Biology subjects

Iglesias, V.

Publications and source records attributed to Iglesias, V..

7 recordsLinked to original sources

bioRxiv2025

Liquid-liquid phase separation (LLPS) as a sensing and adaptation mechanism: An evidence-based hypothesis on AP2 transcription factors in the malaria parasite

BackgroundProtein liquid-liquid phase separation (LLPS) can be driven by prion-like domains (PrLDs) inside intrinsically disordered regions (IDRs). The causing agent of the deadliest form of human malaria, Plasmodium falciparum, has abundant prion-like proteins whose aggregation is presumed to have a functional role. Multiple members of the largest family of transcription factors in P. falciparum, AP2 (PfAP2), responsible for adapting the parasite gene response in different scenarios, were found in aggregation-prone protein screenings. ResultsWe show that the PfAP2s members carry the physicochemical determinants to perform LLPS forming biomolecular condensates in vivo. The long IDRs of PfAP2s could sense changes in the cellular microenvironment, and their PrLDs could drive conformational rearrangements. PfAP2s do not function as centralizing hubs for protein-protein interaction networks, but display significant preferred interactions among themselves, establishing a large, connected subnetwork. Predictions suggest that all PfAP2s have regions to localize into LLPS-condensates, while larger PfAP2s could initiate condensation. We show that four PfAP2 members co-localize in live P. falciparum, bearing the potential to be engaged in LLPS-condensates. ConclusionWe present bioinformatics analyses and experimental data obtained in live parasites suggesting that PfAP2s are able to direct LLPS in P. falciparum. We propose a model in which sensing by the parasite of cellular stresses like host transfer, temperature changes and energy depletion, and the corresponding gene responses are driven by LLPS where the PfAP2 family plays a fundamental role. Finally, we postulate targeting PfAP2 as a new therapeutic antimalarial strategy to curb the emergence of drug-resistant parasites.

bioinformatics↗

bioRxiv2025

Epistasis between Na+/K+-ATPase Substitutions May Influence Salinity Tolerance in Steinernema Entomopathogenic Nematodes

Soil salinity varies widely across geographies both due to natural factors and human activities, including agriculture, road salt application, sea level rise, and desertification. Increases in soil salinity may affect organisms widely and particularly impact soil foodwebs. As parasites, entomopathogenic nematodes (EPNs) occupy crucial links in soil foodwebs and are important for agriculture as biological control agents of insect pests. Previous research found that the EPN Steinernema carpocapsae may exhibit higher salt tolerance than several of its congeners. We recently identified that S. carpocapsae uniquely evolved two amino acid substitutions in the first extracellular loop of the sodium pump (Na{square}/K{square}-ATPase). Here, we tested if these substitutions explain S. carpocapsaes reported lower sensitivity to salt. Our results confirm that S. carpocapsae exhibits higher salt tolerance and show it can more effectively locate and infect insect hosts than its congeners S. feltiae and S. hermaphroditum in highly saline environments. We then retraced the evolution of the two amino acid substitutions in S. carpocapsae by introducing them alone and in combination in Caenorhabditis elegans using CRISPR genome engineering. We found that C. elegans mutants with single substitutions showed improved salt tolerance. However, this improvement disappeared in the double mutant, whose sodium pump mimicked that of S. carpocapsae. This pattern of negative epistasis between the amino acid substitutions suggests they are not responsible for variation in salt tolerance between Steinernema species. Sodium pump evolution in S. carpocapsae might instead be driven by encounters with cardiac glycosides, which are released into soil by several clades of plants including milkweeds, sequestered by some of this EPNs herbivorous insect hosts, and known to target the first extracellular loop of the sodium pump. Our findings provide valuable insights into EPN adaptation to changes in environmental sodium levels and may have implications for their use in biological control.

ecology↗

bioRxiv2025

Amino Acid Substitutions in the Na+/K+-ATPase May Contribute to Salinity Tolerance in Insects

