Biology subjects

Singh, R.

Publications and source records attributed to Singh, R..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

Restoration of Type 17 immune signaling is not sufficient for protection during influenza-associated pulmonary aspergillosis

Influenza-associated pulmonary aspergillosis (IAPA) is a severe complication of influenza infection that occurs in critically ill patients and results in higher mortality compared to influenza infection alone. Interleukin-17 (IL-17) and the Type 17 immune signaling pathway cytokine family are recognized for their pivotal role in fostering protective immunity against various pathogens. In this study, we investigate the role of IL-17 and Type 17 immune signaling components during IAPA. Wild-type mice were challenged with influenza A H1N1 (Flu) and then exposed to Aspergillus fumigatus ATCC42202 resting conidia on day 6 post-influenza infection, followed by the quantification of cytokines and chemokines at 48 hours post-fungal infection. Gene and protein expression levels revealed that IL-17 and Type 17 immune cytokines and antimicrobial peptides are downregulated during IAPA compared to mice singularly infected solely with A. fumigatus. Restoration of Type 17 immunity was not sufficient to provide protection against the increased fungal burden observed during IAPA. These findings contrast those observed during post-influenza bacterial super-infection, in which restoration of Type 17 immune signaling protects against exacerbation seen during super-infection. Our study highlights the need for future studies to understand the immune mechanisms that increase susceptibility to fungal infection. ImportanceIAPA significantly elevates the risk of mortality in patients with severe influenza. Type-17 immunity is critical to host defense during fungal infections and, therefore, vital to understand its role during IAPA. The observations in this study reveal that Type 17 immunity is impaired during IAPA, potentially increasing susceptibility to secondary infection with Aspergillus fumigatus. However, restoration of IL-17 signaling alone is not sufficient to reduce fungal burden in our murine IAPA model. These observations differ from those observed in post-influenza bacterial super-infections, suggesting that the mechanisms underlying viral-fungal super-infection are different than those that underly viral-bacterial super-infection. By elucidating the complex interactions between the host immune system, influenza, and A. fumigatus, these findings are vital for developing strategies to enhance immune responses and improve survival rates during IAPA.

immunology↗

bioRxiv2024

Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma.

Cancer cells show remarkable plasticity and can switch lineages in response to the tumor microenvironment. Cellular plasticity drives invasiveness and metastasis and helps cancer cells to evade therapy by developing resistance to radiation and cytotoxic chemotherapy. Increased understanding of cell fate determination through epigenetic reprogramming is critical to discover how cancer cells achieve transcriptomic and phenotypic plasticity. Glioblastoma is a perfect example of cancer evolution where cells retain an inherent level of plasticity through activation or maintenance of progenitor developmental programs. However, the principles governing epigenetic drivers of cellular plasticity in glioblastoma remain poorly understood. Here, using machine learning (ML) we employ cross-patient prediction of transcript expression using a combination of epigenetic features (ATAC-seq, CTCF ChIP-seq, RNAPII ChIP-seq, H3K27Ac ChIP-seq, and RNA-seq) of glioblastoma stem cells (GSCs). We investigate different ML and deep learning (DL) models for this task and build our final pipeline using XGBoost. The model trained on one patient generalizes to another one suggesting that the epigenetic signals governing gene transcription are consistent across patients even if GSCs can be very different. We demonstrate that H3K27Ac is the epigenetic feature providing the most significant contribution to cross-patient prediction of gene expression. In addition, using H3K27Ac signals from patients-derived GSCs, we can predict gene expression of human neural crest stem cells suggesting a shared developmental epigenetic trajectory between subpopulations of these malignant and benign stem cells. Our cross-patient ML/DL models determine weighted patterns of influence of epigenetic marks on gene expression across patients with glioblastoma and between GSCs and neural crest stem cells. We propose that broader application of this analysis could reshape our view of glioblastoma tumor evolution and inform the design of new epigenetic targeting therapies.

cancer biology↗

bioRxiv2024

Genetic and cellular basis of impaired phagocytosis and photoreceptor degeneration in CLN3 disease.

