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The green algal genus Picochlorum is of biotechnological interest because of its robust response to multiple environmental stresses. We compared the metabolic performance of P. SE3 and P. oklahomense to diverse microbial phototrophs and observed exceptional performance of photosystem II (PSII) in light energy conversion in both Picochlorum species. The quantum yield (QY) for O 2 evolution is the highest of any phototroph yet observed, 32% (20%) by P. SE3 (P. okl) when normalized to total PSII subunit PsbA (D1) protein, and 80% (75%) normalized per active PSII, respectively. Three factors contribute: (1) an efficient water oxidizing complex (WOC) with the fewest photochemical misses of any organism; (2) faster reoxidation of reduced (PQH 2 ) B in P. SE3 than in P. okl. (period-2 Fourier amplitude); and (3) rapid reoxidation of the plastoquinol pool by downstream electron carriers (Cyt b 6 f/PETC) that regenerates PQ faster in P. SE3. This performance gain is achieved without significant residue changes around the Q B site and thus points to a pull mechanism involving faster PQH 2 reoxidation by Cyt b 6 f/PETC that offsets charge recombination. This high flux in P. SE3 may be explained by genomically encoded plastoquinol terminal oxidases 1 and 2, whereas P. oklahomense has neither. Our results suggest two distinct types of PSII centers exist, one specializing in linear electron flow and the other in PSII-cyclic electron flow. Several amino acids within D1 differ from those in the low-light-descended D1 sequences conserved in Viridiplantae, and more closely match those in cyanobacterial high-light D1 isoforms, including changes near tyrosine Y z and a water/proton channel near the WOC. These residue changes may contribute to the exceptional performance of Picochlorum at high-light intensities by increasing the water oxidation efficiency and the electron/proton flux through the PSII acceptors (Q A Q B )., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

The goal of this study is to develop a general strategy for bacterial engineering using an integrated synthetic biology and machine learning (ML) approach. This strategy was developed in the context of increasing L-threonine production in Escherichia coli ATCC 21277. A set of 16 genes was initially selected based on metabolic pathway relevance to threonine biosynthesis and used for combinatorial cloning to construct a set of 385 strains to generate training data (i.e., a range of L-threonine titers linked to each of the specific gene combinations). Hybrid (regression/classification) deep learning (DL) models were developed and used to predict additional gene combinations in subsequent rounds of combinatorial cloning for increased L-threonine production based on the training data. As a result, E. coli strains built after just three rounds of iterative combinatorial cloning and model prediction generated higher L-threonine titers (from 2.7 g/L to 8.4 g/L) than those of patented L-threonine strains being used as controls (4-5 g/L). Interesting combinations of genes in L-threonine production included deletions of the tdh , metL , dapA , and dhaM genes as well as overexpression of the pntAB , ppc , and aspC genes. Mechanistic analysis of the metabolic system constraints for the best performing constructs offers ways to improve the models by adjusting weights for specific gene combinations. Graph theory analysis of pairwise gene modifications and corresponding levels of L-threonine production also suggests additional rules that can be incorporated into future ML models., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (©2023PublishedbyElsevierB.V.)

Diverging from the classic paradigm of random gene order in eukaryotes, gene proximity can be leveraged to systematically identify functionally related gene neighborhoods in eukaryotes, utilizing techniques pioneered in bacteria. Current methods of identifying gene neighborhoods typically rely on sequence similarity to characterized gene products. However, this approach is not robust for nonmodel organisms like algae, which are evolutionarily distant from well-characterized model organisms. Here, we utilize a comparative genomic approach to identify evolutionarily conserved proximal orthologous gene pairs conserved across at least two taxonomic classes of green algae. A total of 317 gene neighborhoods were identified. In some cases, gene proximity appears to have been conserved since before the streptophyte-chlorophyte split, 1,000 Ma. Using functional inferences derived from reconstructed evolutionary relationships, we identified several novel functional clusters. A putative mycosporine-like amino acid, "sunscreen," neighborhood contains genes similar to either vertebrate or cyanobacterial pathways, suggesting a novel mosaic biosynthetic pathway in green algae. One of two putative arsenic-detoxification neighborhoods includes an organoarsenical transporter (ArsJ), a glyceraldehyde 3-phosphate dehydrogenase-like gene, homologs of which are involved in arsenic detoxification in bacteria, and a novel algal-specific phosphoglycerate kinase-like gene. Mutants of the ArsJ-like transporter and phosphoglycerate kinase-like genes in Chlamydomonas reinhardtii were found to be sensitive to arsenate, providing experimental support for the role of these identified neighbors in resistance to arsenate. Potential evolutionary origins of neighborhoods are discussed, and updated annotations for formerly poorly annotated genes are presented, highlighting the potential of this strategy for functional annotation., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Separating specific cell phenotypes from a heterotypic mixture is a critical step in many research projects. Traditional methods usually require a large sample volume and a complex preparation process that may alter cell property during the sorting process. Here we present the use of electrical impedance as an indicator of cell health and for identifying specific microalgal phenotypes. We developed a microfluidic platform for measuring electrical impedance at different frequencies using the bacterium-sized green alga Picochlorum SE3. The cells were cultured under different salinity conditions and sampled at four different time points. Our results demonstrate the utility of electrical impedance as an indicator of cell phenotype by providing results that are consistent with known changes in cell size and physiology. Outliers in the cell data distribution are particularly useful because they represent phenotypes that have the ability to maintain size and/or membrane ionic permeability under prolonged salt stress. This suggests that our device can be used to identify and sort desired (e.g., experimentally evolved, mutant) cell phenotypes based on their electrical impedance properties.

