Jung-Chun Lin

The persistent emergence of multidrug-resistant Mycobacterium tuberculosis (MTB) strains exacerbates the global tuberculosis (TB) epidemic to a worldwide health issue. The phenomenon has highlighted the demand for fast and accurate identification of drug-resistant signatures of MTB isolates, which remains a major challenge for determining the precise regimen. Whole-genome sequencing (WGS) possesses the potential to infer drug-resistant profiles before phenotypic approaches, thereby enabling the formulation of personalized regimens for TB disease. In this study, WGS-generated data assessed with distinct databases, including ONT EPI2ME v1.0.16, ResFinder v4.7.2 for MTB, TBProfiler v6.6.2, Mykrobe v0.10.0, and CLC Genomics Workbench software v25.0.2, were used to identify single nucleotide variants (SNVs) within the rpoB, katG, inhA, and pncA genes relevant to three major first-line drugs in 105 clinical MTB isolates with the phenotypic drug susceptibility test (DST) results. All these analytic tools demonstrated convincing performance in predicting the sensitivity (>90%) and specificity (>90%) of rifampicin resistant (RR)-MTB isolates. The TBProfiler and ResFinder databases stood out for their efficient performance in predicting the drug-resistant signatures of isoniazid resistant (HR)-MTB isolates. Remarkably, the deployment of the CLC-GW pipeline showed exceptional performance in predicting the sensitivity (96%) and specificity (100%) of multi drug resistant (MDR)-MTB isolates. In this study, we assessed the reliability and effectiveness of WGS-coupled analyses in determining the drug-resistant signatures of MTB, thereby contributing to the advancement of MTB treatment.

Overnutrition with a high-fat or high-sugar diet is widely considered to be the risk factor for various metabolic, chronic, or malignant diseases that are accompanied by alterations in gut microbiota, metabolites, and downstream pathways. In this study, we investigated supplementation with soybean fermentation broth containing saponin (SFBS, also called SAPOZYME) in male C57BL/6 mice fed a high-fat-fructose diet or normal chaw. In addition to the lessening of weight gain, the influence of SFBS on reducing hyperlipidemia and hyperglycemia associated with a high-fat-fructose diet was estimated using the results of related biological tests. The results of gut microbial profiling indicated that the high-fat-fructose diet mediated increases in opportunistic pathogens. In contrast, SFBS supplementation reprogrammed the high-fat-fructose diet-related microbial community with a relatively high abundance of potential probiotics, including Akkermansia and Lactobacillus genera. The metagenomic functions of differential microbial composition in a mouse model and enrolled participants were assessed using the PICRUSt2 algorithm coupled with the MetaCyc and the KEGG Orthology databases. SFBS supplementation exerted a similar influence on an increase in the level of 4-aminobutanoate (also called GABA) through the L-glutamate degradation pathway in the mouse model and the enrolled healthy population. These results suggest the beneficial influence of SFBS supplementation on metabolic disorders associated with a high-fat-fructose diet, and SFBS may function as a nutritional supplement for people with diverse requirements.

Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD.

Current approaches to diagnose drug-resistant MTB are time-consuming, consequently leading to inefficient intervention or further disease transmission. In this study, we curated lists of coding variants associated with differential rifampin and rifabutin resistant signatures using a single molecule real-time (SMRT) sequencing platform with a shorter hands-on time.

The gut mucosa is actively absorptive and functions as the physical barrier to separate the gut ecosystem from host. Gut microbiota-utilized or food-derived metabolites are closely relevant to the homeostasis of the gut epithelial cells. Recent studies widely suggested the carcinogenic impact of gut dysbiosis or altered metabolites on the development of colorectal cancer (CRC). In this study, liquid chromatography coupled-mass spectrometry and long-read sequencing was applied to identify gut metabolites and microbiomes with statistically discriminative abundance in CRC patients (n = 20) as compared to those of a healthy group (n = 60) ofenrolled participants diagnosed with adenomatous polyp (n = 67) or occult blood (n = 40). In total, alteration in the relative abundance of 90 operational taxonomic units (OTUs) and 45 metabolites were identified between recruited CRC patients and healthy participants. Among the candidates, the gradual increases in nine OTUs or eight metabolites were identified in healthy participants, patients diagnosed with occult blood and adenomatous polyp, and CRC patients. The random forest regression model constructed with five OTUs or four metabolites achieved a distinct classification potential to differentially discriminate the presence of CRC (area under the ROC curve (AUC) = 0.998 or 0.975) from the diagnosis of adenomatous polyp (AUC = 0.831 or 0.777), respectively. These results provide the validity of CRC-associated markers, including microbial communities and metabolomic profiles across healthy and related populations toward the early screening or diagnosis of CRC.

