Biology subjects

Xin, L.

Publications and source records attributed to Xin, L..

At least 19 recordsLinked to original sources

bioRxiv2025

Ultra-High Field 31P functional Magnetic Resonance Spectroscopy Reveals NAD+ Dynamics in Brain Energy Metabolism during Visual Stimulation.

We investigated dynamic changes in nicotinamide adenine dinucleotide (NAD{square}) metabolism in the human occipital lobe using ultra-high field 31P functional magnetic resonance spectroscopy (fMRS) at 7 Tesla. Twenty-five healthy volunteers (mean age 24 {+/-} 4 years, 10 female) performed a visual task alternating between fixation and flashing checkerboard stimuli. 31P MRS spectra were acquired from a visual cortex voxel functionally localized by prior fMRI. Linear mixed-effects modelling revealed a significant reduction in NAD{square} concentrations during the first stimulation block, while no significant change was observed during the second block. No significant changes were observed for other high-energy phosphate metabolites (ATP, phosphocreatine, and inorganic phosphate), indicating specificity in the NAD{square} response. Exploratory analyses, dividing the blocks in two halves, suggested further reductions in NAD{square} and tNAD in the second halves of both stimulation blocks, though these trends were not statistically significant. Our findings demonstrate the feasibility of using fMRS at 7T to detect stimulus-induced dynamics in cerebral NAD{square} metabolism in vivo, providing insights into the interplay between glycolysis and oxidative phosphorylation during neural activation.

neuroscience↗

bioRxiv2025

De Novo sequencing-assisted homology search for DIA data analysis enables low abundance peptide variants discovery

Data-independent acquisition mass spectrometry (DIA-MS) has emerged as a powerful approach for comprehensive proteome profiling. Spectral library search and library-free search are the two major approaches for DIA data analysis. The spectral library search requires high-quality spectral libraries derived from the search results of data-dependent acquisition (DDA) experiments, while library-free approaches rely on prediction models to generate in silico libraries. Both methodologies constrain the search space to the peptide list in the database, limiting the discovery of variant peptides arising from genetic variations or mutations. We present a novel computational method DIAVariant designed to identify peptide sequence variants directly and solely from complex DIA spectra while rigorously controlling the false discovery rate. Our experimental results demonstrate that DIAVariant successfully identifies sequence variants previously detected through proteogenomic approaches, while maintaining high specificity across multiple datasets. When integrated with existing DIA database search solutions, our approach constitutes a comprehensive analytical workflow capable of identifying peptides both represented within reference protein databases and those arising from sequence variations not captured in standard databases.

bioinformatics↗

bioRxiv2024

Rebalance the inhibitory system in the elderly brain: Influence of balance learning on GABAergic inhibition and functional connectivity

Aging involves complex processes that impact the structure, function, and metabolism of the human brain. Declines in both structural and functional integrity along with reduced local inhibitory tone in the motor areas, as indicated by reduced {gamma}-Aminobutyric acid (GABA) levels, are often associated with compromised motor performance in elderly adults. Using multi-modal neuroimaging techniques including magnetic resonance spectroscopy (MRS), diffusion magnetic resonance imaging (MRI), functional MRI as well as transcranial magnetic stimulation to assess short interval intracortical inhibition (SICI), this study explores whether these age-related changes can be mitigated by motor learning. The investigation focused on the effects of long-term balance learning (3 months) on intracortical inhibition, metabolism, structural and functional connectivity in the cortical sensorimotor network among an elderly cohort. We found that after three months of balance learning, subjects significantly improved balance performance, upregulated sensorimotor cortical GABA levels and ventral sensorimotor network functional connectivity (VSN-FC) compared to a passive control group. Furthermore, correlation analysis suggested a positive association between baseline VSN-FC and balance performance, between baseline VSN-FC and SICI, and between improvements in balance performance and upregulation in SICI in the training group, though these correlations did not survive the false discovery rate correction. These findings demonstrate that balance learning has the potential to counteract aging-related decline in functional connectivity and cortical inhibition on the tonic (MRS) and functional (SICI) level and shed new light on the close interplay between the GABAergic system, functional connectivity, and behavior.

