Biology subjects

Wan, B.

Publications and source records attributed to Wan, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Cortical Hierarchy Dynamically Organizes Large-Scale Neural Propagation

Flexible behaviour depends on the continuous coordination of sensory-driven and internally guided processing, yet whether the cortical hierarchy spanning lower-order sensory to higher-order association systems dynamically organizes large-scale cortical propagation over time remains unclear. Here we combined source-resolved magnetoencephalography with Riemannian cortical-flow modelling to derive hierarchy consistency, a moment-to-moment measure of the alignment between cortical propagation and the principal sensory-to-association functional gradient. We found that large-scale cortical propagation was dynamically organized by the cortical hierarchy. Hierarchy consistency exhibited a reproducible low-frequency periodic component that defined a characteristic timescale for the continuous updating of propagation direction. This dynamic organization was coordinated by a distributed cortical switchboard spanning the default-mode, salience, control and limbic systems, and was constrained by structural connectivity and network-control architecture. It flexibly adapted to behavioural demands, with hierarchy consistency increasing across both sensorimotor and working-memory states, while its characteristic periodicity shifted in a task-dependent manner. Moreover, hierarchy-related propagation dynamics were systematically reorganized across ageing and associated with higher-order cognitive function. Together, these findings establish the cortical hierarchy as a dynamic organizing principle that continuously shapes the direction and temporal evolution of large-scale cortical propagation to support adaptive behaviour.

neuroscience↗

bioRxiv2026

Selective convergence and graded divergence of hippocampal and amygdala subregions using functional connectivity

The hippocampus and amygdala are neighboring medial temporal lobe structures linked to memory and affect, yet how their subregions are jointly embedded within distributed isocortical systems remains unclear. Using resting-state fMRI from 722 Human Connectome Project Young Adult participants, we mapped hippocampal and amygdalar subregions within a unified cortex-wide framework, quantifying subregion-to-cortex connectivity via Pearson correlation (broad co-fluctuation) and GLASSO partial correlation (relatively more direct functional association). We introduced two count-based metrics: dominance (relative hippocampal vs. amygdalar representation) and sharedness (balanced co-representation). Direct associations showed both structures sharing coupling with paralimbic areas and, more modestly, default mode regions, while broader co-fluctuations extended into somatomotor and paralimbic networks. Divergence patterns depended on the estimator: hippocampal subregions preferentially coupled with default-mode and visual networks under direct association, while amygdalar nuclei favored ventral attention and limbic networks; broader co-fluctuations additionally implicated somatomotor cortex for amygdala and visual cortex for hippocampus. These principles held at the subfield/nucleus level, varying along the hippocampal long axis and identifying the paralaminar nucleus as the most hippocampus-like amygdalar subregion. Data-driven connectivity gradients confirmed both systems separation and fine-scale interdigitation. Hippocampal and amygdalar subregions are thus embedded in cortex not as discrete systems, but through structured, spatially organized co-representation.

neuroscience↗

bioRxiv2026

Nucleus-level thalamic organization anchors multimodal signatures of thalamocortical maturation

The human thalamus is composed of multiple nuclei that differ in structure and function. From early development onwards, these nuclei form reciprocal, nucleus-specific connections with the cerebral cortex, contributing to sensory and cognitive processing. In childhood and adolescence, a key period of neurocognitive development, these connections undergo widespread refinement, yet how developmental trajectories of thalamocortical connections vary across nuclei remains unknown. Here, we leveraged the Human Connectome Project in Development dataset (HCP-D, N = 604, age range 8-21) and segmented 10 thalamic nuclei using a segmentation approach optimized for intrathalamic contrast. Applying probabilistic tractography, we reconstructed nucleus-specific thalamocortical connections and charted their maturational profiles based on changes in fractional anisotropy (FA) using generalized additive models. We found FA to increase in thalamocortical connections, with nucleus-specific variation in temporal profiles and magnitude of age effects. Connections of core-cell-rich, sensory-projecting nuclei, such as the lateral geniculate nucleus, showed earlier maturational plateaus, whereas matrix-cell-rich, association-projecting nuclei, such as ventral anterior nucleus, showed more sustained maturation. This links maturational heterochronicity to thalamic organization of cell distribution and connectivity embedding. In parallel, functional thalamocortical connectivity decreased with age, with FA and functional connectivity age effects coupled in nucleus-connections showing prolonged maturation. Finally, concordant age effects in connectivity and nucleus volumes suggest that intra-nucleus remodeling may support refinement of structural connections while reducing thalamocortical functional synchrony. Together, our work reveals that thalamocortical maturation is anchored in the developmental and organizational heterogeneity of thalamic nuclei, offering a framework for understanding how diverse thalamic nuclei contribute to neurocognitive development.

