Article
Biotechnology & Applied Microbiology
Rui Li, Mengjie Hou, Liying Yu, Wen Luo, Jie Kong, Renmei Yu, Ruihan Liu, Qian Li, Lisi Tan, Chunling Pan, Hongyan Wang
Summary: This study aimed to investigate the effects of salivary histatin 5 (Hst5) on Porphyromonas gingivalis (P. gingivalis) biofilms in vitro and in vivo and the possible mechanisms. The results showed that 25μg/mL Hst5 effectively inhibited biofilm formation and increased concentrations of Hst5 increased the inhibitive effect. Hst5 could regulate membrane function and metabolic processes in P. gingivalis, and RpoD and FeoB proteins might play important roles in this process. Moreover, 100μg/mL Hst5 inhibited periodontal inflammation and alveolar bone loss in rat periodontitis through its antibacterial and anti-inflammatory effects.
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
(2023)
Review
Immunology
Veronica Villalobos, Mauricio Garrido, Antonia Reyes, Christian Fernandez, Catalina Diaz, Vicente A. Torres, Pablo A. Gonzalez, Monica Caceres
Summary: Aging negatively affects gingival wound healing and alters cellular responses and tissue functions. Salivary antimicrobial peptides and pathogenic infections (such as P. gingivalis and HSV) are associated with periodontal disease progression and other pathologies.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Dentistry, Oral Surgery & Medicine
Anne Katrine Danielsen, Christian Damgaard, Laura Massarenti, Peter ostrup, Peter Riis Hansen, Palle Holmstrup, Claus H. Nielsen
Summary: This study found that B cells in patients with periodontitis have enhanced cytokine responses to periodontitis-associated bacteria. B cells from severe patients, compared to moderate patients, produced more cytokines after stimulation with Porphyromonas gingivalis. Additionally, the frequency of IL-10-producing B cells in severe patients correlated negatively with clinical attachment loss.
JOURNAL OF PERIODONTOLOGY
(2023)
Article
Immunology
Masahiro Hatasa, Yujin Ohsugi, Sayaka Katagiri, Sumiko Yoshida, Hiromi Niimi, Kazuki Morita, Yosuke Tsuchiya, Tsuyoshi Shimohira, Naoki Sasaki, Shogo Maekawa, Takahiko Shiba, Tomomitsu Hirota, Haruka Tohara, Hirokazu Takahashi, Hiroshi Nitta, Takanori Iwata
Summary: This study found that endotoxemia caused by Porphyromonas gingivalis may affect obesity by disrupting brown adipose tissue (BAT) function, particularly impacting lipolysis and endocrine functions of adipocytes.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2021)
Article
Immunology
Jian-Yu Gu, Zi-Bo Fu, Jia-Lu Chen, Yu-Jie Liu, Xian-Zi Cao, Ying Sun
Summary: Endotoxin tolerance induced by P. gingivalis LPS resulted in a reduced inflammatory response and enhanced wound healing abilities in macrophages. The tolerant macrophages showed an intermediate state between M1/M2 polarization, functioning as M2-like cells. The PTP1B-MEK1/2-STAT6 signaling pathway may play a role in the polarization of tolerant macrophages.
MICROBIAL PATHOGENESIS
(2022)
Article
Cell Biology
Camille Brewer, Tobias Lanz, Caryn R. Hale, Gregory D. Sepich-Poore, Cameron Martino, Austin D. Swafford, Thomas S. Carroll, Sarah Kongpachith, Lisa K. Blum, Serra E. Elliott, Nathalie E. Blachere, Salina Parveen, John Fak, Vicky Yao, Olga Troyanskaya, Mayu O. Frank, Michelle S. Bloom, Shaghayegh Jahanbani, Alejandro M. Gomez, Radhika Iyer, Nitya S. Ramadoss, Orr Sharpe, Sangeetha Chandrasekaran, Lindsay B. Kelmenson, Qian Wang, Heidi Wong, Holly L. Torres, Mark Wiesen, Dana T. Graves, Kevin D. Deane, V. Michael Holers, Rob Knight, Robert B. Darnell, William H. Robinson, Dana E. Orange
Summary: This study found that periodontal disease is more common in individuals with rheumatoid arthritis (RA) who have detectable anticitrullinated protein antibodies (ACPAs), suggesting a link between oral mucosal inflammation and RA pathogenesis. The researchers also discovered that RA patients with periodontal disease experienced repeated oral bacteremias associated with transcriptional signatures of specific monocyte subsets observed in inflamed RA synovia and blood during RA flares. The bacteremia was caused by citrullinated oral bacteria and resulted in activation of ACPA B cells, promoting affinity maturation and epitope spreading to citrullinated human antigens.
