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Xiang, N.

Publications and source records attributed to Xiang, N..

8 recordsLinked to original sources

Genetically encoded systems for cytosolic activity recording and molecular archiving across time

Cellular functions are governed by dynamic changes in molecular abundance, state, activity, and interactions within the cytosol. Current molecular tape recorders leverage nuclear transcriptional programs in eukaryotic cells to provide scalable readout of gene regulation dynamics, but cytosolic activity, molecular abundance, and state remain inaccessible. Here, we introduce CyTRACE, a genetically encoded, scalable framework for cytosolic activity recording and molecular archiving across time. CyTRACE ventures beyond the cell nucleus, deploys cytosol-localized protein tape monomers as direct activity sensors and molecule catchers, and offers physiological sensitivity, spatiotemporal resolution, and programmability. Within this modular framework, CytoSense records protease and kinase signaling activities while CytoCatch archives cytosolic proteins, each with temporal continuity in single mammalian cells. CyTRACE thus opens cytosolic biology to scalable activity readout and molecular interrogation.

Synthetic Biology↗

Unbiased Single-Cell Transcriptome-Proteome Co-Profiling Reveals Malignant Dormancy and Post-Transcriptional Buffering of CTCs

Leptomeningeal metastasis is driven by rare cerebrospinal fluid circulating tumor cells (CSF-CTCs). However, the mechanisms underlying their adaptation to chemotherapeutic stress remain elusive, primarily because transcriptomics alone poorly predicts functional protein states. Here, we present scMAPS, a single-cell multi-omics method that employs magnetic-assisted partitioning cell lysates to enable unbiased transcriptome-proteome co-profiling without loss-prone physical splitting and precision device. By coupling scMAPS with our custom CLEAP (CTC Label-free Enrichment and Accurate Picking) system, we performed the first deep multi-omics profiling of rare clinical CSF-CTCs before and after localized chemotherapy, detecting an average of 2,547 proteins and 7,821 genes per cell. The integrated CLEAP-scMAPS pipeline reveals a coordinated prioritizing survival over proliferation malignant dormancy phenotype and identified post-transcriptional buffering as the primary driver of treatment resistance. Our platform enables the comprehensive molecular phenotyping of rare clinical specimens, providing a highly versatile framework for decoding complex post-transcriptional regulatory networks.

cell biology↗

From genomic decay to functional advantage: Trait-based evidence for long-term host residency of a next-generation coral probiotic

A key bottleneck in microbiome engineering is ensuring the long-term host association of introduced microbes. Selecting probiotic candidates based on evolutionary genomic decay signatures of emerging host dependency offers a potential solution. The Ruegeria strain B4 of the population MC10, identified by such signatures, has shown persistent colonization in corals in a companion study. Whether this persistence translates into a measurable host benefit compared to other coral-associated Ruegeria strains, and which mechanisms underlie such benefit, remained unknown. Here we directly compare the probiotic efficacy of MC10-B4 against two sympatric Ruegeria strains isolated from the same coral colony and mucus compartment, controlling for host genotype and microenvironment. MC10-B4 inoculation significantly increased heat stress tolerance in the coral model cnidarian Aiptasia (Exaiptasia diaphana strain H2), outperforming both sympatric control strains. To understand the mechanistic basis of this probiotic efficacy, we characterized the functional profile of MC10 using an integrated multi-omics approach. The genome of MC10 is enriched in genes associated with host-interaction, including siderophore-mediated iron acquisition and exopolysaccharide biosynthesis, which were phenotypically confirmed by detectable iron scavenging and enhanced biofilm formation. Following exposure to coral tissue extract, MC10-B4 underwent a coordinated motility-to-sessility proteomic reprogramming, downregulating flagellar motor components while upregulating flagellin and biofilm regulators. This response was distinct from its sympatric relatives, which instead mounted broad upregulation of nutrient acquisition systems. MC10-B4s functional profile, particularly its sensitivity to oxidative stress, contrasts with the traits typically favored in conventional probiotic screens. Our results move beyond the descriptive identification of a coral probiotic by providing initial mechanistic insight into traits associated with long-term host association and improved thermal performance. These findings validate an evolution-guided approach that prioritizes innate colonization potential over pre-defined laboratory functionalities, informing the rational design of durable probiotics.

