Engrafting gut bacteriophages have potential to modulate microbial metabolism in fecal microbiota transplantation

doi:10.21203/rs.3.rs-5259313/v1

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Engrafting gut bacteriophages have potential to modulate microbial metabolism in fecal microbiota transplantation

https://doi.org/10.21203/rs.3.rs-5259313/v1

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Background

Fecal microbiota transplantation (FMT) is widely used to treat severe infections and investigated for treatment of complex diseases. The therapeutic efficacy of FMT is related to successful engraftment of bacteriophages from healthy donors to recipients. However, gut bacteriophage contributions to FMT engraftment and treatment outcomes remain unclear.

Methods

The gut phageome from previously published metagenomes of donors and recipients across 23 FMT studies was assembled and functionally annotated for a meta-analysis.

Results

Gut phageome profiles of FMT recipients, especially those with rCDI, shifted towards donor phageomes, accompanied by increasing phageome alpha diversity. Engraftment of donor phages varied between recipient conditions with highest engraftment rate, overrepresented by temperate phage, in patients with rCDI. Consistently, a higher proportion of auxiliary metabolic genes (AMGs), with potential to support and modulate bacterial metabolism, were annotated on temperate phages.

Conclusions

FMT leads to significant taxonomic, functional and lifestyle shifts in recipient phageome composition. Future FMT studies should include gut phageome characterization and consider it as a potential factor in microbial community shifts and treatment outcomes.

Fecal microbiota transplantation (FMT) is investigated for treatment of inflammatory conditions of the gastrointestinal tract, but the exact way it works and the changes it causes in the microbiome are not well understood [1]. In clinical practice, FMT has nearly 90% success rate for treating recurrent Clostridium difficile infection (rCDI) [2]. Additionally, FMT has been investigated for treating symptoms or modulating the disease processes in other conditions associated with gut microbial imbalance [3, 4], including multidrug-resistant bacteria (MDRB) infections [5, 6, 7], Crohn's disease (CD) [8, 9], ulcerative colitis (UC) [5, 10, 11, 12], anti PD-1 therapy-resistant melanoma [13, 14], metabolic syndrome [15], obesity [3], tyrosine kinase inhibitors (TKI)-related diarrhea [16] and Tourette syndrome [17]. Common findings from these studies include that FMT facilitates microbiome recovery [18] and enhances microbial ability to respond to other treatments [13]. While species-specific engraftment patterns in bacteria have been widely characterized [16], only few studies, to date, have investigated viral engraftment.

Viruses, mostly bacteriophages (phages) that are viruses specific to bacteria, constitute a major component of human gut microbiomes. In addition to killing their host bacteria, phages may mutually coexist with their bacterial host while providing them with fitness-promoting auxiliary genes. Intriguingly, an FMT study for rCDI using sterile fecal filtrate with no bacteria showed equal treatment efficacy when the FMT included or lacked bacteria [19], proposing that phages may play important roles in FMT treatment efficacy. Supporting this idea, a fecal virome transplantation (FVT) from lean donors decreased weight gain and normalized blood glucose tolerance in mice with obesity [20]. In humans, FVT for patients with metabolic syndrome prompted significant changes of phage composition with downstream effects in lytic phage-bacteria interactions [21]. While metagenomic data contains information about phages, most FMT studies generating metagenomes lack bacteriophage analysis and post-FMT phageome shifts and potential effects to metabolic regulation of bacteria remain unclear.

Here, we metagenomically investigated commonalities and differences of gut phageome profiles, phage engraftment and its implications in gut microbial metabolism in a meta-analysis of 23 FMT studies. We found that FMT was followed by prominent phageome shifts. Phage engraftment outcomes varied according to different patient conditions while temperate phages tended to be involved in different engraftment outcomes after FMT. We further found that temperate phages might contribute more to regulate bacterial metabolism and commonalities in metabolic regulation across studies might implicate in phageome shifts and phage engraftment after FMT. This study provides a new prospective to explore mechanisms of gut phageome shift and phage engraftment in future FMTs and phage-based therapies.

Datasets

As of March 8, 2024, a total of 39 clinical FMT studies with metagenomic profiling were retrieved using previously established search terms: ((fecal microbiota transplant*) OR (fecal microbial transplant*) OR (faecal microbiota transplant*) OR (faecal microbial transplant*) OR (fecal transplant*) OR (faecal transplant*) OR (stool transplant*) OR (fecal microbiota transfer) OR (fecal microbial transfer) OR (faecal microbiota transfer) OR (faecal microbial transfer) OR (fecal transfer) OR (faecal transfer) OR (stool transfer) OR (fecal microbiota donation) OR (fecal microbial donation) OR (faecal microbiota donation) OR (faecal microbial donation) OR (fecal donation) OR (faecal donation) OR (stool donation) OR (fecal microbiota suspension) OR (fecal microbial suspension) OR (faecal microbiota suspension) OR (faecal microbial suspension) OR (fecal suspension) OR (faecal suspension) OR (fecal microbiota infusion) OR (fecal microbial infusion) OR (faecal microbiota infusion) OR (faecal microbial infusion) OR (fecal infusion) OR (faecal infusion) OR (stool infusion) OR (FMT) OR (bacteriotherapy)) AND ((shotgun) OR (Metagenom*)) [5]. 17 studies were excluded for the following reasons: (1) sequencing data and metadata were not publicly available, (2) poor-quality sequencing data were deposited without recorded reason, or (3) donor samples were not directly from healthy individuals within independent cohorts but standardized human gut microbiota or biobank. The included cohorts were recruited in the United States (n = 671), Canada (n = 187), Netherlands (n = 454), Italy (n = 45), France (n = 115), Russia (n = 17), Israel (n = 75), China (n = 25) and New Zealand (n = 381), and in total included 1,970 fecal metagenomic samples from healthy donors (n = 342), healthy recipients (n = 14, [22]) and patients with C. difficile infection (n = 444, [5,23,24,25,26,27,28,29]), antibiotic resistance or MDRB infections (n = 157, [5,6,7]), CD (n = 156, [8,9]), UC (n = 43, [5,10,11,12]), anti PD-1 therapy-resistant melanoma (n = 223, [13,14]), metabolic syndrome (n = 210, [15]), obesity (n = 323, [3]), TKI-related diarrhea (n = 43, [16]) and Tourette syndrome (n = 15, [17]). The cohorts are described in Supplementary Table 1 and samples in Supplementary Table 2.

