Biology subjects

Bhattacharya, A.

Publications and source records attributed to Bhattacharya, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2021

Delineating the complex mechanistic interplay between autophagy and monocyte to macrophage differentiation: a functional perspective

Autophagy is an extremely essential cellular process aimed to clear redundant and damaged materials. In this study, we demonstrated that mTOR dependent classical autophagy is ubiquitously triggered in differentiating monocytes. Moreover, autophagy plays a decisive role in sustaining the process of monocyte to macrophage differentiation. We have delved deeper into understanding the underlying mechanistic complexities that trigger autophagy during differentiation. We have also shown that autophagy directs monocyte differentiation via protein degradation. Further, we delineated the complex cross-talk between autophagy and cell-cycle arrest in differentiating monocytes. This study also inspects the contribution of adhesion on various steps of autophagy and its ultimate impact on monocyte differentiation. Our study reveals new mechanistic insights into the process of autophagy associated with monocyte differentiation and would undoubtedly help to understand the intricacies of the process better for the effective design of therapeutics as autophagy and autophagy-related processes have enormous importance in human patho-physiology. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cell biology↗

bioRxiv2021

MYC promotes immune-suppression in TNBC via inhibition of IFN signaling

Immune checkpoint inhibitor (ICI) treatment has thus far shown limited efficacy in triple-negative breast cancer (TNBC) patients, presumably due to sparse or unresponsive tumor-infiltrating lymphocytes. We reveal a strong correlation between MYC expression and loss of immune signatures in human TNBC. In mouse models of BRCA1-proficient and -deficient TNBC, MYC overexpression dramatically decreased lymphocyte infiltration in tumors, along with immune signature loss. Likewise, MYC overexpression suppressed inflammatory signaling induced by BRCA1/2 inactivation in human TNBC cell lines. Moreover, MYC overexpression prevented the recruitment and activation of lymphocytes in co-cultures with human and mouse TNBC models. Chromatin immunoprecipitation (ChIP)-sequencing revealed that MYC directly binds promoters of multiple interferon-signaling genes, which were downregulated upon MYC expression. Finally, MYC overexpression suppressed induction of interferon signaling and tumor growth inhibition by a Stimulator of Interferon Genes (STING) agonist. Together, our data reveal that MYC suppresses innate immunity and facilitates immune escape, explaining the poor immunogenicity of MYC-overexpressing TNBCs. Statement of SignificanceMYC suppresses recruitment and activation of immune cells in TNBC by repressing the transcription of interferon genes. These findings provide a mechanistic rationale for the association of high MYC expression levels with immune exclusion in human TNBCs, which might underlie the relatively poor response of many TNBCs to ICI.

cancer biology↗

bioRxiv2021

An mRNA expression-based signature for oncogene-induced replication-stress

BackgroundOncogene-induced replication stress characterizes many aggressive cancers, including triple-negative breast cancer (TNBC). Several drugs are being developed that target replication stress, although it is unclear how tumors with high levels of replication stress can be identified. We aimed to develop a gene expression signature of oncogene-induced replication stress. MethodsTNBC and non-transformed RPE1-TP53wt and RPE1-TP53mut cell lines were engineered to overexpress the oncogenes CDC25A, CCNE1 or MYC. DNA fiber analysis was used to measure replication kinetics. Analysis of RNA sequencing data of cell lines and patient-derived tumor samples (TCGA n=10,592) was used to identify differential gene expression. Immunohistochemical validation was conducted on breast cancer samples (n=330). ResultsRNA sequencing revealed 52 commonly upregulated genes after induction of CDC25A, CCNE1 or MYC in our cell line panel. Integration with gene expression data of TGCA samples with amplification of replication stress-inducing oncogenes (CDC25A, CCNE1, MYC, CCND1, MYB, MOS, KRAS, ERBB2, and E2F1), yielded a six-gene signature of oncogene-induced replication stress (NAT10, DDX27, ZNF48, C8ORF33, MOCS3, and MPP6). Expression of NAT10 in breast cancer samples was correlated with phospho-RPA (R=0.451, p=1.82x10-20) and {gamma}H2AX (R=0.304, p=2.95x10-9). Applying the oncogene-induced replication stress signature to patient samples (TCGA n=8,862 and GEO n=13,912) defined the replication stress landscape across 27 tumor subtypes, and identified diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress. ConclusionWe developed a gene expression signature of oncogene-induced replication stress, which may facilitate patient selection for agents that target replication stress.

