Thomas Pengo

Quantitative evaluation of software packages for single-molecule localization microscopy.

The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.

High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization

Significance The bacterial cytoskeletal protein FtsZ, which forms a constricting “Z-ring” during cell division, is the major cytoskeletal protein involved in cell division in almost all prokaryotes, and is a key next-generation antibiotic target. However, the small size of the Z-ring, approximately 500 nm in diameter, makes it difficult to observe in vivo. We provide a quantitative nanoscale picture of Z-ring organization in live cells; these results improve our understanding of the structural and force-generating roles of FtsZ in bacterial cell division. To achieve this, we created an automated modality of superresolution fluorescence microscopy, allowing high-throughput live cell microscopy at nanoscale resolution; this technique should be broadly useful in prokaryotic and eukaryotic systems. We created a high-throughput modality of photoactivated localization microscopy (PALM) that enables automated 3D PALM imaging of hundreds of synchronized bacteria during all stages of the cell cycle. We used high-throughput PALM to investigate the nanoscale organization of the bacterial cell division protein FtsZ in live Caulobacter crescentus. We observed that FtsZ predominantly localizes as a patchy midcell band, and only rarely as a continuous ring, supporting a model of “Z-ring” organization whereby FtsZ protofilaments are randomly distributed within the band and interact only weakly. We found evidence for a previously unidentified period of rapid ring contraction in the final stages of the cell cycle. We also found that DNA damage resulted in production of high-density continuous Z-rings, which may obstruct cytokinesis. Our results provide a detailed quantitative picture of in vivo Z-ring organization.

Quantitative super-resolution imaging reveals protein stoichiometry and nanoscale morphology of assembling HIV-gag virions

The HIV structural protein Gag assembles to form spherical particles of radius ∼70 nm. During the assembly process, the number of Gag proteins increases over several orders of magnitude from a few at nucleation to thousands at completion. The challenge in studying protein assembly lies in the fact that current methods such as standard fluorescence or electron microscopy techniques cannot access all stages of the assembly process in a cellular context. Here, we demonstrate an approach using super-resolution fluorescence imaging that permits quantitative morphological and molecular counting analysis over a wide range of protein cluster sizes. We applied this technique to the analysis of hundreds of HIV-Gag clusters at the cellular plasma membrane, thus elucidating how different fluorescent labels can change the assembly of virions.

Halton sampling for autofocus

Reliable autofocusing is a critical part of any automated microscopy system: by precisely positioning the sample in the focal plane, the acquired images are sharp and can be accurately segmented and quantified. The three main components of an autofocus algorithm are a contrast function, an optimization algorithm and a sampling strategy. The latter has not been given much attention in the literature. It is however a very important part of the autofocusing algorithm, especially in high content and high throughput image‐based screening. It deals with the problem of sampling the focus surface as sparsely as possible to reduce bleaching and computation time while with sufficient detail as to permit a faithful interpolation. We propose a new strategy that has higher performance compared to the classical square grid or the hexagonal lattice, which is based on the concept of low discrepancy point sets and in particular on the Halton point set. We tested the new algorithm on nine different focus surfaces, each under 24 different combinations of Signal‐to‐Noise ratio (SNR) and sampling rate, obtaining that in 88% of the tested conditions, Halton sampling outperforms its counterparts.

Defined chromosome structure in the genome-reduced bacterium Mycoplasma pneumoniae

DNA-binding proteins are central regulators of chromosome organization; however, in genome-reduced bacteria their diversity is largely diminished. Whether the chromosomes of such bacteria adopt defined three-dimensional structures remains unexplored. Here we combine Hi-C and super-resolution microscopy to determine the structure of the Mycoplasma pneumoniae chromosome at a 10 kb resolution. We find a defined structure, with a global symmetry between two arms that connect opposite poles, one bearing the chromosomal Ori and the other the midpoint. Analysis of local structures at a 3 kb resolution indicates that the chromosome is organized into domains ranging from 15 to 33 kb. We provide evidence that genes within the same domain tend to be co-regulated, suggesting that chromosome organization influences transcriptional regulation, and that supercoiling regulates local organization. This study extends the current understanding of bacterial genome organization and demonstrates that a defined chromosomal structure is a universal feature of living systems.

