Biology subjects

Sarkar, A.

Publications and source records attributed to Sarkar, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

Neutrophil extracellular trap stabilization by platelet factor 4 reduces thrombogenicity and endothelial cell injury

Neutrophil extracellular traps (NETs) are abundant in sepsis, and proposed NET-directed therapies in sepsis prevent their formation or accelerate degradation. Yet NETs are important for microbial entrapment, as NET digestion liberates pathogens and NET degradation products (NDPs) that deleteriously promote thrombosis and endothelial cell injury. We proposed an alternative strategy of NET-stabilization with the chemokine, platelet factor 4 (PF4, CXCL4), which we have shown enhances NET-mediated microbial entrapment. We now show that NET compaction by PF4 reduces their thrombogenicity. In vitro, we quantified plasma thrombin and fibrin generation by intact or degraded NETs and cell-free (cf) DNA fragments, and found that digested NETs and short DNA fragments were more thrombogenic than intact NETs and high molecular weight genomic DNA, respectively. PF4 reduced the thrombogenicity of digested NETs and DNA by interfering, in part, with contact pathway activation. In endothelial cell culture studies, short DNA fragments promoted von Willebrand factor release and tissue factor expression via a toll-like receptor 9-dependent mechanism. PF4 blocked these effects. Cxcl4-/- mice infused with cfDNA exhibited higher plasma thrombin anti-thrombin (TAT) levels compared to wild-type controls. Following challenge with bacterial lipopolysaccharide, Cxcl4-/- mice had similar elevations in plasma TAT and cfDNA, effects prevented by PF4 infusion. Thus, NET-stabilization by PF4 prevents the release of short fragments of cfDNA, limiting the activation of the contact coagulation pathway and reducing endothelial injury. These results support our hypothesis that NET-stabilization reduces pathologic sequelae in sepsis, an observation of potential clinical benefit. HIGHLIGHTSO_LIIn contrast to intact NETs, degraded NETs and cfDNA are prothrombotic and injure the endothelium. C_LIO_LIPF4 reduces the ability of degraded NETs and cfDNA to promote thrombosis and injure the endothelium. C_LI

cell biology↗

bioRxiv2023

Resolving the heterogeneity of L1 DNA methylation reveals the epigenetic and transcriptional interplay between L1s and their integration sites.

Long interspersed element-1 (L1) retrotransposons play important roles in human disease and evolution. Their global activity is repressed by DNA methylation, but studying the regulation of individual copies has been difficult. Here, we combine short- and long-read sequencing to resolve the DNA methylation profiles of these repeated sequences in a panel of normal and cancer cells genome-wide at single-locus resolution. We unveil key principles underpinning L1 methylation heterogeneity among cell-types, families and integration sites. First, intronic L1 methylation is intimately associated with gene transcription. Conversely, L1s can influence the methylation status of the upstream region over short distances (300 bp). This phenomenon is accompanied by the binding of specific transcription factors, which drive the expression of L1 and chimeric transcripts. Finally, L1 hypomethylation alone is generally insufficient to trigger L1 expression due to redundant silencing pathways. Our results illuminate the epigenetic and transcriptional interplay between retrotransposons and their host genome. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/522582v3_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@c78bbcorg.highwire.dtl.DTLVardef@a7112dorg.highwire.dtl.DTLVardef@58abf2org.highwire.dtl.DTLVardef@180d055_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIBs-ATLAS-seq profiles L1 position and methylation genome-wide C_LIO_LIL1 has a frequent but short-range (300 bp) influence on the DNA methylation status of the upstream sequence C_LIO_LIHypomethylated L1s are bound by tissue-specific transcription factors which drive L1 and chimeric transcripts synthesis C_LIO_LIL1 hypomethylation alone is insufficient to enable its transcription at most loci C_LI

genomics↗

bioRxiv2022

A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms. Author summaryPredicting phenotypes from genotypes is a fundamental problem in quantitative genetics. Thanks to recent advances, it is increasingly feasible to collect data on many phenotypes and genome-wide genotypes in large samples. Here, we tackle the problem of predicting multiple phenotypes from genotypes using a new method based on a multivariate, multiple linear regression model. Although the use of a multivariate, multiple linear regression model is not new, in this paper we introduce a flexible and computationally efficient empirical Bayes approach based on this model. This approach uses a prior that captures how the effects of genotypes on phenotypes are shared across the different phenotypes, and then the prior is adapted to the data in order to capture the most prominent sharing patterns present in the data. We assess the benefits of this flexible Bayesian approach in simulated genetic data sets, and we illustrate its application in predicting gene expression measured in multiple human tissues. We show that our methods can outperform competing methods in terms of prediction accuracy, and the computations involved in fitting the model and making the predictions scale well to large data sets.

