Pairwise Contacts Research Articles

Protein language models learn evolutionary statistics of interacting sequence motifs

Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an open question. Motivated by a finding that pLM-based structure predictors erroneously predict nonphysical structures for protein isoforms, we investigated the nature of sequence context needed for contact predictions in the pLM Evolutionary Scale Modeling (ESM-2). We demonstrate by use of a "categorical Jacobian" calculation that ESM-2 stores statistics of coevolving residues, analogously to simpler modeling approaches like Markov Random Fields and Multivariate Gaussian models. We further investigated how ESM-2 "stores" information needed to predict contacts by comparing sequence masking strategies, and found that providing local windows of sequence information allowed ESM-2 to best recover predicted contacts. This suggests that pLMs predict contacts by storing motifs of pairwise contacts. Our investigation highlights the limitations of current pLMs and underscores the importance of understanding the underlying mechanisms of these models.

PartwiseMPC: Interactive Control of Contact‐Guided Motions

AbstractPhysics‐based character motions remain difficult to create and control. We make two contributions towards simpler specification and faster generation of physics‐based control. First, we introduce a novel partwise model predictive control (MPC) method that exploits independent planning for body parts when this proves beneficial, while defaulting to whole‐body motion planning when that proves to be more effective. Second, we introduce a new approach to motion specification, based on specifying an ordered set of contact keyframes. These each specify a small number of pairwise contacts between the body and the environment, and serve as loose specifications of motion strategies. Unlike regular keyframes or traditional trajectory optimization constraints, they are heavily under‐constrained and have flexible timing. We demonstrate a range of challenging contact‐rich motions that can be generated online at interactive rates using this framework. We further show the generalization capabilities of the method.

MDB-19. THE 3D CHROMATIN LANDSCAPE OF MEDULLOBLASTOMA

Abstract BACKGROUND Medulloblastoma (MB) is a highly malignant childhood cerebellar tumor comprised of four molecularly and clinically distinct subgroups. Sporadic yet subgroup-specific genetic and epigenetic landscapes suggest that higher-order chromatin topology may contribute to distinct subgroup identities and disease biology. Herein, we investigated the 3D chromatin landscape of MB by performing genome-wide chromosome conformation capture (Hi-C) across molecular subgroups using a cohort of n=24 patient-derived xenografts and primary tumor specimens, aiming to elucidate regulatory mechanisms facilitated by genome organization. METHODS Integrative analyses were adapted to incorporate a wide variety of sample-paired datasets. Chromatin contact matrices generated from Hi-C allowed for the mapping of active/inactive compartments (A/B compartments), topologically associated domains (TADs), and distal pairwise chromatin contacts (loops). Topological insights of chromatin architecture were complemented with whole-genome sequencing, RNA-seq, ATAC-seq, DNA methylation, CTCF and histone modification (H3K27ac/H3K27me3) ChIP-seq datasets to dissect mechanisms of gene regulation. RESULTS Unsupervised analysis revealed that chromatin compartmentalization is subgroup stratified. Gene loci contained in subgroup-unique active compartments correspondingly exhibited subgroup-specific chromatin contact patterns, adopted open chromatin conformations, and remained transcriptionally active. As an example, LIN28B resides within a Group 3-specific ‘A’ compartment where its local topology displays higher complexity compared to that of other subgroups. This consequentially facilitates a Group 3-unique loop connecting the LIN28B promoter with a distal enhancer, resulting in subgroup-specific transcriptional upregulation. Targeted displacement of CTCF that anchors and stabilizes chromatin looping at the LIN28B locus was sufficient to alter its transcriptional activity. Using similar lines of investigation, mechanistic insights into the topological determinants of known enhancer-hijacking events, including GFI1, GFI1B and PRDM6, were resolved. CONCLUSIONS Pioneering this integrative approach centered on comprehensive Hi-C maps, our study provides a high-resolution blueprint of the 3D chromatin landscape defining MB subgroups, informing the mechanistic basis of recurrent driver gene activation, and disclosing putative subgroup-specific vulnerabilities.

Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder.

Recent advances in chromatin conformation capture technologies, such as SPRITE and Pore-C, have enabled the detection of simultaneous contacts among multiple chromatin loci. This has made it possible to investigate the cooperative transcriptional regulation involving multiple genes and regulatory elements at the resolution of a single molecule. However, these technologies are unavoidably subject to the random polymer looping effect and technical biases, making it challenging to distinguish genuine regulatory relationships directly from random polymer interactions. Here, we present HyperloopFinder, a method for identifying regulatory multi-way chromatin contacts (hyperloops) by jointly modeling the random polymer looping effect and technical biases to estimate the statistical significance of multi-way contacts. The results show that our model can accurately estimate the expected interaction frequency of multi-way contacts based on the distance distribution of pairwise contacts, revealing that most multi-way contacts can be formed by randomly linking the pairwise contacts adjacent to each other. Moreover, we observed the spatial colocalization of the interaction sites of hyperloops from image-based data. Our results also revealed that hyperloops can function as scaffolds for the cooperation among multiple genes and regulatory elements. In summary, our work contributes novel insights into higher-order chromatin structures and functions and has the potential to enhance our understanding of transcriptional regulation and other cellular processes.

III. Geometrical framework for thinking about globular proteins: Turns in proteins.

We have shown recently that the notion of poking pairwise interactions along a chain provides a unifying framework for understanding the formation of both secondary and the tertiary protein structure based on symmetry and geometry. α-helices and β-sheets are found to be special geometries that have systematic poking contacts in a repetitive manner with the contacts being local along the α-helix and non-local along a pair of adjacent strands within a β-sheet. Pairwise poking interactions also govern tertiary structure formation, but they are weaker and there are no special geometrical constraints as in secondary structure formation. Here we demonstrate that protein turns, the most prevalent non-repetitive structural element in proteins, are instances of local (as in α-helices) and isolated (non-repetitive) poking pairwise contacts for which the geometrical constraints are partially relaxed. This simple and purely geometrical definition of protein turns (also sometimes known as reverse turns, β-turns, β-bends, hairpin bends, 310 bends, kinks, widgets, etc.) provides a simple framework for unifying them. We present the results of a systematic analysis and identify their structural classes as well as their respective amino acid preferences.

Epidemic trajectories and awareness diffusion among unequals in simplicial complexes

The interplay between awareness diffusion and epidemic spreading has been an active topic of research in recent years. Studies have shown that group interactions are an important consideration in contagion processes, and that thus higher-order interactions should be introduced into epidemic modeling. Research has also shown that individual responses to an unfolding epidemic are often strongly heterogeneous. We therefore present a two-layer network model, where the diffusion of awareness unfolds over 2-simplicial complexes in one layer, and the actual epidemic spreading unfolds over pairwise physical contacts in the other layer. The model takes into account individual differences in the degree of acceptance of information and self-protection measures once the epidemic is perceived. We use the micro Markov chain approach to determine the epidemic threshold of the model, which agrees well with the results obtained by Monte Carlo simulations. We show that the synergistic reinforcement due to 2-simplicial complexes in the virtual layer can restrain epidemic spreading by facilitating awareness diffusion, and moreover, that individual heterogeneity in the physical layer can increase the epidemic threshold and decrease the size of epidemic transmission. However, heterogeneity in the perception can also have the opposite effect because it inhibits the diffusion of awareness. Our results reveal the intricate interplay between awareness diffusion and epidemic spreading, and we hope they can help determine effective control measures.

