alcoholic Fatty Liver Disease without Type 2 Diabetes: Stratified by Body Mass Index.

The relationship between gut dysbiosis and body mass index (BMI) in non-diabetic patients with non-alcoholic fatty liver disease (NAFLD) is not adequately characterized. This study aimed to assess gut microbiota's signature in non-diabetic individuals with NAFLD stratified by BMI. The 16S ribosomal RNA sequencing was performed for gut microbiota composition in 100 patients with NAFLD and 16 healthy individuals. The differential abundance of bacterial composition between groups was analyzed using the DESeq2 method. The alpha diversity (Chao1, Shannon, and observed feature) and beta diversity of gut microbiota significantly differed between patients with NAFLD and healthy controls. However, significant differences in their diversities were not observed among subgroups of NAFLD. At the phylum level, there was no trend of an elevated Firmicutes/Bacteroidetes ratio according to BMI. At the genus level, patients with lean NAFLD displayed a significant enrichment of Escherichia-Shigella and the depletion of Lachnospira and Subdoligranulum compared to the non-lean subgroups. Combining these bacterial genera could discriminate lean from non-lean NAFLD with high diagnostic accuracy (AUC of 0.82). Non-diabetic patients with lean NAFLD had a significant difference in bacterial composition compared to non-lean individuals. Our results might provide evidence of gut microbiota signatures associated with the pathophysiology and potential targeting therapy in patients with lean NAFLD.

Distinct alterations of gut microbiota between viral- and non-viral-related hepatocellular carcinoma.

Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC. KEY POINTS: • Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker. • Gut microbiota composition is significantly altered in different etiological factors of HCC. • Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.

Circulating Extracellular Vesicle-Derived microRNAs as Novel Diagnostic and Prognostic Biomarkers for Non-Viral-Related Hepatocellular Carcinoma.

Extracellular vesicle-derived microRNAs (EV-miRNAs) are promising circulating biomarkers for chronic liver disease. In this study, we explored the potential significance of plasma EV-miRNAs in non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). We compared, using the NanoString method, plasma EV-miRNA profiles between NBNC-HCC and control groups including patients with non-alcoholic fatty liver disease (NAFLD) and healthy controls. The differentially expressed EV-miRNAs were validated in another set of plasma samples by qRT-PCR. A total of 66 significantly differentially expressed EV-miRNAs between the HCC and the control groups were identified in the discovery set. In the validation cohort, including plasma samples of 70 NBNC-HCC patients, 70 NAFLD patients, and 35 healthy controls, 5 plasma EV-miRNAs were significantly elevated in HCC, which included miR-19-3p, miR-16-5p, miR-223-3p, miR-30d-5p, and miR-451a. These miRNAs were found to participate in several cancer-related signaling pathways based on bioinformatic analysis. Among them, EV-miR-19-3p exhibited the best diagnostic performance and displayed a high sensitivity for detecting alpha-fetoprotein-negative HCC and early-stage HCC. In multivariate analysis, a high EV-miR-19-3p level was demonstrated as an independently unfavorable predictor of overall survival in patients with NBNC-HCC. In conclusion, our data have indicated, for the first time, that EV-miR-19-3p could serve as a novel circulating biomarker for the diagnosis and prognosis of NBNC-HCC.

Binding characteristics of pyrrole-scaffold hepatitis B virus capsid inhibitors and identification of novel potent compounds.

Hepatitis B virus (HBV) capsid assembly modulators (CAMs) are currently being evaluated in clinical trials as potential curative therapies for HBV. This study used in silico computational modeling to provide insights into the binding characteristics between the HBV core protein and two pyrrole-scaffold inhibitors, JNJ-6379 and GLP-26, both in the CAM-Normal (CAM-N) series. Molecular dynamics simulations showed that the pyrrole inhibitors displayed similar general binding-interaction patterns to NVR 3-778, another CAM-N, with hydrophobic interactions serving as the major driving force. However, consistent with their higher potency, the pyrrole inhibitors exhibited stronger nonpolar interactions with key residues in a solvent-accessible region as compared to NVR 3-778. This feature was facilitated by distinct hydrogen bond interactions of the pyrrole scaffold inhibitors with the residue 140 in chain B of the HBV core protein (L140B). Based on these findings, novel CAM-N compounds were designed to mimic the interaction with L140B residue while maximizing nonpolar interactions in the solvent-accessible region. Several 1H-pyrrole-2-carbonyl substituted pyrrolidine-based compounds with various hydrophobic side chains were synthesized and evaluated. Through analyses of the structure-activity and structure-druggability relations of a series of compounds, CU15 emerged as the most promising lead CAM-N compound, exhibiting sub-nanomolar potency and good pharmacokinetic profiles. Overall, the study demonstrated a practical approach to leverage computational methods for understanding key target binding features for rationale-based design, and for guiding the identification of novel compounds.

