Subcellular Biology Research Articles

Real-time simultaneous refractive index and thickness mapping of sub-cellular biology at the diffraction limit

Mapping the cellular refractive index (RI) is a central task for research involving the composition of microorganisms and the development of models providing automated medical screenings with accuracy beyond 95%. These models require significantly enhancing the state-of-the-art RI mapping capabilities to provide large amounts of accurate RI data at high throughput. Here, we present a machine-learning-based technique that obtains a biological specimen’s real-time RI and thickness maps from a single image acquired with a conventional color camera. This technology leverages a suitably engineered nanostructured membrane that stretches a biological analyte over its surface and absorbs transmitted light, generating complex reflection spectra from each sample point. The technique does not need pre-existing sample knowledge. It achieves 10−4 RI sensitivity and sub-nanometer thickness resolution on diffraction-limited spatial areas. We illustrate practical application by performing sub-cellular segmentation of HCT-116 colorectal cancer cells, obtaining complete three-dimensional reconstruction of the cellular regions with a characteristic length of 30 μm. These results can facilitate the development of real-time label-free technologies for biomedical studies on microscopic multicellular dynamics.

Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy.

Accurate delineation of plant cell organelles from electron microscope images is essential for understanding subcellular behaviour and function. Here we develop a deep-learning pipeline, called the organelle segmentation network (OrgSegNet), for pixel-wise segmentation to identify chloroplasts, mitochondria, nuclei and vacuoles. OrgSegNet was evaluated on a large manually annotated dataset collected from 19 plant species and achieved state-of-the-art segmentation performance. We defined three digital traits (shape complexity, electron density and cross-sectional area) to track the quantitative features of individual organelles in 2D images and released an open-source web tool called Plantorganelle Hunter for quantitatively profiling subcellular morphology. In addition, the automatic segmentation method was successfully applied to a serial-sectioning scanning microscope technique to create a 3D cell model that offers unique views of the morphology and distribution of these organelles. The functionalities of Plantorganelle Hunter can be easily operated, which will increase efficiency and productivity for the plant science community, and enhance understanding of subcellular biology.

MoleculeExperiment enables consistent infrastructure for molecule-resolved spatial omics data in bioconductor.

Imaging-based spatial transcriptomics (ST) technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promise unprecedented opportunity toward understanding cellular and subcellular biology. However, in R/Bioconductor, there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarize and transform it for existing widely adopted computational tools in single-cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment (SPE) classes. With the emergence of several commercial offerings of imaging-based ST, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule-level. To this end, we have developed MoleculeExperiment, an R/Bioconductor package, which (i) stores molecule and cell segmentation boundary information at the molecule-level, (ii) standardizes this molecule-level information across different imaging-based ST technologies, including 10× Genomics' Xenium, and (iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of molecule-resolved spatial omics data. The MoleculeExperiment package is publicly available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html. Source code is available on Github at: https://github.com/SydneyBioX/MoleculeExperiment. The vignette for MoleculeExperiment can be found at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html.

Using Expansion Microscopy to Physically Enlarge Whole-Mount Drosophila Embryos for Super-Resolution Imaging.

The workhorse of developmental biology is the confocal microscope, which allows researchers to determine the three-dimensional localization of tagged molecules within complex biological samples. While traditional confocal microscopes allow one to resolve two adjacent fluorescent point sources located a few hundred nanometers apart, observing the finer details of subcellular biology requires the ability to resolve signals in the order of tens of nanometers. Numerous hardware-based methods for super-resolution microscopy have been developed to allow researchers to sidestep such resolution limits, although these methods require specialized microscopes that are not available to all researchers. An alternative method for increasing resolving power is to isotropically enlarge the sample itself through a process known as expansion microscopy (ExM), which was first described by the Boyden group in 2015. ExM is not a type of microscopy per se but is rather a method for swelling a sample while preserving the relative spatial organization of its constituent molecules. The expanded sample can then be observed at an effectively increased resolution using a traditional confocal microscope. Here, we describe a protocol for implementing ExM in whole-mount Drosophila embryos, which is used to examine the localization of Par-3, myosin II, and mitochondria within the surface epithelial cells. This protocol yields an approximately four-fold increase in sample size, allowing for the detection of subcellular details that are not visible with conventional confocal microscopy. As proof of principle, an anti-GFP antibody is used to distinguish distinct pools of myosin-GFP between adjacent cell cortices, and fluorescently labeled streptavidin is used to detect endogenous biotinylated molecules to reveal the fine details of the mitochondrial network architecture. This protocol utilizes common antibodies and reagents for fluorescence labeling, and it should be compatible with many existing immunofluorescence protocols.

