Biology subjects

Verma, P.

Publications and source records attributed to Verma, P..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

RNaseH-based ribodepletion of total planarian RNA improves detection of longer and non-polyadenylated transcripts

The overwhelming majority of RNA species isolated from cells or tissues using organic extraction are ribosomal RNAs (rRNA), whereas a relatively small percentage are messenger RNAs (mRNA). For studies that seek to detect mRNA transcripts and measure changes in their expression, this lopsided ratio of desired transcripts to undesired transcripts creates a significant challenge to obtaining sensitive and reproducible results. One method for improving mRNA detection is to selectively amplify polyadenylated (polyA) mRNA molecules when generating RNA-seq libraries, a strategy that is generally very successful in many species. However, this strategy is less effective when starting with total RNA from some species e.g., the planarian species Schmidtea mediterranea (S.med), as it generates libraries that still contain significant and variable amounts of rRNA reads. Further, commercially available ribodepletion kits do not efficiently deplete rRNAs from these samples because their sequences are divergent from mammalian rRNAs. Here we report a customized, optimized, and economical ribodepletion strategy than allows the generation of comprehensive RNA-seq libraries with less than one percent rRNA contamination. We show that this method improves transcript detection, particularly for those without polyA tails (e.g., core histones) and those that are relatively long (e.g., microtubule motor proteins). Using this custom ribodepletion approach, we also detected many transcripts that are not represented in the most recent set of S.med gene annotations, including a subset that are likely expressed transposable elements (TEs). To facilitate future differential expression analyses of these newly identified loci, we created both an annotation file of the new loci we identified and a bioinformatic pipeline for generating additional annotations from future libraries. As significant recent research shows that TE activation is regulated and functionally important, the resources provided here will provide a starting point for investigating such mechanisms in planarians and other species with less conserved rRNA sequences.

molecular biology↗

bioRxiv2024

Deciphering binding site conformational variability of substrate promiscuous and specialist enzymes

Substrate promiscuity is the ability of enzymes to catalyze reactions with alternate substrate(s) beyond their physiologically relevant ones. Such promiscuous activities expand enzymes functional landscape, enabling evolution or designing novel biochemical reactions. The molecular basis of substrate promiscuity remains elusive, though previous studies have suggested roles of active site structural features, such as flexibility, hydrophobicity, sub-sites, and electrostatics. Moreover, a recent hypothesis proposes the role of active site conformational variability in promiscuity. Accordingly, promiscuous enzymes could accommodate alternate substrate(s) through their pre-existing conformations, whereas specialists have a dominant conformation for their native substrates. To explore the role of active site conformational flexibility in substrate promiscuity, we compared the conformational states of two substrate promiscuous and specialist enzymes by analyzing their binding site structural dynamics from long-time explicit solvent molecular dynamics. Using tICA, we generated conformational states from simulations of the holo-conformation of enzymes. In addition to visual analysis of the variability of binding site conformation states, we performed quantitative estimation of the same using the native functionality score, which measures the contact similarity of conformations to the native structure. We observed that both specialist and generalist enzymes exhibited varied numbers of substrate binding site competent states, indicating that conformational flexibility to accept alternate substrates could exist in both groups of enzymes. Further, it caters to the view of substrate promiscuity as a continuum feature of enzymes.

bioinformatics↗

bioRxiv2024

Exon Nomenclature and Classification of Transcripts (ENACT): Systematic framework to annotate exon attributes

AbstractO_ST_ABSMotivationC_ST_ABSIsoform diversity is known to enhance a genes functional repertoire. Despite studies on transcriptome diversifying processes (Alternate splicing/transcription), their extent and correlated impact on proteome diversity remains rudimentarily understood. ResultsThe current study presents an innovative framework, "Exon Nomenclature and Annotation of Transcripts," that centralizes exonic loci while integrating protein sequence per entity with tracking and assessing splice site variability. The resulting annotation from framework enables exon features to be tractable, facilitating a systematic analysis of isoform diversity. Our findings and case studies unveil systemic exon inclusions roles in regulating diversity in CDS region. Availability and implementationAll data generated during this study are publicly available at www.iscbglab.in/enactdb/. Associated algorithmic procedures have been described in the methods section. Supplementary informationPDF file enclosing supplementary data attached.

