Biology subjects

Pandey, A.

Publications and source records attributed to Pandey, A..

At least 109 records · Page 6Linked to original sources

bioRxiv2020

Model Reduction Tools For Phenomenological Modeling of Input-Controlled Biological Circuits

We present a Python-based software package to automatically obtain phenomenological models of input-controlled synthetic biological circuits from descriptive models. From the parts and mechanism description of a synthetic biological circuit, it is easy to obtain a chemical reaction model of the circuit under the assumptions of mass-action kinetics using various existing tools. However, using these models to guide design decisions during an experiment is difficult due to a large number of reaction rate parameters and species in the model. Hence, phenomenological models are often developed that describe the effective relationships among the circuit inputs, outputs, and only the key states and parameters. In this paper, we present an algorithm to obtain these phenomenological models in an automated manner using a Python package for circuits with inputs that control the desired outputs. This model reduction approach combines the common assumptions of time-scale separation, conservation laws, and species abundance to obtain the reduced models that can be used for design of synthetic biological circuits. We consider an example of a simple gene expression circuit and another example of a layered genetic feedback control circuit to demonstrate the use of the model reduction procedure.

synthetic biology↗

bioRxiv2020

The R2R3-MYB gene family in banana (Musa acuminata): genome-wide identification, classification and expression patterns

The R2R3-MYB genes comprise one of the largest transcription factor gene families in plants, playing regulatory roles in plant-specific developmental processes, defense responses and metabolite accumulation. To date MYB family genes have not yet been comprehensively identified in the major staple fruit crop banana. In this study, we present a comprehensive, genome-wide analysis of the MYB genes from Musa acuminata DH-Pahang (A genome). A total of 285 R2R3-MYB genes as well as genes encoding three other classes of MYB proteins containing multiple MYB repeats were identified and characterised with respect to structure and chromosomal organisation. Organ- and development-specific expression patterns were determined from RNA-seq data. For 280 M. acuminata MYB genes for which expression was found in at least one of the analysed samples, a variety of expression patterns were detected. The M. acuminata R2R3-MYB genes were functionally categorised, leading to the identification of seven clades containing only M. acuminata R2R3-MYBs. The encoded proteins may have specialised functions that were acquired or expanded in Musa during genome evolution. This functional classification and expression analysis of the MYB gene family in banana establishes a solid foundation for future comprehensive functional analysis of MaMYBs and can be utilized in banana improvement programmes.

plant biology↗

bioRxiv2020

Protein evolution is structure dependent and non-homogeneous across the tree of life

MotivationProtein sequence evolution is a complex process that varies among-sites within proteins and across the tree of life. Comparisons of evolutionary rate matrices for specific taxa ( clade-specific models) have the potential to reveal this variation and provide information about the underlying reasons for those changes. To study changes in patterns of protein sequence evolution we estimated and compared clade-specific models in a way that acknowledged variation within proteins due to structure. ResultsClade-specific model fit was able to correctly classify proteins from four specific groups (vertebrates, plants, oomycetes, and yeasts) more than 70% of the time. This was true whether we used mixture models that incorporate relative solvent accessibility or simple models that treat sites as homogeneous. Thus, protein evolution is non-homogeneous over the tree of life. However, a small number of dimensions could explain the differences among models (for mixture models ~50% of the variance reflected relative solvent accessibility and ~25% reflected clade). Relaxed purifying selection in taxa with lower long-term effective population sizes appears to explain much of the among clade variance. Relaxed selection on solvent-exposed sites was correlated with changes in amino acid side-chain volume; other differences among models were more complex. Beyond the information they reveal about protein evolution, our clade-specific models also represent tools for phylogenomic inference. AvailabilityModel files are available from https://github.com/ebraun68/clade_specific_prot_models. Contactebraun68@ufl.edu Supplementary informationSupplementary data are appended to this preprint.

