Biology subjects

Lewis, J.

Publications and source records attributed to Lewis, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Mosaic chromosomal alterations in blood across ancestries via whole-genome sequencing

Mosaic mutations in blood are common with increasing age and are prognostic markers for cancer, cardiovascular dysfunction and other diseases. This group of acquired mutations include megabase-scale mosaic chromosomal alterations (mCAs). These large mutations have mainly been surveyed using SNP array data from individuals of European (EA) or Japanese genetic ancestry. To gain a better understanding of mCA rates and associated risk factors in genetically diverse populations, we surveyed whole genome sequencing data from 67,390 individuals, including 20,132 individuals of African ancestry (AA), and 7,608 of Hispanic ancestry (HA) with deep (30X) whole genome sequencing data from the NHLBI Trans Omics for Precision Medicine (TOPMed) program. We adapted an existing mCA calling algorithm for application to WGS data, and observed higher sensitivity with WGS data, compared with array-based data, in uncovering mCAs at low mutant cell fractions. As in previous reports, we observed a strong association with age and a non-uniform distribution of mCAs across the genome. The presence of autosomal (but not chromosome X) mCAs was associated with an increased risk of both lymphoid and myeloid malignancies. After adjusting for age, we found that individuals of European ancestry have the highest rates of autosomal mCAs, mirroring the higher rate of leukemia in this group. Our analysis also uncovered higher rates of chromosome X mCAs in AA and HA compared to EA, again after adjusting for age. Germline variants in ATM and MPL showed strong associations with mCAs in cis, including ancestry specific variants. And rare variant gene-burden analysis confirmed the association of putatively protein altering variants in ATM and MPL with mCAs in cis. Individual rare variants in DCPS, ADM17, PPP1R16B, and TET2 were all associated with autosomal mCAs and rare variants in OR4C16 were associated with chromosome X mCAs in females. There was significant enrichment of co-occurrence of CHIP mutations and mCAs both altering cancer associated genes TET2, DNMT3A, JAK2, CUX1, and TP53. Overall, our study demonstrates that rates of mCAs differ across populations and that rare inherited germline variants are strongly associated with mCAs across genetically diverse populations. These results strongly motivate further studies of mCAs in under-represented populations to better understand the causes and consequences of this class of somatic variation.

genomics↗

bioRxiv2022

SARS-CoV-2 infects multiple species of North American deer mice and causes clinical disease in the California mouse

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the virus that causes coronavirus disease-19 (COVID-19), emerged in late 2019 in Wuhan, China and its rapid global spread has resulted in millions of deaths. An important public health consideration is the potential for SARS-CoV-2 to establish endemicity in a secondary animal reservoir outside of Asia or acquire adaptations that result in new variants with the ability to evade the immune response and reinfect the human population. Previous work has shown that North American deer mice (Peromyscus maniculatus) are susceptible and can transmit SARS-CoV-2 to naive conspecifics, indicating its potential to serve as a wildlife reservoir for SARS-CoV-2 in North America. In this study, we report experimental SARS-CoV-2 susceptibility of two additional subspecies of the North American deer mouse and two additional deer mouse species, with infectious virus and viral RNA present in oral swabs and lung tissue of infected deer mice and neutralizing antibodies present at 15 days post-challenge. Moreover, some of one species, the California mouse (P. californicus) developed clinical disease, including one that required humane euthanasia. California mice often develop spontaneous liver disease, which may serve as a comorbidity for SARS-CoV-2 severity. The results of this study suggest broad susceptibility of rodents in the genus Peromyscus and further emphasize the potential of SARS-CoV-2 to infect a wide array of North American rodents. ImportanceA significant concern is the spillback of SARS-CoV-2 into North American wildlife species. We have determined that several species of peromyscine rodents, the most abundant mammals in North America, are susceptible to SARS-CoV-2 and that infection is likely long enough that the virus may be able to establish persistence in local rodent populations. Strikingly, some California mice developed clinical disease that suggests this species may be useful for the study of human co-morbidities often associated with severe and fatal COVID-19 disease.

