Fecal siderophore genes are potential biomarkers for ulcerative colitis
Bibliographic record
Abstract
Ulcerative colitis (UC) and Crohn’s disease (CD) are chronic inflammatory bowel diseases (IBDs) with largely unclear etiologies and complex pathogeneses. The pathogenesis of UC has been linked to an imbalance in the gut microbiota, including in the prevalence of Enterobacteriaceae, especially pathogenic Escherichia coli (E. coli).[1] The UC diagnosis and assessment primarily rely on colonoscopy and mucosal biopsy pathology, which are limited by their invasiveness, constraints on medical resources, and potential risks and complications. Several biomarkers, such as serum C-reactive protein (CRP), fecal calprotectin, and fecal lactoferrin, are currently recommended for assessing UC disease activity. However, these markers are primarily inflammation-related factors produced by the host, not specific to IBD, and are influenced by other inflammatory states. Microbiome-related biomarkers are used as direct indicators of the gut microecosystem and have considerable potential for disease assessment and therapeutic guidance in IBD. However, current analyses of gut microbiota, such as 16S rRNA or metagenomic sequencing, are often time-consuming and costly. Siderophore, a low-molecular-weight protein secreted extracellularly to chelate ferric iron, is a crucial virulence factor in iron acquisition of bacteria and fungi. The presence of siderophores can indirectly reflect bacterial abundance and activity.[2] Gram-negative pathogens (E. coli, Klebsiella, Shigella, Salmonella, and Yersinia) have four common types of siderophores, including enterobactin, salmochelin, aerobactin, and yersiniabactin.[3] Here, we aimed to explore the relationships between positivity rates and copy numbers of siderophore genes and clinical characteristics of UC to evaluate their potential as noninvasive biomarkers for assessing UC disease activity. This single-center cohort study involved patients with UC who visited the First Medical Center of the People’s Liberation Army General Hospital from 2017 to 2023. The inclusion criteria were: age, 18–75 years; active UC (Mayo score ≥3); and no history of abdominal surgery or colorectal cancer. Clinical data were retrieved from medical records. The clinical phenotypes and disease activity were determined using the Montreal classification and Mayo score. The healthy control (HC) group consisted of fecal microbiota transplantation (FMT) candidate donors. All participants provided written informed consent. The study was approved by the ethics committee of the Chinese People’s Liberation Army General Hospital (S2016-129-01, S2016-130-01, S2021-602-01). Polymerase chain reaction (PCR) and absolute quantitative real-time PCR provided the positivity rates and copy numbers of siderophore genes. The copy number was calculated as copies/ng DNA = (DNA content [ng] × 6.023 × 1023) (template length × 660). The default template length was set to the base number of the E. coli genome (4700 kb). Standard curves were generated using a 10-fold serial dilution of DNA from the reference strains or plasmids [Supplementary Methods and Supplementary Figure 1, https://links.lww.com/CM9/C258]. Measurement data represent the median and interquartile range, and counting data with numbers and percentages. Differences between groups were assessed using the chi-squared, Mann–Whitney U, and Pearson correlation tests. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. Statistical significance was set at P <0.05. Statistical analyses were performed using SPSS 21.0 (IBM SPSS, Armonk, NY, USA), and figures were created using GraphPad Prism 7.0 (GraphPad Software, San Diego, CA, USA) and Adobe Illustrator CC 22.0 (Adobe, San Jose, CA, USA). We enrolled 166 patients with UC and 168 healthy adults who were FMT candidate donors as HCs. The baseline clinical characteristics of the 166 UC patients are presented in Supplementary Table 1, https://links.lww.com/CM9/C258. According to the Montreal classification, there were 112 cases (67.5%) of extensive UC, 46 (27.7%) of left-sided UC, and 8 (4.8%) of proctitis. Based on the Mayo clinical score, 46 patients were in the severe, 81 in the moderate, and 39 in the mild active stages. According to the Mayo Endoscopic Score, 116 patients were in the severe, 45 in the moderate, and 5 in the mild active stages. The UC group had a higher prevalence of all siderophore genes than the HC group [Supplementary Table 2, https://links.lww.com/CM9/C258], especially for the salmochelin (iroB 30.7% vs. 13.3%, P <0.01; iroN 38.0% vs. 21.8%, P <0.01) and aerobactin genes (iucA 57.8% vs. 42.4%, P <0.01; iutA 59.0% vs. 44.2%, P <0.01). The total copy number of siderophore genes was also higher in the UC group than in the HC group (1182.49 copies vs. 176.44 copies, P <0.01); moreover, the UC group had higher copy numbers of all eight siderophore genes compared to the HC group [Supplementary Table 3, https://links.lww.com/CM9/C258]. We used the total copy number of siderophore genes to distinguish UC patients from HCs, with the area under the receiver operating characteristic (AUROC) of 0.701 (95% confidence interval [CI], 0.644–0.757, P <0.001). A threshold of 2877.68 copies/ng yielded a specificity of 90.3% and a sensitivity of 33.1% [Figure 1A].Figure 1: (A) ROC curves of siderophore gene copy number for distinguishing active UC from HCs. (B) ROC curves of siderophore gene copy number, CRP, and ESR. AUROC: CRP: C-reactive protein; ESR: Erythrocyte sedimentation rate; HC: Healthy control; ROC: Receiver operating characteristic; UC: Ulcerative colitis.The total copy number of siderophore genes was significantly higher in patients