Biology subjects

Smith, J.

Publications and source records attributed to Smith, J..

At least 145 records · Page 8Linked to original sources

bioRxiv2020

A Novel Small Animal Model of Norovirus Diarrhea

Human noroviruses are the leading cause of severe childhood diarrhea worldwide yet we know very little about their pathogenic mechanisms. Murine noroviruses cause diarrhea in interferon-deficient adult mice but these hosts also develop systemic pathology and lethality, reducing confidence in the translatability of findings to human norovirus disease. Herein we report that a murine norovirus causes self-resolving diarrhea in the absence of systemic disease in wild-type neonatal mice, thus mirroring the key features of human norovirus disease and representing a robust norovirus small animal disease model. Intriguingly, lymphocytes are critical for controlling acute norovirus replication while simultaneously contributing to disease severity, likely reflecting their dual role as targets of viral infection and key components of the host response.

microbiology↗

bioRxiv2020

Elucidating the molecular interactions between uremic toxins and the Sudlow II binding site of human serum albumin

Protein bound uremic toxins (PBUTs) are known to bind strongly with the primary drug carrying sites of human serum albumin (HSA), Sudlow site I and Sudlow site II. A detailed energetic and structural description of PBUT interactions with these binding sites would provide useful insight into the design of materials that specifically displace and capture PBUTs. In this work, we used molecular dynamics (MD) simulations to study in atomistic detail 4 PBUTs bound in Sudlow site II. Specifically, we used the experimentally resolved X-ray structure of simulated indoxyl sulfate (IS) bound to Sudlow site II (PBD ID: 2BXH) to generate initial binding poses for p-cresyl sulfate (pCS), indole-3-acetic acid (IAA), and hippuric acid (HA). We calculated the interaction energy between toxin and protein in MD simulations and performed mean shift clustering on the collection of molecular structures from MD to identify the primary binding modes of each toxin. We find that all 4 toxins are primarily stabilized by electrostatic interactions between their anionic moiety and the hydrophilic residues in Sudlow site II. We observed transience in the strongest toxin-protein interaction, a charge-pairing with the positively charged R410 residue. We confirm the finding that the primary binding pose of IS in Sudlow site II is stabilized by a hydrogen bond with the carbonyl oxygen of L430, and find that this is also true for IAA. We provide insight into the chemical functional groups that might be incorporated to improve the specificity of synthetic materials for PBUT capture. This work represents a next step toward the de novo design of solutions to the problem of PBUT management in CKD patients. Significance StatementIn spite of their implication in poor clinical outcomes, surprisingly little information is available about the structure and mechanisms that govern the binding of protein bound uremic toxins to their primary carrier human serum albumin. To date, only the structure of indoxyl sulfate has been determined by experiment. This paper describes a comprehensive characterization of four toxins that are known to bind Sudlow site II using molecular dynamics simulations. Based on the experimental structure of indoxyl sulfate bound to HSA, the binding mode within Sudlow site II of three additional PBUTs was determined. The structures, energetic and mechanistic analysis provide substantial new information for the nephrology community about these toxins as well as new protocols to aid future studies of PBUTs.

biochemistry↗

bioRxiv2020

Population sequencing data reveal a compendium of mutational processes in human germline

Mechanistic processes underlying human germline mutations remain largely unknown. Variation in mutation rate and spectra along the genome is informative about the biological mechanisms. We statistically decompose this variation into separate processes using a blind source separation technique. The analysis of a large-scale whole genome sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. Seven of these processes lend themselves to a biological interpretation. One process is driven by bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes independently track direction of replication fork and replication timing. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions. We also demonstrate that a recently discovered mutagenic process specific to oocytes can be localized solely from population sequencing data. This process is spread across all chromosomes and is highly asymmetric with respect to the direction of transcription, suggesting a major role of DNA damage.

genetics↗

bioRxiv2019

Transcriptomic Profiling of Skeletal Muscle Adaptations to Exercise and Inactivity

The molecular mechanisms underlying the response to exercise and inactivity are not fully understood. We propose an innovative approach to profile the skeletal muscle transcriptome to exercise and inactivity using 66 published datasets. Data collected from human studies of aerobic and resistance exercise, including acute and chronic exercise training, were integrated using meta-analysis methods (www.metamex.eu). Gene ontology and pathway analyses reveal selective pathways activated by inactivity, aerobic versus resistance and acute versus chronic exercise training. We identified NR4A3 as one of the most exercise- and inactivity-responsive genes, and established a role for this nuclear receptor in mediating the metabolic responses to exercise-like stimuli in vitro. The meta-analysis (MetaMEx) also highlights the differential response to exercise in individuals with metabolic impairments. MetaMEx provides the most extensive dataset of skeletal muscle transcriptional responses to different modes of exercise and an online interface to readily interrogate the database.

