Summary highlights of biomanufacturing research performed at the Joint BioEnergy Institute (JBEI) in March 2023

1. Office of Biological and Environmental Research
Lignin Deconstruction by Anaerobic Fungi
Background
• Lignin is the main structural component of plant cell walls
• Only one known mechanism in nature deconstructs lignin, and it requires oxygen
Approach
Anaerobic fungi from large herbivores produce a large volume of enzymes, and are
able to liberate sugars from plants without the use of oxygen. Here, we mined
anaerobic fungi for novel lignin-degrading abilities.
Results
Anaerobic fungi liberate sugars and aromatic groups from crude grasses. 2-D NMR
and GPC indicated that anaerobic fungi are almost completely breaking down the
beta-O-4 bond in these lignocellulosic grasses.
Significance/Impacts
For the first time, this study demonstrated that lignin can be deconstructed without
the use of oxygen. This opens the way to exploit anaerobes for lignin breakdown,
and to harness these enzymes and pathways for biomass conversion.
Lankiewicz, T. S. et al. (2023) Nature Microbiology DOI: 10.1038/s41564-023-01336-8 Figure 1: Anaerobic fungi thrive on crude lignocellulose
(reed canary grass).

2. Office of Biological and Environmental Research
Perspective on Oligomeric Products from Lignin Depolymerization:
Its Generation, Identification, and further Valorization
Background/Objective
• Conversion of lignin into targeted products remains challenging
• This review compares current valorization routes for lignin-derived
oligomers
Approach
Special attention was paid to analytical techniques (e.g., 2D-HSQC-
NMR, GPC, Maldi-TOF-MS and FT-ICR-MS) used for characterizing
depolymerized oligomeric lignin.
Results
The lack of comprehensive lignin standards to identify the lignin
oligomers is a challenge for the analysis of complex oligomeric
products and should be a focus for the community moving forward.
Significance/Impacts
The depolymerization of lignin provides access to a new dimension
of the utilization of lignin-based products.
Han, Y. et al. (2023) Industrial Chemistry & Materials, DOI: 10.1039/d2im00059h
Figure 1: The yields of oligomeric products (orange-colored, the weight percentages of
the oligomeric fractions are indicated inside the pie charts) from various reported
depolymerization processes of lignin.

3. Office of Biological and Environmental Research
Background/Objective
The white-rot fungus Phlebia radiata efficiently degrades lignin by
secreting laccases into its environment. The mechanisms by which P.
radiata controls expression and secretion of laccases are not well studied.
In this study, we identified a compound called promethazine that induces
laccase expression in Phlebia radiata and 4 other white-rot fungi.
Approach
• Measured growth and laccase activity toward oxidation of the
colorimetric compound ABTS across 480 conditions.
• Performed transcriptomics experiments to identify differentially
expressed genes.
Results
• Several Phlebia radiata genes associated with lignin modifying enzymes were
upregulated when grown in presence of promethazine.
• 40X increase in expression of laccase.
• Other white-rot fungi increase expression of laccases in presence of promethazine.
Significance/Impacts
• Increasing lignin degrading enzyme expression and secretion is important for increasing
rates of biological lignin degradation.
• Potential approach to higher enzyme manufacturing yields.
Phenothiazines rapidly induce laccase expression in the
white-rot fungus Phlebia radiata
Laccase activity
Hirakawa M.P., et al. (2023) Journal of Fungi. doi: 10.3390/jof9030371

4. Office of Biological and Environmental Research
Heterologous production of polycyclopropanated
fatty acids in Streptomyces
Background/Objective
• We had recently published on the microbial production of
polycyclopropanated fatty acids (POP-FAs)
• To facilitate further developments, our next aim was to share a protocol
Approach
We described the POP-FA production platform including pathway design,
strain construction, fermentation, extraction and data analysis
Results
Our protocol included video and graphic guidelines, critical steps and key
resources, troubleshooting recommendations, and best practices
Significance/Impacts
This protocol serves as a reference and aims to make reproducible our
accomplishments in the development of POP-FA fuels
Yin K., et al. (2023) STAR Protocols. doi: 10.1016/j.xpro.2023.102190
Figure 1: Graphical Abstract of the POP-FA production platform

5. Office of Biological and Environmental Research
T-Toxin Virulence Genes: Unconnected Dots
in a Sea of Repeats
Background/Objective
• The Southern Corn Leaf Blight epidemic nearly 50 years ago, was caused by
Cochlioblous heterostrophus which acquired the ability to produce T-toxin, a
linear polyketide
• The high A+T rich DNA surrounding the T-toxin biosynthetic cluster had
made large scale genomic assembly in these regions impossible with Sanger
and short read sequencing methods
Approach
We utilized long read sequencing to generate genome sequences for
Cochlioblous heterostrophus lab and field isolates in order to trace the
acquisition and domestication of the T-toxin polyketide gene cluster
Results
Facilitated by long-read sequencing, megabase scale, nucleotide-level resolution
has revealed the true organization of Tox1, the locus responsible for T-toxin
production and the SCLB epidemic of 1970
Significance/Impacts
Selective pressure led to both the acquisition and stabilization in the genome of the biosynthetic cluster, making C.
heterostrophus a "chassis" for synthetic biology driven by natural selection in the environment.
Haridas, S., et al. (2003) mBio, DOI: https://doi.org/10.1128/mbio.00261-23
Figure 1: Structural topography of the Tox1 region. The exact order and
spatial arrangement of known Tox1 genes is shown.

