Biology subjects

Tan, C.

Publications and source records attributed to Tan, C..

103 records · Page 6Linked to original sources

bioRxiv2019

Phosphoprotein-based Biomarkers as Predictors for Cancer Therapy

Disparities in cancer patient responses have prompted widespread searches to identify differences in sensitive vs. non-sensitive populations and form the basis of personalized medicine. This customized approach is dependent upon the development of pathway-specific therapeutics in conjunction with biomarkers that predict patient responses. Here, we show that Cdk5 drives growth in subgroups of human patients with multiple types of neuroendocrine neoplasms. Phosphoproteomics and high throughput screening identified novel phosphorylation sites downstream of Cdk5. These phosphorylation events serve as biomarkers of Cdk5 activity and effectively pinpoint Cdk5-driven tumors. Toward achieving targeted therapy, we demonstrate that mouse models of neuroendocrine cancer are responsive to selective Cdk5 inhibitors and biomimetic nanoparticles are effective vehicles for enhanced tumor targeting and reduction of drug toxicity. Finally, we show that biomarkers of Cdk5-dependent tumors effectively predict response to anti-Cdk5 therapy in patient-derived xenografts. Thus, a phosphoprotein-based diagnostic assay combined with Cdk5-targeted therapy is a rational treatment approach for neuroendocrine malignancies.

cancer biology↗

bioRxiv2019

Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia

Active retrotransposons in the human genome (L1, Alu and SVA elements) can create genomic mobile element insertions (MEIs) in both germline and somatic tissue1. Specific somatic MEIs have been detected at high levels in human cancers2, and at lower to medium levels in human brains3. Dysregulation of somatic retrotransposition in the human brain has been hypothesized to contribute to neuropsychiatric diseases4, 5. However, individual somatic MEIs are present in small proportions of cells at a given anatomical location, and thus standard whole-genome sequencing (WGS) presents a difficult signal-to-noise problem, while single-cell approaches suffer from limited scalability and experimental artifacts introduced by enzymatic whole-genome amplification6. Previous studies produced widely differing estimates for the somatic retrotransposition rates in human brain3, 6-8. Here, we present a highly precise machine learning method (RetroSom) to directly identify somatic L1 and Alu insertions in <1% cells from 200x deep WGS, which allows circumventing the restrictions of whole-genome amplification. Using RetroSom we confirmed a lower rate of retrotransposition for individual somatic L1 insertions in human neurons. We discovered that anatomical distribution of somatic L1 insertion is as widespread in glia as in neurons, and across both hemispheres of the brain, indicating retrotransposition occurs during early embryogenesis. We characterized two of the detected brain-specific L1 insertions in great detail in neurons and glia from a donor with schizophrenia. Both insertions are within introns of genes active in brain (CNNM2, FRMD4A) in regions with multiple genetic associations with neuropsychiatric disorders9-11. Gene expression was significantly reduced by both somatic insertions in a reporter assay. Our results provide novel insights into the potential for pathological effects of somatic retrotransposition in the human brain, now including the large glial fraction. RetroSom has broad applicability in all disease states where somatic retrotransposition is expected to play a role, such as autoimmune disorders and cancer.

bioinformatics↗

bioRxiv2019

Role of Water Mediated Interactions in Calcium-Coupled Allostery of Calmodulin Domains

Allosteric communication between distant parts of proteins controls many cellular functions, in which metal ions are widely utilized as effectors to trigger the allosteric cascade. Due to the involvement of strong coordination interactions, the energy landscape dictating the metal ion binding is intrinsically rugged. How metal ions achieve fast binding by overcoming the landscape ruggedness and thereby efficiently mediate protein allostery is elusive. By performing molecular dynamics simulations for the Ca2+ binding mediated allostery of the calmodulin (CaM) domains, each containing two Ca2+ binding helix-loop-helix motifs (EF-hands), we revealed the key role of water-bridged interactions in Ca2+ binding and protein allostery. The bridging water molecules between Ca2+ and binding residue reduces the ruggedness of ligand exchange landscape by acting as a lubricant, facilitating the Ca2+ coupled protein allostery. Calcium-induced rotation of the helices in the EF-hands, with the hydrophobic core serving as the pivot, leads to exposure of hydrophobic sites for target binding. Intriguingly, despite being structurally similar, the response of the two symmetrically arranged EF-hands upon Ca2+ binding is asymmetric. Breakage of symmetry is needed for efficient allosteric communication between the EF-hands. The key roles that water molecules play in driving allosteric transitions are likely to be general in other metal ion mediated protein allostery.

