Biology subjects

Morgan, J.

Publications and source records attributed to Morgan, J..

32 records · Page 2Linked to original sources

bioRxiv2021

Multiple resource limitations explain biomass-precipitation relationships in grasslands

Interannual variability in grassland primary production is strongly driven by precipitation, nutrient availability and herbivory, but there is no general consensus on the mechanisms linking these variables. If grassland biomass is limited by the single most limiting resource at a given time, then we expect that nutrient addition will not affect biomass production at arid sites. We conducted a distributed experiment manipulating nutrients and herbivores at 44 grassland sites in 8 regions around the world, spanning a broad range in aridity. We estimated the effects of 5-11 years of nutrient addition and herbivore exclusion treatments on precipitation sensitivity of biomass (proportional change in biomass relative to proportional change in rainfall among years), and the biomass in the driest year (to measure treatment effects when water was most limiting) at each site. Grazer exclusion did not interact with nutrients to influence driest year biomass or sensitivity. Nutrient addition increased driest year biomass by 74% and sensitivity by 0.12 (proportional units), and that effect did not change across the range of aridity spanned by our sites. Grazer exclusion did not interact with nutrients to influence sensitivity or driest year biomass. At almost half of our sites, the previous year's rainfall explained as much variation in biomass as current year precipitation. Overall, our distributed fertilization experiment detected co-limitation between nutrients and water governing grasslands, with biomass sensitivity to precipitation being limited by nutrient availability irrespective of site aridity and herbivory. Our findings refute the classical ideas that grassland plant performance is limited by the single most limiting resource at a site. This suggests that nutrient eutrophication will destabilize grassland ecosystems through increased sensitivity to precipitation variation.

ecology↗

bioRxiv2021

Comparison of mouse models reveals the molecular bases for psychotic illness in Prader-Willi syndrome

Prader-Willi Syndrome (PWS) is a neurodevelopmental disorder caused by mutations affecting paternal chromosome 15q11-q13, and characterized by hypotonia, hyperphagia, impaired cognition and behavioural problems. Psychotic illness is a challenging problem for individuals with PWS and has different rates of prevalence in distinct PWS genotypes. Previously, we demonstrated behavioural and cognitive endophenotypes of relevance to psychiatric illness in a mouse model for one of the associated PWS genotypes, namely PWS-IC, in which deletion of the imprinting centre leads to loss of paternal imprinted gene expression and over-expression of Ube3a. Here we examine the broader gene expression changes that are specific to the psychiatric endophenotypes seen in this model. To do this we compared the brain transcriptomic profile of the PWS-IC mouse to the PWS-cr model that carries a deletion of the PWS minimal critical interval spanning the snoRNA Snord116 and Ipw. Firstly, we examined the same behavioural and cognitive endophenotypes of relevance to psychiatric illness in the PWS-cr mice. Unlike the PWS-IC mice, PWS-cr exhibit no differences in locomotor activity, sensory-motor gating, and attention. RNA-seq analysis of neonatal whole brain tissue revealed a greater number of transcriptional changes between PWS-IC and wild-type littermates, than between PWS-cr and wild-type littermates. Moreover, the differentially expressed genes in the PWS-IC brain were enriched for GWAS variants of episodes of psychotic illness but, interestingly, not schizophrenia. These data illustrate the molecular pathways that may underpin psychotic illness in PWS and have implication for potential therapeutic interventions.

neuroscience↗

bioRxiv2020

The influence of axial length upon the retinal ganglion cell layer of the human eye

PurposeWe examined the relationship between axial length and the thickness and volume of the ganglion cell layer (GCL) of the retina, and related these measures to the size of the optic chiasm. MethodsWe used optical coherence tomography to measure the thickness of the GCL over a 50{degrees} extent of the horizontal meridian in 50 normally-sighted participants with a wide range of axial lengths. Using a model eye informed by individual biometry, we converted GCL thickness to tissue volume per square degree. The volume of the optic chiasm was measured for 40 participants using magnetic resonance imaging. ResultsWhile GCL thickness decreases with increasing axial length, there is a positive relationship between GCL tissue volume and axial length, leading us to conclude that increasing axial length is associated with decreased retinal ganglion cell packing, increased cell size, or both. We characterize how retinal ganglion cell tissue varies systematically in volume and spatial distribution as a function of axial length. This model allows us to remove the effect of axial length from individual difference measures of GCL volume. We find that variation in GCL volume correlates well with the size of the optic chiasm as measured using magnetic resonance imaging. ConclusionsOur results provide the volume of ganglion cell tissue in the retina, adjusted for the effects of axial length upon ganglion cell size and/or packing. The resulting volume measure accounts for individual differences in the size of the optic chiasm, supporting its use to characterize the post-retinal visual pathway.

