Biology subjects

Pandit, A.

Publications and source records attributed to Pandit, A..

49 records · Page 3Linked to original sources

bioRxiv2019

Development of a novel preclinical glioblastoma mouse model and therapeutic impact of IRE1 inhibition

Glioblastoma multiforme (GBM) is the most severe primary brain cancer. Despite an aggressive treatment comprising surgical resection and radio/chemotherapy patients survival post diagnosis remains short. A limitation for success in finding novel improved therapeutic options for such dismal disease partly lies in the lack of a relevant animal model that accurately recapitulates patient disease and standard of care. In the present study, we have developed a novel immunocompetent GBM model that includes tumor surgery and a radio/chemotherapy regimen resembling the Stupp protocol and we have used this model to test the impact of the pharmacological inhibition of the endoplasmic reticulum (ER) stress sensor IRE1, on treatment efficacy.

cancer biology↗

bioRxiv2019

Nightmares share strong genetic risk with sleep and psychiatric disorders

Nightmares are vivid, extended and extremely dysphoric dreams that awaken the dreamer. Twin studies indicate that nightmare frequency has a heritability between 36 and 51% providing evidence for genetic factors underlying predisposition to nightmares. Furthermore, while cross-sectional epidemiological findings suggest that heavy alcohol usage, traumatic experiences and psychiatric diseases associate with nightmares, the causal relationships between these conditions and nightmares have remained unknown. To examine the biological mechanisms behind nightmares, we performed a genome-wide association study in 28,596 individuals from Finland and the United States. We identified individual genetic variants that predispose to nightmares near MYOF (rs701873, p=2.18e-8) and PTPRJ (rs11039471,p=3.7e-8), a gene previously associated with sleep duration. We found a strong genetic correlation between the frequency of nightmares and traits related to personality and psychiatric disorders; neuroticism (rg=0.59, p=8e-7), post-traumatic stress disorder (PTSD) (rg=0.58, p=0.004) as well as major depressive disorder (rg=0.68, p=7e-4), and sleep traits; and daytime sleepiness (rg=0.62, p=1e-6) and insomnia (rg=0.50, p=1.87e-5). Analysis of directionality using mendelian randomization showed a significant effect from feelings of fed-up (p=0.001), nervous (p=0.004) and miserableness (p=0.0045) to nightmares with no evidence of pleiotropy and no evidence of nightmares predisposing to psychiatric or psychological problems. Our findings suggest that nightmares are caused by unique genetic risk factors, and here we identify the first individual genetic associations. In addition, a substantial effect on nightmares is conveyed through underlying psychological and sleep problems, with psychological problems being causal for nightmares.

genetics↗

bioRxiv2019

CXCL4 links inflammation and fibrosis through transcriptional and epigenetic reprogramming of monocyte-derived cells

Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis development in systemic sclerosis, a prototypic inflammatory and fibrotic disease. Here, we integrated 65 paired longitudinal transcriptional and methylation profiles from monocyte-derived cells with/without CXCL4 exposure. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters the trajectory of monocyte differentiation, inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key transcriptional regulators including CIITA. CXCL4 exposed monocyte-derived cells directly trigger a fibrotic cascade by producing ECM molecules and inducing myofibroblast differentiation. Inhibition of CIITA mimicked CXCL4 in inducing a pro-inflammatory and pro-fibrotic phenotype, validating the relevance of the gene regulatory network. Our study unveils CXCL4 as a key secreted factor driving innate immune training and forming the long-sought link between inflammation and fibrosis.

bioinformatics↗

bioRxiv2019

Metabarcoding for parallel identification of species, sex and diet: an application to the conservation of globally-threatened Gyps vultures

