Biology subjects

Chang, H.

Publications and source records attributed to Chang, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

A mutation-mediated host shift drives Avian paramyxovirus type 1 evolution

PPMV-1, an antigenic variant of APMV-1, associated with specific pigeon host species. However, its evolutionary strategy and underlying drivers of host specificity remain unknown. In this study, we collect the outbreak data on a global scale to investigate its evolutionary dynamics, and provide an evidence-supported analysis the host shift of PPMV-1 from chickens to pigeons, and this shift is driven by the P protein. Our data indicated that the viruses in the United States and China have undergone convergent evolution. We find that three mutations of P protein, especially R163G, can significantly affect the adaptation of APMV-1 in pigeons. Mechanistically, sensor LSm14A inhibits the replication APMV-1 in DF-1 cells, and R163G substitutionon P protein increase LSm14A degradation. We propose the host shift drive the evolution of PPMV-1 and the underlying mechanism, offering new insights into the adaptive evolutionary process of the virus.

microbiology↗

bioRxiv2023

Protein Engineering for Thermostability through Deep Evolution

Protein engineering for increased thermostability through iterative mutagenesis and high throughput screening is labor-intensive, expensive and inefficient. Here, we developed a deep evolution (DeepEvo) strategy to engineer protein thermostability through global sequence generation and selection using deep learning models. We firstly constructed a thermostability selector based on a protein language model to extract thermostability-related features in high-dimensional latent spaces of protein sequences with high temperature tolerance. Subsequently, we constructed a variant generator based on a generative adversarial network to create protein sequences containing the desirable function with more than 50% accuracy. Finally, the generator and selector were utilized to iteratively improve the performance of DeepEvo on the model protein glyceraldehyde-3-phosphate dehydrogenase (G3PDH), whereby 8 highly thermostable variants were obtained from only 30 generated sequences, demonstrating the high efficiency of DeepEvo for the engineering of protein thermostability.

bioinformatics↗

bioRxiv2023

Rewiring of master transcription factor cistromes during high-grade serous ovarian cancer development

The transcription factors MECOM, PAX8, SOX17 and WT1 are candidate master regulators of high-grade serous ovarian cancer (HGSC), yet their cooperative role in the hypothesized tissue of origin, the fallopian tube secretory epithelium (FTSEC) is unknown. We generated 26 epigenome (CUT&TAG, CUT&RUN, ATAC-seq and HiC) data sets and 24 profiles of RNA-seq transcription factor knock-down followed by RNA sequencing in FTSEC and HGSC models to define binding sites and gene sets regulated by these factors in cis and trans. This revealed that MECOM, PAX8, SOX17 and WT1 are lineage-enriched, super-enhancer associated master regulators whose cooperative DNA-binding patterns and target genes are re-wired during tumor development. All four TFs were indispensable for HGSC clonogenicity and survival but only depletion of PAX8 and WT1 impaired FTSEC cell survival. These four TFs were pharmacologically inhibited by transcriptional inhibitors only in HGSCs but not in FTSECs. Collectively, our data highlights that tumor-specific epigenetic remodeling is tightly related to MECOM, PAX8, SOX17 and WT1 activity and these transcription factors are targetable in a tumor-specific manner through transcriptional inhibitors.

cancer biology↗

bioRxiv2023

The Role of Terminal Uridyl Transferases in the Circadian Rhythm

The 3 terminal oligo-uridylation, a post-transcriptional mRNA modification, is conserved among eukaryotes and drives mRNA degradation, thereby affecting several key biological processes such as animal development and viral infection. Our TAIL-seq experiment of mouse liver mRNA collected from six zeitgeber times reveals transcripts with rhythmic poly(A) tail lengths and demonstrates that overall 3 terminal uridylation frequencies at mRNA poly(A) tail very-ends undergo rhythmic change. Consistently, major terminal uridylyl transferases, TUT4 and TUT7, have cycling protein expression in mouse liver corresponding to 3 terminal uridylation rhythms, indicating that the cycling expression of TUTases correlates with the rhythmic pattern of uridylation. Furthermore, the double knockdown of TUT4 and TUT7 in U2OS cells lengthens the circadian period and decreases the rhythmic amplitude of clock gene expression. Our work thoroughly profiles the dynamic changes in poly(A) tail lengths and terminal modifications and uncovers uridylation as a post-transcriptional modulator in the mammalian circadian clock.

