Biology subjects

Gomez, A.

Publications and source records attributed to Gomez, A..

49 records · Page 3Linked to original sources

bioRxiv2021

Extraordinarily precise nematode sex ratios: Adaptive responses to vanishingly rare mating options

Sex ratio theory predicts both mean sex ratio and variance under a range of population structures. Here, we compare two genera of phoretic nematodes (Parasitodiplogaster and Ficophagus spp.) associated with twelve fig-pollinating wasp species in Panama. The host wasps exhibit classic Local Mate Competition: only inseminated females disperse from natal figs, and their offspring form mating pools that consist of scores of the adult offspring contributed by one or a few foundress mothers. In contrast, in both nematode genera, only sexually undifferentiated juveniles disperse, and their mating pools routinely consist of eight or fewer adults. Across all mating pool sizes, the sex ratios observed in both nematode genera are consistently female-biased (~0.34 males), which is markedly less female-biased than is often observed in the host wasps (~0.10 males). In further contrast with their hosts, variances in nematode sex ratios are also consistently precise (significantly less than binomial). The constraints associated with predictably small mating pools within highly subdivided populations appear to select for precise sex ratios that contribute both to the reproductive success of individual nematodes, and to the evolutionary persistence of nematode species. We suggest that some form of environmental sex determination underlies these precise sex ratios.

evolutionary biology↗

bioRxiv2020

Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning

Quantifying the pathogenicity of protein variants in human disease-related genes would have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences1-3. In principle, computational methods could support the large-scale interpretation of genetic variants. However, prior methods4-7 have relied on training machine learning models on available clinical labels. Since these labels are sparse, biased, and of variable quality, the resulting models have been considered insufficiently reliable8. By contrast, our approach leverages deep generative models to predict the clinical significance of protein variants without relying on labels. The natural distribution of protein sequences we observe across organisms is the result of billions of evolutionary experiments9,10. By modeling that distribution, we implicitly capture constraints on the protein sequences that maintain fitness. Our model EVE (Evolutionary model of Variant Effect) not only outperforms computational approaches that rely on labelled data, but also performs on par, if not better than, high-throughput assays which are increasingly used as strong evidence for variant classification11-23. After thorough validation on clinical labels, we predict the pathogenicity of 11 million variants across 1,081 disease genes, and assign high-confidence reclassification for 72k Variants of Unknown Significance8. Our work suggests that models of evolutionary information can provide a strong source of independent evidence for variant interpretation and that the approach will be widely useful in research and clinical settings.

genetics↗

bioRxiv2020

Development and pre-clinical characterization of two therapeutic equine formulations towards SARS-CoV-2 proteins for the potential treatment of COVID-19

In the current global emergency due to SARS-CoV-2 outbreak, passive immunotherapy emerges as a promising treatment for COVID-19. Among animal-derived products, equine formulations are still the cornerstone therapy for treating envenomations due to animal bites and stings. Therefore, drawing upon decades of experience in manufacturing snake antivenom, we developed and preclinically evaluated two anti-SARS-CoV-2 polyclonal equine formulations as potential alternative therapy for COVID-19. We immunized two groups of horses with either S1 (anti-S1) or a mixture of S1, N, and SEM mosaic (anti-Mix) viral recombinant proteins. Horses reached a maximum anti-viral antibody level at 7 weeks following priming, and showed no major adverse acute or chronic clinical alterations. Two whole-IgG formulations were prepared via hyperimmune plasma precipitation with caprylic acid and then formulated for parenteral use. Both preparations had similar physicochemical and microbiological quality and showed ELISA immunoreactivity towards S1 protein and the receptor binding domain (RBD). The anti-Mix formulation also presented immunoreactivity against N protein. Due to high anti-S1 and anti-RBD antibody content, final products exhibited high in vitro neutralizing capacity of SARS-CoV-2 infection, 80 times higher than a pool of human convalescent plasma. Pre-clinical quality profiles were similar among both products, but clinical efficacy and safety must be tested in clinical trials. The technological strategy we describe here can be adapted by other producers, particularly in low- and middle-income countries.

