Protein Interactomics by Two-Hybrid Methods

Predictomes: A classifier-curated database of AlphaFold-modeled protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying biochemical processes is lacking. Although AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on well curated datasets to train a Structure Prediction and Omics informed Classifier called SPOC that shows excellent performance in separating true and false PPIs, including in proteome-wide screens. We applied SPOC to an all-by-all matrix of nearly 300 human genome maintenance proteins, generating ~40,000 predictions that can be viewed at predictomes.org, where users can also score their own predictions with SPOC. High confidence PPIs discovered using our approach suggest novel hypotheses in genome maintenance. Our results provide a framework for interpreting large scale AF-M screens and help lay the foundation for a proteome-wide structural interactome.

A Yeast BiFC-seq Method for Genome-wide Interactome Mapping

Genome-wide physical protein-protein interaction (PPI) mapping remains a major challenge for current technologies. Here, we reported a high-efficiency BiFC-seq method, yeast-enhanced green fluorescent protein-based bimolecular fluorescence complementation (yEGFP-BiFC) coupled with next-generation DNA sequencing, for interactome mapping. We first applied yEGFP-BiFC method to systematically investigate an intraviral network of the Ebola virus. Two-thirds (9/14) of known interactions of EBOV were recaptured, and five novel interactions were discovered. Next, we used the BiFC-seq method to map the interactome of the tumor protein p53. We identified 97 interactors of p53, more than three-quarters of which were novel. Furthermore, in a more complex background, we screened potential interactors by pooling two BiFC libraries together and revealed a network of 229 interactions among 205 proteins. These results show that BiFC-seq is a highly sensitive, rapid, and economical method for genome-wide interactome mapping.

A bimolecular fluorescence complementation flow cytometry screen for membrane protein interactions

Interactions between membrane proteins within a cellular environment are crucial for all living cells. Robust methods to screen and analyse membrane protein complexes are essential to shed light on the molecular mechanism of membrane protein interactions. Most methods for detecting protein:protein interactions (PPIs) have been developed to target the interactions of soluble proteins. Bimolecular fluorescence complementation (BiFC) assays allow the formation of complexes involving PPI partners to be visualized in vivo, irrespective of whether or not these interactions are between soluble or membrane proteins. In this study, we report the development of a screening approach which utilizes BiFC and applies flow cytometry to characterize membrane protein interaction partners in the host Saccharomyces cerevisiae. These data allow constructive complexes to be discriminated with statistical confidence from random interactions and potentially allows an efficient screen for PPIs in vivo within a high-throughput setup.

Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes

Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging. We have recently extended the targeted proteomics rationale to the level of native protein complex analysis (complex-centric proteome profiling). The complex-centric workflow described herein consists of size exclusion chromatography (SEC) to fractionate native protein complexes, data-independent acquisition mass spectrometry to precisely quantify the proteins in each SEC fraction based on a set of proteotypic peptides and targeted, complex-centric analysis where prior information from generic protein interaction maps is used to detect and quantify protein complexes with high selectivity and statistical error control via the computational framework CCprofiler (https://github.com/CCprofiler/CCprofiler). Complex-centric proteome profiling captures most proteins in complex-assembled state and reveals their organization into hundreds of complexes and complex variants observable in a given cellular state. The protocol is applicable to cultured cells and can potentially also be adapted to primary tissue and does not require any genetic engineering of the respective sample sources. At present, it requires ~8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.

Prebiotic Peptides: Molecular Hubs in the Origin of Life

The fundamental roles that peptides and proteins play in today's biology makes it almost indisputable that peptides were key players in the origin of life. Insofar as it is appropriate to extrapolate back from extant biology to the prebiotic world, one must acknowledge the critical importance that interconnected molecular networks, likely with peptides as key components, would have played in life's origin. In this review, we summarize chemical processes involving peptides that could have contributed to early chemical evolution, with an emphasis on molecular interactions between peptides and other classes of organic molecules. We first summarize mechanisms by which amino acids and similar building blocks could have been produced and elaborated into proto-peptides. Next, non-covalent interactions of peptides with other peptides as well as with nucleic acids, lipids, carbohydrates, metal ions, and aromatic molecules are discussed in relation to the possible roles of such interactions in chemical evolution of structure and function. Finally, we describe research involving structural alternatives to peptides and covalent adducts between amino acids/peptides and other classes of molecules. We propose that ample future breakthroughs in origin-of-life chemistry will stem from investigations of interconnected chemical systems in which synergistic interactions between different classes of molecules emerge.

Emerging concepts and challenges in implementing the exposome paradigm in allergic diseases and asthma: a Practall document

Exposome research can improve the understanding of the mechanistic connections between exposures and health to help mitigate adverse health outcomes across the life span. The exposomic approach provides a risk profile instead of single predictors and thus is particularly applicable to allergic diseases and asthma. Under the PRACTALL collaboration between the European Academy of Allergy and Clinical Immunology (EAACI) and the American Academy of Allergy, Asthma, and Immunology (AAAAI), we evaluated the current concepts and the unmet needs on the role of the exposome in allergic diseases and asthma.