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Pandey, U.

Publications and source records attributed to Pandey, U..

9 recordsLinked to original sources

Structural Determinants of the Energetic Barrier of Phospholipid Flip-Flop

Spontaneous phospholipid flip-flop sets the background against which flippases, floppases, and scramblases create and dissipate membrane asymmetry. How the associated free-energy barrier depends on lipid chemistry and on the surrounding membrane remains unclear, because experiments are few and contradictory and previous simulations covered only a small part of the lipidome. Here, we calculate Martini 3 flip-flop free-energy barriers for over 700 membrane--lipid combinations, the largest such dataset to our knowledge. A systematic single component bilayer panel of five headgroups, three linkages, and 35 tail families is complemented by mixed bilayers, from binary mixtures to organelle-inspired compositions, that place the same lipid in different membranes and thus separate the effects of lipid chemistry and the membrane environment. In single component bilayers, the barrier rises with tighter tail packing and depends strongly on headgroup and tail unsaturation but only weakly on linkage. Moving a lipid into a mixed bilayer shifts its barrier as much as most headgroup substitutions do, and the shift follows the change in local tail order. Within a shared membrane, headgroup differences are mostly smaller than between single component bilayers, so part of a headgroup effect arises from the membrane that the lipid forms. A Bayesian model combining chemical descriptors with local membrane structure predicts barriers for withheld lipid families and membranes with cross-validated errors of 2.8 and 3.8 kJ/mol. The calculated trends agree qualitatively with native-lipid vesicle experiments, although Martini 3 underestimates the barrier differences between lipids, gives lower barriers than atomistic models, and overstates the effect of cholesterol.

biophysics↗

Characterization of a Novel Transmembrane Activating STING Agonist using Genetically Humanized Mice

STING is a pattern recognition receptor that activates type I interferon and proinflammatory responses in addition to unrelated molecular processes following exposure of DNA to the cytosol. Its pharmacologic stimulation enhances vaccine potency and generates effective antitumor responses but clinical trials evaluating STING agonists have not led to approval for human use. STING activation can occur through ligand engagement of either cytosolic or transmembrane protein domains, processes to which distinct cellular phenotypes are attributed. However, the only transmembrane STING agonist identified is human selective and in vivo testing in conventional models is not feasible. Here we describe synthesis of novel STING agonists efficacious against allelic variants of the protein. We also describe genetically humanized STING mice and demonstrate their suitability as a model to evaluate in vivo responses following exogenous administration of human-selective agonists. Experiments demonstrate that the lead molecule (termed INI3069) functions through binding to the STING transmembrane region and its comparison with conventional agonists reveals significant differences in molecular and immune effects. INI3069 can also enhance antibody responses to co-administered antigens and antitumor responses. This work both represents the first in vivo examination of the effects of transmembrane STING agonism and demonstrates efficacy of a potential novel vaccine adjuvant and oncological therapeutic.

immunology↗

DeePNAP: A deep learning method to predict protein-nucleic acids binding affinity from sequence

Predicting the protein-nucleic acid (PNA) binding affinity solely from their sequences is of paramount importance for the experimental design and analysis of PNA interactions (PNAIs). A large number of currently developed models for binding affinity prediction are limited to specific PNAIs, while also relying on both sequence and structural information of the PNA complexes for both train/test and also as inputs. As PNA complex structures available are scarce, this significantly limits the diversity and generalizability due to a small training dataset. Additionally, a majority of the tools predict a single parameter such as binding affinity or free energy changes upon mutations, rendering a model less versatile for usage. Hence, we propose DeePNAP, a machine learning-based model trained on a vast and heterogeneous dataset with 14,401 entries (from both eukaryotes and prokaryotes) of ProNAB database, consisting of wild-type and mutant PNA complex binding parameters. Our model precisely predicts the binding affinity and free energy changes due to the mutation(s) of PNAIs exclusively from the sequences. While other similar tools extract features from both sequence and structure information, DeePNAP employs sequence-based features to yield high correlation coefficients between the predicted and experimental values with low root mean squared errors for PNA complexes in predicting the KD and {Delta}{Delta}G implying the generalizability of DeePNAP. Additionally, we have also developed a web interface hosting DeePNAP that can serve as a powerful tool to rapidly predict binding affinities for a myriad of PNAIs with high precision toward developing a deeper understanding of their implications in various biological systems. Web interface: http://14.139.174.41:8080/

biophysics↗

Deep Whole-Genome Resequencing of Marek's Disease Virus Strains Reveals Intrastrain Variation

