Contact Frequencies Research Articles

A Bioconductor/R Workflow for the Detection and Visualization of Differential Chromatin Loops

Background Chromatin loops play a critical role in gene regulation by connecting regulatory loci and gene promoters. The identification of changes in chromatin looping between cell types or biological conditions is an important task for understanding gene regulation; however, the manipulation, statistical analysis, and visualization of data sets describing 3D chromatin structure is challenging due to the large and complex nature of the relevant data sets. Methods Here, we describe a workflow for identifying and visualizing differential chromatin loops from Hi-C data from two biological conditions using the ‘mariner’, ‘DESeq2’ and ‘plotgardener’ Bioconductor/R packages. The workflow assumes that Hi-C data has been processed into ‘.hic’ or ‘.cool’ files and that loops have been identified using an existing loop-calling algorithm. Results First, the ‘mariner’ package is used to merge redundant loop calls and extract interaction frequency counts. Next, ‘DESeq2’ is used to identify loops that exhibit differential contact frequencies between conditions. Finally, ‘plotgardener’ is used to visualize differential loops. Conclusion Chromatin interaction data is an important modality for understanding the mechanisms of transcriptional regulation. The workflow presented here outlines the use of ‘mariner’ as a tool to manipulate, extract, and aggregate chromatin interaction data, ‘DESeq2’ to perform differential analysis of these data across conditions, samples, and replicates, and ‘plotgardener’ to explore and visualize the results.

Vaccination subsidy allocation under budget constraints considering the human interpersonal contact pattern and vaccine protection effect in epidemics

Vaccination subsidy is one of the most important measures to increase the willingness of people to be vaccinated for epidemic prevention and control. Given the budget constraint of vaccination subsidy and the different roles of various age groups population in the epidemic transmission process, a novel approach is proposed to optimize the utilization of the limited vaccination subsidy budget. First, an age-structured SIR model that integrates the human interpersonal contact pattern and vaccine protection effect is developed to simulate the epidemic trend under a certain vaccination state. Then, a decision model is constructed to determine the optimal vaccination subsidy allocation scheme for various age groups based on the age-structured SIR model. A case study of Wuhan City is used to verify the decision approach, and a series of sensitivity analyses are conducted. The result shows that the peak time of an epidemic is positively related to the total treatment cost for all the infections, and more subsidies should be allocated to the populations with higher interpersonal contact frequencies for epidemic prevention and control.

Peculiar k-mer Spectra Are Correlated with 3D Contact Frequencies and Breakpoint Regions in the Human Genome.

It is widely accepted that the 3D chromatin organization in human cell nuclei is not random and recent investigations point towards an interactive relation of epigenetic functioning and chromatin (re-)organization. Although chromatin organization seems to be the result of self-organization of the entirety of all molecules available in the cell nucleus, a general question remains open as to what extent chromatin organization might additionally be predetermined by the DNA sequence and, if so, if there are characteristic differences that distinguish typical regions involved in dysfunction-related aberrations from normal ones, since typical DNA breakpoint regions involved in disease-related chromosome aberrations are not randomly distributed along the DNA sequence. Highly conserved k-mer patterns in intronic and intergenic regions have been reported in eukaryotic genomes. In this article, we search and analyze regions deviating from average spectra (ReDFAS) of k-mer word frequencies in the human genome. This includes all assembled regions, e.g., telomeric, centromeric, genic as well as intergenic regions. A positive correlation between k-mer spectra and 3D contact frequencies, obtained exemplarily from given Hi-C datasets, has been found indicating a relation of ReDFAS to chromatin organization and interactions. We also searched and found correlations of known functional annotations, e.g., genes correlating with ReDFAS. Selected regions known to contain typical breakpoints on chromosomes 9 and 5 that are involved in cancer-related chromosomal aberrations appear to be enriched in ReDFAS. Since transposable elements like ALUs are often assigned as major players in 3D genome organization, we also studied their impact on our examples but could not find a correlation between ALU regions and breakpoints comparable to ReDFAS. Our findings might show that ReDFAS are associated with instable regions of the genome and regions with many chromatin contacts which is in line with current research indicating that chromatin loop anchor points lead to genomic instability.