evolutionary biology↗

bioRxiv2020

Complement and coagulation cascades are potentially involved in dopaminergic neurodegeneration in alpha-synuclein-based mouse models of Parkinson's disease

Parkinsons disease (PD) is the second most common neurodegenerative disorder that results in motor dysfunction and eventually, cognitive impairment. -Synuclein protein has been known to be the most culprit protein, but the underlying pathological mechanism still remains to be elucidated. As an effort to clarify the pathogenesis mechanism by -synuclein, various PD mouse models with -synuclein overexpression have been developed. However, the systemic analysis of protein abundance change by the overexpressed -synuclein in the whole proteome level has been still lacking. To address this issue, we established two sophisticated mouse models of PD by injecting -synuclein preformed fibrils (PFF) or by inducing overexpression of human A53T -synuclein to discover overlapping pathways, which could be altered in the two different types of PD mouse model. For more accurate quantification of mouse brain proteome, stable isotope labeling with amino acid in mammal-based quantification was implemented. As a result, we have successfully identified a total of 8,355 proteins from both of the mouse models; [~]6,800 and [~]7,200 proteins from -synuclein PFF injected mice and human A53T -synuclein transgenic mice, respectively. From the pathway analysis of the differentially expressed proteins in common, the complement and coagulation cascade pathway were determined as the most enriched ones. This is the first study that highlights the significance of the complement and coagulation pathway in the pathogenesis of PD through proteome analyses with two sophisticated mouse models of PD.

neuroscience↗

bioRxiv2019

Programmable CRISPR interference for gene silencing using Cas13a in mosquitoes

In the CRISPR-Cas systems, Cas13a is an RNA-guided RNA nuclease specifically targeting single strand RNA. We developed a Cas13a mediated CRISPR interference tool to target mRNA for gene silencing in mosquitoes. The machinery was tested in two mosquito species. A Cas13a expressing plasmid was delivered to mosquitoes by intrathoracic injection, and Cas13a transcripts were detectable at least10 days post-delivery. In Anopheles gambiae, vitellogenin gene was silenced by Vg-crRNA injection two hours post-blood meal, which was accompanied by a significant reduction in egg production. In Aedes aegypti, the - and {delta}-subunits of COPI genes were silenced by a post-blood meal crRNA injection, which resulted in mortality and fragile midguts, reproducing a phenotype reported previously. Co-silencing genes simultaneously is achievable when a cocktail of target crRNAs is given. No detectable collateral cleavages of non-target transcripts were observed in the study. This study adds a programmable CRISPR tool to manipulate RNA in mosquitoes.

molecular biology↗

bioRxiv2019

Mapping the micro-proteome of the nuclear lamina and lamin associated domains

The nuclear lamina is a proteinaceous network of filaments that provide both structural and gene regulatory functions by tethering proteins and large domains of DNA, so-called lamin associated domains (LADs), to the periphery of the nucleus. LADs are a large fraction of the mammalian genome that are repressed, in part, by their association to the nuclear periphery. The genesis and maintenance of LADs is poorly understood as are the proteins that participate in these functions. In an effort to identify proteins that reside at the nuclear periphery and potentially interact with LADs, we have taken a two-pronged approach. First, we have undertaken an interactome analysis of the inner nuclear membrane bound LAP2{beta} to further characterize the nuclear lamina proteome. To accomplish this, we have leveraged the BioID system, which previously has been successfully used to characterize the nuclear lamina proteome. Second, we have established a system to identify proteins that bind to LADs by developing a chromatin directed BioID system. We combined the BioID system with the m6A-tracer system which binds to LADs in live cells to identify both LAD proximal and nuclear lamina proteins. In combining these datasets, we have further characterized the protein network at the nuclear lamina, identified putative LAD proximal proteins and found several proteins that appear to interface with both micro-proteomes. Importantly, several proteins essential for LAD function, including heterochromatin regulating proteins related to H3K9 methylation, were identified in this study.

genomics↗

bioRxiv2019

p53-induced apoptosis is specified by a translation program regulated by PCBP2 and DHX30.

