Detection Of Sequences Research Articles

Genomes of a Novel Group of Phages That Use Alternative Genetic Code Found in Human Gut Viromes.

Metagenomics provides detection of phage genome sequences in various microbial communities. However, the use of alternative genetic codes by some phages precludes the correct analysis of their genomes. In this study, the unusual phage genome (phAss-1, 135,976 bp) was found after the de novo assembly of the human gut virome. Genome analysis revealed the presence of the TAG stop codons in 41 ORFs, including characteristic phage ORFs, and three genes of suppressor tRNA. Comparative analysis indicated that no phages with similar genomes were described. However, two phage genomes (BK046881_ctckW2 and BK025033_ct6IQ4) with substantial similarity to phAss-1 were extracted from the human gut metagenome data. These two complete genomes demonstrated 82.7% and 86.4% of nucleotide identity, respectively, similar genome synteny to phAss-1, the presence of suppressor tRNA genes and suppressor TAG stop codons in many characteristic phage ORFs. These data indicated that phAss-1, BK046881_ctckW2, and BK025033_ct6IQ4 are distinct species within the proposed Phassvirus genus. Moreover, a monophyletic group of divergent phage genomes containing the proposed Phassvirus genus was found among metagenome data. Several phage genomes from the group also contain ORFs with suppressor TAG stop codons, indicating the need to use various translation tables when depositing phage genomes in GenBank.

Implementation, Evolution, and Laboratory Performance of Methods-Based Proficiency Testing for Next-Generation Sequencing Detection of Germline Sequence Variants.

Next-generation sequencing (NGS)-based assays are used for diagnosis of diverse inherited disorders. Limited data are available pertaining to interlaboratory analytical performance of these assays. To report on the College of American Pathologists (CAP) NGS Germline Program, which is methods based, and explore the evolution in laboratory testing practices. Results from the NGS Germline Program from 2016-2020 were analyzed for interlaboratory analytical performance. Self-reported laboratory testing practices were also evaluated. From 2016-2020, a total of 297 laboratories participated in at least 1 program mailing. Of the 289 laboratories that provided information on tests offered, 138 (47.8%) offered only panel testing throughout their enrollment, while 35 (12.1%) offered panels and exome testing, 30 (10.4%) offered only exomes, 9 (3.1%) offered only genomes, and 15 (5.2%) offered panels, exomes, and genomes. The remainder (62 laboratories, 21.4%) changed their test offerings during the 2016-2020 timeframe. Considering each genomic position/interval, the median detection percentage at variant positions across the 2016-2020 mailings ranged from 94.3% to 100%, while at reference positions (no variant detected), the median correct response percentage was 100% across all mailings. When considering performance of individual laboratories, 89.5% (136 of 152) to 98.0% (149 of 152) of laboratories successfully met the detection threshold (≥90% of the variants present), while 94.6% (87 of 92) to 100% (163 of 163) of laboratories met the 95% specificity threshold across mailings. Since the inception of this program, laboratories have consistently performed well. The median sensitivity and specificity of detection of sequence variants included in this program (eg, single nucleotide variants, insertions, and deletions) were 100.0%.

The Potential Hypoglycemic Competence of Low Molecular Weight Polysaccharides Obtained from Laminaria japonica.

This study aimed to assess the hypoglycemic efficacy of low molecular weight polysaccharides fractions obtained from Laminaria japonica (LJOO) in a model of type 2 diabetes mellitus (T2DM) constructed using mice. Biochemical parameters were measured after 4 weeks of continuous gavage, and fasting blood glucose (FBG) concentrations were analyzed. Pathological changes in tissues were assessed. The intestinal contents were obtained for 16S rDNA high-throughput sequencing analysis and detection of short-chain fatty acids (SCFAs). LJOO lowered FBG and insulin concentrations. It altered the gut microbiota composition, as evidenced by enriched probiotic bacteria, along with an increase in the Bacteroidetes/Firmicutes ratio and a decrease in the population of harmful bacteria. LJOO stimulated the growth of SCFA-producing bacteria, thereby increasing cecal SCFAs levels. LJOO can potentially aid in alleviating T2DM and related gut microbiota dysbiosis. LJOO may be used as a food supplement for patients with T2DM.

