Biology subjects

Cheng, L.

Publications and source records attributed to Cheng, L..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Neuroepithelial depletion schedules cessation of neurogenesis in the Drosophila optic lobes

The brain is consisted of diverse neurons arising from a limited number of neural stem cells. Drosophila neural stem cells called neuroblasts (NBs) produces specific neural lineages of various lineage sizes depending on their location in the brain. In the Drosophila visual processing centre - the optic lobes (OLs), medulla NBs derived from the neuroepithelium (NE) give rise to neurons and glia cells of the medulla cortex. The timing and the mechanisms responsible for the cessation of medulla NBs are so far not known. In this study, we show that the termination of medulla NBs during pupal development is determined by the exhaustion of the NE stem cell pool. Altering NE-NB transition during larval neurogenesis disrupts the timely termination of medulla NBs. Medulla NBs terminate neurogenesis via a combination of cell death, terminal symmetric division, and a switch to gliogenesis. We show that temporal progression is not required for the termination of medulla NBs. The timing of NB cessation can be altered through the acquisition of a glial cell fate via Glial cells missing, or through conversion to type II NB cell fate via Tailless, or by inhibition of differentiation via Prospero knockdown. As the Drosophila OL shares a similar mode of division with mammalian neurogenesis, determining how and when these progenitors cease proliferation during development can have important implications for mammalian brain size determination and regulation of its overall function.

developmental biology↗

bioRxiv2023

Machine Learning Elucidates Design Features of Plasmid DNA Lipid Nanoparticles for Cell Type-Preferential Transfection

For cell and gene therapies to become more broadly accessible, it is critical to develop and optimize non-viral cell type-preferential gene carriers such as lipid nanoparticles (LNPs). Despite the effectiveness of high throughput screening (HTS) approaches in expediting LNP discovery, they are often costly, labor-intensive, and often do not provide actionable LNP design rules that focus screening efforts on the most relevant chemical and formulation parameters. Here we employed a machine learning (ML) workflow using well-curated plasmid DNA LNP transfection datasets across six cell types to maximize chemical insights from HTS studies and has achieved predictions with 5-9% error on average depending on cell type. By applying Shapley additive explanations to our ML models, we unveiled composition-function relationships dictating cell type-preferential LNP transfection efficiency. Notably, we identified consistent LNP composition parameters that enhance in vitro transfection efficiency across diverse cell types, such as ionizable to helper lipid ratios near 1:1 or 10:1 and the incorporation of cationic/zwitterionic helper lipids. In addition, several parameters were found to modulate cell type-preferentiality, including the ionizable and helper lipid total molar percentage, N/P ratio, cholesterol to PEGylated lipid ratio, and the chemical identity of the helper lipid. This study leverages HTS of compositionally diverse LNP libraries and ML analysis to understand the interactions between lipid components in LNP formulations; and offers fundamental insights that contribute to the establishment of unique sets of LNP compositions tailored for cell type-preferential transfection.

bioengineering↗

bioRxiv2023

The Effect of Pseudoknot Base Pairing on Cotranscriptional Structural Switching of the Fluoride Riboswitch

A central question in biology is how RNA sequence changes influence dynamic conformational changes during cotranscriptional folding. Here we investigated this question through the study of transcriptional fluoride riboswitches, non-coding RNAs that sense the fluoride anion through the coordinated folding and rearrangement of a pseudoknotted aptamer domain and a downstream intrinsic terminator expression platform. Using a combination of E. coli RNA polymerase in vitro transcription and cellular gene expression assays, we characterized the function of mesophilic and thermophilic fluoride riboswitch variants. We showed that only variants containing the mesophilic pseudoknot function at 37 {degrees}C. We next systematically varied the pseudoknot sequence and found that a single wobble base pair is critical for function. Characterizing thermophilic variants at 65 {degrees}C through Thermus aquaticus RNA polymerase in vitro transcription showed the importance of this wobble pair for function even at elevated temperatures. Finally, we performed all-atom molecular dynamics simulations which supported the experimental findings, visualized the RNA structure switching process, and provided insight into the important role of magnesium ions. Together these studies provide deeper insights into the role of riboswitch sequence in influencing folding and function that will be important for understanding of RNA-based gene regulation and for synthetic biology applications.

molecular biology↗

bioRxiv2023

DeepLocRNA: An Interpretable Deep Learning Model for Predicting RNA Subcellular Localization with domain-specific transfer-learning

