Biology subjects

Khan, S. A.

Publications and source records attributed to Khan, S. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Gut-Associated Metabolites (GAMs) revitalize dysfunctional CD8⁺ T lymphocytes in Osteosarcoma

Osteosarcoma (OS) is one of the top ranking and deadliest primary malignant bone tumor of youngsters and adolescents. OS has poor prognostic features due to its immunosuppressive "cold" tumor microenvironment, obstructing the anti-tumor effector functions of immune cells (including cytotoxic CD8 T lymphocytes). Recent developments have focused on the role of Gut Microbiota in modulating effector immune responses in various cancers. However, the immunomodulatory role of gut microbiota and its derived gut-associated metabolites (GAMs) in OS still remains unclear. Here we report that peripheral CD8 T lymphocytes in osteosarcoma patients are less frequent in circulation, hypo-producers of effector cytokines (IFN-{gamma} and TNF-), and have compromised metabolic fitness. We characterized and investigated the effect of a panel of microbiota-derived GAMs on CD8 T lymphocytes, confirming their immunomodulatory role with respect to CD8 T lymphocytes activation, cellular metabolism and effector functions. Indole-3-lactic acid (ILA; product of tryptophan metabolism), was observed to be the strongest immunostimulant among all the GAMs studied. ILA enhanced the anti-tumor effector functions of CD8 T lymphocytes through increased glucose uptake, a higher mitochondrial bio-mass and increased production of IFN-{gamma} and TNF-. Moreover, ILA-primed cytotoxic T lymphocytes exhibited considerably higher cytotoxicity and increased apoptosis of osteosarcoma cells (U2OS). Altogether, our data demonstrates that ILA acts as a microbial-derived immune modulator to metabolically reprogram and restore dysfunctional CD8 T lymphocytes against osteosarcoma. This study for the first time demonstrates the therapeutic potential of exploiting the nexus between "Gut-Immune-Bone Tumor" ternary as a safe and cost-effective combinatorial immunotherapy against osteosarcoma. Graphical AbstractIndole-3-Lactic Acid (ILA) Reinvigorates CD8+ T-Cell Immunity in Osteosarcoma Circulating CD8+ T cells from osteosarcoma patients exhibit impaired metabolic fitness, reduced effector cytokine production, and diminished tumoricidal activity. Screening of gut-associated metabolites identified the microbial tryptophan metabolite indole-3-lactic acid (ILA) as the most potent immunomodulator. ILA restores glucose uptake and mitochondrial biomass, enhances IFN-{gamma} and TNF- production, promotes polyfunctional CD8+ T-cell responses, and significantly improves CTL-mediated killing of osteosarcoma cells, highlighting its potential as a microbiota-derived immunometabolic therapeutic for osteosarcoma. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/741694v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@19809aforg.highwire.dtl.DTLVardef@a3eb09org.highwire.dtl.DTLVardef@19bada3org.highwire.dtl.DTLVardef@1a4c4da_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Aging restricts colorectal tumor growth by epigenetically silencing developmental gene programs

The incidence of early-onset colorectal cancer (CRC) has risen sharply in recent decades1, yet the biological basis underlying the distinct behavior of tumors arising in young versus aged tissues remains poorly understood. Here we show that aging reprograms the epigenetic landscape of the colon, restricting colon tumor growth through stable silencing of developmental and fetal gene programs. We find that colon tumors arising in aged mice are intrinsically less proliferative than those arising in young animals. Multi-omic profiling of normal colon and colon tumors reveals that aging drives DNA hypermethylation, loss of Polycomb-associated chromatin states, and reduced chromatin accessibility at a defined set of developmental genes that are bivalent (marked by both H3K27me3 and H3K4 methylation), transcriptionally active in colon tumors from young animals and repressed in both tumors and normal tissue from old animals. Among the genes most strongly repressed in old animals is Tacstd2 (Trop2), a regulator of fetal intestinal programs and epithelial stemness. Pharmacologic inhibition of DNA methylation reactivates the aging-silenced gene network in organoids from old animals, whereas genetic disruption of Tacstd2 suppresses growth and developmental transcriptional programs in young tumor organoids. TACSTD2, fetal gene signatures, and the aging-associated bivalent gene program are likewise repressed in late-onset vs. early-onset human colorectal cancers. Collectively, these findings identify age-associated epigenetic silencing of developmental gene programs as a causal mechanism that constrains colorectal tumor growth and provide a mechanistic framework for understanding the distinct biology of early-onset colorectal cancer.

