Fast Identification Method Research Articles

Rapid identification of staphylococci by Raman spectroscopy

Clinical treatment of the infections caused by various staphylococcal species differ depending on the actual cause of infection. Therefore, it is necessary to develop a fast and reliable method for identification of staphylococci. Raman spectroscopy is an optical method used in multiple scientific fields. Recent studies showed that the method has a potential for use in microbiological research, too. Our work here shows a possibility to identify staphylococci by Raman spectroscopy. We present a method that enables almost 100% successful identification of 16 of the clinically most important staphylococcal species directly from bacterial colonies grown on a Mueller-Hinton agar plate. We obtained characteristic Raman spectra of 277 staphylococcal strains belonging to 16 species from a 24-hour culture of each strain grown on the Mueller-Hinton agar plate using the Raman instrument. The results show that it is possible to distinguish among the tested species using Raman spectroscopy and therefore it has a great potential for use in routine clinical diagnostics.

STRIDE: Species Tree Root Inference from Gene Duplication Events.

The correct interpretation of any phylogenetic tree is dependent on that tree being correctly rooted. We present STRIDE, a fast, effective, and outgroup-free method for identification of gene duplication events and species tree root inference in large-scale molecular phylogenetic analyses. STRIDE identifies sets of well-supported in-group gene duplication events from a set of unrooted gene trees, and analyses these events to infer a probability distribution over an unrooted species tree for the location of its root. We show that STRIDE correctly identifies the root of the species tree in multiple large-scale molecular phylogenetic data sets spanning a wide range of timescales and taxonomic groups. We demonstrate that the novel probability model implemented in STRIDE can accurately represent the ambiguity in species tree root assignment for data sets where information is limited. Furthermore, application of STRIDE to outgroup-free inference of the origin of the eukaryotic tree resulted in a root probability distribution that provides additional support for leading hypotheses for the origin of the eukaryotes.

EASI-IMS an expedite and secure technique to screen for 25I-NBOH in blotter papers.

The increasing number of new psychoactive substances (NPS) and their quick worldwide spreading, often only slightly modified in the form of new derivatives and analogues, have brought the need for fast, wide-ranging, and unequivocal identification methods in clinical and forensic investigations. Because it usually provides secure results, gas chromatography coupled to mass spectrometry (GC-MS) has been routinely employed as the standard technique for the detection of NPS in blotter papers. For 25I-NBOH (N-(2-hydroxybenzyl)-2-(4-iodo-2,5-dimethoxyphenyl)ethan-1-aminium), however, GC-MS analysis of an blotter paper extract leads to incorrect results. In this work, we investigated whether easy ambient sonic-spray mass spectrometry imaging (EASI-IMS), and ambient ionization MS method can be applied directly to the surface of the sample requiring therefore no extraction or sample preparations, would serve as an efficient, sensitive, and secure alternative for 25I-NBOH screening.

Computer software for identification of honey bee subspecies and evolutionary lineages

Within the western honey bee (Apis mellifera), there are more than 20 recognised subspecies. It is well known that these subspecies differ in their wing venation patterns. However, there is a demand for efficient tools to identify honey bee subspecies, ecotypes, populations or hybrids. The aim of this study was to develop a fast and easy identification method based on analysing forewing vein patterns of honey bees by geometric morphometrics. Reference samples for the subspecies were obtained from the Morphometric Bee Data Bank in Oberursel, Germany. These contained 187 honey bee colonies allocated into 25 subspecies from four evolutionary lineages. The identification of evolutionary lineages of honey bees based on forewing venations proved to be highly reliable, which confirms earlier studies. The accuracy of honey bee subspecies identification was less consistent and ranged from 100 to 50% and was particularly low in African honey bees. The obtained identification data were exported to the IdentiFly computer software, which is freely available.

