Biology subjects

Duarte, F.

Publications and source records attributed to Duarte, F..

13 recordsLinked to original sources

bioRxiv2026

Chromosome-level genome and caste transcriptomes for Africa's most widespread social wasp (Belonogaster juncea) reveal unexpected genomic diversity

Belonogaster is an African genus of primitively eusocial wasps. They are widespread and conspicuous across sub-Saharan Africa and yet are among the least studied groups of social wasps. Here, we present the first high-quality, chromosome-level genome assembly for a representative of this genus, Belonogaster juncea, complemented by an RNA-seq analysis of brain transcription among individuals representing reproductive and non-reproductive castes. The assembled genome spans 315.8 Mb with a scaffold N50 of 7.91 Mb. The annotation contained 15,159 protein-coding genes and 20,046 isoforms, with Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness of 98.0% for the genome and 97.8% for the annotation. Using this new assembly, we show that the B. juncea genome differs notably from other social wasp genomes: a single satellite repeat makes up a fifth of its chromosome-scale sequence, it has the highest putative chromosome number in a sequenced wasp genome to date, and it shows high levels of syntenic breaks. We find caste neuro-transcription differences between queens and workers, revealing 573 differentially expressed genes (341 worker biased, 232 queen biased), with significant overlap in caste-specific genes when compared to Polistes dominula and Liostenogaster flavolineata. This genomic resource provides a foundation for understanding the molecular mechanisms underlying primitive eusociality and social evolution in wasps, and opens up new research opportunities for a genus of little-studied insects from the Global South.

genomics↗

bioRxiv2026

EXCON: a scalable, reproducible Nextflow pipeline for CAFE-based gene EXpansion and CONtraction analysis

Gene family expansion and contraction analysis is a commonly used approach in evolutionary comparative genomics to identify lineage-specific evolutionary pressures on gene copy/family number. CAFE is one of the most popular tools to measure changes in gene family size, but requires a high level of bioinformatics expertise, manual parameter tuning and preprocessing. Here we present EXCON, an automated, Eco-Flow community-developed Nextflow pipeline that integrates NCBI genome download, annotation quality and format pre-processing, orthologous gene family identification (Orthofinder), ultrametric tree formatting, birth-death modelling (CAFE), and GO enrichment analysis (eggNOG-mapper/TopGO) into a single, portable workflow. EXCON accepts genome assemblies and annotations, supports local, HPC and cloud-based computing environments, and requires minimal user configuration. The pipeline auto-selects appropriate CAFE lambda and error models, and separates high variance orthogroups for separate treatment. Applied to a 24-species primate dataset spanning Catarrhini, Platyrrhini and Strepsirrhini, the pipeline identified 358 rapidly evolving gene families, including a DUX (double homeobox) gene showing repeated, independent copy-number turnover across multiple lineages, consistent with the known instability of the D4Z4 macrosatellite repeat it resides in. EXCON is freely available at https://github.com/Eco-Flow/excon.

evolutionary biology↗

bioRxiv2025

Correctness is its own reward: bootstrapping error signals in self-guided reinforcement learning

Reinforcement learning (RL) offers a compelling account of how agents learn complex behaviors by trial and error, yet RL is predicated on the existence of a reward function provided by the agents environment. By contrast, many skills are learned without external guidance, posing a challenge to RLs ability to account for self-directed learning. For instance, juvenile male zebra finches first memorize and then train themselves to reproduce the song of an adult male tutor through extensive practice. This process is believed to be guided by an internally computed assessment of performance quality, though the mechanism and development of this signal remain unknown. Here, we propose that, contrary to prevailing assumptions, tutor song memorization and performance assessment are subserved by the same neural circuit, one trained to predictively cancel tutor song. To test this hypothesis, we built models of a local forebrain circuit that uses contextual premotor signals to cancel tutor song auditory input via synaptic plasticity. After learning, excitatory projection neurons signaled mismatches between the tutor song and birds own performance, best matching experimental data when learning involved anti-Hebbian plasticity in recurrent interneurons. We also found that learning proceeds by both sharpening error sensitivity and minimizing responses to the tutor song. Finally, the error signals produced by this model can train a simple RL agent to replicate the spectrograms of adult bird songs. These results suggest that local learning via predictive cancellation suffices for bootstrapping error signals capable of guiding self-directed learning of natural behaviors. SignificanceMany species, including humans, learn new skills by trial and error. But in the absence of external rewards and punishments, individuals need a means of assessing the quality of their performance. Here, we model the process by which juvenile male zebra finches memorize the song of an adult tutor, showing how local changes in brain circuits responsible for hearing can give rise during this process to an internal error signal that later allows for self-guided learning.

