Biology subjects

Turcotte, M.

Publications and source records attributed to Turcotte, M..

11 recordsLinked to original sources

bioRxiv2026

Gene therapy targeting of AKAP6β-CaMKII signalosomes improves myocardial inflammation and heart failure in a swine model of cardiometabolic syndrome

BackgroundCardiometabolic heart failure with preserved ejection fraction (HFpEF) is associated with systemic and cardiac inflammation and diastolic dysfunction. A-kinase anchoring protein 6{beta} (AKAP6{beta}) is a scaffold protein located at the cardiomyocyte outer nuclear membrane that promotes pathological cardiac remodeling via the recruitment of multiple regulatory proteins including protein kinases. In mice, adeno-associated virus (AAV) mediated expression of a peptide based upon a kinase binding domain (KBD) within AKAP6{beta} inhibited the development of heart failure due to chronic pressure overload. Whether KBD expression can also inhibit the development of cardiometabolic heart failure is unknown, and if so, the mechanism of KBD action in HFpEF has yet to be explored. MethodsThe efficacy of a cardiotropic self-complementary AAV gene therapy that expresses the AKAP6{beta} KBD peptide (AAV9sc.KBD) was tested in a female Ossabaw swine model of cardiometabolic syndrome and HFpEF. Single nucleus and bulk RNA sequencing of swine heart tissue and immunoprecipitation-mass spectrometry, live cell imaging, and biochemical assays using primary rat cardiomyocytes were employed to study KBD mechanism of action. ResultsAAV9sc.KBD inhibited the development of diastolic dysfunction and heart failure in the Ossabaw model, without negatively impacting systolic function. The improvement in cardiac phenotype was associated with decreased T-cell myocardial infiltrates and partial reversal of pathological gene expression. An unbiased interactome study revealed that the KBD peptide binds Ca2+/calmodulin-dependent protein kinase II (CaMKII), identifying CaMKII as a new AKAP6{beta} binding partner. Perinuclear CaMKII activity detected by live cell imaging required AKAP6{beta} expression and was inhibited by KBD expression. In addition, the CaMKII substrate Inhibitor of NF-{kappa}B Kinase {beta} (IKK{beta}) bound AKAP6{beta}. IKK phosphorylation in the Ossabaw model and in myocytes was inhibited by KBD expression, and NF-{kappa}B nuclear translocation in myocytes was dependent upon AKAP6{beta}-CaMKII protein complex formation. AAV9sc.KBD treatment inhibited cardiomyocyte NF-{kappa}B-dependent gene expression in the Ossabaw model. ConclusionsRegulated by perinuclear AKAP6{beta}-CaMKII signalosomes, NF-{kappa}B pro-inflammatory gene expression in cardiomyocytes participates in a positive feedback loop with cardiac inflammation promoting HFpEF. Proof-of-concept is provided in a large animal model that gene therapy-based cardiomyocyte expression of the KBD peptide will prevent cardiac dysfunction in cardiometabolic syndrome. Clinical PerspectiveO_ST_ABSWhat is newC_ST_ABSO_LIThe cardiomyocyte-selective gene therapy AAV9sc.KBD, which targets signalosomes organized by the scaffold protein AKAP6{beta}, is shown to inhibit myocardial T-cell infiltration and improve cardiac structure and function in a large animal model of cardiometabolic HFpEF. C_LIO_LIThe AKAP6{beta} KBD peptide is shown to bind and inhibit the function of CaMKII. C_LIO_LICaMKII and IKK{beta} are shown to participate in perinuclear AKAP6{beta} signalosomes, where they regulate activation of the NF-{kappa}B pro-inflammatory gene regulatory pathway. C_LI Clinical implicationsO_LIProof-of-concept for a novel strategy for the treatment of HFpEF is provided, intracellular expression by a cardiomyocyte-selective gene therapy vector of an inhibitory peptide, which will inhibit compartmentalized intracellular signal transduction. C_LIO_LIIn conjunction with previous studies in small rodents, the new data obtained in Ossabaw swine support clinical translation of the AAV9sc.KBD gene therapy. C_LI

physiology↗

bioRxiv2026

Niche differentiation confers coexistence prior to the species boundary in an aquatic plant

