- The document discusses four types of forage sorghum (brown-midrib, non-brown-midrib, photoperiod sensitive, and photoperiod insensitive) and their potential impact on the minimum ethanol selling price at a biorefinery using ionic liquid pretreatment. - Simulation results show that non-photoperiod sensitive sorghum may result in lower cost biofuels compared to high-yielding photoperiod sensitive varieties under certain conditions. - If lignin value increases, non-brown-midrib varieties become the most attractive option due to their higher biomass yield outweighing the lower lignin content of brown-midrib varieties.

1. Identifying Forage Sorghum Ideotypes for
Advanced Biorefineries
Background
• Sorghum spans a diverse range of phenotypes, and it is unclear which
are most desirable as bioenergy feedstocks.
• There are tradeoffs between biomass yield, lignin content, and starch
and sugar contents. High biomass-yielding PS varieties have
previously been considered preferable for bioenergy production.
Approach
• We explore four forage sorghum types, including brown-midrib (bmr),
non-bmr, photoperiod sensitive (PS), and photoperiod insensitive
(non-PS), from the perspective of their impact on minimum bioethanol
selling price (MESP) at an ionic liquid pretreatment-based biorefinery.
• We use field trial data, including yield and composition for each
commercial forage sorghum line, in combination with process
simulation and cash flow analysis to compare individual varieties and
the averages across each type based on MESP
Outcomes and Impacts
• If most starch and sugars from the panicle are retained during storage,
use of non-PS sorghum may result in lower-cost biofuels (MESP of
$1.26/L-gasoline equivalent) compared to high-yielding PS varieties.
• If advances in lignin utilization increase its value such that it can be
dried and sold for $0.50/kg, the MESP for each scenario is lowered
and non-bmr varieties become the most attractive option (MESP of
$1.08/L-gasoline equivalent).
• While bmr varieties have lower lignin content, their comparatively
lower biomass yield results in higher transportation costs that negate
its fuel-yield advantage.
Yang et al. (2021) ACS Sustain. Chem. Eng., doi: 10.1021/acssuschemeng.1c01706
Figure 2. Sensitivity analysis based on composition.
Scenario 1: lignin combustion for onsite energy
generation. Scenario 2: lignin utilization as a byproduct.
Results based on 5% land utilization.
Figure 1. Relationship between minimum ethanol selling
price (MESP: $/L-gasoline equivalent) and biomass yield t/ha
(Mg ha–1) using four forage sorghum types (18 hybrids)

2. Background
• Carbohydrate active enzymes (CAZymes) are vital for the
lignocellulose-based biorefinery. The development of
hypersecreting fungal protein production hosts is therefore a major
aim for both academia and industry. .
• However, despite advances in our understanding of their
regulation, the number of promising candidate genes for targeted
strain engineering remains limited.
Approach
• Here, we resequenced the genome of the classical
hypersecreting Neurospora crassa mutant exo-1 and identified the
causative point of mutation to reside in the F-box protein-encoding
gene.
Outcomes and Impacts
• The corresponding deletion strain displayed amylase and invertase
activities exceeding those of the carbon catabolite derepressed
strain Δcre-1, while glucose repression was still mostly functional in
Δexo-1.
• Aiming to elucidate the underlying mechanism of enzyme
hypersecretion, we found the high secretion of amylases and
invertase in Δexo-1 to be completely dependent on the
transcriptional regulator COL-26.
• we successfully transferred the hypersecretion trait of the exo-
1 disruption by reverse engineering into the industrially deployed
fungus Myceliophthora thermophila using CRISPR-Cas9.
• Our identification of an important F-box protein demonstrates the
strength of classical mutants combined with next-generation
sequencing to uncover unanticipated candidates for engineering.
Gabriel et al. (2021) Proc Natl Acad Soc, doi: 10.1073/pnas.2025689118
Figure 1. Hypersecretion activity of exo-1 mutant and
∆exo-1
The F-box protein gene exo- 1 is a target for reverse
engineering enzyme hypersecretion in filamentous fungi
Figure 2. A model for the function of Exo-1

3. A multiplexed nanostructure-initiator mass spectrometry
(NIMS) assay for simultaneously detecting glycosyl
hydrolase and lignin modifying enzyme activities
Outcomes
Using time-series analysis we determined that crude laccase from Ab has
the higher GH activity and that laccase from Mt has the higher activity
against our lignin model compound. Inhibitor studies showed a significant
reduction in Mt GH activity under low oxygen conditions and increased
activities in the presence of vanillin (common GH inhibitor).
1) Concept of a NIMS multiplexed glycoside
hydrolase and lignin modifying enzyme assay
Ing et al. Sci Rep 11, 11803 (2021) doi: 10.1038/s41598-021-91181-8
Background
Analytical tools capable of quickly detecting both glycan and lignin
deconstruction are needed to support the development and characterization
of efficient enzymes/enzyme cocktails to deconstruct lignocellulosic biomass.
Significance
These assays enable simultaneous analyses of both glycoside hydrolase
and lignin modifying enzyme activities which we anticipate will be helpful in
developing enzyme cocktails for lignocellulose deconstruction. Importantly,
we find that our assay is suitable to examine the inhibition of GH activities
by aromatics which is an important consideration in the development of
economically viable biomass to biofuels approaches.
2) Effect of mediators and inhibitory conditions on
cellotetraose degradation by (A) Mt (B) Ab and (C)
CelE CBM3a (n=3). “✽” indicate ANOVA post hoc
significant differences compared to enzyme only.
Approach
Previously we have described nanostructure-initiator mass spectrometry-
based assays for the analysis of glycosyl hydrolase and most recently an
assay for lignin modifying enzymes. Here we integrate these two assays into
a single multiplexed assay against both classes of enzymes and use it to
characterize crude commercial enzyme mixtures. Application of our
multiplexed platform based on nanostructure-initiator mass spectrometry
enabled us to characterize crude mixtures of laccase enzymes from fungi
Agaricus bisporus (Ab) and Myceliopthora thermophila (Mt) revealing activity
on both carbohydrate and aromatic substrates.

4. Microbial production of advanced biofuels
Background
• Concerns over climate change have necessitated a rethinking of
our transportation infrastructure.
• One possible alternative to carbon-polluting fossil fuels are
biofuels produced from a renewable carbon source using
engineered microorganisms.
• Two biofuels, ethanol and biodiesel, have made inroads to
displacing petroleum-based fuels, but their penetration has been
limited by the amounts that can be used in conventional engines
and by cost.
Approach
• Advanced biofuels that mimic petroleum-based fuels are not
limited by the amounts that can be used in existing transportation
infrastructure, but have had limited penetration due to costs.
• In this review, we discussed the advances in engineering
microbial metabolism to produce advanced biofuels and prospects
for reducing their costs.
Outcomes and Impacts
• We reviewed the engineering of microbial metabolic pathways to
produce advanced biofuels.
• We discussed recent advancements in the engineering of
microbial hosts to express these pathways.
• Methods for improving the carbon efficiency of conversion of
carbon-rich substrates to advanced biofuels were discussed. This
included systematic ways to improve titers, rates, and yields.
• Finally, we addressed the challenging in scale-up of biofuel
production, and the recent advances to address these challenges.
Keasling et al. (2021) Nat Rev Microbiol. doi: 10.1038/s41579-021-00577-w
Major sources of toxicity and inhibition of growth and production.
Three possible approaches to improve TRY in a systematic
manner. Growth coupling combined with Adaptive Lab Evolution
(ALE), leveraging Genome-Scale Models and Machine Learning.