Biology subjects

Ma, S.

Publications and source records attributed to Ma, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2023

Data-driven optimization yielded a highly-efficient CRISPR/Cas9 system for gene editing in Arabidopsis

The CRISPR/Cas9 technology is widely used for plant gene editing. In Arabidopsis, the early CRISPR/Cas9 systems using constitutive promoters to drive Cas9 expression usually have low heritable mutation efficiencies in the T1 generation. Germ cell-specific or cell division-specific promoters, like EC1.2en-EC1.1p fusion, YAO and CDC45, have been used as alternatives to direct Cas9 expression, but the efficiency of getting nonchimeric mutations is still not high. To further improve gene editing efficiency, we used gene co-expression network analysis to identify NUC1 as a candidate promoter for driving Cas9 expression. NUC1 has expression patterns similar to YAO, but expresses at a much higher level. We constructed a CRISPR/Cas9 system pHY07 that uses the NUC1 promoter to drive Cas9 and carries the mCherry protein as a fluorescent marker for selecting transgenic seeds. Using this system to edit the GL2 gene, we obtained apparently nonchimeric mutations in 55% of the T1 transgenic plants. Among the Cas9-free T2 plants 99% harbored mutations that are stably inherited from the previous generation. Therefore, our system exhibited extremely high editing efficiency, and through fluorescent screening of transgenic seeds, it become easy to obtain Cas9-free and stable genetic mutants in the T2 generation.

plant biology↗

bioRxiv2023

NeuroMotion: Open-source Simulator with Neuromechanical and Deep Network Models to Generate Surface EMG signals during Voluntary Movement

Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental analysis. However, current simulation models of electromyography (EMG), a core physiological signal in neuromechanical analyses, are mainly limited to static contractions and cannot fully represent the dynamic modulation of EMG signals during volitional movements. Here, we overcome these limitations by presenting NeuroMotion, an open-source simulator that provides a full-spectrum synthesis of EMG signals during voluntary movements. NeuroMotion is comprised of three modules. The first module is an upper-limb MSK model with OpenSim API to estimate the muscle fibre lengths and muscle activations during movements. The second module is BioMime, a deep neural network-based EMG generator that receives nonstationary physiological parameter inputs, such as muscle fibre lengths, and efficiently outputs motor unit action potentials (MUAPs). The third module is a motor unit pool model that transforms the muscle activations into discharge timings of motor units. The discharge timings are convolved with the output of BioMime to simulate EMG signals during the movement. Here we also provide representative applications of NeuroMotion. We first show how simulated MUAP waveforms change during different levels of physiological parameter variations and different movements. We then show that the synthetic EMG signals during two-degree-of-freedom hand and wrist movements can be used to augment experimental data for regression. Ridge regressors trained on the synthetic dataset were directly used to predict joint angles from experimental data. NeuroMotion is the first full-spectrum EMG generative model to simulate human forearm electrophysiology during voluntary hand, wrist, and forearm movements. All intermediate variables are available, which allows the user to study cause-effect relationships in the complex neuromechanical system, fast iterate algorithms before collecting experimental data, and validate algorithms that estimate non-measurable parameters in experiments. We expect this full-spectrum model will complement experimental approaches and facilitate neuromechanical research. Author summaryNeuromechanical studies investigate how the nervous system and musculoskeletal system interact to generate movements. Such studies heavily rely on simulation models, which provide non-measurable variables to complement the experimental analyses. However, the simulation models of surface electromyography (EMG), the core physiological signal widely used in neuromechanical analyses, are limited to static conditions. We bridged this gap by proposing NeuroMotion, the first full-spectrum EMG simulator that can be used to generate EMG signals during voluntary movements. NeuroMotion integrates a musculoskeletal model, a neural network-based EMG generator, and an advanced motoneuron model. With representative applications of this simulator, we show that it can be used to investigate the variabilities of EMG signals during voluntary movement. We also demonstrate that the synthetic signals generated by NeuroMotion can be used to augment experimental data for regressing joint angles. We expect the functionality provided by NeuroMotion, which is provided open-source, will stimulate progress in neuromechanics.

