Biology subjects

Mai, T.

Publications and source records attributed to Mai, T..

7 recordsLinked to original sources

bioRxiv2026

A high-level programming language for generative biology with Proto

Programmable composition of complex systems is a longstanding goal of biological research. Generative modeling has improved the reliability of computational design, but existing methods are highly specialized and are difficult to extend or compose. Here, we introduce Proto, a high-level programming language for generative biology. By composing a small set of abstract primitives into structured programs, Proto encodes generative design campaigns across diverse modalities and scales--spanning DNA, RNA, proteins, ligands, and their interactions. Proto readily incorporates predictive models into generative workflows, which we leveraged to design alternatively spliced introns with experimental validation in human cell lines. Proto is natively multi-objective, enabling the design of promoter-repressor pairs with leading experimental success rates for synthetic protein-DNA design. Alongside AI agents, Proto enables the specification of complex pathways and regulatory logic through natural language instructions. We openly release Proto, including software infrastructure and user interfaces, to enable widespread access to generative biological programming.

Synthetic Biology↗

bioRxiv2024

Inhibition of β-catenin signaling by Amyloid-β in endothelial cells impairs vascular barrier integrity

Dysfunction of the blood-brain barrier (BBB) is emerging as a critical mediator of Alzheimers Disease (AD) progression and precedes the formation of large Amyloid-{beta} (A{beta}) plaques in AD patients. Maintenance of the blood brain barrier integrity by brain microvascular endothelial cells (BMECs) is essential for brain homeostasis and is in part maintained by WNT/{beta}-catenin signaling. We hypothesized that A{beta} induces blood-brain barrier dysfunction by inhibiting WNT/{beta}- catenin signaling in brain endothelial cells, leading to reduced expression of BBB-related genes and barrier function. In brain endothelial cells, we found that A{beta} directly decreased {beta}-catenin transcriptional activity, but also inhibited activation of {beta}-catenin by the WNT3A peptide. Additionally, A{beta} reduced barrier integrity of ECs, which was in part restored by exposure to exogenous WNT3A. We observed A{beta}-induced inhibition within 3 hours of exposure. A{beta}-induced inhibition of {beta}-catenin signaling was consistent across both immortalized brain ECs and ECs differentiated from human induced pluripotent stem cells(iPSCs). We next investigated human iPSCs with and without the N141I mutation in presenilin-2 (PSEN2), known to increase A{beta} buildup and familial AD risk. We found the AD ECs showed smaller cell size and expressed lower VE-cadherin at the protein level. RNA sequencing revealed that the presence of PSEN2 N141I did not significantly impact gene expression of genes coding for proteins canonically involved in barrier integrity but did show differences in the expression of transposable elements. These results indicate that BBB dysfunction early in AD may be the result of A{beta} in the brain impairing WNT/{beta}-catenin signaling which maintains the barrier integrity of brain endothelial cells.

neuroscience↗

bioRxiv2024

The enhancement of electricity generation using cellulose based on ternary microbial consortium

Cooperation between microorganisms is crucial to design an efficient inoculum for enhancing the electricity-producing ability of carboxymethyl cellulose (CMC) fed bioreactors. In the present study, the influence of microbial mutualistic interactions and electricity generation capability were investigated by designing several co-culture and ternary culture systems. It was found that a ternary culture system of Cellulomonas Lsc-8, Bacillus subtilis C9 and Geobacter sulfurreducens PCA was used to efficiently convert cellulose into electricity. The maximum current density of 796 {+/-} 30 {micro}A{middle dot}cm-2 were achieved by the ternary culture, which were much higher than that Geobacter sulfurreducens PCA using acetate and co-culture systems to utilize CMC in bioreactors, respectively. In this consortium, Cellulomonas Lsc-8, and Bacillus subtilis C9 simultaneously digested CMC to produce acetate and secreted riboflavin as an electron shuttle; Geobacter sulfurreducens PCA utilized acetate to generate electricity. The introduction of Bacillus subtilis C9 further promoted the degradation of CMC and secreted more riboflavin to enhance electricity generation of the ternary culture. This work suggested that the synergistic interaction between interspecies in microbial consortia is emergent in designing specific community for achieving maximum power generation using CMC as substrate. This research shows new insight into the design of more efficient, stable, and robust microbial consortia applicable in waste treatment and power generation. IMPORTANCEMicrobial fuel cells (MFCs) may benefit from microbial consortia that efficiently convert carbon sources to electricity. A key challenge with this system is how to manage microbial community assembly to maximize electricity generation. Herein, we constructed and tested a three-species microbial consortium to enhance conversion of cellulose to electricity. Cellulomonas Lsc-8 and Bacillus subtilis C9 efficiently converted cellulose to acetate (electron donor) and riboflavin (electron shuttle), which enabled Geobacter sulfurreducens to generate electricity. This study laid the foundation for design of more efficient, stable, and robust microbial consortia for waste treatment and energy applications.

microbiology↗

bioRxiv2024

Active site remodeling in IDH1 mutants drives distinct kinetic and potential resistance mechanisms