cancer biology↗

bioRxiv2025

Cross-Species Morphology Learning Enables Nucleic Acid-Independent Detection of Live Mutant Blood Cells

In both neonates and adults, the presence of malignancy-associated mutations in peripheral blood (PB) correlates with an elevated risk of future neoplastic transformation, with certain mutations, such as KMT2A rearrangements, exhibiting near-complete penetrance. If feasible, pre-malignant screening could enable early intervention and even disease prevention. However, nucleic acid sequencing- and hybridization-based mutation detection have limited cost-efficiency, constraining their use in screening. Here, we introduce a computer vision platform that can identify mutant cells in fresh PB samples that carry KMT2A-MLLT3 (a frequent mutation in pediatric and adult leukemias and detectable in newborn blood samples) or JAK2V617F (a frequent mutation in myeloproliferative neoplasms and clonal hematopoiesis). This is achieved by high-throughput single-cell imaging and mutation detection by machine learning (ML)-powered morphology recognition. The ML models were developed by cross-species learning of conserved features between mutant cells from mouse genetic models and from human samples, enabling a cost-effective approach for detecting mutations in live blood cells. This platform holds promise for pre-malignant screening in asymptomatic neonates and adults with KMT2A-MLLT3 or JAK2V617Fmutation and is potentially generalizable to the detection other malignancy-associate mutations. Our platform provides a novel single-cell morphological data modality that complements existing single-cell genomics.

pathology↗

bioRxiv2025

Medium-Chain Fatty Acid exposure in non-transformed mammary glands leads to pro-tumorigenic alterations associated with aging

The local breast environment is a valuable research focus for identifying the etiological and biological factors that contribute to the development of breast cancer. Single-cell RNA sequencing shows that the increased availability of the medium-chain fatty acid octanoic acid induces changes typical of the aged mammary gland, including downregulation of cell-cell junctions, altered extracellular matrix (ECM)-receptor interactions, and upregulation of aging markers like MDK and GDF15. Ex vivo exposure to medium-chain fatty acids compromises cell-cell junctions leading to cell dissemination. As aging is associated with an increased risk of developing breast cancer, it is crucial to identify the factors driving these age-related changes in the mammary gland to develop effective cancer prevention strategies. Given that the proportion of breast adipocytes increases with age, we propose that the remodeling of the mammary gland associated with aging is partly due to the increase in adipocytes and fatty-acid release.

cancer biology↗

bioRxiv2025

DNA methylation patterns in breast cancer, paired benign tissue from ipsilateral and contralateral breast, and healthy controls.