Despite the prevailing view that ecological divergence drives speciation, we know little about when or how nascent lineages evolve the ecological differences needed to coexist upon secondary contact. Here, we apply ecological coexistence theory to quantify the potential for coexistence among 126 allopatric lineages of the globally distributed duckweed Spirodela polyrhiza. Using competition experiments simulating secondary contact, we found that rapid accumulation of niche differences stabilized coexistence to permit sympatry among potentially interbreeding lineages. Competition against sister-species Spirodela intermedia further showed that niche differences accumulate more slowly post-speciation, revealing that niche differences enabling coexistence evolve well before timescales at which speciation is complete. Our findings suggest that rapid coexistence may thus contribute to time-lags in speciation, shaping both the origin and maintenance of biodiversity.

ecology↗

bioRxiv2025

Targeting of CIP4-Calcineurin Signalosomes Improves Cardiac Structure and Function After Myocardial Infarction

BackgroundCalcineurin in a pleiotropic signaling enzyme that promotes pathological cardiac remodeling but also cardioprotection in ischemia-reperfusion injury. In addition, calcineurin inhibitors are immunosuppressants. This pleiotropy has precluded the use of calcineurin inhibitors as treatments for heart failure. Cdc42-interacting protein 4 (CIP4/TRIP10) is an endosomal scaffold protein that organizes a calcium and calcineurin A{beta}2 (CaNA{beta}2) signaling compartment activated by G-protein coupled receptors independently of contractile calcium. CIP4 binds CaNA{beta}2 via the CaNA{beta}-specific N-terminal polyproline (PP) domain. We previously showed that targeting of CIP4-CaNA{beta}2 signalosomes inhibited pathological cardiac hypertrophy and the development of heart failure induced by chronic pressure overload in mice. It is unknown whether CIP4-CaNA{beta}2 signalosomes contribute to cardioprotection and/or cardiac remodeling in ischemic heart disease. MethodsCIP4 conditional knock-out (CKO) mice were studied by echocardiography with strain analysis and histology following ischemia-reperfusion (I/R) injury and permanent left coronary artery (LCA) ligation to induce myocardial infarction. Wildtype C57BL/6NJ mice were transduced with adeno-associated virus (AAV) engineered for cardiomyocyte-specific expression of either a CaNA{beta}2 shRNA to inhibit CaNA{beta}2 expression, a VIVIT peptide to inhibit CaN-NFAT signaling, or a CaNA{beta}2 PP peptide to block CIP4-CaNA{beta}2 binding. AAV-transduced mice were studied by I/R injury. Additional mice were subjected to permanent LCA ligation and subsequently treated with AAV to test the effects of CaN inhibition in chronic ischemic cardiomyopathy. The effects of CaNA{beta}2 PP-GFP expression on primary T-cell activation were studied in vitro. ResultsCIP4 CKO mice and mice expressing the PP anchoring disruptor peptide exhibited preserved cardiac function after I/R injury and decreased infarct size and preserved cardiac function 8 weeks after myocardial infarction by permanent LCA ligation. In contrast, cardiomyocyte-specific depletion of CaNA{beta}2 and VIVIT peptide expression worsened outcome after I/R injury and in chronic ischemic cardiomyopathy. In addition, in contrast to cardiomyocytes, PP-mediated CaNA{beta} anchoring inhibition had no effect on T-cell activation and cytokine expression in vitro. ConclusionsCIP4-CaNA{beta}2 signalosomes promote adverse cardiac remodeling and are not cardioprotective. Proof-of-concept is provided for the treatment of ischemic cardiomyopathy by a PP anchoring disruptor gene therapy. Targeting these complexes may be beneficial in cardiovascular diseases, including ischemic cardiomyopathy and acute myocardial infarction. Clinical PerspectiveO_ST_ABSWhat is New?C_ST_ABSO_LITargeting CIP4, which is a scaffold protein for the phosphatase calcineurin, improves cardiac function in mice after acute myocardial infarction due to ischemia-reperfusion injury and in chronic ischemic cardiomyopathy. C_LIO_LIGene therapy-based expression of a calcineurin A{beta}-derived polyproline peptide, which can compete CIP4-calcineurin binding, is beneficial in acute and chronic myocardial infarction. C_LI What Are the Clinical Implications?O_LIThis study establishes CIP4 signalosomes as a new drug target for the treatment of ischemia-reperfusion injury and chronic pathological cardiac remodeling. C_LIO_LIThis study provides proof-of-concept for a new gene therapy approach to treating acute myocardial infarction and chronic ischemic cardiomyopathy. C_LI

