Biology subjects

Chen, X.

Publications and source records attributed to Chen, X..

At least 793 records · Page 44Linked to original sources

bioRxiv2023

Ferredoxin 1 is essential for embryonic development and lipid homeostasis

Mammalian ferredoxin 1 and 2 (FDX1/2) belong to an evolutionary conserved family of iron-sulfur cluster containing proteins and act as electron shutters between ferredoxin reductase (FDXR) and numerous proteins involved in critical biological pathways. FDX1 is involved in biogenesis of steroids and bile acids, Vitamin A/D metabolism, and lipoylation of tricarboxylic acid (TCA) cycle enzymes. FDX1 has been extensively characterized biochemically but its role in physiology and lipid metabolism has not been explored. In this study, we generated Fdx1-deficient mice and showed that knockout of both alleles of the Fdx1 gene led to embryonic lethality. We also showed that like Fdxr+/- mice, Fdx1+/- mice had a shorter life span and were prone to steatohepatitis. However, unlike Fdxr+/- mice, Fdx1+/- mice were not prone to spontaneous tumors. Additionally, we showed that FDX1 deficiency led to lipid droplet accumulation possibly via the ABCA1-SREBP1/2 pathway. Specifically, untargeted lipidomic analysis showed that FDX1 deficiency led to alterations in several classes of lipids, including cholesterol, triacylglycerides, acylcarnitines, ceramides, phospholipids and lysophospholipids. Taken together, our data indicate that FDX1 is essential for mammalian embryonic development and lipid homeostasis at both cellular and organismal levels.

cancer biology↗

bioRxiv2023

PRO-LDM: Protein Sequence Generation with Conditional Latent Diffusion Models

AbstractsDeep learning-driven protein design holds enormous potential despite the complexities in sequences and structures. Recent developments in diffusion models yielded success in structure design, but awaits progress in sequence design and are computationally demanding. Here we present PRO-LDM: an efficient framework combining design fidelity and computational efficiency, utilizing the diffusion model in latent space to design proteins with property tuning. The model employs a joint autoencoder to capture latent variable distributions and generate meaningful embeddings from sequences. PRO-LDM (1) learns representations from biological features in natural proteins at both amino-acid and sequence level; (2) generates native-like new sequences with enhanced diversity; and (3) conditionally designs new proteins with tailored properties or functions. The out-of-distribution design enables sampling notably different sequences by adjusting classifier guidance strength. Our model presents a feasible pathway and an integratable tool to extract physicochemical and evolutionary information embedded within primary sequences, for protein design and optimization.

bioengineering↗

bioRxiv2023

Combined Mek inhibition and Pparg activation Eradicates Muscle Invasive Bladder cancer in a Mouse Model of BBN-induced Carcinogenesis

Bladder cancers (BCs) can be divided into 2 major subgroups displaying distinct clinical behaviors and mutational profiles: basal/squamous (BASQ) tumors that tend to be muscle invasive, and luminal/papillary (LP) tumors that are exophytic and tend to be non-invasive. Pparg is a likely driver of LP BC and has been suggested to act as a tumor suppressor in BASQ tumors, where it is likely suppressed by MEK-dependent phosphorylation. Here we tested the effects of rosiglitazone, a Pparg agonist, in a mouse model of BBN-induced muscle invasive BC. Rosiglitazone activated Pparg signaling in suprabasal epithelial layers of tumors but not in basal-most layers containing highly proliferative invasive cells, reducing proliferation but not affecting tumor survival. Addition of trametinib, a MEK inhibitor, induced Pparg signaling throughout all tumor layers, and eradicated 91% of tumors within 7-days of treatment. The 2-drug combination also activated a luminal differentiation program, reversing squamous metaplasia in the urothelium of tumor-bearing mice. Paired ATAC-RNA-seq analysis revealed that tumor apoptosis was most likely linked to down-regulation of Bcl-2 and other pro-survival genes, while the shift from BASQ to luminal differentiation was associated with activation of the retinoic acid pathway and upregulation of Kdm6a, a lysine demethylase that facilitates retinoid-signaling. Our data suggest that rosiglitazone, trametinib, and retinoids, which are all FDA approved, may be clinically active in BASQ tumors in patients. That muscle invasive tumors are populated by basal and suprabasal cell types with different responsiveness to PPARG agonists will be an important consideration when designing new treatments.