neuroscience↗

bioRxiv2026

Sex-related structural alterations across common epilepsies: a worldwide ENIGMA study

Epilepsy is characterized by widespread structural brain alterations extending beyond the epileptic zone, involving both cortical and subcortical regions. Importantly, the clinical manifestation of epilepsy, including seizure types, psychiatric comorbidities, and treatment responses, has been shown to differ between sexes. However, sex differences in structural alterations in epilepsy have been seldomly reported in neuroimaging studies, partly due to limited sample sizes and single-center designs. Here, we systematically investigated sex differences in common epilepsies and their related clinical variables using structural neuroimaging biomarkers in an international multi-center cohort of 1,253 epilepsy patients and 1,077 healthy controls. We studied cortical thickness and subcortical volume in two types of epilepsy: temporal lobe epilepsy (TLE) and genetic generalized epilepsy (GGE). Both male and female patients with TLE showed widespread cortical and subcortical thinning compared with controls. In GGE, when compared separately to controls, male patients showed only subtle structural alterations, whereas female patients exhibited more widespread structural alterations. Sex-stratified analyses revealed some variation in the extent and distribution of cortical thickness and subcortical volume alterations between male and female patients in both epilepsy cohorts. Yet, we did not find significant sex-by-diagnosis interaction effects in TLE and GGE. Similarly, no significant interaction effects were observed between sex and age of onset or disease duration in either patient group. Overall, although we observed some differences in regional cortical thickness and subcortical volume between male and female patients with epilepsy, we did not find significant sex-by-diagnosis interactions. Our findings indicate that sex differences in behavioral and clinical outcomes of epilepsy may involve biological or functional processes that require further investigation.

neuroscience↗

bioRxiv2026

Structural brain networks shape individual-level progression of brain atrophy after stroke

Stroke starts as a focal vascular lesion, but its structural consequences often extend beyond the lesion site, resulting in distributed brain atrophy whose organizing principles remain unclear. Here, using longitudinal MRI data from two stroke cohorts spanning the hyperacute to chronic stages, we tested whether and how post-stroke grey matter volume (GMV) change over time is constrained by large-scale brain networks across individuals. Coordinated deformation modelling showed that longitudinal GMV atrophy patterns were more strongly shaped by structural than by functional connectivity, with structural constraints already detectable in the acute phase. Network diffusion modelling further showed that atrophy patterns at 3 and 12 months were consistent with lesion-initiated propagation on the structural connectome, whereas model performance was weak in the early acute stage. The model-derived propagation stage did not increase monotonically with chronological time, indicating that it reflects the degree to which observed atrophy conforms to a network-consistent diffusion-like pattern rather than elapsed biological time. Inter-individual variation in propagation stage was associated with lesion size and with the topological and molecular properties of lesioned regions. Finally, lesion information combined with network diffusion modelling supported individualized prediction of later GMV atrophy patterns. These findings provide a network-based account of secondary degeneration after stroke and may inform individualized characterization of post-stroke structural reorganization.

neuroscience↗

bioRxiv2026

Separable Brain Maturation Patterns Mediate Exposome Influences on Cognitive Development: A Longitudinal Study