physiology↗

bioRxiv2019

Viral manipulation of functionally distinct neurons from mice to humans

Recent success in identifying gene regulatory elements in the context of recombinant adeno-associated virus vectors have enabled cell type-restricted gene expression. However, within the cerebral cortex these tools are presently limited to broad classes of neurons. To overcome this limitation, we developed a strategy that led to the identification of multiple novel enhancers to target functionally distinct neuronal subtypes. By investigating the regulatory landscape of the disease gene Scn1a, we identified enhancers that target the breadth of its expression, including two that are selective for parvalbumin and vasoactive intestinal peptide cortical interneurons. Demonstrating the functional utility of these elements, we found that the PV-specific enhancer allowed for the selective targeting and manipulation of these neurons across species, from mice to humans. Finally, we demonstrate that our selection method is generalizable to other genes and characterize four additional PV-specific enhancers with exquisite specificity for distinct regions of the brain. Altogether, these viral tools can be used for cell-type specific circuit manipulation and hold considerable promise for use in therapeutic interventions.

neuroscience↗

bioRxiv2019

Selectivity and engineering of the sialoglycan-binding spectrum in Siglec-like adhesins

The Siglec-like Serine-Rich Repeat (SRR) adhesins mediate bacterial attachment to mammalian hosts via sialoglycan receptors. Here, we combine structural, computational, biochemical, and phylogenetic approaches to elucidate the determinants of the sialoglycan-binding spectrum across the family of Siglec-like SRR adhesins. We further identified mutable positions that disproportionately affect sialoglycan selectivity, as demonstrated by increases in binding to alternative ligands of 2- to 3-orders of magnitude. Biologically, these studies highlight how bacteria nimbly modulate the receptor interaction during coevolution of host and pathogen. These studies additionally created binding proteins specific for sialyl-T antigen or 6S-sialyl LewisX that can recognize glycosylation of human plasma proteins. The engineered binding proteins can facilitate the characterization of normal cellular glycan modifications or may be used as diagnostic tools in disease states with altered glycosylation.\n\nSignificanceThe ability of bacteria to bind selectively to host receptors underlies both commensalism and pathogenesis. Here, we identify the molecular basis for receptor selectivity in streptococci that bind to sialoglycan receptors. This revealed how to convert these adhesins into selective probes that measure triand tetrasacharides within the context of larger glycosylations. These probes that can be used in a laboratory with no specialized equipment and can be used to address biological questions relating to sialoglycan-dependent signaling and adhesion.

biochemistry↗

bioRxiv2019

Illuminating the dark side of the human transcriptome with TAMA Iso-Seq analysis

The human transcriptome is one of the most well-annotated of the eukaryotic species. However, limitations in technology biased discovery toward protein coding spliced genes. Accurate high throughput long read RNA sequencing now has the potential to investigate genes that were previously undetectable. Using our Transcriptome Annotation by Modular Algorithms (TAMA) tool kit to analyze the Pacific Bioscience Universal Human Reference RNA Sequel II Iso-Seq dataset, we discovered thousands of potential novel genes and identified challenges in both RNA preparation and long read data processing that have major implications for transcriptome annotation.

genomics↗

bioRxiv2019

Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

neuroscience↗

bioRxiv2019

The wild species genome ancestry of domestic chickens

Hybridization and/or introgression play a key role in the evolutionary history of animal species. It is commonly observed in several orders in wild birds. The domestic chicken Gallus gallus domesticus is the commonest livestock species exploited for the benefit of mankind. The origin of its diversity remains unsettled. Here, we report a genome-wide analyses for signatures of introgression within domestic village chicken. We first established the genome-wide phylogeny and divergence time across the genus Gallus, showing the sister relationships between Grey junglefowl G. sonneratii and Ceylon junglefowl G. lafayettii and that the Green junglefowl is the first diverging lineage within the genus Gallus. Then, by analysing the whole-genome sequences of geographically diverse chicken populations, we reveal extensive bidirectional introgression between Grey junglefowl and domestic chicken and to a much less extent with Ceylon junglefowl. A single case of Green junglefowl G. varius introgression was identified. These introgressed regions include biological functions related to the control of gene expression. Our results show that while the Red junglefowl is the main ancestral species, introgressive hybridization episodes have impacted the genome and contributed to the diversity of domestic chicken, although likely at different level across its geographic range.

