Browsing by Author "Chen, Jing"

Now showing 1 - 20 of 27
  • Thumbnail Image
    Analysis and design of multiple-output forward converter with weighted voltage control
    Chen, Jing (Virginia Tech, 1994-02-09)
    This work presents the modeling and analyses of multiple-output forward converters with weighted voltage control. Based upon the analyses, the systematic design methodologies and design tools are provided. A power stage de model including all the major parasitics, which are detrimental to the output voltages, is derived. A nonlinear programming based design tool is developed to search for the weighting factors. Five methods of stacking secondaries to improve cross-regulation are presented, and the improvement of cross-regulation is quantified. A small-signal model of the multiple-output converters with coupled output filter inductors and weighted voltage control is established. The small-signal characteristics are studied, and the model shows that the system behavior is very sensitive to the coupling coefficient, which has been reported, but never been quantified. The pole-zero interlaced condition is derived. A current-mode control small-signal model is also presented, which can predict all the observed phenomena of current-mode control. Compensator design is discussed for different types of power stage transfer functions for both voltage-mode and current-mode control.
  • Thumbnail Image
    Asymmetric clustering of centrosomes defines the early evolution of tetraploid cells
    Baudoin, Nicolaas C.; Nicholson, Joshua M.; Soto, Kimberly; Martin, Olga; Chen, Jing; Cimini, Daniela (eLife Sciences Publications, 2020-04-29)
    Tetraploidy has long been of interest to both cell and cancer biologists, partly because of its documented role in tumorigenesis. A common model proposes that the extra centrosomes that are typically acquired during tetraploidization are responsible for driving tumorigenesis. However, tetraploid cells evolved in culture have been shown to lack extra centrosomes. This observation raises questions about how tetraploid cells evolve and more specifically about the mechanisms(s) underlying centrosome loss. Here, using a combination of fixed cell analysis, live cell imaging, and mathematical modeling, we show that populations of newly formed tetraploid cells rapidly evolve in vitro to retain a near-tetraploid chromosome number while losing the extra centrosomes gained at the time of tetraploidization. This appears to happen through a process of natural selection in which tetraploid cells that inherit a single centrosome during a bipolar division with asymmetric centrosome clustering are favored for long-term survival.
  • Thumbnail Image
    Bacteria - Hydrogel Interactions: Mechanistic Insights via Microelastography and Deep Learning
    Karmarkar, Bhas Niteen (Virginia Tech, 2024-01-05)
    Bacteria-based cancer therapy (BBCT) holds immense promise in addressing the limitations in treatment of solid tumors. Bacterial strains used for BBCT are engineered to express therapeutics, facilitate precise navigation within the tumor microenvironment by enhancing bacteria's motility, chemotaxis (movement toward or away from specific chemicals), or other mechanisms that aid in reaching and infiltrating the tumor tissue effectively, and complementing traditional chemotherapy and immunotherapies while minimizing side effects. Bacterial motility not only influences the ability of bacteria to navigate within the tumor but also plays a pivotal role in optimizing drug delivery, treatment efficacy, and minimizing potential obstacles associated with the complex microenvironment of human tissues. However, the current understanding of bacterial motility remains limited. In this thesis, we use a reductionist approach and study bacteria motile behavior within human tissue phantoms (collagen and agar) and the bacteria-hydrogel interactions. Apart from motility, it is important to analyze the mechanical properties of the hydrogels the bacteria interact with as they play a vital role in overall behavior and physics of bacteria movement. To that extent, there exists a gap in our understanding of the viscoelastic properties of hydrogels. Lastly, systematic and comprehensive investigation of bacteria behavior in hydrogels requires tracking of thousands of individual cells. Thus, there is an unmet need to develop new automated techniques to reduce the labor-intensive manual tracking of bacteria in low-contrast hydrogel environments, with feature sizes comparable to that of bacteria. To address these gaps, this thesis proposes a trident approach towards mechanistic understanding of bacteria motility in time-invariant agar and temporally evolving collagen hydrogels to bridge critical gaps in understanding bacterial motile behavior in these media, non-destructive microelastography-based mechanical characterization of hydrogels with less than 4.7% error compared with rheology, and the development of deep learning-enabled automated bacteria tracking tools with 77% precision.