Revolutionizing Medical Microbiology: How Molecular and Genomic Approaches Are Changing Diagnostic Techniques.

Molecular and genomic approaches have revolutionized medical microbiology by offering faster and more accurate diagnostic techniques for infectious diseases. Traditional methods, which include culturing microbes and biochemical testing, are time-consuming and may not detect antibiotic-resistant strains. In contrast, molecular and genomic methods, including polymerase chain reaction (PCR)-based techniques and whole-genome sequencing, provide rapid and precise detection of pathogens, early-stage diseases, and antibiotic-resistant strains. These approaches have advantages such as high sensitivity and specificity, the potential for targeted therapies, and personalized medicine. However, implementing molecular and genomic techniques faces challenges related to cost, equipment, expertise, and data analysis. Ethical and legal considerations regarding patient privacy and genetic data usage also arise. Nonetheless, the future of medical microbiology lies in the widespread adoption of molecular and genomic approaches, which can lead to improved patient outcomes and the identification of antibiotic-resistant strains. Continued advancements, education, and exploration of ethical implications are necessary to fully harness the potential of molecular and genomic techniques in medical microbiology.

Development of a nucleic acid-based screen printed electrochemical biosensor using Ti3C2Tx-MXene for the detection of SARS-CoV-2

The SARS-CoV-2 virus poses a major risk to human health which has put a tremendous strain on already stretched healthcare resources. Despite continuous improvements in Coronavirus Disease-19 (COVID-19) detection, treatment technology and ongoing global immunization efforts, the lethal virus has undergone several mutations and is still claiming millions of lives worldwide. In this respect, the development of a hybridization-based nucleic acid biosensor for SARS-CoV-2 virus is the major focus of the current effort in response to the critical demand for developing quick and accurate diagnostic methods. Herein, we employ Screen Printed Carbon Electrode (SPCE) coated with Ti3C2Tx-MXene nanosheets followed by amino-functionalized probe DNA (NH2-pDNA) as a robust surface for the sensing of SARS-CoV-2. Electrochemical impedance spectroscopy, cyclic voltammetry and differential pulse voltammetry were employed for assessing the electrochemical behavior of NH2-pDNA/Ti3C2Tx/SPCE bioelectrode. Meanwhile, the analytical sensor response for SARS-CoV-2 was studied using impedance within target DNA concentration of 0.1 pM − 1 µM. The developed biosensor displayed detection limit of 0.004 pM, showing a high degree of selectivity in the presence of non-complementary interferents with a shelf life of 40 days. Additionally, a good linearity for the detection of target sequence in spiked serum samples was established; as a result, exhibiting huge potential for use in the contemporary healthcare sector for fast, accurate and reliable diagnosis of COVID-19 in a point-of-care scenario.

Detection of wildtype Merkel cell polyomavirus genomic sequence and VP1 transcription in a subset of Merkel cell carcinoma.

Merkel cell carcinoma (MCC) is frequently caused by the Merkel cell polyomavirus (MCPyV). Characteristic for these virus-positive (VP) MCC is MCPyV integration into the host genome and truncation of the viral oncogene Large T antigen (LT), with full-length LT expression considered as incompatible with MCC growth. Genetic analysis of a VP-MCC/trichoblastoma combined tumour demonstrated that virus-driven MCC can arise from an epithelial cell. Here we describe two further cases of VP-MCC combined with an adnexal tumour, i.e. one trichoblastoma and one poroma. Whole-genome sequencing of MCC/trichoblastoma again provided evidence of a trichoblastoma-derived MCC. Although an MCC-typical LT-truncating mutation was detected, we could not determine an integration site and we additionally detected a wildtype sequence encoding full-length LT. Similarly, Sanger sequencing of the combined MCC/poroma revealed coding sequences for both truncated and full-length LT. Moreover, in situ RNA hybridization demonstrated expression of a late region mRNA encoding the viral capsid protein VP1 in both combined as well as in a few cases of pure MCC. The data presented here suggest the presence of wildtype MCPyV genomes and VP1 transcription in a subset of MCC.