bioinformatics↗

bioRxiv2024

Chromatin remodeling protein BPTF regulates transcriptional stability in planarian stem cells

Trimethylation of histone H3 lysine 4 (H3K4me3) correlates strongly with gene expression in many different organisms, yet the question of whether it plays a causal role in transcriptional activity remains unresolved. Although H3K4me3 does not directly affect chromatin accessibility, it can indirectly affect genome accessibility by recruiting the ATP-dependent chromatin remodeling complex NuRF (Nucleosome Remodeling Factor). The largest subunit of NuRF, BPTF/NURF301, binds H3K4me3 specifically and recruits the NuRF complex to loci marked by this modification. Studies have shown that the strength and duration of BPTF binding likely also depends on additional chromatin features at these loci, such as lysine acetylation and variant histone proteins. However, the exact details of this recruitment mechanism vary between studies and have largely been tested in vitro. Here, we use stem cells isolated directly from live planarian animals to investigate the role of BPTF in regulating chromatin accessibility in vivo. We find that BPTF operates at gene promoters and is most effective at facilitating transcription at genes marked by Set1-dependent H3K4me3 peaks, which are significantly broader than those added by the lysine methyltransferase MLL1/2. Moreover, BPTF is essential for planarian stem cell biology and its loss of function phenotype mimics that of Set1 knockdown. Together, these data suggest that BPTF and H3K4me3 are important mediators of both transcription and in vivo stem cell function.

developmental biology↗

bioRxiv2024

Molecular insights into phosphoethanolamine cellulose formation and secretion

Phosphoethanolamine (pEtN) cellulose is a naturally occurring modified cellulose produced by several Enterobacteriaceae. The minimal components of the E. coli cellulose synthase complex include the catalytically active BcsA enzyme, an associated periplasmic semicircle of hexameric BcsB, as well as the outer membrane (OM)-integrated BcsC subunit containing periplasmic tetratricopeptide repeats (TPR). Additional subunits include BcsG, a membrane-anchored periplasmic pEtN transferase associated with BcsA, and BcsZ, a conserved periplasmic cellulase of unknown biological function. While events underlying the synthesis and translocation of cellulose by BcsA are well described, little is known about its pEtN modification and translocation across the cell envelope. We show that the N-terminal cytosolic domain of BcsA positions three copies of BcsG near the nascent cellulose polymer. Further, the terminal subunit of the BcsB semicircle tethers the N-terminus of a single BcsC protein to establish a trans-envelope secretion system. BcsCs TPR motifs bind a putative cello-oligosaccharide near the entrance to its OM pore. Additionally, we show that only the hydrolytic activity of BcsZ but not the subunit itself is necessary for cellulose secretion, suggesting a secretion mechanism based on enzymatic removal of mislocalized cellulose. Lastly, we introduce pEtN modification of cellulose in orthogonal cellulose biosynthetic systems by protein engineering.

biophysics↗

bioRxiv2024

Spectral graph model for fMRI: a biophysical, connectivity-based generative model for the analysis of frequency-resolved resting state fMRI

Resting state functional MRI (rs-fMRI) is a popular and widely used technique to explore the brains functional organization and to examine if it is altered in neurological or mental disorders. The most common approach for its analysis targets the measurement of the synchronized fluctuations between brain regions, characterized as functional connectivity (FC), typically relying on pairwise correlations in activity across different brain regions. While hugely successful in exploring state- and disease-dependent network alterations, these statistical graph theory tools suffer from two key limitations. First, they discard useful information about the rich frequency content of the fMRI signal. The rich spectral information now achievable from advances in fast multiband acquisitions is consequently being under-utilized. Second, the analyzed FCs are phenomenological without a direct neurobiological underpinning in the underlying structures and processes in the brain. There does not currently exist a complete generative model framework for whole brain resting fMRI that is informed by its underlying biological basis in the structural connectome. Here we propose that a different approach can solve both challenges at once: the use of an appropriately realistic yet parsimonious biophysical signal generation model followed by graph spectral (i.e. eigen) decomposition. We call this model a Spectral Graph Model (SGM) for fMRI, using which we can not only quantify the structure-function relationship in individual subjects, but also condense the variable and individual-specific repertoire of fMRI signals spectral and spatial features into a small number of biophysically-interpretable parameters. We expect this model-based inference of rs-fMRI that seamlessly integrates with structure can be used to examine state and trait characteristics of structure-function relations in a variety of brain disorders.

