Metadata matters: access to image data in the real world

cellPLATO - an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data

Advances in imaging, segmentation and tracking have led to the routine generation of large and complex microscopy datasets. New tools are required to process this 'phenomics' type data. Here, we present 'Cell PLasticity Analysis Tool' (cellPLATO), a Python-based analysis software designed for measurement and classification of cell behaviours based on clustering features of cell morphology and motility. Used after segmentation and tracking, the tool extracts features from each cell per timepoint, using them to segregate cells into dimensionally reduced behavioural subtypes. Resultant cell tracks describe a 'behavioural ID' at each timepoint, and similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Here, we use cellPLATO to investigate the role of IL-15 in modulating human natural killer (NK) cell migration on ICAM-1 or VCAM-1. We find eight behavioural subsets of NK cells based on their shape and migration dynamics between single timepoints, and four trajectories based on sequences of these behaviours over time. Therefore, by using cellPLATO, we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

Direct evidence that cryoprotectant mixtures facilitate individual component permeation into living plant cells

The fundamental interactions between plant cells and cryoprotectants during vitrification are understudied in the field of plant cryopreservation. Within this area of research, real time cryoprotectant permeation into plant cells is even less documented. In this study, we monitor the real time permeation of individual cryoprotectants into rice callus cells when in mixtures with other cryoprotectants. Specifically, we use coherent anti-Stokes Raman scattering (CARS) microscopy to observe the permeation of individually deuterated DMSO, ethylene glycol, and glycerol in plant vitrification solution 2 (PVS2) by probing vibrational frequencies that correspond to C-D stretching modes of the cryoprotectant molecules. Additionally, we measure cell plasma membrane responses to PVS2 exposure using brightfield microscopy. We conclude that the permeation of PVS2 components into plant cells occurs faster than the first cell plasma membrane responses observed and therefore permeation and cell plasma membrane response do not appear to be directly correlated. In addition, we observe that cryoprotectant permeation into plant cells occurs more quickly and more uniformly when cryoprotectants are in PVS2 solution than when they are in single component aqueous solutions.

Parametric Solid Models of the At-Term Uterus From Magnetic Resonance Images

Birthing mechanics are poorly understood, though many injuries during childbirth are mechanical, like fetal and maternal tissue damage. Several biomechanical simulation models of parturition have been proposed to investigate birth, but many do not include the uterus. Additionally, most solid models rely on segmenting anatomical structures from clinical images to generate patient geometry, which can be time-consuming. This work presents two new parametric solid modeling methods for generating patient-specific, at-term uterine three-dimensional geometry. Building from an established method of modeling the sagittal uterine shape, this work improves the uterine coronal shape, especially where the fetal head joins the lower uterine wall. Solid models of the uterus and cervix were built from five at-term patients' magnetic resonance imaging (MRI) sets. Using anatomy measurements from MRI-segmented models, two parametric models were created-one that employs an averaged coronal uterine shape and one with multiple axial measurements of the coronal uterus. Through finite element analysis, the two new parametric methods were compared to the MRI-segmented high-fidelity method and a previously published elliptical low-fidelity method. A clear improvement in the at-term uterine shape was found using the two new parametric methods, and agreement in principal Lagrange strain directions was observed across all modeling methods. These methods provide an effective and efficient way to generate three-dimensional solid models of patient-specific maternal uterine anatomy, advancing possibilities for future research in computational birthing biomechanics.

Live-cell analysis of IMPDH protein levels during yeast colony growth provides insights into the regulation of GTP synthesis

The purine nucleotides ATP and GTP are made from the common precursor inosine monophosphate (IMP). Maintaining the correct balance of these nucleotides for optimal cell growth is controlled in part by the enzyme IMP dehydrogenase (IMPDH), which catalyzes the first dedicated step of GTP biosynthesis. The regulation of IMPDH mRNA and protein levels in the yeast S. cerevisiae grown in liquid culture has been studied in some detail, but regulation of IMPDH protein under conditions of cellular crowding on a solid substrate has not been examined. Here, we report real-time, live-cell analysis of the accumulation of the Imd2 isoform of IMPDH in yeast cells forming a monolayer colony in a microfluidic device over a 50-hour time course. We observe two distinct phases of increased Imd2 accumulation: a guanine-insensitive phase early in outgrowth and a guanine-sensitive phase later, when cells become crowded. We show that the IMPDH inhibitor mycophenolic acid enhances both phases of increase. Deletion of a transcription attenuator upstream of the mRNA start site that decreases Imd2 mRNA synthesis in the presence of high GTP increases the baseline level of Imd2 protein 10-fold and abolishes guanine-sensitive but not guanine-insensitive induction. Our results suggest that at least two mechanisms of yeast Imd2 regulation exist, the known GTP-dependent attenuation of RNA polymerase II elongation and a GTP concentration-independent pathway that may be controlled by cell growth state. Live-cell analysis of IMPDH protein levels in a growing yeast colony confirms a known mechanism of regulation and provides evidence for an additional mode of regulation.

IMPORTANCE

This study used live-cell microscopy to track changes in the level of a key enzyme in GTP nucleotide biosynthesis, inosine monophosphate dehydrogenase (IMPDH), during growth of a brewers yeast colony over 2 days in a microfluidic device. The results show that feedback regulation via transcription attenuation allows cells to adapt to nutrient limitation in the crowded environs of a yeast colony. They also identify a novel mode of regulation of IMPDH level that is not driven by guanine nucleotide availability.

Individual thalamic inhibitory interneurons are functionally specialized toward distinct visual features

Inhibitory interneurons in the dorsolateral geniculate nucleus (dLGN) are situated at the first central synapse of the image-forming visual pathway, but little is known about their function. Given their anatomy, they are expected to be multiplexors, integrating many different retinal channels along their dendrites. Here, using targeted single-cell-initiated rabies tracing, we found that mouse dLGN interneurons exhibit a degree of retinal input specialization similar to thalamocortical neurons. Some are anatomically highly specialized, for example, toward motion-selective information. Two-photon calcium imaging performed in vivo revealed that interneurons are also functionally specialized. In mice lacking retinal horizontal direction selectivity, horizontal direction selectivity is reduced in interneurons, suggesting a causal link between input and functional specialization. Functional specialization is not only present at interneuron somata but also extends into their dendrites. Altogether, inhibitory interneurons globally display distinct visual features which reflect their retinal input specialization and are ideally suited to perform feature-selective inhibition.

