Biology subjects

Yu, H.

Publications and source records attributed to Yu, H..

485 records · Page 27Linked to original sources

bioRxiv2018

Local Polyploidy Phenomenon in Escherichia coli and its significance in genetic engineering

Classic Helmstetter & Cooper model asserted that the multifork phenomenon in the process of replication. However, the impacts of the multifork on the evolution and genetic engineering are still vague. Here, we employed CRISPR/Cas9 technology to knock-out eighteen Escherichia coli chromosomal fragments (over 50 kb) that represent all areas of the chromosome. We demonstrated that a single cell could have wild-type, color-reporter, and antibiotic-resistant genes simultaneously in the same locus of the different branches of the duplication forks after multiple rounds of deletions and replacements. This phenomenon that a single cell had different genotypes in its local polyploid chromosomes, which was similar to eukaryotic heterozygote, was named as local polyploidy. Under a defined selective pressure condition, offspring cells containing at least a copy of conditionally beneficial mutation could be enriched, and other alleles could be kept silently and peacefully in the duplication fork(s) of the same cell. The significance of this phenomenon in the genetic engineering was discussed.

microbiology↗

bioRxiv2018

A particle-filter framework for robust cryoEM 3D reconstruction

Electron cryo-microscopy (cryoEM) is now a powerful tool in determining atomic structures of biological macromolecules under nearly natural conditions. The major task of single-particle cryoEM is to estimate a set of parameters for each input particle image to reconstruct the three-dimensional structure of the macromolecules. As future large-scale applications require increasingly higher resolution and automation, robust high-dimensional parameter estimation algorithms need to be developed in the presence of various image qualities. In this paper, we introduced a particle-filter algorithm for cryoEM, which was a sequential Monte Carlo method for robust and fast high-dimensional parameter estimation. The cryoEM parameter estimation problem was described by a probability density function of the estimated parameters. The particle filter uses a set of random and weighted support points to represent such a probability density function. The statistical properties of the support points not only enhance the parameter estimation with self-adaptive accuracy but also provide the belief of estimated parameters, which is essential for the reconstruction phase. The implementation of these features showed strong tolerance to bad particles and enabled robust defocus refinement, demonstrated by the remarkable resolution improvement at the atomic level.

biophysics↗

bioRxiv2018

Impact of Chronic Total Occlusion Lesion Length onSix-month Angiographic and 2-year Clinical Outcomes

BackgroundSuccessful chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is known to be associated with improved clinical outcomes compared with failed CTO PCI. However, it is not clear whether the angiographic and clinical outcomes of long CTO lesionis different with those of short CTO lesion in the drug eluting stent (DES) era.\n\nMethod sand ResultsA total of 235 consecutive patients underwent successful CTO intervention were divided into two groups according the CTO lesion length. Six-month angiographic and two-year clinical outcomes were compared between the two groups. The baseline clinical characteristics were similar between the two groups except prior PCI was more frequent in long CTO group whereas bifurcation lesion was more frequent in the short CTO group. In-hospital complications were similar between the two groups except intimal dissection was more frequent in long CTO group. Both groups had similar angiographic outcomes at 6 months and clinical outcomes up to 2 years except the incidence of repeat PCI, predominantly target vessel revascularization (TVR) was higher in long CTO group. In multivariate analysis, long CTO was an important predictor for repeat PCI (OR;4.26, CI 1.53-11.9, p=0.006).\n\nConclusionThe safety profile, angiographic and 2-year clinical outcomes were similar between the two groups except higher incidence of repeat PCI in long CTO group despite of successful PCI with DESs.

physiology↗

bioRxiv2018

Inter-annual variation in seasonal dengue epidemics driven bymultiple interacting factors in Guangzhou, China

Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005-2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.

