MutVis: Automated framework for analysis and visualization of mutational signatures in pathogenic bacterial strains.

In recent years, mutational signature analysis has become a routine practice in cancer genomics for classification and diagnosis. Characterizing mutational signatures across species or within genomes of a bacteria helps in understanding their evolution and adaptation. However, an integrated framework for analysis and visualization of mutational signatures in bacterial genome is lacking. Hence, we aim to develop an integrated, automated, open-source and user-friendly framework called MutVis to analyze mutational signatures from bacterial whole genome next generation sequencing data. The current framework integrates various publicly available packages using Snakemake workflow management software, Python and R scripting. MutVis supports variant calling, transition (Ti) and transversion (Tv) graphical representation, generation of mutational count matrix, graphical visualization of base-pair substitution spectrum (BPSs) and mutation signatures extraction. TvTi plots provide the 6 base substitution classification for both genome and gene level. Further resolution of base pair substitution classification is provided as 96-profile BPSs plot. Mutation signatures is derived based on the characteristic pattern observed in BPSs using non-negative matrix factorization. Relative contribution of signatures is given as hierarchically clustered heatmap. This provides information on active signatures in the individual given sample and classify samples according to signature contributions. We demonstrated the MutVis framework using geographically different strains of Mycobacterium tuberculosis, downloaded from PATRIC TB-ARC Antibiotic Resistance Catalog (n = 963). The current framework can be used to study mutation biases and characteristic mutational signatures in bacterial genomes and is freely available at https://github.com/AkshathaPrasanna/MutVis.

Development of an immuno-wall device for the rapid and sensitive detection of EGFR mutations in tumor tissues resected from lung cancer patients.

Detecting molecular targets in specimens from patients with lung cancer is essential for targeted therapy. Recently, we developed a highly sensitive, rapid-detection device (an immuno-wall device) that utilizes photoreactive polyvinyl alcohol immobilized with antibodies against a target protein via a streptavidin-biotin interaction. To evaluate its performance, we assayed epidermal growth factor receptor (EGFR) mutations, such as E746_A750 deletion in exon 19 or L858R substitution in exon 21, both of which are common in non-small cell lung cancer and important predictors of the treatment efficacy of EGFR tyrosine kinase inhibitors. The results showed that in 20-min assays, the devices detected as few as 1% (E746_A750 deletion) and 0.1% (L858R substitution) of mutant cells. Subsequent evaluation of detection of the mutations in surgically resected lung cancer specimens from patients with or without EGFR mutations and previously diagnosed using commercially available, clinically approved genotyping assays revealed diagnostic sensitivities of the immuno-wall device for E746_A750 deletion and L858R substitution of 85.7% and 87.5%, respectively, with specificities of 100% for both mutations. These results suggest that the immuno-wall device represents a good candidate next-generation diagnostic tool, especially for screening of EGFR mutations.

Evaluation of the GenoType NTM-DR assay performance for the identification and molecular detection of antibiotic resistance in Mycobacterium abscessus complex.

The first objective of this study was to determine the GenoType NTM-DR assay performance for subspecies identification in Mycobacterium abscessus complex isolates. The second objective was to evaluate the GenoType NTM-DR assay ability to detect clarithromycin and amikacin resistance in M. abscessus complex isolates compared with drug susceptibility testing (DST) and PCR sequencing of the erm(41), rrl and rrs genes. The concordance between the GenoType NTM-DR and MLST results concerning subspecies identification was 100%. The wild type and mutated alleles of the rrl and rrs genes were detected by the GenoType NTM-DR assay and PCR sequencing with 100% (115/115) agreement. Similarly, 100% concordance between GenoType NTM-DR and DST was observed for clarithromycin and amikacin testing. Sensitivity for the detection of clarithromycin and amikacin resistance was 100%. The GenoType NTM-DR assay provides a robust and complementary tool to the gold standard methods (MLST and broth microdilution) for subspecies identification and drug resistance detection.

"Sample-to-Answer" Detection of Rare ctDNA Mutation from 2 mL Plasma with a Fully Integrated DNA Extraction and Digital Droplet PCR Microdevice for Liquid Biopsy.

