bioRxiv Science⌕ Search

Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 721 records · Page 40Linked to original sources

Systems Analysis of de novo Mutations in Congenital Heart Diseases Identified a Molecular Network in Hypoplastic Left Heart Syndrome

Congenital heart diseases (CHD) are a class of birth defects affecting [~]1% of live births. These conditions are hallmarked by extreme genetic heterogeneity, and therefore, despite a strong genetic component, only a very handful of at-risk loci in CHD have been identified. We herein introduced systems analyses to uncover the hidden organization on biological networks of genomic mutations in CHD, and leveraged network analysis techniques to integrate the human interactome, large-scale patient exomes, the fetal heart spatial transcriptomes, and single-cell transcriptomes of clinical samples. We identified a highly connected network in CHD where most of the member proteins had previously uncharacterized functions in regulating fetal heart development. While genes on the network displayed strong enrichment for heart-specific functions, a sub-group, active specifically at early developmental stages, also regulates fetal brain development, thereby providing mechanistic insights into the clinical comorbidities between CHD and neurodevelopmental conditions. At a small scale, we experimentally verified previously uncharacterized cardiac functions of several novel proteins employing cellular assays and gene editing techniques. At a global scale, our study revealed developmental dynamics of the identified CHD network and observed the strongest enrichment for pathogenic mutations in the network specific to hypoplastic left heart syndrome (HLHS). Our single-cell transcriptome analysis further identified pervasive dysregulation of the network in cardiac endothelial cells and the conduction system in the HLHS left ventricle. Taken together, our systems analyses identified novel factors in CHD, revealed key molecular mechanisms in HLHS, and provides a generalizable framework readily applicable to studying many other complex diseases.

systems biology↗

Cable-free brain imaging with miniature wireless microscopes

The invention of the miniaturized microscope has enabled neuroscientists to investigate neural mechanisms in freely moving mice. A lot of efforts have been made to optimize performance of the miniaturized microscope. However, the tethered cables limit the ability of mini-microscope systems to record neural activity from multiple mice simultaneously. Here, we present a wireless mini-microscope (wScope) that enables both real-time remote control and data preview during animal behavior; this design also supports simultaneous recording from up to 8 mice. The wScope has a mass of 2.7 g and a maximum frame rate of 25 Hz at 750 m by 450 m field of view with 1.8 m resolution. We validated the wScopes in video-recording of the cerebral blood flow (CBF) and the activity of neurons in the primary visual cortex (V1) of different mice. The wScope provides a powerful tool for brain imaging of free moving animals, including large primates, in their much larger spaces and more naturalistic environments.

neuroscience↗

A small H2O-soluble ingredient of royal jelly lower cholesterol levels in liver cells by suppressing squalene epoxidase

Excessive cholesterol in the liver is harmful for our health and may cause many diseases, such as fatty liver disease. Many studies in human and animal models have reported that royal jelly (RJ) can be used to treat atherosclerosis. However, the real mechanisms behind this action is unclear. In this study, we investigated the effectivity of RJ on gene expression of squalene epoxidase (SE) a major enzyme involved in cholesterol biosynthesis in HepG2 cells. We found that the expression of SE was decreased in response to RJ treatment. We also found that the origin of the RJ affected its strength. To find out the active ingredient of RJ in cholesterol suppression, we separated RJ into two parts based on the molecular weights using ultrafiltration membrane. We found that the fraction < 10kDa from RJ had comparable effect on SE expression, especially its water-soluble part. Taken together, we think RJ suppresses cholesterol by decreasing SE gene expression in liver. The active ingredient of RJ in this action is < 10kDa in water-soluble form.

cell biology↗

Thinking like a structural biologist: A pocket-based 3D molecule generative model fueled by electron density

We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets including kinase (HPK1), protease (Covid19-3CL), and nuclear receptor (VDR), and evaluated with a reference dataset composed of over 8,000 compounds that have their activities reported in the literature. The evaluation examined the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can reproduce classical active compounds and can also generate novel molecules with similar binding modes as active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create.

