Subcellular Resolution Research Articles

Two-Photon Microscopy to Measure Calcium Signaling in the Living Brain.

Two-photon microscopy enables imaging of calcium signaling at cellular or subcellular resolution up to hundreds of microns deep in the living brain. Changes in the brightness of fluorescent calcium indicators provide a readout of calcium levels over time, affording information about neuronal activity and/or calcium-dependent subcellular signaling. Here, we describe a protocol for repeated two-photon imaging of calcium signals in mice expressing a genetically encoded calcium indicator that have been implanted with a chronic cranial window.

Real-Time Imaging Assessment of Stress-Induced Vascular Inflammation Using Heartbeat-Synchronized Motion Compensation.

Chronic mental stress accelerates atherosclerosis through complicated neuroimmune pathways, needing for advanced imaging techniques to delineate underlying cellular mechanisms. While histopathology, ex vivo imaging, and snapshots of in vivo images offer promising evidence, they lack the ability to capture real-time visualization of blood cell dynamics within pulsatile arteries in longitudinal studies. An electrically tunable lens was implemented in intravital optical microscopy, synchronizing the focal plane with heartbeats to follow artery movements. ApoE-/- mice underwent 2 weeks of restraint stress before baseline imaging followed by 2 weeks of stress exposure in the longitudinal imaging, while nonstressed mice remained undisturbed. The progression of vascular inflammation was assessed in the carotid arteries through intravital imaging and histological analyses. A 4-fold reduction of motion artifact, assessed by interframe SD, and an effective temporal resolution of 25.2 Hz were achieved in beating murine carotid arteries. Longitudinal intravital imaging showed chronic stress led to a 6.09-fold (P=0.017) increase in myeloid cell infiltration compared with nonstressed mice. After 3 weeks, we observed that chronic stress intensified vascular inflammation, increasing adhered myeloid cells by 2.45-fold (P=0.031), while no significant changes were noted in nonstressed mice. Microcirculation imaging revealed increased circulating, rolling, and adhered cells in stressed mice's venules. Histological analysis of the carotid arteries confirmed the in vivo findings that stress augmented plaque area, myeloid cell and macrophage accumulation, and necrotic core volume while reducing fibrous cap thickness indicating accelerated plaque formation. We visualized the 3-dimensional structure of the carotid artery and 4-dimensional dynamics of the venules in the cremaster muscle. Dynamic focusing motion compensation intravital microscopy enabled subcellular resolution in vivo imaging of blood cell dynamics in beating arteries under chronic restraint stress in real time. This novel technique emphasizes the importance of advanced in vivo imaging for understanding cardiovascular disease.

Long-term three-dimensional high-resolution imaging of live unlabeled small intestinal organoids via low-coherence holotomography.

Organoids, which are miniature in vitro versions of organs, possess significant potential for studying human diseases and elucidating their underlying mechanisms. Live imaging techniques play a crucial role in organoid research and contribute to elucidating the complex structure and dynamic biological phenomena of organoids. However, live, unlabeled high-resolution imaging of native organoids is challenging, primarily owing to the complexities of sample handling and optical scattering inherent in three-dimensional (3D) structures. Additionally, conventional imaging methods fail to capture the real-time dynamic processes of growing organoids. In this study, we introduce low-coherence holotomography as an advanced, label-free, quantitative imaging modality designed to overcome several technical obstacles for long-term live imaging of 3D organoids. We demonstrate the efficacy of low-coherence holotomography by capturing high-resolution morphological details and dynamic activities within mouse small intestinal organoids at subcellular resolution. Moreover, our approach facilitates the distinction between viable and nonviable organoids, significantly enhancing its utility in organoid-based research. This advancement underscores the critical role of live imaging in organoid studies, offering a more comprehensive understanding of these complex systems.

Longitudinal intravital microscopy of the mouse kidney: inflammatory responses to abdominal imaging windows.