bioengineering↗

bioRxiv2023

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging

MotivationMultiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data. ResultsTo address the need for an evaluable semi-automated algorithm, we developed GammaGateR, an R package for interactive marker gating designed specifically for segmented cell-level data from mIF images. Based on a novel closed-form gamma mixture model, GammaGateR provides estimates of marker-positive cell proportions and soft clustering of marker-positive cells. The model incorporates user-specified constraints that provide a consistent but slide-specific model fit. We compared GammaGateR against the newest unsupervised approach for annotating mIF data, employing two colon datasets and one ovarian cancer dataset for the evaluation. We showed that GammaGateR produces highly similar results to a silver standard established through manual annotation. Furthermore, we demonstrated its effectiveness in identifying biological signals, achieved by mapping known spatial interactions between CD68 and MUC5AC cells in the colon and by accurately predicting survival in ovarian cancer patients using the phenotype probabilities as input for machine learning methods. GammaGateR is a highly efficient tool that can improve the replicability of marker gating results, while reducing the time of manual segmentation. Availability and ImplementationThe R package is available at https://github.com/JiangmeiRubyXiong/GammaGateR. ContactPlease address correspondence to jiangmei.xiong@vanderbilt.edu and simon.vandekar@vumc.org. Key PointsO_LIGammaGateR is the first semi-automated marker gating tool for mIF image, and it will help to diminish the inconsistency with manual marker gating. C_LIO_LIWith novel cfGMM, GammaGateR can fit flexibly across slides with different distributions and incorporate biology priors. C_LIO_LIGammaGateR is proven to reveal credible prognostic information, and it can quantify known findings in tumor cell populations. C_LI

bioinformatics↗

bioRxiv2023

Linking Gba1 E326K mutation to microglia activation and mild age-dependent dopaminergic Neurodegeneration

Mutations in the GBA1 gene have been identified as a prevalent genetic risk factor for Parkinsons disease (PD). GBA1 mutations impair enzymatic activity, leading to lysosomal dysfunction and elevated levels of -synuclein (-syn). While most research has primarily focused on GBA1s role in promoting synucleinopathy, emerging evidence suggests that neuroinflammation may be a key pathogenic alteration caused by GBA1 deficiency. To examine the molecular mechanism underlying GBA1 deficiency-mediated neuroinflammation, we generated Gba1 E326K knock-in (KI) mice using the CRISPR/Cas9 technology, which is linked to an increased risk of PD and dementia with Lewy bodies (DLB). In the ventral midbrain and hippocampus of 24-month-old Gba1 E326K KI mice, we found a moderate decline in GBA1 enzymatic activity, a buildup of glucosylceramide, and an increase in microglia density. Furthermore, we observed increased levels of pro-inflammatory cytokines and formation of reactive astrocytes in primary microglia and astrocytes, respectively, cultured from Gba1 E326K KI mice following treatment with pathologic -syn preformed fibrils (PFF). Additionally, the gut inoculation of -syn PFF in Gba1 E326K KI mice significantly enhanced the accumulation of Lewy bodies in the dentate gyrus of the hippocampus, accompanied by aggravated neuroinflammation and exacerbated non-motor symptoms. This research significantly enhances our understanding of the Gba1 E326K mutations involvement in neuroinflammation and the cell-to-cell transmission of pathogenic -syn in the brain, thereby opening new therapeutic avenues.

neuroscience↗

bioRxiv2023

The ubiquitin ligase STUB1 suppresses tumorigenesis of renal cell carcinomas through regulating YTHDF1 stability

STIP1 homology and U-box protein 1 (STUB1), a key RING family E3 ubiquitin ligase, plays both oncogenic and tumor-suppressive roles in a variety of human cancers. However, the role and mechanism of STUB1 in clear cell renal cell carcinoma (ccRCC) remains poorly defined. Here, we identified YTHDF1 as a novel STUB1 interactor by affinity purification mass spectrometry (AP-MS). STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation. STUB1 depletion stabilizes YTHDF1 in renal cancer cells. STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Further study demonstrates that STUB1 knockdown promoted the tumorigenicity of ccRCC in a xenograft model. Clinically, STUB1 expression is down-regulated in ccRCC tissues, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. These findings reveal that STUB1 acts as an E3 ubiquitin ligase and promotes degradation of YTHDF1, and STUB1 inhibits the tumorigenicity of ccRCC through ubiquitinating YTHDF1. Novelty & Impact StatementsSTUB1 plays both oncogenic and tumor-suppressive roles in a variety of human cancers. Here, the authors demonstrated that STUB1 acts as a tumor suppressor in ccRCC, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. In addition, STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Mechanistically, STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation.

