Dynamics of the microbiota in patients with Clostridioides difficile: Recurrence, treatment, sex, and immunosuppression.

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Learn more: PMC Disclaimer | PMC Copyright Notice PLoS Pathog . 2026 Apr 6;22(4):e1014063. doi: 10.1371/journal.ppat.1014063 Search in PMC Search in PubMed View in NLM Catalog Add to search Dynamics of the microbiota in patients with Clostridioides difficile : Recurrence, treatment, sex, and immunosuppression Maria Paz Ventero Maria Paz Ventero 1 Microbiology Service, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing Find articles by Maria Paz Ventero 1, ‡, # , Rocio Herrero Rocio Herrero 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – original draft, Writing – review & editing Find articles by Rocio Herrero 2, ‡, # , Iryna Tyshkovska Iryna Tyshkovska 1 Microbiology Service, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain Data curation, Investigation, Methodology, Resources, Writing – review & editing Find articles by Iryna Tyshkovska 1 , Maria-Dolores Valverde-Fredet Maria-Dolores Valverde-Fredet 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain Conceptualization, Data curation, Formal analysis, Investigation, Resources, Writing – review & editing Find articles by Maria-Dolores Valverde-Fredet 2 , Juan Carlos Rodríguez Juan Carlos Rodríguez 1 Microbiology Service, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing Find articles by Juan Carlos Rodríguez 1, 3, * , Miguel Rodríguez-Fernández Miguel Rodríguez-Fernández 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain Data curation, Methodology, Resources, Writing – review & editing Find articles by Miguel Rodríguez-Fernández 2 , Pilar González-De-La-Aleja Pilar González-De-La-Aleja 4 Unit of Infectious Diseases, Alicante General University Hospital - 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Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain Resources, Writing – review & editing Find articles by Silvia Otero 4 , Reinaldo Espindola-Gomez Reinaldo Espindola-Gomez 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain Resources, Writing – review & editing Find articles by Reinaldo Espindola-Gomez 2 , José Manuel Ramos José Manuel Ramos 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain 4 Unit of Infectious Diseases, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain Funding acquisition, Resources, Writing – review & editing Find articles by José Manuel Ramos 3, 4 , Eva M León Eva M León 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain Resources, Writing – review & editing Find articles by Eva M León 2 , Maria García Maria García 5 Unit of Infectious Diseases, Vega Baja University Hospital - Orihuela, Spain-FISABIO, Foundation for the Promotion of Health and Biomedical Research of the Valencian Community, Valencia, Spain Resources, Writing – review & editing Find articles by Maria García 5 , Miguel Nicolas Navarrete-Lorite Miguel Nicolas Navarrete-Lorite 6 Unit of Infectious Diseases, Virgen Macarena University Hospital, Sevilla, Spain Resources, Writing – review & editing Find articles by Miguel Nicolas Navarrete-Lorite 6 , Jara Llenas-García Jara Llenas-García 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain 5 Unit of Infectious Diseases, Vega Baja University Hospital - Orihuela, Spain-FISABIO, Foundation for the Promotion of Health and Biomedical Research of the Valencian Community, Valencia, Spain 7 CIBERINFEC, Carlos III Health Institute, Madrid, Spain Resources, Writing – review & editing Find articles by Jara Llenas-García 3, 5, 7 , Ines Portillo Ines Portillo 6 Unit of Infectious Diseases, Virgen Macarena University Hospital, Sevilla, Spain Resources, Writing – review & editing Find articles by Ines Portillo 6 , Francisco Jover Francisco Jover 8 Unit of Infectious Diseases, Sant Joan D’Alacant University Hospital, Sant Joan D’Alacant, Spain Resources, Writing – review & editing Find articles by Francisco Jover 8 , Maria Tasias Maria Tasias 9 Infectious Diseases Service, La Fe University and Polytechnic Hospital, Valencia, Spain Resources, Writing – review & editing Find articles by Maria Tasias 9 , Juan Jose Caston Juan Jose Caston 10 Unit of Infectious Diseases, Reina Sofía University Hospital, Córdoba, Spain Resources, Writing – review & editing Find articles by Juan Jose Caston 10 , Concepción Gil Concepción Gil 11 Unit of Infectious Diseases, Marina Baixa Hospital, VillaJoiosa, Spain Resources, Writing – review & editing Find articles by Concepción Gil 11 , David Vinuesa-Garcia David Vinuesa-Garcia 12 Unit of Infectious Diseases, San Cecilio University Hospital, Granada, Spain Resources, Writing – review & editing Find articles by David Vinuesa-Garcia 12 , Cristina Gomez-Ayerbe Cristina Gomez-Ayerbe 13 Unit of Infectious Diseases, Virgen de la Victoria University Hospital, Malaga, Spain Resources, Writing – review & editing Find articles by Cristina Gomez-Ayerbe 13 , Francisco J Martínez Marcos Francisco J Martínez Marcos 14 Unit of Infectious Diseases, Juan Ramón Jimenez University Hospital, Huelva, Spain Resources, Writing – review & editing Find articles by Francisco J Martínez Marcos 14 , Nicolas Merchante Nicolas Merchante 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain Formal analysis, Funding acquisition, Investigation, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing, Conceptualization Find articles by Nicolas Merchante 2, 3, ‡ , Esperanza Merino De Lucas Esperanza Merino De Lucas 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain Data curation, Formal analysis, Investigation, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing, Conceptualization Find articles by Esperanza Merino De Lucas 2, 3, ‡ Editor: William Navarre 15 Author information Article notes Copyright and License information 1 Microbiology Service, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain 2 Clinical Unit of Infectious Diseases and Microbiology, Valme University Hospital, Institute of Biomedicine of Seville (IBiS), University of Seville, Sevilla, Spain 3 Clinical Medicine Department, Miguel Hernández University, Elche, Spain 4 Unit of Infectious Diseases, Alicante General University Hospital - Alicante Institute of Health and Biomedical Research (ISABIAL), Alicante, Spain 5 Unit of Infectious Diseases, Vega Baja University Hospital - Orihuela, Spain-FISABIO, Foundation for the Promotion of Health and Biomedical Research of the Valencian Community, Valencia, Spain 6 Unit of Infectious Diseases, Virgen Macarena University Hospital, Sevilla, Spain 7 CIBERINFEC, Carlos III Health Institute, Madrid, Spain 8 Unit of Infectious Diseases, Sant Joan D’Alacant University Hospital, Sant Joan D’Alacant, Spain 9 Infectious Diseases Service, La Fe University and Polytechnic Hospital, Valencia, Spain 10 Unit of Infectious Diseases, Reina Sofía University Hospital, Córdoba, Spain 11 Unit of Infectious Diseases, Marina Baixa Hospital, VillaJoiosa, Spain 12 Unit of Infectious Diseases, San Cecilio University Hospital, Granada, Spain 13 Unit of Infectious Diseases, Virgen de la Victoria University Hospital, Malaga, Spain 14 Unit of Infectious Diseases, Juan Ramón Jimenez University Hospital, Huelva, Spain 15 University of Toronto, CANADA ✉ * E-mail: [email protected] The authors have declared that no competing interests exist. ‡ MPV and RH share first authorship on this work. NM and EMDL are joint senior authors on this work. # Contributed equally. Roles Maria Paz Ventero : Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing Rocio Herrero : Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – original draft, Writing – review & editing Iryna Tyshkovska : Data curation, Investigation, Methodology, Resources, Writing – review & editing Maria-Dolores Valverde-Fredet : Conceptualization, Data curation, Formal analysis, Investigation, Resources, Writing – review & editing Juan Carlos Rodríguez : Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing Miguel Rodríguez-Fernández : Data curation, Methodology, Resources, Writing – review & editing Pilar González-De-La-Aleja : Data curation, Methodology, Resources, Writing – review & editing Marta Trigo : Investigation, Resources, Writing – review & editing Monica Parra : Methodology, Resources, Writing – review & editing Ana-Isabel Aller : Resources, Writing – review & editing Silvia Otero : Resources, Writing – review & editing Reinaldo Espindola-Gomez : Resources, Writing – review & editing José Manuel Ramos : Funding acquisition, Resources, Writing – review & editing Eva M León : Resources, Writing – review & editing Maria García : Resources, Writing – review & editing Miguel Nicolas Navarrete-Lorite : Resources, Writing – review & editing Jara Llenas-García : Resources, Writing – review & editing Ines Portillo : Resources, Writing – review & editing Francisco Jover : Resources, Writing – review & editing Maria Tasias : Resources, Writing – review & editing Juan Jose Caston : Resources, Writing – review & editing Concepción Gil : Resources, Writing – review & editing David Vinuesa-Garcia : Resources, Writing – review & editing Cristina Gomez-Ayerbe : Resources, Writing – review & editing Francisco J Martínez Marcos : Resources, Writing – review & editing Nicolas Merchante : Formal analysis, Funding acquisition, Investigation, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing, Conceptualization Esperanza Merino De Lucas : Data curation, Formal analysis, Investigation, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing, Conceptualization William Navarre : Editor Received 2025 Nov 17; Accepted 2026 Mar 5; Collection date 2026 Apr. © 2026 Ventero et al This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. PMC Copyright notice PMCID: PMC13086424  PMID: 41941490 Abstract Background Alterations in the gut microbiome are central to the pathogenesis and recurrence of Clostridioides difficile infection (CDI). Objective To evaluate intestinal microbiome changes during CDI and their association with recurrence, sex, age, and immunosuppression. Methods Patients from the CDI-ANCRAID-SEICV cohort were consecutively enrolled. Stool samples were obtained at diagnosis (Dx), end of treatment (ET), and eight weeks post-treatment (8W) or upon recurrence. Microbiota composition was analyzed by 16S rRNA sequencing using QIIME2 and R. Outcomes were compared by demographics, immunosuppression, and treatment (vancomycin [VNC], vancomycin-bezlotuzumab [VNC-BZL], fidaxomicin [FDX]). Results Among 143 patients, non-recurrent cases showed higher biodiversity at 8W versus diagnosis (H p = 0.002, ASVs p < 0.001), unlike recurrent cases. Diversity decreased with VNC (H p > 0.001, ASVs p < 0.001) but was preserved with FDX (H p = 0.15). Recovery of Shannon diversity was limited in women (p = 0.50) and immunocompromised patients (p = 0.31). At ET, Fusobacteria and Verrucomicrobiota were less abundant in recurrent than non-recurrent cases (0.77%, 0.53% vs 3.43%, 3.50%). FDX-treated samples showed higher Bacteroidetes (31.33%) compared to VNC (5.23%) or VNC-BZL (3.12%). Women exhibited increased Firmicutes abundance (p = 0.034). Conclusions Restoration of microbial diversity correlates with CDI resolution. FDX preserves gut microbiota better than VNC or VNC-BZL. Women and immunocompromised patients demonstrate impaired microbiota recovery. Author summary Clostridioides difficile infection is a major cause of antibiotic-associated diarrhea and is known for its high risk of recurrence. Alterations in the gut microbiome, a complex community of microorganisms that plays a key role in intestinal health, have been associated with both the risk of recurrence and the clinical course of the disease. In this study, we followed patients with C. difficile infection over time to better understand how the gut microbiome changes during treatment and recovery, and how these changes relate to recurrence, treatment type, sex, age, and immune status. Stool samples were collected at diagnosis, at the end of treatment, and several weeks later, and analyzed using DNA sequencing to characterize the intestinal microbiota. Patients who did not experience recurrence showed a progressive recovery of microbial diversity, whereas this recovery was limited in patients with recurrent infection. Treatment choice also influenced microbiome preservation: fidaxomicin was associated with better maintenance of microbial diversity compared with vancomycin-based regimens. In addition, women and immunocompromised patients showed impaired microbiota recovery. These findings highlight the importance of microbiome restoration in the resolution of C. difficile infection and suggest that both patient characteristics and treatment strategies may influence clinical outcomes. Introduction Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated diarrhea and is associated with increased morbidity and mortality. One of the most significant clinical challenges in managing CDI is its high recurrence rate, affecting approximately 25% of patients following initial treatment. This high recurrence rate underscores the critical need to understand the factors that differentiate sustained clinical resolution from relapse [ 1 , 2 ]. A hallmark of CDI is the disruption of the gut microbiota, characterized by a loss of microbial diversity and alterations in community composition. This dysbiosis creates a favorable environment for the proliferation of C. difficile . Consequently, the restoration of a healthy and resilient gut microbiota is essential for achieving long-term resolution of the infection [ 3 , 4 ]. Numerous studies have generated evidence on the microbiome in patients with recurrent CDI in an effort to identify microbial signatures associated with susceptibility to relapse. However, relatively few have provided analogous data on the microbiome dynamics in patients who achieve sustained clinical cure. Comparative analyses of these two patient populations may provide critical insights into the protective role of the gut microbiota and help identify specific taxa or microbial patterns associated with resistance to recurrence [ 5 , 6 ]. Vancomycin (VNC) and fidaxomicin (FDX) are the two primary agents currently recommended for CDI treatment. Both are effective in achieving initial clinical cure; however, their impact on recurrence rates differs. Emerging evidence suggests that FDX may preserve gut microbial diversity more effectively than VNC. Nonetheless, direct comparative data on their long-term effects on microbiota recovery remain limited [ 7 ]. The aim of this study is to characterize the longitudinal evolution of the gut microbiota in patients with CDI. Secondary aims are to compare the impact of different treatment on microbial diversity, and taxonomic composition, and to identify potential microbiome-related factors that may promote sustained clinical cure or predispose to recurrence. Results A total of 143 patients were included: 137 (95.8%) were primary episode, 58 (40.6%) were male, 50 (34.9%) aged >75 years, and 39 (27.3%) immunocompromised. Most episodes were healthcare-associated or hospital-acquired (40.6%), and nearly three quarters of patients required hospitalization. Comorbidity burden was substantial, with a median Charlson Comorbidity Index of 4 (IQR 2–6). Prior healthcare exposure was frequent, including recent hospitalization and antibiotic use in the preceding three months in over 90% of cases. At the time of CDI diagnosis, 44.7% of patients were receiving active antibiotic therapy, and more than half had chronic proton pump inhibitor use. Severe disease or a complicated clinical course was observed in 23.1% of cases, with low rates of sepsis and ICU admission. Recurrence occurred in approximately one fifth of patients (22.4%) ( Table 1 ).Treatment for CDI consisted of VNC in 88 patients (61.5%), FDX in 33 (23.1%), and VNC–BZL in 22 (15.4%). Exposure to non-CDI antibiotics was observed in 52 patients (36.4%) during CDI treatment, while 83 (58.0%) were exposed during follow-up. Table 1. Demographic characteristics, previous healthcare exposure, comorbidities, clinical course and treatment of Clostridioides difficile infection episode, and clinical outcomes. Population [n= 143] Demographics Age, median (IQR), years 67 (55–79) Age ≥ 75 years old, % (N) 34.9 (50/143) Males, % (N) 40.6 (58/143) Community-acquired (ECDC criteria), % (N) 40.6 (58/143) Healthcare-associated (ECDC criteria), % (N) 29.4 (42/143) Nosocomial (ECDC criteria), % (N) 30.1 (43/143) Hospitalization, % (N) 73.4 (105/143) Previous CDI episode in the past 2 years, % (N) 4.2 (6/143) Previous healthcare exposure Major surgery in the previous 3 months, % (N) 14.7 (21/143) Previous institutionalization, % (N) 3.5 (5/143) Previous hospitalization (last 12 months), % (N) 55.2 (79/143) Previous antibiotic therapy (last 3 months), % (N) 91.6 (131/143) Number of previous antibiotic courses 1, % (N) 48.9 (64/131) 2, % (N) 22.1 (29/131) 3, % (N) 17.6 (23/131) ≥ 4 courses, % (N) 11.5 (15/131) Active antibiotic therapy at CDI diagnosis, % (N) 45.0 (59/131) Discontinuation of concomitant antibiotics, % (N) 27.5 (36/131) Chronic proton pump inhibitor in the previous 3 months, % (N) 58.7 (84/143) Comorbidities Immunosuppression, % (N) 27.3 (39/143) Diabetes, % (N) 22.4 (32/143) Active solid tumor, % (N) 21.0 (30/143) Moderate or severe renal disease, % (N) 9.8 (14/143) Congestive heart failure, % (N) 4.2 (6/143) Chronic respiratory disease, % (N) 3.5 (5/143) Charlson comorbidity index, median (IQR) 4.0 (2.0–6.0) Clinical course and treatment of CDI episode Severe colitis 23.1 (33/143) Sepsis or septic shock associated with CDI 1.4 (2/143) ICU admission 0.7 (1/143) First CDI treatment Vancomycin 56.6 (81/143) Vancomycin + bezlotuzumab 14.0 (20/143) Fidaxomicin 16.1 (23/143) Fidaxomicin extended regimen 3.5 (5/143) Other fidaxomicin-based regimens 4.2 (6/143) Other vancomycin-based regimens 5.6 (8/143) Duration, median (IQR) 10 (9-10) Outcomes Recurrence, % (N) 22.4 (32/143) Recurrence time from diagnostic (days), median (IQR) 26 (19 - 44) Open in a new tab Out of the total cohort, 32 (22.4%) patients experienced a first recurrence of Clostridioides difficile infection (rCDI), of whom 11 progressed to a second recurrence, and 3 subsequently developed a third episode. The first recurrence was predominantly associated with healthcare-related settings (46.9%), subsequent episodes occurred mainly in community-dwelling patients (p = 0.089). A significant reduction in the requirement for hospitalization was observed as the number of recurrences increased, dropping from 50.0% in the first episode to 18.2% in the second (p = 0.046). Furthermore, therapeutic strategies evolved significantly across episodes (p = 0.024); although FDX monotherapy was the preferred choice for the first recurrence (59.4%), management of the second recurrence shifted toward the use of VNC-based regimens and the intensified use of BZL (36.4%) ( S1 Table ). None of the demographic or clinical variables studied were associated with CDI recurrence, which was diagnosed in 32 patients (22.4%) ( S2 Table ). In a similar vein, CDI treatments were similar between age groups and sex, as was exposure to non-CDI antibiotics during and following CDI treatment. However, immunocompromised patients were prescribed VNC in lower percentages, and received more antimicrobial therapy after CDI ( S3 Table ). 