Accurate prediction of RNA subcellular localization plays an important role in understanding cellular processes and functions. Although post-transcriptional processes are governed by trans-acting RNA-binding proteins (RBPs) through interaction with cis-regulatory RNA motifs, current methods do not incorporate RBP-binding information. In this paper, we propose DeepLocRNA, an interpretable deep-learning model that leverages a pre-trained multi-task RBP-binding prediction model to predict the subcellular localisation of RNA molecules via fine-tuning. We constructed DeepLocRNA using a comprehensive dataset with variant RNA types and evaluated it on held-out RNA species. Our model achieved state-of-the-art performance in predicting RNA subcellular localization in mRNA and miRNA. It has demonstrated great generalization capabilities, not only for human RNA but also for mice. Moreover, the interpretability of the model is enhanced through the motif analysis, enabling the understanding of the signal factors that contribute to the predictions. The proposed model provides general and powerful prediction abilities for different RNA and species, offering valuable insights into the localisation patterns of RNA molecules and contributing to advancing our understanding of cellular processes at the molecular level.

bioinformatics↗

bioRxiv2023

Transcriptional profiling of peripheral blood mononuclear cells identifies inflammatory phenotypes in ataxia telangiectasia

Ataxia telangiectasia (A-T) is an autosomal recessive neurodegenerative disease with widespread systemic manifestations and marked variability in clinical phenotypes. In this study, we sought to determine whether transcriptomic profiling of peripheral blood mononuclear cells defines subsets of individuals with A-T beyond mild and classic phenotypes, enabling identification of novel features for disease classification and treatment response to therapy. MethodsParticipants with stable A-T (n=90) were recruited and compared with unaffected controls (n=15). PBMCs were isolated and bulk RNAseq was performed. Plasma was also isolated in a subset of individuals. Affected individuals were designated mild or classic based on ATM mutations and clinical and laboratory features. ResultsPeople with classic A-T were more likely to be younger and IgA deficient and to have higher alpha-fetoprotein levels and lower % forced vital capacity compared to individuals with mild A-T. In classic A-T, the expression of genes required for V(D)J recombination was lower, and the expression of genes required for inflammatory activity was higher. We assigned inflammatory scores to study participants and found that inflammatory scores were highly variable among people with classic A-T and that higher scores were associated with lower ATM mRNA levels. Using a cell type deconvolution approach, we inferred that CD4+ T cells and CD8+ T cells were lower in number in people with classic A-T. Finally, we showed that individuals with classic A-T exhibit higher SERPINE1 (PAI-1) mRNA and plasma protein levels, irrespective of age, and higher FLT4 (VEGFR3) and IL6ST (GP130) plasma protein levels compared with mild A-T and controls. ConclusionUsing an unbiased transcriptomic approach, we identified novel features and developed an inflammatory score to identify subsets of individuals with different inflammatory phenotypes in A-T. Findings from this study could be used to help direct treatment and to track treatment response to therapy.

immunology↗

bioRxiv2023

SCancerRNA: Expression at the Single Cell Level and Interaction Resource of Non-coding RNA Biomarkers for Cancers

Non-coding RNAs (ncRNAs) participate in multiple biological processes associated with cancer as tumor suppressors or oncogenic drivers. Due to their high stability in plasma, urine, and many other fluids, ncRNAs have the potential to serve as key biomarkers for early diagnosis and screening of cancers. During cancer progression, tumor heterogeneity plays a crucial role, and it is particularly important to understand the gene expression patterns of individual cells. With the development of single-cell RNA sequencing (scRNA-seq) technologies, uncovering gene expression in different cell types for human cancers has become feasible by profiling transcriptomes at the cellular level. However, a well-organized and comprehensive online resource that provides access to the expression of genes corresponding to ncRNA biomarkers in different cell types at the single cell level is not available yet. Therefore, we developed the SCancerRNA database to summarize experimentally supported data on long ncRNA (lncRNA), microRNA (miRNA), piwi-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and circular RNA (circRNA) biomarkers, as well as data on their differential expression at the cellular level. Furthermore, we collected biological functions and clinical applications of biomarkers to facilitate the application of ncRNA biomarkers to cancer diagnosis, as well as monitoring of progression and targeted therapies. SCancerRNA also allows users to explore interaction networks of different types of ncRNAs, and build computational models in the future. SCancerRNA is freely accessible at http://www.scancerrna.com/BioMarker.

bioinformatics↗

bioRxiv2023

Social Determinants modulate NK cell activity via obesity, LDL, and DUSP1 signaling