cancer biology↗

bioRxiv2020

DAF-16/FoxO and DAF-12/VDR control cellular plasticity both cell-autonomously and via interorgan signaling

Many cell types display the remarkable ability to alter their cellular phenotype in response to specific external or internal signals. Such phenotypic plasticity is apparent in the nematode C. elegans when adverse environmental conditions trigger entry into the dauer diapause stage. This entry is accompanied by structural, molecular and functional remodeling of a number of distinct tissue types of the animal, including its nervous system. The transcription factor effectors of three different hormonal signaling systems, the insulin-responsive DAF-16/FoxO transcription factor, the TGF{beta}-responsive DAF-3/SMAD transcription factor and the steroid nuclear hormone receptor, DAF-12/VDR, a homolog of the vitamin D receptor, were previously shown to be required for entering the dauer arrest stage, but their cellular and temporal focus of action for the underlying cellular remodeling processes remained incompletely understood. Through the generation of conditional alleles that allowed us to spatially and temporally control gene activity, we show here that all three transcription factors are not only required to initiate tissue remodeling upon entry into the dauer stage, as shown before, but are also continuously required to maintain the remodeled state. We show that DAF-3/SMAD is required in sensory neurons to promote and then maintain animal-wide tissue remodeling events. In contrast, DAF-16/FoxO or DAF-12/VDR act cell autonomously to control anatomical, molecular and behavioral remodeling events in specific cell types. Intriguingly, we also uncover non-cell autonomous function of DAF-16/FoxO and DAF-12/VDR in nervous system remodeling, indicating the presence of several insulin-dependent inter-organ signaling axes. Our findings provide novel perspectives on how hormonal systems control tissue remodeling.

genetics↗

bioRxiv2020

Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms

Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method for simultaneous detection of clinically significant genomic mutations with high sensitivity. However, due to lack of standard NGS protocols, the application of NGS for hematologic malignancies into clinical settings remains limited. We report development and validation of a 48-gene NGS panel for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies [≥]5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n=2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9-99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n=2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms.

cancer biology↗

bioRxiv2020

Nuclear Morphology Optimized Deep Hybrid Learning (NUMODRIL): A novel architecture for accurate diagnosis/prognosis of Ovarian Cancer

Nuclear morphological features are potent determining factors for clinical diagnostic approaches adopted by pathologists to analyse the malignant potential of cancer cells. Considering the structural alteration of nucleus in cancer cells, various groups have developed machine learning techniques based on variation in nuclear morphometric information like nuclear shape, size, nucleus-cytoplasm ratio and various non-parametric methods like deep learning have also been tested for analysing immunohistochemistry images of tissue samples for diagnosing various cancers. Our aim is to study the morphometric distribution of nuclear lamin proteins as a specific parameter in ovarian cancer tissues. Besides being the principal mechanical component of the nucleus, lamins also present a platform for binding of proteins and chromatin thereby serving a wide range of nuclear functions like maintenance of genome stability, chromatin regulation. Altered expression of lamins in different subtypes of cancer is now evident from data across the world. It has already been elucidated that in ovarian cancer, extent of alteration in nuclear shape and morphology can determine degree of genetic changes and thus can be utilized to predict the outcome of low to high form of serous carcinoma. In this work, we have performed exhaustive imaging of ovarian cancer versus normal tissue and introduced a novel Deep Hybrid Learning approach on the basis of the distribution of lamin proteins. Although developed with ovarian cancer datasets in view, this architecture would be of immense importance in accurate and fast diagnosis and prognosis of all types of cancer associated with lamin induced morphological changes and would perform across small/medium to large datasets with equal efficiency. Significance StatementWe have developed a novel Deep Hybrid Learning approach based on nuclear morphology to classify normal and ovarian cancer tissues with highest possible accuracy and speed. Ovarian cancer cells can be easily distinguished from their enlarged nuclear morphology as is evident from lamin A & B distribution pattern. This is the first report to invoke specific nuclear markers like lamin A & B instead of classical haematoxylin-eosin staining in an effort to build parametric datasets. Our approach has been shown to outperform the existing deep learning techniques in training and validation of datasets over a wide range. Therefore this method could be used as a robust model to predict malignant transformations of benign nuclei and thus be implemented in the diagnosis and prognosis of ovarian cancer in future. Most importantly, this method can be perceived as a generalized approach in the diagnosis for all types of cancer.

