bioRxiv Science⌕ Search

Biology subjects

Sharma, M.

Publications and source records attributed to Sharma, M..

At least 73 records · Page 4Linked to original sources

Mapping Chromatin Interactions of ZBP1 and ADAR Z-Alpha Domains: A ChIP-Seq Based Comparison

The DNA double helix typically exists in the canonical B-form conformation, but this structure often can adopt the unique alternative form known as Z-DNA. In Z-DNA, the DNA helix winds to the left in a zigzag pattern instead of the right-handed B-DNA form. Z-DNA is thought to play a key role in transcription, but it is unclear whether is a positive or negative regulator of RNA polymerase activity. Additionally, several studies have shown how Z-DNA contributes to DNA damage or genome instability. However, the precise role of Z-DNA in the genome remains unclear. To address this question, we mapped Z-DNA using a ChIP-Seq assay with two Z-DNA biosensors: Zaa-Zbp1, comprised of a dimerized Z-alpha Z-DNA binding domains from Z-DNA binding protein 1 (Zbp1), and Zaa-Adar1, comprised of dimerized Z-alpha domains from Adenosine deaminase acting on RNA 1 (Adar1). We found that these Zaa probes possessed similar binding profiles when analyzed with motif analysis, but gene ontology analysis revealed that these Z-alpha domains bound to heterogeneous genes, with Zaa-Zbp1 most strongly binding to genes in the RHOQ-GTPase pathway and Zaa-Adar1 binding to genes involved in the M phase of the cell cycle.

genomics↗

The microbiome diversifies N-acyl lipid pools - including short-chain fatty acid-derived compounds

N-acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet, microbial colonization, and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

bioinformatics↗

Building neurovascular tissue from autologous blood for modeling brain-activity

There are no faithful individualized stem cell-based bioengineered neuro-vascularized models that can recapitulate the physiological hemodynamic phenomenon of neuro-vascular coupling (NVC)-the principal behind BOLD (blood oxygen level-dependent) signal in functional neuroimaging, thereby dissuading the research in exploring the brain activity-based investigative studies in neurological/neurosensory diseases. This encouraged us to establish a preclinical optoacoustic (Hb/dHb hemoglobin/deoxyhemoglobin) imaging-competent in vitro neuro-vascularized model by employing a novel cellular reprograming PITTRep (Plasma Induced Transcriptomics/ epi-Transcriptomics Reprograming) approach. The current reprograming approach is based on coaxing autologous blood components to ecto-mesodermal lineage intermediates that can subsequently self-pattern into neurovascular tissue by harnessing the hemorheological properties of RBCs. The nature of blood flow is non-Newtonian and is a function of RBC concentration /haematocrit when they flow through the regions of low shear rates as seen in cerebral microcirculation. The current reprograming approach is a modification of our previous cellular reprograming approach that employed a Newtonian plasma fluid. The autologous blood-derived neurovascular tissue is free from exogenous genetic modification, external growth factors, and induced pluripotent stem cell (iPSC) derivation. This model uniquely integrates functional vasculature and neurogenesis. The current reprogramming approach resulted (in part) serendipitously while testing a potential (yet completely unexplored) hypothesis of haemodynamic reprograming by leveraging the fluid mechanic feature of blood erythrocytes as seen in thrombus formation during cerebral ischemic stroke, that is characterized by physiologically intriguing yet clinically meaningful neurological recovery (neuroplasticity) during an early time window. The current study attempted to induce "a post stroke-like model" of adult neurogenesis with functional synaptogenesis by instructing autologous blood components into thrombus formation through incorporation of erythrocytes in varying concentrations. We tried to instruct adult neurogenesis and neuroplasticity (a relatively non-resilient phenomenon under in vitro conditions) by co-induction of a neuro-vascular niche (NVN). These NVNs are marked by dendrites, synapses, astrogliosis, microglia activation, and growth factor signaling, thus phenocopying molecular and cellular aspects of post-stroke recovery window. The induction of neuro-vascularized niches and functional neuro-vascular coupling (NVC) was characterized by confocal microscopy, scanning electron microscopy, proteomic profiling, and Hb/dHb spectra based optoacoustic imaging. The blood thrombus formation was checked by rotational thromboelastometry (ROTEM), and switching of adult-to-embryonic hemoglobin was confirmed by routine hemoglobin typing. We also attempted to establish patient-specific neuro-vascularized niches from autologous blood of sensorineural hearing loss (SNHL) patients. The individualized neovascularised tissues are intended to be employed for investigating deregulated synaptic plasticity/ long term potentiation underlying poor auditory comprehension outcomes in school going kids suffering from SNHL that greatly compromises their academic performance and socio-behavioural-cognitive development. The attendant multiomics of patient-specific NVNs may have potential implications in developing stem-cell based therapies for neurosensory and cerebrovascular diseases.