Light and nutrients are critical regulators of photosynthesis and metabolism in plants and algae. Many algae have the metabolic flexibility to grow photoautotrophically, heterotrophically, or mixotrophically. Here, we describe reversible Glc-dependent repression/activation of oxygenic photosynthesis in the unicellular green alga Chromochloris zofingiensis. We observed rapid and reversible changes in photosynthesis, in the photosynthetic apparatus, in thylakoid ultrastructure, and in energy stores including lipids and starch. Following Glc addition in the light, C. zofingiensis shuts off photosynthesis within days and accumulates large amounts of commercially relevant bioproducts, including triacylglycerols and the high-value nutraceutical ketocarotenoid astaxanthin, while increasing culture biomass. RNA sequencing reveals reversible changes in the transcriptome that form the basis of this metabolic regulation. Functional enrichment analyses show that Glc represses photosynthetic pathways while ketocarotenoid biosynthesis and heterotrophic carbon metabolism are upregulated. Because sugars play fundamental regulatory roles in gene expression, physiology, metabolism, and growth in both plants and animals, we have developed a simple algal model system to investigate conserved eukaryotic sugar responses as well as mechanisms of thylakoid breakdown and biogenesis in chloroplasts. Understanding regulation of photosynthesis and metabolism in algae could enable bioengineering to reroute metabolism toward beneficial bioproducts for energy, food, pharmaceuticals, and human health., (© 2019 American Society of Plant Biologists. All rights reserved.)

Understanding how microalgae adapt to rapidly changing environments is not only important to science but can help clarify the potential impact of climate change on the biology of primary producers. We sequenced and analyzed the nuclear genome of multiple Picochlorum isolates (Chlorophyta) to elucidate strategies of environmental adaptation. It was previously found that coordinated gene regulation is involved in adaptation to salinity stress, and here we show that gene gain and loss also play key roles in adaptation. We determined the extent of horizontal gene transfer (HGT) from prokaryotes and their role in the origin of novel functions in the Picochlorum clade. HGT is an ongoing and dynamic process in this algal clade with adaptation being driven by transfer, divergence, and loss. One HGT candidate that is differentially expressed under salinity stress is indolepyruvate decarboxylase that is involved in the production of a plant auxin that mediates bacteria-diatom symbiotic interactions. Large differences in levels of heterozygosity were found in diploid haplotypes among Picochlorum isolates. Biallelic divergence was pronounced in P. oklahomensis (salt plains environment) when compared with its closely related sister taxon Picochlorum SENEW3 (brackish water environment), suggesting a role of diverged alleles in response to environmental stress. Our results elucidate how microbial eukaryotes with limited gene inventories expand habitat range from mesophilic to halophilic through allelic diversity, and with minor but important contributions made by HGT. We also explore how the nature and quality of genome data may impact inference of nuclear ploidy.

We report here the 98.5 Mbp haploid genome (12,924 protein coding genes) of Ulva mutabilis, a ubiquitous and iconic representative of the Ulvophyceae or green seaweeds. Ulva's rapid and abundant growth makes it a key contributor to coastal biogeochemical cycles; its role in marine sulfur cycles is particularly important because it produces high levels of dimethylsulfoniopropionate (DMSP), the main precursor of volatile dimethyl sulfide (DMS). Rapid growth makes Ulva attractive biomass feedstock but also increasingly a driver of nuisance "green tides." Ulvophytes are key to understanding the evolution of multicellularity in the green lineage, and Ulva morphogenesis is dependent on bacterial signals, making it an important species with which to study cross-kingdom communication. Our sequenced genome informs these aspects of ulvophyte cell biology, physiology, and ecology. Gene family expansions associated with multicellularity are distinct from those of freshwater algae. Candidate genes, including some that arose following horizontal gene transfer from chromalveolates, are present for the transport and metabolism of DMSP. The Ulva genome offers, therefore, new opportunities to understand coastal and marine ecosystems and the fundamental evolution of the green lineage., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

An expected outcome of climate change is intensification of the global water cycle, which magnifies surface water fluxes, and consequently alters salinity patterns. It is therefore important to understand the adaptations and limits of microalgae to survive changing salinities. To this end, we sequenced the 13.5 Mbp genome of the halotolerant green alga Picochlorum SENEW3 (SE3) that was isolated from a brackish water pond subject to large seasonal salinity fluctuations. Picochlorum SE3 encodes 7367 genes, making it one of the smallest and most gene dense eukaryotic genomes known. Comparison with the pico-prasinophyte Ostreococcus tauri, a species with a limited range of salt tolerance, reveals the enrichment of transporters putatively involved in the salt stress response in Picochlorum SE3. Analysis of cultures and the protein complement highlight the metabolic flexibility of Picochlorum SE3 that encodes genes involved in urea metabolism, acetate assimilation and fermentation, acetoin production and glucose uptake, many of which form functional gene clusters. Twenty-four cases of horizontal gene transfer from bacterial sources were found in Picochlorum SE3 with these genes involved in stress adaptation including osmolyte production and growth promotion. Our results identify Picochlorum SE3 as a model for understanding microalgal adaptation to stressful, fluctuating environments., (© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.)