Biology subjects

Fang, B.

Publications and source records attributed to Fang, B..

At least 19 recordsLinked to original sources

bioRxiv2026

RBP4-BACH1 Interaction Modulates Transcriptional Regulation of Insulin Signaling Pathway Genes

Retinol-binding protein 4 (RBP4) exhibits diurnal oscillatory pattern and is elevated under conditions of circadian disruption and in type 2 diabetes mellitus, yet the molecular link between RBP4 and impaired glucose metabolism remains elusive. Here, we overexpressed RBP4 in human hepatoma Huh7 cells and performed integrated RNA sequencing (RNA-seq), Co-immunoprecipitation (Co-IP) coupled with mass spectrometry (MS), and Cleavage Under Targets and Tagmentation (CUT&Tag). We identified BACH1 as a direct RBP4-interacting transcription factor that predominantly binds the TGACTCA motif in promoter regions of genes involved in carbon metabolism pathways. Integrative analysis of RNA-seq and CUT&Tag data uncovered 63 direct target genes co-regulated by RBP4 and BACH1, including known circadian and metabolic regulators SLC7A11, PFKFB3, CTCF, NR1D2 and WEE1 as well as novel candidates SF1 and PIN1. These target genes are significantly enriched in insulin receptor signaling and carbohydrate metabolic pathways. Mechanistically, the RBP4-BACH1 axis reprograms glucose metabolism, linking circadian rhythm disturbances to dysregulated glucose homeostasis. Collectively, our findings establish a functional role for RBP4 in connecting circadian disruption to diabetes and highlight RBP4 as a potential therapeutic target.

molecular biology↗

bioRxiv2026

TAp63-regulated oncogenic long non-coding RNA-8 ( TROLL-8 ) regulates human breast cancer progression through CPT1A-mediated fatty acid oxidation

Metabolic reprogramming is a crucial hallmark of cancer, supporting tumor growth and adaptation to cellular stress. Although fatty acid oxidation (FAO) has emerged as an important regulator in cancer, the mechanisms that control the FAO machinery remain poorly understood. Here, we demonstrate that the TAp63-regulated long non-coding RNA TROLL-8 is a key regulator of FAO in breast cancer. Using metabolomics and protein microarray assays followed by immunoprecipitation-mass spectrometry, we mechanistically demonstrate that TROLL-8 binds the FAO enzyme CPT1A and promotes the formation of a complex with ACSL1 and VDAC1, thereby enabling efficient fatty acid processing. Loss of TROLL-8 destabilizes this complex, leading to impaired FAO, decreased metabolic fitness, and suppression of tumorigenic phenotypes, such as anchorage-independent growth. Notably, higher levels of CPT1A and VDAC1 are associated with worse survival in breast cancer patients. Given the emerging role of CPT1A in therapy resistance, these findings suggest that targeting TROLL-8 could be a promising approach to selectively disrupt the hyperactive FAO machinery in breast cancers and other tumor types that rely on FAO for their progression.

Cancer Biology↗

bioRxiv2026

Sustained Relief of Chronic Pain via a Nav1.7_Targeting ASO_siRNA Conjugate

Chronic pain affects billions globally, yet safe, long-lasting, and non-addictive analgesics remain lacking. Nav1.7 is a genetically validated pain target, but traditional small molecules have repeatedly failed. Therapeutic oligonucleotides-antisense oligonucleotides (ASOs) and siRNAs-offer selective, durable silencing. We developed N02C0702, an ASO-siRNA conjugate (ASC), achieving robust Nav1.7 knockdown and sustained analgesia without additional delivery vehicles. N02C0702 outperformed individual ASO (N02A114) and siRNA (N02S154) moieties at mRNA and protein levels and in pain relief. In CFA-induced inflammatory pain, a single intrathecal dose exceeded naproxen and suzetrigine, while in SNL neuropathic pain, efficacy persisted up to 56 days, comparable to or surpassing pregabalin. Genome-wide RNA sequencing confirmed minimal off-target effects. N02C0702 highlights Nav1.7 as a key analgesic target and demonstrates the ASC platforms potential for chronic pain and other CNS-related pathologies, offering durable, selective, and safe therapeutic effects.