microbiology↗

bioRxiv2022

The ExtRA Capacity Test: Reliability and validity study of a new tool for assessing shoulder muscle performance

ObjectivesThe primary objective was to evaluate the reliability of a new tool for assessing shoulder muscle performance: The ExtRA Capacity Test. The secondary objective was to assess whether this tool was a valid measure for assessing shoulder strength. MethodsThe ExtRA Capacity test involves two measures: maximal scapular plane lateral raises to 90{degrees} abduction with 2.5kg of external load and the maximal number of prone lying unsupported external rotations with the shoulder at 90{degrees} abduction. Both capacity tests are completed to a metronome set to 30 beats per minute 20 asymptomatic participants were sampled on 2 separate sessions, 1 week apart. The ExtRA Capacity Test was completed by the lead researcher and an independent physiotherapist. Shoulder strength was also measured using isokinetic dynamometry. ResultsThe test showed excellent inter-rater reliability (mean abduction ICC= 0.969, mean external rotation ICC= 0.822, with a 95% CI). Mean intra-rater variability was 3.96{+/-} 4.09 for the abduction measure and 1.70{+/-} 1.17 for the external rotation measure. Validity was calculated using Pearson correlation coefficient. The abduction measure showed good/ moderate correlation for the majority of strength measurements taken using isokinetic dynamometry however the external rotation capacity test did not correlate closely to isokinetic dynamometry strength measures. ConclusionThe abduction component of the ExtRA Capacity Test is a suitable measure for assessing shoulder strength in clinical practice. The external rotation measure is of suitable reliability however if used in clinical practice, it should not be used to assess shoulder strength, instead it may be suitable to assess movement control of the shoulder. SummaryVarious methods of measuring shoulder strength exist, ranging from cost free, relatively inaccurate methods to costly, complex methods which are of high reliability and validity but are challenging to use in a fast-pace, clinical environment. Objective outcome measures are used within a rehabilitation setting however at present there is no upper limb muscle performance test that is suitable to use on all people, regardless of strength or fitness level. Capacity testing of movements provides a functional, insight into strength specific to a real world/ sporting environment with lower limb capacity tests providing clear objective baselines that can be used for goal setting and providing return to play criteria following injury. This study proves the reliability and validity of the ExtRA Capacity Test which is a measure of shoulder muscle performance, suitable for people of all physical activity levels and upper limb strength.

physiology↗

bioRxiv2022

Structural basis for tunable affinity and specificity of LxCxEdependentprotein interactions with the retinoblastoma protein family

The retinoblastoma protein (Rb) and its homologs p107 and p130 are critical regulators of gene expression during the cell cycle. Functional inactivation of Rb family proteins leads to loss of cell-cycle control and promotes genome instability and proliferation, which are hallmarks of cancer. Rb proteins share a structural domain, known as the "pocket domain", which mediates association with a large number of cellular proteins. A cleft in the pocket domain binds an LxCxE sequence motif in these proteins, many of which function with Rb proteins to co-regulate transcription during quiescence and G1. Proteins from oncogenic DNA viruses also bind this cleft to inactivate Rb family proteins, and the E7 protein from the human papillomavirus has been used as the primary model for understanding LxCxE motif interactions. Evidence presented previously and here demonstrates that the E7 sequence binds tighter and competes with cellular proteins for the LxCxE site, but the molecular basis for the relatively weak affinities of the cellular proteins has been poorly understood. Here, we present binding data and a series of crystal structures of the p107 pocket domain in complex with LxCxE peptides derived from the transcriptional co-repressor proteins HDAC1, ARI4DA, and EID1. The structures reveal determinants of protein binding beyond the L-C-E core that include the N and C-terminal sides of the LxCxE motif and the x (wild card) residues. Our results explain how differences in these interactions outside the L-C-E core result in weaker affinities of pocket protein for cellular LxCxE proteins compared to E7 and result in differences in Rb and p107 affinities for some LxCxE-containing sequences. Our study provides new insights into how Rb proteins bind their myriad of cell partners and lays the foundation for structure-based design of peptides that inhibit oncogenic viral protein interactions.

