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Dive into the research topics where Chandrahasya N. Khobragade is active.

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Featured researches published by Chandrahasya N. Khobragade.


International Journal of Biological Macromolecules | 2012

Novel thiazolo-pyrazolyl derivatives as xanthine oxidase inhibitors and free radical scavengers.

Supriya D. Beedkar; Chandrahasya N. Khobragade; Santosh S. Chobe; Bhaskar S. Dawane; Omprakash S. Yemul

Xanthine oxidase (XO) is a complex metalloflavoprotein, overproduction of which usually leads to a pathological condition called Gout. XO inhibitors may prove to be promising antigout agents. Present investigation describes synthesis, characterization and evaluation of 26 thiazolo-pyrazolyl derivatives V(a-z) for XO inhibitory and free radical scavenging activities. Derivatives Vq, Vo and Vh showed most promising XO inhibitory and free radical scavenging activities on the basis of their IC(50) values ranging from (6.5-9 μM). Significant dock scores compared with Allopurinol have been figured out using molecular docking. Evaluation of Vq, Vo and Vh for both the activities for first time may provide a new approach for antigout research.


Marine Pollution Bulletin | 2015

A case study on effects of oil spills and tar-ball pollution on beaches of Goa (India)

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

This paper reports the impact of oil spills and tar-ball pollution on the coastal ecosystem of Goa. The factors responsible for degrading the marine ecosystem of the Goan coastline are analyzed. Uncontrolled activities were found to degrade the marine and coastal biodiversity, in turn polluting all beaches. This had a direct impact on the Goan economy through a decline in tourism. The government must adopt the necessary control measures to restore Goan beaches and the surrounding coastal areas.


Data in Brief | 2016

Digital data for Quick Response (QR) codes of thermophiles to identify and compare the bacterial species isolated from Unkeshwar hot springs (India)

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

16S rRNA sequences of morphologically and biochemically identified 21 thermophilic bacteria isolated from Unkeshwar hot springs (19°85′N and 78°25′E), Dist. Nanded (India) has been deposited in NCBI repository. The 16S rRNA gene sequences were used to generate QR codes for sequences (FASTA format and full Gene Bank information). Diversity among the isolates is compared with known isolates and evaluated using CGR, FCGR and PCA i.e. visual comparison and evaluation respectively. Considerable biodiversity was observed among the identified bacteria isolated from Unkeshwar hot springs. The hyperlinked QR codes, CGR, FCGR and PCA of all the isolates are made available to the users on a portal https://sites.google.com/site/bhagwanrekadwad/.


Data in Brief | 2016

Digital data for quick response (QR) codes of alkalophilic Bacillus pumilus to identify and to compare bacilli isolated from Lonar Crator Lake, India.

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

Microbiologists are routinely engaged isolation, identification and comparison of isolated bacteria for their novelty. 16S rRNA sequences of Bacillus pumilus were retrieved from NCBI repository and generated QR codes for sequences (FASTA format and full Gene Bank information). 16SrRNA were used to generate quick response (QR) codes of Bacillus pumilus isolated from Lonar Crator Lake (19° 58′ N; 76° 31′ E), India. Bacillus pumilus 16S rRNA gene sequences were used to generate CGR, FCGR and PCA. These can be used for visual comparison and evaluation respectively. The hyperlinked QR codes, CGR, FCGR and PCA of all the isolates are made available to the users on a portal https://sites.google.com/site/bhagwanrekadwad/. This generated digital data helps to evaluate and compare any Bacillus pumilus strain, minimizes laboratory efforts and avoid misinterpretation of the species.


