Biology subjects

Jackson, A.

Publications and source records attributed to Jackson, A..

36 records · Page 2Linked to original sources

bioRxiv2023

Human Bone Marrow Plasma Cell Atlas: Maturation and Survival Pathways Unraveled by Single Cell Analyses

Human bone marrow (BM) plasma cells are heterogeneous, ranging from newly arrived antibody-secreting cells (ASC) to long-lived plasma cells (LLPC). We provide single cell transcriptional resolution of 17,347 BM ASC from 5 healthy adults. Fifteen clusters were identified ranging from newly minted ASC (cluster 1) expressing MKI67 and high MHC Class II that progressed to late clusters 5-8 through intermediate clusters 2-4. Additional clusters included early and late IgM-predominant ASC of likely extra-follicular origin; IFN-responsive; and high mitochondrial activity ASC. Late ASCs were distinguished by differences in G2M checkpoints, MTOR signaling, distinct metabolic pathways, CD38 expression, and utilization of TNF-receptor superfamily members. They mature through two distinct paths differentiated by the degree of TNF signaling through NFKB. This study provides the first single cell resolution atlas and molecular roadmap of LLPC maturation, thereby providing insight into differentiation trajectories and molecular regulation of these essential processes in the human BM microniche. This information enables investigation of the origin of protective and pathogenic antibodies in multiple diseases and development of new strategies targeted to the enhancement or depletion of the corresponding ASC. One Sentence Summary: The single cell transcriptomic atlas of human bone marrow plasma cell heterogeneity shows maturation of class-switched early and late subsets, specific IgM and Interferon-driven clusters, and unique heterogeneity of the late subsets which encompass the long-lived plasma cells.

immunology↗

bioRxiv2022

Circuit dissection and functional validation of a cross-species emotional biomarker

Emotional responses arise from limbic circuits including the hippocampus and amygdala. In the human brain, beta-frequency communication between these structures correlates with self-reported mood and anxiety. However, both the mechanism and significance of this biomarker as a readout vs. driver of emotional state remain unknown. Here we show that beta-frequency communication between the ventral hippocampus and basolateral amygdala also predicts anxiety-related behavior in mice on both long timescales ([~]30 min) and immediately preceding behavioral choices. Genetically encoded voltage indicators reveal that this biomarker reflects synchronization between somatostatin interneurons across both structures. Indeed, synchrony between these neurons dynamically predicts approach vs. avoidance, and optogenetically shifting this synchronization by just 25 msec is sufficient to bidirectionally modulate anxiety-related behaviors. Thus, back-translation establishes a human biomarker as a causal determinant (not just predictor) of emotional state, revealing a novel mechanism whereby interregional synchronization that is frequency-, phase- and cell type-specific controls anxiety processing.

neuroscience↗

bioRxiv2022

Conserved population dynamics in the cerebro-cerebellar system between waking and sleep

Despite the importance of the cerebellum for motor learning, and the recognised role of sleep in motor memory consolidation, surprisingly little is known about activity in the sleeping cerebro-cerebellar system. Here we used wireless recording from M1 and the cerebellum in monkeys to examine the relationship between patterns of single-unit spiking activity observed during waking behaviour and in natural sleep. Across the population of recorded units, we observed similarities in the timing of firing relative to local field potential features associated with both movements during waking and up-states during sleep. We also observed a consistent pattern of asymmetry in pair-wise cross-correlograms, indicative of preserved sequential firing in both wake and sleep at low frequencies. Despite the overall similarity in population dynamics between wake and sleep, there was a global change in the timing of cerebellar activity relative to motor cortex, from contemporaneous in the awake state, to motor cortex preceding the cerebellum in sleep. We speculate that similar population dynamics in waking and sleep may imply that cerebellar internal models are activated in both states, but that their output is decoupled from motor cortex in sleep. Nevertheless, spindle frequency coherence between the cerebellum and motor cortex may provide a mechanism for cerebellar computations to influence sleep-dependent learning processes in the cortex. Significance statementIt is well known that sleep can lead to improved motor performance. One possibility is that synaptic changes during sleep result from off-line repetitions of neuronal activity patterns in brain areas responsible for the control of movement. In this study we show for the first time that neuronal patterns in the cerebro-cerebellar system are conserved during both movements and sleep up-states, albeit with a shift in the relative timing between areas. Additionally, we show the presence of simultaneous M1-cerebellar spike coherence at spindle frequencies associated with up-state replay and postulate that this is a mechanism whereby a cerebellar internal models can shape plasticity in neocortical circuits during sleep.