Quality control

Trim Galore [30] was used to trim off low-quality reads and sequencing adapters. Subsequently, clean reads were filtered to remove human genome contamination using KneadData v0.12.0 (--bypass-trf, --reference-db hg37dec_v0.1, --remove-intermediate-output). For each metagenome, high-quality reads were sorted and split into forward, reverse and unpaired output files.

Viral identification and abundance

Both paired and unpaired reads were assembled using MEGAHIT v1.2.8 [31] (--min-contig-len 500). An earlier Standard Operating Procedure (SOP) [32] was modified to identify putative viral contigs. Briefly, the VirSorter2 v2.2.4 [33] was used to detect dsDNA and ssDNA phages from assembled contigs (--min-length 5000, --min-score 0.5). The contamination and completeness were assessed by the CheckV v1.0.1 using the default parameters. As putative viral contigs, contigs were required to contain at least one viral gene identified by CheckV or meet the following criteria: (1) host gene count = 0, or (2) VirSorter2 score ≥ 0.95, or (3) viral hallmark gene count > 2. The viral operational taxonomic units (vOTUs) were clustered using MMseqs2 v15.6f452 [34] (--min-seq-id 0.95, -c 0.85, --cov-mode 1) based on Minimum Information about an Uncultivated Virus Genome (MIUViG) standards (average nucleotide identity (ANI) ≥ 95% over alignment fraction (AF) ≥ 85% of the smaller contig) [35]. Only vOTUs defined as complete genomes or those with completeness greater than 50% were kept for building an index and mapping sequencing reads. The quantification of trimmed vOTUs was performed using coverM v0.7.0.

vOTUs characterization

Prodigal v2.6.3 [36] (-p meta) was used to predict the open reading frames (ORFs) of vOTUs. The trimmed vOTUs were classified into viral clusters (VCs) and taxonomic annotated on of family and genus levels using vConTACT2 [37] (--vcs-mode ClusterONE, --db 'ProkaryoticViralRefSeq207-Merged'). The lifestyle (temperate or lytic, labeled as undefined if lifestyle scores were equal) was predicted using Bacphlip v1.0 [38] using the default parameters. Phage host prediction was performed using iPHoP v1.3.3 [39] with the iPHoP_db_Aug23_rw database. Confidence scores of predicted hosts were calculated according to five host-based tools (Blast, CRISPR, VirHostMatcher, WIsH and PHP) and a phage-based tool (RaFAH).

AMG annotation and abundance

The trimmed vOTUs were processed through VirSorter2 (--seqname-suffix-off, --viral-gene-enrich-off, --provirus-off, --prep-for-dramv). Processed sequences were used to annotate AMGs using DRAM v1.4.6 [40] (DRAM-v annotate) based on PFAM, dbCAN, RefSeq_viral, VOGDB and MEROPS peptidase databases. A summary of potential AMGs was created from the DRAM-v annotations (DRAM-v distill). All annotated AMGs were further classified into KEGG modules and pathways using KEGGREST package v1.44.0. To avoid the possibility of host-derived reads affecting the abundances of viral-encoded AMGs, the abundances of vOTUs were used as representations for the abundances of AMGs [41]. The abundances of KEGG orthologs (KO) were determined by adding the abundances of the AMGs assigned to each KO as previously reported [42].

Classification and quantification of phage engraftment outcomes after FMT

Phage engraftment outcomes at each time point were determined using an allogenic donor sample, a donor-matched recipient pre-FMT baseline sample and the same recipient post-FMT sample. 4 study with multiple donors [3,8,29] was excluded from engraftment analyses. In total, 551 recipient-donor pairs (n = 1,595 metagenomes) were included in engraftment analyses. The classification and quantification of engraftment outcomes were carried out according to [43] with minor modifications. Proportions of engraftment outcomes after FMT were quantified based on the prevalence and abundance of each vOTU. Detailed information is given in Supplementary Table 3.

Statistical analyses

Intergroup comparisons of Shannon index and viral abundance between donors and recipients pre-FMT baselines were carried out using unpaired Student’s t-test with Welch’s correction or Mann-Whitney test according to data distribution. Paired t-test or Wilcoxon matched-pairs signed rank test was applied on comparisons between lifestyles, or when samples were from the same recipient at different time points. Chi-squared test was used for rate comparison. Graphpad Prism v9.0.0 was used to calculate the statistics above. Other statistical analysis and visualization were performed in R v4.1.3. The Bray-Curtis distance with normalization was used to generate PCoA ordination plots, which were visualized by ggplot2 package v3.3.6 and ggthemes package v4.2.4. The marginal histograms on both sides were added using ggExtra package v0.10.0. Adonis2 from the vegan package v2.6-4 was used to perform permutational multivariate analysis of variance (PERMANOVA) analysis. An evaluation of confounders was conducted through SIAMCAT package v2.8.0 [44]. Differential analysis with correction of random effects were performed by MaAsLin2 package v1.6.0 [45] with a threshold of q-value < 0.05 (transform = "LOG", normalization = "NONE", standardize = TRUE, analysis_method = "LM", correction = "BH"). Linear associations between donors’ Shannon index and viral outcomes in recipients after FMT were calculated based on Pearson correlation coefficient. An adjustment for multiple comparisons was made using Benjamini-Hochberg (BH) correction. The KEGG pathway enrichment analysis of bacterial metabolism was performed by MicrobiomeAnalyst v2.0 [46] and significance of pathway was expressed as p value < 0.05.

Gut phageome meta-analysis of 23 FMT studies

We analyzed 23 FMT studies, spanning North America (11 from the USA and one from Canada), Europe (3 from Netherlands, 2 from Italy, one from France and one from the European part of Russia), Asia (2 from Israel and one from mainland China) and Oceania (one from New Zealand) including 1,970 fecal metagenomes from healthy donors and FMT recipients across 10 conditions (patients with 9 diseases and healthy volunteers) (Fig. 1a). Metagenomes were assessed for quality and assembled to identify viral contigs (Fig. 1b). We detected a total of 103,402 viral operational taxonomic units (vOTUs) which were further filtered according to the Uncultivated Virus Genome (MIUViG) standards to obtain 29,208 vOTUs with medium-to-high quality and completeness (Fig. 1c). Only 1,690 of filtered vOTUs were classified into at least one viral cluster (VC) with known reference genomes of uncultured viruses (Fig. 1d). Among these classified vOTUs, >95% of vOTUs belonged to families Kyanoviridae (former Myoviridae, 51.95%), Drexlerviridae (former Siphoviridae, 31.54%) or Autographiviridae (former Podoviridae, 11.72%). (Fig. 1e, Supplementary Table 4). 13,905 (47.61 %) of vOTUs we predicted to have temperate lifestyle and 15,273 (52.29 %) vOTUs were predicted to have lytic lifestyle (Fig. 1f, Supplementary Table 5). Most of classified vOTUs were predicted to bacterial hosts Gammaproteobacteria, Clostridia, Bacilli and Bacterodia at the class level (Fig. 1g, Supplementary Table 6).