bioinformatics↗

Angelman syndrome patient neuron screen identifies a potent and selective clinical ASO targeting UBE3A-ATS with long lasting effect in cynomolgus monkey

Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by the loss of neuronal E3 ligase UBE3A with no available treatment. Restoring UBE3A levels via downregulation of the paternally cis-acting long non-coding antisense transcript (UBE3A-ATS) is a potential disease modifying. Developing molecules targeting human UBE3A-ATS is challenging because it is expressed only in neurons and lacks animal species sequence conservation. To overcome this, we performed a library screen of locked-nucleic acid (LNA)-modified antisense oligonucleotides (ASOs) on AS patient-derived neurons, identifying initial sequences. Further optimization led to the identification of the ASO, RO7248824, which selectively and potently reduces UBE3A-ATS, while concomitantly upregulating the UBE3A mRNA and protein. These properties held true in both human AS patient- and neurotypical-, as well as cynomolgus monkey-derived neurons. In vivo use of tool molecules in wild-type (WT) and AS Ube3am-/p+ mice, revealed a steep relationship between UBE3A-ATS knock-down and UBE3A mRNA/protein upregulation, whereby an almost 90% downregulation was needed to achieve a 50% upregulation, respectively. This relationship was confirmed in cynomolgus monkeys. Whereby, repeated lumbar intrathecal administrations of RO7248824 was well tolerated without adverse in-life effects or tissue pathology and produced a robust, long lasting (up to 3 months) paternal reactivation of UBE3A mRNA/protein across key monkey brain regions. Our results demonstrate that AS human pluripotent stem cell neurons serve as an excellent translational tool and furthermore LNA-modified ASOs exhibit excellent drug-like properties. Sustained efficacy translated to infrequent, intrathecal dosing and serves as the basis for the ongoing clinical development of RO7248824 for AS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/495066v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1c2a97eorg.highwire.dtl.DTLVardef@1059954org.highwire.dtl.DTLVardef@95835aorg.highwire.dtl.DTLVardef@1e2adea_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO From AS patient blood to a neuronal screen, identifies clinical ASO with excellent in vivo properties. (1) Patients were recruited. (2) Whereby blood was reprogrammed into hIPSC and subsequently differentiated into neurons. (3) ASOs were designed and screened on human neurons to downregulate the UBE3A-ATS likely via directed RNase H Cleavage of Nascent Transcripts. (4a) RO7248824 was identified that potently and selective reduces UBE3A-ATS, concomitantly with upregulating the UBE3A sense transcript and protein which was used for in vitro pk/pd. (4b) In parallel tool murine ASO were used demonstrate in vivo POC.(5) Pivotal nonhuman primate studies to monitor safety and predict the human dose. (6) RO7248824 is in AS clinical trial. C_FIG One Sentence SummaryFrom angelman syndrome human neuron screen to cynomolgus monkey proof of concept identifies the clinical molecule RO7248824

neuroscience↗

Microbial Risk Score for Capturing Microbial Characteristics, Integrating Multi-omics Data, and Predicting Disease Risk

BackgroundWith the rapid accumulation of microbiome-wide association studies, a great amount of microbiome data are available to study the microbiomes role in human disease and advance the microbiomes potential use for disease prediction. However, the unique features of microbiome data hinder its utility for disease prediction. MethodsMotivated from the polygenic risk score framework, we propose a microbial risk score (MRS) framework to aggregate the complicated microbial profile into a summarized risk score that can be used to measure and predict disease susceptibility. Specifically, the MRS algorithm involves two steps: 1) identifying a sub-community consisting of the signature microbial taxa associated with disease, and 2) integrating the identified microbial taxa into a continuous score. The first step is carried out using the existing sophisticated microbial association tests and pruning and thresholding method in the discovery samples. The second step constructs a community-based MRS by calculating alpha diversity on the identified sub-community in the validation samples. Moreover, we propose a multi-omics data integration method by jointly modeling the proposed MRS and other risk scores constructed from other omics data in disease prediction. ResultsThrough three comprehensive real data analyses using the NYU Langone Health COVID-19 cohort, the gut microbiome health index (GMHI) multi-study cohort, and a large type 1 diabetes cohort separately, we exhibit and evaluate the utility of the proposed MRS framework for disease prediction and multi-omics data integration. In addition, the disease-specific MRSs for colorectal adenoma, colorectal cancer, Crohns disease, and rheumatoid arthritis based on the relative abundances of 5, 6, 12, and 6 microbial taxa respectively are created and validated using the GMHI multi-study cohort. Especially, Crohns disease MRS achieves AUCs of 0.88 ([0.85-0.91]) and 0.86 ([0.78-0.95]) in the discovery and validation cohorts, respectively. ConclusionsThe proposed MRS framework sheds light on the utility of the microbiome data for disease prediction and multi-omics integration, and provides great potential in understanding the microbiomes role in disease diagnosis and prognosis.

