Autologous fecal microbiota transplantation can retain the metabolic achievements of dietary interventions

Open AccessPublished:April 18, 2021DOI:https://doi.org/10.1016/j.ejim.2021.03.038

      Abstract

      Background

      We recently reported that autologous fecal microbiota transplantation (aFMT), derived from the time of maximal weight-loss and administrated in the regain-phase, might preserve weight loss and glycemic control in moderately obese subjects, and is associated with specific microbiome signatures. Here, we sought to explore the global effect of aFMT on adipokines, inflammatory markers and blood cholesterol and on the overall gut microbiome preservation.

      Methods

      In the DIRECT-PLUS weight-loss trial, abdominally obese participants were randomized to three distinct weight-loss diets. Following the expected weight loss phase (0–6 m), 90 participants were randomized to receive their personal frozen fecal microbiota or placebo oral capsules (ten 1 g-capsules over ten sessions-total=100 g) during the expected weight regain phase (8–14 m).

      Results

      Of the 90 participants (age=52 yr; 0–6 m weight loss=-8.3 kg), 95.6% ingested at least 80/100 oral aFMT/placebo capsules over 6 months. Overall, the gut microbiome community structure was associated with plasma levels of leptin, cholesterol and interleukin-6 at baseline and after 6 m, whereas 6 m (weight loss phase) changes in specific microbiome species associated with the dynamic of leptin and inflammatory biomarkers. Following the 8–14 m aFMT administration phase, aFMT maintained decreased levels of leptin (ΔaFMT=-3.54 ng/mL vs. Δplacebo=-0.82 ng/mL;P = 0.04), C-reactive-protein (ΔaFMT=-1.45 mg/L vs. Δplacebo=-0.66 mg/L;P = 0.009), Interleukin-6 (ΔaFMT=-0.03pg/mL vs. Δplacebo=1.11pg/mL;P = 0.03) and total cholesterol (ΔaFMT=2.2 mg/dl vs. Δplacebo=13.1 mg/dl;P = 0.04) achieved in the weight loss phase. Overall, aFMT induced a significant preservatory effect on personal gut microbiome global composition (P = 0.03;Jensen-Shannon distance), as compared to placebo.

      Conclusions

      aFMT treatment in the regain phase might retain weight-loss induced metabolic benefits. These findings may suggest a novel aFMT treatment approach for personal metabolic attainment preservation.

