Search bioRxiv⌕ Search

bioRxiv · 10.1101/837112

Isolation and molecular identification of pectinase producing Aspergillus species from different soil samples of Bhubaneswar regions

Abstract

With the significant improvement of human civilization there is a spur in the urban, rural and industrial development, which has a profound effect on the surrounding natural environment. Increased utilization of natural resources is often associated with accumulation of waste materials whose management is crucial for sustainable development of life. Availability of different microorganisms in the soil facilitates the degradation of wastes through their potential enzymatic activities. Pectinase seems to be one of the important enzymes produced by a wide variety of microorganisms contained in the soil. It is mainly involved in maceration and rotting of plant extracts and debris by hydrolysis of 1,4-alpha glycosidic bonds of de-esterified pectate of plant call wall. In this paper we report molecular identification of some pectinase producing Aspergillus species selected from soil samples of five different zones of Bhubaneswar city using molecular biology and computational techniques. Among fifteen fungal isolates studied from these five zones Aspergillus parvisclerotigenus was potent for pectinase production next to Aspergillus niger in form of halozone of 0.6 mm. Its 28S rDNA sequence also had some significant identity (>90%) with different subspecies of Aspergillus. We hope that our findings will helpful in genetic manipulation for improvement of fungal strains of isolates. Again large scale use of the improved Aspergillus strains can degrade plant biomass & diverse industrial wastes which will reduce environmental pollution of capital urban like Bhubaneswar.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Satpathy, S., Behera, P. M., Tanty, D. K., Srivastava, S., Thatoi, H., Sahoo, S. L.. 2019-11-09. Isolation and molecular identification of pectinase producing Aspergillus species from different soil samples of Bhubaneswar regions. https://doi.org/10.1101/837112

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cell-scale confinement reorders bacterial speed rankings

Which bacterium swims fastest depends on where the race is run. Speeds are usually measured in open liquid, yet many bacteria live in pores, mucus and host passages no wider than a cell. Using a microfluidic device with eight channel widths (0.80-3.00 m) in one field of view, we tracked unlabeled cells of eight species spanning five motility systems. Chamber height, a polymer additive and channel width each reordered the ranking. Vibrio alginolyticus, the fastest in open liquid, slowed to ~4 m/s in 1.25-m channels, whereas Campylobacter jejuni and Bacillus subtilis kept 33-46 m/s. Open liquid speed did not predict robustness to confinement. In two unrelated lineages, host symbionts that pass through narrow passages during colonization, Caballeronia insecticola and Vibrio fischeri, outran their non-symbiotic relatives in the channels, and crossed them with flagella wrapped around the cell body at nearly the speed of unwrapped cells. Where space is tight, the ability to keep moving, not top speed, sets the ranking.

microbiology↗

The biochemical composition of coronavirus Nucleocapsid proteins drives the bicistronic properties of their sub-genomic mRNAs

The nucleocapsid (N) gene of coronaviruses (CoVs) encodes a structural RNA-binding protein required for viral assembly. In SARS- and MERS-CoV viruses, reading frame 2 of N contains an overlapping open reading frame (ORF) encoding an innate immune antagonist accessory protein. However, the extent of this dual coding capacity across the CoV family, and the genetic features driving overlapping ORF formation, remain unexamined. Here, we developed an in-silico tool (ORFan) to screen structural gene sub-genomic mRNA sequences from 152 species of coronavirus for the presence of overlapping accessory gene candidates. We found that frame 2 of the N gene in Alpha-, Beta- and Delta-CoVs frequently contains a potential accessory ORF (AcORF), conserved at the subgenus level, unlike the spike, envelope and membrane genes. We also show that CoV nucleotide biases in conjunction with codon biases integral to N protein function drive the relatively high abundances of start codons in frame two and stop codons in frame three, explaining the tendency towards frame 2 AcORFs. We further suggest that viral nucleotide biases and the codon composition required for RNA-binding function facilitate overlapping ORF formation in other virus families

microbiology↗

Evaluating non-oxidative glycolysis using 13C metabolic flux analysis

Non-oxidative glycolysis (NOG) converts glucose to acetyl-CoA without emitting CO2 during Escherichia coli bioproduction. Although 13C-metabolic flux analysis (13C-MFA) has the potential to evaluate NOG flux distribution in vivo, the precision of these estimates depends on the labeling patterns of glucose tracers. Because E. coli has multiple native glycolysis pathways, selecting the optimal glucose tracer is important for precise estimates. This study used simulations to evaluate the performance of 18 commercially available glucose tracers in precisely predicting NOG flux. We artificially generated flux distributions of central metabolic pathways, including three types of NOG pathways, and obtained 13C labeling patterns of amino acids metabolized from each glucose tracer. Using these data, we then calculated 95% confidence intervals (CIs) for NOG pathway fluxes. Comparing the sum of CI widths from three NOG fluxes showed that estimation with [1,3-13C]-glucose yielded the narrowest CIs. Several tracers, including [2,3-13C]glucose, were capable of determining fluxes with high precision, but [1-13C]glucose was not one of them, despite often being used for estimating glycolytic fluxes. We then experimentally evaluated [2,3-13C]- and [1-13C]glucose as tracers in E. coli strains with and without the expression of phosphoketolase, which is required for NOG pathways to function. The results suggested that [1-13C]glucose could not detect NOG fluxes, whereas [2,3-13C]glucose estimated the fluxes of all three NOG pathways with narrow CIs.

microbiology↗