  • Thumbnail Image
    Biophysics at the coffee shop: lessons learned working with George Oster
    Igoshin, Oleg A.; Chen, Jing; Xing, Jianhua; Liu, Jian; Elston, Timothy C.; Grabe, Michael; Kim, Kenneth S.; Nirody, Jasmine A.; Rangamani, Padmini; Sun, Sean X.; Wang, Hongyun; Wolgemuth, Charles (American Society for Cell Biology, 2019-07-22)
    Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
  • Thumbnail Image
    The Cell Membrane Proteome of the SKBR3/HER2+ Cells and Implications for Cancer Targeted Therapies
    Karcini, Arba (Virginia Tech, 2023-06-02)
    Breast cancer is the second most common type of cancer among women in the US and the second leading cause of cancer death. HER2+ breast cancers represent ~20% of all cancer types, are highly invasive, and can be treated by using targeted therapies against the HER2 receptor. However, these therapies are challenged by the development of drug resistance, often induced by the presence of mutations in the cell-membrane proteins and receptors and/or by alternative signaling pathways that cross-talk with- or transactivate HER2+ triggered signaling. This study was aimed at investigating the cell membrane proteome of SKBR3 cells, representative of HER2+ breast cancers, and the signaling landscape and cellular responses elicited by the cell membrane receptors when the cells are stimulated with either growth factors or therapeutic drugs. It was hypothesized that the identification of a broad range of cell membrane proteins with roles in cancer progression and signaling crosstalk will lead to a more comprehensive understanding of the biological processes that sustain the proliferation of cancer cells, and will guide the selection of more efficient drug targets. The project was conceptualized in three stages: (1) profiling the cell membrane proteins of SKBR3 cells, (2) determining the functional role of the detected cell membrane proteins in the context of cancer hallmarks and exploring their mutational profile, and (3) analyzing the cellular events that occur in response to treatment with a single therapeutic agent or a combination of drugs. Mass spectrometry technologies were used for performing proteomic and phosphoproteomic profiling of SKBR3 cells, detecting changes in the abundance of the detected proteins, and identifying the presence of mutations in the cell membrane proteins. Orthogonal enrichment methods were developed for profiling the low-abundance cell membrane proteins, for generating a rich landscape of cell membrane receptors with various functional roles and relevance to the cancer hallmarks, and for enabling the detection of potentially new drivers of aberrant proliferation. The analysis of serum-starved, stimulated (with growth factors), or inhibited (with kinase inhibitors) cells revealed alternative protein players and crosstalk activities that determine the fate of cells, and that may fuel the development of resistance to treatment with drugs. The proteome profiles that were generated in this project expand the opportunities for targeting cancer-relevant processes beyond proliferation, which is commonly attempted, broadening the landscape to also include apoptosis, invasion, and metastasis. Altogether, the findings that emerged from this work will lay the ground for future studies that aim at developing more complex and effective targeted cancer treatment approaches.
  • Thumbnail Image
    Combinations of Small RNA, RNA, and Degradome Sequencing Uncovers the Expression Pattern of microRNA–mRNA Pairs Adapting to Drought Stress in Leaf and Root of Dactylis glomerata L.
    Ji, Yang; Chen, Peilin; Chen, Jing; Pennerman, Kayla K.; Liang, Xiaoyu; Yan, Haidong; Zhou, Sifan; Feng, Guangyan; Wang, Chengran; Yin, Guohua; Zhang, Xinquan; Hu, Yuanbin; Huang, Linkai (MDPI, 2018-10-11)
    Drought stress is a global problem, and the lack of water is a key factor that leads to agricultural shortages. MicroRNAs play a crucial role in the plant drought stress response; however, the microRNAs and their targets involved in drought response have not been well elucidated. In the present study, we used Illumina platform (https://www.illumina.com/) and combined data from miRNA, RNA, and degradome sequencing to explore the drought- and organ-specific miRNAs in orchardgrass (Dactylis glomerata L.) leaf and root. We aimed to find potential miRNA–mRNA regulation patterns responding to drought conditions. In total, 519 (486 conserved and 33 novel) miRNAs were identified, of which, 41 miRNAs had significant differential expression among the comparisons (p < 0.05). We also identified 55,366 unigenes by RNA-Seq, where 12,535 unigenes were differently expressed. Finally, our degradome analysis revealed that 5950 transcripts were targeted by 487 miRNAs. A correlation analysis identified that miRNA ata-miR164c-3p and its target heat shock protein family A (HSP70) member 5 gene comp59407_c0 (BIPE3) may be essential in organ-specific plant drought stress response and/or adaptation in orchardgrass. Additionally, Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses found that “antigen processing and presentation” was the most enriched downregulated pathway in adaptation to drought conditions. Taken together, we explored the genes and miRNAs that may be involved in drought adaptation of orchardgrass and identified how they may be regulated. These results serve as a valuable genetic resource for future studies focusing on how plants adapted to drought conditions.
