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Abstract Catalytic constant (Kcat) is to describe the efficiency of catalyzing reactions. The Kcat value of an enzyme-substrate pair indicates the rate an enzyme converts saturated substrates into product during the catalytic process. However, it is challenging to construct robust prediction models for this important property. Most of the existing models, including the one recently published by Nature Catalysis (Li et al.), are suffering from the overfitting issue. In this study, we proposed a novel protocol to construct Kcat prediction models, introducing an intermedia step to separately develop substrate and protein processors. The substrate processor leverages analyzing Simplified Molecular Input Line Entry System (SMILES) strings using a graph neural network model, attentive FP, while the protein processor abstracts protein sequence information utilizing long short-term memory architecture. This protocol not only mitigates the impact of data imbalance in the original dataset but also provides greater flexibility in customizing the general-purpose Kcat prediction model to enhance the prediction accuracy for specific enzyme classes. Our general-purpose Kcat prediction model demonstrates significantly enhanced stability and slightly better accuracy (R2 value of 0.54 versus 0.50) in comparison with Li et al.’s model using the same dataset. Additionally, our modeling protocol enables personalization of fine-tuning the general-purpose Kcat model for specific enzyme categories through focused learning. Using Cytochrome P450 (CYP450) enzymes as a case study, we achieved the best R2 value of 0.64 for the focused model. The high-quality performance and expandability of the model guarantee its broad applications in enzyme engineering and drug research & development. 

Entomopathogenic fungi show significant promise as effective and ecological friendly alternatives to chemical insecticides for insect pest control. However, little is known concerning their effects on soil ecosystems, especially in comparison to application of chemical insecticides. Here, we examined the effects of one biological and two chemical insecticides, Metarhizium anisopliae, imidacloprid (IMI) and emamectin benzoate (EMB) on microbial community structure, metabolic functioning, and soil biochemistry. Treatment with EMB and IMI, reduced Actinobacteriota populations, while increasing that of Acidobacteriota. However, these populations were not significantly altered under M. anisopliae treatment. Chemical pesticides also altered fungal communities including potential pathogens. Activities of soil beneficial nitrogen-cycling-related enzymes were reduced after application of IMI and EMB, but were increased after treatment with M. anisopliae. Metagenomics analysis showed that IMI treatment reduced levels of carbon and nitrogen-related metabolic pathways. However, M. anisopliae treatment increased representation of key enzymes involved in the carbon, nitrogen, and sulfur cycling important for maintenance of soil fertility. Insecticides treatments altered the abundance of a number antibiotic resistance genes (ARGs) but not virulence factors (VFs), whereas application of M. anisopliae resulted had only minimal effects. These findings highlight the consequences of use of biological vs. chemical pesticides on soil microbiology can affect plant and ecosystem health indicating that the fungal biological control agent, M. anisopliae likely has far less detrimental and potentially beneficial effects on soil ecology as compared to chemical pesticides. 

Abstract Development of reliable germplasm repositories is critical for preservation of genetic resources of aquatic species, which are widely utilized to support biomedical innovation by providing a foundational source for naturally occurring variation and development of new variants through genetic manipulations. A significant barrier in repository development is the lack of cryopreservation capability and reproducibility across the research community, posing great risks of losing advances developed from billions of dollars of research investment. The emergence of open scientific hardware has fueled a new movement across biomedical research communities. With the increasing accessibility of consumer‐level fabrication technologies, such as three‐dimensional printers, open hardware devices can be custom designed, and design files distributed to community members for enhancing rigor, reproducibility, and standardization. The overall goal of this review is to explore pathways to create open‐hardware ecosystems among the communities using aquatic model resources for biomedical research. To gain feedback and insights from community members, an interactive workshop focusing on open‐hardware applications in germplasm repository development was held at the 2022 Aquatic Models for Human Disease Conference, Woods Hole, Massachusetts. This work integrates conceptual strategies with practical insights derived from workshop interactions using examples of germplasm repository development. These insights can be generalized for establishment of open‐hardware ecosystems for a broad biomedical research community. The specific objectives were to: (1) introduce an open‐hardware ecosystem concept to support biomedical research; (2) explore pathways toward open‐hardware ecosystems through four major areas, and (3) identify opportunities and future directions. 

The axolotl (Ambystoma mexicanum) draws great attention around the world for its importance as a biomedical research model, but housing and maintaining live animals is increasingly expensive and risky as new transgenic lines are developed. The goal of this work was to develop an initial practical pathway for sperm cryopreservation to support germplasm repository development. The present study assembled a pathway through the investigation of axolotl sperm collection by stripping, refrigerated storage in various osmotic pressures, cryopreservation in various cryoprotectants, and in vitro fertilization using thawed sperm. By the stripping of males, 25–800 µL of sperm fluid was collected at concentrations of 1.6 × 106 to 8.9 × 107 sperm/mL. Sperm remained motile for 5 d in Hanks’ Balanced Salt Solution (HBSS) at osmolalities of 100–600 mOsm/kg. Sperm cryopreserved in 0.25 mL French straws at 20 °C/min in a final concentration of 5% DMFA plus 200 mM trehalose and thawed at 25 °C for 15 s resulted in 52 ± 12% total post-thaw motility. In six in vitro fertilization trials, 20% of eggs tested with thawed sperm continued to develop to stage 7–8 after 24 h, and a third of those embryos (58) hatched. This work is the first report of successful production of axolotl offspring with cryopreserved sperm, providing a general framework for pathway development to establish Ambystoma germplasm repositories for future research and applications. 

SUMMARY Emerging human pluripotent stem cell (hPSC)-based embryo models are useful for studying human embryogenesis. Particularly, there are hPSC-based somitogenesis models using free-floating culture that recapitulate somite formation. Somitogenesisin vivoinvolves intricately orchestrated bio-chemical and -mechanical events. However, none of the current somitogenesis models controls biochemical gradients or biomechanical signals in the culture, limiting their applicability to untangle complex biochemical-biomechanical interactions that drive somitogenesis. Here we report a new human somitogenesis model by confining hPSC-derived presomitic mesoderm (PSM) tissues in microfabricated trenches. Exogenous microfluidic morphogen gradients imposed on PSM cause axial patterning and trigger spontaneous rostral-to-caudal somite formation. A mechanical theory is developed to explain the size dependency between somites and PSM. The microfluidic somitogenesis model is further exploited to reveal regulatory roles of cellular and tissue biomechanics in somite formation. This study presents a useful microengineered, hPSC-based model for understanding the bio-chemical and -mechanical events that guide somite formation. 

The Degasperis-Procesi (DP) equation is an integrable Camassa-Holm-type model which is an asymptotic approximation for the unidirectional propagation of shallow water waves. This work establishes the orbital stability of localized smooth solitary waves to the DP equation on the real line, extending our previous work on their spectral stability [J. Math. Pures Appl. (9) 142 (2020), pp. 298–314]. The main difficulty stems from the fact that the natural energy space is a subspace of L 3 L^3 , but the translation symmetry for the DP equation gives rise to a conserved quantity equivalent to the L 2 L^2 -norm, resulting in L 3 L^3 higher-order nonlinear terms in the augmented Hamiltonian. But the usual coercivity estimate is in terms of L 2 L^2 norm for DP equation, which cannot be used to control the L 3 L^3 higher order term directly. The remedy is to observe that, given a sufficiently smooth initial condition satisfying some mild constraint, the L ∞ L^\infty orbital norm of the perturbation is bounded above by a function of its L 2 L^2 orbital norm, yielding the higher order control and the orbital stability in the L 2 ∩ L ∞ L^2\cap L^\infty space.