neuroscience↗

TECPR2 is a Rab5 effector that regulates endosomal cargo recycling

Small GTP-binding (G) proteins of the Rabs, Arfs, and Arls (Arf-like) family mediate the recruitment of their effectors to subcellular membrane-bound compartments, which in turn mediates vesicle budding, motility, and tethering. Here, we report that Tectonin-{beta}-propeller repeat containing protein 2 (TECPR2), a protein mutated in a form of hereditary sensory and autonomic neuropathy (HSAN), is an effector of early endosomal Rab protein, Rab5, and interacts with Rab5 via its C-terminal TECPR repeats. The HSAN-associated TECPR2 (R1336W) missense variant was deficient in Rab5-binding and, consequently, in membrane recruitment. TECPR2-depletion led to perinuclear collapse of recycling endosomes and increased overlap of sorting and degradative subdomain markers on early endosomes. Consistent with a possible role in endocytic recycling, we observed impaired recycling and increased lysosomal degradation of 5{beta}1 integrin receptors upon TECPR2 knockdown. TECPR2 regulates the early endosomal localization of the cargo adaptor for {beta}1 integrins, SNX17, and its-associated protein complex WASH, which mediates actin polymerization on early endosomes. Finally, TECPR2 depletion in the zebrafish model resulted in delayed motility and changes in the neuromuscular junction. Our study supports an early endosomal role for TECPR2 in cargo recycling and provides insights into how its loss-of- function results in a neurodegenerative genetic disorder.

cell biology↗

Cryo-EM structures of human GPR155 elucidate its regulatory and transport mechanisms

GPR155 is a polymodal lysosomal membrane "transceptor" comprising both a transporter domain and a GPCR domain, predominantly expressed in brain. GPR155 facilitates cholesterol-dependent mTORC1 signaling and is implicated in neurological disorders like Huntingtons disease. The GPCR domain likely does not bind extracellular ligands canonically, and the functional relationship between GPR155 domains remains unclear. Here, we report the first structures of monomeric human GPR155 and two distinct dimers, revealing an inward-open transporter domain and an inactivated GPCR domain with a unique luminal loop 7 conformation occupying orthosteric pocket. The dimeric assembly is cholesterol-sensitive: at low cholesterol, the transporter domain resembles plant PIN transporters and transports auxin molecules; at high cholesterol, it forms a unique dimer stabilized by cholesterol. Altogether, these findings have implications for uncovering new lysosomal signaling pathways.

biochemistry↗

Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults

The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age.

immunology↗

Enhanced Piezoelectric Performance of PVDF-TrFE Nanofibers through Annealing for Tissue Engineering Applications

