Biology subjects

Yi, X.

Publications and source records attributed to Yi, X..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

RealSeq2: a software integrated with UMI identification, error correction, and methylation modifications storing

High-throughput UMI technology sequencing is widely used in early tumor screening, detection, recurrence monitoring, etc. Detecting extremely low-frequency mutations is especially important for monitoring tumor recurrence, so high-precision data, as well as high-quality data, are required. We developed RealSeq2, a new integrated data-preprocessing software based on fastp and gencore, to achieve adapter removal, quality control, UMI identification, and generate consensus reads by clustering and error correction using multithreading in high-throughput next-generation sequencing background. RealSeq2 also supports methylation data of 5-methylcytosine bisulfite-free sequencing. RealSeq2 defined a new tag in SAM for storing methylation information, which is beneficial for co-identifying methylation sites and mutation sites for downstream analysis. RealSeq2 includes three submodules: ReadsProfiler, ReadsCleaner, and ReadsRecycler. In addition, the output format file (BAM or SAM) is universal for downstream analyses. RealSeq2 is the preferred upstream analysis software for the co-detection of ultra-low frequency mutations and bisulfite-free methylation data. The error profile provides data support for downstream analysis. Additionally, XM tags will become a standard protocol for recording methylation signals.

bioinformatics↗

bioRxiv2023

Endogenous fine-mapping of functional regulatory elements in complex genetic loci

The vast majority of genetic loci associated with polygenic complex traits are located in non-coding regions of the human genome. However, many of these regions exhibit high- order gene regulatory relationships and complicated linkage disequilibrium (LD) configurations, which bring challenges to accurately identify causal variants and their target genes controlling specific molecular processes or traits. We employed multiplexed single-cell CRISPR interference and activation perturbations to explore the links between cis-regulatory element (CRE) and target gene expression within tight LD in the endogenous chromatin context. We validated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait locus (eQTL), and revealed fine-grained genetic effects on gene expression within pLD. These effects are difficult to decipher using conventional eQTL fine-mapping or to predict via existing computational methods. We found that nearly half of the casual CREs lack classical epigenetic markers, potentially affecting gene expression through hidden regulatory mechanisms. Integrative analysis on different types of perturbation effects suggested a high regulatory plasticity of the human genome. These findings will propel further in-depth exploration of functional genomic elements, facilitating a more comprehensive understanding of gene expression regulatory patterns and the development of complex traits.

genomics↗

bioRxiv2023

Amoeboid cells undergo durotaxis with soft end polarized NMIIA

Cell migration towards stiff substrates has been coined as durotaxis and implicated in development, wound healing and cancer, where complex interplays between immune and non-immune cells are present. Compared to the emerging mechanisms underlying the strongly adhesive mesenchymal durotaxis, little is known about whether immune cells - migrating in amoeboid mode - could follow mechanical cues. Here we develop an imaging-based confined migration device with stiffness gradient. By tracking live cell trajectory and analyzing the directionality of T cells and neutrophils, we observe that amoeboid cells can durotax. We further delineate the underlying mechanism to involve non-muscle myosin IIA (NMIIA) polarization towards the soft-matrix-side but may not require differential actin flow up- or down-stiffness gradient. Using the protista Dictyostelium, we demonstrate the evolutionary conservation of amoeboid durotaxis. Finally, these experimental phenomena are theoretically captured by an active gel model capable of mechanosensing. Collectively, these results may shed new lights on immune surveillance and recently identified confined migration of cancer cells, within the mechanically inhomogeneous tumor microenvironment or the inflamed fibrotic tissues.

cell biology↗

bioRxiv2023

The cryptic step in biogeochemical Tellurium (Te) cycle: Indirect elementary Te oxidation mediated by manganese-oxidizing bacterium (MnOB)

