Metagenomics: Tools To Unpack the Total Genomes of Microorganisms: Methods, Applications, and Emerging Frontiers- A Narrative Review

Modern approaches to gut microbiome investigation: Sequencing, culturomics, metabolomics, and beyond.

The human gut microbiome is a complex and constantly evolving community of trillions of microorganisms that are crucial to various aspects of health and disease. It impacts digestion, metabolism, immune function, neurological processes, and vulnerability to illnesses. Recent technological advancements in biology and engineering have transformed microbiome research, allowing for more detailed analysis of microbial composition, functions, and interactions with the host. This review offers a thorough overview of both current and emerging methods for studying the gut microbiome, including sample collection techniques, culture-based approaches like culturomics and microfluidics, as well as culture-independent methods such as 16S rRNA sequencing, shotgun metagenomics, and the integration of multi-omics approaches like metabolomics, proteomics, and transcriptomics. It also discusses innovative tools including single-cell genomics, spatial transcriptomics, and microbiome-on-a-chip platforms, which hold promise for revealing host-microbe interactions at unprecedented levels of detail. The review underscores the importance of combining biological insights with engineering innovations particularly microfluidics and organ-on-a-chip models to recreate gut environments that mimic physiological conditions. Additionally, it explores the potential of artificial intelligence and machine learning in analyzing data and developing predictive models for personalized microbiome-based diagnostics and therapies. Acknowledging challenges such as microbial diversity, environmental sensitivity, and technical hurdles, this review aims to guide researchers in choosing optimal tools to study the gut microbiota, deepen mechanistic understanding, and translate findings into clinical applications that enhance human health.

Promises and Pitfalls of Long-Read Sequencing for Resolving Microbial Complexity.

Long-read sequencing (LRS) has driven a transition in microbial genomics, overcoming the assembly fragmentation inherent to short-read sequencing. This review elucidates the impact of LRS across isolate genomics, metagenomics, and multi-omics domains. By spanning extensive repetitive regions, LRS facilitates the reconstruction of circular chromosomes and precisely resolves mobile genetic elements (MGEs). In metagenomics, LRS enables strain-level resolution, the recovery of circular metagenome-assembled genomes, and the precise localization of MGEs within host replicons. Furthermore, the single-molecule, amplification-free properties of LRS provide enhanced resolution of native epigenetic modifications and full-length transcriptomes. Despite these advancements, widespread implementation remains constrained by multidimensional challenges, including stringent high-molecular-weight DNA requirements, depth deficits, and computational overhead. Nevertheless, LRS is increasingly becoming the method of choice for isolate genomics and metagenomics. As detection technologies and algorithms progress, LRS will further improve our ability to decipher the structural and functional diversity of microbial ecosystems.

metaWEPP: leveraging biobank-scale intra-species phylogenies for near-haplotype resolution in metagenomic analysis

Abstract Metagenomic sequencing is transforming diverse areas of health and biological sciences, including pathogen surveillance, clinical diagnostics, and microbiome research. However, the inherent complexity of metagenomic data limits most computational tools to species-level classification and abundance estimation, overlooking within-species genetic diversity that drives key phenotypes. We present metaWEPP, a novel computational pipeline that achieves near-haplotype resolution in metagenomic analysis for species with adequate representation in reference genome biobanks and having sufficient sequencing depth and genome coverage. Specifically, metaWEPP assigns sequencing reads to species using standard taxonomic classifiers, phylogenetically places them onto species-specific mutation-annotated trees of publicly available sequences, and selects the haplotypes that best explain the sample. It also reports unaccounted alleles indicative of novel variants and provides an interactive dashboard for read-level visualization. Applied to diverse metagenomic and mixed-genome samples from prior studies, metaWEPP produced concordant species-level results, while revealing finer lineage- and haplotype-level insights not captured by existing tools. On various clinical samples, metaWEPP identified infecting pathogens and additionally provided credible lineage- and haplotype-level information that can support clinical decision-making. On wastewater samples, metaWEPP uncovered previously undetected haplotype clusters of epidemiological relevance. These findings demonstrate metaWEPP’s ability to advance various clinical, epidemiological, and research applications with deeper, actionable insights.

UC Merced Previously Published Works

Bioinformatic tools for microbiome analysis: from raw sequences to biological insights

This review presents a practical, workflow-oriented guide to microbiome data analysis, from raw DNA sequence processing to statistical interpretation and biological insight, and highlights emerging technologies, including machine learning methods that are beginning to reshape the field.

Siwa spring microbiomes as reservoirs of biosynthetic gene clusters: Unlocking natural product potential

The integrated bioinformatics pipeline enabled the reconstruction of 37 medium-to-high-quality metagenome-assembled genomes (MAGs), and recovered 147 BGCs mostly from Pseudomonadota, Actinomycetota, and Acidobacteriota phyla, highlighting the Siwa Oasis as a promising reservoir of unexplored biosynthetic potential and a valuable resource for natural product discovery to address global health challenges.