PurposeCLN3 Batten disease (also known as Juvenile Neuronal Ceroid Lipofuscinosis; JNCL) is a lysosomal storage disorder that typically initiates with retinal degeneration but is followed by seizure onset, motor decline and premature death. Patient-derived CLN3 disease iPSC-RPE cells show defective phagocytosis of photoreceptor outer segments (POSs). Because modifier genes are implicated in CLN3 disease, our goal here was to investigate a direct link between CLN3 mutation and POS phagocytosis defect. MethodsIsogenic control and CLN3 mutant stem cell lines were generated by CRISPR-Cas9{-}mediated biallelic deletion of exons 7 and 8. A transgenic CLN3{Delta}7-8/{Delta}7-8 (CLN3) Yucatan miniswine was also used to study the impact of CLN3{Delta}7-8/{Delta}7-8 mutation on POS phagocytosis. POS phagocytosis by cultured RPE cells was analyzed by Western blotting and immunohistochemistry. Electroretinogram, optical coherence tomography and histological analysis of CLN3{Delta}7/8 and wild-type miniswine eyes were carried out at 6-, 36-, or 48-month age. ResultsCLN3{Delta}7-8/{Delta}7-8 RPE (CLN3 RPE) displayed reduced POS binding and consequently decreased uptake of POS compared to isogenic control RPE cells. Furthermore, wild-type miniswine RPE cells phagocytosed CLN3{Delta}7-8/{Delta}7-8 POS less efficiently than wild-type POS. Consistent with decreased POS phagocytosis, lipofuscin/autofluorescence was decreased in CLN3 miniswine RPE at 36 months-of-age and was followed by almost complete loss of photoreceptors at 48 months of age. ConclusionsCLN3{Delta}7-8/{Delta}7-8 mutation (that affects up to 85% patients) affects both RPE and POSs and leads to photoreceptor cell loss in CLN3 disease. Furthermore, both primary RPE dysfunction and mutant POS independently contribute to impaired POS phagocytosis in CLN3 disease.

