Biology subjects

Ghosh, S.

Publications and source records attributed to Ghosh, S..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

SUV39H1 Preserves Cancer Stem Cell Chromatin State and Properties in Glioblastoma

Of the more than 100 types of brain cancer, glioblastoma (GBM) is the deadliest. As GBM stem cells (GSCs) are considered to be responsible for therapeutic resistance and tumor recurrence, effective targeting and elimination of GSCs could hold promise for preventing GBM recurrence and achieving potential cures. We show here that SUV39H1, which encodes a histone-3, lysine-9 methyltransferase, plays a critical role in GSC maintenance and GBM progression. Upregulation of SUV39H1 was observed in GBM samples compared to normal brain tissues, and knockdown of SUV39H1 in patient-derived GSCs impaired their proliferation and stemness. Single-cell RNA-seq analysis demonstrated restricted expression of SUV39H1 is in GSCs relative to non-stem GBM cells, likely due to super-enhancer-mediated transcriptional activation, while whole cell RNA-seq analysis revealed that SUV39H1 regulates G2/M cell cycle progression, stem cell maintenance, and cell death pathways in GSCs. By integrating the RNA-seq data with ATAC-seq (assay for transposase-accessible chromatin followed by sequencing), we further demonstrated altered chromatin accessibility in key genes associated with these pathways following SUV39H1 knockdown. Treatment with chaetocin, a SUV39H1 inhibitor, mimicked the functional effects of SUV39H1 knockdown in GSCs and sensitized GSCs to the GBM chemotherapy drug temozolomide. Furthermore, targeting SUV39H1 in vivo using a patient-derived xenograft model for GBM inhibited GSC-driven tumor formation. This is the first report demonstrating a critical role for SUV39H1 in GSC maintenance. SUV39H1-mediated targeting of GSCs could enhance the efficacy of existing chemotherapy, presenting a promising strategy for improving GBM treatment and patient outcomes. HighlightsO_LISUV39H1 is upregulated in GBM, especially GSCs C_LIO_LITargeting SUV39H1 disrupts GSC maintenance and sensitizes GSCs to TMZ C_LIO_LITargeting SUV39H1 alters chromatin accessibility at cell cycle and stemness genes C_LIO_LITargeting SUV39H1 suppresses GSC-driven tumors in a patient-derived xenograft model C_LI

cancer biology↗

bioRxiv2024

Ubiquitination mediates protein localization in RNA virus-infected cells

Viruses trigger monocytes proinflammatory and antiviral responses. Ubiquitination, a post-translational modification primarily marking proteins for degradation, regulates cellular responses to virus infection. However, a comprehensive analysis of virus-induced ubiquitination in monocytes is lacking. Here we identified a widespread increase of ubiquitination under viral RNA challenge or influenza infection in monocytes. Systematic proteome studies revealed that influenza infection elicits dynamic ubiquitinome alterations, with a notable transition from early to late stage. Most of this increased ubiquitination is not proteolytic and targets proteins involved in subcellular localization, such as the mitochondrial protein COA7 which, when ubiquitinated during infection, translocates to the nucleus and inhibits stress granules formation and TNF- expression. Blocking ubiquitination halts viral ribonucleoproteins nuclear export, highlighting ubiquitinations importance for protein localization during virus infection.

molecular biology↗

bioRxiv2024

βA3/A1-crystallin is an epigenetic regulator of histone deacetylase 3 (HDAC3) in the retinal pigmented epithelial (RPE) cells

Introductory paragraphThe retinal pigmented epithelial (RPE) cells maintain retinal homeostasis, and alterations in their function contribute to non-exudative age-related macular degeneration (AMD)1,2. Here, we explore the intricate relationship between RPE cells, epigenetic modifications, and the development of AMD. Importantly, the study reveals a substantial decrease in histone deacetylase 3 (HDAC3) activity and elevated histone acetylation in the RPE of human AMD donor eyes. To investigate epigenetic mechanisms in AMD development, we used a mouse model with RPE-specific Cryba1 knockout3-5, revealing that the loss of {beta}A3/A1-crystallin selectively reduces HDAC3 activity, resulting in increased histone acetylation. {beta}A3/A1-crystallin activates HDAC3 by facilitating its interaction with the casein kinase II (CK2) and phosphorylating HDAC3, as well as by regulating intracellular InsP6 (phytic acid) levels, required for activating HDAC3. These findings highlight a novel function of {beta}A3/A1-crystallin as an epigenetic regulator of HDAC3 in the RPE cells and provide insights into potential therapeutic strategies in non-exudative AMD.