neuroscience↗

bioRxiv2024

Structural insights into the in situ assembly of clustered protocadherin γB4

Clustered protocadherins (cPcdhs) belong to the cadherin superfamily and play important roles in neural development. cPcdhs can mediate homophilic adhesion and lead to self-avoidance and tiling by giving neurons specific identities in vertebrates. Structures and functions of cPcdhs have been studied extensively in the past decades, but the mechanisms behind the functions have not been fully understood. Here we investigate the in situ assembly of cPcdh-{gamma}B4, a member in the {gamma} subfamily of cPcdhs, by electron tomography and find that the full length cPcdh-{gamma}B4 does not show regular organization at the adhesion interfaces. By contrast, cPcdh-{gamma}B4 lacking the intracellular domain can generate an ordered zigzag pattern between cells and the cis interacting mode is different from the crystal packing of the ectodomain. We also identify the residues on the ectodomain that might be important for the zigzag pattern formation by mutagenesis. Furthermore, truncation mutants of the intracellular domain of cPcdh-{gamma}B4 reveal different assembly patterns between cell membranes, suggesting that the intracellular domain plays a crucial role in the intermembrane organization of cPcdh-{gamma}B4. Taken together, these results suggest both ectodomain and intracellular domain regulate the in situ assembly of cPcdh-{gamma}B4 at the adhesion interfaces, thereby providing mechanistic insights into the functional roles of cPcdhs during neuronal wiring.

biophysics↗

bioRxiv2024

A neurometabolic mechanism for effort-based decision-making in the dmPFC/dACC

Motivation levels vary across individuals, yet the underlying mechanisms driving these differences remain elusive. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and the anterior insula (aIns) play crucial roles in effort-based decision-making. Here, we investigate the influence of lactate, a key metabolite involved in energy metabolism and signaling, on decisions involving both physical and mental effort, as well as its effects on neural activation. Using proton magnetic resonance spectroscopy and functional MRI in 63 participants, we find that higher lactate levels in the dmPFC/dACC are associated with reduced motivation for physical effort, a relationship mediated by neural activity within this region. Additionally, plasma and dmPFC/dACC lactate levels correlate, suggesting a systemic influence on brain metabolism. Supported by path analysis, our results highlight lactates role as a modulator of dmPFC/dACC activity, hinting at a neurometabolic mechanism that integrates both peripheral and central metabolic states with brain function in effort-based decision-making.

neuroscience↗

bioRxiv2024

NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing

De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) and the significance of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate their FDRs. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data. Our FDR estimation also shows that some tools may perform better than the others in distinguishing between de novo PSMs and random matches, and can be used to assess the significance of de novo PSMs.

bioinformatics↗

bioRxiv2024

Predicting individual variations in mental effort-based decision-making using machine learning: Neurometabolic signature in the dorsomedial prefrontal cortex/dorsal anterior cingulate cortex

Motivation drives individuals to overcome costs to achieve desired outcomes, such as rewards or avoidance of punishment, with significant variability across individuals. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and anterior insula are key brain regions implicated in effort-based decision-making. Here, we utilized proton magnetic resonance spectroscopy (1H-MRS) at 7 Tesla on 69 healthy participants in these brain regions to uncover the neurometabolic factors that influence these differences. We designed and applied an effort-based decision-making task requiring mental and physical effort to probe motivated behavior, complemented by computational modeling to extract key behavioral parameters. Gradient boosting machine learning was applied to explore the predictive role of specific metabolites in motivated behavior. Our results reveal that a model established on dmPFC/dACC metabolites explains decisions to exert high mental effort and sensitivity to mental effort. In particular, glutamate, aspartate, and lactate in dmPFC/dACC, three metabolites linked through the tricarboxylic acid cycle and glycolysis, were identified as key discriminative metabolites in the dmPFC/dACC, predictive of mental effort choices, underpinning energy supply and cognitive processes. Anterior insula metabolites did not significantly relate to effort-related decisions. Notably, glutamine and lactate levels between the periphery (plasma) and the dmPFC/dACC were correlated, suggesting a metabolic link between peripheral and central biomarkers of effort. Our findings provide novel insights into the neurometabolic underpinnings of motivated behavior and propose novel biomarkers for mental effort-based decision-making. Importantly, our study highlights the relevance of multivariable approaches in elucidating complex cognitive functions.

neuroscience↗

bioRxiv2023

Concurrent profiling of multiscale 3D genome organization and gene expression in single mammalian cells

