Host DNA contents in fecal metagenomics as a biomarker for intestinal diseases and effective treatment

Abstract

Background: Compromised intestinal barrier (CIB) has been associated with many enteropathies, including colorectal cancer (CRC) and inflammatory bowel disease (IBD). We hypothesized that CIB could lead to increased host-derived contents including epithelial cells into the gut, change its physio-metabolic properties, and globally alter microbial community and metabolic capacities. Results: Consistently, we found host DNA contents (HDCs), calculated as the percentage of metagenomic sequencing reads mapped to the host genome, were significantly elevated in patients of CRC and Crohn's disease (CD). Consistent with our hypothesis, we found that HDC correlated with microbial-and metabolic-biomarkers of these diseases, contributed significantly to machine-learning models for patient stratification and was consequently ranked as a top contributor. CD patients with treatment could partially reverse the changes of many CD-signature species over time, with reduced HDC and fecal calprotectin (FCP) levels. Strikingly, HDC showed stronger correlations with the reversing changes of the CD-related species than FCP, and contributed greatly in classifying treatment responses, suggesting that it was also a biomarker for effective treatment. Conclusions: Together, we revealed that association between HDCs and gut dysbiosis, and identified HDC as a novel biomarker from fecal metagenomics for diagnosis and effective treatment of intestinal diseases; our results also suggested that host-derived contents may have greater impact on gut microbiota than previously anticipated.

Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models

“…Together, our results revealed correlated changes between marker species and metabolic pathways and suggested that both species and metabolic functions could be driven by the increased human-derived contents leaked into the gut due to CIB, consistent with our previous results ( 36 ).…”

“…Taxonomic analysis revealed that the alpha diversity was not significantly changed in all but one CRC data set (PRJDB4176) compared with their respective controls; conversely, alpha diversity was decreased significantly in patients of most CD data sets, while it did not show consistent trends in UC patients ( Table S1 , Wilcoxon rank sum test, P value <0.05). Interestingly, we found that the human DNA contents (HDCs), calculated as the percentage of sequencing reads mapped to the human genome, were significantly higher in patients in all diseases except one UC data set (PRJEB1220) ( Table S1 ), consistent with our results ( 36 ) showing that HDC could be used as a marker for intestinal diseases; the increased level of HDCs are likely due to the high level of deciduous epithelial and/or blood cells found in stools of patients with IBD or CRC, resulting from gut injury and quickening cell cycles ( 22 , 25 , 30 , 37 ).…”

“…The remaining “clean” reads were then mapped to the human reference genome (hg19) using bowtie2 (version 2.3.4.3) ( 74 ) with default settings to identify and remove human reads. The identified human reads were also used to compute HDCs for each sample as the percentage of mapped reads out of total clean reads, which have been shown to be a marker for intestinal barrier dysfunction and correlate with the marker species of several intestinal diseases ( 36 ). For samples that were sequenced multiple times (e.g., for the purpose of increasing sequencing depths), the resulting multiple sequencing files were merged before further analysis.…”

Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning

“…Artificial intelligence has recently attracted much attention in various fields of health and medicine. Different artificial intelligence and machine learning (ML) methods have been applied for various purposes, including image recognition, patient phenotyping, and outcome prediction for diseases such as cancer [15][16][17][18][19], cardiac arrest [20], Alzheimer's disease [21][22][23], respiratory diseases [24,25], rheumatic diseases [26], cornea and retinal diseases [27,28], gastrointestinal diseases [29,30], and infectious diseases [31][32][33][34][35]. These studies revealed that artificial intelligence has the capacity to assist clinicians in the disease diagnosis with high efficiency and accuracy.…”

Microbial ecology along the buffalo digestive tract provides insights to their functions and interactions with the host

“…So far, researches on the microbial ecology along the DT in ruminants mostly focus on rumen [27][28][29][30][31][32][33][34][35] with a few studies on gut/feces 36 , while other sites have been largely overlooked, despite accumulating evidence support their important roles. For example, in human, gut microbiota have been linked to many aspects of human life, including health 37,38 and diseases [39][40][41][42][43] , development 44,45 , responses to drugs and treatments [46][47][48] .…”