Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.

How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we developed "Tissue Risk Assessment of Causality by Expression" (TRACE), a machine learning approach to predict genes that underlie tissue-selective diseases and selectivity-related features. TRACE utilized 4,744 biologically interpretable tissue-specific gene features that were inferred from heterogeneous omics datasets. Application of TRACE to 1,031 disease genes uncovered known and novel selectivity-related features, the most common of which was previously overlooked. Next, we created a catalog of tissue-associated risks for 18,927 protein-coding genes (https://netbio.bgu.ac.il/trace/). As proof-of-concept, we prioritized candidate disease genes identified in 48 rare-disease patients. TRACE ranked the verified disease gene among the patient's candidate genes significantly better than gene prioritization methods that rank by gene constraint or tissue expression. Thus, tissue selectivity combined with machine learning enhances genetic and clinical understanding of hereditary diseases.

The landscape of molecular chaperones across human tissues reveals a layered architecture of core and variable chaperones.

The sensitivity of the protein-folding environment to chaperone disruption can be highly tissue-specific. Yet, the organization of the chaperone system across physiological human tissues has received little attention. Through computational analyses of large-scale tissue transcriptomes, we unveil that the chaperone system is composed of core elements that are uniformly expressed across tissues, and variable elements that are differentially expressed to fit with tissue-specific requirements. We demonstrate via a proteomic analysis that the muscle-specific signature is functional and conserved. Core chaperones are significantly more abundant across tissues and more important for cell survival than variable chaperones. Together with variable chaperones, they form tissue-specific functional networks. Analysis of human organ development and aging brain transcriptomes reveals that these functional networks are established in development and decline with age. In this work, we expand the known functional organization of de novo versus stress-inducible eukaryotic chaperones into a layered core-variable architecture in multi-cellular organisms.

Controlling the properties and self-assembly of helical nanofibrils by engineering zinc-binding ß-hairpin peptides.

This work illustrates a series of novel peptides that have the capability to bind Zn2+ ions and to produce fibrillar structures. The location and the type of the residues along the peptide sequence can determine the nature of the fibril. This work presents a proof-of-concept milestone for designing peptides with different properties to produce diverse materials.

Aging promotes reorganization of the CD4 T cell landscape toward extreme regulatory and effector phenotypes.

Age-associated changes in CD4 T-cell functionality have been linked to chronic inflammation and decreased immunity. However, a detailed characterization of CD4 T cell phenotypes that could explain these dysregulated functional properties is lacking. We used single-cell RNA sequencing and multidimensional protein analyses to profile thousands of CD4 T cells obtained from young and old mice. We found that the landscape of CD4 T cell subsets differs markedly between young and old mice, such that three cell subsets-exhausted, cytotoxic, and activated regulatory T cells (aTregs)-appear rarely in young mice but gradually accumulate with age. Most unexpected were the extreme pro- and anti-inflammatory phenotypes of cytotoxic CD4 T cells and aTregs, respectively. These findings provide a comprehensive view of the dynamic reorganization of the CD4 T cell milieu with age and illuminate dominant subsets associated with chronic inflammation and immunity decline, suggesting new therapeutic avenues for age-related diseases.

ResponseNet v.3: revealing signaling and regulatory pathways connecting your proteins and genes across human tissues.

ResponseNet v.3 is an enhanced version of ResponseNet, a web server that is designed to highlight signaling and regulatory pathways connecting user-defined proteins and genes by using the ResponseNet network optimization approach (http://netbio.bgu.ac.il/respnet). Users run ResponseNet by defining source and target sets of proteins, genes and/or microRNAs, and by specifying a molecular interaction network (interactome). The output of ResponseNet is a sparse, high-probability interactome subnetwork that connects the two sets, thereby revealing additional molecules and interactions that are involved in the studied condition. In recent years, massive efforts were invested in profiling the transcriptomes of human tissues, enabling the inference of human tissue interactomes. ResponseNet v.3 expands ResponseNet2.0 by harnessing ∼11,600 RNA-sequenced human tissue profiles made available by the Genotype-Tissue Expression consortium, to support context-specific analysis of 44 human tissues. Thus, ResponseNet v.3 allows users to illuminate the signaling and regulatory pathways potentially active in the context of a specific tissue, and to compare them with active pathways in other tissues. In the era of precision medicine, such analyses open the door for tissue- and patient-specific analyses of pathways and diseases.

