Demonstrating the potential of abiotic stress-tolerant Jeotgalicoccus huakuii NBRI 13E for plant growth promotion and salt stress amelioration

The present study aimed to demonstrate the potential of abiotic stress-tolerant Jeotgalicoccus huakuii NBRI 13E for plant growth promotion and salt stress amelioration. NBRI 13E was characterized for abiotic stress tolerance and plant growth-promoting (PGP) attributes under normal and salt stress conditions. Phylogenetic comparison of NBRI 13E was carried out with known species of the same genera based on 16S rRNA gene. Plant growth promotion and rhizosphere colonization studies were determined under greenhouse conditions using maize, tomato, and okra. Field experiment was also performed to assess the ability of NBRI 13E inoculation for improving growth and yield of maize crop in alkaline soil. NBRI 13E demonstrated abiotic stress tolerance and different PGP attributes under in vitro conditions. Phylogenetic and differential physiological analysis revealed considerable differences in NBRI 13E as compared with the reported species for Jeotgalicoccus genus. NBRI 13E colonizes in the rhizosphere of the tested crops, enhances plant growth, and ameliorates salt stress in a greenhouse experiment. Modulation in defense enzymes, chlorophyll, proline, and soluble sugar content in NBRI 13E-inoculated plants leads to mitigate the deleterious effect of salt stress. Furthermore, field evaluation of NBRI 13E inoculation using maize was carried out with recommended 50 and 100% chemical fertilizer controls, which resulted in significant enhancement of all vegetative parameters and total yield as compared to respective controls. Jeotgalicoccus huakuii NBRI 13E is reported for the first time for its ability to develop a bioinoculant formulation for stress amelioration and improved crop productivity.

     

China’s treatment regimen for fulminant myocarditis is bringing wonderful achievement to the world

Science China Life Sciences -     

Exploring biological network structure with clustered random networks

Background  

Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions) and the extent of clustering (the tendency for a set of three nodes to be interconnected) are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics.     

The influence of natural barriers in shaping the genetic structure of Maharashtra populations

Background

The geographical position of Maharashtra state makes it rather essential to study the dispersal of modern humans in South Asia. Several hypotheses have been proposed to explain the cultural, linguistic and geographical affinity of the populations living in Maharashtra state with other South Asian populations. The genetic origin of populations living in this state is poorly understood and hitherto been described at low molecular resolution level.

Methodology/Principal Findings

To address this issue, we have analyzed the mitochondrial DNA (mtDNA) of 185 individuals and NRY (non-recombining region of Y chromosome) of 98 individuals belonging to two major tribal populations of Maharashtra, and compared their molecular variations with that of 54 South Asian contemporary populations of adjacent states. Inter and intra population comparisons reveal that the maternal gene pool of Maharashtra state populations is composed of mainly South Asian haplogroups with traces of east and west Eurasian haplogroups, while the paternal haplogroups comprise the South Asian as well as signature of near eastern specific haplogroup J2a.

Conclusions/Significance

Our analysis suggests that Indian populations, including Maharashtra state, are largely derived from Paleolithic ancient settlers; however, a more recent (∼10 Ky older) detectable paternal gene flow from west Asia is well reflected in the present study. These findings reveal movement of populations to Maharashtra through the western coast rather than mainland where Western Ghats-Vindhya Mountains and Narmada-Tapti rivers might have acted as a natural barrier. Comparing the Maharastrian populations with other South Asian populations reveals that they have a closer affinity with the South Indian than with the Central Indian populations.     

Isocarnosol,a diterpene from salvia lanigera

Isocarnosol, a novel diterpene from the leaves of Salvia lanigera, has been characterized.     