Profile of Membrane Cargo Trafficking Proteins and Transporters Expressed under N Source Derepressing Conditions in Aspergillus nidulans.

Solute and ion transporters are proteins essential for cell nutrition, detoxification, signaling, homeostasis and drug resistance. Being polytopic transmembrane proteins, they are co-translationally inserted and folded into the endoplasmic reticulum (ER) of eukaryotic cells and subsequently sorted to their final membrane destination via vesicular secretion. During their trafficking and in response to physiological/stress signals or prolonged activity, transporters undergo multiple quality control processes and regulated turnover. Consequently, transporters interact dynamically and transiently with multiple proteins. To further dissect the trafficking and turnover mechanisms underlying transporter subcellular biology, we herein describe a novel mass spectrometry-based proteomic protocol adapted to conditions allowing for maximal identification of proteins related to N source uptake in A. nidulans. Our analysis led to identification of 5690 proteins, which to our knowledge constitutes the largest protein dataset identified by omics-based approaches in Aspergilli. Importantly, we detected possibly all major proteins involved in basic cellular functions, giving particular emphasis to factors essential for membrane cargo trafficking and turnover. Our protocol is easily reproducible and highly efficient for unearthing the full A. nidulans proteome. The protein list delivered herein will form the basis for downstream systematic approaches and identification of protein–protein interactions in living fungal cells.

Micro- and Nano-Devices for Studying Subcellular Biology.

Cells are complex machines whose behaviors arise from their internal collection of dynamically interacting organelles, supramolecular complexes, and cytoplasmic chemicals. The current understanding of the nature by which subcellular biology produces cell-level behaviors is limited by the technological hurdle of measuring the large number (>103 ) of small-sized (<1μm) heterogeneous organelles and subcellular structures found within each cell. In this review, the emergence of a suite of micro- and nano-technologies for studying intracellular biology on the scale of organelles is described. Devices that use microfluidic and microelectronic components for 1) extracting and isolating subcellular structures from cells and lysate; 2) analyzing the physiology of individual organelles; and 3) recreating subcellular assembly and functions in vitro, are described. The authors envision that the continued development of single organelle technologies and analyses will serve as a foundation for organelle systems biology and will allow new insight into fundamental and clinically relevant biological questions.

SMAUG: Analyzing single-molecule tracks with nonparametric Bayesian statistics.

Single-molecule fluorescence microscopy probes nanoscale, subcellular biology in real time. Existing methods for analyzing single-particle tracking data provide dynamical information, but can suffer from supervisory biases and high uncertainties. Here, we develop a method for the case of multiple interconverting species undergoing free diffusion and introduce a new approach to analyzing single-molecule trajectories: the Single-Molecule Analysis by Unsupervised Gibbs sampling (SMAUG) algorithm, which uses nonparametric Bayesian statistics to uncover the whole range of information contained within a single-particle trajectory dataset. Even in complex systems where multiple biological states lead to a number of observed mobility states, SMAUG provides the number of mobility states, the average diffusion coefficient of single molecules in that state, the fraction of single molecules in that state, the localization noise, and the probability of transitioning between two different states. In this paper, we provide the theoretical background for the SMAUG analysis and then we validate the method using realistic simulations of single-particle trajectory datasets as well as experiments on a controlled in vitro system. Finally, we demonstrate SMAUG on real experimental systems in both prokaryotes and eukaryotes to measure the motions of the regulatory protein TcpP in Vibrio cholerae and the dynamics of the B-cell receptor antigen response pathway in lymphocytes. Overall, SMAUG provides a mathematically rigorous approach to measuring the real-time dynamics of molecular interactions in living cells.