Mutations in human isocitrate dehydrogenase 1 (IDH1) drive tumor formation in a variety of cancers by replacing its conventional activity with a neomorphic activity that generates an oncometabolite. Little is understood of the mechanistic differences among tumor-driving IDH1 mutants. We previously reported that the R132Q mutant uniquely preserves conventional activity while catalyzing robust oncometabolite production, allowing an opportunity to compare these reaction mechanisms within a single active site. Here, we employed static and dynamic structural methods and found that, compared to R132H, the R132Q active site adopted a conformation primed for catalysis with optimized substrate binding and hydride transfer to drive improved conventional and neomorphic activity over R132H. This active site remodeling revealed a possible mechanism of resistance to selective mutant IDH1 therapeutic inhibitors. This work enhances our understanding of fundamental IDH1 mechanisms while pinpointing regions for improving inhibitor selectivity.

biochemistry↗

bioRxiv2022

Elevated CD47 is a hallmark of dysfunctional aged muscle stem cells that can be targeted to augment regeneration

In aging, skeletal muscle strength and regenerative capacity declines due, in part, to functional impairment of muscle stem cells (MuSCs), yet the underlying mechanisms remain elusive. Here we capitalize on mass-cytometry to identify high CD47 expression as a hallmark of dysfunctional MuSCs (CD47hi) with impaired regenerative capacity that predominate with aging. The prevalent CD47hi MuSC subset suppresses the residual functional CD47lo MuSC subset through a paracrine signaling loop, leading to impaired proliferation. We uncover that elevated CD47 levels on aged MuSCs result from increased U1 snRNA expression, which disrupts alternative polyadenylation. The deficit in aged MuSC function in regeneration can be overcome either by morpholino-mediated blocking of CD47 alternative polyadenylation or antibody blockade of CD47 signaling, leading to improved regeneration in aged mice, with therapeutic implications. Our findings highlight a previously unrecognized age-dependent alteration in CD47 levels and function in MuSCs, which underlies reduced muscle repair in aging.

cell biology↗

bioRxiv2020

Water and phosphorus uptake by upland rice root systems unraveled under multiple scenarios: linking a 3D soil-root model and data

Background and aimsUpland rice is often grown where water and phosphorus (P) are limited and these two factors interact on P bioavailability. To better understand this interaction, mechanistic models representing small-scale nutrient gradients and water dynamics in the rhizosphere of full-grown root systems are needed. MethodsRice was grown in large columns using a P-deficient soil at three different P supplies in the topsoil (deficient, suboptimal, non-limiting) in combination with two water regimes (field capacity versus drying periods). Root architectural parameters and P uptake were determined. Using a multiscale model of water and nutrient uptake, in-silico experiments were conducted by mimicking similar P and water treatments. First, 3D root systems were reconstructed by calibrating an architecure model with observed phenological root data, such as nodal root number, lateral types, interbranch distance, root diameters, and root biomass allocation along depth. Secondly, the multiscale model was informed with these 3D root architectures and the actual transpiration rates. Finally, water and P uptake were simulated. Key resultsThe plant P uptake increased over threefold by increasing P and water supply, and drying periods reduced P uptake at high but not at low P supply. Root architecture was significantly affected by the treatments. Without calibration, simulation results adequately predicted P uptake, including the different effects of drying periods on P uptake at different P levels. However, P uptake was underestimated under P deficiency, a process likely related to an underestimated affinity of P uptake transporters in the roots. Both types of laterals (i.e. S- and L-type) are shown to be highly important for both water and P uptake, and the relative contribution of each type depend on both soil P availability and water dynamics. Key drivers in P uptake are growing root tips and the distribution of laterals. ConclusionsThis model-data integration demonstrates how multiple co-occurring single root phene responses to environmental stressors contribute to the development of a more efficient root system. Further model improvements such as the use of Michaelis constants from buffered systems and the inclusion of mycorrhizal infections and exudates are proposed.

developmental biology↗

bioRxiv2019

Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

BackgroundThe risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction, and \"expiration date\" of ECG biomarkers is unknown. Our goal was to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing outcomes.\n\nMethodsAtherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n=15,768; 55% female, 73% white, age 54.2{+/-}5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity (GEH) and traditional ECG metrics were measured. Adjudicated SCD served as the primary outcome; non-sudden cardiac death served as competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework.\n\nResultsOver a median 24.4 y follow-up, there were 581 SCDs (incidence 1.77 (95%CI 1.63-1.92)/1,000 person-years), and 838 nonSCDs [2.55 (95%CI 2.39-2.73)]. Resting heart rate was the strongest (AUC 0.930) short-term (3-month) non-specific SCD predictor, whereas spatial peak QRS-T angle predicted specifically SCD 15 years after ECG recording (AUC 0.719). QRS duration (AUC 0.885) and QTc (AUC 0.711) short-term predicted advanced structural heart disease better than SCD. \"Expiration date\" for most ECG biomarkers was two years after ECG recording. GEH significantly improved reclassification of SCD risk beyond age, sex, race, diabetes, hypertension, coronary heart disease and stroke.\n\nConclusionShort-term predictors of SCD, nonSCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.

epidemiology↗