Large-scale analysis of human gene expression variability associates highly variable drug targets with lower drug effectiveness and safety.

MOTIVATION: The effectiveness of drugs tends to vary between patients. One of the well-known reasons for this phenomenon is genetic polymorphisms in drug target genes among patients. Here, we propose that differences in expression levels of drug target genes across individuals can also contribute to this phenomenon. RESULTS: To explore this hypothesis, we analyzed the expression variability of protein-coding genes, and particularly drug target genes, across individuals. For this, we developed a novel variability measure, termed local coefficient of variation (LCV), which ranks the expression variability of each gene relative to genes with similar expression levels. Unlike commonly used methods, LCV neutralizes expression levels biases without imposing any distribution over the variation and is robust to data incompleteness. Application of LCV to RNA-sequencing profiles of 19 human tissues and to target genes of 1076 approved drugs revealed that drug target genes were significantly more variable than protein-coding genes. Analysis of 113 drugs with available effectiveness scores showed that drugs targeting highly variable genes tended to be less effective in the population. Furthermore, comparison of approved drugs to drugs that were withdrawn from the market showed that withdrawn drugs targeted significantly more variable genes than approved drugs. Last, upon analyzing gender differences we found that the variability of drug target genes was similar between men and women. Altogether, our results suggest that expression variability of drug target genes could contribute to the variable responsiveness and effectiveness of drugs, and is worth considering during drug treatment and development. AVAILABILITY AND IMPLEMENTATION: LCV is available as a python script in GitHub (https://github.com/eyalsim/LCV). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The unusual metal ion binding ability of histidyl tags and their mutated derivatives.

Polyhistidine-tags are often used for the affinity purification of polyhistidine-tagged recombinant proteins. These sequences are also found in nature and are often highly conserved across different species. However, their exact role in the biological systems is not clear. The purpose of this work is to shed light on the behavior of poly-His sequences in their interactions with metal ions. This work illustrates the first study of novel poly-(His-Ala) peptides that bind Cu(ii) applying both experimental techniques and extensive computational tools. The studied novel peptides are analogues of the short protected fragment of the pHpG (EDDH9GVG10) peptide, which was found in the venom of Atheris squamigera. Our study presents the properties of metal ion binding-histidine tag complexes and their mutated derivatives. The Cu(ii) binding ability in pHG (Ac-EDDH9G-NH2) is more efficient than in the mutated derivatives, although the number of imidazoles that bind to Cu(ii) ions are similar. Finally, the formation of an α-helical structure is observed in pHG and in one of the mutated derivatives, indicating the importance of the sequence in the poly-(His-Ala) tags.

African Viper Poly-His Tag Peptide Fragment Efficiently Binds Metal Ions and Is Folded into an α-Helical Structure.

Snake venoms are complex mixtures of toxic and often spectacularly biologically active components. Some African vipers contain polyhistidine and polyglycine peptides, which play a crucial role in the interaction with metal ions during the inhibition of snake metalloproteases. Polyhistidine peptide fragments, known as poly-His tags, play many important functions, e.g., in metal ion transport in bacterial chaperon proteins. In this paper, we report a detailed characterization of Cu(2+), Ni(2+), and Zn(2+) complexes with the EDDHHHHHHHHHG peptide fragment (pHG) derived from the venom of the rough scale bush viper (Atheris squamigera). In order to determine the thermodynamic properties, stoichiometry, binding sites, and structures of the metal-pHG complexes, we used a combination of experimental techniques (potentiometric titrations, electrospray ionization mass spectrometry, UV-vis spectroscopy, circular dichroism spectroscopy, and electron paramagnetic resonance spectroscopy) and extensive computational tools (molecular dynamics simulations and density functional theory calculations). The results showed that pHG has a high affinity toward metal ions. The numerous histidine residues located along this sequence are efficient metal ion chelators with high affinities toward Cu(2+), Ni(2+), and Zn(2+) ions. The formation of an α-helical structure induced by metal ion coordination and the occurrence of polymorphic binding states were observed. It is proposed that metal ions can "move along" the poly-His tag, which serves as a metal ion transport pathway. The coordination of Cu(2+), Ni(2+), and Zn(2+) ions to the histidine tag is very effective in comparison with other histidine-rich peptides. The stabilities of the metal-pHG complexes increase in the order Zn(2+) < Ni(2+)≪ Cu(2+).

