Prediction of Functionally Important Phospho-Regulatory Events in Xenopus laevis Oocytes

Global post-translational modification profiling of HIV-1-infected cells reveals mechanisms of host cellular pathway remodeling

Viruses must effectively remodel host cellular pathways to replicate and evade immune defenses, and they must do so with limited genomic coding capacity. Targeting post-translational modification (PTM) pathways provides a mechanism by which viruses can broadly and rapidly transform a hostile host environment into a hospitable one. We use mass spectrometry-based proteomics to quantify changes in protein abundance and two PTM types-phosphorylation and ubiquitination-in response to HIV-1 infection with viruses harboring targeted deletions of a subset of HIV-1 genes. PTM analysis reveals a requirement for Aurora kinase activity in HIV-1 infection and identified putative substrates of a phosphatase that is degraded during infection. Finally, we demonstrate that the HIV-1 Vpr protein inhibits histone H1 ubiquitination, leading to defects in DNA repair.

Enhancing the Discovery of Functional Post-Translational Modification Sites with Machine Learning Models - Development, Validation, and Interpretation

Protein posttranslational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functionals PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Computational approaches that can confidently recommend PTMs of probable function can improve the heuristics of PTM investigation and alleviate these problems. To address this need, we developed SAPH-ire: a multifeature heuristic neural network model that takes community wisdom into account by recommending experimental PTMs similar to those which have previously been established as having regulatory impact. Here, we describe the principle behind the SAPH-ire model, how it is developed, how we evaluate its performance, and important caveats to consider when building and interpreting such models. Finally, we discus current limitations of functional PTM prediction models and highlight potential mechanisms for their improvement.

ConsRM: collection and large-scale prediction of the evolutionarily conserved RNA methylation sites, with implications for the functional epitranscriptome

Motivation N6-methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. Evidence increasingly demonstrates its crucial importance in essential molecular mechanisms and various diseases. With recent advances in sequencing techniques, tens of thousands of m6A sites are identified in a typical high-throughput experiment, posing a key challenge to distinguish the functional m6A sites from the remaining 'passenger' (or 'silent') sites. Results: We performed a comparative conservation analysis of the human and mouse m6A epitranscriptomes at single site resolution. A novel scoring framework, ConsRM, was devised to quantitatively measure the degree of conservation of individual m6A sites. ConsRM integrates multiple information sources and a positive-unlabeled learning framework, which integrated genomic and sequence features to trace subtle hints of epitranscriptome layer conservation. With a series validation experiments in mouse, fly and zebrafish, we showed that ConsRM outperformed well-adopted conservation scores (phastCons and phyloP) in distinguishing the conserved and unconserved m6A sites. Additionally, the m6A sites with a higher ConsRM score are more likely to be functionally important. An online database was developed containing the conservation metrics of 177 998 distinct human m6A sites to support conservation analysis and functional prioritization of individual m6A sites. And it is freely accessible at: https://www.xjtlu.edu.cn/biologicalsciences/con.

Adipokines Expression and Effects in Oocyte Maturation, Fertilization and Early Embryo Development: Lessons from Mammals and Birds

Some evidence shows that body mass index in humans and extreme weights in animal models, including avian species, are associated with low in vitro fertilization, bad oocyte quality, and embryo development failures. Adipokines are hormones mainly produced and released by white adipose tissue. They play a key role in the regulation of energy metabolism. However, they are also involved in many other physiological processes including reproductive functions. Indeed, leptin and adiponectin, the most studied adipokines, but also novel adipokines including visfatin and chemerin, are expressed within the reproductive tract and modulate female fertility. Much of the literature has focused on the physiological and pathological roles of these adipokines in ovary, placenta, and uterine functions. The purpose of this review is to summarize the current knowledge regarding the involvement of leptin, adiponectin, visfatin, and chemerin in the oocyte maturation, fertilization, and embryo development in both mammals and birds.

Conserved phosphorylation hotspots in eukaryotic protein domain families

Protein phosphorylation is the best characterized post-translational modification that regulates almost all cellular processes through diverse mechanisms such as changing protein conformations, interactions, and localization. While the inventory for phosphorylation sites across different species has rapidly expanded, their functional role remains poorly investigated. Here, we combine 537,321 phosphosites from 40 eukaryotic species to identify highly conserved phosphorylation hotspot regions within domain families. Mapping these regions onto structural data reveals that they are often found at interfaces, near catalytic residues and tend to harbor functionally important phosphosites. Notably, functional studies of a phospho-deficient mutant in the C-terminal hotspot region within the ribosomal S11 domain in the yeast ribosomal protein uS11 shows impaired growth and defective cytoplasmic 20S pre-rRNA processing at 16 °C and 20 °C. Altogether, our study identifies phosphorylation hotspots for 162 protein domains suggestive of an ancient role for the control of diverse eukaryotic domain families.

Protein phosphorylation has various regulatory functions. Here, the authors map 241 phosphorylation hotspot regions across 40 eukaryotic species, showing that they are enriched at interfaces and near catalytic residues, and enable the discovery of functionally important phospho-sites.