Adverse social determinants of health (aSDoH) are associated with obesity and related comorbidities like diabetes, cardiovascular disease, and cancer. Obesity is also associated with natural killer cell (NK) dysregulation, suggesting a potential mechanistic link. Therefore, we measured NK phenotypes and function in a cohort of African-American (AA) women from resource-limited neighborhoods. Obesity was associated with reduced NK cytotoxicity and a shift towards a regulatory phenotype. In vitro, LDL promoted NK dysfunction, implicating hyperlipidemia as a mediator of obesity-related immune dysregulation. Dual specific phosphatase 1 (DUSP1) was induced by LDL and was upregulated in NK cells from subjects with obesity, implicating DUSP1 in obesity-mediated NK dysfunction. In vitro, DUSP1 repressed LAMP1/CD107a, depleting NK cells of functional lysosomes to prevent degranulation and cytokine secretion. Together, these data provide novel mechanistic links between aSDoH, obesity, and immune dysregulation that could be leveraged to improve outcomes in marginalized populations.

immunology↗

bioRxiv2023

Converging Topographic Axes of Connectivity and Genetic Architectures Scaffold Cortical Patterning

Genetic information is involved in the gradual emergence of cortical areas since the neural tube begins to form, shaping the heterogeneous functions of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles to reveal the heterogeneity across cortical areas. However, it remains unclear about the organizing principles possibly shared by genetics and cortical wiring to manifest the spatial heterogeneity across the cortex. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the cortical wiring space. Leveraging on the vertex-wise tractography in diffusion-weighted MRI, we derived the global connectopies to reliably index the organizing principles of interareal connectivity variation in a low-dimensional space, which specifically captured three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. More importantly, we demonstrated that the global connectopies converge to the gradients of vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. By diving into the genetic profiles, we found the critical role of genes scaffolding the global connectopies were related to brain morphogenesis and enriched in radial glial cells before birth and excitatory neurons after birth. Taken together, our findings demonstrated the existence of a genetically determined space to encode the interareal connectivity variation, which may give new insights into the links between cortical connections and arealization.

neuroscience↗

bioRxiv2023

Targeting adipocyte ESRRA promotes osteogenesis and vascular formation in adipocyte-rich bone marrow

Ectopic bone marrow adipocytes (BMAds) accumulation occurring under diverse pathophysiological conditions leads to bone deterioration. Estrogen-related receptor (ESRRA) is a key regulator responding to metabolic stress. Here, we show that adipocyte-specific ESRRA deficiency rescues osteogenesis and vascular formation in adipocyte-rich bone marrow due to estrogen deficiency or obesity. Mechanistically, adipocyte ESRRA interferes with E2/ESR1 signaling resulting in transcriptional repression of secreted phosphoprotein 1 (Spp1); and positively modulates Leptin expression by binding to its promoter. ESRRA abrogation results in enhanced SPP1 and decreased LEPTIN secretion from both visceral adipocytes and BMAds, concertedly dictating bone marrow stromal stem cell fate commitment and restoring type H vessel formation, constituting a feed-forward loop for bone formation. Pharmacological inhibition of ESRRA protects obese mice against bone loss and high marrow adiposity. Thus, our findings highlight a therapeutic approach via targeting adipocyte ESRRA to preserve bone formation especially in detrimental adipocyte-rich bone milieu. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/552932v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1132da3org.highwire.dtl.DTLVardef@19342aorg.highwire.dtl.DTLVardef@afe8d7org.highwire.dtl.DTLVardef@dfb1f9_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Mitochondrial fusion and altered beta-oxidation drive muscle wasting in a Drosophila cachexia model

Cancer cachexia is a tumour-induced wasting syndrome, characterised by extreme loss of skeletal muscle. Defective mitochondria can contribute to muscle wasting; however, the underlying mechanisms remain unclear. Using a Drosophila larval model of cancer cachexia, we observed enlarged and dysfunctional muscle mitochondria. Morphological changes were accompanied by upregulation of beta-oxidation proteins and depletion of muscle glycogen and lipid stores. Muscle lipid stores were also decreased in Colon-26 adenocarcinoma mouse muscle samples, and expression of the beta-oxidation gene CPT1A was negatively associated with muscle quality in cachectic patients. Mechanistically, mitochondrial defects result from reduced muscle insulin signalling, downstream of tumour-secreted insulin growth factor binding protein (IGFBP) homolog ImpL2. Strikingly, muscle-specific inhibition of Forkhead box O (FOXO), mitochondrial fusion, or beta-oxidation in tumour-bearing animals preserved muscle integrity. Finally, dietary supplementation with nicotinamide or lipids, improved muscle health in tumour-bearing animals. Overall, our work demonstrates that muscle FOXO, mitochondria dynamics/beta-oxidation and lipid utilisation are key regulators of muscle wasting in cancer cachexia.

