Biology subjects

Desai, S.

Publications and source records attributed to Desai, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Biased agonism of carvedilol in the beta1-adrenergic receptor is governed by conformational exclusion

Only two non-visual arrestins recognize many hundreds of different, intracellularly phosphorylated G protein-coupled receptors (GPCRs). Due to the highly dynamic nature of GPCR*arrestin complexes, the critical determinants of GPCR-arrestin recognition have remained largely unclear. We show here that arrestin2 recruitment to the {beta}1-adrenergic receptor ({beta}1AR) can be induced by an arrestin-activating phosphopeptide that is not covalently linked to the receptor and that the recruitment is independent of the presence and type of the orthosteric receptor ligand. Apparently, the arrestin-receptor interaction is driven by the conformational switch within arrestin induced by the phosphopeptide, whereas the electrostatic attraction towards the receptor phosphosites may only play an auxiliary role. Extensive NMR observations show that in contrast to previous static GPCR*arrestin complex structures, the {beta}1AR complex with the beta-blocker carvedilol and arrestin2 is in a G protein-inactive conformation. The insensitivity to the specific receptor conformation provides a rationale for arrestins promiscuous recognition of GPCRs and explains the arrestin-biased agonism of carvedilol, which largely blocks G protein binding, while still enabling arrestin engagement. Significance statementG protein-coupled receptors regulate cellular signaling through G proteins and arrestins. While G protein interactions are well understood, the molecular basis of arrestin recognition remains unclear due to the dynamic nature of GPCR*arrestin complexes. We show that arrestin recognition of the {beta}1-adrenergic receptor occurs independently of the receptors conformational state or ligand binding. Using NMR, cryo-EM, and biochemical assays, we find that arrestin engagement is driven by a conformational change within arrestin itself, triggered by a non-receptor-attached phosphopeptide, whereas electrostatic attraction towards receptor phosphosites may only play an auxiliary role. These findings provide new insights into arrestin activation, explain its ability to recognize diverse GPCRs, with significant implications for understanding biased signaling mechanisms and designing of selective therapeutic strategies.

biochemistry↗

bioRxiv2024

Pro-survival roles for p21(Cip1/Waf1) in Non-Small Cell Lung Cancer

Quiescence is a reversible state of proliferative arrest, distinct from senescence. While cancer is a disease of dysregulated proliferation, cancer cells can retain the ability to enter quiescence which confers advantages to tumour cells by protecting them from chemotherapy or by allowing metastasis to distant sites. Multiple mechanisms exist to induce and maintain quiescence that are not yet fully understood. Here, we show that high expression of the CDK inhibitor p21Cip1/Waf1 correlates with a poor prognosis in TP53 wild-type, but not TP53 mutant, non-small cell lung cancer (NSCLC) patients. Using quantitative single-cell imaging of genetically-engineered NSCLC reporter cell lines, we show that TP53 wild-type NSCLC cells can enter a p21-dependent spontaneous quiescent state, downstream of replication stress. Furthermore, p21 expression confers survival advantages to TP53 wild-type NSCLC cells, both under normal proliferation and in response to chemotherapy. We also show that p21 can promote tumour relapse by allowing cells to recover from both G1 and G2 arrest states after drug removal. Together, our data suggest that targeting p21 function in TP53 wild-type tumours could lead to better outcomes for chemotherapy treatment in NSCLC patients. Statement of SignificanceWe show that TP53WT Non-Small Cell Lung Cancer cells can enter a p21-dependent spontaneous quiescent state and that p21 maintains the viability of NSCLC cells, is chemoprotective and can promote tumour relapse.

cancer biology↗

bioRxiv2024

Coordination between ESCRT function and Rab conversion during endosome maturation

