One-Pot Biocatalytic Route from Alkanes to α,ω-Diamines by Whole-Cell Consortia of Engineered Yarrowia lipolytica and Escherichia coli.

Metabolically engineered microbial consortia can contribute as a promising production platform for the supply of polyamide monomers. To date, the biosynthesis of long-chain α,ω-diamines from n-alkanes is challenging because of the inert nature of n-alkanes and the complexity of the overall synthesis pathway. We combined an engineered Yarrowia lipolytica module with Escherichia coli modules to obtain a mixed strain microbial consortium that could catalyze an efficient biotransformation of n-alkanes into corresponding α,ω-diamines. The engineered Y. lipolytica strain was constructed (YALI10) wherein the two genes responsible for ß-oxidation and the five genes responsible for the overoxidation of fatty aldehydes were deleted. This newly constructed YALI10 strain expressing transaminase (TA) could produce 0.2 mM 1,12-dodecanediamine (40.1 mg/L) from 10 mM n-dodecane. The microbial consortia comprising engineered Y. lipolytica strains for the oxidation of n-alkanes (OM) and an E. coli amination module (AM) expressing an aldehyde reductase (AHR) and transaminase (TA) improved the production of 1,12-diamine up to 1.95 mM (391 mg/L) from 10 mM n-dodecane. Finally, combining the E. coli reduction module (RM) expressing a carboxylic acid reductase (CAR) and an sfp phosphopantetheinyl transferase with OM and AM further improved the production of 1,12-diamine by catalyzing the reduction of undesired 1,12-diacids into 1,12-diols, which further undergo amination to give 1,12-diamine as the target product. This newly constructed mixed strain consortium comprising three modules in one pot gave 4.1 mM (41%; 816 mg/L) 1,12-diaminododecane from 10 mM n-dodecane. The whole-cell consortia reported herein present an elegant "greener" alternative for the biosynthesis of various α,ω-diamines (C8, C10, C12, and C14) from corresponding n-alkanes.

The complete chloroplast genome assembly of Commelina caroliniana Walter (Commelinaceae).

We sequenced and published the chloroplast genome of Commelina caroliniana Walter, which was previously misidentified as C. diffusa owing to their morphological similarities until 1989. The genome of C. caroliniana is 160,857 bp long [large single copy region: 88,064 bp; a small single copy region: 18,549 bp; two inverted repeat regions: 27,122 bp] and has a GC content of 35.7%. The genome comprises 133 genes, including 87 coding sequences (CDSs), 38 tRNAs, and eight rRNAs. The phylogenetic relationship between C. caroliniana and related species was analyzed using the maximum likelihood method based on the 79 CDSs of the chloroplast genome. Phylogenetic analysis revealed that C. caroliniana is closely related to C. communis. Our findings will contribute to studies on species identification and phylogenetic and evolutionary research. These results enhance our understanding of the Commelina genus.

Comparison of Four Diagnostic Guidelines for Hepatocellular Carcinoma Using Gadoxetic Acid-enhanced Liver MRI.