neuroscience↗

bioRxiv2024

Uncovering the translatome impact of transcriptome induced diversity in eukaryotes: framework and innovative insights

Isoform diversity is known to enhance a genes functional repertoire. Insights into the extent of such sequence variability generated through alternative splicing (AS), may unveil the layers of gene function/regulation. Despite studies on transcriptome diversifying processes, the impact of AS or related processes on sequence diversity still needs to be explored. Current study presents an innovative framework that centralizes exonic loci while integrating protein sequence per entity with attention to splice site variability assessment. The resulting framework enables exon (features) to be tractable, facilitating a systematic, detailed analysis of isoform diversity. We analyzed isoform diversity in five representative organisms and detailed the role of AS and related processes influencing exon inclusion in imparting sequence variation for human genome. Through analyses of exonic variations in two maximally diverged isoforms of human genes, we unraveled intricate splicing patterns prevalent in coding and non-coding regions. We observed that alternative splice sites, sequence changes, and skipping of exons are prevalent in coding exons, while the alternate first exon events are predominant in non-coding exons. Our findings offer a comprehensive understanding of isoform diversity as a function of exonic entity framework, providing valuable insights into the orchestration of exonic events in shaping the proteogenomic landscape.

bioinformatics↗

bioRxiv2024

Morphological Reprogramming of Primary Cilia Length Mitigates the Fibrotic Phenotype in fibroblasts across diverse fibrotic conditions

Fibrosis is a hallmark of systemic sclerosis (SSc) and many diverse and incurable diseases. Myofibroblast activation, a common cellular phenomenon shared across fibrotic diseases, is marked by actin polymerization known to affect primary cilia (PC) length. We discovered that fibroblasts from diverse fibrotic conditions display significantly reduced PC length ex vivo. Treatment of healthy fibroblasts with profibrotic TGF-{beta}1 induced PC shortening, while silencing ACTA2 in SSc skin fibroblasts caused PC elongation. Importantly, we found that PC length is negatively correlated with cellular expression of -SMA in TGF-{beta}1-stimulated healthy fibroblasts, or pharmacologically de-differentiated myofibroblasts. PC elongation by microtubule polymerization induction in SSc skin fibroblasts using LiCl or the HDAC6 inhibitor tubacin, reversed and mitigated fibrotic responses. Our results implicate a key role for microtubule polymerization in restraining fibrotic responses and suggest that modulation of PC dynamics may represent a potential therapeutic strategy for SSc and other treatment-resistant diseases associated with fibrosis. Teaser. PC length shortening is a hallmark of fibrosis.

cell biology↗

bioRxiv2023

Probing the Mechanisms of Global Brain Reconfiguration after Local Manipulations

Understanding how localized brain interventions translate into whole-brain dynamics is crucial for deciphering neural function and tailoring therapeutic strategies. Combining mouse experimental datasets of focal interventions (thalamic lesion and chemogenetic silencing of cortical hubs), we demonstrate both local and global effects. Using whole-brain simulations of experimental data, we not only confirm the distributed nature of local manipulations but also offer mechanistic insights into these processes. Our simulations predict specific alterations in firing rates and spectral characteristics across specific brain networks, leading to structured changes in functional connectivity patterns. Some of these predictions have been empirically validated. Notably, the affected brain subnetworks--and their resultant signatures of change--are contingent on the original intervention site, suggesting a method to accurately localize the source of alteration. Our results provide a general framework for interpreting localized intervention effects, offering insights that could refine clinical interventions for focal brain disorders by enabling targeted circuit-level neuromodulation strategies.