cancer biology↗

bioRxiv2023

Pneumatic Nano-Sieve for CRISPR-based Detection of Drug-resistant Bacteria

The increasing prevalence of antibiotic-resistant bacterial infections, particularly methicillin-resistant Staphylococcus aureus (MRSA), presents a significant public health concern. Timely detection of MRSA is crucial to enable prompt medical intervention, limit its spread, and reduce antimicrobial resistance. Here, we introduce a miniaturized nano-sieve device featuring a pneumatically-regulated chamber for highly efficient MRSA purification from human plasma samples. By using packed magnetic beads as a filter and leveraging the deformability of the nano-sieve channel, we achieve an on-chip concentration factor of 15 for MRSA. We integrated this device with recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas detection system, resulting in an on-chip limit of detection (LOD) of approximately 100 CFU/mL. This developed approach provides a rapid, precise, and centrifuge-free solution suitable for point-of-care diagnostics, with the potential to significantly improve patient outcomes in resource-limited medical conditions.

bioengineering↗

bioRxiv2023

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-{kappa}B regulator IKK{varepsilon}. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKK{varepsilon} implicated by human genetics in risk for SLE.

genetics↗

bioRxiv2023

A vast repertoire of secondary metabolites influences community dynamics and biogeochemical processes in cold seeps

In deep sea cold seeps, diverse microbial communities thrive on the geological seepage of hydrocarbons and inorganic compounds. These chemosynthetically-driven communities are unique in composition, ecology, and biogeochemical activities compared to photosynthetically-driven ecosystems. However, their biosynthetic capabilities remain largely unexplored. Here, we analyzed 81 metagenomes, 33 metatranscriptomes, and seven metabolomes derived from nine globally distributed areas of cold seeps to investigate the secondary metabolites produced by cold seep microbiomes. Cold seep microbiomes encode diverse, abundant, and novel biosynthetic gene clusters (BGCs). Most BGCs are affiliated with understudied bacteria and archaea, including key mediators of methane and sulfur cycling, and multiple candidate phyla. The BGCs encode diverse antimicrobial compounds (e.g. NRPS, PKSs, RiPPs) that potentially shape community dynamics, as well as compounds predicted to influence biogeochemical cycling, such as phosphonates, iron-acquiring siderophores, nitrogenase-protecting glycolipids, and methyl-CoM reductase-modifying proteins. BGCs from key players in cold seeps are widely distributed and highly expressed, with their abundance and expression levels varying with different sediment depths. Numerous unique natural products were detected through untargeted sediment metabolomics, demonstrating a vast, unexplored chemical space and validating in situ expression of the BGCs in cold seep sediments. Overall, these results demonstrate cold seep sediments potentially serve as a reservoir of hidden natural products and provide insights into microbial adaptation in chemosynthetically-driven ecosystems.

microbiology↗

bioRxiv2023

Comprehensive Assessment of Isoform Detection Methods for Third-Generation Sequencing Data

The advancement of Third-Generation Sequencing (TGS) techniques has significantly increased the length of sequencing to several kilobases, thereby facilitating the identification of alternative splicing (AS) events and isoform expressions. Recently, numerous computational methods for isoform detection using long-read sequencing data have been developed. However, there is lack of prior comparative studies that systemically evaluates the performance of these software tools, implemented with different algorithms, under various simulations that encompass potential influencing factors. In this study, we conducted a benchmarking analysis of eleven methods implemented in eight computational tools capable of identifying isoform structures from TGS RNA sequencing data. We evaluated their performances using simulated data, which represented diverse sequencing platforms generated by an in-house simulator, as well as experimental data. Our comprehensive results demonstrate the guided mode of StringTie2 and Bambu achieved the best performance in sensitivity and precision, respectively. This study provides valuable guidance for future research on AS analysis and the ongoing improvement of tools for isoform detection using TGS data.

