Biology subjects

Das, P.

Publications and source records attributed to Das, P..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

4-Phenylbutyric acid modulates Connexin 43 expression restricting murine-β-coronavirus infectivity and virus-induced demyelination

Gap junction intercellular communication, particularly involving Connexin 43 and Connexin 47, plays a critical role in maintaining CNS homeostasis and has been implicated in Multiple Sclerosis (MS) pathology. Thus, warranting further studies in experimental animal models to understand how modulation of Cx43 expression can influence MS pathology. Intracranial infection with murine-{beta}-coronavirus Mouse Hepatitis Virus (MHV-A59) in mice results in acute pathology characterized by high viral titers, glial activation in the brain and chronic neuroinflammatory demyelination, effectively mimicking key pathological hallmarks of MS and serving as a robust model to investigate its viral etiology. MHV-A59 infection leads to a pronounced downregulation of Cx43 during the acute phase, emphasizing its critical role in virus-induced CNS pathology. In this study, we investigated the potential of in vivo 4-phenylbutyric acid (4-PBA) administration in modulating Cx43 expression in this MHV-induced model and its consequence on chronic virus-induced demyelination. Our results reveal that 4-PBA treatment reduced acute MHV-A59 infectivity and viral spread in the brain while modulating the glial cell response, mounting host immunity. Treatment with 4-PBA effectively preserved the expression of both Cx43 and Cx47 in infected CNS cells, counteracting their infection-induced downregulation. Furthermore, MHV-A59 infection downregulated the expression of ER-resident thioredoxin family protein (ERp29), a well-known molecular chaperone of Cx43, which was rescued by 4-PBA treatment. We further validated if such downregulation of ERp29 is also evident in MS demyelinating plaques. In human MS patient-derived brain tissue, reduced Cx43 and ERp29 staining was observed in demyelinating plaques. Our studies revealed that 4-PBA treatment not only limits viral replication and spread throughout the brain but also protects the mice against severe chronic neuroinflammatory demyelination. These findings suggest that targeting Cx43 with 4-PBA holds significant therapeutic potential for addressing virus-induced neuroinflammatory demyelination and MS by preserving gap junction intercellular communication.

neuroscience↗

bioRxiv2024

Functional insights on chemical communication of fishing cats: a strategic mechanism for adaptation in semi-aquatic habitat

Chemical communication system of fishing cats, focusing on volatile organic compounds present in their urine (UR) and marking fluid (MF) has been explored. Using solid-phase microextraction guided gas chromatography mass spectrometry analysis, a diverse range of functional groups from UR and MF were detected, including ketones, aldehydes, sulfur- and nitrogen-containing compounds, among which 3-Mercapto-3-methylbutanol (3MMB) and its related sulfur compounds were found to be sex-specific, predominantly present in males. The unique behavior of fishing cats to urinate frequently in water when experimentally tested with synthetic 3MMB, was aligned for its retention in aqueous medium upto 21 days. This suggests that fishing cats may employ an energy-efficient scent-marking strategy by leveraging aquatic environments for prolonging chemical signalling process. The analysis of less-volatile compounds, such as triglycerides and fatty acids, suggests that these compounds could be acted as fixatives, helping to stabilize and prolong the intensity of chemical messages coded to highly volatile molecules. The combination of highly volatile, less volatile compounds and lipids may create complex synergy to facilitate interindividual communication, potentially serving as pheromones. This research enhances our understanding of the fishing cats adaptation to semi-aquatic environments and its unique behavioural pattern in marshy landforms, thus concentrated with high population density in deltaic South Bengal.

zoology↗

bioRxiv2024

CPSM: R-package of an Automated Machine Learning Pipeline for Predicting the Survival Probability of Single Cancer Patient

Accurate survival prediction is vital for optimizing treatment strategies in clinical practice. The advent of high-throughput multi-omics data and computational methods has enabled machine learning (ML) models for survival analysis. However, handling high-dimensional omics data remains challenging. This study introduces the Cancer Patient Survival Model (CPSM), an R package developed to provide individualized survival predictions through a fully integrated and reproducible computational pipeline. The CPSM package encompasses nine modules that streamline the survival modeling workflow, organized into four key stages: (1) Data Preprocessing and Normalization, (2) Feature Selection, (3) Survival Prediction Model Development, and (4) Visualization. The visual tools facilitate the interpretation of survival predictions, enhancing clinical decision-making. By providing an end-to-end solution for multi-omics data integration and analysis, CPSM not only enhances the precision of survival predictions but also aids in discovering clinically relevant biomarkers. Availability and ImplementationThe CPSM Package is freely available at the GitHub URL: https://github.com/hks5august/CPSM

bioinformatics↗

bioRxiv2024

miRNA Biomarkers in Prostate Cancer: Leveraging Machine Learning for Improved Diagnostic Accuracy

