Biology subjects

Smith, A. M.

Publications and source records attributed to Smith, A. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Modification of amyloplast size in wheat endosperm through mutation of PARC6 affects starch granule morphology

Starch granule morphology is a major factor determining the functional and nutritional properties of starch. Here, we reveal amyloplast structure plays an important role in starch granule morphogenesis in wheat endosperm. Wheat amyloplasts contain large discoid A-type granules and small spherical B-type granules. We isolated a mutant in durum wheat defective in the plastid division protein PARC6, which had increased plastid size in both leaves and endosperm. Endosperm amyloplasts of the mutant contained more A- and B-type granules than those of the wild type. In mature grains, the mutant had larger A- and B-type granules than the wild type, and its A-type granules had a highly aberrant, lobed surface. This defect in granule morphology was already evident at early stages of grain development, when granule size was identical between the mutant and the wild type, and occurred without obvious alterations in starch polymer structure and composition. Plant growth and photosynthetic efficiency, as well as the size, number and starch content of grains, were not affected in the Ttparc6 mutants despite the large changes in plastid size. Interestingly, mutation of the PARC6 paralog, ARC6, in durum wheat did not increase plastid or starch granule size. We suggest this is because TtPARC6 can complement disrupted TtARC6 function by interacting with PDV2, the outer plastid envelope protein that typically interacts with ARC6 to promote plastid division. We propose that amyloplast compartment size and available stromal volume play important roles in determining starch granule size, shape and number per amyloplast.

plant biology↗

bioRxiv2022

DeepBryo: a web app for AI-assisted morphometric characterization of cheilostome bryozoans

O_LIBryozoans are becoming an increasingly popular study system in macroevolutionary, ecological, and paleobiological research. Members of this colonial invertebrate phylum are notable for displaying an exceptional degree of division of labor in the form of specialized modules (polymorphs), which allow for the inference of individual allocation of resources to reproduction, defense, and growth using simple morphometric tools. However, morphometric characterizations of bryozoans are notoriously labored, due to the high number of structures often captured per image, as well as the need for specialized knowledge necessary for classifying individual skeletal structures within those images. C_LIO_LIWe here introduce DeepBryo, a web application for deep learning-based morphometric characterization of cheilostome bryozoans. DeepBryo requires a single image as input and performs measurements automatically using instance segmentation algorithms. DeepBryo is capable of detecting objects belonging to six classes and outputting fourteen morphological shape measurements for each object based on the inferred segmentation maps. The users can visualize the predictions, check for errors, and directly filter model outputs on the web browser. Measurements can then be downloaded as a comma-separated values file. C_LIO_LIDeepBryo has been trained and validated on a total of 72,412 structures, belonging to six different object classes in 935 SEM images of cheilostome bryozoans belonging to 109 different families. The model shows high (>0.8) recall and precision for zooid-level structures. Its misclassification rate is low (~4%) and largely concentrated in a single object class (opesia). The models estimated structure-level area, height, and width measurements are statistically indistinguishable from those obtained via manual annotation (r2 varying from 0.89 to 0.98) and show no detectable bias. DeepBryo reduces the person-hours required for characterizing the zooids in individual colonies to less than 1% of the time required for manual annotation at no significant loss of measurement accuracy. C_LIO_LIOur results indicate that DeepBryo enables cost-, labor,- and time-efficient morphometric characterization of cheilostome bryozoans. DeepBryo can greatly increase the scale of macroevolutionary, ecological, taxonomic, and paleobiological analyses, as well as the accessibility of deep learning tools for this emerging model system. Finally, DeepBryo provides the building blocks necessary for adapting the current application to other study groups. C_LI

bioinformatics↗

bioRxiv2022

Predicting species distributions with environmental time series data and deep learning