417 stool samples were included: 333 samples from patients with no recurrence (111 at each time point) and 84 samples from the 32 patients with recurrence (Diagnostic (Dx) n = 32, End-Treatment (ET) n = 20 from patients responding well to the first round of treatment, and recurrence dx (rec), n = 32). Dynamics of α diversity All samples included in the diversity analyses met the minimum sequencing depth threshold defined by the rarefaction analysis (10,000 reads per sample, S1 Fig ). A homogeneity analysis of the Dx samples showed no statistically significant differences in microbial diversity or taxonomic composition according the studied variables. In the overall cohort of patients, a significant reduction in α diversity was observed after completion of treatment for CDI, as assessed by both the Shannon index (H-index) (Dx: H = 3.14 ± 0.04, ET: H = 2.53 ± 0.06, p < 0.001) and the number of ASVs (Dx: 110.20 ± 4.45, ET: 67.39 ± 3.93, p < 0.001). In patients whose infection resolved, diversity levels at 8W were significantly higher than those observed at the time of CDI diagnosis ( p < 0.001; Fig 1A ). In contrast, in patients who relapsed, the diversity measured in the rec sample remained similar to that in the Dx ( p = 0.69, Fig 1B ). Fig 1. Evolution of α diversity according to the time points studied. Open in a new tab H-index and ASVs observed in the whole population ( n = 143) (A) , and in recurrent patients ( n = 32) (B) . Results of the longitudinal mixed-effects models generated, in green showed the estimated trend for non-recurrent patients, the red line illustrates the same for recurrent patients (C) . Dx = sample from diagnostic, ET: sample from end-treatment, 8W: samples from 8 week post-treatment, rec: sample from recurrence diagnostic. To evaluate the effect of recurrence on microbiota diversity over time using a longitudinal approach, time was included as a continuous variable (defined as the number of days from diagnosis to sample collection). This variable was incorporated into a time-adjusted longitudinal mixed-effects model, yielding results consistent with previous analyses. The linear model showed that patients without recurrence recovered, on average, 0.672 [0.504-0.84], p < 0.001) additional ASVs per day, whereas in patients with recurrence this variable did not increase and instead showed a slight decreasing trend (-0.734, [-1.356-(-0.0112)], p = 0.021) ( Fig 1C and S4 Table ). Similarly, although less markedly, the H-index remained stable over time in patients with recurrence (-0.011 [-0.024-0.002], p = 0.088) (( Fig 1C and S5 Table ). The patients without recurrence were stratified by treatment, sex, immunosuppression and age to assess their influence on diversity dynamics. Among patients treated with VNC, the previously described pattern was confirmed: there was a 57.0% reduction in ASVs ( p < 0.001) and a 23.3% reduction in the H-index ( p < 0.001) at the end of treatment compared to baseline ( Fig 2A and S6 Table ). At 8W, both H-index demonstrated recovery, reaching levels significantly higher than those at diagnosis ( p = 0.002, Fig 2A and S6 Table ). Patients treated with VNC-BZL exhibited a similar pattern during treatment, than patients treated with VNC. In contrast, in patients treated with FDX no significant changes in the H-index were observed over the three time points ( p = 0.15). A reduction in ASVs of 20.8% was observed in ET samples when compared to the diagnostic samples; however, this decrease was not statistically significant ( p = 0.58). The 8W samples showed a higher number of ASVs than the diagnostic samples ( p = 0.020, Fig 2A and S6 Table ). In the ET samples, significantly higher H-index values were observed in patients receiving FDX compared to VNC and VNC-BZL ( p < 0.001). Samples from patients treated with VNZ-BLC showed an H-index comparable to that of patients treated with VNC. This trend was also observed for ASVs ( p = 0.053, S6 Table ). Fig 2. Evolution of α diversity in non-relapsed patients according to the time points studied (1: diagnosis, 2: end of treatment, 3: 8 weeks post-treatment). Open in a new tab H-index and ASVs observed according to the treatment administered (A) , sex (B) , and immunosuppression (C) . Sex-based analyses revealed that men followed the global pattern of α diversity recovery, while women did not. In women, H-index and ASV values observed at 8W did not significantly exceed those obtained at diagnosis ( p = 0.20; p = 0.16, Fig 2B and S6 Table ). To investigate whether these differences were linked to a sex-specific response to treatment, we analyzed patients treated with VNC by sex. At 8W, the 38 women treated with VNC exhibited significantly fewer observed ASVs (133.42 ± 9.26 vs 170.53 ± 13.86, p = 0.024) and a trend toward a lower H-index (H = 3.39 ± 0.09 vs. H = 3.64 ± 0.09, p = 0.068) compared to the 28 men receiving the same treatment. These differences were not observed among patients treated with FDX, in whom both men ( n = 9) and women ( n = 19) showed comparable α diversity values at 8 weeks (male: H = 3.23 ± 0.84, ASVs = 147.88 ± 31.86, female: H = 3.30 ± .0.17, ASVs = 143 ± 20.51; p = 0.90, p = 0.82, respectively). Similarly, immunocompromised patients did not demonstrate an increase in microbial diversity at 8 weeks compared to baseline, as assessed by either the H-index ( p = 0.31) or observed ASVs ( p = 0.18, Fig 2C and S6 Table ). When stratifying by treatment and immunosuppression status, no significant differences in α diversity were detected at 8W among the subgroups. To evaluate the effect of sex on microbiome recovery minimizing the potential confounding effect of immunosuppression, the same analysis was conducted including only immunocompetent patients. In this subgroup, 39.75% of patients were male, a proportion comparable to that of the overall study population. Consistent with our primary analysis, microbiota diversity recovery at eight weeks differed by sex. In women, diversity at eight weeks (ASVs = 141.73, H = 3.33) remained similar to that observed in the CDI diagnosis sample (ASVs = 113.55, H = 3.18) (ASVs: p = 0.30, H: p = 0.86). However, men exhibited a significantly higher diversity at eight weeks (ASVs = 169.48, H = 3.64) compared with diagnostic sample (ASVs = 112.74, H = 3.13) (ASVs: p = 0.002, H: p = 0.002).No significant differences were observed in any diversity index comparisons based on age category. In order to assess the results globally, all variables that showed a significant association in the univariate analysis (recurrence, CDI treatment, sex, and immunosuppression) were included in a longitudinal linear mixed-effects model. In this model, several subgroups with zero observations were identified, which compromised the robustness of the estimates. Therefore, a final model including recurrence, CDI treatment, and sex was generated. The results of this model were consistent with those previously reported. For both, observed ASVs and the H-diversity index, a significant effect of time on microbiome recovery was observed depending on recurrence status. Patients with recurrence exhibited a significantly lower recovery of microbiota diversity over time (ASVs: β = −1.936 [−3.147 to −0.725], p = 0.002; H: β = −0.031 [−0.056 to −0.005], p = 0.018). Sex was also associated with differential recovery of observed ASVs over time, with women showing a significantly lower recovery rate (ASVs: β = −0.496 [−0.939 to −0.053], p = 0.028) ( Fig 3A ). With regard to CDI treatment, differences were observed in the longitudinal evolution of the H-index between patients treated with VNC and FDX (β = −0.016 [−0.030 to −0.001], p = 0.032), with the latter group showing less variation in this index over time ( Fig 3B ). Fig 3. Longitudinal mixed-effects models of microbial diversity over time. Open in a new tab (A) Observed ASV by sex. (B) H-Index by CDI treatment. Points represent individual samples; lines indicate model-predicted trajectories with 95% confidence intervals. These models were also repeated in the subgroup of patients without recurrence, including immunosuppression as a covariate. The same trends were observed, although statistical significance remained close to the threshold. For