Journal: iScience

Article Title: Flowtigs: Safety in flow decompositions for assembly graphs

doi: 10.1016/j.isci.2024.111208

Figure Lengend Snippet:

Article Snippet: Our experiments with real data were performed on the ZymoBIOMICS Gut Microbiome Standard dataset (henceforth referred to by Zymo), a microbial community that mimics the human gut microbiome.

Techniques: Software

Journal: Scientific Data

Article Title: Fox Insight at 5 years - a cohort of 54,000 participants contributing longitudinal patient-reported outcome, genetic, and microbiome data relating to Parkinson’s disease

doi: 10.1038/s41597-024-03407-9

Figure Lengend Snippet: Interface for downloading microbiome data in Fox DEN.

Article Snippet: In partnership with 23andMe, gut and oral microbiome data was collected from approximately 650 participants, both those with PD (approximately 65%) and those without PD (approximately 35%) as part of the Parkinson’s Disease Microbiome (PDMB) Sub-Study.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Known factors that impact the composition and function of human gut microbiome. Various intrinsic and extrinsic stressors contribute to short-term, long-term, or permanent alteration of microbial communities. Medications, especially antibiotics, and infections by gastrointestinal pathogens may cause long-term dysbiosis by permanent changes in the relative abundance of major phyla, especially the ratio of Bacillota (Firmicutes) to Bacteroidota and reducing the abundance of beneficial bacteria, especially SCFA bacteria that may influence the function of HGM. Chronic and metabolic diseases may be caused by changes in the gut microbiome or may influencing the gut microbiome composition and function (Created in BioRender. Safarchi, A. (2025) https://BioRender.com ).

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Medications, Bacteria

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Effects of xenobiotics on the human gut microbiome composition, showing the increase and decrease of bacterial taxa for each class of xenobiotics.

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Pesticides

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Defining resilient and resistant gut microbiome: characteristics and distinctions.

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Functional Assay

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Response of the human gut microbiome to weak and strong stressors. (A) Temporal changes and recovery of microbiome composition, diversity and function under weak and strong stressors illustrated from a resistant to a resilient or susceptible gut microbiome. The impact of this changes may also vary from small to high changes (vertical axis). Recovery to baseline may take a few days for weak stressors (e.g., short-term travel, short-term dietary changes, etc) to several months for strong ones (horizontal axis), with faster recovery observed in resistant and resilient microbiomes. In susceptible microbiomes or individuals with specific conditions (e.g., genetics, environment and lifestyle, infections, medication, cancers, metabolic disorders), the gut microbiome may not return to baseline, leading to stable dysbiosis or prolonged recovery times. The time and intensity of the response to disturbance factors vary among resistant, resilient, and susceptible gut microbiomes. (B) Four human gut microbiome recovery scenarios following exposure to strong disturbance factors. Microbiome composition and function can fully or partially recover or remain unrecovered, resulting in stable dysbiosis. The abundance of SCFA-producing bacteria and Bacteroides taxa in the baseline microbiome plays a crucial role in the recovery of both the composition and function of the human gut microbiome (Created in BioRender. Safarchi, A. (2025) https://BioRender.com ).

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Bacteria

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Nonspecific and specific biomarkers associated with a resilient gut microbiome. Certain biomarkers, including diversity metrics and a greater abundance of beneficial taxa and antimicrobial compounds, are commonly found in resilient and healthy microbiota. These biomarkers are essential for maintaining gut health, promoting resilience, and facilitating faster recovery. Specific biomarkers highly correlated with resilience include recovery-associated bacterial taxa (e.g., Bacteroides , Alistipes , Parabacteroides , and Akkermansia, etc.) and a higher proportion of beneficial bacteria, such as SCFA-producing and bacteriocin-producing bacteria. Additionally, specific antimicrobial peptides (e.g., REG3G) and bacteriocins (e.g., BSAP-3, Acodocin, pINC8, and PIS) play a crucial role in maintaining microbiome stability and recovery by inhibiting the growth and colonization of opportunistic and pathogenic bacteria. These specific biomarkers are likely to play a significant role in maintaining gut resilience and may serve as indicators of a resilient microbiome (Created in BioRender. Safarchi, A. (2025) https://BioRender.com ).

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Bacteria

Journal: Frontiers in Microbiology

Article Title: Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges

doi: 10.3389/fmicb.2025.1559521

Figure Lengend Snippet: Available online databases for multi-omics analysis of human gut microbiome.

Article Snippet: An integration of multi-omics data using machine learning and artificial intelligence (AI) is poised to significantly enhance our understanding of gut microbiome resilience.

Techniques: Biomarker Discovery, Functional Assay, Gene Expression