Biology subjects

Jensen, H.

Publications and source records attributed to Jensen, H..

17 recordsLinked to original sources

bioRxiv2026

IntravChip: a vascularized and perfused microfluidic model of the primary tumor microenvironment to collect intravasated tumor cells

Hematogenous metastasis is initiated when tumor cells (TCs) intravasate into the vasculature, yet intravasation remains poorly understood because it is difficult to observe in vivo and intravasated TCs are challenging to isolate. To address these challenges, we developed IntravChip, a continuously perfused microfluidic platform containing a vascularized primary tumor microenvironment (TME) enabling the observation of TC intravasation, and a downstream chamber to collect intravasated TCs. The IntravChip can support a high TC concentration in the TME while maintaining complete vascular perfusion, which we found was necessary to collect intravasated cells. Using MDA-MB-231 breast TCs, we identified an optimal initial TC seeding density that, by day 9, yields a densely populated TME and 100-440 collected intravasated TCs. We validated the IntravChip across several TC types, showing that MDA-MB-231 and MV3 TCs have the highest intravasation rates while MCF-7 TCs have low intravasation efficiency. We also show that the IntravChip is compatible with super-resolution nano-imaging. Our devices enabled high-quality STORM imaging, which revealed that H3K9me3 nanodomains are significantly differentially distributed in intravasated MDA-MB-231 tumor cells compared to those residing in the TME. Finally, the IntravChip was validated as a platform to test the effects of anti-cancer drugs on tumor cells and on the vasculature. We showed that a 5 M concentration of sorafenib reduced intravasation events by 69% without impacting the morphology of the microvascular networks (MVNs), while a 10 M concentration led to a significant decrease in vessel diameter. This platform enables quantitative analysis of TC intravasation, collection of intravasated TCs for characterization, and screening of anti-metastatic therapies.

bioengineering↗

bioRxiv2025

How Accurate is Genomic Prediction Across Wild Populations?

Evolutionary ecology seeks to understand causes and consequences of evolutionary changes across time and space, and genomic data present novel opportunities to investigate these processes. Genomic prediction - that is, predicting individual genetic values from high-density marker data - has revolutionized breeding programs and medical genetics. In wild populations, however, genomic prediction has been used in only a handful of studies, and only within populations. There is still a lack of applications that predict across wild populations, which could provide answers to questions related to spatially varying evolutionary processes, such as local adaptation. A severe challenge for across-population genomic prediction, however, is the decrease in accuracy when models are trained on data from one population and predict genetic values in another. Here, we used genomic prediction to predict across wild house sparrow populations, and compared the accuracy to within-population prediction. Predictions across populations were less accurate and more variable than within populations. We also highlighted limitations of the current theory for general genomic prediction accuracy, and related across-population accuracy to several population differentiation measures. Our results underline the necessity of understanding why genomic prediction currently performs poorly across populations, and of developing methods that exploit genomic data in novel ways.

evolutionary biology↗

bioRxiv2025

Experimental Removal of Niche Construction Alters the Pace and Mechanisms of Resistance Evolution

Niche construction, a central eco-evolutionary process in which organisms modify their environment, is hypothesised to enhance evolutionary adaptability through feedback between genetic inheritance and the lasting effects of environmental change--known as ecological inheritance. However, while theoretically intriguing, direct empirical support for the effect of niche construction on adaptation is lacking. Red flour beetles modify their environment by releasing quinone-rich stink gland secretions, a form of external immunity. Here, we test in an evolution experiment how experimental removal of niche construction--using RNAi of a key gene needed to produce stink gland secretions--affects the beetles adaptation to the bacterial entomopathogen Bacillus thuringiensis. In each generation, beetles inhabited conditioned flour either with regular or drastically reduced stink gland secretion content. Compared to the non-exposed control, all bacteria-exposed regimes rapidly evolved bacterial resistance within only six generations. However, beetles evolving with intact niche construction acquired resistance as soon as after three generations, indicating that adaptation was initially facilitated by niche construction. RNAseq of evolved beetles showed that gene expression differed strongly between the selection regimes, revealing that the mechanisms underlying resistance were dependent on niche construction. Thus, our findings provide urgently needed empirical evidence on the role of niche construction for resistance evolution and its potential genetic basis.

