Very little is known about the disturbances in the gut microbial communities during an episode of posttransplant diarrhea. In a pilot study comprising 26 kidney allograft recipients, we found that kidney transplant recipients with posttransplant diarrhea have a lower relative abundance of the genera, Ruminococcus, Dorea, Bacteroides, and Coprococcus in their diarrheal fecal specimens. 6 Our findings led us to consider the idea that posttransplant diarrhea is associated with a decrease in the relative abundance of commensal bacterial taxa. To test our supposition, we characterized the gut microbiota in fecal specimens from an independent cohort of 71 kidney transplant recipients and investigated whether posttransplant diarrhea is associated with gut dysbiosis.

In the absence of a specific infectious etiology, transplant physicians often attribute posttransplant diarrhea to immunosuppressive drugs such as mycophenolate mofetil (MMF). 4 Reduction of MMF dosing has thus become a common strategy to treat posttransplant diarrhea, but this commonly used approach can lead to insufficient immunosuppression 4 and an increased risk of acute rejection and allograft loss. 5

Posttransplant diarrhea affects 1 in 5 patients in the first year after kidney transplantation 1 and is associated with a decreased quality of life 2 and with allograft failure and death. 3 Despite being a common complication, the etiology of posttransplant diarrhea is not identified in a majority of cases. In a study of over 7000 cases of posttransplant diarrhea, an astounding 85% of diarrheal cases were classified as unspecified noninfectious diarrhea. 3

The distributions of continuous variables in any 2 unpaired groups were compared using the Wilcoxon rank sum test; the distribution of continuous variables in any paired groups was compared using the Wilcoxon sign rank test. Proportions of categorical variables were compared using the Fisher's exact test. For comparing relative abundances of taxa, multiple comparisons were adjusted for using the Benjamini‐Hochberg correction (adjusted P ≤ .15). A hierarchical logistic model using the stan_glmer function in Rstanarm package version 2.17.2 10 was utilized to identify predictors that distinguish nondiarrheal samples from diarrheal samples from microbial taxa and clinical variables. Repeated measures from the same subject were accounted for using random intercepts per patient ID. We log‐transformed taxa abundances and set 0 values to half of the lowest observed abundance of the corresponding taxon. Uninformative priors were chosen for intercepts (normal distributions with mean 0 and standard deviation of 10) and weakly regularizing priors were chosen for slopes (normal distributions with mean 0 and standard deviation of 2.5); 8000 posterior samples were generated using the Hamiltonian Monte Carlo algorithm. For metabolic genes derived in PICRUSt, we utilized STAMP (statistical analysis of taxonomic and functional profiles) to analyze differences at the KEGG(Kyoto Encyclopedia of Genes and Genomes) level 3, a database for understanding metabolic functions, and at the gene level (Welch's t test, Benjamini‐Hochberg adjustment). 11 Analyses were performed in R 3.1.1 or in STAMP.

One aliquot from each of the diarrheal fecal specimens was analyzed using the FilmArray Gastrointestinal Panel (v2.1) (BioFire Diagnostics, LLC, Salt Lake City, UT, USA) which tests for 22 bacterial, viral, and protozoan diarrheal pathogens (Full list, SI Materials and Methods). 8 Each aliquot was combined with Para‐Pak C&S media (Meridian Bioscience, Inc, Cincinnati, OH, USA) in a 1:3 ratio (fecal specimen to Para‐Pak C&S media) and analyzed using the BioFire FilmArray 2.0 system.

DNA was isolated from the fecal specimens using a phenol‐chloroform extraction method involving bead‐beater disruption. The 16S ribosomal RNA (rRNA) gene V4‐V5 variable region was amplified using polymerase chain reaction (PCR) and was sequenced on an Illumina MiSeq platform (250 × 250 bp) Illumina, Inc, San Diego, CA. 6 Multiplexing of samples, taxonomic classification of reads, and bioinformatics analyses are described in Supporting Information Materials and Methods.