Tellurium (Te) is a rare element in the chalcogen group, and its biogeochemical cycle has been investigated for decades. As the most soluble Te species, tellurite (Te(IV)) possess the highest toxicity to the organisms. Chemical or biological Te(IV) reduction to elemental tellurium (Te0) is generally considered as an effective detoxification route for Te(IV)-containing wastewater. Here, we reported a previously overlooked Te0 oxidation process mediated by manganese-oxidizing bacterium Bacillus sp. FF-1. This strain has both Mn(II)-oxidizing and Te(IV)-reducing activities, which could produce manganese oxides (BioMnOx) and Te0 (BioTe0) when incubating with Mn(II) and Te(IV), respectively. Te(IV) can co-precipitated with Mn(II) to form highly stable Te(IV)-Mn(II) compounds with low bioavailability. While when 5 mM Mn(II) was added after incubating 0.1 mM or 1 mM Te(IV) with strain FF-1 for 16 hours, the BioTe0 were certainly re-oxidized to Te(IV) by BioMnOx according to the results of X-ray photoelectron spectra (XPS) and Transmission electron microscope (TEM). The chemogenic and exogenous biogenic Te0 can also be oxidized by the BioMnOx, although with different rates. This study highlights a new transformation process of tellurium species mediated by manganese-oxidizing bacteria, revealing that the environmental fate and ecological risks of Te0 needed to be re-evaluated. ImportanceBiogeochemical cycle of Te mediated by bacteria mainly focus on the Tellurite reduction and methylation. In this study, the indirect tellurium (Te0) oxidation driven by manganese-oxidizing bacterium is firstly confirmed. As Te0 usually considered as a stable and safe products during Te(IV)-containing wastewater treatment, we suppose the ecological risks of Te0 needed to be re-evaluated due to the possible oxidation by manganese-oxidizing bacterium and its generated manganese oxides.

microbiology↗

bioRxiv2023

Unraveling the causal genes and transcriptomic determinants of human telomere length

Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogated TL-modulated genes and their potential functions. We found that placental TL is relatively longer across human tissues and which maintenance is mostly connected to genes responsible for alternative lengthening of telomeres. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identified 20 novel genetic associations and provided increased polygenic determination of human TL. Next, we integrated the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 31 likely causal genes, among which 4 were functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improved the prediction performance of human TL. This study deepened our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

genetics↗

bioRxiv2023

Contribution of protein conformational heterogeneity to NMR lineshapes at cryogenic temperatures

While low temperature NMR holds great promise for the analysis of unstable samples and for sensitizing NMR detection, spectral broadening in frozen protein samples is a common experimental challenge. One hypothesis explaining the additional linewidth is that a variety of conformations are in rapid equilibrium at room temperature and become frozen, creating an inhomogeneous distribution at cryogenic temperatures. Here we investigate conformational heterogeneity by measuring the backbone torsion angle ({Psi}) in E. coli DHFR at 105K. Motivated by the particularly broad N chemical shift distribution in this and other examples, we modified an established NCCN {Psi} experiment to correlate the chemical shift of Ni+1 to {Psi}i. With selective 15N and 13C enrichment of Ile, only the unique I60-I61 pair was expected to be detected in 13C-15N correlation spectrum. For this unique amide we detected three different conformation basins based on dispersed chemical shifts. Backbone torsion angles {Psi} were determined for each basin 114 {+/-} 7 for the major peak, and 150 {+/-} 8 and 164 {+/-} 16{degrees} for the minor peak as contrasted with 118 for the X-ray crystal structure (and 118-130 for various previously reported structures). These studies support the hypothesis that inhomogeneous distributions of protein backbone torsion angles contribute to the lineshape broadening in low temperature NMR spectra. Significance StatementUnderstanding protein conformational flexibility is essential for insights into the molecular basis of protein function and the thermodynamics of proteins. Here we investigate the ensemble of protein backbone conformations in a frozen protein freezing, which is likely a close representation for the ensemble in rapid equilibrium at room temperature. Various conformers are spectrally resolved due to the exquisite sensitivity of NMR shifts to local conformations, and NMR methods allow us to directly probe the torsion angles corresponding to each band of chemical shifts.

