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Biology subjects

Lu, D.

Publications and source records attributed to Lu, D..

103 records · Page 6Linked to original sources

Choice of host cell line is essential for the functional glycosylation of the fragment crystallizable (Fc) region of human IgG1 inhibitors of influenza B viruses

Antibodies are glycoproteins that carry a conserved N-linked carbohydrate attached to the Fc, whose presence and fine structure profoundly impacts on their in vivo immunogenicity, pharmacokinetics and functional attributes. The host cell line used to produce IgG has a major impact on this glycosylation, as different systems express different glycosylation enzymes and transporters that contribute to the specificity and heterogeneity of the final IgG-Fc glycosylation profile. Here we compare two panels of glycan-adapted IgG1-Fc mutants expressed in either the HEK 293-F or CHO-K1 systems. We show that the types of N-linked glycans between matched pairs of Fc mutants vary significantly, and in particular with respect to sialylation. These cell line effects on glycosylation profoundly influence the ability of the engineered Fcs to interact with either human or pathogen receptors. For example, we describe Fc mutants that potently disrupted influenza B-mediated agglutination of human erythrocytes when expressed in CHO-K1 but not in HEK 293-F cells.

immunology↗

Recombinant Expression of Aldehyde Dehydrogenase 2 (ALDH2) in Escherichia coli Nissle 1917 for Oral Delivery in ALDH2-Deficient Individuals

Turning red after consuming alcohol may seem like a mere social inconvenience. Yet, this flushing response is caused by an accumulation of acetaldehyde, a carcinogenic intermediate of alcohol metabolism. Aldehyde dehydrogenase 2 (ALDH2) deficiency, the result of a point mutation, produces a less efficient ALDH2. The resulting accumulation of acetaldehyde greatly increases the risk of developing esophageal and head and neck cancers. In this study, we produced recombinant ALDH2 in the probiotic E. coli Nissle 1917, which successfully reduces acetaldehyde levels in simulated oral conditions. Packaged in a hard candy, the ALDH2-probiotic would remain in the mouth to specifically target salivary acetaldehyde. Using mathematical modeling, we also determined how much recombinant ALDH2 is needed to reduce elevated acetaldehyde levels.\n\nFinancial DisclosureThis work was funded by Taipei American School. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityYes - all data are fully available without restriction. Sequences for the plasmids used in this study are available through the Registry of Standard Biological Parts. Links to raw data are included in Supplementary Information.

synthetic biology↗

Hypothalamic-extended amygdala circuit regulates temporal discounting

Choice behavior is characterized by temporal discounting, i.e., preference for immediate rewards over delayed rewards. Temporal discounting is often dysfunctional in psychiatric disorders, addiction, and eating disorders. However, the underlying neural mechanisms governing temporal discounting are still poorly understood. We found that food deprivation resulted in steep temporal discounting of food rewards, whereas satiation abolished discounting. In addition, optogenetic activation of AgRP-expressing neurons in the arcuate nucleus or their axon terminals in the posterior bed nucleus of stria terminalis (BNST) restored temporal discounting in sated mice. Activation of postsynaptic neuropeptide Y receptors (Y1Rs) within the BNST, which is influenced by neuropeptide released by AgRP neurons, was sufficient to restore temporal discounting. These results demonstrate for the first time a profound effect of motivational signals from hypothalamic feeding circuits on temporal discounting and reveal a novel neural circuit that regulates choice behavior.

neuroscience↗

Epidemiological Analysis of Ear Diseases in 221 Dogs in Northwest of China

Ear disease is a relatively common disease in veterinary, and it will great effect on the pets life. This study mainly collected and collated the cases of Xian Teaching Hospital of Northwest A&F University from 2012 to 2016, and conducted an epidemiological analysis of the incidence of ear disease in dogs. In this study, the common ear diseases in dogs were divided into otitis externa, otitis media, otitis interna, and ear hematoma. The results showed that the total number of dog ear disease cases was 221, the highest incidence was otitis externa (84.62%), and the main cause of otitis externa was the bacterial infection (44.10%), which followed by fungal infection (32.31%). The ratio of male to female is 1:1.5. In terms of the dog species, the highest incidence was Teddy (18.55%), followed by the Golden Retriever (10.41%). The most common ear diseases in puppies was otitis externa, ear canal hyperplasia and ear canal tumors occur mainly in older dogs. Through the analysis of the 221 cases of ear diseases, we could better understand the development and epidemiology of dog ear diseases, and provide some reference for clinical diagnosis, treatment and prevention of dog ear diseases.

