Biology subjects

Mitchell, E.

Publications and source records attributed to Mitchell, E..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5x107 chemical synapses between [~]130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

neuroscience↗

bioRxiv2023

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types1. Neural cell types have previously been defined by morphology 2, 3, electrophysiology 4, 5, transcriptomic expression 6-8, connectivity 9-13, or even a combination of such modalities 14-16. More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells 17-20. Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex 21. It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type 22, 23 known to be Somatostatin positive (Sst+) 24, 25, were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

neuroscience↗

bioRxiv2023

NEURD: A mesh decomposition framework forautomated proofreading and morphologicalanalysis of neuronal EM reconstructions

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes meshed neurons into compact and extensively-annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state of the art automated proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

neuroscience↗

bioRxiv2023

Functional connectomics reveals general wiring rule in mouse visual cortex

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain implements computation. In the mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited to within V1, leaving much unknown about broader connectivity rules. In this study, we leverage the millimeter-scale MICrONS dataset to analyze synaptic connectivity and functional properties of individual neurons across cortical layers and areas. Our results reveal that neurons with similar responses are preferentially connected both within and across layers and areas -- including feedback connections -- suggesting the universality of the like-to-like connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections, beyond what could be explained by the physical proximity of axons and dendrites. We also found a higher-order rule where postsynaptic neuron cohorts downstream of individual presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on a simple classification task develop connectivity patterns mirroring both pairwise and higher-order rules, with magnitude similar to those in the MICrONS data. Lesion studies in these RNNs reveal that disrupting like-to-like connections has a significantly greater impact on performance compared to lesions of random connections. These findings suggest that these connectivity principles may play a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.

neuroscience↗

bioRxiv2023

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.

neuroscience↗

bioRxiv2022

Large-scale unsupervised discovery of excitatory morphological cell types in mouse visual cortex

Neurons in the neocortex exhibit astonishing morphological diversity which is critical for properly wiring neural circuits and giving neurons their functional properties. However, the organizational principles underlying this morphological diversity remain an open question. Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological "bar code" describing more than 30,000 excitatory neurons in mouse visual areas V1, AL and RL that were reconstructed from the millimeter scale MICrONS serial-section electron microscopy volume. Contrary to previous classifications into discrete morphological types (m-types), our data-driven approach suggests that the morphological landscape of cortical excitatory neurons is better described as a continuum, with a few notable exceptions in layers 5 and 6. Dendritic morphologies in layers 2-3 exhibited a trend towards a decreasing width of the dendritic arbor and a smaller tuft with increasing cortical depth. Inter-area differences were most evident in layer 4, where V1 contained more atufted neurons than higher visual areas. Moreover, we discovered neurons in V1 on the border to layer 5 which avoided deeper layers with their dendrites. In summary, we suggest that excitatory neurons morphological diversity is better understood by considering axes of variation than using distinct m-types.

neuroscience↗

bioRxiv2022

Quantitative Census of Local Somatic Features in Mouse Visual Cortex

Mammalian neocortex contains a highly diverse set of cell types. These types have been mapped systematically using a variety of molecular, electrophysiological and morphological approaches. Each modality offers new perspectives on the variation of biological processes underlying cell type specialization. Cellular scale electron microscopy (EM) provides dense ultrastructural examination and an unbiased perspective into the subcellular organization of brain cells, including their synaptic connectivity and nanometer scale morphology. It also presents a clear challenge for analysis to identify cell-types in data that contains tens of thousands of neurons, most of which have incomplete reconstructions. To address this challenge, we present the first systematic survey of the somatic region of all cells within a cubic millimeter of cortex using quantitative features obtained from EM. This analysis demonstrates a surprising sufficiency of the perisomatic region to identify cell-types, including types defined primarily based on their connectivity patterns. We then describe how this classification facilitates cell type specific connectivity characterization and locating cells with rare connectivity patterns in the dataset.

neuroscience↗

bioRxiv2022

Petascale pipeline for precise alignment of images from serial section electron microscopy

