Biology subjects

Pandey, G.

Publications and source records attributed to Pandey, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Modulation of the sensitivity to ruxolitinib-mediated JAK2 inhibition by mutationally activated SHP2 exhibits cell context dependency in pre-clinical models of myeloproliferative neoplasms

Classic Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) are hematopoietic stem cell cancers that result in aberrant trilineage myeloid cell proliferation, bone marrow fibrosis, and increased risk of acute myeloid leukemia. MPNs are driven by deregulated activity of the JAK2 kinase, induced by mutations in the JAK2, CALR, and MPL genes, but approved JAK2 inhibitors primarily offer palliative effects, not remission. Cell models that demonstrate MPN oncogene driven JAK2 activity requisite for cell proliferation are important research tools for the development of anti-JAK2 and anti-JAK2 signaling therapeutics for MPN. SET2 and UKE1 cells are two such cell lines, as they express JAK2-V617F, one of the major driving mutations of MPN, and require signaling by JAK2 for their growth and viability. These cell lines are AML cell lines that were derived from patients with a previous diagnosis of MPN before they developed AML. Our previous studies demonstrated that the SHP2 phosphatase may be a therapeutic target for MPNs, and here we report our identification and characterization of an activating point mutation of SHP2 (encoded by the PTPN11 gene), SHP2-F71L, in UKE1 cells. Given SHP2 functions downstream of JAK2 and mediates JAK2 activation of RAS, we set out to determine the effect of mutational activation of SHP2 on the sensitivity of MPN model cells to JAK2 inhibition. We used CRISPR-Cas9 to edit this mutation in UKE1 cells back to wildtype such that these cells only express wildtype SHP2. These cells exhibited enhanced sensitivity to SHP2 inhibition and, notably, enhanced sensitivity to the JAK2 inhibitor ruxolitinib. This altered sensitivity was reverted by exogenous expression of SHP2-F71L but not SHP2-WT, indicating expression of an activated SHP2 may alter sensitivity to JAK2 inhibition in MPN model cells. We further explored this by genetically editing SET2 cells to express SHP2-F71L but observed no change in SHP2 inhibitor or JAK2 inhibitor sensitivity in cells with a SHP2-F71L encoding allele of PTPN11. Using the cytokine dependent BaF3 cell line where deregulation of JAK2 signaling by expression of JAK2-V617F induces cytokine independent transformation that remains dependent on this JAK2 signaling, we observed no effect of the expression of an activated SHP2 mutant on the sensitivity of the growth and viability of these cells to ruxolitinib. Recent studies have demonstrated activation of RAS signaling can antagonize JAK2 inhibition in pre-clinical MPN models, and the presence of RAS pathway mutations associates with patients whose disease advances on ruxolitinib therapy. Such mutations include activating mutations in PTPN11, as SHP2 is an upstream activator of RAS signaling. Our results suggest that activating PTPN11 mutations have the potential to desensitize the effects of JAK2 inhibition therapy in patients undergoing therapy and may be dependent on unknown cell and molecular profile contexts.

cancer biology↗

bioRxiv2026

Extracting anomalous diffusion parameters from multi-state ensembles of short single molecule trajectories.

Single-molecule tracking measures the stochastic motion of individual biomolecules in the cellular environment. Statistical analysis of trajectory ensembles is required to gain insight into the biophysical nature of mobility states and molecular interactions that they reflect. Mobility states can be parameterized by a generalized diffusion coefficient and anomalous exponent. Experimental constraints such as finite track length and localization precision limit how accurately these parameters can be determined. We compare the performance of analysis methods to recover the input parameters from ensembles of simulated single molecule tracks from different states spanning the range of anomalous diffusive behaviors observed in the cell nucleus. We further develop a framework to quantify error rates in the assignment of mobility states to individual molecules based on recall rates and precision. Our analysis shows that single-track analysis methods are superior to bulk methods in their ability to recover parametric descriptors from mixed populations. The most complete description is obtained by combining outputs from different tools. Our work provides a guide to assess the accuracy of analyses and obtain the most accurate parametric description of experimental single particle tracking data. Statement of significanceExperimental single particle tracking data provides rich insight into molecular interactions directly in living cells. But data analysis depends critically on choosing the correct diffusion model and appropriate tools to extract accurate information. Importantly, it is usually not obvious from the output of a method whether the results are accurate or not. In this work, we use ensembles of tracks simulated with fractional Brownian motion methods to characterize the impact of track length and localization precision on analysis outcomes. We elaborate on specific strengths and weaknesses of commonly used and newly developed analysis tools to provide a template for thorough assessment and quantification of error rates in experimental data analysis.