6. Office of Biological and Environmental Research
JBEI Enabled Publications

7. Office of Biological and Environmental Research
Biological research and self-driving labs in deep
space supported by artificial intelligence
Background
Space biology research aims to develop foundational knowledge to support deep space exploration and, ultimately,
bioengineer spacecraft and habitats for sustained multi-planetary life.
Approach
Here we present a summary of decadal recommendations from a
workshop organized by the NASA on artificial intelligence machine
learning and that offer solutions to space biology challenges.
Significance/Impacts
The integration of artificial intelligence into the field of space biology
will ultimately enable life to thrive in deep space.
Sanders, Lauren M., et al. (2023) Nature Machine Intelligence 5.3 https://doi.org/10.1038/s42256-023-00618-4
Figure 1: Deep space biological and biomedical data collection
and transfer. A cloud-based data management environment serves
as the nexus between space-based data and research and Earth-
based researchers and analysts, enabling open-science access to
data and analytics and facilitating preparation of AI-ready datasets.
Results/Recommendations
• Ensure all space biological data and information are generated with
strong data stewardship standards embracing FAIR principles.
• Develop self-driving labs for spaceflight, using data management
standards to inform the data output from automated experimental
platforms
• Adapt relevant existing AI, ML and modelling methods best suited
for space biology research implementation

8. Office of Biological and Environmental Research
Dynamic upregulation of the rate-limiting enzyme for
valerolactam biosynthesis in Corynebacterium glutamicum
Background
Valerolactam is a monomer used to manufacture high-value nylon-5 and nylon-6,5,
however, the biological production of valerolactam is limited by the cyclization step in
the valerolactam biosynthesis pathway.
Approach
• We designed a dynamic upregulation system for the enzymes that catalyze the rate-
limiting step in the valerolactam biosynthesis pathway, this dynamic upregulation system
was further engineered to have higher sensitivity and a higher dynamic output range.
• The engineered system were used to regulate the expression of the rate-limiting enzymes.
Results
• We were able to get the highest titer (12.33 g/L) of valerolactam based on the
engineered dynamic upregulation system.
• This study demonstrates the dynamic regulation system has a great application
potential for the metabolic engineering.
Significance/Impacts
• Lactams, with a market of millions of tons per year, is synthesized from petrochemical
source currently, and the biosynthesis of lactams is needed due to the environment
friendly and sustainable.
• The industrial application of the biosynthesized lactams is limited by their titers. Our
study provided a way to significantly improve the titer of valerolactam, which may
open the door for industrial producing of the biological synthesized lactams.
Zhao X., et al. Metabolic Engineering, doi: 10.1016/j.ymben.2023.02.005
Figure 1: (A) Valerolactam production and the dynamic regulatory system developed
here. (B) Comparison of the outputs of the evolved biosensor pBbS-E1 and pBbS-E1B1
with the original biosensor pBbS-sfGFP in different concentrations of valerolactam. (C)
Fed-batch ferementation of valerolactam production in C. glutamicum Val-9, Val-11 and
C. glutamicum Val-13 strains with dynamic regulatory system.
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9. Office of Biological and Environmental Research
Background/Objective
• A lack of oligosaccharides that resemble natural structures of cell wall glycans has been a limit for studying biochemical
features of enzymes involved in plant cell wall synthesis.
• This study has established a platform to synthesize long-chain oligosaccharides that are suitable substrates for cell wall-
synthesizing enzyme studies.
Approach
Two xylan dodecasaccharides with and without an artificial methyl group were chemo-
enzymatically synthesized through a coupling reaction of a glycosyl fluoride donor and
a thioglycoside acceptor that was catalyzed by the glycosynthase XynAE265G.
Results
The resulting methylated and non-methylated xylan dodecasaccharides are able to be
utilized by xylan-modifying enzymes, suggesting that the larger glycan products
generated from this chemo-enzymatic approach enables more biosynthetic studies.
Significance/Impacts
The presented chemo-enzymatic strategy in this study provides an easy access to larger
xylan oligosaccharides for biosynthetic studies, and it is competitive to purely chemical
synthesis where low yields in the glycosylation reactions may be observed.
Álvarez-Martínez, I., et al. Chemistry – A European Journal, DOI: 10.1002/chem.202203941
Figure 1: Scheme of chemo-enzymatic synthesis of long-chain
oligosaccharides for use as substrates for xylan-modifying enzymes. The
reaction products were analyzed by MALDI-TOF MS.
Chemo-Enzymatic Synthesis of Long-Chain
Oligosaccharides for Studying Xylan-Modifying Enzymes

10. Office of Biological and Environmental Research
Biomonitoring and precision health in deep space
supported by artificial intelligence
Background
Paradigm shifts in astronaut health systems are necessary to enable Earth-independent healthcare.
Approach
Here we present a summary of decadal recommendations from a workshop organized by NASA on artificial intelligence, machine
learning and modelling applications that offer key solutions toward these space health challenges.
Significance/Impacts
The recent emergence of terrestrial AI, ML and modelling brings a
key contribution towards making humanity multi-planetary
through spacecraft and habitat biomedical science support.
Scott, Ryan T., et al. Nature Machine Intelligence 5.3 (2023): 196-207, https://doi.org/10.1038/s42256-023-00617-5
Figure 1: The life cycle of AI/ML in space biology research and spaceflight
health enables full utilization of Open and FAIR space biological datasets
through a data management environment. AI/ML methods leveraging
neuromorphic processors and edge computing facilitate a layered and integrated
spectrum of in-flight data acquisition to power a Precision Space Health (PSH)
system for deep-space missions.
Results/Recommendations
• Develop hardware and data systems to enable efficient data collection.
• Develop stronger data management and AI-readiness metrics.
• Invest in an AI/ML/modelling ‘Zoo’: both repurpose current AI/ML
approaches and novel algorithms.
• Transition crew health from treatment to prevention.
• Develop a Precision Space Health (PSH) system for real-time, adaptable,
maximally autonomous decision-making and analysis.