Anti-Aspergillus activities of olorofim at sub-MIC levels during early-stage growth

Olorofim, the first member of the novel class of antifungal drugs, the orotomides, shows promising anti-Aspergillus activity and is currently in phase III clinical development. Using high-throughput microscopy, we monitored olorofim's antifungal potential at sub-minimum inhibitory concentration (MIC) levels with a focus on early-stage growth. Unlike voriconazole, olorofim showed significant growth inhibitory activities against three main pathogenic Aspergillus species, Aspergillus fumigatus, Aspergillus flavus, and Aspergillus niger, at concentrations >100,000-fold below its MIC.

IMPORTANCE

Among antifungal compounds in clinical development for systemic disease, the orotomide olorofim is one of only two that target a completely new mechanism of action. Olorofim is highly potent against pathogenic Aspergillus species including cryptic species that frequently show increased resistance to current agents. In this study, our primary focus was on evaluating in detail the inhibitory activity of voriconazole and olorofim against different pathogenic Aspergillus species employing high-throughput microscopy. Compared to standardized, less-sensitive visual assessment-based methods, microscopy-assisted growth monitoring allowed us to detect sub-MIC drug concentration ranges with significant inhibitory activity at early-stage growth. This revealed that olorofim exerts growth inhibition at concentrations that are several magnitudes below those of voriconazole.

Cells infected with human papilloma pseudovirus display nuclear reorganization and heterogenous infection kinetics

Human papillomaviruses (HPV) are small, non-enveloped DNA viruses, which upon chronic infection can provoke cervical and head-and-neck cancers. Although the infectious life cycle of HPV has been studied and a vaccine is available for the most prevalent cancer-causing HPV types, there are no antiviral agents to treat infected patients. Hence, there is a need for novel therapeutic entry points and a means to identify them. In this work, we have used high-content microscopy to quantitatively investigate the early phase of HPV infection. Human cervical cancer cells and immortalized keratinocytes were exposed to pseudoviruses (PsV) of the widespread HPV type 16, in which the viral genome was replaced by a pseudogenome encoding a fluorescent reporter protein. Using the fluorescent signal as readout, we measured differences in infection between cell lines, which directly correlated with host cell proliferation rate. Parallel multiparametric analysis of nuclear organization revealed that HPV PsV infection alters nuclear organization and inflates promyelocytic leukemia protein body content, positioning these events at the early stage of HPV infection, upstream of viral replication. Time-resolved analysis revealed a marked heterogeneity in infection kinetics even between two daughter cells, which we attribute to differences in viral load. Consistent with the requirement for mitotic nuclear envelope breakdown, pharmacological inhibition of the cell cycle dramatically blunted infection efficiency. Thus, by systematic image-based single cell analysis, we revealed phenotypic alterations that accompany HPV PsV infection in individual cells, and which may be relevant for therapeutic drug screens.

Multi-foci parallelised RESOLFT nanoscopy in an extended field-of-view

Live-cell imaging of biological structures at high resolution poses challenges in the microscope throughput regarding area and speed. For this reason, different parallelisation strategies have been implemented in coordinate- and stochastic-targeted switching super-resolution microscopy techniques. In this line, the molecular nanoscale live imaging with sectioning ability (MoNaLISA), based on reversible saturable optical fluorescence transitions (RESOLFT), offers 45 - 65 nm $45 - 65\;{\rm{nm}}$ resolution of large fields of view in a few seconds. In MoNaLISA, engineered light patterns strategically confine the fluorescence to sub-diffracted volumes in a large area and provide optical sectioning, thus enabling volumetric imaging at high speeds. The optical setup presented in this paper extends the degree of parallelisation of the MoNaLISA microscope by more than four times, reaching a field-of-view of ( 100 - 130 μ m ) 2 ${( {100 - 130\;{\rm{\mu m}}} )^2}$ . We set up the periodicity and the optical scheme of the illumination patterns to be power-efficient and homogeneous. In a single recording, this new configuration enables super-resolution imaging of an extended population of the post-synaptic density protein Homer1c in living hippocampal neurons.

