Biology subjects

Mukherjee, S.

Publications and source records attributed to Mukherjee, S..

At least 235 records · Page 13Linked to original sources

bioRxiv2019

Azadirachta indica (A. Juss.) reduces circulating Dirofilaria immitis microfilariae in vivo

The present study enumerates the effectiveness of ethanolic leaf extract of A. indica against circulating microfilariae (mf) of D. immitis in vivo of Canis familiaris. An ethanolic extract was prepared from the leaves of A. indica (EEA) and treated on dogs infected with the filarial nematode Dirofilaria immitis, the causative agent of canine cardiopulmonary dirofilariasis. Before treatment, all the infected dogs were vigilantly supervised for any natural fluctuation of mf count. Two doses; 25 and 50 mg/kg body weight/twice a day; both for 15 days were selected for in vivo tests along with a control group which received an empty capsule during the study period. The highest reduction of circulating mf was counted on day 60, showing mf reduction of 77.9% and 86.7% respectively for the two doses. Thereafter mf density increased with a minor change and maintained reduction of 49.5% and 64.1% on day 180 respectively. Additionally, no appreciable side effects in the treated dogs were recorded as evident from serum toxicity parameter analyses. In conclusion, the ethanolic formulation of A. indica leaves possesses considerable effectiveness against D. immitis in vivo with no toxic modification in the host after exposure. Thus, EEA appears to be a good alternative remedy against heartworm infection in infected dogs.

zoology↗

bioRxiv2019

Transcriptomic Stratification of Late-Onset Alzheimer’s Cases Reveals Novel Genetic Modifiers of Disease Pathology

Late-Onset Alzheimers disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) analysis to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5x10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

systems biology↗

bioRxiv2019

Photo sensing and quorum sensing are integrated to control bacterial collective behaviors.

Pseudomonas aeruginosa transitions between the free-swimming state and the sessile biofilm mode during its pathogenic lifestyle. We show that quorum sensing represses P. aeruginosa biofilm formation and virulence by activating expression of genes encoding the KinB-AlgB two-component system. Phospho-AlgB represses biofilm and virulence genes, while KinB dephosphorylates, and thereby, inactivates AlgB. We discover that the photoreceptor BphP is the kinase that, in response to light, phosphorylates and activates AlgB. Indeed, exposing P. aeruginosa to light represses biofilm formation and virulence gene expression. To our knowledge, P. aeruginosa was not previously known to detect light. The KinB-AlgB-BphP module is present in all Pseudomonads, and we demonstrate that AlgB is the cognate response regulator for BphP in diverse bacterial phyla. We propose that KinB-AlgB-BphP constitutes a \"three-component\" system and AlgB is the node at which varied sensory information is integrated. This study sets the stage for light-mediated control of P. aeruginosa infectivity.

microbiology↗

bioRxiv2019

SINATRA: A Sub-Image Analysis Pipeline for Selecting Features that Differentiate Classes of 3D Shapes

The recent curation of large-scale databases with 3D surface scans of shapes has motivated the development of tools that better detect global patterns in morphological variation. Studies which focus on identifying differences between shapes have been limited to simple pairwise comparisons and rely on pre-specified landmarks (that are often known). We present SINATRA: the first statistical pipeline for analyzing collections of shapes without requiring any correspondences. Our novel algorithm takes in two classes of shapes and highlights the physical features that best describe the variation between them. We use a rigorous simulation framework to assess our approach. Lastly, as a case study, we use SINATRA to analyze mandibular molars from four different suborders of primates and demonstrate its ability recover known morphometric variation across phylogenies.