Harnessing environmental DNA to reveal biogeographical patterns of non-indigenous species for improved co-governance of the marine environment in Aotearoa New Zealand

Aotearoa New Zealand’s Northern region is a major gateway for the incursion and establishment of non-indigenous species (NIS) populations due to high numbers of recreational and commercial vessels. This region also holds a unique marine ecosystem, home to many taonga (treasured) species of cultural and economic importance. Regular surveillance, eradication plans and public information sharing are undertaken by local communities and governmental organizations to protect these ecosystems from the impact of NIS. Recently, considerable investments went into environmental DNA (eDNA) research, a promising approach for the early detection of NIS for complementing existing biosecurity systems. We applied eDNA metabarcoding for elucidating bioregional patterns of NIS distributions across a gradient from harbors (NIS hotspots) to open seas (spreading areas). Samples were collected during a research cruise sailing across three Aotearoa New Zealand harbors, Waitematā, Whangārei and Pēwhairangi (Bay of Islands), and their adjacent coastal waters. The small-ribosomal subunit (18S rRNA) and mitochondrial cytochrome c oxidase I (COI) genes were screened using the online Pest Alert Tool for automated detection of putative NIS sequences. Using a probabilistic modelling approach, location-dependent occupancies of NIS were investigated and related to the current information on species distribution from biosecurity surveillance programs. This study was collaboratively designed with Māori partners to initiate a model of co-governance within the existing science system.

Validation and comparison of four DNA extraction methods for genetically modified organisms analysis: From DNA quality control to quantification of genetically modified content in real‐life samples matrices

AbstractBackgroundThe analysis of genetically modified organisms (GMOs) in food and feed is broadly based on the detection of target DNA sequences using PCR‐based methods. The first step of a typical workflow in a GMO testing laboratory is DNA extraction and purification. Several DNA extraction methods have been described for this purpose so far. Whatever the method adopted, the yield and the quality of the extracted DNA are essential factors for the success of GMO analysis.ResultsThe DNA extraction yield was variable between the different methods, while quality and efficiency appeared comparable. Each method allowed a different yield and a slight correlation between inhibition and the food/feed matrix extracted was observed. Particularly for challenging matrices, the method used for DNA extraction has a remarkable influence on both the quality and quantity of the recovered DNA. Small variations in value % GM content were observed in complex, heterogeneous matrices but not in CRMs and homogeneous matrices.ConclusionsIn this study, the purpose is not to establish the best method of extraction but to examine several parameters that play an important role in GMO detection and verify a possible effect on the quantified GMO percentage. In particular, it was found that the yield and quality of extracted DNA depends on the type of sample, notably the degree of processing, composition, particle size, and the protocol used, especially in relation to sample intake. The slightly different GM content observed in heterogeneous matrices could raise doubt in the case of samples close to the legal threshold.

CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks.

Changes in coronary artery luminal dimensions during the cardiac cycle can impact the accurate quantification of volumetric analyses in intravascular ultrasound (IVUS) image studies. Accurate ED-frame detection is pivotal for guiding interventional decisions, optimizing therapeutic interventions, and ensuring standardized volumetric analysis in research studies. Images acquired at different phases of the cardiac cycle may also lead to inaccurate quantification of atheroma volume due to the longitudinal motion of the catheter in relation to the vessel. As IVUS images are acquired throughout the cardiac cycle, end-diastolic frames are typically identified retrospectively by human analysts to minimize motion artefacts and enable more accurate and reproducible volumetric analysis. In this paper, a novel neural network-based approach for accurate end-diastolic frame detection in IVUS sequences is proposed, trained using electrocardiogram (ECG) signals acquired synchronously during IVUS acquisition. The framework integrates dedicated motion encoders and a bidirectional attention recurrent network (BARNet) with a temporal difference encoder to extract frame-by-frame motion features corresponding to the phases of the cardiac cycle. In addition, a spatiotemporal rotation encoder is included to capture the IVUS catheter's rotational movement with respect to the coronary artery. With a prediction tolerance range of 66.7 ms, the proposed approach was able to find 71.9%, 67.8%, and 69.9% of end-diastolic frames in the left anterior descending, left circumflex and right coronary arteries, respectively, when tested against ECG estimations. When the result was compared with two expert analysts' estimation, the approach achieved a superior performance. These findings indicate that the developed methodology is accurate and fully reproducible and therefore it should be preferred over experts for end-diastolic frame detection in IVUS sequences.

