Biology subjects

Bui, A.

Publications and source records attributed to Bui, A..

7 recordsLinked to original sources

bioRxiv2024

Maturing giant kelp develop depth-specific microbiomes

Giant kelp (Macrocystis pyrifera) is a photosynthetic macroalga that produces dissolved organic carbon (DOC), essential for marine bacteria and food webs. The bacterial communities residing on giant kelp blades consume and compete for complex carbohydrates, contributing to the microbiome community structure. In this study, we investigate how the microbiome changes in response to the age and depth of giant kelp blades and assess how these changes relate to differences in the hosts photophysiology. We find that the microbial community increases in richness and evenness as kelp blades age. While the microbiomes of juvenile blades are stochastic, communities on mature blades coalesce into less variable, depth-specific community types. Differentially abundant genera in mature microbiomes include members of Bacteroidia and Gammaproteobacteria, known for carbohydrate degradation, and Planctomycetes, which often produce protective secondary metabolites. These shifts in microbiome communities are associated with increased maximum quantum yield of photosystem II of mature blades; therefore, they may be linked to enhanced DOC exudation. By shedding light on these dynamics, our study contributes to a better understanding of the complex interplay between macroalgae, their respective microbiomes, and the surrounding marine environment.

microbiology↗

bioRxiv2024

Solvation Free Energy in Governing Equations for DNA Hybridization, Protein-Ligand Binding, and Protein Folding

This work examines the thermodynamics of model biomolecular interactions using a governing equation that accounts for the participation of bulk water in the balanced reaction. In the first example, the binding affinities of two model DNA duplexes, one of nine and one of ten base pairs in length, are measured and characterized by isothermal titration calorimetry as a function of concentration. The results indicate that the change in solvation free energy that accompanies duplex formation ({Delta}GS) is large and unfavorable. When normalized to the number of base pairs, the duplex with the larger number of G:C pairings yields the largest change in solvation free energy, {Delta}GS = +460 kcal/mol/base pair at 25 {degrees}C. A modelling study demonstrates how the solvation free energy alters the output of a typical titration experiment. Hybridization measurements are completed at four different temperatures, however a vant Hoff analysis of the data is complicated by the varying degree of intramolecular base stacking within each DNA strand as a function of temperature. The same thermodynamic framework is applied to a model protein- ligand interaction, the binding of ribonuclease A with the nucleotide inhibitor 3-UMP, and to a conformational equilibrium, the change in tertiary structure of -lactalbumin in molar guanidinium chloride solutions. The ribonuclease study yields a value of {Delta}GS = +160 kcal/mol, whereas the folding equilibrium yields {Delta}GS {approx} 0, an apparent characteristic of hydrophobic interactions. These examples complement previous applications of the governing equation to the interaction of smaller molecules and demonstrate the importance of solvation energy in biothermodynamics.

biochemistry↗

bioRxiv2023

Finding the LMA needle in the wheat proteome haystack.

Late maturity alpha-amylase (LMA) is a wheat genetic defect causing the synthesis of high isoelectric point (pI) alpha-amylase in the aleurone as a result of a temperature shock during mid-grain development or prolonged cold throughout grain development leading to an unacceptable low falling numbers (FN) at harvest or during storage. High pI alpha-amylase is normally not synthesized until after maturity in seeds when they may sprout in response to rain or germinate following sowing the next seasons crop. Whilst the physiology is well understood, the biochemical mechanisms involved in grain LMA response remain unclear. We have employed high-throughput proteomics to analyse thousands of wheat flours displaying a range of LMA values. We have applied an array of statistical analyses to select LMA-responsive biomarkers and we have mined them using a suite of tools applicable to wheat proteins. To our knowledge, this is not only the first proteomics study tackling the wheat LMA issue, but also the largest plant-based proteomics study published to date. Logistics, technicalities, requirements, and bottlenecks of such an ambitious large-scale high-throughput proteomics experiment along with the challenges associated with big data analyses are discussed. We observed that stored LMA-affected grains activated their primary metabolisms such as glycolysis and gluconeogenesis, TCA cycle, along with DNA- and RNA binding mechanisms, as well as protein translation. This logically transitioned to protein folding activities driven by chaperones and protein disulfide isomerase, as wellas protein assembly via dimerisation and complexing. The secondary metabolism was also mobilised with the up-regulation of phytohormones, chemical and defense responses. LMA further invoked cellular structures among which ribosomes, microtubules, and chromatin. Finally, and unsurprisingly, LMA expression greatly impacted grain starch and other carbohydrates with the up-regulation of alpha-gliadins and starch metabolism, whereas LMW glutenin, stachyose, sucrose, UDP-galactose and UDP-glucose were down-regulated. This work demonstrates that proteomics deserves to be part of the wheat LMA molecular toolkit and should be adopted by LMA scientists and breeders in the future.

plant biology↗

bioRxiv2020

Liver Electrical Impedance Tomography for Early Identification of Fatty Infiltrate in Obesity

Non-alcoholic fatty liver disease (NAFLD) is endemic in developed countries and is one of the most common causes of cardiometabolic diseases in overweight/obese individuals. While liver biopsy or magnetic resonance imaging (MRI) is the current gold standard to diagnose NAFLD, the former is prone to bleeding and the latter is costly. We hereby demonstrated liver electrical impedance tomography (EIT) as a non-invasive and portable detection method for fatty infiltrate. We enrolled 19 subjects (15 females and 4 males; 27 to 74 years old) to undergo liver MRI scans, followed by EIT measurements via a multi-electrode array. The liver MRI scans provided subject-specific a priori knowledge of the liver boundary conditions for segmentation and EIT reconstruction, and the 3-D multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) as a recognized reference standard for validating liver fat infiltrate. Using acquired voltage data and the reconstruction algorithm for the EIT imaging, we computed the absolute conductivity distribution of abdomen in 2-D. Correlation analyses were performed to compare the individual EIT conductivity vs. MRI PDFF with their demographics in terms of gender, BMI (kg{middle dot}m-2), age (years), waist circumference (cm), height (cm), and weight (kg). Our results indicate that EIT conductivity (S{middle dot}m-1) and liver MRI for PDFF were not correlated with the demographics, whereas the decrease in EIT conductivity was correlated with the increase in MRI PDFF (R = - 0.69, p= 0.003). Thus, EIT conductivity holds promise for developing a non-invasive, portable, and quantitative method to detect fatty liver disease.

bioengineering↗

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↗

bioRxiv2017

Uncovering Medical Insights from Vast Amounts of Biomedical Data in Clinical Case Reports

Clinical case reports (CCRs) have a time-honored tradition in serving as an important means of sharing clinical experiences on patients presenting with atypical disease phenotypes or receiving new therapies. However, the huge amount of accumulated case reports are isolated, unstructured, and heterogeneous clinical data, posing a great challenge to clinicians and researchers in mining relevant information through existing indexing tools. In this investigation, in order to render CCRs more findable, accessible, interoperable, and reusable (FAIR) by the biomedical community, we created a resource platform, including the construction of a test dataset consisting of 1000 CCRs spanning 14 disease phenotypes, a standardized metadata template and metrics, and a set of computational tools to automatically retrieve relevant medical information and to analyze all published PubMed clinical case reports with respect to trends in publication journals, citations impact, MeSH Terms, drug use, distributions of patient demographics, and relationships with other case reports and databases. Our standardized metadata template and CCR test dataset may be valuable resources to advance medical science and improve patient care for researchers who are using machine learning approaches with a high-quality dataset to train and validate their algorithms. In the future, our analytical tools may be applied towards other large clinical data sources as well.

bioinformatics↗

bioRxiv2017

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