molecular biology↗

bioRxiv2023

Glutathione supports lipid abundance in vivo

Cells rely on antioxidants to survive. The most abundant antioxidant is glutathione (GSH). The synthesis of GSH is non-redundantly controlled by the glutamate-cysteine ligase catalytic subunit (GCLC). GSH imbalance is implicated in many diseases, but the requirement for GSH in adult tissues is unclear. To interrogate this, we developed a series of in vivo models to induce Gclc deletion in adult animals. We find that GSH is essential to lipid abundance in vivo. GSH levels are reported to be highest in liver tissue, which is also a hub for lipid production. While the loss of GSH did not cause liver failure, it decreased lipogenic enzyme expression, circulating triglyceride levels, and fat stores. Mechanistically, we found that GSH promotes lipid abundance by repressing NRF2, a transcription factor induced by oxidative stress. These studies identify GSH as a fulcrum in the livers balance of redox buffering and triglyceride production.

biochemistry↗

bioRxiv2023

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism

Children with autism spectrum disorders (ASD) often display atypical learning styles, however little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. Critically, while learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

neuroscience↗

bioRxiv2022

Cortical Reactivation of Non-Spatial and Spatial Memory Representations Coordinate with Hippocampus to Form a Memory Dialogue

Episodic memory depends on the association of diverse attribute representations that are distributed across the neocortex, and evidence suggests that these attributes are linked, at least initially, by the hippocampus, which orchestrates retrieval and the offline replay of experience during memory consolidation. The dynamics that characterize this hippocampal-cortical dialogue, however, are only partly understood. Although it was originally proposed that replay is initiated in CA3, with the spontaneous emission of sharp-wave ripple (SWR) bursts, increasing evidence suggests that cortex may seed the process with partial information, leading to pattern completion in CA3 and subsequent global reactivation of the episode. A recent study has shown that the secondary motor cortex (M2), among other areas, carries two distinct types of representations: place cell-like activity, which relies on an intact hippocampus for its development, and responses tied to visuo-tactile cues -- the attributes of the experience, which do not require the hippocampus. Using two-photon Ca2+ imaging, while simultaneously acquiring LFP from the ipsilateral CA1, we assessed the interactions among cortical retrieval of visuo-tactile attributes of previous experiences in a virtual environment, hippocampal SWR, and the cortical reinstatement of the spatial aspects of the same experiences. During rest after the experience, two types of reactivation events occurred, which separately conveyed information about spatial trajectories and visuo-tactile attributes. Reactivation of attribute information preceded that of trajectories in relation to hippocampal SWRs. Furthermore, paired reactivations of cue and trajectory information supported similar features of previous experiences. These results are consistent with the hypothesis that cortical retrieval of non-spatial attributes of recent experience seeds hippocampal reactivation of associated spatial sequences, which is followed by retrieval of episodic memory traces.

neuroscience↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

Predicting Immune Escape with Pretrained Protein Language Model Embeddings

Assessing the severity of new pathogenic variants requires an understanding of which mutations enable escape of the human immune response. Even single point mutations to an antigen can cause immune escape and infection by disrupting antibody binding. Recent work has modeled the effect of single point mutations on proteins by leveraging the information contained in large-scale, pretrained protein language models (PLMs). PLMs are often applied in a zero-shot setting, where the effect of each mutation is predicted based on the output of the language model with no additional training. However, this approach cannot appropriately model immune escape, which involves the interaction of two proteins--antibody and antigen-- instead of one protein and requires making different predictions for the same antigenic mutation in response to different antibodies. Here, we explore several methods for predicting immune escape by building models on top of embeddings from PLMs. We evaluate our methods on a SARS-CoV-2 deep mutational scanning dataset and show that our embedding-based methods significantly outperform zero-shot methods, which have almost no predictive power. We also highlight insights gained into how best to use embeddings from PLMs to predict escape. Despite these promising results, simple statistical and machine learning baseline models that do not use pretraining perform comparably, showing that computationally expensive pretraining approaches may not be beneficial for escape prediction. Furthermore, all models perform relatively poorly, indicating that future work is necessary to improve escape prediction with or without pretrained embeddings1.

bioinformatics↗

bioRxiv2022

Generation of a hybrid AppNL-G-F/NL-G-F xThy1-GCaMP6s+/- Alzheimer disease mouse mitigates the behavioral and hippocampal encoding deficits of APP knock-in mutations of AppNL-G-F/NL-G-F mice