FMT lead to increased phageome diversity and shift towards donors

We first compared phageome diversity, measured by the Shannon index, between different recipient conditions and donor groups. FMT recipients with rCDI consistently showed lower phageome diversity at baseline compared to donors, and shifted to higher phageome diversity after FMT (Fig. 2a). Although we observed similar trends in FMT recipients with MDRB infections and IBD, we did not observe statistically significant differences between recipients and donors, or shifts between pre- and post-FMT diversities in other cohorts (Supplementary Table 7). Gut phageome of pre-FMT recipients under different conditions was significantly differentiated from donors and recipients after FMT (Fig. 2b, PERMANOVA based on Bray-Curtis dissimilarities, P < 0.001, R² = 3%). Especially, samples from rCDI patients clustered separately from other FMT recipients (Fig. 2c). We observed significant differences in beta-diversities within donors (PERMANOVA, P < 0.001, R² = 36%) and pre-FMT recipients (PERMANOVA, P < 0.001, R² = 28%) between different cohorts (Supplementary Fig. 1a, b), highlighting potential geographical, technical and other confounding effects present in these data. Phage profiles significantly shifted towards those of their donors in approximately 75.81% and 69.09% of recipients with rCDI and MDRB infections, respectively (Fig. 2d). After evaluating confounders (Supplementary Fig. 2) and excluding those vOTUs that were significantly correlated with the sequencing depth, country or study cohort, approximately 23.41% (6,837 of 29,208) of vOTUs showed a statistically significant difference between donors and recipients (pre- or post-FMT). Among these, 93.92% (6,421 of 6,837) of differentially abundant vOTUs displayed greater relative abundance in both donors and post-FMT recipients compared to recipients at baseline (Fig. 2e, Supplementary Table 8). For those with taxonomic classification, 24.55% (205 of 835) of temperate phages and 24.24% (207 of 854) of lytic ones showed significant difference between donors and recipients (pre- or post-FMT) (Fig. 2e). This indicates major phageome shifts post-FMT and a wide scale donor phage engraftment in FMT recipients.

Phageome engraftment outcomes varied across patient conditions

We next compared post-FMT samples to samples with their matched donors to determine different engraftment and persistence outcomes of phages in recipients (Fig. 3a). We identified six outcomes for each phage in post-FMT recipient metagenomes: colonization (donor phages observed in the recipients post-FMT); novel phages (either phages not observed in donors and pre-FMT recipients were introduced, or the low-abundance phages that had colonized were expanded); coexistence of phages shared by donor and recipient; persistence (recipient phages that were not detectable in donors and persisted through FMT); rejection (absence of detectable engraftment of donor phages); and loss of recipient phages after FMT (Fig. 3b, Supplementary Table 3). The resilience of recipient phages accounted for only 3.51 ± 2.19% to 10.46 ± 2.85%, while 37.32 ± 21.04% to 75.69 ± 6.48 % of phage outcomes could not be determined (Fig. 3c). More phages from donors or those from either environmental or previously undetected took over phage communities of recipients with rCDI after FMT, while novel donor and environmental phages accounted for, on average, 16.11 ± 8.2% to 39.37 ± 18.91% of the total post-FMT phageome in other recipient groups (Fig. 3c). Phage engraftment outcomes varied considerably in different conditions (Fig. 3d). There was a higher rate of engraftment in FMT cases of rCDI (colonization and novel phages, accounting for 25.79 ± 12.26% and 33.37 ± 13.59% post-FMT phages, respectively). In contrast, coexistence (24.57 ± 14.15%) was the most common outcome cases where phages were present in both donors and pre-FMT recipients, mainly in FMT cases of healthy volunteers and noninfectious diseases (except rCDI and MDRB infections, 31.89 ± 10.08%) (Fig. 3d). We observed phage from all six engraftment outcome groups in each donor-recipient pair and none of the recipients showed complete phage turnover or complete rejection after FMT, despite persistent recipient phages or engrafted phages being rare (Fig. 3d). These results show that phage engraftment varies in different diseases. Recipients with infectious diseases, such as rCDI or MDRB infections, may experience more phage engraftment after FMT.

More abundant temperate phages were associated with engraftment outcomes

To determine whether phage lifestyles were associated with engraftment outcomes, we compared the phage lifestyles before and after FMT across diseases. Overall, temperate phages were more abundant compared to lytic phages in both donors and recipients (Fig 4a). Phages belonging to different engraftment outcome groups showed relatively even proportions of temperate and lytic phage with few exceptions (Fig4. b-e, Supplementary Fig. 3a). Post-FMT healthy volunteers exhibited a higher proportion of lytic phages within novel phages with an unknown source (Fig. 4b) and post-FMT samples from rCDI patients were colonized with slightly more temperate than lytic donor phages (Fig. 4c, Supplementary Fig. 3a). Notably, temperate phages (59.63 ± 5.99%) showed a predominance in phages where the colonization outcome was undetermined (i.e. the vOTU was detected in the donor and pre- and post-FMT recipient samples) (Fig. 4d, Supplementary Fig. 3a). Among vOTUs persistent in FMT recipients (detected both pre- and post-FMT), temperate phages were more common among patients with rCDI (Fig. 4e, Supplementary Fig. 3a). In contrast, we observed more persistent lytic phages in healthy volunteers and recipients with melanoma or metabolic syndrome (Fig. 4d). No statistically significant pairwise differences between donor and recipient samples emerged within either lifestyle before or after FMT when all FMT studies were combined (Fig. 4a). However, relative abundances of temperate phages in approximately 85.38% of donors (292 from 14 datasets) were significantly higher than phages with lytic lifestyle (Supplementary Fig. 3b, Supplementary Table 9). Particularly, 80.2% of recipients with rCDI (243 from 8 datasets) showed higher relative abundances of temperate phages post-FMT compared to pre-FMT (51.77%, 141 from 3 datasets) (Supplementary Fig. 3b, Supplementary Table 9). As an exception, healthy volunteers with equal relative abundances of temperate and lytic phages pre-FMT presented a trend towards donors with relatively higher abundance of lytic phages post-FMT, albeit the difference was not no statistically significant (Supplementary Fig. 3b, Supplementary Table 9). The phageome shift within phage lifestyles varied between patient conditions and FMT studies (Fig. 4f, Supplementary Fig. 3c). Both temperate and lytic recipient phage profiles shifted towards those of their donors in approximately 56% of recipients (Supplementary Fig. 3c). On average, both temperate and lytic phage profiles of recipients with infectious diseases (rCDI and MDRB infections) significantly shifted towards those of their donors after FMT (95% CI of temperate phages: 0.029-0.048 and 0.005-0.03, respectively; lytic phages: 0.034-0.059 and 0.009-0.04, respectively) (Fig. 4f). Taken together, FMT might favor colonization of temperate phages, especially in patients with rCDI, potentially through stable engraftment of their bacterial hosts.

