Biology subjects

Tran, L.

Publications and source records attributed to Tran, L..

40 records · Page 3Linked to original sources

bioRxiv2020

Estimating invasion dynamics with geopolitical-unit level records: performance and similarity of common methods using both simulated data and a real case

Estimating invasion dynamic is important to the management of invasive species, and geopolitical-unit level data are usually the most abundant and available records of invasive species. Here, for the first time we evaluated performances and similarities of eight common methods to estimate spread pattern and spread dynamic of invasive species with geopolitical-unit level data, and assessed impacts of variations in geopolitical-units on each method using simulated spread data. We also formulated a concave hull boundary displacement method (i.e., CEB) and an area-based regression method (i.e., AER) for estimating spread with geopolitical-unit data. Three regions with different sized counties in the United States (U.S.) were selected to conduct simulations and three spread scenarios were simulated. R2 and root mean square error were used to evaluate the abilities of all methods to estimate spread. Correlation coefficients were used to assess the similarity pattern of all methods. Finally, kudzu bug Megacopta cribraria, an invasive insect in the U.S., was used as a case study to test the generality of some results concluded from the simulated research. We found the CEB and two regression methods consistently estimated the right expansion patterns. Two boundary displacement and two area-based regression methods estimated highly correlated spread and were the best four methods, among which CEB had the best estimation. Distance-based regression methods are sensitive to irregularity and stochasticity in spread, and the minimum spread distance method had low ability to estimate spread. The case study showed consistent results with the simulated research. Both regression and boundary displacement methods can estimate spread patterns, overall rate, and spread dynamics of invasive species. Boundary displacement methods best estimate spread rates and dynamics; however, for spread without clear infestation outlines, area-based regression methods can be good alternatives.

ecology↗

bioRxiv2019

TRIM21 and PHLDA3 Negatively Regulate the Cross-Talk between the PI3K/AKT Pathway and PPP Metabolism

PI3K/AKT signaling is known to regulate cancer metabolism but whether metabolic pathway feedbacks and regulates the PI3K/AKT pathway is unclear. Here, we demonstrate the important reciprocal cross-talks between the PI3K/AKT signal and PPP branching metabolic pathways. PI3K/AKT activation stabilizes G6PD, the rate-limiting enzyme of PPP, by inhibiting a newly identified E3 ligase TIRM21, and promotes PPP. PPP metabolites, in turn, reinforce AKT activation and further promote cancer metabolic reprogramming by blocking the expression of an AKT inhibitor PHLDA3. Knockout TRIM21 or PHLDA3 promotes the cross-talks and cell proliferation. Importantly, PTEN null human cancer cells and in vivo murine models are sensitive to anti-PPP treatments, suggesting the importance of PPP in maintaining AKT activation even in the presence of a constitutively activated PI3K pathway. Our study suggests that blockade of these reciprocal cross-talks may have a therapeutic benefit for cancers with PTEN loss or PI3K/AKT activation.

cancer biology↗

bioRxiv2019

CpG-creating Mutations are Costly in Many Human Viruses

Mutations can occur throughout the virus genome and may be beneficial or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly that similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.

evolutionary biology↗

bioRxiv2018

ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes

MotivationProtein-protein interactions (PPIs) play a key role in many cellular processes. Most annotations of PPIs mix experimental and computational data. The mix optimizes coverage, but obfuscates the annotation origin. Some resources excel at focusing on reliable experimental data. Here, we focused on new pairs of interacting proteins for several model organisms based solely on sequence-based prediction methods.\n\nResultsWe extracted reliable experimental data about which proteins interact (binary) for eight diverse model organisms from public databases, namely from Escherichia coli, Schizosaccharomyces pombe, Plasmodium falciparum, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus, Arabidopsis thaliana, and for the previously used Homo sapiens and Saccharomyces cerevisiae. Those data were the base to develop a PPI prediction method for each model organism. The method used evolutionary information through a profile-kernel Support Vector Machine (SVM). With the resulting eight models, we predicted all possible protein pairs in each organism and made the top predictions available through a web application. Almost all of the PPIs made available were predicted between proteins that have not been observed in any interaction, in particular for less well-studied organisms. Thus, our work complements existing resources and is particularly helpful for designing experiments because of its uniqueness. Experimental annotations and computational predictions are strongly influenced by the fact that some proteins have many partners and others few. To optimize machine learning, recent methods explicitly ignored such a network-structure and rely either on domain knowledge or sequence-only methods. Our approach is independent of domain-knowledge and leverages evolutionary information. The database interface representing our results is accessible from https://rostlab.org/services/ppipair/. The data can also be downloaded from https://figshare.com/collections/ProfPPI-DB/4141784.

bioinformatics↗