Current strategies to understand the molecular basis of Mareks disease virus (MDV) virulence primarily consist of cataloguing divergent nucleotides between strains with different phenotypes. However, each MDV strain is typically represented by a single consensus genome despite the confirmed existence of mixed viral populations. To assess the reliability of single-consensus interstrain genomic comparisons, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform 3-way comparisons between consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). In contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Phylogenomic analyses showed all three Md5 consensus genomes clustered closely together, while also showing that CVI988GenBank.BAC diverged from CVI988Pirbright.lab and CVI988USDA.PA.field. Comparison of CVI988 consensus genomes revealed 19 SNPs in the unique regions of CVI988GenBank.BAC that were not present in either CVI988Pirbright.lab or CVI988USDA.PA.field. Finally, we evaluated the genomic heterogeneity of CVI988 and Md5 populations by identifying positions with >2% read support for alternative alleles in two ultra-deeply sequenced samples. We were able to confirm that both populations of CVI988 and Md5 were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. We did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988GenBank.BAC. Taken together, our findings confirm that consensus genomes of the same strain of MDV can vary and suggest that multiple consensus genomes per strain are needed in order to maximize the accuracy of interstrain genomic comparisons.

microbiology↗

Children's Hospital Los Angeles COVID-19 Analysis Research Database (CARD) - A Resource for Rapid SARS-CoV-2 Genome Identification Using Interactive Online Phylogenetic Tools

Effective response to the Coronavirus Disease 2019 (COVID-19) pandemic requires genomic resources and bioinformatics tools for genomic epidemiology and surveillance studies that involve characterizing full-length viral genomes, identifying origins of infections, determining the relatedness of viral infections, performing phylogenetic analyses, and monitoring the continuous evolution of the SARS-CoV-2 viral genomes. The Childrens Hospital, Los Angeles (CHLA) COVID-19 Analysis Research Database (CARD) (https://covid19.cpmbiodev.net/) is a comprehensive genomic resource that provides access to full-length SARS-CoV-2 viral genomes and associated meta-data for over 30,000 (as of May 20, 2020) isolates collected from global sequencing repositories and the sequencing performed at the Center for Personalized Medicine (CPM) at CHLA. Reference phylogenetic trees of global and USA viral isolates were constructed and are periodically updated using selected high quality SARS-CoV-2 genome sequences. These provide the baseline and analytical context for identifying the origin of a viral infection, as well as the relatedness of SARS-CoV-2 genomes of interest. A web-based and interactive Phylogenetic Tree Browser supports flexible tree manipulation and advanced analysis based on keyword search while highlighting time series animation, as well as subtree export for graphical representation or offline exploration. A Virus Genome Tracker accepts complete or partial SARS-CoV-2 genome sequence, compares it against all available sequences in the database (>30,000 at time of writing), detects and annotates the variants, and places the new viral isolate within the global or USA phylogenetic contexts based upon variant profiles and haplotype comparisons, in a few seconds. The generated analysis can potentially aid in genomic surveillance to trace the transmission of any new infection. Using CHLA CARD, we demonstrate the identification of a candidate outbreak point where 13 of 31 CHLA internal isolates may have originated. We also discovered multiple indels of unknown clinical significance in the orf3a gene, and revealed a number of USA-specific variants and haplotypes.

genomics↗

Comparative metagenomic analysis following treatment with vancomycin in C57BL/6 and BALB/c mice to elucidate host immunity and behavior

The gut is the largest reservoir of the resident microbiota. The microbiota can affect the host behavior and immunity. While the consequence of treatment with antibiotics on the gut microbiota can be destructive but can be utilized as a tool to understand the host immunity and behavior. The magnitude of perturbation and time needed for the restoration of gut microbiota can depend on the immune bias of the host. In the current study, we therefore, observed the perturbation and restoration kinetics of gut microbiota following treatment with vancomycin and its effect on the host physiology in both Th1-(C57BL/6) and Th2-(BALB/c) biased mice. A comparative metagenomic analysis revealed that the treatment with vancomycin caused a significant decrease in the abundance of Firmicutes and Bacteroidetes phyla and an initial increase in Proteobacteria. Increase in Proteobacteria decreased with continued treatment with vancomycin to result into a significant rise in Verrucomicrobia phylum. We established the patterns of gut microbiota alteration and its effect on a) the behavior of mice, b) expression of key brain molecules and b) immunity related genes. We followed the gut microbiome restoration for a period of two months following withdrawal of treatment with vancomycin. Maximum restoration (>70%) of gut microbiota happened by the 15th day of withdrawal. BALB/c mice showed a more efficient restoration of gut microbiota compared to C57BL/6 mice. The results, in general, revealed that along with the restoration of major gut microbes, important physiological and behavioral changes of both mice strains returned to the normal level.

