FISIK: Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data

Mapping Intimacies ◽

10.1101/530063 ◽

2019 ◽

Author(s):

Luciana R. de Oliveira ◽

Khuloud Jaqaman

Keyword(s):

Single Molecule ◽

Molecular Interaction ◽

Model Parameters ◽

Single Molecule Imaging ◽

Imaging Data ◽

Tracking Errors ◽

Spatiotemporal Resolution ◽

Wide Range ◽

Interaction Kinetics

AbstractRecent experimental and computational developments have been pushing the limits of live-cell single-molecule imaging, enabling the monitoring of inter-molecular interactions in their native environment with high spatiotemporal resolution. However, interactions are captured only for the labeled subset of molecules, which tends to be a small fraction. As a result, it has remained a challenge to calculate molecular interaction kinetics, in particular association rates, from single-molecule tracking data. To overcome this challenge, we developed a mathematical modeling-based Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data (termed “FISIK”). FISIK consists of (1) devising a mathematical model of molecular movement and interactions, mimicking the biological system and data-acquisition setup, and (2) estimating the unknown model parameters, including molecular association and dissociation rates, by fitting the model to experimental single-molecule data. Due to the stochastic nature of the model and data, we adapted the method of indirect inference for model calibration. We validated FISIK using a series of tests, where we simulated trajectories of diffusing molecules that interact with each other, considering a wide range of model parameters, and including resolution limitations and tracking errors. We found that FISIK has the sensitivity to determine association and dissociation rates, where its accuracy depends on the labeled fraction of molecules and the extent of molecule tracking errors. For cases where the labeled fraction is relatively low (e.g. to afford accurate tracking), combining dynamic but sparse single-molecule imaging data with almost whole-population oligomer distribution data improves FISIK’s performance. All in all, FISIK is a promising approach for the derivation of molecular interaction kinetics in their native environment from single-molecule imaging data.

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FISIK: Framework for the Inference of In Situ Interaction Kinetics from Single-Molecule Imaging Data

Biophysical Journal ◽

10.1016/j.bpj.2018.11.1557 ◽

2019 ◽

Vol 116 (3) ◽

pp. 288a

Author(s):

Luciana R. de Oliveira ◽

Robel Yirdaw ◽

Khuloud Jaqaman

Keyword(s):

Single Molecule ◽

Single Molecule Imaging ◽

Imaging Data ◽

Interaction Kinetics

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FISIK: Framework for the Inference of In Situ Interaction Kinetics from Single-Molecule Imaging Data

Biophysical Journal ◽

10.1016/j.bpj.2019.07.050 ◽

2019 ◽

Vol 117 (6) ◽

pp. 1012-1028 ◽

Cited By ~ 2

Author(s):

Luciana R. de Oliveira ◽

Khuloud Jaqaman

Keyword(s):

Single Molecule ◽

Single Molecule Imaging ◽

Imaging Data ◽

Interaction Kinetics

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Coupled Thermo-Hydro-Geochemical Models of Engineered Barrier Systems: The Febex Project

MRS Proceedings ◽

10.1557/proc-663-561 ◽

2000 ◽

Vol 663 ◽

Cited By ~ 2

Author(s):

J. Samper ◽

R. Juncosa ◽

V. Navarro ◽

J. Delgado ◽

L. Montenegro ◽

...

Keyword(s):