  • Thumbnail Image
    Comparative transcriptome study of switchgrass (Panicum virgatum L.) homologous autopolyploid and its parental amphidiploid responding to consistent drought stress
    Chen, Peilin; Chen, Jing; Sun, Min; Yan, Haidong; Feng, Guangyan; Wu, Bingchao; Zhang, Xinquan; Wang, Xiaoshan; Huang, Linkai (2020-10-15)
    Background Newly formed polyploids may experience short-term adaptative changes in their genome that may enhance the resistance of plants to stress. Considering the increasingly serious effects of drought on biofuel plants, whole genome duplication (WGD) may be an efficient way to proceed with drought resistant breeding. However, the molecular mechanism of drought response before/after WGD remains largely unclear. Results We found that autoploid switchgrass (Panicum virgatum L.) 8X Alamo had higher drought tolerance than its parent amphidiploid 4X Alamo using physiological tests. RNA and microRNA sequencing at different time points during drought were then conducted on 8X Alamo and 4X Alamo switchgrass. The specific differentially expressed transcripts (DETs) that related to drought stress (DS) in 8X Alamo were enriched in ribonucleoside and ribonucleotide binding, while the drought-related DETs in 4X Alamo were enriched in structural molecule activity. Ploidy-related DETs were primarily associated with signal transduction mechanisms. Weighted gene co-expression network analysis (WGCNA) detected three significant DS-related modules, and their DETs were primarily enriched in biosynthesis process and photosynthesis. A total of 26 differentially expressed microRNAs (DEmiRs) were detected, and among them, sbi-microRNA 399b was only expressed in 8X Alamo. The targets of microRNAs that were responded to polyploidization and drought stress all contained cytochrome P450 and superoxide dismutase genes. Conclusions This study explored the drought response of 8X and 4X Alamo switchgrass on both physiological and transcriptional levels, and provided experimental and sequencing data basis for a short-term adaptability study and drought-resistant biofuel plant breeding.
  • Thumbnail Image
    Critical role of deadenylation in regulating poly(A) rhythms and circadian gene expression
    Yao, Xiangyu; Kojima, Shihoko; Chen, Jing (2020-04)
    The mammalian circadian clock is deeply rooted in rhythmic regulation of gene expression. Rhythmic transcriptional control mediated by the circadian transcription factors is thought to be the main driver of mammalian circadian gene expression. However, mounting evidence has demonstrated the importance of rhythmic post-transcriptional controls, and it remains unclear how the transcriptional and post-transcriptional mechanisms collectively control rhythmic gene expression. In mouse liver, hundreds of genes were found to exhibit rhythmicity in poly(A) tail length, and the poly(A) rhythms are strongly correlated with the protein expression rhythms. To understand the role of rhythmic poly(A) regulation in circadian gene expression, we constructed a parsimonious model that depicts rhythmic control imposed upon basic mRNA expression and poly(A) regulation processes, including transcription, deadenylation, polyadenylation, and degradation. The model results reveal the rhythmicity in deadenylation as the strongest contributor to the rhythmicity in poly(A) tail length and the rhythmicity in the abundance of the mRNA subpopulation with long poly(A) tails (a rough proxy for mRNA translatability). In line with this finding, the model further shows that the experimentally observed distinct peak phases in the expression of deadenylases, regardless of other rhythmic controls, can robustly cluster the rhythmic mRNAs by their peak phases in poly(A) tail length and abundance of the long-tailed subpopulation. This provides a potential mechanism to synchronize the phases of target gene expression regulated by the same deadenylases. Our findings highlight the critical role of rhythmic deadenylation in regulating poly(A) rhythms and circadian gene expression. Author summary The biological circadian clock aligns bodily functions to the day-and-night cycle and is important for maintaining health. The rhythms in various biological processes ultimately stem from rhythmic gene expression in each single cell. Because several proteins in the mammalian core clock machinery are transcription factors, studies of mammalian circadian gene expression have focused on rhythmic transcriptional control. However, many recent studies have suggested the importance of rhythmic post-transcriptional controls. Here we use mathematical modeling to investigate how transcriptional and post-transcriptional rhythms jointly control rhythmic gene expression. We particularly focus on rhythmic post-transcriptional regulation of the mRNA poly(A) tail, a nearly universal feature of mRNAs which controls mRNA stability and translation. Our model reveals that the rhythmicities in poly(A) tail length and mRNA translatability are most strongly affected by the rhythmicity in deadenylation, the process that shortens the poly(A) tail. Particularly, the phases of poly(A) tail length and mRNA translatability are dominated by the phase of deadenylation. In light of our findings, rhythmic control of deadenylation deserves greater future attention in the field of circadian gene expression.