biophysics↗

bioRxiv2023

The landscape of m1A modification and its posttranscriptional regulatory functions in primary neurons

Cerebral ischaemia-reperfusion injury, during which neurons undergo oxygen-glucose deprivation/reoxygenation (OGD/R), is a notable pathological process in many neurological diseases. N1-methyladenosine (m1A) is an RNA modification that can affect gene expression and RNA stability. The m1A landscape and potential functions of m1A modification in neurons remain poorly understood. We explored RNA (mRNA, lncRNA, and circRNA) m1A modification in normal and OGD/R-treated neurons and the effect of m1A on diverse RNAs. We investigated the m1A landscape in primary neurons, identified m1A-modified RNAs, and found that OGD/R increased the number of m1A RNAs. m1A modification might also affect the regulatory mechanisms of noncoding RNAs, e.g., lncRNA-RBP interactions and circRNA translation. We showed that m1A modification mediates the circRNA/lncRNA-miRNA-mRNA ceRNA mechanism and that 3UTR methylation of mRNAs can hinder miRNA-mRNA binding. Three methylation patterns were identified, and genes with different patterns had intrinsic mechanisms with potential m1A-regulatory specificity. Systematic analysis of the m1A landscape in normal and OGD/R neurons lays a critical foundation for understanding RNA methylation and provides new perspectives and a theoretical basis for treating and developing drugs for OGD/R pathology-related diseases.

neuroscience↗

bioRxiv2023

Predicted and Experimental NMR Chemical Shifts at Variable Temperatures: The Effect of Protein Conformational Dynamics

NMR chemical shifts provide a sensitive probe of protein structure and dynamics. Prediction of shifts, and therefore interpretation of shifts, particularly for the frequently measured amidic 15N sites, remains a tall challenge. We demonstrate that protein 15N chemical shift prediction from QM/MM predictions can be improved if conformational variation is included via MD sampling, focusing on the antibiotic target, E. coli Dihydrofolate reductase (DHFR). Variations of up to 25 ppm in predicted 15N chemical shifts are observed over the trajectory. For solution shifts the average of fluctuations on the low picosecond timescale results in a superior prediction to a single optimal conformation. For low temperature solid state measurements, the histogram of predicted shifts for locally minimized snapshots with specific solvent arrangements sampled from the trajectory explains the heterogeneous linewidths; in other words, the conformations and associated solvent are frozen out at low temperatures and result in inhomogeneously broadened NMR peaks. We identified conformational degrees of freedom that contribute to chemical shift variation. Backbone torsion angles show high amplitude fluctuations during the trajectory on the low picosecond timescale. For a number of residues, including I60, {psi} varies by up to 60{o} within a conformational basin during the MD simulations, despite the fact that I60 (and other sites studied) are in a secondary structure element and remain well folded during the trajectory. Fluctuations in {psi} appear to be compensated by other degrees of freedom in the protein, including {varphi} of the succeeding residue, resulting in "rocking" of the amide plane with changes in hydrogen bonding interactions. Good agreement for both room temperature and low temperature NMR spectra provides strong support for the specific approach to conformational averaging of computed chemical shifts.

biophysics↗

bioRxiv2023

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

bioinformatics↗

bioRxiv2023

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↗

bioRxiv2022

SEPepQuant enables comprehensive protein isoform characterization in shotgun proteomics

Shotgun proteomics is essential for protein identification and quantification in biomedical research, but protein isoform characterization is inhibited by the extensive number of peptides shared across proteins, hindering our understanding of protein isoform regulation and their roles in normal and disease biology. We systematically assess the challenge and opportunities of shotgun proteomics-based protein isoform characterization using in silico and experimental data, and then present SEPepQuant, a graph theory-based approach to enable isoform characterization. Using published data from one induced pluripotent stem cell study and two human hepatocellular carcinoma studies, we demonstrate the ability of SEPepQuant in addressing the key limitations of existing methods, providing more comprehensive proteome characterization, identifying hundreds of isoform-level regulation events, and facilitating streamlined cross-study comparisons. Our analysis provides solid evidence to support a widespread role of protein isoform regulation in normal and disease processes, and SEPepQuant has broad applications to biological and translational research.