Phage AMGs carriage and diversity differed by lifestyle

The auxiliary metabolic genes (AMGs) have been found in many phages, which can be traced back to bacterial hosts and assist in regulating host metabolism [42]. We annotated a total of 11,505 AMGs across 26.53% (7,750 of 29,208) of the vOTUs (Fig. 5a). Approximately 22.82% (2,625 of 11,505) and 8.59% (988 of 11,505) of AMGs were assigned to the DNA (cytosine-5)-methyltransferase (dcm) and S-adenosylmethionine synthetase (metK), respectively (Fig. 5b). Both of them are involved in the cysteine and methionine metabolism. At the KO level, AMGs were enriched in 22 pathways (Fig. 5c, P < 0.05). Among these, the glycolysis / gluconeogenesis pathway was statistically most significant (Fig. 5c), implying its potential role in providing upstream compounds of amino acids biosynthesis. We further asked whether temperate and lytic phages differed in terms of AMG carriage and whether this had potential implications in metabolism of post-FMT microbiomes. AMG compositions differed significantly between temperate and lytic phages (Fig. 5d, PERMANOVA, P < 0.001, R² = 3%). In addition, both Shannon and richness indexes of AMG profiles were significantly higher in temperate than lytic phages (Fig. 5e, f), implying that temperate phages harbor more AMGs compared to lytic phages. Most pathways, especially the cysteine and methionine metabolism, harbored higher proportion of AMGs from temperate phages compared to lytic phages (Fig. 5g). More abundant and highly diverse AMGs in temperate phages might contribute more to regulate bacterial metabolism, especially the glycolysis / gluconeogenesis pathway and the metabolism of cysteine and methionine.

AMGs in phageome may support and regulate gut microbial metabolism after FMT

We found that cysteine and methionine metabolism genes were enriched among AMGs with potential implications throughout the human lifespan. For example, early-life fecal cysteine levels are positively associated with neurological and physical development [47]. On the other hand, AMGs that assist bacterial methionine metabolism in centenarians may be related to their longevity [48]. In order to investigate these pathways in detail, we combed 33 AMGs related to cysteine and methionine metabolism with potential to regulate microbial metabolism and their abundance in donors and changes in recipients after FMT (Fig.6). In glycolysis, AMGs encoding glucose-6-phosphate isomerase (pgi), fructose-bisphosphate aldolase (class II, fbaA), glyceraldehyde 3-phosphate dehydrogenase (gapA), phosphoglycerate kinase (pgk), 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase (gpmA), pyruvate kinase (pyk) and lactate dehydrogenase (ldh) were significantly increased after FMT potentially promoting the metabolism of α-D-Glucose 6-phosphate to lactate (Supplementary Fig.4a). Pyruvate produced from glycolysis is oxidatively dehydrogenated to form acetyl-CoA, which is further metabolized to acetate through phosphate acetyltransferase (pta) and acetate kinase (ackA). AMGs encoding these enzymes were all elevated in post-FMT samples (Supplementary Fig.4b). 3-Phospho-D-glycerate derived from glycolysis can be interconverted with 3-phosphonooxypyruvate, which is an important intermediate in the synthesis of 3-phosphoserine. The significantly increased AMG encoding cysteine synthase (cysK) in post-FMT samples may promote the conversion of 3-phosphoserine to cysteine (Supplementary Fig.5a). As a precursor of cysteine, cystathionine can be metabolized from aspartate and the process may be promoted by elevated levels of AMGs encoding homoserine dehydrogenase (hom) and homoserine O-acetyltransferase (metA) observed in post-FMT samples (Supplementary Fig.5b). Moreover, the cystathionine can be mutually transformed with homocysteine, which is methylated to form methionine by the 5-methyltetrahydrofolate-homocysteine methyltransferase (metH) and 5-methyltetrahydropteroyltriglutamate-homocysteine methyltransferase (metE). In contrast, the methionine can be converted to S-adenosylmethionine (SAMe) through S-adenosylmethionine synthetase (metK). After that, methyl group of SAMe is transferred to a range of receptor molecules by DNA (cytosine-5)-methyltransferase 1 (dcm, encoded AMG was decreased post-FMT) to generate S-adenosylhomocysteine (SAH), which is then hydrolyzed into homocysteine and adenosine by adenosylhomocysteinase (ahcY, encoded AMG was decreased post-FMT) (Supplementary Fig.4c). As one of the starting compounds of the shikimate pathway, phosphoenolpyruvate from glycolysis might be accelerated to shikimate by dehydration, cyclization and dehydrogenation through elevated AMGs encoding 3-dehydroquinate dehydratase II (aroQ) and shikimate dehydrogenase (aroE) after FMT (Supplementary Fig.6a). Chorismate, which is metabolized from shikimate by the shikimate kinase (aroK/aroL), is a key intermediate in the biosynthesis of aromatic amino acids. Among these, tryptophan synthesis might be enhanced by the tryptophan synthase (alpha chain, trpA; beta chain, trpB; encoded AMGs were increased post-FMT) (Supplementary Fig.6b). These results suggest commonalities in metabolic regulation shared among gut phageomes across FMT studies, potentially implicated in FMT induced post-FMT phageome shifts.

