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Open Access Publications from the University of California
Cover page of A novel approach for large-scale wind energy potential assessment

A novel approach for large-scale wind energy potential assessment

(2025)

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Cellular morphometric biomarkers and large language model predict prognosis and treatment response in neuroblastoma patients: A retrospective and double-blind prospective single arm clinical study

(2025)

Background

The heterogeneity of Neuroblastoma (NB) leads to variation in response to treatment and outcomes. The aim of the current study is to discover AI-empowered cellular morphometric biomarkers (CMBs), to establish the corresponding CMB risk score (CMBRS), CMB risk group (CMBRG), large language model driven CMB risk score (CMB-LLM-RS), and large language model driven CMB risk group (CMB-LLM-RG), and to investigate and validate their prognostic and predictive power in NB.

Methods

In this study, the retrospective cohort enrolled 84 primary NBs between 1/2020 and 12/2021, followed up through 11/22/2024; the prospective cohort enrolled 67 primary NBs between 1/2022 and 7/2023, followed up through 11/22/2024.

Results

We identified 9 CMBs from a retrospective NB cohort, enabling the CMBRS, CMBRG, CMB-LLM-RS, and CMB-LLM-RG. Both CMBRG and CMB-LLM-RG are significantly associated with prognosis (p < 0.0001) and treatment response (p < 0.0001). Furthermore, we double-blindly validated the predictive power of CMBRG and CMB-LLM-RG in a prospective NB cohort, which confirms their potential value in real clinical settings. Importantly, CMBRG provides clinical value independent of the International Neuroblastoma Risk Group (INRG) classification system in both retrospective and prospective NB cohorts (p < 0.05); and the combination of CMBRG and INRG significantly increases prognostic and predictive performance for NB patients.

Conclusions

These findings suggest that CMBRG and CMB-LLM-RG have prognostic and predictive value for NB and warrants evaluation in larger multicenter cohorts.

Cover page of Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source.

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source.

(2025)

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

Cover page of Comparative genomics of Aspergillus nidulans and section Nidulantes.

Comparative genomics of Aspergillus nidulans and section Nidulantes.

(2025)

Aspergillus nidulans is an important model organism for eukaryotic biology and the reference for the section Nidulantes in comparative studies. In this study, we de novo sequenced the genomes of 25 species of this section. Whole-genome phylogeny of 34 Aspergillus species and Penicillium chrysogenum clarifies the position of clades inside section Nidulantes. Comparative genomics reveals a high genetic diversity between species with 684 up to 2433 unique protein families. Furthermore, we categorized 2118 secondary metabolite gene clusters (SMGC) into 603 families across Aspergilli, with at least 40 % of the families shared between Nidulantes species. Genetic dereplication of SMGC and subsequent synteny analysis provides evidence for horizontal gene transfer of a SMGC. Proteins that have been investigated in A. nidulans as well as its SMGC families are generally present in the section Nidulantes, supporting its role as model organism. The set of genes encoding plant biomass-related CAZymes is highly conserved in section Nidulantes, while there is remarkable diversity of organization of MAT-loci both within and between the different clades. This study provides a deeper understanding of the genomic conservation and diversity of this section and supports the position of A. nidulans as a reference species for cell biology.

Cover page of Genetic and microbial determinants of azoxymethane-induced colorectal tumor susceptibility in Collaborative Cross mice and their implication in human cancer

Genetic and microbial determinants of azoxymethane-induced colorectal tumor susceptibility in Collaborative Cross mice and their implication in human cancer

(2024)

The insights into interactions between host genetics and gut microbiome (GM) in colorectal tumor susceptibility (CTS) remains lacking. We used Collaborative Cross mouse population model to identify genetic and microbial determinants of Azoxymethane-induced CTS. We identified 4417 CTS-associated single nucleotide polymorphisms (SNPs) containing 334 genes that were transcriptionally altered in human colorectal cancers (CRCs) and consistently clustered independent human CRC cohorts into two subgroups with different prognosis. We discovered a set of genera in early-life associated with CTS and defined a 16-genus signature that accurately predicted CTS, the majority of which were correlated with human CRCs. We identified 547 SNPs associated with abundances of these genera. Mediation analysis revealed GM as mediators partially exerting the effect of SNP UNC3869242 within Duox2 on CTS. Intestine cell-specific depletion of Duox2 altered GM composition and contribution of Duox2 depletion to CTS was significantly influenced by GM. Our findings provide potential novel targets for personalized CRC prevention and treatment.