evolutionary biology↗

bioRxiv2025

In-solution Characterization of Biomolecular Interaction Kinetics under Native Conditions

Characterizing the kinetics of biomolecular interactions is fundamental for understanding biological mechanisms, devel-oping novel drugs for advancing healthcare and for optimizing processes in protein engineering. Although modern sur-face-based methods have advanced our understanding of protein-protein and protein-ligand kinetics, they rely on immobilized samples, preventing the study of interactions under native conditions and leading to an incomplete understanding. In this work, we propose a paradigm shift by introducing a new method based on flow-induced dispersion analysis to study interaction kinetics while keeping biomolecules in solution, eliminating the need for surface immobilization and thereby preserving molecular mobility and avoiding structural constraints. The method examines reactions outside equilibrium conditions by inducing a rapid concentration change in one of the binding partners (C-Jump) in a controlled microfluidic environment. Notably, it operates without buffer restrictions and requires only minimal sample quantities. We demonstrate C-Jumps capability by accurately determining the association and dissociation rates of both protein-protein and protein-small molecule interactions. Furthermore, we validate its robustness by measuring the rates of a protein-protein interaction in human serum as well as a protein-small molecule interaction in-solution and label free. This under-lines C-Jumps broad applicability for studying biomolecular interactions under native conditions, offering a powerful tool for advancing protein engineering and drug discovery, as well as enabling the characterization of previously inaccessible interactions. TABLE OF CONTENTThis work presents C-Jump, a breakthrough method for the direct measurement of kinetic rates in solution, closely mimicking physiological conditions. Utilizing flow-induced dispersion analysis, C-Jump determines rate constants with high accuracy for protein-protein and protein- small molecule interactions. Free from buffer constraints and requiring only nanograms of protein, it can operate label-free, transforming biomolecular interaction studies across biophysics, chemistry, and medicine. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/645748v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@11385ceorg.highwire.dtl.DTLVardef@b5d88forg.highwire.dtl.DTLVardef@9cc2cforg.highwire.dtl.DTLVardef@1b9d17c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Natural Killer Cell Receptor Signaling and Activation Depend on Cell Cycle Stages

Receptor signaling in Natural Killer (NK) cells leads to post-translational modification (e.g., phosphorylation) of sub-cellular signaling proteins within minutes of receptor stimulation that eventually give rise to diverse effector functions including cell proliferation. Recent single-cell mass cytometry (i.e., CyTOF) experiments in macrophages showed variations of abundances of phosphorylated signaling proteins across cell cycle states indicating a dependence of cell signaling kinetics on an order of magnitude slower kinetics (~ several hours) of cell cycle transitions. We investigated cell cycle dependence of NKG2D signaling kinetics in NK cells by CyTOF measurements performed on IL-2-treated NKG2D-stimulated primary human CD56dim NK cells. The CyTOF experiments revealed monotonic or semi-monotonic increases of the average protein abundances of the majority of signaling proteins such as pCrkL, pPLC{gamma}2, and pErk, and the degranulation marker protein CD107a with progressing cell cycle states at specific time points post-NKG2D stimulation; however, several proteins such as pVav1, pS6, and pAkt, and early activation marker protein CD69 also showed non-monotonic variations in the average abundances with progressing cell cycle states. We used minimal mathematical and computational models coupling signaling and cell cycle processes to show that non-monotonic variations in the signaling protein abundances with progressing cell cycle stages are likely to arise in situations where protein synthesis and degradation and signaling kinetics are actively regulated by cell cycle processes.

immunology↗

bioRxiv2024

Continuous Titration Based Method For Rapid In-solution Analysis Of Non-covalent Interactions