A Novel Preunmixing Framework for Efficient Detection of Linear Mixtures in Hyperspectral Images

In order to provide reliable information about the instantaneous field of view considered in hyperspectral images through spectral unmixing, understanding the kind of mixture that occurs over each pixel plays a crucial role. In this paper, in order to detect nonlinear mixtures, a method for fast identification of linear mixtures is introduced. The proposed method does not need statistical information and performs an a priori test on the spectral linearity of each pixel. It uses standard least squares optimization to achieve estimates of the likelihood of occurrence of linear combinations of endmembers by taking advantage of the geometrical properties of hyperspectral signatures. Experimental results on both real and synthetic data sets show that the aforesaid algorithm is actually able to deliver a reliable and thorough assessment of the kind of mixtures present in the pixels of the scene.

Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine

N6-methyladenosine (m6A) refers to methylation of the adenosine nucleotide acid at the nitrogen-6 position. It plays an important role in a series of biological processes, such as splicing events, mRNA exporting, nascent mRNA synthesis, nuclear translocation and translation process. Numerous experiments have been done to successfully characterize m6A sites within sequences since high-resolution mapping of m6A sites was established. However, as the explosive growth of genomic sequences, using experimental methods to identify m6A sites are time-consuming and expensive. Thus, it is highly desirable to develop fast and accurate computational identification methods. In this study, we propose a sequence-based predictor called RAM-NPPS for identifying m6A sites within RNA sequences, in which we present a novel feature representation algorithm based on multi-interval nucleotide pair position specificity, and use support vector machine classifier to construct the prediction model. Comparison results show that our proposed method outperforms the state-of-the-art predictors on three benchmark datasets across the three species, indicating the effectiveness and robustness of our method. Moreover, an online webserver implementing the proposed predictor has been established at http://server.malab.cn/RAM-NPPS/. It is anticipated to be a useful prediction tool to assist biologists to reveal the mechanisms of m6A site functions.

A new chart-independent method for fast identification of control level of industrial processes using continuous data

A new method is developed for a fast identification of the stability situation of industrial processes. The proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. An indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual data points. It is shown that if the indication ratio comes into values between the corresponding control factor ratios, the process will be under control, and otherwise, if the indication ratio decreases to smaller than the lower control factor ratio or gets more than the upper control factor ratio, the process will be expected to be out-of-control. Validation of the method was successfully resulted using two series of quality control datasets obtained from Zarand Iron Ore Complex (Zarand, Iran) and Miduk Copper Complex (Shahr Babak, Iran). The results obtained show that the process responses predicted by the proposed method are in agreement with those indicated by the conventional chart-based method. The developed method eliminates the need for drawing the process control charts used to assess the process control level. The superiority of the proposed method over the chart-based method becomes apparent especially when a large number of control charts are necessary to be drawn and interpreted for engineering decision-making purposes.

Two-step spectral library pre-search: A novel approach for speeding up compound identification

A new method for fast compound identification in mass spectrometry based on a two-step spectral library pre-search (TSLP) algorithm is presented. The TSLP incorporated a pre-presearch step which made quick comparisons between the mass-to-charge (m/z) ratio values of an unknown query mass spectrum and those of each of the reference mass spectra. The reference mass spectra with partial spectral features matched those of the query mass spectrum were extracted from the reference library by comparing the three maximum m/z values of the query mass spectrum and those of each reference mass spectrum. In the second pre-search step, the similar mass spectra set chosen in the first step were further reduced to generate the “hit(s)” by comparing the six m/z values with highest intensity in the query mass spectrum and those of each mass spectrum extracted. Here, three evaluation indexes were used to test the performance of the method, namely the accuracy, the pre-search time and the remaining spectral numbers after the pre-search. Our results demonstrated that compared with the traditional “ten-peak” method and the cosine correlation similarity algorithm, the TSLP had three evident advantages: a) higher accuracy; b) less pre- search time; and c) fewer remaining mass spectra.