epidemiology↗

bioRxiv2018

Enhancement of Macrophage Function by the Antimicrobial Peptide Sublancin Protects Mice from Methicillin-Resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is the major pathogen responsible for community and hospital bacterial infections. Sublancin, a glocosylated antimicrobial peptide isolated from Bacillus subtilis 168, possesses anti-bacterial infective effects. In this study, we investigated the role and anti-infection mechanism of sublancin in a mouse model of MRSA-induced sublethal infection. Sublancin could modulate innate immunity by inducing the production of IL-1{beta}, IL-6, TNF- and nitric oxide, enhancing phagocytosis and MRSA-killing activity in both RAW264.7 cells and peritoneal macrophages. The enhanced macrophage function by the peptide in vitro correlated with stronger protective activity in vivo in the MRSA-invasive sublethal infection model. Macrophages activation by sublancin was found to be mediated through the TLR4 and the NF-{kappa}B and MAPK signaling pathways. Moreover, oral administration of sublancin increased the frequencies of CD4+ and CD8+ T cells in mesenteric lymph nodes. The protective activity of sublancin was associated with in vivo augmenting phagocytotic activity of peritoneal macrophages and partly improving T cell-mediated immunity. Macrophages thus represent a potentially pivotal and novel target for future development of innate defense regulator therapeutics againt S. aureus infection.

immunology↗

bioRxiv2018

Complex Interplay between Serum and Fibroblasts in 3D Hepatocyte Co-culture

Previous studies have suggested that primary hepatocytes cultured in vitro undergo a rapid loss of function. On the other hand, in the clinic, drug induced liver injury typically manifests 5 days to 3 months after starting a medication. Thus, novel approaches that can maintain the function of primary human hepatocytes for longer durations of time may enable the development of improved in vitro assays for detecting hepatotoxicity. Previous studies have demonstrated that two-dimensional micro-patterning of hepatocytes with fibroblasts leads to improved maintenance of the hepatocyte phenotype relative to hepatocyte monocultures, in serum containing medium. Additionally, we, and others, have shown that three-dimensional culture of hepatocytes leads to enhanced function (in serum-free medium). In this study we wanted to (i) examine the effect of combining the above two approaches on hepatocyte function, and (ii) to further delineate the effect of serum on hepatocyte function. We developed a user-friendly and inexpensive approach for constructing layered spheroids. Similar to previous results in two-dimensional (2d) culture, we observed that 3d culture of hepatocytes alone (i.e. monoculture) in serum-containing medium led to an increase in the urea production rate, but near-complete loss of cytochrome activity in both lots of primary human hepatocytes (PHH) tested. In serum-free sandwich culture, cytochrome activity was maintained at the level observed in freshly thawed PHH for one lot, but almost completely lost in another lot. Spheroid culture of both lots of PHH in serum-free medium led to maintenance of CYP3A4 and CYP1A2 activity at the fresh thaw level, though CYP2B6 activity was reduced. In contrast to PHH monoculture, co-cultures of PHH with NIH 3T3 fibroblast cells benefitted from the presence of serum, and led to 3-5-fold increases in CYP activity relative to even serum-free spheroid monocultures. Layering of the fibroblasts did not result in improvements over mixed co-cultures. These results indicate the importance of appropriate serum-free monoculture control experiments in the evaluation of novel biomaterials and techniques for hepatocyte co-culture. Further, urea production and cytochrome production are decoupled; therefore, urea production is an insufficient readout when developing models for pharmaceutical applications.

cell biology↗

bioRxiv2018

Structural and functional influences of urban and rural childhoods on the medial prefrontal cortex

Global increases in urbanization have brought dramatic economic, environmental and social changes. However, less is understood about how these may influence disease-related brain mechanisms underlying epidemiological observations that urban birth and childhoods may increase the risk for neuropsychiatric disorders, including increased social stress and depression. In a genetically homogeneous Han Chinese adult population with divergent urban and rural birth and childhoods, we examined the structural and functional MRI neural correlates of childhood urbanicity, focusing on behavioral traits responding to social status threats, and polygenic risk for depression. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhoods, however, were associated with higher trait anxiety-depression. On structural MRI, urban childhoods were associated with relatively reduced medial prefrontal gray matter volumes. Functional medial prefrontal engagement under social status threat during working memory correlated with trait anxiety-depression in subjects with urban childhoods, to a significantly greater extent than in their rural counterparts, implicating an exaggerated physiological response to the threat context. Stress-associated medial prefrontal engagement also interacted with polygenic risk for depression, significantly predicting a differential response in individuals with urban but not rural childhoods. Developmental urbanicity thus differentially influenced medial prefrontal structure and function, at least in part through mechanisms associated with the neural processing of social status threat, trait anxiety, and genetic risk for depression, which may be factors in the association of urbanicity with adult psychopathology.\n\nSignificance StatementUrban living has been associated with social inequalities and stress. However, less is understood about the neural underpinnings by which these stressors affect disease risk, and in particular, genetic risk for depression. Leveraging urbanization in China, we studied adults with diverse urban and rural upbringings, who were genetically homogeneous and with similar current socioeconomic status, to isolate the effects of childhood urbanicity. At medial prefrontal cortex, a region critical for processing emotional stressors and social status, genetic risk for depression resulted in more deleterious function under stress in individuals with urban, but not rural childhoods. This implicates medial prefrontal cortexs critical role in brain development, integrating genetic mechanisms of stress and depression with the childhood environment.

