A targeted light-activated therapy may treat periodontitis without disrupting the beneficial bacteria that help maintain oral health.
Treating periodontitis presents a difficult balance: harmful bacteria need to be removed without wiping out the beneficial microbes that help maintain a healthy mouth.
Researchers at Nagoya University in Japan have developed an experimental approach designed to do exactly that by selectively eliminating a major disease-causing bacterium while leaving much of the surrounding microbial community intact. The findings were published in the Journal of Translational Medicine.
A healthy mouth depends on a diverse and balanced population of microorganisms. One bacterium, Porphyromonas gingivalis (P. gingivalis), acts as a keystone pathogen that can promote inflammation and disturb that microbial balance. Over time, the resulting damage can affect the bone supporting the teeth and contribute to tooth loss.
“Current treatments for periodontitis, including antibiotics and antimicrobial photodynamic therapy (aPDT), eliminate both pathogenic and beneficial oral bacteria,” said Kazuhide Sato, one of the corresponding authors and a lecturer at Nagoya University. “These approaches often disrupt the entire oral microbial ecosystem and can also release lipopolysaccharide (LPS), an endotoxin that may exacerbate inflammation.”
Cancer technology enables targeted bacterial removal
Researchers at Nagoya University Graduate School of Medicine adapted near-infrared photoimmunotherapy, an approach originally created to treat cancer. The technique relies on an antibody-dye compound that attaches to a chosen target and becomes active when illuminated with near-infrared light.
The group included first author Hiroshi Maruyama, Professor Hideharu Hibi, and corresponding authors Sato and Kiyoshi Sakai.
For the periodontal treatment, the researchers used IgY, an antibody collected from the egg yolks of hens immunized against P. gingivalis. IgY can be manufactured inexpensively and in large quantities, making it potentially useful for clinical applications.
They named the approach near-infrared photo-antibacterial targeting therapy (NIR-PAT²). To determine whether it could remove P. gingivalis without broadly disturbing the oral environment, they tested it in human cell cultures and mouse models and compared its effects with conventional treatments.
Treatment spared healthy cells and microbes
In cell culture experiments, the antibody-dye compound attached selectively to P. gingivalis while leaving other bacteria and healthy human gum cells unaffected. Once activated with near-infrared light, the dye concentrated on the targeted bacteria, damaged their outer membranes, and eliminated them.
Microscopy revealed small holes in the membranes of treated P. gingivalis, although the bacteria largely retained their overall physical structure. By comparison, aPDT caused complete destruction of the bacterial cells.
Tests also showed that NIR-PAT² did not damage human gum cells. In contrast, aPDT caused cellular injury and slowed healing.
The distinction continued in mice with periodontitis. Animals receiving the targeted treatment showed significantly less alveolar bone loss, which affects the bone supporting the teeth. Analysis of their saliva also indicated that the therapy removed pathogenic P. gingivalis while preserving beneficial Streptococcus populations.
Standard antibiotics and aPDT produced a less selective effect, eliminating both beneficial and harmful bacteria and further disturbing the oral microbial community.
“Results demonstrated that, unlike antibiotics or standard light therapy, this approach selectively removes the primary pathogenic species while preserving the remainder of the oral bacterial community,” Sato said.
AI could identify additional bacterial targets
Periodontitis does not result from a single bacterial species, however, so eliminating P. gingivalis alone may not provide a complete solution. The researchers plan to use artificial intelligence (AI) to examine publicly available oral microbiome data, identify other important bacteria, and clarify how different species interact with one another.
Those analyses could guide the development of more precisely targeted treatments that address additional microbial contributors to periodontal disease.
Periodontitis has also been associated with conditions including rheumatoid arthritis and diabetes. The researchers believe their AI-driven approach could eventually help identify which patients are most likely to benefit from particular targeted treatments.
Reference: “Near infrared photo-bacterialflora modulation technology realized controlling periodontitis: modulation of disease-associated dysbiosis in oral microbiota using near infrared photo-antibacterial targeting therapy (NIR-PAT2)” by Hiroshi Maruyama, Kazuhide Sato, Kiyoshi Sakai, Hirotoshi Yasui, Ryu Okada, Li Xinheng, Koji Umeda, Shofiqur Rahman, Van Sa Nguyen and Hideharu Hibi, 2 June 2026, Journal of Translational Medicine.
DOI: 10.1186/s12967-026-08336-2
Funding: JSPS KAKENHI grant 19K1919, 21K10067, 18K15923, 21K07217,25K03451, 25K22916. Program for Developing Next-generation Researchers (Japan Science and Technology Agency). Research Grant from The Chemo-Sero-Therapeutic Research Institute. Suzuki-kenzo scholarship. TERUMO Science Foundation. The Hori Science & Arts Foundation. CREST (JPMJCR19H2, JST). FOREST-Souhatsu (JPMJFR2017, JST). AMED Seeds A (26ym0126807j0005, A-226, AMED). GAP-FUND Tongali (JST).
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