Biology subjects

Jones, E.

Publications and source records attributed to Jones, E..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Impact of cryopreservation on immune cell metabolism as measured by SCENITH.

The dynamic functioning of immune cells is regulated by cellular metabolic processes, and there is growing interest in the study of immunometabolic correlates of dysfunctional immune responses. SCENITH is a novel flow cytometry-based technique that allows for ex vivo metabolic profiling of immune cells within heterogeneous samples. Cryopreservation of clinical samples is frequently undertaken to facilitate high throughput processing, but is thought to lead to cellular metabolic dysfunction. We aimed to investigate the impact of cryopreservation on immune cell metabolism, harnessing SCENITHs unique ability to describe the divergent bioenergetic characteristics of distinct immune cell subsets. We demonstrate that T cells undergoing activation with a CD3/CD28 stimulus are less readily metabolically reprogrammed following cryopreservation. Additionally, we find that cryopreservation introduces a time-dependent metabolic artefact that favours glycolysis and impairs oxidative phosphorylation, suggesting that cryopreservation results in mitochondrial dysfunction. Despite this artefact, SCENITH was still able to reveal the distinct bioenergetic profiles of contrasting immune cells populations following cryopreservation - for example, non-classical monocytes have a higher mitochondrial dependence than classical monocytes, and T cell CD69 expression is associated with an upregulation of glycolytic capacity. Whilst we believe that SCENITH can provide valuable information about immune cell metabolism even in cryopreserved samples, our findings have important implications for the design of future studies. Investigators should carefully consider how to process and store clinical samples to ensure that cryopreservation does not confound analyses, particularly where longitudinal sampling is required.

immunology↗

bioRxiv2023

A polydiolcitrate-MoS2 composite for 3D printing Radio-opaque, Bioresorbable Vascular Scaffolds

Implantable polymeric biodegradable devices, such as biodegradable vascular stents or scaffolds, cannot be fully visualized using standard X-ray-based techniques, compromising their performance due to malposition after deployment. To address this challenge, we describe composites of methacrylated poly(1,12 dodecamethylene citrate) (mPDC) and MoS2 nanosheets to fabricate novel X-ray visible radiopaque and photocurable liquid polymer-ceramic composite (mPDC-MoS2). The composite was used as an ink with micro continuous liquid interface production (CLIP) to fabricate bioresorbable vascular scaffolds (BVS). Prints exhibited excellent crimping and expansion mechanics without strut failures and, importantly, required X-ray visibility in air and muscle tissue. Notably, MoS2 nanosheets displayed physical degradation over time in a PBS environment, indicating the potential for producing bioresorbable devices. mPDC-MoS2 is a promising bioresorbable X-ray-visible composite material suitable for 3D printing medical devices, particularly vascular scaffolds or stents, that require non-invasive X-ray-based monitoring techniques for implantation and evaluation. This innovative composite system holds significant promise for the development of biocompatible and highly visible medical implants, potentially enhancing patient outcomes and reducing medical complications. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/564364v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@58cb6aorg.highwire.dtl.DTLVardef@192d2b1org.highwire.dtl.DTLVardef@4699a3org.highwire.dtl.DTLVardef@110d7f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Brazilin is a Natural Product Inhibitor of the NLRP3 Inflammasome

Excessive or aberrant NLRP3 inflammasome activation has been implicated in the progression and initiation of many inflammatory conditions; however, currently no NLRP3 inflammasome inhibitors have been approved for therapeutic use in the clinic. Here we have identified that the natural product brazilin effectively inhibits both priming and activation of the NLRP3 inflammasome in cultured murine macrophages, a human iPSC microglial cell line and in a mouse model of acute peritoneal inflammation. Through computational modelling, we predict that brazilin can adopt a favourable binding pose within a site of the NLRP3 protein which is essential for its conformational activation. Our results not only encourage further evaluation of brazilin as a therapeutic agent for NLRP3-related inflammatory diseases, but also introduce this small-molecule as a promising scaffold structure for the development of derivative NLRP3 inhibitor compounds.