  • Thumbnail Image
    Differential Expression Analysis of Type II Toxin-Antitoxin Genes of Pseudomonas aeruginosa PAO1 under Different Environmental Conditions
    Haque, Anamul (Virginia Tech, 2018-07-02)
    Bacterial persistence is considered as one of the primary reason for antibiotic tolerance besides genetically acquired antibiotic resistance. Persisters are the subpopulation of a clonal bacterial population, which can survive environmental extremes and become invulnerable to stresses due to limited metabolic activities and physiological functions. Cognate toxin and antitoxin (TA) pairs, which are transcribed simultaneously from the same or different operons within the bacterial chromosomes or plasmids, play an important role for bacterial survival during stressful growth environments. Pseudomonas aeruginosa PAO1 is one of the most versatile microorganisms in the environment. Despite its ubiquitous presence, no studies have shown the differential expression pattern of its toxin-antitoxins, and persistence related genes. The purpose of the following study is to analyze differential expression of P. aeruginosa PAO1 type II toxin-antitoxins and persistence related genes under different growth conditions and to show how their stoichiometric ratio changes during different growth conditions. Differential expression analysis indicated that the toxins and antitoxin pairs behave differently under different growth conditions. In addition, the genes related to persistence presented relatively consistent differential expression pattern under different growth environment.
  • Thumbnail Image
    Evaluating the role of the fission yeast cyclin B Cdc13 in cell size homeostasis
    Rogers, Jessie Michaela (Virginia Tech, 2021-06-15)
    Most cellular proteins retain a stable concentration as cells grow and divide, but there are exceptions. Some cell cycle regulators change in concentration with cell size. In fission yeast, Cdc13 (cyclin B), an important activator of the core cell cycle kinase Cdc2 (CDK1), increases in concentration as cells grow. It has been proposed that the concentration of such cell cycle regulators serves as a proxy for cell size and makes cell cycle progression dependent on cell size, thereby contributing to cell size homeostasis. The underlying mechanisms for the size-dependent scaling of these cell cycle regulators are poorly understood. Here, I show that Cdc13 protein concentration, but not mRNA concentration, increases with cell size. Furthermore, only the nuclear, but not the cytoplasmic, fraction of Cdc13 increases in concentration as cell size increases. Computational modeling along with half-life measurements suggests that stabilization of Cdc13 in the nucleus plays an important role in establishing this pattern. Taken together, my results suggest that Cdc13 scales with time, and therefore only indirectly—not directly—with cell size. This leaves open the possibility that Cdc13 contributes to cell size homeostasis, but in a different way than originally proposed.
  • Thumbnail Image
    A fine balance among key biophysical factors is required for recovery of bipolar mitotic spindle from monopolar and multipolar abnormalities
    Li, Xiaochu; Bloomfield, Mathew; Bridgeland, Alexandra; Cimini, Daniela; Chen, Jing (American Society for Cell Biology, 2023-06-21)
    During mitosis, equal partitioning of chromosomes into two daughter cells requires assembly of a bipolar mitotic spindle. Because the spindle poles are each organized by a centrosome in animal cells, centrosome defects can lead to monopolar or multipolar spindles. However, the cell can effectively recover the bipolar spindle by separating the centrosomes in monopolar spindles and clustering them in multipolar spindles. To interrogate how a cell can separate and cluster centrosomes as needed to form a bipolar spindle, we developed a biophysical model, based on experimental data, which uses effective potential energies to describe key mechanical forces driving centrosome movements during spindle assembly. Our model identified general biophysical factors crucial for robust bipolarization of spindles that start as monopolar or multipolar. These factors include appropriate force fluctuation between centrosomes, balance between repulsive and attractive forces between centrosomes, exclusion of the centrosomes from the cell center, proper cell size and geometry, and a limited centrosome number. Consistently, we found experimentally that bipolar centrosome clustering is promoted as mitotic cell aspect ratio and volume decrease in tetraploid cancer cells. Our model provides mechanistic explanations for many more experimental phenomena and a useful theoretical framework for future studies of spindle assembly.