Simple and Fast Method for Identification and Quantification of Anthocyanidins in Berries by Ultra Performance Liquid Chromatography-Mass Spectrometry

The objective was identifying three different anthocyanidins and to quantify them in six different berries. Results from the conventional method (using extraction with hydrochloric acid) were compared with data from the proposed method (without acid extraction). The following figures of merit were used: linearity, accuracy, linear range, limits of detection and quantification, using an ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole mass spectrometer equipped with an electrospray ionization source. The separation of anthocyanidins can be achieved in a much smaller period of time (1.30 min) and the cyanidin from Morus nigra L., Rubus idaeus L. and Vaccinium myrtillus L. was found in higher amounts in extracts obtained from the proposed method. Proposed mechanisms of mass spectrometry (MS/MS) collisional induced dissociation for pelargonidin, cyanidin and delphinidin were obtained and this is the first time that concentrations of anthocyanidins present in fruits of Solanum americanum Mill. were reported.

Space charge observation under periodic stresses — Part 1: The simplest system and corresponding phase identification

The simplest space charge measurement system is introduced for the direct space charge observation under arbitrary periodic stresses. An essential component of the system is the frequency allocation strategy for periodic stress fa and detection source fp. This strategy is based on the modified automatic equal phase shift (AEPS) principle, in which the relationship between fa and fp can be an integral multiple and a non-integral multiple. The phase detection in the range of 0°–360° can be completed during Na cycles of periodic stress with Np detected excitation to realize phase resolution Δ' = 2π/Np. Two different allocation strategies, namely, Na = 1 for the integral multiple between fa and fp and Na > 1 for the non-integral multiple between fa and fp, can be used to realize a high-phase resolution with consideration of the available frequency range for the detected source. Phase monitoring can be realized with the discrete voltage Va(i) of periodic stress at the detection phase and with the peak voltage Vg(i) of the raw signal representing the space charge density of the ground electrode. Phase delay is also introduced between the monitoring signal and real phase to avoid phase errors, especially at a high frequency and electric field. The detection phase of the space charge can be accurately identified through the monitoring signal via the data fitting or the Hilbert transform using the base wave component acquired with the Fourier transform. However, the data processing is complex for both methods. Thus, a simple and fast identification method is presented on the basis of the characteristic sequence of the AEPS principle. Finally, the feasibility and accuracy of the proposed system are successfully verified through the direct detection of the space charge within low-density polyethylene under several practical periodic stresses, namely, AC wave at 0.01 Hz, square wave at 1 kHz, and harmonic wave at 10 kHz.

PLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.

One of the fundamental goals in cellular biochemistry is to identify the functions of proteins in the context of compartments that organize them in the cellular environment. To realize this, it is indispensable to develop an automated method for fast and accurate identification of the subcellular locations of uncharacterized proteins. The current study is focused on plant protein subcellular location prediction based on the sequence information alone. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most of the existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions. This kind of multiplex protein is particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called "pLoc-mPlant" by extracting the optimal GO (Gene Ontology) information into the Chou's general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validation on the same stringent benchmark dataset indicated that the proposed pLoc-mPlant predictor is remarkably superior to iLoc-Plant, the state-of-the-art method for predicting plant protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at , by which users can easily get their desired results without the need to go through the complicated mathematics involved.

Collision-induced dissociation of sodiated glucose and identification of anomeric configuration.

Collision-induced dissociation (CID) of sodiated glucose was investigated using electronic structure calculations and resonance excitation in a low-pressure linear ion trap. The major dissociation channels in addition to desodiation are dehydration and C2H4O2 elimination reactions which the barrier heights are near to or lower than the sodiation energy of glucose. Dehydration reaction involves the transfer of the H atom from the O2 atom to the O1 atom, followed by the cleavage of the C1-O1 bond. Notably, α-glucose has a dehydration barrier lower than that of β-glucose. This difference results in the larger branching ratio of dehydration reactions involving α-glucose, which provides a simple and fast method for identifying the anomeric configurations of glucose. The C2H4O2 elimination starts from the H atom transfer from the O1 atom to the O0 atom, followed by the cleavage of the C1-O0 bond. These results were further confirmed by experimental study using 18O-isotope-labeled compounds. Both the experimental data and theoretical calculations suggest that the dehydration reaction and cross-ring dissociation of sodiated carbohydrates mainly occur at the reducing end during low-energy CID.