neuroscience↗

bioRxiv2021

Characterization of light penetration through brain tissue, for optogenetic stimulation

The recent development of optogenetic tools, to manipulate neuronal activity using light, provides opportunities for novel brain-machine interface (BMI) control systems for treating neurological conditions. An issue of critical importance, therefore, is how well light penetrates through brain tissue. We took two different approaches to estimate light penetration through rodent brain tissue. The first employed so-called "nucleated patches" from cells expressing the light-activated membrane channel, channelrhodopsin (ChR2). By recording light-activated currents, we used these nucleated patches as extremely sensitive, microscopic, biological light-meters, to measure light penetration through 300-700{micro}m thick slices of rodent neocortical tissue. The nucleated patch method indicates that the effective illumination drops off with increasing tissue thickness, corresponding to a space constant of 317{micro}m (95% confidence interval between 248-441{micro}m). We compared this with measurements taken from directly visualizing the illumination of brain tissue, orthogonal to the direction of the light. This yielded a contour map of reduced illumination with distance, which along the direction of light delivery, had a space constant,{tau} 453{micro}m. This yields a lower extinction coefficient, {micro}e (the reciprocal of{tau} , [~]3mm-1) than previous estimates, implying better light penetration from LED sources than these earlier studies suggest.

neuroscience↗

bioRxiv2021

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay and seizures. To date, clinical features have been described for eleven patients with (likely) pathogenic SETD1B sequence variants. We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Interestingly, males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Finally, despite the possibility of non-redundant contributions of SETD1B and its paralogue SETD1A to epigenetic control, the clinical phenotypes of the related disorders share many similarities, indicating that elucidating shared and divergent downstream targets of both genes will help to understand the mechanism leading to the neurobehavioral phenotypes. Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome.

genetics↗

bioRxiv2021

An invariant Trypanosoma vivax vaccine antigen inducing protective immunity

Trypanosomes are protozoan parasites that cause infectious diseases including human African trypanosomiasis (sleeping sickness), and nagana in economically-important livestock animals1,2. An effective vaccine against trypanosomes would be an important control tool, but the parasite has evolved sophisticated immunoprotective mechanisms including antigenic variation3 that present an apparently insurmountable barrier to vaccination. Here we show using a systematic genome-led vaccinology approach4 and a murine model of Trypanosoma vivax infection5 that protective invariant subunit vaccine antigens can be identified. Vaccination with a single recombinant protein comprising the extracellular region of a conserved cell surface protein localised to the flagellum membrane termed "invariant flagellum antigen from T. vivax" (IFX) induced long-lasting protection. Immunity was passively transferred with immune serum, and recombinant monoclonal antibodies to IFX could induce sterile protection and revealed multiple mechanisms of antibody-mediated immunity, including a major role for complement. Our discovery identifies a vaccine candidate for an important parasitic disease that has constrained the socioeconomic development of sub-Saharan African countries6 and challenges long-held views that vaccinating against trypanosome infections cannot be achieved.

microbiology↗

bioRxiv2020

Peptide Ancestry Informative Markers in Uterine Neoplasms from Women of European, African and Asian Ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with molecular disease pathogenesis. Nonsynonymous single nucleotide polymorphisms (SNPs) encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis shows that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R2=0.9905). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues resulted in the quantitation of 62 pAIMs that correlate with self-described race and genotype-confirmed patient ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. These efforts describe a generalized set of markers for proteoancestry assessment that will further support studies investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

cancer biology↗

bioRxiv2020

Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression and a severe phenotype. Contrastingly, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay and encode truncated proteins, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability.