Species distribution models (SDMs) are widely used to gain ecological understanding and guide conservation decisions. These models are developed with a wide variety of algorithms - from statistic-based approaches to machine learning approaches - but a requirement almost all share is the use of predictor variables that strongly simplify the temporal variability of driving factors. Conversely, novel architectures of deep learning neural networks allow dealing with fully explicit spatiotemporal dynamics and thus fitting SDMs without the need to simplify the temporal and spatial dimension of predictor data. We present and demonstrate a deep learning based SDM approach that uses time series of spatial data as predictors using distribution data for 74 species from a well-established benchmark dataset. The deep learning approach provided consistently accurate models, directly using time series of predictor data and thus avoiding the use of pre-processed predictor sets that can obscure relevant aspects of environmental variation.

ecology↗

bioRxiv2022

Multiplex PCR Assay for Clade-typing Salmonella Enteritidis

2.Salmonella Enteritidis is one of the most commonly reported serovars of non-typhoidal Salmonella causing human disease and is responsible for both gastroenteritis and invasive non-typhoidal Salmonella (iNTS) disease worldwide. Whole-genome sequence (WGS) comparison of Salmonella Enteritidis isolates from across the world have identified three distinct clades, named Global Epidemic, Central/East African and West African, all of which have been implicated in epidemics: the Global Epidemic clade was linked to poultry-associated gastroenteritis, while the two African clades were related to iNTS disease. However, the distribution and epidemiology of these clades across Africa is poorly understood because identification of these clades currently requires whole genome sequencing capacity. Here, we report a sensitive, time- and cost-effective real-time PCR assay capable of differentiating between the Salmonella Enteritidis clades to facilitate surveillance and to inform public health responses. 3. Impact statementChallenges in the diagnosis and treatment of invasive Salmonella Enteritidis (S. Enteritidis) bloodstream infections in sub-Saharan Africa are responsible for a case fatality rate of approximately 15% (12). It is important to identify distinct clades of S. Enteritidis in diagnostic laboratories in the African setting to determine whether particular outbreaks are associated with different health outcomes. Here, we have described the development of a high-quality molecular classification assay for the clade-typing of S. Enteritidis that is ideal for use in public health laboratories in resource-limited settings.

molecular biology↗

bioRxiv2022

Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps

The SARS-CoV-2 Omicron variant, with 15 mutations in Spike receptor binding domain (Spike-RBD), renders virtually all clinical monoclonal antibodies against WT SARS-CoV-2 ineffective. We recently engineered the SARS-CoV-2 host entry receptor, ACE2, to tightly bind WT-Spike-RBD and prevent viral entry into host cells ("receptor traps"). Here we determine cryo-EM structures of our receptor traps in complex with full length Spike. We develop a multi-model pipeline combining Rosetta protein modeling software and cryo-EM to allow interface energy calculations even at limited resolution and identify interface side chains that allow for high affinity interactions between our ACE2 receptor traps and Spike-RBD. Our structural analysis provides a mechanistic rationale for the high affinity (0.53 - 4.2nM) binding of our ACE2 receptor traps to Omicron-RBD confirmed with biolayer interferometry measurements. Finally, we show that ACE2 receptor traps potently neutralize Omicron- and Delta-pseudotyped viruses, providing alternative therapeutic routes to combat this evolving virus.

biochemistry↗

bioRxiv2022

oca2 targeting using CRISPR/Cas9 in the Malawi cichlid Astatotilapia calliptera

Identifying genetic loci underlying trait variation provides insights into the mechanisms of diversification, but demonstrating causality and characterising the role of genetic loci requires testing candidate gene function, often in non-model species. Here we establish CRISPR/Cas9 editing in Astatotilapia calliptera, a generalist cichlid of the remarkably diverse Lake Malawi radiation. By targeting the gene oca2 required for melanin synthesis in other vertebrate species, we show efficient editing and germline transmission. Gene edits include indels in the coding region, likely a result of non-homologous end joining, and a large deletion in the 3' UTR due to homology-directed repair. We find that oca2 knock-out A. calliptera lack melanin, which may be useful for developmental imaging in embryos and studying colour pattern formation in adults. As A. calliptera resembles the presumed generalist ancestor of the Lake Malawi cichlids radiation, establishing genome editing in this species will facilitate investigating speciation, adaptation and trait diversification in this textbook radiation.

developmental biology↗

bioRxiv2021

Glycosaminoglycans and glycoproteins influence the elastic response of synovial fluid nanofilms on model oxide surfaces

