Biology subjects

Melo, D.

Publications and source records attributed to Melo, D..

11 recordsLinked to original sources

bioRxiv2026

Covalent bond formation caught in a LOV photoreceptor

Light-oxygen-voltage (LOV) domains are blue-light photoreceptors of plants, algae and fungi, and among the most widely used tools in optogenetics. They switch on by forming a covalent thioether bond between a conserved cysteine and their flavin chromophore, in a reaction that needs a proton to cross from the cysteine to the flavin through a pocket containing essentially no water. Its mechanism has been debated for two decades1, and because the chemistry is over within a microsecond its elementary steps have stayed hidden. Here we combine 10 time-resolved serial femtosecond crystallography snapshots and infrared spectroscopy with QM/MM calculations to resolve the entire sequence of events at 1.4 [A] resolution: from excited-state distortion of the flavin ring (10-100 ps), through hydration of a surface channel (10 ns) and a single ordered water reaching the active site as the reactive cysteine shifts between its conformations (100-500 ns), to the thioether bond itself, caught half-formed at 1 {micro}s (half the molecules reacted, half still poised) and complete at 10-100 {micro}s. That water bridges the cysteine and the flavin and shuttles the proton, lowering the barrier from [~]35 to [~]15 kcal/mol and accelerating the reaction by roughly fourteen orders of magnitude (without it, the half-life would be [~]237,000 years), then departs before the bond forms. Proteins can therefore hydrate a dehydrated active site transiently and on demand to overcome otherwise prohibitive reaction barriers, a catalytic strategy that reaches well beyond photoreceptors.

biophysics↗

bioRxiv2026

Aerosol delivery-based serial femtosecond crystallography

Serial femtosecond crystallography (SFX) has revolutionised structural biology by enabling direct visualization of conformational dynamics of biomacromolecules at near-physiological temperatures. However, conventional SFX sample delivery at X-ray free-electron laser (XFEL) facilities introduces a significant X-ray scattering background, which may limit the data quality and resolution. Here, we introduce an aerosol delivery-based method that drastically reduces the back-ground scattering by minimising the liquid environment surrounding the nanocrystals. We validate our method by solving the structure of Cydia pomonella granulovirus nanocrystals at 1.9 [A] resolution, achieving orders-of-magnitude lower background scattering compared to a liquid jet-based method. Structural comparison with the liquid jet-based model revealed similar overall structure, suggesting that the native structure is largely preserved despite dehydration during aerosolisation. Our method enables efficient SFX studies, particularly pump-probe time-resolved SFX on protein nanocrystals with enhanced signal-to-noise ratios, as well as high-throughput small molecule SFX (smSFX) applications for pharmaceuticals and functional materials.

biophysics↗

bioRxiv2025

Invasion of new adaptive zones retains telltale signs of directional selection at macroevolutionary scales in mammals

Directional selection is often viewed as a transient force in macroevolution, with its signal eroded over time by stabilizing and fluctuating selection. Yet, transitions into new adaptive zones are predicted to impose strong and sustained selective pressures that may leave a detectable signature even across deep timescales. We test this prediction by comparing the rates of multivariate skull morphological evolution required to traverse the boundaries between adaptive zones against genetic drift expectations. Our dataset includes 11,793 specimens spanning 231 species from 12 mammalian clades, each containing unique ecological transitions into new adaptive zones. Using a quantitative genetics framework, we estimated the phenotypic distances between ancestral and derived adaptive zones and contrasted them with null expectations under genetic drift. While a few adaptive zone invasions (e.g., marsupials and rodents) are consistent with drift, most exhibit substantially elevated rates of evolution. These results suggest that directional selection has recurrently shaped mammalian cranial evolution during major ecological shifts. We propose that adaptive zone transitions represent evolutionary contexts in which adaptation leaves a persistent macroevolutionary signal, challenging the prevailing view that long-term patterns are dominated by static forces.

evolutionary biology↗

bioRxiv2025

Queen loss unmasks cryptic worker influence and decentralizes the bumble bee social network

Dominant individuals often structure group organization, but less is known about how social networks reorganize in their absence and how variation among subordinates contributes to collective outcomes. Bumble bees (Bombus impatiens) provide an ideal system to study these dynamics: queens typically monopolize reproduction, but in some contexts individual workers can adopt queenlike social roles. Using multi-animal pose tracking, we compared matched queenright and queenless partitions from the same source colonies, quantifying over 80 million social interactions. Queen-less colonies exhibited increased behavioral variation and contained a subset of highly influential workers with elevated movement, spatial centrality, and reproductive activity that was absent in queen-right conditions. The emergence of these individuals coincided with a shift from centralized to decentralized, efficient network architectures. These results demonstrate that queen presence constrains latent worker variation, revealing how individual behavioral differences can scale up to reshape collective social organization in hierarchical societies.