genetics↗

bioRxiv2020

Functional Predictors of Causative Cis-Regulatory Mutations in Mendelian Disease

Undiagnosed neurodevelopmental disease is significantly associated with rare variants in cis-regulatory elements (CRE) but demonstrating causality is challenging as target gene consequences may differ from a causative variant affecting the coding region. Here, we address this challenge by applying a procedure to discriminate likely diagnostic regulatory variants from those of neutral/low-penetrant effect. We identified six rare CRE variants using targeted and whole genome sequencing in 48 unrelated males with apparent X-linked intellectual disability (XLID) but without detectable coding region variants. These variants segregated appropriately in families and altered conserved bases in predicted CRE targeting known XLID genes. Three were unique and three were rare but too common to be plausibly causative for XLID. We compared the cis-regulatory activity of wild-type and mutant alleles in zebrafish embryos using dual-color fluorescent reporters. Two variants showed striking changes: one plausibly causative (FMR1CRE) and the other likely neutral/low-penetrant (TENM1CRE). These variants were "knocked-in" to mice and both altered embryonic neural expression of their target gene. Only Fmr1CRE mice showed disease-relevant behavioral defects. FMR1CRE is plausibly disease-associated resulting in complex misregulation of Fmr1/FMRP rather than loss-of-function. This is consistent both with absence of Fragile X syndrome in the probands and the observed electrophysiological anomalies in the FMR1CRE mouse brain. Although disruption of in vivo patterns of endogenous gene expression in disease-relevant tissues by CRE variants cannot be used as strong evidence for Mendelian disease association, in conjunction with extreme rarity in human populations and with relevant knock-in mouse phenotypes, such variants can become likely pathogenic.

genetics↗

bioRxiv2020

Optimizing spectral quality with quantum dots to enhance crop yield in controlled environments

Bioregenerative life-support systems (BLSS) involving plants will be required to realize self-sustaining human settlements beyond Earth. To improve plant photosynthetic efficiency in BLSS, the quality of the solar spectrum can be modified by lightweight, luminescent films. CuInS2/ZnS quantum dot (QD) films with peak emissions at 600 and 660 nm were used to redshift ultraviolet and blue photons to increase biomass accumulation in red romaine lettuce. Plant growth parameters, except spectral quality, were held constant among three equivalent production environments. Lettuce grown under the 600 and 660 nm-emitting QD films respectively increased edible dry mass (13% and 9%), edible fresh mass (11% each), and total leaf area (8% and 13%) compared to under a control film that contained no QDs. Spectral modifications by the luminescent QD films improved photosynthetic efficiency in lettuce and could enhance crop productivity in greenhouses on Earth or in space, where further improvements are expected from greater availability of ultraviolet photons for conversion.Competing Interest StatementAuthors CHP, DH, AJ, KR, HM, and MRB are employed by UbiQD, Inc. and also have equity in the company. Authors GAG and CHP were not employed by UbiQD, Inc. and had no equity in the company while conducting these experiments.View Full Text

plant biology↗

bioRxiv2020

Why scaling up uncertain predictions to higher levels of organisation will underestimate change

AO_SCPLOWBSTRACTC_SCPLOWUncertainty is an irreducible part of predictive science, causing us to over- or underestimate the magnitude of change that a system of interest will face. In a reductionist approach, we may use predictions at the level of individual system components (e.g. species biomass), and combine them to generate predictions for system-level properties (e.g. ecosystem function). Here we show that this process of scaling up uncertain predictions to higher levels of organization has a surprising consequence: it will systematically underestimate the magnitude of system-level change, an effect whose significance grows with the systems dimensionality. This stems from a geometrical observation: in high dimensions there are more ways to be more different, than ways to be more similar. This general remark applies to any complex system. Here we will focus on ecosystems thus, on ecosystem-level predictions generated from the combination of predictions at the species-level. In this setting, the ecosystems dimensionality is a measure of its diversity. We explain why dimensional effects do not play out when predicting change of a single linear aggregate property (e.g. total biomass), yet are revealed when predicting change of non-linear properties (e.g. absolute biomass change, stability or diversity), and when several properties are considered at once to describe the ecosystem, as in multi-functional ecology. Our findings highlight and describe the counter-intuitive effects of scaling up uncertain predictions, effects that will occur in any field of science where a reductionist approach is used to generate predictions.