Cover page of Methane to bioproducts: unraveling the potential of methanotrophs for biomanufacturing

Methane to bioproducts: unraveling the potential of methanotrophs for biomanufacturing

(2024)

With the continuous increase in the world population, anthropogenic activities will generate more waste and create greenhouse gases such as methane, amplifying global warming. The biological conversion of methane into biochemicals is a sustainable solution to sequester and convert this greenhouse gas. Methanotrophic bacteria fulfill this role by utilizing methane as a feedstock while manufacturing various bioproducts. Recently, methanotrophs have made their mark in industrial biomanufacturing. However, unlike glucose-utilizing model organisms such as Escherichia coli and Saccharomyces cerevisiae, methanotrophs do not have established transformation methods and genetic tools, making these organisms challenging to engineer. Despite these challenges, recent advancements in methanotroph engineering demonstrate great promise, showcasing these C1-carbon-utilizing microbes as prospective hosts for bioproduction. This review discusses the recent developments and challenges in strain engineering, biomolecule production, and process development methodologies in the methanotroph field.

Cover page of Site Suitability and Air Pollution Impacts of Composting Infrastructure for Californias Organic Waste Diversion Law.

Site Suitability and Air Pollution Impacts of Composting Infrastructure for Californias Organic Waste Diversion Law.

(2024)

Californias organic waste diversion law, SB 1383, mandates a 75% reduction in organics disposal by 2025 to reduce landfill methane emissions. Composting will likely be the primary alternative to landfilling, and 75-100 new large-scale composting facilities must be sited in the state to meet its diversion goal. We developed a strategy for evaluating site suitability for commercial composting by incorporating land-use, economic, and environmental justice criteria. In our Baseline scenario, we identified 899 candidate sites, and nearly all are within a cost-effective hauling distance of cropland and rangelands for compost application. About half of sites, mostly in rural areas, are not within a cost-effective collection distance of enough municipal organics to supply an average-sized facility. Conversely, sites near cities have greater access to organics but cause greater health damages from ammonia and volatile organic compounds emitted during the composting process. The additional required composting capacity corresponds to $266-355 million in annual damages from air pollution. However, this excludes avoided emissions from landfilling, and damages could be reduced by 56% if aerated static piles are used instead of windrows. Siting a higher number of smaller decentralized facilities could also help equally distribute air pollution to avoid concentrating burdens in certain communities.

Cover page of Assessing horizontal gene transfer in the rhizosphere of Brachypodium distachyon using fabricated ecosystems (EcoFABs).

Assessing horizontal gene transfer in the rhizosphere of Brachypodium distachyon using fabricated ecosystems (EcoFABs).

(2024)

Horizontal gene transfer (HGT) is a major process by which genes are transferred between microbes in the rhizosphere. However, examining HGT remains challenging due to the complexity of mimicking conditions within the rhizosphere. Fabricated ecosystems (EcoFABs) have been used to investigate several complex processes in plant-associated environments. Here we show that EcoFABs are efficient tools to examine and measure HGT frequency in the rhizosphere. We provide the first demonstration of gene transfer via a triparental conjugation system in the Brachypodium distachyon rhizosphere in an EcoFAB using Pseudomonas putida KT2440 as both donor and recipient bacterial strain with the donor containing a mobilizable and non-self-transmissible plasmid. We observed that the frequency of plasmid transfer in the rhizosphere is potentially dependent on the plant developmental stage and the composition and amount of root exudates. The frequency of plasmid transfer also increased with higher numbers of donor cells. We demonstrate the transfer of plasmid from P. putida to another B. distachyon root colonizer, Burkholderia sp. OAS925, showing HGT within a rhizosphere microbial community. Environmental stresses also influenced the rate and efficiency of HGT in the rhizosphere between different species and genera. This study provides a robust workflow to evaluate transfer of engineered plasmids in the rhizosphere when such plasmids are potentially introduced in a field or other plant-associated environments.IMPORTANCEWe report the use of EcoFABs to investigate the HGT process in a rhizosphere environment. It highlights the potential of EcoFABs in recapitulating the dynamic rhizosphere conditions as well as their versatility in studying plant-microbe interactions. This study also emphasizes the importance of studying the parameters impacting the HGT frequency. Several factors such as plant developmental stages, nutrient conditions, number of donor cells, and environmental stresses influence gene transfer within the rhizosphere microbial community. This study paves the way for future investigations into understanding the fate and movement of engineered plasmids in a field environment.