The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets

A novel intervention of molecular hydrogen on the unbalance of the gut microbiome in opioid addiction: Experimental and human studies

The gut-brain axis mediates the interaction pathway between microbiota and opioid addiction. In recent years, many studies have shown that molecular hydrogen has therapeutic and preventive effects on various diseases. This study aimed to investigate whether molecular hydrogen could serve as pharmacological intervention agent to reduce risks of reinstatement of opioid seeking and explore the mechanism of gut microbiota base on animal experiments and human studies. Morphine-induced conditioned place preference (CPP) was constructed to establish acquisition, extinction, and reinstatement stage, and the potential impact of H2 on the behaviors related to morphine-induced drug extinction was determined using both free accessible and confined CPP extinction paradigms. The effects of morphine on microbial diversity and composition of microbiota, as well as the subsequent changes after H2 intervention, were assessed using 16 S rRNA gene sequencing. Short-Chain Fatty Acids (SCFAs) in mice serum were detected by gas chromatography-mass spectrometry (GC-MS). Meanwhile, we also conducted molecular hydrogen intervention and gut microbiota testing in opioid-addicted individuals. Our results revealed that molecular hydrogen could enhance the extinction of morphine-related behavior, reducing morphine reinstatement. Gut microbes may be a potential mechanism behind the therapeutic effects of molecular hydrogen on morphine addiction. Additionally, molecular hydrogen improved symptoms of depression and anxiety, as well as gut microbial features, in individuals with opioid addiction. This study supports molecular hydrogen as a novel and effective intervention for morphine-induced addiction and reveals the mechanism of gut microbiota.

Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues

Colorectal cancer poses a significant threat to global health, necessitating the development of effective early detection techniques. However, the potential of the fungal microbiome as a putative biomarker for the detection of colorectal adenocarcinoma has not been extensively explored. We analyzed the viability of implementing the fungal mycobiome for this purpose. Biopsies were collected from cancer and polyp patients. The total genomic DNA was extracted from the biopsy samples by utilizing a comprehensive kit to ensure optimal microbial DNA recovery. To characterize the composition and diversity of the fungal mycobiome, high-throughput amplicon sequencing targeting the internal transcribed spacer 1 (ITS1) region was proposed. A comparative analysis revealed discrete fungal profiles among the diseased groups. Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. These findings suggest the utility of gut mycobiome as biomarkers for the detection of colorectal adenocarcinoma. Expanding our understanding of the role of the gut mycobiome in disease detection creates novel opportunities for early intervention and personalized therapeutic strategies for colorectal cancer.•Detailed method to identify the gut mycobiome in colorectal cancer patients using ITS-specific amplicon sequencing.•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening.•Contribution to the advancement of innovative colorectal cancer diagnostic methods and targeted therapies by applying gut mycobiome knowledge.

Associations between impulsivity and fecal microbiota in individuals abstaining from methamphetamine

INTRODUCTION

Methamphetamine (MA) abuse is a major public problem, and impulsivity is both a prominent risk factor and a consequence of addiction. Hence, clarifying the biological mechanism of impulsivity may facilitate the understanding of addiction to MA. The microbiota-gut-brain axis was suggested to underlie a biological mechanism of impulsivity induced by MA.

METHODS

We therefore recruited 62 MA addicts and 50 healthy controls (HCs) to investigate the alterations in impulsivity and fecal microbiota and the associations between them in the MA group. Thereafter, 25 MA abusers who abstained from MA for less than 3 months were followed up for 2 months to investigate the relationship between impulsivity and microbiota as abstinence became longer. 16S rRNA sequencing was conducted for microbiota identification.

RESULTS

Elevated impulsivity and dysbiosis characterized by an increase in opportunistic pathogens and a decrease in probiotics were identified in MA abusers, and both the increased impulsivity and disrupted microbiota tended to recover after longer abstinence from MA. Impulsivity was related to microbiota, and the effect of MA abuse on impulsivity was mediated by microbiota.

CONCLUSION

Our findings potentially highlighted the importance of abstention and implicated the significant role of the microbiota-gut-brain axis in the interrelationship between microbiota and behaviors, as well as the potential of microbiota as a target for intervention of impulsivity.

Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location

Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) presents an efficient and accurate tool, with the ability to autonomously process and analyze high-throughput data, and assimilate multi-omics data, encompassing metagenomics, transcriptomics, and proteomics. This facilitates accurate and efficient estimation of the postmortem interval (PMI), detection of crime location, and elucidation of microbial functionalities. This review presents an overview of microorganisms from cadavers and crime scenes, emphasizes the importance of microbiome, and summarizes the application of AI in high-throughput microbiome data processing in forensic microbiology.