microbiology↗

Evolutionary Genomics Guides Scalable Coral Probiotics for Climate Resilience

A universal bottleneck limiting probiotic efficacy in medicine, aquaculture, agriculture, and wildlife conservation is uncertain long-term colonization, necessitating repeated administration. We present an evolution-guided framework for probiotic identification based on genomic hallmarks of emerging host dependency, including widespread pseudogenization and insertion sequence proliferation driving genomic restructuring. Applied to coral reefs, we screened over 1,200 coral-associated bacterial isolates and identified Ruegeria MC10 as exhibiting these signatures. Its presence was associated with increased thermal tolerance of a model cnidarian. Following nursery application, MC10 persisted in reef corals for an 8-month monitoring period through a natural bleaching event, improving color retention and retaining algal photosynthesis performance. This work establishes a predictive, scalable pipeline for selecting persistent probiotics, directly addressing a central constraint on microbiome-based interventions across host systems.

microbiology↗

Spatial distribution of the proteome in human body and cancers

A comprehensive spatial distribution of the proteome in human body and cancers is fundamental for understanding human biology and diseases including cancers. Here, we present an anatomically resolved human proteome derived from 1781 benign and malignant samples from 58 major tissue types encompassing 251 specific tissues and 25 carcinomas. Based on a spectral library covering over 75% of the human protein-coding genes with 208 understudied and 82 missing proteins characterized, we quantified over 13,000 proteins in these samples using data-independent acquisition proteomics. This data resource presents the so far most comprehensive quantitative proteomic landscape of human tissues and common carcinomas. It allows systematic evaluation of tissue-specific drug responses, identification of drug candidates that may be repurposed as antineoplastics, and discovery of novel targets for anticancer therapy. This resource, available as an online knowledgebase, refines our knowledge of spatial distribution of the human proteome and tumor-specific protein modulation.

systems biology↗

DPHL v2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins.

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v1, a previous pan-human library built from 1096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying 10,943 proteins. However, a major limitation of DPHL v1 is the lack of semi-tryptic peptides and protein isoforms, which are abundant in clinical specimens. Here, we generated DPHL v2 from 1608 DDA-MS data acquired using Orbitrap mass spectrometers. The data included 586 DDA-MS newly acquired from 17 tissue types, while 1022 files were derived from DPHL v1. DPHL v2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v2 to include semi-tryptic peptides and protein isoforms. DPHL v2 was then applied to a publicly available colorectal cancer dataset with 286 DIA-MS files. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v1. Our findings show that the increased human proteome coverage of DPHL v2 provides larger pools of potential protein biomarkers.

bioinformatics↗

Macroscale Adipose Tissue from Cellular Aggregates: A Simplified Method of Mass Producing Cell-Cultured Fat for Food Applications

We present a method of producing bulk cell-cultured fat tissue for food applications. Mass transport limitations (nutrients, oxygen, waste diffusion) of macroscale 3D tissue culture are circumvented by initially culturing murine or porcine adipocytes in 2D, after which bulk fat is produced by mechanically harvesting and aggregating the lipid-filled adipocytes into 3D fats using alginate or transglutaminase binders. The 3D fats were visually similar to fat tissue harvested from animals, with matching textures based on uniaxial compression tests. The mechanical properties of cultured fat tissues were based on binder choice and concentration, and changes in the fatty acid compositions of cellular triacylglyceride and phospholipids were observed after lipid supplementation (soybean oil) during in vitro culture. This approach of aggregating individual adipocytes into a bulk 3D tissue provides a scalable and versatile strategy to produce cultured fat tissue for food-related applications, thereby addressing a key obstacle in cultivated meat production. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/495192v3_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@148ac5eorg.highwire.dtl.DTLVardef@2c8f94org.highwire.dtl.DTLVardef@186553aorg.highwire.dtl.DTLVardef@458c09_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage

Efficient peptide and protein identification from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on an experiment-specific spectral library with a suitable size. Here, we report a computational strategy for optimizing the spectral library for a specific DIA dataset based on a comprehensive spectral library, which is accomplished by a priori analysis of the DIA dataset. This strategy achieved up to 44.7% increase in peptide identification and 38.1% increase in protein identification in the test dataset of six colorectal tumor samples compared with the comprehensive pan-human library strategy. We further applied this strategy to 389 carcinoma samples from 15 tumor datasets and observed up to 39.2% increase in peptide identification and 19.0% increase in protein identification. In summary, we present a computational strategy for spectral library size optimization to achieve deeper proteome coverage of DIA-MS data.

bioinformatics↗