cell biology↗

bioRxiv2024

An anomalous 3'-terminal phosphorothioated mismatch bypass activity and its application as a binary molecular switch

Phosphorothioated (PST) oligonucleotides are increasingly being used in RNA silencing, antisense, and biosensing applications. However, the possibilities and consequences of their desultory interactions with other possible nucleic acids and DNA polymerases inside the cell remain inadequately characterized. In this study, we report the discovery of an unusual terminal mismatch bypass activity involving 3'-PST containing DNA primers and certain strand displacement DNA polymerases. Using rolling circle DNA amplification, we have identified that strand displacement DNA polymerases such as phi29 and BST large fragment (LF) can bypass 3'-terminal PST mismatches upto 1 - 20 nt length. Next, we explore the length and sequence dependence of this unusual attribute, incubation in near-ambient and 60 - 65{degrees}C temperatures, and measures to blockade or modulate this mismatch bypass activity to create a binary fully nucleic acid-based and non-photocontrolled molecular switch (the first of its kind). After proposing possible underlying mechanisms for this activity, we discuss its potential consequences and applications.

biochemistry↗

bioRxiv2024

Mechanism of host cell invasion by Leishmania through KMP-11 mediated cholesterol-transport and membrane phase transition

The first step of successful infection by any intracellular pathogen relies on its ability to invade its host cell membrane. However, the detailed structural and molecular understanding underlying lipid membrane modification during pathogenic invasion remains unclear. In this study, we show that a specific Leishmania donovani (LD) protein, KMP-11, forms oligomers that bridge LD and host macrophage (M{Phi}) membranes. This KMP-11 induced interaction between LD and M{Phi} depends on the variations in cholesterol (CHOL) and ergosterol (ERG) contents in their respective membranes. These variations are crucial for the subsequent steps of invasion, including (a) the initial attachment, (b) CHOL transport from M{Phi} to LD, and (c) detachment of LD from the initial point of contact through a liquid ordered (Lo) to liquid disordered (Ld) membrane-phase transition. To validate the importance of KMP-11, we generated KMP-11 depleted LD, which failed to attach and invade host M{Phi}. Through tryptophan-scanning mutagenesis and synthesized peptides, we developed a generalized mathematical model, which demonstrates that the hydrophobic moment and the symmetry sequence code at the membrane interacting protein domain are key factors in facilitating the membrane phase transition and, consequently, the host cell infection process by Leishmania parasites.

biophysics↗

bioRxiv2024

Functionally Validated Proteome-Wide Bioinformatic Annotation of the Monotopic Phosphoglycosyl Transferase Family

Phosphoglycosyl transferases (PGTs) are membrane proteins that initiate glycoconjugate biosynthesis by transferring a phospho-sugar moiety from a soluble nucleoside diphosphate sugar to a membrane-embedded polyprenol phosphate acceptor. The centrality of PGTs in complex glycan assembly and the current lack of functional information make these enzymes high-value targets for biochemical investigation. In particular, the small monotopic PGT family is exclusively bacterial and represents the minimal functional unit of the monotopic PGT superfamily. Here, we combine a sequence similarity network (SSN) analysis with a generalizable, luminescence-based activity assay to probe the substrate specificity of this family of monoPGTs in a bacterial cell-membrane fraction. This strategy allows us to identify specificity on a far more significant scale than previously achievable and correlate preferred substrate specificities with predicted structural differences within the conserved monoPGT fold. Finally, we present the proof-of-concept for a small-scale inhibitor screen (eight nucleoside analogs) with four monoPGTs of diverse substrate specificity, thus building a foundation for future inhibitor discovery initiatives. SignificanceUncovering the function and specificity of enzymes responsible for glycoconjugate biosynthesis traditionally requires a multi-faceted and individually curated approach. This is especially true for bacterial glycoconjugates due to greater monosaccharide diversity and a paucity of established structural information. Here we leverage bioinformatic and in-vitro tools to predict and validate substrate specificity for a unique, exclusively bacterial family of enzymes responsible for the first step in many of these glycan assembly pathways. We further show that this platform is suitable for enhanced functional annotation and inhibitor testing, paving the way for the development of urgently needed antibiotics.