bioinformatics↗

bioRxiv2019

Molecular estimation of neurodegeneration pseudotime in older brains

The temporal molecular changes that lead to disease onset and progression in Alzheimers disease are still unknown. Here we develop a temporal model for these unobserved molecular changes with a manifold learning method applied to RNA-Seq data collected from human postmortem brain samples collected within the ROS/MAP and Mayo Clinic RNA-Seq studies. We define an ordering across samples based on their similarity in gene expression and use this ordering to estimate the molecular disease stage - or disease pseudotime - for each sample. Disease pseudotime is strongly concordant with the burden of tau (Braak score, P = 1.0x10-5), A{beta} (CERAD score, P = 1.8x10-5), and cognitive diagnosis (P = 3.5x10-7) of LOAD. Early stage disease pseudotime samples are enriched for controls and show changes in basic cellular functions. Late stage disease pseudotime samples are enriched for late stage AD cases and show changes in neuroinflammation and amyloid pathologic processes. We also identify a set of late stage pseudotime samples that are controls and show changes in genes enriched for protein trafficking, splicing, regulation of apoptosis, and prevention of amyloid cleavage pathways. In summary, we present a method for ordering patients along a trajectory of LOAD disease progression from brain transcriptomic data.

neuroscience↗

bioRxiv2019

Engineering an Enzyme for Direct Electrical Monitoring of Activity

Proteins have been shown to be electrically-conductive if tethered to an electrode by means of a specific binding agent, allowing single molecules to be wired into an electrical sensing circuit. This development opens the possibility of exploiting the remarkable chemical versatility of enzymes as sensors, detectors and sequencing devices. We have engineered contact points into a {Phi}29 polymerase by introducing biotinylatable peptide sequences. The modified enzyme was bound to electrodes functionalized with streptavidin. {Phi}29 connected by one biotinylated contact and a second non-specific contact showed rapid small fluctuations in current when activated. Signals were greatly enhanced with two specific contacts. Features in the distributions of DC conductance increased by a factor 2 or more over the open-to closed conformational transition of the polymerase. Polymerase activity is manifested by rapid (millisecond) large (25% of background) current fluctuations imposed on the DC conductance.

bioengineering↗

bioRxiv2019

Whole-Genome Association Analyses of Sleep-disordered Breathing Phenotypes in the NHLBI TOPMed Program

Sleep-disordered breathing (SDB) is a common disorder associated with significant morbidity. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program we report the first whole-genome sequence analysis of SDB. We identified 4 rare gene-based associations with SDB traits in 7,988 individuals of diverse ancestry and 4 replicated common variant associations with inclusion of additional samples (n=13,257). We identified a multi-ethnic set-based rare-variant association (p = 3.48 x 10-8) on chromosome X with ARMCX3. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Results highlighted associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis and HIF1A-mediated hypoxic response.

genetics↗

bioRxiv2019

Failure to detect synergy between variants in transferrin and hemochromatosis and Alzheimer’s disease in large cohort

Alzheimers disease (AD) is the most common cause of dementia and, despite decades of effort, there is no effective treatment. In the last decade, many association studies have identified genetic markers that are associated with AD status. Two of these studies suggest that an epistatic interaction between variants rs1049296 in the Transferrin (TF) gene and rs1800562 in the Homeostatic Iron Regulator (HFE) gene, commonly known as \"the hemochromatosis gene\", is in genetic association with AD. TF and HFE are involved in the transport and regulation of iron in the brain, and disrupting these processes exacerbates AD pathology through increased neurodegeneration and oxidative stress. However, by using a significantly larger dataset from the Alzheimers Disease Genetics Consortium (ADGC), we fail to detect an association between TF rs1049296 or HFE rs1800562 with AD risk (TF rs1049296 p=0.38 and HFE rs1800562 p=0.40). In addition, logistic regression with an interaction term and a Synergy Factor Analysis (SFA) both failed to detect epistasis between TF rs1049296 and HFE rs1800562 (SF=0.94; p=0.48) in AD cases. Each of these analyses had sufficient statistical power (Power>0.99), suggesting that previously-reported associations may be the result of more complex epistatic interactions, genetic heterogeneity, or were false-positive associations due to limited sample sizes.