genetics↗

bioRxiv2022

Prevention of thrombocytopenia and thrombosis in heparin-induced thrombocytopenia (HIT) using deglycosylated KKO: A novel therapeutic?

Heparin-induced thrombocytopenia (HIT) is characterized by mild thrombocytopenia associated with a highly prothrombotic state due to the development of pathogenic antibodies that recognize human (h) platelet factor 4 (PF4) complexed with various polyanions. While non-heparin anticoagulants and intravenous immunoglobulin (IVIG) are the mainstay of care, bleeding may develop, and risk of new thromboembolic events remain. We had described a mouse IgG{kappa}2b antibody KKO that mimics the sentinel features of pathogenic HIT antibodies, including binding to the same neoepitope on hPF4:polyanion complexes. KKO, like HIT IgGs, activates platelets through Fc{gamma}RIIA and induces complement activation. We now asked whether Fc-modified KKO can be used as a novel therapeutic to prevent or treat HIT. Using the endoglycosidase EndoS, we created deglycosylated KKO (DGKKO). DGKKO bound to PF4-polyanion complexes, and blocked Fc{gamma}RIIA-dependent activation of PF4 treated platelets by KKO, 5B9 (another HIT-like monoclonal antibody), and isolated IgGs from HIT patients. DGKKO also decreased complement activation and deposition of C3c on platelets. Injection of DGKKO into "HIT mice" lacking mouse PF4, but transgenic for hPF4 and Fc{gamma}RIIA, prevented and reversed thrombocytopenia when injected before or after KKO, 5B9 or HIT IgG, respectively, in a microfluidic system. DGKKO reversed antibody-induced thrombus growth in HIT mice. In contrast, DGKKO was ineffective in preventing thrombosis by IgG from a patient with the HIT-related disorder, vaccine-induced immune thrombotic thrombocytopenia. Thus, DGKKO may represent a new class of therapeutics for targeted treatment of patients with HIT. Key PointsO_LIDeglycosylated (DG) KKO can reverse thrombocytopenia in a HIT murine model. C_LIO_LIDGKKO can prevent/reverse thrombosis in vitro and in a HIT murine model. C_LI

cell biology↗

bioRxiv2022

Functional connectivity across the human subcortical auditory system using a Gaussian copula graphical model approach with partial correlations

Abstract/SummaryThe auditory system comprises multiple subcortical brain structures that process and refine incoming acoustic signals along the primary auditory pathway. Due to technical limitations of imaging small structures deep inside the brain, most of our knowledge of the subcortical auditory system is based on research in animal models using invasive methodologies. Advances in ultra-high field functional magnetic resonance imaging (fMRI) acquisition have enabled novel non-invasive investigations of the human auditory subcortex, including fundamental features of auditory representation such as tonotopy and periodotopy. However, functional connectivity across subcortical networks is still underexplored in humans, with ongoing development of related methods. Traditionally, functional connectivity is estimated from fMRI data with full correlation matrices. However, partial correlations reveal the relationship between two regions after removing the effects of all other regions, reflecting more direct connectivity. Partial correlation analysis is particularly promising in the ascending auditory system, where sensory information is passed in an obligatory manner, from nucleus to nucleus up the primary auditory pathway, providing redundant but also increasingly abstract representations of auditory stimuli. While most existing methods for learning conditional dependency structures based on partial correlations assume independently and identically Gaussian distributed data, fMRI data exhibit significant deviations from Gaussianity as well as high temporal autocorrelation. In this paper, we developed an autoregressive matrix-Gaussian copula graphical model (ARMGCGM) approach to estimate the partial correlations and thereby infer the functional connectivity patterns within the auditory system while appropriately accounting for autocorrelations between successive fMRI scans. Our results show strong positive partial correlations between successive structures in the primary auditory pathway on each side (left and right), including between auditory midbrain and thalamus, and between primary and associative auditory cortex. These results are highly stable when splitting the data in halves according to the acquisition schemes and computing partial correlations separately for each half of the data, as well as across cross-validation folds. In contrast, full correlation-based analysis identified a rich network of interconnectivity that was not specific to adjacent nodes along the pathway. Overall, our results demonstrate that unique functional connectivity patterns along the auditory pathway are recoverable using novel connectivity approaches and that our connectivity methods are reliable across multiple acquisitions.