ecology↗

bioRxiv2019

The kinase inhibitor AT9283 selectively kills colorectal cancer cells with hyperactive NRF2

Aberrant hyperactivation of NRF2 is a common event in many tumour types and associates with resistance to therapy and poor patient prognosis. The identification of ways to overcome the protection provided by NRF2 and selectively kill cancer cells addicted to NRF2 is a desirable goal. Exploiting the CRISPR/Cas9 technology, we generated colorectal cancer cell lines with hyperactive NRF2, and used them to perform a drug screen. We identified AT9283, an Aurora kinase inhibitor, for its selectivity towards killing cancer cells with hyperactive NRF2 as a consequence to either genetic or pharmacological activation. Our results show that hyperactivation of NRF2 presents a potential vulnerability that could be therapeutically exploited, and further suggest that AT9283, a drug that is currently in clinical trials, holds promise for the treatment of tumours with hyperactive NRF2.\n\nHighlightsO_LIWe present a new model for NRF2 hyperactivation in colorectal cancer cells.\nC_LIO_LIAT9283 selectively kills cancer cells with hyperactive NRF2\nC_LIO_LIBoth genetic and pharmacological activation of NRF2 sensitise cells to AT9283\nC_LI

cancer biology↗

bioRxiv2019

Library of model implementations for sharing deep-learning image segmentation and outcomes models

An open-source library of implementations for deep-learning based image segmentation and outcomes models is presented in this work. As oncology treatment planning becomes increasingly driven by automation, such a library of model implementations is crucial to (i) validate existing models on datasets collected at different institutions, (ii) automate segmentation, (iii) create ensembles for improving performance and (iv) incorporate validated models in the clinical workflow. The library was developed with Computational Environment for Radiological Research (CERR) software platform. CERR is a natural choice to centralize model implementations due to its comprehensiveness, popularity, and ease of use. CERR provides well-validated feature extraction for radiotherapy dosimetry and radiomics with fine control over the calculation settings. This allows users to select the appropriate feature calculation used in the model derivation. Models for automatic image segmentation are distributed via Singularity containers, with seamless i/o to and from CERR. Singularity containers allow for segmentation models to be deployed with a variety of scientific computing architectures. Deployment of models is driven by JSON configuration file, making it convenient to plug-in models. Models from the library can be called programmatically for batch evaluation. The library includes implementations for popular radiotherapy models outlined in the Quantitative Analysis of Normal Tissue Effects in the Clinic effort and recently published literature. Radiomics models include features from Image Biomarker Standardization features found to be important across multiple sites and image modalities. Deep learning-based image segmentation models include state of the art networks such as Deeplab and other problem-specific architectures. The library is distributed as GNU-copyrighted software at https://www.github.com/cerr/CERR.

bioinformatics↗

bioRxiv2019

Slow changes in seizure pathways in individual patients with focal epilepsy

Personalised medicine requires that treatments adapt to not only the patient, but changing factors within each individual. Although epilepsy is a dynamic disorder that is characterised by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network dynamics using intracranial recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures/patient). In all patients, we found variability in seizure paths through the space of possible network dynamics, producing either a spectrum or clusters of different dynamics. Seizures with similar pathways tended to occur closer together in time, and a simple model suggested that seizure pathways change on circadian and/or slower timescales in the majority of patients. These temporal relationships occurred independent of whether the patient underwent antiepileptic medication reduction. Our results suggest that various modulatory processes, operating at different timescales, shape within-patient seizure dynamics, leading to variable seizure pathways that may require tailored treatment approaches.

