scholarly journals Chemotaxis Away from 4-Chloro-2-nitrophenol, 4-Nitrophenol, and 2,6-Dichloro-4-nitrophenol byBacillus subtilisPA-2

2015 ◽  
Vol 2015 ◽  
pp. 1-4 ◽  
Author(s):  
Pankaj Kumar Arora ◽  
Mi-Jeong Jeong ◽  
Hanhong Bae
Keyword(s):  
Bacillus Subtilis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Rrna Gene Sequencing ◽  
The 16S Rrna Gene ◽  
Drop Plate ◽  
Chemotactic Behavior

Bacterial strain PA-2 exhibits chemotaxis away from 4-chloro-2-nitrophenol, 4-nitrophenol, and 2,6-dichloro-4-nitrophenol. This strain was identified asBacillus subtilison the basis of the 16S rRNA gene sequencing. The drop plate assay and the chemical-in-plug method were used to demonstrate negative chemotactic behavior of strain PA-2. The growth studies showed that strain PA-2 did not utilize 4-chloro-2-nitrophenol, 4-nitrophenol, and 2,6-dichloro-4-nitrophenol as its sole sources of carbon and energy. This is the first report of negative chemotaxis of 4-chloro-2-nitrophenol, 4-nitrophenol, and 2,6-dichloro-4-nitrophenol by any bacterium.

scholarly journals Diversity of bacterial communities on the facial skin of different age-group Thai males

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4084 ◽  
Author(s):  
Alisa Wilantho ◽  
Pamornya Deekaew ◽  
Chutika Srisuttiyakorn ◽  
Sissades Tongsima ◽  
Naraporn Somboonna
Keyword(s):  
Young Adults ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Skin Microbiome ◽  
The Us ◽  
Rrna Gene Sequencing ◽  
The 16S Rrna Gene

BackgroundSkin microbiome varies from person to person due to a combination of various factors, including age, biogeography, sex, cosmetics and genetics. Many skin disorders appear to be related to the resident microflora, yet databases of facial skin microbiome of many biogeographies, including Thai, are limited.MethodsMetagenomics derived B-RISA and 16S rRNA gene sequencing was utilized to identify the culture-independent bacterial diversity on Thai male faces (cheek and forehead areas). Skin samples were categorized (grouped) into (i) normal (teenage.hea) and (ii) acne-prone (teenage.acn) young adults, and normal (iii) middle-aged (middle.hea) and (iv) elderly (elderly.hea) adults.ResultsThe 16S rRNA gene sequencing was successful as the sequencing depth had an estimated >98% genus coverage of the true community. The major diversity was found between the young and elderly adults in both cheek and forehead areas, followed by that between normal and acne young adults. Detection of representative characteristics indicated that bacteria from the order Rhizobiales, generaSphingomonasandPseudoalteromonas, distinguished theelderly.heamicrobiota, along the clinical features of wrinkles and pores. Prediction of the metabolic potential revealed reduced metabolic pathways involved in replication and repair, nucleotide metabolism and genetic translation in theelderly.heacompared with that in theteenage.hea. For young adults, some unique compositions such as abundance ofPropionibacterium acnesandStaphylococcus epidermidis, with a minor diversity between normal and acne skins, were detected. The metabolic potentials of the acne vs. normal young adults showed thatteenage.acnwas low in many cellular processes (e.g., cell motility and environmental adaptation), but high in carbohydrate metabolism, which could support acne growth. Moreover, comparison with the age-matched males from the US (Boulder, Colorado) to gain insight into the diversity across national biogeography, revealed differences in the distribution pattern of species, although common bacteria were present in both biogeographical samples. Furthermore, B-RISA served as a crosscheck result to the 16S rRNA gene sequencing (i.e., differences between teenage and elderly microbiota).ConclusionsThis study revealed and compared the microbial diversity on different aged Thai male faces, and included analyses for representing the bacterial flora, the clinical skin characteristics, and comparison with the US age-matched. The results represent the first skin microbiota of Thai males, and helps the design of a large-scale skin microbiome study of Thais. The findings of the diversity among ages, skin type and national biogeography supported the importance of these traits in the skin microbiome and in developing a safe and sustainable treatment for acne and aging skin diseases.

scholarly journals Non-specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sidney P. Walker ◽  
Maurice Barrett ◽  
Glenn Hogan ◽  
Yensi Flores Bueso ◽  
Marcus J. Claesson ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Bacterial Communities ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Sample Type ◽  
Human Dna ◽  
Rrna Gene Sequencing ◽  
The 16S Rrna Gene

