Accuracy of Endoscopic Ultrasound Guided Fine Needle Aspiration In Sampling Of Pancreatic & Gastrointestinal Lesions Using Capillary Versus Suction Technique

Background Endosonography (EUS) evolved from purely diagnostic imaging modality to be a method that allows tissue acquisition and therapeutic intervention. EUS-guided fine needle aspiration (EUS-FNA) permits cytological confirmation of imaging findings and is performed with high sensitivity and specificity in addition to low incidence of adverse events. Standard EUS-FNA involve use of either no-suction or suction techniques. New sampling technique; capillary (stylet slow-pull) technique, involves slow withdrawal of the stylet creating a small negative pressure. Aim of the work The aim of this study is to compare the quality of samples acquired by capillary technique versus suction technique using 22-gauge needles. Patients and methods Patients referred for EUS-FNA for upper gastrointestinal lesions (pancreatic or luminal) were included in the study. Each lesion was sampled twice, the first was taken using suction technique (applying negative pressure suction using standard 10 ml syringe) while the second one by capillary (stylet slow-pull) technique. After sample processing and staining, cytopathologist reviewed the material blinded to the technique used. The quality of samples was assessed regarding 3 aspects; cellularity, sample contamination by blood or mucosal cells. Results A total of 51 patients (37/14 males/females, mean age 55.4) referred for EUSFNA were included. Cytological diagnosis was: pancreatic adenocarcinoma in 38/51 (74.51%), Gastrointestinal stromal tumor in 4/51 (7.84%), inconclusive result in 3/51 (5.88%), the rest were solid pseudopapillary neoplasm, Serous cystic neoplasm, Mucinous cystic neoplasm, inflammatory lesions (papillitis, pancreatitis) and metastatic lesion 1 patient for each (1.96%). The sample cellularity score showed no statistically significant difference between both sampling techniques (P = 0.18). Blood contamination score was significantly lower in the capillary technique (P < 0.0001) indicating more blood contamination in suction technique samples. Conclusion Both techniques provided comparable diagnostic performance. However, capillary technique showed less sample contamination by blood cells resulting in a slightly better-quality sample.

Contamination detection and microbiome exploration with GRIMER

Exploring microbiome data is a time-consuming task that can be only partially automated due to the specific requirements and goals of each project. Visualizations and analysis platforms are crucial to better guide this step. Best practices in the field are constantly evolving and many pitfalls can lead to biased outcomes. Compositionality of data and sample contamination are two important points that should be carefully considered in early stages of microbiome studies. Detecting contamination can be a challenging task, especially in low-biomass samples or in studies lacking proper controls by design. However, external evidences and commonly identified contaminant taxa can be used to discover and mitigate contamination. We propose GRIMER, a tool that automates analysis, generates plots and runs external tools to create a portable dashboard integrating annotation, taxonomy and metadata. It unifies several sources of evidence towards contamination detection. GRIMER is independent of quantification methods and directly analyses contingency tables to create an interactive and offline report. GRIMER reports can be created in seconds and are accessible for non-specialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled an extensive list of common contaminants and possible external contaminant taxa reported in the literature and use it to annotate data. GRIMER is open-source and available at: https://gitlab.com/dacs-hpi/grimer

VCFcontam: A Machine Learning Approach to Estimate Cross-Sample Contamination from Variant Call Data

The quality of genotyping calls resulting from DNA sequencing is reliant on high quality starting genetic material. One factor that can reduce sample quality and lead to misleading genotyping results is genetic contamination of a sample by another source, such as cells or DNA from another sample of the same or different species. Cross-sample contamination by individuals of the same species is particularly difficult to detect in DNA sequencing data, because the contaminating sequence reads look very similar to those of the intended base sample. We introduce a new method that uses a support vector regression model trained on in silico contaminated datasets to predict empirical contamination using a collection of variables drawn from VCF files, including the fraction of sites that are heterozygous, the fraction of heterozygous sites with imbalanced allele counts, and parameters describing distributions fit to heterozygous allele fractions in a sample. We use the method described here to train a model that can accurately predict the extent of cross-sample contamination within 1% of the actual fraction, for simulated contaminated samples in the 0-5% contamination range, directly from the VCF file.DefinitionsLesser alleleThe allele in a heterozygous position that received less sequencing read support (which may be either the REF or ALT allele).Lesser allele fraction (LAF)The number of sequencing reads supporting the less frequently observed allele divided by the sum of reads supporting both alleles in the genotype at a given genomic position.