BackgroundEpigenetic changes, particularly DNA methylation, are crucial to breast cancer development. Tumor-adjacent normal (AN) tissue frequently serves as a reference for characterizing genomic alterations but is reported to share some characteristics with tumors. However, it is unclear whether ANs epigenetic profiles reflect a predisposition to cancer or a response to the presence of the tumor. We address this gap by systematically comparing methylation profiles of tumor, AN, and matched-benign tissues from both breasts, as well as to healthy donated breast tissue. MethodsWe studied four different sample categories from 69 cancer cases: tumor (TU), AN, ipsilateral opposite quadrant (OQ), and contralateral unaffected breast (CUB); and healthy donated breast (HDB) tissue from 182 cancer-unaffected donors. These constitute a "tumor proximity axis" (TPxA): HDB[->]CUB[->]OQ[->]AN[->]TU. Methylation profiles were assayed using Illuminas Infinium Methylation EPICv1.0 BeadChip. Differential methylation (DM) analysis was conducted, and the significantly DM CpGs were analyzed for enrichment of transcription factor binding sites (TFBS) and other features. ResultsFollowing data processing and quality control, there were 69 TU, 60 AN, 67 OQ, 68 CUB, and 182 HDB samples for analysis. DM analysis showed distinct methylation profiles of TU relative to benign tissues, whereas case-benign tissues were similar to each other but distinct from HDB. Hypomethylated sites in case-benign versus HDB were enriched for TF binding sites of TP63, GATA3, ESR1, PR, AR, NR3C1, and GREB1. TU hypermethylation events were enriched for Polycomb-repressive complex 2 (PRC2) binding, including EZH2, SUZ12, and JARID2, with hypermethylation enrichment for PRC2-related binding motifs in both ER+ and ER- tumors. TU methylation profiles were otherwise highly distinct by ER status: TFBS enrichment of hypomethylation events for hormone receptor-related pathways in ER+ tumors and for hematopoiesis/immune-related pathways in ER- tumors. We found no differential methylation between benign tissues from patients with ER+ vs. ER- tumors. ConclusionsDNA methylation profiles differ profoundly at two points: tumor to case-benign and case-benign to HDB, with clear distinction between ER+ and ER- tumors. Case-benign tissues are not epigenetically "normal", are similar across both breasts, and do not differ by ER status of paired tumors.

cancer biology↗

bioRxiv2025

Genetic mapping in Collaborative Cross mouse strains identifies loci that affect initial sensitivity to cocaine

We identified two Collaborative Cross (CC) strains, CC004/TauUncJ (CC004) and CC041/TauUncJ (CC041), that differ significantly for locomotor response and self-administration of cocaine. In the current study, we crossed each of these strains to C57BL/6NJ (B6N) mice to produce two F2 populations and identify genetic loci that influence locomotor response to cocaine. We identified three significant loci on chromosomes 7, 11 and 14 in the CC041 F2 mapping cross that collectively explain 14% of the phenotypic variance for locomotor response to cocaine. We used a bioinformatic approach to identify high quality candidate genes that are genetically plausible, have functional relevance and are suitable for further exploration. Our study is the first to use CC strains to perform QTL mapping for addiction-related phenotypes and proposes several candidate genes for follow-up analyses.

genetics↗

bioRxiv2025

Separation measurement of two freely rotating dipole emitters at near optimal precision

According to Rayleighs criterion, two incoherent emitters with a separation below the diffraction limit are not resolvable with a conventional fluorescence microscope. One method of Super-Resolution Microscopy (SRM) circumvents the diffraction-limited resolution by precisely estimating the position of spatiotemporally independent emitters. However, these methods of SRM techniques are not optimal for estimating the separation of two simultaneously excited emitters. Recently, a number of detection methods based on modal imaging have been developed to achieve the quantum Cramer-Rao lower bound (QCRB) to estimate the separations between two nearby emitters. The QCRB determines the minimum achievable precision for all possible detection methods. Current modal imaging techniques assume a scalar field generated from a point source, such as a distant source from an optical fiber or a pinhole. However, for fluorescently labeled samples, point emitters are single fluorophores that are modeled as dipole emitters and, in practice, are often freely rotating. Dipole radiation must be described by vectorial theory, and the assumption of a scalar field no longer holds. Here, we present a method to numerically calculate the QCRB for measuring the separation of two dipole emitters, incorporating the vectorial theory. Furthermore, we propose a near-quantum optimal detection scheme based on one of the modal imaging techniques, super-localization by image inversion interferometry (SLIVER), for estimating the separation of two freely rotating dipoles. In the proposed method, we introduce a vortex wave plate before the SLIVER detection to separate the radial and azimuthal components of the dipole radiation. With numerical simulations, we demonstrated that our method achieves non-divergent precision at any separation between two dipole emitters. We investigated several practical effects relevant to experimental measurements in super-resolution microscopy, including numerical aperture, detection bandwidth, number of estimation parameters, background, and misalignment on separation estimation. Our proposed measurement provides a near quantum-limited detection scheme for measuring the separation of two freely-rotating dipole emitters, such as fluorescently tagged molecules, which are commonly used in super-resolution microscopy.