Testing the limits of pheromone stigmergy in high-density robot swarms.

Area coverage and collective exploration are key challenges for swarm robotics. Previous research in this field has drawn inspiration from ant colonies, with real, or more commonly virtual, pheromones deposited into a shared environment to coordinate behaviour through stigmergy. Repellent pheromones can facilitate rapid dispersal of robotic agents, yet this has been demonstrated only for relatively small swarm sizes (N < 30). Here, we report findings from swarms of real robots (Kilobots) an order of magnitude larger (N > 300) and from realistic simulation experiments up to N = 400. We identify limitations to stigmergy in a spatially constrained, high-density environment—a free but bounded two-dimensional workspace—using repellent binary pheromone. At larger N and higher densities, a simple stigmergic avoidance algorithm becomes first no better, then inferior to, the area coverage of non-interacting random walkers. Thus, the assumption of robustness and scalability for such approaches may need to be re-examined when they are working at a high density caused by ever-increasing swarm sizes. Instead, subcellular biology, and diffusive processes, may prove a better source of inspiration at large N in high agent density environments.

3D sub-diffraction imaging in a conventional confocal configuration by exploiting super-linear emitters

Sub-diffraction microscopy enables bio-imaging with unprecedented clarity. However, most super-resolution methods require complex, costly purpose-built systems, involve image post-processing and struggle with sub-diffraction imaging in 3D. Here, we realize a conceptually different super-resolution approach which circumvents these limitations and enables 3D sub-diffraction imaging on conventional confocal microscopes. We refer to it as super-linear excitation-emission (SEE) microscopy, as it relies on markers with super-linear dependence of the emission on the excitation power. Super-linear markers proposed here are upconversion nanoparticles of NaYF4, doped with 20% Yb and unconventionally high 8% Tm, which are conveniently excited in the near-infrared biological window. We develop a computational framework calculating the 3D resolution for any viable scanning beam shape and excitation-emission probe profile. Imaging of colominic acid-coated upconversion nanoparticles endocytosed by neuronal cells, at resolutions twice better than the diffraction limit both in lateral and axial directions, illustrates the applicability of SEE microscopy for sub-cellular biology.

Abstract 986: High content analysis of 2D and 3D oncology models for target and phenotypic drug discovery

Abstract Charles River (CR) has developed many disease-relevant cellular models to screen small molecules and genetic modifiers for target and phenotypic based drug discovery. Our expertise and portfolio in bespoke oncology model development (e.g. patient derived xenografts) covers a wide variety of target classes such as inhibitors of cell cycle, cellular motility and migration and transcription factor translocation. Complex cellular models derived from primary cells, patient derived embryonic stem cells and induced pluripotent stem cells have been adapted for phenotypic screening. Models have been further developed to produce physiologically relevant multicellular structure co-cultures. Combining complex biological systems with multiparametric high content analysis provides detailed single cell quantification of cellular and subcellular biology. Such validated High Content assays can be applied to both target and phenotypic based drug-discovery platforms to support preclinical drug discovery and improve translation of targets and compounds to the clinic. Citation Format: Servane Lachize, Rhea van de Bospoort, Marta da Silva da Silva, Niki van der Steentraten, Ian Gowers, Roger Clark, Jeroen DeGroot, Ian Waddell, Hajo Schiewe, Shushant Jain. High content analysis of 2D and 3D oncology models for target and phenotypic drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 986.

