Biology subjects

Jones, S.

Publications and source records attributed to Jones, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Mutation of the allexivirus-specific P40 gene of Wineberry latent virus, an isolate of Blackberry virus E, greatly reduces virus multiplication

The complete sequence of Wineberry latent virus (WLV), a previously reported but uncharacterised Rubus-infecting virus with flexuous particles, has been determined. Analysis shows WLV to have 76% overall nucleotide sequence identity to the more recently discovered Blackberry virus E, an allexivirus belonging to the subgroup of these viruses that lack the 3 proximal cysteine-rich protein (CRP) gene present in Allium-infecting allexiviruses. An infectious cDNA clone of WLV was constructed and a mutation introduced into the P40 gene, which is an allexivirus-specific gene of unknown function. In addition, the infectious clone was modified to express the green fluorescent protein (GFP) as an N-terminal fusion to the WLV coat protein (CP). Using this GFP overcoat strategy it was possible to follow the multiplication and movement of the virus in infected Chenopodium quinoa and spinach leaves. Introduction of the frameshift mutation into the P40 gene of WLV reduced virus accumulation by 97%, and with the GFP overcoated WLV the P40 mutation almost entirely abolished GFP fluorescence in inoculated leaves suggesting that the WLV P40 protein is required for normal levels of virus multiplication. RepositoriesWLV complete sequences deposited at GenBank. Accession Nos. MZ944847.1, OQ877124.1

plant biology↗

bioRxiv2024

KIR3DL1 and Tox identify clonally expanded encephalitogenic neuron-specific CD8+ T cells in autoimmune encephalitis

Autoreactive CD8+ T cells are the principal suspects in autoimmune encephalitis (AIE) with antibodies targeting intracellular neuronal antigens So far, the search for neuron-autoreactive CD8+ T cells has been focused on a few autoantigens and did not yield convincing results. Here, we leveraged natural antigen presentation by hiPSC-derived neurons to look at the global autoreactive CD8+ T cell response, independently of pre-conceived hypothesis of the autoantigens involved in the disease. This unbiased approach allowed for the identification of rare polyclonal neuron-reactive CD8+ T cells in healthy donors, and contrastingly, expanded clonotypes in two patients with anti-Ri AIE. Detailed ex vivo phenotypic characterization of these clonotypes revealed a specific transcriptional program suggestive of a pathogenic potential. In particular, this subset can be identified by the expression of KIR3DL1 and TOX. Strikingly, we could also demonstrate that CD8+ T cells found in the brain of an anti-Ri AIE patient display a similar phenotype associated with cytotoxicity and encephalitogenic features.

immunology↗

bioRxiv2024

Human stem cell derived neurons and astrocytes to detect auto-reactive IgG in neurological diseases

Background and objectivesUp to 46% of patients with presumed autoimmune limbic encephalitis are seronegative for all currently known CNS antigens. We developed a cell-based assay (CBA) to screen for novel neural antibodies in serum and CSF using neurons and astrocytes derived from human induced pluripotent stem cells (hiPSC). MethodsHuman iPSC-derived astrocytes or neurons were incubated with serum/CSF from 99 patients (42 with inflammatory neurological diseases (IND) and 57 with non-IND (NIND)). The IND group included 11 patients with previously established neural antibodies, six with seronegative neuromyelitis optica spectrum disorder (NMOSD), 12 with suspected autoimmune encephalitis/paraneoplastic syndrome (AIE/PNS), and 13 with other IND (OIND). IgG binding to fixed CNS cells was detected using fluorescently-labelled antibodies and analyzed through automated fluorescence measures. IgG neuronal/astrocyte reactivity was further analyzed by flow cytometry. Peripheral blood mononuclear cells (PBMC) were used as CNS-irrelevant control target cells. Reactivity profile was defined as positive using a Robust regression and Outlier removal test with a false discovery rate at 10% following each individual readout. ResultsUsing our CBA, we detected antibodies recognizing hiPSC-derived neural cells in 19/99 subjects. Antibodies bound specifically to astrocytes in nine cases, to neurons in eight cases and to both cell types in two cases, as confirmed by microscopy single-cell analyses. Highlighting the significance of our novel 96-well CBA assay, neural-specific antibody binding was more frequent in IND (15/42) than in NIND patients (4/57) (Fisher test, p=0.0005). Three of three patients with astrocyte- reactive (2 AQP4+ NMO, 1 GFAP astrocytopathy), and 3/4 with intracellular neuron-reactive antibodies (2 Hu+, 1 Ri+ AIE/PNS), as identified in diagnostic laboratories, were also positive with our CBA. Most interestingly, we showed antibody-reactivity in 2/6 seronegative NMOSD, 6/12 probable AIE/PNS, and 1/13 OIND. Flow cytometry using hiPSC-derived CNS cells or PBMC detected antibody binding in 13 versus 0 patients, respectively, establishing the specificity of the detected antibodies for neural tissue. DiscussionOur unique hiPSC-based CBA allows for the screening of novel neuron-/astrocyte-reactive antibodies in patients with suspected immune-mediated neurological syndromes, and negative testing in established routine laboratories, opening new perspectives in establishing early diagnosis of such complex diseases.

