Biology subjects

Estrada, E.

Publications and source records attributed to Estrada, E..

5 recordsLinked to original sources

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

Network Bipartitioning In The Anti-Communicability Euclidean Space

We define the anti-communicability function for the nodes of a simple graph as the nondiagonal entries of exp (-A). We prove that it induces an embedding of the nodes into a Euclidean space. The anti-communicability angle is then defined as the angle spanned by the position vectors of the corresponding nodes in the anti-communicability Euclidean space. We prove analytically that in a given k-partite graph, the anti-communicability angle is larger than 90{degrees} for every pair of nodes in different partitions and smaller than 90{degrees} for those in the same partition. This angle is then used as a similarity metric to detect the "best" k-partitions in networks where certain level of edge frustration exists. We apply this method to detect the "best" k-partitions in 15 real-world networks, finding partitions with a very low level of "edge frustration". Most of these partitions correspond to bipartitions but tri- and pentapartite structures of real-world networks are also reported.

biophysics↗

bioRxiv2020

Analyzing the impact of SARS CoV-2 on the human proteome

The COVID-19 respiratory disease is caused by the novel coronavirus SARS-CoV-2, which uses the enzyme ACE2 to entry human cells. This disease is characterized by important damages at multi-organ level, partially due to the abundant expression of ACE2 in practically all human tissues. However, not every organ in which ACE2 is abundant is affected by SARS CoV-2, which suggests the existence of other multi-organ routes for transmitting the perturbations produced by the virus. We consider here diffusive processes through the protein-protein interaction (PPI) network of proteins targeted by SARS CoV-2 as such alternative route. We found a subdiffusive regime that allows the propagation of virus perturbations through the PPI network at a significant rate. By following the main subdiffusive routes across the PPI network we identify proteins mainly expressed in the heart, cerebral cortex, thymus, testis, lymph node, kidney, among others of the organs reported to be affected by COVID-19.

systems biology↗

bioRxiv2020

Communicability distance reveals hidden patterns of Alzheimer disease

The communicability distance between pairs of regions in human brain is used as a quantitative proxy for studying Alzheimer disease. Using this distance we obtain the shortest communicability path lengths between different regions of brain networks from Alzheimer diseased (AD) patients and healthy cohorts (HC). We show that the shortest communicability path length is significantly better than the shortest topological path length in distinguishing AD patients from HC. Based on this approach we identify 399 pairs of brain regions for which there are very significant changes in the shortest communicability path length after AD appears. We find that 42% of these regions interconnect both brain hemispheres, 28% connect regions inside the left hemisphere only and 20% affects vermis connection with brain hemispheres. These findings clearly agree with the disconnection syndrome hypothesis of Alzheimer disease. Finally, we show that in 76.9% damaged brain regions the shortest communicability path length drops in AD in relation to HC. This counterintuitive finding indicates that AD transforms the brain network into a more efficient system from the perspective of the transmission of the disease, because it drops the circulability of the disease factor around the brain regions in relation to its transmissibility to other regions.

neuroscience↗

bioRxiv2020

Topological Analysis of SARS CoV-2 Main Protease

There is an urgent necessity of effective medication against SARS CoV-2, which is producing the COVID-19 pandemic across the world. Its main protease (Mpro) represents an attractive pharmacological target due to its involvement in essential viral functions. The crystal structure of free Mpro shows a large structural resemblance with the main protease of SARS CoV (nowadays known as SARS CoV-1). Here we report that as average SARS CoV-2 Mpro is 1900% more sensitive than SARS CoV-1 Mpro in transmitting tiny structural changes across the whole protein through long-range interactions. The largest sensitivity of Mpro to structural perturbations is located exactly around the catalytic site Cys-145, and coincides with the binding site of strong inhibitors. These findings, based on a simplified representation of the protein as a residue network, may help in designing potent inhibitors of SARS CoV-2 Mpro. The main protease of the new coronavirus SARS CoV-2 represents one of the most important targets for the antiviral pharmacological actions againsts COVID-19. This enzyme is essential for the virus due to its proteolytic processing of polyproteins. Here we discover that the main protease of SARS CoV-2 is topologically very similar to that of the SARS CoV-1. This is not surprising taking into account that both proteases differ only in 12 amino acids. However, we remarkable found a topological property of SARS CoV-2 that has increased in more than 1900% repect to its SARS CoV-1 analogue. This property reflects the capacity of the new protease of transmitting perturbations across its domains using long-range interactions. Also remarkable is the fact that the amino acids displaying such increased sensitivity to perturbations are around the binding site of the new protease, and close to its catalytic site. We also show that this sensititivy to perturbations is related to the effects of powerful protease inhibitors. In fact, the strongest inhibitors of the SARS CoV-2 main protease are those that produce the least change of this capacity of transmitting perturbations across the protein. We think that these findings may help in the design of new potent anti-SARS CoV-2 inhibitors.

bioinformatics↗