Fast and simple method for identification of adulteration of cow's milk with urea using diffuse reflectance spectroscopy

This work describes the development and application of a simple, fast, cheap, and clean method for the detection of adulteration of raw cow's milk by urea, using a combined spot test/diffuse reflectance spectroscopy procedure.

Surface-enhanced Raman spectroscopy introduced into the International Standard Organization (ISO) regulations as an alternative method for detection and identification of pathogens in the food industry

We show that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) can serve as a fast, reliable, and easy method for detection and identification of food-borne bacteria, namely Salmonella spp., Listeria monocytogenes, and Cronobacter spp., in different types of food matrices (salmon, eggs, powdered infant formula milk, mixed herbs, respectively). The main aim of this work was to introduce the SERS technique into three ISO (6579:2002; 11290–1:1996/A1:2004; 22964:2006) standard procedures required for detection of these bacteria in food. Our study demonstrates that the SERS technique is effective in distinguishing very closely related bacteria within a genus grown on solid and liquid media. The advantages of the proposed ISO-SERS method for bacteria identification include simplicity and reduced time of analysis, from almost 144 h required by standard methods to 48 h for the SERS-based approach. Additionally, PCA allows one to perform statistical classification of studied bacteria and to identify the spectrum of an unknown sample. Calculated first and second principal components (PC-1, PC-2) account for 96, 98, and 90% of total variance in the spectra and enable one to identify the Salmonella spp., L. monocytogenes, and Cronobacter spp., respectively. Moreover, the presented study demonstrates the excellent possibility for simultaneous detection of analyzed food-borne bacteria in one sample test (98% of PC-1 and PC-2) with a goal of splitting the data set into three separated clusters corresponding to the three studied bacteria species. The studies described in this paper suggest that SERS represents an alternative to standard microorganism diagnostic procedures.Graphical New approach of the SERS strategy for detection and identification of food-borne bacteria, namely S. enterica, L. monocytogenes, and C. sakazakii in selected food matrices

Abstract A017: Method for molecular characterization of antigens, epitopes and T cell receptors for adoptive CD4 immunotherapy