neuroscience↗

bioRxiv2022

Targeted nanopore resequencing and methylation analysis of LINE-1 retrotransposons

Retrotransposition of LINE-1 (L1) elements represent a major source of insertional polymorphisms in mammals and their mutagenic activity is restricted by silencing mechanisms, such as DNA methylation. Despite a very high level of sequence identity between copies, their internal sequence contains small nucleotide polymorphisms (SNPs) that can alter their activity. Such internal SNPs can also appear in different alleles of a given L1 locus. Given their repetitive nature and relatively long size, short-read sequencing approaches have limited access to L1 internal sequence or DNA methylation state. Here we describe a targeted method to specifically sequence more than a hundred L1-containing loci in parallel and measure their DNA methylation levels using nanopore long-read sequencing. Each targeted locus is sequenced at high coverage ([~]45X) with unambiguously mapped reads spanning the entire L1 element, as well as its flanking sequences over several kilobases. Our protocol, modified from the nanopore Cas9 targeted sequencing (nCATS) strategy, provides a full and haplotype-resolved L1 sequence and DNA methylation levels. It introduces a streamlined and multiplex approach to synthesize guide RNAs and a quantitative PCR (qPCR)-based quality check during library preparation for cost-effective L1 sequencing. More generally, this method can be applied to any type of transposable elements and organisms.

genomics↗

bioRxiv2022

Allosteric Inhibition of PTP1B by a Nonpolar Terpenoid

Protein tyrosine phosphatases (PTPs) are promising drug targets for treating a wide range of diseases such as diabetes, cancer, and neurological disorders, but their conserved active sites have complicated the design of selective therapeutics. This study examines the allosteric inhibition of PTP1B by amorphadiene (AD), a terpenoid hydrocarbon that is an unusually selective inhibitor. Molecular dynamics (MD) simulations carried out in this study suggest that AD can stably sample multiple neighboring sites on the allosterically influential C-terminus of the catalytic domain. Binding to these sites requires a disordered 7 helix, which stabilizes the PTP1B-AD complex and may contribute to the selectivity of AD for PTP1B over TCPTP. Intriguingly, the binding mode of AD differs from that of the most well-studied allosteric inhibitor of PTP1B. Indeed, biophysical measurements and MD simulations indicate that the two molecules can bind simultaneously. Upon binding, both inhibitors destabilize the 7 helix and disrupt hydrogen bonds that facilitate closure of the catalytically essential WPD loop. These findings indicate that AD is a promising scaffold for building allosteric inhibitors of PTP1B and illustrate, more broadly, how unfunctionalized terpenoids can engage in specific interactions with protein surfaces.

biochemistry↗

bioRxiv2022

Topology Adaptive Graph Convolution Network With Heterogeneous Entities For Predicting Adverse Events from Drug-Drug-Interactions

In times like this, it is imperative to be cautious about the effects of drugs or vaccination doses on patients who are already suffering from other serious diseases. Its not only the virus which can affect the body metabolisms, drugs to encounter the virus may also end up having unwanted negative effects. Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions and inadvertent side effects. Therefore, prediction and identification of DDIs are extremely vital for patient safety and treatment modalities. In this context, we intend to develop a computational method based on functional similarity of drugs. Our objective has been enhanced by the usage of knowledge graphs which allows capturing underlying information embeddings in a biological network with heterogenous entities. On providing this knowledge graph as the input to a Topology Adaptive Graph Convolution Network which performs topologically-aware flexible convolutions, we achieve improvements on priorly proposed GCN models that has been shown as comparison.