From imaging a single cell to implementing precision medicine: an exciting new era

In the age of high-throughput, single-cell biology, single-cell imaging has evolved not only in terms of technological advancements but also in its translational applications. The synchronous advancements of imaging and computational biology have produced opportunities of merging the two, providing the scientific community with tools towards observing, understanding, and predicting cellular and tissue phenotypes and behaviors. Furthermore, multiplexed single-cell imaging and machine learning algorithms now enable patient stratification and predictive diagnostics of clinical specimens. Here, we provide an overall summary of the advances in single-cell imaging, with a focus on high-throughput microscopy phenomics and multiplexed proteomic spatial imaging platforms. We also review various computational tools that have been developed in recent years for image processing and downstream applications used in biomedical sciences. Finally, we discuss how harnessing systems biology approaches and data integration across disciplines can further strengthen the exciting applications and future implementation of single-cell imaging on precision medicine.

Dissecting Neuronal Activation on a Brain-Wide Scale With Immediate Early Genes

Visualizing neuronal activation on a brain-wide scale yet with cellular resolution is a fundamental technical challenge for neuroscience. This would enable analyzing how different neuronal circuits are disrupted in pathology and how they could be rescued by pharmacological treatments. Although this goal would have appeared visionary a decade ago, recent technological advances make it eventually feasible. Here, we review the latest developments in the fields of genetics, sample preparation, imaging, and image analysis that could be combined to afford whole-brain cell-resolution activation mapping. We show how the different biochemical and optical methods have been coupled to study neuronal circuits at different spatial and temporal scales, and with cell-type specificity. The inventory of techniques presented here could be useful to find the tools best suited for a specific experiment. We envision that in the next years, mapping of neuronal activation could become routine in many laboratories, allowing dissecting the neuronal counterpart of behavior.

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals

Cell-to-cell variation of protein expression in genetically homogeneous populations is a common biological trait often neglected during analysis of high-throughput (HT) screens and is rarely used as a metric to characterize chemicals. We have captured single-cell distributions of androgen receptor (AR) nuclear levels after perturbations as a means to evaluate assay reproducibility and characterize a small subset of chemicals. AR, a member of the nuclear receptor family of transcription factors, is the central regulator of male reproduction and is involved in many pathophysiological processes. AR protein levels and nuclear localization often increase following ligand binding, with dihydrotestosterone (DHT) being the natural agonist. HT AR immunofluorescence imaging was used in multiple cell lines to define single-cell nuclear values extracted from thousands of cells per condition treated with DHT or DMSO (control). Analysis of numerous biological replicates led to a quality control metric that takes into account the distribution of single-cell data, and how it changes upon treatments. Dose-response experiments across several cell lines showed a large range of sensitivity to DHT, prompting us to treat selected cell lines with 45 Environmental Protection Agency (EPA)-provided chemicals that include many endocrine-disrupting chemicals (EDCs); data from six of the compounds were then integrated with orthogonal assays. Our comprehensive results indicate that quantitative single-cell distribution analysis of AR protein levels is a valid method to detect the potential androgenic and antiandrogenic actions of environmentally relevant chemicals in a sensitive and reproducible manner.

Image-Based Dynamic Phenotyping Reveals Genetic Determinants of Filamentation-Mediated β-Lactam Tolerance

Antibiotic tolerance characterized by slow killing of bacteria in response to a drug can lead to treatment failure and promote the emergence of resistance. β-lactam antibiotics inhibit cell wall growth in bacteria and many of them cause filamentation followed by cell lysis. Hence delayed cell lysis can lead to β-lactam tolerance. Systematic discovery of genetic factors that affect β-lactam killing kinetics has not been performed before due to challenges in high-throughput, dynamic analysis of viability of filamented cells during bactericidal action. We implemented a high-throughput time-resolved microscopy approach in a gene deletion library of Escherichia coli to monitor the response of mutants to the β-lactam cephalexin. Changes in frequency of lysed and intact cells due to the antibiotic action uncovered several strains with atypical lysis kinetics. Filamentation confers tolerance because antibiotic removal before lysis leads to recovery through numerous concurrent divisions of filamented cells. Filamentation-mediated tolerance was not associated with resistance, and therefore this phenotype is not discernible through most antibiotic susceptibility methods. We find that deletion of Tol-Pal proteins TolQ, TolR, or Pal but not TolA, TolB, or CpoB leads to rapid killing by β-lactams. We also show that the timing of cell wall degradation determines the lysis and killing kinetics after β-lactam treatment. Altogether, this study uncovers numerous genetic determinants of hitherto unappreciated filamentation-mediated β-lactam tolerance and support the growing call for considering antibiotic tolerance in clinical evaluation of pathogens. More generally, the microscopy screening methodology described here can easily be adapted to study lysis in large numbers of strains.

