Detection of differential bait proteoforms through immunoprecipitation-mass spectrometry data analysis.

Proteins are often referred to as the workhorses of cells, and their interactions are necessary to facilitate specific cellular functions. Despite the recognition that protein-protein interactions, and thus protein functions, are determined by proteoform states, such as mutations and post-translational modifications (PTMs), methods for determining the differential abundance of proteoforms across conditions are very limited. Classically, immunoprecipitation coupled with mass spectrometry (IP-MS) has been used to understand how the interactome (preys) of a given protein (bait) changes between conditions to elicit specific cellular functions. Reversing this concept, we present here a new workflow for IP-MS data analysis that focuses on identifying the differential peptidoforms of the bait protein between conditions. This method can provide detailed information about specific bait proteoforms, potentially revealing pathogenic protein states that can be exploited for the development of targeted therapies.

Interactions between BRD4S, LOXL2, and MED1 drive cell cycle transcription in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) often develops resistance to single-agent treatment, which can be circumvented using targeted combinatorial approaches. Here, we demonstrate that the simultaneous inhibition of LOXL2 and BRD4 synergistically limits TNBC proliferation in vitro and in vivo. Mechanistically, LOXL2 interacts in the nucleus with the short isoform of BRD4 (BRD4S), MED1, and the cell cycle transcriptional regulator B-MyB. These interactions sustain the formation of BRD4 and MED1 nuclear transcriptional foci and control cell cycle progression at the gene expression level. The pharmacological co-inhibition of LOXL2 and BRD4 reduces BRD4 nuclear foci, BRD4-MED1 colocalization, and the transcription of cell cycle genes, thus suppressing TNBC cell proliferation. Targeting the interaction between BRD4S and LOXL2 could be a starting point for the development of new anticancer strategies for the treatment of TNBC.

Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

Specialization of the photoreceptor transcriptome by Srrm3-dependent microexons is required for outer segment maintenance and vision.

Retinal photoreceptors have a distinct transcriptomic profile compared to other neuronal subtypes, likely reflecting their unique cellular morphology and function in the detection of light stimuli by way of the ciliary outer segment. We discovered a layer of this molecular specialization by revealing that the vertebrate retina expresses the largest number of tissue-enriched microexons of all tissue types. A subset of these microexons is included exclusively in photoreceptor transcripts, particularly in genes involved in cilia biogenesis and vesicle-mediated transport. This microexon program is regulated by Srrm3, a paralog of the neural microexon regulator Srrm4. Despite the fact that both proteins positively regulate retina microexons in vitro, only Srrm3 is highly expressed in mature photoreceptors. Its deletion in zebrafish results in widespread down-regulation of microexon inclusion from early developmental stages, followed by other transcriptomic alterations, severe photoreceptor defects, and blindness. These results shed light on the transcriptomic specialization and functionality of photoreceptors, uncovering unique cell type-specific roles for Srrm3 and microexons with implications for retinal diseases.

In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species.

The coronavirus disease COVID-19 constitutes the most severe pandemic of the last decades having caused more than 1 million deaths worldwide. The SARS-CoV-2 virus recognizes the angiotensin converting enzyme 2 (ACE2) on the surface of human cells through its spike protein. It has been reported that the coronavirus can mildly infect cats, and ferrets, and perhaps dogs while not pigs, mice, chicken and ducks. Differences in viral infectivity among different species or individuals could be due to amino acid differences at key positions of the host proteins that interact with the virus, the immune response, expression levels of host proteins and translation efficiency of the viral proteins among other factors. Here, first we have addressed the importance that sequence variants of different animal species, human individuals and virus isolates have on the interaction between the RBD domain of the SARS-CoV-2 spike S protein and human angiotensin converting enzyme 2 (ACE2). Second, we have looked at viral translation efficiency by using the tRNA adaptation index. We find that integration of both interaction energy with ACE2 and translational efficiency explains animal infectivity. Humans are the top species in which SARS-CoV-2 is both efficiently translated as well as optimally interacting with ACE2. We have found some viral mutations that increase affinity for hACE and some hACE2 variants affecting ACE2 stability and virus binding. These variants suggest that different sensitivities to coronavirus infection in humans could arise in some cases from allelic variability affecting ACE2 stability and virus binding.

ProteinFishing: a protein complex generator within the ModelX toolsuite.

SUMMARY: Accurate 3D modelling of protein-protein interactions (PPI) is essential to compensate for the absence of experimentally determined complex structures. Here, we present a new set of commands within the ModelX toolsuite capable of generating atomic-level protein complexes suitable for interface design. Among these commands, the new tool ProteinFishing proposes known and/or putative alternative 3D PPI for a given protein complex. The algorithm exploits backbone compatibility of protein fragments to generate mutually exclusive protein interfaces that are quickly evaluated with a knowledge-based statistical force field. Using interleukin-10-R2 co-crystalized with interferon-lambda-3, and a database of X-ray structures containing interleukin-10, this algorithm was able to generate interleukin-10-R2/interleukin-10 structural models in agreement with experimental data. AVAILABILITY AND IMPLEMENTATION: ProteinFishing is a portable command-line tool included in the ModelX toolsuite, written in C++, that makes use of an SQL (tested for MySQL and MariaDB) relational database delivered with a template SQL dump called FishXDB. FishXDB contains the empty tables of ModelX fragments and the data used by the embedded statistical force field. ProteinFishing is compiled for Linux-64bit, MacOS-64bit and Windows-32bit operating systems. This software is a proprietary license and is distributed as an executable with its correspondent database dumps. It can be downloaded publicly at http://modelx.crg.es/. Licenses are freely available for academic users after registration on the website and are available under commercial license for for-profit organizations or companies. CONTACT: javier.delgado@crg.eu or luis.serrano@crg.eu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Protein-assisted RNA fragment docking (RnaX) for modeling RNA-protein interactions using ModelX.

RNA-protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an RNA molecule interacts with a target protein and/or engineering an RNA molecule to specifically bind to a protein could allow for rational interference with these cellular processes and the design of novel therapies. Here we present a robust RNA-protein fragment pair-based method, termed RnaX, to predict RNA-binding sites. This methodology, which is integrated into the ModelX tool suite (http://modelx.crg.es), takes advantage of the structural information present in all released RNA-protein complexes. This information is used to create an exhaustive database for docking and a statistical forcefield for fast discrimination of true backbone-compatible interactions. RnaX, together with the protein design forcefield FoldX, enables us to predict RNA-protein interfaces and, when sufficient crystallographic information is available, to reengineer the interface at the sequence-specificity level by mimicking those conformational changes that occur on protein and RNA mutagenesis. These results, obtained at just a fraction of the computational cost of methods that simulate conformational dynamics, open up perspectives for the engineering of RNA-protein interfaces.

FoldX 5.0: working with RNA, small molecules and a new graphical interface.

SUMMARY: A new version of FoldX, whose main new features allows running classic FoldX commands on structures containing RNA molecules and includes a module that allows parametrization of ligands or small molecules (ParamX) that were not previously recognized in old versions, has been released. An extended FoldX graphical user interface has also being developed (available as a python plugin for the YASARA molecular viewer) allowing user-friendly parametrization of new custom user molecules encoded using JSON format. AVAILABILITY AND IMPLEMENTATION: http://foldxsuite.crg.eu/.