      Keywords

      1. Introduction

      The human gut microbiome, defined by the ecological community of commensal, symbiotic, and pathogenic microorganisms that occupy the human gastrointestinal tract[
      The NIH HMP Working Group
      The NIH human microbiome project.
      ], is known to have a pivotal role in the metabolic health of its human host[
      • Sonnenburg J.L.
      • Bäckhed F.
      Diet–microbiota interactions as moderators of human metabolism.
      ,
      • Bäckhed F.
      • Ding H.
      • Wang T.
      • et al.
      The gut microbiota as an environmental factor that regulates fat storage.
      ,
      • Schroeder B.O.
      • Bäckhed F.
      Signals from the gut microbiota to distant organs in physiology and disease.
      ,
      • Liu R.
      • Hong J.
      • Xu X.
      • et al.
      Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention.
      ]. The gut microbiome function and composition has many contributing factors. Some are fixed, such as age and genetics, and some can be modified, including medications, lifestyle and dietary regime[
      • Yatsunenko T.
      • Rey F.E.
      • Manary M.J.
      • et al.
      Human gut microbiome viewed across age and geography.
      ,
      • Ussar S.
      • Griffin N.W.
      • Bezy O.
      • et al.
      Interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and article interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and metabolic syndrome.
      ,
      • Goodrich J.K.
      • Waters J.L.
      • Poole A.C.
      • et al.
      Human genetics shape the gut microbiome.
      ,
      • Wu G.D.
      • Chen J.
      • Hoffmann C.
      • et al.
      Linking long-term dietary patterns with gut microbial enterotypes.
      ,
      • Forslund K.
      • Hildebrand F.
      • Nielsen T.
      • et al.
      Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota.
      ,
      • Falcony G.
      • Joossens M.
      • Vieira-Silva S.
      • et al.
      Population-level analysis of gut microbiome variation.
      ,
      • Charbonneau M.R.
      • Blanton L.V.
      • DiGiulio D.B.
      • et al.
      A microbial perspective of human developmental biology.
      ,
      • Turnbaugh P.J.
      • Ley R.E.
      • a Mahowald M
      • Magrini V.
      • Mardis E.R.
      • Gordon J.I
      An obesity-associated gut microbiome with increased capacity for energy harvest.
      ]. Fecal microbiota transplantation (FMT) is a therapeutic procedure that has been established as safe and efficient in the treatment of recurrent Clostridioides difficile infection, and is based on the reconstitution of normal microbiota by transplantation of stool from a healthy individual[
      • Youngster I.
      • Russell G.H.
      • Pindar C.
      • Ziv-Baran T.
      • Sauk J.
      • Hohmann E.L.
      Oral, capsulized, frozen fecal microbiota transplantation for relapsing Clostridium difficile infection.
      ,
      • McCune V.L.
      • Struthers J.K.
      • Hawkey P.M.
      Faecal transplantation for the treatment of Clostridium difficile infection: a review.
      ,
      • Austin M.
      • Mellow M.
      • Tierney W.M.
      Fecal microbiota transplantation in the treatment of clostridium difficile infections.
      ]. In recent years, many trials evaluating the efficacy of FMT for various disease-states were conducted, some showing promising results[
      • Kootte R.S.
      • Levin E.
      • Salojärvi J.
      • et al.
      Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition.
      ,
      • Halkjær S.I.
      • Christensen A.H.
      • Lo B.Z.S.
      • et al.
      Faecal microbiota transplantation alters gut microbiota in patients with irritable bowel syndrome: results from a randomised, double-blind placebo-controlled study.
      ,
      • Carlucci C.
      • Petrof E.O.
      • Allen-Vercoe E.
      Fecal microbiota-based therapeutics for recurrent clostridium difficile infection, ulcerative colitis and obesity.
      ,
      • Li S.S.
      • Zhu A.
      • Benes V.
      • et al.
      Durable coexistence of donor and recipient strains after fecal microbiota transplantation.
      ,
      • Costello S.P.
      • Hughes P.A.
      • Waters O.
      • et al.
      Effect of fecal microbiota transplantation on 8-week remission in patients with ulcerative colitis: a randomized clinical trial.
      ]. Three specific trials have evaluated the potential of microbiome transfer as a mean to carry a beneficial “lean” phenotype to obese individuals by FMT, demonstrating a partial metabolic response, mainly in glycemic control[
      • Kootte R.S.
      • Levin E.
      • Salojärvi J.
      • et al.
      Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition.
      ,
      • Vrieze A.
      • Van Nood E.
      • Holleman F.
      • et al.
      Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome.
      ,
      • Allegretti J.R.
      • Kassam Z.
      • Mullish B.H.
      • et al.
      Effects of fecal microbiota transplantation with oral capsules in obese patients.
      ]. To date, however, FMT is not considered standard-of-care for any indications other than recurrent Clostridioides difficile infection.
      Autologous FMT (aFMT) is another form of fecal transplantation, and is based on the self-administration of microbiota from a previous state that is considered beneficial, to a current detrimental state. For example, aFMT was recently shown to induce a rapid and near-complete recovery from antibiotics-associated dysbiosis, within days of administration[
      • Suez J.
      • Zmora N.
      • Zilberman-Schapira G.
      • et al.
      Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous FMT.
      ]. We recently reported the use of aFMT for the attenuation of weight regain following weight loss, as a form of personalized treatment for weight loss maintenance. We have shown evidence supporting this novel approach: beneficial modification of the microbiome during weight loss by distinct dietary regimens, processing of the personal microbiome into personalized aFMT capsules, followed by aFMT administration for long-term weight maintenance[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ]. aFMT may constitute a paradigm shift in personalized medicine, whereas an individual may achieve its optimal microbiome by, for example, dieting, only to serve as his own donor at a later point in time in a safe manner. aFMT may serve as a superior alternative to allogenic microbiota transplantation, with higher efficacy and fewer side effects.
      In this report, we further explore the association between the gut microbiome and cardiometabolic markers during weight-loss, and assess to what extent aFMT preserved the global composition of the gut microbiome. Furthermore, we evaluate the potential of aFMT to induce long-term beneficial changes in cardiometabolic markers, independently of the specific dietary strategy and beyond the effect of weight-loss.

