Biology subjects

Serrano, E.

Publications and source records attributed to Serrano, E..

12 recordsLinked to original sources

bioRxiv2026

Single-cell hit calling in high-content imaging screens with Buscar

High-content screening (HCS) enables the systematic quantification of single-cell morphology features across thousands of perturbations, capturing rich phenotypic heterogeneity. Image-based profiling is a critical bioinformatics processing step in this pipeline, as researchers use it to predict mechanisms of action, assess toxicity, perform hit calling, and more. However, current image-based profiling workflows rely on aggregate statistics, such as calculating mean or median feature values per well, implicitly assuming cell homogeneity. This limitation obscures subpopulation effects, reducing sensitivity to subtle or heterogeneous effects of perturbations. Here we present Buscar, a method that leverages the full heterogeneity of single-cell image-based profiles to call hits. Buscar requires two reference, single-cell populations that define distinct morphology states: a reference state (e.g., disease cells) and a target state (e.g., healthy cells). Buscar then compares these two groups to define on- and off-morphology signatures, which it then uses to score every perturbation in a given screen. The scores quantify perturbation efficacy and off-target effects, or specificity, in an interpretable manner, clarifying which morphologies are appropriately altered and which may arise from off-target activity. We apply Buscar to three datasets. First, as a proof of concept, we applied Buscar to a Cell Painting dataset of cardiac fibroblasts from patients with heart failure. Buscar quantifies both morphology rescue and off-target morphology activity in these cells treated with a TGF{beta} receptor inhibitor. Second, we show that Buscar recovers biologically coherent gene-phenotype associations across 16 manually-labeled phenotypes in the MitoCheck dataset. Lastly, applied to CPJUMP1, we show that Buscar is robust to technical replicates collected across plates in both small-molecule and CRISPR-Cas9 perturbations. Together, these results establish Buscar as a reproducible and interpretable hit calling method that overcomes aggregation bias, enabling the simultaneous quantification of compound efficacy and specificity to enhance hit calling in HCS. We release Buscar as an open-source python package.

bioinformatics↗

bioRxiv2025

Herbivore pressure modulates soil multifunctionality in a Mediterranean landscape

Ongoing global environmental changes demand cost-effective strategies to restore ecosystem functioning. Within this context, the reintroduction of large mammalian herbivores has emerged as a promising approach to recover ecological processes and foster self-sustaining, biodiverse ecosystems. However, the impacts of such initiatives remain poorly understood, particularly regarding their effects on soil functions and ecological processes. We tested whether large herbivore densities (wild horses (Garrano breed) and cattle (Maronesa breed, an ancient lineage close to aurochs) modulates soil multifunctionality (the simultaneous provision of multiple ecosystem functions) across habitats (grasslands, shrublands, and forests) and seasons (fall and spring) in a Mediterranean landscape. Using composite multivariate indices describing soil functions related to biogeochemical cycles (i.e., enzymatic activities) and physicochemical properties (pH, conductivity, organic matter, and nutrient loads), we found that soil enzymatic activities varied seasonally, being higher in spring, and interacted with habitat and herbivore pressure gradients. Habitat and herbivore pressure explained the variation in soil multifunctionality during spring, while in fall it was mainly driven by herbivore pressure. Enzymatic stoichiometry, particularly C:P ratios, strongly predicted soil fertility and multifunctionality, showing positive relationships in forest habitats and under herbivore pressure. A mechanistic approach confirmed that herbivore impacts on soil functioning operated primarily through changes in soil properties and nutrient cycling rather than direct effects. Mediterranean landscapes are rapidly changing, and our results highlight herbivore management as a key tool to sustain soil ecological processes under the rewilding framework. Highlights- Large herbivores impacted soil functions and properties in different habitats - Large herbivores significantly impacted soil nutrient cycling and multifunctionality. - The magnitude of the effects was dependent on season and habitat - Large herbivores indirectly impact soil ecosystem multifunctionality through changes in soil properties.

ecology↗

bioRxiv2025

Scalable data harmonization for single-cell image-based profiling with CytoTable

High-content imaging (HCI) involves the automated acquisition and quantitative analysis of cell phenotypes from microscopy images. These studies often rely on screening, which can involve thousands of chemical or genetic perturbations that produce terabytes of microscopy data. To extract meaningful biological insights, this data must be processed into quantitative features through a technique known as image-based profiling. A major analytical bottleneck is curating the high-dimensional, single-cell data derived from varied image analysis tools. These datasets suffer from inconsistent schemas, inefficient file formats, and undocumented ontological relationships. These challenges reduce reproducibility and slow progress in downstream applications. To solve these issues, we introduce CytoTable1, a software package for harmonizing single-cell image-based profiling. CytoTable enables modular, portable, and cross-language data integration through a robust, reproducible, and scalable engine that harmonizes single-cell readouts from multiple image analysis tools, preparing for feature integration with software in the Cytomining ecosystem such as Pycytominer.2

bioinformatics↗

bioRxiv2024

A versatile information retrieval framework for evaluating profile strength and similarity

In profiling assays, thousands of biological properties are measured across many samples, yielding biological discoveries by capturing the state of a cell population, often at the single-cell level. However, for profiling datasets, it has been challenging to evaluate the phenotypic activity of a sample and the phenotypic consistency among samples, due to profiles high dimensionality, heterogeneous nature, and non-linear properties. Existing methods leave researchers uncertain where to draw boundaries between meaningful biological response and technical noise. Here, we developed a statistical framework that uses the well-established mean average precision (mAP) as a single, data-driven metric to bridge this gap. We validated the mAP framework against established metrics through simulations and real-world data applications, revealing its ability to capture subtle and meaningful biological differences in cell state. Specifically, we used mAP to assess both phenotypic activity for a given perturbation (or a sample) as well as consistency within groups of perturbations (or samples) across diverse high-dimensional datasets. We evaluated the framework on different profile types (image, protein, and mRNA profiles), perturbation types (CRISPR gene editing, gene overexpression, and small molecules), and profile resolutions (single-cell and bulk). Our open-source software allows this framework to be applied to identify interesting biological phenomena and promising therapeutics from large-scale profiling data.

bioinformatics↗

bioRxiv2024

Variations in clustering of multielectrode local field potentials in the motor cortex of macaque monkeys during a reach-and-grasp task

There is experimental evidence of varying correlation among the elements of the neuromuscular system over the course of the reach-and-grasp task. Several neuromuscular disorders are accompanied by anomalies in muscular coupling during the task. The aim of this study was to investigate if modifications in correlations and clustering can be detected in the Local Field Potential (LFP) recordings of the motor cortex during the task. To this end, we analyzed the LFP recordings from a previously published study on monkeys which performed a reach-and-grasp task for targets with a vertical or horizontal orientation. LFP signals were recorded from the motor and premotor cortex of macaque monkeys as they performed the task. We found very robust changes in the correlations of the multielectrode LFP recordings which corresponded to task epochs. Mean LFP correlation increased significantly during reaching and then decreased during grasp. This pattern was very robust for both left and right arm reaches irrespective of target orientation. A hierarchical cluster analysis supported the same conclusion - a decreased number of clusters during reach followed by an increase for grasp. A sliding window computation of the number of clusters was performed to probe the predictive capacities of these LFP clusters for upcoming task events. For a very high percentage of trials (95.3%), there was a downturn in cluster number following the Pellet Drop (GO signal) which reached a minimum shortly preceding the Start of grasp, hence indicating that cluster analyses of LFP signals could provide online indications of the Start of grasp.

neuroscience↗

bioRxiv2024

AdhE spirosome length in enterohaemorrhagic Escherichia coli is correlated with enzymatic directionality and is perturbed by salicylidene acylhydrazide binding

Antibiotics are contraindicated for the treatment of infection enterohemorrhagic Escherichia coli (EHEC), a human pathogen that causes diarrhea or hemorrhagic colitis in humans which can progress to hemolytic uremic syndrome (HUS). As an alternative to the use of antibiotics, previous studies developed the salicylidene acylhydrazides (SA), a family of anti-virulence compounds capable of blocking expression of the type three secretion system (T3SS), thereby reducing bacterial infections. Here we validate AdhE as the anti-virulence protein target of the SA compound ME0054. AdhE is a bidirectional enzyme able to catalyse the conversion of acetyl-CoA to ethanol and vice versa. AdhE oligomerises forming helicoidal filaments heterogeneous in length called spirosomes. In this work, we show that it is possible to partially fractionate AdhE spirosomes using size exclusion chromatography (SEC) and to characterise the spirosome oligomers present in each fraction with biophysical techniques such as small angle X-ray scattering (SAXS) and sedimentation velocity analytical ultracentrifugation (SV-AUC). Also, we observe that short spirosomes are more efficient in the reverse reaction whereas the spirosome length has no impact on the forward reaction. Therefore, for first time, we reveal that AdhE spirosome formation is necessary to regulate the direction of its enzymatic reactions. In addition, we show that ME0054 disrupts AdhE spirosomes, thereby enhancing the conversion of ethanol to acetyl-CoA. Importantly, SV-AUC data show that ME0054 binds to the AdhE filaments. Finally, time-resolved (TR) SAXS allowed us to follow the kinetics of spirosome disruption produced by ME0054, confirming its effectiveness at biologically relevant temperatures and timescales. SIGNIFICANCE STATEMENTThere is an urgent need to develop alternative strategies to combat bacterial infections. Salicylidene acylhydrazides (SA) are able to reduce expression of the bacterial type three secretion system (T3SS), used by many pathogens to manipulate host eukaryotic cells, including our pathogen of interest: enterohaemorrhagic E. coli (EHEC). The mechanism underpinning these compounds is a mystery. Here we show how the SA compound ME0054, by disrupting AdhE spirosomes, enhances metabolic conversion of ethanol to acetyl-CoA. This finding is consistent with the phenotype observed in an EHEC AdhE mutant: alterations in acetate levels and changes in T3SS expression. Our work establishes a crucial mechanistic link between the binding of the SA compound to a key target protein and changes in bacterial metabolism.

biophysics↗

bioRxiv2023

Analysis of the Confidence in the Prediction of the Protein Folding by Artificial Intelligence

The determination of protein structure has been facilitated using deep learning models, which can predict protein folding from protein sequences. In some cases, the predicted structure can be compared to the already-known distribution if there is information from classic methods such as nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, or electron microscopy (EM). However, challenges arise when the proteins are not abundant, their structure is heterogeneous, and protein sample preparation is difficult. To determine the level of confidence that supports the prediction, different metrics are provided. These values are important in two ways: they offer information about the strength of the result and can supply an overall picture of the structure when different models are combined. This work provides an overview of the different deep-learning methods used to predict protein folding and the metrics that support their outputs. The confidence of the model is evaluated in detail using two proteins that contain four domains of unknown function.

bioinformatics↗

bioRxiv2023

Enhancing drug repurposing on graphs by integrating drug molecular structure as feature

Drug repurposing has become increasingly important, particularly in light of the COVID-19 pandemic. This process involves identifying new therapeutic uses for existing drugs, which can significantly reduce the cost, risk, and time associated with developing new drugs, de novo development. A previous conducted study proved that Deep Learning can be used to streamline this process by identifying drug repurposing hypotheses. The study presented a model called REDIRECTION, which utilized the rich biomedical information available in graph form and combined it with Geometric Deep Learning to find new indications for existing drugs. The reported metrics for this model were 0.87 for AUROC and 0.83 for AUPRC. In this current study, the importance of node features in GNNs is explored. Specifically, the study used GNNs to embed two-dimensional drug molecular structures and obtain corresponding features. These features were incorporated into the drug repurposing graph, along with some other enhancements, resulting in an improved model called DMSR. Performance score for the reported metrics values raised by 0.0448 in AUROC and 0.0919 in AUPRC. Based on these findings, we believe that the method used for embedding drug molecular structures is interesting and captures valuable information about drugs. Its incorporation in the graph for drug repurposing can significantly benefit the process, leading to improved performance evaluation metrics.

bioinformatics↗

bioRxiv2022

A Xenopus neuromast bioassay for chemical ototoxicity

BackgroundOtotoxic chemicals can impair the senses of hearing and balance in mammals through irreversible damage to the mechanosensory bundles of inner ear hair cells. Fish and amphibians are useful models for investigating ototoxicity because their inner ear hair cells, like those of mammals, are susceptible to damage by ototoxins. Moreover, amphibian mechanosensation is augmented by a lateral line organ on the body surface that comprises external mechanosensory hair cells. The lateral line hair cells are arranged in clusters (neuromasts) and are structurally and functionally similar to inner ear hair cells, but are more accessible for experimental manipulation. Herein, we implemented neuromasts of the amphibian (Xenopus) lateral line as an organ system for evaluating the effects of ototoxic chemicals, such as antibiotics, on mechanosensory hair cell bundles. MethodsWe examined the ultrastructure of larval Xenopus laevis neuromasts with scanning electron microscopy (SEM) after larvae were continuously exposed to ototoxic aminoglycoside antibiotics at sub-lethal concentrations (gentamicin; streptomycin; neomycin) for 72 hours. ResultsSEM images demonstrated that 72 hours of exposure to antibiotic concentrations greater than 25 {micro}M reduced the hair cell bundle number in lateral line neuromasts. ConclusionTherapeutic drug studies will benefit from the incorporation of bioassay strategies that evaluate ototoxicity across multiple species including genera of amphibian origin such as Xenopus. Our outcomes support the use of the Xenopus lateral line for identification of potential ototoxic chemicals and suggest that Xenopus neuromast hair cell bundles can withstand antibiotic exposure. The Xenopus bioassay presented here can be incorporated into drug discovery methodology as a high-resolution phenotypic screen for ototoxic effects. Summary statementDamage to sensory cells of the inner ear by chemical agents such as antibiotics contributes to the growing global prevalence of disorders of hearing and balance. Our results demonstrate that the Xenopus lateral line, in conjunction with SEM, affords an accessible organ system for otoxicity screens during the drug discovery pipeline.

neuroscience↗

bioRxiv2021

Utilization efficiency of human milk oligosaccharides by human-associated Akkermansia is strain-dependent

Akkermansia muciniphila are mucin degrading bacteria found in the human gut and are often associated with positive human health. However, despite being detected as early as one month of age, little is known about the role of Akkermansia in the infant gut. Human milk oligosaccharides (HMOs) are abundant components of human milk and are structurally similar to the oligosaccharides that comprise mucin, the preferred growth substrate of human-associated Akkermansia. A limited subset of intestinal bacteria has been shown to grow well on HMOs and mucin. We therefore examined the ability of genomically diverse strains of Akkermansia to grow on HMOs. First, we screened 85 genomes representing the four known Akkermansia phylogroups to examine their metabolic potential to degrade HMOs. Furthermore, we examined the ability of representative isolates to grow on individual HMOs in a mucin background and analyzed the resulting metabolites. All Akkermansia genomes were equipped with an array of glycoside hydrolases associated with HMO-deconstruction. Representative strains were all able to grow on HMOs with varying efficiency and growth yield. Strain CSUN-19 belonging to the AmIV phylogroup, grew to the highest level in the presence of fucosylated and sialylated HMOs. This activity may be partially related to the increased copy numbers and/or the enzyme activities of the -fucosidases, -sialidases, and {beta}-galactosidases. Utilization of HMOs by strains of Akkermansia suggests that ingestion of HMOs by an infant may enrich for these potentially beneficial bacteria. Further studies are required to realize this opportunity and deliver long-lasting metabolic benefits to the human host. ImportanceHuman milk oligosaccharides (HMOs) are utilized by a limited subset of bacteria in the infant gut. Akkermansia are detected in infants as young as one month of age and are thought to contribute to the HMO deconstruction capacity of the infant. Here, using phylogenomics, we examined the genomic capacity of different Akkermansia phylogroups to potentially deconstruct HMOs. Furthermore, we experimentally showed that strains from all the currently known phylogroups of Akkermansia can deconstruct all the major types of HMOs, albeit with different utilization efficiencies. This study thus examines Akkermansia-HMO interactions that can potentially influence the gut microbial ecology during the first 1,000 days of life - a critical phase for the development of the gut microbiome and infant health. This study will be of interest to a wide range of scientists from microbiologists, glycochemists/glycobiologists, to functional food developers investigating Akkermansia as probiotics or functional foods containing milk oligosaccharides as prebiotics.

microbiology↗

bioRxiv2020

Recombination proteins differently control the acquisition of homeologous DNA during Bacillus subtilis natural chromosomal transformation

In naturally competent Bacillus subtilis cells the acquisition of closely related genes occurs via homology-directed chromosomal transformation (CT), and its frequency decreases log-linearly with increased sequence divergence (SD) up to 15%. Beyond this and up to 23% SD the interspecies boundary prevails, the CT frequency marginally decreases, and short (<10-nucleotides) segments are integrated via homology-facilitated micro-homologous integration. Both poorly known CT mechanisms are RecA-dependent. Here we identify the recombination proteins required for the acquisition of interspecies DNA. The absence of AddAB, RecF, RecO, RuvAB or RecU, crucial for repair-by-recombination, does not affect CT. However, inactivation of dprA, radA, recJ, recX or recD2 strongly interfered with CT. Interspecies CT was abolished beyond ~8% SD in {Delta}dprA, ~10% in {Delta}recJ, {Delta}radA, {Delta}recX and 14% in {Delta}recD2 cells. We propose that DprA, RecX, RadA/Sms, RecJ and RecD2 help RecA to unconstrain speciation and gene flow. These functions are ultimately responsible for generating genetic diversity and facilitate CT and gene acquisition from bacteria of the same genus.

microbiology↗

bioRxiv2019

Syngap Splice Variants Display Heterogeneous Spatio-Temporal Expression And Subcellular Distribution In The Developing Mammalian Brain

The Syngap1 gene is a major regulator of synapse biology and neural circuit function. Genetic variants linked to epilepsy and intellectual disability disrupt synaptic function and neural excitability. The SynGAP protein has been involved in multiple signaling pathways and can regulate small GTPases with very different functions. Yet, the molecular bases behind this pleiotropy are poorly understood. We hypothesize that different SynGAP isoforms will mediate different sets of functions and that deciphering their spatio-temporal expression and subcellular localization will accelerate our understanding of the multiple functions performed by SynGAP. Using antibodies that detect all isoforms of SynGAP, we found that its subcellular localization changed throughout postnatal development. Consistent with previous reports, SynGAP was enriched in the postsynaptic density in the mature forebrain. However, this was age-dependent and SynGAP was predominantly found in non-synaptic locations in a period of postnatal development highly sensitive to SynGAP levels. Furthermore, we identified different expression patterns in the spatial and temporal axes for different SynGAP isoforms. Particularly noticeable was the delayed expression of SynGAP 1 isoforms, which bind to PSD-95 at the postsynaptic density, in cortex and hippocampus during the first two weeks of postnatal development. The subcellular localization of SynGAP was also isoform-dependent. While, 1 isoforms were highly enriched in the postsynaptic density, other C-terminal isoforms were less enriched or even more abundant in non-synaptic locations, particularly during the postnatal period. Thus, the regulation of expression and subcellular distribution of SynGAP isoforms may contribute to isoform-specific regulation of small GTPases, explaining SynGAP pleiotropy.

neuroscience↗