Refining microbial biomarker identification in rumen microbiome studies: a viability PCR-based approach

Area of Science:

• Rumen microbiology
• Molecular biology
• Animal science

Background:

• The rumen microbiome is crucial for host performance, but conventional DNA sequencing methods can misrepresent microbial populations by including non-viable cells.
• Distinguishing between viable and non-viable microbes is essential for accurate assessment of rumen microbial dynamics and function.

Purpose of the Study:

• To determine optimal conditions for applying propidium monoazide (PMA) in quantitative PCR (qPCR) for viability assessment in rumen cultures.
• To evaluate the impact of PMA treatment on the rumen microbial community structure and function using 16S rRNA gene sequencing in in vitro experiments.

Main Methods:

• Optimized PMA treatment conditions included a fivefold inoculum dilution, 100 µM PMA concentration, 30 min dark incubation, and 20 min light exposure.
• Quantitative PCR (qPCR) was used to validate PMA effectiveness by observing reduced DNA amplification in heat-treated (non-viable) samples.
• 16S rRNA gene sequencing was employed to analyze the effects of PMA treatment on the in vitro rumen microbial community composition and functional profiles.

Main Results:

• PMA treatment successfully inhibited DNA amplification from non-viable cells, as validated by reduced abundance in heat-treated samples.
• PMA application altered the rumen microbial community, decreasing bacterial evenness and shifting the abundance of key bacterial and archaeal taxa, including increases in Ruminobacter and Succinivibrio.
• The observed shifts in microbial taxa under PMA treatment correlated with findings from RNA-based studies, indicating its ability to capture active microbial dynamics.

Conclusions:

• Established PMA treatment conditions provide a reliable method for viability assessment in in vitro rumen experiments.
• PMA-based viability PCR (v-PCR) offers a more accurate and potentially cost-effective alternative to RNA-based methods for analyzing rumen microbial communities.
• This approach facilitates the identification of viability-associated microbial biomarkers, enhancing our understanding of rumen microbial ecology and its impact on host performance.