neuroscience↗

bioRxiv2024

Gene Therapy Mediates Therapeutic Improvement in Cardiac Hypertrophy and Survival in a Murine Model of MYBPC3-Associated Cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) affects an estimated 600,000 people in the U.S. and is the leading cause of sudden cardiac arrest in those under 18. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM. The majority of MYBPC3 mutations causative for HCM result in truncations. The sarcomeric pathophysiology of the majority of HCM patients with MYBPC3 mutations appears to be due to haploinsufficiency, as the total amount of MYBPC3 protein incorporated into sarcomeres falls significantly below normal. MethodsA clear path for the treatment of haploinsufficiency is the restoration of the insufficient gene product; in this case wild-type MYBPC3. To achieve this, we engineered an AAV vector (TN-201) with superior properties for mediating cardiomyocyte-selective expression of MYBPC3 after systemic delivery. ResultsWe have demonstrated for the first time with AAV gene therapy the ability of both a mouse surrogate and TN-201, which encodes human MYBPC3 to reverse cardiac hypertrophy and systolic dysfunction and to improve diastolic dysfunction and survival in a symptomatic MYBPC3-deficient murine model of disease. Dose-ranging efficacy studies exhibited restoration of wild-type MYBPC3 protein levels and saturation of cardiac improvement at the clinically relevant dose of 3E13 vg/kg, outperforming a previously published construct. Further, we have established stable cardiac benefit for greater than one year post-injection, as well as reversal of cardiac dysfunction even in late-stage models of disease. ConclusionsOur data suggest that by restoring MYBPC3 to the sarcomere, TN-201 has the potential to slow and even reverse the course of the disease in patients with MYBPC3-associated HCM.

genetics↗

bioRxiv2024

Suspension Electrospinning of Decellularized Extracellular Matrix

Decellularized extracellular matrices (dECM) have strong regenerative potential as tissue engineering scaffolds; however, current clinical options for dECM are limited to freeze-drying its native form into sheets. Electrospinning is a versatile scaffold fabrication technique that allows control of macro- and microarchitecture. It remains challenging to electrospin dECM; which has led researchers to either blend it with synthetic materials or use enzymatic digestion to fully solubilize the dECM. Both strategies reduce the innate bioactivity of dECM and limit its regenerative potential. Herein, we developed a new suspension electrospinning method to fabricate a pure dECM scaffold that retains its innate bioactivity. Systematic investigation of suspension parameters was used to identify critical rheological properties required to instill "spinnability," including homogenization, concentration, and particle size. Homogenization enhanced particle interaction to impart the requisite elastic behavior to withstand electrostatic drawing without breaking. A direct correlation between concentration and viscosity was observed that altered fiber morphology; whereas, particle size had minimal impact on suspension properties and fiber morphology. The versatility of this new method was demonstrated by electrospinning dECM with three common decellularization techniques (Abraham, Badylak, Luo) and tissue origins (intestinal submucosa, heart, skin). Bioactivity retention after electrospinning was confirmed using cell proliferation, angiogenesis, and macrophage assays. Collectively, these findings provide a framework for researchers to electrospin dECM for diverse tissue engineering applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/577473v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@f6ff3org.highwire.dtl.DTLVardef@17efb2dorg.highwire.dtl.DTLVardef@19c5b9dorg.highwire.dtl.DTLVardef@42a13e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Biophysical modeling of frontocentral ERP generation links circuit-level mechanisms of action-stopping to a behavioral race model

