Biology subjects

Lopes, A.

Publications and source records attributed to Lopes, A..

26 records · Page 2Linked to original sources

bioRxiv2023

The Ribosome Profiling landscape of yeast reveals a high diversity in pervasive translation

Pervasive translation is a widespread phenomenon that plays an important role in de novo gene birth; however, its underlying mechanisms remain unclear. Based on multiple Ribosome Profiling (Ribo-Seq) datasets, we investigated the RiboSeq landscape of coding and noncoding regions of yeast. Therefore, we developed a representation framework which allows the visual representation and rational classification of the entire diversity of Ribo-Seq signals that could be observed in yeast. We show that if coding regions are restricted to specific areas of the Ribo-Seq landscape, noncoding regions are associated with a wide diversity of translation signals and, conversely, populate the entire yeast Ribo-Seq landscape. Specifically, we reveal that noncoding regions are associated with canonical translation signals, but also with non-canonical ones absent from coding regions, and which appear to be a hallmark of pervasive translation. Notably, we report thousands of translated noncoding ORFs among which, 251 led to detectable products with Mass Spectrometry while being characterized by a wide range of translation specificities. Overall, we show that pervasive translation is not random with noncoding ORF translation signals being consistent across Ribo-Seq experiments. Finally, we show that the translation signal of noncoding ORFs is not explained by features related to the emergence of function, but rather determined by the translation start codon and the codon distribution in their two alternative frames. Overall, our results enable us to propose a topology of the pervasive Ribo-Seq landscape of a species, and open the way to future comparative analyses of this translation landscape under different conditions.

evolutionary biology↗

bioRxiv2022

Drinkable, liquid in situ-forming and tough hydrogels for gastrointestinal therapeutics

Tablets and capsules are a cornerstone of medicine, but these solid dosage forms can be challenging to swallow for geriatric and pediatric patients. While liquid formulations are easier to ingest, these formulations lack the capacity to localize therapeutics and excipients nor act as controlled release devices. To bridge the advantages of solid and liquid dosage forms, here we describe drug formulations based on liquid in situ-forming and tough (LIFT) hydrogels. Drug-loaded LIFT hydrogels are formed directly in the stomach through the sequential ingestion of a crosslinker solution of calcium and dithiol crosslinkers, followed by the ingestion of a drug-containing polymer solution of alginate and 4-arm poly(ethylene glycol)-maleimide. We show that LIFT hydrogels are mechanically tough and able to robustly form in the presence of complex gastric fluid and in vivo in rat and porcine stomachs. LIFT hydrogels are retained within the porcine stomach for up to 24 h, biocompatible, and safely cleared. These hydrogels deliver a total dose comparable to unencapsulated drug but with delayed and lower maximum drug plasma concentrations, providing a method for controlled release that may mitigate drug toxicity. Co-encapsulation of lactase as a model biologic drug and calcium carbonate mitigated gastric-mediated deactivation of encapsulated enzyme in rat and porcine models. We also demonstrate the potential of these hydrogels to encapsulate and protect a model therapeutic bacterium, E. coli Nissle 1917, against acid. LIFT hydrogels present a biocompatible means of tough, double-network hydrogel formation in situ in the gastric cavity, and may expand medication access for patients with difficulty swallowing.

bioengineering↗

bioRxiv2022

A machine learning liver-on-a-chip system for safer drug formulation

Drug metabolism leads to biotransformations of pharmaceutical substances that alter drug efficacy, toxicity, as well as drug interactions. Modeling these processes ex vivo stands to greatly accelerate our capacity to develop safe and efficacious drugs and formulations. Recognizing the liver as the primary site of drug metabolism, here we report a novel whole-tissue ex vivo liver screening platform that enabled modeling of hepatic metabolism and tracking of hepatotoxic drug metabolites. We applied the system for the characterization of acetaminophen (APAP) metabolism and identified interactions that can mitigate the generation of toxic metabolites ex vivo. Combining our experimental platform with state-of-the-art machine learning, we validated two novel functional excipients that can prevent APAP hepatotoxicity in vivo in mice. To assess translational potential, we prototyped a novel solid dosage form with controlled release of both APAP and our functional excipients. Our this platform provides innovative potential access to actionable data on drug metabolism to support the development of new therapeutic approaches.