physiology↗

bioRxiv2024

Competitor-induced plasticity modifies the interactions and predicted competitive outcomes between annual plants

Species can modify their traits in response to changes in the environment - a process known as phenotypic plasticity. Because species traits can plastically respond to competition, the competitive effect of one individual on another involves not only reductions in performance, but also changes in morphology, behavior, phenology or physiology that affect interactions with other individuals. In this context, plasticity is often argued to favor species coexistence by increasing the niche differentiation between species, though experimental support that explicitly considers competitive outcomes is largely lacking. Here, we transiently subjected four annual plant species to early-season intraspecific or interspecific competition to explicitly induce plastic responses, and then examined the response of these individuals to other competitors. By measuring the interactions between the species with and without early-season competitors, we isolated the impact of plasticity on species interactions and coexistence. Growing with nearby competitors early in life impacted plant traits including height and morphology. These plastic responses tended to amplify the sensitivity of individuals to competition, and particularly so for interspecific competition. This increase in inter-relative to intraspecific competition caused plasticity to decrease the predicted likelihood of pairwise coexistence. By combining recent theory with a new experimental approach, we provide a pathway towards integrating phenotypic plasticity into our quantitative understanding of coexistence.

ecology↗

bioRxiv2023

Intraspecific variation of two duckweed species influences response to microcystin-LR exposure

Cyanotoxins produced by harmful cyanobacteria blooms can damage freshwater ecosystems and threaten human health. Floating macrophytes may be used as a means of biocontrol by limiting light and resources available to cyanobacteria. However, genetic variation in macrophyte sensitivity to cyanotoxins could influence their suitability as biocontrol agents. We investigated the influence of such intraspecific variation on the response of two rapidly growing duckweed species, Lemna minor and Spirodela polyrhiza, often used in nutrient and metal bioremediation. We assessed two biomarkers related to productivity (biomass and chlorophyll A production) and two related to fitness measures (population size and growth rate). Fifteen genetic lineages of each species were grown in media containing common cyanotoxin microcystin-LR at ecologically relevant concentrations or control media for a period of twelve days. Genotype identity had a strong impact on all biomarker responses. Microcystin concentration did impact the final population sizes of both macrophyte species with a marginal effect on growth rate of L. minor and the chlorophyll A production of S. polyrhiza, but overall these species were very tolerant of microcystin. The strong tolerance supports the potential use of these plants as bioremediators of cyanobacterial blooms. The differential impact of microcystin exposure discovered in single lineage models among genotypes indicates a potential for cyanotoxins to act as selective forces and reduce local macrophyte genetic diversity. HighlightsO_LIEcotoxicology often uses standard genotypes of plants in testing. C_LIO_LIWe tested the influence of clonal variation in duckweeds on their response to common cyanotoxin, microcystin-LR. C_LIO_LIMicrocystin impacts were often masked by genotypic variation in response. C_LIO_LIResults imply that genotype identity may be important to bioremediation and local evolutionary dynamics. C_LI

ecology↗

bioRxiv2023

Plant neopolyploidy and genetic background differentiates the microbiome of duckweed across a variety of natural freshwater sources