neuroscience↗

bioRxiv2023

Economic analysis of disease and control of multi-field epidemics in agriculture

Epidemics of plant diseases are estimated to cause significant economic losses in crop production. Fungicide applications are widely used to control crop diseases but incur substantial indirect costs. One essential class of indirect costs arises due to the evolution of fungicide resistance. This indirect cost must be estimated reliably to design economic policy for more sustainable use of fungicides. Such estimation is difficult because the cost depends on economic parameters and the evo-epidemiological properties of crop pathogens. Even a conceptual framework for such estimation is missing. To address this problem, we combined a spatially implicit mathematical model of crop epidemics with an economic analysis at the landscape scale. We investigated how the net economic return from a landscape depends on the proportion of fungicide-treated fields. We discovered a pattern of accelerating (or decelerating) returns, contrary to expected diminishing returns. Next, we calculated the economic cost of the evolution of fungicide resistance as the difference between the optimal net return of the landscape in the absence and presence of resistance. We found that this cost depends strongly on the fungicide price, the degree of resistance, the pathogens basic reproduction number and the yield loss due to disease. Surprisingly, the cost declines with the fungicide price and exhibits a non-monotonic pattern as a function of the basic reproduction number. Hence, to calculate the cost, we must estimate these parameters robustly, incorporating variations in environmental conditions, crop varieties and the genetic composition of pathogen populations. Appropriate estimation of the cost of resistance evolution can inform economic policy and encourage more sustainable use of fungicides. Author SummaryFungicides protect crops from diseases and are essential for securing the global food supply, but they incur serious indirect costs to society and the environment. One such cost arises because of the evolution of fungicide resistance. Part of the pathogen population (fungicide-resistant) can gain protection from a fungicide via a genetic change. If fungicide applications continue, the fungicide-resistant subpopulation increases and dominates the population, leading to low efficacy. Resistance can lead to severe economic losses, but no conceptual framework exists for estimating them. We present a novel mathematical framework to estimate the economic costs of fungicide resistance at the landscape scale. We combined an epidemiological model describing disease spread with an economic cost-benefit analysis. Surprisingly, we found that the economic cost of resistance declines for more expensive fungicides. This cost also depends on the pathogens capacity to spread (invasiveness): the cost is highest for pathogens with intermediate invasiveness. Thus, the cost of resistance depends on economic parameters and the biological characteristics of plant diseases. Our findings can inform economic policies for sustainable fungicide use, such as taxes or subsidies. Our paper also contributes to the broader discourse on agricultural sustainability while ensuring global food security.

evolutionary biology↗

bioRxiv2023

Modifications of Two ESCRT-I Subunits with Distinct Ubiquitin Chains Regulate Plant Immunity

Sensing of pathogen- or microbe-associated molecular patterns (PAMPs/MAMPs) by pattern recognition receptors (PRRs) at the cell surface induces the first layer of host immunity against invading microbial pathogens. The immune receptor FLS2 perceives bacterial flagellin to initiate host immune signaling upon pathogen infections. It has been known that the FLS2 abundance is crucial for plant pattern-triggered immunity. Nevertheless, the underpinning regulatory mechanisms remain largely unclear. In this study, we demonstrate that XBAT35.2 positively modulates the protein level of FLS2. In addition to the Golgi, XBAT35.2 localizes at the plasma membrane and constitutively associates with FLS2, BAK1, and BIK1. Flg22 treatment increases the association of XBAT35.2 with FLS2 and BAK1 but reduces the interaction with BIK1. XBAT35.2 ubiquitinates two key components of the ESCRT-I complex, VPS37-1 and VPS28-2 with K48 and K63-linked polyubiquitin chains respectively, leading to degradation of VPS37-1 and diminished interaction of VPS28-2 with FLS2. Additionally, VPS37-1 and VPS28-2 play redundant, negative roles in FLS2-mediated immunity by promoting vacuolar breakdown of FLS2. Thus, by intercepting the function of VPS28-2 and VPS37-1, XBAT35.2 stabilizes FLS2 for host immunity. Our findings reveal a new regulatory circuit for modulating the FLS2 abundance and deepen our understanding of controlling the homeostasis of cell surface receptors. One-sentence summaryTargeting the ESCRT-I subunits VPS28-2 and VPS37-1 with distinct ubiquitin chains by the E3 ligase XBT35.2 stabilizes FLS2 and positively modulates plant immunity.

plant biology↗

bioRxiv2023

Bayesian Inference of a Spectral Graph Model for Brain Oscillations

The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which can not be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.

neuroscience↗

bioRxiv2023

Isolated nuclei from frozen tissue are the superior source for single cell RNA-seq compared with whole cells.

