Biology subjects

Hernandez-Garcia, A.

Publications and source records attributed to Hernandez-Garcia, A..

3 recordsLinked to original sources

bioRxiv2022

A nucleation-and-growth model for the packaging of genome in linear virus-like particles: impact of multiple packaging signals

Inspired by recent experiments on the spontaneous assembly of virus-like particles from a solution containing a synthetic coat protein and double-stranded DNA, (1) we put forward a kinetic model that has as main ingredients a stochastic nucleation and a deterministic growth process. The efficiency and rate of the packaging of the DNA turn out to strongly increase by introducing proteins onto the DNA template that are modified using CRISPR-Cas techniques to bind specifically at predesignated locations, mimicking assembly signals in viruses. Our model shows that treating these proteins as nucleation-inducing diffusion barriers is sufficient to explain experimentally observed increase in encapsulation efficiency, but only if the nucleation rate is sufficiently high. We find an optimum in the encapsulation kinetics for conditions where the number of packaging signals is equal to the number of nucleation events that can occur during time required to fully encapsulate the DNA template, presuming that the nucleation events can only take place adjacent to a packaging signal. Our theory is in satisfactory agreement with the available experimental data. SIGNIFICANCEThe rate and efficiency of the encapsulation of double-stranded DNA by synthetic coat proteins was recently found to be strongly enhanced by the presence of specifically positioned protein molecules on the DNA that mimic so-called packaging signals. We present a kinetic theory based on the initial stochastic nucleation and subsequent deterministic elongation of the protein coat with the aim to explain these findings. We find that equidistantly placed nucleation sites that also act as diffusion barriers on the DNA have profound and non-trivial effects, and they can either slow down or speed up encapsulation, depending on how fast nucleation is on the time scale of the elongation process. Our findings may contribute to the rational design of linear virus-like particles.

biophysics↗

bioRxiv2021

Benchmark of data processing methods and machine learning models for gut microbiome-based diagnosis of inflammatory bowel disease

BackgroundInflammatory bowel disease (IBD) patients wait months and undergo numerous invasive procedures between the initial appearance of symptoms and receiving a diagnosis. In order to reduce time until diagnosis and improve patient wellbeing, machine learning algorithms capable of diagnosing IBD from the gut microbiomes composition are currently being explored. To date, these models have had limited clinical application due to decreased performance when applied to a new cohort of patient samples. Various methods have been developed to analyze microbiome data which may improve the generalizability of machine learning IBD diagnostic tests. With an abundance of methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (from data processing to training a machine learning model) for microbiome-based IBD diagnostic tools. ResultsWe collected fifteen 16S rRNA microbiome datasets (7707 samples) from North America to benchmark combinations of gut microbiome features, data normalization methods, batch effect reduction methods, and machine learning models. Pipeline generalizability to new cohorts of patients was evaluated with four binary classification metrics following leave-one dataset-out cross validation, where all samples from one study were left out of the training set and tested upon. We demonstrate that taxonomic features obtained from QIIME2 lead to better classification of samples from IBD patients than inferred functional features obtained from PICRUSt2. In addition, machine learning models that identify non-linear decision boundaries between labels are more generalizable than those that are linearly constrained. Prior to training a non-linear machine learning model on taxonomic features, it is important to apply a compositional normalization method and remove batch effects with the naive zero-centering method. Lastly, we illustrate the importance of generating a curated training dataset to ensure similar performance across patient demographics. ConclusionsThese findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.

microbiology↗

bioRxiv2020

SOX7 deficiency causes ventricular sepal defects through its effects on endocardial-to-mesenchymal transition and the expression of Wnt4 and Bmp2

SOX7 is located in a region on chromosome 8p23.1 that is recurrently deleted in individuals with septal defects. Sox7-/- embryos die of heart failure around E11.5 due to defects in vascular remodeling. These embryos have hypocellular endocardial cushions with severely reduced numbers of mesenchymal cells. We also observed a ventricular septal defect in a rare Sox7flox/-;Tie2-Cre embryo that escaped early lethality. This led us to hypothesize that SOX7 plays a critical developmental role in the endocardium of the atrioventricular (AV) canal. We subsequently used AV explant studies to show that SOX7 deficiency leads to a severe reduction in endocardial-to-mesenchymal transition (EndMT). Since SOX7 is a transcription factor, we hypothesized that it functions in the endocardium by regulating the expression of EndMT-related genes. To identify these genes in an unbiased manner, we performed RNA-seq on pooled E9.5 hearts tubes harvested from Sox7-/- embryos and their wild-type littermates. We found that Wnt4 transcript levels were severely reduced, which we confirmed by RNA in situ hybridization. Previous studies have shown that WNT4 is expressed in the endocardium and promotes EndMT by acting in a paracrine manner to increase the expression of BMP2 in the myocardium. Consistent with these findings, we found that Bmp2 transcript levels were diminished in Sox7-/- embryonic hearts. We conclude that SOX7 promotes EndMT in the developing AV canal by modulating the expression of Wnt4 and Bmp2. These data also provide additional evidence that haploinsufficiency of SOX7 contributes to the congenital heart defects seen in individuals with recurrent 8p23.1 microdeletions. SUMMARY STATEMENTIn the developing atrioventricular canal, SOX7 promotes endocardial-to-mesenchymal transition (EndMT) by positively regulating Wnt4 and Bmp2 expression. SOX7 deficiency leads to the development of hypocellular endothelial cushions and ventricular septal defects.

developmental biology↗