Biology subjects

Jones, D. R.

Publications and source records attributed to Jones, D. R..

14 recordsLinked to original sources

bioRxiv2026

Purinergic signaling promotes gliomagenesis through nuclear calcium transients

Intracellular Ca2+ transients drive key developmental and physiological processes, yet their role in oncogenesis remains incompletely understood. In glioblastoma (GBM), an aggressive brain malignancy, tumor cellular networks exhibit self-sustaining Ca2+ transients that promote tumor growth through unclear mechanisms. Using patient-derived GBM models, we show that these transients depend primarily on intracellular Ca2+ stores and extend to the nucleus to drive tumorigenesis. A neuromodulator screen identified extracellular purines ATP and ADP as potent inducers of both nuclear and cytosolic Ca2+ transients via activation of metabotropic purinergic P2RY1 receptors, whose knockdown attenuates tumorigenicity in vitro and in vivo. Mechanistically, Ca2+ transients promote tumorigenesis via the nuclear Ca2+/calmodulin-dependent kinase CAMK4, which regulates transcriptional and epigenetic programs, as well as ribosomal DNA transcription. From the therapeutic perspective, pharmacologic P2RY1 inhibition suppresses tumor growth in vitro and in vivo. Collectively, these findings reveal a pharmacologically targetable oncogenic mechanism in GBM and possibly other malignancies.

cancer biology↗

bioRxiv2025

Environmental dipolar relaxation during excited state proton transfer in Green Fluorescent Protein

Engineered variants of Green Fluorescent Protein (GFP) are in widespread use as genetically-encoded labels for biological imaging. Excitation of its neutral phenolic ground state chromophore populates an emissive anionic phenolate state via excited state proton transfer (ESPT) to E222 along a molecular wire. Computational studies indicate that ESPT fits to an electronically adiabatic rate expression. Although reactions that operate close to the adiabatic limit can be sensitive to environmental dipolar relaxation, little is known about the role of such relaxation during ESPT in GFP. Here, we present the first experimental evidence that dipolar relaxation of the protein matrix occurs during ESPT in response to the change in electron density distribution in the excited state GFP chromophore and is a key determinant of the reaction pathway. Using fluorescence spectroscopy, we excited along the red edge of the neutral phenolic ground state absorption band of several GFP variants with differing chromophore environments. Instead of resulting in a significant red shift of the centre of spectral mass (CSM) of the emission spectra common for biological chromophores such as tryptophan, the CSM of each GFP variant remains almost unchanged as a function of excitation wavelength. This is consistent with each sub-population that is selectively excited along the red edge reaching the same, fully relaxed state before emission of a photon. The kinetics of environmental dipolar relaxation are therefore on the same sub-nanosecond timescale as ESPT, which provides an explanation for its adiabatic nature and could inform the rational design of novel fluorescent proteins with tailored photophysics.

biophysics↗

bioRxiv2025

A shotgun approach for highly multiplexed mammalian metabolic engineering

Mammalian metabolic engineering is critical to advancing basic biology, bioproduction, and cell therapy. However, as pathway complexity increases, so does the size of both the combinatorial design space and the DNA constructs required, rendering unbiased screens intractable. To address this, we developed Shotgun Genetic Engineering (SGE), a scalable approach that exploits the ease of delivering many barcoded small constructs--rather than a single large one--into mammalian cells. This allows each cell to serve as an independent experiment, carrying a unique synthetic metabolic pathway that explores combinations of gene content, stoichiometry, and organellar localization. Functional pathways are identified by sequencing barcodes from cells exhibiting the desired phenotype. Using SGE, we screened millions of pathway combinations to engineer essential amino acid biosynthesis in two mammalian cell lines (CHO and Jurkat), achieving near-wild-type growth in valine-free medium and, for the first time, enabling isoleucine prototrophy in CHO cells. Successful solutions favored mitochondrial localization and required integration of 23-52 kb of synthetic DNA--lengths that are impractical to screen by conventional methods. The resulting datasets are compatible with machine learning frameworks, positioning SGE as a powerful platform for decoding and engineering complex biosynthetic traits in mammalian systems.

synthetic biology↗

bioRxiv2024

Microbiota and metabolic adaptation shape Staphylococcus aureus virulence and antimicrobial resistance during intestinal colonization

