ResearchPad - 24 https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Nucleoplasmin is a limiting component in the scaling of nuclear size with cytoplasmic volume]]> https://www.researchpad.co/article/elastic_article_15327 How nuclear size is regulated relative to cell size is a fundamental cell biological question. Reductions in both cell and nuclear sizes during Xenopus laevis embryogenesis provide a robust scaling system to study mechanisms of nuclear size regulation. To test if the volume of embryonic cytoplasm is limiting for nuclear growth, we encapsulated gastrula-stage embryonic cytoplasm and nuclei in droplets of defined volume using microfluidics. Nuclei grew and reached new steady-state sizes as a function of cytoplasmic volume, supporting a limiting component mechanism of nuclear size control. Through biochemical fractionation, we identified the histone chaperone nucleoplasmin (Npm2) as a putative nuclear size effector. Cellular amounts of Npm2 decrease over development, and nuclear size was sensitive to Npm2 levels both in vitro and in vivo, affecting nuclear histone levels and chromatin organization. We propose that reductions in cell volume and the amounts of limiting components, such as Npm2, contribute to developmental nuclear size scaling.

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<![CDATA[New candidates for regulated gene integrity revealed through precise mapping of integrative genetic elements]]> https://www.researchpad.co/article/N249fead6-5cee-4399-8f76-356c51ff87d2 Integrative genetic elements (IGEs) are mobile multigene DNA units that integrate into and excise from host bacterial genomes. Each IGE usually targets a specific site within a conserved host gene, integrating in a manner that preserves target gene function. However, a small number of bacterial genes are known to be inactivated upon IGE integration and reactivated upon excision, regulating phenotypes of virulence, mutation rate, and terminal differentiation in multicellular bacteria. The list of regulated gene integrity (RGI) cases has been slow-growing because IGEs have been challenging to precisely and comprehensively locate in genomes. We present software (TIGER) that maps IGEs with unprecedented precision and without attB site bias. TIGER uses a comparative genomic, ping-pong BLAST approach, based on the principle that the IGE integration module (i.e. its int-attP region) is cohesive. The resultant IGEs from 2168 genomes, along with integrase phylogenetic analysis and gene inactivation tests, revealed 19 new cases of genes whose integrity is regulated by IGEs (including dut, eccCa1, gntT, hrpB, merA, ompN, prkA, tqsA, traG, yifB, yfaT and ynfE), as well as recovering previously known cases (in sigK, spsM, comK, mlrA and hlb genes). It also recovered known clades of site-promiscuous integrases and identified possible new ones.

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<![CDATA[S3norm: simultaneous normalization of sequencing depth and signal-to-noise ratio in epigenomic data]]> https://www.researchpad.co/article/N0506ba1c-997c-47e6-a79c-930edbb67ce4 Quantitative comparison of epigenomic data across multiple cell types or experimental conditions is a promising way to understand the biological functions of epigenetic modifications. However, differences in sequencing depth and signal-to-noise ratios in the data from different experiments can hinder our ability to identify real biological variation from raw epigenomic data. Proper normalization is required prior to data analysis to gain meaningful insights. Most existing methods for data normalization standardize signals by rescaling either background regions or peak regions, assuming that the same scale factor is applicable to both background and peak regions. While such methods adjust for differences in sequencing depths, they do not address differences in the signal-to-noise ratios across different experiments. We developed a new data normalization method, called S3norm, that normalizes the sequencing depths and signal-to-noise ratios across different data sets simultaneously by a monotonic nonlinear transformation. We show empirically that the epigenomic data normalized by our method, compared to existing methods, can better capture real biological variation, such as impact on gene expression regulation.

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<![CDATA[Quantitative comparison of within-sample heterogeneity scores for DNA methylation data]]> https://www.researchpad.co/article/N75e6ae97-0171-4a6f-8b66-f518ee86dacf DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed. We performed the first systematic comparison of four published WSH scores based on simulated and publicly available datasets. Moreover, we propose two new scores and provide guidelines for selecting appropriate scores to address cell-type heterogeneity, cellular contamination and allele-specific methylation. Most of the measures were sensitive in detecting DNA methylation heterogeneity in these scenarios, while we detected differences in susceptibility to technical bias. Using recently published DNA methylation profiles of Ewing sarcoma samples, we show that DNA methylation heterogeneity provides information complementary to the DNA methylation level. WSH scores are powerful tools for estimating variance in DNA methylation patterns and have the potential for detecting novel disease-associated genomic loci not captured by established statistics. We provide an R-package implementing the WSH scores for integration into analysis workflows.