biophysics↗

bioRxiv2026

IDRs lead the way: Cooperativity between intrinsically disordered regions and structured interaction domains drives enrichment in transcription condensates

Many biomolecular condensates are thought to form through phase separation driven by weak and multivalent, non-stoichiometric interactions between intrinsically disordered protein regions (IDRs). IDRs are abundant in the transcription-related proteome. In vitro, different transcription-related IDRs coalesce into the same droplets, providing support for this IDR-centric paradigm of protein enrichment in transcription condensates in the cell nucleus. But our experiments show that IDRs are not sufficient to account for the degree of enrichment observed for full-length proteins in endogenous transcription condensates. Instead, we find a pattern in which IDRs facilitate engagement of structured interaction domains with a binding substrate. Instead, we find a pattern in which IDRs facilitate engagement of structured interaction domains with a binding substrate. Our results indicate that the role of IDRs in transcription condensates requires further investigation with tools that assess their mode of action in situ. Understanding the role of different protein domains and their interplay will also be important for interpreting biotechnological assays that utilize parts of condensate forming proteins.

cell biology↗

bioRxiv2026

Transcription condensates are promoter hubs that enhance transcriptional bursts

Transcription of eukaryotic genes by RNA Polymerase II occurs in temporal bursts and spatial clusters. It is regulated by dozens of transcription factor and coactivator proteins and guided by epigenetic histone marks. Colocalization of transcription machinery in dense foci suggests that cooperative effects orchestrate the process. Factory or condensate models provide a framework for the spatial assembly of the transcription machinery at highly active chromatin loci. But conventional methods lack the resolution to determine how chromatin regulatory elements interact with spatial clusters of the transcription machinery, and whether chromatin structural features modulate functional output. Here, we use super-resolution microscopy to elucidate nanoscale organization of regulatory chromatin at Pol II clusters across scales. We find that Pol II clusters exist on a continuous spectrum of sizes and represent promoter chromatin hubs. We uncover a layered organization of regulatory chromatin, where Pol II clusters form at H3K27ac and H3K4me3-rich domains while H3K4me1 positions peripherally at the surface of large Pol II clusters. Perturbation experiments are consistent with a model in which cohesin loop extrusion forms the active chromatin scaffold underlying transcription assemblies while condensate-driven interactions play only a minor role in genome organization at these sites. Importantly, the number and size of transcriptional burst size increases with Pol II cluster size, revealing directly the cooperative benefits of transcription organization in promoter hubs and a functional consequence of local chromatin structure.

cell biology↗

bioRxiv2026

Strong reproductive isolation among sympatric lineages of an international mosquito pest

Background: Reproductive isolation describes the degree to which genetic differences among populations reduce the level of neutral gene flow between them. Genomic approaches are currently showing great utility for identifying reproductive isolation between sympatric, morphologically indistinct populations, where hybridisation and introgression may yet be common. Here we use population genomic approaches and a chromosome-level reference assembly to uncover three highly differentiated, cryptic lineages of Aedes notoscriptus, an Australian mosquito disease vector that has invaded New Zealand (c. 1920) and California (c. 2014). Results: We identified a single lineage (Noto1) that was the source of the New Zealand and Californian invasions, and this lineage was also distributed across much of Australia including the Greater Melbourne region where it was sympatric with a second lineage (Noto2). Although Victorian Noto1 and Noto2 were frequently sampled co-locally, hybrids were observed less frequently than expected under random mating, and admixture levels were low, suggestive of selection against hybrids. A bottleneck observed in Victorian Noto1 suggests that Noto1 may have recently expanded its range into the Greater Melbourne region. We also identified a massive structural variant (~25 Mbp; ~10% of chromosome size) in Noto2 that was segregating at intermediate frequencies across the Greater Melbourne region but was fixed in Noto1. Conclusion: Together, these results identify key genetic differences between cryptic lineages of this international disease vector that warrant further investigation given potential differences in vector competence.

