Biology subjects

Sandoval, D.

Publications and source records attributed to Sandoval, D..

12 recordsLinked to original sources

bioRxiv2026

Extending the least-cost theory of stomatal regulation to include soil moisture stress

O_LITerrestrial biosphere models commonly use empirical scaling factors to represent soil moisture constraints on carbon and water fluxes, but these lack mechanistic grounding and produce inconsistent estimates of soil moisture limitations on primary production and transpiration across models. C_LIO_LIHere we extended the least-cost hypothesis for optimal stomatal conductance to account for soil moisture limitations by allowing soil water availability to modulate the carbon cost of water transport, drawing on the observed temperature dependence of stem respiration, and derived a simple empirical approximation to the theory using global {delta}13C and eddy covariance data. C_LIO_LIThe empirical analysis shows moderated thermal acclimation of stem respiration and a weak increase in water transport costs with aridity, supporting the interpretation that the decline in light-use efficiency (LUE) under arid conditions is primarily attributable to non-stomatal limitations. C_LIO_LIValidation against an independent global dataset of sapflow-derived canopy conductance and transpiration shows that the revised scheme significantly improves the predictive power of the least-cost hypothesis, offering a more mechanistically coherent alternative to existing soil moisture parameterisations. C_LI

Plant Biology↗

bioRxiv2026

An eco-evolutionary approach to defining wildfire regimes

Fuel availability and fuel dryness are consistently shown to be the primary drivers of wildfire intensity and burnt area. Here we hypothesise that differences in the timing of fuel build up and drying determine the optimal time for wildfire occurrence. We use gross primary production (GPP) as a measure of biomass production and hence fuel availability, and vapour pressure deficit (VPD) as a measure of fuel drying. We use the phase difference in the seasonal time course and magnitude of GPP and VPD to cluster regions that should therefore have distinct wildfire behaviour. We then show that each of the resultant clusters is distinctive in terms of one or more fire properties, specifically number of ignitions, burnt area, size, speed, duration, intensity, and length of the wildfire season. The emergence of distinct regimes as a function of two biophysical drivers reflects the fact that both vegetation and wildfire properties are a consequence of eco-evolutionary adaptions to environmental conditions. We then examine the degree to which human activities or vegetation properties modify these fire regimes within each of these clusters. Variability in GPP and VPD largely explains the within-cluster variation in fire properties. The type of vegetation cover has an influence on burnt area and carbon emissions in particular, while human activities are more important for fire properties such as size, rate of spread and duration largely through their influence of landscape fragmentation. Although both human activities and vegetation properties modify wildfire regimes, the ability to distinguish wildfire regimes using GPP and VPD alone emphasizes that land management, fire use and fire suppression are constrained by environmental conditions. This eco-evolutionary optimality approach to characterising wildfire regimes provides a basis for designing a simple fire model for Earth System modelling.

ecology↗

bioRxiv2025

SEL1L-HRD1 ER-Associated Degradation Facilitates Prohormone Convertase 2 Maturation and Glucagon Production in Islet α Cells

Proteolytic cleavage of proglucagon by prohormone convertase 2 (PC2) is required for islet cells to generate glucagon. However, the regulatory mechanisms underlying this process remain largely unclear. Here, we report that SEL1L-HRD1 endoplasmic reticulum (ER)-associated degradation (ERAD), a highly conserved protein quality control system responsible for clearing misfolded proteins from the ER, plays a key role in glucagon production by regulating turnover of the nascent proform of the PC2 enzyme (proPC2). Using a mouse model with SEL1L deletion in proglucagon-expressing cells, we observed a progressive decline in stimulated glucagon secretion and a reduction in pancreatic glucagon content. Mechanistically, we found that endogenous proPC2 is a substrate of SEL1L-HRD1 ERAD, and that degradation of misfolded proPC2 ensures the maturation of activation-competent proPC2 protein. These findings identify ERAD as a novel regulator of PC2 biology and an essential mechanism for maintaining cell function.

