Biology subjects

Hu, Z.

Publications and source records attributed to Hu, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Transcriptomic splicing analysis reveals a gene-independent form of TE reactivation in tumors representing unrecognized source of oncogenes and neoantigens

Transposable elements (TEs) are reactivated in tumors and serve as significant contributors to tumor transcriptomic complexity and heterogeneity. However, their repetitive nature and diverse transcriptional forms have hindered efforts to characterize TE-derived transcripts independent of host gene contexts. Here, using our self-developed splicing-junction analysis tool ASJA, we systematically interrogated TE transcription across 32 cancer types, identifying transcripts autonomously initiated from and exclusively spliced among TEs with high TE content, termed TEtrans. Our analysis revealed 5,361 TEtrans exhibiting pan-cancer prevalence, tumor-specific expression and features of mature transcripts, including canonical splicing, 5 caps and polyA tails. Mostly unannotated and enriched in intergenic regions, TEtrans are predominantly derived from primate-specific classes with conserved splice pattern. TEtrans burden demonstrates heterogeneous associations with prognosis and immune activity across cancers, while their expression can be epigenetically dual-regulated by stemness- and inflammation-associated transcription factors. Functional studies uncovered that TEtrans could act as oncogenes, exemplified by tsTE1, a HERVH-derived transcript that promotes colorectal cancer proliferation by enhancing TOP1-mediated DNA supercoil relaxation. Remarkably, [~]7.2% of TEtrans are identified to encode tumor neoantigens, including viral proteins and unannotated peptides, which are shared among patients and validated by proteogenomic analysis. These TEtrans-derived neoantigens are immunogenic both in vitro and in vivo, and exceed neoepitopes from genomic alterations in abundance per tumor, particularly in cancers with low mutational burden. Collectively, as a gene-independent form of TE-derived transcripts, TEtrans represents a unique source of oncogenes and tumor neoantigens, expanding the functional repertoire of TEs in cancer biology and offering new avenues for therapeutic targeting. HighlightsO_LITEtrans are tumor-specific transcripts with conserved splicing patterns, predominantly derived from primate TEs in intergenic regions. C_LIO_LITEtrans expression is epigenetically activated and dually regulated by stemness/inflammation transcription factors. C_LIO_LITEtrans function as oncogenes, exemplified by tsTE1 enhancing TOP1-mediated DNA relaxation. C_LIO_LITEtrans encode tumor neoantigens that elicit CD8+ T cell responses, providing targets for immunotherapy, especially in low-mutation tumors. C_LI Abstract figure O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/640928v1_ufig1.gif" ALT="Figure 1"> View larger version (78K): org.highwire.dtl.DTLVardef@1d2d4cforg.highwire.dtl.DTLVardef@918f14org.highwire.dtl.DTLVardef@489465org.highwire.dtl.DTLVardef@1069d17_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

LOCATE: using Long-read to Characterize All Transposable Elements

Transposons constitute [~]45% of the human genome, driving gene evolution and contributing to disease, but their repetitive nature complicates the identification of new insertions. We present LOCATE (Long-read to Characterize All Transposable Elements), an algorithm using long-read sequencing to detect and assemble transposon insertions. LOCATE outperforms existing tools on simulated datasets and achieves the best performance in two previous benchmarks, as well as in a new benchmark we constructed using real biological datasets. Applying LOCATE to public datasets revealed that pre-existing Alu copies create two hotspots for Alu and LINE1 insertions: the A-rich linker and the poly(A) tail. We further observed a preference for self-insertions over non-self-insertions in Alu and LINE1, suggesting a "feedforward" transposition mechanism in which Alu and LINE1 RNA transcripts target the hotspots of their source copies to generate new insertions. LOCATE enhances our ability to study transposons and their role in genome dynamics.

bioinformatics↗

bioRxiv2025

Construction and characterization of coronavirus nonstructural protein 3-host protein interaction networks unravel an important role of cleavage and polyadenylation specificity factor 6 in regulation of viral RNA replication

