High-throughput screening and identification of compounds with anti-Mycobacterium kansasii activity

doi:10.19982/j.issn.1000-6621.20240518

Abstract

Abstract:

Objective: To establish a high-throughput screening (HTS) platform for compounds actively against Mycobacterium kansasii and identify novel candidates. Methods: A 96-well plate-based HTS system was developed to screen a G protein-coupled receptor (GPCR) compound library for candidates with anti-M.kansasii activity. Selected candidates were evaluated for antibacterial activity against clinical strains, time-kill kinetics, biofilm inhibition, and cytotoxicity. Data were statistically analyzed using t-tests and analysis of variance (ANOVA) at P<0.05. Results: Seventeen candidate compounds with anti-M.kansasii activity were identified. Promethazine hydrochloride and vorapaxar exhibited best performance against the M.kansasii standard strain (ATCC 12478), with minimum inhibitory concentrations (MIC) of 1.6 μg/ml and 1.23 μg/ml, respectively, and both of them showed a MIC of 2 μg/ml against rifampin-resistant clinical isolates. Time-kill curve experiments and Biofilm inhibition assays demonstrated their anti-ATCC 12478 activity and anti-biofilm effect were both concentration-dependent. Promethazine hydrochloride exhibited an inhibitory effect only at 8 μg/ml (A₄₅₀=3.027 vs. 1.984, t=4.183, P=0.014), whereas vorapaxar showed significant inhibitory effects at both 4 μg/ml (A₄₅₀=3.027 vs. 1.959, t=4.342, P=0.012) and 8 μg/ml (A₄₅₀=3.027 vs. 2.024, t=4.493, P=0.019), with all differences being statistically significant. There was no statistically significant difference in cell viability compared to the control group after cell being cultured with Promethazine hydrochloride for 24 hours. Vorapaxar caused a slight reduction in cell viability only at a concentration of 20 μmol/L compared with control group (survival rate=84.97% vs. 99.97%, t=3.098, P=0.021). Conclusion: A high-throughput screening platform for compounds with anti-M.kansasii activity was successfully established, and both promethazine hydrochloride and vorapaxar exhibited significant anti-M.kansasii activity as well as concentration-dependent antibiofilm activity, providing potential candidate compounds for the development of new anti-M.kansasii drugs.

Key words: Mycobacterium kansasii, High-throughput screening, Promethazine, Vorapaxar, Biofilms

CLC Number:

R978.1

Hu Qianfang, Zhong Rujie, Shang Yuanyuan, Zhang Xuxia, Li Shanshan, Wang Wei. High-throughput screening and identification of compounds with anti-Mycobacterium kansasii activity[J]. Chinese Journal of Antituberculosis, 2025, 47(5): 597-604. doi: 10.19982/j.issn.1000-6621.20240518