An understanding of the factors affecting the diet composition of critically endangered Gyps vultures in the Indian subcontinent has important applications to the design of effective conservation strategies. After suffering a massive decline (~99%) in numbers caused by veterinary use of the nephrotoxic drug diclofenac, vultures now persist in very low numbers, mostly concentrated within or near National Parks. This spatial association might be attributed to the availability of wild ungulate carcasses free from toxic veterinary drugs. Hence, quantification of vulture diets and the factors affecting them is critical to test this hypothesis. Here, we describe and validate a robust \"field-to-benchtop-to-desktop\" metabarcoding workflow for assessing the species- and sex-specific diet of these obligate scavengers from non-invasively collected faecal samples. Seven metabarcodes targeting mitochondrial and nuclear genes were used to simultaneously determine the vulture species identity, sex and species consumed. The amplicons were sequenced using an Illumina Miseq platform. We included controls and three replicates per sample to establish a series of non-arbitrary thresholds to filter the sequence data and eliminate cross-contamination, PCR/sequencing errors and false positives. Using this strategy enabled identification of species and sex for all samples. Diet species-specific sequences could be identified with high taxonomic resolution for 93% of samples. Out of the seven metabarcodes, just four were sufficient to meet the objectives. From this preliminary analysis, domestic livestock seem to be the most frequently consumed diet item across samples from inside and outside protected habitats. Our method provides a rapid and reliable tool for describing large-scale variation in consumption of domestic versus wild species in the diet of these species, paving the way for a better understanding of the role protected areas play in persistence and recovery of the remaining Gyps vulture populations in the wild.

genetics↗

bioRxiv2019

Constitutive IRE1α signaling maintains glioblastoma cell differentiation

Endoplasmic Reticulum (ER) proteostasis control and the Unfolded Protein Response (UPRER) have been shown to contribute to tumor development and aggressiveness. As such, the UPRER sensor IRE1 (referred to as IRE1 hereafter) is a major regulator of glioblastoma (GBM) development and is an appealing therapeutic target. To document IRE1 suitability as an antineoplastic pharmacological target, we investigated how this protein contributed to GBM cell reprogramming, a property involved in treatment resistance and disease recurrence. Probing the IRE1 activity molecular signature on transcriptome datasets of human tumors, showed that high IRE1 activity correlated with low expression of the main GBM stemness transcription factors SOX2, SALL2, POU3F2 and OLIG2. Henceforth, this phenotype was pharmacologically and genetically recapitulated in immortalized and primary GBM cell lines as well as in mouse models. We demonstrated that constitutive activation of the IRE1/XBP1/miR148a signaling axis repressed the expression of SOX2 and led to maintenance of a differentiation phenotype in GBM cells. Our results describe a novel role for IRE1 signaling in maintaining differentiated tumor cell state and highlight opportunities of informed IRE1 modulation utility in GBM therapy.

cancer biology↗

bioRxiv2019

IRE1-UBE2D3 signaling controls the recruitment of myeloid cells to glioblastoma.

Tumor cells are exposed to intrinsic and environmental challenges that trigger endoplasmic reticulum (ER) homeostasis alteration, in turn leading to ER stress. To cope with this, tumor cells engage an adaptive signaling pathway, the unfolded protein response (UPR) thus promoting the acquisition of malignant features. As such, glioblastoma multiforme (GBM), the most aggressive primary brain tumors, exhibit constitutive UPR signals to sustain growth. Herein, we showed that signaling elicited by one of the UPR sensors, IRE1, promotes GBM tumor invasion, angiogenesis and infiltration by macrophages. Hence, high IRE1 activity in tumors predicts worse outcome. We further dissect IRE1-dependent mechanisms that shape the brain tumor immune microenvironment towards myeloid cells. We identify an IRE1-dependent signaling pathway that directly controls the expression/release of proinflammatory chemokines (CXCL2, IL6, IL8) leading to tumor cell-mediated chemoattraction of neutrophils and macrophages. This pathway requires XBP1 non-conventional mRNA splicing and XBP1s-dependent expression of the E2 ubiquitin enzyme UBE2D3. The latter contributes to the degradation of the NF{kappa}B inhibitor I{kappa}B, leading to the up-regulation of proinflammatory chemokines. Our work identifies a novel IRE1/UBE2D3 proinflammatory signaling axis instrumental to pro-tumoral immune regulation of GBM.

