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.

High-Throughput Metabolic Profiling for Model Refinements of Microalgae.

Metabolic models are reconstructed based on an organism's available genome annotation and provide predictive tools to study metabolic processes at a systems-level. Genome-scale metabolic models may include gaps as well as reactions that are unverified experimentally. Reconstructed models of newly isolated microalgal species will result in weaknesses due to these gaps, as there is usually sparse biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology is an effective, high-throughput method that functionally determines cellular metabolic activities in response to a wide array of entry metabolites. Combining the high throughput phenotypic assays with metabolic modeling can allow existing metabolic network models to be rapidly reconstructed or optimized by providing biochemical evidence to support and expand genomic evidence. This work will show the use of PM assays for the study of microalgae by using the green microalgal model species Chlamydomonas reinhardtii as an example. Experimental evidence for over 254 reactions obtained by PM was used in this study to expand and refine a genome-scale C. reinhardtii metabolic network model, iRC1080, by approximately 25 percent. The protocol created here can be used as a basis for functionally profiling the metabolism of other microalgae, including known microalgae mutants and new isolates.

Protocol to generate and characterize biofouling transformants of a model marine diatom.

Diatoms are a major group of microalgae that initiate biofouling by surface colonization of human-made underwater structures; however, the involved regulatory pathways remain uncharacterized. Here, we describe a protocol for identifying and validating regulatory genes involved in the morphology shift of the model diatom species Phaeodactylum tricornutum during surface colonization. We also provide a workflow for characterizing biofouling transformants. By using this protocol, gene targets such as GPCR signaling genes could be identified and manipulated to turn off diatom biofouling. For complete information on the generation and use of this protocol, please refer to Fu et al. (2020).

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.

Large-scale genome sequencing reveals the driving forces of viruses in microalgal evolution.

Being integral primary producers in diverse ecosystems, microalgal genomes could be mined for ecological insights, but representative genome sequences are lacking for many phyla. We cultured and sequenced 107 microalgae species from 11 different phyla indigenous to varied geographies and climates. This collection was used to resolve genomic differences between saltwater and freshwater microalgae. Freshwater species showed domain-centric ontology enrichment for nuclear and nuclear membrane functions, while saltwater species were enriched in organellar and cellular membrane functions. Further, marine species contained significantly more viral families in their genomes (p = 8e-4). Sequences from Chlorovirus, Coccolithovirus, Pandoravirus, Marseillevirus, Tupanvirus, and other viruses were found integrated into the genomes of algal from marine environments. These viral-origin sequences were found to be expressed and code for a wide variety of functions. Together, this study comprehensively defines the expanse of protein-coding and viral elements in microalgal genomes and posits a unified adaptive strategy for algal halotolerance.

GPCR Genes as Activators of Surface Colonization Pathways in a Model Marine Diatom.

Surface colonization allows diatoms, a dominant group of phytoplankton in oceans, to adapt to harsh marine environments while mediating biofoulings to human-made underwater facilities. The regulatory pathways underlying diatom surface colonization, which involves morphotype switching in some species, remain mostly unknown. Here, we describe the identification of 61 signaling genes, including G-protein-coupled receptors (GPCRs) and protein kinases, which are differentially regulated during surface colonization in the model diatom species, Phaeodactylum tricornutum. We show that the transformation of P. tricornutum with constructs expressing individual GPCR genes induces cells to adopt the surface colonization morphology. P. tricornutum cells transformed to express GPCR1A display 30% more resistance to UV light exposure than their non-biofouling wild-type counterparts, consistent with increased silicification of cell walls associated with the oval biofouling morphotype. Our results provide a mechanistic definition of morphological shifts during surface colonization and identify candidate target proteins for the screening of eco-friendly, anti-biofouling molecules.

Advances in microalgal research and engineering development.

Microalgae have been investigated for the photosynthetic production of natural products with industrial and biomedical applications. Their rapid growth offers an advantage over higher plants, while their complex metabolic capacities allow for the production of various molecules. Despite their potentials, molecular techniques are underdeveloped in microalgae compared to higher plants, fungi, and bacteria. However, recent advances in genome sequencing, strain development, and genome editing technologies, are providing thrust to enhance research on microalgal species that have branched out from several focal model organisms to encompass a great diversity of species. In this review, we highlight the recent, significant advances in microalgal research, with a focus on the development of new resources that can enhance work on model and non-model species.

Potential for Heightened Sulfur-Metabolic Capacity in Coastal Subtropical Microalgae.

The activities of microalgae support nutrient cycling that helps to sustain aquatic and terrestrial ecosystems. Most microalgal species, especially those from the subtropics, are genomically uncharacterized. Here we report the isolation and genomic characterization of 22 microalgal species from subtropical coastal regions belonging to multiple clades and three from temperate areas. Halotolerant strains including Halamphora, Dunaliella, Nannochloris, and Chloroidium comprised the majority of these isolates. The subtropical-based microalgae contained arrays of methyltransferase, pyridine nucleotide-disulfide oxidoreductase, abhydrolase, cystathionine synthase, and small-molecule transporter domains present at high relative abundance. We found that genes for sulfate transport, sulfotransferase, and glutathione S-transferase activities were especially abundant in subtropical, coastal microalgal species and halophytic species in general. Our metabolomics analyses indicate lineage- and habitat-specific sets of biomolecules implicated in niche-specific biological processes. This work effectively expands the collection of available microalgal genomes by ∼50%, and the generated resources provide perspectives for studying halophyte adaptive traits.

Systematic interactome mapping of acute lymphoblastic leukemia cancer gene products reveals EXT-1 tumor suppressor as a Notch1 and FBWX7 common interactor.