The organization of mammalian genomes within the nucleus features a complex, multiscale three-dimensional (3D) architecture. The functional significance of these 3D genome features, however, remains largely elusive due to limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we report GAGE-seq, a highly scalable, robust single-cell co-assay that simultaneously measures 3D genome structure and transcriptome within the same cell. Employing GAGE-seq on mouse brain cortex and human bone marrow CD34+ cells, we comprehensively characterized the intricate relationships between 3D genome and gene expression. We found that these multiscale 3D genome features collectively inform cell type-specific gene expressions, hence contributing to defining cell identity at the single-cell level. Integration of GAGE-seq data with spatial transcriptomic data revealed in situ variations of the 3D genome in mouse cortex. Moreover, our observations of lineage commitment in normal human hematopoiesis unveiled notable discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level that is more nuanced than previously appreciated. Together, GAGE-seq provides a powerful, cost-effective approach for interrogating genome structure and gene expression relationships at the single-cell level across diverse biological contexts.

genomics↗

bioRxiv2022

Time-efficient relaxation measurements by 31P MR fingerprinting in human brain at 7T

PurposeThe goal of the study is to develop 31P spectroscopic MRF at 7T to measure T1 and T2 relaxation times simultaneously and to compare time efficiency and test-retest reproducibility of MRF with conventional inversion recovery and multi-TE methods. MethodsA 31P MRF scheme was designed based on a balanced steady-state free precession type sequence. Dictionary was generated using the Bloch equations. B0 map was acquired experimentally and incorporated into the dictionary. 7 phantoms with different T1 and T2 relaxation times were prepared for MRF validation. Simulations were performed to evaluate estimation bias. 7 volunteers were scanned twice using both MRF and the conventional methods to evaluate the reproducibility. ResultsIn phantom measurements, T1 and T2 values between MRF and conventional methods demonstrated a good agreement with Pearsons correlation coefficients of 0.99 and 0.97, respectively. In in vivo experiments, estimated T1 by MRF were in good agreement with those measured by the inversion recovery and in the literature. On the other hand, estimated T2 values by MRF were shorter than those measured by the multi-TE method. 31P MRF method can reduce the acquisition time by 15 min providing less than 10% of mean CV for T1 estimations and less than 20% of mean CV for T2 estimations of metabolites. ConclusionOur results shows the feasibility of simultaneous T1 and T2 measurement of 31P metabolites in human brain using MRF at 7T. High reproducibility can be achieved especially for T1 measurement with 40% time reduction over conventional methods.

bioengineering↗

bioRxiv2022

Developmental changes in cerebral NAD and neuroenergetics of an antioxidant compromised mouse model of schizophrenia

Defects in essential metabolic regulation for energy supply, increased oxidative stress promoting excitatory/inhibitory imbalance and phospholipid membrane dysfunction have been implicated in the pathophysiology of schizophrenia (SZ). The knowledge about the developmental trajectory of these key pathophysiological components and their interplay is important to develop new preventive and treatment strategies. However, this assertion is so far limited. To investigate the developmental regulations of these key components, we assessed, for the first time, in vivo redox state from the oxidized (NAD+) and reduced (NADH) form of Nicotinamide Adenine Dinucleotide (NAD), energy and membrane metabolites, neurotransmitters ({gamma}-aminobutyrate and glutamate) by 31P and 1H MRS during the neurodevelopment of a SZ animal model with genetically compromised glutathione synthesis (gclm-KO mice). When compared to age-matched wild type (WT), an increase in NAD+/NADH redox ratio was found in gclm-KO mice until early adulthood, followed by a decrease in full adults as observed in patients. Especially, in early postnatal life (P20, corresponding to childhood), levels of several metabolites were altered in gclm-KO mice, including NAD+, ATP, phosphocreatine, intracellular pH, glutamine + glutamate and membrane phospholipids components, suggesting an interactive compensation for redox dysregulation between NAD, energy metabolism, and neurotransmission. The identified temporal neurometabolic regulations provide insights in preventive treatment targets for at-risk individuals, and other neurodevelopmental disorders involving oxidative stress and energetic dysfunction.

neuroscience↗

bioRxiv2022

Glutathione in the nucleus accumbens regulates motivation to exert reward-incentivized effort

