A directed genome evolution method to enhance hydrogen production in Rhodobacter capsulatus
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2022-08-24
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Frontiers Media
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Nitrogenase-dependent H2 production by photosynthetic bacteria, such as
Rhodobacter capsulatus, has been extensively investigated. An important
limitation to increase H2 production using genetic manipulation is the scarcity
of high-throughput screening methods to detect possible overproducing
mutants. Previously, we engineered R. capsulatus strains that emitted
fluorescence in response to H2 and used them to identify mutations in the
nitrogenase Fe protein leading to H2 overproduction. Here, we used ultraviolet
light to induce random mutations in the genome of the engineered H2-
sensing strain, and fluorescent-activated cell sorting to detect and isolate the
H2-overproducing cells from libraries containing 5 × 105
mutants. Three rounds
of mutagenesis and strain selection gradually increased H2 production up to
3-fold. The whole genomes of five H2 overproducing strains were sequenced
and compared to that of the parental sensor strain to determine the basis
for H2 overproduction. No mutations were present in well-characterized
functions related to nitrogen fixation, except for the transcriptional activator
nifA2. However, several mutations mapped to energy-generating systems and
to carbon metabolism-related functions, which could feed reducing power
or ATP to nitrogenase. Time-course experiments of nitrogenase depression in
batch cultures exposed mismatches between nitrogenase protein levels and
their H2 and ethylene production activities that suggested energy limitation.
Consistently, cultivating in a chemostat produced up to 19-fold more H2
than the corresponding batch cultures, revealing the potential of selected H2
overproducing strains.
Descripción
La beca de inicio del Consejo Europeo de Investigación (ERC) con el número 205442 financió la generación de cepas de sensores de hidrógeno. La "Fundación Iberdrola Ayudas a la Investigación en Energía y Medio Ambiente 2018" financió el secuenciamiento de ADN. La beca de la Universidad Politécnica de Madrid con el número RP160050022 financió el resto del trabajo.
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