Improved performance of nucleic acid-based assays for genetically diverse norovirus surveillance.

Nucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of their genetic diversity. Here, we calculated the variability of nucleotides within the genomes of 10 human viral species in silico and found that endemic viruses exhibit a high percentage of variable nucleotides (e.g., 51.4% for norovirus genogroup II). This genetic diversity led to the variable probability of detection of PCR assays (the proportion of viral sequences that contain the assay's target sequences divided by the total number of viral sequences). We then experimentally confirmed that the probability of the target sequence detection is indicative of the number of mismatches between PCR assays and norovirus genomes. Next, we developed a degenerate PCR assay that detects 97% of known norovirus genogroup II genome sequences and recognized norovirus in eight clinical samples. By contrast, previously developed assays with 31% and 16% probability of detection had 1.1 and 2.5 mismatches on average, respectively, which negatively impacted RNA quantification. In addition, the two PCR assays with a lower probability of detection also resulted in false negatives for wastewater-based epidemiology. Our findings suggest that the probability of detection serves as a simple metric for evaluating nucleic acid-based assays for genetically diverse virus surveillance. IMPORTANCE Nucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are employed widely as a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of the rapid evolution and genetic variation of viruses. The study analyzed clinical and wastewater samples using multiple PCR assays and found significant performance variation among the PCR assays for genetically diverse norovirus surveillance. This finding suggests that some PCR assays may miss detecting certain virus strains, leading to a compromise in detection sensitivity. To address this issue, we propose a metric called the probability of detection, which can be simply calculated in silico using a code developed in this study, to evaluate nucleic acid-based assays for genetically diverse virus surveillance. This new approach can help improve the sensitivity and accuracy of virus detection, which is crucial for effective infectious disease surveillance and control.

Nucleic-acid-triggered NADase activation of a short prokaryotic Argonaute.

Argonaute (Ago) proteins mediate RNA- or DNA-guided inhibition of nucleic acids1,2. Although the mechanisms used by eukaryotic Ago proteins and long prokaryotic Ago proteins (pAgos) are known, that used by short pAgos remains elusive. Here we determined the cryo-electron microscopy structures of a short pAgo and the associated TIR-APAZ proteins (SPARTA) from Crenotalea thermophila (Crt): a free-state Crt-SPARTA; a guide RNA-target DNA-loaded Crt-SPARTA; two Crt-SPARTA dimers with distinct TIR organization; and a Crt-SPARTA tetramer. These structures reveal that Crt-SPARTA is composed of a bilobal-fold Ago lobe that connects with a TIR lobe. Whereas the Crt-Ago contains a MID and a PIWI domain, Crt-TIR-APAZ has a TIR domain, an N-like domain, a linker domain and a trigger domain. The bound RNA-DNA duplex adopts a B-form conformation that is recognized by base-specific contacts. Nucleic acid binding causes conformational changes because the trigger domain acts as a 'roadblock' that prevents the guide RNA 5' ends and the target DNA 3' ends from reaching their canonical pockets; this disorders the MID domain and promotes Crt-SPARTA dimerization. Two RNA-DNA-loaded Crt-SPARTA dimers form a tetramer through their TIR domains. Four Crt-TIR domains assemble into two parallel head-to-tail-organized TIR dimers, indicating an NADase-active conformation, which is supported by our mutagenesis study. Our results reveal the structural basis of short-pAgo-mediated defence against invading nucleic acids, and provide insights for optimizing the detection of SPARTA-based programmable DNA sequences.