  • Thumbnail Image
    Flagellar Motor Transformed: Biophysical Perspectives of the Myxococcus xanthus Gliding Mechanism
    Chen, Jing; Nan, Beiyan (Frontiers, 2022-05-06)
    Many bacteria move on solid surfaces using gliding motility, without involvement of flagella or pili. Gliding of Myxococcus xanthus is powered by a proton channel homologous to the stators in the bacterial flagellar motor. Instead of being fixed in place and driving the rotation of a circular protein track like the flagellar basal body, the gliding machinery of M. xanthus travels the length of the cell along helical trajectories, while mechanically engaging with the substrate. Such movement entails a different molecular mechanism to generate propulsion on the cell. In this perspective, we will discuss the similarities and differences between the M. xanthus gliding machinery and bacterial flagellar motor, and use biophysical principles to generate hypotheses about the operating mechanism, efficiency, sensitivity to control, and mechanosensing of M. xanthus gliding.
  • Thumbnail Image
    Formation of phage lysis patterns and implications on co-propagation of phages and motile host bacteria
    Li, Xiaochu; Gonzalez, Floricel; Esteves, Nathaniel; Scharf, Birgit E.; Chen, Jing (2020-03)
    Coexistence of bacteriophages, or phages, and their host bacteria plays an important role in maintaining the microbial communities. In natural environments with limited nutrients, motile bacteria can actively migrate towards locations of richer resources. Although phages are not motile themselves, they can infect motile bacterial hosts and spread in space via the hosts. Therefore, in a migrating microbial community coexistence of bacteria and phages implies their co-propagation in space. Here, we combine an experimental approach and mathematical modeling to explore how phages and their motile host bacteria coexist and co-propagate. When lytic phages encountered motile host bacteria in our experimental set up, a sector-shaped lysis zone formed. Our mathematical model indicates that local nutrient depletion and the resulting inhibition of proliferation and motility of bacteria and phages are the key to formation of the observed lysis pattern. The model further reveals the straight radial boundaries in the lysis pattern as a telltale sign for coexistence and co-propagation of bacteria and phages. Emergence of such a pattern, albeit insensitive to extrinsic factors, requires a balance between intrinsic biological properties of phages and bacteria, which likely results from coevolution of phages and bacteria. Author summary Coexistence of phages and their bacterial hosts is important for maintaining the microbial communities. In a migrating microbial community, coexistence between phages and host bacteria implies that they co-propagate in space. Here we report a novel phage lysis pattern that is indicative of this co-propagation. The corresponding mathematical model we developed highlights a crucial dependence of the lysis pattern and implied phage-bacteria co-propagation on intrinsic properties allowing proliferation and spatial spreading of the microbes. In contrast, extrinsic factors, such as overall nutrient level, do not influence phage-bacteria coexistence and co-propagation. Findings from this work have strong implications for dispersal of phages mediated by motile bacterial communities, which will provide scientific basis for the fast-growing applications of phages.
  • Thumbnail Image
    The Goldbeter-Koshland Switch in the First-Order Region and Its Response to Dynamic Disorder
    Xing, Jianhua; Chen, Jing (PLOS, 2008-05-14)
    In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840–6844), Goldbeter and Koshland mathematically analyzed a reversible covalent modification system which is highly sensitive to the concentration of effectors. Its signal-response curve appears sigmoidal, constituting a biochemical switch. However, the switch behavior only emerges in the ‘zero-order region’, i.e. when the signal molecule concentration is much lower than that of the substrate it modifies. In this work we showed that the switching behavior can also occur under comparable concentrations of signals and substrates, provided that the signal molecules catalyze the modification reaction in cooperation. We also studied the effect of dynamic disorders on the proposed biochemical switch, in which the enzymatic reaction rates, instead of constant, appear as stochastic functions of time. We showed that the system is robust to dynamic disorder at bulk concentration. But if the dynamic disorder is quasi-static, large fluctuations of the switch response behavior may be observed at low concentrations. Such fluctuation is relevant to many biological functions. It can be reduced by either increasing the conformation interconversion rate of the protein, or correlating the enzymatic reaction rates in the network.