Exploiting Kinematic Redundancy for Robotic Grasping of Multiple Objects

Humans coordinate the abundant degrees of freedom (DoFs) of hands to dexterously perform tasks in everyday life. We imitate human strategies to advance the dexterity of multi-DoF robotic hands. Specifically, we enable a robot hand to grasp multiple objects by exploiting its kinematic redundancy, referring to all its controllable DoFs. We propose a human-like grasp synthesis algorithm to generate grasps using pairwise contacts on arbitrary opposing hand surface regions, no longer limited to fingertips or hand inner surface. To model the available space of the hand for grasp, we construct a reachability map, consisting of reachable spaces of all finger phalanges and the palm. It guides the formulation of a constrained optimization problem, solving for feasible and stable grasps. We formulate an iterative process to empower robotic hands to grasp multiple objects in sequence. Moreover, we propose a kinematic efficiency metric and an associated strategy to facilitate exploiting kinematic redundancy. We validated our approaches by generating grasps of single and multiple objects using various hand surface regions. Such grasps can be successfully replicated on a real robotic hand.

Risky business: relating probability of direct contact to risk of chronic wasting disease

Chronic wasting disease (CWD) is a fatal, prion disease of cervids that was first detected in Alberta in 2005. Transmission of CWD by direct contact with infected individuals plays a major role in the early phases of an outbreak. Mule deer (Odocoileus hemionus) comprise 85% of CWD-infected animals in the province, and we investigated the seasonal effects of grouping patterns and landscape heterogeneity on direct, pair-wise contacts (distance of 3 m) within and between sex-specific (same or mixed sex) groups of mule deer in east-central Alberta. We determined seasonal contacts of mule deer based on proximity loggers that alter GPS schedules to record contact locations. We modeled the relative risk of contact between sex-specific dyads both within and between social groups based on landscape characteristics at the location of contact. We then assessed the support for 5 hypotheses that linked locations of seasonal contacts to occurrence of CWD on the landscape. Disease occurrence on the landscape was derived by comparing locations of CWD-infected and CWD-uninfected deer collected as part of the Alberta’s CWD hunter-harvest surveillance program. We found that contacts in winter occurred in areas where deer use was concentrated, whereas in summer, contact locations were less constrained in space where patterns of landscape characteristics at contact locations varied between sex-specific dyads. Contact probabilities of within and between-group male dyads in winter and between-group female dyads in summer were the best predictors of CWD risk in east-central Alberta. Our results relate habitat specific, social behaviors between conspecific mule deer to potential routes of CWD transmission and contribute to CWD research that guides management strategies for an emergent wildlife disease.

Molecular determinants of μ-conotoxin KIIIA interaction with the human voltage-gated sodium channel NaV1.7.

The voltage-gated sodium (NaV) channel subtype NaV1.7 plays a critical role in pain signaling, making it an important drug target. Here we studied the molecular interactions between μ-Conotoxin KIIIA (KIIIA) and the human NaV1.7 channel (hNaV1.7). We developed a structural model of hNaV1.7 using Rosetta computational modeling and performed in silico docking of KIIIA using RosettaDock to predict residues forming specific pairwise contacts between KIIIA and hNaV1.7. We experimentally validated these contacts using mutant cycle analysis. Comparison between our KIIIA-hNaV1.7 model and the cryo-EM structure of KIIIA-hNaV1.2 revealed key similarities and differences between NaV channel subtypes with potential implications for the molecular mechanism of toxin block. The accuracy of our integrative approach, combining structural data with computational modeling, experimental validation, and molecular dynamics simulations, suggests that Rosetta structural predictions will be useful for rational design of novel biologics targeting specific NaV channels.

Does multi-way, long-range chromatin contact data advance 3D genome reconstruction?