microbiology↗

bioRxiv2020

CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation

In this work, we describe the CRIMSON (CardiovasculaR Integrated Modelling and SimulatiON) software environment. CRIMSON provides a powerful, customizable and user-friendly system for performing three-dimensional and reduced-order computational haemodynamics studies via a pipeline which involves: 1) segmenting vascular structures from medical images; 2) constructing analytic arterial and venous geometric models; 3) performing finite element mesh generation; 4) designing, and 5) applying boundary conditions; 6) running incompressible Navier-Stokes simulations of blood flow with fluid-structure interaction capabilities; and 7) post-processing and visualizing the results, including velocity, pressure and wall shear stress fields. A key aim of CRIMSON is to create a software environment that makes powerful computational haemodynamics tools accessible to a wide audience, including clinicians and students, both within our research laboratories and throughout the community. The overall philosophy is to leverage best-in-class open source standards for medical image processing, parallel flow computation, geometric solid modelling, data assimilation, and mesh generation. It is actively used by researchers in Europe, North and South America, Asia, and Australia. It has been applied to numerous clinical problems; we illustrate applications of CRIMSON to real-world problems using examples ranging from pre-operative surgical planning to medical device design optimization. CRIMSON binaries for Microsoft Windows 10, documentation and example input files are freely available for download from www.crimson.software, and the source code with compilation instructions is available on GitHub https://github.com/carthurs/CRIMSONFlowsolver (CRIMSON Flowsolver) under the GPL v3.0 license, and https://github.com/carthurs/CRIMSONGUI (CRIMSON GUI), under the AGPL v3.0 license. Support is available on the CRIMSON Google Groups forum, located at https://groups.google.com/forum/#!forum/crimson-users.

bioengineering↗

bioRxiv2020

Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights

MotivationCo-expression networks are a powerful gene expression analysis method to study how genes co-express together in clusters with functional coherence that usually resemble specific cell type behaviour for the genes involved. They can be applied to bulk-tissue gene expression profiling and assign function, and usually cell type specificity, to a high percentage of the gene pool used to construct the network. One of the limitations of this method is that each gene is predicted to play a role in a specific set of coherent functions in a single cell type (i.e. at most we get a single for each gene). We present here GMSCA (Gene Multifunctionality Secondary Co-expression Analysis), a software tool that exploits the co-expression paradigm to increase the number of functions and cell types ascribed to a gene in bulk-tissue co-expression networks. ResultsWe applied GMSCA to 27 co-expression networks derived from bulk-tissue gene expression profiling of a variety of brain tissues. Neurons and glial cells (microglia, astrocytes and oligodendrocytes) were considered the main cell types. Applying this approach, we increase the overall number of predicted triplets by 46.73%. Moreover, GMSCA predicts that the SNCA gene, traditionally associated to work mainly in neurons, also plays a relevant function in oligodendrocytes. AvailabilityThe tool is available at GitHub,https://github.com/drlaguna/GMSCA as open source software. ImplementationGSMCA is implemented in R.

bioinformatics↗

bioRxiv2020

Interspecies variation in hominid gut microbiota controls host gene regulation

The gut microbiome exhibits extreme compositional variation between hominid hosts. However, it is unclear how this variation impacts host physiology, and whether this effect can be mediated through microbial regulation of host gene expression in interacting epithelial cells. Here, we characterized the transcriptional response of colonic epithelial cells in vitro to live microbial communities extracted from humans, chimpanzees, gorillas, and orangutans. We found most host genes exhibit a conserved response, whereby they respond similarly to the four hominid microbiomes, while some genes respond only to microbiomes from specific host species. Genes that exhibit such a divergent response are associated with relevant intestinal diseases in humans, such as inflammatory bowel disease and Crohns disease. Lastly, we found that inflammation-associated microbial species regulate the expression of host genes previously associated with inflammatory bowel disease, suggesting health-related consequences for species-specific host-microbiome interactions across hominids.