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<![CDATA[Automated analysis of scanning electron microscopic images for assessment of hair surface damage]]> https://www.researchpad.co/article/N363bee0f-dcd6-4cb7-88b4-8137645b53d8

Mechanical damage of hair can serve as an indicator of health status and its assessment relies on the measurement of morphological features via microscopic analysis, yet few studies have categorized the extent of damage sustained, and instead have depended on qualitative profiling based on the presence or absence of specific features. We describe the development and application of a novel quantitative measure for scoring hair surface damage in scanning electron microscopic (SEM) images without predefined features, and automation of image analysis for characterization of morphological hair damage after exposure to an explosive blast. Application of an automated normalization procedure for SEM images revealed features indicative of contact with materials in an explosive device and characteristic of heat damage, though many were similar to features from physical and chemical weathering. Assessment of hair damage with tailing factor, a measure of asymmetry in pixel brightness histograms and proxy for surface roughness, yielded 81% classification accuracy to an existing damage classification system, indicating good agreement between the two metrics. Further ability of the tailing factor to score features of hair damage reflecting explosion conditions demonstrates the broad applicability of the metric to assess damage to hairs containing a diverse set of morphological features.

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<![CDATA[Constraining classifiers in molecular analysis: invariance and robustness]]> https://www.researchpad.co/article/Nea33803e-a97c-4264-8a61-36afec4e7efb

Analysing molecular profiles requires the selection of classification models that can cope with the high dimensionality and variability of these data. Also, improper reference point choice and scaling pose additional challenges. Often model selection is somewhat guided by ad hoc simulations rather than by sophisticated considerations on the properties of a categorization model. Here, we derive and report four linked linear concept classes/models with distinct invariance properties for high-dimensional molecular classification. We can further show that these concept classes also form a half-order of complexity classes in terms of Vapnik–Chervonenkis dimensions, which also implies increased generalization abilities. We implemented support vector machines with these properties. Surprisingly, we were able to attain comparable or even superior generalization abilities to the standard linear one on the 27 investigated RNA-Seq and microarray datasets. Our results indicate that a priori chosen invariant models can replace ad hoc robustness analysis by interpretable and theoretically guaranteed properties in molecular categorization.

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<![CDATA[Interplay between competitive and cooperative interactions in a three-player pathogen system]]> https://www.researchpad.co/article/N327f5bff-126a-495d-b2dd-d7a66aefee9c

In ecological systems, heterogeneous interactions between pathogens take place simultaneously. This occurs, for instance, when two pathogens cooperate, while at the same time, multiple strains of these pathogens co-circulate and compete. Notable examples include the cooperation of human immunodeficiency virus with antibiotic-resistant and susceptible strains of tuberculosis or some respiratory infections with Streptococcus pneumoniae strains. Models focusing on competition or cooperation separately fail to describe how these concurrent interactions shape the epidemiology of such diseases. We studied this problem considering two cooperating pathogens, where one pathogen is further structured in two strains. The spreading follows a susceptible-infected-susceptible process and the strains differ in transmissibility and extent of cooperation with the other pathogen. We combined a mean-field stability analysis with stochastic simulations on networks considering both well-mixed and structured populations. We observed the emergence of a complex phase diagram, where the conditions for the less transmissible, but more cooperative strain to dominate are non-trivial, e.g. non-monotonic boundaries and bistability. Coupled with community structure, the presence of the cooperative pathogen enables the coexistence between strains by breaking the spatial symmetry and dynamically creating different ecological niches. These results shed light on ecological mechanisms that may impact the epidemiology of diseases of public health concern.