neuroscience↗

bioRxiv2018

Spatial gradient in activity within the insula reflects dissociable neural mechanisms underlying context-dependent advantageous and disadvantageous inequity aversion

Humans are capable of integrating social contextual information into decision-making processes to adjust their attitudes towards inequity. This context-dependency emerges both when individual is better off (i.e. advantageous inequity) and worse off (i.e. disadvantageous inequity) than others. It is not clear however, whether the context-dependent processing of advantageous and disadvantageous inequity rely on dissociable or shared neural mechanisms. Here, by combining an interpersonal interactive game that gave rise to interpersonal guilt and different versions of the dictator games that enabled us to characterize individual weights on aversion to advantageous and disadvantageous inequity, we investigated the neural mechanisms underlying the two forms of inequity aversion in the interpersonal guilt context. In each round, participants played a dot-estimation task with an anonymous co-player. The co-players received pain stimulation with 50% probability when anyone responded incorrectly. At the end of each round, participants completed a dictator game, which determined payoffs of him/herself and the co-player. Both computational model-based and model-free analyses demonstrated that when inflicting pain upon co-players (i.e., the guilt context), participants cared more about advantageous inequity and became less sensitive to disadvantageous inequity, compared with other social contexts. The contextual effects on two forms of inequity aversion are uncorrelated with each other at the behavioral level. Neuroimaging results revealed that the context-dependent representation of inequity aversion exhibited a spatial gradient in activity within the insula, with anterior parts predominantly involved in the aversion to advantageous inequity and posterior parts predominantly involved in the aversion to disadvantageous inequity. The dissociable mechanisms underlying the two forms of inequity aversion are further supported by the involvement of right dorsolateral prefrontal cortex and dorsomedial prefrontal cortex in advantageous inequity processing, and the involvement of right amygdala and dorsal anterior cingulate cortex in disadvantageous inequity processing. These results extended our understanding of decision-making processes involving inequity and the social functions of inequity aversion.

neuroscience↗

bioRxiv2017

Multiple interactions between Scc1 and Scc2 activate cohesin’s DNA dependent ATPase and replace Pds5 during loading

In addition to sharing with condensin an ability to organize DNA into chromatids, cohesin regulates enhancer-promoter interactions and confers sister chromatid cohesion. Association with chromosomes is regulated by hook-shaped HEAT repeat proteins that Associate With its Kleisin (Scc1) subunit (HAWKs), namely Scc3, Pds5, and Scc2. Unlike Pds5, Scc2 is not a stable cohesin constituent but, as shown here, transiently displaces Pds5 during loading. Scc1 mutations that compromise its interaction with Scc2 adversely affect cohesins ATPase activity, loading, and translocation while Scc2 mutations that alter how the ATPase responds to DNA abolish loading despite cohesins initial association with loading sites. Lastly, Scc2 mutations that permit loading in the absence of Scc4 increase Scc2s association with chromosomal cohesin and reduce that of Pds5. We suggest that cohesin switches between two states, one with Pds5 bound to Scc1 that is not able to hydrolyse ATP efficiently but is capable of release from chromosomes and another in which Scc2, transiently replacing Pds5, stimulates the ATP hydrolysis necessary for loading and translocation away from loading sites.