bioinformatics↗

bioRxiv2023

Accelerated social representational drift in the nucleus accumbens in a model of autism

Impaired social interaction is one of the core deficits of autism spectrum disorder (ASD) and may result from social interactions being less rewarding. How the nucleus accumbens (NAc), as a key hub of reward circuitry, encodes social interaction and whether these representations are altered in ASD remain poorly understood. We identified NAc ensembles encoding social interactions by calcium imaging using miniaturized microscopy. NAc population activity, specifically D1 receptor-expressing medium spiny neurons (D1-MSNs) activity, predicted social interaction epochs. Despite a high turnover of NAc neurons modulated by social interaction, we found a stable population code for social interaction in NAc which was dramatically degraded in Cntnap2-/- mouse model of ASD. Surprisingly, non-specific optogenetic inhibition of NAc core neurons increased social interaction time and significantly improved sociability in Cntnap2-/- mice. Inhibition of D1- or D2-MSNs showed reciprocal effects, with D1 inhibition decreasing social interaction and D2 inhibition increasing interaction. Therefore, social interactions are preferentially, specifically and dynamically encoded by NAc neurons and social representations are degraded in this autism model.

neuroscience↗

bioRxiv2023

DHX36 binding induces RNA structurome remolding and regulates RNA abundance via m6A/YTHDF1

RNA structure constitutes a new layer of gene regulatory mechanisms. RNA binding proteins can modulate RNA secondary structures, thus participating in post-transcriptional regulation. The DEAH-box helicase 36 (DHX36) is known to bind and unwind RNA G-quadruplex (rG4) structure but the transcriptome-wide RNA structure remodeling induced by DHX36 binding and the impact on RNA fate remain poorly understood. Here, we investigate the RNA structurome alteration induced by DHX36 depletion. Our findings reveal that DHX36 binding induces structure remodeling not only at the localized binding sites but also on the entire mRNA transcript most pronounced in3UTR regions. DHX36 binding increase structural accessibility at 3UTRs which is correlated with decreased post-transcriptional mRNA abundance. Further analyses and experiments uncover that DHX36 binding sites are enriched for N6-methyladenosine (m6A) modification and YTHDF1 binding; and DHX36 induced structural change may facilitate YTHDF1 binding to m6A sites leading to RNA degradation. Altogether, our findings uncover the structural remodeling effect of DHX36 binding and its impact on RNA abundance through regulating m6A dependent YTHDF1 binding.

molecular biology↗

bioRxiv2023

Characterization of N-glycosylation and its Functional Role in SIDT1-Mediated RNA Uptake

The mammalian SID-1 transmembrane family members, SIDT1 and SIDT2, are multi-pass transmembrane proteins that mediate the cellular uptake and intracellular trafficking of nucleic acids, playing important roles in the immune response and tumorigenesis. Previous work has suggested that human SIDT1 and SIDT2 are N-glycosylated, but the precise site-specific N-glycosylation information and its functional contribution remain unclear. In this study, we employ high-resolution liquid chromatography tandem mass spectrometry to comprehensively map the N-glycosites and quantify the N-glycosylation profiles of SIDT1 and SIDT2. Further molecular mechanistic probing elucidates the essential role of N-linked glycans in regulating cell surface expression, RNA binding, protein stability, and RNA uptake of SIDT1. Our results provide crucial information about the potential functional impact of N-glycosylation in the regulation of SIDT1-mediated RNA uptake and provide insights into the molecular mechanisms of this promising nucleic acid delivery system, with potential implications for therapeutic applications.

biochemistry↗

bioRxiv2023

Mesoscale DNA Features Impact APOBEC3A and APOBEC3B Deaminase Activity and Shape Tumor Mutational Landscapes