Adolescent cognitive ability develops within a complex landscape of environmental exposures, yet the patterns of brain maturation through which these exposures relate to cognitive development remain poorly understood. Resolving this requires an integrated longitudinal view of the multidimensional exposome, multimodal brain change, and cognitive growth. Here, we examined whether brain maturation mediates the relationship between the exposome and cognitive development in a large longitudinal cohort of 1,112 adolescents, using 4,882 multimodal brain features and 112 exposome variables spanning six domains. Brain maturation patterns associated with cognitive development showed moderate yet consistent spatial correspondence with those associated with the exposome, with the family environment domain showing the strongest correspondence. We identified four latent brain patterns associated with distinct components of the exposome-cognition relationship. Collectively, these results indicate that distinct exposome domains relate to cognitive development through distinct brain maturation pathways, which also exhibit different molecular annotation profiles.

neuroscience↗

bioRxiv2026

Human Cerebral Cortex Organization Characterized by Functional PET-FDG "Metabolic Connectivity"

PurposeIn this study, we characterize the spatiotemporal organization of resting-state metabolic connectivity (RSMC) in the human brain, as measured by [18F]- fluorodeoxyglucose (FDG) functional PET (fPET-FDG). We examine the relationship between RSMC organization and resting-state functional connectivity (RSFC) derived from functional magnetic resonance imaging and other known cortical organizational principles. MethodsResting-state fPET-FDG data from 24 individuals were obtained from a publicly available repository. We characterized local metabolic organization using connectivity-based boundary mapping, with adaptations to account for the low signal-to-noise ratio of fPET-FDG data. We then estimated global metabolic organization through community detection-based network and principal gradient analyses. Furthermore, we examined how metabolic connectivity is shaped by temporal-frequency-specific components of fPET-FDG signal. Finally, we contextualized metabolic organization by relating metabolic gradients to anatomical, functional, and energetic reference measures. ResultsAt the local scale, boundary mapping results indicated structured transitions shaped by a combination of both fast and slow fPET-FDG signals, partly overlapping with RSFC boundary maps. Globally, RSMC analyses revealed a robust metabolic structure organized along a superior-inferior cortical gradient. This pattern remained consistent across network community detection and principal gradient analyses and was primarily driven by low-frequency, minute-scale fPET-FDG dynamics. The identified large-scale metabolic profile aligns closely with several known anatomical and energetic constraints. ConclusionThis study characterizes the spatiotemporal organizational principles of RSMC, deepening insight into the brains energetic framework and providing a basis for future cognitive and clinical investigations of metabolic connectivity organization.

neuroscience↗

bioRxiv2025

Transcriptomic Profiling Reveals Key Molecular Events and Pathways Driving Acquired Chemotherapy Resistance in Relapsed Acute Myeloid Leukemia

BackgroundAcute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy. Although induction therapy induces remission in many patients, relapse and acquired chemoresistance remain the major causes of treatment failure. Defining the molecular mechanisms underlying relapse is essential for improving therapeutic strategies. MethodsBone marrow samples from nine AML patients were analyzed, including five newly diagnosed cases and four relapsed cases after chemotherapy. Transcriptome sequencing and integrative bioinformatics analyses were performed, including differential expression analysis, GO/KEGG enrichment, GSEA, and protein-protein interaction (PPI) network analysis, to delineate relapse-associated molecular alterations. ResultsPrincipal component analysis demonstrated clear transcriptional segregation between primary and relapsed AML, indicating extensive molecular reprogramming during relapse. A total of 2,025 differentially expressed genes were identified, enriched in pathways related to epithelial-mesenchymal transition-like programs, leukemia stem cell maintenance, apoptosis evasion, and bone marrow microenvironment remodeling. Marked upregulation of FOXC1, HOXA11/HOXA11-AS, and AXL suggests key roles in sustaining stemness and promoting drug resistance. GO/KEGG analysis revealed coordinated activation of small GTPase, Rho/Ras signaling, ion transport, and epigenetic regulatory pathways, reflecting multilayered adaptive responses. GSEA indicated metabolic-epigenetic reprogramming in relapsed AML, while primary AML showed enrichment of energy metabolism and chromatin assembly pathways. PPI network analysis highlighted a central inflammation-metabolism axis involving TP53, IL6, CXCL8, and CCL2, associated with apoptosis resistance and metabolic adaptation. ConclusionsRelapsed AML is characterized by transcriptional reprogramming, metabolic remodeling, and microenvironment-driven adaptive resistance. Targeting small GTPase signaling, AXL, or IL6-related inflammatory pathways, alone or combined with epigenetic modulators, may offer promising therapeutic strategies to overcome chemoresistance in AML.