cancer biology↗

bioRxiv2018

The two active glutamates of the plant stress sensor PsbS contribute non-equivalently to its pH-activated molecular response mechanism

Plants need to protect themselves from excess light, which causes photo-oxidative damage and lowers the efficiency of photosynthesis. Photosystem II subunit S (PsbS) is a pH sensor protein that plays a crucial role in plant photoprotection by detecting thylakoid lumen acidification in excess light conditions via two lumen-faced glutamates. However, how PsbS is activated under low-pH conditions is unknown. To reveal the molecular response of PsbS to low pH, we performed an NMR and infrared spectroscopic analysis of Physcomitrella patens PsbS and of the E176Q mutant in which an active glutamate has been replaced. The PsbS response mechanism at low pH involves the concerted action of repositioning of a short amphipathic helix containing E176 facing the lumen and folding of the luminal loop fragment adjacent to E71 to a 310-helix, providing clear evidence of a conformational pH switch. We propose that this concerted mechanism is a shared motif of proteins of the light-harvesting family that may control thylakoid inter-protein interactions driving photoregulatory responses.

biophysics↗

bioRxiv2018

Time-resolved fluorescence analysis of LHCII in the presence of PsbS at neutral and low pH

In plant chloroplast membranes, non-photochemical quenching (NPQ) is activated as a response to a low luminal pH and controlled by the pH-sensing protein PsbS. It has been proposed that PsbS directly interacts with the light-harvesting complexes (LHCII) of Photosystem II, inducing quenching of LHCII Chl excitations, whilst others proposed that PsbS has an indirect role in controlling the organization of the membrane. In this study, we systematically test the influence of low pH and PsbS on the fluorescence lifetimes of membrane-embedded spinach LHCII. The proteoliposome preparations contain LHCII in mild quenched states, aimed to mimic fluorescence conditions of dark-adapted leaves. We find that under those conditions, acidification and the presence of PsbS do not have significant effect on the LHCII Chl fluorescence lifetimes. This supports a view in which the functional role of PsbS consists of re-organizing the thylakoid membrane under light stress, rather than creating direct quencher states. The dimeric form of PsbS appears to be destabilized in lipid membranes compared to detergent micelles, which might explain why the low-pH PsbS crystal structure is dimeric, while in vivo activation of PsbS has been correlated with its monomerization at low pH.\n\nHighlights O_LIPsbS does not affect LHCII Chl excited-state lifetimes\nC_LIO_LIPsbS dimers have lower stability in lipid membranes than in detergent micelles\nC_LIO_LILHCII proteoliposomes with protein-to-lipid molar ratios in the range 0.5.10-3 to 1.10-3 form suitable membrane models for mimicking dark-adapted fluorescence states\nC_LI

biophysics↗

bioRxiv2018

Cell-free soluble expression of the membrane protein PsbS

Photosystem II subunit S (PsbS) is a membrane protein that plays an exclusive role in non-photochemical quenching for photoprotection of plants under high-light conditions. The activation mechanism of PsbS and its pH-induced conformational changes are currently unknown. For structural investigation of PsbS, effective synthesis of PsbS with selective isotope or electron-spin labels or non-natural amino acids incorporated would be a great asset. This communication presents cell-free expression as a successful method for in vitro production of PsbS that would allow such incorporation. We have optimized the cell-free method to yield soluble PsbS of ~500 ng/{micro}l using a continuous-exchange method at 30{degrees}C, along with a successful purification and refolding of PsbS in n-Dodecyl {beta}-D-maltoside ({beta}-DM) detergent. We expect that the presented protocols are transferrable for in vitro expression of other membrane proteins of the Light-Harvesting Complex family.

molecular biology↗

bioRxiv2018

Conformational dynamics of a photosynthetic light-harvesting complex in native thylakoid membranes