Background Noninvasive diagnostic guidelines for hepatocellular carcinoma (HCC) vary across different global geographic areas, especially regarding criteria about gadoxetic acid-enhanced MRI. Purpose To compare the diagnostic performance of four different international HCC diagnosis guidelines and readers' judgment in diagnosing HCC using gadoxetic acid-enhanced MRI in patients at high risk for HCC. Materials and Methods This retrospective study included patients who had not undergone treatment, were at risk for HCC, and who underwent gadoxetic acid-enhanced MRI from January 2015 to June 2018 from 11 tertiary hospitals in South Korea. Four radiologists independently reviewed focal liver lesions (FLLs) according to four guidelines: American Association for the Study of Liver Diseases (AASLD)/Liver Imaging Reporting and Data System (LI-RADS), Korean Liver Cancer Association-National Cancer Center (KLCA-NCC), European Association for the Study of the Liver (EASL), and Asian Pacific Association for the Study of the Liver (APASL). Reader judgment (HCC or not HCC) was also recorded. Malignant FLLs were confirmed at pathology, and histologic and clinical follow-up data were used for benign FLLs. The guidelines' diagnostic performance was compared using generalized estimating equations. Additionally, the diagnostic odds ratio was assessed. Results A total of 2445 FLLs (median size, 27.4 mm) were analyzed in 2237 patients (mean age, 59 years ± 11 [SD]; 1666 male patients); 69.3% (1694 of 2445) were HCCs. KLCA-NCC showed the highest accuracy (80.0%; 95% CI: 78.7, 81.2; P = .001), with high sensitivity in Eastern guidelines (APASL, 89.1% [95% CI: 87.8, 90.3]; KLCA-NCC, 78.2% [95% CI: 76.6, 79.7]) and high specificity in Western guidelines (AASLD/LI-RADS, 89.6% [95% CI: 87.8, 91.2]; EASL, 88.1% [95% CI: 86.2, 89.9]) (P = .001). The diagnostic odds ratios were 20.7 (95% CI: 17.0, 25.3) for AASLD/LI-RADS, 18.9 (95% CI: 15.8, 22.6) for KLCA-NCC, 16.8 (95% CI: 13.8, 20.4) for EASL, and 8.9 (95% CI: 7.4, 10.7) for APASL. The readers' judgment demonstrated higher accuracy than that of the guidelines (accuracy, 86.0%; 95% CI: 84.9, 86.9; P = .001). Conclusion Among four different international HCC diagnosis guidelines, Eastern guidelines demonstrated higher sensitivity, whereas Western guidelines displayed higher specificity. KLCA-NCC achieved the highest accuracy, and AASLD/LI-RADS exhibited the highest diagnostic odds ratio. © RSNA, 2024 Supplemental material is available for this article.

Integrating magnetic tweezers and single-molecule FRET: A comprehensive approach to studying local and global conformational changes simultaneously.

This chapter presents the integration of magnetic tweezers with single-molecule FRET technology, a significant advancement in the study of nucleic acids and other biological systems. We detail the technical aspects, challenges, and current status of this hybrid technique, which combines the global manipulation and observation capabilities of magnetic tweezers with the local conformational detection of smFRET. This innovative approach enhances our ability to analyze and understand the molecular mechanics of biological systems. The chapter serves as our first formal documentation of this method, offering insights and methodologies developed in our laboratory over the past decade.

Revitalizing Oxygen Reduction Reactivity of Composite Oxide Electrodes via Electrochemically Deposited PrOx Nanocatalysts.

Solid oxide fuel cells that operate at intermediate temperatures require efficient catalysts to enhance the inherently poor electrochemical activity of the composite electrodes. Here, a simple and practical electrochemical deposition method is presented for fabricating a PrOx overlayer on lanthanum strontium manganite-yttria-stabilized zirconia (LSM-YSZ) composite electrodes. The method requires less than four minutes for completion and can be carried out under at ambient temperature and pressure. Crucially, the treatment significantly improves the electrode's performance without requiring heat treatment or other supplementary processes. The PrOx-coated LSM-YSZ electrode exhibits an 89% decrease in polarization resistance at 650 °C (compared to an untreated electrode), maintaining a tenfold reduction after ≈400 h. Transmission line model analysis using impedance spectra confirms how PrOx coating improved the oxygen reduction reaction activity. Further, tests with anode-supported single cells reveal an outstanding peak power density compared to those of other LSM-YSZ-based cathodes (e.g., 418 mW cm-2 at 650 °C). Furthermore, it is demonstrated that multicomponent coating, such as (Pr,Ce)Ox, can also be obtained with this method. Overall, the observations offer a promising route for the development of high-performance solid oxide fuel cells.

Development and multicenter validation of deep convolutional neural network-based detection of colorectal cancer on abdominal CT.

