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Biology subjects

Chen, Z.

Publications and source records attributed to Chen, Z..

At least 487 records · Page 27Linked to original sources

Rof is a key regulator of Rho and transcription termination in bacteria

Transcription is crucial for the expression of genetic information and its efficient and accurate termination is required for all living organisms. Rho-dependent termination could rapidly terminate unwanted premature RNAs and play important roles in bacterial adaptation to changing environments. Although Rho has been discovered for about five decades, the regulation mechanisms of Rho-dependent termination are still not fully elucidated. Here we report the cryogenic electron microscopy structure of Rho-Rof antitermination complex. The structure shows that Rof binds to the open-ring Rho hexamer and inhibits the initiation of Rho-dependent termination. Rofs N-terminal -helix is key in facilitating Rof-Rho interactions. Rof binds to Rhos primary binding site (PBS) and excludes Rho from binding with PBS ligand RNA at the initiation step. Further in vivo assays in Salmonella Typhimurium show that Rof is required for virulence gene expression and host cell invasion, unveiling a novel physiological function of Rof and transcription termination in bacterial pathogenesis.

microbiology↗

Polybacterial intracellular coinfection of epithelial stem cells in periodontitis

Periodontitis affects billions of people worldwide. To address interkingdom relationships of microbes and niche on periodontitis, we generated the first sin-gle-cell meta-atlas of human periodontium (34-sample, 105918-cell), harmo-nizing 32 annotations across 4 studies1-4. Highly multiplexed immunofluores-cence (32-antibody; 113910-cell) revealed spatial innate and adaptive immune foci segregation around tooth-adjacent epithelial cells. Sulcular and junctional keratinocytes (SK/JKs) within epithelia skewed toward proinflammatory phe-notypes; diseased JK stem/progenitors displayed altered differentiation states and chemotactic cytokines for innate immune cells. Single-cell metagenomics utilizing unmapped reads revealed 37 bacterial species. 16S and rRNA probes detected polybacterial intracellular pathogenesis ("co-infection") of 4 species within single cells for the first time in vivo. Challenging coinfected primary human SK/JKs with lipopolysaccharide revealed solitary and synergistic ef-fects. Coinfected single-cell analysis independently displayed proinflammatory phenotypes in situ. Here, we demonstrate the first evidence of polybacterial intracellular pathogenesis in human tissues and cells--potentially influencing chronic diseases at distant sites.

cell biology↗

Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations

A predictive evolutionary model was developed to forecast representative influenza viral strains and select vaccine strains for upcoming epidemic seasons. Influenza virus continuously evolves to escape human adaptive immunity and generates seasonal epidemics. A computational approach beth-1 that models site-wise mutation dynamics demonstrated remarkable matching of predicted strains to the circulating viruses in subsequent seasons for the influenza A(H1N1)pdm09 and A(H3N2) viruses in both retrospective and prospective validations. The method offers a promising and ready-to-use tool to facilitate vaccine strain selection for the influenza virus, achieved by capturing heterogeneous evolutionary dynamics over genome space-time and linking molecular variants to population immune response. One-Sentence SummaryA computational model predicts virus evolution and facilitates vaccine strain selection for the influenza virus

evolutionary biology↗

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution

Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 159 samples, 652,160 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, this package also integrated a module to process the seq-based spatial transcriptomic data and analyze the spatial features of TME. Software availability: http://lifeome.net/software/sccancer2/.

bioinformatics↗

Endocytosis gated by emergent properties of membrane-clathrin interactions

Clathrin-mediated endocytosis (CME), the major cellular entry pathway, starts when clathrin assembles on the plasma membrane into clathrin-coated pits (CCPs). Two populations of CCPs are detected within the same cell: productive CCPs that invaginate and pinch off, forming clathrin-coated vesicles (CCVs) [1, 2], and abortive CCPs [3, 4, 5] that prematurely disassemble. The mechanisms of gating between these two populations and their relations to the functions of dozens of early-acting endocytic accessory proteins (EAPs) [5, 6, 7, 8, 9] have remained elusive. Here, we use experimentally-guided modeling to integrate the clathrin machinery and membrane mechanics in a single dynamical system. We show that the split between the two populations is an emergent property of this system, in which a switch between an Open state and a Closed state follows from the competition between the chemical energy of the clathrin basket and the mechanical energy of membrane bending. In silico experiments revealed an abrupt transition between the two states that acutely depends on the strength of the clathrin basket. This critical strength is lowered by membrane-bending EAPs [10, 11, 12]. Thus, CME is poised to be shifted between abortive and productive events by small changes in membrane curvature and/or coat stability. This model clarifies the workings of a putative endocytic checkpoint whose existence was previously proposed based on statistical analyses of the lifetime distributions of CCPs [4, 13]. Overall, a mechanistic framework is established to elucidate the diverse and redundant functions of EAPs in regulating CME progression.

