scholarly journals Label-Free SERS Discrimination and In Situ Analysis of Life Cycle in Escherichia coli and Staphylococcus epidermidis

Biosensors ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 131 ◽  
Author(s):  
Niccolò Paccotti ◽  
Francesco Boschetto ◽  
Satoshi Horiguchi ◽  
Elia Marin ◽  
Alessandro Chiadò ◽  
...  
Keyword(s):  
Bacterial Culture ◽  
Bacterial Species ◽  
Surface Enhanced Raman Spectroscopy ◽  
Complete Characterization ◽  
Sers Spectrum ◽  
Label Free ◽  
Bacterial Strains ◽  
Mesoporous Silicon ◽  
Vibrational Signal ◽  
Subsequent Decrease

Surface enhanced Raman spectroscopy (SERS) has been proven suitable for identifying and characterizing different bacterial species, and to fully understand the chemically driven metabolic variations that occur during their evolution. In this study, SERS was exploited to identify the cellular composition of Gram-positive and Gram-negative bacteria by using mesoporous silicon-based substrates decorated with silver nanoparticles. The main differences between the investigated bacterial strains reside in the structure of the cell walls and plasmatic membranes, as well as their biofilm matrix, as clearly noticed in the corresponding SERS spectrum. A complete characterization of the spectra was provided in order to understand the contribution of each vibrational signal collected from the bacterial culture at different times, allowing the analysis of the bacterial populations after 12, 24, and 48 h. The results show clear features in terms of vibrational bands in line with the bacterial growth curve, including an increasing intensity of the signals during the first 24 h and their subsequent decrease in the late stationary phase after 48 h of culture. The evolution of the bacterial culture was also confirmed by fluorescence microscope images.

scholarly journals Label-free Classification of Bacterial Extracellular Vesicles by Combining Nanoplasmonic Sensors with Machine Learning

2021 ◽  
Author(s):  
Mohammadrahim Kazemzadeh ◽  
Colin Hisey ◽  
Priscila Dauros Singorenko ◽  
Simon Swift ◽  
Kamran Zargar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Extracellular Vesicles ◽  
Incident Light ◽  
Bacterial Species ◽  
Surface Enhanced Raman Spectroscopy ◽  
Machine Learning Algorithms ◽  
Host Cells ◽  
Label Free ◽  
Gut Health ◽  
Purification Method

Bacterial extracellular vesicles (EVs) are nanoscale lipid-enclosed packages that are released by bacteria cells and shuttle various biomolecules between bacteria or host cells. They are implicated in playing several important roles, from infectious disease progression to maintaining proper gut health, however the tools available to characterise and classify them are limited and impractical for many applications. Surface-enhanced Raman Spectroscopy (SERS) provides a promising means of rapidly fingerprinting bacterial EVs in a label-free manner by taking advantage of plasmonic resonances that occur on nanopatterned surfaces, effectively amplifying the inelastic scattering of incident light. In this study, we demonstrate that by applying machine learning algorithms to bacterial EV SERS spectra, EVs from cultures of the same bacterial species Escherichia coli can be classified by strain, culture conditions, and purification method. While these EVs are highly purified and homogeneous compared to complex samples, the ability to classify them from a single species demonstrates the incredible power of SERS when combined with machine learning, and the importance of considering these parameters in future applications. We anticipate that these findings will play a crucial role in developing the laboratory and clinical utility of bacterial EVs, such as the label-free, noninvasive, and rapid diagnosis of infections without the need to culture samples from blood, urine, or other fluids.<br>

scholarly journals Label-free Classification of Bacterial Extracellular Vesicles by Combining Nanoplasmonic Sensors with Machine Learning

2021 ◽  
Author(s):  
Mohammadrahim Kazemzadeh ◽  
Colin Hisey ◽  
Priscila Dauros Singorenko ◽  
Simon Swift ◽  
Kamran Zargar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Extracellular Vesicles ◽  
Incident Light ◽  
Bacterial Species ◽  
Surface Enhanced Raman Spectroscopy ◽  
Machine Learning Algorithms ◽  
Host Cells ◽  
Label Free ◽  
Gut Health ◽  
Purification Method

Bacterial extracellular vesicles (EVs) are nanoscale lipid-enclosed packages that are released by bacteria cells and shuttle various biomolecules between bacteria or host cells. They are implicated in playing several important roles, from infectious disease progression to maintaining proper gut health, however the tools available to characterise and classify them are limited and impractical for many applications. Surface-enhanced Raman Spectroscopy (SERS) provides a promising means of rapidly fingerprinting bacterial EVs in a label-free manner by taking advantage of plasmonic resonances that occur on nanopatterned surfaces, effectively amplifying the inelastic scattering of incident light. In this study, we demonstrate that by applying machine learning algorithms to bacterial EV SERS spectra, EVs from cultures of the same bacterial species Escherichia coli can be classified by strain, culture conditions, and purification method. While these EVs are highly purified and homogeneous compared to complex samples, the ability to classify them from a single species demonstrates the incredible power of SERS when combined with machine learning, and the importance of considering these parameters in future applications. We anticipate that these findings will play a crucial role in developing the laboratory and clinical utility of bacterial EVs, such as the label-free, noninvasive, and rapid diagnosis of infections without the need to culture samples from blood, urine, or other fluids.<br>

scholarly journals The Conservation of Low Complexity Regions in Bacterial Proteins Depends on the Pathogenicity of the Strain and Subcellular Location of the Protein