HIV false positive screening serology due to sample contamination reduced by a dedicated sample and platform in a high prevalence environment

Automated testing of HIV serology on clinical chemistry analysers has become common. High sample throughput, high HIV prevalence and instrument design could all contribute to sample cross-contamination by microscopic droplet carry-over from seropositive samples to seronegative samples resulting in false positive low-reactive results. Following installation of an automated shared platform at our public health laboratory, we noted an increase in low reactive and false positive results. Subsequently, we investigated HIV serology screening test results for a period of 21 months. Of 485 initially low positive or equivocal samples 411 (85%) tested negative when retested using an independently collected sample. As creatinine is commonly requested with HIV screening, we used it as a proxy for concomitant clinical chemistry testing, indicating that a sample had likely been tested on a shared high-throughput instrument. The contamination risk was stratified between samples passing the clinical chemistry module first versus samples bypassing it. The odds ratio for a false positive HIV serology result was 4.1 (95% CI: 1.69–9.97) when creatinine level was determined first, versus not, on the same sample, suggesting contamination on the chemistry analyser. We subsequently issued a notice to obtain dedicated samples for HIV serology and added a suffix to the specimen identifier which restricted testing to a dedicated instrument. Low positive and false positive rates were determined before and after these interventions. Based on measured rates in low positive samples we estimate that before the intervention, of 44 117 HIV screening serology samples, 753 (1.71%) were false positive, declining to 48 of 7 072 samples (0.68%) post-intervention (p<0.01). Our findings showed that automated high throughput shared diagnostic platforms are at risk of generating false-positive HIV test results, due to sample contamination and that measures are required to address this. Restricting HIV serology samples to a dedicated platform resolved this problem.

Performance verification of pre-PCR and real-time PCR step in the molecular diagnosis of pneumococcal meningitis cases

Isolation and determination of s.pneumoniae by culture and serological methods can be time consuming or indeterminate. Molecular diagnosis by real-time PCR is independent of the growth of the pathogen causing meningitis, and is not diminished with non-viable organisms. The aim of this study was to evaluate the performance criteria of pre-PCR-TR DNA extraction step and PCR-TR step by targeting two genes encoding s.pneumoniae. In this study we evaluated the inter-sample contamination of the pre-PCR-TR step, the intermediate fidelity and the repeatability of the DNA essay. PCR-TR verification was performed by two genes targeting s. pneumoniae the Lyt A and SP 2038 gene; sensitivity, specificity and LLD were determined. Contamination rate had a value of less than 0%, which is in agreement with an absence of inter-sample contamination; the repeatability and intermediate fidelity have a cv˂7%. The evaluation of the sensitivity and specificity of the RT-PCR assays targeted 100% the Lyt A gene and the SP 2038 gene. The standard curve generated detected less than 10copies for the Lyt A gene and less than 100copies for the SP 2038 gene. This study showed that the pre-PCR and PCR-TR assays met the performance criteria targeted in this study.

Iron oxide xerogels for improved water quality monitoring of arsenic(iii) in resource-limited environments via solid-phase extraction, preservation, storage, transportation, and analysis of trace contaminants (SEPSTAT)

We show that iron oxide xerogels can quantitatively adsorb, store, and release aqueous arsenic(iii), enabling a new arsenic monitoring paradigm where sample contamination is adsorbed onto solid sorbents for transportation to laboratories for analysis.