This study investigates bioelectric stimulations role in tissue regeneration by enhancing the piezoelectric properties of tissue-engineered grafts using annealed poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) scaffolds. Annealing at temperatures of 80{degrees}C, 100{degrees}C, 120{degrees}C, and 140{degrees}C was assessed for its impact on material properties and physiological utility. Analytical techniques such as Differential Scanning Calorimetry (DSC), Fourier-Transform Infrared Spectroscopy (FTIR), and X-ray Diffraction (XRD) revealed increased crystallinity with higher annealing temperatures, peaking in {beta}-phase content and crystallinity at 140{degrees}C. Scanning Electron Microscopy (SEM) showed that 140{degrees}C annealed scaffolds had enhanced lamellar structures, increased porosity, and maximum piezoelectric response. Mechanical tests indicated that 140{degrees}C annealing improved elastic modulus, tensile strength, and substrate stiffness, aligning these properties with physiological soft tissues. In vitro assessments in Schwann cells demonstrated favorable responses, with increased cell proliferation, contraction, and extracellular matrix attachment. Additionally, genes linked to extracellular matrix production, vascularization, and calcium signaling were upregulated. The foreign body response in C57BL/6 mice, evaluated through Hematoxylin and Eosin (H&E) and Picrosirius Red staining, showed no differences between scaffold groups, supporting the potential for future functional evaluation of the annealed group in tissue repair.

bioengineering↗

An in-silico comparative analysis of lncRNA expression and their role in the pathogenesis of representative fungal, bacterial and viral infections in rice

Long non-coding RNAs (lncRNAs) perform prominent role in the regulation of gene expression during plant development and stress response by directly interacting with DNA, RNA, proteins, and/or triggering production of small regulatory RNA molecules. The objective of our study is to understand the systems-level response of the same plant species to highly diverse pathogens across different kingdoms and evaluate the patterns of similarity vs differences, specifically in the context of lncRNAs. Towards this objective, we performed a comparative in silico analysis of lncRNAs of Rice that are differentially expressed in response to infection by bacteria (Xanthomonas oryzae), fungus (Magnaporthe oryzae) and virus (Rice black dwarf virus). Using a tailored lncRNA analysis pipeline, we successfully identified 1125, 719 and 240 lncRNAs in Xanthomonas oryzae infection susceptible cultivar CT9737-6-1-3P-M, Magnaporthe oryzae susceptible LTH accession, and Rice black streaked dwarf virus susceptible Wuyujing No. 7 rice cultivars respectively. The in-silico predicted Cis- and Trans-target genes of lncRNAs were subsequently used to identify the pathways modulated by these lncRNA and how they cluster into unique categories of plant responses to pathogen infections. To further substantiate the role of predicted lncRNAs in plant defence and immune response our analysis finds that many of the lncRNAs co-localize with the QTLs associated with Blast and Bacterial blight resistance in rice. Our in silico analysis provides a list of common and unique pathogen specific lncRNAs that can provide vital insights into the generic vs tailored mechanisms adopted by rice in different infection scenarios.

plant biology↗

Social clues in risky pools: Perceived conspecific rivals strongly modify individual oviposition decisions in response to larval predation and competition

Reproductive choices are imperative in shaping organismal fitness across diverse taxa. Such choices are particularly critical in organisms with biphasic lifecycles, as females must maximize offspring survival pre-oviposition, with no parental care extended afterward. Consequently, females face strong site selection pressures to effectively respond to offspring competition and predation risks. Ovipositing females encounter yet another challenge during site selection: assessing future competition for their offspring from potential conspecific rivals. Our current knowledge, based on average social versus solitary behaviours, fails to clarify how social signals influence individual behavior within groups. To address these challenges, we leveraged the unique oviposition biology of the mosquito Aedes aegypti where only blood-fed females can lay eggs. By tracking individual behaviour in a social setting, we ask: how does social information from perceived conspecific rivals influence an individuals oviposition site selection? In our lab-based experiment, we examined oviposition strategies at two spatial scales under varying larval competition and predation risk. Our findings reveal that social information exerts a stronger influence on egg-laying behavior at larger spatial scales, i.e., at the scale of pool networks, than between neighboring pools. Social cues facilitated oviposition with increasing larval predation, as social females transitioned from rejecting to accepting pool networks. Conversely, under larval competition, social cues led to inhibition, with females withholding their eggs likely in anticipation of future competition. At finer spatial scales, social information only weakly modified oviposition behavior despite potential negative fitness consequences for the offspring. Thus, perceived conspecific risk strongly modifies oviposition--facilitation, inhibition, or no effect--and is scale-dependent.