In contrast to most transgenic mouse models of Alzheimer disease (AD), knock-in mice expressing familial AD-linked mutations of the amyloid precursor protein (App) gene exhibit stereotypical age-dependent amyloid beta (A{beta}) pathology and cognitive impairment without physiologically unrealistic App overexpression. This study investigated the effect of familial AD-linked App mutations on hippocampal CA1 neuronal activity and function. To enable calcium imaging of neuronal activity, AppNL-G-F/NL-G-F knock-in (APPki) mice were crossed with Thy1-GCaMP6s+/- (C-TG) mice to generate AppNL-G-F/NL-G-FxThy1-GCaMP6s+/- (A-TG) mice, which were characterized at 12 months of age. A-TG mice exhibited A{beta} pathology in the hippocampus. In several configurations of an air-induced running task, A-TG mice and C-TG mice were equally successful in learning to run or to stay immobile. In the Morris water place test, A-TG mice were impaired, but learned the task. Comparisons of hippocampal CA1 neuronal activity in the air-induced running task showed that A-TG mice displayed neuronal hypoactivity both during movement and immobility. A-TG mice and C-TG CA1 neuronal encoding of distance or time in the air induced running task were not different. These results suggest that knock-in of familial AD-linked mutations in A-TG mice results in A{beta} pathology, neuronal hypoactivity, and cognitive impairment without severely affecting CA1 neuronal encoding. In comparison to APPki mice, A-TG mice had less severe AD-like memory impairments at 12 months of age (Saito et al., 2014; Mehla et al., 2019), suggesting that the disease onset was delayed in A-TG mice. The effect of APP mutations may have been mitigated through genetic mechanisms when APPKi mice were crossed with C-TG mice.

neuroscience↗

bioRxiv2022

XIST ribonucleoproteins promote female sex-biased autoimmunity

Autoimmune diseases disproportionately affect females more than males. The XX sex chromosome complement is strongly associated with susceptibility to autoimmunity. Xist long noncoding RNA (lncRNA) is expressed only in females to randomly inactivate one of the two X chromosomes to achieve gene dosage compensation. Here, we show that the Xist ribonucleoprotein (RNP) complex, comprised of numerous autoantigenic components, is an important driver of sex-biased autoimmunity. Inducible transgenic expression of a non-silencing form of Xist in male mice introduced Xist RNP complexes and sufficed to produce autoantibodies. Male SJL/J mice expressing transgenic Xist developed more severe multiorgan pathology in pristane-induced model of lupus than wild-type males. Xist expression in males reprogrammed T and B cell population and chromatin states to more resemble wild type females. Human patients with autoimmune diseases displayed significant autoantibodies to multiple components of XIST RNP. Thus, a sex-specific lncRNA scaffolds ubiquitous RNP components to drive sex-biased immunity. HIGHLIGHTSO_LITransgenic mouse models inducibly express Xist in male animals. C_LIO_LIXist expression in males induce autoantibodies and autoimmune pathology. C_LIO_LIXist in males reprograms T and B cell populations to female-like patterns. C_LIO_LIAutoantibodies to Xist RNP characterize female-biased autoimmune diseases. C_LI

molecular biology↗

bioRxiv2022

Capsid-mediated chromatin state of the AAV vector genome controls host species range

Recombinant adeno-associated viral vectors (rAAVs) are among the most commonly used vehicles for in vivo based gene therapies. However, it is hard to predict which AAV capsid will provide the most robust expression in human subjects due to the observed discordance in vector-mediated transduction between species. We used a primate specific capsid, AAV-LK03, and demonstrated that the limitation of this capsid towards transduction of mouse cells was unrelated to cell entry and nuclear transport but rather due to depleted histone H3 chemical modifications related to active transcription, namely H3K4me3 and H3K27ac, on the vector DNA itself. A single-amino acid insertion into the AAV-LK03 capsid enabled efficient transduction and the accumulation of active histone marks on the vector chromatin in mouse without compromising transduction efficiency in human cells. Our study suggests that the capsid protein itself is involved in determining the chromatin status of the vector genome, most likely during the process of uncoating. Programming viral chromatin states by capsid design may enable facile DNA transduction between vector and host species.

molecular biology↗

bioRxiv2022

Biological age and brain age in midlife: relationship to multimorbidity and mental health

Multimorbidity, co-occurrence of two or more chronic conditions, is one of the top priorities in global health research and has emerged as the gold standard approach to study disease accumulation. As aging underlies the development of many chronic conditions, surrogate aging biomarkers are not disease-specific and capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Biological age has been examined in recent years as a surrogate biomarker to capture the process of aging. However, relatively few studies have investigated the relationship between biological age and multimorbidity. More research is needed to quantify biological age using a broad range of biological markers and multimorbidity based on a comprehensive set of chronic conditions. Brain age estimated by neuroimaging data and machine learning models is another surrogate aging biomarker predictive of a wide range of health outcomes. Little is known about the relationship between brain age and multimorbidity. To answer these questions, our study investigates whether elevated biological age and accelerated brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States (MIDUS) Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using convolutional neural networks and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity and presents the first effort to test whether sex moderates the relationship between these surrogate aging biomarkers and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of the accumulation of physical and mental health conditions, which may contribute to new strategies to improve the treatment of multimorbidity and detection of at-risk individuals.