neuroscience↗

bioRxiv2020

Central vestibular tuning arises from patterned convergence of otolith afferents

As sensory information moves through the brain, higher-order areas exhibit more complex tuning than lower areas. Though models predict this complexity is due to convergent inputs from neurons with diverse response properties, in most vertebrate systems convergence has only been inferred rather than tested directly. Here we measure sensory computations in zebrafish vestibular neurons across multiple axes in vivo. We establish that whole-cell physiological recordings reveal tuning of individual vestibular afferent inputs and their postsynaptic targets. An independent approach, serial section electron microscopy, supports the inferred connectivity. We find that afferents with similar or differing preferred directions converge on central vestibular neurons, conferring more simple or complex tuning, respectively. Our data also resolve a long-standing contradiction between anatomical and physiological analyses by revealing that sensory responses are produced by sparse but powerful inputs from vestibular afferents. Together these results provide a direct, quantifiable demonstration of feedforward input convergence in vivo.

neuroscience↗

bioRxiv2019

Large-scale changes to mRNA polyadenylation in temporal lobe epilepsy

The molecular mechanisms that shape the gene expression landscape during the development and maintenance of chronic states of brain hyperexcitability are incompletely understood. Here we show that cytoplasmic mRNA polyadenylation, a posttranscriptional mechanism for regulating gene expression, undergoes widespread reorganisation in temporal lobe epilepsy. Specifically, over 25% of the hippocampal transcriptome displayed changes in their poly(A) tail in mouse models of epilepsy, particular evident in the chronic phase. The expression of cytoplasmic polyadenylation binding proteins (CPEB1-4) was found to be altered in the hippocampus in mouse models of epilepsy and temporal lobe epilepsy patients and CPEB4 target transcripts were over-represented among those showing poly(A) tail changes. Supporting an adaptive function, CPEB4-deficiency leads to an increase in seizure severity and neurodegeneration in mouse models of epilepsy. Together, these findings reveal an additional layer of gene expression control during epilepsy and point to novel targets for seizure control and disease-modification in epilepsy.

neuroscience↗

bioRxiv2019

A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern

INTRODUCTIONEpidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible and actionable the information produced by these studies was.\n\nMETHODSTo improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE and grey literature review, we identified studies that forecasted, predicted or simulated ecological or epidemiological phenomenon related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility and clarity by independent reviewers.\n\nRESULTS2034 studies were identified, of which n = 73 met eligibility criteria. Spatial spread, R0 (basic reproductive number) and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barre Syndrome burden (4%), sexual transmission risk (4%) and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%) and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions and 54% provided sufficient methodological detail allowing complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median 119 days sooner than journal publication dates, they were used in only 30% of studies.\n\nCONCLUSIONSMany ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response, it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics and pandemics.\n\nAuthor summaryResearchers published many studies which sought to predict and forecast important features of Zika virus (ZIKV) infections and their spread during the 2016-2017 ZIKV pandemic. We conducted a comprehensive review of such ZIKV prediction studies and evaluated their aims, the data sources they used, which methods were used, how timely they were published, and whether they provided sufficient information to be used or reproduced by others. Of the 73 studies evaluated, we found that the accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. We identified that the release of study findings before formal journal publication ( pre-prints) increased the timeliness of Zika prediction studies, but note they were infrequently used during this public health emergency. Addressing these areas can improve our understanding of Zika and other outbreaks and ensure that forecasts can inform preparedness and response to future outbreaks, epidemics and pandemics.

epidemiology↗

bioRxiv2019

Analyses of rare and common alleles in parent-proband trios implicate rare missense variants in SLC6A1 in schizophrenia and confirm the involvement of loss of function intolerant and neurodevelopmental disorder genes.