genomics↗

bioRxiv2020

SMARCA4 deficient tumours are vulnerable to KDM6A/UTX and KDM6B/JMJD3 blockade

Despite the genetic inactivation of SMARCA4, a core component of the SWI/SNF-complex commonly found in cancer, there are no therapies that effectively target SMARCA4-deficient tumours. Here, we show that, unlike the cells with activated MYC oncogene, cells with SMARCA4 inactivation are refractory to the histone deacetylase inhibitor, SAHA, leading to the aberrant accumulation of H3K27me3. This is associated with impaired transactivation and significantly reduced levels of the histone demethylases KDM6A/UTX and KDM6B/JMJD3, which confer a strong dependency on the KDM6s in the SMARCA4-mutant cells, so that its inhibition compromises cell viability. Administering the KDM6 inhibitor GSK-J4 to mice orthotopically implanted with SMARCA4-mutant lung cancer cells or primary small cell carcinoma of the hypercalcaemic type (SCCOHT) had strong anti-tumour effects. Our results highlight the vulnerability of KDM6 inhibitors as a characteristic that could be exploited for treating SMARCA4-mutant cancer patients.

cancer biology↗

bioRxiv2020

Isolation and characterization of Streptomyces bacteriophages and Streptomyces strains encoding biosynthetic arsenals

The threat to public health posed by drug-resistant bacteria is rapidly increasing, as some of healthcares most potent antibiotics are becoming obsolete. Approximately two-thirds of the worlds antibiotics are derived from natural products produced by Streptomyces encoded biosynthetic gene clusters. Thus, in order to identify novel gene clusters, we sequenced the genomes of four bioactive Streptomyces strains isolated from the soil in San Diego County and used Bacterial Cytological Profiling adapted for agar plate culturing in order to examine the mechanisms of bacterial inhibition exhibited by these strains. In the four strains, we identified 101 biosynthetic gene clusters. Some of these clusters were predicted to produce previously studied antibiotics; however, the known mechanisms of these molecules could not fully account for the antibacterial activity exhibited by the strains, suggesting that novel clusters might encode antibiotics. When assessed for their ability to inhibit the growth of clinically isolated pathogens, three Streptomyces strains demonstrated activity against methicillin-resistant Staphylococcus aureus. Additionally, due to the utility of bacteriophages for genetically manipulating bacterial strains via transduction, we also isolated four new phages (BartholomewSD, IceWarrior, Shawty, and TrvxScott) against S. platensis. A genomic analysis of our phages revealed nearly 200 uncharacterized proteins, including a new site-specific serine integrase that could prove to be a useful genetic tool. Sequence analysis of the Streptomyces strains identified CRISPR-Cas systems and specific spacer sequences that allowed us to predict phage host ranges. Ultimately, this study identified Streptomyces strains with the potential to produce novel chemical matter as well as integrase-encoding phages that could potentially be used to manipulate these strains.

microbiology↗

bioRxiv2020

A novel drug-combination screen in zebrafish identifies epigenetic small molecule candidates for Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a severe neuromuscular disorder and is one of the most common muscular dystrophies. There are currently few effective therapies to treat the disease, although many small-molecule approaches are being pursued. Specific histone deacetylase inhibitors (HDACi) can ameliorate DMD phenotypes in mouse and zebrafish animal models and have also shown promise for DMD in clinical trials. However, beyond these HDACi, other classes of epigenetic small molecules have not been broadly and systematically studied for their benefits for DMD. Here, we performed a novel chemical screen of a library of epigenetic compounds using the zebrafish dmd model. We identified candidate pools of epigenetic compounds that improve skeletal muscle structure in dmd zebrafish. We then identified a specific combination of two drugs, oxamflatin and salermide, that significantly rescued dmd zebrafish skeletal muscle degeneration. Furthermore, we validated the effects of oxamflatin and salermide in an independent laboratory. Our results provide novel, effective methods for performing a combination small-molecule screen in zebrafish. Our results also add to the growing evidence that epigenetic small molecules may be promising candidates for treating DMD.