cell biology↗

bioRxiv2025

Modeling Individualized Adolescent Mental Health through a Multifactorial Causal Framework to Identify Potential Intervention Strategies

Associations between psychopathology, cognition, and personality are well established. However, these associations unfold within a broader developmental context shaped by brain maturation, environmental exposures and pubertal transitions, whose influences remain poorly understood. Here, we characterized how cognition and personality relate to adolescent mental health within this developmental context. Using data from the Adolescent Brain Cognitive Development Study (N = 4501), we simultaneously modeled 16610 brain structural, environmental, and pubertal measures to examine 165 behavioral pairs comprising cognitive and personality traits with mental health symptoms. Using an integrated analytic pipeline combining multifactorial mediation and longitudinal interaction-inclusive models, we evaluated whether developmental changes in cognition and personality relate to mental health at the individual level, and whether these associations vary across brain, environmental, and pubertal profiles. Most behavioral pairs showing significant mediation effects likewise exhibited significant longitudinal effects. These pairs were primarily influenced by neurobiological and environmental measures; cortical frontal and temporal regions relevant for cognitive control and emotional regulation as well as family and lifestyle contexts were most prominently implicated. Finally, after accounting for inter-individual heterogeneity, personality traits emerged as the main behavior associated with mental health. These findings characterize developmental associations linking cognition and personality with adolescent mental health, and show that these associations vary across brain, environmental, and pubertal profiles. The study advances understanding of behavioral development and provides a framework for identifying targets for psychopathology prevention.

neuroscience↗

bioRxiv2025

cuBNM: GPU-Accelerated Brain Network Modeling

Brain network modeling uses computer simulations to infer about latent neural properties at micro- and mesoscales by fitting brain dynamic models to empirical data of individual subjects or groups. However, computational costs of (individualized) model fitting is a major bottleneck, limiting the practical feasibility of this approach to larger cohorts and more complex models, and highlighting the need for scalable simulation implementations. Here, we introduce cuBNM, a Python package which leverages parallel processing of graphics processing units to massively accelerate simulations of brain network models. We show running simulations on graphics processing units is several hundred times faster compared to central processing units. We demonstrate the usage of cuBNM by running optimization of group-level and individualized low- and high-dimensional models. As examples of the utility of individualized models, we investigated test-retest reliability and heritability of simulated and empirical measures in the Human Connectome Project dataset. We found simulated features were fairly reliable and significantly heritable, suggesting their biological plausibility. Overall, cuBNM enables large-scale simulations of brain network models, opening new avenues for studying latent neural processes across diverse populations, dense networks, and high-dimensional models, which was previously impractical due to computational constraints.

neuroscience↗

bioRxiv2025

Neurodevelopmental Impact of Bipolar Disorder Genetic Risk on Cortical Thickness and Network Topology in Adolescents