bioinformatics↗

bioRxiv2022

LDL1 and LDL2 histone demethylases interact with FVE to regulate flowering in Arabidopsis

In higher plants, epigenetic modifications provide a stage for both transient and permanent cellular reprogramming required for vegetative to reproductive phase transition. Arabidopsis LSD1-like 1 (LDL1), a histone demethylase positively regulates floral transition, but the molecular and biochemical nature of LDL1 mediated flowering is poorly understood. Here we have shown that LDL1 mediated regulation of flowering is dependent on MADS AFFECTING FLOWERING 4 (MAF4) and MAF5 floral repressors. LDL1 binds on the chromatin of MAF4 and MAF5 and removes H3K4me2 activation marks to repress their expression. Further we show that LDL2 negatively regulates the expression of MAF4 and MAF5 redundantly with LDL1. Both LDL1 and LDL2 interact with an autonomous flowering pathway protein, FLOWERING LOCUS VE (FVE), to regulate the floral transition and thus could be a part of the FVE-corepressor complex. We show that MAF5 interacts with other floral repressors FLC and SHORT VEGETATIVE PHASE (SVP) and repress the expression of FT to delay floral transition. Thus, our results deepen the mechanistic understanding of LDL1/LDL2-FVE mediated floral transition in Arabidopsis.

plant biology↗

bioRxiv2022

Unlocking the microblogging potential for science and medicine

Microblogging platform Twitter allows researchers to showcase their work, receive constructive feedback, find jobs, and build scientific collaborations. While existing literature has analyzed the benefits of Twitter in the development and distribution of scientific knowledge, most of the studies only took into account a limited number of researchers, which affected the generalizability of derived results. Our study analyzed the activity of 6,000 biomedical scientists on Twitter using data-driven approaches, a third of whom were female. Furthermore, we estimated that up to a quarter of the members of the scientific community are engaged on Twitter. While the number of male scientists joining the microblogging platform every year has decreased, the number of female scientists has remained roughly the same. Scientists are very selective in who they are following as compared to the general public. We also found that the type of tweets and retweets one posts may affect the number of followers, specifically, that a moderate to high level of professionalism and a high level of positivity is correlated with followers count. Moreover, female scientists send fewer negative tweets as compared to male scientists (31.1% for females and 34.7% for males). Our analysis could provide insights and launch a conversation on the advantages and limitations of using Twitter for disseminating scientific information and engaging in constructive discussion and collaborations within the scientific community.

scientific communication and education↗

bioRxiv2022

Antibodies targeting conserved non-canonical antigens and endemic coronaviruses associate with favorable outcomes in severe COVID-19

While there have been extensive analyses characterizing cellular and humoral responses across the severity spectrum in COVID-19, predictors of outcomes within severe COVID-19 remain to be comprehensively elucidated. Recently, we identified divergent monocyte states as predictors of outcomes within severe COVID-19, but corresponding humoral profiles of risk have not been delineated. Furthermore, the nature of antibodies (Abs) directed against viral antigens beyond the spike protein or endemic coronavirus antigens and their associations with disease severity and outcomes remain poorly defined. We performed deep molecular profiling of Abs directed against a wide range of antigenic specificities in severe COVID-19 patients admitted to the ICU. The profiles consisted of canonical (S, RBD, N) and non-canonical (orf3a, orf8, nsp3, nps13 and M) antigenic specificities. Notably, multivariate machine learning (ML) models, generated using profiles of Abs directed against canonical or non-canonical antigens, were equally discriminative of recovery and mortality COVID-19 outcomes. In both ML models, survivors were associated with increased virus-specific IgA and IgG3 antibodies and with higher antigen-specific antibody galactosylation. Intriguingly, pre-pandemic healthy controls had cross-reactive Abs directed against nsp13 which is a conserved protein in other alpha and beta coronaviruses. Notably, higher levels of nsp13-specific IgA antibodies were associated with recovery in severe COVID-19. In keeping with these findings, a model built on Ab profiles for endemic coronavirus antigens was also predictive of COVID-19 outcome bifurcation, with higher levels of IgA and IgG3 antibodies against OC43 S and NL63 S being associated with survival. Our results suggest the importance of Abs targeting non-canonical SARS-CoV-2 antigens as well as those directed against endemic coronaviruses in favorable outcomes of severe COVID-19.

