Skip to main content
eScholarship
Open Access Publications from the University of California
Cover page of Design and commissioning of a new synchrotron beamline dedicated to X‐ray footprinting mass spectrometry

Design and commissioning of a new synchrotron beamline dedicated to X‐ray footprinting mass spectrometry

(2026)

The structural biology method of X-ray footprinting mass spectrometry (XFMS) is available at two national synchrotron beamlines in the USA: one at the Advanced Light Source (ALS) on the West Coast and the other at the National Synchrotron Light Source II on the East Coast. XFMS is a solution-state technique that utilizes oxidative modifications of proteins at micromolar concentrations in aqueous buffer to extract structural information. X-rays are employed to generate hydroxyl radicals in situ, which covalently modify specific protein side chains. These modifications are subsequently quantified using liquid chromatography and mass spectrometry. Ratiometric changes in modification levels between two protein states (e.g. with and without ligand) generate a relative solvent accessibility map of the protein pairs, which serves to reveal structural features. Up until recently, the XFMS capability was available as part of a shared program at the ALS without a dedicated beamline. In this article, we describe the commissioning of ALS beamline 3.3.1, dedicated to XFMS, including the installation of a new focusing mirror, the design and construction of a new endstation with automated sample handling and exposure capabilities, and the use of accurate empirical dose calculations using Gafchromic film. Finally, we showcase the new beamline capabilities using two protein systems.

Cover page of From residue to cancer risk: How thirdhand smoke drives cancer hallmarks

From residue to cancer risk: How thirdhand smoke drives cancer hallmarks

(2026)

Thirdhand smoke (THS) is a reservoir of toxic compounds that persist in indoor environments and on surfaces long after active smoking has ceased. Major THS chemicals, including nicotine, tobacco-specific nitrosamines, polycyclic aromatic hydrocarbons, and heavy metals, can induce DNA damage, epigenetic alterations, oxidative stress, and chronic inflammation. These biological changes contribute to one or more canonical hallmarks of cancer. In this minireview, we propose an integrated mechanistic framework that incorporates the hallmarks of cancer into environmental exposure risk assessment. This framework offers a system-level approach to carcinogenicity assessment that transcends the limitations of conventional single-endpoint toxicological assays. As a case application, we systematically analyze how THS chemicals disrupt specific cancer hallmarks and delineate the molecular and cellular mechanisms through which persistent tobacco smoke residues promote carcinogenesis. These insights establish a mechanistically grounded framework for assessing the environmental cancer hazard associated with THS.

Identifying predictive hematological biomarkers for radiation exposure by machine learning in mouse models

(2026)

BackgroundPopulation-scale radiation exposure assessment during radiological emergencies is hindered by the slow and costly nature of current methods, creating a need for rapid, affordable screening tools. Radiation biodosimetry using peripheral blood counts is a promising approach, but estimating low-dose exposures and exposure at extended time points remains challenging, especially when accounting for inter-individual differences in radiation sensitivity.MethodsWe analyze complete blood count (CBC) profiles from a retrospective cohort of 1151 male and female BALB/cJ and C57BL/6 J mice exposed to total-body X-ray radiation at doses ranging from 0.05 to 4 Gy. CBCs are collected 1 to 150 days post exposure. We develop a predictive model of radiation exposure using a sparse representation learning strategy to identify the most informative CBC parameters. Model performance is evaluated through exhaustive cross-validation and validated in a double-blind prospective cohort of 431 animals. To evaluate robustness in a genetically diverse population, we further test the model on CBC data from a Collaborative Cross (CC) cohort of 1720 animals representing 35 CC strains, 24 h and 28 days after sham or 1 Gy total-body X-ray exposure.ResultsExhaustive cross-validation shows good performance of the Sparse CBC model, with AUC, accuracy and sensitivity exceeding 80%. Similar performance is observed in the prospective cohort. In the CC cohort, performance is modest. Importantly, model performance varies across CC strains, suggesting that host genetic background significantly influences predictive accuracy.ConclusionsOur findings demonstrate that the Sparse CBC model effectively leverages CBC data to estimate radiation exposure across multiple mouse cohorts, including genetically diverse CC populations. While CBC-based predictions provide a complementary tool for exposure assessment, model performance varies with genetic backgrounds.