O_LIEnvironmental salinity levels vary naturally across terrestrial ecosystems but can be heightened locally by coastal proximity and desertification as well as human activities such as road salt application and agriculture. Since salt is essential for many physiological processes in insects, rising environmental sodium concentrations may drive behavioral changes, where insects select environments and food sources with suitable sodium levels, or evolutionary changes in constitutive or plastic physiological mechanisms to process salt, potentially altering ecological dynamics and species interactions. C_LIO_LINumerous hematophagous (blood feeding) insects such as the yellow-fever mosquito Aedes aeqypti are known to be able to breed in relatively saline environments. Among phytophagous (plant feeding) insects, grasshoppers can be important herbivores in arid and coastal salt-affected regions, whereas the monarch butterfly (Danaus plexippus) appears to perform relatively well on milkweed host plants growing in roadsides influenced by salt runoff. Several of these insects share a common trait: amino acid substitutions in the first extracellular loop of the Na+/K+-ATPase (NKA), a sodium pump crucial for maintaining ion balance. For the monarch these substitutions confer resistance to toxic cardenolides from milkweeds, but it is unclear whether NKA substitutions may influence salt tolerance. C_LIO_LIHere, we investigate whether the NKA substitutions found in these insects may contribute to salt tolerance using gene-edited Drosophila melanogaster mutant strains as models. We show that flies with substitution Q111L (found in Aedes mosquitoes) or a combination of Q111L and A119S (found in grasshoppers) exhibited greater salt tolerance, whereas flies carrying the combination of substitutions found in the monarch (Q111V, A119S, and N122H) did not. C_LIO_LIOur results suggest that the monarch may rely on alternate mechanisms for salt tolerance and that its NKA substitutions are important primarily for cardenolide resistance. However, substitution Q111L and the combination of Q111L and A119S may be relevant for salt tolerance in a variety of insects. Uncovering mechanisms of salt tolerance enhances our understanding of species distributions, ecological interactions, and evolutionary physiology in response to changing environmental salinity levels. C_LI

genetics↗

bioRxiv2023

Postfire recovery of western US conifer forests (1984-2017) using space-borne lidar data

Coniferous forests account for 78% of the western US forests and store a substantial amount of carbon. Wildfires significantly alter vegetation structure, and hence the forest carbon stock. This study evaluates post-fire vegetation recovery trajectories and rates across the western US using recently launched Global Ecosystem Dynamic Investigations (GEDI) mission lidar data. Three ecoregions studied here, the Pacific Northwest, Southern Rockies, and Northern Rockies, show fire severity and ecoregion specific recovery trajectories for canopy height (CH), plant area index (PAI), and the foliage height diversity (FHD). The recovery trajectories are characterized by an initial decline in vegetation structure (CH, PAI, and FHD) during the first 9-25 years postfire followed by a gain of the structure. Regions of low burn severity can fully recover to the unburned background state within the first three decades while the high burn severity regions may recover in the first century, but only in the absence of fires within this period. The PNW exhibits the slowest recovery rate. According to our results, all three ecoregions feature a loss of growing stock volume (GSV) (-1% - - 48%). Time since fire, fire severity, and altitude were identified as the most significant drivers of postfire vegetation recovery, likely because they integrate the distance to seed source, vegetation composition, and the local climate. Our study suggests that, if fire return intervals become shorter than 50 years, these three ecoregions will have significantly reduced their woody vegetation, hence the carbon stocks. In addition, all the ecoregions studied here exhibit extensive impacts from other disturbances such as beetle invasion. It is therefore important to consider the effects of compound disturbances on vegetation recovery trajectories to infer the future carbon potential in these ecosystems.

ecology↗

bioRxiv2021

Prediction of the effect of pH on the aggregation and conditional folding of intrinsically disordered proteins with SolupHred and DispHred.

Proteins microenvironments modulate their structures. Binding partners, organic molecules, or dissolved ions can alter the proteins compaction, inducing aggregation or order-disorder conformational transitions. Surprisingly, bioinformatic platforms often disregard the protein context in their modeling. In recent work, we proposed that modeling how pH affects protein net charge and hydrophobicity might allow us to forecast pH-dependent aggregation and conditional disorder in intrinsically disordered proteins (IDPs). As these approaches showed remarkable success in recapitulating the available bibliographical data, we made these prediction methods available for the scientific community as two user-friendly web servers. SolupHred is the first dedicated software to predict pH-dependent aggregation, and DispHred is the first pH-dependent predictor of protein disorder. Here we dissect the features of these two software applications to train and assist scientists in studying pH-dependent conformational changes in IDPs.

bioinformatics↗

bioRxiv2021

A3D 2.0 update for the prediction and optimization of protein solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

bioinformatics↗

bioRxiv2018

Understanding and predicting extreme wildfires in the contiguous United States

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30 year wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes.

ecology↗