bioinformatics↗

bioRxiv2022

Proliferative Exhausted CD8 T Cells Exacerbate Long-lasting Anti-tumor Effects in Human Papillomavirus Positive Head and Neck Squamous Cell Carcinoma

The survival prognosis of human papillomavirus (HPV)-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) is largely different, and little is known about the anti-tumor mechanism of tumor-infiltrated CD8+ exhausted T cells (Tex) in HNSCC. We performed cell level multi-omics sequencing on human HNSCC samples to decipher the multi-dimensional characteristics of Tex cells. A proliferative exhausted CD8+ T cell cluster (P-Tex) which was beneficial to survival outcomes of patients with HPV-positive HNSCC was identified. Interestingly, P-Tex cells expressed CDK4 genes as high as cancer cells, which could be simultaneously inhibited by CDK4 inhibitors and might be a potential reason for the ineffectiveness of CDK4 inhibitors in treating HPV-positive HNSCC. P-Tex cells could aggregate in the antigen presenting cell niches and activate certain signaling pathways. Together, our findings suggest a promising role for P-Tex cells in the prognosis of patients with HPV-positive HNSCC by providing modest but persistent anti-tumor effects. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/513993v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1f8810forg.highwire.dtl.DTLVardef@1e11d84org.highwire.dtl.DTLVardef@58fb6aorg.highwire.dtl.DTLVardef@1e20a13_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Gabapentin Disrupts Binding of Perlecan to the α2δ1 Voltage Sensitive Calcium Channel Subunit and Impairs Skeletal Mechanosensation

Our understanding of how osteocytes, the principal mechanosensors within bone, sense and perceive force remains unclear. Previous work identified "tethering elements" (TEs) spanning the pericellular space of osteocytes and transmitting mechanical information into biochemical signals. While we identified the heparan sulfate proteoglycan perlecan (PLN) as a component of these TEs, PLN must attach to the cell surface to induce biochemical responses. As voltage-sensitive calcium channels (VSCCs) are critical for bone mechanotransduction, we hypothesized that PLN binds the extracellular 2{delta}1 subunit of VSCCs to couple the bone matrix to the osteocyte membrane. Here, we showed co-localization of PLN and 2{delta}1 along osteocyte dendritic processes. Additionally, we quantified the molecular interactions between 2{delta}1 and PLN domains and demonstrated for the first time that 2{delta}1 strongly associates with PLN via its domain III. Furthermore, 2{delta}1 is the binding site for the commonly used pain drug, gabapentin (GBP), which is associated with adverse skeletal effects when used chronically. We found that GBP disrupts PLN::2{delta}1 binding in vitro, and GBP treatment in vivo results in impaired bone mechanosensation. Our work identified a novel mechanosensory complex within osteocytes composed of PLN and 2{delta}1, necessary for bone force transmission and sensitive to the drug GBP. This work provides insights into the mechanisms underlying mechanotransduction and will inform future studies to understand the mechanisms responsible for the negative effects of GBP on bone.

molecular biology↗

bioRxiv2022

Inferring CTCF insulators and anchored loops across human tissues and cell types

CCCTC-binding factor (CTCF) is a transcription regulator which is involved in many cellular processes. How CTCF recognizes DNA sequence to exert chromosome barrier or enhancer blocking effects remains to be fully interrogated. Despite many computational tools were developed to predict CTCF-mediated loops qualitatively or quantitatively, few could specially evaluate the regulatory potential of DNA sequence at CTCF binding sites (CBSs) and how it affects chromatin loop formation. Here, we developed a deep learning model, DeepAnchor, to precisely characterize the binding patterns for different types of CBSs. By incorporating base-wise genomic/epigenomic features, we revealed distinct chromatin and sequence features for CTCF-mediated insulation and looping at a high resolution, such as two sequence motifs flanking the core CTCF motif at loop-associated CBSs. Besides, we leveraged the predicted anchor score to optimize the loop extrusion model and achieved the best performance in predicting CTCF-anchored loops. We established a compendium of context-specific CTCF-anchored loops across 52 human tissue/cell types and found that genomic disruption of CTCF-anchored loops may represent a general causal mechanism of disease pathogenesis. These computational models, together with the established resource, could facilitate the mechanistic research on how the CTCF-mediated cis-regulatory elements (CREs) shapes context-specific gene regulation in cell development and disease progression.