A coupled hand and surface hygiene criterion on heterogeneous surface touch networks

Contaminated hands of people and contaminated surfaces of inanimate objects (fomites) can spread microbes that cause enteric and respiratory infections. Thus, hand hygiene and surface hygiene are probably the most widely adopted public health interventions for controlling such infections. However, conclusions of studies on the effectiveness of these interventions are often inconsistent, likely because such studies have examined these interventions separately and thus not detected their interactions, leading to differing conclusions about their individual impact. In this study, it is proposed that hand and environmental surface hygiene (including disinfection) should be coupled to control contamination spread between surfaces, especially within heterogeneous surface touch networks. In these networks, surfaces and individuals have varying contact frequencies and patterns, reflecting the diverse and non-uniform interactions that typically occur in real-world environments. Accordingly, we propose a new theoretical framework to delineate the relationships between hand hygiene and surface hygiene. In addition, the performance of a model based on this framework that used real-world behavioural data from a graduate student office is reported. Moreover, a coupled hygiene criterion for heterogeneous networks is derived. This criterion stipulates that the product of the pathogen-removal rates for hands and surfaces must exceed a cleaning threshold to ensure the exponential decay of contamination. Failure to meet this threshold results in a non-zero steady prevalence of contamination. Furthermore, the cleaning threshold increases as the numbers of surfaces and hands increase, highlighting the significant impact of network structures on hygiene practices. Thus, extensive cleaning may be necessary in crowded indoor environments with many surfaces and occupants, such as cruise ships, to prevent super-large outbreaks of, for example, noroviral infections. Overall, the findings of this study reveal how improved and integrated hygiene control can prevent fomite transmission.

ENT3C: an entropy-based similarity measure for Hi-C and micro-C derived contact matrices.

Hi-C and micro-C sequencing have shed light on the profound importance of 3D genome organization in cellular function by probing 3D contact frequencies across the linear genome. The resulting contact matrices are extremely sparse and susceptible to technical- and sequence-based biases, making their comparison challenging. The development of reliable, robust and efficient methods for quantifying similarity between contact matrices is crucial for investigating variations in the 3D genome organization in different cell types or under different conditions, as well as evaluating experimental reproducibility. We present a novel method, ENT3C, which measures the change in pattern complexity in the vicinity of contact matrix diagonals to quantify their similarity. ENT3C provides a robust, user-friendly Hi-C or micro-C contact matrix similarity metric and a characteristic entropy signal that can be used to gain detailed biological insights into 3D genome organization.

Addressing current limitations of household transmission studies by collecting contact data

Abstract Modeling studies of household transmission data have helped characterize the role of children in influenza and coronavirus disease 2019 (COVID-19) epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like and influenza virus-like infections in a synthetic population of 1000 households, assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father–mother pair, followed by the child–mother, child–child, and finally child–father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.

Multiscale Bayesian simulations reveal functional chromatin condensation of gene loci.

Chromatin, the complex assembly of DNA and associated proteins, plays a pivotal role in orchestrating various genomic functions. To aid our understanding of the principles underlying chromatin organization, we introduce Hi-C metainference, a Bayesian approach that integrates Hi-C contact frequencies into multiscale prior models of chromatin. This approach combines both bottom-up (the physics-based prior) and top-down (the data-driven posterior) strategies to characterize the 3D organization of a target genomic locus. We first demonstrate the capability of this method to accurately reconstruct the structural ensemble and the dynamics of a system from contact information. We then apply the approach to investigate the Sox2, Pou5f1, and Nanog loci of mouse embryonic stem cells using a bottom-up chromatin model at 1 kb resolution. We observe that the studied loci are conformationally heterogeneous and organized as crumpled globules, favoring contacts between distant enhancers and promoters. Using nucleosome-resolution simulations, we then reveal how the Nanog gene is functionally organized across the multiple scales of chromatin. At the local level, we identify diverse tetranucleosome folding motifs with a characteristic distribution along the genome, predominantly open at cis-regulatory elements and compact in between. At the larger scale, we find that enhancer-promoter contacts are driven by the transient condensation of chromatin into compact domains stabilized by extensive internucleosome interactions. Overall, this work highlights the condensed, but dynamic nature of chromatin in vivo, contributing to a deeper understanding of gene structure-function relationships.