biochemistry↗

bioRxiv2022

Metabolism of glucose activates TORC1 through multiple mechanisms in Saccharomyces cerevisiae

Target of Rapamycin Complex 1 (TORC1) is a conserved eukaryotic protein complex that links the presence of nutrients with cell growth. In Saccharomyces cerevisiae, TORC1 activity is positively regulated by the presence of amino acids and glucose in the medium. However, mechanisms underlying nutrient-induced TORC1 activation remain poorly understood. By utilizing a TORC1 activation assay, we demonstrate that differential metabolism of glucose activates TORC1 through three distinct pathways in yeast. The first canonical Rag GTPase-dependent pathway requires conversion of glucose to fructose 1,6-bisphosphate which activates TORC1 via the Rag GTPase heterodimer Gtr1GTP/Gtr2GDP. The second non-canonical Rag GTPase-dependent pathway requires conversion of glucose to glucose 6-phosphate which activates TORC1 via Gtr1GTP/Gtr2GTP. The third Rag GTPase-independent pathway requires complete glycolysis and vacuolar ATPase reassembly for TORC1 activation. Glucose-induced TORC1 activation can be uncoupled from glucose-induced AMPK inactivation. We have established a roadmap to deconstruct the link between glucose metabolism and TORC1 activation.

genetics↗

bioRxiv2022

Soil fungal communities vary more with soil characteristics than tree diversity at a local scale

Soil fungal communities vary spatially due to factors including variations in plant diversity and soil characteristics; however, the relative influences of these factors on composition and therefore function remain unclear. Small-scale variation in fungal communities may drive local variation in nutrient cycling and decomposition and may respond more to local factors compared with large climatic variations. Clarifying the roles of these factors can improve our predictions of soil fungal community and biogeochemical cycling responses to anthropogenic changes. Therefore, we examined relationships among abiotic and biotic factors and soil fungal communities associated with Quercus rubra and Pinus resinosa saplings and mature trees in a mixed-hardwood woodland. We also compared community composition and fungal enzymatic activity. Fungal community composition was associated with spatial heterogeneity of soil characteristics, while host sapling and tree species identity were poor predictors of community composition. Further, most of the compositional variation was unexplained by measured variables, suggesting stochasticity and other environmental characteristics may drive spatial variation in these communities. Additionally, enzymatic activity did not clearly correlate with fungal community composition. Overall, soil fungal communities and enzymatic activity adjacent to saplings in this woodland are influenced primarily by soil characteristics and stochasticity and not plant identity.

ecology↗

bioRxiv2022

Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling

The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Drug perturbations can be readily applied to primary cancer samples at a large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a small compound has a range of affinities to multiple proteins. To computationally infer the molecular dependencies of individual cancers from their ex-vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Our method, DepInfeR, correctly identified known dependencies, including EGFR dependence in Her2+ breast cancer cell line, FLT3 dependence in AML tumors with FLT3-ITD mutations and the differential dependencies on the B-cell receptor pathway in two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a more accurate map of the molecular dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.

bioinformatics↗

bioRxiv2021

Preferential associations of soil fungal taxa under mixed compositions of eastern American tree species