biochemistry↗

bioRxiv2024

Disruption of the PGE2 synthesis / response pathway restrains atherogenesis in programmed cell death-1 (Pd-1) deficient hyperlipidemic mice

Immune checkpoint inhibitors (ICIs) that target programmed cell death 1 (PD-1) have revolutionized cancer treatment by enabling the restoration of suppressed T-cell cytotoxic responses. However, resistance to single-agent ICIs limits their clinical utility. Combinatorial strategies enhance their antitumor effects, but may also enhance the risk of immune related adverse effects of ICIs. Prostaglandin (PG) E2, formed by the sequential action of the cyclooxygenase (COX) and microsomal PGE synthase (mPGES-1) enzymes, acting via its E prostanoid (EP) receptors, EPr2 and EPr4, promotes lymphocyte exhaustion, revealing an additional target for ICIs. Thus, COX inhibitors and EPr4 antagonists are currently being combined with ICIs potentially to enhance antitumor efficacy in clinical trials. However, given the cardiovascular (CV) toxicity of COX inhibitors, such combinations may increase the risk particularly of CV AEs. Here, we compared the impact of distinct approaches to disruption of the PGE2 synthesis /response pathway - global or myeloid cell specific depletion of mPges-1 or global depletion of Epr4 - on the accelerated atherogenesis in Pd-1 deficient hyperlipidemic (Ldlr-/-) mice. All strategies restrained the atherogenesis. While depletion of mPGES-1 suppresses PGE2 biosynthesis, reflected by its major urinary metabolite, PGE2 biosynthesis was increased in mice lacking EPr4, consistent with enhanced expression of aortic Cox-1 and mPges-1. Deletions of mPges-1 and Epr4 differed in their effects on immune cell populations in atherosclerotic plaques; the former reduced neutrophil infiltration, while the latter restrained macrophages and increased the infiltration of T-cells. Consistent with these findings, chemotaxis by bone-marrow derived macrophages from Epr4-/- mice was impaired. Epr4 depletion also resulted in extramedullary lymphoid hematopoiesis and inhibition of lipoprotein lipase activity (LPL) with coincident spelenomegaly, leukocytosis and dyslipidemia. Targeting either mPGES-1 or EPr4 may restrain lymphocyte exhaustion while mitigating CV irAEs consequent to PD-1 blockade.

pharmacology and toxicology↗

bioRxiv2024

Kingdom-specific lipid unsaturation shapes up sequence evolution in membrane arm subunits of eukaryotic respiratory complexes

Sequence evolution of protein complexes (PCs) is constrained by protein-protein interactions (PPIs). PPI-interfaces are predominantly conserved and hotspots for disease-related mutations. How lipid-protein interactions (LPIs) constrain sequence evolution of membrane- PCs? We explore Respiratory Complexes (RCs) as a case study as these allow to compare sequence evolution in subunits exposed to both lipid-rich inner-mitochondrial membrane (IMM) and aqueous matrix. We find that lipid-exposed surfaces of the IMM-subunits but not of the matrix subunits are populated with non-PPI disease-causing mutations signifying LPIs in stabilizing RCs. Further, IMM-subunits including their exposed surfaces show high intra- kingdom sequence conservation but remarkably diverge beyond. Molecular Dynamics simulation suggests contrasting LPIs of structurally superimposable but sequence-wise diverged IMM-exposed helices of Complex I (CI) subunit Ndufa1 from human and Arabidopsis depending on kingdom-specific unsaturation of cardiolipin fatty acyl chains. in cellulo assays consolidate inter-kingdom incompatibility of Ndufa1-helices due to the lipid- exposed amino acids. Plant-specific unsaturated fatty acids in human cells also trigger CI- instability. Taken together, we posit that altered LPIs calibrate sequence evolution at the IMM-arms of eukaryotic RCs.

cell biology↗

bioRxiv2024

Single-cell analysis of human diversity in circulating immune cells

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally1,2. The relationships of human diversity with biological and biomedical phenotypes are pervasive3, yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We detected single-cell signatures of human diversity not apparent at the level of cell types, as well as modulation of the effects of age and sex by self-reported ethnicity. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond.