cancer biology↗

bioRxiv2023

HEARTSVG: a fast and accurate method for spatially variable gene identification in large-scale spatial transcriptomic data

Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higher F1 scores (average F1 score=0.903), improved computational efficiency, scalability, and reduced false positives (FPs). Through analysis of twelve real datasets from various spatial transcriptomic technologies, HEARTSVG identifies a greater number of biologically significant SVGs (average recall=0.985, average AUC=0.788) than other comparative methods without prespecifing spatial patterns. Furthermore, by clustering SVGs, we uncover two distinct tumor spatial domains characterized by unique spatial expression patterns, spatial-temporal locations, and biological functions in human colorectal cancer data, unraveling the complexity of tumors.

bioinformatics↗

bioRxiv2023

High-throughput and genome-scale targeted mutagenesis using CRISPR in a non-model multicellular organism, Bombyx mori

Large-scale genetic mutant libraries are powerful approaches to interrogating genotype-phenotype correlations and identifying genes responsible for certain environmental stimuli, both of which are the central goal of life science study. We produced the first large-scale CRISPR/Cas9-induced library in a non-model multicellular organism, Bombyx mori. We developed a piggyBac-delivered binary genome editing strategy, which can simultaneously meet the requirements of mixed microinjection, efficient multi-purpose genetic operation, and preservation of growth-defect lines. We constructed a single-guide RNA (sgRNA) plasmid library containing 92,917 sgRNAs targeting promoters and exons of 14,645 protein-coding genes, established 1726 transgenic sgRNA lines following microinjection of 66,650 embryos, and generated 300 mutant lines with diverse phenotypic changes. Phenomic characterization of mutant lines identified a large set of genes responsible for visual phenotypic or economically valuable trait changes. Next, we performed pooled context-specific positive screens for tolerance to environmental pollute cadmium exposure, and identified KWMTBOMO12902 as a strong candidate gene for breeding applications in sericulture industry. Collectively, our results provide a novel and versatile approach for functional B. mori genomics, and a powerful resource for identifying key candidate genes potential for improving various economic traits. This study also demonstrates the effectiveness, practicality, and convenience of large-scale mutant libraries in other non-model organisms.

genomics↗

bioRxiv2023

Membrane mechanics dictate axonal morphology and function

Axons are thought to be ultrathin membrane cables of a relatively uniform diameter, designed to conduct electrical signals, or action potentials. Here, we demonstrate that unmyelinated axons are not simple cylindrical tubes. Rather, axons have nanoscopic boutons repeatedly along their length interspersed with a thin cable with a diameter of [~]60 nm like pearls-on-a-string. These boutons are only [~]200 nm in diameter and do not have synaptic contacts or a cluster of synaptic vesicles, hence non-synaptic. Our in silico modeling suggests that axon pearling can be explained by the mechanical properties of the membrane including the bending modulus and tension. Consistent with modeling predictions, treatments that disrupt these parameters like hyper- or hypo-tonic solutions, cholesterol removal, and non-muscle myosin II inhibition all alter the degree of axon pearling, suggesting that axon morphology is indeed determined by the membrane mechanics. Intriguingly, neuronal activity modulates the cholesterol level of plasma membrane, leading to shrinkage of axon pearls. Consequently, the conduction velocity of action potentials becomes slower. These data reveal that biophysical forces dictate axon morphology and function and that modulation of membrane mechanics likely underlies plasticity of unmyelinated axons.

neuroscience↗

bioRxiv2023

Spatiotemporal precise optical manipulation of intracellular molecular activities

Controlling chemical processes in live cells is a challenging task. The spatial heterogeneity of biochemical reactions in cells is often overlooked by conventional means of incubating cells with desired chemicals. A comprehensive understanding of spatially diverse biochemical processes requires precise control over molecular activities at the subcellular level. Herein, we develop a closed-loop optoelectronic control system that allows the manipulation of biomolecular activities in live cells at high spatiotemporal precision. Chemical-selective fluorescence signals are utilized to command lasers that trigger specific chemical reactions or control the activation of photoswitchable inhibitors at desired targets. We demonstrate the capability to selectively produce reactive oxygen species (ROS) solely at targeted organelles using blue light. Notably, the induction of ROS in the endoplasmic reticulum leads to a more pronounced disruption of tubulin polymerization and a reduction in green fluorescent protein signals, in comparison to that in lipid droplets. Moreover, when combined with a photoswitchable inhibitor, we selectively inhibit tubulin polymerization within subcellular compartments. This technology enables spatiotemporal control over chemical processes and drug activities, exclusively at desired targets, while minimizing undesired effects on non-targeted locations.