The endosomal pathway is essential for regulating cell signaling and cellular homeostasis. Rab5-positive early endosomes receive proteins from the plasma membrane. Dependent on a ubiquitin mark on the protein, they will be either recycled or sorted into intraluminal vesicles (ILVs) by ESCRT. During endosome maturation Rab5 will be replaced by Rab7 on endosomes that are able to fuse with lysosomes to form endolysosomes. Whether ESCRT-driven ILV formation and Rab5-to-Rab7 conversion are coordinated remains unknown. Here we show that loss of early ESCRTs leads to enlarged Rab5-positive endosomes and prohibit Rab conversion. Reduction of ubiquitinated cargo alleviated this phenotype. Moreover, ubiquitinated proteins on the endosomal limiting membrane prevented the displacement of the Rab5GEF RABX-5 by the Rab7GEF SAND-1/CCZ-1. Overexpression of Rab7 could partially overcome this block, even in the absence of SAND-1, whereby the HOPS complex presumably acts as Rab7GEF. Our data reveal a hierarchy of events in which cargo corralling by ESCRTs is upstream of Rab conversion and thereby ESCRT-0 and ubiquitinated cargo could act as timers determining the onset of Rab conversion.

cell biology↗

bioRxiv2024

Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

neuroscience↗

bioRxiv2024

High-resolution Inference of Multiplexed Anti-HIV Gene Editing using Single-Cell Targeted DNA Sequencing

Gene therapy-based HIV cure strategies typically aim to excise the HIV provirus directly, or target host dependency factors (HDFs) that support viral persistence. Cure approaches will likely require simultaneous co-targeting of multiple sites within the HIV genome to prevent evolution of resistance, and/or co-targeting of multiple HDFs to fully render host cells refractory to HIV infection. Bulk cell-based methods do not enable inference of co-editing within individual viral or target cell genomes, and do not discriminate between monoallelic and biallelic gene disruption. Here, we describe a targeted single-cell DNA sequencing (scDNA-seq) platform characterizing the near full-length HIV genome and 50 established HDF genes, designed to evaluate anti-HIV gene therapy strategies. We implemented the platform to investigate the capacity of multiplexed CRISPR-Cas9 ribonucleoprotein complexes (Cas9-RNPs) to simultaneously 1) inactivate the HIV provirus, and 2) knockout the CCR5 and CXCR4 HDF (entry co-receptor) genes in microglia and primary monocyte-derived macrophages (MDMs). Our scDNA-seq pipeline revealed that antiviral gene editing is rarely observed at multiple loci (or both alleles of a locus) within an individual cell, and editing probabilities across sites are linked. Our results demonstrate that single-cell sequencing is critical to evaluate the true efficacy and therapeutic potential of HIV gene therapy.

genomics↗

bioRxiv2024

SORBET: Automated cell-neighborhood analysis of spatial transcriptomics or proteomics for interpretable sample classification via GNN

Spatial cellular profiling technologies have revolutionized our understanding of complex biological processes, from development and disease progression to immunity and aging. Despite their promise, integrating spatial information with multiplexed molecular data to accurately predict phenotypes poses significant challenges, especially in clinical settings. Here, we present SORBET, a geometric deep learning framework that directly analyzes complete spatial profiling data, eliminating the need to compress complete cell profiles into a limited set of annotations, such as cell types. SORBET models tissues as graphs of adjacent cells and applies graph convolutional networks to infer emergent phenotypes, such as responses to immunotherapy. The model leverages a novel data augmentation technique to ensure robust predictions, complemented by tailored interpretability analyses to identify the molecular and spatial patterns underlying the models phenotype inferences. We apply our method to a CosMx spatial transcriptomics dataset of pre-treatment metastatic melanoma samples annotated with response to immunotherapy; we show that spatial information significantly improves clinical endpoint, or phenotype, prediction and identifies important biological patterns. To our knowledge, SORBET is the first example of phenotype prediction on spatial transcriptomics data. We further validated our method using two spatial proteomics datasets, Imaging Mass Cytometry (IMC) and Co-detection by indexing (CODEX), obtained from Non-Small Cell Lung Cancer and Colorectal Cancer samples, respectively. SORBET demonstrates superior accuracy in phenotype prediction over leading spatial and non-spatial methods across various datasets of different observed phenotypes and technologies. SORBET sets a new benchmark for predictive analysis in spatial omics, promising to advance personalized medicine through refined patient treatment stratification, grounded in molecular and spatial tissue profiling.

bioinformatics↗

bioRxiv2023

RpoS activates Salmonella Typhi biofilms and drives persistence in a Zebrafish model