cancer biology↗

bioRxiv2020

Altered food habits? Understanding the feeding preference of free-ranging Grey langur (Semnopithecus entellus) within an urban settlement.

Urbanization affects concurrent human-animal movements as a result of altered resource availability and land use pattern, which leads to considerable ecological consequences. While some animals find themselves adrift, homeless with the uncertainty of resources resulting from the urban encroachment, few of them manage to survive by altering their natural behavioural patterns, and co-exist with humans. Folivorous colobines, such as grey langur, whose feeding repertoire largely consists of plant parts, tend to be more attuned to the urban high-calorie food sources to attain maximum fitness benefits within the concrete jungle having an insignificant green cover. However, such a mismatch between their generalized feeding behaviour and specialized gut physiology reminds us of the Liems paradox and demands considerable scientific attention which could tell us the story behind colobines successful co-existence within human settlements. Besides understanding their population dynamics, the effective management of these urbanized, free-ranging, non-human primate populations also depends on their altered feeding preferences, altogether which could lead us to the development of an ecologically sound urban ecosystem. Here, we have used a field-based experimental set up which allows langurs to choose between natural and urban food options, being independent of any inter-specific conflicts over resources due to food scarcity. The multinomial logit model reveals the choice-based decision making of these free-ranging grey langurs in an urban settlement of West Bengal, India, where they have not only learned to approach the human-provisioned urban food items but also shown a keen interest in it. While urbanization imposes tremendous survival challenges to these animals, it also opens up for various alternative options for human-animal co-existence which is reflected in this study, and could guide us for the establishment of a sustainable urban ecosystem in the future. HIGHLIGHTSO_LIThe feeding repertoire of free-ranging grey langurs at Dakshineswar largely consists of urban food items in contrast to the langurs of Nangi, and Nalpur who mostly depend on natural food sources. C_LIO_LIHigh human-langur interactions together with the scarcity of natural plant-based food sources could be considered as an intriguing driving force behind langurs altered feeding habits in Dakhineswar. C_LIO_LIThe field-based experimental set up allows free-ranging langurs to choose between natural and urban food options in an urban settlement like Dakhineswar. C_LIO_LIUrban food items outperformed natural food items as the most chosen one, indicating langurs altered feeding preferences which facilitate their successful co-existence within an urban ecosystem. C_LI

animal behavior and cognition↗

bioRxiv2020

Robust and independent metabolic transcriptional components in 34,494 patient-derived samples and cell lines: a resource for translational cancer research

Patient-derived expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Therefore, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. We, therefore, performed consensus Independent Component Analyses (c-ICA) with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. c-ICA enabled us to create a transcriptional metabolic landscape in which many robust metabolic transcriptional components and their activation score in individual samples were defined. Here we demonstrate how this landscape can be used to explore associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment. The metabolic landscape can be explored at http://www.themetaboliclandscapeofcancer.com.

bioinformatics↗

bioRxiv2020

Imbalance of flight-freeze responses and their cellular correlates in the Nlgn3-/y rat model of autism