epidemiology↗

Limited differential expression of miRNAs and other small RNAs in LPS-stimulated human monocytes

Monocytes are a distinct subset of myeloid cells with diverse functions in early inflammatory immune modulation. While previous studies have surveyed the role of microRNA regulation on different myeloid cell lines and primary cultures, the time-dependent kinetics of inflammatory stimulation on miRNA expression and the relationship between miRNA-to-target-RNA expression have not been comprehensively profiled in monocytes. In this study, we use next-generation sequencing and RT-PCR assays to analyze the non-coding small RNA transcriptome of unstimulated and lipopolysaccharide (LPS)-stimulated monocytes at 6 and 24 hours. We identified a miRNA signature consisting of five mature miRNAs (hsa-mir-146a, hsa-mir-155, hsa-mir-9, hsa-mir-147b, and hsa-mir-193a) upregulated by LPS-stimulated monocytes after 6 hours and found that most miRNAs were also upregulated after 24 hours of stimulation. Only one miRNA gene was down-regulated and no other small RNAs were found dysregulated in monocytes after LPS treatment. In addition, novel tRNA-derived fragments were also discovered in monocytes, although none showed significant changes upon LPS stimulation. Interrogation of validated miRNA targets by transcriptomic analysis revealed that the majority of differential mRNA expression was maintained in LPS-stimulated monocytes although few of miRNA targets seemed to obtain heterogeneous expression pattern along the treatment. Our findings reveal a potential role by which selective miRNA upregulation and stable expression of other small RNAs enable monocytes to develop finely tuned cellular responses during acute inflammation.

genomics↗

Analysing protein post-translational modform regions by linear programming

Post-translational modifications (PTMs) at multiple sites can collectively influence protein function but the scope of such PTM coding has been challenging to determine. The number of potential combinatorial patterns of PTMs on a single molecule increases exponentially with the number of modification sites and a population of molecules exhibits a distribution of such \"modforms\". Estimating these \"modform distributions\" is central to understanding how PTMs influence protein function. Although mass-spectrometry (MS) has made modforms more accessible, we have previously shown that current MS technology cannot recover the modform distribution of heavily modified proteins. However, MS data yield linear equations for modform amounts, which constrain the distribution within a high-dimensional, polyhedral \"modform region\". Here, we show that linear programming (LP) can efficiently determine a range within which each modform value must lie, thereby approximating the modform region. We use this method on simulated data for mitogen-activated protein kinase 1 with the 7 phosphorylations reported on UniProt, giving a modform region in a 128 dimensional space. The exact dimension of the region is determined by the number of linearly independent equations but its size and shape depend on the data. The average modform range, which is a measure of size, reduces when data from bottom-up (BU) MS, in which proteins are first digested into peptides, is combined with data from top-down (TD) MS, in which whole proteins are analysed. Furthermore, when the modform distribution is structured, as might be expected of real distributions, the modform region for BU and TD combined has a more intricate polyhedral shape and is substantially more constrained than that of a random distribution. These results give the first insights into high-dimensional modform regions and confirm that fast LP methods can be used to analyse them. We discuss the problems of using modform regions with real data, when the actual modform distribution will not be known.

systems biology↗

A multi-modal proteomics strategy for characterizing posttranslational modifications of tumor suppressor p53 reveals many sites but few modified forms

Post-translational modifications (PTMs) are found on most proteins, particularly on \"hub\" proteins like the tumor suppressor p53, which has over 100 possible PTM sites. Substantial crosstalk between PTM sites underlies the ability of such proteins to integrate diverse signals and coordinate downstream responses. However, disentangling the combinatorial explosion in global PTM patterns across an entire protein (\"modforms\") has been challenging, as conventional peptide-based mass spectrometry strategies (so-called \"bottom-up\" MS) destroy such global correlations. Alternatively, direct analysis of intact and modified proteins using \"top-down\" MS retains global information. Here, we applied both strategies to recombinant p53 phosphorylated in vitro with Chk1 kinase, which exhibited 41 modified sites by bottom-up MS, but no more than 8 modified sites per molecule detected by top-down MS. This observation that many low-abundance modifications comprise relatively few modforms above a 1% threshold indicates that endogenous p53 PTM complexity may be more definable than previously thought.