Abstract Recent advances in cellular immunotherapy show that cancer cells can be efficiently eliminated by adoptive transfer of modified patient T cells. The main effector functions can be provided by genetically engineered lymphocytes expressing T cell receptors (TCR) isolated from tumor antigen-specific cytotoxic CD8+ lymphocytes, which recognize tumor-associated antigens presented on HLA class I molecules. Nevertheless, for efficient and sustained cytotoxic and memory CD8+ T cell responses, T cell help delivered by CD4+ T lymphocytes plays a critical role. Multifunctional CD4+ T cells are essential to activate, control and maintain immune responses. CD4+ T cells recognize antigen-derived peptides presented by HLA class II molecules, thereby HLA class II tumor antigen-positive cells may also be efficiently eliminated by direct CD4+ cytotoxic mechanisms. Recently it has been shown that adoptive transfer of tumor antigen-specific CD4+ T cells alone can lead to substantial regression of epithelial tumors (Science. 2014 May 9;344(6184):641-5). To appropriately employ CD4+ T cells in tumor defense, detailed molecular knowledge regarding the antigens and corresponding epitopes they recognize is essential. We recently expanded our TCR platform by introducing a fast and efficient method for direct identification of antigens and respective epitopes recognized by CD4+ T cells. During method development, elucidated viral antigens allowed rapid clinical application, and the methodology was also applied for rapid identification of epitopes of CD4+ T cell clones recognizing multiple cancer-testis antigens (CT). For this, PBL from a healthy donor were stimulated with a mixture of autologous APCs transfected with in vitro transcribed RNA encoding various CT antigens fused to targeting signals for directed HLA class II cross-presentation. Antigen-reactive CD4+ T cells were isolated and expanded. In order to identify the antigen and epitope specificity of each T cell clone, DNA sequences of each CT antigen were randomly digested and DNA fragments introduced in a vector mixture that allows expression of the fragments in all possible reading frames fused to a bacterial selection marker. These vectors were then expressed in XL1 blue bacteria and fed as pools to autologous APCs. Thereby the APCs phagocytosed and directly presented random CT epitopes on their HLA class II molecules. Subsequently, these pool-loaded APCs were tested with CT-antigen-specific CD4+ T cell clones. In a second step, the single bacterial colonies of a positive pool were re-tested individually and the antigen fragments recognized were identified by DNA sequencing, and confirmed by testing of synthetic peptides. HLA restriction was determined by testing responses against antigen-positive HLA allogenic cells. Using this approach, TCR sequences, epitope sequences and respective MHC-restriction elements were identified for multiple antigens in a single round procedure. This method has broad application for identification of: 1) antigens and epitopes recognized by CD4 tumor infiltrating lymphocytes, 2) immune relevant patient-specific mutations recognized by CD4+ T cells, 3) defined epitopes recognized by T helper cells for generation of tumor vaccines, 4) epitope-specificity of CD4+ T cells, against any selected antigen. This technology enables the generation and molecular characterization of TCRs originating from tumor-specific CD4+ helper T cells, complementing our already established approach for isolation of high affinity TCRs derived from cytotoxic CD8+ T cells. Citation Format: Milosevic Slavoljub, Ellinger Christian, Wehner Carina, Raffegerst Silke, Wilde Susanne, Weis Manon, Sailer Nadja, Schendel Dolores. Method for molecular characterization of antigens, epitopes and T cell receptors for adoptive CD4 immunotherapy [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A017.

Arbovirus and insect-specific virus discovery in Kenya by novel six genera multiplex high-resolution melting analysis.

A broad diversity of arthropod-borne viruses (arboviruses) of global health concern are endemic to East Africa, yet most surveillance efforts are limited to just a few key viral pathogens. Additionally, estimates of arbovirus diversity in the tropics are likely to be underestimated as their discovery has lagged significantly over past decades due to limitations in fast and sensitive arbovirus identification methods. Here, we developed a nearly pan-arbovirus detection assay that uses high-resolution melting (HRM) analysis of RT-PCR products from highly multiplexed assays to differentiate broad diversities of arboviruses. We differentiated 15 viral culture controls and seven additional synthetic viral DNA sequence controls, within Flavivirus, Alphavirus, Nairovirus, Phlebovirus, Orthobunyavirus and Thogotovirus genera. Among Bunyamwera, sindbis, dengue and Thogoto virus serial dilutions, detection by multiplex RT-PCR-HRM was comparable to the gold standard Vero cell plaque assays. We applied our low-cost method for enhanced broad-range pathogen surveillance from mosquito samples collected in Kenya and identified diverse insect-specific viruses, including a new clade in anopheline mosquitoes, and Wesselsbron virus, an arbovirus that can cause viral haemorrhagic fever in humans and has not previously been isolated in Kenya, in Culex spp. and Anopheles coustani mosquitoes. Our findings demonstrate how multiplex RT-PCR-HRM can identify novel viral diversities and potential disease threats that may not be included in pathogen detection panels of routine surveillance efforts. This approach can be adapted to other pathogens to enhance disease surveillance and pathogen discovery efforts, as well as the study of pathogen diversity and viral evolutionary ecology.