Development of new drugs typically involves the identification and validation of molecular inhibitors or promotors of endogenous biological processes. The identification of ligands that can bind the target of interest is typically achieved by screening large libraries of small molecules, using analytical methods that only provide yes/no answers. These methods are only qualitative and often associated with unacceptable amounts of false positives and negatives. Quantitative methods are in general more accurate but time intensive. This is mainly due to repeating measurements of a dilution series in order to generate a titration curve and measure the dissociation constant (Kd). In this work, we introduce Continuous Titration Based Spectral Related Intensity Change (cSPRING), that combines Taylor dispersion analysis (TDA) with ratiometric fluorescence detection to measure a Kd in a single experiment. cSPRING is an in-solution method that reduces the sample preparation time 8-fold and requires only nanograms of protein. We show a good agreement of cSPRING with other quantitative methods for three well-known protein-small molecule interactions with binding affinities ranging from the low nanomolar to high micromolar. In addition, we show that cSPRING is able to measure binding affinities in under a minute, highlighting its efficiency and potential for screening applications.

biophysics↗

bioRxiv2024

Rapid loss of genetic variation and increased inbreeding in small and isolated populations of Norwegian wild reindeer

Wildlife responses to habitat loss and fragmentation are a central concern in the management and conservation of biodiversity. Small and isolated populations are vulnerable, both due to demographic and genetic mechanisms, which are often linked. Thus, understanding how (changes in) genetic diversity, effective population sizes, and levels of inbreeding relate to population size and degree of isolation is key for developing effective conservation strategies. High-density Single Nucleotide Polymorphism (SNP) arrays represent an increasingly cost-efficient tool to achieve the data needed for such analysis. Here, we present the development of a novel 625k SNP array for reindeer Rangifer tarandus and apply this array to assess conservation genetic issues across thirteen Norwegian wild reindeer populations of varying size, isolation, and genetic origin (i.e., semi-domesticated reindeer origin or a mix of wild reindeer and semi-domesticated reindeer origins). Many of these populations are currently completely isolated, with no gene flow from other populations. We genotyped n = 510 individuals sampled by hunters and found that variation in population size across the populations largely predicted their (recent loss of) genetic variation (observed heterozygosity, Ho), as well as effective population size (Ne) and (change in) level of recent inbreeding. For the smallest and most isolated populations, with total population sizes of <50-100 individuals and a high and increasing level of recent inbreeding, estimated loss of genetic variation was as high as 3-10% over the time span of a generation or less, and estimated Ne was as low as six individuals. With the current level of isolation and associated lack of gene flow, and considering their already low genetic diversity, these populations are hardly viable - neither demographically nor genetically - in the long term. These results have direct relevance for the management of Norwegian wild reindeer, recently red-listed as Near Threatened. Yet, these genetic challenges, characterizing many of the small wild reindeer populations in Norway, have been largely ignored by management thus far. Mitigation efforts such as reducing barriers would introduce substantial conservation dilemma due to the aim of avoiding further spread of chronic wasting disease (CWD), as well as potential further domestic introgression into populations with genetically wild reindeer (or mixed) origin. Nevertheless, our cost-efficient and high-density SNP array especially designed for reindeer and caribou offers a powerful genetic tool to include in future monitoring, providing important contributions to management and conservation decisions.

genetics↗

bioRxiv2024

Bayesian marker-based principal component ridgeregression - a flexible multipurpose framework forquantitative genetics in wild study systems

As larger genomic data sets become available for wild study populations, the need for flexible and efficient methods to estimate and predict quantitative genetic parameters, such as the adaptive potential and measures for genetic change, increases. Animal breeders have produced a wealth of methods, but wild study systems often face challenges due to larger effective population sizes, environmental heterogeneity and higher spatio-temporal variation. Here we adapt methods previously used for genomic prediction in animal breeding to the needs of wild study systems. The core idea is to approximate the breeding values as a linear combination of principal components (PCs), where the PC effects are shrunk with Bayesian ridge regression. Thanks to efficient implementation in a Bayesian framework using integrated nested Laplace approximations (INLA), it is possible to handle models that include several fixed and random effects in addition to the breeding values. Applications to a Norwegian house sparrow meta-population, as well as simulations, show that this method efficiently estimates the additive genetic variance and accurately predicts the breeding values. A major benefit of this modeling framework is computational efficiency at large sample sizes. The method therefore suits both current and future needs to analyze genomic data from wild study systems.

evolutionary biology↗

bioRxiv2024

Disentangling the age-dependent causal pathways affecting multiple paternity in house sparrows