Large Scale ◽

Reference Model ◽

Numerical Models ◽

Full Scale ◽

Small Scale ◽

Model Parameters ◽

In Situ Test ◽

Wide Range ◽

Engineered Barrier

ABSTRACTFEBEX (Full-scale Engineered Barrier EXperiment) is a demonstration and research project dealing with the bentonite engineered barrier designed for sealing and containment of waste in a high level radioactive waste repository (HLWR). It includes two main experiments: an situ full-scale test performed at Grimsel (GTS) and a mock-up test operating since February 1997 at CIEMAT facilities in Madrid (Spain) [1,2,3]. One of the objectives of FEBEX is the development and testing of conceptual and numerical models for the thermal, hydrodynamic, and geochemical (THG) processes expected to take place in engineered clay barriers. A significant improvement in coupled THG modeling of the clay barrier has been achieved both in terms of a better understanding of THG processes and more sophisticated THG computer codes. The ability of these models to reproduce the observed THG patterns in a wide range of THG conditions enhances the confidence in their prediction capabilities. Numerical THG models of heating and hydration experiments performed on small-scale lab cells provide excellent results for temperatures, water inflow and final water content in the cells [3]. Calculated concentrations at the end of the experiments reproduce most of the patterns of measured data. In general, the fit of concentrations of dissolved species is better than that of exchanged cations. These models were later used to simulate the evolution of the large-scale experiments (in situ and mock-up). Some thermo-hydrodynamic hypotheses and bentonite parameters were slightly revised during TH calibration of the mock-up test. The results of the reference model reproduce simultaneously the observed water inflows and bentonite temperatures and relative humidities. Although the model is highly sensitive to one-at-a-time variations in model parameters, the possibility of parameter combinations leading to similar fits cannot be precluded. The TH model of the “in situ” test is based on the same bentonite TH parameters and assumptions as for the “mock-up” test. Granite parameters were slightly modified during the calibration process in order to reproduce the observed thermal and hydrodynamic evolution. The reference model captures properly relative humidities and temperatures in the bentonite [3]. It also reproduces the observed spatial distribution of water pressures and temperatures in the granite. Once calibrated the TH aspects of the model, predictions of the THG evolution of both tests were performed. Data from the dismantling of the in situ test, which is planned for the summer of 2001, will provide a unique opportunity to test and validate current THG models of the EBS.

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Determining Receptor Interaction Kinetics through Single Molecule Imaging and Computational Modeling

Biophysical Journal ◽

10.1016/j.bpj.2017.11.3662 ◽

2018 ◽

Vol 114 (3) ◽

pp. 679a

Author(s):

Luciana R. de Oliveira ◽

Robel Yirdaw ◽

Khuloud Jaqaman

Keyword(s):

Computational Modeling ◽

Single Molecule ◽

Receptor Interaction ◽

Single Molecule Imaging ◽

Interaction Kinetics

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Construction of Dual-Color Probes with Target-Triggered Signal Amplification for In Situ Single-Molecule Imaging of MicroRNA

ACS Nano ◽

10.1021/acsnano.0c01061 ◽

2020 ◽

Vol 14 (7) ◽

pp. 8116-8125

Author(s):

Binxiao Li ◽

Yujie Liu ◽

Yixin Liu ◽

Tongtong Tian ◽

Beibei Yang ◽

...

Keyword(s):

Single Molecule ◽

Signal Amplification ◽

Single Molecule Imaging ◽

Dual Color

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High-performance multiplexed fluorescence in situ hybridization in culture and tissue with matrix imprinting and clearing

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1617699113 ◽

2016 ◽

Vol 113 (50) ◽

pp. 14456-14461 ◽

Cited By ~ 103

Author(s):

Jeffrey R. Moffitt ◽

Junjie Hao ◽

Dhananjay Bambah-Mukku ◽

Tian Lu ◽

Catherine Dulac ◽

...

Keyword(s):

In Situ Hybridization ◽

Single Molecule ◽

High Performance ◽

Detection Efficiency ◽

Tissue Samples ◽

Spatially Resolved ◽

Wide Range ◽

Cellular Context ◽

Target Binding

Highly multiplexed single-molecule FISH has emerged as a promising approach to spatially resolved single-cell transcriptomics because of its ability to directly image and profile numerous RNA species in their native cellular context. However, background—from off-target binding of FISH probes and cellular autofluorescence—can become limiting in a number of important applications, such as increasing the degree of multiplexing, imaging shorter RNAs, and imaging tissue samples. Here, we developed a sample clearing approach for FISH measurements. We identified off-target binding of FISH probes to cellular components other than RNA, such as proteins, as a major source of background. To remove this source of background, we embedded samples in polyacrylamide, anchored RNAs to this polyacrylamide matrix, and cleared cellular proteins and lipids, which are also sources of autofluorescence. To demonstrate the efficacy of this approach, we measured the copy number of 130 RNA species in cleared samples using multiplexed error-robust FISH (MERFISH). We observed a reduction both in the background because of off-target probe binding and in the cellular autofluorescence without detectable loss in RNA. This process led to an improved detection efficiency and detection limit of MERFISH, and an increased measurement throughput via extension of MERFISH into four color channels. We further demonstrated MERFISH measurements of complex tissue samples from the mouse brain using this matrix-imprinting and -clearing approach. We envision that this method will improve the performance of a wide range of in situ hybridization-based techniques in both cell culture and tissues.