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<![CDATA[Emergence of oscillations in a simple epidemic model with demographic data]]> https://www.researchpad.co/article/N6a6b88d4-e593-429f-8355-7161c612af52

A simple susceptible–infectious–removed epidemic model for smallpox, with birth and death rates based on historical data, produces oscillatory dynamics with remarkably accurate periodicity. Stochastic population data cause oscillations to be sustained rather than damped, and data analysis regarding the oscillations provides insights into the same set of population data. Notably, oscillations arise naturally from the model, instead of from a periodic forcing term or other exogenous mechanism that guarantees oscillation: the model has no such mechanism. These emergent natural oscillations display appropriate periodicity for smallpox, even when the model is applied to different locations and populations. The model and datasets, in turn, offer new observations about disease dynamics and solution trajectories. These results call for renewed attention to relatively simple models, in combination with datasets from real outbreaks.

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<![CDATA[How the thermal environment shapes the structure of termite mounds]]> https://www.researchpad.co/article/N31476f69-0900-4f3b-925c-832a14722245

A computational model has been developed to predict the role of environment in the forms and functions of termite mounds. The proposed model considers the most relevant forces involved in the heat transfer process of termite mounds, while also reflecting their gas-exchange function. The method adopts a system configuration procedure to determine thermally optimized mound structures. The model successfully predicts the main architectural characteristics of typical Macrotermes michaelseni mounds for the environmental conditions they live in. The results indicate that the mound superstructure and internal condition strongly depend on the combined effect of environmental forces. It is noted that mounds being exposed to higher solar irradiances develop intricate lateral channels, inside, and taller and more pronounced spire tilt towards the Sun, outside. It is also found that the mounds' spire tilt angle depends on the geographical location, following the local average solar zenith angle for strong irradiances. Although wind does not influence the overall over-ground mound shape, it significantly affects the mound internal condition. The results of this study resonate with what is seen in nature. The proposed approach provides a broader view of the factors that are effective in the form and function of a naturally made structure.

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<![CDATA[A developmentally descriptive method for quantifying shape in gastropod shells]]> https://www.researchpad.co/article/N7ee4724a-de48-492f-8fa9-2fe9e5b9c604

The growth of snail shells can be described by simple mathematical rules. Variation in a few parameters can explain much of the diversity of shell shapes seen in nature. However, empirical studies of gastropod shell shape variation typically use geometric morphometric approaches, which do not capture this growth pattern. We have developed a way to infer a set of developmentally descriptive shape parameters based on three-dimensional logarithmic helicospiral growth and using landmarks from two-dimensional shell images as input. We demonstrate the utility of this approach, and compare it to the geometric morphometric approach, using a large set of Littorina saxatilis shells in which locally adapted populations differ in shape. Our method can be modified easily to make it applicable to a wide range of shell forms, which would allow for investigations of the similarities and differences between and within many different species of gastropods.

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<![CDATA[Decoding collective communications using information theory tools]]> https://www.researchpad.co/article/Ndc82404e-b524-40a7-869e-885860a265ca

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

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<![CDATA[TypeTE: a tool to genotype mobile element insertions from whole genome resequencing data]]> https://www.researchpad.co/article/N7a29cdcb-85ee-4e7d-a0ed-c60567d34603

Abstract

Alu retrotransposons account for more than 10% of the human genome, and insertions of these elements create structural variants segregating in human populations. Such polymorphic Alus are powerful markers to understand population structure, and they represent variants that can greatly impact genome function, including gene expression. Accurate genotyping of Alus and other mobile elements has been challenging. Indeed, we found that Alu genotypes previously called for the 1000 Genomes Project are sometimes erroneous, which poses significant problems for phasing these insertions with other variants that comprise the haplotype. To ameliorate this issue, we introduce a new pipeline – TypeTE – which genotypes Alu insertions from whole-genome sequencing data. Starting from a list of polymorphic Alus, TypeTE identifies the hallmarks (poly-A tail and target site duplication) and orientation of Alu insertions using local re-assembly to reconstruct presence and absence alleles. Genotype likelihoods are then computed after re-mapping sequencing reads to the reconstructed alleles. Using a high-quality set of PCR-based genotyping of >200 loci, we show that TypeTE improves genotype accuracy from 83% to 92% in the 1000 Genomes dataset. TypeTE can be readily adapted to other retrotransposon families and brings a valuable toolbox addition for population genomics.