      2. Methods

      2.1 Study design

      Methods of the DIRECT PLUS and aFMT trial were previously reported in detail[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ].
      Briefly,the trial was a two-phased randomized controlled trial involving 90 overweight/dyslipidemic sedentary adults. It was conducted between May 2017 and July 2018 among employees of the nuclear research center in Dimona, Israel. Eligibility included age above 30 years, abdominal obesity [waist circumference: men>102 cm, women>88 cm] or dyslipidemia (TG>150 and HDL Cholesterol≤40 for men; ≤50 for women). Exclusion criteria included major health impairments and are detailed in the previous report[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ]. The study was approved and monitored by the Soroka University Medical Center human subject committee. All participants provided written informed consent and received no financial compensation.
      The trial included two phases: (1) a randomized, open-label, lifestyle intervention and (2) a randomized, double-blind, aFMT augmentation. In the first phase, participants were randomly assigned in a 1:1:1 ratio to one of three lifestyle intervention groups, (1)Healthy dietary guidelines (2)Mediterranean, or (3)Green-Mediterranean diets. All groups received free gym membership and physical activity guidelines[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ].
      Following 6 months of lifestyle intervention, the expected time of maximal weight reduction[
      • Shai I.
      • Schwarzfuchs D.
      • Henkin Y.
      • et al.
      Weight loss with a low-carbohydrate, mediterranean, or low-fat diet.
      ,
      • Gepner Y.
      • Shelef I.
      • Schwarzfuchs D.
      • et al.
      Effect of distinct lifestyle interventions on mobilization of fat storage pools.
      ], participants with at least 3.5% weight-loss were recruited to the aFMT double blinded, placebo controlled, intervention.
      The eligible volunteers were asked to deliver a fecal sample that was processed into personal FMT capsules. The participants were simultaneously randomized, in a 1:1 ratio, to receive 100 g of aFMT or identical placebo capsules starting 8-months following initiation of the lifestyle intervention, until the completion of this 14-month trial. Capsules were consumed as one-gram units, given as ten capsules, over ten sessions.

      2.2 Outcomes

      Participants were weighed to the nearest 0.1 kg, and waist circumference was measured halfway between the last rib and the iliac crest to the nearest millimeter at baseline, 6 and 14-months. Blood samples were taken before breakfast after a 12 h fast.
      Plasma leptin levels were assessed by enzyme-linked immunosorbent assay (Mediagnost, Reutlingen, Germany), with a coefficient of variation of 2.4%. Serum total cholesterol (TC;Coefficient-of-variation (CV), 1.3%) and lipoprotein-cholesterol (LDL-c), were determined enzymatically with a Cobas-6000 automatic analyzer (Roche). Plasma levels of high-sensitivity C-reactive protein (hsCRP) were measured by ELISA (DiaMed;CV, 1.9%). Interleukin 6 was measured by high-sensitive ELISA according to the manufacturer's protocol. High-sensitivity C- reactive protein (hsCRP) levels >10 mg/L were excluded from analysis as these were suspected to reflect an acute inflammatory response rather than baseline inflammatory activity. Fecal samples were collected at baseline, 6 and 14 months at the study site, immediately frozen to –20 °C for 1–3 days, then transferred to –80 °C pending DNA extraction for shotgun metagenomic sequencing. To characterize the microbiome, fecal DNA was extracted, sequenced and normalized with an average depth of 15.4 ± 2.6 million reads per sample (mean±standard deviation). DNA sequences were aligned using an accelerated version of the Needleman-Wunsch algorithm to a curated database containing all representative genomes in RefSeq v86. Participants prescribed antibiotic therapy two months prior to the delivery of baseline fecal samples were excluded from all microbiome analyses. Further details regarding fecal samples handling and sequencing were previously reported[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ].