Photosynthetic light-harvesting complexes of higher plants, moss and green algae can undergo dynamic conformational transitions, which have been correlated to their ability to adapt to fluctuations in the light environment. Herein, we demonstrate the application of solid-state NMR spectroscopy on native, heterogeneous thylakoid membranes of Chlamydomonas reinhardtii (Cr) and on Cr Light-Harvesting Complex II (LHCII) in thylakoid lipid bilayers to detect LHCII conformational dynamics in its native membrane environment. We show that membrane-reconstituted LHCII contains selective sites that undergo fast, large-amplitude motions, including the phytol tails of two chlorophylls. Protein plasticity is also observed in the N-terminal stromal loop and in protein fragments facing the lumen, involving sites that stabilize the xanthophyll-cycle carotenoid violaxanthin and the two luteins. The results report on the intrinsic flexibility of LHCII pigment-protein complexes in a membrane environment, revealing putative sites for conformational switching. In thylakoid membranes, fast dynamics of protein and pigment sites is significantly reduced, which suggests that in their native organelle membranes, LHCII complexes are locked in specific conformational states. STATEMENT OF SIGNIFICANCEPhotosynthetic Light-Harvesting Complexes undergo dynamic conformational transitions that regulate the capacity of the light-harvesting antenna. We demonstrate the application of solid-state (ss)NMR spectroscopy to investigate the structural dynamics of LHCII, the most abundant LHC complex of plants and algae, in native membranes. Selective dynamic protein and pigment residues are identified that are putative sites for a conformational switch.

biophysics↗

bioRxiv2017

Proper Conditional Analysis in the Presence of Missing Data Identified Novel Independently Associated Low Frequency Variants in Nicotine Dependence Genes

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values. In practice, genotype imputation is not always effective, e.g. when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Naive extensions of existing methods either replace missing summary statistics with 0 or discard studies with missing data. These approaches can bias genetic effect estimates and lead to seriously inflated type-I or II errors in conditional analysis, which is a critical tool for identifying independently associated variants.\n\nTo address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amount of missing values. Based on this estimator, we propose a score statistic we call PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to analyze the CHRNA5-CHRNB4-CHRNA3 locus in a large-scale meta-analysis for cigarettes-per-day. Using the new method, we identified three novel variants, independent of known association signals, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants is .46%, improving that of previously reported associations by 17%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.\n\nAUTHOR SUMMARYIt is of great interest to estimate the joint and conditional effects of multiple correlated variants from large scale meta-analysis, in order to fine map causal variants and understand the genetic architecture for complex traits. The contributed summary statistics from participating studies in a meta-analysis often contain missing values, as the imputation methods are not often effective, especially when the underlying genetic variant is rare or the participating studies use targeted genotyping array that is not suitable for imputation. Existing meta-analysis methods do not properly handle missing data, and can incorrectly estimate correlations between score statistics. As a result, they can produce highly biased estimates of joint effects and highly inflated type-I errors for conditional analysis, which will in turn result in overestimated phenotypic variance explained and incorrect identification of causal variants. We systematically evaluated this bias and proposed a novel partial correlation based score statistic. The new statistic has valid type-I errors for conditional analysis and much higher power than the existing methods, even when the contributed summary statistics in the meta-analysis contain a large fraction of missing values. We expect this method to be highly useful in the sequencing age for complex trait genetics.

genetics↗

bioRxiv2017

Association Analysis and Meta-Analysis of Multi-allelic Variants for Large Scale Sequence Data

MotivationThere is great interest to understand the impact of rare variants in human diseases using large sequence datasets. In deep sequences datasets of >10,000 samples, [~]10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results.\n\nResultsWe propose novel methods to encode multi-allelic sites, conduct single variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of [~]18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single variant association tests, and enhanced gene-level tests over existing approaches.\n\nAvailabilitySoftware packages implementing these methods are available at (https://github.com/zhanxw/rvtests http://genome.sph.umich.edu/wiki/RareMETAL).\n\nContactxiaowei.zhan@utsouthwestem.edu; dajiang.liu@psu.edu

bioinformatics↗

bioRxiv2017

Genetics of the Research Domain Criteria (RDoC): genome-wide association study of delay discounting

Delay discounting (DD), which is the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated SNP was rs6528024 (P = 2.40 x 10-8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype, and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition, and body weight.

genetics↗