Depletion of microbiota increases susceptibility to gastrointestinal colonization and subsequent infection by opportunistic pathogens such as methicillin-resistant Staphylococcus aureus (MRSA). How the absence of gut microbiota impacts the evolution of MRSA is unknown. The present report used germ-free mice to investigate the evolutionary dynamics of MRSA in the absence of gut microbiota. Through genomic analyses and competition assays, we found that MRSA adapts to the microbiota-free gut through sequential genetic mutations and structural changes that enhance fitness. Initially, these adaptations increase carbohydrate transport; subsequently, evolutionary pathways largely diverge to enhance either arginine metabolism or cell wall biosynthesis. Increased fitness in arginine pathway mutants depended on arginine catabolic genes, especially nos and arcC, which promote microaerobic respiration and ATP generation, respectively. Thus, arginine adaptation likely improves redox balance and energy production in the oxygen-limited gut environment. Findings were supported by human gut metagenomic analyses, which suggest the influence of arginine metabolism on colonization. Surprisingly, these adaptive genetic changes often reduced MRSAs antimicrobial resistance and virulence. Furthermore, resistance mutation, typically associated with decreased virulence, also reduced colonization fitness, indicating evolutionary trade-offs among these traits. The presence of normal microbiota inhibited these adaptations, preserving MRSAs wild-type characteristics that effectively balance virulence, resistance, and colonization fitness. The results highlight the protective role of gut microbiota in preserving a balance of key MRSA traits for long-term ecological success in commensal populations, underscoring the potential consequences on MRSAs survival and fitness during and after host hospitalization and antimicrobial treatment. ImportanceThe fitness of MRSA depends on its ability to colonize. A key, underappreciated observation is that gut colonization frequently serves as the site for MRSA infections, especially among vulnerable groups such as children and hospitalized adults. By evolving MRSA strains in germ-free mice, we identify molecular mechanisms underlying how MRSA exploits a depletion in host microbiota to enhance gut colonization fitness. This work points to bacterial colonization factors that may be targetable. Our findings indicate that adaptive changes in MRSA often reduce its antimicrobial resistance and virulence, and are suppressed by the presence of native commensal bacteria. This work helps explain the ecology of pathoadaptive variants that thrive in hospital settings but falter under colonization conditions in healthy hosts. Additionally, it illustrates the potential adverse effects of prolonged, broad-spectrum empirical antimicrobial therapy and adds a new type of weight to calls for microbiota transplantation to reduce colonization by antimicrobial-resistant pathogens.

microbiology↗

bioRxiv2024

Tofacitinib uptake by patient-derived intestinal organoids predicts individual clinical responsiveness

Background & AimsDespite increasing therapeutic options in the treatment of ulcerative colitis (UC), achieving disease remission remains a major clinical challenge. Nonresponse to therapy is common and clinicians have little guidance in selecting the optimal therapy for an individual patient. This study examined whether patient-derived materials could predict individual clinical responsiveness to the Janus kinase (JAK) inhibitor, tofacitinib, prior to treatment initiation. MethodIn 48 patients with UC initiating tofacitinib, we longitudinally collected clinical covariates, stool, and colonic biopsies to analyze the microbiota, transcriptome, and exome variations associated with clinical responsiveness at week 24. We established patient-derived organoids (n = 23) to determine how their viability upon stimulation with proinflammatory cytokines in the presence of tofacitinib related to drug responsiveness in patients. We performed additional biochemical analyses of organoids and primary tissues to identify the mechanism underlying differential tofacitinib sensitivity. ResultsThe composition of the gut microbiota, rectal transcriptome, inflammatory biomarkers, and exome variations were indistinguishable among UC patients prior to tofacitinib treatment. However, a subset of patient-derived organoids displayed reduced sensitivity to tofacitinib as determined by the ability of the drug to inhibit STAT1 phosphorylation and loss of viability upon cytokine stimulation. Remarkably, sensitivity of organoids to tofacitinib predicted individual clinical patient responsiveness. Reduced responsiveness to tofacitinib was associated with decreased levels of the cationic transporter MATE1, which mediates tofacitinib uptake. ConclusionsPatient-derived intestinal organoids predict and identify mechanisms of individual tofacitinib responsiveness in UC. Specifically, MATE1 expression predicted clinical response to tofacitinib.

cell biology↗

bioRxiv2024

DELE1 promotes translation-associated homeostasis, growth, and survival in mitochondrial myopathy

