Search bioRxiv⌕ Search

Biology subjects

Jiang, Y.

Publications and source records attributed to Jiang, Y..

At least 235 records · Page 13Linked to original sources

The gut microbiota is a determinant of sexual dimorphism in ALS-linked TDP43 mice

The mechanisms underlying the earlier onset and male predominance of amyotrophic lateral sclerosis (ALS), the most common form of human motoneuron disease, are poorly understood. Here we show that the gut microbiota protects against TDP43 toxicity and contributes to the sexual dimorphism in mice expressing a mutant form of TDP43 (A315T) linked to ALS. TDP43 mice raised under germ-free conditions, or treated with antibiotics to deplete the gut microbiota, develop motoneuron disease earlier and show no sex differences in onset and lifespan. Behavioral and histopathological analyses confirm the exacerbation in neurodegeneration caused by the absence of gut microbiota. Castration did not alter disease course of male TDP43 mice, suggesting that male sex hormones do not interact with the gut microbiota to confer disease phenotype. Future identification of gut bacteria species and their mechanisms of action offers a unique opportunity to understand sexual dimorphism in ALS, with the ultimate goal to develop non-invasive and sex-specific treatments for ALS.

physiology↗

Discovery of Novel, Potent and Orally Bioavailable SMARCA2 PROTACs with Synergistic Anti-tumor Activity in Combination with KRAS G12C Inhibitors.

Cancer genomic studies have identified frequent mutations in subunits of the SWI/SNF chromatin remodeling complex including SMARCA4 in non-small cell lung cancer with a frequency of up to 33% in advanced stage disease, making it the most frequently mutated complex in lung cancer. We and others have identified SMARCA2 to be synthetic lethal to SMARCA4, indicating SMARCA2 is a high value therapeutic target. Here, we disclose the discovery and characterization of potent, selective and orally bioavailable Cereblon-based SMARCA2 PROTACs. Biochemically, YDR1 and YD54 are potent SMARCA2 degraders with an average DC50 of 7.7nM and 3.5nM respectively in SMARCA4 mutant lung cancer cells. Phenotypically, both YDR1 and YD54 selectively inhibited growth of SMARCA4 mutant cancer cells. Further, we showed anti-tumor growth inhibitory activity of YDR1 and YD54 in SMARCA4 mutant xenograft models of lung cancer. Finally, we show that YDR1 and YD54 synergize with the KRAS G12C inhibitor sotorasib to inhibit growth of SMARCA4 and KRAS G12C co-mutant lung cancer cells. These findings provide additional evidence for the utility of single agent or combination regimens containing SMARCA2 PROTACs as synthetic lethal therapeutics against SMARCA4 mutant cancers.

cancer biology↗

PhyloMix: Enhancing microbiome-trait association prediction through phylogeny-mixing augmentation

MotivationUnderstanding the associations between traits and microbial composition is a fundamental objective in microbiome research. Recently, researchers have turned to machine learning (ML) models to achieve this goal with promising results. However, the effectiveness of advanced ML models is often limited by the unique characteristics of microbiome data, which are typically high-dimensional, compositional, and imbalanced. These characteristics can hinder the models ability to fully explore the relationships among taxa in predictive analyses. To address this challenge, data augmentation has become crucial. It involves generating synthetic samples with artificial labels based on existing data and incorporating these samples into the training set to improve ML model performance. ResultsHere we propose PhyloMix, a novel data augmentation method specifically designed for microbiome data to enhance predictive analyses. PhyloMix leverages the phylogenetic relationships among microbiome taxa as an informative prior to guide the generation of synthetic microbial samples. Leveraging phylogeny, PhyloMix creates new samples by removing a subtree from one sample and combining it with the corresponding subtree from another sample. Notably, PhyloMix is designed to address the compositional nature of microbiome data, effectively handling both raw counts and relative abundances. This approach introduces sufficient diversity into the augmented samples, leading to improved predictive performance. We empirically evaluated PhyloMix on six real microbiome datasets across five commonly used ML models. PhyloMix significantly outperforms distinct baseline methods including sample-mixing-based data augmentation techniques like vanilla mixup and compositional cutmix, as well as the phylogeny-based method TADA. We also demonstrated the wide applicability of PhyloMix in both supervised learning and contrastive representation learning. AvailabilityThe Apache licensed source code is available at (https://github.com/batmen-lab/phylomix).