SCIENCE TRANSLATIONAL MEDICINE
(2023)
Article
Oncology
Zhi-chen Guo, Si-li Jing, Sakendeke Jumatai, Zhong-cheng Gong
Summary: The significance of Porphyromonas gingivalis in promoting tumour progression in the tumour microenvironment of oral squamous cell carcinoma (OSCC) was determined.
CANCER IMMUNOLOGY IMMUNOTHERAPY
(2023)
Article
Biochemistry & Molecular Biology
Yanjing Ou, Mingdong Yan, Guanglin Gao, Wenjie Wang, Qiaoqiao Lu, Jiang Chen
Summary: This study demonstrates the potential of orally administered cinnamaldehyde (CA) in controlling periodontitis by inhibiting bone resorption, anaerobic bacteria accumulation, and immunoinflammatory responses. CA also shows inhibitory effects on cytokine expression, cell senescence, and promotes osteogenic differentiation.
Article
Biochemistry & Molecular Biology
Yuri Song, Jin Chung, Grzegorz Wegrzyn
Summary: This study found that the relative abundance of Porphyromonas gingivalis (P. gingivalis) was significantly higher in periodontitis patients, especially in the elderly. The inflammatory response to P. gingivalis infection was greater in older individuals, and they also experienced more severe bone loss. These findings enhance understanding of the relationship between periodontal immunosenescence and inflammatory response in the elderly.
CURRENT ISSUES IN MOLECULAR BIOLOGY
(2023)
Article
Dentistry, Oral Surgery & Medicine
Wenqi Su, Jingwen Li, Lishan Jiang, Lang Lei, Houxuan Li
Summary: This study found that gingival fibroblasts undergo metabolic reprogramming and rely on aerobic glycolysis when infected with Porphyromonas gingivalis. The increased expression of HK2 and HK2-mediated glycolysis promote inflammatory responses in gingival tissues. Therefore, targeting glycolysis can inhibit the progression of periodontal inflammation.
Article
Dentistry, Oral Surgery & Medicine
Jia-lu Chen, Yue Tong, Qin Zhu, Lan-qing Gao, Ying Sun
Summary: The study revealed that P. gingivalis LPS promotes the formation of NETs, enhancing bactericidal activity of neutrophils. Additionally, through a series of signaling pathways, NETs contribute to the elimination of P. gingivalis.
ARCHIVES OF ORAL BIOLOGY
(2022)
Article
Dentistry, Oral Surgery & Medicine
Jia-lu Chen, Yue Tong, Qin Zhu, Lan-qing Gao, Ying Sun
Summary: The study found that Porphyromonas gingivalis LPS promoted the formation of NETs and increased extracellular DNA levels, enhancing the bactericidal activity of neutrophils. Additionally, P. gingivalis LPS also increased intracellular Ca2+ levels in neutrophils and induced the formation of NETs via a Ca2+-TPL2-MEK-ERK-PAD4 signaling pathway, contributing to the elimination of P. gingivalis.
ARCHIVES OF ORAL BIOLOGY
(2022)
Article
Cell Biology
Carolina Duarte, Chiaki Yamada, Christopher Garcia, Juliet Akkaoui, Anny Ho, Frank Nichols, Alexandru Movila
Summary: Emerging studies suggest that non-eukaryotic ceramide, specifically PGDHC produced by Porphyromonas gingivalis, can promote RANKL-mediated osteoclastogenesis through direct activation of intracellular CatB.