neuroscience↗

bioRxiv2026

Intermittent AP-1 activation in muscles contributes to exercise-induced health benefits

Regular physical exercise extends healthspan, yet the molecular mechanisms that translate intermittent contractile stress into lasting benefit remain incompletely understood. Using global nuclear run-on (GRO-seq) in mouse skeletal muscle after treadmill running, we profiled enhancer RNA (eRNA), a sensitive marker of enhancer activity. Activation protein-1 (AP-1), a family of pioneering factors for senescence, emerged as the top transcription factor with motif enrichment in exercise-activated enhancers. Our screen in the contracting C2C12 myotubes pinpointed cFos/JunD as the primary AP-1 factor responsible for contraction-induced transcriptional changes. Muscle-specific overexpression of A-Fos, a dominant-negative mutant of cFos, disrupted transcriptomic responses to exercise and attenuated exercise-mediated improvement in muscle functions. Interestingly, intermittent but not continuous overexpression of cFos/JunD in mouse muscles mimicked exercise-induced transcriptomic changes, increased mitochondrial volume density, enhanced muscle strength and fatigue resistance, and improved glucose tolerance. These results define a transcriptional regulatory signaling pathway linking exercise intermittency to beneficial adaptations and highlight the necessary recovery cycles in training. The paradoxical anti- and pro-aging roles of AP-1 offer insights into the timing and dynamics of stressors and stress responses in shaping senescence and healthspan.

molecular biology↗

bioRxiv2025

B12 promotes gut dysbiosis and an inflammatory microenvironment that potentiates Tet2-deficient hematopoiesis.

Recent studies have linked elevated vitamin B12 serum levels with the presence of clonal hematopoiesis (CH) and an increased risk of developing myeloid malignancy. High B12 supplementation increases serum levels, alters gut microbial composition, and reduces the production of short-chain fatty acids (SCFAs), which help maintain gut barrier function and mucosal integrity. TET2 mutation is a frequent driver of CH that progresses in a positive feedback loop in response to microbial signals suggesting that B12 may influence CH via the gut microbiome. We evaluated the microenvironmental effects of B12 supplementation in a Tet2-deficient model of CH and found that B12 enhances myelopoiesis, heightens the responses of myeloid cells to bacterial stimuli, and increases the levels of circulating inflammatory cytokines. B12 supplementation also induced gut dysbiosis and reduced the levels of SCFA-producing bacteria in both wild-type and Tet2-deficient mice. Importantly, the effects of excess B12 were reversible upon oral supplementation with the SCFA butyrate. These findings suggest that B12 may promote CH progression by disrupting microbiome-derived SCFA metabolism, highlighting a potential therapeutic role for SCFA supplementation in mitigating CH.

cancer biology↗

bioRxiv2025

Avian germline-restricted chromosomes are reservoirs for active long-terminal-repeat retroviruses

Germline-restricted chromosomes (GRCs) are unique to germ cells and absent from somatic cells in songbirds. However, their contents, functions, and evolutionary mechanisms remain unclear. We performed comparative genomics on long-read assembled GRCs from male House Finch (Haemorhous mexicanus), Common Rosefinch (Carpodacus erythrinus), and Blue Tit (Cyanistes caeruleus), the first two of which are newly presented and annotated here. These long-read GRCs are repeat-rich (63-74%), despite their wide variation in size (16-160 megabases), individually distinct gene content, and variable evolutionary histories. These GRCs have accumulated intact long terminal repeat (LTR) endogenous retroviruses (ERVs), and their proliferation co-occurs with speciation events of passerine birds. In contrast, normal chromosomes (autosomes and sex chromosomes) are known to purge ERVs through ectopic recombination of LTRs that generate solo LTRs. Furthermore, transcriptomic data reveal significantly higher ERV transcription on GRCs than on A-chrs in House Finch testis. We propose that GRCs act as reservoirs of active ERVs, promoting germline transposition and potentially accelerating adaptation and speciation. This study suggests that GRCs play an indispensable role and likely contribute to adaptive diversification in birds. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/662071v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1fdacacorg.highwire.dtl.DTLVardef@1536ceborg.highwire.dtl.DTLVardef@13f166org.highwire.dtl.DTLVardef@14d8795_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2025

