32 results on '"Huilin Ma"'
Search Results
2. QSP‐IO: A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno‐Oncology Applications
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Richard J. Sové, Mohammad Jafarnejad, Chen Zhao, Hanwen Wang, Huilin Ma, and Aleksander S. Popel
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Therapeutics. Pharmacology ,RM1-950 - Abstract
Immunotherapy has shown great potential in the treatment of cancer; however, only a fraction of patients respond to treatment, and many experience autoimmune‐related side effects. The pharmaceutical industry has relied on mathematical models to study the behavior of candidate drugs and more recently, complex, whole‐body, quantitative systems pharmacology (QSP) models have become increasingly popular for discovery and development. QSP modeling has the potential to discover novel predictive biomarkers as well as test the efficacy of treatment plans and combination therapies through virtual clinical trials. In this work, we present a QSP modeling platform for immuno‐oncology (IO) that incorporates detailed mechanisms for important immune interactions. This modular platform allows for the construction of QSP models of IO with varying degrees of complexity based on the research questions. Finally, we demonstrate the use of the platform through two example applications of immune checkpoint therapy.
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- 2020
- Full Text
- View/download PDF
3. Hyperspectral Feature Selection for SOM Prediction Using Deep Reinforcement Learning and Multiple Subset Evaluation Strategies
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Linya Zhao, Kun Tan, Xue Wang, Jianwei Ding, Zhaoxian Liu, Huilin Ma, and Bo Han
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deep reinforcement learning ,actor-critic network ,feature selection ,hyperspectral image regression ,SOM prediction ,Science - Abstract
It has been widely certified that hyperspectral images can be effectively used to monitor soil organic matter (SOM). Though numerous bands reveal more details in spectral features, information redundancy and noise interference also come accordingly. Due to the fact that, nowadays, prevailing dimensionality reduction methods targeted to hyperspectral images fail to make effective band selections, it is hard to capture the spectral features of ground objects quickly and accurately. In this paper, to solve the inefficiency and instability of hyperspectral feature selection, we proposed a feature selection framework named reinforcement learning for feature selection in hyperspectral regression (RLFSR). Specifically, the Markov Decision Process (MDP) was used to simulate the hyperspectral band selection process, and reinforcement learning agents were introduced to improve model performance. Then two spectral feature evaluation methods were introduced to find internal relationships between the hyperspectral features and thus comprehensively evaluate all hyperspectral bands aimed at the soil. The feature selection methods—RLFSR-Net and RLFSR-Cv—were based on pre-trained deep networks and cross-validation, respectively, and achieved excellent results on airborne hyperspectral images from Yitong Manchu Autonomous County in China. The feature subsets achieved the highest accuracy for most inversion models, with inversion R2 values of 0.7506 and 0.7518, respectively. The two proposed methods showed slight differences in spectral feature extraction preferences and hyperspectral feature selection flexibilities in deep reinforcement learning. The experiments showed that the proposed RLFSR framework could better capture the spectral characteristics of SOM than the existing methods.
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- 2022
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4. Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer
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Leisha A Emens, Huilin Ma, Hanwen Wang, Richard J Sové, and Aleksander S Popel
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Published
- 2021
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5. Combination therapy with T cell engager and PD-L1 blockade enhances the antitumor potency of T cells as predicted by a QSP model
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Huilin Ma, Hanwen Wang, Richard J Sové, Craig Giragossian, and Aleksander S Popel
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Background T cells have been recognized as core effectors for cancer immunotherapy. How to restore the anti-tumor ability of suppressed T cells or improve the lethality of cytotoxic T cells has become the main focus in immunotherapy. Bispecific antibodies, especially bispecific T cell engagers (TCEs), have shown their unique ability to enhance the patient’s immune response to tumors by stimulating T cell activation and cytokine production in an MHC-independent manner. Antibodies targeting the checkpoint inhibitory molecules such as programmed cell death protein 1 (PD-1), PD-ligand 1 (PD-L1) and cytotoxic lymphocyte activated antigen 4 are able to restore the cytotoxic effect of immune suppressed T cells and have also shown durable responses in patients with malignancies. However, both types have their own limitations in treating certain cancers. Preclinical and clinical results have emphasized the potential of combining these two antibodies to improve tumor response and patients’ survival. However, the selection and evaluation of combination partners clinically is a costly endeavor. In addition, despite advances made in immunotherapy, there are subsets of patients who are non-responders, and reliable biomarkers for different immunotherapies are urgently needed to improve the ability to prospectively predict patients’ response and improve clinical study design. Therefore, mathematical and computational models are essential to optimize patient benefit, and guide combination approaches with lower cost and in a faster manner.Method In this study, we continued to extend the quantitative systems pharmacology (QSP) model we developed for a bispecific TCE to explore efficacy of combination therapy with an anti-PD-L1 monoclonal antibody in patients with colorectal cancer.Results Patient-specific response to TCE monotherapy, anti-PD-L1 monotherapy and the combination therapy were predicted using this model according to each patient’s individual characteristics.Conclusions Individual biomarkers for TCE monotherapy, anti-PD-L1 monotherapy and their combination have been determined based on the QSP model. Best treatment options for specific patients could be suggested based on their own characteristics to improve clinical trial efficiency. The model can be further used to assess plausible combination strategies for different TCEs and immune checkpoint inhibitors in different types of cancer.
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- 2020
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6. Multitask Learning with Local Attention for Tibetan Speech Recognition
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Hui Wang, Fei Gao, Yue Zhao, Li Yang, Jianjian Yue, and Huilin Ma
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Electronic computers. Computer science ,QA75.5-76.95 - Abstract
In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model.
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- 2020
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7. Dynamic Frequency Allocation Based on Evolutionary Strategy.
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Wen Li, Xiangming Liu, Huilin Ma, and Bing Ma
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- 2023
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8. Hyperspectral Feature Selection for SOM Prediction Using Deep Reinforcement Learning and Multiple Subset Evaluation Strategies.