Mitochondrial dysfunction causes devastating disorders, including mitochondrial myopathy. Here, we identified that diverse mitochondrial myopathy models elicit a protective mitochondrial integrated stress response (mt-ISR), mediated by OMA1-DELE1 signaling. The response was similar following disruptions in mtDNA maintenance, from knockout of Tfam, and mitochondrial protein unfolding, from disease-causing mutations in CHCHD10 (G58R and S59L). The preponderance of the response was directed at upregulating pathways for aminoacyl-tRNA biosynthesis, the intermediates for protein synthesis, and was similar in heart and skeletal muscle but more limited in brown adipose challenged with cold stress. Strikingly, models with early DELE1 mt-ISR activation failed to grow and survive to adulthood in the absence of Dele1, accounting for some but not all of OMA1s protection. Notably, the DELE1 mt-ISR did not slow net protein synthesis in stressed striated muscle, but instead prevented loss of translation-associated proteostasis in muscle fibers. Together our findings identify that the DELE1 mt-ISR mediates a stereotyped response to diverse forms of mitochondrial stress and is particularly critical for maintaining growth and survival in early-onset mitochondrial myopathy.

cell biology↗

bioRxiv2024

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

immunology↗

bioRxiv2023

The expression profile and tumorigenic mechanisms of CD97 (ADGRE5) in glioblastoma render it a targetable vulnerability

Glioblastoma (GBM) is the most common and aggressive primary brain malignancy. Adhesion G protein-coupled receptors (aGPCRs) have attracted interest for their functional role in gliomagenesis and their potential as treatment targets. To identify therapeutically targetable opportunities among aGPCR family members in unbiased fashion, we analyzed expression levels of all aGPCRs in GBM and non-neoplastic brain tissue. Using bulk and single cell transcriptomic and proteomic data, we show that CD97 (ADGRE5), an aGPCR previously implicated in GBM pathogenesis, is the most promising aGPCR target in GBM, by virtue of its abundance in all GBM tumors and its de novo expression profile in GBM compared to normal brain tissue and neural progenitors. CD97 knockdown or knockout significantly reduces the tumor initiation capacity of patient-derived GBM cultures (PDGC) in vitro and in vivo. Transcriptomic and metabolomic data from PDGCs suggest that CD97 promotes glycolytic metabolism. The oncogenic and metabolic effects of CD97 are mediated by the MAPK pathway. Activation of MAPK signaling depends on phosphorylation of the cytosolic C-terminus of CD97 and recruitment of {beta}-arrestin. Using single-cell RNA-sequencing and biochemical assays, we demonstrate that THY1/CD90 is the most likely CD97 ligand in GBM. Lastly, we show that targeting of PDGCs with an anti-CD97 antibody-drug conjugate in vitro selectively kills tumor cells but not human astrocytes or neural stem cells. Our studies identify CD97 as an important regulator of tumor metabolism in GBM, elucidate mechanisms of receptor activation and signaling, and provide strong scientific rationale for developing biologics to target it for therapeutic purposes.

cancer biology↗

bioRxiv2022

Replicative Instability Drives Cancer Progression

In the past decade, defective DNA repair has been increasingly linked with cancer progression. Human tumors with markers of defective DNA repair and increased replication stress have been shown to exhibit genomic instability and poor survival rates across tumor types. Here we utilize-omics data from two independent consortia to identify the genetic underpinnings of replication stress, therapy resistance, and primary carcinoma to brain metastasis in BRCA wildtype tumors. In doing so, we have defined a new pan-cancer class of tumors characterized by replicative instability (RIN). RIN is defined by genomic evolution secondary to replicative challenge. Our data supports a model whereby defective single-strand break repair, translesion synthesis, and non-homologous end joining effectors drive RIN. Collectively, we find that RIN accelerates cancer progression by driving copy number alterations and transcriptional program rewiring that promote tumor evolution. Statement of SignificanceDefining the genetic basis of genomic instability with wildtype BRCA repair effectors is a significant unmet need in cancer research. Here we identify and characterize a pan-cancer cohort of tumors driven by replicative instability (RIN). We find that RIN drives therapy resistance and distant metastases across multiple tumor types.