biophysics↗

bioRxiv2024

SpatialDiffusion: Predicting Spatial Transcriptomics with DenoisingDiffusion Probabilistic Models

Spatial Transcriptomics (ST) allows deep characterization of the 2D organization of expression data within tissue slices. The ST technology provides a tissue contextualization of deep single-cell profiles. Recently, numerous computational and machine learning methods have addressed challenges such as data quality, augmentation, annotation, and the development of integrative platforms for data analysis. In contrast, here we ask whether unseen spatial transcriptomics data can be predicted and if we can interpolate novel transcriptomic slices. To this end, we adopt a denoising diffusion probabilistic-based model (DDPM) to demonstrate the learning of generative ST models for several tissues. Furthermore, our generative diffusion model interpolates (predicts) unseen slices located "between" the collected finite number of ST slices. This methodology set the stage for learning predictive deep 3D models of tissues from a finite number of spatial transcriptomics slices, thus harboring the advent of AI-augmented spatial transcriptomics.

bioinformatics↗

bioRxiv2024

Metabolic shift to serine pathway induced by lipids confers oncogenic properties in non-transformed breast cells

A lipid metabolism gene signature is associated with the risk of estrogen negative breast cancer (ER-BC). In vitro, lipid exposure alters histone methylation affecting gene expression and increasing flux through various metabolic reactions; but little is known about the mechanism(s) linking lipids and epigenetic reprogramming with the genesis of ER-BC. Here we show that the metabolism of the medium-chain fatty acid Octanoic Acid (OA) in preference to glucose and glutamine results in a metabolic shift toward the serine pathway increasing the production of SAM, glutathione, and 2-HG, with implications for oncogenesis: SAM production results in epigenetic fostered plasticity leading to reprogramming/selecting cells that express Neural, EMT and BC related genes. 2-HG exposure results in appearance of DNA breaks, potentially consequent to the inhibition of essential demethylases for HR repair. ROS increases shortly after OA exposure and is mitigated by antioxidant defenses, which favors/enables the survival of specific cell subtypes.

cancer biology↗

bioRxiv2024

Quantifying the fitness effects of resistance alleles with and without anthelmintic selection pressure using Caenorhabditis elegans