cell biology↗

bioRxiv2024

MYBPC3 D389V Variant Induces Hypercontractility in Cardiac Organoids

BACKGROUNDMYBPC3, encoding cardiac myosin binding protein-C (cMyBP-C), is the most mutated gene known to cause hypertrophic cardiomyopathy (HCM). However, since little is known about the underlying etiology, additional in vitro studies are crucial to defining the underlying molecular mechanisms. Accordingly, this study aimed to investigate the molecular mechanisms underlying the pathogenesis of HCM associated with a polymorphic variant (D389V) in MYBPC3 by using human-induced pluripotent stem cell (hiPSC)-derived cardiac organoids (hCOs). METHODSThe hiPSC-derived cardiomyocytes (hiPSC-CMs) and hCOs were generated from human subjects to define the molecular, cellular, and functional changes caused by the MYBPC3D389V variant. This variant is associated with increased fractional shortening and is highly prevalent in South Asian descendants. Recombinant C0-C2, N-region of cMyBP-C (wildtype and D389V), and myosin S2 proteins were also utilized to perform binding and motility assays in vitro. RESULTSConfocal and electron microscopic analyses of hCOs generated from noncarriers (NC) and carriers of the MYBPC3D389V variant revealed the presence of highly organized sarcomeres. Furthermore, functional experiments showed hypercontractility with increased contraction velocity, faster calcium cycling, and faster contractile kinetics in hCOs expressing MYBPC3D389V than NC hCOs. Interestingly, significantly increased cMyBP-C phosphorylation in MYBPC3D389V hCOs was observed, but without changes in total protein levels, in addition to higher oxidative stress and lower mitochondrial membrane potential ({Delta}{Psi}m). Next, spatial mapping revealed the presence of endothelial cells, fibroblasts, macrophages, immune cells, and cardiomyocytes in the hCOs. The hypercontractile function was significantly improved after treatment with the myosin inhibitor mavacamten (CAMZYOS(R)) in MYBPC3D389V hCOs. Lastly, various in vitro binding assays revealed a significant loss of affinity in the presence of MYBPC3D389V with myosin S2 region as a likely mechanism for hypercontraction. CONCLUSIONSConceptually, we showed the feasibility of assessing the functional and molecular mechanisms of HCM using highly translatable hCOs through pragmatic experiments that led to determining the MYBPC3D389V hypercontractile phenotype, which was rescued by administration of a myosin inhibitor. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMYBPC3 mutations have been implicated in hypertrophic cardiomyopathy. C_LIO_LID389V is a polymorphic variant of MYBPC3 predicted to be present in 53000 US South Asians owing to the founder effect. D389V carriers have shown evidence of hyperdynamic heart, and human-induced pluripotent stem cells (hiPSC)-derived cardiomyocytes with D389V show cellular hypertrophy and irregular calcium transients. C_LIO_LIThe molecular mechanism by which the D389V variant develops pathological cardiac dysfunction remains to be conclusively determined. C_LI What New Information Does This Article Contribute?O_LIThe authors leveraged a highly translational cardiac organoid model to explore the role of altered cardiac calcium handling and cardiac contractility as a common pathway leading to pathophysiological phenotypes in patients with early HCM. C_LIO_LIThe MYBPC3D389V-mediated pathological pathway is first studied here by comparing functional properties using three-dimensional cardiac organoids differentiated from hiPSC and determining the presence of hypercontraction. C_LIO_LIOur data demonstrate that faster sarcomere kinetics resulting from lower binding affinity between D389V-mutated cMyBP-C protein and myosin S2, as evidenced by in vitro studies, could cause hypercontractility which was rescued by administration of mavacamten (CAMZYOS(R)), a myosin inhibitor. C_LIO_LIIn addition, hypercontractility causes secondary mitochondrial defects such as higher oxidative stress and lower mitochondrial membrane potential ({Delta}{Psi}m), highlighting a possible early adaptive response to primary sarcomeric changes. C_LIO_LIEarly treatment of MYBPC3D389V carriers with mavacamten may prevent or reduce early HCM-related pathology. C_LI GRAPHICAL ABSTRACTA graphical abstract is available for this article. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/596463v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1489301org.highwire.dtl.DTLVardef@1ab60c1org.highwire.dtl.DTLVardef@5d49d1org.highwire.dtl.DTLVardef@9944d6_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Deep Learning Detection of Subtle Torsional Eye Movements: Preliminary Results

The control of torsional eye position is a key component of ocular motor function. Ocular torsion can be affected by pathologies that involve ocular motor pathways, spanning from the vestibular labyrinth of the inner ears to various regions of the brainstem and cerebellum. Timely and accurate diagnosis enables efficient interventions and management of each case which are crucial for patients with dizziness, vertical double vision, or imbalance. Such detailed evaluation of eye movements may not be possible in all frontline clinical settings, particularly for detecting torsional abnormalities. These abnormalities are often more challenging to identify at the bedside compared to horizontal or vertical eye movements. To address these challenges, we used a dataset of torsional eye movements recorded with video-oculography (VOG) to develop deep learning models for detecting ocular torsion. Our models achieve 0.9308 AUROC and 86.79 % accuracy, leveraging ocular features particularly pertinent to tracking torsional eye position.

neuroscience↗

bioRxiv2024

Identification of Small Molecule Inhibitors of PPM1D Using a Novel Drug Discovery Platform