evolutionary biology↗

bioRxiv2026

Leveraging Pretrained Vision Transformers for classifying Alcohol Use Disorder using Raw Resting-State EEG

Alcohol Use Disorder (AUD) is a prevalent and debilitating neuropsychiatric condition characterized by compulsive alcohol consumption, impaired control, and negative emotional states, affecting about 28 million adults in the United States. Despite its significant public health burden, there are few objective biomarkers and no reliable neurophysiological tools to assist in its clinical diagnosis. In this study, we investigated the potential of deep learning to classify individuals with AUD using raw resting-state electroencephalogram (EEG) data. EEG recordings were obtained from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, longitudinal, multi-site dataset. The initial cohort included a total of 5,402 recordings from 2,710 participants (aged 12-83, mean age 24; 1,338 males and 1,372 females). To reduce confounding factors, we applied demographic matching, and to address class imbalance, we applied undersampling. Minimal preprocessing was applied to preserve the raw EEG features. We utilized EEGViT, a hybrid deep learning architecture that combines convolutional patch embedding with a Vision Transformer (ViT) pretrained on ImageNet, thereby enabling end-to-end learning directly from raw EEG input. The analysis was stratified by sex and age, and all groups were age-matched. To validate the generalization of the model, models were also trained for Cannabis Use Disorder (CUD) and Opioid Use Disorder (OUD). Results for the AUD model showed a classification accuracy of approximately 56% in the overall dataset, 54% for males, and 58% for females. The CUD model showed an accuracy of about 63% with 59% for females and 69% for males. The OUD model showed an accuracy of about 63% with 61% for females and 65% for males. Temporal analysis indicated that the models performance varied across time intervals, with higher accuracy observed in later minutes compared to earlier ones. While modest, these findings underscore the potential of transformer-based models in psychiatric classification using raw EEG data and provide a foundation for future development of EEG-based diagnostic tools for AUD.

neuroscience↗

bioRxiv2025

Neuroanatomical features reveal accelerated brain age in alcohol use disorder

Background/ObjectivesBrain age is a novel measure to characterize the integrity of neurocognitive functioning and brain health in various psychiatric and neurological disorders. Although there is a literature suggesting premature aging of the brain in individuals with alcohol use disorder (AUD), studies directly examining brain age are rare. Therefore, the current study was designed to estimate brain age in AUD individuals using brain morphological features, such as cortical thickness and brain volume. MethodsThe sample included a group of 30 adult males with a history of AUD but maintaining abstinence and a group of 30 male controls without any history of AUD. Brain age was computed using an XGBoost regression model with 187 brain morphological features of cortical thickness and brain volume as predictors. An exploratory correlational analysis between brain age measures and features of neuropsychological performance, impulsivity, and alcohol consumption was also performed. ResultsFindings revealed that AUD individuals showed an increase of 1.70 years in their brain age relative to their chronological age. Further, in the AUD group, higher brain age was significantly associated with poor executive functioning, while a larger gap between brain age and actual age was associated with lower non-planning impulsivity and later age of onset for regular drinking in those with AUD. ConclusionsAUD individuals manifested accelerated brain aging, possibly representing compromised brain health. Brain age measures were found to be associated with some of the measures of neurocognition, impulsivity, and alcohol consumption. These findings may have important implications for the early identification, prevention, and treatment of AUD. However, future studies with larger sample sizes are needed to confirm these preliminary findings.

neuroscience↗

bioRxiv2025

Interleukin-3 as a Potential Bone Anabolic Agent in treating Postmenopausal Osteoporosis