Coronavirus nonstructural protein 3 (nsp3) plays a crucial role in viral replication and immune evasion. However, functional and proteomic characterization of this protein, especially the interaction networks between nsp3 from different coronaviruses and host cell factors, is hindered by its huge size, complex structural feature and the presence of multiple transmembrane domains. In this study, we report the application of a high-performance cytoplasmic expression system to efficiently and accurately express the full-length nsp3 from betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and gammacoronavirus infectious bronchitis virus (IBV), to investigate their interactions with host proteins using proteomics approaches. Our study identified 1,150 host proteins that interact with IBV nsp3 and 920 with SARS-CoV-2 nsp3. Among them, 658 are shared by the two nsp3 proteins. Further validation and preliminary characterization of seven selected candidates, DDX5, DDX39, DHX9, elF4A3, SRRT and CPSF6, demonstrated the reproducibility and reliability of the proteomics data. More interestingly, an important regulatory role of the nsp3-CPSF6 interaction in the replication and transcription of IBV gRNA and sgRNA was unraveled. The construction of nsp3-host protein interaction networks from two distantly related coronaviruses would have provided a foundation for future studies of host cell factors in the regulation of coronavirus replication and pathogenesis.

microbiology↗

bioRxiv2025

Deciphering population-level response under spatial drug heterogeneity on microhabitat structures

Bacteria and cancer cells inhabit spatially heterogeneous environments, where migration shapes microhabitat structures critical for colonization and metastasis. The interplay between growth, migration, and spatial structure complicates the prediction of population responses to drug treatment--such as clearance or persistence--even under the same spatially averaged growth rate. Accurately predicting these responses is essential for designing effective treatment strategies. Here, we propose a minimal growth-migration model to study population dynamics on discrete microhabitat structures under spatial drug heterogeneity. By applying a kernel transformation, we map the original structure to an effective fully connected graph and derive a new exact criterion for population response based on a regularized Laplacian kernel reweighted by local growth rates. This criterion connects to forest closeness centrality and yields analytical bounds and sufficient conditions for population growth or decline. We find that higher structural connectivity--like increased migration--generally promotes decline. Our framework also informs optimal spatial drug assignments, which reduce to selecting interconnected subcores in the effective complete graph. For partially controllable microhabitats or unknown drug distributions, we identify strategies that ensure population decline. Overall, our results offer a new theoretical perspective on drug response in spatially structured populations and provide practical guidance for optimizing spatially explicit dosing strategies in heterogeneous environments.

biophysics↗

bioRxiv2025

Evaluating the toxicity of methanol, formaldehyde and formate on the growth fitness of Yarrowia lipolytica

Liquid C1 feedstock, including methanol, formaldehyde and formic acid can be easily manufactured from greenhouse gases CO2 and CH4. Yarrowia lipolytica, isolated from marine ecosystem, is a non-conventional yeast which is capable of assimilating multiple range of hydrophobic compounds including alcohols, lipids, hydrocarbons, and volatile fatty acids et al. This yeast has been extensively engineered to produce lipids, carotenoids, squalene and other natural products. Herein we tested the growth fitness of Y. lipolytica when exposed to various one-carbon (C1) liquid feedstocks (methanol, formaldehyde, and formic acid). We firstly captured the cell growth kinetics with an automatic Cell Growth Analyzer and fitted the data with a Monod-type growth model. We obtained the inhibition constants of the three liquid C1s from the growth fitness dose-response curves. We found that the lagging phase duration is exponentially correlated with the toxicity of the tested C1 solvents. Notably, Y. lipolytica exhibited tolerance to methanol (IC50 871 mM) and formic acid (IC50 42.6 mM), but showed sensitivity to formaldehyde (IC50 3.8 mM). We next chose fromate as the co-substrate to cultivate Y. lipolytica, confirmed that Y. lipolytica can upcycle formic acid to improve lipid yields and biomass in fed-batch culture. This work broadens Y. lipolyticas substrate scope and facilitates sustainable and cost-efficient production of fuels and chemicals.

