Biology subjects

Lin, C.

Publications and source records attributed to Lin, C..

At least 145 records · Page 8Linked to original sources

bioRxiv2020

Genetics of mouse behavioral and peripheral neural responses to sucrose

Mice of the C57BL/6ByJ (B6) strain have higher consumption of, and stronger peripheral neural responses to, sucrose solution than do mice of the 129P3/J (129) strain. To identify quantitative trait loci (QTLs) responsible for this strain difference and evaluate the contribution of peripheral taste responsiveness to individual differences in sucrose intake, we produced an intercross (F2) of 627 mice, measured their sucrose consumption in two-bottle choice tests, recorded the electrophysiological activity of the chorda tympani nerve elicited by sucrose in a subset of F2 mice, and genotyped the mice with DNA markers distributed in every mouse chromosome. We confirmed a sucrose consumption QTL (Scon2, or Sac) on mouse chromosome (Chr) 4, harboring the Tas1r3 gene, which encodes the sweet taste receptor subunit T1R3 and affects both behavioral and neural responses to sucrose. For sucrose consumption, we also detected five new main-effect QTLs Scon6 (Chr2), Scon7 (Chr5), Scon8 (Chr8), Scon3 (Chr9) and a sex-specific QTL Scon9 (Chr15), and an interacting QTL pair Scon4 (Chr1) and Scon3 (Chr9). No additional QTLs for the taste nerve responses to sucrose were detected besides the previously known one on Chr4 (Scon2). Identification of the causal genes and variants for these sucrose consumption QTLs may point to novel mechanisms beyond peripheral taste sensitivity that could be harnessed to control obesity and diabetes.

animal behavior and cognition↗

bioRxiv2020

A DNA-origami nuclear pore mimic reveals nuclear entry mechanisms of HIV-1 capsid

The capsid of human immunodeficiency virus 1 (HIV-1) plays a pivotal role in viral nuclear import, but the mechanism by which the viral core passages the nuclear pore complex (NPC) is poorly understood. Here, we use DNA-origami mimics of the NPC, termed NuPODs (NucleoPorins Organized by DNA), to reveal the mechanistic underpinnings of HIV-1 capsid nuclear entry. We found that trimeric interface formed via three capsid protein hexamers is targeted by a triple-arginine (RRR) motif but not the canonical phenylalanine-glycine (FG) motif of NUP153. As NUP153 is located on the nuclear face of the NPC, this result implies that the assembled capsid must cross the NPC in vivo. This hypothesis is corroborated by our observations of tubular capsid assemblies penetrating through NUP153 NuPODs. NUP153 prefers to bind highly curved capsid assemblies including those found at the tips of viral cores, thereby facilitating capsid insertion into the NPC. Furthermore, a balance of capsid stabilization by NUP153 and deformation by CPSF6, along with other cellular factors, may allow for the intact capsid to pass NPCs of various sizes. The NuPOD system serves as a unique tool for unraveling the previously elusive mechanisms of nuclear import of HIV-1 and other viruses.

microbiology↗

bioRxiv2020

Receptor tyrosine kinases activate heterotrimeric G proteins via phosphorylation within the interdomain cleft of Gαi

The molecular mechanisms by which receptor tyrosine kinases (RTKs) and heterotrimeric G proteins, two major signaling hubs in eukaryotes, independently relay signals across the plasma membrane have been extensively characterized. How these hubs crosstalk has been a long-standing question, but answers remain elusive. Using linear-ion-trap mass spectrometry in combination with biochemical, cellular, and computational approaches, we unravel a mechanism of activation of heterotrimeric G proteins by RTKs and chart the key steps that mediate such activation. Upon growth factor stimulation, the guanine-nucleotide exchange modulator, GIV, dissociates Gi*{beta}{gamma} trimers, scaffolds monomeric Gi with RTKs, and facilitates the phosphorylation on two tyrosines located within the inter-domain cleft of Gi. Phosphorylation triggers the activation of Gi and inhibits second messengers (cAMP). Tumor-associated mutants reveal how constitutive activation of this pathway impacts cells decision to go vs. grow. These insights define a tyrosine-based G protein signaling paradigm and reveal its importance in eukaryotes. Significance StatementGrowth factors and heterotrimeric G proteins are two of the most widely studied signaling pathways in eukaryotes; their crosstalk shapes some of the most fundamental cellular responses in both health and disease. Although mechanisms by which G protein pathways transactivate growth factor RTKs has been well-defined, how the reverse may happen is less understood. This study defines the key steps and cellular consequences of a fundamental mechanism of signal crosstalk that enables RTKs to transactivate heterotrimeric G protein, Gi. Mutations found in tumors shed light on how derailing this mechanism impacts tumor cell behavior. Thus, findings not only show how cells integrate extracellular signals via pathway crosstalk, but also demonstrate the relevance of this pathway in cancers.