The isolation of intact single cells from frozen tissue is a challenge due to the mechanical and physical stress inflicted upon the cell during the freeze-thaw process. Ruptured cells release ambient RNA into the cell suspension, which can become encapsulated into droplets during droplet based single cell RNA-seq library preparation methods. The presence of ambient RNA in droplets has been suggested to impact data quality, however there have been limited reports on single cell RNA-seq data from frozen tissue. Here, we compare the results of single cell RNA-seq derived from disaggregated cells from frozen brain tissue with single nuclei RNA-seq derived from purified nuclei of identical tissue using the 10X Genomics Chromium 3gene expression assay. Our results indicated that presence of ambient RNA in the cell suspension resulted in single cell RNA-seq data with a 25-fold lower gene count, a 5-fold lower UMI count per cell and a 2-fold lower fraction of reads per cell compared with single nuclei RNA-seq data. Cell clustering with the single cell RNA-seq data was unable to resolve the heterogeneity of brain cell types. Our conclusion is that nuclei from frozen tissue are the superior substrate for single cell transcriptome analysis.

genomics↗

bioRxiv2023

Antibiotic-mediated interactions underlying microbial diversity

The immense diversity observed in natural microbial communities is surprising in light of the numerous weapons microbes have evolved to inhibit each others growth. It is thus imperative to understand which interaction patterns can sustain a biodiverse community when individual species antagonistically affect one another. In this study, we leverage potent methods from theoretical ecology to show how antibiotic-mediated interactions between microbes drive biological diversity. Building on previous experimental and theoretical results, we analyse the dynamics induced by various interaction graphs involving antibiotic production, resistance, and degradation. Previous work has recognised the importance of a particular producer-sensitive-degrader (PSD) motif in the interaction graph. We study this motif in detail and elucidate the mechanistic reason for this importance. Concretely, we give exact rules for coexistence in some simple cases where exhaustive enumeration of the interaction graphs is feasible. More generally, our results suggest that the PSD motif, in combination with a cyclic interaction structure, is sufficient for stable coexistence in well-mixed populations. Using individual-based simulations, we then study the importance of the PSD motif in spatially structured populations. We show that community coexistence is robust for an extensive range of antibiotic and degrader diffusivities. Together, these findings illuminate the interaction patterns that give rise to diversity in complex microbial communities, stressing that antagonism does not imply a lack of diversity and suggesting clear approaches for culturing synthetic microbial consortia.

microbiology↗

bioRxiv2023

Insights into substrate coordination and glycosyl transfer of poplar cellulose synthase-8

Cellulose is an abundant cell wall component of land plants. It is synthesized from UDP-activated glucose molecules by cellulose synthase, a membrane-integrated processive glycosyltransferase. Cellulose synthase couples the elongation of the cellulose polymer with its translocation across the plasma membrane. Here, we present substrate and product-bound cryogenic electron microscopy structures of the homotrimeric cellulose synthase isoform-8 (CesA8) from hybrid aspen (poplar). UDP-glucose binds to a conserved catalytic pocket adjacent to the entrance to a transmembrane channel. The substrates glucosyl unit is coordinated by conserved residues of the glycosyltransferase domain and amphipathic interface helices. Site-directed mutagenesis of a conserved gating loop capping the active site reveals its critical function for catalytic activity. Molecular dynamics simulations reveal prolonged interactions of the gating loop with the substrate molecule, particularly across its central conserved region. These transient interactions likely facilitate the proper positioning of the substrate molecule for glycosyl transfer and cellulose translocation. HighlightsO_LICryo-EM structures of substrate and product bound poplar cellulose synthase provide insights into substrate selectivity C_LIO_LISite directed mutagenesis signifies a critical function of the gating loop for catalysis C_LIO_LIMolecular dynamics simulations support persistent gating loop - substrate interactions C_LIO_LIGating loop helps in positioning the substrate molecule to facilitate cellulose elongation C_LIO_LIConserved cellulose synthesis substrate binding mechanism across the kingdoms C_LI

biochemistry↗

bioRxiv2022

Chaperonin activity of Plasmodium prefoldin complex is essential to guard proteotoxic stress response and presents a new target for drug discovery

