scholarly journals Adaptive nanopore sequencing on miniature flow cell detects extensive antimicrobial resistence

2021 ◽  
Author(s):  
Adrian Viehweger ◽  
Mike Marquet ◽  
Martin Hölzer ◽  
Nadine Dietze ◽  
Mathias Pletz ◽  
...  

Rapid screening of hospital admissions to detect asymptomatic carriers of resistant bacteria can prevent pathogen outbreaks. However, the resulting isolates rarely have their genome sequenced due to cost constraints and long turn-around times to get and process the data, limiting their usefulness to the practitioner. Here we use real-time, on-device target enrichment ("adaptive") sequencing on a new type of low-cost nanopore flow cell as a highly multiplexed assay covering 1,147 antimicrobial resistance genes. Using this method, we detected four types of carbapenemase in a single isolate of Raoultella ornithinolytica (NDM, KPC, VIM, OXA). Further investigation revealed extensive horizontal gene transfer within the underlying microbial consortium, increasing the risk of resistance spreading. Real-time sequencing could thus quickly inform how to monitor this case and its surroundings.

2020 ◽  
Author(s):  
Hanh Vu ◽  
Cornelia Appiah-Kwarteng ◽  
Kaori Tanaka ◽  
Ryuji Kawahara ◽  
Diep Thi Khong ◽  
...  

Abstract Background: The dissemination of colistin-resistant bacteria carrying the colistin-resistant mobile gene, mcr-1 threatens medical care worldwide. In particular, contamination of food with colistin-resistant bacteria accelerates the community dissemination of colistin-resistant bacteria. Therefore, monitoring of colistin-resistant bacteria in food is important for controlling resistant bacteria. Unfortunately, the conventional culture methods for detecting colistin-resistant bacteria are not practical for monitoring food saftey. Therefore, development of a simple and rapid method to detect food contamination with colistin-resistant bacteria is desirable as an effective means for preventing the dissemination of resistant bacteria, particularly colistin-resistant bacteria.Findings: We developed a simple and rapid method for detecting Escherichia coli harboring the mcr-1 colistin resistance gene using a high-speed real-time polymerase chain reaction (PCR). The entire procedure, from sample processing to finals results, was performed within one hour. The practical utility of this method was verified by analyzing 27 retail meat samples for the presence of colistin-resistant bacteria. The results of the developed method were in agreement with the results of culturing colistin-resistant E. coli from the meat samples, demonstrating its efficacy and usefulness.Conclusions: A simple and rapid real-time PCR-based screening method was developed for detecting E. coli harboring mcr-1 in food samples. The practical utility of the procedure was confirmed using retail meat samples, indicating its potential as a convenient and rapid method to detect bacterial contamination of food items, especially in developing communities.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Estefania Nunez-Bajo ◽  
Alexander Silva Pinto Collins ◽  
Michael Kasimatis ◽  
Yasin Cotur ◽  
Tarek Asfour ◽  
...  

AbstractRapid screening and low-cost diagnosis play a crucial role in choosing the correct course of intervention when dealing with highly infectious pathogens. This is especially important if the disease-causing agent has no effective treatment, such as the novel coronavirus SARS-CoV-2, and shows no or similar symptoms to other common infections. Here, we report a disposable silicon-based integrated Point-of-Need transducer (TriSilix) for real-time quantitative detection of pathogen-specific sequences of nucleic acids. TriSilix can be produced at wafer-scale in a standard laboratory (37 chips of 10 × 10 × 0.65 mm in size can be produced in 7 h, costing ~0.35 USD per device). We are able to quantitatively detect a 563 bp fragment of genomic DNA of Mycobacterium avium subspecies paratuberculosis through real-time PCR with a limit-of-detection of 20 fg, equivalent to a single bacterium, at the 35th cycle. Using TriSilix, we also detect the cDNA from SARS-CoV-2 (1 pg) with high specificity against SARS-CoV (2003).