      2.3 Statistical analysis

      The aim of this report was to evaluate the effect of aFMT treatment following weight-loss on specific cardiometabolic biomarkers including adipokines, inflammatory markers and levels of deleterious cholesterols, and to assess the microbial patterns associated with these markers. Continuous variables are presented as means ± standard deviations, and categorical variables are presented as total count. Differences between time points are expressed as absolute values, unless specified otherwise. The Kolmogorov-Smirnov test was used to determine whether variables were normally distributed. To detect differences between treatment groups, t tests were used for parametric variables. Nonparametric variables and data determined to be non-normal after log-transformation were analyzed using the Mann-Whitney test. Biomarker change analysis adjustments were done using a generalized linear egression models, adjusting for weight change, gender and lifestyle intervention group. For microbiome analysis, Jensen-Shannon distance was used to assess between-samples similarity. distance-based redundancy analysis were performed using the R package vegan[

      Oksanen J., Kindt R, O’ B, Maintainer H.Vegan: community ecology package.; 2019. http://cc.oulu.fi/~jarioksa/. Accessed February 22, 2021.

      ]. Per-feature tests for the association between specific microbial species and clinical biomarkers were done using the R package MaAsLin2[
      • Mallick H.
      • Rahnavard A.
      • McIver L.J.
      • et al.
      Multivariable association discovery in population-scale meta-omics studies.
      ]. Further information regarding data processing and sample size calculation was previously reported[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ]. Differences were considered significant for P < 0.05 or FDR-corrected q<0.25 for exploratory analysis. Statistical analyses were performed using R software, version 3.5.3.

      3. Results

      3.1 Baseline characteristics and weight-loss phase

      Eligible subjects who consented to take part in the trial were randomly assigned to aFMT (n = 44) or placebo (n = 46) administration. Baseline characteristics of the participants across treatment groups, are presented in Table 1 with more data previously reported[
      • Rinott E.
      • Youngster I.
      • Meir A.Y.
      • et al.
      Effects of diet-modulated autologous fecal microbiota transplantation on weight regain.
      ]. At baseline, mean age of the aFMT and placebo groups was 53.1 years and 51.6 years, respectively (P = 0.51), and mean body mass index (BMI) was 30.9 kg/m2 and 31.4 kg/m2, respectively (P = 0.53). Across the cohort, 91% of participants were male, with no significant difference in male:female ratio between treatment groups (P = 1). No significant differences in the measured laboratory parameters were observed at baseline between the randomized treatment groups. Following 6-months of lifestyle intervention, the aFMT and placebo groups experienced a similar 0 to 6-month (i.e., baseline) weight-loss (aFMT= −8.28Kg vs. placebo=−8.25 Kg, P = 0.91). Assessing the overall treatment compliance rate by 14 months, defined as intake of >80 capsules, overall rate was 95.6%, with no difference between treatment groups.
      Table 1.Baseline characteristics of the study population.
      TotalaFMTPlaceboP value
      Number of participants904446
      Dietary group (%)
      Healthy dietary guidelines16 (17.8)8 (18.2)8 (17.4)1
      Mediterranean diet35 (38.9)19 (43.2)20 (43.5)1
      Green Mediterranean diet39 (43.3)19 (43.2)20 (43.5)1
      Male sex (%)82 (91.1)40 (90.9)42 (91.3)1
      Age- yr (sd)52.37 (10.83)53.14 (9.97)51.63 (11.65)0.51
      BMI (sd)31.14 (3.78)30.89 (3.45)31.39 (4.09)0.532
      Cholesterol -mg/dl (sd)186.44 (29.81)190.60 (26.13)182.46 (32.73)0.197
      LDL Cholesterol – mg/dl(sd)124.05 (29.18)128.26 (26.36)120.02 (31.40)0.182
      Leptin - ng/ml (sd)12.98 (10.35)12.01 (8.90)13.92 (11.59)0.385
      C reactive protein – mg/liter (sd)2.78 (1.81)2.95 (1.92)2.62 (1.71)0.413
      Interleukin 6 – mg/liter (sd)3.80 (2.10)4.01 (2.12)3.59 (2.08)0.348
      Values are presented as means (standard deviation) for continuous variables and total number (percent) for categorical variables. No significant differences were observed between treatment groups in the measured baseline characteristics. BMI denotes body mass index; LDL denotes low-density lipoprotein.