genetics↗

bioRxiv2019

Novel strategy for treating neurotropic viral infections using hypolipidemic drug Atorvastatin

Chandipura virus (CHPV) and Japanese Encephalitis Virus (JEV) are known to infect neurons followed by their successful propagation. Increased incidences of central nervous system invasion by the abovementioned viruses have been reported in case of children and elderly thus culminating into severe neurological damage. Literature suggests induction of endoplasmic reticulum (ER)-stress related proteins upon CHPV and JEV infection which help promote viral reproduction. Since earlier studies underscore the pleotropic role of atorvastatin (AT) in neuroprotection against flaviviruses like Hepatitis C and dengue, it was hypothesized that AT might also act as a neuroprotective agent against RNA viruses like CHPV and JEV. AT-mediated antiviral activity was evaluated by assessing survivability of virus-infected mouse pups treated with the drug. Balb C mice were used for in vivo experiments. Neuro2A cell line was used as the model for in vitro experiments. Cells subjected to AT treatment were infected by CHPV and JEV followed by evaluation of ER stress-related and apoptosis-related proteins by immunoblotting technique and immunofluorescence microscopy. Interaction of host protein with viral genome was assessed by RNA-Co-IP. AT treatment exhibited significant anti-viral activity against CHPV and JEV infections via hnRNPC-dependent manner. Viral genome-hnRNPC interaction was found to be abrogated upon AT action. AT was also observed to reduce secretion of proinflammatory cytokines by the neurons in response to viral infection. Moreover, AT treatment was also demonstrated to reduce neuronal death by abrogating virus-induced miR-21 upregulation in hnRNPC-dependent fashion. This study thus suggests probable candidature of AT as antiviral against CHPV and JEV infections.

microbiology↗

bioRxiv2019

Structural state recognition facilitates tip tracking of EB1 at growing microtubule ends in cells

The microtubule binding protein EB1 specifically targets the growing ends of microtubules in cells, where EB1 facilitates the interactions of cellular proteins with microtubule plus-ends. Microtubule end targeting of EB1 has been attributed to high affinity binding of EB1 to GTP-tubulin that is present at growing microtubule ends. However, our 3D single-molecule diffusion simulations predicted a [~]6000% increase in EB1 arrivals to open, tapered microtubule tip structures relative to closed lattice conformations. Using quantitative fluorescence, single-molecule, and electron microscopy experiments, we found that the binding of EB1 onto opened, structurally disrupted microtubules was dramatically increased relative to closed, intact microtubules, regardless of hydrolysis state. Correspondingly, in cells, the conversion of growing microtubule ends from a tapered into a blunt configuration resulted in reduced EB1 targeting. Together, our results suggest that microtubule structural recognition, based on a fundamental diffusion-limited binding model, facilitates the tip tracking of EB1 at growing microtubule ends.

cell biology↗

bioRxiv2019

Genomic Analysis of Emerging Florfenicol-Resistant Campylobacter coli Isolated from the Intestinal Cecal Contents of Cattle in the United States