molecular biology↗

bioRxiv2023

Knockout of Sporadic Creutzfeldt-Jakob Disease Risk Gene Stx6 in Mice Extends Prion Disease Incubation Time

Sporadic Creutzfeldt-Jakob disease (sCJD), the most common human prion disease, is thought to occur when the cellular prion protein (PrPC) spontaneously misfolds and assembles into prion fibrils, culminating in fatal neurodegeneration. In a genome-wide association study of sCJD, we recently identified risk variants in and around the gene STX6, with evidence to suggest a causal increase of STX6 expression in disease-relevant brain regions. STX6 encodes syntaxin-6, a SNARE protein primarily involved in early endosome to trans-Golgi network retrograde transport. Here we developed and characterised a mouse model with genetic depletion of Stx6 and investigated a causal role of Stx6 expression in mouse prion disease through a classical prion transmission study, assessing the impact of homozygous and heterozygous syntaxin-6 knockout on disease incubation periods and prion-related neuropathology. Following inoculation with RML prions, incubation periods in Stx6-/- and Stx6+/- mice differed by 12 days relative to wildtype. Similarly, in Stx6-/- mice, disease incubation periods following inoculation with ME7 prions also differed by 12 days. Histopathological analysis revealed a modest increase in astrogliosis in ME7-inoculated Stx6-/- animals and a variable effect of Stx6 expression on microglia activation, however no differences in neuronal loss, spongiform change or PrP deposition were observed at endpoint. Importantly, Stx6-/- mice are viable and fertile with no gross impairments on a range of neurological, biochemical, histological and skeletal structure tests. Our results provide some support for a pathological role of Stx6 expression in prion disease, which warrants further investigation in the context of prion disease but also other neurodegenerative diseases considering syntaxin-6 appears to have pleiotropic risk effects in progressive supranuclear palsy and Alzheimers disease. Author SummarySporadic Creutzfeldt-Jakob disease (sCJD), the most common human prion disease, is an invariably fatal disease with no established disease-modifying treatments. The identification of STX6 as a proposed risk gene for sCJD motivated the generation of a new mouse knockout model, in which we found no grossly deleterious phenotypes. A transmission study in Stx6-/-, Stx6+/- and Stx6+/+ mice challenged with two prion strains showed reduced syntaxin-6 expression is associated with a modest prolongation of prion disease incubation periods, supporting a pathological role of Stx6 expression in prion disease pathogenesis. Syntaxin-6 appears to have pleiotropic risk effects across multiple neurodegenerative diseases including progressive supranuclear palsy and Alzheimers disease. Thus, this work supports further exploration of the STX6 susceptibility mechanism, which likely has relevance across multiple neurodegenerative diseases.

neuroscience↗

bioRxiv2022

Gaze onsets during naturalistic infant-caregiver interaction associate with 'sender' but not 'receiver' neural responses, and do not lead to changes in inter-brain synchrony.

Temporal coordination during infant-caregiver social interaction is thought to be crucial for supporting early language acquisition and cognitive development. Despite a growing prevalence of theories suggesting that increased inter-brain synchrony associates with many key aspects of social interactions such as mutual gaze, little is known about how this arises during development. Here, we investigated the role of mutual gaze onsets as a potential driver of inter-brain synchrony. We extracted dual EEG activity around naturally occurring gaze onsets during infant-caregiver social interactions in N=55 dyads (mean age 12 months). We differentiated between two types of gaze onset, depending on each partners role. Sender gaze onsets were defined at a time when either the adult or the infant made a gaze shift towards their partner at a time when their partner was either already looking at them (mutual) or not looking at them (non-mutual). Receiver gaze onsets were defined at a time when their partner made a gaze shift towards them at a time when either the adult or the infant was already looking at their partner (mutual) or not (non-mutual). Contrary to our hypothesis we found that, during a naturalistic interaction, both mutual and non-mutual gaze onsets were associated with changes in the sender, but not the receivers brain activity and were not associated with increases in inter-brain synchrony above baseline. Further, we found that mutual, compared to non-mutual gaze onsets were not associated with increased inter brain synchrony. Overall, our results suggest that the effects of mutual gaze are strongest at the intra-brain level, in the sender but not the receiver of the mutual gaze.