neuroscience↗

bioRxiv2023

Substrate recognition and selectivity in SARS-CoV-2 main protease: Unveiling the role of subsite interactions through dynamical nonequilibrium molecular dynamics simulations

The main protease (Mpro) of the SARS-CoV-2 coronavirus employs a cysteine-histidine dyad in its active site to catalyse hydrolysis of the viral polyproteins. It is well established that binding of the substrate P1-Gln in the S1 subsite of Mpro active site is crucial for catalysis and this interaction has been employed to inform inhibitor design; however, how Mpro dynamically recognises and responds to substrate binding remains difficult to probe by experimental methods. We thus employed the dynamical nonequilibrium molecular dynamics (D-NEMD) approach to probe the response of Mpro to systematic substrate variations. The results emphasise the importance of P1-Gln for initiating a productive enzymatic reaction. Specifically, substituting P1-Gln with alanine disrupts the conformations of the Cys145 and His41 dyad, causing Cys145 to transition from the productive gauche conformation to the non-productive trans conformation. Importantly, our findings indicate that Mpro exhibits dynamic responses to substrate binding and likely to substrate-mimicking inhibitors within each of the S4-S2' subsites. The results inform on the substrate selectivity requirements and shed light on the observed variations in hydrolytic efficiencies of Mpro towards different substrates. Some interactions between substrate residues and enzyme subsites involve more induced fit than others, implying that differences in functional group flexibility may optimise the binding of a substrate or inhibitor in a particular subsite.

biochemistry↗

bioRxiv2023

A systematic screening assay identifies efficient small guide RNAs for CRISPR activation

CRISPR-mediated gene activation (CRISPRa) encompasses a growing field of biotechnological approaches with exciting implications for gene therapy. However, there is a lack of experimental validation tools for selecting efficient sgRNAs for downstream applications. Here, we present a screening assay capable of identifying efficient single- and double sgRNAs through fluorescence quantification in vitro. In addition, we provide a tailored Golden Gate cloning workflow for streamlined incorporation of selected sgRNA candidates into lentiviral (LVs) or adeno-associated vectors (AAVs). The overall workflow was validated using therapeutically relevant genes for neurodegenerative diseases, such as Tfeb, Adam17, and Sirt1. The most efficient sgRNAs also demonstrated activation of endogenous gene expression at mRNA and protein levels. Further proof- of-principle assays using Tfeb indicated that gene activation was accompanied by increased levels of Lc3b. This data demonstrates the potential of the screening assay to identify functionally efficient sgRNA candidates across multiple genes along with streamlined cloning of viral vectors and may assist in accelerating future developments of CRISPRa-focused applications.

molecular biology↗

bioRxiv2023

Studies on the selectivity of the SARS-CoV-2 papain-like protease reveal the importance of the P2' proline of the viral polyprotein