Human frontocentral event-related potentials (FC-ERPs) are ubiquitous neural correlates of cognition and control, but their generating multiscale mechanisms remain mostly unknown. We used the Human Neocortical Neurosolver(HNN)s biophysical model of a canonical neocortical circuit under exogenous thalamic and cortical drive to simulate the cell and circuit mechanisms underpinning the P2, N2, and P3 features of the FC-ERP observed after Stop-Signals in the Stop-Signal task (SST). We demonstrate that a sequence of simulated external thalamocortical and cortico-cortical drives can produce the FC-ERP, similar to what has been shown for primary sensory cortices. We used this model of the FC-ERP to examine likely circuit-mechanisms underlying FC-ERP features that distinguish between successful and failed action-stopping. We also tested their adherence to the predictions of the horse-race model of the SST, with specific hypotheses motivated by theoretical links between the P3 and Stop process. These simulations revealed that a difference in P3 onset between successful and failed Stops is most likely due to a later arrival of thalamocortical drive in failed Stops, rather than, for example, a difference in effective strength of the input. In contrast, the same model predicted that early thalamocortical drives underpinning the P2 and N2 differed in both strength and timing across stopping accuracy conditions. Overall, this model generates novel testable predictions of the thalamocortical dynamics underlying FC-ERP generation during action-stopping. Moreover, it provides a detailed cellular and circuit-level interpretation that supports links between these macroscale signatures and predictions of the behavioral race model. Significance statementThe frontocentral event-related potential (FC-ERP) is an easily-measurable neural correlate of cognition and control. However, the cortical dynamics that produce this signature in humans are complex, limiting the ability of researchers to make predictions about its underlying mechanisms. In this study, we used the biophysical model included in the open-source Human Neocortical Neurosolver software to simulate and evaluate the likely cellular and circuit mechanisms that underlie the FC-ERP in the Stop-Signal task. We modeled mechanisms of the FC-ERP during successful and unsuccessful stopping, generating testable predictions regarding Stop-associated computations in human frontal cortex. Moreover, the resulting model parameters provide a starting point for simulating mechanisms of the FC-ERP and other frontal scalp EEG signatures in other task conditions and contexts.

neuroscience↗

bioRxiv2023

Hydrogel-Polyurethane Fiber Composites With Enhanced Microarchitectural Control For Heart Valve Replacement

Polymeric heart valves offer the potential to overcome the limited durability of tissue based bioprosthetic valves and the need for anticoagulant therapy of mechanical valve replacement options. However, developing a single-phase material with requisite biological properties and target mechanical properties remains a challenge. In this study, a composite heart valve material was developed where an electrospun mesh provides tunable mechanical properties and a hydrogel coating confers an antifouling surface for thromboresistance. Key biological responses were evaluated in comparison to glutaraldehyde-fixed pericardium. Platelet and bacterial attachment were reduced by 38% and 98%, respectively, as compared to pericardium that demonstrated the antifouling nature of the hydrogel coating. There was also a notable reduction (59%) in the calcification of the composite material as compared to pericardium. A custom 3D printed hydrogel coating setup was developed to make valve composites for device-level hemodynamic testing. Regurgitation fraction (9.6 {+/-} 1.8%) and effective orifice area (1.52 {+/-} 0.34 cm2) met ISO 5840-2:2021 requirements. Additionally, the mean pressure gradient was comparable to current clinical bioprosthetic heart valves demonstrating preliminary efficacy. Although the hemodynamic properties are promising, it is anticipated that the random microarchitecture will result in suboptimal strain fields and peak stresses that may accelerate leaflet fatigue and degeneration. Previous computational work has demonstrated that bioinspired fiber microarchitectures can improve strain homogeneity of valve materials toward improving durability. To this end, we developed advanced electrospinning methodologies to achieve polyurethane fiber microarchitectures that mimic or exceed the physiological ranges of alignment, tortuosity, and curvilinearity present in the native valve. Control of fiber alignment from a random fiber orientation at a normalized orientation index (NOI) 14.2 {+/-} 6.9% to highly aligned fibers at a NOI of 85.1 {+/-} 1.4%. was achieved through increasing mandrel rotational velocity. Fiber tortuosity and curvilinearity in the range of native valve features were introduced through a post-spinning annealing process and fiber collection on a conical mandrel geometry, respectively. Overall, these studies demonstrate the potential of hydrogel-polyurethane fiber composite as a heart valve material. Future studies will utilize the developed advanced electrospinning methodologies in combination with model-directed fabrication toward optimizing durability as a function of fiber microarchitecture.