OBJECTIVES: This study aims to develop computer-aided detection (CAD) for colorectal cancer (CRC) using abdominal CT based on a deep convolutional neural network. METHODS: This retrospective study included consecutive patients with colorectal adenocarcinoma who underwent abdominal CT before CRC resection surgery (training set = 379, test set = 103). We customized the 3D U-Net of nnU-Net (CUNET) for CRC detection, which was trained with fivefold cross-validation using annotated CT images. CUNET was validated using datasets covering various clinical situations and institutions: an internal test set (n = 103), internal patients with CRC first determined by CT (n = 54) and asymptomatic CRC (n = 51), and an external validation set from two institutions (n = 60). During each validation, data from the healthy population were added (internal = 60; external = 130). CUNET was compared with other deep CNNs: residual U-Net and EfficientDet. The CAD performances were evaluated using per-CRC sensitivity (true positive/all CRCs), free-response receiver operating characteristic (FROC), and jackknife alternative FROC (JAFROC) curves. RESULTS: CUNET showed a higher maximum per-CRC sensitivity than residual U-Net and EfficientDet (internal test set 91.3% vs. 61.2%, and 64.1%). The per-CRC sensitivity of CUNET at false-positive rates of 3.0 was as follows: internal CRC determined by CT, 89.3%; internal asymptomatic CRC, 87.3%; and external validation, 89.6%. CUNET detected 69.2% (9/13) of CRCs missed by radiologists and 89.7% (252/281) of CRCs from all validation sets. CONCLUSIONS: CUNET can detect CRC on abdominal CT in patients with various clinical situations and from external institutions. KEY POINTS: • Customized 3D U-Net of nnU-Net (CUNET) can be applied to the opportunistic detection of colorectal cancer (CRC) in abdominal CT, helping radiologists detect unexpected CRC. • CUNET showed the best performance at false-positive rates ≥ 3.0, and 30.1% of false-positives were in the colorectum. CUNET detected 69.2% (9/13) of CRCs missed by radiologists and 87.3% (48/55) of asymptomatic CRCs. • CUNET detected CRCs in multiple validation sets composed of varying clinical situations and from different institutions, and CUNET detected 89.7% (252/281) of CRCs from all validation sets.

Development and validation of CT­based radiomics model of PET-negative residual CT masses: a potential biomarker for predicting relapse­free survival in non-Hodgkin lymphoma patients showing complete metabolic response.

PURPOSE: PET-negative residual CT masses (PnRCMs) are usually dismissed as nonviable post-treatment lesions in non-Hodgkin lymphoma (NHL) patients showing complete metabolic response (CMR). We aimed to develop and validate computed tomography (CT)-based radiomics model of PET-negative residual CT mass (PnRCM) for predicting relapse-free survival (RFS) in NHL patients showing CMR. METHODS: A total of 224 patients who showed CMR after completing first-line chemotherapy for PET-avid NHL were recruited for model development. Patients with PnRCM were selected in accordance with the Lugano classification. Three-dimensional segmentation was done by two readers. Radiomic scores (RS) were constructed using features extracted using the Least-absolute shrinkage and selection operator analysis among radiomics features of PnRCMs showing more than substantial interobserver agreement (> 0.6). Cox regression analysis was performed with clinical and radiologic features. The performance of the model was evaluated using area under the curve (AUC). For validation, 153 patients from an outside hospital were recruited and analyzed in the same way. RESULTS: In the model development cohort, 68 (30.4%) patients had PnRCM. Kaplan-Meier analysis showed that patients with PnRCM had significantly (p = 0.005) shorter RFS than those without PnRCM. In Kaplan-Meier analysis, the high RS group showed significantly (p = 0.038) shorter RFS than the low-scoring group. Multivariate Cox regression analysis showed that high IPI score [hazard ratio (HR) 2.46; p = 0.02], treatment without rituximab (HR 3.821; p = 0.019) were factors associated with shorter RFS. In estimating RFS, combined model in both development and validation cohort showed AUC values of 0.81. CONCLUSION: The combined model that incorporated both clinical parameters and CT-based RS showed good performance in predicting relapse in NHL patients with PnRCM.

Particulate matter 10 induces oxidative stress and apoptosis in rhesus macaques skin fibroblast.