The "sample-to-answer" integration and automation of circulating tumor DNA (ctDNA)-based liquid biopsy using digital PCR (dPCR) has been hampered by the complicated operations of liquids with volumes ranging from milliliter samples to nanoliter droplets. On the basis of a "3D extensible" design paradigm proposed previously, an integrated droplet digital PCR (IddPCR) microdevice was successfully developed to automate the entire process of liquid biopsy, from the extraction of ctDNA in 2 mL of plasma using magnetic beads to the generation, amplification, and screening of over 30 000 droplets for detection. A series of reagent mixing structures, including macro-, meso-, and micromixers, was designed to enable efficient reagent handling and mixing at different volume scales. The volume thresholds of the microscale and macroscale in the IddPCR device were calculated to be 40 and 100 µL, respectively, based on the fluid dynamics and sizes of the device structures, so that different mixers can be selected according to the reagent volumes. The DNA extraction efficiency obtained on the device was determined to be ∼60%, and the on-chip ddPCR demonstrated a high correlation with an R2 of 0.9986 between the readouts and the estimations by a Poisson distribution. Finally, the IddPCR microdevice was able to detect rare tumor mutations (T790M) with an occurring frequency as low as ∼1% from 2 mL of human plasma in a "sample-to-answer" manner. This work offers a feasible solution for the automation of liquid biopsy and paves the way for its broad applications in clinics.

Isolation and mutational assessment of pancreatic cancer extracellular vesicles using a microfluidic platform.

Cancer cells release extracellular vesicles known as extracellular vesicles (EVs), containing tumor-derived DNA, RNA and proteins within their cargo, into the circulation. Circulating tumor-derived extracellular vesicles (TEV) can be used in the context of serial "liquid biopsies" for early detection of cancer, for monitoring disease burden in patients, and for assessing recurrence in the post-resection setting. Nonetheless, isolating sufficient TEV by ultracentrifugation-based approaches, in order to enable molecular assessment of EVs cargo, can be an arduous, time-consuming process and is inconsistent in the context of yield and purity among institutions. Herein, we describe a microfluidic platform, which we have named MITEV (Microfluidic Isolation of Tumor-derived Extracellular Vesicles) for the rapid isolation of TEV from the plasma of pancreatic cancer patients. The device, which has ~100,000 pillars placed in a zigzag pattern and is coated with antibodies against generic EV surface proteins (anti-CD63, -CD9, and -CD81 antibodies) or the TEV specific anti-Epithelial Cell Adhesion Molecule (EpCAM) antibody, is capable of high-throughput EVs isolation and yields sufficient DNA (total of ~2-14 ng from 2-ml plasma) for downstream genomic analysis. Using two independent quantitative platforms, droplet digital polymerase chain reaction (ddPCR) and molecular barcoding using nanoString nCounter® technology, we can reliably identify KRAS mutations within isolated TEV of treatment-naïve metastatic pancreatic cancer patients. Our study suggests that the MITEV device can be used for point-of-care applications, such as in the context of monitoring residual or recurrent tumor presence in pancreatic cancer patients undergoing therapy.

Evaluation of KRAS, NRAS and BRAF mutations detection in plasma using an automated system for patients with metastatic colorectal cancer.

BACKGROUND: Cell-free DNA detection is becoming a surrogate assay for tumor genotyping. Biological fluids often content a very low amount of cell-free tumor DNA and assays able to detect very low allele frequency mutant with a few quantities of DNA are required. We evaluated the ability of the fully-automated molecular diagnostics platform Idylla for the detection of KRAS, NRAS and BRAF hotspot mutations in plasma from patients with metastatic colorectal cancer (mCRC). MATERIALS AND METHODS: First, we evaluated the limit of detection of the system using two set of laboratory made samples that mimic mCRC patient plasma, then plasma samples from patients with mCRC were assessed using Idylla system and BEAMing digital PCR technology. RESULTS: Limits of detection of 0.1%, 0.4% and 0.01% for KRAS, NRAS and BRAF respectively have been reached. With our laboratory made samples, sensitivity up to 0.008% has been reached. Among 15 patients' samples tested for KRAS mutation, 2 discrepant results were found between Idylla and BEAMing dPCR. A 100% concordance between the two assays has been found for the detection of NRAS and BRAF mutations in plasma samples. CONCLUSIONS: The Idylla system does not reach as high sensitivity as assays like ddPCR but has an equivalent sensitivity to modified NGS technics with a lower cost and a lower time to results. These data allowed to consider the Idylla system in a routine laboratory workflow for KRAS, NRAS and BRAF mutations detection in plasma.

EGFR Mutation Analysis in Non-small Cell Lung Carcinoma from Tissue Samples Using the Fully Automated Idylla™ qPCR System.

