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Jiang, J.

Publications and source records attributed to Jiang, J..

At least 217 records · Page 12Linked to original sources

A novel order-level lineage of ammonia-oxidizing Thaumarchaeota is widespread in marine and terrestrial environments

Ammonia-oxidizing archaea (AOA) are among the most ubiquitous and abundant groups of Archaea on Earth, widely distributed in marine, terrestrial, and geothermal ecosystems. However, the genomic diversity, biogeography, and evolutionary process of AOA populations in subsurface environments are vastly understudied compared to those of marine and soil AOA. We here report a novel AOA order Candidatus Nitrosomirales that forms a deeply branching basal sister lineage to the thermophilic Ca. Nitrosocaldales. Metagenomic and 16S rRNA gene read mapping demonstrates the dominant presence of Nitrosomirales AOA in various groundwater environments and their widespread distribution across a range of geothermal, terrestrial, and marine habitats. Notably, terrestrial Nitrosomirales AOA show the genetic capacity of using formate as an alternative source of reductant and appear to have acquired key metabolic genes and operons from other mesophilic populations via horizontal gene transfer, including the genes encoding urease, nitrite reductase, and V-type ATPase. Potential metabolic versatility and acquired functions may facilitate their radiation into a variety of subsurface, marine, and soil environments. Molecular thermometer-based evolutionary analysis suggests that Nitrosomirales originated from thermophilic environments and transitioned into temperate habitats in parallel with Nitrososphaerales and Nitrosopumilales. We also provide evidence that terrestrial-marine habitat transitions occurred within each one of the four AOA orders, which reveals a more complex evolutionary trajectory of major AOA lineages than previously proposed. Together, these findings establish a robust taxonomic and evolutionary framework of AOA and provide new insights into the ecology and evolution of this globally abundant functional guild.

microbiology↗

Conflicts are represented in a cognitive space to reconcile domain-general and domain-specific cognitive control

Cognitive control resolves conflicts between task-relevant and -irrelevant information to enable goal-directed behavior. As conflicts can arise from different sources (e.g., sensory input, internal representations), how a limited set of cognitive control processes can effectively address diverse conflicts remains a major challenge. Based on the cognitive space theory, different conflicts can be parameterized and represented as distinct points in a (low-dimensional) cognitive space, which can then be resolved by a limited set of cognitive control processes working along the dimensions. It leads to a hypothesis that conflicts similar in their sources are also represented similarly in the cognitive space. We designed a task with five types of conflicts that could be conceptually parameterized. Both human performance and fMRI activity patterns in the right dorsolateral prefrontal (dlPFC) support that different types of conflicts are organized based on their similarity, thus suggesting cognitive space as a principle for representing conflicts.

neuroscience↗

Attentional capture by fearful faces requires consciousness and is modulated by task-relevancy: a dot-probe EEG study

In the current EEG study, we used a dot-probe task in conjunction with backward masking to examine the neural activity underlying awareness and spatial processing of fearful faces and the neural processes for subsequent cued spatial targets. We presented face images under different viewing conditions (subliminal and supraliminal) and manipulated the relation between a fearful face in the pair and a subsequent target. Through both mass univariate analysis and multivariate pattern analysis, we found that fearful faces can be processed to an extent where they attract spatial attention only when they are presented supraliminally and when they are task-relevant. The spatial attention capture by fearful faces also modulated the processing of subsequent lateralised targets that were spatially congruent with the fearful face, in both behavioural and neural data. There was no evidence for nonconscious processing of the fearful faces in the current paradigm. We conclude that spatial attentional capture by fearful faces requires visual awareness and it is modulated by top-down task demands.

neuroscience↗

Bioinformatic identification of ClpI, a distinct class of Clp unfoldases in Actinomycetota

All clades of bacteria possess Hsp100/Clp family unfoldase enzymes that contribute to aspects of protein quality control. In Actinomycetota, these include ClpB, which functions as an independent chaperone and disaggregase, and ClpC, which cooperates with the ClpP1P2 peptidase to carry out regulated proteolysis of client proteins. We initially sought to algorithmically catalog Clp unfoldase orthologs from Actinomycetota into ClpB and ClpC categories. In the process, we uncovered a phylogenetically distinct third group of double-ringed Clp enzymes, which we term ClpI. ClpI enzymes are architecturally similar to ClpB and ClpC, with intact ATPase modules and motifs associated with substrate unfolding and translation. While ClpI possess an M-domain similar in length to that of ClpC, their N-terminal domain is more variable than the strongly conserved N-terminal domain of ClpC. Surprisingly, we identified separate sets of ClpI sequences that possess or lack the LGF-motifs required for stable assembly with ClpP1P2. In species where they occur, we suggest that ClpI enzymes provides additional pathways and points of regulatory control over protein quality control programs, supplementing the conserved roles of ClpB and ClpC.