Background: Particulate matter (PM) is a major air pollutant that affects human health worldwide. PM can pass through the skin barrier, thus causing skin diseases such as heat rash, allergic reaction, infection, or inflammation. However, only a few studies have been conducted on the cytotoxic effects of PM exposure on large-scale animals. Therefore, herein, we investigated whether and how PM affects rhesus macaque skin fibroblasts. Methods: Rhesus macaque skin fibroblasts were treated with various concentrations of PM10 (1, 5, 10, 50, and 100 µg/mL) and incubated for 24, 48, and 72 h. Then, cell viability assay, TUNEL assay, and qRT-PCR were performed on the treated cells. Further, the reactive oxygen species, glutathione, and cathepsin B levels were determined. The MTT assay revealed that PM10 (>50 µg/mL) proportionately reduced the cell proliferation rate. Results: PM10 treatment increased TUNEL-positive cell numbers, following the pro-apoptosis-associated genes (CASP3 and BAX) and tumor suppressor gene TP53 were significantly upregulated. PM10 treatment induced reactive oxidative stress. Cathepsin B intensity was increased, whereas GSH intensity was decreased. The mRNA expression levels of antioxidant enzyme-related genes (CAT, GPX1 and GPX3) were significantly upregulated. Furthermore, PM10 reduced the mitochondrial membrane potential. The mRNA expression of mitochondrial complex genes, such as NDUFA1, NDUFA2, NDUFAC2, NDUFS4, and ATP5H were also significantly upregulated. In conclusion, these results showed that PM10 triggers apoptosis and mitochondrial damage, thus inducing ROS accumulation. These findings provide potential information on the cytotoxic effects of PM10 treatment and help to understand the mechanism of air pollution-induced skin diseases.

Machine Learning-Based Magnetic Resonance Radiomics Analysis for Predicting Low- and High-Grade Clear Cell Renal Cell Carcinoma.

PURPOSE: To explore whether high- and low-grade clear cell renal cell carcinomas (ccRCC) can be distinguished using radiomics features extracted from magnetic resonance imaging. METHODS: In this retrospective study, 154 patients with pathologically proven clear ccRCC underwent contrast-enhanced 3 T magnetic resonance imaging and were assigned to the development (n = 122) and test (n = 32) cohorts in a temporal-split setup. A total of 834 radiomics features were extracted from whole-tumor volumes using 3 sequences: T2-weighted imaging (T2WI), diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging. A random forest regressor was used to extract important radiomics features that were subsequently used for model development using the random forest algorithm. Tumor size, apparent diffusion coefficient value, and percentage of tumor-to-renal parenchymal signal intensity drop in the tumors were recorded by 2 radiologists for quantitative analysis. The area under the receiver operating characteristic curve (AUC) was generated to predict ccRCC grade. RESULTS: In the development cohort, the T2WI-based radiomics model demonstrated the highest performance (AUC, 0.82). The T2WI-based radiomics and radiologic feature hybrid model showed AUCs of 0.79 and 0.83, respectively. In the test cohort, the T2WI-based radiomics model achieved an AUC of 0.82. The range of AUCs of the hybrid model of T2WI-based radiomics and radiologic features was 0.73 to 0.80. CONCLUSION: Magnetic resonance imaging-based classifier models using radiomics features and machine learning showed satisfactory diagnostic performance in distinguishing between high- and low-grade ccRCC, thereby serving as a helpful noninvasive tool for predicting ccRCC grade.

Multiple toll-like receptors (TLRs) display differential bacterial and ligand specificity in the earthworm, Eisenia andrei.

Toll-like receptors (TLRs), an ancient and well-conserved group of pattern recognition receptors (PRRs), recognize conserved pathogen-associated molecular patterns. TLRs consist of three domains: the extracellular N-terminal domain, containing one or more leucine-rich repeats (LRRs), responsible for the recognizing and binding of antigens; the type-I transmembrane domain; and the intracellular domain known as the Toll/Interleukin-1 receptor (TIR) domain required for the downstream signaling pathway. We identified six new full-length complementary DNA (cDNA) sequences, Ean-TLR1/2/3/4/5/6. The deduced amino acid sequences indicate that Ean-TLRs consist of one signal peptide, one LRR N-terminal domain (Ean-TLR4/5), varying numbers of LRRs, one (Ean-TLR1/2/3/4/5) or two (Ean-TLR6) LRR C-terminal domains, one type-I transmembrane domain, and a TIR domain. In addition, a TIR domain alignment revealed that three conserved motifs, designated as Box 1, Box 2, and Box 3, contain essential amino acid residues for downstream signaling activity. Phylogenetic analysis of earthworm TLRs generated two separate evolutionary branches representing single (sccTLR) and multiple (mccTLR) cysteine cluster TLRs. Ean-TLR1/2/3/4 (sccTLR type) and Ean-TLR6 (mccTLR type) were clustered with corresponding types of previously reported earthworm TLRs as well as TLRs from Clitellata and Polychaete. As PRRs, earthworm TLRs should be capable of sensing a diverse range of pathogens. Except for Ean-TLR3, which was not responsive to any bacteria, earthworm TLR expression was significantly induced by Gram-positive but not Gram-negative bacteria. Moreover, it is likely that earthworms can differentiate between different species of Gram-positive bacteria via their TLR responses. The ligand specificity of earthworm TLRs suggests that their pathogenic ligand recognition is likely to be as specific and diverse as the mammalian TLR pathogen-sensing system.

