Biology subjects

Luo, Y.

Publications and source records attributed to Luo, Y..

29 records · Page 2Linked to original sources

bioRxiv2017

Coordination between discrete Mitotic Arrest Deficient 1 (MAD1) domains is required for efficient mitotic checkpoint signaling

As a sensitive signaling system, the mitotic checkpoint ensures faithful chromosome segregation by delaying anaphase onset when even a single kinetochore is unattached. The key signal amplification reaction for the checkpoint is the conformational conversion of open MAD2 (O-MAD2) into closed MAD2 (C-MAD2). The reaction was suggested to be catalyzed by an unusual catalyst, a MAD1:C-MAD2 tetramer, but how the catalysis is executed and regulated remains elusive. Here we report that in addition to the well-characterized middle region (MIM), both amino- and carboxyl-terminal domains (NTD and CTD) of MAD1 also contribute to the mitotic checkpoint. In contrast to MIM that stably associates with C-MAD2, MAD1-NTD and CTD surprisingly bind to both O-MAD2 and C-MAD2, suggesting their interactions with substrates and products of the O-C conversion. MAD1-NTD also interacts with CTD. MPS1 kinase interacts with and phosphorylates both NTD and CTD. The phosphorylation reduces the NTD:CTD interaction and CTD interaction with MPS1. Mutating CTD phosphorylation sites including Thr716 compromises MAD2 binding and the checkpoint responses. Ser610 and Tyr634 also contribute to the checkpoint. Our results have uncovered previously unknown interactions of MAD1-NTD and CTD with MAD2 conformers and their regulation by MPS1 kinase, providing novel insights into the mitotic checkpoint signaling.

cell biology↗

bioRxiv2017

Cadmium Exposure Increases The Risk Of Juvenile Obesity: A Human And Zebrafish Comparative Study

OBJECTIVEHuman obesity is a complex metabolic disorder disproportionately affecting people of lower socioeconomic strata, and ethnic minorities, especially African Americans and Hispanics. Although genetic predisposition and a positive energy balance are implicated in obesity, these factors alone do not account for the excess prevalence of obesity in lower socioeconomic populations. Therefore, environmental factors, including exposure to pesticides, heavy metals, and other contaminants, are agents widely suspected to have obesogenic activity, and they also are spatially correlated with lower socioeconomic status. Our study investigates the causal relationship between exposure to the heavy metal, cadmium (Cd), and obesity in a cohort of children and a zebrafish model of adipogenesis.\n\nDESIGNAn extensive collection of first trimester maternal blood samples obtained as part of the Newborn Epigenetics Study (NEST) were analyzed for the presence Cd, and these results were cross analyzed with the weight-gain trajectory of the children through age five years. Next, the role of Cd as a potential obesogen was analyzed in an in vivo zebrafish model.\n\nRESULTSOur analysis indicates that the presence of Cd in maternal blood during pregnancy is associated with increased risk of juvenile obesity in the offspring, independent of other variables, including lead (Pb) and smoking status. Our results are recapitulated in a zebrafish model, in which exposure to Cd at levels approximating those observed in the NEST study is associated with increased adiposity.\n\nCONCLUSIONOur findings identify Cd as potential human obesogen. Moreover, these observations are recapitulated in a zebrafish model, suggesting that the underlying mechanisms may be evolutionarily conserved, and that zebrafish may be a valuable model for uncovering pathways leading to Cd-mediated obesity in human populations.

epidemiology↗

bioRxiv2017

Polymodal Allosteric Regulation of Type 1 Serine/Threonine Kinase Receptors via a Conserved Electrostatic Lock

Type 1 Serine/Threonine Kinase Receptors (STKR1) transduce a wide spectrum of biological signals mediated by TGF-{beta} superfamily members. The STKR1 activity is tightly controlled by their regulatory glycine-serine rich (GS) domain adjacent to the kinase domain. Despite decades of studies, it remains unknown how physiological or pathological GS domain modifications are coupled to STKR1 kinase activity. Here, by performing molecular dynamics simulations and free energy calculation of Activin-Like Kinase 2 (ALK2), we found that GS domain phosphorylation, FKBP12 dissociation, and disease mutations all destabilize a D354-R375 salt-bridge, which normally acts as an electrostatic lock to prevent coordination of adenosine triphosphate (ATP) to the catalytic site. We developed a WAFEX-guided principal analysis and unraveled how phosphorylation destabilizes this highly conserved salt-bridge in temporal and physical space. Using current-flow betweenness scores, we identified an allosteric network of residue-residue contacts between the GS domain and the catalytic site that controls the formation and disruption of this salt bridge. Importantly, our novel network analysis approach revealed how certain disease-causing mutations bypass FKBP12-mediated kinase inhibition to produce leaky signaling in the absence of ligand. We further provide experimental evidence that this salt-bridge lock exists in other STKR1s, and acts as a general safety mechanism in STKR1 to prevent pathological leaky signaling. In summary, our study provides a compelling and unifying allosteric activation mechanism in STKR1 kinases that reconciles a large number of experimental studies and sheds light on a novel therapeutic avenue to target disease-related STKR1 mutants.\n\nAUTHOR SUMMARYKinases play central role in essential physiological process and are attractive therapeutic drug targets. One of the important kinase families is Type 1 Serine/Threonine Kinase Receptors (STKR1), which control gene expression in response to extracellular growth factors. The activities of STKR1 are tightly controlled by their regulatory domain, which is distant from the kinase catalytic site. The underlying molecular mechanism is elucidated here. We identified that formation or disruption of a highly conserved charge-charge interaction located near the ATP binding site, mediates the physiological inhibition or activation of STKR1. We find that the stability of this charge-charge interaction is remotely controlled by interactions propagated from the distant regulatory domain. Several disease-causing mutations are located at the regulatory domain. We demonstrate how those mutations bypass these endogenous STKR1 inhibition mechanisms to produce pathological phenotypes. This study provides a general activation mechanism in STKR1 kinases, thus may benefit understanding the molecular mechanism of diseases and drug development.