The development of strategies for targeting the asymptomatic carriage of Salmonella Typhi in chronic typhoid patients has suffered owing to our basic lack of understanding of the molecular mechanisms that enable the formation of S. Typhi biofilms. Traditionally, studies have relied on cholesterol-attached biofilms formed by a closely related serovar, Typhimurium, to mimic multicellular Typhi communities formed on human gallstones. In long-term infections, S. Typhi adopts the biofilm lifestyle to persist in vivo and survive in the carrier state, ultimately leading to the spread of infections via the fecal-oral route of transmission. In the present work, we studied S. Typhi biofilms directly, applied targeted as well as genome-wide genetic approaches to uncover unique biofilm components that do not conform to the CsgD-dependent pathway established in S. Typhimurium. We undertook a genome-wide Tn5 mutation screen in H58, a clinically relevant multidrug resistance strain of S. Typhi, in gallstone-mimicking conditions. We generated New Generation Sequencing libraries based on the ClickSeq technology to identify the key regulators, IraP and RpoS, and the matrix components Sth fimbriae, Vi capsule and lipopolysaccharide. We discovered that the starvation sigma factor, RpoS, was required for the transcriptional activation of matrix-encoding genes in vitro, and for S. Typhi colonization in persistent infections in vivo, using a heterologous fish larval model. An rpoS null mutant failed to colonize the gall bladder in chronic zebrafish infections. Overall, our work uncovered a novel RpoS-driven, CsgD-independent paradigm for the formation of cholesterol-attached Typhi biofilms, and emphasized the role(s) of stress signaling pathways for adaptation in chronic infections. Our identification of the biofilm regulators in S. Typhi paves the way for the development of drugs against typhoid carriage, which will ultimately control the increased incidence of gall bladder cancer in typhoid carriers.

microbiology↗

bioRxiv2023

GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses

Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter (https://muster.jax.org), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

genetics↗

bioRxiv2022

Syndecan-4 Proteoliposomes Enhance Revascularization in a Rabbit Hind Limb Ischemia Model of Peripheral Ischemia

Regenerative therapeutics for treating peripheral arterial disease are an appealing strategy for creating more durable solutions for limb ischemia. In this work, we performed preclinical testing of an injectable formulation of syndecan-4 proteoliposomes combined with growth factors as treatment for peripheral ischemia delivered in an alginate hydrogel. We tested this therapy in an advanced model of hindlimb ischemia in rabbits with diabetes and hyperlipidemia. Our studies demonstrate enhancement in vascularity and new blood vessel growth with treatment with syndecan-4 proteoliposomes in combination with FGF-2 or FGF-2/PDGF-BB. The effects of the treatments were particularly effective in enhancing vascularity in the lower limb with a 2-4 increase in blood vessels in the treatment group in comparison to the control group. In addition, we demonstrate that the syndecan-4 proteoliposomes have stability for at least 28 days when stored at 4{degrees}C to allow transport and use in the hospital environment. In addition, we performed toxicity studies in the mice and found no toxic effects even when injected at high concentration. Overall, our studies support that syndecan-4 proteoliposomes markedly enhance the therapeutic potential of growth factors in the context of disease and may be promising therapeutics for inducing vascular regeneration in peripheral ischemia.

bioengineering↗

bioRxiv2022

Upregulation of Trem2 expression occurs exclusively on microglial contact with plaques

Using spatial cell-type-enriched transcriptomics, we compare plaque-induced gene (PIG) expression in microglia touching plaques, neighboring plaques, and far from plaques in 18-month-old APPNLF/NLF knock-in mice with and without the Alzheimers disease risk mutation Trem2R47H/R47H. We report that, in AppNLF/NLF mice, expression of 35/55 PIGs, is exclusively upregulated in microglia that are touching plaques. In 7 PIGs including Trem2 this upregulation is prevented by the Trem2R47H/R47H mutation. Unlike in young mice, knockin of the Trem2R47H/R47H mutation does not significantly decrease the Trem2 expression but decreases protein levels by 20% in the absence of plaques. On plaques, despite the mutation preventing increased gene expression, TREM2 protein levels increased by 1.6-fold (compared to 3-fold with Trem2WT/WT) and microglial density increased 20-fold compared to 30-fold. Hence microglia must touch plaques before Trem2 gene expression is increased but small changes in protein expression can increase microglia density without a change in gene expression.