Mutations in the postsynaptic transmembrane protein neuroligin-3 are highly correlative with autism spectrum disorders (ASDs) and intellectual disabilities (IDs). Fear learning is well studied in models of these disorders, however differences in fear response behaviours are often overlooked. Whilst examining fear in a rat model of ASD/ID lacking Nlgn3, we observed that they display a greater propensity to exhibit flight responses in contrast to classic freezing seen in wildtypes during fearful situations. Consequently, we examined the physiological underpinnings of this in neurons of the periaqueductal grey (PAG), a midbrain area involved in flight-or-freeze responses. In ex vivo slices from Nlgn3-/y, rats, dorsal PAG (dPAG) neurons showed intrinsic hyperexcitability. Further analysis of this revealed lower magnitude in vivo dPAG stimulation evoked flight behaviour in Nlgn3-/y, rats, indicating the functional impact of the increased cellular excitability. This study provides new insight into potential pathophysiologies leading to emotional disorders in individuals with ASD.

neuroscience↗

bioRxiv2020

DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing

Targeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.

bioinformatics↗

bioRxiv2020

Evidence for the Placenta-Brain Axis: Multi-Omic Kernel Aggregation Predicts Intellectual and Social Impairment in Children Born Extremely Preterm

BackgroundChildren born extremely preterm are at heightened risk for intellectual and social impairment, including Autism Spectrum Disorder (ASD). There is increasing evidence for a key role of the placenta in prenatal developmental programming, suggesting that the placenta may explain origins of neurodevelopmental outcomes. MethodsWe examined associations between placental genomic and epigenomic profiles and assessed their ability to predict intellectual and social impairment at age 10 years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II (DAS-II) and Social Responsiveness Scale (SRS), respectively. Examining IQ and SRS allows for studying ASD risk beyond the diagnostic criteria, as IQ and SRS are continuous measures strongly correlated with ASD. Genome-wide mRNA, CpG methylation and miRNA were assayed with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcriptome Assay, and Illumina EPIC/850K array, respectively. We conducted genome-wide differential mRNA/miRNA and epigenome-wide placenta analyses. These molecular features were integrated for a predictive analysis of IQ and SRS outcomes using kernel aggregation regression. We lastly examined associations between ASD and the genomically-predicted component of IQ and SRS. ResultsGenes with important roles in placenta angiogenesis and neural function were associated with intellectual and social impairment. Kernel aggregations of placental multi-omics strongly predicted intellectual and social function, explaining approximately 8% and 12% of the variance in SRS and IQ scores via cross-validation, respectively. Predicted in-sample SRS and IQ showed significant positive and negative associations with ASD case-control status. LimitationsThe ELGAN is a cohort of children born pre-term, andgeneralization may be affected by unmeasured confounders associated with low gestational age. We conducted external validation of predictive models, though the sample size of the out-sample dataset (N = 49) and the scope of the available placental datasets are limited. Further validation of the models is merited. ConclusionsAggregating information from biomarkers within and between molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits influenced by the placenta-brain axis may be omnigenic.

genomics↗

bioRxiv2020

CD4+ T-cell epitope prediction by combined analysis of antigen conformational flexibility and peptide-MHCII binding affinity