biophysics↗

Melatonin alleviates valproic acid-induced neural tube defects by modulating Src/PI3K/ERK signaling and oxidative stress

Neural tube defects (NTDs) represent a developmental disorder of the nervous system that can lead to significant disability in children and impose substantial social burdens. Valproic acid (VPA), a widely prescribed first-line antiepileptic drug for epilepsy and various neurological conditions, has been associated with a fourfold increase in the risk of NTDs when used during pregnancy. Consequently, urgent efforts are required to identify innovative prevention and treatment approaches for VPA-induced NTDs. Studies have demonstrated that the disruption in the delicate balance between cell proliferation and apoptosis is a crucial factor contributing to NTDs induced by VPA. Encouragingly, our current data reveal that melatonin (MT) exerts significant inhibition on apoptosis while promoting the restoration of neuroepithelial cells proliferation impaired by VPA. Moreover, further investigations demonstrate that MT substantially reduces the incidence of neural tube malformations resulting from VPA exposure, primarily achieved by suppressing apoptosis through the modulation of intracellular reactive oxygen species levels. In addition, the Src/PI3K/ERK signaling pathway appears to play a pivotal role in VPA-induced NTDs, with a significant inhibition observed in the affected samples. Notably, MT treatment successfully reinstates the Src/PI3K/ERK signals, thereby offering a potential underlying mechanism for MTs protective effects against VPA-induced NTDs. In summary, our current study substantiates the considerable protective potential of MT in mitigating VPA-triggered NTDs, thereby offering valuable strategies for the clinical management of VPA-related birth defects.

developmental biology↗

Directly selecting differentially expressed genes for single-cell clustering analyses

In single-cell RNA sequencing (scRNA-seq) studies, cell-types and their associated marker genes are often identified by clustering and differential expression gene (DEG) analysis. scRNA-seq data contain many genes not relevant to cell-types and gene selection procedures are needed for more accurate clustering. An ideal gene selection procedure should select all DEGs between cell-types for best cell-type identification. However, because cell-types are unknown, gene selection and DEG analysis are performed separately using different methods. Genes are selected using surrogate criteria not directly related with clustering, which often miss important genes or select unimportant genes. Clustering accuracy could be seriously influenced because of the inferior gene selection. DEGs are often detected by comparing different clusters, leading to many false DEGs due to the selection bias problem. In this paper, we present Festem, a unified method for gene selection and DEG analysis in scRNA-seq studies. Festem investigates genes clustering information based on the observation that marginal distributions of DEGs are mixtures of their different cell-type-conditional distributions, and can directly select the clustering-informative DEGs and avoid the selection bias problem. Extensive simulation and real data analyses show that Festem achieves high precision and recall for DEG detection, and enables more accurate clustering and cell-type identification. Applications to several scRNA-seq datasets demonstrate that Festem can identify cell-types that are often missed by other methods. In a large intrahepatic cholangiocarcinoma dataset, we identify CD8+ T cell-types and find that their marker genes are novel prognostic biomarkers.

bioinformatics↗

Cuprizone drives divergent neuropathological changes in different mouse models of Alzheimer's disease