developmental biology↗

bioRxiv2023

SpatialView: An interactive web application forvisualization of multiple samples in spatialtranscriptomics experiments

Spatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments. To fill this gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10x Genomics ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease. AvailabilitySpatialView is available at https://github.com/kendziorski-lab/SpatialView ; a demo application is available at https://www.biostat.wisc.edu/~kendzior/spatialviewdemo/ Contactcmohanty2@wisc.edu, ckendziorski@wisc.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Convergent Insulin and TGF-β signalling drives cancer cachexia by promoting aberrant fatbody ECM accumulation in a Drosophila tumour model

Cancer cachexia is a wasting disease suffered by advanced stage cancer patients and ultimately causes [~]30% of cancer mortalities. Clinical observations have shown that extracellular matrix (ECM) remodelling which leads to fibrosis in the adipose tissue is a key feature of cancer cachexia. However, the molecular regulators of adipose ECM remodelling are not known and how this leads to muscle wasting is unclear. In this study, using a Drosophila cachexia model, we found that in the adipose tissue of both wildtype and tumour bearing animals, insulin and TGF-{beta} signalling converge via a BMP antagonist short gastrulation (sog) to regulate ECM remodelling. In tumour bearing animals, the aberrant ECM accumulation in the fatbody, contributes towards muscle detachment by preventing ECM secretion and subsequently depleting muscles of fatbody-secreted ECM proteins. Strikingly, activation of insulin signalling, inhibition of TGF-{beta} signalling, or modulation of ECM secretion via SPARC or Rab10 in the fatbody, was able to rescue tissue wasting in the presence of tumour. Together, our study highlights the importance of adipose ECM remodelling in the context of cancer cachexia.

developmental biology↗

bioRxiv2023

A Gpr35 tuned gut-brain metabolic axis regulates depressive-like behavior

Gene-environment interactions shape animal behavior and the susceptibility to neurobehavioral symptoms such as depression. However, little is known about the signaling pathway that integrates genetic and environmental inputs with neurobehavioral outcomes, preventing the development of targeted therapies. Here we report that Gpr35 engages a gut microbe-to-brain metabolic pathway to modulate neuronal plasticity and depressive behavior in mice. Chronic stress decreases gut epithelial Gpr35, the genetic deletion of which induces despair and social impairment in a microbiome-dependent manner. We identify a dominant role for the imbalance of microbe-derived indole-3-carboxaldehyde (IAld) and indole-3-lactate (ILA) in the behavioral symptoms with Gpr35 deficiency. Mechanistically, these bacterial metabolites counteractively modulate dendritic spine density and synaptic transmission in the nucleus accumbens. Supplementation of IAld, which is similarly decreased in depressive patients, produce anti-depressant effects in mice with stress or gut epithelial Gpr35 deficiency. Together, these findings identify a genetics-shaped gut-brain connection underlying the susceptibility to depression and suggest a microbial metabolite-based therapeutic strategy to genetic predisposition.

animal behavior and cognition↗

bioRxiv2023

The impact of common variants on gene expression in the human brain: from RNA to protein to schizophrenia risk