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Linya Zhao, Kun Tan, Xue Wang 0008, Jianwei Ding, Zhaoxian Liu, Huilin Ma, and Bo Han
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- 2023
- Full Text
- View/download PDF
9. Discovery and engineering of Tsp2Cas9 for genome editing
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Huilin Mao, Yuwen Tian, Ziwen Wang, Jingtong Liu, Jingjing Wei, Yao Wang, Chen Tao, Miaomiao Li, Shengzhou Wang, Li Shen, Junnan Tang, Rui Wang, Song Gao, Feng Lan, and Yongming Wang
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Cytology ,QH573-671 - Published
- 2024
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10. Multitask Learning with Local Attention for Tibetan Speech Recognition
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Li Yang, Yue Zhao, Hui Wang, Huilin Ma, Jianjian Yue, and Fei Gao
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Multidisciplinary ,Article Subject ,General Computer Science ,Computer science ,Speech recognition ,Multi-task learning ,Context (language use) ,QA75.5-76.95 ,02 engineering and technology ,Speaker recognition ,030507 speech-language pathology & audiology ,03 medical and health sciences ,Identification (information) ,Electronic computers. Computer science ,0202 electrical engineering, electronic engineering, information engineering ,Feature (machine learning) ,020201 artificial intelligence & image processing ,0305 other medical science - Abstract
In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model.
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- 2020
11. End-to-End Speech Synthesis Method for Lhasa-Tibetan Multi-speaker
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Xiaona Xu, Wanyue Ma, Zhengjia Dan, Huilin Ma, Tianyi Liu, and Yue Zhao
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- 2022
12. QSP‐IO: A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno‐Oncology Applications
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Chen Zhao, Aleksander S. Popel, Mohammad Jafarnejad, Huilin Ma, Richard J. Sové, and Hanwen Wang
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Drug Industry ,Computer science ,Systems biology ,Machine learning ,computer.software_genre ,Medical Oncology ,Models, Biological ,Drug Development ,Allergy and Immunology ,Neoplasms ,Drug Discovery ,Tutorial ,Biomarkers, Tumor ,Tumor Microenvironment ,Humans ,Pharmacology (medical) ,Computer Simulation ,Predictive biomarker ,Pharmacology ,business.industry ,lcsh:RM1-950 ,Models, Immunological ,Models, Theoretical ,Immune Checkpoint Proteins ,Multiscale modeling ,Toolbox ,Treatment Outcome ,lcsh:Therapeutics. Pharmacology ,Evaluation Studies as Topic ,Modeling and Simulation ,Research questions ,Artificial intelligence ,Immunotherapy ,business ,computer ,Systems pharmacology - Abstract
Immunotherapy has shown great potential in the treatment of cancer; however, only a fraction of patients respond to treatment, and many experience autoimmune‐related side effects. The pharmaceutical industry has relied on mathematical models to study the behavior of candidate drugs and more recently, complex, whole‐body, quantitative systems pharmacology (QSP) models have become increasingly popular for discovery and development. QSP modeling has the potential to discover novel predictive biomarkers as well as test the efficacy of treatment plans and combination therapies through virtual clinical trials. In this work, we present a QSP modeling platform for immuno‐oncology (IO) that incorporates detailed mechanisms for important immune interactions. This modular platform allows for the construction of QSP models of IO with varying degrees of complexity based on the research questions. Finally, we demonstrate the use of the platform through two example applications of immune checkpoint therapy.
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- 2020
13. Application oriented bioaugmentation processes: Mechanism, performance improvement and scale-up
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Chenggong Zhang, Yue Wang, Yingxin Zhao, Min Ji, Kaichao Yang, and Huilin Ma
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Bioaugmentation ,Treatment system ,Environmental Engineering ,Renewable Energy, Sustainability and the Environment ,Computer science ,Mechanism (biology) ,Microbiota ,Pilot scale ,Bioengineering ,General Medicine ,Water Purification ,Bioreactors ,Biofilms ,SCALE-UP ,Optimization methods ,Sewage treatment ,Biochemical engineering ,Performance improvement ,Waste Management and Disposal - Abstract
Bioaugmentation is an optimization method with great potential to improve the treatment effect by introducing specific strains into the biological treatment system. In this study, a comprehensive review of the mechanism of bioaugmentation from the aspect of microbial community structure, the optimization methods facilitating application as well as feasible approaches of scale-up application has been provided. The different contribution of indigenous and exogenous strains was critically analyzed, the relationship between microbial community variation and system performance was clarified. Operation regulation and immobilization technologies are effective methods to deal with the possible failure of bioaugmentation. The gradual expansion from lab-scale, pilot scale to full-scale, the transformation and upgrading of wastewater treatment plants through the combination of direct dosing and biofilm, and the application of side-stream reactors are feasible ways to realize the full-scale application. The future challenges and prospects in this field were also proposed.
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- 2021
14. Comparison of therapeutic effects between big-bubble deep anterior lamellar keratoplasty and penetrating keratoplasty for medically unresponsive Acanthamoeba keratitis
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Xiaolin Qi, Huilin Mao, Jinhui Liu, Yanling Dong, Man Du, Ting Liu, Ting Zhang, Xiuhai Lu, and Hua Gao
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Acanthamoeba keratitis ,Big-bubble deep anterior lamellar keratoplasty ,Penetrating keratoplasty ,Postoperative recurrence ,Immune rejection ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Purpose To compare the outcomes of big-bubble deep anterior lamellar keratoplasty (BB-DALK) and penetrating keratoplasty (PKP) in the management of medically unresponsive Acanthamoeba keratitis (AK). Methods This retrospective study included 27 eyes of BB-DALK and 24 eyes of PKP from a tertiary ophthalmology care centre. Glucocorticoid eye drops were subsequently added to the treatment plan 2 months postoperatively based on the evaluation using confocal laser scanning microscopy. The clinical presentations, best-corrected visual acuity (BCVA), postoperative refractive outcomes, graft survival, and Acanthamoeba recurrence were analyzed. Results The AK patients included in the study were in stage 2 or stage 3, and the percentage of patients in stage 3 was higher in the PKP group (P = 0.003). Clinical presentations were mainly corneal ulcers and ring infiltrates, and endothelial plaques, hypopyon, uveitis and glaucoma were more common in the PKP group (P = 0.007). The BCVA and the graft survival rate showed no statistically significant differences between the two groups at 1 year after surgery. However, 3 years postoperatively, the BCVA of 0.71 ± 0.64 logMAR, the graft survival rate of 89.5%, and the endothelial cell density of 1899 ± 125 cells per square millimeter in the BB-DALK group were significantly better than those of the PKP group (P = 0.010, 0.046, and 0.032, respectively). 3 eyes (11.1%) in the BB-DALK group and 2 eyes (8.3%) in the PKP group experienced Acanthamoeba recurrence, but the rates showed no statistically significant difference between the two groups (P = 1.000). In the PKP group, immune rejection and elevated intraocular pressure were observed in 5 and 6 eyes, respectively. Conclusion Corneal transplantation is recommended for AK patients unresponsive to antiamoebic agents. The visual acuity and graft survival can be maintained after BB-DALK surgery. Acanthamoeba recurrence is not related to the surgical approach performed, whereas complete dissection of the infected corneal stroma and delayed prescribing of glucocorticoid eye drops were important to prevent recurrence.