RESPAN: an accurate, unbiased and automated pipeline for analysis of dendritic morphology and dendritic spine mapping

Accurate and unbiased reconstructions of neuronal morphology, including quantification of dendritic spine morphology and distribution, are widely used in neuroscience but remain a major roadblock for large-scale analysis. Traditionally, spine analysis has required labor-intensive manual annotation, which is prone to human error and impractical for large 3D datasets. Previous automated tools for reconstructing neuronal morphology and quantitative dendritic spine analysis face challenges in generating accurate results and, following close inspection, often require extensive manual correction. While recent tools leveraging deep learning approaches have substantially increased accuracy, they lack functionality and useful outputs, necessitating additional tools to perform a complete analysis and limiting their utility. In this paper, we describe Restoration Enhanced SPine And Neuron (RESPAN) analysis, a new comprehensive pipeline developed as an open-source, easily deployable solution that harnesses recent advances in deep learning and GPU processing. Our approach demonstrates high accuracy and robustness, validated extensively across a range of imaging modalities for automated dendrite and spine mapping. It also offers extensive visual and tabulated data outputs, including detailed morphological and spatial metrics, dendritic spine classification, and 3D renderings. Additionally, RESPAN includes tools for validating results, ensuring scientific rigor and reproducibility.

Months-long tracking of neuronal ensembles spanning multiple brain areas with Ultra-Flexible Tentacle Electrodes

We introduce Ultra-Flexible Tentacle Electrodes (UFTEs), packing many independent fibers with the smallest possible footprint without limitation in recording depth using a combination of mechanical and chemical tethering for insertion. We demonstrate a scheme to implant UFTEs simultaneously into many brain areas at arbitrary locations without angle-of-insertion limitations, and a 512-channel wireless logger. Immunostaining reveals no detectable chronic tissue damage even after several months. Mean spike signal-to-noise ratios are 1.5-3x compared to the state-of-the-art, while the highest signal-to-noise ratios reach 89, and average cortical unit yields are ~1.75/channel. UFTEs can track the same neurons across sessions for at least 10 months (longest duration tested). We tracked inter- and intra-areal neuronal ensembles (neurons repeatedly co-activated within 25 ms) simultaneously from hippocampus, retrosplenial cortex, and medial prefrontal cortex in freely moving rodents. Average ensemble lifetimes were shorter than the durations over which we can track individual neurons. We identify two distinct classes of ensembles. Those tuned to sharp-wave ripples display the shortest lifetimes, and the ensemble members are mostly hippocampal. Yet, inter-areal ensembles with members from both hippocampus and cortex have weak tuning to sharp wave ripples, and some have unusual months-long lifetimes. Such inter-areal ensembles occasionally remain inactive for weeks before re-emerging.

A guide to artificial intelligence for cancer researchers

Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to a readily accessible tool for cancer researchers. AI-based tools can boost research productivity in daily workflows, but can also extract hidden information from existing data, thereby enabling new scientific discoveries. Building a basic literacy in these tools is useful for every cancer researcher. Researchers with a traditional biological science focus can use AI-based tools through off-the-shelf software, whereas those who are more computationally inclined can develop their own AI-based software pipelines. In this article, we provide a practical guide for non-computational cancer researchers to understand how AI-based tools can benefit them. We convey general principles of AI for applications in image analysis, natural language processing and drug discovery. In addition, we give examples of how non-computational researchers can get started on the journey to productively use AI in their own work.

A practical guide to bioimaging research data management in core facilities

Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging - Society for Microscopy and Image Analysis (GerBI-GMB), cross-institutional working groups and third-party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging-core-facility-centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.

Spatially distinct epithelial and mesenchymal cell subsets along progressive lineage restriction in the branching embryonic mammary gland

How cells coordinate morphogenetic cues and fate specification during development remains a fundamental question in organogenesis. The mammary gland arises from multipotent stem cells (MaSCs), which are progressively replaced by unipotent progenitors by birth. However, the lack of specific markers for early fate specification has prevented the delineation of the features and spatial localization of MaSC-derived lineage-committed progenitors. Here, using single-cell RNA sequencing from E13.5 to birth, we produced an atlas of matched mouse mammary epithelium and mesenchyme and reconstructed the differentiation trajectories of MaSCs toward basal and luminal fate. We show that murine MaSCs exhibit lineage commitment just prior to the first sprouting events of mammary branching morphogenesis at E15.5. We identify early molecular markers for committed and multipotent MaSCs and define their spatial distribution within the developing tissue. Furthermore, we show that the mammary embryonic mesenchyme is composed of two spatially restricted cell populations, and that dermal mesenchyme-produced FGF10 is essential for embryonic mammary branching morphogenesis. Altogether, our data elucidate the spatiotemporal signals underlying lineage specification of multipotent MaSCs, and uncover the signals from mesenchymal cells that guide mammary branching morphogenesis.

Identification of genetic suppressors for a BSCL2 lipodystrophy pathogenic variant in Caenorhabditis elegans

Seipin (BSCL2), a conserved endoplasmic reticulum protein, plays a critical role in lipid droplet (LD) biogenesis and in regulating LD morphology, pathogenic variants of which are associated with Berardinelli-Seip congenital generalized lipodystrophy type 2 (BSCL2). To model BSCL2 disease, we generated an orthologous BSCL2 variant, seip-1(A185P), in Caenorhabditis elegans. In this study, we conducted an unbiased chemical mutagenesis screen to identify genetic suppressors that restore embryonic viability in the seip-1(A185P) mutant background. A total of five suppressor lines were isolated and recovered from the screen. The defective phenotypes of seip-1(A185P), including embryonic lethality and impaired eggshell formation, were significantly suppressed in each suppressor line. Two of the five suppressor lines also alleviated the enlarged LDs in the oocytes. We then mapped a suppressor candidate gene, lmbr-1, which is an ortholog of human limb development membrane protein 1 (LMBR1). The CRISPR/Cas9 edited lmbr-1 suppressor alleles, lmbr-1(S647F) and lmbr-1(P314L), both significantly suppressed embryonic lethality and defective eggshell formation in the seip-1(A185P) background. The newly identified suppressor lines offer valuable insights into potential genetic interactors and pathways that may regulate seipin in the lipodystrophy model.

Multiplexed chromatin imaging reveals predominantly pairwise long-range coordination between Drosophila Polycomb genes

Polycomb (Pc) group proteins are transcriptional regulators with key roles in development, cell identity, and differentiation. Pc-bound chromatin regions form repressive domains that interact in 3D to assemble repressive nuclear compartments. Here, we use multiplexed chromatin imaging to investigate whether Pc compartments involve the clustering of multiple Pc domains during Drosophila development. Notably, 3D proximity between Pc targets is rare and involves predominantly pairwise interactions. These 3D proximities are particularly enhanced in segments where Pc genes are co-repressed. In addition, segment-specific expression of Hox Pc targets leads to their spatial segregation from Pc-repressed genes. Finally, non-Hox Pc targets are more proximal in regions where they are co-expressed. These results indicate that long-range Pc interactions are temporally and spatially regulated during differentiation and development but do not induce frequent clustering of multiple distant Pc genes.