Myelin degradation is a normal feature of brain aging that accelerates in Alzheimers disease (AD). To date, however, the underlying biological basis of this correlation remains elusive. The amyloid cascade hypothesis predicts that demyelination is caused by increased levels of the {beta}-amyloid (A{beta}) peptide. Here we report on work supporting the alternative hypothesis that early demyelination is upstream of amyloid. We challenged two different mouse models of AD (R1.40 and APP/PS1) using cuprizone-induced demyelination and tracked the responses with both neuroimaging and neuropathology. In oppose to amyloid cascade hypothesis, R1.40 mice, carrying only a single human mutant APP (Swedish; APPSWE) transgene, showed a more abnormal changes of magnetization transfer ratio and diffusivity than in APP/PS1 mice, which carry both APPSWE and a second PSEN1 transgene (delta exon 9; PSEN1dE9). Although cuprizone targets oligodendrocytes (OL), magnetic resonance spectroscopy and targeted RNA-seq data in R1.40 mice suggested a possible metabolic alternation in axons. In support of alternative hypotheses, cuprizone induced significant intraneuronal amyloid deposition in young APP/PS1, but not in R1.40 mice, and it suggested the presence of PSEN deficiencies, may accelerate A{beta} deposition upon demyelination. In APP/PS1, mature OL is highly vulnerable to cuprizone with significant DNA double strand breaks (53BP1+) formation. Despite these major changes in myelin, OLs, and A{beta} immunoreactivity, no cognitive impairment or hippocampal pathology was detected in APP/PS1 mice after cuprizone treatment. Together, our data supports the hypothesis that myelin loss can be the cause, but not the consequence, of AD pathology. SIGNIFICANCE STATEMENTThe causal relationship between early myelin loss and the progression of Alzheimers disease remains unclear. Using two different AD mouse models, R1.40 and APP/PS1, our study supports the hypothesis that myelin abnormalities are upstream of amyloid production and deposition. We find that acute demyelination initiates intraneuronal amyloid deposition in the frontal cortex. Further, the loss of oligodendrocytes, coupled with the accelerated intraneuronal amyloid deposition, interferes with myelin tract diffusivity at a stage before any hippocampus pathology or cognitive impairments occur. We propose that myelin loss could be the cause, not the consequence, of amyloid pathology during the early stages of Alzheimers disease.

neuroscience↗

A Plant Flavonol Rescues a Pathogenic Mutation Associated with Kinesin in Neurons

KIF1A, a microtubule-based motor protein responsible for axonal transport, is linked to a group of neurological disorders known as KIF1A-associated neurological disorder (KAND). Current therapeutic options for KAND are limited. Here, we introduced the clinically relevant KIF1A(R11Q) variant into the C. elegans homolog UNC-104, resulting in uncoordinated animal behaviors. Through genetic suppressor screens, we identified intragenic mutations in UNC-104s motor domain that rescued synaptic vesicle localization and coordinated movement. We showed that two suppressor mutations partially recovered motor activity in vitro by counteracting the structural defect caused by R11Q at KIF1As nucleotide-binding pocket. We found that supplementation with fisetin, a plant flavonol, improved KIF1A(R11Q) worms movement and morphology. Notably, our biochemical and single-molecule assays revealed that fisetin directly restored the ATPase activity and processive movement of human KIF1A(R11Q) without affecting wild-type KIF1A. These findings suggest fisetin as a potential intervention for enhancing KIF1A(R11Q) activity and alleviating associated defects in KAND.

cell biology↗

Non-cell autonomous cardiomyocyte regulation complicates gene supplementation therapy for LMNA cardiomyopathy

AimsRecombinant adeno-associated viruses (rAAVs) are federally approved gene delivery vectors for in vivo gene supplementation therapy. Loss-of-function truncating variants of LMNA, the coding gene for Lamin-A/C, are one of the primary causes of inherited dilate cardiomyopathy (DCM). Here we aim to study whether AAV-based LMNA supplementation could treat LMNA deficiency-triggered cardiac defects. Methods and ResultsWe compared whole-body, cardiomyocyte-specific and genetic-mosaic mouse models that carry Lmna truncating variants at the same genetic loci and uncovered primarily a non-cell autonomous impact of Lmna on cardiomyocyte maturation. Whole-body lamin-A supplementation by rAAVs moderately rescued the cardiac defects in Lmna germline mutants. By contrast, cardiomyocyte-specific lamin-A addback failed to restore the cardiomyocyte growth defects. A Cre-loxP-based AAV vector that expresses lamin-A throughout the body but excluding the heart was able to restore cardiomyocyte growth in Lmna germline mutants. ConclusionsLmna regulates cardiomyocyte growth non-cell autonomously. Non-myocytes are the key cell targets for a successful gene therapy for LMNA-associated cardiac defects. Translational perspectiveLMNA truncating mutations are among the major causes of inherited DCM. AAV gene supplementation therapy is emerging as a promising strategy to treat genetic cardiomyopathy, but whether this strategy is suitable for LMNA cardiomyopathy remained unclear. Our study counterintuitively showed that the cardiomyocytes are not necessarily the correct therapeutic cell targets for AAV-based treatment of LMNA cardiomyopathy. By contrast, careful elucidation of cell-autonomous versus non-cell-autonomous gene functions is essential for the proper design of a gene supplementation therapy for cardiomyopathy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/549413v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@37cfdaorg.highwire.dtl.DTLVardef@2f2cd1org.highwire.dtl.DTLVardef@1278d08org.highwire.dtl.DTLVardef@19c4869_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