Prostate cancer (PCa) diagnosis often relies on prostate-specific antigen (PSA) testing, but its high false-positive rates often lead to unnecessary biopsies. MicroRNAs (miRNAs) have emerged as promising non-invasive biomarkers for cancer detection due to their stability in biological fluid and disease specificity. Despite their potential, the clinical translation of miRNAs as non-invasive cancer biomarkers is hindered by several challenges - population-based variability, environmental Factors, methodological Inconsistencies, lack of standardization, normalization Issues, and complexity of the biological System. These factors significantly impact the consistency of miRNA expression readouts, particularly in terms of Ct-values, across different studies, which in turn affects the determination of cutoff values that are crucial in a diagnostic setup. This preliminary study offers a pilot demonstration for integrating miRNA biomarker expression with machine learning (ML), which can help identify patterns and improve classification, potentially reducing the reliance on fixed cutoff values in certain contexts and pave the path to wider clinical translation. We analyzed the expression of key miRNAs (miR-21-5p, miR-221-3p, and miR-141-3p) in blood samples from patients with PCa and benign prostatic hyperplasia (BPH). Utilizing a Random Forest classifier, we achieved an accuracy of 77.42%, a precision of 86.21%, a recall of 71.43%, and an AUC-ROC score of 0.78. The application of ML enabled us to leverage complex features, such as combinations and ratios of miRNA expression data, which enhanced the robustness and reliability of the diagnostic model. Additionally, bioinformatics analysis of the preferential features identified by the ML model confirmed the biological relevance of these miRNAs in PCa-related pathways, further supporting their potential as clinical biomarkers. In the future, ML is poised to significantly enhance diagnostic performance compared to traditional linear analyses of a limited set of biomarkers. While our study did not explore multiple populations or the effects of methodological variables, it highlights the potential of ML by demonstrating improved accuracy and eliminating the need for cutoff values. This capability could broaden the applicability of miRNA-based diagnostics, making them more reliable and actionable in clinical settings. However, to fully realize this potential, further validation with larger and more diverse cohorts is essential. Overall, this study lays the groundwork for utilizing ML-enhanced miRNA panels as powerful tools for the early and non-invasive diagnosis of PCa in future clinical practice. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/618146v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@2eddd9org.highwire.dtl.DTLVardef@e6d6c8org.highwire.dtl.DTLVardef@11eea0forg.highwire.dtl.DTLVardef@989c15_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Structural insights and rational design of Pseudomonas putida KT2440 Omega transaminases for enhanced biotransformation of (R)-Phenylacetylcarbinol to (1R, 2S)-Norephedrine

Omega transaminases ({omega}-TAs) can mediate the chiral amination of several unnatural substrates without the requirement of an -COOH group, and are highly relevant in the production of several pharmaceutical intermediates of commercial interest. Development of better variants of {omega}-TAs are hence essential for their industrial uses. We have studied the active site architecture of the wild-type {omega}-TAs, to develop engineered enzymes for enhancing the biotransformation of (R)-Phenylacetylcarbinol to (1R, 2S)-Norephedrine. Two such {omega}-TAs (TA_5182 and TA_2799) from P. putida KT2440 strain were overexpressed and purified as recombinant proteins. Crystal structures of TA_5182 were solved in two conformations, and significant movements of two highly flexible loops were observed in these different states. The TA_2799 structure was determined in the co-factor bound state with a PLP molecule covalently bonded to the catalytic K286 as an internal aldimine. Enzyme assays indicated that TA_2799 required significantly higher concentrations of co-factor than TA_5182 to achieve satisfactory biotransformation of (R)-PAC. A key mutation of L322F in TA_2799 drastically reduced the co-factor dependency of the TA_2799_L322F mutant enzyme, and the mutant remained active for 96h at 30{degrees}C. The crystal structure of the mutant enzyme revealed an asparagine residue that mediates a hydrogen bonding network at the dimeric interface of the enzyme and is absent in TA_5182. The TA_5182_G119N mutant also showed enhanced co-factor affinity. The results of our studies will help generate Pseudomonad {omega}-TAs and {omega}-TAs from other organisms with high efficiency for asymmetric synthesis, to be used in host systems for optimal large-scale industrial biotransformation.