Flow chart of the profiled fecal specimens from the Diarrhea Group and the No Diarrhea Group. Seventy‐one kidney transplant recipients provided 199 fecal specimens and 183 fecal specimens were analyzed. Twenty‐five kidney transplant recipients developed posttransplant diarrhea (Diarrhea Group) in the first 3 months following kidney transplantation and provided 71 fecal specimens that were classified as prediarrheal specimens, diarrheal specimens (collected at the time of a diarrheal episode), or postdiarrheal specimens. Forty‐six kidney transplant recipients did not develop posttransplant diarrhea within the first 3 months of transplantation (No Diarrhea Group) and provided 112 fecal specimens that were collected during posttransplant week 1, posttransplant week 2, posttransplant week 4, or posttransplant week 12. KT, kidney transplant; Post‐Tx, posttransplant

The subjects provided 199 fecal specimens, with 193 specimens (97%) collected within 1 day and 6 (3%) specimens collected within 2 days. Further details of the specimens are found in Figure 1 . In addition to the 199 fecal specimens, we analyzed 2 subjects who underwent fecal microbial transplantation (FMT), one of which was part of the 71 subjects. These 2 subjects provided an additional 14 fecal specimens.

Diarrhea was defined as a complaint of diarrhea and by the World Health Organization (WHO) definition of 3 or more unusually loose/liquid bowel movements per day. 7 Diarrheal fecal specimens were defined as fecal specimens collected within 24 hours of an episode of active posttransplant diarrhea. Further details are described in SI Materials and Methods.

Subjects were instructed to provide a fecal specimen within 1 day of collection. Each fecal specimen was subsequently aliquoted into approximately 200 mg aliquots and stored at −80°C. Fecal specimens were collected at posttransplant week 1, week 2, week 4, and week 12, and during episodes of diarrhea. We collected the specimens during the first 3 months of transplantation as little is known about early posttransplant diarrhea and we had close clinical follow‐up during this time period.

One hundred twenty‐five patients received a kidney transplant at New York Presbyterian Hospital – Weill Cornell Medical Center between August 2015 and February 2016. We enrolled 107 for serial fecal specimen collections, and 71 of the 107 enrollees provided at least 1 fecal specimen. Demographic and transplant‐related information from the 71 transplant recipients are further described in Supporting Information Materials and Methods. The institutional review board approved this study (Protocol Number: 1207012730) and each patient provided written informed consent.

Among the 6921 predicted genes in the total population, 810 genes differed significantly between the 2 groups (BH adjusted P ≤ .15). The top 25 genes that were significantly different between the 2 groups were all genes decreased in the diarrheal fecal specimens with 10 genes related to metabolism functions, 3 genes related to environmental‐information processing functions, and 12 genes related to unclassified functions (Figure 4 B). Detailed analysis is described in Supporting Information Results.

Metabolic pathways and bacterial genes distinguishing the diarrheal fecal specimens from the fecal specimens in the No Diarrhea group. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis was performed on the 28 diarrheal fecal specimens from the 18 subjects in the Diarrhea Group and the 112 fecal specimens from the 46 subjects in the No Diarrhea Group. A, The top 21 metabolic KEGG 3 pathways significantly different between the diarrheal fecal specimens and the fecal specimens from the No Diarrhea Group are shown. On the left is the relative mean abundance of the different KEGG pathways with the diarrheal fecal specimens in magenta and the fecal specimens in the No Diarrhea Group in gray. On the right are the mean differences between the diarrheal fecal specimens and the fecal specimens in the No Diarrhea Group, by KEGG pathways, with the magenta point representing a significantly higher abundance in the diarrheal fecal specimens and the gray point representing a significantly higher abundance in the fecal specimens in the No Diarrhea Group. Each point is accompanied by a 95% confidence interval indicated by the error bars. The metabolic pathways are sorted by BH adjusted P value. B, The top 25 genes that differed significantly between the diarrheal fecal specimens and the fecal specimens from the No Diarrhea Group are shown. On the left is the relative mean abundance of the different genes with the diarrheal fecal specimens in magenta and the fecal specimens in the No Diarrhea Group in gray. On the right are the mean differences between the diarrheal fecal specimens and the fecal specimens in the No Diarrhea Group, by bacterial genes, with the gray points representing a significantly higher abundance in the fecal specimens in the No Diarrhea Group. Each point is accompanied by a 95% confidence interval indicated by the error bars. The genes are sorted by BH adjusted P ‐value

We utilized PICRUSt 9 to predict the metagenome functions in the 28 diarrheal fecal specimens from the 18 subjects in the Diarrhea Group and the 112 fecal specimens from the 46 subjects in the No Diarrhea Group. At KEGG Level 3 that included 328 KEGG pathways, we identified 21 different KEGG pathways that were significantly different between the 2 groups (Benjamini‐Hochberg [BH] adjusted P ≤ .15, minimum threshold of 10 000 occurrences per KEGG pathway). The 15 pathways that were decreased in the diarrheal fecal specimens included 9 metabolism‐related pathways, 3 genetic information processing pathways, and 3 uncharacterized pathways. Among the 6 pathways that were increased in the diarrheal fecal specimens, 2 were environmental information processing pathways, 1 was a metabolism‐related pathway, 1 was a genetic information processing pathway, and 2 were uncharacterized pathways (Figure 4 A).

