A ratiometric fluorescent sensor array for bacterial pathogen investigation
用于细菌病原体研究的比率荧光传感器阵列
基本信息
- 批准号:10425245
- 负责人:
- 金额:$ 34.31万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-07-08 至 2025-03-31
- 项目状态:未结题
- 来源:
- 关键词:AlgorithmsAntibodiesBacteriaBar CodesBiochemicalBiologicalBiosensing TechniquesCell WallCharacteristicsChemicalsChemistryClassificationClinicalConsumptionCustomDataDependenceDetectionDevelopmentDrug resistanceDyesElementsEnvironmentEquipmentExhibitsFingerprintFluorescenceFluorescent DyesGoalsGram-Negative BacteriaGrowthHomeostasisHospitalsImageIndustrializationInvestigationLaboratoriesLaboratory PersonnelLibrariesMetabolicMethodsMicrobial BiofilmsMicrobiologyModelingMolecularMulti-Drug ResistanceNoseOpticsOrganismOutputPathogen detectionPathogenicityPatternPattern RecognitionPerformancePhenotypePolysaccharidesProcessPropertyPublic HealthReporterReproducibilityReproducibility of ResultsResearchSafetySamplingSeriesSignal TransductionSpecificityStaphylococcus aureusStatistical Data InterpretationTechniquesTechnologyTestingTimeVariantVirulenceaptamerbasecell envelopecostdesigndiagnostic toolexperienceexperimental studyflexibilityfluorophorehigh throughput screeninginnovationlaboratory experiencelaboratory experimentlarge datasetsmicroorganismmutantnanoparticlenext generationnovel strategiespathogenic bacteriaratiometricresponseroutine Bacterial stainsensortooltrend
项目摘要
PROJECT SUMMARY
Rapid and reliable identification of pathogenic microorganisms is critical for efficient protection of public health
and safety. The high versatility of bacterial pathogens allows them to survive in various environments and the
emergence of multidrug-resistant species pose a particularly severe threat. Current identification of bacteria
largely relies on phenotypic characterization, Gram staining, culturing, and PCR. However, these techniques are
time consuming and require trained laboratory personnel and expensive equipment. Thus, there is a tremendous
need to develop a simple and efficient bacterial identification method. Recently, a sensing strategy has emerged
that utilizes chemicals that do not specifically interact with a particular analyte, but instead react to the general
chemical microenvironment. By using a combination of these chemicals, response patterns can be modelled for
highly sensitive and specific detection of chemical and biological analytes. These barcoding arrays or so-called
“chemical noses” often rely upon absorbance or fluorescence intensity as the output, which makes them highly
susceptible to the sensor concentration. Innovative methods are required to harness the versatility of chemical
barcodes and simultaneously eliminate the pitfalls of concentration dependence. The approach we will employ
here is to generate chemical barcodes that come from fluorophores with a ratiometric response, i.e. ratio of
fluorescence intensities at different wavelengths that depend on the local chemical environment. Moreover, our
recent investigations suggest that dye entrapment in polysaccharide-derived nanoparticles will result in sensors
that are stable and able to interact with Gram positive and Gram negative bacteria under various conditions.
Thus, the overarching goal of this proposal is to design, synthesize, characterize and evaluate a new sensor
array that is based on environment-sensitive ratiometric dyes. The proposed approach will provide a versatile
platform for express identification of pathogenic microorganisms in a clinical laboratory setting and in the field.
We hypothesize that environment-sensitive fluorescent dyes possessing various substituents will exhibit different
spectral responses upon interaction with bacterial cell walls. Being combined into an array, these dyes will produce
a unique bar code-like spectral fingerprint for various bacteria, enabling their fast detection and identification. This
hypothesis will be tested in three aims that are at the interface of chemistry and microbiology. The first aim is to
develop a fluorescent sensor platform that provides a specific multiparametric spectral response with different
bacteria. The second aim is to investigate the interactions of the dyes with bacteria to optimize the reproducibility
of the sensor response. The third aim is to implement the sensor array as a research tool for probing of bacterial
cell envelope homeostasis. Achieving these aims will establish a new class of sensors for rapid and robust
bacterial pathogen detection and identification.