biophysics↗

bioRxiv2017

Chemical Gating of the Mechanosensitive Piezo1 Channel by Asymmetric Binding of its Agonist Yoda1

Piezo proteins are homotrimeric ion channels that play major roles in normal and pathological mechanotransduction signaling in mammalian organisms. Their pharmacological control hence represents a potential therapeutic avenue. Yoda1, a Piezo1-selective small molecule agonist, is the only known selective Piezo modulator. How Yoda1 selectively interacts with Piezo1 and opens its pore is unknown. Here, by engineering and characterizing chimeras, we identified a minimal region responsible for Yoda1 binding. This region is located at the interface between the pore and the putative mechanosensory domains in each subunit. By characterizing hybrid channels containing Yoda1-insensitive and Yoda1-sensitive monomers, we demonstrate that the presence of only one Yoda1-sensitive Piezo1 subunit is sufficient for chemical activation, implicating that the asymmetric binding of Yoda1 to a single subunit enables channel opening. These findings shed light onto the gating mechanisms of Piezo channels and will pave the way for the rationale design of new Piezo channels modulators.

biochemistry↗

bioRxiv2017

The rumen microbiome: an underexplored resource for novel antimicrobial discovery

Antimicrobial peptides (AMPs) are promising drug candidates to target multi-drug resistant bacteria. The rumen microbiome presents an underexplored resource for the discovery of novel microbial enzymes and metabolites, including AMPs. Using functional screening and computational approaches, we identified 181 potentially novel AMPs from a rumen bacterial metagenome. Here, we show that three of the selected AMPs (Lynronne-1, 2 and 3) were effective against numerous bacterial pathogens, including methicillin resistant Staphylococcus aureus (MRSA). No decrease in MRSA susceptibility was observed after 25 days of sub-lethal exposure to these AMPs. The AMPs bound preferentially to bacterial membrane lipids and induced membrane permeability leading to cytoplasmic leakage. Topical administration of Lynronne-1 (10% w/v) to a mouse model of MRSA wound infection elicited a significant reduction in bacterial counts, which was comparable to treatment with 2% mupirocin ointment. Our findings indicate that the rumen microbiome may provide viable alternative antimicrobials for future therapeutic application.

microbiology↗

bioRxiv2017

Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [≤]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

genetics↗

bioRxiv2017

Metagenomic binning through low density hashing

Bacterial microbiomes of incredible complexity are found throughout the world, from exotic marine locations to the soil in our yards to within our very guts. With recent advances in Next-Generation Sequencing (NGS) technologies, we have vastly greater quantities of microbial genome data, but the nature of environmental samples is such that DNA from different species are mixed together. Here, we present Opal for metagenomic binning, the task of identifying the origin species of DNA sequencing reads. Our Opal method introduces low-density, even-coverage hashing to bioinformatics applications, enabling quick and accurate metagenomic binning. Our tool is up to two orders of magnitude faster than leading alignment-based methods at similar or improved accuracy, allowing computational tractability on large metagenomic datasets. Moreover, on public benchmarks, Opal is substantially more accurate than both alignment-based and alignment-free methods (e.g. on SimHC20.500, Opal achieves 95% F1-score while Kraken and CLARK achieve just 91% and 88%, respectively); this improvement is likely due to the fact that the latter methods cannot handle computationally-costly long-range dependencies, which our even-coverage, low-density fingerprints resolve. Notably, capturing these long-range dependencies drastically improves Opals ability to detect unknown species that share a genus or phylum with known bacteria. Additionally, the family of hash functions Opal uses can be generalized to other sequence analysis tasks that rely on k-mer based methods to encode long-range dependencies.

bioinformatics↗

bioRxiv2017

Generation And Comparative Analysis Of Full-Length Transcriptomes In Sweetpotato And Its Putative Wild Ancestor I. trifida