Transcription decouples estrogen-dependent changes in enhancer-promoter contact frequencies and spatial proximity.

How enhancers regulate their target genes in the context of 3D chromatin organization is extensively studied and models which do not require direct enhancer-promoter contact have recently emerged. Here, we use the activation of estrogen receptor-dependent enhancers in a breast cancer cell line to study enhancer-promoter communication at two loci. This allows high temporal resolution tracking of molecular events from hormone stimulation to efficient gene activation. We examine how both enhancer-promoter spatial proximity assayed by DNA fluorescence in situ hybridization, and contact frequencies resulting from chromatin in situ fragmentation and proximity ligation, change dynamically during enhancer-driven gene activation. These orthogonal methods produce seemingly paradoxical results: upon enhancer activation enhancer-promoter contact frequencies increase while spatial proximity decreases. We explore this apparent discrepancy using different estrogen receptor ligands and transcription inhibitors. Our data demonstrate that enhancer-promoter contact frequencies are transcription independent whereas altered enhancer-promoter proximity depends on transcription. Our results emphasize that the relationship between contact frequencies and physical distance in the nucleus, especially over short genomic distances, is not always a simple one.

HIPPO: HIstogram-based Pseudo-POtential for scoring protein-ssRNA fragment-based docking poses

BackgroundThe RNA-Recognition motif (RRM) is a protein domain that binds single-stranded RNA (ssRNA) and is present in as much as 2% of the human genome. Despite this important role in biology, RRM-ssRNA interactions are very challenging to study on the structural level because of the remarkable flexibility of ssRNA. In the absence of atomic-level experimental data, the only method able to predict the 3D structure of protein-ssRNA complexes with any degree of accuracy is ssRNA’TTRACT, an ssRNA fragment-based docking approach using ATTRACT. However, since ATTRACT parameters are not ssRNA-specific and were determined in 2010, there is substantial opportunity for enhancement.ResultsHere we present HIPPO, a composite RRM-ssRNA scoring potential derived analytically from contact frequencies in near-native versus non-native docking models. HIPPO consists of a consensus of four distinct potentials, each extracted from a distinct reference pool of protein-trinucleotide docking decoys. To score a docking pose with one potential, for each pair of RNA–protein coarse-grained bead types, each contact is awarded or penalised according to the relative frequencies of this contact distance range among the correct and incorrect poses of the reference pool. Validated on a fragment-based docking benchmark of 57 experimentally solved RRM-ssRNA complexes, HIPPO achieved a threefold or higher enrichment for half of the fragments, versus only a quarter with the ATTRACT scoring function. In particular, HIPPO drastically improved the chance of very high enrichment (12-fold or higher), a scenario where the incremental modelling of entire ssRNA chains from fragments becomes viable. However, for the latter result, more research is needed to make it directly practically applicable. Regardless, our approach already improves upon the state of the art in RRM-ssRNA modelling and is in principle extendable to other types of protein-nucleic acid interactions.

Bottom-up data integration in polymer models of chromatin organisation

Cellular functions crucially depend on the precise execution of complex biochemical reactions taking place on the chromatin fiber in the tightly packed environment of the cell nucleus. Despite the availability of large data sets probing this process from multiple angles, bottom-up frameworks which allow the incorporation of the sequence-specific nature of biochemistry in a unified model of 3D chromatin structure remain scarce. Here we propose SEMPER (Sequence Enhanced Magnetic PolymER), a novel stochastic polymer model which naturally incorporates observational data about sequence-driven biochemical processes, such as binding of transcription factor proteins, in a 3D model of chromatin structure. We introduce a novel approximate Bayesian algorithm to quantify a posteriori the relative importance of various factors, including the polymeric nature of DNA, in determining chromatin epigenetic state, thus providing a transparent way to generate biological hypotheses. While accurate prediction of contact frequencies (a problem already extensively studied in the literature) is not our main aim, as a byproduct of the inference procedure and without additional input from the genome 3D structure, our model can predict with reasonable accuracy some notable and nontrivial conformational features of chromatin folding within the nucleus. Our work highlights the importance of introducing physically realistic statistical models for predicting chromatin states from epigenetic data and opens the way to a new class of more systematic approaches to interpreting epigenomic data.