Emerging evidence is implicating mitochondrial function and metabolism in the nucleus accumbens in motivated performance. However, the brain is vulnerable to excessive oxidative insults resulting from neurometabolic processes and whether antioxidant levels in the nucleus accumbens contribute to motivated performance is not known. Here, we identify a critical role for glutathione (GSH), the most important endogenous antioxidant in the brain, in motivation. Using proton magnetic resonance spectroscopy (1H-MRS) at ultra-high field in both clinical and preclinical populations, we establish that higher accumbal GSH levels are highly predictive of better, and particularly steady performance over time in effort-related tasks. Causality was established in preclinical in vivo experiments that, first, showed that down-regulating GSH levels through micro-injections of the GSH synthesis inhibitor buthionine sulfoximine in the nucleus accumbens impaired effort-based reward-incentivized performance. In addition, systemic treatment with the GSH precursor N-acetyl-cysteine (NAC) increased accumbal GSH levels and led to improved performance, potentially mediated by a cell-type specific shift in glutamatergic inputs to accumbal medium spiny neurons. Our data indicate a close association between accumbal GSH levels and individuals capacity to exert reward-incentivized effort over time. They also suggest that improvement of accumbal antioxidant function may be a feasible approach to boost motivation.

neuroscience↗

bioRxiv2021

Metabolic and transcriptomic profiles of glioblastoma invasion revealed by comparisons between patients and corresponding orthotopic xenografts in mice

The invasive behavior of glioblastoma, the most aggressive primary brain tumor, is considered highly relevant for tumor recurrence. However, the invasion zone is difficult to visualize by Magnetic Resonance Imaging (MRI) and is protected by the blood brain barrier, posing a particular challenge for treatment. We report biological features of invasive growth accompanying tumor progression and invasion based on associated metabolic and transcriptomic changes observed in patient derived orthotopic xenografts (PDOX) in the mouse and the corresponding patients tumors. The evolution of metabolic changes, followed in vivo longitudinally by 1H-Magnetic Resonance Spectroscopy (MRS) at ultra-high field, reflected growth and the invasive properties of the human glioblastoma transplanted into the brains of mice (PDOX). Comparison of MRS derived metabolite signatures, reflecting temporal changes of tumor development and invasion in PDOX, revealed high similarity to spatial metabolite signatures of combined multi-voxel MRS analyses sampled across different areas of the patients tumors. Pathway analyses of the transcriptome associated with the metabolite profiles of the PDOX, identified molecular signatures of invasion, comprising extracellular matrix degradation and reorganization, growth factor binding, and vascular remodeling. Specific analysis of expression signatures from the invaded mouse brain, revealed extent of invasion dependent induction of immune response, recapitulating respective signatures observed in glioblastoma. Integrating metabolic profiles and gene expression of highly invasive PDOX provided insights into progression and invasion associated mechanisms of extracellular matrix remodeling that is essential for cell-cell communication and regulation of cellular processes. Structural changes and biochemical properties of the extracellular matrix are of importance for the biological behavior of tumors and may be druggable. Ultra-high field MRS reveals to be suitable for in vivo monitoring of progression in the non-enhancing infiltration zone of glioblastoma.

cancer biology↗

bioRxiv2021

Automated, high-accuracy, remote measurement of heart rate

Arrhythmia is a marked symptom of many cardiovascular diseases (CVDs). The accurate and timely detection of heart rate can greatly reduce the harm of arrhythmia to people. However, it is still a challenge to robustly and remotely measure heart rate in daily life due to the changing environmental conditions during measurement, such as the varying light intensity, the movement of people, and the uncertain distance between the sensor to people. In this study, we propose a method to accurately measure human heart rate within a distance of 4.5 meters under different light intensities by simply using a surveillance camera. After a 20-second color video of a persons hand is captured by the camera, a method based on the Fast Fourier Transform (FFT) algorithm is designed to extract the blood volume pulse wave to calculate the heart rate. According to the comparison between the real heart rate and results measured by electrocardiography (ECG), the proposed method achieves an accuracy of 95.8% when the measurement is performed within a distance of 4.5 meters and 90% when within 5.0 meters. Our experiments show that when the illuminance varies between 100-1000 lux (lighting level indoor), we still get the correct results. Our experiments also demonstrate that the proposed method accurately obtain heart rate even when the light intensity is below 32 lux (300-500 lux in a workplace environment). The methods strong adaptability to changing environmental conditions makes it applicable to many scenarios, such as homes of the elderly, classrooms, and other public spaces.

