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Tan, Justin

Publications and source records attributed to Tan, Justin.

7 records
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DOE OSTI2025

Precision string phenomenology

Calabi-Yau compactifications of the E 8 × E 8 heterotic string provide a promising route to recovering the four-dimensional particle physics described by the Standard Model. While the topology of the Calabi-Yau space determines the overall matter content in the low-energy effective field theory, further details of the compactification geometry are needed to calculate the normalized physical couplings and masses of elementary particles. In this work, we present numerical computations of physical Yukawa couplings in a number of heterotic models in the standard embedding and demonstrate the existence of natural hierarchies, a coveted feature in string model building. Published by the American Physical Society 2025

Berglund, Per (ORCID:0000000316754133)↗
DOE OSTI2024

Physical Yukawa couplings in heterotic string compactifications

One of the challenges of heterotic compactification on a CalabiYau threefold is to determine the physical (27) 3 Yukawa couplings of the resulting four-dimensional $\mathcal{N}$ = 1 theory. In general, the calculation necessitates knowledge of the Ricci-flat metric. However, in the standard embedding, which references the tangent bundle, we can compute normalized Yukawa couplings from the Weil-Petersson metric on the moduli space of complex structure deformations of the Calabi-Yau manifold. In various examples (the Fermat quintic, the intersection of two cubics in $\mathbb{P}$ 5 , and the TianYau manifold), we calculate the normalized Yukawa couplings for (2,1)-forms using the Weil-Petersson metric obtained from the Kodaira-Spencer map. In cases where $h^{1,1}$ = 1 , this is compared to a complementary calculation based on performing period integrals. A third expression for the normalized Yukawa couplings is obtained from a machine learned approximate Ricci-flat metric making use of explicit harmonic representatives. Finally, the excellent agreement between the different approaches opens the door to precision string phenomenology.

Butbaia, Giorgi↗
DOE OSTI2020

The Importance of Protein Phosphorylation for Signaling and Metabolism in Response to Diel Light Cycling and Nutrient Availability in a Marine Diatom

Diatoms are major contributors to global primary production and their populations in the modern oceans are affected by availability of iron, nitrogen, phosphate, silica, and other trace metals, vitamins, and infochemicals. However, little is known about the role of phosphorylation in diatoms and its role in regulation and signaling. We report a total of 2759 phosphorylation sites on 1502 proteins detected in Phaeodactylum tricornutum. Conditionally phosphorylated peptides were detected at low iron (n = 108), during the diel cycle (n = 149), and due to nitrogen availability (n = 137). Through a multi-omic comparison of transcript, protein, phosphorylation, and protein homology, we identify numerous proteins and key cellular processes that are likely under control of phospho-regulation. We show that phosphorylation regulates: (1) carbon retrenchment and reallocation during growth under low iron, (2) carbon flux towards lipid biosynthesis after the lights turn on, (3) coordination of transcription and translation over the diel cycle and (4) in response to nitrogen depletion. We also uncover phosphorylation sites for proteins that play major roles in diatom Fe sensing and utilization, including flavodoxin and phytotransferrin (ISIP2A), as well as identify phospho-regulated stress proteins and kinases. These findings provide much needed insight into the roles of protein phosphorylation in diel cycling and nutrient sensing in diatoms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Cellular responses to reactive oxygen species are predicted from molecular mechanisms

Catalysis using iron–sulfur clusters and transition metals can be traced back to the last universal common ancestor. The damage to metalloproteins caused by reactive oxygen species (ROS) can prevent cell growth and survival when unmanaged, thus eliciting an essential stress response that is universal and fundamental in biology. Here we develop a computable multiscale description of the ROS stress response in Escherichia coli , called OxidizeME. We use OxidizeME to explain four key responses to oxidative stress: 1) ROS-induced auxotrophy for branched-chain, aromatic, and sulfurous amino acids; 2) nutrient-dependent sensitivity of growth rate to ROS; 3) ROS-specific differential gene expression separate from global growth-associated differential expression; and 4) coordinated expression of iron–sulfur cluster (ISC) and sulfur assimilation (SUF) systems for iron–sulfur cluster biosynthesis. These results show that we can now develop fundamental and quantitative genotype–phenotype relationships for stress responses on a genome-wide basis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

Significance While the transcriptional regulatory network (TRN) of Escherichia coli has expanded considerably in recent years through new chromatin immunoprecipitation (ChIP) data, an open question remains: Does the global TRN, reconstructed by combining ChIP data for individual transcriptions factors, consistently explain observed differential gene expression? We have reconstructed a high-confidence TRN, determined its consistency with transcriptomics and predictive capabilities across multiple conditions, extracted 10 functional regulatory modules, and characterized this network at the sequence and structural levels. Our multiomics algorithmic pipeline is expected to facilitate rigorous validation and prioritization of experiments to elucidate TRNs in other bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Multi-omic data integration enables discovery of hidden biological regularities

Rapid growth in size and complexity of biological data sets has led to the ‘Big Data to Knowledge’ challenge. We develop advanced data integration methods for multi-level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome-scale models, based on genomic and bibliomic data, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can be formally represented in a computable format allowing for coherent interpretation and prediction of fitness and selection that underlies cellular physiology.

59 BASIC BIOLOGICAL SCIENCES↗