Spontaneous structural transition in phospholipid-inspired aromatic phosphopeptide nanostructures.

Phospholipid membranes could be considered a prime example of the ability of nature to produce complex yet ordered structures, by spontaneous and efficient self-assembly. Inspired by the unique properties and architecture of phospholipids, we designed simple amphiphilic decapeptides, intended to fold in the center of the peptide sequence, with a phosphorylated serine "head" located within a central turn segment, and two hydrophobic "tails". The molecular design also included the integration of the diphenylalanine motif, previously shown to facilitate self-assembly and increase nanostructure stability. Secondary structure analysis of the peptides indeed indicated the presence of stabilized conformations in solution, with a central turn connecting two hydrophobic "tails", and interactions between the hydrophobic strands. The mechanisms of assembly into supramolecular structures involved structural transitions between different morphologies, which occurred over several hours, leading to the formation of distinctive nanostructures, including half-elliptical nanosheets and curved tapes. The phosphopeptide building blocks appear to self-assemble via a particular combination of aromatic, hydrophobic and ionic interactions, as well as hydrogen bonding, as demonstrated by proposed constructed simulated models of the peptides and self-assembled nanostructures. Molecular dynamics simulations also gave insight into mechanisms of structural transitions of the nanostructures at a molecular level. Because of the biocompatibility of peptides, the phosphopeptide assemblies allow for expansion of the library of biomolecular nanostructures available for future design and application of biomedical devices.

The unusual binding mechanism of Cu(II) ions to the poly-histidyl domain of a peptide found in the venom of an African viper.

Copper complexes of a poly-His/poly-Gly peptide (EDDHHHHHHHHHGVGGGGGGGGGG-NH2), a natural component of a snake venom, were studied by means of both experimental (thermodynamic, spectroscopic and MS) techniques and molecular dynamics (MD) simulations and density functional theory (DFT) calculations. This peptide proved to be an exceptionally effective copper chelator, forming complexes which are thermodynamically more stable than those formed by both the albumin-like ATCUN motif and several other poly-histidine protein fragments. We show that, in a poly-histidine stretch, copper seems to prefer binding to residues separated by one amino acid and that a correlation between an α-helical structure of the predicted complexes and their thermodynamic stability is observed.

Insight into the coordination and the binding sites of Cu(2+) by the histidyl-6-tag using experimental and computational tools.

His-tags are specific sequences containing six to nine subsequent histydyl residues, and they are used for purification of recombinant proteins by use of IMAC chromatography. Such polyhistydyl tags, often used in molecular biology, can be also found in nature. Proteins containing histidine-rich domains play a critical role in many life functions in both prokaryote and eukaryote organisms. Binding mode and the thermodynamic properties of the system depend on the specific metal ion and the histidine sequence. Despite the wide application of the His-tag for purification of proteins, little is known about the properties of metal-binding to such tag domains. This inspired us to undertake detailed studies on the coordination of Cu(2+) ion to hexa-His-tag. Experiments were performed using the potentiometric, UV-visible, CD, and EPR techniques. In addition, molecular dynamics (MD) simulations and density functional theory (DFT) calculations were applied. The experimental studies have shown that the Cu(2+) ion binds most likely to two imidazoles and one, two, or three amide nitrogens, depending on the pH. The structures and stabilities of the complexes for the Cu(2+)-Ac-(His)6-NH2 system using experimental and computational tools were established. Polymorphic binding states are suggested, with a possibility of the formation of α-helix structure induced by metal ion coordination. Metal ion is bound to various pairs of imidazole moieties derived from the tag with different efficiencies. The coordination sphere around the metal ion is completed by molecules of water. Finally, the Cu(2+) binding by Ac-(His)6-NH2 is much more efficient compared to other multihistidine protein domains.