Identification of Stachybotrys spp. by MALDI-TOF mass spectrometry

Stachybotrys (S.) spp. are omnipresent cellulolytic molds. Some species are highly toxic owing to their ability to synthesize various secondary metabolites such as macrocyclic trichothecenes or hemolysins. The reliable identification of Stachybotrys at species level is currently limited to genome-based identification. This study aimed to establish a fast and reliable MALDI-TOF MS identification method by optimizing the pre-analytical steps for protein extraction for subsequent generation of high-quality fingerprint mass spectra. Eight reference strains of the American Type Culture Collection and the Technical University of Denmark were cultivated in triplicate (biological repetitions) for 2days in malt extract broth. The mycelia (1.5ml) were first washed with 75% ethanol and an additional washing step with dimethyl sulfoxide (10%) was added to remove unspecific low weight masses. Furthermore, mycelia were broken with roughened glass beads in formic acid (70%) and acetonitrile. The method was successfully applied to a total of 45 isolates of Stachybotrys originating from three different habitats (indoor, feed, and food samples; n = 15 each): Twenty-seven isolates of S. chartarum and 18 isolates of S. chlorohalonata could be identified by MALDI-TOF MS. The data obtained exactly matched those obtained by genome-based identification. The mean score values for S. chartarum ranged from 2.509 to 2.739 and from 2.148 to 2.622 for S. chlorohalonata with a very good reproducibility: the relative standard deviations were between 0.3% and 6.8%. Thus, MALDI-TOF MS proved to be a fast and reliable alternative to identification of Stachybotrys spp. by nucleotide amplification and sequencing.

HattCI: Fast and Accurate attC site Identification Using Hidden Markov Models.

Integrons are genetic elements that facilitate the horizontal gene transfer in bacteria and are known to harbor genes associated with antibiotic resistance. The gene mobility in the integrons is governed by the presence of attC sites, which are 55 to 141-nucleotide-long imperfect inverted repeats. Here we present HattCI, a new method for fast and accurate identification of attC sites in large DNA data sets. The method is based on a generalized hidden Markov model that describes each core component of an attC site individually. Using twofold cross-validation experiments on a manually curated reference data set of 231 attC sites from class 1 and 2 integrons, HattCI showed high sensitivities of up to 91.9% while maintaining satisfactory false-positive rates. When applied to a metagenomic data set of 35 microbial communities from different environments, HattCI found a substantially higher number of attC sites in the samples that are known to contain more horizontally transferred elements. HattCI will significantly increase the ability to identify attC sites and thus integron-mediated genes in genomic and metagenomic data. HattCI is implemented in C and is freely available at http://bioinformatics.math.chalmers.se/HattCI .

Optimal design of solvents for extractive reaction processes

It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3238–3249, 2016

Specific Magnetic Isolation of E6 HPV16 Modified Magnetizable Particles Coupled with PCR and Electrochemical Detection.

The majority of carcinomas that were developed due to the infection with human papillomavirus (HPV) are caused by high-risk HPV types, HPV16 and HPV18. These HPV types contain the E6 and E7 oncogenes, so the fast detection of these oncogenes is an important point to avoid the development of cancer. Many different HPV tests are available to detect the presence of HPV in biological samples. The aim of this study was to design a fast and low cost method for HPV identification employing magnetic isolation, polymerase chain reaction (PCR) and electrochemical detection. These assays were developed to detect the interactions between E6-HPV16 oncogene and magnetizable particles (MPs) using commercial Dynabeads M-280 Streptavidin particles and laboratory-synthesized “homemade” particles called MANs (MAN-37, MAN-127 and MAN-164). The yields of PCR amplification of E6-HPV16 oncogene bound on the particles and after the elution from the particles were compared. A highest yield of E6-HPV16 DNA isolation was obtained with both MPs particles commercial M-280 Streptavidin and MAN-37 due to reducing of the interferents compared with the standard PCR method. A biosensor employing the isolation of E6-HPV16 oncogene with MPs particles followed by its electrochemical detection can be a very effective technique for HPV identification, providing simple, sensitive and cost-effective analysis.