Serial microbiome profiles before and after fecal microbial transplantation in 2 kidney transplant recipients with recurrent episodes of diarrhea. Each panel represents a unique patient with each bar within the panel representing the microbiome profile in a single stool specimen. On the x axis, day 0 is the day the patient underwent fecal microbial transplantation (FMT); the relative abundance ( y axis) of the 13 taxa that is decreased in diarrheal fecal specimens (gray), the relative abundance of the 3 taxa that is increased in the diarrheal fecal specimens (magenta), and the relative abundance of all other taxa (yellow) are shown. The donor microbiome profile is shown to the right of Patient 1. Testing for Clostridium difficile toxin B by PCR assay (Xpert C. difficile /Epi, Cepheid, Sunnyvale, CA) is indicated by arrows above the graph. Following FMT from an allogeneic donor, the relative abundance of the 13 taxa that are significantly lower in the diarrheal fecal specimens together increased after FMT, whereas the relative abundance of the 3 taxa that are significantly higher in the diarrheal fecal specimens together decreased after FMT

We evaluated 2 kidney transplant recipients who had a history of Clostridium difficile infections and underwent donor allogeneic FMT. Notably, both had persistent diarrhea despite repeated negative C. difficile testing prior to FMT. In both cases, diarrhea resolved in the first month after FMT. Microbiome profiles in these 2 recipients revealed an overall increase in the abundance of the 13 taxa that were found to be significantly lower in diarrheal fecal specimens and an overall decrease in the abundance of the 3 taxa that were found to be significantly higher in diarrheal fecal specimens after FMT (Figure 3 ).

Within the No Diarrhea Group, we determined the relative abundance of taxa in posttransplant week 1, week 2, and week 4 specimens and analyzed the data using paired specimens. The relative abundance of Blautia and Fusicatenibacter significantly increased and the relative abundance of Ruminiclostridium, Oscillibacter, and Anaerostipes significantly decreased from posttransplant week 1 to posttransplant week 2 (Table S10 ). The relative abundance of Eubacterium and Dorea increased significantly from posttransplant week 2 to posttransplant week 4 (Table S11 ).

Within the Diarrhea Group, we determined the relative abundance of taxa in prediarrheal specimens, diarrheal specimens, and postdiarrheal specimens and analyzed the data using paired specimens. There was 1 taxon, Ruminococcus , that significantly decreased from prediarrheal specimens to diarrheal specimens (Table S7 ). There were no taxa that differed significantly between diarrheal specimens and postdiarrheal specimens (Table S8 ), and no taxa that differed significantly between prediarrheal specimens and postdiarrheal specimens (Table S9 ).

To account for the contribution of multiple samples from a single subject and to address clinical variables, a hierarchical Bayesian logistic regression (with random intercepts per patient ID) was performed to assess each of the genera's independent association with diarrheal specimens. We utilized all of the genera assessed in Table 2 as well as the following clinical variables listed in Table 1 : age, gender, African American race, living donor transplantation, anti‐thymocyte globulin therapy, perioperative cefazolin surgical prophylaxis, and trimethoprim/sulfamethoxazole Pneumocystis jiroveci prophylaxis. We confirmed 9 of the 16 genera identified as significant in Table 2 to have parameter estimate posterior intervals that did not cross 0 (Table 3 ). The logistic regression also identified 5 additional taxa (Gemmiger, Streptococcus, Erysipelatoclostridium , Intestinibacter , and unspecified Erysipelotrichaceae ) that were not significant by univariate analysis in Table 2 .