bioengineering↗

bioRxiv2023

UNNT: A novel Utility for comparing Neural Net and Tree-based models

Using deep learning in cancer research to tackle scientific challenges is becoming an increasingly popular technique. Advances in enhanced data generation, machine learning algorithms, and compute infrastructure have led to an acceleration in the use of deep learning in various domains of cancer research such as drug response problems. In our study, we explored tree-based models to improve the accuracy of a single drug response model and demonstrate that tree-based models such as XGBoost have advantages over deep learning models, such as a convolutional neural network (CNN), for single drug response problems. However, comparing models is not a trivial task. To make training and comparing CNNs and XGBoost (eXtreme Gradient Boosting) more accessible to users, we developed an open-source library called UNNT (A novel Utility for comparing Neural Net and Tree-based models). The case studies, in this manuscript, focus on cancer drug response datasets however the application can be used on datasets from other domains, such as chemistry. Author summaryAdvancement in data science, machine learning (ML), and artificial intelligence (AI) methods has enabled extraction of meaningful information from large and complex datasets that has assisted in better understanding, diagnosing, and treating cancer. The understanding of the drug response domain in cancer research has been accelerated with developing ML models to aid in predicting the effectiveness of the drugs based on a specific genomic molecular feature. In this study we developed a novel robust framework called UNNT (A novel Utility for comparing Neural Net and Tree-based models) that trains and compares deep learning method such as CNN and tree-based method such as XGBoost on the user input dataset. We applied this software to single drug response problem in cancer to identify the best performing ML method based on the National Cancer Institute 60 (NCI60) dataset. In addition, we studied the computational aspects of training each of these models where our results show that neither is evidently superior on both CPUs and GPUs while training. This shows that when both models have similar error rates for a dataset the hardware available determines the model choice for training as discussed in tables 7 and 11. UNNT: https://github.com/vgutta/UNNT.git O_TBL View this table: org.highwire.dtl.DTLVardef@410860org.highwire.dtl.DTLVardef@18ce417org.highwire.dtl.DTLVardef@d2b43corg.highwire.dtl.DTLVardef@1370c16org.highwire.dtl.DTLVardef@fa7a00_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 7.C_FLOATNO O_TABLECAPTIONFastest training times for CNN and XGBoost on CPU and GPU (all features) C_TABLECAPTION C_TBL O_TBL View this table: org.highwire.dtl.DTLVardef@5f9fbborg.highwire.dtl.DTLVardef@1efecc1org.highwire.dtl.DTLVardef@a0813borg.highwire.dtl.DTLVardef@1845b46org.highwire.dtl.DTLVardef@8463e8_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 11.C_FLOATNO O_TABLECAPTIONFastest training times for CNN and XGBoost on CPU and GPU (FDA model) C_TABLECAPTION C_TBL

bioinformatics↗

bioRxiv2023

IMPALA: A Comprehensive Pipeline for Detecting and Elucidating Mechanisms of Allele Specific Expression in Cancer

SummaryAllele-specific expression (ASE), where transcripts from one allele are more abundant than transcripts from the other, can arise from various genetic mechanisms and has implications for gene regulation and disease. We present IMPALA (Integrated Mapping and Profiling of Allelically-expressed Loci with Annotations), a versioned and containerized pipeline for detecting ASE in samples including cancer genomes. IMPALA leverages RNA sequencing data and, optionally, phased variant, copy number variant (CNV), allelic methylation, and mutation data to identify ASE genes and uncover underlying regulatory mechanisms. IMPALA incorporates the MBASED framework for ASE detection, and outputs a comprehensive summary table and informative figures to visualize the genomic distribution of ASE genes and their correlation with potential regulatory causes. We applied IMPALA to a cancer sample and identified thousands of genes with ASE and highlighted potential somatic events that may have influenced ASE of these genes. ASE data can be used to detect the downstream consequences of genomic alterations, which facilitates the identification of dysregulated cancer-related genes. IMPALA thus provides researchers with a powerful tool for both ASE analysis and for investigating genetic factors correlated with ASE. Availability and implementationIMPALA is licensed under GNU General Public License v3.0 and freely available at https://github.com/bcgsc/IMPALA and https://doi.org/10.5281/zenodo.8019168 with documentation and tutorial. Contactsjones@bcgsc.ca Supplemental informationSupplemental materials are available at Bioinformatics online. Issue section: Gene expression

bioinformatics↗

bioRxiv2023

Characterization of Identified Dopaminergic Neurons in the Mouse Olfactory Bulb and Midbrain

