Macroalgal deep genomics illuminate multiple paths to aquatic, photosynthetic multicellularity.

Macroalgae are multicellular, aquatic autotrophs that play vital roles in global climate maintenance and have diverse applications in biotechnology and eco-engineering, which are directly linked to their multicellularity phenotypes. However, their genomic diversity and the evolutionary mechanisms underlying multicellularity in these organisms remain uncharacterized. In this study, we sequenced 110 macroalgal genomes from diverse climates and phyla, and identified key genomic features that distinguish them from their microalgal relatives. Genes for cell adhesion, extracellular matrix formation, cell polarity, transport, and cell differentiation distinguish macroalgae from microalgae across all three major phyla, constituting conserved and unique gene sets supporting multicellular processes. Adhesome genes show phylum- and climate-specific expansions that may facilitate niche adaptation. Collectively, our study reveals genetic determinants of convergent and divergent evolutionary trajectories that have shaped morphological diversity in macroalgae and provides genome-wide frameworks to understand photosynthetic multicellular evolution in aquatic environments.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor.

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Basal interaction of the orphan receptor GPR101 with arrestins leads to constitutive internalization.

GPR101 is an orphan G protein-coupled receptor that promotes growth hormone secretion in the pituitary. The microduplication of the GPR101 gene has been linked with the X-linked acrogigantism, or X-LAG, syndrome. This disease is characterized by excessive growth hormone secretion and abnormal rapid growth beginning early in life. Mechanistically, GPR101 induces growth hormone secretion through constitutive activation of multiple heterotrimeric G proteins. However, the full scope of GPR101 signaling remains largely elusive. Herein, we investigated the association of GPR101 to multiple transducers and uncovered an important basal interaction with Arrestin 2 (ß-arrestin 1) and Arrestin 3 (ß-arrestin 2). By using a GPR101 mutant lacking the C-terminus and cell lines with an Arrestin 2/3 null background, we show that the arrestin association leads to constitutive clathrin- and dynamin-mediated GPR101 internalization. To further highlight GPR101 intracellular fate, we assessed the colocalization of GPR101 with Rab protein markers. Internalized GPR101 was mainly colocalized with the early endosome markers, Rab5 and EEA-1, and to a lesser degree with the late endosome marker Rab7. However, GPR101 was not colocalized with the recycling endosome marker Rab11. These findings show that the basal arrestin recruitment by GPR101 C-terminal tail drives the receptor constitutive clathrin-mediated internalization. Intracellularly, GPR101 concentrates in the endosomal compartment and is degraded through the lysosomal pathway. In conclusion, we uncovered a constitutive intracellular trafficking of GPR101 that potentially represents an important layer of regulation of its signaling and function.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor.

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

Identification of small molecule antivirals against HTLV-1 by targeting the hDLG1-Tax-1 protein-protein interaction.

Human T-cell leukemia virus type-1 (HTLV-1) is the first pathogenic retrovirus discovered in human. Although HTLV-1-induced diseases are well-characterized and linked to the encoded Tax-1 oncoprotein, there is currently no strategy to target Tax-1 functions with small molecules. Here, we analyzed the binding of Tax-1 to the human homolog of the drosophila discs large tumor suppressor (hDLG1/SAP97), a multi-domain scaffolding protein involved in Tax-1-transformation ability. We have solved the structures of the PDZ binding motif (PBM) of Tax-1 in complex with the PDZ1 and PDZ2 domains of hDLG1 and assessed the binding of 10 million molecules by virtual screening. Among the 19 experimentally confirmed compounds, one systematically inhibited the Tax-1-hDLG1 interaction in different biophysical and cellular assays, as well as HTLV-1 cell-to-cell transmission in a T-cell model. Thus, our work demonstrates that interactions involving Tax-1 PDZ-domains are amenable to small-molecule inhibition, which provides a framework for the design of targeted therapies for HTLV-1-induced diseases.

The helicase-like transcription factor redirects the autophagic flux and restricts human T cell leukemia virus type 1 infection.