Dual targeting of RET and SRC synergizes in RET fusion-positive cancer cells

RET fusions drive subsets of non-small cell lung cancer (NSCLC) and papillary thyroid carcinoma (PTC). Despite new selective RET tyrosine kinase inhibitors (TKIs) resistance usually occurs and is often driven by RET-independent bypass mechanisms. Previous studies have implied crosstalk between RET and SRC, but the anti-cancer effects of targeting SRC combined with selective RET TKIs and the underlying molecular mechanisms are not fully understood. Our results showed that the multitargeted SRC TKI dasatinib significantly enhanced efficacy of RET TKIs in RET fusion-positive (RET+) NSCLC and PTC cells. Genetic rescue experiments validated that the combination effects between RET TKIs and dasatinib were indeed SRC-dependent. Phosphoproteomics analysis and validation using selective inhibitors and siRNAs determined that synergy was primarily mediated by suppression of downstream PAK signaling, with contributions from AKT and S6. Importantly, synergy was also observed with eCF506 (NXP900), a next-generation clinical SRC inhibitor. Finally, both SRC TKIs restored sensitivity in selpercatinib-resistant RET+PTC cells. These results elucidate RET and SRC signaling crosstalk in RET+ NSCLC and PTC suggesting that co-inhibiting SRC has clinical potential in TKI-naive and -resistant RET+ cancers.

cancer biology↗

bioRxiv2025

Acquired resistance to sotorasib in mutant NSCLC is vulnerable to PI3K-mTOR pathway inhibition mediated by 4E-BP1 regulator of cap-dependent translation

Sotorasib and adagrasib have shown significant efficacy in KRASG12C mutant NSCLC; however, acquired resistance (AR) occurs within 6-12 months. While some resistance arises from new mutations, over half of the resistant cases lack identifiable genomic alterations. We hypothesize that resistance is driven by signaling network rewiring, creating new therapeutic vulnerabilities. To investigate AR mechanisms, multiple AR models, including cell lines, PDXs, CDXs, and PDXOs, were developed. H23AR and H358AR cells displayed >600-fold and 200-fold; and PDXO303AR and PDXO314AR organoids exhibited >300-fold and >100-fold resistance to sotorasib, respectively; however, no additional mutations in KRAS or other potential genetic alterations were identified. The AR cells and PDXOs also showed comparable resistance to adagrasib. Distinct protein signatures associated with KRAS reactivation, mTORC1 signaling upregulation, and PI3K/AKT/mTOR pathway activation were identified in TC303AR & TC314AR PDXs. PI3K protein levels were significantly elevated in AR PDXs, H23AR, and H358AR cells. Pharmacological inhibition of PI3K with copanlisib or genetic knockout via CRISPR-Cas9 restored sotorasib sensitivity, suppressed colony formation, and inhibited downstream effectors, including p-AKT, p-mTOR, p-S6, p70S6K, p-GSK3{beta}, and p-PRAS40 in AR cells. Copanlisib also sensitized both acquired and primary resistant PDXOs and synergized with sotorasib in restoring drug sensitivity. p4E-BP1 was significantly upregulated in H23AR and H358AR cells, which is suppressed by copanlisib. The level of p4E-BP1 expression was correlated with Sotorasib sensitivity in PI3K knockout clones, where the most sensitive clone displayed reduced or no p4E-BP1 expression. CRISPR-Cas9-mediated knockout of 4E-BP1, either alone or in combination with PI3K knockout, dramatically restored sotorasib sensitivity to levels comparable to parental cells. Suppression of 4E-BP1 hyperphosphorylation required dual inhibition of mTORC1 and mTORC2, and treatment with AZD8055 or sapanisertib (mTORC1/2 dual inhibitors) significantly dephosphorylated 4E-BP1 and restored sotorasib sensitivity in resistant cells and PDXOs. In PDX, CDX, and xenograft models in vivo, the combination of sotorasib with either copanlisib or sapanisertib resulted in robust, synergistic, and durable tumor regression at well-tolerated doses. These findings showed the critical role of PI3K/mTOR signaling as a bypass mechanism of resistance to KRASG12C inhibitors. We conclude that mTORC1/2 mediated inhibition of p4E-BP1 and combination strategies targeting this pathway effectively overcome acquired resistance to KRASG12C inhibitors in NSCLC.