Synovial fluid (SF) is the natural lubricant found in articulated joints, providing unique cartilage surface protecting films under confinement and relative motion. While it is known that the synergistic interactions of the macromolecular constituents provide its unique load-bearing and tribological performance, it is not fully understood how two of the main constituents, glycosaminoglycans (GAGs) and glycoproteins, regulate the formation and mechanics of robust load-bearing films. Here, we present evidence that the load-bearing capabilities, rather than the tribological performance, of the formed SF films depend strongly on its components integrity. For this purpose, we used a combination of enzymatic treatments, quartz crystal microbalance with dissipation (QCM-D) and the surface forces apparatus (SFA) to characterize the formation and load-bearing capabilities of SF films on model oxide (i.e., silicates) surfaces. We find that, upon cleavage of proteins, the elasticity of the films is reduced and that cleaving GAGs results in irreversible (plastic) molecular re-arrangements of the film constituents when subjected to confinement. Understanding thin film mechanics of SF can provide insight into the progression of diseases, such as arthritis, but may also be applicable to the development of new implant surface treatments or new biomimetic lubricants.

biophysics↗

bioRxiv2021

Single nuclear transcriptional signatures of dysfunctional brain vascular homeostasis in Alzheimer's disease

Brain perfusion and normal blood brain barrier integrity are reduced early in Alzheimers disease (AD). We performed single nucleus RNA sequencing of vascular cells isolated from AD and control brains to characterise pathological transcriptional signatures. We found that endothelial cells (EC) are enriched for expression of genes associated with susceptibility to AD. EC transcriptional signatures identified mechanisms for impaired {beta}-amyloid clearance. Evidence for immune activation was found with upregulation of interferon signalling genes in EC and in pericytes (PC). Transcriptional signatures suggested dysregulation of vascular homeostasis and angiogenesis with upregulation of pro-angiogenic signals (HIF1A) and metabolism in EC, but downregulation of homeostatic growth factor pathways (VEGF, EGF, insulin) in EC and PC and of extracellular matrix genes in fibroblasts (FB). Our genomic dissection of vascular cell risk gene enrichment suggests a potentially causal role for EC and defines transcriptional signatures associated with microvascular dysfunction in AD.

neuroscience↗

bioRxiv2021

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes.

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

biophysics↗

bioRxiv2021

Sentinel cells enable genetic detection of SARS-CoV-2 Spike protein

The COVID-19 pandemic has demonstrated the need for exploring different diagnostic and therapeutic modalities to tackle future viral threats. In this vein, we propose the idea of sentinel cells, cellular biosensors capable of detecting viral antigens and responding to them with customizable responses. Using SARS-CoV-2 as a test case, we developed a live cell sensor (SARSNotch) using a de novo-designed protein binder against the SARS-CoV-2 Spike protein. SARSNotch is capable of driving custom genetically-encoded payloads in immortalized cell lines or in primary T lymphocytes in response to purified SARS-CoV-2 Spike or in the presence of Spike-expressing cells. Furthermore, SARSNotch is functional in a cellular system used in directed evolution platforms for development of better binders or therapeutics. In keeping with the rapid dissemination of scientific knowledge that has characterized the incredible scientific response to the ongoing pandemic, we extend an open invitation for others to make use of and improve SARSNotch sentinel cells in the hopes of unlocking the potential of the next generation of smart antiviral therapeutics.

synthetic biology↗

bioRxiv2021

Combining chemogenomic and gene-dose assays to investigate drug synergy

From the earliest days of using natural remedies to modern applications of clinically tested medications, combining therapies for disease treatment has been standard practice. Combination treatments can exhibit synergistic effects, broadly defined as a greater-than-additive effect of two or more therapeutic agents. Indeed, clinicians often use their experience and expertise to tailor such combinations in the hopes of maximizing the therapeutic effect. Alongside these efforts, computational studies into understanding and predicting the biophysical underpinnings of how synergy is achieved have benefitted from high-throughput screening and computational biology. One challenge is how to best design and analyze the results of synergy studies performed at scale, especially because the number of possible combinations to test quickly becomes unmanageable, and the tools to analyze the resulting data are quite new. Nevertheless, the benefits of such studies are clear -- by combining multiple drugs in the treatment of infectious disease and cancer, for instance, one can lessen host toxicity and simultaneously reduce the likelihood of resistance to treatment. In this study, we extend the widely validated chemogenomic HIPHOP assay to drug combinations. We identify a class of "combination-specific sensitive strains" that suggest mechanisms for the synergies we observe and further suggest focused follow-up studies.