bioinformatics↗

Structural insights into regulation of TRPM7 divalent cation uptake by the small GTPase ARL15

Cystathionine-{beta}-synthase (CBS)-pair domain divalent metal cation transport mediators (CNNMs) are an evolutionarily conserved family of magnesium transporters. They promote efflux of Mg2+ ions on their own or uptake of divalent cations when coupled to the transient receptor potential ion channel subfamily M member 7 (TRPM7). Recently, ADP-ribosylation factor-like GTPase 15 (ARL15) has been identified as CNNM binding partner and an inhibitor of divalent cation influx by TRPM7. Here, we characterize ARL15 as a GTP-binding protein and demonstrate that it binds the CNNM CBS-pair domain with low micromolar affinity. The crystal structure of the complex between ARL15 GTPase domain and CNNM2 CBS-pair domain reveals the molecular determinants of the interaction and allowed the identification of mutations in ARL15 and CNNM2 mutations that abrogate binding. Loss of CNNM binding prevented ARL15 suppression of TRPM7 channel activity in support of previous reports that the proteins function as a ternary complex. Binding experiments with phosphatase of regenerating liver 2 (PRL2 or PTP4A2) revealed that ARL15 and PRLs compete for binding CNNM, suggesting antagonistic regulation of divalent cation transport by the two proteins.

biochemistry↗

Estimating the energy requirements for long term memory formation

Brains consume metabolic energy to process information, but also to store memories. The energy required for memory formation can be substantial, for instance in fruit flies memory formation leads to a shorter lifespan upon subsequent starvation (Mery and Kawecki, 2005). Here we estimate that the energy required corresponds to about 10mJ/bit and compare this to biophysical estimates as well as energy requirements in computer hardware. We conclude that while the reason behind it is not known, biological memory storage is metabolically expensive,

neuroscience↗

Forces driving transposable element load variation during Arabidopsis range expansion

Genetic load refers to the accumulated and potentially life-threatening deleterious mutations in populations. Understanding the mechanisms underlying genetic load variation of transposable elements (TEs), one major large-effect mutations, during range expansion is an intriguing question in biology. Here, we used 1,115 globally natural accessions of Arabidopsis thaliana, to study the driving forces of TE load variation during its range expansion. The TE load increased with range expansion, especially in the recently established Yangtze River basin population. The effective population size explained 62.0% of the variance in TE load, and high transposition rate and positive selection or hitch-hiking effect contributed to the accumulation of TEs in the expanded populations. We genetically mapped the candidate causal genes or TEs and revealed the genetic architecture of TE load. Overall, this study reveals the variation in the genetic load of TEs during Arabidopsis expansion and highlights the causes of TE load variation.

evolutionary biology↗

High Throughput Detection of Capillary Stalling Events with Bessel Beam Two-Photon Microscopy

Disruptions in capillary flow have the potential to drive pathology across numerous diseases. But our understanding of the temporal and spatial dynamics of these events are hindered by slow volumetric imaging rates and the reliance on laborious manual analysis to process data. To address the challenges of increasing volumetric imaging speed, we use a custom-built Bessel beam two-photon microscope for efficient volumetric imaging of the capillary network. We demonstrate its ability to continuously monitor roughly 200 capillaries for capillary flow stoppages (i.e. stalling events) at a frame rate of approximately 0.5 Hz and develop a semi-automated correlation-based approach for identifying these stalling events. We applied our system and algorithm in a photothrombotic model of stroke and show elevated levels of stalling 1-week post-stroke in regions both within and outside of the stroke region, demonstrating that stalling may have impacts on stroke recovery that extend past the acute stage.

neuroscience↗

Predicting distributed working memory activity in a large-scale mouse brain: the importance of the cell type-specific connectome

Recent advances in connectome and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the mouse multiregional brain for a cardinal cognitive function called working memory, the brains ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for inter-areal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.

neuroscience↗

Germline determinants of the prostate tumor genome

A persons germline genome strongly influences their risk of developing cancer. Yet the molecular mechanisms linking the host genome to the specific somatic molecular phenotypes of individual cancers are largely unknown. We quantified the relationships between germline polymorphisms and somatic mutational features in prostate cancer. Across 1,991 prostate tumors, we identified 23 co-occurring germline and somatic events in close 2D or 3D spatial genomic proximity, affecting 10 cancer driver genes. These driver quantitative trait loci (dQTLs) overlap active regulatory regions, and shape the tumor epigenome, transcriptome and proteome. Some dQTLs are active in multiple cancer types, and information content analyses imply hundreds of undiscovered dQTLs. Specific dQTLs explain at least 16.7% ancestry-biases in rates of TMPRSS2-ERG gene fusions and 67.3% of ancestry-biases in rates of FOXA1 point mutations. These data reveal extensive influences of common germline variation on somatic mutational landscapes.