Albendazole and ivermectin are the two most commonly co-administered anthelmintic drugs in mass-drug administration programs worldwide. Despite emerging resistance, we do not fully understand the mechanisms of resistance to these drugs nor the consequences of delivering them in combination. Albendazole resistance has primarily been attributed to variation in the drug target, a beta-tubulin gene. Ivermectin targets glutamate-gated chloride channel (GluCl) genes, but it is unknown whether these genes are involved in ivermectin resistance in nature. Using Caenorhabditis elegans, we defined the fitness costs associated with loss of the drug target genes singly or in combinations of the genes that encode GluCl subunits. We quantified the loss-of-function effects on three traits: (i) multi-generational competitive fitness, (ii) fecundity, and (iii) development. In competitive fitness and development assays, we found that a deletion of the beta-tubulin gene ben-1 conferred albendazole resistance, but ivermectin resistance required loss of two GluCl genes (avr-14 and avr-15) or loss of three GluCl genes (avr-14, avr-15, and glc-1). The fecundity assays revealed that loss of ben-1 did not provide any fitness benefit in albendazole and that no GluCl deletion mutants were resistant to ivermectin. Next, we searched for evidence of multi-drug resistance across the three traits. Loss of ben-1 did not confer resistance to ivermectin, nor did loss of any single GluCl subunit or combination confer resistance to albendazole. Finally, we assessed the development of 124 C. elegans wild strains across six benzimidazoles and seven macrocyclic lactones to identify evidence of multi-drug resistance between the two drug classes and found a strong phenotypic correlation within a drug class but not across drug classes. Because each gene affects various aspects of nematode physiology, these results suggest that it is necessary to assess multiple fitness traits to evaluate how each gene contributes to anthelmintic resistance. AUTHOR SUMMARYControl of parasitic nematodes often depends on mass-drug administration (MDA) programs, where combinations of anthelmintics are distributed to at-risk populations. Two commonly co-administered anthelmintic drugs in MDA programs are albendazole and ivermectin, and resistance to both drugs has emerged. Although the mechanism of resistance (MoR) to albendazole has been primarily attributed to variation in a beta-tubulin gene, the MoR to ivermectin remains unknown. Ivermectin acts through pentameric glutamate-gated chloride channels (GluCls). However, it is unclear whether genes that encode GluCls are involved in ivermectin resistance in parasitic nematodes. Using Caenorhabditis elegans, we quantified the fitness costs associated with deletions of the beta-tubulin gene ben-1 and three genes encoding GluCl subunits avr-14, avr-15, and glc-1 on three traits: (i) multi-generational competitive fitness, (ii) fecundity, and (iii) development. We found different anthelmintic responses across strains and traits but no evidence of multi-drug resistance. Our results suggest that multiple traits should be considered to understand resistance comprehensively and that the determination of whether a gene plays a role in anthelmintic resistance depends on the trait measured. Understanding the quantitative effects and fitness-associated costs of each GluCl subunit in C. elegans can help explain the costs of mutations in these subunits in parasites.

genetics↗

bioRxiv2023

Foundation Models Meet Imbalanced Single-Cell Data When Learning Cell Type Annotations

With the emergence of single-cell foundation models, an important question arises: how do these models perform when trained on datasets having an imbalance in cell type distribution due to rare cell types or biased sampling? We benchmark three foundation models, scGPT, scBERT, and Geneformer, using skewed single-cell cell-type distribution for cell-type annotation. While all models had reduced performance when challenged with rare cell types, scGPT and scBERT, performed better than Geneformer. Notably, in contrast to scGPT and scBERT, Geneformer uses ordinal positions of the tokenized genes rather than actual raw gene expression values. To mitigate the effect of a skewed distribution, we find that random oversampling, but not random undersampling, improved the performance for all three foundation models. Finally, scGPT, using FlashAttention, has the fastest computational speed, whereas scBERT is more memory-efficient. We conclude that tokenization and data representation are essential areas of research, and new strategies are needed to mitigate the effects of imbalanced learning in single-cell foundation models. Code and data for reproducibility are available at https://github.com/SabbaghCodes/ImbalancedLearningForSingleCellFoundationModels.

bioinformatics↗

bioRxiv2023

Asparagine synthetase and G-protein coupled estrogen receptor are critical responders to nutrient supply in KRAS mutant colorectal cancer