We investigated gut phageome profiles, phage engraftment and its implications in gut microbial metabolism in a meta-analysis of 23 FMT studies with metagenomic data. We observed major phageome shifts and a wide scale donor phage engraftment in FMT recipients. Recipients with infectious diseases had higher rate of donor phage engraftment after FMT. Especially in patients with rCDI, FMT led to colonization of temperate phages, potentially through stable engraftment of their bacterial hosts. We further compared phage AMGs between lifestyles and found that AMGs in temperate contribute functions with potential to regulate bacterial metabolism. These commonalities in metabolic regulation across studies may further support persistent gut microbiome shifts potentially implicated in clinical outcomes in FMT.

We observed decreased phage diversity in most FMT recipients at baseline, across diseases, compared to healthy donors. More diverse and rich gut phageomes from FMT donors promoted the recovery of phage diversity in post-FMT phageomes. Previous studies suggested that the viral richness and diversity were significantly increased after FMT, especially in recipients with rCDI [49, 50]. In patients with obesity, especially those with type 2 diabetes, the gut phage diversity and richness were also significantly reduced [51]. The resolution of diarrhea in rCDI recipients after FMT has been associated with greater phage diversity [52]. Consistent with our results, post-FMT recipients with rCDI tended to have gut phage communities more similar to those of donors than recipients at baselines [53, 54].

We observed differences in post-FMT engraftment of donor phages across different patient conditions. Specifically, we found the highest turnover of pre-FMT recipient phages in patients with rCDI accompanied by large scale engraftment of recipient phages, consistent with previous studies [53, 55]. The phages observed in pre-FMT samples accounted for the majority of post-FMT gut phageomes in patient conditions other than rCDI. Data from fecal viral transplantation and phage-bacteria correlations suggest that phages play a significant role in clinical outcomes following FMT [56]. In addition, an open-label clinical trial showed that the effectiveness of FMT in autism spectrum disorders was accompanied by engraftment of phage communities from the donor [57]. Another recent randomized clinical trial using FMT to treat metabolic syndrome found a significantly positive correlation between phage diversity and donor phage engraftment [44]. Clearly, detailed information on phage engraftment, long-term persistence of engrafted phages and correlation between engraftment and therapeutic effect need to be investigated in future FMT trials [58]. In longer term, a phage-specific modification of FMT may have potential to address donor variability, unstable efficacy and infection risks.

We further compared commonalities and differences in phage lifestyles across diseases. Uniformly, the relative abundance of lytic phages was significantly reduced in recipients after FMT, tending to be more similar to the donor. An increase in extracellular lytic phages was reported as one of the signs of gut dysbiosis [59]. It has been demonstrated that lytic phages can weaken the intestinal colonization of bacteriome and can coexist for a long time [60]. In contrast, temperate phages are more likely to introduce new functional genes to host genomes naturally via generalized or specialized transduction, which favors bacterial evolution [23]. An earlier study suggested that a significant proportion of FMT transfers were from temperate phages, which formed stable associations with their hosts [61]. Due to the fact that temperate phages are capable of exchanging their genetic material, FMT may transfer high-risk genetic information from donor phages to recipients that will maintain their host health. This also explains that the symbiosis between Bacteroidetes and Firmicutes with temperate and lytic phages is an important step toward dysbiosis alleviation [62]. Expectedly, our meta-analysis showed that more engraftment of temperate phages was present in most of recipients with rCDI after FMT. Nevertheless, about 90% of healthy individuals did not have a dominant phage sequence harboring a temperate phage genome marker, suggesting that human gut phages might persist for long periods without being integrated into their host genomes [63]. Of note, the coexisting phages in post-FMT recipients were mainly temperate ones, which were consistent across conditions. By introducing temperate phages into the community, related bacterial hosts may be killed, but not the original hosts [64].

To explore these post-FMT commonalities associated with temperate phages, we annotated and compared AMGs in phages with different lifestyles. AMGs are essential for a wide range of microbial functions, such as nutrient metabolism, biofilm formation, bacterial motility and transportation [65]. As expected, higher richness and diversity of AMGs were observed in temperate phages. In phage evolution, horizontal gene transfer (HGT) is a major driving force, and the frequency of HGT varies with different lifestyle [66]. Temperate phages often experience more HGT than lytic ones, as more frequent HGT enables phage genomes to become more functionally diverse [67]. Additionally, we found that a higher proportion of AMGs was identified from temperate rather than lytic phages. Under gut dysbiosis, a low bacterial diversity could lead to low phage diversity, indicating phages adapt strategies that are not dependent on their hosts for abundance, possibly favoring the temperate lifestyle [58]. Meanwhile, the presence of AMGs in temperate phages might enhance the survivability of their bacterial hosts [43].

This meta-analysis outlined some commonalities in phage-assisted metabolic regulation of bacterial hosts after FMT. Our results supported a hypothesis that FMT might enhance phage AMGs assisted in microbial glycolysis and biosynthesis of lactate and acetate across diseases. It has been reported that genes involved in the glycolysis were associated with more physical activity, which were transmissible from exercised donors to recipients after FMT [68]. Lactate, a major product derived from carbohydrates, inhibited the reproduction of pathogenic bacteria [69]. AMGs involved in microbial short-chain fatty acid biosynthesis have been found in low-risk patients undergoing allogeneic stem cell transplants, which may assist in providing protective immunomodulatory metabolites during FMT [70]. Acetate, another potential beneficial factor with immunomodulatory effects, was reduced in chronic disease states and was significantly elevated by FMTs [71, 72]. Moreover, we speculate that phage AMGs might assist in regulating bacterial DNA methyltransferase. SAMe might transfer less methyl group under the action of DNA (cytosine-5)-methyltransferase that was significantly reduced after FMT. Previous studies have showed that the bacterial DNA methyltransferase is a transcriptional regulator that enables bacteria to adapt more quickly to environmental changes, for example, to resist antibiotics [73]. In addition, FMT promoted AMGs-assisted microbial biosynthesis of shikimate and tryptophan. Numerous studies have demonstrated that tryptophan and its derivatives play important roles in maintaining gut health and alleviating inflammation [74]. The shikimate pathway that produces aromatic amino acids (mainly including tyrosine, phenylalanine and tryptophan) in microbes has been identified as a highly conserved metabolic module in the human gut [75]. Interestingly, gut phages from donors have the potential to regulate microbial shikimate pathway through FMT, although the detailed mechanism is currently unexplained. Overall, these results highlight the importance of phages in the gut ecosystem and provide a novel perspective for future FMT/FVT research to investigate underlying mechanisms.