Bipolar disorder (BD) is a highly heritable psychiatric condition characterized by recurrent mood episodes that commonly manifest during adolescence. Although polygenic risk scores (PRS) effectively quantify genetic susceptibility to BD, the neurobiological correlates of this genetic risk during adolescent brain development remain unclear. Using normative modeling and longitudinal neuroimaging data from the Adolescent Brain Cognitive Development (ABCD) cohort (N = 4519), we examined cortical thickness (CT) deviations and structural covariance network (SCN) alterations in adolescents stratified into high and low BD genetic risk groups based on PRS. Adolescents with high PRS for bipolar disorder exhibited greater cortical thickening in the inferior frontal gyrus and primary visual cortex, whereas those with low PRS demonstrated greater thickening in the posterior cingulate cortex and middle precentral gyrus. These patterns suggest PRS-related variations in cortical maturation, potentially reflecting distinct neurodevelopmental trajectories associated with genetic susceptibility to bipolar disorder. Furthermore, high PRS individuals displayed altered SCN topology, characterized by decreased local clustering and enhanced global network efficiency. Longitudinal data show that these abnormal regions exhibit atypical developmental trajectories, accompanied by a global reorganization of network topology. Additionally, high genetic risk was associated with lifestyle factors, especially correlated with increased positive expectancies toward substance use. Eventually, we found three potential BD risk genes during adolescence, including PLEKHA2, ZSCAN31 and ANK3, encoding the function of the postsynaptic membrane and synaptic membrane. These findings elucidate early neurodevelopmental deviations linked to genetic risk for BD, highlighting potential biomarkers for early identification and targeted interventions.

neuroscience↗

bioRxiv2025

Multimodal cortical connectome in the default mode network across the adult lifespan

The default mode network (DMN) critically underpins cognitive and affective functions throughout the adult lifespan; however, detailed insights into its complex neuroarchitecture and connectivity patterns across aging remain limited. Leveraging the open-access CamCAN dataset, comprising structural and diffusion magnetic resonance imaging (MRI) alongside magnetoencephalography (MEG) data from 599 adults spanning ages 18 to 88 years, we systematically investigated age-associated changes in multimodal connectomes within the DMN. Our analyses revealed a progressive decline in both structural and functional connectivity among DMN subregions with advancing age. Additionally, MEG-based connectivity assessment demonstrated age-related decreases in high-frequency oscillatory activity (alpha, beta, gamma bands) accompanied by increases in low-frequency oscillations (theta band). Integrating structural data with neurophysiological measures further revealed age-dependent shifts in neurophysiological-structural coupling within the prefrontal cortex, characterized by strengthened coupling at theta frequencies but weakened coupling at higher frequencies. Conversely, coupling within the posterior cingulate cortex consistently declined across all examined frequency bands. Notably, theta-band coupling within the prefrontal cortex significantly correlated with age-related memory performance variations. Collectively, our findings delineate nuanced changes in DMN information transmission dynamics across adulthood, underscoring its promise as a neurobiological biomarker reflective of cognitive aging heterogeneity.

neuroscience↗

bioRxiv2025

PepSeek: Universal Functional Peptide Discovery with Cooperation Between Specialized Deep Learning Models and Large Language Model

Recent computational foundation models have revitalized the scientific discovery pipeline. However, developing foundational models for functional peptide discovery is costly due to the scarcity of wet-lab validated data. Meanwhile, conventional deep learning models are hard to generalize to unseen tasks or data distribution. Here, we introduce PepSeek, a universal approach for peptide discovery that synergistically integrates the most advanced large language model (LLM) with specialized small models. PepSeek harnesses the robust reasoning and generalization capabilities of LLM while leveraging the high predictive accuracy of specialized models trained for tasks such as antimicrobial activity regression and functional peptide generation. We have devised multiple collaborative strategies and task-specific modules demonstrating leading performance in peptide identification and generation. Notably, PepSeek achieves remarkable zero-shot prediction accuracy for peptides with diverse functionalities. We used PepSeek to identify a group of broad-spectrum antimicrobial peptide that exhibits low toxicity and high activity against drug-resistant bacteria, with the best surpassing all peptides currently undergoing clinical trials. Our framework establishes a new pipeline for scientific discovery with the help of LLM and specialized models.