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- 2024
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15. Development of the computational antibiotic screening platform (CLASP) to aid in the discovery of new antibiotics
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Soor Rajiv Vora, Shikha Nangia, Huilin Ma, Dacheng Ren, Meishan Wu, Yinghui Dai, and Tory Alane Welsch
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Carbapenem ,Imipenem ,Computer science ,medicine.drug_class ,Antibiotics ,Porins ,Computational biology ,Microbial Sensitivity Tests ,01 natural sciences ,Meropenem ,03 medical and health sciences ,chemistry.chemical_compound ,Antibiotic resistance ,0103 physical sciences ,medicine ,030304 developmental biology ,0303 health sciences ,010304 chemical physics ,Small Molecule Libraries ,General Chemistry ,Condensed Matter Physics ,Anti-Bacterial Agents ,chemistry ,Carbapenems ,Doripenem ,Ertapenem ,medicine.drug - Abstract
Bacterial colonization of biotic and abiotic surfaces and antibiotic resistance are grand challenges with paramount societal impacts. However, in the face of increasing bacterial resistance to all known antibiotics, efforts to discover new classes of antibiotics have languished, creating an urgent need to accelerate the antibiotic discovery pipeline. A major deterrent in the discovering of new antibiotics is the limited permeability of molecules across the bacterial envelope. Notably, the Gram-negative bacteria have nutrient specific protein channels (or porins) that restrict the permeability of non-essential molecules, including antibiotics. Here, we have developed the Computational Antibiotic Screening Platform (CLASP) for screening of potential drug molecules through the porins. The CLASP takes advantage of coarse grain (CG) resolution, advanced sampling techniques, and a parallel computing environment to maximize its performance. The CLASP yields comprehensive thermodynamic and kinetic output data of a potential drug molecule within a few hours of wall-clock time. Its output includes the potential of mean force profile, energy barrier, the rate constant, and contact analysis of the molecule with the pore-lining residues, and the orientational analysis of the molecule in the porin channel. In our first CLASP application, we report the transport properties of six carbapenem antibiotics-biapenem, doripenem, ertapenem, imipenem, meropenem, and panipenem-through OccD3, a major channel for carbapenem uptake in Pseudomonas aeruginosa. The CLASP is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. The CLASP will be freely distributed to enable accelerated antibiotic drug discovery.
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- 2021
16. The Influence of Water on Choline-Based Ionic Liquids
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Shikha Nangia, Kathryn M Piston, Kelly N. Ibsen, Samir Mitragotri, Eden E. L. Tanner, and Huilin Ma
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Geranic acid ,Chemistry ,0206 medical engineering ,Biomedical Engineering ,02 engineering and technology ,Conductivity ,021001 nanoscience & nanotechnology ,Mole fraction ,020601 biomedical engineering ,Ion ,Biomaterials ,chemistry.chemical_compound ,Viscosity ,Chemical engineering ,Ionic liquid ,Molecule ,0210 nano-technology ,Water content - Abstract
Choline and geranic acid (CAGE)-based ionic liquids have been recently developed for applications in drug delivery. Understanding the microscopic structures of CAGE in the presence of water is critical for its continued use in biomedical applications as it will undoubtedly come into contact with water in physiological fluids. Water can drastically impact the physicochemical properties of the ionic liquids, including CAGE. Computational and experimental characterization, namely viscosity, conductivity, and self-diffusion coefficient, were employed here to understand the properties of equimolar CAGE (1:1 choline/geranic acid) in the presence of varying amounts of water. It was found that under stored conditions, 1:1 CAGE contained up to 0.20 mole fraction water. Experimental and computational studies indicate that microscopic intraionic interactions within CAGE are not substantially changed until the water content exceeds 0.65 mole fraction. At this point, we theorize that the geranate ions undergo reorganization to minimize contact between the hydrophobic tails and the water molecules. This is evidenced by the plateau in viscosity at this mole fraction, and the increased interactions between the tails of the anions. This suggests that CAGE could be used without predrying in most applications and can be diluted to induce the organization of the anions where desired.