microbiology↗

massDatabase: utilities for the operation of the public compound and pathway database

SummaryOne of the major challenges in LC-MS data (metabolome, lipidome, and exposome) is converting many metabolic feature entries to biological function information, such as metabolite annotation and pathway enrichment, which are based on the compound and pathway databases. Multiple online databases have been developed, containing lots of information about compounds and pathways. However, there is still no tool developed for operating all these databases for biological analysis. Therefore, we developed massDatabase, an R package that operates the online public databases and combines with other tools for streamlined compound annotation and pathway enrichment analysis. massDatabase is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the users to leverage all the online public databases for biological function mining. A detailed tutorial and a case study are provided in the Supplementary Materials. Availability and implementationhttps://massdatabase.tidymass.org/. Contactshenxt@stanford.edu and mpsnyder@stanford.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Invigorating human MSCs for transplantation therapy via Nrf2/DKK1 co- stimulation in a mice acute-on-chronic liver failure model

Boosting stem cell resilience against an extrinsically harsh recipient environment is critical to therapeutic efficiency of stem cell-based transplantation innovations in liver disease contexts. We aimed to establish the efficacy of a transient plasmid-based preconditioning strategy to boost mesenchymal stromal cells (MSCs) capacity for anti-inflammation/antioxidant defense and paracrine actions on recipient hepatocytes. In MSCs, the master antioxidant regulator Nrf2 was found to bind directly to the antioxidant response element in the DKK1 promoter region. Activation of Nrf2 and DKK1 enhanced the anti-stress capacities of MSCs in vitro. In an acute-on-chronic liver failure (ACLF) murine model, transient co-overexpression of Nrf2 and DKK1 via plasmid transfection markedly improved MSC resilience against inflammatory and oxidative assaults, boosted MSC transplantation efficacy and promoted recipient liver regeneration because of a shift from the activation of the anti-regenerative IFN-{gamma}/STAT1 pathway to the pro-regenerative IL-6/STAT3 pathway in the liver. Moreover, specific ablation of DKK1 receptor CKAP4 but not LRP6 in recipient hepatocytes nullified therapeutic benefits from MSC transplantation. In long-term observations, tumorigenicity was undetected in mice following transplantation of such transiently preconditioned MCSs. In conclusion, co-stimulation of Nrf2/DKK1 signaling decisively and safely improves the efficacy of human MSC-based therapies in mouse ACLF models through apparently CKAP4-dependent paracrine mechanisms.

molecular biology↗

Spatiotemporal heterogeneity and the long-term impact of meteorological , environmental and socio-economic factors of scrub typhus in China from 2012 to 2018

