Reliable Biomarker discovery from Metagenomic data via RegLRSD algorithm

Wise Roles and Future Visionary Endeavors of Current Emperor: Advancing Dynamic Methods for Longitudinal Microbiome Meta-Omics Data in Personalized and Precision Medicine

Understanding the etiological complexity of diseases requires identifying biomarkers longitudinally associated with specific phenotypes. Advanced sequencing tools generate dynamic microbiome data, providing insights into microbial community functions and their impact on health. This review aims to explore the current roles and future visionary endeavors of dynamic methods for integrating longitudinal microbiome multi-omics data in personalized and precision medicine. This work seeks to synthesize existing research, propose best practices, and highlight innovative techniques. The development and application of advanced dynamic methods, including the unified analytical frameworks and deep learning tools in artificial intelligence, are critically examined. Aggregating data on microbes, metabolites, genes, and other entities offers profound insights into the interactions among microorganisms, host physiology, and external stimuli. Despite progress, the absence of gold standards for validating analytical protocols and data resources of various longitudinal multi-omics studies remains a significant challenge. The interdependence of workflow steps critically affects overall outcomes. This work provides a comprehensive roadmap for best practices, addressing current challenges with advanced dynamic methods. The review underscores the biological effects of clinical, experimental, and analytical protocol settings on outcomes. Establishing consensus on dynamic microbiome inter-studies and advancing reliable analytical protocols are pivotal for the future of personalized and precision medicine.

MetaAnalyst: a user-friendly tool for metagenomic biomarker detection and phenotype classification

BACKGROUND

Many metagenomic studies have linked the imbalance in microbial abundance profiles to a wide range of diseases. These studies suggest utilizing the microbial abundance profiles as potential markers for metagenomic-associated conditions. Due to the inevitable importance of biomarkers in understanding the disease progression and the development of possible therapies, various computational tools have been proposed for metagenomic biomarker detection. However, most existing tools require prior scripting knowledge and lack user friendly interfaces, causing considerable time and effort to install, configure, and run these tools. Besides, there is no available all-in-one solution for running and comparing various metagenomic biomarker detection simultaneously. In addition, most of these tools just present the suggested biomarkers without any statistical evaluation for their quality.

RESULTS

To overcome these limitations, this work presents MetaAnalyst, a software package with a simple graphical user interface (GUI) that (i) automates the installation and configuration of 28 state-of-the-art tools, (ii) supports flexible study design to enable studying the dataset under different scenarios smoothly, iii) runs and evaluates several algorithms simultaneously iv) supports different input formats and provides the user with several preprocessing capabilities, v) provides a variety of metrics to evaluate the quality of the suggested markers, and vi) presents the outcomes in the form of publication quality plots with various formatting capabilities as well as Excel sheets.

CONCLUSIONS

The utility of this tool has been verified through studying a metagenomic dataset under four scenarios. The executable file for MetaAnalyst along with its user manual are made available at https://github.com/mshawaqfeh/MetaAnalyst .

Music of metagenomics-a review of its applications, analysis pipeline, and associated tools

This humble effort highlights the intricate details of metagenomics in a simple, poetic, and rhythmic way. The paper enforces the significance of the research area, provides details about major analytical methods, examines the taxonomy and assembly of genomes, emphasizes some tools, and concludes by celebrating the richness of the ecosystem populated by the "metagenome."

Dysbiosis Signatures of Fecal Microbiota in South African Infants with Respiratory, Gastrointestinal, and Other Diseases

OBJECTIVE

To determine the association between the fecal microbiota diversity of the infants with different disease conditions, and vitamin A supplementation, antibiotic, and deworming therapies.

STUDY DESIGN

In this case-control study, the bacterial community variations and the potential pathogens were identified through 16S ribosomal RNA gene-based amplicon sequencing and quantitative insights into microbial ecology pipeline in fecal samples. The participants were South African infants (mean age, 16 ± 8 months; 17 male and 17 female) hospitalized and diagnosed with gastrointestinal, respiratory, and other diseases.

RESULTS

The top phyla of the infants with respiratory disease were Proteobacteria, followed by Firmicutes, which were equally abundant in gastrointestinal disease. A significant difference in Shannon (alpha) diversity index (95% CI, 2.6-4.4; P = .008), among the microbiota of the fecal samples categorized by disease conditions, was observed. In beta diversity analysis of fecal microbiota, remarkable variations were found within the groups of deworming therapy (95% CI, 0.40-0.90; P = .033), disease conditions (95% CI, 0.44-0.86; P < .012) through unweighted and antibiotic therapy (95% CI, 0.20-0.75; P = .007), vitamin A intake (95% CI, 0.10-0.80; P < .033) and disease conditions (95% CI, 0.10-0.79; P = .006) through weighted UniFrac distances. The candidate pathogen associated with the disease groups were identified through analysis of the composition of microbiomes analysis.

CONCLUSIONS

This study provides preliminary evidence for the fecal microbiome-derived dysbiosis signature and pathobiome concept that may be observed in young children during illness.

Jatrorrhizine Balances the Gut Microbiota and Reverses Learning and Memory Deficits in APP/PS1 transgenic mice

Alzheimer's disease (AD) is a complex disorder influenced by both genetic and environmental components and has become a major public health issue throughout the world. Oxidative stress and inflammation play important roles in the evolution of those major pathological symptoms. Jatrorrhizine (JAT), a main component of a traditional Chinese herbal, coptidis rhizome, has been shown to have neuroprotective effects and we previously showed that it is also able to clear oxygen free radicals and reduce inflammatory responses. In this study, we demonstrated that JAT administration could alleviate the learning and memory deficits in AD. Furthermore, we also found that JAT treatment reduced the levels of Aβ plaques in the cortex and hippocampus of APP/PS1 double-transgenic mice. Other studies suggest that there are gut microbiome alterations in AD. In order to explore the underlying mechanisms between gut microbiota and AD, DNA sequencing for 16s rDNA V3-V4 was performed in fecal samples from APP/PS1 transgenic mice and C57BL/6 wild-type (WT) mice. Our results indicated that APP/PS1 mice showed less Operational Taxonomic Units (OTUs) abundance in gut microbiota than WT mice and with different composition. Furthermore, JAT treatment enriched OTUs abundance and alpha diversity in APP/PS1 mice compared to WT mice. High dose of JAT treatment altered the abundance of some specific gut microbiota such as the most predominant phylum Firmicutes and Bacteroidetes in APP/PS1 mice. In conclusion, APP/PS1 mice display gut dysbiosis, and JAT treatment not only improved the memory deficits, but also regulated the abundance of the microbiota. This may provide a therapeutic way to balance the gut dysbiosis in AD patients.

Metagenomics in ophthalmology: current findings and future prospectives

Less than 1% of all microorganisms of the available environmental microbiota can be cultured with the currently available techniques. Metagenomics is a new methodology of high-throughput DNA sequencing, able to provide taxonomic and functional profiles of microbial communities without the necessity to culture microbes in the laboratory. Metagenomics opens to a ‘hypothesis-free’ approach, giving important details for future research and treatment of ocular diseases in ophthalmology, such as ocular infection and ocular surface diseases.