evolutionary biology↗

bioRxiv2019

Critiquing Protein Family Classification Models Using Sufficient Input Subsets

In many application domains, neural networks are highly accurate and have been deployed at large scale. However, users often do not have good tools for understanding how these models arrive at their predictions. This has hindered adoption in fields such as the life and medical sciences, where researchers require that models base their decisions on underlying biological phenomena rather than peculiarities of the dataset introduced. In response, we propose a set of methods for critiquing deep learning models and demonstrate their application for protein family classification, a task for which high-accuracy models have considerable potential impact. Our methods extend the sufficient input subsets technique, which we use to identify subsets of features (SIS) in each protein sequence that are alone sufficient for classification. Our suite of tools analyzes these subsets to shed light on the decision-making criteria employed by models trained on this task. These tools expose that while deep models may perform classification for biologically-relevant reasons, their behavior varies considerably across choice of network architecture and parameter initialization. While the techniques that we develop are specific to the protein sequence classification task, the approach taken generalizes to a broad set of scientific contexts in which model interpretability is essential.

bioinformatics↗

bioRxiv2019

Optogenetic Modulation of Cortical Neurons Using Organic Light Emitting Diodes (OLEDs)

ObjectiveThere is a need for low power, scalable photoelectronic devices and systems for emerging optogenetic needs in neuromodulation. Conventional light emitting diodes (LEDs) are constrained by power and lead-counts necessary for scalability. Organic LEDs (OLEDs) offer an exciting approach to decrease power and lead-counts while achieving high channel counts on thin, flexible substrates that conform to brain surfaces or peripheral neuronal fibers. In this study, we investigate the potential for using OLEDs to modulate neuronal networks cultured in vitro on a transparent microelectrode array (MEA) and subsequently validate neurostimulation in vivo in a transgenic mouse model.\n\nApproachCultured mouse cortical neurons were transfected with light-sensitive opsins such as blue-light sensitive channel-rhodopsin (ChR2) and green-light sensitive chimeric channel-rhodopsin (C1V1tt) and stimulated using blue and green OLEDs (with 455 and 520 nm peak emission spectra respectively) at a power of 1 mW/mm2 under pulsed conditions.\n\nMain resultsWe demonstrate neuromodulation and optostimulus-locked, single unit-neuronal activity in neurons expressing stimulating and inhibiting opsins (n=4 MEAs, each with 16 recordable channels). We also validated the optostimulus-locked response in a channel-rhodopsin expressing transgenic mouse model, where at least three isolatable single neuronal cortical units respond to OLED stimulation.\n\nSignificanceThe above results indicate the feasibility of generating sufficient luminance from OLEDs to perform neuromodulation both in vitro and in vivo. This opens up the possibility of developing thin, flexible OLED films with multiple stimulation sites that can conform to the shape of the neuronal targets in the brain or the peripheral nervous system. However, stability of these OLEDs under chronic conditions still needs to be carefully assessed with appropriate packaging approaches.

bioengineering↗

bioRxiv2019

Immunogenicity assessment of PRRS polylactic acid glycolic acid DNA vaccine

In order to enhance the immune effect of DNA vaccine, poly(lactide-co-glycolide (PLGA)] microparticles were prepared by solvent evaporation method, and the porcine reproductive and respiratory syndrome (PRRS) DNA vaccine pCI-ORF5 was adsorbed to the porcine reproductive and respiratory syndrome (PRRS) DNA vaccine. The surface of the microparticles was used to detect the amount of DNA adsorbed by PLGA microparticles, in vitro release, and immunogenicity in mice. The results showed that the DNA adsorption capacity of PLGA particles could reach 0.9% within 6h, and the release in vitro was affected by many factors such as CTAB content, PLGA molecular weight, PLGA concentration and internal water phase volume. After immunizing mice with the naked DNA vaccine, PLGA microparticles were found to significantly enhance the humoral and cellular immunity induced by the adsorbed DNA vaccine, indicating that it has a good application prospect as a vector for delivering DNA vaccines.

biochemistry↗

bioRxiv2019

Group B meningococcal outer membrane protein vaccine promote potent anti-viral effect