Large-scale outbreaks of scrub typhus combined with the emergence of this vector-borne rickettsiosis in new areas indicate that this disease remains seriously neglected. This study aimed to explore the long-term changes and regional leading factors of scrub typhus in China, so as to provide fresh insights for the prevention and control of this disease. In this study, a Bayesian space-time hierarchical model (BSTHM) was used to identify the long-term spatiotemporal heterogeneity of scrub typhus and quantify the association between meteorological factors and scrub typhus in southern and northern China from 2012 to 2018. GeoDetector model was used to quantify the dominant forces of environmental and socioeconomic factors in the Northern and the Southern China. Scrub typhus often appeared in summer and autumn (June to November), and epidemically peaked in October, with obvious temporal seasonality. Spatially, the hot spots (high-risk regions) were concentrated in the south, on the contrary the cold spots (low-risk regions) in the north. In addition, the main meteorological factor, average temperature, gave a significant impact in both areas. The average temperature increased by 1 {degrees}C, resulting in a decrease of 1.10% in southern China and an increase of 0.96% in northern China in the risk of scrub typhus. The determinant environmental and socio-economic factors of scrub typhus in the two areas were altitude and per capita GDP, with q-values of 0.91 and 0.87, respectively. Meteorological, environmental and socio-economic factors had a significant impact on the distribution of scrub typhus, with obvious seasonality and spatial heterogeneity. This study provides helpful suggestions and basis for reasonably allocating resources and controlling the occurrence of scrub typhus. Author summaryScrub typhus is a natural-focus disease caused by the bite of chigger mite larval. In this study, we use BSTHM to capture the overall temporal trend and spatial hot spots of scrub typhus, and quantify the relationship between the disease and major meteorological factors. Meanwhile, Geodetector model was used to quantify the influence of other potential risk factors and estimate the spatio-temporal heterogeneity of scrub typhus. The results showed that scrub typhus had significant seasonality, with a q value of 0.52, and spatial heterogeneity, with a q-value of 0.64. Scrub typhus mainly occurred in summer and autumn, and high-risk areas were mainly distributed in southern China (Yunnan, Hainan and Guangdong). These heterogeneity were closely related to the vector and host. Whether in the South or the north, scrub typhus was closely related to risk factors such as temperature, per capita GDP, NDVI, altitude and the percentage of children aged 0-14. These results suggest that the relevant departments should strengthen the monitoring of the ecological environment, the host and vector of Orientia tsutsugamushi, and strengthen the risk awareness, so as to prevent and control the possible increased risk of scrub typhus under these meteorological, environmental and socio-economic conditions. Considering the differences in different regions, resources should be allocated reasonably.

ecology↗

The pentatricopeptide repeat protein MTSF3 is required for nad2 mRNA stability and embryogenesis in Arabidopsis

Gene expression in plant mitochondria is predominantly governed at the post-transcriptional level and relies mostly on nuclear-encoded proteins. However, the involved protein factors and the underlying molecular mechanisms are still not well understood. In this study, we report the function of the mitochondrial stability factor 3 (MTSF3) protein and we show that it is essential for accumulation of the mitochondrial nad2 transcript in Arabidopsis and not for the splicing of nad2 intron 2, as recently proposed (Marchetti et al., 2020). The MTSF3 gene encodes a pentatricopeptide repeat protein that localizes in the mitochondrion. An MTSF3 null mutation induces embryonic lethality but viable mtsf3 mutant plants could be generated by partial complementation with the developmentally-regulated ABSCISIC ACID INSENSITIVE3 promoter. Genetic analyses reveal that mtsf3 rescued plants display growth retardation due to the specific destabilization of a nad2 precursor transcript bearing exons 3 to 5. Biochemical data demonstrate that MTSF3 protein specifically binds to the 3-terminus of nad2. The destabilization of nad2 mRNA induces a significant decrease in complex I assembly and activity, and an overexpression of the alternative respiratory pathway. Our results support that the MTSF3 protein protects nad2 transcript from degradation by mitochondrial exoribonucleases by binding to its 3 extremity.

plant biology↗

Enhancing the anti-tumor efficacy of Bispecific T cell engagers via cell surface glycocalyx editing

Bispecific T-cell engager (BiTE)-based cancer therapies that activate the cytotoxic T cells of a patients own immune system have gained momentum with the recent FDA approval of Blinatumomab for treating B cell malignancies. However, this approach has had limited success in targeting solid tumors. Here, we report the development of BiTE-sialidase fusion proteins that enhance tumor cell susceptibility to BiTE-mediated cytolysis by T cells via targeted desialylation at the BiTE-induced T cell-tumor cell interface. Targeted desialylation results in better immunological synapse formation, T-cell activation and effector function. As a result, BiTE-sialidase fusion proteins show remarkably increased efficacy in inducing T-cell-dependent tumor cell cytolysis in response to target antigens compared to the parent BiTE molecules alone. This enhanced function is seen both in vitro and in in vivo xenograft and syngeneic solid tumor mouse models. Our findings highlight BiTE-sialidase fusion proteins as promising candidates for the development of next-generation bispecific T-cell engaging molecules for cancer immunotherapy.