bioinformatics↗

ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets

Recent advances in calcium imaging enable simultaneous recordings of up to a million neurons in behaving animals, producing datasets of unprecedented scales. Although individual neurons and their activity traces can be extracted from these videos with automated algorithms, the results often require human curation to remove false positives, a laborious process called cell sorting. To address this challenge, we introduce ActSort, an active-learning algorithm for sorting large-scale datasets that integrates features engineered by domain experts together with data formats with minimal memory requirements. By strategically bringing outlier cell candidates near the decision boundary up for annotation, ActSort reduces human labor to about 1-3% of cell candidates and improves curation accuracy by mitigating annotator bias. To facilitate the algorithms widespread adoption among experimental neuroscientists, we created a user-friendly software and conducted a first-of-its-kind benchmarking study involving about 160,000 annotations. Our tests validated ActSorts performance across different experimental conditions and datasets from multiple animals. Overall, ActSort addresses a crucial bottleneck in processing large-scale calcium videos of neural activity and thereby facilitates systems neuroscience experiments at previously inaccessible scales.

neuroscience↗

Shared and Unique Neural Codes for Biological Motion Perception in Humans and Macaque Monkeys

Throughout evolution, living organisms have honed the ability to swiftly recognize biological motion (BM) across species. However, how the brain processes within- and cross-species BM, and the evolutionary progression of these processes, remain unclear. To investigate these questions, we examined brain activity in the lateral temporal areas of humans and monkeys as they passively observed upright and inverted human and macaque BM stimuli. In humans, the middle temporal area (hMT+) responded to both human and macaque BM stimuli, while the right posterior superior temporal sulcus (pSTS) exhibited selective responses to human BM stimuli. This selectivity was evidenced by an increased feedforward connection from hMT+ to pSTS during the processing of human BM stimuli. In monkeys, the MT region processed BM stimuli from both species, but no subregion in the STS anterior to MT was specific to conspecific BM stimuli. A comparison of these findings suggests that upstream brain regions (i.e., MT) may retain homologous functions across species, while downstream brain regions (i.e., STS) may have undergone differentiation and specialization throughout evolution. These results provide insights into the commonalities and differences in the specialized visual pathway engaged in processing within- and cross-species BMs, as well as their functional divergence during evolution.

neuroscience↗

Gut microbiota metabolically mediate intestinal helminth infection in Zebrafish

Intestinal helminth parasite (IHP) infection induces alterations in the composition of microbial communities across vertebrates, although how gut microbiota may facilitate or hinder parasite infection remains poorly defined. In this work we utilized a zebrafish model to investigate the relationship between gut microbiota, gut metabolites, and IHP infection. We found that extreme disparity in zebrafish parasite infection burden is linked to the composition of the gut microbiome, and that changes in the gut microbiome are associated with variation in a class of endogenously-produced signaling compounds, N-acylethanolamines, that are known to be involved in parasite infection. Using a statistical mediation analysis, we uncovered a set of gut microbes whose relative abundance explains the association between gut metabolites and infection outcomes. Experimental investigation of one of the compounds in this analysis reveals salicylaldehyde, which is putatively produced by the gut microbe Pelomonas, as a potent anthelmintic with activity against Pseudocapillaria tomentosa egg hatching, both in vitro and in vivo. Collectively, our findings underscore the importance of the gut microbiome as a mediating agent in parasitic infection and highlights specific gut metabolites as tools for the advancement of novel therapeutic interventions against IHP infection. ImportanceIntestinal helminth parasites (IHPs) impact human health globally and interfere with animal health and agricultural productivity. While anthelmintics are critical to controlling parasite infections, their efficacy is increasingly compromised by drug resistance. Recent investigations suggest the gut microbiome might mediate helminth infection dynamics. So, identifying how gut microbes interact with parasites could yield new therapeutic targets for infection prevention and management. We conducted a study using a zebrafish model of parasitic infection to identify routes by which gut microbes might impact helminth infection outcomes. Our research linked the gut microbiome to both parasite infection, and to metabolites in the gut to understand how microbes could alter parasite infection. We identified a metabolite in the gut, salicylaldehyde, that is putatively produced by a gut microbe and that inhibits parasitic egg growth. Our results also point to a class of compounds, N-acyl-ethanolamines, which are affected by changes in the gut microbiome and are linked to parasite infection. Collectively, our results indicate the gut microbiome may be a source of novel anthelmintics which can be harnessed to control IHPs.