Sensitive detection of DNA contamination in tumor samples via microhaplotypes

BackgroundLow levels of sample contamination can have disastrous effects on the accurate identification of somatic variation in tumor samples. Detection of sample contamination in DNA is generally based on observation of low frequency variants that suggest more than a single source of DNA is present. This strategy works with standard DNA samples but is especially problematic in solid tumor FFPE samples because there can be huge variations in allele frequency (AF) due to massive copy number changes arising from large gains and losses across the genome. The tremendously variable allele frequencies make detection of contamination challenging. A method not based on individual AF is needed for accurate determination of whether a sample is contaminated and to what degree.MethodsWe used microhaplotypes to determine whether sample contamination is present. Microhaplotypes are sets of variants on the same sequencing read that can be unambiguously phased. Instead of measuring AF, the number and frequency of microhaplotypes is determined. Contamination detection becomes based on fundamental genomic properties, linkage disequilibrium (LD) and the diploid nature of human DNA, rather than variant frequencies. We optimized microhaplotype content based on 164 single nucleotide variant sets located in genes already sequenced within a cancer panel. Thus, contamination detection uses existing sequence data and does not require sequencing of any extraneous regions. The content is chosen based on LD data from the 1000 Genomes Project to be ancestry agnostic, providing the same sensitivity for contamination detection with samples from individuals of African, East Asian, and European ancestry.ResultsDetection of contamination at 1% and below is possible using this design. The methods described here can also be extended to other DNA mixtures such as forensic and non-invasive prenatal testing samples where DNA mixes of 1% or less can be similarly detected.ConclusionsThe microhaplotype method allows sensitive detection of DNA contamination in FFPE tumor samples. These methods provide a foundation for examining DNA mixtures in a variety of contexts. With the appropriate panels and high sequencing depth, low levels of secondary DNA can be detected and this can be valuable in a variety of applications.

VTAM: A robust pipeline for validating metabarcoding data using internal controls

Metabarcoding studies should be carefully designed to minimize false positives and false negative occurrences. The use of internal controls, replicates, and several overlapping markers is expected to improve the bioinformatics data analysis.VTAM is a tool to perform all steps of data curation from raw fastq data to taxonomically assigned ASV (Amplicon Sequence Variant or simply variant) table. It addresses all known technical error types and includes other features rarely present in existing pipelines for validating metabarcoding data: Filtering parameters are obtained from internal control samples; cross-sample contamination and tag-jump are controlled; technical replicates are used to ensure repeatability; it handles data obtained from several overlapping markers.Two datasets were analysed by VTAM and the results were compared to those obtained with a pipeline based on DADA2. The false positive occurrences in samples were considerably higher when curated by DADA2, which is likely due to the lack of control for tag-jump and cross-sample contamination.VTAM is a robust tool to validate metabarcoding data and improve traceability, reproducibility, and comparability between runs and datasets.

A pioneer calf foetus microbiome

Foetus sterility until parturition is under debate due to reports of microorganisms in the foetal environment and meconium. Sufficient controls to overcome sample contamination and provide direct evidence of microorganism viability in the pre-rectal gastrointestinal tract (GIT) have been lacking. We conducted molecular and culture-based analyses to investigate the presence of a microbiome in the foetal GIT of calves at 5, 6 and 7 months gestation, while controlling for contamination. The 5 components of the GIT (ruminal fluid, ruminal tissue, caecal fluid, caecal tissue and meconium) and amniotic fluid were found to contain a pioneer microbiome of distinct bacterial and archaeal communities. Bacterial and archaeal richness varied between GIT components. The dominant bacterial phyla in amniotic fluid differed to those in ruminal and caecal fluids and meconium. The lowest bacterial and archaeal abundances were associated with ruminal tissues. Viable bacteria unique to the ruminal fluids, which were not found in the controls from 5, 6 and 7 months gestation, were cultured, subcultured, sequenced and identified. We report that the foetal GIT is not sterile but is spatially colonised before birth by a pioneer microbiome.