bioinformatics↗

bioRxiv2025

Adolescents with major depression featured by sensory-association subtyping show divergent information dynamics and streams

Adolescent major depressive disorder (MDD) exhibits complex and heterogeneous alterations of brain functional organization. To understand the neurobiological basis of adolescent MDD, we adopted resting-state functional MRI data and used various matrix decomposition approaches to obtain the organization gradients, temporal dynamics, and information streams. With clustering sensory-association gradient features in our exploratory sample (NMDD = 250 and NControls = 203), we identified two MDD subtypes. Subtype 1 was characterized by sensory contraction and subtype 2 was associated with association expansion. In addition, two subtypes showed divergent bottom-up and top-down information flows in sensory and association areas using temporal dynamics analysis. These subtypes exhibit distinct age-related changes and reorganization trajectories along sensory-association and auditory-visual axes, highlighting that cortical information flow patterns systematically vary and relate differently to sensory integration, cognitive complexity, and aging. These network distinctions are linked to clinical severity and molecular mechanisms. Subtype 1 is predominantly associated with early neurodevelopmental abnormalities and emotional regulation deficits, while Subtype 2 is more related to synaptic dysfunction and reduced neuronal excitability. These results could be largely replicated in another independent sample (NMDD = 73 and NControls = 28). We therefore construct a sensory-association dual functional framework to characterize MDD heterogeneity in adolescent MDD. Itl integrates cortical hierarchy, developmental trajectories, and genetic influences, offering novel insights into MDD pathophysiology and providing a theoretical foundation for precision psychiatry, facilitating personalized diagnosis and intervention strategies.

neuroscience↗

bioRxiv2025

Label-Free Quantification of Apoptosis and Necrosis Using Stimulated Raman Scattering Microscopy

Recombinant proteins are critical for modern therapeutics and diagnostics, with Chinese hamster ovary (CHO) cells serving as the primary production platform. However, environmental and chemical stressors in bioreactors often trigger cell death, particularly apoptosis, posing a significant challenge to recombinant protein manufacturing. Rapid, label-free methods to monitor cell death are essential for ensuring better production quality. Stimulated Raman scattering (SRS) microscopy offers a powerful, label-free approach to measure lipid and protein compositions in live cells. We demonstrate that SRS microscopy enables rapid and reagent-free analysis of apoptotic and necrotic transitions. Our results show that apoptotic cells exhibit higher protein concentrations, while necrotic cells show an opposite trend. To enhance analysis, we developed a quantitative single-cell analysis pipeline that extracts chemotypic and phenotypic signatures of apoptosis and necrosis, enabling the identification of subpopulations with varied responses to stressors or treatments. Furthermore, the cell death analysis was successfully generalized to other stressors and cell types. This study highlights SRS microscopy as a robust and non-invasive tool for rapid monitoring of live cell apoptotic and necrotic transitions. Our method and findings hold potential for improving quality control in CHO cell-based biopharmaceutical production and for evaluating cell death in diverse biological contexts.

cell biology↗

bioRxiv2025

Translational activators align mRNAs at the small mitoribosomal subunit for translation initiation

Mitochondrial gene expression is essential for oxidative phosphorylation. Mitochondrial-encoded mRNAs are translated by dedicated mitochondrial ribosomes (mitoribosomes), whose regulation remains elusive. In the bakers yeast Saccharomyces cerevisiae, nuclear-encoded mitochondrial translational activators (TAs) facilitate transcript-specific translation by a yet unknown mechanism. Here, we investigated the function of TAs containing RNA-binding pentatricopeptide repeats (PPRs) using selective mitoribosome profiling and cryo-EM structural analysis. These analyses revealed that TAs exhibit strong selectivity for mitoribosomes initiating on their target transcripts. Moreover, TA-mitoribosome footprints indicated that TAs recruit mitoribosomes proximal to the start codon. Two cryo-EM structures of mRNA-TA complexes bound to post-initiation/pre-elongation-stalled mitoribosomes revealed the general mechanism of TA action. Specifically, the TAs bind to structural elements in the 5 UTR of the client mRNA as well as to the mRNA channel exit to align the mRNA in the small subunit during initiation. Our findings provide a mechanistic basis for understanding how mitochondria achieve transcript-specific translation initiation without relying on general sequence elements to position mitoribosomes at start codons.