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

neuroscience↗

bioRxiv2021

Clonal dynamics of haematopoiesis across the human lifespan

Age-related change in human haematopoiesis causes reduced regenerative capacity1, cytopenias2, immune dysfunction3 and increased risk of blood cancer. The cellular alterations that underpin the abruptness of this functional decline after the age of 70 years remain elusive. We sequenced 3579 genomes from single-cell-derived colonies of haematopoietic stem cell/multipotent progenitors (HSC/MPPs) across 10 haematologically normal subjects aged 0-81 years. HSC/MPPs accumulated 17 mutations/year after birth and lost 30bp/year of telomere length. Haematopoiesis in adults aged <65 was massively polyclonal, with high indices of clonal diversity and a stable population of 20,000-200,000 HSC/MPPs contributing evenly to blood production. In contrast, haematopoiesis in individuals aged >75 showed profoundly decreased clonal diversity. In each elderly subject, 30-60% of haematopoiesis was accounted for by 12-18 independent clones, each contributing 1-34% of blood production. Most clones had begun their expansion before age 40, but only 22% had known driver mutations. Genome-wide selection analysis estimated that 1/34 to 1/12 non-synonymous mutations were drivers, occurring at a constant rate throughout life, affecting a wider pool of genes than identified in blood cancers. Loss of Y chromosome conferred selective benefits on HSC/MPPs in males. Simulations from a simple model of haematopoiesis, with constant HSC population size and constant acquisition of driver mutations conferring moderate fitness benefits, entirely explained the abrupt change in clonal structure in the elderly. Rapidly decreasing clonal diversity is a universal feature of haematopoiesis in aged humans, underpinned by pervasive positive selection acting on many more genes than currently identified.

genomics↗

bioRxiv2021

The longitudinal dynamics and natural history of clonal haematopoiesis

Human cells acquire somatic mutations throughout life, some of which can drive clonal expansion. Such expansions are frequent in the haematopoietic system of healthy individuals and have been termed clonal haematopoiesis (CH). While CH predisposes to myeloid neoplasia and other diseases, we have limited understanding of how and when CH develops, what factors govern its behaviour, how it interacts with ageing and how these variables relate to malignant progression. Here, we track 697 CH clones from 385 individuals aged 55 or older over a median of 13 years. We find that 92.4% of clones expanded at a stable exponential rate over the study period, with different mutations driving substantially different growth rates, ranging from 5% (DNMT3A, TP53) to over 50%/yr (SRSF2-P95H). Growth rates of clones with the same mutation differed by approximately +/-5%/yr, proportionately impacting "slow" drivers more substantially. By combining our time-series data with phylogenetic analysis of 1,731 whole genome-sequenced haematopoietic colonies from 7 older individuals, we reveal distinct patterns of lifelong clonal behaviour. DNMT3A-mutant clones preferentially expanded early in life and displayed slower growth in old age, in the context of an increasingly competitive oligoclonal landscape. By contrast, splicing gene mutations only drove expansion later in life, while growth of TET2-mutant clones showed minimal age-dependency. Finally, we show that mutations driving faster clonal growth carry a higher risk of malignant progression. Our findings characterise the lifelong natural history of CH and give fundamental insights into the interactions between somatic mutation, ageing and clonal selection.

cancer biology↗

bioRxiv2021

Petascale neural circuit reconstruction: automated methods

3D electron microscopy (EM) has been successful at mapping invertebrate nervous systems, but the approach has been limited to small chunks of mammalian brains. To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels as axon, dendrite, soma, and other semantic categories, and detect synapses and assign them to presynaptic and postsynaptic segments. The output of neuronal boundary detection is segmented by mean affinity agglomeration with semantic and size constraints. Pipeline operations are implemented by leveraging distributed and cloud computing. Intermediate results of the pipeline are held in cloud storage, and can be effortlessly viewed as images, which aids debugging. We applied the pipeline to create an automated reconstruction of an EM image volume spanning four visual cortical areas of a mouse brain. Code for the pipeline is publicly available, as is the reconstructed volume.

neuroscience↗

bioRxiv2021

Functional connectomics spanning multiple areas of mouse visual cortex

To understand the brain we must relate neurons functional responses to the circuit architecture that shapes them. Here, we present a large functional connectomics dataset with dense calcium imaging of a millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm) in an awake mouse viewing natural movies and synthetic stimuli. The functional data were co-registered with a volumetric electron microscopy (EM) reconstruction containing more than 200,000 cells and 0.5 billion synapses. Subsequent proofreading of a subset of neurons in this volume yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Here, we release this dataset as an open-access resource to the scientific community including a set of tools that facilitate data retrieval and downstream analysis. In accompanying papers we describe our findings using the dataset to provide a comprehensive structural characterization of cortical cell types1-3 and the most detailed synaptic level connectivity diagram of a cortical column to date2, uncovering unique cell-type specific inhibitory motifs that can be linked to gene expression data4. Functionally, we identify new computational principles of how information is integrated across visual space5, characterize novel types of neuronal invariances6 and bring structure and function together to decipher a general principle that wires excitatory neurons within and across areas7, 8.