A Mixture of Morus alba and Angelica keiskei Leaf Extracts Improves Muscle Atrophy by Activating the PI3K/Akt/mTOR Signaling Pathway and Inhibiting FoxO3a In Vitro and In Vivo.

Muscle atrophy, which is defined as a decrease in muscle mass and strength, is caused by an imbalance between the anabolism and catabolism of muscle proteins. Thus, modulating the homeostasis between muscle protein synthesis and degradation represents an efficient treatment approach for this condition. In the present study, the protective effects against muscle atrophy of ethanol extracts of Morus alba L. (MA) and Angelica keiskei Koidz. (AK) leaves and their mixtures (MIX) were evaluated in vitro and in vivo. Our results showed that MIX increased 5-aminoimidazole-4-carboxamide ribonucleotide-induced C2C12 myotube thinning, and enhanced soleus and gastrocnemius muscle thickness compared to each extract alone in dexamethasone-induced muscle atrophy Sprague Dawley rats. In addition, although MA and AK substantially improved grip strength and histological changes for dexamethasone-induced muscle atrophy in vivo, the efficacy was superior in the MIX-treated group. Moreover, MIX further increased the expression levels of myogenic factors (MyoD and myogenin) and decreased the expression levels of E3 ubiquitin ligases (atrogin-1 and muscle-specific RING finger protein-1) in vitro and in vivo compared to the MA- and AK-alone treatment groups. Furthermore, MIX increased the levels of phosphorylated phosphoinositide 3-kinase (PI3K), protein kinase B (Akt), and mammalian target of rapamycin (mTOR) that were reduced by dexamethasone, and downregulated the expression of forkhead box O3 (FoxO3a) induced by dexamethasone. These results suggest that MIX has a protective effect against muscle atrophy by enhancing muscle protein anabolism through the activation of the PI3K/Akt/mTOR signaling pathway and attenuating catabolism through the inhibition of FoxO3a.

Comparative analysis of the complete chloroplast genome of Papaveraceae to identify rearrangements within the Corydalis chloroplast genome.

Chloroplast genomes are valuable for inferring evolutionary relationships. We report the complete chloroplast genomes of 36 Corydalis spp. and one Fumaria species. We compared these genomes with 22 other taxa and investigated the genome structure, gene content, and evolutionary dynamics of the chloroplast genomes of 58 species, explored the structure, size, repeat sequences, and divergent hotspots of these genomes, conducted phylogenetic analysis, and identified nine types of chloroplast genome structures among Corydalis spp. The ndh gene family suffered inversion and rearrangement or was lost or pseudogenized throughout the chloroplast genomes of various Corydalis species. Analysis of five protein-coding genes revealed simple sequence repeats and repetitive sequences that can be potential molecular markers for species identification. Phylogenetic analysis revealed three subgenera in Corydalis. Subgenera Cremnocapnos and Sophorocapnos represented the Type 2 and 3 genome structures, respectively. Subgenus Corydalis included all types except type 3, suggesting that chloroplast genome structural diversity increased during its differentiation. Despite the explosive diversification of this subgenus, most endemic species collected from the Korean Peninsula shared only one type of genome structure, suggesting recent divergence. These findings will greatly improve our understanding of the chloroplast genome of Corydalis and may help develop effective molecular markers.

Prussian Blue-Type Sodium-ion Conducting Solid Electrolytes for All Solid-State Batteries.