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 451
Author(s):  
Pablo Mier ◽  
Miguel A. Andrade-Navarro
Keyword(s):  
Membrane Proteins ◽  
Outer Membrane ◽  
Bacterial Species ◽  
Outer Membrane Proteins ◽  
Subcellular Location ◽  
Low Complexity ◽  
Extracellular Proteins ◽  
Bacterial Strains ◽  
Bacterial Proteins ◽  
Protein Subcellular Location

Low complexity regions (LCRs) in proteins are characterized by amino acid frequencies that differ from the average. These regions evolve faster and tend to be less conserved between homologs than globular domains. They are not common in bacteria, as compared to their prevalence in eukaryotes. Studying their conservation could help provide hypotheses about their function. To obtain the appropriate evolutionary focus for this rapidly evolving feature, here we study the conservation of LCRs in bacterial strains and compare their high variability to the closeness of the strains. For this, we selected 20 taxonomically diverse bacterial species and obtained the completely sequenced proteomes of two strains per species. We calculated all orthologous pairs for each of the 20 strain pairs. Per orthologous pair, we computed the conservation of two types of LCRs: compositionally biased regions (CBRs) and homorepeats (polyX). Our results show that, in bacteria, Q-rich CBRs are the most conserved, while A-rich CBRs and polyA are the most variable. LCRs have generally higher conservation when comparing pathogenic strains. However, this result depends on protein subcellular location: LCRs accumulate in extracellular and outer membrane proteins, with conservation increased in the extracellular proteins of pathogens, and decreased for polyX in the outer membrane proteins of pathogens. We conclude that these dependencies support the functional importance of LCRs in host–pathogen interactions.

scholarly journals Isolation and efficacy of two bacterial strains antagonists of Erwinia amylovora and Pectobacterium carotovorum

2021 ◽  
Vol 31 (1) ◽  
Author(s):  
M’hamed BENADA ◽  
Boualem BOUMAAZA ◽  
Sofiane BOUDALIA ◽  
Omar KHALADI
Keyword(s):  
Fire Blight ◽  
Erwinia Amylovora ◽  
Bacterial Species ◽  
Crop Protection ◽  
Soft Rot ◽  
Causal Agent ◽  
Plant Diseases ◽  
Ecological Niches ◽  
Pectobacterium Carotovorum ◽  
Bacterial Strains

Abstract Background The development of ecofriendly tools against plant diseases is an important issue in crop protection. Screening and selection process of bacterial strains antagonists of 2 pathogenic bacterial species that limit very important crops, Erwinia amylovora, the causal agent of the fire blight disease, and Pectobacterium carotovorum, the causal agent of bacterial potato soft rot, were reported. Bacterial colonies were isolated from different ecological niches, where both pathogens were found: rhizosphere of potato tubers and fruits and leaves of pear trees from the northwest region of Algeria. Direct and indirect confrontation tests against strains of E. amylovora and P. carotovorum were performed. Results Results showed a significant antagonistic activity against both phytopathogenic species, using direct confrontation method and supernatants of cultures (p<0.005). In vitro assays showed growth inhibitions of both phytopathogenic species. Furthermore, results revealed that the strains of S. plymuthica had a better inhibitory effect than the strains of P. fluorescens against both pathogens. In vivo results on immature pear fruits showed a significant decrease in the progression of the fire blight symptoms, with a variation in the infection index from one antagonistic strain to another between 31.3 and 50%, and slice of potato showed total inhibition of the pathogen (P. carotovorum) by the antagonistic strains of Serratia plymuthica (p<0.005). Conclusion This study highlighted that the effective bacteria did not show any infection signs towards plant tissue, and considered as a potential strategy to limit the fire blight and soft rot diseases.

scholarly journals Antimicrobial Resistance among Neonates with Bacterial Sepsis and Their Clinical Outcomes in a Tertiary Hospital in Kathmandu Valley, Nepal

2021 ◽  
Vol 6 (2) ◽  
pp. 56
Author(s):  
Bijendra Raj Raghubanshi ◽  
Karuna D. Sagili ◽  
Wai Wai Han ◽  
Henish Shakya ◽  
Priyanka Shrestha ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Neonatal Sepsis ◽  
Bacterial Culture ◽  
Bacterial Species ◽  
Antibiotic Sensitivity ◽  
College Teaching ◽  
Hospital Treatment ◽  
Resistant Bacteria ◽  
Coagulase Negative Staphylococcus ◽  
Cross Sectional