biochemistry↗

bioRxiv2020

RNF219 interacts with CCR4-NOT in regulating stem cell differentiation

Regulation of RNA stability plays a crucial role in gene expression control. Deadenylation is the initial rate-limiting step for the majority of RNA decay events. Here, we show that RING Finger Protein 219 (RNF219) interacts with the CCR4-NOT deadenylase complex. RNF219-CCR4-NOT exhibits deadenylation activity in vitro. RNA-seq analyses identify some of the 2-cell specific genes and the neuronal genes significantly down-regulated upon RNF219 knockdown, while up-regulated after depletion of the CCR4-NOT subunit CNOT10 in mouse embryonic stem (ES) cells. RNF219 depletion leads to impaired neuronal lineage commitment during ES cell differentiation. Our study suggests that RNF219 is a novel interacting partner of CCR4-NOT, and required for maintenance of ES cell pluripotency.View Full Text

molecular biology↗

bioRxiv2020

Calcitriol, the active form of vitamin D, is a promising candidate for COVID-19 prophylaxis

COVID-19, the disease caused by SARS-CoV-2 (1), was declared a pandemic by the World Health Organization (WHO) in March 2020 (2). While awaiting a vaccine, several antivirals are being used to manage the disease with limited success (3, 4). To expand this arsenal, we screened 4 compound libraries: a United States Food and Drug Administration (FDA) approved drug library, an angiotensin converting enzyme-2 (ACE2) targeted compound library, a flavonoid compound library as well as a natural product library. Of the 121 compounds identified with activity against SARS-CoV-2, 7 were shortlisted for validation. We show for the first time that the active form of Vitamin D, calcitriol, exhibits significant potent activity against SARS-CoV-2. This finding paves the way for consideration of host-directed therapies for ring prophylaxis of contacts of SARS-CoV-2 patients.

microbiology↗

bioRxiv2020

Crystal structure of SARS-CoV-2 main protease in complex with a Chinese herb inhibitor shikonin

Main protease (Mpro, also known as 3CLpro) has a major role in the replication of coronavirus life cycle and is one of the most important drug targets for anticoronavirus agents. Here we report the crystal structure of main protease of SARS-CoV-2 bound to a previously identified Chinese herb inhibitor shikonin at 2.45 angstrom resolution. Although the structure revealed here shares similar overall structure with other published structures, there are several key differences which highlight potential features that could be exploited. The catalytic dyad His41-Cys145 undergoes dramatic conformational changes, and the structure reveals an unusual arrangement of oxyanion loop stabilized by the substrate. Binding to shikonin and binding of covalent inhibitors show different binding modes, suggesting a diversity in inhibitor binding. As we learn more about different binding modes and their structure-function relationships, it is probable that we can design more effective and specific drugs with high potency that can serve as effect SARS-CoV-2 anti-viral agents.

biophysics↗

bioRxiv2020

Inhibition of CAMKK2 impairs autophagy and castration-resistant prostate cancer via suppression of AMPK-ULK1 signaling