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- 2021
17. High-Level Antibiotic Tolerance of a Clinically Isolated Enterococcus faecalis Strain
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Xiaohui Zheng, Sweta Roy, Tian Gao, Zafer Soultan, Shikha Nangia, Christopher Fortner, Dacheng Ren, Huan Gu, and Huilin Ma
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Multidrug tolerance ,medicine.drug_class ,Tetracycline ,Antibiotics ,Microbial Sensitivity Tests ,Applied Microbiology and Biotechnology ,Enterococcus faecalis ,Microbiology ,03 medical and health sciences ,chemistry.chemical_compound ,Vancomycin ,Drug Resistance, Multiple, Bacterial ,Ampicillin ,medicine ,TetR ,030304 developmental biology ,0303 health sciences ,Ecology ,biology ,Public and Environmental Health Microbiology ,030306 microbiology ,biology.organism_classification ,Anti-Bacterial Agents ,chemistry ,Efflux ,Food Science ,Biotechnology ,medicine.drug - Abstract
Bacteria can survive antibiotic treatment both by acquiring antibiotic resistance genes and through mechanisms of tolerance that are based on phenotypic changes and the formation of metabolically inactive cells. Here, we report an Enterococcus faecalis strain (E. faecalis UM001B) that was isolated from a cystic fibrosis patient and had no increase in resistance but extremely high-level tolerance to ampicillin, vancomycin, and tetracycline. Specifically, the percentages of cells that survived 3.5-h antibiotic treatment (at 100 μg · ml−1) were 25.4% ± 4.3% and 51.9% ± 4.0% for ampicillin and tetracycline, respectively; vancomycin did not exhibit any significant killing. Consistent with the changes in antibiotic susceptibility, UM001B was found to have reduced penetration of ampicillin and vancomycin and accumulation of tetracycline compared to the reference strain ATCC 29212. Based on whole-genome sequencing, four amino acid substitutions were identified in one of the tetracycline efflux pump repressors (TetRs), compared to ATCC 29212. Results of molecular simulations and experimental assays revealed that these mutations could lead to higher levels of tetracycline efflux activity. Consistently, replicating these mutations in Escherichia coli MG1655 increased its tolerance to tetracycline. Overall, these findings provide new insights into the development of multidrug tolerance in E. faecalis, which can facilitate future studies to better control enterococcal infections. IMPORTANCEEnterococcus faecalis represents a major group of pathogens causing nosocomial infections that are resistant to multiple classes of antibiotics. An important challenge associated with E. faecalis infection is the emergence of multidrug-tolerant strains, which have normal MICs but do not respond to antibiotic treatment. Here, we report a strain of E. faecalis that was isolated from a cystic fibrosis patient and demonstrated high-level tolerance to ampicillin, vancomycin, and tetracycline. Whole-genome sequencing revealed critical substitutions in one of the tetracycline efflux pump repressors that are consistent with the increased tolerance of E. faecalis UM001B to tetracycline. These findings provide new information about bacterial antibiotic tolerance and may help develop more effective therapeutics.
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- 2020
18. Quantitative Systems Pharmacology Modeling of PBMC-Humanized Mouse to Facilitate Preclinical Immuno-oncology Drug Development
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Huilin Ma, Craig Giragossian, Jun Wang, Aleksander S. Popel, and Minu Pilvankar
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Pharmacology ,business.industry ,T cell ,medicine.medical_treatment ,Immunotherapy ,medicine.disease ,Primary tumor ,Immune checkpoint ,Pre-clinical development ,medicine.anatomical_structure ,Immune system ,Humanized mouse ,Cancer research ,Medicine ,Pharmacology (medical) ,business ,Systems pharmacology - Abstract
[Image: see text] Progress in immunotherapy has resulted in explosively increased new therapeutic interventions and they have shown promising results in the treatment of cancer. Animal testing is performed to provide preliminary efficacy and safety data for drugs under development prior to clinical trials. However, translational challenges remain for preclinical studies such as study design and the relevance of animal models to humans. Hence, only a small fraction of cancer patients showed response. The explosion of drug candidates and therapies makes preclinical assessment of every plausible option impossible, but it can be easily tested using Quantitative System Pharmacology (QSP) models. Here, we developed a QSP model for humanized mice. Tumor growth dynamics, T cell dynamics, cytokine release, immune checkpoint expression, and drug administration were modeled and calibrated using experimental data. Tumor growth inhibition data were used for model validation. Pharmacokinetics of T cell engager (TCE), tumor growth profile, T cell expansion in the blood and infiltration into tumor, T cell dissemination from primary tumor, cytokine release profile, and expression of additional PD-L1 induced by IFN-γ were modeled and calibrated using a variety of experimental data and showed good consistency. Mouse-specific response to T cell engager monotherapy also showed the key features of in vivo efficacy of TCE. This novel QSP model, designed for human peripheral blood mononuclear cells (PBMC) engrafted xenograft mice, incorporating the most critical components of the mouse model with key cancer and immune cells, can become an integral part of preclinical drug development.
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- 2020
19. Evaluation of clinical efficacy, adverse reactions, and safety of PD-1 inhibitors combined with chemotherapy when treating advanced gastric cancer
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Xue Huang, Du He, Lin Lai, Jun Chen, Yukun Zhang, and Huilin Mao
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PD-1 inhibitor ,Chemotherapy ,Advanced gastric cancer ,Efficacy ,Life quality ,Adverse reactions ,Diseases of the digestive system. Gastroenterology ,RC799-869 - Abstract
Abstract Objective This paper aimed to assess the clinical efficacy, adverse reactions, and safety of employing PD-1 inhibitors in conjunction with chemotherapy as a treatment strategy for advanced gastric cancer (GC). Methods Ninety patients with advanced GC from January 2020 to December 2021 were divided into the research group (n = 45) and the control group (n = 45). The control group was treated with apatinib and tigio. The study group was treated with PD-1 inhibitor combined with apatinib and tigio. The remission rate (RR), disease control rate (DCR), overall survival (OS), Eastern Oncology Collaborative Group Physical Status Assessment (ECOG-PS) score, EORTCQLQ-C30 (v3.0) score, and incidence of adverse reactions were compared between the two groups. Results The research group exhibited improved outcomes in several key metrics relative to the control group. Specifically, the RR, DCR, and OS were notably higher in the research group. Additionally, the ECOG-PS score was significantly reduced, indicating better performance. At a median follow-up of 8.7 months, the research group’s functional and total health scores on the EORTC QLQ-C30 (v3.0) scale had seen significant improvement compared to their initial scores and were also superior to the control group’s scores. Importantly, both groups demonstrated comparable incidence rates for adverse reactions, with no significant difference observed (P > 0.05). Conclusion PD-1 inhibitor combined with chemotherapy was more effective when treating patients with advanced GC. It was more beneficial to enhance the patient’s condition, promote survival time, and improve physical status and life quality. In addition, the adverse reactions could be controlled.
