Biology subjects

Sarkar, S.

Publications and source records attributed to Sarkar, S..

5 recordsLinked to original sources

bioRxiv2018

Transgenerational effect of adult density through paternal effect in Drosophila melanogaster

O_LINotwithstanding recent evidences, paternal environment is thought to be a potential but unlikely source of fitness variation that can affect trait evolution. Here we studied intergenerational effects of males exposure to varying adult density in Drosophila melanogaster laboratory populations.\nC_LIO_LIWe held sires at normal (N), medium (M) and high (H) adult densities for two days before allowing them to mate with virgin females. This treatment did not introduce selection through differential mortality. Further, we randomly paired males and females and allowed a single round of mating between the sires and the dams. We then collected eggs from the dams and measured the egg size. Finally, we investigated the effect of the paternal treatment on juvenile and adult (male) fitness components.\nC_LIO_LIWe found a significant treatment effect on juvenile competitive ability where the progeny sired by the H-males had higher competitive ability. Since we did not find the treatment to affect egg size, this effect is unlikely to be mediated through variation in female provisioning.\nC_LIO_LIMale fitness components were also found to have a significant treatment effect: M-sons had lower dry weight at eclosion, higher mating latency and lower competitive mating success.\nC_LIO_LIWhile being the first study to show both adaptive and non-adaptive effect of the paternal density in Drosophila, our results highlight the importance of considering paternal environment as important source of fitness variation.\nC_LI

evolutionary biology↗

bioRxiv2018

Integrating genotype and weather variables for soybean yield prediction using deep learning

Realized performance of complex traits is dependent on both genetic and environmental factors, which can be difficult to dissect due to the requirement for multiple replications of many genotypes in diverse environmental conditions. To mediate these problems, we present a machine learning framework in soybean (Glycine max (L.) Merr.) to analyze historical performance records from Uniform Soybean Tests (UST) in North America, with an aim to dissect and predict genotype response in multiple envrionments leveraging pedigree and genomic relatedness measures along with weekly weather parameters. The ML framework of Long Short Term Memory - Recurrent Neural Networks works by isolating key weather events and genetic interactions which affect yield, seed oil, seed protein and maturity enabling prediction of genotypic responses in unseen environments. This approach presents an exciting avenue for genotype x environment studies and enables prediction based systems. Our approaches can be applied in plant breeding programs with multi-environment and multi-genotype data, to identify superior genotypes through selection for commercial release as well as for determining ideal locations for efficient performance testing.

bioinformatics↗

bioRxiv2018

Dynamic PET of Human Liver Inflammation: Impact of Kinetic Modeling with Optimization-Derived Dual-Blood Input Function

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. This paper aims to identify the optimal dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen patients with nonalcoholic fatty liver disease were included. Each patient underwent 1-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and new model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation score. Results showed that the optimization-derived DBIF model improved liver time activity curve fitting and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for dynamic liver FDG-PET kinetic analysis in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation.

physiology↗

bioRxiv2017

Induction of autophagy by trehalose limits opportunistic mycobacterial infections in HIV-infected macrophages

Opportunistic bacterial infections amongst HIV-infected individuals pose serious health challenge. While immediate control of bacterial pathogens is typically attributed to innate defense mechanisms, whether HIV-mediated modulation of innate mechanisms like autophagy promote opportunistic infections, remains obscure. Using U1.1 and U937 macrophages, we show, HIV activation or infection inhibits autophagy and helps survival of pathogenic Mycobacterium tuberculosis and non-pathogenic non-tuberculous mycobacterial strains (NTMs) like Mycobacterium avium complex and Mycobacterium fortuitum. HIV achieves this by blocking xenophagy flux, which could be reversed by the autophagy inducer trehalose that kills intracellular Mtb and NTMs. We found trehalose acts as a PI (3,5) P2 agonist and activates TRPML1 to induce autophagy. Remarkably, trehalose treatment significantly reduced p24 levels in PBMCs infected with clinical HIV strains and in PBMCs derived from treatment-naive HIV patients. Taken together, our study highlights the immense potential of autophagy modulators in the therapeutic intervention of HIV and associated opportunistic infection.

immunology↗

bioRxiv2017

Development of a novel Francisella tularensis Live Vaccine Strain expressing ovalbumin provides insight into Francisella tularensis-specific CD8+ T cell responses.

Progress towards a safe and effective vaccine for the prevention of tularemia has been hindered by a lack of knowledge regarding the correlates of protective adaptive immunity and a lack of tools to generate this knowledge. CD8+ T cells are essential for protective immunity against virulent strains of Francisella tularensis, but to-date, it has not been possible to study these cells in a pathogen-specific manner. Here, we report the development of a tool for expression of the model antigen ovalbumin (OVA) in F. tularensis, which allows for the study of CD8+ T cell responses to the bacterium. We demonstrate that in response to intranasal infection with the F. tularensis Live Vaccine Strain, pathogen-specific CD8+ T cells expand after the first week and produce IFN-{gamma} but not IL-17. Effector and central memory subsets develop with disparate kinetics in the lungs, draining lymph node and spleen. Notably, F. tularensis-specific cells are poorly retained in the lungs after clearance of infection. We also show that intranasal vaccination leads to more pathogen-specific CD8+ T cells in the lung-draining lymph node compared to scarification vaccination, but that an intranasal booster overcomes this difference. Together, our data show that this novel tool can be used to study multiple aspects of the CD8+ T cell response to F. tularensis. Use of this tool will enhance our understanding of immunity to this deadly pathogen.

immunology↗