BERLIN: Basic Explorer for single-cell RNAseq analysis and cell Lineage Determination.

Single-cell RNA sequencing has revolutionized the study of immuno-oncology, cancer biology, and developmental biology by enabling the joint characterization of gene expression and cellular heterogeneity in a single platform. As of July 2023, the Gene Expression Omnibus now contains over 4000 published single-cell data sets, providing an invaluable opportunity for reanalysis to identify new cell types or cellular states as well as their defining transcriptional programs. To facilitate the reprocessing of these public datasets, we have devised a single-cell RNA sequencing analysis framework for data retrieval, quality control, expression normalization, dimension reduction, cell clustering, and data integration. Additionally, we have developed a Shiny App visualization platform that enables the exploration of gene expression, cell type annotations, and cell lineages through a user interface. We performed a re-analysis of single-cell RNAseq data generated from acute myeloid leukemia and tumor-reactive lymphocytes and found our pipeline to faithfully recapitulated the cell type assignment as well as expected lineage trajectories. Altogether, we present BERLIN, a single-cell RNAseq analysis pipeline that facilitates the integration and public dissemination of results from the reanalysis.

bioinformatics↗

Long-read Transcriptome Landscapes of Primary and Metastatic Liver Cancers at Transcript Resolution

BackgroundThe liver is the sixth most common site of primary cancer in humans and is frequently colonized by metastases from cancers of other organs. Few studies have investigated the transcriptomic profiles of matched primary tumor and hepatic metastases of patients. Moreover, the read length of 100-200 bases in conventional short-read RNA sequencing is too short, which makes it difficult to directly infer the full-length transcript structure. To help develop effective treatments and improve survival, it is crucial to understand the complex and diverse molecular mechanisms of primary and metastatic liver cancers. MethodsNinety-five primary and secondary liver cancer patients who underwent hepatic resection were included with long-read sequencing isoform-sequencing and short-read RNA sequencing. We compared the transcriptome landscapes of primary and metastatic liver cancers and systematically investigated HCC, paired primary tumors and liver metastases, and matched non-tumor liver tissues. ResultsWe defined the full-length isoform-level transcriptome of human primary and metastatic liver cancers and identified isoform-level diversity in HCC and metastasis-associated transcriptome variations in metastatic liver cancers. Specific RNA transcripts and isoform switching events with clinical implications were profoundly discovered in liver cancer. Metastasis-specific transcripts that can predict the metastatic risk and identify the primary sites of cancers of unknown primary liver metastasis patients were defined. Additionally, we found that adjacent paracancerous liver tissues are abnormal and characterized the premetastatic immunological and metabolic alterations in the liver that favor the spread of cancer metastases. ConclusionsOur findings strongly highlight the powerfulness of full-length transcriptome profiling to yield novel biological insights into understanding the molecular basis of tumorigenesis and will further benefit the treatment of primary and metastatic liver cancers.