ecology↗

Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-m-thick, mechanically flexible micro-electrocorticography (ECoG) BCI, integrating a 256x256 array of electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording channels, from which we can simultaneously record a selectable subset of up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.

neuroscience↗

eIF4A controls translation of estrogen receptor alpha and is a therapeutic target in advanced breast cancer

The majority of human breast cancers are dependent on hormone-stimulated estrogen receptor alpha (ER) and are sensitive to its inhibition. Treatment resistance arises in most advanced cancers due to genetic alterations that promote ligand independent activation of ER itself or ER target genes. Whereas re-targeting of the ER ligand binding domain (LBD) with newer ER antagonists can work in some cases, these drugs are largely ineffective in many genetic backgrounds including ER fusions that lose the LBD or in cancers that hyperactivate ER targets. By identifying the mechanism of ER translation, we herein present an alternative strategy to target ER and difficult to treat ER variants. We find that ER translation is cap-independent and mTOR inhibitor insensitive, but dependent on 5 UTR elements and sensitive to pharmacologic inhibition of the translation initiation factor eIF4A, an mRNA helicase. EIF4A inhibition rapidly reduces expression of ER and short-lived targets of ER such as cyclin D1 and other components of the cyclin D-CDK complex in breast cancer cells. These effects translate into suppression of growth of a variety of ligand-independent breast cancer models including those driven by ER fusion proteins that lack the ligand binding site. The efficacy of eIF4A inhibition is enhanced when it is combined with fulvestrant--an ER degrader. Concomitant inhibition of ER synthesis and induction of its degradation causes synergistic and durable inhibition of ER expression and tumor growth. The clinical importance of these findings is confirmed by results of an early clinical trial (NCT04092673) of the selective eIF4A inhibitor zotatifin in patients with estrogen receptor positive metastatic breast cancer. Multiple clinical responses have been observed on combination therapy including durable regressions. These data suggest that eIF4A inhibition could be a useful new strategy for treating advanced ER+ breast cancer.

cancer biology↗

Explainable models using transcription factor binding and epigenome patterns at promoters reveal disease-associated genes and their regulators in the context of cell-types

Understanding genome-wide epigenetic regulation of diseases is important in establishing pathogenic factors and could aid in disease diagnosis, prognosis, and therapeutics. In this study, we have utilized transcription factors (TFs) and co-factor profiles (n=823) as features in machine learning models to link them to various diseases. Further, along with TFs and co-factor profiles, histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) as features allowed for the modeling of association of coding and non-coding genes to diseases. Such predicted associations could be independently validated using genome-wide association data and survival analysis. However, the unique aspect of our approach is that it highlights the link between TF binding patterns and diseases in the context of cell types. Besides highlighting relevant TF-binding in known cell-types associated with diseases, it also provided their surprising link with TFs expressed in immune cells and other seemingly non-related cells. Further investigation revealed such links to be genuine and potentially useful for prognosis, further revealing the need to deconvolve a set of known genes associated with diseases.

bioinformatics↗

Characterization and classification of fine-resolution soil profile for precision agriculture using random forest and self-organizing map

The availability of high throughput soil profile information is an important component in precision agriculture to perform efficient soil management for sustainable production. We collected 14 soil physiochemical features from Nagpur, Pune, and Haveri, representing target environments of safflower cultivation and also from our experiment station at Delhi, at fine resolution and created graphical maps to depict the variability. Additionally, we evaluated the predictive ability of two statistical learning models, random forest (RF) and self-organizing maps (SOM) against multinomial regression models for correctly classifying the soil profile. Clustering was performed around the medoids produced from the dissimilarity matrices of these models using partitioning around medoids (PAM) model. The robustness, versatility, and predictive ability of models in correctly classifying the soil profile to clusters were then tested using cross-validation which was repeated 100 times. This study was performed using training data with proportionate size varying from 60 to 95%, and increasing the unit area of observation up to nine times (or decreasing the total number of observations up to a ninth). RF model was found to be the best performing with average prediction accuracy above 85% in all settings which reached close to 100% in some settings. The predictive ability of all the models was maintained even when only the most influencing six variables were used for classification. The optimal training population size for prediction was found to be 70 - 80%. Based on our study, it is recommended to i) collect fine resolution edaphic features from a marginal farm before crop season, ii) use RF or SOM model to identify the most influencing features distinguishing the soil samples iii) expand the area of sample collection, find values for the most influencing features, and use RF model to correctly predict the class to which the new set of the soil belongs to. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/587707v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@2f404forg.highwire.dtl.DTLVardef@2707c2org.highwire.dtl.DTLVardef@6e6418org.highwire.dtl.DTLVardef@16da481_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

