Biology subjects

Liu, Y.-Z.

Publications and source records attributed to Liu, Y.-Z..

9 recordsLinked to original sources

bioRxiv2025

Genomic insights into polysaccharide substrate utilization and novel genera resource mining in macroalgal epiphytic bacteria

Marine macroalgae, among the fastest photosynthesizing organisms, play a crucial role in the ocean carbon cycle by converting fixed carbon dioxide into polysaccharides. Macroalgal epiphytic bacteria possessing specific polysaccharide utilization loci (PULs) have a generalized polysaccharide degradation potential that facilitates their growth and colonization. In this study, we conducted extensive research on their polysaccharide degradation potential. Through sampled and purified epiphytic bacteria and metagenomic analysis revealed a high prevalence of novel genera and species. Two novel genera, 1117T and 3-347T, were taxonomically characterized and conducted detailed functional analyses. The results demonstrated that these genera possess abundant PULs and strong capabilities for synthesizing secondary metabolites. Furthermore, their high relative abundance on macroalgal surfaces aligns with global ecological distribution patterns. These traits facilitate their colonization, growth, and environmental adaptation on macroalgal surfaces. We further performed in-depth annotation of a large number of PULs and CAZyme genes of macroalgal epiphytic bacteria. Potential polysaccharide substrates for their degradation can be predicted and focused on. Additionally, we conducted growth curve analyses by starch, xylan, {beta}-1,3-glucan, and carboxymethyl cellulose substrates to validate the genomic predictions. In summary, our findings demonstrate that macroalgal epiphytic bacteria possess significant potential for degrading algal polysaccharides. This capability may enhance their competitiveness and survival probability on macroalgal surfaces. These bacteria, originating from different sources and genera, possess similar PULs, which may result from horizontal gene transfer or evolutionary relationships. ImportanceMacroalgae are major primary producers in coastal areas and their carbon sequestration capacity per unit area far exceeds that of terrestrial forests. In this work, we extensively studied macroalgal epiphytic bacteria with polysaccharide degradation potential. We found that epiphytic bacteria from different macroalgal sources and genera share similar PULs to degrade the same polysaccharide, which may be the result of horizontal gene transfer or evolutionary relationships. Core taxa on the macroalgal surface have gradually evolved polysaccharide-degrading abilities of different marine macroalgae in order to expand their colonization and survival chances. We also identified a large number of uncultivated algal biosphere species and unreported new genera and species for expansion of macroalgal epiphytic bacteria studies. These studies have thus highlighted the important ecological and research value of macroalgal epiphytic bacteria, especially in influencing polysaccharide carbon storage and marine carbon cycling.

microbiology↗

bioRxiv2025

Two-photon activation, deactivation, and coherent control of melanopsin in live cells

Intrinsically photosensitive retinal ganglion cells are photoreceptors discovered in the last 20 years. These cells project to the suprachiasmatic nucleus of the brain to drive circadian rhythms, regulated by ambient light levels. The photopigment responsible for photoactivation in these cells, melanopsin, has been shown to exhibit many unique activation features among opsins. Notably, the photopigment can exist in three states dependent on the intensity and spectrum of ambient light, which affects its function. Despite increasing knowledge about these cells and melanopsin, tools that can manipulate their three states, and do so with single-cell precision, are limited. This reduces the extent to which circuit-level phenomena, and studying the implications of melanopsin tri-stability in living systems, can be pursued. In this report, we evoke and modulate calcium transients in live cells and intrinsically photosensitive retinal ganglion cells from isolated retinal tissues following two-photon excitation using near-infrared light pulses. We demonstrate that two-photon activation of melanopsin can successfully stimulate melanopsin-expressing cells with high spatio-temporal precision. Moreover, we demonstrate that the functional tri-stability of the photopigment can be interrogated by multiphoton excitation using spectral-temporal modulation of a broadband, ultrafast laser source.

bioengineering↗

bioRxiv2024

Du-IN-v2: Unleashing the Power of Vector Quantization for Decoding Cognitive States from Intracranial Neural Signals