The SARS-CoV-2 papain-like protease (PLpro) is an antiviral drug target that catalyzes the hydrolysis of the viral polyproteins pp1a/1ab, releasing the non-structural proteins (nsps) 1-3 that are essential for the coronavirus lifecycle. The LXGG{downarrow}X motif found in pp1a/1ab is crucial for recognition and cleavage by PLpro. We describe molecular dynamics, docking, and quantum mechanics/molecular mechanics (QM/MM) calculations to investigate how oligopeptide substrates derived from the viral polyprotein bind to PLpro. The results reveal how the substrate sequence affects the efficiency of PLpro-catalyzed hydrolysis. In particular, a proline at the P2' position promotes catalysis, as validated by residue substitutions and mass spectrometry-based analyses. Analysis of PLpro catalyzed hydrolysis of LXGG motif-containing oligopeptides derived from human proteins suggests that factors beyond the LXGG motif and the presence of a proline residue at P2' contribute to catalytic efficiency, possibly reflecting the promiscuity of PLpro. The results will help in identifying PLpro substrates and guiding inhibitor design.

bioinformatics↗

bioRxiv2022

Dynamical nonequilibrium molecular dynamics simulations identify allosteric sites and positions associated with drug resistance in the SARS-CoV-2 main protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in the coronavirus lifecycle by catalysing hydrolysis of the viral polyproteins at specific sites. Mpro is the target of drugs, such as nirmatrelvir, though resistant mutants have emerged that threaten drug efficacy. Despite its importance, questions remain on the mechanism of how Mpro binds its substrates. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to evaluate structural and dynamical responses of Mpro to the presence and absence of a substrate. The results highlight communication between the Mpro dimer subunits and identify networks, including some far from the active site, that link the active site with a known allosteric inhibition site, or which are associated with nirmatrelvir resistance. They imply that some mutations enable resistance by altering the allosteric behaviour of Mpro. More generally, the results show the utility of the D-NEMD technique for identifying functionally relevant allosteric sites and networks including those relevant to resistance.

biochemistry↗

bioRxiv2022

Activity-driven extracellular volume expansion drives vertebrate axis elongation

The vertebrate bauplan is primarily established via the formation of embryonic tissues in a head-to-tail progression. The biomechanics of this elongation, which requires the presomitic mesoderm (PSM), remains poorly understood. Here, we find that avian PSM explants can elongate autonomously when physically confined in vitro, producing a pushing force that can largely account for the posterior elongation of the embryo. Tissue elongation results from volumetric expansion that is driven by cellular activity and accompanied by inhomogeneous increase of the extracellular fraction along the AP axis. We show that FGF signaling promotes glycolysis-dependent production of Hyaluronic Acid (HA), which is required for expansion of the posterior PSM. Our findings link body axis elongation to tissue expansion through the metabolic control of extracellular matrix production downstream of FGF signaling. One-Sentence SummaryActive tissue expansion propels body elongation independent of cell proliferation-driven growth

developmental biology↗

bioRxiv2021

A neural hub that coordinates learned and innate courtship behaviors

Holistic behaviors often require the coordination of innate and learned movements. The neural circuits that enable such coordination remain unknown. Here we identify a midbrain cell group (A11) that enables male zebra finches to coordinate their learned songs with various innate behaviors, including female-directed calling, orientation and pursuit. Anatomical mapping reveals that A11 is at the center of a complex network including the song premotor nucleus HVC as well as brainstem regions crucial to innate calling and locomotion. Notably, lesioning A11 terminals in HVC blocked female-directed singing, but did not interfere with female-directed calling, orientation or pursuit. In contrast, lesioning A11 cell bodies abolished all female-directed courtship behaviors. However, males with either type of lesion still produced songs when in social isolation. Lastly, monitoring A11 terminals in HVC showed that during courtship A11 inputs to the song premotor cortex signal the transition from innate to learned vocalizations. These results show how a brain region important to reproduction in both birds and mammals coordinates learned vocalizations with innate, ancestral courtship behaviors.

neuroscience↗

bioRxiv2021

Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding

The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mpro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mpro competitively. The combined results provide new insight useful for the development of Mpro inhibitors.

bioinformatics↗

bioRxiv2020

Microbial Species Abundance Distributions Guide Human Population Size Estimation from Sewage Metagenomes