Antigen processing in the class II MHC pathway depends on conventional proteolytic enzymes, potentially acting on antigens in native-like conformational states. CD4+ epitope dominance arises from a competition between antigen folding, proteolysis, and MHCII binding. Protease-sensitive sites, linear antibody epitopes, and CD4+ T-cell epitopes were mapped in the plague vaccine candidate F1-V to evaluate the various contributions to CD4+ epitope dominance. Using X-ray crystal structures, antigen processing likelihood (APL) predicts CD4+ epitopes with significant accuracy without considering peptide-MHCII binding affinity. The profiles of conformational flexibility derived from the X-ray crystal structures of the F1-V proteins, Caf1 and LcrV, were similar to the biochemical profiles of linear antibody epitope reactivity and protease-sensitivity, suggesting that the role of structure in proteolysis was captured by the analysis of the crystal structures. The patterns of CD4+ T-cell epitope dominance in C57BL/6, CBA, and BALB/c mice were compared to epitope predictions based on APL, peptide binding to MHCII proteins, or both. For a sample of 13 diverse antigens larger than 200 residues, accuracy of epitope prediction by the combination of APL and I-Ab-MHCII-peptide affinity approached 40%. When MHCII allele specificity is also diverse, such as in human immunity, prediction of dominant epitopes by APL alone approached 40%. Since dominant CD4+ epitopes tend to occur in conformationally stable antigen domains, crystal structures typically are available for analysis by APL; and thus, the requirement for a crystal structure is not a severe limitation.

immunology↗

bioRxiv2020

Novel class of OTU deubiquitinases regulate substrate ubiquitinationupon Legionella infection

Legionella pneumophila is a gram-negative pathogenic bacterium that causes Legionaries disease. The Legionella genome codes more than 300 effector proteins able to modulate host-pathogen interactions during infection. Among them are also enzymes altering the host-ubiquitination system including bacterial ligases and deubiquitinases. In this study, based on homology-detection screening on 305 Legionella effector proteins, we identified two Legionella OTU-like deubiquitinases (LOT; LotB (Lpg1621/Ceg23) and LotC (Lpg2529), LotA (Lpg2248/Lem21) is already known). A crystal structure of LotC catalytic core (LotC14-310) was determined at 2.4 [A] and compared with other OTU deubiquitinases, including LotB. Unlike the classical OTU-family, the structures of Legionella OTU-family (LotB and LotC) shows an extended helical lobe between the Cys-loop and the variable loop, which define a novel class of OTU-deubiquitinase. Despite structural differences in their helical lobes, both LotB and LotC interact with ubiquitin. LotB has an additional ubiquitin binding site (S1) enabling specific cleavage of Lys63-linked poly-ubiquitin chains. By contrast, LotC only contains the S1 site and cleaves different species of ubiquitin chains. MS analysis of catalytically inactive LotB and LotC identified different categories of host-substrates for these two related DUBs. Together, our results provide new structural insights of bacterial OTU deubiquitinases and indicate distinct roles of bacterial deubiquitinases in host-pathogen interactions.

molecular biology↗

bioRxiv2020

Multi-omic strategies for transcriptome-wide prediction and association studies

Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or other molecular effects underlying the SNP-gene association. Here, we outline multi-omics strategies for transcriptome imputation from germline genetics to allow more powerful testing of gene-trait associations by prioritizing distal-SNPs to the gene of interest. In one extension, we identify mediating biomarkers (CpG sites, microRNAs, and transcription factors) highly associated with gene expression and train predictive models for these mediators using their local SNPs. Imputed values for mediators are then incorporated into the final predictive model of gene expression, along with local SNPs. In the second extension, we assess distal-eQTLs (SNPs associated with genes not in a local window around it) for their mediation effect through mediating biomarkers local to these distal-eSNPs. Distal-eSNPs with large indirect mediation effects are then included in the transcriptomic prediction model with the local SNPs around the gene of interest. Using simulations and real data from ROS/MAP brain tissue and TCGA breast tumors, we show considerable gains of percent variance explained (1-2% additive increase) of gene expression and TWAS power to detect gene-trait associations. This integrative approach to transcriptome-wide imputation and association studies aids in identifying the complex interactions underlying genetic regulation within a tissue and important risk genes for various traits and disorders. AUTHOR SUMMARYTranscriptome-wide association studies (TWAS) are a powerful strategy to study gene-trait associations by integrating genome-wide association studies (GWAS) with gene expression datasets. TWAS increases study power and interpretability by mapping genetic variants to genes. However, traditional TWAS consider only variants that are close to a gene and thus ignores important variants far away from the gene that may be involved in complex regulatory mechanisms. Here, we present MOSTWAS (Multi-Omic Strategies for TWAS), a suite of tools that extends the TWAS framework to include these distal variants. MOSTWAS leverages multi-omic data of regulatory biomarkers (transcription factors, microRNAs, epigenetics) and borrows from techniques in mediation analysis to prioritize distal variants that are around these regulatory biomarkers. Using simulations and real public data from brain tissue and breast tumors, we show that MOSTWAS improves upon traditional TWAS in both predictive performance and power to detect gene-trait associations. MOSTWAS also aids in identifying possible mechanisms for gene regulation using a novel added-last test that assesses the added information gained from the distal variants beyond the local association. In conclusion, our method aids in detecting important risk genes for traits and disorders and the possible complex interactions underlying genetic regulation within a tissue.