ObjectiveGenomic analyses were performed on florfenicol resistant (FFNR) Campylobacter coli (C. coli) isolated from cattle and the cfr(C) gene-associated multi-drug resistance (MDR) plasmid was characterized.\n\nMethodsSixteen FFNR C. coli isolates recovered between 2013-2018 from beef cattle were sequenced using MiSeq. Genomes and plasmids were closed for three of the isolates using the PacBio(R) system. Single nucleotide polymorphisms (SNPs) across the genome and the structures of MDR plasmids were investigated. Conjugation experiments were performed to determine the transferability of cfr(C) associated MDR plasmids. The spectrum of resistance encoded by the cfr(C) gene was further investigated by agar dilution antimicrobial susceptibility testing.\n\nResultsAll 16 FFNR isolates were MDR and exhibited co-resistance to ciprofloxacin, nalidixic acid, clindamycin and tetracycline. All isolates shared the same resistance genotype, carrying aph(3)-III, hph, {triangleup}aadE (truncated), blaOXA-61, cfr(C), and tet(O) genes plus a mutation of GyrA T86I. The cfr(C), aph(3)-III, hph {triangleup}aadE, and tet(O) genes were co-located on transferable MDR plasmids with size 48-50 kb. These plasmids showed high sequence homology with the pTet plasmid, and carried several Campylobacter virulence genes, including virB2, virB4, virB5, VirB6, virB7, virB8, virb9, virB10, virB11 and virD4. The cfr(C) gene conferred resistance to florfenicol (8-32 {micro}g/ml), clindamycin (512-1,024 {micro}g/ml), linezolid (128-512 {micro}g/ml), and tiamulin (1,024 {micro}g/ml). Phylogenetic analysis showed SNP differences ranging from 11-2,248 among the 16 isolates.\n\nConclusionsThe results showed that the cfr(C) gene located in the conjugative pTet MDR/virulence plasmid is present in diverse strains, where it confers high levels of resistance to several antimicrobials, including linezolid, a critical drug for treating Gram positive bacterial infections in humans. This study highlights the power of genomic antimicrobial resistance surveillance to uncover the intricacies of transmissible co-resistance and provides information that is needed for accurate risk assessment and mitigation strategies.

microbiology↗

bioRxiv2019

Measuring and Mitigating PCR Bias in Microbiome Data

PCR amplification plays a central role in the measurement of mixed microbial communities via high-throughput sequencing. Yet PCR is also known to be a common source of bias in microbiome data. Here we present a paired modeling and experimental approach to characterize and mitigate PCR bias in microbiome studies. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR bias under real-world conditions. Our results suggest that PCR can bias estimates of microbial relative abundances by a factor of 2-4 but that this bias can be mitigated using simple Bayesian multinomial logistic-normal linear models.\n\nAuthor summaryHigh-throughput sequencing is often used to profile host-associated microbial communities. Many processing steps are required to transform a community of bacteria into a pool of DNA suitable for sequencing. One important step is amplification where, to create enough DNA for sequencing, DNA from many different bacteria are repeatedly copied using a technique called Polymerase Chain Reaction (PCR). However, PCR is known to introduce bias as DNA from some bacteria are more efficiently copied than others. Here we introduce an experimental procedure that allows this bias to be measured and computational techniques that allow this bias to be mitigated in sequencing data.

genomics↗

bioRxiv2019

Identification and classification of hubs in miRNA target gene networks in human neural stem/progenitor cells following Japanese encephalitis virus infection

Micro RNA dysregulation is observed in many viral diseases. RNA viruses modulate host miRNA machinery for their own benefit. JEV, a neurotropic RNA virus has been reported to manipulate several miRNAs in neuron or microglia. However, no report indicates a complete sketch of the miRNA profile of NSPCs contributing to viral persistence; hence being focused in our current study. We performed a miRNA array of 84 miRNAs in human neuronal progenitor cell line and primary neural precursor cells isolated from aborted foetus. Several fold down-regulation of hsa-miR-9-5p, hsa-miR-22-3p, hsa-miR-124-3p and hsa-miR-132-3p were found in both of the cells. Subsequently, we screened for the target genes of these miRNAs and looked for the important biological pathways the genes significantly regulate. Then we sorted out the target genes which are involved in two or more than two pathways. We constructed a protein-protein interaction (PPI) network of the miRNA target genes based on their interaction patterns. A binary adjacency matrix for each gene network was prepared. Different modules or communities were identified in those networks using community detection algorithms. Mathematically, we identified the hub genes by analyzing their degree centrality and participation co-efficient in the network. The hub genes were classified either as provincial (P<0.4) or connector hubs (P>0.4). We validated the expression of hub genes in both cell line and primary cells through qRT-PCR post JEV infection and respective miR-mimic transfection. Taken together, our findings highlight the importance of specific target gene networks of miRNAs affected by JEV infection in NSPCs.\n\nImportanceJEV damages the neural stem/progenitor cell population of mammalian brain. However, JEV induced alteration in miRNA expression pattern of the cell population remains an open question, hence warrants our present study. In this study, we specifically address the down-regulation of four miRNAs and we prepared a protein-protein interaction network of miRNA target genes. We identified two types of hub genes in the PPI network namely connector hubs and provincial hubs. These two types of miRNA target hub genes critically influence the participation strength in the networks and thereby significantly influence up and down regulation in several key biological pathways. Computational analysis of the PPI networks identifies key protein interactions and hubs in those modules which opens up the possibility of precise identification and classification of host factors for viral infection in NSPCs and how RNA viruses modulate host miRNA machinery for their own benefit post JEV infection to the cells.

