Biology subjects

Santos, G. S.

Publications and source records attributed to Santos, G. S..

8 recordsLinked to original sources

bioRxiv2025

Memory B cell Development in Response to mRNA SARS-CoV-2 and Nanoparticle Immunization in Mice

Nanoparticle immunogens excel at rapidly inducing high levels of circulating antibodies and are being deployed as part of several novel vaccines. However, their ability to elicit memory B cell responses is less well understood. Here we compared serologic and memory B cell responses to prime boost vaccination with either SARS-CoV-2 Wuhan-Hu-1 mRNA vaccine, or protein nanoparticles: SARS-CoV-2 B.1.351 homotypic containing a single receptor binding domain (RBD); (homotypic beta) or a combination of different Sarbecovirus RBDs (mosaic 8b), respectively. The memory B cells elicited by the 3 vaccine regimens showed closely related antibody sequences, similar levels of somatic mutation and clonal diversity. The breadth of serologic responses elicited by the mosaic nanoparticles were comparable to the homotypic nanoparticle and superior to the mRNA vaccine for some mismatched strains. However, serum neutralizing titers to SARS-CoV-2 were highest after mRNA vaccination. The three vaccines elicited memory B cells that produced antibodies specific to a broad range of epitopes on the RBD that differed in a way that may reflect epitope masking. Monoclonal antibodies derived from memory B cells elicited by the mosaic 8b nanoparticle showed greater breadth against a panel of SARS-CoV-2 variants and SARS-CoV. Significance StatementNanoparticle vaccines are promising next-generation vaccine candidates, yet their capacity to generate durable memory B cell responses remains incompletely understood. We compared immune responses following SARS-CoV-2 mRNA, homotypic beta nanoparticle, or mosaic 8b nanoparticle vaccination in mice. Serum antibody neutralizing responses against a panel of SARS-CoV-2 variants elicited by an mRNA vaccine were equivalent or superior to those elicited by mosaic 8b nanoparticle vaccines. However, the monoclonal antibodies derived from memory B cells elicited by the mosaic 8b nanoparticle showed better neutralizing breadth against heterologous pseudoviruses. These findings highlight individual strengths of mRNA and nanoparticle vaccines and show that mosaic 8b nanoparticle immunogens can enhance the breadth of memory B cell-derived antibodies.

immunology↗

bioRxiv2024

Affinity maturation of antibody responses is mediated by differential plasma cell proliferation

Increased antibody affinity over time after vaccination, known as affinity maturation, is a prototypical feature of immune responses. Recent studies have shown that a diverse collection of B cells, producing antibodies with a wide spectrum of different affinities, are selected into the plasma cell (PC) pathway. How affinity-permissive selection enables PC affinity maturation remains unknown. Here we report that PC precursors (prePC) expressing high affinity antibodies receive higher levels of T follicular helper (Tfh)-derived help and divide at higher rates than their lower affinity counterparts once they leave the GC. Thus, differential cell division by selected prePCs accounts for how diverse precursors develop into a PC compartment that mediates serological affinity maturation.

immunology↗

bioRxiv2024

A sustainable and bee-pollinated coffee to start your day

The integration of managed pollinators into agricultural systems represents a practical strategy for boosting crop production, optimising sustainable farming practices, and improving rural livelihoods. However, the use of managed bees to supplement the contribution of wild pollinators still faces challenges, such as over-reliance on pesticides in intensively managed agroecosystems. Here, we placed managed bee colonies on conventional farms to assess their impact on arabica coffee yield, quality and market value, while also to evaluate colony health in coffee fields treated with field rates of thiamethoxam-based products. We show that supplementing farms with managed bees increased farmer income by enhancing coffee yield and beverage quality, which is rewarded by specialty coffee markets. Moreover, our field-based study reveals that, even when exposed to field-realistic levels of the neonicotinoid thiamethoxam, managed bee colonies exhibited no significant adverse effects on their health within coffee fields. Our results underline that pollination is a key input on intensively managed coffee farms, and that agricultural production and environmental conservation interact synergically to maximize profitability, which is fundamental to encourage farmers to be good stewards of their croplands by adopting nature-positive practices.

ecology↗

bioRxiv2024

Population responses to environmental stochasticity are primarily driven by survival-reproduction trade-offs and mediated by aridity

Forecasting responses of natural populations to increasingly stochastic environments is a major challenge in Ecology and Conservation Biology. We now know that populations can modulate how their vital rates (e.g., survival, reproduction) change through time to minimise the negative impacts of environmental stochasticity. However, despite the important analytical and theoretical advances that have led to this knowledge, we still do not know (1) how much this ability of natural populations to buffer against environmental stochasticity can vary in nature, nor (2) the drivers of these strategies, with likely candidates including the environmental regimes themselves, as well as the life history traits and phylogenetic ancestry of the species of interest. To address these questions, we parameterised a Bayesian generalised linear mixed model with high-resolution vital rate data from 134 natural populations across 89 species of plants and animals. We show that population responses to environmental stochasticity vary three orders of magnitude along a demographic buffering continuum. Furthermore, the position of a given population along said continuum is predicted by a survival-reproduction trade-off and by the degree of aridity the population experiences. Our findings open a promising avenue of research to improve ecological forecasts and management of natural populations in the Anthropocene.