Whole genome duplication has long been appreciated for its role in driving phenotypic novelty in plants, often altering the way organisms interface with the abiotic environment. Only recently, however, have we begun to investigate how polyploidy influences interactions of plants with other species, despite the biotic niche being predicted as one of the main determinants of polyploid establishment. Nevertheless, we lack critical information about how polyploidy affects the diversity and composition of the microbial taxa that colonize plants, and whether this is genotype-dependent and repeatable across natural environments. This information is a critical first step toward understanding whether the microbiome contributes to polyploid establishment. We thus tested the immediate effect of polyploidy on the diversity and composition of the bacterial microbiome of the aquatic plant Spirodela polyrhiza using four pairs of diploids and synthetic autotetraploids. Under controlled conditions, axenic plants were inoculated with pond waters collected from 10 field sites across a broad environmental gradient. Autotetraploids hosted 4-11 % greater bacterial taxonomic and phylogenetic diversity than their diploid progenitors. Polyploidy, along with its interactions with the inoculum source and genetic lineage, collectively explained 7 % of the total variation in microbiome composition. Furthermore, polyploidy broadened the core microbiome, with autotetraploids having 15 unique bacterial taxa in addition to the 55 they shared with diploids. Our results show that whole genome duplication directly leads to novelty in plant microbiome and importantly, that the effect is dependent on the genetic ancestry of the polyploid and generalizable over many environmental contexts.

ecology↗

bioRxiv2023

Trophic interactions in microbiomes influence plant host population size and ecosystem function

Plant microbiomes that comprise diverse microorganisms, including prokaryotes, eukaryotes, and viruses are the key determinant of plant population dynamics and ecosystem function. Despite their importance, little is known about how interactions, especially trophic interactions, between microbes from different domains modify the importance of microbiomes for plant hosts and ecosystems. Using the common duckweed Lemna minor, we experimentally examined the effects of predation (by bacterivorous protozoa) and parasitism (by bacteriophage) within microbiomes on plant population size and ecosystem phosphorus removal. Our results revealed that predation increased plant population size and phosphorus removal whereas parasitism showed the opposite pattern. The structural equation modeling further pointed out that predation and parasitism affected plant population size and ecosystem function via distinct mechanisms that were both mediated by microbiomes. Our results highlight the importance of understanding microbial trophic interactions for predicting the outcomes and ecosystem impacts of plant-microbiome symbiosis.

microbiology↗

bioRxiv2022

Cell Type Specific DNA Signatures of Transcription Factor Binding

Transcription factors (TFs) bind to different parts of the genome in different types of cells. These differences may be due to alterations in the DNA-binding preferences of a TF itself, or mechanisms such as chromatin accessibility, steric hindrance, or competitive binding, that result in a DNA "signature" of differential binding. We propose a method called SigTFB (Signatures of TF Binding), based on deep learning, to detect and quantify cell type specificity in a TFs DNA-binding signature. We conduct a wide scale investigation of 194 distinct TFs across various cell types. We demonstrate the existence of cell type specificity in approximately 30% of the TFs. We stratify our analysis by different antibodies for the same TF, to rule out the possibility of certain technical artifacts, yet we find that cell type specificity estimates are largely consistent when the same TF is assayed with different antibodies. To further explain the biology behind a TFs cell type specificity, or lack thereof, we conduct a wide scale motif enrichment analysis of all TFs in question. We show that the presence of alternate motifs correlates with a higher degree of cell type specificity in TFs, such as ATF7, while finding consistent motifs throughout is usually associated with the absence of cell type specificity in a TF, such as CTCF. In particular, we observe that several important TFs show distinct DNA binding signatures in different cancer cell types, which may point to important differences in modes of action. Moreover, we find that motif enrichment sometimes correlates with gene expression in TFs with higher cell type specificity. Our comprehensive investigation provides a basis for further study of the mechanisms behind differences in TF-DNA binding in different cell types.