We conducted further analysis of the fecal specimens based on MMF dosage (1000 mg/day vs 2000 mg/day) and by group (Diarrhea Group vs No Diarrhea Group) status. Analysis of MMF dosage restricted to the Diarrhea Group showed no significant difference at the genus level in the diarrheal fecal specimens from the subjects prescribed 2000 mg/day of MMF compared with the subjects prescribed 1000 mg/day of MMF (Table S3 ). Analysis of MMF dosage restricted to the No Diarrhea Group revealed 1 genus, unspecified Erysipelotrichaceae, that was significantly different in the fecal specimens from the subjects prescribed 2000 mg/day of MMF compared with the subjects prescribed 1000 mg/day of MMF (Table S4 ). In contrast, analysis restricted to the MMF dosage of 1000 mg/day showed that 11 of the 16 genera identified as significant in Table 2 remained significantly different between the diarrheal fecal specimens from the Diarrhea Group and the fecal specimens from the No Diarrhea Group (Table S5 ). In a similar way, analysis restricted to the MMF dosage of 2000 mg/day revealed that 13 of the 16 genera identified as significant in Table 2 remained significantly different between the diarrheal fecal specimens from the Diarrhea Group and the fecal specimens from the No Diarrhea (Table S6 ).

To investigate whether posttransplant diarrhea was caused by common gastrointestinal pathogens, we evaluated a separate aliquot of the 28 diarrheal fecal specimens using the FilmArray Gastrointestinal Panel. 8 This assay utilizes multiplex polymerase chain reaction (PCR) to detect 22 diarrheal bacterial, viral, and protozoan pathogens such as Clostridioides (formerly Clostridium ) difficile, diarrheagenic Escherichia coli , and norovirus (complete list in SI Materials and Methods).

To account for the contribution of multiple samples from a single subject, we also separately evaluated the first fecal specimen associated with diarrhea from each of the 18 subjects in the Diarrhea Group (N = 18 specimens) and compared the microbial profiles of these samples with the profiles in fecal specimens from each of the 46 subjects in the No Diarrhea Group, matched for time from day of collection after kidney transplantation (N = 46 specimens). Twelve of the 16 genera identified as significant in Table 2 still remained significantly different between the Diarrhea Group and the No Diarrhea Group (Table S1). Given that antibiotics influence the gut microbiota, 13 we performed additional analysis after exclusion of 21 posttransplant fecal specimens collected from patients after exposure to antibiotics beyond routine antibiotic prophylaxis. We compared the microbial profiles of 18 diarrheal fecal specimens with the microbial profiles of 100 fecal specimens from the No Diarrhea Group. Thirteen of the 16 genera identified as significant in Table 2 still remained significantly different between the Diarrhea Group and the No Diarrhea Group (Table S2 ).

Heatmap of the most abundant bacterial genera by Diarrhea Group status. On the x axis are the 140 fecal specimens ordered by the 28 diarrheal fecal specimens from the 18 subjects in the Diarrhea Group (dark blue line) and the 112 fecal specimens from the 46 subjects in the No Diarrhea Group (yellow line). On the y axis are the top 24 genera with a >1% mean relative microbial abundance. The 13 genera significantly lower in the diarrheal fecal specimens compared to fecal specimens from the No Diarrhea Group are represented at the top portion of the y axis (in order of significance), and the 3 genera significantly higher in the diarrheal fecal specimens compared to fecal specimens from the No Diarrhea Group are represented at the bottom portion of the y axis (in order of significance). The intensity of the yellow color represents the relative abundance and is log‐scaled

Evaluation of the most common taxa (>1% mean relative abundance among all fecal specimens) was performed at the genus level. The relative abundance of Eubacterium, Anaerostipes, Coprococcus, Romboutsia, Ruminococcus, Dorea, Faecalibacterium, Fusicatenibacter , Oscillibacter, Ruminiclostridium, Blautia, Bifidobacterium, and Bacteroides was significantly lower and the relative abundance of Enterococcus , Escherichia, and Lachnoclostridium was significantly higher in the diarrheal fecal specimens than in the fecal specimens from the No Diarrhea Group (16 significantly different taxa at the genus level) (Table 2 ). A heatmap of the 24 genera is shown, with 13 genera being significantly lower in the diarrheal fecal specimens and 3 genera being significantly higher in the diarrheal fecal specimens compared to the fecal specimens from the No Diarrhea Group (Figure 2 ).