genetics↗

bioRxiv2020

An approach for normalization and quality control for NanoString RNA expression data

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility, and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization, and iterative data visualization and biological validation. The approach was evaluated using a large cohort (N = 1,649) from the Carolina Breast Cancer Study, two cohorts of moderate sample size (N = 359 and 130), and a small published dataset (N = 12). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoStrings commercial package, without diminishing biological variation, especially in long-term longitudinal multi-phase or multi-site cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization, and visualization of NanoString nCounter data is an imperative component of study design that influences results in downstream analyses.

genomics↗

bioRxiv2020

Lipid Sponge Droplets as Programmable Synthetic Organelles

Living cells segregate molecules and reactions in various subcellular compartments known as organelles. Spatial organization is likely essential for expanding the biochemical functions of synthetic reaction systems, including artificial cells. Many studies have attempted to mimic organelle functions using lamellar membrane-bound vesicles. However, vesicles typically suffer from highly limited transport across the membranes and an inability to mimic the dense membrane networks typically found in organelles such as the endoplasmic reticulum. Here we describe programmable synthetic organelles based on highly stable nonlamellar sponge phase droplets that spontaneously assemble from a single-chain galactolipid and non-ionic detergents. Due to their nanoporous structure, lipid sponge droplets readily exchange materials with the surrounding environment. In addition, the sponge phase contains a dense network of lipid bilayers and nanometric aqueous channels, which allows different classes of molecules to partition based on their size, polarity, and specific binding motifs. The sequestration of biologically relevant macromolecules can be programmed by the addition of suitably functionalized amphiphiles to the droplets. We demonstrate that droplets can harbor functional soluble and transmembrane proteins, allowing for the co-localization and concentration of enzymes and substrates to enhance reaction rates. Droplets protect bound proteins from proteases, and these interactions can be engineered to be reversible and optically controlled. Our results show that lipid sponge droplets permit the facile integration of membrane-rich environments and self-assembling spatial organization with biochemical reaction systems. Significance statementOrganelles spatially and temporally orchestrate biochemical reactions in a cell to a degree of precision that is still unattainable in synthetic reaction systems. Additionally, organelles such as the endoplasmic reticulum (ER) contain highly interconnected and dense membrane networks that provide large reaction spaces for both transmembrane and soluble enzymes. We present lipid sponge droplets to emulate the functions of organelles such as the ER. We demonstrate that lipid sponge droplets can be programmed to internally concentrate specific proteins, host and accelerate biochemical transformations, and to rapidly and reversibly sequester and release proteins to control enzymatic reactions. The self-assembled and programmable nature of lipid sponge droplets will facilitate the integration of complex functions for bottom up synthetic biology.

synthetic biology↗

bioRxiv2020

Evaluation of modulators of cAMP-response in terms of their impact on cell cycle and mitochondrial activity of Leishmania donovani