cell biology↗

bioRxiv2024

Protein structure, a genetic encoding for glycosylation

Unlike DNA, RNA, and protein biosynthesis, dogma describes glycosylation as primarily determined by intrinsic cellular limitations, such as glycosyltransferase expression and precursor availability. However, this cannot explain the commonly-observed differences between glycans on the same protein. By examining site-specific glycosylation on diverse human proteins, we detected associations between protein structure and glycan structure, broadly generalizable to human-expressed glycoproteins. Through structural analysis of site-specific glycosylation data, we found protein-sequence and structural features consistently correlated with specific glycan features. To quantify these relationships, we present a new amino acid substitution matrix describing "glycoimpact", i.e., the association of primary protein structure and glycosylation. High-glycoimpact amino acids co-evolve with glycosites, and glycoimpact is high when estimates of amino acid conservation and variant pathogenicity diverge. We report thousands of disease variants near glycosites with high-glycoimpact, including several with known links to aberrant glycosylation (e.g., Oculocutaneous Albinism, Jakob-Creutzfeldt disease, Gerstmann-Straussler-Scheinker, and Gauchers Disease). Finally, glycoimpact quantification is validated by studying oligomannose-complex glycan ratios on HIV ENV, differential sialylation on IgG3 Fc, differential glycosylation on SARS-CoV-2 Spike, and fucose-modulated function of a tuberculosis monoclonal antibody. Finally, to test the causality of protein-glycan associations, we created 5 glycoimpact-designed novel Rituximab variants, 4 of which substantially changed glycoprofiles as predicted. In all, we report that site-specific glycan biosynthesis is influenced by underlying protein structure, enabling glycan structure prediction and genetic sequence-guided glycoengineering.

genetics↗

bioRxiv2024

Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network

Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.

bioinformatics↗

bioRxiv2023

Temperature effects on the global patterns of photosynthetic quantum efficiency

SummaryO_LIHistorically, terrestrial biosphere models (TBMs) have assigned the intrinsic (maximum) quantum yield of photosynthesis ({varphi}0) a constant value for each plant functional type. However, experimental studies have shown that {varphi}0- when measured on light-adapted leaves - depends on temperature. It is unclear whether this dependence is universal or biome-specific; how it is manifested at the ecosystem level; and how it should be represented in TBMs. C_LIO_LIBy fitting empirical light-response curves to a global set of eddy-covariance CO2 flux measurements and correcting for photorespiration, we inferred apparent, ecosystem-level {varphi}0values and their temperature responses across a wide range of environments. C_LIO_LIThe temperature response of apparent ecosystem-level {varphi}0 follows a universal bell-shaped curve. The shape of this curve does not markedly differ among biomes, but the maximum value of {varphi}0 decreases with increasing aridity, its temperature optimum increases with increasing growth temperature, and its sensitivity to temperature increases as growth temperature declines. C_LIO_LIOur model for {varphi}0(T) aligns with recent theory highlighting the role of cytochrome b6f in regulating the light reactions of photosynthesis. If implemented in TBMs, this model should allow better predictions of the responses of terrestrial ecosystem function to a warming climate. C_LI

ecology↗

bioRxiv2023

Incorporating photosynthetic acclimation improves stomatal optimisation models

Stomatal opening in plant leaves is regulated through a balance of carbon and water exchange under different environmental conditions. Accurate estimation of stomatal regulation is crucial for understanding how plants respond to changing environmental conditions, particularly under climate change. A new generation of optimality-based modelling schemes determines instantaneous stomatal responses from a balance of trade-offs between carbon gains and hydraulic costs, but most such schemes do not account for biochemical acclimation in response to drought. Here, we compare the performance of seven instantaneous stomatal optimisation models with and without accounting for photosynthetic acclimation. Using experimental data from 38 plant species, we found that accounting for photosynthetic acclimation improves the prediction of carbon assimilation in a majority of the tested models. Non-stomatal mechanisms contributed significantly to the reduction of photosynthesis under drought conditions in all tested models. Drought effects on photosynthesis could not accurately be explained by the hydraulic impairment functions embedded in the stomatal models alone, indicating that photosynthetic acclimation must be considered to improve estimates of carbon assimilation during drought. Summary StatementAccounting for photosynthetic acclimation improves the predictions of carbon assimilation in all the stomatal optimization models evaluated. The influence of drought on photosynthesis cannot be fully explained by the hydraulic impairment function of the stomatal models alone.

biophysics↗

bioRxiv2023

Neuronal Ndst1 depletion accelerates prion protein clearance and slows neurodegeneration in prion infection