Retroviruses and their host have coevolved in a delicate balance between viral replication and survival of the infected cell. In this equilibrium, restriction factors expressed by infected cells control different steps of retroviral replication such as entry, uncoating, nuclear import, expression, or budding. Here, we describe a mechanism of restriction against human T cell leukemia virus type 1 (HTLV-1) by the helicase-like transcription factor (HLTF). We show that RNA and protein levels of HLTF are reduced in primary T cells of HTLV-1-infected subjects, suggesting a clinical relevance. We further demonstrate that the viral oncogene Tax represses HLTF transcription via the Enhancer of zeste homolog 2 methyltransferase of the Polycomb repressive complex 2. The Tax protein also directly interacts with HLTF and induces its proteasomal degradation. RNA interference and gene transduction in HTLV-1-infected T cells derived from patients indicate that HLTF is a restriction factor. Restoring the normal levels of HLTF expression induces the dispersal of the Golgi apparatus and overproduction of secretory granules. By synergizing with Tax-mediated NF-κB activation, physiologically relevant levels of HLTF intensify the autophagic flux. Increased vesicular trafficking leads to an enlargement of the lysosomes and the production of large vacuoles containing viral particles. HLTF induction in HTLV-1-infected cells significantly increases the percentage of defective virions. In conclusion, HLTF-mediated activation of the autophagic flux blunts the infectious replication cycle of HTLV-1, revealing an original mode of viral restriction.

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease.

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

Assessment of community efforts to advance network-based prediction of protein-protein interactions.

Comprehensive understanding of the human protein-protein interaction (PPI) network, aka the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of previously uncharacterized PPIs. Many such methods have been proposed. Yet, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 26 representative network-based methods to predict PPIs across six different interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. Through extensive computational and experimental validations, we found that advanced similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods in the interactomes we considered.

Human papillomavirus E6/E7 oncoproteins promote radiotherapy-mediated tumor suppression by globally hijacking host DNA damage repair.

Rationale: Whatever the mucosa primary infected, HPV-positive cancers are traditionally associated with a favorable outcome, attributable to a high sensitivity to radiation therapy. However, the direct impact of viral E6/E7 oncoproteins on the intrinsic cellular radiosensitivity (and, globally, on host DNA repair) remains mostly speculative. Methods: Using several isogenic cell models expressing HPV16 E6 and/or E7, the effect of viral oncoproteins on global DNA damage response was first investigated by in vitro/in vivo approaches. The binary interactome of each individual HPV oncoprotein with factors involved in the various host DNA damage/repair mechanisms was then precisely mapped by Gaussia princeps luciferase complementation assay (and validated by co-immunoprecipitation). The stability/half-life of protein targets for HPV E6 and/or E7 as well as their subcellular localizations were determined. At last, the host genome integrity following E6/E7 expression and the synergy between radiotherapy and compounds targeting DNA repair were analyzed. Results: We first showed that the sole expression of one viral oncoprotein from HPV16 was able to significantly increase the sensitivity to irradiation of cells without affecting their basal viability parameters. In total, 10 novel targets (CHEK2, CLK2, CLK2/3, ERCC3, MNAT1, PER1, RMI1, RPA1, UVSSA and XRCC6) for E6 and 11 (ALKBH2, CHEK2, DNA2, DUT, ENDOV, ERCC3, PARP3, PMS1, PNKP, POLDIP2 and RBBP8) for E7 were identified. Importantly, not degraded following their interaction with E6 or E7, these proteins have been shown to be less linked to host DNA and to colocalize with HPV replication foci, denoting their crucial implication in viral life cycle. Finally, we found that E6/E7 oncoproteins globally jeopardize host genome integrity, increase the cellular sensitivity to DNA repair inhibitors and enhance their synergy with radiotherapy. Conclusion: Taken together, our findings provide a molecular insight into the direct hijacking of host DNA damage/repair responses by HPV oncoproteins, demonstrate the significant impact of this phenomenon on both intrinsic cellular radiosensitivity and host DNA integrity and suggest novel connected therapeutic vulnerabilities.

A proteome-scale map of the SARS-CoV-2-human contactome.

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

Closing the Gap between Bio-Based and Petroleum-Based Plastic through Bioengineering.

Bioplastics, which are plastic materials produced from renewable bio-based feedstocks, have been investigated for their potential as an attractive alternative to petroleum-based plastics. Despite the harmful effects of plastic accumulation in the environment, bioplastic production is still underdeveloped. Recent advances in strain development, genome sequencing, and editing technologies have accelerated research efforts toward bioplastic production and helped to advance its goal of replacing conventional plastics. In this review, we highlight bioengineering approaches, new advancements, and related challenges in the bioproduction and biodegradation of plastics. We cover different types of polymers, including polylactic acid (PLA) and polyhydroxyalkanoates (PHAs and PHBs) produced by bacterial, microalgal, and plant species naturally as well as through genetic engineering. Moreover, we provide detailed information on pathways that produce PHAs and PHBs in bacteria. Lastly, we present the prospect of using large-scale genome engineering to enhance strains and develop microalgae as a sustainable production platform.