microbiology↗

Cell Storage Conditions Impact Single-Cell Proteomic Landscapes

Single-cell transcriptomics (SCT) has revolutionized our understanding of cellular heterogeneity, yet the emergence of single-cell proteomics (SCP) promises a more functional view of cellular dynamics. A challenge is that not all mass spectrometry facilities can perform SCP, and not all labs have access to cell sorting equipment required for SCP, which together motivate an interest in sending bulk cell samples through the mail for sorting and SCP analysis. Shipping requires cell storage, which has an unknown impact on SCP results. This study investigates the impact of cell storage conditions on the proteomic landscape at the single-cell level utilizing a Data-Independent Acquisition (DIA) coupled with Parallel Accumulation Serial Fragmentation (diaPASEF). Three storage conditions were compared in 293T cells: (1) 37{degrees}C (control), (2) 4{degrees}C overnight, and (3) - 80{degrees}C storage followed by liquid nitrogen preservation. Either cold or frozen storage induced significant alterations in cell diameter, elongation, and proteome composition. By elucidating how cell storage conditions alter cellular morphology and proteome profiles, this study contributes foundational technical information about SCP sample preparation and data quality.

cell biology↗

Pharmacological rescue of motor circuit dysfunction in a Drosophila model of paroxysmal dyskinesia

BackgroundParoxysmal dyskinesias (PxDs) are characterised by bouts of involuntary dystonic and choreiform movements. The patho-mechanisms underlying these debilitating disorders remain poorly understood, and drug treatments are often limited. We recently generated a Drosophila model of a PxD-linked mutation causing BK potassium channel gain- of-function (BK GOF), and showed that BK GOF perturbs movement in Drosophila by disrupting neurodevelopment. However, whether locomotor capacity in BK GOF flies can be pharmacologically restored following neurodevelopmental insults has remained unclear. ObjectiveTo identify pharmacological suppressors of motor defects caused by BK GOF. MethodsUsing adult BK GOF flies, we performed an unbiased, in vivo, locomotion-based screen of 370 FDA-approved drugs. To test the impact of positive hits from this screen on motor circuit activity, we used optical imaging to record the intrinsic rhythmic activity of Drosophila larval motor circuits driving peristalsis and turning behaviors. ResultsWe found that inhibitors of acetylcholinesterase - a protein that degrades acetylcholine in cholinergic synapses - partially rescued movement defects caused by BK GOF. Inhibition of acetylcholinesterase also partially restored intrinsic activity of motor circuits controlling forward movement and turning in BK GOF larvae. ConclusionsOur findings indicate that elevating cholinergic tone can reverse motor circuit dysfunction in an animal model of PxD caused by BK GOF. Furthermore, our study provides proof-of-principle that Drosophila can be utilised for screens to uncover putative drug treatments for involuntary movement disorders.