The introduction of tyrosine-kinase inhibitors (TKI) targeting specific EGFR mutations for the treatment non-small cell lung cancer patients (NSCLC) dramatically increased the clinical outcome in a subset of patients harboring specific activating EGFR mutations. Three different generations of TKI have been developed until now, demonstrating increasing progression-free survival as well as overall survival. However, to benefit of the treatment, the analysis of the genomic content of each patient is mandatory. Additionally, resistance mutations are prevalent and occur frequently and rapidly during treatment. Therefore, tests to detect EGFR mutations at initial diagnosis as well as during treatment, e.g., from liquid biopsies, have been developed and implemented in clinical daily practice for theranostic purpose.As EGFR mutation testing has to be highly reliable, fast, and easy to perform, the automatic qPCR system Idylla™ has been developed and implemented for clinical mutation testing from tissue samples and soon from circulating free DNA. Therefore, we here describe how the Idylla™ system can be used for the analysis of EGFR mutations in NSCLC patients. Importantly, as the results are massively influenced by the preanalytical steps, we also provide information on the correct sample selection to avoid nonconclusive results.

CRISPR/Cas9 as a tool to dissect cancer mutations.

The CRISPR/Cas9 system is transforming many biomedical disciplines, including cancer research. Through its flexible programmability and efficiency to induce DNA double strand breaks it has become straightforward to introduce cancer mutations into cells in vitro and/or in vivo. However, not all mutations contribute equally to tumorigenesis and distinguishing essential mutations for tumor growth and survival from biologically inert mutations is cumbersome. Here we present a method to screen for the functional relevance of mutations in high throughput in established cancer cell lines. We employ the CRISPR/Cas9 system to probe cancer vulnerabilities in a colorectal carcinoma cell line in an attempt to identify novel cancer driver mutations. We designed 100 high quality sgRNAs that are able to specifically cleave mutations present in the colorectal carcinoma cell line RKO. An all-in-one lentiviral library harboring these sgRNAs was then generated and used in a pooled screen to probe possible growth dependencies on these mutations. Genomic DNA at different time points were collected, the sgRNA cassettes were PCR amplified, purified and sgRNA counts were quantified by means of deep sequencing. The analysis revealed two sgRNAs targeting the same mutation (UTP14A: S99delS) to be depleted over time in RKO cells. Validation and characterization confirmed that the inactivation of this mutation impairs cell growth, nominating UTP14A: S99delS as a putative driver mutation in RKO cells. Overall, our approach demonstrates that the CRISPR/Cas9 system is a powerful tool to functionally dissect cancer mutations at large-scale.

Targeted Single Primer Enrichment Sequencing with Single End Duplex-UMI.

For specific detection of somatic variants at very low levels, artifacts from the NGS workflow have to be eliminated. Various approaches using unique molecular identifiers (UMI) to analytically remove NGS artifacts have been described. Among them, Duplex-seq was shown to be highly effective, by leveraging the sequence complementarity of two DNA strands. However, all of the published Duplex-seq implementations so far required pair-end sequencing and in the case of combining duplex sequencing with target enrichment, lengthy hybridization enrichment was required. We developed a simple protocol, which enabled the retrieval of duplex UMI in multiplex PCR based enrichment and sequencing. Using this protocol and reference materials, we demonstrated the accurate detection of known SNVs at 0.1-0.2% allele fractions, aided by duplex UMI. We also observed that low level base substitution artifacts could be introduced when preparing in vitro DNA reference materials, which could limit their utility as a benchmarking tool for variant detection at very low levels. Our new targeted sequencing method offers the benefit of using duplex UMI to remove NGS artifacts in a much more simplified workflow than existing targeted duplex sequencing methods.

Deep convolutional neural networks for accurate somatic mutation detection.

Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different sequencing platforms, sequencing strategies, and tumor purities. NeuSomatic summarizes sequence alignments into small matrices and incorporates more than a hundred features to capture mutation signals effectively. It can be used universally as a stand-alone somatic mutation detection method or with an ensemble of existing methods to achieve the highest accuracy.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip.

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 104 variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 105 molecular variants of full-length human O6-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

A rapid bioanalytical tool for detection of sequence-specific circular DNA and mitochondrial DNA point mutations.