cancer biology↗

Systematic mining and genetic characterization of regulatory factors for wheat spike development

The spike architecture of wheat plays a crucial role in determining grain number, making it a key trait to optimize in wheat breeding programs. In this study, through a multi-omic approach, we analyzed the transcriptome and epigenome profiles of the shoot apex at eight developmental stages, revealing coordinated changes in chromatin accessibility and H3K27me3 abundance during the flowering transition. We constructed a core transcriptional regulatory network (TRN) that drives wheat spike formation, and experimentally validated a multi-layer regulatory module involving TaSPL15, TaAGLG1, and TaFUL2. By integrating the TRN with genome-wide association analysis (GWAS), we identified 227 transcription factors (TFs), including 42 with known functions and 185 with unknown functions. Further investigation of 61 novel TFs using multiple homozygous mutant lines uncovered 36 TFs with altered spike architecture or flowering time, such as TaMYC2-A1, TaMYB30-A1, and TaWRKY37-A1. Of particular interest, TaMYB30-A1, downstream and repressed by WFZP, was found to regulate fertile spikelet number. Notably, during the domestication and breeding process in China, the excellent haplotype of TaMYB30-A1 containing a C allele at the WFZP binding site was enriched, leading to improved agronomic traits. Our study presents novel and high-confidence regulators and offers an effective strategy for understanding the genetic basis of wheat spike development, with practical impact for wheat breeding applications.

plant biology↗

Technical Note: STRATIS: A Cloud-enabled Software Toolbox for Radiotherapy and Imaging Analysis

PurposeRecent advances in computational resources, including software libraries and hardware, have enabled the use of high-dimensional, multi-modal datasets to build Artificial Intelligence (AI) models and workflows for radiation therapy and image analysis. The purpose of Software Toolbox for RAdioTherapy and Imaging analysiS (STRATIS) is to provide cloud-enabled, easy-to-share software workflows to train and deploy AI models for transparency and multi-institutional collaboration. MethodSTRATIS leverages open source medical image informatics software for application-specific analysis. Jupyter notebooks for AI modeling workflows are provided with Python language as the base kernel. In addition to Python, workflows use software written in other languages, such as MATLAB, GNU-Octave, R, and C++, with the help of bridge libraries. The workflows can be run on a cloud platform, local workstation, or an institutional HPC cluster. Computational environments are provided in the form of publicly available docker images -and build scripts for local Anaconda environments. Utilities provided with STRATIS simplify bookkeeping of associations between imaging objects and allow chaining data processing operations defined via a setting file for AI models. ResultsWorkflows available on STRATIS can be broadly categorized into image segmentation, deformable image registration, and outcomes modeling for radiotherapy toxicity and tumor control using radiomics and dosimetry features. The STRATIS-forge GitHub organization https://www.github.com/stratis-forge hosts build-scripts for Docker and Anaconda as well as Jupyter notebooks for analysis workflows. The software for building environments and workflow notebooks has open source-GNU-GPL copyright, and AI models retain the copyright chosen by their original developers. ConclusionSTRATIS enables researchers to deploy and share AI modeling workflows for radiotherapy and image analysis. STRATIS is publicly available on Terra.bios FireCloud platform with a pre-deployed computational environment and on GitHub organization for users pursuing local deployment.

bioinformatics↗

Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China

BackgroundAlthough inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed. MethodsWe enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests. ResultsOur results revealed that binding antibody IgM peaked 14-28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The NAb inhibition rate subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89) to 17.8% (16/90). ConclusionsTwo doses of CoronaVac vaccine resulted in limited protection over a short duration. The homologous booster slightly increased antibody responses to the Delta and Omicron variants; therefore, the optimization of booster procedures is vital. FundingKey Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation.

immunology↗

Machine learning-guided directed evolution for the development of small-molecule antibiotics originating from antimicrobial peptides

Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics that possess a variety of potent biological activities by exerting immunomodulatory effects to clear difficult-to-treat infections. Understanding the structure-activity relationships (SARs) of AMPs can direct the synthesis of desirable therapeutics. In this study, we use machine learning-guided directed evolution to develop the lipopolysaccharide-binding domain (LBD), which acts as a functional domain of anti-lipopolysaccharide factor (ALF), a family of AMPs, identified from Marsupenaeus japonicus. We report the identification of LBDA-D as an output of this algorithm with the input of the original LBDMj sequence and show the NMR solution structure of LBDB, which possesses a circular extended structure with a disulfide crosslink in each terminus and two 310-helices and exhibits a broad antimicrobial spectrum. Scanning electron microscopy and transmission electron microscopy showed LBDB induced the formation of a cluster of bacteria wrapped in a flexible coating that ruptured and consequently killed the bacteria. The co-injection of LBDB and Vibrio alginolyticus, Staphylococcus aureus and another major pathogen in shrimp aquaculture white spot syndrome virus in vivo improved the survival of M. japonicus, indicating a promising therapeutic role of LBDB for infectious disease. The findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics.

