Single‐molecule localization microscopy (SMLM) has the potential to revolutionize proteomic and genomic analyses by providing information on the number and stoichiometry of proteins or nucleic acids aggregating at spatial scales below the diffraction limit of light. Here, a method for molecular counting is presented with SMLM built upon the exponentially distributed blinking statistics of photoswitchable fluorophores, with a focus on organic dyes. A guide to performing this newly developed technique is provided, highlighting many of the challenges and pitfalls, by benchmarking the method on fluorescently labeled, surface mounted DNA origami grids. The accuracy of the results illustrates SMLM's utility for optical “‐omics” analysis.

Single-molecule localization microscopy (SMLM) has the potential to revolutionize proteomic and genomic analyses by providing information on the number and stoichiometry of proteins or nucleic acids aggregating at spatial scales below the diffraction limit of light. Here we present a method for molecular counting with SMLM built upon the exponentially distributed blinking statistics of photoswitchable fluorophores, with a focus on organic dyes.We provide a practical guide to molecular counting, highlighting many of the challenges and pitfalls, by benchmarking the method on fluorescently labeled, surface mounted DNA origami grids. The accuracy of the results illustrates SMLM's utility for optical '-omics' analysis.

Single-molecule localization microscopy (SMLM) yields an image resolution 1-2 orders of magnitude below that of conventional light microscopy, resolving fine details on intracellular structure and macromolecular organization. The massive pointillistic data sets generated by SMLM require the development of new and highly e cient quantification tools. Density based clustering algorithms, such as DBSCAN, can provide spatial statistics on protein/nucleic acid aggregation or dispersion while explicitly identifying macromolecular clusters. The performance of DBSCAN, however, is typically dependent upon an arbitrary, or at least highly subjective, parametric tuning of the algorithm. Moreover, DBSCAN can be computationally expensive, which makes it arduous to evaluate on large image stacks. This is all the more important in 3-dimensions where there exist limited alternatives for quantifying clustering in SMLM data, and where a 2-dimensional analysis of true 3-dimensional data may give rise to image artefacts. We have developed an open-source software package in Python for both identifying and quantifying spatial clustering in 3-dimensional SMLM datasets. FOCAL3D is an extension of our previously developed, 2-dimensional, grid based clustering algorithm FOCAL. FOCAL3D provides a highly e cient way to spatially cluster SMLM datasets, scaling linearly with the number of localizations, and the algorithmic parameters may be systematically optimized so that the resulting analysis is insensitive to variation over a range of parameter choices. We initially validate the performance and parametric insensitivity of FOCAL3D on simulated datasets, then apply the algorithm to 3-dimensional, astigmatic dSTORM images of the nuclear pore complex in human osteosarcoma cells.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium ( 2 H) MRS. Following treatment, changes in the 2 H-labelled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2 H-labelled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukaemia (AML) cells, which had been treated with 10 μg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 h after cisplatin treatment the cells were supplied with 20 mM of [6,6 0 -2 H 2 ]glucose and scanned over 2 h using a two-dimensional 2 H MR spectroscopic imaging sequence. The resulting signals from 2 H-labelled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the Oxford Spectroscopy Analysis MATLAB toolbox. After scanning, the cells were processed for histological stains (terminal deoxynucleotidyl transferase UTP nick end labelling and haematoxylin and eosin) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2 H-labelled lactate were observed in the 48 h treated cells compared with the untreated and 24 h treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2 H-labelled lactate signal, these findings suggest that 2 H MRS of lactate may be valuable in evaluating early tumour response.

Single-molecule localization microscopy (SMLM) is a powerful tool for studying intracellular structure and macromolecular organization at the nanoscale. The increasingly massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Here we present FOCAL3D, an accurate, flexible and exceedingly fast (scaling linearly with the number of localizations) density-based algorithm for quantifying spatial clustering in large 3D SMLM data sets. Unlike DBSCAN, which is perhaps the most commonly employed density-based clustering algorithm, an optimum set of parameters for FOCAL3D may be objectively determined. We initially validate the performance of FOCAL3D on simulated datasets at varying noise levels and for a range of cluster sizes. These simulated datasets are used to illustrate the parametric insensitivity of the algorithm, in contrast to DBSCAN, and clustering metrics such as the F1 and Silhouette score indicate that FOCAL3D is highly accurate, even in the presence of significant background noise and mixed populations of variable sized clusters, once optimized. We then apply FOCAL3D to 3D astigmatic dSTORM images of the nuclear pore complex (NPC) in human osteosaracoma cells, illustrating both the validity of the parameter optimization and the ability of the algorithm to accurately cluster complex, heterogeneous 3D clusters in a biological dataset. FOCAL3D is provided as an open source software package written in Python.

Stereotactic radiosurgery for the treatment of brain metastases delivers a high dose of radiation with excellent local control, but increases the likelihood of radiation necrosis. As shown in our previous work, saturation transfer MRI, consisting of quantitative magnetization transfer (qMT) and chemical exchange saturation transfer (CEST), is a promising technique for distinguishing radiation necrosis (RN) from tumour progression (TP) in brain metastases. A 3D qMT/CEST acquisition was recently implemented and over 100 patients have been scanned to date. The purpose of this work is to assess the ability of advanced MRI parameters, including qMT and CEST metrics, which are sensitive to macromolecules and metabolism. The specific metrics that were explored included the amide and NOE contributions of the magnetization transfer ratio (MTR), the MTR asymmetry, the apparent exchange-dependent relaxation (AREX), the qMT semi-solid pool fraction and the T1 and T2 relaxation times. For a subset of the patients, dynamic susceptibility contrast (DSC) perfusion images were acquired. Examples of confirmed tumour progression and radiation necrosis cases will be presented, comparing the structural images (pre- and post-contrast T1-weighted and FLAIR images) with parameter maps from qMT and CEST and also the relative cerebral blood flow (rCBF) from DSC perfusion imaging. Interim cohort results will be presented. Approaches for standardizing the parameters across multiple MRI vendors are also explored.

Modeling diffusion that incorporates the microscopic partially absorbing wall is a more realistic description compared to the standard Bloch equation based two-site model with exchange. The resulting signal equations are more complex and involve working in the Laplace domain. Here, we demonstrate that the increased spatial relevance of the partially absorbing wall model does not improve fitting in our AML model treated with cisplatin for cell death. In fact, the partially absorbing wall model fits and parameters are poorer. Therefore, extracting diffusion parameters from the Bloch equation based two-site exchange model is sufficient for our diffusion MRI datasets.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium ( 2H) magnetic resonance spectroscopy (MRS). Following treatment, changes in the 2H-labeled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2H-labeled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukemia cells which had been treated with 10 μg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 hours after cisplatin treatment, the cells were injected with 20 mM of [6,6′-2H2]glucose and scanned over two hours using a two-dimensional 2H MR spectroscopic imaging sequence. The resulting signals from 2H-labeled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the OXford Spectroscopy Analysis (OXSA) MATLAB toolbox. After scanning, the cells were processed for histological stains (TUNEL [terminal deoxynucleotidyl transferase UTP nick end labeling] and H&E [hematoxylin and eosin]) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2H-labeled lactate were observed in the 48-hour treated cells compared to the untreated and 24-hour treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2H-labeled lactate signal, these findings suggest that 2H MRS of lactate may be valuable in evaluating early tumour response.