systems biology↗

A single cell transcriptomic analysis of human neocortical development

Defining the number, proportion, or lineage of distinct cell types in the developing human brain is an important goal of modern brain research. We defined single cell transcriptomic profiles for 40,000 cells at mid-gestation to identify cell types in the developing human neocortex. We define expression profiles corresponding to all known major cell types at this developmental period and identify multiple transcription factors and co-factors expressed in specific cell types, providing an unprecedented resource for understanding human neocortical development including the first single-cell characterization of human subplate neurons. We characterize major developmental trajectories during early neurogenesis, showing that cell type differentiation occurs on a continuum that involves transitions that tie cell cycle progression with early cell fate decisions. We use these data to deconvolute regulatory networks and map neuropsychiatric disease genes to specific cell types, implicating dysregulation of specific cell types, as the mechanistic underpinnings of several neurodevelopmental disorders. Together these results provide an extensive catalog of cell types in human neocortex and extend our understanding of early cortical development, human brain evolution and the cellular basis of neuropsychiatric disease.\n\nOne Sentence SummaryComprehensive single cell transcriptomes in developing human cortex inform models of cell diversity, differentiation and disease risk.

neuroscience↗

Predicting Growth and Carcass Traits in Swine Using Metagenomic Data and Machine Learning Algorithms

In this paper, we evaluated the power of metagenome measures taken at three time points over the growth test period (weaning, 15 and 22 weeks) to foretell growth and carcass traits in 1039 individuals of a line of crossbred pigs. We measured prediction accuracy as the correlation between actual and predicted phenotypes in a five-fold cross-validation setting. Phenotypic traits measured included live weight measures and carcass composition obtained during the trial as well as at slaughter. We employed a null model excluding microbiome information as a baseline to assess the increase in prediction accuracy stemming from the inclusion of operational taxonomic units (OTU) as predictors. We further contrasted performance of models from the Bayesian alphabet (Bayesian Lasso) as well machine learning approaches (Random Forest and Gradient Boosting) and semi-parametric kernel models (Reproducing Kernel Hilbert space). In most cases, prediction accuracy increased significantly with the inclusion of microbiome data. Accuracy was more substantial with the inclusion of metagenomic information taken at week 15 and 22, with values ranging from approximately 0.30 for loin traits to more than 0.50 for back-fat. Conversely, microbiome composition at weaning resulted in most cases in marginal gains of prediction accuracy, suggesting that later measures might be more useful to include in predictive models. Model choice affected predictions marginally with no clear winner for any model/trait/time point. We, therefore, suggest average prediction across models as a robust strategy in fitting metagenomic information. In conclusion, microbiome composition can effectively be used as a predictor of growth and composition traits, particularly for fatness traits. The inclusion of OTU predictors could potentially be used to promote fast growth of individuals while limiting fat accumulation. Early microbiome measures might not be good predictors of growth and OTU information might be best collected at later life stages. Future research should focus on the inclusion of both microbiome as well as host genome information in predictions, as well as the interaction between the two. Furthermore, the influence of microbiome on feed efficiency as well as carcass and meat quality should be investigated.

genetics↗

Recombinant expression of Proteorhodopsin and biofilm regulators in Escherichia coli for nanoparticle binding and removal in a wastewater treatment model

The small size of nanoparticles is both an advantage and a problem. Their high surface-area-to-volume ratio enables novel medical, industrial, and commercial applications. However, their small size also allows them to evade conventional filtration during water treatment, posing health risks to humans, plants, and aquatic life. This project aims to remove nanoparticles during wastewater treatment using genetically modified Escherichia coli in two ways: 1) binding citrate-capped nanoparticles with the membrane protein Proteorhodopsin, and 2) trapping nanoparticles using Escherichia coli biofilm produced by overexpressing two regulators: OmpR234 and CsgD. We demonstrate experimentally that Escherichia coli expressing Proteorhodopsin binds to 60 nm citrate-capped silver nanoparticles. We also successfully upregulate biofilm production and show that Escherichia coli biofilms are able to trap 30 nm gold particles. Finally, both Proteorhodopsin and biofilm approaches are able to bind and remove nanoparticles in simulated wastewater treatment tanks. We envision integrating our trapping system in both rural and urban wastewater treatment plants to efficiently capture all nanoparticles before treated water is released into the environment.\n\nFinancial DisclosureThis work was funded by the Taipei American School. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityYes - all data are fully available without restriction. Sequences for the plasmids used in this study are available through the Registry of Standard Biological Parts. Links to raw data are included in Supplementary Information.