genomics↗

UNI-RNA: UNIVERSAL PRE-TRAINED MODELS REVOLUTIONIZE RNA RESEARCH

AO_SCPLOWBSTRACTC_SCPLOWRNA molecules play a crucial role as intermediaries in diverse biological processes. Attaining a profound understanding of their function can substantially enhance our comprehension of lifes activities and facilitate drug development for numerous diseases. The advent of high-throughput sequencing technologies makes vast amounts of RNA sequence data accessible, which contains invaluable information and knowledge. However, deriving insights for further application from such an immense volume of data poses a significant challenge. Fortunately, recent advancements in pre-trained models have surfaced as a revolutionary solution for addressing such challenges owing to their exceptional ability to automatically mine and extract hidden knowledge from massive datasets. Inspired by the past successes, we developed a novel context-aware deep learning model named Uni-RNA that performs pre-training on the largest dataset of RNA sequences at the unprecedented scale to date. During this process, our model autonomously unraveled the obscured evolutionary and structural information embedded within the RNA sequences. As a result, through fine-tuning, our model achieved the state-of-the-art (SOTA) performances in a spectrum of downstream tasks, including both structural and functional predictions. Overall, Uni-RNA established a new research paradigm empowered by the large pre-trained model in the field of RNA, enabling the community to unlock the power of AI at a whole new level to significantly expedite the pace of research and foster groundbreaking discoveries.

bioinformatics↗

Polygenic Risk Score Associates with Atherosclerotic Plaque Characteristics at Autopsy

BackgroundPolygenic risk scores (PRS) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically. MethodsFrom 4,327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner (OCME) for sudden death between 1994 and 2015, 2,455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas (TCFA), and thrombotic CAD. ResultsAfter exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age 48.8{+/-}14.7; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared to subjects in the lowest quintile, with greater %stenosis (80.3%{+/-}27.0% vs. 50.4%{+/-}38.7%; adjusted p<0.001) and a higher frequency of calcification (69.6% vs. 35.8%; adjusted p=0.004) and TCFAs (26.7% vs. 9.5%; adjusted p=0.007). Even after adjustment for traditional CAD risk factors subjects within the highest PRS quintile had higher odds of severe atherosclerosis (i.e., [&ge;]75% stenosis; adjusted OR 3.77; 95%CI 2.10-6.78; p<0.001) and plaque rupture (adjusted OR 4.05; 95%CI 2.26-7.24; p<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged 50 years and younger (adjusted OR 4.08; 95%CI 2.01-8.30; p<0.001). No associations were observed with plaque erosion. ConclusionsThis is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects. HighlightsO_LIIn this autopsy study including 954 subjects within the CVPath Sudden Death Registry, high PRS correlated with plaque burden and atherosclerosis severity. C_LIO_LIThe PRS showed differential associations with plaque rupture and plaque erosion, suggesting different etiologies to these two causes of thrombotic CAD. C_LIO_LIPRS may be useful for risk stratification, particularly in the young. Further examination of individual risk loci and their association with plaque morphology may help understand molecular mechanisms of atherosclerosis, potentially revealing new therapy targets of CAD. C_LI Graphic AbstractA polygenic risk score, generated from 291 known CAD risk loci, was assessed in 954 subjects within the CVPath Sudden Death Registry. Histopathologic examination of the coronary arteries was performed in all subjects. Subjects in the highest PRS quintile exhibited more severe atherosclerosis as compared to subjects in the lowest quintile, with a greater plaque burden, more calcification, and a higher frequency of plaque rupture.

genetics↗

DeepCristae, a CNN for the restoration of mitochondria cristae in live microscopy images

Mitochondria play an essential role in the life cycle of eukaryotic cells. However, we still dont know how their ultrastructure, like the cristae of the inner membrane, dynamically evolves to regulate these fundamental functions, in response to external conditions or during interaction with other cell components. Although high-resolution fluorescent microscopy coupled with recently developed innovative probes can reveal this structural organization, their long-term, fast and live 3D imaging remains challenging. To address this problem, we have developed a convolutional neural network, called DeepCristae, to restore mitochondria cristae in low spatial resolution microscopy images. Our network is trained from 2D STED images using a novel loss specifically designed for cristae restoration. To efficiently increase the size of the training set, we also developed a random image patch sampling centered on mitochondrial areas. To evaluate DeepCristae, quantitative assessments were carried out using metrics we derived by focusing on the mitochondria and cristae pixels rather than on the whole image as usual. Depending on the conditions of use indicated, DeepCristae works well on broad microscopy modalities (Stimulated Emission Depletion (STED), Live-SR, AiryScan and Lattice Light Sheet Microscopy). It is ultimately applied in the context of mitochondrial network dynamics during interaction with endo/lysosome membranes.

bioinformatics↗

ColabDock: inverting AlphaFold structure prediction model for protein-protein docking with experimental restraints

