Summary Solute carrier family 11 member 1 (SLC11A1) is critical for host resistance to diverse intracellular pathogens. During infection, SLC11A1 limits Salmonella’s access to iron, zinc, and magnesium, but only magnesium deprivation significantly impairs Salmonella replication. To understand the unexpected minor impact of iron, we determined Salmonella’s iron access in infected SLC11A1-deficient and normal mice. Using reporter strains and mass spectrometry of Salmonella purified from the spleen, we found that SLC11A1 caused growth-restricting iron deprivation in a subset of Salmonella. Volume electron microscopy revealed that another Salmonella subset circumvented iron restriction by targeting iron-rich endosomes in macrophages degrading red blood cells (erythrophagocytosis). These iron-replete bacteria dominated overall Salmonella growth, masking the effects of the other Salmonella subset’s iron deprivation. Thus, SLC11A1 effectively sequesters iron, but heterogeneous Salmonella populations partially bypass this nutritional immunity by targeting iron-rich tissue microenvironments.

No abstract available.

Phase separation is an important mechanism to generate certain biomolecular condensates and organize the cell interior. Condensate formation and function remain incompletely understood due to difficulties in visualizing the condensate interior at high resolution. Here, we analyzed the structure of biochemically reconstituted chromatin condensates through cryoelectron tomography. We found that traditional blotting methods of sample preparation were inadequate, and high-pressure freezing plus focused ion beam milling was essential to maintain condensate integrity. To identify densely packed molecules within the condensate, we integrated deep learning-based segmentation with context-aware template matching. Our approaches were developed on chromatin condensates and were also effective on condensed regions of in situ native chromatin. Using these methods, we determined the average structure of nucleosomes to 6.1 and 12 Å resolution in reconstituted and native systems, respectively, found that nucleosomes form heterogeneous interaction networks in both cases, and gained insight into the molecular origins of surface tension in chromatin condensates. Our methods should be applicable to biomolecular condensates containing large and distinctive components in both biochemical reconstitutions and certain cellular systems.

Preprint: https://www.biorxiv.org/content/10.1101/2024.12.01.626131v2

No abstract available.

In cancer progression, tumor microenvironments progressively become denser and hypoxic, and cell migrate toward higher oxygen levels as they invade across the tumor-stromal boundary. While cell invasion dependence on optimal collagen density is well appreciated, it remains unclear whether past oxygen conditions alter future invasion phenotype of cells. Here, we show that normal human mammary epithelial cells (MCF10A) and leader-like human breast tumor cells (BT549) undergo higher rates of invasion and collagen deformation after past exposure to hypoxia, compared to normoxia controls. Upon increasing collagen density by ∼50%, cell invasion under normoxia reduced, as expected due to the increased matrix crowding. However, surprisingly, past hypoxia increased cell invasion in future normoxic dense collagen, with more pronounced invasion of cancer cells. This culmination of cancer-related conditions of hypoxia history, tumor cell, and denser collagen led to more aggressive invasion phenotypes. We found that hypoxia-primed cancer cells produce laminin332, a basement membrane protein required for cell-matrix adhesions, which could explain the additional adhesion feedback from the matrix that led to invasion after hypoxia priming. Depletion of Cdh3 disrupts the hypoxia-dependent laminin production and thus disables the rise in rates of cancer cell invasion and collagen deformation caused by hypoxia memory. These findings highlight the importance of considering past oxygen conditions in combination with current mechanical composition of tissues to better understand tumor invasion in physically evolving tumor microenvironments.

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their functions. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse transgenic driver lines targeting 196 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. In addition, we identified correspondences between the cells in this collection and a recent connectomic data set of the ventral nerve cord. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neuronal circuits and connectivity of premotor circuits while linking them to behavioral outputs.

Modern microscopy methods incorporate computational modeling of optical systems as an integral part of the imaging process, either to solve inverse problems or enable optimization of the optical system design. These methods often depend on differentiable simulations of optical systems, yet no standardized framework exists—forcing computational optics researchers to repeatedly and independently implement simulations that are prone to errors, difficult to reuse in other applications, and often computationally suboptimal. These common problems limit the potential impact of computational optics as a field. We present Chromatix: an open-source, GPU-accelerated differentiable wave optics library. Chromatix builds on JAX to enable fast simulation of diverse optical systems and inverse problem solving, scaling these simulations from single-CPU laptops to multi-GPU servers. The library implements various optical elements (e.g., lenses, polarizers and spatial light modulators) and multiple light propagation models (e.g., Fresnel approximation, angular spectrum and off-axis propagation) that can be flexibly combined to model various computational optics applications such as snapshot microscopy, holography, and phase retrieval of multiple scattering samples. These simulations can be automatically parallelized to scale across multiple GPUs with a single-line change to the modeling code, enabling simulation and optimization of previously impractical optical system designs. We demonstrate Chromatix’s capacity to substantially accelerate optics simulation and optimization on existing methods in computational optics, speeding up optical simulation and optimization from 2-6× on a single GPU to up to 22× on 8 GPUs (depending on the particular system being modeled) compared to the original implementations. Chromatix establishes a standard for wave optics simulations, democratizing access to and expanding the design space of computational optics.i

Many animals navigate using optic flow, detecting rotational image velocity differences between their eyes to adjust direction. Forward locomotion produces strong symmetric translational optic flow that can mask these differences, yet the brain efficiently extracts these binocular asymmetries for course control. In Drosophila melanogaster, monocular horizontal system neurons facilitate detection of binocular asymmetries and contribute to steering. To understand these functions, we reconstructed horizontal system cells' central network using electron microscopy datasets, revealing convergent visual inputs, a recurrent inhibitory middle layer and a divergent output layer projecting to the ventral nerve cord and deeper brain regions. Two-photon imaging, GABA receptor manipulations and modeling, showed that lateral disinhibition reduces the output's translational sensitivity while enhancing its rotational selectivity. Unilateral manipulations confirmed the role of interneurons and descending outputs in steering. These findings establish competitive disinhibition as a key circuit mechanism for detecting rotational motion during translation, supporting navigation in dynamic environments.

Preprint: https://doi.org/10.1101/2023.08.06.552150

Modern algorithms for biological segmentation can match inter-human agreement in annotation quality. This however is not a performance bound: a hypothetical human-consensus segmentation could reduce error rates in half. To obtain a model that generalizes better we adapted the pretrained transformer backbone of a foundation model (SAM) to the Cellpose framework. The resulting Cellpose-SAM model substantially outperforms inter-human agreement and approaches the human-consensus bound. We increase generalization performance further by making the model robust to channel shuffling, cell size, shot noise, downsampling, isotropic and anisotropic blur. The new model can be readily adopted into the Cellpose ecosystem which includes finetuning, human-in-the-loop training, image restoration and 3D segmentation approaches. These properties establish Cellpose-SAM as a foundation model for biological segmentation.