Activation of p53 by the small molecule Nutlin can result in a combination of cell cycle arrest and apoptosis. The relative strength of these events is difficult to predict by classical gene expression analysis, leaving uncertainty as to the therapeutic benefits of Nutlin. Here, we report a new translational control mechanism shaping p53-dependent apoptosis. Using polysome profiling, we establish Nutlin-induced apoptosis to be associated with the enhanced translation of mRNAs carrying multiple copies of a newly identified 3UTR CG-rich motif mediating p53-dependent death (CGPD-motif). We identified PCBP2 and DHX30 as CGPD-motif interactors. We found that in cells undergoing persistent cell cycle arrest in response to Nutlin, CGPD-motif mRNAs are repressed by the PCBP2-dependent binding of DHX30 to the motif. Thus, upon DHX30 depletion in these cells, the translation of CGPD-motif mRNAs is increased, and the response to Nutlin shifts towards apoptosis. Instead, DHX30 inducible overexpression in SJSA1 cells, that undergo Nutlin-induced apoptosis, leads to decreased translation of CGPD-motif mRNAs. Overall, this work establishes the role of PCBP2-DHX30 in controlling the translation of CGPD-motif mRNAs and thus provide a new mechanism to modulate the induction of p53-dependent apoptosis.

molecular biology↗

bioRxiv2019

Proteome-wide characterization and biomarker identification of intracranial aneurysm

The scientific basis of intracranial aneurysm (IA) formation, its rupture and further development of cerebral vasospasm remains incompletely understood. Deciphering the molecular mechanisms underlying these events will lead to identification of early detection biomarkers and in turn, improved treatment outcomes. Aberrant protein expression may drive structural alterations of vasculature found in IA. To unravel these aberrations, we performed untargeted, global, quantitative proteomic analysis of aneurysm tissue and serum from patients with IA. Samples were derived from patients of three clinical sub groups- 1) unruptured aneurysm 2) ruptured aneurysm without vasospasm 3) ruptured aneurysm who developed vasospasm. A total of 937 and 294 proteins were identified in aneurysm tissue and serum samples respectively. Several proteins that are known to maintain the structural integrity of vasculature were found to be dysregulated. ORM1, a glycoprotein, was significantly upregulated in both the aneurysm tissue and serum samples of unruptured IA patients. We employed a larger cohort of patients and validated ORM1 as a potential biomarker for screening of unruptured aneurysm using ELISA. Samples from ruptured aneurysm with vasospasm showed significant upregulation of MMP9 as compared to ruptured aneurysm without vasospasm. Using a cohort of ruptured aneurysm patients with and without vasospasm, we validated MMP9 as a potential biomarker for vasospasm. This study reveals pathophysiology underlying different clinical sub groups of IA and also suggests potential biomarkers.

neuroscience↗

bioRxiv2019

Extraction of common task features in EEG-fMRI data using coupled tensor-tensor decomposition

The fusion of simultaneously recorded EEG and fMRI data is of great value to neuroscience research due to the complementary properties of the individual modalities. Traditionally, techniques such as PCA and ICA, which rely on strong strong non-physiological assumptions such as orthogonality and statistical independence, have been used for this purpose. Recently, tensor decomposition techniques such as parallel factor analysis have gained more popularity in neuroimaging applications as they are able to inherently contain the multidimensionality of neuroimaging data and achieve uniqueness in decomposition without imposing strong assumptions. Previously, the coupled matrix-tensor decomposition (CMTD) has been applied for the fusion of the EEG and fMRI. Only recently the coupled tensor-tensor decomposition (CTTD) has been proposed. Here for the first time, we propose the use of CTTD of a 4th order EEG tensor (space, time, frequency, and participant) and 3rd order fMRI tensor (space, time, participant), coupled partially in time and participant domains, for the extraction of the task related features in both modalities. We used both the sensor-level and source-level EEG for the coupling. The phase shifted paradigm signals were incorporated as the temporal initializers of the CTTD to extract the task related features. The validation of the approach is demonstrated on simultaneous EEG-fMRI recordings from six participants performing an N-Back memory task. The EEG and fMRI tensors were coupled in 9 components out of which 7 components had a high correlation (more than 0.85) with the task. The result of the fusion recapitulates the well-known attention network as being positively, and the default mode network working negatively time-locked to the memory task.