ASV richness, the p-value for the interaction between time and sex was 0.077, and for the H-index the p-value for the interaction between time and treatment was 0.078. The results of all fitted models are provided in the supplementary material ( S4 and S5 Tables ). Finally, in patients who experienced recurrence, the previously described treatment- and sex-related trends persisted. Specifically, patients treated with FDX showed higher H-index values after completing treatment compared to VNC and VNC-BZL ( p = 0.030), while women exhibited a significantly lower number of observed ASVs compared to men ( p = 0.043, S6 Table ). Taxonomic composition of the microbiota Differences at phylum level. In the Dx samples of the overall study population, the dominant bacterial phyla were Firmicutes (58.1%), Bacteroidetes (27.0%), Proteobacteria (10.0%), Verrucomicrobia (1.6%), Actinobacteria (1.5%), and Fusobacteria (1.5%). These relative abundances remained consistent across all subgroups analyzed. No statistically significant differences in phylum-level composition at diagnosis were observed by the studied variables. In contrast, in the ET samples there were differences according to sex, treatment, and recurrence, but not immunosuppression or age. Sex-based analysis revealed that women had significantly lower levels of Proteobacteria compared to men ( p = 0.018, Fig 4A ). Patients treated with FDX showed a higher relative abundance of Bacteroidetes than those treated with VNC ( p < 0.001) or VNC-BZL ( p < 0.001). Conversely, the proportion of Proteobacteria was lower in FDX-treated patients compared to those treated with VNC ( p < 0.001, Fig 4B ). Finally, patients with recurrence exhibited significantly lower relative abundances of the phyla Fusobacteria ( p = 0.012) and Verrucomicrobia ( p = 0.003), along with a trend toward reduced Bacteroidetes ( p = 0.054) compared to patients without recurrence ( Fig 4C ). Fig 4. Phyla with a relative abundance greater than 1% in the ET samples stratified by sex (A), CDI treatment (B) and recurrence (C). Open in a new tab The x-axis represents the percentage of relative abundances. Related to dynamics of microbiota composition, treatment with FDX did not alter the taxonomic composition of the microbiota, with similar relative abundance percentages maintained for the six phyla studied over the three time points. In patients treated with VNC, the taxonomic composition was modified in five out of the six phyla, and in the case of VNC-BZL, three of these six phyla were altered ( Fig 5A ). In relation to sex, the abundance of Fusobacteria did not show significant changes in men ( p = 0.22). However, in women it increased then decreased significantly ( p = 0.002). Similarly, the phylum Firmicutes exhibited a similar abundance at diagnosis and 8 weeks post-treatment in men ( p = 0.81). In contrast, in women, the 8W sample showed a significantly higher percentage of Firmicutes compared to the diagnostic sample ( p = 0.034, Fig 5B ). Fig 5. Evolution of taxonomic composition in non-relapsed patients according to CDI treatment (A) and sex (B). Open in a new tab Dx = sample from diagnostic, ET: sample from end-treatment, 8W: samples from 8 week post-treatment, rec: sample from recurrence diagnostic. Differentially represented genera. No differentially represented genera were identified in the diagnostic samples or at 8 weeks post-treatment when stratified by age, sex, immunosuppression status, or recurrence. The only time point where the representation of genera showed differences was at the ET. These differences were associated with immunosuppression, treatment, and recurrence, but not sex or age. Immunocompromised patients showed an increased representation of Anaerostipes and Blautia . Patients who experienced recurrence exhibited a higher relative abundance of the genera Methanobrevibacter and Ruminiclostridium 5 . Patients treated with FDX showed a significantly higher abundance of several genera, including Bacteroides , Faecalibacterium , Ruminococcus , Lachnoclostridium , and Blautia , as well as members of the family Lachnospiraceae , when compared to those treated with VNC. In contrast, no differentially represented genera were observed in patients treated with VNC-BZL versus VNC alone. Finally, patients who experienced recurrence exhibited a higher relative abundance of the genera Methanobrevibacter and Ruminiclostridium 5 . Discussion CDI represents a paradigmatic example of a pathobiont-driven infection—an opportunistic microorganism that exploits alterations in the host microbiome to initiate disease [ 8 ]. In a healthy gut, the microbiota is predominantly composed of Firmicutes and Bacteroidetes , which play a protective role against CDI by competing for nutrients, producing inhibitory substances, and stimulating host immune responses. In contrast, CDI is associated with reduced microbial diversity, including a depletion of beneficial taxa such as Bacteroidetes, Prevotella, and Bifidobacterium [ 9 , 10 ]. The present study contributes novel data to the understanding of this complex pathophysiological process, examining the longitudinal impact of different CDI treatments on gut microbiota composition and diversity. Related to the overall dynamics of the microbiome, patients with CDI experienced a notable decline in α diversity following completion of antimicrobial therapy. At 8 weeks post-treatment in individuals without recurrence, diversity recovered to levels exceeding those observed at diagnosis. In contrast, patients who experienced recurrence demonstrated similar diversity levels at the time of recurrence as at initial diagnosis, suggesting an impaired capacity for microbiome recovery. This reduced restoration of diversity after treatment-induced depletion may be a factor for increased recurrence risk. To date, few published studies have analyzed the microbiota longitudinally with such a long follow-up and in such a large sample of patients as in our study. Nevertheless, our results are in line with previous reports. In particular, Seekatz et al. [ 11 ] showed in a smaller cohort with intra-individual comparisons that patients who experienced recurrence were less likely to recover microbiota diversity, and that recurrence was associated with persistently reduced diversity throughout the CDI episode [ 12 ]. These findings support our observation that impaired microbiota recovery is a key determinant of recurrence. Moreover, in our cohort recurrent cases were characterized by reduced microbial richness and diversity, decreased abundance of short-chain fatty-acid-producing bacteria, and an increase in bile salt hydrolase-producing organisms, features associated with impaired microbiome recovery and persistent dysbiosis [ 13 , 14 ]. Failure to restore the gut microbiota to a healthy state in relapsing patients may explain why the use of non-selective drugs that perpetuate dysbiosis, such as VNC, are associated with higher relapse rates, in part due to the loss of secondary bile acid production derived from the microbiome [ 15 ]. Thus, several meta-analyses have reported that treatment with VNC results in a higher relapse rate than when using FDX, a drug that is much less damaging to the patient’s microbiome [ 16 , 17 ]. In line with this evidence, our work reveals treatment-dependent differences among non-recurrent patients. This discrepancy may be attributed to the broader-spectrum activity of VNC, which disrupts microbiota-derived production of secondary bile acid, compounds essential for maintaining healthy microbiota [ 18 ]. Early microbiome responses to CDI therapy have been shown to correlate strongly with recurrence risk [ 14 , 19 ]. Patients treated with FDX exhibited fewer disturbances in the gut microbiome, and retained a higher relative abundance of health-associated genera such as Bacteroides , Faecalibacterium , and Ruminococcus , when compared with those treated with VNC. These findings support the role of FDX in preserving microbiota integrity, which is crucial for preventing recurrence, and are agree with previous studies showing that VNC causes greater dysbiosis in the microbiome in patients with CDI [ 20 ], while decreasing the proportion of some genera associated with a healthy microbiome, such as Bacteroides [ 21 ]. In this regard, members of the phylum Bacteroidetes appear to be critical to maintaining gut homeostasis. For all these reasons, FDX has been consistently identified as a protective agent against CDI recurrence [ 16 , 22 , 23 ]. Our findings are consistent with prior reports showing that FDX has a limited deleterious effect on this phylum compared to VNC [ 20 , 21 , 24 ]. Clinical factors also modulated microbiome recovery. We observed that women and immunocompromised individuals exhibited limited recovery of microbial diversity by week 8, with the diversity index remaining comparable to that at diagnosis. Furthermore, VNC treatment was associated with a more pronounced reduction in microbial diversity in women than in men. Sex-based differences were also noted in the behavior of certain phyla, such as Fusobacteria and Firmicutes , which are key to microbiota stability [ 25 ]. These findings may help