Differential endothelial cell cycle status in postnatal retinal vessels revealed using a novel PIP-FUCCI reporter and zonation analysis

Cell cycle regulation is critical to blood vessel formation and function, but how the endothelial cell cycle integrates with vascular regulation is not well-understood, and available dynamic cell cycle reporters do not precisely distinguish all cell cycle stage transitions in vivo. Here we characterized a recently developed improved cell cycle reporter (PIP-FUCCI) that precisely delineates S phase and the S/G2 transition. Live image analysis of primary endothelial cells revealed predicted temporal changes and well-defined stage transitions. A new inducible mouse cell cycle reporter allele was selectively expressed in postnatal retinal endothelial cells upon Cre-mediated activation and predicted endothelial cell cycle status. We developed a semi-automated zonation program to define endothelial cell cycle status in spatially defined and developmentally distinct retinal areas and found predicted cell cycle stage differences in arteries, veins, and remodeled and angiogenic capillaries. Surprisingly, the predicted dearth of S-phase proliferative tip cells relative to stalk cells at the vascular front was accompanied by an unexpected enrichment for endothelial tip and stalk cells in G2, suggesting G2 stalling as a contribution to tip-cell arrest and dynamics at the front. Thus, this improved reporter precisely defines endothelial cell cycle status in vivo and reveals novel G2 regulation that may contribute to unique aspects of blood vessel network expansion.

SERS Microsensors for the Study of pH Regulation in Cystic Fibrosis Patient-Derived Airway Cultures

Acidification of the airway surface liquid in the respiratory system could play a role in the pathology of Cystic Fibrosis, but its low volume and proximity to the airway epithelium make it a challenging biological environment in which to noninvasively collect pH measurements. To address this challenge, we explored surface enhanced Raman scattering microsensors (SERS-MS), with a 4-mercaptobenzoic acid (MBA) pH reporter molecule, as pH sensors for the airway surface liquid of patient-derived in vitro models of the human airway. Using air-liquid interface (ALI) cultures to model the respiratory epithelium, we show that SERS-MS facilitates the optical measurement of trans-epithelial pH gradients between the airway surface liquid and the basolateral culture medium. SERS-MS also enabled the successful quantification of pH changes in the airway surface liquid following stimulation of the Cystic Fibrosis transmembrane conductance regulator (CFTR, the apical ion channel that is dysfunctional in Cystic Fibrosis airways). Finally, the influence of CFTR mutations on baseline airway surface liquid pH was explored by using SERS-MS to measure the pH in ALIs grown from Cystic Fibrosis and non-Cystic Fibrosis donors.

ZebraReg-a novel platform for discovering regulators of cardiac regeneration using zebrafish

Cardiovascular disease is the leading cause of death worldwide with myocardial infarction being the most prevalent. Currently, no cure is available to either prevent or revert the massive death of cardiomyocytes that occurs after a myocardial infarction. Adult mammalian hearts display a limited regeneration capacity, but it is insufficient to allow complete myocardial recovery. In contrast, the injured zebrafish heart muscle regenerates efficiently through robust proliferation of pre-existing myocardial cells. Thus, zebrafish allows its exploitation for studying the genetic programs behind cardiac regeneration, which may be present, albeit dormant, in the adult human heart. To this end, we have established ZebraReg, a novel and versatile automated platform for studying heart regeneration kinetics after the specific ablation of cardiomyocytes in zebrafish larvae. In combination with automated heart imaging, the platform can be integrated with genetic or pharmacological approaches and used for medium-throughput screening of presumed modulators of heart regeneration. We demonstrate the versatility of the platform by identifying both anti- and pro-regenerative effects of genes and drugs. In conclusion, we present a tool which may be utilised to streamline the process of target validation of novel gene regulators of regeneration, and the discovery of new drug therapies to regenerate the heart after myocardial infarction.

The Brain Image Library: A Community-Contributed Microscopy Resource for Neuroscientists

Advancements in microscopy techniques and computing technologies have enabled researchers to digitally reconstruct brains at micron scale. As a result, community efforts like the BRAIN Initiative Cell Census Network (BICCN) have generated thousands of whole-brain imaging datasets to trace neuronal circuitry and comprehensively map cell types. This data holds valuable information that extends beyond initial analyses, opening avenues for variation studies and robust classification of cell types in specific brain regions. However, the size and heterogeneity of these imaging data have historically made storage, sharing, and analysis difficult for individual investigators and impractical on a broad community scale. Here, we introduce the Brain Image Library (BIL), a public resource serving the neuroscience community that provides a persistent centralized repository for brain microscopy data. BIL currently holds thousands of brain datasets and provides an integrated analysis ecosystem, allowing for exploration, visualization, and data access without the need to download, thus encouraging scientific discovery and data reuse.

Persistent TFIIH binding to non-excised DNA damage causes cell and developmental failure

Congenital nucleotide excision repair (NER) deficiency gives rise to several cancer-prone and/or progeroid disorders. It is not understood how defects in the same DNA repair pathway cause different disease features and severity. Here, we show that the absence of functional ERCC1-XPF or XPG endonucleases leads to stable and prolonged binding of the transcription/DNA repair factor TFIIH to DNA damage, which correlates with disease severity and induces senescence features in human cells. In vivo, in C. elegans, this prolonged TFIIH binding to non-excised DNA damage causes developmental arrest and neuronal dysfunction, in a manner dependent on transcription-coupled NER. NER factors XPA and TTDA both promote stable TFIIH DNA binding and their depletion therefore suppresses these severe phenotypical consequences. These results identify stalled NER intermediates as pathogenic to cell functionality and organismal development, which can in part explain why mutations in XPF or XPG cause different disease features than mutations in XPA or TTDA.

A recurrent neural circuit in Drosophila deblurs visual inputs

A critical goal of vision is to detect changes in light intensity, even when these changes are blurred by the spatial resolution of the eye and the motion of the animal. Here we describe a recurrent neural circuit in Drosophila that compensates for blur and thereby selectively enhances the perceived contrast of moving edges. Using in vivo , two-photon voltage imaging, we measured the temporal response properties of L1 and L2, two cell types that receive direct synaptic input from photoreceptors. These neurons have biphasic responses to brief flashes of light, a hallmark of cells that encode changes in stimulus intensity. However, the second phase was often much larger than the first, creating an unusual temporal filter. Genetic dissection revealed that recurrent neural circuitry strongly shapes the second phase of the response, informing the structure of a dynamical model. By applying this model to moving natural images, we demonstrate that rather than veridically representing stimulus changes, this temporal processing strategy systematically enhances them, amplifying and sharpening responses. Comparing the measured responses of L2 to model predictions across both artificial and natural stimuli revealed that L2 tunes its properties as the model predicts in order to deblur images. Since this strategy is tunable to behavioral context, generalizable to any time-varying sensory input, and implementable with a common circuit motif, we propose that it could be broadly used to selectively enhance sharp and salient changes.