neuroscience↗

bioRxiv2018

Extrinsic and Intrinsic Dynamics in Movement Intermittency

What determines how we move in the world? Motor neuroscience often focusses either on intrinsic rhythmical properties of motor circuits or extrinsic sensorimotor feedback loops. Here we show that the interplay of both intrinsic and extrinsic dynamics is required to explain the intermittency observed in continuous tracking movements. Using spatiotemporal perturbations in humans, we demonstrate that apparently discrete submovements made 2-3 times per second reflect constructive interference between motor errors and continuous feedback corrections that are filtered by intrinsic circuitry in the motor system. Local field potentials in monkey motor cortex revealed characteristic signatures of a Kalman filter giving rise to both low-frequency cortical cycles during movement, and delta oscillations during sleep. We interpret these results within the framework of optimal feedback control, and suggest that the intrinsic rhythmicity of motor cortical networks reflects an internal model of external dynamics which is used for state estimation during feedback-guided movement.

neuroscience↗

bioRxiv2018

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

Cranial growth and development affects the closely related traits of head circumference (HC) and intracranial volume (ICV). Here we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV+HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood.

genetics↗

bioRxiv2018

Gene function contributes to gene expression levels in S. cerevisiae

It is not understood what evolutionary factors drive some genes to be expressed at a higher level than others. Here, we hypothesized that a genes function plays an important role in setting expression level. First, we established that each S. cerevisiae gene is maintained at a specific expression level by analyzing RNA-seq data from multiple studies. Next, we found that mRNA and protein levels were maintained for the orthologous genes in S. pombe, showing that gene function, conserved in orthologs, is important in setting expression level. To further explore the role of gene function in setting expression level, we analyzed mRNA and protein levels of S. cerevisiae genes within gene ontology (GO) categories. The GO framework systematically defines gene function based on experimental evidence. We found that several GO categories contain genes with statistically significant expression extremes; for example, genes involved in translation or energy production are highly expressed while genes involved in chromosomal activities, such as replication and transcription, are weakly expressed. Finally, we were able to predict expression levels using GO information alone. We created and optimized a linear equation that predicted a genes expression based on the genes membership in 161 GO categories. The greater number of GO categories with which a gene is associated, the more accurately expression could be predicted. Taken together, our analysis systematically demonstrates that gene function is an important determinant of expression level.

genetics↗

bioRxiv2017

Compact Standalone Platform for Neural Recording with Real-Time Spike Sorting and Data Logging

ObjectiveLongitudinal observation of single unit neural activity from large numbers of cortical neurons in awake and mobile animals is often a vital step in studying neural network behaviour and towards the prospect of building effective Brain Machine Interfaces (BMIs). These recordings generate enormous amounts of data for transmission & storage, and typically require offline processing to tease out the behaviour of individual neurons. Our aim was to create a compact system capable of: 1) reducing the data bandwidth by circa 3 orders of magnitude (greatly improving battery lifetime and enabling low power wireless transmission); 2) producing real-time, low-latency, spike sorted data; and 3) long term untethered operation. Approach. We have developed a headstage that operates in two phases. In the short training phase a computer is attached and classic spike sorting is performed to generate templates. In the second phase the system is untethered and performs template matching to create an event driven spike output that is logged to a micro-SD card. To enable validation the system is capable of logging the high bandwidth raw neural signal data as well as the spike sorted data. Main results. The system can successfully record 32 channels of raw neural signal data and/or spike sorted events for well over 24 hours at a time and is robust to power dropouts during battery changes as well as SD card replacement. A 24-hour initial recording in a non-human primate M1 showed consistent spike shapes with the expected changes in neural activity during awake behaviour and sleep cycles. Significance The presented platform allows neural activity to be unobtrusively monitored and processed in real-time in freely behaving untethered animals revealing insights that are not attainable through scheduled recording sessions and provides a robust, low-latency, low-bandwidth output suitable for BMIs, closed loop neuromodulation, wireless transmission and long term data logging.

bioengineering↗