neuroscience↗

TRPML1 gating modulation by allosteric mutations and lipids

Transient Receptor Potential Mucolipin 1 (TRPML1) is a lysosomal cation channel whose loss-of-function mutations directly cause the lysosomal storage disorder mucolipidosis type IV (MLIV). TRPML1 can be allosterically regulated by various ligands including natural lipids and small synthetic molecules and the channel undergoes a global movement propagated from ligand-induced local conformational changes upon activation. In this study, we identified a functionally critical residue, Tyr404, at the C-terminus of the S4 helix, whose mutations to tryptophan and alanine yield gain- and loss-of-function channels, respectively. These allosteric mutations mimic the ligand activation or inhibition of the TRPML1 channel without interfering with ligand binding and both mutant channels are susceptible to agonist or antagonist modulation, making them better targets for screening potent TRPML1 activators and inhibitors. We also determined the high-resolution structure of TRPML1 in complex with the PI(4,5)P2 inhibitor, revealing the structural basis underlying this lipid inhibition. In addition, an endogenous phospholipid likely from sphingomyelin is identified in the PI(4,5)P2-bound TRPML1 structure at the same hotspot for agonists and antagonists, providing a plausible structural explanation for the inhibitory effect of sphingomyelin on agonist activation.

biophysics↗

Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome

Intra-tumor heterogeneity is characterized by a diverse population of tumor clones and subclones which are important drivers of tumor evolution and therapeutic response. However, accurate subclonal reconstruction at scale remains challenging. We developed a machine learning tool, CliPP, and surveyed 9,972 tumors from 32 cancer types. We found that high subclonal mutation load (sML), the fraction of subclonal single nucleotide variants (SNVs) to all SNVs in the coding region, was prognostic of survival (progression free survival or overall survival) in 18 cancer types. In 14 cancers with low to moderate tumor mutation burden (TMB), high sML was associated with better prognosis. In immunotherapy trials for 42 metastatic prostate cancer (mCRPC), high sML was predictive of favorable response to ipilimumab and associated with increased CD8+ T-cell infiltration and decreased macrophage population. A validation using 613 whole-genomes of esophageal adenocarcinoma confirms the favorable effect of high sML and the observed tumor-associated macrophage. Our study identifies sML as a key feature of cancer, suggesting a biphasic relationship between evolutionary dynamics and differential immune environments. Finally, sML may serve as an orthogonal approach to identify likely responders of immune checkpoint blockade in low to moderate TMB tumors.

genomics↗

Mapping the Learning Curves of Deep Learning Networks

There is an important challenge in systematically interpreting the internal representations of deep neural networks. This study introduces a multi-dimensional quantification and visualization approach which can capture two temporal dimensions of a model learning experience: the "information processing trajectory" and the "developmental trajectory." The former represents the influence of incoming signals on an agents decision-making, while the latter conceptualizes the gradual improvement in an agents performance throughout its lifespan. Tracking the learning curves of a DNN enables researchers to explicitly identify the model appropriateness of a given task, examine the properties of the underlying input signals, and assess the models alignment (or lack thereof) with human learning experiences. To illustrate the method, we conducted 750 runs of simulations on two temporal tasks: gesture detection and natural language processing (NLP) classification, showcasing its applicability across a spectrum of deep learning tasks. Based on the quantitative analysis of the learning curves across two distinct datasets, we have identified three insights gained from mapping these curves: nonlinearity, pairwise comparisons, and domain distinctions. We reflect on the theoretical implications of this method for cognitive processing, language models and multimodal representation. Author summaryDeep learning networks, specifically recurrent neural networks (RNNs), are designed for processing incoming signals sequentially, making them intuitive computational systems for studying cognitive processing that involves dynamic contexts. There has been a tradition in the fields of machine learning and neuro-cognitive science to examine how a system (either humans or models) represents information through various computational and statistical techniques. Our study takes this one step further by devising a technique for examining the "learning curves" of deep learning networks utilizing the sequential representations as part of RNNs architectures. Just as humans develop learning curves when solving problems, the introduced method captures both how incoming signals help improve decision-making and how a systems problem-solving abilities enhance when encountering the same situation multiple times throughout its lifespan. Our study selected two distinct tasks: gesture detection and emotion tweet classification, to illustrate the insights researchers can draw from mapping models learning curves. The proposed method hinted that gesture learning experiences are smoother, while language learning relies on sudden knowledge gains during processing, corroborating the findings from previous literature.