Resolving conjugated polymer film morphology with polarised transmission and time-resolved emission microscopy

The alignment of chromophores plays a crucial role in determining the optoelectronic properties of materials. Such alignment can make interpretation of fluorescence anisotropy microscopy (FAM) images somewhat ambiguous. The time-resolved emission behaviour can also influence the fluorescence anisotropy. This is particularly the case when probing excitation energy migration between chromophores in a condensed phase. Ideally information concerning the chromophoric alignment, emission decay kinetics and fluorescence anisotropy can be recorded and correlated. We report on the use of polarised transmission imaging (PTI) coupled with both steady-state and time-resolved FAM to enable accurate identification of chromophoric alignment and morphology in thin films of a conjugated polydiarylfluorene. We show that the combination of these three imaging modes presents a comprehensive methodology for investigating the alignment and morphology of chromophores in thin films, particularly for accurately mapping the distribution of amorphous and crystalline phases within the thin films, offering valuable insights for the design and optimization of materials with enhanced optoelectronic performance.

SRRM2 splicing factor modulates cell fate in early development

Embryo development is an orchestrated process that relies on tight regulation of gene expression to guide cell differentiation and fate decisions. The Srrm2 splicing factor has recently been implicated in developmental disorders and diseases, but its role in early mammalian development remains unexplored. Here, we show that Srrm2 dosage is critical for maintaining embryonic stem cell pluripotency and cell identity. Srrm2 heterozygosity promotes loss of stemness, characterised by the coexistence of cells expressing naive and formative pluripotency markers, together with extensive changes in gene expression, including genes regulated by serum-response transcription factor (SRF) and differentiation-related genes. Depletion of Srrm2 by RNA interference in embryonic stem cells shows that the earliest effects of Srrm2 heterozygosity are specific alternative splicing events on a small number of genes, followed by expression changes in metabolism and differentiation-related genes. Our findings unveil molecular and cellular roles of Srrm2 in stemness and lineage commitment, shedding light on the roles of splicing regulators in early embryogenesis, developmental diseases and tumorigenesis.

Adaptation of Magnified Analysis of the Proteome for Excitatory Synaptic Proteins in Varied Samples and Evaluation of Cell Type-Specific Distributions

Growing evidence suggests a remarkable diversity and complexity in the molecular composition of synapses, forming the basis for the brain to execute complex behaviors. Hence, there is considerable interest in visualizing the spatial distribution of such molecular diversity at individual synapses within intact brain circuits. Yet this task presents significant technical challenges. Expansion microscopy approaches have revolutionized our view of molecular anatomy. However, their use to study synapse-related questions outside of the labs developing them has been limited. Here we independently adapted a version of Magnified Analysis of the Proteome (MAP) and present a step-by-step protocol for visualizing over 40 synaptic proteins in brain circuits. Surprisingly, our findings show that the advantage of MAP over conventional immunolabeling was primarily due to improved antigen recognition and secondarily physical expansion. Furthermore, we demonstrated the versatile use of MAP in brains perfused with paraformaldehyde or fresh-fixed with formalin and in formalin-fixed paraffin-embedded tissue. These tests expand the potential applications of MAP to combinations with slice electrophysiology or clinical pathology specimens. Using male and female mice expressing YFP-ChR2 exclusively in interneurons, we revealed a distinct composition of AMPA and NMDA receptors and Shank family members at synapses on hippocampal interneurons versus on pyramidal neurons. Quantitative single synapse analyses yielded comprehensive cell type distributions of synaptic proteins and their relationships. These findings exemplify the value of the versatile adapted MAP procedure presented here as an accessible tool for the broad neuroscience community to unravel the complexity of the "synaptome" across brain circuits and disease states.

Dynamic local mRNA localization and translation occurs during the postnatal molecular maturation of perivascular astrocytic processes

Astrocytes are highly ramified and send out perivascular processes (PvAPs) that entirely sheathe the brain's blood vessels. PvAPs are equipped with an enriched molecular repertoire that sustains astrocytic regulatory functions at the vascular interface. In the mouse, PvAP development starts after birth and is essentially complete by postnatal day (P) 15. Progressive molecular maturation also occurs over this period, with the acquisition of proteins enriched in PvAPs. The mechanisms controlling the development and molecular maturation of PvAPs have not been extensively characterized. We reported previously that mRNAs are distributed unequally in mature PvAPs and are locally translated. Since dynamic mRNA localization and local translation influence the cell's polarity, we hypothesized that they might sustain the postnatal maturation of PvAPs. Here, we used a combination of molecular biology and imaging approaches to demonstrate that the development of PvAPs is accompanied by the transport of mRNA and polysomal mRNA into PvAPs, the development of a rough endoplasmic reticulum (RER) network and Golgi cisternae, and local translation. By focusing on genes and proteins that are selectively or specifically expressed in astrocytes, we characterized the developmental profile of mRNAs, polysomal mRNAs and proteins in PvAPs from P5 to P60. We found that some polysomal mRNAs polarized progressively towards the PvAPs. Lastly, we found that expression and localization of mRNAs in developing PvAPs is perturbed in a mouse model of megalencephalic leukoencephalopathy with subcortical cysts. Our results indicate that dynamic mRNA localization and local translation influence the postnatal maturation of PvAPs.

Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY

Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the 'Histology Analysis Pipeline.PY' (HAPPY), a deep learning hierarchical method for quantifying the variability of cells and micro-anatomical tissue structures across placenta histology whole slide images. HAPPY differs from patch-based features or segmentation approaches by following an interpretable biological hierarchy, representing cells and cellular communities within tissues at a single-cell resolution across whole slide images. We present a set of quantitative metrics from healthy term placentas as a baseline for future assessments of placenta health and we show how these metrics deviate in placentas with clinically significant placental infarction. HAPPY's cell and tissue predictions closely replicate those from independent clinical experts and placental biology literature.

Phylogenomic, structural, and cell biological analyses reveal that Stenotrophomonas maltophilia replicates in acidified Rab7A-positive vacuoles of Acanthamoeba castellanii