bioinformatics↗

bioRxiv2019

EpCAM Aptamer siRNA chimeras: Therapeutic efficacy in epithelial cancer cells.

In the era of personalized medicine as well as precision medicine, targeted therapy has become an integral part of cancer treatment in conjunction with conventional chemo- and radiotherapy. We designed aptamer-siRNA chimeras that can specifically target cancers expressing EpCAM, a stem cell marker and deliver the specific siRNA required for therapy response. The siRNAs were chosen against PLK1, BCL2 and STAT3 as these oncogenes play prominent role in tumour progression of several cancers. Targeted delivery of EpCAM-siRNA chimeras resulted in cell death in several cancer cell lines such as cancers of the breast, lung, head and neck, liver and retinoblastoma. In vivo analysis of EpCAM-siRNA chimera mediated silencing on RB xenografts tumour model showed increased tumor reduction in all the three EpCAM-siRNA treated conditions. However, regulation of PLK1 exhibited higher efficacy in tumour reduction. Therefore. We studied signaling mechanism using global phosphoproteomics analysis. An increased P53 mediated downstream signalling pathway might have enabled increased apoptosis in the cancer cells. In conclusion, this study demonstrated the efficacy of EpCAM aptamer chimeras coupled to siRNA gene silencing for targeted anti-cancer therapy.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC=\"FIGDIR/small/656199v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (48K):\norg.highwire.dtl.DTLVardef@1ce89daorg.highwire.dtl.DTLVardef@bc5daeorg.highwire.dtl.DTLVardef@aa4ceforg.highwire.dtl.DTLVardef@a1159e_HPS_FORMAT_FIGEXP M_FIG C_FIG Illustration showing how EpCAM aptamer-mediated silencing of PLK1 could control the cell cycle progression at multiple number of check points and induce apoptosis involving hyper and hypophosphorylation of variety of signalling molecules

cancer biology↗

bioRxiv2019

An automated model reduction tool to guide the design and analysis of synthetic biological circuits

We present an automated model reduction algorithm that uses quasi-steady state approximation to minimize the error between the desired outputs. Additionally, the algorithm minimizes the sensitivity of the error with respect to parameters to ensure robust performance of the reduced model in the presence of parametric uncertainties. We develop the theory for this model reduction algorithm and present the implementation of the algorithm that can be used to perform model reduction of given SBML models. To demonstrate the utility of this algorithm, we consider the design of a synthetic biological circuit to control the population density and composition of a consortium consisting of two different cell strains. We show how the model reduction algorithm can be used to guide the design and analysis of this circuit.

synthetic biology↗

bioRxiv2019

Control of density and composition in an engineered two-member bacterial community

As studies continue to demonstrate how our health is related to the status of our various commensal microbiomes, synthetic biologists are developing tools and approaches to control these microbiomes and stabilize healthy states or remediate unhealthy ones. Building on previous work to control bacterial communities, we have constructed a synthetic two-member bacterial consortium engineered to reach population density and composition steady states set by inducer inputs. We detail a screening strategy to search functional parameter space in this high-complexity genetic circuit as well as initial testing of a functional two-member circuit.\n\nWe demonstrate non-independent changes in total population density and composition steady states with a limited set of varying inducer concentrations. After a dilution to perturb the system from its steady state, density and composition steady states are not regained. Modeling and simulation suggest a need for increased degradation of intercellular signals to improve circuit performance. Future experiments will implement increased signal degradation and investigate the robustness of control of each characteristic to perturbations from steady states.