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- 2023
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20. Combination therapy with T cell engager and PD-L1 blockade enhances the antitumor potency of T cells as predicted by a QSP model
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Hanwen Wang, Richard J. Sové, Craig Giragossian, Huilin Ma, Jun Wang, and Aleksander S. Popel
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0301 basic medicine ,Male ,Cancer Research ,tumor ,Combination therapy ,medicine.drug_class ,medicine.medical_treatment ,T cell ,T-Lymphocytes ,Immunology ,Programmed Cell Death 1 Receptor ,Quantitative Structure-Activity Relationship ,Monoclonal antibody ,03 medical and health sciences ,0302 clinical medicine ,Immune system ,computational biology ,Cancer immunotherapy ,Antigen ,Immunotherapy Biomarkers ,Immunology and Allergy ,Medicine ,Cytotoxic T cell ,Humans ,RC254-282 ,Pharmacology ,CD8-positive T-Lymphocytes ,business.industry ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,biomarkers ,Immunotherapy ,Combined Modality Therapy ,030104 developmental biology ,medicine.anatomical_structure ,Oncology ,030220 oncology & carcinogenesis ,B7-H1 antigen ,Cancer research ,Molecular Medicine ,Female ,business - Abstract
BackgroundT cells have been recognized as core effectors for cancer immunotherapy. How to restore the anti-tumor ability of suppressed T cells or improve the lethality of cytotoxic T cells has become the main focus in immunotherapy. Bispecific antibodies, especially bispecific T cell engagers (TCEs), have shown their unique ability to enhance the patient’s immune response to tumors by stimulating T cell activation and cytokine production in an MHC-independent manner. Antibodies targeting the checkpoint inhibitory molecules such as programmed cell death protein 1 (PD-1), PD-ligand 1 (PD-L1) and cytotoxic lymphocyte activated antigen 4 are able to restore the cytotoxic effect of immune suppressed T cells and have also shown durable responses in patients with malignancies. However, both types have their own limitations in treating certain cancers. Preclinical and clinical results have emphasized the potential of combining these two antibodies to improve tumor response and patients’ survival. However, the selection and evaluation of combination partners clinically is a costly endeavor. In addition, despite advances made in immunotherapy, there are subsets of patients who are non-responders, and reliable biomarkers for different immunotherapies are urgently needed to improve the ability to prospectively predict patients’ response and improve clinical study design. Therefore, mathematical and computational models are essential to optimize patient benefit, and guide combination approaches with lower cost and in a faster manner.MethodIn this study, we continued to extend the quantitative systems pharmacology (QSP) model we developed for a bispecific TCE to explore efficacy of combination therapy with an anti-PD-L1 monoclonal antibody in patients with colorectal cancer.ResultsPatient-specific response to TCE monotherapy, anti-PD-L1 monotherapy and the combination therapy were predicted using this model according to each patient’s individual characteristics.ConclusionsIndividual biomarkers for TCE monotherapy, anti-PD-L1 monotherapy and their combination have been determined based on the QSP model. Best treatment options for specific patients could be suggested based on their own characteristics to improve clinical trial efficiency. The model can be further used to assess plausible combination strategies for different TCEs and immune checkpoint inhibitors in different types of cancer.
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- 2020
21. Interaction of amphiphilic coumarin with DPPC/DPPS lipid bilayer: effects of concentration and alkyl tail length
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Anju Gupta, Tyler Zimmermann, Poornima Kalyanram, Istvan Stadler, Shena Marshall, Ana Cartaya, Huilin Ma, Christina Goudreau, and Shikha Nangia
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1,2-Dipalmitoylphosphatidylcholine ,Lipid Bilayers ,General Physics and Astronomy ,02 engineering and technology ,Phosphatidylserines ,Conjugated system ,Molecular Dynamics Simulation ,010402 general chemistry ,01 natural sciences ,Fluorescence spectroscopy ,chemistry.chemical_compound ,Surface-Active Agents ,Coumarins ,Amphiphile ,Zeta potential ,heterocyclic compounds ,Physical and Theoretical Chemistry ,Lipid bilayer ,Alkyl ,chemistry.chemical_classification ,Liposome ,Molecular Structure ,Chemistry ,021001 nanoscience & nanotechnology ,Coumarin ,0104 chemical sciences ,Biophysics ,lipids (amino acids, peptides, and proteins) ,0210 nano-technology ,Hydrophobic and Hydrophilic Interactions - Abstract
In this work, interactions between amphiphilic amino methyl coumarin and dipalmitoyl-sn-glycero-3-phosphocholine/dipalmitoyl-sn-glycero-3-phosphoserine (DPPC/DPPS) lipid bilayer were investigated. A combination of experimental techniques (zeta potential, fluorescence spectroscopy, and differential scanning calorimetry) along with molecular dynamics simulations was employed to examine the influence of alkyl tail length and concentration of the amphiphilic coumarin on the lipid bilayer. Alkyl tails comprising 5(C5), 9(C9), and 12(C12) carbon atoms were conjugated to amino methyl coumarin via a single-step process. The binding and insertion mechanisms of the amphiphilic coumarins were studied in increasing concentrations for short-tailed (C5) and long-tailed (C12) coumarins. The simulation results show that C5 coumarin molecules penetrate the lipid bilayer, but owing to the short alkyl tail, they interact primarily with the lipid head groups resulting in lipid bilayer thinning; however, at high concentrations, the C5 coumarins undergo continuous insertion–ejection from the outer leaflet of the lipid bilayer. In contrast, C12 coumarins interact favorably with the hydrophobic lipid tails and lack the ejection–reinsertion behavior. Instead, the C12 coumarin molecules undergo flip-flops between the outer and inner leaflets of the lipid bilayer. At high concentrations, the high-frequency flip-flops lead to lipid destabilization, causing the lipid bilayer to rupture. The simulation results are in excellent agreement with the toxicity of amphiphilic coumarin activity in cancer cells. The efficacy of amphiphilic coumarins in liposomal lipid bilayers demonstrates the promise of these molecules as a tool in the treatment of cancer.