neuroscience↗

bioRxiv2021

Genome-wide mutational signatures of immunological diversification in normal lymphocytes

A lymphocyte suffers many threats to its genome, including programmed mutation during differentiation, antigen-driven proliferation and residency in diverse microenvironments. After developing protocols for single-cell lymphocyte expansions, we sequenced whole genomes from 717 normal naive and memory B and T lymphocytes and hematopoietic stem cells. Lymphocytes carried more point mutations and structural variation than stem cells, accruing at higher rates in T than B cells, attributable to both exogenous and endogenous mutational processes. Ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every one on-target IGV mutation during the germinal center reaction. Structural variation was 16-fold higher in lymphocytes than stem cells, with ~15% of deletions being attributable to off-target RAG activity. One Sentence SummaryThe mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.

genomics↗

bioRxiv2020

FlyWire: Online community for whole-brain connectomics

Due to advances in automated image acquisition and analysis, new whole-brain connectomes beyond C. elegans are finally on the horizon. Proofreading of whole-brain automated reconstructions will require many person-years of effort, due to the huge volumes of data involved. Here we present FlyWire, an online community for proofreading neural circuits in a fly brain, and explain how its computational and social structures are organized to scale up to whole-brain connectomics. Browser-based 3D interactive segmentation by collaborative editing of a spatially chunked supervoxel graph makes it possible to distribute proofreading to individuals located virtually anywhere in the world. Information in the edit history is programmatically accessible for a variety of uses such as estimating proofreading accuracy or building incentive systems. An open community accelerates proofreading by recruiting more participants, and accelerates scientific discovery by requiring information sharing. We demonstrate how FlyWire enables circuit analysis by reconstructing and analysing the connectome of mechanosensory neurons.

neuroscience↗

bioRxiv2020

Elevated somatic mutation burdens in normal human cells due to defective DNA polymerases

Mutation accumulation over time in normal somatic cells contributes to cancer development and is proposed as a cause of ageing. DNA polymerases Pol {varepsilon} and Pol {delta} replicate DNA with high fidelity during normal cell divisions. However, in some cancers defective proofreading due to acquired mutations in the exonuclease domains of POLE or POLD1 causes markedly elevated somatic mutation burdens with distinctive mutational signatures. POLE and POLD1 exonuclease domain mutations also cause familial cancer predisposition when inherited through the germline. Here, we sequenced normal tissue DNA from individuals with germline POLE or POLD1 exonuclease domain mutations. Increased mutation burdens with characteristic mutational signatures were found to varying extents in all normal adult somatic cell types examined, during early embryogenesis and in sperm. Mutation burdens were further markedly elevated in neoplasms from these individuals. Thus human physiology is able to tolerate ubiquitously elevated mutation burdens. Indeed, with the exception of early onset cancer, individuals with germline POLE and POLD1 exonuclease domain mutations are not reported to show abnormal phenotypic features, including those of premature ageing. The results, therefore, do not support a simple model in which all features of ageing are attributable to widespread cell malfunction directly resulting from somatic mutation burdens accrued during life.

genomics↗

bioRxiv2020

Estimating daily intakes of manganese due to breast milk, infant formulas, or young child nutritional beverages in the United States and France: Comparison to sufficiency and toxicity thresholds