biochemistry↗

bioRxiv2024

A three-country analysis of the gut microbiome indicates taxon associations with diet vary by location and strain

Emerging research suggests that diet plays a vital role in shaping the composition and function of the gut microbiota. While significant efforts have been made to identify general patterns linking diet to the gut microbiome, much of this research lacks representation from low- and middle-income countries such as Mexico. Additionally, both diet and the gut microbiome have highly complex and individualized configurations, and there is growing evidence that tailoring diets to individual gut microbiota profiles may optimize the path toward improving or maintaining health and preventing disease. Using fecal metagenomic data from 1,291 individuals across three countries, we examine two bacterial genera prevalent in the human gut, Prevotella and Faecalibacterium, which have gained significant attention due to their potential roles in human health. We find that they show significant associations with many aspects of diet, but that these associations vary in scale and direction, depending on the level of metagenomic resolution and the contextual population. These results highlight the growing importance of assembling metagenomic datasets that are standardized, comprehensive, and representative of diverse populations to increase our ability to tease apart the complex relationship between diet and the microbiome.

microbiology↗

bioRxiv2024

Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules

Traditional drug design methods are costly and time-consuming due to their reliance on trial-and-error processes. As a result, computational methods, including diffusion models, designed for molecule generation tasks have gained significant traction. Despite their potential, they have faced criticism for producing physically implausible outputs. We alleviate this problem by conditionally training a diffusion model capable of generating molecules of varying and controllable levels of structural plausibility. This is achieved by adding distorted molecules to training datasets, and then annotating each molecule with a label representing the extent of its distortion, and hence its quality. By training the model to distinguish between favourable and unfavourable molecular conformations alongside the standard molecule generation training process, we can selectively sample molecules from the high-quality region of learned space, resulting in improvements in the validity of generated molecules. In addition to the standard two datasets used by molecule generation methods (QM9 and GEOM), we also test our method on a druglike dataset derived from ZINC. We use our conditional method with EDM, the first E(3) equivariant diffusion model for molecule generation, as well as two further models--a more recent diffusion model and a flow matching model--which were built off EDM. We demonstrate improvements in validity as assessed by RD-Kit parsability and the PoseBusters test suite; more broadly, though, our findings highlight the effectiveness of conditioning methods on low-quality data to improve the sampling of high-quality data.

bioinformatics↗

bioRxiv2024

The Hox Gene, abdominal A controls timely mitotic entry of neural stem cell and their growth during CNS development in Drosophila

Cell size is a critical determinant of its function and physiology. In this study, we investigated the regulation of stem cell size during Drosophila central nervous system (CNS) development and its association with cell fate. We note that neural stem cells (NSCs) in different regions of ventral nerve cord increase their size at different rates. The, thoracic NSCs grow at a faster rate compared to those in the abdominal region. We show that in addition to its role in apoptosis and nervous system remodeling, abdA also plays an instructive role in regulating the rate of NSC size increase and its timely entry into mitosis. Weak expression of abdA in larval abdominal NSCs was sufficient to retard the rate of their size increase and delay their mitotic entry compared to thoracic NSCs. Knockdown of abdA in NSCs enhances their rate of size increase leading to early mitotic entry, while ectopic abdA expression in thoracic NSCs reduces their size and delays their mitotic entry. We show that abdA-mediated NSC size regulation acts downstream of nutrition-induced NSC activation, which fine-tunes the stem cell potential spatiotemporally. This study highlights the instructive role of abdA in regulating various fates of larval NSCs during CNS patterning. Significance statementO_LIUnderstanding the upstream regulation of various aspects of the cell cycle is crucial; however, the influence of cell size on this process remains largely unknown. C_LIO_LIWe found an instructive role for the Hox gene abdominal A in maintaining the small size of neural stem cells (NSCs) and in regulating the time and rate of mitosis. C_LIO_LIThis mechanism is crucial because it helps NSCs generate the necessary number of neurons at an appropriate developmental stage, thereby contributing to proper central nervous system patterning. C_LI

developmental biology↗

bioRxiv2024

Rearrangement of 3D genome organization in breast cancer epithelial - mesenchymal transition and metastasis organotropism