Acanthamoeba species are clinically relevant free-living amoebae (FLA) ubiquitously found in soil and water bodies. Metabolically active trophozoites graze on diverse microbes via phagocytosis. However, functional studies on Rab GTPases (Rabs), which are critical for controlling vesicle trafficking and maturation, are scarce for this FLA. This knowledge gap can be partly explained by the limited genetic tools available for Acanthamoeba cell biology. Here, we developed plasmids to generate fusions of A. castellanii strain Neff proteins to the N- or C-termini of mEGFP and mCherry2. Phylogenomic and structural analyses of the 11 Neff Rab7 paralogs found in the RefSeq assembly revealed that eight of them had non-canonical sequences. After correcting the gene annotation for the Rab7A ortholog, we generated a line stably expressing an mEGFP-Rab7A fusion, demonstrating its correct localization to acidified macropinocytic and phagocytic vacuoles using fluorescence microscopy live cell imaging (LCI). Direct labeling of live Stenotrophomonas maltophilia ESTM1D_MKCAZ16_6a (Sm18) cells with pHrodo Red, a pH-sensitive dye, demonstrated that they reside within acidified, Rab7A-positive vacuoles. We constructed new mini-Tn7 delivery plasmids and tagged Sm18 with constitutively expressed mScarlet-I. Co-culture experiments of Neff trophozoites with Sm18::mTn7TC1_Pc_mScarlet-I, coupled with LCI and microplate reader assays, demonstrated that Sm18 underwent multiple replication rounds before reaching the extracellular medium via non-lytic exocytosis. We conclude that S. maltophilia belongs to the class of bacteria that can use amoeba as an intracellular replication niche within a Stenotrophomonas-containing vacuole that interacts extensively with the endocytic pathway.IMPORTANCEDiverse Acanthamoeba lineages (genotypes) are of increasing clinical concern, mainly causing amoebic keratitis and granulomatous amebic encephalitis among other infections. S. maltophilia ranks among the top 10 most prevalent multidrug-resistant opportunistic nosocomial pathogens and is a recurrent member of the microbiome hosted by Acanthamoeba and other free-living amoebae. However, little is known about the molecular strategies deployed by Stenotrophomonas for an intracellular lifestyle in amoebae and other professional phagocytes such as macrophages, which allow the bacterium to evade the immune system and the action of antibiotics. Our plasmids and easy-to-use microtiter plate co-culture assays should facilitate investigations into the cellular microbiology of Acanthamoeba interactions with Stenotrophomonas and other opportunistic pathogens, which may ultimately lead to the discovery of new molecular targets and antimicrobial therapies to combat difficult-to-treat infections caused by these ubiquitous microbes.

P21-activated kinase-1 signaling is required to preserve adipose tissue homeostasis and cardiac function

While P21-activated kinase-1 (PAK1) has been extensively studied in relation to cardiovascular health and glucose metabolism, its roles within adipose tissue and cardiometabolic diseases are less understood. In this study, we explored the effects of PAK1 deletion on energy balance, adipose tissue homeostasis, and cardiac function utilizing a whole-body PAK1 knockout (PAK1-/-) mouse model. Our findings revealed that body weight differences between PAK1-/- and WT mice emerged at 9 weeks of age, with further increases observed at 12 weeks. Furthermore, PAK1-/- mice displayed increased fat mass and decreased lean mass at 12 weeks, indicating a shift towards adiposity. In conjunction with the increased body weight, PAK1-/- mice had increased food intake and reduced energy expenditure. At a mechanistic level, PAK1 deletion boosted the expression of lipogenic markers while diminishing thermogenic markers expression in adipose tissues, contributing to reduced energy expenditure and the overall obesogenic phenotype. Moreover, our findings highlighted a significant impact on cardiac function following PAK1 deletion, including alterations in calcium kinetics and compromised systolic and lusitropy functions. In summary, our study emphasizes the significant role of PAK1 in weight regulation and cardiac function, enriching our comprehension of heart health and metabolism. These findings could potentially facilitate the identification of novel therapeutic targets in cardiometabolic diseases.

Learning Continuous 2D Diffusion Maps from Particle Trajectories without Data Binning

Diffusion coefficients often vary across regions, such as cellular membranes, and quantifying their variation can provide valuable insight into local membrane properties such as composition and stiffness. Toward quantifying diffusion coefficient spatial maps and uncertainties from particle tracks, we use a Bayesian method and place Gaussian Process (GP) Priors on the maps. For the sake of computational efficiency, we leverage inducing point methods on GPs arising from the mathematical structure of the data giving rise to non-conjugate likelihood-prior pairs. We analyze both synthetic data, where ground truth is known, as well as data drawn from live-cell single-molecule imaging of membrane proteins. The resulting tool provides an unsupervised method to rigorously map diffusion coefficients continuously across membranes without data binning.

Ten recommendations for organising bioimaging data for archival

Organised data is easy to use but the rapid developments in the field of bioimaging, with improvements in instrumentation, detectors, software and experimental techniques, have resulted in an explosion of the volumes of data being generated, making well-organised data an elusive goal. This guide offers a handful of recommendations for bioimage depositors, analysts and microscope and software developers, whose implementation would contribute towards better organised data in preparation for archival. Based on our experience archiving large image datasets in EMPIAR, the BioImage Archive and BioStudies, we propose a number of strategies that we believe would improve the usability (clarity, orderliness, learnability, navigability, self-documentation, coherence and consistency of identifiers, accessibility, succinctness) of future data depositions more useful to the bioimaging community (data authors and analysts, researchers, clinicians, funders, collaborators, industry partners, hardware/software producers, journals, archive developers as well as interested but non-specialist users of bioimaging data). The recommendations that may also find use in other data-intensive disciplines. To facilitate the process of analysing data organisation, we present bandbox, a Python package that provides users with an assessment of their data by flagging potential issues, such as redundant directories or invalid characters in file or folder names, that should be addressed before archival. We offer these recommendations as a starting point and hope to engender more substantial conversations across and between the various data-rich communities.

A mutation in F-actin polymerization factor suppresses the distal arthrogryposis type 5 PIEZO2 pathogenic variant in Caenorhabditis elegans

The mechanosensitive PIEZO channel family has been linked to over 26 disorders and diseases. Although progress has been made in understanding these channels at the structural and functional levels, the underlying mechanisms of PIEZO-associated diseases remain elusive. In this study, we engineered four PIEZO-based disease models using CRISPR/Cas9 gene editing. We performed an unbiased chemical mutagen-based genetic suppressor screen to identify putative suppressors of a conserved gain-of-function variant pezo-1[R2405P] that in human PIEZO2 causes distal arthrogryposis type 5 (DA5; p. R2718P). Electrophysiological analyses indicate that pezo-1(R2405P) is a gain-of-function allele. Using genomic mapping and whole-genome sequencing approaches, we identified a candidate suppressor allele in the C. elegans gene gex-3. This gene is an ortholog of human NCKAP1 (NCK-associated protein 1), a subunit of the Wiskott-Aldrich syndrome protein (WASP)-verprolin homologous protein (WAVE/SCAR) complex, which regulates F-actin polymerization. Depletion of gex-3 by RNAi, or with the suppressor allele gex-3(av259[L353F]), significantly increased brood size and ovulation rate, as well as alleviating the crushed oocyte phenotype of the pezo-1(R2405P) mutant. Expression of GEX-3 in the soma is required to rescue the brood size defects in pezo-1(R2405P) animals. Actin organization and orientation were disrupted and distorted in the pezo-1 mutants. Mutation of gex-3(L353F) partially alleviated these defects. The identification of gex-3 as a suppressor of the pathogenic variant pezo-1(R2405P) suggests that the PIEZO coordinates with the cytoskeleton regulator to maintain the F-actin network and provides insight into the molecular mechanisms of DA5 and other PIEZO-associated diseases.

