The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization

Nelson, David R.; Khraiwesh, Basel; Fu, Weiqi; Alseekh, Saleh; Jaiswal, Ashish; Chaiboonchoe, Amphun; Hazzouri, Khaled M.; O'Connor, M.V.; Butterfoss, Glenn L.; Drou, Nizar; Rowe, Jillian; Harb, Jamil; Fernie, Alisdair R.; Gunsalus, Kristin C.; Salehi‐Ashtiani, Kourosh

doi:10.7554/elife.25783

Cited by 19 publications

(10 citation statements)

References 94 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because Trebouxiophytes, like Chloroidium, can use a wide variety of carbon sources for heterotrophic growth (Nelson et al, 2017), and viruses have been known to transfer carbohydrate-acting genes to their hosts (Van Etten et al, 2017), we searched for viral-associated carbohydrate-acting genes in the Chloroidium sp. UTEX3077 genome (Nelson et al, 2019).…”

Section: Llmentioning

confidence: 99%

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

Nelson

Hazzouri

Lauersen

et al. 2021

Cell Host & Microbe

Self Cite

View full text Add to dashboard Cite

Section: Llmentioning

confidence: 99%

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

Nelson

Hazzouri

Lauersen

et al. 2021

Cell Host & Microbe

Self Cite

View full text Add to dashboard Cite

“…WS7 ), and other freshwater green microalgae Chloroidium sp . UTEX3077 (Nelson et al., 2017), Chlorella variabilis NC64A, and Coccomyxa subellipsoidea clustered together, indicating a relatively similar HMM functional match profile (Figure 3). Dunaliella species were the exception to this clustering based on phylogenetic affinities, as they clustered with marine strains including diatom (Bacillariophyceae) and picoeukaryotic, oceanic ( Ostreococcus and Micromonas ) species.…”

Section: Resultsmentioning

confidence: 98%

Potential for Heightened Sulfur-Metabolic Capacity in Coastal Subtropical Microalgae

Nelson

Chaiboonchoe²,

Fu³

et al. 2019

iScience

Self Cite

View full text Add to dashboard Cite

SummaryThe 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.

show abstract

“…Further, as the nutritional requirements of most microalgae are not known, this platform can be used to define these rapidly. Nelson et al 43 had successfully applied these methods to identify new compounds that support the growth of the microalgae Chloroidium sp. UTEX 3007 and used the obtained information to define the species entry metabolites, which, unlike Chlamydomonas, include 40 different carbon sources.…”

Section: Discussionmentioning

confidence: 99%

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Alzahmi

Daakour

Assal

et al. 2021

JoVE

Self Cite

View full text Add to dashboard Cite

Metabolic models are reconstructed based on an organism's available genome annotation and provide predictive tools to study metabolic processes at a systemslevel. 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.network models can guide the rational designs for the rapid development of optimization strategies 1 , 2 , 3 , 4 .Although approximately 160 microalgal species have been sequenced 5 , there are, to our knowledge, only 44 algal

show abstract

The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization

Cited by 19 publications

References 94 publications

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

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

Potential for Heightened Sulfur-Metabolic Capacity in Coastal Subtropical Microalgae

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Contact Info

Product

Resources

About