synthetic biology↗

bioRxiv2025

A wireless, 60-channel, AI-enabled neurostimulation platform

ObjectiveClosed-loop neuromodulatory therapies require devices that can both decode ongoing brain states and deliver multi-site stimulation. MethodsWe describe the Smart Neurostimulation System (SNS), a cranially mounted implant with 60 configurable recording/stimulation channels, inductive power, and onboard spectral-feature classification. In three freely-moving sheep we streamed local-field potentials and conducted two parameter sweep experiments. ResultsCross-validated movement classifiers achieved an average AUC > 0.95. Increasing stimulation amplitude and frequency produced post-stimulation elevations in -band (8-12 Hz) and{gamma} -band (78-82 Hz) power at most target locations. ConclusionThe SNS unifies high-density sensing, real-time brain state decoding, and programmable closed-loop stimulation in a single device, demonstrating behavioral-state prediction and parameter-dependent neuromodulation in vivo. SignificanceThese findings establish a preclinical foundation for biomarker-guided stimulation targeting distributed cortical networks underlying memory and cognition. HighlightsO_LIWireless 60-channel implant enables simultaneous sensing and stimulation C_LIO_LIvine study demonstrates reliable classification of movement and stimulation-related modulation of spectral activity C_LIO_LIThe SNS represents a platform for biomarker-guided neuromodulation therapies C_LI

neuroscience↗

bioRxiv2025

Gut meta-virome reveals potential zoonotic pathogens and environmental RNA viruses carried by non-human primates

The majority of human infectious diseases originate from mammals and are inherently zoonotic. Non-human primates (NHPs) are not only carriers of many zoonotic pathogens, but also the best intermediary for virus shift from harmless to harmful due to their similar phylogenetic relationship with humans. Knowledge of NHP viral composition and its underlying information can therefore provide an assessment of the risk of cross-species transmission and spillover of zoonotic diseases. However, studies that have successfully eliminated the effects of different natural habitat environments on viral carriage have been limited, making it difficult to identify which zoonotic viruses and potentially species-barrier-crossing viruses are carried by widely distributed NHP hosts. Here, we analyze viruses excreted in feces from NHP hosts and reveal the presence of possible zoonotic pathogens. Most of the viruses found come from plants that are eaten by them. Analysis of the evolutionary relationships of potential pathogens suggests that other clinical isolates are genetically correlated to HIV, PBV, and EV we identified. This study provides foundational data for surveillance of NHP enteroviruses that could help to be challenging to track potential human viruses carried by NHP in the absence of clinical surveillance. ImportanceAs a result of internationalization and other factors, many viruses have broken through the limits of geographical units and spread into human society, causing many emerging and re-emerging infectious disease hazards. However, the virus spreads and is by no means infectious to humans overnight. There is a phenomenon of host shift, in which the virus does not necessarily cause disease in an intermediate host, but causes significant damage when transmitted to humans. We focus on captive non-human primates, close relatives of humans in cities, because the phenomenon of host shifts is related to both biological similarity and geographical proximity of the host. Primates may carry zoonotic viruses and viruses that are currently incapable of infecting humans but have evolved with pathogenic potential. In summary, comprehensive viral surveillance and screening of captive nonhuman primates is necessary.

ecology↗

bioRxiv2024

GP-ML-DC: An Ensemble Machine Learning-Based Genomic Prediction Approach with Automated Two-Phase Dimensionality Reduction via Divide-and-Conquer Techniques