Harmonizing the Generation and Pre-publication Stewardship of FAIR Image data

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges, and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.

The Vps13-like protein BLTP2 is pro-survival and regulates phosphatidylethanolamine levels in the plasma membrane to maintain its fluidity and function

Lipid transport proteins (LTPs) facilitate nonvesicular lipid exchange between cellular compartments and have critical roles in lipid homeostasis1. A new family of bridge-like LTPs (BLTPs) is thought to form lipid-transporting conduits between organelles2. One, BLTP2, is conserved across species but its function is not known. Here, we show that BLTP2 and its homolog directly regulate plasma membrane (PM) fluidity by increasing the phosphatidylethanolamine (PE) level in the PM. BLTP2 localizes to endoplasmic reticulum (ER)-PM contact sites34, 5, suggesting it transports PE from the ER to the PM. We find BLTP2 works in parallel with another pathway that regulates intracellular PE distribution and PM fluidity6, 7. BLTP2 expression correlates with breast cancer aggressiveness8-10. We found BLTP2 facilitates growth of a human cancer cell line and sustains its aggressiveness in an in vivo model of metastasis, suggesting maintenance of PM fluidity by BLTP2 may be critical for tumorigenesis in humans.

Community-developed checklists for publishing images and image analyses

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

A defined clathrin-mediated trafficking pathway regulates sFLT1/VEGFR1 secretion from endothelial cells

FLT1/VEGFR1 negatively regulates VEGF-A signaling and is required for proper vessel morphogenesis during vascular development and vessel homeostasis. Although a soluble isoform, sFLT1, is often mis-regulated in disease and aging, how sFLT1 is trafficked and secreted from endothelial cells is not well understood. Here we define requirements for constitutive sFLT1 trafficking and secretion in endothelial cells from the Golgi to the plasma membrane, and we show that sFLT1 secretion requires clathrin at or near the Golgi. Perturbations that affect sFLT1 trafficking blunted endothelial cell secretion and promoted intracellular mis-localization in cells and zebrafish embryos. siRNA-mediated depletion of specific trafficking components revealed requirements for RAB27A, VAMP3, and STX3 for post-Golgi vesicle trafficking and sFLT1 secretion, while STX6, ARF1, and AP1 were required at the Golgi. Live-imaging of temporally controlled sFLT1 release from the endoplasmic reticulum showed clathrin-dependent sFLT1 trafficking at the Golgi into secretory vesicles that then trafficked to the plasma membrane. Depletion of STX6 altered vessel sprouting in 3D, suggesting that endothelial cell sFLT1 secretion influences proper vessel sprouting. Thus, specific trafficking components provide a secretory path from the Golgi to the plasma membrane for sFLT1 in endothelial cells that utilizes a specialized clathrin-dependent intermediate, suggesting novel therapeutic targets.

VISTA promotes the metabolism and differentiation of myeloid-derived suppressor cells by STAT3 and polyamine-dependent mechanisms

Myeloid-derived suppressor cells (MDSCs) impair antitumor immune responses. Identifying regulatory circuits during MDSC development may bring new opportunities for therapeutic interventions. We report that the V-domain suppressor of T cell activation (VISTA) functions as a key enabler of MDSC differentiation. VISTA deficiency reduced STAT3 activation and STAT3-dependent production of polyamines, which causally impaired mitochondrial respiration and MDSC expansion. In both mixed bone marrow (BM) chimera mice and myeloid-specific VISTA conditional knockout mice, VISTA deficiency significantly reduced tumor-associated MDSCs but expanded monocyte-derived dendritic cells (DCs) and enhanced T cell-mediated tumor control. Correlated expression of VISTA and arginase-1 (ARG1), a key enzyme supporting polyamine biosynthesis, was observed in multiple human cancer types. In human endometrial cancer, co-expression of VISTA and ARG1 on tumor-associated myeloid cells is associated with poor survival. Taken together, these findings unveil the VISTA/polyamine axis as a central regulator of MDSC differentiation and warrant therapeutically targeting this axis for cancer immunotherapy.

Organelle proteomic profiling reveals lysosomal heterogeneity in association with longevity

Lysosomes are active sites to integrate cellular metabolism and signal transduction. A collection of proteins associated with the lysosome mediate these metabolic and signaling functions. Both lysosomal metabolism and lysosomal signaling have been linked to longevity regulation; however, how lysosomes adjust their protein composition to accommodate this regulation remains unclear. Using deep proteomic profiling, we systemically profiled lysosome-associated proteins linked with four different longevity mechanisms. We discovered the lysosomal recruitment of AMP-activated protein kinase and nucleoporin proteins and their requirements for longevity in response to increased lysosomal lipolysis. Through comparative proteomic analyses of lysosomes from different tissues and labeled with different markers, we further elucidated lysosomal heterogeneity across tissues as well as the increased enrichment of the Ragulator complex on Cystinosin-positive lysosomes. Together, this work uncovers lysosomal proteome heterogeneity across multiple scales and provides resources for understanding the contribution of lysosomal protein dynamics to signal transduction, organelle crosstalk, and organism longevity.

Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images

Most of the time, the deep analysis of a biological sample requires the acquisition of images at different time points, using different modalities and/or different stainings. This information gives morphological, functional, and physiological insights, but the acquired images must be aligned to be able to proceed with the co-localisation analysis. Practically speaking, according to Aristotle's principle, "The whole is greater than the sum of its parts", multi-modal image registration is a challenging task that involves fusing complementary signals. In the past few years, several methods for image registration have been described in the literature, but unfortunately, there is not one method that works for all applications. In addition, there is currently no user-friendly solution for aligning images that does not require any computer skills. In this work, DS4H Image Alignment (DS4H-IA), an open-source ImageJ/Fiji plugin for aligning multimodality, immunohistochemistry (IHC), and/or immunofluorescence (IF) 2D microscopy images, designed with the goal of being extremely easy to use, is described. All of the available solutions for aligning 2D microscopy images have also been revised. The DS4H-IA source code; standalone applications for MAC, Linux, and Windows; video tutorials; manual documentation; and sample datasets are publicly available.