The causes of variation in multiple paternity (MP) in socially monogamous birds have received considerable attention. Traits like age and age-dependent morphology have been shown to be important for the distribution of MP. However, most studies fail to separate between the different processes underlying age-effects on MP, such as selective disappearance (that is, higher survival probability for certain phenotypes) versus individually plastic changes in morphology and mating behaviour with age. Using Bayesian multi-level path analysis on a long-term dataset from a house sparrow (Passer domesticus) metapopulation, we disentangle the effects of age on male and female MP, both independently from and through morphological traits. Age was a key determinant of MP for males when accounting for morphological traits, with males having MP more often as they get older (plastic component of age) and not due to disappearance of males unsuccessful to get MP (selective disappearance), challenging good genes explanations for MP. Conversely, selective disappearance explained the higher levels of MP in older females, suggesting that higher quality females have MP more often than lower quality females. We show how an appropriate statistical decomposition of age-components and age-dependent processes provides insights to the biological drivers of MP.

ecology↗

bioRxiv2023

Fibril Paint to detect Amyloids and determine Fibril Length

Tau aggregation into amyloid fibrils is linked to the development of neurodegenerative diseases, including Alzheimers Disease. The molecular processes underlying aggregation in disease are poorly understood. Here, we introduce FibrilPaint1 as a tool to measure the size of Tau amyloid fibrils in fluids, from early aggregation stages to mature fibrils. FibrilPaint1 is a 22mer peptide with many exciting properties, which makes it a tool for diagnostics and an attractive start point for developing a class of effective fibril targeting degraders: (i) FibrilPaint1 binds fibrils with nanomolar affinity; (ii) it does also bind to oligomeric precursors, down to a size of only 4 layers; (iii) it does not bind to monomers (KD > 100 {micro}M); (iv) it is fluorescently labelled, which allows monitoring and localising interactions. (v) FibrilPaint1 recognises various Tau fibrils, including patient derived fibrils from Alzheimer, Corticobasal degeneration and Frontotemporal dementia; (vi) FibrilPaint1 is selective for the amyloid state and does not have background binding to amorphous aggregates, blood serum or cell lysate. In combination with Flow Induced Dispersion Analysis (FIDA), a microfluidics technology, we determined the molecular size of amyloid fibrils with sub-microliter sample volumes. This set-up acts as a molecular ruler at layer resolution - we determined Tau fibril length from 4 to 1100 layers in solution. This is an interesting parameter that can be used for diagnostic applications and biochemical research in dementia.

biochemistry↗

bioRxiv2023

Sex-differences in the genetic architecture of individual recombination rates in wild house sparrows (Passer domesticus).

Meiotic recombination through chromosomal crossing-over is a fundamental feature of sex and an important driver of genomic diversity. It ensures proper disjunction, allows increased selection responses, and prevents mutation accumulation; however, it is also mutagenic and can break up favourable haplotypes. This cost/benefit dynamic is likely to vary depending on mechanistic and evolutionary contexts, and indeed, recombination rates show huge variation in nature. Identifying the genetic architecture of this variation is key to understanding its causes and consequences. Here, we investigate individual recombination rate variation in wild house sparrows (Passer domesticus). We integrate genomic and pedigree data to identify autosomal crossover counts (ACC) and intra-chromosomal allelic shuffling ([r]intra) in 13,056 gametes. Females had 1.37 times higher ACC, and 1.55 times higher[r] intra than males. ACC and[r] intra were heritable in females and males (ACC h2 = 0.23 and 0.11;[r] intra h2 = 0.12 and 0.14), but cross-sex additive genetic correlations were low (rA = 0.29 and 0.32 for ACC and[r] intra). Conditional bivariate analyses showed that all measures remained heritable after accounting for genetic values in the opposite sex, indicating that sex-specific ACC and[r] intra can evolve somewhat independently. Genome-wide models showed that ACC and[r] intra are polygenic and driven by many small-effect loci, many of which are likely to act in trans as global recombination modifiers. Our findings show that recombination rates of females and males can have different evolutionary potential in wild birds, providing a compelling mechanism for the evolution of sexual dimorphism in recombination.

