Biology subjects

Huang, R.

Publications and source records attributed to Huang, R..

152 records · Page 9Linked to original sources

bioRxiv2018

A potential role for epigenetic processes in the acclimation response to elevated pCO2 in the model diatom Phaeodactylum tricornutum

Understanding of the molecular responses underpinning diatom responses to ocean acidification is fundamental for predicting how important primary producers will be shaped by the continuous rise in atmospheric CO2. In this study, we have analyzed global transcriptomic changes of the model diatom Phaeodactylum tricornutum following growth for 15 generations in elevated pCO2 by strand-specific RNA sequencing (ssRNA-seq). Our results indicate that no significant effects of elevated pCO2 and associated carbonate chemistry changes on the physiological performance of the cells were observed after 15 generations whereas the expression of genes encoding histones and other genes involved in chromatin structure were significantly down-regulated, while the expression of transposable elements (TEs) and genes encoding histone acetylation enzymes were significantly up-regulated. Furthermore, we identified a series of long non-protein coding RNAs (lncRNAs) specifically responsive to elevated pCO2, suggesting putative regulatory roles for these largely uncharacterized genome components. Taken together, our integrative analyses reveal that epigenetic elements such as TEs, histone modifications and lncRNAs may have important roles in the acclimation of diatoms to elevated pCO2 over short time scales and thus may influence longer term adaptive processes in response to progressive ocean acidification.

microbiology↗

bioRxiv2018

Aerobic removal of microcystin-LR by a novel native effective bacterial community designated as YFMCD4 isolated from Lake Taihu

Microcystins (MCs) are a group of monocyclic heptapeptide hepatotoxins produced by species of cyanobacteria. MC-LR is the most toxic and frequently detected MCs variant in water, which poses a great threat to the natural ecosystem and public health. Its important to seek environment-friendly and cost-efficient methods to remove MC-LR. To investigate the MC-degrading capacities of a novel indigenous bacterial community designated as YFMCD4 and the influence of environmental factors including various temperatures, MC concentrations and pH on the MC-degrading activities, the concentration of MC-LR was measured by high performance liquid chromatography. In addition, the MC-degrading mechanism containing the degradation pathway and products of YFMCD4 was studied using HPLC coupled with an ultra-high resolution LTQ Orbitrap Velos Pro ETD mass spectrometry equipped with electrospray ionization interface. The data showed MC-LR can be removed at the maximum rate of 0.5 {micro}g/(ml{middle dot}h) by YFMCD4 containing Alcaligenes faecalis and Stenotrophomonas acidaminiohila. The MC-degrading rates of YFMCD4 were significantly affected by different temperatures, pH and MC-LR concentrations. Two intermediates of a tetrapeptide and Adda appeared in the degradation process. These results illustrate that the novel bacterial community YFMCD4 can remove MC-LR effectively and completely, which indicates YFMCD4 possesses a significant potential to be used in bioremediation of water bodies contaminated by MC-LR.

ecology↗

bioRxiv2018

Predicting the effects of epidural stimulation to improve hand function in patients with spinal cord injury: An active learning-based solution using dynamic sample weighting

In patients with chronic spinal cord injury (SCI), few therapies are available to improve neurological function. Neuromodulation of the spinal cord with epidural stimulation (EDS) has shown promise enabling the voluntary activation of motor pools caudal to the level of the injury. EDS is performed with multiple electrode arrays in which several stimulation variables such as the frequency, amplitude, and location of the stimulation significantly affect the type and amplitude of motor responses. This paper presents a novel technique to predict the final functionality of a patient with SCI after cervical EDS within a deep learning framework. Additionally, we suggest a committee-based active learning method to reduce the number of clinical experiments required to optimize EDS stimulation variables by exploring the stimulation configuration space more efficiently. We also developed a novel method to dynamically weight the results of different experiments using neural networks to create an optimal estimate of the quantity of interest. The essence of our approach was to use machine learning methods to predict the hand contraction force in a patient with chronic SCI based on different EDS parameters. The accuracy of the prediction of stimulation outcomes was evaluated based on three measurements: mean absolute error, standard deviation, and correlation coefficient. The results show that the proposed method can be used to reliably predict the outcome of cervical EDS on maximum voluntary contraction force of the hand with a prediction error of approximately 15%. This model could allow scientists to establish stimulation parameters more efficiently for SCI patients to produce enhanced motor responses in this novel application.\n\nAuthor SummarySpinal cord injury (SCI) can lead to permanent sensorimotor deficits that have a major impact on quality of life. In patients with a motor complete injury, there is no therapy available to reliably improve motor function. Recently, neuromodulation of the spinal cord with epidural stimulation (EDS) has allowed patients with motor-complete SCI regain voluntary movement below the level of injury in the cervical and thoracic spine. EDS is performed using multi-electrode arrays placed in the dorsal epidural space spanning several spinal segments. There are numerous stimulation parameters that can be modified to produce different effects on motor function. Previously, defining these parameters was based on observation and empiric testing, which are time-consuming and inefficient processes. There is a need for an automated method to predict motor and sensory function based on a given combination of EDS settings. We developed a novel method to predict the gripping function of a patient with SCI undergoing cervical EDS based on a set of stimulation parameters within a deep learning framework. We also addressed a limiting factor in machine learning methods in EDS, which is a general lack of training measurements for the learning model. We proposed a novel active learning method to minimize the number of training measurements required. The model for predicting responses to EDS could be used by scientists and clinicians to efficiently determine a set of stimulation parameters that produce a desired effect on motor function.