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In Situ Single-Molecule Imaging with Attoliter Detection Using Objective Total Internal Reflection Confocal Microscopy†

Biochemistry ◽

10.1021/bi052097d ◽

2006 ◽

Vol 45 (13) ◽

pp. 4058-4068 ◽

Cited By ~ 24

Author(s):

Thomas P. Burghardt ◽

Katalin Ajtai ◽

Julian Borejdo

Keyword(s):

Confocal Microscopy ◽

Single Molecule ◽

Total Internal Reflection ◽

Internal Reflection ◽

Single Molecule Imaging

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Agent-based modelling of complex factors impacting malaria prevalence

Malaria Journal ◽

10.1186/s12936-021-03721-2 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Miracle Amadi ◽

Anna Shcherbacheva ◽

Heikki Haario

Keyword(s):

Malaria Transmission ◽

Field Data ◽

Control Measures ◽

Model Parameters ◽

Economic Factors ◽

Agent Based ◽

Wide Range ◽

The Impact ◽

Socio Economic Factors

Abstract Background Increasingly complex models have been developed to characterize the transmission dynamics of malaria. The multiplicity of malaria transmission factors calls for a realistic modelling approach that incorporates various complex factors such as the effect of control measures, behavioural impacts of the parasites to the vector, or socio-economic variables. Indeed, the crucial impact of household size in eliminating malaria has been emphasized in previous studies. However, increasing complexity also increases the difficulty of calibrating model parameters. Moreover, despite the availability of much field data, a common pitfall in malaria transmission modelling is to obtain data that could be directly used for model calibration. Methods In this work, an approach that provides a way to combine in situ field data with the parameters of malaria transmission models is presented. This is achieved by agent-based stochastic simulations, initially calibrated with hut-level experimental data. The simulation results provide synthetic data for regression analysis that enable the calibration of key parameters of classical models, such as biting rates and vector mortality. In lieu of developing complex dynamical models, the approach is demonstrated using most classical malaria models, but with the model parameters calibrated to account for such complex factors. The performance of the approach is tested against a wide range of field data for Entomological Inoculation Rate (EIR) values. Results The overall transmission characteristics can be estimated by including various features that impact EIR and malaria incidence, for instance by reducing the mosquito–human contact rates and increasing the mortality through control measures or socio-economic factors. Conclusion Complex phenomena such as the impact of the coverage of the population with long-lasting insecticidal nets (LLINs), changes in behaviour of the infected vector and the impact of socio-economic factors can be included in continuous level modelling. Though the present work should be interpreted as a proof of concept, based on one set of field data only, certain interesting conclusions can already be drawn. While the present work focuses on malaria, the computational approach is generic, and can be applied to other cases where suitable in situ data is available.

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Multiplexed imaging of high density libraries of RNAs with MERFISH and expansion microscopy

10.1101/238899 ◽

2017 ◽

Cited By ~ 1

Author(s):

Guiping Wang ◽

Jeffrey R. Moffitt ◽

Xiaowei Zhuang

Keyword(s):

Single Molecule ◽

Detection Efficiency ◽

High Abundance ◽

Total Density ◽

Accurate Identification ◽

Rna Molecules ◽

Wide Range ◽

Multiplexed Imaging ◽

Labeling Approach

AbstractAs an image-based single-cell transcriptomics approach, multiplexed error-robust fluorescence in situ hybridization (MERFISH) allows hundreds to thousands of RNA species to be identified, counted and localized in individual cells while preserving the native spatial context of RNAs. In MERFISH, RNAs are identified via a combinatorial labeling approach that encodes RNA species with error-robust barcodes followed by sequential rounds of single-molecule FISH (smFISH) to read out these barcodes. The accuracy of RNA identification relies on spatially separated signals from individual RNA molecules, which limits the density of RNAs that can be measured and makes the multiplexed imaging of a large number of high-abundance RNAs challenging. Here we report an approach that combines MERFISH and expansion microscopy to substantially increase the total density of RNAs that can be measured. Using this approach, we demonstrate accurate identification and counting of RNAs, with a near 100% detection efficiency, in a ~130-RNA library composed of many high-abundance RNAs, the total density of which is more than 10 fold higher than previously reported. In parallel, we demonstrate the combination of MERFISH with immunofluorescence. These advances increase the versatility of MERFISH and will facilitate its application of a wide range of biological problems.

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