The median Shannon diversity index 12 was lower in the 28 diarrheal fecal specimens from the 18 subjects in the Diarrhea Group than in the 112 fecal specimens from the 46 subjects in the No Diarrhea Group (2.4 vs 3.1, P = 3 × 10 −7 , Wilcoxon rank‐sum test). Nonmetric multidimensional scaling (NMDS) was performed on the 28 diarrheal fecal specimens from the 18 subjects in the Diarrhea Group and the 112 fecal specimens from the 46 subjects in the No Diarrhea Group, using Bray‐Curtis dissimilarity index. The diarrheal fecal specimens separated from the fecal specimens from the No Diarrhea Group by NMDS analysis (Figure S1 ).

Among the 25 subjects in the Diarrhea Group, fecal specimens were not available from 7 recipients at the time of the diarrheal episode. A total of 28 diarrheal fecal specimens were available at the time of diarrheal episode from 18 subjects in the Diarrhea Group. We compared the gut microbial composition of these 28 diarrheal fecal specimens from the Diarrhea Group to the microbial profiles of 112 specimens from the 46 subjects in the No Diarrhea Group.

Seventy‐one kidney transplant recipients provided 199 fecal specimens within the first 3 months after transplantation. Twenty‐five transplant recipients developed posttransplant diarrhea within the first 3 months after transplantation and provided 71 fecal specimens (Diarrhea Group). Forty‐six transplant recipients did not develop posttransplant diarrhea at any time during the first 3 months of transplantation and provided 112 fecal specimens (No Diarrhea Group). Further details of the fecal specimens are found in Figure 1 , and a summary of clinical demographics and transplant‐related characteristics is listed in Table 1 . We performed 16S rRNA gene deep sequencing on DNA isolated from the fecal specimens and obtained a mean (± standard deviation [SD]) of high‐quality 16S rRNA gene sequences of 25 133 ± 13 858 per specimen.

4 DISCUSSION

The current study offers new insights into the gut dysbiosis that occurs during posttransplant diarrhea. Our study has identified the following: diarrheal fecal specimens are characterized by lower microbial diversity and lower abundance of commensal bacterial taxa; most early posttransplant diarrhea is not associated with common infectious diarrheal pathogens.

In a pilot study, we previously found a lower microbial diversity in fecal specimens associated with posttransplant diarrhea as well as a lower relative abundance of the commensal bacterial genera Ruminococcus, Dorea, Coprococcus, and Bacteroides.6 In the current validation study, we confirm and extend these previous findings. We report the relative abundance of Ruminococcus, Dorea, Coprococcus, and Bacteroides to be lower in diarrheal fecal specimens and identify additional commensal bacterial taxa whose abundance was decreased in posttransplant diarrhea, as well as Enterococcus and Escherichia whose abundance was increased.

Of interest, many of the 13 taxa identified as significantly lower in posttransplant diarrheal fecal specimens belong to the Lachnospiraceae family and Ruminococcaceae family and belong to Clostridium Cluster XIVa and IV, which is collectively known as the Commensal Clostridia.14 Among many other important functions, these bacterial taxa contribute butyrate to colonocytes and contribute to overall gut health.14 For example, bacteria in the Faecalibacterium genus degrade glucose, fructose, fructo‐oligosaccharides, and complex molecules such as pectin, and bacteria in the Dorea genus perform glucose fermentation.15 Altogether, these data suggest that decreased commensal bacterial taxa in the gut creates a dysfunctional metabolic state indicating and potentially leading to diarrhea. Consistent with this, a similar lower abundance of commensal bacteria during diarrhea has also been reported in nontransplant recipients. In a study of 39 individuals with C. difficile–associated diarrhea, 36 subjects with C. difficile–negative diarrhea, and 40 healthy volunteers, the genera Blautia, Faecalibacterium, Anaerostipes, Ruminococcus, Dorea, and Coprococcus were depleted in both the C. difficile–associated diarrhea group and the C. difficile–negative diarrhea group compared to the healthy control group.16 It is worth noting that our observational translational study cannot determine whether diarrhea caused the observed dysbiosis or the observed dysbiosis caused diarrhea. Nevertheless, it is interesting to point out that in the 2 cases of FMT for recurrent C. difficile infections, resolution of diarrhea correlated with an overall increase in the relative abundance of the 13 taxa identified as significantly lower in diarrheal specimens and with an overall decrease in the relative abundance of the 3 taxa identified as significantly higher in diarrheal specimens.