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxas relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome. Author summaryWastewater-based epidemiology (WBE) is an emerging field that employs sewage as aggregated samples of human populations. This approach is particularly promising for tracking diseases that can spread asymptomatically in large populations, such as the COVID-19. As a new type of biological data, sewage has its own unique challenges to utilize. While wastewater samples are usually assumed to represent large populations, it is not guaranteed, because of stochasticity in toilet flushes; unlike epidemiological experiments collecting data from individuals, sample size, i.e., the human population size represented by a wastewater sample, is a fundamental yet difficult-to-characterize parameter for sewage samples. Researchers would need to aggregate data from large areas and week-long collection to stabilize data, during which, important spikes in small areas or short time scales may be lost. It also remains challenging to turn viral titers into case prevalences, evaluating representativeness, or comparing measurements across sites/studies. This study provides a framework to estimate human population size from sewage utilizing human gut-associated microorganisms. Through analysis, we demonstrate that variance of taxon abundances and single-nucleotide polymorphism as two variables that change with population size. We provide a new tool MicrobiomeCensus that performs population size estimation from microbial taxon abundances. MicrobiomeCensus outperforms generic algorithms in terms of computational efficiency while at comparable or better accuracy. Using MicrobiomeCensus, we detected population size differences in sewage samples taken in Cambridge, MA, under two sampling approaches, i.e., "grab" or "composite" sampling. This study provides a framework to utilize individual-level microbiomes to learn from sewage, paving the way to prevalence estimation and improved spatio-temporal resolutions in WBE..

bioinformatics↗

bioRxiv2019

Inference and effects of barcode multiplets in droplet-based single-cell assays

A widespread assumption for single-cell analyses specifies that one cells nucleic acids are predominantly captured by one oligonucleotide barcode. However, we show that [~]13-21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call \"barcode multiplets\". We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that [~]4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that [~]5-7% of beads may contain multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data.

genomics↗

bioRxiv2019

Interkinetic nuclear movements promote apical expansion in pseudostratified epithelia at the expense of apicobasal elongation

Pseudostratified epithelia (PSE) are a common type of columnar epithelia found in a wealth of embryonic and adult tissues such as ectodermal placodes, the trachea, the ureter, the gut and the neuroepithelium. PSE are characterized by the choreographed displacement of cells nuclei along the apicobasal axis according to phases of their cell cycle. Such movements, called interkinetic movements (INM) have been proposed to influence tissue expansion and shape and suggested as culprit in several congenital diseases such as CAKUT and esophageal atresia. INM rely on cytoskeleton dynamics just as adhesion, contractility and mitosis do. Therefore, longer term impairment of INM without affecting proliferation and adhesion is currently technically unachievable. Here we bypassed this hurdle by generating a 2D agent-based model of a proliferating PSE and compared its output to the growth of the chick neuroepithelium to assess the interplay between INM and these other important cell processes during growth of a PSE. We found that INM directly generates apical expansion and apical nuclear crowding. In addition, our data strongly suggest that apicobasal elongation of cells is not an emerging property of a proliferative PSE but rather requires a specific elongation program. We then discuss how such program might functionally link INM, tissue growth and differentiation.\n\nAuthors SummaryPseudostratified epithelia (PSE) are a common type of epithelia characterized by the choreographed displacement of cells nuclei along the apicobasal axis during proliferation. These so-called interkinetic movements (INM) were proposed to influence tissue expansion and suggested as culprit in several congenital diseases. INM rely on cytoskeleton dynamics. Therefore, longer term impairment of INM without affecting proliferation and adhesion is currently technically unachievable. We bypassed this hurdle by generating a mathematical model of PSE and compared it to the growth of an epithelium of reference. Our data show that INM drive expansion of the apical domain of the epithelium and suggest that apicobasal elongation of cells is not an emerging property of a proliferative PSE but might rather requires a specific elongation program.

developmental biology↗