Breast cancer cells exhibit organotropism during metastasis, showing preferential homing to certain organs such as bone, lung, liver, and brain. One potential explanation for this organotropic behavior is that cancer cells gain properties that enable thriving in certain microenvironments. Such specific metastatic traits may arise from gene regulation at the primary tumor site. Spatial genome organization plays a crucial role in oncogenic transformation and progression, but the extent to which chromosome architecture contributes to organ-specific metastatic traits is unclear. This work characterizes chromosome architecture changes associated with organotropic metastatic traits. By comparing a collection of genomic data from different subtypes of localized and lung metastatic breast cancer cells with both normal and cancerous lung cells, we find important trends of genomic reorganization. The most striking differences in 3D genome compartments segregate cell types according to their epithelial vs. mesenchymal status. This EMT compartment signature occurs at genomic regions distinct from transcription-defined EMT signatures, suggesting a separate layer of regulation. Specifically querying organotropism, we find 3D genome changes consistent with adaptations needed to survive in a new microenvironment, with lung metastatic breast cells exhibiting compartment switch signatures that shift the genome architecture to a lung cell-like conformation and brain metastatic prostate cancer cells showing compartment shifts toward a brain-like state. TCGA patient data reveals gene expression changes concordant with these organ-permissive compartment changes. These results suggest that genome architecture provides an additional level of cell fate specification informing organotropism and enabling survival at the metastatic site. SIGNIFICANCEComputational analysis of a cohort of cancer cell lines reveals some 3D genome spatial compartment changes are associated with transitions in cancer cell state that relate to metastasis (EMT) and others reflect the characteristics of the metastatic organ context.

cancer biology↗

bioRxiv2024

Construction of ceRNA networks in endocrine therapy resistance model systems

BackgroundEndocrine therapy resistance (ETR) in breast cancer is achieved via multiple pathways including a decrease in ER, dysregulation of cell cycle genes, and/or mutations in ER/co-activators/co-repressors. We have reported earlier that high expression of Jumonji domaining containing protein 6 (JMJD6) induced ETR by depleting ER expression. In this study, 3 cellular models representing distinct ETR pathways; Tamoxifen resistant (TAMR), Long-term Estrogen deprived (LTEDI), JMJD6 overexpressing (JOE) cells, and parental MCF7 were subjected to RNA-sequencing, CNC, and ceRNA network analysis. We hypothesised that post-comparison RNA regulations that are common to all cell lines, will reveal actionable markers and targets. These will be shared by all patients with ET-resistant disease, independent of the initiating event. Results170 differentially expressed genes were found, of these, 73 maintained the same directionality in expression (ETR cassette genes). These genes segregated TCGA ER+ tumors into two groups, one intermixing with ER-tumors. Pathway-based curation of ETR genes identified 21 genes (7 up- and 14 down-regulated) that participated in multiple cancer hallmark pathways. Genes upregulated in ETR cells were less expressed in ER+ tumors at diagnosis when compared to normal breast samples but their higher expression indicated adverse survival outcomes. Next, these genes were used for CNC and ceRNA network construction and a triad FLT4:MIR503HG:miR-497/195/424 was discovered. The expression levels of miRNAs were predicted via network analysis and quantitative RT-PCR was used to validate the down regulation of miR-497/195/424 and upregulation of their targets, FLT4 and MIR503HG in ETR cells. ConclusionsWe show that total RNA-seq data can be successfully used to predict actionable miRNAs that achieve drug resistance. Re-expression of ETR genes such as FLT4 in tumor cells, that are less expressed at diagnosis, may be indicative of ETR onset. Finally, ETR may arise due to suppression of miR-424/497/195 leading to higher expression of FLT4 and MIR503HG. We posit that FLT4 may be a suitable target and RT-PCR analysis of this RNA triad could be developed as a detection strategy for ETR in ER+ breast cancer.

cancer biology↗

bioRxiv2024

Conformational dynamics associated with remote residues regulate the kinetic properties of homologous glutamate dehydrogenases (GDHs)