Limnological reconnaissance of waterbodies in central and southern Nepal

Ionic composition of waterbodies in central and southern Nepal sampled in spring 1985 differed from that normally found in freshwater. Distinguishing characteristics were: 1) predominance of bicarbonate among the anions — accounting for > 90% of the negative equivalents in two-thirds of the waterbodies, 2) the near absence of sulfates — accounting for < 1 % of the anions in half the samples so that chloride exceeded sulfate (as meq/L) in three-fourths of the waters tested and 3) calcium was the dominant cation, although in certain waters the relative proportion of either magnesium or the monovalent cations was much higher than the world average. Regional patterns in water chemistry were apparent and are largely explained by differences in local geology, inputs from artesian wells or extensive use by humans. Most ionic salinity values were <400 mg/L. Using conventional criteria to assess trophic state, most water-bodies were eutrophic or hypereutrophic when judged by total phosphorus and chlorophyll content but as a whole the lakes sampled were low in nitrogen. Nitrogen: phosphorus ratios (generally < 10) and a significant empirical relation for chlorophyll-nitrogen provide evidence that nitrogen limited algal biomass. Secchi transparency values indicate light regimes were affected by nonalgal materials. Contribution of the Missouri Agricultural Experiment Station Journal Series No. 10503. Contribution of the Missouri Agricultural Experiment Station Journal Series No. 10503.     

Multiple alignment of sequences on parallel computers

A software package that allows one to carry out multiple alignmentof protein and nucleic acid sequences of almost unlimited lengthand number of sequences is developed on C-DAC parallel computer—atransputer-based machine. The farming approach is used for dataparallelization. The speed gains are almost linear when thenumber of transputers is increased from 4 to 64. The softwareis used to carry out multiple alignment of 100 sequences eachof -chain and ß-chain of hemoglobin and 83 cytochromec sequences. The signature sequence of cytochrome c was foundto be PGTKMXF. The single parameter, multiple alignment score,S, has been used to categorize proteins in different subfamiliesand groups.     

Induced expression of miR-1250-5p exerts tumor suppressive role in triple-negative breast cancer cells

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and it has a prevalence rate of 15%–20% among all breast cancer cases in younger women. Still, the underlying molecular mechanisms of its pathogenesis are not entirely understood. In the previous study, we identified that microRNA (miR)-1250-5p is significantly down-expressed in TNBC cells. Thus, in the present study, we explore the functional anticancer role of miR‑1250‑5p in the transient mimic transfected TNBC cells. 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay was used to examine the effect of miR-1250-5p on cell viability of TNBC (MDA-MB-231 and MDA-MB-453) cells. The confocal microscopy, quantitative real-time polymerase chain reaction, and western blot analysis techniques were used to assess the effect of miR-1250-5p on cancer hallmarks in test cells. Induced miR‑1250-5p expression in MDA-MB-231 and MDA-MB-453 cells decreased cell viability in a time-dependent manner. Increased miR‑1250-5p expression levels significantly decreased cell cycle G1/S phase transition markers (Cyclin D1 and CDK4) at messenger RNA (mRNA) and protein levels in TNBC cells compared to scrambled sequence transfected cells. Transient transfection of TNBC cells with miR-1250-5p mimic increased apoptosis in TNBC cells by increasing the level of active caspase (Caspase 8 and Caspase 3) of the intrinsic pathway. Apoptosis-related morphological changes were also observed in the test cells. Further, the induced expression of miR-1250-5p significantly decreased epithelial-mesenchymal transition (EMT) by altering the mRNA and protein levels of E-cadherin and Vimentin. Moreover, results of confocal microscopy revealed increased reactive oxygen species generation, and decreased mitochondria membrane potential in miR-1250-5p mimic transient transfected TNBC cells. In conclusion, miR‑1250-5p acts as tumor suppressor in TNBC cells and its induction by therapeutics might be a novel strategy for the disease treatment.     

Predicting enhancer-promoter interaction from genomic sequence with deep neural networks

Background: In the human genome, distal enhancers are involved in regulating target genes through proximal promoters by forming enhancer-promoter interactions. Although recently developed high-throughput experimental approaches have allowed us to recognize potential enhancer-promoter interactions genome-wide, it is still largely unclear to what extent the sequence-level information encoded in our genome help guide such interactions. Methods: Here we report a new computational method (named “SPEID”) using deep learning models to predict enhancer-promoter interactions based on sequence-based features only, when the locations of putative enhancers and promoters in a particular cell type are given. Results: Our results across six different cell types demonstrate that SPEID is effective in predicting enhancer-promoter interactions as compared to state-of-the-art methods that only use information from a single cell type. As a proof-of-principle, we also applied SPEID to identify somatic non-coding mutations in melanoma samples that may have reduced enhancer-promoter interactions in tumor genomes. Conclusions: This work demonstrates that deep learning models can help reveal that sequence-based features alone are sufficient to reliably predict enhancer-promoter interactions genome-wide.