DARTS: an open-source Python pipeline for Ca2+ microdomain analysis in live cell imaging data

Ca2+ microdomains play a key role in intracellular signaling processes. For instance, they mediate the activation of T cells and, thus, the initial adaptive immune system. They are, however, also of utmost importance for activation of other cells, and a detailed understanding of the dynamics of these spatially localized Ca2+ signals is crucial for a better understanding of the underlying signaling processes. A typical approach to analyze Ca2+ microdomain dynamics is live cell fluorescence microscopy imaging. Experiments usually involve imaging a larger number of cells of different groups (for instance, wild type and knockout cells), followed by a time consuming image and data analysis. With DARTS, we present a modular Python pipeline for efficient Ca2+ microdomain analysis in live cell imaging data. DARTS (Deconvolution, Analysis, Registration, Tracking, and Shape normalization) provides state-of-the-art image postprocessing options like deep learning-based cell detection and tracking, spatio-temporal image deconvolution, and bleaching correction. An integrated automated Ca2+ microdomain detection offers direct access to global statistics like the number of microdomains for cell groups, corresponding signal intensity levels, and the temporal evolution of the measures. With a focus on bead stimulation experiments, DARTS provides a so-called dartboard projection analysis and visualization approach. A dartboard projection covers spatio-temporal normalization of the bead contact areas and cell shape normalization onto a circular template that enables aggregation of the spatiotemporal information of the microdomain detection results for the individual cells of the cell groups of interest. The dartboard visualization allows intuitive interpretation of the spatio-temporal microdomain dynamics at the group level. The application of DARTS is illustrated by three use cases in the context of the formation of initial Ca2+ microdomains after cell stimulation. DARTS is provided as an open-source solution and will be continuously extended upon the feedback of the community. Code available at: 10.5281/zenodo.10459243.

Microglial Refinement of A-Fiber Projections in the Postnatal Spinal Cord Dorsal Horn Is Required for Normal Maturation of Dynamic Touch

Sensory systems are shaped in postnatal life by the refinement of synaptic connectivity. In the dorsal horn of the spinal cord, somatosensory circuits undergo postnatal activity-dependent reorganization, including the refinement of primary afferent A-fiber terminals from superficial to deeper spinal dorsal horn laminae which is accompanied by decreases in cutaneous sensitivity. Here, we show in the mouse that microglia, the resident immune cells in the CNS, phagocytose A-fiber terminals in superficial laminae in the first weeks of life. Genetic perturbation of microglial engulfment during the initial postnatal period in either sex prevents the normal process of A-fiber refinement and elimination, resulting in an altered sensitivity of dorsal horn cells to dynamic tactile cutaneous stimulation, and behavioral hypersensitivity to dynamic touch. Thus, functional microglia are necessary for the normal postnatal development of dorsal horn sensory circuits. In the absence of microglial engulfment, superfluous A-fiber projections remain in the dorsal horn, and the balance of sensory connectivity is disrupted, leading to lifelong hypersensitivity to dynamic touch.

Differential endothelial cell cycle status in postnatal retinal vessels revealed using a novel PIP-FUCCI reporter and zonation analysis

Cell cycle regulation is critical to blood vessel formation and function, but how the endothelial cell cycle integrates with vascular regulation is not well-understood, and available dynamic cell cycle reporters do not precisely distinguish all cell cycle stage transitions in vivo. Here we characterized a recently developed improved cell cycle reporter (PIP-FUCCI) that precisely delineates S phase and the S/G2 transition. Live image analysis of primary endothelial cells revealed predicted temporal changes and well-defined stage transitions. A new inducible mouse cell cycle reporter allele was selectively expressed in postnatal retinal endothelial cells upon Cre-mediated activation and predicted endothelial cell cycle status. We developed a semi-automated zonation program to define endothelial cell cycle status in spatially defined and developmentally distinct retinal areas and found predicted cell cycle stage differences in arteries, veins, and remodeled and angiogenic capillaries. Surprisingly, the predicted dearth of proliferative tip cells at the vascular front was accompanied by an unexpected enrichment for endothelial tip cells in G2, suggesting G2 stalling as a contribution to tip-cell arrest. Thus, this improved reporter precisely defines endothelial cell cycle status in vivo and reveals novel G2 regulation that may contribute to unique aspects of blood vessel network expansion.

MAARS Software for Automatic and Quantitative Analysis of Mitotic Progression

In this chapter, we describe a software called MAARS (Mitotic Analysis And Recording System) that enables automatic and quantitative analysis of mitotic progression on an open-source platform. This computer-assisted analysis of cell division allows the unbiased acquisition of multiple parameters such as cell shape or size, metaphase or anaphase delays, as well as various mitotic abnormalities. This chapter describes the power of such an expert system to highlight the complexity of the mechanisms required to prevent mitotic chromosome segregation errors, leading to aneuploidy.

Believing is seeing - the deceptive influence of bias in quantitative microscopy

The visual allure of microscopy makes it an intuitively powerful research tool. Intuition, however, can easily obscure or distort the reality of the information contained in an image. Common cognitive biases, combined with institutional pressures that reward positive research results, can quickly skew a microscopy project towards upholding, rather than rigorously challenging, a hypothesis. The impact of these biases on a variety of research topics is well known. What might be less appreciated are the many forms in which bias can permeate a microscopy experiment. Even well-intentioned researchers are susceptible to bias, which must therefore be actively recognized to be mitigated. Importantly, although image quantification has increasingly become an expectation, ostensibly to confront subtle biases, it is not a guarantee against bias and cannot alone shield an experiment from cognitive distortions. Here, we provide illustrative examples of the insidiously pervasive nature of bias in microscopy experiments - from initial experimental design to image acquisition, analysis and data interpretation. We then provide suggestions that can serve as guard rails against bias.

Quantitation of ER Morphology and Dynamics

The plant endoplasmic reticulum forms a network of tubules connected by three-way junctions or sheet-like cisternae. Although the network is three-dimensional, in many plant cells, it is constrained to thin volume sandwiched between the vacuole and plasma membrane, effectively restricting it to a 2-D planar network. The structure of the network, and the morphology of the tubules and cisternae can be automatically extracted following intensity-independent edge-enhancement and various segmentation techniques to give an initial pixel-based skeleton, which is then converted to a graph representation. ER dynamics can be determined using optical flow techniques from computer vision or persistency analysis. Collectively, this approach yields a wealth of quantitative metrics for ER structure and can be used to describe the effects of pharmacological treatments or genetic manipulation. The software is publicly available.

Long-Term Imaging of Endoplasmic Reticulum Morphology in Embryos During Seed Germination

Imaging plant embryos at the cellular level over time is technically challenging, since the embryo, once its protective seed coat is removed, must be kept viable and unstressed on a microscope slide for the duration of the experiment. Here we describe a procedure and suitable apparatus for the visualization, over several days, of changes in endoplasmic reticulum (ER) morphology associated with the process of germination in Arabidopsis thaliana seeds. Moreover, we also present a user-friendly image analysis tool, which enables subtle perturbations in the ER network to be measured.