neuroscience↗

bioRxiv2021

Kinetic tracking of Plasmodium falciparum antigen presentation reveals determinants of protein export and membrane insertion

Intracellular malaria parasites export many proteins into their host cell, inserting several into the erythrocyte plasma membrane to enable interactions with their external environment. While static techniques have identified some surface-exposed proteins, other candidates have eluded definitive localization and membrane topology determination. Moreover, both export kinetics and the mechanisms of membrane insertion remain largely unexplored. We introduce Reporter of Insertion and Surface Exposure (RISE), a method for continuous nondestructive tracking of antigen exposure on infected cells. RISE utilizes a small 11 aa NanoLuc fragment inserted into a target protein and detects surface exposure through high-affinity complementation. We tracked insertion of CLAG3, a malaria parasite protein linked to nutrient uptake, throughout the P. falciparum cycle in human erythrocytes. Our approach also revealed key determinants of trafficking and surface exposure. Removal of a C-terminal transmembrane domain aborted export. Unexpectedly, certain increases in the exposed reporter size improved surface exposure by up to 50-fold, revealing that both size and charge of the extracellular epitope influence membrane insertion. Insertion of parasite proteins at the host cell surface and antigen accessibility is regulated by multiple factors, enabling intracellular parasite survival and immune evasion under a broad range of conditions.

microbiology↗

bioRxiv2021

Genomic evolution of the globally disseminated multidrug-resistant Klebsiella pneumoniae clonal group 147

BackgroundThe rapid emergence of multidrug-resistant Klebsiella pneumoniae (Kp) is largely driven by the spread of specific clonal groups (CG). Of these, CG147 includes 7-gene MLST sequence types ST147, ST273 and ST392. CG147 has caused nosocomial outbreaks across the world, but its global population dynamics remain unknown. Here, we report a pandrug-resistant ST147 clinical isolate from India (strain DJ) and define the evolution and global emergence of CG147. MethodsAntimicrobial susceptibility testing (EUCAST guidelines) and genome sequencing (Illumina and Oxford Nanopore technologies, Unicycler assembly) were performed on strain DJ. Additionally, we collated 217 publicly available CG147 genomes (NCBI, May 2019). CG147 evolution was inferred within a temporal phylogenetic framework (BEAST) based on a recombination-free sequence alignment (Roary/Gubbins). Comparative genomic analyses focused on resistance and virulence genes and other genetic elements (BIGSdb, Kleborate, PlasmidFinder, PHASTER, ICEFinder and CRISPRCasFinder). ResultsStrain DJ had a pandrug resistance phenotype. Its genome comprised 7 plasmids and 1 linear phage-plasmid. Four carbapenemase genes were detected: blaNDM-5 and 2 copies of blaOXA-181 in the chromosome, and a second copy of blaNDM-5 on an 84 kb IncFII plasmid. CG147 genomes carried a mean of 13 acquired resistance genes or mutations; 63% carried a carbapenemase gene and 83% harbored blaCTX-M. All CG147 genomes presented GyrA and ParC mutations and a common subtype IV-E CRISPR-Cas system. ST392 and ST273 emerged in 2005 and 1995, respectively. ST147, the most represented phylogenetic branch, was itself divided into two main clades with distinct capsular loci: KL64 (74%, DJ included, emerged in 1994 and disseminated worldwide, with carbapenemases varying among world regions) and KL10 (20%, 2002, predominantly found in Asian countries, associated with carbapenemases NDM and OXA-48-like). Further, subclades within ST147-KL64 differed in the yersiniabactin locus, OmpK35/K36 mutations, plasmid replicons and prophages. The absence of IncF plasmids in some subclades was associated with a possible activity of a CRISPR-Cas system. ConclusionsK. pneumoniae clonal group CG147 comprises pandrug- or extensively-resistant isolates and carries multiple and diverse resistance genes and mobile genetic elements, including chromosomal blaNDM-5. Its emergence is driven by the spread of several phylogenetic clades marked by their own genomic features and specific temporo-spatial dynamics. These findings highlight the need for precision surveillance strategies to limit the spread of particularly concerning CG147 subsets.