cancer biology↗

Epitranscriptomic Modification of MicroRNA Increases Atherosclerosis Susceptibility

Emerging evidence indicates that oxidative stress causes the hydroxylation of guanine (G) to generate 8-oxo-7,8-dihydro guanosine (8OH-G) in microRNAs (miRs), which induces the guanine-to-uracil (G-to-U) transversion and thus changes the miR targetomes. However, whether and how the 8OH-G-modified miRs are involved in vascular endothelial dysfunction and atherogenesis were unexplored. Using 8OH-G crosslinking immunoprecipitation miR sequencing (8OH-G CLIP-miR-seq), we found that 8OH-G miR-483 were among the most enriched 8OH-G miR species in ECs induced by ox-LDL. Transcriptomic profiling by RNA-seq indicated that the G-to-U transversion of miR-483 altered the original mRNA targeting efficacy and allows 8OH-G miR-483 to recognize new mRNA target sites. A reduced ratio of 8OH-G miR-483 to miR-483 in lung ECs was found in the endothelial-specific miR-483 transgenic (EC-miR-483 Tg) mice. Moreover, reduction of atherosclerosis was significant in EC-miR-483 Tg mice administrated AAV8-PCSK9 and fed an atherogenic diet. In situ miR hybridization revealed an increased 8OH-G miR-483 level in the intima of human atherosclerotic arteries. Collectively, this study demonstrates that the redox burden incurred by cardiovascular risk factors is a culprit of the miR-483 to 8OH-G miR-483 transversion. Such epitranscriptomic modification of miR-483 causes endothelial dysfunction and increases atherosclerosis susceptibility via its targetomes shift.

molecular biology↗

Accurate speech decoding requires high-resolution neural interfaces

Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One promising solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed novel, high-resolution, micro-electrocorticographic (ECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57x higher spatial resolution and 48% higher signal-to-noise ratio compared to standard invasive recordings. This increased signal quality improved phoneme decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show for the first time that ECoG can enable high-quality speech decoding, demonstrating its ability to improve neural interfaces for neural speech prostheses.

neuroscience↗

A comprehensive investigation of statistical and machine learning approaches for predicting complex human diseases on genomic variants

BackgroundQuantifying an individuals risk for common diseases is an important goal of precision health. The polygenic risk score (PRS), which aggregates multiple risk alleles of candidate diseases, has emerged as a standard approach for identifying high-risk individuals. A variety of tools have been developed to implement PRS. However, benchmarks for comparatively evaluating the performance of these different methods and for assessing their potential to guide future clinical applications are lacking. ResultsWe systematically validated and compared thirteen statistical methods, five machine learning models and two ensemble models using simulated data, twenty-two common diseases with internal training sets and four diseases with external summary statistics from the UK Biobank resource. The effects of disease heritability, single nucleotide polymorphism (SNP) effect size and sample size are evaluated using simulated data. We also investigated the correlations between methods and their standard deviations of different diseases. ConclusionsIn general, statistical methods outperform machine learning models, and ensemble models, such as Super Learner, generally perform the best for most situations. We observed the correlations were relatively high if the methods were from the same category and the external summary statistics from large cohort GWAS could decrease the standard deviation of method correlations. By varying three factors in the simulated data, we also identified that disease heritability had a strong effect on the predictive performance of individual methods. Both the number and effect sizes of risk SNPs are important; and while sample size strongly influences the performance of machine learning models, but not statistical methods.

bioinformatics↗

Multiple omic investigations of freeze tolerance adaptation in the aquatic ectothermic vertebrate, the Amur sleeper