  • Thumbnail Image
    Image Analysis for Sliding Motility of Clostridium perfringens
    Chopdekar, Nidhi (Virginia Tech, 2024-05-07)
    The research investigates the sliding motility of Clostridium perfringens by employing machine learning-based image segmentation techniques and tracking to extract key quantitative characteristics of the movement of the bacteria. C. perfringens cells maintain end-to-end connections after cell divisions and form elongated chains that expand in a one-dimensional fashion. Cells in the elongating chains are pushed by each other to achieve a sliding movement at potentially high speeds. However, these chains are susceptible to breakage due to stress accumulation from rapid growth, which would undermine efficiency of the passive sliding motility. Utilizing AI-powered image analysis, this research aims to obtain detailed quantification of these dynamics and generate data for future mechanistic studies of the sliding motility. Results from this work highlight the effectiveness of machine learning in detecting individual cells from microscopy images. The accurately segmented cells enable enhanced tracking and detailed analysis of bacterial motility. The results generate useful quantitative data such as growth rate, velocity, and division frequency of C. perfringens.
  • Thumbnail Image
    Interlocking mechanisms regulating the circadian clock response to DNA damage
    Zou, Xianlin (Virginia Tech, 2021-06-15)
    Almost all organisms have an endogenously generated and self-sustained time-keeping system that oscillates with a periodicity of about 24 h, namely the circadian clock, that help them adapt to daily environmental changes. Mammalian circadian rhythms are generated and maintained by transcription-translation feedback loops (TTFLs) and include post-translational modifications to help fine-tune the oscillation. Circadian rhythms control a broad range of cellular signaling pathways including those mechanisms involved in cell division and DNA damage response (DDR). We have previously established that the core clock component PERIOD2 (PER2) binds to the tumor suppressor protein p53, a key regulatory checkpoint component that modulates cell cycle progression and the cellular response to genotoxic stress. PER2 binding to p53 modulates p53's stability, cellular localization, and transcriptional activity. As described in Chapter 2, we now identified PER2 as a previously uncharacterized substrate for the ubiquitin E3 ligase mouse double minute 2 homolog (MDM2), an oncoprotein and negative regulator of p53. Our findings showed that the association between PER2 and MDM2 is independent of the presence of p53. In addition, MDM2 targets PER2 for ubiquitylation and degradation in a phosphorylation-independent fashion. Lastly, our studies showed that MDM2 collaborates with β-transducin repeat-containing proteins (β-TrCPs), an E3 ligase that targets PER2 for ubiquitylation in a phosphorylation-dependent manner, to control PER2 degradation and thus the length of circadian period. Because the p53:MDM2 pathway plays a critical role in the cellular response to genotoxic stress, the project described in Chapter 3 is based on the hypothesis that DNA damage caused by radiation shifts the circadian clock phase via the p53:PER2:MDM2 complex. Firstly, we generated Trp53KO (Trp53 gene encodes mouse p53) cell lines in NIH 3T3 Per2:dLuc reporter cells expressing luciferase driven by the Per2 promoter. Phase-response curves (PRCs) for Trp53WT and Trp53KO reporter cells were obtained in response to ionizing radiation (IR) treatments. Results indicated that Trp53 knockout did not affect radiation-induced circadian phase shifts, whereas increased p53 levels induced by transient inhibitor treatments prevented phase shifts when IR was performed at the trough of PER2 abundance. Additional mechanisms were unveiled that kinases ATM (Ataxia Telangiectasia Mutated), ATR (ATM- and Rad3-related) and CHK2 (Checkpoint Kinase 2) regulate radiation-induced phase shifts. Lastly, we found that CLOCK (Circadian Locomotor Output Cycles Kaput) and CRY1 (CRYPTOCHROME 1) were phosphorylated in response to radiation. Taken together, these results indicate that radiation-induced clock phase shifts involve the activity of kinases ATM, ATR and CHK2, and the modification in CLOCK and CRY1. Chapter 4 is a review of current findings about the interaction between circadian rhythms and the cell division cycle regulation pathway. The article highlights a multidisciplinary approach that combines mathematical modeling and experimental data to reveal how p53:PER2:MDM2 acts as a node controlling timely cell cycle progression. In summary, our work provided evidence that MDM2 targets PER2 for ubiquitylation and degradation in a phosphorylation-independent manner, and this influences circadian oscillation. Furthermore, the exploration of p53:PER2:MDM2 association shed light on how radiation-induced DNA damage shifts clock phase. These findings expose a crosstalk mechanism that senses DNA damage and shifts the clock system.