At the level of 25 000 sequences per specimen, 16S rRNA gene deep sequencing data may not capture lower abundance of bacterial pathogens, does not distinguish between diarrheagenic and nondiarrheagenic E. coli, and does not evaluate for viral and protozoan pathogens. We overcame this limitation by using a multiplexed PCR assay that detects 22 infectious diarrheal etiologies. We demonstrated that 26 of the 28 diarrheal fecal specimens were negative for bacterial, viral, and protozoan diarrheal pathogens, whereas only 2 were positive for Y. enterocolitica. It is important to note that 16S rRNA gene deep sequencing may not have identified Y. enterocolitica DNA because of the technique's insensitivity at the species level as well as sequencing depth. In our study, the FilmArray Gastrointestinal Panel complemented 16S rRNA gene deep sequencing and supports the hypothesis that early posttransplant diarrhea is mostly noninfectious.

To further explore the potential mechanisms by which decreased commensal bacterial taxa contribute to diarrhea, we utilized PICRUSt9 to predict the metagenomic functions of the bacterial communities. KEGG level 3 analysis revealed significant decreases in metabolic pathways such as sucrose and starch metabolism and amino sugar and nucleotide sugar metabolism in the diarrheal fecal specimens. The predicted metagenomic data suggest that posttransplant diarrhea may be a state of altered metabolic homeostasis with diminished ability to digest complex sugars. As an example, the top gene that was significantly different between diarrheal fecal specimens and the fecal specimens from the No Diarrhea Group was cellobiose phosphorylase, which degrades disaccharide cellobiose into alpha‐d‐glucose 1‐phosphate and d‐glucose.17 Cellobiose has been found in rat models to induce diarrhea.18 Alpha‐N‐arabinofuranosidase is also significantly lower in the diarrheal fecal specimens. Alpha‐N‐arabinofuranosidase is involved in the hydrolysis of terminal arabinofuranoside bonds in hemicellulose homopolysaccharides and heteropolysaccharides.19 Together, cellobiose phosphorylase and alpha‐N‐arabinofuranosidase are involved in the degradation of complex polysaccharides, supporting the idea that the posttransplant diarrhea is characterized by decreased abundance of commensal bacteria taxa that are involved in key metabolism in the gut.

Noninfectious posttransplant diarrhea is commonly attributed to immunosuppressive medications such as MMF.4, 5 As a consequence, transplant physicians routinely reduce MMF dosing in order to treat posttransplant diarrhea. The current study does not directly address the microbiota changes due to MMF, as almost all subjects were on MMF. However, our data suggest that the taxa identified as significantly different between the diarrheal fecal specimens and fecal specimens in the No Diarrhea Group remained significantly different when stratified either by 1000 mg MMF dosage or by 2000 mg MMF dosage (Tables S5 and S6). In contrast, within the Diarrhea Group or within the No Diarrhea Group, there was only one significantly different taxon between the 1000 mg MMF dosage and 2000 mg MMF dosage (Tables S3 and S4). These results are supportive of the interpretation that changes in the gut microbiota may not be attributed solely to MMF dosage.

There are several limitations to our study. Our study focused on diarrhea within the first 3 months of transplantation. Late chronic posttransplant diarrhea has been attributed to infectious etiologies like norovirus20 and whether our findings are also applicable to late posttransplant diarrhea requires additional investigation. We were not able to obtain fecal specimens at all serial time points and during every episode of posttransplant diarrhea. Limited data regarding the diet of subjects is a limitation, since diet is known to influence the gut microbiota.21 Our data highlight decreased commensal bacterial diversity during diarrhea but do not address whether diarrhea caused the gut dysbiosis or whether the dysbiosis caused the diarrhea. Another limitation is that we utilized a prediction system to postulate bacterial metagenome functions. Future studies focused on the metagenome of posttransplant diarrhea are needed to confirm whether bacterial metabolism genes and metabolites are associated with posttransplant diarrhea.

In summary, we report that posttransplant diarrhea early after transplantation is associated with lower diversity of commensal bacterial taxa and lower microbial diversity and is uncommonly associated with diarrheal infectious pathogens. Moreover, posttransplant diarrhea is characterized by a predicted lower abundance of metabolism‐associated bacterial genes. Future validation studies are needed to further investigate the gut microbiota dysbiosis present in posttransplant diarrhea and options to prevent and/or treat this common complication.