Soil fungi are vital to forest ecosystem functions, in part through their role mediating tree responses to environmental factors, as well as directly through effects on resource cycling. While the distribution of these key taxa may vary with a suite of abiotic and biotic factors, the relative role of host species identity on soil fungal community composition and function remains unresolved. In this study, we used a combination of amplicon sequencing and enzymatic assays to assess soil fungal composition and associated function under three tree species, Quercus rubra, Betula nigra, and Acer rubrum, planted individually and in all combinations in a greenhouse, with added fungal inoculum collected below mature field trees. Across treatments, fungal communities were dominated by the phylum Ascomycota, followed by Basidiomycota and Mortierellomycota. Nonetheless, fungal communities differed between each of the solo planted treatments, suggesting at least some taxa may associate preferentially with these tree species. Additionally, fungal community composition under mixed sapling treatments broadly differed from solo saplings. The data also suggests that there were larger enzymatic activities in the solo treatments as compared with all mixed treatments. This difference may be due to the greater relative abundance of saprobic taxa found in the solo treatments. This study provides evidence of the importance of tree identity on soil microbial communities and functional changes to forest soils.

ecology↗

bioRxiv2021

Priority effects among amphibian microbes lead to varying levels of Bd infection

Priority effects in host-associated microbiomes can influence not only community composition and structure, but also community functions, such as disease resistance. However, evidence for these priority effects remains scarce. Past studies suggest that amphibian protection from chytridiomycosis, caused by the pathogenic fungus Batrachochytrium dendrobatidis (Bd), is related to antifungal bacterial composition on host skin. Priority effects in these bacterial communities may influence susceptibility to Bd, but this possibility has not been tested. Using in vitro microcosms, we demonstrated that priority effects can influence interactions among amphibian-associated microbes. We observed strong priority effects irrespective of high antifungal ability such that the Bd-inhibitory potential of two strongly inhibitory bacterial species did not always produce higher levels of Bd-inhibition. This result suggests that interactions may be more complex than previously thought. Additionally, our results suggest that priority effects between commensal and pathogenic taxa can be either facilitatory or inhibitory, with the strength and direction of this effect dependent on the composition of the community. Thus, changes in assembly may lead to varying levels of Bd infection, influencing how we might augment amphibian-associated microbiomes to conserve taxa currently at risk of extinction.

ecology↗

bioRxiv2021

A synergistic interaction between HDAC- and PARP inhibitors in childhood tumors with chromothripsis

Chromothripsis is a form of genomic instability characterized by the occurrence of tens to hundreds of clustered DNA double-strand breaks in a one-off catastrophic event. Rearrangements associated with chromothripsis are detectable in numerous tumor entities and linked with poor prognosis in some of these, such as Sonic Hedgehog medulloblastoma, neuroblastoma and osteosarcoma. Hence, there is a need for therapeutic strategies eliminating tumor cells with chromothripsis. Defects in DNA double-strand break repair, and in particular homologous recombination repair, have been linked with chromothripsis. Targeting DNA repair deficiencies by synthetic lethality approaches, we performed a synergy screen using drug libraries (n = 375 compounds, 15 models) combined with either a PARP inhibitor or cisplatin. This revealed a synergistic interaction between the HDAC inhibitor romidepsin and PARP inhibition. Functional assays, transcriptome analyses, and in vivo validation in patient-derived xenograft mouse models confirmed the efficacy of the combinatorial treatment.

cancer biology↗

bioRxiv2021

A novel glucocorticoid and androgen receptor modulator reduces viral entry and innate immune inflammatory responses in the Syrian Hamster model of SARS-CoV-2