cell biology↗

bioRxiv2023

Engineering transposon-associated TnpB-1 ωRNA system for efficient gene editing and disease treatment in mouse

Transposon-associated ribonucleoprotein TnpB is known to be the ancestry endonuclease of diverse Cas12 effector proteins from type-V CRISPR system. Given its small size (409 aa), it is of interest to examine whether engineered TnpB could be used for efficient mammalian genome editing. Here, we showed that the gene editing activity of native TnpB in mouse embryos was already higher than previously identified small-sized Cas12f1. Further stepwise engineering of noncoding RNA ({omega}RNA or reRNA) component of TnpB significantly elevated the nuclease activity of TnpB. Notably, an optimized TnpB-{omega}RNA system could be efficiently delivered in vivo with single adeno-associated virus (AAV) and prevented the disease phenotype in a tyrosinaemia mouse model. Thus, the engineered miniature TnpB system represents a new addition to the current genome editing toolbox, with the unique feature of the smallest effector size that facilitate efficient AAV delivery for editing of cells and tissues.

molecular biology↗

bioRxiv2023

Distinct Neurodevelopmental Patterns and Intermediate Integration-Based Predictive Modeling in Autism Spectral Disorder

Autism Spectrum Disorder (ASD) is known to exhibit a more rapid expansion in brain structure during the early years of life compared to typically developing children (TD). This is of utmost importance in understanding atypical brain development and forecasting the onset of ASD. However, the precise age-related cortical changes (trajectories) that could pinpoint atypical brain development in ASD remain largely unknown. In this study, we characterize the distinct developmental patterns of cortical morphology in individuals with ASD, investigate the important neural biomarkers for ASD diagnostics, and propose a deep-learning workflow that combined graph convolutional networks with low-rank multi-model tensor fusion (LMFGCN) for ASD prediction. Our findings reveal that the constituents of gray matter volume (GV), cortical thickness (CT), and surface area (SA) exhibit separable developmental trajectories in ASD. Furthermore, we identify regional differences in CT and SA that underscore the separable brain developmental trajectories, both of which contribute to changes in GV. Our study also demonstrates that LMFGCN, an end-to-end deep-learning model with intermediate integrative approach, outperforms early and late integration methods and other state-of-the-art models in ASD classification. Overall, our results highlight the importance of distinguishing between cortical SA and CT for understanding ASD pathobiology, particularly during the early brain overgrowth period, and demonstrate the potential utility of LMFGCN in ASD classification.

neuroscience↗

bioRxiv2023

Oligomeric state of β-coronavirus non-structural protein 10 stimulators studied by OmniSEC and Small Angle X-ray Scattering

Members of the {beta}-coronavirus family such as SARS-CoV-2, SARS, and MERS have caused pandemics over the last 20 years. Future pandemics are likely and studying the coronavirus family members is necessary for their understanding and treatment. Coronaviruses possess 16 non-structural proteins, many of which are involved in viral replication and other vital functions. Non-structural protein 10 (nsp10) is an essential stimulator of nsp14 and nsp16, modulating RNA proofreading and viral RNA cap formation. Studying nsp10 of pathogenic coronaviruses is central to understanding its multifunctional role. We report the biochemical and biophysical characterisation of full-length nsp10 from MERS, SARS and SARS-CoV-2. Proteins were subjected to a combination of OmniSEC and SEC-MALS to characterise their oligomeric state. Full-length nsp10s were predominantly monomeric in solution, while truncated versions of nsp10 have a higher tendency to oligomerise. Small angle X-ray scattering (SAXS) experiments reveal a globular shape of nsp10 which is conserved in all three coronaviruses, including MERS nsp10, which diverges most from SARS and SARS-CoV-2 nsp10s. In conclusion, unbound nsp10 proteins from SARS, MERS, and SARS-CoV-2 are globular and predominantly monomeric in solution. Additionally, we describe for the first time a functional role of the C-terminus of nsp10 for tight binding to nsp14.

