Biology subjects

Xie, W. J.

Publications and source records attributed to Xie, W. J..

6 recordsLinked to original sources

bioRxiv2025

Sourdough starter-inspired living materials grown from probiotic consortia with engineered division-of-labor

Genetic circuits enable precise control over cellular behavior. As circuits become more complex, implementing them within a single cell population becomes difficult. Tasks can instead be distributed in engineered consortia. However, selecting appropriate consortia and harnessing the natural traits of each species for such a division of labor remain unsolved challenges. Here, we report the creation of SINERGY, an engineered synthetic sourdough starter in which functional modules are distributed between the two constituent species. These modules, consisting of sensing, communication, and response, enable in vitro biosensing and in vivo drug delivery and modulate the gut ecosystem in an animal disease model. SINERGY not only preserves the safety and health-promoting properties of the natural components but also endows microbes with programmable functionalities, facilitating broad applications in biomedicine.

synthetic biology↗

bioRxiv2023

Enhancing Luciferase Activity and Stability through Generative Modeling of Natural Enzyme Sequences

The availability of natural protein sequences synergized with generative artificial intelligence (AI) provides new paradigms to create enzymes. Although active enzyme variants with numerous mutations have been produced using generative models, their performance often falls short compared to their wild-type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate of designed single mutants is [~]50% to improve either luciferase activity or stability. These finding highlights natures ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in Renilla luciferase towards emitting blue light that holds advantages in terms of water penetration compared to other light spectrum. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

bioinformatics↗

bioRxiv2019

Characterizing chromatin folding coordinate and landscape with deep learning

Genome organization is critical for setting up the spatial environment of gene transcription, and substantial progress has been made towards its high-resolution characterization. The underlying molecular mechanism for its establishment is much less understood. We applied a deep-learning approach, variational autoencoder (VAE), to analyze the fluctuation and heterogeneity of chromatin structures revealed by single-cell super-resolution imaging and to identify a reaction coordinate for chromatin folding. This coordinate monitors the progression of topologically associating domain (TAD) formation and connects the seemingly random structures observed in individual cohesin-depleted cells as intermediate states along the folding pathway. Analysis of the folding landscape derived from VAE suggests that well-folded structures similar to those found in wild-type cells remain energetically favorable in cohesin-depleted cells. The interaction energies, however, are not strong enough to overcome the entropic penalty, leading to the formation of only partially folded structures and the disappearance of TADs from contact maps upon averaging. Implications of these results for the molecular driving forces of chromatin folding are discussed.

biophysics↗

bioRxiv2018

Learning mechanism of chromatin domain formation with big data

Chromatin modifications play critical roles in gene regulation and encoding cell phenotypic diversity. The molecular mechanism for their establishment and maintenance is not fully understood due to the complexity of chromatin regulatory pathways. Here we took a data-driven approach and parameterized an information-theoretic model to infer mechanism of chromatin domain formation from genome-wide epigenetic modification profiles. The energy landscape of this model reveals many important chromatin domains that span multiple nucleosomes and exhibit distinct combinatorial patterns of histone modifications, including super (stretch) enhancers, broad H3K4me3 promoter domains, heterochromatin, etc. Transition path analysis further demonstrates that enhancer and promoter domains undergo a sequential maturation process along which the regulatory elements grow from short but stable nucleosome segments to long and potent ones that are modified with many activation marks. On the other hand, the formation of heterochromatin domains is a highly cooperative process, and no intermediate states were found along the transition path. Interaction energies of the information-theoretic model further suggest that heterochromatin domains adopt collapsed, globular three-dimensional conformations that can be stabilized by phase-separated liquid droplets.Our results demonstrate the usefulness of statistical mechanical models and molecular biophysical approaches in interpreting the rich information encoded in epigenomics data.

biophysics↗

bioRxiv2016

Folding Principle of Chromosome Emerges from Mapping of Genome Features onto its 3D Structure

How chromosomes fold into 3D structures and how genome functions are affected or even controlled by their spatial organization remain challenging questions. Hi-C experiment has provided important structural insights for chromosome, and Hi-C data are used here to construct the 3D chromatin structure which are characterized by two spatially segregated chromatin compartments A and B. By mapping a plethora of genome features onto the constructed 3D chromatin model, we show vividly the close connection between genome properties and the spatial organization of chromatin. We are able to dissect the whole chromatin into two types of chromatin domains which have clearly different Hi-C contact patterns as well as different sizes of chromatin loops. The two chromatin types can be respectively regarded as the basic units of chromatin compartments A and B, and also spatially segregate from each other as the two chromatin compartments. Therefore, the chromatin loops segregate in the space according to their sizes, suggesting the excluded volume or entropic effect in chromatin compartmentalization as well as chromosome positioning. Taken together, these results provide clues to the folding principles of chromosomes, their spatial organization, and the resulted clustering of many genome features in the 3D space.

biophysics↗

bioRxiv2016

DNA Methylation Landscape Reflects the Spatial Organization of Chromatin in Different Cells

The relation between DNA methylation and chromatin structure is still largely unknown. By analyzing a large set of sequencing data, we observed a long-range power law correlation of DNA methylation with cell-class-specific scaling exponents in the range of thousands to millions of base pairs. We showed such cell-class-specific scaling exponents are caused by different patchiness of DNA methylation in different cells. By modeling the chromatin structure using Hi-C data and mapping the methylation level onto the modeled structure, we demonstrated the patchiness of DNA methylation is related to chromatin structure. The scaling exponents of the power law correlation is thus a display of the spatial organization of chromatin. Besides, the local correlation of DNA methylation is associated with nucleosome positioning and different between partially-methylated-domain and non-partially-methylated-domain, suggesting their different chromatin structures at several nucleosomes level. Our study provides a novel view of the spatial organization of chromatin structure from a perspective of DNA methylation, in which both long-range and local correlations of DNA methylation along the genome reflect the spatial organization of chromatin.

biophysics↗