Figures/Tables 8

References 30

[1]	聂琦, 周勇, 陈华, 等. 非结核分枝杆菌病流行病学研究进展. 中华临床感染病杂志, 2020, 13(5):394-400. doi:10.3760/cma.j.issn.1674-2397.2020.05.014.
[2]	中华医学会结核病学分会. 非结核分枝杆菌病诊断与治疗指南(2020年版). 中华结核和呼吸杂志, 2020, 43(11):918-946. doi:10.3760/cma.j.cn112147-20200508-00570.
[3]	Xu N, Li L, Wu S. Epidemiology and laboratory detection of non-tuberculous mycobacteria. Heliyon, 2024, 10(15):e35311. doi:10.1016/j.heliyon.2024.e35311.
[4]	梁锋, 刘德情, 陈华, 等. 广州市非结核分枝杆菌病流行病学特征分析. 中国防痨杂志, 2024, 46(11):1373-1379. doi:10.19982/j.issn.1000-6621.20240185.
[5]	Zhang Y, Sun R, Yu C, et al. Spatial Heterogeneity of Nontuberculous Mycobacterial Pulmonary Disease in Shanghai: Insights from a Ten-Year Population-Based Study. Int J Infect Dis, 2024,143:107001. doi:10.1016/j.ijid.2024.107001.
[6]	刘曾维, 陈品儒, 黎惠如, 等. 堪萨斯分枝杆菌肺病的临床及CT影像特征. 分子影像学杂志, 2024, 47(3):321-326. doi:10.12122/j.issn.1674-4500.2024.03.16.
[7]	Daley CL, Iaccarino JM, Lange C, et al. Treatment of nontuberculous mycobacterial pulmonary disease: an official ATS/ERS/ESCMID/IDSA clinical practice guideline. Eur Respir J, 2020, 56(1):2000535. doi:10.1183/13993003.00535-2020.
[8]	Wang PH, Pan SW, Wang SM, et al. The Impact of Nontuberculous Mycobacteria Species on Mortality in Patients With Nontuberculous Mycobacterial Lung Disease. Front Microbiol, 2022,13:909274. doi:10.3389/fmicb.2022.909274.
[9]	Cheng LP, Chen SH, Lou H, et al. Factors Associated with Treatment Outcome in Patients with Nontuberculous Mycobacterial Pulmonary Disease: A Large Population-Based Retrospective Cohort Study in Shanghai. Trop Med Infect Dis, 2022, 7(2):27. doi:10.3390/tropicalmed7020027.
[10]	Liu CJ, Huang HL, Cheng MH, et al. Outcome of patients with and poor prognostic factors for Mycobacterium kansasii-pulmonary disease. Respir Med, 2019, 151:19-26. doi:10.1016/j.rmed.2019.03.015.
[11]	Zhang YY, Yu CL, Jiang Y, et al. Drug resistance profile of Mycobacterium kansasii clinical isolates before and after 2-month empirical antimycobacterial treatment. Clin Microbiol Infect, 2023, 29(3):353-359. doi:10.1016/j.cmi.2022.10.002.
[12]	任忠雪. 创新药物研发中的高通量筛选技术. 工程技术研究, 2024, 6(16):128-130. doi:10.12417/2705-0998.24.16.043.
[13]	Yasi EA, Kruyer NS, Peralta-Yahya P. Advances in G protein-coupled receptor high-throughput screening. Curr Opin Biotechnol, 2020, 64:210-217. doi:10.1016/j.copbio.2020.06.004.
[14]	Woods GL, Brown-Elliott BA, Conville PS, et al. Susceptibility Testing of Mycobacteria, Nocardiae, and Other Aerobic Actinomycetes [Internet]. 2nd ed. Wayne (PA): Clinical and Laboratory Standards Institute, 2011.
[15]	Pennings LJ, Ruth MM, Wertheim HFL, et al. The Benzimidazole SPR719 Shows Promising Concentration-Dependent Activity and Synergy against Nontuberculous Mycobacteria. Antimicrob Agents Chemother, 2021, 65(4):e02469-20. doi:10.1128/AAC.02469-20.
[16]	武瑞君, 李玮琦, 杨阳, 等. 小分子药物筛选技术研究现状及其应用进展. 医药导报, 2024, 43(2):255-261. doi:10.3870/j.issn.1004-0781.2024.02.017.
[17]	Wang Y, Jeon H. 3D cell cultures toward quantitative high-throughput drug screening. Trends Pharmacol Sci, 2022, 43(7):569-581. doi:10.1016/j.tips.2022.03.014. pmid: 35504760
[18]	Gentile F, Yaacoub JC, Gleave J, et al. Artificial intelligence-enabled virtual screening of ultra-large chemical libraries with deep docking. Nat Protoc, 2022, 17(3):672-697. doi:10.1038/s41596-021-00659-2. pmid: 35121854
[19]	Giri AK, Ianevski A. High-throughput screening for drug discovery targeting the cancer cell-microenvironment interactions in hematological cancers. Expert Opin Drug Discov, 2022, 17(2):181-190. doi:10.1080/17460441.2022.1991306.
[20]	Shinn P, Chen L, Ferrer M, et al. High-Throughput Screening for Drug Combinations. Methods Mol Biol, 2019,1939:11-35. doi:10.1007/978-1-4939-9089-4_2.
[21]	Cao D, Yuan X, Jiang X, et al. Antimicrobial and Antibiofilm Effects of Bithionol against Mycobacterium abscessus. Antibio-tics (Basel), 2024, 13(6):529. doi:10.3390/antibiotics13060529.
[22]	Li H, Li T, Zhang L, et al. Antimicrobial compounds from an FDA-approved drug library with activity against Streptococcus suis. J Appl Microbiol, 2022, 132(3):1877-1886. doi:10.1111/jam.15377.
[23]	Blasco B, Jang S, Terauchi H, et al. High-throughput screening of small-molecules libraries identified antibacterials against clinically relevant multidrug-resistant A. baumannii and K. pneumoniae. EBioMedicine, 2024,102:105073. doi:10.1016/j.ebiom.2024.105073.
[24]	Zweijpfenning SMH, Ingen JV, Hoefsloot W. Geographic Distribution of Nontuberculous Mycobacteria Isolated from Clinical Specimens: A Systematic Review. Semin Respir Crit Care Med, 2018, 39(3):336-342. doi:10.1055/s-0038-1660864. pmid: 30071548
[25]	Wu J, Zhang Y, Li J, et al. Increase in nontuberculous mycobacteria isolated in Shanghai, China: results from a population-based study. PLoS One, 2014, 9(10):e109736. doi:10.1371/journal.pone.0109736.
[26]	Kwon YS, Koh WJ. Diagnosis and Treatment of Nontuberculous Mycobacterial Lung Disease. J Korean Med Sci, 2016, 31(5):649-659. doi:10.3346/jkms.2016.31.5.649.
[27]	Larsson LO, Polverino E, Hoefsloot W, et al. Pulmonary disease by non-tuberculous mycobacteria-clinical management, unmet needs and future perspectives. Expert Rev Respir Med, 2017, 11(12):977-989. doi:10.1080/17476348.2017.1386563.
[28]	Srivastava S, Gumbo T. Clofazimine for the Treatment of Mycobacterium kansasii. Antimicrob Agents Chemother, 2018, 62(8):e00248-18. doi:10.1128/AAC.00248-18.
[29]	李春杏, 朱珠. 抗血小板新药 vorapaxar. 中国新药杂志, 2015, 24(6):601-604,643.
[30]	Chaudhary R, Mohananey A, Sharma SP, et al. Improving Outcomes in Cardiovascular Diseases: A Review on Vorapaxar. Cardiol Rev, 2022, 30(5):241-246. doi:10.1097/CRD.0000000000000390.