Dopaminergic (DA) neurons play pivotal roles in diverse brain functions, spanning movement, reward processing, and sensory perception. DA neurons are most abundant in the midbrain (Substantia Nigra pars compacta, SNC, and Ventral Tegmental Area, VTA) and the olfactory bulb (OB) in the forebrain. Interestingly, a subtype of OB DA neurons is capable of regenerating throughout life, while a second class is exclusively born during embryonic development. Emerging evidence in SNC and VTA also indicates substantial heterogeneity in terms of morphology, connectivity, and function. To further investigate this heterogeneity and directly compare form and function of midbrain and forebrain DA neurons, we performed immunohistochemistry and whole-cell patch-clamp recordings in ex vivo brain slices from juvenile DAT-tdTomato mice. After confirming the penetrance and specificity of the dopamine transporter (DAT) Cre line, we compared soma shape, passive membrane properties, voltage sags and action potential firing across midbrain and forebrain DA subtypes. We found that each DA subgroup within midbrain and forebrain was highly heterogeneous, and that DA neurons across the two brain areas are also substantially different. These findings complement previous work in rats as well as gene expression and in vivo datasets, further questioning the existence of a single "dopaminergic" neuronal phenotype.

neuroscience↗

bioRxiv2023

How best to co-deploy insecticides to minimise selection for resistance.

Insecticides are widely used to control the insects that spread human infectious diseases, in particular falciparum malaria. This widespread use has driven insecticide resistance (IR) to high levels that may threaten the effectiveness of future control programmes. There is interest in identifying deployment methods that alleviate the pressures driving IR and we investigate three. Mixtures are, as already known, highly effective in slowing IR providing their effectiveness (ability to kill fully sensitive insects) remain close to 100%. Mixtures may be expensive and/or operationally difficult so two alternatives to mixtures were investigated. Panels, where different insecticides are physically closely adjacent, for examples, different panels on the same bednet; mosquitoes may therefore encounter both insecticides in the same foraging cycle. Micro-mosaics where different insecticides are deployed in slightly wider geographic proximity, for example in adjacent dwellings. The mosquitoes are unlikely to encountered both insecticides in the same foraging cycle but may encounter different insecticides in subsequent foraging. It is hoped that panels and/or micro-mosaics may, by allowing individual mosquitoes to potentially encounter both insecticides, be effective, lower-cost alternatives to mixtures. Our results suggest this is unlikely to be the case. When insecticides are fully effective then mixtures remain clearly the best strategy. As effectiveness falls then all three strategies are roughly equal. The operational decision of what deployment methods to use depends on how confident we are that insecticides will have high effectiveness that will be maintained in realistic field conditions post-deployment.

genetics↗

bioRxiv2023

Unique proteomic signature of JCPyV-infected human astrocytes: from cells to extracellular vesicles

JC polyomavirus (JCPyV) is an opportunistic virus that remains in a latent state in the kidneys of more than half of the human adult population. In rare cases of severe immune suppression, the virus is able to establish a lytic infection of glial cells in the brain, resulting in a debilitating, demyelinating disease known as progressive multifocal leukoencephalopathy (PML). Because of the exceptional species and tissue specificity of the virus, appropriate models of JCPyV infection in the brain are lacking, thus hampering progress towards the development of novel antiviral strategies and biomarkers of disease activity. While PML has traditionally been characterized as a lytic infection of oligodendrocytes, more recent findings suggest an important role for astrocytes during the initial stages of disease. Here, using human induced pluripotent stem cell (hiPSC) derived-astrocytes coupled with a multiparametric approach, we show that 1. JCPyV readily infects and replicates in astrocytes, 2. JCPyV strongly dysregulates the cell biology and 3. these findings adequately reflect ex vivo findings. We perform an in-depth characterization of the effect of JCPyV on the cell proteome over time, demonstrating a strong dysregulation of the cell cycle and activation of the DNA damage response. Furthermore, we show that the proteomic signature observed for infected astrocytes is extended to excreted vesicles, underlining their potential to gain valuable insights into JCPyV propagation in the brain.