explain why immunosuppression is recognized as a risk factor for CDI recurrence [ 26 ]. In relation to gender, there is a dearth of research addressing the differential effect of CDI treatment in men and women. Our data revealed that VNC damages the microbiota more in women than in men, so it would be interesting to conduct further studies in this area. In fact, some studies are beginning to show female sex is associated with a higher risk of complications and recurrences in the course of CDI [ 27 ], and also a higher risk of acquiring this infection [ 19 ]. Limitations Our work contributes valuable data that help to explain the complex phenomenon of the interaction between the patient’s microbiome and the microorganism causing CDI. Patients were enrolled consecutively, but the exclusion of those who did not have samples available for all time points may have introduced a risk of selection bias. Furthermore, microbiota were studied using 16S ribosomal gene amplification, which, although it is the most widely used and cost-effective technique in clinical studies, does not allow in-depth analysis of the relationship between the different microbial communities, nor the presence of genes that indicate their functionality. Likewise, transcriptomics and metabolomics studies were not included. However, the studies performed provide significant data on the influence of drugs on the microbiome and the different interaction of these drugs according to sex. Materials and methods Ethics statement This project was conducted with the written approval of the Clinical Research Ethics Committee (CEIC) of the Virgen de Valme University Hospital (reference: 1254-N-20). Study design, patients, and setting The CDI-ANCRAID-SEICV cohort (ClinicalTrials.gov Identifier: NCT04801862 ) is a prospective, multicenter study conducted across eight hospitals in Spain. Established in 2020 the cohort is coordinated by hospital antimicrobial stewardship teams and systematically includes patients with CDI based on both microbiological confirmation and compatible clinical presentation. Stool samples were obtained at three time points: diagnosis, end-treatment, and 8 weeks post-treatment or at the time of recurrence. All samples are cryopreserved at −80°C for downstream analyses. Patients were included who had provided samples at all three study time points and who had completed the 12-week follow-up before December 31, 2024. Variables and data collection Primary outcome variables was gut microbiota diversity and composition, evaluated using standard α-diversity indices (Shannon index [H] and amplicon variant sequences [ASVs]). Diversity was assessed at three predefined time points, in order to capture the longitudinal evolution of the gut microbiome. Taxonomic composition was also collected, based on the relative abundance of dominant phyla (defined as those representing >1% of total abundance) and differentially represented genera. Explanatory variables, including patient age (dichotomized as < 75 vs. ≥ 75 years) and sex, were collected for all participants. CDI-related clinical variables comprised the treatment administered (VNC, FDX, VNC-bezlotuzumab (VNC-BLZ) and the presence of recurrence. Recurrence was defined according to the criteria of the IDSA [ 28 ]. Treatment for C. difficile infection was selected in accordance with current ESCMID [ 29 ] and IDSA [ 30 ] guidelines, and within a structured, multidisciplinary clinical pathway for systematic case assessment and treatment indication [ 31 ]. VNC or FDX was used for initial episodes based on recurrence risk, and FDX or VNC plus BZL for first recurrences. Clinical variables were concomitant antibiotic therapy during CDI treatment and/or follow-up, and immunosuppression. Study data were collected and managed using REDCap [ 32 , 33 ]. Microbiota analyses Microbial DNA was isolated from the stool samples using the QIAamp PowerFecal Pro DNA kit (Qiagen). Microbiota amplicon sequencing was conducted according to the 16S Metagenomics Sequencing Library Preparation protocol (Illumina). V3-V4 regions of the 16S rRNA were amplified by PCR, and sequenced on the MiSeq (600 cycles, 2 × 300 bp). Raw reads were analyzed using QIIME2 (2021.2) [ 34 ]. Denoising was performed with the DADA2. Taxonomy was assigned with SILVA (Release 138) [ 35 ]. Prior to diversity analyses, rarefaction curves were generated ( S4 Table ) for the observed ASVs and for the H-index in order to determine the sequencing depth threshold. A minimum sequencing depth of 10,000 reads was defined based on these curves, and only samples that reached this threshold were included in the analyses. H-index and ASVs were calculated, and longitudinal analysis were performed using the R package MicrobiomeStat (1.2). The genera differentially represented were determined using ANCOM-BC (4.1.0), which accounts for the compositional nature of microbiome data and applies an internal correction for multiple comparisons bases on the false discovery rate (FDR). Genera with FDR-adjusted q values < 0.05 and absolute log2 fold (|log2FC|) > 2 were considered statistically significant. The robustness of the results was evaluated using pseudcount sensitivity analysis and only accepted the genera when this parameter was true. Statistical analysis The H and ASVs are expressed as means, and the relative abundances and categorical variables as frequencies (percentages). Differences in diversity indices and taxonomic composition among groups were assessed using parametric tests or non-parametric tests, depending on data distribution and variance homogeneity. For paired comparisons across time points, paired t-test or repeated measures ANOVA were used for normally distributed data, while the Wilcoxon signed-rank test or Friedman’s test for non-normally distributed data. For comparisons between independent groups with normally distributed data, Welch’s t-test was used. P-values were adjusted for multiple testing using the holm method. All statistical tests were two-tailed, and a p -value < 0.05 was considered statistically significant. Analyses were performed using IBM SPSS Statistics v25 (Armonk, NY). Highlights In patients with non-recurrent Clostridioides difficile infection (CDI), microbiota α diversity at 8 weeks post-treatment is higher than at diagnosis. In patients with recurrent CDI, α diversity on recurrence is similar to that at diagnosis. CDI treatment with fidaxomicin is less damaging to the microbiome than vancomycin (with or without bezlotuzumab). Recovery of microbiota diversity at 8 weeks is slower in women and immunosuppressed patients. Supporting information S1 Table. Characteristics and Management of Clostridioides difficile Recurrence Episodes. FDX: Fidaxomicin, VCN: Vancomycin, BZL: Bezlotuzumad. (DOCX) ppat.1014063.s001.docx (16.2KB, docx) S2 Table. Recurrence rates according to the clinical and demographic variables analyzed. (DOCX) ppat.1014063.s002.docx (15.3KB, docx) S3 Table. Percentages according to sex, age and immunosuppression according to concomitant and post-treatment antimicrobial therapy of CDI, and treatment of CDI. (DOCX) ppat.1014063.s003.docx (15.9KB, docx) S4 Table. Mean ± se values of α diversity according to study time points and explanatory variables and pvalue for comparison among groups. (DOCX) ppat.1014063.s004.docx (20.7KB, docx) S5 Table. Longitudinal lineal mixed effects models. Observed ASVs. (XLSX) ppat.1014063.s005.xlsx (12.9KB, xlsx) S6 Table. Longitudinal lineal mixed effects models. H-index. (XLSX) ppat.1014063.s006.xlsx (12.8KB, xlsx) S1 Fig. Rarefaction curves of observed ASV (A) and H-index (B). (TIF) ppat.1014063.s007.tif (41.2KB, tif) Data Availability The sequencing raw data are available in NCBI, Bioproject PRJNA1313452. Funding Statement This study was funded by respective grants to NM from the Institute of Health Carlos III (ISCIII) (PI20/01450) and to JMR from the Ministry of Education, Culture, Universities and Employment of the Valencian Community (CIAICO/2023/274) and to MPV received from the Alicante Institute for Health and Biomedical Research (ISABIAL) (project 2024/B/29). The MPV’s salary was funded by a grant for hiring technical staff: the “ESF Investing in your future” along with a PTA Grant (PTA2021-020215-I) funded by MCIN/AEI/10.13039/501100011033. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. References 1. Abbas A, Zackular JP. Microbe-microbe interactions during Clostridioides difficile infection. Curr Opin Microbiol. 2020;53:19–25. doi: 10.1016/j.mib.2020.01.016 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Bella SD, Sanson G, Monticelli J, Zerbato V, Principe L, Giuffrè M, et al. Clostridioides difficile infection: history, epidemiology, risk factors, prevention, clinical manifestations, treatment, and future options. Clinical Microbiology Reviews. 2024. doi: 10.1128/CMR.00135-23 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Spigaglia P, Barbanti F, Faccini S, Vescovi M, Criscuolo EM, Ceruti R, et al. Clostridioides difficile in pigs and dairy cattle in Northern Italy: prevalence, characterization and comparison between animal and human strains. Microorganisms. 