biochemistry↗

bioRxiv2019

Assessing nasal obstruction with the nasal acoustic device: a pilot study on distinguishing between subjects with and without chronic rhinosinusitis

This article aims to demonstrate the concept and potential of a novel diagnostic device - the nasal acoustic device (NAD), which captures the nasal breathing sounds over the ala on both sides of the nose. Using the newly defined inspiratory nasal acoustic score (INA score), the unique characteristics of the nasal breathing sounds can be quantified and used for diagnostic purposes.\n\nIn this pilot study, the NAD was compared with the well-established nasal inspiratory peak flow meter (NIPF) to try to distinguish between subjects with and without chronic rhinosinusitis (CRS). Measurements were made before and after nasal decongestants, which were applied to eliminate the nasal cycle. Patients were divided into two groups based on the presence or absence of CRS, irrespective of other pathological conditions being present.\n\nBased on the post-decongestant measurements, the sensitivity/specificity in distinguishing subjects who have CRS (n=11) from subjects who do not (n=29; of whom 13 were controls) were 70%/66% for the NIPF and 82%/79% for the NAD. The non-CRS groups showed statistically significant changes after decongestant for both methods, but the CRS group did not. The results firstly demonstrated that the CRS subjects in this cohort tended to be less responsive to decongestant and therefore the post-decongestant NIPF measurements provided a certain degree of diagnostic value in identifying CRS subjects, but it would appear the NAD better captured the unique sounds associated with CRS, providing a superior diagnostic capability. This study also demonstrates that the NAD can measure the improvement in the nasal airway following treatment effect.

bioengineering↗

bioRxiv2019

A methodology for morphological feature extraction and unsupervised cell classification

Cell morphology is an important indicator of cell state, function, stage of development, and fate in both normal and pathological conditions. Cell shape is among key indicators used by pathologists to identify abnormalities or malignancies. With rapid advancements in the speed and amount of biological data acquisition, including images and movies of cells, computer-assisted identification and analysis of images becomes essential. Here, we report on techniques for recognition of cells in microscopic images and automated cell shape classification. We illustrate how our unsupervised machine-learning-based approach can be used to classify distinct cell shapes from a large number of microscopic images.\n\nTechnical AbstractWe develop a methodology to segment cells from microscopy images and compute quantitative descriptors that characterize their morphology. Using unsupervised techniques for dimensionality reduction and density-based clustering, we perform label-free cell shape classification. Cells are identified with minimal user input using mathematical morphology and region-growing segmentation methods. Physical quantities describing cell shape and size (including area, perimeter, Feret diameters, etc.) are computed along with other features including shape factors and Hus image moments.\n\nCorrelated features are combined to obtain a low-dimensional (2-D or 3-D) embedding of data points corresponding to individual segmented cell shapes. Finally, a hierarchical density-based clustering algorithm (HDBSCAN) is used to classify cells. We compare cell classification results obtained from different combinations of features to identify a feature set that delivers optimum classification performance for our test data consisting of phase-contrast microscopy images of a pancreatic-cancer cell line, MIA PaCa-2.

bioinformatics↗

bioRxiv2019

Targeted sequencing of candidate genes of dyslipidemia in Punjabi Sikhs: Population-specific rare variants in GCKR promote ectopic fat deposition