Data in Brief | 2016

Bioinformatics data supporting revelatory diversity of cultivable thermophiles isolated and identified from two terrestrial hot springs, Unkeshwar, India

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

A total of 21 thermophilic bacteria were isolated and identified using 16S rRNA gene sequencing method. Sequences were submitted to NCBI website. Short DNA sequences JN392966–JN392972; KC120909–KC120919; KM998072–KM998074 and KP053645 strains were downloaded from NCBI BioSample database. ENDMEMO GC calculating tool was used for calculation of maximum, minimum and average GC percentage and graphical representation of GC content. Data generated indicate 20 short DNA sequences have maximum GC content ranged from 60% to 100% with an average GC content 52.5–59.8%. It is recorded that Bacillus sp. W7, Escherichia coli strain NW1 and Geobacillus thermoleovorans strain rekadwadsis strains showed GC content maximum up to 70%; Actinobacterium EF_NAK1-7 up to 85.7%, while Bacillus megaterium and E. coli strain NW2 showed GC content maximum to 100%. Digital data on thermophilic bacteria isolated from Unkeshwar hot springs would be useful for interpretation of presence of biodiversity in addition to phenotypic, physiological characteristics and data generated through 16S rRNA gene sequencing technology.


Data in Brief | 2016

Digital data of quality control strains under general deposit at Microbial Culture Collection (MCC), NCCS, Pune, India: A bioinformatics approach.

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

A total of 13 short DNA sequences of quality control strains (MCC 2052, MCC 2077, MCC 2078, MCC 2080, MCC 2309, MCC 2322, MCC 2408, MCC 2409, MCC 2412, MCC 2413, MCC 2415, MCC 2483 and MCC 2515) were retrieved from NCBI BioSample database and generated quick response (QR) codes for sequences. 16S rRNA was used for creation of Chaose Game representation (CGR), Chaose Game Representation of Frequencies (FCGR) and measurement of GC percentage. Digital data in the form of QR codes, CGR, FCGR and GC plot would be useful for identification, visual comparison and evaluation of newly isolated strains with quality control strains. The digital data of QR codes, CGR, FCGR and GC content all the quality control strains are made available to users through this paper. This generated digital data helps to evaluate and compare newly isolated strains, less laborious and avoid misinterpretation of newly isolated species.


Archive | 2017

Bacterial Quorum Sensing (QS) in Rhizosphere (Paddy Soil): Understanding Soil Signaling and N-Recycling for Increased Crop Production

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

The multispecies communication in the environment exists as quorum sensing (QS). It is influenced by cell density and the production rate of sensory molecules. Numerous bacteria and other microorganisms have cellular communication through these molecules. It gives an idea about the coevolution in the rhizosphere. The QS supply utilizable form of nitrogen (N), solubilize phosphate, and induce systematic resistance in plants or suppress pathogenic bacteria in the rhizosphere. It is noticed that the conversion of high-molecular-weight N− into low-molecular-weight N− depends on cell density (biofilm) and their behaviors in rhizospheric soil. Thus, QS may be a control point in the rhizosphere (paddy soil) N-mineralization (i.e., N-recycling).


Archive | 2017

Microbial Biofilm: Role in Crop Productivity

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

Bacteria, fungi, and mycorrhizae and their metabolic products when adhere to the biotic and abiotic surfaces as a single or multicellular assembly can be described as biofilms. Beneficial microorganisms associated with plants interact with host tissues and deal with many issues during symbiosis, commensal relationship (mutualism), and pathogenesis. The numbers of beneficial microorganisms associated with plants are less than that present in biofilms and vary from small clusters of cells to extensive biofilms. Beneficial biofilms of bacteria, plant growth-promoting rhizobacteria (PGPR), fungi, and mycorrhizae are the important group of microbial inoculants among the beneficial biofilms forming microorganisms which has been studied extensively for their ability to promote growth of crop plants and their improved ability. PGPR and PGPR-like microorganisms’ acts through direct or indirect mechanisms either inhibit or prevent the effects of phytopathogenic microorganisms facilitating the availability and uptake of essential nutrients such as nitrogen, phosphorus, potassium, ferrous, zinc, etc., from the atmosphere (air, water, and soil). Environmental stresses such as high salinity, drought, high or low pH, high or low temperature, pressure of heavy metals like Fe and Ni, flooding, and pathogens have a negative impact on crop plants. These problems can be solved using the PGPR biofilm to enhance the growth and productivity of crops, lower the ethylene concentration, increase phytohormones and exopolysaccharide production, induce systematic resistance in plants, and secrete noticeable quantity of siderophores that helps to solubilize iron (Fe) and increase its availability for plant uptake. Similarly, arbuscular mycorrhizal (AM) biofilm also helps the plant under stressful conditions by regulation of plant nutrition and enhancing production of phytohormones and antioxidant enzymes. Additionally, a variety of siderophores secreted by soil and marine microorganisms made essential minerals available to microbial cells to confer resistance to disease and improved the plant productivity. These polymicrobial, multiple beneficial functions in polyextremophilic condition such as phosphate solubilization, biocontrol, dinitrogen (N2) fixation performed by biofilms, and consortia of biofilms promote the possible positive new developments in this research area. Therefore, it is necessary to develop inoculum of biofilm and consortia of biofilm for increased crop productivity on a large scale.