化合物名称	临床状态	分子量	化学式	形态	MIC(μmol/L)	MIC(μg/ml)
沃拉帕沙	FDA批准	492.58	C₂₉H₃₃FN₂O₄	游离碱	2.50	1.23
盐酸异丙嗪	FDA批准	320.88	C₁₇H₂₀ClN₂S	盐酸盐	5.00	1.60
AM251	其他	555.24	C₂₂H₂₁Cl₂IN₄O	游离碱	10.00	5.55
甲磺酸溴隐亭	FDA批准	750.70	C₃₂H₄₀BrN₅O₅·CH₄O₃S	甲磺酸盐	10.00	7.51
马来酸PRX-08066	其他	517.96	C₂₃H₂₁ClFN₅O₄S	马来酸盐	10.00	5.18
氢溴酸沃替西汀	其他	379.36	C₁₈H₂₃BrN₂S	氢溴酸盐	10.00	3.79
匹莫范色林	其他	1005.20	C₅₄H₇₄F₂N₆O₁₀	酒石酸盐	10.00	10.05
JMS-17-2	其他	419.95	C₂₅H₂₆ClN₃O	游离碱	10.00	4.20
阿立哌唑	其他	448.39	C₂₃H₂₇Cl₂N₃O₂	游离碱	10.00	4.48
二甲酸丙氯拉嗪	其他	606.09	C₂₈H₃₂ClN₃O₈S	二甲基马来酸盐	10.00	6.06
马来酸环丙西平	其他	386.40	C₂₀H₂₂N₂O₆	马来酸盐	10.00	3.86
盐酸硫利达嗪	其他	407.04	C₂₁H₂₇ClN₂S₂	盐酸盐	20.00	8.14
盐酸阿莫地喹	FDA批准	428.78	C₂₀H₂₄Cl₃N₃O	二水合物	10.00	4.29
NIBR189	临床前阶段	429.31	C₂₁H₂₁BrN₂O₃	游离碱	10.00	4.29
二氢氯化二水合阿莫地喹	其他	464.81	C₂₀H₂₈Cl₃N₃O₃	二氢氯化物二水合物	10.00	4.65
JK184	其他	350.44	C₁₉H₁₈N₄OS	游离碱	20.00	7.01
APD597	临床试验阶段	479.55	C₂₁H₂₉N₅O₆S	游离碱	20.00	9.59

菌株号	利福平	克拉霉素	盐酸异丙嗪	沃拉帕沙
ATCC 12478	0.25	0.50	2.00	2.00
1	0.50	0.50	2.00	2.00
2	0.50	0.50	2.00	2.00
3	0.25	0.50	4.00	>4.00
4^a	>2.00	0.50	2.00	2.00
5^a	>2.00	0.50	2.00	2.00