Intravital microscopy enables direct observation of cell biology and physiology at subcellular resolution in real time in living animals. Implanted windows extend the scope of intravital microscopy to processes extending for weeks or even months, such as disease progression or tumor development. However, a question that must be addressed in such studies is whether the imaging window, like any foreign body, triggers an inflammatory response, and if that response alters the biological process under investigation. To directly evaluate this question, we conducted large-scale intravital microscopy of the kidney of LysM-EGFP mice over time after implantation of abdominal imaging windows. These studies demonstrate that windows stimulated a variety of changes consistent with a foreign body response. Within a few days of implantation, leukocytes were recruited to the window and the region between the window and kidney where, over the next 16 days, they increased in number in an expanding volume that developed a new vascular network. These changes were accompanied by a dramatic increase in glomerular albumin permeability within 2 - 5 days of implantation. Similar results were obtained from mice implanted with windows coated with PLL-g-PEG, but not from immune-deficient mice. These studies demonstrate the importance of evaluating whether implanted windows induce an inflammatory response, and whether that response impacts the processes under evaluation in longitudinal intravital microscopy studies.

Abstract C117: Integrative multi-omics profiling in patients of African descent diagnosed with prostate cancer reveals distinct tumor-promoting immunosuppressive niches at a single-cell level and spatial resolution

Abstract In the United States and globally, prostate cancer (PCa) mortality rates are the highest among men of African descent. 24% of the disparities in PCa remains even when controlled for access to care and stage at presentation. Moreover, the tumor microenvironment plays an essential role in tumor progression, aggressiveness, therapeutic response, and patient outcomes. Additionally, the association of the genomic findings with patient ancestry and other characteristics, such as tumor biology and transcriptomic alterations, remains poorly understood. Here, we performed a multi-Omics approach (N=447) to unravel the complexity of tumor heterogeneity and understand disease progression & distinct tumor biology influenced by genetic ancestry. We performed Whole Exome (Normal/tumor paired) Sequencing matched with Methyl Seq and Whole transcriptomic Sequencing for three datasets of our African, African American Men (AAM), and European Men (EAM). Additionally, we ran Spatial NanoString high-plex GeoMx-DSP for a total of 118 treatment-naive PCa patients (around 500 ROIs). Simultaneously, we added matched whole transcriptome Sequencing for these patients. The cohort comprised 87 AAM, 3 unknown, and 28 EAM self-reported individuals. To verify the self-reported race, the genomic ancestry was qualified using genotype and Admixture analysis. To further validate differentially expressed genes at the protein level, we performed multi-plex histological staining of 40 markers to determine the spatial resolution and neighborhood clustering within the tumor and the microenvironment. In parallel, we performed scMultiOmics sequencing (scRNA & scATAC-Seq) at a single-cell resolution (6000 cells/sample at 25K reads per cell) from an additional 12 patients (9 AAM & 3 EAM). We reconstructed a 3D model of the distinct tumor microenvironment at subcellular resolution using serially sectioned hematoxylin and eosin- stained tissue sections (CODA technology). Our results demonstrate that patients who self-report as AAM or Nigerian are assigned to high African (> 70%) Ancestry with either Yoruba (Nigeria) and/or Bantu subpopulation in the Sub-Saharan area. Additionally, high African Ancestry patients are diagnosed at a younger age and show advanced pathology stages compared to patients with European Ancestry. AAM of Yoruba descent expresses significantly higher immune-inflammatory signatures (STAT/IFNG-signaling pathway) compared to the Nigerian-Yoruba subpopulation. Our scRNA-Seq analysis shows that AAM has suppressive myeloid cells infiltrate within the tumor cells. The infiltrations of these cells change with age, Gleason Grade, and pathology stage. Moreover, AAM-tumor cells (scATAC-Seq) have increased open Chromatin accessibility with STAT motifs enrichment (p-value;0.0001), which could be the driver regulators of the immune-suppressive signature as well as influence the upregulation of STAT/IFNG signature within African Ancestry patients. Our study provides new insight into how genetic ancestry impacts immune signatures in AAM/African and contributes to PCa racial disparities. Citation Format: Isra Elhussin, Ezra Baraban1, Ashley Kiemen, Tamara L Lotan, Cathy Handy Marshall, Emmanuel Antonarakis, Moray J Campbell, Melissa Davis, Michael Dixon, Isaac Kim, Stefan Ambs, Rick Kittles, Adam B Murphy, Clayton Yates. Integrative multi-omics profiling in patients of African descent diagnosed with prostate cancer reveals distinct tumor-promoting immunosuppressive niches at a single-cell level and spatial resolution [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C117.