neuroscience↗

bioRxiv2022

Transcriptional reprogramming from innate immune functions to a pro-thrombotic signature upon SARS-CoV-2 sensing by monocytes in COVID-19

Alterations in the myeloid immune compartment have been observed in COVID-19, but the specific mechanisms underlying these impairments are not completely understood. Here we examined the functionality of classical CD14+ monocytes as a main myeloid cell component in well-defined cohorts of patients with mild and moderate COVID-19 during the acute phase of infection and compared them to that of healthy individuals. We found that ex vivo isolated CD14+ monocytes from mild and moderate COVID-19 patients display specific patterns of costimulatory and inhibitory receptors that clearly distinguish them from healthy monocytes, as well as altered expression of histone marks and a dysfunctional metabolic profile. Decreased NF{kappa}B activation in COVID-19 monocytes ex vivo is accompanied by an intact type I IFN antiviral response. Subsequent pathogen sensing ex vivo led to a state of functional unresponsiveness characterized by a defect in pro-inflammatory cytokine expression, NF{kappa}B-driven cytokine responses and defective type I IFN response in moderate COVID-19 monocytes. Transcriptionally, COVID-19 monocytes switched their gene expression signature from canonical innate immune functions to a pro-thrombotic phenotype characterized by increased expression of pathways involved in hemostasis and immunothrombosis. In response to SARS-CoV-2 or other viral or bacterial components, monocytes displayed defects in the epigenetic remodelling and metabolic reprogramming that usually occurs upon pathogen sensing in innate immune cells. These results provide a potential mechanism by which innate immune dysfunction in COVID-19 may contribute to disease pathology.

immunology↗

bioRxiv2022

Reduced synaptic activity and dysregulated extracellular matrix pathways are common phenotypes in midbrain neurons derived from sporadic and mutation-associated Parkinson's disease patients

Several mutations that cause Parkinsons disease (PD) have been identified over the past decade. These account for 15-25% of PD cases; the rest of the cases are considered sporadic. Currently, it is accepted that PD is not a single monolithic disease but rather a constellation of diseases with some common phenotypes. While rodent models exist for some of the PD-causing mutations, research on the sporadic forms of PD is lagging due to a lack of cellular models. In our study, we differentiated PD patient-derived dopaminergic (DA) neurons from induced pluripotent stem cells (iPSCs) of several PD-causing mutations as well as from sporadic PD patients. Strikingly, we observed a common neurophysiological phenotype: Neurons derived from PD patients had a severe reduction in the rate of synaptic currents compared to those derived from healthy controls. While the relationship between mutations in genes such as the SNCA and LRRK2 and a reduction in synaptic transmission has been investigated before, here we show evidence that the pathogenesis of the synapses in neurons is a general phenotype in PD. Analysis of RNA sequencing results displayed changes in gene expression in different synaptic mechanisms as well as other affected pathways such as extracellular matrix-related pathways. Some of these dysregulated pathways are common to all PD patients (monogenic or idiopathic). Our data, therefore, shows changes that are central and convergent to PD and suggests a strong involvement of the tetra-partite synapse in PD pathophysiology.