Previous work has suggested androgen receptor (AR) signaling mediates cancer progression in part through the modulation of autophagy. Accordingly, we demonstrate that chloroquine, an inhibitor of autophagy, can inhibit tumor growth in preclinical mouse models of castration-resistant prostate cancer (CRPC). However, clinical trials testing chloroquine derivatives in men with CRPC have yet to yield promising results, potentially due to side effects. We hypothesized that identification of the upstream activators of autophagy in prostate cancer could highlight alternative, context-dependent targets for blocking this important cellular process during disease progression. Here, we used molecular (inducible overexpression and shRNA-mediated knockdown), genetic (CRISPR/Cas9), and pharmacological approaches to elucidate an AR-mediated autophagy cascade involving Ca2+/calmodulin-dependent protein kinase kinase 2 (CAMKK2; a kinase with a restricted expression profile), 5-AMP-activated protein kinase (AMPK) and Unc-51 like autophagy activating kinase 1 (ULK1). These findings are consistent with data indicating CAMKK2-AMPK-ULK1 signaling correlates with disease progression in genetic mouse models and patient tumor samples. Importantly, CAMKK2 disruption impaired tumor growth and prolonged survival in multiple CRPC preclinical mouse models. Finally, we demonstrate that, similar to CAMKK2 inhibition, a recently described inhibitor of AMPK-ULK1 signaling blocked autophagy, cell growth and colony formation in prostate cancer cells. Taken together, our findings converge to demonstrate that AR signaling can co-opt the CAMKK2-AMPK-ULK1 signaling cascade to promote prostate cancer by increasing autophagy. Further, we propose that an inhibitor of this signaling cascade could serve as an alternative, more specific therapeutic compared to existing inhibitors of autophagy that, to date, have demonstrated limited efficacy in clinical trials due to their toxicity and poor pharmacokinetics.

cancer biology↗

bioRxiv2020

Structure of SARS-CoV-2 main protease in the apo state reveals the inactive conformation

Mpro is of considerable interest as a drug target in the treatment of COVID-19 since the proteolytic activity of this viral protease is essential for viral replication. Here we report the first insight of the structure Mpro for SARS-CoV-2 in the inactive conformation under conditions close to the physiological state (pH 7.5) to an overall resolution of 1.9 [A]. The comparisons of Mpro in different states reveal that substrate binding site and the active site are more flexible in the inactive conformation than that in the active conformations. Notably, compared with the active conformation of the apo state structure in pH7.6 of SARS, the SARS-CoV-2 apo state is in the inactive conformation under condition close to physiological state (pH7.5). Two water molecules are present in the oxyanion hole in our apo state structure, whereas in the ligand-bound structure, water molecular is absence in the same region. This structure provides novel and important insights that have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational, structure-based, approaches for the design of specific SARS-CoV-2 ligands as new therapeutic agents.

biochemistry↗

bioRxiv2020

Genome mapping resolves structural variation within segmental duplications associated with microdeletion/microduplication syndromes

Segmental duplications (SDs) are a class of long, repetitive DNA elements whose paralogs share a high level of sequence similarity with each other. SDs mediate chromosomal rearrangements that lead to structural variation in the general population as well as genomic disorders associated with multiple congenital anomalies, including the 7q11.23 (Williams-Beuren Syndrome, WBS), 15q13.3, and 16p12.2 microdeletion syndromes. These three genomic regions, and the SDs within them, have been previously analyzed in a small number of individuals. However, population-level studies have been lacking because most techniques used for analyzing these complex regions are both labor- and cost-intensive. In this study, we present a high-throughput technique to genotype complex structural variation using a single molecule, long-range optical mapping approach. We identified novel structural variants (SVs) at 7q11.23, 15q13.3 and 16p12.2 using optical mapping data from 154 phenotypically normal individuals from 26 populations comprising 5 super-populations. We detected several novel SVs for each locus, some of which had significantly different prevalence between populations. Additionally, we refined the microdeletion breakpoints located within complex SDs in two patients with WBS, one patient with 15q13.3, and one patient with 16p12.2 microdeletion syndromes. The population-level data presented here highlights the extreme diversity of large and complex SVs within SD-containing regions. The approach we outline will greatly facilitate the investigation of the role of inter-SD structural variation as a driver of chromosomal rearrangements and genomic disorders.

