Bridging structural and cell biology with cryo-electron microscopy.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Role of collagen and immunostaining for TGF-β in the clinical andmicroscopic findings of pyogenic granuloma and peripheral ossifying fibroma

Background: Collagen is a component of Pyogenic Granuloma (PG) and Peripheral Ossifying Fibroma (POF) and performs different functions in these lesions. The objective of this study is to evaluate the role of collagen and immunostaining for Transforming Growth Factor beta (TGF-β) in the clinical and microscopic findings of PG and POF. Material and Methods: PG (n=20) and POF (n=20) were selected for clinical evaluation (sex, age, localization, size and evolution time) and microscopic analysis (picrosirius red staining for collagen analysis and immunohistochemistry for TGF-β) performed in the superficial and deep areas of the two lesions. ANOVA/Bonferroni and t-test, Pearson correlation and χ2 were used to compare the sites and parameters analyzed (p<0.05, GraphPad Prism 5.0). Results: The depth of PG presented the highest amount of collagen (p<0.001), and its surface showed the lowest amount of type 1 collagen (yellow-red strong birefringence). Type 1 collagen gradually increased in depth of PG, surface and depth of POF (p<0.001). The number of TGF-β+ cells was lower on the surface of PG compared with the depth of PG and the two areas of POF (p<0.001). Sex and localization did not affect these parameters, but the profile of collagen and immunostaining for TGF-β suffered from modifications by the time of evolution and the size of the lesion. Conclusions: Although PG and POF are reactive gingival lesions, the expression of TGF-β and its role in collagen showed different biological behaviors in these lesions, suggesting different biological origins for its components. (AU)

Recording physiological history of cells with chemical labeling.

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G protein-coupled receptor activation, and increases in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogeneous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

Cell-type-directed design of synthetic enhancers.

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

The free energy landscape of small-world networks of cells.

The properties of organs, tissues, organoids, and other systems of cells, are influenced by the spatial localization and distribution of their elements. Here, we used networks to describe distributions of cells on a surface where the small-world coefficient (SW) of the networks was varied between SW~1 (random uniform distributions) and SW~10 (clustered distributions). The small-world coefficient is a topological measure of graphs: networks with SW>1 are topologically biased to transmit information. For each system configuration, we then determined the total energy U as the sum of the energies that describe cell-cell interactions - approximated by a harmonic potential. The graph of energy (U) across the configuration space of the networks (SW) is the energy landscape: it indicates which configuration a system of cells will likely assume over time. We found that, depending on the model parameters, the energy landscapes of 2D distributions of cells may be of different types: from type I to type IV. Type I and type II systems have high probability to evolve into random distributions. Type III and type IV systems have a higher probability to form clustered architectures. A great many of simulations indicated that cultures of cells with high initial density and limited sensing range could evolve into clustered configurations with enhanced topological characteristics. Moreover, the strongest the binding between cells, the greater the likelihood that they will assume configurations characterized by finite values of SW. Results of the work are relevant for those working the field of tissue engineering, regenerative medicine, the formation of in-vitro-models, the analysis of neuro-degenerative diseases.

The regulatory effect of growth differentiation factor 11 on different cells.

Growth differentiation factor 11 (GDF11) is one of the important factors in the pathophysiological process of animals. It is widely expressed in many tissues and organs of animals, showing its wide biological activity and potential application value. Previous research has demonstrated that GDF11 has a therapeutic effect on various diseases, such as anti-myocardial aging and anti-tumor. This has not only sparked intense interest and enthusiasm among academics but also spurred some for-profit businesses to attempt to develop GDF11 as a medication for regenerative medicine or anti-aging application. Currently, Sotatercept, a GDF11 antibody drug, is in the marketing application stage, and HS-235 and rGDF11 are in the preclinical research stage. Therefore, we believe that figuring out which cells GDF11 acts on and its current problems should be an important issue in the scientific and commercial communities. Only through extensive, comprehensive research and discussion can we better understand the role and potential of GDF11, while avoiding unnecessary risks and misinformation. In this review, we aimed to summarize the role of GDF11 in different cells and its current controversies and challenges, providing an important reference for us to deeply understand the function of GDF11 and formulate more effective treatment strategies in the future.

Bye bye, linearity, bye: quantification of the mean for linear CRNs in a random environment.