neuroscience↗

bioRxiv2021

Climate and mountains shaped human ancestral genetic lineages

Extensive sequencing of modern and ancient human genomes has revealed that contemporary populations can be explained as the result of recent mixing of a few distinct ancestral genetic lineages1. But the small number of aDNA samples that predate the Last Glacial Maximum means that the origins of these lineages are not well understood. Here, we circumvent the limited sampling by modelling explicitly the effect of climatic changes and terrain on population demography and migrations through time and space, and show that these factors are sufficient to explain the divergence among ancestral lineages. Our reconstructions show that the sharp separation between African and Eurasian lineages is a consequence of only a few limited periods of connectivity through the arid Arabian peninsula, which acted as the gate out of the Arican continent. The subsequent spread across Eurasia was then mostly shaped by mountain ranges, and to a lesser extent deserts, leading to the split of European and Asians, and the further diversification of these two groups. A high tolerance to cold climates allowed the persistence at high latitudes even during the Last Glacial Maximum, maintaining a pocket in Beringia that led to the later, rapid colonisation of the Americas. The advent of food production was associated with an increase in movement2, but mountains and climate have been shown to still play a major role even in this latter period3,4, affecting the mixing of the ancestral lineages that we have shown to be shaped by those two factors in the first place.

genomics↗

bioRxiv2021

Genetic Susceptibility to Enteric Fever in Experimentally Challenged Human Volunteers

BackgroundInfection with Salmonella enterica serovars Typhi and Paratyphi A cause an estimated 14 million cases of enteric fever annually. Here the controlled nature of challenge studies is exploited to identify genetic variants associated with enteric fever susceptibility. MethodsHuman challenge participants were genotyped by Illumina OmniExpress-24 BeadChip array (n=176) and/or transcriptionally profiled by RNA-sequencing (n=178). ResultsTwo SNPs within CAPN14 and MIATNB were identified with p<10-5 for association with development of symptoms or bacteraemia following oral S. Typhi or S. Paratyphi A challenge. Imputation of classical human leukocyte antigen (HLA) types from genomic and transcriptomic data identified HLA-B*27:05, previously associated with non-typhoidal Salmonella-induced reactive arthritis, as the HLA type most strongly associated with enteric fever susceptibility (p=0.012). Genes related to the unfolded protein response and heat shock were over-represented in HLA-B*27:05+ participants following challenge (p=0.01). Furthermore, intracellular replication of S. Typhi is higher in C1R cells transfected with HLA-B*27:05 (p=0.02). ConclusionThese data suggest that activation of the unfolded protein response by HLA-B*27:05 misfolding may create an intracellular environment conducive to S. Typhi replication, increasing susceptibility to enteric fever.

genetics↗

bioRxiv2021

Phenotyping heart failure using model-based analysis and physiology-informed machine learning

To determine the underlying mechanistic differences between diagnoses of Heart Failure (HF) and specifically heart failure with reduced and preserved ejection fraction (HFrEF & HFpEF), a closed loop model of the cardiovascular system coupled with patient specific transthoracic echocardiography (TTE) and right heart catheterization (RHC) measures was used to identify key parameters representing cardiovascular hemodynamics. Thirty-one patient records (10 HFrEF, 21 HFpEF) were obtained from the Cardiovascular Health Improvement Project (CHIP) database at the University of Michigan. Model simulations were tuned to match RHC and TTE pressure, volume and cardiac output measures in each patient with average error between data and model of 4.87 {+/-} 2%. The underlying physiological model parameters were then plotted against model-based norms and compared between the HFrEF and HFpEF group. Our results confirm that the main mechanistic parameter driving HFrEF is reduced left ventricular contractility, while for HFpEF a much wider underlying phenotype is presented. Conducting principal component analysis (PCA), k-means, and hierarchical clustering on the optimized model parameters, but not on clinical measures, shows a distinct group of HFpEF patients sharing characteristics with the HFrEF cohort, a second group that is distinct as HFpEF and a group that exhibits characteristics of both. Significant differences are observed (p-value<.001) in left ventricular active contractility and left ventricular relaxation, when comparing HFpEF patients to those grouped as similar to HFrEF. These results suggest that cardiovascular system modeling of standard clinical data is able to phenotype and group HFpEF as different subdiagnoses, possibly elucidating patient-specific treatment strategies.