cell biology↗

bioRxiv2017

Type 2 diabetes promotes cell centrosome amplification and the role of AKT-ROS-dependent signalling of ROCK1 and 14-3-3σ

Type2 diabetes is associated with oxidative stress which can cause cell centrosome amplification. The study investigated centrosome amplification in type 2 diabetes and the underlying mechanisms. We found that centrosome amplification was increased in the peripheral blood mononuclear cells (PBMC) from the type 2 diabetic patients, which correlated with the levels of fasting blood glucose and HbA1c. High glucose, insulin and palmitic acid, alone or in combinations, induced ROS production and centrosome amplification. Together, they increased AKT activation as well as the expression, binding and centrosome translation of ROCK1 and 14-3-3{sigma}. Results from further analyses showed that AKT-ROS-dependent upregulations of expression, binding and centrosome translocation of ROCK1 and 14-3-3{sigma} was the molecular pathway underlying the centrosome amplification induced by high glucose, insulin and palmitic acid. Moreover, the increases in AKT activation and ROS production as well as expression, binding and centrosome distribution of ROCK1 and 14-3-3{sigma} were confirmed in the PBMC from the patients with type 2 diabetes. In conclusion, our results show that type 2 diabetes promotes cell centrosome amplification, and suggest that the diabetic pathophysiological factors-activated AKT-ROS-dependent signalling of ROCK1 and 14-3-3{sigma} is the underlying molecular mechanism.

cell biology↗

bioRxiv2017

Imaging action potential in single mammalian neurons by tracking the accompanying sub-nanometer mechanical motion

Action potentials in neurons have been studied traditionally by the patch clamp and more recently by the fluorescence detection methods. Here we describe a label-free optical imaging method that can measure mechanical motion in single cells with sub-nanometer detection limit and sub-millisecond temporal resolution. Using the method, we have observed sub-nanometer mechanical motion accompanying the action potential in single mammalian neurons. The shape and width of the transient displacement are similar to those of the electrically recorded action potential, but the amplitude varies from neuron to neuron, and from one region of a neuron to another, ranging from 0.2 - 0.4 nm. The work indicates that action potentials may be studied non-invasively in single mammalian neurons by label-free imaging of the accompanying subnanometer mechanical motion.

bioengineering↗

bioRxiv2017

Changing geographic patterns and risk factors for avian influenza A(H7N9) infection in China

The 5th epidemic wave in 2016-2017 of avian influenza A(H7N9) virus in China caused more human cases than any previous waves but the factors that may explain the recent range expansion and surge in incidence remain unknown. We investigated the effect of anthropogenic, poultry and wetland information and of market closures on all epidemic waves (1-5). Poultry predictor variables recently became much more important than before, supporting the assumption of much wider H7N9 transmission in the chicken reservoir, that could be linked to increases in pathogenicity. We show that the future range expansion of H7N9 to northern China may translate into a higher risk of coinciding peaks with those of seasonal influenza, leading to a higher risk of reassortments. Live-poultry market closures are showed to be effective in reducing the local incidence rates of H7N9 human cases, but should be paired with other prevention and control measures to prevent transmission.

epidemiology↗

bioRxiv2017

Root Interactions And Plant Growth In A Tomato/Potato Onion Intercropping System Under Different Phosphorus Levels

Intercropping systems have been implemented in many parts of the world due to their beneficial effects on yield and biomass. In intercropping systems, changes in plant growth are usually related to variations in root distribution and phosphorus (P) levels, however, root distributions and root tendencies are difficult to study, as root systems grow beneath the soil surface. Therefore, we have a relatively poor understanding of the relationship between plant root interactions and plant growth in intercropping systems. In this study, a custom apparatus consisting of a transparent manual root box was used to observe intact root systems in situ. We investigated how root distribution and root tendency changed in a tomato/potato onion intercropping system under two P treatments, and how tomato plant growth was influenced. The results showed that the shoot and total biomass for the tomato plants were increased by intercropping with potato onion plants under both tested P levels, the root distribution of intercropped tomato plants was deeper than that of monocultured plants, and the tomato roots tended to grow away from the potato onion roots. Our research reveals that a deeper and more evasive root distribution is more conductive to the plant growth of the intercropped tomato.\n\nSUMMARY STATEMENTOur study can help more people clearly know the relationship between the root interactions and plant growth in mixed cultures.