Protein phosphatase, Mg2+/Mn2+ dependent 1D (PPM1D), is a serine/threonine phosphatase that is recurrently activated in cancer, regulates the DNA damage response (DDR), and suppresses the activation of p53. Consistent with its oncogenic properties, genetic loss or pharmacologic inhibition of PPM1D impairs tumor growth and sensitizes cancer cells to cytotoxic therapies in a wide range of preclinical models. Given the therapeutic potential of targeting PPM1D specifically and the DDR and p53 pathway more generally, we sought to deepen our biological understanding of PPM1D as a drug target and determine how PPM1D inhibition differs from other therapeutic approaches to activate the DDR. We performed a high throughput screen to identify new allosteric inhibitors of PPM1D, then generated and optimized a suite of enzymatic, cell-based, and in vivo pharmacokinetic and pharmacodynamic assays to drive medicinal chemistry efforts and to further interrogate the biology of PPM1D. Importantly, this drug discovery platform can be readily adapted to broadly study the DDR and p53. We identified compounds distinct from previously reported allosteric inhibitors and showed in vivo on-target activity. Our data suggest that the biological effects of inhibiting PPM1D are distinct from inhibitors of the MDM2-p53 interaction and standard cytotoxic chemotherapies. These differences also highlight the potential therapeutic contexts in which targeting PPM1D would be most valuable. Therefore, our studies have identified a series of new PPM1D inhibitors, generated a suite of in vitro and in vivo assays that can be broadly used to interrogate the DDR, and provided important new insights into PPM1D as a drug target.

cancer biology↗

bioRxiv2024

Fast skeletal myosin binding protein-C expression exacerbates dysfunction in heart failure

During heart failure, gene and protein expression profiles undergo extensive compensatory and pathological remodeling. We previously observed that fast skeletal myosin binding protein-C (fMyBP-C) is upregulated in diseased mouse hearts. While fMyBP-C shares significant homology with its cardiac paralog, cardiac myosin binding protein-C (cMyBP-C), there are key differences that may affect cardiac function. However, it is unknown if the expression of fMyBP-C expression in the heart is a pathological or compensatory response. We aim to elucidate the cardiac consequence of either increased or knockout of fMyBP-C expression. To determine the sufficiency of fMyBP-C to cause cardiac dysfunction, we generated cardiac-specific fMyBP-C over-expression mice. These mice were further crossed into a cMyBP-C null model to assess the effect of fMyBP-C in the heart in the complete absence of cMyBP-C. Finally, fMyBP-C null mice underwent transverse aortic constriction (TAC) to define the requirement of fMyBP-C during heart failure development. We confirmed the upregulation of fMyBP-C in several models of cardiac disease, including the use of lineage tracing. Low levels of fMyBP-C caused mild cardiac remodeling and sarcomere dysfunction. Exclusive expression of fMyBP-C in a heart failure model further exacerbated cardiac pathology. Following 8 weeks of TAC, fMyBP-C null mice demonstrated greater protection against heart failure development. Mechanistically, this may be due to the differential regulation of the myosin super-relaxed state. These findings suggest that the elevated expression of fMyBP-C in diseased hearts is a pathological response. Targeted therapies to prevent upregulation of fMyBP-C may prove beneficial in the treatment of heart failure. Significance StatementRecently, the sarcomere - the machinery that controls heart and muscle contraction - has emerged as a central target for development of cardiac therapeutics. However, there remains much to understand about how the sarcomere is modified in response to disease. We recently discovered that a protein normally expressed in skeletal muscle, is present in the heart in certain settings of heart disease. How this skeletal muscle protein affects the function of the heart remained unknown. Using genetically engineered mouse models to modulate expression of this skeletal muscle protein, we determined that expression of this skeletal muscle protein in the heart negatively affects cardiac performance. Importantly, deletion of this protein from the heart could improve heart function suggesting a possible therapeutic avenue.

physiology↗

bioRxiv2024

Modulation of endogenous opioid signaling by inhibitors of puromycin sensitive aminopeptidase