Predictive Role of Pretreatment Circulating miR-221 in Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.

Aberrantly expressed circulating microRNAs (miRNAs) have been demonstrated to have a crucial role in the diagnosis and prognostication of various cancers, including hepatocellular carcinoma (HCC). This research aimed to examine the role of specific miRNAs in predicting the outcomes for individuals with hepatitis B virus (HBV)-related HCC treated with transarterial chemoembolization (TACE). Stored serum specimens collected prior to the first TACE procedure were employed to determine the expression of serum miR-122, miR-221, and miR-224 using quantitative real-time PCR analysis. The study included 100 HCC patients (84% males, with an average age of 60 years) who were treated with TACE. Throughout the median follow-up spanning 18.5 months (within a range of 3 to 60 months), 42 (42.0%) patients met the criteria of TACE refractoriness. Through multivariate analysis, elevated expressed miR-221 (≥4.0 log10 copies) and advanced HCC staging were identified as independent factors related to TACE refractoriness and short overall survival. However, serum miR-122 and miR-224 levels were not linked to treatment response or overall survival. These findings underscored the potential of incorporating pretreatment levels of serum miR-221 into the established tumor staging to enhance the accurate assessment of TACE responsiveness and prognostic outcome of patients with HCC.

Long-term benefit of DAAs on gut dysbiosis and microbial translocation in HCV-infected patients with and without HIV coinfection.

Long-term effect of Direct-acting antivirals (DAAs) on gut microbiota, short-chain fatty acids (SCFAs) and microbial translocation in patients with hepatitis C virus (HCV) infection who achieve sustained virological response (SVR) were limited. A longitudinal study of 50 patients with HCV monoinfection and 19 patients with HCV/HIV coinfection received DAAs were conducted. Fecal specimens collected at baseline and at week 72 after treatment completion (FUw72) were analyzed for 16S rRNA sequencing and the butyryl-CoA:acetateCoA transferase (BCoAT) gene expression using real-time PCR. Plasma lipopolysaccharide binding protein (LBP) and intestinal fatty acid binding protein (I-FABP) were quantified by ELISA assays. SVR rates in mono- and coinfected patients were comparable (94% vs. 100%). The improvement of gut dysbiosis and microbial translocation was found in responders but was not in non-responders. Among responders, significant restoration of alpha-diversity, BCoAT and LBP were observed in HCV patients with low-grade fibrosis (F0-F1), while HCV/HIV patients exhibited partial improvement at FUw72. I-FABP did not decline significantly in responders. Treatment induced microbiota changes with increasing abundance of SCFAs-producing bacteria, including Blautia, Fusicatenibacter, Subdoligranulum and Bifidobacterium. In conclusion, long-term effect of DAAs impacted the restoration of gut dysbiosis and microbial translocation. However, early initiation of DAAs required for an alteration of gut microbiota, enhanced SCFAs-producing bacteria, and could reduce HCV-related complications.

The Usefulness of Resistant Maltodextrin and Chitosan Oligosaccharide in Management of Gut Leakage and Microbiota in Chronic Kidney Disease.

Microbiota-dysbiosis-induced gut leakage is a pathophysiologic change in chronic kidney disease (CKD), leading to the production of several uremic toxins and their absorption into the bloodstream to worsen the renal complications. We evaluate the benefits of resistant maltodextrin (RMD) and chitosan oligosaccharide (COS) supplements in cell culture and CKD-induced rats. The RMD exerted a significant anti-inflammatory effect in vitro and intestinal occludin and zonula occluden-1 up-regulation in CKD rats compared with inulin and COS. While all prebiotics slightly improved gut dysbiosis, RMD remarkably promoted the relative abundance and the combined abundance of Lactobacillus, Bifidobacteria, Akkermansia, and Roseburia in CKD rats. Supplements of RMD should be advantageous in the treatment of gut leakage and microbiota dysbiosis in CKD.