项目摘要
快速可靠地鉴定病原微生物对于有效保护公众健康至关重要
和安全性细菌病原体的高度通用性使它们能够在各种环境中生存,
对多种药物具有抗药性的物种的出现构成了特别严重的威胁。当前细菌鉴定
在很大程度上依赖于表型表征、革兰氏染色、培养和PCR。然而,这些技术
并且需要经过训练的实验室人员和昂贵的设备。因此,
需要开发一种简单高效的细菌鉴定方法。最近,一种传感策略出现了
它利用的化学物质不会与特定的分析物发生特定的相互作用,而是与一般的分析物发生反应。
化学微环境通过使用这些化学品的组合,可以模拟响应模式,
高灵敏度和特异性的化学和生物分析物检测。这些条形码阵列或所谓的
“化学鼻子”通常依赖于吸收或荧光强度作为输出,这使得它们高度依赖于荧光。
对传感器浓度敏感。需要创新的方法来利用化学品的多功能性
条形码,同时消除浓度依赖的陷阱。我们将采用的方法
这里是生成来自具有比率响应的荧光团的化学条形码,即,
不同波长的荧光强度取决于当地的化学环境。而且我们
最近的研究表明,染料包埋在多糖衍生的纳米颗粒将导致传感器
其是稳定的,并且能够在各种条件下与革兰氏阳性和革兰氏阴性细菌相互作用。
因此,本提案的总体目标是设计、合成、表征和评估一种新的传感器
基于环境敏感的比率染料的阵列。所提出的方法将提供一个通用的
用于在临床实验室环境和现场快速鉴定病原微生物的平台。
我们假设,具有不同取代基的环境敏感性荧光染料将表现出不同的性质。
与细菌细胞壁相互作用时的光谱响应。这些染料组合成一个阵列,
一种独特的条形码般的光谱指纹为各种细菌,使他们能够快速检测和识别。这
假设将在化学和微生物学界面的三个目标中进行测试。第一个目标是
开发荧光传感器平台,提供具有不同的多参数光谱响应的特定多参数光谱响应,
细菌第二个目的是研究染料与细菌的相互作用,以优化重现性
传感器的反应。第三个目标是将传感器阵列作为探测细菌的研究工具。
细胞被膜稳态实现这些目标将建立一种新的传感器,
细菌病原体检测和鉴定。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Aaron M. Mohs其他文献
Machine learning assisted identification of antibiotic-resistant emStaphylococcus aureus/em strains using a paper-based ratiometric sensor array
基于纸的比率传感器阵列的机器学习辅助鉴定耐抗生素金黄色葡萄球菌菌株
- DOI:
10.1016/j.microc.2024.111395 - 发表时间:
2024-11-01 - 期刊:
- 影响因子:5.100
- 作者:
Aayushi Laliwala;Ritika Gupta;Denis Svechkarev;Kenneth W. Bayles;Marat R. Sadykov;Aaron M. Mohs - 通讯作者:
Aaron M. Mohs
Aaron M. Mohs的其他文献
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{{ truncateString('Aaron M. Mohs', 18)}}的其他基金
Preclinical development of a novel antibody conjugate for intraoperative detection of pancreatic cancer
用于术中检测胰腺癌的新型抗体偶联物的临床前开发
- 批准号:
10584614 - 财政年份:2022
- 资助金额:
$ 34.31万 - 项目类别:
Preclinical development of a novel antibody conjugate for intraoperative detection of pancreatic cancer
用于术中检测胰腺癌的新型抗体偶联物的临床前开发
- 批准号:
10365729 - 财政年份:2022
- 资助金额:
$ 34.31万 - 项目类别:
Tunable Fluorescent Organic Nanoparticles for Cancer Imaging Applications
用于癌症成像应用的可调谐荧光有机纳米颗粒
- 批准号:
9230752 - 财政年份:2017
- 资助金额:
$ 34.31万 - 项目类别:
Hyaluronic Acid Based Nanoparticles for Targeted Image-Guided Tumor Surgery
用于靶向图像引导肿瘤手术的透明质酸纳米颗粒
- 批准号:
9071684 - 财政年份:2015
- 资助金额:
$ 34.31万 - 项目类别:
Hyaluronic Acid Based Nanoparticles for Targeted Image-Guided Tumor Surgery
用于靶向图像引导肿瘤手术的透明质酸纳米颗粒
- 批准号:
9110996 - 财政年份:2015
- 资助金额:
$ 34.31万 - 项目类别:
Hyaluronic Acid Based Nanoparticles for Targeted Image-Guided Tumor Surgery
用于靶向图像引导肿瘤手术的透明质酸纳米颗粒
- 批准号:
8800903 - 财政年份:2014
- 资助金额:
$ 34.31万 - 项目类别:
Nanotechnology for Minimally Invasive Cancer Detection and Resection
用于微创癌症检测和切除的纳米技术
- 批准号:
8413972 - 财政年份:2012
- 资助金额:
$ 34.31万 - 项目类别:
Nanotechnology for Minimally Invasive Cancer Detection and Resection
用于微创癌症检测和切除的纳米技术
- 批准号:
8628788 - 财政年份:2012
- 资助金额:
$ 34.31万 - 项目类别:
Nanotechnology for Minimally Invasive Cancer Detection and Resection
用于微创癌症检测和切除的纳米技术
- 批准号:
8456176 - 财政年份:2012
- 资助金额:
$ 34.31万 - 项目类别:
Nanotechnology for Minimally Invasive Cancer Detection and Resection
用于微创癌症检测和切除的纳米技术
- 批准号:
8137885 - 财政年份:2010
- 资助金额:
$ 34.31万 - 项目类别:
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