Viral Respiratory Epidemic Modeling of Societal Segregation Based on Vaccination Status.

Societal segregation of unvaccinated people from public spaces has been a novel and controversial coronavirus disease 2019 (COVID-19)-era public health practice in many countries. Models exploring potential consequences of vaccination-status-based segregation have not considered how segregation influences the contact frequencies in the segregated groups. We systematically investigate implementing effects of segregation on population-specific contact frequencies and show this critically determines the predicted epidemiological outcomes, focusing on the attack rates in the vaccinated and unvaccinated populations and the share of infections among vaccinated people that were due to contacts with infectious unvaccinated people. We describe a susceptible-infectious-recovered (SIR) two-population model for vaccinated and unvaccinated groups of individuals that transmit an infectious disease by person-to-person contact. The degree of segregation of the two groups, ranging from zero to complete segregation, is implemented using the like-to-like mixing approach developed for sexually transmitted diseases, adapted for presumed severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) transmission. We allow the contact frequencies for individuals in the two groups to be different and depend, with variable strength, on the degree of segregation. Segregation can either increase or decrease the attack rate among the vaccinated, depending on the type of segregation (isolating or compounding), and the contagiousness of the disease. For diseases with low contagiousness, segregation can cause an attack rate in the vaccinated, which does not occur without segregation. There is no predicted blanket epidemiological advantage to segregation, either for the vaccinated or the unvaccinated. Negative epidemiological consequences can occur for both groups.

Differential roles of positive and negative supercoiling in organizing the E. coli genome.

This study aims to explore whether and how positive and negative supercoiling contribute to the three-dimensional (3D) organization of the bacterial genome. We used recently published Escherichia coli GapR ChIP-seq and TopoI ChIP-seq (also called EcTopoI-seq) data, which marks positive and negative supercoiling sites, respectively, to study how supercoiling correlates with the spatial contact maps obtained from chromosome conformation capture sequencing (Hi-C and 5C). We find that supercoiled chromosomal loci have overall higher Hi-C contact frequencies than sites that are not supercoiled. Surprisingly, positive supercoiling corresponds to higher spatial contact than negative supercoiling. Additionally, positive, but not negative, supercoiling could be identified from Hi-C data with high accuracy. We further find that the majority of positive and negative supercoils coincide with highly active transcription units, with a minor group likelyassociated with replication and other genomic processes. Our results show that both positive and negative supercoiling enhance spatial contact, with positive supercoiling playing a larger role in bringing genomic loci closer in space. Based on our results, we propose new physical models of how the E. coli chromosome is organized by positive and negative supercoils.

Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics.

The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXAand Fbn2 mouse genes ranging in size from 50 to 100kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.

Trisomies Reorganize Human 3D Genome.

Trisomy is the presence of one extra copy of an entire chromosome or its part in a cell nucleus. In humans, autosomal trisomies are associated with severe developmental abnormalities leading to embryonic lethality, miscarriage or pronounced deviations of various organs and systems at birth. Trisomies are characterized by alterations in gene expression level, not exclusively on the trisomic chromosome, but throughout the genome. Here, we applied the high-throughput chromosome conformation capture technique (Hi-C) to study chromatin 3D structure in human chorion cells carrying either additional chromosome 13 (Patau syndrome) or chromosome 16 and in cultured fibroblasts with extra chromosome 18 (Edwards syndrome). The presence of extra chromosomes results in systematic changes of contact frequencies between small and large chromosomes. Analyzing the behavior of individual chromosomes, we found that a limited number of chromosomes change their contact patterns stochastically in trisomic cells and that it could be associated with lamina-associated domains (LAD) and gene content. For trisomy 13 and 18, but not for trisomy 16, the proportion of compacted loci on a chromosome is correlated with LAD content. We also found that regions of the genome that become more compact in trisomic cells are enriched in housekeeping genes, indicating a possible decrease in chromatin accessibility and transcription level of these genes. These results provide a framework for understanding the mechanisms of pan-genome transcription dysregulation in trisomies in the context of chromatin spatial organization.