Conventional solid electrolyte frameworks typically consist of anions such as sulphur, oxygen, chlorine, and others, leading to inherent limitations in their properties. Despite the emergence of sulphide, oxide, and halide-based solid electrolytes for all-solid-state batteries, their utilization is hampered by issues, including the evolution of H2 S gas, the need for expensive elements, and poor contact. Here, we first introduce Prussian Blue analogue (PBA) open-framework structures as a solid electrolyte that demonstrates appreciable Na+ conductivity (>10-2 mS cm-1 ). We delve into the relationship between Na+ conductivity and the lattice parameter of N-coordinated transition metal, which is attributed to the reduced interaction between Na+ and the framework, corroborated by the distribution of relaxation times and density functional theory calculations. Among the five PBAs studied, Mn-PBA have exhibited the highest Na+ conductivity of 9.1×10-2 mS cm-1 . Feasibility tests have revealed that Mn-PBA have maintained a cycle retention of 95.1 % after 80cycles at 30 °C and a C-rate of 0.2C. Our investigation into the underlying mechanisms that play a significant role in governing the conductivity and kinetics of these materials contributes valuable insights for the development of alternative strategies to realize all-solid-state batteries.

Ovastacin: An oolemma protein that cleaves the zona pellucida to prevent polyspermy.

Monospermy occurs in the process of normal fertilization where a single sperm fuses with the egg, resulting in the formation of a diploid zygote. During the process of fertilization, the sperm must penetrate the zona pellucida (ZP), the outer layer of the egg, to reach the egg's plasma membrane. Once a sperm binds to the ZP, it undergoes an acrosomal reaction, which involves the release of enzymes from the sperm's acrosome that help it to penetrate the ZP. Ovastacin is one of the enzymes that is involved in breaking down the ZP. Studies have shown that ovastacin is necessary for the breakdown of the ZP and for successful fertilization to occur. However, the activity of ovastacin is tightly regulated to ensure that only one sperm can fertilize the egg. One way in which ovastacin helps to prevent polyspermy (the fertilization of an egg by more than one sperm) is by rapidly degrading the ZP after a sperm has penetrated it. This makes it difficult for additional sperm to penetrate the ZP and fertilize the egg. Ovastacin is also thought to play a role in the block to polyspermy, a mechanism that prevents additional sperm from fusing with the egg's plasma membrane after fertilization has occurred. In summary, the role of ovastacin in monospermic fertilization is to help ensure that only one sperm can fertilize the egg, while preventing polyspermy and ensuring successful fertilization.

Acoustic radiation force for analyzing the mechanical stress in ultrasound neuromodulation.

Objective. Although recent studies have shown that mechanical stress plays an important role in ultrasound neuromodulation, the magnitude and distribution of the mechanical stress generated in tissues by focused ultrasound transducers have not been adequately examined. Various acoustic radiation force (ARF) equations used in previous studies have been evaluated based on the tissue displacement results and are suitable for estimating the displacement. However, it is unclear whether mechanical stress can be accurately determined. This study evaluates the mechanical stress predicted by various AFR equations and suggests the optimal equation for estimating the mechanical stress in the brain tissue.Approach. In this paper, brain tissue responses are compared through numerical finite element simulations by applying the three most used ARF equations-Reynolds stress force ((RSF)), momentum flux density tensor force, and attenuation force. Three ARF fields obtained from the same pressure field were applied to the linear elastic model to calculate the displacement, mechanical stress, and mean pressure generated inside the tissue. Both the simple pressure field using a single transducer and the complex standing wave pressure field using two transducers were simulated.Main results. For the case using a single transducer, all three ARFs showed similar displacement. However, when comparing the mechanical stress results, only the results using the RSF showed a strong stress tensor at the focal point. For the case of using two transducers, the displacement and stress tensor field of the pattern related to the standing wave were calculated only from the results using the RSF.Significance. The model using RSF equation allows accurate analysis on stress tensor inside the tissue for ultrasound neuromodulation.

Efficient production of natural sunscreens shinorine, porphyra-334, and mycosporine-2-glycine in Saccharomyces cerevisiae.