The nutrient status of the tumor microenvironment has major impacts on cell growth. Under nutrient depletion, asparagine synthetase (ASNS)-mediated asparagine production increases to sustain cell survival. G protein-coupled estrogen receptor-1 (GPER1) signaling converges via cAMP/PI3K/AKT with KRAS signaling to regulate ASNS expression. However, the role of GPER1 in CRC progression is still debated, and the effect of nutrient supply on both ASNS and GPER1 relative to KRAS genotype is not well understood. Here, we modeled a restricted nutrient supply by eliminating glutamine from growing cancer cells in a 3D spheroid model of human female SW48 KRAS wild-type (WT) and KRAS G12A mutant (MT) CRC cells, to examine effects on ASNS and GPER1 expression. Glutamine depletion significantly inhibited cell growth in both KRAS MT and WT cells; however, ASNS and GPER1 were upregulated in KRAS MT compared to WT cells. When nutrient supply was adequate, ASNS and GPER1 were not altered between cell lines. The impact of estradiol, a ligand for GPER1, was examined for any additional effects on cell growth. Under glutamine deplete conditions, estradiol decreased the growth of KRAS WT cells but had no effect on KRAS MT cells; estradiol had no additive or diminutive effect on the upregulation of ASNS or GPER1 between the cell lines. We further examined the association of GPER1 and ASNS levels with overall survival in a clinical colon cancer cohort of The Cancer Genome Atlas. Both high GPER1 and ASNS expression associated with poorer overall survival for females only in advanced stage tumors. These findings suggest that KRAS MT cells have mechanisms in place that respond to decreased nutrient supply, typically observed in advanced tumors, by increasing the expression of ASNS and GPER1 to drive cell growth. Furthermore, KRAS MT cells are resistant to the protective effects of estradiol under nutrient deplete conditions. ASNS and GPER1 may therefore be potential therapeutic targets that can be exploited to manage and control KRAS MT CRC.

cancer biology↗

bioRxiv2023

LEP-AD: Language Embedding of Proteins and Attention to Drugs predicts drug target interactions

AO_SCPLOWBSTRACTC_SCPLOWPredicting drug-target interactions is a tremendous challenge for drug development and lead optimization. Recent advances include training algorithms to learn drug-target interactions from data and molecular simulations. Here we utilize Evolutionary Scale Modeling (ESM-2) models to establish a Transformer protein language model for drug-target interaction predictions. Our architecture, LEP-AD, combines pre-trained ESM-2 and Transformer-GCN models predicting binding affinity values. We report new best-in-class state-of-the-art results compared to competing methods such as SimBoost, DeepCPI, Attention-DTA, GraphDTA, and more using multiple datasets, including Davis, KIBA, DTC, Metz, ToxCast, and STITCH. Finally, we find that a pre-trained model with embedding of proteins (the LED-AD) outperforms a model using an explicit alpha-fold 3D representation of proteins (e.g., LEP-AD supervised by Alphafold). The LEP-AD model scales favorably in performance with the size of training data. Code available at https://github.com/adaga06/LEP-AD

bioinformatics↗

bioRxiv2023

A comparative study of low-pH tolerance and chitinase activity between toxigenic and non-toxigenic strains of Vibrio cholerae

Cholera toxin, encoded by the ctx gene, is a key virulence factor in toxigenic Vibrio cholerae (ctx+) strains. However, some non-toxigenic V. cholerae (ctx-) strains are also pathogenic to humans and the mechanism involved in low-pH tolerance and pathogenicity in these strains remains unclear. To address this, we profiled the growth and chitinase activity in different pH of two clinical isolates of V. cholerae: VC20, a ctx+ strain, and WO5, a ctx- strain. We also compared the expression level of key genes involved in pathogenesis between the strains. WO5, the non-toxigenic strain had robust growth and greater chitinase activity across a wide pH range, in comparison to VC20. Additionally, WO5 expressed higher levels of transcripts from genes implicated in host cell adhesion and virulence, namely ompK and toxT, respectively. Notably, we propose that lower hapR levels in WO5 contrary to VC20 is key to its low-pH tolerance. To systematically identify genes involved in low pH tolerance, we used a sequence-based homology search and found a widespread presence of low-pH adaptation modules, lysine-cadaverine, and ornithine-putrescine in multiple representative species of the Vibrio phylum. Furthermore, our analysis suggests that the loss of a gene encoding nitrite reductase that confers low pH tolerance is specific to V. cholerae and V. mimicus. Together, these findings reveal that the low-pH tolerance enhances the chitinase activity of the non-toxigenic strain that could help V. cholerae to survive the acidic environment of the stomach and readily colonize the intestine.

