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. 2025 Jul 1:15:1595884.
doi: 10.3389/fcimb.2025.1595884. eCollection 2025.

Exploration of fecal microbiota in newly diagnosed patients with inflammatory bowel disease using shotgun metagenomics

Macarena Orejudo  1 , Manuel J Gómez  2 , Sabino Riestra  3 , Montserrat Rivero  4 , Ana Gutiérrez  5 , Iago Rodríguez-Lago  6 , Luis Fernández-Salazar  7 , Daniel Ceballos  8 , José Manuel Benítez  9 , Mariam Aguas  10 , Iria Bastón-Rey  11 , Fernando Bermejo  12 , María José Casanova  1 , Rufo H Lorente-Poyatos  13 , Yolanda Ber  14 , Daniel Ginard  15 , María Esteve  16 , Ruth de Francisco  3 , María José García  4 , Rubén Francés  17   18 , Ainhoa Rodríguez  6 , Noelia Alcaide Suárez  7 , Elena Guerra Del Río  8 , Pilar Soto  9 , Pilar Nos  10 , Manuel Barreiro-de Acosta  11 , Iván Guerra  12 , Daniel Hervías Cruz  13 , Manuel Domínguez Cajal  14 , Vanesa Royo  15 , Montserrat Aceituno  16 , Laila Aldars-García  1 , Ana Garre  1 , Cristina Ramírez  1 , Irene Soleto  1 , Ina Schuppe-Koistinen  19 , Lars Engstrand  19 , Montse Baldán-Martín  1 , Fátima Sánchez-Cabo  2 , Javier P Gisbert #  1 , María Chaparro #  1
Affiliations

Exploration of fecal microbiota in newly diagnosed patients with inflammatory bowel disease using shotgun metagenomics

Macarena Orejudo et al. Front Cell Infect Microbiol. .

Abstract

Introduction: Dysbiosis is a key mechanism in inflammatory bowel disease (IBD) pathophysiology. Previous microbiota studies in IBD generally have involved patients treated with immunosuppressive agents, which can affect the results. We aimed to elucidate the fecal microbiota composition in newly diagnosed treatment-naïve IBD patients.

Methods: Microbiota from stool samples were investigated using shotgun metagenomics sequencing and subsequent bioinformatics analysis.

Results: A total of 103 patients with Crohn's disease (CD), 144 with ulcerative colitis (UC), and 49 healthy controls (HC) were included. CD patients had significantly lower species-level diversity than those with UC and HC. CD subgroups with Ileocolonic location and stricturing behavior showed reduced diversity compared to HC. A negative correlation was observed between endoscopic severity and microbial diversity in CD patients. UC patients had similar microbial diversity to HC, which was unaffected by disease activity. Taxonomic abundance analysis revealed a tendency towards a higher relative abundance of Escherichia coli and a lower relative abundance of Faecalibacterium prausnitzii in IBD patients compared to HC. However, the most significant differences in these patients compared to HC were observed in less abundant species, such as Toxoplasma gondii, Gemella morbillorum, and several species of the Adlercreutzia genera. Functional analysis in these patients highlighted changes in carbohydrate and nucleotide pathways.

Discussion: Our data suggest that newly diagnosed CD patients show significant microbiota composition disparities compared to UC patients and HC. Microbiota differences in these patients are linked to dysbiosis, characterized by a reduction in beneficial genera such as Gemella and Adlercreutzia, and a rise in pathogenic species.

Keywords: Crohn’s disease; inflammatory bowel disease; metagenomics; microbiota; shotgun; ulcerative colitis.