Molecular reactions within a cell are inherently stochastic, and cells often differ in morphological properties or interact with a heterogeneous environment. Consequently, cell populations exhibit heterogeneity both due to these intrinsic and extrinsic causes. Although state-of-the-art studies that focus on dissecting this heterogeneity use single-cell measurements, the bulk data that shows only the mean expression levels is still in routine use. The fingerprint of the heterogeneity is present also in bulk data, despite being hidden from direct measurement. In particular, this heterogeneity can affect the mean expression levels via bimolecular interactions with low-abundant environment species. We make this statement rigorous for the class of linear reaction systems that are embedded in a discrete state Markov environment. The analytic expression that we provide for the stationary mean depends on the reaction rate constants of the linear subsystem, as well as the generator and stationary distribution of the Markov environment. We demonstrate the effect of the environment on the stationary mean. Namely, we show how the heterogeneous case deviates from the quasi-steady state (Q.SS) case when the embedded system is fast compared to the environment.

What is a cell type?

A next step for cell atlases should be to chart perturbations in human model systems.

Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy.

Raman spectroscopy shows great potential for practical clinical applications. By analyzing the structure and composition of molecules through real-time, non-destructive measurements of the scattered light from living cells and tissues, it offers valuable insights. The Raman spectral data directly link to the molecular composition of the cells and tissues and provides a "molecular fingerprint" for various disease states. This review focuses on the practical and clinical applications of Raman spectroscopy, especially in the early detection of human diseases. Identifying predisease, which marks the transition from a healthy to a disease state, is crucial for effective interventions to prevent disease onset. Raman spectroscopy can reveal biological processes occurring during the transition states and may eventually detect the molecular dynamics in predisease conditions.

A histone deacetylase 3 and mitochondrial complex I axis regulates toxic formaldehyde production.

Cells produce considerable genotoxic formaldehyde from an unknown source. We carry out a genome-wide CRISPR-Cas9 genetic screen in metabolically engineered HAP1 cells that are auxotrophic for formaldehyde to find this cellular source. We identify histone deacetylase 3 (HDAC3) as a regulator of cellular formaldehyde production. HDAC3 regulation requires deacetylase activity, and a secondary genetic screen identifies several components of mitochondrial complex I as mediators of this regulation. Metabolic profiling indicates that this unexpected mitochondrial requirement for formaldehyde detoxification is separate from energy generation. HDAC3 and complex I therefore control the abundance of a ubiquitous genotoxic metabolite.

Solid-liquid transition induced by rigidity disparity in a binary mixture of cell tissues.

The two-dimensional melting of a binary mixture of cell tissues is numerically investigated in the presence of rigidity disparity. We present the full melting phase diagrams of the system by using the Voronoi-based cellular model. It is found that the enhancement of rigidity disparity can induce a solid-liquid transition at both zero temperature and finite temperature. (i) In the case of zero temperature, the system undergoes a continuous solid-hexatic transition followed by a continuous hexatic-liquid transition for zero rigidity disparity, but a discontinuous hexatic-liquid transition for finite rigidity disparity. Remarkably, the solid-hexatic transitions always arise when the soft cells reach the rigidity transition point of monodisperse systems. (ii) In the case of finite temperature, the melting occurs via a continuous solid-hexatic transition followed by a discontinuous hexatic-liquid transition. Our study may contribute to the understanding of solid-liquid transitions in binary mixture systems with rigidity disparity.

Targeting Cell Cycle Facilitates E1A-Independent Adenoviral Replication.

DNA replication of E1-deleted first-generation adenoviruses (AdV) in cultured cancer cells has been reported repeatedly and it was suggested that certain cellular proteins could functionally compensate for E1A, leading to the expression of the early region 2 (E2)-encoded proteins and subsequently virus replication. Referring to this, the observation was named E1A-like activity. In this study, we investigated different cell cycle inhibitors with respect to their ability to increase viral DNA replication of dl70-3, an E1-deleted adenovirus. Our analyses of this issue revealed that in particular inhibition of cyclin-dependent kinases 4/6 (CDK4/6i) increased E1-independent adenovirus E2-expression and viral DNA replication. Detailed analysis of the E2-expression in dl70-3 infected cells by RT-qPCR showed that the increase in E2-expression originated from the E2-early promoter. Mutations of the two E2F-binding sites in the E2-early promoter (pE2early-LucM) caused a significant reduction in E2-early promoter activity in trans-activation assays. Accordingly, mutations of the E2F-binding sites in the E2-early promoter in a virus named dl70-3/E2Fm completely abolished CDK4/6i induced viral DNA replication. Thus, our data show that E2F-binding sites in the E2-early promoter are crucial for E1A independent adenoviral DNA replication of E1-deleted vectors in cancer cells. IMPORTANCE E1-deleted AdV vectors are considered replication deficient and are important tools for the study of virus biology, gene therapy, and large-scale vaccine development. However, deletion of the E1 genes does not completely abolish viral DNA replication in cancer cells. Here, we report, that the two E2F-binding sites in the adenoviral E2-early promoter contribute substantially to the so-called E1A-like activity in tumor cells. With this finding, on the one hand, the safety profile of viral vaccine vectors can be increased and, on the other hand, the oncolytic property for cancer therapy might be improved through targeted manipulation of the host cell.