Abstract The targeted sequencing of the 16S rRNA gene is one of the most frequently employed techniques in the field of microbial ecology, with the bacterial communities of a wide variety of niches in the human body have been characterised in this way. This is performed by targeting one or more hypervariable (V) regions within the 16S rRNA gene in order to produce an amplicon suitable in size for next generation sequencing. To date, all technical research has focused on the ability of different V regions to accurately resolve the composition of bacterial communities. We present here an underreported artefact associated with 16S rRNA gene sequencing, namely the off-target amplification of human DNA. By analysing 16S rRNA gene sequencing data from a selection of human sites we highlighted samples susceptible to this off-target amplification when using the popular primer pair targeting the V3–V4 region of the gene. The most severely affected sample type identified (breast tumour samples) were then re-analysed using the V1–V2 primer set, showing considerable reduction in off target amplification. Our data indicate that human biopsy samples should preferably be amplified using primers targeting the V1–V2 region. It is shown here that these primers result in on average 80% less human genome aligning reads, allowing for more statistically significant analysis of the bacterial communities residing in these samples.

Archaeal diversity in permafrost deposits of Bunger Hills Oasis and King George Island (Antarctica) according to the 16S rRNA gene sequencing

Microbiology ◽  
2014 ◽  
Vol 83 (4) ◽  
pp. 398-406 ◽  
Author(s):  
E. S. Karaevskaya ◽  
L. S. Demchenko ◽  
N. E. Demidov ◽  
E. M. Rivkina ◽  
S. A. Bulat ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Archaeal Diversity ◽  
King George Island ◽  
Rrna Gene Sequencing ◽  
The 16S Rrna Gene

Intravaginal microbial flora by the 16S rRNA gene sequencing

2011 ◽  
Vol 205 (3) ◽  
pp. 235.e1-235.e9 ◽  
Author(s):  
Kazuaki Yoshimura ◽  
Nobuo Morotomi ◽  
Kazumasa Fukuda ◽  
Masahiro Nakano ◽  
Masamichi Kashimura ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Microbial Flora ◽  
Rrna Gene ◽  
Rrna Gene Sequencing ◽  
The 16S Rrna Gene

Screening and Molecular Characterization of Cellulase Producing Actinobacteria from Litchi Orchard

2019 ◽  
Vol 13 (1) ◽  
pp. 90-101
Author(s):  
Sanju Kumari ◽  
Utkarshini Sharma ◽  
Rohit Krishna ◽  
Kanak Sinha ◽  
Santosh Kumar
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Molecular Characterization ◽  
Biochemical Characterization ◽  
Evolutionary Relationship ◽  
Gene Sequencing ◽  
Cellulase Activity ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Rrna Gene Sequencing

Background: Cellulolysis is of considerable economic importance in laundry detergents, textile and pulp and paper industries and in fermentation of biomass into biofuels. Objective: The aim was to screen cellulase producing actinobacteria from the fruit orchard because of its requirement in several chemical reactions. Methods: Strains of actinobacteria were isolated on Sabouraud’s agar medium. Similarities in cultural and biochemical characterization by growing the strains on ISP medium and dissimilarities among them perpetuated to recognise nine groups of actinobacteria. Cellulase activity was measured by the diameter of clear zone around colonies on CMC agar and the amount of reducing sugar liberated from carboxymethyl cellulose in the supernatant of the CMC broth. Further, 16S rRNA gene sequencing and molecular characterization were placed before NCBI for obtaining recognition with accession numbers. Results: Prominent clear zones on spraying Congo Red were found around the cultures of strains of three groups SK703, SK706, SK708 on CMC agar plates. The enzyme assay for carboxymethylcellulase displayed extra cellulase activity in broth: 0.14, 0.82 and 0.66 µmol mL-1 min-1, respectively at optimum conditions of 35°C, pH 7.3 and 96 h of incubation. However, the specific cellulase activities per 1 mg of protein did not differ that way. It was 1.55, 1.71 and 1.83 μmol mL-1 min-1. The growing mycelia possessed short compact chains of 10-20 conidia on aerial branches. These morphological and biochemical characteristics, followed by their verification by Bergey’s Manual, categorically allowed the strains to be placed under actinobacteria. Further, 16S rRNA gene sequencing, molecular characterization and their evolutionary relationship through phylogenetics also confirmed the putative cellulase producing isolates of SK706 and SK708 subgroups to be the strains of Streptomyces. These strains on getting NCBI recognition were christened as Streptomyces glaucescens strain SK91L (KF527284) and Streptomyces rochei strain SK78L (KF515951), respectively. Conclusion: Conclusive evidence on the basis of different parameters established the presence of cellulase producing actinobacteria in the litchi orchard which can convert cellulose into fermentable sugar.

