Full text
2,774 characters
· extracted from
oa-doi-fallback
· click to expand
Abstract
Bioprospecting algae strains with tolerance to extreme conditions such as pH, temperature, salinity, and light is crucial for advancing biotechnology and environmental applications. However, traditional screening methods often involve significant costs and labor, restricting their accessibility and practical use. In this study, we developed and validated low-cost, high-throughput screening techniques, predominantly employing agar plates and liquid culture assays, to effectively differentiate tolerance levels among various algae strains. The methodologies were optimized using the model microalga Chlamydomonas reinhardtii and its closely related species Chlamydomonas incerta and the recently discovered extremophilic Chlamydomonas pacifica. We systematically evaluated the algae for tolerance to extremes by establishing precise gradients of pH (acidic to alkaline conditions), salinity (0 to 5 M NaCl), temperature (34–42°C), and light intensity (40 to 2977 μE·m⁻²·s⁻¹). Our results demonstrated that these cost-effective, agar plate-based methods effectively distinguished algae strains exhibiting superior tolerance to extreme environmental conditions. These screening techniques not only provided clear differentiation among the closely related strains but also delivered reproducible outcomes suitable for scaling up to larger bioprospecting efforts. Furthermore, the affordability and simplicity of these methods facilitate their implementation in resource-limited laboratories, thereby broadening participation in algae bioprospecting endeavors. This study highlights the potential of low-cost, accessible screening techniques to significantly enhance the discovery and characterization of algal strains with extreme traits. Ultimately, these methods support the development of robust algae-based resources, driving innovation in diverse industrial processes and environmental solutions.
Competing Interest Statement
SM was a founding member and holds an equity stake in Algenesis Materials Inc. Algenesis Materials played no role in funding, study design, data collection and analysis, the decision to publish, or manuscript preparation. Our adherence to policies on sharing data and material remains the same. The remaining authors declare that the research was conducted without commercial or financial relationships that could be construed as a potential conflict of interest.
Footnotes
Barbara Saucedo: barbarasaucedozoso{at}gmail.com, Kalisa Kang: k4kang{at}ucsd.edu, Lauren May: lmay7302{at}gmail.com, Abhishek Gupta: a8gupta{at}ucsd.edu, Évellin do Espirito Santo: evellin.santo{at}usp.br, Stephen Mayfield: smayfield{at}ucsd.edu, João Vitor Dutra Molino: candidomolino{at}gmail.com
https://www.youtube.com/watch?v=4yDHsPnsOm8&feature=youtu.be
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.