Molecular Dynamics Simulation Study of the Selective Inhibition of Coagulation Factor IXa over Factor Xa.

Thromboembolic disorders, arising from abnormal coagulation, pose a significant risk to human life in the modern world. The FDA has recently approved several anticoagulant drugs targeting factor Xa (FXa) to manage these disorders. However, these drugs have potential side effects, leading to bleeding complications in patients. To mitigate these risks, coagulation factor IXa (FIXa) has emerged as a promising target due to its selective regulation of the intrinsic pathway. Due to the high structural and functional similarities of these coagulation factors and their inhibitor binding modes, designing a selective inhibitor specifically targeting FIXa remains a challenging task. The dynamic behavior of protein-ligand interactions and their impact on selectivity were analyzed using molecular dynamics simulation, considering the availability of potent and selective compounds for both coagulation factors and the co-crystal structures of protein-ligand complexes. Throughout the simulations, we examined ligand movements in the binding site, as well as the contact frequencies and interaction fingerprints, to gain insights into selectivity. Interaction fingerprint (IFP) analysis clearly highlights the crucial role of strong H-bond formation between the ligand and D189 and A190 in the S1 subsite for FIXa selectivity, consistent with our previous study. This dynamic analysis also reveals additional FIXa-specific interactions. Additionally, the absence of polar interactions contributes to the selectivity for FXa, as observed from the dynamic profile of interactions. A contact frequency analysis of the protein-ligand complexes provides further confirmation of the selectivity criteria for FIXa and FXa, as well as criteria for binding and activity. Moreover, a ligand movement analysis reveals key interaction dynamics that highlight the tighter binding of selective ligands to the proteins compared to non-selective and inactive ligands.

Exploring 3D community inconsistency in human chromosome contact networks

Abstract Researchers have developed chromosome capture methods such as Hi-C to better understand DNA’s 3D folding in nuclei. The Hi-C method captures contact frequencies between DNA segment pairs across the genome. When analyzing Hi-C data sets, it is common to group these pairs using standard bioinformatics methods (e.g. PCA). Other approaches handle Hi-C data as weighted networks, where connected node pairs represent DNA segments in 3D proximity. In this representation, one can leverage community detection techniques developed in complex network theory to group nodes into mesoscale communities containing nodes with similar connection patterns. While there are several successful attempts to analyze Hi-C data in this way, it is common to report and study the most typical community structure. But in reality, there are often several valid candidates. Therefore, depending on algorithm design, different community detection methods focusing on slightly different connectivity features may have differing views on the ideal node groupings. In fact, even the same community detection method may yield different results if using a stochastic algorithm. This ambiguity is fundamental to community detection and shared by most complex networks whenever interactions span all scales in the network. This is known as community inconsistency. This paper explores this inconsistency of 3D communities in Hi-C data for all human chromosomes. We base our analysis on two inconsistency metrics, one local and one global, and quantify the network scales where the community separation is most variable. For example, we find that TADs are less reliable than A/B compartments and that nodes with highly variable node-community memberships are associated with open chromatin. Overall, our study provides a helpful framework for data-driven researchers and increases awareness of some inherent challenges when clustering Hi-C data into 3D communities.