animal behavior and cognition↗

bioRxiv2024

Longitudinal sequencing reveals polygenic andepistatic nature of genomic response to selection

Evolutionary adaptation to new environments likely results from a combination of selective sweeps and polygenic shifts, depending on the genetic architecture of traits under selection. While selective sweeps have been widely studied, polygenic responses are considered more prevalent but challenging to quantify. The infinitesimal model makes explicit the hypothesis about the dynamics of changes in allele frequencies under selection, where only allelic effect sizes, frequencies, linkage, and gametic disequilibrium matter. Departures from this, like long-range correlations of allele frequency changes, could be a signal of epistasis in polygenic response. We performed an Evolve & Resequence experiment in Drosophila melanogaster exposing flies to a high-sugar diet as a source of environmental stress for over 100 generations. We tracked allele frequency changes in >3000 individually sequenced flies as well as population pools and searched for loci under selection by identifying sites with allele frequency trajectories that differentiated selection regimes consistently across replicates. We estimate that at least 4% of the genome was under positive selection, the result of a highly polygenic response. Most of this response was seen as small but consistent allele frequency changes over time, and there were only a few large allele-frequency changes (selective sweeps). We then searched for signatures of selection on pairwise combinations of alleles in the new environment and found several strong signals of putative epistatic interactions across unlinked loci that were consistent across selected populations. Finally, we measured differentially expressed genes (DEGs) across treatments and show that DEGs are enriched for selected SNPs, suggesting a regulatory basis for the selective response. Our results suggest that epistatic contributions to polygenic selective response are common and lead to detectable signatures.

evolutionary biology↗

bioRxiv2024

Crystal structure of a bacterial photoactivated adenylate cyclase determined at room temperature by serial femtosecond crystallography

OaPAC is a recently discovered blue-light using flavin adenosine dinucleotide (BLUF) photoactivated adenylate cyclase from the cyanobacterium Oscillatoria acuminata that uses adenosine triphosphate and translates the light signal into the production of cyclic adenosine monophosphate. Here, we report the crystal structures of the enzyme in the absence of its natural substrate determined from room temperature serial crystallography data collected at both an X-ray free electron laser and a synchrotron and we compare them with the cryo macromolecular crystallography structures obtained at a synchrotron by us and others. These results reveal slight differences in the structure of the enzyme due to data collection at different temperatures and X-ray sources. We further investigate the effect of the Y6 mutation in the blue-light using flavin adenosine dinucleotide domain, a mutation which results in a rearrangement of the hydrogen-bond network around the flavin and a notable rotation of the side-chain of the critical Q48 residue. These studies pave the way for ps - ms time-resolved serial crystallography experiments at X-ray free electron lasers and synchrotrons in order to determine the early structural intermediates and correlate them with the well-studied ps - ms spectroscopic intermediates. SynopsisStructures of the dark-adapted state of a photoactivated adenylate cyclase are determined from serial crystallography (SX) data collected at room temperature at an X-ray free electron laser (XFEL) and a synchrotron and are compared with cryo macromolecular crystallography (MX) synchrotron structures obtained by us and others. These structures of the wild-type enzyme in combination with the cryo MX synchrotron structure of a light-sensor domain mutant provide insight into the hydrogen bond network rearrangement upon blue-light illumination and pave the way for the determination of structural intermediates of the enzyme by time-resolved SX.

biophysics↗

bioRxiv2023

Reassessing the modularity of gene co-expression networks using the Stochastic Block Model

Finding communities in gene co-expression networks is a common first step toward extracting biological insight from these complex datasets. Most community detection algorithms expect genes to be organized into assortative modules, that is, groups of genes that are more associated with each other than with genes in other groups. While it is reasonable to expect that these modules exist, using methods that assume they exist a priori is risky, as it guarantees that alternative organizations of gene interactions will be ignored. Here, we ask: can we find meaningful communities without imposing a modular organization on gene co-expression networks, and how modular are these communities? For this, we use a recently developed community detection method, the weighted degree corrected stochastic block model (SBM), that does not assume that assortative modules exist. Instead, the SBM attempts to efficiently use all information contained in the co-expression network to separate the genes into hierarchically organized blocks of genes. Using RNA-seq gene expression data measured in two tissues derived from an outbred population of Drosophila melanogaster, we show that (a) the SBM is able to find ten times as many groups as competing methods, that (b) several of those gene groups are not modular, and that (c) the functional enrichment for non-modular groups is as strong as for modular communities. These results show that the transcriptome is structured in more complex ways than traditionally thought and that we should revisit the long-standing assumption that modularity is the main driver of the structuring of gene co-expression networks.