genomics↗

bioRxiv2021

Precision neoantigen discovery using large-scale immunopeptidomes and composite modeling of MHC peptide presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anti-cancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass-spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past two decades. However, improvement in the sensitivity and specificity of prediction algorithms is needed for clinical applications such as the development of personalized cancer vaccines, the discovery of biomarkers for response to checkpoint blockade and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 mono-allelic cell lines and created Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale mono-allelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA alleles to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC binding pocket diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 mono-allelic and 384 multi-allelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44 fold improvement of positive predictive value compared to existing tools when evaluated on independent mono-allelic datasets and a 1.15 fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

bioinformatics↗

bioRxiv2020

Graph of graphs analysis for multiplexed data with application to imaging mass cytometry

Hyper spectral imaging, sensor networks, spatial multiplexed proteomics, and spatial transcriptomics assays is a representative subset of distinct technologies from diverse domains of science and engineering that share common data structures. The data in all these modalities consist of high-dimensional multivariate observations (m-dimensional feature space) collected at different spatial positions and therefore can be analyzed using similar computational methodologies. Furthermore, in many studies practitioners collect datasets consisting of multiple spatial assays of this type, each capturing such data from a single biological sample, patient, or hyper spectral image, etc. Each of these spatial assays could be characterized by several regions of interest (ROIs). The focus of this paper is on a particular application, imaging mass cytometry (IMC), which falls into this problem setup. To extract meaningful information from the multi-dimensional observations recorded at different ROIs across different assays, we propose to analyze such datasets using a two-step graph-based approach. We first construct for each ROI a graph representing the interactions between the m covariates and compute an m dimensional vector characterizing the steady state distribution among features. We then use all these m-dimensional vectors to construct a graph between the ROIs from all assays. This second graph is subjected to a nonlinear dimension reduction analysis, retrieving the intrinsic geometric representation of the ROIs. Such a representation provides the foundation for efficient and accurate organization of the different ROIs that correlates with their phenotypes. Theoretically, we show that when the ROIs have a particular bi-modal distribution, the new representation gives rise to a better distinction between the two modalities compared to the maximum a posteriori (MAP) estimator. We applied our method to predict the sensitivity to PD-1 axis blockers treatment of lung cancer subjects based on IMC data, achieving 92% accuracy. This serves as empirical evidence that the graph of graphs approach enables us to integrate multiple ROIs and the intra-relationships between the features at each ROI, giving rise to an informative representation that is strongly associated with the phenotypic state of the entire image. Importantly, this approach is applicable to other modalities such as spatial transcriptomics. Author summaryWe propose a two-step graph-based analyses for high-dimensional multiplexed datasets characterizing ROIs and their inter-relationships. The first step consists of extracting the steady state distribution of the random walk on the graph, which captures the mutual relations between the covariates of each ROI. The second step employs a nonlinear dimensionality reduction on the steady state distributions to construct a map that unravels the intrinsic geometric structure of the ROIs. We show theoretically that when the ROIs have a two-class structure, our method accentuates the distinction between the classes. Particularly, in a setting with Gaussian distribution it outperforms the MAP estimator, implying that the mutual relations between the covariates and spatial coordinates are well captured by the steady state distributions. We apply our method to imaging mass cytometry (IMC). Our analysis provides a representation that facilitates prediction of the sensitivity to PD-1 axis blockers treatment of lung cancer subjects. Particularly, our approach achieves state of the art results with accuracy of 92%.

bioinformatics↗

bioRxiv2020

Durable Control of HIV-1 Using a Staphylococcus aureus Cas9-Expressing Lentivirus Co-Targeting Viral Latency and Host Susceptibility

CRISPR/Cas9 gene editing has the potential to revolutionize the clinical management of HIV-1 infection, and may eliminate the need for antiretroviral therapy (ART). Current gene therapies attempt to either excise HIV-1 provirus or target HIV-1 entry receptors to prevent infection of new cells. Using a viral dynamic model, we determined that combining these two interventions, in the presence or absence of ART, significantly lowers the gene editing efficacy thresholds required to achieve an HIV-1 cure. To implement this dual-targeting approach, we engineered a single lentiviral vector that simultaneously targets multiple highly-conserved regions of the provirus and the host CXCR4 coreceptor, and developed a novel coculture system enabling real-time monitoring of latent infection, viral reactivation, and infection of new target cells. Simultaneous dual-targeting depleted HIV-1-infected cells with significantly greater potency than vectors targeting either virus or host independently, highlighting its potential as an HIV-1 cure strategy.