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<![CDATA[IDR2D identifies reproducible genomic interactions]]> https://www.researchpad.co/article/Nef0ffebe-61d3-4baf-b291-7020b4b04c56

Abstract

Chromatin interaction data from protocols such as ChIA-PET, HiChIP and Hi-C provide valuable insights into genome organization and gene regulation, but can include spurious interactions that do not reflect underlying genome biology. We introduce an extension of the Irreproducible Discovery Rate (IDR) method called IDR2D that identifies replicable interactions shared by chromatin interaction experiments. IDR2D provides a principled set of interactions and eliminates artifacts from single experiments. The method is available as a Bioconductor package for the R community, as well as an online service at https://idr2d.mit.edu.

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<![CDATA[Effects of niche overlap on coexistence, fixation and invasion in a population of two interacting species]]> https://www.researchpad.co/article/N7d27642e-fda8-4f63-a458-0c8771ec3304

Synergistic and antagonistic interactions in multi-species populations—such as resource sharing and competition—result in remarkably diverse behaviours in populations of interacting cells, such as in soil or human microbiomes, or clonal competition in cancer. The degree of inter- and intra-specific interaction can often be quantified through the notion of an ecological ‘niche’. Typically, weakly interacting species that occupy largely distinct niches result in stable mixed populations, while strong interactions and competition for the same niche result in rapid extinctions of some species and fixations of others. We investigate the transition of a deterministically stable mixed population to a stochasticity-induced fixation as a function of the niche overlap between the two species. We also investigate the effect of the niche overlap on the population stability with respect to external invasions. Our results have important implications for a number of experimental systems.

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<![CDATA[Control of synchronization ratios in clock/cell cycle coupling by growth factors and glucocorticoids]]> https://www.researchpad.co/article/N16e8b0d3-4bb1-4527-809b-5683015dc7c6

The cell cycle and the circadian clock are essential cyclic cellular processes often synchronous in healthy cells. In this work, we use previously developed mathematical models of the mammalian cell cycle and circadian cellular clock in order to investigate their dynamical interactions. Firstly, we study unidirectional cell cycle → clock coupling by proposing a mechanism of mitosis promoting factor (MPF)-controlled REV-ERBα degradation. Secondly, we analyse a bidirectional coupling configuration, where we add the CLOCK : BMAL1-mediated MPF repression via the WEE1 kinase to the first system. Our simulations reproduce ratios of clock to cell cycle period in agreement with experimental observations and give predictions of the system’s synchronization state response to a variety of control parameters. Specifically, growth factors accelerate the coupled oscillators and dexamethasone (Dex) drives the system from a 1 : 1 to a 3 : 2 synchronization state. Furthermore, simulations of a Dex pulse reveal that certain time regions of pulse application drive the system from 1 : 1 to 3 : 2 synchronization while others have no effect, revealing the existence of a responsive and an irresponsive system’s phase, a result we contextualize with observations on the segregation of Dex-treated cells into two populations.

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<![CDATA[Stochastic fluctuations in apoptotic threshold of tumour cells can enhance apoptosis and combat fractional killing]]> https://www.researchpad.co/article/N2c67239a-e7d6-4c0e-9ed2-9f3ffb06910b

Fractional killing, which is a significant impediment to successful chemotherapy, is observed even in a population of genetically identical cancer cells exposed to apoptosis-inducing agents. This phenomenon arises not from genetic mutation but from cell-to-cell variation in the activation timing and level of the proteins that regulates apoptosis. To understand the mechanism behind the phenomenon, we formulate complex fractional killing processes as a first-passage time (FPT) problem with a stochastically fluctuating boundary. Analytical calculations are performed for the FPT distribution in a toy model of stochastic p53 gene expression, where the cancer cell is killed only when the p53 expression level crosses an active apoptotic threshold. Counterintuitively, we find that threshold fluctuations can effectively enhance cellular killing by significantly decreasing the mean time that the p53 protein reaches the threshold level for the first time. Moreover, faster fluctuations lead to the killing of more cells. These qualitative results imply that fluctuations in threshold are a non-negligible stochastic source, and can be taken as a strategy for combating fractional killing of cancer cells.