Schizophrenia is a highly polygenic disorder with important contributions coming from both common and rare risk alleles, the latter including CNVs and rare coding variants (RCVs), sometimes occurring as de novo variants (DNVs). We performed DNV analysis in whole exome-sequencing data obtained from a new sample of 613 schizophrenia trios, and combined this with published data for a total of 3,444 trios. Loss-of-function (LoF) DNVs were significantly enriched among 3,488 LoF intolerant genes in our new trio data (rate ratio (RR) (95% CI) = 2.23 (1.31, 3.79); p = 2.2 x 10-3), supporting previous findings. In the full dataset, genes associated with neurodevelopmental disorders (NDD; n=160) were significantly enriched for LoF DNVs (RR (95% CI) = 3.32 (2.0, 5.21); p = 7.4 x 10-6). Within this set of NDD genes, SLC6A1, encoding a gamma-aminobutyric acid transporter, was associated with missense-damaging DNVs (p = 5.2 x 10-5). Using data from a subset of 1,122 trios for which we had genome-wide common variant data, schizophrenia polygenic risk was significantly over-transmitted to probands (p = 2.6 x 10-60), as was bipolar disorder common variant polygenic risk (p = 5.7 x 10-17). We defined carriers of candidate schizophrenia-related DNVs as those with LoF or deletion DNVs in LoF intolerant or NDD genes. These individuals had significantly less over-transmission of common risk alleles than non-carriers (p = 3.5 x 10-4), providing robust support for the hypothesis that this set of DNVs is enriched for those related to schizophrenia.

genetics↗

bioRxiv2019

A high throughput multi-locus insecticide resistance marker panel for tracking resistance emergence and spread in Anopheles gambiae

The spread of resistance to insecticides in the mosquito vectors of diseases such as malaria and dengue poses a threat to the effectiveness of control programmes, which rely largely on insecticide-based interventions. Monitoring the resistance status of mosquito populations is therefore essential, but obtaining direct phenotypic measurements of resistance is laborious and error-prone. In contrast, high-throughput genotyping offers the prospect of quick and repeatable estimates of resistance, while also allowing the genotypic markers of resistance to be tracked and studied. We developed a panel of 28 known or putative markers of resistance in the major malaria vector Anopheles gambiae, which we use to test the association of these markers with resistance and to study their geographic distribution. We screened resistance-phenotyped An. gambiae from populations from a wide swathe of Sub-Saharan Africa (Burkina Faso, Ghana, Democratic Republic of Congo (DRC) and Kenya), and found evidence of resistance association for four mutations, including a novel mutation in the detoxification gene Gste2 (Gste2-119V). We also identified a gene duplication in Gste2 which combines a resistance-associated mutant form of the gene with its wild-type counterpart, potentially alleviating the costs of resistance. Finally, we describe the distribution of the multiple evolutionary origins of kdr resistance, finding unprecedented levels of diversity in the DRC. This panel represents the first step towards developing a quantitative predictive genotypic model of insecticide resistance that can be used to screen An. gambiae populations and predict resistance status.

evolutionary biology↗

bioRxiv2018

Regenerative capacity in the lamprey spinal cord is not altered after a repeated transection

The resilience of regeneration in vertebrate tissues is not well understood. Yet understanding how well tissues can regenerate after repeated insults, and identifying any limitations, is an important step towards elucidating the underlying mechanisms of tissue plasticity. This is particularly challenging in tissues such as the nervous system, which contain a large number of terminally differentiated cells (i.e. neurons) and that often exhibits limited regenerative potential in the first place. However, unlike mammals that exhibit very little spinal cord regeneration, many non-mammalian vertebrate species, including lampreys, fishes, amphibians and reptiles, regenerate their spinal cords and functionally recover even after a complete spinal cord transection. It is well established that lampreys undergo full functional recovery of swimming behaviors after a single spinal cord transection, which is accompanied by tissue repair at the lesion as well as axon and synapse regeneration. Here, using the lamprey model, we begin to explore resilience of spinal cord regeneration after a second spinal re-transection. We report that by all functional and anatomical measures tested, the lampreys regenerated after spinal re-transection just as robustly as after single transections. Recovery of swimming behaviors, axon regeneration, synapse and cytoskeletal distributions, and neuronal survival were nearly identical after a single spinal transection or a repeated transection. Thus, regenerative potential in the lamprey spinal cord is largely unaffected by spinal re-transection, indicating a greater persistent regenerative potential than exists in some other highly-regenerative models. These findings establish a new path for uncovering pro-regenerative targets that could be deployed in non-regenerative conditions.