scientific communication and education↗

EPILEPTOGENESIS INHIBITS THE CIRCADIAN CLOCK AND RESHAPES THE DIURNAL TRANSCRIPTOMIC RHYTHMICITY IN THE MOUSE HIPPOCAMPUS

Epileptogenesis is the process that leads the brain into epileptic activity. Clinical evidence shows that [~]90% of people with epilepsy present rhythmicity in the timing of their seizures presentation. However, whether the circadian clock is a key player during epileptogenesis remains unknown. Here, we triggered epileptogenesis in mice by the intra-amygdala injection of kainic acid and profiled by RNA sequencing their hippocampal diurnal mRNA rhythmicity. We show that epileptogenesis largely reshapes the hippocampal transcriptomic rhythmicity and that the molecular clock machinery is inhibited due to the disruption of the core clock gene Bmal1. We identified relevant dysregulated pathways and their dynamics in epileptogenesis, predicting a key role for microglial-driven neuroinflammation. We predicted the genes that Bmal1 is directly controlling over time. Finally, we sought for translational relevance evidence by performing RNA sequencing in hippocampal samples resected from patients with mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE-HS) and cross-analyzing datasets.

neuroscience↗

Frontal-posterior loop integrating captured attention into visual consciousness in the human brain

We usually perceive what we are attending to. How goal-directed attention contributes to conscious perception remains yet elusive. Here we combined a novel psychophysical paradigm with intracranial electroencephalography data to investigate this issue in the human brain. Relative to unattended conditions, goal-directed attention modulated early activity and inter-regional connectivity, even though this part of attention failed to predict image detectability. Later, the coupling between the frontal and posterior brain got established and maintained but the signals exchanged did not inform fine-grained image contents but instead reflect success or failure of attentional capture. This part of captured attention proportionally predicted image detectability. These results attribute consciousness to attention-based coupling between the frontal and posterior brain as a whole, rather than activity of either part alone.

neuroscience↗

Gene Regulatory Programs that Specify Age-Related Differences during Thymocyte Development

T cell development is fundamental to immune system establishment, yet how this development changes with age remains poorly understood. Here, we construct a transcriptional and epigenetic atlas of T cell developmental programs in neonatal and adult mice, revealing the ontogeny of divergent gene regulatory programs and their link to age-related differences in phenotype and function. Specifically, we identify a gene module that diverges with age from the earliest stages of genesis and includes programs that govern effector response and cell cycle regulation. Moreover, we reveal that neonates possess more accessible chromatin during early thymocyte development, likely establishing poised gene expression programs that manifest later in thymocyte development. Finally, we leverage this atlas, employing a CRISPR-based perturbation approach coupled with single-cell RNA sequencing as a readout to uncover a conserved transcriptional regulator, Zbtb20, that contributes to age-dependent differences in T cell development. Altogether, our study defines transcriptional and epigenetic programs that regulate age-specific differences in T cell development.

genomics↗

H2A.Z deposition at meiotic prophase I underlies homologous recombination and pachytene genome activation during male meiosis

Accurate meiotic progression is important for gamete formation and the generation of genetic diversity. However, little is known about the identity of chromatin regulators that underlie mammalian meiosis in vivo. Here, we identify the multifaceted functions of the chromatin remodeler ZNHIT1 in governing meiosis. The expression of Znhit1 gradually increases during the meiotic prophase, and Znhit1 knockout in spermatocytes results in arrested pachytene development, impaired DNA double-strand break repair, and defective homologous recombination. Single-cell RNA sequencing and transcriptome analysis reveal that Znhit1 loss dysregulates meiotic transcriptional programs at the pachytene stage. Chromatin immunoprecipitation data show that ZNHIT1 is needed for the incorporation of the histone variant H2A.Z into pachytene chromatin. Moreover, we found that H2A.Z cooperates with the transcription factor A-MYB to co-bind DNA elements and control gene activity. Our findings provide insights into the regulatory mechanisms governing meiotic progression and highlight ZNHIT1 as a critical regulator of meiotic progression.