Large-scale fabrication of ion-selective electrodes for simultaneous detection of Na+, K+, and Ca2+ in biofluids using a smartphone-based potentiometric sensing platform.

A significant bottleneck exists for mass-production of ion-selective electrodes despite recent developments in manufacturing technologies. Here, we present a fully-automated system for large-scale production of ISEs. Three materials, including polyvinyl chloride, polyethylene terephthalate and polyimide, were used as substrates for fabricating ion-selective electrodes (ISEs) using stencil printing, screen-printing and laser engraving, respectively. We compared sensitivities of the ISEs to determine the best material for the fabrication process of the ISEs. The electrode surfaces were modified with various carbon nanomaterials including multi-walled carbon nanotubes, graphene, carbon black, and their mixed suspensions as the intermediate layer to enhance sensitivities of the electrodes. An automated 3D-printed robot was used for the drop-cast procedure during ISE fabrication to eliminate manual steps. The sensor array was optimized, and the detection limits were 10-5 M, 10-5 M and 10-4 M for detection of K+, Na+ and Ca2+ ions, respectively. The sensor array integrated with a portable wireless potentiometer was used to detect K+, Na+ and Ca2+ in real urine and simulated sweat samples and results obtained were in agreement with ICP-OES with good recoveries. The developed sensing platform offers low-cost detection of electrolytes for point-of-care applications.

Electrochemical capillary-driven microfluidic DNA sensor for HIV-1 and HCV coinfection analysis.

Electrochemical DNA sensors can be operated in either static or flow-based detection schemes. In static schemes, manual washing steps are still necessary, resulting in a tedious and time-consuming process. In contrast, in flow-based electrochemical sensors, the current response is collected when the solution flows through the electrode continuously. However, the drawback of such a flow system is the low sensitivity due to the limited time for the interaction between the capturing element and the target. Herein, we propose a novel electrochemical capillary-driven microfluidic DNA sensor to combine the advantages of static and flow-based electrochemical detection systems into a single device by incorporating burst valve technology. The microfluidic device with a two-electrode configuration was applied for the simultaneous detection of two different DNA markers, human immunodeficiency virus-1 (HIV-1) and hepatitis C virus (HCV) cDNA, via the specific interaction between pyrrolidinyl peptide nucleic acids (PNA) probes and the DNA target. The integrated system, while requiring a small sample volume (7 µL for each sample loading port) and less analysis time, achieved good performance in terms of the limits of detection (LOD) (3SDblank/slope) and quantification (LOQ) (10SDblank/slope) at 1.45 nM and 4.79 nM for HIV and 1.20 nM and 3.96 nM for HCV, respectively. The simultaneous detection of HIV-1 and HCV cDNA prepared from human blood samples showed results that are in complete agreement with the RT‒PCR assay. The results qualify this platform as a promising alternative for the analysis of either HIV-1/HCV or coinfection that can be easily adapted for other clinically important nucleic acid-based markers.

Identification of a novel gut microbiota signature associated with colorectal cancer in Thai population.

Colorectal cancer (CRC) is the third most common cancer worldwide. Dysbiosis of human gut microbiota has been linked to sporadic CRC. This study aimed to compare the gut microbiota profiles of 80 Thai volunteers over 50 years of age among 25 CRC patients, 33 patients with adenomatous polyp, and 22 healthy controls. The 16S rRNA sequencing was utilized to characterize the gut microbiome in both mucosal tissue and stool samples. The results revealed that the luminal microbiota incompletely represented the intestinal bacteria at the mucus layer. The mucosal microbiota in beta diversity differed significantly among the three groups. The stepwise increase of Bacteroides and Parabacteroides according to the adenomas-carcinomas sequence was found. Moreover, linear discriminant analysis effect size showed a higher level of Erysipelatoclostridium ramosum (ER), an opportunistic pathogen in the immunocompromised host, in both sample types of CRC patients. These findings indicated that the imbalance of intestinal microorganisms might involve in CRC tumorigenesis. Additionally, absolute quantitation of bacterial burden by quantitative real-time PCR (qPCR) confirmed the increasing ER levels in both sample types of cancer cases. Using ER as a stool-based biomarker for CRC detection by qPCR could predict CRC in stool samples with a specificity of 72.7% and a sensitivity of 64.7%. These results suggested ER might be a potential noninvasive marker for CRC screening development. However, a larger sample size is required to validate this candidate biomarker in diagnosing CRC.