Cover page of Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

(2026)

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

Cover page of Assembly and Reactions of Artificial Metalloenzymes in Streptomyces albus

Assembly and Reactions of Artificial Metalloenzymes in Streptomyces albus

(2026)

Artificial metalloenzymes (ArMs) expand the suite of synthetically valuable, new-to-nature biocatalytic reactions. Integrating these enzymes into biosynthetic pathways enables reactions not found in nature to occur in living cells with the intermediates or products of the metabolic pathways. However, the integration of reactions catalyzed by ArMs into complex metabolic pathways is constrained by the lack of methods to assemble these ArMs in organisms that are commonly used for metabolic engineering. We report the assembly of an iridium-containing artificial metalloenzyme (Ir-ArM) in Streptomyces albus, a Gram-positive bacterial chassis widely used for the heterologous expression of natural products. In this engineered organism, the Ir-ArM assembles in the cytoplasm and catalyzes abiological carbene transfer to the unactivated, disubstituted double bond of an exogenously added terpene with turnover numbers (TONs) that are two times higher than those for the same reaction catalyzed within E. coli cells harboring Ir-ArM and 20 times higher than the TONs for the same reaction catalyzed by the purified holoprotein itself.

Cover page of Demonstrating a butylamine-based deconstruction method for poplar biomass and conversion by diverse microbial strains

Demonstrating a butylamine-based deconstruction method for poplar biomass and conversion by diverse microbial strains

(2026)

Pretreatment of poplar biomass with butylamine released >100 g L −1 of fermentable sugars and supported the biosynthesis of three different bioproducts. Low-boiling alkylamines such as butylamine offer promise as effective biomass pretreatment solvents that can be readily recovered and recycled; however, their capability to support microbial conversion of nutrients present in hydrolysates represents an important area for investigation. Here we employed butylamine to pretreat poplar biomass and characterize its effects on the release of fermentable sugars after solvent removal and enzymatic hydrolysis, as well as the biocompatibility of the produced hydrolysates with three organisms commonly used as bioconversion hosts. We observed that residual butylamine and the derivative butylacetamide were present in high enough concentrations to exert toxicity to strains of Aspergillus niger , Pseudomonas putida , and Rhodosporidium toruloides that produce malic acid, isoprenol and bisabolene, respectively. Removal of the toxic compounds by charcoal filtration and nutrient supplementation resulted in a hydrolysate containing >100 g L −1 of sugars that enabled strong growth, substrate consumption and bioproduct accumulation, outperforming defined cultivation media. This is the first demonstration of a butylamine-based deconstruction process for poplar biomass at a pilot-scale to achieve conversion of high sugar concentrations to valuable bioproducts with engineered microbes.

Cover page of A “Sweet” Biorefinery: Sugar-derived ionic liquids for the pretreatment of lignocellulosic biomass

A “Sweet” Biorefinery: Sugar-derived ionic liquids for the pretreatment of lignocellulosic biomass

(2026)

Sugar-based ionic liquids (ILs) derived from biomass-based cations (choline, betaine) and sugar-derived anions were developed as sustainable pretreatment solvents to advance the concept of self-reliant biorefinery. Cholinium gluconate ([Ch][GlcA]) enabled streamlined one-pot sorghum pretreatment without the need for pH adjustment or washing, while betainium gluconate ([Bet][GlcA]) achieved higher sugar yields, improving overall process efficiency and economics. Both ILs produced hydrolysates fully compatible with microbial fermentation, demonstrating their potential for efficient, simplified biomass conversion. This work positions sugar-based ILs as powerful platforms that unite sustainable chemistry with integrated bioprocessing, marking a pivotal step toward realizing the self-reliant biorefinery.