neuroscience↗

bioRxiv2023

Distinguishing integrated sub-viral fragments from infectious Rubus yellow net virus in Scottish commercial red raspberry cultivars

Short read sequencing of two field-grown plants of red raspberry cv Glen Dee identified sequences derived from Rubus yellow net virus (RYNV). Surprisingly, PCR primers designed to target these sequences amplified RYNV-specific DNA fragments from some high health nuclear stock raspberry plants, previously tested as free from RYNV infection. The complete sequence of a Scottish isolate of RYNV (RYNV LG) was determined and a panel of primers covering the entire virus genome was designed to demonstrate that nuclear stock plants of cultivars Glen Dee, Glen Ericht, Glen Fyne and Glen Moy all contain partial fragments of the RYNV genome as integrated elements but do not contain the entire RYNV genome. The complete, circular genome of RYNV could be detected in RYNV LG-infected plants by rolling circle amplification but was not detected in Glen Dee plants. Grafting experiments showed that infectious RYNV could be transferred from RYNV LG plants but not from Glen Dee or Glen Moy plants, further demonstrating that these cultivars contain only partial, integrated RYNV elements. Grafting of RYNV LG to the certification-approved indexing species R. occidentalis (black raspberry) and R. macraei, showed that RYNV LG induced recognisable symptoms in both plants but that R. macraei was more susceptible and produced more recognizable symptoms. Effective testing for RYNV in high health certified raspberry plants can be achieved by combining graft testing with multifragment PCR.

plant biology↗

bioRxiv2022

Rising SARS-CoV-2 Seroprevalence and Patterns of Cross-Variant Antibody Neutralization in UK Domestic Cats

Recent evidence confirming cat-to-human SARS-CoV-2 transmission has highlighted the importance of monitoring infection in domestic cats. Although the effects of SARS-CoV-2 infection on feline health are poorly characterized, cats have close contact with humans, and with both domesticated and wild animals. Accordingly, they could act as a reservoir of infection, an intermediate host and a source of novel variants. To investigate the spread of the virus in the cat population, serum samples were tested for SARS-CoV-2 antibodies by ELISA and a pseudotype-based virus neutralization assay, designed to detect exposure to variants known to be circulating in the human population. Overall seroprevalence was 3.2%, peaking at 5.3% in autumn 2021. Variant-specific neutralizing antibody responses were detected with titers waning over time. The variant-specific response in the feline population correlated with and trailed the variants circulating in the human population, indicating multiple ongoing human-to-cat spill-over events.

immunology↗

bioRxiv2022

A collaborative approach to improving representation in viral genomic surveillance

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building microbial genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness. Author summaryGenomic surveillance involves decoding a pathogens genetic code to track its spread and evolution. During the pandemic, genomic surveillance programs around the world provided valuable data to scientists, doctors, and public health officials. Knowing the complete SARS-CoV-2 genome has helped detect the emergence of new variants, including ones that are more transmissible or cause more severe disease, and has supported the development of diagnostics, vaccines, and therapeutics. The impact of genomic surveillance on public health depends on representative sampling that accurately reflects the diversity and distribution of populations, as well as rapid turnaround time from sampling to data sharing. After a slow start, SARS-CoV-2 genomic surveillance in the United States grew exponentially. Despite this, many rural regions and ethnic minorities remain poorly represented, leaving significant gaps in the data that informs public health responses. To address this problem, we formed a network of universities and clinics in Louisiana, Georgia, and Mississippi with the goal of increasing SARS-CoV-2 sequencing volume, representation, and equity. Our results demonstrate the advantages of rapidly sequencing pathogens in the same communities where the cases occur and present a model that leverages existing academic and clinical infrastructure for a powerful decentralized genomic surveillance system.

microbiology↗

bioRxiv2022

Disturbed trophoblast transition links preeclampsia progression from placenta to the maternal syndrome