With the identification of novel cAMP binding effecter molecules in Trypanosoma, role of cAMP in kinetopalstida parasites gained an intriguing break through. Despite earlier demonstrations of role of cAMP in survival of Leishmania during macrophage infection, there is essential need to specifically clarify involvement of cAMP in various cellular processes in the parasite. In this context, we sought to gain a comprehensive understanding of the effect of cAMPanalogs and cAMP-phosphodiesterase (PDE) inhibitors on proliferation of log phase parasites. Administration of both hydrolysable (8-pCPT-cAMP) and non-hydrolysable analogs (Sp-8-pCPT-cAMPS) of cAMP resulted in significant decrease of Leishmania proliferation. Amongst the various PDE inhibitors, etazolate was found to be potently anti-proliferative. BrdU cell proliferation and K/N/F-enumeration microscopic study revealed that both cAMP analogues and selective PDE inhibitors resulted in significant cell cycle arrest at G1 phase with reduced S-phase population. Furthermore, careful examination of the flagellar motility patterns revealed significantly reduced coordinated forward flagellar movement of the promastigotes with a concomitant decrease in cellular ATP levels. Alongside, 8-pCPT-cAMP and PDE inhibitors etazolate and trequinsin showed marked reduction in mitochondrial membrane potential. Treatment of etazolate at subcytotoxic concentration to infected macrophages significantly reduced parasite burden and administration of etazolate to Leishmania-infected BALB/c mice showed reduced liver and spleen parasite burden. Collectively, these results imply involvement of cAMP in various crucial processes paving the avenue for developing potent anti-leishmanial agent. Author SummaryLeishmania donovani is the causative agent of fatal Visceral Leishmaniasis. The current available medications are toxic, expensive and require long term daily administrations. With an aim to develop improved therapeutic, components of cAMP homeostasis, particularly cAMP-phosphodiesteares, has been targeted for Leishmania and other kinetoplastid pathogens. cAMP plays diverse roles in functional processes involved in cell division, transition into different stages of the life cycle of Leishmania and motility. In this study, the authors found administration of both hydrolysable and non-hydrolysable analogs of cAMP and certain PDE inhibitors resulted in remarkable decrease proliferation with considerable cytopathic impact on promastigotes. The mammalian phosphodiestearse inhibitor etazolate caused significant reduction in parasite load in L. donovani infected macrophages and demonstrated considerable reduction of liver and spleen parasite burden in in vivo mouse infection model. The study suggested that etazolate, with its slightest impact on mammalian host, can be repurposed for developing effective anti-leishmanials.

cell biology↗

bioRxiv2020

A comprehensive and comparative study on the action of pentacyclic triterpenoids on Vibrio cholerae biofilms.

While serving as environmental reservoir for V. cholerae infection, biofilms are also crucial for intestinal colonization of the pathogen. Triterpenoids, a group of bioactive phytochemicals, have been tested for antibiofilm activity against model biofilm forming bacteria in recent times. In this context, glycyrrhetinic acid (GRA), ursolic acid (UA) and betulinic acid (BA), representing three categorically distinct groups of pentacyclic triterpenoids, are targeted for profiling their impact on Vibrio cholerae C6709 biofilms. The triterpenoids substantially affected biofilm associated attributes like formation, substratum adherence and dispersion from preformed biofilms. Though at variable degree, the compounds decreased cell surface hydrophobicity and composition in terms of macromolecular content. Not only EPS-associated extracellular enzyme activities were estimated to be reduced by triterpenoid exposure, ultra structural analysis also revealed that GRA, UA and BA can affect extracellular polymeric substance (EPS) content. Albeit total extracellular proteolytic activity remained unaffected by the triterpenoids, GRA treatment resulted in considerable reduction of extracellular gelatinase activity. Molecular docking analysis indicated potential interaction with cyclic di-GMP sensor VpsT, autoinducer-2 sensor kinase LuxP-LuxQ and transcriptional activator HapR, component of complex quorum sensing networks modulating biofilm formation. Comprehensive analysis of antibiotic action revealed accentuation of cephalosporin antibiotics with GRA and UA while BA potentiated action of fluoroquinolones, widening the scope of combinatorial therapeutic strategy.

microbiology↗