CHO Cells Adapted to Inorganic Phosphate Limitation Show Higher Growth and Higher Pyruvate Carboxylase Flux in Phosphate Replete Conditions - Maralingannavar, Vishwanathgouda; Parmar, Dharmeshkumar; Pant, Tejal; Gadgil, Chetan; Panchagnula, Venkateswarlu; Gadgil, Mugdha (Biotechnology progress, 2017)
Inorganic phosphate (P-i) is an essential ion involved in diverse cellular processes including metabolism. Changes in cellular metabolism upon long term adaptation to P-i limitation have been reported in E. coli. Given the essential role of P-i, adaptation to P-i limitation may also result in metabolic changes in animal cells. In this study, we have adapted CHO cells producing recombinant IgG to limiting P-i conditions for 75 days. Not surprisingly, adapted cells showed better survival under P-i limitation. Here, we report the finding that such cells also showed better growth characteristics compared to control in batch culture replete with P-i ( higher peak density and integral viable cell density), accompanied by a lower specific oxygen uptake rate and cytochrome oxidase activity towards the end of exponential phase. Surprisingly, the adapted cells grew to a lower peak density under glucose limitation. This suggests long term P-i limitation may lead to selection for an altered metabolism with higher dependence on glucose availability for biomass assimilation compared to control. Steady state U-C-13 glucose labeling experiments suggest that adapted cells have a higher pyruvate carboxylase flux. Consistent with this observation, supplementation with aspartate abolished the peak density difference whereas supplementation with serine did not abolish the difference. This supports the hypothesis that cell growth in the adapted culture might be higher due to a higher pyruvate carboxylase flux. Decreased fitness under carbon limitation and mutations in the sucABCD operon has been previously reported in E. coli upon long term adaptation to P-i limitation, suggestive of a similarity in cellular response among such diverse species. (C) 2017 American Institute of Chemical Engineers

Differential responses of CHO cells adapted to limitation of inorganic phosphate, glucose or glutamine - Maralingannavar, Vishwanathgouda; Parmar, Dharmeshkumar; Pant, Tejal; Gadgil, Chetan; Panchagnula, Venkateswarlu; Gadgil, Mugdha (255th National Meeting and Exposition of the American-Chemical-Society (ACS) - Nexus of Food, Energy, and Water, 2018)

Clathrin-mediated endocytosis regulates a balance between opposing signals to maintain the pluripotent state of embryonic stem cells - Narayana, V, Yadavalli; Gadgil, Chetan; Mote, Ridim D.; Rajan, Raghav; Subramanyam, Deepa (Stem Cell Reports, 2019)
Endocytosis is implicated in the maintenance of embryonic stem cell (ESC) pluripotency, although its exact role and the identity of molecular players remain poorly understood. Here, we show that the clathrin heavy chain (CLTC), involved in clathrin-mediated endocytosis (CME), is vital for maintaining mouse ESC (mESC) pluripotency. Knockdown of Cltc resulted in a loss of pluripotency accompanied by reduced E-cadherin (E-CAD) levels and increased levels of transforming growth factor beta (TGF-beta) and extracellular signal-regulated kinase (ERK) signaling. We demonstrate that both E-CAD and TGF-beta receptor type 1 (TGF-beta R1) are internalized through CME in mESCs. While E-CAD is recycled, TGF-beta R1 is targeted for lysosomal degradation thus maintaining inverse levels of these molecules. Finally, we show that E-CAD interacts with ERK, and that the decreased pluripotency upon CME loss can be rescued by inhibiting TGF-beta R, MEK, and GSK3 beta, or overexpressing E-CAD. Our results demonstrate that CME is critical for balancing signaling outputs to regulate ESC pluripotency, and possibly cell fate choices in early development.

Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations - Kuntal, Bhusan K.; Gadgil, Chetan; Mande, Sharmila S. (Frontiers in Microbiology, 2019)
The affordability of high throughput DNA sequencing has allowed us to explore the dynamics of microbial populations in various ecosystems. Mathematical modeling and simulation of such microbiome time series data can help in getting better understanding of bacterial communities. In this paper; we present Web-gLV- a GUI based interactive platform for generalized Lotka-Volterra (gLV) based modeling and simulation of microbial populations. The tool can be used to generate the mathematical models with automatic estimation of parameters and use them to predict future trajectories using numerical simulations. We also demonstrate the utility of our tool on few publicly available datasets. The case studies demonstrate the ease with which the current tool can be used by biologists to model bacterial populations and simulate their dynamics to get biological insights. We expect Web-gLV to be a valuable contribution in the field of ecological modeling and metagenomic systems biology.
Keywords: lotka-volterra; microbial population; Microbiome; Modeling; numerical-simulation; time-series; visualization; web-server