microbiology↗

bioRxiv2023

Indigenous Reduction of Multi-drug Resistant Bacterial Pathogens in a Natural Uncontrolled Fermented Milk Ecosystem

Raw milk and its products have been questioned for microbiological safety. However, Dahi: an artisanally fermented milk product that is yet microbiologically unexplored is popularly known for therapeutic uses in public. Aiming safety and therapeutic assessment of dahi, samples of raw milk and dahi were analysed for microbiology and bacterial pathogens. The pathogens were also evaluated for antibiotic resistance. Further dahi samples were assessed for antipathogen effect. The total bacterial count of raw milk was between 3.80 x 1002 to 2.97 x 1007 and total fungal count was 2.50 x 1001 to 4.90 x 1002 whereas total bacterial and fungal count of Dahi was 3.00 x 1001 to 4.05 x 1009 and 2.00 x 1001 to 5.30 x 1007. Bacterial population of the Dahi was found dominated by lactic acid bacteria. In milk samples, E. coli was detected as 38%, S. aureus 28%, L. monocytogenes 3%, Salmonella 42% and Pseudomonas spp 31%. In Dahi samples, their percentages were 7%, 10%, 7%, 8% and 2% respectively. The detected pathogens were found resistant against different antibiotics especially to third and fourth generations of cephalosporin and other beta-lactam drugs. When assessed invitro, the low incidence of pathogens in the Dahi samples were associated to its inhibitory effect against pathogens. Dahi samples also inhibited the growth of antibiotic resistance ATCC strains. The inhibitory activity of the Dahi is due to the changes occurs during fermentation but not corelated to the pH of the Dahi.

microbiology↗

bioRxiv2022

Homeostatic responses to hypoxia by the carotid body and adrenal medulla are based on mutual antagonism between HIF-1α and HIF-2α

Respiration and blood pressure (BP) are regulated to maintain optimal delivery of O2 to every cell in the body. Arterial hypoxemia is sensed by the carotid body (CB), which initiates sympathetic reflex arcs to the diaphragm to increase ventilation, and to the adrenal medulla (AM) to increase catecholamine secretion and thereby increase BP. However, the underlying molecular mechanisms have not been fully delineated. Here, we report that the relative activities of hypoxia-inducible factor-1 (HIF-1) and HIF-2 determine the set point for the CB and AM, with respect to their maintenance of BP and respiration. In Hif2a+/- mice, which are heterozygous for a knockout allele at the locus encoding HIF-2, expression of HIF-1 and NADPH oxidase 2 was increased in the CB and AM, resulting in an oxidized intracellular redox state with augmented sensitivity to hypoxia, increased BP, and respiratory abnormalities, which were all normalized by treatment with a HIF-1 inhibitor or a superoxide anion scavenger. By contrast, in Hif1a+/- mice, which are heterozygous for a knockout allele at the locus encoding HIF-1, the expression of HIF-2 and superoxide dismutase 2 was increased in the CB and AM, resulting in a reduced intracellular redox state with impaired CB and ventilatory responses to chronic hypoxia, which were normalized by treatment with a HIF-2 inhibitor. None of the abnormalities that were observed in Hif1a+/- or Hif2a+/- mice were observed in Hif1a+/-; Hif2a+/- double- heterozygous mice. Our results demonstrate that redox balance in the CB and AM, which is determined by mutual antagonism between HIF- isoforms, establishes the set point for responses of the CB and AM to hypoxia, and is required for the maintenance of normal BP and respiration.

physiology↗

bioRxiv2022

Multi-modal single-cell and whole-genome sequencing of minute, frozen specimens to propel clinical applications