synthetic biology↗

bioRxiv2019

Juvenile hormone interacts with multiple factors to modulate aggression and dominance in a social bumblebee

Juvenile hormone (JH) is a key regulator of insect development and reproduction. Given that JH commonly affects adult insect fertility, it has been hypothesized to also regulate behaviors such as dominance and aggression that are associated with reproduction. We tested this hypothesis in the bumble bee Bombus terrestris for which JH has been shown to be the major gonadotropin. We used the allatoxin Precocene-I (P-I) to reduce hemolymph JH titers and replacement therapy with the natural JH to revert this effect. In small orphan groups of workers with similar body size but mixed treatment, P-I treated bees showed lower aggressiveness, oogenesis, and dominance rank compared with control and replacement therapy treated bees. In similar groups in which all bees were treated similarly, there was a clear dominance hierarchy, even in P-I and replacement therapy treatment groups in which the bees showed similar levels of ovarian activation. In a similar experiment in which bees differed in body size, larger bees were more likely to be dominant despite their similar JH treatment and ovarian state. In the last experiment, we show that JH manipulation does not affect dominance rank in groups that had already established a stable dominance hierarchy. These findings solve previous ambiguities concerning whether or not JH affects dominance in bumble bees. JH positively affects dominance, but bees with similar levels of JH can nevertheless establish dominance hierarchies. Thus, multiple factors including JH, body size, and previous experience affect dominance and aggression in social bumble bees.

animal behavior and cognition↗

bioRxiv2019

Proteomic Analysis of Plasmodium Merosomes: The Link Between Liver and Blood Stages in Malaria

The pre-erythrocytic liver stage of the malaria parasite, comprising sporozoites and the liver stages into which they develop, remains one of the least understood parts of the lifecycle, in part owing to the low numbers of parasites. Nonetheless, it is recognized as an important target for anti-malarial drugs and vaccines. Here we provide the first proteomic analysis of merosomes, which define the final phase of the liver stage and are responsible for initiating the blood stage of infection. We identify a total of 1879 parasite proteins, and a core set of 1188 proteins quantitatively detected in every biological replicate, providing an extensive picture of the protein repertoire of this stage. This unique dataset will allow us to explore key questions about the biology of merosomes and hepatic merozoites.\n\nHighlightsO_LIFirst proteome of the merosome stage of malaria parasites\nC_LIO_LIQuantitative detection of 1188 parasite proteins across 3 biological replicates\nC_LIO_LIComparison to blood stage proteomes identifies shared and unique proteins\nC_LIO_LIDiscovery of cleaved PEXEL motifs highlights liver stage protein export\nC_LI\n\nIn BriefThe merosome stage that links malaria liver and blood stage infection is poorly understood. Here we provide the first proteome of this life cycle stage using the Plasmodium berghei rodent malaria model.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=27 SRC=\"FIGDIR/small/580266_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (11K):\norg.highwire.dtl.DTLVardef@5bd8b1org.highwire.dtl.DTLVardef@1ef4fb9org.highwire.dtl.DTLVardef@5b3833org.highwire.dtl.DTLVardef@c69c73_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2019

Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world. Here we describe the first tranche of large-scale exome sequence data for 49,960 study participants, revealing approximately 4 million coding variants (of which ~98.4% have frequency < 1%). The data includes 231,631 predicted loss of function variants, a >10-fold increase compared to imputed sequence for the same participants. Nearly all genes (>97%) had [≥]1 predicted loss of function carrier, and most genes (>69%) had [≥]10 loss of function carriers. We illustrate the power of characterizing loss of function variation in this large population through association analyses across 1,741 phenotypes. In addition to replicating a range of established associations, we discover novel loss of function variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical significance in this population, finding that 2% of the population has a medically actionable variant. Additionally, we leverage the phenotypic data to characterize the relationship between rare BRCA1 and BRCA2 pathogenic variants and cancer risk. Exomes from the first 49,960 participants are now made accessible to the scientific community and highlight the promise offered by genomic sequencing in large-scale population-based studies.