physiology↗

bioRxiv2021

Automatic classification of ICA components from infant EEG using MARA

Automated systems for identifying and removing non-neural ICA components are growing in popularity among adult EEG researchers. Infant EEG data differs in many ways from adult EEG data, but there exists almost no specific system for automated classification of source components from paediatric populations. Here, we adapt one of the most popular systems for adult ICA component classification for use with infant EEG data. Our adapted classifier significantly outperformed the original adult classifier on samples of naturalistic free play EEG data recorded from 10 to 12-month-old infants, achieving agreement rates with the manual classification of over 75% across two validation studies (n=44, n=25). Additionally, we examined both classifiers ability to remove stereotyped ocular artifact from a basic visual processing ERP dataset, compared to manual ICA data cleaning. Here the new classifier performed on level with expert manual cleaning and was again significantly better than the adult classifier at removing artifact whilst retaining a greater amount of genuine neural signal, operationalised through comparing ERP activations in time and space. Our new system (iMARA) offers developmental EEG researchers a flexible tool for automatic identification and removal of artifactual ICA components.

neuroscience↗

bioRxiv2020

Neuroimaging: Into the Multiverse

AO_SCPLOWBSTRACTC_SCPLOWFor most neuroimaging questions the huge range of possible analytic choices leads to the possibility that conclusions from any single analytic approach may be misleading. Examples of possible choices include the motion regression approach used and smoothing and threshold factors applied during the processing pipeline. Although it is possible to perform a multiverse analysis that evaluates all possible analytic choices, this can be computationally challenging and repeated sequential analyses on the same data can compromise inferential and predictive power. Here, we establish how active learning on a low-dimensional space that captures the inter-relationships between analysis approaches can be used to efficiently approximate the whole multiverse of analyses. This approach balances the benefits of a multiverse analysis without the accompanying cost to statistical power, computational power and the integrity of inferences. We illustrate this approach with a functional MRI dataset of functional connectivity across adolescence, demonstrating how a multiverse of graph theoretic and simple pre-processing steps can be efficiently navigated using active learning. Our study shows how this approach can identify the subset of analysis techniques (i.e., pipelines) which are best able to predict participants ages, as well as allowing the performance of different approaches to be quantified.

neuroscience↗

bioRxiv2020

AN ADMIXTURE SIGNAL IN ARMENIANS AROUND THE END OF THE BRONZE AGE REVEALS WIDESPREAD POPULATION MOVEMENT ACROSS THE MIDDLE EAST

The Armenians, a population inhabiting the region in West Asia known as the Armenian Highland, has been argued to show a remarkable degree of population continuity since the Early Neolithic. Here we test the degree of continuity of this population as well as its plausible origin, by collating modern and ancient genomic data, and adding a number of novel contemporary genomes. We show that Armenians have indeed remained unadmixed through the Neolithic and at least until the first part of the Bronze Age, and fail to find any support for historical suggestions by Herodotus of an input from the Balkans. However, we do detect a genetic input of Sardinian-like ancestry during or just after the Middle-Late Bronze Age. A similar input at approximately the same time was detected in East Africa, suggesting large-scale movement both North and South of the Middle East. Whether such large-scale population movement was a result of climatic or cultural changes is unclear, as well as the true source of gene flow remains an open question that needs to be addressed in future ancient DNA studies.

genomics↗

bioRxiv2020

Lipid membrane templated misfolding and self-assembly of intrinsically disordered tau protein