This study merits further consideration in the following aspects. First, there was a limited sample size for some conditions to draw firm conclusions. Second, detailed metadata was missing in most of donors and recipients. Given that potential batch effects cannot be excluded, the comparative analysis across different datasets and diseases is extremely important, but remains difficult. Associations between metagenomic features alone are insufficient to explain how gut phages function after FMT. Third, longitudinally statistical comparisons in each dataset, condition or sample type were not performed due to the lack of uniform follow-up scheme and protocol in different diseases. Despite these limitations and challenges, our meta-analysis compared commonalities and differences of gut phages and viral outcomes of engraftment after FMT in a cross-disease perspective, providing a visual overview of previously clinical FMT studies and a novel insight into phage involvement in FMTs.

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Not applicable.

Acknowledgements

We gratefully thank the Finnish IT Center for Science (CSC – IT Center for Science Ltd.) for providing high performance computing (HPC) Puhti and storage platform Allas. We are also grateful to the China Scholarship Council (CSC Scholarship No. 202308440504).

Funding

This work was supported by the Joint Funds of National Natural Science Foundation of China (U22A20365), the National Natural Science Foundation of China (T2341019), the Natural Science Foundation of Guangdong Province (2023A1515012429) and the Guangzhou Science and Technology Plan Project (2024B03J1343).

Availability of data and materials

Datasets used in this study were previously deposited in the Sequence Read Archive (SRA) (PRJNA637878, PRJNA678737, PRJNA628604, PRJNA285502, PRJNA672867, PRJNA525458, PRJNA643802, PRJNA625520, PRJNA349197, PRJNA321058, PRJNA705895, PRJNA701961, PRJNA628029, PRJNA438164, PRJNA353655, PRJNA510036, PRJNA728680, PRJNA637785) and the European Nucleotide Archive (ENA) (PRJEB39023, PRJEB47909, PRJEB12357, PRJEB44737, PRJEB64621).

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

S.J. drafted the manuscript and performed metagenome analysis. T.V. and F.A. contributed to metagenomic workflows. B.P., Y.Y. and M.S. contributed to interpretation of clinical results and manuscript preparation. X.Z. and T.V. supervised the work, conceived the study and contributed to manuscript preparation. All authors reviewed the manuscript.