Genetic interaction library screening with a next-generation dual guide CRISPR system

Pairwise perturbation of gene function using the CRISPR/Cas9 system has huge potential in screening for genetic interactions and synthetic lethal gene pairs to identify novel combination therapies for cancer. However, existing dual guide expression systems are cumbersome to clone, often result in a large proportion of undesired guide pairs and have imbalance of guide expression from the two positions. Here, we demonstrate a next-generation system for dual guide delivery based around a tRNA spacer that allows a single step cloning strategy, as little as 2% of undesired guide pairs, and highly balanced expression of the two guides. This system allows efficient library-scale screening for hundreds of thousands of genetic interactions using the well understood Streptococcus pyogenes Cas9 (SpCas9) system. We use this to screen a 100,136 guide pair library in colorectal cancer cells and successfully identify synthetic lethal genetic interactions between paralogs or other known interacting genes, establishing our method for performing efficient large scale genetic interaction screens. This system is versatile and can be used with most guide RNA vector systems, and for other uses of paired guide delivery such as improving single gene knockout efficiency or improving guide detection in single cell or optical CRISPR screens.

molecular biology↗

Comprehensive Invitro and Insilico Analysis of Secondary Metabolites from Datura metel: Promising Anti-Alzheimer's Therapeutics.

This research investigates secondary metabolites from Datura metel as potential anti-Alzheimers therapies. In vitro techniques isolated extracts for AD pathology targeting, with in silico analysis identifying gene targets for prevention. Apigenin, Luteolin, and Withanolide A were studied, each with 300 potential gene targets and core gene counts of 54, 52, and 58 respectively. Lipinskis Rule assessed their pharmacological properties, showing good absorption but limited blood-brain barrier penetration. Protein interaction mapping revealed shared targets among the compounds. GO enrichment and KEGG pathway analysis highlighted their impact on biological processes and pathways, suggesting their anti-Alzheimers potential. Luteolin notably reduced A{beta}1-42 levels by up to 35.2% (*p<0.05) in SH-SY5Y cells, positioning it and Withanolide A as promising multi-functional Alzheimers medications. These findings underscore the significance of Datura phytochemicals in AD prevention and treatment.

neuroscience↗

Machine Learning Approaches in Label-Free Small Extracellular Vesicles Analysis with Surface-Enhanced Raman Scattering (SERS) for Cancer Diagnostics

Early diagnosis remains of pivotal importance in reducing patient morbidity and mortality in cancer. To this end, liquid biopsy is emerging as a tool to perform broad cancer screenings. Small extracellular vesicles (sEVs), also called exosomes, found in bodily fluids can serve as important cancer biomarkers in these screenings. Our group has recently developed a label-free electrokinetic microchip to purify sEVs from blood. Herein, we demonstrate the feasibility to integrate this approach with surface-enhanced Raman scattering (SERS) analysis. SERS can be used to characterized extracted sEVs through their vibrational fingerprint that changes depending on the origin of sEVs. While these changes are not easily identified in spectra, they can be modeled with machine learning (ML) approaches. Common ML approaches in the field of spectral analysis use dimensionality reduction method that often function as a black box. To avoid this pitfall, we used Shapley additive explanations (SHAP) is a type of explainable AI (XAI) that bridges ML models and human comprehension by calculating the specific contribution of individual features to a models predictions, directly correlating model/decisions with the original data. Using these approaches we demonstrated a proof-of-concept model predictive of cancer from isolated sEVs, integrating the electrokinetic device and SERS. This work explores the use of explainable AI to perform diagnostic analysis on complex SERS data of clinical samples, while reporting interpretable biochemical information. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/581099v2_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1cbcb8aorg.highwire.dtl.DTLVardef@9ffc00org.highwire.dtl.DTLVardef@15999a9org.highwire.dtl.DTLVardef@1775726_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Neuroinflammation underlies the development of social stress induced cognitive deficit in sickle cell disease.