Since its initial discovery in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID19, has spread worldwide and despite significant research efforts, treatment options remain limited. Replication of SARS-CoV-2 in lung is associated with marked infiltration of macrophages and activation of innate immune inflammatory responses triggered, in part, by heightened production of interleukin-6 (IL-6) that recruits lymphocytes to the site of infection that amplify tissue injury. Antagonists of the glucocorticoid and androgen receptors have shown promise in experimental models of COVID19 and in clinical studies, because cell surface proteins required for viral entry, angiotensin converting enzyme 2 (ACE2) and the transmembrane serine protease 2 (TMPRSS2), are transcriptionally regulated by these receptors. We therefore postulated that the glucocorticoid (GR) and androgen receptor (AR) antagonist, PT150, would reduce infectivity of SARS-CoV-2 and prevent inflammatory lung injury in the Syrian golden hamster model of COVID19. Animals were infected intranasally with 2.5 x 104 TCID50/ml equivalents of SARS-CoV-2 (strain 2019-nCoV/USA-WA1/ 2020) and PT150 was administered by oral gavage at 30 and 100 mg/Kg/day for a total of 7 days. Animals were then examined at days 3, 5 and 7 post-infection (DPI) for lung histopathology, viral load and production of proteins regulating the initiation and progression of SARS-CoV-2 infection. Results of these studies indicated that oral administration of PT150 decreased replication of SARS-CoV-2 in lung, as well as expression of ACE2 and TMPRSS2 protein. Hypercellularity and inflammatory cell infiltration driven by macrophage responses were dramatically decreased in PT150-treated animals, as was tissue damage and expression of IL-6. Molecular modeling suggested that PT150 binds to the co-activator interface of the ligand binding domain of both AR and GR and thereby acts as an allosteric modulator and transcriptional repressor of these receptors. Phylogenetic analysis of AR and GR across multiple species permissive to SARS-CoV-2 infection revealed a high degree of sequence identity maintained across species, including human, suggesting that the mechanism of action and therapeutic efficacy observed in Syrian hamsters would likely be predictive of positive outcomes in patients. PT150 is therefore a strong candidate for further clinical development for the treatment of COVID19 across variants of SARS-CoV-2.

immunology↗

bioRxiv2021

The DAXX-SREBP axis promotes oncogenic lipogenesis and tumorigenesis

De novo lipogenesis produces lipids for membrane biosynthesis and cell signaling. Elevated lipogenesis is a major metabolic feature in cancer cells. In breast and other cancer types, genes involved in lipogenesis are highly upregulated, but the mechanisms that control their expression remain poorly understood. DAXX modulates gene expression through binding to diverse transcription factors although the functional impact of these diverse interactions remains to be defined. Our recent analysis indicates that DAXX is overexpressed in diverse cancer types. However, mechanisms underlying DAXXs oncogenic function remains elusive. Using global integrated transcriptomic and lipidomic analyses, we show that DAXX plays a key role in lipid metabolism. DAXX depletion attenuates, while its overexpression enhances, lipogenic gene expression, lipid synthesis and tumor growth. Mechanistically, DAXX interacts with SREBP1 and SREBP2 and activates SREBP-mediated transcription. DAXX associates with lipogenic gene promoters through SREBPs. Underscoring the critical roles for the DAXX-SREBP interaction for lipogenesis, SREBP2 knockdown attenuates tumor growth in cells with DAXX overexpression, and a DAXX mutant unable to bind SREBPs are incapable of promoting lipogenesis and tumor growth. Our results identify the DAXX-SREBP axis as an important pathway for tumorigenesis.

cancer biology↗

bioRxiv2020

A potent SARS-CoV-2 neutralizing human monoclonal antibody that reduces viral burden and disease severity in Syrian hamsters

The emergence of COVID-19 has led to a pandemic that has caused millions of cases of disease, variable morbidity and hundreds of thousands of deaths. Currently, only remdesivir and dexamethasone have demonstrated limited efficacy, only slightly reducing disease burden, thus novel approaches for clinical management of COVID-19 are needed. We identified a panel of human monoclonal antibody clones from a yeast display library with specificity to the SARS-CoV-2 spike protein receptor binding domain that neutralized the virus in vitro. Administration of the lead antibody clone to Syrian hamsters challenged with SARS-CoV-2 significantly reduced viral load and histopathology score in the lungs. Moreover, the antibody interrupted monocyte infiltration into the lungs, which may have contributed to the reduction of disease severity by limiting immunopathological exacerbation. The use of this antibody could provide an important therapy for treatment of COVID-19 patients.