Solid-State Single-Molecule Sensing with the Electronic Life-Detection Instrument for Enceladus/Europa (ELIE).

Growing evidence of the potential habitability of Ocean Worlds across our solar system is motivating the advancement of technologies capable of detecting life as we know it-sharing a common ancestry or physicochemical origin with life on Earth-or don't know it, representing a distinct emergence of life different than our one known example. Here, we propose the Electronic Life-detection Instrument for Enceladus/Europa (ELIE), a solid-state single-molecule instrument payload that aims to search for life based on the detection of amino acids and informational polymers (IPs) at the parts per billion to trillion level. As a first proof-of-principle in a laboratory environment, we demonstrate the single-molecule detection of the amino acid L-proline at a 10 μM concentration in a compact system. Based on ELIE's solid-state quantum electronic tunneling sensing mechanism, we further propose the quantum property of the HOMO-LUMO gap (energy difference between a molecule's highest energy-occupied molecular orbital and lowest energy-unoccupied molecular orbital) as a novel metric to assess amino acid complexity. Finally, we assess the potential of ELIE to discriminate between abiotically and biotically derived α-amino acid abundance distributions to reduce the false positive risk for life detection. Nanogap technology can also be applied to the detection of nucleobases and short sequences of IPs such as, but not limited to, RNA and DNA. Future missions may utilize ELIE to target preserved biosignatures on the surface of Mars, extant life in its deep subsurface, or life or its biosignatures in a plume, surface, or subsurface of ice moons such as Enceladus or Europa. One-Sentence Summary: A solid-state nanogap can determine the abundance distribution of amino acids, detect nucleic acids, and shows potential for detecting life as we know it and life as we don't know it.

Detection of COVID-19 Using Protein Sequence Data via Machine Learning Classification Approach

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019 resulted in the COVID-19 pandemic, necessitating rapid and accurate detection of pathogens through protein sequence data. This study is aimed at developing an efficient classification model for coronavirus protein sequences using machine learning algorithms and feature selection techniques to aid in the early detection and prediction of novel viruses. We utilized a dataset comprising 2000 protein sequences, including 1000 SARS-CoV-2 sequences and 1000 non-SARS-CoV-2 sequences. Feature extraction provided 27 essential features representing the primary structural data, achieved through the Discere package. To optimize performance, we employed machine learning classification algorithms such as K-nearest neighbor (KNN), XGBoost, and Naïve Bayes, along with feature selection techniques like genetic algorithm (GA), LASSO, and support vector machine recursive feature elimination (SVM-RFE). The SVM-RFE+KNN model exhibited exceptional performance, achieving a classification accuracy of 99.30%, specificity of 99.52%, and sensitivity of 99.55%. These results demonstrate the model’s efficacy in accurately classifying coronavirus protein sequences. Our research successfully developed a robust classification model capable of early detection and prediction of protein sequences in SARS-CoV-2 and other coronaviruses. This advancement holds great promise in facilitating the development of targeted treatments and preventive strategies for combating future viral outbreaks.

B-234 The Quality in NGS: Do You Know How Much We Lost?

Abstract Background Next generation sequencing (NGS) is a new high throughput approach for genomic sequencing and variations detection. The consumption of NGS is numerous, such as times, money and human resource, therefore, some hospitals provided the service but delivered the specimen to other laboratories. Hence, we aimed to establish a procedure to monitor the quality and integrity of report. Method Here we used one clinical case to elucidate the whole process of raw sequence data analysis by free resource, a website usegalaxy.org and the IGV visualization software, with flowchart and quality control (QC) items. A delivered case will be an example to show how to monitor the QC. Results The flow chart showed the whole steps of analysis of NGS, including evaluation genetic variants in the report from individual laboratory. We processed the FASTQ file and analyzed the quality with three parameters. An overall picture of bases showed the phred score (QV) less than 28. Distribution of sequence lengths over all sequences highlighted a prominent peak at 110–119 bp. The mean QV of reads was around 26 with low quality (QV less than 20) in some reads. We then filtered the FASTQ file and the reads with length less than 45 bp or greater than 150 bp and QV less than 20 were filtered out. The data of the BAM file mapped to the designed panel were output. There were 8252 genome regions designed over 23 chromosomes (chr). A total number of reads was 1 085 653 with the average 131.6 reads (range: 0–31034; quartiles, IQ25: 1; IQ50: 27; IQ75: 152). 7746 of designed genome regions (93.9%) had reads less than 500 (quartiles, IQ25: 0; IQ50: 20; IQ75: 118). We further used IGV to check one of mutations which showed KRAS G12V in the report. KRAS G12V (chr.12: 25245350) was read 25 times with the variant allele frequency (C to A) of 24%. Conclusion We showed how to monitor the NGS quality by free resource. It is important to ensure high-quality data after we received the individual laboratory reports. That may help increase the quality of patient care and clinical service.