2023;11(7):1738. doi: 10.3390/microorganisms11071738 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Lin S-W, Shen C-F, Cheng C-M. Potential trends of point-of-care diagnostics-the next generation of the laboratory diagnosis. Diagnostics (Basel). 2020;10(10):774. doi: 10.3390/diagnostics10100774 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Jenior ML, Papin JA. Computational approaches to understanding Clostridioides difficile metabolism and virulence. Curr Opin Microbiol. 2022;65:108–15. doi: 10.1016/j.mib.2021.11.002 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Fehily SR, Basnayake C, Wright EK, Kamm MA. The gut microbiota and gut disease. Intern Med J. 2021;51:1594–604. doi: 10.1111/IMJ.15520 [ DOI ] [ PubMed ] [ Google Scholar ] 7. Lawler AJ, Lambert PA, Worthington T. A revised understanding of clostridioides difficile spore germination. Trends Microbiol. 2020;28(9):744–52. doi: 10.1016/j.tim.2020.03.004 [ DOI ] [ PubMed ] [ Google Scholar ] 8. Chandra H, Sharma KK, Tuovinen OH, Sun X, Shukla P. Pathobionts: mechanisms of survival, expansion, and interaction with host with a focus on Clostridioides difficile. Gut Microbes. 2021;13(1):1979882. doi: 10.1080/19490976.2021.1979882 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Mougiou D, Gioula G, Skoura L, Anastassopoulou C, Kachrimanidou M. Insights into the interaction between Clostridioides difficile and the gut microbiome. J Pers Med. 2025;15(3):94. doi: 10.3390/jpm15030094 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Wang L, Chen X, Pollock NR, Villafuerte Gálvez JA, Alonso CD, Wang D, et al. Metagenomic analysis reveals distinct patterns of gut microbiota features with diversified functions in C. difficile infection (CDI), asymptomatic carriage and non-CDI diarrhea. Gut Microbes. 2025;17(1):2505269. doi: 10.1080/19490976.2025.2505269 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Seekatz AM, Rao K, Santhosh K, Young VB. Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med. 2016;8(1):47. doi: 10.1186/s13073-016-0298-8 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. DuPont HL, DuPont AW, Tillotson GS. Microbiota restoration therapies for recurrent Clostridioides difficile infection reach an important new milestone. Ther Adv Gastroenterol. 2024;17. doi: 10.1177/17562848241253089 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. van Rossen TM, van Beurden YH, Bogaards JA, Budding AE, Mulder CJJ, Vandenbroucke-Grauls CMJE. Fecal microbiota composition is a better predictor of recurrent Clostridioides difficile infection than clinical factors in a prospective, multicentre cohort study. BMC Infect Dis. 2024;24(1):687. doi: 10.1186/s12879-024-09506-7 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Çetin S, Uğur M. Clostridioides difficile infections and factors associated with recurrence. Infect Dis Clin Microbiol. 2024;6(4):268–75. doi: 10.36519/idcm.2024.380 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. Spigaglia P. Clostridioides difficile and gut microbiota: from colonization to infection and treatment. Pathogens. 2024;13(8):646. doi: 10.3390/pathogens13080646 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Zhao Z, Wu Y, Geng X, Yuan C, Fu Y, Yang G. Efficacy of fidaxomicin versus vancomycin in the treatment of Clostridium difficile infection: a systematic meta-analysis. Medicine (Baltimore). 2024;103(32):e39213. doi: 10.1097/MD.0000000000039213 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Bednárik DS, Földvári-Nagy KC, Simon V, Rancz A, Gede N, Veres DS, et al. Comparative effectiveness of different therapies for Clostridioides difficile infection in adults: a systematic review and network meta-analysis of randomized controlled trials. Lancet Reg Health Eur. 2025;49:101151. doi: 10.1016/j.lanepe.2024.101151 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. Arcay R, Barceló-Nicolau M, Suárez L, Martín L, Reigada R, Höring M, et al. Gut microbiome and plasma lipidome analysis reveals a specific impact of Clostridioides difficile infection on intestinal bacterial communities and sterol metabolism. mBio. 2024;15(10):e0134724. doi: 10.1128/mbio.01347-24 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Alrahmany D, Ereshefsky BJ, El Nekidy WS, Harb G, Pontiggia L, Ghazi IM. Risk factors for recurrence of Clostridioides difficile in hospitalized patients. J Infect Public Health. 2021;14(11):1642–9. doi: 10.1016/j.jiph.2021.09.016 [ DOI ] [ PubMed ] [ Google Scholar ] 20. Okhuysen PC, Ramesh MS, Louie T, Kiknadze N, Torre-Cisneros J, de Oliveira CM, et al. A randomized, double-blind, phase 3 safety and efficacy study of ridinilazole versus vancomycin for treatment of Clostridioides difficile infection: clinical outcomes with microbiome and metabolome correlates of response. Clin Infect Dis. 2024;78(6):1462–72. doi: 10.1093/cid/ciad792 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Louie TJ, Cannon K, Byrne B, Emery J, Ward L, Eyben M, et al. Fidaxomicin preserves the intestinal microbiome during and after treatment of Clostridium difficile infection (CDI) and reduces both toxin reexpression and recurrence of CDI. Clin Infect Dis. 2012;55(Suppl 2). doi: 10.1093/CID/CIS338 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Tiseo G, Yahav D, Atamna A, Avni T, Causse M, Pérez-Nadales E, et al. Recurrent Clostridioides difficile infections in solid organ transplant recipients: the international CALIPSO study. J Infect. 2024;89(6):106306. doi: 10.1016/j.jinf.2024.106306 [ DOI ] [ PubMed ] [ Google Scholar ] 23. Rao K, Zhao Q, Bell J, Krishnan J, Henig O, Daniel J, et al. An open-label, randomized trial comparing fidaxomicin with oral vancomycin for the treatment of Clostridioides difficile Infection in hospitalized patients receiving concomitant antibiotics for concurrent infections. Clin Infect Dis. 2024;78(2):277–82. doi: 10.1093/cid/ciad606 [ DOI ] [ PubMed ] [ Google Scholar ] 24. Giacobbe DR, Vena A, Falcone M, Menichetti F, Bassetti M. Fidaxomicin for the treatment of Clostridioides difficile infection in adult patients: an update on results from randomized controlled trials. Antibiotics (Basel). 2022;11(10):1365. doi: 10.3390/antibiotics11101365 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Shanahan F, Ghosh TS, O’Toole PW. The healthy microbiome—what is the definition of a healthy gut microbiome? Gastroenterology. 2021;160(2):483–94. doi: 10.1053/j.gastro.2020.09.057 [ DOI ] [ PubMed ] [ Google Scholar ] 26. Avni T, Babitch T, Ben-Zvi H, Hijazi R, Ayada G, Atamna A, et al. Clostridioides difficile infection in immunocompromised hospitalized patients is associated with a high recurrence rate. Int J Infect Dis. 2020;90:237–42. doi: 10.1016/j.ijid.2019.10.028 [ DOI ] [ PubMed ] [ Google Scholar ] 27. Ghosh S, Antunes A, Rinta-Kokko H, Chaparova E, Lay-Flurrie S, Tricotel A, et al. Clostridioides difficile infections, recurrences, and clinical outcomes in real-world settings from 2015 to 2019: The RECUR England study. Int J Infect Dis. 2024;140:31–8. doi: 10.1016/J.IJID.2024.01.002 [ DOI ] [ PubMed ] [ Google Scholar ] 28. McDonald LC, Gerding DN, Johnson S, Bakken JS, Carroll KC, Coffin SE, et al. Clinical Practice Guidelines for Clostridium difficile Infection in Adults and Children: 2017 Update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA). Clin Infect Dis. 2018;66(7):e1–48. doi: 10.1093/cid/cix1085 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. van Prehn J, Reigadas E, Vogelzang EH, Bouza E, Hristea A, Guery B, et al. European Society of Clinical Microbiology and Infectious Diseases: 2021 Update on the Treatment Guidance Document for Clostridioides Difficile Infection in Adults. Clin Microbiol Infect 2021;27:S1–S21. doi: 10.1016/J.CMI.2021.09.038 [ DOI ] [ PubMed ] [ Google Scholar ] 30. Johnson S, Lavergne V, Skinner AM, Gonzales-Luna AJ, Garey KW, Kelly CP, et al. Clinical Practice Guideline by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA): 2021 Focused Update Guidelines on Management of Clostridioides difficile Infection in Adults. Clin Infect Dis. 2021;73(5):e1029–44. doi: 10.1093/cid/ciab549 [ DOI ] [ PubMed ] [ Google Scholar ] 31. Rodríguez-Fernández M, Herrero R, González-De-La-Aleja P, Valverde-Fredet MD, Ventero M-P, Trigo-Rodríguez M, et al. Clinical impact of implementing a specific clinical pathway for the management of Clostridioides difficile Infection. Infect Dis Ther. 2026;15(1):85–100. doi: 10.1007/s40121-025-01261-9 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al. The REDCap Consortium: Building an International Community of Software Platform Partners. J Biomed Inform. 