The endogenous opioid system regulates pain through local release of neuropeptides and modulation of their action on opioid receptors. However, the effect of opioid peptides, the enkephalins, is short-lived due to their rapid hydrolysis by enkephalin-degrading enzymes. In turn, an innovative approach to the management of pain would be to increase the local concentration and prolong the stability of enkephalins by preventing their inactivation by neural enkephalinases such as puromycin sensitive aminopeptidase (PSA). Our previous structure-activity relationship studies offered the S-diphenylmethyl cysteinyl derivative of puromycin (20) as a nanomolar inhibitor of PSA. This chemical class, however, suffered from undesirable metabolism to nephrotoxic puromycin aminonucleoside (PAN). To prevent such toxicity, we designed and synthesized 5'-chloro substituted derivatives. The compounds retained the PSA inhibitory potency of the corresponding 5'-hydroxy analogs and had improved selectivity toward PSA. In vivo treatment with the lead compound 19 caused significantly reduced pain response in antinociception assays, alone and in combination with Met-enkephalin. The analgesic effect was reversed by the opioid antagonist naloxone, suggesting the involvement of opioid receptors. Further, PSA inhibition by compound 19 in brain slices caused local increase in endogenous enkephalin levels, corroborating our rationale. Pharmacokinetic assessment of compound 19 showed desirable plasma stability and identified the cysteinyl sulfur as the principal site of metabolic liability. We gained additional insight into inhibitor-PSA interactions by molecular modeling, which underscored the importance of bulky aromatic amino acid in puromycin scaffold. The results of this study strongly support our rationale for the development of PSA inhibitors for effective pain management.

pharmacology and toxicology↗

bioRxiv2024

The 3'-untranslated regions of yeast ribosomal protein mRNAs determine paralog incorporation into ribosomes and recruit factors necessary for specialized functions

Ribosome heterogeneity arises via the differential incorporation of ribosomal protein (RP) paralogs, post-transcriptionally modified rRNA, post-translationally modified RPs, and ribosome-associated proteins (RAPs) into ribosomes. This has led to the hypothesis that heterogeneous or "specialized" ribosomes, which translate specific mRNA subsets, confer key roles in cell growth and development. While proven examples of functional ribosome heterogeneity in eukaryotes exist, there is no comprehensive analysis of specialized ribosome formation. We employed yeast RP paralog deletion libraries and high-throughput screening to investigate the functional specificity and redundancy between paralogs under various growth conditions. Composition and translatome analyses verified paralog specificity in the assembly and function of ribosomes specialized for growth on different carbon sources, and identified a novel RAP required for the efficient translation of peroxisomal proteins. Importantly, we also show that the mechanism by which specific RP paralogs incorporate into ribosomes requires their unique 3-untranslated regions to yield ribosomes that differ in composition and function. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/585503v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@15ba935org.highwire.dtl.DTLVardef@c210b7org.highwire.dtl.DTLVardef@d77b7dorg.highwire.dtl.DTLVardef@ec72f4_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Signaling pathway evaluation of leading ATRi, PARPi and CDK7i cancer compounds targeting the DNA Damage Response using Causal Inference

IntroductionThere are many cancer drugs in development which target the DNA damage response (DDR), following early successes of drugs such as olaparib. However, various challenges to the success of these inhibitors exist, including the emergence of resistance, the identification of appropriate biomarkers to identify patients who will respond to treatment, as well as the identification of combination therapies that improve efficacy without a concomitant increase in toxicity. While the identification of biomarkers of resistance could aid in overcoming these challenges, current methods mostly generate lists of potential genes, proteins that display changes in cancer patients, without exposing the underlying, and often critical, mechanisms of resistance. MethodsWe have developed the Adaptable Large-Scale Causal Analysis (ALaSCA) software platform, which applies Pearlian Causal Inference (PCI) techniques to specifically transcriptomic, proteomic and phenotypic multi-omics data. ALaSCA quantifies the causal contributions of different biological pathways to an outcome such as responsiveness to treatment. The strength of applying PCI to biological pathways lies in quantifying the causal contributions of targets, through their related pathways, to drug sensitivity - as opposed to merely enriching or grouping lists of genes into pathways. We applied ALaSCA to transcriptomic data for several different compounds related to three known inhibitor types that target DDR proteins: an ATR, a CDK7, and several PARP inhibitors. Our aim was to use causal methods to evaluate biological signaling pathways to identify resistance mechanisms that can be used for patient stratification and development of combination therapies in breast, ovarian and non-small cell lung cancer (NSCLC). Key findingsWe observed that niraparib seems to have a different resistance mechanism than other PARPi inhibitors in breast and NSCLC, which is driven by CDK1 as opposed to base excision or nucleotide excision repair. Additionally, CDK7 appears to be a significant driver of PARP inhibitor resistance, especially for niraparib, through predominantly the G2/M cell cycle phase and to a lesser extent nucleotide excision repair in breast and ovarian cancer, but not in NSCLC. Lastly, we identified that genes from the homologous recombination pathway drive resistance to AZD6738, an ATR inhibitor, in breast cancer, and that AZD6738 and irinotecan have differing resistance mechanisms in ovarian cancer, indicating the potential of combining these treatments. Next stepsOur findings demonstrate the potential of ALaSCA to generate interesting insights for treatments when applied to public data and well-known inhibitors. Partnership with industry drug discovery groups using proprietary data to rerun the above evaluations will further refine and confirm these findings.