Mutations in mitochondrial DNA (mtDNA) have been an essential cause of numerous diseases, making their identification critically important. The majority of mtDNA screening techniques require polymerase chain reaction (PCR) amplification, enzymatic digestion, and denaturation procedures, which are laborious and costly. Herein, we developed a sensitive PCR-free electrokinetic-based sensor combined with a customized bis-peptide nucleic acid (bis-PNA) and gamma-PNA (γ-PNA) probes immobilized on beads, for the detection of mtDNA point mutations and sequence-specific supercoiled plasmid DNA at the picomolar range. The probes are capable of invading the double-stranded circular DNA and forming a stable triplex structure. Thus, this method can significantly reduce the sample preparation and omit the PCR amplification steps prior to sensing. Further, this bioanalytical tool can open up a new paradigm in clinical settings for the screening of double-stranded circular nucleic acids with a single-base mismatch specificity in a rapid and sensitive manner.

Integrated routine workflow using next-generation sequencing and a fully-automated platform for the detection of KRAS, NRAS and BRAF mutations in formalin-fixed paraffin embedded samples with poor DNA quality in patients with colorectal carcinoma.

BACKGROUND: KRAS and NRAS mutations are identified resistance mutations to anti-epidermal growth factor receptor monoclonal antibodies in patients with metastatic colorectal cancer. BRAF status is also routinely assessed for its poor prognosis value. In our institute, next-generation sequencing (NGS) is routinely used for gene-panel mutations detection including KRAS, NRAS and BRAF, but DNA quality is sometimes not sufficient for sequencing. In our routine practice, Idylla platform is used for the analysis of samples that don't reach sufficient quality criteria for NGS assay. METHODS: In this study, data from mCRC samples analyzed from May 2017 to 2018 were retrospectively collected. All samples with a poor DNA quality for sequencing have been assessed using Idylla platform. First, KRAS Idylla assay cartridge has been used for the determination of KRAS mutational status. All KRAS wild-type samples have then been analyzed using NRAS-BRAF assay. Among 669 samples, 67 samples failed the DNA quality control and have been assessed on Idylla KRAS mutation test. RESULTS: Among 67 samples, 50 (75%) samples had a valid result with Idylla KRAS mutation test including 22 carrying a KRAS mutation. For 28 samples, NRAS and BRAF mutational statuses have been assessed using Idylla NRAS-BRAF mutation test. Among 28 samples, 27 (96%) had a valid result including 2 samples bearing a NRAS mutation and 3 samples bearing a BRAF mutation. CONCLUSIONS: Our study shows that an integrated workflow using NGS and Idylla platform allows the determination of KRAS, NRAS and BRAF mutational statuses of 651/669 (97.3%) samples and retrieve 49/67 (73.1%)samples that don't reach DNA quality requirements for NGS.

Single gold-bridged nanoprobes for identification of single point DNA mutations.

Consensus ranking of protein affinity to identify point mutations has not been established. Therefore, analytical techniques that can detect subtle variations without interfering with native biomolecular interactions are required. Here we report a rapid method to identify point mutations by a single nanoparticle sensing system. DNA-directed gold crystallization forms rod-like nanoparticles with bridges based on structural design. The nanoparticles enhance Rayleigh light scattering, achieving high refractive-index sensitivity, and enable the system to monitor even a small number of protein-DNA binding events without interference. Analysis of the binding affinity can compile an atlas to distinguish the potential of various point mutations recognized by MutS protein. We use the atlas to analyze the presence and type of single point mutations in BRCA1 from samples of human breast and ovarian cancer cell lines. The strategy of synthesis-by-design of plasmonic nanoparticles for sensors enables direct identification of subtle biomolecular binding distortions and genetic alterations.

Immunoglobulin Gene Analysis in Chronic Lymphocytic Leukemia.

The formation of B-cell receptor immunoglobulin (BcR IG) is the result of a multi-step process that starts at the pro-B cell stage with the VDJ gene recombination of IG genes of the heavy chain, followed by VJ recombination of the light chain genes at the pre-B II cell stage. As a result, a fully functional BcR IG is expressed on the surface of any given naive B cell. After antigen encounter, somatic hypermutation (SHM) and class-switch recombination (CSR) act on the rearranged IG genes within the context of affinity maturation, leading to the expression of a BcR IG with unique immunogenetic and functional characteristics. Since B-cell neoplasms arise from the transformation of a single B cell, this renders IG gene rearrangements ideal clonal markers as they will be identical in all neoplastic cells of each individual clone. Furthermore, the rearranged IG sequence can also serve as a cell development/maturation marker, given that its configuration is tightly linked to specific B-cell developmental stages. Finally, in certain instances, as in the case of chronic lymphocytic leukemia (CLL), the clonotypic IG sequence and, more specifically, the load of somatic hypermutations within the rearranged IG heavy variable (IGHV) gene, holds prognostic and potentially predictive value. However, in order to take full advantage of the information provided from the analysis of the clonotypic IG gene rearrangement sequences, robust methods and tools need to be applied. Here, we provide details regarding the methodologies necessary to ensure reliable IG sequence analysis based on the recognized expertise of the European Research initiative on CLL (ERIC). All methodological and analytical steps are described below, starting from the isolation of blood mononuclear cells (PBMC), moving to the identification of the clonotypic IG rearrangement and ending with the accurate interpretation of the SHM status.