with severe active UC than in those with moderate (3111.03 copies/ng vs. 1183.54 copies/ng DNA, P = 0.013) and mild (3111.03 copies/ng vs. 672.60 copies/ng DNA, P = 0.005) active UC [Supplementary Figure 2, Supplementary Table 4, https://links.lww.com/CM9/C258]. Patients with severe endoscopic activity exhibited an increased total copy number of fecal siderophore genes, higher than that in patients with mild-to-moderate endoscopic activity (1318.02 copies vs. 723.10 copies, P = 0.044) [Supplementary Figure 3, Supplementary Table 5, https://links.lww.com/CM9/C258]. There were no significant differences in the total copy number between different sexes, disease extents, and medication administration. The ROC curves indicated that a threshold of 10,298.63 copies/ng DNA diagnosed severe active UC, with a specificity of 92.5% and a sensitivity of 43.5%. In contrast, a CRP cut-off value of 0.8 mg/dL showed a sensitivity and specificity of 61.4% and 82.2%, respectively, in diagnosing severe active UC, and ESR (threshold 30 mm/h) presented a sensitivity of 36.4% and a specificity of 86.3%, respectively [Figure 1B]. When combining total fecal siderophore gene copy number and serum CRP in a parallel test, the sensitivity and specificity were 89.1% and 75.8%, respectively, with a positive predictive value (PPV) and a negative predictive value (NPV) of 58.6% and 94.8%, respectively. When total fecal siderophore gene copy number was combined with a parallel fecal immunochemical test (FIT), the sensitivity, specificity, PPV, and NPV for severe UC were 45.7%, 94.2%, 75.0%, and 81.9%, respectively [Supplementary Table 6, https://links.lww.com/CM9/C258]. Regarding the detection of severe endoscopic activity, the threshold of 10,298.63 copies/ng achieved a sensitivity and specificity of 22.4% and 94.0%, respectively. When tested in parallel with serum CRP, a specificity of 88.0%, sensitivity of 55.2%, PPV of 91.4%, and NPV of 45.8% were obtained. In terms of siderophores as disease biomarkers, it has been reported that fungal siderophores have potential diagnostic value in invasive aspergillosis.[3] Isolated E. coli in inflamed mucosal sites of patients with UC had a higher prevalence of siderophore genes, such as iroN (72.7%), fyuA (68.2%), and iucC (68.2%).[4] However, the applicability of bacterial siderophores as disease biomarkers, particularly in UC, remains underexplored. In the current study, we first reported that the positivity rates and copy numbers of eight genes associated with four siderophores (enterobactin, salmochelin, aerobactin, and yersiniabactin) were significantly higher in the feces of patients with active UC than in those of HCs. A total siderophore gene copy number had high specificity in differentiating patients with active UC and HC. Gut dysbiosis predates the onset of the disease, and studies have shown that a panel of serum antibodies, including anti-E. coli outer membrane porin C and anti-flagellins antibodies, can predict CD diagnosis years before.[5] Our work represents an important foundation for future work on the preclinical phase of UC, especially in early detection and diagnosis. In clinical practice, noninvasive biomarkers have gained considerable attention owing to their extensive application in disease monitoring and therapeutic efficacy assessment. The diagnostic efficacy of fecal calprotectin and lactoferrin has been investigated in differentiating patients with active and inactive UC. However, there are few studies on biomarkers for distinguishing mild-to-moderate from severe active UC, especially in endoscopic severe patients. We found that severe active UC had a higher total siderophore gene copy number than moderate and mild active UC. Notably, when tested in parallel with serum CRP, total siderophore gene copy number had both high specificity and sensitivity in diagnosing patients with severe active UC, both in clinical and endoscopic scores. A high specificity reduces misdiagnosis rates, and the frequency of colonoscopy in mild-to-moderate patients. Our study has several limitations. First, the patient sample size was relatively limited. Future research should verify the relationship between the total copy number of siderophore genes and UC disease activity in a larger cohort, and develop predictive models for assessing disease activity. Long-term monitoring is also necessary to evaluate the diagnostic efficacy during the course of the disease. Second, further analysis by combining metagenomic sequencing and gene detection could more comprehensively reflect microbiota changes. Third, comparative studies with other fecal biomarkers, like fecal calprotectin, should be carried out to fully evaluate the value of siderophore gene copy number as a UC biomarker. In conclusion, this is a pioneering study to report higher siderophore gene prevalence and total copy number in the feces of patients with active UC than in those of HCs, particularly in severe active UC. These bacterial biomarkers performed well in the diagnosis and assessment of UC and provided a new noninvasive quantitative tool for UC severity clinical evaluation. Siderophore gene copy number constitutes a specific and direct parameter for clinicians to use in disease management. Combined with existing biomarkers, this approach can aid in the formulation of personalized treatment plans and reduce reliance on invasive diagnostic methods for determining clinical and endoscopic disease activity in UC. Acknowledgments We express our deepest appreciation to Professor Kaichun Wu (Xijing Hospital, Xi’an, China) for his kind donation of E. coli strain LF82. Funding None. Conflicts of interest None.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".