synthetic biology↗

A Unified Modular Framework to Incorporate Structural Dependency in Spatial Omics Data

Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution revealed plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allowed for spatial mapping of reference populations with significantly reduced ambiguity.

bioinformatics↗

Measuring Capillary Flow Dynamics using Interlaced Two-Photon Volumetric Scanning

Two photon microscopy and optical coherence tomography (OCT) are two standard methods for measuring flow speeds of red blood cells in microvessels, particularly in animal models. However, traditional two photon microscopy lacks the depth of field to adequately capture the full volumetric complexity of the cerebral microvasculature and OCT lacks the specificity offered by fluorescent labeling. In addition, the traditional raster scanning technique utilized in both modalities requires a balance of image frame rate and field of view, which severely limits the study of RBC velocities in the microvascular network. Here, we overcome this by using a custom two photon system with an axicon based Bessel beam to obtain volumetric images of the microvascular network with fluorescent specificity. We combine this with a novel scan pattern that generates pairs of frames with short time delay sufficient for tracking red blood cell flow in capillaries. We track flow speed in 10 or more capillaries simultaneously at 1 Hz in a 237 m x 237m x 120 m volume and quantify both spatial and temporal variability in speed. We also demonstrate the ability to track flow speed changes around stalls in capillary flow.

bioengineering↗

Loss of FBXO11 function establishes a stem cell program in acute myeloid leukemia through dysregulation of the mitochondrial protease LONP1

Acute myeloid leukemia (AML) is an aggressive cancer with very poor outcomes. To identify additional drivers of leukemogenesis, we analyzed sequence data from 1,727 unique individual AML patients, which revealed mutations in ubiquitin ligase family genes in 11.2% of adult AML samples with mutual exclusivity. The Skp1/Cul1/Fbox (SCF) E3 ubiquitin ligase complex gene FBXO11 was the most significantly downregulated gene of the SCF complex in AML. FBXO11 catalyzes K63-linked ubiquitination of a novel target, LONP1, which promotes entry into mitochondria, thereby enhancing mitochondrial respiration. Reduced mitochondrial respiration secondary to FBXO11 depletion imparts myeloid-biased stem cell properties in primary CD34+ hematopoietic stem progenitor cells (HSPC). In a human xenograft model, depletion of FBXO11 cooperated with AML1-ETO and mutant KRASG12D to generate serially transplantable AML enriched for primitive cells. Our findings suggest that reduced FBXO11 primes HSPC for myeloid-biased self-renewal through attenuation of LONP1-mediated regulation of mitochondrial respiration.

cancer biology↗

Zinc Fingers and Homeoboxes 2 is Required for Diethylnitrosamine-induced Liver Tumor Formation in C57BL/6 Mice

Liver cancer, comprised mainly of hepatocellular carcinoma (HCC), is the third leading cause of cancer deaths worldwide and increasing in Western countries. We previously identified the transcription factor Zinc Fingers and Homeoboxes 2 (Zhx2) as a regulator of hepatic gene expression, and many Zhx2 target genes are dysregulated in HCC. Here, we investigate HCC in Zhx2-deficient mice using the Diethylnitrosamine (DEN)-induced liver tumor model. Our study using whole-body Zhx2 knock-out (Zhx2KO) mice revealed the complete absence of liver tumors 9 and 10 months after DEN exposure.Analysis soon after DEN treatment showed no differences in expression of the DEN bioactivating enzyme CYP2E1 and DNA polymerase delta 2, or in the numbers of {gamma}H2AX foci between Zhx2KO and wild-type (Zhx2wt) mice. The absence of Zhx2, therefore, did not alter DEN bioactivation or DNA damage. Zhx2KO livers showed fewer positive foci for Ki67 staining and reduced IL-6 and AKT2 expression compared to Zhx2wt livers, suggesting that Zhx2 loss reduces liver cell proliferation and may account for reduced tumor formation. Tumors were reduced but not absent in DEN-treated liver-specific Zhx2 knock-out mice, suggesting that Zhx2 acts in both hepatocytes and non-parenchymal cells to inhibit tumor formation. Analysis of data from The Cancer Genome Atlas and Clinical Proteomic Tumor Consortium indicated that ZHX2 mRNA and protein levels were significantly higher in HCC patients and associated with clinical pathological parameters. ConclusionsIn contrast to previous studies in human hepatoma cell lines and other HCC mouse models showing that Zhx2 acts as a tumor suppressor, our data indicate that Zhx2 acts as an oncogene in the DEN-induced HCC model and is consistent with the higher ZHX2 expression in HCC patients.

cancer biology↗