ecology↗

bioRxiv2023

Structured demographic buffering: A framework to explore the environment drivers and demographic mechanisms underlying demographic buffering

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of these strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environment factors and demographic characteristics are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to quantify the relative effects of three key drivers of demographic buffering: environment components (e.g., temporal autocorrelation and variance), population structure, and demographic rates (e.g., progression and fertility). Using Integral Projection Models, we explore how these drivers impact the demographic buffering abilities of three plant species with different life histories and demonstrate how our approach successfully characterises a populations capacity to demographically buffer against environmental stochasticity in a changing world.

ecology↗

bioRxiv2023

A unified framework to identify demographic buffering in natural populations

The Demographic Buffering Hypothesis (DBH) predicts that natural selection reduces the temporal fluctuations in demographic processes (such as survival, development, and reproduction), due to their negative impacts on population dynamics. However, a comprehensive approach that allows for the examination of demographic buffering patterns across multiple species is still lacking. Here, we propose a three-step framework aimed at identifying and quantifying demographic buffering. Firstly, we categorize species along a continuum of variance based on their stochastic elasticities. Secondly, we examine the linear selection gradients, followed by the examination of nonlinear selection gradients as the third step. With these three steps, our framework overcomes existing limitations of conventional approaches to identify and quantify demographic buffering, allows for multi-species comparisons, and offers an insight into the evolutionary forces that shape demographic buffering. We apply this framework to mammal species and discuss both the advantages and potential of our framework.

ecology↗

bioRxiv2022

MOSAIC: A Unified Trait Database to Complement Structured Population Models

O_LIThe ecological sciences have joined the big data revolution. However, despite exponential growth in data availability, broader interoperability amongst datasets is still needed to unlock the potential of open access. The interface of demography and functional traits is well-positioned to benefit from said interoperability. Trait-based ecological approaches have been criticised because of their inability to predict fitness components, the core of demography; likewise, demographic approaches are data-hungry, and so using traits as ecological shortcuts to understanding and forecasting population viability could offer great value. C_LIO_LIHere, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data have been digitised and curated through a combination of existing datasets and additional taxonomic and/or trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC also includes species-level phylogenies for 1,359 species and population-specific climate data where locations are recorded. C_LIO_LIUsing MOSAIC, we highlight a taxonomic mismatch of widely used trait databases with existing structured population models. Despite millions of trait records available in open-access databases, taxonomic overlap between open-access demographic and trait databases is <5%. We identify where traits of interest to ecologists can benefit from database integration and start to quantify traits that are poorly quantified (e.g., growth determination, modularity). C_LIO_LIThe MOSAIC database evidences the importance of improving interoperability in open-access efforts in ecology as well as the need for complementary digitisation to fill targeted taxonomic gaps. In addition, MOSAIC highlights emerging challenges associated with the disparity between locations where different trait records are sourced. C_LI

ecology↗

bioRxiv2021

To buffer or to be labile? A framework to disentangle demographic patterns and evolutionary processes

Until recently, natural selection was assumed to reduce temporal fluctuation in vital rates due to its negative effects on population dynamics - the so-called Demographic Buffering Hypothesis (DBH). After several failures to support the DBH in the two decades since it was first posited, an alternative hypothesis was suggested; the Demographic Lability Hypothesis (DLH), where population vital rates should track rather than buffer the environmental conditions. Despite the huge contribution of both hypotheses to comprehend the demographic strategies to cope the environmental stochasticity, it remains unclear if they represent two competing patterns or the extreme ends of a continuum encompassing all demographic strategies. To solve this historical debate, we unify several methods with an integrative theoretical approach where: i) using the sum of stochastic elasticity with respect to mean and variance - a first-order derivative approach - we rank species on a Buffering-Lability (DB-DL) continuum and ii) using the second-order derivative, we examine how vital rates are shaped by natural selection. Our framework, applied to 40 populations of 34 mammals, successfully placed the species on the DB-DL continuum. We could also link the species' position on the DB-DL continuum to their generation time and time to recovery. Moreover, the second-order derivative unveiled that vital rates with lower temporal variation are not necessarily under a strong pressure of stabilizing selection, as predicted by DBH and DLH. Our framework provides an important step towards unifying the different perspectives of DBH and DLH with key evolutionary concepts.

ecology↗