genomics↗

bioRxiv2020

Fluorogenic probe for fast 3D whole-cell DNA-PAINT

DNA-PAINT is an increasingly popular super-resolution microscopy method that can acquire high-fidelity images at nanometer resolution. It suffers, however, from high background and very slow imaging speed, both of which can be attributed to the presence of unbound fluorophores in solution. We present a fluorogenic DNA-PAINT probe that solves these problems and demonstrate 3D imaging without the need for optical sectioning and a 26-fold increase in imaging speed over regular DNA-PAINT.

biophysics↗

bioRxiv2020

Control of ribosomal protein synthesis by Microprocessor complex

Ribosome biogenesis in eukaryotes requires stoichiometric production and assembly of 80 ribosomal proteins (RPs) and 4 ribosomal RNAs, and its rate must be coordinated with cellular growth. The indispensable regulator of RP biosynthesis is the 5-terminal oligopyrimidine (TOP) motif, spanning the transcription start site of all RP genes. Here we show that the Microprocessor complex, previously linked to the first step of processing microRNAs (miRNAs), coregulates RP expression by binding the TOP motif of nascent RP mRNAs and stimulating transcription elongation via resolution of DNA/RNA hybrids. Cell growth arrest triggers nuclear export and degradation of the Microprocessor protein Drosha by the E3 ubiquitin ligase Nedd4, accumulation of DNA/RNA hybrids at RP gene loci, decreased RP synthesis, and ribosome deficiency, hence synchronizing ribosome production with cell growth. Conditional deletion of Drosha in erythroid progenitors phenocopies human ribosomopathies, in which ribosomal insufficiency leads to anemia. Outlining a miRNA-independent role of the Microprocessor complex at the interphase between cell growth and ribosome biogenesis offers a new paradigm by which cells alter their protein biosynthetic capacity and cellular metabolism.

molecular biology↗

bioRxiv2020

Rapid and quantitative detection of COVID-19 markers in micro-liter sized samples

COVID-19 pandemic has caused tens of thousands of deaths and is now a severe threat to global health. Clinical practice has demonstrated that the SARS-CoV-2 S1 specific antibodies and viral antigens can be used as diagnostic and prognostic markers of COVID-19. However, the popular point-of-care biomarker detection technologies, such as the lateral-flow test strips, provide only yes/no information and have very limited sensitivities. Thus, it has a high false negative rate and cannot be used for the quantitative evaluation of patients immune response. Conventional ELISA (enzyme-linked immunosorbent assay), on the other hand, can provide quantitative, accurate, and sensitive results, but it involves complicated and expensive instruments and long assay time. In addition, samples need to be sent to centralized labs, which significantly increases the turn-around time. Here, we present a microfluidic ELISA technology for rapid (15-20 minutes), quantitative, sensitive detection of SARS-CoV-2 biomarkers using SARS-CoV-2 specific IgG and viral antigen - S protein in serum. We also characterized various humanized monoclonal IgG, and identified a candidate with a high binding affinity towards SARS-CoV-2 S1 protein that can serve as the calibration standard of anti-SARS-CoV-2 S1 IgG in serological analyses. Furthermore, we demonstrated that our microfluidic ELISA platform can be used for rapid affinity evaluation of monoclonal anti-S1 antibodies. The microfluidic ELISA device is highly portable and requires less than 10 L of samples for each channel. Therefore, our technology will greatly facilitate rapid and quantitative analysis of COVID-19 patients and vaccine recipients at point-of-care.

bioengineering↗

bioRxiv2020

Identification of the associated expression patterns as potential predictive markers for cancer prognosis

Dysregulated gene expression can develop as a consequence of uncontrolled alterations of tumor cells. Analysis of these abnormal alterations will improve our understanding of the tumor development and reveal the corresponding clinical associations. It is well known that multiple genetic abnormalities could be observed in the same tumor, however, the interactions between those abnormal events are rarely analyzed. To address this problem, we constructed a novel gene expression correlation network by integrating the transcriptomes of 5,001 cancer patients from 22 cancer types. We investigated how the change of associated expression pattern (AEP), which describe certain associations between gene expression, could affect the cancer patients prognosis. Consequently, we identified an AEP composed of mitosis-related gene expressions, which is significantly correlated with overall survival in most cancer types. In particular, the AEPs could present the association between gene expressions and show distinct effects on prognosis prediction for cancer patients, suggesting that AEP analysis is indispensable to uncover the complex interactions of abnormal gene expressions in tumor development.