Multi-Omics Analysis Reveals Age-Related Microbial and Metabolite Alterations in Non-Human Primates.

Aging is a systemic physiological degenerative process, with alterations in gut microbiota and host metabolism. However, due to the interference of multiple confounding factors, aging-associated molecular characteristics have not been elucidated completely. Therefore, based on 16S ribosomal RNA (rRNA) gene sequencing and non-targeted metabolomic detection, our study systematically analyzed the composition and function of the gut microbiome, serum, and fecal metabolome of 36 male rhesus monkeys spanning from 3 to 26 years old, which completely covers juvenile, adult, and old stages. We observed significant correlations between 41 gut genera and age. Moreover, 86 fecal and 49 serum metabolites exhibited significant age-related correlations, primarily categorized into lipids and lipid-like molecules, organic oxygen compounds, organic acids and derivatives, and organoheterocyclic compounds. Further results suggested that aging is associated with significant downregulation of various amino acids constituting proteins, elevation of lipids, particularly saturated fatty acids, and steroids. Additionally, age-dependent changes were observed in multiple immune-regulatory molecules, antioxidant stress metabolites, and neurotransmitters. Notably, multiple age-dependent genera showed strong correlations in these changes. Together, our results provided new evidence for changing characteristics of gut microbes and host metabolism during aging. However, more research is needed in the future to verify our findings.

Highly specific and sensitive sandwich-type electrochemiluminescence biosensor for HPV16 DNA detection based on the base-stacking effect and bovine serum albumin carrier platform

The detection of specific DNA sequences and the identification of single nucleotide polymorphisms are important for disease diagnosis. Herein, by combining the high specificity of the base-stacking effect with the high reproducibility of bovine serum albumin (BSA) modified electrodes and the high loading performance of DNA nanoclews (DNA NCs), a novel sandwich-type electrochemiluminescence (ECL) biosensor is reported for the highly specific detection of HPV16 (chosen as the model target). The capture probes are loaded by BSA carrier platforms modified on the gold electrode surface to improve reproducibility. DNA NCs loaded with a large amount of Ru(phen)32+ worked as signal probes. The template probe is composed of the complementary strand of the target and two free nucleic acid anchors at the head and tail. In the presence of the target DNA, the template probes can form stacked base pairs with target, generating high base-stacking energy. This results in the shorter free anchors of template probes being able to bind to the capture and signal probes. This eventually forms a sandwich structure that allows Ru(phen)32+ to be near the electrode surface, producing an ECL signal. There is a linear relationship between the signal and the target concentration range from 10 fM to 100 pM, with a detection limit of 5.03 fM (S/N=3). Moreover, the base-stacking effect has single base recognition ability for base pairs, effectively avoiding false positive signals. The results of this strategy for clinical samples are consistent with classical methods.

Partial Genome Detection, Characterization of TYLCV (MZ546492) Infecting Tomato Plants and siRNA Sequences Detection for Alternative Control Strategy

Partial Genome Detection, Characterization of TYLCV (MZ546492) Infecting Tomato Plants and siRNA Sequences Detection for Alternative Control Strategy

Colorectal Cancer Archaeome: A Metagenomic Exploration, Tunisia.