Mid-infrared chemical imaging of living cells enabled by plasmonic metasurfaces.

Mid-Infrared (MIR) chemical imaging provides rich chemical information of biological samples in a label-free and non-destructive manner. Yet, its adoption to live-cell analysis is limited by the strong attenuation of MIR light in water, often necessitating cell culture geometries that are incompatible with the prolonged viability of cells and with standard high-throughput workflow. Here, we introduce a new approach to MIR microscopy, where cells are imaged through their localized near-field interaction with a plasmonic metasurface. Chemical contrast of distinct molecular groups provided sub-cellular resolution images of the proteins, lipids, and nucleic acids in the cells that were collected using an inverted MIR microscope. Time-lapse imaging of living cells demonstrated that their behaviors, including motility, viability, and substrate adhesion, can be monitored over extended periods of time using low-power MIR light. The presented approach provides a method for the non-perturbative MIR imaging of living cells, which is well-suited for integration with modern high-throughput screening technologies for the label-free, high-content chemical imaging of living cells.

Abstract B076: Morphological diversity predicts functional traits in pancreatic cancer

Abstract Cell morphologies represent a phenotypic integration of intrinsic cellular processes, changes in cell state, and interactions with neighboring cells. While analyses of large cell line collections such as the Cancer Dependency Map (DepMap) have greatly enhanced discovery of novel molecular biomarkers and therapeutic targets, morphological analysis of these models has not yet been performed. Hence, there is a rich opportunity to discover novel regulators and functional properties of cell morphologies by linking image-based profiling to -omics based assays. Here, we studied the transcriptional and functional properties of 16 human pancreatic cancer cell lines, associations with distinct cell morphologies, and treatment-induced remodeling. At baseline, we observed extensive morphological heterogeneity across and within cell lines, as well as differences in multicellular organization. We categorized cell line morphologies into epithelial, mesenchymal, and spheroid, and organizational patterns into tightly aggregated, multilayered, and dispersed. We performed differential expression analysis across morphological subtypes utilizing DepMap transcriptomics data and queried functional correlates including CRISPR dependency, drug sensitivity, and proclivity for metastasis. For example, we discovered that the mesenchymal morphology and multilayered organizational pattern [WH3] were associated with metastatic potential, while expressing reduced levels of tight junction and cell adhesion genes. We then explored treatment associated morphological changes and their potential as cost-effective biomarkers for cell-intrinsic resistance to chemotherapy (e.g., 5-FU and gemcitabine) and KRAS inhibitors (e.g., MRTX1133 and RMC- 6236). Cells were treated continuously and monitored with live cell imaging (Incucyte SX5) followed by Cell Painting at the three-day endpoint. We observed conserved morphological responses to therapy across cell lines including a shift towards spindle-like cell shapes with neurite-like projections in chemotherapy-treated conditions, and a cell bloating phenomena characterized by an increase in cell area in KRAS inhibitor treated conditions. To directly link transcriptional state to morphology, we performed 1000-plex spatial molecular imaging (Nanostring CosMx) at subcellular resolution to pools of cell lines, demonstrating that morphological diversity within cell lines corresponded to distinct transcriptional states. In conclusion, this study highlights the potential of harnessing cell morphological information in a rapid, cost-effective phenotyping assay to aid precision oncology efforts leveraging patient- derived in vitro models. Citation Format: Dennis Gong, William L Hwang. Morphological diversity predicts functional traits in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B076.

Subcellular Level Spatial Transcriptomics with PHOTON.

The subcellular localization of RNA is closely linked to its function. Many RNA species are partitioned into organelles and other subcellular compartments for storage, processing, translation, or degradation. Thus, capturing the subcellular spatial distribution of RNA would directly contribute to the understanding of RNA functions and regulation. Here, we present PHOTON (Photoselection of Transcriptome over Nanoscale), a method which combines high resolution imaging with high throughput sequencing to achieve spatial transcriptome profiling at subcellular resolution. We demonstrate PHOTON as a versatile tool to accurately capture the transcriptome of target cell types in situ at the tissue level such as granulosa cells in the ovary, as well as RNA content within subcellular compartments such as the nucleolus and the stress granule. Using PHOTON, we also reveal the functional role of m6A modification on mRNA partitioning into stress granules. These results collectively demonstrate that PHOTON is a flexible and generalizable platform for understanding subcellular molecular dynamics through the transcriptomic lens.