immunology↗

bioRxiv2022

Signaling modality within gp130 receptor enhances tissue regeneration

Adult mammals are incapable of multi-tissue regeneration and augmentation of this potential may drastically shift current therapeutic paradigms. Here, we found that a common co-receptor of IL-6 cytokines, glycoprotein 130 (gp130), serves as a major nexus integrating various context-specific signaling inputs to either promote regenerative outcomes or aggravate disease progression. Via genetic and pharmacological experiments in vitro and in vivo, we demonstrated that a signaling tyrosine 814 (Y814) within gp130 serves as a major cellular stress sensor. Mice with constitutively inactivated Y814 (F814) exhibit regenerative, not reparative, responses after wounding in skin and anti-degenerative responses in the synovial joint. In addition, pharmacological inhibition of gp130 Y814 results in regeneration of multiple tissues in several species as well as disease modification in animal models of osteoarthritis. Our study characterizes a novel molecular mechanism that, if selectively manipulated, enhances the intrinsic regenerative capacity while preventing pathological outcomes in injury and disease. SummaryGp130 Y814 signaling module serves as a cellular stress sensor responsible for hindering tissue regeneration while triggering pathological outcomes after injury.

molecular biology↗

bioRxiv2021

Quinacrine binds to the kinase domain of FGFR1 and inhibits its activity

BackgroundFGF family receptors, especially FGFR1, have been widely implicated for their potential role in the promotion of oncogenesis and chemoresistance in lung cancer. Quinacrine, an anti-malarial drug, has been widely reported to exhibit anti-neoplastic properties through the activation of p53 and simultaneous inhibition of NF-kB signaling pathways in cancer cells. MethodsThe binding of QC to FGFR1 was studied using molecular docking and molecular dynamics simulation studies. The experimental kinase activity assay for the protein was performed using a luminescence-based kinase assay. FGF-induced phosphorylation and proliferation were studied by cell counting and western blotting. Matrigel-based cell migration was conducted to assess migration activity. ResultsQC interacted with multiple residues around the kinase insert domain of FGFR1 through hydrogen bonding, hydrophobic interactions, and water bridges. The kinase activity inhibition assay demonstrated a significant reduction in FGFR1 kinase activity by QC at higher concentrations, which was further observed at the cellular level in inhibition of FGFR1 phosphorylation and proliferation by QC at higher exposure concentrations of FGF stimulated cells. These effects were further validated downstream in the FGF-induced activation of cell migration. ConclusionQC did form a stable interaction with residues of FGFR1 at another allosteric site surrounding the kinase domain, leading to inhibition of its kinase activity at higher drug concentrations. This effect was further observed at the cellular level in both acidic and basic FGF ligand-induced proliferation, phosphorylation of FGFR1, and cell migration, where a trend of significant reduction in activity was observed at higher drug concentrations.

cancer biology↗

bioRxiv2021

The systematic assessment of completeness of public metadata accompanying omics studies

Recent advances in high-throughput sequencing technologies have made it possible to collect and share a massive amount of omics data, along with its associated metadata. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability by reducing sample interpretability and limiting secondary analyses. In this study, we performed a comprehensive assessment of metadata completeness shared in both scientific publications and/or public repositories by analyzing over 253 studies encompassing over 164 thousands samples, including both human and non-human mammalian studies. We observed that studies often omit over a quarter of important phenotypes, with an average of only 74.8% of them shared either in the text of publication or the corresponding repository. Notably, public repositories alone contained 62% of the metadata, surpassing the textual content of publications by 3.5%. Only 11.5% of studies completely shared all phenotypes, while 37.9% shared less than 40% of the phenotypes. Studies involving non-human samples were more likely to share metadata than studies involving human samples. We observed similar results on the extended dataset spanning 2.1 million samples across over 61,000 studies from the Gene Expression Omnibus repository. The limited availability of metadata reported in our study emphasizes the necessity for improved metadata sharing practices and standardized reporting. Finally, we discuss the numerous benefits of improving the availability and quality of metadata to the scientific community and beyond, supporting data-driven decision-making and policy development in the field of biomedical research. This work provides a scalable framework for evaluating metadata availability and may help guide future policy and infrastructure development.