Dyslipidemia is a well-established risk factor for cardiovascular diseases. Although, advances in genome-wide technologies have enabled the discovery of hundreds of genes associated with blood lipid phenotypes, most of the heritability remains unexplained. Here we performed targeted resequencing of 13 bona fide candidate genes of dyslipidemia to identify the underlying biological functions. We sequenced 940 Sikh subjects with extreme serum levels of hypertriglyceridemia (HTG) and 2,355 subjects were used for replication studies; all 3,295 participants were part of the Asian Indians Diabetic Heart Study. Gene-centric analysis revealed a burden of variants for increasing HTG risk in GCKR (p=2.1x10-5), LPL (p=1.6x10-3) and MLXIPL (p=1.6x10-2) genes. Of these, three missense and damaging variants within GCKR were further examined for functional consequences in vivo using a transgenic zebrafish model. All three mutations were South Asian population-specific and were largely absent in other multiethnic populations of the Exome Aggregation Consortium. We built different transgenic models of human GCKR with and without mutations and analyzed the effects of dietary changes in vivo. Despite the short-term feeding, profound phenotypic changes were apparent in hepatocyte histology and fat deposition associated with increased expression of GCKR in response to a high fat diet (HFD). Liver histology of the GCKRmut showed severe fatty metamorphosis which correlated with ~7 fold increase in the mRNA expression in the GCKRmut fish even in the absence of a high fat diet. These findings suggest that functionally disruptive GCKR variants not only increase the risk of HTG but may enhance ectopic lipid/fat storage defects in the absence of obesity and HFD. To our knowledge, this is the first transgenic zebrafish model of a putative human disease gene built to accurately assess the influence of rare genetic changes and their phenotypic consequences in vivo.

genetics↗

bioRxiv2018

Gut microbiome of an unindustrialized population have characteristic enrichment of SNPs in species and functions with the succession of seasons

Most studies investigating human gut microbiome dynamics are conducted in modern populations. However, unindustrialized populations are arguably better subjects in answering human-gut microbiome coevolution questions due to their lower exposure to antibiotics and higher dependence on natural resources. Hadza hunter-gatherers in Tanzania have been found to exhibit high biodiversity and seasonal patterns in their gut microbiome composition at family level, where some taxa disappear in one season and reappear at later time. However, such seasonal changes have previously been profiled only according to species abundances, with genome-level variant dynamics unexplored. As a result it is still elusive how microbial communities change at the genome-level under environmental pressures caused by seasonal changes. Here, a strain-level SNP analysis of Hadza gut metagenome is performed for 40 Hadza fecal samples collected in three seasons. First, we benchmarked three SNP calling tools based on simulated sequencing reads, and selected VarScan2 that has highest accuracy and sensitivity after a filtering step. Second, we applied VarScan2 on Hadza gut microbiome, with results showing that: with more SNP presented in wet season in general, eight prevalent species have significant SNP enrichments in wet season of which only three species have relatively high abundances. This indicates that SNP characteristics are independent of species abundances, and provides us a unique lens towards microbial community dynamics. Finally, we identify 83 genes with the most characteristic SNP distributions between wet season and dry season. Many of these genes are from Ruminococcus obeum, and mainly from metabolic pathways like carbon metabolism, pyruvate metabolism and glycolysis, as shown by KEGG annotation. This implies that the seasonal changes might indirectly impact the mutational patterns for specific species and functions for gut microbiome of an unindustrialized population, indicating the role of these variants in their adaptation to the changing environment and diets.\n\nImportanceBy analyzing the changes of SNP enrichments in different seasons, we have found that SNP characteristics are independent of species abundances, and could provide us a unique lens towards microbial community dynamics at the genomic level. Many of the genes in microbiome also presented characteristic SNP distributions between wet season and dry season, indicating the role of variants in specific species in their adaptation to the changing environment for an unindustrialized population.

microbiology↗

bioRxiv2018

A robust image registration interface for large volume brain atlas

Mapping the brain structures in three-dimensional accurately is critical for an in-depth understanding of the brain functions. By using the brain atlas as a hub, mapping detected datasets into a standard brain space enables efficiently use of various datasets. However, because of the heterogeneous and non-uniform characteristics of the brain structures at cellular level brought with the recently developed high-resolution whole-brain microscopes, traditional registration methods are difficult to apply to the robust mapping of various large volume datasets. Here, we proposed a robust Brain Spatial Mapping Interface (BrainsMapi) to address the registration of large volume datasets at cellular level by introducing the extract regional features of the anatomically invariant method and a strategy of parameter acquisition and large volume transformation. By performing validation on model data and biological images, BrainsMapi can not only achieve robust registration on sample tearing and streak image datasets, different individual and modality datasets accurately, but also are able to complete the registration of large volume dataset at cellular level which dataset size reaches 20 TB. Besides, it can also complete the registration of historical vectorized dataset. BrainsMapi would facilitate the comparison, reuse and integration of a variety of brain datasets.