Antiviral DNA cytosine deaminases APOBEC3A and APOBEC3B are major sources of mutations in cancer by catalyzing cytosine-to-uracil deamination. APOBEC3A preferentially targets singlestranded DNAs, with a noted affinity for DNA regions that adopt stem-loop secondary structures. However, the detailed substrate preferences of APOBEC3A and APOBEC3B have been fully established, and the specific influence of the DNA sequence on APOBEC3A APOBEC3B deaminase activity remains to be investigated. Here, we find that APOBEC3B selectively targets DNA stem-loop structures, and they are distinct from those subjected deamination by APOBEC3A. We develop Oligo-seq, a novel in vitro sequencing-based to identify specific sequence contexts promoting APOBEC3A and APOBEC3B activity. Through this approach, we demonstrate that APOBEC3A an APOBEC3B deaminase activity is strongly regulated by specific sequences surrounding the targeted cytosine. Moreover, we identify structural features of APOBEC3B and APOBEC3A responsible for their substrate preferences. Importantly, we determine that APOBEC3B-induced mutations in hairpin-forming sequences within tumor genomes differ from the DNA stem-loop sequences mutated by APOBEC3A. Together, our study provides evidence that APOBEC3A and APOBEC3B can generate mutation landscapes in cancer genomes, driven by their unique substrate selectivity.

biochemistry↗

bioRxiv2023

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a novel optimization procedure to identify the optimal network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression. SignificanceA combined bioinformatics and systems-biology modeling approach is designed to model a transcriptional regulatory network for AML with IDH mutations. Network modeling identifies key regulators DNMT1 and E2F1, which is supported by patient survival data.

systems biology↗

bioRxiv2023

Machine learning assisted health viability assay for mouse embryos with artificial confocal microscopy (ACM)

The combination of a good quality embryo and proper maternal health factors promise higher chances of a successful in vitro fertilization (IVF) procedure leading to clinical pregnancy and live birth. Of these two factors, selection of a good embryo is a controllable aspect. The current gold standard in clinical practice is visual assessment of an embryo based on its morphological appearance by trained embryologists. More recently, machine learning has been incorporated into embryo selection "packages". Here, we report a machine-learning assisted embryo health assessment tool utilizing a quantitative phase imaging technique called artificial confocal microscopy (ACM). We present a label-free nucleus detection method with novel quantitative embryo health biomarkers. Two viability assessment models are presented for grading embryos into two classes: healthy/intermediate (H/I) or sick (S) class. The models achieve a weighted F1 score of 1.0 and 0.99 respectively on the in-distribution test set of 72 fixed embryos and a weighted F1 score of 0.9 and 0.95 respectively on the out-of-distribution test dataset of 19 time-instances from 8 live embryos.

bioengineering↗

bioRxiv2023

Modelling collective behavior in groups of mice housed under semi-naturalistic conditions

In social behavior research, the focus often remains on animal dyads, limiting the understanding of complex interactions. Recent trends favor naturalistic setups, offering unique insights into intricate social behaviors. Social behavior stems from chance, individual preferences, and group dynamics, necessitating high-resolution quantitative measurements and statistical modeling. This study leverages the Eco-HAB system, an automated experimental setup which employs RFID tracking to observe naturally formed mouse cohorts in a controlled yet naturalistic setting, and uses statistical inference models to decipher rules governing the collective dynamics of groups of 10-15 individuals. Applying maximum entropy models on the coarse-grained co-localization patterns of mice unveils social rules in mouse hordes, quantifying sociability through pairwise interactions within groups, the impact of individual versus social preferences, and the effects of considering interaction structures among three animals instead of two. Reproducing co-localization patterns of individual mice reveals stability over time, with the statistics of the inferred interaction strength capturing social structure. By separating interactions from individual preferences, the study demonstrates that altering neuronal plasticity in the prelimbic cortex - the brain structure crucial for sociability - does not eliminate signatures of social interactions, but makes the transmission of social information between mice more challenging. The study demonstrates how the joint probability distribution of the mice positions can be used to quantify sociability.

animal behavior and cognition↗

bioRxiv2023

miRNA-encoded regulatory peptides modulate cadmium tolerance and accumulation in rice