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<![CDATA[Structures of SALSA/DMBT1 SRCR domains reveal the conserved ligand-binding mechanism of the ancient SRCR fold]]> https://www.researchpad.co/article/N9f1d551f-9bc8-4210-81cc-7c218f6e15af

The structures of SALSA SRCR domains 1 and 8 reveal a cation-dependent mechanism for ligand recognition, contributing to important roles in the immune system and cellular signalling. The cation-binding sites are conserved across all SRCR domains, suggesting conserved functional mechanisms.

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<![CDATA[Parameter inference in dynamical systems with co-dimension 1 bifurcations]]> https://www.researchpad.co/article/N26f1677c-79b8-453e-b4f2-ae08ffaf31a5

Dynamical systems with intricate behaviour are all-pervasive in biology. Many of the most interesting biological processes indicate the presence of bifurcations, i.e. phenomena where a small change in a system parameter causes qualitatively different behaviour. Bifurcation theory has become a rich field of research in its own right and evaluating the bifurcation behaviour of a given dynamical system can be challenging. An even greater challenge, however, is to learn the bifurcation structure of dynamical systems from data, where the precise model structure is not known. Here, we study one aspects of this problem: the practical implications that the presence of bifurcations has on our ability to infer model parameters and initial conditions from empirical data; we focus on the canonical co-dimension 1 bifurcations and provide a comprehensive analysis of how dynamics, and our ability to infer kinetic parameters are linked. The picture thus emerging is surprisingly nuanced and suggests that identification of the qualitative dynamics—the bifurcation diagram—should precede any attempt at inferring kinetic parameters.

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<![CDATA[Rab11FIP proteins link endocytic recycling vesicles for cytoskeletal transport and tethering]]> https://www.researchpad.co/article/5c6863c2d5eed0c484023b12

Regulated trafficking of internalised integrins and growth factor receptors enables polarisation of morphology and motility and enables lumen formation in multicellular structures. Recycling vesicles marked with Rab11 direct internalised cargo back to the plasma membrane to affect biological processes such as polarised trafficking and cancer cell invasion. A recent study by Ji and colleagues, provides insight into how the trafficking protein Rab11FIP2 links with the actin-based motor myo5b and the small GTPase Rab11 to regulate vesicle tethering and transport along actin filaments [1]. The authors used biochemical methods to demonstrate that Rab11a binds directly to the tail of myo5b and that Rab11FIP2 also forms direct interactions with both Rab11a and myo5b tails. These proteins essentially compete for binding to similar regions and thus can regulate the association and activity of each other. Ji and colleagues further demonstrate that Rab11a activates myo5b by binding to its globular tail and relieving a head-tail autoinhibition. Due to differing affinities between Rab11 and myo5b or Rab11FIP2, they propose that Rab11FIP2 mediates the association of myo5b with cargo vesicles, while Rab11a regulates the motor activity of myo5b. The present study thus elucidates how myo5b is regulated by its interactions with Rab11a and Rab11FIP2 and proposes a model for coordination of recycling vesicle tethering and motor activity. The present study has implications for how cells control polarity and motility in health and disease and suggests how Rab11FIP proteins might control motor protein activity and engagement for transport.

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<![CDATA[RefSeq curation and annotation of stop codon recoding in vertebrates]]> https://www.researchpad.co/article/5c5f1bc3d5eed0c48469ba48

Abstract

Recoding of stop codons as amino acid-specifying codons is a co-translational event that enables C-terminal extension of a protein. Synthesis of selenoproteins requires recoding of internal UGA stop codons to the 21st non-standard amino acid selenocysteine (Sec) and plays a vital role in human health and disease. Separately, canonical stop codons can be recoded to specify standard amino acids in a process known as stop codon readthrough (SCR), producing extended protein isoforms with potential novel functions. Conventional computational tools cannot distinguish between the dual functionality of stop codons as stop signals and sense codons, resulting in misannotation of selenoprotein gene products and failure to predict SCR. Manual curation is therefore required to correctly represent recoded gene products and their functions. Our goal was to provide accurately curated and annotated datasets of selenoprotein and SCR transcript and protein records to serve as annotation standards and to promote basic and biomedical research. Gene annotations were curated in nine vertebrate model organisms and integrated into NCBI’s Reference Sequence (RefSeq) dataset, resulting in 247 selenoprotein genes encoding 322 selenoproteins, and 93 genes exhibiting SCR encoding 94 SCR isoforms.

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