Postmenopausal osteoporosis (PMO), a silent disorder caused due to estrogen deficiency, is characterized by loss of bone mass and low bone mineral density. Despite advancements in treatment, current medications often fail to fully restore bone integrity and prevent fragility fractures in the osteoporotic individuals. Thus, there is a high demand of novel therapeutic modalities in dealing with osteoporosis. Interleukin-3 (IL-3), a cytokine secreted by activated T cells, emerges as a promising therapeutic candidate. The dual role of IL-3 in inhibiting osteoclast differentiation and promoting osteoblast differentiation, offers protection against bone and joint degeneration in arthritic mice. However, its role in osteoporosis is not yet delineated. Therefore, our investigation focuses on elucidating the role of IL-3 in PMO, employing both prophylactic and therapeutic strategies in ovariectomized mice, mimicking human PMO. In our study, at the onset of osteoporosis, IL-3 treatment effectively preserved trabecular bone architecture and enhanced bone mineral density in OVX mice, particularly notable in therapeutic interventions where fully developed osteoporosis was addressed. Notably, in preventive measures, IL-3 inhibited osteoclast differentiation, thereby suppressing bone resorption, while in therapeutic approaches, it enhanced osteoblast differentiation, promoting bone formation. Irrespective of gender specific, microCT analysis of IL-3-/- (KO) mice showed reduced trabecular bone development compared to its respective wild type (WT) mice, highlighting essential role of IL-3 in skeletal integrity. Moreover, IL-3 increased Treg cells population while inhibiting B cell lymphopoiesis in ovariectomized mice with no adverse effects on hematopoiesis or vital organs. In conclusion, our findings collectively underscore the potential of IL-3 as a novel therapy for PMO, offering insights into its mechanisms of action and clinical applications. One Sentence SummaryIL-3 has a dual action on bone: anti-osteoclastic and pro-osteoblastic in OVX mice, thus can be a novel therapeutic drug in treating postmenopausal osteoporosis.

pathology↗

bioRxiv2025

Genetically encoded nAChR upregulation is neuroprotective in female parkinsonian mice

Parkinsons disease is projected to rise to pandemic proportions by 2050, which has resulted in an urgent need for disease-modifying treatments. In this regard, we previously showed that in a mouse model of parkinsonism with unilateral 6-hydroxydopamine (6-OHDA) injection into the dorsolateral striatum (DLS), low doses of the neuronal nicotinic acetylcholine receptor (nAChR) partial agonist and smoking cessation drug, cytisine exerts sex-specific neuroprotection in substantia nigra pars compacta (SNc) dopaminergic (DA) neurons of only female mice by reducing apoptotic endoplasmic reticulum (ER) stress. Although these data suggest that neuroprotection might occur via cytisine-mediated upregulation of {beta}2 subunit-containing ({beta}2*) nAChRs in SNc DA neurons, there is no direct evidence to support this idea. Therefore, this study asks the critical question of whether upregulation of {beta}2* nAChRs in SNc DA neurons alone is sufficient to reduce apoptotic ER stress and exert neuroprotection in a preclinical unilateral DLS mouse model of 6-OHDA-induced parkinsonism. To address this question, we generate and characterize a novel {beta}2-upregulated transgenic mouse line. These transgenic mice possess mutations in the M3-M4 intracytoplasmic loop of {beta}2 subunits that cause constitutive upregulation of {beta}2* nAChRs without nicotinic ligands. Surprisingly, when compared to wild-type littermates, only female {beta}2-upregulated transgenic mice demonstrate upregulation of {beta}2* nAChRs in SNc DA neurons as assessed by significant increases in Sec24D-containing ER exit sites (Sec24D-ERES). Using the optogenetic calcium and dopamine sensors, GCaMP6f and GRABDA respectively, we found significant increases in dihydro-beta-erythroidine (Dh{beta}E)-sensitive {beta}2* nAChR-mediated calcium influx in SNc DA neuron dendrites and Dh{beta}E-sensitive acetylcholine (ACh)-evoked dopamine release at SNc DA neuron terminals of the DLS in female transgenic mice. We then used four independent readouts to assess neuroprotection of SNc DA neurons following unilateral 6-OHDA injection into the DLS, viz., contralateral apomorphine-induced rotations, preservation of SNc DA neurons, inhibition of a major proapoptotic ER stress protein, C/EBP homologous protein (CHOP) and glial fibrillary acid protein (GFAP) expression in SNc astrocytes. In all four readouts, female {beta}2-upregulated transgenic mice showed significant neuroprotection. From a clinical perspective, this study shows that upregulation without nicotinic ligand-mediated activation of {beta}2* nAChRs in SNc DA neurons can be a translationally viable disease-modifying strategy for Parkinsons disease. In addition, we envision that the novel transgenic {beta}2-upregulated mice created in this study will provide a valuable tool for understanding the role of nAChR upregulation in major neurological disorders such as addiction, anxiety, depression and dementia.