BACKGROUND: Perturbed genotypes in cancer can now be identified by whole genome sequencing of large number of diverse tumor samples, and observed gene mutations can be used for prognosis and classification of cancer subtypes. Although mutations in a few causative genes are directly linked to key signaling pathways perturbation, a global understanding of how known cancer genes drive oncogenesis in human is difficult to assess. METHODS: We collected available information about mutated genes in Acute Lymphoblastic Leukemia (ALL). Validated human protein interactions (PPI) were collected from IntAct, HPRD and BioGRID interactomics databases, or obtained using yeast two-hybrid screening assay. RESULTS: We have mapped interconnections between 116 cancer census gene products associated with ALL. Combining protein-protein interactions data and cancer-specific gene mutations information, we observed that 63 ALL-gene products are interconnected and identified 37 human proteins interacting with at least 2 ALL-gene products. We highlighted exclusive and coexistence genetic alterations in key signaling pathways including the PI3K/AKT and the NOTCH pathways. We then used different cell lines and reporter assay systems to validate the involvement of EXT1 in the Notch pathway. CONCLUSION: We propose that novel ALL-gene candidates can be identified based on their functional association with well-known cancer genes. We identified EXT1, a gene not previously linked to ALL via mutations, as a common interactor of NOTCH1 and FBXW7 regulating the NOTCH pathway in an FBXW7-dependend manner.

Targeting oncogenic interleukin-7 receptor signalling with N-acetylcysteine in T cell acute lymphoblastic leukaemia.

Activating mutations of the interleukin-7 receptor (IL7R) occur in approximately 10% of patients with T cell acute lymphoblastic leukaemia (T-ALL). Most mutations generate a cysteine at the transmembrane domain leading to receptor homodimerization through disulfide bond formation and ligand-independent activation of STAT5. We hypothesized that the reducing agent N-acetylcysteine (NAC), a well-tolerated drug used widely in clinical practice to treat acetaminophen overdose, would reduce disulfide bond formation, and inhibit mutant IL7R-mediated oncogenic signalling. We found that treatment with NAC disrupted IL7R homodimerization in IL7R-mutant DND-41 cells as assessed by non-reducing Western blot, as well as in a luciferase complementation assay. NAC led to STAT5 dephosphorylation and cell apoptosis at clinically achievable concentrations in DND-41 cells, and Ba/F3 cells transformed by an IL7R-mutant construct containing a cysteine insertion. The apoptotic effects of NAC could be rescued in part by a constitutively active allele of STAT5. Despite using doses lower than those tolerated in humans, NAC treatment significantly inhibited the progression of human DND-41 cells engrafted in immunodeficient mice. Thus, targeting leukaemogenic IL7R homodimerization with NAC offers a potentially effective and feasible therapeutic strategy that warrants testing in patients with T-ALL.

Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia.

Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their products is challenging because diseased phenotypes are likely dependent of complex molecular interaction networks. Using as models three different chromosomal translocations-ETV6-RUNX1 (TEL-AML1), BCR-ABL1, and TCF3-PBX1 (E2A-PBX1)-frequently found in precursor-B-cell acute lymphoblastic leukemia (preB-ALL), we develop an approach to extract perturbed molecular interactions from gene expression changes. We show that the MYC and JunD transcriptional circuits are specifically deregulated after ETV6-RUNX1 and TCF3-PBX1 gene fusions, respectively. We also identified the bulk mRNA NXF1-dependent machinery as a direct target for the TCF3-PBX1 fusion protein. Through a novel approach combining gene expression and interactome data analysis, we provide new insight into TCF3-PBX1 and ETV6-RUNX1 acute lymphoblastic leukemia.

Hox protein interactions: screening and network building.

Understanding the mode of action of Hox proteins requires the identification of molecular and cellular pathways they take part in. This includes to characterize the networks of protein-protein interactions involving Hox proteins. In this chapter we propose a strategy and methods to map Hox interaction networks, from yeast two-hybrid and high-throughput yeast two-hybrid interaction screening to bioinformatic analyses based on the software platform Cytoscape.

Host-pathogen interactome mapping for HTLV-1 and -2 retroviruses.

BACKGROUND: Human T-cell leukemia virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar to HTLV-1, causes no known overt disease. HTLV gene products are engaged in a dynamic struggle of activating and antagonistic interactions with host cells. Investigations focused on one or a few genes have identified several human factors interacting with HTLV viral proteins. Most of the available interaction data concern the highly investigated HTLV-1 Tax protein. Identifying shared and distinct host-pathogen protein interaction profiles for these two viruses would enlighten how they exploit distinctive or common strategies to subvert cellular pathways toward disease progression. RESULTS: We employ a scalable methodology for the systematic mapping and comparison of pathogen-host protein interactions that includes stringent yeast two-hybrid screening and systematic retest, as well as two independent validations through an additional protein interaction detection method and a functional transactivation assay. The final data set contained 166 interactions between 10 viral proteins and 122 human proteins. Among the 166 interactions identified, 87 and 79 involved HTLV-1 and HTLV-2 -encoded proteins, respectively. Targets for HTLV-1 and HTLV-2 proteins implicate a diverse set of cellular processes including the ubiquitin-proteasome system, the apoptosis, different cancer pathways and the Notch signaling pathway. CONCLUSIONS: This study constitutes a first pass, with homogeneous data, at comparative analysis of host targets for HTLV-1 and -2 retroviruses, complements currently existing data for formulation of systems biology models of retroviral induced diseases and presents new insights on biological pathways involved in retroviral infection.