Bin2cell reconstructs cells from high resolution Visium HD data.

Visium HD by 10X Genomics is the first commercially available platform capable of capturing full scale transcriptomic data paired with a reference morphology image from archived FFPE blocks at sub-cellular resolution. However, aggregation of capture regions to single cells poses challenges. Bin2cell reconstructs cells from the highest resolution data (2 μm bins) by leveraging morphology image segmentation and gene expression information. It is compatible with established Python single cell and spatial transcriptomics software, and operates efficiently in a matter of minutes without requiring a GPU. We demonstrate improvements in downstream analysis when using the reconstructed cells over default 8 μm bins on mouse brain and human colorectal cancer data. Bin2cell is available at https://github.com/Teichlab/bin2cell, along with documentation and usage examples, and can be installed from pip. Probe design functionality is available at https://github.com/Teichlab/gene2probe.

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples

Multiplexed imaging technologies have made it possible to interrogate complex tissue microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily and accurately segment cells into their sub-cellular compartments. Within the supervised learning paradigm, deep learning-based segmentation methods demonstrating human level performance have emerged. However, limited work has been done in developing such generalist methods within the unsupervised context. Here we present an easy-to-use unsupervised segmentation (UNSEG) method that achieves deep learning level performance without requiring any training data via leveraging a Bayesian-like framework, and nucleus and cell membrane markers. We show that UNSEG is internally consistent and better at generalizing to the complexity of tissue morphology than current deep learning methods, allowing it to unambiguously identify the cytoplasmic compartment of a cell, and localize molecules to their correct sub-cellular compartment. We also introduce a perturbed watershed algorithm for stably and automatically segmenting a cluster of cell nuclei into individual nuclei that increases the accuracy of classical watershed. Finally, we demonstrate the efficacy of UNSEG on a high-quality annotated gastrointestinal tissue dataset we have generated, on publicly available datasets, and in a range of practical scenarios.

Graph Fourier transform for spatial omics representation and analyses of complex organs

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Large field of view and spatial region of interest transcriptomics in fixed tissue

Expression profiling in spatially defined regions is crucial for systematically understanding tissue complexity. Here, we report a method of photo-irradiation for in-situ barcoding hybridization and ligation sequencing, named PBHL-seq, which allows targeted expression profiling from the photo-irradiated region of interest in intact fresh frozen and formalin fixation and paraffin embedding (FFPE) tissue samples. PBHL-seq uses photo-caged oligodeoxynucleotides for in situ reverse transcription followed by spatially targeted barcoding of cDNAs to create spatially indexed transcriptomes of photo-illuminated regions. We recover thousands of differentially enriched transcripts from different regions by applying PBHL-seq to OCT-embedded tissue (E14.5 mouse embryo and mouse brain) and FFPE mouse embryo (E15.5). We also apply PBHL-seq to the subcellular microstructures (cytoplasm and nucleus, respectively) and detect thousands of differential expression genes. Thus, PBHL-seq provides an accessible workflow for expression profiles from the region of interest in frozen and FFPE tissue at subcellular resolution with areas expandable to centimeter scale, while preserving the sample intact for downstream analysis to promote the development of transcriptomics.

ClearScope: a fully integrated light sheet theta microscope for sub-cellular resolution imaging without lateral size constraints.