Select prion diseases are characterized by widespread cerebral plaque-like deposits of amyloid fibrils enriched in heparan sulfate (HS), a major extracellular matrix component. HS facilitates fibril formation in vitro, yet how HS impacts fibrillar plaque growth within the brain is unclear. Here we found that prion-bound HS chains are highly sulfated, and that the sulfation is essential for HS accelerating prion conversion in vitro. Using conditional knockout mice to deplete the HS sulfation enzyme, Ndst1 (N-deacetylase, N-sulfotransferase), from neurons or astrocytes, we investigated how reducing HS sulfation impacts survival and prion aggregate distribution during a prion infection. Neuronal Ndst1-depleted mice survived longer and showed fewer and smaller parenchymal plaques, shorter fibrils, and increased vascular amyloid, consistent with enhanced aggregate transit toward perivascular drainage channels. The prolonged survival was strain-dependent, affecting mice infected with extracellular, plaque-forming, but not membrane bound, prion strains. Live PET imaging revealed rapid clearance of prion protein monomers into the CSF in mice expressing unsulfated HS, further suggesting that HS sulfate groups hinder transit of extracellular prion monomers. Our results directly show how a host cofactor slows the spread of prion protein through the extracellular space and identify an enzyme target to facilitate aggregate clearance. Author summaryPrions cause a rapidly progressive neurologic disease and death with no curative treatment available. Prion aggregates accumulate exponentially in the brain in affected individuals triggering neuronal loss and neuroinflammation. Yet the additional molecules that facilitate aggregation are largely unknown, and their identification may lead to new therapeutic targets. We have found that prions in the brain preferentially bind to a highly sulfated endogenous polysaccharide, known as heparan sulfate (HS). Here we use genetically modified mice that express poorly sulfated neuron-derived HS, and infect mice with different prions strains. We find that the mice infected with a plaque-forming prion strain show a prolonged survival and fewer plaques compared to the controls. We also found that the prion protein was efficiently transported in the interstitial fluid in mice having poorly sulfated HS, suggesting that the prion protein is more readily cleared from the brain. Our study provides insight into how HS retains prion aggregates in the brain to accelerate disease and indicates the specific HS biosynthetic enzymes to target for enhancing protein clearance.

pathology↗

bioRxiv2023

Photosynthetic and water transport strategies of plants along a tropical forest aridity gradient: a test of optimality theory

(1) The research conducted, including the rationaleThe direct effect of aridity on photosynthetic and water-transport strategies is not easy to discern in global analyses because of large-scale correlations between precipitation and temperature. We analyze tree traits collected along an aridity gradient in Ghana, West Africa that shows little temperature variation, in an attempt to disentangle thermal and hydraulic influences on plant traits. (2) MethodsPredictions derived from optimality theory on the variation of key plant traits along the aridity gradient are tested with field measurements. (3) resultsMost photosynthetic traits show trends consistent with optimality-theory predictions, including higher photosynthetic capacity in the drier sites, and an association of higher photosynthetic capacity with greater respiration rates and greater water transport. Hydraulic traits show less consistency with theory or global-scale pattern, especially predictions based on xylem efficiency-safety tradeoff. Nonetheless, the link between photosynthesis and water transport still holds: species (predominantly deciduous species found in drier sites) with both higher sapwood-to-leaf area ratio (AS/AL) and potential hydraulic conductivity (Kp), implying higher transpiration, tend to have both higher photosynthetic capacity and lower leaf-internal CO2. (4) ConclusionsThese results indicate that aridity is an independent driver of spatial patterns of photosynthetic traits, while plants show a diversity of water-transport strategies along the aridity gradient. Plain language summaryAlong an aridity gradient in Ghana, West-Africa, we used optimality theory to explain that aridity is an important driver of photosynthetic traits, independent of temperature. Toward drier sites, plants have higher photosynthetic capacities per leaf area but have fewer leaves. We also explain how plants arrange water transportation to support quicker photosynthesis at drier sites. However, plants at the drier sites seem to have diverse combinations of hydraulic traits to satisfy the need for photosynthesis. We reported surprising data-theory inconsistency for some hydraulic traits along the aridity gradient where further research is needed.

ecology↗

bioRxiv2022

Multiple NTS Neuron Populations Synergistically Suppress Physiologic Food Intake but are Dispensable for the Response to VSG