Traditional machine learning (ML) and deep learning (DL) methods for genome prediction often face challenges due to the imbalance between the limited number of samples (n) and the large number of single nucleotide polymorphisms (SNPs) (p), where n is much smaller than p. To address this, we propose GP-ML-DC, an innovative genome predictor that combines traditional ML and DL models with a unique two-phase, parameter-free dimensionality reduction technique. Initially, GP-ML-DC reduces feature dimensionality by characterizing genes as features. Building on big data methodologies, it employs a divide-and-conquer approach to segment gene regions into multiple haplotypes, further decreasing dimensionality. Each haplotype segment is processed by a sub-task based on traditional ML, followed by integration via a neural network that synthesizes the results of all sub-tasks. Our experiments, conducted on four cattle milk-related traits using ten-fold cross-validation and independent testing, show that GP-ML-DC significantly surpasses current state-of-the-art genome predictors in prediction performance.

bioinformatics↗

bioRxiv2024

Base-modified nucleotides mediate immune signaling in bacteria

Signaling from pathogen sensing to effector activation is a fundamental principle of cellular immunity. While cyclic (oligo)nucleotides have emerged as key signaling molecules, the existence of other messengers remains largely unexplored. Here, we reveal a bacterial anti-phage system that mediates immune signaling through nucleobase modification. Immunity is triggered by phage nucleotide kinases, which, combined with the system-encoded adenosine deaminase, produce deoxyinosine 5-triphosphate (dITP) as immune messengers. The dITP signal activates downstream effector to mediate cellular NAD+ depletion, resulting in population-level defense through the death of infected cells. To counteract immune signaling, phages deploy specialized enzymes that deplete cellular dAMP, the precursor of dITP messengers. Our findings uncover a nucleobase modification-based anti-phage signaling pathway, establishing noncanonical nucleotides as a new type of immune messengers in bacteria.

microbiology↗

bioRxiv2024

Injured endocardium obtains characteristics of haemogenic endothelium during adult zebrafish heart regeneration

Reactivation of embryonic developmental pathways during regeneration aims to restore tissue architecture and functionality. We previously reported that following cryoinjury, a heterogeneous population of Runx1-expressing endocardial cells differentially upregulates genes associate with scarring and myofibroblast identity. Further analysis of our published RNAseq data alongside 5 publicly available datasets now identifies additional heterogeneity in the Runx1-positive injured endocardium. Here, we show that the endocardium also reactivates a dormant endocardial-to-haematopoietic transition (EHT) mechanism. Runx1-expressing endocardial cells upregulate genes associated with haemogenesis and morphologically display features of EHT. Live imaging shows cells budding off the endocardium and lineage analysis identifies overlap with leukocyte markers. Ablation of runx1 function further shifts differentiation of the endocardium towards the EHT fate. The identification of transient runx1-expressing cells transitioning towards myofibroblast or haemogenic endocardium identities demonstrates the complexity of the zebrafish endocardial injury response and highlights the role of Runx1 in regulating cell fate decisions in the endocardium.

developmental biology↗

bioRxiv2024

Spatial drug asymmetry modulates phenotypic diversity-migration relationships under resistance evolution

At long timescales, resistant phenotypes will emerge and be selected within the bacterial population as an evolutionary response to drug exposure. This phenomenon reduces the efficacy of drug therapies and thus compromises patient health. In spatially heterogeneous drug environments, recent evidence shows that migration can either promote or decelerate the evolution of antibiotic resistance, thereby affecting the rate of resistant phenotype emergence. However, another important quantitative aspect of resistance evolution--bacterial phenotypic diversity--has often been overlooked and remains challenging to investigate in spatially extended systems, both experimentally and clinically. In order to study how diversity is reshaped by migration across space, here we designed a minimal 2-well experimental system with spatial drug asymmetry. One well contained a bacteriostatic drug (Linezolid) at the minimum inhibitory concentration, while the other well served as a sanctuary with just media. We found that the relationship between diversity and migration follows the "Intermediate Disturbance Hypothesis" (IDH), with migration as the disturbance to each well. By varying the selective drug concentrations, we observed that the diversity-migration relationship changes, and IDH can disappear. This behavior was explained by an asymmetry parameter derived from a two-phenotype growth-migration dynamic model. To further validate how different spatial drug asymmetries modulate the diversity-migration relationship through this asymmetry parameter, we applied another bactericidal drug, Ampicillin, and observed similar results. In a more complex scenario involving both Linezolid and Ampicillin, four distinct phenotypes, including cross-resistant variants, emerged. Our asymmetry parameter successfully explained the diversity-migration relationship, with unique diversity dynamics such as multiple peaks appearing from the model. The minimal generalist-specialist framework predicted these unique behaviors through global fitness advantages. Our findings provide experimental support and theoretical explanations for the emergence of phenotypic diversity in clinical settings, such as gut-lung translocation. These insights may pave the way for improved clinical strategies to manage antibiotic resistance evolution.