biochemistry↗

bioRxiv2023

High-confidence placement of difficult-to-fit fragments into electron density by using anomalous signals - a case study using hits targeting SARS-CoV-2 non-structural protein 1

The identification of multiple simultaneous orientations of small molecule inhibitors binding to a protein target is a common challenge. It has recently been reported that the conformational heterogeneity of ligands is widely underreported in the Protein Data Bank, which is likely to impede optimal exploitation to improve affinity of these ligands1. Significantly less is even known about multiple binding orientations for fragments (< 300 Da) although this information would be essential for subsequent fragment optimisation using growing, linking or merging and rational structure-based design. Here we use recently reported fragment hits for the SARS-CoV-2 non-structural protein 1 (nsp1) N-terminal domain to propose a general procedure for unambiguously identifying binding orientations of 2-dimensional fragments containing either sulphur or chloro substituents within the wavelength range of most tunable beamlines. By measuring datasets at two energies, using a tuneable beamline operating in vacuum and optimised for data collection at very low X-ray energies, we show that the anomalous signal can be used to identify multiple orientations in small fragments containing sulphur and/or chloro substituents or to verify recently reported conformations. Although in this specific case we identified the positions of sulphur and chlorine in fragments bound to their protein target, we are confident that this work can be further expanded to additional atoms or ions which often occur in fragments. Finally, our improvements in the understanding of binding orientations will also serve to advance the rational optimisation of SARS-CoV-2 nsp1 targeting fragment hits.

biochemistry↗

bioRxiv2023

A KDELR-mediated ER retrieval system guides the signaling pathways of UPR and AMPK to maintain cellular homeostasis

KDELR (Erd2 in yeasts) mediates the retrieval of ER-resident proteins from the Golgi apparatus, yet how the KDELR-mediated ER retrieval system is involved in regulating cellular homeostasis has been unclear. Here we report that the loss of the Erd2-mediated ER retrieval system induces the unfolded protein response (UPR) and increases mitochondrial respiration and reactive oxygen species (ROS) in an UPR-dependent manner. Moreover, transcriptomic analysis revealed that expression of the genes involved in mitochondrial respiration and the tricarboxylic acid cycle is enhanced in an UPR-dependent manner in cells lacking Erd2. In cells lacking Erd2, the enhancement of mitochondrial respiration and ROS is required for maintaining cell viability. The loss of the Erd2-mediated ER retrieval system also activates AMPK, and consequently derepresses carbon catabolite repression. Hence, our work establishes a role of the KDELR/Erd2-mediated ER retrieval system in guiding the signalling pathways of AMPK and UPR and underscores the crucial role of the KDELR/Erd2-mediated ER retrieval system in the maintenance of cellular homeostasis.

cell biology↗

bioRxiv2023

AGILE Platform: A Deep Learning-Powered Approach to Accelerate LNP Development for mRNA Delivery

Ionizable lipid nanoparticles (LNPs) have seen widespread use in mRNA delivery for clinical applications, notably in SARS-CoV-2 mRNA vaccines. Despite their successful use, expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored to different target cell types. The traditional process of LNP development remains labor-intensive and cost-inefficient, relying heavily on trial and error. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines the iterative development of ionizable lipids, crucial components for LNP-mediated mRNA delivery. This approach brings forth three significant features: efficient design and synthesis of combinatorial lipid libraries, comprehensive in silico lipid screening employing deep neural networks, and adaptability to diverse cell lines. Using AGILE, we were able to rapidly design, synthesize, and evaluate new ionizable lipids for mRNA delivery in muscle and immune cells, selecting from a library of over 10,000 candidates. Importantly, AGILE has revealed cell-specific preferences for ionizable lipids, indicating the need for different tail lengths and head groups for optimal delivery to varying cell types. These results underscore the potential of AGILE in expediting the development of customized LNPs. This could significantly contribute to addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies. One Sentence SummaryAI and combinatorial chemistry expedite ionizable lipid creation for mRNA delivery.

biochemistry↗

bioRxiv2023

Droplet-based bisulfite sequencing for high-throughput profiling of single-cell DNA methylomes