bioinformatics↗

bioRxiv2020

Sorting liposomes of distinct sizes by DNA-brick assisted centrifugation

The "tiny bubbles of fluid" wrapped by lipid-bilayer membranes, termed vesicles, are abundant in cells and extracellular space, performing critical tasks including nutrient uptake, cargo transport, and waste confinement. Vesicles on different missions and transport routes are often distinct both in size and in chemical composition, which confers specificity to their interactions with other membranous compartments. Therefore, to accurately recapitulate the vesicles structure and behavior, it is important to use homogeneous liposomes (vesicles made of synthetic components) with precisely defined attributes as model membranes. Although existing methods can generate liposomes of selected sizes with reasonable homogeneity, the scalable production of uniformly-sized liposomes across a wide range of dimensions and compositions remains challenging. Here we report a streamlined, high-throughput sorting technique that uses cholesterol-modified "nanobricks" made of a few DNA oligonucleotides to differentiate hetero-sized liposomes by their buoyant densities. After DNA-brick coating, milligrams of liposomes of different origins (e.g., produced via extrusion or sonication, and reconstituted with membrane proteins) can be separated by centrifugation into six to eight homogeneous populations with mean diameters from 30 to 130 nm. In proof of concept experiments, we show that these uniform, leak-free liposomes are ideal substrates to study, with an unprecedented resolution, how membrane curvature influences the activity of peripheral (ATG3) and integral (SNARE) membrane proteins. We anticipate that our sorting technique will facilitate the quantitative understanding of membrane curvature in vesicular transport. Furthermore, adding a facile and standardized separation step to the conventional liposome preparation pipeline may benefit the formulation and prototyping of liposomal drug-carrying vehicles.

biophysics↗

bioRxiv2020

Studies of human twins reveal genetic variation that affects dietary fat perception

To learn more about the mechanisms of human dietary fat perception, 398 human twins rated fattiness and liking for six types of potato chips that differed in triglyceride content (2.5, 5, 10, and 15% corn oil); reliability estimates were obtained from a subset (n = 50) who did the task twice. Some chips also had a saturated long-chain fatty acid (hexadecanoic acid, 16:0) added (0.2%) to evaluate its effect on fattiness and liking. We computed the heritability of these measures and conducted a genome-wide association study (GWAS) to identify regions of the genome that co-segregate with fattiness and liking. Perceived fattiness and liking for the potato chips were reliable (r = 0.31-0.62, p < 0.05) and heritable (up to h2 = 0.29, p < 0.001, for liking). Adding hexadecanoic acid to the potato chips significantly increased ratings of fattiness but decreased liking. Twins with the G allele of rs263429 near GATA3-AS1 or the G allele of rs8103990 within ZNF729 reported more liking for potato chips than did twins with the other allele (multivariate GWAS, p < 1x10-5), with results reaching genome-wide suggestive but not significance criteria. Person-to-person variation in the perception and liking of dietary fat was (a) negatively affected by the addition of a saturated fatty acid and (b) related to inborn genetic variants. These data suggest liking for dietary fat is not due solely to fatty acid content and highlight new candidate genes and proteins within this sensory pathway.

genetics↗

bioRxiv2019

No strong evidence that social network index is associated with gray matter volume from a data-driven investigation