bioinformatics↗

bioRxiv2021

Hepatocyte Cell Cycle Progression Depends on a Transcriptional Repressor Cascade Downstream of Wnt Signaling

Cell proliferation is tightly controlled by inhibitors that block cell cycle progression until growth signals relieve this inhibition. In several tissues including the liver, transcriptional repressors such as E2F7 and E2F8 function as inhibitors of mitosis and promote polyploidy, but how growth factors release these mitotic inhibitors to facilitate cell cycle progression is unknown. We describe here a newly identified mechanism of cell division control in which Wnt/{beta}catenin signaling in the postnatal liver maintains active hepatocyte proliferation through Tbx3, a Wnt target gene. TBX3 directly represses transcription of E2f7 and E2f8, promoting a low ploidy state and cell cycle progression. This sequential transcriptional repressor cascade, initiated by Wnts, provides a new paradigm for exploring how a commonly active developmental signal impacts cell cycle completion.

cell biology↗

bioRxiv2021

Intermittent fasting induces rapid hepatocyte proliferation

Nutrient availability fluctuates in most natural populations, forcing organisms to undergo periods of fasting and re-feeding. It is unknown how dietary changes influence liver homeostasis. Here, we show that a switch from ad libitum feeding to intermittent fasting, IF, promotes rapid hepatocyte proliferation. Mechanistically, IF-induced hepatocyte proliferation is driven by the combined action of intestinally produced, systemic endocrine FGF15 and localized WNT signaling. Hepatocyte proliferation during periods of fasting and re-feeding re-establishes a constant liver-to-body-mass ratio, thus maintaining the hepatostat. This study provides the first example of dietary influence on adult hepatocyte proliferation and challenges the widely held view that liver tissue is mostly quiescent unless chemically or mechanically injured.

cell biology↗

bioRxiv2021

gp130/STAT3 signaling is required for homeostatic proliferation and anabolism in postnatal growth plate and articular chondrocytes

Growth of long bones and vertebrae is maintained postnatally by a long-lasting pool of progenitor cells. Little is known about the molecular mechanisms that regulate the output and maintenance of the cells that give rise to mature cartilage. Here we demonstrate that postnatal chondrocyte-specific deletion of a transcription factor Stat3 results in severely reduced proliferation coupled with increased hypertrophy, growth plate fusion, stunting and signs of progressive dysfunction of the articular cartilage. This effect is dimorphic, with females more strongly affected than males. Chondrocyte-specific deletion of the IL-6 family cytokine receptor gp130, which activates Stat3, phenocopied Stat3-deletion; deletion of Lifr, one of many co-receptors that signals through gp130, resulted in a milder phenotype. These data define a new molecular circuit that regulates chondrogenic cell maintenance and output and reveals a novel, hitherto unrecognized function of IL-6 cytokines in the skeletal system with direct implications for skeletal development and regeneration.

cell biology↗

bioRxiv2021

A force-balance model for centrosome positioning and spindle elongation during Interphase and Anaphase B

A computational model in one dimension is proposed to position a single centrosome using astral microtubules (MTs) interacting with the cell cortex. The mechanism exploits mutually antagonistic pulling and pushing forces arising from the astral MTs binding to cortical dynein motors in the actin-rich cell cortex and their buckling while growing against the cell cortex, respectively. The underlying mechanism is extended to account for the elongation and positioning of the bipolar spindle during mitotic anaphase B. Besides astral MTs, the model for bipolar spindle involves interpolar microtubules (IPMTs). The composite model can predict spindle elongation and position under various circumstances. The outcome reveals that the bipolar spindle elongation, weakened by decreasing overlap between the antiparallel IPMTs in the spindle mid-zone, is recovered by the astral MTs. The one-dimensional models are extended in two dimensions to include the effect of cortical sliding of the astral MTs for studying the dynamics of the interphase centrosome and the anaphase B spindles in elongated cells. The results reveal that the dynamics in two dimensions stay qualitatively similar to the one dimension.

biophysics↗