Spatiotemporal signal propagation in complex networks

A major achievement in the study of complex networks is the realization that diverse systems, from sub-cellular biology to social networks, exhibit universal topological characteristics. Yet, such universality does not naturally translate to the dynamics of these systems, as dynamic behaviour cannot be uniquely predicted from topology alone. Rather, it depends on the interplay of the network’s topology with the dynamic mechanisms of interaction between the nodes. Hence, systems with similar structure may exhibit profoundly different dynamic behaviour. We therefore seek a general theoretical framework to help us systematically translate topological elements into their predicted dynamic outcome. Here, we offer such a translation in the context of signal propagation, linking the topology of a network to the observed spatiotemporal spread of perturbative signals across it, thus capturing the network’s role in propagating local information. For a range of nonlinear dynamic models, we predict that the propagation rules condense into three highly distinctive dynamic regimes, characterized by the interplay between network paths, degree distribution and the interaction dynamics. As a result, classifying a system’s intrinsic interaction mechanisms into the relevant dynamic regime allows us to systematically translate topology into dynamic patterns of information propagation. Complex networks with identical topology may exhibit different dynamics. A systematic analysis of signal propagation in networks reveals the existence of three specific dynamic regimes that connect topological features to dynamic patterns.

Epistemologiczne problemy w biologii subkomórkowej: obserwacje, modele matematyczne i symulacje komputerowe

Relations between theory and empirical knowledge belong to basic problemsin philosophy of science and have been undergone detailed philosophical reflection,including epistemological aspects. During last several dozen years,due to development of computer technology, numerical simulations becamea common tool in natural sciences. Their epistemological aspects, however,have not worked out yet. A specific role of computer simulations manifestsin subcellular biology, where possibilities of performing experiments and observationsare limited. Computer simulation is complementary to observationand experiment and comes into complex relations with them. It allows us tocome to a conclusion if experiment or observations are impossible to perform.In particular, simulations allow researchers to estimate the parameters thatcannot be measured.

Dielectrophoresis-Assisted Raman Spectroscopy of Intravesicular Analytes on Metallic Pyramids.

Chemical analysis of membrane-bound containers such as secretory vesicles, organelles, and exosomes can provide insights into subcellular biology. These containers are loaded with a range of important biomolecules, which further underscores the need for sensitive and selective analysis methods. Here we present a metallic pyramid array for intravesicular analysis by combining site-selective dielectrophoresis (DEP) and Raman spectroscopy. Sharp pyramidal tips act as a gradient force generator to trap nanoparticles or vesicles from the solution, and the tips are illuminated by a monochromatic light source for concurrent spectroscopic detection of trapped analytes. The parameters suitable for DEP trapping were optimized by fluorescence microscopy, and the Raman spectroscopy setup was characterized by a nanoparticle based model system. Finally, vesicles loaded with 4-mercaptopyridine were concentrated at the tips and their Raman spectra were detected in real time. These pyramidal tips can perform large-area array-based trapping and spectroscopic analysis, opening up possibilities to detect molecules inside cells or cell-derived vesicles.

Trade-offs between elimination and detoxification in rainbow trout and common bivalve molluscs exposed to metal stressors

The purpose of this paper was to examine trade-offs between elimination and detoxification in rainbow trout and three common bivalve molluscs (clam, oyster, and scallop) exposed to cadmium (Cd), copper (Cu), and zinc (Zn) based on recent reported experimental data. We incorporated metal influx threshold with subcellular partitioning to estimate rate constants of detoxification ( k d) and elimination ( k 2). We found that the relationships between k 2 and k d were negative for rainbow trout and positive for bivalve molluscs. However, the relationships between k d and % metal in metabolically detoxified pool were found positive for rainbow trout and negative for bivalve molluscs. Our results also indicated that rainbow trout had higher accumulation (∼60–90%) in metabolically active pool when exposed to essential metals of Cu and Zn and had only 10–50% accumulation in response to non-essential metal of Cd. Based on a cluster analysis, this study indicated that similarity of physiological regulations among study species was found between Cd and Zn. Our study suggested that detoxification can be predicted by an elimination–detoxification scheme with the known elimination rate constant. We concluded that quantification of trade-offs between subcellular partitioning and detoxification provides valuable insights into the ecotoxicology of aquatic organisms and enhances our understanding of the subcellular biology of trace metals.