  • Thumbnail Image
    Mathematical analysis of robustness of oscillations in models of the mammalian circadian clock
    Yao, Xiangyu; Heidebrecht, Benjamin L.; Chen, Jing; Tyson, John J. (Public Library of Science, 2022-03-18)
    Circadian rhythms in a wide range of organisms are mediated by molecular mechanisms based on transcription-translation feedback. In this paper, we use bifurcation theory to explore mathematical models of genetic oscillators, based on Kim & Forger’s interpretation of the circadian clock in mammals. At the core of their models is a negative feedback loop whereby PER proteins (PER1 and PER2) bind to and inhibit their transcriptional activator, BMAL1. For oscillations to occur, the dissociation constant of the PER:BMAL1 complex, Kbd, must be ≤ 0.04 nM, which is orders of magnitude smaller than a reasonable expectation of 1–10 nM for this protein complex. We relax this constraint by two modifications to Kim & Forger’s ‘single negative feedback’ (SNF) model: first, by introducing a multistep reaction chain for posttranscriptional modifications of Per mRNA and posttranslational phosphorylations of PER, and second, by replacing the first-order rate law for degradation of PER in the nucleus by a Michaelis-Menten rate law. These modifications increase the maximum allowable Kbd to ~2 nM. In a third modification, we consider an alternative rate law for gene transcription to resolve an unrealistically large rate of Per2 transcription at very low concentrations of BMAL1. Additionally, we studied extensions of the SNF model to include a second negative feedback loop (involving REV-ERB) and a supplementary positive feedback loop (involving ROR). Contrary to Kim & Forger’s observations of these extended models, we find that, with our modifications, the supplementary positive feedback loop makes the oscillations more robust than observed in the models with one or two negative feedback loops. However, all three models are similarly robust when accounting for circadian rhythms (~24 h period) with Kbd ≥ 1 nM. Our results provide testable predictions for future experimental studies.
  • Thumbnail Image
    Mathematical modeling of biological dynamics
    Li, Xiaochu (Virginia Tech, 2023-12-11)
    This dissertation unravels intricate biological dynamics in three distinct biological systems as the following. These studies combine mathematical models with experimental data to enhance our understanding of these complex processes. 1. Bipolar Spindle Assembly: Mitosis relies on the formation of a bipolar mitotic spindle, which ensures an even distribution of duplicated chromosomes to daughter cells. We address the issue of how the spindle can robustly recover bipolarity from the irregular forms caused by centrosome defects/perturbations. By developing a biophysical model based on experimental data, we uncover the mechanisms that guide the separation and/or clustering of centrosomes. Our model identifies key biophysical factors that play a critical role in achieving robust spindle bipolarization, when centrosomes initially organize a monopolar or multipolar spindle. These factors encompass force fluctuations between centrosomes, balance between repulsive and attractive inter-centrosomal forces, centrosome exclusion from the cell center, proper cell size and geometry, and limitation of the centrosome number. 2. Chromosome Oscillation: During mitotic metaphase, chromosomes align at the spindle equator in preparation for segregation, and form the metaphase plate. However, these chromosomes are not static; they exhibit continuous oscillations around the spindle equator. Notably, either increasing or decreasing centromeric stiffness in PtK1 cells can lead to prolonged metaphase chromosome oscillations. To understand this biphasic relationship, we employ a force-balance model to reveal how oscillation arises in the spindle, and how the amplitude and period of chromosome oscillations depend on the biological properties of spindle components, including centromeric stiffness. 3. Pattern Formation in Bacterial-Phage Systems: The coexistence of bacteriophages (phages) and their host bacteria is essential for maintaining microbial communities. In resource-limited environments, mobile bacteria actively move toward nutrient-rich areas, while phages, lacking mobility, infect these motile bacterial hosts and disperse spatially through them. We utilize a combination of experimental methods and mathematical modeling to explore the coexistence and co-propagation of lytic phages and their mobile host bacteria. Our mathematical model highlights the role of local nutrient depletion in shaping a sector-shaped lysis pattern in the 2D phage-bacteria system. Our model further shows that this pattern, characterized by straight radial boundaries, is a distinctive indicator of extended coexistence and co-propagation of bacteria and phages. Such patterns rely on a delicate balance among the intrinsic biological characteristics of phages and bacteria, which have likely arisen from the coevolution of cognate pairs of phages and bacteria.