The aggregation of the intrinsically disordered tau protein into highly ordered {beta}-sheet fibrils is implicated in many neurodegenerative disorders. Fibrillation mechanism remains unresolved, particularly early events that trigger tau misfolding and assembly. We investigated the role membrane plays in modulating aggregation of three tau variants, the largest isoform hTau40, the truncated construct K18, and a hyperphosphorylation mutant hTau40/3Epi. Despite being charged and soluble, tau proteins were also highly surface active and favorably interacted with anionic, but not zwitterionic, lipid monolayer at the air/water interface. Membrane binding induced macroscopic tau phase separation and {beta}-sheet-rich tau oligomer formation. Concomitantly, membrane morphology and lipid packing became disrupted. Our findings support a general tau aggregation mechanism wherein taus inherent surface activity and favorable electrostatic interactions drive tau-membrane association, inducing tau phase separation that is accompanied by misfolding and self-assembly of disordered tau into {beta}-sheet-rich oligomers, which subsequently seed fibrillation and deposition into diseased tissues.

biophysics↗

bioRxiv2019

Restoration, dispersal and settlement of native European oyster (Ostrea edulis) in energetic tidal areas

We modelled the pelagic larval phase of native European oyster (Ostrea edulis) in the Solent. The Solent is a complex and tidally energetic environment on the south coast of the UK. Until recently it was the largest self-sustaining fishery of the native oyster in Europe. We developed a new larval settlement behavioural model that is the simplest plausible model which remains consistent with all available data and evidence on larval behaviour. We used a hydrodynamic sub-model, a Lagrangian advection sub-model, and an individual agent based model. The results demonstrate how isolated oyster assemblages can re-populate larger areas of historical inhabitance. We predict the most likely patterns of redistribution from refugia or from fisheries seeding. We show that settlement swimming behaviour is as equally important as passive hydrodynamic transport for larval survival and adult distribution and that settlement swimming behaviour has a profound impact on settlement patterns. The models show that managed broodstock refugia have the potential to seed much larger oyster beds in contrast to broad-scale seeding. Such refugia have the advantage of maintaining a locally high and mature population with potential for reef features and their associated biodiversity. We show that such refugia may be best placed in the tidally dynamic and exposed areas rather than on sheltered coastal sites as they have been in the past. Our model is insensitive to parameter variation and could be an effective and practical management tool in the face of a paucity of field data on larval distribution and behaviour.

zoology↗

bioRxiv2019

Functional and in-silico interrogation of rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

PurposeTo develop a comprehensive analysis framework to identify pre-messenger RNA splicing mutations in the context of rare disease.\n\nMethodsWe assessed variants of uncertain significance through six in-silico prioritization strategies. Firstly, through comparison to functional analyses, we determined the precise effect on splicing of variants identified through clinical multi-disciplinary meetings. Next, we calculated the sensitivity of in-silico prioritization strategies to distinguish known splicing mutations from common variation (>2% in allele frequency in gnomAD) within relevant disease genes. These approaches defined an accurate in-silico strategy for variant prioritization, which we retrospectively applied to a large cohort of 2783 individuals who had previously received genomic testing for rare genomic disorders. We assessed the clinical impact of such prioritization strategies alongside routine diagnostic testing strategies.\n\nResultsWe identified 21 variants that potentially impacted splicing, and used cell based splicing assays to identify those variants which disrupted normal splicing. These findings underpinned new molecular diagnoses for 14 individuals. This process established that the use of pre-defined thresholds from a machine learning splice prediction algorithm, SpliceAI, was the most efficient method for variant prioritization, with a positive predictive value of 86%. We analysed 1,346,744 variants identified through diagnostic testing for 2783 individuals and observed that splicing variant prioritization strategies would improve clarity in clinical analysis for 15% of the individuals surveyed. Prioritized variants could provide new molecular diagnoses or provide additional support for molecular diagnosis for up to 81 individuals within our cohort.\n\nConclusionWe present an in-silico and functional analysis framework for the assessment of variants impacting pre-messenger RNA splicing which is applicable across monogenic disorders. Incorporation of these strategies improves clarity in diagnostic reporting, increases diagnostic yield and, with the advent of targeted treatment strategies, can directly alter patient clinical management.\n\nKey HighlightsO_LIWe establish an in-silico and functional analysis framework for the incorporation of splice variant assessment into diagnostic testing that is applicable across monogenic disorders.\nC_LIO_LIAfter assessment of six distinct variant prioritization strategies, we concluded that SpliceAI was the best method to accurately identify genomic variation disrupting normal pre-mRNA splicing. We determined this through (i) functional assessment of novel variants of uncertain significance described in this study, and (ii) calculation of sensitivity and specificity for prioritization strategies to distinguish known splicing mutations from common variants in the general population.\nC_LIO_LIWe describe novel disease-causing variants with support from cell based functional assays which underpin autosomal recessive, autosomal dominant and X-linked Mendelian disorders. This includes variants which are deeply intronic, within the nearby splice region of canonical splice sites and variants which activate cryptic splice sites within the protein-coding regions of genes.\nC_LIO_LIWe integrated the best performing variant prioritization strategy alongside clinical diagnostic testing for 2783 individuals referred to a well-established targeted gene panel test available through the UK National Health Service. We show that integration of such strategies will increase accuracy and clarity of diagnostic reporting, including the identification of variants which could provide new diagnoses and new carrier findings for referred individuals.\nC_LIO_LIFunctional assessment is essential for accurate clinical assessment of variants disrupting pre-mRNA splicing. We show through cell based functional assessments that variants impacting splicing may have complex impacts on pre-mRNA splicing, which may cause multiple interpretable consequences according to ACMG guidelines.\nC_LI