pharmacology and toxicology↗

bioRxiv2019

ARMC9 and TOGARAM1 define a Joubert syndrome-associated protein module that regulates axonemal post-translational modifications and cilium stability

Joubert syndrome (JBTS) is a recessive neurodevelopmental ciliopathy, characterized by a pathognomonic hindbrain malformation. All known JBTS-genes encode proteins involved in the structure or function of primary cilia, ubiquitous antenna-like organelles essential for cellular signal transduction. Here, we use the recently identified JBTS-associated protein ARMC9 in tandem-affinity purification and yeast two-hybrid screens to identify a novel ciliary module composed of ARMC9-TOGARAM1-CCDC66-CEP104- CSPP1. TOGARAM1-variants cause JBTS and disrupt its interaction with ARMC9. Using a combination of protein interaction analyses and characterization of patient-derived fibroblasts, CRISPR/Cas9-engineered zebrafish and hTERT-RPE1 cells, we demonstrate that dysfunction of ARMC9 or TOGARAM1 results in short cilia with decreased axonemal acetylation and glutamylation, but relatively intact transition zone function. Aberrant serum-induced ciliary resorption and cold-induced depolymerization in both ARMC9 and TOGARAM1 patient cells lines suggest a role for this new JBTS-associated protein complex in ciliary stability.

genetics↗

bioRxiv2018

Supragingival plaque microbiome ecology and functional potential in the context of health and disease

To address the question of how microbial diversity and function in the oral cavities of children relates to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. Caries phenotypes contained statistically significant enrichments in specific genome abundances and distinct community composition profiles including strain-level changes. Metabolic pathways that are statistically associated with caries include several sugar-associated phosphotransferase systems, antimicrobial resistance, and metal transport. Numerous closely-related previously-uncharacterized microbes had substantial variation in central metabolism, including the loss of biosynthetic pathways resulting in auxotrophy, changing the ecological role. We also describe the first complete Gracilibacteria genomes from the human microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology and our results provide the information needed for next generation diagnostic tools and therapeutics for caries.

microbiology↗

bioRxiv2017

The Object Space Task for mice and rats

Declarative memory encompasses representations of specific events as well as knowledge extracted by accumulation over multiple episodes. To investigate how these different sorts of memories are created, we developed a new behavioral task in rodents. The task consists of three distinct conditions (stable, overlapping, random). Rodents are exposed to multiple sample trials, in which they explore objects in specific spatial arrangements. In the stable condition, the locations are constant during all sample trials; in the test trial, one objects location is changed. In the random condition, object locations are presented in the sample phase without a specific spatial pattern. In the overlapping condition, one location is shared (overlapping) between all trials while the other location changes during sample trials. We show that in the overlapping condition, instead of only remembering the last sample trial, rodents form a cumulative memory of the sample trials.\n\nHere we could show that both mice and rats can accumulate information across multiple trials and express a long-term abstracted memory.

animal behavior and cognition↗

bioRxiv2017

Transcription Factors Orchestrate Dynamic Interplay Between Genome Topology And Gene Regulation During Cell Reprogramming

Chromosomal architecture is known to influence gene expression, yet its role in controlling cell fate remains poorly understood. Reprogramming of somatic cells into pluripotent stem cells by the transcription factors (TFs) Oct4, Sox2, Klf4 and Myc offers an opportunity to address this question but is severely limited by the low proportion of responding cells. We recently developed a highly efficient reprogramming protocol that synchronously converts somatic into pluripotent stem cells. Here, we employ this system to integrate time-resolved changes in genome topology with gene expression, TF binding and chromatin state dynamics. This revealed that TFs drive topological genome reorganization at multiple architectural levels, which often precedes changes in gene expression. Removal of locus-specific topological barriers can explain why pluripotency genes are activated sequentially, instead of simultaneously, during reprogramming. Taken together, our study implicates genome topology as an instructive force for implementing transcriptional programs and cell fate in mammals.

molecular biology↗