JOURNAL OF CELLULAR AND MOLECULAR MEDICINE
(2022)
Article
Immunology
Yue Tong, Yue Xin, Lanqing Fu, Jia Shi, Ying Sun
Summary: This study aimed to investigate the roles and mechanisms of NET formation in high glucose inflammatory microenvironment. The study found that Porphyromonas gingivalis (P. gingivalis) lipopolysaccharide (LPS) or high glucose could induce the formation of NETs, and this formation was enhanced in high glucose inflammatory microenvironment. Formation of NETs in high glucose inflammatory microenvironment was enhanced via oxidative stress, which further aggravated the subsequent inflammatory responses.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Erika Inoue, Shiyo Minatozaki, Yui Katsuta, Saori Nonaka, Hiroshi Nakanishi
Summary: Recently, the potential therapeutic effects of antibacterial peptides in Alzheimer's disease have been suggested. This study investigated whether human beta-defensins (hBDs) can suppress Pg LPS-induced oxidative and inflammatory responses in microglia. The results showed that hBD3 significantly inhibited the production of nitric oxide and interleukin-6 (IL-6) in mouse and human microglial cells. Furthermore, hBD3 suppressed the translocation of p65 nuclear and inhibited the enzymatic activities of cathepsins B and L, which are necessary for NF-kappa B activation. This study suggests that hBD3 can suppress oxidative and inflammatory responses in microglia by inhibiting cathepsins B and L.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemical Research Methods
Zongyang Du, Zhenling Peng, Jianyi Yang
Summary: The study proposed 19 metrics to measure the accuracy of protein distance prediction, with some metrics showing high correlation with model accuracy. Experimental results showed that the metrics largely coincided with the official version when ranking distance prediction groups in CASP14. These findings suggest that the proposed metrics are effective in measuring distance prediction.
Article
Biochemical Research Methods
Elijah A. MacCarthy, Chengxin Zhang, Yang Zhang, B. K. C. Dukka
Summary: The GPU-accelerated I-TASSER (GPU-I-TASSER) is a tool for fast and accurate protein structure prediction, achieving a 10x speedup on average compared to the CPU version while maintaining comparable structure prediction accuracy.
Article
Biochemical Research Methods
Yajun Dai, Yang Li, Liping Wang, Zhenling Peng, Jianyi Yang
Summary: In this study, the protein-ligand interactions in monomeric and quaternary structures were compared using molecular docking experiments and binding free energy estimations. The results showed that ligands in quaternary structures can simultaneously interact with multiple protein chains, and quaternary structures have lower binding free energy and more accurate ligand conformations compared to monomeric structures. Therefore, it is recommended to use quaternary structures in future studies on protein-ligand interactions.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Saisai Sun, Jianyi Yang, Zhaolei Zhang
Summary: RNA molecules can fold into complex three-dimensional structures and interact with small molecule ligands. Researchers have established a database of RNA secondary structural motifs and bound small molecule ligands. They also developed a computational pipeline to predict RNA secondary structures and search for similar motifs and interacting small molecules. The server was successfully used to identify potential matches for a specific RNA sequence.
Article
Multidisciplinary Sciences
Syed Nabeel-Shah, Hyunmin Lee, Nujhat Ahmed, Giovanni L. Burke, Shaghayegh Farhangmehr, Kanwal Ashraf, Shuye Pu, Ulrich Braunschweig, Guoqing Zhong, Hong Wei, Hua Tang, Jianyi Yang, Edyta Marcon, Benjamin J. Blencowe, Zhaolei Zhang, Jack F. Greenblatt
Summary: The imbalance in immune response observed in SARS-CoV-2 infected patients may be due to the altered interaction between the nucleocapsid protein (N protein) and stress granule resident proteins, which in turn affects the stress response of host cells.
Article
Clinical Neurology
Panagiotis Kratimenos, Abhya Vij, Robinson Vidva, Ioannis Koutroulis, Maria Delivoria-Papadopoulos, Vittorio Gallo, Aaron Sathyanesan
Summary: The study identified critical molecular events in excitotoxicity-induced apoptosis in the cerebral cortex of newborn piglets using experimental and computational methods. The computational model of the Ca2+/CaM-Src-kinase signaling cascade revealed new dynamics of components leading to neuronal injury, providing a framework for drug efficacy studies in neonatal brain injury.
JOURNAL OF NEURODEVELOPMENTAL DISORDERS
(2022)
Article
Multidisciplinary Sciences
Xingjian Chen, Zifan Zhu, Weitong Zhang, Yuchen Wang, Fuzhou Wang, Jianyi Yang, Ka-Chun Wong
Summary: Predicting human diseases from microbiome data is important in medical applications. Existing methods often overlook the abundance profiles of known and unknown microbial organisms, as well as the taxonomic relationships among them, resulting in information loss. To address these issues, we developed a comprehensive machine learning framework called MetaDR that combines deep learning and various information sources to predict human diseases.