genetics↗

bioRxiv2022

Contrasting genomic consequences of anthropogenic reintroduction and natural recolonisation in high-arctic wild reindeer

Anthropogenic reintroduction can supplement natural recolonisation in reestablishing a species distribution and abundance. However, both reintroductions and recolonisations can give rise to population bottlenecks that reduce genetic diversity and increase inbreeding, potentially causing accumulation of genetic load and reduced fitness. Most current populations of the endemic high-arctic Svalbard reindeer (Rangifer tarandus platyrhynchus) originate from recent reintroductions or recolonisations following regional extirpations due to past overharvesting. We investigated and compared the genomic consequences of these two paths to reestablishment using whole-genome shotgun sequencing of 100 Svalbard reindeer across their range. We found little admixture between reintroduced and natural populations. Two reintroduced populations, each founded by 12 individuals around four decades (i.e. 8 reindeer generations) ago, formed two distinct genetic clusters. Compared to the source population, these populations showed only small decreases in genome-wide heterozygosity and increases in inbreeding and lengths of runs of homozygosity. In contrast, the two naturally recolonised populations without admixture possessed much lower heterozygosity, higher inbreeding, and longer runs of homozygosity, possibly caused by serial population bottlenecks and/or fewer or more genetically related founders than in the reintroduction events. Naturally recolonised populations can thus be more vulnerable to the accumulation of genetic load than reintroduced populations. This suggests that in some organisms even small-scale reintroduction programs based on genetically diverse source populations can be more effective than natural recolonisation in establishing genetically diverse populations. These findings warrant particular attention in the conservation and management of populations and species threatened by habitat fragmentation and loss.

genomics↗

bioRxiv2022

DNA methylation regulates sex-biased gene expression in the house sparrow

Sexual dimorphism is often mediated by tissue-specific, differential gene expression, but the mechanisms that regulate these gene expression patterns are not well understood. Here, we investigate DNA methylation as a potential regulator of sex-biased gene expression in the house sparrow (Passer domesticus). First, we examine whether sex-bias in gene expression or DNA methylation is present in this species, and whether any sex differences are tissue-general or tissue-specific. Second, we assess the correlation between gene expression and DNA methylation at different genomic features in several tissues. Samples clustered by tissue type when looking at both gene expression and DNA methylation, and in gonads samples clustered according to sex. We demonstrate sex-bias in DNA methylation and gene expression on the Z-chromosome as well as on autosomes, but find that most of the sex-biased genes are tissue-specific and that the majority of sex-bias occurs in gonads, although some tissue-general sex differences were observed. This underscores the importance of choosing a tissue relevant to the studied phenotype in DNA methylation or gene expression studies. We find strong negative correlation between DNA methylation and gene expression at the transcription start site (TSS), and that the TSS of highly expressed genes is hypomethylated in comparison to the TSS of genes with low expression. Furthermore, we show that sex-biased DNA methylation can account for 14% of the sex differences in gene expression in gonads. Together these results indicate that DNA methylation differences between the sexes can provide a mechanistic explanation for sex-biased gene expression that likely contributes to trait sexual dimorphism in nature.

evolutionary biology↗

bioRxiv2021

Inbreeding is associated with shorter early-life telomere length in a wild passerine

Inbreeding can have negative effects on survival and reproduction, which may be of conservation concern in small and isolated populations. However, the physiological mechanisms underlying inbreeding depression are not well-known. The length of telomeres, the DNA sequences protecting chromosome ends, has been associated with health or fitness in several species. We investigated effects of inbreeding on early-life telomere length in two small island populations of wild house sparrows (Passer domesticus) known to be affected by inbreeding depression. Using genomic and pedigree-based measures of inbreeding we found that inbred nestling house sparrows have shorter telomeres. This negative effect of inbreeding on telomere length may have been complemented by a heterosis effect resulting in longer telomeres in individuals that were less inbred than the population average. Furthermore, we found some evidence of stronger effects of inbreeding on telomere length in males than females. Thus, telomere length may reveal subtle costs of inbreeding in the wild and demonstrate a route by which inbreeding negatively impacts the physiological state of an organism already at early life-history stages.