synthetic biology↗

Unconsciously Implanted Visuoauditory Memory in the Presence of Cholecystokinin Retrieved in Behavioral Contexts

We investigated whether visuoauditory association can be artificially implanted in rodents and then retrieved in a behaviorally relevant context. Rats were trained to approach the left or right hole of a behavioral apparatus to retrieve a reward depending on the side of electrical stimulation of the auditory cortex (EAC) they received and mice were fear-conditioned to EAC. Next, an irrelevant visual stimulus (VS) was repeatedly paired with EAC in the presence of cholecystokinin (CCK) or with activation of terminals of entorhinal CCK neurons in the auditory cortex. In subsequent behavioral testing with VS, rats approached the hole associated with reward availability and mice showed a freezing response to the VS. A CCK antagonist blocked the establishment of visuoauditory association, whereas a CCK agonist rescued the deficit of association. Our findings provide a scientific foundation for \"memory implantation\" and indicate that CCK is the switching chemical for formation of visuoauditory association.

neuroscience↗

Genome-wide Variants of Eurasian Facial Shape Differentiation and a prospective model of DNA based Face Prediction

It is a long standing question as to which genes define the characteristic facial features among different ethnic groups. In this study, we use Uyghurs, an ancient admixed population to query the genetic bases why Europeans and Han Chinese look different. Facial traits were analyzed based on high-dense 3D facial images; numerous biometric spaces were examined for divergent facial features between European and Han Chinese, ranging from inter-landmark distances to dense shape geometrics. Genome-wide association analyses were conducted on a discovery panel of Uyghurs. Six significant loci were identified four of which, rs1868752, rs118078182, rs60159418 at or near UBASH3B, COL23A1, PCDH7 and rs17868256 were replicated in independent cohorts of Uyghurs or Southern Han Chinese. A prospective model was also developed to predict 3D faces based on top GWAS signals, and tested in hypothetic forensic scenarios.

genetics↗

Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation

Both genetic variants and brain region abnormalities are recognized to play a role in cognitive decline. We explore the association between singlenucleotide polymorphisms (SNPs) in linkage regions for Alzheimers disease and rates of decline in brain structure using data from the Alzheimers Disease Neuroimaging Initiative (ADNI).\n\nIn an initial discovery stage, we assessed the presence of linear association between the minor allele counts of 75,845 SNPs in the Alzgene linkage regions and predicted rates of change in structural MRI measurements for 56 brain regions using an RV test. In a second, refinement stage, we reduced the number of SNPs using a bootstrap-enhanced sparse canonical correlation analysis (SCCA) with a fixed tuning parameter. Each SNP was assigned an importance measure proportional to the number of times it was estimated to have a nonzero coefficient in repeated re-sampling from the ADNI-1 sample. We created refined lists of SNPs based on importance probabilities greater than 50% and 90%, respectively. In a third, validation stage, we assessed the multivariate association between these refined lists of SNPs and the rates of structural change in the independent ADNI-2 study dataset.\n\nThere was strong statistical evidence for linear association between the SNPs in the Alzgene linkage regions and the 56 imaging phenotypes in both the ADNI-1 and ADNI-2 samples (p < 0.0001). The bootstrap-enhanced SCCA identified 1,694 priority SNPs with importance probabilities > 50% and 22 SNPs with importance probabilities > 90%. The 1,694 prioritized SNPs in the ADNI-1 data were associated with imaging phenotypes in the ADNI-2 data (p = 0.0021).\n\nThis manuscript presents an analysis that addresses challenges in current imaging genetics studies such as biased sampling designs and highdimensional data with low-signal. Genes corresponding to priority SNPs having the highest contribution in the validation data have previously been implicated or hypothesized to be implicated in AD, including GCLC, IDE, and STAMBP1andFAS. We hypothesize that the effect sizes of the 1,694 SNPs in the priority set are likely small, but further investigation within this set may advance understanding of the missing heritability in late-onset Alzheimers disease. Multivariate analysis; Linkage regions; Imaging genetics; Endophenotypes; Inverse probability weighting; Variable importance probabilities

neuroscience↗