cancer biology↗

bioRxiv2021

Resurrecting essential amino acid biosynthesis in a mammalian cell

Major genomic deletions in independent eukaryotic lineages have led to repeated ancestral loss of biosynthesis pathways for nine of the twenty canonical amino acids1. While the evolutionary forces driving these polyphyletic deletion events are not well understood, the consequence is that extant metazoans are unable to produce nine essential amino acids (EAAs). Previous studies have highlighted that EAA biosynthesis tends to be more energetically costly2,3, raising the possibility that these pathways were lost from organisms with access to abundant EAAs in the environment4,5. It is unclear whether present-day metazoans can reaccept these pathways to resurrect biosynthetic capabilities that were lost long ago or whether evolution has rendered EAA pathways incompatible with metazoan metabolism. Here, we report progress on a large-scale synthetic genomics effort to reestablish EAA biosynthetic functionality in a mammalian cell. We designed codon-optimized biosynthesis pathways based on genes mined from Escherichia coli. These pathways were de novo synthesized in 3 kilobase chunks, assembled in yeasto and genomically integrated into a Chinese Hamster Ovary (CHO) cell line. One synthetic pathway produced valine at a sufficient level for cell viability and proliferation, and thus represents a successful example of metazoan EAA biosynthesis restoration. This prototrophic CHO line grows in valine-free medium, and metabolomics using labeled precursors verified de novo biosynthesis of valine. RNA-seq profiling of the valine prototrophic CHO line showed that the synthetic pathway minimally disrupted the cellular transcriptome. Furthermore, valine prototrophic cells exhibited transcriptional signatures associated with rescue from nutritional starvation. This work demonstrates that mammalian metabolism is amenable to restoration of ancient core pathways, thus paving a path for genome-scale efforts to synthetically restore metabolic functions to the metazoan lineage.

synthetic biology↗

bioRxiv2020

Single cell profiling reveals novel tumor and myeloid subpopulations in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 54,523 cellular transcriptomes from 21 human biospecimens. Our single-cell SCLC atlas reveals tumor diversity exceeding lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discovered a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival, and manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis.

cancer biology↗

bioRxiv2020

Quantifying fluorescent glycan uptake to elucidate strain-level variability in foraging behaviors of rumen bacteria

Gut microbiomes have vast catabolic potential and are essential to host health and nutrition. An in-depth understanding of the metabolic pathways in these ecosystems will enable us to design treatments (i.e. prebiotics) that influence microbiome structure and enhance host physiology. Currently, the investigation of metabolic pathways relies on inferences derived from metagenomics or in vitro cultivations, however, novel approaches targeting specific cell physiologies can illuminate the functional potential encoded within microbial (meta)genomes to accurately assess metabolic abilities. Here, we present a multi-faceted study using complimentary next-generation physiology and omics approaches to characterize the microbial adaptation to a prebiotic in the rumen ecosystem. Using fluorescently labeled polysaccharides, we identified bacteria that actively metabolize a glycan prebiotic in the rumen microbiome ex vivo. Subsequently, we characterized strain-level variability in carbohydrate utilization systems and predict metabolic strategies of isolated bovine-adapted strains of Bacteroides thetaiotaomicron using comparative whole genome sequencing, RNA-Seq, and carbohydrate-active enzyme fingerprinting.

microbiology↗

bioRxiv2020

Rapid purification and metabolomic profiling of synaptic vesicles from mammalian brain

Neurons communicate by the activity-dependent release of small-molecule neurotransmitters packaged into synaptic vesicles (SVs). Although many molecules have been identified as neurotransmitters, technical limitations have precluded a full metabolomic analysis of synaptic vesicle content. Here, we present a workflow to rapidly isolate SVs and to interrogate their metabolic contents at a high-resolution using mass spectrometry. We validated the enrichment of glutamate in SVs of primary cortical neurons using targeted polar metabolomics. Unbiased and extensive global profiling of SVs isolated from these neurons revealed that the only detectable polar metabolites they contain are the established neurotransmitters glutamate and GABA. Finally, we adapted the approach to enable quick capture of SVs directly from brain tissue and determined the neurotransmitter profiles of diverse brain regions in a cell-type specific manner. The speed, robustness, and precision of this method to interrogate SV contents will facilitate novel insights into the chemical basis of neurotransmission.

neuroscience↗

bioRxiv2016

Metabolome Identification by Systematic Stable Isotope Labeling Experiments and False Discovery Analysis with a Target-Decoy Strategy

We introduce a formula-based strategy and algorithm (JUMPm) for global metabolite identification and false discovery analysis in untargeted mass spectrometry-based metabolomics. JUMPm determines the chemical formulas of metabolites from unlabeled and stable-isotope labeled metabolome data, and derives the most likely metabolite identity by searching structure databases. JUMPm also estimates the false discovery rate (FDR) with a target-decoy strategy based on the octet rule of chemistry. With systematic stable isotope labeling of yeast, we identified 2,085 chemical formulas (10% FDR), 892 of which were assigned with metabolite structures. We evaluated JUMPm with a library of synthetic standards, and found that 96% of the formulas were correctly identified. We extended the method to mammalian cells with direct isotope labeling and by heavy yeast spike-in. This strategy and algorithm provide a powerful a practical solution for global identification of metabolites with a critical measure of confidence.

biochemistry↗