neuroscience↗

bioRxiv2025

Alcohol use disorder is associated with increases in frontocentral phase-amplitude coupling strength during resting state

Considerable evidence from functional neuroimaging and EEG coherence studies indicates that individuals afflicted with alcohol use disorder (AUD) manifest aberrant patterns of connectivity, particularly in frontal brain regions. Phase-amplitude coupling (PAC) is another form of functional connectivity, reflecting the association between the phase at one frequency and amplitude changes at a higher frequency. Significant PAC differences have been reported for other substance use disorders, but it has not yet been investigated in AUD. We compared frontomedial PAC strength during resting state, eyes closed, in adult participants with severe AUD and age-matched unaffected controls from the Collaborative Study on the Genetics of Alcoholism (COGA). Comodulograms of PAC estimates between phase frequencies (0.1-13 Hz) and amplitude frequencies (4-50 Hz) were calculated for all participants. PAC differences between AUD and unaffected groups were assessed at each phase-amplitude frequency pair in comodulograms to identify clusters of significant test results, reporting only those clusters satisfying all validation and significance testing steps. Severe AUD was associated with clusters of significantly greater PAC in alpha-gamma domains of both men and women. Candidate clusters were found in theta-gamma domains of both sexes, but were only significant greater in men with AUD. Significant PAC clusters were found in the delta-gamma domain of both sexes, though women with AUD showed significant decreases in contrast to greater PAC found in men with AUD. The significant PAC clusters identified in this exploratory study could provide new insights into the dysregulation of brain connectivity underlying AUD.

neuroscience↗

bioRxiv2025

Alzheimer's subtypesA supervised, unsupervised, multimodal, multilayered embedded recursive (SUMMER) AI study

Since Alzheimers disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, requiring tailored interventions. While several proposed subtypes of AD exist, there is still no clear consensus on a definitive classification. By leveraging complementary AI approaches, including supervised and unsupervised learning, within a recursive pipeline (SUMMER) that integrates multimodal datasets encompassing MRI measurements, phenotypes, and genetic data, our goal was to generate robust scientific evidence for identifying AD subtypes. Data was downloaded from the Alzheimers Disease Neuroimaging Initiative (ADNI) database and included neuroimaging data (MRI), genetics (SNPs), clinical diagnosis, and demographics. 1133 European American participants images, aged 55-95, were included in this study. The analysis was multi-fold, where the first step involved applying an unsupervised application to a subset of the MRI sample (AD + cognitively normal (CN) aged matched groups, 100 men aged 68-85 years, and 76 women aged 68-85 years). The MRI brain gray matter was segmented into 44 regions of interest (ROIs) according to a standard atlas, and 618 features were extracted, including ROI voxel intensity measurements such as minimum, maximum, and histogram variables. Results identified a cluster of subtype AD men and a cluster of subtype AD women that were distinct from the rest of their respective samples. In the next step, the integrity of the identified subtype AD clusters was investigated using the XGBoost supervised machine learning application with genetic features (SNPs, N=36,724) and labels: the identified subtype AD cluster vs. the rest of the sample, stratified by sex. A significant AD subtype men model (accuracy=0.85, F1=0.72, AUC=0.83) and a significant women AD subtype model (accuracy=0.81, F1=0.81, AUC=0.81) were built, confirming the homogeneity of the isolated AD subtype clusters. Discriminative biomarkers were extracted from the significant models, including selected ROIs and SNPs. Finally, the subtype models were tested on an unseen subset of ADNI data. The genetic-based models identified clusters of AD subtype participants consisting of 34% of the men AD group and 47% of the women AD group. Phenotypic analysis indicates that lower body weight was associated with the womens AD subtype. Complex diseases like AD demand a sophisticated, multimodal approach for precise diagnosis. Effectively identifying disease subtypes enhances the potential for personalized treatment, ultimately improving patient outcomes.

neuroscience↗

bioRxiv2025

Preconditioning Matters: Enhancing or Impairing Antitumor Immunity with DC Vaccines