Detection and Functional Analysis of TP53 Mutations in CLL.

Chronic lymphocytic leukemia (CLL) represents a prototype disease in which TP53 gene defects lead to inferior prognosis. Here, we present two distinct methodologies which can be used to identify TP53 mutations in CLL patients; both protocols are primarily intended for research purposes. The functional analysis of separated alleles in yeast (FASAY) can be flexibly adapted to a variable number of samples and provides an immediate functional readout of identified mutations. Amplicon-based next-generation sequencing then allows for a high throughput and accurately detects subclonal TP53 variants (sensitivity <1% of mutated cells).

Analysis of KRAS, NRAS and BRAF mutational profile by combination of in-tube hybridization and universal tag-microarray in tumor tissue and plasma of colorectal cancer patients.

Microarray technology fails in detecting point mutations present in a small fraction of cells from heterogeneous tissue samples or in plasma in a background of wild-type cell-free circulating tumor DNA (ctDNA). The aim of this study is to overcome the lack of sensitivity and specificity of current microarray approaches introducing a rapid and sensitive microarray-based assay for the multiplex detection of minority mutations of oncogenes (KRAS, NRAS and BRAF) with relevant diagnostics implications in tissue biopsies and plasma samples in metastatic colorectal cancer patients. In our approach, either wild-type or mutated PCR fragments are hybridized in solution, in a temperature gradient, with a set of reporters with a 5' domain, complementary to the target sequences and a 3' domain complementary to a surface immobilized probe. Upon specific hybridization in solution, which occurs specifically thanks to the temperature gradients, wild-type and mutated samples are captured at specific location on the surface by hybridization of the 3' reporter domain with its complementary immobilized probe sequence. The most common mutations in KRAS, NRAS and BRAF genes were detected in less than 90 minutes in tissue biopsies and plasma samples of metastatic colorectal cancer patients. Moreover, the method was able to reveal mutant alleles representing less than 0,3% of total DNA. We demonstrated detection limits superior to those provided by many current technologies in the detection of RAS and BRAF gene superfamily mutations, a level of sensitivity compatible with the analysis of cell free circulating tumor DNA in liquid biopsy.

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consuming, costly, poorly standardized, and non-reproducible. Here, we systematized and standardized somatic variant refinement using a machine learning approach. The final model incorporates 41,000 variants from 440 sequencing cases. This model accurately recapitulated manual refinement labels for three independent testing sets (13,579 variants) and accurately predicted somatic variants confirmed by orthogonal validation sequencing data (212,158 variants). The model improves on manual somatic refinement by reducing bias on calls otherwise subject to high inter-reviewer variability.

Design and MinION testing of a nanopore targeted gene sequencing panel for chronic lymphocytic leukemia.

We report a customized gene panel assay based on multiplex long-PCR followed by third generation sequencing on nanopore technology (MinION), designed to analyze five frequently mutated genes in chronic lymphocytic leukemia (CLL): TP53, NOTCH1, BIRC3, SF3B1 and MYD88. For this purpose, 12 patients were selected according to specific cytogenetic and molecular features significantly associated with their mutational status. In addition, simultaneous analysis of the targets genes was performed by molecular assays or Sanger Sequencing. Data analysis included mapping to the GRCh37 human reference genome, variant calling and annotation, and average sequencing depth/error rate analysis. The sequencing depth resulted on average higher for smaller amplicons, and the final breadth of coverage of the panel was 94.1%. The error rate was about 6% and 2% for insertions/deletions and single nucleotide variants, respectively. Our gene panel allows analysis of the prognostically relevant genes in CLL, with two PCRs per patient. This strategy offers an easy and affordable workflow, although further advances are required to improve the accuracy of the technology and its use in the clinical field. Nevertheless, the rapid and constant development of nanopore technology, in terms of chemistry advances, more accurate basecallers and analysis software, offers promise for a wide use of MinION in the future.