Colorectal cancer (CRC) is a serious public health problem known to have a multifactorial etiology. The association between gut microbiota and CRC has been widely studied; however, the link between archaea and CRC has not been sufficiently studied. To investigate the involvement of archaea in colorectal carcinogenesis, we performed a metagenomic analysis of 68 formalin-embedded paraffin fixed tissues from tumoral (n = 33) and healthy mucosa (n = 35) collected from 35 CRC Tunisian patients. We used two DNA extraction methods: Generead DNA FFPE kit (Qiagen, Germantown, MD, USA) and Chelex. We then sequenced the samples using Illumina Miseq. Interestingly, DNA extraction exclusively using Chelex generated enough DNA for sequencing of all samples. After data filtering and processing, we reported the presence of archaeal sequences, which represented 0.33% of all the reads generated. In terms of abundance, we highlighted a depletion in methanogens and an enrichment in Halobacteria in the tumor tissues, while the correlation analysis revealed a significant association between the Halobacteria and the tumor mucosa (p < 0.05). We reported a strong correlation between Natrialba magadii, Sulfolobus acidocaldarius, and tumor tissues, and a weak correlation between Methanococcus voltae and healthy adjacent mucosa. Here, we demonstrated the feasibility of archaeome analysis from formol fixed paraffin-embedded (FFPE) tissues using simple protocols ranging from sampling to data analysis, and reported a significant association between Halobacteria and tumor tissues in Tunisian patients with CRC. The importance of our study is that it represents the first metagenomic analysis of Tunisian CRC patients' gut microbiome, which consists of sequencing DNA extracted from paired tumor-adjacent FFPE tissues collected from CRC patients. The detection of archaeal sequences in our samples confirms the feasibility of carrying out an archaeome analysis from FFPE tissues using a simple DNA extraction protocol. Our analysis revealed the enrichment of Halobacteria, especially Natrialba magadii, in tumor mucosa compared to the normal mucosa in CRC Tunisian patients. Other species were also associated with CRC, including Sulfolobus acidocaldarius and Methanococcus voltae, which is a methanogenic archaea; both species were found to be correlated with adjacent healthy tissues.

Reproducibility of next-generation-sequencing-based analysis of a CRISPR/Cas9 genome edited oil seed rape

Next-generation-sequencing (NGS) becomes increasingly important for laboratories tasked with the detection of genetically modified organisms (GMOs) in food, feed and seeds. Its implementation into standardized workflows demands reliable intra- and inter-laboratory reproducibility. Here, we analyze the reproducibility of short- and long-read targeted NGS and long-read whole genome sequencing (WGS) data between three independent laboratories. Replicate samples were submitted for sequencing and comparatively analyzed. The targeted-NGS-samples consisted of oil seed rape (OSR) sampled from a commodity shipment spiked with a genome edited (GE) OSR and the WGS-samples consisted of leaf material from the GMOs’ parental line. All laboratories delivered highly reproducible high-quality targeted NGS data with little variation. The detection of GMO-related sequences works well regardless of the facility, while the mapping to the complex genome is superior using long read data. Long read WGS is currently not suitable for routine use in enforcement laboratories, due to a large inter-laboratory variation.

Video Global Motion Compensation Based on Affine Inverse Transform Model.

Global motion greatly increases the number of false alarms for object detection in video sequences against dynamic backgrounds. Therefore, before detecting the target in the dynamic background, it is necessary to estimate and compensate the global motion to eliminate the influence of the global motion. In this paper, we use the SURF (speeded up robust features) algorithm combined with the MSAC (M-Estimate Sample Consensus) algorithm to process the video. The global motion of a video sequence is estimated according to the feature point matching pairs of adjacent frames of the video sequence and the global motion parameters of the video sequence under the dynamic background. On this basis, we propose an inverse transformation model of affine transformation, which acts on each adjacent frame of the video sequence in turn. The model compensates the global motion, and outputs a video sequence after global motion compensation from a specific view for object detection. Experimental results show that the algorithm proposed in this paper can accurately perform motion compensation on video sequences containing complex global motion, and the compensated video sequences achieve higher peak signal-to-noise ratio and better visual effects.