2019;95:103208. doi: 10.1016/J.JBI.2019.103208 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. doi: 10.1016/J.JBI.2008.08.010 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41(1):e1. doi: 10.1093/nar/gks808 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] PLoS Pathog. doi: 10.1371/journal.ppat.1014063.r001 Decision Letter 0 Anne Jamet Anne Jamet Section Editor Find articles by Anne Jamet Author information Copyright and License information Roles Anne Jamet : Section Editor © 2026 Anne JametAnne JametAnne JametAnne Jamet This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. We look forward to receiving your revised manuscript. Kind regards, William Navarre Academic Editor PLOS Pathogens Anne Jamet Section Editor Editor-in-Chief PLOS Pathogens orcid.org/0000-0003-2946-9497 Michael Malim PLOS Pathogens orcid.org/0000-0002-7699-2064 Additional Editor Comments: Three experts reviewed your submission. The strengths of this study are both the importance of the question and the impressively large cohort that was analyzed. Reviewers indicate that the research findings are not novel and that a major shortcoming of the submitted work is the lack of context provided against the backdrop of many other similar studies. One reviewer has significant concerns about the methods used for analysis (see reviewer 3). All reviewers feel the reporting of the methods and results were inadequate, and that the manuscript itself is in need of substantial editing to improve clarity. Journal Requirements: If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. 1) Please ensure that the CRediT author contributions listed for every co-author are completed accurately and in full. At this stage, the following Authors/Authors require contributions: Maria Paz Ventero, Rocio Herrero, Iryna Tyshkovska, María Dolores Valverde-Fredet, Juan Carlos Rodríguez, Miguel Rodríguez-Fernández, Pilar González-De-La-Aleja, Marta Trigo, Monica Parra, Ana-Isabel Aller, Silvia Otero, Reinaldo Espindola-Gomez, José Manuel Ramos, Eva M Leon, Maria García, Miguel Nicolas Navarrete-Lorite, Jara Llenas-García, Ines Portillo, Francisco Jover, Maria Tasias, Juan Jose Caston, Concepción Gil, David Vinuesa-Garcia, Cristina Gomez-Ayerbe, Francisco J. Martínez Marcos, Nicolas Merchante, and Esperanza Merino De Lucas. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form. The list of CRediT author contributions may be found here: https://journals.plos.org/plospathogens/s/authorship#loc-author-contributions 2) Please provide an Author Summary. This should appear in your manuscript between the Abstract (if applicable) and the Introduction, and should be 150-200 words long. The aim should be to make your findings accessible to a wide audience that includes both scientists and non-scientists. Sample summaries can be found on our website under Submission Guidelines: https://journals.plos.org/plospathogens/s/submission-guidelines#loc-parts-of-a-submission 3) Please upload all main figures as separate Figure files in .tif or .eps format. For more information about how to convert and format your figure files please see our guidelines: https://journals.plos.org/plospathogens/s/figures 4) We notice that your supplementary Figures, and Tables are included in the manuscript file. Please remove them and upload them with the file type 'Supporting Information'. Please ensure that each Supporting Information file has a legend listed in the manuscript after the references list. 5) Please amend your detailed Financial Disclosure statement. This is published with the article. It must therefore be completed in full sentences and contain the exact wording you wish to be published. 1) State the initials, alongside each funding source, of each author to receive each grant. For example: "This work was supported by the National Institutes of Health (####### to AM; ###### to CJ) and the National Science Foundation (###### to AM)." 2) State what role the funders took in the study. If the funders had no role in your study, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 3) If any authors received a salary from any of your funders, please state which authors and which funders.. If you did not receive any funding for this study, please simply state: u201cThe authors received no specific funding for this work.u201d Reviewers' Comments: Reviewer's Responses to Questions Part I - Summary Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship. Reviewer #1: 1. The main conclusions largely confirm previously published reports that are unfortunately not considered in this manuscript. The authors need to assess their results in the light of these other studies, noting the concurrence of results. There is always value in validation of results with different cohorts. Specifically, regarding three of the four highlights listed (lines 44-53), the authors might consider the following manuscripts: i. Okhuysen PC, Ramesh MS, Louie T, Kiknadze N, Torre-Cisneros J, de Oliveira CM, Van Steenkiste C, Stychneuskaya A, Garey KW, Garcia-Diaz J, Li J, Duperchy E, Chang BY, Sukbuntherng J, Montoya JG, Styles L, Clow F, James D, Dubberke ER, Wilcox M. A randomized, double-blind, Phase 3 Safety and Efficacy study of ridinilazole versus vancomycin for treatment of Clostridioides difficile infection: clinical outcomes with microbiome and metabolome correlates of response. Clin Infect Dis. 2024 Jun 14;78(6):1462-1472. doi: 10.1093/cid/ciad792. PMID: 38305378; PMCID: PMC11175683. ii. Seekatz, A.M., Rao, K., Santhosh, K. et al. Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med 8, 47 (2016). https://doi.org/10.1186/s13073-016-0298-8 iii. Louie TJ, Cannon K, Byrne B, Emery J, Ward L, Eyben M, Krulicki W. Fidaxomicin preserves the intestinal microbiome during and after treatment of Clostridium difficile infection (CDI) and reduces both toxin reexpression and recurrence of CDI. Clin Infect Dis. 2012 Aug;55 Suppl 2(Suppl 2):S132-42. doi: 10.1093/cid/cis338. PMID: 22752862; PMCID: PMC3388020 2. As noted in the fourth highlight (lines 52-53), the authors determined that recovery of microbiota diversity at 8 weeks is slower in women and immunosuppressed patients. How many of the immunosuppressed individuals were women? It might be more helpful to only consider immunocompetent men and women when evaluating gender influences on microbiome dynamics. Reviewer #2: This article has focused on studying how the treatment of C. difficile diarrhoea affects the gut microbiota and its relationship with recurrence. Its strengths are that it has a considerable number of patients, the statistical analysis is well done, and significant results are found for the different treatments. The limitations are that the characteristics of the patients have been poorly defined, and this could be a significant handicap. Reviewer #3: Review of Ventero et al., “Dynamics of the microbiota in patients with Clostridioides difficile: recurrence, treatment, sex, and immunosuppression” This manuscript investigates microbiota dynamics in patients with Clostridioides difficile infection (CDI), focusing on recurrence, treatment modality, sex, age, and immunosuppression. The study includes 143 patients and is generally well written. The authors report that patients who experience recurrent CDI exhibit lower microbial diversity compared to those who do not relapse, and that fidaxomicin better preserves gut microbiota relative to vancomycin, either alone or combined with bezlotoxumab. These findings are broadly consistent with previously published studies and therefore largely confirmatory. The manuscript addresses a clinically relevant topic and includes a substantial cohort. However, the analytical approach requires refinement to ensure robust and interpretable results. ********** Part II – Major Issues: Key Experiments Required for Acceptance Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.required to validate study conclusions.required to validate study conclusions.required to validate study conclusions. Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject". Reviewer #1: (No Response) Reviewer #2: It is necessary to describe the characteristics of the patients; it has not been specified whether the CDI episode is primary or whether they have had any recurrences. Reference is made to antibiotic use during CDI treatment, but it might be interesting to include previous exposure. There is no explanation of how the treatment is chosen, why some patients receive fidaxomicin and others vancomycin, only that vancomycin is less commonly used in immunocompromised patients. It would be interesting to describe the changes in recurrences and after treatment of recurrence. Reviewer #3: • Analytical Concerns: o There is no indication that p-values were adjusted for multiple testing. Given the number of comparisons, this is essential to reduce false positives. o The manuscript states that t-tests were used for parametric data but does not specify which type. Welch’s t-test is generally recommended when sample sizes and variances differ between groups. o Sampling timepoints are not matched between outcome groups. While relapse timing is inherently unpredictable, comparing fixed post-treatment intervals in non-recurrent patients to variable relapse timepoints introduces bias. Time-adjusted mixed-effects models for Shannon diversity and ASV counts would provide a more robust analysis. o Figure 1 relies on observed ASVs and the Shannon index. Observed ASVs are highly sensitive to sequencing depth, yet normalization procedures and sensitivity analyses (e.g., rarefaction) are not reported. Apparent recovery in Figure 1 may reflect differences in sequencing depth rather than biological change. o The impact of treatment (vancomycin vs. fidaxomicin vs. vancomycin + bezlotoxumab) on alpha diversity is not adjusted for key confounders and does not account for repeated measures. Mixed-effects models are standard for longitudinal microbiome data and should be employed. ********** Part III – Minor Issues: Editorial and Data Presentation Modifications Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. Reviewer #1: 1. Line numbering ends towards the end of Results section. There are also no page numbers. 