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Conflict of interest statement

MC has served as speaker, consultant or research or education funding from MSD, Abbvie, Hospira, Pfizer, Takeda, Janssen, Ferring, Shire Pharmaceuticals, Dr. Falk Pharma, Tillotts Pharma, Biogen, Gilead and Lilly. JG has served as speaker, consultant, and advisory member for or has received research funding from MSD, Abbvie, Pfizer, Kern Pharma, Biogen, Mylan, Takeda, Janssen, Roche, Sandoz, Celgene/Bristol Myers, Gilead/Galapagos, Lilly, Ferring, Faes Farma, Shire Pharmaceuticals, Dr. Falk Pharma, Tillotts Pharma, Chiesi, Casen Fleet, Gebro Pharma, Otsuka Pharmaceutical, Norgine and Vifor Pharma. LF-S has served as advisory member for Ferring and has received research funding from Ferring, Janssen and Takeda. FB has been a speaker, consultant and advisory member or has received research funding from Abbvie, Takeda, Janssen, Pfizer, MSD, Biogen, Amgen, Galapagos, Ferring, Faes Farma, Tillotts Pharma, Chiesi, Vifor Pharma, Lilly. MB-A has served as a speaker, consultant and advisory member for or has received research funding from MSD, AbbVie, Janssen, Kern Pharma, Takeda, Galapagos-Alpha Sigma, Pfizer, Sandoz, Fresenius, Avibax, Lilly, Ferring, Faes Farma, Dr. Falk Pharma, Chiesi, Adacyte and TillotsPharma. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Serum C-reactive protein (CRP) levels in patients with newly diagnosed inflammatory bowel disease. Bar charts showing C-reactive protein (CRP) levels in CD and UC patients (A) according to CD location (B), CD behavior (C), CD activity (D), UC extension (E) and UC activity (F).
Figure 2
Figure 2
Principal Component Analysis of gut microbiome composition at the phylum level in healthy controls and patients with inflammatory bowel disease (IBD). Panels A-F show the distribution of samples according to: IBD type (A), CD location (B), CD behavior (C), CD severity (D), UC extension (E), and UC severity (F).
Figure 3
Figure 3
α-Diversity analysis in fecal samples from IBD patients and healthy controls (HC). Panels A-F depict comparisons of α-diversity assessed by the Shannon Diversity Index between HC and patients groups based on: IBD type (A), CD location (B), CD behavior (C), CD severity (D), UC extension (E), and UC severity (F). *p ≤ 0.05.
Figure 4
Figure 4
Microbiological composition at domain and species levels in the IBDomics cohort. Histograms exhibit taxonomic distribution at domain (A) and species (B) levels across the CD, UC and HC study groups. The graphs represent a selection of species with significant differences (Kruskal-Wallis p_value < 0.05) between groups: Toxoplasma gondii (C), Aspergillus oryzae (D), and Gemella morbillorum (E) levels, expressed in counts per million.
Figure 5
Figure 5
Taxonomic abundance based on Crohn’s disease location. Stacked bars in both histograms show the average relative abundances of all domains (A) and the most prevalent species (B) identified in the three CD patient groups defined according to disease location, and in HC. Panels C-E exhibit a selection of species with significant differences (Kruskal-Wallis p_value < 0.05) between groups: Eubacterium sp. MSJ-33 (C), Wijia chipingensis (D), and Adlercreutzia hattorii (E) levels, expressed in counts per million.
Figure 6
Figure 6
Microbiological profile corresponding to Crohn’s disease behavior. The first two panels display the average relative abundances of all domains (A) and the most common species (B) in the three CD patient groups defined according to disease behavior, and in HC. The remaining graphics show a selection of species with significant differences (Kruskal-Wallis p_value < 0.05) between groups: Wijia chipingensis (C), Eubacterium sp. MSJ-33 (D), and Limosilactobacillus frumenti (E) levels, represented in counts per million.
Figure 7
Figure 7
Metagenomics profile in Crohn’s disease patients categorized according to their disease activity. Histograms show the taxonomic abundances of all domains (A) and the most common species (B), detected in the three CD patient groups defined according to disease activity, and in HC. Graphs show a selection of species with significant differences (Kruskal-Wallis p_value < 0.05) between groups: Eubacterium sp. MSJ-33 (C), Wijia chipingensis (D), and Roseburia intestinalis (E) levels, represented in counts per million.
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