neuroscience↗

bioRxiv2022

Increased ozone levels disrupt insect sexual communication

Insect sexual communication often relies upon sex pheromones1-3. Most insect pheromones, however, contain carbon-carbon double bonds and potentially degrade by oxidation4. Here, we show that already frequently reported increased levels of Anthropocenic ozone can oxidize all described male-specific pheromones of Drosophila melanogaster5-7, resulting in reduced amounts of e.g. cis-Vaccenyl Acetate and (Z)-7-Tricosene. At the same time female acceptance of ozone-exposed males is significantly delayed. Interestingly, groups of ozonized males also exhibit unnaturally high levels of male-male courtship behavior. When repeating similar experiments with nine other drosophilid species, we observe pheromone degradation and/or corrupted sex recognition in eight of them. Our data suggest that Anthropocenic levels of ozone can oxidize double bonds in a variety of insect pheromones extensively, thereby leading to deviations in sexual recognition.

animal behavior and cognition↗

bioRxiv2022

Optogenetic reduction of theta oscillations reveals that a single reliable time cell sequence is not required for working memory

In a delayed alternation spatial working memory task, hippocampal time cells fire during specific moments of the delay period to form a stable, sequential representation of the entire delay interval. The causal relationship between these sequences and working memory remains unclear. Similarly, hippocampal theta oscillations are thought to support working memory, primarily through the generation of time cell sequences. To causally examine these relationships, we optogenetically silenced the medial septal GABAergic theta-generating circuit during the delay portion of a delayed spatial alternation task. Without hippocampal theta oscillations, many time cells exhibited remapping, new time cells were recruited, and time cell information was increased; collectively resulting in a new time cell sequence during the delay period. Despite this remapping of time cells on random selection of theta-reduced trials, behavioral performance was unimpaired, demonstrating that working memory is not dependent on a single or unique time cell sequence during the delay period.

neuroscience↗

bioRxiv2022

Non-redundant odorant detection in a locust

Olfactory coding, from insects to humans, is canonically considered to involve considerable across-fiber coding already at the peripheral level, thereby allowing recognition of very large numbers of odor compounds. Here we show that the migratory locust, Locusta migratoria, has evolved an alternative strategy built on highly specific odorant receptors feeding into a complex primary processing center in the brain. By collecting odors from food and different life stages of the locust, we identified 208 ecologically relevant odorants, which we used to deorphanize 48 locust olfactory receptors via ectopic expression in Drosophila. Contrary to the often broadly tuned olfactory receptors of other insects, almost all locust receptors were found to be narrowly tuned to one ligand and most of these best ligands exclusively excited only one receptor. Knocking out a single receptor using CRISPR-Cas9 resulted in an abolished physiological and behavioral response to the corresponding ligand. We conclude that the locust olfactory system, with an apparent lack of redundancy among most olfactory receptors, differs from so-far described olfactory systems.

neuroscience↗

bioRxiv2022

Thinking like a structural biologist: A pocket-based 3D molecule generative model fueled by electron density

We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets including kinase (HPK1), protease (Covid19-3CL), and nuclear receptor (VDR), and evaluated with a reference dataset composed of over 8,000 compounds that have their activities reported in the literature. The evaluation examined the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can reproduce classical active compounds and can also generate novel molecules with similar binding modes as active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create.

bioinformatics↗

bioRxiv2022

ISG15 Monomer Promotes IFNα-mediated Antiviral Activity against Pseudorabies Virus by Facilitating phosphorylation of STAT1/STAT2

Pseudorabies virus (PRV), which presently lacks both an antiviral drug and a viable therapeutic option, is a major viral pathogen that poses a danger to the pig industry worldwide. Interferon-stimulated gene 15 (ISG15) is strongly upregulated during viral infections and has been reported to have proviral or antiviral properties, depending on the virus and host species. Our previous studies demonstrated ISG15 was remarkably upregulated during PRV infection, and the overexpression of ISG15 inhibited PRV replication. Nevertheless, the exact mechanism through which ISG15 influences PRV replication poorly understood unclear. Here, we demonstrate that ISG15 accumulation induced by PRV infection requires viral gene expression and viral growth. Conjugation inhibition assays showed that ISG15 imposes its antiviral effects via unconjugated (free) ISG15 and affects the viral release. In addition, we found ISG15 promoted IFN-mediated antiviral activity against PRV by facilitating the phosphorylation of STAT1 and STAT2, along with an increase of ISGF3-induced ISRE promoter activity. Furthermore, we evaluated the role of ISG15 in host defense to control PRV infection by using ISG15-/- mice model. When challenged with PRV, ISG15-/- mice exhibited increased morbidity and mortality, as well as viral load compared to WT mice. Pathological examination revealed increased lesions, mononuclear cellular infiltration and neuronal death in the brains of ISG15-/- mice, along with the upregulation of the cytokines. Our findings establish the importance of ISG15 in IFN-induced antiviral response and in the control of PRV infection.

molecular biology↗