Understanding membrane protein folding and interfaciality

Despite the bast abundance of membrane proteins encoded in the human genome, the understanding of their biosynthesis and folding is far from the knowledge we have of soluble proteins. In the present thesis the main objective is to increase our knowledge on membrane protein biogenesis and folding, from the first steps of folding within the ribosome to the native structure acquisition in the membrane. Hydrophobicity, helicity and length of the polypeptide chain have been stablished as the major determinants for alpha-helical conformation adoption within the ribosome exit tunnel. Also, a 'biological' interfacial scale for the 20 naturally occurring amino acids were determined due to the development of the Lep3G assay. This scale is important to deeply study the membrane interface contribution to the membrane protein integration since not all membrane proteins across the membrane, but some keep anchored to one layer. Concerning to the membrane packing, an exhaustive analysis of hydrophobic matching between largely different hydrophobic region in cells has been done for the first time. We confirmed that, in living cells, adaptations in both, the membrane thickness and transmembrane domain tilting, enable helix-helix packing besides length differences between both. Finally, we determined once again that the final topology acquisition is not only guided by the hydrophobicity of the transmembrane domains which compose the protein, but also by packing between transmembrane helices and the presence of specialized connecting loops

Implementação de diferentes leis de controle por meio de Arduino para um sistema de hélices paralelas

Este trabalho de conclusão de curso apresenta o uso da plataforma Arduino para a implementação de um sistema de hélices paralelas composto por uma dinâmica não linear com três graus de liberdade desenvolvido em instalações da USP. Para tanto, começamos com um breve percurso histórico sobre os sistemas de controle, de modo a entender o contexto macro no qual se insere a nossa pesquisa, e avançamos com uma investigação acerca da aplicabilidade da plataforma Arduino e dos métodos desenvolvidos especificamente para o controle da planta experimental mediante uma placa Mega 2560. Com isso, pretendemos, ao final do trabalho, ter apresentado não só o avanço dos sistemas de controle ao longo da história, mas, sobretudo, destacar a importância do Arduino como ferramenta para simulação de diferentes modelos. Ademais, a pesquisa desenvolvida tem como finalidade subsidiar os alunos em futuros estudos acerca dos sistemas de controle moderno, por apresentar uma visão mais ampla sobre a temática.This course conclusion work presents the use of the Arduino platform for the implementation of a parallel helix system composed of a nonlinear dynamics with three degrees of freedom developed in USP facilities. To do so, we start with a brief historical journey about control systems, in order to understand the macro context in which our research is inserted, and we proceed with an investigation about the applicability of the Arduino platform and the methods developed specifically for the control of experimental plant using a Mega 2560 plate. With this, we intend, at the end of the work, to have presented not only the advances in control systems throughout history, but, above all, to highlight the importance of Arduino as a tool for simulating different models. Furthermore, the research developed aims to support students in future studies on modern control systems, as it presents a broader view on the subject

Folding and insertion of transmembrane helices at the ER

In eukaryotic cells, the endoplasmic reticulum (ER) is the entry point for newly synthesized proteins that are subsequently distributed to organelles of the endomembrane system. Some of these proteins are completely translocated into the lumen of the ER while others integrate stretches of amino acids into the greasy 30 Å wide interior of the ER membrane bilayer. It is generally accepted that to exist in this non-aqueous environment the majority of membrane integrated amino acids are primarily non-polar/hydrophobic and adopt an α-helical conformation. These stretches are typically around 20 amino acids long and are known as transmembrane (TM) helices. In this review, we will consider how transmembrane helices achieve membrane integration. We will address questions such as: Where do the stretches of amino acids fold into a helical conformation? What is/are the route/routes that these stretches take from synthesis at the ribosome to integration through the ER translocon? How do these stretches 'know' to integrate and in which orientation? How do marginally hydrophobic stretches of amino acids integrate and survive as transmembrane helices