Background Although manganese (Mn) is an essential nutrient, recent research has revealed that excess Mn in early childhood may have adverse effects on neurodevelopment.Methods We estimated daily total Mn intake due to breast milk at average body weights by reviewing reported concentrations of breast milk Mn and measurements of body weight and breast milk intake at 3 weeks, 4.25 months, 7 months, and 18 months. We compared these figures to the Mn content measured in 44 infant, follow-up, and toddler formulas purchased in the United States and France. We calculated Mn content of formula products made with ultra-trace elemental analysis grade water (0 µg Mn/L) and with water containing 250 µg Mn/L, a concentration which is relatively high but less than the World Health Organization Health-based value of 400 µg Mn/L or the United States Environmental Protection Agency Health Advisory of 350 µg Mn/L.Results Estimated mean daily Mn intake from breast milk ranged from 1.2 µg Mn/kg/day (3 weeks) to 0.16 µg Mn/kg/day (18 months), with the highest intakes at the youngest age stage we considered, 3 weeks. Estimated daily Mn intake from formula products reconstituted with 0 µg Mn/L water ranged from 130 µg Mn/kg/day (3 weeks) to 4.8 µg Mn/kg/day (18 months) with the highest intakes at 3 weeks. Formula products provided 28 to 520 times greater than the mean daily intake of Mn from breast milk for the 4 age stages that we considered. Estimated daily Mn intake from formula products reconstituted with water containing 250 µg Mn/L ranged from 12 µg Mn/kg/day to 170 µg Mn/kg/day, which exceeds the United States Environmental Protection Agency Reference Dose of 140 µg Mn/kg/day for adults.Conclusions Mn deficiency is highly unlikely with exclusive breast milk or infant formula feeding, but established tolerable daily intake levels for Mn may be surpassed by some of these products when following labeled instructions.HighlightsMn deficiency is unlikely with exclusive breast milk or infant formula feeding.Breast milk Mn mean intake is 1.2 µg/kg/day (3 weeks)-0.16 µg/kg/day (18 months).Formula Mn intake range is 130 µg/kg/day (3 weeks)-4.8 µg/kg/day (18 months).Formula products reconstituted with 250 µg Mn/L water may exceed 140 µg Mn/kg/day.Formula products may surpass regulatory tolerable daily intake levels for Mn.Competing Interest StatementThe authors have declared no competing interest.1 List of abbreviationsAIAdequate IntakeANSESAgence nationale de sécurité sanitaire de l’alimentation, de l’environnement et du travail (French Agency for Food, Environmental and Occupational Health & Safety)DJAdose journalière admissible (daily admissible dose, tolerable daily intake)EFSAEuropean Food Safety AuthorityEUEuropean UnionFAOFood and Agriculture OrganizationHBVHealth-Based ValueINSPQInstitut national de santé publique du Québec (National Institute of Public Health of Québec)IOMInstitute of MedicineIQintelligence quotientJECFAJoint FAO/WHO Expert Committee on Food AdditivesLOAELLowest Observed Adverse Effect LevelMnManganeseMnSODmanganese superoxide dismutaseMRmagnetic resonanceNOAELNo Observed Adverse Effect LevelPIXEparticle induced X-ray emissionPNparental nutritionRBSRutherford backscatteringRfDReference DoseSCFScientific Committee on FoodT1RT1 relaxationTPNtotal parenteral nutritionU.S.United States Environmental Protection AgencyEPAEnvironmental Protection AgencyUSUnited StatesView Full Text

pharmacology and toxicology↗

bioRxiv2020

Lineage tracing of human embryonic development and foetal haematopoiesis through somatic mutations

To date, ontogeny of the human haematopoietic system during foetal development has been characterized mainly through careful microscopic observations. Here we used whole-genome sequencing (WGS) of 511 single-cell derived haematopoietic colonies from healthy human foetuses of 8 and 18 post-conception weeks (pcw) coupled with deep targeted sequencing of tissues of known embryonic origin to reconstruct a phylogenetic tree of blood development. We found that in healthy foetuses, individual haematopoietic progenitors acquire tens of somatic mutations by 18 pcw. Using these mutations as barcodes, we timed the divergence of embryonic and extra-embryonic tissues during development and estimated the number of blood antecedents at different stages of embryonic development. Our analysis has shown that ectoderm originates from a smaller set of blood antecedents compared to endoderm and mesoderm. Finally, our data support a hypoblast origin of the extra-embryonic mesoderm and primitive blood in humans.

genomics↗

bioRxiv2019

Prophylactic host behaviour discourages pathogen exploitation

Much work has considered the evolution of pathogens, but little is known about how they respond to changes in host behaviour. We build a model where hosts are able to choose to engage in prophylactic measures that reduce the likelihood of disease transmission. This choice is mediated by costs and benefits associated with prophylaxis, but the fraction of hosts engaged in prophylaxis is also affected by population dynamics. We identify a critical cost threshold above which hosts do not engage in prophylaxis. Below the threshold, prophylactic host behaviour does occur and pathogen virulence, measured by the extent to which it exploits its host, is reduced by the action of selection relative to the level that would otherwise be predicted in the absence of prophylaxis. Our work emphasizes the significance of the dual nature of the trade-off faced by the pathogen between balancing transmission and recovery, and creating new infections in hosts engaging or not engaging in prophylaxis.

evolutionary biology↗