While invasive brain-computer interfaces have shown promise for high-performance speech decoding under medical use, the potential of intracranial stereoElectroEn-cephaloGraphy (sEEG), which causes less damage to patients, remains underex-plored. With the rapid progress in representation learning, leveraging abundant pure recordings to further enhance speech decoding becomes increasingly attractive. However, some popular methods pre-train temporal models based on brain-level tokens, overlooking the brains desynchronization nature; others pre-train spatial-temporal models based on channel-level tokens, yet fail to evaluate them on more challenging tasks, e.g., speech decoding, which demands intricate processing in specific brain regions. To tackle these issues, we introduce a general pre-training framework for speech decoding - Du-IN-v2, which can extract contextual embeddings based on region-level tokens through discrete codex-guided mask modeling. To further push its limits, we propose Decoupling Product Quantization (DPQ), where different codexes are designed to extract different parts of brain dynamics. Our model achieves SOTA performance on both the 61-word classification task and the 49-syllable sequence classification task, surpassing all baselines. Model comparison and ablation studies reveal that our design choices, including (i) temporal modeling based on region-level tokens by utilizing 1D depthwise convolution to fuse channels in vSMC and STG regions and (ii) self-supervision by discrete decoupling codex-guided mask modeling, significantly contribute to these performances. Collectively, our approach, inspired by neuroscience findings, capitalizing on region-level representations from specific brain regions, is suitable for invasive brain modeling. It marks a promising neuro-inspired AI approach in BCI.

bioengineering↗

bioRxiv2024

The triose phosphate/phosphate translocator exports photosynthetic glyceraldehyde 3-phosphate from chloroplasts to trigger antimicrobial immunity in plants.

Chloroplasts play a crucial role in plant immunity against invading microbes. However, it remains poorly understood whether photosynthetic metabolites from chloroplasts participate directly in host defenses. Here, we uncovered Arabidopsis thalinana triose phosphate/phosphate translocator (AtTPT), a known translocator for chloroplast inner membrane, plays an indispensable role in suppressing virus infection and evoking defense responses. Interestingly, overexpression of AtTPT impairs virus accumulation in plants, while loss-of-function tpt3 mutants exhibit an increased viral load. The antiviral activity of AtTPT requires its phosphate transport capacity, implying that it actually functions through its metabolite(s). To this end, we found that glyceraldehyde 3-phosphate (GAP), one of AtTPTs translocated metabolites, can drastically enhance expression of defense-related genes and prominently induce defense signaling pathways. More excitingly, AtTPT or GAP robustly restricts the proliferation of multiple types of phytopathogens. Collectively, we propose that AtTPT exports GAP to mediate broad-spectrum resistance to pathogens, which provides new insights into the mechanism underlying the chloroplast-mediated immunity by a photosynthetic metabolite.

plant biology↗

bioRxiv2023

Neoadjuvant Therapy Differentially Remodels Carcinoma and Tumor Microenvironment in Pancreatic Ductal Adenocarcinoma: Insights from Spatially Resolved Transcriptomics

PurposeNeoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its distinct effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study employs spatial transcriptomics and single-cell RNA sequencing to investigate how NAT differentially remodels PDACs carcinoma cells and TME. Experimental DesignWe used spatial transcriptomics to compare gene expression profiles in carcinoma cells and the TME between NAT-treated and NAT-naive PDAC patients and correlated with their clinicopathologic features. Complementary single-nucleus RNA sequencing (snRNA-seq) analysis was conducted to validate our findings and identify cell types driving NAT-induced gene expression alterations. ResultsWe found NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival; more immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes and mast cells; and lower immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement upregulation specifically in CAFs but not in other stroma cell types. ConclusionsOur findings indicate that NAT may reduce immunosuppression in PDAC by enhancing complement production and signaling within the TME. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients. Translational RelevanceAs neoadjuvant therapy (NAT) increasingly becomes the preferred approach in treating resectable and borderline resectable pancreatic ductal adenocarcinoma (PDAC), there is a growing demand for novel biomarkers specifically tailored for post-NAT PDAC patients. Our study focused on how NAT differentially remodels the tumor cells and the tumor microenvironment (TME). We demonstrate that NAT can enhance local complement production and signaling in PDACs TME, which is associated with reduced immune exhaustion and improved overall survival. Our results highlight the importance of local complement dynamics in influencing treatment response, resistance, and overall clinical outcomes in PDAC. This new mechanism provides new opportunities in biomarker development which could facilitate more accurate prognostication and precise treatment stratification, particularly for patients undergoing NAT in PDAC.

