Evidence map›Paper›PMID 35087023›Full record

ArticleNature communications2022

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.

Bin Long, Bart Fischer, Yining Zeng, Zoe Amerigian, Qiang Li, Henry Bryant, Man Li, Susie Y Dai, Joshua S Yuan

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Review
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  6. Harnessing microalgae for bioproducts: innovations in synthetic biology.World journal of microbiology & biotechnology · 2025
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  7. Review
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  11. Towards AI-designed genomes using a variational autoencoder.Proceedings. Biological sciences · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Bin LongDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA.ORCID http://orcid.org/0000-0003-1680-4700
Bart FischerDepartment of Agricultural Economics, Texas A&M University, College Station, TX, 77843, USA.
Yining ZengRenewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA.
Zoe AmerigianDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA.ORCID http://orcid.org/0000-0003-0259-9582
Qiang LiDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA.
Henry BryantDepartment of Agricultural Economics, Texas A&M University, College Station, TX, 77843, USA.
Man LiDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA.
Susie Y DaiDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA.
Joshua S YuanDepartment of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77843, USA. syuan@tamu.edu.ORCID http://orcid.org/0000-0002-0129-3904

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a semi-continuous algal cultivation (SAC) to sustain optimal cell growth and minimize mutual shading. An aggregation-based sedimentation (ABS) strategy is then designed to achieve low-cost biomass harvesting and economical SAC. The ABS is achieved by engineering a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which increases cyanobacterial cell surface hydrophobicity and enables efficient cell aggregation and sedimentation. SAC unleashes cyanobacterial growth potential with 0.1 g/L/hour biomass productivity and 0.2 mg/L/hour limonene productivity over a sustained period in photobioreactors. Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 g/m

Indexed as

BiofuelsMachine LearningSynthetic BiologyBiomassBiotechnologyIndustrial MicrobiologyMetabolic EngineeringMicroalgaePhotobioreactorsPondsRenewable EnergySynechococcusBiofuels

Identifiers

PMID35087023
PMCPMC8795378

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.