Several discrete groups of feeding-regulated neurons in the nucleus tractus solitarius (NTS) suppress food intake, including aversion-promoting neurons that express Cck (NTSCck cells) and distinct Lepr- and Calcr-expressing neurons (NTSLepr and NTSCalcr cells, respectively) that suppress food intake without promoting aversion. To test synergies among these cell groups we manipulated multiple NTS cell populations simultaneously. We found that activating multiple sets of NTS neurons (e.g., NTSLepr plus NTSCalcr (NTSLC), or NTSLC plus NTSCck (NTSLCK)) suppressed feeding more robustly than activating single populations. While activating groups of cells that include NTSCck neurons promoted conditioned taste avoidance (CTA), NTSLC activation produced no CTA despite abrogating feeding. Thus, the ability to promote CTA formation represents a dominant effect, but activating multiple non-aversive populations additively suppresses food intake without provoking aversion. Although silencing multiple NTS neuron groups augmented food intake and body weight more dramatically than silencing single populations, feeding activated many non-NTSLCK neurons and silencing NTSLCK neurons failed to blunt the weight loss response to vertical sleeve gastrectomy (VSG). Hence, while each of these NTS neuron populations plays crucial and additive roles in the control of energy balance, as-yet undefined cell types must make additional contributions to the control of feeding and the response to VSG.

neuroscience↗

bioRxiv2021

Mechanically Transduced Immunosorbent Assay To Measure Protein-Protein Interactions

Measuring protein-protein interaction (PPI) affinities is fundamental to biochemistry. Yet, conventional methods rely upon the law of mass action and cannot measure many PPIs due to a scarcity of reagents and limitations in the measurable affinity ranges. Here we present a novel technique that leverages the fundamental concept of friction to produce a mechanical signal that indicates binding. The mechanically transduced immunosorbent (METRIS) assay utilizes rolling magnetic probes to measure PPI interaction affinities. METRIS measures the translational displacement of protein-coated particles on a protein-functionalized substrate. The translational displacement scales with the effective friction induced by a PPI, thus producing a mechanical signal when a binding event occurs. The METRIS assay uses as little as 20 pmols of reagents to measure a wide range of affinities while exhibiting a high resolution and sensitivity. Here we use METRIS to measure several PPIs that were previously inaccessible using traditional methods, providing new insights into epigenetic recognition.

biochemistry↗

bioRxiv2020

Leptin Receptors in RIP-Cre25Mgn neurons Mediate Anti-Dyslipidemia Effects of Leptin in Insulin-Deficient Male Mice

Leptin is a potent endocrine hormone produced by adipose tissue and regulates a broad range of metabolism including glucose and lipid metabolism, with and without insulin. It is evident that central leptin signaling can lower hyperglycemia in insulin-deficient rodents via multiple mechanisms including restoration of dyslipidemia. However, the specific neurons that regulate these glucose-lowering and anti-dyslipidemia effects of leptin remain unidentified. Here we report that leptin receptors (LEPRs) in neurons expressing Cre recombinase driven by a short fragment of a promoter region of Ins2 gene (RIP-Cre25Mgn neurons) are required for central leptin signaling to reverse hyperglycemia and dyslipidemia in insulin-deficient mice. Ablation of LEPRs in RIP-Cre25Mgn neurons completely blocks glucose-lowering effects of leptin in insulin-deficient mice. Further investigations reveal that insulin-deficient mice lacking LEPRs in RIP-Cre25Mgn neurons (RIP-Cre{Delta}LEPR mice) exhibit greater lipid levels in blood and liver compared to wild-type controls, and that leptin injection into the brain does not suppress dyslipidemia in insulin-deficient RIP-Cre{Delta}LEPR mice. Leptin administration into the brain combined with acipimox, which lowers blood lipids by suppressing triglyceride lipase activity, can restore normal glycemia in insulin-deficient RIP-Cre{Delta}LEPR mice, suggesting that excess circulating lipids are a driving-force of hyperglycemia in insulin-deficient RIP-Cre{Delta}LEPR mice. Collectively, our data demonstrate that LEPRs in RIP-Cre25Mgn neurons significantly contribute to glucose-lowering effects of leptin in an insulin-independent manner by suppression of dyslipidemia.

neuroscience↗