microbiology↗

bioRxiv2019

Transient non-integrative nuclear reprogramming promotes multifaceted reversal of aging in human cells

Aging is characterized by a gradual loss of function occurring at the molecular, cellular, tissue and organismal levels1-3. At the chromatin level, aging is associated with the progressive accumulation of epigenetic errors that eventually lead to aberrant gene regulation, stem cell exhaustion, senescence, and deregulated cell/tissue homeostasis3. The technology of nuclear reprogramming to pluripotency, through over-expression of a small number of transcription factors, can revert both the age and the identity of any cell to that of an embryonic cell by driving epigenetic reprogramming2,4,5. Recent evidence has shown that transient transgenic reprogramming can ameliorate age-associated hallmarks and extend lifespan in progeroid mice6. However, it is unknown how this form of epigenetic rejuvenation would apply to physiologically aged cells and, importantly, how it might translate to human cells. Here we show that transient reprogramming, mediated by transient expression of mRNAs, promotes a rapid reversal of both cellular aging and of epigenetic clock in human fibroblasts and endothelial cells, reduces the inflammatory profile in human chondrocytes, and restores youthful regenerative response to aged, human muscle stem cells, in each case without abolishing cellular identity. Our method, that we named Epigenetic Reprogramming of Aging (ERA), paves the way to a novel, potentially translatable strategy for ex vivo cell rejuvenation treatment. In addition, ERA holds promise for in vivo tissue rejuvenation therapies to reverse the physiological manifestations of aging and the risk for the development of age-related diseases.

cell biology↗

bioRxiv2019

Cortical tracking of speech reveals top-down reconstructive processes

Cortical entrainment to the (quasi-) rhythmic components of speech seems to play an important role in speech comprehension. It has been suggested that neural entrainment may reflect top-down temporal predictions of sensory signals. Key properties of a predictive model are its anticipatory nature and its ability to reconstruct missing information. Here we put both these two properties to experimental test. We acoustically presented sentences and measured cortical entrainment to both acoustic speech envelope and lips kinematics acquired from the speaker but not visible to the participants. We then analyzed speech-brain and lips-brain coherence at multiple negative and positive lags. Besides the well-known cortical entrainment to the acoustic speech envelope, we found significant entrainment in the delta range to the (latent) lips kinematics. Most interestingly, the two entrainment phenomena were temporally dissociated. While entrainment to the acoustic speech peaked around +0.3 s lag (i.e., when EEG followed speech by 0.3 s), entrainment to the lips was significantly anticipated and peaked around 0-0.1 s lag (i.e., when EEG was virtually synchronous to the putative lips movement). Our results demonstrate that neural entrainment during speech listening involves the anticipatory reconstruction of missing information related to lips movement production, indicating its fundamentally predictive nature and thus supporting analysis by synthesis models.

neuroscience↗

bioRxiv2019

Identifying and ranking potential driver genes of Alzheimer's Disease using multi-view evidence aggregation