The intraerythrocytic growth of malaria parasite is challenged by the presence of proteotoxic stress and intrinsically unstructured proteins in the cytoplasm due to formation of toxic heme during haemoglobin digestion. To overcome the unavoidable stress and maintain the cellular protein homeostasis, parasite encodes for a number of chaperones and co-chaperones. Here, we functionally characterize the Plasmodium falciparum prefoldins (PfPFD1-6), a hexameric co-chaperone complex, for their role in protein homeostasis. We demonstrate that PfPFD1-6 localise to cytosol of the parasite and the subunits perform an orchestrated interaction (-PFD3-PFD2-PFD1-PFD5-PFD6-PFD4-) to form an active jelly-fish like complex. Biperiden, an N-propylpiperidine analogue identified by chemotype search from FDA, strongly binds and restricts the formation of prefoldin complex and inhibited its interaction with the substrates, PfMSP-1 and -tubulin-I. Biperiden treatment potently inhibited the in vitro (IC50: 1M) and in vivo growth of malaria parasite. Thus, this study provides novel virtues towards understanding the role of PfPFDs in regulating protein homeostasis and opens new avenues for drug discovery against malaria.

molecular biology↗

bioRxiv2022

Human blood plasma proteins modeling and binding affinities with Δ9-tetrahydrocannabinol active metabolites: In silico approach

Tetrahydrocannabinol (THC) is a key psychotropic constituent of cannabis sativa. It is also known as {Delta}9-tetrahydrocannabinol ({Delta}9-THC). Previous study suggested that owing to its high lipophilicity, it piles up in adipose tissue and it is disseminated into blood stream for prolonged time. Research suggests that numerous diseases such as multiple sclerosis, neurodegenerative disorders, epilepsy, schizophrenia, osteoporosis, cancer, glaucoma and cardiovascular disorders can be treated using this substance. However, apart from having therapeutic potential, many studies have reported detrimental outcomes along with addiction of {Delta}9-THC for short-term and long-term consumption. Thus, in this study, we determined the binding affinities of {Delta}9-THC and its two active metabolites, 11-Hydroxy-{Delta}9-tetrahydrocannabinol (11-OH-{Delta}9-THC) and 8beta,11-dihydroxy-{Delta}9-tetrahydrocannabinol (8{beta},11-diOH-{Delta}9-THC) with 401 human blood plasma proteins using molecular docking analysis. Results show that {Delta}9-THC has greater binding potential with plasma proteins as compared to other two metabolites. Overall, ADGRE5, ALB, APOA5, APOD, CP, PON1 and PON3 proteins showed the highest binding affinities with three cannabis metabolites.

bioinformatics↗

bioRxiv2022

Whole brain network analysis of neural synchrony and information flow during transition from wakefulness to light non-rapid eye movement sleep

Sleep is a highly stereotyped phenomenon, requiring robust spatial and temporal coordination of neural activity. How the brain coordinates neural activity with sleep onset can provide insight into the physiological functions subserved by sleep and pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wake to non-rapid eye movement (NREM) sleep using magnetoencephalography imaging in healthy subjects. In addition, we performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The sleep transition was identified to be encoded in spatially and temporally specific patterns of local and long-range neural synchrony. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset. Finally, biophysical neural mass modeling demonstrated spatially heterogeneous properties of cortical excitation-to-inhibition from wake to NREM. Together, these findings reveal whole-brain corticocortical structure in the sleep-wake transition and demonstrate the orchestration of local and long-range, frequency-specific cortical interactions that are fundamental to sleep onset.

bioengineering↗