immunology↗

Small molecules for modulating protein driven liquid-liquid phase separation in treating neurodegenerative disease

Neurodegenerave diseases such as amyotrophic lateral sclerosis (ALS) are oten associated with mutaons in proteins that are associated with stress granules. Stress granules are condensates formed by liquid-liquid phase separaon which, when aberrant, can lead to altered condensaon behaviours and disease phenotypes. Here, we identified lipoamide, a small molecule which specifically prevents cytoplasmic condensaon of stress granule proteins. Thermal proteome profiling showed that lipoamide preferentially stabilises intrinsically disordered domain-containing proteins. These include SRSF1 and SFPQ, stress granule proteins necessary for lipoamide activity. The redox state of SFPQ correlates with its condensate-dissolving behaviour, in concordance with the importance of the dithiolane ring for lipoamide activity. In animals, lipoamide ameliorates aging-associated aggregaon of a stress granule reporter, improves neuronal morphology, and recovers motor defects caused by expression of ALS-associated FUS and TDP-43 mutants. In conclusion, lipoamide is a well-tolerated small molecule modulator of stress granule condensaon and dissection of its molecular mechanism identified a cellular pathway for redox regulaon of stress granule formaon.

cell biology↗

Oral tenofovir disoproxil fumarate/emtricitabine for HIV pre-exposure prophylaxis increases expression of type I/III interferon-stimulated factors in the gastrointestinal tract but not in the blood

Tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) are used for HIV treatment and prevention. Previously, we found that topical rectal tenofovir gel caused immunological changes in the mucosa. Here we assessed the effect of oral TDF/FTC in three HIV pre-exposure prophylaxis trials, two with gastrointestinal and one with cervicovaginal biopsies. TDF/FTC induced type I/III interferon-related (IFN I/III) genes in the gastrointestinal tract, but not blood, with strong correlations between the two independent rectal biopsy groups (Spearman r=0.91) and between the rectum and duodenum (r=0.81). Gene set testing also indicated stimulation of type I/III pathways in the ectocervix, as well as of cellular proliferation in the duodenum. mRNA sequencing, digital droplet PCR, proteomics, and immunofluorescence staining confirmed IFN I/III pathway stimulation in the gastrointestinal tract. Thus, oral TDF/FTC stimulates an IFN-I/III signature throughout the gut, which could increase antiviral efficacy but also cause chronic immune activation in HIV prevention and treatment settings.

immunology↗

Genotypic and phenotypic diversity within the neonatal HSV-2 population

More than 14,000 neonates are infected with herpes simplex virus (HSV) annually. Approximately half display manifestations limited to the skin, eyes, or mouth (SEM disease). The rest develop invasive infections that spread to the central nervous system (CNS disease or encephalitis) or systemically (disseminated disease). Invasive HSV disease is associated with significant morbidity and mortality, but viral and host factors that predispose neonates to these forms are unknown. To define viral diversity within the infected neonatal population, we evaluated ten HSV-2 isolates from newborns with a range of clinical presentations. To assess viral fitness independent of host immune factors, we measured viral growth characteristics in cultured cells and found diverse in vitro phenotypes. Isolates from neonates with CNS disease were associated with larger plaque size and enhanced spread, with isolates from cerebrospinal fluid (CSF) exhibiting the most robust growth. We sequenced complete viral genomes of all ten neonatal viruses, providing new insights into HSV-2 genomic diversity in this clinical setting. We found extensive inter-host and intra-host genomic diversity throughout the viral genome, including amino acid differences in more than 90% of the viral proteome. The genes encoding glycoprotein G (gG, US4), gI (US7), gK (UL53), and viral proteins UL8, UL20, UL24, and US2 contained variants that were found in association with CNS isolates. Many of these viral proteins are known to contribute to cell spread and neurovirulence in mouse models of CNS disease. This study represents the first application of comparative pathogen genomics to neonatal HSV disease. ImportanceHerpes simplex virus (HSV) causes invasive disease in half of infected neonates, resulting in significant mortality and permanent cognitive morbidity. The factors that contribute to invasive disease are not understood. This study reveals diversity among HSV isolates from infected neonates, and makes the first associations between viral genetic variations and clinical disease manifestations. We found that viruses isolated from newborns with encephalitis show enhanced spread in culture. These viruses contain protein-coding variations not found in viruses causing non-invasive disease. Many of these variations are found in proteins known to impact neurovirulence and viral spread between cells. This work advances our understanding of HSV diversity in the neonatal population and how it may impact disease outcome.

microbiology↗