neuroscience↗

bioRxiv2018

Disrupting folate metabolism alters the capacity of bacteria in exponential growth to develop persisters to antibiotics

Bacteria can survive high doses of antibiotics through stochastic phenotypic diversification.We present initial evidence that folate metabolism could be involved with the formation of persisters. The aberrant expression of the folate enzyme gene fau seems to reduce the incidence of persisters to antibiotics. Folate impaired bacteria had a lower generation rate for persisters to both antibiotics ampicillin and ofloxacin. Persister bacteria were detectable from the outset of the exponential growth phase in the complex media. Gene expression analyses showed tentatively distinctive profiles in exponential growth at times when bacteria persisters were observed. Levels of persisters were assessed in bacteria with altered, genetically and pharmacologically, folate metabolism. This work shows that by disrupting folate biosynthesis and usage, bacterial tolerance to antibiotics seems to be diminished. Based on these findings there is a possibility that bacteriostatic antibiotics such as antifolates could have a role to play in clinical settings where the incidence of antibiotic persisters seem to drive recalcitrant infections.

microbiology↗

bioRxiv2018

Interim impact evaluation of the hepatitis C virus elimination program in Georgia

Background and AimsGeorgia has one of the highest hepatitis C virus (HCV) prevalence rates in the world, with >5% of the adult population (~150,000 people) chronically infected. In April 2015, the Georgian government, in collaboration with CDC and other partners, launched a national program to eliminate HCV through scaling up HCV treatment and prevention interventions, with the aim of achieving a 90% reduction in prevalence by 2020. We evaluate the interim impact of the HCV treatment program as of 31 October 2017, and assess the feasibility of achieving the elimination goal by 2020.\n\nMethodWe developed a dynamic HCV transmission model to capture the current and historical epidemic dynamics of HCV in Georgia, including the main drivers of transmission. Using the 2015 national sero-survey and prior surveys conducted among people who inject drugs (PWID) from 1997-2015, the model was calibrated to data on HCV prevalence by age, gender and PWID status, and the age distribution of PWID. We use the model to project the interim impact of treatment strategies currently being undertaken as part of the ongoing Georgia HCV elimination program, while accounting for treatment failure/loss to follow up, in order to determine whether they are on track to achieving their HCV elimination target by 2020, or whether strategies need to be modified to ensure success.\n\nResultsA treatment rate of 2,050 patients/month was required from the beginning of the national program to achieve a 90% reduction in prevalence by the end of 2020, with equal treatment rates of PWID and the general population. From May 2015 to October 2017, 40,420 patients were treated, an average of ~1,350 per month; although the treatment rate has recently declined from a peak of 4,500/month in September 2016 to 2100/month in November-December 2016, and 1000/month in August-October 2017, with a sustained virological response rate (SVR) of 98% per-protocol or 78% intent to treat. The model projects that the treatments undertaken up to October 2017 have reduced adult chronic prevalence by 26% (18-35%) to 3.7% (2.9-5.1%), reduced total incidence by 25% (15-35%), and prevented 1845 (751-3969) new infections and 93 (31-177) HCV-related deaths. If the treatment rate of 1000 patients initiated per month continues, prevalence will have halved by 2020, and reduce by 90% by 2026. In order to reach a 90% reduction by 2020, the treatment rate must increase 3.5-fold to 4000/month.\n\nConclusionThe Georgia HCV elimination program has accomplished an impressive scale up of treatment, which has already impacted on prevalence and incidence, and averted deaths due to HCV. However, extensive scale up is needed to achieve a 90% reduction in prevalence by 2020.

epidemiology↗

bioRxiv2018

Association between schizophrenia and both loss of function and missense mutations in paralog conserved sites of voltage-gated sodium channels

