Related Experiment Video
Updated: Jan 30, 2026

Author Spotlight: Development and Evaluation of a Compound Acne Rodent Model Using C. acnes and Oleic Acid
Published on: November 1, 2024
In silico prediction and qPCR validation of novel sRNAs in Propionibacterium acnes KPA171202
Praveen P Balgir1, Shobha R Dhiman2, Puneet Kaur1
1Department of Biotechnology, Punjabi University, Patiala, Punjab 147 002, India.
Abstract:
Propionibacterium acnes is an anaerobic, Gram-positive, opportunistic pathogen known to be involved in a wide variety of diseases ranging from mild acne to prostate cancer. Bacterial small non-coding RNAs are novel regulators of gene expression and are known to be involved in, virulence, pathogenesis, stress tolerance and adaptation to environmental changes in bacteria. The present study was undertaken keeping in view the lack of predicted sRNAs of P. acnes KPA171202 in databases. This report represents the first attempt to identify sRNAs in P. acnes KPA171202. A total of eight potential candidate sRNAs were predicted using SIPHT, one was found to have a Rfam homolog and seven were novel. Out of these seven predicted sRNAs, five were validated by reverse transcriptase-polymerase chain reaction (RT-PCR) and sequencing. The expression of these sRNAs was quantified in different growth phases by qPCR (quantitative PCR). They were found to be expressed in both exponential and stationary stages of growth but with maximum expression in stationary phase which points to a regulatory role for them. Further investigation of their targets and regulatory functions is in progress.
Insights
This study identified novel small non-coding RNAs (sRNAs) in Propionibacterium acnes, a pathogen linked to acne and cancer. Five new sRNAs were validated, showing peak expression during the stationary growth phase, suggesting a regulatory role.
Area of Science:
- Microbiology
- Molecular Biology
- Genomics
Background:
- Propionibacterium acnes is an opportunistic pathogen implicated in diseases from acne to prostate cancer.
- Bacterial small non-coding RNAs (sRNAs) are crucial regulators of gene expression, influencing virulence and adaptation.
- No sRNAs were previously predicted for P. acnes KPA171202 in existing databases.
Purpose of the Study:
- To identify and characterize small non-coding RNAs (sRNAs) in Propionibacterium acnes KPA171202.
- To validate predicted sRNAs and investigate their expression patterns during bacterial growth.
- To lay the groundwork for understanding sRNA-mediated gene regulation in P. acnes.
Main Methods:
- Bioinformatic prediction of sRNAs using SIPHT.
- Homology searches against Rfam database.
- Validation of candidate sRNAs via reverse transcriptase-polymerase chain reaction (RT-PCR) and sequencing.
- Quantitative PCR (qPCR) to determine sRNA expression levels across different growth phases.
Main Results:
- Eight potential candidate sRNAs were predicted in P. acnes KPA171202.
- One predicted sRNA had a known homolog, while seven were identified as novel.
- Five novel sRNAs were successfully validated through RT-PCR and sequencing.
- Validated sRNAs were expressed in both exponential and stationary growth phases, with highest expression in the stationary phase.
Conclusions:
- This study represents the first identification of sRNAs in P. acnes KPA171202.
- The validated sRNAs are expressed differentially across growth phases, indicating a potential regulatory role.
- Further research is warranted to elucidate the specific targets and regulatory functions of these novel sRNAs in P. acnes pathogenesis.
Related Concept Videos
Reliability and Validity
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Data Validation
Key parameters for method validation include:
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting...