microbiology↗

bioRxiv2020

Oculomotor Target Selection is Cortically Mediated by Complex Objects

Successful oculomotor target selection often requires discriminating visual features but it remains contentious whether oculomotor substrates encoding saccade vectors functionally contribute to this process. One possibility is that visual features are discriminated cortically and oculomotor modules select the object with the highest activation in the set of all preprocessed cortical object representations, while an alternative possibility is that oculomotor modules actively discriminate potential targets based on visual features. If the latter view is correct, these modules should not require input from specialized visual cortices encoding the task relevant features. We therefore examined whether the latency of visual onset responses elicited by abrupt distractor onsets is consistent with input from specialized visual cortices by non-invasively measuring human saccade metrics (saccade curvature, endpoint deviations, saccade frequency, error proportion) as a function of distractor processing time for novel, visually complex distractors that had to be discriminated from a target to guide saccades. Visual onset response latencies were ~110 ms, consistent with projections from anterior cortical sites specialized for object processing. Surprisingly, oculomotor visual onset responses encoded features, as we manipulated the visual similarity between targets and distractors and observed an increased visual onset response magnitude and duration when the distractor was highly similar to the target, which was not attributable to an inhibitory processing delay. Visual onset responses were dynamically modulated by executive function, as these responses were anticipatorily extinguished over the time course of the experiment. As expected, the latency of distractor-related inhibition was modulated by the behavioral relevance of the distractor. Significance StatementWe provide novel insights into the role of the oculomotor system in saccadic target selection by challenging the convention that neural substrates that encode oculomotor vectors functionally contribute to target discrimination. Our data show that the oculomotor system selects a winner from amongst the preprocessed object representations output from specialized visual cortices as supposed to discriminating visual features locally. We also challenge the convention that oculomotor visual onset responses are feature-invariant, as they encoded task-relevance.

neuroscience↗

bioRxiv2020

SARS-CoV-2 infection, neuropathogenesis and transmission among deer mice: Implications for reverse zoonosis to New World rodents

Coronavirus disease-19 (COVID-19) emerged in November, 2019 in China and rapidly became pandemic. As with other coronaviruses, a preponderance of evidence suggests the virus originated in horseshoe bats (Rhinolophus spp.) and likely underwent a recombination event in an intermediate host prior to entry into human populations. A significant concern is that SARS-CoV-2 could become established in secondary reservoir hosts outside of Asia. To assess this potential, we challenged deer mice (Peromyscus maniculatus) with SARS-CoV-2 and found robust virus replication in the upper respiratory tract, lungs and intestines, with detectable viral RNA for up to 21 days in oral swabs and 14 days in lungs. Virus entry into the brain also occurred, likely via gustatory-olfactory-trigeminal pathway with eventual compromise to the blood brain barrier. Despite this, no conspicuous signs of disease were observed and no deer mice succumbed to infection. Expression of several innate immune response genes were elevated in the lungs, notably IFN, Cxcl10, Oas2, Tbk1 and Pycard. Elevated CD4 and CD8{beta} expression in the lungs was concomitant with Tbx21, IFN{gamma} and IL-21 expression, suggesting a type I inflammatory immune response. Contact transmission occurred from infected to naive deer mice through two passages, showing sustained natural transmission. In the second deer mouse passage, an insertion of 4 amino acids occurred to fixation in the N-terminal domain of the spike protein that is predicted to form a solvent-accessible loop. Subsequent examination of the source virus from BEI Resources indicated the mutation was present at very low levels, demonstrating potent purifying selection for the insert during in vivo passage. Collectively, this work has determined that deer mice are a suitable animal model for the study of SARS-CoV-2 pathogenesis, and that they have the potential to serve as secondary reservoir hosts that could lead to periodic outbreaks of COVID-19 in North America.

microbiology↗

bioRxiv2020

Evaluation of a novel multiplexed assay for determining IgG levels and functional activity to SARS-CoV-2.