Article
Biochemical Research Methods
Robin Pearce, Yang Li, Gilbert S. Omenn, Yang Zhang
Summary: We developed an open-source program called DeepFold, which combines spatial restraints predicted by multi-task deep residual neural networks with a knowledge-based energy function to guide folding simulations of proteins lacking sequence and/or structure homologs. Large-scale benchmark tests showed that DeepFold outperforms classical folding approaches and other deep learning methods in creating full-length models with higher accuracy. Particularly, DeepFold achieved significantly higher average TM-scores than trRosetta and DMPfold for the most challenging targets with very few homologous sequences. Furthermore, the folding simulations of DeepFold were 262 times faster than traditional fragment assembly simulations. These results demonstrate the power of accurately predicted deep learning potentials to improve both the accuracy and speed of ab initio protein structure prediction.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Zhenling Peng, Wenkai Wang, Renmin Han, Fa Zhang, Jianyi Yang
Summary: This article reviews the progress of deep learning-based protein structure prediction methods in the past two years, analyzes the advantages and disadvantages of the two-step and end-to-end approaches, emphasizes the value of developing both approaches, and points out the challenges in function-oriented protein structure prediction.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2022)
Article
Environmental Sciences
Carlie A. LaLone, Donovan J. Blatz, Marissa A. Jensen, Sara M. F. Vliet, Sally Mayasich, Kali Z. Mattingly, Thomas R. Transue, Wilson Melendez, Audrey Wilkinson, Cody W. Simmons, Carla Ng, Chengxin Zhang, Yang Zhang
Summary: Computational screening using molecular modeling approaches is widely used in drug discovery. This study aimed to develop an analysis pipeline for cross-species extrapolation in chemical safety evaluation. The SeqAPASS tool and ITASSER-generated protein models were used for sequence and structural comparisons, providing evidence of conservation for toxicity extrapolation. The pipeline facilitates rapid and efficient toxicological assessments among species with limited or no existing toxicity data.
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2023)
Article
Biochemistry & Molecular Biology
Chengxin Zhang, Yang Zhang, Anna Marie Pyle
Summary: The researchers have developed a hierarchical pipeline called rMSA for sensitive search and accurate alignment of RNA homologs for a target RNA. rMSA significantly outperforms existing MSA generation methods in terms of rSS and long-range contact prediction, with approximately 20% and 5% higher F1-scores, respectively.
JOURNAL OF MOLECULAR BIOLOGY
(2023)
Article
Biochemical Research Methods
Yi-Heng Zhu, Chengxin Zhang, Dong-Jun Yu, Yang Zhang
Summary: Accurate identification of protein function is crucial for understanding life mechanisms and developing new drugs. This study presents a novel deep-learning method, ATGO, that uses pre-trained language models and a triplet neural-network architecture to predict Gene Ontology attributes of proteins from their sequences. Experimental results show that ATGO significantly outperforms other state-of-the-art approaches in predicting molecular function, biological process, and cellular component. The utilization of pre-trained transformer language models and the use of a triplet network enhance the accuracy of the predicted models.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Zhenling Peng, Wenkai Wang, Hong Wei, Xiaoge Li, Jianyi Yang
Summary: We present the results of our monomer and multimer structure prediction methods in CASP15. By utilizing complementary sequence databases and advanced database searching algorithms, we generated high-quality multiple sequence alignments (MSAs) and selected top MSAs for structure prediction. Our methods, named Yang-Server and Yang-Multimer, ranked first and fourth for monomer and multimer structure prediction, respectively. The predicted structure models by Yang-Server showed an average TM-score of 0.876 for 94 monomers, compared to 0.798 by the default AlphaFold2, while the predicted structure models by Yang-Multimer showed an average DockQ score of 0.464 for 42 multimers, compared to 0.389 by the default AlphaFold-Multimer. Factors such as improved MSAs, iterated modeling, and interplay between monomer and multimer structure prediction contributed to the improvement.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Wenkai Wang, Zhenling Peng, Jianyi Yang
Summary: trRosettaX-Single is an automated algorithm for single-sequence protein structure prediction that predicts two-dimensional geometry and reconstructs three-dimensional structures using a multi-scale network and knowledge distillation. It outperforms AlphaFold2 and RoseTTAFold on orphan proteins and works well on human-designed proteins.
NATURE COMPUTATIONAL SCIENCE
(2022)
Article
Geriatrics & Gerontology
C. Zhou, S. Yang, Y. Zhang, Q. Wu, Z. Ye, M. Liu, P. He, R. Li, C. Liu, Jing Nie, Xianhui Qin
Summary: This study found that consuming a greater variety and appropriate quantity of proteins from different food sources is significantly associated with a lower risk of mortality in Chinese adults and older adults.
JOURNAL OF NUTRITION HEALTH & AGING
(2022)