neuroscience↗

bioRxiv2018

Gut microbiota density influences host physiology and is shaped by host and microbial factors

To identify factors that regulate gut microbiota density and the impact of varied microbiota density on health, we assayed this fundamental ecosystem property in fecal samples across mammals, human disease, and therapeutic interventions. Physiologic features of the host (carrying capacity) and the fitness of the gut microbiota shape microbiota density. Therapeutic manipulation of microbiota density in mice altered host metabolic and immune homeostasis. In humans, gut microbiota density was reduced in Crohns disease, ulcerative colitis, and ileal pouch-anal anastomosis. The gut microbiota in recurrent Clostridium difficile infection had lower density and reduced fitness that were restored by fecal microbiota transplantation. Understanding the interplay between microbiota and disease in terms of microbiota density, host carrying capacity, and microbiota fitness provide new insights into microbiome structure and microbiome targeted therapeutics.

microbiology↗

bioRxiv2017

An internal sensor detects dietary amino acids and promotes food consumption in Drosophila

Adequate protein intake is crucial for animals. Despite the recent progress in understanding protein hunger and satiety in the fruit fly Drosophila melanogaster, how fruit flies assess prospective dietary protein sources and ensure protein consumption remains elusive. We show here that three specific amino acids, L-glutamate (L-Glu), L-alanine (L-Ala), and L-aspartate (L-Asp), rapidly promote food consumption in fruit flies when present in food. The effect of dietary amino acids to promote food consumption is independent of mating experience and internal nutritional status. Genetic analysis identifies six brain neurons expressing diuretic hormone 44 (DH44) as a sensor of dietary amino acids. DH44+ neurons can be directly activated by these three amino acids, and are both necessary and sufficient for dietary amino acids to promote food consumption. By conducting single cell RNAseq analysis, we also identify an amino acid transporter, CG13248, which is highly expressed in DH44+ neurons and is required for dietary amino acids to promote food consumption. Therefore, these data suggest that dietary amino acids may enter DH44+ neurons via CG13248 and modulate their activity and hence food consumption. Taken together, these data identify an internal amino acid sensor in the fly brain that evaluate food sources post-ingestively and facilitates adequate protein intake.

neuroscience↗

bioRxiv2017

De Novo Annotation And Characterization Of The Translatome With Ribosome Profiling Data

By capturing and sequencing the RNA fragments protected by translating ribosomes, ribosome profiling sketches the landscape of translation at subcodon resolution. We developed a new method, RiboCode, which uses ribosome profiling data to assess the translation of each RNA transcript genome-wide. As shown by multiple tests with simulated data and cell type-specific QTI-seq and mass spectrometry data, RiboCode exhibits superior efficiency, sensitivity, and accuracy for de novo annotation of the translatome, which covers various types of novel ORFs in the previously annotated coding and non-coding regions and overlapping ORFs. Finally, to showcase its application, we applied RiboCode on a published ribosome profiling dataset and assembled the context-dependent translatomes of yeast under normal condition, heat shock, and oxidative stress. Comparisons among these translatomes revealed stress-activated novel upstream and downstream ORFs, some of which are associated with potential translational dysregulations of the main protein coding ORFs in response to the stress signals.

bioinformatics↗

bioRxiv2017

An inducible CRISPR-ON system for controllable gene activation in human pluripotent stem cells

Human pluripotent stem cells (hPSCs) are an important system to study early human development, model human diseases, and develop cell replacement therapies. However, genetic manipulation of hPSCs is challenging and a method to simultaneously activate multiple genomic sites in a controllable manner is sorely needed. Here, we constructed a CRISPR-ON system to efficiently upregulate endogenous genes in hPSCs. A doxycycline (Dox) inducible dCas9-VP64-p65-Rta (dCas9-VPR) transcription activator and a reverse Tet transactivator (rtTA) expression cassette were knocked into the two alleles of the AAVS1 locus to generate an iVPR hESC line. We showed that the dCas9-VPR level could be precisely and reversibly controlled by addition and withdrawal of Dox. Upon transfection of multiplexed gRNA plasmid targeting the NANOG promoter and Dox induction, we were able to control NANOG gene expression from its endogenous locus. Interestingly, an elevated NANOG level did not only promote naive pluripotent gene expression but also enhanced cell survival and clonogenicity, and it enabled integration of hESCs with the inner cell mass (ICM) of mouse blastocysts in vitro. Thus, iVPR cells provide a convenient platform for gene function studies as well as high-throughput screens in hPSCs.

cell biology↗

bioRxiv2017

Structure of a AAA+ unfoldase in the process of unfolding substrate

AAA+ unfoldases are thought to unfold substrate through the central pore of their hexameric structures, but how this process occurs is not known. VAT, the Thermoplasma acidophilum homologue of eukaryotic CDC48/p97, works in conjunction with the proteasome to degrade misfolded or damaged proteins. We show that in the presence of ATP, VAT with its regulatory N-terminal domains removed unfolds other VAT complexes as substrate. We captured images of this transient process by electron cryomicroscopy (cryo-EM) to reveal the structure of the substrate-bound intermediate. Substrate binding breaks the six-fold symmetry of the complex, allowing five of the six VAT subunits to constrict into a tight helix that grips an ~80 [A] stretch of unfolded protein. The structure suggests a processive hand-over-hand unfolding mechanism, where each VAT subunit releases the substrate in turn before re-engaging further along the target protein, thereby unfolding it.

biochemistry↗