genomics↗

bioRxiv2023

Saturating the eQTL map in Drosophila melanogaster: genome-wide patterns of cis and trans regulation of transcriptional variation in outbred populations

Decades of genome-wide mapping have shown that most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing the effect of such genetic variation presents a formidable challenge, and eQTL mapping has been a key approach to understand the non-coding genome. However, comprehensive eQTL maps are available only for a few species like yeast and humans. With the aim of understanding the genetic landscape that regulates transcriptional variation in Drosophila melanogaster, we developed an outbred mapping panel in this species, the Drosophila Outbred Synthetic Panel (Dros-OSP). Using this community resource, we collected transcriptomic and genomic data for 1800 individual flies and were able to map cis and trans eQTLs for 98% of the genes expressed in D. melanogaster, increasing by thousands the number of genes for which regulatory loci are known in this species. We described, for the first time in the context of an outbred population, the properties of local and distal regulation of gene expression in terms of genetic diversity, heritability, connectivity, and pleiotropy. We uncovered that, contrary to long-standing assumptions, a significant part of gene co-expression networks is organized in a non-modular fashion. These results bring the fruit fly to the level of understanding that was only available for a few other organisms, and offer a new mapping resource that will expand the possibilities currently available to the Drosophila community. This data is available at Drosophilaeqtl.org.

genomics↗

bioRxiv2023

From GWAS to signal validation: An approach for estimating SNP genetic effects while preserving genomic context

Validating associations between genotypic and phenotypic variation remains a challenge, despite advancements in association studies. Common approaches for signal validation rely on gene-level perturbations, such as loss-of-function mutations or RNAi, which test the effect of genetic modifications usually not observed in nature. CRISPR-based methods can validate associations at the SNP level, but have significant drawbacks, including resulting off-target effects and being both time-consuming and expensive. Both approaches usually modify the genome of a single genetic background, limiting the generalizability of experiments. To address these challenges, we present a simple, low-cost experimental scheme for validating genetic associations at the SNP level in outbred populations. The approach involves genotyping live outbred individuals at a focal SNP, crossing homozygous individuals with the same genotype at that locus, and contrasting phenotypes across resulting synthetic outbred populations. We tested this method in Drosophila melanogaster, measuring the longevity effects of a polymorphism at a naturally-segregating cis-eQTL for the midway gene. Our results demonstrate the utility of this method in SNP-level validation of naturally occurring genetic variation regulating complex traits. This method provides a bridge between the statistical discovery of genotype-phenotype associations and their validation in the natural context of heterogeneous genomic contexts.

genetics↗

bioRxiv2022

Characterizing the landscape of gene expression variance in humans

Gene expression variance has been linked to organismal function and fitness but remains a commonly ne-glected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease. Author SummaryGene expression variance, or the variation in the level of gene expression within a population, can have significant impacts on physiology, disease, and evolutionary adaptations. While the average level of gene expression is typically the focus of research, the variation around this average level (i.e., gene expression variance) can also be important for understanding complex traits and disease. Here, we investigate the landscape of transcriptional variance across tissues, populations, and studies. Using large publicly available RNA-seq data sets, we were able to identify the general properties associated with high- and low-variance genes, as well as factors driving variation in variance across genes. Specifically, we uncovered gene expression variance was significantly associated with gene length, nucleotide diversity, the degree of connectivity and the presence of non-coding RNA. Our results suggest that the mechanisms responsible for maintaining optimal levels of variation in high-versus low-variance differ, and that this variability is the result of different patterns of selection.

genomics↗

bioRxiv2020

Catalytic cleavage of HEAT and subsequent covalent binding of the tetralone moiety by the SARS-CoV-2 main protease

Here we present the crystal structure of SARS-CoV-2 main protease (Mpro) covalently bound to 2-methyl-1-tetralone. This complex was obtained by co-crystallization of Mpro with HEAT (2-(((4-hydroxyphenethyl)amino)methyl)-3,4-dihydronaphthalen-1(2H)-one) in the framework of a large X-ray crystallographic screening project of Mpro against a drug repurposing library, consisting of 5632 approved drugs or compounds in clinical phase trials. Further investigations showed that HEAT is cleaved by Mpro in an E1cB-like reaction mechanism into 2-methylene-1-tetralone and tyramine. The catalytic Cys145 subsequently binds covalently in a Michael addition to the methylene carbon atom of 2-methylene-1-tetralone. According to this postulated model HEAT is acting in a pro-drug-like fashion. It is metabolized by Mpro, followed by covalent binding of one metabolite to the active site. The structure of the covalent adduct elucidated in this study opens up a new path for developing non-peptidic inhibitors.

biophysics↗