cancer biology↗

bioRxiv2025

Comparative population pangenomes reveal unexpected complexity and fitness effects of structural variants

Structural variants (SVs) are widespread in vertebrate genomes, yet their evolutionary dynamics remain poorly understood. Using 45 long-read de novo genome assemblies and pangenome tools, we analyze SVs within three closely related species of North American jays (Aphelocoma, scrub-jays) displaying a 60-fold range in effective population size. We find rapid evolution of genome architecture, including [~]100 Mb variation in genome size driven by dynamic satellite landscapes with unexpectedly long (> 10 kb) repeat units and widespread variation in gene content, influencing gene expression. SVs exhibit slightly deleterious dynamics modulated by variant length and population size, with strong evidence of adaptive fixation only in large populations. Our results demonstrate how population size shapes the distribution of SVs and the importance of pangenomes to characterizing genomic diversity.

evolutionary biology↗

bioRxiv2024

Ligand-Receptor Interactions for Cell-Cell Communication Analysis in Rat, Chicken, Pig, and Monkey Single-Cell and Spatial Transcriptomics

Cell-cell communication is a frequently used analysis approach in single cell RNA and spatial transcriptomics, and many tools like CellPhoneDB, CellChat and stLearn have been developed. Ligand-receptor interactions are the core of cell-cell communication analysis. Since receptor-ligand and even protein-protein interactions were focus on humans and mice research, curated human and mouse receptor-ligand databases have been established, cell-cell interactions for these two species single-cell RNA sequencing data can be directly analyzed. However, for rats, chickens, pigs, monkeys, and other species, cell-cell interaction analysis is often implemented through orthologous gene mapping, due to the lack of curated ligand-receptor interaction databases for these species. We collected cell-cell interaction data mainly from KEGG for rats, chickens, pigs, and monkeys, and extended the data from Reactome and IntAct. Then, by using CellChatV2 with our collected rat ligand-receptor interactions and CellChatV2s own mouse data, respectively, we analyzed 10x Genomics rat public scRNA data, and found that 70 significantly ligand-receptor interactions from the mouse analysis result were also significantly in rats. We also obtained some chicken, pig, and monkey scRNA data from published literature, and analyzed cell-cell interactions using our collected ligand-receptor interactions for these species, and it was proved that our data is reliable and useful. Lastly, we have transformed the ligand-receptor interactions for rat, chicken, pig, and monkey species into the CellChatDB format, which enables swift and straightforward analysis of cell-cell communication in single-cell and spatial data of these four species. All the ligand-receptor interaction datasets for rats, chickens, pigs, and monkeys, as well as the program codes, are available at https://github.com/qingchen36/ligand-receptor. Using our program, one can rapidly obtain receptor-ligand interaction data for other species.

bioinformatics↗

bioRxiv2024

Cancer-associated fibroblasts confer ALK inhibitor resistance in EML4-ALK-driven lung cancer via concurrent integrin and MET signaling