Sweetpotato [Ipomoea batatas (L.) Lam.] is one of the most important crops in many developing countries and provides a candidate source of bioenergy. However, neither high-quality reference genome nor large-scale full-length cDNA sequences for this outcrossing hexaploid are still lacking, which in turn impedes progress in research studies in sweetpotato functional genomics and molecular breeding. In this study, we apply a combination of second- and third-generation sequencing technologies to sequence full-length transcriptomes in sweetpotato and its putative ancestor I. trifida. In total, we obtained 53,861/51,184 high-quality transcripts, which includes 34,963/33,637 putative full-length cDNA sequences, from sweetpotato/I. trifida. Amongst, we identified 104,540/94,174 open reading frames, 1476/1475 transcription factors, 25,315/27,090 simple sequence repeats, 417/531 long non-coding RNAs out of the sweetpotato/I. trifida dataset. By utilizing public available genomic contigs, we analyzed the gene features (including exon number, exon size, intron number, intron size, exon-intron structure) of 33,119 and 32,793 full-length transcripts in sweetpotato and I. trifida, respectively. Furthermore, comparative analysis between our transcript datasets and other large-scale cDNA datasets from different plant species enables us assessing the quality of public datasets, estimating the genetic similarity across relative species, and surveyed the evolutionary pattern of genes. Overall, our study provided fundamental resources of large-scale full-length transcripts in sweetpotato and its putative ancestor, for the first time, and would facilitate structural, functional and comparative genomics studies in this important crop.

plant biology↗

bioRxiv2017

CAR T Cells Secreting IL18 Augment Antitumor Immunity and Increase T Cell Proliferation and Costimulation

Interleukin 18 (IL18) is known to induce the expression of interferon-{gamma} (IFNG), but its effects on T cell proliferation and costimulation are not completely understood. In this study, we demonstrate that ectopic expression of IL18 in CART cells caused significant T cell proliferation in vitro and in vivo, and enhanced antitumor effects in xenograft models. Moreover, IL18 mediated T cell expansion required neither tumor antigen nor CAR expression, and produced severe GVHD in NSG mice. Furthermore, recombinant IL18 costimulated IFNG secretion and proliferation of anti-CD3 beads treated T cells. Interestingly, IL18 costimulation could expand purified CD4 T cells, but not CD8 T cells. However, CD8 T cells proliferated greater than CD4 T cells in magnitude within bulk T cells, suggesting CD4 help effect was involved. Using CRISPR/Cas9 gene editing, we confirmed that IL18-driven expansion was both TCR and IL18 receptor (IL18R) dependent. Importantly, we demonstrated that TCR-deficient, IL18-expressing CD19 CART cells exhibited remarkable proliferation and persistent antitumor activity against CD19-expressing tumor cells in vivo, without eliciting any detectable GVHD symptom. Finally, we describe APACHE T cells, a novel strategy for coupling IL18 expression in CART cells to antigen stimulation, thereby limiting potential toxicity associated with persistent IL18 production. In sum, our study supports human IL18 as a T cell costimulatory cytokine for fueling CART therapy.

synthetic biology↗

bioRxiv2017

A Network Integration Approach for Drug-Target Interaction Prediction and Computational Drug Repositioning from Heterogeneous Information

The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. Systematic integration of these heterogeneous data not only serves as a promising tool for identifying new drug-target interactions (DTIs), which is an important step in drug development, but also provides a more complete understanding of the molecular mechanisms of drug action. In this work, we integrate diverse drug-related information, including drugs, proteins, diseases and side-effects, together with their interactions, associations or similarities, to construct a heterogeneous network with 12,015 nodes and 1,895,445 edges. We then develop a new computational pipeline, called DTINet, to predict novel drug-target interactions from the constructed heterogeneous network. Specifically, DTINet focuses on learning a low-dimensional vector representation of features for each node, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then predicts the likelihood of a new DTI based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for DTI prediction. Moreover, we have experimentally validated the novel interactions between three drugs and the cyclooxygenase (COX) protein family predicted by DTINet, and demonstrated the new potential applications of these identified COX inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs. The source code of DTINet and the input heterogeneous network data can be downloaded from http://github.com/luoyunan/DTINet.

bioinformatics↗

bioRxiv2016

Genetic overlap between in-scanner head motion and the default network connectivity

The association between in-scanner head motion and intrinsic functional connectivity (iFC) may confound explanations for individual differences in functional connectomics. However, the etiology of the correlation between head motion and iFC has not been established. This study aimed to investigate genetic and environmental contributions on the association between head motion and iFC using a twin dataset (175 same-sex twin pairs, aged 14-23 years, 48% females). After establishing that both head motion and default network iFC are moderately heritable, we found large genetic correlations (-0.52 to -0.73) between head motion and the default network iFCs. Common genes can explain 48% - 61% of the negative phenotypic correlation between the two phenotypes. These results advance our understanding of the relationship between head motion and iFC, and may have profound implications for interpreting individual differences in default network connectivity in clinical research and brain-behavior association.

neuroscience↗