James Jonkman

A commercially available microfluidics flow cell was utilized together with widefield fluorescence microscopy to evaluate the effects of disinfectants on bacterial strains. The flow cell’s inner surface supports the formation of biofilms of numerous bacterial species. The modular setup of the flow cell accessories allows connection to syringes, pumps and collection vials, facilitating aseptic experiments in a controlled fluidics environment which can be documented with precisely timed microscopy imaging. The flow cell is inoculated with a suspension of bacteria in a nutrient medium and incubated for several days allowing bacterial cells to form a biofilm. Shortly before performing an assay, the biofilm is labelled with a dual-fluorescent DNA probe which distinguishes unharmed and damaged bacteria. Then a disinfectant sample (or control) is gently injected and time-lapse imaging is used for quantifying the course of bacterial biomass response. We use a simplified widefield microscopy method that allows intensive recording and quantification of time series of two-dimensional frames for tracking the course of disinfectant action on a variety of microbial strains. This procedure has potential for the rapid evaluation of novel products.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

When used appropriately, a confocal fluorescence microscope is an excellent tool for making quantitative measurements in cells and tissues. The confocal microscope’s ability to block out-of-focus light and thereby perform optical sectioning through a specimen allows the researcher to quantify fluorescence with very high spatial precision. However, generating meaningful data using confocal microscopy requires careful planning and a thorough understanding of the technique. In this tutorial, the researcher is guided through all aspects of acquiring quantitative confocal microscopy images, including optimizing sample preparation for fixed and live cells, choosing the most suitable microscope for a given application and configuring the microscope parameters. Suggestions are offered for planning unbiased and rigorous confocal microscope experiments. Common pitfalls such as photobleaching and cross-talk are addressed, as well as several troubling instrumentation problems that may prevent the acquisition of quantitative data. Finally, guidelines for analyzing and presenting confocal images in a way that maintains the quantitative nature of the data are presented, and statistical analysis is discussed. A visual summary of this tutorial is available as a poster (https://doi.org/10.1038/s41596-020-0307-7).

Unfortunately, the eighth author James Jonkman has been missed in the published article.

Visible light is the principal stimulus for resetting the mammalian central circadian pacemaker. Circadian phase resetting is most sensitive to short-wavelength (blue) visible light. We examined the effects of removing short-wavelengths < 500 nm from polychromatic white light using optical filters on circadian phase resetting in rats. Under high irradiance conditions, both long- (7 h) and short- (1 h) duration short-wavelength filtered (< 500 nm) light exposure attenuated phase-delay shifts in locomotor activity rhythms by (∼40–50%) as compared to unfiltered light exposure. However, there was no attenuation in phase resetting under low irradiance conditions. Additionally, the reduction in phase-delay shifts corresponded to regionally specific attenuation in molecular markers of pacemaker activation in response to light exposure, including c-FOS, Per1 and Per2. These results demonstrate that removing short-wavelengths from polychromatic white light can attenuate circadian phase resetting in an irradiance dependent manner. These results have important implications for designing and optimizing lighting interventions to enhance circadian adaptation.

Raman microspectroscopy in conjunction with multivariate statistical analysis is a powerful technique for label-free classification of live cells based on their molecular composition, which can be correlated to variations in protein, DNA/RNA, and lipid macromolecules. We apply this technique in vitro, to discriminate between normal mouse ovarian surface epithelial (MOSE) cells and spontaneously-transformed ovarian surface epithelial (STOSE) cells, which are derived from the MOSE cells and are a model for high-grade serous ovarian cancer. The Raman spectra collected from individual cells undergo initial preprocessing (background subtraction, normalization and noise reduction) to yield true Raman spectra representative of the cells for subsequent statistical analysis. Using Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) yields a separation of the cells into the two groups (MOSE and STOSE). This classification model has a sensitivity and specificity of 92% and 85%, respectively, after treatment of the cells to bring them into cell cycle synchrony. The main source of this separation is correlated with the increased nucleic acid content in the malignant OSE cells. As expected, a lower accuracy of 72% is obtained with asynchronous MOSE and STOSE cell populations. These results are expected to have a positive impact on the future development of improved strategies for early detection and therapeutics related to ovarian cancer.

Spatially targeted optical microproteomics (STOMP) is a novel proteomics technique for interrogating micron-scale regions of interest (ROIs) in mammalian tissue, with no requirement for genetic manipulation. Methanol or formalin-fixed specimens are stained with fluorescent dyes or antibodies to visualize ROIs, then soaked in solutions containing the photo-tag: 4-benzoylbenzyl-glycyl-hexahistidine. Confocal imaging along with two photon excitation are used to covalently couple photo-tags to all proteins within each ROI, to a resolution of 0.67 µm in the xy-plane and 1.48 µm axially. After tissue solubilization, photo-tagged proteins are isolated and identified by mass spectrometry. As a test case, we examined amyloid plaques in an Alzheimer's disease (AD) mouse model and a post-mortem AD case, confirming known plaque constituents and discovering new ones. STOMP can be applied to various biological samples including cell lines, primary cell cultures, ex vivo specimens, biopsy samples, and fixed post-mortem tissue.