evolutionary biology↗

bioRxiv2024

Mapping Global Causal Responses to Noninvasive Modulation of Genetically and Spatially Targeted Neural Populations with Sonogenetic-fPET

Despite significant progress in brain circuit mapping over recent decades, a major challenge remains: no method currently allows for the noninvasive modulation of genetically and spatially defined neural populations while simultaneously monitoring their global effects throughout the brain and body. Here, we present sonogenetic-fPET, a technique that integrates sonogenetics with [18F]-2-fluoro-2-deoxy-D-glucose functional positron emission tomography (FDG-fPET) to overcome this challenge. Sonogenetics enables noninvasive, spatially targeted modulation of neurons genetically engineered to express the ultrasound-sensitive ion channel TRPV1, while FDG-fPET captures glucose metabolic changes triggered by this stimulation across the brain and body. We demonstrate the effectiveness of this technique by targeting neurons in the dorsal striatum, showcasing its capability to map global network responses to specific neuronal activation. Incorporating an acoustic hologram for sonogenetics further enables flexible modulation of different brain regions within a single mouse while concurrently mapping the resulting network activity. In summary, sonogenetic-fPET offers a tool for dissecting the global responses of the brain and body to the noninvasive modulation of genetically and spatially defined neuronal populations.

neuroscience↗

bioRxiv2024

RegVelo: gene-regulatory-informed dynamics of single cells

RNA velocity has emerged as a popular approach for modeling cellular change along the phenotypic landscape but routinely omits regulatory interactions between genes. Conversely, methods that infer gene regulatory networks (GRNs) do not consider the dynamically changing nature of biological systems. To integrate these two currently disconnected fields, we present RegVelo, an end-to-end dynamic, interpretable, and actionable deep learning model that learns a joint model of splicing kinetics and gene regulatory relationships and allows us to perform in silico perturbation predictions. When applied to datasets of the cell cycle, human hematopoiesis, and murine pancreatic endocrinogenesis, RegVelo demonstrates superior predictive power for interactions and perturbation simulations, for example, compared to methods that focus solely on dynamics or GRN inference. To leverage RegVelos full potential, we studied the dynamics of zebrafish neural crest development and underlying regulatory mechanisms using our Smart-seq3 dataset and shared gene expression and chromatin accessibility measurements. Using RegVelos in silico perturbation predictions, validated by CRISPR/Cas9-mediated knockout and single-cell Perturb-seq, we establish transcription factor tfec as an early driver and elf1 as a novel regulator of pigment cell fate and propose a gene-regulatory circuit involving tfec and elf1 interactions via the toggle-switch model.

developmental biology↗

bioRxiv2024

The Cardioprotective Effect of Ischemic Postconditioning is Mediated by Inhibiting RAP2C-MAP4K4 Pathway