Glutamate dehydrogenase (GDH) is a key enzyme in all living organisms and some of the GDHs exhibit substrate-dependent homotropic cooperativity. However, the mode of allosteric communication during the homotropic effect in GDHs remains poorly understood. In this study, we examined two homologous GDHs, Aspergillus niger GDH (AnGDH) and Aspergillus terreus GDH (AtGDH), with differing substrate utilization kinetics to uncover the factors driving their distinct behavior. The crystal structures and first-ever cryo-EM structures of apo-AtGDH captured arrays of conformational ensembles. Comparative structural analysis has revealed a wider mouth opening in allosteric AnGDH ([~] 21 [A]) compared to non-allosteric AtGDH ([~]17 [A]) in their apo states. A network of interaction related to the amino acid substitutions in Domain II is responsible for differential structural dynamics in these GDHs. Remarkably, we identified one remotely located substitution in Domain II, i.e., R246 to S, a part of the network, which reversed the kinetic properties of AtGDH into an allosteric one and controls the mouth opening. Our data also indicate that dynamic discrepancy influences the substrate binding affinity and catalytic activity in AnGDH and AtGDH. We have successfully demonstrated for the first time, that remotely located residues and the conformational dynamics regulate the kinetic properties in homologous GDHs.

biochemistry↗

bioRxiv2024

A Mycobacterium tuberculosis secreted virulence factor disrupts host snRNP biogenesis

We earlier reported that Mycobacterium tuberculosis (Mtb) alters host RNA splicing to help its intracellular growth. Here, we report an unprecedented mechanism whereby a secreted virulence factor from Mtb interferes with the biogenesis of key spliceosomal components, causing an altered RNA splicing pattern. A high-throughput yeast-2-hybrid screen identified several Mtb-secreted proteins that can interact with the host RNA splicing factors (SFs). Through custom-designed in-cell assays, we show that one of those proteins, Rv1435c, targets specific exon-skipping events to alter RNA splicing. We show that Rv14345c or host splicing regulator 1 (hsr1) facilitates direct interaction between Mtb phagosomes and U5 snRNA and SNRPF, key components of the snRNPs. Genetic deletion of hsr1 reverses the specific exon-skipping events caused by WT Mtb infection. The{Delta} hsr1 strain shows compromised growth during ex vivo infection in the macrophages and in vivo infection in the mice. Tissue sections from the WT Mtb or{Delta} hsr1-infected mice showed significant hsr1-dependent SNRPF staining, a phenomenon also noted in the human intestinal tuberculosis (ITB) biopsies. We infer that hsr1 is a virulence factor which alters RNA splicing by interacting with U5snRNA and SNRPF. The splicing regulators from the host and pathogen are novel targets for anti-tuberculosis therapy.

molecular biology↗

bioRxiv2023

Node Features of Chromosome Structure Network and Their Connections to Genome Annotation

The 3D conformations of chromosomes can encode biological significance, and its implication is being increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from pairwise contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. Here, we investigate how additional properties of chromosome structure can be deduced using the abstract graph representation of the contact heatmap, and how network properties can have a better connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties of these CSNs. We found these network properties are useful for characterizing chromosome structure features. We examined the ability of network properties in differentiating several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties are more capable of characterizing genome annotations than diffusive or ultra-local node features. For example, local square clustering coefficient can be a strong classifier of lamina-associated domains (LADs), whereas a path-based network property, closeness centrality, does not vary concordantly with LAD status. We demonstrated that network properties can be useful for discerning large-scale chromosome structures that emerge in different biological situations. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/573476v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@45df0forg.highwire.dtl.DTLVardef@13776daorg.highwire.dtl.DTLVardef@5c1519org.highwire.dtl.DTLVardef@16d447f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Guggulsterone Enhances NKX3.1 Expression and Induces Apoptosis in Prostate Cancer Cells: Implications for Chemoprevention