genomics↗

bioRxiv2019

Benchmarking Database Systems for Genomic Selection Implementation

MotivationWith high-throughput genotyping systems now available, it has become feasible to fully integration genotyping information into breeding programs [22]. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize them in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs one would need an efficient genotype data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems.\n\nResultsWe found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix.\n\nAvailabilityhttp://gobiinx1.bti.cornell.edu:6083/projects/GBM/repos/benchmarking/browse\n\nContactyn259@cornell.edu

genomics↗

bioRxiv2018

Integrative analysis of Paneth cell proteomic data from intestinal organoids reveals functional processes affected in Crohn’s disease due to autophagy impairment

Summary statementUsing an integrative approach encompassing intestinal organoid culture, proteomics, transcriptomics and protein-protein interaction networks, we list Paneth cell functions dependent on autophagy.\n\nAbstractPaneth cells are key epithelial cells providing an antimicrobial barrier and maintaining integrity of the small intestinal stem cell niche. Paneth cell abnormalities are unfortunately detrimental to gut health and often associated with digestive pathologies such as Crohns disease or infections. Similar alterations are observed in individuals with impaired autophagy, a process which recycles cellular components. The direct effect of autophagy-impairment on Paneth cells has not been analysed. To investigate this, we generated a mouse model lacking Atg16l1 specifically in intestinal epithelial cells making these cells impaired in autophagy. Using 3D intestinal organoids enriched for Paneth cells, we compared the proteomic profiles of wild-type (WT) and autophagy-impaired organoids. We used an integrated computational approach combining protein-protein interaction networks, autophagy targeted proteins and functional information to identify the mechanistic link between autophagy-impairment and disrupted pathways. Of the 284 altered proteins, 198 (70%) were more abundant in autophagy-impaired organoids, suggesting reduced protein degradation. Interestingly, these differentially abundant proteins comprised 116 proteins (41%), predicted targets of the selective autophagy proteins p62, LC3 and ATG16L1. Our integrative analysis revealed autophagy-mediated mechanisms degrading proteins key to Paneth cell functions, such as exocytosis, apoptosis and DNA damage repair. Transcriptomic profiling of additional organoids confirmed that 90% of the observed changes upon autophagy alteration affect protein level and not gene expression. We performed further validation experiments showing differential lysozyme secretion, confirming our computationally inferred down-regulation of exocytosis. Our observations could explain how protein level alterations affect Paneth cell homeostatic functions upon autophagy impairment.

systems biology↗