This report demonstrates a novel method to explore and evaluate the specific humoral/cellular immune response levels and immunoprotective effects of NMB0315 nucleic acid vaccine, recombinant protein vaccine and nucleic acid vaccine + recombinant protein vaccine in combination with mice, and to further explore the effective immunization method for NMB0315 vaccine. This route provides experimental basis. Nucleic acid vaccines [pcDNA3 1(+) / NMB0315] and recombinant protein vaccines (pET 30a / NMB0315) were prepared in large quantities, and immunologically or separately immunized female BALB/c mice were determined by nucleic acid priming protein boosting method. The specific humoral/cell immune response level, the in vitro bactericidal titer of immune serum, and the immunoprotective effect of the vaccine on mice infected with group B meningococcus were observed. Serum-specific IgG, IgG1, IgG2a and genital lavage fluids induced by NMB0315 nucleic acid vaccine group (pNMB0315 CpG), protein vaccine group (rNMB0315 FA) and combined immunization group (pNMB0315 CpG+rNMB0315 FA). The specific sIgA level reached the peak in the eighth week, and the A450 values were in vitro, and the in vitro bactericidal antibody titers of the nucleic acid vaccine group, the protein vaccine group and the combined immunization group were 1, 64, 1128, respectively. The immune protection rate of experimental mice were 70%, 95% and 80%, respectively. At 2, 4, 6, and 8 weeks, the ratio of IgG2a / IgG1 in the nucleic acid vaccine group, the recombinant protein vaccine group, and the combined immunization vaccine group was less than 1.

pharmacology and toxicology↗

bioRxiv2019

Host density dependence and environmental factors affecting laurel wilt invasion

Host size, density and distribution, in addition to climate, can affect the likelihood a pathogen will invade and saturate landscapes. Laurel wilt, caused by the vector-borne forest pathogen Raffaelea lauricola, has devastated populations of native Lauraceae in the Southeastern US, and continues to spread. We surveyed 87 plots in six coastal islands in South Carolina, Georgia and North Florida, and one inland site (Archbold Biological Station) in South Florida for laurel wilt-affected and non-affected individual plants belonging to the genus Persea. The coastal island sites were surveyed once in 2008 or 2009, and the inland site was surveyed eight times from 2011 to 2013. Disease incidence per plot ranged from 0% to 96%, with mean disease incidence 45% across all sites. Disease incidence was positively correlated with trunk diameter and density of hosts with trunk diameter > 5 cm, but negatively with the degree of clustering, which was highest for small trees. A recursive partitioning model indicated that higher disease incidence was associated with moderate temperatures, wider trunk diameter, lower relative humidity, and lower wind speeds. Disease progress over time at Archbold followed a Gompertz curve, plateauing at 3% in two years. The dispersal kernel for disease incidence from a focus followed a negative exponential distribution. The number of plots with diseased trees at Archbold was similar for redbay (P. borbonia) and swampbay (P. palustris), but was lower for silkbay (P. humilis). Understanding how host density, size, and diversity interact with environmental effects will help guide future risk prediction efforts.

plant biology↗

bioRxiv2019

Consensus Machine Learning for Gene Target Selection in Pediatric AML Risk

Acute myeloid leukemia (AML) is a cancer of hematopoietic systems that poses high population burden, especially among pediatric populations. AML presents with high molecular heterogeneity, complicating patient risk stratification and treatment planning. While molecular and cytogenetic subtypes of AML are well described, significance of subtype-specific gene expression patterns is poorly understood and effective modeling of these patterns with individual algorithms is challenging. Using a novel consensus machine learning approach, we analyzed public RNA-seq and clinical data from pediatric AML patients (N = 137 patients) enrolled in the TARGET project.\n\nWe used a binary risk classifier (Low vs. Not-Low Risk) to study risk-specific expression patterns in pediatric AML. We applied the following workflow to identify important gene targets from RNA-seq data: (1) Reduce data dimensionality by identification of differentially expressed genes for AML risk (N = 1984 loci); (2) Optimize algorithm hyperparameters for each of 4 algorithm types (lasso, XGBoost, random forest, and SVM); (3) Study ablation test results for penalized methods (lasso and XGBoost); (4) Bootstrap Boruta permutations with a novel consensus importance metric.\n\nWe observed recurrently selected features across hyperparameter optimizations, ablation tests, and Boruta permutation bootstrap iterations, including HOXA9 and putative cofactors including MEIS1. Consensus feature selection from Boruta bootstraps identified a larger gene set than single penalized algorithm runs (lasso or XGBoost), while also including correlated and predictive genes from ablation tests.\n\nWe present a consensus machine learning approach to identify gene targets of likely importance for pediatric AML risk. The approach identified a moderately sized set of recurrent important genes from across 4 algorithm types, including genes identified across ablation tests with penalized algorithms (HOXA9 and MEIS1). Our approach mitigates exclusion biases of penalized algorithms (lasso and XGBoost) while obviating arbitrary importance cutoffs for other types (SVM and random forest). This approach is readily generalizable for research of other heterogeneous diseases, single-assay experiments, and high-dimensional data. Resources and code to recreate our findings are available online.

