Biology subjects

Pascual, N.

Publications and source records attributed to Pascual, N..

4 recordsLinked to original sources

bioRxiv2026

Preimplantation factor (PIF) links embryo-derived signaling to maternal pancreatic β-cell adaptation through an ERα-dependent pathway

Pregnancy requires maternal pancreatic {beta}-cells adaptations to increased insulin demand, yet the embryo-derived signals contributing to this response remain poorly defined. Here we identify preimplantation factor (PIF), an embryo-derived peptide present in maternal circulation from early gestation, as a regulator of {beta}-cell adaptation. In a murine model of gestational diabetes mellitus (GDM), circulating PIF levels were reduced during mid-gestation, indicating that this endogenous signal is altered under gestational metabolic dysfunction. Conversely, chronic exposure of non-pregnant female mice to synthetic PIF (sPIF) recapitulated key temporal features of gestational {beta}-cell adaptation, including early {beta}-cell proliferation, increased glucose-stimulated circulating C-peptide, expansion of {beta}-cell mass and sustained enhancement of ex vivo glucose-stimulated insulin secretion (GSIS). Mechanistically, sPIF activated rapid ERK-, AKT- and PKA-dependent signaling that converged on estrogen receptor alpha (ER) phosphorylation and nuclear translocation. Pharmacological inhibition and genetic silencing demonstrated that ER is required for full propagation of the functional and kinase responses. This kinase-ER axis was conserved in human islets, where sPIF enhanced insulin secretion in an ER-dependent manner. These findings identify PIF as an embryo-derived metabolic signal supporting maternal {beta}-cell compensation and suggest that reduced PIF availability may contribute to inadequate {beta}-cell adaptation in GDM.

physiology↗

bioRxiv2026

Effect of the functional environment on the cardiac differentiation of iPSC

Pristine carbon nanotubes (CNTs) have proven to be excellent supports for cardiac cell growth, survival and maturation, as well to improve cellular function, enhance spontaneous beating activity and benefit their cellular structure. Due to the large quantity of cardiomyocytes that have to be replaced for myocardial regeneration, iPSCs are the most promising candidates for robust generation of cardiomyocytes in vivo/vitro. Herein, iPSCs are cultured and differentiated into cardiomyocytes on functionalized carbon nanotubes (fCNTs). For this purpose, a first optimization of the type of plate and the number of iPSCs suitable for the passaging is performed. Thus, 5{middle dot}105 cells per cm2 are cultured in 24-well and 8-well plates. After 19-days of differentiation and maturation, calcium imaging was done to analyze the spontaneous beating behavior by means of beat frequency and amplitude, immunofluorescence was done to observe evaluate the degree of maturation by staining the sarcomere and the cell nucleus. A set of diverse functionalized CNTs were also tested: pristine CNT, ox-CNT, CNT-COOH, CNT-NH2, CNT-NO2 and CNT-SO3. Calcium analysis showed that all but the nitro-functionalization were beating, with acid-and oxygen derivative CNTs producing an increase in frequency with respect to control, while amino-functional groups decrease it. This suggests that the beating and contractile behavior of cardiomyocyte can be modulated according to the cardiac issue to be faced. In addition, CNT-SO3 produces a striated and elongated sarcomere, proper of the real tissue.

bioengineering↗

bioRxiv2023

AP-LASR: Automated Protein Libraries from Ancestral Sequence Reconstruction

BackgroundAncestral sequence reconstruction (ASR) provides an informative roadmap of evolutionary protein sequence space that benefits protein design and engineering in pursuit of high stability and diverse functionality. Using statistical and biological knowledge, ASR can determine the most probable ancestor among potential alternative amino acid states. However, the inherent uncertainty of ASR can be further leveraged to determine viable "nearby" ancestors with wide-ranging functionalities by sampling alternative amino acid states. ResultsHere we introduce AP-LASR which i) automates ASR and ii) leverages uncertainty in ASR to generate diverse protein sequence libraries that consist of ancestral sequences and near-ancestor sequences. In addition to automating pre-processing tasks (e.g., data cleaning, multiple sequence alignment, and software dependency management), AP-LASR offers several user-definable hyperparameters (e.g., input data size, ancestral probability cut-off, and sequence supplementation) to control the properties of the generated library. AP-LASR features an improved eLnP score (a metric for quantifying reconstructed ancestral sequence confidence) compared to FireProtASR, a well-established ASR workflow, for all four functionally diverse protein families studied. Furthermore, the rigorous statistical analysis undertaken in this study elucidates the influence of hyperparameters on ASR, enabling researchers to refine AP-LASR to their specific research. ConclusionAP-LASR offers an automated ASR experience that surpasses existing software by including a novel library design feature, powering curated protein libraries for wet-lab evaluation. We demonstrate how computational parameters impact the quality of ASR results, library composition, and the tradeoffs therein. AP-LASR offers a powerful tool for protein engineers to efficiently navigate the vast protein sequence landscape. Software available at: https://github.com/WoldringLabMSU/AP-LASR

bioinformatics↗

bioRxiv2022

The evolution of host resistance to a virus is determined by resources, historical contingency, and time scale

Hosts can often evolve resistance to parasites (and other stressors), but such resistance is generally thought to be constrained by trade-offs with other traits. These trade-offs determine the hosts optimal resistance strategy and whether resistance cycles, diversifies, and/or is maintained in the absence of parasite. However, trade-offs are often inconsistently measured across experiments and can depend on environmental conditions. Here, we extend a selection experiment evolving resistance to viral infection under variable resource quality in the Plodia interpunctella model system to explore the evolutionary conditions leading to an incongruent earlier measurement of costless resistance. We find that environmental resource quality, historical contingency, and the time scale of selection all affect trade-offs in our long-term selection experiment. Specifically, populations selected for resistance with the dual stressor of low resource quality are slowed, but not prevented, from evolving resistance. Second, variation in starting populations or early sampled adaptations led to contingency towards context-dependent resistance. Finally, some costs to resistance observed at early time points were compensated over longer evolutionary time scales. Our work therefore informs perspectives for the predictability of adaptation and how variation in specific evolutionary conditions can alter the evolutionary trajectories of a population towards costly or costless resistance strategies.

evolutionary biology↗