Preconditioning regimens are essential for the success of adoptive cell therapies like CAR T-cells due to effects on the T-cell response, yet they are underexplored and generally absent from cancer vaccine clinical trials. To address this gap, we evaluated the impact of various preconditioning strategies on dendritic cell (DC) vaccine efficacy in a murine tumor model. Mice bearing syngeneic KP tumors expressing ovalbumin received preconditioning with low-dose radiation (LD RT; whole body or tumor only), cyclophosphamide, paclitaxel, LD RT plus cyclophosphamide, or no preconditioning, followed by administration of antigen-loaded DC1s. Tumor growth, survival, and antigen-specific CD8+ T-cell responses were assessed. LD RT preconditioning, whether whole body or tumor-directed, significantly enhanced vaccine-induced antitumor CD8+ T-cell responses and improved survival compared to DC vaccine alone and all other groups. Cyclophosphamide preconditioning reduced vaccine efficacy and negated the benefits of LD RT, while paclitaxel had no significant effect. Notably, whole-body LD RT induced the strongest antigen-specific T-cell response. These findings demonstrate that, similar to CAR T-cell therapy, preconditioning regimens can significantly influence cancer vaccine outcomes. Rational selection of preconditioning agents may either maximize or minimize the therapeutic potential of DC cancer vaccines, and should be considered carefully in clinical trials.

immunology↗

bioRxiv2025

Reward Network Activations of Win versus Loss in a Monetary Gambling Task

Reward processing is a vital function for health and survival and is impaired in various psychiatric and neurological disorders. Using a monetary gambling task, the current study aims to elucidate neural substrates in the reward network underlying evaluation of win versus loss outcomes, and their association with behavioral characteristics, such as impulsivity and task performance, and neuropsychological functioning. Functional MRI was recorded in thirty healthy, male community volunteers (mean age = 27.4 years) while they performed a monetary gambling task in which they bet with either 10 or 50 tokens and received feedback of whether they won or lost the bet amount. Results showed that a set of key brain structures in the reward network, including putamen, caudate nucleus, superior and inferior parietal lobule, angular gyrus, and Rolandic operculum, had greater blood oxygenation level dependent (BOLD) signal during win relative to loss trials, and the BOLD signals in most of these regions were highly correlated with one another. Further, exploratory bivariate analyses between these reward related regions and behavioral and neuropsychological domains showed significant correlations with moderate effect sizes, including: (i) negative correlations between non-planning impulsivity and activations in putamen and caudate regions, (ii) positive correlations between risky bets and right putamen activation, (iii) negative correlations between safer bets and right putamen activation, (iv) a negative correlation between short-term memory capacity and right putamen activity, and (v) a negative correlation between poor planning skills and left inferior occipital cortex activation. These findings contribute to our understanding of the neural underpinnings of monetary reward processing and their relationships to aspects of behavior and cognitive function. Future studies may confirm these findings with larger samples of healthy controls and extend these findings by investigating various clinical groups with impaired reward processing.

neuroscience↗

bioRxiv2025

Populations of the Australian saltmarsh mosquito Aedes vigilax vary between panmixia and temporally stable local genetic structure

Pest management programs can operate more effectively when movement patterns of target species are known. As individual insects are difficult to track, genomic data can instead be used to infer movement patterns based on pest population structure and connectivity. These data can also provide critical information about cryptic taxa relevant to management. Here we present the first genomic investigation of Aedes vigilax, the Australian saltmarsh mosquito, a major arbovirus vector across Australasia. We used a ddRAD pool-seq approach and a draft genome assembly to investigate genetic variation in 60 Ae. vigilax pools from across Australia but with a focus on urban Newcastle and Sydney, NSW. There was strong genetic structure between samples from the west and east coasts of Australia, and additional structure that differentiated east coast populations. Within Newcastle and Sydney, contrasting patterns of genetic structure were evident. In Newcastle, there was no differentiation among subregions up to 60 km apart. In Sydney, samples from one urban subregion were differentiated from others < 3 km apart, and this structure was stable across sampling years. Heterozygosity and Tajimas D indicated no bottlenecks in Newcastle or Sydney populations, suggesting this structure represents a gene flow barrier. Nuclear differentiation patterns contrast with previous mtDNA data indicating two COI clades in the east coast, one of which was also present in Western Australia. The panmixia over 60 km across the Newcastle region corroborates previous field observations of high dispersal capacity in this mosquito. These findings indicate specific challenges that may hinder local suppression strategies for this species.