Boolean model for melanogenesis - Dnyane, Pooja; Gadgil, Chetan (Physical Biology, 2021)
Melanogenesis is a highly regulated process through which the pigment melanin is produced in skin cells. Irregularities in the molecular events that govern the process of skin pigmentation can cause disorders like vitiligo. In order to understand the biology of disease progression, it is important to have an in depth understanding of intracellular events. Mathematical models provide an integrated view of intracellular signalling. There are very few models to date that incorporate intracellular processes relevant to melanogenesis and only one to our knowledge that simulates the dynamics of response to varying levels of input. Here, we report the formulation of the largest Boolean model (265 nodes) for melanogenesis to date. The model was built on the basis of a detailed interaction network graph published by Raghunath et al. Through additional manual curation of the reported interactions, we converted the graph into a set of Boolean rules, following the procedure of the first Boolean model (62 nodes) for melanogenesis published by Lee et al. Simulations show that the predicted response to varying UV levels for most of the nodes is similar to the predictions of the existing model. The greater complexity allows investigation of the sensitivity of melanin to additional nodes. We carried out perturbation analysis of the network through node deletion and constitutive activation to identify sensitivity of outcomes, and compared the nodes identified as sensitive to previous reports.
Keywords: Boolean model; melanogenesis; Signal transduction

Web-gLV: a web based platform for lotka-volterra based modeling and simulation of microbial populations (vol 10, 288, 2019) - Kuntal, Bhusan K.; Gadgil, Chetan; Mande, Sharmila S. (Frontiers in Microbiology, 2021)
Keywords: lotka-volterra; microbial population; Microbiome; Modeling; numerical-simulation; time-series; visualization; web-server

Kinetic model of GPCR-G protein interactions reveals allokairic modulation of signaling - Culhane, Kelly; Gupte, Tejas; Madhugiri, Indrani; Gadgil, Chetan; Sivaramakrishnan, Sivaraj (Biophysical Journal, 2022)

Temporal analysis of melanogenesis identifies fatty acid metabolism as key skin pigment regulator - Sultan, Farina; Basu, Reelina; Murthy, Divya; Kochar, Manisha; Attri, Kuldeep S.; Aggarwal, Ayush; Kumari, Pooja; Dnyane, Pooja; Tanwar, Jyoti; Motiani, Rajender K.; Singh, Archana; Gadgil, Chetan; et al. (Plos Biology, 2022)
Therapeutic methods to modulate skin pigmentation has important implications for skin cancer prevention and for treating cutaneous hyperpigmentary conditions. Towards defining new potential targets, we followed temporal dynamics of melanogenesis using a cell-autonomous pigmentation model. Our study elucidates 3 dominant phases of synchronized metabolic and transcriptional reprogramming. The melanogenic trigger is associated with high MITF levels along with rapid uptake of glucose. The transition to pigmented state is accompanied by increased glucose channelisation to anabolic pathways that support melanosome biogenesis. SREBF1-mediated up-regulation of fatty acid synthesis results in a transient accumulation of lipid droplets and enhancement of fatty acids oxidation through mitochondrial respiration. While this heightened bioenergetic activity is important to sustain melanogenesis, it impairs mitochondria lately, shifting the metabolism towards glycolysis. This recovery phase is accompanied by activation of the NRF2 detoxication pathway. Finally, we show that inhibitors of lipid metabolism can resolve hyperpigmentary conditions in a guinea pig UV-tanning model. Our study reveals rewiring of the metabolic circuit during melanogenesis, and fatty acid metabolism as a potential therapeutic target in a variety of cutaneous diseases manifesting hyperpigmentary phenotype.

Feedback driven autonomous cycles of assembly and disassembly from minimal building blocks - Reja, Antara; Jha, Sangam; Sreejan, Ashley; Pal, Sumit; Bal, Subhajit; Gadgil, Chetan; Das, Dibyendu (Nature Communications, 2024)
The construction of complex systems by simple chemicals that can display emergent network dynamics might contribute to our understanding of complex behavior from simple organic reactions. Here we design single amino acid/dipeptide-based systems that exhibit multiple periodic changes of (dis)assembly under non-equilibrium conditions in closed system, importantly in the absence of evolved biocatalysts. The two-component based building block exploits pH driven non-covalent assembly and time-delayed accelerated catalysis from self-assembled state to install orthogonal feedback loops with a single batch of reactants. Mathematical modelling of the reaction network establishes that the oscillations are transient for this network structure and helps to predict the relative contribution of the feedback loop to the ability of the system to exhibit such transient oscillation. Such autonomous systems with purely synthetic molecules are the starting point that can enable the design of active materials with emergent properties. The study of the network dynamics of complex systems formed by simple chemicals can contribute to our understanding of complex behavior from simple organic reactions. Here, built on the minimal building blocks, the authors describe a system with periodic (dis)assembly utilizing feedback loops controlled by time-delayed catalysis and pH-driven assembly.

Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth - Pandey, Ujjiti; Madhugiri, Indrani; Gadgil, Chetan; Gadgil, Mugdha (BIOTECHNOLOGY PROGRESS, 2024)
Keywords: Absorption; Cytotoxicity; ENTEROCYTES; HISTIDINE