MicroRNAs (miRNAs) are small non-coding RNAs that play a vital role in plant responses to abiotic and biotic stress. Recently, it has been discovered that some primary miRNAs (pri-miRNAs) encode regulatory short peptides called miPEPs. However, the presence of miPEPs in rice, and their functions in response to abiotic stress, particularly stress induced by heavy metals, remain poorly understood. Here, we identified a functional small peptide (miPEP156e) encoded by pri-miR156e that regulates the expression of miR156 and its target SPL genes, thereby affecting miR156-mediated cadmium (Cd) tolerance in rice. Overexpression of miPEP156e led to a reduction in the accumulation of reactive oxygen species (ROS) and Cd in plants under Cd stress, resulting in improved rice Cd tolerance, as observed in miR156-overexpressing lines and seedlings treated with exogenous miPEP156e. In contrast, miPEP156e mutants displayed sensitivity to Cd stress due to the elevated accumulation of ROS and Cd. Transcriptome analysis further revealed that miPEP156e improved rice Cd tolerance by modulating Cd transporter and ROS scavenging genes. Moreover, we identified five novel miPEPs involved in regulating Cd resistance through exogenous treatment of seedlings with synthetic corresponding miPEPs. Our study provides insights into the regulatory mechanism of miPEP156e in rice response to Cd stress and demonstrates the potential of miPEPs as an effective tool for improving crop abiotic stress tolerance.

plant biology↗

bioRxiv2023

Sequential colonization events with restricted gene flow in a widespread European carnation species

The key questions relating to the evolutionary processes underlying plant colonization success pertain to the geographic origin of the source population(s), the location of the migration routes, the extent to which genetic diversity is reduced via founder effects, and the extent of gene flow among populations during expansion. However, these questions must still be addressed for perennial herbaceous plants with large geographic distributions. We investigated the colonization history of Dianthus carthusianorum (the Carthusian Pink), one of the most widespread European carnation species. We called genome-wide 236,964 SNPs from a large sample across the D. carthusianorum distribution range, and used up-to-date population genomics approaches (approximate Bayesian computation Random-Forest method, ABC-RF) to infer population demographic history. Spatial genetic structure and diversity analyses and demographic inferences indicated successive East-West colonization events by the Carthusian Pink. ABC-RF also revealed gene flow during colonization, but only among geographically close populations. This study provides important insights into the colonization processes of herbaceous perennial species belonging to one of Europes most diverse plant genera.

evolutionary biology↗

bioRxiv2023

Extraordinary preservation of gene collinearity over three hundred million years revealed in homosporous lycophytes

Homosporous lycophytes (Lycopodiaceae) are a deeply diverged lineage in the plant tree of life, having split from heterosporous lycophytes (Selaginella and Isoetes) [~]400 million years ago (MYA). Compared to the heterosporous lineage, Lycopodiaceae has markedly larger genome sizes and remains the last major plant clade for which no genomic data has been available. Here, we present chromosomal genome assemblies for two homosporous lycophyte species, the allotetraploid Huperzia asiatica and the diploid Diphasiastrum complanatum. Remarkably, despite that the two species diverged [~]350 MYA, around 30% of the genes are still in syntenic blocks. Furthermore, both genomes had undergone independent whole genome duplications and the resulting intra-genomic syntenies have likewise been preserved relatively well. Such slow genome evolution over deep time is in stark contrast to heterosporous lycophytes and is correlated with a decelerated rate of nucleotide substitution. Together, the genomes of H. asiatica and D. complanatum not only fill a crucial gap in the plant genomic landscape, but also uncover a possibly unique genomic contrast between homosporous and heterosporous species.

genomics↗

bioRxiv2023

Endothelial SARS-CoV-2 infection is not the underlying cause of COVID19-associated vascular pathology in mice

Endothelial damage and vascular pathology have been recognized as major features of COVID-19 since the beginning of the pandemic. Two main theories regarding how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) damages endothelial cells and causes vascular pathology have been proposed: direct viral infection of endothelial cells or indirect damage mediated by circulating inflammatory molecules and immune mechanisms. However, these proposed mechanisms remain largely untested in vivo. Here, we utilized a set of new mouse genetic tools1 developed in our lab to test both the necessity and sufficiency of endothelial human angiotensin-converting enzyme 2 (hACE2) in COVID19 pathogenesis. Our results demonstrate that endothelial ACE2 and direct infection of vascular endothelial cells does not contribute significantly to the diverse vascular pathology associated with COVID-19.

pathology↗