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- 2020
22. A Quantitative Systems Pharmacology Model of T Cell Engager Applied to Solid Tumor
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Jun Wang, Mohammad Jafarnejad, Richard J. Sové, Aleksander S. Popel, Chia Hung Tsai, Craig Giragossian, Huilin Ma, and Hanwen Wang
- Subjects
medicine.medical_treatment ,T cell ,T-Lymphocytes ,Pharmaceutical Science ,colorectal cancer ,cancer systems biology ,Models, Biological ,Antineoplastic Agents, Immunological ,computational biology ,Antigen ,Cancer immunotherapy ,medicine ,Humans ,immuno-oncology ,cancer immunotherapy ,Effector ,Chemistry ,Systems Biology ,Cancer ,medicine.disease ,medicine.anatomical_structure ,Cancer systems biology ,Cancer cell ,Cancer research ,Immunotherapy ,Colorectal Neoplasms ,Systems pharmacology ,Research Article - Abstract
Cancer immunotherapy has recently drawn remarkable attention as promising results in the clinic have shown its ability to improve the overall survival, and T cells are considered to be one of the primary effectors for cancer immunotherapy. Enhanced and restored T cell tumoricidal activity has shown great potential for killing cancer cells. Bispecific T cell engagers (TCEs) are a growing class of molecules that are designed to bind two different antigens on the surface of T cells and cancer cells to bring them in close proximity and selectively activate effector T cells to kill target cancer cells. New T cell engagers are being investigated for the treatment of solid tumors. The activity of newly developed T cell engagers showed a strong correlation with tumor target antigen expression. However, the correlation between tumor-associated antigen expression and overall response of cancer patients is poorly understood. In this study, we used a well-calibrated quantitative systems pharmacology (QSP) model extended to bispecific T cell engagers to explore their efficacy and identify potential biomarkers. In principle, patient-specific response can be predicted through this model according to each patient’s individual characteristics. This extended QSP model has been calibrated with available experimental data and provides predictions of patients’ response to TCE treatment. Electronic supplementary material The online version of this article (10.1208/s12248-020-00450-3) contains supplementary material, which is available to authorized users.
- Published
- 2020
23. Mechanism of Antibacterial Activity of Choline-Based Ionic Liquids (CAGE)
- Author
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Eden E. L. Tanner, Amrita Banerjee, Kelly N. Ibsen, Samir Mitragotri, Huilin Ma, and Shikha Nangia
- Subjects
0301 basic medicine ,Biocide ,Geranic acid ,Chemistry ,Biomedical Engineering ,02 engineering and technology ,021001 nanoscience & nanotechnology ,medicine.disease_cause ,Antimicrobial ,Biomaterials ,Cell wall ,03 medical and health sciences ,chemistry.chemical_compound ,030104 developmental biology ,Biochemistry ,medicine ,Choline ,0210 nano-technology ,Antibacterial activity ,Cage ,Escherichia coli - Abstract
The continued emergence of antibiotic-resistant organisms has severely depleted our arsenal of effective antimicrobials. Ionic liquids (ILs) show great promise as antibacterial agents but understanding the mechanism of attack on bacterial cells is key to ensuring that design of IL-based biocides impart maximum efficacy with minimal toxicity, while also avoiding the potential for the target organisms to become resistant. Here we report the antibacterial attributes of a set of choline and geranate (CAGE)-based ILs and identify the mechanism by which they interact with the Gram-negative cell wall of Escherichia coli. CAGE is envisaged as an antimicrobial agent to treat topical infections in skin. Our earlier work has shown that CAGE is highly effective across a breadth of bacterial, fungal, and viral species and is benign to human cells. This combination makes CAGE an ideal antimicrobial for human use. Four CAGE variants with varying ratios of choline and geranic acid were synthesized and tested for their an...
- Published
- 2018
24. Volcanic rock‐based ceramsite adsorbent for highly selective fluoride removal: function optimization and mechanism
- Author
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Huilin Ma, Qian Song, Wang Zijian, Chunfang Chao, Ji Min, Xin Li, and Yingxin Zhao
- Subjects
geography ,geography.geographical_feature_category ,Renewable Energy, Sustainability and the Environment ,Chemistry ,Function optimization ,General Chemical Engineering ,Organic Chemistry ,chemistry.chemical_element ,Aluminium sulfate ,Highly selective ,Pollution ,Inorganic Chemistry ,Volcanic rock ,chemistry.chemical_compound ,Fuel Technology ,Adsorption ,Chemical engineering ,Aluminium ,Bentonite ,Waste Management and Disposal ,Fluoride ,Biotechnology - Published
- 2019
25. Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer
- Author
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Aleksander S. Popel, Leisha A. Emens, Richard J. Sové, Hanwen Wang, and Huilin Ma
- Subjects
0301 basic medicine ,Oncology ,Cancer Research ,medicine.medical_specialty ,Time Factors ,Paclitaxel ,medicine.medical_treatment ,Immunology ,Triple Negative Breast Neoplasms ,Network Pharmacology ,Antibodies, Monoclonal, Humanized ,B7-H1 Antigen ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,Virtual patient ,Atezolizumab ,Albumins ,Internal medicine ,Antineoplastic Combined Chemotherapy Protocols ,Tumor Microenvironment ,medicine ,Humans ,Immunology and Allergy ,CTLA-4 Antigen ,Computer Simulation ,Immune Checkpoint Inhibitors ,RC254-282 ,Triple-negative breast cancer ,Retrospective Studies ,Pharmacology ,Clinical Trials as Topic ,business.industry ,Correction ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Immunotherapy ,medicine.disease ,Immune checkpoint ,Clinical trial ,Treatment Outcome ,030104 developmental biology ,030220 oncology & carcinogenesis ,Molecular Medicine ,Female ,business ,Algorithms ,Systems pharmacology - Abstract
BackgroundImmune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the patients benefit from the treatments. While a number of ongoing clinical trials are investigating different combinations of checkpoint inhibitors and chemotherapeutic agents, predictive biomarkers that identify patients most likely to benefit remains one of the major challenges. Here we present a modular quantitative systems pharmacology (QSP) platform for immuno-oncology that incorporates detailed mechanisms of immune–cancer cell interactions to make efficacy predictions and identify predictive biomarkers for treatments using atezolizumab and nab-paclitaxel.MethodsA QSP model was developed based on published data of triple-negative breast cancer. With the model, we generated a virtual patient cohort to conduct in silico virtual clinical trials and make retrospective analyses of the pivotal IMpassion130 trial that led to the accelerated approval of atezolizumab and nab-paclitaxel for patients with programmed death-ligand 1 (PD-L1) positive triple-negative breast cancer. Available data from clinical trials were used for model calibration and validation.ResultsWith the calibrated virtual patient cohort based on clinical data from the placebo comparator arm of the IMpassion130 trial, we made efficacy predictions and identified potential predictive biomarkers for the experimental arm of the trial using the proposed QSP model. The model predictions are consistent with clinically reported efficacy endpoints and correlated immune biomarkers. We further performed a series of virtual clinical trials to compare different doses and schedules of the two drugs for simulated therapeutic optimization.ConclusionsThis study provides a QSP platform, which can be used to generate virtual patient cohorts and conduct virtual clinical trials. Our findings demonstrate its potential for making efficacy predictions for immunotherapies and chemotherapies, identifying predictive biomarkers, and guiding future clinical trial designs.