evolutionary biology↗

bioRxiv2024

Chromosome structural rearrangements in invasive haplodiploid ambrosia beetles revealed by the genomes of Euwallacea fornicatus and Euwallacea similis (Coleoptera, Curculionidae, Scolytinae)

Bark and ambrosia beetles are among the most ecologically and economically damaging introduced plant pests worldwide, with life history traits including polyphagy, haplodiploidy, inbreeding polygyny and symbiosis with fungi contributing to their dispersal and impact. Species vary in host tree ecologies, with many attacking stressed or recently dead trees, such as the globally distributed E. similis (Ferrari). Other species, like the Polyphagous Shot Hole Borer (PSHB) Euwallacea fornicatus (Eichhoff), can attack over 680 host plants and is causing considerable economic damage in several countries worldwide. Despite their notoriety, publicly accessible genomic resources for Euwallacea Hopkins species are scarce, hampering better understanding of their invasive capabilities as well as modern control measures, surveillance and management. Using a combination of long and short read sequencing platforms we assembled and annotated high quality (BUSCO > 98% complete) chromosome level genomes for these species. Comparative macro-synteny analysis showed an increased number of chromosomes in the haplodiploid inbreeding species of Euwallacea compared to diploid outbred species, due to fission events. This suggests that life history traits can impact chromosome structure. Further, the genome of E. fornicatus had a higher relative proportion of repetitive elements, up to 17% more, than E. similis. Additionally, metagenomic assembly pipelines identified microbiota associated with both species including Fusarium fungal symbionts and a novel Wolbachia strain. These novel genomes of haplodiploid inbreeding species will contribute to the understanding of how life history traits are related to their evolution and will contribute to the management of these invasive pests. SignificanceScolytinae are significant forestry pests around the world and commonly translocated due to human trade of wood and plant products. Life history traits including inbreeding and haplodiploidy are attributed to their successful establishment in novel environments. Euwallacea fornicatus is widely distributed and attacks a wide variety of live host trees. This study reports the genome of this species and for, E. similis, which colonises dead host trees. The genome assemblies presented herein are highly complete and scaffolded to pseudo-chromosomal level. Comparative analyses of these genomes and of other Scolytinae highlight significant chromosomal rearrangements between haplodiploid inbreeding Euwallacea and diploid outbreeding scolytinae species. Higher relative proportions of transposable elements were identified E. fornicatus, which may promote the species ability to attack live host trees. These genomes are the first for haplodiploid beetles and will contribute to the understanding of evolution of life history traits and the management of invasive insects.

genomics↗

bioRxiv2024

The smoking cessation drug cytisine requires systemically circulating estrogen for sex-specific neuroprotection in female parkinsonian mice

The smoking cessation drug cytisine exerts neuroprotection in substantia nigra pars compacta (SNc) dopaminergic (DA) neurons of female but not male 6-hydroxydopamine (6-OHDA) lesioned parkinsonian mice. To address the important question of whether circulating estrogen mediates this effect, we employ two mouse models aimed at depleting systemically circulating estrogen: (i) bilateral ovariectomy (OVX), and (ii) aromatase inhibition with systemically administered letrozole. In both models, depleting systemically circulating estrogen in female 6-OHDA lesioned parkinsonian mice results in the loss of cytisine-mediated neuroprotection as measured using apomorphine-induced contralateral rotations and SNc DA neurodegeneration. Our experiments also reveal that OVX alone exerts neuroprotection in SNc DA neurons due to compensatory changes not observed in the letrozole model, which underscores the importance of using independent models of estrogen depletion to study neuroprotection. Taken together, our findings suggest that the smoking cessation drug cytisine is a viable neuroprotective drug for pre-menopausal women with Parkinsons disease.

neuroscience↗

bioRxiv2024

Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features

Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.

neuroscience↗

bioRxiv2024

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most effective predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, an effective data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK models performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

cell biology↗