genomics↗

bioRxiv2021

The pathway of starch synthesis in Arabidopsis thaliana leaves

Many plants accumulate transitory starch reserves in their leaves during the day to buffer their carbohydrate supply against fluctuating light conditions, and to provide carbon and energy for survival at night. It is universally accepted that transitory starch is synthesized from ADP-glucose (ADPG) in the chloroplasts. However, the consensus that ADPG is made in the chloroplasts by ADPG pyrophosphorylase has been challenged by a controversial proposal that ADPG is made primarily in the cytosol, probably by sucrose synthase (SUS), and then imported into the chloroplasts. To resolve this long-standing controversy, we critically re-examined the experimental evidence that appears to conflict with the consensus pathway. We show that when precautions are taken to avoid artefactual changes during leaf sampling, Arabidopsis thaliana mutants that lack SUS activity in mesophyll cells (quadruple sus1234) or have no SUS activity (sextuple sus123456) have wild-type levels of ADPG and starch, while ADPG is 20 times lower in the pgm and adg1 mutants that are blocked in the classical pathway of starch synthesis. We conclude that the ADPG needed for starch synthesis in leaves is synthesized primarily by ADPG pyrophosphorylase in the chloroplasts. Significance statementMutant analysis shows that sucrose synthase makes no significant contribution to transitory starch synthesis in Arabidopsis leaves, resolving a 20-year old controversy about one of the most important pathways of photosynthetic metabolism.

plant biology↗

bioRxiv2021

COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results indicate that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation. Author summaryUnderstanding of how the immune system responds to SARS-CoV-2 infections is critical for improving diagnostic and treatment approaches. Identifying which immune mechanisms lead to divergent outcomes can be clinically difficult, and experimental models and longitudinal data are only beginning to emerge. In response, we developed a mechanistic, mathematical and computational model of the immunopathology of COVID-19 calibrated to and validated against a broad set of experimental and clinical immunological data. To study the drivers of severe COVID-19, we used our model to expand a cohort of virtual patients, each with realistic disease dynamics. Our results identify key processes that regulate the immune response to SARS-CoV-2 infection in virtual patients and suggest viable therapeutic targets, underlining the importance of a rational approach to studying novel pathogens using intra-host models.

immunology↗

bioRxiv2020

A broadly resolved molecular phylogeny of New Zealand cheilostome bryozoans as a framework for hypotheses of morphological evolution

Larger molecular phylogenies based on ever more genes are becoming commonplace with the advent of cheaper and more streamlined sequencing and bioinformatics pipelines. However, many groups of inconspicuous but no less evolutionarily or ecologically important marine invertebrates are still neglected in the quest for understanding species- and higher-level phylogenetic relationships. Here, we alleviate this issue by presenting the molecular sequences of 165 cheilostome bryozoan species from New Zealand waters. New Zealand is our geographic region of choice as its cheilostome fauna is taxonomically, functionally and ecologically diverse, and better characterized than many other such faunas in the world. Using this most taxonomically broadly-sampled and statistically-supported cheilostome phylogeny comprising 214 species, when including previously published sequences, we tested several existing systematic hypotheses based solely on morphological observations. We find that lower taxonomic level hypotheses (species and genera) are robust while our inferred trees did not reflect current higher-level systematics (family and above), illustrating a general need for the rethinking of current hypotheses. To illustrate the utility of our new phylogeny, we reconstruct the evolutionary history of frontal shields (i.e., a calcified bodywall layer in ascus-bearing cheilostomes) and asked if its presence has any bearing on the diversification rates of cheilostomes.