Single-cell genomics are enabling technologies, but their broad clinical application remains challenging. We report an easily adaptable approach for single-cell transcriptome and T cell receptor (TCR)-sequencing, and matched whole-genome sequencing from tiny, frozen clinical specimens. We achieve similar quality and biological outputs while reducing artifactual signals compared to data from matched fresh tissue samples. Profiling sequentially collected melanoma samples from the KEYNOTE-001 trial, we resolve cellular, genomic, and clonotype dynamics that encapsulate molecular patterns of tumor evolution during anti-PD-1 therapy. To demonstrate applicability to banked biospecimens of rare diseases, we generate a large uveal melanoma liver metastasis single-cell and matched WGS atlas, which revealed niche-specific impairment of clonal T cell expansion. This study provides a foundational framework for propelling single-cell genomics to the clinical arena.

genomics↗

bioRxiv2021

Prolonged tonic pain in healthy humans enhances functional connectivity of descending pain modulation networks involving the amygdala, periaqueductal gray and parabrachial nucleus to cortical sensory-discriminative areas

IntroductionResting state functional connectivity (FC) is widely used to assess functional brain alterations in patients with chronic pain. However, reports of FC changes accompanying tonic pain in pain-free persons is rare. A brain network disrupted during chronic pain is a network we term the Descending Pain Modulatory Network (DPMN). Here, we evaluate the effect of tonic pain on FC of this network: anterior cingulate cortex (ACC), amygdala (AMYG), periaqueductal gray (PAG), and parabrachial nuclei (PBN). MethodsIn 50 pain-free participants (30F), we induced tonic pain using a capsaicin-heat pain model. We used functional MRI to measure resting BOLD signal during pain-free rest where participants experienced warmth and tonic pain where participants experienced the same temperature thermode combined with capsaicin. We evaluated FC from ACC, AMYG, PAG, and PBN with correlation of self-report pain intensity with FC during both states. We hypothesized tonic pain would disrupt FC dyads within the DPMN. We used partial correlation to determine FC correlated with pain intensity and BOLD signal. ResultsOf hypothesized FC dyads, PAG and subgenual ACC was weakly disrupted during tonic pain (F=3.34; p=0.074; pain-free>pain d=0.25). sgACC-PAG FC became positively related to pain intensity (R=0.38; t=2.81; p=0.007). Right PBN-PAG FC during pain-free rest positively correlated with subsequently experienced pain (R=0.44; t=3.43; p=0.001). During tonic pain, FC of this connection was abolished (paired t=-3.17; p=0.0026). During pain-free rest, FC between left AMYG and right superior parietal lobule and caudate nucleus were positively correlated with subsequent pain. During tonic pain, FC between left AMYG and right inferior temporal and superior frontal gyri negatively correlated with pain. Subsequent pain positively correlated with right AMYG FC and right claustrum; left and right primary visual cortex; right middle temporal gyrus and right temporo-occipitoparietal junction. Finally, subsequent pain positively correlated with PAG FC and left cerebellum, left dorsolateral prefrontal, right posterior cingulate cortex and paracentral lobule, inferior parietal lobule, medial precuneus and PBN. ConclusionWe demonstrate 1) tonic pain weakly disrupts of sgACC-PAG FC; 2) sgACC-PAG tonic pain FC positively correlates with pain; 3) right PBN-PAG FC predicts subsequent pain and is abolished during tonic pain. Finally, we reveal PAG- and right AMYG-anchored networks which predict intensity of tonic pain. Our findings suggest specific connectivity patterns within the DPMN at rest predict experienced pain and are modulated by tonic pain. These nodes and their functional modulation may reveal new therapeutic targets for neuromodulation and biomarkers to guide interventions. HighlightsO_LIParabrachial-periaqueductal gray (PAG) functional connectivity (FC) predicts pain C_LIO_LISubgenual anterior cingulate cortex-PAG FC correlates with pain during tonic pain C_LIO_LIPAG- and amydalocortical networks at rest predict tonic pain intensity C_LIO_LIResting FC of PAG supports cortical targets of neuromodulation to control pain C_LI

neuroscience↗