Genomic analysis and characterization of Scenedesmus glucoliberatum PABB004: An unconventional sugar-secreting green alga

Natalia Calixto Mancipe, Evelyn M. McLaughlin, Brett M. Barney

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4 Scopus citations


Aims: In this report, we present Scenedesmus glucoliberatum PABB004, a microalga that was isolated from an association with Paramecium bursaria with the potential for application in fermentative processes and co-culture schemes due to its advantageous high sugar secretion phenotype. Methods and Results: We sequenced, assembled and annotated the draft genome and transcriptome for this newly reported strain. The nuclear genome has an exceptionally high GC content of 78%. Our results revealed significant sugar accumulation over a range from 6.2 to 7.8 pH units. The predicted proteome was compared with other green algae that show different sugar secretion phenotypes aiming to help uncover their common features for simple sugar secretion and those unique to S. glucoliberatum PABB004. Conclusions: The evolutionary history of this organism, inferred from its genomic traits, expands our current understanding of algal mutualistic relationships involving photosynthate exchanges. S. glucoliberatum PABB004 secreted ready-to-use fermentable sugars (glucose and maltose) directly to the extracellular media achieving concentrations greater than 2.7 g/L of free glucose and 1.2 g/L of maltose in batch cultures. Significance and Impact of the Study: A draft genome is provided for a new member of an important class of green algae. Scenedesmus glucoliberatum PABB004 secretes high levels of simple sugars over a broad pH range.

Original languageEnglish (US)
Pages (from-to)2004-2019
Number of pages16
JournalJournal of Applied Microbiology
Issue number3
StatePublished - Mar 2022

Bibliographical note

Funding Information:
The authors thank Dr. Gail Celio at the University of Minnesota – University Imaging Centers for her assistance on the production of microscopy images, Dr. Kevin Silverstein and the Minnesota Supercomputer Institute for their helpful suggestions and support on the bioinformatic analysis. The authors thank Aaron Becker and Karl Oles for direction and assistance related to DNA and RNA sequencing data collection and optimization. We also thank Cassedy Coleman, Matthew Arriola, Kalene Mulliner and Mary Plunkett for early assistance with data collection. The authors declare no conflict of interest associated with this work. This work was supported by grants (RC‐0007‐12) from the Initiative for Renewable Energy & the Environment (Institute on the Environment); the MnDRIVE transdisciplinary research initiative through the University of Minnesota based on funding from the state of Minnesota; the National Institute of Food and Agriculture (Project Numbers MIN‐12‐070 and MIN‐12‐081); and award number 2020‐67019‐31148 through the United States Department of Agriculture. NCM thanks the 2020 UMII MnDRIVE Graduate Assistantship for its support.

Publisher Copyright:
© 2021 The Society for Applied Microbiology


  • Scenedesmus
  • algae
  • fermentation
  • genome
  • sugar secretion


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