bioinformatics↗

bioRxiv2019

Prediction of 8-state protein secondary structures by 1D-Inception and BD-LSTM

Protein secondary structure is crucial to create an information bridge between the primary structure and the tertiary (3D) structure. Precise prediction of 8-state protein secondary structure (PSS) significantly utilized in the structural and functional analysis of proteins in bioinformatics. In this recent period, deep learning techniques have been applied in this research area and raise the Q8 accuracy remarkably. Nevertheless, from a theoretical standpoint, there still lots of room for improvement, specifically in 8-state (Q8) protein secondary structure prediction. In this paper, we presented two deep learning architecture, namely 1D-Inception and BD-LSTM, to improve the performance of 8-classes PSS prediction. The input of these two architectures is a carefully constructed feature matrix from the sequence features and profile features of the proteins. Firstly, 1D-Inception is a Deep convolutional neural network-based approach that was inspired by the InceptionV3 model and containing three inception modules. Secondly, BD-LSTM is a recurrent neural network model which including bidirectional LSTM layers. Our proposed 1D-Inception method achieved 76.65%, 71.18%, 76.86%, and 74.07% Q8 accuracy respectively on benchmark CullPdb6133, CB513, CASP10, and CASP11 datasets. Moreover, BD-LSTM acquired 74.71%, 69.49%, 74.07%, and 72.37% state-8 accuracy after evaluated on CullPdb6133, CB513, CASP10, and CASP11 datasets, respectively. Both these architectures enable the efficient processing of local and global interdependencies between amino acids to make an accurate prediction of each class is very beneficial in the deep neural network. To the best of our knowledge, experiment results of the 1D-Inception model demonstrate that it outperformed all the state-of-art methods on the benchmark CullPdb6133, CB513, and CASP10 datasets.

bioinformatics↗

bioRxiv2019

WACS: Improving Peak Calling by Optimally Weighting Controls

MotivationChromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq), initially introduced more than a decade ago, is widely used by the scientific community to detect protein/DNA binding and histone modifications across the genome. Every experiment is prone to noise and bias, and ChIP-seq experiments are no exception. To alleviate bias, the incorporation of control datasets in ChIP-seq analysis is an essential step. The controls are used to account for the background signal, while the remainder of the ChIP-seq signal captures true binding or histone modification. However, a recurrent issue is different types of bias in different ChIP-seq experiments. Depending on which controls are used, different aspects of ChIP-seq bias are better or worse accounted for, and peak calling can produce different results for the same ChIP-seq experiment. Consequently, generating "smart" controls, which model the non-signal effect for a specific ChIP-seq experiment, could enhance contrast and increase the reliability and reproducibility of the results. ResultsWe propose a peak calling algorithm, Weighted Analysis of ChIP-seq (WACS), which is an extension of the well-known peak caller MACS2. There are two main steps in WACS: First, weights are estimated for each control using non-negative least squares regression. The goal is to customize controls to model the noise distribution for each ChIP-seq experiment. This is then followed by peak calling. We demonstrate that WACS significantly outperforms MACS2 and AIControl, another recent algorithm for generating smart controls, in the detection of enriched regions along the genome, in terms of motif enrichment and reproducibility analyses. ConclusionThis ultimately improves our understanding of ChIP-seq controls and their biases, and shows that WACS results in a better approximation of the noise distribution in controls.

bioinformatics↗

bioRxiv2018

Time-scale separation and stochasticity conspire to impact phenotypic dynamics in the canonical and inverted Bacillus subtilis core genetic regulation circuits.

In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil. We focus on hitherto unchartered aspects of the dynamics by exploring the effect of time scale separation between transcription and translation and, as well, the effect of intrinsic molecular stochasticity. We consider these aspects of regulatory control as two possible evolutionary handles. Hence, using theory and computations, we study how the onset of oscillations breaks the excitability-based competence phenotype in two topologically close evolutionary competing circuits: the canonical \"wild-type\" regulation circuit selected by Evolution and, the indirect-feedback inverted circuit that failed to be selected by Evolution, as was shown elsewhere, due to dynamical reasons.

systems biology↗