      3.2 The gut microbiome during the weight-loss period (0–6 months)

      Assessing the association between microbiome composition and the measured clinical parameters before the initiation of capsule administration (baseline and 6-months), we employed a distance-based redundancy analysis on Jensen-Shannon distance. The model was used in order to estimate the impact of specific variables on the ordination and therefore bacterial community composition. Of the analyzed clinical biomarkers, body-weight (P = 0.003), leptin (P = 0.01), LDL and total plasma cholesterol (P = 0.04 and P = 0.009, respectively), and Interluekin-6 (P = 0.02) represented parameters significantly shaping community composition. CRP (P = 0.15) was the only tested variable not showing significant association with the microbiome composition (Fig. 1A). We next performed per-feature testing in MaAsLin2 using linear mixed models to identify microbial species associated with the measured blood biomarkers (leptin, CRP, Interluekin-6, LDC and total cholesterol) and body weight during the initial 6-month weight-loss phase. The model included each participant's identifier as random effect, simultaneously adjusting for time and body-weight effect, as well as all other clinical parameters. A total of 44 species-level features were significantly associated with at least one biomarker. Among the observed associations, leptin levels were directly associated with in Bifidobacterium bifidum levels, and hsCRP level were directly associated with Lactobacillus sakei (Fig. 1B).
      Fig. 1
      Fig. 1The gut microbiome during the weight-loss (0–6 m) and weight regain (6–14 m) phases
      (A) distance-based redundancy analysis (dbRDA) with fitting of explanatory variables; significantly impactful variables after permutation analysis are marked with asterisks. p values *: p<0.05, **: p<0.01, ***: p<0.001 (B) Associations between clinical biomarkers and bacterial species, colors denote positive (red) and negative (color) associations measured by MaAsLin2 coefficients.
      FDR- adjusted p values *: q<0.25, **: q<0.05, ***: q<0.01, ****: q<0.001. (C) Microbiome preservation, measured as person-specific composition similarity to baseline (weight-loss phase) minus composition similarity to endpoint (weight regain phase, during capsules administration). Similarity was measured by the Jensen-Shannon Divergence index.

      3.3 Preservation of gut microbiome composition by aFMT treatment

      We next sought to examine to what extent the global composition of the microbiome was preserved by the aFMT treatment. To that end, for each individual's microbiome composition at the 6-months timepoint, we measured the difference between the similarity to baseline (composition change during weight-loss; 0–6 m) and similarity to endpoint (composition change during weight regain; 6–14 m) using the Jensen-Shannon distance. While the mean difference between (0-6) m and (6–14) m composition for the placebo group was −0.004 (within group P = 0.8), the mean difference for the aFMT group was −0.057, with the 6 m composition being significantly more similar to endpoint (within group P = 0.002). Comparing the difference between the two treatment groups the aFMT group showed a significantly higher similarity between the 6–14 m timepoints (P = 0.03; Fig. 1C).