neuroscience↗

bioRxiv2018

A capsular polysaccharide-expressing live vaccine suppresses streptococcal toxic shock-like syndrome and provides sequence type-independent protection during Streptococcus suis infection

Streptococcus suis (S. suis) is an encapsulated zoonotic pathogen, which is responsible for bacterial meningitis and streptococcal toxic shock-like syndrome (STSLS). Despite many attempts to develop an effective vaccine, none is currently available. Here, a capsular polysaccharide (CPS)-expressing attenuated mutant 2015033 was constructed by deleting five virulence-associated factors (sly, scpA, ssnA, fhb, and ssads) in an outbreak S. suis strain SC19. Genes mentioned above are associated with either innate immunity-evading or tissue barrier-invading. Deletion of these genes did not impact the growth ability and CPS generation of 2015033, and the mutant exhibited no hemolytic activity to erythrocytes and no cytotoxicity to different epithelial or endothelial cells. In addition, 2015033 was more easily eliminated by whole human blood in vitro and by mouse blood in vivo. In addition, 2015033 showed a diminished invasive ability in different mouse organs (brain, lung, and liver) and avirulent properties in mice associated with weak inflammation-inducing ability. Immunization with 2015033 triggered T cell-dependent immunity and this immunity suppressed STSLS during SC19 infection by inhibiting excessive proinflammatory responses. In addition, immunization with 2015033 successfully conferred sequence type (STs)-independent protection to mice during heterogeneous infections (ST1, ST7, and ST658). This study presents the feasibility of the strategy of multi-gene deletion for the development of promising live vaccines against invasive encapsulated pathogens.\n\nIMPORTANCES. suis is a traditional zoonotic agent causing human meningitis and STSLS, which is also a neglected emerging food-borne pathogen. Increasing antimicrobial resistance invokes reduction of preventative use of antibiotics in livestock creating an urgent need for effective vaccines. Given the expression of CPS is the basis for promising vaccines against encapsulated pathogens, and in order to find an effective and economical strategy for CPS-based vaccine development, multi-gene deletion was introduced into the design of a S. suis vaccine for the first time. From our results, CPS-expressing attenuated mutant 2015033 exhibited diminished evasive ability against the innate immune system and reduced invasive properties against different host barriers. To our knowledge, 2015033 is the first STSLS-suppressing S. suis vaccine to provide STs-independent protection during heterogeneous infections.

microbiology↗

bioRxiv2018

Intracellular absorption underlies collective bacterial tolerance towards an antimicrobial peptide

The collective tolerance towards antimicrobial peptides (APs) is thought to occur primarily through mechanisms associated with live bacterial cells. In contrast to the focus on live cells, we discover that the LL37 antimicrobial peptide kills Escherichia coli, forming a subpopulation of dead cells that absorbs the remaining LL37 into its intracellular space. Combining mathematical modeling with population and single-cell experiments, we show that bacteria absorb LL37 at a timing that coincides with the permeabilization of their cytoplasmic membranes. Furthermore, we show that one bacterial strain can absorb LL37 and protect another strain from killing by LL37. Finally, we demonstrate that the intracellular absorption of LL37 can be reduced using a peptide adjuvant. In contrast to the existing collective tolerance mechanisms, we show that the dead-bacterial absorption of APs is a dynamic process that leads to emergent population behavior, and the work suggests new directions to enhance the efficacy of APs.