Genome-wide DNA methylation profile, or DNA methylome, is a critical component of the overall epigenomic landscape that modulates gene activities and cell fate. Single-cell DNA methylomic studies offer unprecedented resolution for detecting and profiling cell subsets based on methylomic features. However, existing single-cell methylomic technologies are all based on use of tubes or well plates and these platforms are not easily scalable for handling a large number of single cells. Here we demonstrate a droplet-based microfluidic technology, Drop-BS, to construct single-cell bisulfite sequencing libraries for DNA methylome profiling. Drop-BS takes advantage of the ultrahigh throughput offered by droplet microfluidics to prepare bisulfite sequencing libraries of up to 10,000 single cells within 2 d. We applied the technology to profile mixed cell lines, mouse and human brain tissues to reveal cell type heterogeneity. Drop-BS will pave the way for single-cell methylomic studies requiring examination of a large cell population.

genomics↗

bioRxiv2023

Ketone-loading as A Novel Sports Nutrition Strategy: Chronic Ketone Supplementation Elicits Further Favorable Metabolic Changes in Keto-adapted Mice

BackgroundA ketogenic diet (KD) induces nutritional ketosis (NS), benefits fatty acid oxidation (FAO), and favors moderate-intensity exercise capacity. The status that the body accommodates to produce and utilize ketone bodies (KB) and fatty acids as primary fuel sources is termed keto-adaptation. However, keto-adaptation requires time, while long-term KD also involves unfavored adverse effects. Exogenous ketone body (EKBs) administration has been introduced to elicit the advantages of NS. However, the direct use of EKBs fails to bring desired outcomes. We hypothesized that EKBs might only be effective during keto-adaptation. MethodsMale C57BL/6J mice (n = 24) were divided into three groups: a control diet (Con, n = 8), a ketogenic diet (KD, n = 8), and a KD plus a ketone body (DL-{beta}-Hydroxybutyric acid sodium salt, BHB) administration (KD+BHB, n = 8). After six weeks of KD administration, mice in the KD+BHB group receive BHB added into water bottles for another six weeks. Blood KB concentration is monitored throughout the experiment, while liver, gastrocnemius, and soleus mRNA are analyzed using RT-PCR. ResultsBoth KD and KD+BHB induced and sustained NS and enhanced hepatic and muscular key genes regulating FAO. In addition, BHB administration upon keto-adaptation further increased circulating KB concentration and enhanced expressional levels of FAO-mediating genes (ACO, HADH, ACADM, and MLYCD in the gastrocnemius muscle; ACO, HADH, and MLYCD in the soleus muscle), and energy-regulating genes (PPARA and PPARG) in the liver and skeletal muscle compared to a KD. ConclusionCompared to KD alone, chronic administration of KBs upon keto-adaptation increased the expression of key genes that favor FAO or maintain energy homeostasis in the liver and skeletal muscle. Instead of directly using EKBs in non-keto-adapted individuals, it is encouraged to use EKBs upon keto-adaptation status to elicit their energy-utilizing effects. HighlightsThis is the first report to evaluate the metabolic effects using exogenous ketone bodies on keto-adapted individuals. Administration of exogenous ketone body upon keto-adaptation furtherly increased circulating ketone bodies. Administration of exogenous ketone body upon keto-adaptation individuals enhanced expression of genes related to fatty acid oxidation and energy hemostasis.

biochemistry↗

bioRxiv2023

Chemical screens in aging-relevant human motor neurons identify MAP4Ks as therapeutic targets for amyotrophic lateral sclerosis

Effective therapeutics is much needed for amyotrophic lateral sclerosis (ALS), an adult-onset neurodegenerative disease mainly affecting motor neurons. By screening chemical compounds in human patient-derived and aging-relevant motor neurons, we identify a neuroprotective compound and show that MAP4Ks may serve as therapeutic targets for treating ALS. The lead compound broadly improves survival and function of motor neurons directly converted from human ALS patients. Mechanistically, it works as an inhibitor of MAP4Ks, regulates the MAP4Ks-HDAC6-TUBA4A-RANGAP1 pathway, and normalizes subcellular distribution of RANGAP1 and TDP-43. Finally, in an ALS mouse model we show that inhibiting MAP4Ks preserves motor neurons and significantly extends animal lifespan.

neuroscience↗