ecology↗

bioRxiv2017

Systematic Analysis Of RNA-Seq-Based Gene Co-Expression Across Multiple Plants

The complex cellular network was formed by the interacting gene modules. Building the high-quality RNA-seq-based Gene Co-expression Network (GCN) is critical for uncovering these modules and understanding the phenotypes of an organism. Here, we established and analyzed the RNA-seq-based GCNs in two monocot species rice and maize, and two eudicot species Arabidopsis and soybean, and subdivided them into co-expressed modules. Taking rice as an example, we associated these modules with biological functions and agronomic traits by enrichment analysis, and discovered a large number of conditin-specific or tissue-specific modules. In addition, we also explored the regulatory mechanism of the modules by enrichment of the known cis-elements, transcription factors and miRNA targets. Their coherent enrichment with the inferred functions of the modules revealed their synergistic effect on the gene expression regulation. Moreover, the comparative analysis of gene co-expression was performed to identify conserved and species-specific functional modules across 4 plant species. We discovered that the modules shared across 4 plants participate in the basic biological processes, whereas the species-specific modules were involved in the spatiotemporal-specific processes linking the genotypes to phenotypes. Our research provides the massive modules relating to the cellular activities and agronomic traits in several model and crop plant species.

bioinformatics↗

bioRxiv2017

High-Quality Rice RNA-Seq-Based Co-Expression Network For Predicting Gene Function And Regulation

Inferring the genome-scale gene co-expression network is important for understanding genetic architecture underlying the complex and various biological phenotypes. The recent availability of large-scale RNA-seq sequencing-data provides great potential for co-expression network inference. In this study, for the first time, we presented a novel heterogeneous ensemble pipeline integrating three frequently used inference methods, to build a high-quality RNA-seq-based Gene Co-expression Network (GCN) in rice, an important monocot species. The quality of the network obtained by our proposed method was first evaluated and verified with the curated positive and negative gene functional link datasets, which obviously outperformed each single method. Secondly, the powerful capability of this network for associating unknown genes with biological functions and agronomic traits was showed by enrichment analysis and case studies. Particularly, we demonstrated the potential applications of our proposed method to predict the biological roles of long non-coding RNA (lncRNA) and circular RNA (circRNA) genes. Our results provided a valuable data source for selecting candidate genes to further experimental validation during rice genetics research and breeding. To enhance identification of novel genes regulating important biological processes and agronomic traits in rice and other crop species, we released the source code of constructing high-quality RNA-seq-based GCN and rice RNA-seq-based GCN, which can be freely downloaded online at https://github.com/czllab/NetMiner.