Cognitive deficit is a debilitating complication of SCD with multifactorial pathobiology. Here we show that neuroinflammation and dysregulation in lipidomics and transcriptomics profiles are major underlying mechanisms of social stress-induced cognitive deficit in SCD. Townes sickle cell (SS) mice and controls (AA) were exposed to social stress using the repeat social defeat (RSD) paradigm concurrently with or without treatment with minocycline. Mice were tested for cognitive deficit using novel object recognition (NOR) and fear conditioning (FC) tests. SS mice exposed to RSD without treatment had worse performance on cognitive tests compared to SS mice exposed to RSD with treatment or to AA controls, irrespective of their RSD or treatment disposition. Additionally, compared to SS mice exposed to RSD with treatment, SS mice exposed to RSD without treatment had significantly more cellular evidence of neuroinflammation coupled with a significant shift in the differentiation of neural progenitor cells towards astrogliogenesis. Additionally, brain tissue from SS mice exposed to RSD was significantly enriched for genes associated with blood-brain barrier dysfunction, neuron excitotoxicity, inflammation, and significant dysregulation in sphingolipids important to neuronal cell processes. We demonstrate in this study that neuroinflammation and lipid dysregulation are potential underlying mechanisms of social stress-related cognitive deficit in SS mice. Key PointsO_LINeuroinflammation and lipid dysfunction are potential underlying mechanisms of social stress-related cognitive deficit in SCD patients. C_LIO_LIMitigating or ameliorating the impact of cognitive deficits in SCD needs to consider the biological changes already created by exposure to social stress. C_LI Novelty of our FindingsWe show for the first time, that neuroinflammation along with changes in the brain lipidome and transcriptome, are underlying biological mechanism contributing to the development and potentially progression of cognitive impairment among sickle cell patients. These findings also provide for the first time, a mechanistic basis for an earlier reported observation of a higher likelihood of having lower intelligence quotient scores among children with sickle cell disease exposed to social stress in the form of low parental socioeconomic status.

neuroscience↗

ERK Activation by BRAFV600E suppresses mesenchymal migration and tumorigenesis by inhibiting RAC1.

BRAFV600E mutation occurs in 46% of melanomas and drives high levels of ERK activity and ERK-dependent proliferation. However, BRAFV600E is insufficient to drive melanoma in GEMM models, and 82% of human benign nevi harbor BRAFV600E mutations. We show here that BRAFV600E inhibits mesenchymal migration by causing feedback inhibition of RAC1 activity. ERK pathway inhibition induces RAC1 activation and restores migration and invasion. In cells with BRAFV600E, mutant RAC1, overexpression of PREX1, PREX2, or PTEN inactivation restore RAC1 activity and cell motility. Together, these lesions occur in 48% of BRAFV600E melanomas. Thus, although BRAFV600E activation of ERK deregulates cell proliferation, it prevents full malignant transformation by causing feedback inhibition of cell migration. Secondary mutations are, therefore, required for tumorigenesis. One mechanism underlying tumor evolution may be the selection of lesions that rescue the deleterious effects of oncogenic drivers. Statement of significanceBRAFV600E activation of ERK causes feedback inhibition of cell migration and invasion and thus blocks tumorigenesis. Secondary genetic lesions are required to rescue these processes and enable tumor development. Thus, oncogenic feedback can shape the details of tumor progression and, in doing so, selects for new mutations that may be therapeutic targets.

cancer biology↗