Sequencing studies have highlighted candidate sets of genes involved in schizophrenia, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Two genes, SETD1A and RBM12, have also been associated with robust statistical evidence. Larger samples and novel methods for identifying disease-associated missense variants are needed to reveal novel genes and biological mechanisms associated with schizophrenia. We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5,207 cases and 4,991 controls. Included were members of ARC and NMDAR post-synaptic protein complexes, as well as voltage-gated sodium and calcium channels. We observed a significant case excess of rare (<0.1% in frequency) loss-of-function (LoF) mutations across all 187 genes (OR = 1.36; Pcorrected = 0.0072) but no individual gene was associated with schizophrenia after correcting for multiple testing. We found novel evidence that LoF and missense variants at paralog conserved sites were enriched in sodium channels (OR = 1.26; P = 0.0035). Meta-analysis of our new data with published sequencing data (11,319 cases, 15,854 controls and 1,136 trios) supported and refined this association to sodium channel alpha subunits (P = 0.0029). Meta-analysis also confirmed association between schizophrenia and rare variants in ARC (P = 4.0 x 10-4) and NMDAR (P = 1.7 x 10-5) synaptic genes. No association was found between rare variants in calcium channels and schizophrenia.\n\nIn one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis, and increase the evidence for association between rare variants in ARC and NMDAR post-synaptic complexes and schizophrenia. Larger samples are required to identify specific genes and variants driving these associations.\n\nAuthor SummaryCommon and rare genetic variations are known to play a substantial role in the development of schizophrenia. Recently, sequencing studies have started to highlight specific sets of genes that are enriched for rare variation in schizophrenia, such as the synaptic gene sets ARC and NMDAR, as well as voltage-gated sodium and calcium channels. To confirm the role of these gene sets in schizophrenia, and identify specific risk genes, we sequenced 187 genes in a new sample of 5,207 schizophrenia cases and 4,991 controls. We find an excess of protein truncating mutations with a frequency <0.1% in all 187 targeted genes, and provide novel evidence that mutations altering amino acids conserved across sodium channel proteins are risk factors for schizophrenia. Through meta-analysing our new data with previously published sequencing data sets, for a total of 11,319 cases, 15,854 controls and 1,136 trios, we increase the evidence for association between rare coding variants and schizophrenia in voltage-gated sodium channels, as well as in synaptic gene sets ARC and NMDAR. Although no individual gene was associated with schizophrenia, these findings suggest larger studies will identify the specific genes driving these associations.

genetics↗

bioRxiv2017

Programmable transport of micro- and nanoparticles by Paramecium caudatum

We exploit chemo- and galvanotactic behaviour of Paramecium caudatum to design a hybrid device that allows for controlled uptake, transport and deposition of environmental micro- and nanoparticulates in an aqueous medium. Manipulation of these objects is specific, programmable and parallel. We demonstrate how device operation and output interpretation may be automated via a DIY low-cost fluorescence spectrometer, driven by a microprocessor board. The applications of the device presented range from collection and detoxification of environmental contaminants (e.g. nanoparticles), to micromixing, to natural expressions of computer logic.

microbiology↗

bioRxiv2017

High-risk Autism Spectrum Disorder Utah pedigrees: a novel Shared Genomic Segments analysis.

Progress in gene discovery for Autism Spectrum Disorder (ASD) has been rapid over the past decade, with major successes in validation of risk of predominantly rare, penetrant, de novo and inherited mutations in over 100 genes (de Rubies et al., 2015; Sanders et al., 2015). However, the majority of individuals with ASD diagnoses do not carry a rare, penetrant genetic risk factor. In fact, recent estimates suggest that most of the genetic liability of ASD is due to as yet undiscovered common, less penetrant inherited variation (Gaugler et al., 2014) which is much more difficult to detect. The study of extended, high-risk families adds significant information in our search for these common inherited risk factors. Here, we present results of a new, powerful pedigree analysis method (Shared Genomic Segments--SGS) on three large families from the Utah Autism Research Program. The method improves upon previous methods by allowing for within-family heterogeneity, and identifying exact region boundaries and subsets of cases who share for targeted follow-up analyses. Our SGS analyses identified one genome-wide significant shared segment on chromosome 17 (q21.32, p=1.47x10-8). Additional regions with suggestive evidence were identified on chromosomes 3, 4, 6, 8, 11, 13, 14, 15, and 18. Several of these segments showed evidence of sharing across families. Genes of interest in these regions include ATP8A1, DOCK3, CACNA2D2, ITGB3, AMBRA1, FOLH1, DGKZ, MTHFS, ARNT2, BTN2A2, BTN3A1, BTN3A3, BTN2A1, and BTN1A1. We are exploring multiple other lines of evidence to follow up these implicated regions and genes.

genetics↗