PALMsiever: a tool to turn raw data into results for single-molecule localization microscopy

During the past decade, localization microscopy (LM) has transformed into an accessible, commercially available technique for life sciences. However, data processing can be challenging to the non-specialist and care is still needed to produce meaningful results. PALMsiever has been developed to provide a user-friendly means of visualizing, filtering and analyzing LM data. It includes drift correction, clustering, intelligent line profiles, many rendering algorithms and 3D data visualization. It incorporates the main analysis and data processing modalities used by experts in the field, as well as several new features we developed, and makes them broadly accessible. It can easily be extended via plugins and is provided as free of charge open-source software. Contact: thomas.pengo@gmail.com

Efficient Blind Spectral Unmixing of Fluorescently Labeled Samples Using Multi-Layer Non-Negative Matrix Factorization

The ample variety of labeling dyes and staining methods available in fluorescence microscopy has enabled biologists to advance in the understanding of living organisms at cellular and molecular level. When two or more fluorescent dyes are used in the same preparation, or one dye is used in the presence of autofluorescence, the separation of the fluorescent emissions can become problematic. Various approaches have been recently proposed to solve this problem. Among them, blind non-negative matrix factorization is gaining interest since it requires little assumptions about the spectra and concentration of the fluorochromes. In this paper, we propose a novel algorithm for blind spectral separation that addresses some of the shortcomings of existing solutions: namely, their dependency on the initialization and their slow convergence. We apply this new algorithm to two relevant problems in fluorescence microscopy: autofluorescence elimination and spectral unmixing of multi-labeled samples. Our results show that our new algorithm performs well when compared with the state-of-the-art approaches for a much faster implementation.

Cytotoxic T-cells and granzyme B associated with improved colorectal cancer survival in a prospective cohort of older women.

Background: Host immune response may predict the course of colorectal cancer. We examined the survival of 468 colorectal cancer patients associated with two tumor-infiltrating immune biomarkers, the number of cytotoxic T lymphocytes (CTLs), and the activated CTLs, as reflected by the number of cells expressing granzyme B (GZMB) in the prospective Iowa Womens Health Study. Methods: Using paraffin-embedded tissue samples, we constructed and immunostained tumor microarrays with CD8 (for CTL) and GZMB antibodies. We scored CTL and GZMB densities in tumor epithelial and stromal tissues and also created a composite score for each biomarker (sum of the scores across tissue compartments). Cox regression estimated the HR and 95% confidence intervals (CI) for all-cause and colorectal cancer–specific death associated with each composite score. Results: CTL and GZMB composite scores were positively correlated (r = 0.65) and each biomarker was inversely correlated with stage at diagnosis. Both composite scores were higher in proximal colon tumors and tumors characterized by MSI-high, CIMP-high, or BRAF mutation status. HRs (95% CI) were 0.53 (0.38–0.75; Ptrend = 0.0004) and 0.66 (0.51–0.86; Ptrend = 0.002) for all-cause death, respectively, and 0.30 (0.18–0.51; Ptrend < 0.0001) and 0.41 (0.27–0.63; Ptrend < 0.0001) for colorectal cancer–related death, respectively. Including CTL and GZMB scores simultaneously in the model significantly improved the predictive performance of the models for all-cause and colorectal cancer–related death. Conclusions: Higher tumor infiltration with CTL and GZMB cells is associated with improved all-cause and cancer-specific survival of colorectal cancer patients. Impact: Both the number of CTLs and GZMB appear to be useful prognostic factors in colorectal cancer, irrespective of stage. Cancer Epidemiol Biomarkers Prev; 26(4); 622–31. ©2016 AACR.

Computer Assisted Detection of Cancer Cells in Minimal Samples of Lung Cancer

We present and validate a quantitative, multidimensional image analysis protocol to assist in the early detection of lung cancer in minimal samples of bronchoalveolar lavage (BAL). To that end we stained BAL samples using Fluorescence Immunophenotyping and Interphase Cytogenetics as a Tool for the Investigation of Neoplasms (FICTION). Our method allows preliminary immunophenotypic detection of rare cancerous candidate cells, followed by accurate three-dimensional analysis of genomic integrity, to confirm or refute the initial assessment. Our results show that our automated analysis can accurately assist a human expert in the diagnostic evaluation of BAL samples.

Photon migration simulator for fluorescence tomography

Analytically predicting photon paths in real-high scattering-anisotropic tissues is extremely complex, due to the significant random scattering events that photons suffer as they traverse the tissue, especially at boundaries between areas with different optical properties. An statistically correct optical and anatomical model of photon trajectories inside laboratory animals will therefore improve considerably our understanding about how light diffuses within the animals, and therefore help us designing efficient experimental setups and reconstruction algorithms for fluorescence mediated tomography (FMT). Here, we present new simulations of photon propagation and fluorescence emission in anisotropic media using realistic models of laboratory animals and a Monte Carlo (MC) based approach. We compare the MC simulation results with an approximation of the solution of the diffusion equation using finite differences and discuss the different behaviour of the two methods.