Background: With the advancement of next generation sequencing technologies (NGS), whole-genome sequencing (WGS) has been deployed to a wide range of clinical scenarios. Rapid and accurate classification of drug-resistant Mycobacterium tuberculosis (MTB) would be advantageous in reducing the amplification of additional drug resistance and disease transmission. Methods: In this study, a long-read sequencing approach was subjected to the whole-genome sequencing of clinical MTB clones with susceptibility test profiles, including isoniazid (INH) susceptible clones (n = 10) and INH resistant clones (n = 42) isolated from clinical specimens. Non-synonymous variants within the katG or inhA gene associated with INH resistance was identified using Nanopore sequencing coupled with a corresponding analytical workflow. Results: In total, 54 nucleotide variants within the katG gene and 39 variants within the inhA gene associated with INH resistance were identified. Consistency among the results of genotypic profiles, susceptibility test, and minimal inhibitory concentration, the high-INH resistance signature was estimated using the area under the receiver operating characteristic curve with the existence of Ser315Thr (AUC = 0.822) or Thr579Asn (AUC = 0.875). Conclusions: Taken together, we curated lists of coding variants associated with differential INH resistance using Nanopore sequencing, which may constitute an emerging platform for rapid and accurate identification of drug-resistant MTB clones.

Methylprednisolone (MP) is an anti-inflammatory drug approved for the treatment of acute spinal cord injuries (SCIs). However, MP administration for SCIs has become a controversial issue while the molecular effects of MP remain unexplored to date. Therefore, delineating the benefits and side effects of MP and determining what MP cannot cure in SCIs at the molecular level are urgent issues. Here, genomic profiles of the spinal cord in rats with and without injury insults, and those with and without MP treatment, were generated at 0, 2, 4, 6, 8, 12, 24, and 48 h post-injury. A comprehensive analysis was applied to obtain three distinct classes: side effect of MP (SEMP), competence of MP (CPMP), and incapability of MP (ICMP). Functional analysis using these genes suggested that MP exerts its greatest effect at 8~12 h, and the CPMP was reflected in the immune response, while SEMP suggested aspects of metabolism, such as glycolysis, and ICMP was on neurological system processes in acute SCIs. For the first time, we are able to precisely reveal responsive functions of MP in SCIs at the molecular level and provide useful solutions to avoid complications of MP in SCIs before better therapeutic drugs are available.

A growing body of study have documented the association of gut dysbiosis or fecal metabolites with chronic kidney disease (CKD). However, it is not clear whether the phenomenon simply reflects the microenvironment changes correlated with the CKD severity or contributes to the progression of CKD. In this study, we identified the gut microbiota and metabolite in feces samples correlated with CKD severity using the Nanopore long-read sequencing platform and UPLC-coupled MS/MS approach. A cross-sectional cohort study was performed from 1 June 2020 to 31 December 2020. One hundred and fifty-six clinical participants, including 60 healthy enrollees and 96 Stage 1–5 CKD patients, were enrolled in this study. The ROC curve generated with the relative abundance of Klebsiella pneumonia or S-Adenosylhomocysteine showed a gradual increase with the CKD severity. Our results further revealed the positive correlation of increased K. pneumonia and S-Adenosylhomocysteine in gut environment, which may be of etiological importance to the deterioration of a CKD patient. In that sense, the microbiota or metabolite changes constitute potential candidates for evaluating the progression of CKD.