Cancer-associated fibroblasts (CAFs) are associated with tumor progression and modulate drug sensitivity of cancer cells. However, the underlying mechanisms are often incompletely understood and crosstalk between tumor cells and CAFs involves soluble secreted as well as adhesion proteins. Interrogating a panel of non-small cell lung cancer (NSCLC) cell lines driven by EML4-ALK fusions, we observed substantial CAF-mediated drug resistance to clinical ALK tyrosine kinase inhibitors (TKIs). Array-based cytokine profiling of fibroblast-derived conditioned- media identified HGF-MET signaling as a major contributor to CAF-mediated paracrine resistance that can be overcome by MET TKIs. However, Cell Type specific labeling using Amino acid Precursors (CTAP)-based expression and phosphoproteomics in direct coculture also highlighted a critical role for the fibronectin-integrin pathway. Flow cytometry analysis confirmed activation of integrin {beta}1 (ITGB1) in lung cancer cells by CAF coculture. Treatment with pharmacological inhibitors, cancer cell-specific silencing or CRISPR-Cas9-mediated knockout of ITGB1 overcame adhesion protein-mediated resistance. Concurrent targeting of MET and integrin signaling effectively abrogated CAF-mediated resistance of EML4-ALK-driven NSCLC cells to ALK TKIs in vitro. Consistently, combination of the ALK TKI alectinib with the MET TKI capmatinib and/or the integrin inhibitor cilengitide was significantly more efficacious than single agent treatment in suppressing tumor growth using an in vivo EML4-ALK-dependent allograft mouse model of NSCLC. In summary, these findings emphasize the complexity of resistance-associated crosstalk between CAFs and cancer cells, which can involve multiple concurrent signaling pathways, and illustrate how comprehensive elucidation of paracrine and juxtacrine resistance mechanisms can inform on more effective therapeutic approaches.

cancer biology↗

bioRxiv2024

Fitness consequences of structural variation inferred from a House Finch pangenome

Genomic structural variants (SVs) play a crucial role in adaptive evolution, yet their average fitness effects and characterization with pangenome tools are understudied in wild animal populations. We constructed a pangenome for House Finches, a model for studies of host-pathogen coevolution, using long-read sequence data on 16 individuals (32 de novo-assembled haplotypes) and one outgroup. We identified 643,207 SVs larger than 50 base pairs, mostly (60%) involving repetitive elements, with reduced SV diversity in the eastern US as a result of its introduction by humans. The distribution of fitness effects of genome-wide SVs was estimated using maximum likelihood approaches and showed SVs in both coding and non-coding regions to be on average more deleterious than smaller indels or single nucleotide polymorphisms. The reference-free pangenome facilitated discovery of a 10-million-year-old, 11-megabase-long pericentric inversion on chromosome 1. We found that the genotype frequencies of the inversion, estimated from 135 birds widely sampled geographically and temporally, increased steadily over the 25 years since House Finches were first exposed to the bacterial pathogen Mycoplasma gallispecticum and showed signatures of balancing selection, capturing genes related to immunity and telomerase activity. We also observed shorter telomeres in populations with a greater number of years exposure to Mycoplasma. Our study illustrates the utility of applying pangenome methods to wild animal populations, helps estimate fitness effects of genome-wide SVs, and advances our understanding of adaptive evolution through structural variation. Significance StatementPrevailing genomic research on adaptive and neutral evolution has focused primarily on single nucleotide polymorphisms (SNPs). However, structural variation (SV) plays a critical role in animal adaptive evolution, often directly underlying fitness-relevant traits, although their average effects on fitness are less well understood. Our study constructs a pangenome for the House Finch using long-read sequencing, capturing the full spectrum of genomic diversity without use of a reference genome. In addition to detecting over half a million SVs, we also document a large inversion that shows evidence of contributing to disease resistance. Our use of long-read sequencing and pangenomic approaches in a wild bird population presents a compelling approach to understanding the complexities of molecular ecology and adaptive evolution. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/594184v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@214697org.highwire.dtl.DTLVardef@a18da1org.highwire.dtl.DTLVardef@59486dorg.highwire.dtl.DTLVardef@1a2196b_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2024