2021 ◽  
Vol 2079 (1) ◽  
pp. 012032
Author(s):  
Rui Su ◽  
Yawen Dai

Abstract In the era of the Internet of Everything, applications based on real-time location continue to appear in various industries. The indoor and outdoor positioning, analysis and management of personnel and objects can effectively improve the efficiency of production and management, which is of great significance to many industries. The use of Bluetooth beacon positioning has the advantages of low energy consumption, low cost, and fast data transmission speed. However, in real life, there are two obstacles to receiving signals, which are easily affected by the environment and the need for frequent on-site maintenance. This paper designs and implements a new type of LoRa-based smart Bluetooth beacon, which can be quickly connected to LoRa. Online monitoring and remote control can achieve better adaptation to the environment, and can fit a better signal attenuation model in the deployment environment in real time. Traditional signal strength positioning solutions have their own limitations. In order to improve the positioning accuracy of the Bluetooth beacon and the universality of the algorithm, in view of the low deployment density of beacons, the positioning accuracy is not good and the anchor circle has various situations, an optimized weighted centroid positioning scheme integrating greedy strategy is proposed.


Author(s):  
Estefania Nunez-Bajo ◽  
Michael Kasimatis ◽  
Yasin Cotur ◽  
Tarek Asfour ◽  
Alex Collins ◽  
...  

AbstractRapid screening and low-cost diagnosis play a crucial role in choosing the correct course of intervention e.g., drug therapy, quarantine, no action etc. when dealing with highly infectious pathogens. This is especially important if the disease-causing agent has no effective treatment, such as the novel coronavirus SARS-CoV-2 (the pathogen causing COVID-19), and shows no or similar symptoms to other common infections. We report a silicon-based integrated Point-of-Need (PoN) transducer (TriSilix) that can chemically-amplify and detect pathogen-specific sequences of nucleic acids (NA) quantitatively in real-time. Unlike other silicon-based technologies, TriSilix can be produced at wafer-scale in a standard laboratory; we have developed a series of methodologies based on metal-assisted chemical (wet) etching, electroplating, thermal bonding and laser-cutting to enable a cleanroom-free low-cost fabrication that does not require processing in an advanced semiconductor foundry. TriSilix is, therefore, resilient to disruptions in the global supply chain as the devices can be produced anywhere in the world. To create an ultra-low-cost device, the architecture proposed exploits the intrinsic properties of silicon and integrates three modes of operation in a single chip: i) electrical (Joule) heater, ii) temperature sensor (i.e. thermistor) with a negative temperature coefficient that can provide the precise temperature of the sample solution during reaction and iii) electrochemical sensor for detecting target NA. Using TriSilix, the sample solution can be maintained at a single, specific temperature (needed for isothermal amplification of NA such as Recombinase Polymerase Amplification (RPA) or cycled between different temperatures (with a precision of ±1.3°C) for Polymerase Chain Reaction (PCR) while the exact concentration of amplicons is measured quantitatively and in real-time electrochemically. A single 4-inch Si wafer yields 37 TriSilix chips of 10×10×0.65 mm in size and can be produced in 7 hours, costing ~US $0.35 per device. The system is operated digitally, portable and low power – capable of running up to 35 tests with a 4000 mAh battery (a typical battery capacity of a modern smartphone). We were able to quantitatively detect a 563-bp fragment (Insertion Sequence IS900) of the genomic DNA of M. avium subsp. paratuberculosis (extracted from cultured field samples) through PCR in real-time with a Limit-of-Detection of 20 fg, equivalent to a single bacterium, at the 30th cycle. Using TriSilix, we also detected the cDNA from SARS-CoV-2 (1 pg), through PCR, with high specificity against SARS-CoV (2003).


Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).


2021 ◽  
Vol 11 (11) ◽  
pp. 4940
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.


Sign in / Sign up

Export Citation Format

Share Document