- Published
- 2021
26. Dynamics of OmpF Trimer Formation in the Bacterial Outer Membrane of Escherichia coli
- Author
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Shikha Nangia, Aliza Khan, and Huilin Ma
- Subjects
Dimer ,Porins ,Trimer ,Molecular Dynamics Simulation ,010402 general chemistry ,medicine.disease_cause ,01 natural sciences ,chemistry.chemical_compound ,Molecular dynamics ,0103 physical sciences ,Electrochemistry ,medicine ,Escherichia coli ,General Materials Science ,Lipid bilayer ,Spectroscopy ,010304 chemical physics ,Surfaces and Interfaces ,computer.file_format ,Condensed Matter Physics ,Protein Data Bank ,0104 chemical sciences ,Crystallography ,Monomer ,chemistry ,Thermodynamics ,Bacterial outer membrane ,computer - Abstract
The self-assembly of outer membrane protein F (OmpF) in the outer membrane of Escherichia coli Gram-negative bacteria was studied using multiscale molecular dynamics simulations. To accommodate the long time scale required for protein assembly, coarse-grained parametrization of E. coli outer membrane lipids was first developed. The OmpF monomers formed stable dimers at specific protein–protein interactions sites irrespective of the lipid membrane environment. The dimer intermediate was asymmetric but provided a template to form a symmetric trimer. Superposition analysis of the self-assembled trimer with the X-ray crystal structure of the trimer available in the protein data bank showed excellent agreement with global root-mean-square deviation of less than 2.2 A. The free energy change associated with dimer formation was −26 ± 1 kcal mol–1, and for a dimer to bind to a monomer and to form a trimer yielded −56 ± 4 kcal mol–1. Based on thermodynamic data, an alternate path to trimer formation via interactio...
- Published
- 2017
27. Modeling Diversity in Structures of Bacterial Outer Membrane Lipids
- Author
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Tara Picudella, Natalie Brooke Edelstein, Sarah Rose Willsey, Shikha Nangia, Huilin Ma, Aliza Khan, Daniel D. Cummins, Masud Dikita Llewellyn, and Jerry Gomez
- Subjects
0301 basic medicine ,Models, Molecular ,Bordetella pertussis ,Molecular Conformation ,medicine.disease_cause ,01 natural sciences ,Campylobacter jejuni ,Microbiology ,Lipid A ,03 medical and health sciences ,Membrane Lipids ,Species Specificity ,0103 physical sciences ,medicine ,Transition Temperature ,Physical and Theoretical Chemistry ,Porphyromonas gingivalis ,010304 chemical physics ,biology ,Bacteria ,Neisseria meningitidis ,Cell Membrane ,biology.organism_classification ,Computer Science Applications ,030104 developmental biology ,Biochemistry ,lipids (amino acids, peptides, and proteins) ,Bacteroides fragilis ,Bacterial outer membrane - Abstract
Lipopolysaccharides (LPSs) are vital components of the outer membrane of Gram-negative bacteria, and they act as extremely strong stimulators of innate immunity in diverse eukaryotic species. The primary immunostimulatory center of the LPS molecule is lipid A, a disaccharide-bound lipophilic domain. Considering the broad diversity in bacterial species, there are variations in the lipid A structures and their immunogenic potencies. In this work, we model the lipid A structures of eight commensal or human pathogenic bacterial species: Helicobacter pylori, Porphyromonas gingivalis, Bacteroides fragilis, Bordetella pertussis, Chlamydia trachomatis, Campylobacter jejuni, Neisseria meningitidis, and Salmonella minnesota. The membrane properties of these bacterial species were characterized and compared using molecular simulations. The structure-property relationships that emerge from this lipid A molecular library highlight the roles of acyl chain lengths, number of chains, phosphorylation state, membrane composition, and counterion charge in regulating the phase transition temperature of the membrane, diffusion coefficient of the lipids, and membrane thickness. The molecular and structural insights provided reveal the diversity in bacterial outer membrane lipids and their contribution to human disease and immunity.
- Published
- 2017
28. Simulating Gram-Negative Bacterial Outer Membrane: A Coarse Grain Model
- Author
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Wenjuan Jiang, Flaviyan Jerome Irudayanathan, Huilin Ma, and Shikha Nangia
- Subjects
Gram-negative bacteria ,biology ,Chemistry ,Cell Membrane ,Biological membrane ,biology.organism_classification ,Models, Biological ,Exocytosis ,Surfaces, Coatings and Films ,Membrane ,Biochemistry ,Membrane protein ,Gram-Negative Bacteria ,Materials Chemistry ,Biophysics ,Virulence-related outer membrane protein family ,Physical and Theoretical Chemistry ,Cell envelope ,Bacterial outer membrane - Abstract
The cell envelope of Gram-negative bacteria contains a lipopolysaccharide (LPS) rich outer membrane that acts as the first line of defense for bacterial cells in adverse physical and chemical environments. The LPS macromolecule has a negatively charged oligosaccharide domain that acts as an ionic brush, limiting the permeability of charged chemical agents through the membrane. Besides the LPS, the outer membrane has radially extending O-antigen polysaccharide chains and β-barrel membrane proteins that make the bacterial membrane physiologically unique compared to phospholipid cell membranes. Elucidating the interplay of these contributing macromolecular components and their role in the integrity of the bacterial outer membrane remains a challenge. To bridge the gap in our current understanding of the Gram-negative bacterial membrane, we have developed a coarse grained force field for outer membrane that is computationally affordable for simulating dynamical process over physiologically relevant time scales. The force field was benchmarked against available experimental and atomistic simulations data for properties such as membrane thickness, density profiles of the residues, area per lipid, gel to liquid-crystalline phase transition temperatures, and order parameters. More than 17 membrane compositions were studied with a combined simulation time of over 100 μs. A comparison of simulated structural and dynamical properties with corresponding experimental data shows that the developed force field reproduces the overall physiology of LPS rich membranes. The affordability of the developed model for long time scale simulations can be instrumental in determining the mechanistic aspects of the antimicrobial action of chemical agents as well as assist in designing antimicrobial peptides with enhanced outer membrane permeation properties.