systems biology↗

bioRxiv2018

Transcription Factor Regulation of RNA polymerase’s Torsional Capacity

During transcription, RNA polymerase (RNAP) supercoils DNA as it forsward-translocates. Accumulation of this torsional stress in DNA can become a roadblock for an elongating RNAP and thus should be subject to regulation during transcription. Here, we investigate whether, and how, a transcription factor may regulate the torque generation capacity of RNAP and torque-induced RNAP stalling. Using a real-time assay based on an angular optical trap, we found that under a resisting torque, RNAP was highly prone to extensive backtracking. However, the presence of GreB, a transcription factor that facilitates the cleavage of the 3 end of the extruded RNA transcript, greatly suppressed backtracking and remarkably increased the torque that RNAP was able to generate by 65%, from 11.2 to 18.5 pN{middle dot}nm. Analysis of the real-time trajectories of RNAP position at a stall revealed the kinetic parameters of backtracking and GreB rescue. These results demonstrate that backtracking is the primary mechanism that limits transcription against DNA supercoiling and the transcription factor GreB effectively enhances the torsional capacity of RNAP. These findings broaden the potential impact of transcription factors on RNAP functionality.

biophysics↗

bioRxiv2018

Dynamic and Structural Modeling of the Specificity in Protein-DNA Interactions Guided by Binding Assay and Structure Data

How transcription factors (TFs) recognize their DNA sequences is often investigated complementarily by high-throughput protein binding assays and by structural biology experiments. The former quantifies the specificity of TF binding sites for numerous DNA sequences, often represented as the position-weight-matrix (PWM). The latter provides mechanistic insights into the interactions via the protein-DNA complex structures. However, these two types of data are not readily integrated. Here, we propose and test a new modeling method that incorporates the PWM with complex structure data. Based on pre-tuned coarse-grained models for proteins and DNAs, we model the specific protein-DNA interactions, PWMcos, in terms of an orientation-dependent potential function, which enables us to perform molecular dynamics simulations at unprecedentedly large scales. We show that the PWMcos model reproduces subtle specificity in the protein-DNA recognition. During the target search in genomic sequences, TF moves on highly rugged landscapes and occasionally flips on DNA depending on the sequence. The TATA-binding protein exhibits two remarkably distinct binding modes, of which frequencies differ between TATA-containing and TATA-less promoters. The PWMcos is general and can be applied to any protein-DNA interactions given their PWMs and complex structure data are available.

biophysics↗

bioRxiv2017

Sequence-dependent nucleosome sliding in rotation-coupled and uncoupled modes revealed by molecular simulations

While nucleosome positioning on eukaryotic genome play important roles for genetic regulation, molecular mechanisms of nucleosome positioning and sliding along DNA are not well understood. Here we investigated thermally-activated spontaneous nucleosome sliding mechanisms developing and applying a coarse-grained molecular simulation method that incorporates both long-range electrostatic and short-range hydrogen-bond interactions between histone octamer and DNA. The simulations revealed two distinct sliding modes depending on the nucleosomal DNA sequence. A uniform DNA sequence showed frequent sliding with one base pair step in a rotation-coupled manner, akin to screw-like motions. On the contrary, a strong positioning sequence, the so-called 601 sequence, exhibits rare, abrupt transitions of five and ten base pair steps without rotation. Moreover, we evaluated the importance of hydrogen bond interactions on the sliding mode, finding that strong and weak bonds favor respectively the rotation-coupled and -uncoupled sliding movements.\n\nAuthor summaryNucleosomes are fundamental units of chromatin folding consisting of double-stranded DNA wrapped [~]1.7 times around a histone octamer. By densely populating the eukaryotic genome, nucleosomes enable efficient genome compaction inside the cellular nucleus. However, the portion of DNA occupied by a nucleosome can hardly be accessed by other DNA-binding proteins, obstructing fundamental cellular processes such as DNA replication and transcription. DNA compaction and access by other proteins can simultaneously be achieved via the dynamical repositioning of nucleosomes, which can slide along the DNA sequence. In this study, we developed and used coarse-grained molecular dynamics simulations to reveal the molecular details of nucleosome sliding. We find that the sliding mode is highly dependent on the underlying DNA sequence. Specifically, a sequence with a strong nucleosome positioning signal slides via large jumps by five and ten base pairs, preserving the optimal DNA bending profile. On the other hand, uniform sequences without the positioning signal slide via a screw-like motion of DNA, one base pair at the time. These results show that sequence has a large effect not only on the formation of nucleosomes, but also on the kinetics of repositioning.

biophysics↗