  • Thumbnail Image
    Mathematical Modeling of Circadian Gene Expression in Mammalian Cells
    Yao, Xiangyu (Virginia Tech, 2023-06-28)
    Circadian rhythms in mammals are self-sustained repeating activities driven by the circadian gene expression in cells, which is regulated at both transcriptional and posttranscriptional stages. In this work, we first used mathematical modeling to investigate the transcriptional regulation of circadian gene expression, with a focus on the mechanisms of robust genetic oscillations in the mammalian circadian core clock. Secondly, we built a coarse-grained model to study the post-transcriptional regulation of the rhythmicities of poly(A) tail length observed in hundreds of mRNAs in mouse liver. Lastly, we examined the application of Sobol indices, which is a global sensitivity analysis method, to mathematical models of biological oscillation systems, and proposed two methods tailored for the calculation of circular Sobol indices. In the first project, we modified the core negative feedback loop in a mathematical model of the mammalian genetic oscillator so that the unrealistic tight binding between the repressor PER and the activator BMAL1 is relaxed for robust oscillations. By studying the modified extended models, we found that the auxiliary positive feedback loop, rather than the auxiliary negative feedback loop, makes the oscillations more robust, yet they are similar when accounting for circadian rhythms (~24h period). In the second project, we investigated the regulation of rhythmicities in poly(A) tail length by four coupled rhythmic processes, which are transcription, deadenylation, polyadenylation, and degradation. We found that rhythmic deadenylation is the strongest contributor to the rhythmicity in poly(A) tail length and the rhythmicity in the abundance of the mRNA subpopulation with long poly(A) tails. In line with this finding, the model further showed that the experimentally observed distinct peak phases in the expression of deadenylases, regardless of other rhythmic controls, can robustly cluster the rhythmic mRNAs by their peak phases in poly(A) tail length and abundance of the long-tailed subpopulation. In the last project, we reviewed the theoretical basis of Sobol indices and identified potential problems when it is applied to mathematical models of biological oscillation systems. Based on circular statistics, we proposed two methods for the calculation of circular Sobol indices and compared their performance with the original Sobol indices in several models. We found that though the relative rankings of the contribution from parameters are the same across three methods, circular Sobol indices can better quantitatively distinguish the contribution of individual parameters. Through this work, we showed that mathematical modeling combined with sensitivity analysis can help us understand the mechanisms underlying the circadian gene expression in mammalian cells. Also, testable predictions are made for future experiments and new ideas are provided that can enable potential chronopharmacology research.
  • Thumbnail Image
    Mathematical modeling of macronutrient signaling in Saccharomyces cerevisiae
    Jalihal, Amogh Prabhav (Virginia Tech, 2020-07-08)
    In eukaryotes, distinct nutrient signals are integrated in order to produce robust cellular responses to fluctuations in the environment. This process of signal integration is attributed to the crosstalk between nutrient specific signaling pathways, as well as the large degree of overlap between their regulatory targets. In the budding yeast Saccharomyces cerevisiae, these distinct pathways have been well characterized. However, the significant overlap between these pathways confounds the interpretation of the overall regulatory logic in terms of nutrient-dependent cell state determination. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling pathway in budding yeast, focussing on carbon and nitrogen signaling. We build a computational model of this pathway to reconcile the available experimental data with our proposed molecular mechanism. We evaluate the robustness of the model fit to data with respect to the variations in the values of kinetic parameters used to calibrate the model. Finally, we use the model to make novel, experimentally testable predictions of transcription factor activities in mutant strains undergoing complex nutrient shifts. We also propose a novel framework, called BoolODE for utilizing published Boolean models to generate synthetic datasets used to benchmark the performance of algorithms performing gene regulatory network inference from single cell RNA sequencing data.