genomics↗

bioRxiv2024

IntegrIBS: Towards Building a Robust IBS Classifier with Integrated Microbiome Data

Irritable Bowel Syndrome (IBS) is a condition that is quite complicated and shares its symptoms with other related diseases, making it difficult to diagnose. In this study, we initially trained machine learning models on individual microbiome datasets and tested their performance on other datasets, observing variability and low precision among them. To mitigate this, we hypothesised that integrating multiple publicly available microbiome datasets will capture a wide spectrum of microbiome variations across different geographies and demographics. Utilizing this integrated dataset, the XGBoost model achieved a mean accuracy of 0.75 with a standard deviation of 0.04 in 10-fold cross-validation, demonstrating its potential for robust IBS prediction. Explainability analysis identified key bacterial taxa influencing predictions, aligning with existing literature. However, the models performance declined significantly when using a leave-one-dataset-out approach, where the model was trained on all but one dataset and tested on the excluded dataset. The results highlight the challenges of generalizing across diverse datasets due to biological and technical variability. These findings present a cautionary tale regarding the integration of datasets and interpretation of results, emphasizing the need for more comprehensive approaches to develop reliable diagnostic tools for IBS.

bioinformatics↗

bioRxiv2024

Structure-function relationship of PE11 esterase of Mycobacterium tuberculosis with respect to its role in virulence

The lipolytic enzymes of Mycobacterium tuberculosis play a critical role in immunomodulation and virulence. Among these proteins, PE11 which also belongs to the PE/PPE family, is the smallest ([~]10.8 kDa) and play a significant role in cell wall remodelling and virulence. PE11 is established to be an esterase, but its enzymatic and structural properties are not yet characterized. In this study, using homology modelling we deduced the putative structure which shows the presence of both -helix and {beta}-sheet structures which is in close agreement with that observed by CD spectra of the purified protein. PE11 was found to contain a GX3SX4G motif homologous to canonical GxSxG motif present in many serin hydrolases. The catalytic triad appears to be located within this motif as substitution of Serine26 and Glycine31 residues abrogated its enzymatic activity. Gel-filtration chromatography data indicate that PE11 possibly exists as dimer and tetramer showing positive cooperativity for binding its substrates. In addition, PE11 esterase activity was found to be critical for cell wall remodelling, antibiotic resistance and conferring survival advantages to M. tuberculosis. Our data suggest that PE11 can be targeted for designing potential therapeutic strategies.

microbiology↗

bioRxiv2024

Genomic Insights and Biocontrol Potential of Ten Bacterial Strains from the Tomato Core Microbiome

Despite their adverse environmental effects, modern agriculture relies heavily on agrochemicals to manage diseases and pests and enhance plant growth and productivity. Some of these functions could instead be fulfilled by endophytes from the plant microbiota, which have diverse activities beneficial for plant growth and health. We therefore used a microbiome-guided top-down approach to select ten bacterial strains from different taxa in the core microbiome of tomato plants in the production chain for evaluation as potential bioinoculants. These taxa included some that are commonly used as biofertilizers and biocontrol agents (Pseudomonas and Bacillus) as well as the less studied genera Leclercia, Chryseobacterium, Glutamicibacter, and Paenarthorbacter. When inoculated in the tomato rhizosphere, these strains promoted plant growth and reduced the severity of Fusarium Crown and Root Rot and Bacterial Spot infections. High-quality genomes for each strain were obtained using Oxford Nanopore long-read and Illumina short-read sequencing, enabling the dissection of their genetic makeup to identify phyto-beneficial traits. This yielded a comprehensive inventory of genes from each strain related to processes including colonization, biofertilization, phytohormones, and plant signaling. Traits directly relevant to fertilization including phosphate solubilization and acquisition of nitrogen and iron were also identified. Moreover, the strains carried several functional genes putatively involved in abiotic stress alleviation and biotic stress management, traits that indirectly foster plant health and growth. The gathered genomic information will be instrumental in planning the use of these bacteria individually or in consortia to enhance plant growth by coupling strains with different traits, effects, and mechanisms of action.