Mycosporine-like amino acids (MAAs) are promising natural sunscreens mainly produced in marine organisms. Until now, metabolic engineering efforts to produce MAAs in heterologous hosts have mainly focused on shinorine production, and the low production levels are still not suitable for industrial applications. In this study, we successfully developed Saccharomyces cerevisiae strains that can efficiently produce various disubstituted MAAs, including shinorine, porphyra-334, and mycosporine-2-glycine (M2G), which are formed by conjugating serine, threonine, and glycine to mycosporine-glycine (MG), respectively. We first generated an MG-producing strain by multiple integration of the biosynthetic genes from cyanobacteria and applying metabolic engineering strategies to increase sedoheptulose-7-phosphate pool, a substrate for MG production. Next, five mysD genes from cyanobacteria, which encode D-Ala-D-Ala ligase homologues that conjugate an amino acid to MG, were introduced into the MG-producing strain to determine the substrate preference of each MysD enzyme. MysDs from Lyngbya sp., Nostoclinckia, and Euhalothece sp. showed high specificity toward serine, threonine, and glycine, resulting in efficient production of shinorine, porphyra-334, and M2G, respectively. This is the first report on the production of porphyra-334 and M2G in S. cerevisiae. Furthermore, we identified that the substrate specificity of MysD was determined by the omega loop region of 43-45 amino acids predicted based on its structural homology to a D-Ala-D-Ala ligase from Thermus thermophilus involved in peptidoglycan biosynthesis. The substrate specificities of two MysD enzymes were interchangeable by swapping the omega loop region. Using the engineered strain expressing mysD from Lyngbya sp. or N. linckia, up to 1.53 g/L shinorine or 1.21 g/L porphyra-334 was produced by fed-batch fermentation in a 5-L bioreactor, the highest titer reported so far. These results suggest that S. cerevisiae is a promising host for industrial production of different types of MAAs, providing a sustainable and eco-friendly alternative for the development of natural sunscreens.

Identifying Key Residues in Lysine Decarboxylase for Soluble Expression Using Consensus Design Soluble Mutant Screening (ConsenSing).

Although recent advances in deep learning approaches for protein engineering have enabled quick prediction of hot spot residues improving protein solubility, the predictions do not always correspond to an actual increase in solubility under experimental conditions. Therefore, developing methods that rapidly confirm the linkage between computational predictions and empirical results is essential to the success of improving protein solubility of target proteins. Here, we present a simple hybrid approach to computationally predict hot spots possibly improving protein solubility by sequence-based analysis and empirically explore valuable mutants using split GFP as a reporter system. Our approach, Consensus design Soluble Mutant Screening (ConsenSing), utilizes consensus sequence prediction to find hot spots for improvement of protein solubility and constructs a mutant library using Darwin assembly to cover all possible mutations in one pot but still keeps the library as compact as possible. This approach allowed us to identify multiple mutants of Escherichia coli lysine decarboxylase, LdcC, with substantial increases in soluble expression. Further investigation led us to pinpoint a single critical residue for the soluble expression of LdcC and unveiled its mechanism for such improvement. Our approach demonstrated that following a protein's natural evolutionary path provides insights to improve protein solubility and/or increase protein expression by a single residue mutation, which can significantly change the profile of protein solubility.

Single-Molecule Methods to Study Z-DNA Mechanics and Dynamics.

Single-molecule methods are powerful in revealing physical and mechanobiological details about biological phenomena. Here, we describe the single-molecule methods applied to study mechanical properties of Z-DNA and dynamics of the B-Z transition.

Hybrid Composite of Sn(IV)-Porphyrin and Mesoporous Structure for Enhanced Visible Light Photocatalytic Degradation of Organic Dyes.

Two hybrid composites (SnP@MCM-41 and SnP@SiO2) were fabricated by chemical adsorption of (trans-dihydroxo)(5,10,15,20-tetraphenylporphyrinato)tin(IV) (SnP) on mesoporous structured Mobil Composition of Matter No. 41 (MCM-41) and SiO2 nanoparticles. These materials were characterized by Fourier-transform infrared spectroscopy, ultraviolet-visible spectroscopy, fluorescence spectroscopy, transmission electron microscopy, and field-emission scanning electron microscopy techniques. The incorporation of SnP into MCM-41 and SiO2 supports efficient photocatalytic degradation of the anionic erioglaucine, cationic rhodamine B, and neutral m-cresol purple dyes under visible light irradiation in an aqueous solution. The performances of degradation of these dyes by these photocatalysts under visible light irradiation varied from 87 to 95%. The pseudo-first-order degradation rate constant of organic dyes for SnP@MCM-41 was higher than those of SnP@SiO2 and SnP. These visible light photocatalysts showed remarkable stability and reliable reusability.