bioengineering↗

bioRxiv2021

SURFMAP: a software for mapping in two dimensions protein surface features

Molecular cartography using two-dimensional (2D) representation of protein surfaces has been shown to be very promising for protein surface analysis. Here, we present SURFMAP, a free standalone and easy-to-use software that enables the fast and automated 2D projection of either predefined features of protein surface (i.e., electrostatic potential, Kyte-Doolittle hydrophobicity, stickiness, and surface relief) or any descriptor encoded in the temperature factor column of a PDB file. SURFMAP uses a pseudo-cylindrical sinusoidal "equal-area" projection that has the advantage of preserving the area measures. It provides the user with (i) 2D maps that enable the easy and visual analysis of protein surface features of interest and (ii) maps in a text file format allowing the fast and straightforward quantitative comparison of 2D maps of homologous proteins.

bioinformatics↗

bioRxiv2021

Intergenic ORFs as elementary structural modules of de novo gene birth and protein evolution

The noncoding genome plays an important role in de novo gene birth and in the emergence of genetic novelty. Nevertheless, how noncoding sequences properties could promote the birth of novel genes and shape the evolution and the structural diversity of proteins remains unclear. Therefore, by combining different bioinformatic approaches, we characterized the fold potential diversity of the amino acid sequences encoded by all intergenic ORFs (Open Reading Frames) of S. cerevisiae with the aim of (i) exploring whether the large structural diversity observed in proteomes is already present in noncoding sequences, and (ii) estimating the potential of the noncoding genome to produce novel protein bricks that can either give rise to novel genes or be integrated into pre-existing proteins, thus participating in protein structure diversity and evolution. We showed that amino acid sequences encoded by most yeast intergenic ORFs contain the elementary building blocks of protein structures. Moreover, they encompass the large structural diversity of canonical proteins with strikingly the majority predicted as foldable. Then, we investigated the early stages of de novo gene birth by identifying intergenic ORFs with a strong translation signal in ribosome profiling experiments and by reconstructing the ancestral sequences of 70 yeast de novo genes. This enabled us to highlight sequence and structural factors determining de novo gene emergence. Finally, we showed a strong correlation between the fold potential of de novo proteins and the one of their ancestral amino acid sequences, reflecting the relationship between the noncoding genome and the protein structure universe.

evolutionary biology↗

bioRxiv2019

Computationally guided high-throughput design of self-assembling drug nanoparticles

Nanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials - with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.

bioengineering↗

bioRxiv2018

Encapsulated mononuclear stem cells: paracrine action for the treatment of acute myocardial infarction

Cell therapy is considered as a treatment option for acute myocardial infarction (AMI). Released molecules by cells paracrine action may promote tissue regeneration. Therefore we used bone-marrow mononuclear cells (BMMNCs) from GFP+ Wistar rats encapsulated in sodium alginate for AMI treatment. Animals were randomly allocated into groups - empty (EC); BMMNC capsules; or sham. AMI was induced by occlusion of left anterior artery and capsules were delivered intrathoracically. Troponin I was measured 24h after AMI and echocardiography was performed at 48h and 7d after AMI. On day 7 animals were euthanized and their hearts were harvested. Tissue levels of TNF-, IL-6, IL-10, cleaved caspase-3, and catalase were measured. Technical procedures were performed by blinded operators. There was no difference in either heart morphofunctional parameters or biochemical analysis between AMI groups. We conclude that the paracrine effects of BMMNCs lacks efficacy to modulate events associated with AMI in the rat.

pathology↗

bioRxiv2018

Protein interaction energy landscapes are shaped by functional and also non-functional partners

In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. We developed an original theoretical framework in order to interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters. Our theoretical framework relies on a two-dimensional (2D) representation of interaction energy landscapes with 2D energy maps that reflect in a synthetic way the propensity of a protein to interact with another protein. We investigated the propensity of protein surfaces to interact with functional and arbitrary partners and asked whether their interaction propensity is conserved during the evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the whole energy landscapes of 74 proteins interacting with different sets of homologs, corresponding to their functional partners family or arbitrary protein families. Then, we systematically compared the energy maps resulting from the docking of a given protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding site but also of the rest of the protein surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also to arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of selected partners and opens the way for further developments to study the behavior of proteins in a specific environment.

bioinformatics↗