Bioscreening and pre-clinical evaluation of the impact of bioactive molecules from Ptychotis verticillata on the multilineage potential of mesenchymal stromal cells towards immune- and inflammation-mediated diseases.

OBJECTIVE AND DESIGN: Mesenchymal stromal cells (MSCs) are currently used in cell reparative medicine due to their trophic and ant-inflammatory properties. The modulation of stem cell properties by phytochemicals has been suggested as a tool to empower their tissue repair capacity. In vitro, MSCs are characterized by their tri-lineage potential that holds great interest for tissue regeneration. Ptychotis Verticillata (PV), an aromatic and medicinal plant, may be thus used to modulate the in vitro multilineage potential of MSCs. MATERIALS AND METHODS: We screened the impact of PV-derived essential oil and their bioactive molecules (thymol and carvacrol) on the in vitro multilineage potential of MSCs. Different concentrations and incubation times of these compounds were assessed during the osteogenesis and adipogenesis of MSCs. RESULTS: The analysis of 75 conditions indicates that these compounds are biologically active by promoting two major differentiation lineages from MSCs. In a time- and dose-dependent manner, thymol and carvacrol increased the osteogenesis and adipogenesis. CONCLUSION: According to these preliminary observations, the addition of PV extract may stimulate the tissue regenerative and repair functions of MSCs. Further optimization of compound extraction and characterization from PV as well as cell treatment conditions should increase their therapeutic value in combination with MSCs.

HPV infection alters vaginal microbiome through down-regulating host mucosal innate peptides used by Lactobacilli as amino acid sources.

Despite the high prevalence of both cervico-vaginal human papillomavirus (HPV) infection and bacterial vaginosis (BV) worldwide, their causal relationship remains unclear. While BV has been presumed to be a risk factor for HPV acquisition and related carcinogenesis for a long time, here, supported by both a large retrospective follow-up study (n = 6,085) and extensive in vivo data using the K14-HPV16 transgenic mouse model, we report a novel blueprint in which the opposite association also exists. Mechanistically, by interacting with several core members (NEMO, CK1 and ß-TrCP) of both NF-κB and Wnt/ß-catenin signaling pathways, we show that HPV E7 oncoprotein greatly inhibits host defense peptide expression. Physiologically secreted by the squamous mucosa lining the lower female genital tract, we demonstrate that some of these latter are fundamental factors governing host-microbial interactions. More specifically, several innate molecules down-regulated in case of HPV infection are hydrolyzed, internalized and used by the predominant Lactobacillus species as amino acid source sustaining their growth/survival. Collectively, this study reveals a new viral immune evasion strategy which, by its persistent/negative impact on lactic acid bacteria, ultimately causes the dysbiosis of vaginal microbiota.

Extracellular Vesicle Proteomes Shed Light on the Evolutionary, Interactive, and Functional Divergence of Their Biogenesis Mechanisms.

Extracellular vesicles (EVs) are membranous structures containing bioactive molecules, secreted by most cells into the extracellular environment. EVs are classified by their biogenesis mechanisms into two major subtypes: ectosomes (enriched in large EVs; lEVs), budding directly from the plasma membrane, which is common in both prokaryotes and eukaryotes, and exosomes (enriched in small EVs; sEVs) generated through the multivesicular bodies via the endomembrane system, which is unique to eukaryotes. Even though recent proteomic analyses have identified key proteins associated with EV subtypes, there has been no systematic analysis, thus far, to support the general validity and utility of current EV subtype separation methods, still largely dependent on physical properties, such as vesicular size and sedimentation. Here, we classified human EV proteomic datasets into two main categories based on distinct centrifugation protocols commonly used for isolating sEV or lEV fractions. We found characteristic, evolutionarily conserved profiles of sEV and lEV proteins linked to their respective biogenetic origins. This may suggest that the evolutionary trajectory of vesicular proteins may result in a membership bias toward specific EV subtypes. Protein-protein interaction (PPI) network analysis showed that vesicular proteins formed distinct clusters with proteins in the same EV fraction, providing evidence for the existence of EV subtype-specific protein recruiters. Moreover, we identified functional modules enriched in each fraction, including multivesicular body sorting for sEV, and mitochondria cellular respiration for lEV proteins. Our analysis successfully captured novel features of EVs embedded in heterogeneous proteomics studies and suggests specific protein markers and signatures to be used as quality controllers in the isolation procedure for subtype-enriched EV fractions.