      3.4 aFMT effect on blood biomarkers following 14 months

      While leptin levels were decreased in both treatment groups following the weight-loss phase (0–6 m; aFMT: −6.72 ng/mL, placebo: −6.76 ng/mL; P = 0.92), by 14-months, leptin reduction was maintained only in the aFMT group, with a significant difference between groups, both in a crude comparison, and after further adjusting to sex, dietary group, and 14-month weight change (aFMT: −3.54 ng/mL, placebo: −0.82 ng/mL; Crude P = 0.04, Adjusted model P = 0.03). Comparing the levels of blood FGF21 along the trial, while both treatment groups underwent a similar reduction following 6-months (aFMT: −10.2pg/mL, placebo: −15.82 ng/mL; Adjusted model P = 0.89), by 14 months, an increase was observed in the placebo group while the reduction continued in the aFMT group, with a non-significant difference between the two treatment groups (aFMT: −24.7pg/mL, placebo: 24.2 ng/mL; Adjusted model P = 0.09; Fig. 2A). Evaluating the effect of aFMT treatment on inflammatory markers, High-sensitivity C-reactive protein (hs-CRP) levels were reduced in both intervention groups following 14-months, with a significantly greater reduction observed in the aFMT group (−1.45 mg/L vs. −0.66 mg/L respectively; Crude P = 0.03; Adjusted model P = 0.02). Furthermore, after 14-months interleukin-6 (IL-6) levels did not significantly change in the aFMT group, but were increased in the placebo group, with a significant difference between groups (−0.03pg/mL vs. 1.11pg/mL respectively; Crude P = 0.03; Adjusted model P = 0.04; Fig. 2B). Evaluating 14 months changes in LDL and total cholesterol, a non-significant trend was noted in the change of LDL cholesterol levels between groups (aFMT: −4.92 mg/dl vs. placebo: 2.01 mg/dl; Adjusted model P = 0.07) and a significant difference between groups was observes in total cholesterol (aFMT: 2.22 mg/dl vs. placebo: 13.1 mg/dl; Adjusted model P = 0.04) (Fig. 2C).
      Fig. 2
      Fig. 214-month changes in blood biomarkers by aFMT treatment
      Bar values denote mean change and vertical bars indicate standard errors. Between-groups P values were generated using a generalized linear egression models, adjusting for weight change, gender and lifestyle intervention group. hsCRP levels of more than 10 mg/L at any time point were excluded from analysis, as they reflect an unusual intercurrent inflammatory condition rather than a steady state inflammatory activity.40 LDL denotes low-density lipoprotein.