Three-dimensional (3D) ex vivo imaging of cleared intact brains of animal models and large human and non-human primate postmortem brain specimens is important for understanding the physiological neural network connectivity patterns and the pathological alterations underlying neuropsychiatric and neurological disorders. Light-sheet microscopy has emerged as a highly effective imaging modality for rapid high-resolution imaging of large cleared samples. However, the orthogonal arrangements of illumination and detection optics in light sheet microscopy limits the size of specimen that can be imaged. Recently developed light sheet theta microscopy (LSTM) technology addressed this by utilizing a unique arrangement of two illumination light paths oblique to the detection light path, while allowing perpendicular arrangement of the detection light path relative to the specimen surface. Here, we report development of a next-generation, fully integrated, and user-friendly LSTM system for rapid sub-cellular resolution imaging uniformly throughout a large specimen without constraining the lateral (XY) size. In addition, we provide a seamlessly integrated workflow for image acquisition, data storage, pre- and post-processing, enhancement, and quantitative analysis. We demonstrate the system performance by high-resolution 3D imaging of intact mouse brains and human brain samples, and complete data analysis including digital neuron tracing, vessel reconstruction and design-based stereological analysis in 3D. This technically enhanced and user-friendly LSTM implementation will enable rapid quantitative mapping of molecular and cellular features of interests in diverse types of very large samples.

Spatial distribution of active compounds in stratum corneum—partitioning between corneocytes and lipid matrix

The interaction of active substances with molecular structures in stratum corneum (SC) is crucial for the efficacy and safety of cosmetic formulations and topical drugs. However, the molecular architecture of SC is highly complex and methods to unambiguously localize exogenous molecules within SC are lacking. Consequently, little is known about the distribution of actives within SC, and proposed penetration mechanisms through SC are typically limited to simple diffusion via a tortuous (lipid only) or transverse (across corneocytes and lipid matrix) pathway. In this work, 3D mass spectrometry imaging is used to determine the spatial distributions of four active substances at subcellular resolution in SC, including partitioning between the corneocytes and the intercellular lipid matrix. The results indicate that caffeine, 2-methyl resorcinol and oxybenzone are homogeneously distributed in the corneocytes but largely absent in the lipid matrix, despite considerable differences in lipophilicity. In contrast, the distribution- of jasmonic acid derivative is more inhomogeneous and indicates considerable localization to both the lipid phase and the corneocytes.

3D live imaging and phenotyping of CAR-T cell mediated-cytotoxicity using high-throughput Bessel oblique plane microscopy

Clarification of the cytotoxic function of T cells is crucial for understanding human immune responses and immunotherapy procedures. Here, we report a high-throughput Bessel oblique plane microscopy (HBOPM) platform capable of 3D live imaging and phenotyping of chimeric antigen receptor (CAR)-modified T-cell cytotoxicity against cancer cells. The HBOPM platform has the following characteristics: an isotropic subcellular resolution of 320 nm, large-scale scouting over 400 interacting cell pairs, long-term observation across 5 hours, and quantitative analysis of the Terabyte-scale 3D, multichannel, time-lapse image datasets. Using this advanced microscopy platform, several key subcellular events in CAR-T cells are captured and comprehensively analyzed; these events include the instantaneous formation of immune synapses and the sustained changes in the microtubing morphology. Furthermore, we identify the actin retrograde flow speed, the actin depletion coefficient, the microtubule polarization and the contact area of the CAR-T/target cell conjugates as essential parameters strongly correlated with CAR-T-cell cytotoxic function. Our approach will be useful for establishing criteria for quantifying T-cell function in individual patients for all T-cell-based immunotherapies.

Spatial omics technologies for understanding molecular status associated with cancer progression.

Cancer cells are generally exposed to numerous extrinsic stimulations in the tumor microenvironment. In this environment, cancer cells change their expression profiles to fight against circumstantial stresses, allowing their progression in the challenging tissue space. Technological advancements of spatial omics have had substantial influence on cancer genomics. This technical progress, especially that occurring in the spatial transcriptome, has been drastic and rapid. Here, we describe the latest spatial analytical technologies that have allowed omics feature characterization to retain their spatial and histopathological information in cancer tissues. Several spatial omics platforms have been launched, and the latest platforms finally attained single-cell level or even higher subcellular level resolution. We discuss several key papers elucidating the initial utility of the spatial analysis. In fact, spatial transcriptome analyses reveal comprehensive omics characteristics not only in cancer cells but also their surrounding cells, such as tumor infiltrating immune cells and cancer-associated fibroblasts. We also introduce several spatial omics platforms. We describe our own attempts to investigate molecular events associated with cancer progression. Furthermore, we discuss the next challenges in analyzing the multiomics status of cells, including their morphology and location. These novel technologies, in conjunction with spatial transcriptome analysis and, more importantly, with histopathology, will elucidate even novel key aspects of the intratumor heterogeneity of cancers. Such enhanced knowledge is expected to open a new path for overcoming therapeutic resistance and eventually to precisely stratify patients.