The role of hydrophobic matching on transmembrane helix packing in cells

Folding and packing of membrane proteins are highly influenced by the lipidic component of the membrane. Here, we explore how the hydrophobic mismatch (the difference between the hydrophobic span of a transmembrane protein region and the hydrophobic thickness of the lipid membrane around the protein) influences transmembrane helix packing in a cellular environment. Using a ToxRED assay in Escherichia coli and a Bimolecular Fluorescent Complementation approach in human-derived cells complemented by atomistic molecular dynamics simulations we analyzed the dimerization of Glycophorin A derived transmembrane segments. We concluded that, biological membranes can accommodate transmembrane homo-dimers with a wide range of hydrophobic lengths. Hydrophobic mismatch and its effects on dimerization are found to be considerably weaker than those previously observed in model membranes, or under in vitro conditions, indicating that biological membranes (particularly eukaryotic membranes) can adapt to structural deformations through compensatory mechanisms that emerge from their complex structure and composition to alleviate membrane stress. Results based on atomistic simulations support this view, as they revealed that Glycophorin A dimers remain stable, despite of poor hydrophobic match, using mechanisms based on dimer tilting or local membrane thickness perturbations. Furthermore, hetero-dimers with large length disparity between their monomers are also tolerated in cells, and the conclusions that one can draw are essentially similar to those found with homo-dimers. However, large differences between transmembrane helices length hinder the monomer/dimer equilibrium, confirming that, the hydrophobic mismatch has, nonetheless, biologically relevant effects on helix packing in vivo.Peer reviewe

SARS-CoV-2 envelope protein topology in eukaryotic membranes

Coronavirus E protein is a small membrane protein found in the virus envelope. Different coronavirus E proteins share striking biochemical and functional similarities, but sequence conservation is limited. In this report, we studied the E protein topology from the new SARS-CoV-2 virus both in microsomal membranes and in mammalian cells. Experimental data reveal that E protein is a single-spanning membrane protein with the N-terminus being translocated across the membrane, while the C-terminus is exposed to the cytoplasmic side (Ntlum/Ctcyt). The defined membrane protein topology of SARS-CoV-2 E protein may provide a useful framework to understand its interaction with other viral and host components and contribute to establish the basis to tackle the pathogenesis of SARS-CoV-2

Combinatorial analysis of deletion repair in SARS-CoV-2 variants of concern

Resumen del póster presentado a las III Jornadas Científicas PTI+ Salud Global, celebradas en el Centro de Ciencias Humanas y Sociales (CCHS), CSIC (Madrid) del 20 al 22 de noviembre de 2023.[Background] The spike protein of SARS-CoV-2 is a key determinant of viral fitness and immune evasion, and its N-terminal domain (NTD) is prone to mutations that may confer fitness advantages to the virus. Most variants of concern (VOCs), including Alpha, Delta, and Omicron, have harbored distinct NTD lineage-defining mutations. However, the relationship between genotype and the impact on viral transmission and viral phenotype is not yet fully understood.[Methods] We analyzed over 10 million SARS-CoV-2 genomes from GISAID to investigate the prevalence and estimate the transmission of different combinations of NTD mutations across the Alpha and the Omicron variants. Additionally, we characterized the viral phenotype of deletion repair events in a surrogate in vitro system, assessing their infectivity, fusogenicity, thermal stability, protein surface expression, and neutralization sensitivity.[Results] Some NTD mutations, such the repair of deleted amino acids at sites S:69/70 and S:144 in Alpha viruses, were associated with an increased transmission rate and higher frequency among older age groups. These deletion repairs were also detected in Omicron, but with different patterns and effects. For instance, the repair of deletion at site S:143/145 in Omicron enhanced viral fusogenicity and neutralization by sera from vaccinated individuals. However, the repair of the deletion at site S:69/70 reduced viral infectivity and did not affect these traits. The co-occurrence of both repairs resulted in reduced fusogenicity.[Conclusions] Our study reveals the complex interplay between NTD mutations, including those that lead to deletion repair, and viral success in SARS-CoV-2. This may have implications for viral transmission, immunity, and vaccine efficacy. Our findings improve our understanding of SARS- CoV-2 evolution, and provide insights for future research and public health interventions.Peer reviewe

Membrane insertion and topology of the translocon-associated protein (TRAP) gamma subunit

Translocon-associated protein (TRAP) complex is intimately associated with the ER translocon for the insertion or translocation of newly synthesised proteins in eukaryotic cells. The TRAP complex is comprised of three single-spanning and one multiple-spanning subunits. We have investigated the membrane insertion and topology of the multiple-spanning TRAP-γ subunit by glycosylation mapping and green fluorescent protein fusions both in vitro and in cell cultures. Results demonstrate that TRAP-γ has four transmembrane (TM) segments, an Nt/Ct cytosolic orientation and that the less hydrophobic TM segment inserts efficiently into the membrane only in the cellular context of full-length protein

Therapy-Related MDS Can be Separated into Different Risk-Groups According to Tools for Classification and Prognostication of Primary MDS