genomics↗

bioRxiv2019

Identification of lncRNAs associated with early stage breast cancer and their prognostic implications

Breast cancer is a common malignancy among women with the highest incidence rate worldwide. Dysregulation of long non-coding RNAs occurring in the preliminary stages of breast carcinogenesis is poorly understood. In this study, RNA sequencing was done to identify long non-coding RNA expression profiles associated with early-stage breast cancer. RNA sequencing was done in 6 invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, 7 ductal carcinoma in situ (DCIS) tissues and 5 apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts ([~]58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was done in n=52 IDC and paired normal tissue by qRT-PCR for the identified targets (ADAMTS9-AS2, EPB41L4A-AS1, WDFY3-AS2, RP11-295M3.4, RP11-161M6.2, RP11-490M8.1, CTB-92J24.3 and FAM83H-AS)1. We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and overexpression of FAM83H-AS1 was associated with patient poor survival. We confirmed that the down-regulation of ADAMTS9-AS2 in breast cancer was due to promoter hypermethylation through in-vitro silencing experiments and pyrosequencing.

cancer biology↗

bioRxiv2019

Microarray analyses of liver and brain tissues after REM sleep deprivation in rats

Sleep is essential for the survival of most living beings. Numerous researchers have identified a series of genes that are thought to regulate "sleep-state" or the "deprived state". As sleep has significant effect on physiology, we believe that lack of sleep or particularly REM sleep for a prolonged period would have a profound impact on various body tissues. Therefore, using microarray method, we sought to determine which genes and processes are affected in the brain and liver of rats following 9 days of REM sleep deprivation. Our findings showed that REM sleep deprivation affected a total of 652 genes in the brain and 426 genes in the liver. Only 23 genes were affected commonly, 10 oppositely and 13 similarly across brain and liver tissue. Our results suggest that 9-day REM sleep deprivation differentially affects genes and processes in the brain and liver of rats. Highlights of the study[tpltrtarr] Gene expression profile of brain and liver tissues of rats was analyzed using microarray technique following 9 days of REM Sleep deprivation. [tpltrtarr]Many of the genes involved in essential physiological processes, such as protein synthesis and neuronal metabolism are affected differently in the brain and liver tissue of rats after 9-day REM sleep deprivation.

genomics↗

bioRxiv2018

Why do phylogenomic analyses of early animal evolution continue to disagree? Sites in different structural environments yield different answers

Phylogenomics has revolutionized the study of evolutionary relationships. However, genome-scale data have not been able to resolve all relationships in the tree of life. This could reflect the poor-fit of the models used to analyze heterogeneous datasets; that heterogeneity is likely to have many explanations. However, it seems reasonable to hypothesize that the different patterns of selection on proteins based on their structures might represent a source of heterogeneity. To test that hypothesis, we developed an efficient pipeline to divide phylogenomic datasets that comprise proteins into subsets based on secondary structure and relative solvent accessibility. We then tested whether amino acids in different structural environments had different signals for the deepest branches in the metazoan tree of life. Sites located in different structural environments did support distinct tree topologies. The most striking difference in phylogenetic signal reflected relative solvent accessibility; analyses of sites on the surface of proteins yielded a tree that placed ctenophores sister to all other animals whereas sites buried inside proteins yielded a tree with a sponge-ctenophore clade. These differences in phylogenetic signal were not ameliorated when we repeated our analyses using the site-heterogeneous CAT model, a mixture model that is often used for analyses of protein datasets. In fact, analyses using the CAT model actually resulted in rearrangements that are unlikely to represent evolutionary history. These results provide striking evidence that it will be necessary to achieve a better understanding the constraints due to protein structure to improve phylogenetic estimation.

evolutionary biology↗