Multimodal Approach to Assessment of Fecal Microbiota Donors based on Three Complementary Methods

Abstract

<jats:p>Methods of stool assessment are mostly focused on next-generation sequencing (NGS) or classical culturing, but only rarely both. We conducted a series of experiments using a multi-method approach to trace the stability of gut microbiota in various donors over time, to find the best method for the proper selection of fecal donors and to find “super-donor” indicators. Ten consecutive stools donated by each of three donors were used for the experiments (30 stools in total). The experiments assessed bacterial viability measured by flow cytometry, stool culturing on different media and in various conditions, and NGS (90 samples in total). There were no statistically significant differences between live and dead cell numbers; however, we found a group of cells classified as not-dead-not-alive, which may be possibly important in selection of “good” donors. Donor C, being a regular stool donor, was characterized by the largest number of cultivable species (64). Cultivable core microbiota (shared by all donors) was composed of only 16 species. ANCOM analysis of NGS data highlighted particular genera to be more abundant in one donor vs. the others. There was a correlation between the not-dead-not-alive group found in flow cytometry and Anaeroplasma found by NGS, and we could distinguish a regular stool donor from the others. In this work, we showed that combining various methods of microbiota assessment gives more information than each method separately.</jats:p>

Fresh Versus Frozen Stool for Fecal Microbiota Transplantation—Assessment by Multimethod Approach Combining Culturing, Flow Cytometry, and Next-Generation Sequencing

“…Samples from donor C appeared to react more consistently to freezing than samples from the other two donors. Figure 6 shows that cell count distributions of frozen samples from donors A and B show much more variability than those from donor C. This could be explained by the more stable composition of donors' C microbiota over the sampling time, as was proved previously (Bilinski et al, 2020).…”

“…The samples were analyzed on an LSR Fortessa flow cytometer (Becton Dickinson, New Jersey, United States) with FACS Diva v8 software (Becton Dickinson). The gating strategy was as described in our first work (Bilinski et al, 2020). Three main cell populations were observed-alive, dead, and unknown (probably alive, probably dead) with a special not-alive-not-dead group of cells (SYTO9 − PI − ).…”

“…Results obtained for fresh samples have already been analyzed and described in our previous work (Bilinski et al, 2020).…”

“…The research hypothesis was that such preservation protocol (freezed whole stool, then thawed and processed) is equipotent to classical fresh FMT preparation. For testing this hypothesis three complementary methods were applied, including: (i) culturing in aerobic and anaerobic conditions, (ii) measuring viability by flow cytometric method, and (iiii) next-generation sequencing (Bilinski et al, 2020). We postulated that the stool has protective properties for bacteria itself, and its processing before freezing is not obligatory, since anaerobic conditions inside the feces and low hydrated matter content may be a natural cryo-and viabilitypreservative.…”

Evaluating Bacterial Viability in Faecal Microbiota Transplantation: A Comparative Analysis of In Vitro Cultivation and Membrane Integrity Methods

“…Fluorescent staining for membrane integrity, typically performed with flow cytometry, is a commonly adopted culture-independent method (35)(36)(37). Nevertheless, its effectiveness can vary across different bacterial taxa, and its application to the heterogeneous matrix of stool presents additional challenges (20,21,29,32) Given these complexities, we compared the two prevalent methods-cultivation and membrane integrity assessment-for their accuracy and clinical applicability. Our adaptation of the LIVE/DEAD™ BacLight™ Bacterial Viability Kit for stool analysis demonstrated the potential to discriminate between microbial DNA signals and background noise effectively.…”