2. A single table providing demographics of the patient cohort, combining the relevant data from Table 1 and S1 would be valuable for ease of understanding by the reader. 3. Much of the microbiome-related data in Table 1 is more readily observed in Figure 2. Perhaps these data could be moved to supplementary data. 4. Since this paper is focused on antibiotic effects, it would be meaningful to better describe the treatment regimens (dose, length of treatment). It would help to have time of recurrence/relapse also presented in the tables. 5. Bezlotoxumab is referred to variously as bezlotuzumab/bezlotuzumad and should be referred to correctly. Some comment should also be included on whether bezlotoxumab treatment made any difference to microbiome outcome. 6. Please define Dx, and rec when introducing for the first time (Lines 121-122). 7. Maintain consistency with regard to use of H-index/Shannon diversity index in text and figure (line 139, Figures 1 and 2). Reviewer #2: Figure 4, the label of Fusobacteria is wrong Reviewer #3: • The terms “H Index” and “Shannon Index” appear to be used interchangeably. It should be explicitly clarified that these refer to the same metric, or corrected if they do not. • Figure legends. o Abbreviations used in figures should be defined within the legends for reader clarity. o In Figure 3, the phrase “according to” could be replaced with “stratified by” for greater precision. o The legend for Figure 3 states that “percentages are shown in logarithmic scale,” but the figure does not appear to use a logarithmic scale. This should be corrected. • The manuscript appears to apply an arbitrary cutoff for displaying p-values. It would be preferable to either report all p-values or restrict reporting to those meeting a predefined significance threshold. ********** PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our Privacy Policy .... Reviewer #1: No Reviewer #2: Yes: Rosa del CampoRosa del CampoRosa del CampoRosa del Campo Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] Figure resubmission: Reproducibility: ?> Attachment Submitted filename: Review for PLOS Pathogens.pdf ppat.1014063.s008.pdf (32.6KB, pdf) PLoS Pathog. 2026 Apr 6;22(4):e1014063. doi: 10.1371/journal.ppat.1014063.r002 Author response to Decision Letter 1 Article notes Copyright and License information Collection date 2026 Apr. PMC Copyright notice 10 Feb 2026 Attachment Submitted filename: Response to reviewers.docx ppat.1014063.s009.docx (84.6KB, docx) PLoS Pathog. doi: 10.1371/journal.ppat.1014063.r003 Decision Letter 1 Anne Jamet Anne Jamet Section Editor Find articles by Anne Jamet Author information Copyright and License information Roles Anne Jamet : Section Editor © 2026 Anne JametAnne JametAnne JametAnne Jamet This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. PMC Copyright notice 5 Mar 2026 Dear Dr. Rodríguez, We are pleased to inform you that your manuscript 'Dynamics of the microbiota in patients with Clostridioides difficile: recurrence, treatment, sex, and immunosuppression.' has been provisionally accepted for publication in PLOS Pathogens. Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests. Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated. IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript. Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS. Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Pathogens. Best regards, William Navarre Academic Editor PLOS Pathogens Anne Jamet Section Editor PLOS Pathogens Sumita Bhaduri-McIntosh Editor-in-Chief PLOS Pathogens orcid.org/0000-0003-2946-9497 Michael Malim Editor-in-Chief PLOS Pathogens orcid.org/0000-0002-7699-2064 *********************************************************** Thanks for your attention to the comments and suggestions provided by the reviewers. All three agree the manuscript is substantially improved. Very minor edits were suggested by Reviewer #1. Reviewer Comments (if any, and for reference): Reviewer's Responses to Questions Part I - Summary Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship. Reviewer #1: The authors have largely addressed the concerns raised in prior review. A couple of minor issues remain. Reviewer #2: The new version is substantially improved, I believe it can be accepted in its current form. Reviewer #3: I appreciate the authors work in addressing all of this reviewers' comments and it is my opinion that the MS has been significantly improved. While this study confirms results that have been observed in smaller cohorts the large scale and importance of the work merit significance. ********** Part II – Major Issues: Key Experiments Required for Acceptance Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.required to validate study conclusions.required to validate study conclusions.required to validate study conclusions. Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject". Reviewer #1: (No Response) Reviewer #2: The new version is substantially improved, I believe it can be accepted in its current form. Reviewer #3: None. ********** Part III – Minor Issues: Editorial and Data Presentation Modifications Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. Reviewer #1: 1. Line 141: BZL- first introduction of Bezoltoxumb/Bexzotuzumab in text needs to be spelt out before using abbreviation. 2. S1 legend: please correct spelling (currently Bezlotuzumad) 3. Line 228: “VNZ-BLC” needs to be corrected 4. It would be helpful to include the number of stool samples used for analysis in each group in figure legends. Reviewer #2: The new version is substantially improved, I believe it can be accepted in its current form. Reviewer #3: None ********** PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our For information about this choice, including consent withdrawal, please see our Privacy Policy .... Reviewer #1: No Reviewer #2: Yes: Rosa del CampoRosa del CampoRosa del CampoRosa del Campo Reviewer #3: No PLoS Pathog. doi: 10.1371/journal.ppat.1014063.r004 Acceptance letter Anne Jamet Anne Jamet Section Editor Find articles by Anne Jamet Author information Copyright and License information Roles Anne Jamet : Section Editor © 2026 Anne JametAnne JametAnne JametAnne Jamet This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. PMC Copyright notice Dear Dr. Rodríguez, We are delighted to inform you that your manuscript, "Dynamics of the microbiota in patients with Clostridioides difficile: recurrence, treatment, sex, and immunosuppression.," has been formally accepted for publication in PLOS Pathogens. We have now passed your article onto the PLOS Production Department who will complete the rest of the pre-publication process. All authors will receive a confirmation email upon publication. The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Pearls, Reviews, Opinions, etc...) are generated on a different schedule and may not be made available as quickly. Soon after your final files are uploaded, the early version of your manuscript, if you opted to have an early version of your article, will be published online. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers. For Research Articles, you will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing . Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Pathogens. Best regards, Sumita Bhaduri-McIntosh Editor-in-Chief PLOS Pathogens orcid.org/0000-0003-2946-9497 Michael Malim Editor-in-Chief PLOS Pathogens orcid.org/0000-0002-7699-2064 Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials S1 Table. Characteristics and Management of Clostridioides difficile Recurrence Episodes. FDX: Fidaxomicin, VCN: Vancomycin, BZL: Bezlotuzumad. (DOCX) ppat.1014063.s001.docx (16.2KB, docx) S2 Table. Recurrence rates according to the clinical and demographic variables analyzed. (DOCX) ppat.1014063.s002.docx (15.3KB, docx) S3 Table. Percentages according to sex, age and immunosuppression according to concomitant and post-treatment antimicrobial therapy of CDI, and treatment of CDI. (DOCX) ppat.1014063.s003.docx (15.9KB, docx) S4 Table. Mean ± se values of α diversity according to study time points and explanatory variables and pvalue for comparison among groups. (DOCX) ppat.1014063.s004.docx (20.7KB, docx) S5 Table. Longitudinal lineal mixed effects models. Observed ASVs. (XLSX) ppat.1014063.s005.xlsx (12.9KB, xlsx) S6 Table. Longitudinal lineal mixed effects models. H-index. (XLSX) ppat.1014063.s006.xlsx (12.8KB, xlsx) S1 Fig. Rarefaction curves of observed ASV (A) and H-index (B). (TIF) ppat.1014063.s007.tif (41.2KB, tif) Attachment Submitted filename: Review for PLOS Pathogens.pdf ppat.1014063.s008.pdf (32.6KB, pdf) Attachment Submitted filename: Response to reviewers.docx ppat.1014063.s009.docx (84.6KB, docx) Data Availability Statement The sequencing raw data are available in NCBI, Bioproject PRJNA1313452. 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