scholarly journals Much ado about nothing? Off-target amplification can lead to false-positive bacterial brain microbiome detection in healthy and Parkinson’s disease individuals

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Janis R. Bedarf ◽  
Naiara Beraza ◽  
Hassan Khazneh ◽  
Ezgi Özkurt ◽  
David Baker ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
False Positive ◽  
Gene Sequencing ◽  
Bacterial Biomass ◽  
16S Rrna Gene Sequencing ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Rrna Gene Sequencing

Abstract Background Recent studies suggested the existence of (poly-)microbial infections in human brains. These have been described either as putative pathogens linked to the neuro-inflammatory changes seen in Parkinson’s disease (PD) and Alzheimer’s disease (AD) or as a “brain microbiome” in the context of healthy patients’ brain samples. Methods Using 16S rRNA gene sequencing, we tested the hypothesis that there is a bacterial brain microbiome. We evaluated brain samples from healthy human subjects and individuals suffering from PD (olfactory bulb and pre-frontal cortex), as well as murine brains. In line with state-of-the-art recommendations, we included several negative and positive controls in our analysis and estimated total bacterial biomass by 16S rRNA gene qPCR. Results Amplicon sequencing did detect bacterial signals in both human and murine samples, but estimated bacterial biomass was extremely low in all samples. Stringent reanalyses implied bacterial signals being explained by a combination of exogenous DNA contamination (54.8%) and false positive amplification of host DNA (34.2%, off-target amplicons). Several seemingly brain-enriched microbes in our dataset turned out to be false-positive signals upon closer examination. We identified off-target amplification as a major confounding factor in low-bacterial/high-host-DNA scenarios. These amplified human or mouse DNA sequences were clustered and falsely assigned to bacterial taxa in the majority of tested amplicon sequencing pipelines. Off-target amplicons seemed to be related to the tissue’s sterility and could also be found in independent brain 16S rRNA gene sequences. Conclusions Taxonomic signals obtained from (extremely) low biomass samples by 16S rRNA gene sequencing must be scrutinized closely to exclude the possibility of off-target amplifications, amplicons that can only appear enriched in biological samples, but are sometimes assigned to bacterial taxa. Sequences must be explicitly matched against any possible background genomes present in large quantities (i.e., the host genome). Using close scrutiny in our approach, we find no evidence supporting the hypothetical presence of either a brain microbiome or a bacterial infection in PD brains.

scholarly journals Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francesco Durazzi ◽  
Claudia Sala ◽  
Gastone Castellani ◽  
Gerardo Manfreda ◽  
Daniel Remondini ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Shotgun Sequencing ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Experimental Conditions ◽  
Rrna Gene Sequencing

AbstractIn this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

scholarly journals Non-Specific Immunity Associated Gut Microbiome in Aristichthys nobilis under Different Rearing Strategies

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 916
Author(s):  
Jianming Yuan ◽  
Zhijian Wang ◽  
Bo Wang ◽  
Huiqing Mei ◽  
Xuliang Zhai ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Bighead Carp ◽  
Live Food ◽  
Rrna Gene ◽  
Food Fish ◽  
Rrna Gene Sequencing

To understand the intestinal microbial diversity and community structure of bighead carp (Aristichthys nobilis) under different feeding strategies, 39 fish from three groups (A: 9 fish, natural live food only; B: 15 fish, natural live food + fish formulated feeds; C: 15 fish, natural live food + fish formulated feed + lactic acid bacteria) were obtained for the high throughput 16S rRNA gene sequencing. We first examined five non-specific immunity indications of the carp—lysozyme (LZM), catalase (CAT), glutathione reductase (GR), glutathione peroxidase (GSH-PX), and superoxide dismutase (SOD). Interestingly, the composition of gut microbiota and related non-specific immune indices were affected by the feeding treatment of the bighead carp. Notably, all enzyme activity indexes were significantly different (p < 0.01) in the spleen and three enzyme activity indexes (LZM, GSH-PX, and SOD) had significant differences in the hepatopancreas (p < 0.001) of the carp from the three groups. The 16S rRNA gene sequencing showed higher diversity in groups B and C. Compared to group A, the relative abundance of Actinobacteria increased significantly and the relative abundance of Proteobacteria and Firmicutes decreased significantly in groups B and C at the phylum level. Functional analysis revealed the association between non-specific immune indicators and import genera in the hepatopancreas and spleen of bighead carp. This study provides new insights into the gut microbiomes and non-specific immune of bighead carp.

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