Globally, antibiotic resistance in bacteria isolated from neonatal sepsis is increasing. In this cross-sectional study conducted at a medical college teaching hospital in Nepal, we assessed the antibiotic resistance levels in bacteria cultured from neonates with sepsis and their in-hospital treatment outcomes. We extracted data of neonates with sepsis admitted for in-patient care from June 2018 to December 2019 by reviewing hospital records of the neonatal intensive care unit and microbiology department. A total of 308 neonates with sepsis were admitted of which, blood bacterial culture antibiotic sensitivity reports were available for 298 neonates. Twenty neonates (7%) had bacteriologic culture-confirmed neonatal sepsis. The most common bacterial species isolated were Staphylococcus aureus (8), followed by coagulase-negative Staphylococcus (5). Most of these bacteria were resistant to at least one first-line antibiotic used to manage neonatal sepsis. Overall, there were 7 (2%) deaths among the 308 neonates (none of them from the bacterial culture-positive group), and 53 (17%) neonates had left the hospital against medical advice (LAMA). Improving hospital procedures to isolate bacteria in neonates with sepsis, undertaking measures to prevent the spread of antibiotic-resistant bacteria, and addressing LAMA’s reasons are urgently needed.

scholarly journals Label-Free Detection of Human Serum Using Surface-Enhanced Raman Spectroscopy Based on Highly Branched Gold Nanoparticle Substrates for Discrimination of Non-Small Cell Lung Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Xiaowei Cao ◽  
Zhenyu Wang ◽  
Liyan Bi ◽  
Jie Zheng
Keyword(s):  
Lung Cancer ◽  
Raman Spectroscopy ◽  
Cell Lung Cancer ◽  
Surface Enhanced Raman Spectroscopy ◽  
Small Cell ◽  
Label Free ◽  
Small Cell Lung ◽  
Surface Enhanced ◽  
Different Types ◽  
Surface Enhanced Raman

Surface-enhanced Raman spectroscopy (SERS) is a good candidate for the development of fast and easy-to-use diagnostic tools, possibly used on serum in screening tests. In this study, a potential label-free serum test based on SERS spectroscopy was developed to analyze human serum for the diagnosis of the non-small cell lung cancer (NSCLC). We firstly synthesized novel highly branched gold nanoparticles (HGNPs) at high yield through a one-step reduction of HAuCl4 with dopamine hydrochloride at 60°C. Then, HGNP substrates with good reproducibility, uniformity, and high SERS effect were fabricated by the electrostatically assisted (3-aminopropyl) triethoxysilane-(APTES-) functionalized silicon wafer surface-sedimentary self-assembly method. Using as-prepared HGNP substrates as a high-performance sensing platform, SERS spectral data of serum obtained from healthy subjects, lung adenocarcinoma patients, lung squamous carcinoma patients, and large cell lung cancer patients were collected. The difference spectra among different types of NSCLC were compared, and analysis result revealed their intrinsic difference in types and contents of nucleic acids, proteins, carbohydrates, amino acids, and lipids. SERS spectra were analyzed by principal component analysis (PCA), which was able to distinguish different types of NSCLC. Considering its time efficiency, being label-free, and sensitivity, SERS based on HGNP substrates is very promising for mass screening NSCLC and plays an important role in the detection and prevention of other diseases.

In vitro evaluation of the effect of nicotine, cotinine, and caffeine on oral microorganisms

2008 ◽  
Vol 54 (6) ◽  
pp. 501-508 ◽  
Author(s):  
Karina Cogo ◽  
Michelle Franz Montan ◽  
Cristiane de Cássia Bergamaschi ◽  
Eduardo D. Andrade ◽  
Pedro Luiz Rosalen ◽  
...  
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
Culture Media ◽  
Bacterial Species ◽  
In Vitro Study ◽  
Bacterial Strains ◽  
Planktonic Cells ◽  
Susceptibility Tests

The aim of this in vitro study was to evaluate the effects of nicotine, cotinine, and caffeine on the viability of some oral bacterial species. It also evaluated the ability of these bacteria to metabolize those substances. Single-species biofilms of Streptococcus gordonii , Porphyromonas gingivalis , or Fusobacterium nucleatum and dual-species biofilms of S. gordonii – F. nucleatum and F. nucleatum – P. gingivalis were grown on hydroxyapatite discs. Seven species were studied as planktonic cells, including Streptococcus oralis , Streptococcus mitis , Propionibacterium acnes , Actinomyces naeslundii , and the species mentioned above. The viability of planktonic cells and biofilms was analyzed by susceptibility tests and time-kill assays, respectively, against different concentrations of nicotine, cotinine, and caffeine. High-performance liquid chromatography was performed to quantify nicotine, cotinine, and caffeine concentrations in the culture media after the assays. Susceptibility tests and viability assays showed that nicotine, cotinine, and caffeine cannot reduce or stimulate bacterial growth. High-performance liquid chromatography results showed that nicotine, cotinine, and caffeine concentrations were not altered after bacteria exposure. These findings indicate that nicotine, cotinine, and caffeine, in the concentrations used, cannot affect significantly the growth of these oral bacterial strains. Moreover, these species do not seem to metabolize these substances.

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