Data in Brief | 2016

Data on true tRNA diversity among uncultured and bacterial strains

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

Complete genome sequences of two uncultured archaea (BX649197 and CR937008) and 10 uncultured bacteria (AC160099, FP245538-FP245540, FP312972, FP312974-75, FP312977, FP312985 and NZ_JPJG01000067) were used for creation of digital data of tRNA. tRNAscan-SE and ENDMEMO GC calculating tools were used for detection of tRNA, drawing their structures and calculation of GC percent. Seven archaeal and 48 bacterial tRNA were detected from above 12 sequences. Four archaeal and 30 bacterial tRNA showed cove score more than 20% are called as true tRNA. Three tRNA of uncultured bacteria (AC160099) has the presence of the variable loop. The tRNA of FP245540, FP245575, FP245577 and FP245585 has one variable loop each. The true tRNA of archaea were Alanine, Arginine and Cysteine-type tRNA, while the majority of bacteria true tRNA classified as Alanine, Glutamic acid, Isoleucine, Leucine, Methionine, Phenylalanine, Proline and Valine-type tRNA with cove score ranged from 70% to 97.15%. Archaeal and bacterial have GC content approximately 43% and 34.7–63.3% respectively. Archaeal tRNA has 60.4–64.2% GC content. Similarly, bacterial tRNA contributed 49.3–66.3% GC content to the total GC content. This generated data is useful for studies on diversity of tRNA among prokaryotes.


Data in Brief | 2016

Determination of GC content of Thermotoga maritima, Thermotoga neapolitana and Thermotoga thermarum strains: A GC dataset for higher level hierarchical classification

Bhagwan N. Rekadwad; Chandrahasya N. Khobragade

A total of 16 strains of hyperthermophilic Thermotoga complete genome sequences viz. Thermotoga maritima (AE000512, CP004077, CP007013, CP011107, NC_000853, NC_021214, NC_023151, NZ_CP011107, CP011108, NZ_CP011108, CP010967 & NZ_CP010967), Thermotoga neapolitana (CP000916, & NC_011978) and Thermotoga thermarum (CP002351 & NC_015707) complete genome sequences were retrieved from NCBI BioSample database. ENDMEMO GC used for creation of data on GC content in Thermotoga sp. DNA sequences. Maximum GC content was observed in Thermotoga strains AE000512 & NC_000853 (69 %GC), followed by NZ_CP011108, CP011108, NZ_CP011107, NC_023151, NC_021214, CP011107 & CP004077 (68.5 %GC), followed by NZ_CP010967 & CP010967 (68.3 %GC), followed by CP000916, CP007013 & NC_011978 (68 %GC), followed by CP002351 & NC_015707 (67 %GC) strains. The use of GC dataset ratios helps in higher level hierarchical classification in Bacterial Systematics in addition to phenotypic and other genotypic characters.

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Bhagwan N. Rekadwad

Swami Ramanand Teerth Marathwada University

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Supriya D. Beedkar

Swami Ramanand Teerth Marathwada University

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Juan M. Gonzalez

Spanish National Research Council

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A.C. Kumbharkhane

Swami Ramanand Teerth Marathwada University

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Bhaskar S. Dawane

Swami Ramanand Teerth Marathwada University

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Omprakash S. Yemul

Swami Ramanand Teerth Marathwada University

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Ravindra B. Talware

Swami Ramanand Teerth Marathwada University

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Santosh S. Chobe

Swami Ramanand Teerth Marathwada University

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