bioinformatics↗

bioRxiv2024

scGrapHiC: Deep learning-based graph deconvolution for Hi-C using single cell gene expression

Single-cell Hi-C (scHi-C) protocol helps identify cell-type-specific chromatin interactions and sheds light on cell differentiation and disease progression. Despite providing crucial insights, scHi-C data is often underutilized due the high cost and the complexity of the experimental protocol. We present a deep learning framework, scGrapHiC, that predicts pseudo-bulk scHi-C contact maps using pseudo-bulk scRNA-seq data. Specifically, scGrapHiC performs graph deconvolution to extract genome-wide single-cell interactions from a bulk Hi-C contact map using scRNA-seq as a guiding signal. Our evaluations show that scGrapHiC, trained on 7 cell-type co-assay datasets, outperforms typical sequence encoder approaches. For example, scGrapHiC achieves a substantial improvement of 23.2% in recovering cell-type-specific Topologically Associating Domains over the baselines. It also generalizes to unseen embryo and brain tissue samples. scGrapHiC is a novel method to generate cell-type-specific scHi-C contact maps using widely available genomic signals that enables the study of cell-type-specific chromatin interactions. Availabilityhttps://github.com/rsinghlab/scGrapHiC Contactritambhara@brown.edu

genomics↗

bioRxiv2024

Aggregating Residue-Level Protein Language Model Embeddings with Optimal Transport

Protein language models (PLMs) have emerged as powerful approaches for mapping protein sequences into embeddings suitable for various applications. As protein representation schemes, PLMs generate per-token (i.e., per-residue) representations, resulting in variable-sized outputs based on protein length. This variability poses a challenge for protein-level prediction tasks that require uniform-sized embeddings for consistent analysis across different proteins. Previous work has typically used average pooling to summarize token-level PLM outputs, but it is unclear whether this method effectively prioritizes the relevant information across token-level representations. We introduce a novel method utilizing optimal transport to convert variable-length PLM outputs into fixed-length representations. We conceptualize per-token PLM outputs as samples from a probabilistic distribution and employ sliced-Wasserstein distances to map these samples against a reference set, creating a Euclidean embedding in the output space. The resulting embedding is agnostic to the length of the input and represents the entire protein. We demonstrate the superiority of our method over average pooling for several downstream prediction tasks, particularly with constrained PLM sizes, enabling smaller-scale PLMs to match or exceed the performance of average-pooled larger-scale PLMs. Our aggregation scheme is especially effective for longer protein sequences by capturing essential information that might be lost through average pooling.

bioinformatics↗

bioRxiv2024

Tar Spot Disease Severity Influences Phyllosphere-Associated Bacterial and Fungal Microbiomes