Centromere. Structure and evolution. Progress in Molecular and Subcellular Biology, Vol. 48

Centromere. Structure and evolution. Progress in Molecular and Subcellular Biology, Vol. 48

On the backroads to cellular asymmetry

Asymmetric cell division is a process whereby one cell generates two daughter cells that differ in size or developmental potential. Asymmetric cell divisions were first described during the initial, cleavage-like divisions of the zygote, where they contribute to the establishment of the body axes in

On the foundations of the stochastic immersed boundary method

We explore the theoretical foundations for the inclusion of thermal fluctuations in the immersed boundary method for simulating microscale fluid systems with immersed flexible structures, as in cellular and subcellular biology. We investigate in particular the physical validity of the thermal forcing scheme with respect to the coupling of fluid and immersed structural degrees of freedom and non-equilibrium conditions. We discuss also the shortcomings of a natural alternative scheme in which the thermal fluctuations are applied directly to the structural degrees of freedom through Langevin-type dynamics.

Perennial challenges and opportunities

Perennial challenges and opportunities

Bcl-2 Protein Is Required for the Adenine/Uridine-rich Element (ARE)-dependent Degradation of Its Own Messenger

We have shown previously that the decay of human bcl-2 mRNA is mediated by an adenine/uridine-rich element (ARE) located in the 3'-untranslated region. Here, we have utilized a non-radioactive cell-free mRNA decay system to investigate the biochemical and functional mechanisms regulating the ARE-dependent degradation of bcl-2 mRNA. Using RNA substrates, mutants, and competitors, we found that decay is specific and ARE-dependent, although maximized by the ARE-flanking regions. In unfractionated extracts from different cell types and in whole cells, the relative enzymatic activity was related to the amount of Bcl-2 protein expressed by the cells at steady state. The degradation activity was lost upon Bcl-2 depletion and was reconstituted by adding recombinant Bcl-2. Ineffective extracts from cells that constitutively do not express Bcl-2 acquire full degradation activity by adding recombinant Bcl-2 protein. We conclude that Bcl-2 is necessary to activate the degradation complex on the relevant RNA target.

Finding a needle in a haystack: detection of a small protein (the 12-kDa VP26) in a large complex (the 200-MDa capsid of herpes simplex virus).

Macromolecular complexes that consist of homopolymeric protein frameworks with additional proteins attached at strategic sites for a variety of structural and functional purposes are widespread in subcellular biology. One such complex is the capsid of herpes simplex virus type 1 whose basic framework consists of 960 copies of the viral protein, VP5 (149 kDa), arranged in an icosahedrally symmetric shell. This shell also contains major amounts of three other proteins, including VP26 (12 kDa), a small protein that is approximately equimolar with VP5 and accounts for approximately 6% of the capsid mass. With a view to inferring the role of VP26 in capsid assembly, we have localized it by quantitative difference imaging based on three-dimensional reconstructions calculated from cryo-electron micrographs. Purified capsids from which VP26 had been removed in vitro by treatment with guanidine hydrochloride were compared with preparations of the same depleted capsids to which purified VP26 had been rebound and with native (undepleted) capsids. The resulting three-dimensional density maps indicate that six VP26 subunits are distributed symmetrically around the outer tip of each hexon protrusion on VP26-containing capsids. Because VP26 may be readily dissociated from and reattached to the capsid, it does not appear to contribute significantly to structural stabilization. Rather, its exposed location suggests that VP26 may be involved in linking the capsid to the surrounding tegument and envelope at a later stage of viral assembly.