Mapping robust multiscale communities in chromosome contact networks

To better understand DNA’s 3D folding in cell nuclei, researchers developed chromosome capture methods such as Hi-C that measure the contact frequencies between all DNA segment pairs across the genome. As Hi-C data sets often are massive, it is common to use bioinformatics methods to group DNA segments into 3D regions with correlated contact patterns, such as Topologically associated domains and A/B compartments. Recently, another research direction emerged that treats the Hi-C data as a network of 3D contacts. In this representation, one can use community detection algorithms from complex network theory that group nodes into tightly connected mesoscale communities. However, because Hi-C networks are so densely connected, several node partitions may represent feasible solutions to the community detection problem but are indistinguishable unless including other data. Because this limitation is a fundamental property of the network, this problem persists regardless of the community-finding or data-clustering method. To help remedy this problem, we developed a method that charts the solution landscape of network partitions in Hi-C data from human cells. Our approach allows us to scan seamlessly through the scales of the network and determine regimes where we can expect reliable community structures. We find that some scales are more robust than others and that strong clusters may differ significantly. Our work highlights that finding a robust community structure hinges on thoughtful algorithm design or method cross-evaluation.

Experimental Study of Triboelectric Energy Harvesting for Different Pairs of Materials and under Various Contact Frequencies

Background: In order to harvest triboelectric energy for self-powered devices, triboelectric nanogenerator technology (TENG) is used. It converts mechanical energy into electrical energy using materials' contact motion. Objective: The purpose of this study is to produce electrical energy for different material pairs and under various contact frequencies using triboelectric separation mode. Methods: To produce electricity through triboelectric separation mode, a vibratory exciter was used to provide the contact frequency between the pairs of materials which were connected to an oscilloscope by a capacitive electric circuit containing a diode bridge. The studied materials are: Mica, Polyamide (Nylon), Polytetrafluoroethylene (PTFE), Polyvinylidene fluoride (PVDF), and Polyethylene terephthalate (PET). Mica and Nylon are positive charge materials, while PTFE, PVDF, and PET are negative charge materials. The material pairs are then: Nylon-PVC, Mica-PVC, Nylon-PET, Mica-PET, Nylon- PTFE, and Mica-PTFE. Results: The increase of the contact frequency improves the recovered electrical energy for all the material pairs. The produced electrical energy can reach 5μJ which allows supply for low consumption devices. Conclusion: The research results lead to identify favorable configurations of material pairs and contact frequencies, allowing to recover enough electrical energy supply to low-power devices.

Ultra-long-range interactions between active regulatory elements.

Contacts between enhancers and promoters are thought to relate to their ability to activate transcription. Investigating factors that contribute to such chromatin interactions is therefore important for understanding gene regulation. Here, we have determined contact frequencies between millions of pairs of cis-regulatory elements from chromosome conformation capture data sets and analyzed a collection of hundreds of DNA-binding factors for binding at regions of enriched contacts. This analysis revealed enriched contacts at sites bound by many factors associated with active transcription. We show that active regulatory elements, independent of cohesin and polycomb, interact with each other across distances of tens of megabases in vertebrate and invertebrate genomes and that interactions correlate and change with activity. However, these ultra-long-range interactions are not dependent on RNA polymerase II transcription or individual transcription cofactors. Using simulations, we show that a model of chromatin and multivalent binding factors can give rise to long-range interactions via bridging-induced clustering. We propose that long-range interactions between cis-regulatory elements are driven by at least three distinct processes: cohesin-mediated loop extrusion, polycomb contacts, and clustering of active regions.

Higher convergence of human-great ape enteric eukaryotic viromes in central African forest than in a European zoo: a One Health analysis

Human-animal pathogenic transmissions threaten both human and animal health, and the processes catalyzing zoonotic spillover and spillback are complex. Prior field studies offer partial insight into these processes but overlook animal ecologies and human perceptions and practices facilitating human-animal contact. Conducted in Cameroon and a European zoo, this integrative study elucidates these processes, incorporating metagenomic, historical, anthropological and great ape ecological analyses, and real-time evaluation of human-great ape contact types and frequencies. We find more enteric eukaryotic virome sharing between Cameroonian humans and great apes than in the zoo, virome convergence between Cameroonian humans and gorillas, and adenovirus and enterovirus taxa as most frequently shared between Cameroonian humans and great apes. Together with physical contact from hunting, meat handling and fecal exposure, overlapping human cultivation and gorilla pillaging in forest gardens help explain these findings. Our multidisciplinary study identifies environmental co-use as a complementary mechanism for viral sharing.