BackgroundIschemic postconditioning (PostC) serves as a vital defense for cardiomyocytes against the deleterious effects of ischemia/reperfusion (I/R) injury, the beneficial effects could be further enhanced through pharmacological strategies. Our prior research demonstrated upregulated expression of the GTP-binding protein RAP2C in H9C2 cells post hypoxia-reoxygenation (H/R). The cardioprotective effects of RAP2C and underlying mechanisms are unclear. We therefore explored the role of RAP2C in PostC-induced cardioprotection against I/R injury. MethodsOpen-chest rat I/R and primary cultured cardiomyocytes H/R models were used. RAP2C and MAP4K4 expression was detected by immunohistochemistry and Western blotting. The BioGRID and STRING databases were tapped to predict the RAP2C-MAP4K4 binding, which was confirmed by co-immunoprecipitation and immunofluorescence. ResultsResults indicated that I/R and H/R upregulated the protein levels of RAP2C, MAP4K4, phospho-JNK, phospho-P38, and phospho-ERK, concomitant with increased apoptosis. PostC mitigated these effects. The pro-apoptotic impacts and the activation of the MAPK pathway induced by H/R were attenuated by RAP2C knockdown and intensified by RAP2C overexpression. H/R increased the interaction between RAP2C and MAP4K4, and PostC attenuated this effect. MAP4K4 knockdown reduced the pro-apoptotic and MAPK-activating effects induced by both RAP2C overexpression and hypoxia/reoxygenation (H/R). ConclusionsThese results demonstrate that PostC reduces cardiomyocyte apoptosis via modulating RAP2C/MAP4K4 pathways, suggesting their potential as therapeutic targets for the treatment of ischemic heart disease.

cell biology↗

bioRxiv2024

From Micro to Macro: Avian Chromosome Evolution is Dominated by Natural Selection

Birds display striking variation in chromosome number, defying the traditional view of highly conserved avian karyotypes. However, the evolutionary drivers of this variability remain unclear. To address this, we fit probabilistic models of chromosome number evolution across birds, enabling us to estimate rates of evolution for total chromosome number and the number of microchromosomes and macrochromosomes while simultaneously accounting for the impact of other evolving traits. Our analyses revealed higher rates of chromosome fusion than fission across all bird lineages. Notably, much of this signal was driven by Passeriformes, where migratory species showed a particularly strong bias towards fusions compared to sedentary counterparts. Furthermore, a robust correlation between the rearrangement rates of microchromosomes and macrochromosomes suggests that genome-wide processes drive rates of structural evolution. Additionally, we found that lineages with larger population sizes exhibited higher rates of both fusion and fission, indicating that positive selection plays a dominant role in driving divergence in chromosome number. Our findings illuminate the evolutionary dynamics of avian karyotypes and highlight that, while the fitness effects of random structural mutations are often deleterious, beneficial mutations may dominate karyotype divergence in some clades.

evolutionary biology↗

bioRxiv2024

NaDyNet: A Toolbox for Dynamic Network Analysis of Naturalistic Stimuli

Experiments with naturalistic stimuli (e.g., listening to stories or watching movies) are emerging paradigms in brain function research. The content of naturalistic stimuli is rich and continuous. The fMRI signals of naturalistic stimuli are complex and include different components. A major challenge is isolate the stimuli-induced signals while simultaneously tracking the brains responses to these stimuli in real-time. To this end, we have developed a user-friendly graphical interface toolbox called NaDyNet (Naturalistic Dynamic Network Toolbox), which integrates existing dynamic brain network analysis methods and their enhanced versions. The main features of NaDyNet are: 1) extracting signals of interest from naturalistic fMRI signals; 2) incorporating six commonly used dynamic analysis methods and three static analysis methods; 3) enhanced versions of these dynamic methods by adopting inter-subject analysis to eliminate the effects of non-interest signals; 4) performing K-means clustering analysis to identify temporally reoccurring states along with their temporal and spatial attributes. We then introduced the rationale for incorporating inter-subject analysis to improve existing dynamic brain network analysis methods, and presented numerous examples. We also summarized research progress in comparing methodological efficacy, offered our recommendations for method selection in dynamic network analysis, and discussed the limitations of current approaches and directions for future research. We hope that this open source toolbox will promote the development of naturalistic neuroscience. The toolbox is available at https://github.com/yuanbinke/Naturalistic-Dynamic-Network-Toolbox.