Freeze tolerance is an amazing overwintering strategy that enables ectotherms to occupy new niches and survive in cold climates. However, the genetic basis underpinning this ecologically relevant adaptation is largely unknown. Amur sleeper is the only known freeze-tolerant fish species that can overwinter with its entire body frozen in ice. Here, we sequenced the chromosome-level genome of the Amur sleeper and performed comparative genomic, transcriptomic, and metabolomic analyses to investigate this remarkable adaptation. Phylogenetic analyses showed that the Amur sleeper diverged from its close relative with no cold hardiness about 15.07 million years ago and revealed two unusual population expansions during the glacial epochs. Integrative omics data identified a synchronous regulation of genes and metabolites involved in hypometabolism and cellular stress response, and several related genes showed strong evidence of accelerated evolution and positive selection. Potential evolutionary innovations that might aid in freezing survival were found to be associated with the dynamic rearrangement of the cytoskeleton to maintain cell viability, redistribution of water and cryoprotectants to limit cell volume reduction, and inhibition in nerve activity to facilitate dormancy, demonstrating a coordinated evolution for this complex adaptation. Overall, our work provides valuable resources and opportunities to unveil the genetic basis of freeze tolerance adaptation in ectothermic vertebrates.

evolutionary biology↗

Resetting of H3K4me2 during mammalian parental-to-zygote transition

Upon sperm and oocyte fertilization, the embryo undergoes drastic histone modification reprogramming during pre-implantation development. In this study, we investigated the erasure and re-establishment of H3K4me2 in mouse GV, MII, and embryos using an improved approach called Cleavage Under Targets and Release Using Nuclease (CUT&RUN) with high-throughput sequencing. We found that H3K4me2 extensively occurs as a non-canonical pattern in mouse GV oocytes and early embryos, and parental H3K4me2 was erased by maternal LSD2 during forming the pronucleus in the zygote. The H3K4me2 was erased from GV to MII oocyte and was re-established in the late two-cell stage, removing this epigenetic burden is crucial for ZGA. We then revealed the H3K4me2 locates widespread in the CpG-rich and hypomethylated regulatory regions in the four-cell stage, and the eight-cell stage, but dramatic changes occurred in the inner cell mass (ICM) in mouse embryos. Then, these CpG-rich H3K4me2 regulatory regions became either activated or repressed. To summarize, in this study, we elucidated the pattern of H3K4me2 transition from parent to zygote and H3K4me2 profile during early embryo development. Our findings might provide deeper insights into epigenetic reprogramming during early development and in vitro fertilization in mammalian. HighlightsO_LIH3K4me2 showed differential patterns in sperms and oocytes; non-canonical pattern occurred in GV oocytes, but canonical patterns were found in the sperm cells of mice. C_LIO_LIThe H3K4me2 peaks of GV were almost erased in MII oocytes and reconstructed after the major ZGA occurred. Maternal LSD2 was found to regulate H3K4me2 resetting during the parental-to-zygote transition. H3K4me2 may impose an "Epigenetic Burden" on ZGA. C_LIO_LINon-canonical H3K4me2 pattern was found in mammalian embryos, however, pervasive H3K4me2 in CpG-rich regulatory regions were found in four-cell and eight-cell stage embryos; The CpG-rich H3K4me2 regulatory regions were either activated or repressed in the ICM. C_LI

genetics↗

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topology

The specific functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome in a single experiment. Biochemical and imaging-based follow-up studies demonstrate that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, establishes a method for concomitant profiling of sub-organelle and membrane proteomes, and provides a resource for mitochondrial spatial biology.

systems biology↗

Deep Learning-based Pseudo-Mass Spectrometry Imaging Analysis for Precision Medicine

Liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics provides systematic profiling of metabolic. Yet its applications in precision medicine (disease diagnosis) have been limited by several challenges, including metabolite identification, information loss, and low reproducibility. Here, we present the deepPseudoMSI project (https://www.deeppseudomsi.org/), which converts LC-MS raw data to pseudo-MS images and then processes them by deep learning for precision medicine, such as disease diagnosis. Extensive tests based on real data demonstrated the superiority of deepPseudoMSI over traditional approaches and the capacity of our method to achieve an accurate individualized diagnosis. Our framework lays the foundation for future metabolic-based precision medicine.

bioinformatics↗