evolutionary biology↗

bioRxiv2020

Rapid community-driven development of a SARS-CoV-2 tissue simulator

The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable "choke points" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.

systems biology↗

bioRxiv2020

Molecular phylogeny of historical micro-invertebrate specimens using de novo sequence assembly

Resolution of relationships at lower taxonomic levels is crucial for answering many evolutionary questions, and as such, sufficiently varied species representation is vital. This latter goal is not always achievable with relatively fresh samples. To alleviate the difficulties in procuring rarer taxa, we have seen increasing utilization of historical specimens in building molecular phylogenies using high throughput sequencing. This effort, however, has mainly focused on large-bodied or well-studied groups, with small-bodied and under-studied taxa under-prioritized. Here, we present a pipeline that utilizes both historical and contemporary specimens, to increase the resolution of phylogenetic relationships among understudied and small-bodied metazoans, namely, cheilostome bryozoans. In this study, we pioneer sequencing of air-dried bryozoans, utilizing a recent library preparation method for low DNA input. We use the de novo mitogenome assembly from the target specimen itself as reference for iterative mapping, and the comparison thereof. In doing so, we present mitochondrial and ribosomal RNA sequences of 43 cheilostomes representing 37 species, including 14 from historical samples ranging from 50 to 149 years old. The inferred phylogenetic relationships of these samples, analyzed together with publicly available sequence data, are shown in a statistically well-supported 65 taxa and 17 genes cheilostome tree. Finally, the methodological success is emphasized by circularizing a total of 27 mitogenomes, seven from historical cheilostome samples. Our study highlights the potential of utilizing DNA from micro-invertebrate specimens stored in natural history collections for resolving phylogenetic relationships between species.

evolutionary biology↗

bioRxiv2020

Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks

Multiple Sclerosis (MS) is a neurodegenerative disorder characterized by a complex set of clinical assessments. We use an unsupervised machine learning model called a Conditional Restricted Boltzmann Machine (CRBM) to learn the relationships between covariates commonly used to characterize subjects and their disease progression in MS clinical trials. A CRBM is capable of generating digital twins, which are simulated subjects having the same baseline data as actual subjects. Digital twins allow for subject-level statistical analyses of disease progression. The CRBM is trained using data from 2395 subjects enrolled in the placebo arms of clinical trials across the three primary subtypes of MS. We discuss how CRBMs are trained and show that digital twins generated by the model are statistically indistinguishable from their actual subject counterparts along a number of measures.

bioinformatics↗

bioRxiv2019

OPTN translocates to an ATG9A-positive compartment to regulate innate immune signalling and cytokine secretion

Optineurin (OPTN) is a multifunctional protein involved in autophagy, secretion as well as NF-{kappa}B and IRF3 signalling and mutations are associated with several human diseases including primary open-angle glaucoma (POAG), amyotrophic lateral sclerosis (ALS), Pagets disease of bone (PDB) and Crohns disease (CD). Here we show that, in response to viral RNA, OPTN translocates to foci in the perinuclear region, where it negatively regulates NF-{kappa}B and IRF3 signalling pathways and downstream pro-inflammatory cytokine secretion. These OPTN foci consist of a tight cluster of small membrane vesicles, which are positive for marker proteins of the trans-Golgi network/recycling compartment - most notably ATG9A. Disease mutations linked to POAG cause aberrant formation of this compartment in the absence of stimuli, which correlates with the ability of OPTN to inhibit signalling. Using proximity labelling proteomics (BioID), we identify the linear ubiquitin assembly complex (LUBAC), CYLD and TBK1 as part of the OPTN interactome and show that these proteins, along with NEMO, are recruited to this OPTN-positive perinuclear compartment. Together, we propose OPTN might be responsible for dampening the NF-{kappa}B and IRF3 signalling responses through the sequestration of LUBAC and other positive regulators of these pathways in this dsRNA-induced compartment leading to altered pro-inflammatory cytokine secretion.\n\nSummaryDisease associated OPTN mutations impact on the formation of the perinuclear compartment and result in hypo- or hyper-activation of the immune response, which could drive the development of human diseases such as POAG, ALS and also Pagets disease of bone.

cell biology↗