microbiology↗

bioRxiv2020

Biomechanical Regulation of Breast Cancer Metastasis and Progression

Physical activity has been consistently linked to decreased incidence of breast cancer and a substantial increase in the length of survival of patients with breast cancer. However, the understanding of how applied physical forces directly regulate breast cancer remains limited. We investigated the role of mechanical forces in altering the chemoresistance, proliferation and metastasis of breast cancer cells. We found that applied mechanical tension can dramatically alter gene expression in breast cancer cells, leading to decreased proliferation, increased resistance to chemotherapeutic treatment and enhanced adhesion to inflamed endothelial cells and collagen I under fluidic shear stress. A mechanistic analysis of the pathways involved in these effects supported a complex signaling network that included Abl1, Lck, Jak2 and PI3K to regulate pro-survival signaling and enhancement of adhesion under flow. Studies using mouse xenograft models demonstrated reduced proliferation of breast cancer cells with orthotopic implantation and increased metastasis to the skull when the cancer cells were treated with mechanical load. Using high throughput mechanobiological screens we identified pathways that could be targeted to reduce the effects of load on metastasis and found that the effects of mechanical load on bone colonization could be reduced through treatment with a PI3K{gamma} inhibitor.

cancer biology↗

bioRxiv2019

Alzheimer’s genetic risk factor FERMT2 (Kindlin-2) is regulated by risk allele-binding of miR-4504 and leads to synaptic dysfunction in an APP-dependent manner

Although APP metabolism is being intensively investigated, a large fraction of its modulators are yet to be characterized. In this context, we combined two genome-wide high-content screenings to assess the functional impact of miRNAs and genes on APP metabolism and the signaling pathways involved. This approach highlighted the involvement of FERMT2 (or Kindlin-2), a genetic risk factor of Alzheimers disease (AD), as a potential key modulator of axon guidance; a neuronal process that depends on the regulation of APP metabolism. We found that FERMT2 directly interacts with APP to modulate its metabolism and that FERMT2 under-expression impacts axonal growth, synaptic connectivity and long-term potentiation in an APP-dependent manner. Lastly, the rs7143400-T allele, which is associated with an increased AD risk and localized within the 3UTR of FERMT2, induced a down-regulation of FERMT2 expression through binding of miR-4504 among others. This miRNA is mainly expressed in neurons and significantly overexpressed in AD brains compared to controls. Altogether, our data provide strong evidence for a detrimental effect of FERMT2 under-expression in neurons and insight on how this may influence AD pathogenesis.

pathology↗

bioRxiv2019

Kappa Opioid Receptor and Dynorphin Signaling in the Central Amygdala Regulates Alcohol Intake

Excessive alcohol drinking has been shown to modify brain circuitry to predispose individuals for future alcohol abuse. Previous studies have implicated the central nucleus of the amygdala (CeA) as an important site for mediating the somatic symptoms of withdrawal and for regulating alcohol intake. In addition, recent work has established a role for both the Kappa Opioid Receptor (KOR) and its endogenous ligand dynorphin in mediating these processes. However, it is unclear whether these effects are due to dynorphin or KOR arising from within the CeA itself or other input brain regions. To directly examine the role of preprodynorphin (PDYN) and KOR expression in CeA neurons, we performed region-specific conditional knockout of these genes and assessed the effects on the Drinking in the Dark (DID) and Intermittent Access (IA) paradigms. We then examined the effects of DID on PDYN and KOR modulation of CeA circuit physiology. Conditional gene knockout resulted in sex-specific responses wherein PDYN knockout decreased alcohol drinking in both male and female mice, whereas KOR knockout decreased drinking in males only. We also found that neither PDYN nor KOR knockout protected against anxiety caused by alcohol drinking. Lastly, a history of alcohol drinking did not alter synaptic transmission in PDYN neurons in the CeA of either sex, but excitability of PDYN neurons was increased in male mice only. Taken together, our findings indicate that PDYN and KOR signaling in the CeA plays an important role in regulating excessive alcohol consumption and highlight the need for future studies to examine how this is mediated through downstream effector regions.

neuroscience↗