- Published
- 2015
29. Identification of SaCas9 orthologs containing a conserved serine residue that determines simple NNGG PAM recognition.
- Author
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Shuai Wang, Chen Tao, Huilin Mao, Linghui Hou, Yao Wang, Tao Qi, Yuan Yang, Sang-Ging Ong, Shijun Hu, Renjie Chai, and Yongming Wang
- Subjects
Biology (General) ,QH301-705.5 - Abstract
Due to different nucleotide preferences at target sites, no single Cas9 is capable of editing all sequences. Thus, this highlights the need to establish a Cas9 repertoire covering all sequences for efficient genome editing. Cas9s with simple protospacer adjacent motif (PAM) requirements are particularly attractive to allow for a wide range of genome editing, but identification of such Cas9s from thousands of Cas9s in the public database is a challenge. We previously identified PAMs for 16 SaCas9 orthologs. Here, we compared the PAM-interacting (PI) domains in these orthologs and found that the serine residue corresponding to SaCas9 N986 was associated with the simple NNGG PAM requirement. Based on this discovery, we identified five additional SaCas9 orthologs that recognize the NNGG PAM. We further identified three amino acids that determined the NNGG PAM requirement of SaCas9. Finally, we engineered Sha2Cas9 and SpeCas9 to generate high-fidelity versions of Cas9s. Importantly, these natural and engineered Cas9s displayed high activities and distinct nucleotide preferences. Our study offers a new perspective to identify SaCas9 orthologs with NNGG PAM requirements, expanding the Cas9 repertoire.
- Published
- 2022
- Full Text
- View/download PDF
30. Dynamics of OmpF Trimer Formation in the Bacterial Outer Membrane of Escherichia coli.
- Author
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Huilin Ma, Khan, Aliza, and Nangia, Shikha
- Subjects
- *
ESCHERICHIA coli , *MEMBRANE proteins , *GRAM-negative bacteria , *MOLECULAR dynamics , *THERMODYNAMICS , *DIMERS - Abstract
The self-assembly of outer membrane protein F (OmpF) in the outer membrane of Escherichia coli Gram-negative bacteria was studied using multiscale molecular dynamics simulations. To accommodate the long time scale required for protein assembly, coarse-grained parametrization of E. coli outer membrane lipids was first developed. The OmpF monomers formed stable dimers at specific protein-protein interactions sites irrespective of the lipid membrane environment. The dimer intermediate was asymmetric but provided a template to form a symmetric trimer. Superposition analysis of the self-assembled trimer with the X-ray crystal structure of the trimer available in the protein data bank showed excellent agreement with global root-mean-square deviation of less than 2.2 Å. The free energy change associated with dimer formation was -26 ± 1 kcal mol-1, and for a dimer to bind to a monomer and to form a trimer yielded -56 ± 4 kcal mol-1. Based on thermodynamic data, an alternate path to trimer formation via interaction of two dimers is also presented. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
31. Compact SchCas9 Recognizes the Simple NNGR PAM
- Author
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Shuai Wang, Huilin Mao, Linghui Hou, Ziying Hu, Yao Wang, Tao Qi, Chen Tao, Yuan Yang, Chengdong Zhang, Miaomiao Li, Huihui Liu, Shijun Hu, Renjie Chai, and Yongming Wang
- Subjects
CRISPR/Cas9 ,genome editing ,PAM ,SaCas9 ,SchCas9 ,Science - Abstract
Abstract Clustered regularly interspaced short palindromic repeat (CRISPR)/SaCas9 is the most popular tool for in vivo genome editing due to its high efficiency and small genome. The authors previously developed four SaCas9 orthologs as genome‐editing tools. Here, to expand the targeting scope, they investigate the diversity of protospacer adjacent motifs (PAMs) by screening a list of 16 SaCas9 orthologs, twelve of which display editing activity in mammalian cells. They recognize five types of PAMs: NNGRRT, NNGRRR, NNGRC, NNGA, and NNGR. Importantly, SchCas9 recognizes the simple NNGR PAM, representing the most relaxed PAM preference of compact Cas9s to date. It is further demonstrated that SchCas9 enables efficient genome editing in multiple human cell lines. Altogether, these compact Cas9 tools offer a new option for both basic research and clinical applications.
- Published
- 2022
- Full Text
- View/download PDF
32. High-Level Antibiotic Tolerance of a Clinically Isolated Enterococcus faecalis Strain.
- Author
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Huan Gu, Roy, Sweta, Xiaohui Zheng, Tian Gao, Huilin Ma, Soultan, Zafer, Fortne, Christopher, Nangia, Shikha, and Ren, Dacheng
- Subjects
- *
ENTEROCOCCUS , *ENTEROCOCCUS faecalis , *ANTIBIOTICS , *ENTEROCOCCAL infections , *NUCLEOTIDE sequencing , *DRUG resistance in bacteria , *TETRACYCLINE - Abstract
Bacteria can survive antibiotic treatment both by acquiring antibiotic resistance genes and through mechanisms of tolerance that are based on phenotypic changes and the formation of metabolically inactive cells. Here, we report an Enterococcus faecalis strain (E. faecalis UM001B) that was isolated from a cystic fibrosis patient and had no increase in resistance but extremely high-level tolerance to ampicillin, vancomycin, and tetracycline. Specifically, the percentages of cells that survived 3.5-h antibiotic treatment (at 100 μg · mlμ1) were 25.4% ± 4.3% and 51.9%±4.0% for ampicillin and tetracycline, respectively; vancomycin did not exhibit any significant killing. Consistent with the changes in antibiotic susceptibility, UM001B was found to have reduced penetration of ampicillin and vancomycin and accumulation of tetracycline compared to the reference strain ATCC 29212. Based on whole-genome sequencing, four amino acid substitutions were identified in one of the tetracycline efflux pump repressors (TetRs), compared to ATCC 29212. Results of molecular simulations and experimental assays revealed that these mutations could lead to higher levels of tetracycline efflux activity. Consistently, replicating these mutations in Escherichia coli MG1655 increased its tolerance to tetracycline. Overall, these findings provide new insights into the development of multidrug tolerance in E. faecalis, which can facilitate future studies to better control enterococcal infections. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
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