BackgroundMethods for inferring the three-dimensional (3D) configuration of chromatin from conformation capture assays that provide strictly pairwise interactions, notably Hi-C, utilize the attendant contact matrix as input. More recent assays, in particular split-pool recognition of interactions by tag extension (SPRITE), capture multi-way interactions instead of solely pairwise contacts. These assays yield contacts that straddle appreciably greater genomic distances than Hi-C, in addition to instances of exceptionally high-order chromatin interaction. Such attributes are anticipated to be consequential with respect to 3D genome reconstruction, a task yet to be undertaken with multi-way contact data. However, performing such 3D reconstruction using distance-based reconstruction techniques requires framing multi-way contacts as (pairwise) distances. Comparing approaches for so doing, and assessing the resultant impact of long-range and multi-way contacts, are the objectives of this study.ResultsWe obtained 3D reconstructions via multi-dimensional scaling under a variety of weighting schemes for mapping SPRITE multi-way contacts to pairwise distances. Resultant configurations were compared following Procrustes alignment and relationships were assessed between associated Procrustes root mean square errors and key features such as the extent of multi-way and/or long-range contacts. We found that these features had surprisingly limited influence on 3D reconstruction, a finding we attribute to their influence being diminished by the preponderance of pairwise contacts.ConclusionDistance-based 3D genome reconstruction using SPRITE multi-way contact data is not appreciably affected by the weighting scheme used to convert multi-way interactions to pairwise distances.

Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing.

High-order three-dimensional (3D) interactions between more than two genomic loci are common in human chromatin, but their role in gene regulation is unclear. Previous high-order 3D chromatin assays either measure distant interactions across the genome or proximal interactions at selected targets. To address this gap, we developed Pore-C, which combines chromatin conformation capture with nanopore sequencing of concatemers to profile proximal high-order chromatin contacts at the genome scale. We also developed the statistical method Chromunity to identify sets of genomic loci with frequencies of high-order contacts significantly higher than background ('synergies'). Applying these methods to human cell lines, we found that synergies were enriched in enhancers and promoters in active chromatin and in highly transcribed and lineage-defining genes. In prostate cancer cells, these included binding sites of androgen-driven transcription factors and the promoters of androgen-regulated genes. Concatemers of high-order contacts in highly expressed genes were demethylated relative to pairwise contacts at the same loci. Synergies in breast cancer cells were associated with tyfonas, a class of complex DNA amplicons. These results rigorously link genome-wide high-order 3D interactions to lineage-defining transcriptional programs and establish Pore-C and Chromunity as scalable approaches to assess high-order genome structure.

Engineered Metal-Binding Sites to Probe Protein Folding Transition States: Psi Analysis.

The formation of the transition state ensemble (TSE) represents the rate-limiting step in protein folding. The TSE is the least populated state on the pathway, and its characterization remains a challenge. Properties of the TSE can be inferred from the effects on folding and unfolding rates for various perturbations. A difficulty remains on how to translate these kinetic effects to structural properties of the TSE. Several factors can obscure the translation of point mutations in the frequently used method, "mutational Phi analysis." We take a complementary approach in "Psi analysis," employing rationally inserted metal binding sites designed to probe pairwise contacts in the TSE. These contacts can be confidently identified and used to construct structural models of the TSE. The method has been applied to multiple proteins and consistently produces a considerably more structured and native-like TSE than Phi analysis. This difference has significant implications to our understanding of protein folding mechanisms. Here we describe the application of the method and discuss how it can be used to study other conformational transitions such as binding.

MrFbP: Markov random field‐driven spatial entropy‐based routing protocol in opportunistic networks

SummaryRecently, research towards technologies associated with the 5G communication is in full operation. Amongst these enabling technologies, device‐to‐device(D2D) communication is one of the critical factors for scaling up the network efficiency in 5G communication. Intermittent connections due to higher mobility lead to frequent path breaks, and hence a mobility‐based opportunistic routing is suitable enough to control the forwarding process. Opportunistic networks (OppNet) use the pairwise opportunistic contacts and higher mobility to rely on the store‐carry and forward mechanism for routing purpose. In this work, a novel mobility‐induced context‐based routing process has been designed to support D2D communication. The designed Markov random field‐induced protocol (MrFbP) is based on spatial entropy for capturing the coverage span of the forwarding node in the network. The work relies on the monitored historic mobility of a node and is then used to capture the utility metric for taking forwarding decision. MrFbP is compared against the established Direct Delivery (DD), Epidemic (EP), Spray & Wait (SW), and PropHet (PR) on parameters like throughput, delay, hops, overheads, and energy consumption. Simulation has been carried out using ONE simulator to validate an improvement in the design of a designed protocol against the baseline protocols.