The HTLV-1 viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape.

Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.

Alternative glycosylation controls endoplasmic reticulum dynamics and tubular extension in mammalian cells.

The endoplasmic reticulum (ER) is a central eukaryotic organelle with a tubular network made of hairpin proteins linked by hydrolysis of guanosine triphosphate nucleotides. Among posttranslational modifications initiated at the ER level, glycosylation is the most common reaction. However, our understanding of the impact of glycosylation on the ER structure remains unclear. Here, we show that exostosin-1 (EXT1) glycosyltransferase, an enzyme involved in N-glycosylation, is a key regulator of ER morphology and dynamics. We have integrated multiomics and superresolution imaging to characterize the broad effect of EXT1 inactivation, including the ER shape-dynamics-function relationships in mammalian cells. We have observed that inactivating EXT1 induces cell enlargement and enhances metabolic switches such as protein secretion. In particular, suppressing EXT1 in mouse thymocytes causes developmental dysfunctions associated with the ER network extension. Last, our data illuminate the physical and functional aspects of the ER proteome-glycome-lipidome structure axis, with implications in biotechnology and medicine.

Host PDZ-containing proteins targeted by SARS-CoV-2.

Small linear motifs targeting protein interacting domains called PSD-95/Dlg/ZO-1 (PDZ) have been identified at the C terminus of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins E, 3a, and N. Using a high-throughput approach of affinity-profiling against the full human PDZome, we identified sixteen human PDZ binders of SARS-CoV-2 proteins E, 3A, and N showing significant interactions with dissociation constants values ranging from 3 to 82 µm. Six of them (TJP1, PTPN13, HTRA1, PARD3, MLLT4, LNX2) are also recognized by SARS-CoV while three (NHERF1, MAST2, RADIL) are specific to SARS-CoV-2 E protein. Most of these SARS-CoV-2 protein partners are involved in cellular junctions/polarity and could be also linked to evasion mechanisms of the immune responses during viral infection. Among the binders of the SARS-CoV-2 proteins E, 3a, or N, seven significantly affect viral replication under knock down gene expression in infected cells. This PDZ profiling identifying human proteins potentially targeted by SARS-CoV-2 can help to understand the multifactorial severity of COVID19 and to conceive effective anti-coronaviral agents for therapeutic purposes.

Non-cytotoxic 1,2,3-triazole tethered fused heterocyclic ring derivatives display Tax protein inhibition and impair HTLV-1 infected cells.

Human T cell lymphotropic virus type 1 (HTLV-1) is a human retrovirus that infects approximately 10-20 million people worldwide and causes an aggressive neoplasia (adult T-cell leukemia/lymphoma - ATL). Therapeutic approaches for the treatment of ATL have variable effectiveness and poor prognosis, thus requiring strategies to identify novel compounds with activity on infected cells. In this sense, we initially screened a small series of 25 1,2,3-triazole derivatives to discover cell proliferation inhibitors and apoptosis inducers in HTLV-1-infected T-cell line (MT-2) for further assessment of their effect on viral tax activity through inducible-tax reporter cell line (Jurkat LTR-GFP). Eight promising compounds (02, 05, 06, 13, 15, 21, 22 and 25) with activity ≥70% were initially selected, based on a suitable cell-based assay using resazurin reduction method, and evaluated towards cell cycle, apoptosis and Tax/GFP expression analyses through flow cytometry. Compound 02 induced S phase cell cycle arrest and compounds 05, 06, 22 and 25 promoted apoptosis. Remarkably, compounds 22 and 25 also reduced GFP expression in an inducible-tax reporter cell, which suggests an effect on Tax viral protein. More importantly, compounds 02, 22 and 25 were not cytotoxic in human hepatoma cell line (Huh-7). Therefore, the discovery of 3 active and non-cytotoxic compounds against HTLV-1-infected cells can potentially contribute, as an initial promising strategy, to the development process of new drugs against ATL.