Tar spot, caused by the obligate fungal pathogen Phyllachora maydis, is a foliar disease of corn that has become a major economic concern in the United States. To test the hypothesis that P. maydis can interact with other foliar microorganisms, we investigated phyllosphere microbiomes in relation to corn inbreds with differential tar spot symptoms under natural infestation in the field. Leaf samples from sixteen inbred lines were assessed for tar spot symptoms, and bacterial and fungal microbiomes were characterized by paired-end sequencing on the Illumina MiSeq platform. Comparison of the phyllosphere microbiomes revealed distinct bacterial and fungal communities between resistant and susceptible lines. Bacterial and fungal species richness was significantly higher in resistant compared to susceptible inbred lines in a sample-specific manner. In contrast, there were no clear differences in diversity when including evenness of bacterial communities between the resistant and susceptible lines. Diversity of fungal communities differed significantly, particularly between twelve of the fourteen susceptible lines versus resistant lines. Plant-beneficial bacterial genera such as Methylorubrum and Quadrisphaera were associated with resistant lines, while Pantoea, Deinococcus and Pseudomonas were the least abundant. The second-most commonly detected fungus likely was a Coniothyrium, but whether it is the same species that was identified as a possible mycoparasite of P. maydis in Central and South America is not known. Fungal genera Cladosporium, Papiliotrema, Cryptococcus, Tilletiopsis and Alternaria were associated with resistant lines while Sphaerellopsis was the least-abundant genus. In contrast, Puccinia, Sphaerellopsis and Phyllachora were the dominant fungal genera in susceptible lines. Our findings imply that P. maydis infection may result in a distinct microbiota with lower diversity. Further analyses of these distinct microbiota between resistant and susceptible lines could lead to a better understanding of the potential role of foliar microbiomes in causing or resisting P. maydis infection.

plant biology↗

bioRxiv2024

Tissue Inhibitor of Metalloproteinase 3 (TIMP3) mutations increase glycolytic activity and dysregulate glutamine metabolism in RPE cells

Mutations in Tissue Inhibitor of Metalloproteinases 3 (TIMP3) cause Sorsbys Fundus Dystrophy (SFD), a dominantly inherited, rare form of macular degeneration that results in vision loss. TIMP3 is synthesized primarily by retinal pigment epithelial (RPE) cells, which constitute the outer blood-retinal barrier. Quantitative proteomics and RNAseq analysis on the choroid/RPE of mice expressing mutant TIMP3 identified a dysregulation in metabolic processes. We examined the effects of mutant TIMP3 on RPE metabolism using human ARPE-19 cells expressing mutant S179C TIMP3 and patient-derived induced pluripotent stem cell-derived RPE (iRPE) carrying the S204C TIMP3 mutation. Stable isotope tracing experiments demonstrated enhanced glucose utilization and glycolytic activity in mutant RPE concomitantly with altered glutamine utilization. This study provides important information on the dysregulation of the metabolome of RPE cells in SFD and implicates a potential commonality with other retinal degenerative diseases, emphasizing RPE cellular metabolism as a therapeutic target.

biochemistry↗

bioRxiv2023

Ensemble-based design of tau to inhibit aggregation while preserving biological activity.

The microtubule-associated protein tau is implicated in neurodegenerative diseases characterized by amyloid formation. Mutations associated with frontotemporal dementia increase tau aggregation propensity and disrupt its endogenous microtubule-binding activity. However, the structural relationship between aggregation propensity and biological activity remains unclear. We employed a multi-disciplinary approach, including computational modeling, NMR, cross-linking mass spectrometry, and cell models to engineer tau sequences that modulate its structural ensemble. Our findings show that substitutions near the conserved PGGG {beta}-turn motif informed by tau isoform context reduce tau aggregation in vitro and cells and can even counteract aggregation induced by turn destabilizing disease-associated proline-to-serine mutations. Engineered tau sequences maintain microtubule binding and explain why 3R isoforms exhibit reduced pathogenesis compared to 4R. We propose a simple mechanism to reduce the formation of pathogenic species while preserving biological function, thus offering insights for therapeutic strategies aimed at reducing tau protein misfolding in neurodegenerative diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/571598v2_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@178a79org.highwire.dtl.DTLVardef@1842dc7org.highwire.dtl.DTLVardef@d9a32borg.highwire.dtl.DTLVardef@676dec_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Optimizing Glycemic Control in Type 1 Diabetic Patients using a Deep Learning-Based Artificial Pancreas with a Secure Glucagon and Insulin Delivery System

Type 1 diabetes impacts millions worldwide, with some patients facing rapid fluctuations in their blood sugar levels. These fluctuations can negatively impact an individuals quality of life and if untreated, can lead to nerve damage, coma, and death. While current methods have helped address hyperglycemia (high blood sugar), there has been less success with hypoglycemia (low blood sugar) and glucagon administration. To bridge this gap, an artificial pancreas with a novel insulin and glucagon pump was developed. Initiating the system, a personalized mobile app enables users to input meal carbohydrate and insulin bolus data. The data is then transmitted to a deep learning model that incorporates Continuous Glucose Monitor readings, along with carbohydrate and insulin data from the app. The two-layer Long Short-Term Memory network, developed in Python, accurately forecasts blood sugar levels on Ohio Universitys OhioT1DM patient dataset and the UVa/Padova simulations data for a 30 minute-interval. An algorithm then utilizes the predictions to calculate optimal insulin and glucagon doses using metabolization formulas. To ensure system security, data is transmitted through a cloud-based MQ Telemetry Transport server and secured with industry-standard authentication and encryption methods. Finally, a microcontroller-based prototype accurately dispenses insulin and glucagon doses. The system kept in-silico patients at optimal levels for 38% longer and reduced dangerous levels by 22% compared to conventional controllers on an FDA-approved preclinical trial alternative simulation. By addressing both hypo and hyperglycemia, this real-time medical device can be a transformative tool for individuals with diabetes, enabling them to live healthier and more fulfilling lives.

bioengineering↗

bioRxiv2023

Modeling aging and retinal degeneration with mitochondrial DNA mutation burden.

Somatic mitochondrial DNA (mtDNA) mutation accumulation has been observed in individuals with retinal degenerative disorders. To study the effects of aging and mtDNA mutation accumulation in the retina, a Polymerase gamma (POLG) deficiency model, the POLGD257A mutator mice (PolgD257A), was used. POLG is an enzyme responsible for regulating mtDNA replication and repair. Retinas of young and older mice with this mutation were analyzed in vivo and ex vivo to provide new insights into the contribution of age-related mitochondrial dysfunction due to mtDNA damage. Optical coherence tomography (OCT) image analysis revealed a decrease in retinal and photoreceptor thickness starting at 6 months of age in mice with the POLGD257A mutation compared to wild-type (WT) mice. Electroretinography (ERG) testing showed a significant decrease in all recorded responses at 6 months of age. Sections labeled with markers of different types of retinal cells, including cones, rods, and bipolar cells, exhibited decreased labeling starting at 6 months. However, electron microscopy analysis revealed differences in retinal pigment epithelium (RPE) mitochondria morphology beginning at 3 months. Interestingly, there was no increase in oxidative stress observed in the retina or RPE of POLGD257A mice. Additionally, POLGD257A RPE exhibited an accelerated rate of autofluorescence cytoplasmic granule formation and accumulation. Mitochondrial markers displayed decreased abundance in protein lysates obtained from retina and RPE samples. These findings suggest that the accumulation of mitochondrial DNA mutations leads to impaired mitochondrial function and accelerated aging, resulting in retinal degeneration.

cell biology↗

bioRxiv2023

H2A.Z chaperones converge on histone H4 acetylation for melanoma cell proliferation

High levels of H2A.Z promote melanoma cell proliferation and correlate with poor prognosis. However, the role of the two distinct H2A.Z histone chaperone complexes, SRCAP and P400-TIP60, in melanoma remains unclear. Here, we show that individual depletion of SRCAP, P400, and VPS72 (YL1) not only results in loss of H2A.Z deposition into chromatin, but also a striking reduction of H4 acetylation in melanoma cells. This loss of H4 acetylation is found at the promoters of cell cycle genes directly bound by H2A.Z and its chaperones, suggesting a highly coordinated regulation between H2A.Z deposition and H4 acetylation to promote their expression. Knockdown of each of the three subunits downregulates E2F1 and its targets, resulting in a cell cycle arrest akin to H2A.Z depletion. However, unlike H2A.Z deficiency, loss of the shared H2A.Z chaperone subunit YL1 induces apoptosis. Furthermore, YL1 is overexpressed in melanoma tissues, and its upregulation is associated with poor patient outcome. Together, these findings provide a rationale for future targeting of H2A.Z chaperones as an epigenetic strategy for melanoma treatment.

cancer biology↗