An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis

An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation.

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis

S-adenosyl-L-methionine, trehalose and oleanolic acid in few plants

O jornal i distribui hoje uma edição especial durante o congresso da World Association of Newspapers, a decorrer em Hyderabad, Índia (fonte: Meios e Publicidade). A edição é um “best of com as melhores histórias do i e algumas páginas premiadas na Society for News Design” e coincide com a apresentação de Martim Avillez Figueiredo, director do diário, sobre o tema The Power of Print

Immotilin, a novel sperm immobilizing protein

This article does not have an abstract

Placental Proteomics Provides Insights into Pathophysiology of Pre-Eclampsia and Predicts Possible Markers in Plasma

Pre-eclampsia is a hypertensive disorder characterized by the new onset of hypertension >140/90 mmHg and proteinuria after the 20th week of gestation. The disorder is multifactorial and originates with abnormal placentation. Comparison of the placental proteome of normotensive (<i>n</i> = 25) and pre-eclamptic (<i>n</i> = 25) patients by gel-free proteomic techniques identified a total of 2145 proteins in the placenta of which 180 were differentially expressed (>1.3 fold, <i>p</i> < 0.05). Gene ontology enrichment analysis of biological process suggested that the differentially expressed proteins belonged to various physiological processes such as angiogenesis, apoptosis, oxidative stress, hypoxia, and placental development, which are implicated in the pathophysiology of pre-eclampsia. Some of the differentially expressed proteins were monitored in the plasma by multiple reaction monitoring analysis, which showed an increase in apolipoproteins A-I and A-II in gestational weeks 26–30 (2-fold, <i>p</i> < 0.01), while haptoglobin and hemopexin decreased in gestational weeks 26–30 and week 40/at delivery (1.8 fold, <i>p</i> < 0.01) in pre-eclamptic patients. This study provides a proteomic insight into the pathophysiology of pre-eclampsia. Identified candidate proteins can be evaluated further for the development of potential biomarkers associated with pre-eclampsia pathogenesis

A High Throughput Lipidomics Method Using Scheduled Multiple Reaction Monitoring

Lipid compositions of cells, tissues, and bio-fluids are complex, with varying concentrations and structural diversity making their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based lipidomics screening method using a combination of variable retention time window and relative dwell time weightage. Using this method, we identified more than 1000 lipid species within 24-min. The limit of detection varied from the femtomolar to the nanomolar range. About 883 lipid species were detected with a coefficient of variance &lt;30%. We used this method to identify plasma lipids altered due to vitamin B12 deficiency and found a total of 18 lipid species to be altered. Some of the lipid species with &omega;-6 fatty acid chains were found to be significantly increased while &omega;-3 decreased in vitamin B12 deficient samples. This method enables rapid screening of a large number of lipid species in a single experiment and would substantially advance our understanding of the role of lipids in biological processes

Delineating Variabilities of Groundwater Level Prediction Across the Agriculturally Intensive Transboundary Aquifers of South Asia

Groundwater depletion in South Asia’s Himalayan, transboundary Indus-Ganges-Brahmaputra-Meghna (IGBM) rivers basin is among the highest globally. Given the high irrigation demand and population, groundwater sustainability requires an improved understanding of groundwater systems for the accurate prediction of groundwater levels (GWLs). However, the prediction of groundwater system behaviors is a significant challenge since it is dominated by spatiotemporal and subsurface depth-dependent drivers. Earlier studies that address the challenges are mainly based on the short spatial and temporal extent and/or do not separate the renewable (i.e., shallow) vs nonrenewable (i.e., deeper) groundwater signals. Here, we first identified the variable importance of spatial and depth-dependent drivers on GWL in the IGBM basin. Our results indicate a greater influence of anthropogenic factors (i.e., widespread pumping and increased population) in most parts of the IGBM basin, except in the precipitation-dominated basin of the Brahmaputra. Our next purpose was to delineate a multifactorial approach for GWL prediction using the two most used machine learning models (i.e., support vector machine and feed-forward neural network) in the literature. In general, the machine learning model outputs show a good match in comparison to the GWL from the observation wells (n = 2303 distributed across India and Bangladesh) with some limitations in areas with increased groundwater irrigation. We separately compared the results from shallow (35 m) observation wells, emphasizing the significance of deep groundwater pumping. Our approach highlights the importance of spatiotemporal to multidepth factors in GWL prediction and can be adopted in other parts of the globe to predict GWLs

Co-purification of Glucanase with Acid Trehalase–Invertase Aggregate in Saccharomyces Cerevisiae

An electrophoretically homogenous aggregate of acid trehalase, invertase and an unidentified 37–41 kDa protein was purified from Saccharomyces cerevisiae. N-terminal analysis of the protein revealed an amino acid sequence identical to that of Bgl2p (endo-b-l,3-glucanase) of S. cerevisiae. Acid trehalase activity with co-eluted glucanase activity was observed from late growth phase through early stationary phase. Pools with high percentage of Bgl2p corresponded with high acid trehalase activity. A BGL2 deletion strain had lower acid trehalase activity. The 37–41 kDa protein represents Bgl2p which, besides imparting glucanase activity, could also be acting as a regulator for the acid trehalase activity by association in the enzyme aggregate