Phosphorylation promotes binding affinity of Rap-Raf complex by allosteric modulation of switch loop dynamics

The effects of phosphorylation of a serine residue on the structural and dynamic properties of Ras-like protein, Rap, and its interactions with effector protein Ras binding domain (RBD) of Raf kinase, in the presence of GTP, are investigated via molecular dynamics simulations. The simulations show that phosphorylation significantly effects the dynamics of functional loops of Rap which participate in the stability of the complex with effector proteins. The effects of phosphorylation on Rap are significant and detailed conformational analysis suggest that the Rap protein, when phosphorylated and with GTP ligand, samples different conformational space as compared to non-phosphorylated protein. In addition, phosphorylation of SER11 opens up a new cavity in the Rap protein which can be further explored for possible drug interactions. Residue network analysis shows that the phosphorylation of Rap results in a community spanning both Rap and RBD and strongly suggests transmission of allosteric effects of local alterations in Rap to distal regions of RBD, potentially affecting the downstream signalling. Binding free energy calculations suggest that phosphorylation of SER11 residue increases the binding between Rap and Raf corroborating the network analysis results. The increased binding of the Rap-Raf complex can have cascading effects along the signalling pathways where availability of Raf can influence the oncogenic effects of Ras proteins. These simulations underscore the importance of post translational modifications like phosphorylation on the functional dynamics in proteins and can be an alternative to drug-targeting, especially in notoriously undruggable oncoproteins belonging to Ras-like GTPase family.

Phosphorylation Dynamics Dominate the Regulated Proteome during Early Xenopus Development

The earliest stages of animal development are largely controlled by changes in protein phosphorylation mediated by signaling pathways and cyclin-dependent kinases. In order to decipher these complex networks and to discover new aspects of regulation by this post-translational modification, we undertook an analysis of the X. laevis phosphoproteome at seven developmental stages beginning with stage VI oocytes and ending with two-cell embryos. Concurrent measurement of the proteome and phosphoproteome enabled measurement of phosphosite occupancy as a function of developmental stage. We observed little change in protein expression levels during this period. We detected the expected phosphorylation of MAP kinases, translational regulatory proteins, and subunits of APC/C that validate the accuracy of our measurements. We find that more than half the identified proteins possess multiple sites of phosphorylation that are often clustered, where kinases work together in a hierarchical manner to create stretches of phosphorylated residues, which may be a means to amplify signals or stabilize a particular protein conformation. Conversely, other proteins have opposing sites of phosphorylation that seemingly reflect distinct changes in activity during this developmental timeline.

Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks

Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the genome alone. While the rate of identification of PTMs has rapidly increased in recent years, our knowledge of PTM functionality encompasses less than 5% of this data. We previously developed SAPH-ire (Structural Analysis of PTM Hotspots) for the prioritization of eukaryotic PTMs based on function potential of discrete modified alignment positions (MAPs) in a set of 8 protein families. A proteome-wide expansion of the dataset to all families of PTM-bearing, eukaryotic proteins with a representational crystal structure and the application of artificial neural network (ANN) models demonstrated the broader applicability of this approach. Although structural features of proteins have been repeatedly demonstrated to be predictive of PTM functionality, the availability of adequately resolved 3D structures in the Protein Data Bank (PDB) limits the scope of these methods. In order to bridge this gap and capture the larger set of PTM-bearing proteins without an available, homologous structure, we explored all available MAP features as ANN inputs to identify predictive models that do not rely on 3D protein structural data. This systematic, algorithmic approach explores 8 available input features in exhaustive combinations (247 models; size 2-8). To control for potential bias in random sampling for holdback in training sets, we iterated each model across 100 randomized, sample training and testing sets-yielding 24,700 individual ANNs. The size of the analyzed dataset and iterative generation of ANNs represents the largest and most thorough investigation of predictive models for PTM functionality to date. Comparison of input layer combinations allows us to quantify ANN performance with a high degree of confidence and subsequently select a top-ranked, robust fit model which highlights 3,687 MAPs, including 10,933 PTMs with a high probability of biological impact but without a currently known functional role.

KinView: a visual comparative sequence analysis tool for integrated kinome research

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable body of potential regulatory elements that impact hundreds of different biological processes important in eukaryotic biology and human health.

Chapter Two - Heterotrimeric G Protein Ubiquitination as a Regulator of G Protein Signaling

Ubiquitin-mediated regulation of G proteins has been known for over 20 years as a result of discoveries made independently in yeast and vertebrate model systems for pheromone and photoreception, respectively. Since that time, several details underlying the cause and effect of G protein ubiquitination have been determined-including the initiating signals, responsible enzymes, trafficking pathways, and their effects on protein structure, function, interactions, and cell signaling. The collective body of evidence suggests that Gα subunits are the primary targets of ubiquitination. However, longstanding and recent results suggest that Gβ and Gγ subunits are also ubiquitinated, in some cases impacting cell polarization-a process essential for chemotaxis and polarized cell growth. More recently, evidence from mass spectrometry (MS)-based proteomics coupled with advances in PTM bioinformatics have revealed that protein families representing G protein subunits contain several structural hotspots for ubiquitination-most of which have not been investigated for a functional role in signal transduction. Taken together, our knowledge and understanding of heterotrimeric G protein ubiquitination as a regulator of G protein signaling-despite 20 years of research-is still emerging.