Yadegar A, Bar-Yoseph H, Monaghan TM, et al. Fecal microbiota transplantation: current challenges and future landscapes. Clin Microbiol Rev. 2024;37(2):e0006022.
Baunwall SMD, Lee MM, Eriksen MK, et al. Faecal microbiota transplantation for recurrent Clostridioides difficile infection: An updated systematic review and meta-analysis. EClinicalMedicine. 2020;29-30:100642.
Wilson BC, Vatanen T, Jayasinghe TN, et al. Strain engraftment competition and functional augmentation in a multi-donor fecal microbiota transplantation trial for obesity. Microbiome. 2021;9(1):107.
Chen Q, Wu C, Xu J, et al. Donor-recipient intermicrobial interactions impact transfer of subspecies and fecal microbiota transplantation outcome. Cell Host Microbe. 2024;32(3):349-365.e4.
Ianiro G, Punčochář M, Karcher N, et al. Variability of strain engraftment and predictability of microbiome composition after fecal microbiota transplantation across different diseases. Nat Med. 2022;28(9):1913-1923.
Bar-Yoseph H, Carasso S, Shklar S, et al. Oral Capsulized Fecal Microbiota Transplantation for Eradication of Carbapenemase-producing Enterobacteriaceae Colonization With a Metagenomic Perspective. Clin Infect Dis. 2021;73(1):e166-e175.
Woodworth MH, Conrad RE, Haldopoulos M, et al. Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement. Sci Transl Med. 2023;15(720):eabo2750.
Kong L, Lloyd-Price J, Vatanen T, et al. Linking Strain Engraftment in Fecal Microbiota Transplantation With Maintenance of Remission in Crohn's Disease. Gastroenterology. 2020;159(6):2193-2202.e5.
Vaughn BP, Vatanen T, Allegretti JR, et al. Increased Intestinal Microbial Diversity Following Fecal Microbiota Transplant for Active Crohn's Disease. Inflamm Bowel Dis. 2016;22(9):2182-2190.
Damman CJ, Brittnacher MJ, Westerhoff M, et al. Low Level Engraftment and Improvement following a Single Colonoscopic Administration of Fecal Microbiota to Patients with Ulcerative Colitis. PLoS One. 2015;10(8):e0133925.
Nusbaum DJ, Sun F, Ren J, et al. Gut microbial and metabolomic profiles after fecal microbiota transplantation in pediatric ulcerative colitis patients. FEMS Microbiol Ecol. 2018;94(9):fiy133.
Lee STM, Kahn SA, Delmont TO, et al. Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics. Microbiome. 2017;5(1):50.
Baruch EN, Youngster I, Ben-Betzalel G, et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science. 2021;371(6529):602-609.
Davar D, Dzutsev AK, McCulloch JA, et al. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science. 2021;371(6529):595-602.
Kootte RS, Levin E, Salojärvi J, et al. Improvement of Insulin Sensitivity after Lean Donor Feces in Metabolic Syndrome Is Driven by Baseline Intestinal Microbiota Composition. Cell Metab. 2017;26(4):611-619.e6.
Ianiro G, Rossi E, Thomas AM, et al. Faecal microbiota transplantation for the treatment of diarrhoea induced by tyrosine-kinase inhibitors in patients with metastatic renal cell carcinoma. Nat Commun. 2020;11(1):4333.
Zhao HJ, Luo X, Shi YC, et al. The Efficacy of Fecal Microbiota Transplantation for Children With Tourette Syndrome: A Preliminary Study. Front Psychiatry. 2020;11:554441.
Suez J, Zmora N, Zilberman-Schapira G, et al. Post-Antibiotic Gut Mucosal Microbiome Reconstitution Is Impaired by Probiotics and Improved by Autologous FMT. Cell. 2018;174(6):1406-1423.e16.
Ott SJ, Waetzig GH, Rehman A, et al. Efficacy of Sterile Fecal Filtrate Transfer for Treating Patients With Clostridium difficile Infection. Gastroenterology. 2017;152(4):799-811.e7.
Rasmussen TS, Mentzel CMJ, Kot W, et al. Faecal virome transplantation decreases symptoms of type 2 diabetes and obesity in a murine model. Gut. 2020;69(12):2122-2130.
Wortelboer K, de Jonge PA, Scheithauer TPM, et al. Phage-microbe dynamics after sterile faecal filtrate transplantation in individuals with metabolic syndrome: a double-blind, randomised, placebo-controlled clinical trial assessing efficacy and safety. Nat Commun. 2023;14(1):5600.
Goloshchapov OV, Olekhnovich EI, Sidorenko SV, et al. Long-term impact of fecal transplantation in healthy volunteers. BMC Microbiol. 2019;19(1):312.
Aggarwala V, Mogno I, Li Z, et al. Precise quantification of bacterial strains after fecal microbiota transplantation delineates long-term engraftment and explains outcomes. Nat Microbiol. 2022;7(5):736.
Hourigan SK, Ahn M, Gibson KM, et al. Fecal Transplant in Children With Clostridioides difficile Gives Sustained Reduction in Antimicrobial Resistance and Potential Pathogen Burden. Open Forum Infect Dis. 2019;6(10):ofz379.
Moss EL, Falconer SB, Tkachenko E, et al. Long-term taxonomic and functional divergence from donor bacterial strains following fecal microbiota transplantation in immunocompromised patients. PLoS One. 2017;12(8):e0182585.
Podlesny D, Arze C, Dörner E, et al. Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation. Microbiome. 2022;10(1):53.
Verma S, Dutta SK, Firnberg E, Phillips L, Vinayek R, Nair PP. Identification and engraftment of new bacterial strains by shotgun metagenomic sequence analysis in patients with recurrent Clostridioides difficile infection before and after fecal microbiota transplantation and in healthy human subjects. PLoS One. 2021;16(7):e0251590.
Watson AR, Füssel J, Veseli I, et al. Metabolic independence drives gut microbial colonization and resilience in health and disease. Genome Biol. 2023;24(1):78.
Nooij S, Vendrik KEW, Zwittink RD, et al. Long-term beneficial effect of faecal microbiota transplantation on colonisation of multidrug-resistant bacteria and resistome abundance in patients with recurrent Clostridioides difficile infection. Genome Med. 2024;16(1):37.
Felix Krueger. Trim Galore. https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/.
Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31(10):1674-1676.
Jiarong Guo, Dean Vik, Akbar Adjie Pratama, Simon Roux, Matthew Sullivan 2021. Viral sequence identification SOP with VirSorter2. https://dx.doi.org/10.17504/protocols.io.bwm5pc86.
Guo J, Bolduc B, Zayed AA, et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome. 2021;9(1):37.
Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35(11):1026-1028.
Roux S, Adriaenssens EM, Dutilh BE, et al. Minimum Information about an Uncultivated Virus Genome (MIUViG). Nat Biotechnol. 2019;37(1):29-37.
Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119.
Bin Jang H, Bolduc B, Zablocki O, et al. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nat Biotechnol. 2019;37(6):632-639.
Hockenberry AJ, Wilke CO. BACPHLIP: predicting bacteriophage lifestyle from conserved protein domains. PeerJ. 2021;9:e11396.
Roux S, Camargo AP, Coutinho FH, et al. iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria. PLoS Biol. 2023;21(4):e3002083.
Shaffer M, Borton MA, McGivern BB, et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 2020;48(16):8883-8900.
Jian H, Yi Y, Wang J, Hao Y, Zhang M, Wang S, et al. Diversity and distribution of viruses inhabiting the deepest ocean on Earth. ISME J. 2021;15:3094–3110.
Luo XQ, Wang P, Li JL, et al. Viral community-wide auxiliary metabolic genes differ by lifestyles, habitats, and hosts. Microbiome. 2022;10(1):190.
Zuppi M, Vatanen T, Wilson BC, et al. Fecal microbiota transplantation alters gut phage communities in a clinical trial for obesity. Microbiome. 2024;12(1):122.
Wirbel J, Zych K, Essex M, et al. Microbiome meta-analysis and cross-disease comparison enabled by the SIAMCAT machine learning toolbox. Genome Biol. 2021;22(1):93.
Mallick H, Rahnavard A, McIver LJ, et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol. 2021;17(11):e1009442.
Chong J, Liu P, Zhou G, Xia J. Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc. 2020;15(3):799-821.
Yang J, Hou L, Wang J, et al. Unfavourable intrauterine environment contributes to abnormal gut microbiome and metabolome in twins. Gut. 2022;71(12):2451-2462.
Johansen J, Atarashi K, Arai Y, et al. Centenarians have a diverse gut virome with the potential to modulate metabolism and promote healthy lifespan. Nat Microbiol. 2023;8(6):1064-1078.
Zuo T, Wong SH, Lam K, et al. Bacteriophage transfer during faecal microbiota transplantation in Clostridium difficile infection is associated with treatment outcome. Gut. 2018;67(4):634-643.
Fujimoto K, Kimura Y, Allegretti JR, et al. Functional Restoration of Bacteriomes and Viromes by Fecal Microbiota Transplantation. Gastroenterology. 2021;160(6):2089-2102.e12.
Yang K, Niu J, Zuo T, et al. Alterations in the Gut Virome in Obesity and Type 2 Diabetes Mellitus. Gastroenterology. 2021;161(4):1257-1269.e13.
Park H, Laffin MR, Jovel J, et al. The success of fecal microbial transplantation in Clostridium difficile infection correlates with bacteriophage relative abundance in the donor: a retrospective cohort study. Gut Microbes. 2019;10(6):676-687.
Draper LA, Ryan FJ, Smith MK, et al. Long-term colonisation with donor bacteriophages following successful faecal microbial transplantation. Microbiome. 2018;6(1):220.
Chehoud C, Dryga A, Hwang Y, et al. Transfer of Viral Communities between Human Individuals during Fecal Microbiota Transplantation. mBio. 2016;7(2):e00322.
Broecker F, Klumpp J, Moelling K. Long-term microbiota and virome in a Zürich patient after fecal transplantation against Clostridium difficile infection. Ann N Y Acad Sci. 2016;1372(1):29-41.
Rasmussen TS, Mao X, Forster S, et al. Overcoming donor variability and risks associated with fecal microbiota transplants through bacteriophage-mediated treatments. Microbiome. 2024;12(1):119.
Kang DW, Adams JB, Gregory AC, et al. Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study. Microbiome. 2017;5(1):10.
Liu Q, Xu Z, Dai M, Su Q, Leung Chan FK, Ng SC. Faecal microbiota transplantations and the role of bacteriophages. Clin Microbiol Infect. 2023;29(6):689-694.
Lin DM, Lin HC. A theoretical model of temperate phages as mediators of gut microbiome dysbiosis. F1000Res. 2019;8:F1000 Faculty Rev-997.
Gogokhia L, Buhrke K, Bell R, et al. Expansion of Bacteriophages Is Linked to Aggravated Intestinal Inflammation and Colitis. Cell Host Microbe. 2019;25(2):285-299.e8.
Gummalla VS, Zhang Y, Liao YT, Wu VCH. The Role of Temperate Phages in Bacterial Pathogenicity. Microorganisms. 2023;11(3):541.
van Lier YF, Vos J, Blom B, Hazenberg MD. Allogeneic hematopoietic cell transplantation, the microbiome, and graft-versus-host disease. Gut Microbes. 2023;15(1):2178805.
Shkoporov AN, Clooney AG, Sutton TDS, et al. The Human Gut Virome Is Highly Diverse, Stable, and Individual Specific. Cell Host Microbe. 2019;26(4):527-541.e5.
Brown TL, Charity OJ, Adriaenssens EM. Ecological and functional roles of bacteriophages in contrasting environments: marine, terrestrial and human gut. Curr Opin Microbiol. 2022;70:102229.
Rosenwasser S, Ziv C, Creveld SGV, Vardi A. Virocell Metabolism: Metabolic Innovations During Host-Virus Interactions in the Ocean. Trends Microbiol. 2016;24(10):821-832.
Dion MB, Oechslin F, Moineau S. Phage diversity, genomics and phylogeny. Nat Rev Microbiol. 2020;18(3):125-138.
Moura de Sousa JA, Pfeifer E, Touchon M, Rocha EPC. Causes and Consequences of Bacteriophage Diversification via Genetic Exchanges across Lifestyles and Bacterial Taxa. Mol Biol Evol. 2021;38(6):2497-2512.
Lai ZL, Tseng CH, Ho HJ, et al. Fecal microbiota transplantation confers beneficial metabolic effects of diet and exercise on diet-induced obese mice. Sci Rep. 2018;8(1):15625.
Cheng S, Ma X, Geng S, et al. Fecal Microbiota Transplantation Beneficially Regulates Intestinal Mucosal Autophagy and Alleviates Gut Barrier Injury. mSystems. 2018;3(5):e00137-18.
Thiele Orberg E, Meedt E, Hiergeist A, et al. Bacteria and bacteriophage consortia are associated with protective intestinal metabolites in patients receiving stem cell transplantation. Nat Cancer. 2024;5(1):187-208.
Su SH, Chen M, Wu YF, et al. Fecal microbiota transplantation and short-chain fatty acids protected against cognitive dysfunction in a rat model of chronic cerebral hypoperfusion. CNS Neurosci Ther. 2023;29 Suppl 1(Suppl 1):98-114.
Hu C, Xu B, Wang X, et al. Gut microbiota-derived short-chain fatty acids regulate group 3 innate lymphoid cells in HCC. Hepatology. 2023;77(1):48-64.
Wang X, Yu D, Chen L. Antimicrobial resistance and mechanisms of epigenetic regulation. Front Cell Infect Microbiol. 2023;13:1199646.
Lavelle A, Sokol H. Gut microbiota-derived metabolites as key actors in inflammatory bowel disease. Nat Rev Gastroenterol Hepatol. 2020;17(4):223-237.
Almeida A, Nayfach S, Boland M, et al. A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat Biotechnol. 2021;39(1):105-114.