Cover page of Polyketide synthase-based controlled synthesis of polycyclopropanated fuel molecules

Polyketide synthase-based controlled synthesis of polycyclopropanated fuel molecules

(2026)

Reducing carbon emissions from aviation and long-distance transportation sectors requires the development of sustainable biofuels with suitable energy density, freezing point, and other physical properties. We previously demonstrated biological production of high energy polycyclopropanated fatty acids (POP-FAs, class I) using an iterative polyketide synthase (iPKS) pathway in a Streptomyces host. Here, we used a computational model of fuel properties to identify chain length and cyclopropanation control as critical steps to engineer this iPKS for biofuel applications. We next explored the natural diversity of POP biosynthesis by investigating homologous pathways. Then, by in vivo gene exchange, we determined cyclopropanase (CP) catalysis to be key for POP-FA engineering. Leveraging both natural and engineered pathway product diversity, we demonstrate targeted production of improved POP-FAs, namely shortened POP-FAs with predicted superior freezing point properties for aviation, as well as fully cyclopropane-saturated POP-FAs which should have superior energy-density. These precise and controllable modifications to POP-FA structure open the door for bioproduction of designer POP fuels.

Cover page of The Use of Synchrotron Radiation in the Medical Sciences

The Use of Synchrotron Radiation in the Medical Sciences

(2026)

Synchrotron radiation (SR) sources provide unparalleled brilliance, collimation, coherence, and tunability, enabling specialized techniques that are crucial for advancing medical research across diverse fields from radiation oncology to rational drug design. Certain SR methods, such as macromolecular crystallography, are highly developed and automated, and have been used for decades for both fundamental understanding of biomolecules as well as pharmaceutical design, while other methods, such as microbeam radiation therapy, represent relatively recent developments. Scattering and diffraction methods using SR can provide atomic-level structural mapping of proteins, nucleic acids, and complexes. Imaging applications using SR continue to be developed and advanced for mapping of biological structures and potential use as diagnostics in disease detection. Spectroscopic methods are used to study elemental distributions relevant for detection of contamination in biological systems. Collectively, SR research delivers detailed multiscale structural and molecular information essential for addressing complex biomedical challenges. In this mini-review, we cover SR methods that are specifically relevant to medical applications, focusing mainly on SR X-ray and SR infrared techniques and applications. We include diffraction and scattering, imaging, absorption and fluorescent spectroscopy, use of SR in oncology treatments, and radiation damage methods that integrate one or another aspect of an SR method in conjunction with other non-SR techniques.

Cover page of Engineered Production of Hydroxycinnamoyl Tyramine Conjugates Limits the Growth of the Pathogen Pseudomonas syringae in Arabidopsis

Engineered Production of Hydroxycinnamoyl Tyramine Conjugates Limits the Growth of the Pathogen Pseudomonas syringae in Arabidopsis

(2026)

Hydroxycinnamoyl tyramine conjugates are phenolamides produced by plants in response to pathogen attack and biotic stresses. Their proposed mechanisms of action include cytotoxicity towards pathogens, cell wall reinforcement to restrict pathogen proliferation, and signaling activity to trigger general stress responses. Here, we engineered the production of the tyramine conjugates p-coumaroyltyramine (CT) and feruloyltyramine (FT) in Arabidopsis to gain insight into their mode of action. Co-expression of feedback-insensitive 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase and tyrosine decarboxylase increased tyramine content. Additional expression of tyramine hydroxycinnamoyltransferase led to de-novo production of CT and FT, which were found as soluble and cell-wall-bound forms. FT was associated with lignin in stems. The growth of pathogenic Pseudomonas syringae was reduced in rosettes of the Arabidopsis CT- and FT-producing lines compared to wild type. These lines also exhibited increased transpirational water loss in excised rosettes. Transcriptomic analysis of transgenic lines grown under normal conditions revealed alterations in the expression of genes associated with the biological circadian clock. These changes led to a reduction in flavonoids and an early flowering phenotype. Important changes in the expression of genes related to abiotic stress such as drought, cold, heat, and hypoxia potentially contribute to reduced growth of P. syringae in engineered Arabidopsis.