MotivationLate onset Alzheimers disease (LOAD) is currently a disease with no known effective treatment options. To address this, there have been a recent surge in the generation of multi-modality data (Hodes and Buckholtz, 2016; Mueller et al., 2005) to understand the biology of the disease and potential drivers that causally regulate it. However, most analytic studies using these data-sets focus on uni-modal analysis of the data. Here we propose a data-driven approach to integrate multiple data types and analytic outcomes to aggregate evidences to support the hypothesis that a gene is a genetic driver of the disease. The main algorithmic contributions of our paper are: i) A general machine learning framework to learn the key characteristics of a few known driver genes from multiple feature-sets and identifying other potential driver genes which have similar feature representations, and ii) A flexible ranking scheme with the ability to integrate external validation in the form of Genome Wide Association Study (GWAS) summary statistics. While we currently focus on demonstrating the effectiveness of the approach using different analytic outcomes from RNA-Seq studies, this method is easily generalizable to other data modalities and analysis types. ResultsWe demonstrate the utility of our machine learning algorithm on two benchmark multi-view datasets by significantly outperforming the baseline approaches in predicting missing labels. We then use the algorithm to predict and rank potential drivers of Alzheimers. We show that our ranked genes show a significant enrichment for SNPs associated with Alzheimers, and are enriched in pathways that have been previously associated with the disease. AvailabilitySource code and link to all feature sets is availabile at https://github.com/Sage-Bionetworks/EvidenceAggregatedDriverRanking. Contactben.logsdon@sagebionetworks.org

bioinformatics↗

bioRxiv2019

Identification of potential new vaccine candidates in Salmonella typhi using reverse vaccinology and subtractive genomics-based approach

Salmonella enterica serovar typhi is the causative agent of typhoid fever in human. The available vaccine lacks the effectiveness and further overuse of the antibiotics throughout the past decades lead to the emergence of antibiotic-resistant strains. To reduce the spread of antibiotic resistance, it is essential to develop new vaccines. In this study using an extensive bioinformatic analysis based on reverse vaccinology and subtractive genomics-based approach, we searched the genome of S typhi. We found that two outermost membrane proteins LptD and LptE, which are responsible for the final transport of the LPS across the membrane having most of the essential signature for being vaccine target. Both of these proteins are found highly conserved and possess shared surface epitopes among several species of Salmonella pathogens. This indicates that these two proteins could be the potential target for vaccine development, which could be effective for a broad range of Salmonella pathogens.

bioinformatics↗

bioRxiv2019

Meta-analysis of the human brain transcriptome identifies heterogeneity across human AD coexpression modules robust to sample collection and methodological approach

Alzheimers disease (AD) is a complex and heterogenous brain disease that affects multiple inter-related biological processes. This complexity contributes, in part, to existing difficulties in the identification of successful disease-modifying therapeutic strategies. To address this, systems approaches are being used to characterize AD-related disruption in molecular state. To evaluate the consistency across these molecular models, a consensus atlas of the human brain transcriptome was developed through coexpression meta-analysis across the AMP-AD consortium. Consensus analysis was performed across five coexpression methods used to analyze RNA-seq data collected from 2114 samples across 7 brain regions and 3 research studies. From this analysis, five consensus clusters were identified that described the major sources of AD-related alterations in transcriptional state that were consistent across studies, methods, and samples. AD genetic associations, previously studied AD-related biological processes, and AD targets under active investigation were enriched in only three of these five clusters. The remaining two clusters demonstrated strong heterogeneity between males and females in AD-related expression that was consistently observed across studies. AD transcriptional modules identified by systems analysis of individual AMP-AD teams were all represented in one of these five consensus clusters except ROS/MAP-identified Module 109, which was specific for genes that showed the strongest association with changes in AD-related gene expression across consensus clusters. The other two AMP-AD transcriptional analyses reported modules that were enriched in one of the two sex-specific Consensus Clusters. The fifth cluster has not been previously identified and was enriched for genes related to proteostasis. This study provides an atlas to map across biological inquiries of AD with the goal of supporting an expansion in AD target discovery efforts.

systems biology↗