developmental biology↗

Natural killer cell migration in HIV-infected individuals is inhibited by impairment of HIF-1alpha-mediated glycolysis

Natural killer (NK) cells serve as the first line of defense of the immune system and play a crucial role in fighting against HIV infection. The effective function of NK cells is closely related to their migration ability, but the status of NK cell migration in HIV-infected individuals and the regulation mechanism for NK cell migration remains unknown. Here, we found that NK cell migration was significantly impaired in HIV-infected individuals, lower in immune non-responders (INRs) compared with immune responders (IRs), and positively correlated with CD4+ T cell counts. Further investigations showed that the decreased NK cell migration in HIV infection was caused by the impairment of glycolysis. Mechanistically, we found that NK cell migration was regulated by HIF-1 pathway, and inhibitory receptor TIGIT restrained HIF-1 expression by inhibiting PI3K/AKT/mTORC1 or ERK signaling pathway, consequently weakening the glycolysis of NK cells in HIV-infected individuals, and ultimately leading to down-regulation of migration. Collectively, we uncovered a mechanism of reduced NK cell migration in HIV infection and provided a new insight for immunotherapy in HIV infection. In BriefThe effective function of NK cells is closely related to its migration ability. The authors show that impaired NK cell migration in HIV-infected individuals is caused by TIGIT inhibiting HIF-1-mediated glycolysis via PI3K/AKT/mTORC1 or ERK pathway.

immunology↗

Spatiotemporally resolved transcriptome atlas of developing mouse placenta reveals mechanisms of embryonic lethality.

Proper placentation is fundamental to the growth and viability of the maturing embryo. However, a thorough grasp of the spatial organization of cell types, their interactions, and gene expression patterns along the maternal-fetal function during placental development remains incomplete. Here, we utilized Stereo-seq to construct the spatiotemporal transcriptomic atlas of the mouse placenta (STAMP) spanning embryonic (E) days 9.5 to 18.5 at single cell resolution (https://db.cngb.org/stomics/stamp/). This resource delineates spatially resolved cellular dynamics and gene expression patterns across placental and maternal compartments. We identified distinct glycogen trophoblast cell (GC) subclusters, mapped their developmental trajectories, and uncovered transcriptional transitions accompanying their migration from the junctional zone to the maternal decidua from E12.5 onward. In a defective placentation model with perinatal lethality, GCs abnormally persisted at E18.5 with excessive glycogen and reduced degradation metabolites in placenta and fetal liver, indicating impaired glycogen breakdown. Maternal glucose supplementation restored glucose levels and rescued fetal survival, underscoring GC-mediated metabolic support as critical for viability. Together, this study provides a comprehensive spatiotemporal placental atlas and demonstrates that GC-mediated glycogen metabolism is essential for sustaining fetal viability.

developmental biology↗

Genome sequencing of 'Fuji' apple clonal varieties reveals evolutionary history and genetic mechanism of the spur-type morphology

Somatic variations arising during asexual reproduction can lead to the emergence of bud sports exhibiting advantageous traits, forming the basis for bud sport breeding in perennial plants. Here, we report a near-complete, fully phased genome assembly of Fuji apple, enabling comprehensive identification of somatic variants across 74 clonally propagated Fuji varieties. Phylogenetic analysis of Fuji sport varieties indicates that the emergence of spur-type and early maturation traits results from multiple independent formation events. A number of putative functional somatic variants are identified, including one spur-type specific deletion located in the promoter of the TCP transcription factor gene MdTCP11. DNA methylation level of the deletion-associated miniature inverted-repeat transposable element is lower in the spur-type varieties compared to the standard-type varieties, while the expression of MdTCP11 is significantly higher. Overexpression of MdTCP11 in apple decreases the plant height, highlighting its important role in the development of spur-type apple varieties. This study sheds light on the 80-year cloning history of Fuji and provides valuable candidate causative mutations for apple breeding.

plant biology↗