      4. Discussion

      In this 14-month human trial including 90 participants, aFMT derived from the maximal weight loss timepoint had a significant preservatory effect on the gut microbiome composition, with the bacterial community structure at baseline being associated with several cardiometabolic markers, including body weight, the adipokine leptin, total cholesterol and the inflammatory marker interleukin-6. Following aFMT administration, beneficial cardiometabolic effects were observed, independently of weight change and weight-loss strategy, on leptin levels and inflammatory markers CRP and interleukin-6, with a significant effect on total cholesterol and a marginal effect on LDL-cholesterol.
      The trial had several limitations that should be acknowledged. The low proportion of women, reflecting the proportion of women in the workplace, limits the generalizability of findings to women. Furthermore, due to our stringent inclusion criteria and demanding nature of our intervention, the sample size of our trial was somewhat limited. However, our trial was sufficiently powered to reveal preservatory patterns of several biomarkers and the gut microbiome during the regain phase. The strengths of the study include the high adherence rate, the double-blinded placebo-controlled design with strict monitoring of capsule administrations, and the high-resolution microbiome characterization by shotgun metagenomics.
      In recent years, a growing body of literature explores the approach of FMT as a method to transfer various beneficial microbial signatures from donor's to recipient's gut, and by that, transferring specific health-related phenotypes[
      • Kootte R.S.
      • Levin E.
      • Salojärvi J.
      • et al.
      Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition.
      ,
      • Halkjær S.I.
      • Christensen A.H.
      • Lo B.Z.S.
      • et al.
      Faecal microbiota transplantation alters gut microbiota in patients with irritable bowel syndrome: results from a randomised, double-blind placebo-controlled study.
      ,
      • Carlucci C.
      • Petrof E.O.
      • Allen-Vercoe E.
      Fecal microbiota-based therapeutics for recurrent clostridium difficile infection, ulcerative colitis and obesity.
      ,
      • Li S.S.
      • Zhu A.
      • Benes V.
      • et al.
      Durable coexistence of donor and recipient strains after fecal microbiota transplantation.
      ]. The backbone of this paradigm is that exogenic communities can prosper when introduced to a new environment. Two recent studies evaluated the determinants of bacterial engraftment in FMT recipients for Clostridioides difficile patients and patients with the metabolic syndrome. Both studies concluded that introduced strains are more likely to populate a new environment if the species is already present[
      • Li S.S.
      • Zhu A.
      • Benes V.
      • et al.
      Durable coexistence of donor and recipient strains after fecal microbiota transplantation.
      ,
      • Smillie C.S.
      • Sauk J.
      • Gevers D.
      • et al.
      Strain tracking reveals the determinants of bacterial engraftment in the human gut following fecal microbiota transplantation.
      ]. This evidence reinforced our hypothesis that aFMT might have distinct advantages over FMT, as aFMT harbors almost 100% presence of species in the recipient. A different study done with obese and lean mice in a reciprocal, bi-directional, FMT-like setting, studied the invasion patterns of lean-specific and obese-specific bacterial strains. Interestingly enough, it appeared that there was a significant invasion of lean-specific strains into the obese-mice microbiota, but not vice versa[
      • Ridaura V.K.
      • Faith J.J.
      • Rey F.E.
      • et al.
      Gut microbiota from twins discordant for obesity modulate metabolism in mice.
      ]. Beyond the preservatory effect of aFMT we report, we observed beneficial effects of aFMT on several cardiometabolic biomarkers. Leptin, an adipokine that may play a signaling role from adipose tissue to the brain, directly contributing to weight regain, demonstrated significantly lower levels in the aFMT group. This finding is of relevance, as it was reported that although metabolic and behavioral responses contribute to the maintenance of body weight, part of the opposition force, inducing weight regain, can be attributed to leptin[
      • Rosenbaum M.
      • Leibel R.L.
      Adaptive thermogenesis in humans.
      ]. Furthermore, the joint effect of aFMT on plasma CRP and leptin, might reflect the previously reported association between higher levels of inflammatory markers and leptin resistance[
      • Hribal M.
      • Fiorentino T.
      • Sesti G.
      Role of C Reactive Protein (CRP) in leptin resistance.
      ].
      In conclusion, taking into account the individualized nature of the human gut microbiome and the known patterns of engraftment, we introduce a personalized approach for long-term weight maintenance by optimization and conservation of the gut microbiome during weight-loss.

      Funding sources

      This work was funded by grants from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project number 209933838 —Collaborative Research CenterCentre SFB1052 ’Obesity Mechanisms’, to I Shai (SFB-1052/B11); the Rosetrees trust (grant A2623); the Israel Ministry of Health (grant no. 87472511), Israel Ministry of Science and Technology (grant 3-13604 ); Israeli Science Foundation (grant 1733/ 18) and the California Walnuts Commission. None of the funders were involved in any stage of the design, conduct, or analysis of the study, and had no access to the study results before publication.

      Declaration of Competing Interest

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

      Acknowledgments

      We thank the DIRECT PLUS trial participants for their significant contributions. We thank Dr Ilan Shelef from Soroka University Medical Center for his contribution to the trial. We thank Dr Dov Brickner, Efrat Pupkin, Eyal Goshen, Avi Ben Shabat, and Benjamin Sarusi from the Nuclear Research Center for their valuable contributions. We thank Hodaya Hanya and Nirit Keren from the Center for Microbiome Research at Shamir Medical Center for their contributions. We thank the California Walnuts Commission, Wissotsky tea, Ltd. and Hinoman, Ltd. for the specific products provided during the trial. All authors read and approved the final manuscript, had full access to all the data in the study, and take responsibility for the integrity of the data and the accuracy of the data analysis. The investigators were responsible for the design and conduct of the study; for the collection, management, analysis, and interpretation of the data; for the preparation, review, and approval of the manuscript; and for the decision to submit the manuscript for publication. Ehud Rinott managed the data analysis. Dr Iris Shai is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

      References

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