AHR activation accelerates the resolution of TGF-β1 induced fibroblast activation and promotes alveolar type 1 cell regeneration in alveolar organoids

Regeneration of the alveolar epithelium is necessary to restore tissue architecture and gas exchange capabilities in chronic pulmonary diseases such as fibrosing interstitial lung disease. While it is known alveolar type 2 (AT2) cells give rise to alveolar type 1 (AT1) cells to repair the alveolar epithelium after injury, methods to promote this process under pathological settings are poorly understood. Here, using a complex 3D organoid culture with TGF-{beta}1 dependent impaired AT1 spheroid formation, we performed a high-throughput screen (HTS) with [~]16,800 compounds to identify small molecules that increase number of AT1 spheroids. Longitudinal single cell RNA sequencing (scRNA-seq) revealed that DB-11-BE87 increased AT1 regeneration by reducing TGF-{beta}1 induced fibroblast activation, concurrently with AHR activation in those cells. These studies highlight a novel HTS system to identify factors that can promote AT1 differentiation and suggest AHR activation as a method to counteract pathological TGF-{beta}1 signaling in pulmonary disease.

cell biology↗

bioRxiv2024

A natural language processing system for the efficient extraction of cell markers

1.BackgroundIn the last few years, single-cell RNA sequencing (scRNA-seq) has been widely used in various species and tissues. The construction of the cellular landscape for a given species or tissue requires precise annotation of cell types, which relies on the quality and completeness of existing empirical knowledge or manually curated cell marker databases. The natural language processing (NLP) technique is a potent tool in text mining that enables the rapid extraction of entities of interest and relationships between them by parsing the syntax structure. Methods and resultsWe developed MarkerGeneBERT, an NLP-based system designed to automatically extract information about species, tissues, cell types and cell marker genes by parsing the full texts of the literature from single-cell sequencing studies. As a result, 8873 cell markers of 1733 cell types in 435 human tissues/subtissues and 9064 cell markers of 1832 cell types in 492 mouse tissues/subtissues were collected from 3987 single-cell sequencing-related studies. By comparison with the marker genes of existing manual curated cell marker databases, our method achieved 76% completeness and 75% accuracy. Furthermore, within the same literature, we found 89 cell types and 183 marker genes for which the cell marker database was not available. Finally, we annotated brain tissue single-cell sequencing data directly using the compiled list of brain tissue marker genes from our software, and the results were consistent with those of the original studies. Taken together, the results of this study illustrate for the first time how systematic application of NLP-based methods could expedite and enhance the annotation and interpretation of scRNA-seq data.

bioinformatics↗

bioRxiv2023

Compound activity prediction with dose-dependent transcriptomic profiles and deep learning

Predicting compound activity in assays is a long-standing challenge in drug discovery. Computational models based on compound-induced gene-expression signatures from a single profiling assay have shown promise towards predicting compound activity in other, seemingly unrelated, assays. Applications of such models include predicting mechanisms-of-action (MoA) for phenotypic hits, identifying off-target activities, and identifying polypharmacologies. Here, we introduce Transcriptomics-to-Activity Transformer (TAT) models that leverage gene-expression profiles observed over compound treatment at multiple concentrations to predict compound activity in other biochemical or cellular assays. We built TAT models based on gene-expression data from a RASL-Seq assay to predict the activity of 2,692 compounds in 262 dose response assays. We obtained useful models for 51% of the assays as determined through a realistic held-out set. Prospectively, we experimentally validated the activity predictions of a TAT model in a malaria inhibition assay. With a 63% hit rate, TAT successfully identified several sub-micromolar malaria inhibitors. Our results thus demonstrate the potential of transcriptomic responses over compound concentration and the TAT modeling framework as a cost-efficient way to identify the bioactivities of promising compounds across many assays.