Recent studies in adult humans have reported correlations between individual differences in peoples Social Network Index (SNI) and gray matter volume (GMV) across multiple regions of the brain. However, the cortical and subcortical loci identified are inconsistent across studies. These discrepancies might arise because different regions of interest were hypothesized and tested in different studies without controlling for multiple comparisons, and/or from insufficiently large sample sizes to fully protect against statistically unreliable findings. Here we took a data-driven approach in a pre-registered study to comprehensively investigate the relationship between SNI and GMV in every cortical and subcortical region, using three predictive modeling frameworks. We also included psychological predictors such as cognitive and emotional intelligence, personality, and mood. In a sample of healthy adults (n = 92), neither multivariate frameworks (e.g., ridge regression with cross-validation) nor univariate frameworks (e.g., univariate linear regression with cross-validation) showed a significant association between SNI and any GMV or psychological feature after multiple comparison corrections (all R-squared values [≤] 0.1). These results emphasize the importance of large sample sizes and hypothesis-driven studies to derive statistically reliable conclusions, and suggest that future meta-analyses will be needed to more accurately estimate the true effect sizes in this field.

neuroscience↗

bioRxiv2019

Integrating ensemble systems biology feature selection and bimodal deep neural network for breast cancer prognosis prediction

MotivationBreast cancer is a heterogeneous disease. In order to guide proper treatment decisions for each individual patient, there is an urgent need for robust prognostic biomarkers that allow reliable prognosis prediction. Gene feature selection on microarray data is an approach to systematically discover potential biomarkers. However, common pure-statistical feature selection approaches often fail to incorporate prior biological knowledge and thus tend to select genes that lack biological insights. In addition, due to the high dimensionality and low sample size properties of microarray data, selecting robust gene features is an intrinsically challenging problem. We therefore combined systems biology feature selection with ensemble learning in this study, aiming to address the above challenges and select genes with biological insights, as well as robust prognostic predictive power. Moreover, in order to capture the complex molecular processes of breast cancer, where multiple disease-contributing genes may exist and interact, we adopted a multi-gene approach to predict the prognosis status using machine learning classifiers.\n\nResultsWe systematically evaluated three different ensemble approaches that all improved the original systems biology feature selector. We found that compared to the most popular data-perturbation approach, function perturbation can produce significant improvement with just a few ensembles. Among all, the hybrid ensemble approach led to the most robust feature selection result, and the identified genes were shown to be highly involved in pathways, such as ubiquitination and cell cycle. Final prognosis prediction models were constructed using the identified genes and clinical information as input features. Among all models, bimodal deep neural network (DNN) achieved the highest AUC (area under receiver operating characteristic curve) in test performance evaluation, where subsequent survival analysis also verified its ability to differentiate patients with different prognosis statuses. In summary, the study demonstrated the potential of ensemble learning to improve gene feature selection robustness, as well as the potential of bimodal DNN in providing reliable prognosis prediction and guiding precision medicine.

bioinformatics↗

bioRxiv2019

Single-cell time-series mapping of cell fate trajectories reveals an expanded developmental potential for human PSC-derived distal lung progenitors

Alveolar epithelial type 2 cells (AEC2s) are the facultative progenitors responsible for maintaining lung alveoli throughout life, yet are difficult to access from patients for biomedical research or lung regeneration applications. Here we engineer AEC2s from human induced pluripotent stem cells (iPSCs) in vitro and use single cell RNA sequencing (scRNA-seq) to profile the detailed kinetics of their differentiation over time. We focus on both the desired target cells as well as those that appear to diverge to alternative endodermal fates. By combining scRNA-seq with lentiviral barcoding to trace differentiating clones, we reveal the bifurcating cell fate trajectories followed as primordial lung progenitors differentiate into mature AEC2s. We define the global transcriptomic signatures of primary developing human AEC2s from fetal through adult stages in order to identify the subset of in vitro differentiating cells that appear to recapitulate the path of in vivo development. In addition, we develop computational methods based on Continuous State Hidden Markov Models (CSHMM) to identify the precise timing and type of signals, such as over-exuberant Wnt responses, that induce some early multipotent NKX2-1+ progenitors to lose lung fate as they clonally diverge into a variety of non-lung endodermal lineages. Finally, we find that this initial developmental plasticity is regulatable via Wnt modulation, and subsides over time, ultimately resulting in iPSC-derived AEC2s that exhibit a stable phenotype and nearly limitless self-renewal capacity in vitro. Our methods and computational approaches can be widely applied to study and control directed differentiation, producing an inexhaustible supply of mature lineages, exemplified here by the generation of AEC2s.

developmental biology↗