Prediction of protein complex structures and interfaces potentially has wide applications and can benefit the study of biological mechanisms involving protein-protein interactions. However, the surface prediction accuracy of traditional docking methods and AlphaFold-Multimer is limited. Here we present ColabDock, a framework that makes use of ColabDesign, but reimplements it for the purpose of restrained complex conformation prediction. With a generation-prediction architecture and trained ranking model, ColabDock outperforms HADDOCK and ClusPro not only in complex structure predictions with simulated residue and surface restraints, but also in those assisted by NMR chemical shift perturbation as well as covalent labeling. It further assists antibody-antigen interface prediction with emulated interface scan restraints, which could be obtained by experiments such as Deep Mutation Scan. ColabDock provides a general approach to integrate sparse interface restraints of different experimental forms and sources into one optimization framework.

bioinformatics↗

Multiple exposures to sevoflurane during the neonatal period impair hippocampus development and cognitive function in young mice

Sevoflurane is a commonly used anesthesia for infants and young children. Sevoflurane has potential neurotoxicity in immature brains; however, its specific mechanism has not been fully elucidated. Therefore, we used an established sevoflurane anesthesia model and evaluated hippocampal synaptic function using transcriptome sequencing, biochemical analyses, and animal behavior to investigate the effect of multiple neonatal sevoflurane exposures on the hippocampus in mice. C57BL/6J mice were randomly divided into sevoflurane and control groups. All experimental conditions were identical in the two groups except for the anesthetization procedure. Mice in the sevoflurane group were anesthetized with 2.5% sevoflurane for 2 h daily for 3 consecutive days (postnatal days 6-8). Mice in the control group did not receive sevoflurane anesthesia. During anesthesia, mice were administered 50% oxygen, and the respiratory rate and skin color were monitored. On day 3 of modeling, half of the mice were randomly selected to undergo harvesting of the hippocampus. RNA sequencing (RNA-seq) of RNA extracted from the hippocampus identified 736 differentially expressed genes (DEGs), including 433 upregulated and 303 downregulated DEGs, after multiple sevoflurane exposures. Gene ontology term enrichment analysis results suggested that sevoflurane exposure altered the expression of neurodevelopment-related genes in neonatal mice. Several enriched biological processes involved in brain development (axon/forebrain development) and adenosine monophosphate-activated protein kinase signaling pathways were highlighted. Comparison with RNA-seq database information showed that DEGs of the neonatal hippocampus after multiple exposures to sevoflurane were specific to neonatal mice. Furthermore, Morris water maze testing confirmed that sevoflurane anesthesia induced learning and memory impairments in young mice. Additionally, Western blot and immunofluorescence analyses showed that sevoflurane treatment decreased synaptic protein levels, such as postsynaptic density protein 95, synaptosomal-associated protein, 25 kDa, and B-cell lymphoma 2-associated athanogene 3, in the hippocampus, which induced synaptic dysfunction, resulting in impaired nervous system development in young mice.

neuroscience↗

Polygenic basis of strong and rapid flowering time response to environment perturbations in wild Arabidopsis thaliana population

Despite the importance in understanding the impact of climate change, the genetics of rapid response to changing environments and its role in adaptive evolution remains elusive. Here, we studied flowering time response to environment changes using 514 Arabidopsis thaliana worldwide accessions with re-sequencing genomes and flowering time measurements from ten unique environments with variable temperature, drought, daylight and competition stresses. We revealed a polygenic basis of flowering time mean and plasticity, underpinned by 52 mean and plasticity QTL. Widespread interaction between mean QTL, polygenic background and surrounding environments considerably altered the amount of additive genetic variance and allelic effects of detected QTL. This caused variability in phenotype plasticity and across environment variation in genetic variance, resulting in rapid flowering time response to environment perturbations. In addition, the plastic alleles showed a higher correlation with the environment factors than that from randomly sampled alleles, suggesting a potential role in climate adaptation. We therefore proposed a polygenic interaction model, whereby large effect QTL and polygenic background simultaneously interacted with the surrounding environment, underlying rapid response to changing environments. Results from our study thus provided deeper insights into the genetics of plasticity, with potential benefit in genomic selection of crops in heterogeneous environments and predicting changes in species distribution and the evolutionary trajectory of wild populations.

genetics↗