molecular biology↗

bioRxiv2024

Bridging Glucose Metabolism and Intrinsic Functional Organization of the Human Cortex

The human brain requires a continuous supply of energy to function effectively. Here, we investigated how the low-dimensional organization of intrinsic functional connectivity patterns based on resting-state functional magnetic resonance imaging relates to brain energy expenditure measured by fluorodeoxyglucose positron emission tomography. By incrementally adding more dimensions of brain organization (via functional gradients), we were able to show that increasing amounts of variance in the map of brain energy expenditure could be accounted for. In particular, the brain organization dimensions that explained a large amount of the variance in intrinsic brain function also explained a large amount of the regional variance in the energy expenditure maps. This was particularly true for brain organization maps based on the strongest connections, suggesting that "weak" connections may not explain as much energy variance. Notably, our topological model was more effective than random brain organization configurations, suggesting that brain organization may be specifically associated with energy optimization. Finally, using brain asymmetry as a model for metabolic efficiency, we found that optimizing energy expenditure independently in each hemisphere outperformed non-independent optimization. This supports the concept of hemispheric competition rather than lateralization in energy allocation. Our results demonstrate how the spatial organization of functional connections is systematically linked to optimized energy expenditure in the human brain, providing new insights into the metabolic basis of brain function.

neuroscience↗

bioRxiv2024

Protein target search diffusion-association/dissociation free energy landscape around DNA binding site with flanking sequences

Proteins including transcription factors (TFs) and regulating enzymes search DNA for specific sites by alternating 3D diffusion in cell nucleus space and 1D diffusion on DNA. The search dynamics and free energy landscape of the protein along DNA depend essentially on the protein-DNA interactions, which simultaneously determine the protein-DNA association strength and relative population profiling along DNA, e.g., measured from protein binding microarray (PBM) to genome-wide mapping. Here we present a minimal structure-based model of protein diffusional search along DNA amid protein binding and unbinding events on the DNA, taking into account protein-DNA electrostatic interactions and hydrogen-bonding (HB) interactions or contacts at the interface. We accordingly constructed the protein diffusion-association/dissociation free energy surface and mapped it to 1D as the protein slides along DNA, maintaining the protein-DNA interfacial HB contacts that presumably dictate the DNA sequence information detection. Upon DNA helical path correction, the protein 1D diffusion rates along DNA can be physically derived to be consistent with experimental measurements. We also show that the sequence-dependent protein sliding or stepping patterns along DNA are regulated by collective interfacial HB dynamics, which also determines the ruggedness of the 1D diffusion free energy landscape. In comparison, protein association or binding with DNA are generically dictated by the protein-DNA electrostatic interactions, with an interaction zone of nanometers around DNA. Extra degrees of freedom (DOFs) of the protein such as rotations and conformational fluctuations can be well accommodated within the electrostatic interaction zone. As such we demonstrate that the protein binding or association free energy profiling along DNA smoothens over the 1D diffusion free energy landscape, which leads to population variations for an order of magnitude upon a marginal free energetic smoothening around the specific or consensus sites. We further show that the protein unbinding or dissociation from a comparatively high-binding affinity DNA site is dominated by lateral diffusion to the flanking low-affinity sites. The results suggest that experimental characterizations on the relative protein-DNA binding affinities or population profiling on the DNA are systematically and physically impacted by the extra DOFs of protein motions aside from translation as well as from flanking DNA sequences due to protein 1D diffusion and non-specific binding/unbinding.

biophysics↗