No competing interests reported.

SupplementaryFig.1.pdf
Supplementary Fig.1 PCoA plots of Bray-Curtis dissimilarity between phageome profiles of donors (a, PERMANOVA, P < 0.001, R² = 36%) and recipients (b, PERMANOVA, P < 0.001, R² = 28%) in each dataset.
SupplementaryFig.2.pdf
Supplementary Fig.2 Evaluation of confounding covariates (post-QC sequencing read count, country and FMT study ID) on an inter-group comparison between donors and recipients at baselineaccording to SIAMCAT.
SupplementaryFig.3.pdf
Supplementary Fig.3 a) Proportions of temperate and lytic phages in different phage engraftment outcomes in each recipient. b) Comparisons of phage relative abundance between lifestyles. Data are represented as median ± IQR. Outliers are marked as black points. * p< 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. c) Phageome shift towards donor phageome profiles in different patient conditions and FMT studies. Data from studies with multiple donors per recipient [3,8,29] were excluded from this graph. Data are represented as median ± IQR. Outliers are marked as black points.
SupplementaryFig.4.pdf
Supplementary Fig.4 Pairwise comparisons of AMG relative abundances involved in glycolysis (a) and pyruvate metabolism (b) of bacterial hosts between donors and recipients (pre- and post-FMT).
SupplementaryFig.5.pdf
Supplementary Fig.5 Pairwise comparisons of AMG relative abundances involved in cysteine biosynthesis (a), methionine biosynthesis (b) and methionine degradation (c) of bacterial hosts between donors and recipients (pre- and post-FMT).
SupplementaryFig.6.pdf
Supplementary Fig.6 Pairwise comparisons of AMG relative abundances involved in shikimate pathway (a) and tryptophan biosynthesis (b) of bacterial hosts between donors and recipients (pre- and post-FMT).
SupplementaryTables.xlsx

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Engrafting gut bacteriophages have potential to modulate microbial metabolism in fecal microbiota transplantation

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Abstract

Background

Methods

Results

Conclusions

Figures

Introduction

Methods

Datasets

Quality control

Viral identification and abundance

vOTUs characterization

AMG annotation and abundance

Classification and quantification of phage engraftment outcomes after FMT

Statistical analyses

Results

Gut phageome meta-analysis of 23 FMT studies

FMT lead to increased phageome diversity and shift towards donors

Phageome engraftment outcomes varied across patient conditions

More abundant temperate phages were associated with engraftment outcomes

Phage AMGs carriage and diversity differed by lifestyle

AMGs in phageome may support and regulate gut microbial metabolism after FMT

Discussion

Limitations

Declarations

References

Additional Declarations

Supplementary Files

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Version 1