bioinformatics↗

bioRxiv2019

Multi-walled carbon nanotubes/nano-Ag-TiO2 membrane DNA electrochemical biosensor

A highly sensitive DNA electrochemical biosensor was prepared based on multi-walled carbon nanotube/nano-Ag-TiO2 composite membrane. The Ag-TiO2 composite is mixed with a suitable amount of multi-walled carbon nanotubes (MWNT) dispersed in N,N-dimethylformamide to form a uniform and stable mixed solution, which is applied onto the surface of the bare carbon paste electrode. A MWNT/Ag-TiO2 modified carbon paste electrode was prepared. The large specific surface area and good electron transport properties of carbon nanotubes have a good synergistic effect on the good biocompatibility of Ag-TiO2 nanocomposites and excellent adsorption capacity of DNA, which significantly improves the immobilization and DNA hybridization of DNA probes. Detection sensitivity. The preparation of the sensing membrane and the immobilization and hybridization of DNA were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The exogenous glufosinate acetyltransferase gene fragment of transgenic plants was detected by electrochemical impedance spectroscopy. The linear range was 1. 0 x 10 - 11 [~]1. 0 x 10 - 6 mol / L. The detection limit was 3. 12 x 10 - 12 mol / L.

bioengineering↗

bioRxiv2019

Preparation and optimization of MEPEG-PLGA nanoparticles for gene delivery

This paper demonstrates a method to prepare a cationic methoxy-terminated polyethylene glycol-polylactic acid polyglycolic acid block polymer (MePEG-PLGA) nanoparticle by a nanoparticle precipitation method was established. This study used single factor design and orthogonal experiment to select the optimal experimental scheme and examined the physical properties of the nanoparticles such as surface morphology, particle size distribution, zeta potential, DNA binding rate, and DNA protection ability. Results indicate that the optimal size of the prepared nanoparticles was 89.7 nm and the surface potential was 28.3 mV. The nanoparticles were scattered under transmission electron microscope, the size was uniform, the surface was smooth, and the distribution was spherical. The DNA binding rate was 80.2 %, and can well protect the contained genes from nuclease degradation. Conclusion The cationic nanoparticles prepared by nanoparticle precipitation method are expected to be highly efficient gene carriers. The preparation of cationic methoxy-terminated polyethylene glycol-polylactic acid polyglycolic acid block polymer (MePEG-PLGA) by nanoparticle precipitation method. Nanoparticle method. Method This study used single factor design and orthogonal experiment to select the optimal experimental scheme, and examined the physical properties of the nanoparticles such as surface morphology, particle size distribution, Zeta potential, DNA binding rate, and DNA protection ability. Results The optimal size of the prepared nanoparticles was 89.7 nm and the surface potential was 28.3 mV. The nanoparticles were scattered under transmission electron microscope, the size was uniform, the surface was smooth, and the distribution was spherical. The DNA binding rate was 80.2 %, and can well protect the contained genes from nuclease degradation. Conclusion The cationic nanoparticles prepared by nanoparticle precipitation are expected to be efficient gene carriers.

bioengineering↗

bioRxiv2019

Immunological efficacy of self-assembled nanoparticle anti-mite vaccine

This report demonstrates the effects of self-assembled nanoparticle anti-caries vaccine Glu-FTH and Glu+ Poly(I:C) (in combination with adjuvant Poly(I:C) and antigen Glu) on specific humoral and mucosal immunity in mice. Mice were randomly divided into 6 groups, and Glu-FTH, Glu, Glu-FTH + Poly (I: C), Glu+Poly (I: C), FTH, and PBS were injected into mice via nasal mucosa. Enzyme-linked immunosorbent assay (ELISA) to detect specific antibody levels in serum and saliva. Results indicate that Glu-FTH, Glu, Glu-FTH+Poly(I:C), Glu+Poly(I:C) can effectively increase anti-Glu IgG levels in mouse serum; Glu+Poly(I:C) and Glu It can effectively increase the level of anti-GlusIgA in mouse saliva. Therefore, we demonstrate that Glu-FTH has a certain immune effect. The combination of adjuvant Poly(I:C) and antigen Glu can induce strong immune response.

bioengineering↗