genomics↗

bioRxiv2022

Falign: An effective alignment tool for long noisy 3C data

Fragmented long noisy reads (FLNRs), such as Pore-C, contain multiple fragments of varied length separated by restriction enzyme sites. Existing alignment tools have a low mapping rate for short fragments and find incorrect fragment boundaries, which affects the utilization of FLNRs for downstream studies. Here, we develop Falign, a sequence alignment method that is adapted to the nature of FLNRs. Falign adopts a two-phase approach to efficiently align both long and short fragments. Falign uses the restriction enzyme sites on the reference genome as boundaries, which avoids the problem of destroyed fragment boundaries on FLNRs. Falign employs a multiple-stage searching mechanism to effectively recover the alignments of FLNRs with multiple fragments and interchromosomal fragments. Experiments on simulated and experimental fragmented long noisy 3C datasets show that Falign can effectively recover the constructs of reads and the sampled loci of the fragments. Falign allows significantly higher data utilization for FLNRs.

bioinformatics↗

bioRxiv2020

HIT-scISOseq: High-throughput and High-accuracy Single-cell Full-length Isoform Sequencing for Corneal Epithelium

Single-cell isoform sequencing can reveal transcriptomic dynamics in individual cells invisible to bulk- and single-cell RNA analysis based on short-read sequencing. However, current long-read single-cell sequencing technologies have been limited by low throughput and high error rate. Here we introduce HIT-scISOseq for high-throughput single-cell isoform sequencing. This method was made possible by full-length cDNA capture using biotinylated PCR primers, and by our novel library preparation procedure that combines head-to-tail concatemeric full-length cDNAs into a long SMRTbell insert for high-accuracy PacBio sequencing. HIT-scISOseq yields > 10 million high-accuracy full-length isoforms in a single PacBio Sequel II 8M SMRT Cell, providing > 8 times more data output than the standard single-cell isoform PacBio sequencing protocol. We exemplified HIT-scISOseq by first studying transcriptome profiles of 4,000 normal and 8,000 injured corneal epitheliums from cynomolgus monkeys. We constructed dynamic transcriptome landscapes of known and rare cell types, revealed novel isoforms, and identified injury-related splicing and switching events that are previously not accessible with low throughput isoform sequencing. HIT-scISOseq represents a high-throughput, cost-effective, and technically simple method to accelerate the burgeoning field of long-read single-cell transcriptomics.

genomics↗

bioRxiv2020

Fast and accurate assembly of Nanopore reads via progressive error correction and adaptive read selection

Although long Nanopore reads are advantageous in de novo genome assembly, applying Nanopore reads in genomic studies is still hindered by their complex errors. Here, we developed NECAT, an error correction and de novo assembly tool designed to overcome complex errors in Nanopore reads. We proposed an adaptive read selection and two-step progressive method to quickly correct Nanopore reads to high accuracy. We introduced a two-stage assembler to utilize the full length of Nanopore reads. NECAT achieves superior performance in both error correction and de novo assembly of Nanopore reads. NECAT requires only 7,225 CPU hours to assemble a 35X coverage human genome and achieves a 2.28-fold improvement in NG50. Furthermore, our assembly of the human WERI cell line showed an NG50 of 29 Mbp. The high-quality assembly of Nanopore reads can significantly reduce false positives in structure variation detection.

bioinformatics↗

bioRxiv2019

Genome-wide association study of appendicular lean mass in UK Biobank cohort

Lean body mass (LBM), an important physiological measure, has a strong genetic determination. To clarify its genetic basis, a large-scale genome-wide association study (GWAS) of appendicular lean mass (ALM) was conducted in 450,580 UK Biobank subjects. A total of 717 variants (p<5x10-9) from 561 loci were identified, which were replicated across genders (achieving p<5x10-5 in both genders). The identified variants explained ~11% phenotypic variance, accounting for one quarter of the total ~40% GWAS-attributable heritability. The identified variants were enriched in gene sets related to musculoskeletal and connective tissue development. Of interest are several genes, including ADAMTS3, PAM, SMAD3 and MEF2C, that either contain multiple significant variants or serve as the hub genes of the associated gene sets. Polygenic score prediction based on the associated variants was able to distinguish subjects of high from low ALM. Overall, our results offered significant findings on the genetic basis of lean mass through an extraordinarily large sample GWAS. The findings are important to not only lean mass per se but also other complex diseases, such as type 2 diabetes and fracture, as our Mendelian randomization analysis showed that ALM is a protective factor for these two diseases.

genetics↗