IST1 regulates select recycling pathways

ESCRTs (Endosomal Sorting Complex Required for Transports) are a modular set of protein complexes with membrane remodeling activities that include the formation and release of intraluminal vesicles (ILVs) to generate multivesicular endosomes. While most of the 12 ESCRT-III proteins are known to play roles in ILV formation, IST1 has been associated with a wider range of endosomal remodeling events. Here, we extend previous studies of IST1 function in endosomal trafficking and confirm that IST1, along with its binding partner CHMP1B, contributes to scission of early endosomal carriers. Functionally, depleting IST1 impaired delivery of transferrin receptor from early/sorting endosomes to the endocytic recycling compartment and instead increased its rapid recycling to the plasma membrane via peripheral endosomes enriched in the clathrin adaptor AP-1. IST1 is also important for export of mannose 6-phosphate receptor from early/sorting endosomes. Examination of IST1 binding partners on endosomes revealed that IST1 interacts with the MIT domain-containing sorting nexin SNX15, a protein previously reported to regulate endosomal recycling. Our kinetic and spatial analyses establish that SNX15 and IST1 occupy a clathrin-containing subdomain on the endosomal perimeter distinct from those previously implicated in cargo retrieval or degradation. Using live-cell microscopy, we see that SNX15 and CHMP1B alternately recruit IST1 to this subdomain or the base of endosomal tubules. These findings indicate that IST1 contributes to a subset of recycling pathways from the early/sorting endosome.

ImageJ in Computational Fractal-Based Neuroscience: Pattern Extraction and Translational Research

To explore questions asked in neuroscience, neuroscientists rely heavily on the tools available. One such toolset is ImageJ, open-source, free, biological digital image analysis software. Open-source software has matured alongside of fractal analysis in neuroscience, and today ImageJ is not a niche but a foundation relied on by a substantial number of neuroscientists for work in diverse fields including fractal analysis. This is largely owing to two features of open-source software leveraged in ImageJ and vital to vigorous neuroscience: customizability and collaboration. With those notions in mind, this chapter's aim is threefold: (1) it introduces ImageJ, (2) it outlines ways this software tool has influenced fractal analysis in neuroscience and shaped the questions researchers devote time to, and (3) it reviews a few examples of ways investigators have developed and used ImageJ for pattern extraction in fractal analysis. Throughout this chapter, the focus is on fostering a collaborative and creative mindset for translating knowledge of the fractal geometry of the brain into clinical reality.

Toward a common standard for data and specimen provenance in life sciences

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.

Multi-modal fusion network with intra- and inter-modality attention for prognosis prediction in breast cancer

Accurate breast cancer prognosis prediction can help clinicians to develop appropriate treatment plans and improve life quality for patients. Recent prognostic prediction studies suggest that fusing multi-modal data, e.g., genomic data and pathological images, plays a crucial role in improving predictive performance. Despite promising results of existing approaches, there remain challenges in effective multi-modal fusion. First, albeit a powerful fusion technique, Kronecker product produces high-dimensional quadratic expansion of features that may result in high computational cost and overfitting risk, thereby limiting its performance and applicability in cancer prognosis prediction. Second, most existing methods put more attention on learning cross-modality relations between different modalities, ignoring modality-specific relations that are complementary to cross-modality relations and beneficial for cancer prognosis prediction. To address these challenges, in this study we propose a novel attention-based multi-modal network to accurately predict breast cancer prognosis, which efficiently models both modality-specific and cross-modality relations without bringing in high-dimensional features. Specifically, two intra-modality self-attentional modules and an inter-modality cross-attentional module, accompanied by latent space transformation of channel affinity matrix, are developed to successfully capture modality-specific and cross-modality relations for efficient integration of genomic data and pathological images, respectively. Moreover, we design an adaptive fusion block to take full advantage of both modality-specific and cross-modality relations. Comprehensive experiment demonstrates that our method can effectively boost prognosis prediction performance of breast cancer and compare favorably with the state-of-the-art methods.

CD62L expression marks a functionally distinct subset of memory B cells

The memory B cell response consists of phenotypically distinct subsets that differ in their ability to respond upon antigen re-encounter. However, the pathways regulating the development and function of memory B cell subsets are poorly understood. Here, we show that CD62L and CD44 are progressively expressed on mouse memory B cells and identify transcriptionally and functionally distinct memory B cell subsets. Bcl6 is important in regulating memory B cell subset differentiation with overexpression of Bcl6 resulting in impaired CD62L+ memory B cell development. Bcl6 regulates memory B cell subset development through control of a network of genes, including Bcl2 and Zeb2. Overexpression of Zeb2 impairs the development of CD62L+ memory B cells. Importantly, CD62L is also differentially expressed on human memory B cells following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination and identifies phenotypically distinct populations. Together, these data indicate that CD62L expression marks functionally distinct memory B cell subsets.

Multiscale spatial segregation analysis in digital images of biofilms

Quantifying the degree of spatial segregation of two bacterial strains in mixed biofilms is an important topic in microbiology. Spatial segregation is dependent on spatial scale as two strains may appear to be well mixed if observed from a distance, but a closer look can reveal strong separation. Typically, this information is encoded in a digital image that represents the binary system, e.g., a microscopy image of a two species biofilm. To decode spatial segregation information, we have developed quantitative measures for evaluating the degree of the spatial scale-dependent segregation of two bacterial strains in a digital image. The constructed algorithm is based on the new segregation measures and overcomes drawbacks of existing approaches for biofilm segregation analysis. The new approach is implemented in a freely available software and was successfully applied to biofilms of two strains and bacterial suspensions for detection of the different spatial scale-dependent segregation levels.

Quantitative live-cell imaging of Candida albicans escape from immune phagocytes

Population-level dynamics of host-pathogen interactions can be characterized using quantitative live-cell imaging. Here, we present a protocol for infecting macrophages with the fungal pathogen Candida albicans in vitro and quantitative live-cell imaging of immune and pathogen responses. We describe steps for detailed image analysis and provide resources for quantification of phagocytosis and pathogen escape, as well as macrophage membrane permeabilization and viability. This protocol is modifiable for applications with a range of pathogens, immune cell types, and host-pathogen mechanisms. For complete details on the use and execution of this protocol, please refer to Olivier et al.1.

Axis convergence in C. elegans embryos

Embryos develop in a surrounding that guides key aspects of their development. For example, the anteroposterior (AP) body axis is always aligned with the geometric long axis of the surrounding eggshell in fruit flies and worms. The mechanisms that ensure convergence of the AP axis with the long axis of the eggshell remain unresolved. We investigate axis convergence in early C. elegans development, where the nascent AP axis, when misaligned, actively re-aligns to converge with the long axis of the egg. We identify two physical mechanisms that underlie axis convergence. First, bulk cytoplasmic flows, driven by actomyosin cortical flows, can directly reposition the AP axis. Second, active forces generated within the pseudocleavage furrow, a transient actomyosin structure similar to a contractile ring, can drive a mechanical re-orientation such that it becomes positioned perpendicular to the long axis of the egg. This in turn ensures AP axis convergence. Numerical simulations, together with experiments that either abolish the pseudocleavage furrow or change the shape of the egg, demonstrate that the pseudocleavage-furrow-dependent mechanism is a major driver of axis convergence. We conclude that active force generation within the actomyosin cortical layer drives axis convergence in the early nematode.