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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]