Ion beam subcellular tomography, bioRxiv, 2019-02-23
Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional subcellular MIBI is presented. We term the approach ion beam tomography (IBT) wherein ion beam images are acquired iteratively across successive, multiple scans and later compiled into a 3D format. For IBT, cells were imaged at 0.2-4 pA ion current across 1,000 axial scans. Consecutive subsets of ion beam images were binned over 3 to 20 slices (above and below) to create a resolved image, wherein binning was incremented one slice at a time to yield an enhanced multi-depth data without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, was then applied to the transformed ion image series using a hybrid deblurring algorithm and an ion beam current-dependent point-spread function. Three-dimensional processing was implemented by segmentation, mesh, molecular neighborhoods, and association maps. In cultured cancer cells and tissues, IBT enabled accessible visualization of three-dimensional volumetric distributions of genomic regions, RNA transcripts, and protein factors with 65-nm lateral and 5-nm axial resolution. IBT also enabled label-free elemental mapping of cells, allowing point of source cellular component measurements not possible for most optical microscopy targets. Detailed multiparameter imaging of subcellular features at near macromolecular resolution should now be made possible by the IBT tools and reagents provided here to open novel venues for interrogating subcellular biology.
biorxiv systems-biology 100-200-users 2019Subcellular localization of drug distribution by super-resolution ion beam imaging, bioRxiv, 2019-02-22
Technologies that visualize multiple biomolecules at the nanometer scale in cells will enable deeper understanding of biological processes that proceed at the molecular scale. Current fluorescence-based methods for microscopy are constrained by a combination of spatial resolution limitations, limited parameters per experiment, and detector systems for the wide variety of biomolecules found in cells. We present here super-resolution ion beam imaging (srIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added small molecules. Uniquely, the atomic constituents of the biomolecules themselves can often be used in our system as the tag. We visualized the subcellular localization of the chemotherapy drug cisplatin simultaneously with localization of five other nuclear structures, with further carbon elemental mapping and secondary electron visualization, down to ~30 nm lateral resolution. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. These data highlight how multiplexed super-resolution techniques, such as srIBI, will enable studies of biomolecule distributions in biologically relevant subcellular microenvironments.
biorxiv systems-biology 200-500-users 2019Full-length mRNA sequencing reveals principles of poly(A) tail length control, bioRxiv, 2019-02-12
Although mRNAs are key molecules for understanding life, there exists no method to determine the full-length sequence of endogenous mRNAs including their poly(A) tails. Moreover, although poly(A) tails can be modified in functionally important ways, there also exists no method to accurately sequence them. Here, we present FLAM-seq, a rapid and simple method for high-quality sequencing of entire mRNAs. We report a cDNA library preparation method coupled to single-molecule sequencing to perform FLAM-seq. Using human cell lines, brain organoids, and C. elegans we show that FLAM-seq delivers high-quality full-length mRNA sequences for thousands of different genes per sample. We find that (a) 3' UTR length is correlated with poly(A) tail length, (b) alternative polyadenylation sites and alternative promoters for the same gene are linked to different tail lengths, (c) tails contain a significant number of cytosines. Thus, we provide a widely useful method and fundamental insights into poly(A) tail regulation.
biorxiv systems-biology 100-200-users 2019Short-range interactions govern cellular dynamics in microbial multi-genotype systems, bioRxiv, 2019-01-27
Ecosystem processes result from interaction between organisms. When interactions are local, the spatial organization of organisms defines their network of interactions, and thus influences the system's functioning. This can be especially relevant for microbial systems, which often consist of spatially structured communities of cells connected by a dense interaction network. Here we measured the spatial interaction network between cells in microbial systems and identify the factors that determine it. Combining quantitative single-cell analysis of synthetic bacterial communities with mathematical modeling, we find that cells only interact with other cells in their immediate neighbourhood. This short interaction range impacts the functioning of the whole system by reducing its ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of cell-to-cell interaction plays a fundamental role in understanding and controlling natural communities, and in engineering microbial systems for specific purposes.
biorxiv systems-biology 100-200-users 2019Statistical physics of liquid brains, bioRxiv, 2018-11-27
Liquid neural networks (or “liquid brains”) are a widespread class of cognitive living networks characterised by a common feature the agents (ants or immune cells, for example) move in space. Thus, no fixed, long-term agent-agent connections are maintained, in contrast with standard neural systems. How is this class of systems capable of displaying cognitive abilities, from learning to decision-making? In this paper, the collective dynamics, memory and learning properties of liquid brains is explored under the perspective of statistical physics. Using a comparative approach, we review the generic properties of three large classes of systems, namely standard neural networks (“solid brains”), ant colonies and the immune system. It is shown that, despite their intrinsic physical differences, these systems share key properties with standard neural systems in terms of formal descriptions, but strongly depart in other ways. On one hand, the attractors found in liquid brains are not always based on connection weights but instead on population abundances. However, some liquid systems use fluctuations in ways similar to those found in cortical networks, suggesting a relevant role of criticality as a way of rapidly reacting to external signals.
biorxiv systems-biology 500+-users 2018Lineage tracing on transcriptional landscapes links state to fate during differentiation, bioRxiv, 2018-11-11
AbstractA challenge in stem cell biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Though the development of single cell assays allows for the capture of progenitor cell states in great detail, these assays cannot definitively link cell states to their long-term fate. Here, we use expressed DNA barcodes to clonally trace single cell transcriptomes dynamically during differentiation and apply this approach to the study of hematopoiesis. Our analysis identifies functional boundaries of cell potential early in the hematopoietic hierarchy and locates them on a continuous transcriptional landscape. We reconstruct a developmental hierarchy showing separate ontogenies for granulocytic subtypes and two routes to monocyte differentiation that leave a persistent imprint on mature cells. Finally, we use our approach to benchmark methods of dynamic inference from single-cell snapshots, and provide evidence of strong early fate biases dependent on cellular properties hidden from single-cell RNA sequencing.
biorxiv systems-biology 100-200-users 2018