BackgroundThe emergence of SARS-CoV-2 has led to the development of new serological assays that could aid in diagnosis and evaluation of seroprevalence to inform an understanding of the burden of COVID-19 disease. Many available tests lack rigorous evaluation and therefore results may be misleading. ObjectivesThe aim of this study was to assess the performance of a novel multiplexed immunoassay for the simultaneous detection of antibodies against SARS-CoV-2 trimeric spike (S), spike receptor binding domain (RBD), spike N terminal domain and nucleocapsid antigen and a novel pseudo-neutralisation assay. MethodsA multiplexed solid-phase chemiluminescence assay (Meso Scale Discovery) was evaluated for the simultaneous detection of IgG binding to four SARS-CoV-2 antigens and the quantification of antibody-induced ACE-2 binding inhibition (pseudo-neutralisation assay). Sensitivity was evaluated with a total of 196 COVID-19 serum samples (169 confirmed PCR positive and 27 anti-nucleocapsid IgG positive) from individuals with mild symptomatic or asymptomatic disease. Specificity was evaluated with 194 control serum samples collected from adults prior to December 2019. ResultsThe specificity and sensitivity of the binding IgG assay was highest for S protein with a specificity of 97.4% and sensitivity of 96.2% for samples taken 14 days and 97.9% for samples taken 21 days following the onset of symptoms. IgG concentration to S and RBD correlated strongly with percentage inhibition measured by the pseudo-neutralisation assay. ConclusionExcellent sensitivity for IgG detection was obtained over 14 days since onset of symptoms for three SARS-CoV-2 antigens (S, RBD and N) in this multiplexed assay which can also measure antibody functionality.

immunology↗

bioRxiv2020

Dynamics of a neuronal pacemaker in the weakly electric fish Apteronotus

The precise timing of neuronal activity is critical for normal brain function. In weakly electric fish, the medullary pacemaker network (PN) sets the timing for an oscillating electric organ discharge (EOD) used for electric sensing. This network is the most precise biological oscillator known, with sub-microsecond variation in oscillator period. The PN consists of two principle sets of neurons, pacemaker and relay cells, that are connected by gap junctions and normally fire in synchrony, one-to-one with each EOD cycle. However, the degree of gap junctional connectivity between these cells appears insufficient to provide the population averaging required for the observed temporal precision of the EOD. This has led to the hypothesis that individual cells themselves fire with high precision, but little is known about the oscillatory dynamics of these pacemaker cells. To this end, we have developed a biophysical model of a pacemaker neuron action potential based on experimental recordings. We validated the model by comparing the changes in oscillatory dynamics produced by different experimental manipulations. Our results suggest that a relatively simple model captures the complex dynamics exhibited by pacemaker cells, and that these dynamics may enhance network synchrony and precision. Author summaryMany neural networks in the brain exhibit activity patterns which oscillate regularly in time. These oscillations, like a clock, can provide a precise sense of time, enabling drummers to maintain complex beat patterns and pets to anticipate "feeding time". The exact mechanisms by which brain networks give rise to these biological clocks are not clear. The pacemaker network of weakly electric fish has the highest precision of all known biological clocks. In this study, we develop a detailed biophysical model of neurons in the pacemaker network. We then validate the model against experiments using a nonlinear dynamics approach. Our results show that pacemaker precision is due, at least in part, to how individual pacemaker cells generate their activity. This supports the idea that temporal precision in this network is not solely an emergent property of the network but also relies on the dynamics of individual neurons.

neuroscience↗

bioRxiv2020

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

O_LIMotion-activated wildlife cameras (or "camera traps") are frequently used to remotely and non-invasively observe animals. The vast number of images collected from camera trap projects have prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. C_LIO_LIWe used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the "species model," and one that determines if an image is empty or if it contains an animal, the "empty-animal model." C_LIO_LIOur species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36-91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91-94% on out-of-sample datasets from different continents. C_LIO_LIOur software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths. C_LI

ecology↗