Abstract The current classification system for Myelodysplastic Syndromes lumps all therapy-related (tMDS) into one subgroup assuming all tMDS had the same poor prognosis. We have put together a database including 2032 patients with a diagnosis of tMDS from several different IWG centers and the MDS clinical research consortium. With the idea of developing an individual scoring system for tMDS, we decided to start by optimizing the cytogenetic part of the IPSSR. First, we did an extensive review of karyotypes. Finally, 1245 patients had complete data and correct ISCN formula to be used for score development. We could show regarding karyotypes there are very limited differences between primary and tMDS. Mainly the distribution of risk groups differs with complex occurring more (37%) and normal karyotypes occurring less frequent, although still accounting for 30%. There are few exceptions that are relatively special for tMDS, like translocations including 11q23. A few karyotypes are less frequent; therefore, we could not evaluate the value of IPSS-R cytogenetics for all karyotypes. However, if we apply IPSS-R cytogenetics to our patient cohort, we can separate 5 different risk groups as in pMDS. We tested the performance of the score by using the Dxy. As main endpoint we chose transformation-free survival giving better information about the severity of the disease compared to the single endpoints survival and AML transformation that where calculated for completeness as well. The Dxy for the IPSS-R cytogenetic part is 0.31 for transformation-free survival. This indicates an effective prognostic performance although not as good as in pMDS. Several attempts were done to develop a tMDS specific cytogenetic score. The best draft scoring component achieves a Dxy of 0.33. Counting the number of aberrations achieves a score of 0.30. If normal clone present or not is added, the performance of this very simple model is improved with a Dxy of 0.32. As we could show, all these different approaches lead to a comparable performance. One can argue that still regarding a few karyotypes the prognostic impact is slightly different between p and tMDS (e.g. +8). On the other hand, the most practical approach seems to be to adopt the original cytogenetic part of the IPSS-R for further score development since clinicians do not need to use different scoring systems for different MDS subtypes. While the final analyses for the development of a tMDS specific risk score are currently under way, extensive calculations regarding the performance of different scores like WHO- (Dxy 0.24), FAB-classification (Dxy 0.19), WPSS-R (Dxy 0.35), IPSS-R (Dxy 0.37), and IPSS-R+age (Dxy 0.36), show all these systems can separate different risk groups within our cohort. However, these results also show an inferior performance of the scoring systems in t compared to pMDS. There are multiple possible reasons for this. The most important seem to be tMDS patients are often not cured from the primary disease and its disease specific risk of death should ideally be considered. Unfortunately, we don't have that data. And second, we included treated as well as untreated patients. It seems not to be feasible otherwise since the selection bias for old unfit patients would be unacceptable. We could show already in pMDS that the score performances are considerably worse if we analyze treated patients and the score performance in our cohort is better if limited to untreated patients. To conclude, we can say existing classification and scoring systems work in tMDS and can separate groups with clearly different risk for death and transformation. Although we could not develop a tMDS specific cytogenetic score this could be seen positively since it underlines tMDS do not seem to be much different regarding disease specific risk. This should initiate a discussion of a revision of the WHO-classification and encourage clinicians to use the existing tools for risk assessment and treatment decisions. A simple solution could be to use the WHO classification for pMDS and precede each subgroup with a t, like tMDS-SLD, and so on. Such an approach would be of importance for patients falsely classified as tMDS. After all this classification is done according to anamnestic information only and sporadic cases cannot be excluded. Until now, in the first analyzes performed with the final tMDS-database, we did not find any indication that risk factors established in pMDS would lose or change their meaning in tMDS. Figure. Figure. Disclosures Komrokji: Celgene: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees. List:Celgene: Research Funding. Roboz:Orsenix: Consultancy; Eisai: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Astex Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Pfizer: Consultancy; Cellectis: Research Funding; Daiichi Sankyo: Consultancy; Sandoz: Consultancy; Otsuka: Consultancy; Daiichi Sankyo: Consultancy; Eisai: Consultancy; Pfizer: Consultancy; Roche/Genentech: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Celgene Corporation: Consultancy; Cellectis: Research Funding; Orsenix: Consultancy; Aphivena Therapeutics: Consultancy; Otsuka: Consultancy; Jazz Pharmaceuticals: Consultancy; Sandoz: Consultancy; Roche/Genentech: Consultancy; Aphivena Therapeutics: Consultancy; AbbVie: Consultancy; Bayer: Consultancy; Bayer: Consultancy; Astex Pharmaceuticals: Consultancy; Celgene Corporation: Consultancy; AbbVie: Consultancy. Döhner:Jazz: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Pfizer: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Valent:Pfizer: Honoraria; Novartis: Honoraria; Incyte: Honoraria. Platzbecker:Celgene: Research Funding. Lübbert:TEVA: Other: Study drug; Celgene: Other: Travel Support; Cheplapharm: Other: Study drug; Janssen: Honoraria, Research Funding. Díez-Campelo:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Stauder:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Teva: Research Funding. Germing:Janssen: Honoraria; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding