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Lobo, D.

Publications and source records attributed to Lobo, D..

14 recordsLinked to original sources

Wolves in black: multiple introgressions and natural selection may explain melanism in Italian wolves

Hybridisation between wild and domestic taxa can favour the spread of domestic alleles into wild populations through backcrossing. The complex interplay of random genetic drift, recombination, and selection can shape the fate of introgressed alleles. Maladaptive domestic variants are likely to be purged by natural selection, but others may persist across generations. It has long been known that the Apennine Italian wolf population, exposed to large numbers of free-ranging dogs, has experienced extensive introgression. The unusually high frequency of black wolves observed in Italy, compared to other European populations, may parallel patterns documented in North American wolves, where the melanistic KB allele at the CBD103 gene, of domestic origin, has spread over thousands of years of introgression. We tested whether the KB mutation entered the peninsular Italian wolf population via hybridisation and spread through adaptive introgression. Genome-wide analyses of black and wild-type (grey-coated) Apennine wolves showed no clear signatures of recent dog ancestry in most melanistic animals. Our ancestry reconstruction approaches identified two distinct KB haplogroups of domestic origin, suggesting multiple introgression events. Notably, we found molecular evidence consistent with balancing selection on the KB haplotypes, whose functional role, nonetheless, warrants further research. Therefore, the microevolutionary genomic and ecological consequences of wolf-dog hybridisation in Italy should be carefully investigated to inform appropriate science-based conservation management strategies.

genomics↗

Misleading Success: Genomes Reveal Critical Risks to European Gray Wolves

Have European gray wolves recovered? Despite an increase to [~]21,000 wolves (Canis lupus), our genomic analyses reveal significant risks to their long-term viability. We analyzed over 200 whole-genomes spanning five major European populations. Rather than a single recovering population, European wolves form a mosaic of isolated, independently evolving lineages, mostly diverging in the late Pleistocene. All lineages have contemporary effective population sizes below the threshold for long-term viability (Ne [≥] 500) and show extensive inbreeding. Runs of homozygosity reveal population-specific inbreeding histories spanning recent to deep timeframes. Most lineages exhibit higher realized than masked genetic load, indicating emerging inbreeding depression. These findings challenge claims that downlisting European wolves is biologically warranted: none of these populations currently meets thresholds associated with favorable conservation status.

evolutionary biology↗

Mesenchymal Stromal Cell Therapeutic Potential to RestoreNeurovascular Integrity in Machado-Joseph Disease

BackgroundMachado-Joseph disease (MJD), or Spinocerebellar Ataxia type 3 (SCA3), is a neurodegenerative disorder caused by an expansion of the CAG repeat in the MJD1/ATXN3 gene, which encodes for a polyglutamine-expansion in Ataxin-3. Similar to what occurs in other neurodegenerative disorders, the cerebrovascular system, particularly the blood-brain barrier (BBB), is impaired in MJD. BBB is an important cellular barrier that controls homeostasis of the central nervous system, and its disruption compromises neuronal function. To date, there is no disease-modifying therapy for MJD. Our group previously demonstrated that MSC administration can ameliorate the phenotype of MJD transgenic mice. However, the effect of MSC on the neurovascular unit and BBB integrity remains unexplored in the context of MJD. In the present work, we aimed to evaluate the therapeutic potential of MSC in mitigating vascular abnormalities and BBB disruption in MJD. MethodsEight-month-old MJD transgenic mice were treated with two consecutive bone marrow-MSC intravenous injections (1 week apart). Behavioral tests to assess motor coordination were conducted before and after treatment. Vascular structure, function, and BBB disruption were evaluated by immunohistochemistry and western blot. ResultsMSC administration partially restored vascular impairment in MJD transgenic mice. Treated mice exhibited improved gait and motor performance footprint and beam walking tests) and concurrently attenuated vascular dysfunction. Specifically, MSC-treated mice exhibited a decrease in collagen IV surface area and stabilized cerebellar blood supply. Additionally, MSC treatment diminished BBB permeability to the Evans blue (EB) dye in MJD mice and restored the levels of important adherent and tight junction-associated proteins in the cellular membrane, including vascular endothelial cadherin (VE-cadherin), claudin-5, and occludin, in a sex-specific manner. Conclusionsour results highlight significant cerebrovascular dysregulations in MJD, which are sex-dependent and progress with the disease stage. Moreover, our findings suggest that MSC administration partially reverted vascular impairments, providing valuable insights into the mechanisms underlying the therapeutic potential of MSC in MJD. Graphical AbstractMSC treatment partially reverts neurovascular dysregulation in MJD. MJD mice exhibit increased vessel coverage, increased BBB permeability, and altered TJ and AJ expression and subcellular localization. MSC administration modulates vessel coverage, reduces BBB leakage, and partially normalizes TJ/AJ subcellular localization. List of abbreviations: AJ - Adherent junction; BBB - Blood-Brain barrier; MJD- Machado-Joseph disease; MSC - mesenchymal stromal cell; TJ - thigh junction. Created with BioRender.com O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/703043v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@8fa0a2org.highwire.dtl.DTLVardef@17b13f9org.highwire.dtl.DTLVardef@15c5ce3org.highwire.dtl.DTLVardef@d67539_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Emergent Tissue Shapes from the Regulatory Feedback between Morphogens and Cell Growth

The development and regeneration of multicellular organisms require dynamic coordination between cellular behaviors and mechanochemical signals to achieve precise and stable tissue shapes. Plastic organisms, such as planarians, can regenerate, grow, and degrow as adults while maintaining precise whole-body and organ tissue shapes. However, the mechanisms underlying the pathways that coordinate and integrate these signals into the correct balance between cellular growth, mitosis, and apoptosis to form emergent target tissue shapes remain poorly understood. Here, we present a systematic theoretical study of the biological drivers controlling the feedback mechanisms between tissue growth and morphogen signaling. The approach is based on lattice-free, center-based simulations of cell size dynamics, mitosis, and apoptosis governed by both intercellular diffusible morphogen concentrations and mechanical stress between cells to drive their spatial organization. The results demonstrate how different morphogen properties and tissue mechanics form a feedback loop that is essential for the robust regulation of target tissue shapes. Furthermore, we show that stable tissue shapes can emerge from self-regulated patterning processes, such as Turing systems, controlling cellular growth dynamics. A stable feedback loop can form between the emergent morphogen patterns and the dynamics of cellular growth they regulate, as the tissue dynamics define the domain in which morphogens diffuse and hence pattern. Overall, this study highlights the essential role of the feedback loop between morphogen patterning and cellular growth in the regulation of tissue dynamics for stable shape formation. Moreover, this work establishes a framework for further experiments to understand the regulatory dynamics of whole-body development and regeneration using models with high spatiotemporal resolution. SignificanceTight coordination and interpretation of the multitude of signals at different biological scales- from intracellular signals to mechanical interactions-are essential during the development and regeneration of multicellular organisms. In this work, we investigate the leading role of the feedback between mechanochemical signaling networks and tissue shape through cellular behaviors such as growth, proliferation, and apoptosis. This study demonstrates the interdependence between tissue growth and pattern formation mechanisms in the regulation of stable tissue shapes. Overall, this research provides novel mechanistic insights into the formation of tissue shapes through the regulatory feedback interaction between cell growth and patterning dynamics.

biophysics↗

Circadian Rhythms are Disrupted in Patients and Preclinical Models of Machado-Joseph Disease

Machado-Joseph disease (MJD) is caused by an abnormal CAG repeat expansion in the ATXN3 gene, leading to the expression of a mutant ataxin-3 (mutATXN3) protein. MJD patients exhibit a wide range of clinical symptoms, including motor incoordination. Emerging evidence highlights circadian rhythm disruptions as early indicators and potential risk factors for the progression of neurodegenerative conditions. Circadian rhythms are regulated by internal clocks, with the suprachiasmatic nucleus (SCN) acting as the master pacemaker to synchronize timing across the bodys behavioural and physiological functions. While sleep disturbances have been observed in MJD, the role of clock regulation in its pathophysiology remains largely unexplored in spinocerebellar ataxias. This study aimed to investigate circadian rhythms, characterize associated disruptions, and uncover the mechanisms underlying clock dysregulation in patients and preclinical models of MJD. Circadian activity in MJD patients was assessed over two weeks using actigraphy, while in a YAC-MJD transgenic mouse model, circadian rhythms were examined through: (a) wheel-running experiments; (b) telemetry-based monitoring of core body temperature; (c) immunohistochemical analysis of the neuropeptides arginine vasopressin (AVP) and vasoactive intestinal polypeptide (VIP) in the SCN and paraventricular nucleus (PVN); and (d) RT-qPCR evaluation of clock gene expression in the cerebellum. The impact of mutATXN3 on clock mechanisms was further investigated using Bmal1/Per2-luciferase reporters. MJD patients exhibited a progressive decline in robustness of behavioural rhythms, demonstrated by negative correlations between the circadian function index, rest-activity fragmentation, and sleep efficiency with MJD clinical scales. YAC-MJD mice exhibited reduced activity levels, increased behavioural fragmentation, and required three additional days to re-entrain after a jet lag protocol, compared to controls. Disrupted core body temperature rhythms were observed, including a phase advance and elevated temperature ([~]1 {degrees}C) at the onset of the active period. Furthermore, transgenic mice showed reduced levels of VIP and AVP in the SCN and PVN, and decreased clock gene expression in the cerebellum. Lastly, we found new mechanistic evidence that WT ATXN3 activates the promoters of Bmal1 and Per2, whereas mutATXN3 loses the capacity to drive Per2 upon polyglutamine expansion. Overall, our findings indicate that central clock dysfunction in MJD is associated with impaired clock gene expression and disruptions in activity and temperature rhythms. This study provides the first robust evidence of circadian rhythm dysregulation and underlying mechanisms in MJD, paving the way for the identification of new biomarkers and the development of novel circadian-based interventions to tackle MJD and possibly other spinocerebellar ataxias. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/631212v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@25078dorg.highwire.dtl.DTLVardef@112e523org.highwire.dtl.DTLVardef@1818356org.highwire.dtl.DTLVardef@1d5a6c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models

Genome-scale metabolic models (GEMs) and other constraint-based models (CBMs) play a pivotal role in understanding biological phenotypes and advancing research in areas like metabolic engineering, human disease modelling, drug discovery, and personalized medicine. Despite their growing application, a significant challenge remains in ensuring the reproducibility of GEMs, primarily due to inconsistent reporting and inadequate model documentation of model results. Addressing this gap, we introduce FROG analysis, a community-driven initiative aimed at standardizing reproducibility assessments of CBMs and GEMs. The FROG framework encompasses four key analyses--Flux variability, Reaction deletion, Objective function, and Gene deletion--to produce standardized, numerically reproducible FROG reports. These reports serve as reference datasets, enabling model evaluators, curators, and independent researchers to verify the reproducibility of GEMs systematically. BioModels, a leading repository of systems biology models, has integrated FROG analysis into its curation workflow, enhancing the reproducibility and reusability of submitted GEMs. In our study evaluating 65 GEM submissions from the community, approximately 40% reproduced without intervention, 28% requiring minor adjustments, and 32% needing input from authors. The standardization introduced by FROG analysis facilitated the detection and resolution of issues, ultimately leading to the successful reproduction of all models. By establishing a standardized and comprehensive approach to evaluating GEM reproducibility, FROG analysis significantly contributes to making CBMs and GEMs more transparent, reusable, and reliable for the broader scientific community.

systems biology↗

Mechanistic Regulation of Planarian Shape During Growth and Degrowth

Adult planarians can grow when fed and degrow (shrink) when starved while maintaining their whole-body shape with correct proportions. Different planarian morphogens are expressed at the anterior-posterior poles, medio-lateral border, and midline to provide positional information signals for the specification of different tissues at the right locations. However, it is currently unknown how these signals are coordinated together during feeding or starvation and how they modulate the differential tissue growth or degrowth necessary to form correct whole-body shapes. Here we investigate the dynamics of planarian shape during growth and degrowth together with a theoretical study to evaluate the mechanisms that regulate whole-body proportions and shape. We found that the planarian body proportions scale isometrically following similar linear rates during growth and degrowth, but that fed worms are significantly wider than starved worms. By combining a descriptive model of planarian shape and size with a mechanistic model of anterior-posterior and medio-lateral signaling calibrated with a novel machine learning methodology, we demonstrate that the feedback loop between these positional information signals and the shape they control can regulate the planarian whole-body shape during growth. Furthermore, the model can predict the correct shape and size dynamics during degrowth due to an increase in apoptosis rate and pole signal during starvation. These results offer mechanistic insights into planarian shape and size dynamics and the regulation of whole-body morphologies.

developmental biology↗

Automatic design of gene regulatory mechanisms for spatial pattern formation

Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms--including the number of genes necessary for the formation of the target pattern--we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover pattern-producing genetic circuits.

systems biology↗

Isolation of Biologically Active Extracellular Vesicles-Associated AAVs for Gene Delivery to the Brain by Size Exclusion Chromatography

Extracellular vesicles-associated adeno-associated viral vectors (EV-AAVs) emerged as a new opportunity for non-invasive gene therapy targeting the central nervous system (CNS). However, in previous reports, only AAV serotypes with known ability to cross the blood-brain barrier (BBB) have been used for EV-AAV production and testing through non-invasive strategies. In this work, we aimed at optimizing a size exclusion chromatography (SEC) protocol for the production and isolation of natural and biologically active brain-targeting EV-AAVs, that could be applied to any AAV serotype and further used for non-invasive gene delivery to the CNS. We performed a comparison between SEC and differential ultracentrifugation (UC) isolation protocols in terms of yield, contaminants, and transgene expression efficiency. We found that SEC allows a higher recovery of EV-AAVs, free of cell contaminating proteins and with less solo AAVs than UC. Remarkably, SEC-purified EV-AAVs also showed to be more potent at transgene expression than solo AAVs in neuronal cell lines. EV-AAVs exhibited the ability to cross the BBB in neonatal mice upon intravenous administration. In conclusion, SEC-purified brain-targeting EV-AAVs show to be a promising gene delivery vector for therapy of brain disorders. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/542901v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@7016b8org.highwire.dtl.DTLVardef@e3a5f3org.highwire.dtl.DTLVardef@1a43286org.highwire.dtl.DTLVardef@f110c5_HPS_FORMAT_FIGEXP M_FIG C_FIG During the production of AAV vectors, a small percentage of AAVs is secreted in association with extracellular vesicles, named "EV-AAVs". EV-AAVs can be efficiently isolated by size exclusion chromatography (SEC). When intravenously injected in mice, brain targeting EV-AAVs can cross the blood brain barrier (BBB) and transduce neuronal cells.

molecular biology↗

mergem: merging and comparing genome-scale metabolic models using universal identifiers

Numerous methods exist to produce and refine genome-scale metabolic models. However, due to the use of incompatible identifier systems for metabolites and reactions, computing and visualizing the metabolic differences and similarities of such models is a current challenge. Furthermore, there is a lack of automated tools that can combine the strengths of multiple reconstruction pipelines into a curated single comprehensive model by merging different drafts, which possibly use incompatible namespaces. Here we present mergem, a novel method to compare and merge two or more metabolic models. Using a universal metabolic identifier mapping system constructed from multiple metabolic databases, mergem robustly can compare models from different pipelines and merge their common elements. mergem is implemented as a command line tool, a Python package, and on the web-application Fluxer, which allows simulating and visually comparing multiple models with different interactive flux graphs. The ability to merge and compare diverse genome scale metabolic models can facilitate the curation of comprehensive reconstructions and the discovery of unique and common metabolic features among different organisms.

systems biology↗

Automatic Generation of Interactive Multidimensional Phase Portraits

Mathematical models formally and precisely represent biological mechanisms with complex dynamics. To understand the possible behaviors of such systems, phase portrait diagrams can be used to visualize their overall global dynamics across a domain. However, producing these phase portrait diagrams is a laborious process reserved to mathematical experts. Here, we developed a computational methodology to automatically generate phase portrait diagrams to study biological dynamical systems based on ordinary differential equations. The method only needs as input the variables and equations describing a multidimensional biological system and it automatically outputs for each pair of dependent variables a complete phase portrait diagram, including the critical points and their stability, the nullclines of the system, and a vector space of the trajectories. Crucially, the portraits generated are interactive, and the user can move the visualized planar slice, change parameters with sliders, and add trajectories in the phase and time domains, after which the diagrams are updated in real time. The method is available as a user-friendly graphical interface or can be accessed programmatically with a Mathematica package. The generated portraits and particular views can be saved as computable notebooks preserving the interactive functionality, an approach that can be adopted for reproducible science and interactive pedagogical materials. The method, code, and examples are freely-available at https://lobolab.umbc.edu/autoportrait.

systems biology↗

On taming the effect of transcript level intra-condition count variation during differential expression analysis: a story of dogs, foxes and wolves

The evolution of RNA-seq technologies has yielded datasets of high scientific value that are often generated as condition associated biological replicates within differential expression studies. As the number of replicates increase, so to does confidence in identifying differentially expressed transcripts. With rapidly expanding RNA-seq data archives there is opportunity to augment replicate numbers when conditions of interest overlap at an inter-study level. Despite correction procedures for estimating transcript abundance, a remaining source of error is transcript level intra-condition count variation; as partially indicated by the disjointed results between differential expression analysis tools. Such variation is amplified at an inter-study level. Here, we present TVscript, a tool that removes reference-based transcripts associated with intra-condition variation above specified thresholds. With this tool we explore the effects of removing transcripts associated with varying degrees of intra-condition variation on differential expression analysis. This is done in relation to inter- and intra-study datasets representing brain samples of dogs, wolves and foxes (wolves vs. dogs and aggressive vs. tame foxes). We demonstrate that 20% of the transcripts identified as being differentially expressed are associated with high levels of intra-condition variation. This is an over-representation relative to the reference set. As transcripts harbouring such variation are removed from the reference prior to differential expression analysis a discordance from 26 to 40% in the lists of differentially expressed transcripts is observed when compared to those obtained using the non-filtered reference. For our data, the removal of transcripts possessing intra-condition variation values within (and above) the 97th and 95th percentiles, for wolves vs. dogs and aggressive vs. tame foxes, maximized the detection of differentially expressed transcripts as a result of alterations within gene-wise dispersion estimates. Through this analysis the support for seven genes with potential for being involved with selection for tameness is provided. TVscript is available at: https://sourceforge.net/projects/tvscript/.

bioinformatics↗

CView: A network based tool for enhanced alignment visualization

To date basic visualization of sequence alignments have largely focused on displaying per-site columns of nucleotide, or amino acid, residues along with associated frequency summarizations. The persistence of this tendency to the more recent tools designed for the viewing of mapped read data indicates that such a perspective not only provides a reliable visualization of per-site alterations, but also offers implicit reassurance to the end user in relation to data accessibility. However, the initial insight gained is limited, something that is especially true when viewing alignments consisting of many sequences representing differing factors, such as geographical location, date and subtype. A basic alignment viewer can have potential to increase initial insight through visual enhancement, whilst not delving into the realms of complex sequence analysis. Here we present CView, a visualizer that expands on the per-site representation of residues through the incorporation of a dynamic network that is based on the summarization of diversity present across different regions of the alignment. Within the network nodes are based on the clustering of sequence fragments spanning windows that are placed consecutively along the alignment. Edges are placed between nodes of neighbouring windows where they share sequence ids. Thus, if a single node is selected on the network, then the relationship that all sequences passing through that node have to other regions of diversity within the alignment can be instantly observed through the tracing of paths. In addition to augmenting visual insight, CView provides many export features including variant summarization, per-site residue and kmer frequency matrixes, consensus sequence generation, alignment dissection as well as general sequence clustering, each of which are useful across a range of research areas. The software has been designed to be user friendly, intuitive and interactive. It, along with source code, a quick start guide and test data, are available through the SourceForge project page: https://sourceforge.net/projects/cview/.

bioinformatics↗

Continuous dynamic modeling of regulated cell adhesion

Cell-cell adhesion is essential for tissue growth and multicellular pattern formation, and crucial for the cellular dynamics during embryogenesis and cancer progression. Understanding the dynamical gene regulation of cell adhesion molecules (CAMs) responsible for the emerging spatial tissue behaviors is a current challenge due to the complexity of these non-linear interactions and feedback loops at different levels of abstraction--from genetic regulation to whole-organism shape formation. Continuous mathematical models of cell adhesion are ideal for the modeling of the spatial dynamics of large cell populations, where different cell types define inherent adhesion strengths. However, biologically the adhesive properties of the cell arise dynamically from differential expression of CAMs, which are precisely regulated during development and cancer progression. To extend our understanding of cell and tissue behaviors due to the regulation of adhesion molecules, here we present a novel model for the spatial dynamics of cellular patterning, growth, and shape formation due to the differential expression of CAMs and their regulation. Capturing the dynamic interplay between genetic regulation, CAM expression, and differential cell adhesion, the proposed continuous model can recapitulate the complex and emergent spatial behaviors of cell populations that change their adhesion properties dynamically due to inter- and intracellular genetic regulation. This approach can demonstrate the mechanisms responsible for classical cell sorting behaviors, cell intercalation in proliferating populations, and the involution of germ layer cells induced by a diffusing morphogen during gastrulation. Integrating the emergent spatial tissue behaviors with the regulation of genes responsible for essential cellular properties such as adhesion will pave the way towards understanding the genetic regulation of large-scale complex patterns and shapes formation in developmental, regenerative, and cancer biology.

biophysics↗