genomics↗

bioRxiv2024

Amplitude entropy captures chimera-like behavior in epileptic seizure dynamics

Epilepsy is a neurological disease characterized by epileptic seizures, which commonly manifest with pronounced frequency and amplitude changes in the EEG signal. In the case of focal seizures, initially localized pathological activity spreads from a so-called "onset zone" to a wider network of brain areas. Chimeras, defined as states of simultaneously occurring coherent and incoherent dynamics in symmetrically coupled networks are increasingly invoked for characterization of seizures. In particular, chimera-like states have been observed during the transition from a normal (asynchronous) to a seizure (synchronous) network state. However, chimeras in epilepsy have only been investigated with respect to the varying phases of oscillators. We propose a novel method to capture the characteristic pronounced changes in the recorded EEG amplitude during seizures by estimating chimera-like states directly from the signals in a frequency- and time-resolved manner. We test the method on a publicly available intracranial EEG dataset of 16 patients with focal epilepsy. We show that the proposed measure, titled Amplitude Entropy, is sensitive to the altered brain dynamics during seizure, demonstrating its significant increases during seizure as compared to before and after seizure. This finding is robust across patients, their seizures, and different frequency bands. In the future, Amplitude Entropy could serve not only as a feature for seizure detection, but also help in characterizing amplitude chimeras in other networked systems with characteristic amplitude dynamics.

neuroscience↗

bioRxiv2024

Electroencephalogram (EEG) Classification using a bio-inspired Deep Oscillatory Neural Network

In this paper, we propose two models of oscillatory neural networks - the Deep Oscillatory Neural Network (DONN) and a convolutional variation of it named Oscillatory Convolutional Neural Network (OCNN) - and apply the models to a variety of problems involving the classification and prediction of Electroencephalogram (EEG) signals. Deep neural networks applied to signal processing problems will have to incorporate various architectural features to remember the history of the input signals e.g., loops between the layers, "gated" neurons, and tapped delay lines. But real brains have rich dynamics expressed in terms of frequency bands like alpha, beta, gamma, delta, etc. To incorporate this aspect of brain dynamics in a Recurrent Neural Network (RNN) we propose to use nonlinear oscillators as dynamic neuron models in the hidden layers. The two oscillatory deep neural networks proposed are applied to the following EEG classification and prediction problems: Prediction of nearby EEG channels, classification of single-channel EEG data (healthy vs. epileptic, different stages of sleep stage classification), and multi-channel EEG data (Epileptic vs. Normal, Left vs. right-hand Motor imagery movement, and healthy vs. Claustrophobic EEG).

bioengineering↗

bioRxiv2024

Functional roles of neural aPKCs in mouse brain development and survival

Conserved protein complexes establish and maintain cell polarity. In turn, cell polarity is indispensable for fundamental developmental processes such as asymmetric division of stem cells and establishment of subcellular membrane polarization during cell differentiation. There are three well characterized polarity complexes. Atypical Protein Kinase C (aPKC) is a conserved constituent of the PAR complex that phosphorylates not only substrates within this complex, but also in the other polarity complexes. Outside of the polarity complex, aPKC regulates a myriad of cellular processes such as migration, metabolism, and survival. In mammals, two paralogs, Prkci and Prkcz, form the aPKC subfamily. Here, we characterized the expression of the Prkci and Prkcz paralogs, including a variant transcript of Prkcz, in the mouse brain and specific cells of the neural lineage. We generated a series of mice with individual and collective ablation of the two aPKC paralogs in neural stem cells, new-born neurons, astrocytes and NG2+ cells, as well as a mouse expressing kinase-inactive PRKCI in neural progenitors. We examine the effects of loss of aPKC paralogs or its kinase activity on gross brain development and organismal viability. Our results identify a critical window in neural progenitor differentiation wherein aPKC function is indispensable for neurodevelopment. Beyond this period, the ablation of even both aPKCs is characterized by a conspicuous absence of anticipated drastic effects. The genetic models developed might prove useful for further interrogating aPKC function in neurodevelopment and neuronal function or to reveal the role of polarity complex function in neurons, astrocytes and oligodendrocytes during stress, injuries or diseases.

developmental biology↗

bioRxiv2024

Encoding seizures with partial synchronization: A spiking neural network for biosignal monitoring on a mixed signal neuromorphic processor

Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, developing wearable systems that are able to monitor, analyze, and detect epileptic seizures with long-lasting operation times using current technologies is still an open challenge. Brain-inspired spiking neural networks (SNNs) represent a promising signal processing and computing framework as they can be deployed on ultra-low power neuromorphic computing systems, for this purpose. Here, we introduce a novel SNN architecture, co-designed and validated on a mixed-signal neuromorphic chip, that shows potential for always-on monitoring of epileptic activity. We demonstrate how the hardware implementation of this SNN captures the phenomenon of partial synchronization within neural activity during seizure periods. We assess the network using a full-custom asynchronous mixed-signal neuromorphic platform, processing analog signals in real-time from an Electroencephalographic (EEG) seizure dataset. The neuromorphic chip comprises an analog front-end (AFE) signal conditioning stage and an asynchronous delta modulation (ADM) circuit directly integrated on the same die, which can produce the stream of spikes as input to the SNN, directly from the analog EEG signals. We show a linear classifier in a post processing stage that is sufficient to reliably classify and detect seizures, from the local features extracted by the SNN, indicating the feasibility of full on-chip seizure monitoring in the future. This research marks a significant advancement toward developing embedded intelligent "wear and forget" units for resource-constrained environments. These units could autonomously detect and log relevant EEG events of interest in out-of-hospital environments, offering new possibilities for patient care and management of neurological disorders.

neuroscience↗

bioRxiv2024

Stress hyperglycemia exacerbates inflammatory brain injury after stroke

Post-stroke hyperglycemia occurs in 30% - 60% of ischemic stroke patients as part of the systemic stress response, but neither clinical evidence nor pre-clinical studies indicate whether post-stroke hyperglycemia affects stroke outcome. Here we investigated this issue using a mouse model of permanent ischemia. Mice were maintained either normoglycemic or hyperglycemic during the interval of 17 - 48 hours after ischemia onset. Post-stroke hyperglycemia was found to increase infarct volume, blood-brain barrier disruption, and hemorrhage formation, and to impair motor recovery. Post-stroke hyperglycemia also increased superoxide formation by peri-infarct microglia/macrophages. In contrast, post-stroke hyperglycemia did not increase superoxide formation or exacerbate motor impairment in p47phox-/- mice, which cannot form an active superoxide-producing NADPH oxidase-2 complex. These results suggest that hyperglycemia occurring hours-to-days after ischemia can increase oxidative stress in peri-infarct tissues by fueling NADPH oxidase activity in reactive microglia/macrophages, and by this mechanism contribute to worsened functional outcome.

neuroscience↗

bioRxiv2024

Mechanical Analysis of Cell Migration Using Hybrid Structural Optimization

Cell migration requires the dynamic formation and dissolution of mechanical structures inside the cytoplasm. Stress fibers are made of F-actin during cell migration driven by the strategic localization of focal adhesion complexes at the cell-substrate interface. The nucleus is also strategically positioned in the cell during the migration and the stress fibers wrap around the nucleus possibly to carry the nucleus with the cell. Cell migration is energetically demanding and should require strategic utilization of resources such as the F-actin stress fiber formation at specific locations so that they generate enough force by actomyosin contraction at the cell-matrix adhesion sites for a directed movement. In this work we propose a structural optimization based biophysical model to predict the strategic localization and sizes of F-actin fibers that supports the nucleus and the cytoplasm during migration. With the use of a nonlinear controller via a Newton-Euler-based model of the generated design, we further quantified the force in the stress fibers during migration, with results close to those obtained through experimental methods such as traction force microscopy. The predicted force decreases for a cell that migrates slowly due to a pharmacological perturbation. Such quantification of forces only require the information of the trajectory of the cell that can be readily obtained from time lapse microscopy. With novel microscopy techniques emerging, such biophysical model framework can be combined with traction force microscopy data to achieve unprecedented mechanical information inside and outside cells during migration, which is otherwise not possible by experiments only. SIGNIFICANCECell migration plays a critical role in biological functions. It requires the strategic formation of F-actin stress fibers at specific locations, to generate forces by actomyosin contraction for cells to migrate in a directed manner. The present study predicts the localization and force generated by stress fibers based on the trajectory of the cell, which can be obtained via time lapse microscopy. The technique can complement other techniques such as traction force microscopy to provide mechanical information inside and outside cells during cell migration.

biophysics↗