AimProstate cancer is a leading cause of cancer-related mortality, necessitating novel therapeutic and preventive strategies. This study aimed to investigate the anti-cancer properties of Guggulsterone (GS) on prostate cancer cells, specifically focusing on its effects on homeobox protein NKX3.1, apoptosis, and mitochondrial function. MethodThe study utilized the LNCaP prostate cancer cell line and involved cell culture, dose-response analysis, flow cytometry for apoptosis quantification, siRNA-mediated knockdown of NKX3.1, mitochondrial membrane potential assessment using TMRM staining, qRT-PCR analysis, and Western blotting. The stability of NKX3.1 mRNA and protein in response to GS was also evaluated. ResultGS treatment induced apoptosis in LNCaP cells in a dose and time-dependent manner, with an impact on early and late-stage apoptosis. This effect was mediated, at least in part, through the upregulation of NKX3.1. GS enhanced NKX3.1 expression at both the protein and mRNA levels, even in the absence of androgens. Furthermore, GS treatment extended the half-life of NKX3.1 mRNA and protein, suggesting an effect on their stability. ConclusionThis study provides valuable insights into the anti-cancer mechanisms of GS in prostate cancer cells. The upregulation of NKX3.1 by GS and its role in mediating apoptosis offers NKX3.1 as a potential prevention target for PCa. The findings open new research avenues for the development of targeted therapies that stabilize NKX3.1 expression and protect mitochondrial function. Further investigations are needed to understand the intricate molecular mechanisms underlying GSs effects fully, potentially improving prostate cancer management and outcomes.

cancer biology↗

bioRxiv2023

gQuant: A Robust and Generalizable Algorithm for Identifying Normalizer Genes in qRT-PCR Data: A Case Study on Urinary Exosomal miRNAs

The emergent role of nucleic acid-based biomarkers, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs), is becoming increasingly prominent in the realms of disease diagnostics and risk assessment. Quantitative reverse transcription PCR (qRT-PCR) is the primary analytical method for quantitative measurement of biomarkers. Yet, the relative infancy of non-coding RNAs (ncRNAs) recognition as biomarkers poses a challenge due to the absence of a consensus on a universally accepted normalizer gene, which is pivotal for accurate quantification. Current tools for selecting normalizer genes in qRT-PCR are fraught with limitations, including inadequate handling of null values, reliance on elementary statistical tools, use of a biased integrated approach, outlier sensitivity, and suboptimal graphical user interface for data visualization. These deficiencies underscore the necessity for a more nuanced and algorithmically balanced tool tailored to handle qRT-PCR datasets and facilitate the discernment of the most appropriate normalizer gene for specific datasets. Addressing the identified challenges, we have developed gQuant, a tool crafted to address the limitations present in existing methods. In gQuant we employed voting classifiers as an ensemble technique that combines predictions from multiple statistical methods to make more accurate rankings than any individual statistical measures. The tools efficacy was substantiated through rigorous validation against datasets from the Gene Expression Omnibus (GEO) database and corroborated with experimental data derived from urinary exosomal miRNAs. Comparative analysis with existing tools revealed that their integrated methodologies could skew the ranking of normalizer genes, whereas gQuant consistently yielded rankings characterized by lower standard deviation, reduced covariance, and enhanced kernel density estimation (KDE) values. Given gQuants promising performance, normalizer gene identification will be greatly improved, improving the precision of gene expression quantification in a variety of research scenarios.

molecular biology↗

bioRxiv2023

The sleep quality- and myopia-linked PDE11A-Y727C variant impacts neural physiology by reducing catalytic activity and altering subcellular compartmentalization of the enzyme

Recently, a Y727C variant in the dual-specific 3,5-cyclic nucleotide phosphodiesterase 11A (PDE11A-Y727C) was linked to increased sleep quality and reduced myopia risk in humans. Given the well-established role that the PDE11 substrates cAMP and cGMP play in eye physiology and sleep, we determined if 1) PDE11A protein is expressed in the retina or other eye segments in mouse, 2) PDE11A-Y7272C affects catalytic activity and/or subcellular compartmentalization more so than the nearby suicide-associated PDE11A-M878V variant, and 3) Pde11a deletion alters eye growth or sleep quality in male and female mice. Western blots show distinct protein expression of PDE11A4, but not PDE11A1-3, in eyes of Pde11a WT--but not KO mice--that vary by eye segment and age. In HT22 and COS-1 cells, PDE11A4-Y727C reduces PDE11A4 catalytic activity far more than PDE11A4-M878V, with both variants reducing PDE11A4-cAMP more so than PDE11A4-cGMP activity. Despite this, Pde11a deletion does not alter age-related changes in retinal or lens thickness, axial length, nor vitreous or anterior chamber depth. Further, Pde11a deletion only minimally changes refractive error and sleep quality. That said, both variants also dramatically alter the subcellular compartmentalization of human and mouse PDE11A4, an effect occurring independently of dephosphorylating PDE11A4-S117/S124 or phosphorylating PDE11A4-S162. Rather, re-compartmentalization of PDE11A4-Y727C is due to the loss of the tyrosine changing how PDE11A4 is packaged/repackaged via the trans-Golgi network. Therefore, the protective impact of the Y727C variant may reflect a gain-of-function (e.g., PDE11A4 displacing another PDE) that warrants further investigation in the context of reversing/preventing sleep disturbances or myopia.