Pre-eclampsia (PE) is a syndrome that affects multiple organ systems and is the most severe hypertensive disorder in pregnancy. It frequently leads to preterm delivery, maternal and fetal morbidity and mortality and life-long complications1. We currently lack efficient screening tools2, 3 and early therapies4, 5 to address PE. To investigate the early stages of early onset PE, and identify candidate markers and pathways, we performed spatio-temporal multi-omics profiling of human PE placentae and healthy controls and validated targets in early gestation in a longitudinal clinical cohort. We used a single-nuclei RNA-seq approach combined with spatial proteo- and transcriptomics and mechanistic in vitro signalling analyses to bridge the gap from late pregnancy disease to early pregnancy pathomechanisms. We discovered a key disruption in villous trophoblast differentiation, which is driven by the increase of transcriptional coactivator p300, that ultimately ends with a senescence-associated secretory phenotype (SASP) of trophoblasts. We found a significant increase in the senescence marker activin A in preeclamptic maternal serum in early gestation, before the development of clinical symptoms, indicating a translation of the placental syndrome to the maternal side. Our work describes a new disease progression, starting with a disturbed transition in villous trophoblast differentiation. Our study identifies potential pathophysiology-relevant biomarkers for the early diagnosis of the disease as well as possible targets for interventions, which would be crucial steps toward protecting the mother and child from gestational mortality and morbidity and an increased risk of cardiovascular disease later in life.

systems biology↗

bioRxiv2022

Allelic compatibility in plant immune receptors facilitates engineering of new effector recognition specificities.

Engineering expanded effector recognition in plant immune receptors is a promising prospect for generating new disease resistant crop varieties. However, modification of plant NLR receptors has proven challenging due to the lack of understanding of their context as part of complex immune systems. Here, we demonstrate a new avenue for NLR-mediated engineering that exploits the allelic diversity in the Pik NLR pair to allow for the generation of receptors with expanded recognition specificities, which would otherwise result in constitutive cell death. This work lays the foundation for the incorporation of new effector recognition motifs into the Pik system and advances the development of designer NLRs that can be tailored to specific secreted pathogen signatures. AbstractEngineering the plant immune system offers genetic solutions to mitigate crop diseases caused by diverse agriculturally significant pathogens and pests. Modification of intracellular plant immune receptors of the nucleotide-binding leucine rich repeat (NLRs) superfamily for expanded recognition of pathogen virulence proteins (effectors) is a promising approach for engineering novel disease resistance. However, engineering can cause NLR autoactivation, resulting in constitutive defence responses that are deleterious to the plant. This may be due to plant NLRs associating in highly complex signalling networks that co-evolve together, and changes through breeding or genetic modification can generate incompatible combinations, resulting in autoimmune phenotypes. We have previously shown how alleles of the rice NLR pair Pik have differentially co-evolved, and how sensor/helper mismatching between non-co-evolved alleles triggers constitutive activation and cell death (De la Concepcion et al., 2021b). Here, we dissect incompatibility determinants in the Pik pair and found that HMA domains integrated in Pik-1 not only evolved to bind pathogen effectors but also likely co-evolved with other NLR domains to maintain immune homeostasis. This explains why changes in integrated domains can lead to autoactivation. We then used this knowledge to facilitate engineering of new effector recognition specificities overcoming initial autoimmune penalties. We show that by mismatching alleles of the rice sensor and helper NLRs Pik-1 and Pik-2, we can enable the integration of synthetic HMA domains with novel and enhanced recognition of an effector from the rice blast fungus. Taken together, our results reveal a new strategy for engineering NLRs, which has the potential to allow an expanded set of integrations and therefore new disease resistance specificities in plants.

plant biology↗

bioRxiv2022

Evaluating rotations as a strategy to delay the evolution of insecticide resistance in vectors of human diseases.

IntroductionInsecticide resistance threatens the control of important human vector-borne diseases such as malaria and dengue. The current de facto strategy is to target the insect vectors using a sequential deployment of insecticides i.e. use one insecticide (usually the cheapest available) until resistance has made it ineffective and then replace it with the next insecticide in the repertoire. Rotations of insecticides are often advocated as a potentially superior method of using the insecticide repertoire to delay the evolution of resistance. Testing this hypothesis in the field is logistically demanding and an in silico approach offers a much faster, flexible and transparent method of evaluating rotations. MethodsWe develop an in silico approach to evaluate rotations using sequential deployment as the baseline. We explored a wide range of deployment scenarios, underlying genetics of resistance, and incorporated costs of resistance and gene flow to/from untreated refugia. ResultsWe found that, under most circumstances, resistance to all the insecticides in the repertoire were reached at very similar times for rotations and sequences. Any advantages of one strategy over the other tended to be small (typically <10%) and unpredictable. ConclusionsOperational factors, such as cost or supply-chain security, may therefore largely determine the optimal choice of insecticide deployment strategies.

evolutionary biology↗