Four-dimensional chromosome reconstruction elucidates the spatiotemporal reorganization of the mammalian X chromosome

Chromosomes are segmented into domains and compartments, but how these structures are spatially related in three dimensions (3D) is unclear. Here, we developed tools that directly extract 3D information from Hi-C experiments and integrate the data across time. With our "4DHiC" method, we use X chromosome inactivation (XCI) as a model to examine the time evolution of 3D chromosome architecture during large-scale changes in gene expression. Our modeling resulted in several insights. Both A/B and S1/S2 compartments divide the X chromosome into hemisphere-like structures suggestive of a spatial phase-separation. During the XCI, the X chromosome transits through A/B, S1/S2, and megadomain structures by undergoing only partial mixing to assume new structures. Interestingly, when an active X chromosome (Xa) is reorganized into an inactive X chromosome (Xi), original underlying compartment structures are not fully eliminated within the Xi superstructure. Our study affirms slow mixing dynamics in the inner chromosome core and faster dynamics near the surface where escapees reside. Once established, the Xa and Xi resemble glassy polymers where mixing no longer occurs. Finally, Xist RNA molecules initially reside within the A compartment but transition to the interface between the A and B hemispheres and then spread between hemispheres via both surface and core to establish the Xi.

Using video-analysis technology to estimate social mixing and simulate influenza transmission at a mass gathering

Mass gatherings create settings conducive to infectious disease transmission. Empirical data to model infectious disease transmission at mass gatherings are limited. Video-analysis technology could be used to generate data on social mixing patterns needed for simulating influenza transmission at mass gatherings. We analyzed short video recordings of persons attending the GameFest event at a university in Troy, New York, in April 2013 to demonstrate the feasibility of this approach. Attendees were identified and tracked during three randomly selected time periods using an object-tracking algorithm. Tracks were analyzed to calculate the number and duration of unique pairwise contacts. A contact occurred each time two attendees were within 2 m of each other. We built and tested an agent-based stochastic influenza simulation model assuming two scenarios of mixing patterns in a geospatially accurate representation of the event venue —one calibrated to the mean cumulative contact duration estimated from GameFest video recordings and the other using a uniform mixing pattern. We compared one-hour attack rates (i.e., becoming infected) generated from these two scenarios following the introduction of a single infectious seed. Across the video recordings, 278 attendees were identified and tracked, resulting in 1,247 unique pairwise contacts with a cumulative mean contact duration of 74.76 s (SD: 80.71). The one-hour simulated mean attack rates were 2.17 % (95 % CI:1.45 – 2.82) and 0.21 % (95 % CI: 0.14 – 0.28) in the calibrated and uniform mixing model scenarios, respectively. We simulated influenza transmission at the GameFest event using social mixing data objectively captured through video-analysis technology. Microlevel geospatially accurate simulations can be used to assess the layout of event venues on social mixing and disease transmission. Future work can expand on this demonstration project to larger spatial and temporal scenes in more diverse settings.

Evolving Nature of Human Contact Networks with Its Impact on Epidemic Processes

Human contact networks constitute a multitude of individuals and pairwise contacts among them. However, the dynamic nature, which generates the evolution of human contact networks, of contact patterns is unknown yet. Here, we analyse three empirical datasets and identify two crucial mechanisms of the evolution of temporal human contact networks, i.e., the activity state transition laws for an individual to be socially active and the contact establishment mechanism that active individuals adopt. We consider both of the two mechanisms to propose a temporal network model, the so-called memory-driven (MD) model, of human contact networks. Then, we study the susceptible-infected (SI) spreading processes on empirical human contact networks as well as four corresponding temporal network models and compare the full prevalence time of SI processes with various infection rates on the networks. The full prevalence time of SI processes in the MD model is the same as that in real-world human contact networks. Moreover, we find that the individual activity state transition promotes the spreading process, while the contact establishment of active individuals suppresses the prevalence. Besides, we observe that individuals who establish social ties with a small exploring rate are still able to induce an endemic which prevails in the networks. The study offers new insights to predict and control the diffusion processes on networks.