physiology↗

bioRxiv2021

A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines

The human genome contains more than 200,000 gene isoforms. However, different isoforms can be highly similar, and with an average length of 1.5kb remain difficult to study with short read sequencing. To systematically evaluate the ability to study the transcriptome at a resolution of individual isoforms we profiled 5 human cell lines with short read cDNA sequencing and Nanopore long read direct RNA, amplification-free direct cDNA, PCR-cDNA sequencing. The long read protocols showed a high level of consistency, with amplification-free RNA and cDNA sequencing being most similar. While short and long reads generated comparable gene expression estimates, they differed substantially for individual isoforms. We find that increased read length improves read-to-transcript assignment, identifies interactions between alternative promoters and splicing, enables the discovery of novel transcripts from repetitive regions, facilitates the quantification of full-length fusion isoforms and enables the simultaneous profiling of m6A RNA modifications when RNA is sequenced directly. Our study demonstrates the advantage of long read RNA sequencing and provides a comprehensive resource that will enable the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

genomics↗

bioRxiv2020

A negative feedback model to explain regulation of SARS-CoV-2 replication and transcription

BackgroundCoronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription mechanisms of SARS-CoV-2 has recently emerged, their regulation remains unclear. ResultsBased on reanalysis of public data, we propose a negative feedback model to explain the regulation of replication and transcription in--but not limited to--SARS-CoV-2. The key step leading to new discoveries was the identification of the cleavage sites of nsp15--an RNA uridylate-specific endoribonuclease, encoded by CoVs. According to this model, nsp15 regulates the synthesis of subgenomic RNAs (sgRNAs) and genomic RNAs (gRNAs) by cleaving transcription regulatory sequences in the body. The expression level of nsp15 determines the relative proportions of sgRNAs and gRNAs, which in turn change the expression level of nps15 to reach equilibrium between the replication and transcription of CoVs. ConclusionsThe replication and transcription of CoVs are regulated by a negative feedback mechanism that influences the persistence of CoVs in hosts. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, and provide new clues for future studies. One important clue is that nsp15 may be an important and ideal target for the development of drugs (e.g. uridine derivatives) against CoVs.

bioinformatics↗

bioRxiv2020

AERON: Transcript quantification and gene-fusion detection using long reads

Single-molecule sequencing technologies have the potential to improve measurement and analysis of long RNA molecules expressed in cells. However, analysis of error-prone long RNA reads is a current challenge. We present AERON for the estimation of transcript expression and prediction of gene-fusion events. AERON uses an efficient read-to-graph alignment algorithm to obtain accurate estimates for noisy reads. We demonstrate AERON to yield accurate expression estimates on simulated and real datasets. It is the first method to reliably call gene-fusion events from long RNA reads. Sequencing the K562 transcriptome, we used AERON and found known as well as novel gene-fusion events.

bioinformatics↗

bioRxiv2019

Identifying neoantigens for cancer vaccines by personalized deep learning of individual immunopeptidomes

Tumor-specific neoantigens play the main role for developing personal vaccines in cancer immunotherapy. We propose, for the first time, a personalized de novo sequencing workflow to identify HLA-I and HLA-II neoantigens directly and solely from mass spectrometry data. Our workflow trains a personal deep learning model on the immunopeptidome of an individual patient and then uses it to predict mutated neoantigens of that patient. This personalized learning and mass spectrometry-based approach enables comprehensive and accurate identification of neoantigens. We applied the workflow to datasets of five melanoma patients and substantially improved the accuracy and identification rate of de novo HLA peptides by 14.3% and 38.9%, respectively. This subsequently led to the identification of 10,440 HLA-I and 1,585 HLA-II new peptides that were not presented in existing databases. Most importantly, our workflow successfully discovered 17 neoantigens of both HLA-I and HLA-II, including those with validated T cell responses and those novel neoantigens that had not been reported in previous studies.

bioinformatics↗

bioRxiv2019

Integrated multi-omics analysis to study the effects of simulated weightlessness on rhesus macaques (Macaca mulatta)

Safety and health of astronauts in space is one of the most important aspects of space exploration, however, the genomic research about how a weightless space can affect astronauts health was limited. In this study, we sequenced 25 transcriptomic, 42 metabolomic and 35 metagenomic data of 15 rhesus macaques (Macaca mulatta) spanning seven simulated weightlessness experiment stages. We identified 84 genes, 1911 features and 55 genera which are significantly changed in blood and muscle, hippocampal region, dorsomedial prefrontal cortex as well as fecal, respectively. Furthermore, performing the integrated analysis of three omics data, we found several pathways which were related to regulation of immune system process, glucose uptake, reaction to threatens, neurotoxic and bone or joints damage, such as tyrosine metabolism and tryptophan metabolism. Our results provided an initial attempt of "multi-omics" approaches which combined transcriptomics, metabolomics and metagenomics to illustrate some molecular clues for simulated weightlessness effect on the rhesus macaques and potential sight of microgravitys effect on astronauts health.

immunology↗