bioinformatics↗

bioRxiv2023

Human subcortical pathways automatically detect collision trajectory without attention and awareness

Detecting imminent collisions is essential for our survival and is likely supported by evolutionarily conserved mechanisms in the brain. Using high-resolution 7T fMRI, we investigated subcortical pathways for detecting collision trajectories in healthy human subjects and hemianopic patients. When healthy participants focused their attention on a central fixation task, their superior colliculus (SC), ventromedial pulvinar (vmPul) and ventral tegmental area (VTA) elicited stronger responses to a peripheral object approaching on head-collision courses compared to near-miss trajectories. Correlation and path analyses of collision-sensitive responses revealed collision sensitivity in the SC-vmPul and SC-VTA pathways without attention and cortical influence. Both behavioral performance and SC responses showed higher sensitivity to looming stimuli from the upper visual field. For hemianopic patients with unilateral lesions of the geniculostriate pathway, the ipsilesional SC, vmPul and VTA showed collision sensitivity to looming stimuli in their blind visual field, in the absence of their awareness. Stronger responses in the SC were also associated with better detection performance of the collision events. These findings clearly demonstrate that human tectofugal pathways, without attention and awareness, automatically detects approaching objects on a collision course, supporting blindsight to impending visual threats. HighlightsO_LISC-vmPul and SC-VTA pathways show collision sensitivity without attention and cortical influence in healthy participants. C_LIO_LIBoth behavioral performance and SC responses show higher sensitivity to looming stimuli from the upper visual field. C_LIO_LIThe ipsilesional SC, vmPul and VTA of hemianopic patients automatically detects collision trajectories in their blind visual field without awareness. C_LIO_LISC response is associated with "blindsight" detection of impending collisions. C_LI

neuroscience↗

bioRxiv2022

A high-throughput COPD bronchosphere model for disease-relevant phenotypic compound screening

COPD is the third leading cause of death worldwide, but current therapies for COPD are only effective at treating the symptoms of the disease rather than targeting the underlying pathways that are driving the pathogenic changes. The lack of targeted therapies for COPD is in part due to a lack of knowledge about drivers of disease progression and the difficulty in building relevant and high throughput models that can recapitulate the phenotypic and transcriptomic changes associated with pathogenesis of COPD. To identify these drivers, we have developed a cigarette smoke extract (CSE)-treated bronchosphere assay in 384-well plate format that exhibits CSE-induced decreases in size and increase in luminal secretion of MUC5AC. Transcriptomic changes in CSE-treated bronchospheres resemble changes that occur in human smokers both with and without COPD compared to healthy groups, indicating that this model can capture human smoking signature. To identify new targets, we ran a small molecule compound deck screening with diversity in target mechanisms of action and identified hit compounds that attenuated CSE induced changes, either decreasing spheroid size or increasing secreted mucus. This work provides insight into the utility of this bronchosphere model in examining human respiratory diseases, the pathways implicated by CSE, and compounds with known mechanisms of action for therapeutic development.

cell biology↗

bioRxiv2022

Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy. Author SummaryProtein post-translational modifications (PTMs), such as phosphorylation, ubiquitination, and acetylation, are extensively employed by cell signaling pathways that regulate cell division, differentiation, migration, and cancer. We used machine learning to identify PTM clusters that represent functional modules in cell signaling pathways. These clusters were used to identify protein-protein interactions, and interactions between cell signaling pathways, that were active in lung cancer cells that were treated with anti-cancer drugs. We model these interactions as networks at three levels of granularity at the pathway, protein-protein interaction, and PTM levels. Interrogation of these networks yielded insights into molecular interactions between cell signaling pathways activated by oncogenes, transmembrane transport of small molecules, and glycolysis and gluconeogenesis. These analyses identify previously unappreciated mechanisms of crosstalk among signaling pathways between oncogenic tyrosine kinase signaling and proteins that regulate metabolic reprogramming in lung cancer, revealing new potential drug targets for combination therapy.

cancer biology↗