bioinformatics↗

bioRxiv2022

A common mechanism of temperature-sensing in thermoTRP channels

Detecting temperature is crucial for the survival of living organisms. Though the thermo transient receptor potential (thermoTRP) channels, such as TRPV1 or TRPM8, have been identified as prototypic heat or cold sensors, respectively, how they detect temperature remains elusive. Here we first identified groups of clustered residues in these channels that undergo burial/exposure conformational rearrangements during temperature activation by analyzing available protein structures or hydroxyl radical footprinting-mass spectroscopy (HRF-MS). By systematically perturbing water-protein interactions at these residues, we found that the temperature sensitivity in these channels were modulated in accordance with the sidechain hydrophobicity. The changes in energy associated with changes in water-protein interactions were sufficient for thermo activation. Therefore, our study has established that the water-protein interactions as a common mechanism underlying temperature sensing in TRPM8 and TRPV1.

biophysics↗

bioRxiv2022

Single Particle Tracking With Compressive Sensing Using Progressive Refinement Method On Sparse Recovery (spt-PRIS)

Single particle tracking (SPT) is an indispensable tool for scientific studies. However, SPT for datasets with a high density of particles is still challenging, especially for the study of particle interactions where the point spread functions (PSFs) are overlapping. In this study, we present spt-PRIS, a new SPT solution where we apply compressive sensing to SPT by integrating the progressive refinement method on sparse recovery (PRIS) into the framework of the state-of-the-art SPT algorithm (uTrack). We systematically characterized and validated spt-PRIS performance using simulations, applied it to the experimental data of membrane-bound KRAS4b proteins in either 2-lipid or 8-lipid membrane supported lipid bilayers (SLB), and compared the results to the conventional method (uTrack). Our results show that spt-PRIS is effective for SPT when the data contains overlapping PSFs and provides unprecedented information about KRAS4b subpopulations. spt-PRIS is helpful for a broad range of scientific studies where precise and fast high-density localization is beneficial. spt-PRIS is also flexible for extensions for multi-species, multi-multi-channel, and multi-dimensional SPT methods with the generalization of PRIS reconstruction schemes.

biophysics↗

bioRxiv2022

Dynamic tripartite construct of interregional engram circuits underlies forgetting of extinction memory

Fear extinction allows for adaptive control of learned fear responses but often fails, resulting in a renewal or spontaneous recovery of the extinguished fear, i.e., forgetting of the extinction memory readily occurs. Using an activity-dependent neuronal labeling strategy, we demonstrate that engram neurons for fear extinction memory are dynamically positioned in the medial prefrontal cortex (mPFC), basolateral amygdala (BLA), and ventral hippocampus (vHPC), which constitute an engram construct in the term of directional engram synaptic connectivity from the BLA or vHPC to mPFC, but not that in the opposite direction, for retrieval of extinction memory. Fear renewal or spontaneous recovery switches the extinction engram construct from an accessible to inaccessible state, whereas additional extinction learning or optogenetic induction of long-term potentiation restores the directional engram connectivity and prevents the return of fear. Thus, the plasticity of engram construct underlies forgetting of extinction memory.

neuroscience↗

bioRxiv2022

A Tailored Approach To Study Legionella Infection Using Lattice Light Sheet Microscope (LLSM)

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis [1]. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis [2,3], great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The Lattice Light Sheet Microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage [4]. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel Reconfigurable Galvanometer Scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

bioengineering↗