bioinformatics↗

bioRxiv2017

Genomic Relatedness Strengthens Genetic Connectedness Across Management Units

Genetic connectedness refers to a measure of genetic relatedness across management units (e.g., herds and flocks). With the presence of high genetic connectedness in management units, best linear unbiased prediction (BLUP) is known to provide reliable comparisons between genetic values. Genetic connectedness has been studied for pedigree-based BLUP; however, relatively little attention has been paid to using genomic information to measure connectedness. In this study, we assessed genome-based connectedness across management units by applying prediction error variance of difference (PEVD), coefficient of determination (CD), and prediction error correlation (r) to a combination of computer simulation and real data (mice and cattle). We found that genomic information (G) increased the estimate of connectedness among individuals from different management units compared to that based on pedigree (A). A disconnected design benefited the most. In both datasets, PEVD and CD statistics inferred increased connectedness across units when using G- rather than A-based relatedness suggesting stronger connectedness. With r once using allele frequencies equal to one-half or scaling G to values between 0 and 2, which is intrinsic to A, connectedness also increased with genomic information. However, PEVD occasionally increased, and r decreased when obtained using the alternative form of G, instead suggesting less connectedness. Such inconsistencies were not found with CD. We contend that genomic relatedness strengthens measures of genetic connectedness across units and has the potential to aid genomic evaluation of livestock species.\n\nThe problem of connectedness or disconnectedness is particularly important in genetic evaluation of managed populations such as domesticated livestock. When selecting among animals from different management units (e.g., herds and flocks), caution is needed; choosing one animal over others across management units may be associated with greater uncertainty than selection within management units. Such uncertainty is reduced if individuals from different management units are genetically linked or connected. In such a case, best linear unbiased prediction (BLUP) offers meaningful comparison of the breeding values across management units for genetic evaluation (e.g., Kuehn et al., 2007).\n\nStructures of breeding programs have a direct influence on levels of connectedness. Wide use of artificial insemination (AI) programs generally increases genetic connectedness across management units. For example, dairy cattle populations are considered highly connected due to dissemination of genetic material from a small number of highly selected sires. The situation may be different for species with less use of AI and more use of natural service mating such as for beef cattle or sheep populations. Under these scenarios, the magnitude of connectedness across management units is reduced and genetic links are largely confined within management units.\n\nPedigree-based genetic connectedness has been evaluated and applied in practice (e.g., Kuehn et al., 2009; Eikje and Lewis, 2015). However, there is a relative paucity of use of genomic information such as single nucletide polymorphisms (SNPs) to ascertain connectedness. It still remains elusive in what scenarios genomics can strengthen connectedness and how much gain can be expected relative to use of pedigree information alone. Connectedness statistics have been used to optimize selective genotyping and phenotyping in simulated livestock (Pszczola et al., 2012) and plant populations (Maenhout et al., 2010), and in real maize (Rincent et al., 2012; Isidro et al., 2015), and real rice data (Isidro et al., 2015). These studies concluded that the greater the connectedness between the reference and validation populations, the greater the predictive performance. However, 1) connectedness among different management units and 2) differences in connectedness measures between pedigree and genomic relatedness were not explored in those studies. For better understanding of genome-based connectedness, it is critical to examine how the presence of management units comes into play. For instance, genomic relatedness provides relationships between distant individuals that appear disconnected according to the pedigree information. In addition, it captures Mendelian sampling that is not present in pedigree relationships (Hill and Weir, 2011). Thus, genomic information is expected to strengthen measures of connectedness, which in turn refines comparisons of genetic values across different management units. The objective of this study was to assess measures of genetic connectedness across management units with use of genomic information. We leveraged the combination of real data and computer simulation to compare gains in measures of connectedness when moving from pedigree to genomic relationships. First, we studied a heterogenous mice dataset stratified by cage. Then we investigated approaches to measure connectedness using real cattle data coupled with simulated management units to have greater control over the degree of confounding between fixed management groups and genetic relationships.

genetics↗

bioRxiv2017

Interactome INSIDER: A Multi-Scale Structural Interactome Browser For Genomic Studies

Protein interactions underlie nearly all known cellular function, making knowledge of their binding conformations paramount to understanding the physical workings of the cell. Studying binding conformations has allowed scientists to explore some of the mechanistic underpinnings of disease caused by disruption of protein interactions. However, since experimentally determined interaction structures are only available for a small fraction of the known interactome such inquiry has largely excluded functional genomic studies of the human interactome and broad observations of the inner workings of disease. Here we present Interactome INSIDER, an information center for genomic studies using the first full-interactome map of human interaction interfaces. We applied a new, unified framework to predict protein interaction interfaces for 184,605 protein interactions with previously unresolved interfaces in human and 7 model organisms, including the entire experimentally determined human binary interactome. We find that predicted interfaces share several known functional properties of interfaces, including an enrichment for disease mutations and recurrent cancer mutations, suggesting their applicability to functional genomic studies. We also performed 2,164 de novo mutagenesis experiments and show that mutations of predicted interface residues disrupt interactions at a similar rate to known interface residues and at a much higher rate than mutations outside of predicted interfaces. To spur functional genomic studies in the human interactome, Interactome INSIDER (http://interactomeinsider.yulab.org) allows users to explore known population variants, disease mutations, and somatic cancer mutations, or upload their own set of mutations to find enrichment at the level of protein domains, residues, and 3D atomic clustering in known and predicted interaction interfaces.

genomics↗