neuroscience↗

bioRxiv2023

Apobec-Mediated Retroviral Hypermutation In Vivo is Dependent on Mouse Strain

Replication of the complex retrovirus mouse mammary tumor virus (MMTV) is antagonized by murine Apobec3 (mA3), a member of the Apobec family of cytidine deaminases. We have shown that MMTV-encoded Rem protein inhibits proviral mutagenesis by the Apobec enzyme, activation-induced cytidine deaminase (AID) during viral replication in BALB/c mice. To further study the role of Rem in vivo, we have infected C57BL/6 (B6) mice with a superantigen-independent lymphomagenic strain of MMTV (TBLV-WT) or a mutant strain (TBLV-SD) that is defective in Rem and its cleavage product Rem-CT. Unlike MMTV, TBLV induced T-cell tumors in {micro}MT mice, indicating that mature B cells, which express the highest AID levels, are not required for TBLV replication. Compared to BALB/c, B6 mice were more susceptible to TBLV infection and tumorigenesis. The lack of Rem expression accelerated B6 tumorigenesis at limiting doses compared to TBLV-WT in either wild-type B6 or AID-deficient mice. However, unlike proviruses from BALB/c mice, high-throughput sequencing indicated that proviral G-to-A or C-to-T changes did not significantly differ in the presence and absence of Rem expression. Ex vivo stimulation showed higher levels of mA3 relative to AID in B6 compared to BALB/c splenocytes, but effects of agonists differed in the two strains. RNA-Seq revealed increased transcripts related to growth factor and cytokine signaling in TBLV-SD-induced tumors relative to those from TBLV-WT, consistent with a third Rem function. Thus, Rem-mediated effects on tumorigenesis in B6 mice are independent of Apobec-mediated proviral hypermutation.

microbiology↗

bioRxiv2023

Neutrophil-derived IL-17 limits protective host responses and promotes tuberculosis pathogenesis

The protective correlates of Mycobacterium tuberculosis (Mtb) infection-elicited host immune responses are incompletely understood. Here, we report pro-pathogenic crosstalk involving Ly6G+granulocytes (Ly6G+Gra), IL-17 and COX2. We show that in the lungs of Mtb-infected wildtype mice, either BCG-vaccinated or not, most intracellular bacilli are Ly6G+Gra-resident four weeks post-infection onwards. In the genetically susceptible IFN{psi} -/- mice, excessive Ly6G+Gra infiltration correlates with severe bacteraemia. Neutralizing IL-17 (anti-IL17mAb) and COX2 inhibition by celecoxib reverse Ly6G+Gra infiltration, associated pathology and death in IFN{psi} -/- mice. Surprisingly, Ly6G+Gra also serves as the major source of IL-17 in the lungs of Mtb-infected WT or IFN{psi} -/- mice. The IL-17-COX2-Ly6G+Gra interplay also operates in WT mice. Inhibiting ROR{psi}t, the key transcription factor for IL-17 production or COX2, reduces the bacterial burden in Ly6G+Gra, leading to reduced bacterial burden and pathology in the lungs of WT mice. In the Mtb-infected WT mice, COX2 inhibition abrogates IL-17 levels in the lung homogenates and significantly enhances BCGs protective efficacy, mainly by targeting the Ly6G+Gra-resident Mtb pool, a phenotype also observed when IL-17 is blocked by ROR{psi}t inhibitor. Furthermore, in pulmonary TB patients, high neutrophil count and IL-17 correlated with adverse treatment outcomes. Together, our results suggest that IL-17 and PGE2 are the negative correlates of protection, and we propose targeting the pro-pathogenic IL-17-COX2-Ly6G+Gra axis for TB prevention and therapy.

immunology↗