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model’s applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.

Spatial immunophenotyping using multiplexed imaging of immune follicles in secondary lymphoid tissues.

Secondary lymphoid organs (SLOs), including tonsils (TS), lymph nodes (LN), and Peyer's Patches, exhibit complementary immune functions. However, little is known about the spatial organization of immune cells and extracellular matrix (ECM) in the SLOs. Traditional imaging is limited to a few markers, confining our understanding of the differences between the SLOs. Herein, imaging mass cytometry addressed this gap by simultaneously profiling 25-plex proteins in SLO tissues at subcellular resolution. The antibody panel targeted immune, stromal, chemokine, epigenetic, and functional markers. For robust cell identification, a computational workflow SpatialVizPheno was developed to spatially phenotype 999,970 cells using two approaches, including manual gating and semi-supervised gating, iterative clustering, and annotation. LN exhibited the highest density of B cells while the intestinal tissues contained the highest proportion of regulatory and follicular helper T cells. SpatialVizPheno identified the most prevalent interaction between follicular dendritic cells and stromal cells (SCs), plasmablasts/plasma cells, and the SCs across the lymphoid tissues. Collagen-enriched regions were associated with the spatial orientation of B cell follicles in both TS and LN tissues, but not in intestinal lymphoid tissues. Such spatial differences of immunophenotypes and ECM in different SLO tissues can be used to quantify the relationship between cellular organization and ultimate immune responses.

Genetically Encoded Sensors for the In Vivo Detection of Neurochemical Dynamics.

The ability to measure dynamic changes in neurochemicals with high spatiotemporal resolution is essential for understanding the diverse range of functions mediated by the brain. We review recent advances in genetically encoded sensors for detecting neurochemicals and discuss their in vivo applications. For example, notable progress has been made with respect to sensors for second messengers such as cyclic adenosine monophosphate, enabling in vivo real-time monitoring of these messengers at single-cell and even subcellular resolution. Moreover, the emergence of highly sensitive sensors for neurotransmitters and neuromodulators has greatly accelerated the study of these signaling molecules in a wide variety of behavioral models using an array of powerful imaging techniques. Finally, we discuss the future direction of neurochemical sensors, including their ability to measure neurochemical concentrations and the potential for multiplex imaging.

Unveiling Challenging Microbial Fossil Biosignatures from Rio Tinto with Micro-to-Nanoscale Chemical and Ultrastructural Imaging.

Understanding the nature and preservation of microbial traces in extreme environments is crucial for reconstructing Earth's early biosphere and for the search for life on other planets or moons. At Rio Tinto, southwestern Spain, ferric oxide and sulfate deposits similar to those discovered at Meridiani Planum, Mars, entomb a diversity of fossilized organisms, despite chemical conditions commonly thought to be challenging for life and fossil preservation. Investigating this unique fossil microbiota can elucidate ancient extremophile communities and the preservation of biosignatures in acidic environments on Earth and, potentially, Mars. In this study, we use an innovative multiscale approach that combines the state-of-the-art synchrotron X-ray nanoimaging methods of ptychographic X-ray computed laminography and nano-X-ray fluorescence to reveal Rio Tinto's microfossils at subcellular resolution. The unprecedented nanoscale views of several different specimens within their geological and geochemical contexts reveal novel intricacies of preserved microbial communities. Different morphotypes, ecological interactions, and possible taxonomic affinities were inferred based on qualitative and quantitative 3D ultrastructural information, whereas diagenetic processes and metabolic affinities were inferred from complementary chemical information. Our integrated nano-to-microscale analytical approach revealed previously invisible microbial and mineral interactions, which complemented and filled a gap of spatial resolution in conventional methods. Ultimately, this study contributes to the challenge of deciphering the faint chemical and morphological biosignatures that can indicate life's presence on the early Earth and on distant worlds.