Dual-beam confocal light-sheet microscopy via flexible acousto-optic deflector

Confocal detection in digital scanned laser light-sheet fluorescence microscopy (DSLM) has been established as a gold standard method to improve image quality. The selective line detection of a complementary metal–oxide–semiconductor camera (CMOS) working in rolling shutter mode allows the rejection of out-of-focus and scattered light, thus reducing background signal during image formation. Most modern CMOS have two rolling shutters, but usually only a single illuminating beam is used, halving the maximum obtainable frame rate. We report on the capability to recover the full image acquisition rate via dual confocal DSLM by using an acousto-optic deflector. Such a simple solution enables us to independently generate, control and synchronize two beams with the two rolling slits on the camera. We show that the doubling of the imaging speed does not affect the confocal detection high contrast.

From observing to predicting single-cell structure and function with high-throughput/high-content microscopy

In the past 15 years, cell-based microscopy has evolved its focus from observing cell function to aiming to predict it. In particular-powered by breakthroughs in computer vision, large-scale image analysis and machine learning-high-throughput and high-content microscopy imaging have enabled to uniquely harness single-cell information to systematically discover and annotate genes and regulatory pathways, uncover systems-level interactions and causal links between cellular processes, and begin to clarify and predict causal cellular behaviour and decision making. Here we review these developments, discuss emerging trends in the field, and describe how single-cell 'omics and single-cell microscopy are imminently in an intersecting trajectory. The marriage of these two fields will make possible an unprecedented understanding of cell and tissue behaviour and function.

Large-scale image-based screening and profiling of cellular phenotypes

Cellular phenotypes are observable characteristics of cells resulting from the interactions of intrinsic and extrinsic chemical or biochemical factors. Image-based phenotypic screens under large numbers of basal or perturbed conditions can be used to study the influences of these factors on cellular phenotypes. Hundreds to thousands of phenotypic descriptors can also be quantified from the images of cells under each of these experimental conditions. Therefore, huge amounts of data can be generated, and the analysis of these data has become a major bottleneck in large-scale phenotypic screens. Here, we review current experimental and computational methods for large-scale image-based phenotypic screens. Our focus is on phenotypic profiling, a computational procedure for constructing quantitative and compact representations of cellular phenotypes based on the images collected in these screens. © 2016 International Society for Advancement of Cytometry.

High-Content Screening for Quantitative Cell Biology

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future.

Pipeline for illumination correction of images for high-throughput microscopy

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements.

In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z′-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument.

To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments.

Analysis of the influence of cell heterogeneity on nanoparticle dose response

Understanding the effect of variability in the interaction of individual cells with nanoparticles on the overall response of the cell population to a nanoagent is a fundamental challenge in bionanotechnology. Here, we show that the technique of time-resolved, high-throughput microscopy can be used in this endeavor. Mass measurement with single-cell resolution provides statistically robust assessments of cell heterogeneity, while the addition of a temporal element allows assessment of separate processes leading to deconvolution of the effects of particle supply and biological response. We provide a specific demonstration of the approach, in vitro, through time-resolved measurement of fibroblast cell (HFF-1) death caused by exposure to cationic nanoparticles. The results show that heterogeneity in cell area is the major source of variability with area-dependent nanoparticle capture rates determining the time of cell death and hence the form of the exposure–response characteristic. Moreover, due to the particulate nature of the nanoparticle suspension, there is a reduction in the particle concentration over the course of the experiment, eventually causing saturation in the level of measured biological outcome. A generalized mathematical description of the system is proposed, based on a simple model of particle depletion from a finite supply reservoir. This captures the essential aspects of the nanoparticle–cell interaction dynamics and accurately predicts the population exposure–response curves from individual cell heterogeneity distributions.

High-throughput immunofluorescence microscopy using yeast spheroplast cell-based microarrays

We have described a protocol for performing high-throughput immunofluorescence microscopy on microarrays of yeast cells. This approach employs immunostaining of spheroplasted yeast cells printed as high-density cell microarrays, followed by imaging using automated microscopy. A yeast spheroplast microarray can contain more than 5,000 printed spots, each containing cells from a given yeast strain, and is thus suitable for genome-wide screens focusing on single cell phenotypes, such as systematic localization or co-localization studies or genetic assays for genes affecting probed targets. We demonstrate the use of yeast spheroplast microarrays to probe microtubule and spindle defects across a collection of yeast strains harboring tetracycline-down-regulatable alleles of essential genes.