neuroscience↗

bioRxiv2024

Bacterial lipoate protein ligases rescue lipoylation and respiration deficiency in mammals

Human lipoylation pathway deficiencies caused by LIPT2/LIAS/LIPT1 gene mutations lead to inherited metabolic disorders characterized by severe defects of mitochondrial energy and amino acids metabolism. Patients with such mutations suffer from hyperlactic acidemia, encephalopathy, hypotonia and early death. So far there is no effective treatment. Here we introduced the bacteria salvage lipoylation pathway, which is absent in eukaryotes, into lipoylation defective human cells and mouse models. Both E. coli-derived LplA and B. subtilis-derived LplJ restored the phenotypes of LIPT2/LIAS/LIPT1 gene knockout cells to those of wildtype cells with lipoic acid supplementation. Biochemical and isotope tracing analysis demonstrated LplA and LplJ function through direct lipoylation of the H protein of glycine cleavage system and the E2 subunits of 2-oxoacid dehydrogenases, thereby reactivating the short-circuited TCA cycle and amino acids metabolism. This strategy is further extended to treat lipoyl precursor supply defects caused by MECR and FDX1 mutations and its efficacy and safety are validated in Lipt1-/- and LplAOE/+ mouse models. This study provides systematic characterization of lipoylation deficiency and paves the way to gene therapy for treatment of lipoylation-deficient patients.

cell biology↗

bioRxiv2024

Linking spatial drug heterogeneity to microbial growthdynamics in theory and experiment

Diffusion and migration play pivotal roles in microbial communities - shaping, for example, colonization in new environments and the maintenance of spatial structures of biodiversity. While previous research has extensively studied free diffusion, such as range expansion, there remains a gap in understanding the effects of biologically or physically deleterious confined environments. In this study, we examine the interplay between migration and spatial drug heterogeneity within an experimental meta-community of E. faecalis, a Gram-positive opportunistic pathogen. When the community is confined to spatially-extended habitats ( islands) bordered by deleterious conditions, we find that the population level response depends on the trade-off between the growth rate within the island and the rate of transfer into regions with harsher conditions, a phenomenon we explore by modulating antibiotic concentration within the island. In heterogeneous islands, composed of spatially patterned patches that support varying levels of growth, the populations fate depends critically on the specific spatial arrangement of these patches - the same spatially averaged growth rate leads to diverging responses. These results are qualitatively captured by simple simulations, and analytical expressions which we derive using first-order perturbation approximations to reaction-diffusion models with explicit spatial dependence. Among all possible spatial arrangements, our theoretical and experimental findings reveal that the arrangement with the highest growth rates at the center most effectively mitigates population decline, while the arrangement with the lowest growth rates at the center is the least effective. Extending this approach to more complex experimental communities with varied spatial structures, such as a ring-structured community, further validates the impact of spatial drug arrangement. Our findings suggest new approaches to interpreting diverging clinical outcomes when applying identical drug doses and inform the possible optimization of spatially-explicit dosing strategies. Author summaryIn this study, we develop an automated platform to experimentally investigate short-term population growth and migration dynamics under spatial drug heterogeneity. Our findings reveal that the collective spatial response of the population can vary significantly, even with the same migration rate and averaged drug dose, due to different spatial drug arrangements. By constructing a simple reaction-diffusion model, we observed that simulated short-term spatial growth rate closely matches the experimental data. Furthermore, this short-term spatial growth rate aligns well with the long-term spatial growth rate, defined by the largest eigenvalue, as the spatial system quickly enters the equilibrium growth state. Using concepts from perturbation theory, we derived an analytical relationship between the boundary diffusion effect, homogeneous growth effect, and heterogeneous effect. Our results highlight that in spatially-extended habitats, the spatial growth response is an emergent property. The bacterial population quickly enters equilibrium growth, suggesting that the spatial growth rate measured at an ecological scale may be used to predict resistance evolutionary behavior.

biophysics↗