molecular biology↗

bioRxiv2021

Genomic estimation of quantitative genetic parameters in wild admixed populations

O_LIHeritable genetic variation among free-living animals or plants is essential for populations to respond to selection and adapt. It is therefore important to be able to estimate additive genetic variance VA, which can be obtained using a generalized linear mixed model known as the animal model. An underlying assumption of the standard animal model is that the study population is genetically unstructured, which is often unrealistic. In fact, admixture might be the norm rather than the exception in the wild, like in geographically structured populations, in the presence of (im)migration, or in re-introduction and conservation contexts. Unfortunately, animal model estimators may be biased in such cases. So-called genetic group animal models that account for genetically differentiated subpopulations have recently become popular, but methodology is currently only available for cases where relatedness among individuals can be estimated from pedigrees. C_LIO_LITo ensure that genetic group animal models with heterogeneous VA remain applicable to populations with genomic data but no pedigrees, there is a clear need to generalize these models to the case when exclusively genomic data is available. We therefore introduce such methodology for wild admixed systems by extending methods that were recently suggested in the context of plant breeding. Our extension relaxes the limiting assumptions that currently restrict their use to artificial breeding setups. C_LIO_LIWe illustrate the usefulness of the extended genomic genetic groups animal model on a wild admixed population of house sparrows resident in an island system in Northern Norway, where genome-wide data on more than 180 000 single nucleotide polymorphisms (SNPs) is available to derive genomic relatedness. We compare our estimates of quantitative genetic parameters to those derived from a corresponding pedigree-based genetic groups animal model. The satisfactory agreement indicates that the new method works as expected. C_LIO_LIOur extension of the very popular animal model ensures that the upcoming challenges with increasing availability of genomic data for quantitative genetic studies of wild admixed populations can be handled. To make the method widely available to the scientific community, we offer guidance in the form of a tutorial including step-by-step instructions to facilitate implementation. C_LI

evolutionary biology↗

bioRxiv2018

Animal models with group-specific additive genetic variances: extending genetic group models

1. The animal model is a key tool in quantitative genetics and has been used extensively to estimate fundamental parameters, such as additive genetic variance, heritability, or inbreeding effects. An implicit assumption of animal models is that all founder individuals derive from a single population. This assumption is commonly violated, for instance in cross-bred livestock breeds, when an observed population receive immigrants, or when a meta-population is split into genetically differentiated subpopulations. Ignoring genetic differences among different source populations of founders may lead to biased parameter estimates, in particular for the additive genetic variance.\n\n2. To avoid such biases, genetic group models, extensions to the animal model that account for the presence of more than one genetic group, have been proposed. As a key limitation, the method to date only allows that the breeding values differ in their means, but not in their variances among the groups. Methodology previously proposed to account for group-specific variances included terms for segregation variance, which rendered the models infeasibly complex for application to most real study systems.\n\n3. Here we explain why segregation variances are often negligible when analyzing the complex polygenic traits that are frequently the focus of evolutionary ecologists and animal breeders. Based on this we suggest an extension of the animal model that permits estimation of group-specific additive genetic variances. This is achieved by employing group-specific relatedness matrices for the breeding value components attributable to different genetic groups. We derive these matrices by decomposing the full relatedness matrix via the generalized Cholesky decomposition, and by scaling the respective matrix components for each group. To this end, we propose a computationally convenient approximation for the matrix component that encodes for the Mendelian sampling variance. Although convenient, this approximation is not critical.\n\n4. Simulations and an example from an insular meta-population of house sparrows in Norway with three genetic groups illustrate that the method is successful in estimating group-specific additive genetic variances and that segregation variances are indeed negligible in the empirical example.\n\n5. Quantifying differences in additive genetic variance within and among populations is of major biological interest in ecology, evolution, and animal and plant breeding. The proposed method allows to estimate such differences for subpopulations that form a connected meta-population, which may also be useful to study temporal or spatial variation of additive genetic variance.

evolutionary biology↗

bioRxiv2017

An Effective Model Of The Retinoic Acid Induced HL-60 Differentiation Program

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPAR$[gamma] were critical to the ATRA-induced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

systems biology↗