BackgroundThe impact of genetic variants on gene expression has been intensely studied at the transcription level, yielding invaluable insights into the association between genes and the risk of complex disorders, such as schizophrenia (SCZ). However, the downstream impact of these variants and the molecular mechanisms connecting transcription variation to disease risk are not well understood. ResultsWe quantitated ribosome occupancy in prefrontal cortex samples of the BrainGVEX cohort. Together with transcriptomics and proteomics data from the same cohort, we performed cis-Quantitative Trait Locus (QTL) mapping and identified, at 10% false discovery rate, 3,253 expression QTLs (eQTLs), 1,344 ribosome occupancy QTLs (rQTLs), and 657 protein QTLs (pQTLs) out of 7,458 genes from 185 samples. Of the eQTLs identified, only 34% have their effects propagated to the protein level. Further analysis on the effect size of prefrontal cortex eQTLs identified from an independent dataset clearly replicated the post-transcriptional attenuation of eQTL effects. We identified omics-specific QTLs and investigated their potential in driving disease risks. Using both a variant-based approach and a gene-based approach, we identified genes containing expression-specific QTLs (esQTLs), ribosome-occupancy-specific QTLs (rsQTLs), and protein-specific QTLs (psQTLs). Among the variant-based omics-specific QTL, 38 showed strong colocalization with brain associated disorder GWAS signals, 29 of them are esQTLs. From the gene-based approach, we found 11 brain associated disorder risk genes that are driven predominantly by omics-specific QTL, all of them are driven by variants impacting transcriptional regulation. To take a complementary approach to further investigate the functional relevance of genes driven predominantly by attenuated eQTL signals, we identified SCZ risk genes using each omics independently and then investigated the omics-specificity of the driver regulatory process for each risk gene. Using S-PrediXcan we identified 74 SCZ risk genes across the three omics, 30% of which were novel, and 67% of these risk genes were confirmed to be causal in a MR-Egger test. Notably, 52 out of the 74 risk genes were identified using eQTL data and 68% of these SCZ-risk-gene-driving eQTLs show little to no evidence of driving corresponding variations at the protein level. ConclusionThe effect of eQTLs on gene expression in the prefrontal cortex is commonly attenuated post-transcriptionally. Many of the attenuated eQTLs still correlate with GWAS signals of brain associated complex disorders, indicating the possibility that these eQTL variants drive disease risk through mechanisms other than regulating protein expression level. Further investigation is needed to elucidate the mechanistic link between attenuated eQTLs and brain associated complex disorders.

genetics↗

bioRxiv2023

Accurate identification of structural variations from cancer samples

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion, and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the COMSV method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

genomics↗

bioRxiv2023

An all-atom protein generative model

AO_SCPLOWBSTRACTC_SCPLOWProteins mediate their functions through chemical interactions; modeling these interactions, which are typically through sidechains, is an important need in protein design. However, constructing an all-atom generative model requires an appropriate scheme for managing the jointly continuous and discrete nature of proteins encoded in the structure and sequence. We describe an all-atom diffusion model of protein structure, Protpardelle, which instantiates a "superposition" over the possible sidechain states, and collapses it to conduct reverse diffusion for sample generation. When combined with sequence design methods, our model is able to co-design all-atom protein structure and sequence. Generated proteins are of good quality under the typical quality, diversity, and novelty metrics, and sidechains reproduce the chemical features and behavior of natural proteins. Finally, we explore the potential of our model conduct all-atom protein design and scaffold functional motifs in a backbone- and rotamer-free way.

bioengineering↗

bioRxiv2023

Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae

Genomic rearrangements contribute to gene copy number alterations, disruption of protein-coding sequences and/or perturbation of cis-regulatory networks. SCRaMbLE, a Cre/loxP-based system implanted in synthetic yeast chromosomes, can effectively introduce genomic rearrangements, and is thus a potential tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we constructed a yeast strain, SparLox83, containing 83 loxPsym sites distributed across all 16 chromosomes, with at least two sites per chromosome. Inducing Cre recombinase expression in SparLox83 produced versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, SCRaMbLE of the hetero-diploid strains derived from crossing SparLox83 with strains possessing synthetic chromosome III (synIII) from the Sc2.0 project led to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to a strain with only synIII. Analysis of these evolved strains demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and can consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool to study the consequence of genomic rearrangements and help accelerate strain engineering in Saccharomyces cerevisiae.

synthetic biology↗

bioRxiv2023

Native-state proteomics of Parvalbumin interneurons identifies novel molecular signatures and metabolic vulnerabilities to early Alzheimer's disease pathology

One of the earliest pathophysiological perturbations in Alzheimers Disease (AD) may arise from dysfunction of fast-spiking parvalbumin (PV) interneurons (PV-INs). Defining early protein-level (proteomic) alterations in PV-INs can provide key biological and translationally relevant insights. Here, we use cell-type-specific in vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state proteomes of PV interneurons. PV-INs exhibited proteomic signatures of high metabolic, mitochondrial, and translational activity, with over-representation of causally linked AD genetic risk factors. Analyses of bulk brain proteomes indicated strong correlations between PV-IN proteins with cognitive decline in humans, and with progressive neuropathology in humans and mouse models of A{beta} pathology. Furthermore, PV-IN-specific proteomes revealed unique signatures of increased mitochondrial and metabolic proteins, but decreased synaptic and mTOR signaling proteins in response to early A{beta} pathology. PV-specific changes were not apparent in whole-brain proteomes. These findings showcase the first native state PV-IN proteomes in mammalian brain, revealing a molecular basis for their unique vulnerabilities in AD.

neuroscience↗