Washed microbiota transplantation vs. manual fecal microbiota transplantation: clinical findings, animal studies and in vitro screening

Abstract

Fecal microbiota transplantation (FMT) by manual preparation has been applied to treat diseases for thousands of years. However, this method still endures safety risks and challenges the psychological endurance and acceptance of doctors, patients and donors. Population evidence showed the washed microbiota preparation with microfiltration based on an automatic purification system followed by repeated centrifugation plus suspension for three times significantly reduced FMT-related adverse events. This washing preparation makes delivering a precise dose of the enriched microbiota feasible, instead of using the weight of stool. Intraperitoneal injection in mice with the fecal microbiota supernatant obtained after repeated centrifugation plus suspension for three times induced less toxic reaction than that by the first centrifugation following the microfiltration. The toxic reactions that include death, the change in the level of peripheral white blood cells, and the proliferation of germinal center in secondary lymphoid follicles in spleen were noted. The metagenomic next-generation sequencing (NGS) indicated the increasing types and amount of viruses could be washed out during the washing process. Metabolomics analysis indicated metabolites with pro-inflammatory effects in the fecal microbiota supernatant such as leukotriene B4, corticosterone, and prostaglandin G2 could be removed by repeated washing. Near-infrared absorption spectroscopy could be served as a rapid detection method to control the quality of the washing-process. In conclusion, this study for the first time provides evidence linking clinical findings and animal experiments to support that washed microbiota transplantation (WMT) is safer, more precise and more quality-controllable than the crude FMT by manual.

Keywords: adverse event; fecal microbiota transplantation; infection; metabolomics; safety; spectroscopy; transplant; virus; washed microbiota transplantation.

Conflict of interest statement

Faming Zhang invented the concept of GenFMTer, TET and the related devices. Ting Zhang, Gaochen Lu, Zhe Zhao, Yafei Liu, Quan Shen, Pan Li, Yaoyao Chen, Haoran Yin, Huiquan Wang, Cicilia Marcella, Bota Cui, Lei Cheng, and Guozhong Ji declare that they have no competing interests. All procedures followed were in accordance with the ethical standards of the institutional review board of the Second Affiliated Hospital of Nanjing Medical University and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study. All institutional and national guidelines for the care and use of laboratory animals were followed.

Figures

Figure 1

Flow chart of the study

Figure 2

Evidence related to fecal microbiota preparation from human population to animal. (A–C) AEs related to manual and automatic preparation for fecal microbiota in patients. (D–F) Relationship between fecal weight and enriched microbiota from FMT donors. (H) Death time and rate after intraperitoneal injection of fecal supernatant in mice (i.p., intraperitoneal injection). Statistical comparisons are performed using chi-square test; *P < 0.05, **P < 0.01, ***P < 0.001. Correlation analysis was performed using Spearman correlation analysis. Data are presented as mean ± standard deviation (SD)

Figure 3

Changes of peripheral blood cells in the five groups of mice after 6 h of intraperitoneal injection of fecal microbiota supernatant. (A) Changes of WBC (n = 8 animals/group). (B) Changes of RBC (n = 8 animals/group). (C) Changes of PLT (n = 8 animals/group). Statistical comparisons are performed using one-way ANOVA; *P < 0.05, **P < 0.01, ***P < 0.001. Data are presented as mean ± SD

Figure 4

Changes of peripheral blood cells of mice after intraperitoneal injection of fecal microbiota supernatant. (A) Changes of WBC in the five groups of mice after 24 h (Supernatant 1, n = 3; other groups, n = 8). (B) Changes of RBC in the five groups of mice after 24 h (Supernatant 1, n = 3; other groups, n = 8). (C) Changes of PLT in the five groups of mice after 24 h (Supernatant 1, n = 3; other groups, n = 8). (D) Changes of WBC at 6 h and 24 h after injection with Supernatant 1 (Supernatant 1 6 h, n = 8; Supernatant 1 24 h, n = 3). (E) Changes in the percentage of NEUT at 6 h and 24 h after injection with Supernatant 1 (Supernatant 1 6 h, n = 8; Supernatant 1 24 h, n = 3). (F) Changes of WBC at 6 h and 24 h after injection with Supernatant 3 (n = 8/group). (H) Changes in the percentage of NEUT at 6 h and 24 h after injection with Supernatant 3 (n = 8/group). Statistical comparisons (A–C) are performed using one-way ANOVA; statistical comparisons (D–H) are performed using unpaired t-tests; *P < 0.05, **P < 0.01, ***P < 0.001. Data are presented as mean ± SD

Figure 5

HE staining of spleen in mice at 6 h after intraperitoneal injection with the fecal microbiota supernatant. (A) No proliferation of primary follicles was observed in the group of normal saline (×200). (B) The proliferation of secondary follicles was observed in the group of Supernatant 1 (×200). (C) No proliferation of primary follicles was observed in the group of Supernatant 3 (×200). (D) NEUT infiltration in the group of normal saline (×400). (E) NEUT infiltration in the group of Supernatant 1 (×400). (F) NEUT infiltration in the group of Supernatant 3 (×400) . White arrow noted: germinal center of secondary follicles; yellow arrow noted: NEUT infiltration

Figure 6

Differential screening of virus changing during the washing process. (A) Changes of virus types. (B) Changes of metagenomic NGS reads number. (C and D) Changes of the same virus in the washed fecal supernatant. (E) Top ten viruses with the most significant fold change

Figure 7

Top five viruses in each donor

Figure 8

Differential screening of metabolomics during the washing process. Group 1: Supernatant 1; Group 2: Supernatant 3. (A) A score map of the PCA model. (B) Cluster analysis of differential metabolites. Each row represented a differential metabolite with each column representing a sample, and the color from green to red corresponding expression from low to high. (C) A score map of the PLS-DA model. (D) Volcanic map of differential metabolites. The down-regulated differential metabolites were labeled green, the up-regulated ones were marked in red, and the undifferentiated metabolites were labeled as purple-grey. (E) The response ranking check chart of the PLS-DA model. (F) Bubble map of metabolic pathway enrichment analysis. The X-axis enrichment factor (RichFactor) is the value of differential metabolites annotated to the pathway divided by all identified metabolites annotated to the pathway. The larger value indicated the greater proportion of differential metabolites annotated in the pathway. The dot size represented the number of differential metabolites annotated to the pathway

Figure 9

Differential testing by near-infrared absorption (NIRS) spectroscopy. (A) Incident surface of Supernatant 1, 2, 3, 4, 5 and normal saline. (B) Exit surface of Supernatant 1, 2, 3, 4, 5 and normal saline. (C) The light intensity of fecal microbiota supernatant by near-infrared absorption spectroscopy. (D) The absorbance of fecal microbiota supernatant by near-infrared absorption spectroscopy. (E) Euclidean distance between the spectrum of the supernatant of different washing times and the spectrum of the normal saline. (F) Correlation coefficient between the spectrum of the supernatant of different washing times and the spectrum of the normal saline