Inferring chromosome radial organization from Hi-C data

BackgroundThe nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations.ResultsA number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells.ConclusionsOur analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.

Protein Conformational States-A First Principles Bayesian Method.

Automated identification of protein conformational states from simulation of an ensemble of structures is a hard problem because it requires teaching a computer to recognize shapes. We adapt the naïve Bayes classifier from the machine learning community for use on atom-to-atom pairwise contacts. The result is an unsupervised learning algorithm that samples a ‘distribution’ over potential classification schemes. We apply the classifier to a series of test structures and one real protein, showing that it identifies the conformational transition with >95% accuracy in most cases. A nontrivial feature of our adaptation is a new connection to information entropy that allows us to vary the level of structural detail without spoiling the categorization. This is confirmed by comparing results as the number of atoms and time-samples are varied over 1.5 orders of magnitude. Further, the method’s derivation from Bayesian analysis on the set of inter-atomic contacts makes it easy to understand and extend to more complex cases.

Multi-contact 4C: long-molecule sequencing of complex proximity ligation products to uncover local cooperative and competitive chromatin topologies.

We present the experimental protocol and data analysis toolbox for multi-contact 4C (MC-4C), a new proximity ligation method tailored to study the higher-order chromatin contact patterns of selected genomic sites. Conventional chromatin conformation capture (3C) methods fragment proximity ligation products for efficient analysis of pairwise DNA contacts. By contrast, MC-4C is designed to preserve and collect large concatemers of proximity ligated fragments for long-molecule sequencing on an Oxford Nanopore or Pacific Biosciences platform. Each concatemer of proximity ligation products represents a snapshot topology of a different individual allele, revealing its multi-way chromatin interactions. By inverse PCR with primers specific for a fragment of interest (the viewpoint) and DNA size selection, sequencing is selectively targeted to thousands of different complex interactions containing this viewpoint. A tailored statistical analysis toolbox is able to generate background models and three-way interaction profiles from the same dataset. These profiles can be used to distinguish whether contacts between more than two regulatory sequences are mutually exclusive or, conversely, simultaneously occurring at chromatin hubs. The entire procedure can be completed in 2 w, and requires standard molecular biology and data analysis skills and equipment, plus access to a third-generation sequencing platform.

How the node’s vital and tie strength effect rumor spreading on social network

The spread of rumors on complex networks has attracted wide attention in the field of management. In this paper, the generalized rumor spreading model is modified to take into account the vital of the spreader and the tie strength for the pairwise contacts between nodes in complex networks at degree-dependent spreading rate. Concretely, we introduce the infectivity exponent [Formula: see text], and the degree influenced real exponent [Formula: see text] into the analytical rumor spreading model. Rumor infectivity, [Formula: see text], where [Formula: see text], defines that each spreader node may contact [Formula: see text] neighbors within one time step. The tie strength between two nodes with degrees [Formula: see text] and [Formula: see text] are measured by [Formula: see text], [Formula: see text] is the degree influenced real exponent which depends on the type of complex networks and [Formula: see text] is a positive quantity. We use a tuning parameter [Formula: see text] to combine both the effect of the vital nodes and the strength of connectivity between nodes. We use analytical and numerical solutions to examine the threshold behavior and dynamics of the model on several models of social network. It was found that the infectivity exponent [Formula: see text], the degree influenced real exponent [Formula: see text] and tuning parameter [Formula: see text] affect the rumor threshold, one can adjust the parameters to control the rumor threshold which is absent for the standard rumor spreading model.