Ångström-resolution fluorescence microscopy.

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.

Estudo revela que células podem ser reprogramadas para combater câncer de mama

Tratamentos que estimulam o sistema imunológico a combater o câncer vêm sendo o foco de estudos científicos no mundo inteiro. Na Fiocruz Minas, uma equipe de pesquisadores mostrou que é possível impedir o crescimento de tumores malignos de mama, por meio da alteração do perfil de um dos tipos de célula de defesa do organismo, os macrófagos, usando nanopartículas de óxido de ferro.

An ELISA-based assay for determining haemagglutinin potency in egg, cell, or recombinant protein derived influenza vaccines.

Background: The current compendial assay for haemagglutinin antigen potency in influenza vaccine is the single radial immunodiffusion (SRID) which is time consuming and can lead to delays in release of vaccine. We previously described an alternate capture and detection enzyme linked immunoassay (ELISA) that utilizes sub-type specific, sub-clade cross-reactive monoclonal antibodies (mAbs) that are haemagglutination inhibiting (HAI) and correlate with SRID. The aim of this study is to determine the applicability of ELISA across current platforms for quantitation of seasonal quadrivalent vaccine. Methods: A single mAb capture and detection ELISA was employed to quantitate hemagglutinin (HA) derived from different vaccine platforms and host organisms and compared to SRID and a polyclonal antibody based ELISA. Results: We selected mAbs that displayed appropriate characteristics for a stability indicating potency assay which reacted to avian, insect and mammalian derived HA. Qualification of the homologous mAb assay against egg and cell derived HA demonstrated performance similar to that of the SRID however, superiority in sensitivity and specificity against strains from both influenza B/Victoria and B/Yamagata lineages. Analysis of drifted strains across multiple seasons demonstrated continued utility of this approach, reducing the need to develop reagents each season. With modification of the assay, we were able to accurately measure HA from different platforms and process stages using a single calibrated reference standard. We demonstrated the accuracy of ELISA when testing vaccine formulations containing selected adjuvants at standard and higher concentrations. Accelerated stability analysis indicated a strong correlation in the rate of degradation between the homologous mAb ELISA and SRID but not with ELISA utilizing polyclonal antisera. Further, we demonstrated specificity was restricted to the trimeric and oligomeric forms of HA but not monomeric HA. Conclusion: We believe this homologous mAb ELISA is a suitable replacement for the SRID compendial assay for HA antigen quantitation and stability assessment. Identification of suitable mAbs that are applicable across multiple vaccine platforms with extended sub-type reactivity across a number of influenza seasons, indicate that this assay has broad applicability, leading to earlier availability of seasonal and pandemic vaccines without frequent replacement of polyclonal antisera that is required with SRID.

Specimen, biological structure, and spatial ontologies in support of a Human Reference Atlas.

The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. The third HRA release (v1.2) covers spatial reference data and ontology annotations for 26 organs. Experts access the HRA annotations via spreadsheets and view reference object models in 3D editing tools. This paper introduces the Common Coordinate Framework (CCF) Ontology v2.0.1 that interlinks specimen, biological structure, and spatial data, together with the CCF API that makes the HRA programmatically accessible and interoperable with Linked Open Data (LOD). We detail how real-world user needs and experimental data guide CCF Ontology design and implementation, present CCF Ontology classes and properties together with exemplary usage, and report on validation methods. The CCF Ontology graph database and API are used in the HuBMAP portal, HRA Organ Gallery, and other applications that support data queries across multiple, heterogeneous sources.