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Updated: May 29, 2026

Purification of a High Molecular Mass Protein in Streptococcus mutans
Published on: September 14, 2019
Establishment of Streptococcus mutans in infants induces decrease in the proportion of salivary α-haemolytic
Mamoru Kawaguchi1, Tomonori Hoshino, Takashi Ooshima
1Department of Pediatric Dentistry, Osaka University Graduate School of Dentistry, Osaka, Japan.
A decrease in alpha-hemolytic bacteria in infant saliva can predict Streptococcus mutans establishment. This finding helps assess caries risk before infection, guiding early dental care for infants.
Area of Science:
- Oral microbiology
- Pediatric dentistry
- Infectious disease epidemiology
Background:
- Assessing caries risk in infants is crucial for pediatric dentists.
- Current indicators like Streptococcus mutans levels are insufficient for pre-infected infants.
- A reliable indicator for early S. mutans establishment is needed.
Purpose of the Study:
- To identify a reliable indicator for the establishment of Streptococcus mutans in infants.
- To evaluate changes in oral microbiota associated with S. mutans colonization.
- To establish a method for predicting caries risk before S. mutans infection.
Main Methods:
- Longitudinal monitoring of oral microbiota in two pre-dentate infants over three years.
- Cross-sectional study of 40 nursery school children.
- Saliva cultivation on selective and nonselective agar, with isolate identification.
Main Results:
- Longitudinal studies indicated a decrease in alpha-hemolytic bacteria with S. mutans establishment.
- Cross-sectional data confirmed this, showing S. mutans colonization (10(3) CFU/mL) correlates with <55% alpha-hemolytic bacteria.
- A reduced proportion of alpha-hemolytic bacteria predicts S. mutans presence.
Conclusions:
- A decrease in salivary alpha-hemolytic bacteria is a viable indicator for predicting S. mutans establishment in infants.
- This indicator can be used to assess dental caries risk before S. mutans infection.
- Findings support proactive dental care planning for infants based on microbiota analysis.
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